Analytical validation of a novel comprehensive genomic profiling informed circulating tumor DNA monitoring assay for solid tumors.

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).

Development of Gene Expression-Based Biomarkers on the nCounter® Platform for Immuno-Oncology Applications.

Biomarkers based on transcriptional profiling can be useful in the measurement of complex and/or dynamic physiological states where other profiling strategies such as genomic or proteomic characterization are not able to adequately measure the biology. One particular advantage of transcriptional biomarkers is the ease with which they can be measured in the clinical setting using robust platforms such as the NanoString nCounter system. The nCounter platform enables digital quantitation of multiplexed RNA from small amounts of blood, formalin-fixed, paraffin-embedded tumors, or other such biological samples that are readily available from patients, and the chapter uses it as the primary example for diagnostic assay development. However, development of diagnostic assays based on RNA biomarkers on any platform requires careful consideration of all aspects of the final clinical assay a priori, as well as design and execution of the development program in a way that will maximize likelihood of future success. This chapter introduces transcriptional biomarkers and provides an overview of the design and development process that will lead to a locked diagnostic assay that is ready for validation of clinical utility.

Pan-cancer adaptive immune resistance as defined by the Tumor Inflammation Signature (TIS): results from The Cancer Genome Atlas (TCGA).

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.

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: The analytical performance of NanoString's Prosigna assay has been validated using FFPE breast tumor specimens across multiple clinical testing laboratories.

PAM50 breast cancer intrinsic subtypes and effect of gemcitabine in advanced breast cancer patients.

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.

Werner syndrome gene variants in human sarcomas.

Werner syndrome is an autosomal inherited disease that is characterized by premature aging. The gene mutated in Werner syndrome (WS), WRN, encodes both a 3' --> 5' DNA helicase and a 3' --> 5' DNA exonuclease. Among the WS phenotypes is an exceptionally high incidence of sarcomas. We asked whether spontaneous sarcomas, not known to be associated with WS, also harbor mutations or unreported single nucleotide polymorphisms (SNPs) in WRN. We analyzed RNA or DNA sequences within the helicase and exonuclease domains from 51 and 69 matched sarcoma and adjacent normal tissues, respectively. Among a total of 13 nucleotide variants detected, we identified three novel nonsynonymous substitutions: c.611C>T, c.809_810insT, and c.1882C>G. We further characterized one, c.611C>T, which results in substitution of an evolutionarily conserved proline at amino acid 204 in the exonuclease domain with leucine. We show that P204L WRN exhibits a reduction of WRN exonuclease activity; the specific activity is approximately 10-fold lower than that of wild-type WRN. In contrast, the helicase activity of P204L WRN is reduced less than twofold.

Truncated RAR beta isoform enhances proliferation and retinoid resistance.

We previously reported the existence of a truncated isoform of the retinoic acid receptor beta, termed beta prime. Beta prime lacks the N-terminal domains of beta 2 and beta 4, including the DNA-binding domain. However, beta prime is able to heterodimerize and interact with transcription cofactors. To determine the effects of different retinoic acid receptor isoforms on cell proliferation and apoptosis, we transduced retinoid sensitive (MCF7) and retinoid-resistant (MDA-MB-231) cells with retinoic acid receptor beta 2, beta 4, or beta prime. Expression of the truncated beta prime isoform induces resistance to retinoic acid treatment in retinoid sensitive MCF7 cells. In both retinoid sensitive and resistant cells, expression of full-length beta 2 and beta 4 isoforms results in elevated sensitivity to retinoic acid treatment and caspase-independent cell death. Cell death in beta 4 transduced MDA-MB-231 cells was accompanied by metaphase chromosome decondensation and breakage suggestive of mitotic catastrophe. Our results provide evidence that: (a) the truncated form of the retinoic acid receptor beta induces retinoid resistance rather than sensitivity; and (b) alternative pathways of cell death are mediated by different isoforms in breast cancer cells.

Antimetastatic gene expression profiles mediated by retinoic acid receptor beta 2 in MDA-MB-435 breast cancer cells.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSION: 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.