External validation of a multi-biomarker-based score for predicting risk of cardiovascular disease in patients with rheumatoid arthritis.

BACKGROUND: A multi-biomarker disease activity (MBDA)-based cardiovascular disease (CVD) risk score was developed and internally validated in a Medicare cohort to predict 3-year risk for myocardial infarction (MI), stroke or CVD death in patients with rheumatoid arthritis (RA). It combines the MBDA score, leptin, MMP-3, TNF-R1, age and four clinical variables. We are now externally validating it in a younger RA cohort. METHODS: Claims data from a private aggregator were linked to MBDA test data to create a cohort of RA patients ≥18 years old. A univariable Cox proportional hazards regression model was fit using the MBDA-based CVD risk score as sole predictor of time-to-a-CVD event (hospitalized MI or stroke). Hazard ratio (HR) estimate was determined for all patients and for clinically relevant subgroups. A multivariable Cox model evaluated whether the MBDA-based CVD risk score adds predictive information to clinical data. RESULTS: 49,028 RA patients (340 CVD events) were studied. Mean age was 52.3 years; 18.3% were male. HR for predicting 3-year risk of a CVD event by the MBDA-based CVD risk score in the full cohort was 3.99 (95% CI: 3.51-4.49, p = 5.0×10-95). HR were also significant for subgroups based on age, comorbidities, disease activity, and drug use. In a multivariable model, the MBDA-based CVD risk score added significant information to hypertension, diabetes, tobacco use, history of CVD, age, sex and CRP (HR = 2.27, p = 1.7×10-7). CONCLUSION: The MBDA-based CVD risk score has been externally validated in an RA cohort that is younger than and independent of the Medicare cohort that was used for development and internal validation.

Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients With Newly Diagnosed Prostate Cancer.

PURPOSE: Guidelines recommend adding androgen-deprivation therapy (ADT) to radiation therapy (RT) in certain patients with localized prostate cancer. Individualized genomic testing may improve the prognostic accuracy of risk assessments. Herein, we describe a mathematical model of the benefit of adding ADT to RT as a function of the personalized clinical cell-cycle risk (CCR) score to inform 10-year metastasis risk. METHODS: A model of absolute risk reduction (ARR) was built using a retrospective cohort of men tested with Prolaris who received RT alone (N = 467). The relative benefit of ADT added to RT to reduce distant metastasis was estimated at 41% on the basis of a meta-analysis of randomized trials. The ARR and number needed to treat (NNT) were computationally derived in patients clinically tested with Prolaris between January 1, 2020, and October 31, 2022 (N = 56,485). Risks were predicted using a cause-specific Cox proportional hazards model with CCR score predicting time to metastasis. A CCR score of 2.112 represents the validated multimodal treatment (MMT) threshold. RESULTS: The ARR from ADT increased from almost zero at low CCR scores to 17.1% at CCR = 3.690 with the corresponding NNT = 6, indicating that adding ADT to RT would prevent metastasis within 10 years for one of every six treated individuals. In the clinical cohort, the average ARR was 0.86% in individuals under the MMT threshold (NNT = 116). The average ARR was 8.19% in individuals above the MMT threshold (NNT = 12). Broad ranges of ADT benefit were observed within National Comprehensive Cancer Network risk categories. CONCLUSION: The precise and personalized risk estimate of metastasis provided by the CCR score can help inform patients and physicians when considering treatment intensification.

Identifying homologous recombination deficiency in breast cancer: genomic instability score distributions differ among breast cancer subtypes.

PURPOSE: A 3-biomarker homologous recombination deficiency (HRD) score is a key component of a currently FDA-approved companion diagnostic assay to identify HRD in patients with ovarian cancer using a threshold score of ≥ 42, though recent studies have explored the utility of a lower threshold (GIS ≥ 33). The present study evaluated whether the ovarian cancer thresholds may also be appropriate for major breast cancer subtypes by comparing the genomic instability score (GIS) distributions of BRCA1/2-deficient estrogen receptor-positive breast cancer (ER + BC) and triple-negative breast cancer (TNBC) to the GIS distribution of BRCA1/2-deficient ovarian cancer. METHODS: Ovarian cancer and breast cancer (ER + BC and TNBC) tumors from ten study cohorts were sequenced to identify pathogenic BRCA1/2 mutations, and GIS was calculated using a previously described algorithm. Pathologic complete response (pCR) to platinum therapy was evaluated in a subset of TNBC samples. For TNBC, a threshold was set and threshold validity was assessed relative to clinical outcomes. RESULTS: A total of 560 ovarian cancer, 805 ER + BC, and 443 TNBC tumors were included. Compared to ovarian cancer, the GIS distribution of BRCA1/2-deficient samples was shifted lower for ER + BC (p = 0.015), but not TNBC (p = 0.35). In the subset of TNBC samples, univariable logistic regression models revealed that GIS status using thresholds of ≥ 42 and ≥ 33 were significant predictors of response to platinum therapy. CONCLUSIONS: This study demonstrated that the GIS thresholds used for ovarian cancer may also be appropriate for TNBC, but not ER + BC. GIS thresholds in TNBC were validated using clinical response data to platinum therapy.

The association between age at breast cancer diagnosis and prevalence of pathogenic variants.

PURPOSE: Young age at breast cancer (BC) diagnosis and family history of BC are strongly associated with high prevalence of pathogenic variants (PVs) in BRCA1 and BRCA2 genes. There is limited evidence for such associations with moderate/high penetrance BC-risk genes such as ATM, CHEK2, and PALB2. METHODS: We analyzed multi-gene panel testing results (09/2013-12/2019) for women unaffected by any cancer (N = 371,594) and those affected with BC (N = 130,151) ascertained for suspicion of hereditary breast and/or ovarian cancer. Multivariable logistic regression was used to test association between PV status and age at BC diagnosis (≤ 45 vs. > 45 years) or family history of BC after controlling for personal/family non-BC histories and self-reported ancestry. RESULTS: An association between young age (≤ 45 years) at diagnosis and presence of PVs was strong for BRCA1 (OR 3.95, 95% CI 3.64-4.29) and moderate for BRCA2 (OR 1.98, 95% CI 1.84-2.14). Modest associations were observed between PVs and young age at diagnosis for ATM (OR 1.22, 95% CI 1.08-1.37) and CHEK2 (OR 1.34, 95% CI 1.21-1.47) genes, but not for PALB2 (OR 1.12, 95% CI 0.98-1.27). For women with BC, earliest age of familial BC diagnosis followed a similar pattern. For unaffected women, earliest age of family cancer diagnosis was significantly associated with PV status only for BRCA1 (OR 2.34, 95% CI 2.13-2.56) and BRCA2 (OR 1.25, 95% CI 1.16-1.35). CONCLUSIONS: Young age at BC diagnosis is not a strong risk factor for carrying PVs in BC-associated genes ATM, CHEK2, or PALB2.

Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.

PURPOSE: Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS: Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS: In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; P = 8.6 × 10-308) and within each major ancestry. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women. CONCLUSION: The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.

Clinical Validation of EndoPredict in Pre-Menopausal Women with ER-Positive, HER2-Negative Primary Breast Cancer.

PURPOSE: The EndoPredict prognostic assay is validated to predict distant recurrence and response to chemotherapy primarily in post-menopausal women with estrogen receptor-positive (ER+), HER2- breast cancer. This study evaluated the performance of EndoPredict in pre-menopausal women. EXPERIMENTAL DESIGN: Tumor samples from 385 pre-menopausal women with ER+, HER2- primary breast cancer (pT1-3, pN0-1) who did not receive chemotherapy in addition to endocrine therapy were tested with EndoPredict to produce a 12-gene EP molecular score and an integrated EPclin score that includes pathologic tumor size and nodal status. Associations of molecular and EPclin scores with 10-year distant recurrence-free survival (DRFS) were evaluated by Cox proportional hazards models and Kaplan-Meier analysis. RESULTS: After a median follow-up of 9.7 years, both the EP molecular score and the molecular-clinicopathologic EPclin score were associated with increased risk of distant recurrence [HR, 1.33; 95% confidence interval (CI), 1.18-1.50; P = 7.2 × 10-6; HR, 3.58; 95% CI, 2.26-5.66; P = 9.8 × 10-8, respectively]. Both scores remained significant after adjusting for clinical factors in multivariate analysis. Patients with low-risk EPclin scores (64.7%) had significantly improved DRFS compared with high-risk patients (HR, 4.61; 95% CI, 1.40-15.17; P = 4.2 × 10-3). At 10 years, patients with low-risk and high-risk EPclin scores had a DRFS of 97% (95% CI, 93%-99%) and 76% (95% CI, 67%-82%), respectively. CONCLUSIONS: The EPclin score is strongly associated with DRFS in pre-menopausal women who received adjuvant endocrine therapy alone. On the basis of these data, pre-menopausal women with EPclin low-risk breast cancer may be treated with endocrine therapy only and safely forgo adjuvant chemotherapy.

Performance of the IBIS/Tyrer-Cuzick model of breast cancer risk by race and ethnicity in the Women's Health Initiative.

BACKGROUND: The IBIS/Tyrer-Cuzick model is used clinically to guide breast cancer screening and prevention, but was developed primarily in non-Hispanic White women. Little is known about its long-term performance in a racially/ethnically diverse population. METHODS: The Women's Health Initiative study enrolled postmenopausal women from 1993-1998. Women were included who were aged <80 years at enrollment with no prior breast cancer or mastectomy and with data required for IBIS/Tyrer-Cuzick calculation (weight; height; ages at menarche, first birth, and menopause; menopausal hormone therapy use; and family history of breast or ovarian cancer). Calibration was assessed by the ratio of observed breast cancer cases to the number expected by the IBIS/Tyrer-Cuzick model (O/E; calculated as the sum of cumulative hazards). Differential discrimination was tested for by self-reported race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian or Pacific Islander, and American Indian or Alaskan Native) using Cox regression. Exploratory analyses, including simulation of a protective single-nucleotide polymorphism (SNP), rs140068132 at 6q25, were performed. RESULTS: During follow-up (median 18.9 years, maximum 23.4 years), 6783 breast cancer cases occurred among 90,967 women. IBIS/Tyrer-Cuzick was well calibrated overall (O/E ratio = 0.95; 95% CI, 0.93-0.97) and in most racial/ethnic groups, but overestimated risk for Hispanic women (O/E ratio = 0.75; 95% CI, 0.62-0.90). Discrimination did not differ by race/ethnicity. Exploratory simulation of the protective SNP suggested improved IBIS/Tyrer-Cuzick calibration for Hispanic women (O/E ratio = 0.80; 95% CI, 0.66-0.96). CONCLUSIONS: The IBIS/Tyrer-Cuzick model is well calibrated for several racial/ethnic groups over 2 decades of follow-up. Studies that incorporate genetic and other risk factors, particularly among Hispanic women, are essential to improve breast cancer-risk prediction.

Comprehensive Breast Cancer Risk Assessment for CHEK2 and ATM Pathogenic Variant Carriers Incorporating a Polygenic Risk Score and the Tyrer-Cuzick Model.

PURPOSE: Breast cancer risks for CHEK2 and ATM pathogenic variant (PV) carriers are modified by an 86-single nucleotide polymorphism polygenic risk score (PRS) and individual clinical factors. Here, we describe comprehensive risk prediction models for women of European ancestry combining PV status, PRS, and individual clinical variables. MATERIALS AND METHODS: This study included deidentified clinical records from 358,095 women of European ancestry who received testing with a multigene panel (September 2013 to November 2019). Model development included CHEK2 PV carriers (n = 4,286), ATM PV carriers (n = 2,666), and women negative for other breast cancer risk gene PVs (n = 351,143). Odds ratios (ORs) were calculated using multivariable logistic regression with adjustment for familial cancer history. Risk estimates incorporating PV status, PRS, and Tyrer-Cuzick v7.02 were calculated using a Fixed-Stratified method that accounts for correlations between risk factors. Stratification of PV carriers into risk categories on the basis of remaining lifetime risk (RLR) was assessed in independent cohorts of PV carriers. RESULTS: ORs for association of PV status with breast cancer were 2.01 (95% CI, 1.88 to 2.16) and 1.83 (95% CI, 1.68 to 2.00) for CHEK2 and ATM PV carriers, respectively. ORs for PRS per one standard deviation were 1.51 (95% CI, 1.37 to 1.66) and 1.45 (95% CI, 1.30 to 1.64) in CHEK2 and ATM PV carriers, respectively. Using the combined model (PRS plus Tyrer-Cuzick plus PV status), RLR was low (≤ 20%) for 24.2% of CHEK2 PV carriers, medium (20%-50%) for 63.8%, and high (> 50%) for 12.0%. Among ATM PV carriers, RLR was low for 31.5% of patients, medium for 58.5%, and high for 9.7%. CONCLUSION: In CHEK2 and ATM PV carriers, risk assessment including PRS, Tyrer-Cuzick, and PV status has the potential for more precise direction of screening and prevention strategies.

Integrating Clinical and Polygenic Factors to Predict Breast Cancer Risk in Women Undergoing Genetic Testing.

PURPOSE: Screening and prevention decisions for women at increased risk of developing breast cancer depend on genetic and clinical factors to estimate risk and select appropriate interventions. Integration of polygenic risk into clinical breast cancer risk estimators can improve discrimination. However, correlated genetic effects must be incorporated carefully to avoid overestimation of risk. MATERIALS AND METHODS: A novel Fixed-Stratified method was developed that accounts for confounding when adding a new factor to an established risk model. A combined risk score (CRS) of an 86-single-nucleotide polymorphism polygenic risk score and the Tyrer-Cuzick v7.02 clinical risk estimator was generated with attenuation for confounding by family history. Calibration and discriminatory accuracy of the CRS were evaluated in two independent validation cohorts of women of European ancestry (N = 1,615 and N = 518). Discrimination for remaining lifetime risk was examined by age-adjusted logistic regression. Risk stratification with a 20% risk threshold was compared between CRS and Tyrer-Cuzick in an independent clinical cohort (N = 32,576). RESULTS: Simulation studies confirmed that the Fixed-Stratified method produced accurate risk estimation across patients with different family history. In both validation studies, CRS and Tyrer-Cuzick were significantly associated with breast cancer. In an analysis with both CRS and Tyrer-Cuzick as predictors of breast cancer, CRS added significant discrimination independent of that captured by Tyrer-Cuzick (P < 10-11 in validation 1; P < 10-7 in validation 2). In an independent cohort, 18% of women shifted breast cancer risk categories from their Tyrer-Cuzick-based risk compared with risk estimates by CRS. CONCLUSION: Integrating clinical and polygenic factors into a risk model offers more effective risk stratification and supports a personalized genomic approach to breast cancer screening and prevention.

Clinical validation of combinatorial pharmacogenomic testing and single-gene guidelines in predicting psychotropic medication blood levels and clinical outcomes in patients with depression.

We evaluated the clinical validity of a combinatorial pharmacogenomic test and single-gene Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines against patient outcomes and medication blood levels to assess their ability to inform prescribing in major depressive disorder (MDD). This is a secondary analysis of the Genomics Used to Improve DEpression Decisions (GUIDED) randomized-controlled trial, which included patients with a diagnosis of MDD, and ≥1 prior medication failure. The ability to predict increased/decreased medication metabolism was validated against blood levels at screening (adjusted for age, sex, smoking status). The ability of predicted gene-drug interactions (pharmacogenomic test) or therapeutic recommendations (single-gene guidelines) to predict patient outcomes was validated against week 8 outcomes (17-item Hamilton Depression Rating Scale; symptom improvement, response, remission). Analyses were performed for patients taking any eligible medication (outcomes N=1,022, blood levels N=1,034) and the subset taking medications with single-gene guidelines (outcomes N=584, blood levels N=372). The combinatorial pharmacogenomic test was the only significant predictor of patient outcomes. Both the combinatorial pharmacogenomic test and single-gene guidelines were significant predictors of blood levels for all medications when evaluated separately; however, only the combinatorial pharmacogenomic test remained significant when both were included in the multivariate model. There were no substantial differences when all medications were evaluated or for the subset with single-gene guidelines. Overall, this evaluation of clinical validity demonstrates that the combinatorial pharmacogenomic test was a superior predictor of patient outcomes and medication blood levels when compared with guidelines based on individual genes.

Derivation and internal validation of a multi-biomarker-based cardiovascular disease risk prediction score for rheumatoid arthritis patients.

BACKGROUND: Rheumatoid arthritis (RA) patients have increased risk for cardiovascular disease (CVD). Accurate CVD risk prediction could improve care for RA patients. Our goal is to develop and validate a biomarker-based model for predicting CVD risk in RA patients. METHODS: Medicare claims data were linked to multi-biomarker disease activity (MBDA) test results to create an RA patient cohort with age ≥ 40 years that was split 2:1 for training and internal validation. Clinical and RA-related variables, MBDA score, and its 12 biomarkers were evaluated as predictors of a composite CVD outcome: myocardial infarction (MI), stroke, or fatal CVD within 3 years. Model building used Cox proportional hazard regression with backward elimination. The final MBDA-based CVD risk score was internally validated and compared to four clinical CVD risk prediction models. RESULTS: 30,751 RA patients (904 CVD events) were analyzed. Covariates in the final MBDA-based CVD risk score were age, diabetes, hypertension, tobacco use, history of CVD (excluding MI/stroke), MBDA score, leptin, MMP-3 and TNF-R1. In internal validation, the MBDA-based CVD risk score was a strong predictor of 3-year risk for a CVD event, with hazard ratio (95% CI) of 2.89 (2.46-3.41). The predicted 3-year CVD risk was low for 9.4% of patients, borderline for 10.2%, intermediate for 52.2%, and high for 28.2%. Model fit was good, with mean predicted versus observed 3-year CVD risks of 4.5% versus 4.4%. The MBDA-based CVD risk score significantly improved risk discrimination by the likelihood ratio test, compared to four clinical models. The risk score also improved prediction, reclassifying 42% of patients versus the simplest clinical model (age + sex), with a net reclassification index (NRI) (95% CI) of 0.19 (0.10-0.27); and 28% of patients versus the most comprehensive clinical model (age + sex + diabetes + hypertension + tobacco use + history of CVD + CRP), with an NRI of 0.07 (0.001-0.13). C-index was 0.715 versus 0.661 to 0.696 for the four clinical models. CONCLUSION: A prognostic score has been developed to predict 3-year CVD risk for RA patients by using clinical data, three serum biomarkers and the MBDA score. In internal validation, it had good accuracy and outperformed clinical models with and without CRP. The MBDA-based CVD risk prediction score may improve RA patient care by offering a risk stratification tool that incorporates the effect of RA inflammation.

Development and Validation of a Clinical Polygenic Risk Score to Predict Breast Cancer Risk.

PURPOSE: Women with a family history of breast cancer are frequently referred for hereditary cancer genetic testing, yet < 10% are found to have pathogenic variants in known breast cancer susceptibility genes. Large-scale genotyping studies have identified common variants (primarily single-nucleotide polymorphisms [SNPs]) with individually modest breast cancer risk that, in aggregate, account for considerable breast cancer susceptibility. Here, we describe the development and empirical validation of an SNP-based polygenic breast cancer risk score. METHODS: A panel of 94 SNPs was examined for association with breast cancer in women of European ancestry undergoing hereditary cancer genetic testing and negative for pathogenic variants in breast cancer susceptibility genes. Candidate polygenic risk scores (PRSs) as predictors of personal breast cancer history were developed through multivariable logistic regression models adjusted for age, cancer history, and ancestry. An optimized PRS was validated in 2 independent cohorts (n = 13,174; n = 141,160). RESULTS: Within the training cohort (n = 24,259), 4,291 women (18%) had a personal history of breast cancer and 8,725 women (36%) reported breast cancer in a first-degree relative. The optimized PRS included 86 variants and was highly predictive of breast cancer status in both validation cohorts (P = 6.4 × 10-66; P < 10-325). The odds ratio (OR) per unit standard deviation was consistent between validations (OR, 1.45 [95% CI, 1.39 to 1.52]; OR 1.47 [95% CI, 1.45 to 1.49]). In a direct comparison, the 86-SNP PRS outperformed a previously described PRS of 77 SNPs. CONCLUSION: The validation and implementation of a PRS for women without pathogenic variants in known breast cancer susceptibility genes offers potential for risk stratification to guide surveillance recommendations.

Association of a Polygenic Risk Score With Breast Cancer Among Women Carriers of High- and Moderate-Risk Breast Cancer Genes.

Importance: To date, few studies have examined the extent to which polygenic single-nucleotide variation (SNV) (formerly single-nucleotide polymorphism) scores modify risk for carriers of pathogenic variants (PVs) in breast cancer susceptibility genes. In previous reports, polygenic risk modification was reduced for BRCA1 and BRCA2 PV carriers compared with noncarriers, but limited information is available for carriers of CHEK2, ATM, or PALB2 PVs. Objective: To examine an 86-SNV polygenic risk score (PRS) for BRCA1, BRCA2, CHEK2, ATM, and PALB2 PV carriers. Design, Setting, and Participants: A retrospective case-control study using data on 150 962 women tested with a multigene hereditary cancer panel between July 19, 2016, and January 11, 2019, was conducted in a commercial testing laboratory. Participants included women of European ancestry between the ages of 18 and 84 years. Main Outcomes and Measures: Multivariable logistic regression was used to examine the association of the 86-SNV score with invasive breast cancer after adjusting for age, ancestry, and personal and/or family cancer history. Effect sizes, expressed as standardized odds ratios (ORs) with 95% CIs, were assessed for carriers of PVs in each gene as well as for noncarriers. Results: The median age at hereditary cancer testing of the population was 48 years (range, 18-84 years); there were 141 160 noncarriers in addition to carriers of BRCA1 (n = 2249), BRCA2 (n = 2638), CHEK2 (n = 2564), ATM (n = 1445), and PALB2 (n = 906) PVs included in the analysis. The 86-SNV score was associated with breast cancer risk in each of the carrier populations (P < 1 × 10-4). Stratification was more pronounced for noncarriers (OR, 1.47; 95% CI, 1.45-1.49) and CHEK2 PV carriers (OR, 1.49; 95% CI, 1.36-1.64) than for carriers of BRCA1 (OR, 1.20; 95% CI, 1.10-1.32) or BRCA2 (OR, 1.23; 95% CI, 1.12-1.34) PVs. Odds ratios for ATM (OR, 1.37; 95% CI, 1.21-1.55) and PALB2 (OR, 1.34; 95% CI, 1.16-1.55) PV carrier populations were intermediate between those for BRCA1/2 and CHEK2 noncarriers. Conclusions and Relevance: In this study, the 86-SNV score was associated with modified risk for carriers of BRCA1, BRCA2, CHEK2, ATM, and PALB2 PVs. This finding supports previous reports of reduced PRS stratification for BRCA1 and BRCA2 PV carriers compared with noncarriers. Modification of risk in CHEK2 carriers associated with the 86-SNV score appeared to be similar to that observed in women without a PV. Larger studies are needed to provide more refined estimates of polygenic modification of risk for women with PVs in other moderate-penetrance genes.

Evaluation of the 12-Gene Molecular Score and the 21-Gene Recurrence Score as Predictors of Response to Neo-adjuvant Chemotherapy in Estrogen Receptor-Positive, HER2-Negative Breast Cancer.

BACKGROUND: Neo-adjuvant chemotherapy (NaCT) facilitates complete surgical resection in locally advanced breast cancer. Due to its association with improved outcome, complete pathologic response (pCR) to neo-adjuvant treatment has been accepted as a surrogate for long-term outcome in clinical trials of human epidermal growth factor receptor 2 (HER2)-positive, triple-negative, or luminal B breast cancer patients. In contrast, NaCT is effective in only ~ 7-10% of estrogen receptor (ER)-positive, HER2-negative disease. Response biomarkers would enable such patients to be selected for NaCT. METHODS: Two commercially available breast cancer prognostic signatures [12-gene molecular score (MS) and the 21-gene Recurrence Score (RS)] were compared in their ability to predict pCR to NaCT in ER-positive, HER2-negative breast cancer in six public RNA expression microarray data sets. Scores were approximated according to published algorithms and analyzed by logistic regression. RESULTS: Expression data were available for 764 ER-positive, HER2-negative breast cancer samples, including 59 patients with pCR. The two scores were well correlated. Either score was a significant predictor of pCR (12-gene MS p = 9.4 × 10-5; 21-gene RS p = 0.0041). However, in a model containing both scores, the 12-gene MS remained significant (p = 0.0079), while the 21-gene RS did not (p = 0.79). CONCLUSIONS: In this microarray study, two commercial breast cancer prognostic scores were significant predictors of response to NaCT. In direct comparison, the 12-gene MS outperformed the 21-gene RS as a predictive marker for NaCT. Considering pCR as surrogate for improved survival, these results support the ability of both scores to predict chemotherapy sensitivity.

Predicting Expected Absolute Chemotherapy Treatment Benefit in Women With Early-Stage Breast Cancer Using EndoPredict, an Integrated 12-Gene Clinicomolecular Assay.

PURPOSE: Previous studies have shown EndoPredict (EPclin), a test that integrates 12-gene expression data with nodal status and tumor size, to be predictive for risk of distant recurrence in women with estrogen receptor-positive, human epidermal growth factor receptor 2-negative early-stage breast cancer. Here, we modeled expected absolute chemotherapy benefit on the basis of EPclin test results. METHODS: The effect of chemotherapy was modeled using previously validated 10-year risk of distant recurrence as a function of EPclin score for patients treated without chemotherapy. Average relative chemotherapy benefit to reduce breast cancer distant recurrence was evaluated using a published meta-analysis from the Early Breast Cancer Trialists' Collaborative Group. Absolute chemotherapy benefit differences were estimated across a range of interaction strengths between relative chemotherapy benefit and EPclin score. The average absolute benefit was calculated for patients with high and low EPclin scores using the distribution of scores in 2,185 samples tested by Myriad Genetics. RESULTS: The average expected absolute benefit of chemotherapy treatment for patients with a low EPclin score was 1.8% in the absence of interaction and 1.5% for maximal interaction. Conversely, the expected average absolute chemotherapy benefit for patients with a high EPclin score was 5.3% and 7.3% for no interaction and maximal interaction, respectively. CONCLUSION: For women with estrogen receptor-positive, human epidermal growth factor receptor 2-negative early-stage breast cancer, a high EPclin score identified which patients would benefit most from adjuvant chemotherapy in terms of absolute reduction of distant recurrence, regardless of the amount of interaction between EPclin and relative chemotherapy benefit. A high degree of prognostic discrimination for distant recurrence is more important for identifying patients likely to benefit most from chemotherapy than an interaction between EPclin and treatment-relative benefit.

Adjustment of the multi-biomarker disease activity score to account for age, sex and adiposity in patients with rheumatoid arthritis.

OBJECTIVE: To develop and evaluate an adjusted score for the multi-biomarker disease activity (MBDA) test to account for the effects of age, sex and adiposity in patients with RA. METHODS: Two models were developed to adjust MBDA score for age, sex and adiposity, using either serum leptin concentration or BMI as proxies for adiposity. Two cohorts were studied. A cohort of 325 781 RA patients who had undergone commercial MBDA testing and had data for age, sex and serum leptin concentration was used for both models. A cohort of 1411 patients from five studies/registries with BMI data was used only for the BMI-adjusted MBDA score. Univariate and multivariate linear regression analyses evaluated the adjusted MBDA scores and conventional clinical measures as predictors of radiographic progression, assessed in terms of modified total Sharp score (ΔmTSS). RESULTS: Two models were developed, based on findings that MBDA score was higher in females than males and increased with age, leptin concentration and BMI. In pairwise regression analyses, the leptin-adjusted (P = 0.00066) and BMI-adjusted (P = 0.0027) MBDA scores were significant independent predictors of ΔmTSS after adjusting for DAS28-CRP, whereas DAS28-CRP was not, after adjusting for leptin-adjusted (P = 0.74) or BMI-adjusted (P = 0.87) MBDA score. Moreover, the leptin-adjusted MBDA score was a significant predictor of ΔmTSS after adjusting for the BMI-adjusted MBDA score (P = 0.025) or the original MBDA score (0.027), whereas the opposite was not true. CONCLUSION: Leptin-adjusted MBDA score significantly adds information to DAS28-CRP and the original MBDA score in predicting radiographic progression. It may offer improved clinical utility for personalized management of RA.

Candidate biomarkers of PARP inhibitor sensitivity in ovarian cancer beyond the BRCA genes.

BACKGROUND: Olaparib (Lynparza™) is a PARP inhibitor approved for advanced BRCA-mutated (BRCAm) ovarian cancer. PARP inhibitors may benefit patients whose tumours are dysfunctional in DNA repair mechanisms unrelated to BRCA1/2. We report exploratory analyses, including the long-term outcome of candidate biomarkers of sensitivity to olaparib in BRCA wild-type (BRCAwt) tumours. METHODS: Tumour samples from an olaparib maintenance monotherapy trial (Study 19, D0810C00019; NCT00753545) were analysed. Analyses included classification of mutations in genes involved in homologous recombination repair (HRR), BRCA1 promoter methylation status, measurement of BRCA1 protein and Myriad HRD score. RESULTS: Patients with BRCAm tumours gained most benefit from olaparib; a similar treatment benefit was also observed in 21/95 patients whose tumours were BRCAwt but had loss-of-function HRR mutations compared to patients with no detectable HRR mutations (58/95). A higher median Myriad MyChoice® HRD score was observed in BRCAm and BRCAwt tumours with BRCA1 methylation. Patients without BRCAm tumours derived benefit from olaparib treatment vs placebo although to a lesser extent than BRCAm patients. CONCLUSIONS: Ovarian cancer patients with tumours harbouring loss-of-function mutations in HRR genes other than BRCA1/2 may constitute a small, molecularly identifiable and clinically relevant population who derive treatment benefit from olaparib similar to patients with BRCAm.

Carboplatin in BRCA1/2-mutated and triple-negative breast cancer BRCAness subgroups: the TNT Trial.

Germline mutations in BRCA1/2 predispose individuals to breast cancer (termed germline-mutated BRCA1/2 breast cancer, gBRCA-BC) by impairing homologous recombination (HR) and causing genomic instability. HR also repairs DNA lesions caused by platinum agents and PARP inhibitors. Triple-negative breast cancers (TNBCs) harbor subpopulations with BRCA1/2 mutations, hypothesized to be especially platinum-sensitive. Cancers in putative 'BRCAness' subgroups-tumors with BRCA1 methylation; low levels of BRCA1 mRNA (BRCA1 mRNA-low); or mutational signatures for HR deficiency and those with basal phenotypes-may also be sensitive to platinum. We assessed the efficacy of carboplatin and another mechanistically distinct therapy, docetaxel, in a phase 3 trial in subjects with unselected advanced TNBC. A prespecified protocol enabled biomarker-treatment interaction analyses in gBRCA-BC and BRCAness subgroups. The primary endpoint was objective response rate (ORR). In the unselected population (376 subjects; 188 carboplatin, 188 docetaxel), carboplatin was not more active than docetaxel (ORR, 31.4% versus 34.0%, respectively; P = 0.66). In contrast, in subjects with gBRCA-BC, carboplatin had double the ORR of docetaxel (68% versus 33%, respectively; biomarker, treatment interaction P = 0.01). Such benefit was not observed for subjects with BRCA1 methylation, BRCA1 mRNA-low tumors or a high score in a Myriad HRD assay. Significant interaction between treatment and the basal-like subtype was driven by high docetaxel response in the nonbasal subgroup. We conclude that patients with advanced TNBC benefit from characterization of BRCA1/2 mutations, but not BRCA1 methylation or Myriad HRD analyses, to inform choices on platinum-based chemotherapy. Additionally, gene expression analysis of basal-like cancers may also influence treatment selection.

Biomarker Assessment of HR Deficiency, Tumor BRCA1/2 Mutations, and CCNE1 Copy Number in Ovarian Cancer: Associations with Clinical Outcome Following Platinum Monotherapy.

The current study evaluated three biomarkers [homologous recombination deficiency (HRD), tumor BRCA1/2 (tBRCA) mutations, and CCNE1 copy-number variation (CNV)] in ovarian tumors from patients enrolled on the SCOTROC4 clinical trial for associations with outcome following carboplatin monotherapy. Ovarian tumors (n = 250), with high-grade serous (HGSOC) subgroup analysis (n = 179) were classified as HRD positive (HRD score ≥42 or tBRCA mutation) and as CCNE1 amplification positive (CCNE1 CNV score >2.4). Seventy-four (30%) tumors were HRD positive, including 34 (14%) with tBRCA mutations. Forty-seven (19%) were CCNE1 amplification positive, all of which were tBRCA wild-type. HRD and tBRCA, but not CCNE1 amplification, were significantly associated with CA125 complete response in the entire cohort (HRD, P = 0.00015; tBRCA P = 0.0096), and the HGSOC subgroup (HRD, P = 0.0016; tBRCA P = 0.032). HRD and lack of CCNE1 amplification were associated with improved progression-free survival (PFS) and overall survival (OS) in the full cohort and HGSOC subgroup (HRD, P = 0.00021; CCNE1 status P = 0.038). HRD remained significant for OS and PFS after adjusting for clinical factors, while CCNE1 status only remained significant for PFS. Patients with HRD-positive tumors had greater PFS and OS benefit from platinum dose intensification than HRD-negative tumors (P = 0.049 and P = 0.035, respectively). An alternative exploratory HRD score threshold (≥33 or tBRCA mutation) was also significantly associated with both PFS and OS in the HGSOC subset.Implications: HRD, tumor BRCA1/2 mutations, and absence of CCNE1 amplification are associated with improved survival of ovarian cancer patients treated with platinum monotherapy and HRD-positive patients may benefit from platinum dose intensification. Mol Cancer Res; 16(7); 1103-11. ©2018 AACR.

Identification of men with low-risk biopsy-confirmed prostate cancer as candidates for active surveillance.

BACKGROUND: A combined clinical cell-cycle risk (CCR) score that incorporates prognostic molecular and clinical information has been recently developed and validated to improve prostate cancer mortality (PCM) risk stratification over clinical features alone. As clinical features are currently used to select men for active surveillance (AS), we developed and validated a CCR score threshold to improve the identification of men with low-risk disease who are appropriate for AS. METHODS: The score threshold was selected based on the 90th percentile of CCR scores among men who might typically be considered for AS based on NCCN low/favorable-intermediate risk criteria (CCR = 0.8). The threshold was validated using 10-year PCM in an unselected, conservatively managed cohort and in the subset of the same cohort after excluding men with high-risk features. The clinical effect was evaluated in a contemporary clinical cohort. RESULTS: In the unselected validation cohort, men with CCR scores below the threshold had a predicted mean 10-year PCM of 2.7%, and the threshold significantly dichotomized low- and high-risk disease (P = 1.2 × 10-5). After excluding high-risk men from the validation cohort, men with CCR scores below the threshold had a predicted mean 10-year PCM of 2.3%, and the threshold significantly dichotomized low- and high-risk disease (P = 0.020). There were no prostate cancer-specific deaths in men with CCR scores below the threshold in either analysis. The proportion of men in the clinical testing cohort identified as candidates for AS was substantially higher using the threshold (68.8%) compared to clinicopathologic features alone (42.6%), while mean 10-year predicted PCM risks remained essentially identical (1.9% vs. 2.0%, respectively). CONCLUSIONS: The CCR score threshold appropriately dichotomized patients into low- and high-risk groups for 10-year PCM, and may enable more appropriate selection of patients for AS.