An internally and externally validated nomogram for predicting cancer-specific survival in octogenarians after radical resection for colorectal cancer.

AIMS: We aimed to develop an elaborative nomogram that predicts cancer-specific survival (CSS) in American and Chinese octogenarians treated with radical resection for CRC. METHODS: The patient data of newly diagnosed patients aged 80 years or older who underwent radical resection for CRC from 2010 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and then randomly divided into a training cohort and a validation cohort. The patients collected from our hospital were defined as the external validation cohort. Univariate and multivariate Cox regression was used to select independent predictive factors for the construction of a nomogram to predict 1-, 2- and 3-year CSS. RESULTS: The multivariate Cox regression model identified age, T stage, N stage, perineural invasion, chemotherapy, tumour deposits, carcinoembryonic antigen level, number of lymph node metastases, and number of solid organ metastases as independent predictors of survival. The C-index of the nomogram for 1-, 2- and 3-year CSS was 0.758, 0.762, and 0.727, respectively, demonstrating significant clinical value and substantial reliability compared to the TNM stage. The calibration curve and area under the curve also indicated considerable predictive accuracy. In addition, decision curve analysis demonstrated desirable net benefits in clinical application. CONCLUSION: We constructed a nomogram for predicting the CSS of individual octogenarian patients with CRC who underwent radical resection. The nomogram performed better than the TNM staging system in this particular population and could guide clinicians in clinical follow-up and individual therapeutic plan formulation.

Developing a machine learning-based prognosis and immunotherapeutic response signature in colorectal cancer: insights from ferroptosis, fatty acid dynamics, and the tumor microenvironment.

Instruction: Colorectal cancer (CRC) poses a challenge to public health and is characterized by a high incidence rate. This study explored the relationship between ferroptosis and fatty acid metabolism in the tumor microenvironment (TME) of patients with CRC to identify how these interactions impact the prognosis and effectiveness of immunotherapy, focusing on patient outcomes and the potential for predicting treatment response. Methods: Using datasets from multiple cohorts, including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we conducted an in-depth multi-omics study to uncover the relationship between ferroptosis regulators and fatty acid metabolism in CRC. Through unsupervised clustering, we discovered unique patterns that link ferroptosis and fatty acid metabolism, and further investigated them in the context of immune cell infiltration and pathway analysis. We developed the FeFAMscore, a prognostic model created using a combination of machine learning algorithms, and assessed its predictive power for patient outcomes and responsiveness to treatment. The FeFAMscore signature expression level was confirmed using RT-PCR, and ACAA2 progression in cancer was further verified. Results: This study revealed significant correlations between ferroptosis regulators and fatty acid metabolism-related genes with respect to tumor progression. Three distinct patient clusters with varied prognoses and immune cell infiltration were identified. The FeFAMscore demonstrated superior prognostic accuracy over existing models, with a C-index of 0.689 in the training cohort and values ranging from 0.648 to 0.720 in four independent validation cohorts. It also responses to immunotherapy and chemotherapy, indicating a sensitive response of special therapies (e.g., anti-PD-1, anti-CTLA4, osimertinib) in high FeFAMscore patients. Conclusion: Ferroptosis regulators and fatty acid metabolism-related genes not only enhance immune activation, but also contribute to immune escape. Thus, the FeFAMscore, a novel prognostic tool, is promising for predicting both the prognosis and efficacy of immunotherapeutic strategies in patients with CRC.

Development of a Novel Lipid Metabolism-related Gene Prognostic Signature for Patients with Colorectal Cancer.

BACKGROUND: The purpose of this study was to explore the expression profiles of lipid metabolism-related genes in patients with Colorectal Cancer (CRC). METHODS: The lipid metabolism statuses of CRC patients from The Cancer Genome Atlas (TCGA) were analyzed. Risk characteristics were constructed by univariate Cox regression and minimum Absolute contraction and Selection Operator (LASSO) Cox regression. A histogram was constructed based on factors such as age, sex, TNM stage, T stage, N stage, and risk score to provide a visual tool for clinicians to predict the probability of 1-year, 3-year, and 5-year OS for CRC patients. By determining Area Under Curve (AUC) values, the time-dependent Receiver Operating characteristic Curve (ROC) was used to evaluate the efficiency of our model in predicting prognosis. RESULTS: A novel risk signal based on lipid metabolism-related genes was constructed to predict the survival of CRC patients. Risk characteristics were shown to be an independent prognostic factor in CRC patients (p <0.001). There were significant differences in the abundance and immune characteristics of tumor-filtering immune cells between high-risk and low-risk groups. The nomogram had a high potential for clinical application and the ROC AUC value was 0.827. Moreover, ROC analysis demonstrated that the nomogram model was more accurate to predict the survival of CRC patients than age, gender, stage and risk score. CONCLUSION: In this study, we demonstrated a lipid metabolism-related genes prognosis biomarker associated with the tumor immune micro-environment in patients with CRC.

Prognostic Value of Tumor Deposits in Stage III Colorectal Cancer Patients with Different N Stages: A Population-Based, Retrospective, Cohort Study.

PURPOSE: Tumor deposits (TDs) seem to be associated with the prognosis of patients with colorectal cancer (CRC). The goal of this study was to investigate the prognostic value of TDs among patients with stage III CRC at different N stages. METHODS: A retrospective analysis was performed on two independent cohorts of stage III CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database (n = 8232) and the First Affiliated Hospital of Wenzhou Medical University (n = 423). Primary outcomes were overall survival (OS) and cancer-specific survival (CSS). RESULTS: Of 8232 patients in the SEER cohort, the presence of TDs revealed poorer 5-year OS rates and 5-year CSS rates in all N-stage subgroups. X-tile software identified 5 (5-year OS: P = 0.004; 5-year CSS: P < 0.001) as the optimal cutoff value for TD count in the TD-positive subgroup at the N2 stage. The OS (5-year OS: 62.0% vs. 42.0%, P < 0.001) and CSS (5-year CSS: 66.0% vs. 43.8%, P < 0.001) of patients with five or more TDs were significantly worse than those with one to four TDs in the N2 stage subgroups. Of 423 patients in the Wenzhou cohort, the 3-year OS rate for patients in the positive group was worse than that for patients in the negative group (88.7% vs. 94.3%, P = 0.015). CONCLUSIONS: TD count should be considered when evaluating the prognosis of patients with the N2 stage. Those with higher TD counts (≥ 5) might have a worse prognosis.