Communication practices about HPV testing among providers in Federally Qualified Health Centers
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Artificial intelligence in cancer research, diagnosis and therapy
Artificial intelligence and machine learning techniques are breaking into biomedical research and health care, which importantly includes cancer research and oncology, where the potential applications are vast. These include detection and diagnosis of cancer, subtype classification, optimization of cancer treatment and identification of new therapeutic targets in drug discovery. While big data used to train machine learning models may already exist, leveraging this opportunity to realize the full promise of artificial intelligence in both the cancer research space and the clinical space will first require significant obstacles to be surmounted. In this Viewpoint article, we asked four experts for their opinions on how we can begin to implement artificial intelligence while ensuring standards are maintained so as transform cancer diagnosis and the prognosis and treatment of patients with cancer and to drive biological discovery.
60 APPLIED LIFE SCIENCES↗
WE-G-12A-01: High Intensity Focused Ultrasound Surgery and Therapy
More and more emphasis is being made on alternatives to invasive surgery and the use of ionizing radiation to treat various diseases including cancer. Novel screening, diagnosis, treatment and monitoring of response to treatment are also hot areas of research and new clinical technologies. Ultrasound(US) has gained traction in all of the aforementioned areas of focus. Especially with recent advances in the use of ultrasound to noninvasively treat various diseases/organ systems. This session will focus on covering MR-guided focused ultrasound and the state of the art clinical applications, and the second speaker will survey the more cutting edge technologies e.g. Focused Ultrasound (FUS) mediated drug delivery, principles of cavitation and US guided FUS. Learning Objectives: Fundamental physics and physical limitations of US interaction with tissue and nanoparticles The alteration of tissue transport using focused ultrasound US control of nanoparticle drug carriers for targeted release The basic principles of MRI-guided focused ultrasound (MRgFUS) surgery and therapy the current state of the art clinical applications of MRgFUS requirements for quality assurance and treatment planning.
60 APPLIED LIFE SCIENCES↗
Plasma Biomarker Profiles Differ Depending on Breast Cancer Subtype but RANTES is Consistently Increased
Background: Current biomarkers for breast cancer have little potential for detection. We determined if breast cancer subtypes influence circulating protein biomarkers. Methods: A sandwich-ELISA microarray platform was used to evaluate 23 candidate biomarkers in plasma samples that were obtained from subjects with either benign breast disease or invasive breast cancer. All plasma samples were collected at the time of biopsy, after a referral due to a suspicious screen (e.g., mammography). Cancer samples were evaluated based on breast cancer subtypes, as defined by the HER2 and estrogen receptor statuses. Results: Ten proteins were statistically altered in at least one breast cancer subtype, including four epidermal growth factor receptor ligands, two matrix metalloproteases, two cytokines, and two angiogenic factors. Only one cytokine, RANTES, was significantly increased (P<0.01 for each analysis) in all four subtypes, with areas under receiver operating characteristic curves (AUC) that ranged from 0.76 to 0.82, depending on cancer subtype. The best AUC values were observed for analyses that combined data from multiple biomarkers, with values ranging from 0.70 to 0.99, depending on the cancer subtype. Although the results for RANTES are consistent with previous publications, the multi-assay results need to be validated in independent sample sets. Conclusions: Different breast cancer subtypes produce distinct biomarker profiles, and circulating protein biomarkers have potential to differentiate between true and false positive screens for breast cancer. Impact: Subtype-specific biomarker panels may be useful for detecting breast cancer or as an adjunct assay to improve the accuracy of current screening methods.
59 BASIC BIOLOGICAL SCIENCES↗
WE-D-207-02: Capturing Data Elements and the Role of Imaging Informatics
In the United States, Lung Cancer is responsible for more cancer deaths than the next four cancers combined. In addition, the 5 year survival rate for lung cancer patients has not improved over the past 40 to 50 years. To combat this deadly disease, in 2002 the National Cancer Institute launched a very large Randomized Control Trial called the National Lung Screening Trial (NLST). This trial would randomize subjects who had substantial risk of lung cancer (due to age and smoking history) into either a Chest X-ray arm or a low dose CT arm. In November 2010, the National Cancer Institute announced that the NLST had demonstrated 20% fewer lung cancer deaths among those who were screened with low-dose CT than with chest X-ray. In December 2013, the US Preventive Services Task Force recommended the use of Lung Cancer Screening using low dose CT and a little over a year later (Feb. 2015), CMS announced that Medicare would also cover Lung Cancer Screening using low dose CT. Thus private and public insurers are required to provide Lung Cancer Screening programs using CT to the appropriate population(s). The purpose of this Symposium is to inform medical physicists and prepare them to support the implementation of Lung Screening programs. This Symposium will focus on the clinical aspects of lung cancer screening, requirements of a screening registry for systematically capturing and tracking screening patients and results (such as required Medicare data elements) as well as the role of the medical physicist in screening programs, including the development of low dose CT screening protocols. Learning Objectives: To understand the clinical basis and clinical components of a lung cancer screening program, including eligibility criteria and other requirements. To understand the data collection requirements, workflow, and informatics infrastructure needed to support the tracking and reporting components of a screening program. To understand the role of the medical physicist in implementing Lung Cancer Screening protocols for CT, including utilizing resources such as the AAPM Protocols and the ACR Designated Lung Screening Center program. UCLA Department of Radiology has an Institutional research agreement with Siemens Healthcare; Dr. McNitt-Gray has been a recipient of Research Support from Siemens Healthcare in the past. Dr. Aberle has been a Member of Advisory Boards for the LUNGevity Foundation (2011-present) and Siemens Medical Solutions. (2013)
60 APPLIED LIFE SCIENCES↗
Estimation of breast percent density in raw and processed full field digital mammography images via adaptive fuzzy c-means clustering and support vector machine segmentation
Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') and vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which are then aggregated into a final dense tissue segmentation that is used to compute breast PD%. Our method is validated on a group of 81 women for whom bilateral, mediolateral oblique, raw and processed screening digital mammograms were available, and agreement is assessed with both continuous and categorical density estimates made by a trained breast-imaging radiologist. Results: Strong association between algorithm-estimated and radiologist-provided breast PD% was detected for both raw (r= 0.82, p < 0.001) and processed (r= 0.85, p < 0.001) digital mammograms on a per-breast basis. Stronger agreement was found when overall breast density was assessed on a per-woman basis for both raw (r= 0.85, p < 0.001) and processed (0.89, p < 0.001) mammograms. Strong agreement between categorical density estimates was also seen (weighted Cohen's {kappa}{>=} 0.79). Repeated measures analysis of variance demonstrated no statistically significant differences between the PD% estimates (p > 0.1) due to either presentation of the image (raw vs processed) or method of PD% assessment (radiologist vs algorithm). Conclusions: The proposed fully automated algorithm was successful in estimating breast percent density from both raw and processed digital mammographic images. Accurate assessment of a woman's breast density is critical in order for the estimate to be incorporated into risk assessment models. These results show promise for the clinical application of the algorithm in quantifying breast density in a repeatable manner, both at time of imaging as well as in retrospective studies.
60 APPLIED LIFE SCIENCES↗
Resveratrol analogue 3,4,4′,5-tetramethoxystilbene inhibits growth, arrests cell cycle and induces apoptosis in ovarian SKOV‐3 and A-2780 cancer cells
In the screening studies, cytotoxicity of 12 methylated resveratrol analogues on 11 human cancer cell lines was examined. The most active compound 3,4,4′5-tetramethoxystilbene (DMU-212) and two ovarian cancer cell lines A-2780 (IC{sub 50} = 0.71 μM) and SKOV-3 (IC{sub 50} = 11.51 μM) were selected for further investigation. To determine the mechanism of DMU-212 cytotoxicity, its ability to induce apoptosis was examined. DMU-212 arrested cell cycle in the G2/M or G0/G1 phase which resulted in apoptosis of both cell lines. The expression level of 84 apoptosis-related genes was investigated. In SKOV-3 cells DMU-212 caused up-regulation of pro-apoptotic Bax, Apaf-1 and p53 genes, specific to intrinsic pathway of apoptosis, and a decrease in Bcl-2 and Bcl 2110 mRNA expressions. Conversely, in A-2780 cells an increased expression of pro-apoptotic genes Fas, FasL, TNF, TNFRSF10A, TNFRSF21, TNFRSF16 specific to extracellular mechanism of apoptosis was observed. There are no data published so far regarding the receptor mediated apoptosis induced by DMU-212. The activation of caspase-3/7 was correlated with decreased TRAF-1 and BIRC-2 expression level in A-2780 cells exposed to DMU-212. DMU-212 caused a decrease in CYP1A1 and CYP1B1 mRNA levels in A-2780 by 50% and 75%, and in SKOV-3 cells by 15% and 45%, respectively. The protein expression was also reduced in both cell lines. It is noteworthy that the expression of CYP1B1 protein was entirely inhibited in A-2780 cells treated with DMU-212. It can be suggested that different CYP1B1 expression patterns in either ovarian cell line may affect their sensitivity to cytotoxic activity of DMU-212. -- Highlights: ► DMU-212 was the most cytotoxic among 12 O-methylated resveratrol analogues. ► DMU-212 arrested cell cycle at G2/M and G0/G1phase ► DMU-212 triggered mitochondria- and receptor‐mediated apoptosis. ► DMU-212 entirely inhibited CYP1B1 protein expression in A-2780 cells.
60 APPLIED LIFE SCIENCES↗
Automated System for Early Breast Cancer Detection in Mammograms
The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.
Bankman, Isaac N.↗
Identification of a genetic interaction between the tumor suppressor EAF2 and the retinoblastoma protein (Rb) signaling pathway in C. elegans and prostate cancer cells
Highlights: • RNAi screen identified genetic enhancers for the C. elegans homolog of EAF2. • EAF2 and RBBP4 proteins physically bind to each other and alter transcription. • Overexpression of EAF2 and RBBP4 induces the cell death in prostate cancer cells. - Abstract: The tumor suppressor EAF2 is regulated by androgen signaling and associated with prostate cancer. While EAF2 and its partner ELL have been shown to be members of protein complexes involved in RNA polymerase II transcriptional elongation, the biologic roles for EAF2 especially with regards to the development of cancer remains poorly understood. We have previously identified the eaf-1 gene in Caenorhabditiselegans as the ortholog of EAF2, and shown that eaf-1 interacts with the ELL ortholog ell-1 to control development and fertility in worms. To identify genetic pathways that interact with eaf-1, we screened RNAi libraries consisting of transcription factors, phosphatases, and chromatin-modifying factors to identify genes which enhance the effects of eaf-1(tm3976) on fertility. From this screen, we identified lin-53, hmg-1.2, pha-4, ruvb-2 and set-6 as hits. LIN-53 is the C. elegans ortholog of human retinoblastoma binding protein 4/7 (RBBP 4/7), which binds to the retinoblastoma protein and inhibits the Ras signaling pathway. We find that lin-53 showed a synthetic interaction with eaf-1(tm3976) where knockdown of lin-53 in an eaf-1(tm3976) mutant resulted in sterile worms. This phenotype may be due to cell death as the treated worms contain degenerated embryos with increased expression of the ced-1:GFP cell death marker. Further we find that the interaction between eaf-1 and lin-53/RBBP4/7 also exists in vertebrates, which is reflected by the formation of a protein complex between EAF2 and RBBP4/7. Finally, overexpression of either human EAF2 or RBBP4 in LNCaP cells induced the cell death while knockdown of EAF2 in LNCaP enhanced cell proliferation, indicating an important role of EAF2 in controlling the growth and survival of prostate cancer cells. Together these findings identify a novel physical and functional interaction between EAF2 and the Rb pathway.
60 APPLIED LIFE SCIENCES↗
Fractal Analysis of Visual Search Activity for Mass Detection During Mammographic Screening
Purpose: The objective of this study was to assess the complexity of human visual search activity during mammographic screening using fractal analysis and to investigate its relationship with case and reader characteristics. Methods: The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus data for this study. The fractal dimension of the readers’ visual scanning patterns was computed with the Minkowski–Bouligand box-counting method and used as a measure of gaze complexity. Individual factor and group-based interaction ANOVA analysis was performed to study the association between fractal dimension, case pathology, breast density, and reader experience level. The consistency of the observed trends depending on gaze data representation was also examined. Results: Case pathology, breast density, reader experience level, and individual reader differences are all independent predictors of the visual scanning pattern complexity when screening for breast cancer. No higher order effects were found to be significant. Conclusions: Fractal characterization of visual search behavior during mammographic screening is dependent on case properties and image reader characteristics.
47 OTHER INSTRUMENTATION↗
Sequentially calibrating a Bayesian microsimulation model to incorporate new information and assumptions
Background: Microsimulation models are mathematical models that simulate event histories for individual members of a population. They are useful for policy decisions because they simulate a large number of individuals from an idealized population, with features that change over time, and the resulting event histories can be summarized to describe key population-level outcomes. Model calibration is the process of incorporating evidence into the model. Calibrated models can be used to make predictions about population trends in disease outcomes and effectiveness of interventions, but calibration can be challenging and computationally expensive. Methods: This paper develops a technique for sequentially updating models to take full advantage of earlier calibration results, to ultimately speed up the calibration process. A Bayesian approach to calibration is used because it combines different sources of evidence and enables uncertainty quantification which is appealing for decision-making. We develop this method in order to re-calibrate a microsimulation model for the natural history of colorectal cancer to include new targets that better inform the time from initiation of preclinical cancer to presentation with clinical cancer (sojourn time), because model exploration and validation revealed that more information was needed on sojourn time, and that the predicted percentage of patients with cancers detected via colonoscopy screening was too low. Results: The sequential approach to calibration was more efficient than recalibrating the model from scratch. Incorporating new information on the percentage of patients with cancers detected upon screening changed the estimated sojourn time parameters significantly, increasing the estimated mean sojourn time for cancers in the colon and rectum, providing results with more validity. Conclusions: A sequential approach to recalibration can be used to efficiently recalibrate a microsimulation model when new information becomes available that requires the original targets to be supplemented with additional targets.
60 APPLIED LIFE SCIENCES↗
Cancer survival in the United States 2007–2016: Results from the National Program of Cancer Registries
Background Cancer survival has improved for the most common cancers. However, less improvement and lower survival has been observed in some groups perhaps due to differential access to cancer care including prevention, screening, diagnosis, and treatment. Methods To further understand contemporary relative cancer survival (one- and five- year), we used survival data from CDC’s National Program of Cancer Registries (NPCR) for cancers diagnosed during 2007–2016. We examined overall relative cancer survival by sex, race and ethnicity, age, and county-level metropolitan and non-metropolitan status. Relative cancer survival by metropolitan and non-metropolitan status was further examined by sex, race and ethnicity, age, and cancer type. Results Among persons with cancer diagnosed during 2007–2016 the overall one-year and five-year relative survival was 80.6% and 67.4%, respectively. One-year relative survival for persons living in metropolitan counties was 81.1% and 77.8% among persons living in non-metropolitan counties. We found that persons who lived in non-metropolitan counties had lower survival than those who lived in metropolitan counties, and this difference persisted across sex, race and ethnicity, age, and most cancer types. Conclusion Further examination of the differences in cancer survival by cancer type or other characteristics might be helpful for identifying potential interventions, such as programs that target screening and early detection or strategies to improve access to high quality cancer treatment and follow-up care, that could improve long-term outcomes. Impact This analysis provided a high-level overview of contemporary cancer survival in the United States.
60 APPLIED LIFE SCIENCES↗
Commercial Opportunity Cancer Imaging Ultrasonics-based methods for cancer imaging & diagnostics
Breast cancer is the most frequently diagnosed cancer in U.S. women and prostate cancer is the second leading cause of cancer death in American men. X-ray mammography is the principal breastcancer screening tool available, but its false positive rate is more than 80%. Prostate-specific antigen (PSA) screening, which measures the level of PSA in a man’s blood, is no longer recommended by the U.S. task force for prostate-cancer screening. Los Alamos National Security (LANS) has developed novel imaging technologies for early-stage cancer detection based on advanced ultrasonic analyses. In particular, Los Alamos has developed ultrasoundwaveform tomography and related super-resolution ultrasound- imaging technologies that can provide significantly improved image resolution and characterization of early-stage cancers and thus potentially save lives.
60 APPLIED LIFE SCIENCES↗
Disordered methionine metabolism in MTAP/CDKN2A-deleted cancers leads to dependence on PRMT5
5-Methylthioadenosine phosphorylase (MTAP) is a key enzyme in the methionine salvage pathway. The MTAP gene is frequently deleted in human cancers because of its chromosomal proximity to the tumor suppressor gene CDKN2A. By interrogating data from a large-scale short hairpin RNA–mediated screen across 390 cancer cell line models, we found that the viability of MTAP-deficient cancer cells is impaired by depletion of the protein arginine methyltransferase PRMT5. MTAP-deleted cells accumulate the metabolite methylthioadenosine (MTA), which we found to inhibit PRMT5 methyltransferase activity. Deletion of MTAP in MTAP-proficient cells rendered them sensitive to PRMT5 depletion. Conversely, reconstitution of MTAP in an MTAP-deficient cell line rescued PRMT5 dependence. Thus, MTA accumulation in MTAP–deleted cancers creates a hypomorphic PRMT5 state that is selectively sensitized toward further PRMT5 inhibition. Inhibitors of PRMT5 that leverage this dysregulated metabolic state merit further investigation as a potential therapy for MTAP/CDKN2A-deleted tumors.
59 BASIC BIOLOGICAL SCIENCES↗
Genome-wide screen identifies a novel prognostic signature for breast cancer survival
Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion, cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.
59 BASIC BIOLOGICAL SCIENCES↗
Dedicated breast computed tomography: Basic aspects
X-ray mammography of the compressed breast is well recognized as the “gold standard” for early detection of breast cancer, but its performance is not ideal. One limitation of screening mammography is tissue superposition, particularly for dense breasts. Since 2001, several research groups in the USA and in the European Union have developed computed tomography (CT) systems with digital detector technology dedicated to x-ray imaging of the uncompressed breast (breast CT or BCT) for breast cancer screening and diagnosis. This CT technology—tracing back to initial studies in the 1970s—allows some of the limitations of mammography to be overcome, keeping the levels of radiation dose to the radiosensitive breast glandular tissue similar to that of two-view mammography for the same breast size and composition. This paper presents an evaluation of the research efforts carried out in the invention, development, and improvement of BCT with dedicated scanners with state-of-the-art technology, including initial steps toward commercialization, after more than a decade of R and D in the laboratory and/or in the clinic. The intended focus here is on the technological/engineering aspects of BCT and on outlining advantages and limitations as reported in the related literature. Prospects for future research in this field are discussed.
60 APPLIED LIFE SCIENCES↗
RNA interference screening identifies clathrin-B and cofilin-1 as mediators of MT1-MMP in endometrial cancer
The matrix metalloproteinases (MMPs) are implicated in tumor invasion and metastasis. Given their multiple tumor promoting roles, MMPs are promising targets for the treatment of metastatic cancer. Using a siRNA library screen of 140 membrane trafficking genes, we identified 41 genes in HEC-1B and 36 in Ishikawa cancer cells that decreased metalloproteinases activity. The 16 genes common in both cancer cell lines that decreased MMPs activity are involved in cargo sorting, vesicle formation and vesicle recycling. The top two genes clathrin-B and cofilin-1 were chosen for post hoc functional studies. Higher expression of both genes was confirmed in cancer cells and knockdown with respective siRNAs inhibited their invasive potential and matrix metalloproteinases activity. Membrane Type 1- Matrix Metalloproteinase (MT1-MMP) is a master switch proteinase and regulator of invasion and metastasis. A marked decrease in MT1-MMP expression and activity was seen in clathrin-B and cofilin-1 knockdown cancer cells which was associated with a marked decreased expression of invadopodia formation proteins. Our results suggest that the decreased expression of clathrin-B and cofilin-1 decreases the expression of MT1-MMP and results in attenuation of MT1-MMP at the cell surface, thus inhibiting tumor cell invasion and metastasis.
60 APPLIED LIFE SCIENCES↗
Rare key functional domain missense substitutions in MRE11A, RAD50 , and NBN contribute to breast cancer susceptibility: results from a Breast Cancer Family Registry case-control mutation-screening study
The MRE11A-RAD50-Nibrin (MRN) complex plays several critical roles related to repair of DNA double-strand breaks. Inherited mutations in the three components predispose to genetic instability disorders and the MRN genes have been implicated in breast cancer susceptibility, but the underlying data are not entirely convincing. Here, we address two related questions: (1) are some rare MRN variants intermediate-risk breast cancer susceptibility alleles, and if so (2) do the MRN genes follow a BRCA1/BRCA2 pattern wherein most susceptibility alleles are protein-truncating variants, or do they follow an ATM/CHEK2 pattern wherein half or more of the susceptibility alleles are missense substitutions? Using high-resolution melt curve analysis followed by Sanger sequencing, we mutation screened the coding exons and proximal splice junction regions of the MRN genes in 1,313 early-onset breast cancer cases and 1,123 population controls. Rare variants in the three genes were pooled using bioinformatics methods similar to those previously applied to ATM, BRCA1, BRCA2, and CHEK2, and then assessed by logistic regression. Results: Re-analysis of our ATM, BRCA1, and BRCA2 mutation screening data revealed that these genes do not harbor pathogenic alleles (other than modest-risk SNPs) with minor allele frequencies >0.1% in Caucasian Americans, African Americans, or East Asians. Limiting our MRN analyses to variants with allele frequencies of <0.1% and combining protein-truncating variants, likely spliceogenic variants, and key functional domain rare missense substitutions, we found significant evidence that the MRN genes are indeed intermediate-risk breast cancer susceptibility genes (odds ratio (OR) = 2.88, P = 0.0090). Key domain missense substitutions were more frequent than the truncating variants (24 versus 12 observations) and conferred a slightly higher OR (3.07 versus 2.61) with a lower P value (0.029 versus 0.14). These data establish that MRE11A, RAD50, and NBN are intermediate-risk breast cancer susceptibility genes. Like ATM and CHEK2, their spectrum of pathogenic variants includes a relatively high proportion of missense substitutions. However, the data neither establish whether variants in each of the three genes are best evaluated under the same analysis model nor achieve clinically actionable classification of individual variants observed in this study.
59 BASIC BIOLOGICAL SCIENCES↗