Racial Differences in Clinical Outcomes for Metastatic Renal Cell Carcinoma Patients Treated With Immune-Checkpoint Blockade

Genomic ancestry in kidney cancer: Correlations with clinical and molecular features

INTRODUCTION

Genetic ancestry (GA) refers to population hereditary patterns that contribute to phenotypic differences seen among race/ethnicity groups, and differences among GA groups may highlight unique biological determinants that add to our understanding of health care disparities.

METHODS

A retrospective review of patients with renal cell carcinoma (RCC) was performed and correlated GA with clinicopathologic, somatic, and germline molecular data. All patients underwent next-generation sequencing of normal and tumor DNA using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets, and contribution of African (AFR), East Asian (EAS), European (EUR), Native American, and South Asian (SAS) ancestry was inferred through supervised ADMIXTURE. Molecular data was compared across GA groups by Fisher exact test and Kruskal-Wallis test.

RESULTS

In 953 patients with RCC, the GA distribution was: EUR (78%), AFR (4.9%), EAS (2.5%), SAS (2%), Native American (0.2%), and Admixed (12.2%). GA distribution varied by tumor histology and international metastatic RCC database consortium disease risk status (intermediate-poor: EUR 58%, AFR 88%, EAS 74%, and SAS 73%). Pathogenic/likely pathogenic germline variants in cancer-predisposition genes varied (16% EUR, 23% AFR, 8% EAS, and 0% SAS), and most occurred in CHEK2 in EUR (3.1%) and FH in AFR (15.4%). In patients with clear cell RCC, somatic alteration incidence varied with significant enrichment in BAP1 alterations (EUR 17%, AFR 50%, SAS 29%; p = .01). Comparing AFR and EUR groups within The Cancer Genome Atlas, significant differences were identified in angiogenesis and inflammatory pathways.

CONCLUSION

Differences in clinical and molecular data by GA highlight population-specific variations in patients with RCC. Exploration of both genetic and nongenetic variables remains critical to optimize efforts to overcome health-related disparities.

Biomarkers and factors in small cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

OBJECTIVE

The aim of this meta-analysis was to summarize the available results of immunotherapy predictors for small cell lung cancer (SCLC) and to provide evidence-based information for their potential predictive value of efficacy.

METHODS

We searched PubMed, EMBASE, Web of Science, The Cochrane Library, and ClinicalTrials (from January 1, 1975 to November 1, 2021). The hazard ratios (HR) and its 95% confidence intervals (CIs) and tumor response rate of the included studies were extracted.

RESULTS

Eleven studies were eventually included and the pooled results showed that programmed cell death ligand 1 (PD-L1) positive: objective response rate (ORR) (relative risk [RR] = 1.39, 95% CI [0.48, 4.03], p = 0.54), with high heterogeneity (p = 0.05, I²  = 56%); disease control rate [DCR] (RR = 1.31, 95% CI [0.04, 38.57], p = 0.88), with high heterogeneity (p = 0.04, I²  = 75%); overall survival (OS) (HR = 0.89, 95% CI [0.74, 1.07], p = 0.22); and progression-free survival (PFS) (HR = 0.83, 95% CI [0.59, 1.16], p = 0.27), with high heterogeneity (p = 0.005, I²  = 73.1%). TMB-High (TMB-H): OS (HR = 0.86, 95% CI [0.74, 1.00], p = 0.05); PFS (HR = 0.71, 95% CI [0.6, 0.85], p < 0.001). Lactate dehydrogenase (LDH) >upper limit of normal (ULN): OS (HR = 0.95, 95% CI [0.81, 1.11], p = 0.511). Asian patients: OS (HR = 0.87, 95% CI [0.72, 1.04], p = 0.135); White/Non-Asian patients: OS (HR = 0.83, 95% CI [0.76, 0.90], p < 0.001). Liver metastasis patients: OS (HR = 0.93, 95% CI [0.83, 1.05], p = 0.229); PFS (HR = 0.84, 95% CI [0.67, 1.06], p = 0.141). Central nervous system (CNS) metastasis patients: OS (HR = 0.91, 95% CI [0.71, 1.17], p = 0.474); PFS (HR = 1.03, 95% CI [0.66, 1.60], p = 0.903).

CONCLUSION

The available research results do not support the recommendation of PD-L1 positive and TMB-H as predictors for the application of immune checkpoint inhibitors (ICIs) in SCLC patients. LDH, baseline liver metastasis and CNS metastasis may be used as markers/influencing factors for predicting the efficacy of ICIs in SCLC patients. Non-Asian SCLC patients had better efficacy with ICIs in our results.

Baseline Neutrophil-to-Eosinophil Ratio Is Associated with Outcomes in Metastatic Renal Cell Carcinoma Treated with Immune Checkpoint Inhibitors

BACKGROUND

Biomarkers have the potential to guide treatment selection and clinical care in metastatic renal cell carcinoma (mRCC) in an expanding treatment landscape. We report baseline neutrophil-to-eosinophil ratios (NER) in patients with mRCC treated with immune checkpoint inhibitors (CPIs) and their association with clinical outcomes.

METHODS

We conducted a retrospective review of patients with mRCC treated with CPIs at Winship Cancer Institute from 2015 to 2020 in the United States of America (USA). Demographics, disease characteristics, and laboratory data, including complete blood counts (CBC) were described at the initiation of CPIs. Clinical outcomes were measured as overall survival (OS), progression-free survival (PFS), and clinical benefit (CB) associated with baseline lab values.

RESULTS

A total of 184 patients were included with a median follow-up time of 25.4 months. Patients with baseline NER were categorized into high or low subgroups; high group was defined as NER >49.2 and low group was defined as NER <49.2 with 25% of patients in the high NER group. Univariate analyses (UVA) and multivariable analyses (MVA) identified decreased overall survival (OS) associated with elevated NER. In MVA, patients with a high baseline NER group had a hazard ratio (HR) of 1.68 (95%CI, 1.01-2.82, P = .048) for OS; however, there was no significant difference between groups for PFS. Clinical benefit was seen in 47.3% of patients with low baseline NER and 40% with high NER.

CONCLUSIONS

We conclude that elevated baseline NER may be associated with worse clinical outcomes in mRCC. Although results require further validation, NER is a feasible biomarker in patients with CPI-treated mRCC.