The pattern of gene copy number alteration (CNAs) in hepatocellular carcinoma: an in silico analysis

Potentially functional variants of CHMP4A and PANX1 in the pyroptosis-related pathway predict survival of patients with non-oropharyngeal head and neck squamous cell carcinoma

BACKGROUND

Pyroptosis has been implicated in the advancement of various cancers. Triggering pyroptosis within tumors amplifies the immune response, thereby fostering an antitumor immune environment. Nonetheless, few published studies have evaluated associations between functional variants in the pyroptosis-related genes and clinical outcomes of patients with non-oropharyngeal head and neck squamous cell carcinoma (NON-ORO HNSCC).

METHODS

We conducted an association study of 985 NON-ORO HNSCC patients who were randomly divided into two groups: the discovery group of 492 patients and the replication group of 493 patients. We used Cox proportional hazards regression analysis to examine associations between genetic variants of the pyroptosis-related genes and survival of patients with NON-ORO HNSCC. Bayesian false discovery probability (BFDP) was used for multiple testing correction. Functional annotation was applied to the identified survival-associated genetic variants.

RESULTS

There are 8254 single-nucleotide polymorphisms (SNPs) located in 82 pyroptosis-related genes, of which 202 SNPs passed multiple testing correction with BFDP < 0.8 in the discovery and six SNPs retained statistically significant in the replication. In subsequent stepwise multivariable Cox regression analysis, two independent SNPs (CHMP4A rs1997996 G > A and PANX1 rs56175344 C > G) remained significant with an adjusted hazard ratios (HR) of 1.31 (95% confidence interval [CI] = 1.09-1.57, p = 0.004) and 0.65 (95% CI = 0.51-0.83, p = 0.0005) for overall survival (OS), respectively. Further analysis of the combined genotypes revealed progressively worse OS associated with the number of unfavorable genotypes (ptrend < 0.0001 and 0.021 for OS and disease-specific survival, respectively). Moreover, both PANX1 rs56175344G and CHMP4A rs1997996A alleles were correlated with reduced mRNA expression levels.

CONCLUSIONS

Genetic variants in the pyroptosis pathway genes may predict the survival of NON-ORO HNSCC patients, likely by reducing the gene expression, but our findings need to be replicated by larger studies.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the global leading lethal tumors. Pyroptosis has recently been defined as an inflammatory programmed cell death, which is closely linked to cancer progression. However, the significance of pyroptosis-related genes (PRGs) in the prognosis of HCC remains elusive.

Methods

RNA sequencing (RNA-seq) data of HCC cases and their corresponding clinical information were collected from the Cancer Genome Atlas (TCGA) database, and differential PRGs were explored. The prognostic PRGs were analyzed with univariate COX regression and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to build a prognostic model in the TCGA training cohort. The predictive model was further validated in the TCGA test cohort and ICGC validation cohort. Differential gene function and associated pathway analysis were performed by Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG). Single-sample gene set enrichment analysis (ssGSEA) was used to identify distinct immune cell infiltration. The mRNA and protein expression of prognostic PRGs was examined by quantitative RT-qPCR and immunohistochemistry.

Results

We identified 46 PRGs that were differentially expressed between normal and HCC tissues in a TCGA cohort, and HCC patients could be well categorized into two clusters associated with distinct survival rates based on expression levels of the PRGs. A three-PRG prognostic model comprising CHMP4A, HMGB1 and PLK1 was constructed in the training cohort, and HCC patients could be classified into the high- and low-risk subgroups based on the median risk score. High-risk patients exhibited shorter overall survival (OS) than low-risk ones, which was validated in the test cohort and ICGC validation cohort. The risk score of this model was confirmed as an independent prognostic factor to predict OS of HCC patients. GO, KEGG and ssGSEA demonstrated the differential immune cell infiltrations were associated with the risk scores. The higher expression of CHMP4A, HMGB1 and PLK1 were validated in HCC compared to normal in vivo and in vitro.

Conclusion

The three-PRG signature (CHMP4A, HMGB1, and PLK1) could act as an independent factor to predict the prognosis of HCC patients, which would shed light upon a potent therapeutic strategy for HCC treatment.

A novel pyroptosis-related gene signature for predicting laryngeal carcinoma prognosis

Pyroptosis, a newly-defined mode of cell death related to inflammation, is closely related to cancers but has not yet been studied in laryngeal carcinoma (LC). We investigated pyroptosis in LC and constructed a prognostic model. Using RNA sequencing data, we identified differentially expressed genes (DEGs) in LC and normal tissues to construct a prognostic risk model. The model's accuracy and independent prognostic value were evaluated using survival- and receiver operating characteristic (ROC)- curves; and univariate and multivariate Cox regression analyses, respectively. Gene Expression Omnibus (GEO) data was utilized as a model validation set. Differential analysis revealed 37 DEGs, and consistent clustering showed that pyroptosis-related genes could predict LC prognosis. Six genes (CHMP7, GSDME, GZMB, CASP9, IL6, and NLRP1) were obtained by Lasso Cox regression analysis to construct a prognostic model. The high-risk group had a poor prognosis with areas under the ROC curve at 1-, 3-, and 5-years of 0.619, 0.692, and 0.656, respectively. Univariate and multivariate Cox analyses showed that the risk score was an independent prognostic factor. Enrichment analysis of GO and KEGG pathways revealed that differentially expressed genes may be related to infection, T cell differentiation, immunity, and inflammation. It was further found that the low survival rate of the high-risk group may be related to the significant reduction of immune cell infiltration and immune function. With the bioinformatic method, six genes related to pyroptosis affecting LC prognosis were screened and a prognostic risk model was constructed, which laid a foundation for pyroptosis study in LC.