Immune-Related Adverse Events After Immune Checkpoint Inhibitors for Melanoma Among Older Adults.

Importance: Immune checkpoint inhibitors (ICIs) have improved survival in patients with advanced melanoma but can be associated with a spectrum of immune-related adverse events (AEs), including both autoimmune-related AEs and other immune-related inflammatory AEs. These associations have primarily been evaluated in clinical trials that include highly selected patients, with older adults often underrepresented. Objective: To evaluate the association between use of ICIs and immune-related AEs (autoimmune and other immune related) among older patients with cutaneous melanoma. Design, Setting, and Participants: A population-based cohort study was conducted from January 1, 2011, to December 31, 2015. Data were analyzed from January 31 to May 31, 2021. With use of a linked database of Medicare claims and Surveillance, Epidemiology, and End Results (SEER) Program population-based cancer registries, patients of White race diagnosed with stages II-IV or unknown (American Joint Committee on Cancer, AJCC Cancer Staging Manual 6th edition) first primary cutaneous melanoma during 2011-2015, as reported to SEER, and followed up through December 31, 2015, were identified. Exposures: Immune checkpoint inhibitors for treatment of melanoma. Main Outcomes and Measures: The association between ICIs and immune-related AEs ascertained from Medicare claims data was estimated using multivariable Cox regression with hazard ratios (HRs) and 95% CIs and with cumulative incidence accounting for competing risk of death. Results: The study included 4489 patients of White race with first primary melanoma (3002 men [66.9%]; median age, 74.9 [range, 66.0-84.9] years). During follow-up (median, 1.4 [range, 0-5.0] years), 1576 patients (35.1%) had an immune-related AE on a Medicare claim. Use of ICIs (reported for 418 patients) was associated with autoimmune-related AEs (HR, 2.5; 95% CI, 1.6-4.0), including primary adrenal insufficiency (HR, 9.9; 95% CI, 4.5-21.5) and ulcerative colitis (HR, 8.6; 95% CI, 2.8-26.3). Immune checkpoint inhibitors also were associated with other immune-related AEs (HR, 2.2; 95% CI, 1.7-2.8), including Cushing syndrome (HR, 11.8; 95% CI, 1.4-97.2), hyperthyroidism (HR, 6.3; 95% CI, 2.0-19.5), hypothyroidism (HR, 3.8; 95% CI, 2.4-6.1), hypopituitarism (HR, 19.8; 95% CI, 5.4-72.9), other pituitary gland disorders (HR, 6.0; 95% CI, 1.2-30.2), diarrhea (HR, 3.5; 95% CI, 2.5-4.9), and sepsis or septicemia (HR, 2.2; 95% CI, 1.4-3.3). Most associations were pronounced within 6 months following the first ICI claim and comparable with or without a baseline history of autoimmune disease. The cumulative incidence at 6 months following the first ICI claim was 13.7% (95% CI, 9.7%-18.3%) for autoimmune-related AEs and 46.8% (95% CI, 40.7%-52.7%) for other immune-related AEs. Conclusions and Relevance: In this cohort study of older adults with melanoma, ICIs were associated with autoimmune-related AEs and other immune-related AEs. Although some findings were consistent with clinical trials of ICIs, others warrant further investigation. As ICI use continues to expand rapidly, ongoing investigation of the spectrum of immune-related AEs may optimize management of disease in patients.

Joint IARC/NCI International Cancer Seminar Series Report: expert consensus on future directions for ovarian carcinoma research.

Recently, ovarian cancer research has evolved considerably because of the emerging recognition that rather than a single disease, ovarian carcinomas comprise several different histotypes that vary by etiologic origin, risk factors, molecular profiles, therapeutic approaches and clinical outcome. Despite significant progress in our understanding of the etiologic heterogeneity of ovarian cancer, as well as important clinical advances, it remains the eighth most frequently diagnosed cancer in women worldwide and the most fatal gynecologic cancer. The International Agency for Research on Cancer and the United States National Cancer Institute jointly convened an expert panel on ovarian carcinoma to develop consensus research priorities based on evolving scientific discoveries. Expertise ranged from etiology, prevention, early detection, pathology, model systems, molecular characterization and treatment/clinical management. This report summarizes the current state of knowledge and highlights expert consensus on future directions to continue advancing etiologic, epidemiologic and prognostic research on ovarian carcinoma.

Racial Disparities in Lung Cancer Survival: The Contribution of Stage, Treatment, and Ancestry.

INTRODUCTION: Lung cancer is a leading cause of cancer-related death worldwide. Racial disparities in lung cancer survival exist between blacks and whites, yet they are limited by categorical definitions of race. We sought to examine the impact of African ancestry on overall survival among blacks and whites with NSCLC cases. METHODS: Incident cases of NSCLC in blacks and whites from the prospective Southern Community Cohort Study (N = 425) were identified through linkage with state cancer registries in 12 southern states. Vital status was determined by linkage with the National Death Index and Social Security Administration. We evaluated the impact of African ancestry (as estimated by using genome-wide ancestry-informative markers) on overall survival by calculating the time-dependent area under the curve (AUC) for Cox proportional hazards models, adjusting for relevant covariates such as stage and treatment. We replicated our findings in an independent population of NSCLC cases in blacks. RESULTS: Global African ancestry was not significantly associated with overall survival among NSCLC cases. There was no change in model performance when Cox proportional hazards models with and without African ancestry were compared (AUC = 0.79 for each model). Removal of stage and treatment reduced the average time-dependent AUC from 0.79 to 0.65. Similar findings were observed in our replication study. CONCLUSIONS: Stage and treatment are more important predictors of survival than African ancestry is. These findings suggest that racial disparities in lung cancer survival may disappear with similar early detection efforts for blacks and whites.

Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

BACKGROUND: Increasing evidence points to the role of tumor immunologic environment on urothelial bladder cancer prognosis. This effect might be partly dependent on the host genetic context. We evaluated the association of SNPs in inflammation-related genes with non-muscle-invasive bladder cancer (NMIBC) risk-of-recurrence and risk-of-progression. METHODS: We considered 822 NMIBC included in the SBC/EPICURO Study followed-up >10 years. We selected 1,679 SNPs belonging to 251 inflammatory genes. The association of SNPs with risk-of-recurrence and risk-of-progression was assessed using Cox regression single-marker (SMM) and multimarker methods (MMM) Bayes A and Bayesian LASSO. Discriminative abilities of the models were calculated using the c index and validated with bootstrap cross-validation procedures. RESULTS: While no SNP was found to be associated with risk-of-recurrence using SMM, three SNPs in TNIP1, CD5, and JAK3 showed very strong association with posterior probabilities >90% using MMM. Regarding risk-of-progression, one SNP in CD3G was significantly associated using SMM (HR, 2.69; P = 1.55 × 10(-5)) and two SNPs in MASP1 and AIRE, showed a posterior probability ≥80% with MMM. Validated discriminative abilities of the models without and with the SNPs were 58.4% versus 60.5% and 72.1% versus 72.8% for risk-of-recurrence and risk-of-progression, respectively. CONCLUSIONS: Using innovative analytic approaches, we demonstrated that SNPs in inflammatory-related genes were associated with NMIBC prognosis and that they improve the discriminative ability of prognostic clinical models for NMIBC. IMPACT: This study provides proof of concept for the joint effect of genetic variants in improving the discriminative ability of clinical prognostic models. The approach may be extended to other diseases. Cancer Epidemiol Biomarkers Prev; 25(7); 1144-50. ©2016 AACR.

Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

Assessment of copy number variation using the Illumina Infinium 1M SNP-array: a comparison of methodological approaches in the Spanish Bladder Cancer/EPICURO study.

High-throughput single nucleotide polymorphism (SNP)-array technologies allow to investigate copy number variants (CNVs) in genome-wide scans and specific calling algorithms have been developed to determine CNV location and copy number. We report the results of a reliability analysis comparing data from 96 pairs of samples processed with CNVpartition, PennCNV, and QuantiSNP for Infinium Illumina Human 1Million probe chip data. We also performed a validity assessment with multiplex ligation-dependent probe amplification (MLPA) as a reference standard. The number of CNVs per individual varied according to the calling algorithm. Higher numbers of CNVs were detected in saliva than in blood DNA samples regardless of the algorithm used. All algorithms presented low agreement with mean Kappa Index (KI) <66. PennCNV was the most reliable algorithm (KI(w=) 98.96) when assessing the number of copies. The agreement observed in detecting CNV was higher in blood than in saliva samples. When comparing to MLPA, all algorithms identified poorly known copy aberrations (sensitivity = 0.19-0.28). In contrast, specificity was very high (0.97-0.99). Once a CNV was detected, the number of copies was truly assessed (sensitivity >0.62). Our results indicate that the current calling algorithms should be improved for high performance CNV analysis in genome-wide scans. Further refinement is required to assess CNVs as risk factors in complex diseases.

A custom 148 gene-based resequencing chip and the SNP explorer software: new tools to study antibody deficiency.

Hyper-IgM syndrome and Common Variable Immunodeficiency are heterogeneous disorders characterized by a predisposition to serious infection and impaired or absent neutralizing antibody responses. Although a number of single gene defects have been associated with these immune deficiency disorders, the genetic basis of many cases is not known. To facilitate mutation screening in patients with these syndromes, we have developed a custom 300-kb resequencing array, the Hyper-IgM/CVID chip, which interrogates 1,576 coding exons and intron-exon junction regions from 148 genes implicated in B-cell development and immunoglobulin isotype switching. Genomic DNAs extracted from patients were hybridized to the array using a high-throughput protocol for target sequence amplification, pooling, and hybridization. A Web-based application, SNP Explorer, was developed to directly analyze and visualize the single nucleotide polymorphism (SNP) annotation and for quality filtering. Several mutations in known disease-susceptibility genes such as CD40LG, TNFRSF13B, IKBKG, AICDA, as well as rare nucleotide changes in other genes such as TRAF3IP2, were identified in patient DNA samples and validated by direct sequencing. We conclude that the Hyper-IgM/CVID chip combined with SNP Explorer may provide a cost-effective tool for high-throughput discovery of novel mutations among hundreds of disease-relevant genes in patients with inherited antibody deficiency.

Genome-wide SNP typing reveals signatures of population history.

Single-nucleotide polymorphism (SNP) arrays have become a popular technology for disease-association studies, but they also have potential for studying the genetic differentiation of human populations. Application of the Affymetrix GeneChip Human Mapping 500K Array Set to a population of 102 individuals representing the major ethnic groups in the United States (African, Asian, European, and Hispanic) revealed patterns of gene diversity and genetic distance that reflected population history. We analyzed allelic frequencies at 388,654 autosomal SNP sites that showed some variation in our study population and 10% or fewer missing values. Despite the small size (23-31 individuals) of each subpopulation, there were no fixed differences at any site between any two subpopulations. As expected from the African origin of modern humans, greater gene diversity was seen in Africans than in either Asians or Europeans, and the genetic distance between the Asian and the European populations was significantly lower than that between either of these two populations and Africans. Principal components analysis applied to a correlation matrix among individuals was able to separate completely the major continental groups of humans (Africans, Asians, and Europeans), while Hispanics overlapped all three of these groups. Genes containing two or more markers with extraordinarily high genetic distance between subpopulations were identified as candidate genes for health differences between subpopulations. The results show that, even with modest sample sizes, genome-wide SNP genotyping technologies have great promise for capturing signatures of gene frequency difference between human subpopulations, with applications in areas as diverse as forensics and the study of ethnic health disparities.