Impact of tumor size on overall survival and cancer-specific survival of early-onset colon and rectal cancer: a retrospective cohort study.

PURPOSE: This study aimed to investigate the impact of tumor size on survival in early-onset colon and rectal cancer. METHODS: Early-onset colon and rectal cancer patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Tumor size was analyzed as both continuous and categorical variables. Several statistical techniques, including restricted cubic spline (RCS), Cox proportional hazard model, subgroup analysis, propensity score matching (PSM), and Kaplan-Meier survival analysis, were employed to demonstrate the association between tumor size and overall survival (OS) and cancer-specific survival (CSS) of early-onset colon and rectal cancer. RESULTS: Seventeen thousand five hundred fifty-one (76.7%) early-onset colon and 5323 (23.3%) rectal cancer patients were included. RCS analysis confirmed a linear association between tumor size and survival. Patients with a tumor size > 5 cm had worse OS and CSS, compared to those with a tumor size ≤ 5 cm for both early-onset colon and rectal cancer. Notably, subgroup analysis showed that a smaller tumor size (≤ 50 mm) was associated with worse survival in stage II early-onset colon cancer, although not statistically significant. After PSM, Kaplan-Meier survival curves showed that the survival of patients with tumor size ≤ 50 mm was better than that of patients with tumor size > 50 mm. CONCLUSION: Patients with tumors larger than 5 cm were associated with worse survival in early-onset colon and rectal cancer. However, smaller tumor size may indicate a more biologically aggressive phenotype, correlating with poorer survival in stage II early-onset colon cancer.

Construction and validation of a nomogram for predicting overall survival of patients with stage III/IV early-onset colorectal cancer.

Purpose: This study aimed to identify prognostic factors and develop a nomogram for predicting overall survival (OS) in stage III/IV early-onset colorectal cancer (EO-CRC). Methods: Stage III/IV EO-CRC patients were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The datasets were randomly divided (2:1) into training and validation sets. A nomogram predicting OS was developed based on the prognostic factors identified by Cox regression analysis in the training cohort. Moreover, the predictive performance of the nomogram was assessed using the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Subsequently, the internal validation was performed using the validation cohort. Finally, a risk stratification system was established based on the constructed nomogram. Results: Of the 10,387 patients diagnosed with stage III/IV EO-CRC between 2010 and 2015 in the SEER database, 8,130 patients were included. In the training cohort (n=3,071), sex, marital status, race/ethnicity, primary site, histologic subtypes, grade, T stage, and N stage were identified as independent prognostic variables for OS. The 1-, 3-, and 5-year area under the curve (AUC) values of the nomogram were robust in both the training (0.751, 0.739, and 0.723) and validation cohorts (0.748, 0.733, and 0.720). ROC, calibration plots, and DCA indicated good predictive performance of the nomogram in both the training and validation sets. Furthermore, patients were categorized into low-, middle-, and high-risk groups based on the nomogram risk score. Kaplan-Meier curve showed significant survival differences between the three groups. Conclusion: We developed a prognostic nomogram and risk stratification system for stage III/IV EO-CRC, which may facilitate clinical decision-making and individual prognosis prediction.

Prognostic impact of tumor size on patients with metastatic colorectal cancer: a large SEER-based retrospective cohort study.

Given the poor prognosis of metastatic colorectal cancer (mCRC), this research aimed to investigate the correlation between tumor size and prognosis, and develop a novel prediction model to guide individualized treatment. Patients pathologically diagnosed with mCRC were recruited from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and were randomly divided (7:3 ratio) into a training cohort (n = 5597) and a validation cohort (n = 2398). Kaplan-Meier curves were used to analyze the relationship between tumor size and overall survival (OS). Univariate Cox analysis was applied to assess the factors associated with the prognosis of mCRC patients in the training cohort, and then multivariate Cox analysis was used to construct a nomogram model. The area under the receiver-operating characteristics curve (AUC) and calibration curve were used to evaluate the predictive ability of the model. Patients with larger tumors had a worse prognosis. While brain metastases were associated with larger tumors compared to liver or lung metastases, bone metastases tended to be associated with smaller tumors. Multivariate Cox analysis revealed that tumor size was an independent prognostic risk factor (HR 1.28, 95% CI 1.19-1.38), in addition to the other ten variables (age, race, primary site, grade, histology, T stage, N stage, chemotherapy, CEA level and metastases site). The 1-, 3-, and 5-year OS nomogram model yielded AUC values of more than 0.70 in both the training and validation cohorts, and its predictive performance was superior to that of the traditional TNM stage. Calibration plots demonstrated a good agreement between the predicted and observed 1-, 3-, and 5-year OS outcomes in both cohorts. The size of primary tumor was found to be significantly associated with prognosis of mCRC, and was also correlated with specific metastatic organ. In this study, we presented the first effort to create and validate a novel nomogram for predicting 1-, 3- and 5-year OS probabilities of mCRC. The prognostic nomogram was demonstrated to have an excellent predictive ability in estimating individualized OS of patients with mCRC.

Roles of macrophages on ulcerative colitis and colitis-associated colorectal cancer.

Colitis-associated colorectal cancer is the most serious complication of ulcerative colitis. Long-term chronic inflammation increases the incidence of CAC in UC patients. Compared with sporadic colorectal cancer, CAC means multiple lesions, worse pathological type and worse prognosis. Macrophage is a kind of innate immune cell, which play an important role both in inflammatory response and tumor immunity. Macrophages are polarized into two phenotypes under different conditions: M1 and M2. In UC, enhanced macrophage infiltration produces a large number of inflammatory cytokines, which promote tumorigenesis of UC. M1 polarization has an anti-tumor effect after CAC formation, whereas M2 polarization promotes tumor growth. M2 polarization plays a tumor-promoting role. Some drugs have been shown to that prevent and treat CAC effectively by targeting macrophages.

Roles of RNA Methylation on Tumor Immunity and Clinical Implications.

RNA methylation is a kind of RNA modification that exists widely in eukaryotes and prokaryotes. RNA methylation occurs not only in mRNA but also in ncRNA. According to the different sites of methylation, RNA methylation includes m6A, m5C, m7G, and 2-O-methylation modifications. Modifications affect the splicing, nucleation, stability and immunogenicity of RNA. RNA methylation is involved in many physiological and pathological processes. In the immune system, especially for tumor immunity, RNA methylation affects the maturation and response function of immune cells. Through the influence of RNA immunogenicity and innate immune components, modifications regulate the innate immunity of the body. Some recent studies verified that RNA methylation can regulate tumor immunity, which also provides a new idea for the future of treating immunological diseases and tumor immunotherapy.