9b0f7a4cfbc63d13254631a4a2458022 pmc_34207612.pdf 391b988c81f60e7ed2dac99586554b0ab55f9936 pmc_34207612.pdf 10ee208c1cceef21a49d8473bde55f7b67352965ebeb1c95232eeaf1b023e0fa pmc_34207612.pdf Title: Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants Subject: The present limitations in the pathogenicity prediction of BRCA1 and BRCA2 (BRCA1/2) missense variants constitute an important problem with negative consequences for the diagnosis of hereditary breast and ovarian cancer. However, it has been proposed that the use of endophenotype predictions, i.e., computational estimates of the outcomes of functional assays, can be a good option to address this bottleneck. The application of this idea to the BRCA1/2 variants in the CAGI 5-ENIGMA international challenge has shown promising results. Here, we developed this approach, exploring the predictive performances of the regression models applied to the BRCA1/2 variants for which the values of the homology-directed DNA repair and saturation genome editing assays are available. Our results first showed that we can generate endophenotype estimates using a few molecular-level properties. Second, we show that the accuracy of these estimates is enough to obtain pathogenicity predictions comparable to those of many standard tools. Third, endophenotype-based predictions are complementary to, but do not outperform, those of a Random Forest model trained using variant pathogenicity annotations instead of endophenotype values. In summary, our results confirmed the usefulness of the endophenotype approach for the pathogenicity prediction of the BRCA1/2 missense variants, suggesting different options for future improvements. Keywords: BRCA1; BRCA2; endophenotype; breast cancer; functional assays; pathogenicity predictions; homology-directed DNA repair (HDR); molecular diagnosis; ovarian cancer; protein-specific predictor Author: Selen Özkan, Natàlia Padilla and Xavier de la Cruz Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Wed Jun 9 10:24:54 2021 CEST ModDate: Wed Jun 9 10:29:47 2021 CEST Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 20 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 7899540 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- CIQLLF+VnURWPalladioL Type 1 Custom yes yes no 10 0 IWYIGY+URWPalladioL-Ital Type 1 Custom yes yes no 15 0 DDUWOC+URWPalladioL-Bold Type 1 Custom yes yes no 20 0 MQXXST+URWPalladioL-Roma Type 1 Custom yes yes no 24 0 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subsubsection.2.1.1 Item: Title: Predicting the Outcome of BRCA1/2 Variants with Other Regression Models Destination: subsubsection.2.1.2 Item: Title: The Effect of the MSA on Endophenotype Estimates Destination: subsubsection.2.1.3 Item: Title: Are Endophenotype Estimates Good Enough for Pathogenicity Prediction? Destination: subsection.2.2 Item: Title: Benchmarking Endophenotype-Based Pathogenicity Predictions against Standard In Silico Predictions Destination: subsection.2.3 Item: Title: Discussion Destination: section.3 Item: Title: Materials and Methods Destination: section.4 Children: Item: Title: The Variant Datasets Destination: subsection.4.1 Item: Title: The Predictive Features Destination: subsection.4.2 Item: Title: Regression Models Destination: subsection.4.3 Item: Title: Binarization of the Endophenotype Estimates into Pathogenic/Benign Values Destination: subsection.4.4 Item: Title: Classification Models Destination: subsection.4.5 Item: Title: Performance Assessment Destination: subsection.4.6 Item: Title: References Destination: AMS.20 Info: Title: Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants Author: Selen Özkan, Natàlia Padilla and Xavier de la Cruz Subject: The present limitations in the pathogenicity prediction of BRCA1 and BRCA2 (BRCA1/2) missense variants constitute an important problem with negative consequences for the diagnosis of hereditary breast and ovarian cancer. However, it has been proposed that the use of endophenotype predictions, i.e., computational estimates of the outcomes of functional assays, can be a good option to address this bottleneck. The application of this idea to the BRCA1/2 variants in the CAGI 5-ENIGMA international challenge has shown promising results. Here, we developed this approach, exploring the predictive performances of the regression models applied to the BRCA1/2 variants for which the values of the homology-directed DNA repair and saturation genome editing assays are available. Our results first showed that we can generate endophenotype estimates using a few molecular-level properties. Second, we show that the accuracy of these estimates is enough to obtain pathogenicity predictions comparable to those of many standard tools. Third, endophenotype-based predictions are complementary to, but do not outperform, those of a Random Forest model trained using variant pathogenicity annotations instead of endophenotype values. In summary, our results confirmed the usefulness of the endophenotype approach for the pathogenicity prediction of the BRCA1/2 missense variants, suggesting different options for future improvements. 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Annotation: Subtype: Link Rect: 519, 123, 557, 134 Annotation: Subtype: Link Rect: 520, 111, 555, 122 Annotation: Subtype: Link Rect: 301, 89, 338, 99 Page: Sequence: 20 Annotations: Annotation: Subtype: Link Rect: 248, 710, 285, 720 Annotation: Subtype: Link Rect: 349, 675, 387, 686 Annotation: Subtype: Link Rect: 168, 640, 205, 651 Annotation: Subtype: Link Rect: 422, 617, 459, 628 Annotation: Subtype: Link Rect: 149, 595, 186, 605 Annotation: Subtype: Link Rect: 157, 572, 194, 582 Annotation: Subtype: Link Rect: 329, 548, 366, 559 Annotation: Subtype: Link Rect: 359, 525, 396, 536 Annotation: Subtype: Link Rect: 151, 492, 188, 502 Annotation: Subtype: Link Rect: 165, 469, 202, 479 Annotation: Subtype: Link Rect: 262, 445, 300, 456 Annotation: Subtype: Link Rect: 233, 423, 271, 433 Annotation: Subtype: Link Rect: 423, 399, 461, 410 Checksum: b69c729e Type: CRC32 Checksum: 9b0f7a4cfbc63d13254631a4a2458022 Type: MD5 Checksum: 391b988c81f60e7ed2dac99586554b0ab55f9936 Type: SHA-1 Checksum: 10ee208c1cceef21a49d8473bde55f7b67352965ebeb1c95232eeaf1b023e0fa Type: SHA-256