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Given the success of targeted agents in specific populations it is expected that some degree of molecular biomarker testing will become standard of care for many, if not all, cancers. To facilitate this, cancer centers worldwide are experimenting with targeted “panel” sequencing of selected mutations. Recent advances in genomic technology enable the generation of genome-scale data sets for individual patients. Recognizing the risk, inherent in panel sequencing, of failing to detect meaningful somatic alterations, we sought to establish processes to integrate data from whole-genome analysis (WGA) into routine cancer care. Between June 2012 and August 2014, 100 adult patients with incurable cancers consented to participate in the Personalized OncoGenomics (POG) study. Fresh tumor and blood samples were obtained and used for whole-genome and RNA sequencing. Computational approaches were used to identify candidate driver mutations, genes, and pathways. Diagnostic and drug information were then sought based on these candidate “drivers.” Reports were generated and discussed weekly in a multidisciplinary team setting. Other multidisciplinary working groups were assembled to establish guidelines on the interpretation, communication, and integration of individual genomic findings into patient care. Of 78 patients for whom WGA was possible, results were considered actionable in 55 cases. In 23 of these 55 cases, the patients received treatments motivated by WGA. Our experience indicates that a multidisciplinary team of clinicians and scientists can implement a paradigm in which WGA is integrated into the care of late stage cancer patients to inform systemic therapy decisions.

Background Breast cancer is a complex disease with clinical, pathological, and molecular heterogeneity. Recent studies have identified several subtypes of breast cancers driven by specific molecular pathways that can be inhibited by targeted drugs. We studied the feasibility of using molecular data from whole genome and transcriptome sequencing of breast cancers to guide treatment. Methods Patients were consented as part of the Personalized Onco-Genomics (POG) study at the British Columbia Cancer Agency. Fresh tumor, blood for normal DNA, and archival tumor were collected. Tissue and blood samples were sequenced using the Ion Torrent AmpliSeq panel, followed by comprehensive DNA and RNA sequencing. In-depth bioinformatic analyses were performed. Somatic mutations, copy number changes, structural variants and gene expression were characterized. Results from genomic analyses were reviewed in a multi-disciplinary team. Results From August 2012 to October 2014, tissue samples from 30 patients with advanced stage breast cancer were analyzed. The median age at diagnosis was 53 years (range 32-75). The median number of lines of cytotoxic therapy prior to sequencing was 2 (range 0-10). All cases were invasive ductal carcinoma; 63% were ER+ and HER2-; 27% triple negative; 7% ER+ and HER2+; and 3% ER- and HER2+. The most frequently mutated genes were TP53 (67%), PI3KCA (23%), ESR1 (20%), ATM (10%), ARID1A (10%), and BRCA1/2 (10%). Somatic mutations in other genes of interest including HER2, PARP1, NF1, BAP1, PTEN, NOTCH1, were also identified. Molecular data were informative for patient care and/or actionable to guide treatment in 57% (17/30) of cases. Conclusion The use of whole genome sequencing technology to identify valuable molecular information to guide personalized breast cancer treatment is feasible. Further studies are warranted to evaluate the usefulness of genome-wide sequencing of breast cancers in clinical practice. Citation Format: Sophie Sun, Karen A. Gelmon, Stephen Chia, Caroline Lohrisch, Tamara Shenkier, Diego Villa, Yaoqing Shen, Martin Jones, Erin Pleasance, Katayoon Kasaian, Peter Eirew, Sreeja Leelakumari, Yusanne Ma, Tony Ng, Stephen Yip, Steven JM Jones, Marco A. Marra, Janessa J. Laskin. Personalized oncogenomics in advanced stage breast cancer. [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 1122. doi:10.1158/1538-7445.AM2015-1122

Elucidation of the cellular and molecular mechanisms that maintain mammary epithelial tissue integrity is of broad interest and paramount to the design of more effective treatments for breast cancer. Evidence from both in vitro and in vivo experiments suggests that mammary cell differentiation is a hierarchical process originating in an uncommitted stem cell with self-renewal potential. However, analysis of the properties and regulation of mammary stem cells has been limited by a lack of methods for their prospective isolation. Here we report the use of multi-parameter cell sorting and limiting dilution transplant analysis to demonstrate the purification of a rare subset of adult mouse mammary cells that are able individually to regenerate an entire mammary gland within 6 weeks in vivo while simultaneously executing up to ten symmetrical self-renewal divisions. These mammary stem cells are phenotypically distinct from and give rise to mammary epithelial progenitor cells that produce adherent colonies in vitro. The mammary stem cells are also a rapidly cycling population in the normal adult and have molecular features indicative of a basal position in the mammary epithelium.

The Personalized Oncogenomics initiative at the British Columbia Cancer Agency aims to identify tumor-specific therapeutic targets in cancer patients with late stage disease who have failed standard therapy. Comprehensive profiling of individual patients' tumor(s) at the DNA and RNA level allows for characterization of altered pathways and hence identification of therapeutics designed to specifically target them. Data for each individual study included whole genome and transcriptome sequence of the fresh biopsy and whole genome sequence of patient's blood. When tissues were available, transcriptome of a matched normal sample and genome of the commonly formalin-fixed paraffin-embedded primary tumor were also sequenced. All sequencing experiments were performed on Illumina machines. Genomic data was examined, depending on the case, for germline and/or somatic mutations. These included single nucleotide variants, small insertions and deletions and copy number variations. All sequence data were assembled de novo in order to identify rearrangements causing gene fusions; transcriptome data also revealed allelic expression of variants and provided a profile for the entire transcribed genome. Differential abundance estimation was run against a rich repository of publicly available data from The Cancer Genome Atlas project and transcriptome datasets available in-house. The variants and pathways were then mapped to drug databases as well as clinical trial records. This was followed by an extensive literature search for evidence of drug combinations, drug-drug interactions and efficacy of a drug for a particular cancer type, especially those not recognized as the approved disease group for the drug under consideration. The project has sequenced 50 patients; the average length of time between acquiring the biopsy and delivering a report to clinical oncologists was 37 days. Bioinformatic analysis of the sequence data led to identification of informative or actionable targets in up to 80% of cases. The findings were not restricted to target identification but also led to change of diagnosis, treatment and characterization of tumor evolution. De novo assembly of the data in a non-small cell lung cancer patient led to the identification of the well-characterized EML4-ALK oncogenic fusion which had been missed through the use of clinically approved fluorescence in situ hybridization test. Analysis of two separate malignant masses in another patient revealed two divergent and unique tumors. Two different therapeutic were prescribed in order to target these; this led to the disappearance of both tumors and disease stabilization for 7 months. Through the design of an efficient and automated bioinformatics pipeline, individual patient's tumor specimen(s) were profiled in a clinically relevant time frame. This in turn enabled the delivery of targeted therapies and disease stabilization in patients who had no remaining standard therapeutic options. Citation Format: Katayoon Kasaian, Yaoqing Shen, Sreeja Leelakumari, Peter Eirew, Yvonne Y. Li, Erin Pleasance, Richard Corbett, Karen L. Mungall, Jacquie Schein, Andrew J. Mungall, Yongjun Zhao, Richard A. Moore, Stephen Yip, Karen Gelmon, Howard Lim, Daniel Renouf, Robyn Roscoe, Yussanne Ma, Marco A. Marra, Janessa Laskin, Steven JM Jones. Bioinformatic analyses approaches for personalized oncogenomics. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5340. doi:10.1158/1538-7445.AM2014-5340

Background: It is increasingly common to use targeted cancer panels to assess for informative or actionable targets to guide cancer treatment. We compared the utility of information obtained from such a panel compared to whole genome and transcriptome sequencing. Methods: Eligible subjects with incurable cancers for whom there were limited or no standard chemotherapy options, have several samples analyzed: a fresh tumour biopsy; a blood sample for normal comparison; and archival tumours when available. Samples underwent both the Ion Torrent AmpliSeq cancer panel analysis and comprehensive DNA (80X) and RNA sequencing followed by in-depth bioinformatic analysis to identify somatic mutations, copy number alterations, structural rearrangements, and corresponding gene expression changes that may be cancer “drivers” or provide informative (diagnostic) or actionable/druggable targets. Aberrant pathways were matched to drug databases and manual literature reviews undertaken to identify drugs that may be useful or potentially contraindicated; a report is generated and discussed in a multidisciplinary team. Results: Between July 2012 - November 2013, 51 subjects have consented and 45 have been sequenced: 12 breast, 7 lung; 4 colorectal, 3 squamous, 3 adrenal; 2 pancreas; 2 sarcomas, and 1 of each of nasopharynx, primary unknown, CLL-peripheral mantle cell, parotid, anal, appendix, peripheral T-cell, prostate, ovary, endometrial, glioma, and mesothelioma. The median number of lines of chemo prior to sequencing was 3. Of the first 40 cases, the panel did not yield informative or actionable results in 60% of cases: 36% of the cases the panel did not detect any somatic variants and in a further 24% TP53 mutations were the only variants identified. In the other 40% of cases, the panel might have identified an informative abnormality but when put into context of the pathways that can be drawn with the whole genome and transcriptome data the detected panel abnormalities were not comprehensive enough to guide treatment decisions. Examples include: in two colon cancer patients the panel detected a KRAS mutation in one and a RET mutation in the other, however both were actually inactivating mutations and therefore unlikely to be good targets. In contrast, the full genomic data was informative in 70% of cases and treatments were delivered based on the results in 60%, in this heavily pretreated population. Conclusions: The future of cancer medicine lies in genomic profiling to assist therapeutic decision-making. The cancer panel has advantages in terms of speed and cost; however it has not been as informative for identifying candidate druggable driver events and it has missed critical genomic abnormalities that have changed diagnoses. Given the complexity of the cancer genome it is our observation that the panels do not provide the depth and context required to make treatment decisions for the majority of patients with cancer. Citation Format: Janessa J. Laskin, Yaoqing Shen, Howard Lim, Karen A. Gelmon, Daniel Renouf, Stephen Yip, David Huntsman, Anna Tinker, Cheryl Ho, Stephen Chia, Yvonne Li, Katayoon Kasaian, Peter Eirew, Sreeja Leelakumari, Richard Moore, Samuel Aparicio, Yusanne Ma, Steven Jones, Marco Marra. Whole genome sequencing is superior to cancer panels to aid in decision-making in patients with advanced malignancies. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4283. doi:10.1158/1538-7445.AM2014-4283

Aim: Tumour heterogeneity poses a significant challenge to the success of treatment; tumours with similar histological features may have substantially different biological drivers. This analysis is part of a study in which we use whole genome and transcriptome sequencing to aid in therapeutic decision-making in patients (pts) with advanced cancers. Analysis of tumours at different time points is an integral feature to our study design. Methods: Eligible pts with incurable cancers with limited or no standard chemotherapy options, have several samples analyzed: a fresh tumour biopsy; a blood sample for normal comparison; and archival tumours if available. Samples undergo comprehensive DNA (40X-80X) and RNA sequencing (fresh biopsy) and in-depth bioinformatic analysis to identify somatic mutations, copy number alterations, structural rearrangements, and corresponding gene expression changes that may provide informative (diagnostic) or actionable targets. Results: Between July 2012- May 2014, 80 pts have consented, representing 28 different tumour types. Median number of lines of chemo prior to sequencing was 3. Of the 51 pts analyzed, 21 have matched archival and fresh biopsy material. Typically the archival material is from the primary and the fresh tissue is from a metastatic site. We compared the genetic variants between the primary tumors and metastases, and those identified in both samples. The number of shared non-synonymous single nucleotide variants (SNV) between the archival and fresh samples varied considerably from 0 to 117 with the most overlap observed in the 3 colorectal cancer pts. In the pts with no shared SNV, germline variants, copy number profiles and other variants clearly demonstrated the metastatic biopsy was from the same primary. Non-synonymous SNV were detected in individual pt DNA in both the fresh biopsy (range 21-423) and the archival (range 7-338). These included actionable variants in genes such as KRAS, TP53 and BRCA2. There was the suggestion that some genes may be more stable over time (TP53). Conclusions: Our data demonstrates the large and variable heterogeneity of advanced cancer when compared to archival samples. This included important actionable and druggable targets that would influence treatment decisions. This highlights the importance of repeat biopsies to guide treatment decisions wherever possible. Disclosure: All authors have declared no conflicts of interest.

11026 Background: We used information obtained from whole genome and transcriptome sequencing to aid in therapeutic decision-making in patients (pts) with advanced cancers. Methods: Eligible pts wi...

e22078 Background: mCRC carries a high mortality rate, and invariably becomes resistant to treatment. Whole genome sequencing (WGS) of DNA and RNA, and bioinformatic analysis can be performed in a ...

Reactive oxygen species (ROS) are known mediators of DNA damage and likely contributors to oncogenesis. However, very little is known about the mechanisms controlling ROS in the cells that make up the normal human mammary gland, in spite of its being a major site of cancer development. To investigate how ROS are generated and their potential role in two functionally distinct, primitive normal human mammary epithelial cell compartments (luminal and basal), we isolated these subsets at high purities by FACS and compared the levels within them of ROS, components that positively and negatively regulate ROS, their responses to oxidative stressors and evidence of ROS-associated DNA damage. The results show that purified progenitors of the cells that line the gland lumen (defined by their EpCAM+ CD49f+ phenotype) contain significantly higher levels of superoxide (O2*) anions and H2O2 than the basal cells (defined as EpCAMlow/- CD49fhigh cells and highly enriched in bipotent progenitors and stem cells). We also find that the elevated levels of these ROS elements in the luminal progenitors are associated with a higher content of mitochondria and higher levels of all 3 superoxide dismutases (SOD-1, 2 and 3). The luminal progenitors are also highly resistant to glutathione depletion and express higher levels of both non-canonical non-glutathione anti-oxidant enzymes and multiple enzymes that control ROS-induced nucleotide damage (i.e., OGG-1, MTH-1, MUTYH) providing a likely explanation for their ability to survive following GSH depletion. Interestingly, we found the mitochondrial antioxidant glutathione peroxidase (GPX)-2 enzyme to be expressed almost exclusively and at high levels in basal mammary cells and its depletion, using a shRNA lentivirus, resulted in loss of progenitor viability/activity by basal but not luminal cells. Luminal progenitors also displayed greater resistance to acute oxidative insults (H2O2 and X-radiation) and displayed an increased accrual of oxidative damage-induced (genomic 8-oxo-dGTP) mutations. Our findings reveal a major difference in the molecular machinery that control ROS levels in normal human basal and luminal mammary progenitors. These correlate with an ability of the luminal progenitors to maintain and tolerate elevated levels of ROS and the continuous acquisition of unrepaired ROS-induced DNA damage, thus suggesting a novel and previously unanticipated vulnerability of these cells to undergo oncogenic transformation. (Supported by Canadian Breast Cancer Foundation/BC-Yukon and the Canadian Cancer Society) Citation Format: Nagarajan Kannan, Maisam Makarem, Long Nguyen, Jeff Dong, Peter Eirew, Connie Eaves. Different ROS control mechanisms and mutagenic consequences in primitive subsets of normal human mammary cells. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2919. doi:10.1158/1538-7445.AM2013-2919