Sharon Austin

Abstract 2757: Using liquid biopsies and NGS as tools to analyze mutation burden and copy number variation in the blood of a patient with triple negative breast cancer to better inform therapeutic targets

The ability to characterize molecular features of cancer from liquid biopsies is resulting in the development of innovative health care for patients. Longitudinal changes in the mutational profiles of DNA isolated from liquid biopsies are being used to better understand and monitor the development, progression, and evolution of therapy resistance in cancer patients. To define changes in the mutational landscape and predict drug susceptibilities in Triple Negative Breast Cancer (TNBC) patients, we used whole exome analysis to profile circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) from eight selected time points of a patient enrolled in the Intensive Trial of OMics in Cancer clinical Trial (ITOMIC-001). The patient initially received weekly cisplatin infusions followed by additional targeted therapy. Peripheral blood samples were collected at specific time points over a period of 272 days following enrollment in the clinical trial. Our data indicates that the identified mutations in genomic DNA isolated from CTCs and ctDNA can be used to understand and mitigate the impact of tumor heterogeneity in addition to identifying clinically relevant mutations at these selected time points. To further increase the resolution of our analysis, we profiled ctDNA from these samples to a higher depth targeting only clinically relevant genes. These analyses increased the sensitivity of detection and identified additional targets that could have been used for therapeutic intervention. In addition to sequence variants, copy number variations (CNVs) have also been significantly associated with the development of metastasis and changes in CNVs have been used to monitor disease progression. We performed a bioinformatics analysis of genomic instability and CNVs across 32 different time points from ctDNA from the same patient throughout the treatment period. The genomic instability number (GIN) calculated for each of the 32 time points seems to mirror the overall CTC burden in the patient at each time point tested. CNV analysis is ongoing and these data sets are being further analyzed in combination with TCGA data to define possible cancer driver genes for the functional prediction of significant TNBC candidate alterations and the results of these analyses will be presented. Citation Format: Kellie Howard, Kimberly Kruse, Brianna Greenwood, Elliott Swanson, Mathias Ehrich, Christopher K. Ellison, Taylor Jensen, Sharon Austin, Arturo Ramirez, Debbie Boles, John Pruitt, Elisabeth Mahen, Jackie L. Stilwell, Eric P. Kaldjian, Michael Dorschner, Sibel Blau, Marcia Eisenberg, Steve Anderson, Anup Madan. Using liquid biopsies and NGS as tools to analyze mutation burden and copy number variation in the blood of a patient with triple negative breast cancer to better inform therapeutic targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2757. doi:10.1158/1538-7445.AM2017-2757

Abstract 4436: Synergistic effects of promoter associated DNA methylation and genetic alterations to better understand oncogenic gene expression profiles

The emergence of Next Generation Sequencing (NGS) along with computational biology has broadened the scope in which diverse cellular processes can be interrogated. While there has been considerable progress in understanding the impact of genetic and epigenetic mechanisms in tumorigenesis using whole genomic, epigenomic and transcriptional analysis by NGS, there has been little consideration of the importance of interplay between these processes. We performed a comparative analysis of array and NGS technologies to identify differentially methylated CpG sites in colorectal cancer cell lines. NGS had more specificity in addition to profiling more CpG sites relative to Illumina 450K arrays. Base-level resolution of sequencing data can identify any strand specific methylation bias. Our analysis shows that methylation frequency between the sense and antisense strand are highly correlated (average R2 ∼ 0.81), and coefficient of variance (CV) between the strands is generally low (about half of observed sites have We also used NGS and publically available gene expression datasets in colorectal cancer cell lines-HCT116 and HCT116 DKO (cell line with genetic knockouts of both DNA methyltransferases DNMT1 and DMNT3b) to identify roles of differential methylation in regulating gene expression. A majority of genes were down-regulated between HCT116 and HCT116 DKO cell lines including those involved in chromatin, nucleic acid, and nucleotide binding and cell cycle regulation. Interestingly, many differentially expressed genes are also involved in immune response. We then used bisulfite treated genomic data to evaluate genetic regulation of gene expression. For this, we converted bisulfite treated data into genomic space using custom in-house developed bio-informatics tools that were first tested using DNA isolated from NA12878 cell line. Our analysis showed that 65% of the known variants detected in NA12878 cell line by the genome in a bottle consortium can be identified by bisulfite sequencing of promoter associated CpG islands. One limitation of this analysis is the inability to identify C>T genomic variants. This data is being analyzed to evaluate effects of genetic mutations in promoter binding sites on gene expression in colorectal cancers. Comparative analysis of genetic and epigenetic regulation of gene expression will allow better understanding of gene regulatory networks in colorectal cancer. Citation Format: Claire Olson, Fang Yin Lo, Kerry Deutsch, Sharon Austin, Kellie Howard, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kathryn Shiji, Shradha Patil, Steven Anderson, Anup Madan. Synergistic effects of promoter associated DNA methylation and genetic alterations to better understand oncogenic gene expression profiles. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4436.

Abstract 498: Meta-analysis of genomic aberrations identified in CTCs andctDNA in triple negative breast cancer

Technological innovation and scientific advances in understanding cancer at the molecular level have accelerated the discovery and development of both diagnostics and therapeutics. Circulating tumor cells (CTCs) and plasma circulating tumor DNA (ctDNA) are non-invasive prognostic markers that have been associated with metastatic and aggressive disease. Both CTCs and ctDNA allow molecular characterization of a tumor that is inaccessible or too risky to biopsy. The analysis of genomic aberrations in both sample types provides insights into drug resistance and can help determine appropriate, targeted cancer treatments. Mutations found in the primary or metastatic tumor can be identified in both CTCs and ctDNA as well as novel mutations that may reflect intratumoral and intermetastatic heterogeneity. When collected and evaluated over an extended period of time, changes in the CTC and/or ctDNA mutational profile can offer guidance into the effectiveness of a treatment, indicate the progression of disease, and detect recurrence of disease earlier. We have performed whole exome sequencing of CTCs and ctDNA from a metastatic triple negative breast cancer (TNBC) patient to better understand the evolution of tumor heterogeneity during therapy. The patient was enrolled in the Intensive Trial of OMics in Cancer clinical Trial (ITOMIC-001) and initially received weekly cisplatin infusions followed by additional targeted therapy. Longitudinal peripheral blood samples were collected over a period of 272 days following enrollment in the clinical trial. CTCs were identified using the AccuCyte-CyteFinder system (RareCyte, Seattle WA). We used next generation sequencing, and computational biology tools to analyze genomic DNA from multiple CTCs, white blood cells (WBCs) and ctDNA from various time points. We observed similar genomic aberrations in both CTCs and ctDNA that could be classified into three groups: a) a static group that remains unchanged during the course of therapy, b) a sample-specific group that is unique to each time point and c) an intermediate group that has variants that are short-lived but are present across multiple time points. Variants identified in the liquid biopsy samples were compared with variants observed in primary breast tumor, metastatic bone marrow tumor and publically available pan-cancer datasets. We then performed meta-analysis on somatic variants to identify changes in affected networks in response to therapy over time. Several key nodes were identified that could rationally have been targeted for therapy using compounds currently in clinical trials. We then compared and combined the perturbed networks obtained from the CTCs and ctDNA to better understand the etiology of TNBC. These studies represent the first step of a synergistic partnership between the genetic information obtained from the analysis of CTCs and ctDNA with innovative health care for patients with metastatic breast cancer. Citation Format: Kellie Howard, Sharon Austin, Fang Yin Lo, Arturo Ramirez, Debbie Boles, John Pruitt, Elisabeth Mahen, Heather Collins, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kerry Deutsch, Jackie Stilwell, Eric Kaldjian, Michael Dorschner, Sibel Blau, Anthony Blau, Marcia Eisenberg, Steven Anderson, Anup Madan. Meta-analysis of genomic aberrations identified in CTCs andctDNA in triple negative breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 498.

Abstract 3946: Stratification of metastatic colorectal cancer patients using DNA and RNA sequencing and in-silico prediction of tumor antigens for consideration in immunotherapy

Colorectal cancer (CRC) is the third most common type of cancer in the United States. Although chemotherapy, radiation and targeted therapies can improve survival rates, recent studies have shown the potential benefit of immunotherapies to improve outcomes for patients with advanced CRC. Targeted therapies that use monoclonal antibodies (mAbs) to EGFR have been shown to benefit some CRC patients. Until recently, KRAS has been the only predictive biomarker for anti-EGFR therapy for metastatic CRC. However, 40% to 60% of patients with wild-type KRAS do not respond to anti-EGFR therapy. Therefore, to accurately predict patients’ response to treatments and improve clinical outcomes, additional prediction and treatment methods are imperative. One of the many efforts to improve prediction for CRC patient9s response to the anti-EGFR therapy is the development of gene expression based RAS signature scores for identification of RAS activated tumors independent of mutations in the KRAS gene. Recently there have been major advances in immunotherapeutic approaches in a wide variety of cancers. In solid tumors such as melanoma and colon cancers, immune checkpoints have been shown to improve clinical outcomes. There is considerable effort being placed on combinations of targeted therapy and immunotherapies to improve responses for these cancers. Similarly, since no single treatment can apply to all CRC patients, we aim to stratify patients using a combination of three methods: 1. RAS signature score based on the expression profile of 18 genes. This RAS signature score enables measurements of mitogen-activated protein/extracellular signal-regulated kinase (MEK) pathway functional output independent of tumor genotype. 2. Expression profile of immune checkpoint inhibitor target genes, such as PD1 and PDL1, and 3. In-silico prediction of neo-antigens and peptide binding affinity between tumor antigens derived from mutations and human HLA alleles. 55 FFPE samples were selected from a cohort of 468 samples with matching FF samples. These 55 samples have about 1:1:1 ratio of high, medium and low RAS scores. Here we showed our ability to obtain RAS signature scores with concordant results using different platforms including RNA-seq, targeted RNA-seq, Nanostring and Affymetrix microarray. Samples that have RAS activating mutations such as KRAS and BRAF have significant higher RAS scores (p Citation Format: FangYin Lo, Sharon Austin, Kellie Howard, Mollie McWhorter, Heather Collins, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Christopherson, Kathryn Shiji, Shradha Patil, Saman Tahir, Sally Dow, Evan Anderson, Jon Oblad, Kerry Deutsch, Timothy Yeatman, Steven Anderson, Anup Madan. Stratification of metastatic colorectal cancer patients using DNA and RNA sequencing and in-silico prediction of tumor antigens for consideration in immunotherapy. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3946.

Abstract P2-02-21: Longitudinal analysis of circulating tumor cells and cell free tumor DNA by next generation sequencing in triple negative breast cancer

As the practice of genetically profiling patient tumors is considered for making clinical treatment decisions, recent methodologies for screening of genomic aberrations in circulating tumor cells (CTCs) and cell-free plasma DNA (cfDNA) may provide non-invasive tools for such applications. Genomic analysis of DNA from CTCs and plasma can also provide useful insight into tumor heterogeneity and thus disease progression by revealing sub-populations of tumor cells that evolve during treatment, have novel drug-resistant genotypes, or carry alternate cancer driver mutations not identified by the sequencing of primary tumors. Comprehensive evaluation of DNA isolated from CTCs and cfDNA from a breast cancer patient by whole exome sequencing was performed to better understand the role of liquid biopsies in investigating the etiology of tumor progression. The patient was diagnosed with metastatic triple negative breast cancer (TNBC) six years after remission from estrogen receptor (ER-3+), progesterone receptor (PR-1+), human epidermal receptor growth factor 2 negative (Her2-), grade 3 intra-ductal carcinoma of the right breast. Metastatic lesions were found in the spine, pelvis and sacrum and bone-marrow. The patient was enrolled in the Intensive Trial of OMics in Cancer clinical Trial (ITOMIC-001; ClinicalTrials.gov ID NCT01957514) and initially received weekly cisplatin infusions followed by additional targeted therapy. Peripheral blood was obtained during regular clinic visits over the 272 days the patient was enrolled in the clinical trial. CTCs were identified and enumerated from each blood draw using the AccuCyte® -CyteFinder® (AC/CF) system (RareCyte, Seattle WA). Multiple CTCs along with white blood cells (WBCs) were picked from various time points throughout the treatment regimen. The selected CTCs and WBCs were whole genome amplified and whole exome sequencing was performed to identify tumor specific variants. A comparative analysis with variants present in genomic DNA isolated from the bone-marrow metastasis tissue biopsy samples and cfDNA revealed the evolution of tumor-specific variants during therapy. Each CTC had somatic alterations in genes associated with therapies in current use or those in the clinical trials setting. Sequencing analysis of cfDNA provided similar information on potential therapeutic approaches. The monitoring of disease over time through genomic analysis of CTCs and cfDNA can identify novel sub-populations related to disease progression for the tailoring of cancer treatment regimens. Further analysis is being performed to better understand the evolution of the genomic heterogeneity among CTCs at the same time point and across different time points and therefore better understand the etiology of progression of metastatic breast cancer in this patient. Citation Format: Howard K, Austin S, Ramirez AB, Ritter L, Boles D, Pruitt J, Collins H, Mahen E, Leonti A, Maassel L, Subia C, Tuuli S, Heying N, Deutsch K, Cox J, Lo FY, Stilwell JL, Kaldjian EP, Dorschner M, Blau S, Blau A, Eisenberg M, Anderson S, Madan A. Longitudinal analysis of circulating tumor cells and cell free tumor DNA by next generation sequencing in triple negative breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-02-21.

Abstract 4842: Pharmacodynamic stratification of metastatic colorectal cancer patients using genomic datasets

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Previously, the mutation status of KRAS was the only validated predictive biomarker for metastatic colorectal cancer (CRC). While KRAS mutated tumors demonstrated resistance to epidermal growth factor (EGFR) inhibitors like cetuximab, KRAS WT and EGFR-expressing tumors were predicted to be responsive. However, KRAS WT metastatic colorectal cancer (CRC) patients have a poor prognosis even with EGFR inhibitor therapy as not all KRAS WT CRCs are responsive to such targeted agents. A gene expression based RAS signature score was developed based on multiple tumor tissue samples to identify RAS activated tumors independent of mutations in the KRAS gene [1, 2]. To further refine this score and define technologies that can be used on FFPE samples isolated in a clinical setting, we analyzed DNA and RNA derived from fifty-five (55) FFPE preserved colorectal cancer tumor biopsies using multiple sequencing, digital and array-based technologies. These samples were selected from a CRC cohort in which the initial gene expression-based RAS signature score was calculated utilizing data compiled from fresh frozen (FF) tumor samples from the same 55 patients. The 55 samples were selected for this study as they had representative samples with high, medium and low RAS signature scores. Transcriptomic analyses (RNA-Seq, Affymetrix microarrays, Nanostring and Targeted RNA-Seq) were performed on all 55 FFPE samples and three new RAS scores were calculated from the gene expression datasets. These RAS scores were based on different gene signatures (1) an 18 gene signature (2) a 13 gene signature, and (3) a 147 gene signature. A significant correlation was identified between RAS scores calculated from the 18 and 13 gene signatures (Correlation coefficient ∼ 0.88 and ∼0.76 respectively, p-value < 0.0001). To further refine gene expression signatures, samples were grouped based upon their mutation status obtained by whole exome sequencing (WES) and targeted DNA sequencing data (Illumina TruSight and LifeTech Cancer Panels). In our sample set, the 18 gene RAS score was found to be dependent on the mutation status of KRAS. Further analysis is being carried out to better understand the relationship between the calculated RAS signature scores and the mutation status of other genes. This analysis will lead to the development of a novel genomic signature for better pharmacodynamic stratification of colorectal carcinoma patients. 1. Loboda A et al. A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors. 2. BMC Medical Genomics 2010, 3:26Dry JR et al. Transcriptional Pathway Signatures Predict MEK Addiction and Response to Selumetinib (AZD6244). Cancer Res. 2010 Mar 15;70(6):2264-73. Citation Format: Sharon Austin, Fang Yin Lo, Kellie Howard, Mollie McWhorter, Heather Collins, Amanda Leonti, Lindsey Maassel, Christopher Subia, Tuuli Saloranta, Nicole Heying, Leila Ritter, Kerry Deutsch, James Cox, Steven Anderson, Anup Madan, Timothy Yeatman. Pharmacodynamic stratification of metastatic colorectal cancer patients using genomic datasets. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4842. doi:10.1158/1538-7445.AM2015-4842

Abstract 1609: Comprehensive multi-omic analysis of circulating tumor cells isolated from a metastatic triple-negative breast cancer patient to identify pathogenic genomic aberrations

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Increasing evidence confirms the prognostic relevance of Circulating Tumor Cells (CTCs) in a variety of cancers including advanced breast cancer. Recent data also suggests that CTCs are a useful tool for monitoring treatment and identifying potential targets for therapeutic intervention. The objective of this study was to investigate technologies that can be used for defining the genomic landscape of CTCs in order to compare the derived genomic information (1) among CTCs to assess genetic heterogeneity and (2) with that derived from bone-marrow metastasis tissue biopsy (BMM) samples to assess how reflective the molecular profile from CTCs is to the metastasis. To evaluate these potential applications, positive CTCs were identified using the AccuCyte -CyteFinder (AC/CF) system (RareCyte, Seattle WA) from the blood of a patient with triple negative breast cancer (TNBC). Twenty CTCs and twenty white blood cells (WBCs) were picked from slides using the AC/CF system. To determine whether tumor specific genomic characteristics are reflected in the isolated cells, we used whole genome amplification (WGA) followed by next-generation sequencing to perform a comprehensive analysis using WBCs as genome controls. Whole genome, exome and targeted sequencing of known cancer-associated genes using Illumina and Life Tech panels identified mutations in TP53, PTEN, ERBB2, STK11, ABL1, HRAS, MLL2 and INPPL1 which were present in the CTCs alone and not in the WBCs. Further analysis comparing the results between CTCs revealed that the majority of the identified mutations were specific to individual CTCs revealing a high degree of genetic heterogeneity. Only 5% of mutations were shared between at least 40% of the CTCs examined and included mutations in ATM, ALK, BRAF, NOTCH1, ATR, JAK3, COL1A1 and XPC. Additionally, all of the profiled CTCs contained two novel mutations in LPP and HLA-A which were not present in the WBCs. Mutations in these genes have recently been associated with aggressive solid tumors. Genetic heterogeneity was also observed in the WBC population enabling the calculation and subsequent subtraction of background noise associated with WGA of single cells. Molecular information derived from the CTCs is being compared to multiple BMM samples from the same patient. Additional analyses of copy number and structural variations and transcriptomic analysis are being performed in order to gain further insights into the genetic heterogeneity of CTCs and identify genomic markers to establish the utility of CTCs as a non-invasive real-time liquid biopsy for breast cancer. Citation Format: Kellie Howard, Sharon Austin, Arturo Ramirez, Leila Ritter, Debbie Boles, James Cox, Fang Yin Lo, Kerry Deutsch, Christopher Subia, Tuuli Saloranta, Nicole Heying, Heather Collins, Amanda Leonti, Lindsey Maassel, Jackie Stilwell, Eric Kaldjian, Michael Dorschner, Anthony Blau, Marcia Eisenberg, Steven Anderson, Anup Madan. Comprehensive multi-omic analysis of circulating tumor cells isolated from a metastatic triple-negative breast cancer patient to identify pathogenic genomic aberrations. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1609. doi:10.1158/1538-7445.AM2015-1609