Research Use Only Research Articles

Autoantibody Discovery, Assay Development and Adoption: Death Valley, the Sea of Survival and Beyond.

Dating to the discovery of the Lupus Erythematosus (LE) cell in 1948, there has been a dramatic growth in the discovery of unique autoantibodies and their cognate targets, all of which has led to the availability and use of autoantibody testing for a broad spectrum of autoimmune diseases. Most studies of the sensitivity, specificity, commutability, and harmonization of autoantibody testing have focused on widely available, commercially developed and agency-certified autoantibody kits. However, this is only a small part of the spectrum of autoantibody tests that are provided through laboratories world-wide. This manuscript will review the wider spectrum of testing by exploring the innovation pathway that begins with autoantibody discovery followed by assessment of clinical relevance, accuracy, validation, and then consideration of regulatory requirements as an approved diagnostic test. Some tests are offered as “Research Use Only (RUO)”, some as “Laboratory Developed Tests (LDT)”, some enter Health Technology Assessment (HTA) pathways, while others are relegated to a “death valley” of autoantibody discovery and become “orphan” autoantibodies. Those that achieve regulatory approval are further threatened by the business world’s “Darwinian Sea of Survival”. As one example of the trappings of autoantibody progression or failure, it is reported that more than 200 different autoantibodies have been described in systemic lupus erythematosus (SLE), a small handful (~10%) of these have achieved regulatory approval and are widely available as commercial diagnostic kits, while a few others may be available as RUO or LDT assays. However, the vast majority (90%) are orphaned and languish in an autoantibody ‘death valley’. This review proposes that it is important to keep an inventory of these “orphan autoantibodies” in ‘death valley’ because, with the increasing availability of multi-analyte arrays and artificial intelligence (MAAI), some can be rescued to achieve a useful role in clinical diagnostic especially in light of patient stratification and precision medicine.

Minipool testing for SARS-CoV-2 RNA in United States blood donors.

SARS-CoV-2 RNA prevalence in blood donors from large geographic areas of high community transmission is limited. We tested residual donor plasma minipools (MPs) to determine SARS-CoV-2 RNAemia prevalence in six United States areas. Blood donations collected from 7 March 2020 to 25 September 2020 were tested for SARS-CoV-2 RNA (vRNA) in MP of 6 or 16 donations using the Grifols Procleix SARS-CoV-2 research-use only (RUO) transcription-mediated amplification (TMA) assay. Reactive results were confirmed using an alternate target region TMA assay. Reactive MPs were tested by TMA after serial dilution to estimate viral load. Testing for anti-SARS-CoV-2 antibodies and infectivity was performed. A total of 17,995 MPs corresponding to approximately 258,000 donations were tested for vRNA. Three confirmed reactive MP16 were identified. The estimated prevalence of vRNA reactive donations was 1.16/100,000 (95% CI 0.40, 3.42). The vRNA-reactive samples were non-reactive for antibody, and the estimated viral loads of the (presumed single) positive donations within each MP ranged from <1000 to <4000 copies/ml. When tested, no infectivity was observed in inoculated permissive cell cultures. Blood donation MP-nucleic acid testing (NAT) indicated that SARS-CoV-2 RNAemia is infrequent and, when detected, the vRNA was at low concentrations. Only one RNA-reactive MP could be tested for infectivity for operational reasons and was not infectious in cell culture. These findings support current recommendations from international and national regulatory agencies to not screen donors by NAT.

Gene expression profiling signatures for immunophenotyping of tumor microenvironment using HTG EdgeSeq Precision Immuno-Oncology Panel.

e14528 Background: Immunotherapy has revolutionized cancer treatment by harnessing the power of the patient’s immune system to fight the disease. While immunotherapies have become increasingly effective, the proportion of patients not responding to immunotherapy ranges between only 20-50%. New breakthroughs in the understanding of the tumor immune biology have led to the development of new, more effective therapies; however, these breakthroughs often hinge on tools that can elucidate the role and abundance of individual components of the patient’s immune system in the tumor microenvironment. Methods: This poster describes the performance of 26 gene enrichment signatures that allow for the measurement of the relative abundance of 23 individual immune and stromal cells in the tumor environment, in addition to providing composite inflammation, stroma and tumor microenvironment scores. These Research Use Only (RUO) signatures are based on gene expression profiling (GEP) data for 1,392 genes implicated in tumor-immune interaction generated using the HTG EdgeSeq Precision Immuno-Oncology Panel (RUO). The signatures were developed and validated using GEP data from 1,073 colorectal, gastric and ovarian cancer formalin-fixed paraffin-embedded (FFPE) tissue specimens. Results: The signature accuracy was independently verified by spiking known numbers of representative immune and stromal cells into an FFPE tissue lysate; the signature outputs were highly correlated to the number of immune and stromal cells present in the sample, with Pearson correlation coefficients ranging from 0.71 to 0.98. In addition, the outputs of some of the signatures were compared to multiple commonly used immunohistochemistry markers of immune cells in 61 non-small-cell lung carcinoma FFPE samples. The results showed a high degree of correlation, with Pearson correlation coefficients of 0.77 and 0.81 for CD4 and CD8, respectively. Conclusions: These immunophenotyping signatures provide a suite of robust tools for the characterization of the tumor microenvironment in order to better understand the tumor immune biology and mechanisms of resistance to immunotherapy. The signature scores can typically be generated from a single section of FFPE tissue using HTG’s extraction-free GEP technology and a fully automated bioinformatic pipeline available in the HTG EdgeSeq Reveal software.

10 STARTUPS TO WATCH 2021: Early-stage companies advance precision medicine by applying AI, clinical genomics, and other new technologies

10 STARTUPS TO WATCH 2021: Early-stage companies advance precision medicine by applying AI, clinical genomics, and other new technologies

Abstract PS2-03: Comparison of pathologist reads of sp142 and sp263 with quantitative measurement of protein and mRNA in triple negative breast cancer

Abstract Background: PD-L1 SP142 immunohistochemistry (IHC) assay has been approved as a companion test by the US Food and Drug Administration (FDA) to identify eligibility for atezolizumab therapy in patients with advanced triple negative breast cancer (TNBC) but a number of studies suggest the assay suffers from poor reproducibility. Using readings of 70 TNBC chromogenic FDA approved assays from 19 pathologists in a previous study as a baseline, we compared pathologist reads to quantitatively measured mRNA and protein expression Methods: Formalin-fixed paraffin-embedded (FFPE) slides representing primary invasive triple negative breast cancer (stage I-III) from 100 patients between 2012-16 were selected from the Yale Pathology archives. Slides were macrodissected to tumor enrichment for quantitative assessment of CD274 (PD-L1 mRNA) measured using a closed-system, real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) research use only (RUO)* prototype assay on the GeneXpert® instrument. We also measured protein expression levels using the AQUA method of quantitative immunofluorescence (QIF) in both the tumor and non-tumor compartments on full sections by QIF stained using SP142 in a lab derived test (LDT). The IHC stained slides were prepared using SP142 and SP263 assays prepared exactly according the FDA approved label followed by reading by 19 pathologists. This study was approved by Yale Human Investigation IRB protocol ID 9505008219.Results: Previous work from our group showed overall percent agreement for both the SP142 and SP263 IHC assays read by pathologists was in the 40-50% range. We used the median CD274 score to compare positive (IC≥1) vs negative (IC&amp;lt;1) and found that the levels of mRNA were not statistically significantly different between the two categorical scores. However, quantitative measurement of protein expression (including both tumor and non-tumor regions) showed statistically significant differences between pathologist read PD-L1 positive/negative scoring for SP142 (p=0.0004) and SP263 (p=0.0185). Concordance of quantitative PD-L1 measurement between protein QIF scores and transcript RT-qPCR levels was modest, with a Spearman coefficient r = 0.18. Conclusions: By chromogenic IHC, using the FDA approved assays, pathologist read scoring shows no difference to mRNA for CD274. Quantitative continuous scoring of protein expression show that, on average, when pathologists score IC≥1, there is more protein present than when they score IC&amp;lt;1. Further studies are needed to determine if RNA and protein for PD-L1 are concordant and to determine which assay(s) and cutoff values are best correlated with clinical outcomes on atezolizumab therapy. *For Research Use Only - Not for use in diagnostic procedures. Not approved or reviewed by any regulatory body Citation Format: Swati Gupta, Vesal Yaghoobi, Aileen Fernandez, Leena McCann, Jodi Weidler, Michael Bates, Emily Reisenbichler, David Rimm. Comparison of pathologist reads of sp142 and sp263 with quantitative measurement of protein and mRNA in triple negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-03.

Development and validation for research assessment of Oncotype DX\xae Breast Recurrence Score, EndoPredict\xae and Prosigna\xae

Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2− breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (rc(RS) = 0.96, 95% CI 0.93–0.97 with level of agreement (LoA) of −7.69 to 8.12; rc(EP) = 0.97, 95% CI 0.96–0.98 with LoA of −0.64 to 1.26 and rc(ROR) = 0.97 (95% CI 0.94–0.98) with LoA of −8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data.

Abstract 6499: Small slide, big world: Fast detection of altered proteins and RNA levels in clinical samples using Nanostring nCounter® GeoMxTM Digital Spatial Profiler

Abstract Although many new drugs have been approved and more clinical trials are being conducted for various disease therapies in recent decades, efficient identification of reliable therapeutic targets is still a big challenge during drug development. Therefore, tremendous efforts have been put into advancing the technology to quickly determine the altered biomarkers in clinical samples. Nanostring nCounter GeoMxTM Digital Spatial Profiling (GeoMx DSP) has been used in multiple projects and exhibited its outstanding performance on collecting analyzable digital counts for up-to 96 proteins and 20,000 RNAs in a specific area on a single FFPE slide. Tissue regions of interests are identified by fluorescent staining of morphology markers, and either proteins or RNAs in the specific defined regions are collected as the digital nCounter count format. By using this state-of-art technology, spatial distributions of immune- and cancer- relevant proteins were identified in 71 tumor cell rich-, 70 immune cell rich-, and 69 stromal cell rich- area respectively in three Pancreatic cancer patient groups including surgery alone, neoadjuvant FOLFIRINOX (a combination of fluorouracil, folinic acid, irinotecan and oxaliplatin) alone or combined with stereotactic body radiation therapy (F+SBRT). Our results showed that differential regulations among immune checkpoint markers, pan-immune markers and tumor markers in these treatment groups. In tumor-rich regions, CD44 is present at higher levels in FOLFIRINOX treated patients than surgery-alone group. VISTA was significantly down-regulated in F+SBRT group. Also, several key factors from pStat3, PTEN and Bcl2 pathways are also regulated by treatment methods. In immune-rich regions, both T cells markers (CD3 and CD4) and B cell markers (CD19 and CD20) were regulated differently by treatment methods. GeoMx DSP platform provides a novel and more precise view of the spatial regulation of micro-world in the tissue, which enable us to explore more about internal regulation within sub-population of the tissue cells. GeoMxTM DSP platform is only for RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Jingjing Gong, Matthew R. Farren, Walid Shaib, Gregory Lesinski, Sarah Warren, Yan Liang. Small slide, big world: Fast detection of altered proteins and RNA levels in clinical samples using Nanostring nCounter® GeoMxTM Digital Spatial Profiler [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6499.

Abstract 1688: High-throughput immune cell phenotyping using GeoMx DSP reveals Non-Small Cell Lung Cancers (NSCLC) are divided into distinct immunological subtypes

Abstract GeoMx DSP reveals NSCLCs are divided into distinct immunological subtypes, and local immune signatures of tumor sub-regions differentially affect neighboring tumor biology. Although cancer immunotherapy is considered an effective cancer-treatment option, means to measure its effect on sub-tumor regions are on demands. Despite its popularity, scRNA-seq only reveals cell populations found within a tissue but is mute on roles in tumor microenvironment (TME) like the impact of one cell type on another's behavior. To gain insights inaccessible to single-cell methods, we demonstrate a harmonized analysis of scRNA-seq and NanoString GeoMx™ data in lung tumors. This approach reveals the spatial distribution of cell populations defined via scRNA-seq, enabling rich descriptions of cells' responses to each other and to their locations within the tumor. GeoMx Digital Spatial Profiler (GeoMx DSP) is based on barcoding technology that enables spatially resolved, digital characterization of proteins or mRNA in a highly multiplexed (over 1,500-plex) assay. The oligonucleotide tags cleaved from discrete regions are quantitated by NGS, and counts are mapped back to tissue location, yielding a spatially-resolved digital profile of analyte abundance. To measure immune infiltrates in tumors, we employed machine learning techniques to classify gene sets of immune cell phenotypes and built an immune cell phenotyping panel for GeoMx DSP. Gene expression data from subregions of a tumor tissue were analyzed through this immune cell phenotyping pipeline to quantify immune infiltrates. We applied scRNA-seq to predefine the cell populations present in NSCLC tumors, and we applied the GeoMx platform to measure these populations across dozens of FFPE tumor sections. We found that there were three immunological subtypes; cold, myeloid enriched and lymphoid enriched groups. This finding was validated using traditional methods, such as FACS or immunohistochemistry analysis. In addition, we also profiled immune infiltrates of sub-tumor regions within a tumor tissue and found that spatial profiling of subregions and their neighboring environment (TME) enabled us to measure how TME differentially affects tumor biology. These measurements enable us to describe the distribution of immune populations across spatial variables like tumor interior vs. margin, to catalog the degree to which immune populations traffic together within the tumor, and to correlate gene expression in tumor cells with neighboring immune populations. These analyses demonstrate the ability of spatial RNA profiling to reach conclusions inaccessible to single-cell data alone. “FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.” Citation Format: Youngmi Kim, Patrick Danaher, Brenn Nelson, Maddy Griswold, Margaret Hoang, McGarry A. Houghton, Joseph M. Beechem. High-throughput immune cell phenotyping using GeoMx DSP reveals Non-Small Cell Lung Cancers (NSCLC) are divided into distinct immunological subtypes [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1688.

Abstract 5237: High-throughput slide preparation for spatially-resolved, multiplexed quantification of protein or mRNA in tumor tissues with automation of GeoMx™ DSP Assays on Leica Biosystems BOND RX

Abstract Characterization of the spatial distribution and abundance of proteins and mRNAs with morphological context within tissues enables a better understanding of biological systems in many research areas, including immunology and oncology. The GeoMxTM Digital Spatial Profiler (DSP) enables the highly-multiplexed detection of mRNA or protein targets within distinct regions of tissues, including FFPE. This assay utilizes in situ hybridization (ISH) probes or antibodies linked to indexing oligo barcodes via a photo-cleavable linker. The GeoMx DSP enables profiling of RNA or protein targets by releasing and collecting these barcodes from user-defined regions-of-interest. Manual preparation of FFPE tissue uses conventional immuno-fluorescence (IF) and ISH reagents, however it requires greater than two hours of hands-on-time over 2 days. Protocols have been developed to enable the automation of these tissue preparation protocols using the Leica Biosystems BOND RX and BOND RXm Fully Automated Research Stainers. Here we describe protocols for the semi-automated preparation of GeoMx RNA and protein assays as well as the fully-automated preparation of GeoMx RNA assays. These protocols reduce the hands-on time of performing the assay to 72 minutes and 35 minutes for the semi- and fully-automated protocols, respectively. Signal-to-noise ratios (SNR) are highly concordant between serial sections processed manually and processed on the Leica BOND RXm using the GeoMx Immune Cell Profiling Panel for protein (58-plex) and GeoMx Immune Pathways Panel for RNA (84-plex). Furthermore, automated assays show high concordance between the BOND RX and BOND RXm instruments. Lastly, we demonstrate the use of the fully automated slide preparation protocol with the GeoMx Cancer Transcriptome Atlas, a panel that targets &amp;gt;1,600 key cancer mRNAs that are read out by next-generation sequencing. GeoMx Assays are for RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Daniel R. Zollinger, Sarah Ketting, Kristina Sorg, Oliver Appelbe, Danielle Aaker, Damian Cockfield, Chris Merritt, Joseph M. Beechem. High-throughput slide preparation for spatially-resolved, multiplexed quantification of protein or mRNA in tumor tissues with automation of GeoMx™ DSP Assays on Leica Biosystems BOND RX [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5237.

Abstract 735: Sensitive detection of ctDNA in early stage non-small cell lung cancer patients with a personalized sequencing assay

Abstract Introduction Identification of minimal residual disease (MRD) following curative intervention of localized non-small cell lung cancer (NSCLC) holds promise for identifying patients who are at higher risk of relapse and who would benefit from adjuvant treatment. Current routine clinical practice involves serial radiographic imaging following surgery to detect macroscopic disease. Liquid biopsy can identify patients who have MRD without macroscopic disease. Currently available assays have only identified circulating tumor DNA (ctDNA) in a limited number of cases with early stage NSCLC. More sensitive methods are needed to accurately identify the majority of patients who will relapse. Here we evaluate the performance of InVision®MRD, a personalized sequencing assay for plasma cell-free DNA, for detection of ctDNA in patients with early-stage NSCLC undergoing treatment with curative intent. Methods InVision®MRD is a highly sensitive in vitro diagnostic assay, currently available for research use only (RUO), that can detect the presence of tumor DNA traces in cell-free DNA from plasma samples of cancer patients. InVision®MRD identifies tumor-specific variants from exome sequencing of tumor tissue and tracks them in plasma specimens by multiplex PCR and high-depth next-generation sequencing. We evaluated the detection of ctDNA in plasma samples collected from the LUng cancer - CIrculating tumor DNA (LUCID) study, which collected plasma samples from 100 patients with NSCLC stages I-III who underwent radical treatment with curative intent, either surgery or radiotherapy ± chemotherapy. Of patients in the LUCID study, 60% had stage I NSCLC and 40% patients had stage II/III disease, according to TNM 7th edition. Results To evaluate the InVision®MRD assay, a subset of samples from the LUCID study were analyzed. Samples were collected before and after surgery and chemo-radiotherapy from patients with early-stage NSCLC. Using multiplexed analysis of 48 patient-specific variants and high-depth sequencing, ctDNA was detected in 50% of pre-treatment samples analyzed from the first set of 18 patients, at ctDNA fractions ranging from 20 ppm (equivalent to 0.002%) to 19576 ppm (equivalent to 1.958%). Conclusions These findings highlight an opportunity to improve ctDNA detection for early stage NSCLC using a patient-specific plasma sequencing assay. Initial detection rates have reached 50% for patients with early-stage disease prior to treatment, including detection of ctDNA to levels as low as a few parts per million. Together with further data to be presented, this suggests a possible route to improving treatment for early stage NSCLC by detection of residual disease post treatment and for monitoring for early detection of relapse. Citation Format: Katrin Heider, Davina Gale, Andrea Ruiz-Valdepenas, Giovanni Marsico, Garima Sharma, Malcolm Perry, Robert Osborne, Karen Howarth, Tadd Lazarus, Viona Rundell, Jelena Belic, Jerome Wulff, Susan Harden, Doris M. Rassl, Robert C. Rintoul, Nitzan Rosenfeld. Sensitive detection of ctDNA in early stage non-small cell lung cancer patients with a personalized sequencing assay [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 735.

Abstract 3097: Analytical development of the RaDaRTM assay, a highly sensitive and specific assay for the monitoring of minimal residual disease

Abstract Background 5%-30% of patients with primary non-metastatic cancer eventually relapse and die of metastatic disease, even though no macroscopic disease remains after initial curative-intent treatment. Adjuvant therapy is often administered to target minimal residual disease (MRD) that may be present but does not change outcome for most patients. Detecting MRD by liquid biopsy analysis after initial treatment and in advance of overt relapse could help identify patients who may benefit from adjuvant therapy or enrolment in clinical trials. Methods We developed InVision®MRD, a highly sensitive and specific method for detection of trace levels of tumor DNA in plasma cell-free DNA. Tumor-specific variants are identified using whole exome sequencing of tumor tissue samples, and a bespoke process designs primer panels targeting mutated loci. A multiplex high-fidelity PCR using InVision® technology captures and amplifies up to 48 patient–specific tumor variants in cell-free DNA, followed by high depth next generation sequencing. Proprietary algorithms compare patient-specific sequencing data to controls,and integrate information across variants and replicates to detect trace levels of tumor-derived signal. The method is currently available for research use only (RUO). Results We evaluated the performance of the InVision®MRD assay using samples from cancer patients and cell-line dilutions. We diluted three different tumor cell-lines into their matched normal counterparts. Primer panels were designed against 48 variants, specific to the tumor-cell line. Dilutions were amplified by multiplex PCR and sequenced on the Illumina NovaSeq to depth &amp;gt;100,000 reads per locus. Using 48 variants, the InVision®MRD assay had a mean sensitivity of 100% at 20 parts per million (20 ppm, equivalent to 0.002%) and sensitivity of 70% at 10 ppm (0.001%) with an overall specificity of 100%. To evaluate the effect of the number of variants on sensitivity and specificity we performed bootstrapping experiments selecting subsets of variants. When using only 16 variants, the I InVision®MRD assay had a mean sensitivity of 95% at 40 ppm (0.004%), 64% at 20 ppm (0.002%) and 22% at 10 ppm (0.001%) with specificity 99.99%. We tested the InVision®MRD assay on samples from cancer patients and detected tumor DNA in patient plasma and diluted samples with estimated tumor fractions at and below 20 ppm (0.002%). Conclusions The InVision®MRD assay provides a highly sensitive and specific method to detect MRD in plasma samples of cancer patients. Our results demonstrate excellent sensitivity with analysis of 16 variants which is further enhanced when 48 variants are analyzed. The high sensitivity of our approach is key to providing early information to guide treatment decisions after initial treatment by surgery or chemo/radiotherapy. The approach is generalisable to multiple tumor types and specimen types. Citation Format: Giovanni Marsico, Garima Sharma, Malcolm Perry, Sophie Hackinger, Tim Forshew, Karen Howarth, Jamie Platt, Nitzan Rosenfeld, Robert Osborne. Analytical development of the RaDaRTM assay, a highly sensitive and specific assay for the monitoring of minimal residual disease [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3097.

The new IVD Regulation 2017/746: a case study at a large university hospital laboratory in Belgium demonstrates the need for clarification on the degrees of freedom laboratories have to use lab-developed tests to improve patient care.

The new European InVitro Diagnostic (IVD) Regulation 2017/746 (IVDR) restricts the use of lab-developed tests (LDT) after 26th May 2022. There are no data on the impact of the IVDR on laboratories in the European Union. Laboratory tests performed in UZ Leuven were divided in four groups: core laboratory, immunology, special chemistry, and molecular microbiology testing. Each test was classified as Conformité Européenne (CE)-IVD, modified/off-label CE-IVD, commercial Research Use Only (RUO) or LDT. Each matrix was considered a separate test. We found that 97.6% of the more than 11.5 million results/year were generated with a CE-IVD method. Of the 922 different laboratory tests, however, only 41.8% were CE-IVD, 10.8% modified/off-label CE-IVD, 0.3% RUO, and 47.1% LDT. Off-label CE-IVD was mainly used to test alternative matrices not covered by the claim of the manufacturer (e.g., pleural or peritoneal fluid). LDTs were mainly used for special chemistry, flow cytometry, and molecular testing. Excluding flow cytometry, the main reasons for the use of 377 LDTs were lack of a CE-IVD method (71.9%), analytical requirements (14.3%), and the fact the LDT was in use before CE-IVD available (11.9%). While the large majority of results (97.6%) were generated with a CE-IVD method, only 41.8% of laboratory tests were CE-IVD. There is currently no alternative on the market for 71.5% of the 537 LDTs performed in our laboratory which do not fall within the scope of the current IVD directive (IVDD). Compliance with the IVDR will require a major investment of time and effort.

Evaluation of Commercial Molecular Diagnostic Methods for Detection and Determination of Macrolide Resistance in Mycoplasma pneumoniae.

We evaluated six commercial molecular tests targeting Mycoplasma pneumoniae, namely, the BioFire FilmArray respiratory panel (RP), the Meridian Alethia Mycoplasma Direct, the GenMark ePlex respiratory pathogen panel (RPP), the Luminex NxTAG RPP, the ELITech ELITe InGenius Mycoplasma MGB research use only (RUO) PCR, and the SpeeDx Resistance Plus MP assays. Laboratory-developed PCR assays at the University of Alabama at Birmingham and the Centers for Disease Control and Prevention were used as reference standards. Among 428 specimens, 212 were designated confirmed positives for M. pneumoniae The highest clinical sensitivities were found with the InGenius PCR (99.5%) and the FilmArray RP (98.1%). The Resistance Plus MP identified 93.3% of the confirmed-positive specimens, whereas 83.6, 64.6, and 55.7% were identified by the ePlex RPP, NxTAG RPP, and Mycoplasma Direct assays, respectively. There was no significant difference between the sensitivity of the reference methods and that of the FilmArray RP and InGenius assays, but the remaining four assays detected significantly fewer positive specimens (P < 0.05). Specificities of all assays were 99.5 to 100%. The Resistance Plus MP assay detected macrolide resistance in 27/33 specimens, resulting in a sensitivity of 81.8%. This study provides the first large-scale comparison of commercial molecular assays for detection of M. pneumoniae in the United States and identified clear differences among their performance. Additional studies are necessary to explore the impact of various test performances on patient outcome.

2144. Performance of 2019 CLSI Ciprofloxacin Breakpoint Antimicrobial Susceptibility Testing Algorithms for Enterobacteriaceae and Pseudomonas aeruginosa Directly from Positive Blood Culture on the Accelerate Pheno™ System

BackgroundThe Clinical and Laboratory Standards Institute (CLSI) updated fluoroquinolone breakpoints in 2019 in response to evolving resistance and new outcome data. The performance of updated antimicrobial susceptibility testing (AST) algorithms for ciprofloxacin with the 2019 breakpoints for Enterobacteriaceae and Pseudomonas aeruginosa was evaluated using the Accelerate Pheno™ system with contrived positive blood culture samples compared with broth microdilution (BMD).MethodsA total of 294 clinical isolates (100 P. aeruginosa, 82 Klebsiella spp., 56 E. coli, 24 Citrobacter spp., 14 Enterobacter spp., 15 Proteus spp., and 3 S. marcescens) were tested with ciprofloxacin. Aliquots of BD BACTEC™ Standard Aerobic media containing healthy donor blood were seeded with 10–100 bacterial cells and incubated until positivity. Aliquots of the positive blood cultures were run using the Accelerate PhenoTest™ BC kit on the Accelerate Pheno™ system according to the manufacturer instructions for use. Results were obtained using an updated ciprofloxacin algorithm and compared with CLSI standard reference BMD. Only samples with valid results with both the Accelerate Pheno™ system and reference BMD were included in analysis. Essential agreement (EA), categorical agreement (CA), very major error (VME), major error (ME) and minor error (mE) rates were calculated using 2019 CLSI breakpoints.ResultsEA and CA for all antimicrobial/organism combinations were >94%. There were 2 MEs (1 K. pneumoniae, 1 C. freundii) and no VMEs.ConclusionResults with the new research use only (RUO) algorithms are very good and meet FDA acceptance criteria for AST performance. These data will be submitted to the FDA for clearance, once FDA recognizes the CLSI breakpoints. Disclosures All authors: No reported disclosures.

Closed system RT-qPCR as a potential companion diagnostic test for immunotherapy outcome in metastatic melanoma

BackgroundIn melanoma, there is no companion diagnostic test to predict response to programmed cell death 1 (PD-1) axis immune checkpoint inhibitor (ICI) therapy. In the adjuvant setting, only one in five patients may benefit from ICI, so a biomarker is needed to select those that may or may not benefit. Here, we test a new 4-gene multiplex immunotherapy panel with research use only (RUO) prototype mRNA expression profile on the GeneXpert closed system using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) for association with clinical benefit after treatment with ICI therapy in metastatic melanoma patients.MethodsPretreatment formalin-fixed paraffin-embedded (FFPE) tissue sections from melanoma patients treated with anti-PD-1 therapy (pembrolizumab, nivolumab, or ipilimumab plus nivolumab) between 2011 and 17 were selected from the Yale Pathology archives. FFPE sections were macrodissected to enrich for tumor for quantitative assessment of CD274 (PD-L1), PDCD1LG2 (PD-L2), CD8A, and IRF1 by RT-qPCR multiplex mRNA panel. Multiplex panel transcript levels were correlated with clinical benefit (complete response [CR], partial response [PR], stable disease [SD]); disease outcomes (progression-free survival [PFS] and overall survival [OS]); and protein levels assessed by quantitative immunofluorescence (QIF).ResultsTranscript levels were significantly higher in responders (CR/PR/SD) than in nonresponders (PD) for CD8A (p = 0.0001) and IRF1 (p = 0.0019). PFS was strongly associated with high CD274 (p = 0.0046), PDCD1LG2 (p = 0.0039), CD8A (p = 0.0002), and IRF1 (p = 0.0030) mRNA expression. Similar associations were observed for OS with high CD274 (p = 0.0004), CD8A (p = 0.0030), and IRF1 (p = 0.0096) mRNA expression. Multivariate analyses revealed significant PFS and OS associations with immunotherapy panel markers independent of baseline variables. Exploratory analyses revealed a novel significant association of high combined CD274 & PDCD1LG2 (L1/L2) transcript expression with PFS (p < 0.0001) and OS (p = 0.0011), which remained significant at a multivariate level for both PFS (HR = 0.31) and OS (HR = 0.39).ConclusionsIndividual immunotherapy panel markers CD274, PDCD1LG2, CD8A, IRF1 and a combined L1/L2 mRNA levels show promising associations with melanoma immunotherapy outcome. The turnaround time of the test (2 h) and easy standardization of the platform makes this an attractive approach for further study in the search for predictive biomarkers for ICI.

Abstract 3142: A CD274, PDCD1LG2, CD8A, and IRF1 multiplex in a closed system RT-qPCR panel and immunotherapy outcome in metastatic melanoma

Abstract Background: In melanoma, there is no companion diagnostic test to predict response to programmed cell death 1 (PD-1) axis immune checkpoint inhibitor therapy (ICI). In the adjuvant setting, only 1 in 5 patients may benefit from ICI, so biomarker is needed to select those that may or may not benefit. Candidate techniques for the assessment of predictive markers include immunohistochemistry (IHC), multiplex fluorescence, genome sequencing, and RNA expression profiles. Here we test a new 4-gene research use only (RUO)* prototype mRNA expression profile on the GeneXpert closed system using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) for association with clinical benefit after treatment with ICI in metastatic melanoma patients. Methods: Pretreatment formalin-fixed paraffin-embedded (FFPE) tissue sections from melanoma patients treated with anti-PD-1 therapy (pembrolizumab, nivolumab, or ipilimumab plus nivolumab) between 2011-17 were selected from the Yale Pathology archives. FFPE sections were macrodissected to enrich for tumor for quantitative assessment of CD274 (PD-L1), PDCD1LG2 (PD-L2), CD8A, and IRF1 by RT-qPCR multiplex mRNA panel. Multiplex panel transcript levels were correlated with clinical benefit (CR/PR/SD); disease outcomes (progression-free survival, PFS and overall survival, OS); and protein levels assessed by quantitative immunofluorescence (QIF). Median values for each marker were used to define high versus low mRNA or protein expression groups. This study was approved by Yale Human Investigation IRB protocol ID 9505008219. Results: Inter-transcript regression was observed among all four markers with R2 ranging from 0.20 to 0.51. Transcript levels were significantly higher in CR/PR/SD than in PD for CD8A (p = 0.0001) and IRF1 (p = 0.0019). PFS was strongly associated with high CD274 (p = 0.0046), PDCD1LG2 (p = 0.0039), CD8A (p = 0.0002), and IRF1 (p = 0.0030) mRNA expression. Similar associations were observed for OS with high CD274 (p = 0.0004), CD8A (p = 0.0030), and IRF1 (p = 0.0096) mRNA expression. Multivariate analyses revealed significant associations with OS independent of age, sex, stage, mutation, treatment, and prior ICI for CD274 (HR = 0.30), CD8A (HR = 0.40) and IRF1 mRNA (HR = 0.36). Similar PFS association with CD8A (HR = 0.39) and IRF1 (HR = 0.48) parameters were observed by multivariate analyses. Nonlinear exponential relationship was observed between transcript and protein levels for CD8A (R2 = 0.66) and IRF1 (R2 = 0.40). Conclusions: Although tested in only a single melanoma cohort, CD274, CD8A and IRF1 mRNA levels show promising associations with outcome. The turnaround time of the test (2h) and easy standardization of the platform makes this an attractive approach for further study in the search for predictive biomarkers for ICI. *for Research Use Only - not approved or reviewed by any regulatory body Citation Format: Swati Gupta, Leena McCann, Yvonne G.Y. Chan, Edwin W. Lai, Pok Fai Wong, James W. Smithy, Jodi Weidler, Brian Rhees, Michael Bates, Harriet M. Kluger, David L. Rimm. A CD274, PDCD1LG2, CD8A, and IRF1 multiplex in a closed system RT-qPCR panel and immunotherapy outcome in metastatic melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3142.

Automated Early Detection of Myelodysplastic Syndrome with Beckman-Coulter DxH 800 Hematologyanalyzer By Using Ten Research Parameters

IntroductionModerate anemia affects a substantial fraction of the elderly population and blood smear analysis can help to guide towards a diagnosis of myelodysplastic syndrome (MDS). Nevertheless, in medical laboratories, review of blood smear is realized only if there is quantitative or qualitative flag on the complete blood count (CBC). Consequently, the suspicion of MDS could be delayed because of the absence of systematic blood smear triggering, this smear being crucial to induce the diagnosis process by cytological analysis of bone marrow aspiration. The DxH 800 Hematology Analyzer measures and calculates 126 cytological parameters based on photometry, impedance or light scatter. These parameters regroup 23 standard CBC parameters and 103 unexploited “research parameters”. The goal of our study was to create an original mathematical model using “research parameters” to determine a Suspicion Score of MDS which triggers blood smear examination and consequently the process of identification of subclinical patients suffering from MDS.MethodsThis study compared the 126 parameters measured by the Beckman-Coulter DxH 800 Hematology Analyzer from peripheral blood samples of MDS patients and healthy volunteers. MDS cohort was composed of 101 patients of the university hospital of Tours (9 MDS-SLD, 28 MDS-MLD, 8 MDS-RS-SLD, 8 MDS-RS-MLD, 20 MDS-EB-1, 19 MDS-EB-2, 9 5q-). The cohort of healthy volunteers included 88 aged-matched subjects from HEALTHOX and PLASMYC protocols (ClinicalTrials.gov # NCT02789839 and # NCT02809222, respectively). The “research parameters” contained Research Use Only (RUO) parameters and Cell Population Data (CPD). CPD were composed of 98 parameters measured by Volume Conductivity Scatter (VCS) module. The parameters derived from reticulocytes, which require a specific prescription, were excluded. Statistical analyses were performed using Rstudio version 1.0.153. The normal distribution of values was studied by Shapiro-Wilk tests (p-value<0.05) and the homoscedasticity by Levene tests (p-value>0.05). Means comparisons were performed by Wilcoxon and Student tests. Principal component analysis (PCA) was performed using FactoMineR. The logarithmic logistic regression was done thanks to the glm() function of the stats package. The general linear model was obtained by using logistic regression with weighted parameters and was validated by split-sample strategy (10,000 repeats). Samples were divided into two groups (“learning” and “test” groups) randomly mixing MDS patients and healthy volunteers. The “learning” group (n=130) allowed to build the model and the “test” group (n=59) was used to validate it.ResultsAfter mono-parametric and multi-parametric comparisons, 10 parameters were selected to establish the model of interest according to the best contributions at the first axe of PCA, the best correlations at two first axes of PCA and the most significant p-values (parameters described in the Table: MN.LALS.NNRBC, MN.LMALS.NNRBC, MN.UMALS.NNRBC, SD.MALS.NE, SD.UMALS.NE, SD.V.NE, MN.MALS.NE, SD.AL2.NE, SD.AL2.MO, SD.V.MO ). In order to determine the Suspicion Score of MDS (SS-MDS), the 10 selected parameters were weighted during split sampling strategy by logistic regression. After repeat of 10,000 split-samples, the SS-MDS determined using weighted parameters was validated with average efficiency of 92.3%. For each parameter, the median of weighting coefficients was used in the mathematical model: “SS-MDS = ΣCi.Pi + intercept” with “Ci: weighting coefficient of parameter i” and “Pi: parameter i value”. On the whole cohort, SS-MDS induced “MDS” flag for 11 MDS patients (red points in the Figures) for which conventional CBC algorithms failed to generate flag spreading peripheral blood smear. By fixing the threshold at -1.5, the sensitivity and specificity of SS-MDS were 100% and 92%, respectively. Moreover, the positive and negative predictive values were 93.5% and 100%, respectively.ConclusionsThe incidence of MDS increases with aging and the early diagnosis enables optimal care of these diseases. The Beckman-Coulter DxH 800 HematologyAnalyzer is widely used over the world. We propose in this study the clinical use of 10 unexploited “research parameters” to early detect subclinical MDS by selective triggering of blood smear examination. A prospective/multicentric study will allow the optimization of SS-MDS. DisclosuresNo relevant conflicts of interest to declare.

1991. A Prospective Pilot Evaluation of a Research Use Only (RUO) Prototype of a Highly Multiplexed Sample-to-Answer PCR System for the Detection of Pathogens From Positive Blood Culture

BackgroundRapid identification of causative agents from positive blood culture (PBC) can aid earlier targeted therapy, as well as reduce mortality, length of stay, and costs associated with systemic infections. The BioFire® Blood Culture Identification 2 (BCID2) Panel being developed by BioFire Diagnostics, LLC, aims to maintain or improve the performance of the BioFire® FilmArray® Blood Culture Identification (BCID) Panel with updated and novel assays (15 new analytes: six antimicrobial resistance (AMR), six bacterial, and three fungal analytes). The performance of an RUO BioFire BCID2 Panel during a prospective pilot study is compared with standard of care (SoC), as well as independent PCR comparator assay (compPCR) results.MethodsTwo pilot sites enrolled de-identified PBC (<24 hours post-positivity) for which clinician-ordered SoC tests had been performed. Aliquots of residual PBC and isolates were frozen for compPCR testing of AMR markers and discrepancy resolution. 100 aerobic PBC (A-PBC) and 85 anaerobic PBC (AN-PBC) were tested with the BioFire BCID2 Panel; 70 A-PBCs and 56 AN-PBCs were concurrently tested on BioFire BCID Panel. Also, isolates from PBCs positive for AMR markers were tested using compPCR.ResultsThe BioFire BCID2 Panel results matched SoC results in 176/177 detections from 100 A-PBC, and in 167/168 detections from 85 AN-PBC. Both BioFire panels detected Candida glabrata and Candida parapsilosis from an A-PBC with only C. parapsilosis SOC result; interestingly, C. glabrata was detected by SoC in the paired AN-PBC. False-positive Bacteroides fragilis detection in an AN-PBC was resolved favorably by compPCR. Two patient samples, positive in both A-PBC and AN-PBC by SoC, were not detected by either the Staphylococcus epidermidis or the Staphylococcus spp. assays on the BioFire BCID2 Panel. All 26 AMR marker detections in both types of PBC were concordant with either SoC or compPCR results.ConclusionWith an expanded menu, >99% specificity, and >97% sensitivity, the BioFire BCID2 Panel is expected to provide rapid and accurate results for key pathogens associated with systemic infections, as well as important AMR markers.RUO products used in this study have not been evaluated by the FDA or other regulatory agencies for In Vitro Diagnostic use.Disclosures U. Spaulding, BioFire Diagnostics, LLC: Employee, Salary. J. Stone, BioFire Diagnostics, LLC: Employee, Salary. K. Koch, BioFire Diagnostics, LLC: Employee, Salary. J. Antosch, BioFire Diagnostics, LLC: Employee, Salary. M. Jones, BioFire Diagnostics, LLC: Employee, Salary. Z. Lu, BioFire Diagnostics, LLC: Employee, Salary. T. Todorov, BioFire Diagnostics, LLC: Employee, Salary. S. Kerr, BioFire Diagnostics, LLC: Employee, Salary. K. Holmberg, BioFire Diagnostics, LLC: Employee, Salary. M. Rogatcheva, BioFire: Employee, Salary.

1990. Reactivity and Specificity of a Research Use Only (RUO) Prototype of a Highly Multiplexed Sample-to-Answer PCR System for the Detection of Pathogens from Positive Blood Culture

BackgroundRapid diagnosis of causative agents of bloodstream infections improves patient outcomes and antibiotic stewardship. BioFire Diagnostics, LLC, is developing the BioFire® Blood Culture Identification 2 (BCID2) Panel, increasing the coverage of the BioFire® FilmArray® Blood Culture Identification (BCID) Panel for key pathogens and antimicrobial resistance (AMR) markers in aerobic and anaerobic positive blood culture (PBC). This revision expands the menu from 27 to 42 targets, with 26 bacterial (14 revised, six new) and seven fungal analytes (two revised, three new), as well as nine AMR markers (one revised, six new). Notable additions include the anaerobe Bacteroides fragilis, the emerging fungus Candida auris, and the mobile colistin resistance gene, mcr-1. This study details the reactivity and specificity of an RUO BioFire BCID2 panel.MethodsThe prototype was tested with fungal and bacterial isolates, some carrying AMR markers, at two sites by multiple operators. Reactivity was assessed at 106 CFU/mL for 301 analytes, and specificity at 108 CFU/mL for 43 on-panel and 93 off-panel strains. Evaluation included multiple strains for species level and AMR marker assays, as well as multiple species for family/genus level assays. Concordance with standard of care (SoC) results was examined for 126 archived PBC.ResultsTesting against 136 on-panel organisms, phylogenetic-neighbors, and normal cutaneous flora, showed 100% specificity for 41/42 targets. Reactivity was confirmed for 346/351 target analytes, and comprehensive detection was observed for the revised family-level Enteric assay (90/90) and genus-level Staphylococcus spp. (51/51), Streptococcus spp. (17/17), and Candida spp. (67/71) assays. The prototype showed excellent sensitivity (97.1%) and specificity (99.7%) compared with SoC with archived PBC.ConclusionPerformance of this RUO BioFire BCID2 Panel indicates that many key pathogens implicated in bloodstream infections can be identified with high sensitivity and specificity, and highlights the utility of the expanded menu to provide actionable information. Future panel versions will address observed deficiencies.RUO products used in this study have not been evaluated by the FDA or other regulatory agencies for In Vitro Diagnostic use.Disclosures J. Antosch, BioFire Diagnostics, LLC: Employee, Salary. U. Spaulding, BioFire Diagnostics, LLC: Employee, Salary. J. Stone, BioFire Diagnostics, LLC: Employee, Salary. C. Later, BioFire Diagnostics, LLC: Employee, Salary. K. Koch, BioFire Diagnostics, LLC: Employee, Salary. I. Kavetska, BioFire Diagnostics, LLC: Employee, Salary. H. Ton, BioFire Diagnostics, LLC: Employee, Salary. C. Alberti-Segui, bioMérieux: Employee, Salary. A. Grange, bioMereiux, Inc.: Employee, Salary. C. Dubost, bioMérieux: Employee, Salary. M. Rogatcheva, BioFire: Employee, Salary.

Abstract 4542: Analytical validation of the SignateraTM RUO assay, a highly sensitive patient-specific multiplex PCR NGS-based noninvasive cancer recurrence detection and therapy monitoring assay

Abstract Introduction: Liquid biopsy-based detection and monitoring of tumor-specific somatic mutations in cell-free DNA has great potential to improve patient care by detecting cancer early, assisting adjuvant therapy decision-making, monitoring residual disease, determining treatment effects, assessing relapse and the consequent need for follow-up intervention. We have developed a novel highly sensitive and specific approach for the detection and quantification of circulating tumor DNA (ctDNA) by tracking personalized cancer signatures in plasma. We recently described our ability to detect ctDNA presence longitudinally in patients with non-small cell lung cancer (NSCLC) and have validated this personalized approach for detection of tumor DNA in plasma, and made it available for research use only (RUO). Summary of Experimental Procedures: This study describes results of the Signatera RUO assay's analytical validation test titrations of cancer cell lines and their matched normal counterparts. Multiplex-PCR (mPCR) assay pools specific to the tumor mutational signatures were derived from whole-exome data analysis of the tumor cell line and its corresponding matched normal cell line. Tumor DNA spike-in mixtures were amplified using the mPCR assays and then barcoded and sequenced at ultra-high depth on the Illumina HiSeq instrument (average &amp;gt; 100,000 reads per target). This study also demonstrates the ability to detect ctDNA using Signatera RUO assay's personalized somatic mutations in patients with epithelial and non-epithelial ovarian cancer. Results/Data Summary: The Signatera RUO analytical validation results demonstrate a variant-level sensitivity of ~60% at spiked-in tumor DNA concentrations of 0.03% along with an assay specificity of 99.9% in wild-type DNA. By targeting 16 somatic mutations present in the tumor, an estimated LOD of 0.01% tumor DNA in a patient's plasma is achieved. The Signatera RUO assay also demonstrates the ability to detect ctDNA in plasma down to less than 0.1% VAF at baseline (prior to treatment) in epithelial and non-epithelial ovarian cancer. Conclusion: The Signatera RUO assay provides a unique method to noninvasively detect ctDNA by assaying for personalized cancer signatures in plasma by ultra-high-depth sequencing of custom-made multiplex PCR assays, with high sensitivity and high specificity. Our study demonstrates the potential of this technology to improve the current standard of care by enabling early recurrence detection and the monitoring of treatment effectiveness across several tumor types. Citation Format: Himanshu Sethi, Raheleh Salari, Samantha Navarro, Prashanthi Natarajan, Ramya Srinivasan, Scott Dashner, Tony Tin, Mustafa Balcioglu, Ryan Swenerton, Bernhard Zimmermann. Analytical validation of the SignateraTM RUO assay, a highly sensitive patient-specific multiplex PCR NGS-based noninvasive cancer recurrence detection and therapy monitoring assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4542.