Cell-inflamed Gene Expression Profile Research Articles

Abstract 4912: Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC

Abstract Background: Understanding the composition of cancer-associated stroma (CAS) is vital, as the number and location of immune cells and fibroblasts, as well as the degree of extracellular matrix deposition, have implications for cancer progression and response to treatment, including in non-small cell lung cancer (NSCLC). Manual analysis of CAS does not fully describe the stromal milieu, especially from a spatial perspective, and is highly subjective. To this end, we have developed an unsupervised machine learning (ML) model to characterize the CAS in NSCLC from hematoxylin and eosin (H&E) stained whole slide images (WSI) at scale. Methods: PathExploreTM models were deployed to predict stromal tissue and cell types, while another ML model was used to detect collagen fibers from H&E stained WSIs from the TCGA LUAD (N=536) and LUSC (N=464) datasets. Stroma was divided into small regions (median = 0.02 mm2), and 88 features characterizing cell distribution, tissue composition and fiber density were extracted from each region. Graphs were generated connecting neighboring regions (nodes), and an unsupervised variational graph auto-encoder (VGAE) model was trained to learn 8 latent features through dimensionality reduction. Stromal phenotypes were then derived from the latent features using k-means clustering. The fraction of each phenotype in the stroma was correlated against immune- and stroma-related gene expression signatures (GES) and overall survival (OS). Results: Deployment of VGAE on LUAD and LUSC WSIs revealed three distinct stromal phenotypes - P0, P1 and P2. Fibroblast density was elevated in P0 and P1 regions (p<0.001), immune cell density was elevated in P2 regions (p<0.001), and collagen fiber intensity was highest in P1 regions (p<0.001). P2 enrichment was correlated with elevated expression of the T cell-inflamed gene expression profile (TGEP; Spearman ρ = 0.43 in LUAD; ρ = 0.27 in LUSC) and with improved OS (HR = 0.696; 95% CIs: 0.571-0.847 in LUSC). Conversely, P1 enrichment was positively associated with a transforming growth factor-β-induced cancer associated fibroblast GES (TGFβ-CAF: ρ = 0.19 in LUAD and ρ = 0.12 in LUSC) and poor OS (HR = 1.358; 95% CIs: 1.149-1.603 in LUSC). These phenotypes are consistent with fibroblast-enriched, collagen-depleted stroma (P0), collagen-rich, fibroblast-enriched tumor-promoting stroma (P1), and immune cell-enriched, tumor-suppressive stroma (P2). Conclusions: We describe an unsupervised, data-driven method of predicting stromal regions with discrete patterns of cell composition and collagen deposition in NSCLC. This approach identified three phenotypes of NSCLC stroma. These results highlight the ability of ML models to characterize and find meaningful patterns within the cell, tissue, and matrix components of a tumor. This work provides further evidence of the potential of ML to discover novel precision medicine biomarkers in NSCLC. Citation Format: Neel Patel, Nhat Le, Tan Nguyen, Fedaa Najdawi, Sandhya Srinivasan, Adam Stanford-Moore, Deeksha Kartik, Jun Zhang, Jacqueline Brosnan-Cashman, Robert Egger, Justin Lee, Matthew Bronnimann. Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4912.

Plasma cell-free DNA hydroxymethylation profiling reveals anti-PD-1 treatment response and resistance biology in non-small cell lung cancer

BackgroundTreatment with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) can yield durable antitumor responses, yet not all patients respond to ICIs. Current approaches to select patients who may benefit...

Predicting T Cell-Inflamed Gene Expression Profile in Hepatocellular Carcinoma Based on Dynamic Contrast-Enhanced Ultrasound Radiomics.

The T cell-inflamed gene expression profile (GEP) quantifies 18 genes' expression indicative of a T-cell immune tumor microenvironment, playing a crucial role in the immunotherapy of hepatocellular carcinoma (HCC). Our study aims to develop a radiomics-based machine learning model using contrast-enhanced ultrasound (CEUS) for predicting T cell-inflamed GEP in HCC. The primary cohort of HCC patients with preoperative CEUS and RNA sequencing data of tumor tissues at the single center was used to construct the model. A total of 5936 radiomics features were extracted from the regions of interest in representative images of each phase, and the least absolute shrinkage and selection operator and logistic regression were used to construct four models including three phase-specific models and an integrated model. The area under the curve (AUC) was calculated to evaluate the performance of the model. The independent cohort of HCC patients with preoperative CEUS and Immunoscore based on immunohistochemistry and digital pathology was used to validate the correlation between model prediction value and T-cell infiltration. There were 268 patients enrolled in the primary cohort and 46 patients enrolled in the independent cohort. Compared with the other three models, the AP model constructed by 36 arterial phase (AP) features showed good performance with a mean AUC of 0.905 in the 5-fold cross-validation and was easier to apply in the clinical setting. The decision curve and calibration curve confirmed the clinical utility of the model. In the independent cohort, patients with high Immunoscores showed significantly higher GEP prediction values than those with low Immunoscores (t=-2.359, p=0.029). The CEUS-based model is a reliable predictive tool for T cell-inflamed GEP in HCC, and might facilitate individualized immunotherapy decision-making.

POLD1 DEDD Motif Mutation Confers Hypermutation in Endometrial Cancer and Durable Response to Pembrolizumab.

Mutations in the DNA polymerase delta 1 (POLD1) exonuclease domain cause DNA proofreading defects, hypermutation, hereditary colorectal and endometrial cancer, and are predictive of immunotherapy response. Exonuclease activity is carried out by two magnesium cations, bound to four highly conserved, negatively charged amino acids (AA) consisting of aspartic acid at amino acid position 316 (p.D316), glutamic acid at position 318 (p.E318), p.D402, and p.D515 (termed DEDD motif). Germline polymorphisms resulting in charge-discordant AA substitutions in the DEDD motif are classified as variants of uncertain significance (VUSs) by laboratories and thus would be considered clinically inactionable. We hypothesize this mutation class is clinically pathogenic. A review of clinical presentation was performed in our index patient with a POLD1(p.D402N) heterozygous proband with endometrial cancer. Implications of this mutation class were evaluated by a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided systematic review, in silico analysis with orthogonal biochemical confirmation, and whole-exome and RNA sequencing analysis of the patient's tumor and engineered cell lines. Our systematic review favored a Mendelian disease mutation class associated with endometrial and colorectal cancers. In silico analysis predicted defective protein function, confirmed by biochemical assay demonstrating loss of nuclease activity. A POLD1-specific mutational signature was found in both the patient's tumor and POLD1(p.D402N) overexpressing cell. Furthermore, paired whole-exome/transcriptome analysis of endometrial tumor demonstrated hypermutation and T cell-inflamed gene expression profile (GEP), which are joint predictive biomarkers for pembrolizumab. Our patient showed a deep, durable response to immune checkpoint inhibitor (ICI). Charge-discordant AA substitution in the DEDD motif of POLD1 is detrimental to DNA proofreading and should be reclassified as likely pathogenic and possibly predictive of ICI sensitivity.

Exploratory biomarker analysis of the phase 3 KEYNOTE-604 study of pembrolizumab plus etoposide for extensive-stage SCLC.

8503 Background: In the phase 3 KEYNOTE-604 study of extensive-stage small-cell lung cancer (ES-SCLC; NCT03066778), first-line pembrolizumab (pembro) plus etoposide and platinum (EP) significantly improved PFS vs placebo (pbo) plus EP (HR, 0.75; P = 0.0023), with favorable OS (significance threshold not met; HR, 0.80; P = 0.0164). PFS/OS were similar regardless of PD-L1 CPS. In this exploratory analysis, tumor mutational burden (TMB), 18-gene T cell–inflamed gene expression profile (TcellinfGEP) and SCLC transcriptional subtypes were assessed as correlates of survival. Methods: Patients (pts) eligible for this analysis of KEYNOTE-604 had previously untreated ES-SCLC with evaluable pretreatment tumor samples. TMB was assessed by whole-exome sequencing (WES) of tumor and matched normal DNA. RNA-seq was used to determine TcellinfGEP and SCLC transcriptional subtypes (ASCL1, POU2F3, NEUROD1, YAP1, or inflamed). Associations of TMB, TcellinfGEP, and SCLC subtype with OS were analyzed using an adjusted Cox proportional hazards model. 1-sided (pembro + EP) and 2-sided (pbo + EP) P values were calculated for TMB and TcellinfGEP (prespecified α = 0.05); 2-sided P values were calculated for SCLC subtype (multiplicity-adjusted, α = 0.10). Clinical utility was assessed using prespecified cutoffs of ≥175 mut/exome for TMB and the first tertile for TcellinfGEP. Clinical data cutoff date was Dec 2, 2019. Results: Of 453 pts randomized in KEYNOTE-604 (ITT), 318 had WES data (pembro + EP, n = 167; pbo + EP, n = 151), and 316 had RNA-seq data (pembro + EP, n = 159; pbo + EP, n = 157). High TMB was positively associated with OS in the pbo + EP group ( P = 0.005) but not the pembro + EP group ( P = 0.450). There was a positive association between higher TcellinfGEP and OS in the pembro + EP ( P = 0.003) and pbo + EP ( P < 0.005) groups. SCLC subtypes were not associated with OS in either group (pembro + EP, P = 0.960; pbo + EP, P = 0.999). Clinical benefit of pembro + EP over pbo + EP was demonstrated for TMB <175 mut/exome, but not for TMB ≥175 mut/exome. Pembro + EP benefit over pbo + EP was consistent across TcellinfGEP subgroups. Conclusions: In this exploratory analysis of biomarker subgroups of KEYNOTE-604, TMB and SCLC subtypes were not associated with OS in the pembro + EP group in pts with ES-SCLC. While TcellinfGEP was positively associated with OS in both treatment groups, no additional OS benefit was observed with pembro + EP. Further research is warranted to better identify predictive biomarkers to immunotherapy. Clinical trial information: NCT03066778 . [Table: see text]

Evaluation of immunotherapy efficacy in gynecologic cancer.

Various immunotherapies have demonstrated remarkable success over the past few decades, and have been approved for the treatment of different cancer types. However, patient responses to immunotherapy are variable, and approximately 50% of cases are refractory to these agents. Tumor biomarker-based stratification of cases may therefore help identify subpopulations that are sensitive/resistant to immunotherapy; it may also improve prediction of response in various cancers including gynecologic cancer. These biomarkers include the tumor mutational burden, microsatellite instability, mismatch repair deficiency, T cell-inflamed gene expression profile, programmed cell death protein 1 ligand 1, tumor-infiltrating lymphocytes, and numerous other genomic alterations. Future directions in the treatment of gynecologic cancer include the utilization of these biomarkers to select ideal candidates. This review focused on recent advances in the predictive ability of molecular biomarkers in patients with gynecologic cancer who undergo immunotherapy. The most recent developments in combined immunotherapy and targeted therapy strategies and novel immune interventions against gynecologic cancers have also been discussed.

T cell-inflamed gene expression profile is associated with favorable disease-specific survival in non-hypermutated microsatellite-stable colorectal cancer patients.

The anti-tumor immune response plays a key role in colorectal cancer (CRC) progression and survival. The T cell-inflamed gene expression profile (GEP) is a biomarker predicting response to checkpoint inhibitor immunotherapy across immunogenic cancer types, but the prognostic value in CRC is unknown. We evaluated associations with disease-specific survival, somatic mutations, and examined its differentially expressed genes and pathways among 84 sporadic CRC patients from the Seattle Colon Cancer Family Registry. Gene expression profiling was performed using Nanostring's nCounter PanCancer IO 360 panel. Somatic mutations were identified by a targeted DNA sequencing panel. The T cell-inflamed GEP was positively associated with tumor mutation burden and microsatellite instability high (MSI-H). Higher T cell-inflamed GEP had favorable CRC-specific survival (hazard ratio [HR] per standard deviation unit=0.50, p=0.004) regardless of hypermutation or MSI status. Analysis of recurrently mutated genes having at least 10 mutation carriers, suggested that the T cell-inflamed GEP is positively associated with RYR1, and negatively associated with APC. However, these associations were attenuated after adjusting for hypermutation or MSI status. We also found that expression of genes RPL23, EPCAM, AREG and ITGA6, and the Wnt signaling pathway was negatively associated with the T cell-inflamed GEP, which might indicate immune-inhibitory mechanisms. Our results show that the T cell-inflamed GEP is a prognostic biomarker in non-hypermutated microsatellite-stable CRC. This also suggests that patient stratification for immunotherapy within this CRC subgroup should be explored further. Moreover, reported immune-inhibitory gene expression signals may suggest targets for therapeutic combination with immunotherapy.

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas.

Although some biomarkers have been used to predict prognosis of lower-grade gliomas (LGGs), a pathway-related signature associated with immune response has not been developed. A key signaling pathway was determined according to the lowest adjusted p value among 50 hallmark pathways. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox analyses were performed to construct a pathway-related gene signature. Somatic mutation, drug sensitivity and prediction of immunotherapy analyses were conducted to reveal the value of this signature in targeted therapies. In this study, an allograft rejection (AR) pathway was considered as a crucial signaling pathway, and we constructed an AR-related five-gene signature, which can independently predict the prognosis of LGGs. High-AR LGG patients had higher tumor mutation burden (TMB), Immunophenscore (IPS), IMmuno-PREdictive Score (IMPRES), T cell-inflamed gene expression profile (GEP) score and MHC I association immunoscore (MIAS) than low-AR patients. Most importantly, our signature can be validated in four immunotherapy cohorts. Furthermore, IC50 values of the six classic chemotherapeutic drugs were significantly elevated in the low-AR group compared with the high-AR group. This signature might be regarded as an underlying biomarker in predicting prognosis for LGGs, possibly providing more therapeutic strategies for future clinical research.

T cell-inflamed gene expression profile and PD-L1 expression and pembrolizumab efficacy in advanced esophageal cancer.

Aim: Investigate the relationship between response to pembrolizumab and expression of the 18-gene T cell-inflamed gene expression profile (TcellinfGEP) or PD-L1 combined positive score (CPS) in esophageal cancer. Materials & methods: This analysis included heavily pretreated patients with advanced/metastatic esophageal/gastroesophageal junction adenocarcinoma or squamous cell carcinoma who received pembrolizumab in the single-arm, phase II study KEYNOTE-180. PD-L1 CPS was evaluated with PD-L1 IHC 22C3 pharmDx. Results: In patients with squamous cell carcinoma, trends toward enrichment for responders were observed for patients with PD-L1 CPS ≥10 tumors. In patients with adenocarcinoma, a trend was observed for TcellinfGEP but not for PD-L1. Conclusion: TcellinfGEP and PD-L1 CPS may enrich for responders to pembrolizumab in patients with esophageal cancer. Clinical trial registration: NCT02559687 (ClinicalTrials.gov).

Baseline and post-treatment biomarkers of resistance to anti-PD-1 therapy in acral and mucosal melanoma: an observational study

BackgroundImmunotherapies targeting programmed cell death-1 (PD-1) and its ligands have improved clinical outcomes for advanced melanoma. However, many tumors exhibit primary resistance or acquire secondary resistance after an initial positive...

Better tumor immune microenvironment in patients with older lung adenocarcinoma.

e20544 Background: Lung adenocarcinomas (LUAD) is the most common histological subtype of lung cancers. Immunotherapies (ICIs) have been confirmed to improve the clinical outcomes of LUAD patients. Efficacies of ICIs are considered strongly associated with tumor immune microenvironments (TIME). Age-related immune dysfunction might induce difference on the efficacy of ICIs between younger and older patients. However, the potential effect of age on TIME remains little known and controversial. Herein, we aimed to analysis the association between age and TIME based on The Cancer Genome Atlas (TCGA) database. Methods: We screened out 582 LUAD patients with complete information, whose tumors underwent next-generation sequencing (NGS) detection in TCGA. All patients were divided into two groups according to age, the younger group (age < 50-year old) and the older group (age≥50-year old). The differences of immune-related signatures between the two groups were calculated according to previous reports. We also analyzed the differences in immune-related signature between different clinical stages. P-values were calculated via the T.Test. Results: In total 582 patients with LUAD in our study, 115 (19.76%) patients in younger group and 467 (80.24%) patients in older group were found. Many immune-related signatures were found significantly higher in older group than in younger group, including cytolytic activity (CYT) (p = 0.0352), expanded immune signature (p = 0.0065), T cell inflamed gene expression profile (GEP) (p = 0.0048), IFN-γ-related response genes (p = 0.0346), immune signature (p = 0.0022), immunosuppression (p = 0.0065), major histocompatibility complex class I (MHC class I) (p = 0.0319), T-cell survival (p = 0.0235), tertiary lymphoid structures (TLS) signature (p = 0.0001) and total_TILs_scores (p = 0.0020). In addition, tertiary lymphoid structure (p = 0.0355) and TLS_signature (p = 0.0243) were found significantly difference in different clinical staging, which decreased as the staging get later. On the contrary, cell cycle score (p = 0.0001) increased as the staging get later. Conclusions: Our study evaluated the impact of age and clinical stage on the TIME in patients with LUAD using a threshold of 50 years old for the first time. We founded that LUAD patients in older group had better TIME than in younger group and some immune-related signatures were significantly related with clinical staging.

Identification and Validation of a Gene Signature for Lower-Grade Gliomas Based on Pyroptosis-Related Genes to Predict Survival and Response to Immune Checkpoint Inhibitors.

Pyroptosis plays a critical role in the immune response to immune checkpoint inhibitors (ICIs) by mediating the tumor immune microenvironment. However, the impact of pyroptosis-related biomarkers on the prognosis and efficacy of ICIs in patients with lower-grade gliomas (LGGs) is unclear. An unsupervised clustering analysis identified pyroptosis-related subtypes (PRSs) based on the expression profile of 47 pyroptosis-related genes in The Cancer Genome Atlas-LGG cohort. A PRS gene signature was established using univariate Cox regression, random survival forest, least absolute shrinkage and selection operator, and stepwise multivariable Cox regression analyses. The predictive power of this signature was validated in the Chinese Glioma Genome Atlas database. We also investigated the differences between high- and low-risk groups in terms of the tumor immune microenvironment, tumor mutation, and response to target therapy and ICIs. The PRS gene signature comprised eight PRS genes, which independently predicted the prognosis of LGG patients. High-risk patients had a worse overall survival than did the low-risk patients. The high-risk group also displayed a higher proportion of M1 macrophages and CD8+ T cells and higher immune scores, tumor mutational burden, immunophenoscore, IMmuno-PREdictive Score, MHC I association immune score, and T cell-inflamed gene expression profile scores, but lower suppressor cells scores, and were more suitable candidates for ICI treatment. Higher risk scores were more frequent in patients who responded to ICIs using data from the ImmuCellAI website. The presently established PRS gene signature can be validated in melanoma patients treated with real ICI treatment. This signature is valuable in predicting prognosis and ICI treatment of LGG patients, pending further prospective verification.

Integrative genomic analysis reveals low T-cell infiltration as the primary feature of tobacco use in HPV-positive oropharyngeal cancer

SummaryAlthough tobacco use is an independent adverse prognostic feature in HPV(+) oropharyngeal squamous cell carcinoma (OPSCC), the biologic features associated with tobacco use have not been systematically investigated. We characterized genomic and immunologic features associated with tobacco use through whole exome sequencing, mRNA hybridization, and immunohistochemical staining in 47 HPV(+) OPSCC tumors. Low expression of transcripts in a T cell-inflamed gene expression profile (TGEP) was associated with tobacco use at diagnosis and lower overall and disease-free survival. Tobacco use was associated with an increased proportion of T > C substitutions and a lower proportion of expected mutational signatures, but not with increases in mutational burden or recurrent oncogenic mutations. Our findings suggest that rather than increased mutational burden, tobacco’s primary and clinically relevant association in HPV(+) OPSCC is immunosuppression of the tumor immune microenvironment. Quantitative assays of T cell infiltration merit further study as prognostic markers in HPV(+) OPSCC.

Abstract 3044: The unexplored immune landscape of high-risk pediatric cancers

Abstract In adult cancer, immune signatures such as the T cell-inflamed gene expression profile (GEP) have been developed to predict which patients are likely to respond to immune checkpoint inhibitors (ICIs) beyond high tumor mutation burden (TMB) and PD-L1 expression. The GEP infers T cell infiltration and activation in the tumor microenvironment (TME) from transcriptomic data. However, it is not known whether tools such as GEP are applicable in pediatric cancer, as the TME in childhood cancers is largely unexplored and response to ICIs are rare. We have undertaken an integrated analysis of the pediatric TME using RNA-sequencing (RNA-seq) and immunohistochemistry (IHC). Our goal is to identify patients with T cell-inflamed or “hot” tumors who may benefit from ICIs. Through Australia's ZERO childhood cancer precision medicine program we performed RNA-seq on 347 high-risk pediatric cancers (estimated <30% chance of survival) and performed IHC for CD4, CD8, CD45 and PD-L1 on 112 matching samples. Using both informatic assessments and IHC as independent measures of immune infiltration, we mapped the immune landscape of the TME across a broad range of high-risk pediatric cancers. As RNA-seq is increasingly used in the analysis of patient tumors, we investigated numerous molecular correlates of immune infiltration, tailored specifically to pediatric patients. RNA-seq was used to generate the GEP and map expression profiles of immune checkpoint genes, and deconvolution algorithms were used to extract the immune cell composition for every tumor. The correlation analysis between IHC, deconvolution of cell mixture composition and GEP were assessed, including PD-L1 protein and mRNA expression. We observed significant correlation between PD-L1 protein and mRNA expression and a weak correlation of CD8+ T cells with GEP. Deconvoluted TME estimates were most tightly correlated with the presence of T cell infiltrates (CD4 and CD8) with IHC. TMB and tumor purity estimates were derived from whole genome sequencing for each case. No correlation was observed between TMB and immune infiltration, however, tumor purity was negatively correlated with immune infiltration. Using IHC as an independent marker of a T cell-inflamed TME, we have identified a novel pediatric immune signature that includes markers of CD4 and CD8 T cells, T cell cytotoxicity, T and NK cell recruitment and activation, MHC Class II molecules and immune checkpoints. This is the first study to comprehensively analyze the pediatric TME in a cohort of this size and diversity, with matching IHC for orthogonal validation. Through the combination of RNA-seq and IHC, we have devised a novel immune signature specific to pediatrics and these techniques have identified a subset of patients that are immune “hot” and may potentially respond to ICIs. Conversely, we also highlight the potential of identifying immune “cold” patients who may need immunomodulatory combination strategies to maximize immune response. Citation Format: Chelsea Mayoh, Rachael L. Terry, Marie Wong, Loretta M. Lau, Dong Anh Khuong-Quang, Marion K. Mateos, Vanessa Tyrrell, Michelle Haber, David S. Ziegler, Mark J. Cowley, Joseph A. Trapani, Paul J. Neeson, Paul G. Ekert. The unexplored immune landscape of high-risk pediatric cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3044.

Abstract 2009: Evaluation of RNA-sequencing signatures with response to pembrolizumab (pembro) monotherapy in ipilimumab-naive patients (pts) with melanoma

Abstract Introduction: KEYNOTE-001 (NCT01295827) was a phase 1 study of pembro in pts with locally advanced or metastatic melanoma (parts B and D). KEYNOTE-006 (NCT01866319) was a randomized phase 3 study of pembro vs ipilimumab in pts with advanced melanoma. We explored potential relationships between key tumor microenvironment canonical signatures beyond T cell-inflamed gene expression profile (GEP) and response/resistance to pembro monotherapy in pts with melanoma. Methods: In pembro-treated, ipilimumab-naive pts from KEYNOTE-001 and KEYNOTE-006 with available RNA-sequencing and clinical data (n = 476), we analyzed association of 9 non-T cell-inflamed GEP canonical signatures (angiogenesis, gMDSC, glycolysis, hypoxia, Myc, proliferation, RAS, stromal/EMT/TGFβ, WNT) with clinical outcomes. Signatures were defined with TCGA and Moffitt databases (independent of any pembro trial) using a correlation algorithm to select individual genes for membership in the canonical signature based on correlation with reference signatures identified in literature or internal work. Relationships between RNA signatures and clinical outcomes were assessed using 2 models: 1 adjusted for ECOG PS and batch effect and 1 adjusted for T cell-inflamed GEP to understand the additional explanatory value of a non-T cell-inflamed GEP signature for clinical outcomes. P values were adjusted for multiplicity; significance was predefined at α = 0.05. Database cutoffs for clinical data: 11/27/2017 (KEYNOTE-001), 12/4/2017 (KEYNOTE-006). Results: T cell-inflamed GEP was statistically significantly associated with response to pembro (P < 0.0001). No canonical signatures showed statistically significant association with response/resistance to pembro after multiplicity adjustment when adjusting for T cell-inflamed GEP, ECOG PS, and batch effect. Without adjusting for T cell-inflamed GEP, Myc signature was the only signature identified as statistically significantly associated with response to pembro in the postulated direction of negative association. Prolonged OS, but not PFS, was observed in pts with a lower Myc signature. Myc signature did not show independent predictive value beyond T cell-inflamed GEP, indicating that interferon γ-related T-cell inflammation has a more dominant impact on immunotherapy efficacy than the Myc signature and other gene sets in immune-suppressive axes. Conclusions: In this exploratory analysis, no canonical signatures showed statistical significance after adjusting for T cell-inflamed GEP. Although observed only without adjusting for T cell-inflamed GEP, Myc signature was negatively associated with response in ipilimumab-naive pts with melanoma receiving pembro monotherapy. Citation Format: Adil Daud, Matteo S. Carlino, Antoni Ribas, Ana Arance, Jean-Jacques Grob, James Larkin, Georgina V. Long, Jacob Schachter, Andrea L. Webber, Clemens Krepler, Chunsheng Zhang, Jared Lunceford, Razvan Cristescu, Qing Zhao, Junshui Ma, Caroline Robert. Evaluation of RNA-sequencing signatures with response to pembrolizumab (pembro) monotherapy in ipilimumab-naive patients (pts) with melanoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2009.

Abstract CT032: A phase 1/2, open-label, multicenter, dose escalation and efficacy study of mRNA-2416, a lipid nanoparticle encapsulated mRNA encoding human OX40L, for intratumoral injection alone or in combination with durvalumab for patients with advanced malignancies

Abstract Background: While PD-1/L1 blockade is an effective therapeutic approach for many patients with solid and hematologic malignancies, it is not sufficient to induce tumor regressions in the majority of patients. Optimal T cell responses require T cell receptor activation and co-stimulation, which can be provided via ligation of tumor necrosis factor receptor family members, such as OX40. Binding of OX40 by OX40L in the presence of a recognized antigen promotes CD4+ and CD8+ T cell expansion, enhances memory responses and inhibits regulatory T cell function. mRNA-2416 is a novel mRNA-based lipid nanoparticle therapeutic agent that expresses the wild type human OX40L. Preclinical in vivo anti-tumor activity of a murine mRNA-2416 surrogate and synergy with anti-PD-L1 antibodies in syngeneic cancer models are observed (unpublished). Here we present the findings of a first-in-human study of mRNA-2416 monotherapy delivered intratumorally in solid tumor patients with accessible lesions. Methods: This study tested the safety and efficacy of mRNA-2416 administered every 2 weeks for up to 12 doses in a standard 3+3 phase 1 dose escalation in patients with locally advanced, recurrent or metastatic solid malignancy or lymphoma. Tumor biopsies were collected pre- and post-treatment and evaluated by quantitative immunofluorescence (QIF) and RNA sequencing to characterize OX40L expression and immune response following treatment. Results: As of November 13, 2019, 39 patients have been treated at 4 dose levels from 1-8 mg. mRNA-2416 was generally well-tolerated with no DLTs. 6 out of 39 patients experienced grade 3 treatment related AEs. Out of 14 patients with best overall response of stable disease by RECIST, 6 had stable disease for ≥ 14 weeks, and 4 had tumor shrinkage in the injected lesions. Analyses of paired biopsies from injected lesions by QIF showed increased OX40L protein expression as well as elevated T cell scores post-treatment. Activation of a pro-inflammatory gene expression response post-treatment was observed in many cases, including increased cytolytic activity scores, elevated PD-L1 expression, and stimulation of a T cell-inflamed gene expression profile predictive of anti-PD-1/L1 response. These findings were observed in patients with long duration on study or tumor shrinkage. Conclusion: Intratumoral mRNA-2416 is tolerable at all dose levels studied when given as monotherapy and analyses of tumor post-treatment demonstrate increased OX40L protein expression, elevated PD-L1 levels and pro-inflammatory activity. Taken together with the observation of preclinical in vivo synergy with PD-L1 blockade, these data support the evaluation of a combination of intratumoral mRNA-2416 with the anti-PD-L1 inhibitor durvalumab in solid tumors, which is ongoing in part B of this study. Citation Format: Antonio Jimeno, Shilpa Gupta, Ryan Sullivan, Khanh T. Do, Wallace L. Akerley, Ding Wang, Deanna Teoh, Kurt Schalper, Sima J. Zacharek, Jing Sun, Andressa S. Laino, Joshua Frederick, Honghong Zhou, William Randolph, Stephanie Pascarella, Lisa Johansen, Pamela S. Cohen, ROBERT S. MEEHAN, Todd M. Bauer. A phase 1/2, open-label, multicenter, dose escalation and efficacy study of mRNA-2416, a lipid nanoparticle encapsulated mRNA encoding human OX40L, for intratumoral injection alone or in combination with durvalumab for patients with advanced malignancies [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT032.

Macrophage correlates with immunophenotype and predicts anti-PD-L1 response of urothelial cancer.

Immune-checkpoint blockades (ICBs) have been routinely implemented to treat metastatic urothelial cancer (mUC), whereas robust biomarkers are urgently warranted. Herein, we explored latent promising biomarkers based on 348 pretreatment mUC samples from IMvigor210.Methods: The genome, transcriptome, immunome, and metabolome were systemically analyzed using the external TCGA dataset for validation. Kaplan-Meier and ROC curve analyses were performed to estimate the predictive capacity of M1-macrophage infiltration. Chi-square/Spearman/Mann Whitney U test are used to determine its correlation to genetic, biochemical, and clinicopathological parameters.Results: M1 frequency is a robust biomarker for predicting the prognosis and response to ICBs, which is non-inferior to tumor mutation burden (TMB) or tumor neoantigen burden (TNB), and exceeds CD8 T cells, T cell inflamed gene expression profile (GEP), and PD-L1 expression. Moreover, M1 infiltration is associated with immune phenotypes (AUC = 0.785) and is negatively correlated with immune exclusion. Additionally, transcriptomic analysis showed immune activation in the high-M1 subgroup, whereas it showed steroid and drug metabolism reprograming in the M1-deficient subset, which characterized the limited sensitivity to ICB therapy. Notably, investigation of the corresponding intrinsic genomic profiles highlighted the significance of TP53 and FGFR alterations.Conclusions: M1 infiltration is a robust biomarker for immunotherapeutic response and immunophenotype determination in an mUC setting. Innate immunity activation involving macrophage polarization remodeling and anti-FGFR mutations may be promising strategies for synergy with anti-PD-L1 treatments and may help prolong the clinical survival of patients with mUC.

Transcriptomic landscape of tumour cells undergoing T-cell attack

Abstract Background The study of crosstalks between cancer cells and T cells in the tumour microenvironment (TME) can inform on tumour immune escape and help in predicting responses to immunotherapy. By reproducing in vitro how tumour infiltrating lymphocytes (TILs) interact with cancer cells, novel methodologies may allow a thorough characterization of the transcriptomic changes induced in tumours undergoing a T cell attack (TuTACK). Methods Thirteen pairs of highly tumour-reactive TILs and autologous cancer cell lines, covering four distinct tumour types, were selected and co-cultured to induce a cytostatic effect in tumour cultures. The global TuTACK transcriptome was characterized, and a TuTACK gene signature was extracted to be tested for prediction of response to anti-PD-1/anti-PD-L1. Results We showed that an autologous T cell attack induced large transcriptomic changes in tumours, that were independent of IFN-g signaling. Transcriptomic changes were tumour-type independent and allowed the identification of a gene-set (TuTACK gene-set) containing 256 genes covering 55 defined biological processes, that included several potential actionable adaptive immune resistance pathways. We extracted a 14-gene signature (TuTACK signature) that allowed a novel scoring of the TME. The TuTACK score correlated well to the estimated immunological activity in the TME (measured by the T cell-inflamed gene expression profile or GEP), and was predictive of response to anti-PD-1/PD-L1 therapy across 26 tumour types (Spearman R = 0.54, Pearson R = 0.57) outperforming the T cell-inflamed GEP score (Spearman R = 0.25, Pearson R = 0.34) and with a comparable predictive power to the tumour mutational burden (TMB; Spearman R = 0.65, Pearson R = 0.56). The TuTACK score was only moderately correlated to the TMB (Spearman R = 0.36; Pearson R = 0.53), indicating that these biomarkers may be independent. Conclusion TuTACK measured the effects of an immune response rather than its activity and it represents an innovative method to identify immunologically hot tumours. Our findings suggested that TuTACK may allow better patient selection in immunotherapy clinical trials and provide hints to improve the treatment of “hot” tumours resistant to current immunotherapies. Legal entity responsible for the study The authors. Funding The Danish Cancer Society (grant number R148-A9862); The Lundbeck Foundation (grant number R233-2016-3728); The Capital Region of Denmark Research Foundation (grant number R146-A5693); The National Research, Development and Innovation Fund of Hungary (FIEK_16-1-2016-0005). Disclosure All authors have declared no conflicts of interest.

1589TiP - KEYNOTE-495/KeyImPaCT: A randomized, biomarker-directed, phase II trial of pembrolizumab-based therapy for non–small cell lung cancer (NSCLC)

BackgroundKEYNOTE-495 is a randomized, open-label, phase II trial (NCT03516981) evaluating the clinical activity and safety of pembrolizumab (pembro)-based combination (combo) therapy in patients (pts) with treatment-naive, advanced NSCLC in biomarker-defined response groups. This biomarker-based approach is based on 2 validated, independent, next-generation biomarkers (T cell–inflamed gene expression profile [GEP] and tumor mutational burden [TMB]) and can help determine the differential efficacy of pembro-based combo therapy, based on the composite biomarker profile, and inform precision immunotherapy in the future. Trial designIn this group-sequential, adaptive randomized trial, pts (N∼288) receive pembro 200mg Q3W intravenously (IV) combined with MK-4280 (anti–LAG-3) 200mg Q3W IV, lenvatinib (lenv) 20mg PO QD, or MK-1308 (anti–CTLA-4) 25mg Q6W IV for 35 cycles (∼2 years); pts in the lenv arm may receive lenv monotherapy until disease progression or toxicity. After biomarker screening, pts are assigned to 1 of 4 groups—TMBlowGEPlow, TMBhighGEPlow, TMBlowGEPhigh, and TMBhighGEPhigh—then randomized to 1 of 3 pembro-based regimens; adaptive design elements are used to adjust randomization based on objective responses. Eligible pts are ≥18 years of age with histologically or cytologically confirmed treatment-naive, advanced NSCLC; documented absence of EGFR and B-Raf mutations and ALK and ROS1 gene rearrangements; measurable disease per RECIST v1.1; and ECOG PS 0-1. Response is assessed by imaging Q9W for the first year and Q12W thereafter using RECIST v1.1. Primary end point is investigator-assessed objective response rate (RECIST v1.1). Secondary end points are progression-free survival, overall survival, and safety. Multiple interim analyses may be performed given the group-sequential design. Enrollment is ongoing. Clinical trial identificationNCT03516981: Trial initiation, October 1, 2018. Editorial acknowledgementHolly C. Cappelli, PhD, and Dana Francis, PhD, of the ApotheCom pembrolizumab team (Yardley, PA, USA); funded by Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. Legal entity responsible for the studyMerck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. FundingMerck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA. DisclosureM. Gutierrez: Advisory / Consultancy: Eli Lilly, Foundation One, Essanex, Guardant 360; Speaker Bureau / Expert testimony: Merck, BMS. M.D. Hellmann: Advisory / Consultancy: Merck, Bristol-Myers Squibb, AstraZeneca, Genentech/Roche, Janssen, Nektar, Syndax, Mirati, and Shattuck Labs; Shareholder / Stockholder / Stock options: Shattuck Labs; Research grant / Funding (institution): BMS; Travel / Accommodation / Expenses: AstraZeneca, BMS; Non-remunerated activity/ies, A patent has been filed by MSK related to the use of tumor mutation burden to predict response to immunotherapy (PCT/US2015/062208), which has received licensing fees from PGDx.: MSK. M.A. Gubens: Advisory / Consultancy: AbbVie, ARIAD, AstraZeneca, BMS, Roche/Genentech, Heron, Mersana, Novartis, Pfizer; Research grant / Funding (institution), Travel / Accommodation / Expenses: Celgene, Merck, Novartis; Research grant / Funding (institution): OncoMed, Roche. C. Aggarwal: Advisory / Consultancy: BMS, Celgene, Roche/Genentech, AstraZeneca. D.S.W. Tan: Honoraria (self): Novartis, Bayer, Boehringer Ingelheim, AstraZeneca, BMS, Roche, Takeda, Pfizer; Research grant / Funding (self): Novartis, Bayer, AstraZeneca, GSK, Pfizer; Advisory / Consultancy: Novartis, Bayer, Boehringer Ingelheim. E. Felip: Advisory / Consultancy, Speaker Bureau / Expert testimony: AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Eli Lilly, Merck KGaA, MSD, Novartis, Pfizer, Roche, Takeda; Advisory / Consultancy: Blue Print Medicines, Celgene, Guardant Health. J.C. Yang: Honoraria (self), Advisory / Consultancy: Boehringer Ingelheim, Eli Lilly, Bayer, Roche/Genentech, Chugai, MSD, Pfizer, Novartis, BMS, Ono Pharmaceuticals ; Advisory / Consultancy: Merck Serono, Celgene, Merrimack, Yuhan Pharmaceuticals, Daiichi Sankyo, Hansoh Pharmaceuticals, Takeda Pharmaceuticals Blueprint Medicines. E.B. Garon: Research grant / Funding (self), Clinical trial funding: Merck, AstraZeneca, BMS. A. Basso: Full / Part-time employment: Merck . H. Ma: Full / Part-time employment: Merck . L. Fong: Research grant / Funding (self): Merck . A. Snyder: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck . J. Yuan: Full / Part-time employment: Merck . R.S. Herbst: Advisory / Consultancy: AbbVie, AstraZeneca, Biodesix, BMS, Eli Lilly, EMD Serano, Roche/Genentech, Heat Biologics, Junshi, Loxo Oncology Merck, Nektar, NextCure, Novartis, Pfizer, Sanofi, Seattle Genetics, Shire PLC, Spectrum, Symphogen, Tesaro ; Research grant / Funding (self): AstraZeneca, Eli Lilly, Merck; Advisory / Consultancy, Scientific Advisory Boards: Neon Therapeutics, Infinity Pharmaceuticals, NextCure; Officer / Board of Directors: Junshi Pharmaceuticals. All other authors have declared no conflicts of interest.

Abstract 4217: Tumor mutational burden (TMB), T cell-inflamed gene expression profile (GEP) and PD-L1 are independently associated with response to pembrolizumab (Pembro) in patients with advanced melanoma in the KEYNOTE (KN)-006 study

Abstract Background: Biomarkers may aid in identifying pts who can benefit from checkpoint blockade therapies. Biomarkers of response to anti-PD-1 therapy include TMB and inflammatory biomarkers such as PD-L1 expression and T cell-inflamed GEP. Effects of TMB and GEP on clinical outcomes were evaluated for Pembro (anti-PD-1) and Ipi (anti-CTLA-4) monotherapies in the KN-006 study. Methods: In this phase 3, controlled, open label study, 834 pts were randomized to receive Pembro 10 mg/kg every 2 or 3 wks or 4 doses of Ipi 3 mg/kg every 3 wks. Data were available for analysis of TMB (whole exome sequencing) in 216 pts (Pembro n=151 and Ipi n=65), for GEP (RNA, NanoString nCounter) in 641 pts (Pembro n=461 and Ipi n=180) and 134 pts had both TMB and GEP data available. All pts with TMB data and 458 pts with GEP data had PD-L1 expression data (PD-L1 IHC 22C3 pharmDx, MEL score). Statistical testing was prespecified prior to merging biomarker and clinical outcome data. Relationships between biomarkers and best overall response (BOR) were assessed by logistic regression and by area under the ROC (AUROC) curve; progression free survival (PFS) and overall survival (OS) by Cox proportional hazards regression. Prespecified cutoffs were -0.318 for GEP and 175 (mutations/exome) for TMB. Clinical data cutoff was Dec 04, 2017. Results: TMB, GEP and PD-L1 MEL were significantly associated with BOR, PFS and OS in the Pembro arm (p<0.050). Response rates to Pembro therapy were greater in pts who had high levels of both TMB ≥175 and GEP ≥-0.318 or TMB ≥175 and PD-L1 MEL ≥2 compared with those with low levels of these biomarkers (54% vs 14% and 51% vs 33%, respectively). TMB, GEP and PD-L1 MEL remained significantly associated with response to Pembro for BOR and PFS, and in general for OS, when assessed in joint models. TMB showed low correlations with GEP (0.14; p=0.057) and PD-L1 (0.22; p=0.001); GEP and PD-L1 were moderately correlated (0.60; p<0.001). In Ipi-treated pts, TMB was not significantly associated with BOR (p=0.428) and trended toward significance for PFS (0.098) and OS (p=0.099); GEP was also not significantly associated with BOR (p=0.188) but was significantly associated with PFS (p=0.012) and OS (p<0.001). AUROCs (95% CI) were 0.64 (0.55, 0.73) and 0.53 (0.35, 0.70) for TMB, and 0.64 (0.59, 0.7) and 0.56 (0.45, 0.67) for GEP with Pembro and Ipi. Note the observed TMB relationship with Ipi is based on an assessment of limited data in that arm and definitive conclusions cannot be made. Conclusion: TMB and inflammatory biomarkers (GEP and PD-L1) showed statistically significant and independent associations with BOR, PFS and OS in Pembro-treated pts with advanced melanoma. Only GEP showed significant associations with PFS and OS for Ipi, potentially indicating a prognostic value. Citation Format: Antoni Ribas, Caroline Robert, Jacob Schachter, Georgina V. Long, Ana Arance, Matteo S. Carlino, James Larkin, Andrea L. Webber, Jared Lunceford, Qing Zhao, Razvan Cristescu, Michael Nebozhyn, Chunsheng Zhang, Wendy Blumenschein, Clemens Krepler, Nageatte Ibrahim, Adil Daud, Jean-Jacques Grob. Tumor mutational burden (TMB), T cell-inflamed gene expression profile (GEP) and PD-L1 are independently associated with response to pembrolizumab (Pembro) in patients with advanced melanoma in the KEYNOTE (KN)-006 study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4217.