Donor KIR B Genotype Improves Progression-Free Survival of Non-Hodgkin Lymphoma Patients Receiving Unrelated Donor Transplantation

Donor killer immunoglobulin-like receptor (KIR) genotypes are associated with relapse protection and survival after allotransplantation for acute myelogenous leukemia. We examined the possibility of a similar effect in a cohort of 614 non-Hodgkin lymphoma (NHL) patients receiving unrelated donor (URD) T cell-replete marrow or peripheral blood grafts. Sixty-four percent (n = 396) of donor-recipient pairs were 10/10 allele HLA matched and 26% were 9/10 allele matched. Seventy percent of donors had KIR B/x genotype; the others had KIR A/A genotype. NHL patients receiving 10/10 HLA-matched URD grafts with KIR B/x donors experienced significantly lower relapse at 5 years (26%; 95% confidence interval [CI], 21% to 32% versus 37%; 95% CI, 27% to 46%; P = .05) compared with KIR A/A donors, resulting in improved 5-year progression-free survival (PFS) (35%; 95% CI, 26% to 44% versus 22%; 95% CI, 11% to 35%; P = .007). In multivariate analysis, use of KIR B/x donors was associated with significantly reduced relapse risk (relative risk [RR], .63, P = .02) and improved PFS (RR, .71, P = .008). The relapse protection afforded by KIR B/x donors was not observed in HLA-mismatched transplantations and was not specific to any particular KIR-B gene. Selecting 10/10 HLA-matched and KIR B/x donors should benefit patients with NHL receiving URD allogeneic transplantation

Molecular, immunologic, and clinicodemographic landscape of MYC-amplified (MYCamp) advanced prostate cancer (PCa)

5041 Background: The MYC oncogene is one of the most commonly amplified genes in PCa, contributes to androgen independent growth, and is potentially targetable. We sought to define the molecular, immunologic, and clinicodemographic landscape of MYCamp in advanced PCa to better understand progression and establish rationale for personalized treatments and combinations. Methods: Hybrid capture-based comprehensive genomic profiling (CGP) was performed on tumor samples from predominantly advanced PCa samples. MYCamp was defined as copy number (CN) ≥6. PD-L1 IHC was performed using Dako 22C3. A subset of patients (pts) with advanced PCa were selected from the Flatiron Health- Foundation Medicine (FM) clinicogenomic database (CGDB), a nationwide de-identified EHR-derived clinical DB linked to FM CGP data for pts treated from 01/2011-12/2020. The de-identified data originated from approximately 280 US cancer clinics (̃800 sites of care). Results: The genomic profiles of 12,528 tissue samples from unique PCa pts (including hormone sensitive and castrate resistant) were evaluated. MYCamp was detected in 10.6%, with a median MYC CN of 8. Median age was 67 years (67 for MYCwt versus 68 for MYCamp). MYCamp occurred at a higher frequency in men with African (N = 190/1,473, 12.9%) versus European (N = 996/9,796, 10.2%) ancestry (P = 0.002), was more frequent in metastatic biopsy sites vs primary (15.7% vs 6.2%, P 15 was enriched for PD-L1 positivity (26.1%) compared with MYCwt (9.8%) or MYCamp CN 6-15 (11.5%) (CN > 15 vs wt P = 0.025). In pts with MYCamp vs MYCwt PCa AR, RAD21, PTEN, CCND1, ZNF703, FGF19, FGFR1, and FGF3 each had significantly higher rates of CN changes (all p 0) from PCa pts MYCamp was detected in 2.0% (28/1,402), and in 4.5% (20/445) with cTF > 20%. Among evaluable PCa pts in the CGDB, (67 MYCamp and 658 MYCwt) MYCamp did not significantly impact treatment decisions, with the majority receiving novel hormone therapies (35.8% MYCamp vs. 31.5% MYCwt) or chemotherapy containing regimens (37.3% MYCamp vs. 27.7% MYCwt) as first therapy after CGP report. Conclusions: Herein, we report the largest analysis to date of molecular, immunologic, and clinicodemographic features of MYCamp advanced PCa. These findings suggest that MYCamp defines a biologically distinct subset of PCa pts for whom personalized combination treatments utilizing targeted and/or immunotherapies may be effective. Independent cohorts are needed to validate these findings

Ancestral characterization of the genomic landscape, comprehensive genomic profiling utilization, and treatment patterns may inform disparities in advanced prostate cancer: A large-scale analysis

5003 Background: Prostate cancer (PCa) incidence, mortality, and outcomes vary widely across race/ethnicity. The underlying drivers of these differences are multifactorial, including systemic barriers that lead to wide variation in access to care including genomic and precision medicine. Men of African ancestry (AFR) are particularly underrepresented in genomic and precision medicine studies. Therefore, we sought to comprehensively assess patterns of gene alterations, comprehensive genomic profiling (CGP) utilization, and treatment patterns in a large, diverse advanced PCa cohort. Methods: 11,741 PCa patients with CGP, as part of routine clinical care (Foundation Medicine Inc., FMI) were evaluated for their genomic landscape. Predominant ancestry was inferred using a SNP-based approach (Connelly et al, AACR 2018). Independently, the US-based de-identified Flatiron Health (FH)-FMI clinico-genomic database (CGDB) of 897 evaluable PCa patients was also queried. Clinical characteristics and treatment selections were described for patients who received metastatic or castrate-resistant diagnosis between 1/2011 and 6/2020. Results: The FMI cohort included 1,422 (12%) men of AFR and 9,244 (79%) men of European ancestry (EUR). Median age was lower in AFR compared with EUR men (64 vs. 67, p < 0.001). TP53 and PTEN alterations and TMPRSS2-ERG rearrangements occurred less frequently in AFR than EUR men (35% vs. 43%, 21% vs. 33%, 15% vs. 33% respectively, p < 0.05). In contrast, alterations in SPOP (11.9% vs. 7.3%), CDK12 (10.0% vs. 5.2%), CCND1 (6.0% vs. 3.8%), KMT2D (7.7% vs. 5.1%), HGF (4.1% vs. 2.5%), and MYC (13.4% vs. 10.6%) were enriched in the AFR cohort (p < 0.05). Alteration frequency in BRCA1/2, AR, DNA damage response pathway genes, and actionable genes with therapy implications, were similar across ancestry. Of note, BRAF alterations were slightly enriched in AFR (5.0% vs. 3.2%, p < 0.05). In the CGDB cohort (79 AFR, 762 EUR), AFR men received a median of 2 lines of therapy prior to CGP, compared to 1 line for EUR men. Notably, the proportion of patients receiving immunotherapy and PARPi was similar across ancestry, however AFR men were less likely to receive clinical study drug compared with EUR men (11% vs 30%, p < 0.001), even among men with actionable alterations (1% vs 6%, p < 0.001). Conclusions: To our knowledge, this study encompasses the largest cohort, particularly of AFR men in a genomic study, that defines CGP utilization, the genomic landscape and therapeutic implications of CGP in PCa across ancestry. Overall, there were largely similar rates of actionable gene alterations across ancestry. Notably, AFR men were less likely to receive CGP earlier in their treatment course, and less likely to be treated on clinical trials, which could impact the genomic landscape, outcomes, and ultimately disparities

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC).

PURPOSE: Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care. Therefore, it is essential to address this unmet need. METHODS: Clinical Genome Resource (ClinGen) Somatic Cancer Clinical Domain Working Group and ClinGen Germline/Somatic Variant Subcommittee, the Cancer Genomics Consortium, and the Variant Interpretation for Cancer Consortium used a consensus approach to develop a standard operating procedure (SOP) for the classification of oncogenicity of somatic variants. RESULTS: This comprehensive SOP has been developed to improve consistency in somatic variant classification and has been validated on 94 somatic variants in 10 common cancer-related genes. CONCLUSION: The comprehensive SOP is now available for classification of oncogenicity of somatic variants