首页|Southern Medical University Reports Findings in Cancer (Singlecell and whole-transcriptome sequencing of lymph node metastasisrelated gene signature: A large-scale pan-cancer cohort, machine learning and experimental study)
Southern Medical University Reports Findings in Cancer (Singlecell and whole-transcriptome sequencing of lymph node metastasisrelated gene signature: A large-scale pan-cancer cohort, machine learning and experimental study)
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New research on Cancer is the subject of a report. According to news reporting from Guangdong, People’s Republic of China, by NewsRx journalists, research stated, “Lymph node metastasis (LNM) is an independent prognostic factor in numerous types of cancer. Therefore, a LNM-related genebased nomogram may precisely predict survival and drug sensitivity, and reveal the mechanism underlying LNM.” The news correspondents obtained a quote from the research from Southern Medical University, “Gene sequencing profiles of pan-cancer data (33 cancer types) were acquired from The Cancer Genome Atlas UCSC Xena database. Patients were classified into primary (N = 10,071) and testing (N = 5,036) cohorts. The lymph node score (LNscore) was established via single-cell RNA sequencing, whole-transcriptome sequencing, machine learning, and Cox regression analyses. A novel prognosis model, formulated by incorporating the LNscore and clinical characteristics, was evaluated using the concordance index, calibration curve, and decision curve analysis. Moreover, patients were assigned into high- and low-risk groups according to the median LNscore. We investigated these two groups for survival prognosis, functional enrichment, immune infiltration, and drug sensitivity. In addition, we silenced and overexpressed insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2). We also analyzed the behavior of breast cancer (BRCA) cells regarding lymphatic metastasis and lymphangiogenesis in vitro. IGF2BP2 stimulated the proliferation of BRCA cells via 5-Ethynyl-2’-deoxyuridine and Cell Counting Kit-8 experiments. A LNM-related set of 12 genes was identified and utilized to determine the LNscore. The concordance-index of both cohorts in the LNscore-based model was >0.7. The immune landscape revealed that the sensitivity to immunotherapy might be better in the high-risk group versus the low-risk group. In addition, we discovered that IGF2BP2 was overexpressed in BRCA tissues and significantly associated with poor survival. Functional analysis indicated that IGF2BP2 promoted BRCA cell migration and proliferation. Additionally, IGF2BP2 accelerated lymphatic metastasis and lymphangiogenesis in vivo. A novel LNscore-based model was established via comprehensive analysis of LNM-related genes.”
GuangdongPeople’s Republic of ChinaAsiaCancerCyborgsEmerging TechnologiesGeneticsHealth and MedicineHemic and Immune SystemsImmunologyLymph NodesLymphoid TissueMachine LearningOncology
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