Extracellular matrix stiffness and tumor-associated macrophage polarization: new fields affecting immune exclusion.

In the malignant progression of tumors, there is deposition and cross-linking of collagen, as well as an increase in hyaluronic acid content, which can lead to an increase in extracellular matrix stiffness. Recent research evidence have shown that the extracellular matrix plays an important role in angiogenesis, cell proliferation, migration, immunosuppression, apoptosis, metabolism, and resistance to chemotherapeutic by the alterations toward both secretion and degradation. The clinical importance of tumor-associated macrophage is increasingly recognized, and macrophage polarization plays a central role in a series of tumor immune processes through internal signal cascade, thus regulating tumor progression. Immunotherapy has gradually become a reliable potential treatment strategy for conventional chemotherapy resistance and advanced cancer patients, but the presence of immune exclusion has become a major obstacle to treatment effectiveness, and the reasons for their resistance to these approaches remain uncertain. Currently, there is a lack of exact mechanism on the regulation of extracellular matrix stiffness and tumor-associated macrophage polarization on immune exclusion. An in-depth understanding of the relationship between extracellular matrix stiffness, tumor-associated macrophage polarization, and immune exclusion will help reveal new therapeutic targets and guide the development of clinical treatment methods for advanced cancer patients. This review summarized the different pathways and potential molecular mechanisms of extracellular matrix stiffness and tumor-associated macrophage polarization involved in immune exclusion and provided available strategies to address immune exclusion.

Prognostic model for the prediction of cancer-specific survival in elderly patients with stage I-III gastric cancer.

Elderly patients with gastric cancer (GC) exhibit unique physiological conditions and population characteristics. However, no efficient predictive tools have been developed for this patient subgroup. We extracted data on elderly patients diagnosed with stage I-III GC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database, and applied Cox regression analysis to examine factors associated with cancer-specific survival (CSS). A prognostic model was developed and validated to predict CSS. We assessed the performance of the prognostic model and stratified patients based on their prognostic scores. Notably, 11 independent prognostic factors, including age, race, grade, the tumor-node-metastasis (TNM) stage, T-stage, N-stage, operation, tumor size, regional nodes, radiation, and chemotherapy, associated with CSS were identified using multivariate Cox regression. A nomogram was constructed based on these predictors. The C-index score of the nomogram was 0.802 (95% (confidence interval) [CI]: 0.7939-0.8114), which is superior to the American Joint Commission on Cancer (AJCC) TNM staging prediction ability in the training cohort (C-index: 0.589; 95% CI: 0.5780-0.6017). Based on the receiver operating characteristic (ROC) and calibration curve, the predicted value of the nomogram demonstrated a satisfactory accuracy with the actual observation value. Additionally, decision curve analysis (DCA) showed that the nomogram had a more ideal clinical net benefit than TNM staging. Survival analysis of the different risk groups confirmed the noteworthy clinical and statistical utility of the nomogram in prognosis stratification. This retrospective study reports the successful creation and validation of a nomogram for predicting CSS at 1-, 3- and 5-years in elderly patients with stage I-III GC. This nomogram critically guides personalized prognostic assessments and may contribute to clinical decision-making and consultation for postoperative survival.

Socioeconomic deprivation and survival outcomes in patients with colorectal cancer.

Socioeconomic deprivation has been linked to detrimental healthcare outcomes. We sought to examine whether patients with colorectal cancer (CRC) from socioeconomically disadvantaged areas experience worse survival outcomes and how it interacts with other factors. In this population-based study, patients with CRC diagnosed between 2007 to 2015 in the SEER program were reviewed. Socioeconomic deprivation was measured using the Area Deprivation Index (ADI) linked to patients' residence addresses. The effect of ADI on cancer-specific survival and overall survival was evaluated using survival analysis. The Inverse Probability of Weighted (IPW) method and multiple regression was performed to account for the confounding bias. Subgroup analyses were used to test interactions. Multiple mediation analysis was used to estimate the mediating effects. Overall, 266,620 eligible patients were included in further analyses. Compared with low ADI patients, high ADI patients had more unfavorable characteristics and worse cancer-specific (hazard ratio [HR] 1.14, 95% CI 1.12-1.16, P<.001) and overall survival (HR 1.11, 95% CI 1.09-1.12, P<0.001). The results were similar after accounting for confounding factors using the IPW and multiple regression methods. Subgroup analyses revealed the relative robustness of ADI as a prognostic factor. They detected significant interactions between ADI and other covariates on cancer survival, such as age, race, insurance status, disease stage, and receipt of treatment. Multiple mediation analyses identified several factors mediating survival disparities, including anticancer therapy, insurance status, race, marital status, and age. This study suggested that high ADI CRC patients were associated with more unfavorable characteristics at presentation and lower cancer and noncancer survival after treatment than their low ADI counterparts. Multiple factors interacted and mediated these survival disparities associated with the ADI.