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1.
Med Phys ; 2021 Feb 17.
Artigo em Inglês | MEDLINE | ID: mdl-33595105

RESUMO

PURPOSE: To develop a two-stage 3D-CNN for fully automated volumetric segmentation of pancreas on CT and to further evaluate its performance in the context of intra-reader and inter-reader reliability at full dose and reduced radiation dose CTs on a public dataset. METHODS: A dataset of 1994 abdomen CT scans (portal venous phase, slice thickness ≤ 3.75-mm, multiple CT vendors) was curated by two radiologists (R1 and R2) to exclude cases with pancreatic pathology, sub-optimal image quality, and image artifacts (n=77). Remaining 1917 CTs were equally allocated between R1 and R2 for volumetric pancreas segmentation [ground truth (GT)]. This internal dataset was randomly divided into training (n=1380), validation (n=248) and test (n=289) sets for the development of a two-stage 3D CNN model based on a modified U-net architecture for automated volumetric pancreas segmentation. Model's performance for pancreas segmentation and the differences in model-predicted pancreatic volumes versus GT volumes were compared on the test set. Subsequently, an external dataset from The Cancer Imaging Archive (TCIA) that had CT scans acquired at standard radiation dose and same scans reconstructed at a simulated 25% radiation dose was curated (n=41). Volumetric pancreas segmentation was done on this TCIA dataset by R1 and R2 independently on the full dose and then at the reduced radiation dose CT images. Intra-reader and inter-reader reliability, model's segmentation performance, and reliability between model-predicted pancreatic volumes at full versus reduced-dose were measured. Finally, model's performance was tested on the benchmarking National Institute of Health (NIH)-Pancreas CT (PCT) dataset. RESULTS: 3D-CNN had mean (SD) Dice Similarity Coefficient (DSC): 0.91 (0.03) and average Hausdorff distance of 0.15 (0.09) mm on the test set. Model's performance was equivalent between males and females (p=0.08) and across different CT slice thicknesses (p>0.05) based on non-inferiority statistical testing. There was no difference in model-predicted and GT pancreatic volumes [mean predicted volume 99 cc (31cc); GT volume 101 cc (33 cc), p=0.33]. Mean pancreatic volume difference was -2.7 cc (percent difference: -2.4% of GT volume) with excellent correlation between model-predicted and GT volumes [concordance correlation coefficient (CCC)=0.97]. In the external TCIA dataset, the model had higher reliability than R1 and R2 on full versus reduced dose CT scans [model mean (SD) DSC: 0.96 (0.02), CCC=0.995 versus R1 DSC: 0.83 (0.07), CCC=0.89, and R2 DSC:0.87 (0.04), CCC=0.97]. The DSC and volume concordance correlations for R1 versus R2 (inter-reader reliability) were 0.85 (0.07), CCC=0.90 at full-dose and 0.83 (0.07), CCC=0.96 at reduced dose datasets. There was good reliability between model and R1 at both full and reduced dose CT [Full dose: DSC: 0.81 (0.07), CCC=0.83 and reduced dose DSC:0.81 (0.08), CCC=0.87]. Likewise, there was good reliability between model and R2 at both full and reduced dose CT [Full dose: DSC: 0.84 (0.05), CCC=0.89 and reduced dose DSC:0.83(0.06), CCC=0.89]. There was no difference in model-predicted and GT pancreatic volume in TCIA dataset (mean predicted volume 96 cc (33); GT pancreatic volume 89 cc (30), p=0.31). Model had mean (SD) DSC: 0.89 (0.04) (minimum- maximum DSC: 0.79 -0.96) on the NIH-PCT dataset. CONCLUSION: A 3D-CNN developed on the largest dataset of CTs is accurate for fully automated volumetric pancreas segmentation and is generalizable across a wide-range of CT slice thicknesses, radiation dose and patient gender. This 3D-CNN offers a scalable tool to leverage biomarkers from pancreas morphometrics and radiomics for pancreatic diseases including for early pancreatic cancer detection.

2.
Am J Hum Genet ; 2021 Feb 17.
Artigo em Inglês | MEDLINE | ID: mdl-33609447

RESUMO

Determination of the clinical relevance of rare germline variants of uncertain significance (VUSs) in the BRCA2 cancer predisposition gene remains a challenge as a result of limited availability of data for use in classification models. However, laboratory-based functional data derived from validated functional assays of known sensitivity and specificity may influence the interpretation of VUSs. We evaluated 252 missense VUSs from the BRCA2 DNA-binding domain by using a homology-directed DNA repair (HDR) assay and identified 90 as non-functional and 162 as functional. The functional assay results were integrated with other available data sources into an ACMG/AMP rules-based classification framework used by a hereditary cancer testing laboratory. Of the 186 missense variants observed by the testing laboratory, 154 were classified as VUSs without functional data. However, after applying protein functional data, 86% (132/154) of the VUSs were reclassified as either likely pathogenic/pathogenic (39/132) or likely benign/benign (93/132), which impacted testing results for 1,900 individuals. These results indicate that validated functional assay data can have a substantial impact on VUS classification and associated clinical management for many individuals with inherited alterations in BRCA2.

3.
Ultrasound Med Biol ; 47(4): 1115-1119, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33446373

RESUMO

Ultrasound bladder vibrometry (UBV) parameters have been shown in previous studies to strongly correlate with measurements from urodynamic studies. Just like urodynamic studies, UBV can be performed in supine and sitting positions. The objective of this study is to compare UBV parameters obtained in the two different positions using statistical methods. We recruited eight volunteers with healthy bladders for this purpose. The elasticity, group velocity squared and thickness of the bladder were the UBV parameters of interest, and their values were recorded at different bladder volumes for each volunteer. The results presented indicate that the measurements made in the two positions are in agreement using the Bland-Altman method and a parameter q which compares the values at each bladder volume for each volunteer. UBV parameters were also repeatable for measurements recorded in the supine and sitting positions.

4.
J Biophotonics ; 2020 Dec 13.
Artigo em Inglês | MEDLINE | ID: mdl-33314731

RESUMO

Embolectomy is one of the emergency procedures performed to remove emboli. Assessing the composition of human blood clots is an important diagnostic factor and could provide guidance for an appropriate treatment strategy for interventional physicians. Immunostaining has been used to identity compositions of clots as a gold-standard procedure, but it is time-consuming and cannot be performed in situ. Here, we proposed that the optical attenuation coefficient of optical coherence tomography (OCT) can be a reliable indicator as a new imaging modality to differentiate clot compositions. Fifteen human blood clots with multiple red blood cell (RBC) compositions from 21% to 95% were prepared using healthy human whole blood. A homogeneous gelatin phantom experiment and numerical simulation based on the Lambert-Beer's law were examined to verify the validity of the attenuation coefficient estimation. The results displayed that optical attenuation coefficients were strongly correlated with RBC compositions. We reported that attenuation coefficients could be a promising biomarker to guide the choice of an appropriate interventional device in a clinical setting and assist in characterizing blood clots. This article is protected by copyright. All rights reserved.

5.
Breast ; 54: 248-255, 2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33188991

RESUMO

PURPOSE: To investigate the diagnostic role of new metrics, defined as individualized-thresholding of Shear Wave Elastography (SWE) parameters, in association with clinical factors (such as age, mammographic density, lesion size and depth) and the BI-RADS features in differentiating benign from malignant breast lesions. METHODS: Of 644 consecutive patients (median age, 55 years), prospectively referred for evaluation, 659 ultrasound detected breast lesions underwent SWE measurements. Multivariable logistic regression analysis was used to estimate the probability of malignancy. The area under the curve (AUC), optimal cutoff value, and the corresponding sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were determined. RESULTS: 265 of 659 (40.2%) masses were malignant. Using two Emean cutoffs, 69.6 kPa for large superficial lesions (size >10 mm, depth ≤5 mm) and 39.2 kPa for the rest, the overall specificity, sensitivity, PPV and NPV were 92.6%, 86.8%, 88.8% and 91.3%, respectively. Combining multiple factors, including Emean with two cutoffs, age and BI-RADS, the new ROC curve based on the malignancy probability calculation showed the highest AUC (0.954, 95% CI: 0.938-0.969). Using the optimal probability threshold of 0.514, the corresponding specificity, sensitivity, PPV and NPV were 92.9%, 89.1%, 89.4% and 92.7%, respectively. CONCLUSIONS: The false-positive rate can be significantly reduced when applying two Emean cutoffs based on lesion size and depth. Moreover, the combination of age, Emean with two cutoffs and BI-RADS can further reduce the false negatives and false positives. Overall, this multifactorial analysis improves the specificity of ultrasound while maintaining a high sensitivity.

6.
J Natl Cancer Inst ; 2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33146377

RESUMO

To evaluate the racial/ethnic differences in prevalence of germline pathogenic variants (PVs) and the effect of race/ethnicity on breast cancer (BC) risk among carriers, results of multigene testing of 77,900 women with BC (Non-Hispanic White [NHW] = 57,003; Ashkenazi-Jewish = 4,798; Black = 6,722; Hispanic = 5,194; and Asian = 4,183) were analyzed and the frequency of PVs in each gene were compared between BC cases and race/ethnicity-matched gnomAD reference controls. Compared to NHWs, BRCA1 PVs were enriched in Ashkenazi-Jews and Hispanics while CHEK2 PVs were statistically significantly lower in Blacks, Hispanics, and Asians (all two-sided P< 0.05). In case-control studies BARD1 PVs were associated with high risks (Odds Ratio>4.00) of BC in Blacks, Hispanics and Asians; ATM PVs were associated with increased risk of BC among all races/ethnicities except Asians; whereas CHEK2 and BRIP1 PVs were associated with increased risk of BC among NHWs and Hispanics only. These findings suggest a need for personalized management of BC risk in PV carriers based on race/ethnicity.

7.
Clin Cancer Res ; 2020 Oct 07.
Artigo em Inglês | MEDLINE | ID: mdl-33028596

RESUMO

PURPOSE: To compare the clinical characteristics and overall survival (OS) of germline mutation carriers in homologous recombination repair (HRR) genes and noncarriers with pancreatic ductal adenocarcinoma (PDAC). METHODS: Germline DNA from 3,078 patients with PDAC enrolled in a prospective registry at Mayo Clinic between 2000 and 2017 was analyzed for mutations in 37 cancer predisposition genes. Characteristics and OS of patients with mutations in eight genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, PALB2, RAD51C, and RAD51D) involved in HRR were compared with patients testing negative for mutations in all 37 genes. RESULTS: The 175 HRR mutation carriers and 2,730 noncarriers in the study had a median duration of follow-up of 9.9 years. HRR mutation carriers were younger (median age at diagnosis: 63 vs. 66 years, P < 0.001) and more likely to have metastatic disease at diagnosis (46% vs. 36%, P = 0.004). In a multivariable model adjusting for sex, age at diagnosis, and tumor staging, patients with germline HRR mutations had a significantly longer OS compared with noncarriers [HR, 0.83; 95% confidence interval (CI), 0.70-0.97; P = 0.02]. Further gene-level analysis demonstrated that germline ATM mutation carriers had longer OS compared with patients without germline mutations in any of the 37 genes (HR, 0.72; 95% CI, 0.55-0.94; P = 0.01). CONCLUSIONS: This study demonstrates that germline mutation carrier status in PDAC is associated with longer OS compared with noncarriers. Further research into tumor biology and response to platinum-based chemotherapy in germline mutation carriers with PDAC are needed to better understand the association with longer OS.

8.
JCO Precis Oncol ; 4: 32-43, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32832836

RESUMO

PURPOSE: In studies of men of European ancestry, rare pathogenic variants in DNA repair pathway genes have been shown to be associated with risk of aggressive prostate cancer. The contribution of rare coding variation to prostate cancer risk in men of African ancestry has not been established. METHODS: We sequenced a panel of 19 DNA repair and cancer predisposition genes in 2,453 African American and 1,151 Ugandan prostate cancer cases and controls. Rare variants were classified as pathogenic or putatively functionally disruptive and examined in association with prostate cancer risk and disease aggressiveness in gene and pathway-level association analyses. RESULTS: Pathogenic variants were found in 75 out of 2,098 cases (3.6%) and 31 out of 1,481 controls (2.1%) (OR=1.82, 95% CI=1.19 to 2.79, P=0.0044) with the association being stronger for more aggressive disease phenotypes (OR=3.10, 95% CI=1.54 to 6.23, P=0.0022). The highest risks for aggressive disease were observed with pathogenic variants in the ATM, BRCA2, PALB2 and NBN genes, with odds ratios ranging from ~4 to 15 in the combined study sample of African American and Ugandan men. Rare, non-pathogenic, non-synonymous variants did not have a major impact on risk of overall prostate cancer or disease aggressiveness. CONCLUSIONS: Rare pathogenic variants in DNA repair genes have appreciable effects on risk of aggressive prostate cancer in men of African ancestry. These findings have potential implications for panel testing and risk stratification in this high-risk population.

9.
NPJ Breast Cancer ; 6: 13, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32377563

RESUMO

In silico predictions of missense variants is an important consideration when interpreting variants of uncertain significance (VUS) in the BRCA1 and BRCA2 genes. We trained and evaluated hundreds of machine learning algorithms based on results from validated functional assays to better predict missense variants in these genes as damaging or neutral. This new optimal "BRCA-ML" model yielded a substantially more accurate method than current algorithms for interpreting the functional impact of variants in these genes, making BRCA-ML a valuable addition to data sources for VUS classification.

10.
Hum Mutat ; 41(8): e1-e6, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32442341

RESUMO

Multigene panel testing for cancer predisposition mutations is becoming routine in clinical care. However, the gene content of panels offered by testing laboratories vary significantly, and data on mutation detection rates by gene and by the panel is limited, causing confusion among clinicians on which test to order. Using results from 147,994 multigene panel tests conducted at Ambry Genetics, we built an interactive prevalence tool to explore how differences in ethnicity, age of onset, and personal and family history of different cancers affect the prevalence of pathogenic mutations in 31 cancer predisposition genes, across various clinically available hereditary cancer gene panels. Over 13,000 mutation carriers were identified in this high-risk population. Most were non-Hispanic white (74%, n = 109,537), but also Black (n = 10,875), Ashkenazi Jewish (n = 10,464), Hispanic (n = 10,028), and Asian (n = 7,090). The most prevalent cancer types were breast (50%), ovarian (6.6%), and colorectal (4.7%), which is expected based on genetic testing guidelines and clinician referral for testing. The Hereditary Cancer Multi-Gene Panel Prevalence Tool presented here can be used to provide insight into the prevalence of mutations on a per-gene and per-multigene panel basis, while conditioning on multiple custom phenotypic variables to include race and cancer type.

11.
J Natl Cancer Inst ; 2020 May 19.
Artigo em Inglês | MEDLINE | ID: mdl-32427313

RESUMO

BACKGROUND: The risks of breast cancer in African American (AA) women associated with inherited mutations in breast cancer predisposition genes are not well defined. Thus, whether multigene germline hereditary cancer testing panels are applicable to this population is unknown. We assessed associations between mutations in panel-based genes and breast cancer risk in 5054 AA women with breast cancer and 4993 unaffected AA women drawn from 10 epidemiologic studies. METHODS: Germline DNA samples were sequenced for mutations in 23 cancer predisposition genes using a QIAseq multiplex amplicon panel. Prevalence of mutations and odds ratios (ORs) for associations with breast cancer risk were estimated with adjustment for study design, age, and family history of breast cancer. RESULTS: Pathogenic mutations were identified in 10.3% of women with estrogen receptor (ER)-negative breast cancer, 5.2% of women with ER-positive breast cancer, and 2.3% of unaffected women. Mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (OR = 47.55, 95% confidence interval [CI] = 10.43 to >100; OR = 7.25, 95% CI = 4.07 to 14.12; OR = 8.54, 95% CI = 3.67 to 24.95, respectively). RAD51D mutations were associated with high risk of ER-negative disease (OR = 7.82, 95% CI = 1.61 to 57.42). Moderate risks were observed for CHEK2, ATM, ERCC3, and FANCC mutations with ER-positive cancer, and RECQL mutations with all breast cancer. CONCLUSIONS: The study identifies genes that predispose to breast cancer in the AA population, demonstrates the validity of current breast cancer testing panels for use in AA women, and provides a basis for increased referral of AA patients for cancer genetic testing.

12.
J Clin Oncol ; 38(13): 1409-1418, 2020 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-32125938

RESUMO

PURPOSE: To determine the sensitivity and specificity of genetic testing criteria for the detection of germline pathogenic variants in women with breast cancer. MATERIALS AND METHODS: Women with breast cancer enrolled in a breast cancer registry at a tertiary cancer center between 2000 and 2016 were evaluated for germline pathogenic variants in 9 breast cancer predisposition genes (ATM, BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, and TP53). The performance of the National Comprehensive Cancer Network (NCCN) hereditary cancer testing criteria was evaluated relative to testing of all women as recommended by the American Society of Breast Surgeons. RESULTS: Of 3,907 women, 1,872 (47.9%) meeting NCCN criteria were more likely to carry a pathogenic variant in 9 predisposition genes compared with women not meeting criteria (9.0% v 3.5%; P < .001). Of those not meeting criteria (n = 2,035), 14 (0.7%) had pathogenic variants in BRCA1 or BRCA2. The sensitivity of NCCN criteria was 70% for 9 predisposition genes and 87% for BRCA1 and BRCA2, with a specificity of 53%. Expansion of the NCCN criteria to include all women diagnosed with breast cancer at ≤ 65 years of age achieved > 90% sensitivity for the 9 predisposition genes and > 98% sensitivity for BRCA1 and BRCA2. CONCLUSION: A substantial proportion of women with breast cancer carrying germline pathogenic variants in predisposition genes do not qualify for testing by NCCN criteria. Expansion of NCCN criteria to include all women diagnosed at ≤ 65 years of age improves the sensitivity of the selection criteria without requiring testing of all women with breast cancer.

13.
Int J Biostat ; 2020 Feb 22.
Artigo em Inglês | MEDLINE | ID: mdl-32097120

RESUMO

Survival analysis is a widely used method to establish a connection between a time to event outcome and a set of potential covariates. Accurately predicting the time of an event of interest is of primary importance in survival analysis. Many different algorithms have been proposed for survival prediction. However, for a given prediction problem it is rarely, if ever, possible to know in advance which algorithm will perform the best. In this paper we propose two algorithms for constructing super learners in survival data prediction where the individual algorithms are based on proportional hazards. A super learner is a flexible approach to statistical learning that finds the best weighted ensemble of the individual algorithms. Finding the optimal combination of the individual algorithms through minimizing cross-validated risk controls for over-fitting of the final ensemble learner. Candidate algorithms may range from a basic Cox model to tree-based machine learning algorithms, assuming all candidate algorithms are based on the proportional hazards framework. The ensemble weights are estimated by minimizing the cross-validated negative log partial likelihood. We compare the performance of the proposed super learners with existing models through extensive simulation studies. In all simulation scenarios, the proposed super learners are either the best fit or near the best fit. The performances of the newly proposed algorithms are also demonstrated with clinical data examples.

14.
J Natl Cancer Inst ; 2020 Feb 24.
Artigo em Inglês | MEDLINE | ID: mdl-32091585

RESUMO

BACKGROUND: The germline cancer predisposition genes associated with increased risk of each clinical subtype of breast cancer, defined by estrogen receptor (ER), progesterone receptor (PR), and HER2, are not well defined. METHODS: A total of 54,555 invasive breast cancer patients with 56,480 breast tumors were subjected to clinical hereditary cancer multigene panel testing. Heterogeneity for predisposition genes across clinical breast cancer subtypes was assessed by comparing mutation frequencies by gene among tumor subtypes and by association studies between each tumor subtype and reference controls. RESULTS: Mutations in 15 cancer predisposition genes were detected in 8.6% of patients with ER+/HER2-; 8.9% with ER+/HER2+; 7.7% with ER-/HER2+; and 14.4% of ER-/PR-/HER2- tumors. BRCA1, BRCA2, BARD1 and PALB2 mutations were enriched in ER- and HER2- tumors, RAD51C and RAD51D mutations were enriched in ER- tumors only, TP53 mutations were enriched in HER2+ tumors, and ATM and CHEK2 mutations were enriched in both ER+ and/or HER2+ tumors. All genes were associated with moderate (odds ratio (OR)>2.00) or strong (OR > 5.00) risks of at least one subtype of breast cancer in case-control analyses. Mutations in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53 had predicted lifetime absolute risks of ≥ 20.0% for breast cancer. CONCLUSIONS: Germline mutations in hereditary cancer panel genes confer subtype-specific risks of breast cancer. Combined tumor subtype, age at breast cancer diagnosis, and family history of breast and/or ovarian cancer information provides refined categorical estimates of mutation prevalence for women considering genetic testing.

16.
PLoS One ; 15(1): e0226994, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31929558

RESUMO

OBJECTIVES: To evaluate the predictive performance of comb-push ultrasound shear elastography for the differentiation of reactive and metastatic axillary lymph nodes. METHODS: From June 2014 through September 2018, 114 female volunteers (mean age 58.1±13.3 years; range 28-88 years) with enlarged axillary lymph nodes identified by palpation or clinical imaging were prospectively enrolled in the study. Mean, standard deviation and maximum shear wave elastography parameters from 117 lymph nodes were obtained and compared to fine needle aspiration biopsy results. Mann-Whitney U test and ROC curve analysis were performed. RESULTS: The axillary lymph nodes were classified as reactive or metastatic based on the fine needle aspiration outcomes. A statistically significant difference between reactive and metastatic axillary lymph nodes was observed based on comb-push ultrasound shear elastography (CUSE) results (p<0.0001) from mean and maximum elasticity values. Mean elasticity showed the best separation with a ROC analysis resulting in 90.5% sensitivity, 94.4% specificity, 0.97 area under the curve, 95% positive predictive value, and 89.5% negative predictive value with a 30.2-kPa threshold. CONCLUSIONS: CUSE provided a quantifiable parameter that can be used for the assessment of enlarged axillary lymph nodes to differentiate between reactive and metastatic processes.


Assuntos
Técnicas de Imagem por Elasticidade/métodos , Linfonodos/diagnóstico por imagem , Metástase Linfática/diagnóstico por imagem , Valor Preditivo dos Testes , Ultrassonografia Mamária/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Biópsia por Agulha Fina/normas , Diagnóstico Diferencial , Técnicas de Imagem por Elasticidade/normas , Feminino , Humanos , Pessoa de Meia-Idade , Sensibilidade e Especificidade , Ultrassonografia Mamária/normas
17.
Genet Med ; 22(2): 407-415, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-31406321

RESUMO

PURPOSE: Despite the rapid uptake of multigene panel testing (MGPT) for hereditary cancer predisposition, there is limited guidance surrounding indications for testing and genes to include. METHODS: To inform the clinical approach to hereditary cancer MGPT, we comprehensively evaluated 32 cancer predisposition genes by assessing phenotype-specific pathogenic variant (PV) frequencies, cancer risk associations, and performance of genetic testing criteria in a cohort of 165,000 patients referred for MGPT. RESULTS: We identified extensive genetic heterogeneity surrounding predisposition to cancer types commonly referred for germline testing (breast, ovarian, colorectal, uterine/endometrial, pancreatic, and melanoma). PV frequencies were highest among patients with ovarian cancer (13.8%) and lowest among patients with melanoma (8.1%). Fewer than half of PVs identified in patients meeting testing criteria for only BRCA1/2 or only Lynch syndrome occurred in the respective genes (33.1% and 46.2%). In addition, 5.8% of patients with PVs in BRCA1/2 and 26.9% of patients with PVs in Lynch syndrome genes did not meet respective testing criteria. CONCLUSION: Opportunities to improve upon identification of patients at risk for hereditary cancer predisposition include revising BRCA1/2 and Lynch syndrome testing criteria to include additional clinically actionable genes with overlapping phenotypes and relaxing testing criteria for associated cancers.

18.
Genet Med ; 22(4): 701-708, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-31853058

RESUMO

PURPOSE: Genetic testing of individuals often results in identification of genomic variants of unknown significance (VUS). Multiple lines of evidence are used to help determine the clinical significance of these variants. METHODS: We analyzed ~138,000 individuals tested by multigene panel testing (MGPT). We used logistic regression to predict carrier status based on personal and family history of cancer. This was applied to 4644 tested individuals carrying 2383 BRCA1/2 variants to calculate likelihood ratios informing pathogenicity for each. Heterogeneity tests were performed for specific classes of variants defined by in silico predictions. RESULTS: Twenty-two variants labeled as VUS had odds of >10:1 in favor of pathogenicity. The heterogeneity analysis found that among variants in functional domains that were predicted to be benign by in silico tools, a significantly higher proportion of variants were estimated to be pathogenic than previously indicated; that missense variants outside of functional domains should be considered benign; and that variants predicted to create de novo donor sites were also largely benign. CONCLUSION: The evidence presented here supports the use of personal and family history from MGPT in the classification of VUS and will be integrated into ongoing efforts to provide large-scale multifactorial classification.

19.
NPJ Breast Cancer ; 6(1): 13, 2020 Apr 29.
Artigo em Inglês | MEDLINE | ID: mdl-33579916

RESUMO

In silico predictions of missense variants is an important consideration when interpreting variants of uncertain significance (VUS) in the BRCA1 and BRCA2 genes. We trained and evaluated hundreds of machine learning algorithms based on results from validated functional assays to better predict missense variants in these genes as damaging or neutral. This new optimal "BRCA-ML" model yielded a substantially more accurate method than current algorithms for interpreting the functional impact of variants in these genes, making BRCA-ML a valuable addition to data sources for VUS classification.

20.
Breast Cancer Res ; 21(1): 68, 2019 05 22.
Artigo em Inglês | MEDLINE | ID: mdl-31118087

RESUMO

BACKGROUND: Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. METHODS: Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. RESULTS: Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38-1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28-1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45-1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. CONCLUSIONS: The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.


Assuntos
Biomarcadores Tumorais , Densidade da Mama/genética , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Herança Multifatorial , Adulto , Idoso , Algoritmos , Índice de Massa Corporal , Estudos de Casos e Controles , Feminino , Humanos , Pessoa de Meia-Idade , Modelos Biológicos , Razão de Chances , Polimorfismo de Nucleotídeo Único , Medição de Risco , Fatores de Risco
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