Using whole-exome sequencing and protein interaction networks to prioritize candidate genes for germline cutaneous melanoma susceptibility

Prevalence and impact of sarcopenia in individuals with heart failure with reduced ejection fraction (the SARC-HF study): A prospective observational study protocol

Sarcopenia, a clinical syndrome primarily associated with reduced muscle mass in the elderly, has a negative impact on quality of life and survival. It can occur secondarily to other diseases such as heart failure (HF), a complex clinical syndrome with high morbidity and mortality. The simultaneous occurrence of these two conditions can worsen the prognosis of their carriers, especially in the most severe cases of HF, as in patients with reduced left ventricular ejection fraction (LVEF). However, due to the heterogeneous diagnostic criteria for sarcopenia, estimates of its prevalence present a wide variation, leading to new criteria having been recently proposed for its diagnosis, emphasizing muscle strength and function rather than skeletal muscle mass. The primary objective of this study is to evaluate the prevalence of sarcopenia and/or dynapenia in individuals with HF with reduced LVEF according to the most recent criteria, and compare the gene and protein expression of those patients with and without sarcopenia. The secondary objectives are to evaluate the association of sarcopenia and/or dynapenia with the risk of clinical events and death, quality of life, cardiorespiratory capacity, ventilatory efficiency, and respiratory muscle strength. The participants will answer questionnaires to evaluate sarcopenia and quality of life, and will undergo the following tests: handgrip strength, gait speed, dual-energy X-ray absorptiometry, respiratory muscle strength, cardiopulmonary exercise, as well as genomic and proteomic analysis, and dosage of N-terminal pro-B-type natriuretic peptide and growth differentiation factor-15. An association between sarcopenia and/or dynapenia with unfavorable clinical evolution is expected to be found, in addition to reduced quality of life, cardiorespiratory capacity, ventilatory efficiency, and respiratory muscle strength.

By using machine learning and in vitro testing, SERPINH1 functions as a novel tumorigenic and immunogenic gene and predicts immunotherapy response in osteosarcoma

Introduction

The most prevalent bone tumor with a relatively high level of aggressiveness and malignancy is osteosarcoma. The characteristics of the serpin family in osteosarcoma have not been defined.

Methods

In this study, the predictive significance of the serpin superfamily was investigated in the osteosarcoma and Gene Expression Omnibus (GEO) databases from The Cancer Genome Atlas (TCGA).

Results

It was discovered that SERPINH1 is a significant biological marker in osteosarcoma. According to the CCK-8, EdU, and Transwell assays as well as the IHC assay, SERPINH1 may promote osteosarcoma proliferation and migration. It is also more expressed in tumor samples than in healthy samples. SERPINH1 might forecast the effects of immunotherapy. Additionally, immune cells are interacted with through checkpoint, cytokine, and growth factor pathways in osteosarcomas with high SERPINH1 levels. The biological function, immunological characteristics, and treatment response (immunotherapy and chemotherapy responses) of patients with osteosarcoma were successfully predicted using a model related to SERPINH1. SERPINH1 and the SERPINH1-related score predict ferroptosis/pyroptosis/apoptosis/necroptosis in osteosarcoma.

Discussion

The SERPINH1-related score was an effective method for identifying osteosarcoma patients who would respond to immunotherapy and chemotherapy, as well as for predicting the survival outcomes of such patients.

PWN: enhanced random walk on a warped network for disease target prioritization

BACKGROUND

Extracting meaningful information from unbiased high-throughput data has been a challenge in diverse areas. Specifically, in the early stages of drug discovery, a considerable amount of data was generated to understand disease biology when identifying disease targets. Several random walk-based approaches have been applied to solve this problem, but they still have limitations. Therefore, we suggest a new method that enhances the effectiveness of high-throughput data analysis with random walks.

RESULTS

We developed a new random walk-based algorithm named prioritization with a warped network (PWN), which employs a warped network to achieve enhanced performance. Network warping is based on both internal and external features: graph curvature and prior knowledge.

CONCLUSIONS

We showed that these compositive features synergistically increased the resulting performance when applied to random walk algorithms, which led to PWN consistently achieving the best performance among several other known methods. Furthermore, we performed subsequent experiments to analyze the characteristics of PWN.

Rare germline deleterious variants increase susceptibility for lung cancer

Although multiple common susceptibility loci for lung cancer (LC) have been identified by genome-wide association studies, they can explain only a small portion of heritability. The etiological contribution of rare deleterious variants (RDVs) to LC risk is not fully characterized and may account for part of the missing heritability. Here, we sequenced the whole exomes of 2777 participants from the Environment and Genetics in Lung cancer Etiology study, a homogenous population including 1461 LC cases and 1316 controls. In single-variant analyses, we identified a new RDV, rs77187983 [EHBP1, odds ratio (OR) = 3.13, 95% confidence interval (CI) = 1.34-7.30, P = 0.008] and replicated two previously reported RDVs, rs11571833 (BRCA2, OR = 2.18; 95% CI = 1.25-3.81, P = 0.006) and rs752672077 (MPZL2, OR = 3.70, 95% CI = 1.04-13.15, P = 0.044). In gene-based analyses, we confirmed BRCA2 (P = 0.007) and ATM (P = 0.014) associations with LC risk and identified TRIB3 (P = 0.009), involved in maintaining genome stability and DNA repair, as a new candidate susceptibility gene. Furthermore, cases were enriched with RDVs in homologous recombination repair [carrier frequency (CF) = 22.9% versus 19.5%, P = 0.017] and Fanconi anemia (CF = 12.5% versus 10.2%, P = 0.036) pathways. Our results were not significant after multiple testing corrections but were enriched in cases versus controls from large scale public biobank resources, including The Cancer Genome Atlas, FinnGen and UK Biobank. Our study identifies novel candidate genes and highlights the importance of RDVs in DNA repair-related genes for LC susceptibility. These findings improve our understanding of LC heritability and may contribute to the development of risk stratification and prevention strategies.

Joint analysis of functionally related genes yields further candidates associated with Tetralogy of Fallot

Although several genes involved in the development of Tetralogy of Fallot have been identified, no genetic diagnosis is available for the majority of patients. Low statistical power may have prevented the identification of further causative genes in gene-by-gene survey analyses. Thus, bigger samples and/or novel analytic approaches may be necessary. We studied if a joint analysis of groups of functionally related genes might be a useful alternative approach. Our reanalysis of whole-exome sequencing data identified 12 groups of genes that exceedingly contribute to the burden of Tetralogy of Fallot. Further analysis of those groups showed that genes with high-impact variants tend to interact with each other. Thus, our results strongly suggest that additional candidate genes may be found by studying the protein interaction network of known causative genes. Moreover, our results show that the joint analysis of functionally related genes can be a useful complementary approach to classical single-gene analyses.

Family-based whole-exome sequencing identifies rare variants potentially related to cutaneous melanoma predisposition in Brazilian melanoma-prone families

Genetic predisposition accounts for nearly 10% of all melanoma cases and has been associated with a dozen moderate- to high-penetrance genes, including CDKN2A, CDK4, POT1 and BAP1. However, in most melanoma-prone families, the genetic etiology of cancer predisposition remains undetermined. The goal of this study was to identify rare genomic variants associated with cutaneous melanoma susceptibility in melanoma-prone families. Whole-exome sequencing was performed in 2 affected individuals of 5 melanoma-prone families negative for mutations in CDKN2A and CDK4, the major cutaneous melanoma risk genes. A total of 288 rare coding variants shared by the affected relatives of each family were identified, including 7 loss-of-function variants. By performing in silico analyses of gene function, biological pathways, and variant pathogenicity prediction, we underscored the putative role of several genes for melanoma risk, including previously described genes such as MYO7A and WRN, as well as new putative candidates, such as SERPINB4, HRNR, and NOP10. In conclusion, our data revealed rare germline variants in melanoma-prone families contributing with a novel set of potential candidate genes to be further investigated in future studies.

LncRNA BASP1-AS1 interacts with YBX1 to regulate Notch transcription and drives the malignancy of melanoma

Melanoma is a fatal skin malignant tumor with a poor prognosis. We found that long noncoding RNA BASP1-AS1 is essential for the development and prognosis of melanoma. The methylation, RNA sequencing, copy number variation, mutation data, and sample follow-up information of melanoma from The Cancer Genome Atlas (TCGA) were analyzed using weighted gene co-expression network analysis and 366 samples common to the three omics were selected for multigroup clustering analysis. A four-gene prognostic model (BASP1-AS1, LOC100506098, ARHGAP27P1, and LINC01532) was constructed in the TCGA cohort and validated using the GSE65904 series. The expression of BASP1-AS1 was upregulated in melanoma tissues and various melanoma cell lines. Functionally, the ectopic expression of BASP1-AS1 promoted cell proliferation, migration, and invasion in both A375 and SK-MEL-2 cells. Mechanically, BASP1-AS1 interacted with YBX1 and recruited it to the promoter of NOTCH3, initiating its transcription process. The activation of the Notch signaling then resulted in the transcription of multiple oncogenes, including c-MYC, PCNA, and CDK4, which contributed to melanoma progression. Thus, BASP1-AS1 could act as a potential biomarker for cutaneous malignant melanoma.

Melanoma susceptibility: an update on genetic and epigenetic findings

Malignant melanoma is one of the most highly ranked cancers in terms of years of life lost. Hereditary melanoma with its increased familial susceptibility is thought to affect up to 12% of all melanoma patients. In the past, only a few high-penetrance genes associated with familial melanoma, such as CDKN2A and CDK4, have been clinically tested. However, findings now indicate that melanoma is a cancer most likely to develop not only due to high-penetrance variants but also due to polygenic inheritance patterns, leaving no clear division between the hereditary and sporadic development of malignant melanoma. Various pathogenic low-penetrance variants were recently discovered through genome-wide association studies, and are now translated into polygenic risk scores. These can show superior sensitivity rates for the prediction of melanoma susceptibility and related mixed cancer syndromes than risk scores based on phenotypic traits of the patients, with odds ratios of up to 5.7 for patients in risk groups. In addition to describing genetic findings, we also review the first results of epigenetic research showing constitutional methylation changes that alter the susceptibility to cutaneous melanoma and its risk factors.