Approaches to integrating germline and tumor genomic data in cancer research

SNPs-Panel Polymorphism Variations in GHRL and GHSR Genes Are Not Associated with Prostate Cancer

Prostate cancer (PCa) is a major public health problem worldwide. Recent studies have suggested that ghrelin and its receptor could be involved in the susceptibility to several cancers such as PCa, leading to their use as an important predictive way for the clinical progression and prognosis of cancer. However, conflicting results of single nucleotide polymorphisms (SNPs) with ghrelin (GHRL) and its receptor (GHSR) genes were demonstrated in different studies. Thus, the present case-control study was undertaken to investigate the association of GHRL and GHSR polymorphisms with the susceptibility to sporadic PCa. A cohort of 120 PCa patients and 95 healthy subjects were enrolled in this study. Genotyping of six SNPs was performed: three tag SNPs in GHRL (rs696217, rs4684677, rs3491141) and three tag SNPs in the GHSR (rs2922126, rs572169, rs2948694) using TaqMan. The allele and genotype distribution, as well as haplotypes frequencies and linked disequilibrium (LD), were established. Multifactor dimensionality reduction (MDR) analysis was used to study gene-gene interactions between the six SNPs. Our results showed no significant association of the target polymorphisms with PCa (p > 0.05). Nevertheless, SNPs are often just markers that help identify or delimit specific genomic regions that may harbour functional variants rather than the variants causing the disease. Furthermore, we found that one GHSR rs2922126, namely the TT genotype, was significantly more frequent in PCa patients than in controls (p = 0.040). These data suggest that this genotype could be a PCa susceptibility genotype. MDR analyses revealed that the rs2922126 and rs572169 combination was the best model, with 81.08% accuracy (p = 0.0001) for predicting susceptibility to PCa. The results also showed a precision of 98.1% (p < 0.0001) and a PR-AUC of 1.00. Our findings provide new insights into the influence of GHRL and GHSR polymorphisms and significant evidence for gene-gene interactions in PCa susceptibility, and they may guide clinical decision-making to prevent overtreatment and enhance patients' quality of life.

miR-29a-5p modulates ferroptosis by targeting ferritin heavy chain FTH1 in prostate cancer

Ferroptosis is a kind of regulatory necrosis caused by phospholipid iron-dependent peroxidation. MiRNAs are known to play key roles in diverse biological functions. However, the molecular basis of miRNA-mediated ferroptosis in prostate cancer has not been fully stated. Here, with TCGA prostate cancer miRNA-seq data, we utilized Multivariate Cox regression analysis to prioritize potential miRNA and validated it in vitro and in vivo. We identified miR-29a-5p by TCGA prostate cancer miRNA-seq dataset. And we confirmed the expression of miR-29a-5p in prostate cancer cell lines. MiR-29a-5p knockdown reduced proliferation in PC-3 and LNCaP cells while increased Fe²⁺ and malondialdehyde (MDA) levels, the opposite phenomenon was observed with miR-29a-5p overexpression. Luciferase reporter assay showed an interaction between miR-29a-5p and Nrf2 downstream gene FTH1, subsequent rescue experiments also indirectly proved their direct effect. Finally, suppression of miR-29a-5p effectively inhibited tumor growth in vivo. These findings proved that the important role of miR-29a-5p in prostate cancer ferroptosis.

Pharmacogenetics of Anticancer Drugs: Clinical Response and Toxicity

Cancer is the most challenging disease for medical professionals to treat. The factors underlying the complicated situation include anticancer drug-associated toxicity, non-specific response, low therapeutic window, variable treatment outcomes, development of drug resistance, treatment complications, and cancer recurrence. The remarkable advancement in biomedical sciences and genetics, over the past few decades, however, is changing the dire situation. The discovery of gene polymorphism, gene expression, biomarkers, particular molecular targets and pathways, and drug-metabolizing enzymes have paved the way for the development and provision of targeted and individualized anticancer treatment. Pharmacogenetics is the study of genetic factors having the potential to affect clinical responses and pharmacokinetic and pharmacodynamic behaviors of drugs. This chapter emphasizes pharmacogenetics of anticancer drugs and its applications in improving treatment outcomes, selectivity, toxicity of the drugs, and discovering and developing personalized anticancer drugs and genetic methods for prediction of drug response and toxicity.

IMP3 accelerates the progression of prostate cancer through inhibiting PTEN expression in a SMURF1-dependent way

BACKGROUND

Insulin-like growth factor 2 (IGF2) messenger RNA binding protein 3 (IMP3) has been testified to be overexpressed in prostate cancer and strongly related to patients' poor prognosis. However, the functions of IMP3 and the underlying mechanisms in prostate cancer still remain unknown. Therefore, the current study was carried out to reveal the role and molecular mechanism of IMP3 in prostate cancer progression.

METHODS

The expression levels of IMP3 in prostate cancer tissues and cells were detected by immunohistochemistry (IHC), western blotting and RT-PCR. CCK-8, clone formation, flow cytometry and in vivo tumor formation assays were used to determine cell growth, clone formation apoptosis and tumorigenesis, respectively. The effect of IMP3 on the expression levels of the key proteins in PI3K/AKT/mTOR signaling pathway, including PIP2, PIP3, p-AKT, AKT, p-mTOR, mTOR, PTEN and BAD activation of was determined by western blotting. IP (Immunoprecipitation) assay was used to evaluate the effects of IMP3 and SMURF1 (SMAD specific E3 ubiquitin protein ligase 1) on the ubiquitination of PTEN protein.

RESULTS

IMP3 expression level was significantly increased in prostate cancer tissues and cell lines (LNCap, PC3 and DU145) as compared with the paracancerous normal tissues and cells (RWPE-1), respectively. High expression of IMP3 apparently promoted cell viability, tumorigenesis and inhibited cell apoptosis in prostate cancer LNCap, DU145 and PC3 cell lines. In mechanism, IMP3 upregulation significantly increased the phosphorylation levels of AKT and mTOR, and elevated PIP3 expression level, while induced significant reductions in the expression levels of BAD, PTEN and PIP2. And, IMP3 overexpression increased SMURF1 expression, which facilitated PTEN ubiquitination. In addition, SMURF1 overexpression enhanced prostate cancer cell viability and inhibited cell apoptosis. Silence of SMURF1 rescued the enhancements in cell proliferation and tumorigenesis and the inhibition in cell apoptosis rates induced by IMP3 in prostate cancer DU145 and LNCap cells.

CONCLUSION

This study reveals that IMP3 is overdressed in prostate cancer, which accelerates the progression of prostate cancer through activating PI3K/AKT/mTOR signaling pathway via increasing SMURF1-mediated PTEN ubiquitination.

A paradigm shift in medicine: A comprehensive review of network-based approaches

Network medicine is a rapidly evolving new field of medical research, which combines principles and approaches of systems biology and network science, holding the promise to uncovering the causes and to revolutionize the diagnosis and treatments of human diseases. This new paradigm reflects the fact that human diseases are not caused by single molecular defects, but driven by complex interactions among a variety of molecular mediators. The complexity of these interactions embraces different types of information: from the cellular-molecular level of protein-protein interactions to correlational studies of gene expression and regulation, to metabolic and disease pathways up to drug-disease relationships. The analysis of these complex networks can reveal new disease genes and/or disease pathways and identify possible targets for new drug development, as well as new uses for existing drugs. In this review, we offer a comprehensive overview of network types and algorithms used in the framework of network medicine. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

Interactions between Germline and Somatic Mutated Genes in Aggressive Prostate Cancer

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the USA. Advances in high-throughput genotyping and next generation sequencing technologies have enabled discovery of germline genetic susceptibility variants and somatic mutations acquired during tumor formation. Emerging evidence indicates that germline variations may interact with somatic events in carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic variation and their role in aggressive PCa remain largely unexplored. Here we investigated the possible oncogenic interactions and cooperation between genes containing germline variation from genome-wide association studies (GWAS) and genes containing somatic mutations from tumor genomes of 305 men with aggressive tumors and 52 control samples from The Cancer Genome Atlas (TCGA). Network and pathway analysis were performed to identify molecular networks and biological pathways enriched for germline and somatic mutations. The analysis revealed 90 functionally related genes containing both germline and somatic mutations. Transcriptome analysis revealed a 61-gene signature containing both germline and somatic mutations. Network analysis revealed molecular networks of functionally related genes and biological pathways including P53, STAT3, NKX3-1, KLK3, and Androgen receptor signaling pathways enriched for germline and somatic mutations. The results show that integrative analysis is a powerful approach to uncovering the possible oncogenic interactions and cooperation between germline and somatic mutations and understanding the broader biological context in which they operate in aggressive PCa.

Integrating germline and somatic variation information using genomic data for the discovery of biomarkers in prostate cancer

BACKGROUND

Prostate cancer (PCa) is the most common diagnosed malignancy and the second leading cause of cancer-related deaths among men in the United States. High-throughput genotyping has enabled discovery of germline genetic susceptibility variants (herein referred to as germline mutations) associated with an increased risk of developing PCa. However, germline mutation information has not been leveraged and integrated with information on acquired somatic mutations to link genetic susceptibility to tumorigenesis. The objective of this exploratory study was to address this knowledge gap.

METHODS

Germline mutations and associated gene information were derived from genome-wide association studies (GWAS) reports. Somatic mutation and gene expression data were derived from 495 tumors and 52 normal control samples obtained from The Cancer Genome Atlas (TCGA). We integrated germline and somatic mutation information using gene expression data. We performed enrichment analysis to discover molecular networks and biological pathways enriched for germline and somatic mutations.

RESULTS

We discovered a signature of 124 genes containing both germline and somatic mutations. Enrichment analysis revealed molecular networks and biological pathways enriched for germline and somatic mutations, including, the PDGF, P53, MYC, IGF-1, PTEN and Androgen receptor signaling pathways.

CONCLUSION

Integrative genomic analysis links genetic susceptibility to tumorigenesis in PCa and establishes putative functional bridges between the germline and somatic variation, and the biological pathways they control.

The genetic heterogeneity of colorectal cancer predisposition - guidelines for gene discovery

BACKGROUND

Colorectal cancer (CRC) is a cumulative term applied to a clinically and genetically heterogeneous group of neoplasms that occur in the bowel. Based on twin studies, up to 45 % of the CRC cases may involve a heritable component. Yet, only in 5-10 % of these cases high-penetrant germline mutations are found (e.g. mutations in APC and DNA mismatch repair genes) that result in a familial aggregation and/or an early onset of the disease. Genome-wide association studies have revealed that another ~5 % of the CRC cases may be explained by a cumulative effect of low-penetrant risk factors. Recent attempts to identify novel genetic factors using whole exome and whole genome sequencing has proven to be difficult since the remaining, yet to be discovered, high penetrant CRC predisposing genes appear to be rare. In addition, most of the moderately penetrant candidate genes identified so far have not been confirmed in independent cohorts. Based on literature examples, we here discuss how careful patient and cohort selection, candidate gene and variant selection, and corroborative evidence may be employed to facilitate the discovery of novel CRC predisposing genes.

CONCLUSIONS

The picture emerges that the genetic predisposition to CRC is heterogeneous, involving complex interplays between common and rare (inter)genic variants with different penetrances. It is anticipated, however, that the use of large clinically well-defined patient and control datasets, together with improved functional and technical possibilities, will yield enough power to unravel this complex interplay and to generate accurate individualized estimates for the risk to develop CRC.

Somatic Mutations and Genetic Variants of NOTCH1 in Head and Neck Squamous Cell Carcinoma Occurrence and Development

A number of genetic variants have been associated with cancer occurrence, however it may be the acquired somatic mutations (SMs) that drive cancer development. This study investigates the potential SMs and related genetic variants associated with the occurrence and development of head and neck squamous cell carcinoma (HNSCC). We identified several SMs in NOTCH1 from whole-exome sequencing and validated them in a 13-year cohort of 128 HNSCC patients using a high-resolution melting analysis and resequencing. Patients who have NOTCH1 SMs show higher 5-year relapse-free recurrence (P = 0.0013) and lower survival proportion (P = 0.0447) when the risk-associated SMs were analysed by Cox proportional hazard models. Interestingly, the NOTCH1 gene rs139994842 that shares linkage with SMs is associated with HNSCC risk (OR = 3.46), increasing when SMs in NOTCH1 are involved (OR = 7.74), and furthermore when there are SMs in conjunction to betel quid chewing (OR = 32.11), which is a related independent environmental risk factor after adjusting for substances use (alcohol, betel quid, cigarettes) and age. The findings indicate that betel quid chewing is highly associated with NOTCH1 SMs (especially with changes in EGF-like domains), and that rs139994842 may potentially serve as an early predictive and prognostic biomarker for the occurrence and development of HNSCC.

Familial predisposition and genetic risk factors for lymphoma

Our understanding of familial predisposition to lymphoma (collectively defined as non-Hodgkin lymphoma [NHL], Hodgkin lymphoma [HL], and chronic lymphocytic leukemia [CLL]) outside of rare hereditary syndromes has progressed rapidly during the last decade. First-degree relatives of NHL, HL, and CLL patients have an ∼1.7-fold, 3.1-fold, and 8.5-fold elevated risk of developing NHL, HL, and CLL, respectively. These familial risks are elevated for multiple lymphoma subtypes and do not appear to be confounded by nongenetic risk factors, suggesting at least some shared genetic etiology across the lymphoma subtypes. However, a family history of a specific subtype is most strongly associated with risk for that subtype, supporting subtype-specific genetic factors. Although candidate gene studies have had limited success in identifying susceptibility loci, genome-wide association studies (GWAS) have successfully identified 67 single nucleotide polymorphisms from 41 loci, predominately associated with specific subtypes. In general, these GWAS-discovered loci are common (minor allele frequency >5%), have small effect sizes (odds ratios, 0.60-2.0), and are of largely unknown function. The relatively low incidence of lymphoma, modest familial risk, and the lack of a screening test and associated intervention, all argue against active clinical surveillance for lymphoma in affected families at this time.