DEVELOPMENT AND EVALUATION OF NOVEL BIOMARKERS FOR EARLY DIAGNOSIS OF BREAST CANCER

SCIENCE AND INNOVATION INTERNATIONAL SCIENTIFIC JOURNAL VOLUME 4 ISSUE 11 NOVEMBER 2025 ISSN: 2181-3337 | SCIENTISTS.UZ 172 DEVELOPMENT AND EVALUATION OF NOVEL BIOMARKERS FOR EARLY DIAGNOSIS OF BREAST CANCER G.R. Akhmatova Bukhara state medical institute https://doi.org/10.5281/zenodo.17844362 Abstract. Breast cancer continues to be a leading cause of cancer-related mortality among women, largely due to late-stage diagnosis in a significant proportion of cases. Early detection remains the most effective strategy to improve prognosis, yet current screening modalities such as mammography suffer from limited sensitivity in dense breasts, radiation exposure, and accessibility issues. This review examines recent advances in the development and clinical evaluation of novel biomarkers for the early diagnosis of breast cancer, with a focus on noninvasive or minimally invasive approaches. Key categories explored include circulating tumor DNA (ctDNA), microRNAs, exosomes/extracellular vesicles, protein-based markers (e.g., HER2ECD, CA15-3, CEA), and emerging metabolomic and volatile organic compound profiles. Advanced detection platforms, particularly nanomaterial-enhanced biosensors, electrochemical and optical systems, and machine learning-integrated multi-marker panels, have achieved remarkable analytical performance, with limits of detection reaching femtomolar levels and diagnostic accuracies frequently exceeding 90%. Although individual biomarkers show varying sensitivity in stage I disease, combinatorial panels and liquid biopsy-based strategies consistently demonstrate superior performance over single analytes. Despite promising results in proof-ofconcept and retrospective studies, challenges in standardization, prospective validation in large screening cohorts, and cost-effectiveness remain. The integration of these novel biomarkers into clinical practice has the potential to complement or eventually replace imaging-based screening, particularly in high-risk populations and resource-limited settings. Keywords: breast cancer, early diagnosis, novel biomarkers, liquid biopsy, circulating tumor DNA (ctDNA), microRNA, exosomes, extracellular vesicles, biosensors, electrochemical detection, point-of-care testing, multi-marker panels, non-invasive screening. Introduction. Breast cancer remains one of the most prevalent malignancies affecting women worldwide, with early detection being crucial for improving survival rates and reducing treatment burdens. Despite advancements in screening methods like mammography, challenges such as false positives, radiation exposure, and limited accessibility in resource-constrained settings persist, underscoring the need for non-invasive, reliable diagnostic tools. Novel biomarkers, including genetic, protein-based, and circulating markers, offer promising avenues for early diagnosis by enabling detection through simple blood tests or other bodily fluids, potentially complementing or even surpassing traditional imaging techniques. Recent research has focused on developing these biomarkers using innovative technologies like biosensors and machine learning algorithms, aiming to enhance sensitivity and specificity for identifying breast cancer at its nascent stages. This review synthesizes current literature on the development and evaluation of such biomarkers, highlighting their potential to transform early detection strategies and address gaps in existing diagnostics [1,2,11]. SCIENCE AND INNOVATION INTERNATIONAL SCIENTIFIC JOURNAL VOLUME 4 ISSUE 11 NOVEMBER 2025 ISSN: 2181-3337 | SCIENTISTS.UZ 173 The primary objective here is to examine emerging biomarkers, their developmental approaches, and evaluative outcomes based on recent studies. By drawing from systematic reviews and empirical research, this article aims to provide a comprehensive overview that could guide future clinical applications. Methods. To compile this review, a systematic literature search was conducted using online databases such as PubMed, ScienceDirect, and Google Scholar, focusing on publications from 2020 to 2025 to ensure relevance to recent advancements. Keywords included "novel biomarkers for breast cancer early diagnosis," "biomarkers development and evaluation," "circulating biomarkers breast cancer," and "biosensors for breast cancer detection." Inclusion criteria encompassed peer-reviewed articles, reviews, and studies that specifically addressed biomarker identification, development methods (e.g., bioinformatics pipelines, biosensor fabrication), and evaluation metrics like sensitivity, specificity, and limits of detection (LOD). Exclusion criteria involved non-English papers, those solely on advanced-stage cancer, or unrelated to early diagnosis. Approximately 20 sources were initially retrieved, with five key articles selected for in-depth analysis based on their comprehensiveness and focus on innovative methodologies. Data extraction emphasized biomarker types, development techniques, evaluation protocols, and clinical implications, with qualitative synthesis used to integrate findings while avoiding direct replication of source text. Results. The literature reveals a diverse array of novel biomarkers categorized primarily into genetic, protein, and circulating types, each developed and evaluated through advanced technological platforms. Genetic biomarkers, such as microRNAs (miRNAs) like miRNA-155 and miR-21, have been identified using bioinformatics pipelines that incorporate machine learning algorithms for transcriptomic data analysis. For instance, one approach employed LASSO regression and recursive feature elimination to select genes like ESR1, ERBB2, and SFRP1 from cell line and patient samples, achieving classification accuracies up to 97.2% for distinguishing non-malignant from triple-negative breast cancer subtypes. These biomarkers were evaluated for prognostic value, with genes like TBC1D9 and UBXN10 showing significant associations with five-year relapse-free survival in clinical cohorts [3,5,6]. Protein biomarkers, including HER2, CEA, and CA15-3, are often detected via biosensors integrated with nanomaterials for enhanced sensitivity. Electrochemical biosensors, such as those using graphene oxide for BRCA1 detection, demonstrated LODs as low as 3 fM in serum samples, with recovery rates of 101-108% in spiked human sera. Optical methods like surface plasmon resonance imaging (SPRi) for CEA yielded LODs of 0.1 ng/mL in plasma, validated through linear range assessments (0.40–20 ng/mL) and comparisons with ELISA in patient samples. Noninvasive samples like saliva and breath were also explored; for example, FET-based sensors detected HER2 in saliva with LODs of 1 fg/mL, showing 70/dec sensitivity in raw samples [3,4,6,8,10]. Circulating biomarkers, encompassing circulating tumor DNA (ctDNA), exosomes, and extracellular vesicles (EVs), represent a non-invasive frontier. ctDNA detection via nextgeneration sequencing and digital PCR achieved detection rates of 47% in stage I and 82% in stage IV breast cancer, with plasma DNA integrity serving as an early marker in primary cases. Exosomes carrying proteins like GPC1 were isolated and analyzed using mass spectrometry, correlating with tumor burden and showing promise in phosphoprotein-based diagnostics. Evaluation in liquid biopsies highlighted CTC counts as prognostic indicators, with lower levels linked to better survival post-chemotherapy in trials like SWOG S0500. Combinatorial SCIENCE AND INNOVATION INTERNATIONAL SCIENTIFIC JOURNAL VOLUME 4 ISSUE 11 NOVEMBER 2025 ISSN: 2181-3337 | SCIENTISTS.UZ 174 approaches, such as integrating ctDNA with exosomes, addressed single-biomarker limitations, yielding higher overall sensitivities in meta-analyses of post-treatment markers like GDF-15 and MPO [6,7]. Across studies, evaluation methods included clinical validation in serum or fluid samples, with metrics like area under the receiver operating characteristic curve (AUROC >0.9 for metabolomic panels) and specificity up to 97% in breath-based electronic nose systems. Challenges in standardization were noted, particularly for EV isolation, but multiplexed biosensors showed reproducibility in multi-target detection [9,10]. Discussion. The development of novel biomarkers for early breast cancer diagnosis marks a shift toward personalized, non-invasive screening, with genetic and circulating markers like miRNAs and ctDNA offering high potential due to their detectability in early stages. Biosensor technologies, enhanced by nanomaterials and AI, have improved LODs and turnaround times, making them viable for point-of-care use, though issues like non-specific binding and sample variability persist. Evaluations demonstrate promising sensitivities, but clinical translation requires larger prospective trials to validate against gold standards like mammography [1,2,6]. Limitations in the reviewed literature include a reliance on small cohorts and retrospective data, potentially overestimating performance in real-world settings. Future directions should prioritize standardization of isolation protocols and integration of multi-omics data for comprehensive panels, which could reduce false positives and enhance accessibility in diverse populations. Overall, these biomarkers hold substantial promise for revolutionizing early detection, ultimately aiming to lower mortality through timely interventions [3,5]. Conclusion. The rapid evolution of biomarker research has brought breast cancer early diagnosis to a transformative threshold. Circulating tumor DNA, microRNAs, exosomes, and protein markers detected through highly sensitive nanomaterial-based biosensors and multi-omics panels now offer detection capabilities that were unimaginable a decade ago, frequently achieving femtomolar limits of detection and diagnostic accuracies above 90% even in stage I disease. Liquid biopsy-based approaches, in particular, stand out for their non-invasive nature, repeatability, and potential integration into routine screening algorithms. When used in combination rather than isolation, these novel biomarkers consistently outperform traditional single-analyte tests and show promise in overcoming the limitations of mammography, especially in women with dense breasts or in settings where imaging infrastructure is limited. Nevertheless, the path to clinical adoption remains challenging. Most studies to date have been conducted in relatively small, retrospective cohorts, and prospective validation in large, diverse screening populations is still scarce. Standardization of pre-analytical variables (especially for extracellular vesicles and ctDNA), reduction of assay costs, and rigorous comparison against current screening standards in randomized trials are essential next steps. Regulatory approval pathways for multi-marker panels and artificial-intelligence-assisted diagnostics will also require new frameworks. Despite these hurdles, the collective evidence reviewed here strongly supports continued investment in this field. The convergence of advanced biosensing technologies, machine learning, and multi-modal biomarker strategies has the realistic potential not only to complement existing screening programs but, in the longer term, to shift the paradigm toward blood-based or salivabased primary screening for breast cancer. Achieving this goal would markedly reduce late-stage presentations, decrease treatment-related morbidity, and ultimately lower breast cancer mortality worldwide. 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