Six-long non-coding RNA signature predicts recurrence-free survival in hepatocellular carcinoma

Six-long non-coding RNA signature predicts recurrence-free survival in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) ranks the fourth in terms of cancer-related mortality globally. Herein, in this research, we attempted to develop a novel immune-related gene signature that could predict survival and efficacy of immunotherapy for HCC patients. The transcriptomic and clinical data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) and GSE14520 datasets, followed by acquiring immune-related genes from the ImmPort database. Afterwards, an immune-related gene-based prognostic index (IRGPI) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Kaplan–Meier survival curves as well as time-dependent receiver operating characteristic (ROC) curve were performed to evaluate its predictive capability. Besides, both univariate and multivariate analyses on overall survival for the IRGPI and multiple clinicopathologic factors were carried out, followed by the construction of a nomogram. Finally, we explored the possible correlation of IRGPI with immune cell infiltration or immunotherapy efficacy. Analysis of 365 HCC samples identified 11 differentially expressed immune-related genes, which were selected to establish the IRGPI. Notably, it can predict the survival of HCC patients more accurately than published biomarkers. Furthermore, IRGPI can predict the infiltration of immune cells in the tumor microenvironment of HCC, as well as the response of immunotherapy. Collectively, the currently established IRGPI can accurately predict survival, reflect the immune microenvironment, and predict the efficacy of immunotherapy among HCC patients.

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An immune-related gene signature for predicting survival and immunotherapy efficacy in hepatocellular carcinoma

Hypoxia, a common feature of the tumor microenvironment in various types of cancers, weakens cytotoxic T cell function and causes recruitment of regulatory T cells, thereby reducing tumoral immunogenicity. Studies have demonstrated that hypoxia and hypoxia-inducible factors (HIFs) 1 and 2 alpha (HIF1A and HIF2A) are involved in tumor immune escape. Under hypoxia, activation of HIF1A induces a series of signaling events, including through programmed death receptor-1/programmed death ligand-1. Moreover, hypoxia triggers shedding of complex class I chain-associated molecules through nitric oxide signaling impairment to disrupt immune surveillance by natural killer cells. The HIF-1-galactose-3-O-sulfotransferase 1-sulfatide axis enhances tumor immune escape via increased tumor cell-platelet binding. HIF2A upregulates stem cell factor expression to recruit tumor-infiltrating mast cells and increase levels of cytokines interleukin-10 and transforming growth factor-β, resulting in an immunosuppressive tumor microenvironment. Additionally, HIF1A upregulates expression of tumor-associated long noncoding RNAs and suppresses immune cell function, enabling tumor immune escape. Overall, elucidating the underlying mechanisms by which HIFs promote evasion of tumor immune surveillance will allow for targeting HIF in tumor treatment. This review discusses the current knowledge of how hypoxia and HIFs facilitate tumor immune escape, with evidence to date implicating HIF1A as a molecular target in such immune escape. This review provides further insight into the mechanism of tumor immune escape, and strategies for tumor immunotherapy are suggested. 

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Hypoxia-inducible factors: master regulators of hypoxic tumor immune escape

Hepatocellular carcinoma (HCC) is the most common type of primary liver tumor and becomes a lethal malignancy on account of high mortality and increasing incidence. A growing body of studies has proved that long noncoding RNAs (lncRNAs) participate in the development of diverse cancers. Although it has been commonly accepted that SNHG16 is a procancer gene in numerous cancers, the regulatory mechanism of SNHG16 in HCC still needs more explorations. In this study, our results delineated that SNHG16 presented much higher expression levels in HCC tissues and cells, particularly in advanced stages of HCC. Enhanced SNHG16 expression was strongly related to poor prognosis. SNHG16 facilitated HCC progression by promoting cell proliferation, migration, invasion, and epithelial-mesenchymal transition process as well as inhibiting cell apoptosis. SNHG16 served as a sponge for miR-4500 in HCC and miR-4500 neutralized the influences of SNHG16 knockdown on HCC. SNHG16 was confirmed to compete with signal transducer and activator of transcription 3 (STAT3) to bind with miR-4500. SNHG16 aggravated the development of HCC via sponging miR-4500 so as to upregulate STAT3. In other words, this study was the first to investigate the potential mechanism of SNHG16 in HCC and verified SNHG16 exerted its carcinogenesis by miR-4500/STAT3 axis, suggesting SNHG16 may be a new underlying therapeutic target for HCC treatment.

LncRNA SNHG16 aggravates tumorigenesis and development of hepatocellular carcinoma by sponging miR-4500 and targeting STAT3.

Increasing evidence highlights the clinical significance of stromal cells and immune cells in the liver cancer microenvironment. However, reliable prognostic models have not been well established. This study aimed to develop a gene signature for liver cancer based on stromal and immune scores. Using the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) algorithm, stromal and immune scores were estimated based on the transcriptome profile of The Cancer Genome Atlas (TCGA) liver cancer cohort. Stromal-/immune-related differentially expressed genes were identified, followed by functional enrichment analysis. The Cox regression model was used to select prognostic genes and construct a gene signature. Its predictive potential was evaluated by receiver operating characteristic (ROC). The correlation between the risk score and immune cell infiltration was analyzed using Tumor Immune Estimation Resource (TIMER). Three hundred sixty-four upregulated and 10 downregulated stromal-/immune-related genes were identified, were mainly enriched in immune-related processes and pathways. Through univariate and multivariate cox survival analysis, a five-gene risk score was constructed, composed of FABP3, HTRA3, OLFML2B, PDZD4 and SLAMF6. Patients with high score indicated a poorer prognosis than those with low risk score. The areas under the ROC curves of overall survival (OS), progression-free interval, 3-, 5-year, OS status were 0.68, 0.57, 0.72, 0.74 and 0.728, indicating its well performance on predicting patients' prognoses. Furthermore, the risk score and the five genes were significantly correlated with immune cell infiltration in the tumor microenvironment. In this study, we proposed a prognostic five-gene signature based on stromal/immune scores in the liver cancer microenvironment.

A Five-Gene Signature Based on Stromal/Immune Scores in the Tumor Microenvironment and Its Clinical Implications for Liver Cancer.

Identification of a five-long non-coding RNA signature to improve the prognosis prediction for patients with hepatocellular carcinoma

Identification of a five-long non-coding RNA signature to improve the prognosis prediction for patients with hepatocellular carcinoma.

Napsin B Aspartic Peptidase, Pseudogene (NAPSB) was associated with CD4 + T cell infiltration in pancreatic ductal adenocarcinoma. However, the biological role of NAPSB in hepatocellular carcinoma (HCC) remains to be determined.The expression of NAPSB in HCC as well as its clinicopathological association were analyzed using data from several public datasets. qRT-PCR was used to verify the relative expression of NAPSB in patients with HCC using the Zhongnan cohort. Kaplan-Meier analyses, and univariate and multivariate Cox regression were conducted to determine the prognosis value of NAPSB on patients with HCC. Then enrichment analyses were performed to identify the possible biological functions of NAPSB. Subsequently, the immunological characteristics of NAPSB in the HCC tumor microenvironment (TME) were demonstrated comprehensively. The role of NAPSB in predicting hot tumors and its impact on immunotherapy and chemotherapy responses was also analyzed by bioinformatics methods.NAPSB was downregulated in patients with HCC and high NAPSB expression showed an improved survival outcome. Enrichment analyses showed that NAPSB was related to immune activation. NAPSB was positively correlated with immunomodulators, tumor-infiltrating immune cells, T cell inflamed score and cancer-immunity cycle, and highly expressed in immuno-hot tumors. High expression of NAPSB was sensitive to immunotherapy and chemotherapy, possibly due to its association with pyroptosis, apoptosis and necrosis.NAPSB was correlated with an immuno-hot and inflamed TME, and tumor cell death. It can be utilized as a promising predictive marker for prognosis and therapy in HCC. 

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Qiu-Jie Zhao

Papers

Identification of a five-long non-coding RNA signature to improve the prognosis prediction for patients with hepatocellular carcinoma.

NAPSB as a predictive marker for prognosis and therapy associated with an immuno-hot tumor microenvironment in hepatocellular carcinoma