Thursday, December 6th

8:00 AM

Registration/Continental Breakfast

9:00 AM

Welcome and Logistics

John Mudgett, Co-Founder and Chief Scientific Officer

JsM BioScience, LLC

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Welcome and Logistics

Track 3: Long-Term Goal of Bridging Drug Treatments with Genetic and Genomic Data

9:05 AM

Successfully Leveraging Gene Expression for Biomarker Discovery

Leeona Galligan, VP UK Operations

Almac Diagnostics

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Successfully Leveraging Gene Expression for Biomarker Discovery

The relative stability of DNA in archived formalin-fixed paraffin-embedded (FFPE) clinical material, alongside the wide availability of in silico data, has facilitated the dominance of gene aberration biomarkers in the molecular oncology space. However, RNA assessment offers significant additional opportunities to harness the dynamic tumour landscape for the development of predictive and prognostic biomarkers. The clinical utility of such gene expression profiling has been clearly demonstrated by commercialised biomarker assays including Agendia’s Mammaprint® 70 gene signature and Genomic Health’s OncoType DX® panel series.

Assessment of RNA is not without challenges; most notably those associated with the RNA degradation in archived FFPE material and subsequent data interpretation. In order to mitigate these challenges, Almac Diagnostics has optimised a novel Next Generation Sequencing (NGS) solution to allow gene expression biomarker discovery from FFPE tumor tissue. Utilising Illumina’s TruSeq® RNA Exome Panel for initial data generation, Almac Diagnostics’ proprietary bioinformatics pipeline is then applied, which classifies samples using biologically relevant gene expression signatures and produces a unique gene expression report – claraT. claraT is a unique software-driven solution, classifying biologically relevant gene expression signatures into a comprehensive, easy-to-interpret report.

Included is a range of relevant public gene expression signatures, Almac proprietary assays and single gene targets linked to key biologies within the Hallmarks of Cancer. When combined, they provide a comprehensive review of tumour biology. Results are presented in easily interpreted, interactive cohort and individual sample molecular data reports intended for use as a pan-cancer biomarker discovery tool and in translational research.

During this talk participants will learn about: The challenges inherent in gene expression oncology biomarker development The power of assessing the RNA exome How to effectively harness the power of the transcriptome for biomarker discovery through effective experimental design and data analyses How claraT can be used as a pan-cancer biomarker discovery tool and in translational research Customised sample reporting enabling simple interpretation of molecular data

Authors Leeona Galligan, Nuala McCabe, Laura Knight, Steve Walker, Richard Kennedy

9:30 AM

Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion

Shanrong Zhao, Director, Computational Biology and Bioinformatics

Pfizer

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Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion

Authors:  Shanrong Zhao*, Ying Zhang, Ramya Gamini, Baohong Zhang, David von Schack

To allow efficient transcript/gene detection, highly abundant ribosomal RNAs (rRNA) are generally removed from total RNA either by positive polyA+ selection or by rRNA depletion (negative selection) before sequencing. Comparisons between the two methods have been carried out by various groups, but the assessments have relied largely on non-clinical samples. In this study, we evaluated these two RNA sequencing approaches using human blood and colon tissue samples. Our analyses showed that rRNA depletion captured more unique transcriptome features, whereas polyA+ selection outperformed rRNA depletion with higher exonic coverage and better accuracy of gene quantification. For blood- and colon-derived RNAs, we found that 220% and 50% more reads, respectively, would have to be sequenced to achieve the same level of exonic coverage in the rRNA depletion method compared with the polyA+ selection method. Therefore, in most cases we strongly recommend polyA+ selection over rRNA depletion for gene quantification in clinical RNA sequencing. Our evaluation revealed that a small number of lncRNAs and small RNAs made up a large fraction of the reads in the rRNA depletion RNA sequencing data. Thus, we recommend that these RNAs are specifically depleted to improve the sequencing depth of the remaining RNAs.

9:55 AM

From Coverage to Reimbursement: Coverage and reimbursement for new technology

Laurie Howard, Vice President, Policy and Payer Relations

LabCorp

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From Coverage to Reimbursement: Coverage and reimbursement for new technology

This presentation will address the crucial steps for successful coverage and reimbursement for new technology:  CPT coding, technical assessments, evidence review, Z-Codes, rate setting, NCD/LCD, appeals and other issues that cause barriers to payment.

10:20 AM

Abundant, Ultra-Short Trans-Renal Tumor DNA Fragments in Urine For Non-Invasive Cancer Detection and Monitorin

Qing Kang, Senior Scientist

Syros Pharmaceuticals

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Abundant, Ultra-Short Trans-Renal Tumor DNA Fragments in Urine For Non-Invasive Cancer Detection and Monitorin

Circulating tumor DNA (ctDNA) has shown great promise as a cancer biomarker in detecting tumor genotypes, monitoring cancer recurrence and resistance, as well as assessing treatment response. Compared to increased studies in plasma ctDNA, trans-renal tumor DNA (trDNA) exists as a largely untapped field. Here we present a proof-of-concept study to comprehensively understand the fundamentals of trDNA in different cohorts of cancer patients.

Authors
Kang Q,Hovelson DH,Ulintz PJ,Opron K,Gates CM,Parkin B,Liu CJ,Brown NA,Ramnath N, Henry NL,Krauss JC,Talpaz M,Kandarpa M,Baker L,Hadjiyski L,Goicochea A,Lindstrom R,Tuck M, Herman K,Tomlins S,Tewari M

10:45 AM

Networking Break

10:55 AM

Early Assessment of Treatment Response in Solid Tumors via Quantitating Circulating Tumor DNA

Max Ma, Director, Medical Affairs

Roche Sequencing Solutions

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Early Assessment of Treatment Response in Solid Tumors via Quantitating Circulating Tumor DNA

Thanks to the advancement of modern medicine, multiple therapeutic options often exist for the treatment of various cancers. Lessons learned from managing blood cancers under therapy have taught us the importance of monitoring early response. Longitudinal monitoring of circulating tumor DNA (ctDNA) is an emerging method for disease management in solid tumors. We employed a 197-gene NGS assay, the AVENIO ctDNA Surveillance Kit, which allowed us to perform longitudinal ctDNA analysis and measure changes in ctDNA levels in plasma. Specifically, we evaluated the association between change in ctDNA levels within first two cycles of treatment and survival data from a cohort of 106 advanced lung adenocarcinoma subjects treated with first-line chemo or chemoradiation therapies. Our data show that a decrease in post-treatment ctDNA level measured by the Surveillance Kit (For Research Use Only, not for use in diagnostic procedures) was associated with better outcome (both PFS and OS) in advanced lung adenocarcinoma. In addition, clinical research results on disease monitoring under targeted therapies and disease surveillance under adjuvant setting will be discussed.

11:20 AM

Speeding up Genomic Data Creation, Aggregation and Impactful Interpretation

James Flynn, Scientific Engagement Manager

Illumina

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Speeding up Genomic Data Creation, Aggregation and Impactful Interpretation

Traditional drug development paradigms have shifted toward gaining proof of concept information on clinical benefit as early as possible in distinct populations based on biomarker profiles. At the same time, individualized treatment regimens are becoming more personalized to better target the specific manifestations of disease. Illumina’s BaseSpace™ Informatics Suite is a cloud-based discovery and integration platform that provides practical ways to generate, process, store and mine vast quantities of complex biological and clinical data. Illumina engineered new paradigms of correlative, data-driven discovery that have accelerated biomedical research by combining private and public ‘omics’ data in biologist-friendly interfaces. Advances in summarizing subject level attributes, therapies, molecular profiles, survival and drug sensitivity reporting enrich translational development programs with deep-reaching analytical guidance. In this presentation, we will i) review the extent to which public data is available in BaseSpace™ Cohort Analyzer and Correlation Engine, and ii) perform live demonstrations of effectively applying genome scale data analytics to positively impact research programs.

11:45 AM

Networking Break

WORKSHOP

11:55 AM

WORKSHOP: Understanding Innate Anti-PD-1 Resistance Therapy in Melanoma Through Integrative Transcriptome Analysis Using ArraySuite (AS) and Ingenuity Pathway Analysis (IPA)

Qian Dong, Bioinformatics

QIAGEN

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WORKSHOP: Understanding Innate Anti-PD-1 Resistance Therapy in Melanoma Through Integrative Transcriptome Analysis Using ArraySuite (AS) and Ingenuity Pathway Analysis (IPA)

Understanding innate resistance to anti-PD-1 therapy in melanoma through transcriptomics Immunotherapy consisting of blocking immune checkpoints,  such as PD-1, has shown promise in treating melanoma. However, innate and acquired resistance to anti-PD-1 therapy often results in recurrence after initial successful treatment leading to advanced metastatic melanoma. This presentation will show the combined power of OmicSoft’s OncoLand, Array Suite and Ingenuity Pathway Analysis (QIAGEN) to analyze and interpret whole transcriptome from RNA-sequencing from pre-treatment mRNAs of patients with advanced metastatic melanoma and with respect to their subsequent immunotherapy treatment outcomes. We will provide highlights into the biological signatures that determine non-responder versus responder status.

12:55 PM

Closing Event Comments

John Mudgett, Co-Founder and Chief Scientific Officer

JsM BioScience, LLC

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Closing Event Comments

1:00 PM

Lunch