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Purpose: As we have published expertise in breast cancer xenograft models and clonal dynamics, our aim was to explore rates of engraftment based on type of tissue for attempted xenografting (primary vs relapsed/metastatic disease) and clinical breast biomarker subtype. Methods: Tissue from patients (pts) enrolled in a locally advanced/metastatic study and a breast tumour tissue repository (ie. resectable primaries) between Sept. 2008 and July 2015 underwent xenografting using NodScid/IL2rgKO (NSG) mice. Xenografts were passaged when tumour volume reached 1 cm3. Mice with no engraftment after 12 months (mos) were sacrificed. Pt charts were reviewed to determine biomarker status (hormone receptor [HR], HER2), date and type of tissue collection for xenografting. Prediction of successful engraftment based on tissue type and biomarker status was performed using nominal logistic regression. Results: A total of 70 tissue samples with known engraftment status were included in the analysis: 51 from primary breast tumour, 10 from relapsed disease (dz) with ≤ 1 line of therapy in the advanced setting and 9 from relapsed dz with > 1 line of therapy in the advanced setting. Tumours from pts treated with > 1 line of therapy were more likely to engraft compared to primary or recurrent dz with ≤ 1 line of therapy (89%, 35%, and 40% respectively; p=.008). HR- primary tumours were more likely to engraft compared to HR+ primary tumours: 71% of HR-/HER2- (triple negative) and 67% of HR-/HER2+ tumours versus 4% of HR+/HER2- and 38% of HR+/HER2+ tumours; p Conclusion: This preliminary study highlights potential differences in successful xenoengraftment based on biomarker status at diagnosis and type of tissue, primary vs relapsed tumour, the latter suggesting that the underlying biology of primary or first relapsed recurrent disease is distinct from more refractory disease, and warrants further exploration. This work is ongoing. (Funded by CBCRA, BCCF) Engraftment of primary tumour vs relapsed disease Primary tumour (N=52) N, (%)Recurrent disease and ≤ 1 line of Rx in advanced setting (N=10) N, (%)Recurrent disease and > 1 line of Rx in advanced setting (N=9) N, (%)Engraftment Yes18 (35)4 (40)8 (89)HR-/HER2-10 (55)1 (25)2 (25)HR-/HER2+4 (22)1 (25)1 (13)HR+/HER2+3 (17)00HR+/HER2-1 (6)2 (50)5 (62)Engraftment No33 (65)6 (60)1 (11)HR-/HER2-4 (12)00HR-/HER2+2 (6)1 (17)0HR+/HER2+5 (15)00HR+/HER2-22 (67)5 (83)1 (100) Citation Format: den Brok W-l, Chia S, Kalloger S, Bates C, Aparicio S, Mar C, Gelmon K, Eirew P. Rates of successful engraftment in breast cancer xenograft models based on tissue type: Primary vs relapsed disease [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-06-10.

Background: Homologous recombination deficiency (HRD) is common in cancer - germline BRCA1 & BRCA2 mutations account for 5-10% of breast cancers and confer 85% lifetime risk. HRD cancers exhibit genomic instability and sensitivity to platinum-based therapy and PARP inhibitors. While not all causes of HRD are known, recent sequencing efforts have revealed genome-wide somatic mutation signatures that characterize the HRD genomic instability phenotype, also known as “BRCA-ness”. This provides a promising new assay to predict sensitivity to platinum-based therapy. Here, we integrate two whole-genome sequencing metrics to assess their association with therapeutic outcomes in a breast cancer cohort. Methods: Whole-genome sequencing of 47 breast cancer tumors (100x coverage) and matched normals (60x) was performed on an Illumina HiSeq. Alignment, assembly, SNV calling, and loss of heterozygosity (LOH) detection were performed with BWA, ABySS, Strelka, and APOLLOH respectively. SNV signatures were deciphered by non-negative matrix factorization with Monte Carlo resampling. An HRD score comprised of LOH, telomeric allelic imbalance (TAI), and large scale transition (LST) counts was computed. Clinical endpoints were obtained by retrospective review of treatment and imaging reports. Analysis is ongoing in an independent validation cohort of 62 sequenced cases. Results: The HRD-linked SNV signature was significantly associated with radiographic clinical response (CR) to platinum-based therapy (p=0.015). Logistic regression demonstrated a 59% improved odds of CR to platinum-based therapy per 1000 somatic SNVs attributed to HRD (odds ratio 1.16-2.50). Tumors carried up to 10,246 such SNVs and all patients with CR were among the top quartile. The LOH-TAI-LST score was correlated with SNV signature (r=0.6, p=7×10-6) and associated with CR (p=0.025). Notably, elevated HRD signatures associated with CR were identified in tumors with wild-type BRCA1/BRCA2 or variants of unknown significance. Tumors with above median HRD signatures were associated with a 69-day longer time to treatment failure and an 18% daily decreased probability of treatment failure per 1000 HRD-attributed SNVs (hazard ratio 0.71-0.95, p = 0.007). Discussion: We found that HRD mutation signatures are associated with clinical response and longer time to treatment failure with platinum-based therapy. While similar benefits were observed in patients with somatic bi-allelic loss of BRCA1/BRCA2, such cases are less common (8% of our cohort) compared to those with elevated HRD signature. Thus, mutation signature methods may identify patients who stand to benefit from platinum-based therapy missed by BRCA screening alone. Citation Format: Eric Y. Zhao, Yaoqing Shen, Erin Pleasance, Katayoon Kasaian, Martin R. Jones, Carolyn Ch'ng, Caralyn Reisle, Peter Eirew, Karen Mungall, Nina Thiessen, Yussanne Ma, Alexandra Fok, Andrew J. Mungall, Yongjun Zhao, Richard Moore, Diego Villa, Tamara Shenkier, Caroline Lohrisch, Stephen Chia, Stephen Yip, Karen Gelmon, Howard Lim, Sophie Sun, Kasmintan A. Schrader, Sean Young, Aly Karsan, Robyn Roscoe, Janessa Laskin, Marco A. Marra, Steven J. Jones. Breast cancer whole genomes link homologous recombination deficiency (HRD) with therapeutic outcomes [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 2473. doi:10.1158/1538-7445.AM2017-2473

Background: In the absence of defined tumor molecular subtypes and validated predictive markers, PDAC has been largely treated as a single disease. Recent studies of molecular subtyping in PDAC [1-4] reveal a complex mutational landscape with data suggesting the presence of genomic and gene expression signatures that may have prognostic and therapeutic significance. However, most of these PDAC datasets consisted of resected tumors, cell lines or xenografts and lack data on metastatic tumors. The aim of this study is to evaluate gene signatures using whole genome sequencing (WGS) and transcriptome (RNA-Seq) data from metastatic biopsy samples in patients with advanced PDAC. Methods: Patients with incurable advanced cancers undergo fresh tumor biopsies for indepth WGS and RNA sequencing as part of an ongoing prospective study (NCT02155621). DNA and RNA extraction and library construction were performed according to standard protocols. Paired-end reads were generated on an Illumina HiSeq2500 sequencer. RNA-Seq expression values were converted into centile expression ranks against the TCGA PDAC dataset. Centile distributions for genes in published signatures were compared by pairwise Wilcoxon-Mann-Whitney tests using one-sided p=0.1 as the significance cutoff. Survival analysis was performed using the Kaplan-Meier method. Results: Molecular data is available for 12 patients with metastatic PDAC; median age 63 years, 6 males, 8 with de novo metastatic disease (67%). 10 tumor samples (83%) were obtained from liver biopsies; average tumor content was 41% (range 24-51%). The average number of structural variants per sample was 125 (range 40-271). Rearrangement-based subtypes [3] were distributed as follows: stable (n=3), locally rearranged (n=1), scattered (n=7) and unstable (n=1). 1 patient harbored a germline BRCA1 185delAG founder mutation but had a stable genotype. Gene expression analysis for classical and basal subtypes similar to those recently described [4] identified 3 and 7 patients with classical and basal expression patterns respectively. Gene signatures were undetermined for 2 patients, where no significant difference in expression of classical or basal signature genes was noted. At median follow-up of 16.7 months, 8 patients had died. Median overall survival was 19.1 vs 7 months in patients with classical and basal subtypes respectively (p=0.078). Conclusion: Despite small patient numbers, gene expression analysis demonstrated the presence of distinct signatures in metastatic PDAC, with a trend towards worse outcomes for patients with a basal expression subtype. Future challenges include prospective validation in larger cohorts, standardization of RNA data acquisition and analysis, and better definition of prognostic and predictive signatures that may be of clinical utility in metastatic PDAC. References 1. Collison E, et al. Nat Med. 2011 [PMID: 21460848] 2. Biankin A, et al. Nature. 2012 [PMID: 23103869] 3. Waddell N, et al. Nature. 2015 [PMID: 25719666] 4. Moffitt R, et al. Nat Genet. 2015 [PMID: 26343385] Citation Format: Hui-li Wong, Joanna M. Karasinska, Martin Jones, Peter Eirew, Kasmintan Schrader, Howard Lim, Yaoqing Shen, Steven Jones, Stephen Yip, Janessa Laskin, Marco Marra, David F. Schaeffer, Daniel J. Renouf.{Authors}. Gene expression analysis demonstrates prognostic subtypes in metastatic pancreatic ductal adenocarcinoma (PDAC). [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B81.

Biallelic pathogenic germline variants in the DNA repair glycosylase, MUTYH, cause MUTYH-associated polyposis, characterised by an increased susceptibility to colorectal adenomas and carcinomas secondary to defective base excision repair. We report a patient diagnosed with Stage IIB distal pancreatic ductal adenocarcinoma (PDAC) at the age of 45 years. Prior colonoscopy and gastroscopy noted three colonic tubular adenomas and a gastric fundic gland polyp. The patient was consented to whole genome and transcriptome sequencing of the PDAC and matched normal blood DNA through the British Columbia Personalized Onco-Genomics (POG) program. Analysis of germline and somatic variants including single nucleotide variants, copy number determination, loss of heterozygosity detection and mutational signatures was undertaken. Expression fold-changes were calculated against Illumina BodyMap pancreatic tissue averages and compared against The Cancer Genome Atlas PDAC cases. Germline analysis revealed biallelic mutations in the MUTYH gene. In light of this patient's personal and family history of adenomatous colon polyps, clinic-initiated panel testing of 14 cancer susceptibility genes, including MUTYH, via Illumina sequencing with reflex Sanger confirmation revealed the same biallelic MUTYH changes. Analysis of the patient's PDAC revealed a base excision repair pathway signature, demonstrated by an increased frequency of C:G>A:T transversions, consistent with deficient MUTYH activity. This is the first association of germline MUTYH biallelic pathogenic variants with PDAC and provides evidence of the contribution of aberrant MUTYH function to the genomic landscape of a PDAC. Detection of the base excision repair mutational signature may be a sensitive way to screen tumors for aberrant MUTYH function that can reveal potential germline MUTYH-related cancer susceptibility, and allow inference of pathogenicity of detected MUTYH variants, which may have cancer prevention and therapeutic implications. Citation Format: Kasmintan A. Schrader, Carolyn Chu’ng, Eric Zhao, Hui-li Wong, Yaoqing Shen, Martin Jones, Tom Thomson, Howard Lim, Sean Young, Carol Cremin, Robert Holt, Peter Eirew, Joanna Karasinska, Jacquie Schein, Yongjun Zhao, Andy Mungall, Richard Moore, Yussanne Ma, Alexandra Fok, Robyn Roscoe, Stephen Yip, Gillian Mitchell, Aly Karsan, Steven Jones, David Schaeffer, Janessa Laskin, Marco Marra, Daniel Renouf. Genomic analysis of pancreatic ductal adenocarcinoma in a patient with MUTYH-associated polyposis. [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 5226.

Purpose: We have expertise in breast cancer xenograft models and have previously published data on clonal dynamics. Our aim was to explore clinical characteristics of those patients (pts) whose breast cancer tumours engrafted versus those that did not. Methods: Tissue from pts enrolled in a locally advanced/metastatic (MBC) study and a breast tumour tissue repository between Sept. 2008 and July 2014 underwent xenografting using NodScid/IL2rgKO (NSG) mice. Xenografts were passaged when tumour volume reached 1 cm3. Mice were sacrificed if no engraftment by 12 months (mos). Pt charts were reviewed to determine biomarker status (hormone receptor [HR], HER2), grade, LVI, time free from disease/progression, and pathologic complete response (pCR) for pts receiving neoadjuvant therapy. Results: A total of 64 pts had known xenograft status: 32 engrafters, 32 non-engrafters. Biomarker status did not predict likelihood of engraftment (p = .0695) and is shown in Table 1 along with site/timing of biopsy for tissue engraftment within biomarker groups. When HER2+ cases are excluded from analysis, the HR-/HER2- phenotype yields a 72% probability of engraftment compared to 39% for the HR+/HER2- group (p = .0418). For engrafters, 22/32 (68%) of pts had or went on to have relapsed or de novo MBC. For non-engrafters, 7/32 (22%) had or went on to have relapsed disease (p = .0004). Grade and LVI did not predict engraftment (p = .1806 and p = .8657 respectively). No grade 1 tumours engrafted (n = 3). There were 25 pts who received neoadjuvant chemotherapy: 14 engrafters, 11 non-engrafters. None of the engrafters achieved a pCR; 3 non-engrafters achieved a pCR. Median time to engraftment was 5 mos for pts with relapsed/advanced disease vs 9.8 mos for pts who did not relapse however, treatment was variable. Conclusion: This preliminary study highlights potential differences in clinical characteristics of engrafters vs non-engrafters in breast cancer xenograft models and warrants further exploration. (Funded by CBCRA, BCCF) TABLE 1.Biomarker status, tissue site/type in attempted xenografts.Engrafter (N = 32) N, (%)Non-engrafter (N = 32) N, (%)HR+/HER2-14 (44)22 (69)Tissue from:Primary tumour419Recurrence23Advanced dz on therapy80HR-/HER2-13 (40)5 (16)Tissue from:Primary tumour114Recurrence21Advanced dz on therapy00HER2+/HR+0 (0)2 (9)Tissue from:Primary tumour02Recurrence00Advanced dz on therapy00HER2+/HR-5 (16)3 (9)Tissue from:Primary tumour42Recurrence01Advanced dz on therapy10 Citation Format: Wendie D. den Brok, Stephen Chia, Cherie Bates, Steve Kalloger, Samuel Aparicio, Mar Mar, Karen Gelmon, Peter Eirew. Clinical characteristics of breast cancer xenograft models. [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 638.

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

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

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