{"title":"Insight into NSCLC through novel analysis of gene interactions and characteristics.","authors":"Eric Pan, Yongsheng Bai","doi":"10.62347/ANLV4963","DOIUrl":null,"url":null,"abstract":"<p><p>Around 80 to 85% of all lung cancers are non-small cell lung cancer (NSCLC). Previous research has aimed at exploring the genetic basis of NSCLC through individual approaches, but studies have yet to investigate the results of combining them. Here we show that analyzing NSCLC genetics through three approaches simultaneously creates unique insights into our understanding of the disease. Through a combination of previous research and bioinformatics tools, we determined 35 NSCLC candidate genes. We analyzed these genes in 3 different approaches. First, we found the gene fusions between these candidate genes. Second, we found the common superfamilies between genes. Finally, we identified mutational signatures that are possibly associated with NSCLC. Each approach has its individual, unique results. Fusion relationships identify specific gene fusion targets, common superfamilies identify possible avenues to determine novel target genes, and identifying NSCLC associated mutational signatures has diagnostic and prognostic benefits. Combining the approaches, we found that gene CD74 has significant fusion relationships, but it has no association with the other two approaches, suggesting that CD74 is associated with NSCLC mainly because of its fusion relationships. Targeting the gene fusions of CD74 may be an alternative NSCLC treatment. This genetic analysis has indeed created unique insight into NSCLC genes. Both the results from each of the approaches separately and combined allow pursuit of more effective treatment strategies for this cancer. The methodology presented can also apply to other cancers, creating insights that current analytical methods could not find.</p>","PeriodicalId":72163,"journal":{"name":"American journal of clinical and experimental immunology","volume":"13 2","pages":"58-67"},"PeriodicalIF":1.4000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11101995/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of clinical and experimental immunology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.62347/ANLV4963","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Around 80 to 85% of all lung cancers are non-small cell lung cancer (NSCLC). Previous research has aimed at exploring the genetic basis of NSCLC through individual approaches, but studies have yet to investigate the results of combining them. Here we show that analyzing NSCLC genetics through three approaches simultaneously creates unique insights into our understanding of the disease. Through a combination of previous research and bioinformatics tools, we determined 35 NSCLC candidate genes. We analyzed these genes in 3 different approaches. First, we found the gene fusions between these candidate genes. Second, we found the common superfamilies between genes. Finally, we identified mutational signatures that are possibly associated with NSCLC. Each approach has its individual, unique results. Fusion relationships identify specific gene fusion targets, common superfamilies identify possible avenues to determine novel target genes, and identifying NSCLC associated mutational signatures has diagnostic and prognostic benefits. Combining the approaches, we found that gene CD74 has significant fusion relationships, but it has no association with the other two approaches, suggesting that CD74 is associated with NSCLC mainly because of its fusion relationships. Targeting the gene fusions of CD74 may be an alternative NSCLC treatment. This genetic analysis has indeed created unique insight into NSCLC genes. Both the results from each of the approaches separately and combined allow pursuit of more effective treatment strategies for this cancer. The methodology presented can also apply to other cancers, creating insights that current analytical methods could not find.