STX11 functions as a novel tumor suppressor gene in peripheral T-cell lymphomas

A novel machine learning-derived four-gene signature predicts STEMI and post-STEMI heart failure

High mortality and morbidity rates associated with ST-elevation myocardial infarction (STEMI) and post-STEMI heart failure (HF) necessitate proper risk stratification for coronary artery disease (CAD). A prediction model that combines specificity and convenience is highly required. This study aimed to design a monocyte-based gene assay for predicting STEMI and post-STEMI HF. A total of 1,956 monocyte expression profiles and corresponding clinical data were integrated from multiple sources. Meta-results were obtained through the weighted gene co-expression network analysis (WGCNA) and differential analysis to identify characteristic genes for STEMI. Machine learning models based on the decision tree (DT), support vector machine (SVM), and random forest (RF) algorithms were trained and validated. Five genes overlapped and were subjected to the model proposal. The discriminative performance of the DT model outperformed the other two methods. The established four-gene panel (HLA-J, CFP, STX11, and NFYC) could discriminate STEMI and HF with an area under the curve (AUC) of 0.86 or above. In the gene set enrichment analysis (GSEA), several cardiac pathogenesis pathways and cardiovascular disorder signatures showed statistically significant, concordant differences between subjects with high and low expression levels of the four-gene panel, affirming the validity of the established model. In conclusion, we have developed and validated a model that offers the hope for accurately predicting the risk of STEMI and HF, leading to optimal risk stratification and personalized management of CAD, thereby improving individual outcomes.

Integrative Analysis Identifies Cell-Type-Specific Genes Within Tumor Microenvironment as Prognostic Indicators in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, but effective early detection and prognostication methods are lacking.

Methods

The Cox regression model was built to stratify the HCC patients. The single-cell RNA sequencing data analysis and gene set enrichment analysis were employed to investigate the biological function of identified markers. PLCB1 gain- or loss-of-function experiments were performed, and obtained HCC samples were analyzed using quantitative real-time PCR and immunohistochemistry assay to validate the biological function of identified markers.

Results

In this study, we developed a model using optimized markers for HCC recurrence prediction. Specifically, we screened out 8 genes through a series of data analyses, and built a multivariable Cox model based on their expression. The risk stratifications using the Eight-Gene Cox (EGC) model were closely associated with the recurrence-free survivals (RFS) in both training and three validation cohorts. We further demonstrated that this risk stratification could serve as an independent predictor in predicting HCC recurrence, and that the EGC model could outperform other models. Moreover, we also investigated the cell-type-specific expression patterns of the eight recurrence-related genes in tumor microenvironment using single-cell RNA sequencing data, and interpreted their functional roles from correlation and gene set enrichment analyses, in vitro and in vivo experiments. Particularly, PLCB1 and SLC22A7 were predominantly expressed in malignant cells, and they were predicted to promote angiogenesis and to help maintain normal metabolism in liver, respectively. In contrast, both FASLG and IL2RB were specifically expressed in T cells, and were highly correlated with T cell marker genes, suggesting that these two genes might assist in maintaining normal function of T cell-mediated immune response in tumor tissues.

Conclusion

In conclusion, the EGC model and eight identified marker genes could not only facilitate the accurate prediction of HCC recurrence, but also improve our understanding of the mechanisms behind HCC recurrence.

Identification of Immune-Cell-Related Prognostic Biomarkers of Esophageal Squamous Cell Carcinoma Based on Tumor Microenvironment

Background

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal cancers in the world. The 5-year survival rate of ESCC is <30%. However, few biomarkers can accurately predict the prognosis of patients with ESCC. We aimed to identify potential survival-associated biomarkers for ESCC to improve its poor prognosis.

Methods

ImmuneAI analysis was first used to access the immune cell abundance of ESCC. Then, ESTIMATE analysis was performed to explore the tumor microenvironment (TME), and differential analysis was used for the selection of immune-related differentially expressed genes (DEGs). Weighted gene coexpression network analysis (WGCNA) was used for selecting the candidate DEGs. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to build the immune-cell-associated prognostic model (ICPM). Kaplan–Meier curve of survival analysis was performed to evaluate the efficacy of the ICPM.

Results

Based on the ESTIMATE and ImmuneAI analysis, we obtained 24 immune cells’ abundance. Next, we identified six coexpression module that was associated with the abundance. Then, LASSO regression models were constructed by selecting the genes in the module that is most relevant to immune cells. Two test dataset was used to testify the model, and we finally, obtained a seven-genes survival model that performed an excellent prognostic efficacy.

Conclusion

In the current study, we filtered seven key genes that may be potential prognostic biomarkers of ESCC, and they may be used as new factors to improve the prognosis of cancer.

Genomic and transcriptomic characterization of desmoplastic small round cell tumors

Desmoplastic small round cell tumor (DSRCT) is a highly aggressive soft tissue tumor primarily affecting children and young adults. Most cases display a pathognomonic EWSR1-WT1 gene fusion, presumably constituting the primary driver event. Little is, however, known about secondary genetic changes that may affect tumor progression. We here studied 25 samples from 19 DSRCT patients using single nucleotide polymorphism arrays and found that all samples had copy number alterations. The most common imbalances were gain of chromosomes/chromosome arms 1/1q and 5/5p and loss of 6/6q and 16/16q, all occurring in at least eight of the patients. Five cases showed homozygous deletions, affecting a variety of known tumor suppressor genes, for example, CDKN2A and NF1. As almost all patients died of their disease, the impact of individual imbalances on survival could not be evaluated. Global gene expression analysis using mRNA sequencing on fresh-frozen samples from seven patients revealed a distinct transcriptomic profile, with enrichment of genes involved in neural differentiation. Two genes - GJB2 and GAL - that showed higher expression in DSRCT compared to control tumors could be further investigated for their potential as diagnostic markers at the protein level.

Comprehensive genomic analysis identifying heterogeneity in peripheral T-cell lymphoma

Peripheral T-cell lymphoma (PTCL) is a heterogeneous entity generally with a poor prognosis. Recent genomic analyses have characterized genomic alterations and described gene expression profiling and epigenetic mechanisms in PTCL, leading to reveal molecular pathophysiology in detail. One of several important findings is that heterogeneities exist in both the disease and in individuals. Among PTCL subtypes, adult T-cell leukemia/lymphoma (ATLL) and peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) are common in Japan. ATLL is an incurable T-cell malignancy induced by human T-cell lymphotropic virus type 1 (HTLV-1). The global genomics of ATLL can be summarized as alterations involving T-cell receptor (TCR) signaling and immune escape mechanisms. This highlights the fact that ATLL is a viral-mediated T-cell malignancy. Interestingly, several previous studies have found that the genomics of ATLL differ according to geographical region and age at diagnosis, suggesting disease heterogeneity, though they share HTLV-1 infection as initial disease hit. Clonal expansion of the cells acquired by somatic mutations in ATLL-related genes is identified in a part of HTLV-1 carriers who developed ATLL later. The risk for ATLL may be updated based on findings in detail. PTCL-NOS is a heterogeneous disease type of T-cell lymphoma that does not correspond to any other type of PTCL. Several studies have stratified PTCL-NOS according to transcriptional, genomic, microenvironmental, and clinical aspects. These kinds of analysis from multiple aspects are useful to understand the heterogeneous group. These efforts will help guide suitable translational research to target PTCL.

UTRN inhibits melanoma growth by suppressing p38 and JNK/c-Jun signaling pathways

Background

Utrophin (UTRN), as a tumor suppressor gene, is involved in various cancer progression. The function of UTRN in the melanoma process and the related molecular mechanisms are still unclear. Herein, we studied the function of UTRN in melanoma growth and the relevant molecular mechanisms.

Methods

Using the GEO database and UCSC Xena project, we compared the expression of UTRN in non-cancerous and melanoma tissues. Immunohistochemistry (IHC) staining, qRT-PCR and Western Blot (WB) were performed to evaluate UTRN expression in clinical samples. A total of 447 cases with UTRN expression data, patient characteristics and survival data were extracted from TCGA database and analyzed. After stable transduction and single cell cloning, the proliferation ability of A375 human melanoma cells was analyzed by Cell Counting Kit‑8 (CCK) and 5‑ethynyl‑2′‑deoxyuridine (EdU) incorporation assays. GSEA was performed to predict the mechanism by which UTRN regulated melanoma growth. Then WB analysis was used to assess the protein expression levels of pathway signaling in overexpression (EXP) melanoma cells. Epac activator 8-pCPT-2′-O-Me-cAMP was then used to evaluate the proliferation ability by activation of p38 and JNK/c-Jun signaling pathways.

Results

Data from GEO and UCSC Xena project indicated that UTRN expression was decreased in melanoma. Experiment on clinical samples further confirmed our finding. TCGA results showed that a reduced expression of UTRN in 447 melanoma samples was associated with advanced clinical characteristics (T stage, Clark level, ulceration), shorter survival time and poorer prognosis. In addition, up-regulated UTRN expression inhibited melanoma cell proliferation when compared to control group. MAPK signaling pathway was presented in both KEGG and BioCarta databases by using GSEA tool. WB results confirmed the down-regulated expression of p38, JNK1 and c-Jun in EXP group when compared to control group. Epac activator 8-pCPT-2′-O-Me-cAMP treatment could partially rescue proliferation of tumor cells.

Conclusion

We have demonstrated that reduced UTRN predicted poorer prognosis and UTRN inhibited melanoma growth via p38 and JNK1/c-Jun pathways. Therefore, UTRN could serve as a tumor suppressor and novel prognostic biomarker for melanoma patients.

Chloride intracellular channel protein 2: prognostic marker and correlation with PD-1/PD-L1 in breast cancer

Immune checkpoint inhibition has emerged as an effective treatment for multiple solid tumors, including advanced-stage breast cancer (BC). During the past decade, the US Food and Drug Administration has approved a number of agents for immune checkpoint blockade (ICB). However, the limited data on monotherapy anti-tumor activity in BC underscores the need for robust predictive biomarker development. Here, we used weighted gene coexpression network analysis of genes differentially expressed between BC and normal tissue to identify genes coexpressed with programmed death-1 (PD-1) and its ligand (PD-L1). Tumor Immune Estimation Resource and Gene Expression Profiling Interaction Analysis were used to assess the relationship between gene expression and the abundance of tumor-infiltrating lymphocytes (TILs). We found that chloride intracellular channel protein 2 (CLIC2) was not only coexpressed with PD-1 and PD-L1, but its increased expression was associated with a favorable prognosis and enrichment of multiple TIL types, particularly CD8+ T cells. These results suggest that CLIC2 is a potentially useful biomarker for identifying BC patients who could benefit from ICB.

Probing the changes in gene expression due to α-crystallin mutations in mouse models of hereditary human cataract

The mammalian eye lens expresses a high concentration of crystallins (α, β and γ-crystallins) to maintain the refractive index essential for lens transparency. Crystallins are long-lived proteins that do not turnover throughout life. The structural destabilization of crystallins by UV exposure, glycation, oxidative stress and mutations in crystallin genes leads to protein aggregation and development of cataracts. Several destabilizing mutations in crystallin genes are linked with human autosomal dominant hereditary cataracts. To investigate the mechanism by which the α-crystallin mutations Cryaa-R49C and Cryab-R120G lead to cataract formation, we determined whether these mutations cause an altered expression of specific transcripts in the lens at an early postnatal age by RNA-seq analysis. Using knock-in mouse models previously generated in our laboratory, in the present work, we identified genes that exhibited altered abundance in the mutant lenses, including decreased transcripts for Clic5, an intracellular water channel in Cryaa-R49C heterozygous mutant lenses, and increased transcripts for Eno1b in Cryab-R120G heterozygous mutant lenses. In addition, RNA-seq analysis revealed increased histones H2B, H2A, and H4 gene expression in Cryaa-R49C mutant lenses, suggesting that the αA-crystallin mutation regulates histone expression via a transcriptional mechanism. Additionally, these studies confirmed the increased expression of histones H2B, H2A, and H4 by proteomic analysis of Cryaa-R49C knock-in and Cryaa;Cryab gene knockout lenses reported previously. Taken together, these findings offer additional insight into the early transcriptional changes caused by Cryaa and Cryab mutations associated with autosomal dominant human cataracts, and indicate that the transcript levels of certain genes are affected by the expression of mutant α-crystallin in vivo.

Mechanisms underlying the antiproliferative effects of a series of quinoxaline-derived chalcones

The present study aimed to characterize the effects of quinoxaline-derived chalcones, designed on the basis of the selective PI3Kγ inhibitor AS605240, in oral cancer cells. Three lead compounds, namely N9, N17 and N23, were selected from a series of 20 quinoxaline-derived chalcones, based on an initial screening using human and rat squamous cell carcinoma lineages, representing compounds with at least one methoxy radical at the A-ring. The selected chalcones, mainly N9 and N17, displayed marked antiproliferative effects, via apoptosis and autophagy induction, with an increase of sub-G1 population and Akt inhibition. The three chalcones displayed marked in vitro antitumor effects in different protocols with standard chemotherapy drugs, with acceptable toxicity on normal cells. There was no growth retrieval, after exposure to chalcone N9 alone, in a long-term assay to determine the cumulative population doubling (CPD) of human oral cancer cells. A PCR array evaluating 168 genes related to cancer and inflammation, demonstrated striking actions for N9, which altered the expression of 74 genes. Altogether, our results point out quinoxalinic chalcones, mainly N9, as potential strategies for oral cancer treatment.

Mismatch Repair Proteins Initiate Epigenetic Alterations during Inflammation-Driven Tumorigenesis

Aberrant silencing of genes by DNA methylation contributes to cancer, yet how this process is initiated remains unclear. Using a murine model of inflammation-induced tumorigenesis, we tested the hypothesis that inflammation promotes recruitment of epigenetic proteins to chromatin, initiating methylation and gene silencing in tumors. Compared with normal epithelium and noninflammation-induced tumors, inflammation-induced tumors gained DNA methylation at CpG islands, some of which are associated with putative tumor suppressor genes. Hypermethylated genes exhibited enrichment of repressive chromatin marks and reduced expression prior to tumorigenesis, at a time point coinciding with peak levels of inflammation-associated DNA damage. Loss of MutS homolog 2 (MSH2), a mismatch repair (MMR) protein, abrogated early inflammation-induced epigenetic alterations and DNA hypermethylation alterations observed in inflammation-induced tumors. These results indicate that early epigenetic alterations initiated by inflammation and MMR proteins lead to gene silencing during tumorigenesis, revealing a novel mechanism of epigenetic alterations in inflammation-driven cancer. Understanding such mechanisms will inform development of pharmacotherapies to reduce carcinogenesis. Cancer Res; 77(13); 3467-78. ©2017 AACR.