Gene Expression Profile Score Research Articles

Evaluation of tumor gene expression profile and Gleason score in patients with metastatic prostate cancer.

Evaluation of tumor gene expression profile and Gleason score in patients with metastatic prostate cancer.

A Deep Learning–Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, the evaluation of TILs has not been applied to routine clinical practice due to reproducibility issues. We developed two convolutional neural network models to detect TILs and to determine their spatial location in whole-slide images, and established a spatial assessment pipeline to objectively quantify intraepithelial and stromal TILs in patients with high-grade serous ovarian carcinoma. The predictions of the established models showed a significant positive correlation with the number of CD8+ T cells and immune gene expressions. We demonstrated that patients with a higher density of intraepithelial TILs had a significantly prolonged overall survival (OS) and progression-free survival (PFS) in multiple cohorts. Based on the density of intraepithelial and stromal TILs, we classified patients into three immunophenotypes: immune-inflamed, excluded, and desert. The immune-desert subgroup showed the worst prognosis. Gene expression analysis showed that the immune-desert subgroup had lower immune cytolytic activity (CYT) and T-cell-inflamed gene-expression profile (GEP) scores, whereas immune-excluded subgroup had higher expression of interferon-γ and programmed death 1 receptor (PD-1) signaling pathway. Our established evaluation method provides detailed and comprehensive quantification of intraepithelial and stromal TILs throughout hematoxylin and eosin (H&E)-stained slides, and has potential for clinical application for personalized treatment of patients with ovarian cancer.

Correlation of tumor gene expression profile and gleason score (GS) in patients (pts) with metastatic prostate cancer

Correlation of tumor gene expression profile and gleason score (GS) in patients (pts) with metastatic prostate cancer

Abstract 12035: Impact of Viruses on Donor Derived Cell Free DNA After Heart Transplantation

Introduction: Little is known about the relationship between active viral infections and donor-derived cell free DNA (dd-cfDNA) levels in patients following heart transplantation. Methods: Paired respiratory viral panel, cytomegalovirus (CMV) or other for-cause viral studies and dd-cfDNA (AlloSure) results were prospectively collected on single-organ heart transplant recipients enrolled between August 2022 and March 2023. The levels of dd-cfDNA were compared between patients with positive and negative viral results at enrollment. Results: Of 44 patients enrolled, 18 tested positive with viral infections. Baseline characteristics were comparable between groups (median age 61 years, 73% male). The median time post-transplant was 289 days in patients with viral infections and 126 days in those without infections (p=0.046). None of the patients had concerns for concomitant rejection or graft dysfunction at time of their viral infection. Viral infection cases included 10 CMV, 1 Hepatitis-B and CMV, 3 Epstein-Barr virus (EBV), 2 Influenza, 1 Respiratory Syncytial virus (RSV), and 1 Coronavirus-19. Allomap gene-expression profile scores were similar between groups (p=0.15); whereas dd-cfDNA levels were significantly higher in patients with viral infections compared to controls (p=0.002). Table 1, Figure 1 Conclusion: Active viral infections can raise the level of dd-cfDNA levels in patients following heart transplantation. Further studies are needed to validate these preliminary findings.

Abstract 4655: The prognostic significance of a 12-chemokine tertiary lymphoid structure (TLS) gene signature in uveal melanoma (UM)

Abstract Introduction Lymphoid aggregates are commonly associated with better prognosis and enhanced response to immune modulators in several cancers. Considering the immune-privileged status of the eye we sought to investigate the immune, genomic and prognostic significance of 12-chemokine TLS gene signature in UM patients. Methods A previously validated 12-chemokine gene signature established in cutaneous melanoma was used (CCL2-5, CCL8, CCL18, CCL19, CCL21, CXCL9-11, CXCL13). Clinical, genomic and transcriptomic data was retrieved from The Cancer Genomic Atlas UM cohort (n = 80) and the GSE22138 dataset (n = 63) from the gene expression omnibus. The signature was constructed using principal component (PC) analyses based on the first PC1. Patients with a PC1 score > +4 or < -4 were considered gene expression profile (GEP) high and low, respectively. The CIBERSORT algorithm was used to estimate the immune composition in tumor tissue. Gene Set Enrichment Analysis (GSEA) was conducted using the Hallmarks gene sets. A cytotoxic T cell (CTL) score was calculated based on the coordinate expression of CD8A, CD8B, GZMA, GZMB and PRF1. Results The 12-chemokine score was higher among epithelioid vs. spindle cell or mixed histology (mean: 7.84 vs -4.91 vs 1.22, p = 0.038) and there were no differences across different tumor sites or stages. GEP low patients had significantly better overall survival (HR: 0.10, 95% CI: 0.03-0.36, p < 0.001) and disease-free survival (HR: 0.23, 95% CI: 0.06-0.88, p = 0.031) compared to GEP high. Metastasis-free survival was not significantly different in the second cohort (0.47, 95% CI: 0.16-1.42, p = 0.182). The EIF1AX and SF3B1 driver mutations were significantly more frequent among GEP low (22.5% and 35%) compared to GEP high patients (3.7% and 7.4%). Tumor mutational burden and other driver mutations (BAP1, GNA11, GNAQ) were similar between both groups. GSEA revealed significant enrichment of inflammatory response (IFN-α/γ, TNF-α signalling via NF-κB, IL2-STAT5, IL6-JAK-STAT3 signalling), Epithelial Mesenchymal Transition (EMT), reactive oxygen species, and angiogenesis pathways in GEP high patients. GEP low patients had lower CTL scores compared to GEP high patients (31.3 vs 11.4, p < 0.001). M1 macrophages, CD8+ and regulatory T cells were enriched in GEP high patients whereas CD4+ memory T cells and activated dendritic cells were more prevalent in GEP low patients. Conclusion Uveal melanoma patients with a high GEP score had inferior survival and were enriched for inflammatory, angiogenic, and EMT pathways, while patients with a low GEP score were more likely to express prognostically favourable driver mutations (EIF1AX, SF3B1). Our results suggest a variable prognostic role of lymphoid aggregates in the setting of UM compared to other solid tumors, warranting further investigation for their differential underlying mechanisms. Citation Format: Hassan Mohammed Abushukair, Ayah Al-Bzour, Andrew Knight, Walter J. Storkus, John M. Kirkwood, Lilit Karapetyan. The prognostic significance of a 12-chemokine tertiary lymphoid structure (TLS) gene signature in uveal melanoma (UM). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4655.

Routine imaging guided by a 31-gene expression profile assay results in earlier detection of melanoma with decreased metastatic tumor burden compared to patients without surveillance imaging studies

Patients with early-stage disease typically have a good prognosis, but still have a risk of recurrence, even with negative sentinel lymph node biopsy (SLNB). This study explores the utility of routine imaging to detect metastases in patients with negative SLNB but high-risk 31 gene expression profile (31-GEP) scores. We retrospectively identified melanoma patients with negative SLNBs. Patients with high-risk GEP results were placed in the experimental group and patients without GEP testing were placed in the control group. Among both cohorts, recurrent melanoma groups were identified. The tumor burden at the time of recurrence and the time to recurrence were compared between experimental group patients with routine imaging and control group patients without imaging schedules. We identified 327 control patients and 307 experimental patients, of which 14.1% versus 20.5% had melanoma recurrence, respectively. Of the patients with recurrent melanoma, those in the experimental group were older (65.75 versus 59.20), had higher Breslow depths (3.72 mm versus 3.31 mm), and had advanced tumor staging (89.5% versus 71.4% of patients presenting clinical stage ≥ II) compared to the control group at primary diagnosis. However, melanoma recurrence was detected earlier (25.50 months versus 35.35 months) in the experimental group at a lower overall tumor burden (73.10 mm versus 27.60 mm). A higher percentage of experimental patients started immunotherapy when offered (76.3% and 67.9%). Patients who received routine imaging after high-risk GEP test scores had an earlier recurrence diagnosis with lower tumor burden, leading to better clinical outcomes.

Correlation of tumor gene expression profile and gleason score (GS) in patients (pts) with metastatic prostate cancer.

235 Background: GS is the most powerful prognostic predictor in prostate adenocarcinoma. However, the underlying reasons of disease aggressiveness as a function of GS are currently unknown. Herein we sought to investigate the corresponding differences in gene expression profiles of pts with prostate adenocarcinoma with respect to GS. Methods: In this IRB approved retrospective study, eligibility criteria included histologically confirmed prostate adenocarcinoma and available RNA sequencing results from treatment naïve primary prostate tissue by a CLIA certified lab. Pts were categorized into two cohorts: low GS (GS <8) and high GS (GS ≥ 8). The DEseq2 pipeline was used to analyze differentially expressed genes between the groups. The data included the Log2 fold change, Wald-Test p-values, and Benjamini-Hochberg adjusted p-values for each differentially expressed gene. These results were subjected to Gene Set Enrichment software analysis (GSEA) in order to identify pathways enriched in each cohort. All bioinformatic analyses were undertaken using R v4.2. Results: Fifty-seven pts were eligible, of which 13 had a GS <8 and 44 had a GS ≥8. Tumor tissues with high GS had a significantly higher expression of genes involved in the immune pathways (e.g., inflammatory response, interferon-γ, allograft rejection, and interferon-α), epithelial-mesenchymal transition, KRAS signaling, E2F targets and G2M checkpoint (q for all <0.01). The genes involved in the androgen response pathway were significantly more expressed in biopsies with a low GS (q<0.01). Normalized enrichment scores are reported in the table. Differential individual gene expression profiles will be presented at the meeting. Conclusions: Pts with prostatic adenocarcinoma with a GS ≥8 demonstrated a different transcriptomic profile than those with a GS <8. Higher GS tumor tissues had upregulated of inflammatory, proliferation, and KRAS signaling. Lower GS tumor tissues had upregulated androgen signaling pathway. These hypothesis-generating results upon external validation may provide the rationale for personalized therapy in men with prostatic cancer. [Table: see text]

Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic Pathway Signatures.

Breast cancer is one of the most common female malignancies worldwide. Due to its early metastases formation and a high degree of malignancy, the 10 year-survival rate of metastatic breast cancer does not exceed 30%. Thus, more precise biomarkers are urgently needed. In our study, we first estimated the tumor microenvironment (TME) infiltration using the xCell algorithm. Based on TME infiltration, the three main TME clusters were identified using consensus clustering. Our results showed that the three main TME clusters cause significant differences in survival rates and TME infiltration patterns (log-rank test, p = 0.006). Then, multiple machine learning algorithms were used to develop a nine-pathway-based TME-related risk model to predict the prognosis of breast cancer (BRCA) patients (the immune-related pathway-based risk score, defined as IPRS). Based on the IPRS, BRCA patients were divided into two subgroups, and patients in the IPRS-low group presented significantly better overall survival (OS) rates than the IPRS-high group (log-rank test, p < 0.0001). Correlation analysis revealed that the IPRS-low group was characterized by increases in immune-related scores (cytolytic activity (CYT), major histocompatibility complex (MHC), T cell-inflamed immune gene expression profile (GEP), ESTIMATE, immune, and stromal scores) while exhibiting decreases in tumor purity, suggesting IPRS-low patients may have a strong immune response. Additionally, the gene-set enrichment analysis (GSEA) result confirmed that the IPRS-low patients were significantly enriched in several immune-associated signaling pathways. Furthermore, multivariate Cox analysis revealed that the IPRS was an independent prognostic biomarker after adjustment by clinicopathologic characteristics. The prognostic value of the IPRS model was further validated in three external validation cohorts. Altogether, our findings demonstrated that the IPRS was a powerful predictor to screen out certain populations with better prognosis in breast cancer and may serve as a potential biomarker guiding clinical treatment decisions.

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).

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.

Immune Biomarkers in Metastatic Castration-resistant Prostate Cancer

BackgroundMetastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease in which molecular stratification is needed to improve clinical outcomes. The identification of predictive biomarkers can have a major impact on the care of these patients, but the availability of metastatic tissue samples for research in this setting is limited. ObjectiveTo study the prevalence of immune biomarkers of potential clinical utility to immunotherapy in mCRPC and to determine their association with overall survival (OS). Design, setting, and participantsFrom 100 patients, mCRPC biopsies were assayed by whole exome sequencing, targeted next-generation sequencing, RNA sequencing, tumor mutational burden, T-cell–inflamed gene expression profile (TcellinfGEP) score (Nanostring), and immunohistochemistry for programmed cell death 1 ligand 1 (PD-L1), ataxia-telangiectasia mutated (ATM), phosphatase and tensin homolog (PTEN), SRY homology box 2 (SOX2), and the presence of neuroendocrine features. Outcome measurements and statistical analysisThe phi coefficient determined correlations between biomarkers of interest. OS was assessed using Kaplan-Meier curves and adjusted hazard ratios (aHRs) from Cox regression. Results and limitationsPD-L1 and SOX2 protein expression was detected by immunohistochemistry (combined positive score ≥1 and >5% cells, respectively) in 24 (33%) and 27 (27%) mCRPC biopsies, respectively; 23 (26%) mCRPC biopsies had high TcellinfGEP scores (>–0.318). PD-L1 protein expression and TcellinfGEP scores were positively correlated (phi 0.63 [0.45; 0.76]). PD-L1 protein expression (aHR: 1.90 [1.05; 3.45]), high TcellinfGEP score (aHR: 1.86 [1.04; 3.31]), and SOX2 expression (aHR: 2.09 [1.20; 3.64]) were associated with worse OS. ConclusionsPD-L1, TcellinfGEP score, and SOX2 are prognostic of outcome from the mCRPC setting. If validated, predictive biomarker studies incorporating survival endpoints need to take these findings into consideration. Patient summaryThis study presents an analysis of immune biomarkers in biopsies from patients with metastatic prostate cancer. We describe tumor alterations that predict prognosis that can impact future studies.

Survival Genie, a web platform for survival analysis across pediatric and adult cancers

The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan–Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile. The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/.

A novel gene signature associated with poor response to chemoradiotherapy in patients with locally advanced cervical cancer.

ObjectiveWe aimed to investigate the distinct transcriptional landscape in poor responders to concurrent chemoradiotherapy (CCRT) and to gain mechanistic insights into treatment resistance in cervical cancer.MethodsRNA sequencing was performed in patients with locally advanced cervical cancer treated with platinum-based CCRT. Transcriptome data of no durable benefit (NDB; progression-free period <3 years) and durable clinical benefit (DCB; progression-free period >5 years) patients were compared. The NDB score was estimated for each patient using differentially expressed genes between NDB and DCB patients. The potential response to programmed death-1 blockade was estimated using the tumor immune dysfunction and exclusion (TIDE) score and T-cell-inflamed gene expression profile (GEP).ResultsNDB patients exhibited a distinct transcriptional profile compared to DCB patients, such as higher signatures of extracellular matrix organization and epithelial-to-mesenchymal transition. The fraction of cancer-associated fibroblasts (CAFs) within the tumor was significantly higher in NDB patients than in DCB patients. High NDB scores were significantly associated with poor survival in the Cancer Genome Atlas cervical cancer cohort (n=274; p=0.015) but only in patients who received curative aim radiotherapy (p=0.002). Patients with high NDB scores displayed significantly higher TIDE prediction scores and lower T-cell-inflamed GEP scores than those with low NDB scores.ConclusionPatients with cervical cancer having poor CCRT or RT outcomes exhibited a distinct gene signature that could predict treatment outcomes. For poor responders, immune checkpoint inhibitors may be less effective whereas CAF-targeting treatments may be a promising approach.

Survival Genie: A Web Portal for Single-Cell Data, Gene-Ratio, and Cell Composition-Based Survival Analyses

The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. Many packages and tools have been developed to correlate single-gene features to clinical outcomes, but lack in performing such analysis based on multiple-genes, gene sets, and genes ratio. Furthermore, cluster marker genes associated with cell types, states and function from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates associations between the enrichment of known cell types and survival outcome across cancers.We have developed Survival Genie (https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/, a web tool to perform survival analysis on single-cell RNA-seq data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden (Fig. 1). For comprehensive survival evaluation, the Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs for both adult and pediatric cancers including different types of leukemia. Users can upload single-cell data or gene sets and select partitioning methods (i.e., mean, median, quartile, cutp) to determine the effect of their levels on patient survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile (Fig. 1). The Survival Genie source code is written in the R programming language and the interactive web application with the R Shiny framework.We demonstrate the application of the Survival Genie tool by exploring the prognostic utility of blast cell and immune cell markers generated from single cell RNA-seq analysis of paired pediatric AML bone marrow samples taken at the time of diagnosis and end of induction (Thomas, Perumalla et al. 2020) . We identified AML blast specific signature consisting of 7 genes (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH) that depicted significant association with poor survival (HR=2.3 and Log Rank P-value=.007). Further analysis of AML relapse-associated single cell clusters showed increased levels of individual markers, including CRIP1, FLNA, and RFLNB/FAM101B and their significant association with poor survival in TARGET AML dataset. Additionally, expression of combined RFLNB/FAM101B and WDFY4 genes was associated with poor overall survival (HR=1.8 Log Rank P-value=0.01) and shorter event-free survival (HR=1.9, Log Rank P-value<0.0001). This clearly shows the usefulness of Survival Genie tool in exploring the prognostic association of genes as well as gene sets.Survival Genie is a one-stop web-portal for single-cell phenotype clusters, list of genes, and cell composition-based survival analyses across multiple cancer datasets including hematological malignancies. The analytical options and harmonized collection of multiple cancer types makes Survival Genie a comprehensive resource to correlate gene sets, pathways, cellular enrichment, and single cell clusters to clinical outcome to assist in developing next generation prognostic and therapeutic biomarkers. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Prognostic significance of T-cell-inflamed gene expression profile and PD-L1 expression in patients with esophageal cancer.

PurposeThe ability of the T‐cell–inflamed gene expression profile (GEP) to predict clinical outcome in esophageal cancer (EC) is unknown. This retrospective observational study assessed the prognostic value of GEP and programmed death ligand 1 (PD‐L1) expression in patients with EC treated in routine clinical practice.MethodsTumor samples of 294 patients from three centers in Denmark, South Korea, and the United States, collected between 2005 and 2017, were included. T‐cell–inflamed GEP score was defined as non‐low or low using a cutoff of −1.54. A combined positive score (CPS) ≥10 was defined as PD‐L1 expression positivity. Associations between overall survival (OS) and GEP status and PD‐L1 expression were explored by Cox proportional hazards models adjusting for age, sex, histology, stage, and performance status.ResultsMedian age was 65 years; 63% of patients had adenocarcinoma (AC) and 37% had squamous cell carcinoma (SCC). Thirty‐six percent of tumors were GEP non‐low, with higher prevalence in AC (46%) than SCC (18%). Twenty‐one percent were PD‐L1–positive: 32% in South Korean samples versus 16% in non‐Asian samples and 26% in SCC versus 18% in AC. GEP scores and PD‐L1 CPS were weakly correlated (Spearman’s R = 0.363). OS was not significantly associated with GEP status (non‐low vs low; adjusted hazard ratio, 0.91 [95% CI, 0.69–1.19]) or PD‐L1 expression status.ConclusionNeither GEP nor PD‐L1 expression was a prognostic marker in Asian and non‐Asian patients with EC.

A Novel Gene Signature Associated With Poor Response to Chemoradiotherapy in Patients With Locally Advanced Cervical Cancer

We aimed to investigate the distinct transcriptional landscape in the poor responders to concurrent chemoradiotherapy (CCRT) and to gain mechanistic insights on treatment resistance in cervical cancer.RNA sequencing was performed using archived pre-treatment tissue biopsies of patients with locally advanced cervical cancer treated with concurrent platinum-based CCRT. Transcriptome data of patients with no durable benefit (NDB; progression-free period < 3 years) and durable clinical benefit (DCB; progression-free period > 5 years) after were compared. NDB score was estimated for each patient using the differentially expressed genes between NDB and DCB patients. Three independent cohorts, including The Cancer Genome Atlas cervical cancer (TCGA-CESC) cohort, were utilized for validation of NDB score. Potential response to PD-1 blockade was estimated with Tumor Immune Dysfunction and Exclusion (TIDE) score and T-cell-inflamed gene expression profile (GEP).Patients with NDB exhibited a distinct transcriptional profile compared to those with DCB such as higher signatures of extracellular matrix organization and epithelial-to-mesenchymal transition. The fraction of cancer-associated fibroblasts (CAFs) within the tumor was significantly higher in NDB than DCB patients. Higher NDB score was significantly associated with poor survival in the TCGA-CESC cohort (n = 274; P = 0.015), but only in patients that received curative aim radiotherapy (P = 0.002) and not in patients who received other treatments (P = 0.57). The transcriptomic characteristics of patients with NDB were recapitulated in patients with high NDB score in TCGA-CESC. Patients with high NDB score displayed significantly higher TIDE prediction score and lower T-cell-inflamed GEP score compared to patients with low NDB scores.Cervical cancer patients with poor treatment outcome following CCRT exhibited a distinct gene signature that was able to predict treatment outcomes. For poor responders, immune checkpoint inhibitors may be less effective and CAF-targeting treatments may be a promising approach.K. Kim: None. J. Chang: None. Y. Kim: None.

A Phase II Trial of the Anti -PD-1 Monoclonal Antibody Pembrolizumab (MK-3475) + Lenalidomide + Dexamethasone As Post Autologous Stem Cell Transplant Consolidation in Patients with High-Risk Multiple Myeloma

Introduction: High-risk multiple myeloma (HRMM) patients (pts) will relapse post-autologous stem cell transplant (ASCT) within 1-2 years. Blockade of the PD-1/PD-L1 interaction on activated T-cells may allow the re-establishment of an effective anti-MM immune response. Our hypothesis is that in the post-ASCT setting, where the host immune system is in significant flux, the PD-1/PDL-1 blockade using pembrolizumab (pem), a monoclonal antibody to PD-1, in combination with the immunomodulatory drug (IMiD) lenalidomide (len) and dexamethasone (dex), will prolong post-ASCT remission by eradicating any existing clones and recapturing the smoldering immunophenotype.Methods: The open-label, Phase II, single center trial of pem + len + dex enrolled pts with HRMM 3-6 months post-ASCT. Pts received pem 200 mg IV day 1; len 25 mg po daily days 1-14; and dex 40 mg daily days 1,8,15 of a 21-day cycle for a total of 2 cycles and then an additional 2 cycles of pem + len without corticosteroids at the same dose and frequency. Pts were eligible if they had HRMM defined by ISS stage 3 and/or del 13q by cytogenetics, and/or 1q amplification, 1p deletion (del), p53 del, t(4;14), t(14;16), t(14;20), hypodiploidy by FISH, and/or high-risk gene expression profile score. Exploratory biomarker analysis of the immune phenotype and composition of the intestinal microbiome at pre-treatment, day 1 of each cycle of treatment and end of treatment are currently being done.Results: Fifteen pts were screened, 12 received at least one dose of therapy and thus were deemed evaluable. Baseline characteristics are shown in Table 1. Thirty-three percent were ISS 3, 41.6% received induction bortezomib-len-dex; 33% received induction carfilzomib-len-dex, and the remaining 24.9% received bortezomib-based induction. Overall response rate (ORR) to upfront therapy was 100% with 1 (8.3%) achieving a complete remission (CR), 5 (41.6%) achieving a very good partial remission and 6 (50%) achieving a partial remission to induction. Table 2 shows best response to treatment by cycle. Four pts (33%) have achieved a stringent CR. Of the 4 pts who have completed therapy, 2 were negative for minimal residual disease by multiparametric flow cytometry. Median follow-up is 8.5 months. None of the pts progressed. All patients had AEs of any grade, defined by AEs attributed to pembro/len/dex rather than from ASCT. A total of 90 adverse events (AEs) were reported, with 94% grade 1 or 2 and 5.6% grade 3 (Table 3). The most common hematologic AE was neutropenia (41.7%), with 3 pts (25%) grade 1 and 2, and 2 pts (16.6%) grade 3. The most common non-hematologic AEs were intermittent constipation (16.6%), diarrhea (16.6%), fatigue (8.3%), and increased ALT (8.3%) and were all grade 1 and 2. Non-hematologic grade 3 AEs occurred in 2 pts and included hypoxia and maculopapular rash. There was 1 serious AE, H. influenza pneumonia requiring inpatient admission, and was not thought to be related to pem. After Merck studies using the combination of pem and IMiDS were placed on hold by the FDA, this study was suspended as of 7/5/17.Conclusions: The combination of pem and len with steroids appears to be well tolerated in the post-ASCT setting in pts with high-risk MM. More mature efficacy follow-up and correlative data will be available at the time of presentation. [Display omitted] DisclosuresBiran:Takeda: Speakers Bureau; Celgene, Amgen: Consultancy, Speakers Bureau. Vesole:Celgene: Speakers Bureau; Takeda: Speakers Bureau. Richter:Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Speakers Bureau; BMS: Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Siegel:Celgene, Takeda, Amgen Inc, Novartis and BMS: Consultancy, Speakers Bureau; Merck: Consultancy.

YAP1 transcription factor expression to define subsets of cancers with T-cell inflamed phenotype in a pan-tumor analysis across 33 tumor types.

2610 Background: Immune checkpoint blockade (ICB) has become an established treatment option for the majority of solid tumors. PD-L1 expression, tumor mutation burden (TMB) and mismatch repair (MMR) deficiency are established but suboptimal predictive markers to select patients for ICB therapy. The identification of better predictive biomarkers to complement existing biomarkers is an area of need. We previously identified Yes Associated Protein 1 (YAP1) gene expression as a marker of inflamed tumor phenotype in small cell lung cancer. We sought to elucidate the role of YAP1 as a tumor agnostic biomarker of inflamed tumor phenotype. Methods: We obtained the publicly available TCGA normalized RSEM expression data (version dated September 29, 2019) from the GDC legacy archive (https://portal.gdc.cancer.gov/legacy-archive) for this analysis. We used the shinySISPA method ( https://bbisr.shinyapps.winship.emory.edu/shinySISPA/ ) to classify the primary tumor samples into YAP1 high or low on the basis of the normalized expression profile for YAP1 gene. The T-cell–inflamed gene expression profile score for each sample was calculated as weighted sum of the normalized expression values of the 18 genes ( PSMB10, HLA-DQA1, HLA-DRB1, CMKLR1, HLA-E, NKG7, CD8A, CCL5, CXCL9, CD27, CXCR6, IDO1, STAT1, TIGIT, LAG3, CD274, PDCD1LG2, CD276) as originally published in the Patent filed under “WO201609437” and validated as a predictor of clinical efficacy in patients treated with anti PD1 immunotherapy drug, pembrolizumab. Results: A total of 11283 samples from 33 different histologic tumor types contained in the TCGA database were included in this analysis. A small but meaningful subset of cases 271 (2%) were classified as YAP1 high with a wide range in proportion of YAP1 high tumors of 0.67% to 12.09% across the 33 histologic tumor types. Adrenocortical, cholangiocarcinoma, chromophobe RCC, DLBCL, and mesothelioma had a high rate of YAP1 high tumors (&gt; 10% of cases). Overall trend showed a higher median interferon gamma GEP score in YAP1 high versus YAP1 low tumors with a GEP score of 11.2 vs. 10.7 respectively. A minority of histologic tumor subtypes (HNSCC, clear cell RCC, sarcoma, uterine carcinosarcoma, testicular GCT, melanoma, mesothelioma and ovarian cancer) showed a reverse trend of lower GEP score in association with YAP1 high status. Ongoing validation of these findings in an independent cohort of clinical samples and correlation of YAP1 status with other predictive biomarkers (TMB, PD-L1 and MSS status) will be presented at the meeting. Conclusions: YAP1 is highly expressed in a small but meaningful subsets of cancers and is associated with the inflamed phenotype in the majority of cancers. YAP1 expression is most common in rarer tumor types and in histologic types where currently available biomarkers have not been shown to predict the benefit of ICB.

YAP1 Expression in SCLC Defines a Distinct Subtype With T-cell-Inflamed Phenotype.

The clinical and biological significance of the newly described SCLC subtypes, SCLC-A, SCLC-N, SCLC-Y, and SCLC-P, defined by the dominant expression of transcription factors ASCL1, NeuroD1, YAP1, and POU2F3, respectively, remain to be established. We generated new RNA sequencing expression data from a discovery set of 59 archival tumor samples of neuroendocrine tumors and new protein expression data by immunohistochemistry in 99 SCLC cases. We validated the findings from this discovery set in two independent validation sets consisting of RNA sequencing data generated from 51 SCLC cell lines and 81 primary human SCLC samples. We successfully classified 71.8% of SCLC and 18.5% of carcinoid cases in our discovery set into one of the four SCLC subtypes. Gene set enrichment analysis for differentially expressed genes between the SCLC survival outliers (top and bottom deciles) matched for clinically relevant prognostic factors revealed substantial up-regulation of interferon-γ response genes in long-term survivors. The SCLC-Y subtype was associated with high expression of interferon-γ response genes, highest weighted score on a validated 18-gene T-cell-inflamed gene expression profile score, and high expression of HLA and T-cell receptor genes. YAP1 protein expression was more prevalent and more intensely expressed in limited-stage versus extensive-stage SCLC (30.6% versus 8.5%; p= 0.0058) indicating good prognosis for the SCLC-Y subtype. We replicated the inflamed phenotype of SCLC-Y in the two independent validation data sets from the SCLC cell lines and tumor samples. SCLC subtyping using transcriptional signaling holds clinical relevance with the inflamed phenotype associated with the SCLC-Y subset.