An Analytical Framework Characterizes the Biological Processes that Shape Copy Number-Based Genome Instability Patterns in Breast Cancer.

Copy number alterations (CNAs), involving the acquisition and loss of DNA segments, are common genetic changes associated with cancer initiation and genomic instability (GI). Similar to single base substitutions, CNAs in cancer genomes often accumulate non-randomly, linked to aberrant DNA damage and repair mechanisms. Investigating higher-order CNA patterns, especially in CNA-prone malignancies like breast cancer, offers insights into GI's nature, causes, and clinical implications. While GI is historically described using predefined scores or de novo CNA signature extraction, these approaches haven't been comprehensively combined and profiled in genomically diverse diseases such as breast cancer. Fourteen pre-existing CNA scores depicting diverse GI phenomena were reintegrated within a unified computational framework. Applied to a large cohort of breast cancer patients (n = 2, 763) from TCGA and METABRIC, this framework, along with de novo CNA signature extraction, identified eight robust signatures. CNA scores and signature activities were associated with genomic features and clinical information, including subtype and patient outcomes. Breast cancer oncogenes such as ESR1, CCND1, and IKBKE were preferentially amplified by tandem duplication in a subtype-dependent manner. Additionally, two CNA signatures were characterized as harboring relatively few CNAs ("CNA quiet") within diploid and tetraploid genomes, respectively, with the latter representing an unreported subset of whole genome doubled tumors. Samples with a combination of CNA quiet genomes and low macrophage infiltration exhibited significantly better survival outcomes, independent of standard clinical risk factors. Intriguingly, several signatures coincided with the inactivation of BRCA1/2, genes critical for proficient homologous recombination (HR). These signatures showed differential activity in samples lacking BRCA1 and BRCA2, indicating a potential gene-specific CN pattern of HR deficiency. Segments assigned to another signature exhibited substantial overlap with chromothripsis-like patterns and extrachromosomal DNA (ecDNA), suggesting a common process underlying the generation of these complex GI phenomena. These findings emphasize how exploring scores and signatures can elucidate diverse mechanisms underlying CNA-driven GI in breast cancer. The relative activities of these signatures may hold notable prognostic potential, especially when integrated with other clinically relevant data modalities such as immune cell infiltration. Overall, comprehensive profiling of higher-order CNA patterns in breast cancer can not only uncover the diversity and sources of GI but also provides translational impact. Citation Format: Hannan Wong, Anna Korsakova, Andy Wu, Akila Perera, C. Pawan K. Patro, Shangying Chen, Shwetha Sundararaman, Vinay Warrier, Daniel G. Tenen, Jason J. Pitt. Copy number-based instability in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2410.

Unprecedented intensity in the investigation of cancer genomes over the past 20 years has firmly established genome instability as a central hallmark of cancer. Publications from international consortia, particularly The Cancer Genome Atlas (TCGA), have painstakingly cataloged the genomic alterations that are frequently observed in all major cancer types (1-5). There are two primary categories of genome alterations: mutations at the nucleotide level and alterations at the level of chromosomal copy number (deletion and amplification). In some cancer types, such as colorectal cancer (CRC), genomic instability can be broadly classified as having chromosome instability (CIN) or microsatellite instability (MSI) (6,7). Whereas a majority of research investigation and drug development has been targeted on missense mutations (8,9), CIN has clearly been shown to play a key role in cancer development and progression and is associated with poor prognosis and drug resistance (10,11). Therefore, copy number alterations represent a wellspring for both research and therapeutics that have been underexplored. In this regard, nucleotide mutations and copy number alterations are really two sides of the same genomics instability coin for tumorigenesis. With the recent realization of the “randomness” in gene mutations due to replication errors in cancer (12), perhaps copy number alterations provide less randomness in therapeutic design.

Background: Triple-negative breast cancer (TNBC) comprises 10%-20% of invasive breast carcinoma cases. Patients with TNBC exhibit poorer 5-year survival and higher rates of metastasis and recurrence than patients with other breast cancer subtypes. TNBC is further divided based on gene expression profiling into androgen receptor (AR)-positive (AR+) TNBC and AR-negative TNBC (or quadruple-negative breast cancer [QNBC]). While AR is an emerging therapeutic target for AR+ TNBC, there are no treatment options for QNBC. AR expression is associated with favorable disease-free, overall, and recurrence-free survival in patients with TNBC, suggesting that AR loss in TNBC tumors confers an aggressive disease course. Genomic instability has been recognized as one of the drivers of tumorigenesis and can be evidenced by the presence of chromosomal instability, such as DNA copy number alterations (CNAs). Although there are many studies characterizing the genomic profiles of TNBCs, little is known about the tumor biology and genetic makeup of QNBCs. In this study, we explored the impact of CNAs on microRNA (miRNA) expression and, subsequently, on signaling pathways associated with QNBC aggressiveness and clinical outcomes. Methods: AR expression was immunohistochemically assessed in tissues of 53 patients with TNBC from the Histopathology and Tissue Shared Resources of Georgetown University. AR positivity was defined as AR expression in >1% of cells. Genome-wide copy number profiling of formalin-fixed paraffin-embedded samples was performed using the Agilent SurePrint G3 Human CGH Microarray, and miRNA expression analysis was conducted using NanoString nCounter Human v3a miRNA Expression Assay. Differentially expressed miRNAs between TNBC and. QNBC samples were integrated with array CGH data from the same tissue sample to identify common gene targets that may be affected by both CNAs and miRNA deregulation. Functional enrichment analysis was performed to identify cancer pathways deregulated in QNBC. The expression levels of Centrosome Amplification 20 (CA20) and Chromosome Instability 25 (CIN 25) gene signatures were evaluated in 524 primary invasive breast cancers from The Cancer Genome Atlas (TCGA) database. Results: We observed that 64% of TNBC samples lacked AR expression and that QNBCs exhibited a significantly higher CNA level (p<0.05) and frequency (p<0.0001) compared with TNBCs. Gains at 1q21-q44, 6p25.3-p12.1, 8q11.1-q24.3, 9p24.3-p13.1, 10p15.3-p11.1, and 12p13.33-p11.1 were common CNAs observed in >50% of QNBCs. Additionally, CNAs affecting genes of the CIN25 signature were significantly higher in QNBC than in TNBC; however, CNAs in CA20 signature genes were similar in QNBC and TNBC samples. Notably, the expression levels of CA20 and CIN25 genes were significantly higher in QNBC than in TNBC. Moreover, we identified 184 differentially expressed miRNAs between QNBC and TNBC samples (p<0.05, FDR<0.25). Among these miRNAs, 15 were mapped at cytobands with CNAs, and eight (miR-23c, miR-548ai, miR-567, miR-613, miR-943, miR-1204, miR-1265, and miR-1267) presented concordance between their expression levels and CNAs. The target genes of these eight miRNAs were associated with genomic instability, cell cycle, and DNA damage response. Importantly, the combined expression levels of these eight miRNAs robustly discriminated between TNBCs and QNBCs with an area under the curve of 0.946. Conclusions: Our study highlights that loss of AR expression in TNBC is associated with profound genomic instability as evidenced by CNAs and deregulation of miRNA expression, which leads to upregulation of signaling pathways associated with cancer aggressiveness. Citation Format: Shristi Bhattarai, Bruna M. Sugita, Luciane Cavalli, Ritu Aneja. Androgen receptor loss is associated with genomic instability characterized by copy number alterations and mirna deregulation in triple-negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-09-13.

Breast cancer (BC) stands as the foremost female malignancy globally and is the most prevalent cancer in numerous developing countries, particularly in sub-Saharan Africa (SSA). Over the past decade, significant strides in comprehending the pathobiology of the disease and tumour dynamics have greatly enhanced treatment options, particularly in industrialized nations. Regrettably, SSA countries have witnessed only marginal, if any, improvements, with mortality rates surpassing incidence rates. Unfavourable outcome, early onset and high-grade tumours are predominant in SSA. Despite these challenging clinical phenotypes, there is currently a limited understanding of the primary molecular drivers, primarily due to a dearth of reliable data. Furthermore, there is a paucity of research conducted in, and pertinent to, the challenges of the disease in low-income countries (LICs), despite a rising incidence and higher mortality-to-incidence ratios. We thus established an international translational cancer research consortium in five distinct African countries. This initiative has contributed to the creation of a high-quality repository of biomaterials. Additionally, we have conducted whole exome sequencing on the initial 100 cases of breast cancer, comparing the molecular architecture of these tumors with data from The Cancer Genome Atlas (TCGA). We examining and compared the clinical disease phenotypes between indigenous African women and Western patients. A higher proportion of grade III tumors was observed in African patients aged between 30 to 59 years as compared to other patients within the same age group. In comparative molecular analyses, we found a significantly elevated tumor mutational burden in African patients (median of >15/MB) in contrast to other populations within the TCGA (median ~ 0.7/MB). Gene sets featuring co-occurring mutations, predicted to be associated with survival using the TCGA dataset, showed high mutation rates in the African cohort. Notably, co-occurring mutations between PIK3CA and genes linked to genomic instability, such as BIRC6 (HR: 11.7, p = 2.7e-05), KMT2C (HR: 4.7, p = 4.01e-04), NEB (HR: 3.84, p = 0.48), and PCLO (HR: 4.9, p = 0.016), among others, strongly correlated with poor overall survival and were highly mutated within the African cohort. Interestingly, within the TCGA, patients with early breast cancer onset exhibit twice as many mutations in KMT2C, a gene known for its association with DNA damage repair, genomic instability, and showed an improved response to immune checkpoint inhibition. These initial findings suggest that breast cancer genomics in indigenous African populations may exhibit substantial differences, potentially warranting consideration for distinct therapeutic modalities for these patients. Citation Format: Smiths Sengkwawoh Lueong, Pamela Derliche Tonouo Derliche Tonouo, Arnol Auvaker Tiofack, Rovaldo Nguims Kenfack, Jules Roger Kuiate, Esther Dina Mbassi, Sidonie Noa Ananga, Etienne Okobalemba Atenguena, Gustave Simo, Abdel Jelil Njouendou, Walters Ndaka, Zacharie Sando, Emmanuella Mayemi, Rachel Tayou, Gilles Gael Aghoagni, Anne Sango, Benjamin Pokam, Augustin Tozoula Bambara, Jens T. Siveke. Comparative genomics of breast cancer in indigenous African and western populations first results from the E-Predict study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3929.

Lessons from the Cancer Genome

Cancer genomics consortia have identified somatic drivers of breast cancer subtypes. However, these studies have predominantly included older, non-Black women, and the related socioeconomic status (SES) data are limited. Increased representation and depth of social data are crucial for understanding how health inequity is intertwined with somatic landscapes. Here, we conducted targeted sequencing on primary tumors from the Carolina Breast Cancer Study (N = 357; 52% Black; 47% <50) and compared the results with The Cancer Genome Atlas (N = 948; 18% Black; 27% <50). Race (Black vs. non-Black), age, and SES were evaluated in association with mutations, copy number alterations, and aneuploidy using generalized linear models. Pathway dysfunction was also assessed by aggregating mutation and copy number alterations. Adjusting for age, Black participants (N = 350) were significantly more likely to have TP53 and FAT1 mutations and less likely to have PIK3CA, CDH1, DDR2, and GATA3 mutations than non-Black participants. Younger participants had more GATA3 alterations and fewer KMT2C, PTEN, MAP3K1, and CDH1 alterations. Black participants had significant enrichment for MYC (8q) and PIK3CA (3q26) amplifications and higher total aneuploidy, but age was not associated with copy number variation. SES was associated with different patterns of alteration in Black versus non-Black women. Overall, Black participants showed modest differences in TP53, PIK3CA, and other alterations that further varied by SES. Race is a social construct, and varying distributions of etiologic factors across social strata may predispose Black, young, and low SES women to cancer subtypes characterized by these alterations. Significance: The collection and analysis of DNA sequencing with comprehensive socioeconomic factor associations in a large Black breast cancer patient cohort could help uncover mechanisms by which social conditions contribute to tumor biology.

Pan-cancer analysis of non-coding transcripts reveals the prognostic onco-lncRNA HOXA10-AS in gliomas.

Background: At present, conventional clinical and histopathological evaluations are not sufficient to distinguish biologically indolent cancers from those that will exhibit aggressive behavior. We hypothesize that global transcriptomic activity of tumor cells reflects the end cumulative result of somatic, germline, and epigenetic alterations, as well as additional transcriptional regulatory events. Therefore, it may be more directly associated with clinical outcomes. However, the total number of mRNA molecules is not directly measurable, either in bulk or single-cell RNA sequencing data. To this end, we develop a novel metric: the transcriptional activity score (TAS), to measure the relative global tumor-cell specific transcriptional activity in heterogeneous tumor samples. Materials and Methods: We propose TAS as the ratio of average total transcript proportion over the count proportion of tumor cells versus surrounding non-tumor cells. The transcript proportions are estimated using RNAseq deconvolution method DeMixT and the count proportions are estimated using DNAseq deconvolution methods such as ASCAT and ABSOLUTE. Using matching bulk RNA and DNA sequencing data from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), we calculated TAS for a total of 5,031 patient samples across 15 cancer types. For validation, we obtained TAS for two genomic studies: 1) from patients with early-onset prostate cancer (n=99) as part of the ICGC, and 2) from patients with localized prostate cancer as part of the Canadian Prostate Cancer Genome Network (CPC-GENE, n=144). Results: We found that higher TAS corresponds to a more aggressive state of cancer, as characterized by MYC dysregulation, genome instability, known marker genes, and molecular subtypes. By examining the association between TAS and survival outcomes across cancer types, we also found that TAS refines the prognostic ability of pathologic stage, identifying aggressive early-stage tumors associated with poor survival as well as late-stage tumors with favorable outcomes. In prostate cancer, TAS is linearly associated with progression-free probabilities, useful to rank patients within the median risk group (Gleason score = 7). This added prediction power is consistent in TCGA and two independent validation data (ICGC and CPC-GENE). Conclusion: We have developed a new summary metric using matched DNA and RNA sequencing data from tumor samples, to compute, in vivo and using deconvolution, the relative global gene expression level of tumor cells. The TAS metric evaluates global transcriptional activity, an intrinsic behavior of cells that is well-known, but now for the first time is shown through TAS to be associated with prognosis. TAS may serve as a tractable phenotype to help elucidate the biology that underlies metastasis, prognosis and response to treatment in cancer patients. Citation Format: Shaolong Cao, Jennifer R. Wang, Jonas Demeulemeester, Jingxiao Chen, Kaixian Yu, Peng Yang, Bora Lim, Alfonso Urbanucci, Peter Campbell, Hongtu Zhu, Peter Van loo, Wenyi Wang. Global tumor transcriptional activity reveals aggressiveness across multiple cancers [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 829.

Simultaneous Integration of Multi-omics Data Improves the Identification of Cancer Driver Modules.

Background: The role of long-chain noncoding RNA (lncRNA) in genomic instability has been demonstrated to be increasingly importance. Therefore, in this study, lncRNAs associated with genomic instability were identified and kidney renal papillary cell carcinoma (KIRP)-associated predictive features were analysed to classify high-risk patients and improve individualised treatment. Methods: The training (n = 142) and test (n = 144) sets were created using raw RNA-seq and patient’s clinical data of KIRP obtained from The Cancer Genome Atlas (TCGA).There are 27 long-chain noncoding RNAs (lncRNAs) that are connected with genomic instability, these lncRNAs were identified using the ‘limma’ R package based on the numbers of somatic mutations and lncRNA expression profiles acquired from KIRP TCGA cohort. Furthermore, Cox regression analysis was carried out to develop a genome instability-derived lncRNA-based gene signature (GILncSig), whose prognostic value was confirmed in the test cohort as well as across the entire KIRP TCGA dataset. Results: A GILncSig derived from three lncRNAs (BOLA3-AS1, AC004870, and LINC00839), which were related with poor KIRP survival, was identified, which was split up into high- and low-risk groups. Additionally, the GILncSig was found to be an independent prognostic predictive index in KIRP using univariate and multivariate Cox analysis. Furthermore, the prognostic significance and characteristics of GilncSig were confirmed in the training test and TCGA sets. GilncSig also showed better predictive performance than other prognostic lncRNA features. Conclusion: The function of lncRNAs in genomic instability and the genetic diversity of KIRP were elucidated in this work. Moreover, three lncRNAs were screened for prediction of the outcome of KIRP survival and novel insights into identifying cancer biomarkers related to genomic instability were discussed.

834 Background: The expression of protein kinase CK2 subunits (CSNK2A1, CSNK2A2, CSNK2A3, and CSNK2B) in gastrointestinal cancers has not been fully characterized. In this study, we seek to evaluate how changes in CK2 subunit expression are associated with GI cancer clinical characteristics and genetics. Methods: Data analysis was performed with data from The Cancer Genome Atlas (TCGA). R version 4.2.2 was used for analysis. We provide an analysis of several cancer cohorts looking at CK2 subunit expression, as well as cancer mutations, copy number alterations, and clinical characteristics. Results: From the TCGA datasets containing mRNA expression data, we assessed hepatocellular carcinoma (n=361), colorectal adenocarcinoma (n=339), gastric adenocarcinoma (n=306) and diffuse type gastric adenocarcinoma (n=69), pancreatic adenocarcinoma (n=169), esophageal adenocarcinoma (n=89) and squamous cell carcinoma (n=95), and cholangiocarcinoma (n=36). We explored associations between CK2 subunit expression and GI cancer-specific known driver mutations, of which we report the following significant findings (p &lt; 0.05 for all). Mutations in TP53 were associated with increased expression of CSNK2A1 in hepatocellular carcinoma and stomach adenocarcinoma, increased CSNK2A2 in colorectal adenocarcinoma, and CSNK2B in colorectal adenocarcinoma, pancreatic adenocarcinoma, and stomach adenocarcinoma. Mutations in KRAS were associated with increased expression of CSNK2A1 and CSNK2B in pancreatic adenocarcinoma. Mutations in BRAF were associated with decreased expression of CSNK2A2 and CSNK2B in colorectal adenocarcinoma. We also noted significant changes in CSNK2 subunit expression when looking at mutations and copy number alterations in signaling pathways such as Wnt, NOTCH, PI3K, TGFβ, and more. We also explored associations between CK2 subunit expression and GI cancer clinical characteristics, of which we report the following significant findings (p &lt; 0.05 for all). In colorectal adenocarcinoma, increased CSNK2A2 expression was associated with lymph node invasion and advanced clinical stage. In hepatocellular carcinoma, increased CSNK2A1 and CSNK2A3 expression was associated with greater tumor grade, tumor size, and more advanced clinical staging. Increased CSNK2A2 expression was associated with greater tumor size, more advanced clinical staging, and vascular invasion. Increased CS2NKB expression was associated with increased tumor grade, size, and vascular invasion. In pancreatic adenocarcinoma, increased CSNK2A3 expression was associated with a worse response to the first treatment course. Conclusions: Our results suggest that changes in protein kinase CK2 expression are associated with different cancer clinical characteristics as well as cancer-specific mutations and signaling pathways.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced extensive mass spectrometry-based proteomics data for selected breast, colon, and ovarian tumors from The Cancer Genome Atlas (TCGA). We have incorporated the CPTAC proteomics data into the cBioPortal to support easy exploration and integrative analysis of these proteomic datasets in the context of the clinical and genomics data from the same tumors. cBioPortal is an open source platform for exploring, visualizing, and analyzing multidimensional cancer genomics and clinical data. The public instance of the cBioPortal (http://cbioportal.org/) hosts more than 200 cancer genomics studies, including all of the data from TCGA. Its biologist-friendly interface provides many rich analysis features, including a graphical summary of gene-level data across multiple platforms, correlation analysis between genes or other data types, survival analysis, and per-patient data visualization. Here, we present the integration of the CPTAC mass spectrometry-based proteomics data into the cBioPortal, consisting of 77 breast, 95 colorectal, and 174 ovarian tumors that already have been profiled by TCGA for mutations, copy number alterations, gene expression, and DNA methylation. As a result, the CPTAC data can now be easily explored and analyzed in the cBioPortal in the context of clinical and genomics data. By integrating CPTAC data into cBioPortal, limitations of TCGA proteomics array data can be overcome while also providing a user-friendly web interface, a web API, and an R client to query the mass spectrometry data together with genomic, epigenomic, and clinical data.

Background: Aberrant signaling via the PI3K pathway is a common alteration in breast cancer (BC), with frequent activating mutations in the PIK3CA gene helical (exon 9) and catalytic (exon 20) domains. These mutations occur across all BC subtypes with an overall incidence of 36%, with the highest frequency (∼45%) in luminal A/ER+ tumors. Lobular phenotype is common among luminal A tumors. We examined associations between lobular histology and molecular features among BC samples submitted for comprehensive molecular analyses for The Cancer Genome Atlas (TCGA). Design: Experts in breast pathology reviewed digital slides of breast cancer samples submitted for comprehensive molecular profiling to the TCGA. Tumors were graded, subtyped and scored for additional histopathologic features. We tested pairwise associations between lobular features and components of grade, PAM50-derived molecular subtype and mutational status for BRAC1/2, PIK3CA, TP53 and CDH1 by performing Chi-Square analysis for comparisons with a categorical variable and the Mann-Whitney test for comparisons with an ordinal variable Results: A total of 1132 images were scored from 589 unique cases in TCGA. For cases with multiple scorers (43% of cases), we summarized scores by taking the median (for ordinal variables) or the consensus diagnosis (for categorical variables). A total of 567 cases had a consensus diagnosis for lobular features, all of which had pathological information on components of histologic grade and 540 of which had data for TP53, CDH1, and PIK3CA mutations. 110/567 (19%) of cases were classified as invasive lobular or invasive mammary carcinoma with lobular features. The lobular cases had significantly less nuclear pleomorphism (p = 3.3 e -12), lower mitotic index (p = 3.4e-16), less tubule formation (p = 3.9e-8), increased association with lobular carcinoma in situ (p &amp;lt; 2.2 e-16), decreased stromal inflammation (p = 1.5e-7), and decreased necrosis (p = 4.4e-11) compared with cases without lobular features. Cases with lobular features were highly enriched for CDH1 mutations with 19% of cases with lobular features having CDH1 mutations, compared with only 1% of cases without lobular features (p = 2.4 e-14). The lobular features cases were more likely to have PIK3CA mutations (p = 0.01), with 33% of the lobular features cases having PIK3CA mutations, compared with 21% of the non-lobular cases. The lobular features cases were less likely to have TP53 mutations (p = 0.02), with 13% of lobular features cases having TP53 mutations as compared with 24% of the non-lobular feature cases. Lobular status was associated with PAM50 molecular subtype (Chi-square p = 0.002) with the lobular cases significantly less likely to be basal molecular subtype and more likely to be Luminal-A. Conclusions: PIK3CA mutations are enriched in invasive lobular carcinomas and invasive mammary carcinomas with lobular features. These associations point to the possibility that PIK3CA mutations as well as CDH1 alterations are important drivers of invasive lobular carcinomas. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-05-10.

307 Background: AR targeted therapies in combination with PARP inhibitors have recently shown efficacy in mCRPC patients with specific DNA repair gene mutations in metastatic tissue biopsies. Homologous recombination DNA repair deficiencies (HRD), associated with response to PARP inhibitors, can also be assessed by genomic instability/scarring. Accurate genomic scarring measurement in tumors can be confounded by intra-tumor heterogeneity and/or non-tumor genome contamination. To better identify PARPi sensitivity in mCRPC patients, we developed a genomic instability and scarring assay starting from single CTCs. Methods: VCaP, LnCaP or PC3 cell lines were spiked into healthy donor blood. Individual spiked cells were identified and recovered for genomic analysis using the standard Epic CTC assay. Post recovery, cells were lysed, whole genome amplified, constructed into shotgun libraries and sequenced to ~2M 2x150bp PE reads. Following alignment, whole genome copy number and instability analysis was performed to identify large scale transitions (LST, n of chromosomal breaks between adjacent regions of at least 10 Mb), % of genome altered (percentage of 1Mbp bins with copy number alterations), as well as specific tumor suppressor/oncogene copy number alterations. The association of PTEN loss with increases in genomic instability and scaring was performed. Results: Loss of PTEN function was previously shown to be associated with genomic instability. Our assessment of PTEN deletion was confirmed in PC3, while at least one genomic copy was observed in LnCaP and VCaP. The number of LSTs and % of genome altered was higher in PC3 (n = 19 +/- 3; 9.3% +/- 2.6%) than both VCaP and LnCap (n = 8 +/- 2; 6.1% +/- 0.4%). Conclusions: The association of higher genomic instability in a PTEN null cell line (PC3) vs. those with either heterozygous (LnCaP) or wild type (VCaP) PTEN status, matches published reports associating PTEN loss with increased genomic instability. Although, PC3 only demonstrates mild PARPi sensitivity in vitro, the detection of increased genomic scarring vs. cells with at least 1 functional PTEN allele confirms the assays ability to quantify genome instability at the single cell level from CTCs in a liquid biopsy.

I come from a family in which there have been no scientists or doctors. I was interested, however, in biology at school and started my scientific career by training in medicine at Oxford University and Guys Hospital, London. Practising as a doctor reinforced my curiosity about the biological processes underlying human disease. As a consequence, I pursued a clinical vocation in histopathology, a discipline that couples exposure to the sights and smells of the autopsy room with a daily journey into the often beautiful, sometimes ugly world of healthy and diseased human tissues under the microscope. After an introduction to general histopathology in Nick Wright's department at the Hammersmith Hospital, London, I completed my postgraduate medical training in neuropathology with Peter Lantos at the Maudsley Hospital, London.Peering at the nuclei of cancer cells under the microscope, for me it was a matter of fascination that hidden within them were the key events converting normal cells into cancer cells, and frustration because they were out of reach. Many of the tissue samples examined by pathologists are from cancers. The clonal theory of cancer development and the general role of DNA mutations in generating cancer cell clones had been established by 1986 when I was working as a junior pathologist. Indeed, the first mutated cancer gene, HRAS , had recently been identified through application of the, then new, technologies of recombinant DNA technology. Peering at the nuclei of cancer cells under the microscope, for me it was a matter of fascination that hidden within them were the key events converting normal cells into cancer cells, and frustration because they were out of reach. So, I took 3 years break from medicine to study for a PhD, learning the methods and thinking of molecular oncology in Colin Cooper's laboratory at the Institute …