Dataset Information

HLA Genotyping in Synovial Sarcoma: Identifying HLA-A*02 and Its Association with Clinical Outcome.

ABSTRACT:

Purpose

To determine if a targeted exome panel utilizing matched normal DNA can accurately detect germline and somatic HLA genes in patients with synovial sarcoma (SS) and whether select HLA-A*02 genotypes are prognostic or predictive of outcome in metastatic SS.

Experimental design

Patients with metastatic SS consented to HLA typing by a Clinical Laboratory Improvement Amendments (CLIA)-certified test to determine eligibility for a clinical trial of NY-ESO-1-specific engineered T cells restricted to carriers of HLA-A*02:01, -A*02:05, or -A*02:06 (HLA-A*02 eligible). HLA genotype was determined from Memorial Sloan Kettering Integrated Molecular Profiling of Actionable Cancer Targets (MSK-IMPACT), where feasible, and somatic loss of heterozygosity (LOH) in HLA alleles was identified. Overall survival (OS) was estimated and stratified by HLA-A*02 eligibility.

Results

A total of 23 patients had HLA genotyping by a CLIA-certified lab and MSK-IMPACT. Ninety percent (108/110) of the sequenced alleles were concordant between IMPACT and the outside lab. LOH of HLA genes was detected in three tumors, one had loss of HLA-A*02:01. In total, 66 patients were screened for T-cell therapy and 20 (30%) were HLA-A*02 eligible on outside testing. Univariate analysis of OS from the time of metastasis found HLA-A*02 eligibility was marginally associated with shorter OS [HR = 1.95; 95% confidence interval (CI), 0.995-3.813; P = 0.052]. On multivariate analysis, older age and larger tumor size, but not HLA-A*02 eligibility, were significantly associated with decreased OS. HLA-A*02 eligibility did not impact OS after chemotherapy or pazopanib in the metastatic setting.

Conclusions

Targeted gene panels like MSK-IMPACT may accurately report HLA type and identify loss of somatic HLA alleles. In a multivariable model, HLA-A*02 eligibility was not significantly associated with OS in patients with metastatic SS.

SUBMITTER: Rosenbaum E

PROVIDER: S-EPMC7572879 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 2019 (COVID-19) was announced as an outbreak by the World Health Organization (WHO) in January 2020 and as a pandemic in March 2020. The majority of infected individuals have experienced no or only mild symptoms, ranging from fully asymptomatic cases to mild pneumonic disease. However, a minority of infected individuals develop severe respiratory symptoms. The objective of this study was to identify susceptible HLA alleles and clinical markers that can be used in risk prediction model for the early identification of severe COVID-19 among hospitalized COVID-19 patients. A total of 137 patients with mild COVID-19 (mCOVID-19) and 53 patients with severe COVID-19 (sCOVID-19) were recruited from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan for the period of February-August 2020. High-resolution sequencing-based typing for eight HLA genes was performed using next-generation sequencing. In the HLA association studies, HLA-A*11:01:01:01 [Pc = 0.013, OR = 2.26 (1.27-3.91)] and HLA-C*12:02:02:01-HLA-B*52:01:01:02 [Pc = 0.020, OR = 2.25 (1.24-3.92)] were found to be significantly associated with the severity of COVID-19. After multivariate analysis controlling for other confounding factors and comorbidities, HLA-A*11:01:01:01 [P = 3.34E-03, OR = 3.41 (1.50-7.73)], age at diagnosis [P = 1.29E-02, OR = 1.04 (1.01-1.07)] and sex at birth [P = 8.88E-03, OR = 2.92 (1.31-6.54)] remained significant. The area under the curve of the risk prediction model utilizing HLA-A*11:01:01:01, age at diagnosis, and sex at birth was 0.772, with sensitivity of 0.715 and specificity of 0.717. To the best of our knowledge, this is the first article that describes associations of HLA alleles with COVID-19 at the 4-field (highest) resolution level. Early identification of potential sCOVID-19 could help clinicians prioritize medical utility and significantly decrease mortality from COVID-19.