Stratification of Pancreatic Ductal Adenocarcinoma: Combinatorial Genetic, Stromal, and Immunologic Markers.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is associated with an immunosuppressive milieu that supports immune system evasion and disease progression. Here, we interrogated genetic, stromal, and immunologic features of PDAC to delineate impact on prognosis and means to more effectively employ immunotherapy.Experimental Design: A cohort of 109 PDAC cases annotated for overall survival was utilized as a primary discovery cohort. Gene expression analysis defined immunologic subtypes of PDAC that were confirmed in the Cancer Genome Atlas dataset. Stromal and metabolic characteristics of PDAC cases were evaluated by histologic analysis and immunostaining. Enumeration of lymphocytes, as well as staining for CD8, FOXP3, CD68, CD163, PDL1, and CTLA4 characterized immune infiltrate. Neoantigens were determined by analysis of whole-exome sequencing data. Random-forest clustering was employed to define multimarker subtypes, with univariate and multivariate analyses interrogating prognostic significance.Results: PDAC cases exhibited distinct stromal phenotypes that were associated with prognosis, glycolytic and hypoxic biomarkers, and immune infiltrate composition. Immune infiltrate was diverse among PDAC cases and enrichment for M2 macrophages and select immune checkpoints regulators were specifically associated with survival. Composite analysis with neoantigen burden, immunologic, and stromal features defined novel subtypes of PDAC that could have bearing on sensitivity to immunologic therapy approaches. In addition, a subtype with low levels of neoantigens and minimal lymphocyte infiltrate was associated with improved overall survival.Conclusions: The mutational burden of PDAC is associated with distinct immunosuppressive mechanisms that are conditioned by the tumor stromal environment. The defined subtypes have significance for utilizing immunotherapy in the treatment of PDAC. Clin Cancer Res; 23(15); 4429-40. ©2017 AACR.

An Expression Signature as an Aid to the Histologic Classification of Non-Small Cell Lung Cancer.

PURPOSE: Most non-small cell lung cancers (NSCLC) are now diagnosed from small specimens, and classification using standard pathology methods can be difficult. This is of clinical relevance as many therapy regimens and clinical trials are histology dependent. The purpose of this study was to develop an mRNA expression signature as an adjunct test for routine histopathologic classification of NSCLCs. EXPERIMENTAL DESIGN: A microarray dataset of resected adenocarcinomas (ADC) and squamous cell carcinomas (SCC) was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used for validation. Another microarray dataset of ADCs and matched nonmalignant lung was used as the learning set for a tumor versus nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach. RESULTS: We developed a 62-gene expression signature that contained many genes used in immunostains for NSCLC typing. It includes 42 genes that distinguish ADC from SCC and 20 genes differentiating nonmalignant lung from lung cancer. Testing of the TCGA and other public datasets resulted in high prediction accuracies (93%-95%). In addition, a prediction score was derived that correlates both with histologic grading and prognosis. We developed a practical version of the Classifier using the HTG EdgeSeq nuclease protection-based technology in combination with next-generation sequencing that can be applied to formalin-fixed paraffin-embedded (FFPE) tissues and small biopsies. CONCLUSIONS: Our RNA classifier provides an objective, quantitative method to aid in the pathologic diagnosis of lung cancer. Clin Cancer Res; 22(19); 4880-9. ©2016 AACR.

Quantitative nuclease protection assay in paraffin-embedded tissue replicates prognostic microarray gene expression in diffuse large-B-cell lymphoma.

Gene expression profiling (GEP) has identified genes whose expression levels predict patient survival in diffuse large-B-cell lymphoma (DLBCL). Such discovery techniques generally require frozen samples unavailable for most patients. We developed a quantitative nuclease protection assay to measure expression levels of prognostic DLBCL genes using formalin-fixed, paraffin-embedded (FFPE) tissue. FFPE tissue was sectioned, permeabilized, denatured in the presence of specific probes, and hybridized to mRNA in situ. Nuclease subsequently destroyed non-hybridized probe. Alkaline hydrolysis freed mRNA-bound probes from tissue, which were transferred to ArrayPlates for probe capture and chemiluminescent quantification. We validated assay performance using frozen, fresh, and FFPE DLBCL samples, then used 39 archived DLBCL, previously microarray analyzed, to correlate GEP and ArrayPlate results. We compared old (>18 years) with new (<2 months) paraffin blocks made from previously frozen tissue from the original biopsy. ArrayPlate gene expression results were confirmed with immunohistochemistry for BCL2, BCL6, and HLA-DR, showing agreement between mRNA species and the proteins they encode. Assay performance was linear to approximately 1 mg sample/well. RNase and DNase treatments demonstrated assay specificity for RNA detection, both fixed and soluble RNA detection. Comparisons were excellent for lysate vs snap-frozen vs FFPE (R(2)>0.98 for all comparisons). Coefficients of variation for quadruplicates on FFPE were generally <20%. Correlation between new and old paraffin blocks from the same biopsy was good (R(2)=0.71). Comparison of ArrayPlate to Affymetrix and cDNA microarrays showed reasonable correlations. Insufficient power from small sample size prevented successfully correlating results with patient survival, although hazard ratios trended the expected directions. We developed an assay to quantify expression levels of survival prediction genes in DLBCL using FFPE, fresh, or frozen tissue. While this technique cannot replace GEP for discovery, it indicates that expression differences identified by GEP can be replicated on a platform applicable to archived FFPE samples.

Multiplexed screening assay for mRNA combining nuclease protection with luminescent array detection.

The principles and performance are described for the ArrayPlate mRNA assay, a multiplexed mRNA assay for high-throughput and high-content screening and drug development. THP-1 monocytes grown and subjected to compound treatments in 96-well plates were subjected to a multiplexed nuclease protection assay in situ. The nuclease protection assay destroyed all cell-derived mRNA, but left intact stoichiometric amounts of 16 target-specific oligonucleotide probes. Upon transfer of processed cell lysates to a microplate that contained a 16-element oligonucleotide array at the bottom of each well, the various probe species were separated by immobilization at predefined elements of the array. Quantitative detection of array-bound probes was by enzyme-mediated chemiluminescence. A high-resolution charge-coupled device imager was used for the simultaneous readout of all 1536 array elements in a 96-well plate. For the measurement of 16 genes in samples of 25000 cells, the average standard deviation from well to well within a plate was 8.6% of signal intensity and was 10.8% from plate to plate. Assay response was linear and reproducibility was constant for all detected genes in samples ranging from 1000 to 50000 cells. When THP-1 monocytes were differentiated with phorbol ester and subsequently activated with bacterial lipopolysaccharide that contained different concentrations of dexamethasone, dose-dependent effects of dexamethasone on the mRNA levels of several genes were observed.