Chih Chieh Wu

Joint Effects of Germ-Line p53 Mutation and Sex on Cancer Risk in Li-Fraumeni Syndrome

Germ-line p53 mutations have been identified in most families with Li-Fraumeni syndrome (LFS). For germ-line p53 mutation carriers, there is considerable variability with respect to age of cancer onset and tumor type, suggesting that additional genetic effects influence the clinical severity and tumor spectrum. To identify factors that might contribute to the observed heterogeneity in time to onset, we used segregation analysis to analyze the joint effects of germ-line p53 mutations and risk modifier(s) on cancer incidence. We studied 159 kindreds, ascertained through probands who had been diagnosed with childhood soft-tissue sarcoma before 16 years of age, survived >3 years after diagnosis, and treated at The University of Texas M.D. Anderson Cancer Center (Houston, TX) from 1944 to 1975. This unique cohort has been followed systematically for >20 years and has had germ-line p53 mutation testing in probands and extended family members. The analyses revealed that germ-line p53 mutations and sex had significant effects on cancer risk: men with p53 mutations had 151-fold higher odds of developing cancer than did those without mutations [95% confidence interval (95% CI), 60-380], and women with p53 mutations had 1,075-fold higher odds than did those without mutations (95% CI, 358-3,229) and 7.1-fold higher odds of having cancer than did men with mutations (95% CI, 2.5-20.3). These findings provide quantitative cancer risk assessments for LFS families.

Perceptions of skill development of participants in three national career development programs for women faculty in academic medicine.

Purpose The Association of American Medical Colleges (AAMC) and Drexel University College of Medicine have designed and implemented national career development programs (CDPs) to help women faculty acquire and strengthen skills needed for success in academic medicine. The authors hypothesized that skills women acquired in CDPs would vary by career stage and program attended. Method In 2011, the authors surveyed a national cohort of 2,779 women listed in the AAMC Faculty Roster who also attended one of three CDPs (Early- and Mid-Career Women in Medicine Seminars, and/or Executive Leadership in Academic Medicine) between 1988 and 2010 to examine their characteristics and CDP experiences. Participants indicated from a list of 16 skills whether each skill was newly acquired, improved, or not improved as a result of their program participation. Results Of 2,537 eligible CDP women, 942 clicked on the link in an invitation e-mail, and 879 (93%) completed the survey. Respondents were representative of women faculty in academic medicine. Participants rated the CDPs highly. Almost all reported gaining and/or improving skills from the CDP. Four skills predominated across all three programs: interpersonal skills, leadership, negotiation, and networking. The skills that attendees endorsed differed by respondents’ career stages, more so than by program attended. Conclusions Women participants perceived varying skills gained or improved from their attendance at the CDPs. Determining ways in which CDPs can support women’s advancement in academic medicine requires a deeper understanding of what participants seek from CDPs and how they use program content to advance their careers.

Systems of Career Influences: A Conceptual Model for Evaluating the Professional Development of Women in Academic Medicine

BACKGROUND Surprisingly little research is available to explain the well-documented organizational and societal influences on persistent inequities in advancement of women faculty. METHODS The Systems of Career Influences Model is a framework for exploring factors influencing womens progression to advanced academic rank, executive positions, and informal leadership roles in academic medicine. The model situates faculty as agents within a complex adaptive system consisting of a trajectory of career advancement with opportunities for formal professional development programming; a dynamic system of influences of organizational policies, practices, and culture; and a dynamic system of individual choices and decisions. These systems of influence may promote or inhibit career advancement. Within this system, women weigh competing influences to make career advancement decisions, and leaders of academic health centers prioritize limited resources to support the schools mission. RESULTS AND CONCLUSIONS The Systems of Career Influences Model proved useful to identify key research questions. We used the model to probe how research in academic career development might be applied to content and methods of formal professional development programs. We generated a series of questions and hypotheses about how professional development programs might influence professional development of health science faculty members. Using the model as a guide, we developed a study using a quantitative and qualitative design. These analyses should provide insight into what works in recruiting and supporting productive men and women faculty in academic medical centers.

Linkage analysis of affected sib pairs allowing for parent-of-origin effects.

Parent‐of‐origin effects, also known as genomic imprinting, exist for many mammalian genes. For imprinted genes the expression of an allele depends upon the sex of the transmitting parent. Here we have developed a method based on alleles that are shared identical by descent by affected sib pairs, that allows for parent‐of‐origin effects. Our method allows for sex‐specific recombination rates, an important consideration in studying imprinted genes. We have also derived a tetrahedron for the true identical‐by‐descent frequencies accounting for parent‐of‐origin effects. Using this tetrahedron, we propose a robust generalized minmax test for linkage and discuss its properties in the presence of genomic imprinting. We have also performed power comparisons of various allele sharing tests and provide regions of the tetrahedron in which the different tests are optimal. We also provide useful strategies to determine the optimal tests to use while performing a genome scan.

Alpha-Actinin 4 Is Associated with Cancer Cell Motility and Is a Potential Biomarker in Non–Small Cell Lung Cancer

Background: Differential expression and secretion of alpha-actinin 4 (ACTN4) in the lung cancer cell lines CL1-0 and CL1-5 have been reported in previous proteomic studies. The aim of this study is to investigate the functional properties of the ACTN4 protein in non–small-cell lung cancer (NSCLC) cells and evaluate its clinical importance. Methods: We used RNA interference to knock down and overexpress ACTN4 protein to evaluate the effects of this intervention on cancer cell invasion and migration, as well as on microscopic cellular morphology. Furthermore, we examined by immunohistochemistry the expression of ACTN4 protein in tissue samples at different stages of lung cancerand compared the protein levels of ACTN4 in blood plasma samples from patients with histologically confirmed lung cancer and healthy controls. Results: CL1-5 cell motility was significantly suppressed by the knockdown of ACTN4 protein. The morphology of CL1-5 cells changed from a predominantly mesenchymal-like shape into a globular shape in response to ACTN4 protein knockdown. A quantitative immunohistochemical assessment of lung cancer tissues revealed that ACTN4 protein level was considerably higher in cancerous tissues than in the adjacent normal ones, and the area under the receiver operating characteristic curve was 0.736 (p < 0.001). According to an enzyme-linked immunosorbent assay, the plasma levels of ACTN4 protein were significantly different between cancer patients and healthy controls, and the areas under the receiver operating characteristic curves were 0.828 and 0.909, respectively, for two independent cohorts (p < 0.001). Conclusions: We demonstrate that the knockdown of ACTN4 protein inhibited cell invasion and migration. These results suggest that ACTN4 is associated with lung cancer cell motility. Thus, the level of ACTN4 in cancerous tissue and plasma is related to the presence of lung cancer.

Qualification and Verification of Serological Biomarker Candidates for Lung Adenocarcinoma by Targeted Mass Spectrometry.

Lung cancer is the leading cause of cancer mortality worldwide. Although many biomarkers have been identified for lung cancer, their low specificity and sensitivity present an urgent need for the identification of more candidate biomarkers. In this study, we conducted MRM-based targeted analysis to evaluate the potential utility of a list of candidate proteins for lung cancer diagnosis. A total of 1249 transitions of 420 peptides representing 102 candidate proteins from our previous study and the literature were first screened by MRM analysis in pooled plasma samples, resulting in 78 proteins remaining in the list. Relative quantification of these 78 proteins was further performed in 60 individual plasma samples from lung adenocarcinoma patients in stages I-III and matched healthy control subjects. Ultimately, nine proteins were found to be able to distinguish patients from controls. Further combinations of five, three, and two candidate marker proteins improved the sensitivity to discriminate patients from controls and resulted in a merged AUC value of nearly 1.00 in stages I-III patients versus controls. Our results highlighted several possible markers for lung adenocarcinoma, and the proposed protein panels require further validation in a larger cohort to evaluate their potential use in clinical applications or development of therapeutics.

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Genomic deletions have long been known to play a causative role in microdeletion syndromes. Recent whole-genome genetic studies have shown that deletions can increase the risk for several psychiatric disorders, suggesting that genomic deletions play an important role in the genetic basis of complex traits. However, the association between genomic deletions and common, complex diseases has not yet been systematically investigated in gene mapping studies. Likelihood-based statistical methods for identifying disease-associated deletions have recently been developed for familial studies of parent-offspring trios. The purpose of this study is to develop statistical approaches for detecting genomic deletions associated with complex disease in case–control studies. Our methods are designed to be used with dense single nucleotide polymorphism (SNP) genotypes to detect deletions in large-scale or whole-genome genetic studies. As more and more SNP genotype data for genome-wide association studies become available, development of sophisticated statistical approaches will be needed that use these data. Our proposed statistical methods are designed to be used in SNP-by-SNP analyses and in cluster analyses based on combined evidence from multiple SNPs. We found that these methods are useful for detecting disease-associated deletions and are robust in the presence of linkage disequilibrium using simulated SNP data sets. Furthermore, we applied the proposed statistical methods to SNP genotype data of chromosome 6p for 868 rheumatoid arthritis patients and 1,197 controls from the North American Rheumatoid Arthritis Consortium. We detected disease-associated deletions within the region of human leukocyte antigen in which genomic deletions were previously discovered in rheumatoid arthritis patients.

Effects of measured susceptibility genes on cancer risk in family studies

Numerous family studies have been performed to assess the associations between cancer incidence and genetic and non-genetic risk factors and to quantitatively evaluate the cancer risk attributable to these factors. However, mathematical models that account for a measured hereditary susceptibility gene have not been fully explored in family studies. In this report, we proposed statistical approaches to precisely model a measured susceptibility gene fitted to family data and simultaneously determine the combined effects of individual risk factors and their interactions. Our approaches are structured for age-specific risk models based on Cox proportional hazards regression methods. They are useful for analyses of families and extended pedigrees in which measured risk genotypes are segregated within the family and are robust even when the genotypes are available only in some members of a family. We exemplified these methods by analyzing six extended pedigrees ascertained through soft-tissue sarcoma patients with p53 germ-line mutations. Our analyses showed that germ-line p53 mutations and sex had significant interaction effects on cancer risk. Our proposed methods in family studies are accurate and robust for assessing age-specific cancer risk attributable to a measured hereditary susceptibility gene, providing valuable inferences for genetic counseling and clinical management.

Whole-genome detection of disease-associated deletions or excess homozygosity in a case–control study of rheumatoid arthritis

Unlike genome-wide association studies, few comprehensive studies of copy number variations contribution to complex human disease susceptibility have been performed. Copy number variations are abundant in humans and represent one of the least well-studied classes of genetic variants; in addition, known rheumatoid arthritis susceptibility loci explain only a portion of familial clustering. Therefore, we performed a genome-wide study of association between deletion or excess homozygosity and rheumatoid arthritis using high-density 550 K SNP genotype data from a genome-wide association study. We used a genome-wide statistical method that we recently developed to test each contiguous SNP locus between 868 cases and 1194 controls to detect excess homozygosity or deletion variants that influence susceptibility. Our method is designed to detect statistically significant evidence of deletions or homozygosity at individual SNPs for SNP-by-SNP analyses and to combine the information among neighboring SNPs for cluster analyses. In addition to successfully detecting the known deletion variants on major histocompatibility complex, we identified 4.3 and 28 kb clusters on chromosomes 10p and 13q, respectively, which were significant at a Bonferroni-type-corrected 0.05 nominal significant level. Independently, we performed analyses using PennCNV, an algorithm for identifying and cataloging copy numbers for individuals based on a hidden Markov model, and identified cases and controls that had chromosomal segments with copy number <2. Using Fishers exact test for comparing the numbers of cases and controls with copy number <2 per SNP, we identified 26 significant SNPs (protective; more controls than cases) aggregating on chromosome 14 with P-values <10(-8).

Statistical properties of affected sib-pair linkage tests

Genetic linkage analysis is a powerful tool for the identification of disease susceptibility loci. Among the most commonly applied genetic linkage strategies are affected sib-pair tests, but the statistical properties of these tests have not been well characterized. Here, we present a study of the distribution of affected sib-pair tests comparing the type I error rate and the power of the mean test and the proportion test, which are the most commonly used, along with a novel exact test. In contrast to existing literature, our findings showed that the mean and proportion tests have inflated type I error rates, especially when used with small samples. We developed and applied corrections to the tests which provide an excellent adjustment to the type I error rate for both small and large samples. We also developed a novel approach to identify the areas of higher power for the mean test versus the proportion test, providing a wider and simpler comparison with fewer assumptions about parameter values than existing approaches require.