Mark Gardner

Robust detection of immune transcripts in FFPE samples using targeted RNA sequencing

Current criteria for identifying cancer patients suitable for immunotherapy with immune checkpoint blockers (ICBs) are subjective and prone to misinterpretation, as they mainly rely on the visual assessment of CD274 (best known as PD-L1) expression levels by immunohistochemistry (IHC). To address this issue, we developed a RNA sequencing (RNAseq)-based approach that specifically measures the abundance of immune transcripts in formalin-fixed paraffin embedded (FFPE) specimens. Besides exhibiting superior sensitivity as compared to whole transcriptome RNAseq, our assay requires little starting material, implying that it is compatible with RNA degradation normally caused by formalin. Here, we demonstrate that a targeted RNAseq panel reliably profiles mRNA expression levels in FFPE samples from a cohort of ovarian carcinoma patients. The expression profile of immune transcripts as measured by targeted RNAseq in FFPE versus freshly frozen (FF) samples from the same tumor was highly concordant, in spite of the RNA quality issues associated with formalin fixation. Moreover, the results of targeted RNAseq on FFPE specimens exhibited a robust correlation with mRNA expression levels as measured on the same samples by quantitative RT-PCR, as well as with protein abundance as determined by IHC. These findings demonstrate that RNAseq profiling on archival FFPE tissues can be used reliably in studies assessing the efficacy of cancer immunotherapy.

Analytical Validation of a Next-Generation Sequencing Assay to Monitor Immune Responses in Solid Tumors

We have developed a next-generation sequencing assay to quantify biomarkers of the host immune response in formalin-fixed, paraffin-embedded (FFPE) tumor specimens. This assay aims to provide clinicians with a comprehensive characterization of the immunologic tumor microenvironment as a guide for therapeutic decisions on patients with solid tumors. The assay relies on RNA-sequencing (seq) to semiquantitatively measure the levels of 43 transcripts related to anticancer immune responses and 11 transcripts that reflect the relative abundance of tumor-infiltrating lymphocytes, as well as on DNA-seq to estimate mutational burden. The assay has a clinically relevant 5-day turnaround time and can be conducted on as little as 2.5 ng of RNA and 1.8 ng of genomic DNA extracted from three to five standard FFPE sections. The standardized next-generation sequencing workflow produced sequencing reads adequate for clinical testing of matched RNA and DNA from several samples in a single run. Assay performance for gene-specific sensitivity, linearity, dynamic range, and detection threshold was estimated across a wide range of actual and artificial FFPE samples selected or generated to address preanalytical variability linked to specimen features (eg, tumor-infiltrating lymphocyte abundance, percentage of necrosis), and analytical variability linked to assay features (eg, batch size, run, day, operator). Analytical precision studies demonstrated that the assay is highly reproducible and accurate compared with established orthogonal approaches.

Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden

BackgroundImmune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers have not been studied in melanoma.MethodsCutaneous metastatic melanoma patients at eight institutions were evaluated for PD-L1 expression, CD8+ T-cell infiltration pattern, mutational burden, and 394 immune transcript expression. PD-L1 IHC and mutational burden were assessed for association with overall survival (OS) in 94 patients treated prior to ICI approval by the FDA (historical-controls), and in 137 patients treated with ICIs. Unsupervised analysis revealed distinct immune-clusters with separate response rates. This comprehensive immune profiling data were then integrated to generate a continuous Response Score (RS) based upon response criteria (RECIST v.1.1). RS was developed using a single institution training cohort (n = 48) and subsequently tested in a separate eight institution validation cohort (n = 29) to mimic a real-world clinical scenario.ResultsPD-L1 positivity ≥1% correlated with response and OS in ICI-treated patients, but demonstrated limited predictive performance. High mutational burden was associated with response in ICI-treated patients, but not with OS. Comprehensive immune profiling using RS demonstrated higher sensitivity (72.2%) compared to PD-L1 IHC (34.25%) and tumor mutational burden (32.5%), but with similar specificity.ConclusionsIn this study, the response score derived from comprehensive immune profiling in a limited melanoma cohort showed improved predictive performance as compared to PD-L1 IHC and tumor mutational burden.

Abstract 620: Tumor microenvironment heterogeneity is not identified across multiple histologically similar tumors from the same patient

Introduction: Tumor heterogeneity has been well documented for mutational analysis in virtually all types of tumors and is accepted as a true finding. Heterogeneity of the tumor microenvironment (TME) in the context of response to checkpoint inhibitors has not been well studied; the belief is that variation will be identified across multiple tumors from the same patient. The expectation is that multiple tumors from a single patient would demonstrate extensive TME heterogeneity driven by the neoplasm. Methods: We validated and utilized a targeted RNA-seq immune panel of >350 genes to interrogate the TME of 49 different tumors from 17 unique patients. These samples for one patient represented primary and metastatic tumors that were separated by multiple years. Prior to this study we built a reference database of RNA-seq immune results for this panel of 167 samples. An in-depth analysis of genes associated with checkpoint inhibition (CPI) and tumor infiltrating lymphocytes (TILs) were the focus of the comparative analysis. Unsupervised analysis and gene rank by RNA-seq were the primary modes of comparison. Results: For more than one-half of these patients the different tumors for a single patient separated by multiple years more closely resembled the other tumors from that patient than the reference population by unsupervised clustering. When ranked by LOW, MODERATE, or HIGH expression of genes associated with TILs or CPI the results for the majority of patients were highly concordant: LOW TILs / LOW CPI associated gene expression. Conclusion: Our results support a paradigm shift in the influence of the host on TME heterogeneity with evidence that the host and not the neoplastic cells are the primary determining factor. TME heterogeneity is not identified across multiple tumors of the same histology collected from different sites across time points from the same patient. This study does not evaluate multiple primary tumors from the same patient, but is an additional study we have planned. Citation Format: Carl D. Morrison, Jeffrey Conroy, Sean Glenn, Blake Burgher, Sarabjot Pabla, Maochun Qin, Antonios Papanicolau-Sengos, Jon Andreas, Vincent Giamo, Mary Nesline, Shipra Gandhi, Manu Pandey, Nischala Ammannagari, Kunle Odunsi, Marc Ernstoff, Mark Gardner. Tumor microenvironment heterogeneity is not identified across multiple histologically similar tumors from the same patient [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 620. doi:10.1158/1538-7445.AM2017-620

Abstract 1626: Technical variability in NGS immune gene expression and mutation profiling has a nominal effect on tumor classification

Background: A custom NGS cancer immune gene expression assay was developed which measures the transcript level of >350 genes involved in T-cell receptor signaling (TCRS), tumor infiltrating lymphocyte (TILs) complement as well as other key targets expected to predict the likelihood of patient response to checkpoint inhibitors (CPI). In parallel to the gene expression assay, mutational profiling was carried out using the 409 gene Comprehensive Cancer Panel (ThermoFisher). As variability between runs is common when performing NGS assays a detailed comparison of specific technical variations were assessed for their ability to effect gene expression and mutation profiles of clinical FFPE samples. Methods: Studies were designed to characterize the analytical performance of the immune response NGS assay using RNA and DNA from a subset of 300 FFPE tissues representing NSCLC, melanoma, renal cell carcinoma and bladder cancer. As part of the study, we tested the impact of variability in RNA and DNA input quantity at the library preparation step, sample batch size which affects mapped reads/sample and depth of coverage, and linearity of expression and sensitivity of mutation profiling through serial dilutions of pico-molar (pM) input of normalized library. PCA and unsupervised clustering was performed on samples with checkpoint inhibition, TCRS and TILs genes as well as mutational profiling to reveal sample groups with three distinct immune signatures (low, indeterminate and high). Further correlation and over-representation analysis was performed to determine impact of technical characteristics on these three immune signatures. Results: Immune signatures including mutation profiles and gene expression levels were maintained throughout variable RNA/DNA input amounts at the library generation level as well as with diminution of pM levels of library pooled at the sequencing step. Increase in the number of mapped reads and sequencing depth through decreasing the number of batched samples per sequencing run also did not affect the gene expression and mutation profile signatures of the FFPE derived samples. Conclusion: The gene expression and mutation profiles responsible for classifying FFPE samples using NGS are not affected by variation normally introduced in the technical workflow commonly associated with these platforms. The analytical assessment of input at the nucleic acid, library, and sample size level has shown the plasticity available when using amplicon based NGS technologies for classifying the immune gene expression signature as well as mutational profiles of FFPE derived clinical tumor samples. This flexibility increases the strength and utility of NGS-base gene expression profiling and mutational analysis of tumor samples for both basic research and clinical applications. Citation Format: Sean Glenn, Jeffrey Conroy, Blake Burgher, Sarabjot Pabla, Maochun Qin, Jon Andreas, Vincent Giamo, Marc Ernstoff, Mary Nesline, Ji He, Mark Gardner, Carl Morrison. Technical variability in NGS immune gene expression and mutation profiling has a nominal effect on tumor classification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1626. doi:10.1158/1538-7445.AM2017-1626