Estimating Heritability of Prostate Cancer‐Specific Survival Using Population‐Based Registers

Szulkin, Robert; Clements, Mark; Magnusson, Patrik K. E.; Wiklund, Fredrik; Kuja‐Halkola, Ralf

doi:10.1002/pros.23344

Cited by 4 publications

(3 citation statements)

References 34 publications

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“…6 So far, genome-wide studies have identified more than 100 common mutations in prostate cancer patients, which account for a significant portion of the genetic factors underlying prostate cancer, including mutations in DNA damage repair genes. [7][8][9][10] Genomic DNA is frequently harmed by a variety of internal and external factors such as double-strand breaks. Cells have evolved a well-coordinated signal cascade network called DNA damage response (DDR) to maintain genomic integrity, which senses and transmits damage signals to effector proteins and induces cell responses such as cell cycle arrest, DNA repair pathway activation, and cell death, and many genes are involved, including BRCA, ATM, and CHEK2.…”

Section: Introductionmentioning

confidence: 99%

Prognostic Role of DNA Damage Response Genes Mutations and their Association With the Sensitivity of Olaparib in Prostate Cancer Patients

Zhang

Wei

et al. 2022

Cancer Control

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Objective Evidence shows that gene mutation is a significant proportion of genetic factors associated with prostate cancer. The DNA damage response (DDR) is a signal cascade network that aims to maintain genomic integrity in cells. This comprehensive study was performed to determine the link between different DNA damage response gene mutations and prostate cancer. Materials and methods A systematic literature search was performed using PubMed, Web of Science, and Embase. Papers published up to February 1, 2022 were retrieved. The DDR gene mutations associated with prostate cancer were identified by referring to relevant research and review articles. Data of prostate cancer patients from multiple PCa cohorts were obtained from cBioPortal. The OR or HR and 95% CIs were calculated using both fixed-effects models (FEMs) and random-effects models (REMs). Results Seventy-four studies were included in this research, and the frequency of 13 DDR genes was examined. Through the analysis of 33 articles that focused on the risk estimates of DDR genes between normal people and PCa patients, DDR genes were found to be more common in prostate cancer patients (OR = 3.6293 95% CI [2.4992; 5.2705]). Also, patients in the mutated group had a worse OS and DFS outcome than those in the unmutated group ( P < .05). Of the 13 DDR genes, the frequency of 9 DDR genes in prostate cancer was less than 1%, and despite differences in race, BRCA2 was the potential gene with the highest frequency (REM Frequency = .0400, 95% CI .0324 - .0541). The findings suggest that mutations in genes such as ATR, BLM, and MLH1 in PCa patients may increase the sensitivity of Olaparib, a PARP inhibitor. Conclusion These results demonstrate that mutation in any DDR pathway results in a poor prognosis for PCa patients. Furthermore, mutations in ATR, BLM, and MLH1 or the expression of POLR2L, PMS1, FANCE, and other genes significantly influence Olaparib sensitivity, which may be underlying therapeutic targets in the future.

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Section: Introductionmentioning

confidence: 99%

Prognostic Role of DNA Damage Response Genes Mutations and their Association With the Sensitivity of Olaparib in Prostate Cancer Patients

Zhang

Wei

et al. 2022

Cancer Control

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“…Thus, our method can be straightforwardly applied to variable selection in multicomponent AFT models with various random‐effect structures (nested and/or crossed) and also in the AFT models with left truncated and right censored . The structure equation models (SEMs) allow for good modeling of log‐normal AFTs (eg, the work of Szulkin et al). Extension to the SEM via the proposed method would be an interesting future topic.…”

Section: Discussionmentioning

confidence: 99%

Penalized variable selection for accelerated failure time models with random effects

Park

2018

Statistics in Medicine

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Accelerated failure time (AFT) models allowing for random effects are linear mixed models under the log‐transformation of survival time with censoring and describe dependence in correlated survival data. It is well known that the AFT models are useful alternatives to frailty models. To the best of our knowledge, however, there is no literature on variable selection methods for such AFT models. In this paper, we propose a simple but unified variable‐selection procedure of fixed effects in the AFT random‐effect models using penalized h‐likelihood (HL). We consider four penalty functions (ie, least absolute shrinkage and selection operator (LASSO), adaptive LASSO, smoothly clipped absolute deviation (SCAD), and HL). We show that the proposed method can be easily implemented via a slight modification to existing h‐likelihood estimation procedures. We thus demonstrate that the proposed method can also be easily extended to AFT models with multilevel (or nested) structures. Simulation studies also show that the procedure using the adaptive LASSO, SCAD, or HL penalty performs well. In particular, we find via the simulation results that the variable selection method with HL penalty provides a higher probability of choosing the true model than other three methods. The usefulness of the new method is illustrated using two actual datasets from multicenter clinical trials.

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“…However, these SNPs (single nucleotide polymorphism) mostly show little or no ability to discriminate between indolent and fatal forms of the disease. In contrast to the high genetic component accounting for the overall prostate cancer risk, the heritability of prostate cancer-specific survival was estimated to be 10% ( 5 ) and consequently, few genetic variants have been specifically associated with aggressive prostate cancer ( 6 , 7 ). Since the majority of all diagnosed prostate cancer cases do not progress to lethality, biological markers that can distinguish between potentially lethal and non-aggressive cases would greatly improve prognostication and guide treatment decisions.…”

Section: Introductionmentioning

confidence: 99%

The variant rs77559646 associated with aggressive prostate cancer disrupts ANO7 mRNA splicing and protein expression

Wahlström

Heron

Knuuttila

et al. 2022

Human Molecular Genetics

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Prostate cancer is among the most common cancers in men, with a large fraction of the individual risk attributable to heritable factors. A majority of the diagnosed cases does not lead to a lethal disease, and hence biological markers that can distinguish between indolent and fatal forms of the disease are of great importance for guiding treatment decisions. Although over 300 genetic variants are known to be associated with prostate cancer risk, few have been associated with the risk of an aggressive disease. One such variant is rs77559646 located in ANO7. This variant has a dual function. It constitutes a missense mutation in the short isoform of ANO7 and a splice region mutation in full-length ANO7. In this study, we have analyzed the impact of the variant allele of rs77559646 on ANO7 mRNA splicing using a minigene splicing assay and by performing splicing analysis with the tools IRFinder, rMATS and LeafCutter on RNA-Seq data from prostate tissue of six rs77559646 variant allele carriers and 43 non-carriers. The results revealed a severe disruption of ANO7 mRNA splicing in rs77559646 variant allele carriers. Immunohistochemical analysis of prostate samples from patients homozygous for the rs77559646 variant allele demonstrated a loss of apically localized ANO7 protein. Our study is the first to provide a mechanistic explanation for the impact of a prostate cancer risk SNP on ANO7 protein production. Furthermore, the rs77559646 variant is the first known germline loss-of-function mutation described for ANO7. We suggest that loss of ANO7 contributes to prostate cancer progression.

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Estimating Heritability of Prostate Cancer‐Specific Survival Using Population‐Based Registers

Cited by 4 publications

References 34 publications

Prognostic Role of DNA Damage Response Genes Mutations and their Association With the Sensitivity of Olaparib in Prostate Cancer Patients

Prognostic Role of DNA Damage Response Genes Mutations and their Association With the Sensitivity of Olaparib in Prostate Cancer Patients

Penalized variable selection for accelerated failure time models with random effects

The variant rs77559646 associated with aggressive prostate cancer disrupts ANO7 mRNA splicing and protein expression

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