Analysis of genomic pathogenesis according to the revised Bethesda guidelines and additional criteria

SH2D4A inhibits esophageal squamous cell carcinoma progression through FAK/PI3K/AKT signaling pathway

Esophageal squamous cell carcinoma (ESCC), one of the most common malignant tumors, is now afflicting approximately 80% of patients diagnosed with esophageal cancers. The therapeutic effect and prognosis of ESCC remain inadequate due to the unusual early symptoms and rapid malignant progression. SH2 Domain containing 4 A (SH2D4A) is downregulated in malignancies and is closely associated with tumor progression. However, neither the biological functions nor the fundamental mechanisms of SH2D4A on ESCC are known. In this study, it was found that SH2D4A is downregulated in ESCC tissues and cell lines. Incorporating immunohistochemistry and clinicopathological findings, we determined that decreased SH2D4A expression was substantially associated with adverse clinical outcomes. Overexpression of SH2D4A inhibited cell proliferation and migration, whereas suppressing SH2D4A has the opposite effect. SH2D4A mechanistically inhibited cells from proliferating and migrating through the FAK/PI3K/AKT signaling pathway. Furthermore, the results of xenograft tumor growth confirmed the preceding findings. In conclusion, our findings reveal that SH2D4A is a gene which can serve as a cancer suppressor in ESCC and may inhibits the ESCC progression by interfering with the FAK/PI3K/AKT signaling pathway. SH2D4A could act as a target for diagnostic or therapeutic purpose in ESCC.

Association between the cashmere production performance, milk production performance, and body size traits and polymorphism of COL6A5 and LOC102181374 genes in Liaoning cashmere goats

The purpose of this study was to analyze the relationship between COL6A5 (collagen type VI alpha 5 chain) and LOC102181374 (alcohol dehydrogenase 1) genes and the production performance of Liaoning cashmere goats by single nucleotide polymorphism (SNP). We have searched for SNP loci of COL6A5 and LOC102181374 genes through sequence alignment and PCR experiments, and have used SPSS and SHEsis software to analyze production data. We obtained five SNP loci in total, including three SNP loci (G50985A, G51140T, G51175A) in COL6A5 gene and two SNP loci (A10067G, T10108C) in LOC102181374 gene. The genotypes G50985A (AG), G51140T (GT), G51175A (AA), A10067G (AA), and T10108C (CC) of these loci have certain advantages in improving the production performance of Liaoning cashmere goats. The haplotype combinations that can improve production performance in COL6A5 gene were H1H5:AGGGAG, H4H4:GGGGAA, and H4H4:GGGGAA. H3H3:GGCC and H2H4:AGTT were the dominant combinations in LOC102181374 gene. At G51175A and A10067G loci, we found that H1H2:AAAG and H1H3:AGAA have dominant effects. These results may provide some support for the molecular breeding of production traits in Liaoning cashmere goats.

Integrated clustering signature of genomic heterogeneity, stemness and tumor microenvironment predicts glioma prognosis and immunotherapy response

BACKGROUND

Glioma is the most frequent primary tumor of the central nervous system. The high heterogeneity of glioma tumors enables them to adapt to challenging environments, leading to resistance to treatment. Therefore, to detect the driving factors and improve the prognosis of glioma, it is essential to have a comprehensive understanding of the genomic heterogeneity, stemness, and immune microenvironment of glioma.

METHODS

We classified gliomas into various subtypes based on stemness, genomic heterogeneity, and immune microenvironment consensus clustering analysis. We identified risk hub genes linked to heterogeneous characteristics using WGCNA, LASSO, and multivariate Cox regression analysis and utilized them to create an effective risk model.

RESULTS

We thoroughly investigated the genomic heterogeneity, stemness, and immune microenvironment of glioma and identified the risk hub genes RAB42, SH2D4A, and GDF15 based on the TCGA dataset. We developed a risk model utilizing these genes that can reliably predict the prognosis of glioma patients. The risk signature showed a positive correlation with T cell exhaustion and increased infiltration of immunosuppressive cells, and a negative correlation with the response to immunotherapy. Moreover, we discovered that SH2D4A, one of the risk hub genes, could stimulate the migration and proliferation of glioma cells.

CONCLUSIONS

This study identified risk hub genes and established a risk model by analyzing the genomic heterogeneity, stemness, and immune microenvironment of glioma. Our findings will facilitate the diagnosis and prediction of glioma prognosis and may lead to potential treatment strategies for glioma.

Structure, activity and function of the lysine methyltransferase SETD5

SET domain-containing 5 (SETD5) is an uncharacterized member of the protein lysine methyltransferase family and is best known for its transcription machinery by methylating histone H3 on lysine 36 (H3K36). These well-characterized functions of SETD5 are transcription regulation, euchromatin formation, and RNA elongation and splicing. SETD5 is frequently mutated and hyperactive in both human neurodevelopmental disorders and cancer, and could be down-regulated by degradation through the ubiquitin-proteasome pathway, but the biochemical mechanisms underlying such dysregulation are rarely understood. Herein, we provide an update on the particularities of SETD5 enzymatic activity and substrate specificity concerning its biological importance, as well as its molecular and cellular impact on normal physiology and disease, with potential therapeutic options.

Systematic identification of biochemical networks in cancer cells by functional pathway inference analysis

MOTIVATION

Pathway inference methods are important for annotating the genome, for providing insights into the mechanisms of biochemical processes and allow the discovery of signalling members and potential new drug targets. Here, we tested the hypothesis that genes with similar impact on cell viability across multiple cell lines belong to a common pathway, thus providing a conceptual basis for a pathway inference method based on correlated anti-proliferative gene properties.

METHODS

To test this concept, we used recently available large-scale RNAi screens to develop a method, termed functional pathway inference analysis (FPIA), to systemically identify correlated gene dependencies.

RESULTS

To assess FPIA, we initially focused on PI3K/AKT/MTOR signalling, a prototypic oncogenic pathway for which we have a good sense of ground truth. Dependencies for AKT1, MTOR and PDPK1 were among the most correlated with those for PIK3CA (encoding PI3Kα), as returned by FPIA, whereas negative regulators of PI3K/AKT/MTOR signalling, such as PTEN were anti-correlated. Following FPIA, MTOR, PIK3CA and PIK3CB produced significantly greater correlations for genes in the PI3K-Akt pathway versus other pathways. Application of FPIA to two additional pathways (p53 and MAPK) returned expected associations (e.g. MDM2 and TP53BP1 for p53 and MAPK1 and BRAF for MEK1). Over-representation analysis of FPIA-returned genes enriched the respective pathway, and FPIA restricted to specific tumour lineages uncovered cell type-specific networks. Overall, our study demonstrates the ability of FPIA to identify members of pro-survival biochemical pathways in cancer cells.

AVAILABILITY AND IMPLEMENTATION

FPIA is implemented in a new R package named 'cordial' freely available from https://github.com/CutillasLab/cordial.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.