Predictive Impact of Tumor Mutational Burden on Real-World Outcomes of First-Line Immune Checkpoint Inhibition in Metastatic Melanoma.

PURPOSE: The choice of threshold and reliability of high tumor mutational burden (TMB) to predict outcomes and guide treatment choice for patients with metastatic melanoma receiving first-line immune checkpoint inhibitor (ICI) therapy in the real world is not well known. METHODS: Using a deidentified nationwide (US-based) melanoma clinicogenomic database, we identified a real-world cohort of patients with metastatic melanoma (N = 497) who received first-line monotherapy anti-PD-1 (n = 240) or dual anti-PD-1 and anti-CTLA-4 ICI (n = 257) and had a tissue-based comprehensive genomic profiling test TMB score. RESULTS: TMB-high (TMB-H; ≥10 mutations per megabase [muts/Mb], n = 352, 71%) was independently predictive of superior real-world progression-free survival and overall survival versus TMB-low (<10 mut/Mb, n = 145, 29%) in both mono ICI (hazard ratio [HR], 0.45 [95% CI, 0.32 to 0.63]; P < .001; HR, 0.61 [95% CI, 0.41 to 0.90]; P = .01, respectively) and dual ICI (HR, 0.67 [95% CI, 0.49 to 0.90]; P = .009; HR, 0.61 [95% CI, 0.42 to 0.88]; P = .007, respectively) patients. Dual ICI offered no significant advantage in BRAFwt patients and unexpectedly demonstrated greatest benefit in the TMB 10-19 mut/Mb group, identifying a TMB-very high (≥20 mut/Mb, n = 247, 50%) BRAFmut patient subgroup for whom mono ICI may be preferable. CONCLUSION: TMB-H predicts superior outcomes on ICI while coassessment of BRAF status and TMB may inform first-line regimen choice.

The effectiveness of mindfulness-based stress reduction (MBSR) on the mental health, HbA1C, and mindfulness of diabetes patients: A systematic review and meta-analysis of randomised controlled trials.

The clinically standardised mindfulness-based stress reduction (MBSR) has been utilised as an intervention for improving mental health among diabetes patients The present study aimed to assess the effectiveness of mindfulness-based stress reduction (MBSR) on the mental health, haemoglobin A1c (HbA1C), and mindfulness of diabetes patients. A systematic review and meta-analysis approach was employed to review randomised controlled trials published in the English language between the inception of eight databases to July 2022. Eleven articles from 10 studies, with a combined sample size of 718 participants, were included in the systematic review, and nine studies were included in the meta-analysis. In the meta-analysis, outcomes at post-intervention and follow-up were compared between the MBSR intervention and control groups with an adjustment of the baseline values. The results showed that MBSR demonstrated effects at post-intervention and follow-up (in a period between one to 12 months with a mean length of 4.3 months) in reducing anxiety and depressive symptoms, and enhancing mindfulness, with large effect sizes. However, the effect of MBSR on reducing stress was observed at follow-up, but not at post-intervention. Effects of MBSR on HbA1C were not detected at post-intervention and follow-up. The findings suggest that MBSR appears to be an effective treatment for improving mental health conditions and mindfulness in people with diabetes. The measurement of cortisol is recommended to be used as a biological measure to evaluate the effectiveness of MBSR in diabetes patients in future research.

Comparative Effectiveness of Immune Checkpoint Inhibitors vs Chemotherapy in Patients With Metastatic Colorectal Cancer With Measures of Microsatellite Instability, Mismatch Repair, or Tumor Mutational Burden.

Importance: The KEYNOTE-177 trial demonstrated that patients with metastatic colorectal cancer (MCRC) with high microsatellite instability (MSI-H) and/or mismatch repair deficiency (DMMR) have better outcomes when receiving first-line immune checkpoint inhibitors (ICIs) compared with chemotherapy. Data on performance of ICIs in patients with MCRC in standard practice settings remain limited, and direct MMR vs MSI outcome association comparisons are lacking. Objective: To validate MSI (determined by next-generation sequencing [NGS]) as a biomarker of ICI effectiveness among patients with MCRC in standard practice settings and examine the association of MSI assessed by NGS, DMMR by immunohistochemistry, and tumor mutational burden (cutoff, 10 mutations/megabase) with ICI outcomes. Design, Setting, and Participants: This comparative effectiveness research study of outcomes in prospectively defined biomarker subgroups used data from a deidentified clinicogenomic database and included patients who received Foundation Medicine testing (FoundationOne or FoundationOne CDx) during routine clinical care at approximately 280 US academic or community-based cancer clinics between March 2014 and December 2021. The population included 1 cohort of patients with MSI-H MCRC who received first-line ICIs or chemotherapy and a second cohort who received ICIs in any line of therapy (LOT) for biomarker examination. Exposures: ICI therapy or chemotherapy assigned at physician discretion without randomization. Main Outcomes and Measures: The main outcomes were time to next treatment (TTNT), progression-free survival (PFS), and overall survival (OS). Hazard ratios were adjusted for known prognostic imbalances. Comparisons of explanatory power used the likelihood ratio test. Results: A total of 138 patients (median age, 67.0 years [IQR, 56.2-74.0 years]; 73 [52.9%] female) with MSI-H MCRC received first-line ICIs or chemotherapy. A total of 182 patients (median age, 64.5 years [IQR, 55.2-72.0]; 98 [53.8%] female) received ICIs in any LOT. Patients receiving first-line ICIs vs chemotherapy had longer TTNT (median, not reached [NR] vs 7.23 months [IQR, 6.21-9.72 months]; adjusted hazard ratio [AHR], 0.17; 95% CI, 0.08-0.35; P < .001), PFS (median, 24.87 months [IQR, 19.10 months to NR] vs 5.65 months [IQR, 4.70-8.34 months]; AHR, 0.31; 95% CI, 0.18-0.52; P < .001), and OS (median, NR vs 24.1 months [IQR, 13.90 months to NR]; HR, 0.45; 95% CI, 0.23-0.88; P = .02). MSI added to DMMR better anticipated TTNT and PFS in patients receiving ICIs than DMMR alone. The same was not observed when DMMR evaluation was added to MSI. Conclusions and Relevance: In this comparative effectiveness research study, MSI assessed by NGS robustly identified patients with favorable outcomes on first-line ICIs vs chemotherapy and appeared to better anticipate ICI outcomes compared with DMMR.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants.

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Biology and Targetability of the Extended Spectrum of PIK3CA Mutations Detected in Breast Carcinoma.

PURPOSE: Alpelisib is a PI3K alpha (PI3Kα)-selective inhibitor approved for the treatment of hormone receptor-positive/HER2-negative (HR+/HER2-) PIK3CA-mutated advanced breast cancer (ABC) based on the SOLAR-1 trial, which defined 11 substitutions in exons 7, 9, and 20 in PIK3CA (SOLAR1m). We report alpelisib effectiveness for ABC harboring SOLAR1m, as well as other pathogenic PIK3CA mutations (OTHERm) using comprehensive genomic profiling (CGP). EXPERIMENTAL DESIGN: A total of 33,977 tissue and 1,587 liquid biopsies were analyzed using hybrid capture-based CGP covering the entire coding sequence of PIK3CA. Clinical characteristics and treatment history were available for 10,750 patients with ABC in the deidentified Flatiron Health-Foundation Medicine clinico-genomic database (FH-FMI CGDB). RESULTS: PIK3CAm were detected in 11,767/33,977 (35%) of tissue biopsies, including 2,300 (7%) samples with OTHERm and no SOLAR1m. Liquid biopsy had 77% sensitivity detecting PIK3CAm, increasing to 95% with circulating tumor DNA fraction ≥2%. In patients with HR+/HER2- ABC and PIK3CAm receiving alpelisib/fulvestrant (ALP+FUL; n = 182) or fulvestrant alone (FUL; n = 119), median real-world progression-free survival (rwPFS) was 5.9 months on ALP+FUL [95% confidence interval (CI): 5.1-7.4] versus 3.1 months on FUL (95% CI: 2.7-3.7; P < 0.0001). In patients with OTHERm, median rwPFS was 4.0 months on ALP+FUL (95% CI: 2.8-10.1) versus 2.5 months on FUL (95% CI: 2.2-3.7; P = 0.0054). CONCLUSIONS: CGP detects diverse PIK3CAm in a greater number of patients with ABC than PCR hotspot testing; 20% of patients with PIK3CAm do not have SOLAR1m. These patients may derive benefit from alpelisib. See related commentary by Tau and Miller, p. 989.

Multi-state survival models with treatment effects and biomarkers: Simulations for study design assessment.

BACKGROUND: Comparative effectiveness studies of cancer therapeutics in observational data face confounding by patterns of clinical treatment over time. The validity of survival analysis in longitudinal health records depends on study design choices including index date definition and model specification for covariate adjustment. METHODS: Overall survival in cancer is a multi-state transition process with mortality and treatment switching as competing risks. Parametric Weibull regression quantifies proportionality of hazards across lines of therapy in real-world cohorts of 12 solid tumor types. Study design assessments compare alternative analytic models in simulations with realistic disproportionality. The multi-state simulation framework is adaptable to alternative treatment effect profiles and exposure patterns. RESULTS: Event-specific hazards of treatment-switching and death are not proportional across lines of therapy in 12 solid tumor types. Study designs that include all eligible lines of therapy per subject showed lower bias and variance than designs that select one line per subject. Confounding by line number was effectively mitigated across a range of simulation scenarios by Cox proportional hazards models with stratified baseline hazards and inverse probability of treatment weighting. CONCLUSION: Quantitative study design assessment can inform the planning of observational research in clinical oncology by demonstrating the potential impact of model misspecification. Use of empirical parameter estimates in simulation designs adapts analytic recommendations to the clinical population of interest.

SPOP Mutations as a Predictive Biomarker for Androgen Receptor Axis-Targeted Therapy in De Novo Metastatic Castration-Sensitive Prostate Cancer.

PURPOSE: Intensification of androgen deprivation therapy (ADT) with either docetaxel or androgen receptor axis-targeted therapies (ARAT) are the current standard of care for patients with metastatic castration-sensitive prostate cancer (mCSPC). However, biomarkers guiding treatment selection are lacking. We hypothesized that ADT intensification with ARAT, but not with docetaxel, would be associated with improved outcomes in patients with de novo (dn)-mCSPC harboring SPOP mutations. EXPERIMENTAL DESIGN: Patient-level data from a deidentified nationwide (U.S.-based) prostate cancer clinico-genomic database between January 2011 and December 2021 were extracted. Eligibility criteria: diagnosis of metastatic disease within 30 days of original prostate cancer diagnosis, genomic profiling of a tissue biopsy collected within 90 days of original diagnosis, and initiation of ARAT or docetaxel within 120 days of initial diagnosis. The log-rank test and Cox proportional hazards models were used to compare time to castration-resistant prostate cancer (TTCRPC) and overall survival (OS) for patients with and without SPOP mutations undergoing ADT intensification with ARAT or docetaxel. RESULTS: In the ARAT cohort, presence of SPOP mutation compared with wild-type was associated with more favorable TTCRPC [not reached (NR) vs. 16.7 months; adjusted HR (aHR), 0.20; 95% confidence interval (CI), 0.06-0.63; P = 0.006] and OS (NR vs. 27.2 months; aHR, 0.19; 95% CI, 0.05-0.79; P = 0.022). In contrast, SPOP mutation status was not associated with TTCRPC or OS in docetaxel-treated cohort. CONCLUSIONS: In real-world settings, SPOP mutations were associated with improved outcomes to ADT plus ARAT (but not ADT plus docetaxel) in patients with dn-mCSPC. This may serve as a predictive biomarker to guide treatment selection for patients with mCSPC.

Tumor Mutational Burden as a Predictor of First-Line Immune Checkpoint Inhibitor Versus Carboplatin Benefit in Cisplatin-Unfit Patients With Urothelial Carcinoma.

PURPOSE: In real-world settings, patients with metastatic urothelial carcinoma (mUC) are often more frail than clinical trials, underscoring an unmet need to identify patients who might be spared first-line chemotherapy. We sought to determine whether tumor mutational burden (TMB) identifies patients with comparable or superior clinical benefit of first-line single-agent immune checkpoint inhibitors (ICPI) in real-world patients deemed cisplatin-unfit. METHODS: Patients with mUC treated in first-line advanced setting (N = 401) received ICPI (n = 245) or carboplatin regiment without ICPI (n = 156) at physician's discretion in standard-of-care settings across approximately 280 US academic or community-based cancer clinics between March 2014 and July 2021. Deidentified data were captured into a real-world clinicogenomic database. All patients underwent testing using Foundation Medicine assays. Progression-free survival (PFS), time to next treatment (TTNT), and overall survival (OS) comparing ICPI versus chemotherapy were adjusted for known treatment assignment imbalances using propensity scores. RESULTS: TMB ≥ 10 was detected in 122 of 401 (30.4%) patients. Among patients receiving ICPI, those with TMB ≥ 10 had more favorable PFS (HR, 0.59; 95% CI, 0.41 to 0.85), TTNT (HR, 0.59; 95% CI, 0.43 to 0.83), and OS (HR, 0.47; 95% CI, 0.32 to 0.68). Comparing ICPI versus carboplatin, adjusting for imbalances, patients with TMB ≥ 10 had more favorable PFS (HR, 0.51; 95% CI, 0.32 to 0.82), TTNT (HR, 0.56; 95% CI, 0.35 to 0.91), and OS (HR, 0.56; 95% CI, 0.29 to 1.08) on ICPI versus chemotherapy, but not TMB < 10. Comparisons unadjusted for imbalances had similar associations. CONCLUSIONS: In real-world settings, mUC patients with TMB ≥ 10 have more favorable outcomes on first-line single-agent ICPI than carboplatin, adding clinical validity to TMB assessed by an existing US Food and Drug Administration-approved platform.

Clinical and pathological features associated with circulating tumor DNA content in real-world patients with metastatic prostate cancer.

BACKGROUND: Liquid biopsy is a powerful tool that can enable treatment decisions for metastatic prostate cancer patients with difficult-to-biopsy tumors. However, the detection of genomic alterations via liquid biopsy is limited by the fraction (tumor fraction [TF]) of circulating tumor DNA (ctDNA) within the total cell-free DNA content. While prior work has preliminarily correlated TF with clinical features of prostate cancer, we sought to validate and provide additional resolution, such that a clinical practitioner might anticipate the probability of successful liquid biopsy profiling leveraging commonly assessed clinical and laboratory features. METHODS: A total of 813 liquid biopsy specimens were assessable, with 545 associated with a PSA prostate specific antigen measurement, collected in standard-of-care settings across approximately 280 US academic or community-based cancer clinics from September 2018 to July 2021. Deidentified data were captured into a real-world clinico-genomic database (CGDB). Comprehensive genomic profiling (CGP) was performed on extracted cell-free DNA from liquid biopsy samples. RESULTS: In multivariable models, higher PSA level, lower hemoglobin, lower albumin, higher alkaline phosphatase (all p < 0.001), and collection of liquid biopsy blood draw within 60 days of new treatment initiation (p = 0.002) were the most strongly associated features with higher TF. At PSA levels of <5 ng/ml, 43% of patients had a TF of <1% indicating an increased likelihood of unevaluable results. Conversely, at PSA levels of >5 ng/ml, 78% of patients had a TF of at least 1% and 46% had a TF of ≥10%, suggesting improved sensitivity for detection of targetable alterations. CONCLUSIONS: Universal genomic profiling of prostate cancers will require complementary use of liquid biopsy and tumor tissue profiling for suitable patients. The likelihood of adequate ctDNA shedding into plasma is one consideration when deciding whether to pursue CGP via liquid biopsy versus tumor profiling. Our real-world data suggest that PSA < 5 ng/ml is associated with lower ctDNA yield on liquid biopsy, potentially increasing the incidence of negative results or a need for confirmation with tissue testing.

Comparative Effectiveness of Immune Checkpoint Inhibitors vs Chemotherapy by Tumor Mutational Burden in Metastatic Castration-Resistant Prostate Cancer.

Importance: The most useful biomarkers for clinical decision-making identify patients likely to have improved outcomes with one treatment vs another. Objective: To evaluate treatment class-specific outcomes of patients receiving immune checkpoint inhibitor (ICI) vs taxane chemotherapy by tumor mutational burden (TMB). Design, Setting, and Participants: This comparative effectiveness analysis of clinical variables and outcomes used prospectively defined biomarker-stratified genomic data from a deidentified clinicogenomic database. Data included men with previously treated metastatic castration-resistant prostate cancer (mCRPC) receiving ICI or single-agent taxane chemotherapy from January 2011 to April 2021 at approximately 280 US academic or community-based cancer clinics (approximately 800 sites of care). Data were analyzed from July to August 2021. Exposures: Single-agent ICI or single-agent taxanes. Treatments were assigned at discretion of physician and patient without randomization. Imbalances of known factors between treatment groups were adjusted with propensity weighting. Main Outcomes and Measures: Prostate-specific antigen (PSA) response, time to next therapy (TTNT), and overall survival (OS). Results: A total of 741 men (median [IQR], 70 [64-76] years) with mCRPC received comprehensive genomic profiling and were treated with ICI or single-agent taxane therapy. At baseline, the median (IQR) PSA level was 79.4 (19.0-254) ng/mL, 108 men (18.8%) had Eastern Cooperative Oncology Group Performance Status scores of 2 or greater, and 644 men (86.9%) had received prior systemic treatments for mCRPC. A total of 45 patients (6.1%) received ICI therapy and 696 patients (93.9%) received taxane therapy. Among patients with TMB of fewer than 10 mutations per megabase (mt/Mb) receiving ICI, compared with those receiving taxanes, had worse TTNT (median [IQR], 2.4 [1.1-3.2] months vs 4.1 [2.2-6.3] months; hazard ratio [HR], 2.65; 95% CI, 1.78-3.95; P < .001). In contrast, for patients with TMB of 10 mt/Mb or greater, use of ICIs, compared with use taxanes, was associated with more favorable TTNT (median [IQR], 8.0 [3.4 to unknown] months vs 2.4 [2.4-7.3] months; HR, 0.37, 95% CI, 0.15-0.87; P = .02) and OS (median 19.9 [8.06 to unknown] months vs 4.2 [2.69 - 6.12] months; HR, 0.23; 95% CI, 0.10-0.57; P = .001). Among all 741 patients, 44 (5.9%) had TMB of 10 mt/Mb or greater, 22 (3.0%) had high microsatellite instability, and 20 (2.7%) had both. Treatment interactions with TMB of 10 mt/Mb or greater (TTNT: HR, 0.10; 95% CI, 0.32-0.31; P < .001; OS: HR, 0.25; 95% CI, 0.076-0.81; P = .02) were stronger than high microsatellite instability alone (TTNT: HR, 0.12; 95% CI, 0.03-0.51; P = .004; OS: HR, 0.38; 95% CI, 0.13-1.12; P = .08). Conclusions and Relevance: In this comparative effectiveness study, ICIs were more effective than taxanes in patients with mCRPC when TMB was 10 mt/Mb or greater but not when TMB was fewer than 10 mt/Mb. The results add validity to the existing TMB cutoff of 10 mt/Mb for ICI use in later lines of therapy, and suggest that ICIs may be a viable alternative to taxane chemotherapy for patients with mCRPC with high TMB.

Natural History of Human Epidermal Growth Factor Receptor 2-Amplified and Human Epidermal Growth Factor Receptor 2 Wild-Type Refractory Metastatic Colorectal Cancer in US Clinical Practice.

PURPOSE: The molecular heterogeneity of metastatic colorectal cancer (mCRC) presents a therapeutic challenge, with few trials focused on patients with human epidermal growth factor receptor 2 amplification (HER2-Amp). Our limited understanding of real-world patterns and outcomes by HER2 status of treatment-refractory patients leaves treatment decisions with little contextual information. We conducted a retrospective cohort study to describe the natural disease history of patients with refractory mCRC using an electronic health record-derived database with oncogenomic information. METHODS: We included patients with stage IV or recurrent mCRC diagnosed from January 2011 through December 2019 from a deidentified clinicogenomic database. Patients with ≥ 2 documented clinic visits, ≥ 2 lines of therapy (LOT) after mCRC diagnosis, and comprehensive genomic profiling were eligible. Patient records defined by treatment-refractory LOT were allocated to the HER2-Amp or HER2 wild-type (WT) cohort on the basis of comprehensive genomic profiling. Index date was defined as the start of any treatment-refractory LOT (≥ 2 LOT; patients could contribute multiple records). Descriptive statistics included demographic and clinical characteristics, treatments, laboratory values, and biomarkers. Overall survival (OS) was calculated as time (in months) from the index date until death from any cause and analyzed using Kaplan-Meier methodology. Sensitivity analyses were conducted to test the robustness of the primary findings. RESULTS: A total of 576 patients were included (1,339 records); 63 (158 records) were HER2-Amp, and 513 (1,181 records) were HER2-WT. Demographics, clinical characteristics, biomarkers, and laboratory values were comparable between HER2 cohorts. OS was similar, with an unadjusted median OS of 11.2 months (95% CI, 8.6 to 15.1) and 9.9 months (95% CI, 8.3 to 10.9) across LOT for HER2-Amp and HER2-WT cohorts, respectively. CONCLUSION: This study showed considerable treatment heterogeneity and poor outcomes among patients with treatment-refractory mCRC, emphasizing a substantial unmet therapeutic need.

Real-world Validation of TMB and Microsatellite Instability as Predictive Biomarkers of Immune Checkpoint Inhibitor Effectiveness in Advanced Gastroesophageal Cancer.

Patients with advanced gastroesophageal cancer (mEG) and tumor mutational burden ≥10 mut/Mb (TMB ≥ 10) have more favorable outcomes on immune checkpoint inhibitor (ICPI) monotherapy compared with chemotherapy in subgroup analyses of randomized controlled trials. We sought to evaluate the robustness of these associations in real-world settings where patients and practices are more diverse. A total of 362 2 L and 692 1 L patients, respectively received ICPI (n = 99, 33) or chemotherapy (n = 263, 659) across approximately 280 U.S. academic or community-based cancer clinics March 2014-July 2021. Deidentified data were captured into a real-world clinico-genomic database. All patients underwent Foundation Medicine testing. Time to next treatment (TTNT) and overall survival (OS) comparing ICPI versus chemotherapy were adjusted for treatment assignment imbalances using propensity scores. 2L: TMB ≥ 10 had more favorable TTNT [median 24 vs. 4.1 months; HR: 0.19; 95% confidence interval (CI): 0.09-0.44; P = 0.0001] and OS (median 43.1 vs. 6.2 months; HR: 0.24; 95% CI: 0.011-0.54; P = 0.0005), TMB < 10 did not (P > 0.05). 1L: TMB ≥ 10 had more favorable TTNT (not reached vs. median 4.1 months; HR: 0.13; 95% CI: 0.03-0.48; P = 0.0024) and OS (not reached vs. median 17.1 months; HR: 0.30; 95% CI: 0.08-1.14; P = 0.078), TMB < 10 had less favorable TTNT (median 2.8 vs. 6.5 months; HR: 2.36; 95% CI: 1.25-4.45; P = 0.008) and OS (median 4.5 vs. 13.1 months; HR: 1.82, 95% CI: 0.87-3.81; P = 0.11). TMB ≥ 10 robustly identifies patients with mEG with more favorable outcomes on 2 L ICPI monotherapy versus chemotherapy. 1 L data are more limited, but effects are consistent with 2L. Significance: Using real-world data, we sought to evaluate robustness of these clinical associations using the same assay platform and biomarker cut-off point used in both clinical trials and pan-tumor CDx approvals for later treatment lines. TMB ≥ 10 robustly identified patients with mEG with more favorable outcomes on ICPI monotherapy versus chemotherapy and suggests this subset of patients could be targeted for further trial development.

Predictive Genomic Biomarkers of Hormonal Therapy Versus Chemotherapy Benefit in Metastatic Castration-resistant Prostate Cancer.

BACKGROUND: Biomarkers predicting second-generation novel hormonal therapy (NHT) benefit relative to taxanes are critical for optimized treatment decisions for metastatic castration-resistant prostate cancer (mCRPC) patients. These associations have not been reported simultaneously for common mCRPC genomic biomarkers. OBJECTIVE: To evaluate predictive associations of common genomic aberrations in mCRPC using an established comprehensive genomic profiling (CGP) system. DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort study used data from a deidentified US-based clinicogenomic database comprising patients treated in routine clinical practice between 2011 and 2020, evaluated with Foundation Medicine CGP in tissue biopsies obtained around the time of treatment decision. The main cohort included 180 NHT and 179 taxane lines of therapy (LOTs) from 308 unique patients. The sequential cohort comprised a subset of the main cohort NHT LOTs immediately followed by taxane from 55 unique patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Prostate-specific antigen (PSA) response, time to next treatment (TTNT), and overall survival (OS) were assessed. Main cohort analyses were adjusted for known treatment assignment biases via inverse probability of treatment weighting (IPTW) in treatment interaction models. RESULTS AND LIMITATIONS: In the main cohort, patients with AR amplification (ARamp) or PTEN aberrations (PTENalt) had worse relative PSA response on NHT versus taxanes compared with patients without. Patients with ARamp, PTENalt, or RB1 aberrations (RB1alt) also had worse relative TTNT and OS on NHT but not on taxanes. In multivariable models for TTNT and OS adjusted via IPTW, ARamp, PTENalt, and RB1alt were shown as poor prognostic factors overall and demonstrated significant treatment interactions, indicating reduced hazards of therapy switch and death on taxanes versus NHT. Consistent associations favoring increased benefit from subsequent taxane despite prior NHT treatment line were observed only for ARamp in the sequential cohort, in which very few patients had RB1alt for assessment. CONCLUSIONS: ARamp status is a candidate biomarker to predict poor effectiveness of NHT relative to taxanes in mCRPC in scenarios where both options are considered. PATIENT SUMMARY: Specific alterations in the DNA of tumors may assist in choosing between novel oral hormonal therapies and standard chemotherapy in advanced prostate cancer patients.

ANNORE: genetic fine-mapping with functional annotation.

Genome-wide association studies (GWASs) have successfully identified loci of the human genome implicated in numerous complex traits. However, the limitations of this study design make it difficult to identify specific causal variants or biological mechanisms of association. We propose a novel method, AnnoRE, which uses GWAS summary statistics, local correlation structure among genotypes and functional annotation from external databases to prioritize the most plausible causal single-nucleotide polymorphisms (SNPs) in each trait-associated locus. Our proposed method improves upon previous fine-mapping approaches by estimating the effects of functional annotation from genome-wide summary statistics, allowing for the inclusion of many annotation categories. By implementing a multiple regression model with differential shrinkage via random effects, we avoid reductive assumptions on the number of causal SNPs per locus. Application of this method to a large GWAS meta-analysis of body mass index identified six loci with significant evidence in favor of one or more variants. In an additional 24 loci, one or two variants were strongly prioritized over others in the region. The use of functional annotation in genetic fine-mapping studies helps to distinguish between variants in high LD and to identify promising targets for follow-up studies.

TRK Fusion Cancer: Patient Characteristics and Survival Analysis in the Real-World Setting.

BACKGROUND: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are oncogenic drivers in various tumor types. While NTRK gene fusions are predictive of benefit from tropomyosin receptor kinase inhibitors regardless of tumor type, the prognostic significance of NTRK gene fusions in a pan-tumor setting remains unclear. OBJECTIVE: This study evaluated the characteristics and prognosis of tropomyosin receptor kinase fusion cancer in the real-world setting. PATIENTS AND METHODS: This retrospective study used a de-identified clinico-genomic database and included patients with cancer who had comprehensive genomic profiling between January 2011 and July 2018. Patients were classified as having cancer with NTRK gene fusions or NTRK wild-type genes. Patients were matched with a 1:4 ratio (NTRK fusion:NTRK wild-type) using the Mahalanobis distance method on demographic and clinical characteristics, including age and Eastern Cooperative Oncology Group performance status. Descriptive analysis of clinical and molecular characteristics was conducted. Kaplan-Meier estimator and Cox regression were used for overall survival analysis. RESULTS: Median overall survival was 12.5 months (95% confidence interval 9.5-not estimable) and 16.5 months (95% confidence interval 12.5-22.5) in the NTRK gene fusion (n = 27) and NTRK wild-type cohorts (n = 107), respectively (hazard ratio 1.44; 95% confidence interval 0.61-3.37; p = 0.648). Co-occurrence of select targetable biomarkers including ALK, BRAF, ERBB2, EGFR, ROS1, and KRAS was lower in cancers with NTRK gene fusions than in NTRK wild-type cancers. CONCLUSIONS: Although the hazard ratio for overall survival suggested a higher risk of death for patients with NTRK gene fusions, the difference was not statistically significant. Co-occurrence of NTRK gene fusions and other actionable biomarkers was uncommon.

Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response.

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non-small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs. SIGNIFICANCE: This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected "Goldilocks" relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development.This article is highlighted in the In This Issue feature, p. 211.

Direct Versus Calculated LDL Cholesterol and C-Reactive Protein in Cardiovascular Disease Risk Assessment in the Framingham Offspring Study.

BACKGROUND: Increases in circulating LDL cholesterol (LDL-C) and high-sensitivity C-reactive protein (hsCRP) concentrations are significant risk factors for cardiovascular disease (CVD). We assessed direct LDL-C and hsCRP concentrations compared to standard risk factors in the Framingham Offspring Study. METHODS: We used stored frozen plasma samples (-80 °C) obtained after an overnight fast from 3147 male and female participants (mean age, 58 years) free of CVD at cycle 6 of the Framingham Offspring Study. Overall, 677 participants (21.5%) had a CVD end point over a median of 16.0 years of follow-up. Total cholesterol (TC), triglyceride (TG), HDL cholesterol (HDL-C), direct LDL-C (Denka Seiken and Kyowa Medex methods), and hsCRP (Dade Behring method) concentrations were measured by automated analysis. LDL-C was also calculated by both the Friedewald and Martin methods. RESULTS: Considering all CVD outcomes on univariate analysis, significant factors included standard risk factors (age, hypertension, HDL-C, hypertension treatment, sex, diabetes, smoking, and TC concentration) and nonstandard risk factors (non-HDL-C, direct LDL-C and calculated LDL-C, TG, and hsCRP concentrations). On multivariate analysis, only the Denka Seiken direct LDL-C and the Dade Behring hsCRP were still significant on Cox regression analysis and improved the net risk reclassification index, but with modest effects. Discordance analysis confirmed the benefit of the Denka Seiken direct LDL-C method for prospective hard CVD endpoints (new-onset myocardial infarction, stroke, and/or CVD death). CONCLUSIONS: Our data indicate that the Denka Seiken direct LDL-C and Dade Behring hsCRP measurements add significant, but modest, information about CVD risk, compared to standard risk factors and/or calculated LDL-C.

Revisit Population-based and Family-based Genotype Imputation.

Genome-Wide Association (GWA) with population-based imputation (PBI) has been successful in identifying common variants associated with complex diseases; however, much heritability remains to be explained and low frequency variants (LFV) may contribute. To identify LFV, a study of unrelated individuals may no longer be as efficient as a family study, where rare population variants can be frequent in families. Family-based imputation (FBI) provides an opportunity to evaluate LFV. To compare the performance of PBI and FBI, we conducted extensive simulations, generating genotypes using SeqSIMLA from various reference panels for families. We masked genotype information for variants unavailable in Framingham 550 K GWA genotype data in less informative subjects selected by GIGI-Pick. We implemented IMPUTE2 with duoHMM in SHAPEIT (Impute2_duoHMM) for PBI, MERLIN and GIGI for FBI and PedBLIMP for a hybrid approach. In general, FBI in both MERLIN and GIGI outperformed other approaches with imputation accuracy greater than 0.99 for the squared correlation and imputation quality scores (IQS) especially for LFV, although imputation accuracy from MERLIN depends on pedigree splitting for larger families. PBI performed worst with the exception of good imputation accuracy for common variants when a closely ancestry matched reference is used. In summary, linkage disequilibrium (LD) information from large available genotype resources provides good imputation for common variants with well-selected reference panels without requiring densely sequenced data in family members, while imputation of LFV with FBI benefits more from information on inheritance patterns within families yielding better imputation.

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.

An efficient analytic approach in genome-wide identification of methylation quantitative trait loci response to fenofibrate treatment.

BACKGROUND: The study of DNA methylation quantitative trait loci (meQTLs) helps dissect regulatory mechanisms underlying genetic associations of human diseases. In this study, we conducted the first genome-wide examination of genetic drivers of methylation variation in response to a triglyceride-lowering treatment with fenofibrate (response-meQTL) by using an efficient analytic approach. METHODS: Subjects (n = 429) from the GAW20 real data set with genotype and both pre- (visit 2) and post- (visit 4) fenofibrate treatment methylation measurements were included. Following the quality control steps of removing certain cytosine-phosphate-guanine (CpG) probes, the post-/premethylation changes (post/pre) were log transformed and the association was performed on 208,449 CpG sites. An additive linear mixed-effects model was used to test the association between each CpG probe and single nucleotide polymorphisms (SNPs) around ±1 Mb region, with age, sex, smoke, batch effect, and principal components included as covariates. Bonferroni correction was applied to define the significance threshold (p < 5.6 × 10- 10, given a total of 89,217,303 tests). Finally, we integrated our response-meQTL (re-meQTL) findings with the published genome-wide association study (GWAS) catalog of human diseases/traits. RESULTS: We identified 1087 SNPs as cis re-meQTLs associated with 610 CpG probes/sites located in 351 unique gene loci. Among these 1087 cis re-meQTL SNPs, 229 were unique and 6 were co-localized at 8 unique disease/trait loci reported in the GWAS catalog (enrichment p = 1.51 × 10- 23). Specifically, a lipid SNP, rs10903129, located in intron regions of gene TMEM57, was a re-meQTL (p = 3.12 × 10- 36) associated with the CpG probe cg09222892, which is in the upstream region of the gene RHCE, indicating a new target gene for rs10903129. In addition, we found that SNP rs12710728 has a suggestive association with cg17097782 (p = 1.77 × 10- 4), and that this SNP is in high linkage disequilibrium (LD) (R2 > 0.8) with rs7443270, which was previously reported to be associated with fenofibrate response (p = 5.00 × 10- 6). CONCLUSIONS: By using a novel analytic approach, we efficiently identified thousands of cis re-meQTLs that provide a unique resource for further characterizing functional roles and gene targets of the SNPs that are most responsive to fenofibrate treatment. Our efficient analytic approach can be extended to large response quantitative trait locus studies with large sample sizes and multiple time points data.