BackgroundLong non-coding RNAs (lncRNAs) are known to play important roles in different cell contexts, including cancers. However, little is known about lncRNAs in cholangiocarcinoma (CCA), a cholangiocyte malignancy with poor prognosis, associated with chronic inflammation and damage to the biliary epithelium. The aim of the study is to identify if any lncRNA might associate with inflammation or oxidative stress in CCA and regulate the disease progression.MethodsIn this study, RNA-seqs datasets were used to identify aberrantly expressed lncRNAs. Small interfering RNA and overexpressed plasmids were used to modulate the expression of lncRNAs, and luciferase target assay RNA immunoprecipitation (RIP) was performed to explore the mechanism of miRNA-lncRNA sponging.ResultsWe firstly analyzed five available RNA-seqs datasets to investigate aberrantly expressed lncRNAs which might associate with inflammation or oxidative stress. We identified that two lncRNAs, H19 and HULC, were differentially expressed among all the samples under the treatment of hypoxic or inflammatory factors, and they were shown to be stimulated by short-term oxidative stress responses to H2O2 and glucose oxidase in CCA cell lines. Further studies revealed that these two lncRNAs promoted cholangiocyte migration and invasion via the inflammation pathway. H19 and HULC functioned as competing endogenous RNAs (ceRNAs) by sponging let-7a/let-7b and miR-372/miR-373, respectively, which activate pivotal inflammation cytokine IL-6 and chemokine receptor CXCR4.ConclusionsOur study revealed that H19 and HULC, up-regulated by oxidative stress, regulate CCA cell migration and invasion by targeting IL-6 and CXCR4 via ceRNA patterns of sponging let-7a/let-7b and miR-372/miR-373, respectively. The results suggest that these lncRNAs might be the chief culprits of CCA pathogenesis and progression. The study provides new insight into the mechanism linking lncRNA function with CCA and may serve as novel targets for the development of new countermeasures of CCA.

Additional file 1: Figure S1. of LncRNAs H19 and HULC, activated by oxidative stress, promote cell migration and invasion in cholangiocarcinoma through a ceRNA manner

Immunotherapy, represented by immune checkpoint inhibitors (ICI), is transforming the treatment of cancer. However, only a small percentage of patients show response to ICI and there is an unmet need for biomarkers that will identify patients who are more likely to respond to immunotherapy. The fundamental basis for ICI response is the immunogenicity of a tumor, which is primarily determined by tumor antigenicity and antigen presentation efficiency. Here, we propose a method to measure tumor immunogenicity score (TIGS), which combines tumor mutational burden (TMB) and an expression signature of the antigen processing and presenting machinery (APM). In both correlation with pan-cancer ICI objective response rates (ORR) and ICI clinical response prediction for individual patients, TIGS consistently showed improved performance compared to TMB and other known prediction biomarkers for ICI response. This study suggests that TIGS is an effective tumor inherent biomarker for ICI-response prediction.

Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction

Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-based integrative procedure for constructing a consensus immune-related lncRNA signature (IRLS). IRLS is an independent risk factor for overall survival and displays stable and powerful performance, but only demonstrates limited predictive value for relapse-free survival. Additionally, IRLS possesses distinctly superior accuracy than traditional clinical variables, molecular features, and 109 published signatures. Besides, the high-risk group is sensitive to fluorouracil-based adjuvant chemotherapy, while the low-risk group benefits more from bevacizumab. Notably, the low-risk group displays abundant lymphocyte infiltration, high expression of CD8A and PD-L1, and a response to pembrolizumab. Taken together, IRLS could serve as a robust and promising tool to improve clinical outcomes for individual CRC patients. 

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Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer

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Since online publication of this article, the authors noticed that an incorrect image was used during the compilation of Fig. 2a, which was caused during manuscript preparation. The correct Fig. 2a is shown below.

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Exosomal miR-25-3p from mesenchymal stem cells alleviates myocardial infarction by targeting pro-apoptotic proteins and EZH2.

Transcriptome dysregulation by epigenetics plays a significant role in the heterogeneous characteristic of bladder cancer. 1,2 However, the epigenetic mechanisms underlying BLCA heterogeneity are unclear and stable epigenetic molecular subtypes are still lacking. The

Epigenetically regulated gene expression profiles recognized three molecular classifications with prognostic and therapeutic implications in bladder cancer

The identification of reliable tumor prognostic markers can help clinicians and researchers predict tumor development and patient survival outcomes more accurately, which plays a vital role in clinical diagnosis, treatment effectiveness assessment, and prognostic evaluation. Existing web tools supporting online survival analysis are gradually failing to meet the increasing demands of researchers in terms of the dataset size, richness of survival analysis methods, and diversity of customization features. Therefore, there is an urgent need for a large-scale, one-stop pan-cancer survival analysis web server. We developed PanCanSurvPlot (https://smuonco.shinyapps.io/PanCanSurvPlot/), a Shiny web tool that has incorporated a total of 215 cancer-related datasets from the GEO and TCGA databases, covering nearly 100,000 genes (mRNAs, miRNAs, and lncRNAs), approximately 45,000 samples, 51 different cancer types, and 13 different survival outcomes. The website also provides two cutoff methods based on median and optimal cutpoints. All survival analysis results from the log-rank test and univariate Cox regression are presented in a clear and straightforward summary table. Finally, users can customize color schemes and cutpoint levels to quickly obtain high-quality Kaplan-Meier survival plots that meet publication requirements.

PanCanSurvPlot: A Large-scale Pan-cancer Survival Analysis Web Application

Radiogenomics: a key component of precision cancer medicine.

Gastrointestinal symptoms of long COVID-19 related to the ectopic colonization of specific bacteria that move between the upper and lower alimentary tract and alterations in serum metabolites

https://doi.org/10.1016/j.isci.2023.105959

Zaoqu Liu

Papers

Epigenetically regulated gene expression profiles recognized three molecular classifications with prognostic and therapeutic implications in bladder cancer

PanCanSurvPlot: A Large-scale Pan-cancer Survival Analysis Web Application

Radiogenomics: a key component of precision cancer medicine.

Gastrointestinal symptoms of long COVID-19 related to the ectopic colonization of specific bacteria that move between the upper and lower alimentary tract and alterations in serum metabolites

Exploring the roles of intestinal flora in enhanced recovery after surgery