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.

Validating critical analytical variables of a multiplexed gene expression assay measuring tumor inflammation designed to predict response to anti-PD1 therapy

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Background: The development and analytical performance of the Tumor Inflammation Signature (TIS) assay has been described previously. The TIS is an investigational use RNA expression assay on the nCounter Dx Analysis System, which is being evaluated as a patient enrichment biomarker for treatment with pembrolizumab single agent across multiple solid tumor types. Here we describe the analytical validation of the RNA input range and analytical precision starting from RNA isolated from formalin fixed paraffin embedded (FFPE) tissue blocks. Methods: Analytical validation of TIS assay performance across an RNA input range was performed using samples from 11 tumor types. The analytical precision between sites, instruments, reagent lots, and users was measured, using RNA samples isolated from FFPE tissue blocks. Results: The assay was validated across the specified RNA input range with ≥ 94% concordance at the minimum specified RNA input (50ng). The total standard deviation of the TIS score was < 0.04 units across three sites with ≥98% concordance between sites. The 6 users across the three sites did not significantly contribute to the assay variability. There was 100% concordance in biomarker high/low categorization between multiple reagent lots and multiple instruments. Conclusions: The analytical performance of the NanoString TIS assay has been validated to give consistent results across the RNA input range and between site, instrument, assay user, and reagent kit lot. The assay is well suited for decentralized clinical testing and is currently under investigation as a biomarker to enrich for response to anti-PD1 therapy across multiple tumor types.

Verification of the analytical performance of a molecular diagnostic for response to anti-PD1 therapy on the nCounter Dx Analysis System

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Background: Pembrolizumab is a humanized anti-PD1 antibody that is approved for use in advanced melanoma, recurrent or metastatic head and neck squamous cell carcinoma, and metastatic non-small-cell lung cancer. It has also shown clinical activity in a number of other tumor types in clinical trials, but there is need for a precise and accurate test that can identify patients most likely to benefit from therapy. We have previously described the development and analytical performance of a NanoString RNA expression clinical trial assay, referred to here as the Tumor Inflammation Signature (TIS) assay, which is being evaluated as a patient enrichment biomarker in multiple solid tumor types for treatment with pembrolizumab. Here we describe additional performance data and analytical verification of reproducibility from tissue and RNA input range in multiple tumor types. Methods: Linearity and specificity were assessed with single targets or pools of in vitro transcribed RNAs with sequences matching the 18 biomarker and 10 normalization gene probe targets. The verification of the previously reported analytical precision from RNA and reproducibility from tissue was performed using independent samples from 11 tumor types. The biological variability of the signature within a patient sample was evaluated by testing multiple core punches from formalin fixed paraffin embedded (FFPE) tissue blocks. Results: The TIS assay’s measurement of the 28 genes was linear across a wide dynamic range ( ≥ 4 logs) and was highly specific with < 1% cross reactivity between probes. The assay was verified across the specified RNA input range with > 90% concordance at the low end (50ng) of the RNA input range. The total standard deviation of the anti-PD1 Predictor Score from tissue was verified as < 5% of the signature score range and > 90% concordance in biomarker high/low categorization within the biological replicates. Conclusions: The analytical performance of the NanoString TIS assay was verified to be robust. The assay is well suited for decentralized clinical testing and is currently under investigation to identify responders to anti-PD1 therapy in multiple tumor types in several clinical studies.

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.

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.

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.

Abstract P3-06-03: Association between PAM50 breast cancer intrinsic subtypes and effect of gemcitabine in advanced breast cancer patients

Background: Breast cancer can be subclassified into luminal A and B, basal-like and HER2-enriched subtypes, each with distinct biology, prognosis and response to therapy. Pre-clinical studies have suggested that a basal-like subtype is associated with responsiveness to gemcitabine. Additional data suggest that patients with highly proliferating tumors (non-luminal A) might be particularly responsive to gemcitabine. We examined these hypotheses on SBG0102, a randomized trial comparing gemcitabine plus docetaxel (GD) to single agent docetaxel (D) in patients with advanced breast cancer. Secondarily, we analyzed prognosis by PAM50 subtype, which has not previously been addressed in a metastatic setting.

Patients and Methods: RNA was isolated from archival formalin-fixed, paraffin-embedded primary breast tumor tissue from patients randomly assigned to GD or D, and analyzed with NanoString Technologies' nCounter system and PAM50 intrinsic subtyping algorithm. Using time to progression (TTP) as primary endpoint, overall survival (OS) and response rate (RR) as secondary endpoints, relationships between subtypes and outcome after chemotherapy were analyzed by methods prespecified in writing as a formal prospective-retrospective clinical trial correlative study. Data analysis was performed independently by the DBCG statistical core.

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 significantly associated with TTP (P = .0006) and OS (P = .0083) by Kaplan-Meier analysis. In the adjusted Cox model PAM50 remained independently prognostic. RR was not significantly different by subtype, and PAM50 was not a significant predictor of TTP by treatment arm. PAM50 was however a highly significant predictor of OS following GD compared to D (Pinteraction=.0016). The 43 patients with a basal-like subtype had a significant reduction in OS events (hazard ratio (HR)=0.29; 95% CI 0.15–0.57; Pinteraction=.0006), although TTP events were not significant by interaction test (HR = 0.39; 95% CI 0.19–0.82; Pinteraction=.22). Kaplan-Meier estimates revealed a gain in median OS of 10 months in the doublet arm compared to the monotherapy arm (18.7 (95% CI, 12.4–23.0) v 8.5 (95% CI, 4.2–11.8) months).

Conclusion: A significantly improved and clinical important prolongation of survival was seen from the addition of gemcitabine to docetaxel in advanced basal-like breast cancer patients. However, we could not show a similar significant reduction in TTP events. These results need validation in a second similar trial or a prospective study stratified for basal-like breast cancer to obtain convincing evidence that identification of a basal-like profile may be used to direct the use of gemcitabine in combination with docetaxel.

Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P3-06-03.

Abstract LB-327: Analytical performance of the nCounter analysis system for gene expression cancer signatures

Background:

The nCounter Analysis System is a platform for performing highly multiplexed, digital quantification of hundreds of different nucleic acid species in a single reaction. The system is being developed for use as a platform for in vitro diagnostic applications. The current study aimed to evaluate the analytical performance of the system by implementing a 50-gene signature used for determining the intrinsic subtype and prognostic risk of a breast cancer tumor from formalin-fixed, paraffin-embedded (FFPE) tissue samples. The gene expression profiles can be used to divide breast cancer into four intrinsic subtypes: Basal-like, Luminal A, Luminal B, and HER2 enriched. A normal-like subtype identifies tumor specimens contaminated with a high percentage of normal tissue. A prognostic Risk-Of-Relapse (ROR) score is also calculated.

Methods:

The nCounter assay is performed by direct, multiplexed hybridization of molecular barcodes to target mRNAs. For this study, a CodeSet containing probes for 50 classification genes and 8 normalizing genes was developed. The intrinsic subtyping algorithm was trained by supervised hierarchical clustering of data from 538 samples. Prototypical centroids for tumor subtypes were chosen as statistically significant clusters, while the normal-like centroid was trained from reduction mammoplasty samples. All samples were correlated to the five prototypical centroids and assigned the subtype with the largest positive correlation. The analytical precision of the assay was measured by testing the same sample across replicates. The precision of the subtyping test was determined by assaying 40 different samples across 9 different combinations of reagent lots. The performance of the assay was also evaluated with varying input levels of RNA.

Results:

The precision of the nCounter assay was found to be driven by Poisson noise in the digital measurements at low expression levels. When samples were subtyped across multiple reagent lots, the correlations to each of the five subtypes were narrowly distributed. One sample varied in the categorical subtype call between Luminal B and HER2-enriched across all lots, however, this sample was similarly correlated between both Luminal B and HER2-enriched across all lot combinations. Not surprisingly, the variability for the ROR was minimal, even for the case where the categorical subtype call changed. Finally, the subtype call and ROR score were stable across a 10x range of RNA input.

Conclusions:

The NanoString nCounter system has the sensitivity and precision to be implemented as a distributed platform for multiplexed gene expression profiling of tumors. The sensitivity and direct digital detection without the need for enzymatic amplification make the technology compatible with FFPE tissue samples. The precision should make the technology robust under the many varied conditions seen in testing labs.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-327. doi:10.1158/1538-7445.AM2011-LB-327

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 (RARβ2) gene modulates proliferation and survival of cultured human breast cancer cells. Previously we showed that ectopic expression of RARβ2 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 RARβ2 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

RARβ2 cells exhibit gene profiles with overrepresentation of genes from Xq28 (p = 2 × 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 RARβ2 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 RARβ2 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 RARβ2 signalling include cell adhesion functions (e.g, CD164) nutritional or metabolic processes (e.g., FABP6), and the transcription factor, JUN.

Prognostic indicators and early home rehabilitation in elderly patients with hip fractures

A program for early mobilization in the hospital and rehabilitation at home after hip fracture was developed in cooperation with local health and social authorities and applied to 103 consecutive patients having a mean age of 75 years. All were admitted to the hospital from their own homes. Three fourths of the patients returned home directly after postoperative mobilization periods of usually two to three weeks in hospital. Four months after the fracture 81 of 99 surviving patients were at home, most of them having regained their prefracture functional status. One year after the fracture 91 patients were alive, and 78 of these were at home with no functional loss, compared with their condition at four months. Some of the social and medical factors which may already be pertinent to the recovery outcome at the time of fracture are identified. Eight to nine of ten patients with two or three positive factors ("healthy," living with someone, and ability to walk two weeks postsurgery) returned directly home. This study suggests the importance of intensive support, in the form of information to patients and relatives, and close cooperation between hospital staff and community care authorities. By this means, a continuity of care and early permanent independence can be achieved for elderly hip fracture patients and institutionalized rehabilitation can be reduced with benefit for both the individual and society.