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.

Background The unknown etiology of sarcoidosis with variable clinical features leads to delayed diagnosis and limited therapeutic strategies. Hence, exploring the latent mechanisms and constructing an accessible and reliable diagnostic model of sarcoidosis is vital for innovative therapeutic approaches to improve prognosis. Methods This retrospective study analyzed transcriptomes from 11 independent sarcoidosis cohorts, comprising 313 patients and 400 healthy controls. The weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were performed to identify molecular biomarkers. Machine learning was employed to fit a diagnostic model. The potential pathogenesis and immune landscape were detected by bioinformatics tools. Results A 10-gene signature SARDS consisting of GBP1, LEF1, IFIT3, LRRN3, IFI44, LHFPL2, RTP4, CD27, EPHX2, and CXCL10 was further constructed in the training cohorts by the LASSO algorithm, which performed well in the four independent cohorts with the splendid AUCs ranging from 0.938 to 1.000. The findings were validated in seven independent publicly available gene expression datasets retrieved from whole blood, PBMC, alveolar lavage fluid cells, and lung tissue samples from patients with outstanding AUCs ranging from 0.728 to 0.972. Transcriptional signatures associated with sarcoidosis revealed a potential role of immune response in the development of the disease through bioinformatics analysis. Conclusions Our study identified and validated molecular biomarkers for the diagnosis of sarcoidosis and constructed the diagnostic model SARDS to improve the accuracy of early diagnosis of the disease.

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Integrative bioinformatics analysis to explore a robust diagnostic signature and landscape of immune cell infiltration in sarcoidosis

Infection susceptibility, poor vaccination efficacy, age-related disease onset, and neoplasms are linked to innate and adaptive immune dysfunction that accompanies aging (known as immunosenescence). During aging, organisms tend to develop a characteristic inflammatory state that expresses high levels of pro-inflammatory markers, termed inflammaging. This chronic inflammation is a typical phenomenon linked to immunosenescence and it is considered the major risk factor for age-related diseases. Thymic involution, naïve/memory cell ratio imbalance, dysregulated metabolism, and epigenetic alterations are striking features of immunosenescence. Disturbed T-cell pools and chronic antigen stimulation mediate premature senescence of immune cells, and senescent immune cells develop a proinflammatory senescence-associated secretory phenotype that exacerbates inflammaging. Although the underlying molecular mechanisms remain to be addressed, it is well documented that senescent T cells and inflammaging might be major driving forces in immunosenescence. Potential counteractive measures will be discussed, including intervention of cellular senescence and metabolic-epigenetic axes to mitigate immunosenescence. In recent years, immunosenescence has attracted increasing attention for its role in tumor development. As a result of the limited participation of elderly patients, the impact of immunosenescence on cancer immunotherapy is unclear. Despite some surprising results from clinical trials and drugs, it is necessary to investigate the role of immunosenescence in cancer and other age-related diseases. 

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Immunosenescence: molecular mechanisms and diseases

Pharmacogenomics is crucial for individualized drug therapy and plays an increasingly vital role in precision medicine decision-making. However, pharmacogenomics-based molecular subtypes and their potential clinical significance remain primarily unexplored in lung adenocarcinoma (LUAD). A total of 2065 samples were recruited from eight independent cohorts. Pharmacogenomics data were generated from the profiling of relative inhibition simultaneously in mixtures (PRISM) and the genomics of drug sensitivity in cancer (GDSC) databases. Multiple bioinformatics approaches were performed to identify pharmacogenomics-based subtypes and find subtype-specific properties. Three reproducible molecular subtypes were found, which were independent prognostic factors and highly associated with stage, survival status, and accepted molecular subtypes. Pharmacogenomics-based subtypes had distinct molecular characteristics: S-Ⅰ was inflammatory, proliferative, and immune-evasion; S-Ⅱ was proliferative and genetics-driven; S-III was metabolic and methylation-driven. Finally, our study provided subtype-guided personalized treatment strategies: Immune checkpoint blockers (ICBs), doxorubicin, tipifarnib, AZ628, and AZD6244 were for S-Ⅰ; Cisplatin, camptothecin, roscovitine, and A.443654 were for S-Ⅱ; Docetaxel, paclitaxel, vinorelbine, and BIBW2992 were for S-III. We provided a novel molecular classification strategy and revealed three pharmacogenomics-based subtypes for LUAD patients, which uncovered potential subtype-related and patient-specific therapeutic strategies. 

https://doi.org/10.1016/j.csbj.2022.06.064

Integrative pharmacogenomics revealed three subtypes with different immune landscapes and specific therapeutic responses in lung adenocarcinoma

The interplay between long non-coding RNAs (lncRNAs) and the Notch pathway involves a variety of malignancies. However, Notch-derived lncRNAs and their latent clinical significance remain elusive in colorectal cancer (CRC). In this study, we introduced a framework that could screen Notch-derived lncRNAs (named “NLncer”) and ultimately identified 24 NLncers. To further explore the clinical significance of these NLncers, we performed LASSO and Cox regression in TCGA-CRC cohort (n = 584) and then retained six lncRNAs tightly associated with prognosis. The final model (termed “NLncS”) was subsequently tested in GSE38832 (n = 122), GSE39582 (n = 573), and an in-house clinical cohort (n = 115). Ultimately, our NLncS model could serve as an independent risk factor and afford a robust performance for assessing the prognosis of CRC patients. Additionally, patients with high NLncS risk scores were characterized by upregulation of immune pathways, strong immunogenicity, abundant CD8 + T-cell infiltration, and potentially higher response rates to CTLA4 blockers, which turned out to be suitable for immunotherapy. Aiming at globally observing the characteristics of high-risk patients, somatic mutation and methylation modification analysis provide us with evidence at the genomic and transcriptomic levels. To facilitate the clinical transformability, we mined deeply into the sensitive compounds targeting high-risk individuals and identified dasatinib as a candidate agent for patients with a high Notch risk score. In conclusion, our NLncS model is a promising biomarker for optimizing the clinical management of CRC patients.

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LncRNA profiles from Notch signaling: Implications for clinical management and tumor microenvironment of colorectal cancer

Background: Aldehyde dehydrogenase 2 (ALDH2) is well-known to be a key enzyme in alcohol metabolism. However, a comprehensive understanding of ALDH2 across human cancers is lacking. Methods: A systematic and comprehensive analysis of the molecular alterations and clinical relevance for ALDH2 in more than 10,000 samples from 33 cancer types was performed. qRT-PCR was performed on 60 cancer and 60 paired nontumor tissues. Results: It was observed that ALDH2 was generally downregulated in most cancers, which was mainly driven by DNA hypermethylation rather than mutations or copy number variations. Besides, ALDH2 was closely related to the inhibition and activation of tumor pathways and a variety of potential targeted agents had been discovered in our research. Last but not least, ALDH2 had the best prediction efficacy in assessing immunotherapeutic response compared with PD-L1, PD-1, CTLA4, CD8, and tumor mutation burden (TMB) in cutaneous melanoma. According to the analysis of large-scale public data and 60 pairs of clinical cancer samples, we found the downregulation of ALDH2 expression tends to suggest the malignant phenotypes and adverse prognosis, which might enhance the precise diagnosis and timely intervention of cancer patients. Conclusion: This study advanced the understanding of ALDH2 across cancers, and provided important insight into chemotherapy, immunotherapy and prognosis of patients with cancer.

Zaoqu Liu

Papers

Integrative bioinformatics analysis to explore a robust diagnostic signature and landscape of immune cell infiltration in sarcoidosis

Immunosenescence: molecular mechanisms and diseases

Integrative pharmacogenomics revealed three subtypes with different immune landscapes and specific therapeutic responses in lung adenocarcinoma

LncRNA profiles from Notch signaling: Implications for clinical management and tumor microenvironment of colorectal cancer

Molecular Characterization and Clinical Relevance of ALDH2 in Human Cancers