Biomarkers prediction and immune landscape in ulcerative colitis: Findings based on bioinformatics and machine learning

BACKGROUND

Ulcerative colitis (UC) presents diagnostic and therapeutic difficulties. The primary objective of this study is to identify efficacious biomarkers for diagnosis and treatment, as well as acquire a deeper understanding of the immuneological characteristics associated with the disease.

METHODS

Datasets relating to UC were obtained from GEO database. Among these, three datasets were merged to create a metadata for bioinformatics analysis and machine learning. Additionally, one dataset specifically utilized for external validation. Least absolute shrinkage and selection operator (LASSO) and random forest (RF) were employed to screen signature genes. The artificial neural network (ANN) model and receiver operating characteristic (ROC) curve were used to assess the diagnostic performance of signature genes. The single sample gene set enrichment analysis (ssGSEA) was applied to reveal the immune landscape. Finally, the relationship between the signature genes, immune infiltration, and clinical characteristics was investigated through correlation analysis.

RESULT

By intersecting the result of LASSO, RF and WGCNA, 8 signature genes were identified, including S100A8, IL-1B, CXCL1, TCN1, MMP10, GREM1, DUOX2 and SLC6A14. The biological progress of this gene mostly encompasses acute inflammatory response, aggregation and chemotaxis of leukocyte, and response to lipopolysaccharide by mediating IL-17 signaling pathway, NF-kappa B signaling pathway, TNF signaling pathway, NOD-like receptor signaling pathway. Immune infiltration analysis shows 25 immune cells are significantly elevated in UC samples. Moreover, these signature genes exhibit a strong correlation with various immune cells and a mild to moderate correlation with the Mayo score.

CONCLUSION

S100A8, IL-1B, CXCL1, TCN1, MMP10, GREM1, DUOX2 and SLC6A14 have been identified as credible potential biomarkers for the diagnosis and therapy of UC. The immune response mediated by these signature biomarkers plays a crucial role in the occurrence and advancement of UC by means of the reciprocal interaction between the signature biomarkers and immune-infiltrated cells.

Biological role of long non-coding RNA KCNQ1OT1 in cancer progression

Long non-coding RNAs (lncRNAs) are a type of RNAs that are more than 200 nucleotides without protein-coding potential. In recent years, more and more attention has been paid to the role of lncRNAs in cancer pathogenesis. LncRNA KCNQ1 overlapping transcript 1 (KCNQ1OT1) is located on chromosome 11p15.5 with a total length of 91 kb and is highly expressed in various malignancies, which is closely related to tumor growth, lymph node metastasis, survival cycle and recurrence rate. In addition, KCNQ1OT1 is involved in the regulation of PI3K/AKT and Wnt/β-catenin signaling pathways. In this review, the mechanism and related progress of KCNQ1OT1 in different cancers were reviewed. It was found that KCNQ1OT1 can stabilize mRNA expression through sponging miRNA, which not only induced tumor cell proliferation, migration, invasion, drug resistance, epithelial-mesenchymal transition (EMT) and inhibited cell apoptosis in vitro, but also promoted tumor growth and metastasis in vivo. Therefore, as a new biomarker and therapeutic target, KCNQ1OT1 has broad prospects for the diagnosis and treatment of different cancers.

Efficacy and Safety of Washed Microbiota Transplantation to Treat Patients with Mild-to-Severe COVID-19 and Suspected of Having Gut Microbiota Dysbiosis: Study Protocol for a Randomized Controlled Trial

OBJECTIVE

Coronavirus disease 2019 (COVID-19) is often accompanied by gastrointestinal symptoms, which are related to gut microbiota dysbiosis (GMD). Whether washed microbiota transplantation (WMT) is an effective treatment for COVID-19 patients suspected of having GMD by restoring the gut microbiota is unknown. This study is designed to explore the efficacy and safety of WMT in COVID-19 patients suspected of having GMD.

METHODS

This is a randomized, multicenter, single-blind prospective study. COVID-19 patients suspected of having GMD will be randomly divided to receive routine treatment only or to receive routine treatment and WMT. The frequency of WMT will be once a day for three consecutive days. Laboratory and imaging examinations will be performed at admission, 1 and 2 weeks after treatment, and on the day of discharge. Then a telephone follow-up will be conducted at 1st week, 2nd week, and 6th month after discharge. The clinical efficacy and safety of WMT in COVD-19 patients suspected of having GMD and the effects of WMT on the organ function, homeostasis, inflammatory response, intestinal mucosal barrier function, and immunity of the patients will be evaluated.

RESULTS

By following the proposed protocol, WMT is expected to be efficacious and safe for the treatment of COVID-19 patients suspected of having GMD, and the therapeutic effect is expected to be associated with improvement of the intestinal mucosal barrier function, inflammatory response, and immunity.

CONCLUSION

The findings from this study may offer a new approach for the prevention and treatment of COVID-19 patients suspected of having GMD.