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.

Translational Relevance

The MSK-IMPACT assay, a targeted next-generation sequencing (NGS) panel utilizing matched-normal DNA, was utilized in a real-world cohort of patients with metastatic synovial sarcoma to report HLA genotype. Results were highly concordant with HLA typing performed by a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory outside our institution. HLA typing via NGS can potentially expedite the screening process for patients interested in participating in adoptive T-cell therapy trials restricted to select HLA genotypes. Targeted panels may also detect somatic loss of heterozygosity of HLA-A*02:01, a potential mechanism of resistance to adoptive T-cell therapies that rely on HLA-A*02 expression. As randomized trials of adoptive T-cell strategies are unlikely in a rare disease like synovial sarcoma, we sought to determine the prognostic potential of HLA-A*02-eligible patients who are not treated with engineered T cells.

Synovial sarcoma (SS) is a rare malignancy of mesenchymal origin representing approximately 5% to 10% of soft tissue sarcomas, with an incidence of 1.42 per million U.S. adults (1, 2). It frequently arises in the extremities of young adults in the third and fourth decade and is characterized by a pathognomonic translocation, t(X;18)(p11.2;q11.2) leading to a fusion of SS18 with SSX (3, 4). The prognosis of SS varies depending on the primary tumor site, patient age at diagnosis, tumor grade, size, and diagnosis stage. The estimated 5-year survival of patients with SS is between 55% and 75% (1, 2, 5–8). Although SS may be responsive to chemotherapy, the median overall survival (OS) for patients with locally advanced or metastatic disease is only 15 months, according to one estimate (2).

The standard of care chemotherapy in the first-line setting for patients with unresectable or metastatic SS is an anthracycline or an alkylator (9). In a retrospective study of more than 1,000 patients with advanced SS, the median progression-free survival (PFS) after ifosfamide with or without doxorubicin was 30 weeks, with a median OS of 64 weeks and an overall response rate (ORR) of 34% (10). Patients who progress on cytotoxic chemotherapy are eligible to receive pazopanib, a multitargeted tyrosine kinase inhibitor with activity against the VEGF and platelet-derived growth factor (PDGF) receptors. In a randomized phase III trial versus placebo, the median PFS of patients with SS receiving pazopanib was 4.1 months, compared with 1.0 month in the placebo arm (11). The median OS of Japanese patients with SS treated with pazopanib was 11.2 months (12).

Efforts are underway to develop novel therapies that can induce durable responses in patients with advanced SS refractory to available agents. One promising approach consists of targeting cancer-testis antigens such as NY-ESO-1, an antigen not normally expressed in healthy tissue outside the testis, but heterogeneously expressed in a minority of cancers including SS (13, 14). Approximately 80% of SSs express NY-ESO-1, possibly due to the X-linked translocation that defines the disease (15, 16). Similarly, 88% of SS tumors in one study expressed the MAGE cancer-testis antigen (17).

Select CD8+ T cells can recognize a fragment of NY-ESO-1 bound to the HLA class I molecule on the surface of cancer cells and trigger immune-mediated cancer cell death. High-affinity variants of the T-cell receptor (TCR) that can recognize the immunodominant HLA-A*02-restricted peptide of NY-ESO-1 (amino acids 157–165) have been engineered for use as an adoptive immunotherapy strategy against tumors expressing NY-ESO-1 (18–22). The engineered TCR binds with high affinity to the following HLA class I subtypes when bound to NY-ESO-1: HLA-A*02:01, HLA-A*02:05, and HLA-A*02:06 (herein referred to as HLA-A*02-eligible subtypes). A similar strategy is being utilized to target other cancer-testis antigens, such as MAGE-A4 (23).

The adoptive T-cell therapy trials reported to date are single-arm studies and therefore subject to confounding. One possible confounder is an HLA-A*02-eligible genotype, which in theory could predispose patients to have disparate outcomes compared with a “real-world” population of SS patients with heterogenous HLA genotypes. This study seeks to determine whether HLA-A*02-eligible genotypes, a sine qua non for those treated with engineered T cells, impacts clinical outcome in patients with SS. In addition, we report that a targeted genomic sequencing panel [Memorial Sloan Kettering Integrated Molecular Profiling of Actionable Cancer Targets (MSK-IMPACT)] can successfully be utilized to determine HLA genotype. This is of interest, as the screening process to enroll on adoptive T-cell protocols may require a lengthy wait time to determine eligibility based on HLA testing. As targeted next-generation sequencing (NGS) panels are often utilized in patients with advanced SS, we reason that leveraging this data to determine HLA genotype can facilitate identification of appropriate patients for enrollment on adoptive T-cell protocols.

Patient selection

This study was approved by the Memorial Sloan Kettering Cancer Center (MKSCC) institutional review board. Patients with histologically confirmed SS who provided informed consent to screen for a clinical trial of genetically engineered NY-ESO-1-specific T cells (NCT01343043) at MSKCC were included in this retrospective study. The design of NCT01343043, key eligibility criteria, and the results of the initial cohorts that received adoptive T cells have been described previously (21, 22). The study was conducted in compliance with the Declaration of Helsinki and in accordance with local legal and regulatory requirements and written informed consent was obtained for all participating patients. As part of the trial screening procedures, patients underwent high-resolution HLA testing in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory to determine if they were eligible to receive adoptive T-cell therapy per protocol. Patients who were treated with NY-ESO-1–specific engineered T cells were excluded from this analysis.

Study design

The objectives of this study were to measure HLA genotype utilizing the MSK-IMPACT assay and to determine the prognostic potential of HLA-A*02 status on clinical outcomes in a subset of patients with advanced SS who were not treated with HLA-A*02-specific therapy. Demographic, pathologic, and clinical information were retrieved from the medical record for each patient. The following variables were included: age at diagnosis, sex, SS subtype (monophasic or biphasic), primary tumor location, primary tumor size, use of neoadjuvant or adjuvant chemotherapy and/or radiation, date of unresectability, first recurrence or metastasis, date of initiation of systemic chemotherapy in the metastatic setting, number of systemic therapies used in the metastatic setting, start date of pazopanib, HLA typing via high-resolution testing, and date of death or last contact. The cutoff date for clinical follow-up was August 15, 2019.

HLA typing

A select number of patients included in this study provided informed written consent to participate in MSK-IMPACT, a prospective tumor sequencing initiative that has been described in detail elsewhere (24, 25). MSK-IMPACT is a hybridization capture-based matched tumor-normal sequencing platform that profiles up to 468 genes (depending on the assay version; ref. 25) for mutations, copy number alterations, and select structural variants. HLA genotyping was performed in a research setting using POLYSOLVER (26). Briefly, POLYSOLVER first extracts all reads that are putatively aligned to the HLA locus and then performs a multistep inference that accounts for the aligned reads, base qualities, and observed insert sizes to predict the HLA class I genotypes.

Statistical analyses

Patients were divided into subgroups based on the presence of an HLA-A*02-eligible genotype. Survival analyses were performed on three overlapping sets of patients: the first included all patients from the time of metastatic disease, the second included patients who received doxorubicin or ifosfamide-based treatment in the first-line metastatic setting, and the third included only patients who were treated with pazopanib in the metastatic setting. For the first patient set, OS was defined as the time the patient was considered to have unresectable, recurrent, or metastatic disease until the date of death or last contact; patients who were alive at the time of last contact were censored. A sensitivity analysis was performed within the first patient set that only included patients who consented to screen for the NY-ESO-1–specific T-cell trial within 1 year of developing unresectable, recurrent, or metastatic disease. In the latter two patient sets, OS was defined as the date of first chemotherapy or pazopanib administration until the date of death or last contact; patients who were alive at the time of last contact were censored.

Summary statistics, median and interquartile range, were used to describe continuous variables and count and percent for categorical variables. Wilcoxon rank sum test and Fisher exact test were used to compare continuous and categorical variables, respectively, between groups. Survival outcomes were analyzed using Kaplan–Meier methods and log-rank test were used to associate factors. Univariable and multivariable analysis were performed with Cox proportional hazard regression models for PFS and OS. Multivariable models were selected using backward selection with inclusion criteria of being significant at 0.10 in the univariable analysis. SAS version 9.4 (SAS institute Inc.) was used for all analyses. All tests were two-sided and P < 0.05 was considered significant.

Patient characteristics

Between March 24, 2014 and November 21, 2017, 75 patients consented to screen for a clinical trial of NY-ESO-1–specific engineered T cells. Of the screened patients, 39% (n = 29) tested positive for HLA-A*02:01 (n = 18), HLA-A*02:05 (n = 1), or HLA-A*02:06 (n = 1) by an outside CLIA-certified test. The time to receive outside HLA results, a measure available in all but 2 patients, ranged between 3 and 27 days (median: 8). Nine patients ultimately received treatment with engineered T cells on trial and were excluded from this analysis (Fig. 1; their characteristics are outlined in Supplementary Table S1). Of the 20 patients who were HLA eligible, 5 were not treated because of clinical deterioration (n = 3) or death (n = 2). The remaining patients were not treated for reasons other than a change in clinical status (Supplementary Table S2).

Figure 1.

Schematic of synovial sarcoma patients included and excluded from this retrospective study.

Figure 1.

Schematic of synovial sarcoma patients included and excluded from this retrospective study.

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The characteristics of the 66 patients not treated with engineered T cells are presented in Table 1. Patient and tumor characteristics were well balanced between groups. The median age at diagnosis was 35 years (range: 8–84) and the median primary tumor size was 7.8 cm (range: 1.5–19.0). Most patients (70%) were male, had an extremity (46%) or thoracic (24%) primary tumor, and a monophasic tumor histology (73%). Twenty-three patients (35%) had unresectable or metastatic disease at the time of diagnosis. The median time from diagnosis until the date of recurrence or metastasis was 12 months (range: 0–189). Of the 43 patients with potentially resectable disease at diagnosis, 51% (n = 22) were treated with neoadjuvant chemotherapy and/or radiation. Of those who did not receive neoadjuvant therapy, the majority (57%; n = 12) were treated with adjuvant chemotherapy and/or radiation. Nine patients (21% of those with resectable disease) received no perioperative therapy.

Table 1.

Patient characteristics.

Total (n = 66)HLA-A*02Negative (n = 46)HLA-A*02Positive (n = 20)P value
Age at diagnosis Median (range) 35 (8–84) 35 (8–84) 35 (14–75) 0.601 
Sex 20 (30.3) 14 (30.4) 6 (30) >0.95 
 46 (69.7) 32 (69.6) 14 (70) — 
Race Unknown 5 (.) 5 (.) 0 (.) >0.95 
 Other 14 (23) 10 (24.4) 4 (20) — 
 White 47 (77) 31 (75.6) 16 (80) — 
Ethnicity Hispanic 6 (9.1) 4 (8.7) 2 (10) >0.95 
 Non-Hispanic 60 (90.9) 42 (91.3) 18 (90) — 
Location Abdominal/visceral 6 (9.1) 2 (4.3) 4 (20) 0.170 
 Bone 1 (1.5) 0 (0) 1 (5) — 
 Extremity 30 (45.5) 23 (50) 7 (35) — 
 Head and neck 3 (4.5) 3 (6.5) 0 (0) — 
 Pulmonary/thoracic 16 (24.2) 11 (23.9) 5 (25) — 
 Truncal soft tissue 10 (15.2) 7 (15.2) 3 (15) — 
Primary tumor size (cm) Median (range) 7.80 (1.50–19.0) 7.20 (1.50–19.0) 8.00 (2.80–14.5) 0.887 
Histology Unknown 6 (.) 5 (.) 1 (.) 0.754 
 Biphasic 16 (26.7) 12 (29.3) 4 (21.1) — 
 Monophasic 44 (73.3) 29 (70.7) 15 (78.9) — 
Neoadjuvant chemotherapy No 48 (72.7) 34 (73.9) 14 (70) 0.770 
 Yes 18 (27.3) 12 (26.1) 6 (30) — 
Neoadjuvant RT No 55 (83.3) 40 (87) 15 (75) 0.287 
 Yes 11 (16.7) 6 (13) 5 (25) — 
Adjuvant chemotherapy No 48 (72.7) 34 (73.9) 14 (70) 0.770 
 Yes 18 (27.3) 12 (26.1) 6 (30) — 
Adjuvant RT No 51 (77.3) 35 (76.1) 16 (80) >0.95 
 Yes 15 (22.7) 11 (23.9) 4 (20) — 
Time from diagnosis to metastasis (months) Median (range) 12 (0–189) 12 (0–189) 11 (0–59) 0.498 
Survivor follow-up (months) Median (range) 47.96 (3.82–307.93) 65.81 (3.82–307.93) 37.38 (17.96–47.17)  
Total (n = 66)HLA-A*02Negative (n = 46)HLA-A*02Positive (n = 20)P value
Age at diagnosis Median (range) 35 (8–84) 35 (8–84) 35 (14–75) 0.601 
Sex 20 (30.3) 14 (30.4) 6 (30) >0.95 
 46 (69.7) 32 (69.6) 14 (70) — 
Race Unknown 5 (.) 5 (.) 0 (.) >0.95 
 Other 14 (23) 10 (24.4) 4 (20) — 
 White 47 (77) 31 (75.6) 16 (80) — 
Ethnicity Hispanic 6 (9.1) 4 (8.7) 2 (10) >0.95 
 Non-Hispanic 60 (90.9) 42 (91.3) 18 (90) — 
Location Abdominal/visceral 6 (9.1) 2 (4.3) 4 (20) 0.170 
 Bone 1 (1.5) 0 (0) 1 (5) — 
 Extremity 30 (45.5) 23 (50) 7 (35) — 
 Head and neck 3 (4.5) 3 (6.5) 0 (0) — 
 Pulmonary/thoracic 16 (24.2) 11 (23.9) 5 (25) — 
 Truncal soft tissue 10 (15.2) 7 (15.2) 3 (15) — 
Primary tumor size (cm) Median (range) 7.80 (1.50–19.0) 7.20 (1.50–19.0) 8.00 (2.80–14.5) 0.887 
Histology Unknown 6 (.) 5 (.) 1 (.) 0.754 
 Biphasic 16 (26.7) 12 (29.3) 4 (21.1) — 
 Monophasic 44 (73.3) 29 (70.7) 15 (78.9) — 
Neoadjuvant chemotherapy No 48 (72.7) 34 (73.9) 14 (70) 0.770 
 Yes 18 (27.3) 12 (26.1) 6 (30) — 
Neoadjuvant RT No 55 (83.3) 40 (87) 15 (75) 0.287 
 Yes 11 (16.7) 6 (13) 5 (25) — 
Adjuvant chemotherapy No 48 (72.7) 34 (73.9) 14 (70) 0.770 
 Yes 18 (27.3) 12 (26.1) 6 (30) — 
Adjuvant RT No 51 (77.3) 35 (76.1) 16 (80) >0.95 
 Yes 15 (22.7) 11 (23.9) 4 (20) — 
Time from diagnosis to metastasis (months) Median (range) 12 (0–189) 12 (0–189) 11 (0–59) 0.498 
Survivor follow-up (months) Median (range) 47.96 (3.82–307.93) 65.81 (3.82–307.93) 37.38 (17.96–47.17)  

Values are n (%), unless otherwise indicated.

HLA genotype detection from MSK-IMPACT

A total of 32 patients underwent prospective sequencing with MSK-IMPACT during their treatment course. Seventy-five percent of sequenced tumors were from metastatic sites, rather than primary tumors. Two patients had no matched-normal control samples and 6 had an early version of IMPACT that precluded analysis of HLA genotype. The remaining 24 patient samples were eligible for analysis of HLA genotype and are reported in Supplementary Table S3. Of these 24 patients, 16 had their complete HLA class I genotype (two alleles each of HLA-A, HLA-B, and HLA-C) determined at an outside CLIA-certified laboratory and 7 had HLA-A gene analysis only. The outside HLA genotype of one patient was unavailable, but was documented to be HLA-A*02 negative in the medical record and thus ineligible for the clinical trial.

Of the 23 patients who had HLA genotyping by IMPACT and an outside CLIA-certified laboratory, 21 (91%) had matching HLA genotypes (including the 7 patients with outside testing of HLA-A only). The two patients that were not a complete match had five of six matching HLA alleles. At an allele-specific level, 110 HLA alleles sequenced by an outside lab were available for comparison (two alleles each of HLA-A, HLA-B, and HLA-C for 16 patients, and two HLA-A alleles for 7 patients). Ninety-eight percent (n = 108) of all HLA alleles matched the IMPACT analysis and 100% of HLA-A*02 alleles were a match.

Somatic loss of heterozygosity (LOH) status was available for the 24 patients who had HLA genotyping by IMPACT. Three patients demonstrated LOH of at least one HLA gene (Fig. 2). Two were HLA-A*02 eligible; one had LOH of HLA-A*02:01 in the primary tumor. This patient was treated with three cycles of neoadjuvant doxorubicin plus ifosfamide prior to initial surgical resection of the primary tumor. None of the HLA-A*02-eligible patients who had LOH were treated with engineered T cells.

Figure 2.

LOH at HLA alleles in three patients with metastatic synovial sarcoma (A,B, and C, respectively) who underwent MSK-IMPACT testing. The log ratio of depth of coverage in the tumor and normal tissue is displayed along HLA alleles, highlighting loss of HLA gene coverage depth in tumor tissue, compared with normal.

Figure 2.

LOH at HLA alleles in three patients with metastatic synovial sarcoma (A,B, and C, respectively) who underwent MSK-IMPACT testing. The log ratio of depth of coverage in the tumor and normal tissue is displayed along HLA alleles, highlighting loss of HLA gene coverage depth in tumor tissue, compared with normal.

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OS independent of treatment modality

To determine whether HLA-A*02-eligible status was prognostic of clinical outcome independent of treatment modality, survival was estimated from the time of unresectable or metastatic disease in patients not previously treated with NY-ESO-1–specific T cells (n = 66, excluding 9 HLA-A*02-eligible patients treated with SPEAR T cells). Median follow-up for survivors was 48 months. On univariate analysis, larger primary tumor size [HR = 1.2; 95% confidence interval (CI), 1.12–1.34] and longer time from diagnosis until metastatic disease (HR = 0.99; 95% CI, 0.976–0.999) were significantly associated with OS (P < 0.001 and P = 0.032, respectively), the former with a shorter survival and the latter with longer survival. HLA-A*02-eligible status (HR = 1.95; 95% CI, 0.96–3.81) and age at diagnosis (HR = 1.021; 95% CI, 0.99–1.04) were slightly above the threshold for statistical significance (P = 0.052 and P = 0.061, respectively; Table 2). The median OS of HLA-A*02-eligible patients was 25.1 months (95% CI, 10.8–35.7), compared with 43.9 months (95% CI, 25.7–69.5) in the HLA-A*02-ineligible group (Fig. 3A).

Table 2.

Univariable analyses of OS

Univariate analysis
Study groupChemotherapyPazopanibAll patients
ParameterHR95% CIP valueHR95% CIP valueHR95% CIP value
HLA-A*02 eligible 1.763 0.706 4.404 0.225 1.062 0.471 2.393 0.884 1.948 0.995 3.813 0.052 
Age at diagnosis 1.021 0.986 1.058 0.242 1.013 0.985 1.041 0.362 1.021 0.999 1.044 0.061 
Sex 1.140 0.448 2.898 0.783 1.141 0.522 2.494 0.742 1.203 0.626 2.313 0.579 
Primary tumor size 1.224 1.073 1.396 0.003a 1.068 0.974 1.170 0.162 1.229 1.123 1.345 <0.001a 
Histology (monophasic/biphasic) 2.025 0.753 5.446 0.162 1.030 0.383 2.766 >0.95 1.040 0.484 2.234 0.920 
Neoadjuvant chemotherapy 0.882 0.258 3.009 0.840 0.902 0.406 2.003 0.801 1.201 0.605 2.385 0.601 
Neoadjuvant radiotherapy 2.847 0.816 9.929 0.101 0.644 0.192 2.156 0.475 1.255 0.523 3.011 0.611 
Adjuvant chemotherapy 0.808 0.300 2.175 0.673 1.062 0.444 2.538 0.893 0.714 0.339 1.504 0.375 
Adjuvant radiotherapy 0.492 0.146 1.661 0.253 1.226 0.512 2.935 0.648 0.719 0.342 1.514 0.385 
Time from diagnosis to metastasis 0.990 0.979 1.002 0.113 0.995 0.984 1.005 0.294 0.987 0.976 0.999 0.032a 
Univariate analysis
Study groupChemotherapyPazopanibAll patients
ParameterHR95% CIP valueHR95% CIP valueHR95% CIP value
HLA-A*02 eligible 1.763 0.706 4.404 0.225 1.062 0.471 2.393 0.884 1.948 0.995 3.813 0.052 
Age at diagnosis 1.021 0.986 1.058 0.242 1.013 0.985 1.041 0.362 1.021 0.999 1.044 0.061 
Sex 1.140 0.448 2.898 0.783 1.141 0.522 2.494 0.742 1.203 0.626 2.313 0.579 
Primary tumor size 1.224 1.073 1.396 0.003a 1.068 0.974 1.170 0.162 1.229 1.123 1.345 <0.001a 
Histology (monophasic/biphasic) 2.025 0.753 5.446 0.162 1.030 0.383 2.766 >0.95 1.040 0.484 2.234 0.920 
Neoadjuvant chemotherapy 0.882 0.258 3.009 0.840 0.902 0.406 2.003 0.801 1.201 0.605 2.385 0.601 
Neoadjuvant radiotherapy 2.847 0.816 9.929 0.101 0.644 0.192 2.156 0.475 1.255 0.523 3.011 0.611 
Adjuvant chemotherapy 0.808 0.300 2.175 0.673 1.062 0.444 2.538 0.893 0.714 0.339 1.504 0.375 
Adjuvant radiotherapy 0.492 0.146 1.661 0.253 1.226 0.512 2.935 0.648 0.719 0.342 1.514 0.385 
Time from diagnosis to metastasis 0.990 0.979 1.002 0.113 0.995 0.984 1.005 0.294 0.987 0.976 0.999 0.032a 

aStatistically significant, as defined by prespecified threshold of P < 0.05.

Figure 3.

OS by HLA-A*02 status from the time of metastasis (A), from time of metastasis in those who signed consent within 1 year of metastasis (sensitivity analysis; B), from start of chemotherapy in the metastatic setting (C), and from start of pazopanib in the metastatic setting (D). Patients treated with SPEAR T cells were not included in these analyses.

Figure 3.

OS by HLA-A*02 status from the time of metastasis (A), from time of metastasis in those who signed consent within 1 year of metastasis (sensitivity analysis; B), from start of chemotherapy in the metastatic setting (C), and from start of pazopanib in the metastatic setting (D). Patients treated with SPEAR T cells were not included in these analyses.

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In a multivariate analysis accounting for HLA status, age at diagnosis, and primary tumor size, HLA-A*02-eligible status was above the threshold for significance (HR = 1.8; 95% CI, 0.94–3.6; P = 0.076). In contrast, older age at diagnosis (HR = 1.03; 95% CI, 1.002–1.049) and larger tumor size (HR = 1.2; 95% CI, 1.1–1.4) were associated with a significantly shorter OS (P = 0.037 and P < 0.001, respectively; Table 3).

Table 3.

Multivariable analysis of overall survival in all patients from the time of metastasis.

ParameterHR95% CIP value
HLA-A*02 eligible 1.840 0.939 3.606 0.076 
Age at diagnosis 1.025 1.002 1.049 0.037a 
Primary tumor size 1.243 1.127 1.370 <0.001a 
ParameterHR95% CIP value
HLA-A*02 eligible 1.840 0.939 3.606 0.076 
Age at diagnosis 1.025 1.002 1.049 0.037a 
Primary tumor size 1.243 1.127 1.370 <0.001a 

aStatistically significant, as defined by prespecified threshold of P < 0.05.

Given that providing informed consent for the clinical trial was a key inclusion criterion and that time from diagnosis of metastatic disease until informed consent varied, a sensitivity analysis was performed in the 39 patients (59% of the study population) who consented to screen for the trial within 1 year of developing metastatic disease. This excluded patients whose prolonged time to consent could have influenced the OS analysis. The median OS of HLA-A*02-eligible patients was 13.6 months (95% CI, 16.3–38.9) versus 25.7 months (95% CI, 8.5–15.2) for ineligible patients (P = 0.016; Fig. 3B). On univariate analysis, HLA-A*02 status was the only variable that significantly impacted survival (HR = 2.79; 95% CI, 1.18–6.61; P = 0.020; Supplementary Table S4).

OS after first-line chemotherapy

Two-thirds of the above cohort (n = 44) received either doxorubicin or ifosfamide-based therapy in the first-line metastatic setting. The date of treatment initiation was not known for 8 patients. Therefore, a total of 36 patients were eligible for inclusion in survival analyses, 25% (n = 9) of whom were HLA-A*02 eligible. OS did not significantly differ between the HLA-A*02-eligible and -ineligible groups [32.8 months (95% CI, 3.8–39.6) vs. 38.4 months (95% CI, 21.2–72.3) months, respectively; P = 0.217; Fig. 3C]. On univariate analysis, only primary tumor size was significantly associated with a shorter OS (HR = 1.2; 95% CI, 1.1–1.4; P = 0.003; Table 2). The remaining clinicopathologic factors tested did not significantly associate with OS.

OS after pazopanib

A total of 39 patients were treated with pazopanib at some point during their treatment course. OS data from the date of pazopanib initiation was available for 37 patients, 32% of whom (n = 12) were HLA-A*02 eligible. OS did not significantly differ between the HLA-A*02-eligible and -ineligible groups [11.2 (95% CI, 6.6–23.7) and 14.1 (95% CI, 4.5–17.7) months, respectively; P = 0.884; Fig. 3D]. No clinicopathologic variables were associated with a significant difference in OS (Table 2).

This study reports our experience using a targeted genetic sequencing panel (MSK-IMPACT) to identify HLA genotype. The MSK-IMPACT assay had a high concordance rate with HLA genotyping performed at a CLIA-certified laboratory outside our institution. This has the potential to become an important tool as we continue to learn about the impact of HLA and antigen presentation machinery on response to cancer therapies such as immune checkpoint blockade (27–29). It may also help expedite the screening process for patients interested in participating in adoptive T-cell therapy trials at our institution, whose HLA type is unknown. At present, the screening process can be lengthy, which is compounded by the time it takes to manufacture the NY-ESO-1 SPEAR T cells. Using NGS data that are readily available could save the patient time as he or she considers the next line of systemic treatment.

Furthermore, LOH analysis of SS tumors may be a useful tool to clarify mechanisms of resistance to NY-ESO-1 SPEAR T cells. We identified a patient with the HLA-A*02:01 genotype who would have been eligible for a clinical trial of engineered T cells based on this HLA type, who lost this critical HLA gene in his tumor after treatment with neoadjuvant chemotherapy. This may represent immunoediting as a form of resistance to innate antitumor T-cell activity (30). Investigation of somatic LOH at HLA loci on serial biopsy specimens in patients who receive engineered T cells on trial may further clarify whether LOH is a potential mechanism of resistance.

This study reports that patients with SS with an HLA-A*02 genotype had a shorter OS when survival was analyzed from the time of metastasis. This finding did not reach the threshold for significance in a multivariable model that accounted for additional clinical variables. Retrospective studies in other malignancies, including ovarian cancer (31), non–small cell lung cancer (32), prostate cancer (33), and HPV-positive tonsillar squamous cell carcinoma (34) report an HLA-A*02 genotype as a negative prognostic factor. A retrospective analysis of 453 patients with melanoma treated with ipilimumab with or without a peptide vaccine identified a trend toward a worse OS in a subgroup of HLA-A*02:01-positive patients treated with 10 mg/kg of ipilimumab. The authors attributed this finding to statistical variability between groups and consider discordant findings between subgroups an expected limitation in retrospective studies (35).

Theoretical mechanisms for an adverse prognosis in HLA-A*02-eligible patients with SS compared with other HLA genotypes may include decreased expression of HLA-A*02 in the tumor due to transcriptional downregulation, hypermethylation, or alteration of key cytokine signaling in the tumor microenvironment required for immune activation (36). However, given the small sample size of this cohort we interpret these findings with caution, as do Wolchok and colleagues in patients with ipilimumab-treated melanoma. Confirmatory studies are warranted to further investigate the effect of HLA haplotype on prognosis in SS.

Adoptive T-cell therapy is now being utilized in SS clinical trials with encouraging early results. Robbins and colleagues utilized genetically engineered autologous T cells in a small study of 18 patients with SS and reported a 61% objective RR (20). In another pilot study, D'Angelo and colleagues treated 12 patients with NY-ESO-1–expressing SS with genetically engineered NY-ESO-1–targeted T cells (NY-ESO-1c259 SPEAR T cells). The ORR was 50%, with one complete response, five partial responses, and a median PFS of 15 weeks (21). A recent update reported that 15 of 42 patients (36%) achieved a confirmed objective response (22). Given the rarity of SS as a diagnosis, conducting a large, randomized, phase III trial of adoptive T-cell therapy will be a challenge. Thus, defining the prognostic effect of eligible HLA-A*02 genotypes on clinical outcome may serve as an important historic control.

The clinicopathologic characteristics of patients in this study are comparable to previously published studies of SS, suggesting that our population may be a representative sample. The median age of diagnosis was in the third decade, primary tumors were most commonly identified in the extremities, and monophasic histology was more common than biphasic. The median time from diagnosis until the date of metastasis was 12 months and OS from date of metastasis was 29 months. For comparison, a Royal Marsden Hospital retrospective of 104 patients of SS found a time from diagnosis until metastasis of 16 months and a median OS of 22 months from the time of metastasis (37). In addition, among Caucasians in this study—the largest ethnic group in this cohort—32% (15 of 47) tested positive for HLA-A*02:01. This is on par with the allele frequency of 29.6% found among U.S. adults of European ancestry (38). In addition, our OS analyses identified older age and larger tumor size to be two prognostic factors of outcome, which corroborates the results of a previous analysis by Singer and colleagues (39).

The strengths of this study include its relatively large cohort size for a single-center retrospective in a rare disease, its investigation of a genomic biomarker, and its focus on patients screened on a prospective study. Its retrospective nature and the selection bias that follows is a potential weakness. Specifically, patients treated with SPEAR T cells were excluded, whereas HLA-eligible patients who were not treated on trial because of clinical deterioration were included. These two groups may have different outcomes, highlighting the difficulties of defining a uniform cohort for analysis among a group of patients that have disparate clinicopathologic, molecular, and treatment characteristics. Thus, validation of these findings in a future study is warranted.

In summary, HLA genotype is a necessary predictive biomarker for patients with SS interested in receiving genetically engineered T cells. Our findings indicate that select HLA-A*02 genotypes may be prognostic of poor outcome in the advanced setting. Although this study is restricted to an analysis of HLA-A*02:01, HLA-A*02:05, or HLA-A*02:06, it would be of interest to learn whether other HLA alleles are prognostic or predictive in this disease. Utilizing a targeted genomic sequencing panel to determine HLA genotype could help facilitate patient screening for SS and other clinical trials, clarify mechanisms of resistance to therapy, and allow future study of HLA gene on clinical outcomes.

E. Rosenbaum reports other from Adaptimmune (patients in this study consented to a clinical trial that was funded by Adaptimmune. No funding was directly provided for the work involved in this manuscript.) during the conduct of the study. P. Chi reports personal fees from Deciphera (advisory or consulting) and Exelixis (advisory or consulting), and grants from Deciphera (clinical research) and Array/Pfizer (clinical research) outside the submitted work. S. Movva reports grants from Adaptimmune (institutional funding for NY-ESO adoptive T-cell therapy clinical trial) during the conduct of the study, as well as grants from Novartis (institutional funding for clinical trial) outside the submitted work. B. Nacev reports a one-time uncompensated consulting activity with Delphi Diagnostics, a one-time uncompensated collaborative discussion with Rapafusyn Pharmaceuticals, and nonfinancial support from Johns Hopkins University in the form of sponsored travel. W.D. Tap reports other from Adaptimmune (standard budget for site participation in a clinical trial in synovial sarcoma) and GlaxoSmithKline (standard budget for site participation in a clinical trial in synovial sarcoma) during the conduct of the study; personal fees from Eli Lilly (advisory board and consulting to discuss sarcoma and drug development in sarcoma; travel expenses), EMD Serono (advisory board and consulting to discuss drug development in cancer; travel expenses), Eisai (advisory board and consulting to discuss drug development in sarcoma; travel expenses), Janssen (advisory board and consulting to discuss drug development in sarcoma; travel expenses), Immune Design (advisory board and consulting to discuss drug development in sarcoma; travel expenses), Daiichi Sankyo (advisory board and consulting to discuss drug development in sarcoma), Blueprint (advisory board and consulting to discuss drug development in GIST), Loxo (advisory board and consulting to discuss drug development in sarcoma), GlaxoSmithKline (advisory board and consulting to discuss drug development in sarcoma), Agios (advisory board and consulting to discuss drug development in chondrosarcoma), Nanocarrier (advisory board to discuss drug development in sarcoma), and Deciphera (advisory board to discuss drug development in GIST and tenosynovial giant cell tumor) outside the submitted work; and is on the scientific advisory board for Certis Oncology Solutions (stock ownership). S.P. D'Angelo reports other from Adaptimmune (consulting/advisory role) and GSK (consulting/advisory role) during the conduct of the study; consulting advisory role for Amgen, EMD Serono, ImmuneDesign, Incyte, Merck, and Nektar; research funding from Amgen, BMS, Deciphera, EMD Serono, Incyte, Merck, and Nektar; and travel accommodations from Adaptimmune, EMD Serono, and Nektar outside the submitted work. No potential conflicts of interest were disclosed by the other authors.

E. Rosenbaum: Conceptualization, data curation, methodology, writing-original draft, writing-review and editing. K. Seier: Conceptualization, data curation, formal analysis, visualization, writing-original draft, writing-review and editing. C. Bandlamudi: Conceptualization, data curation, formal analysis, visualization, methodology, writing-original draft, writing-review and editing. M. Dickson: Writing-review and editing. M. Gounder: Writing-review and editing. M.L. Keohan: Writing-review and editing. P. Chi: Writing-review and editing. C. Kelly: Writing-review and editing. S. Movva: Writing-review and editing. B. Nacev: Writing-review and editing. N. Simeone: Writing-review and editing. M. Donoghue: Resources, writing-review and editing. E.K. Slotkin: Resources. L.-X. Qin: Conceptualization, formal analysis, project administration, writing-review and editing. C.R. Antonescu: Resources. W.D. Tap: Resources, supervision, project administration, writing-review and editing. S.P. D'Angelo: Conceptualization, supervision, writing-review and editing.

Brian Olivo and Samantha Wheeler contributed to this research. This research is supported by the NCI of the NIH (P30 CA008748). Patients in this study screened for a clinical trial funded by Adaptimmune. MSKCC is supported in part by the NIH/NCI Core grant P30 CA008748. Patients on this study consented to screen for a clinical trial that was funded by Adaptimmune.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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Supplementary data