Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer

Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer Cindy Y. Jiang, Lili Zhao, Michael D. Green, Shashidhar Ravishankar, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2929223/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jan, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Immune checkpoint inhibitors (ICI) are important treatment options for metastatic non-small cell lung cancer (NSCLC). However, not all patients benefit from ICIs and can experience immune related adverse events (irAEs). Limited understanding exists for germline determinants of ICI efficacy and toxicity, but human leukocyte antigen (HLA) has emerged as a potential predictive biomarker. We obtained HLA genotypes from 85 metastatic NSCLC patients on ICI therapy and analyzed the impact of HLA Class II genotype on progression free survival (PFS), overall survival (OS), and irAEs. Most patients received pembrolizumab (83.5%). HLA-DRB4 correlated with improved survival in both univariable (PFS 9.9 months, p = 0.040; OS 26.3 months, p = 0.0085 ) and multivariable analysis (PFS p = 0.0310, HR 0.55, 95% CI [0.31, 0.95]) ; OS p = 0.003, HR 0.40, 95% CI [0.21, 0.73]). 11 patients developed endocrine irAEs. HLA-DRB4 was expressed in 39/85 (45.9%) patients and was the predominant genotype for endocrine irAEs (9/11, 81.8%). Cumulative incidence of endocrine irAEs was higher in patients with HLA-DRB4 ( p = 0.0139). Our study is the first to suggest metastatic NSCLC patients on ICI therapy with HLA-DRB4 genotype experienced improved survival outcomes. Additionally, we found a correlation between HLA-DRB4 and endocrine irAEs. Biological sciences/Cancer/Lung cancer Biological sciences/Cancer Biological sciences/Cancer/Cancer therapy/Cancer immunotherapy immune check point inhibitor immune related adverse events human leukocyte antigen toxicity lung cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION In the United States, lung cancer is the third most common cancer with over 236,700 new cases in 2022 and the leading cause of cancer deaths, accounting for 24% of all cancer related deaths. 1 Around 85% of lung cancer cases are non-small cell lung cancer (NSCLC). 2 While surgery and stereotactic body radiotherapy are potentially curative for early stage disease, the majority of patients present with locally advanced or metastatic disease which is more refractory to treatment. 3 Historically, for patients with locally advanced disease, the 5-year survival after chemoradiation was 32% 4 , and for patients with metastatic disease, the 2-year survival after chemotherapy was 11%. 5 Immune checkpoint inhibitors (ICIs) have considerably improved the outcomes of patients with all stages of lung cancer. Neoadjuvant nivolumab plus ipilimumab prior to surgical resection of Stage I/II NSCLC results in complete pathologic responses in as many as 38% of patients. 6 Resectable NSCLC patients who received neoadjuvant nivolumab in combination with chemotherapy experienced improved progression free survival to 77% 7 and complete pathologic response in 24% of patients. 8 The addition of adjuvant durvalumab following chemoradiation in Stage III NSCLC improves the 5-year overall survival to 43%. 9 Finally, the use of pembrolizumab in metastatic NSCLC patients has improved the 5-year overall survival to 31%. 10 Other regimens include combination of chemotherapy (platinum based plus pemetrexed) and pembrolizumab, atezolizumab +/- chemotherapy and bevacizumab, cemiplimab, nivolumab plus ipilimumab +/- chemotherapy. 11 – 15 This has led to widespread use of ICI across all stages of NSCLC. However, not all patients may experience benefit from immunotherapy and identification of predictive biomarkers is crucial. Currently, the only clinically approved biomarker for immunotherapy in NSCLC patients is program death ligand 1 (PDL-1) and it plays an important role in treatment decision making. 16 There has been exploration of other potential biomarkers, such as tumor mutational burden (TMB), deficient mismatch repair, microsatellite instability, tumor infiltrating lymphocytes (TIL), gut microbiome, microRNA, and peripheral markers (i.e. neutrophil to lymphocyte ratio and lactate dehydrogenase), but no additional predictive biomarkers have been validated. 16 – 18 Class I and II human leukocyte antigens (HLA) are encoded by major histocompatibility complex (MHC) genes and have emerged as an area of strong interest for predictive biomarker discovery. 19 HLA class I proteins (HLA A, B, and C) are widely expressed on all nucleated cells and present antigens to CD8 + T cells 20 . HLA class II proteins (HLA DP, DQ, DR) have limited expression predominantly on antigen presenting cells (i.e. dendritic cells, macrophages, B cells) and present antigens to CD4 + T cells. 21 The HLA system is critical for self vs non-self-discrimination by the immune system as well as for the detection of cancer. Loss of HLA Class I has emerged as an important immune evasion mechanism in NSCLC 22 , and specific HLA class I alleles have been associated with immunotherapy efficacy and toxicity. 23 – 27 For example, HLA-A*03 and HLA-B62 supertype have been found to predict poor response to immunotherapy, while HLA-B44 supertype predicts for improved survival. 28 , 29 In most studies, patient’s are more commonly tested for HLA class I genotypes. This has led to limited clinical studies examining the association between HLA class II antigens and immontherapy efficacy. The current available studies note that increased HLA class II related gene expression correlates with improved outcomes. 30 Notably, higher HLA-DR expression has been suggested to predict response to ICI. 31 , 32 ICIs are associated with a unique spectrum of side effects known as immune related adverse events (irAEs). irAEs can affect any organ, with the most commonly affected organs including the skin, colon, liver, lungs, and endocrine glands. 13 While the majority of irAEs in patients with NSCLC are low grade, severe side effects requiring therapy discontinuation occur in up to 20% of Stage III NSCLC patients 14 and in 17% of patients with Stage IV NSCLC. 15 Fulminant and fatal toxicities may occur. 16 Management relies on immunosuppression with glucocorticoids, TNFa antagonists, or other agents, but, on occasion these therapies have resulted in tumor progression. 17 Immune checkpoints play a role in limiting autoimmune disease, and therefore, use of checkpoint inhibitors triggers autoimmune off- target inflammation in normal tissues. Consistent with this, irAEs occur with higher frequency in patients with autoimmune antibodies. 18 However, there is limited understanding of whether germline determinants regulate irAE development. Herein, we examined patients with metastatic NSCLC who received immunotherapy and primarily evaluated the correlation between HLA class II genotype and treatment efficacy. Secondarily, we conducted an exploratory analysis on HLA class II and the development of immune related adverse events (irAEs). METHODS Patients We conducted a prospective study that involved the collection of baseline tumor biopsy and blood samples in patients being treated with ICIs for metastatic NSCLC to identify biomarkers predictive of therapeutic response and toxicity. The study was conducted at the Veterans Administration, Ann Arbor Healthcare System (VAAAHS). Enrollment for the study began November 2015 and ended in June 2022. Study eligibility for patients included diagnosis of metastatic NSCLC and initiation of ICI therapy. A total of 85 patients with clinical outcomes and HLA genotype data are available. All patients were reviewed for the development of any adverse event and both classification and grading were based on the Common Terminology Criteria for Adverse Events version 5.0 (CTCAE). Our study did not include additional review of adverse events by independent investigators. HLA Genotyping Data HLA genotyping was completed via ScisGo HLA typing kits (Scisco Genetics, Seattle, WA). The full standardized protocol is available online. 39 DNA was extracted from patient blood and this was followed by genomic DNA quantification and library preparation using the ScisGo HLA Typing Kit. HLA genotypes of each patient were directly compared to each other and closely analyzed for similarities and presence of HLA loci known to be associated with autoimmune endocrine disorders. 40 , 41 Statistical Analysis Descriptive statistics of the clinical and demographic data included mean, median, and range for numerical variables as well as percentages for categorical variables. Important clinical and demographic data included gender, race, histology, smoking history, performance status, and prior therapies. Progression free survival (PFS) was defined as time from imunnotherapy start to radiographic disease progression. Overall survival (OS) was defined as time from immunotherapy start to death or date of last follow up. Kaplan-Meier methods were used to estimate the PFS and OS functions, and log-rank tests were used for the comparisons. Cox proportional hazards regression was used to assess the association between HLA- DRB4 and PFS/OS, adjusting for age, gender, race, stage, smoking history, and histology. To further study the association of irAE to survival, we included it as a time-varying covariate in the Cox model. The time-varying covariate had a value of 0 before the irAE and 1 after irAE; for patients who did not have irAE, this covariate had a value of 0 during the entire follow-up period. SAS (version 9.4) was used for the analyses and significance was defined by a two-tailed p value < 0.05. To assess association between HLA-DRB4 and development of endocrine irAEs, cumulative incidence functions were used and significance was based on Gray’s test. Study Approval This clinical study was approved by the VA Ann Arbor Healthcare System institutional review board and ethics committee. Written informed consent was obtained from all patients. All research was performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki. RESULTS Patient Demographics There were 98 eligible cancer patients with metastatic NSCLC enrolled on this study. Of these, 85 (86%) had complete clinical data and adequate baseline DNA for HLA genotype analysis. Most patients were men (96.5%), majority were former/active smokers (98.8%), and the median age was 72 years (IQR 66–75). The patients were predominantly Caucasian (75.3%). Prior to receiving ICI therapy, 21.2% had received chemotherapy only and 49.4% had received both chemotherapy and radiation therapy. All patients who received chemotherapy were exposed to platinum regimens (n = 60). The average number of prior therapies (prior to immunotherapy) was 0.92 (range 0–2). Other therapies tried before immunotherapy included carboplatin/pemetrexed, cisplatin/etoposide, carboplatin/paclitaxel, carboplatin/etoposide, carboplatin/gemcitabine, cisplatin/vinorelbine, cisplatin/gemcitabine, carboplatin/pemetrexed/bevacizumab, and cisplatin/docetaxel. Most patients received pembrolizumab (83.5%) with 14 receiving pembrolizumab in conjunction with carboplatin and pemetrexed. Other ICIs included durvalumab and nivolumab. 20 patients (23.5%) developed irAEs: 11 with endocrine irAEs (diabetes = 1; thyroiditis = 5, adrenal insufficiency = 2, and both = 3) and 9 with other irAEs (Table 1 ). Table 1 Patient Demographics and Clinical Characteristic Pts w/o Endocrine irAEs (n = 74) Pts w/Endocrine irAEs (n = 11) Age, years – Median (IQR) 69 (65.3–73.8) 70 (65-72.5) Sex Male– No. (%) Female – No. (%) 71 (95.9) 3 (3.5) 11 (100) 0 (0) Self-Identified Race White, Caucasian – No. (%) African American – No. (%) Hawaiian or Pacific Islander – No. (%) Did not declare – No. (%) 55 (74.3) 9 (12.2) 2 (2.7) 8 (10.8) 9 (81.8) 1 (9.1) 0 (0) 1 (9.1) Histology Squamous – No. (%) Adenocarcinoma – No. (%) Adenosquamous – No. (%) Poorly Differentiated – No. (%) Unknown – No. (%) 26 (35.1) 43 (58.1) 0 (0) 4 (5.4) 1 (1.4) 5 (45.5) 5 (45.5) 1 (9.1) 0 (0) 0 (0) Charleston Comorbidity Index – Mean (range) 9.7 (4–13) 9.8 (9–14) Pack years – Mean (range) Former smoker – No. (%) Active smoker – No. (%) Never smoker – No. (%) 50.6 (1-165) 48 (64.9) 26 (35.1) 0 (0) 43.0 (0-110) 8 (72.7) 2 (18.2) 1 (9.1) Prior Therapies Prior Chemotherapy Only – No. (%) Prior Radiation Therapy Only – No. (%) Prior Chemotherapy + Radiation – No. (%) No Prior Therapy – No. (%) 14 (18.9) 14 (18.9) 37 (50.0) 9 (12.2) 4 (36.4) 0 (0) 7 (63.6) 0 (0) ICI Therapy Pembrolizumab – No. (%) Nivolumab – No. (%) Durvalumab – No. (%) 62 (83.8) 4 (5.4) 8 (10.8) 10 (90.9) 0 (0) 1 (9.1) Number of ICI cycles – Median (range) 5 (1–53) 8 (3–35) Durable Clinical Benefit Yes – No. (%) No – No. (%) Unknown – No. (%) 30 (40.5) 42 (56.8) 2 (2.7) 9 (81.8) 2 (18.2) 0 (0) Immune Related Adverse Event Thyroiditis only – No. (%) AI only – No. (%) Both Thyroiditis and AI – No. (%) Diabetes – No. (%) Encephalitis – No. (%) Arthralgia – No. (%) Pneumonitis – No. (%) Bullous Pemphigoid – No. (%) Pruritis – No. (%) Rash – No. (%) Transaminitis – No. (%) 0 (0) 0 (0) 0 (0) 0 (0) 1 (1.4) 1 (1.4) 2 (2.7) 1 (1.4) 1 (1.4) 2 (2.7) 1 (1.4) 5 (45.5) 2 (18.2) 3 (27.3) 1 (9.1) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Time from ICI initiation to irAE, months – Median (range) 4.6 (2.8– 27.5) 5.37 (1.5–58.6) Status at Last Follow-Up Deceased – No. (%) Alive – No. (%) Discontinued ICI Therapy – No. (%) 55 (74.3) 19 (25.7) 64 (86.5) 5 (45.5) 6 (54.5) 11 (100) Overall Treatment Efficacy The median follow-up time for all 85 patients was 42.8 months (IQR 23.7–63.6). The median PFS was 6.7 months (IQR 2.1–20.9) and median OS was 13.2 months (IQR 6.05–33.9). 39/85 (45.9%) of patients experienced durable clinical benefit, defined as response or stable disease on therapy at ≥ 6 months. 9 patients remained alive for ≥ 36 months. HLA Characteristics We assessed the complete HLA genotype in all patients. Overall, the most common HLA class I types were HLA-C*07 (n = 46), HLA-A*02 (n.= 43), and HLA-A*03 (n = 27). The most frequent HLA class II genotypes were HLA-DPA1*01 (n = 82), HLA-DPB1*04 (n = 62), and HLA-DQA1*01 (n = 61). HLA-DRB4*01 was present in 39 patients. HLA-DRB4 Allele Variation Allelic variation is an important determinant of HLA function. 43 To explore whether specific HLA-DRB4 subtypes were associated with ICI treatment tolerance, we examined these more closely. Interestingly, all the patients with both thyroiditis and adrenal insufficiency (3/3) had HLA-DRB4 *01:03:01 as well as 40% of the patients with thyroiditis only (2/5) and one patient with diabetes (1/1). HLA-DRB4 *01:01:01 was present in two patients with adrenal insufficiency only and an additional patient with thyroiditis only. For patients who developed other types of irAEs, HLA-DRB4 *01:03:01 was present in 44.4% of the patients (4/9). In patients who did not develop any irAEs, HLA-DRB4 was present in 40% (n = 26) of patients with HLA-DRB4*01:03:01 allele predominating in 84.6% of the patients (n = 22), HLA-DRB4 *01:01:01 in 11.5% of the patients (n = 3), and HLA-DRB4*01:03:02 in 2.7% of patients (n = 1). 6 out of the 39 patients with HLA-DRB4 present were homozygous with two of these patients developing endocrine irAEs. The remaining patients were heterozygous (n = 30) or did not have the second allele present (n = 3). Correlation between HLA-DRB4 and Survival Presence of HLA-DRB4 correlated with improved OS ( p = 0.0085 by log-rank; median OS 26.3 months vs 8.8 months) (See Fig. 1 KM curve) and PFS ( p = 0.040 by log-rank; median PFS 9.9 months vs. 4.6 months) (See Fig. 2 KM curve). We assessed OS for HLA-DRB4*01:03:01 compared to other allele types (HLA-DRB4*01:01:01 plus HLA-DRB4*01:03:02) and no HLA-DRB4 presence (median OS 21.4 vs not reached vs 8.8 months) and found that other allele types (HLA-DRB4*01:01:01 plus HLA-DRB4*01:03:02) had the best OS (p = 0.015 by log rank). However, when comparing PFS between HLA-DRB4*01:03:01, other allele groups, and no HLA-DRB4 presence (median PFS 9.7 vs 22.6 vs 4.6 months) there was no significant statistical difference ( p = 0.080 by log-rank). Multivariable Analysis After adjusting for age, gender, race, stage, and histology, presence of HLA-DRB4 was associated with improved OS ( p = 0.003 , HR 0.40, 95% CI [0.21, 0.73]) and PFS ( p = 0.0310 , HR 0.55, 95% CI [0.31, 0.95]). Description of irAEs Of the 85 patients identified, 11 developed endocrine irAEs (12.9%). 10 (90.9%) patients received pembrolizumab and 1 received durvalumab (9.1%). The most frequent toxicity grade was 1 (n = 5). Overall, patient clinical characteristics and demographics were similar between those who developed endocrine irAEs and those who did not (Table 1 ). Thyroiditis was the most common endocrine irAE (n = 5) followed by both thyroiditis and adrenal insufficiency (n = 3), adrenal insufficiency alone (n = 2), and diabetes (n = 1). No patients in this cohort experienced new onset hyperthyroidism or hypoparathyroidism. The management and impact of endocrine irAEs on patients is outlined in Table 2 . Table 2 Clinical Description of Patients with Endocrine irAEs *Ethnicity: AA = African American; **Endocrine irAE: T = thyroiditis, AI = adrenal insufficiency, DM = diabetes mellitus; ***Initial Treatment/Continued Treatment: L = levothyroxine, H = hydrocortisone, P = prednisone Age 70 72 68 71 64 65 70 78 62 73 65 Gender Male Male Male Male Male Male Male Male Male Male Male Ethnicity * White White White White White White Unknown White AA White White ICI Therapy Pembro Pembro Pembro Pembro Pembro Pembro Pembro Pembro Pembro Pembro Durva Prior Endo Conditions Yes – hypothyroid 2/2 Radiation Yes – Hypothyroid No No No No No No No No No Endocrine irAE** T T; AI T AI T T; AI T; AI T DM AI T irAE Grade 1 1 2 3 2 3 1; 2 1 2 3 1 Time to Onset -months 1.47 4.13; 9.27 3.73 14.93 4.20 3.27; 3.73 5.37; 10.0 5.60 6.6 58.6 6.4 Other irAEs No colitis No No No No No No No Colitis, dermatitis pneumonitis Initial Treatment*** L L; H then P, back to H L; P P L; P L; P L; H L Metformin, lantus, aspart Steroid taper L Continued Treatment*** L L; weaned off steroids P P L L L; H L Metformin, lantus, aspart H L TSH Baseline/ After ICI 5.29/11.69 4.40/7.17 0.9/116 0.45/2.75 0.72/76.3 2.79/97.6 3.37/8.57 2.64/21.7 0.80/1.03 5.18/7.54 2.66/5.26 AM Cortisol 13.7 1.4 - 1.7 2.6 10.7 0.7 7.6 < 0.1 13 18.6 ACTH - 10 - < 5 - 22 5 - < 0.1 - 11.6 --> 14.3 - 1.0 --> 0.7 --> 9.6 - - - - - - - ICI Status post-irAE Continued until PD Continued until surveillance Held 2/2 irAE Held 2/2 irAE Held 2/2 irAE Discontinued prior to irAE given PD Continued until PD Held 2/2 irAE Held 2/2 irAE Held 2/2 irAE Held 2/2 irAE Endocrine irAEs and HLA Characteristics Among the 11 patients that developed endocrine irAEs, we noted HLA-C*07 (n = 6) and HLA-A*02 (n = 5) as the most predominant Class I HLA gene and HLA-DPA1*01 (n = 11) and HLA-DRB4*01 (n = 9) were the most frequent Class II HLA genes (Fig. 4 ). The Allele Frequency Net Database notes that HLA-DPA1*01 is very common in the United States (US) Amerindian population and the European Caucasians with 95% of individuals having the allele. 42 In comparison, HLA-DRB4 is less common in the US Caucasian population and present in approximately 40–50% individuals, this was estimated based on limited available data. 42 Thirty-nine of of 85 (45.9%) patients in our cohort had HLA-DRB4, with 9/11 (81.8%) patients with endocrine irAEs presenting the HLA-DRB4 genotype (Table 3 ). Table 3 HLA-DRB4 Presence in Patients with Endocrine irAEs vs Other irAEs vs No irAEs HLA-DRB4 Present HLA-DRB4 Not Present Total Pts w/Endocrine irAEs (%) 9 (81.8) 2 (18.2) 11 Pts w/Other irAEs (%) 4 (44.4) 5 (55.6) 9 Pts w/o irAEs (%) 26 (40.0) 39 (60.0) 65 Total 39 46 85 Association between HLA-DRB4 and irAEs Patients were assessed for the cumulative incidence of endocrine irAEs over time based on the the presence of HLA-DRB4. We found that patients who expressed HLA-DRB4 were statistically more likely to develop incidences of endocrine irAE’s compared to those who did not have HLA-DRB4 present (p = 0.0139 by Gray’s test, Fig. 3 ). Correlation between irAEs and Survival To investigate if development of irAEs correlated with ICI therapy efficacy, we carefully assessed survival outcomes. The presence of any irAE (endocrine or other) did not statistically improve PFS ( p = 0.226 , HR 0.61, 95% CI [0.268,1.365]) or OS (p = 0.219 , HR 0.63, 95% CI [0.301,1.316]). When comparing survival outcomes between endocrine and other irAEs, there was again no statistically significant improvement in PFS ( p = 0.530 , HR 0.5, 95% CI [0.230–17.4]) Multivariable Analysis After adjusting for age, gender, race, stage, and histology, the development of any irAE did not improve PFS ( p = 0.085) , HR 0.339, 95% CI [0.099, 1.162]) or OS ( p = 0.275 , HR 0.636, 95% CI [0.282,1.434]). Multivariable analysis of endocrine irAE patients was not possible given the small sample size. DISCUSSION Immunotherapy has significantly improved lung cancer outcomes. However, there remains a population of patients who do not benefit from therapy and others who experience fulminant toxicities. Preclinical and translational studies have identified primary and acquired mechanisms of resistance 45 including hepatic siphoning, 46 tumoral loss of HLA Class I, 47 T cell chemokine silencing, 48 and immunometabolic checkpoints. 49 Preclinical and translational work have begun to identify the cellular mediators of immune related adverse events, including hepatitis, 50 thyroiditis, 51 and colitis. 52 Our study revealed a significant correlation between HLA-DRB4 and improved PFS and OS, on both univariable and multivariable analysis and to our knowledge this is the first such report. Other studies have reported on different HLA class II genes, such as Correale et al noting longer survival in patients who were heterozygous for HLA DRB1. 25 Yang et al explored clinical outcomes in patients who received both immunotherapy and chemotherapy with findings of increased expression of HLA class II genes being associated with improved survival. 30 In their study, HLA-DMB, HLA-DOA, HLA-DPB1, and HLA-DMA were included in the top HLA genes related to outcomes. More recently, HLA-A*03 has been associated with inferior outcomes in patients receiving ICIs. 28 In our study, we looked at allele variation and found improved OS with allele subtypes HLA-DRB4*01:01:01 in comparison to HLA-DRB4*01:03:01. However, our study was not powered to make significant conclusions as we had more patients with HLA-DRB4*01:03:01 compared to other allele subtypes. Other groups have described an inverse correlation between loss of heterozygosity (LOH) for HLA Class I and II loci in tumors with survival. Schaafsma et al reported that any presence of Class I or II is protective and may result in improved activity from immune checkpoint inhibitors. 66 Interestingly, presence of any Class I or Class II in the tumor bearing cells was associated with improved survival in this cohort of patients, derived from multiple datasets of patients on ICIs. Importantly, this study was based on somatic expression and not germline. In non-small-cell lung cancers, HLA LOH occurs in 40% of early-stage cancers. 22 Additionally, the HLA homozygosity was preferentially selected for at metastatic cancer sites. 22 Advanced cancer patients that were heterozygous at all HLA class I loci had improved survival as compared to patients who were homozygous at any one locus. 29 Furthermore, Schaafsma et al observed significant increase in an HLA class II gene expression when comparing patients with and without clinical benefit in on-treatment samples as compared to pre-treatment samples, suggesting that on-treatment samples are more informative of clinical benefit when using HLA class II gene expression as an indicator of response. 66 This was not the case for HLA class I genes, which showed much less significance in on-treatment samples compared to HLA class II genes, suggesting that HLA class II genes might be more important for an effective response to ICI therapy. The importance of HLA class II genes has been shown in the context of ICI therapy in a number of studies. 53 , 67 It is proposed that the activation of CD4 + T cells by HLA class II expression helps to initiate CD8 + T cells that consequently mount a successful antitumor immune response during ICI therapy. 68 Our study was limited by lack of on treatment biopsy to confirm this phenomenon. Furthermore, the LOH status sof HLADRB4 in tumor samples were not available, given the limited lung cancer panel that was used for molecular testing as part of clinical care in these patients. Future studies should correlate germline and somatic status of Class II HLA genotypes with ICI response. Secondarily, we found a significant association between HLA DRB4 presence and incidence of endocrine irAEs. We found an overrepresentation of HLA-DRB4 in 13/20 patients with any degree of irAEs and 9/11 patients with endocrine irAEs. In comparison, only 40–50% of the general Caucasian population express HLA-DRB4. 42 This observation has not been previously reported. Extensive genetic polymorphisms and high a degree of homology within the HLA locus make it challenging to HLA type patients. 42 , 53 The exact mechanism leading to the development of irAEs is not clear, however there have been translational studies indicating the involvement of autoreactive T cells, autoantibodies, and pro-inflammatory cytokines. 54 The blockade of checkpoints like PD-1 allows T-cells to react against self antigens presented by HLA, and this in turn can led to inflammatory damage to normal organ tissue where these checkpoints are normally found. 55 HLA-DRB4 has been linked to a number of autoimmune diseases, including autoimmune hepatitis, 56 type 1 diabetes, 57 , 58 autoimmune myocarditis, 59 anti-LG1 encephalitis, 60 rheumatoid arthritis, 61 and juvenile idiopathic arthritis. 62 Notably, there are multiple reports of a significant association between HLA-DRB4 and development of Hashimoto’s Thyroiditis. 63 – 65 This finding demonstrates potential similarities between irAEs and autoimmune diseases, suggesting that certain HLA genotypes may predispose to endocrine irAEs. Ongoing challenges with identifying a specific allele associated with development of disease include the MHC region having the highest gene density in the human genome, extended haplotypes having other plausible candidate genes, and associated diseases not presenting in a Mendelian inheritance pattern. Further investigation with family studies, a larger cohort, and more diverse population are necessary to explore these challenges. Additionally, future studies should assess the impact of linkage disequilibrium with stratification of HLA haplotypes. This study has several important limitations. While prospective, the number of patients is small, and not powered to detect survival differences between HLADRB4 allele subtypes. Secondly, this is a single institution study with predominantly Caucasian male patients. Multi-institutional studies with more diverse patient populations will be needed. Finally, the toxicity rate was overall relatively low, possibly secondary to predominately single agent ICI utilization. In conclusion, our study is the first to report that a subset of patients with metatstatic NSCLC and expression of HLA-DRB4 are more likely to have improved survival outcomes. We also found that HLA-DRB4 expression led to increased likelihood of developing endocrine irAEs while on ICI therapy. Future studies are needed to validate HLA-DRB4 as a predictive biomarker for survival and development of endocrine irAEs. Additionally, mechanistic studies aimed at understanding if there is a conserved antigen presented by HLA-DRB4 which drives irAE development that result in cross presentation of tumor antigens and ICI benefit are needed. Declarations Funding: This work was supported by the Veterans Affairs Merit Award I01CX001560 to Nithya Ramnath Competing interests: The authors have no relevant financial or non-financial interests to disclose. Author Contributions: CYJ: Methodology, investigation, data analysis and interpretation, writing – original draft, writing – revising and editing. LZ: Data analysis and interpretation, writing- original draft, writing – revising and editing. MDG: writing- revising and editing. SR: investigation, data analysis and interpretation, writing- original draft, writing- revising and editing. AMHT: TCRB bulk NGS sequencing and genomic DNA extractions on all specimens, writing- revising and editing. AJS : identification of population level HLA Class II- DRB4, MR: writing – revising and editing. MFC: writing – revising and editing. EHW: writing – revising and editing. NR: Conceptualization, methodology, data interpretation, writing – revising and editing, supervision. Data Availability: The dataset analyzed during this current study is available from the corresponding author upon request. Ethics approval: Approved by VA Ann Arbor Healthcare System institutional review board and ethics committee. 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Nat Rev Immunol. 10 2018;18(10):635–647. doi: 10.1038/s41577-018-0044-0 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Jan, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Major revision 21 Sep, 2023 Reviews received at journal 16 Sep, 2023 Reviewers agreed at journal 28 Aug, 2023 Reviews received at journal 01 Aug, 2023 Reviewers agreed at journal 14 Jul, 2023 Reviewers agreed at journal 13 Jul, 2023 Reviewers invited by journal 13 Jul, 2023 Editor assigned by journal 13 Jul, 2023 Editor invited by journal 19 May, 2023 Submission checks completed at journal 19 May, 2023 First submitted to journal 12 May, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Kettles VA Medical Center VA Ann Arbor Healthcare System","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Nithya","middleName":"","lastName":"Ramnath","suffix":""}],"badges":[],"createdAt":"2023-05-12 21:29:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2929223/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2929223/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-023-48546-y","type":"published","date":"2024-01-03T15:01:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":37381591,"identity":"44beb7cc-42b1-4a05-bf90-615aeeaccd6e","added_by":"auto","created_at":"2023-05-23 14:12:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":160546,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier Analysis of Overall Survival in Patients with HLA-DRB4 present and without HLA-DRB4 present\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend: N= HLA-DRB4 not present, Y = HLA-DRB4 present\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2929223/v1/f00366c724c1940b9cd2940b.png"},{"id":37381594,"identity":"966971fe-f9e6-4b83-8694-81126c9e98b7","added_by":"auto","created_at":"2023-05-23 14:12:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":269715,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier Analysis of Progression Free Survival in Patients with HLA-DRB4 present and without HLA-DRB4 present\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend: N= HLA-DRB4 not present, Y = HLA-DRB4 present\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2929223/v1/01398722bbf8ffd62665d687.png"},{"id":37381593,"identity":"50435b42-429b-4c7e-ae96-acc6c38b234c","added_by":"auto","created_at":"2023-05-23 14:12:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":120552,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative Incidence of Endocrine irAEs Based on HLA-DRB4 Expression\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLegend: N= HLA-DRB4 not present, Y = HLA-DRB4 present\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2929223/v1/dc31be95985618b7a040c7c4.png"},{"id":37382652,"identity":"199e2551-f724-4acc-87ae-fc58d596b589","added_by":"auto","created_at":"2023-05-23 14:20:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":102277,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map comparing HLA class I and II genotypes between Endocrine irAE and no Endocrine irAE patients\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-2929223/v1/8a6931e9965ff194a8fc8861.png"},{"id":49315785,"identity":"b7fda143-58a0-4c80-9317-1f9e924d3faf","added_by":"auto","created_at":"2024-01-08 15:10:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":758881,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2929223/v1/33847f5d-38e2-4824-bb20-d91dbcae7ddc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn the United States, lung cancer is the third most common cancer with over 236,700 new cases in 2022 and the leading cause of cancer deaths, accounting for 24% of all cancer related deaths.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Around 85% of lung cancer cases are non-small cell lung cancer (NSCLC).\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e While surgery and stereotactic body radiotherapy are potentially curative for early stage disease, the majority of patients present with locally advanced or metastatic disease which is more refractory to treatment.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Historically, for patients with locally advanced disease, the 5-year survival after chemoradiation was 32%\u003csup\u003e4\u003c/sup\u003e, and for patients with metastatic disease, the 2-year survival after chemotherapy was 11%.\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eImmune checkpoint inhibitors (ICIs) have considerably improved the outcomes of patients with all stages of lung cancer. Neoadjuvant nivolumab plus ipilimumab prior to surgical resection of Stage I/II NSCLC results in complete pathologic responses in as many as 38% of patients.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Resectable NSCLC patients who received neoadjuvant nivolumab in combination with chemotherapy experienced improved progression free survival to 77%\u003csup\u003e7\u003c/sup\u003e and complete pathologic response in 24% of patients.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The addition of adjuvant durvalumab following chemoradiation in Stage III NSCLC improves the 5-year overall survival to 43%.\u003csup\u003e9\u003c/sup\u003e Finally, the use of pembrolizumab in metastatic NSCLC patients has improved the 5-year overall survival to 31%.\u003csup\u003e10\u003c/sup\u003e Other regimens include combination of chemotherapy (platinum based plus pemetrexed) and pembrolizumab, atezolizumab +/- chemotherapy and bevacizumab, cemiplimab, nivolumab plus ipilimumab +/- chemotherapy.\u003csup\u003e\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e This has led to widespread use of ICI across all stages of NSCLC. However, not all patients may experience benefit from immunotherapy and identification of predictive biomarkers is crucial.\u003c/p\u003e \u003cp\u003eCurrently, the only clinically approved biomarker for immunotherapy in NSCLC patients is program death ligand 1 (PDL-1) and it plays an important role in treatment decision making.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e There has been exploration of other potential biomarkers, such as tumor mutational burden (TMB), deficient mismatch repair, microsatellite instability, tumor infiltrating lymphocytes (TIL), gut microbiome, microRNA, and peripheral markers (i.e. neutrophil to lymphocyte ratio and lactate dehydrogenase), but no additional predictive biomarkers have been validated.\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Class I and II human leukocyte antigens (HLA) are encoded by major histocompatibility complex (MHC) genes and have emerged as an area of strong interest for predictive biomarker discovery.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e HLA class I proteins (HLA A, B, and C) are widely expressed on all nucleated cells and present antigens to CD8\u0026thinsp;+\u0026thinsp;T cells\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. HLA class II proteins (HLA DP, DQ, DR) have limited expression predominantly on antigen presenting cells (i.e. dendritic cells, macrophages, B cells) and present antigens to CD4\u003csup\u003e+\u003c/sup\u003e T cells.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e The HLA system is critical for self vs non-self-discrimination by the immune system as well as for the detection of cancer. Loss of HLA Class I has emerged as an important immune evasion mechanism in NSCLC\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, and specific HLA class I alleles have been associated with immunotherapy efficacy and toxicity.\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25 CR26\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e For example, HLA-A*03 and HLA-B62 supertype have been found to predict poor response to immunotherapy, while HLA-B44 supertype predicts for improved survival.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e In most studies, patient\u0026rsquo;s are more commonly tested for HLA class I genotypes. This has led to limited clinical studies examining the association between HLA class II antigens and immontherapy efficacy. The current available studies note that increased HLA class II related gene expression correlates with improved outcomes.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Notably, higher HLA-DR expression has been suggested to predict response to ICI.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eICIs are associated with a unique spectrum of side effects known as immune related adverse events (irAEs). irAEs can affect any organ, with the most commonly affected organs including the skin, colon, liver, lungs, and endocrine glands.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e While the majority of irAEs in patients with NSCLC are low grade, severe side effects requiring therapy discontinuation occur in up to 20% of Stage III NSCLC patients\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and in 17% of patients with Stage IV NSCLC.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Fulminant and fatal toxicities may occur.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Management relies on immunosuppression with glucocorticoids, TNFa antagonists, or other agents, but, on occasion these therapies have resulted in tumor progression.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Immune checkpoints play a role in limiting autoimmune disease, and therefore, use of checkpoint inhibitors triggers autoimmune off- target inflammation in normal tissues. Consistent with this, irAEs occur with higher frequency in patients with autoimmune antibodies.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e However, there is limited understanding of whether germline determinants regulate irAE development.\u003c/p\u003e \u003cp\u003eHerein, we examined patients with metastatic NSCLC who received immunotherapy and primarily evaluated the correlation between HLA class II genotype and treatment efficacy. Secondarily, we conducted an exploratory analysis on HLA class II and the development of immune related adverse events (irAEs).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eWe conducted a prospective study that involved the collection of baseline tumor biopsy and blood samples in patients being treated with ICIs for metastatic NSCLC to identify biomarkers predictive of therapeutic response and toxicity. The study was conducted at the Veterans Administration, Ann Arbor Healthcare System (VAAAHS). Enrollment for the study began November 2015 and ended in June 2022. Study eligibility for patients included diagnosis of metastatic NSCLC and initiation of ICI therapy. A total of 85 patients with clinical outcomes and HLA genotype data are available. All patients were reviewed for the development of any adverse event and both classification and grading were based on the Common Terminology Criteria for Adverse Events version 5.0 (CTCAE). Our study did not include additional review of adverse events by independent investigators.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eHLA Genotyping Data\u003c/h2\u003e \u003cp\u003eHLA genotyping was completed via ScisGo HLA typing kits (Scisco Genetics, Seattle, WA). The full standardized protocol is available online.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e DNA was extracted from patient blood and this was followed by genomic DNA quantification and library preparation using the ScisGo HLA Typing Kit. HLA genotypes of each patient were directly compared to each other and closely analyzed for similarities and presence of HLA loci known to be associated with autoimmune endocrine disorders.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics of the clinical and demographic data included mean, median, and range for numerical variables as well as percentages for categorical variables. Important clinical and demographic data included gender, race, histology, smoking history, performance status, and prior therapies. Progression free survival (PFS) was defined as time from imunnotherapy start to radiographic disease progression. Overall survival (OS) was defined as time from immunotherapy start to death or date of last follow up. Kaplan-Meier methods were used to estimate the PFS and OS functions, and log-rank tests were used for the comparisons. Cox proportional hazards regression was used to assess the association between HLA- DRB4 and PFS/OS, adjusting for age, gender, race, stage, smoking history, and histology. To further study the association of irAE to survival, we included it as a time-varying covariate in the Cox model. The time-varying covariate had a value of 0 before the irAE and 1 after irAE; for patients who did not have irAE, this covariate had a value of 0 during the entire follow-up period. SAS (version 9.4) was used for the analyses and significance was defined by a two-tailed p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. To assess association between HLA-DRB4 and development of endocrine irAEs, cumulative incidence functions were used and significance was based on Gray\u0026rsquo;s test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy Approval\u003c/h2\u003e \u003cp\u003e This clinical study was approved by the VA Ann Arbor Healthcare System institutional review board and ethics committee. Written informed consent was obtained from all patients. All research was performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient Demographics\u003c/h2\u003e \u003cp\u003eThere were 98 eligible cancer patients with metastatic NSCLC enrolled on this study. Of these, 85 (86%) had complete clinical data and adequate baseline DNA for HLA genotype analysis. Most patients were men (96.5%), majority were former/active smokers (98.8%), and the median age was 72 years (IQR 66\u0026ndash;75). The patients were predominantly Caucasian (75.3%). Prior to receiving ICI therapy, 21.2% had received chemotherapy only and 49.4% had received both chemotherapy and radiation therapy. All patients who received chemotherapy were exposed to platinum regimens (n\u0026thinsp;=\u0026thinsp;60). The average number of prior therapies (prior to immunotherapy) was 0.92 (range 0\u0026ndash;2). Other therapies tried before immunotherapy included carboplatin/pemetrexed, cisplatin/etoposide, carboplatin/paclitaxel, carboplatin/etoposide, carboplatin/gemcitabine, cisplatin/vinorelbine, cisplatin/gemcitabine, carboplatin/pemetrexed/bevacizumab, and cisplatin/docetaxel. Most patients received pembrolizumab (83.5%) with 14 receiving pembrolizumab in conjunction with carboplatin and pemetrexed. Other ICIs included durvalumab and nivolumab. 20 patients (23.5%) developed irAEs: 11 with endocrine irAEs (diabetes\u0026thinsp;=\u0026thinsp;1; thyroiditis\u0026thinsp;=\u0026thinsp;5, adrenal insufficiency\u0026thinsp;=\u0026thinsp;2, and both =\u0026thinsp;3) and 9 with other irAEs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Demographics and Clinical Characteristic\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePts w/o Endocrine irAEs (n\u0026thinsp;=\u0026thinsp;74)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePts w/Endocrine irAEs (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years \u0026ndash; Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (65.3\u0026ndash;73.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 (65-72.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003cp\u003eMale\u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eFemale \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (95.9)\u003c/p\u003e \u003cp\u003e3 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (100)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Identified Race\u003c/p\u003e \u003cp\u003eWhite, Caucasian \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eAfrican American \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eHawaiian or Pacific Islander \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eDid not declare \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (74.3)\u003c/p\u003e \u003cp\u003e9 (12.2)\u003c/p\u003e \u003cp\u003e2 (2.7)\u003c/p\u003e \u003cp\u003e8 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (81.8)\u003c/p\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003cp\u003eSquamous \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eAdenocarcinoma \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eAdenosquamous \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003ePoorly Differentiated \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eUnknown \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (35.1)\u003c/p\u003e \u003cp\u003e43 (58.1)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e4 (5.4)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (45.5)\u003c/p\u003e \u003cp\u003e5 (45.5)\u003c/p\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharleston Comorbidity Index \u0026ndash; Mean (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.7 (4\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.8 (9\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePack years \u0026ndash; Mean (range)\u003c/p\u003e \u003cp\u003eFormer smoker \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eActive smoker \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eNever smoker \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.6 (1-165)\u003c/p\u003e \u003cp\u003e48 (64.9)\u003c/p\u003e \u003cp\u003e26 (35.1)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.0 (0-110)\u003c/p\u003e \u003cp\u003e8 (72.7)\u003c/p\u003e \u003cp\u003e2 (18.2)\u003c/p\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Therapies\u003c/p\u003e \u003cp\u003ePrior Chemotherapy Only \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003ePrior Radiation Therapy Only \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003ePrior Chemotherapy\u0026thinsp;+\u0026thinsp;Radiation \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eNo Prior Therapy \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (18.9)\u003c/p\u003e \u003cp\u003e14 (18.9)\u003c/p\u003e \u003cp\u003e37 (50.0)\u003c/p\u003e \u003cp\u003e9 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (36.4)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e7 (63.6)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICI Therapy\u003c/p\u003e \u003cp\u003ePembrolizumab \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eNivolumab \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eDurvalumab \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (83.8)\u003c/p\u003e \u003cp\u003e4 (5.4)\u003c/p\u003e \u003cp\u003e8 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (90.9)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of ICI cycles \u0026ndash; Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1\u0026ndash;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (3\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDurable Clinical Benefit\u003c/p\u003e \u003cp\u003eYes \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eNo \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eUnknown \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (40.5)\u003c/p\u003e \u003cp\u003e42 (56.8)\u003c/p\u003e \u003cp\u003e2 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (81.8)\u003c/p\u003e \u003cp\u003e2 (18.2)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmune Related Adverse Event\u003c/p\u003e \u003cp\u003eThyroiditis only \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eAI only \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eBoth Thyroiditis and AI \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eDiabetes \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eEncephalitis \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eArthralgia \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003ePneumonitis \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eBullous Pemphigoid \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003ePruritis \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eRash \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eTransaminitis \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003cp\u003e2 (2.7)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003cp\u003e2 (2.7)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (45.5)\u003c/p\u003e \u003cp\u003e2 (18.2)\u003c/p\u003e \u003cp\u003e3 (27.3)\u003c/p\u003e \u003cp\u003e1 (9.1)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime from ICI initiation to irAE, months \u0026ndash; Median (range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.6 (2.8\u0026ndash; 27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.37 (1.5\u0026ndash;58.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatus at Last Follow-Up\u003c/p\u003e \u003cp\u003eDeceased \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eAlive \u0026ndash; No. (%)\u003c/p\u003e \u003cp\u003eDiscontinued ICI Therapy \u0026ndash; No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (74.3)\u003c/p\u003e \u003cp\u003e19 (25.7)\u003c/p\u003e \u003cp\u003e64 (86.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (45.5)\u003c/p\u003e \u003cp\u003e6 (54.5)\u003c/p\u003e \u003cp\u003e11 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eOverall Treatment Efficacy\u003c/h2\u003e \u003cp\u003eThe median follow-up time for all 85 patients was 42.8 months (IQR 23.7\u0026ndash;63.6). The median PFS was 6.7 months (IQR 2.1\u0026ndash;20.9) and median OS was 13.2 months (IQR 6.05\u0026ndash;33.9). 39/85 (45.9%) of patients experienced durable clinical benefit, defined as response or stable disease on therapy at \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;6 months. 9 patients remained alive for \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;36 months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eHLA Characteristics\u003c/h2\u003e \u003cp\u003eWe assessed the complete HLA genotype in all patients. Overall, the most common HLA class I types were HLA-C*07 (n\u0026thinsp;=\u0026thinsp;46), HLA-A*02 (n.= 43), and HLA-A*03 (n\u0026thinsp;=\u0026thinsp;27). The most frequent HLA class II genotypes were HLA-DPA1*01 (n\u0026thinsp;=\u0026thinsp;82), HLA-DPB1*04 (n\u0026thinsp;=\u0026thinsp;62), and HLA-DQA1*01 (n\u0026thinsp;=\u0026thinsp;61). HLA-DRB4*01 was present in 39 patients.\u003c/p\u003e \u003cp\u003eHLA-DRB4 Allele Variation\u003c/p\u003e \u003cp\u003eAllelic variation is an important determinant of HLA function.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e To explore whether specific HLA-DRB4 subtypes were associated with ICI treatment tolerance, we examined these more closely. Interestingly, all the patients with both thyroiditis and adrenal insufficiency (3/3) had HLA-DRB4 *01:03:01 as well as 40% of the patients with thyroiditis only (2/5) and one patient with diabetes (1/1). HLA-DRB4 *01:01:01 was present in two patients with adrenal insufficiency only and an additional patient with thyroiditis only. For patients who developed other types of irAEs, HLA-DRB4 *01:03:01 was present in 44.4% of the patients (4/9). In patients who did not develop any irAEs, HLA-DRB4 was present in 40% (n\u0026thinsp;=\u0026thinsp;26) of patients with HLA-DRB4*01:03:01 allele predominating in 84.6% of the patients (n\u0026thinsp;=\u0026thinsp;22), HLA-DRB4 *01:01:01 in 11.5% of the patients (n\u0026thinsp;=\u0026thinsp;3), and HLA-DRB4*01:03:02 in 2.7% of patients (n\u0026thinsp;=\u0026thinsp;1). 6 out of the 39 patients with HLA-DRB4 present were homozygous with two of these patients developing endocrine irAEs. The remaining patients were heterozygous (n\u0026thinsp;=\u0026thinsp;30) or did not have the second allele present (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation between HLA-DRB4 and Survival\u003c/h2\u003e \u003cp\u003ePresence of HLA-DRB4 correlated with improved OS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0085\u003c/em\u003e by log-rank; median OS 26.3 months vs 8.8 months) (See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e KM curve) and PFS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.040\u003c/em\u003e by log-rank; median PFS 9.9 months vs. 4.6 months) (See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e KM curve). We assessed OS for HLA-DRB4*01:03:01 compared to other allele types (HLA-DRB4*01:01:01 plus HLA-DRB4*01:03:02) and no HLA-DRB4 presence (median OS 21.4 vs not reached vs 8.8 months) and found that other allele types (HLA-DRB4*01:01:01 plus HLA-DRB4*01:03:02) had the best OS (p\u0026thinsp;=\u0026thinsp;0.015 by log rank). However, when comparing PFS between HLA-DRB4*01:03:01, other allele groups, and no HLA-DRB4 presence (median PFS 9.7 vs 22.6 vs 4.6 months) there was no significant statistical difference (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.080\u003c/em\u003e by log-rank).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMultivariable Analysis\u003c/p\u003e \u003cp\u003eAfter adjusting for age, gender, race, stage, and histology, presence of HLA-DRB4 was associated with improved OS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.003\u003c/em\u003e, HR 0.40, 95% CI [0.21, 0.73]) and PFS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0310\u003c/em\u003e, HR 0.55, 95% CI [0.31, 0.95]).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDescription of irAEs\u003c/h2\u003e \u003cp\u003eOf the 85 patients identified, 11 developed endocrine irAEs (12.9%). 10 (90.9%) patients received pembrolizumab and 1 received durvalumab (9.1%). The most frequent toxicity grade was 1 (n\u0026thinsp;=\u0026thinsp;5). Overall, patient clinical characteristics and demographics were similar between those who developed endocrine irAEs and those who did not (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Thyroiditis was the most common endocrine irAE (n\u0026thinsp;=\u0026thinsp;5) followed by both thyroiditis and adrenal insufficiency (n\u0026thinsp;=\u0026thinsp;3), adrenal insufficiency alone (n\u0026thinsp;=\u0026thinsp;2), and diabetes (n\u0026thinsp;=\u0026thinsp;1). No patients in this cohort experienced new onset hyperthyroidism or hypoparathyroidism. The management and impact of endocrine irAEs on patients is outlined in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eClinical Description of Patients with Endocrine irAEs\u003c/b\u003e *Ethnicity: AA\u0026thinsp;=\u0026thinsp;African American; **Endocrine irAE: T\u0026thinsp;=\u0026thinsp;thyroiditis, AI\u0026thinsp;=\u0026thinsp;adrenal insufficiency, DM\u0026thinsp;=\u0026thinsp;diabetes mellitus; ***Initial Treatment/Continued Treatment: L\u0026thinsp;=\u0026thinsp;levothyroxine, H\u0026thinsp;=\u0026thinsp;hydrocortisone, P\u0026thinsp;=\u0026thinsp;prednisone\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICI Therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePembro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDurva\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior Endo Conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes \u0026ndash; hypothyroid 2/2 Radiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes \u0026ndash;\u003c/p\u003e \u003cp\u003eHypothyroid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndocrine irAE**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT; AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eT; AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eT; AI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eirAE Grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1; 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to Onset -months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.13; 9.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.27; 3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.37; 10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e58.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther irAEs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecolitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eColitis, dermatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003epneumonitis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial Treatment***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL; H then P, back to H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eL; P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eL; P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eL; P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eL; H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMetformin, lantus, aspart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eSteroid taper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContinued Treatment***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL; weaned off steroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eL; H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMetformin, lantus, aspart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSH Baseline/ After ICI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.29/11.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.40/7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9/116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45/2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72/76.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.79/97.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.37/8.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.64/21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.80/1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.18/7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.66/5.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAM Cortisol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACTH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCosyntropin Simulation Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.1 --\u0026gt; 11.6 --\u0026gt; 14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0 --\u0026gt; 0.7 --\u0026gt; 9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICI Status post-irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContinued until PD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eContinued until surveillance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDiscontinued prior to irAE given PD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eContinued until PD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHeld 2/2 irAE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEndocrine irAEs and HLA Characteristics\u003c/p\u003e \u003cp\u003eAmong the 11 patients that developed endocrine irAEs, we noted HLA-C*07 (n\u0026thinsp;=\u0026thinsp;6) and HLA-A*02 (n\u0026thinsp;=\u0026thinsp;5) as the most predominant Class I HLA gene and HLA-DPA1*01 (n\u0026thinsp;=\u0026thinsp;11) and HLA-DRB4*01 (n\u0026thinsp;=\u0026thinsp;9) were the most frequent Class II HLA genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The Allele Frequency Net Database notes that HLA-DPA1*01 is very common in the United States (US) Amerindian population and the European Caucasians with 95% of individuals having the allele. \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e In comparison, HLA-DRB4 is less common in the US Caucasian population and present in approximately 40\u0026ndash;50% individuals, this was estimated based on limited available data. \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Thirty-nine of of 85 (45.9%) patients in our cohort had HLA-DRB4, with 9/11 (81.8%) patients with endocrine irAEs presenting the HLA-DRB4 genotype (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHLA-DRB4 Presence in Patients with Endocrine irAEs vs Other irAEs vs No irAEs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHLA-DRB4 Present\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHLA-DRB4 Not Present\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePts w/Endocrine irAEs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePts w/Other irAEs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePts w/o irAEs (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (40.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e65\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e46\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between HLA-DRB4 and irAEs\u003c/h2\u003e \u003cp\u003ePatients were assessed for the cumulative incidence of endocrine irAEs over time based on the the presence of HLA-DRB4. We found that patients who expressed HLA-DRB4 were statistically more likely to develop incidences of endocrine irAE\u0026rsquo;s compared to those who did not have HLA-DRB4 present (p\u0026thinsp;=\u0026thinsp;0.0139 by Gray\u0026rsquo;s test, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation between irAEs and Survival\u003c/h2\u003e \u003cp\u003eTo investigate if development of irAEs correlated with ICI therapy efficacy, we carefully assessed survival outcomes. The presence of any irAE (endocrine or other) did not statistically improve PFS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.226\u003c/em\u003e, HR 0.61, 95% CI [0.268,1.365]) or OS \u003cem\u003e(p\u0026thinsp;=\u0026thinsp;0.219\u003c/em\u003e, HR 0.63, 95% CI [0.301,1.316]). When comparing survival outcomes between endocrine and other irAEs, there was again no statistically significant improvement in PFS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.530\u003c/em\u003e, HR 0.5, 95% CI [0.230\u0026ndash;17.4])\u003c/p\u003e \u003cp\u003eMultivariable Analysis\u003c/p\u003e \u003cp\u003eAfter adjusting for age, gender, race, stage, and histology, the development of any irAE did not improve PFS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.085)\u003c/em\u003e, HR 0.339, 95% CI [0.099, 1.162]) or OS (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.275\u003c/em\u003e, HR 0.636, 95% CI [0.282,1.434]). Multivariable analysis of endocrine irAE patients was not possible given the small sample size.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eImmunotherapy has significantly improved lung cancer outcomes. However, there remains a population of patients who do not benefit from therapy and others who experience fulminant toxicities. Preclinical and translational studies have identified primary and acquired mechanisms of resistance\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e including hepatic siphoning,\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e tumoral loss of HLA Class I,\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e T cell chemokine silencing,\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e and immunometabolic checkpoints.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e Preclinical and translational work have begun to identify the cellular mediators of immune related adverse events, including hepatitis,\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e thyroiditis,\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e and colitis.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur study revealed a significant correlation between HLA-DRB4 and improved PFS and OS, on both univariable and multivariable analysis and to our knowledge this is the first such report. Other studies have reported on different HLA class II genes, such as Correale et al noting longer survival in patients who were heterozygous for HLA DRB1.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Yang et al explored clinical outcomes in patients who received both immunotherapy and chemotherapy with findings of increased expression of HLA class II genes being associated with improved survival.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e In their study, HLA-DMB, HLA-DOA, HLA-DPB1, and HLA-DMA were included in the top HLA genes related to outcomes. More recently, HLA-A*03 has been associated with inferior outcomes in patients receiving ICIs.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e In our study, we looked at allele variation and found improved OS with allele subtypes HLA-DRB4*01:01:01 in comparison to HLA-DRB4*01:03:01. However, our study was not powered to make significant conclusions as we had more patients with HLA-DRB4*01:03:01 compared to other allele subtypes. Other groups have described an inverse correlation between loss of heterozygosity (LOH) for HLA Class I and II loci in tumors with survival. Schaafsma et al reported that any presence of Class I or II is protective and may result in improved activity from immune checkpoint inhibitors.\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e Interestingly, presence of any Class I or Class II in the tumor bearing cells was associated with improved survival in this cohort of patients, derived from multiple datasets of patients on ICIs. Importantly, this study was based on somatic expression and not germline. In non-small-cell lung cancers, HLA LOH occurs in 40% of early-stage cancers. \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Additionally, the HLA homozygosity was preferentially selected for at metastatic cancer sites. \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Advanced cancer patients that were heterozygous at all HLA class I loci had improved survival as compared to patients who were homozygous at any one locus. \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Furthermore, Schaafsma et al observed significant increase in an HLA class II gene expression when comparing patients with and without clinical benefit in on-treatment samples as compared to pre-treatment samples, suggesting that on-treatment samples are more informative of clinical benefit when using HLA class II gene expression as an indicator of response. \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e This was not the case for HLA class I genes, which showed much less significance in on-treatment samples compared to HLA class II genes, suggesting that HLA class II genes might be more important for an effective response to ICI therapy. The importance of HLA class II genes has been shown in the context of ICI therapy in a number of studies.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e It is proposed that the activation of CD4\u0026thinsp;+\u0026thinsp;T cells by HLA class II expression helps to initiate CD8\u0026thinsp;+\u0026thinsp;T cells that consequently mount a successful antitumor immune response during ICI therapy. \u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e Our study was limited by lack of on treatment biopsy to confirm this phenomenon. Furthermore, the LOH status sof HLADRB4 in tumor samples were not available, given the limited lung cancer panel that was used for molecular testing as part of clinical care in these patients. Future studies should correlate germline and somatic status of Class II HLA genotypes with ICI response.\u003c/p\u003e \u003cp\u003eSecondarily, we found a significant association between HLA DRB4 presence and incidence of endocrine irAEs. We found an overrepresentation of HLA-DRB4 in 13/20 patients with any degree of irAEs and 9/11 patients with endocrine irAEs. In comparison, only 40\u0026ndash;50% of the general Caucasian population express HLA-DRB4.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e This observation has not been previously reported. Extensive genetic polymorphisms and high a degree of homology within the HLA locus make it challenging to HLA type patients. \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e The exact mechanism leading to the development of irAEs is not clear, however there have been translational studies indicating the involvement of autoreactive T cells, autoantibodies, and pro-inflammatory cytokines.\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e The blockade of checkpoints like PD-1 allows T-cells to react against self antigens presented by HLA, and this in turn can led to inflammatory damage to normal organ tissue where these checkpoints are normally found.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e HLA-DRB4 has been linked to a number of autoimmune diseases, including autoimmune hepatitis,\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e type 1 diabetes,\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e autoimmune myocarditis,\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e anti-LG1 encephalitis,\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e rheumatoid arthritis,\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e and juvenile idiopathic arthritis.\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e Notably, there are multiple reports of a significant association between HLA-DRB4 and development of Hashimoto\u0026rsquo;s Thyroiditis.\u003csup\u003e\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e This finding demonstrates potential similarities between irAEs and autoimmune diseases, suggesting that certain HLA genotypes may predispose to endocrine irAEs. Ongoing challenges with identifying a specific allele associated with development of disease include the MHC region having the highest gene density in the human genome, extended haplotypes having other plausible candidate genes, and associated diseases not presenting in a Mendelian inheritance pattern. Further investigation with family studies, a larger cohort, and more diverse population are necessary to explore these challenges. Additionally, future studies should assess the impact of linkage disequilibrium with stratification of HLA haplotypes.\u003c/p\u003e \u003cp\u003eThis study has several important limitations. While prospective, the number of patients is small, and not powered to detect survival differences between HLADRB4 allele subtypes. Secondly, this is a single institution study with predominantly Caucasian male patients. Multi-institutional studies with more diverse patient populations will be needed. Finally, the toxicity rate was overall relatively low, possibly secondary to predominately single agent ICI utilization.\u003c/p\u003e \u003cp\u003eIn conclusion, our study is the first to report that a subset of patients with metatstatic NSCLC and expression of HLA-DRB4 are more likely to have improved survival outcomes. We also found that HLA-DRB4 expression led to increased likelihood of developing endocrine irAEs while on ICI therapy. Future studies are needed to validate HLA-DRB4 as a predictive biomarker for survival and development of endocrine irAEs. Additionally, mechanistic studies aimed at understanding if there is a conserved antigen presented by HLA-DRB4 which drives irAE development that result in cross presentation of tumor antigens and ICI benefit are needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by the Veterans Affairs Merit Award I01CX001560 to Nithya Ramnath\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCYJ:\u003c/strong\u003e Methodology, investigation, data analysis and interpretation, writing \u0026ndash; original draft, writing \u0026ndash; revising and editing.\u0026nbsp;\u003cstrong\u003eLZ:\u003c/strong\u003e Data analysis and interpretation, writing- original draft, writing \u0026ndash; revising and editing.\u0026nbsp;\u003cstrong\u003eMDG:\u003c/strong\u003e writing- revising and editing.\u0026nbsp;\u003cstrong\u003eSR:\u003c/strong\u003e investigation, data analysis and interpretation, writing- original draft, writing- revising and editing.\u0026nbsp;\u003cstrong\u003eAMHT:\u003c/strong\u003e TCRB bulk NGS sequencing and genomic DNA extractions on all specimens, writing- revising and editing.\u0026nbsp;\u003cstrong\u003eAJS\u003csup\u003e:\u003c/sup\u003e\u003c/strong\u003eidentification of population level HLA Class II- DRB4,\u0026nbsp;\u003cstrong\u003eMR:\u003c/strong\u003e writing \u0026ndash; revising and editing.\u0026nbsp;\u003cstrong\u003eMFC:\u003c/strong\u003e writing \u0026ndash; revising and editing.\u0026nbsp;\u003cstrong\u003eEHW:\u003c/strong\u003e writing \u0026ndash; revising and editing.\u0026nbsp;\u003cstrong\u003eNR:\u0026nbsp;\u003c/strong\u003eConceptualization, methodology, data interpretation, writing \u0026ndash; revising and editing, supervision.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe dataset analyzed during this current study is available from the corresponding author upon request.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eApproved by VA Ann Arbor Healthcare System institutional review board and ethics committee.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to publish:\u003c/strong\u003e Informed consent given for publications.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCancer Stat Facts: Lung and Bronchus Cancer. 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Nat Rev Immunol. 10 2018;18(10):635\u0026ndash;647. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41577-018-0044-0\u003c/span\u003e\u003cspan address=\"10.1038/s41577-018-0044-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"immune check point inhibitor, immune related adverse events, human leukocyte antigen, toxicity, lung cancer","lastPublishedDoi":"10.21203/rs.3.rs-2929223/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2929223/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eImmune checkpoint inhibitors (ICI) are important treatment options for metastatic non-small cell lung cancer (NSCLC). However, not all patients benefit from ICIs and can experience immune related adverse events (irAEs). Limited understanding exists for germline determinants of ICI efficacy and toxicity, but human leukocyte antigen (HLA) has emerged as a potential predictive biomarker. We obtained HLA genotypes from 85 metastatic NSCLC patients on ICI therapy and analyzed the impact of HLA Class II genotype on progression free survival (PFS), overall survival (OS), and irAEs. Most patients received pembrolizumab (83.5%). HLA-DRB4 correlated with improved survival in both univariable (PFS 9.9 months, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.040;\u003c/em\u003e OS 26.3 months, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0085\u003c/em\u003e) and multivariable analysis (PFS \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0310, HR 0.55, 95% CI [0.31, 0.95])\u003c/em\u003e; OS \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.003, HR 0.40, 95% CI [0.21, 0.73]).\u003c/em\u003e 11 patients developed endocrine irAEs. HLA-DRB4 was expressed in 39/85 (45.9%) patients and was the predominant genotype for endocrine irAEs (9/11, 81.8%). Cumulative incidence of endocrine irAEs was higher in patients with HLA-DRB4 (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0139).\u003c/em\u003e Our study is the first to suggest metastatic NSCLC patients on ICI therapy with HLA-DRB4 genotype experienced improved survival outcomes. Additionally, we found a correlation between HLA-DRB4 and endocrine irAEs.\u003c/p\u003e","manuscriptTitle":"Class II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-05-23 14:12:42","doi":"10.21203/rs.3.rs-2929223/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-09-21T10:07:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-09-17T00:05:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"baeb5f0f-4b40-4737-b57a-d55b80a30a3c","date":"2023-08-28T21:08:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-08-01T21:21:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6a7c1e9e-2e1a-4a66-8a69-da5ef48c1a6a","date":"2023-07-14T14:33:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"ee4b17f5-974b-402c-8f76-ef1c2d1349f6","date":"2023-07-13T15:34:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-07-13T15:21:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-07-13T08:55:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-05-19T09:57:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-05-19T09:36:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2023-05-12T21:24:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6a639e36-66de-4282-8d87-4eb4ac497633","owner":[],"postedDate":"May 23rd, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":21650026,"name":"Biological sciences/Cancer/Lung cancer"},{"id":21650027,"name":"Biological sciences/Cancer"},{"id":21650028,"name":"Biological sciences/Cancer/Cancer therapy/Cancer immunotherapy"}],"tags":[],"updatedAt":"2024-01-08T15:07:01+00:00","versionOfRecord":{"articleIdentity":"rs-2929223","link":"https://doi.org/10.1038/s41598-023-48546-y","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-01-03 15:01:48","publishedOnDateReadable":"January 3rd, 2024"},"versionCreatedAt":"2023-05-23 14:12:42","video":"","vorDoi":"10.1038/s41598-023-48546-y","vorDoiUrl":"https://doi.org/10.1038/s41598-023-48546-y","workflowStages":[]},"version":"v1","identity":"rs-2929223","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2929223","identity":"rs-2929223","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}