Introduction: Disparities in the incidence, mortality, and survival of cancer types between urban and rural areas in China reflect the effects of different risk factor exposure, education, and different medical availability. We aimed to characterize the disparities in the incidence, mortality, and survivals of cancer types between urban and rural areas in Shanghai, China, 2002-2015. Materials and Methods: The incidence and mortality were standardized by Segi's world standard population. Trends in the incidence and mortality of cancers were compared using annual percent change. The 5-year observed and relative survivals were calculated with life table and Ederer II methods. Results: Age-standardized incidences and mortalities were 212.55/105 and 109.45/105 in urban areas and 210.14/105 and 103.99/105 in rural areas, respectively. Female breast cancer and colorectal cancer occurred more frequently in urban than in rural areas, quite in contrast to liver cancer and cervical cancer. Cancers of lung and bronchus, liver, stomach, and colon and rectum were the leading causes of cancer death in both areas. Age-standardized incidence of female breast cancer and colorectal cancer in urban areas increased while gastric cancer and liver cancer decreased in both areas. Age-standardized mortalities of cancers of breast, esophagus, stomach, colon and rectum, liver, and lung and bronchus decreased in both areas. For all cancers combined, the 5-year observed and relative survivals of cancer patients were higher in urban than in rural areas. The 5-year observed and relative survivals of cancers of liver, pancreas, stomach, brain and central nervous system (CNS), and prostate were higher in urban than in rural areas. The 5-year observed and relative survivals of cervical cancer were higher in rural than in urban areas. Conclusions: Factors promoting female breast cancer and colorectal cancer in urban areas and liver cancer and cervical cancer in rural areas should be specifically intervened in cancer prophylaxis. Improved medical services can greatly prolong the survival of major cancers in rural areas.

Immunotherapy has become the most promising therapy in digestive system tumors besides conventional chemotherapy and radiotherapy. But only a few patients can benefit from different types of immunotherapies, such as immune checkpoint blockade (ICB). To identify these ICB-susceptible patients, methods are urgently needed to screen and profile subgroups of patients with different responsiveness to ICB.

Objectives: We used radiomic analysis to establish a radiomic signature based on preoperative contrast enhanced computed tomography (CT) and explore its effectiveness as a novel recurrence risk prognostic marker for advanced high-grade serous ovarian cancer (HGSOC). Methods: This study had a retrospective multicenter (two hospitals in China) design and a radiomic analysis was performed using contrast enhanced CT in advanced HGSOC (FIGO stage III or IV) patients. We used a minimum 18-month follow-up period for all patients (median 38.8 months, range 18.8-81.8 months). All patients were divided into three cohorts according to the timing of their surgery and hospital stay: training cohort (TC) and internal validation cohort (IVC) were from one hospital, and independent external validation cohort (IEVC) was from another hospital. A total of 620 3-D radiomic features were extracted and a Lasso-Cox regression was used for feature dimension reduction and determination of radiomic signature. Finally, we combined the radiomic signature with seven common clinical variables to develop a novel nomogram using a multivariable Cox proportional hazards model. Results: A final 142 advanced HGSOC patients were enrolled. Patients were successfully divided into two groups with statistically significant differences based on radiomic signature, consisting of four radiomic features (log-rank test P = 0.001, <0.001, <0.001 for TC, IVC, and IEVC, respectively). The discrimination accuracies of radiomic signature for predicting recurrence risk within 18 months were 82.4% (95% CI, 77.8-87.0%), 77.3% (95% CI, 74.4-80.2%), and 79.7% (95% CI, 73.8-85.6%) for TC, IVC, and IEVC, respectively. Further, the discrimination accuracies of radiomic signature for predicting recurrence risk within 3 years were 83.4% (95% CI, 77.3-89.6%), 82.0% (95% CI, 78.9-85.1%), and 70.0% (95% CI, 63.6-76.4%) for TC, IVC, and IEVC, respectively. Finally, the accuracy of radiomic nomogram for predicting 18-month and 3-year recurrence risks were 84.1% (95% CI, 80.5-87.7%) and 88.9% (95% CI, 85.8-92.5%), respectively. Conclusions: Radiomic signature and radiomic nomogram may be low-cost, non-invasive means for successfully predicting risk for postoperative advanced HGSOC recurrence before or during the perioperative period. Radiomic signature is a potential prognostic marker that may allow for individualized evaluation of patients with advanced HGSOC.

Anti-PD-1 therapy has been approved for cancer treatment. However, the response rate is unsatisfactory. The expression of PD-L1 in tumor tissues is unreliable to predict the treatment response. Recent studies have suggested that exosomal PD-L1 not only exerts immunosuppressive effects but also plays a significant role in the development of tumor microenvironment. Thus, the present study aims to investigate exosomal PD-L1 in improving its predictive value and efficacy. A total of 44 patients of advanced tumors of several types, treated with anti-PD-1 therapy, were enrolled. Exosomes were collected and purified from plasma. The exosomal PD-L1 was detected with ELISA. The cytokines were measured with the MILLIPLEX magnetic bead assay. Compared to the responders, exosomal PD-L1 of the non-responders was significantly higher than that of the responders (P = 0.010) before the treatment. Concurrently, exosomal PD-L1 and tumor burden decreased when the therapy was effective. And, the baseline expression of CD28 was higher in the responders than that in the non-responders (P = 0.005). Univariate and multivariate analyses validated with 1,000 times bootstrapping suggested that high exosomal PD-L1 and low CD28 expressions were negative factors for progression-free survival (PFS) of the patients who underwent anti-PD-1 treatment. The combination of exosomal PD-L1 and CD28 obtained more area under the curve (AUC) of receiver operating characteristic (ROC) (AUC 0.850 vs. 0.784 vs. 0.678) and showed a higher probability of no progression via nomograph. These findings suggested that the expression of exosomal PD-L1 and CD28 could serve as the predictive biomarkers for clinical responses to anti-PD-1 treatment.

The immune microenvironment is important for the development, progression, and prognosis of anaplastic glioma (AG). This complex milieu has not been fully elucidated, and a high-dimensional analysis is urgently required. Utilizing mass cytometry (CyTOF), we performed an analysis of immune cells from 5 patients with anaplastic astrocytoma, IDH-mutant (AAmut) and 10 patients with anaplastic oligodendroglioma, IDH-mutant and 1p/19q codeletion (AOD) and their paired peripheral blood mononuclear cells (PBMCs). Based on a panel of 33 biomarkers, we demonstrated the tumor-driven immune changes in the AG immune microenvironment. Our study confirmed that mononuclear phagocytes and T cells are the most abundant immunocytes in the AG immune microenvironment. Glioma-associated microglia/macrophages in both AAmut and AOD samples showed highly immunosuppressive characteristics. Compared to those in the PBMCs, the ratios of immune checkpoint-positive exhausted CD4+ T cells and CD8+ T cells were higher at the AG tumor sites. The AAmut immune milieu exhibits more immunosuppressive characteristics than that in AOD.

Purpose: The present study aimed to evaluate the performance of radiomics features in the preoperative prediction of epileptic seizure following surgery in patients with LGG. Methods: This retrospective study collected 130 patients with LGG. Radiomics features were extracted from the T2-weighted MR images obtained before surgery. Multivariable Cox-regression with two nested leave-one-out cross validation (LOOCV) loops was applied to predict the prognosis, and elastic net was used in each LOOCV loop to select the predictive features. Logistic models were then built with the selected features to predict epileptic seizures at two time points. Student's t-tests were then used to compare the logistic model predicted probabilities of developing epilepsy in the epilepsy and non-epilepsy groups. The t-test was used to identify features that differentiated patients with early-onset epilepsy from their late-onset counterparts. Results: Seventeen features were selected with the two nested LOOCV loops. The index of concordance (C-index) of the Cox model was 0.683, and the logistic model predicted probabilities of seizure were significantly different between the epilepsy and non-epilepsy groups at each time point. Moreover, one feature was found to be significantly different between the patients with early- or late-onset epilepsy. Conclusion: A total of 17 radiomics features were correlated with postoperative epileptic seizures in patients with LGG and one feature was a significant predictor of the time of epilepsy onset.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has received extensive attention as a cancer therapeutic due to its high propensity for tumor targeting with minimal toxicity to healthy tissue. Gastric cancer (GCa) cells show high levels of TRAIL resistance. Epidermal growth factor receptor (EGFR) antagonizes TRAIL-induced apoptosis, but the mechanisms of these effects remain unclear. Our past research confirmed TRAIL-resistant (BGC823 and SGC7901) and TRAIL-sensitive cells (HGC27 and MKN45). miR-429 associated with TRAIL sensitivity was screened using microRNA arrays. The transfection of mimics and inhibitors confirmed that miR-429 negatively correlated with GCa TRAIL resistance. The target gene of miR-429 was identified as PD-L1, which positively correlated with TRAIL resistance through gene silencing and recovery experiments. Using co-immunoprecipitation (co-IP) and proximity ligation assay, we demonstrated that the pro-survival effects of PD-L1 are mediated through the binding and activation of EGFR. Cell viability experiments demonstrated that PD-L1 is key to the maintenance of cell viability in TRAIL-treated cells. This indicated that PD-L1 binds to and participates in EGFR activation through miR-429 regulation to antagonize TRAIL-induced apoptosis. This provides a new theoretical basis for the combination of the EGFR monoclonal antibodies including cetuximab, PD-L1 inhibitors, and human recombinant TRAIL in gastric cancer therapy and can filter patients who are currently sensitive to TRAIL treatment.

This study focused on the expression of mitochondrial serine hydroxymethyltransferase (SHMT2) in oral squamous cell carcinoma (OSCC) and its correlation with clinical traits and the prognosis of OSCC patients. Immunochemical staining and Western blotting were used to quantify the expression of SHMT2 and related immune markers in OSCC. Using OSCC microarrays and The Cancer Genome Atlas (TCGA) database, we evaluated the association between SHMT2 and various clinical traits. We found that increased expression of SHMT2 was detected in OSCC and correlated with advanced pathological grade and recurrence of OSCC. By a multivariate Cox proportional hazard model, high expression of SHMT2 was shown to indicate a negative prognosis. In addition, in the OSCC microenvironment, increasing the expression of SHMT2 was associated with high expression levels of programmed cell death-ligand 1 (PD-L1), CKLF-like MARVEL transmembrane domain containing 6 (CMTM6), V-type immunoglobulin domain-containing suppressor (VISTA), B7-H4, Slug, and CD317. In the future, more effort will be required to investigate the role of SHMT2 in the OSCC microenvironment.

Purpose: MicroRNAs are known to regulate cellular processes in non-small cell lung cancer (NSCLC) cells and predict prognosis. However, identification of specific microRNAs in NSCLC as potential therapeutic targets is controversial. We aim to determine the clinical significance of miR-1323 in the prognosis of patients with lung cancer and the potential mechanism. Patients and methods: A bioinformatics approach was used to screen the importance microRNA in NSCLC through the online GEO database (GSE42425). The relationship between expression level of miR-1323 and overall survival of lung cancer patients was analyzed. Additionally, an independent corhort including 53 NSCLC cases that underwent resection validated the connection between miR-1323 and LUAD patients' overall survival. Next, the function of miR-1323 was studied in vitro by transient transfection. A more in-depth mechanism was studied through luciferase reporter gene experiments. Results: High miR-1323 expression correlated with poor survival in NSCLC patients (P = 0.011), and in lung adenocarcinoma (LUAD) patients (P = 0.015) based on GEO database (GSE42425). In the independent cohort based on our hospital, high miR-1323 expression was associated with LUAD patients (P = 0.025). Moreover, transfection with mimics of miR-1323 showed an increased migratory capacity in LUAD A549 and HCC827 cells. In addition, E3 ubiquitin-protein ligase Casitas B-lineage Lymphoma-b (Cbl-b) was found to be the target genes of miR-1323 and significantly down regulated after mimics of miR-1323 transfection, and high Cbl-b expression predicted better prognosis in NSCLC and LUAD (P = 0.00072 and P = 0.02, respectively). Conclusion: The miR-1323 promoted LUAD migration through inhibiting Cbl-b expression. High miR-1323 expression predicted poor prognosis in LUAD patients.

Targeting androgen receptor (AR) has been shown to be promising in treating glioblastoma (GBM) in cell culture and flank implant models but the mechanisms remain unclear. AR antagonists including enzalutamide are available for treating prostate cancer patients in clinic and can pass the blood-brain barrier, thus are potentially good candidates for GBM treatment but have not been tested in GBM orthotopically. Our current studies confirmed that in patients, a majority of GBM tumors overexpress AR in both genders. Enzalutamide inhibited the proliferation of GBM cells both in vitro and in vivo. Although confocal microscopy demonstrated that AR is expressed but not specifically in glioma cancer stem cells (CSCs) (CD133+), enzalutamide treatment significantly decreased CSC population in cultured monolayer cells and spheroids, suppressed tumor sphere-forming capacity of GBM cells, and downregulated CSC gene expression at mRNA and protein levels in a dose- and time-dependent manner. We have, for the first time, demonstrated that enzalutamide treatment decreased the density of CSCs in vivo and improved survival in an orthotopic GBM mouse model. We conclude that AR antagonists potently target glioma CSCs in addition to suppressing the overall proliferation of GBM cells as a mechanism supporting their repurposing for clinical applications treating GBM.

Although the cytotoxic chemotherapeutic agent 5-fluorouracil (5-FU) is generally considered to directly kill cancer cells and exert immunostimulatory effects in advanced gastric cancer, accumulating evidence indicates that it upregulates the expression of PD-L1, a representative immune checkpoint blockade molecule involved in negative regulation of the immune response. It was reported that exosomes could transfer functional PD-L1 locally and distantly to suppress the antitumor immune response. However, whether 5-FU alters the expression of exosomal PD-L1 and induces immunosuppression in gastric cancer remains unclear. Herein, we found that 5-FU increased gastric cancer-derived exosomal PD-L1. Importantly, compared with baseline levels, circulating exosomal PD-L1 was significantly upregulated in 21 stage III-IV gastric cancer patients after two, four, and six repeated cycles of fluoropyrimidine treatment (P = 0.009, P = 0.047, and P = 0.023, respectively), accompanied by decreased amounts of IFN-γ, TNF-α, IL-2, IL-6, and GM-CSF (P = 0.014, P = 0.004, P = 0.009, P = 0.031, and P = 0.014, respectively). Additionally, circulating exosomal PD-L1 was increased more significantly in clinical non-responders compared with responders (P = 0.018). Furthermore, exosomal PD-L1 induced apoptosis in Jurkat T cells and inhibited T cell activation in PBMCs, which could be partly reversed by nivolumab. These results suggested that 5-FU-induced upregulation of exosomal PD-L1 causes systemic immunosuppression in advanced gastric cancer following multiple cycles of chemotherapy, especially after two cycles.

Purpose: We aimed to analyze 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images via the radiomic method to develop a model and validate the potential value of features reflecting glioma metabolism for predicting isocitrate dehydrogenase (IDH) genotype and prognosis. Methods: PET images of 127 patients were retrospectively analyzed. A series of quantitative features reflecting the metabolic heterogeneity of the tumors were extracted, and a radiomic signature was generated using the support vector machine method. A combined model that included clinical characteristics and the radiomic signature was then constructed by multivariate logistic regression to predict the IDH genotype status, and the model was evaluated and verified by receiver operating characteristic (ROC) curves and calibration curves. Finally, Kaplan-Meier curves and log-rank tests were used to analyze overall survival (OS) according to the predicted result. Results: The generated radiomic signature was significantly associated with IDH genotype (p < 0.05) and could achieve large areas under the ROC curve of 0.911 and 0.900 on the training and validation cohorts, respectively, with the incorporation of age and type of tumor metabolism. The good agreement of the calibration curves in the validation cohort further validated the efficacy of the constructed model. Moreover, the predicted results showed a significant difference in OS between high- and low-risk groups (p < 0.001). Conclusions: Our results indicate that the 18F-FDG metabolism-related features could effectively predict the IDH genotype of gliomas and stratify the OS of patients with different prognoses.