Negative checkpoint regulators (NCRs) temper the T cell immune response to self-antigens and limit the development of autoimmunity. Unlike all other NCRs that are expressed on activated T lymphocytes, V-type immunoglobulin domain-containing suppressor of T cell activation (VISTA) is expressed on naïve T cells. We report an unexpected heterogeneity within the naïve T cell compartment in mice, where loss of VISTA disrupted the major quiescent naïve T cell subset and enhanced self-reactivity. Agonistic VISTA engagement increased T cell tolerance by promoting antigen-induced peripheral T cell deletion. Although a critical player in naïve T cell homeostasis, the ability of VISTA to restrain naïve T cell responses was lost under inflammatory conditions. VISTA is therefore a distinctive NCR of naïve T cells that is critical for steady-state maintenance of quiescence and peripheral tolerance.

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Background Lung cancer is associated with the highest mortality rate of all cancer types, and the most common histological subtype of lung cancer is adenocarcinoma. In order to apply more effective therapeutic treatment, molecular markers that are able to predict the recurrence risk of patients with adenocarcinoma are critically needed. Mutations in TP53 tumor suppressor gene have been found in approximately 50% of lung adenocarcinoma cases, but the presence of a TP53 mutation does not always associate with increased mortality. Methods The Cancer Genome Atlas (TCGA) RNA-seq data of lung adenocarcinoma were used to define a novel gene signature for P53 deficiency. This signature was then used to calculate a sample-specific P53-deficiency score based on a patient’s transcriptomic profile and tested in four independent lung adenocarcinoma microarray datasets. Results In all datasets, P53-deficiency score was a significant predictor for recurrence-free survival where high P53-deficiency score was associated with poor survival. The score was prognostic even after adjusting for several key clinical variables including age, tumor stage, smoking status, and P53 mutation status. Furthermore, the score was able to predict recurrence-free survival in patients with stage I adenocarcinoma, and was also associated with smoking status. Conclusions The P53 deficiency score was a better predictor of recurrence-free survival compared to P53 mutation status and provided additional prognostic values to established clinical factors. Impact The P53 deficiency score can be used to stratify early-stage patients into subgroups based on their risk of recurrence for aiding physicians to decide personalized therapeutic treatment.

Background Intra-tumor heterogeneity stems from genetic, epigenetic, functional, and environmental differences among tumor cells. A major source of genetic heterogeneity comes from DNA sequence differences and/or whole chromosome and focal copy number variations (CNVs). Whole chromosome CNVs are caused by chromosomal instability (CIN) that is defined by a persistently high rate of chromosome mis-segregation. Accordingly, CIN causes constantly changing karyotypes that result in extensive cell-to-cell genetic heterogeneity. How the genetic heterogeneity caused by CIN influences gene expression in individual cells remains unknown. Methods We performed single-cell RNA sequencing on a chromosomally unstable glioblastoma cancer stem cell (CSC) line and a control normal, diploid neural stem cell (NSC) line to investigate the impact of CNV due to CIN on gene expression. From the gene expression data, we computationally inferred large-scale CNVs in single cells. Also, we performed copy number adjusted differential gene expression analysis between NSCs and glioblastoma CSCs to identify copy number dependent and independent differentially expressed genes. Results Here, we demonstrate that gene expression across large genomic regions scales proportionally to whole chromosome copy number in chromosomally unstable CSCs. Also, we show that the differential expression of most genes between normal NSCs and glioblastoma CSCs is largely accounted for by copy number alterations. However, we identify 269 genes whose differential expression in glioblastoma CSCs relative to normal NSCs is independent of copy number. Moreover, a gene signature derived from the subset of genes that are differential expressed independent of copy number in glioblastoma CSCs correlates with tumor grade and is prognostic for patient survival. Conclusions These results demonstrate that CIN is directly responsible for gene expression changes and contributes to both genetic and transcriptional heterogeneity among glioblastoma CSCs. These results also demonstrate that the expression of some genes is buffered against changes in copy number, thus preserving some consistency in gene expression levels from cell-to-cell despite the continuous change in karyotype driven by CIN. Importantly, a gene signature derived from the subset of genes whose expression is buffered against copy number alterations correlates with tumor grade and is prognostic for patient survival that could facilitate patient diagnosis and treatment. Electronic supplementary material The online version of this article (10.1186/s12920-019-0532-5) contains supplementary material, which is available to authorized users.

Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)-Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine. This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis.

In recent years, the success of immunotherapy targeting immunoregulatory receptors (immune checkpoints) in cancer have generated enthusiastic support to target these receptors in a wide range of other immune related diseases. While the overwhelming focus has been on blockade of these inhibitory pathways to augment immunity, agonistic triggering via these receptors offers the promise of dampening pathogenic inflammatory responses. V-domain Ig suppressor of T cell activation (VISTA) has emerged as an immunoregulatory receptor with constitutive expression on both the T cell and myeloid compartments, and whose agonistic targeting has proven a unique avenue relative to other checkpoint pathways to suppress pathologies mediated by the innate arm of the immune system. VISTA agonistic targeting profoundly changes the phenotype of human monocytes towards an anti-inflammatory cell state, as highlighted by striking suppression of the canonical markers CD14 and Fcγr3a (CD16), and the almost complete suppression of both the interferon I (IFN-I) and antigen presentation pathways. The insights from these very recent studies highlight the impact of VISTA agonistic targeting of myeloid cells, and its potential therapeutic implications in the settings of hyperinflammatory responses such as cytokine storms, driven by dysregulated immune responses to viral infections (with a focus on COVID-19) and autoimmune diseases. Collectively, these findings suggest that the VISTA pathway plays a conserved, non-redundant role in myeloid cell function.

Neoadjuvant chemotherapy is the current standard of care for large, advanced, and/or inoperable tumors, including triple‐negative breast cancer. Although the clinical benefits of neoadjuvant chemotherapy have been illustrated through numerous clinical trials, more than half of the patients do not experience therapeutic benefit and needlessly suffer from side effects. Currently, no clinically applicable biomarkers are available for predicting neoadjuvant chemotherapy response in triple‐negative breast cancer; the discovery of such a predictive biomarker or marker profile is an unmet need. In this study, we introduce a generic computational framework to calculate a response‐probability score (RPS), based on patient transcriptomic profiles, to predict their response to neoadjuvant chemotherapy. We first validated this framework in ER‐positive breast cancer patients and showed that it predicted neoadjuvant chemotherapy response with equal performance to several clinically used gene signatures, including Oncotype DX and MammaPrint. Then, we applied this framework to triple‐negative breast cancer data and, for each patient, we calculated a response probability score (TNBC‐RPS). Our results indicate that the TNBC‐RPS achieved the highest accuracy for predicting neoadjuvant chemotherapy response compared to previously proposed 143 gene signatures. When combined with additional clinical factors, the TNBC‐RPS achieved a high prediction accuracy for triple‐negative breast cancer patients, which was comparable to the prediction accuracy of Oncotype DX and MammaPrint in ER‐positive patients. In conclusion, the TNBC‐RPS accurately predicts neoadjuvant chemotherapy response in triple‐negative breast cancer patients and has the potential to be clinically used to aid physicians in stratifying patients for more effective neoadjuvant chemotherapy.