Search Results (117)

The concept of agnostic biomarkers—molecular modifications that guide therapy irrespective of tumor origin—has gained increasing relevance in oncology, including colorectal cancer (CRC). This review aims to critically evaluate the role of such biomarkers in CRC, highlighting their clinical significance as therapeutic targets and indicators of prognosis. Through a PubMed search using the terms “agnostic treatment AND colorectal cancer,” eight key studies were identified and qualitatively analyzed. We focus on several biomarkers commonly regarded as agnostic across tumor types, including BRAF V600E mutation, receptor tyrosine kinase (RTK) and PI3K fusions, the CpG island methylator phenotype (CIMP), high tumor mutational burden (TMB), and microsatellite instability (MSI). These markers are inspected for their prevalence in CRC, underlying pathophysiological mechanisms of cancer promotion, and predictive or prognostic implications. Moreover, we integrate findings from broader oncologic studies to contextualize the evolving role of agnostic biomarkers beyond organ-specific paradigms. Emerging evidence suggests that leveraging these molecular signatures may inform the use of targeted and immunotherapeutic agents as first-line options in select CRC populations. Collectively, agnostic biomarkers represent an auspicious avenue for personalizing CRC treatment, particularly in advanced-stage disease where traditional treatment options remain limited. Full article

Colorectal cancer (CRC) remains one of the leading causes of cancer-related morbidity and mortality worldwide. Despite significant advances in screening and treatment, the prognosis for advanced-stage disease continues to be poor. One thriving area of research focuses on the use of epigenetic alterations for the diagnosis, prediction of treatment response, and prognosis of CRC. In this study, we evaluated original studies and meta-analyses published within the past five years to identify the most clinically relevant epigenetic biomarkers. DNA methylation-based assays, particularly those targeting SDC2 and SEPT9 in stool and plasma, exhibit superior diagnostic accuracy compared to other epigenetic modalities. Circulating microRNAs (miRNAs), including miR-211, miR-197, and miR-21, as well as specific long non-coding RNAs (lncRNAs) such as SNHG14, LINC01485, and ASB16-AS1, also show promising diagnostic potential. Furthermore, panels combining multiple epigenetic markers, especially those incorporating DNA methylation targets, have demonstrated improved sensitivity and specificity for early-stage CRC detection. In the context of therapeutic prediction, microRNAs such as miR-140, miR-21, and miR-4442 have been associated with chemotherapy resistance and recurrence risk. DNA methylation markers like LINE-1, mSEPT9 and ERCC1 have also shown predictive value, while lncRNAs including MALAT1 and GAS6-AS1 remain less validated. Regarding prognosis, miRNAs appear to be the most promising biomarkers, with miR-675-5p and miR-150 being associated with poor survival, while miR-767-5p and miR-215 predict favorable outcomes. Methylation of NKX6.1, IGFBP3, and LMX1A has been identified as an independent negative prognostic factor, while SFRP2 hypermethylation is linked to better prognosis. Selected lncRNAs, including THOR and LINC01094, have also demonstrated significant prognostic value. Despite these advances, challenges persist, including inconsistent reporting, limited external validation, and a lack of replication by independent research groups. Full article

Liquid biopsy has emerged as a valuable tool for the detection and monitoring of colorectal cancer (CRC), providing minimally invasive insights into tumor biology through circulating biomarkers such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Additional biomarkers, including tumor-educated platelets (TEPs) and exosomal RNAs, offer further potential for early detection and prognostic role, although ongoing clinical validation is still needed. This review summarizes the current evidence on the diagnostic, prognostic, and predictive capabilities of liquid biopsy in both metastatic and non-metastatic CRC. In the non-metastatic setting, liquid biopsy is gaining traction in early detection through screening and in identifying minimal residual disease (MRD), potentially guiding adjuvant treatment and reducing overtreatment. In contrast, liquid biopsy is more established in metastatic CRC for monitoring treatment responses, clonal evolution, and mechanisms of resistance. The integration of ctDNA-guided treatment algorithms into clinical practice could optimize therapeutic strategies and minimize unnecessary interventions. Despite promising advances, challenges remain in assay standardization, early-stage sensitivity, and the integration of multi-omic data for comprehensive tumor profiling. Future efforts should focus on enhancing the sensitivity of liquid biopsy platforms, validating emerging biomarkers, and expanding multi-omic approaches to support more targeted and personalized treatment strategies across CRC stages. Full article

Objective: Tumor progression is regulated by systemic immune status, nutritional metabolism, and the inflammatory microenvironment. This study aims to investigate inflammatory–nutritional biomarkers associated with metachronous liver metastasis (MLM) in colorectal cancer (CRC) and develop a machine learning model for accurate prediction. Methods: This study enrolled 680 patients with CRC who underwent curative resection, randomly allocated into a training set (n = 477) and a validation set (n = 203) in a 7:3 ratio. Feature selection was performed using Boruta and Lasso algorithms, identifying nine core prognostic factors through variable intersection. Seven machine learning (ML) models were constructed using the training set, with the optimal predictive model selected based on comprehensive evaluation metrics. An interactive visualization tool was developed to interpret the dynamic impact of key features on individual predictions. The partial dependence plots (PDPs) revealed a potential dose–response relationship between inflammatory–nutritional markers and MLM risk. Results: Among 680 patients with CRC, the cumulative incidence of MLM at 6 months postoperatively was 39.1%. Multimodal feature selection identified nine key predictors, including the N stage, vascular invasion, carcinoembryonic antigen (CEA), systemic immune–inflammation index (SII), albumin–bilirubin index (ALBI), differentiation grade, prognostic nutritional index (PNI), fatty liver, and T stage. The gradient boosting machine (GBM) demonstrated the best overall performance (AUROC: 0.916, sensitivity: 0.772, specificity: 0.871). The generalized additive model (GAM)-fitted SHAP analysis established, for the first time, risk thresholds for four continuous variables (CEA > 8.14 μg/L, PNI < 44.46, SII > 856.36, ALBI > −2.67), confirming their significant association with MLM development. Conclusions: This study developed a GBM model incorporating inflammatory-nutritional biomarkers and clinical features to accurately predict MLM in colorectal cancer. Integrated with dynamic visualization tools, the model enables real-time risk stratification via a freely accessible web calculator, guiding individualized surveillance planning and optimizing clinical decision-making for precision postoperative care. Full article

Colorectal cancer (CRC) is one of the most prevalent and deadly neoplasms globally; this fact puts emphasis on the need for accurate molecular biomarkers for early detection and accurate prognosis. Circular RNAs (circRNAs) have recently emerged as very promising cancer biomarkers. In this study, we thoroughly examined whether the expression levels of circular transcripts of the protein arginine methyltransferase 1 (PRMT1) gene can predict the prognosis of patients diagnosed with colorectal adenocarcinoma, the most frequent type of CRC. Hence, a highly sensitive quantitative PCR (qPCR) assay was developed and applied to quantify circ-PRMT1 expression in cDNAs from 210 primary colorectal adenocarcinoma tissue specimens and 86 paired normal colorectal mucosae. Extensive biostatistical analysis was then performed to assess the potential prognostic power of circ-PRMT1. Significant overexpression of this molecule was observed in colorectal adenocarcinoma tissue samples in contrast to their non-cancerous counterparts. Moreover, higher circ-PRMT1 expression was correlated with poorer disease-free survival (DFS) and worse overall survival (OS) in colorectal adenocarcinoma patients. Interestingly, multivariate Cox regression analysis revealed that the prognostic value of the expression of this circRNA does not depend on other established prognostic factors included in the prognostic model. Furthermore, the stratification of patients based on TNM staging revealed that higher circ-PRMT1 levels were significantly related to shorter DFS and OS intervals, particularly in patients with colorectal adenocarcinoma of TNM stage II or III. In summary, this original research study provides evidence that circ-PRMT1 overexpression represents a promising molecular biomarker of poor prognosis in colorectal adenocarcinoma, not depending on other established prognostic factors such as TNM staging. Full article

Purpose: Previous studies have reported that blood-based inflammatory markers are associated with prognosis in patients with various solid tumors, including colorectal cancer (CRC). The pan-immune inflammation value (PIV) is a novel prognostic biomarker based on blood count. Here, we aimed to study the association between PIV and survival following transarterial radioembolization (TARE) in patients with liver-dominant metastatic colorectal cancer (CLM). Methods: A total of 49 patients with CLM who underwent TARE at the Ankara University Department of Medical Oncology were retrospectively analyzed. The relationship between clinical and laboratory parameters with post-TARE overall survival (OS) was analyzed by multivariate analyses. Results: The median age was 60 years and 71.4% of patients had received at least two lines of chemotherapy. The objective response rate (ORR) was 59.1% following TARE. Patients with hepatic response after TARE treatment demonstrated significantly longer survival compared to non-responders (p: 0.033). The optimal PIV threshold value was calculated as 629 in ROC analyses. This PIV value had 81% sensitivity and 80% specificity for OS prediction (AUC 0.86; 95% CI: 0.75–0.98, p = 0.008). Patients with elevated PIV > 629 had significantly shorter OS (p = 0.002). In the multivariate analysis, adjusted for ECOG PS, TARE response, presence of extrahepatic disease, number of chemotherapy lines, CEA levels and post-TARE NLR and PIV, only low PIV level was associated with longer OS (>629 vs. ≤629; HR: 4.87; 95% CI: 1.32–17.92; p = 0.017). Conclusions: PIV, a blood-based inflammatory score, may reflect the host’s immune response following TARE and serve as a novel predictor of survival. Full article

Machine learning (ML) algorithms hold the potential to outperform the selection of patients for immunotherapy (ICIs) compared to previous biomarker studies. We analyzed the predictive performance of ML models and compared them to traditional clinical biomarkers (TCBs) in the field of gastrointestinal (GI) cancers. The study has been registered in PROSPERO (number: CRD42023465917). A systematic search of PubMed was conducted to identify studies applying different ML algorithms to GI cancer patients treated with ICIs using tumor RNA gene expression profiles. The outcomes included were response to immunotherapy (ITR) or survival. Additionally, we compared the ML methodology details and predictive power inherent in the published gene sets using 5-fold cross-validation and logistic regression (LR), on an available well-defined ICI-treated metastatic gastric cancer (GC) cohort (n = 45). A set of standard clinical ICI biomarkers (MLH, MSH, and CD8 genes, plus PMS2 and PD-L1)) and de-novo calculated principal components (PCs) of the original datasets were also included as additional points of comparison. Nine articles were identified as eligible to meet the inclusion criteria. Three were pan-cancer studies, five assessed GC, and one studied colorectal cancer (CRC). Classification and regression models were used to predict ICI efficacy. Next, using LR, we validated the predictive power of applied ML algorithms on RNA signatures, using their reported receiver operating characteristics (ROC) analysis area under the curve (AUC) values on a well-defined ICI-treated gastric cancer (GC) dataset (n = 45). In two cases our method has outperformed the published results (reported/LR comparison: 0.74/0.831, 0.67/0.735). Besides the published studies, we have included two benchmarks: a set of TCBs and using principal components based on the whole dataset (PCA, 99% explained variance, 40 components). Interestingly, a study using a selected gene set (immuno-oncology panel) with AUC = 0.83 was the only one that outperformed the TCB (AUC = 0.8) and the PCA (AUC =0.81) results. Cross-validation of the predictive performance of these genes on the same GC dataset and an investigation of their prognostic role on a collated multi-cohort GC dataset of n = 375 resected, or chemotherapy-treated patients revealed that genes mannose-6-phosphate receptor (M6PR), Indoleamine 2,3-Dioxygenase 1 (IDO1), Neuropilin-1 (NRP1), and MAGEA3 performed similarly, or better than established biomarkers like PD-L1 and MSI. We found an immuno-oncology panel with an AUC = 0.83 that outperformed the clinical benchmark or the PC results. We recommend further investigation and experimental validation in the case of M6PR, IDO1, NRP1, and MAGEA3 expressions based on their strong predictive power in GC ITR. Well-designed studies with larger sample sizes and nonlinear ML models might help improve biomarker selections. Full article

Peritoneal carcinomatosis (PC) represents a challenge in the management of metastatic colorectal cancer (mCRC) because of the difficulties in diagnosis, tumor burden assessment, and in selecting the optimal treatments. A critical limitation is the lack of robust prognostic and predictive biomarkers, largely relying on serum markers (e.g., carcinoembryonic antigen) or the peritoneal carcinomatosis index (PCI) for disease extent. Circulating tumor DNA (ctDNA)—genomic fragments shed by tumor cells into the bloodstream—is now recommended by international guidelines for mCRC management. Its potential extends to PC, where it may enhance diagnostic, therapeutic, and follow-up strategies. However, PC from CRC (PC-CRC) is associated with lower ctDNA levels and detection rates compared to other metastatic sites, posing a challenge for its clinical utility. To address these limitations, peritoneal fluid analysis has emerged as a promising alternative, with peritoneal tumor DNA (ptDNA) detected at higher concentrations in this anatomical space. Integrating ctDNA and ptDNA may offer a deeper understanding of PC-CRC biology and provide more precise tools for managing this complex disease. This approach has the potential to revolutionize the treatment paradigm for PC-CRC, bringing precision medicine even to this subgroup of patients traditionally associated with poor outcomes. This review aims to evaluate the diagnostic, prognostic, and therapeutic implications of ctDNA and ptDNA in PC-CRC, highlighting current limitations and future directions. Full article

Background and Objectives: KRAS genes are among the most prominent oncogenes that trigger tumor formation in colorectal cancer (CRC) and serve as predictive biomarkers for resistance to anti-EGFR therapies in metastatic colorectal cancer (mCRC) patients. However, the prevalence and mutation spectrum of the KRAS gene family in mCRC patients in Turkey have not been sufficiently analyzed. This study investigates the frequency and distribution of mutations in the KRAS gene family across different regions of Turkey and examines gender-related variations. Materials and Methods: This multicenter observational study included 2458 histologically confirmed mCRC patients collected from 52 centers across Turkey. In a central laboratory, KRAS mutations in codons 12 and 13 were analyzed using polymerase chain reaction (PCR). Statistical analyses were performed using chi-square tests and Monte Carlo simulations, with a significance threshold set at p < 0.05. Results: Depending on the region, KRAS mutations were detected in 45% of patients, ranging from 39.6% to 47.5%. The mutation rate was significantly higher in female patients (48.8%) compared to male patients (42.6%) (p = 0.002). Codon 12 mutations were more frequent than codon 13 mutations. G12D, G12V, and G13D mutations accounted for 80% of all detected mutations. The G12V mutation was prevalent in female patients (p = 0.007). Based on region, mutation diversity was similar, and no statistically significant difference was found (p > 0.05). Conclusions: This large-scale, multicenter study provides the most comprehensive dataset of KRAS mutations in mCRC patients in Turkey. This study revealed regional trends, as well as gender differences. The findings highlight the importance of routine KRAS genotyping in guiding personalized treatment strategies, especially regarding candidate selection for anti-EGFR therapies. Further research is required to elucidate the prognostic and therapeutic implications of specific KRAS mutations. Full article

Colorectal cancer (CRC) is the third most common cancer and a leading cause of cancer-related mortality worldwide, with prognosis significantly deteriorating at advanced stages. While current diagnostic methods, such as colonoscopy and tissue biopsy, are widely employed in clinical practice, they are invasive, expensive, and limited in assessing tumor heterogeneity and monitoring disease processes, including therapy response. Therefore, early and accurate detection, coupled with minimal invasion and cost-effective strategies, are critical for improving patient outcomes. Liquid biopsy has emerged as a promising, minimally invasive alternative, enabling the detection of tumor-derived components. This approach is increasingly utilized in clinical settings. The current key liquid biopsy modalities in CRC include circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and RNA-based biomarkers such as long non-coding RNAs (lncRNAs), microRNAs(miRNAs), and circular RNAs (circRNAs), and tumor-educated platelets (TEPs). These methods provide valuable insights into genetic and epigenetic tumor alterations, and serve as indicators for early detection, treatment monitoring, and recurrence prediction. However, challenges such as assay standardization and variability in sensitivity persist. This review delves into the clinical applications of liquid biopsy in CRC management, highlighting the transformative roles of ctDNA, CTCs, and non-coding RNAs, TEPs in early detection, prognostic assessment, and personalized therapy. In addition, it addresses current limitations and explores potential advancements to facilitate their integration into routine clinical practice. Full article

The immune system is alerted for virally infected cells in the body by the antigen presentation pathway, which is in turn mediated by the major histocompatibility complex (MHC) class I and II molecules. Cancer cells overcome immune evasion as a major hallmark by downregulation of the antigen presentation pathway. Therefore, the present study aimed to explore the effect of genetic variants in genes involved in MHC class I and II pathways in patients treated with first-line chemotherapy in combination with targeted antibodies in metastatic colorectal cancer (mCRC) patients. Genomic DNA from the blood samples of 775 patients enrolled in three independent, randomized, first-line trials, namely TRIBE (FOLFIRI-bevacizumab, N = 215), FIRE-3 (FOLFIRI-bevacizumab, N = 107; FOLFIRI-cetuximab, N = 129), and MAVERICC (FOLFIRI-bevacizumab, N = 163; FOLFOX6-bevacizumab, N = 161), was genotyped through OncoArray, a custom array manufactured by Illumina including approximately 530K SNP markers. The impact on the outcome of 40 selected SNPs in 22 genes of MHC class I and II pathways was analyzed. We identified several SNPs in multiple genes associated with targeted treatment benefits across different treatment arms in our study population (p < 0.05). Treatment–SNP interaction analyses confirmed a significant treatment interaction with the targeted agents (bevacizumab vs. cetuximab) and the chemotherapy backbone (FOLFIRI vs. FOLFOX) in certain selected SNPs. Our results highlight a potential role for MHC SNPs as prognostic and predictive biomarkers for first-line treatment in mCRC, with differential effects based on the biologic agent and chemotherapy backbone. These biomarkers, when further validated, may contribute to personalized treatment strategies for mCRC patients. Full article

The role of adjuvant chemotherapy (adj-CT) in stage II colon cancer remains controversial. Circulating tumor DNA (ctDNA) is a promising biomarker for detecting minimal residual disease (MRD) and predicting recurrence. This systematic review and meta-analysis evaluated the prognostic value of ctDNA in stage II colorectal cancer (CRC), focusing on postoperative detection, post adj-CT outcomes, and dynamic surveillance. A literature search identified studies correlating ctDNA positivity in stage II CRC with recurrence risk, recurrence-free survival (RFS), and disease-free survival (DFS). Seven studies met the inclusion criteria. Postoperative ctDNA positivity significantly increased the risk of recurrence (pooled risk ratio [RR:] 3.66; 95% confidence interval [CI]: 1.25–10.72; p = 0.002). CtDNA positivity after adj-CT was strongly associated with poor survival, while dynamic ctDNA monitoring detected recurrence earlier than conventional methods, including carcinoembryonic antigen (CEA) and imaging. CtDNA is a robust prognostic biomarker in stage II CRC, enabling personalized treatment. High-risk ctDNA-positive patients may benefit from intensified therapy, while ctDNA-negative patients could avoid unnecessary treatments. However, the standardization of detection methods and large-scale validation studies are needed before integrating ctDNA into routine clinical practice as a non-invasive, dynamic tool for personalized care. Full article

Non-coding RNAs (ncRNAs) play crucial roles in colorectal cancer (CRC) development and progression. Recent developments in single-cell transcriptome profiling methods have revealed surprising levels of expression variability among seemingly homogeneous cells, suggesting the existence of many more cell types than previously estimated. This review synthesizes recent advances in ncRNA research in CRC, emphasizing single-cell bioinformatics approaches for their analysis. We explore computational methods and tools used for ncRNA identification, characterization, and functional prediction in CRC, with a focus on single-cell RNA sequencing (scRNA-seq) data. The review highlights key bioinformatics strategies, including sequence-based and structure-based approaches, machine learning applications, and multi-omics data integration. We discuss how these computational techniques can be applied to analyze differential expression, perform functional enrichment, and construct regulatory networks involving ncRNAs in CRC. Additionally, we examine the role of bioinformatics in leveraging ncRNAs as diagnostic and prognostic biomarkers for CRC. We also discuss recent scRNA-seq studies revealing ncRNA heterogeneity in CRC. This review aims to provide a comprehensive overview of the current state of single-cell bioinformatics in ncRNA CRC research and outline future directions in this rapidly evolving field, emphasizing the integration of computational approaches with experimental validation to advance our understanding of ncRNA biology in CRC. Full article

CRC remains a significant public health challenge due to its high prevalence and mortality rates. Emerging evidence highlights the critical role of the gut microbiota in both the pathogenesis of CRC and the efficacy of treatment strategies, including chemotherapy and immunotherapy. Dysbiosis, characterized by imbalances in microbial communities, has been implicated in CRC progression and therapeutic outcomes. This review examines the intricate relationship between gut microbiota composition and CRC, emphasizing the potential for microbial profiles to serve as biomarkers for early detection and prognosis. Various interventions, such as prebiotics, probiotics, postbiotics, fecal microbiota transplantation, and dietary modifications, aim to restore microbiota balance and shift dysbiosis toward eubiosis, thereby improving health outcomes. Additionally, the integration of microbial profiling into clinical practice could enhance diagnostic capabilities and personalize treatment strategies, advancing the field of oncology. The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. Given the growing understanding of the gut microbiome–cancer axis, developing microbiota-oriented strategies for CRC prevention and treatment holds promise for improving patient care and clinical outcomes. Full article

Colorectal cancer (CRC) is the third-most common cancer globally and a leading cause of cancer-related deaths. While the prognostic and predictive roles of RAS mutations in advanced CRC are well-established, their significance in early-stage CRC remains a topic of debate. Studies have been conducted for many years on clinical and pathological parameters that may be associated with RAS mutation, and there are inconsistent results in this regard. Currently, the only biomarker used in early-stage CRC is microsatellite status. KRAS mutations are detected in 40–50% of patients with colorectal cancer. RAS activating mutations cause loss of EGFR regulation by acting on the RAS/RAF/MAPK signaling pathways. In advanced colorectal cancer, these mechanisms cause a decrease in the effectiveness of EGFR inhibitors. However, studies on patients with early-stage colorectal cancer have inconsistent results. This review highlights the prognostic and clinical significance of KRAS mutations in early-stage CRC, particularly in MSS tumors. In the MSS group, KRAS mutations were associated with shorter TTR and OS compared to DWT patients. In contrast, in the MSI-H group, KRAS mutations showed no prognostic effect in TTR and OS. However. KRAS mutations were associated with shorter SAR in both MSI-H and MSS groups of patients. The findings underscore the need for routine molecular profiling, including KRAS and MSI status, to refine risk stratification and guide adjuvant therapy decisions. Further studies are warranted to explore targeted therapeutic approaches for KRAS-mutant CRC in the adjuvant setting. Full article