Challenges and approaches to calibrating patient phenotype as evidence for cancer gene variant classification under ACMG/AMP guidelines.

Since first publication of the American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) variant classification guidelines, additional recommendations for application of certain criteria have been released (https://clinicalgenome.org/docs/), to improve their application in the diagnostic setting. However, none have addressed use of the PS4 and PP4 criteria, capturing patient presentation as evidence towards pathogenicity. Application of PS4 can be done through traditional case-control studies, or "proband counting" within or across clinical testing cohorts. Review of the existing PS4 and PP4 specifications for Hereditary Cancer Gene Variant Curation Expert Panels revealed substantial differences in the approach to defining specifications. Using BRCA1, BRCA2 and TP53 as exemplar genes, we calibrated different methods proposed for applying the "PS4 proband counting" criterion. For each approach, we considered limitations, non-independence with other ACMG/AMP criteria, broader applicability, and variability in results for different datasets. Our findings highlight inherent overlap of proband-counting methods with ACMG/AMP frequency codes, and the importance of calibration to derive dataset-specific code weights that can account for potential between-dataset differences in ascertainment and other factors. Our work emphasizes the advantages and generalizability of logistic regression analysis over simple proband-counting approaches to empirically determine the relative predictive capacity and weight of various personal clinical features in the context of multigene panel testing, for improved variant interpretation. We also provide a general protocol, including instructions for data formatting and a web-server for analysis of personal history parameters, to facilitate dataset-specific calibration analyses required to use such data for germline variant classification.

CHEK2 is not a Li-Fraumeni syndrome gene: time to update public resources.

The gene-disease relationship for CHEK2 remains listed as 'Li-Fraumeni syndrome 2' in public resources such as OMIM and MONDO, despite published evidence to the contrary, causing frustration among Li-Fraumeni syndrome (LFS) clinical experts. Here, we compared personal cancer characteristics of 2095 CHEK2 and 248 TP53 pathogenic variant carriers undergoing multigene panel testing at Ambry Genetics against 15 135 individuals with no known pathogenic variant. Our results from a within-cohort logistic regression approach highlight obvious differences between clinical presentation of TP53 and CHEK2 pathogenic variant carriers, with no evidence of CHEK2 being associated with any of the TP53-related core LFS cancers. These findings emphasise the need to replace 'Li-Fraumeni syndrome 2' as the CHEK2-associated disease name, thereby limiting potential confusion.

Pathogenic variants among females with breast cancer and a non-breast cancer reveal opportunities for cancer interception.

PURPOSE: Herein, we report the frequency and distribution of germline pathogenic variants (PVs) among females with breast cancer (BC) and at least one other non-BC who underwent multi-gene panel testing (MGPT). Among females with PVs diagnosed first with BC or ovarian cancer (OC), we sought to enumerate the frequency of subsequent PV-associated cancers. METHODS: Females with BC and cancer of ≥ 1 other site (multiple primary cancers, MPC) who underwent MGPT through Ambry Genetics from March 2012 to December 2016 were included if they had testing of at least 21 genes of interest (ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH, NBN, NF1, PALB2, PMS2, PTEN, RAD51C, RAD51D, STK11, and TP53). Phenotypic data were abstracted from test requisition forms and clinical notes. RESULTS: Of 6,617 evaluable patients, most were White (70.8%) and median age at first cancer, second cancer, and MGPT was 49 (interquartile range [IQR]: 18), 59 (IQR: 16), and 63 (IQR: 16) years, respectively. PVs were found among 14.1% (932/6617) of the overall cohort and in 16.4% (440/2687) of females who were diagnosed first with BC. Among those, 55.2% (243/440) had an actionable PV associated with a subsequent cancer diagnosis including 150 OCs. Of the 2443 females with breast and ovarian cancer, few (n = 97, 9.5%) were diagnosed first with OC, limiting our analysis. CONCLUSIONS: Females with MPC, including BC, have a high frequency of germline PVs (14.1%). These data delineate the opportunities for intercepting subsequent cancers associated with genetic risk among females diagnosed first with BC.

Characterization of POT1 tumor predisposition syndrome: Tumor prevalence in a clinically diverse hereditary cancer cohort.

PURPOSE: Germline variants in POT1 have been implicated in predisposition to melanoma, sarcoma, and glioma in limited studies. Here, we determine the prevalence of cancer types in individuals with POT1 pathogenic variants (PVs) undergoing multigene panel testing (MGPT) for a broad variety of cancer indications. METHODS: We performed a retrospective review of data provided on clinical documents from individuals with POT1 PVs identified via MGPT over a 5-year period. Tumor prevalence in POT1 PV heterozygotes was compared with MGPT-negative wild-type (WT) controls using χ2 test. RESULTS: POT1 PVs were identified in 227 individuals. POT1 PV and WT (n = 13,315) cohorts had a similar proportion of reported tumors (69.6% and 69.2%, respectively); however, POT1 PV heterozygotes were more likely to be diagnosed with multiple tumors (18.9% vs 8.7%; P < .001). Compared with POT1 WT, we identified a significant increase in melanoma (odds ratio 7.03; 95% CI 4.7-10.5; P < .001) and sarcoma (odds ratio 6.6; 95% CI 3.1-13.9; P < .001). CONCLUSION: This analysis of the largest POT1 PV cohort to date validates the inclusion of POT1 in hereditary cancer MGPT and has the potential to impact clinical management recommendations, particularly for patients and families at risk for melanoma and sarcoma.

Germline Genetic Testing After Cancer Diagnosis.

Importance: Germline genetic testing is recommended by practice guidelines for patients diagnosed with cancer to enable genetically targeted treatment and identify relatives who may benefit from personalized cancer screening and prevention. Objective: To describe the prevalence of germline genetic testing among patients diagnosed with cancer in California and Georgia between 2013 and 2019. Design, Setting, and Participants: Observational study including patients aged 20 years or older who had been diagnosed with any type of cancer between January 1, 2013, and March 31, 2019, that was reported to statewide Surveillance, Epidemiology, and End Results registries in California and Georgia. These patients were linked to genetic testing results from 4 laboratories that performed most germline testing for California and Georgia. Main Outcomes and Measures: The primary outcome was germline genetic testing within 2 years of a cancer diagnosis. Testing trends were analyzed with logistic regression modeling. The results of sequencing each gene, including variants associated with increased cancer risk (pathogenic results) and variants whose cancer risk association was unknown (uncertain results), were evaluated. The genes were categorized according to their primary cancer association, including breast or ovarian, gastrointestinal, and other, and whether practice guidelines recommended germline testing. Results: Among 1 369 602 patients diagnosed with cancer between 2013 and 2019 in California and Georgia, 93 052 (6.8%) underwent germline testing through March 31, 2021. The proportion of patients tested varied by cancer type: male breast (50%), ovarian (38.6%), female breast (26%), multiple (7.5%), endometrial (6.4%), pancreatic (5.6%), colorectal (5.6%), prostate (1.1%), and lung (0.3%). In a logistic regression model, compared with the 31% (95% CI, 30%-31%) of non-Hispanic White patients with male breast cancer, female breast cancer, or ovarian cancer who underwent testing, patients of other races and ethnicities underwent testing less often: 22% (95% CI, 21%-22%) of Asian patients, 25% (95% CI, 24%-25%) of Black patients, and 23% (95% CI, 23%-23%) of Hispanic patients (P < .001 using the χ2 test). Of all pathogenic results, 67.5% to 94.9% of variants were identified in genes for which practice guidelines recommend testing and 68.3% to 83.8% of variants were identified in genes associated with the diagnosed cancer type. Conclusions and Relevance: Among patients diagnosed with cancer in California and Georgia between 2013 and 2019, only 6.8% underwent germline genetic testing. Compared with non-Hispanic White patients, rates of testing were lower among Asian, Black, and Hispanic patients.

Prevalence and spectrum of pathogenic variants among patients with multiple primary cancers evaluated by clinical characteristics.

BACKGROUND: Multiple primary cancers (MPCs) are a hallmark of cancer predisposition syndromes. Here the frequency of germline pathogenic variants (PVs) among patients with MPCs is reported. METHODS: Patients with MPCs who underwent multigene panel testing from March 2012 to December 2016 were studied. Eligible patients had an analysis of 21 genes: ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH, NBN, NF1, PALB2, PMS2, PTEN, RAD51C, RAD51D, STK11, and TP53. The frequencies of PVs by sex, number of cancers, and age at diagnosis were compared with 2-sided χ2 tests or Fisher exact tests when the number was <10. RESULTS: Among the 9714 patients analyzed, most were female (91.1%) and White (71.0%); the median age at testing was 63 years, and the median ages at first and second cancer diagnoses were 49 and 58 years, respectively. Overall, 1320 (13.6%) had PVs. The prevalence of PVs increased with the number of primary cancers (PCs): 13.1% with 2 PCs, 15.9% with 3 PCs, and 18.0% with ≥4 PCs (P = .00056). Differences in the prevalence of PVs by age at diagnosis were significant: 14.7% with 2 PCs at an age < 50 years, 15.8% with 1 PC at an age < 50 years, and 12.0% with all PCs at an age ≥ 50 years (P = 2.07E-05). PVs by the age at second cancer diagnosis were also significant: 14.7% at an age < 50 years, 13.9% at an age of 50 to 69 years, and 11.4% at an age ≥ 70 years (P for trend = .005). CONCLUSIONS: Among patients with MPCs, there is a high frequency of germline PVs, with a higher frequency found among patients with a higher number of PCs. These findings suggest that genetic testing should be considered even among patients who are older at the diagnosis of an additional primary malignancy.

Quantifying evidence toward pathogenicity for rare phenotypes: The case of succinate dehydrogenase genes, SDHB and SDHD.

PURPOSE: The weight of the evidence to attach to observation of a novel rare missense variant in SDHB or SDHD in individuals with the rare neuroendocrine tumors, pheochromocytomas and paragangliomas (PCC/PGL), is uncertain. METHODS: We compared the frequency of SDHB and SDHD very rare missense variants (VRMVs) in 6328 and 5847 cases of PCC/PGL, respectively, with that of population controls to generate a pan-gene VRMV likelihood ratio (LR). Via windowing analysis, we measured regional enrichments of VRMVs to calculate the domain-specific VRMV-LR (DS-VRMV-LR). We also calculated subphenotypic LRs for variant pathogenicity for various clinical, histologic, and molecular features. RESULTS: We estimated the pan-gene VRMV-LR to be 76.2 (54.8-105.9) for SDHB and 14.8 (8.7-25.0) for SDHD. Clustering analysis revealed an SDHB enriched region (ɑɑ 177-260, P = .001) for which the DS-VRMV-LR was 127.2 (64.9-249.4) and an SDHD enriched region (ɑɑ 70-114, P = .000003) for which the DS-VRMV-LR was 33.9 (14.8-77.8). Subphenotypic LRs exceeded 6 for invasive disease (SDHB), head-and-neck disease (SDHD), multiple tumors (SDHD), family history of PCC/PGL, loss of SDHB staining on immunohistochemistry, and succinate-to-fumarate ratio >97 (SDHB, SDHD). CONCLUSION: Using methodology generalizable to other gene-phenotype dyads, the LRs relating to rarity and phenotypic specificity for a single observation in PCC/PGL of a SDHB/SDHD VRMV can afford substantial evidence toward pathogenicity.

Case-case analysis addressing ascertainment bias for multigene panel testing implicates BRCA1 and PALB2 in endometrial cancer.

Hereditary endometrial cancer (EC) is most commonly attributed to pathogenic variants in mismatch repair genes. Evidence supports the existence of additional genetic risk factors in the context of multiple cancer diagnoses and/or family history of EC. EC patients (n = 5292) referred for diagnostic multigene cancer panel testing were annotated for presence of a pathogenic gene variant; personal history of prior, concurrent, or subsequent cancer of another type; reported family history of Lynch syndrome or EC. The Pearson χ2 test was used to assess differences in gene variant prevalence between case sub-groups defined by personal and/or family history of cancer/s, using cases with no family history of Lynch/EC as reference. Another cancer diagnosis was reported for 55% of EC cases. EC cases with a prior and reported family history of Lynch cancer were enriched for variants in MLH1 (p = 3.5 × 10-7 ), MSH2 (p = 3.1 × 10-7 ), and PMS2 (p = .02). Consistent with expectations for a breast cancer gene also predisposing to EC, the variant frequency was increased in EC patients with prior BC and family history of EC for BRCA1 (p = 1.7 × 10-5 ) and PALB2 (p = .0002). Strategic case-case analyses to address cohort ascertainment bias have provided a rationale to direct future studies of candidate hereditary EC genes.

An updated quantitative model to classify missense variants in the TP53 gene: A novel multifactorial strategy.

Multigene panel testing has led to an increase in the number of variants of uncertain significance identified in the TP53 gene, associated with Li-Fraumeni syndrome. We previously developed a quantitative model for predicting the pathogenicity of P53 missense variants based on the combination of calibrated bioinformatic information and somatic to germline ratio. Here, we extended this quantitative model for the classification of P53 predicted missense variants by adding new pieces of evidence (personal and family history parameters, loss-of-function results, population allele frequency, healthy individual status by age 60, and breast tumor pathology). We also annotated which missense variants might have an effect on splicing based on bioinformatic predictions. This updated model plus annotation led to the classification of 805 variants into a clinically relevant class, which correlated well with existing ClinVar classifications, and resolved a large number of conflicting and uncertain classifications. We propose this model as a reliable approach to TP53 germline variant classification and emphasize its use in contributing to optimize TP53-specific ACMG/AMP guidelines.

Differences in patient ascertainment affect the use of gene-specified ACMG/AMP phenotype-related variant classification criteria: Evidence for TP53.

The American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant classification are widely used for clinical interpretation of gene test results. These guidelines may be specified to genes/syndromes of interest to improve their utility in the clinical setting. As part of these specifications, phenotype-related criteria can be detailed and weighted depending on the personal history of disease for a given variant carrier. We investigated how ascertainment can affect the significance and/or weight of patient phenotype as a predictor of germline-variant pathogenicity, using the Li-Fraumeni Syndrome gene TP53 as an example. Likelihood ratios in favor of variant pathogenicity were determined for a report of the personal history of several TP53-related cancers, using data from 2,656 probands undergoing single-gene testing (SGT) and 15,483 undergoing multi-gene panel testing (MGPT). Overall, TP53-associated cancers were more predictive of pathogenicity, and demonstrated greater evidence weight, in the MGPT versus SGT dataset. This observation is almost certainly explained by differences in proband ascertainment for the two streams of testing, and these findings have implications for germline-variant classification using ACMG/AMP guidelines.

Mutation prevalence tables for hereditary cancer derived from multigene panel testing.

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.

Suggested application of HER2+ breast tumor phenotype for germline TP53 variant classification within ACMG/AMP guidelines.

Early onset breast cancer is the most common malignancy in women with Li-Fraumeni syndrome, caused by germline TP53 pathogenic variants. It has repeatedly been suggested that breast tumors from TP53 carriers are more likely to be HER2+ than those of noncarriers, but this information has not been incorporated into variant interpretation models for TP53. Breast tumor pathology is already being used quantitatively for assessing pathogenicity of germline variants in other genes, and it has been suggested that this type of evidence can be incorporated into current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification. Here, by reviewing published data and using internal datasets separated by different age groups, we investigated if breast tumor HER2+ status has utility as a predictor of TP53 germline variant pathogenicity, considering age at diagnosis. Overall, our results showed that the identification of HER2+ breast tumors diagnosed before the age of 40 can be conservatively incorporated into the current TP53-specific ACMG/AMP PP4 criterion, following a point system detailed in this manuscript. Further larger studies will be needed to reassess the value of HER2+ breast tumors diagnosed at a later age.

A clinical guide to hereditary cancer panel testing: evaluation of gene-specific cancer associations and sensitivity of genetic testing criteria in a cohort of 165,000 high-risk patients.

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.

Women with breast and uterine cancer are more likely to harbor germline mutations than women with breast or uterine cancer alone: A case for expanded gene testing.

OBJECTIVE: We explored the germline mutation spectrum and prevalence among 1650 women with breast and uterine cancer (BUC) who underwent multi-gene hereditary cancer panel testing at a single commercial laboratory. METHODS: The combined frequency of mutations in 23 BC and/or UC genes was compared between BUC cases and control groups with (1) no personal cancer history; (2) BC only; and (3) UC only using logistic regression. RESULTS: Fourteen percent (n = 231) of BUC cases tested positive for mutations in BC and/or UC genes and were significantly more likely to test positive than individuals with BC only (P < 0.001), UC only (P < 0.01), or unaffected controls (P < 0.001). Analysis of gene-specific mutation frequencies revealed that MSH6, CHEK2, BRCA1, BRCA2, ATM, PMS2, PALB2 and MSH2 were most frequently mutated among BUC cases. Compared to BC only, BRCA1, MLH1, MSH2, MSH6, PMS2 and PTEN mutations were more frequent among BUC; however, only ATM mutations were more frequent among BUC compared to UC only. All of the more commonly mutated genes have published management guidelines to guide clinical care. Of patients with a single mutation in a gene with established testing criteria (n = 152), only 81.6% met their respective criteria, and 65.8% met criteria for multiple syndromes. CONCLUSIONS: Women with BUC are more likely to carry hereditary cancer gene mutations than women with breast or uterine cancer alone, potentially warranting expanded genetic testing for these women. Most mutations found via multi-gene panel testing in women with BUC have accompanying published management guidelines and significant implications for clinical care.

A genotype-first approach identifies high incidence of NF1 pathogenic variants with distinct disease associations.

Loss of function variants in the NF1 gene cause neurofibromatosis type 1 (NF1), a genetic disorder characterized by complete penetrance, prevalence of 1 in 3,000, characteristic physical exam findings, and a substantially increased risk for malignancy. However, our understanding of the disorder is entirely based on patients ascertained through phenotype-first approaches. Leveraging a genotype-first approach in two large patient cohorts, we demonstrate unexpectedly high prevalence (1 in 450-750) of NF1 pathogenic variants. Half were identified in individuals lacking clinical features of NF1, with many appearing to have post-zygotic mosaicism for the identified variant. Incidentally discovered variants were not associated with classic NF1 features but were associated with an increased incidence of malignancy compared to a control population. Our findings suggest that NF1 pathogenic variants are substantially more common than previously thought, often characterized by somatic mosaicism and reduced penetrance, and are important contributors to cancer risk in the general population.

Functional and Clinical Characterization of Variants of Uncertain Significance Identifies a Hotspot for Inactivating Missense Variants in RAD51C.

Pathogenic protein-truncating variants of RAD51C, which plays an integral role in promoting DNA damage repair, increase the risk of breast and ovarian cancer. A large number of RAD51C missense variants of uncertain significance (VUS) have been identified, but the effects of the majority of these variants on RAD51C function and cancer predisposition have not been established. Here, analysis of 173 missense variants by a homology-directed repair (HDR) assay in reconstituted RAD51C-/- cells identified 30 nonfunctional (deleterious) variants, including 18 in a hotspot within the ATP-binding region. The deleterious variants conferred sensitivity to cisplatin and olaparib and disrupted formation of RAD51C/XRCC3 and RAD51B/RAD51C/RAD51D/XRCC2 complexes. Computational analysis indicated the deleterious variant effects were consistent with structural effects on ATP-binding to RAD51C. A subset of the variants displayed similar effects on RAD51C activity in reconstituted human RAD51C-depleted cancer cells. Case-control association studies of deleterious variants in women with breast and ovarian cancer and noncancer controls showed associations with moderate breast cancer risk [OR, 3.92; 95% confidence interval (95% CI), 2.18-7.59] and high ovarian cancer risk (OR, 14.8; 95% CI, 7.71-30.36), similar to protein-truncating variants. This functional data supports the clinical classification of inactivating RAD51C missense variants as pathogenic or likely pathogenic, which may improve the clinical management of variant carriers. SIGNIFICANCE: Functional analysis of the impact of a large number of missense variants on RAD51C function provides insight into RAD51C activity and information for classification of the cancer relevance of RAD51C variants.

Universal Germline Panel Testing for Individuals With Pheochromocytoma and Paraganglioma Produces High Diagnostic Yield.

BACKGROUND: Practice guidelines to identify individuals with hereditary pheochromocytomas and paragangliomas (PPGLs) advocate for sequential gene testing strategy guided by specific clinical features and predate the routine use of multigene panel testing (MGPT). OBJECTIVE: To describe results of MGPT for hereditary PPGL in a clinically and ancestrally diverse cohort. SETTING: Commercial laboratory based in the United States. METHODS: Clinical data and test results were retrospectively reviewed in 1727 individuals who had targeted MGPT from August 2013 through December 2019 because of a suspicion of hereditary PPGL. RESULTS: Overall, 27.5% of individuals had a pathogenic or likely pathogenic variant (PV), 9.0% had a variant of uncertain significance, and 63.1% had a negative result. Most PVs were identified in SDHB (40.4%), followed by SDHD (21.1%), SDHA (10.1%), VHL (7.8%), SDHC (6.7%), RET (3.7%), and MAX (3.6%). PVs in FH, MEN1, NF1, SDHAF2, and TMEM127 collectively accounted for 6.5% of PVs. Clinical predictors of a PV included extra-adrenal location, early age of onset, multiple tumors, and positive family history of PPGL. Individuals with extra-adrenal PGL and a positive family history were the most likely to have a PV (85.9%). Restricting genetic testing to SDHB/C/D misses one-third (32.8%) of individuals with PVs. CONCLUSION: Our data demonstrate a high diagnostic yield in individuals with and without established risk factors, a low inconclusive result rate, and a substantial contribution to diagnostic yield from rare genes. These findings support universal testing of all individuals with PPGL and the use of concurrent MGPT as the ideal platform.

Development and Validation of the PREMMplus Model for Multigene Hereditary Cancer Risk Assessment.

PURPOSE: With the availability of multigene panel testing (MGPT) for hereditary cancer risk assessment, clinicians need to assess the likelihood of pathogenic germline variants (PGVs) across numerous genes in parallel. This study's aim was to develop and validate a clinical prediction model (PREMMplus) for MGPT risk assessment. MATERIALS AND METHODS: PREMMplus was developed in a single-institution cohort of 7,280 individuals who had undergone MGPT. Logistic regression models with Least Absolute Shrinkage and Selection Operator regularization were used to examine candidate predictors (age, sex, ethnicity, and personal/family history of 18 cancers/neoplasms) to estimate one's likelihood of carrying PGVs in 19 genes (broadly categorized by phenotypic overlap and/or relative penetrance: 11 category A [APC, BRCA1/2, CDH1, EPCAM, MLH1, MSH2, MSH6, biallelic MUTYH, PMS2, and TP53] and eight category B genes [ATM, BRIP1, CDKN2A, CHEK2, PALB2, PTEN, RAD51C, and RAD51D]). Model performance was validated in nonoverlapping data sets of 8,691 and 14,849 individuals with prior MGPT ascertained from clinic- and laboratory-based settings, respectively. RESULTS: PREMMplus (score ≥ 2.5%) had 93.9%, 91.7%, and 89.3% sensitivity and 98.3%, 97.5%, and 97.8% negative-predictive value (NPV) for identifying category A gene PGV carriers in the development and validation cohorts, respectively. PREMMplus assessment (score ≥ 2.5%) had 89.9%, 85.6%, and 84.2% sensitivity and 95.0%, 93.5%, and 93.5% NPV, respectively, for identifying category A/B gene PGV carriers. Decision curve analyses support MGPT for individuals predicted to have ≥ 2.5% probability of a PGV. CONCLUSION: PREMMplus accurately identifies individuals with PGVs in a diverse spectrum of cancer susceptibility genes with high sensitivity/NPV. Individuals with PREMMplus scores ≥ 2.5% should be considered for MGPT.

An integrative model for the comprehensive classification of BRCA1 and BRCA2 variants of uncertain clinical significance.

Loss-of-function variants in the BRCA1 and BRCA2 susceptibility genes predispose carriers to breast and/or ovarian cancer. The use of germline testing panels containing these genes has grown dramatically, but the interpretation of the results has been complicated by the identification of many sequence variants of undefined cancer relevance, termed "Variants of Uncertain Significance (VUS)." We have developed functional assays and a statistical model called VarCall for classifying BRCA1 and BRCA2 VUS. Here we describe a multifactorial extension of VarCall, called VarCall XT, that allows for co-analysis of multiple forms of genetic evidence. We evaluated the accuracy of models defined by the combinations of functional, in silico protein predictors, and family data for VUS classification. VarCall XT classified variants of known pathogenicity status with high sensitivity and specificity, with the functional assays contributing the greatest predictive power. This approach could be used to identify more patients that would benefit from personalized cancer risk assessment and management.