Although several animal and cell studies have described the association between HOXB9 and cancers, there is no pan-cancer investigation of HOXB9. In this article, we explored the expression levels and prognosis of HOXB9 in pan-cancer. We evaluated the correlation of HOXB9 expression level with the efficacy of immunotherapy.

Glucosamine-phosphate N-acetyltransferase 1 (GNPNAT1) is a key enzyme associated with glucose metabolism and uridine diphosphate-N-acetylglucosamine biosynthesis. Abnormal GNPNAT1 expression might be associated with carcinogenesis. We analyzed multiple lung adenocarcinoma (LUAD) gene expression databases and verified GNPNAT1 higher expression in LUAD tumor tissues than in normal tissues. Moreover, we analyzed the survival relationship between LUAD patients' clinical status and GNPNAT1 expression, and found higher GNPNAT1 expression in LUAD patients with unfavorable prognosis. We built GNPNAT1 gene co-expression networks and further annotated the co-expressed genes' Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and various associated regulatory factors. These co-expression genes' functional networks mainly participate in chromosome segregation, RNA metabolic process, and RNA transport. We analyzed GNPNAT1 genetic alterations and co-occurrence networks, and the functional networks of these genes showed that GNPNAT1 participates in multiple steps of cell cycle transition and in the development of some cancers. We assessed the correlation between GNPNAT1 expression and cancer immune infiltrates and showed that GNPNAT1 expression is correlated with several immune cells, chemokines, and immunomodulators in LUAD. We found that GNPNAT1 correlates with LUAD development and prognosis, laying a foundation for further research, especially in immunotherapy.

Intratumoral fibrosis is a frequent histologic finding in highly vascularized clear cell renal cell carcinoma (ccRCC). Here, we investigated the expression of a family of collagen-modifying enzymes, procollagen-lysine, 2-oxoglutarate 5-dioxygenases 1, 2, and 3 (PLOD1/2/3), in ccRCC tissues and assessed the prognostic value of wild-type and genetically mutated PLOD1/2/3 for ccRCC patients. Normal kidney and ccRCC mRNA and protein expression datasets were obtained from Oncomine, The Cancer Genome Atlas, and Human Protein Atlas databases. Associations between PLOD1/2/3 expression, clinicopathological variables, and patient survival were evaluated using Cox regression and Kaplan-Meier analyses. PLOD1/2/3 mRNA and protein expression levels were significantly elevated in ccRCC tissues compared with normal kidney. Increased PLOD1/2/3 mRNA expression was significantly associated with advanced tumor stage, high pathological grade, and shorter progression-free and overall survival (all p<0.01). Genetic mutation of PLOD1/2/3 was present in ~3% of ccRCC patients and was associated with significantly poorer prognosis compared with expression of wild-type PLOD1/2/3 (p<0.001). This study thus identifies tumor expression of wild-type or mutated PLOD1/2/3 mRNA as a potential predictive biomarker for ccRCC patients and sheds light on the underlying molecular pathogenesis of ccRCC.

Bladder cancer (BLCA) is one of the common malignant tumors of the urinary system. The poor prognosis of BLCA patients is due to the lack of early diagnosis and disease recurrence after treatment. Increasing evidence suggests that gene products of the nuclear factor of activated T-cells (NFAT) family are involved in BLCA progression and subsequent interaction(s) with immune surveillance. In this study, we carried out a pan-cancer analysis of the NFAT family and found that NFAT2 is an independent prognostic factor for BLCA. We then screened for differentially expressed genes (DEGs) and further analyzed such candidate gene loci using gene ontology enrichment to curate the KEGG database. We then used Lasso and multivariate Cox regression to identify 4 gene loci (FER1L4, RNF128, EPHB6, and FN1) which were screened together with NFAT2 to construct a prognostic model based on using Kaplan-Meier analysis to predict the overall survival of BLCA patients. Moreover, the accuracy of our proposed model is supported by deposited datasets in the Gene Expression Omnibus (GEO) database. Finally, a nomogram of this prognosis model for BLCA was established which could help to provide better disease management and treatment.

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers worldwide. Despite intense efforts to elucidate its pathogenesis, the molecular mechanisms and genetic characteristics of this cancer remain unknown. In this study, three expression profile data sets (GSE15641, GSE16441 and GSE66270) were integrated to identify candidate genes that could elucidate functional pathways in ccRCC. Expression data from 63 ccRCC tumors and 54 normal samples were pooled and analyzed. The GSE profiles shared 379 differentially expressed genes (DEGs), including 249 upregulated genes, and 130 downregulated genes. A protein-protein interaction network (PPI) was constructed and analyzed using STRING and Cytoscape. Functional and signaling pathways of the shared DEGs with significant p values were identified. Kaplan-Meier plots of integrated expression scores were used to analyze survival outcomes. These suggested that FN1, ICAM1, CXCR4, TYROBP, EGF, CAV1, CCND1 and PECAM1/CD31 were independent prognostic factors in ccRCC. Finally, to investigate early events in renal cancer, we screened for the hub genes CCND1 and PECAM1/CD31. In summary, integrated bioinformatics analysis identified candidate DEGs and pathways in ccRCC that could improve our understanding of the causes and underlying molecular events of ccRCC. These candidate genes and pathways could be therapeutic targets for ccRCC.