Identification of Key Biomarkers and Candidate Molecules in Non-Small-Cell Lung Cancer by Integrated Bioinformatics Analysis.

Background: Non-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis. Methods: From the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools. Results: We found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis (P < 0.05). We also found that the expression of SPP1 was associated with miR-146a-5p, while the high expression of miR-146a-5p was related to good prognosis (P < 0.05). On the contrary, the lower miR-21-5p on upstream of PIK3R1 is associated with a higher surviving rate in cancer patients (P < 0.05). Finally, we found that the immune checkpoint genes CD274(PD-L1) and PDCD1LG2(PD-1) were also related to SPP1 in lung adenocarcinoma. Conclusions: The results indicated that SPP1 is a cancer promoter (oncogene), while PECAM1 and PIK3R1 are cancer suppressor genes. These genes take part in the regulation of biological activities in lung adenocarcinoma, which provides a basis for improving detection and immunotherapeutic targets for lung adenocarcinoma.

The relationship between prognosis and temporal muscle thickness in 102 patients with glioblastoma.

Temporal muscle thickness measured on 3D MRI has recently been linked to prognosis in glioblastoma patients and may serve as an independent prognostic indicator. This single-center study looked at temporal muscle thickness and prognosis in patients with primary glioblastoma. Overall survival was the major study outcome. For a retrospective analysis from 2010 to 2020, clinical data from 102 patients with glioblastoma at the Department of Oncology Radiotherapy of the First Affiliated Hospital of Dalian Medical University were gathered. Fifty-five cases from 2016 to 2020 contained glioblastoma molecular typing data, of which 45 were IDH wild-type glioblastomas and were analysed separately. TMT was measured on enhanced T1-weighted magnetic resonance images in patients with newly diagnosed glioblastoma.Overall patient survival (OS) was calculated by the Kaplan-Meier method and survival curves were plotted using the log-rank-sum test to determine differences between groups, and multifactorial analyses were performed using a Cox proportional-risk model.The median TMT for 102 patients was 6.775 mm (range: 4.95-10.45 mm). Patients were grouped according to median TMT, and the median overall survival (23.0 months) was significantly longer in the TMT > median group than in the TMT median group (P 0.001; Log-rank test). Analysing 45 patients with IDH wild type alone, the median overall survival (12 months) of patients in the TMT > median group was significantly longer than that of patients in the TMT ≤ median group (8 months) (P < 0.001; Log-rank test).TMT can serve as an independent prognostic factor for glioblastoma.

A simplified non-coplanar volumetric modulated arc therapy for the whole brain radiotherapy with hippocampus avoidance.

Purpose: To evaluate the feasibility of using a simplified non-coplanar volumetric modulated arc therapy (NC-VMAT) and investigate its dosimetric advantages compared with intensity modulated radiation therapy (IMRT) and coplanar volumetric modulated arc therapy (C-VMAT) for hippocampal-avoidance whole brain radiation therapy (HA-WBRT). Methods: Ten patients with brain metastase (BM) were included for HA-WBRT. Three treatment plans were generated for each case using IMRT, C-VMAT, and NC-VMAT, respectively. Results: The dosimetric results of the three techniques complied roughly with the RTOG 0933 criteria. After dose normalization, the V30Gy of whole brain planned target volume (WB-PTV) in all the plans was controlled at 95%. Homogeneity index (HI) of WB-PTV was significantly reduced in NC-VMAT (0.249 ± 0.017) over IMRT (0.265 ± 0.020, p=0.005) and C-VMAT (0.261 ± 0.014, p=0.020). In terms of conformity index (CI), NC-VMAT could provide a value of 0.821 ± 0.010, which was significantly superior to IMRT (0.788 ± 0.019, p<0.001). According to D2% of WB-PTV, NC-VMAT could provide a value of 35.62 ± 0.37Gy, significantly superior to IMRT (36.43 ± 0.65Gy, p<0.001). According to D50% of WB-PTV, NC-VMAT can achieve the lowest value of 33.18 ± 0.29Gy, significantly different from IMRT (33.47 ± 0.43, p=0.034) and C-VMAT (33.58 ± 0.37, p=0.006). Regarding D2%, D98%, and Dmean of hippocampus, NC-VMAT could control them at 15.57 ± 0.18Gy, 8.37 ± 0.26Gy and 11.71 ± 0.48Gy, respectively. D2% and Dmean of hippocampus for NC-VMAT was significantly lower than IMRT (D2%: 16.07 ± 0.29Gy, p=0.001 Dmean: 12.18 ± 0.33Gy, p<0.001) and C-VMAT (D2%: 15.92 ± 0.37Gy, p=0.009 Dmean: 12.21 ± 0.54Gy, p<0.001). For other organs-at-risk (OARs), according to D2% of the right optic nerves and the right lenses, NC-VMAT had the lowest values of 31.86 ± 1.11Gy and 7.15 ± 0.31Gy, respectively, which were statistically different from the other two techniques. For other organs including eyes and optic chiasm, NC-VMAT could achieve the lowest doses, different from IMRT statistically. Conclusion: The dosimetry of the three techniques for HA-WBRT could roughly comply with the proposals from RTOG 0933. After dose normalization (D95%=30Gy), NC-VMAT could significantly improve dose homogeneity and reduce the D50% in the brain. Besides, it can reduce the D2% of the hippocampus, optic nerves, and lens. With this approach, an efficient and straightforward plan was accomplished.

Advances in the relationship between temporal muscle thickness and prognosis of patients with glioblastoma: a narrative review.

The most dangerous variety of glioma, glioblastoma, has a high incidence and fatality rate. The prognosis for patients is still bleak despite numerous improvements in treatment approaches. We urgently need to develop clinical parameters that can evaluate patients' conditions and predict their prognosis. Various parameters are available to assess the patient's preoperative performance status and degree of frailty, but most of these parameters are subjective and therefore subject to interobserver variability. Sarcopenia can be used as an objective metric to measure a patient's physical status because studies have shown that it is linked to a bad prognosis in those with cancers. For the purpose of identifying sarcopenia, temporal muscle thickness has demonstrated to be a reliable alternative for a marker of skeletal muscle content. As a result, patients with glioblastoma may use temporal muscle thickness as a potential marker to correlate with the course and fate of their disease. This narrative review highlights and defines the viability of using temporal muscle thickness as an independent predictor of survival in glioblastoma patients, and it evaluates recent research findings on the association between temporal muscle thickness and prognosis of glioblastoma patients.

RBM4 regulates cellular senescence via miR1244/SERPINE1 axis.

Cellular senescence serves as a powerful tumor suppressing mechanism that inhibits the proliferation of cancer cells bearing oncogenic mutations at the initial stage of cancer development. RNA-binding proteins (RBPs) play important roles in cancer progression and treatment through distinct functions. However, functions and mechanisms of RNA binding proteins in regulating senescence remain elusive. Here we reported that the RNA binding protein RBM4 contributed to cellular senescence. Depletion of RBM4 induced senescence in different types of cells, including multiple cancer cells. Meanwhile, RBM4 ablation inhibited cancer cell progression both in vitro and in vivo. Specifically, knockdown of RBM4 significantly increased the level of SERPINE1, a known promoter of senescence, thereby inducing the senescence of lung cancer cells. Mechanistically, miR-1244 bound to the 3'-UTR of SERPINE1 to suppress its expression, whereas depletion of RBM4 reduced the level of miR-1244 by promoting the degradation of primary miR-1244 transcripts (pri-miR1244), thus increasing the expression of SERPINE1 and inducing subsequent senescence. Moreover, either SERPINE1 inhibitor or miR-1244 mimics attenuated the RBM4 depletion-induced senescence. Altogether, our study revealed a novel mechanism of RBM4 in the regulation of cancer progression through controlling senescence, providing a new avenue for targeting RBM4 in cancer therapeutics.

SRSF1 inhibits autophagy through regulating Bcl-x splicing and interacting with PIK3C3 in lung cancer.

Alternative splicing is a critical process to generate protein diversity. However, whether and how alternative splicing regulates autophagy remains largely elusive. Here we systematically identify the splicing factor SRSF1 as an autophagy suppressor. Specifically, SRSF1 inhibits autophagosome formation by reducing the accumulation of LC3-II and numbers of autophagosomes in different cell lines. Mechanistically, SRSF1 promotes the splicing of the long isoform of Bcl-x that interacts with Beclin1, thereby dissociating the Beclin1-PIK3C3 complex. In addition, SRSF1 also directly interacts with PIK3C3 to disrupt the interaction between Beclin1 and PIK3C3. Consequently, the decrease of SRSF1 stabilizes the Beclin1 and PIK3C3 complex and activates autophagy. Interestingly, SRSF1 can be degraded by starvation- and oxidative stresses-induced autophagy through interacting with LC3-II, whereas reduced SRSF1 further promotes autophagy. This positive feedback is critical to inhibiting Gefitinib-resistant cancer cell progression both in vitro and in vivo. Consistently, the expression level of SRSF1 is inversely correlated to LC3 level in clinical cancer samples. Our study not only provides mechanistic insights of alternative splicing in autophagy regulation but also discovers a new regulatory role of SRSF1 in tumorigenesis, thereby offering a novel avenue for potential cancer therapeutics.

Second-Generation Sequencing with Deep Reinforcement Learning for Lung Infection Detection.

Recently, deep reinforcement learning, associated with medical big data generated and collected from medical Internet of Things, is prospective for computer-aided diagnosis and therapy. In this paper, we focus on the application value of the second-generation sequencing technology in the diagnosis and treatment of pulmonary infectious diseases with the aid of the deep reinforcement learning. Specifically, the rapid, comprehensive, and accurate identification of pathogens is a prerequisite for clinicians to choose timely and targeted treatment. Thus, in this work, we present representative deep reinforcement learning methods that are potential to identify pathogens for lung infection treatment. After that, current status of pathogenic diagnosis of pulmonary infectious diseases and their main characteristics are summarized. Furthermore, we analyze the common types of second-generation sequencing technology, which can be used to diagnose lung infection as well. Finally, we point out the challenges and possible future research directions in integrating deep reinforcement learning with second-generation sequencing technology to diagnose and treat lung infection, which is prospective to accelerate the evolution of smart healthcare with medical Internet of Things and big data.

SRSF1 modulates PTPMT1 alternative splicing to regulate lung cancer cell radioresistance.

BACKGROUND: Radioresistance is the major cause of cancer treatment failure. Additionally, splicing dysregulation plays critical roles in tumorigenesis. However, the involvement of alternative splicing in resistance of cancer cells to radiotherapy remains elusive. We sought to investigate the key role of the splicing factor SRSF1 in the radioresistance in lung cancer. METHODS: Lung cancer cell lines, xenograft mice models, and RNA-seq were employed to study the detailed mechanisms of SRSF1 in lung cancer radioresistance. Clinical tumor tissues and TCGA dataset were utilized to determine the expression levels of distinct SRSF1-regulated splicing isoforms. KM-plotter was applied to analyze the survival of cancer patients with various levels of SRSF1-regulated splicing isoforms. FINDINGS: Splicing factors were screened to identify their roles in radioresistance, and SRSF1 was found to be involved in radioresistance in cancer cells. The level of SRSF1 is elevated in irradiation treated lung cancer cells, whereas knockdown of SRSF1 sensitizes cancer cells to irradiation. Mechanistically, SRSF1 modulates various cancer-related splicing events, particularly the splicing of PTPMT1, a PTEN-like mitochondrial phosphatase. Reduced SRSF1 favors the production of short isoforms of PTPMT1 upon irradiation, which in turn promotes phosphorylation of AMPK, thereby inducing DNA double-strand break to sensitize cancer cells to irradiation. Additionally, the level of the short isoform of PTPMT1 is decreased in cancer samples, which is correlated to cancer patients' survival. CONCLUSIONS: Our study provides mechanistic analyses of aberrant splicing in radioresistance in lung cancer cells, and establishes SRSF1 as a potential therapeutic target for sensitization of patients to radiotherapy.

Bioinformatics analysis of SRSF1-controlled gene networks in colorectal cancer.

Colorectal cancer is the third most common type of cancer and the fourth leading cause of cancer-associated mortality worldwide. Serine/arginine-rich splicing factor 1 (SRSF1) is a well-characterized oncogenic factor that promotes tumorigenesis by controlling a number of alternative splicing events. However, there is limited network analysis, from a global aspect, to study the effect of SRSF1 on colorectal cancer. In the present study, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of available gene regulation data from The Cancer Genome Atlas database revealed the enriched functions and signaling pathways of SRSF1. Subsequently, Oncomine analysis was performed, which demonstrated that SRSF1 was upregulated in a number of types of colon cancer. From overlapping the analysis of 2,678 SRSF1-related genes and 3,625 colorectal cancer genes in GeneCards, 468 genes were identified as SRSF1-related colorectal cancer genes. The GO results revealed that these overlapped genes were primarily enriched in metabolic processes, response to DNA damage, regulation of the cell cycle and a number of additional biological processes. KEGG pathway analysis revealed that SRSF1-related colorectal cancer genes were associated with the cell cycle, deregulated signaling pathways associated with cancer progression and colorectal cancer signaling pathways. In addition, the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape analysis demonstrated that 468 SRSF1-related colorectal cancer genes exhibit potential interaction networks in which these genes were enriched in DNA metabolic processes, cell cycle regulation and regulation of apoptosis. The results of the present study suggested that SRSF1 exhibited an increased degree of interaction with key molecules, including NUF2 NDC80 kinetochore complex component, kinesin family member 2C, structural maintenance of chromosomes 3, ATM serine/threonine kinase, BRCA1 DNA repair associated, protein kinase DNA-activated catalytic polypeptide, heat shock protein 90 alpha family class A member 1, ras homolog family member A, and phosphatase and tensin homolog. Collectively, the bioinformatics analysis of the present study indicated that SRSF1 may have key functions in the progression and development of colorectal cancer.