Comprehensive analysis of Transcription Factors identified novel prognostic biomarker in human bladder cancer

Identification of bladder cancer subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes

Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.

Exploring the Relationship between CLPTM1L-MS2 Variants and Susceptibility to Bladder Cancer

CLPTM1L (Cleft Lip and Palate Transmembrane Protein 1-Like) has previously been implicated in tumorigenesis and drug resistance in cancer. However, the genetic link between CLPTM1L and bladder cancer remains uncertain. In this study, we investigated the genetic association of variable number of tandem repeats (VNTR; minisatellites, MS) regions within CLPTM1L with bladder cancer. We identified four CLPTM1L-MS regions (MS1~MS4) located in intron regions. To evaluate the VNTR polymorphic alleles, we analyzed 441 cancer-free controls and 181 bladder cancer patients. Our analysis revealed a higher frequency of specific repeat sizes within the MS2 region in bladder cancer cases compared to controls. Notably, 25 and 27 repeats were exclusively present in the bladder cancer group. Moreover, rare alleles within the medium-length repeat range (25-29 repeats) were associated with an elevated bladder cancer risk (odds ratio [OR] = 5.78, 95% confidence interval [CI]: 1.49-22.47, p = 0.004). We confirmed that all MS regions followed Mendelian inheritance, and demonstrated that MS2 alleles increased CLPTM1L promoter activity in the UM-UC3 bladder cancer cells through a luciferase assay. Our findings propose the utility of CLPTM1L-MS regions as DNA typing markers, particularly highlighting the potential of middle-length rare alleles within CLPTM1L-MS2 as predictive markers for bladder cancer risk.

Involvement of toxic metals and PCBs mixture in the thyroid and male reproductive toxicity: In silico toxicogenomic data mining

Toxicological research is mostly limited to considering the effects of a single substance, even though the real exposure of people is reflected in their daily exposure to many different chemical substances in low-doses. This in silico toxicogenomic study aims to provide evidence for the selected environmental (organo)metals (lead, cadmium, methyl mercury) + polychlorinated biphenyls mixture involvement in the possible alteration of thyroid, and male reproductive system function, and furthermore to predict the possible toxic mechanisms of the environmental cocktail. The Comparative Toxicogenomic Database, GeneMANIA online software, and ToppGene Suite portal were used as the main tools for toxicogenomic data mining and gene ontology analysis. The results show that 35 annotated common genes between selected chemicals and endocrine system diseases can interact on the co-expression level. Our study highlighted the disruption of the cytokines, the cell's response to oxidative stress, and the influence of the transcription factors as the potential core of toxicological mechanisms of the discussed mixture's effects. The connected toxicological effects of the tested mixture were abnormal sperm cells, a disrupted level of testosterone, and thyroid hormones. The core mechanisms of these effects were inflammation, oxidative stress, disruption of androgen receptor signaling, and the alteration of the FOXO3-Keap-1/NRF2-HMOX1-NQO1 pathway signaling most likely controlled by the co-expression of overlapped genes among used chemicals. This in silico research can be used as a potential core for the determination of biomarkers that can be monitored in future further in vitro and in vivo experiments.

Identification and Validation of Key Genes of Differential Correlations in Gastric Cancer

Background: Gastric cancer (GC) is aggressive cancer with a poor prognosis. Previously bulk transcriptome analysis was utilized to identify key genes correlated with the development, progression and prognosis of GC. However, due to the complexity of the genetic mutations, there is still an urgent need to recognize core genes in the regulatory network of GC.

Methods: Gene expression profiles (GSE66229) were retrieved from the GEO database. Weighted correlation network analysis (WGCNA) was employed to identify gene modules mostly correlated with GC carcinogenesis. R package ‘DiffCorr’ was applied to identify differentially correlated gene pairs in tumor and normal tissues. Cytoscape was adopted to construct and visualize the gene regulatory network.

Results: A total of 15 modules were detected in WGCNA analysis, among which three modules were significantly correlated with GC. Then genes in these modules were analyzed separately by “DiffCorr”. Multiple differentially correlated gene pairs were recognized and the network was visualized by the software Cytoscape. Moreover, GEMIN5 and PFDN2, which were rarely discussed in GC, were identified as key genes in the regulatory network and the differential expression was validated by real-time qPCR, WB and IHC in cell lines and GC patient tissues.

Conclusions: Our research has shed light on the carcinogenesis mechanism by revealing differentially correlated gene pairs during transition from normal to tumor. We believe the application of this network-based algorithm holds great potential in inferring relationships and detecting candidate biomarkers.

Functional Role of AKNA: A Scoping Review

Human akna encodes an AT-hook transcription factor whose expression participates in various cellular processes. We conducted a scoping review on the literature regarding the functional role of AKNA according to the evidence found in human and in vivo and in vitro models, stringently following the “PRISMA-ScR” statement recommendations. Methods: We undertook an independent PubMed literature search using the following search terms, AKNA OR AKNA ADJ gene OR AKNA protein, human OR AKNA ADJ functions. Observational and experimental articles were considered. The selected studies were categorized using a pre-determined data extraction form. A narrative summary of the evidence was produced. Results: AKNA modulates the expression of CD40 and CD40L genes in immune system cells. It is a negative regulator of inflammatory processes as evidenced by knockout mouse models and observational studies for several autoimmune and inflammatory diseases. Furthermore, AKNA contributes to the de-regulation of the immune system in cancer, and it has been proposed as a susceptibility genetic factor and biomarker in CC, GC, and HNSCC. Finally, AKNA regulates neurogenesis by destabilizing the microtubules dynamics. Conclusion: Our results provide evidence for the role of AKNA in various cellular processes, including immune response, inflammation, development, cancer, autoimmunity, and neurogenesis.