Lung cancer is the leading cause of mortality from cancer worldwide. Lung adenocarcinoma (LUAD) is a type of non-small cell lung cancer (NSCLC) with highest prevalence. Kinesins a class of motor proteins are shown to be involved in carcinogenesis. We conducted expression, stage plot and survival analyses on kinesin superfamily (KIF) and scrutinized the key prognostic kinesins. Genomic alterations of these kinesins were studied thereafter via cBioPortal. A protein–protein interaction network (PPIN) of selected kinesins and 50 closest altering genes was constructed followed by gene ontology (GO) term and pathway enrichment analyses. Multivariate survival analysis based on CpG methylation of selected kinesins was performed. Lastly, we conducted tumor immune infiltration analysis. Our results found KIF11/15/18B/20A/2C/4A/C1 to be significantly upregulated and correlated with poor survival in LUAD patients. These genes also showed to be highly associated with cell cycle. Out of our seven selected kinesins, KIFC1 showed the highest genomic alteration with highest number of CpG methylation. Also, CpG island (CGI) cg24827036 was discovered to be linked to LUAD prognosis. Therefore, we deduced that reducing the expression of KIFC1 could be a feasible treatment strategy and that it can be a wonderful individual prognostic biomarker. CGI cg24827036 can also be used as a therapy site in addition to being a great prognostic biomarker.

Background Hepatocellular carcinoma (HCC) is the most common primary liver cancer. It has the sixth most incident cases with poor prognosis. Adipokines are known to have been linked with oncogenesis and progression of HCC. Methods We extracted TCGA-HCC data and identified differentially expressed genes (DEGs) using R. Genes of adipokines and adipogenesis family were scrutinized from DEGs and expression of genes in normal versus tumor patients was studied. Prognostic and stage plot analyses were performed, and key genes were selected. Pathway and gene ontology (GO) enrichment analysis was conducted. Expression analysis based on nodal metastasis, tumor protein p53 (TP53) mutation and tumor grade, and mutation analysis was performed using UALCAN and cBioPortal. Tumor infiltration analysis was performed to study the correlation of gene expression with tumor-infiltrating immune cells. Results We found four genes apelin (APLN), aldehyde dehydrogenase, mitochondrial (ALDH2), E2F transcription factor 1 (E2F1) and phosphoenolpyruvate carboxykinase, cytosolic (PCK1) highly associated with HCC. APLN and E2F1 were upregulated and ALDH2 and PCK1 were downregulated in HCC patients. High expression of APLN and E2F1 and low expression of ALDH2 and PCK1 resulted in poor prognosis of HCC patients. In expression analysis, ALDH2 showed significant change in all three categories. PCK1 showed highest mutation of out all $$4$$ 4 genes in HCC patients. T cell CD8+ is found to be positively correlated with APLN, ALDH2 and E2F1 and macrophages showed a positive correlation with APLN and E2F1. Conclusions ALDH2 and PCK1 are great prognostic biomarkers and play a vital role in the development of HCC. Overexpression of ALDH2 and PCK1 can be a potential treatment strategy for HCC.