Profiling the molecular and clinical landscape of glioblastoma utilizing the Oncology Research Information Exchange Network brain cancer database.

Background: Glioblastoma exhibits aggressive growth and poor outcomes despite treatment, and its marked variability renders therapeutic design and prognostication challenging. The Oncology Research Information Exchange Network (ORIEN) database contains complementary clinical, genomic, and transcriptomic profiling of 206 glioblastoma patients, providing opportunities to identify novel associations between molecular features and clinical outcomes. Methods: Survival analyses were performed using the Logrank test, and clinical features were evaluated using Wilcoxon and chi-squared tests with q-values derived via Benjamini-Hochberg correction. Mutational analyses utilized sample-level enrichments from whole exome sequencing data, and statistical tests were performed using the one-sided Fisher Exact test with Benjamini-Hochberg correction. Transcriptomic analyses utilized a student's t-test with Benjamini-Hochberg correction. Expression fold changes were processed with Ingenuity Pathway Analysis to determine pathway-level alterations between groups. Results: Key findings include an association of MUC17, SYNE1, and TENM1 mutations with prolonged overall survival (OS); decreased OS associated with higher epithelial growth factor receptor (EGFR) mRNA expression, but not with EGFR amplification or mutation; a 14-transcript signature associated with OS > 2 years; and 2 transcripts associated with OS < 1 year. Conclusions: Herein, we report the first clinical, genomic, and transcriptomic analysis of ORIEN glioblastoma cases, incorporating sample reclassification under updated 2021 diagnostic criteria. These findings create multiple avenues for further investigation and reinforce the value of multi-institutional consortia such as ORIEN in deepening our knowledge of intractable diseases such as glioblastoma.

Germline predictors for bevacizumab induced hypertensive crisis in ECOG-ACRIN 5103 and BEATRICE.

BACKGROUND: Bevacizumab is a beneficial therapy in several advanced cancer types. Predictive biomarkers to better understand which patients are destined to benefit or experience toxicity are needed. Associations between bevacizumab induced hypertension and survival have been reported but with conflicting conclusions. METHODS: We performed post-hoc analyses to evaluate the association in 3124 patients from two phase III adjuvant breast cancer trials, E5103 and BEATRICE. Differences in invasive disease-free survival (IDFS) and overall survival (OS) between patients with hypertension and those without were compared. Hypertension was defined as systolic blood pressure (SBP) ≥ 160 mmHg (n = 346) and SBP ≥ 180 mmHg (hypertensive crisis) (n = 69). Genomic analyses were performed to evaluate germline genetic predictors for the hypertensive crisis. RESULTS: Hypertensive crisis was significantly associated with superior IDFS (p = 0.015) and OS (p = 0.042), but only IDFS (p = 0.029; HR = 0.28) remained significant after correction for prognostic factors. SBP ≥ 160 mmHg was not associated with either IDFS or OS. A common single-nucleotide polymorphism, rs6486785, was significantly associated with hypertensive crisis (p = 8.4 × 10-9; OR = 5.2). CONCLUSION: Bevacizumab-induced hypertensive crisis is associated with superior outcomes and rs6486785 predicted an increased risk of this key toxicity.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors. SIGNIFICANCE: Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

Molecular and clinical effects of aromatase inhibitor therapy on skeletal muscle function in early-stage breast cancer.

We evaluated biochemical changes in skeletal muscle of women with breast cancer initiating aromatase inhibitors (AI), including oxidation of ryanodine receptor RyR1 and loss of stabilizing protein calstabin1, and detailed measures of muscle function. Fifteen postmenopausal women with stage I-III breast cancer planning to initiate AI enrolled. Quadriceps muscle biopsy, dual-energy x-ray absorptiometry, isokinetic dynamometry, Short Physical Performance Battery, grip strength, 6-min walk, patient-reported outcomes, and serologic measures of bone turnover were assessed before and after 6 months of AI. Post-AI exposure, oxidation of RyR1 significantly increased (0.23 ± 0.37 vs. 0.88 ± 0.80, p < 0.001) and RyR1-bound calstabin1 significantly decreased (1.69 ± 1.53 vs. 0.74 ± 0.85, p < 0.001), consistent with dysfunctional calcium channels in skeletal muscle. Grip strength significantly decreased at 6 months. No significant differences were seen in isokinetic dynamometry measures of muscle contractility, fatigue resistance, or muscle recovery post-AI exposure. However, there was significant correlation between oxidation of RyR1 with muscle power (r = 0.60, p = 0.02) and muscle fatigue (r = 0.57, p = 0.03). Estrogen deprivation therapy for breast cancer resulted in maladaptive changes in skeletal muscle, consistent with the biochemical signature of dysfunctional RyR1 calcium channels. Future studies will evaluate longer trajectories of muscle function change and include other high bone turnover states, such as bone metastases.

Racial Disparities in Breast Cancer: from Detection to Treatment.

PURPOSE OF REVIEW: Update on current racial disparities in the detection and treatment of breast cancer. RECENT FINDINGS: Breast cancer remains the leading cause of cancer death among Black and Hispanic women. Mammography rates among Black and Hispanic women have surpassed those among White women, with studies now advocating for earlier initiation of breast cancer screening in Black women. Black, Hispanic, Asian, and American Indian and Alaskan Native women continue to experience delays in diagnosis and time to treatment. Further, racial discrepancies in receipt of guideline-concordant care, access to genetic testing and surgical reconstruction persist. Disparities in the initiation, completion, toxicity, and efficacy of chemotherapy, endocrine therapy, and targeted drug therapy remain for racially marginalized women. Efforts to evaluate the impact of race and ethnicity across the breast cancer spectrum are increasing, but knowledge gaps remain and further research is necessary to reduce the disparity gap.

Clinically significant germline pathogenic variants are missed by tumor genomic sequencing.

A germline pathogenic variant may be present even if the results of tumor genomic sequencing do not suggest one. There are key differences in the assay design and reporting of variants between germline and somatic laboratories. When appropriate, both tests should be completed to aid in therapy decisions and determining optimal screening and risk-reduction interventions.

Computational pharmacogenotype extraction from clinical next-generation sequencing.

Background: Next-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively. Methods: Germline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1. Results: Mean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort. Conclusion: Aldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.

A bioinformatics tool for identifying intratumoral microbes from the ORIEN dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, MEGA, to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of 9 cancer centers in the Oncology Research Information Exchange Network (ORIEN). This package has 3 unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2704 tumor RNA-seq samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.

Aligning Germline Cancer Predisposition With Tumor-Based Next-Generation Sequencing for Modern Oncology Diagnosis, Interception, and Therapeutic Development.

In the era of precision medicine, genomic interrogation for identification of both germline and somatic genetic alterations has become increasingly important. While such germline testing was usually undertaken via a phenotype-driven single-gene approach, with the advent of next-generation sequencing (NGS) technologies, the widespread utilization of multigene panels, often agnostic of cancer phenotype, has become a commonplace in many different cancer types. At the same time, somatic tumor testing in oncology performed for the purpose of guiding therapeutic decisions for targeted therapies has also rapidly expanded, recently starting to incorporate not just patients with recurrent or metastatic cancer but even patients with early-stage disease. An integrated approach may be the best approach for the optimal management of patients with different cancers. The lack of complete congruence between germline and somatic NGS tests does not minimize the power or importance of either, but highlights the need to understand their limitations so as not to overlook an important finding or omission. NGS tests built to more uniformly and comprehensively evaluate both the germline and tumor simultaneously are urgently required and are in development. In this article, we discuss approaches to somatic and germline analyses in patients with cancer and the knowledge gained from integration of tumor-normal sequencing. We also detail strategies for the incorporation of genomic analysis into oncology care delivery models and the important emergence of poly(ADP-ribose) polymerase and other DNA Damage Response inhibitors in the clinic for patients with cancer with germline and somatic BRCA1 and BRCA2 mutations.

Cytochrome P450 Oxidoreductase (POR) Associated with Severe Paclitaxel-Induced Peripheral Neuropathy in Patients of European Ancestry from ECOG-ACRIN E5103.

PURPOSE: Paclitaxel is a widely used anticancer therapeutic. Peripheral neuropathy is the dose-limiting toxicity and negatively impacts quality of life. Rare germline gene markers were evaluated for predicting severe taxane-induced peripheral neuropathy (TIPN) in the patients of European ancestry. In addition, the impact of Cytochrome P450 (CYP) 2C8, CYP3A4, and CYP3A5 metabolizer status on likelihood of severe TIPN was also assessed. EXPERIMENTAL DESIGN: Whole-exome sequencing analyses were performed in 340 patients of European ancestry who received a standard dose and schedule of paclitaxel in the adjuvant, randomized phase III breast cancer trial, E5103. Patients who experienced grade 3-4 (n = 168) TIPN were compared to controls (n = 172) who did not experience TIPN. For the analyses, rare variants with a minor allele frequency ≤ 3% and predicted to be deleterious by protein prediction programs were retained. A gene-based, case-control analysis using SKAT was performed to identify genes that harbored an imbalance of deleterious variants associated with increased risk of severe TIPN. CYP star alleles for CYP2C8, CYP3A4, and CYP3A5 were called. An additive logistic regression model was performed to test the association of CYP2C8, CYP3A4, and CYP3A5 metabolizer status with severe TIPN. RESULTS: Cytochrome P450 oxidoreductase (POR) was significantly associated with severe TIPN (P value = 1.8 ×10-6). Six variants were predicted to be deleterious in POR. There were no associations between CYP2C8, CYP3A4, or CYP3A5 metabolizer status with severe TIPN. CONCLUSIONS: Rare variants in POR predict an increased risk of severe TIPN in patients of European ancestry who receive paclitaxel.

"How is it going to help?": Exploring Black breast cancer patients' questions about biomarker testing to predict chemotherapy-induced peripheral neuropathy.

Objective: Many Black breast cancer patients experience chemotherapy-induced peripheral neuropathy (CIPN). Our study assessed Black breast cancer patients' questions about a biomarker test that can predict likelihood of CIPN. Methods: Nineteen Black women who were previous/current breast cancer patients participated in focus groups. Researchers briefly explained CIPN and the biomarker test, and then participants were asked what questions they would have about the test and its use in treatment decisions. These participant-voiced questions composed the data for this study and were analyzed using thematic analysis. Results: Participants' questions centered on six themes: reasons for the test, effect on timeline of breast cancer treatment, testing procedure, limits of test (including accuracy), research done to develop this test (including research participants), and concerns about personal information connected to the test (including DNA). Conclusion: This study provides an exploratory look at questions that Black breast cancer patients may have about toxicity biomarker testing use in breast cancer treatment decisions. Innovation: These findings provide a starting point for developing patient-centered approaches for integrating this precision medicine tool into clinical care. The methodological choice to generate participants' questions (rather than answers to a question) led to robust, actionable data.

Clinicogenomic Landscape of Metastatic Thymic Epithelial Tumors.

BACKGROUND: Despite favorable clinical outcomes, a subset of patients with thymic epithelial tumors (TETs) develop metastasis. The Cancer Genome Atlas (TCGA) provides genomic data on primary TETs (pTETs). This study assessed the molecular alterations and uncovered targetable pathways in metastatic TETs (mTETs). METHODS: From 2015 to 2020, 49 patients with stage IV TETs underwent Clinical Laboratory Improvement Amendments-based sequencing using whole-exome sequencing (n = 33), panel-based testing (n = 12), and/or liquid biopsy (n = 24). Specimens were obtained from a metastatic organ (n = 36) or relapsed primary mediastinal mass (n = 10), whereas four patients underwent a liquid biopsy only. Data on pTETs were derived from the TCGA. RESULTS: Compared with the pTET data set, patients with mTETs were younger (54 years v 60.5 years, P = .009) and had more aggressive histologies, with the most common tumor type being thymic carcinoma (n = 22, 40.7%) and B3 thymoma (n = 15, 27.8%). GTF2I was the most altered gene in primary thymomas (48.80%, n = 60). In metastatic thymoma and thymic carcinoma, TP53 was the most common genetic alteration (31% and 36%, respectively). In mTETs, the genomic alteration occurred in the TP53/CDK, EGFR/RAS, and PI3K/mTOR pathways. Biopsies obtained from distant metastasis were more commonly found to contain targetable mutations. There was an overlap of 61% (22 of 36) between tissue and liquid biopsy genomic alterations. CONCLUSION: Clinically actionable genomic alterations are frequently observed in mTETs, indicating a value of repeat biopsy (preferably from a metastatic site of TETs for sequencing at the time of recurrence (TCGA data).

Passage number affects differentiation of sensory neurons from human induced pluripotent stem cells.

Induced pluripotent stem cells (iPSCs) are a valuable resource for neurological disease-modeling and drug discovery due to their ability to differentiate into neurons reflecting the genetics of the patient from which they are derived. iPSC-derived cultures, however, are highly variable due to heterogeneity in culture conditions. We investigated the effect of passage number on iPSC differentiation to optimize the generation of sensory neurons (iPSC-dSNs). Three iPSC lines reprogrammed from the peripheral blood of three donors were differentiated into iPSC-dSNs at passage numbers within each of the following ranges: low (5-10), intermediate (20-26), and high (30-38). Morphology and pluripotency of the parent iPSCs were assessed prior to differentiation. iPSC-dSNs were evaluated based on electrophysiological properties and expression of key neuronal markers. All iPSC lines displayed similar morphology and were similarly pluripotent across passage numbers. However, the expression levels of neuronal markers and sodium channel function analyses indicated that iPSC-dSNs differentiated from low passage numbers better recapitulated the sensory neuron phenotype than those differentiated from intermediate or high passage numbers. Our results demonstrate that lower passage numbers may be better suited for differentiation into peripheral sensory neurons.

Initial Phase I Safety Study of Gedatolisib plus Cofetuzumab Pelidotin for Patients with Metastatic Triple-Negative Breast Cancer.

PURPOSE: The PI3K pathway is dysregulated in the majority of triple-negative breast cancers (TNBC), yet single-agent inhibition of PI3K has been ineffective in TNBC. PI3K inhibition leads to an immediate compensatory upregulation of the Wnt pathway. Dual targeting of both pathways is highly synergistic against TNBC models in vitro and in vivo. We initiated a phase I clinical trial combining gedatolisib, a pan-class I isoform PI3K/mTOR inhibitor, and cofetuzumab pelidotin, an antibody-drug conjugate against the cell-surface PTK7 protein (Wnt pathway coreceptor) with an auristatin payload. PATIENTS AND METHODS: Participants (pt) had metastatic TNBC or estrogen receptor (ER) low (ER and PgR < 5%, HER2-negative) breast cancer, and had received at least one prior chemotherapy for advanced disease. The primary objective was safety. Secondary endpoints included overall response rate (ORR), clinical benefit at 18 weeks (CB18), progression-free survival (PFS), and correlative analyses. RESULTS: A total of 18 pts were enrolled in three dose cohorts: gedatolisib 110 mg weekly + cofetuzumab pelidotin 1.4 mg/kg every 3 weeks (n = 4), 180 mg + 1.4 mg/kg (n = 3), and 180 mg + 2.8 mg/kg (n = 11). Nausea, anorexia, fatigue, and mucositis were common but rarely reached ≥grade 3 severity. Myelosuppression was uncommon. ORR was 16.7% (3/18). An additional 3 pts had stable disease (of these 2 had stable disease for >18 weeks); CB18 was 27.8%. Median PFS was 2.0 months (95% confidence interval for PFS: 1.2-6.2). Pts with clinical benefit were enriched with genomic alterations in the PI3K and PTK7 pathways. CONCLUSIONS: The combination of gedatolisib + cofetuzumab pelidotin was well tolerated and demonstrated promising clinical activity. Further investigation of this drug combination in metastatic TNBC is warranted.

Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing.

Germline whole exome sequencing from molecular tumor boards has the potential to be repurposed to support clinical pharmacogenomics. However, accurately calling pharmacogenomics-relevant genotypes from exome sequencing data remains challenging. Accordingly, this study assessed the analytical validity of the computational tool, Aldy, in calling pharmacogenomics-relevant genotypes from exome sequencing data for 13 major pharmacogenes. Germline DNA from whole blood was obtained for 164 subjects seen at an institutional molecular solid tumor board. All subjects had whole exome sequencing from Ashion Analytics and panel-based genotyping from an institutional pharmacogenomics laboratory. Aldy version 3.3 was operationalized on the LifeOmic Precision Health Cloud with copy number fixed to two copies per gene. Aldy results were compared with those from genotyping for 56 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, and TPMT. Read depth was >100× for all variants except CYP3A4∗22. For 75 subjects in the validation cohort, all 3393 Aldy variant calls were concordant with genotyping. Aldy calls for 736 diplotypes containing alleles assessed by both platforms were also concordant. Aldy identified additional star alleles not covered by targeted genotyping for 139 diplotypes. Aldy accurately called variants and diplotypes for 13 major pharmacogenes, except for CYP2D6 variants involving copy number variations, thus allowing repurposing of whole exome sequencing to support clinical pharmacogenomics.

Impact of African ancestry on the relationship between body mass index and survival in an early-stage breast cancer trial (ECOG-ACRIN E5103).

BACKGROUND: African ancestry (AA) and obesity are associated with worse survival in early-stage breast cancer. Obesity disproportionately affects women of AA; however, the intersection between ancestry and obesity on breast cancer outcomes remains unclear. METHODS: A total of 2854 patients in the adjuvant trial E5103 were analyzed. Genetic ancestry was determined using principal components from a genome-wide array. The impact of continuous or binary body mass index (BMI) on disease-free survival (DFS) and overall survival (OS) was evaluated by multivariable Cox proportional hazards models in AA patients and European ancestry (EA) patients. RESULTS: There were 2471 EA patients and 383 AA patients. Higher BMI was significantly associated with worse DFS and OS only in AA patients (DFS hazard ratio [HR], 1.25; 95% CI, 1.07-1.46; OS HR, 1.38; 95% CI, 1.10-1.73), not in EA patients (DFS HR, 0.97; 95% CI, 0.90-1.05; OS HR, 1.03; 95% CI, 0.93-1.14). Severe obesity (BMI ≥40) was significantly associated with worse survival in AA patients (DFS HR, 2.04; 95% CI, 1.21-3.43; OS HR, 2.21; 95% CI, 1.03-4.75) but had no impact on that of EA patients. In the estrogen receptor-positive (ER+) and triple-negative breast cancer subgroups, BMI was significantly associated with worse outcomes only in those AA patients with ER+ disease. Within the AA group, BMI remained associated with worse survival regardless of the AA proportion. CONCLUSIONS: Higher BMI was statistically significantly associated with worse breast cancer outcomes in AA but not EA patients. This association was most significant for severe obesity and those with ER+ disease. These observations help define optimal populations for weight change interventions designed to affect disparities and survival in early-stage breast cancer. LAY SUMMARY: African ancestry and obesity are both risk factors for worse survival after early-stage breast cancer. Women of African descent are also disproportionately affected by obesity; however, it is unclear what impact body weight has on racial disparities in breast cancer. Data from a large phase 3 clinical trial in high-risk, early-stage breast cancer were used to determine how body weight affects survival outcomes in European versus African Americans. Study results demonstrate that a higher body mass index is associated with increased risk of breast cancer recurrence and worse survival in women of African ancestry but not in women of European ancestry.

Clinical Opportunities for Germline Pharmacogenetics and Management of Drug-Drug Interactions in Patients With Advanced Solid Cancers.

PURPOSE: Precision medicine approaches, including germline pharmacogenetics (PGx) and management of drug-drug interactions (DDIs), are likely to benefit patients with advanced cancer who are frequently prescribed multiple concomitant medications to treat cancer and associated conditions. Our objective was to assess the potential opportunities for PGx and DDI management within a cohort of adults with advanced cancer. METHODS: Medication data were collected from the electronic health records for 481 subjects since their first cancer diagnosis. All subjects were genotyped for variants with clinically actionable recommendations in Clinical Pharmacogenetics Implementation Consortium guidelines for 13 pharmacogenes. DDIs were defined as concomitant prescription of strong inhibitors or inducers with sensitive substrates of the same drug-metabolizing enzyme and were assessed for six major cytochrome P450 (CYP) enzymes. RESULTS: Approximately 60% of subjects were prescribed at least one medication with Clinical Pharmacogenetics Implementation Consortium recommendations, and approximately 14% of subjects had an instance for actionable PGx, defined as a prescription for a drug in a subject with an actionable genotype. The overall subject-level prevalence of DDIs and serious DDIs were 50.3% and 34.8%, respectively. Serious DDIs were most common for CYP3A, CYP2D6, and CYP2C19, occurring in 24.9%, 16.8%, and 11.7% of subjects, respectively. When assessing PGx and DDIs together, approximately 40% of subjects had at least one opportunity for a precision medicine-based intervention and approximately 98% of subjects had an actionable phenotype for at least one CYP enzyme. CONCLUSION: Our findings demonstrate numerous clinical opportunities for germline PGx and DDI management in adults with advanced cancer.

Quality of Life Following Receipt of Adjuvant Chemotherapy With and Without Bevacizumab in Patients With Lymph Node-Positive and High-Risk Lymph Node-Negative Breast Cancer.

IMPORTANCE: Breast cancer treatment can impact not only short-term health but may also affect longer-term quality of life (QOL). OBJECTIVE: To describe and evaluate factors associated with diminished QOL following completion of active treatment. DESIGN, SETTING, AND PARTICIPANTS: This was a secondary analysis of a randomized clinical trial included patients with lymph node-positive or high-risk lymph node-negative breast cancer who had undergone definitive surgery and were enrolled in ECOG-ACRIN E5103, a multisite phase 3 trial. A survey was administered 18 months after enrollment to patients enrolled between January and June 2010. Final analysis of the data took place from March to December 2021. INTERVENTIONS: Patients received adjuvant doxorubicin, cyclophosphamide, and paclitaxel with either bevacizumab or placebo. MAIN OUTCOMES AND MEASURES: QOL and health status assessed with the EuroQol 5-Dimension 3-Levels (EQ-5D-3L), EQ-visual analog scale (EQ-VAS), and the Functional Assessment of Cancer Therapy-Breast Cancer, with arm subscale (FACT-B+4). Groups were compared by Fisher exact test, Wilcoxon rank sum, or Kruskal-Wallis test. Multivariable linear regression was used to assess factors independently associated with FACT-B scores. RESULTS: Data at 18 months were available from 455 of 519 patients (87.7%) enrolled in the trial. Median (range) age at enrollment was 52 (25-76) years. No differences in QOL (median [range] FACT-B scores: group A, 123 [67-146]; group B, 114 [54-148]; group C, 117 [42-148]; P = .23) or health status (median [range] EQ-5D-3L index scores: group A, 0.83 [0.28-1.00]; group B, 0.83 [0.20-1.00]; group C, 0.83 [0.17-1.00], P = .80; median EQ-VAS: group A, 85 [20-100]; group B, 85 [0-100]; group C, 85 [0-100]; P = .79) were observed across treatment groups; results for subsequent analyses were therefore reported irrespective of primary treatment. Overall, half of patients (258 of 444 [58%]) reported at least some pain or discomfort; 170 (38%) reported symptoms of anxiety or depression. In multivariable analyses, mastectomy with radiation (vs breast conserving surgery) and Asian, Black, or American Indian or Alaska Native race (vs White race) were associated with lower QOL (mastectomy with radiation: coefficient: -5.5; 95% CI, -10.1 to -0.9; Asian, Black, or American Indian or Alaska Native race: coefficient: -7.3; 95% CI, -13.2, -1.4). CONCLUSIONS AND RELEVANCE: In this study, the addition of bevacizumab to chemotherapy was not negatively associated with QOL at 18 months. A substantial proportion of participants reported problems related to pain or discomfort and anxiety or depression, demonstrating persistent consequences for physical and psychosocial well-being in this heavily treated population. Many problems reported are amenable to intervention, underscoring the need for timely referral to supportive resources, especially for women of color and those who have more extensive local therapy. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00433511.