A Panel-Based Mutational Signature of Mismatch Repair Deficiency is Associated With Durable Response to Pembrolizumab in Metastatic Castration-Resistant Prostate Cancer

INTRODUCTION/BACKGROUND

Immune checkpoint inhibitors (ICIs) have limited efficacy in prostate cancer (PCa). Better biomarkers are needed to predict responses to ICIs. We sought to demonstrate that a panel-based mutational signature identifies mismatch repair (MMR) deficient (MMRd) PCa and is a biomarker of response to pembrolizumab.

PATIENTS AND METHODS

Clinico-genomic data was obtained for 2664 patients with PCa sequenced at Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering (MSK). Clinical outcomes were collected for patients with metastatic castration-resistant PCa (mCRPC) treated with pembrolizumab at DFCI. SigMA was used to characterize tumors as MMRd or MMR proficient (MMRp). The concordance between MMRd with microsatellite instability (MSI-H) was assessed. Radiographic progression-free survival (rPFS) and overall survival (OS) were collected for patients treated with pembrolizumab. Event-time distributions were estimated using Kaplan-Meier methodology.

RESULTS

Across both cohorts, 100% (DFCI: 12/12; MSK: 43/43) of MSI-H tumors were MMRd. However, 14% (2/14) and 9.1% (6/66) of MMRd tumors in the DFCI and MSK cohorts respectively were microsatellite stable (MSS), and 26% (17/66) were MSI-indeterminate in the MSK cohort. Among patients treated with pembrolizumab, those with MMRd (n = 5) versus MMRp (n = 14) mCRPC experienced markedly improved rPFS (HR = 0.088, 95% CI: 0.011-0.70; P = .0064) and OS (HR = 0.11, 95% CI: 0.014-0.80; P = .010) from start of treatment. Four patients with MMRd experienced remissions of >= 2.5 years.

CONCLUSION

SigMA detects additional cases of MMRd as compared to MSI testing in PCa and identifies patients likely to experience durable response to pembrolizumab.

Molecular markers of metastatic disease in KRAS-mutant lung adenocarcinoma

BACKGROUND

Prior studies characterized the association of molecular alterations with treatment-specific outcomes in KRAS-mutant (KRASMUT) lung adenocarcinoma (LUAD). Less is known about the prognostic role of molecular alterations and their associations with metastatic disease.

PATIENTS AND METHODS

We analyzed clinicogenomic data from 1817 patients with KRASMUT LUAD sequenced at the Dana-Farber Cancer Institute (DFCI) and Memorial Sloan Kettering Cancer Center (MSKCC). Patients with metastatic (M1) and nonmetastatic (M0) disease were compared. Transcriptomic data from The Cancer Genome Atlas (TCGA) were investigated to characterize the biology of differential associations with clinical outcomes. Organ-specific metastasis was associated with overall survival (OS).

RESULTS

KEAP1 (DFCI: OR = 2.3, q = 0.04; MSKCC: OR = 2.2, q = 0.00027) and SMARCA4 mutations (DFCI: OR = 2.5, q = 0.06; MSKCC: OR = 2.6, q = 0.0021) were enriched in M1 versus M0 tumors. On integrative modeling, NRF2 activation was the genomic feature most associated with OS. KEAP1 mutations were enriched in M1 versus M0 tumors independent of STK11 status (KEAP1MUT/STK11WT: DFCI OR = 3.0, P = 0.0064; MSKCC OR = 2.0, P = 0.041; KEAP1MUT/STK11MUT: DFCI OR = 2.3, P = 0.0063; MSKCC OR = 2.5, P = 3.6 × 10-05); STK11 mutations without KEAP1 loss were not associated with stage (KEAP1WT/STK11MUT: DFCI OR = 0.97, P = 1.0; MSKCC OR = 1.2, P = 0.33) or outcome. KEAP1/KRAS-mutated tumors with and without STK11 mutations exhibited high functional STK11 loss. The negative effects of KEAP1 were compounded in the presence of bone (HR = 2.3, P = 4.4 × 10-14) and negated in the presence of lymph node metastasis (HR = 1.0, P = 0.91).

CONCLUSIONS

Mutations in KEAP1 and SMARCA4, but not STK11, were associated with metastatic disease and poor OS. Functional STK11 loss, however, may contribute to poor outcomes in KEAP1MUT tumors. Integrating molecular data with clinical and metastatic-site annotations can more accurately risk stratify patients.

Addition of Germline Testing to Tumor-Only Sequencing Improves Detection of Pathogenic Germline Variants in Men With Advanced Prostate Cancer

PURPOSE

Guidelines recommend somatic and germline testing for men with advanced prostate cancer (PCa). Barriers to widespread implementation result in underutilization of germline testing. Somatic testing alone risks missing pathogenic germline variants (PGVs). We sought to determine whether the addition of germline testing to tumor-only sequencing improves detection of PGVs in men with advanced PCa. Secondarily, we sought to define the added value of combining somatic and germline testing to optimize detection of clinically actionable alterations.

PATIENTS AND METHODS

We analyzed results of independent germline testing and tumor-only sequencing from 100 men with advanced PCa from a prospective clinical trial (ClinicalTrials.gov identifier: NCT03328091). The primary outcome was the proportion of PGVs not reported with tumor-only sequencing. The secondary outcome was the association of locus-specific loss of heterozygosity for PGVs in homologous recombination genes with clinical-genomic features.

RESULTS

In the 100 men who underwent germline testing and tumor-only sequencing, 24 PGVs were identified, 17 of which were clinically actionable, in 23 patients. Tumor-only sequencing failed to report four (17%) of the PGVs. One additional PGV (4.2%) had variant allele frequency on tumor-sequencing below the threshold for follow-up germline testing. When integrating tumor-only sequencing with germling testing results, 33% of patients harbored clinically actionable alterations. Rates of locus-specific loss of heterozygosity were higher for BRCA2 PGVs in castration-resistant PCa than PGVs in other homologous recombination genes in hormone-sensitive PCa (P = .029).

CONCLUSION

Tumor-only sequencing failed to report more than 20% of PGVs in men with advanced PCa. These findings strongly support guideline recommendations for universal germline and somatic testing in this population. Combining tumor and germline sequencing doubled the chance of detecting a clinically actionable alteration.

Abstract 2181: Genomic correlates of Metastasis in KRAS mutant lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is a disease classified by molecular markers. In KRAS-mutant LUAD, STK11 and KEAP1 mutations are associated with decreased overall survival (OS), but predictors of metastasis have been poorly defined. In this study, we identify clinical and genomic predictors of metastatic KRAS-mutant LUAD.

Methods: Patients with KRAS-mutant LUAD profiled by targeted next generation sequencing (OncoPanel) were included. Stage, histology, recurrence-free and overall survival were assessed. Clinical and genomic features between metastatic vs non-metastatic samples were compared. KRAS-mutant LUAD samples profiled using MSK-IMPACT in the AACR GENIE database were used to validate our findings. Continuous variables were compared using the Mann-Whitney U test and categorical variables were compared using the Fisher’s Exact test. Survival analysis was performed using the Cox Proportional Hazards model. WExT was used to identify co-occurring and mutually exclusive genetic alterations. Benjamini-Hochberg was used to correct for multiple comparisons. P-values < 0.05 and q-values < 0.10 were considered significant.

Results: In the OncoPanel cohort (metastatic n=290; non-metastatic n=324), tumor mutational burden (TMB) (p = .001) and KEAP1 mutations (q = 0.05) were enriched in metastatic samples, while NFKBIA amplifications (q = 0.07) were enriched in non-metastatic samples. KEAP1/STK11 mutations significantly co-occurred (q < 1e-8). Compared to double wild-type samples: KEAP1/STK11 co-mutations were significantly enriched in metastatic samples (n = 72, p = 0.0002, OR 3.4); KEAP1-mutant samples trended towards enrichment in metastatic samples, (n = 21,p = 0.07, OR 2.47); STK11 mutations did not associate with stage (n = 53, p = 0.88, OR = 0.94). In multivariable survival analysis, metastasis (p < 0.005), KEAP1 mutation (p=0.01), and STK11 mutation (p=0.02) were associated with worse OS.

In the MSK-IMPACT validation cohort (metastatic site n=417, primary site n = 781), KEAP1 was the only gene enriched in metastatic samples (q < 0.001) at q < 0.05. Compared to double wild type samples: KEAP/STK11 co-mutations (n=138, p < 0.0001, OR 2.1) and KEAP1 mutations (n=59, p = 0.04, OR 1.77) were enriched in metastatic samples; STK11-mutations did not associate with metastasis (n = 190, p = 0.34, OR 0.83). Other predictors of metastasis included Fraction Genome Altered (FGA) (p < 1e-5), TMB (p < 1e-5), and CDKN2A/B deletions (q < 0.003).

Conclusion: While both KEAP1 and STK11 mutations are associated with decreased OS in KRAS-mutant LUAD, we find in two independent cohorts that only KEAP1 mutations and KEAP1/STK11 co-mutations, but not STK11 mutations, are associated with metastasis. We also found that FGA, TMB, CDKN2A/B deletions are strongly associated with metastasis. Further research is necessary to understand the influence of KEAP1 mutations, independent of and in-conjunction with STK11 mutations, on metastasis.

Citation Format: Daniel Boiarsky, Christine A. Lydon, Emily Chambers, Pasi A. Janne, Mark M. Awad, Eliezer M. Van Allen, David Barbie, Natalie I. Vokes. Genomic correlates of Metastasis in KRAS mutant lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2181.

Post-stroke rehabilitation: Factors predicting discharge to acute versus subacute rehabilitation facilities

The aim of this study was to examine predictors of discharge of hospitalized stroke patients to either an acute inpatient rehabilitation facility (IRF) or subacute skilled nursing facility (SNF).A retrospective cohort study was done in a large multicampus urban academic medical center of individuals hospitalized for stroke between January 1, 2015 and December 31, 2015 and who were discharged to either an IRF (n = 84) or SNF (n = 59). A set of characteristics and scales were collected on each patient and assessed using univariate and multivariate regression analyses.Although univariate analyses revealed multiple measures were associated with discharge destination, the most predictive multivariate logistic regression model for discharge to SNF incorporated age (odds ratio [OR] = 1.09, 95% confidence interval [CI], 1.05-1.13), premorbid physical disability (OR 7.52, 95% CI 1.66-34.14), and inability to ambulate before discharge (OR 5.84, 95% CI 2.01-16.92) with an overall c-statistic of 0.85.Increasing age, premorbid physical disability, and inability to ambulate increase the overall likelihood of discharge to a SNF. These findings need to be replicated in larger samples to determine whether they are generalizable.