The Tumor Inflammation Signature (TIS) is an investigational use only (IUO) 18-gene signature that measures a pre-existing but suppressed adaptive immune response within tumors. The TIS has been ...shown to enrich for patients who respond to the anti-PD1 agent pembrolizumab. To explore this immune phenotype within and across tumor types, we applied the TIS algorithm to over 9000 tumor gene expression profiles downloaded from The Cancer Genome Atlas (TCGA). As expected based on prior evidence, tumors with known clinical sensitivity to anti-programmed cell death protein 1 (PD-1) blockade had higher average TIS scores. Furthermore, TIS scores were more variable within than between tumor types, and within each tumor type a subset of patients with elevated scores was identifiable although with different prevalence associated with each tumor type, the latter consistent with the observed clinical responsiveness to anti PD-1 blockade. Notably, TIS scores only minimally correlated with mutation load in most tumors and ranking tumors by median TIS score showed differing association to clinical sensitivity to PD-1/PD-1 ligand 1 (PD-L1) blockade than ranking of the same tumors by mutation load. The expression patterns of the TIS algorithm genes were conserved across tumor types yet appeared to be minimally prognostic in most cancers, consistent with the TIS score serving as a pan-cancer measurement of the inflamed tumor phenotype. Characterization of the prevalence and variability of TIS will lead to increased understanding of the immune status of untreated tumors and may lead to improved indication selection for testing immunotherapy agents.
The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and ...chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories.
514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies.
The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online.
The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.
Emerging technologies focused on the detection and quantification of circulating tumor DNA (ctDNA) in blood show extensive potential for managing patient treatment decisions, informing risk of ...recurrence, and predicting response to therapy. Currently available tissue-informed approaches are often limited by the need for additional sequencing of normal tissue or peripheral mononuclear cells to identify non-tumor-derived alterations while tissue-naïve approaches are often limited in sensitivity. Here we present the analytical validation for a novel ctDNA monitoring assay, FoundationOne®Tracker. The assay utilizes somatic alterations from comprehensive genomic profiling (CGP) of tumor tissue. A novel algorithm identifies monitorable alterations with a high probability of being somatic and computationally filters non-tumor-derived alterations such as germline or clonal hematopoiesis variants without the need for sequencing of additional samples. Monitorable alterations identified from tissue CGP are then quantified in blood using a multiplex polymerase chain reaction assay based on the validated SignateraTM assay. The analytical specificity of the plasma workflow is shown to be 99.6% at the sample level. Analytical sensitivity is shown to be >97.3% at ≥5 mean tumor molecules per mL of plasma (MTM/mL) when tested with the most conservative configuration using only two monitorable alterations. The assay also demonstrates high analytical accuracy when compared to liquid biopsy-based CGP as well as high qualitative (measured 100% PPA) and quantitative precision (<11.2% coefficient of variation).
NanoString's Prosigna™ Breast Cancer Prognostic Gene Signature Assay is based on the PAM50 gene expression signature. The test outputs a risk of recurrence (ROR) score, risk category, and intrinsic ...subtype (Luminal A/B, HER2-enriched, Basal-like). The studies described here were designed to validate the analytical performance of the test on the nCounter Analysis System across multiple laboratories.
Analytical precision was measured by testing five breast tumor RNA samples across 3 sites. Reproducibility was measured by testing replicate tissue sections from 43 FFPE breast tumor blocks across 3 sites following independent pathology review at each site. The RNA input range was validated by comparing assay results at the extremes of the specified range to the nominal RNA input level. Interference was evaluated by including non-tumor tissue into the test.
The measured standard deviation (SD) was less than 1 ROR unit within the analytical precision study and the measured total SD was 2.9 ROR units within the reproducibility study. The ROR scores for RNA inputs at the extremes of the range were the same as those at the nominal input level. Assay results were stable in the presence of moderate amounts of surrounding non-tumor tissue (<70% by area).
The analytical performance of NanoString's Prosigna assay has been validated using FFPE breast tumor specimens across multiple clinical testing laboratories.
The retinoic acid receptor beta 2 (RARbeta2) gene modulates proliferation and survival of cultured human breast cancer cells. Previously we showed that ectopic expression of RARbeta2 in a mouse ...xenograft model prevented metastasis, even in the absence of the ligand, all-trans retinoic acid. We investigated both cultured cells and xenograft tumors in order to delineate the gene expression profiles responsible for an antimetastatic phenotype.
RNA from MDA-MB-435 human breast cancer cells transduced with RARbeta2 or empty retroviral vector (LXSN) was analyzed using Agilent Human 1A Oligo microarrays. The one hundred probes with the greatest differential intensity (p < 0.004, jointly) were determined by selecting the top median log ratios from eight-paired microarrays. Validation of differences in expression was done using Northern blot analysis and quantitative RT-PCR (qRT-PCR). We determined expression of selected genes in xenograft tumors.
RARbeta2 cells exhibit gene profiles with overrepresentation of genes from Xq28 (p = 2 x 10(-8)), a cytogenetic region that contains a large portion of the cancer/testis antigen gene family. Other functions or factors impacted by the presence of exogenous RARbeta2 include mediators of the immune response and transcriptional regulatory mechanisms. Thirteen of fifteen (87%) of the genes evaluated in xenograft tumors were consistent with differences we found in the cell cultures (p = 0.007).
Antimetastatic RARbeta2 signalling, direct or indirect, results in an elevation of expression for genes such as tumor-cell antigens (CTAG1 and CTAG2), those involved in innate immune response (e.g., RIG-I/DDX58), and tumor suppressor functions (e.g., TYRP1). Genes whose expression is diminished by RARbeta2 signalling include cell adhesion functions (e.g, CD164) nutritional or metabolic processes (e.g., FABP6), and the transcription factor, JUN.
Introduction: Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin’s lymphoma with two distinct molecular subtypes defined by Cell-of-Origin (COO): germinal center B-cell (GCB) ...and activated B-cell (ABC). COO is being evaluated as a predictive biomarker in multiple DLBCL clinical trials hence the need for an accurate and precise companion diagnostics (CDx). NanoString LST is an investigational multiplexed digital gene expression assay performed on the nCounter® Dx Analysis System that identifies COO from FFPE tissue with a turnaround time of 2-3 days (Wallden B et al, JCO 2015; Storhoff J et al, Blood 2015). The test is based on the Lymph2Cx gene expression assay which profiles 15 classifier genes and 5 housekeeping genes to compute a linear predictor score (LPS) and determine the COO subtype (Scott D et al, Blood 2014). To establish a CDx, both analytical and clinical validations are required using the locked algorithm and assay procedure. Clinical validity of the LST is currently being evaluated in a global Phase 3 study in which the assay is used to prospectively select patients with ABC-type DLBCL to receive in a randomized fashion R2-CHOP or R-CHOP (Nowakowski G et al, JCO 2016). The analytical validation studies described herein were designed to evaluate the analytical performance of the test across multiple laboratory sites, operators, instruments, reagent lots, and RNA input levels.
Design: Reproducibility was measured across 3 sites and 6 operators by testing replicate tissue sections from 43 FFPE DLBCL tumor blocks following independent pathology review at each site. The testing included both core needle and surgical biopsy specimens. The standard deviation (SD) of the LPS output was analyzed as a continuous variable using a linear mixed model to estimate assay variance, and the site-to-site concordance was evaluated. Analytical precision was measured across 3 sites and 6 operators by testing 5 pooled DLBCL tumor RNA samples representing each COO subtype including samples near the subtype thresholds. The sensitivity of the assay was evaluated by testing 4 RNA levels within the recommended input range (62.5 ng, 125 ng, 500 ng, 1000 ng) and 2 input levels outside of this range (50 ng and 1250 ng) using 14 DLBCL tumor RNA samples and 2 reagent lots. The percentage of test samples passing all QC metrics was determined at each input level, and the subtype concordance was evaluated compared to the nominal test input level (500 ng). Interference of human genomic DNA was assessed by omitting DNase from the assay procedure. The impact of including non-tumor tissue was assessed by omitting the tissue macrodissection step from the assay.
Results: In the multi-site reproducibility study, the average site-to-site LST subtype concordance with independent pathology review was >97% with no ABC-to-GCB discordances (or vice versa). The overall range of LPS spanned approximately 5000 units. The total SD was <100 LPS units including all sources of variation (site/pathologist, operator, and between-run/residual). No differences in variance were observed between excisional and core needle biopsies and <1% of the variance was attributed to sites and operators. In the multi-site precision study, the total SD of LPS was 46 including all sources of variation (site, operator, between-runs/day, input level, and within-run/residual). There were no significant differences between sites, operators or days of run. A separate precision study showed that reagent lot and instrument do not significantly contribute to assay variability. In the RNA input study, all input levels inside and outside the specified operating range had 100% assay pass rate. The estimated rate of samples switching from ABC to GCB was <0.00001% for all input levels. In the interference study, genomic DNA contamination resulted in a negative bias in LPS (mean bias = -186), indicating the necessity of DNase treatment in this assay.
Conclusions: The investigational NanoString LST has been analytically validated for identifying COO subtypes across multiple testing laboratories. The test provides a highly precise, sensitive and rapid method for measuring COO on FFPE DLBCL tumor specimens, including both excisional and core needle biopsies.
Chen:NanoString Technologies, Inc.: Employment, Other: Stock option. Dennis:NanoString Technologies, Inc.: Employment, Other: Stock option. Danaher:NanoString Technologies, Inc.: Employment, Other: Stock option. Wallden:NanoString Technologies, Inc.: Employment. Hood:NanoString Technologies, Inc.: Employment, Other: Stock option. Ren:NanoString Technologies, Inc.: Employment, Other: Stock option. Liu:NanoString Technologies, Inc.: Employment, Other: Stock option. Dowidar:NanoString Technologies, Inc.: Employment, Other: Stock option. Sullivan:NanoString Technologies, Inc.: Employment, Other: Stock option. Haffner:NanoString Technologies, Inc.: Employment, Other: Stock option. Cesano:NanoString Technologies, Inc.: Employment, Other: Stock option. Ferree:NanoString Technologies, Inc.: Employment, Other: Stock option, Patents & Royalties: NanoString Technologies, Inc.. Storhoff:NanoString Technologies, Inc.: Employment, Other: Stock option.
Background: Diffuse large B-cell lymphoma (DLBCL) is an aggressive non-Hodgkin's lymphoma with two distinct molecular cell-of-origin (COO) subtypes known as germinal center B-cell (GCB) or activated ...B-cell (ABC). DLBCL subtypes have been reported to be prognostic and potentially predictive of treatment benefit, underscoring the need for a precise and accurate CDx test (Roschewski, Nat Rev Clin Oncol, 2014). NanoString's LST was developed to enable identification of the COO subtypes on the nCounter® Dx Analysis System using formalin fixed paraffin embedded (FFPE) tissue specimens based on the previously developed Lymph2Cx gene expression profiling assay (Scott, Blood 2014). The test assigns the COO subtypes based on a Linear Predictor Score (LPS) that is calculated using a weighted sum of the gene expression. The LST is currently being used as a CDx in a phase III global clinical validation trial (clinicaltrials.gov NCT02285062) to identify newly diagnosed DLBCL patients of the ABC type who may preferentially respond to lenalidomide.
The LST was previously reported to be a highly precise and accurate method of determining DLBCL subtypes (ABC and GCB) when using FFPE excisional/surgical biopsy tissue specimens as a test input (Wallden, JCO 2015). Although excisional biopsies are recommended for DLBCL diagnosis by current ESMO and NCCN guidelines, recent studies have reported excellent sensitivity and specificity in diagnosing malignant lymphomas by core needle biopsy (CNB) leading to increased usage of this method (Hu Q, Am J Clin Pathol, 2013, de Kerviler, Best Pract Res Cl Ha, 2012). The aim of the current study was to assess the analytical performance of the LST when using CNB samples as a test input.
Methods: Recently archived CNB and small biopsy DLBCL samples were procured from Oregon Health & Science University (Portland, OR) (n=23), Hôpital Saint-Louis (Paris, France) (n=19), and Asterand Bioscience (n=12). Both nodal and extra-nodal tissue sites were included. Pathology review was performed on an H&E stained slide from each tissue sample to identify the area of DLBCL. Unstained slide mounted FFPE tissue sections (5 µm) were prepared from each sample for assay processing. The RNA extraction and LST procedures were the same as reported previously for surgical biopsy samples (Wallden, JCO 2015). The number of sections used for each RNA extraction was based on the tumor surface area (TSA) measured on the slide (typically 4-6 slides for TSA<10 mm2; 2-4 slides for TSA≥10 mm2). Multiple extractions were performed and subsequently tested independently for each sample (n=148 total). Additional variables tested in this study were user (n=2), reagent lot (n=2), and instrument (n=2). The reproducibility of the test outputs were evaluated using a linear mixed model (LMM) for LPS variance and concordance for subtype call. Principal component analysis (PCA) was performed on the gene expression profile to determine the major source(s) of variability.
Results: Of the 54 total samples tested, 51 provided test results (failures were due to RNA degradation). With the 51 passing samples, an assay pass rate of 97% (144/148) was achieved. The total tissue area input into the test was correlated to RNA yield (R2 =0.54). The LPS was highly reproducible across sample replicates (Figure 1) with a total assay standard deviation of 59 LPS units (<2% of the LPS range). This estimate was similar to surgical biopsy samples (76 LPS units). The subtype concordance was estimated as 96-98% (between users) where 2 of 51 samples with LPS scores close to the thresholds moved from ABC or GCB to unclassified, or vice versa. A PCA of the gene expression data demonstrated that the first principle component is highly correlated to the LPS providing further evidence that the biology underlying the LST is the major driver of algorithm gene expression in CNB.
Conclusions: In this study we demonstrated robust performance of the LST using FFPE DLBCL CNB/small biopsy samples. Our data support that sufficient RNA yield and gene expression quality can be achieved from biopsy samples with measured TSA of 2 mm2 or greater. We also show that the analytical performance of the LST is comparable between CNB/small biopsy samples and surgical biopsies and that the principal component of gene expression variation is LPS. The LST sample input requirements for the ongoing phase III trial will be updated to include CNB/small biopsy samples to accommodate clinical practice.
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Storhoff:NanoString Technologies, Inc.: Employment, Other: Stock . Wallden:NanoString Technologies, Inc.: Employment, Other: Stock. Braziel:Oregon Health & Sciences University: Employment. Thieblemont:St. Louis Hospital, Paris, France: Employment. Hood:NanoString Technologies, Inc.: Employment, Other: Stock. Ravi:NanoString Technologies, Inc.: Employment, Other: Stock. Dennis:NanoString Technologies, Inc.: Employment, Other: Stock. Dowidar:NanoString Technologies, Inc.: Employment, Other: Stock. Danaher:NanoString Technologies, Inc.: Employment, Other: Stock. Dunlap:Oregon Health & Sciences University: Employment. Briere:St. Louis Hospital, Paris, France: Employment. de Kerviler:St. Louis Hospital, Paris, France: Employment. Ferree:NanoString Technologies, Inc.: Employment, Other: Stock, Patents & Royalties: NanoString Technologies, Inc..
Abstract
Background. In vitro studies suggest basal breast cancers are more sensitive to gemcitabine relative to other intrinsic subtypes. The main objective of this study was to use specimens from a ...randomized clinical trial to evaluate whether the basal-like subtype identifies patients with advanced breast cancer who benefit from gemcitabine plus docetaxel (GD) compared to single agent docetaxel (D).
Material and methods. From patients randomly assigned to GD or D, RNA was isolated from archival formalin-fixed, paraffin-embedded primary breast tumor tissue and used for PAM50 intrinsic subtyping by NanoString nCounter. Statistical analyses were prespecified as a formal prospective-retrospective clinical trial correlative study. Using time to progression (TTP) as primary endpoint, overall survival (OS) and response rate as secondary endpoints, relationships between subtypes and outcome after chemotherapy were analyzed by the Kaplan-Meier method, and Cox proportional hazards regression models. Data analysis was performed independently by the Danish Breast Cancer Cooperative Group (DBCG) statistical core and all statistical tests were two-sided.
Results. RNA from 270 patients was evaluable; 84 patients (31%) were classified as luminal A, 97 (36%) luminal B, 43 (16%) basal-like, and 46 (17%) as HER2-enriched. PAM50 intrinsic subtype was a significant independent prognostic factor for both TTP (p = 0.014) and OS (p = 0.0003). Response rate was not different by subtype, and PAM50 was not a predictor of TTP by treatment arm. PAM50 was however a highly significant predictor of OS following GD compared to D (pinteraction = 0.0016). Patients with a basal-like subtype had a significant reduction in OS events hazard ratio (HR) = 0.29, 95% confidence interval (CI) = 0.15-0.57; pinteraction = 0.0006.
Conclusion. A significantly improved and clinically important prolongation of survival was seen from the addition of gemcitabine to docetaxel in advanced basal-like breast cancer patients.
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