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Purpose Determine the localized expression pattern and clinical significance of VISTA/PD-1H in human NSCLC. Experimental Design Using multiplex quantitative immunofluorescence (QIF), we performed localized measurements of VISTA, PD-1 and PD-L1 protein in 758 stage I-IV NSCLCs from 3 independent cohorts represented in tissue microarray format. The targets were selectively measured in cytokeratin+ tumor epithelial cells, CD3+ T-cells, CD4+ T-helper cells, CD8+ cytotoxic T-cells, CD20+ B-lymphocytes and CD68+ tumor-associated macrophages. We determined the association between the targets, clinico-pathological/molecular variables and survival. Genomic analyses of lung cancer cases from TCGA was also performed. Results VISTA protein was detected in 99% of NSCLCs with a predominant membranous/cytoplasmic staining pattern. Expression in tumor and stromal cells was seen in 21% and 98% of cases, respectively. The levels of VISTA were positively associated with PD-L1, PD-1, CD8+ T-cells and CD68+ macrophages. VISTA expression was higher in T-lymphocytes than in macrophages; and in cytotoxic T-cells than in T-helper cells. Elevated VISTA was associated with absence of EGFR mutations and lower mutational burden in lung adenocarcinomas. Presence of VISTA in tumor compartment predicted longer 5-year survival. Conclusions VISTA is frequently expressed in human NSCLC and shows association with increased TILs, PD-1 axis markers, specific genomic alterations and outcome. These results support the immuno-modulatory role of VISTA in human NSCLC and suggests its potential as therapeutic target.

BackgroundsUterine corpus endometrial carcinoma (UCEC) is one of the greatest threats on the female reproductive system. The aim of this study is to explore the inflammation-related LncRNA (IRLs) signature predicting the clinical outcomes and response of UCEC patients to immunotherapy and chemotherapy.MethodsConsensus clustering analysis was employed to determine inflammation-related subtype. Cox regression methods were used to unearth potential prognostic IRLs and set up a risk model. The prognostic value of the prognostic model was calculated by the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate analyses. Differential abundance of immune cell infiltration, expression levels of immunomodulators, the status of tumor mutation burden (TMB), the response to immune checkpoint inhibitors (ICIs), drug sensitivity, and functional enrichment in different risk groups were also explored. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the expression patterns of model IRLs in clinical specimens.ResultsAll UCEC cases were divided into two clusters (C1 = 454) and (C2 = 57) which had significant differences in prognosis and immune status. Five hub IRLs were selected to develop an IRL prognostic signature (IRLPS) which had value in forecasting the clinical outcome of UCEC patients. Biological processes related to tumor and immune response were screened. Function enrichment algorithm showed tumor signaling pathways (ERBB signaling, TGF-β signaling, and Wnt signaling) were remarkably activated in high-risk group scores. In addition, the high-risk group had a higher infiltration level of M2 macrophages and lower TMB value, suggesting patients with high risk were prone to a immunosuppressive status. Furthermore, we determined several potential molecular drugs for UCEC.ConclusionWe successfully identified a novel molecular subtype and inflammation-related prognostic model for UCEC. Our constructed risk signature can be employed to assess the survival of UCEC patients and offer a valuable reference for clinical treatment regimens.

BackgroundsLung adenocarcinoma (LUAD) is the most common subtype of lung cancer, which is the leading cause of cancer death. Dysregulation of cell proliferation and death plays a crucial role in the development of LUAD. As of recently, the role of a new form of cell death, cuproptosis, and it has attracted more and more attention. As of yet, it is not clear whether cuproptosis is involved in the progression of LUAD.MethodsAn integrated set of bioinformatics tools was utilized to analyze the expression and prognostic significance of cuproptosis-related genes. Meanwhile, a robust risk signature was developed using machine learning based on prognostic cuproptosis-related genes and explored the value of prognostic cuproptosis-related signature for clinical applications, functional enrichment and immune landscape. Lastly, the dysregulation of the cuproptosis-related genes in LUAD was validated by in vitro experiment.ResultsIn this study, first, cuproptosis-related genes were found to be differentially expressed in LUAD patients of public databases, and nine of them had prognostic value. Next, a cuproptosis-related model with five features (DLTA, MTF1, GLS, PDHB and PDHA1) was constructed to separate the patients into high- and low-risk groups based on median risk score. Internal validation set and external validation set were used for model validation and evaluation. What’s more, Enrichment analysis of differential genes and the WGCNA identified that cuproptosis-related signatures affected tumor prognosis by influencing tumor immunity. Small molecule compounds were predicted based on differential expressed genes to improve poor prognosis in the high-risk group and a nomogram was constructed to further advance clinical applications. In closing, our data showed that FDX1 affected the prognosis of lung cancer by altering the expression of cuproptosis-related signature.ConclusionA new cuproptosis-related signature for survival prediction was constructed and validated by machine learning algorithm and in vitro experiments to reflect tumor immune infiltration in LUAD patients. The purpose of this article was to provide a potential diagnostic and therapeutic strategy for LUAD.

As the most common gastrointestinal malignancy, colorectal cancer (CRC) remains a leading cause of cancer death worldwide. Although multimodal chemotherapy has effectively improved the prognosis of patients with CRC in recent years, severe chemotherapy-associated side effects and chemoresistance still greatly impair efficacy and limit its clinical application. In response to these challenges, an increasing number of traditional Chinese medicines have been used as synergistic agents for CRC administration. In particular, ginseng, quercetin, and tea, three common dietary supplements, have been shown to possess the potent capacity of enhancing the sensitivity of various chemotherapy drugs and reducing their side effects. Ginseng, also named “the king of herbs”, contains a great variety of anti-cancer compounds, among which ginsenosides are the most abundant and major research objects of various anti-tumor studies. Quercetin is a flavonoid and has been detected in multiple common foods, which possesses a wide range of pharmacological properties, especially with stronger anti-cancer and anti-inflammatory effects. As one of the most consumed beverages, tea has become particularly prevalent in both West and East in recent years. Tea and its major extracts, such as catechins and various constituents, were capable of significantly improving life quality and exerting anti-cancer effects both in vivo and in vitro. In this review, we mainly focused on the adjunctive effects of the three herbs and their constituents on the chemotherapy process of CRC.