3015
Background: The clinical care of oncology patients is routinely informed by tumor and inherited genetic profiles. This is accomplished by molecular pathologists synthesizing the growing body of ...clinical guidelines and scientific evidence that associates cancer genome alterations and therapeutic response, and applying that knowledge during case reviews. Many academic medical centers formalize this process in the form of molecular tumor boards. As the number of cases for review and literature continue to increase, there is opportunity to leverage clinical interpretation algorithms to computationally prioritize molecular features and both enhance and automate the sample contextualization process. Here, we present the Molecular Oncology Almanac (MOAlmanac) to enable the rapid assessment of tumor actionability. Methods: Molecular Oncology Almanac is an open source clinical interpretation algorithm and paired knowledge base for precision cancer medicine. It is used to rapidly characterize and identify genomic features related to therapeutic sensitivity and resistance and of prognostic relevance. This is performed by assessing not only individual genomic features (e.g. somatic variants, copy number alterations, germline variants, and fusions) but also interactions between these events as well as secondary features such as mutational burden, mutational signatures, MSI status, and aneuploidy. MOAlmanac summarizes all clinically relevant findings into a web-based actionability report. The underlying knowledge base can be accessed through our API endpoints and web browser, and entries may be recommended through either Github or our browser extension. In addition, we developed a cloud-based web portal on top of the Terra framework to increase accessibility. Results: A total of 32,108 samples from 30,607 patients across 66 cancer types received targeted sequencing to characterize somatic variants, copy number alterations, and fusions from PROFILE’s Oncopanel and were evaluated with MOAlmanac. Based on Oncopanel’s tier 1 and tier 2 criteria for clinical actionability, we observed that 8,285 samples (26%, 0 - 69% by cancer type) of patients harbored at least one alteration suggesting therapeutic sensitivity based on FDA approvals or clinical guidelines. Actionability increases to 18,117 samples (56%, 0 - 85% by cancer type) when considering an expanded set of evidence to include relationships captured from clinical trials, clinical, preclinical, and inferential evidence; consequently providing at least one therapeutic hypothesis to otherwise variant-negative patients. Conclusions: Clinical actionability of molecular tumor data was increased in individual patients by expanding the set of evidence considered. Source code and a web portal for this project are available at moalmanac.org .
5082
Background: Enrichment of germline PVs in metastatic castration resistant prostate cancer (mCRPC), compared to localized disease, has directly informed genetic testing guidelines. The prevalence ...and prognostic/predictive associations of such variants are not well characterized in the mHSPC state, in particular the effect of susceptibility mutations related to DNA damage and repair (DDR) pathways. Methods: We performed whole exome sequencing of germline DNA derived from whole blood available from patients (pts) in the phase III CHAARTED trial (NCT00309985) of androgen deprivation therapy (ADT) versus ADT plus docetaxel (ADT+D). After filtering for low coverage, variant annotation and effect prediction, PVs from a curated list of 588 prostate cancer-associated genes were reviewed. The prognostic effect of PVs was evaluated within each treatment arm. Endpoints of time to CRPC (ttCRPC), time to clinical progression (ttClinPD), and overall survival (OS) were estimated by Kaplan-Meier method. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated by Cox models evaluating association of endpoints with biomarkers/arm. Multivariable analysis adjusted for metastatic timing and volume. Results: Of 137 pts, 135 had unique germline exomes that passed downstream analysis. Most pts had synchronous (66.7%) and high-volume (62.2%) disease. This biomarker cohort showed benefit of adding docetaxel to ADT (ttCRPC: HR 0.55, 95% CI 0.37-0.82; OS: HR 0.68, 95% CI 0.44-1.07). In total, 61 PVs were detected; 49 pts (36.3%) harbored at least 1 PV in 41 different genes. The most frequently-mutated gene was BRCA2 (6.67%). In addition, PVs were found in DDR-associated genes including PALB2 (1.48%), CHEK2 (1.48%), BRCA1 (0.74%) and PMS2 (0.74%) for an overall prevalence of 11.1% (15/135). Pts with BRCA2 PV on ADT alone had shorter ttCRPC compared with men without the PV (UVA: HR 2.67, 95% CI 0.93-7.63, log rank p=0.057; MVA: HR 2.59, 95% CI 0.91-7.39, p=0.074). There was no evidence of a difference in the ADT+D arm (UVA: HR 1.00, 95% CI 0.31-3.25, log rank p=0.1). Supportive data was observed for ttClinPD in ADT arm (HR 2.85, 95% CI 1.01-8.08, log rank p=0.04). Metastatic volume and timing were not significantly associated with germline BRCA1/2 or DDR PVs. Conclusions: The prevalence of germline BRCA1/2 and DDR PVs in mHSPC is similar to mCRPC and BRCA2 PV may confer worse outcomes on ADT alone. This supports the need for genetic testing at diagnosis of mHSPC. Table: see text
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3014
Background: Precision medicine has revolutionized oncologic care in the United States (US) in the past two decades. While the US cancer population is rapidly diversifying, ...enrollment of a diverse patient population into clinical trials lags behind. In particular, it is unclear whether minority patients are adequately represented in precision oncology trials. Herein, we report racial/ethnic representation in precision oncology studies spanning four common cancer types (breast, lung, prostate, colorectal cancers). Methods: Completed US clinical studies incorporating precision medicine objectives based on a set of 12 precision oncology search terms (including tumor biomarker, whole exome sequencing, tumor mutation testing, gene expression signatures, tumor microarray, tumor genomics, et cetera) were identified from Clinicaltrials.gov. Studies were reviewed for reporting race/ethnicity for inclusion in the analysis. The Surveillance, Epidemiology, and End Results (SEER) database was used to determine incidence of race/ethnicity in the US cancer population, correlated with disease site and median year of enrollment for each trial. The difference in incidence (D-I) was defined as the median absolute difference in study racial enrollment and SEER incidence, with a negative value corresponding to underrepresentation. Wilcoxon signed-rank test was used to compare median D-I to a value of 0 by racial/ethnic subgroups. Results: Overall, 156 studies were identified; 40.3 and 27.5% studies enrolling from 2000 through 2020 met the inclusion criteria for racial and ethnic subgroups reporting, respectively. Of 4,418 total enrollees, 82.5% were White, 10.5% Black, 3.8% Asian, and 0.4% American Indian/Alaskan Native (AIAN). Ethnically, 6.4% were Hispanic. The D-I was +2.2% for Whites (interquartile range (IQR) = -43.7% to 25.4%; P < 0.013), -0.74% AIAN (IQR = -0.8% to +5.9%; P < 0.001), -2.5% Asians (IQR = -4.1% to 30.4%; P < 0.152), -4.6% Blacks (IQR = -20.1% to +45.0%; P < 0.001), and -8.1% Hispanics (IQR = -14.8% to + 29.6%; P < 0.001). By disease site, Blacks were significantly underrepresented proportional to their cancer incidence among prostate (D-I of -11.8%, p = 0.009) and lung studies (D-I of -5.9%, p = 0.013), while prostate studies significantly overrepresented Whites (D-I +14.0%, p = 0.005). Lung studies overrepresented Asians (D-I +0.49%) consistent with the prominent role of targetable oncogene drivers in this population. Conclusions: Results demonstrate an underrepresentation of minority racial groups and an overrepresentation of Whites in precision oncology studies. Increased emphasis on equitable enrollment onto these studies is critical, as resulting precision Omic conclusions are used to stratify populations and personalize treatments. A continued lack of diversity among enrollees may further leave behind vulnerable minority populations in the era of precision oncology.
5088 Background: The landscape and clinical impact of genomic variants in mHSPC are incompletely understood. We have shown that deleterious germline BRCA2 alterations (alts) associate with shorter ...time to castration resistant prostate cancer (TTCRPC) on androgen deprivation therapy (ADT), but not on ADT plus docetaxel (ADT+D) (ASCO 2023). Somatic variation from tissue of patients (pts) with mHSPC is not well characterized and may influence therapeutic outcomes. Methods: We performed whole exome sequencing of HSPC specimens obtained at initial diagnosis and germline DNA from whole blood from pts in the CHAARTED trial (NCT00309985) of ADT vs ADT+D. Somatic single nucleotide variants (SNV) and allele-specific copy number alts (CNAs) were identified, including estimation of tumor mutational burden (TMB) and copy number burden (CNB). Prognostic effects were evaluated in both arms. Loss of selected tumor suppressor genes was defined by monoallelic or biallelic loss. TTCRPC and overall survival (OS) were estimated by Kaplan-Meier method. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated by Cox models. Results: After quality control, 68 tumor-normal cases were analyzed. The majority of pts had synchronous (51.5%) and high volume (58.8%) disease. Most frequent somatic SNVs were TP53 (33.8%), PTEN (7.4%), PIK3CA (5.9%) and SPOP (5.9%). AR amplification was uncommon (4.4%), however frequent MYC gain (60.3%) was seen as well as monoallelic deletion of NKX3-1, TP53, PTEN and BRCA2. Whole genome doubling occurred in 14.7%. Median TMB and CNB were 4.7 mut/Mb and 9.1%, respectively. CNB was elevated in synchronous (p=0.01) and high volume (p=0.046) disease. CNB greater than median was associated with shorter TTCRPC in the overall cohort (HR 2.06, 95%CI 1.13-3.75, p=0.015) and ADT+D arm (HR 2.98, 95%CI 1.17-7.58, p=0.016). The effect in the overall cohort was reduced after adjustment for volume and presentation (HR 1.72, p=0.091). A compounding effect of PTEN and TP53 alts was seen in the ADT arm where median TTCRPC for wild-type (WT), 1-gene hit, 2-gene hit was 19.6 mos, 8.5 mos, 6.3 mos, respectively. The median OS of WT vs 1-hit/2-hit loss was 47.1 mos vs 26.8 mos (HR 2.05, 95% CI 0.90-4.68, p=0.087). Similar differences in TTCRP and OS by PTEN/ TP53 status were not observed with ADT+D. Conclusions: The genomic landscape of mHSPC is characterized by frequent alts in putative drivers known to be enriched in mCRPC (Table). We observed a low rate of genomic instability and AR amplification/mutation similar to non-metastatic HSPC. Concordant with the STAMPEDE trial, greater CNB confers a higher risk of progression. Combined tumor suppressor gene alts associate with prognosis in mHSPC, which may differ by therapy intensification. Table: see text
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Background: One model for testicular germ cell tumor (TGCT) formation posits that these tumors arise from a failure of germ cell determination characterized by persistent pluripotency and ...apoptotic escape. Risk assessment for relapse in clinical stage 1 (CS1) TGCT is dictated by clinical factors; molecular biomarkers to improve patient stratification for post-orchiectomy care are lacking. In this study, we examined the relationship between protein expression of pluripotency and apoptosis factors and risk of relapse in clinical stage 1 TGCT. Methods: Orchiectomy specimens from 73 patients treated for clinical stage 1 TGCT at one institution (27 seminoma, 46 non-seminoma) were subjected to immunohistochemistry (IHC) to assess protein expression of DAZL, POU5F1, BAK1, DDX4, NANOG, and PMAIP1. Samples were dichotomized as negative or positive for target protein expression. Patients with CS1 TGCT managed with surveillance were annotated for baseline clinical characteristics and whether they experienced relapse within two years of orchiectomy. Exact logistic regression estimated odds ratios (OR) and 95% confidence intervals were calculated for the association between protein expression and relapse. Results: At two years, 17% of patients in our cohort experienced relapse. DAZL expression (score > 0) was detected in 43% of seminoma samples and 13% of embryonal carcinomas. After adjusting for histology, tumors negative for DAZL expression were more likely to recur within two years (adjusted OR for recurrence 0.08, 95% CI 0 – 0.81, p = 0.03). The direction of this relationship was consistent in seminoma when adjusted for tumor size (adjusted OR 0.14, 95% CI 0-1.83, p = 0.18) and non-seminoma after adjustment for embryonal predominance and lymphovascular invasion (adjusted OR 0.53, 95% CI 0-3.10, p = 0.30). No notable findings were observed for POU5F1, BAK1, DDX4, NANOG, and PMAIP1. Validation studies in two independent cohorts from other institutions are ongoing. Conclusions: The absence of DAZL expression by IHC is associated with a greater risk of relapse in CS1 TGCT. As DAZL promotes germ cell commitment by suppressing the pluripotency program, absence of DAZL expression may promote an oncogenic germ cell phenotype and more aggressive tumor behavior. Validation in larger patient cohorts is required to credential DAZL as a biomarker for clinical stage 1 relapse on surveillance.
e17002
Background: Radiation therapy (RT) is a backbone of treatment for patients with prostate cancer (PCa). However, locally recurrent disease after definitive RT (i.e. radiorecurrent PCa) is not ...uncommon and is associated with a higher risk of distant metastases and death from PCa. While the genomic landscape of primary PCa is well-characterized, little is known regarding the genomic landscape of radiorecurrent PCa or how this compares to that of primary PCa. We hypothesized that the genomic landscape of radiorecurrent PCa differs significantly from primary PCa and that these differences have clinical relevance. We examined this hypothesis by performing whole exome sequencing (WES) of radiorecurrent PCa. Methods: We identified 25 patients with radiorecurrent PCa with available post-RT tissue obtained from biopsy or radical prostatectomy, as well as germline tissue. The tumor and germline tissue for 19 patients successfully underwent WES. We identified genomic variants including single nucleotide variants (SNVs), insertions/deletions, and copy number alterations. Furthermore, we estimated the tumor mutational burden (TMB; number of nonsynonymous mutations per megabase Mb) and contribution of individual mutational signatures. We compared our samples to a publicly available large cohort of primary PCa (n = 680) to define genomic alterations unique to radiorecurrent PCa. Results: In the overall cohort of 25 patients, the RT modality included external beam RT (56%), brachytherapy (36%), and combination of both (8%). 40% of patients received upfront androgen deprivation therapy with RT. The median time to local recurrence was 6.5 years. For the 19 radiorecurrent patients with WES data, the median TMB was 2.7 mutations/Mb, which was significantly higher than the median TMB of 0.7 mutation/Mb for primary PCa ( P= 0.002 after multivariable adjustment). Radiorecurrent PCa demonstrated an enrichment of short deletions, with a significantly higher deletion/SNV ratio compared to primary PCa ( P= 0.006). TP53 was the most frequently mutated gene in radiorecurrent PCa (n = 6), and the TP53 mutation prevalence was significantly higher compared to primary PCa (32% vs 10%, P= 0.016 by Fisher’s exact test). TP53 was also determined to be recurrently mutated using MutSigCV (Q = 0.0003). Additionally, 3 samples demonstrated evidence of whole genome doubling. Conclusions: Radiorecurrent PCa has a distinct genomic profile compared to primary PCa, characterized by a higher TMB with an enrichment of short deletions as part of the mutational composition, which may be a scar of nonhomologous end joining subsequent to RT-induced DNA double-stranded breaks. In addition, TP53 mutations may be of functional consequence in radiorecurrent PCa. Further efforts are underway to examine other genomic features apparent in WES data, as well as perform whole transcriptome sequencing to provide complementary insights into radiorecurrent PCa.
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3627
Background: Differential gene expression (DGE) methods, initially developed for analyzing bulk RNA changes in pure tumor cell lines under experimental settings, are commonly used ...to identify biomarkers in and infer biological differences between patient tumor samples, which are admixtures of tumor and non-tumor components. Methods to sensitively and accurately detect cell type-specific expression differences in admixed patient samples are not well characterized but may greatly affect emerging targeted and immunotherapy biomarker strategies. To address this issue, we developed a simulation framework to benchmark our ability to detect changes in tumor-intrinsic gene expression. Methods: Pseudobulk RNAseq melanoma cohorts were simulated by sampling from melanoma single cell RNAseq data. Simulation parameters were optimized to maximize concordance of gene expression means and variances (Spearman r = 0.81, 0.68, respectively) between the TCGA SKCM cohort (n = 462) and matched simulated cohort, and then validated in two independent melanoma cohorts (n = 42, 129; means Spearman r = 0.80, 0.78; variances Spearman r = 0.68, 0.63). Using this simulation framework, we benchmarked the effect of sample size, magnitude of differential expression, and differences in cell type proportions on the sensitivity and positive predictive value (PPV) of detecting true differentially expressed genes in the tumor-intrinsic compartment. Results: Reference cohorts of 50 total tumors (n = 10) were simulated to contain a 2 standard deviation tumor-intrinsic expression change in 50 randomly selected genes and a 11% difference in mean purity between two equally sized 25-tumor subgroups. DGE analysis using DESeq2 with an FDR q-value threshold of 0.1 yielded a sensitivity of 0.37 and PPV of 0.29. DGE analysis of the same simulated cohorts using a non-parametric Mann-Whitney U test with an FDR q-value threshold of 0.1 yielded a sensitivity of 0.13 and PPV of 0.76. Conclusions: Commonly used DGE methods for existing expression-based biomarker strategies have poor sensitivity and PPV in admixed tumor samples, limiting our ability to find meaningful transcriptional biomarkers in clinical cohorts. We are currently developing methods to more accurately detect true differentially expressed genes in admixed bulk RNAseq samples and applying these approaches for biomarker discovery in immunotherapy-treated patient cohorts and other clinical tumor cohorts.
12140 Background: Immune checkpoint inhibitors (ICIs) have dramatically improved outcomes of patients (pts) with metastatic renal cell carcinoma (mRCC). Unfortunately, adverse events (AEs) can limit ...treatment efficacy and worsen patient outcomes. Recently, a germline IL7 SNP (rs16906115) was identified as a potential biomarker for prediction of irAEs. We aimed to characterize the association between a germline IL7 SNP (rs16906115) and AEs in a prospective clinical trial of patients with mRCC treated with nivolumab (NIVO) or everolimus (EVE). Methods: Whole-exome sequencing (WES) data of tumor and peripheral blood samples from CheckMate 025 (NCT01668784) were used to infer somatic alterations using the Cancer Genome Analysis pipeline, as well as SNP carrier status using the STITCH pipeline. Within each treatment arm, time to incident adverse events (AEs) were compared between carriers (SNP+) and non-carriers (SNP-) via multivariable Cox regression, controlling for age, sex and sample purity, followed by a SNP´treatment interaction term in the whole cohort. Overall survival (OS) and progression-free survival (PFS) were also assessed. Finally, a recurrent event analysis for AEs was conducted using the Andersen-Gill model, controlling for the same variables. Results: In total, 382 pts were included (NIVO: n=189, EVE: n=193), among which 56 (14.7%) were SNP+. There were no differences in clinical and pathological characteristics between SNP+ and SNP-, except for sex (SNP+ 16.1% vs. SNP- 30.1% females, P=0.046). Similarly, no differences in somatic alterations, including single nucleotide and copy number variants were seen between SNP+ and SNP-. SNP carrier status had no effect on OS nor PFS in both treatment arms (all P≥0.47). Regarding AEs, 63 pts (33.3%) in the NIVO arm experienced at least 1 grade 2+ AE, compared to 78 pts (40.4%) in the EVE arm. The most common types of grade 2+ AEs were cutaneous (21.0%), hepatobiliary (16.8%) and endocrine (15.8%) in the NIVO arm, and respiratory (30.1%), cutaneous (22.3%) and gastrointestinal (19.4%) in the EVE arm. The rate of grade 2+ AEs was significantly higher in SNP+ vs. SNP- in the NIVO arm (HR=2.911.48-5.72), but not in the EVE arm (HR=0.630.3-1.29, SNP´treatment P interaction =0.002). The rate of recurrent grade 2+ AEs was also significantly higher in SNP+ vs. SNP- in the NIVO arm (HR=3.431.83-6.43), whereas a trend for fewer recurrent grade 2+ AEs was seen in SNP+ vs. SNP- in the EVE arm (HR=0.460.17-1.25, SNP´treatment P interaction =0.0005). Conclusions: The IL7 SNP (rs16906115) is associated with significantly higher rates of grade 2+ AEs, including recurrent events, in pts with mRCC treated with NIVO but not with EVE, with no effect on survival outcomes. These results affirm the SNP’s predictive potential as a biomarker for irAEs to guide therapeutic decisions in pts treated with ICIs.
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Background: Radiation therapy (RT) can improve survival in oligometastatic prostate cancer (OMPC) patients (pts). Reports implicate immune system contribution to both local tumor control and ...systemic regression of metastases. Understanding molecular and immune drivers of clinical responses in irradiated OMPC pts may elucidate mechanisms of RT-driven antitumor immune activity. Methods: Prospective samples from consented pts with OMPC (de novo/oligorecurrent) receiving RT included baseline (pre-RT) and 3 post-RT blood samples (RT end, 3-, 6-months). Peripheral blood mononuclear cells (PMBC) were obtained at each timepoint. PBMC sample barcoding and antibody labeling was performed prior to analysis by mass cytometry by time of flight (CyTOF). Data were debarcoded/analyzed using standard deconvolution/gating/clustering algorithms. Wilcoxon signed-rank tests identified longitudinal differences in comparison to baseline. P <0.05 denotes significance. Results: Between 2020-2022, 14 OMPC pts (56 samples) met inclusion criteria (2 de novo, 12 oligorecurrent). All received androgen deprivation therapy. De novo OMPC pts received simultaneous RT to the prostate, pelvis, and OM lesions. 6/12 oligorecurrent pts received simultaneous RT to a pelvic field along with OM lesions, while the remainder received RT to the OM lesions alone. Median follow-up was 17 months (r, 3-29). Four pts (28.6%) experienced recurrence (defined by PSA progression). Median time to recurrence after RT was 10.5 months. Significant differences in immune cell subsets after RT compared to pre-RT levels were identified by CyTOF analysis. CD4+ naïve cells peaked 6 months post-RT, while CD4+ effector memory (EM) cells peaked immediately post-RT (p=0.0012) and decreased to baseline levels at 3 months. CD4+ effector cells expressing TIGIT, OX40, ICOS, and CD69 were significantly more abundant immediately post-RT (p<0.05) compared to baseline. CD8+ cells expressing ICOS increased post-RT and were significantly increased at 6 months (p=0.03). In marked contrast to recurrent pts, non-recurrent pts exhibited increasing CD4+ T regulatory cells that peaked 6 months post-RT (p=0.04) and CD4+ EM cells that peaked post-RT (p=0.02). CD4+ effector cells expressing ICOS (p=0.01) and PD-1 (p=0.01) were both increased immediately post-RT, while cells expressing 4-1BB continued to increase and peaked 6 months post-RT (p=0.04). These changes were not observed or not significant in the recurrent population. Conclusions: Longitudinal immune cell subset changes can be observed after RT for OMPC. These data support immune activation, particularly immediately post-RT in non-recurrent pts, with some longitudinal changes lasting up to 6 months. Further analyses include TCR sequencing, inclusion of serum proteomics, and baseline genomic markers that may predict immune system activation and clinical outcomes.
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2515
Background: ICB has improved survival in melanoma. Patients with stable disease (SD) as best treatment response represent an intermediate response phenotype whose biology has been ...incompletely characterized. Methods: Whole exome and transcriptome sequencing from pre-treatment tumors in melanoma patients treated with ICB (anti-CTLA-4 and/or anti-PD-1) were assembled and uniformly analyzed (WES n = 293; WES+RNA-seq n = 159). RECIST (v1.1) was used to determine complete or partial response (CR/PR; n = 94), SD (n = 42), or progressive disease (PD; n = 157). Gene set enrichment analysis (GSEA) was performed on 50 “hallmark” gene sets to identify pathways differentially expressed in patients with SD. CIBERSORT was used to infer relative proportions of 22 immune cell types in each sample. Mutation antigenicity was determined by calculating patient-specific mutation affinity for MHC class I peptides. Results: GSEA identified enrichment of multiple immune-related gene sets in SD tumors, including TNF-α signaling and interferon-ɣ response (FDR q < 0.1, SD vs CR/PR and SD vs PD). SD tumors had higher HLA and antigen presentation pathway expression, and increased cytolytic T cell activity compared to CR/PR and PD. CIBERSORT analysis identified higher total immune infiltrate in SD patients compared to CR/PR and PD (Mann-Whitney U p = 0.03 and p < 0.001, respectively) but not in patients with CR/PR vs PD (p = 0.124). However, checkpoint expression, including PD-1, PD-L1, and LAG3, was also higher in SD patients. Mutation load did not differ between SD and CR/PR or PD patients (SD median 2.87 vs CR/PR median 7.98, Mann-Whitney U p = 0.104; PD median 3.42, p = 0.210). However, SD patients had more antigenic passenger mutations (SD vs CR/PR, p = 0.001; vs PD, p < 0.001); there was no difference in antigenicity of driver mutations. Conclusions: Pre-treatment melanomas from patients with SD contain more antigenic passenger mutations and demonstrate a global increase in immune signaling. This may describe a subset of patients with pre-existing dysfunctional immune response that is minimally responsive to ICB. Further characterization of the tumor-immune interaction in these patients may inform improved interventions.
