Gene expression signature of exercise and change of diet on non-alcoholic fatty liver disease in mice

Non-alcoholic fatty liver diseases (NAFLD) are particularly prevalent in the general Western adult population, with around one third of the population suffering from the disease. Evidence shows that NAFLD is associated with metabolic syndromes such as obesity, insulin resistance, and hypertension. Currently, the sole therapy for NAFLD involves exercise intervention. Studies showed that, with and without weight loss, exercise interventions produced a significant cutback in intrahepatic lipid content in humans, but better controlled studies that can investigate the cellular and molecular mechanisms are still lacking. In the current study we perform RNA sequencing analysis on liver samples from C57BL/6 mice submitted to aerobic exercise and diet interventions that are human-translatable and determine the genetic expression signature of exercise in the NAFLD onset. We show that aerobic exercise affects genes and pathways related to liver metabolism, muscle contraction and relaxation, immune response and inflammation, and development of liver cancer, counteracting non-alcoholic steatohepatitis and hepatocellular carcinoma development. While genes and pathways implicating immune response are activated by aerobic exercise in all interventions, the most effective intervention in terms of improvement of NASH is the combination of aerobic exercise with change of diet.

Identification and Validation of a Novel Six-Gene Expression Signature for Predicting Hepatocellular Carcinoma Prognosis

BackgroundHepatocellular carcinoma (HCC) is a highly lethal disease. Effective prognostic tools to guide clinical decision-making for HCC patients are lacking.ObjectiveWe aimed to establish a robust prognostic model based on differentially expressed genes (DEGs) in HCC.MethodsUsing datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Genome Consortium (ICGC), DEGs between HCC tissues and adjacent normal tissues were identified. Using TCGA dataset as the training cohort, we applied the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analyses to identify a multi-gene expression signature. Proportional hazard assumptions and multicollinearity among covariates were evaluated while building the model. The ICGC cohort was used for validation. The Pearson test was used to evaluate the correlation between tumor mutational burden and risk score. Through single-sample gene set enrichment analysis, we investigated the role of signature genes in the HCC microenvironment.ResultsA total of 274 DEGs were identified, and a six-DEG prognostic model was developed. Patients were stratified into low- or high-risk groups based on risk scoring by the model. Kaplan–Meier analysis revealed significant differences in overall survival and progression-free interval. Through univariate and multivariate Cox analyses, the model proved to be an independent prognostic factor compared to other clinic-pathological parameters. Time-dependent receiver operating characteristic curve analysis revealed satisfactory prediction of overall survival, but not progression-free interval. Functional enrichment analysis showed that cancer-related pathways were enriched, while immune infiltration analyses differed between the two risk groups. The risk score did not correlate with levels of PD-1, PD-L1, CTLA4, or tumor mutational burden.ConclusionsWe propose a six-gene expression signature that could help to determine HCC patient prognosis. These genes may serve as biomarkers in HCC and support personalized disease management.

Single cell analysis reveals stochastic cell-to-cell variation in stress response and senescence program

Cells have various means to respond to molecular stress. Upon stress, proliferating cells can adopt different fates, e.g. commit to apoptosis, go into senescence or recover from stress and resume proliferation, depending on severity of the stress. Proper balance between these modes of response is critical for maintaining tissue homeostasis with age, as both exacerbated and insufficient response can result in pathology. Remarkably, even genetically identical cells of the same type in the controlled environment can exhibit a spectrum of responses to the same stress challenge. We hypothesized that analyzing response of individual cells in controlled environment can help better understand the mechanisms that ensure a balanced response to molecular stress. We used large scale single cell RNA-sequencing to analyze response of individual human fibroblasts to oxidative stress. Consistent with various fates adopted by individual cells upon stress, we observed different transcriptional signatures, that correspond to those fates. Surprisingly, when we specifically analyzed ß-gal+ senescent cells, we still observed transcriptional heterogeneity, with only a subset of cells exhibiting pro-senescent transcriptional signature (e.g. activated p53 and TNF-a pathways) while another subset exhibits a gene expression signature of senescent-like arrest. Hence, we find that in addition to known stress-related fates (apoptosis, senescence, recovery) senescence-like response is heterogeneous with only subset of cells exhibiting expected pro-senescent gene expression signature. Further characterization of heterogeneity of stress response and senescent-like fates will help better understand the mechanisms of homeostatic control in the face of molecular stress and aging.

Drug Repurposing in Rare Diseases: An Integrative Study of Drug Screening and Transcriptomic Analysis in Nephropathic Cystinosis

Diagnosis and cure for rare diseases represent a great challenge for the scientific community who often comes up against the complexity and heterogeneity of clinical picture associated to a high cost and time-consuming drug development processes. Here we show a drug repurposing strategy applied to nephropathic cystinosis, a rare inherited disorder belonging to the lysosomal storage diseases. This approach consists in combining mechanism-based and cell-based screenings, coupled with an affordable computational analysis, which could result very useful to predict therapeutic responses at both molecular and system levels. Then, we identified potential drugs and metabolic pathways relevant for the pathophysiology of nephropathic cystinosis by comparing gene-expression signature of drugs that share common mechanisms of action or that involve similar pathways with the disease gene-expression signature achieved with RNA-seq.

A Minimal Subset of Seven Genes Associated with Tumor Hepatocyte Differentiation Predicts a Poor Prognosis in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a deadly cancer worldwide as a result of a frequent late diagnosis which limits the therapeutic options. Tumor progression in HCC is closely correlated with the dedifferentiation of hepatocytes, the main parenchymal cells in the liver. Here, we hypothesized that the expression level of genes reflecting the differentiation status of tumor hepatocytes could be clinically relevant in defining subsets of patients with different clinical outcomes. To test this hypothesis, an integrative transcriptomics approach was used to stratify a cohort of 139 HCC patients based on a gene expression signature established in vitro in the HepaRG cell line using well-controlled culture conditions recapitulating tumor hepatocyte differentiation. The HepaRG model was first validated by identifying a robust gene expression signature associated with hepatocyte differentiation and liver metabolism. In addition, the signature was able to distinguish specific developmental stages in mice. More importantly, the signature identified a subset of human HCC associated with a poor prognosis and cancer stem cell features. By using an independent HCC dataset (TCGA consortium), a minimal subset of seven differentiation-related genes was shown to predict a reduced overall survival, not only in patients with HCC but also in other types of cancers (e.g., kidney, pancreas, skin). In conclusion, the study identified a minimal subset of seven genes reflecting the differentiation status of tumor hepatocytes and clinically relevant for predicting the prognosis of HCC patients.

700 Increasing MHC-I expression to potentiate immune checkpoint blockade therapy

BackgroundCancer immunotherapy, especially immune checkpoint blockade (ICB) therapy, is leading to a paradigm shift in cancer treatment, as a small percentage of cancer patients have obtained durable remission following ICB treatment. Successful ICB responses rely on cancer cells presenting antigens to the cell surface via the major histocompatibility complex (MHC), which activates antigen-specific T-lymphocytes to kill cancer cells. Type-I MHC (MHC-I) is wildly expressed in all cell types and mediates the interaction with cytotoxic CD8 T cells. However, over 65% of cancer patients are estimated to show defects in MHC-I-mediated antigen presentation, including downregulation of its expression that can lead to primary or acquired resistance to ICB therapy, and therapeutic strategies to effectively restore or boost MHC-I are limited.MethodsHere, we employed a CRISPR screening approach with dual-marker FACS sorting to identify factors that decouple the regulation of MHC-I and PD-L1. The experimentally validated target was used to generate a KO differential expression signature. Using this signature, we analyzed transcriptome data from drug perturbation studies to identify drugs that regulate MHC-I but not PD-L1. Finally, we validated the effect of the identified drug to enhance ICB response in a T-cell-dependent manner in vivo.ResultsCRISPR screens identified TRAF3, a suppressor of the NF-κB pathway, as a negative regulator of MHC-I but not PD-L1. The Traf3-knockout (Traf3-KO) gene expression signature is associated with better survival in ICB-naive cancer patients and better ICB response. We then screened for drugs with similar transcriptional effects as this signature and identified SMAC mimetics. We experimentally validated that the SMAC mimetic birinapant upregulates MHC-I, sensitizes cancer cells to T-cell-dependent killing, and adds to ICB efficacy. However, in cancer cells with high NF-κB activity, the effect of birinapant on MHC-I is weak, indicating context-dependent MHC-I regulation.ConclusionsIn summary, Traf3 deletion specifically upregulates MHC-I without inducing PD-L1 in response to various cytokines and sensitizes cancer cells to T-cell-driven cytotoxicity. The SMAC mimetic birinapant phenocopies Traf3-knockout and sensitizes MHC-I-low melanoma to ICB therapy. Further studies are needed to elucidate the context-dependencies of MHC-I regulation. Our findings provide preclinical rationale for treating some tumors expressing low MHC-I with SMAC mimetics to enhance sensitivity to immunotherapy. The approach used in this study can be generalized to identify other drugs that enhance immunotherapy efficacy.AcknowledgementsThis study was supported by grants from the NIH (R01CA234018 to XSL, R01AI137337 to BEG, P50CA101942-12 and P50CA206963 to GJF), Breast Cancer Research Foundation (BCRF-19-100 to XSL), Burroughs Wellcome Career Award in Medical Sciences (to BEG), and Sara Elizabeth O'Brien Trust Fellowship (to SG).We thank Drs. Kai Wucherpfennig and Deng Pan for their insightful suggestions on this study.Ethics ApprovalAll mice were housed in standard cage in Dana-Farber Cancer Institute Animal Resources Facility (ARF). All animal procedures were carried out under the ARF Institutional Animal Care and Use Committee (IACUC) protocol and were in accordance with the IACUC standards for the welfare of animals.