RNA-seq-based copy number inference for retrospective genomic characterization of lung cancer transcriptomes.
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Journal Article↗
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Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.
Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (ΔAUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.
Humans↗
Exploring the Role of DNA Methylation in the Epigenetic Landscape of Cancer.
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Cancer epigenetic↗
Precision Oncology in Hepatopancreatobiliary Cancer Surgery.
Advances in technology have allowed for the characterization of tumors at the genomic, transcriptomic, and proteomic levels. There are well-established targets for biliary tract cancers, with exciting new targets emerging in pancreatic ductal adenocarcinoma and potential targets in hepatocellular carcinoma. Taken together, these data suggest an important role for molecular profiling for personalizing cancer therapy in advanced disease and need for design of novel neoadjuvant studies to leverage these novel therapeutics perioperatively in the surgical patient.
Humans↗
PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.
BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.
Humans↗
In vitro evaluation of sacituzumab govitecan in non-small cell lung cancer with actionable genomic alterations.
PURPOSE: The TROP2-directed antibody-drug conjugate sacituzumab govitecan (SG) has shown substantial therapeutic benefit in several malignancies; however, preclinical evidence supporting its activity in non-small cell lung cancer (NSCLC) is rare. MATERIALS AND METHODS: We evaluated 16 NSCLC cell lines harboring actionable genomic alterations for TROP2 expression and treated them with SG or its unconjugated payload, SN-38, for 3 days to determine cytotoxic effects. Apoptosis and DNA damage signaling were assessed using flow cytometry and western blot. SG internalization and lysosomal trafficking were visualized by confocal microscopy. RESULTS: SG had greater cytotoxic potency than SN-38, across all NSCLC cell lines, independent of genomic subtype or TROP2 expression level. Cell lines that were sensitive to SN-38 showed enhanced vulnerability to SG (P < 0.0001). Higher SLFN11 expression, a recognized determinant of SN-38 responsiveness, correlated with lower SG IC50 values. Both SG and SN-38 triggered apoptotic and DNA damage responses within 6-48 h, with SG inducing stronger activation of these pathways than SN-38. SG was efficiently taken up in CUTO17 and SNU-3173 adenocarcinoma cells, with more than 60% of the conjugate internalized within 3 h and subsequently localized to lysosomes. CONCLUSION: Our study provides in vitro evidence supporting the potential activity of SG in NSCLC with actionable genomic alterations. The efficacy of SG closely paralleled intrinsic sensitivity to the SN-38 payload, suggesting that DNA-damage responses, rather than oncogenic drivers, predominantly contribute to SG activity.
Actionable genomic alterations↗
Distinct functions of mammalian RAD51 paralogs in genome maintenance.
RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) are evolutionarily conserved essential proteins for cell survival and genome maintenance. RAD51 paralogs were originally identified to play a role in homologous recombination-mediated repair of DNA double-strand breaks (DSBs). However, investigations over the last decade have uncovered new roles of RAD51 paralogs beyond DSB repair in replication stress responses, including replication fork progression, fork stability, and its restart. Recent structural studies have not only uncovered the molecular architecture of previously known RAD51 paralog complexes but also identified novel paralog complex assemblies, providing mechanistic insights into their various genome-maintenance functions. Additionally, a role for RAD51 paralogs in resolving R-loops has been identified, and studies with cancer-associated variants suggest that RAD51 paralogs are potential determinants of cancer susceptibility and therapeutic responses. In the present review, we highlight the recently deciphered structures and novel functions of RAD51 paralog complexes and discuss the clinical and therapeutic implications.
Rad51 Recombinase↗
Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.
Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.
cancer cell lines↗
Matched targeted therapy use after broad genomic profiling in advanced Non-Small cell lung cancer.
INTRODUCTION: While broad genomic profiling is increasingly used in advanced NSCLC (aNSCLC), the impact of test results on subsequent guideline-concordant targeted therapy selection remains incompletely understood. METHODS: Using a merged dataset of two large, nationwide, patient-level databases, we identified patients who were diagnosed with aNSCLC 2017-2023, had potentially actionable genomic profiling findings, and initiated systemic therapy. Patients were categorized into actionability subgroups based on contemporaneous regulatory approvals and NCCN guideline recommendations. Within each subgroup, we assessed receipt of guideline-concordant targeted therapy within 24 months, including potential underuse (non-receipt of recommended treatment) and overuse (receipt of non-recommended treatment). RESULTS: Among 6620 patients (67.4% ≥65 years, 54.6% female, 68.9% White), guideline-concordant targeted therapy use varied substantially by actionability category: 2313 (89.6%) of 2582 patients with available 1st-line on-label options received them (10.4% underuse), while 212 (67.3%) of 315 patients with available later-line on-label options received them after 1st-line (32.7% underuse). Among 441 patients with available guideline-concordant off-label options, only 122 (27.7%) received them (72.3% underuse). Conversely, 238 (8.6%) of 3282 patients received matched but guideline-discordant off-label options, representing overuse of ineffective or unestablished therapies. Smoking history, squamous histology, and high PD-L1 expression were associated with lower targeted therapy receipt. CONCLUSIONS: In this cohort study of aNSCLC care, the guideline concordance of targeted therapy use varied by clinical actionability of molecular testing results. Underuse was more common in patients with later-line and off-label targeted therapy options. Patients with classical smoking-related risk profiles were substantially less likely to receive targeted therapy even when actionable alterations were identified.
Journal Article↗
Intramuscular patient-derived xenografts achieve high engraftment rates in gastric cancer: implications for pharmacodynamic testing and genomic biomarker discovery.
BACKGROUND: Gastric cancer (GC) exhibits marked inter-patient heterogeneity, limiting empirical chemotherapy efficacy. Patient-derived xenograft (PDX) models preserve the molecular features of parental tumors and can serve as pharmacodynamic surrogates, but conventional subcutaneous PDX suffers from low engraftment rates. This study evaluated an optimized intramuscular PDX platform for individualized drug testing in GC and applied whole exome sequencing (WES) for biomarker identification (Clinical trial registry: ChiCTR-OOC-17012731). MATERIALS AND METHODS: Ninety-eight treatment-naive GC patients were enrolled between April 2018 and December 2020. Fresh tumor tissues were engrafted into NCG mice by intramuscular transplantation. Drug efficacy was evaluated using tumor cell necrosis rate and Ki-67 expression. WES was performed on 32 engrafted tumorgrafts to characterize driver mutations in fast- and slow-growing subgroups. RESULTS: An engraftment rate of 71.7% (43/60) was achieved, substantially exceeding rates reported in prior studies. Clinical characteristics were independent of engraftment success and outgrowth time (all p > 0.05). Fast- and slow-growing tumorgrafts diverged in frequently altered genes: KMT2C, APOB, CDK12 and MSH2 predominated in fast-growing grafts, whereas TP53, CHD3 and TET2 were enriched in slow-growing grafts. Slow-growing tumorgrafts correlated with longer progression-free survival (p = 0.02). PDX-guided treatment was associated with improved prognosis. CONCLUSIONS: Intramuscular transplantation into NCG mice yields high engraftment rates for GC PDX. PDX-guided chemotherapy selection is associated with favorable outcomes. Driver mutation divergence between fast- and slow-growing tumorgrafts provides candidate prognostic biomarkers.
Animals↗
3D epigenomic remodelling mediated by Foxa1 drives gemcitabine resistance in pancreatic cancer.
Gemcitabine remains a cornerstone treatment for pancreatic ductal adenocarcinoma (PDAC), yet the emergence of resistance constitutes a major clinical challenge with poorly understood epigenomic mechanisms. Here, we identified the pioneer transcription factor Foxa1 as a master regulator of gemcitabine resistance through multi-omics analysis. Mechanistically, Foxa1 drives widespread super-enhancer (SE) reprogramming and 3D genome remodelling in resistant cells, which coordinately activates the expression of key resistance genes, notably Rrm1 and Cdadc1. This is accompanied by increased chromatin accessibility, elevated H3K27ac enrichment at SEs, and enhanced Foxa1 binding at regulatory elements. Moreover, post-translational stabilization of Foxa1 via USP7-mediated deubiquitination sustains this epigenomic program. Genetic ablation of Foxa1 or specific SE regions near Rrm1 resensitizes resistant cells to gemcitabine. Building upon this mechanism, we demonstrate that bromodomain and extraterminal (BET) inhibitors, which disrupt SE function, potently reverse resistance. Notably, the clinical-stage BET inhibitor AZD5153, in combination with gemcitabine, achieves robust tumor suppression and overcomes resistance in cell-derived xenograft (CDX) models by dismantling the Foxa1-mediated resistant transcriptome and reinvigorating drug sensitivity. Our findings establish Foxa1-orchestrated enhancer reprogramming as a fundamental mechanism of gemcitabine resistance and unveil a promising epigenetic therapy to restore treatment efficacy in PDAC.
Hepatocyte Nuclear Factor 3-alpha↗
Identification of CD55 as a downstream factor of EP4 receptor signaling in colorectal cancer cells.
Prostaglandin E2 (PGE2) signaling through the E-type prostanoid 4 (EP4) receptor has been implicated in the pathophysiology of colorectal cancer (CRC). We herein identified decay-accelerating factor, also known as CD55, as a novel CRC-associated downstream factor of the EP4 receptor. The integration of transcriptomic profiling of PGE2-stimulated HCA-7 human colon cancer cells with analyses of cancer genomic databases predicted CD55 as a potential EP4 receptor-regulated target. Inhibitor-based experiments showed the induction of CD55 after a PGE2 stimulation required the EP4 receptor and Gi protein in HCA-7 cells, whereas protein kinase A signaling was dispensable. In combination with a toxicogenomic database analysis, p38 mitogen-activated protein kinase (MAPK) was identified as the predominant effector connecting the EP4 receptor to CD55 upregulation. A single-cell RNA-seq re-analysis of human CRC tissues revealed CD55 upregulation and p38 MAPK-related gene set enrichment in epithelial cells expressing the EP4 receptor, suggesting that this induction mechanism may operate in a subset of epithelial cells in clinical specimens. Collectively, these results delineate a PGE2/EP4 receptor/Gi protein/p38 MAPK signaling axis that induces CD55 expression in HCA-7 cells and epithelial tumor cells, provide new mechanistic clues for understanding the regulation of complement regulatory molecule CD55 expression by prostaglandin signaling.
Humans↗
A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.
INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.
Humans↗
Antibody-drug conjugates against multidrug-resistant cancers: Biomarker-guided patient selection, payload engineering, linker chemistry, and bystander effects.
Antibody-drug conjugates (ADCs) are one of the most significant advancements in modern cancer therapeutics. Combining the target selectivity of monoclonal antibodies with the cytotoxic potential of payloads, ADCs effectively kill cancer cells and offer hope to patients with even refractory cancer types. Beyond simply increasing the number of therapeutic options available for cancer patients, ADCs have become a powerful frontline agent in overcoming multidrug resistance (MDR). As one of the most challenging obstacles to effective cancer care, MDR is mediated by ATP-binding cassette (ABC) transporter-mediated drug efflux, target-based mutations, and dysregulated apoptosis. The clinical success of ADCs specifically engineered to overcome MDR, including in heterogeneous tumors and cancer cells that exhibit bypass signaling, is well established. This is especially evident with trastuzumab deruxtecan (T-DXd) in HER2-low, HER2-positive, and HER2-mutant cancers; sacituzumab govitecan (SG) in TROP2-expressing triple-negative breast cancer (TNBC) and urothelial carcinoma; and enfortumab vedotin in Nectin-4-positive bladder cancer. By overcoming MDR, ADCs have enabled more effective treatment algorithms across multiple malignancies. Most importantly, the clinical application of ADCs has become inextricably linked to cancer genomics. HER2 testing has evolved from a two-tiered system to a continuous spectrum including HER2-ultralow, HER2-low, HER2-positive, and ERBB2-mutant categories. Each of these categories exhibits different eligibility guidelines for ADC patient selection. As cancer cells continue to evolve and develop resistance to even ADCs through mutations and variants, researchers and clinicians have used pharmacogenomics to predict ADC response and resistance. To define the genomic architecture of ADC-resistant tumor subpopulations, single-cell transcriptomic studies and liquid biopsy approaches are being used to enable real-time examination of the tumor genome during ADC therapy, thereby optimizing treatment and circumventing resistance driven by emerging mutations and variants. This review provides a comprehensive analysis of the molecular structure of ADCs, the pharmacological principles underlying their potent cytotoxic activity against MDR cancer cells, the genomic and transcriptomic biomarkers that guide ADC patient selection, and the emerging resistance mechanisms that will shape the next generation of promising ADC development.
Humans↗
Integrative quantum and systems biology of cancer: From molecular fluctuations to ecological outcomes.
This review treats cancer as a multiscale adaptive system, asks what the framework must predict to be worth adopting, and separates at each scale what the evidence establishes from what is proposed. It is an expert narrative synthesis, not a systematic review, and states the limits of that design. Proton transfer and tautomeric shifts contribute to spontaneous mispairing but do not license claims of directed or non-random mutation: replication timing, three-dimensional chromatin organization, sequence context and known mutagenic processes explain most mutational heterogeneity, leaving any quantum contribution as a residual against that baseline. The Waddington quasi-potential is bounded: outside detailed balance the dynamics are not gradient-derivable and require a probability-flux term. Hysteresis, rate-limited bimodality and return to state after perturbation distinguish an attractor from a transcriptomic cluster. Single-cell karyotype and live-imaging evidence supports whole-genome doubling as an unstable intermediate of heterogeneous origin and context-dependent consequence, not a uniform adaptive strategy. Systems and synthetic biology, virtual cells and digital twins are assessed against benchmarks, not promise. Tissue-scale ecology is reported with the spatial measurements now quantifying it, including evidence that stromal niche construction is not uniformly tumor-supporting. RNA modification is a layer in its own right, showing that the interpretation of a regulatory signal, not its magnitude, is biologically decisive. A dedicated section states the framework's commitments, the observable and evidence at each scale, and what would falsify them, asking what this adds to somatic mutation theory with clonal evolution and plasticity.
Neoplasms↗
Conserved host-exclusive oligonucleotide motifs enriched in pathogenic genes of human oncogenic viruses.
Comparative viral genomics can reveal sequence-level constraints influencing virus-host interactions. Relative minimal absent words (rMAWs) are short oligonucleotide motifs present in viral genomes but completely absent from the host, potentially reflecting selective pressures related to host adaptation and immune evasion. Using the EAGLE algorithm and the GRCh38 human reference genome, we systematically screened for prevalent rMAWs (prMAWs) across six major human oncogenic viruses: Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), human papillomavirus (HPV), human T-cell leukemia virus type 1 (HTLV-1), and human herpesvirus 8/Kaposi's sarcoma-associated herpesvirus (HHV-8/KSHV). highly conserved 11- and 12-bp prMAWs were identified in EBV, HBV, HTLV-1, and HHV-8/KSHV, with sequence prevalences ranging from 91.5% to 97.9%. Conversely, no short prMAWs were detected in HCV or HPV, likely reflecting differences in genome architecture, mutation rates, and long-term host adaptation to the human host. Importantly, the identified host-exclusive motifs exhibited non-random genomic distribution and were preferentially embedded within viral genes central to replication, persistence, immune modulation, and oncogenesis, including EBNA-1 (EBV), HBx (HBV), Tax-associated regions (HTLV-1), and lytic replication genes of HHV-8/KSHV. Notably, all detected prMAWs were enriched in GC nucleotides and exhibited marked CpG over-representation, suggesting sequence constraints associated with epigenetic regulation and viral persistence. Collectively, these highly conserved, host-exclusive signatures offer promising, candidates for sequence-directed approaches in the diagnosis, monitoring, and investigation of virus-associated cancers.
Humans↗
Targeted sequencing reveals a distinct genetic alteration landscape in oral multiple primary squamous cell carcinomas.
OBJECTIVE: Oral multiple primary cancers (MPCs) are associated with poor clinical outcomes, yet their genomic characteristics remain insufficiently understood. DESIGN: Fifty-four formalin-fixed paraffin-embedded (FFPE) tumor samples from 30 patients with oral MPCs were analyzed using high-depth targeted sequencing of a customized 14-gene panel derived from prior whole-exome sequencing data. Detected alterations were analyzed after removal of synonymous mutations. RESULTS: Non-silent genomic alterations were identified in 59.3% (32/54) of samples, involving 19 patients. A total of 70 variant loci across 13 genes were detected. AKAP13 was the most frequently mutated gene at both the sample (22.2%, 12/54), with recurrent mutations observed across multiple patients. In contrast, TP53 mutations occurred at a substantially lower frequency (11.1%, 6/54). Marked inter- and intra-patient mutational heterogeneity was observed. CONCLUSIONS: FFPE-based targeted sequencing enabled an initial characterization of genomic alterations in oral MPCs. Recurrent alterations in AKAP13, GLI2, JMJD1C, and DNAH8, together with the relatively low frequency of TP53 alterations, identify candidate genomic features for further investigation and provide a basis for future studies of the molecular basis of oral MPCs.
Humans↗
A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.
BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers. While the aberrant expression of circadian rhythm-related genes has been implicated in cancer pathogenesis, its comprehensive role in CRC progression and predicted therapeutic vulnerabilities remains inadequately characterized. METHODS: Bulk and single-cell RNA-sequencing data were integrated from multiple CRC cohorts. A circadian rhythm signature (CRS) was developed through machine learning algorithms and validated for prognostic value. Comprehensive analyses of tumor microenvironment, genomic alterations, and drug sensitivity were performed. Furthermore, the biological function of the core gene, BHLHE40, was validated in CRC cell lines through CCK-8, EdU, and wound healing assays. RESULTS: Single-cell analysis demonstrated an elevated expression signature of circadian rhythm-related genes in dendritic cells. The optimized CRS, comprising 14 circadian rhythm-related genes, successfully categorized patients into high- and low-risk groups. Patients with a high CRS showed markedly poorer overall survival and computationally inferred immunosuppressive features, including reduced CD8+ T cell infiltration and increased M2 macrophage polarization. Genomic analysis revealed enhanced mutation burden in TP53 and alterations in RTK-RAS/WNT pathways. Notably, in vitro assays confirmed that BHLHE40 is significantly overexpressed in CRC cells. Knockdown of BHLHE40 markedly inhibited tumor cell proliferation and migration. Drug sensitivity profiling identified bexarotene and SMER-3 as potential therapeutic options for high-CRS patients. A nomogram integrating CRS with clinical parameters demonstrated superior predictive accuracy for 1-, 3-, and 5-year survival. CONCLUSIONS: The CRS represents a promising prognostic biomarker that reflects tumor immune status and genomic features, providing valuable insights for personalized treatment strategies in CRC.
Circadian rhythm↗