PIWIL4 and SUPT5H combine to predict prognosis and immune landscape in intrahepatic cholangiocarcinoma

RNA-binding protein transcripts as potential biomarkers for detecting Primary Sclerosing Cholangitis and for predicting its progression to Cholangiocarcinoma

Primary Sclerosing Cholangitis (PSC) is a persistent inflammatory liver condition that affects the bile ducts and is commonly diagnosed in young individuals. Despite efforts to incorporate various clinical, biochemical and molecular parameters for diagnosing PSC, it remains challenging, and no biomarkers characteristic of the disease have been identified hitherto. PSC is linked with an uncertain prognosis, and there is a pressing need to explore multiomics databases to establish a new biomarker panel for the early detection of PSC's gradual progression into Cholangiocarcinoma (CCA) and for the development of effective therapeutic interventions. Apart from non-coding RNAs, other components of the Ribonucleoprotein (RNP) complex, such as RNA-Binding Proteins (RBPs), also hold great promise as biomarkers due to their versatile expression in pathological conditions. In the present review, an update on the RBP transcripts that show dysregulated expression in PSC and CCA is provided. Moreover, by utilizing a bioinformatic data mining approach, we give insight into those RBP transcripts that also exhibit differential expression in liver and gall bladder, as well as in body fluids, and are promising as biomarkers for diagnosing and predicting the prognosis of PSC. Expression data were bioinformatically extracted from public repositories usingTCGA Bile Duct Cancer dataset for CCA and specific NCBI GEO datasets for both PSC and CCA; more specifically, RBPs annotations were obtained from RBP World database. Interestingly, our comprehensive analysis shows an elevated expression of the non-canonical RBPs, FANCD2, as well as the microtubule dynamics regulator, ASPM, transcripts in the body fluids of patients with PSC and CCA compared with their respective controls, with the same trend in expression being observed in gall bladder and liver cancer tissues. Consequently, the manipulation of tissue expression of RBP transcripts might be considered as a strategy to mitigate the onset of CCA in PSC patients, and warrants further experimental investigation. The analysis performed herein may be helpful in the identification of non-invasive biomarkers for the early detection of PSC and for predicting its progression into CCA. In conclusion, future clinical research should investigate in more depth the full potential of RBP transcripts as biomarkers for human pathologies.

Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma is a kind of epithelial cell malignancy with high mortality. Intratumor heterogeneity (ITH) is involved in tumor progression, aggressiveness, treatment resistance, and disease recurrence.

METHODS

Integrative machine learning procedure including 10 methods (random survival forest, elastic network, Lasso, Ridge, stepwise Cox, CoxBoost, partial least squares regression for Cox, supervised principal components, generalized boosted regression modeling, and survival support vector machine) was performed to construct an ITH-related signature (IRS) for cholangiocarcinoma. Single cell analysis was performed to clarify the communication between immune cell subtypes. Cellular experiment was used to verify the biological function of hub gene.

RESULTS

The optimal prognostic IRS developed by Lasso method served as an independent risk factor and had a stable and powerful performance in predicting the overall survival rate in cholangiocarcinoma, with the AUC of 2-, 3-, and 4-year ROC curve being 0.955, 0.950 and 1.000 in TCGA cohort. low IRS score indicated with a lower tumor immune dysfunction and exclusion score, lower tumor microsatellite instability, lower immune escape score, lower MATH score, and higher mutation burden score in cholangiocarcinoma. Single cell analysis revealed a strong communication between fibroblasts, microphage and epithelial cells by specific ligand-receptor pairs, including COL4A1-(ITGAV+ITGB8) and COL1A2-(ITGAV+ITGB8). Down-regulation of BET1L inhibited the proliferation, migration and invasion as well as promoted apoptosis of cholangiocarcinoma cell.

CONCLUSION

Integrative machine learning analysis was performed to construct a novel IRS in cholangiocarcinoma. This IRS acted as an indicator for predicting the prognosis and immunotherapy benefits of cholangiocarcinoma patients.

Novel roles of PIWI proteins and PIWI-interacting RNAs in human health and diseases

Non-coding RNA has aroused great research interest recently, they play a wide range of biological functions, such as regulating cell cycle, cell proliferation, and intracellular substance metabolism. Piwi-interacting RNAs (piRNAs) are emerging small non-coding RNAs that are 24-31 nucleotides in length. Previous studies on piRNAs were mainly limited to evaluating the binding to the PIWI protein family to play the biological role. However, recent studies have shed more lights on piRNA functions; aberrant piRNAs play unique roles in many human diseases, including diverse lethal cancers. Therefore, understanding the mechanism of piRNAs expression and the specific functional roles of piRNAs in human diseases is crucial for developing its clinical applications. Presently, research on piRNAs mainly focuses on their cancer-specific functions but lacks investigation of their expressions and epigenetic modifications. This review discusses piRNA's biogenesis and functional roles and the recent progress of functions of piRNA/PIWI protein complexes in human diseases. Video Abstract.

Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.

Exploring the oncogenic roles of LINC00857 in pan-cancer

Although aberrant LINC00857 expression may play a key role in oncogenesis, no research has analyzed the pan-cancer oncogenic roles of LINC00857, particularly in tumor immunology. Here, we integrated data from several databases to analyze the characteristics of LINC00857 in pan-cancer. We found that LINC00857 was overexpressed and correlated with a poor prognosis in a variety of cancers. Furthermore, high-expression of LINC00857 was negatively associated with immune cell infiltration and immune checkpoint gene expression. Notably, LINC00857 expression was negatively related to microsatellite instability and tumor mutation burden in colorectal cancer, implying poor reaction to immunotherapy when LINC00857 was highly expressed. Targeting LINC00857 could dramatically impair the proliferative ability of colorectal cancer cells. After RNA-sequencing in HCT116 cells, gene set enrichment analysis showed that LINC00857 may accelerate cancer progression by inhibiting the ferroptosis pathway and promoting glycolipid metabolism in colorectal cancer. Screening by weighted gene co-expression network analysis determined PIWIL4 as a target of LINC00857, which also performed an immunosuppressive role in colorectal cancer. Based on the structure of PIWIL4, a number of small molecule drugs were screened out by virtual screening and sensitivity analysis. In summary, LINC00857 expression was closely correlated with an immunosuppressive microenvironment and may be a novel diagnostic and prognostic biomarker for diverse cancers. The LINC00857/PIWIL4 axis may be predictive biomarkers for immunotherapy and valuable molecular targets for malignant tumors.

TP53 /KRAS Co-Mutations Create Divergent Prognosis Signatures in Intrahepatic Cholangiocarcinoma

Background: Due to high invasiveness and heterogeneity, the morbidity and mortality of intrahepatic cholangiocarcinoma (ICC) remain unsatisfied. Recently, the exploration of genomic variants has decoded the underlying mechanisms of initiation and progression for multiple tumors, while has not been fully investigated in ICC.

Methods: We comprehensively analyzed 899 clinical and somatic mutation data of ICC patients from three large-scale cohorts. Based on the mutation landscape, we identified the common high-frequency mutation genes (FMGs). Subsequently, the clinical features, prognosis, tumor mutation burden (TMB), and pharmacological landscape from patients with different mutation carriers were further analyzed.

Results: We found TP53 and KRAS were the common FMGs in the three cohorts. Kaplan–Meier survival curves and univariate and multivariate analysis displayed that TP53 and KRAS mutations were associated with poor prognosis. Considering the co-mutation phenomenon of TP53 and KRAS, we stratified patients into “Double-WT,” “Single-Hit,” and “Double-Hit” phenotypes by mutation status. Patients with the three phenotypes showed significant differences in the mutation landscape. Additionally, compared with “Double-WT” and “Single-Hit” phenotypes, patients with “Double-Hit” presented a dismal prognosis and significantly high TMB. Through chemotherapy sensitivity analysis, we identified a total of 30 sensitive drugs for ICC patients, of which 22 were drugs sensitive to “Double-WT,” 7 were drugs sensitive to “Double-Hit,” and only one was a drug sensitive to “Single-Hit.”

Conclusion: Our study defined a novel mutation classification based on the common FMGs, which may contribute to the individualized treatment and management of ICC patients.