Rebbeck, Timothy R.

Abstract Background: Engaging diverse populations in cancer genomics research is of critical importance and is a fundamental goal of the NCI Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Established as part of the Cancer Moonshot, PE-CGS is a consortium of stakeholders including clinicians, scientists, genetic counselors, and representatives of potential study participants and their communities. Participant engagement is an ongoing, bidirectional, and mutually beneficial interaction between study participants and researchers. PE-CGS sought to set priorities in participant engagement for conducting the network's research. Methods: PE-CGS deliberatively engaged its stakeholders in the following four-phase process to set the network's research priorities in participant engagement: (i) a brainstorming exercise to elicit potential priorities; (ii) a 2-day virtual meeting to discuss priorities; (iii) recommendations from the PE-CGS External Advisory Panel to refine priorities; and (iv) a virtual meeting to set priorities. Results: Nearly 150 PE-CGS stakeholders engaged in the process. Five priorities were set: (i) tailor education and communication materials for participants throughout the research process; (ii) identify measures of participant engagement; (iii) identify optimal participant engagement strategies; (iv) understand cancer disparities in the context of cancer genomics research; and (v) personalize the return of genomics findings to participants. Conclusions: PE-CGS is pursuing these priorities to meaningfully engage diverse and underrepresented patients with cancer and posttreatment cancer survivors as participants in cancer genomics research and, subsequently, generate new discoveries. Impact: Data from PE-CGS will be shared with the broader scientific community in a manner consistent with participant informed consent and community agreement.

Abstract Background Multiple myeloma (MM) evolves from monoclonal gammopathy of undetermined significance (MGUS), a clinically detectable but asymptomatic premalignant phase seen in ~3% of the general population 50 years of age or older. The prevalence of MGUS has not been described in a population at high risk of developing MM, specifically Black/African American (AA) individuals or first-degree relatives of patients with hematologic malignancies (HM). In 2019, we launched the first nationwide US screening study for individuals at high risk of MM to help better identify what population would benefit most from screening and early intervention for precursor MM stages. We aim to assess the prevalence of MGUS in a population at high risk of MM and characterize clinical variables of individuals who screen positive. Here, we report interim screening data on the first 2,960 participants. Methods Individuals aged 40 or older with an additional MM risk factor are eligible to be screened in the PROMISE Study. High-risk individuals include Black/AAs and those with a first-degree relative diagnosed with a hematologic malignancy or a precursor condition to MM. Blood from all participants was analyzed via serum protein electrophoresis, immunofixation, and Optilite® to measure the serum free light chains (sFLC), IgG, IgA and IgM. Results were returned to all participants, and those who tested positive for a monoclonal gammopathy (MGUS/SMM) were referred to a hematologist for clinical follow-up and invited to periodically complete epidemiologic exposure and psychosocial questionaries, including a 4-item cancer worry questionnaire and the RAND 36-item Short Form Survey (SF-36). To investigate the use of the higher-sensitivity matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) with the Optilite® IgG, IgA, IgM and sFLC results as a screening test for all participants, we rescreened 1,092 samples from PROMISE. The Binding Site Group proprietary software was used for the analysis of the combined MS/Optilite® results, allowing for the detection and quantification of M-protein. Heavy-Chain MGUS (HC-MGUS) was defined by the presence of one or more paired heavy and light chain monoclonal peaks detected by MS. Pairing was based on mass to charge ratio of identified peaks. To enrich the PROMISE cohort with Black/AA individuals, we identified and screened 1,868 Black/AA additional individuals from the Mass General Brigham (MGB) Biobank who met the PROMISE enrollment criteria. Screening was performed by MS/Optilite®, and results have not been returned to participants. Results We screened 2,960 participants with the combined MS/Optilite® approach. We report here the prevalence of HC-MGUS and plan on presenting the estimated rate of light chain MGUS in our cohort, at the meeting. We detected HC-MGUS in 9.6% (95% CI: 8.6-11%) of our cohort, with a prevalence of 10% (95% CI: 8.3-12%) in the PROMISE cohort and 9.4% (95% CI: 8.1-11%) in the MGB cohort (Table 1 and Figure 1). HC-MGUS prevalence increased with age in high-risk individuals from 4.9% (CI: 3.3-6.9%) for participants aged 40-49 to 13% (CI: 10-17%) in the 70-79 range (P < 1.2E-5). Among monoclonal HC-MGUS, we found 65% IgG, 18% IgM, and 18% IgA. M-spike was quantified in 97% of samples. Median M-spike concentration was, 0.058g/dL (max. 2.6g/dL) for IgG, 0.0043g/dL (max. 0.6g/dL) for IgM, and 0.067g/dL (max. 0.8g/dL) for IgA. In the Promise cohort, no significant change in cancer worry was observed across the pre- and post-screening interval among participants who screened positive (P = 0.52). Health-related quality of life, as measured by the SF-36, was not significantly different in screen-positive vs. screen-negative individuals for any of the eight subscales (all P > 0.20). Conclusions We present the largest dataset on monoclonal gammopathy prevalence and screening in individuals at high risk for MM, and more specifically the largest cohort of Black/AA, using a novel high-sensitivity testing approach. Our results confirm that older adults who are Black/AA or have a first-degree relative with an HM have a high prevalence MGUS and may benefit from precision screening approaches to allow for early detection and clinical intervention. Preliminary data on cancer worry and quality of life indicates that the psychosocial burden of screening in this population is likely minimal. Figure 1 Figure 1. Disclosures Sakrikar: The Binding Site: Current Employment. Krause: The Binding Site: Current Employment. Barnidge: The Binding Site: Current Employment. Bustoros: Takeda: Consultancy, Honoraria; Janssen, Bristol Myers Squibb: Honoraria, Speakers Bureau. Perkins: The Binding Site: Current Employment. Harding: The Binding Site: Current Employment, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Kapoor: Ichnos Sciences: Research Funding; Amgen: Research Funding; Pharmacyclics: Consultancy; Takeda: Research Funding; Sanofi: Consultancy; Regeneron Pharmaceuticals: Research Funding; AbbVie: Research Funding; BeiGene: Consultancy; Sanofi: Research Funding; Karyopharm: Research Funding; Glaxo SmithKline: Research Funding; Karyopharm: Consultancy; Cellectar: Consultancy. Mo: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy; Eli Lilly: Consultancy; Janssen: Honoraria; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees. Murray: The Binding Site: Patents & Royalties: Potential Royalties for use of mass spectrometry in M-protein detection. Getz: Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees; IBM, Pharmacyclics: Research Funding. Marinac: JBF Legal: Consultancy; GRAIL Inc: Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.

Abstract Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers. Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data. Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10−7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation. Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis. Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

Abstract Purpose: The role of immune-oncologic mechanisms of racial disparities in prostate cancer remains understudied. Limited research exists to evaluate the molecular underpinnings of immune differences in African American men (AAM) and European American men (EAM) prostate tumor microenvironment (TME). Experimental Design: A total of 1,173 radiation-naïve radical prostatectomy samples with whole transcriptome data from the Decipher GRID registry were used. Transcriptomic expressions of 1,260 immune-specific genes were selected to assess immune-oncologic differences between AAM and EAM prostate tumors. Race-specific differential expression of genes was assessed using a rank test, and intergene correlational matrix and gene set enrichment was used for pathway analysis. Results: AAM prostate tumors have significant enrichment of major immune-oncologic pathways, including proinflammatory cytokines, IFNα, IFNγ, TNFα signaling, ILs, and epithelial–mesenchymal transition. AAM TME has higher total immune content score (ICSHIGH) compared with 0 (37.8% vs. 21.9%, P = 0.003). AAM tumors also have lower DNA damage repair and are genomically radiosensitive as compared with EAM. IFITM3 (IFN-inducible transmembrane protein 3) was one of the major proinflammatory genes overexpressed in AAM that predicted increased risk of biochemical recurrence selectively for AAM in both discovery [HRAAM = 2.30; 95% confidence interval (CI), 1.21–4.34; P = 0.01] and validation (HRAAM = 2.42; 95% CI, 1.52–3.86; P = 0.0001) but not in EAM. Conclusions: Prostate tumors of AAM manifest a unique immune repertoire and have significant enrichment of proinflammatory immune pathways that are associated with poorer outcomes. Observed immune-oncologic differences can aid in a genomically adaptive approach to treating prostate cancer in AAM.

Abstract Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two‐sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low‐density lipoprotein [LDL] and high‐density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels ( P < 5 × 10 −8 ) were identified as instrumental variables, and assessed using genome‐wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non‐endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non‐endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non‐endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non‐endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.

PURPOSE Germline testing (GT) is a central feature of prostate cancer (PCA) treatment, management, and hereditary cancer assessment. Critical needs include optimized multigene testing strategies that incorporate evolving genetic data, consistency in GT indications and management, and alternate genetic evaluation models that address the rising demand for genetic services. METHODS A multidisciplinary consensus conference that included experts, stakeholders, and national organization leaders was convened in response to current practice challenges and to develop a genetic implementation framework. Evidence review informed questions using the modified Delphi model. The final framework included criteria with strong (> 75%) agreement (Recommend) or moderate (50% to 74%) agreement (Consider). RESULTS Large germline panels and somatic testing were recommended for metastatic PCA. Reflex testing—initial testing of priority genes followed by expanded testing—was suggested for multiple scenarios. Metastatic disease or family history suggestive of hereditary PCA was recommended for GT. Additional family history and pathologic criteria garnered moderate consensus. Priority genes to test for metastatic disease treatment included BRCA2, BRCA1, and mismatch repair genes, with broader testing, such as ATM, for clinical trial eligibility. BRCA2 was recommended for active surveillance discussions. Screening starting at age 40 years or 10 years before the youngest PCA diagnosis in a family was recommended for BRCA2 carriers, with consideration in HOXB13, BRCA1, ATM, and mismatch repair carriers. Collaborative (point-of-care) evaluation models between health care and genetic providers was endorsed to address the genetic counseling shortage. The genetic evaluation framework included optimal pretest informed consent, post-test discussion, cascade testing, and technology-based approaches. CONCLUSION This multidisciplinary, consensus-driven PCA genetic implementation framework provides novel guidance to clinicians and patients tailored to the precision era. Multiple research, education, and policy needs remain of importance.