Yasi Xu

Glioma is the most prevalent and aggressive primary nervous system tumor with an unfavorable prognosis. Microtubule plus-end-related genes (MPERGs) play critical biological roles in the cell cycle, cell movement, ciliogenesis, and neuronal development by coordinating microtubule assembly and dynamics. This research seeks to systematically explore the oncological characteristics of these genes in microtubule-enriched glioma, focusing on developing a novel MPERG-based prognostic signature to improve the prognosis and provide more treatment options for glioma patients. First, we thoroughly analyzed and identified 45 differentially expressed MPERGs in glioma. Based on these genes, glioma patients were well distinguished into two subgroups with survival and tumor microenvironment infiltration differences. Next, we further screened the independent prognostic genes (CTTNBP2, KIF18A, NAV1, SLAIN2, SRCIN1, TRIO, and TTBK2) using 36 prognostic-related differentially expressed MPERGs to construct a signature with risk stratification and prognostic prediction ability. An increased risk score was related to the malignant progression of glioma. Therefore, we also designed a nomogram model containing clinical factors to facilitate the clinical use of the risk signature. The prediction accuracy of the signature and nomogram model was verified using The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. Finally, we examined the connection between the signature and tumor microenvironment. The signature positively correlated with tumor microenvironment infiltration, especially immunoinhibitors and the tumor mutation load, and negatively correlated with microsatellite instability and cancer stemness. More importantly, immune checkpoint blockade treatment and drug sensitivity analyses confirmed that this prognostic signature was helpful in anticipating the effect of immunotherapy and chemotherapy. In conclusion, this research is the first study to define and validate an MPERG-based signature closely associated with the tumor microenvironment as a reliable and independent prognostic biomarker to guide personalized choices of immunotherapy and chemotherapy for glioma patients.

Introduction: Radiation pneumonitis (RP) is the most significant dose-limiting toxicity in patients receiving thoracic radiotherapy. The underlying mechanisms of RP are still inconclusive. Our objective was to determine the genes and molecular pathways associated with RP using computational tools and publicly available data. Methods: RP-associated genes were determined by text mining, and the intersection of the two gene sets was selected for Gene Ontology analysis using the GeneCodis program. Protein-protein interaction network analysis was performed using STRINGdb to identify the final genes. Results: Our analysis identified 256 genes related to RP with text mining. The enriched biological process annotations resulted in 47 sets of annotations containing a total of 156 unique genes. KEGG analysis of the enriched pathways identified 24 pathways containing a total of 41 unique genes. The protein-protein interaction analysis yielded 23 genes (mostly the PI3K family). Conclusion: Gene discovery using in silico text mining and pathway analysis tools can facilitate the identification of the underlying mechanisms of RP.

Lung cancer is the second most common cancer with an extremely poor overall survival rate. Post-transcriptional regulation of gene expression play many important roles in human cancer, and one of the potential mechanisms underlying this is alternative mRNA maturation at its 3′ untranslated regions (3′-UTRs). Cancer tissues and paired adjacent normal lung tissues from 26 patients diagnosed with non-small cell lung cancer (NSCLC) were analyzed by in vitro transcription-sequencing alternative polyadenylation sites (IVT-SAPAS). 41,773,101 reads in average were obtained from each paired sample. A potential regulation of Cleavage Stimulation Factor Subunit 2 (CSTF2) on 3′UTR length of genes was tested in H460 cells. 1439 (10.26%) genes showed up-regulated expression and 1364 (9.72%) genes showed down-regulated expression in lung cancer tissue versus normal lung tissue, and shorten 3′UTR in cancer tissue was detected in cancer tissues collected from 96.2% (25/26) patients, indicating lung cancer tend to have shortened 3′UTRs of these identified genes. KEGG analysis showed 1855 genes with shorten 3′UTR were enriched in mTOR signaling, ubiquitin mediated proteolysis and RNA degradation. Knocking down CSTF2 expression in H460 cells results in 3′UTR elongation of genes that was identified to be with shortened length in cancer tissues. Alternative polyadenylation (APA) site-switching of 3′UTRs is prevalent in NSCLC, and CSTF2 may serve as an oncogene regulates the 3′UTR length of cancer related genes in NSCLC.