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In the past few years, immune checkpoint blockade (ICB) therapy has emerged as a breakthrough treatment for cancers and has demonstrated inspiring effects in tumor patients with Epstein-Barr virus (EBV) infection. To allow more patients to benefit from immunotherapy, exploring novel biomarkers based on EBV-related tumors and immunotherapy cohorts was pursued in the present study. The essential biomarkers that may enhance antitumor immunity across EBV-related tumors were identified using the large-scale transcriptomic profiles of EBV-associated tumors and tumor immunotherapy cohorts. The clinical significance of vital genes was evaluated in multiple tumor immunotherapy cohorts. Moreover, the potential function of essential genes in immunotherapy was explored via bioinformatic analyses and verified by qRT-PCR, Western blot analysis, CCK8 assay and flow cytometry. Apolipoprotein L6 (APOL6) was considered the essential biomarker for enhancing antitumor immunity across EBV-positive tumors. The upregulation of APOL6 was correlated with increased response rates and prolonged survival in multiple tumor immunotherapy cohorts. Bioinformatic analyses suggested that APOL6 may enhance tumor immunotherapy by inducing immunogenic cell death. Pancreatic cancer cells transfected with APOL6 overexpression plasmid underwent apoptosis, necroptosis, and pyroptosis with immunogenic features. The biomarker upregulated in EBV-related tumors could further elucidate the drivers of immunotherapy response. The upregulation of APOL6 could improve immunotherapy by triggering immunogenic cell death, thus offering a new target to optimize cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles. [ABSTRACT FROM AUTHOR]