Survival Of Colorectal Cancer Patients Research Articles

Machine learning-driven estimation of mutational burden highlights DNAH5 as a prognostic marker in colorectal cancer.

Tumor Mutational Burden (TMB) have emerged as pivotal predictive biomarkers in determining prognosis and response to immunotherapy in colorectal cancer (CRC) patients. While Whole Exome Sequencing (WES) stands as the gold standard for TMB assessment, carry substantial costs and demand considerable time commitments. Additionally, the heterogeneity among high-TMB patients remains poorly characterized. We employed eight advanced machine learning algorithms to develop gene-panel-based models for TMB estimation. To rigorously compare and validate these TMB estimation models, four external cohorts, involving 1,956 patients, were used. Furthermore, we computed the Pearson correlation coefficient between the estimated TMB and tumor neoantigen levels to elucidate their association. CD8+ tumor-infiltrating lymphocyte (TIL) density was assessed via immunohistochemistry. The TMB estimation model based on the Lasso algorithm, incorporating 20 genes, exhibiting satisfactory performance across multiple independent cohorts (R2 ≥ 0.859). This 20-gene TMB model proved to be an independent prognostic indicator for the progression-free survival (PFS) of CRC patients (p = 0.001). DNAH5 mutations were associated with a more favorable prognosis in high-TMB CRC patients, and correlated strongly with tumor neoantigen levels and CD8+ TIL density. The 20-gene model offers a cost-efficient approach to precisely estimating TMB, providing prognosis in patients with CRC. Incorporating DNAH5 within this model further refines the categorization of patients with elevated TMB. Utilizing the 20-gene model facilitates the stratification of patients with CRC, enabling more precise treatment planning.

Identifying colorectal cancer subtypes and establishing a prognostic model using metabolic plasticity and ferroptosis genes

Metabolic plasticity and ferroptosis are essential for colorectal cancer (CRC) progression. The effects and prognostic value of metabolic plasticity- and ferroptosis-related genes (MPFRGs) in CRC remain unclear. We established a prognostic model for CRC patients by identifying important genes in metabolic plasticity and ferroptosis. Data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus; MPFRG data were obtained from GeneCards and FerrDb. We performed functional (to explore differences between the two metabolic subtypes) and single-sample gene set (to assess the immune environment) enrichment analyses. Immunophenotype, tumor immunological dysfunction, and exclusion scores were assessed to determine patient immune responses. A least absolute shrinkage and selection operator-Cox regression model comprising 10 significant differentially expressed genes of metabolic plasticity and ferroptosis (MPFDEGs) was constructed using TCGA training cohort and validated using the GSE17536 and GSE39582 datasets. We established a nomogram comprising metabolic plasticity- and ferroptosis-based signatures, revealing the clinical application and potential molecular mechanisms underlying the role of MPFRGs in CRC. Our model (developed based on 10 MPFDEGs) is efficient for calculating the overall survival of CRC patients. Our findings provide new strategies for the clinical management and individualized treatment of these patients.

Targeting SLITRK4 Restrains Proliferation and Liver Metastasis in Colorectal Cancer via Regulating PI3K/AKT/NFκB Pathway and Tumor-Associated Macrophage.

Liver metastasis is the major cause of death in colorectal cancer (CRC) due to the lack of effective treatment. To explore novel drivers of CRC liver metastasis, the transcriptomes of primary paracancerous, colorectal tumors and metastases from human patients are profiled. It is found that SLIT- and NTRK-like family member 4 (SLITRK4) is the top upregulated gene in liver metastases and is associated with worse overall survival of CRC patients. Multiple in vitro and in vivo models suggested SLITRK4 promoted CRC tumorigenesis, invasion, migration, and angiogenesis, and inhibition of it restrained CRC tumor growth and liver metastasis with a more profound effect on the tumor microenvironment (TME). Mechanistically, SLITRK4 overexpression significantly activated the PI3K/AKT/NFκB pathway, regulated extracellular matrix organization, and multiple cytokines expression. Furthermore, the results from coculture models and single-cell RNA sequencing analyses suggested SLITRK4 promoted tumor-associated macrophages (TAMs) infiltration and polarization. In addition, macrophage depletion significantly inhibited SLITRK4-induced liver metastasis in CRC. Finally, pharmacological inhibition of SLITRK4 by using lipid-polymer hybrid nanoparticles (NPs) for systemic siRNA delivery can effectively inhibit CRC liver metastasis. Taken together, these results pinpoint that SLITRK4 regulates CRC tumorigenesis and liver metastasis, and siRNA delivering NPs agents validate the therapeutic potential of targeting SLITRK4 in CRC.

Establishment and Validation of a Prognostic Nomogram for Predicting Postoperative Overall Survival in Advanced Stage III-IV Colorectal Cancer Patients.

Most colorectal cancer (CRC) patients are at an advanced stage when they are first diagnosed. Risk factors for predicting overall survival (OS) in advanced stage CRC patients are crucial, and constructing a prognostic nomogram model is a scientific method for survival analysis. A total of 2956 advanced stage CRC patients were randomised into training and validation groups at a 7:3 ratio. Univariate and multivariate Cox proportional hazards regression analyses were used to screen risk factors for OS and subsequently construct a prognostic nomogram model for predicting 1-, 3-, 5-, 8- and 10-year OS of advanced stage CRC patients. The performance of the model was demonstrated by the area under the curve (AUC) values, calibration curves and decision curve analysis (DCA). Kaplan-Meier curves were used to plot the survival probabilities for different strata of each risk factor. There was no statistically significant difference (p > 0.05) in the 32 clinical variables between patients in the training and validation groups. Univariate and multivariate Cox proportional hazards regression analyses demonstrated that age, location, TNM, chemotherapy, liver metastasis, lung metastasis, MSH6, CEA, CA199, CA125 and CA724 were risk factors for OS. We estimated the AUC values for the nomogram model to predict 1-, 3-, 5-, 8- and 10-year OS, which in the training group were 0.826 (95% CI: 0.807-0.845), 0.836 (0.819-0.853), 0.839 (0.820-0.859), 0.835 (0.809-0.862) and 0.825 (0.779-0.870) respectively; in the validation group, the corresponding AUC values were 0.819 (0.786-0.852), 0.831 (0.804-0.858), 0.830 (0.799-0.861), 0.815 (0.774-0.857) and 0.802 (0.723-0.882) respectively. Finally, the 1-, 3-, 5-, 8- and 10-year OS rates for advanced stage CRC patients were 73.4 (71.8-75.0), 49.5 (47.8-51.4), 43.3 (41.5-45.2), 40.1 (38.1-41.9) and 38.6 (36.6-40.8) respectively. We constructed and validated an original nomogram for predicting the postoperative OS of advanced stage CRC patients, which can help facilitates physicians to accurately assess the individual survival of postoperative patients and identify high-risk patients.

The Effect of Statin Usage on Survival in Metastatic Colorectal Cancer Patients Receiving Regorafenib.

Regorafenib is an oral multikinase inhibitor used in later lines for metastatic colorectal carcinoma (mCRC) treatment, but its efficacy and tolerability are low. To improve the response rates and ameliorate adverse effects, different strategies have been implemented. In our study, we examined the effect of statin usage in patients with mCRC treated with regorafenib. This single-center retrospective study included patients with mCRC who were treated with regorafenib between January 2015 and December 2023. The primary outcomes were progression-free survival (PFS) and overall survival (OS), and the secondary outcomes were adverse effects and the tolerability of regorafenib. The data of 105 patients were collected retrospectively. The median age of the patients was 66 years, and 60 patients were male. Seventeen patients (16.1%) were receiving statins. Statin-using patients were significantly older than non-users (72 years vs. 66.5 years, p=0.05). Comorbid diseases were more common in patients using statins. The median PFS was 1.9 months for statin users and 4.2 months for statin non-users (p<0.001), and the median OS was 4.7 vs. 6.7 months (p=0.01). Cox regression revealed that statin usage was significantly associated with a higher hazard ratio (HR) for PFS (2.53) and OS (2.06) (both p<0.01 and p=0.02, respectively). Statins are associated with decreased survival and response rates in patients with mCRC treated with regorafenib. However, further studies are needed to confirm these results.

Identification of key lncRNAs associated with oxaliplatin resistance in colorectal cancer cells and isolated exosomes: From In-Silico prediction to In-Vitro validation.

One of the critical challenges in managing colorectal cancer (CRC) is the development of oxaliplatin (OXP) resistance. Long non-coding RNAs (lncRNAs) have a crucial role in CRC progression and chemotherapy resistance, with exosomal lncRNAs emerging as potential biomarkers. This study aimed to predict key lncRNAs involved in OXP-resistance using in-silico methods and validate them using RT-qPCR methods in CRC cells and their isolated exosomes. Two public datasets, GSE42387 and GSE119481, were downloaded from the GEO database to identify differentially expressed genes (DEGs) and miRNAs (DEmiRNAs) associated with OXP-resistance in the HCT116 cell line. The analysis of GSE42387 revealed 210 DEGs, and GSE119481 identified 73 DEmiRNAs. A protein-protein interaction (PPI) network analysis of the DEGs identified 133 interconnected genes, from which the top ten genes with the highest degree scores were selected. By intersecting predicted miRNAs targeting these genes with the DEmiRNAs, 38 common miRNAs were found. Subsequently, 224 lncRNAs targeting these common miRNAs were predicted. LncRNA-miRNA-mRNA network were constructed and the top five lncRNAs with the highest degree scores were identified. Analysis using the Kaplan-Meier plotter database revealed that the key lncRNAs NEAT1, OIP5-AS1, and MALAT1 are significantly associated with the overall survival of CRC patients. To validate these lncRNAs, OXP-resistant HCT116 sub-cell line (HCT116/OXR) was developed by exposing parental HCT116 cells to gradually increasing concentrations of OXP. Exosomes derived from both HCT116 and HCT116/OXR cells were isolated and characterized utilizing dynamic light scattering (DLS), transmission electron microscopy (TEM), and Western blotting. RT-qPCR confirmed elevated levels of NEAT1, OIP5-AS1, and MALAT1 in HCT116/OXR cells and their exosomes compared to parental HCT116 cells and their exosomes. This study concludes that NEAT1, OIP5-AS1, and MALAT1 are associated with the OXP-resistance in CRC. The high levels of these lncRNAs in exosomes of resistant cells suggest their involvement in intercellular communication and resistance propagation. This positioning makes them promising biomarkers for OXP-resistance in CRC.

Evaluation of the prognostic effectiveness of liver metastasis volume by volumetric measurement in colorectal cancer.

Aim: To evaluate the relationship between liver metastasis volume and survival in colorectal cancer patients using the volumetric measurement method.Methods: 114 colorectal cancer patients with isolated liver metastases were included in the study. Liver tumor volume, total liver volume were calculated from the patients images at the time of diagnosis. Vitrea 7.14 imaging software was used for liver volume analysis and volume analysis of each metastasis.Results: Median overall survival(OS) in the group with tumor volume <42ml3 was 30.98months In the group with tumor volume ≥42ml3, median OS was 16.36months (p: 0.001). In patients who underwent metastasectomy, the median OS in the group with a tumor volume <42ml3 was 52.3months, the median OS in the group with a tumor volume ≥42ml3 was 22.2months. In patients who did not undergo metastasectomy, the median OS in the <42ml3 group was 20.23months, the median OS in the ≥42ml3 group was 15.63months.Conclusion: In our study, we found that liver metastasis volume was prognostic for OS. It is argued that tumor volume measurement by volumetric measurement is a widely used method in the decision for metastasectomy in liver metastatic colorectal cancer patients.

Bulk integrated single-cell-spatial transcriptomics reveals the impact of preoperative chemotherapy on cancer-associated fibroblasts and tumor cells in colorectal cancer, and construction of related predictive models using machine learning

BackgroundPreoperative chemotherapy (PC) is an important component of Colorectal cancer (CRC) treatment, but its effects on the biological functions of fibroblasts and epithelial cells in CRC are unclear. MethodsThis study utilized bulk, single-cell, and spatial transcriptomic sequencing data from 22 independent cohorts of CRC. Through bioinformatics analysis and in vitro experiments, the research investigated the impact of PC on fibroblast and epithelial cells in CRC. Subpopulations associated with PC and CRC prognosis were identified, and a predictive model was constructed using machine learning. ResultsPC significantly attenuated the pathways related to tumor progression in fibroblasts and epithelial cells. NOTCH3 + Fibroblast (NOTCH3 + Fib), TNNT1 + Epithelial (TNNT1 + Epi), and HSPA1A + Epithelial (HSPA1A + Epi) subpopulations were identified in the adjacent spatial region and were associated with poor prognosis in CRC. PC effectively diminished the presence of these subpopulations, concurrently inhibiting pathway activity and intercellular crosstalk. A risk signature model, named the Preoperative Chemotherapy Risk Signature Model (PCRSM), was constructed using machine learning. PCRSM emerged as an independent prognostic indicator for CRC, impacting both overall survival (OS) and recurrence-free survival (RFS), surpassing the performance of 89 previously published CRC risk signatures. Additionally, patients with a high PCRSM risk score showed sensitivity to fluorouracil-based adjuvant chemotherapy (FOLFOX) but resistance to single chemotherapy drugs (such as Bevacizumab and Oxaliplatin). Furthermore, this study predicted that patients with high PCRSM were resistant to anti-PD1therapy. ConclusionIn conclusion, this study identified three cell subpopulations (NOTCH3 + Fib, TNNT1 + Epi, and HSPA1A + Epi) associated with PC, which can be targeted to improve the prognosis of CRC patients. The PCRSM model shows promise in enhancing the survival and treatment of CRC patients.

Hypoxia-Associated GPNMB+ Macrophages Promote Malignant Progression of Colorectal Cancer and Its RelatedRisk Signature Are Powerful Predictive Tool for theTreatment of Colorectal Cancer Patients.

Colorectal cancer (CRC) is a highly malignant tumor with hypoxia being a crucial feature during its progression. This study utilized multiple independent CRC cohorts for bioinformatics analysis and in vitro experiments to investigate the role of hypoxia-related subgroups in CRC. Machine learning was employed to construct risk features associated with this subgroup and further explore its therapeutic value in CRC. The study identified the GPNMB+ Macrophage (GPNMB+ Macr) subgroup as most relevant to hypoxia. GPNMB+ Macr showed significantly higher infiltration in tumor tissues compared to non-tumor tissues, increasing with CRC stage. High infiltration of GPNMB+ Macr was associated with poor prognosis in terms of overall and recurrence-free survival in CRC patients. GPNMB+ Macrophages exhibit M2-like characteristics and have the ability to promote 5-FU resistance, proliferation, and metastasis of CRC cells. The study developed the Hypoxia-Related Macrophage Risk Score (HMRS), which not only served as an independent prognostic factor for CRC patients but also demonstrated robust prognostic performance compared to 84 previously published prognostic features. Patients with low HMRS were sensitive to fluorouracil, oxaliplatin (FOLFOX), and anti-PD-1 immunotherapy, while those with high HMRS showed resistance. Additionally, HMRS was identified as an independent prognostic factor in other digestive tract tumors (hepatocellular carcinoma, pancreatic cancer, esophageal cancer, and gastric cancer), indicating potential extrapolation to other tumor types. In conclusion, GPNMB+ Macr promotes the malignant progression of CRC, and HMRS serves as a powerful predictive tool for prognosis, chemotherapy, and immunotherapy in CRC patients, aiding in improving the quality of survival.

Grading carcinoembryonic antigen levels can enhance the effectiveness of prognostic stratification in patients with colorectal cancer: a single-centre retrospective study.

This study developed a refined carcinoembryonic antigen (CEA) grading system using CEA cut-off points of 5, 20 and 50 ng/mL and to explore the prognostic value of CEA grading in predicting the progression-free survival (PFS) and overall survival (OS) of colorectal cancer (CRC) patients. A retrospective cohort study. First Affiliated Hospital of Guangxi Medical University. 1107 CRC patients who received surgical treatment. Survival analysis was conducted using the Kaplan-Meier method and compared using the log-rank test. A Cox regression model with a 95% CI was used to evaluate the independent prognostic risk factors for CRC. Prognostic nomograms were constructed to predict the 1-5-year PFS/OS. Elevated serum CEA levels are often indicative of recurrence and death in CRC patients. Higher CEA levels were significantly associated with more aggressive tumour phenotypes. The CEA grading system was an independent predictor of prognosis in CRC patients and effectively stratified PFS (62.0% vs 51.2% vs 33.7% vs 20.2%, p<0.001) and OS (64.7% vs 54.4% vs 36.6% vs 22.5%, p<0.001) in CRC patients. As the CEA grade increased, the risk of poor prognosis gradually increased in a gradient manner, with an approximately 10% difference in risk grade between each CEA grade. The internal validation cohort further confirmed that CEA grade remains an effective prognostic factor for the survival of CRC patients. Prognostic nomograms, which integrate individual characteristics, tumour features and CEA grading, provide a more comprehensive prognostic evaluation for CRC patients. The CEA grading system is an independent predictor of prognosis for CRC patients and can effectively stratify PFS and OS.

Sarcopenia Predicts Postoperative Complications and Survival of Colorectal Cancer Patients Undergoing Radical Surgery.

Aims/Background Previous literature has indicated that sarcopenia is related to poor outcomes after radical resection for colorectal cancer (CRC). However, its effect on the postoperative clinical outcomes of CRC remains controversial. This study aimed to elucidate the predictive value of sarcopenia for postoperative complications and survival in CRC patients. Methods This investigation retrospectively assessed the clinical data of 226 CRC patients who underwent radical resection at the Department of Gastrointestinal Surgery, Affiliated Hospital of Zunyi Medical University from January 2018 to December 2020. Sarcopenia was diagnosed according to the recommendations of the Asian Working Group for Sarcopenia in 2019, and patients were categorized into sarcopenia and non-sarcopenia groups. Multivariate and univariate analyses were employed to assess the risk factors for postoperative complications. The Kaplan-Meier method and survival curve were used to analyze postoperative survival time. Cox proportional hazards regression models were used to evaluate risk factors affecting the prognosis of CRC patients. Results This investigation included 226 patients, of which 68 were diagnosed with sarcopenia. Furthermore, it was revealed that sarcopenia was linked with older age (p < 0.001), low body mass index (p < 0.001), high prevalence of diabetes (p = 0.002), high cystatin level (p = 0.017), and low 3rd lumbar spine (L3) planar skeletal muscle index (p < 0.001), but was not related to the tumour stage or the gender. Moreover, sarcopenia was also correlated with increased occurrence of all postoperative complications (p = 0.050). The results of the multivariate analysis indicated that sarcopenia was an independent risk factor for postoperative complications (odds ratio (OR): 7.154; 95% confidence interval (CI): 2.261-22.633; p = 0.017). The Kaplan-Meier analysis revealed that sarcopenia patients had significantly lower 5-year disease-free survival (DFS) (48.5% vs 59.5%; log-rank p = 0.033) and 5-year overall survival (OS) (57.4% vs 77.2%; log-rank p < 0.001) rates. Sarcopenia was an independent risk factor for poor DFS (hazard ratio (HR) = 1.404; p = 0.016) and OS (HR = 1.290; p = 0.021). Conclusion In CRC patients undergoing radical surgery, sarcopenia is an independent risk factor for postoperative complications. Sarcopenia may be a predictive factor for the prognosis and survival of CRC patients undergoing radical resection.

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery.

Cancer-specific survival (CSS) in multiple primary colorectal cancer (MPCC) patients is competitively affected by death from other causes. This study aimed to investigate CSS and associated risk factors by competing risk analysis in MPCC patients. The data of this study is from the SEER database. Using univariable and multivariable analysis of the competitive risk model to weaken the impact of competitive events, it explores the risk factors of CSS and develops a nomogram model. Then, the performance of the model is verified by the ROC curve, calibration curve, and DCA. The study encompasses a total of 8931 patients, with 6255 in the training cohort and 2676 in the validation cohort. Univariable and multivariable analyses showed that sex, Tumor Node Metastasis (TNM) stage, and tumor grade are independent risk factors for cancer-specific survival in MPCC patients. Based on the risk factors, we developed a diagram model to predict CSS. ROC curve, calibration curve, and DCA also show good results. In conclusion, a nomogram is developed that serves as a valuable tool for predicting CSS in MPCC patients, providing clinicians with crucial insights for personalized treatment planning.

The Impact of Preoperative and Postoperative Nutritional Interventions on Treatment Outcomes and Quality of Life in Colorectal Cancer Patients-A Comprehensive Review.

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, with high morbidity and mortality rates. Nutritional status has emerged as a significant factor influencing the prognosis and survival of CRC patients. This comprehensive literature review examines the role of nutritional support in improving treatment outcomes, including the efficacy of interventions, patient quality of life (QoL), and the modulation of inflammatory responses. The findings suggest that tailored nutritional interventions improve clinical outcomes, enhance QoL, and reduce treatment-related complications, particularly by attenuating inflammation. Furthermore, the review highlights the cost-effectiveness of nutritional strategies and identifies key methods to enhance patient compliance with dietary recommendations. In conclusion, integrating nutritional support into CRC treatment plans is crucial for optimizing clinical management and improving patient well-being.

Overexpression of Osteopontin-a and Osteopontin-c Splice Variants Are Worse Prognostic Features in Colorectal Cancer

Background: Osteopontin (OPN) is a glycoprotein involved in various physiological and pathological processes, and its aberrant expression in cancer cells is closely linked to tumor progression. In colorectal cancer (CRC), OPN is overexpressed, but the roles of its splice variants (OPN-SVs), OPNa, OPNb, and OPNc, are not well understood. This study aimed to characterize the expression patterns of OPN-SVs and their potential diagnostic and prognostic implications in CRC using transcriptomic data deposited in TSVdb and TCGA. Methods: The expression patterns of each OPN-SV were analyzed using transcriptomic data deposited in TSVdb and TCGA, which were correlated to patient data available at cBioPortal. Results: Bioinformatic analysis revealed that OPNa, OPNb, and OPNc are overexpressed in CRC samples compared to non-tumor samples. Notably, OPNa and OPNc are overexpressed in CRC stages (II, III, and IV) compared to stage I. Higher levels of OPNa and OPNc transcripts are associated with worse overall survival (OS) and shorter progression-free survival (PFS) in CRC patients. Additionally, the expression of OPNa, OPNb, and OPNc is correlated with BRAFV600E mutations in CRC samples. Conclusions: These findings suggest that OPNa and OPNc, in particular, have potential as diagnostic and prognostic biomarkers, paving the way for their further evaluation in CRC diagnosis and prognosis.

Circulating tryptophan–kynurenine pathway metabolites are associated with all‐cause mortality among patients with stage I–III colorectal cancer

AbstractAlterations within the tryptophan–kynurenine metabolic pathway have been linked to the etiology of colorectal cancer (CRC), but the relevance of this pathway for prognostic outcomes in CRC patients needs further elucidation. Therefore, we investigated associations between circulating concentrations of tryptophan–kynurenine pathway metabolites and all‐cause mortality among CRC patients. This study utilizes data from 2102 stage I–III CRC patients participating in six prospective cohorts involved in the international FOCUS Consortium. Preoperative circulating concentrations of tryptophan, kynurenine, kynurenic acid (KA), 3‐hydroxykynurenine (HK), xanthurenic acid (XA), 3‐hydroxyanthranilic acid (HAA), anthranilic acid (AA), picolinic acid (PA), and quinolinic acid (QA) were measured by liquid chromatography–tandem mass spectrometry. Using Cox proportional hazards regression, we examined associations of above‐mentioned metabolites with all‐cause mortality, adjusted for potential confounders. During a median follow‐up of 3.2 years (interquartile range: 2.2–4.9), 290 patients (13.8%) deceased. Higher blood concentrations of tryptophan, XA, and PA were associated with a lower risk of all‐cause mortality (per doubling in concentrations: tryptophan: HR = 0.56; 95%CI:0.41,0.76, XA: HR = 0.74; 95%CI:0.64,0.85, PA: HR = 0.76; 95%CI:0.64,0.92), while higher concentrations of HK and QA were associated with an increased risk of death (per doubling in concentrations: HK: HR = 1.80; 95%CI:1.47,2.21, QA: HR = 1.31; 95%CI:1.05,1.63). A higher kynurenine‐to‐tryptophan ratio, a marker of cell‐mediated immune activation, was associated with an increased risk of death (per doubling: HR = 2.07; 95%CI:1.52,2.83). In conclusion, tryptophan–kynurenine pathway metabolites may be prognostic markers of survival in CRC patients.

A Novel Approach for Predicting the Survival of Colorectal Cancer Patients Using Machine Learning Techniques and Advanced Parameter Optimization Methods.

Colorectal cancer is one of the most prevalent forms of cancer and is associated with a high mortality rate. Additionally, an increasing number of adults under 50 are being diagnosed with the disease. This underscores the importance of leveraging modern technologies, such as artificial intelligence, for early diagnosis and treatment support. Eight classifiers were utilized in this research: Random Forest, XGBoost, CatBoost, LightGBM, Gradient Boosting, Extra Trees, the k-nearest neighbor algorithm (KNN), and decision trees. These algorithms were optimized using the frameworks Optuna, RayTune, and HyperOpt. This study was conducted on a public dataset from Brazil, containing information on tens of thousands of patients. The models developed in this study demonstrated high classification accuracy in predicting one-, three-, and five-year survival, as well as overall mortality and cancer-specific mortality. The CatBoost, LightGBM, Gradient Boosting, and Random Forest classifiers delivered the best performance, achieving an accuracy of approximately 80% across all the evaluated tasks. This research enabled the development of effective classification models that can be applied in clinical practice.

HNRNPA1 gene is highly expressed in colorectal cancer: its prognostic implications and potential as a therapeutic target

To investigate the expression level of HNRNP A1 in colorectal cancer (CRC) and its prognostic implications. We investigated HNRNP A1 expression level in CRC using HPA, TIMER, and GEPIA databases and analyzed its association with Ki-67 and VEGFA expressions. Kaplan-Meier Plotter database was used to analyze the correlation of HNRNP A1 mRNA levels with the survival rates of CRC patients. Pathway enrichment analysis was performed for predicting the biological roles of HNRNP A1 in CRC progression. Immunohistochemistry and Western blotting were used to examine the protein levels of HNRNP A1 in CRC versus adjacent tissues, and TIMER was used for assessing its expression in the infiltrating immune cells. In RKO/Caco2 cells, the effects of lentivirus-mediated knockdown of HNRNP A1 on cell proliferation and migration were observed, and the inhibitory effect of VPC-80051 (a HNRNP A1 inhibitor) on cell proliferation was evaluated to assess its potential as a therapeutic agent. HNRNP A1 was significantly overexpressed in CRC tissues and correlated with a poor prognosis of the patients. HNRNP A1 expression level was correlated with the infiltrating immune cells in CRC microenvironment and positively correlated with MKI67 and VEGFA expressions in CRC. A high HNRNP A1 expression predicted a in survival and progression-free survival of CRC patients and was involved in multiple biological processes related with CRC progression. In RKO/Caco2 cells, HNRNP A1 knockdown significantly suppressed cell proliferation and migration, and treatment with VPC-80051 also effectively inhibited CRC cell proliferation. Immunohistochemical study demonstrated a close correlation of HNRNP A1 overexpression with tumor stage of CRC. HNRNP A1 is overexpressed in CRC tissues to modulate cell proliferation and migration and is correlated with a poorer prognosis. VPC-80051 can effectively inhibit CRC cell proliferation, suggesting the potential of HNRNP A1 as a therapeutic target for CRC.

MiRNA expression affects survival in patients with obstructive sleep apnea and metastatic colorectal cancer

IntroductionThe relationship between obstructive sleep apnea (OSA) and cancer has been recognized for some time now. However, little is known about the mechanisms by which sleep apnea promotes tumorigenesis and the impact of OSA on survival after cancer diagnosis. In the last few years, research has focused on the exploration of different biomarkers to understand the mechanisms underlying this relationship and miRNAs, non-coding single strands of about 22 nucleotides that post-transcriptionally regulate gene expression, have emerged as possible actors of this process.The aim of the study was to evaluate the impact of OSA on survival of metastatic colorectal cancer (mCRC) patients based on the expression of specific miRNAs. MethodsThe expression of 6 miRNAs, respectively miR-21, miR-23b, miR-26a, miR-27b, miR-145 and miR-210, was analyzed by qRT-PCR in patients’ sera. Response to first-line therapy, Kaplan-Meier curves of overall and progression-free survival were used to evaluate survival in mCRC patients with and without OSA stratified for the expression of miRNAs. ResultsThe expression of miR-21, miR-23b, miR-26a and miR-210 was significantly upregulated in mCRCs with OSA compared to no OSA. In mCRC patients with OSA and increasing expression of miR-21, miR-23b, miR-26a and miR-210 risk of progression after first-line therapy was higher and both overall and progression-free survival were significantly worst. Conversely, as miR-27b and miR-145 expression increased, the life expectancy of patients diagnosed with OSA and mCRC improved markedly. ConclusionsThis study highlights the relevance of specific miRNAs on OSA in mCRCs and their significance as non-invasive biomarkers in predicting the prognosis in patients with mCRC and OSA.

Retrospective cohort study on the postoperative survival rate enhancement of patients with colorectal cancer using three traditional Chinese medicine formulations: evidence from 1,361 cases

Background: Prior studies have affirmed the safety and effectiveness of traditional Chinese medicine in treating colorectal cancer patients. However, definitive evidence regarding whether traditional Chinese medicine can significantly enhance the survival of colorectal cancer patients remains elusive. This study seeks to provide conclusive insights by examining the postoperative administration of Xihuang capsules, Pingxiao capsules, and Zilongjin tablets and its impact on the 5-year overall survival (OS) and disease-free survival (DFS) rates among colorectal cancer patients. Methods: A retrospective study was conducted, involving 1,361 patients selected from the medical center. This retrospective study was carried out at a medical center in Tianjin, China. We assessed differences in postoperative OS and DFS between the control group and the medication group using Kaplan–Meier survival analysis and Cox proportional hazards modeling. Additionally, propensity score matching was used to mitigate imbalances in baseline characteristics among patients. Results: Before propensity score matching, Xihuang capsules could prolong the 5-year OS (79.9% vs. 81.4%, P = 0.0480) and 5-year DFS (74.9% vs. 79.5%, P = 0.0046) of patients after surgery. Similar conclusions were obtained after propensity score matching: OS (74.8% vs. 78.3%, P = 0.0084), DFS (72.7% vs. 78.9%, P = 0.008). Patients taking Pingxiao capsules showed improved 5-year OS (77.2% vs. 84.0%, P = 0.0383) and 5-year DFS (69.9% vs. 80.0%, P = 0.0157) after propensity score matching. Patients taking Zilongjin tablets showed improvement in the 2-year OS (84.2% vs. 93.1%, P = 0.0390) and 1-year DFS (88.2% vs. 92.0%, P = 0.0320) after propensity score matching. Conclusion: Xihuang capsules and Pingxiao capsules significantly improved the 5-year OS and DFS of patients with colorectal cancer after surgery. Zilongjin tablets showed improvement in the 2-year OS and 1-year DFS after surgery for patients.

Prognostic Impact of Para-Aortic Lymph Node Dissection in Colorectal Cancer Patients Suspected of Para-Aortic Lymph Node Metastasis: A Retrospective Cohort Study

BackgroundPara-aortic lymph node metastasis (PALNM) is a rare occurrence in colorectal cancer (CRC), and the high risk of radical lymphadenectomy leads to persistent debate about the best treatment strategy. This study aims to evaluate the predictor for PALNM and the clinical value of para-aortic lymph node dissection (PALND) in CRC patients with radiologically suspected synchronous PALNM. MethodsPatients who has synchronous radiologically suspected PALNM and underwent primary tumor resection were included. Logistic regression and receiver operating characteristic curve analysis were used to assess the predictive value of lymph node short axis in preoperative CT, identifying the optimal cut-off value. Propensity score matching and Cox regression explored factors affecting overall and disease-free survival, while Kaplan-Meier curves and decision tree models identified patient characteristics suitable for synchronous paraaortic lymph node dissection. ResultsA total of 578 patients were enrolled, and 125 patients received synchronous PALND. We found that simultaneous PALND significantly improved overall survival (HR, 0.56; 95% CI, 0.35-0.91; P = .019) in multivariate analysis, while disease-free survival showed no significant difference (P = .41). The short axis diameter of PALN on preoperative CT is a crucial predictor of PALNM (P < .001, AUC = 0.759) with a threshold of > 7 mm. N-stage and distant metastasis were included as independent predictors in the diagnostic model to enhance accuracy. A larger short axis diameter of PALN correlated with advanced tumor stage and poorer prognosis. Subgroup analysis revealed that PALND offers survival benefits for colorectal cancer patients at all stages with a short axis diameter >10mm on preoperative CT (P = .037) and for stage III patients with a diameter between 7 to10 mm (P < .001, AUC = 0.810). ConclusionSynchronous PALND can improve overall survival in CRC patients with suspected PALNM, with the maximum short axis diameter of PALN serving as a key criterion for selecting patients for surgery.