A Critical Re-Evaluation of "MAPK-Driven Epithelial Cell Plasticity Drives Colorectal Cancer Therapeutic Resistance" by White et al., Nature 2025; doi:10.1038/s41586-025-09916-w

1 A Critical Re-evaluation of “MAPK-driven epithelial cell plasticity drives colorectal cancer therapeutic resistance” by White et al., Nature 2025; doi:10.1038/s41586-025-09916-w Chen Shen, Mingyue Gao, Siyu Zhong and Shu-Feng Zhou* College of Chemical Engineering, Huaqiao University, Xiamen 361021, China *Correspondence: [email protected] Abstract This commentary presents a comprehensive re-evaluation of the study by White, Mills, Millett and colleagues, which proposes that MAPK-driven epithelial cell plasticity is a principal determinant of therapeutic resistance in colorectal cancer. Although the original paper offers an ambitious framework linking MAPK pathway reactivation to adaptive cellular state transitions, our reassessment finds that the central claim is insufficiently supported by the experimental, computational, and contextual evidence provided. The study employs organoid models, mouse experiments, pharmacological perturbations, and single-cell transcriptomic analyses to argue that colorectal cancer cells escape therapy by entering MAPKdependent plastic states. However, many of these data can be alternatively explained by stress responses, clonal selection dynamics, incomplete pathway suppression, off-target drug effects, and transient transcriptional fluctuations rather than genuine lineage or identity transitions. Key methodological issues include the inconsistent definition of “epithelial plasticity,” limited validation of transcriptionally inferred states, underpowered lineage-tracing experiments, incomplete MAPK pathway inhibition controls, and insufficient replication in patient-derived samples. Computational analyses exhibit unverified clustering stability, ambiguous pseudotime trajectories, and missing cross-dataset validation. Imaging and proteomic experiments lack essential controls, raw data, and normalization details, thereby weakening the ability to draw causal conclusions. The broader conceptual framework presented in the original study also conflicts with well-established mechanisms of colorectal cancer therapeutic resistance, which include WNT-driven identity anchoring, stromal and immune interactions, evolutionary selection, metabolic rewiring, and canonical MAPK pathway reactivation that does not inherently mandate changes in epithelial identity. Through a detailed, figure-by-figure and methods-focused critique, this commentary concludes that the evidence does not robustly establish MAPK-driven epithelial 2 plasticity as a primary mechanism of resistance. Instead, the observations align more plausibly with heterogeneous, multifactorial adaptive processes needing deeper mechanistic validation. 1. Introduction 1.1. Background and Context in Colorectal Cancer Biology The study by White and colleagues1 positions MAPK-driven epithelial cell plasticity as a central determinant of therapeutic resistance in colorectal cancer. This is an ambitious framing, proposing that MAPK pathway reactivation triggers not only biochemical restoration of proliferative signaling but also a biologically meaningful alteration in epithelial identity that allows cancer cells to withstand targeted therapy. Given the entrenched molecular architecture of colorectal cancer and its dependency on intestinal epithelial lineage programs, the proposal that MAPK signaling alone can induce functional identity shifts necessitates especially robust evidence. Colorectal cancer develops within a biological environment governed by WNT signaling, APC loss, chromatin landscape stability, and tissue-specific transcription factor networks, all of which impose substantial constraints on cellular identity2. While adaptive responses and phenotypic fluctuations are known to occur under stress, genuine lineage transitions are comparatively rare3-7 and require strong mechanistic justification. This context demands caution when interpreting transcriptional heterogeneity, signaling dynamics or survival patterns as evidence of reprogramming. 1.2. Established Frameworks of Therapeutic Resistance Therapeutic resistance in colorectal cancer has historically been understood as a multifactorial outcome shaped by evolutionary selection, pathway rewiring, clonal diversification, microenvironmental modulation and metabolic adaptation8,9. EGFR inhibitors, BRAF inhibitors, MEK inhibitors and combinations thereof frequently face resistance because colorectal cancer cells are adept at restoring growth pathways, particularly through MAPK reactivation8,9. This reactivation, however, generally reflects compensatory biochemical restoration rather than alterations of cellular identity. Previous studies have demonstrated that resistant cells frequently acquire KRAS or NRAS mutations, upregulate receptor tyrosine kinases, engage alternative survival pathways or modulate metabolic circuits to buffer apoptotic stress8,9. These mechanisms do not typically involve large-scale shifts in lineage state. Therefore, any claim that MAPK reactivation induces a stable identity change must provide direct evidence distinguishing identity transitions from the myriad adaptive stress responses well known to characterize resistant colorectal cancer. 3 1.3. Limitations of Organoid and Murine Model Interpretations The evidence presented in the original study relies heavily on organoid cultures and murine tumor models. While these are valuable systems, they are inherently limited in their ability to mimic the architectural, immunological and stromal complexity of human tumors. Organoid cultures are susceptible to transcriptional artifacts resulting from artificial growth factor exposure, mechanical constraints and nutrient gradients absent from physiological tissues10. Similarly, murine models of colorectal cancer, even those generated through sophisticated genetic engineering, often diverge from human tumors in lineage behavior, niche dependency and therapeutic response. When interpretations concerning epithelial identity transitions are derived primarily from such models, rigorous validation across diverse human tumor samples becomes essential. The study does not provide these validations, leaving open questions about whether the proposed plasticity mechanism is an artifact of experimental conditions rather than a genuine biological phenomenon in human colorectal cancer. 1.4. Challenges in Interpreting Single-Cell Transcriptomic Data A major portion of the study’s mechanistic argument is based on single-cell RNA sequencing, where transcriptional clusters are interpreted as distinct identity states indicative of epithelial plasticity. Single-cell analyses are transformative but prone to substantial interpretative pitfalls when used to infer lineage transitions. Clustering algorithms impose discrete boundaries on what often exists as a continuum or noise. Pseudotime trajectories can suggest directionality even in systems lacking true developmental progression11. Stress responses associated with therapeutic exposure can generate transcriptional signatures that resemble lineage reprogramming yet do not correspond to actual changes in cell identity. In the original paper, multiple cell states are defined solely through transcriptional criteria without demonstrating stability across replicates, consistency across analytic pipelines or correlation with protein-level phenotypes. Without such validation, the designation of these states as manifestations of epithelial plasticity remains speculative. 1.5. Insufficient Lineage-Tracing Resolution Lineage tracing is essential for establishing true plasticity. To demonstrate that colorectal cancer cells undergo MAPK-dependent identity transitions, lineagetracing experiments must show that individual cells shift between defined states in a temporally coherent manner that correlates directly with MAPK pathway modulation and survival outcomes. The lineage-tracing data presented rely on tamoxifen-inducible reporters that label heterogeneous populations and do not provide single-cell or clonal resolution. The temporal windows between labeling, 4 MAPK induction and therapeutic resistance assessment are narrow and imprecise, making it impossible to draw conclusions about the directionality of the purported transitions. Moreover, the presence of resistant subpopulations prior to treatment cannot be excluded, meaning that what appears as plasticity might instead represent the selective expansion of rare pre-existing clones whose identity is fixed rather than altered. 1.6. Conflicts with Established Lineage Stability in Colorectal Cancer Colorectal cancer cells, despite undergoing malignant transformation, are characterized by relatively stable epithelial lineage identity. The intestinal epithelium maintains its structure through well-characterized stem cell hierarchies, crypt–villus gradients and tightly regulated transcriptional networks12. Even in the context of severe therapeutic stress or chronic inflammation, colorectal epithelial cells rarely undergo lineage transformation on the scale suggested by the original study. This structural and molecular rigidity makes the proposed MAPK-driven epithelial plasticity particularly unconventional. MAPK pathway activation plays a major role in proliferation and survival but has never been convincingly shown to reshape lineage identity in colorectal cancer13. The conceptual leap from signaling adaptation to lineage reprogramming therefore contradicts foundational principles of intestinal epithelial biology and requires far more rigorous evidence than what is presented. 1.7. Alternative Explanations for Heterogeneity and Adaptation The heterogeneity described in the study may be more accurately explained by established adaptive responses rather than lineage transitions. Stress-induced gene expression, fluctuations associated with cell cycle states, metabolic adaptation to microenvironmental perturbations, and cytokine-driven activation can all generate transcriptional diversity that mimics plasticity. In addition, interactions with cancerassociated fibroblasts, immune infiltrates and extracellular matrix components can modulate cell behavior in ways that appear transitional but do not involve identity change. These mechanisms are well documented across numerous colorectal cancer studies and provide highly plausible explanations for the observations reported. Without ruling out these alternatives, attributing all observed heterogeneity to epithelial plasticity constructs an overly unified interpretation that may not reflect the true complexity of tumor biology. 1.8. Unrealized Translational Implications of the Plasticity Hypothesis If MAPK-driven epithelial plasticity were genuinely central to therapeutic resistance, clinical data should reflect such transitions in patient tumors. Yet histological comparisons of pre-treatment and post-relapse colorectal cancer samples rarely reveal alterations in epithelial identity. Instead, they typically 5 demonstrate classical patterns such as MAPK pathway reactivation through genetic or epigenetic means, stromal remodeling, immune evasion and metabolic rewiring. The absence of identity transitions in human relapse specimens contradicts the narrative proposed in the original paper. Additionally, therapeutic efforts that inhibit MAPK signaling at multiple nodes, including combinations of BRAF, MEK and ERK inhibition, do not prevent resistance when applied clinically8, suggesting that mechanisms beyond putative plasticity are more central to treatment escape. 1.9. Rationale for a Comprehensive Reassessment Given these conceptual conflicts, methodological concerns and interpretative uncertainties, a detailed re-evaluation of the study is necessary. The original paper proposes a mechanism that challenges long-standing understandings of colorectal cancer biology and therapeutic resistance, yet the evidence provided does not meet the threshold required for such a paradigm shift. This commentary therefore examines the study from all possible dimensions, including biological plausibility, methodological rigor, computational transparency, data interpretation and figureby-figure scrutiny. Only through such systematic assessment can the true validity of the MAPK-driven epithelial plasticity model be determined. 2. Conceptual and Theoretical Critique 2.1. The Biological Foundations of Epithelial Identity in the Intestinal Epithelium The conceptual framework proposed in the study by White and colleagues1 asserts that MAPK-driven epithelial cell plasticity forms a central mechanism of therapeutic resistance in colorectal cancer. Assessing this claim requires grounding the discussion in the fundamental biology of the intestinal epithelium. The colonic epithelium represents one of the most hierarchically organized tissues in the human body. Its lineage fidelity is governed by stem cell dynamics at the base of the crypt, a highly regulated gradient of differentiation, and a tightly interwoven network of WNT, BMP, Notch and Hedgehog signals that maintain stable transcriptional and chromatin programs14. Even in malignancy, these lineage constraints persist. Colorectal cancer cells, despite accumulating diverse mutations, rarely undergo substantial deviations from their epithelial identity. Because of this deeply entrenched lineage framework, the proposal that MAPK signaling alone can override these constraints and induce true identity transformation stands at odds with longstanding biological models of intestinal tissue development and maintenance. 2.2. Distinguishing Plasticity from Transient Stress Responses The study interprets MAPK-associated transcriptional shifts as evidence of epithelial plasticity, yet this interpretation is conceptually problematic. Stress-induced 6 transcriptional changes are ubiquitous across cancers and can mimic the appearance of identity transitions. Immediate-early genes, inflammatory pathways, metabolic response modules and proliferative slow-down signatures often emerge after drug exposure. These changes are short-lived and reversible, and they align with known adaptive programs rather than lineage alterations. A critical conceptual flaw in the original paper lies in conflating these transient responses with true plasticity. True identity transitions require stable changes in fate-defining transcription factors, chromatin remodeling, and functional differences at the cellular level. The study does not present evidence of durable changes that carry lineage significance, raising concerns that the central claim of plasticity reflects a misinterpretation of generic adaptive responses to MAPK stress. 2.3. MAPK Signaling and Its Lack of Lineage-Defining Capacity MAPK signaling integrates mitogenic signals to drive proliferation, survival and metabolic states. It is not, however, a lineage-specifying pathway in intestinal tissue. While MAPK activity influences local differentiation processes in select developmental systems, these are highly contextual and do not generalize to colonic epithelium15. In colorectal cancer, MAPK reactivation has been repeatedly shown to restore proliferation after targeted inhibition, but it does not rewire lineage commitments. The theoretical basis for claiming that MAPK can initiate identity transformation is therefore tenuous unless supported by evidence of chromatin restructuring, sustained transcription factor reorganization or irreversible changes in signaling dependency. Absent such evidence, interpreting MAPK activity as a driver of epithelial identity changes lacks biological plausibility and stretches the theoretical role of the pathway beyond its known functional domain. 2.4. Overinterpretation of Transcriptional Heterogeneity as Identity Change The central evidence for the proposed plasticity model relies on transcriptionally defined states derived from single-cell RNA sequencing. Yet transcriptional heterogeneity in cancer is multifactorial and not synonymous with lineage change. Cycling patterns, metabolic fluctuations, environmental stressors, nutrient gradients and stochastic transcriptional noise all produce heterogeneous profiles in single-cell datasets. Without demonstrating that transcriptional states correspond to functional, phenotypic or chromatin-level identity differences, these states cannot be assumed to represent plasticity. The original study infers identity transitions solely from cluster-level diversity, ignoring alternative explanations that better align with established tumor biology. A conceptual model built on such inferences risks mistaking the inherent chaos of cancer transcription for lineage reprogramming. 7 2.5. Misinterpretation of Pseudotime and Trajectory Analyses Trajectory inference is a computational technique that imposes directionality on high-dimensional data, but in cancer systems undergoing drug exposure, transcriptional landscapes frequently reflect reversible stress responses rather than developmental progression11. Pseudotime methods can generate apparently coherent transitions even when the underlying system lacks true lineage flux. The original study interprets pseudotime arrangements as evidence of MAPK-driven transitions between epithelial states. However, there is no experimental demonstration that trajectories correspond to real temporal transitions, nor that MAPK activity determines their direction. Without validation through lineage tracing, live-cell imaging or temporally resolved functional assays, trajectory-based interpretations amount to computational speculation rather than biological fact. 2.6. Misalignment with Ecological and Microenvironmental Constraints The theoretical plausibility of epithelial plasticity must also be evaluated within the ecological constraints of colorectal tumors. Tumor evolution occurs within a colonic microenvironment shaped by oxygen gradients, nutrient availability, immune surveillance, stromal interactions and microbiome influences. These pressures tend to reinforce epithelial identity rather than permit deviation. Cells that diverge significantly from this identity would likely struggle to survive without acquiring compensatory mechanisms. A model proposing broad epithelial identity transitions must explain how such transitions are ecologically advantageous within this environment. The original study does not address these ecological constraints, nor does it demonstrate that MAPK-driven states confer survival benefits consistent with microenvironmental realities. 2.7. Inconsistencies with Clinical Resistance Patterns Any theoretical framework proposing a new mechanism of resistance must integrate and be consistent with clinical patterns observed in patients. In colorectal cancer, relapse after MAPK-targeted therapy almost always involves restoration of MAPK activity through secondary mutations, amplification of receptor tyrosine kinases, activation of parallel pathways, or stromal-induced bypass signaling16-18. Importantly, relapsed tumors do not display altered epithelial histology or loss of lineage markers. They remain unequivocally epithelial. This clinical reality contradicts the notion that MAPK-driven plasticity constitutes a dominant resistance mechanism. If identity transitions were central to resistance, they would appear in human relapse specimens; yet they do not. The disconnect between the proposed model and clinical behavior highlights a major theoretical weakness. 8 2.8. Conceptual Ambiguity in the Definition of Plasticity The study’s definition of epithelial plasticity fluctuates across sections, contributing to internal inconsistency. At times, plasticity refers to discrete transcriptional states; at others, it is framed as altered signaling dependencies or phenotypic behaviors. This fluidity undermines conceptual rigor. A sound theoretical model demands a clear, stable definition of what constitutes identity change and how it differs from adaptation, stress response or selection of pre-existing subpopulations. Without such definitional clarity, the interpretive framework becomes elastic enough to accommodate nearly any experimental outcome, diminishing its explanatory power. 2.9. Lack of Evolutionary and Fitness-Based Justification Theoretical evaluations of mechanisms driving resistance must consider evolutionary dynamics. Colorectal cancer evolves under Darwinian selection where the fittest clones survive therapeutic pressure5. For epithelial plasticity to serve as the primary resistance mechanism, it must confer greater fitness advantages than classical processes such as mutational escape or pathway reactivation. Yet the study does not quantify fitness contributions of putative plasticity states, nor does it demonstrate selective pressure favoring them over well-established resistance mechanisms. Without an evolutionary rationale, the plasticity hypothesis lacks grounding in the fundamental logic that governs tumor progression. 2.10. Overall Conceptual Assessment In aggregate, the conceptual foundation of MAPK-driven epithelial cell plasticity as presented in the original study is weak, internally inconsistent, and biologically implausible without considerably more rigorous mechanistic support. The model fails to distinguish between lineage transformation and stress adaptation, overextends the theoretical influence of MAPK signaling, misinterprets transcriptional heterogeneity, relies heavily on computational inference without experimental validation, and does not align with clinical or evolutionary realities. A more coherent interpretation of the data is that MAPK reactivation—already known to be central to resistance—restores proliferative capacity but does not alter epithelial identity. Established mechanisms such as clonal selection, bypass pathway activation, metabolic adaptation and microenvironmental interactions provide far more plausible and biologically grounded explanations for the therapeutic resistance observed in colorectal cancer. The theoretical framework proposed by the study thus remains speculative and unsubstantiated, requiring extensive refinement before it can be considered a viable paradigm shift in the field. 9 3. Methodological Evaluation 3.1. Overview of Methodological Dependencies and the Central Role of Model Systems A rigorous methodological evaluation must begin by acknowledging that the mechanistic conclusions proposed in the original study depend heavily on a sequence of interconnected experimental systems: organoid cultures, genetically engineered murine models, pharmacological perturbations, single-cell RNA sequencing pipelines, proteomic assays, and imaging-based lineage assessments. Each system carries intrinsic limitations that must be acknowledged when drawing mechanistic conclusions, particularly those as ambitious as the assertion that MAPK activation drives epithelial identity transitions in colorectal cancer. The study treats each methodological layer as supportive of the central claim, yet a careful examination reveals that the limitations of each system accumulate rather than offset one another. Instead of forming a coherent evidentiary chain, these components introduce methodological noise, interpretative ambiguity and technical artifacts that compromise the reliability of the conclusions. Because the concept of MAPK-driven epithelial plasticity requires multi-tiered validation across molecular, functional, and cellular dimensions, any methodological weakness at one level has downstream implications for the interpretative framework. The study does not adequately account for these vulnerabilities, and the methodological design is not sufficiently robust to justify the sweeping mechanistic claims. 3.2. Limitations of Genetic Models and Lineage Manipulations The study uses genetically engineered mouse models and CRISPR-based genetic perturbations to infer the role of MAPK signaling in driving identity transitions. However, the genetic systems employed lack the precision required to make such claims. Genetically induced MAPK activation in murine intestinal tissue does not inherently mimic the heterogeneous and multifactorial MAPK reactivation mechanisms observed in human colorectal cancer under therapeutic pressure. The murine intestinal epithelium has a distinct developmental trajectory, niche architecture and regenerative capacity, which fundamentally alter how MAPK perturbations manifest at the tissue level. The transgenic constructs employed in the study activate MAPK signaling in a global or semi-global manner across crypt populations, rather than recapitulating the mosaic, cell-specific, or subclonal MAPK dynamics characteristic of human tumors. This distinction is not merely academic; lineage transitions, if they occur, depend critically on local context, clonal interactions and niche signals. By activating MAPK signaling broadly, the study disrupts the microenvironmental heterogeneity that shapes identity constraints, 16 4.5. Pseudotime Reconstruction and Unsupported Claims of Directionality Pseudotime inference is a powerful computational tool but must be applied with extreme caution, especially in systems undergoing transient stress. The algorithmic logic of pseudotime methods assumes a continuum of transcriptional states reflecting progressive biological processes. Yet colorectal cancer cells exposed to MAPK inhibition or activation experience shock-like transcriptional fluctuations that do not necessarily correspond to structured developmental trajectories. The study uses pseudotime tools to infer linear or branching paths that purportedly map transitions between epithelial identity states. However, there is no validation of these trajectories using temporally sampled data, lineage-labeled populations or independent markers of progression. The inferred trajectories may simply reflect the geometric structure of the high-dimensional dataset rather than actual biological transitions. Without confirming directionality, pseudotime cannot be used as evidence for MAPK-driven transitions. Statistical measures of trajectory uncertainty, such as bootstrap confidence intervals or manifold stability tests, are also absent. The lack of these essential validation steps leaves the pseudotime-based claims conceptually and statistically unsubstantiated. 4.6. Single-Cell Statistical Power, Sampling Bias and the Absence of Cross-Dataset Validation Single-cell datasets are inherently high-dimensional and sparse, and the reliability of statistical inference depends on adequate biological replication and robust crossvalidation. In the present study, the sample sizes, though large at the level of total cells, are limited at the biological replicate level, meaning that statistical power is overestimated. Additionally, dissociation procedures introduce sampling biases that alter the representation of certain populations, particularly fragile or adherent cells. Without technical replicates using distinct dissociation methods, it is impossible to determine whether cell state frequencies reflect biology or preparation bias. The study does not test whether cell states identified in one dataset appear consistently in another. Cross-dataset validation using external colorectal cancer single-cell atlases, including patient-derived data, is essential when proposing novel cell states. In the absence of such comparisons, it remains unclear whether the inferred states reflect broadly reproducible biology or model-specific artifacts. Computational claims of new identity states must be supported by external validation, yet no such evidence is presented. 17 4.7. Normalization and Statistical Treatment of Proteomic and Phosphoproteomic Data The study’s reliance on proteomic and phosphoproteomic analyses to support transcriptional inferences requires exceptionally rigorous normalization and statistical evaluation. However, the reporting of proteomic methods is insufficient. There is no detailed description of peptide quantification methods, normalization strategies, batch correction procedures or statistical thresholds. When proteomic datasets contain few biological replicates, false positives are common, and proteinlevel differences may reflect experimental variance rather than biological signaling shifts. The statistical treatment of phosphoproteomic data is particularly problematic. Phosphorylation levels fluctuate rapidly in response to stress, dissociation, inhibition and nutrient conditions. Accurate normalization requires either stable reference phospho-sites, isotopically labeled standards or rigorous internal controls. These elements appear absent or insufficiently described. Moreover, the study interprets small fold-changes in phosphorylation as robust evidence of pathway rewiring, yet in proteomics, fold-changes below twofold are often overwhelmed by technical noise. Without statistical confidence intervals, p-values corrected for multiple testing, and validation using orthogonal assays, proteomic interpretations remain tentative. 4.8. Statistical Interpretation of Imaging and Colocalization Data Imaging data, while visually compelling, require numerical and statistical evaluation to support mechanistic conclusions. The study often presents representative images without quantitation, leaving uncertainty about whether observed patterns reflect systematic differences or selection of favorable fields. Image analysis pipelines must include unbiased region selection, intensity thresholding, normalization of exposure times, segmentation reproducibility and statistical comparison across multiple fields and biological replicates. These elements are not adequately described. The statistical interpretation of colocalization must involve formal metrics such as Pearson’s correlation coefficients, Manders’ coefficients or spatial cross-correlation analyses. Without these metrics, claims based on colocalization remain qualitative and insufficiently grounded statistically. The absence of time-resolved imaging further limits the interpretation, as static images cannot distinguish identity transitions from transient expression changes. 18 4.9. Statistical Design of In Vivo Experiments and the Absence of Power Analysis In vivo experiments require statistical power calculations to ensure that sample sizes are sufficient to detect biologically meaningful differences. The study provides limited information regarding powering, inclusion criteria or randomization. The number of animals used per group appears inadequate to support strong statistical conclusions, particularly in the presence of high tumor heterogeneity. Variability in tumor sizes, proliferation rates and signaling markers must be addressed through sufficiently powered replicates, yet the study’s design does not appear to meet these standards. Survival analyses also lack critical statistical details, including hazard ratios, model assumptions, censoring criteria and confidence intervals. Without rigorous statistical treatment, survival curves offer only superficial insights and cannot substantively support claims about MAPK-driven resistance mechanisms. 4.10. Pathway Enrichment Analyses and the Problem of Circular Inference The study relies heavily on pathway enrichment analyses to support claims that MAPK signaling drives identity reprogramming. Yet pathway analyses often rely on gene sets derived from the same dataset being tested, creating a risk of circular inference. For example, if clusters are defined using genes that include MAPK targets, enrichment for MAPK signatures becomes mathematically inevitable rather than biologically informative. Pathway enrichment must be validated by testing externally derived gene sets, applying permutation-based significance testing and evaluating whether enrichment remains robust when controlling for biases inherent in gene set construction. The study does not appear to perform these safeguards. Consequently, claims about MAPK-specific enrichment lack the statistical independence necessary to support mechanistic conclusions. 4.11. Reproducibility, Transparency and the Absence of Code Availability A central requirement for computational reproducibility is the availability of code, parameter settings, versions of software packages and full pipelines. The study offers insufficient detail in this regard. Without access to the computational workflows, independent researchers cannot verify cluster boundaries, normalization choices, pseudotime ordering or pathway enrichment. Lack of transparency hinders reproducibility and renders key claims unverifiable. For a conceptually transformative claim such as MAPK-driven epithelial plasticity, computational transparency is indispensable. 19 4.12. Integration of Statistical and Computational Weaknesses The statistical and computational limitations outlined across single-cell RNA sequencing, proteomics, imaging and in vivo experiments do not operate in isolation. They intersect and compound one another, amplifying interpretative fragility. The study repeatedly interprets high-dimensional noise as structured biological signal, transient fluctuations as evidence of lineage transition and algorithmic outcomes as confirmation of mechanistic hypotheses. Without rigorous statistical grounding, robust normalization, replicate-level analysis, and cross-dataset validation, the computational architecture cannot sustain the weight of the study’s mechanistic claims. The result is a set of conclusions that may reflect computational artifacts rather than genuine biological insights. 5. Figure-by-Figure Critique 5.1. Figure 1: Foundational Claims Built on Ambiguous Identity Markers and Methodological Instability Figure 1 is intended to establish the existence of MAPK-linked epithelial plasticity by defining a set of transcriptional and phenotypic states that differentiate “plastic” from “non-plastic” epithelial cells. It anchors the conceptual framework for the entire study. However, this central figure suffers from substantial methodological ambiguity, interpretive overreach and structural weaknesses that undermine the foundational premise. The figure introduces identity markers that are neither lineage-specific nor validated across independent datasets. Many of the markers that the authors use to define states are known to fluctuate in response to stress, proliferation dynamics, metabolic shifts or mechanical dissociation, which are common confounders in organoid and in vivo tumor preparations. The choice of markers appears driven by differential expression rather than by biological relevance to lineage identity, raising concerns that the entire classification scheme rests on unstable criteria. The single-cell data displayed in Figure 1 rely on UMAP embeddings and cluster boundaries that lack validation through replicate datasets or computational robustness checks. The figure presents clusters as discrete entities, yet no evidence is provided that these clusters persist across varied clustering resolutions, parameter settings or biological replicates. The separation observed on the UMAP plot is interpreted as proof of distinct identity states induced by MAPK modulation. However, UMAP imposes nonlinear distortions, and cluster boundaries in twodimensional space do not necessarily reflect meaningful biological separation. Without quantitative metrics such as silhouette scores, dispersion tests or crossbatch reproducibility, the visual clustering presented in Figure 1 cannot be assumed to correspond to stable cell states. 20 The figure also includes immunostaining panels that purport to show spatial localization of plasticity markers. Yet the imaging is qualitative, lacking quantification of intensity, co-expression or spatial enrichment. The images appear to capture selected fields, raising the risk of unintentional or intentional selection bias. Exposure settings, thresholding, segmentation and background normalization are not detailed, making the results impossible to reproduce or verify. The figure fails to clarify whether images represent the average behavior of the population or isolated examples chosen for visual clarity. Without objective quantification, the imaging data cannot substantiate claims of identity transitions. Finally, the figure provides no functional evidence that the transcriptional states defined lead to meaningful differences in survival or response to therapy. Without linking identity states to function, the interpretation remains speculative. As a result, Figure 1 fails to convincingly establish that MAPK activation induces bona fide epithelial plasticity, instead presenting visual and transcriptional artifacts as putative biological states. 5.2. Figure 2: Overinterpretation of Pharmacological Perturbations Without Adequate Controls Figure 2 attempts to show that pharmacological modulation of the MAPK pathway induces transitions between the cell states defined in Figure 1. The authors treat drug-induced shifts in transcriptional signatures as evidence of identity reprogramming, yet the methodological limitations inherent in drug studies, particularly those involving MAPK inhibitors, undermine this interpretation. Drugs used to inhibit BRAF, MEK or ERK often exhibit dose-dependent toxicities and offtarget effects, which can dramatically reshape transcriptional landscapes independent of MAPK modulation. The doses employed in the study are not justified as being clinically relevant, physiologically tolerable or optimized for minimal stress induction. Without careful dose–response characterization, it is impossible to determine whether observed transcriptional shifts reflect specific pathwaydependent mechanisms or simply broad stress responses. The figure’s transcriptional analyses again rely on UMAP plots and cluster transitions that are presented without temporal resolution. The assumption that cells move from one cluster to another under drug treatment is unsubstantiated, because static snapshots cannot document transitions. Drug treatment may selectively kill subsets of cells, enrich others or alter cell-cycle states, all of which generate cluster shifts without any identity transformation. The figure provides no time-course analysis showing that the same cells change state over time. Without this, the interpretation of cluster transitions as identity shifts is fundamentally flawed. 21 The figure also includes Western blot or phospho-protein panels meant to demonstrate MAPK inhibition or reactivation. However, these data are presented qualitatively, often without loading controls, quantification or replicate demonstration. Signal changes are subtle, and the absence of normalization creates uncertainty about interpretation. If MAPK inhibition is incomplete or inconsistent across replicates, transcriptional responses may reflect fluctuating MAPK output rather than discrete transitions. The figure fails to demonstrate a mechanistic link between MAPK signaling levels and the proposed identity states beyond correlative impressions. Overall, Figure 2 fails to establish causality between MAPK pathway modulation and the emergence of plasticity states. Instead, it presents drug-induced transcriptional noise and stress-related alterations as evidence of identity transformations. 5.3. Figure 3: Pseudotime Misinterpretation and Absence of Lineage Validation Figure 3 is presented as evidence that cells traverse a continuum of transcriptional states under MAPK modulation, implying a lineage-like progression between epithelial identity states. The authors use trajectory inference and pseudotime modeling to map endpoints and intermediate states. However, pseudotime modeling is highly sensitive to data structure, and in the absence of independent validation, it cannot be used as evidence of directional biological transitions. The figure’s pseudotime axis is treated as a temporal sequence, yet pseudotime represents a computational ordering, not a real temporal unfolding. The method assumes linear or branching progression, but cancer transcriptomes often reflect stochastic fluctuations rather than ordered transitions. Without experimentally determined time points or lineage barcoding, the ordering is speculative. The figure attempts to show that cells exposed to MAPK inhibitors occupy early pseudotime states, while cells in MAPK-reactivated conditions occupy late states. However, such patterns can arise from batch effects or differential sensitivity to dissociation stress. Without batch correction validation, the trajectory may reflect technical differences rather than biological progression. The figure also includes gene-expression heatmaps aligned along the pseudotime axis. These heatmaps appear to show gradual changes in expression, but the selection of genes may reflect cherry-picking to enhance visual coherence. Genes that fluctuate strongly with stress, such as immediate-early genes or mitochondrial stress markers, often show pseudotime-like patterns independent of lineage changes. Without external validation, the trajectory mapping is unconvincing. Furthermore, the authors failed to test whether the same transcriptionally inferred states correspond to protein-level signatures or chromatin changes, which are 22 essential indicators of stable identity transitions. Because pseudotime is interpreted without orthogonal validation, the conclusions in Figure 3 remain speculative, representing computational artifacts rather than evidence of MAPK-driven plasticity. 5.4. Figure 4: Inadequate Proteomic Evidence and Misinterpretation of Signaling Changes Figure 4 attempts to provide proteomic and phosphoproteomic support for the existence of plasticity states and their dependence on MAPK signaling. The proteomic data are presented as evidence of pathway rewiring and altered transcription factor activity in MAPK-modulated states. However, the proteomic and phosphoproteomic methodologies are underpowered, insufficiently controlled and poorly described. The number of replicates appears inadequate to support robust statistical differentiation between states. Many proteins show modest fold-changes that fall within the expected variability of proteomic quantification. The figure presents heatmaps of differentially phosphorylated proteins, but without normalization details, it is impossible to evaluate whether differences are genuine. If normalization was performed using global scaling, changes in protein abundance or sample preparation efficiency may distort phosphorylation estimates. The study does not specify whether spike-in standards, internal controls or housekeeping normalization were used. Without these details, the interpretations of pathway activity are ungrounded. The figure attempts to link phosphorylation changes to alterations in transcription factor activity or chromatin regulators. Yet such linkages require orthogonal validation, such as ATAC-seq for chromatin accessibility or electrophoretic mobility shift assays. None are provided. The proteomic layer therefore does not rise to the level necessary to substantiate claims of identity reprogramming. Instead, the proteomic evidence appears to be selected to reinforce a predetermined narrative, rather than emerging organically from robust statistical analysis. 5.5. Figure 5: Insufficient Lineage-Tracing Evidence and Misinterpretation of Clonal Dynamics Figure 5 is perhaps the most critical figure in the study because it purports to demonstrate that individual epithelial cells transition between states under MAPK modulation. The figure uses lineage-tracing strategies involving tamoxifen-inducible reporters. However, these systems label large subsets of cells rather than enabling true clonal tracking. Without tracking individual clones, the figure cannot establish whether transitions occur at the single-cell level or whether resistant populations emerge through selection of pre-existing clones. The authors assume lineage 23 transitions based on altered marker distributions but do not prove that lineagetraced cells change identity. The temporal spacing between tamoxifen induction and MAPK manipulation is insufficient to establish directionality. If labeling occurs shortly before drug treatment, the labeled population may include cells at different stages of differentiation or stress readiness. Under these conditions, differential survival or proliferation rather than identity transition can generate apparent changes in state frequency. Because the lineage-tracing lacks temporal granularity, it cannot support claims that MAPK activation induces state transitions. The imaging panels in this figure show co-expression patterns of lineage markers and plasticity markers, yet as in prior figures, the selection of markers lacks specificity and functional relevance to identity transitions. Many of the markers are associated with proliferation rates, stress activation or cytokine signaling. Their coexpression is not indicative of lineage flux. Overall, Figure 5 fails to provide the single-cell resolution necessary to claim true plasticity and instead presents clonal selection patterns as evidence of identity transitions. 5.6. Figure 6: Therapeutic Resistance Assays and Overinterpretation of Tumor Response Dynamics Figure 6 aims to connect MAPK-driven plasticity with therapeutic resistance in vitro and in vivo. The authors present survival curves, drug-response assays and in vivo tumor regression data. However, the statistical and methodological weaknesses in these experiments undermine their interpretation. In vitro viability assays are conducted without demonstrating that cell populations were synchronized, equivalently seeded or uniformly exposed to drug conditions. Variability in cell density, nutrient availability or drug penetration can generate survival differences unrelated to identity transitions. The figure does not provide replicate-level statistical assessments, confidence intervals or effect sizes. Without rigorous quantification, the apparent differences may reflect noise rather than biological signal. In vivo tumor response data suffer from insufficient sample sizes and inconsistent quantification. Tumor volumes are often measured manually, introducing operator bias. Survival analyses are presented without hazard ratios or proper statistical treatment of censored data. Differences in tumor growth may reflect variability in engraftment efficiency or microenvironmental factors rather than MAPK-dependent identity transitions. The figure also attempts to show that targeting MAPK signaling restores sensitivity in plastic cells. Yet the study does not validate whether the plasticity markers used 24 to designate resistant cells are indeed predictive of drug response. Without demonstrating that the proposed identity states causally influence therapeutic sensitivity, the conclusions remain correlative. 5.7. Figure 7: Therapeutic Targeting Strategy Based on an Unsupported Mechanistic Model Figure 7 extrapolates the findings into a therapeutic strategy intended to prevent or reverse plasticity. However, because the earlier figures fail to convincingly establish the existence of MAPK-driven plasticity, the translational conclusions in Figure 7 are built on an unstable conceptual foundation. The authors propose interventions targeting the MAPK pathway or putative plasticity regulators, yet the mechanistic evidence connecting these interventions to identity state transitions is weak. The figure presents schematic models and drug-combination experiments that appear to suppress plasticity markers. Yet changes in marker expression do not equate to identity restoration. The figure lacks mechanistic assays validating that proposed interventions stabilize epithelial identity at the chromatin level or prevent state transitions in a lineage-informative manner. Without such validation, the strategy is premature and may mislead researchers toward therapeutics that target artifacts rather than genuine biological drivers of resistance. Moreover, the therapeutic strategy does not integrate well-known clinical realities: combined MAPK pathway inhibition has not yielded durable responses in colorectal cancer, even in advanced combinatorial regimens. The translational claims in Figure 7 therefore conflict with established clinical evidence. 5.8. Integrated Assessment Across All Figures: Structural Fragility and Narrative Construction Taken together, Figures 1-7 constitute a narrative that attempts to demonstrate a coherent process of MAPK-driven epithelial plasticity, from state definition to mechanistic mapping to therapeutic implications. Yet close analysis demonstrates that the figures do not collectively support this narrative. Each figure contains methodological gaps, interpretive weakness or unvalidated assumptions. The study does not present a single line of evidence that unequivocally documents a lineage transition at the single-cell, chromatin, transcriptional or functional level. Instead, the figures present a sequence of correlated but unproven phenomena, often influenced by stress, drug exposure, or computational artifacts. The cumulative effect is a constructed narrative rather than a mechanistically validated model. Because each figure depends on the previous one for conceptual continuity, the weaknesses in early figures propagate through the entire study, leaving the final conclusions unsupported. 25 6. Extended Data (ED) Figures Analysis 6.1. Overview of the ED Landscape and Its Role in Supporting a HighRisk Mechanistic Claim The ED figures in the study by White and colleagues constitute a substantial portion of the evidentiary framework used to bolster the paper’s ambitious claim that MAPK-driven epithelial cell plasticity underlies therapeutic resistance in colorectal cancer. Because the main figures rely heavily on conceptual leaps, computational inference and selective imaging, the Extended Data are positioned as the technical backbone meant to provide robustness, depth and reproducibility. In principle, Extended Data should clarify ambiguities, validate computational outputs across replicates, provide mechanistic support through independent assays and offer transparency for quantitative procedures. However, across nearly all ED figures, methodological gaps, insufficient replication, ambiguous quantification, biased sampling, and interpretative overreach recur. Instead of strengthening the study, the Extended Data reveal fragilities in experimental design, computational pipelines and biological interpretation that significantly weaken the central conclusions. What follows is a detailed analysis of each major category of Extended Data, examining the evidence at a methodological, statistical, and conceptual level. 6.2. ED Figure 1: Marker Validation and the Fundamental Instability of the Plasticity Classifiers ED Figure 1 is intended to validate the molecular markers used throughout the study to define “plastic” versus “non-plastic” epithelial states. This figure is particularly important because the entire framework of the paper relies on the definition of these states. Unfortunately, the validation remains incomplete, inconsistent and biologically unconvincing. Markers presented as plasticityassociated lack specificity and often correspond to known stress-response pathways, proliferation-associated genes or metabolic regulators. Many of the markers upregulated under MAPK-modulated conditions are also upregulated under hypoxia, nutrient deprivation, cytokine exposure or dissociation-induced stress. The figure provides no evidence that these markers reflect stable or lineagedetermining changes. Protein-level confirmation is minimal and largely qualitative, with small panels of immunofluorescence images showing inconsistent staining patterns. The figure does not provide quantification across multiple biological replicates, nor does it compare marker expression across independent datasets or patient-derived samples. Without multi-layer validation, these markers cannot reliably define identity states. The figure thus fails to justify their use as classifiers, rendering all downstream analyses that rely on these markers unstable. 32 7.4. SF4: Pseudotime and Trajectory Analyses Expanded Without New Validation SF4 presents additional pseudotime and trajectory analyses, presumably to strengthen the argument that epithelial cells move through MAPK-dependent transitional states. However, these expanded analyses suffer from the same conceptual and computational limitations identified earlier. The figure does not include time-resolved single-cell data, lineage-traced datasets or functional assays capable of validating the inferred trajectories. The trajectories appear smooth and coherent due to algorithmic smoothing and gene selection rather than reflecting biological transitions. The figure also includes gene expression trends plotted along pseudotime. These trends show gradual changes for selected genes, but without biological validation, such changes cannot be interpreted as genuine lineage dynamics. The figure lacks demonstrations that pseudotime ordering is robust to subsampling, alternative dimensionality reductions or changes in trajectory inference parameters. Without such validation, the pseudotime analyses remain speculative and cannot be used as evidence for MAPK-driven transitions. 7.5. SF5: Additional Western Blots with Minimal Quantitative Value SF5 presents expanded Western blots intended to corroborate the MAPK pathway activity patterns described in the main figures. However, the blots appear inconsistently processed, with variable exposure levels, inconsistent loading controls and insufficient replicates. The faintness of several bands raises concerns about signal quality and quantifiability. Without digital quantification across multiple replicates, Western blots serve only as qualitative indicators, offering limited mechanistic value. Moreover, the figure does not address whether MAPK activation or inhibition is spatially heterogeneous across tissues or organoids. If MAPK activity varies across microenvironments, the Western blot data—which represent bulk measurements— could mask critical spatial dynamics. As a result, the supplementary Western blots do not materially strengthen the mechanistic foundation of the study. 7.6. SF6: Imaging Panels Without Temporal or Quantitative Context SF6 expands on imaging analyses by providing additional immunofluorescence or immunohistochemistry staining. Yet, as in the main text and Extended Data, these images are qualitative and lack quantitation. Without automated segmentation, normalized exposure, unbiased field selection or statistical analysis, imaging cannot support mechanistic claims. The supplementary material fails to provide any deeper 33 resolution into how markers change over time, which is essential for claims of cellstate transitions. A major conceptual issue emerges here: imaging snapshots cannot establish whether markers represent transient stress responses or stable markers of identity. Without live-cell imaging or time-resolved snapshots, the supplementary figure adds volume but not mechanistic clarity. Thus, this figure does not strengthen the claim of epithelial plasticity. 7.7. SF7: Expanded Proteomic Heatmaps Without Statistical Transparency SF7 presents additional proteomic and phosphoproteomic analyses. However, these expanded datasets continue to suffer from insufficient statistical annotation. Heatmaps are presented without p-values, fold-change thresholds, normalization strategies or false-discovery correction. Without these details, proteomic claims rest on interpretive rather than statistical foundations. The supplementary material attempts to map signaling networks based on differential phosphorylation. Yet these networks appear inferred rather than experimentally validated. Protein-protein interactions derived from public databases or computational tools must be supported by biochemical assays in the system under study. The figure, lacking such validation, contributes little to the mechanistic argument. 7.8. SF8: Additional Genetic Manipulations with Limited Mechanistic Insight SF8 expands upon genetic perturbations, including CRISPR knockdown and overexpression strategies. The figure repeats earlier weaknesses: incomplete validation of editing efficiency, absence of off-target assessment, and limited demonstration that engineered perturbations mimic the conditions seen in therapeutic resistance. The figure provides no long-term analyses to determine whether perturbations lead to stable identity changes or merely short-lived transcriptional responses. The use of genetic perturbations is central to any mechanistic study claiming causality. Yet the supplementary material falls short of demonstrating causality, offering only suggestive correlations without rigorous mechanistic testing. The figure therefore does not strengthen the study’s theoretical foundation. 34 7.9. SF9: Organoid-Based Functional Assays With Incomplete Quantification SF9 presents organoid viability, proliferation and morphology assays. As with related Extended Data, these supplement figures suffer from insufficient quantification and control for confounding variables. Organoid systems are highly sensitive to culture batch, matrix thickness, growth factor concentrations and oxygen gradients. The figure does not control for these factors. Proliferation assays using EdU or Ki-67 staining lack quantification across replicates, and viability assays rely on metabolic readouts that do not distinguish between proliferation changes and cell death. The supplementary figure attempts to relate organoid morphology to identity state, but morphology can be influenced by numerous non-identity variables. Without connecting morphology to lineage markers, chromatin states or transcription factor activity, the conclusions drawn from these assays remain speculative. 7.10. SF10: Computational Predictions of Differentiation or Stemness Signatures Without Experimental Confirmation SF10 introduces computational analyses meant to infer changes in differentiation, stemness or progenitor-like characteristics in plasticity-associated states. The figure presents enrichment scores for gene sets associated with stemness or differentiation. However, enrichment analysis is only as reliable as the underlying gene sets, normalization steps and statistical thresholds. The figure does not disclose whether multiple-testing correction was applied or whether enrichment robustness was assessed using permutation tests. Furthermore, computational predictions of stemness require biological validation— such as sphere-forming assays, transplantation assays or lineage-specific metabolic profiling. None are provided. Without confirmation that predicted stemness corresponds to functional stemness, the figure’s conclusions remain interpretive and do not support claims of identity reprogramming. 7.11. SF11: Attempts at Linking Plasticity to Drug Response Without Adequate Controls SF11 presents expanded drug-response data aiming to link plasticity state markers to therapeutic sensitivity. Yet the assays lack essential controls. Drug-response curves should normalize for cell number, proliferation rate and metabolic state. The figure does not show whether plastic versus non-plastic cells proliferate at similar rates at baseline. If proliferation differs, drug-response metrics become confounded. The figure uses IC50 values derived from datasets that lack biological replicates. Without replicate-level statistical metrics or confidence intervals, IC50 estimates 35 cannot support strong conclusions. Furthermore, the figure does not demonstrate that cell-state markers predict drug response in patient-derived samples. Without clinical validation, the supplementary drug-response data remain model-specific and do not establish translational relevance. 7.12. SF12: Expanded In Vivo Analyses Without Improved Rigor SF12 presents additional in vivo imaging, tumor volume quantification, or survival curves. However, the weaknesses of the main in vivo experiments persist in the supplementary material. Sample sizes remain small, quantification methods remain insufficiently documented, and statistical analyses are absent or incomplete. Tumorrange variability is high, suggesting substantial biological noise or inconsistency in tumor engraftment. Several supplementary panels display images of tumors expressing various markers, but without quantification across multiple animals, these images cannot support claims of identity transitions. The supplementary material also does not address whether plasticity-associated states appear in human relapse samples, which is essential for translation. As a result, the supplementary in vivo data fail to provide additional support for the study’s conclusions. 7.13. Integrated Assessment of the Supplementary Material: Volume Over Substance Across all supplementary figures, a consistent pattern emerges: extensive but shallow visual and computational data presented as mechanistic evidence without the quantitative, replication-based and functional depth required to substantiate claims of MAPK-driven epithelial plasticity. While the supplementary material offers an appearance of comprehensiveness, it frequently repackages the same methodological weaknesses seen in the main text and Extended Data. Most supplementary analyses lack independent validation, robust statistics, functional assays or clear mechanistic interpretation. The supplementary figures therefore do not reinforce the central claims but instead highlight the fragility of the study’s conceptual and methodological foundation. They rely on descriptive, correlative, underpowered or poorly controlled data that fail to distinguish transient transcriptional variation from true lineage reprogramming. As a result, the supplementary material magnifies uncertainties in the study rather than resolving them. 36 8. Biological Plausibility and Mechanistic Interpretation 8.1. Overview: Situating the Proposed Mechanism Within the Known Biology of Colorectal Cancer A mechanistic model proposing MAPK-driven epithelial plasticity as a central determinant of therapeutic resistance must withstand scrutiny not only at the technical and statistical level but at the level of biological plausibility. Colorectal cancer is one of the most intensely studied malignancies, with decades of work defining its mutational architecture, lineage fidelity, microenvironmental dependencies, metabolic constraints and therapeutic response patterns. Any new mechanistic model must harmonize with this extensive foundational knowledge unless it explicitly demonstrates that established frameworks are incomplete or misleading. The study by White and colleagues attempts to introduce a mechanism that deviates significantly from the dominant understanding of colorectal cancer biology. The proposed mechanism asserts that MAPK pathway activity induces dynamic, reversible transitions in epithelial identity that fundamentally alter therapeutic response. However, when considered against known biological principles governing intestinal epithelium, cancer evolution, tissue identity maintenance, therapeutic adaptation and signaling pathway hierarchies, the model reveals substantial implausibilities. This section examines the mechanistic coherence of the MAPK-driven plasticity hypothesis through a lens grounded in established colorectal cancer biology. 8.2. The Stability of Epithelial Identity in the Intestinal Epithelium The intestinal epithelium is among the most structurally constrained and lineagestable tissues in the body. Its identity is governed by a tightly coordinated interplay of stem-cell niche signals, crypt-villus architecture, transcription factor networks and chromatin landscape features that maintain epithelial fidelity even under significant environmental stress. Intestinal stem cells at the crypt base give rise to transient amplifying cells, which then differentiate along well-defined lineages into absorptive enterocytes, goblet cells, enteroendocrine cells or Paneth cells. This hierarchy is maintained through robust epigenetic programming, including lineagedefining transcription factors such as CDX2, KLF4 and HNF4A, and canonical WNTdependent chromatin structures that anchor gene regulatory networks. Even when mutated to form colorectal cancers, epithelial cells retain these lineage architectures. Mutation of APC, KRAS, BRAF or TP53 does not dissolve epithelial identity, and even in metastatic lesions, colorectal cancer cells continue to express core epithelial markers, maintain epithelial junctions and exhibit lineageconstrained differentiation patterns. This biological rigidity stands in contrast to tumor types such as melanoma or small-cell lung cancer, where identity shifts have 37 been documented. For colorectal cancer, stable epithelial identity is fundamental to both physiology and oncogenesis. For the MAPK-driven plasticity model to be plausible, one would expect evidence of disrupted lineage determinants, altered chromatin architecture or destabilized epithelial transcription factor networks. However, the study does not present such evidence. Without demonstrating that fundamental epithelial identity machinery is altered, the claim that MAPK drives large-scale identity transitions lacks biological plausibility. 8.3. The Established Role of MAPK Signaling in Colorectal Cancer: Proliferation, Stress Response and Survival, Not Identity MAPK signaling plays well-established roles in colorectal cancer: regulating proliferation, supporting survival, enabling metabolic adaptation and controlling stress-response pathways. These functions have been extensively validated through genetic models, pharmacological experiments, clinical trials and patient-derived data. MAPK activation following EGFR inhibition is a hallmark of resistance, but this reactivation reflects restoration of proliferative and mitogenic signaling rather than identity transition. MAPK is not a lineage-specifying pathway in intestinal biology. The pathway does not control chromatin state transitions, transcription factor hierarchies or epigenetic anchoring of lineage programs. Its influence is largely post-translational, affecting phosphorylation of downstream effectors such as ERK, MEK and RSK, which control transcription of immediate-early genes and regulate cell-cycle progression. MAPK pathway dynamics occur on timescales of minutes to hours, whereas lineage transitions require stable chromatin remodeling on timescales of days or longer. For MAPK to induce epithelial plasticity, it would need to modulate transcription factor networks or chromatin modifiers at a level not previously established. The study does not provide evidence that MAPK activation affects lineage-defining transcription factors, induces chromatin accessibility changes or rewires gene regulatory networks. Without demonstrating that MAPK activity achieves something beyond its known function, the claim that it drives identity transitions remains unsubstantiated. 8.4. Distinguishing Transient Transcriptional Responses from Stable Identity Changes Colorectal cancer cells exhibit significant transcriptional heterogeneity, especially under therapeutic stress. This heterogeneity arises from metabolic fluctuations, cytokine signaling, cell-cycle differences, mitochondrial stress and 38 microenvironmental influences. MAPK pathway modulation is known to trigger immediate-early gene responses affecting transcription for short periods. These transient responses include genes associated with proliferation, inflammation and oxidative stress. The study fails to distinguish transient, stress-induced transcriptional changes from true plasticity. A lineage transition implies durable changes in gene expression, chromatin accessibility and cellular phenotype that persist after removal of the initial stimulus. However, the study presents no time-resolved data demonstrating persistence of the proposed states. The transcriptional clusters could reflect temporary stress responses rather than identity changes. Without demonstrating stability across time and conditions, the proposed plasticity states remain biologically implausible. 8.5. The Role of Clonal Selection in Therapeutic Resistance Therapeutic resistance in colorectal cancer is dominated by clonal selection rather than identity transformation. Resistant clones often pre-exist in small numbers and harbor mutations that confer a fitness advantage under selection pressure. Numerous studies have documented that pre-existing KRAS or NRAS mutations drive resistance to EGFR inhibitors, and expanded subclones emerge under treatment. Even in MAPK-targeted therapies, resistance typically arises through restoration of MAPK output via secondary mutations or activation of bypass pathways. There is overwhelming evidence that resistance emerges through Darwinian evolution of tumor populations rather than reprogramming of established clones. For identity transitions to be biologically plausible as a driving force of resistance, the proposed plasticity states would need to confer greater fitness advantages than classical mechanisms such as mutational escape. The study does not quantify fitness differences, nor does it demonstrate that plastic states persist or expand during treatment. Without showing selective advantage, the plasticity model lacks evolutionary grounding. 8.6. Chromatin-Level Requirements for Identity Change Are Not Met Lineage identity in epithelial tissues is anchored by chromatin architecture and epigenetic programs that stabilize regulatory gene networks. Genuine plasticity requires changes in chromatin accessibility, nucleosome positioning, histone modifications or DNA methylation patterns. These mechanisms enable transitions into alternative identity states, as documented in EMT, stemness reprogramming or neural crest-like transitions in other cancers. 39 The study presents no chromatin-level data—no ATAC-seq, no ChIP-seq, no DNA methylation analyses and no reporter assays for lineage-specific enhancers. Without evidence at this mechanistic tier, claims of identity change remain biologically hollow. Transcriptional fluctuations alone cannot establish plasticity, because gene expression changes frequently occur without chromatin remodeling. Unless the authors demonstrate that MAPK modulation induces epigenetic reconfiguration, the model is incompatible with known mechanisms of lineage fidelity. 8.7. Microenvironmental Constraints That Limit Cellular Identity Transitions The tumor microenvironment of colorectal cancer is structurally rigid and imposes strong identity constraints. The colon is subject to mechanical forces, microbiome interactions, hypoxia gradients and stromal architecture that reinforce epithelial identity. Even metastatic sites such as the liver impose constraints that prevent drastic identity transitions. Any model proposing identity shifts must account for these ecological pressures. The study does not provide evidence that microenvironmental conditions support identity transitions or that plastic states exist in patient tumor samples. The absence of microenvironmental integration renders the model disconnected from ecological realities. Without showing that proposed plastic states can survive and expand in vivo, the mechanism remains implausible. 8.8. Lack of Consistency with Human Clinical and Histopathological Data The most compelling test of biological plausibility lies in clinical evidence. Colorectal tumors that relapse under MAPK-targeted therapies do not exhibit the histopathological changes expected from identity transitions. They remain epithelial, retain lineage markers and show no evidence of dedifferentiation consistent with the states proposed in the study. Clinical relapse almost always reflects reactivation of MAPK signaling through mutations, bypass pathway activation or stromal remodeling. If MAPK-driven plasticity were central to resistance, one would expect clear histological evidence in relapse specimens, spatial heterogeneity consistent with plasticity gradients, or transcriptomic signatures detectable in patient biopsies. The study presents none of these data. Without demonstrating relevance to human disease, the mechanism remains biologically implausible. 8.9. Conceptual Inconsistencies Within the Plasticity Narrative Biological plausibility is further undermined by internal inconsistencies within the proposed mechanism. The authors define plasticity differently across sections: at 40 times as transcriptional heterogeneity, at times as functional shifts and at times as spatial marker co-expression. These definitional inconsistencies diminish theoretical clarity. A stable mechanistic model requires clear criteria for plasticity, grounded in measurable biological features. Without such clarity, the mechanism becomes elastic enough to absorb any dataset, risking circular reasoning. Additionally, the study claims that MAPK activity simultaneously drives plasticity and sustains proliferation. These functions can be antagonistic; plastic or transitional states often exhibit reduced proliferation as part of identity remodeling. The study does not clarify how MAPK signaling maintains proliferative signaling while simultaneously pushing cells into altered identity states. This conceptual conflict further diminishes biological plausibility. 8.10. The Missing Mechanistic Intermediaries: Transcription Factors, Epigenetic Regulators and Signaling Cascades For MAPK-driven plasticity to be credible, one would expect identification of mechanistic intermediaries. Such intermediaries could include transcription factors altered by MAPK activity, epigenetic regulators that respond to ERK signaling or signaling cascades that integrate MAPK output with chromatin remodeling. However, the study does not identify any such intermediaries. No transcription factors are experimentally validated as mediators of plasticity. No epigenetic regulators are shown to be modulated by MAPK. No signaling cross-talk is mechanistically mapped. Without defining intermediaries, the mechanism remains incomplete. MAPK output alone cannot plausibly orchestrate identity change without downstream transcriptional or epigenetic machinery. The absence of mechanistic intermediaries represents a significant conceptual gap. 8.11. The Misinterpretation of Model-Specific Artifacts as Biological Plasticity Finally, the biological implausibility of the mechanism becomes evident when considering the likelihood that observed phenomena reflect artifacts of model systems rather than intrinsic biological processes. Organoid cultures create artificial microenvironments that induce stress, alter differentiation gradients and amplify transcriptional variability. Murine tumors, although informative, differ significantly from human tumors in lineage behavior and microenvironmental complexity. Dissociation stress in single-cell sequencing can induce transcriptional states that mimic injury or plasticity. Overexpression systems and genetic perturbations often cause supraphysiological pathway activation, inducing stress responses unrelated to identity state. 41 The failure to account for these artifacts leads the study to misinterpret modeldependent transcriptional noise as evidence of lineage transformation. Without validating findings across patient specimens, spatial transcriptomics or chromatinlevel assays, the claims remain biologically suspect. 8.12. Integrated Biological Assessment of the MAPK-Driven Plasticity Model Across all dimensions—lineage biology, signaling hierarchy, chromatin structure, microenvironmental constraints, clinical reality and evolutionary logic—the MAPKdriven epithelial plasticity model proposed by the authors fails to meet the threshold of biological plausibility. The model attempts to ascribe lineagetransforming capacity to a pathway known for its mitogenic, stress-response and metabolic regulatory roles. It misinterprets transient transcriptional fluctuations as identity shifts, overlooks the necessity of chromatin remodeling for true lineage change, and ignores microenvironmental and clinical evidence that contradict the mechanism. A biologically coherent model of therapeutic resistance in colorectal cancer must incorporate established principles: clonal selection, pathway reactivation, microenvironmental remodeling, metabolic adaptation and genomic evolution. These mechanisms provide robust explanatory frameworks that align with decades of clinical and experimental evidence. The proposed MAPK-driven plasticity model, lacking mechanistic clarity and biological grounding, represents a conceptual overreach rather than a substantiated addition to the field. 9. Reproducibility, Transparency, and Data Integrity 9.1. Overview: The Necessity of Rigorous Reproducibility Standards in High-Impact Mechanistic Claims Reproducibility and data integrity form the foundation upon which reliable scientific conclusions must rest, particularly in a study that proposes a mechanistic model positioned to reshape existing paradigms in cancer biology. The claim that MAPK-driven epithelial plasticity defines therapeutic resistance in colorectal cancer is a high-risk, high-impact assertion. For such a claim to be credible, it must be supported by transparent data reporting, reproducible computational workflows, validated experimental systems, and openly available resources enabling independent verification. Yet the study by White and colleagues exhibits significant deficiencies across nearly every dimension of reproducibility and transparency. The absence of essential datasets, incomplete reporting of computational parameters, unclear methodological descriptions and inconsistent documentation of experimental replicates collectively impede the ability of external investigators to 48 leap from this well-established functional role to a new claim of lineage-altering plasticity is vast and unsupported. The study treats any change in transcriptional profile as indicative of identity transformation, conflating transient adaptation with stable lineage reconfiguration. True cellular plasticity requires evidence of sustained phenotype alteration, the involvement of lineage-defining transcription factors, chromatin openness shifts, epigenetic remodeling and functional changes that persist independently of the inducing signal. The study provides none of these elements. Instead, it interprets modest transcriptional differences as signs of identity flux. This conceptual confusion results in a mechanistic narrative built on an unstable definitional foundation. The failure to rigorously differentiate between transcriptional noise, stress-induced signatures and genuine identity transitions generates conclusions that exceed what the data can support. 10.3. Structural Weakness in Experimental Design and Its Impact on Interpretation Across all experimental modalities, the study exhibits design inconsistencies that undermine mechanistic inference. Organoid cultures are used to model complex biological transitions without accounting for their inherent limitations, including stress-induced transcriptional shifts, absence of full microenvironmental context, and susceptibility to differentiation fluctuations. In vivo experiments use insufficient sample sizes, lack quantification, and show variability that suggests biological heterogeneity but is presented as mechanistic specificity. Genetic perturbations are inadequately validated, creating ambiguity about whether observed phenotypes arise from intended gene modifications or off-target effects. Drug experiments are conducted without rigorous dose optimization, solvent controls or time-course analyses, making it impossible to distinguish MAPK-specific effects from general cytotoxicity. Single-cell sequencing experiments treat thousands of dependent cellular observations as independent replicates, inflating significance and masking batch effects. These design weaknesses pervade the entire study, making mechanistic interpretation unreliable. When experimental design does not align with mechanistic hypotheses, the resulting interpretation becomes vulnerable to confounding variables, technical artifacts and misclassification. Therefore, even before evaluating specific findings, the structural weaknesses in experimental design alone call into question the validity of the study’s central claims. 49 10.4. Analytical Fragility: High-Dimensional Data Misinterpreted as Biological Trajectories The study’s reliance on single-cell RNA sequencing and computational trajectory inference represents one of its most profound interpretive vulnerabilities. Highdimensional transcriptomic data are powerful, but when used without rigorous statistical controls and biological validation, they can generate illusory structure. Clusters identified through UMAP or t-SNE embeddings often reflect technical artifacts or continuous variation rather than true biological categories. Trajectory inference applied to static datasets cannot establish temporal directionality without independent validation through lineage tracing or sampling across defined time points. In this study, clusters and trajectories are interpreted as discrete identity states and transitional paths. However, several lines of analysis demonstrate that these computational outcomes are unstable, under-validated and vulnerable to batch effects. The clustering results vary across replicates, and cluster stability is not statistically demonstrated. Pseudotime trajectories appear algorithmically smooth but lack biological anchors. The selection of marker genes for trajectory visualization reflects interpretive bias rather than comprehensive analysis. Without epigenetic data, chromatin maps or lineage-resolved temporal datasets, these trajectories cannot serve as evidence of lineage reprogramming. Thus, the computational framework, instead of providing mechanistic clarity, introduces an interpretive mirage that leads the authors toward an unwarranted conclusion. The interpretive fragility in high-dimensional data analysis is a major factor in the study’s conceptual overreach. 10.5. Failure to Integrate Chromatin, Epigenetic or Transcription Factor-Level Mechanistic Evidence One of the most striking weaknesses in the study is the absence of any mechanistic evidence at the level of chromatin structure, epigenetic programming or transcription factor regulation. Identity transitions require stable changes in gene regulatory networks anchored to chromatin-level remodeling. Without ATAC-seq, ChIP-seq, methylome analysis or transcription factor occupancy mapping, it is impossible to determine whether MAPK activity induces epigenetic changes capable of altering lineage identity. The study’s absence of such evidence is not merely a missing detail; it is a foundational deficiency. A claim of identity transformation without evidence at the regulatory level contradicts established principles in developmental biology, stemcell biology and cancer lineage plasticity research. Without showing that MAPK drives changes in enhancer accessibility, lineage transcription factor expression, 50 chromatin topology or epigenetic marks, the mechanistic chain from MAPK modulation to identity transition remains speculative and unsupported. The lack of epigenetic evidence also undermines the plausibility of stability in the proposed plastic states. If the states are not accompanied by epigenetic remodeling, then they are unlikely to persist after removal of the inducing signal, rendering them adaptive rather than plastic. This fundamental gap weakens the mechanistic credibility of the entire model. 10.6. The Missing Microenvironment: Ecological Constraints Ignored in the Model The intestinal epithelium exists within a highly structured microenvironment composed of stromal cells, fibroblasts, immune cells, vasculature, extracellular matrix, microbiota and mechanical forces. These elements influence cellular identity through paracrine signaling, metabolic gradients, inflammation and physical constraints. A mechanistic model proposing identity transitions must demonstrate that such transitions are feasible within this ecological framework. However, the study largely ignores the microenvironment, except in isolated organoid or xenograft experiments that do not replicate the complexity of human colorectal cancer. Microenvironmental constraints often reinforce epithelial identity rather than promote plasticity. For example, WNT gradients across crypts constrain stemness, while BMP signals promote differentiation. Stromal interactions maintain epithelial polarity, and immune infiltration influences functional but not lineage identity. Thus, any claim that identity transitions drive resistance must demonstrate that these transitions occur within the intact tumor ecosystem. The absence of spatial transcriptomics, imaging mass cytometry, or microenvironment-integrated analyses leaves the model ecologically ungrounded. Without microenvironmental integration, the model reflects cell-intrinsic assumptions that do not translate to the architectural, biochemical and cellular complexity of human tumors. 10.7. The Incompatibility of the Proposed Mechanism With Clinical Patterns of Resistance Clinically, resistance to MAPK pathway inhibitors in colorectal cancer almost always reflects genetic evolution or pathway reactivation rather than lineage transformation. Relapsed tumors retain epithelial identity, express canonical markers, and rarely demonstrate dedifferentiation patterns. If MAPK-driven plasticity were a major driver of resistance, one would expect relapse biopsies to show histological or molecular evidence of plastic states. The absence of such 51 patterns across decades of clinical observations strongly suggests that identity transitions do not represent a central mechanism of resistance. The study does not present patient-derived data demonstrating the presence or expansion of plastic states in clinical relapse. Without such validation, the model remains confined to artificial experimental systems and cannot credibly describe patient resistance mechanisms. Furthermore, the model conflicts with extensive clinical genomic evidence indicating that resistance is driven by secondary MAPK pathway mutations, activation of parallel pathways, or stromal reprogramming rather than phenotypic plasticity. Thus, the mechanism is not only unsupported by the study’s data but inconsistent with established clinical realities. 10.8. Alternative Interpretations Consistent With Both Data and Colorectal Cancer Biology When the data in the study are examined independently of the interpretive framework imposed by the authors, they align far more closely with alternative explanations that are well supported by current knowledge of colorectal cancer biology. Several biologically plausible interpretations arise naturally from established mechanisms and require no departure from existing paradigms. A primary explanation is that the transcriptional perturbations observed following MAPK inhibition reflect transient stress responses rather than bona fide lineage transitions. MAPK-targeted therapies are known to induce metabolic strain, mitochondrial dysfunction, oxidative stress, unfolded protein response activation and inflammatory signaling; these processes can readily generate transient transcriptional diversity without altering the underlying epithelial identity. An equally compelling and widely supported mechanism is clonal selection. Minor subpopulations with intrinsic MAPK reactivation capacity or activation of compensatory bypass pathways can preferentially expand under therapeutic pressure, producing shifts in cellular composition that superficially resemble state transitions but actually reflect Darwinian selection rather than plasticity. Cell-cycle heterogeneity represents another parsimonious explanation. Variability in the proportion of cells occupying S-phase, undergoing G1 arrest or initiating apoptosis can create structured differences in single-cell transcriptomes that computational algorithms may misinterpret as distinct identity states. In addition, dissociation-induced stress during single-cell preparation can artifactually activate stress-response genes, many of which overlap with the genes the authors label as markers of “plasticity.” Without rigorous controls for dissociation protocols and stress-induced artifacts, these signatures cannot be interpreted as evidence of stable biological states. Finally, the inherent spatial heterogeneity within tumor microenvironments—including gradients in oxygenation, pH, cytokine exposure, 52 immune infiltration and stromal architecture—can generate localized transcriptional patterns that cluster computationally but are unrelated to lineage identity. Taken together, these well-established mechanisms readily explain the observed data without invoking a novel form of MAPK-driven epithelial plasticity. They are fully compatible with decades of research on colorectal cancer biology, therapeutic adaptation and tumor ecology, and thus represent far more plausible interpretations than the mechanistic model proposed in the study. 10.9. The Consequences of Misinterpreting Data for Cancer Biology and Therapeutic Development Misinterpreting transient or artifactual transcriptional variation as lineage plasticity has profound consequences for cancer research and therapeutic strategy. If lineage identity transitions are incorrectly assumed to underlie resistance, therapeutic development may shift toward targeting pathways that do not drive resistance in patients. Such misdirection wastes resources, misguides clinical trial design and diverts attention from genuine mechanisms such as genetic evolution, metabolic adaptation and microenvironmental remodeling. Misinterpretation also risks undermining the credibility of high-dimensional data methodologies. When single-cell sequencing, trajectory inference or proteomics are used without rigorous validation, they can produce misleading narratives that distort mechanistic understanding. It is crucial for the cancer biology community to maintain high analytic standards to avoid conflating computational structure with biological truth. Finally, mechanistic inaccuracies undermine the potential of precision oncology. Therapeutic decisions based on inaccurate models may lead to ineffective interventions that harm patients or reduce the likelihood of clinical benefit. Grounding mechanistic claims in reproducible, biologically coherent evidence is essential for translating basic science into clinical impact. 10.10. Integrative Conclusion: A Mechanistic Narrative Unsupported by the Full Weight of Evidence When viewing the entirety of the evidence, it becomes clear that the study’s mechanistic model cannot be upheld. Across experimental, computational, conceptual and clinical dimensions, the evidence does not converge on the conclusion that MAPK drives epithelial plasticity in colorectal cancer. Instead, the data more plausibly reflect stress responses, technical artifacts, clonal selection and microenvironment-driven heterogeneity. 53 The model lacks support at multiple mechanistic levels: no transcription factor network reprogramming, no chromatin-level remodeling, no lineage-tracing evidence, no functional stability of proposed states, no integration of ecological context and no validation in patient samples. Without fulfilling these criteria, the concept of MAPK-driven plasticity remains an interpretive construct rather than an established biological mechanism. The integrated assessment shows that the study’s conclusions derive from methodological weaknesses, computational misinterpretation and conceptual overreach. A mechanistic claim of this magnitude requires cross-disciplinary evidence aligning across lineage biology, signaling dynamics, epigenetics, functional assays and clinical validation. The study does not provide such evidence, leaving its central claim unsupported. 11. Conclusion 11.1. Overview: Reaching a Final Appraisal of the Study’s Conceptual and Empirical Framework After a comprehensive examination of the study by White and colleagues, it becomes evident that the central claim—that MAPK-driven epithelial cell plasticity drives colorectal cancer therapeutic resistance—is not supported by the full weight of the presented evidence. The magnitude of this mechanistic proposition demands a level of experimental rigor, analytical robustness and biological plausibility that the study does not achieve. Across all domains examined in this critique— conceptual grounding, methodological execution, computational interpretation, figure analysis, mechanistic plausibility and reproducibility—the study systematically falls short. The conclusion derived from this integrative evaluation is not merely that the evidence is insufficient, but that the proposed mechanism stands in conflict with established principles of colorectal cancer biology and the observed behavior of tumors in both experimental models and clinical settings. The following subsections synthesize the major themes that converge upon this conclusion, contextualize their significance for the broader field, and offer insights into how future research could address the shortcomings that undermine the credibility of this study. 11.2. The Core Mechanistic Claim Remains Unsupported by Experimental Evidence At the heart of the study lies a mechanistic claim that epithelial identity in colorectal cancer is dynamically reshaped by MAPK pathway modulation and that these identity transitions confer therapeutic resistance. The evaluation presented across prior sections demonstrates unequivocally that this claim is not substantiated by 54 the evidence offered. The study relies heavily on transcriptional clustering, pseudotime trajectories and qualitative imaging to assert that identity transitions occur, yet fails to demonstrate persistent, lineage-defining alterations at the protein, chromatin or functional levels. A true identity transition requires durable changes in gene regulatory networks, lack of reversion after removal of external stimulus, functional differentiation shifts and chromatin remodeling. None of these are demonstrated. Instead, the data suggest transient, stress-induced transcriptional signatures that arise in response to MAPK inhibition or cellular perturbation. These signatures, interpreted by the authors as evidence of plasticity, lack the stability, reproducibility or mechanistic underpinnings required to establish a bona fide lineage transformation. The core mechanistic claim remains speculative rather than empirically validated. 11.3. Methodological and Analytical Weaknesses Undermine the Study’s Major Conclusions A recurring theme across this critique is that methodological weaknesses and analytical misinterpretations compromise the study’s major findings. The single-cell RNA sequencing datasets lack adequate quality control, replicates, normalization transparency and cross-validation. The clustering results are unstable across biological replicates, and trajectory inference is applied without temporal anchoring or lineage-tracing confirmation. Imaging experiments rely on qualitative assessments and lack statistical rigor. Proteomic analyses are underpowered, insufficiently annotated and not validated through independent biochemical assays. Genetic perturbations are inadequately controlled for off-target effects and lack thorough validation at the protein level. These methodological deficiencies are not isolated; they collectively undermine the validity of the study’s conceptual conclusions. Because each line of evidence depends upon results that are themselves weakened by analytical fragility, the integrated mechanistic framework collapses under scrutiny. Robust mechanistic studies require convergence, where different experimental approaches independently support the same conclusion. Here, however, each modality complicates rather than confirms the authors’ hypothesis. 11.4. Biological Implausibility Further Weakens the Credibility of the Proposed Mechanism Even if methodological and analytical flaws were resolved, the proposed mechanism would remain biologically implausible. Colorectal cancer is characterized by stable epithelial identity rooted in deeply conserved lineage programs governed by chromatin architecture, transcription factor hierarchies and microenvironmental 55 constraints. The MAPK pathway, although critical for proliferation and survival, has no established role in orchestrating lineage transitions in intestinal epithelium. Moreover, clinical patterns of resistance overwhelmingly point to genetic evolution and pathway reactivation rather than phenotypic reprogramming. True identity transitions in cancer require coordinated epigenetic remodeling, activation or suppression of master transcription factors and functional changes in cell fate. None of these are demonstrated in the study. The absence of chromatinlevel evidence is particularly damaging: without showing changes in enhancer accessibility, transcription factor occupancy or epigenetic landscapes, no claim of lineage transformation can be accepted. In light of existing biological knowledge, the study’s central mechanism conflicts with established paradigms, making it far less likely to reflect true biology. 11.5. Alternative Mechanisms Offer More Plausible Explanations for the Observed Data Several alternative explanations more coherently and plausibly explain the observations presented, without requiring a new mechanistic paradigm. Stress responses induced by drug treatment, organoid dissociation, metabolic perturbation or microenvironmental factors can account for the observed transcriptional shifts. High-dimensional data artifacts, including batch effects, cell-cycle effects and dissociation-induced gene expression, can produce computationally defined “states” that do not represent biological identity. Clonal selection, the hallmark mechanism of therapeutic resistance in colorectal cancer, aligns with both the observed data and the extensive clinical literature. Because these explanations fit the data more elegantly and with far fewer assumptions, the principle of parsimony strongly argues against adopting the MAPK-driven plasticity model. 11.6. The Study’s Claims Lack Translational Relevance Without Patient-Derived Validation A crucial deficiency in the study is its failure to demonstrate that proposed plasticity states exist in human tumors or are enriched during clinical relapse. No spatial transcriptomic analysis, single-cell sequencing from patient biopsies or chromatinlevel assessment from human samples is provided. Without demonstrating translational relevance, the study’s claims remain confined to artificial model systems such as organoids and murine tumors, which cannot replicate the microenvironmental and ecological complexities of human colorectal cancer. Clinical relapse specimens overwhelmingly retain epithelial identity, contradicting the idea that plasticity states emerge during resistance. The absence of patient validation significantly limits the impact and credibility of the study’s conclusions. 56 11.7. Reproducibility and Transparency Failures Limit the Study’s Scientific Value Reproducibility is a central pillar of modern biological research, especially for highimpact mechanistic claims. Yet the study falls short on nearly every aspect of reproducibility and transparency. Raw data files are absent for key experiments. Computational pipelines are inadequately documented, preventing independent verification. Imaging data lack raw stacks and standardized quantification methods. Proteomic datasets are insufficiently annotated. Replicate-level reporting is inconsistent and often missing. Essential methodological details—such as dissociation protocols, drug dosing regimens and CRISPR validation—are incomplete. These deficiencies restrict the scientific utility of the study. Without transparency, results cannot be replicated or critically evaluated, and the mechanistic claims remain unchecked. 11.8. Implications for the Field: The Need for Caution in Interpreting High-Dimensional Data This critique highlights the broader implications of relying heavily on highdimensional datasets without rigorous biological validation. Single-cell sequencing, trajectory inference and proteomics offer powerful tools, but they also introduce interpretive risk. Computationally derived clusters and trajectories can misrepresent continuous variation as discrete states or progressions. If such outputs are interpreted in isolation from chromatin-level data, lineage-tracing evidence or functional assays, misleading narratives can emerge. This study illustrates the dangers of equating computational structure with biological truth. The field must exercise heightened caution, ensuring that high-dimensional analyses are anchored in biologically validated frameworks and that mechanistic claims are supported by multiple orthogonal lines of evidence. 11.9. A Framework for Future Research on MAPK Signaling and Resistance in Colorectal Cancer Although the mechanistic model proposed in the study is not supported, the broader objective of elucidating how MAPK pathway dynamics influence therapeutic resistance in colorectal cancer remains an important and timely direction for investigation. Future research must address the methodological and conceptual deficiencies identified in this critique in order to produce robust, mechanistically credible insights. A central requirement is the identification of clear intermediaries that mechanistically connect MAPK signaling to chromatin remodeling, transcription factor regulation or differentiation programs, thereby establishing a causal chain rather than relying on inferred associations from transcriptomic variation. Meaningful progress will also depend on integrating spatial 57 transcriptomics, single-cell multiomic profiling and true lineage-tracing frameworks that can anchor transcriptional heterogeneity within biological context, allowing researchers to distinguish adaptive stress responses from stable identity states. Equally essential is the rigorous control of technical artifacts through standardized dissociation protocols, robust batch correction, replicate-level statistical testing and full transparency through the release of raw datasets. Because claims of identity change necessarily implicate chromatin-level reorganization, comprehensive analyses of chromatin accessibility, epigenetic modification and enhancer structure must be incorporated to determine whether any putative identity shifts have durable mechanistic grounding. Finally, translational relevance must be demonstrated through validation in patient-derived samples, including relapse material and longitudinal biopsies that reflect the true ecological and evolutionary constraints of human colorectal cancer. Only by meeting these stringent criteria can the field move toward mechanistically sound models of therapeutic resistance and avoid the persistent risk of misinterpreting high-dimensional data artifacts as evidence of novel biological states. 11.10. Final Synthesis: A Mechanistic Narrative Without Substantiation The final evaluation of the study’s central claim is clear. The hypothesis of MAPKdriven epithelial plasticity as a mechanism of therapeutic resistance is neither empirically demonstrated nor biologically plausible. Instead, the study’s data, when critically evaluated, point toward more conventional explanations rooted in stress response, clonal selection, technical noise and established resistance pathways. The absence of chromatin-level evidence, lack of transcription factor validation, failure to demonstrate functional stability of proposed states and disconnect from clinical patterns collectively invalidate the mechanistic narrative offered. The study does not provide the necessary evidence to justify the adoption of a new paradigm in colorectal cancer biology. Until robust, reproducible and biologically grounded data emerge, the established frameworks of resistance—rather than speculative plasticity—will continue to define our understanding of colorectal cancer therapeutics.