Abstract
Objectives:
Compared to low-grade irAEs, high-grade irAEs are more often dose-limiting and can alter the long-term treatment options for a patient. Predicting the incidence of high-grade irAEs would help with treatment selection and therapeutic drug monitoring.
Materials and methods:
We performed a retrospective study of 430 stage III and IV patients with non-small cell lung cancer (NSCLC) who received an immune checkpoint inhibitor (ICI), either with or without chemotherapy, at a single comprehensive cancer center from 2015 to 2022. The study team retrieved sequencing data and complete clinical information, including detailed irAEs medical records. Fisher’s exact test was used to determine the association between mutations and the presence or absence of high-grade irAEs. Patients were analyzed separately based on tumor subtypes and sequencing platforms.
Results:
High-grade and low-grade irAEs occurred in 15.2% and 46.2% of patients, respectively. Respiratory and gastrointestinal irAEs were the two most common irAEs. The distribution of patients with or without irAEs was similar between ICI and ICI+chemotherapy-treated patients. By analyzing the mutation data, we identified five genes (MYC, TEK, FANCA, FAM123B, and MET) with mutations that were correlated with an increased risk of high-grade irAEs. For the adenocarcinoma subtype, mutations in TEK, MYC, FGF19, RET, and MET were associated with high-grade irAEs; while for the squamous subtype, ERBB2 mutations were associated with high-grade irAEs.
Conclusion:
This study is the first to demonstrate that specific tumor mutations correlate with the incidence of high-grade irAEs in patients with NSCLC treated with an ICI, providing molecular guidance for treatment selection and drug monitoring.
Keywords: Non-small cell lung cancer, sequencing, immune related adverse effect, immunotherapy
Microabstract
High grade immune-related adverse events (irAEs) in vital organs are likely to cause permanent discontinuation of ICI therapy, greatly affecting the efficacy of ICI as well as patients’ health conditions. This study analyzed the correlation between high-grade irAEs and tumor sequencing data from 430 Non-small cell lung cancer (NSCLC) patients from 2015 to 2022. Our data suggest that specific gene mutations are associated with the occurrence of high-grade irAEs which offers novel insights of post-ICI monitoring.
Introduction
Immunotherapies for treating non-small cell lung cancer (NSCLC) has revolutionized the treatment options for patients without a targetable mutation [1]. In 2015, monotherapy with an immune checkpoint inhibitor (ICI) became a standard option for patients with metastatic NSCLC due to improved overall survival (OS) as compared to chemotherapy [2, 3]. In 2018, the combination of an ICI with platinum-based chemotherapy was first approved for the first-line treatment of NSCLC without a targetable alteration in EGFR or ALK [4]. Today, an ICI, either with or without chemotherapy, remains the standard first-line treatment for most patients with advanced or metastatic NSCLC.
Although many patients benefit from ICI therapy, immune-related adverse events (irAEs) are commonly reported. irAEs can occur at any time during the treatment in up to 90% of patients, and how to predict and prevent the occurrence of irAEs remain elusive[5–7]. irAEs can occur in multiple organs, such as the lung, liver, endocrine glands, gastrointestinal tract, and skin [8]. The degree of irAEs can range from mild to severe, and it can affect the treatment regimen for the patient depending on the grade of the irAEs. Grades are accessed according to the Common Terminology Criteria for Adverse Events+ (CTCAE+) guidelines, which detail the type of irAE and the exact symptoms for each grade of irAE [9]. Low-grade irAEs (grades 1–2) generally do not lead to dose discontinuation when identified and treated promptly[6]. When a grade 1 irAE occurs, clinicians will typically continue ICI treatment with monitoring except in specific cases of neurologic, hematologic, or cardiac irAEs. When a grade 2 irAE occurs, most patients will pause treatment until the irAE has resolved or reverts to grade 1[10]. Patients may also be given corticosteroids to help relieve the symptoms, although it has been reported that this may blunt the efficacy of immunotherapy [11]. In contradistinction, high-grade irAEs (grades 3–5) usually lead to dose discontinuation. For grade 3 irAEs, the ICI is suspended indefinitely, and high doses of systemic corticosteroids are given to treat the symptoms [10]. Although patients with grade 3 irAEs will sometimes undergo eventual rechallenge with ICI, grade 4 irAEs nearly always lead to permanent discontinuation of ICI therapy, and grade 5 irAEs are defined by the death of the patient. Notably, many studies have found an association between irAEs and enhanced tumor response to ICI therapy, potentially due to the systemic over-activation of the immune system [10, 12]. However, whether such enhanced response to ICI is correlated with the grades of irAEs is largely unknown.
Because high-grade irAEs may substantially impair the ICI treatment and patients’ health conditions, there is a critical need to identify predictive biomarkers for high-grade irAEs [13]. However, history of autoimmune disease, a well-established risk factor for high-grade irAEs is only present in a fraction of patients. A melanoma-based study found that increased BMI is correlated with the development of irAE [14, 15]. Other factors that have been proposed as being potentially predictive of irAEs include neutrophil-lymphocyte ratio, autoantibody serology levels, and HLA genotypes [16]. Growing evidence suggests that gut microbial composition may play a role in irAEs, and fecal microbiota transplantation has been reported to treat colitis caused by ICI treatment [17]. Germline variants, such as immunogenetic-related gene SNPs, have also been shown to predict ICI response and irAE incidence [18]. However, the association between somatic mutations identified in tumors and incidence of irAEs remain elusive. In this study, we identified key genetic alterations that are correlated with the incidence of irAEs in patients with different subtypes of NSCLC sequenced by two platforms. Our data suggest that genetic alterations can serve as a potential predictor for high-grade irAEs that identify patients who require additional monitoring after receiving immunotherapies.
Material and Methods
Eligibility
We included patients diagnosed with NSCLC at a single comprehensive cancer center between January 2015 to December 2022 were selected. All tumor samples were collected before treatment from newly diagnosed patients, patients who received more than one treatment, and patients who did not have sequencing data were excluded. The study was approved by the institutional review board at Wake Forest School of Medicine (IRB00078147).
Clinical Variables and Outcomes
Our study team created a retrospective registry of all patients who received at least one dose of an ICI for any indication at a comprehensive cancer center and its outreach clinics. The investigators created the secure, cloud-based registry (REDCap), validated it with data quality rules, and resolved all discrepancies; clinical research specialists at Vasta Global captured most of the data. Sociodemographic, clinical characteristics, cancer subtypes, treatment types and outcomes were documented from electronic medical records. PD-L1 expression and tumor mutational burden (TMB) were reported for most patients with adequate tumor tissue for testing. PD-L1 was measured by immunohistochemistry (IHC) performed on formalin-fixed, paraffin-embedded sections using PD-L1 IHC 22C3 pharmDx and defined as unknown, <1%, 1–49%, and ≥50% of total positively stained tumor cells. We collected comorbidity outcomes from the time of ICI initiation. Patients’ immune-related adverse events (irAEs) were diagnosed based on American Society of Clinical Oncology Clinical Practice Guideline [19]. irAEs category was determined based on Common Terminology Criteria for adverse events (CTCAE) and documented throughout the therapy duration.[19]
Genomic Profiling
Genomic profiling was conducted using next-generation sequencing of tumor tissue (FoundationOne CDx, Foundation Medicine, Cambridge, MA) and circulating tumor DNA (Guardant360 CDx, Guardant Health, Redwood City, CA). Sequenced genes from both platforms were listed in Supplementary Table 1. A total of 345 genes were sequenced by FoundationOne (FM) and 78 gene were sequenced by Guardant Health (GH). All molecular testing and data analysis were performed by GH or FM. Sample preparation, NGS sequencing and identification of genomic mutation were performed as previously described. [20, 21] For Gurdant360 CDx test, ctDNA extracted from plasma were analyzed by paired-end sequencing using Illumina Hi-Seq 2000 platform and were mapped to the reference human genome (hg19) by a custom Guardant Health’s proprietary bioinformatics algorithms. Identification of mutation were performed by a custom script. For FoundationOne CDx test, library prepared from sectioned FFPE sample were sequenced by IlluminaHiSeq 2000 platform and were mapped to the reference human genome (hg19) using the Burrows-Wheeler Aligner and the publicly available SAM tools, Picard and GATK(Genome Analysis Toolkit). Identification of mutation were performed by a Bayesian algorithm.
Statistical Analysis
Fisher’s exact test was used to determine association between mutation and the presence or absence of high grade irAEs. Mutations with less than <3% were included from fisher’s exact test. Fisher’s exact test was used to assess significance (p<0.05) of gene mutation frequencies that differed between patients with high-grade irAE and patients with low-grade irAEs or without any irAEs ( referred to as patients without high-grade irAE hereafter). All analyses were performed with R statistical computer software version 4.1.3. Multivariate analyses were calculated by R glmnet package. GraphPad Prism version 8.4 was used to perform all survival analyses. For gene mutation co-occurrence and mutual exclusion Analysis, we examined the co-occurrence of genes in the signature and the top ten mutated genes in each treatment group. Fisher’s exact test was applied to detect significant somatic interactions. The Maftools package analyzed the mutation patterns and visualized the results in R 4.1.3 [22]. The log rank Matel Cox test was used to determine significance on survival graphs. A p-value less than 0.05 was used in all analyses to determine significance.
Results
Patients Characteristics
We retrospectively identified 430 patients with NSCLC that were stage III or stage IV, wild-type EGFR, and treated either with routine care or as part of a clinical trial at a single comprehensive cancer center between 2015 and 2022. The patient’s characteristics who were sequenced using tissue DNA (Foundation Medicine, FM) or circulating tumor DNA (Guardant Health, GH) are summarized in Table 1. As shown in Fig. 1A, most patients developed either no (38.6%) or low-grade (46.0%) irAEs, and around 15% of patients developed high-grade irAEs. The distribution of patients with none irAE, low grade irAEs and high grade irAEs are similar between two sequencing cohorts (Supplementary Fig. 1A). Notably, those who were treated with ICI monotherapy had a similar levels of irAEs compared to combination Chemo+ICI treated patients, suggesting that addition of chemotherapy did not increase the incidence or degree of irAEs (Supplementary Fig.1B). The length of time on treatment was similar among patients with none irAE, low-grade, and high-grade irAE (Supplementary Fig.1C). IrAEs can affect multiple organ systems and we found majority of patients had multiple irAEs (26.16%) while for single irAEs respiratory (17.80%), gastrointestinal (GI)(16.29%) and skin(13.26%) were the most common irAEs (Fig. 1B). The multiple irAEs group represents the patients who had two or more irAEs at the same time and they were considered to have high-grade irAEs if one of the symptoms reaches high-grade. We found that fatigue and respiratory irAEs are two most common irAEs that appeared at same time (Supplementary Figure 1D). Notably, respiratory and endocrine irAEs were more frequently observed in patients with high-grade irAEs while skin, circulatory, and pain related irAEs were more common in patients with low-grade irAEs (Fig. 1C). Next, we calculated how long it takes for each irAE to occur in patients with either low-grade or high-grade irAEs and found delayed occurrence of most of the high grade irAEs compared to low grade irAEs (Fig. 1D). We also found that pain related irAEs developed more rapidly in ICI treated patients compared to Chemo+ICI treated patients, whereas Chemo+ICI treated patients developed respiratory and skin related irAEs earlier than ICI treated patients (Supplementary Fig. 1E). Interestingly, all the endocrine irAEs came from patients treated with chemo + ICI compared to ICI (Supplementary Fig. 1E). Several studies reported that irAEs is correlated with an enhanced response to ICI treatment, however, it is still unclear whether the response is associated with the grade of irAEs. Kaplan-Meier analysis showed there was no significant difference in overall survival (OS) between patients with different grades of irAEs in our cohort regardless of the ICI based treatments (Fig. 1E, Supplementary Fig 1.F). No significant difference in terms of survival calculated from occurrence of irAEs to death was found between patients with low-grade or high-grade irAEs (Supplementary Fig. 1G). Previous study showed that tumor mutation burden (TMB) is positively associated with irAEs in melanoma and NSCLC patients[23]. Therefore, we examined the correlation between TMB and the grade of irAEs and found that patients with low-grade irAE had a higher TMB compared to irAE-free patients (Supplementary Fig. 1H).
Table.1.
Demographic of NSCLC clinical cohort at Atrium Wake Forest Baptist
| Foundation Medicine (tumor tissue DNA) (n=236) | Guardant Health (ctDNA) (n=194) | Overall (n=430) | |
|---|---|---|---|
|
| |||
| Sex | |||
| Female | 111 (47.0%) | 89 (45.9%) | 200 (46.5%) |
| Male | 125 (53.0%) | 105 (54.1%) | 230 (53.5%) |
| Age | |||
| Mean (SD) | 67.1 (9.50) | 67.6 (9.13) | 67.3 (9.33) |
| Race | |||
| American Indian | 2 (0.8%) | 0 (0%) | 2 (0.5%) |
| Asian | 3 (1.3%) | 2 (1.0%) | 5 (1.2%) |
| Black | 35 (14.8%) | 30(15.5%) | 65 (15.1%) |
| Hispanic | 2 (0.8%) | 1 (0.5%) | 3 (0.7%) |
| White | 194 (82.2%) | 161 (83.0%) | 355 (82.6%) |
| BMI | |||
| Mean (SD) | 24.5 (5.36) | 25.0 (6.32) | 24.7 (5.81) |
| Smoker | |||
| Non-smoker | 16 (6.8%) | 20 (10.3%) | 36 (8.4%) |
| Smoker | 220 (93.2%) | 174 (89.7%) | 394 (91.6%) |
| Stage | |||
| Three | 61 (25.8%) | 42 (21.6%) | 103 (24.0%) |
| Four | 175 (74.2%) | 152 (78.4%) | 327 (76.0%) |
| Grade of Adverse | |||
| High | 38 (16.1%) | 28 (14.4%) | 66 (15.3%) |
| Low | 109 (46.2%) | 89 (45.9%) | 198 (46.0%) |
| None | 89 (37.7%) | 77 (39.7%) | 166 (38.6%) |
| Treatment Type | 109 (46.2%) | 94 (48.5%) | 203 (47.2%) |
| Chemo + ICI ICI | 127 (53.8%) | 100 (51.5%) | 227 (52.8%) |
Fig. 1. Overview of irAEs in immunotherapies treated NSCLC patients.
(A) Distribution of different grades of irAEs in all patients. (B) Categories of overall irAEs in all patients. (C) Categories of irAEs in patients with high grade (left) or low grade (right) irAEs.(D) Swimmer plot of the median months it takes to develop a specific types of high grade (HG) or low grade (LG) irAEs in overall patients. (E) Overall Survival analysis in patients with different grades of irAEs. **,p<0.01
Association between genetic alterations and high-grade irAEs
To examine whether any patients’ clinical characteristics are associated with the occurrence of high-grade irAEs, we performed multivariate analyses and found that BMI was significantly correlated with a high-grade irAE (Supplementary Fig 2A). We found that patients with high BMI(>25) had higher incidence to develop high-grade irAEs compared to lean patients (Supplementary Figure 2B) Next, we analyzed the mutational profiles obtained from tumor tissue (Foundation Medicine, FM, n=236) or circulating tumor DNA in the peripheral blood (Guardant Health, GH, n=194) to examine whether any genetic alterations are associated with high-grade irAEs. For patients who developed multiple irAEs, the Patients were separated based on different sequencing platforms, followed by mutational analyses. As shown in Fig. 2A, the top 10 mutated genes in patients from each sequencing platform are listed. To identify the mutations associated with high-grade irAEs, we performed Fisher’s exact test by calculating the presence or absence of one particular mutation in patients with or without high-grade irAEs.
Fig. 2. Mutational analyses of NSCLC patients with or without high grade irAEs.
(A) Mutation landscape of NSCLC patients who were sequenced by FM (upper) or GH(lower). (B) List of mutations that were correlated with the absence or presence of high grade irAEs in FM cohort (upper) and GH cohort (lower). (C) Co-occurring and mutually exclusive mutations with other major mutations in FM cohort (upper) and GH cohort (lower).
Among the FM-cohort, we identified four mutated genes (MYC, TEK, FANCA, and FAM123B) that were associated with an increased risk of developing a high-grade irAEs (Fig. 2B, upper). We only identified one mutated gene (MET) in the GH-cohort that correlated with an increased risk of developing a high-grade irAE (Fig. 2B, lower). The position of individual mutation was mapped by lollipop plots (Supplementary 2C&D). Specific variants information of those mutations was listed in supplementary table 2. We also identified the co-occurrent and mutually exclusive mutations in both FM and GH cohorts by aligning the top 10 most mutated genes with mutations identified in Fig. 2B. As shown in Fig. 2C, FAM123B co-occurred with KRAS and MLL2 while MET was also found to be mutually exclusive with KRAS mutations.
Correlation between irAEs and different subtypes of NSCLC
Adenocarcinoma (LUAD) and squamous cell (LUSC) subtypes have distinct pathological features and respond differently to therapies, including immunotherapies [24]. Therefore, we separated patients based on tumor subtypes and found that LUSC patients had a higher incidence of developing irAEs compared to LUSC patients (59.24%, LUAD vs. 66.95%, LUSC) (Supplementary Fig. 3A). No difference was found between two sequencing platforms regarding to the subtypes of patients (Supplementary Figure 3B). We also compared the OS between patients with different subtypes of NSCLC, ICI treatments (ICI alone or Chemo+ICI) and grading of irAEs. In the Chemo+ICI treated LUSC group, we found that patients developed low-grade irAE had longer OS compared to patients without irAE (Supplementary Fig. 3C). Next, we examined whether the categories of irAEs is correlated with the tumor subtypes and treatments. As shown in Fig. 3A, LUSC patients treated with ICI had a higher chance of developing respiratory irAEs compared to LUAD patients treated with ICI. In patients treated with Chemo+ICI, gastrointestinal and respiratory related irAEs were more prevalent in LUAD patients while neurologic related irAEs were higher in LUSC patients (Fig. 3B). We also found a delayed occurrence of high-grade irAEs compared to low-grade irAEs in both LUAD and LUSC patients.For LUAD patients, both low-grade skin and hepatobiliary related irAEs were found appeared significantly earlier than high-grade irAEs. For LUSC patients, low-grade respiratory irAEs were observed significantly earlier than in patients with high-grade respiratory irAEs (Fig. 3C). To examine whether treatments affect the pace of irAEs development in different subtypes of NSCLC patients, we calculated the average months before irAEs occurrence in both LUAD and LUSC patients treated with ICI and Chemo+ICI. We found that circulatory, pain, and hepatobiliary irAEs occurred earlier in ICI-treated LUAD patients. In contrast, skin and GI-related irAEs occurred earlier in Chemo+ICI-treated LUAD patients (Supplementary Fig. 3D). Among LUSC patients, gastrointestinal and pain-related irAEs occurred earlier in ICI-treated-patients compared to Chemo+ICI treated patients (Supplementary Fig. 3E).
Fig. 3. Overview of irAEs in immunotherapies treated patients with different subtypes.
(A) Categories of irAEs in ICI treated LUAD (left) and LUSC (right) patients. (B) Categories of irAEs in Chemo+ ICI LUAD (left) and LUSC (right) patients. (C) Swimmer plot of median months it took to develop either high or low grade irAEs in LUAD(right) and LUSC (left) patients. *,p<0.05;**,p<0.01
Identification of high-grade irAE-associated mutations in different subtypes of NSCLC
To identify subtype specific mutations that correlated with high-grade irAEs, patients were regrouped based on the subtype and sequencing platforms. The percentages of LUAD patients with or without irAEs were similar between two sequencing platforms (Fig. 4A,C). We identified four mutations that were significantly correlated with high-grade irAEs in LUAD patients sequenced by FM (Fig. 4B). Two out of the four mutations (TEK and MYC) overlapped with the mutations identified in Fig. 2B. We identified one mutation (MET) significantly correlated with the high-grade irAEs in the LUAD-GH cohort (Fig. 4D). This mutation was also the same mutation that we identified in Fig. 2B. The distribution of LUSC patients with or without irAEs from two sequencing platforms were shown (Fig. 4 E,G). Interestingly, LUSC patients sequenced with GH had the highest percentage of low grade irAEs compared to other groups (Fig. 4E). Consistent with our previous finding that ERBB2 was found to be significantly correlated with high grade irAEs in LUSC-GH cohort, suggesting that ERBB2 could be a potential biomarker to predict the occurrence of high-grade irAEs in LUSC patients (Fig. 4E). No high-grade irAEs associated mutation was identified in LUSC-FM cohort.
Fig. 4. Mutational analyses of patients with or without high grade irAEs in different subtypes of NSCLC.
(A) Distribution of irAEs in FM sequenced LUAD patients. (B) List of mutation that was correlated with the absence or presence of high grade irAEs in LUAD-FM patients. (C) Distribution of irAEs in GH sequenced LUAD patients. (D) List of mutations that were correlated with the absence or presence of high grade irAEs in LUAD-GH patients. (E) Distribution of irAEs in FM sequenced LUSC patients. (F) Distribution of irAEs in GH sequenced LUSC patients. (G) List of mutation that was correlated with the absence or presence of high grade irAEs in LUSC-GH patients.
Discussion
This study demonstrates the potential for somatic tumor mutations as predictive biomarkers for high-grade irAEs in different subtypes of NSCLC patients treated with various immunotherapies. To the best of our knowledge, our cohort is one of the largest single institute cohorts that contains comprehensive information on patient characteristics, TMB, overall survival, sequencing data, grades of irAEs, and treatment regimens. To gain a more comprehensive view of how different types of immunotherapies affect the incidence of irAEs, we included patients who received Chemo+ICI treatment which is one of the newest first-line treatment regimens approved in 2018 for treating NSCLC patients with advanced stages, and it got recently approved by FDA for treating early-stage NSCLC patients [25, 26]. We observed a similar percentage of patients who developed low (ICI:50.22% vs. Chemo+ICI:41.38%) or high-grade irAEs in both treatment groups (ICI:13.66% vs. Chemo+ICI:17.24%). However, we found that patients who received Chemo + ICI had a significantly higher chance of developing endocrine irAE compared to ICI monotherapy treated patients. Although patients with high-grade irAEs had shorter or incomplete treatment regimens due to early termination, there was no significant difference regarding to their OS compared to patients with low-grade irAEs or irAEs free, suggesting that initial activation of tumor immunity cycle by ICI may have a long lasting effect on T cell mediated tumor eradication. However, due to limited number of high-grade irAEs patients, further validation in a larger size cohort is required.
Previous publications have shown that blood cell count can predict the incidence of irAEs. However, blood cell count can be affected by many variables, such as physical state and myelosuppression from treatment [27]. Zhou et al. found that biomarkers from blood tests failed to predict the development of irAEs in advanced NSCLC patients [28]. Germline variants such as immunogenetic-related gene SNPs have been shown to predict checkpoint inhibitor response and the occurrence of irAEs [18, 29]. Chat et al. identified 25 potential SNPs associated with auto immune diseases from published GWAS studies and found rs17388568, a risk variant in the IL2 and IL21, is correlated with a better response to anti-PD-1 treatment in 436 advanced melanoma patients [30]. However, the incidence of irAEs in those patients was unknown. Therefore, both germline variants in key immune-related genes and somatic mutations of tumors may contribute to the occurrence of irAEs. We found that MET and ERBB2 mutation were associated with increased risk of high-grade irAEs in LUAD and LUSC patients respectively. Both of genes belong to receptor tyrosine kinase (RTK) and mutations of those two genes usually lead to activation of pathways including PI3K, MAPK and STAT signaling [31, 32]. Several studies demonstrated that targeting RTK by tyrosine kinase inhibitors significantly enhanced ICI efficacy by reversing the immune suppressing tumor microenvironment [33].
Due to the differences in sample sources (tissue vs. blood) and size of gene panels (345 vs. 78), we did not find any overlapped mutations within the same irAEs group sequenced by two platforms. Chae et al. showed that over 50% of the mutations were not detected in the same patient’s blood-based or tissue-based sequencing method [34]. Therefore, a validation cohort with a more extensive data set with matching sequencing platforms is needed to cross-validate the findings.
To summarize, our results demonstrate the potential usage of mutation data to help identify NSCLC patients at a higher risk of developing an irAE from immunotherapy. With the increasing number of patients who receive immunotherapy-based therapies and sequencing services, genetic data may provide valuable information on choosing the most effective treatments. They may serve as a potential biomarker for identifying patients who require additional post-treatment monitoring after receiving immunotherapy.
Supplementary Material
CLINICAL PRACTICE POINTS.
High-grade irAEs in vital organs are likely to cause permanent discontinuation of ICI therapy and sever damage to patients’ health. Predicting the occurrence of high-grade irAEs is challenging but has great clinical implications for post-treatment monitoring. irAEs can occur at any time during the treatment and the degree of irAEs can range from mild to severe. Therefore, it is of paramount importance to identify patients who are more likely to develop high-grade irAEs prior to the treatment. Genomic profiling from either tumor tissue or blood has become a routine diagnostic approach which provides critical genetic information that help clinician to select the optimized regimen for patients carrying druggable mutations. In addition to treatment selection, genetic alterations can be used for other purposes such as predicting patients’ outcome to certain therapies and risk of developing distant metastases. In this study, we explored the feasibility using patients’ sequencing data to predict the risk of developing high-grade irAEs in ICI treated NSCLC patients.
Highlights.
High-grade irAEs occur in around 15% of total immunotherapy treated NSCLC patients.
Respiratory related irAEs are the most popular among patients who developed high-grade irAEs.
Specific gene mutations were associated with the occurrence of high-grade irAEs
Different subtypes of NSCLC have unique mutation signatures that were associated with high-grade irAEs.
Acknowledgments:
This work was supported by NIH grant R37CA230451 and METAVivor. This study used various Shared Resources, including Biostatistics, Tumor Tissue and Pathology, Cancer Genomics, Flow Cytometry, and Cell Engineering, supported by the Comprehensive Cancer Center of Wake Forest University NCI, National Institutes of Health Grant (P30CA012197). J.S. is partially sponsored by NIH grant (P30CA082709, Indiana University Melvin and Bren Simon Comprehensive Cancer Center Support Grant) and the Indiana University Precision Health Initiative.
Footnotes
Competing Interests
No authors have any particular competing interests.
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Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.