Xingchen Peng

Peripheral and tumor‐infiltrating immune cells are correlated with patient outcomes in ovarian cancer

AbstractObjectiveAt present, there is still a lack of reliable biomarkers for ovarian cancer (OC) to guide prognosis prediction and accurately evaluate the dominant population of immunotherapy. In recent years, the relationship between peripheral blood markers and tumor‐infiltrating immune cells (TICs) with cancer has attracted much attention. However, the relationship between the survival of OC patients and intratumoral‐ or extratumoral‐associated immune cells remains controversial.MethodsIn this study, four machine‐learning algorithms were used to predict overall survival in OC patients based on peripheral blood indicators. To further screen out immune‐related gene and molecular targets, we systematically explored the correlation between TICs and OC patient survival based on The Cancer Genome Atlas database. Using the TICs score method, patients were divided into a low immune infiltrating cell group and a high immune infiltrating cell group.ResultsThe results showed that there was a significant statistical significance between the peripheral blood indicators and the survival prognosis of OC patients. Survival analysis showed that TICs play a crucial role in the survival of OC patients. Four core genes, CXCL9, CD79A, MS4A1, and MZB1, were identified by cross‐PPI and COX regression analysis. Further analysis found that these genes were significantly associated with both TICs and survival in OC patients.ConclusionsThese results suggest that both peripheral blood markers and TICs can be used as prognostic predictors in patients with OC, and CXCL9, CD79A, MS4A1, and MZB1 may be potential therapeutic targets for OC immunotherapy.

Survival outcomes following treatment delays among patients with early-stage female cancers: a nationwide study

Abstract Background The coronavirus disease 2019 (COVID-19) severely hindered the timely receipt of health care for patients with cancer, especially female patients. Depression and anxiety were more pronounced in female patients than their male counterparts with cancer during treatment wait-time intervals. Herein, investigating the impact of treatment delays on the survival outcomes of female patients with early-stage cancers can enhance the rational and precise clinical decisions of physicians. Methods We analyzed five types of cancers in women from the Surveillance, Epidemiology, and End Results (SEER) program between Jan 2010 and Dec 2015. Univariate and multivariate Cox regression analyses were used to determine the impacts of treatment delays on the overall survival (OS) and cancer-specific survival (CSS) of the patients. Results A total of 241,661 females with early-stage cancer were analyzed (12,617 cases of non-small cell lung cancer (NSCLC), 166,051 cases of infiltrating breast cancer, 31,096 cases of differentiated thyroid cancer, 23,550 cases of colorectal cancer, and 8347 cases of cervical cancer). Worse OS rates were observed in patients with treatment delays ≥ 3 months in stage I NSCLC (adjustedHazard ratio (HR) = 1.11, 95% Confidence Interval (CI): 1.01–1.23, p = 0.044) and stage I infiltrating breast cancer (adjustedHR = 1.23, 95% CI 1.11–1.37, p < 0.001). When the treatment delay intervals were analyzed as continuous variables, similar results were observed in patients with stage I NSCLC (adjustedHR = 1.04, 95% CI 1.01–1.06, p = 0.010) and in those with stage I breast cancer (adjustedHR = 1.03, 95% CI 1.00–1.06, p = 0.029). However, treatment delays did not reduce the OS of patients with differentiated thyroid cancer, cervical cancer, or colorectal cancer in the early-stage. Only intermediate treatment delays impaired the CSS of patients with cervical cancer in stage I (adjustedHR = 1.31, 95% CI 1.02–1.68, p = 0.032). Conclusion After adjusting for confounders, the prolonged time from diagnosis to the initiation of treatment (< 6 months) showed limited negative effects on the survival of most of the patients with early-stage female cancers. Whether our findings serve as evidence supporting the treatment deferral decisions of clinicians for patients with different cancers in resource-limited situations needs further validation.