Genomic Copy Number Profiling Research Articles

Clinical, histopathological and molecular features of dedifferentiated melanomas: An EORTC Melanoma Group Retrospective Analysis

PurposeDedifferentiated melanoma (DedM) poses significant diagnostic challenges. We aimed to investigate the clinical, histopathological and molecular features of DedM. Methylation signature (MS) and copy number profiling (CNP) were carried out in a subgroup of cases. Patients and methodsA retrospective series of 78 DedM tissue samples from 61 patients retrieved from EORTC (European Organisation for Research and Treatment of Cancer) Melanoma Group centres were centrally reviewed. Clinical and histopathological features were retrieved. In a subgroup of patients, genotyping through Infinium Methylation microarray and CNP analysis was carried out. ResultsMost patients (60/61) had a metastatic DedM showing most frequently an unclassified pleomorphic, spindle cell, or small round cell morphology akin to undifferentiated soft tissue sarcoma, rarely associated with heterologous elements. Overall, among 20 successfully analysed tissue samples from 16 patients, we found retained melanoma-like MS in only 7 tissue samples while a non-melanoma-like MS was observed in 13 tissue samples. In two patients from whom multiple specimens were analysed, some of the samples had a preserved cutaneous melanoma MS while other specimens exhibited an epigenetic shift towards a mesenchymal/sarcoma-like profile, matching the histological features. In these two patients, CNP was largely identical across all analysed specimens, in line with their common clonal origin, despite significant modification of their epigenome. ConclusionsOur study further highlights that DedM represents a real diagnostic challenge. While MS and genomic CNP may help pathologists to diagnose DedM, we provide proof-of-concept that dedifferentiation in melanoma is frequently associated with epigenetic modifications.

DNA-methylation and genomic copy number in primary tumors and corresponding lymph node metastases in prostate cancer from patients with low and high Gleason score

In prostate cancer, the indication to irradiate the pelvic lymphatic pathways in clinical node-negative patients is solely based on clinical nomograms. To define biological risk patterns of lymphatic spread, we studied DNA-methylation and genomic copy number in primary tumors and corresponding lymph nodes metastases. DNA-methylation and genomic copy number profiles of primary tumors (PT) and paired synchronous lymph node metastases (LN) from Gleason Score (GS)-6/7a (n=20 LN-positive, n=20 LN-negative) and GS-9/10 patients (LN-positive n=20) after prostatectomy and lymphonodectomy were analyzed. GS-6/7a pN0 PTs and GS-6/7a pN1 PTs differed in histone H3K27me3/H3K9me3 mediated methylation. PTs compared to LNs, in both, GS-6/7a pN1 and GS-9/10 pN1 patients showed large differences in DNA-methylation mediated by histones H3K4me1/2, in addition to copy number changes of chromosomal regions 11q13.1, 14q11.2 and 15q26.1. Between GS-6/7a pN1 and GS-9/10 pN1 patients, methylation levels differed more when comparing LNs than PTs. 16q21-22.1 was specifically lost in GS-9/10 pN0 PTs. Immune system-related pathways characterized the differences between PTs and LNs in both GS-6/7a pN1 and GS-9/10 pN1 patients. Comparing PTs and LKs between GS-6/7a pN1 and GS-9/10 pN1 patients revealed altered transmembrane and G-protein-coupled receptor signaling. Our data suggest that progression of prostate cancer, including lymphatic spread, is associated with histone-mediated DNA-methylation and we hypothesize a methylation signature predicting lymphatic spread in GS-6/7a patients from primary tumors. Lymphatic spread in GS-6/7a patients, flanked by DNA-methylation and CNA alterations, appears to be more complex than in GS-9/10 patients, in whom the primary tumors already appear to bear lymph node metastasis-enabling alterations.

Analysis of antitumor immunity in mouse glioma microenvironment through intercellular communication.

This study aimed to map the antitumor immunity in the glioma microenvironment by analyzing intercellular communication. The single-cell RNA-sequencing (scRNA-Seq) data were obtained from fresh mouse gliomas. Tumor cells were inferred by estimating genomic copy number profiles. CellMarker database was used to identify cell types. Intercellular communication was inferred using CellChat. Flow cytometry was used to detect the effect of microglia or stroma-educated monocytes on CD4+ T cell proliferation. Mouse glioma contained at least eight cell populations, and T cells were the only infiltrating immunocytes. Whether in signal outgoing or signal incoming, intercellular communication could be divided into four patterns by which cell populations in the tumor microenvironment (TME) cooperate with each other. By analyzing the complex communication between brain cell populations and infiltrating T cells in TME, we found that the brain cell populations used 25 signaling pathways to connect to T cells, and T cells used 21 signaling pathways to connect to brain cell populations. We also found that microglia from normal mice and brain stroma-educated monocytes exhibited immunosuppressive activity against CD4+ T cell proliferation. We described the previously underestimated complex communication between infiltrating T cells and brain cell populations. Our data suggest that the tolerogenic property of glioma TME is related to the immune privilege of CNS.

Genomic and Transcriptomic Characteristics of Esophageal Adenocarcinoma.

Simple SummaryCancer of the esophagus is a deadly disease. There are two main subtypes, adenocarcinoma and squamous cell carcinoma, with adenocarcinoma of the esophagus (EAC) being more common in Western countries. Barrett’s esophagus (BE) describes a change in the esophageal surface near the stomach in response to reflux of gastric acid into the esophagus. BE increases the risk of developing EAC, and the incidence of EAC has risen dramatically over recent decades. One likely reason for the poor prognosis of EAC is based on the fact that each tumor has many genes affected by mutations, and most of these genes differ across patients, hampering the efficacy of therapies that target specific cancer driver proteins. In this review, we provide an overview of the gene mutations and gene activity changes in EAC and how these features can be used to divide patients into groups that might have different clinical characteristics.Esophageal adenocarcinoma (EAC) is a deadly disease with limited options for targeted therapy. With the help of next-generation sequencing studies over the last decade, we gained an understanding of the genomic architecture of EAC. The tumor suppressor gene TP53 is mutated in 70 to 80% of tumors followed by genomic alterations in CDKN2A, KRAS, ERBB2, ARID1A, SMAD4 and a long tail of less frequently mutated genes. EAC is characterized by a high burden of point mutations and genomic rearrangements, resulting in amplifications and deletions of genomic regions. The genomic complexity is likely hampering the efficacy of targeted therapies. Barrett’s esophagus (BE), a metaplastic response of the esophagus to gastro-esophageal reflux disease, is the main risk factor for the development of EAC. Almost all EACs are derived from BE. The sequence from BE to EAC provides an opportunity to study the genomic evolution towards EAC. While the overlap of point mutations between BE and EAC within the same patient is, at times, surprisingly low, there is a correlation between the complexity of the genomic copy number profile and the development of EAC. Transcriptomic analyses separated EAC into a basal and a classical subtype, with the basal subtype showing a higher level of resistance to chemotherapy. In this review, we provide an overview of the current knowledge of the genomic and transcriptomic characteristics of EAC and their relevance for the development of the disease and patient care.

Acquired RAD51C Promoter Methylation Loss Causes PARP Inhibitor Resistance in High-Grade Serous Ovarian Carcinoma.

In high-grade serous ovarian carcinoma (HGSC), deleterious mutations in DNA repair gene RAD51C are established drivers of defective homologous recombination and are emerging biomarkers of PARP inhibitor (PARPi) sensitivity. RAD51C promoter methylation (meRAD51C) is detected at similar frequencies to mutations, yet its effects on PARPi responses remain unresolved.In this study, three HGSC patient-derived xenograft (PDX) models with methylation at most or all examined CpG sites in the RAD51C promoter show responses to PARPi. Both complete and heterogeneous methylation patterns were associated with RAD51C gene silencing and homologous recombination deficiency (HRD). PDX models lost meRAD51C following treatment with PARPi rucaparib or niraparib, where a single unmethylated copy of RAD51C was sufficient to drive PARPi resistance. Genomic copy number profiling of one of the PDX models using SNP arrays revealed that this resistance was acquired independently in two genetically distinct lineages.In a cohort of 12 patients with RAD51C-methylated HGSC, various patterns of meRAD51C were associated with genomic "scarring," indicative of HRD history, but exhibited no clear correlations with clinical outcome. Differences in methylation stability under treatment pressure were also observed between patients, where one HGSC was found to maintain meRAD51C after six lines of therapy (four platinum-based), whereas another HGSC sample was found to have heterozygous meRAD51C and elevated RAD51C gene expression (relative to homozygous meRAD51C controls) after only neoadjuvant chemotherapy.As meRAD51C loss in a single gene copy was sufficient to cause PARPi resistance in PDX, methylation zygosity should be carefully assessed in previously treated patients when considering PARPi therapy. SIGNIFICANCE: Homozygous RAD51C methylation is a positive predictive biomarker for sensitivity to PARP inhibitors, whereas a single unmethylated gene copy is sufficient to confer resistance.

Abstract 587: Genomic copy number profiling of single CTCs reveals clonal evolution in metastatic breast cancer and identifies actionable targets for informing treatment decisions

Abstract Introduction: Genomic profiling of circulating tumor cells (CTCs) is an approach to help to understand tumour heterogeneity and evolution in metastatic breast cancer (MBC) to inform prognosis and guide treatment options. We showed previously that single CTCs provide complementary information on hot spot mutations to those detected in circulating tumor DNA (ctDNA) and the primary tumour tissue, and now extend analyses to include genomic copy number changes. Herein, we report that identification of actionable targets through copy number profiling of single CTCs is achievable at any time point during metastatic progression and could be a valuable tool to guide treatment options. Methods: Fourteen patients (13 12 progressing and 1 2 responding) who were receiving treatment for MBC (12 13 HR pos, 1 HER2 pos, I1 TNBC) were recruited to the study with ethical consent and followed up with a single blood sample. A 7.5ml blood sample was collected into a CellSave Preservative tube and processed and counted within 96 hours of collection using the CELLSEARCH® system and the Circulating Tumor Cell Kit (Menarini Silicon Biosystems). The DEPArray™ System was used to identify and recover individual, intact CTCs of epithelial origin (Cytokeratin 8, 18, 19 +ve, CD45 -ve) and white blood cells (WBCs) as single cells or as a small pool of cells. Whole genome amplification was performed using the Ampli1 WGA kit. Libraries were generated using the Ampli1 LowPass Kit (Menarini Silicon Biosystems) and samples passing QC were analysed f by next generation sequencing on an S5 platform (Thermo fFisher). Results were analysed using the MSBiosuite software and data was compared with in- house informatics workfows. Results: From the 14 patients included in the study, we profiled a total of 97 samples using the Ampli1 LowPass sequencing workflow comprising 79 individual cells (across 14 patients) and 18 pools of approximately 10 cells. Successful genome- wide copy number profiles were generated in 12 of the 14 patients; samples from 2 patients had low QC scores and were inconclusive. In all, 12 patients individual CTCs from 12 patients showed similar copy number profiles, but with some heterogeneity, that revealed gene specific changes not detected by the cell pool. Moreover, 10 of the 12 patients had gene- specific changes (5 with CCND1 amplification, 2 with FGFR1 amplification, 1 with JAK2 amplification and 2 with STK11 deletion) that could have guided treatment decisions, for example offering an FGFR1 or JAK2 inhibitor. Conclusion: This study highlights the genomic heterogeneity in CTCs seen in MBC and the potential of monitoring gene specific changes to identify actionable targets in order to inform treatment decisions. The work requires further evaluation and validation but it may offer a new approach to managing treatment decisions in MBC for those patients with detectable CTCs. Citation Format: Daniel Fernandez Garcia, Georgios Nteliopoulos, Robert Hastings, Amelia Rushton, Karen Page, Luke J. Martinson, Molly Gray, David S. Guttery, Alberto Ferrarini, Nicolò Manaresi, Charles Coombes, Jacqui Shaw. Genomic copy number profiling of single CTCs reveals clonal evolution in metastatic breast cancer and identifies actionable targets for informing treatment decisions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 587.

Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes.

Single-cell transcriptomic analysis is widely used to study human tumors. However it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called CopyKAT (Copynumber Karyotyping of Aneuploid Tumors) to estimate genomic copy number profiles at an average genomic resolution of 5Mb from read depth in high-throughput scRNA-seq data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinomas, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes such as KRAS and signatures including EMT, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid the analysis of scRNA-seq data in a variety of solid human tumors.

Abstract IA14: Breast cancer evolution – Insights from single cell genomics

Abstract In this talk I will discuss our efforts to develop and apply single cell genome sequencing methods to study premalignant breast cancer invasion, as well as our efforts to build an atlas of normal cell types in human breast tissues. To study invasion in 10 patients with ductal carcinomas in situ (DCIS) premalignancies we developed a Topographic Single Cell Sequencing (TSCS) method that has spatial resolution to measure genomic copy number profiles in patients with synchronous DCIS-IDC tissues. Our data revealed a multi-clonal invasion model, in which genome evolution occurred within the ducts leading to the generation of multiple clones that co-migrated across the basement membrane to establish the invasive carcinomas. Our group is leading a collaborative effort to establish a human breast atlas of normal tissues using single cell RNA sequencing of 30 women. These data have identified major cell types including epithelial cells (luminal HR+, luminal secretory, basal), fibroblasts, adipocytes and endothelial cells (vascular, lymphatic) as well as immune cells (lymphocytes, myeloid). For each cell type, we have identified multiple (2-5) expression states that correspond to different biological functions. Collectively these data provide a ‘human genome’ reference of normal cell types and cell states in the human breast tissues to understand how the stromal and immune microenvironment is reprogrammed in breast cancers. Citation Format: Nicholas E. Navin. Breast cancer evolution – Insights from single cell genomics [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA14.

Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing

BackgroundInvestigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma samples. This approach is applied to study longitudinal blood plasma samples from prostate cancer patients, where longitudinal tissue biopsies from the bone and other metastatic sites have been challenging to collect.ResultsA molecular characterization of archival plasma DNA from 233 patients and genomic profiling of 101 patients identifies clinical correlations of aneuploid plasma DNA profiles with poor survival, increased plasma DNA concentrations, and lower plasma DNA size distributions. Deep-exome sequencing and genomic copy number profiling are performed on 23 patients, including 9 patients with matched metastatic tissues and 12 patients with serial plasma samples. These data show a high concordance in genomic alterations between the plasma DNA and metastatic tissue samples, suggesting the plasma DNA is highly representative of the tissue alterations. Longitudinal sequencing of 12 patients with 2–5 serial plasma samples reveals clonal dynamics and genome evolution in response to hormonal and chemotherapy. By performing an integrated evolutionary analysis, minor subclones are identified in 9 patients that expanded in response to therapy and harbored mutations associated with resistance.ConclusionsThis study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer.

Abstract 455: Innovations in large scale liquid biopsy analysis and the Broad/IBM Cancer Resistance Project

Abstract Broad Genomics offers a comprehensive liquid biopsy sequencing platform designed to provide the optimal flexibility for conducting research studies in a broad range of applications including: biomarker discovery, treatment resistance monitoring, and clinical grade ctDNA profiling. By utilizing low cost, low coverage whole genome sequencing in conjunction with dual unique molecular indexed (UMI) libraries we can offer a range of analysis that allow researchers to select the most appropriate samples for whole exome profiling or for deeper coverage, higher sensitivity targeted gene panels. To date we have generated over 3000 liquid biopsy whole genome copy number profiles and purity estimates and are supporting driver projects including the Broad/IBM Cancer Resistance Project and Count Me In. The study design for the Broad/IBM effort takes advantage of the discovery potential of tissue-based sequencing combined with serial liquid biopsy analysis to elucidate resistance events by tracking clonal and subclonal populations in patient samples over time. Sourcing samples for this and other similar efforts is a major undertaking and a combination of methods for maximally broad and deep genomic profiling are required to assay patients throughout the course of care, as tumor fraction in blood fluctuates. Responding to this need, and other applications requiring increased sensitivity we have developed a high throughput, automated workflow to efficiently assay cfDNA samples with lower tumor content. Benchmarking data using healthy donor pooled cfDNA samples indicates our assay is capable of detecting > 90% of variants present at ~1% minor allele fraction with less than 1 false positive variant called per megabase. This established laboratory and analytic process forms the basis of our 2Mb, 400 gene CLIA targeted assay currently undergoing validation. Through this suite of products we hope to enable an expansion of cfDNA sequencing efforts in support of clinical and research applications. Early results from emerging studies utilizing this platform to be presented. Citation Format: Carrie Cibulskis, Brendan Blumenstiel, Matthew DeFelice, Mark Fleharty, Justin Abreu, Viktor Adalsteinsson, Laxmi Parida, Susanna Hamilton, Gad Getz, Niall Lennon. Innovations in large scale liquid biopsy analysis and the Broad/IBM Cancer Resistance Project [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 455.

Abstract 2477: CopyCat: estimating genomic copy number profiles from high-throughput single cell RNA seq data

Abstract CopyCat is a computational approach for estimate genomic-copy number profiles from high-throughput single cell RNAseq data that is generated by technologies, such as Drop-Seq, 10X genomics or Nanowells. CopyCat involves first normalizing and transforming unique molecular index (UMI) count data matrices to calculate single cell copy number states from low-coverage datasets using gene-bin windows across the human genome, and does not require a reference normal cell control. The resulting binned data is normalized and used for segmentation to reduce noise from individual genes that can contribute to gene dosage effects along chromosomes. We show that this methods is highly effective at distinguishing diploid and aneuploid cells in human tumors or cancer cell lines, and can efficiently detect major (>10mb) chromosomal amplifications and deletions compared to copy number data generated by DNA sequencing of match samples. We further show that this method can resolve some clonal substructure within individual tumors, when subpopulations are distinguished by large chromosomal events. Our method outputs segmented copy number profiles and predicted classifications of normal (diploid) and tumor (aneuploid) cell states for individual single cells. It is implemented in R and is available on Github. Citation Format: Ruli Gao, Nicholas Navin. CopyCat: estimating genomic copy number profiles from high-throughput single cell RNA seq data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2477.

CTC versus biopsy tissue sequencing: A concordance analysis of genomic copy number profile from mCRPC patients (pts).

3050 Background: MSK-IMPACT (Integrated Mutation Profiling of Actionable Cancer Targets), is a high throughput, targeted-DNA-sequencing panel for somatic mutations created by the Department of Pathology at Memorial Sloan Kettering Cancer Center (MSK). The MSK-IMPACT is FDA approved for tumor tissue profiling to guide treatment selection. Recognizing access to tumor tissue in many cancers is difficult and may harbor inter & intra lesional heterogeneity, we sought to evaluate concordance of sequencing single CTCs vs. paired biopsy analyzed by MSK-IMPACT, to assess CTC vs. tumor clonality, and their relationship to outcomes. Methods: 148 biopsy samples from 138 mCRPC pts were submitted for IMPACT analysis and a blood draw within 30-day prior to initiation of a new line of treatment. Blood samples were sent to Epic Sciences for CTC detection. The detected CTCs underwent single cell low pass whole genome sequencing for copy number variation (CNV). For each set of matched samples, DNA copy number profiles from IMPACT and CTC sequencing were compared for similarity. Results: Of the 114 successfully sequenced samples 58 were from lymph nodes, 23 from bone, 25 from liver or lung, and 8 from other soft tissue. Of the 111 patients with CTCs analyzed, a total of 1073 CTCs were sequenced (range 1-27, median = 4 per pt). Of patients with both IMPACT & CTC, >80% pts had multiple subclones with distinguishable CNV. Concordance of genomics clones was found in 63%, and discordant in 37% cases. The clonal concordance between tissue biopsy and CTC was higher when the biopsy was obtained from bone marrow or a visceral site (71% concordance) than from a lymph node (53% concordance). Conclusions: Single CTC sequencing is often concordant to metastatic tissue, but unique CTC clones and the presence of multi-clonal disease highlight the potential to be underrepresented through tissue biopsy, especially when taken from the lymph node.[Table: see text]

Progression Potential of Ductal Carcinoma in situ Assessed by Genomic Copy Number Profiling

Background: Ductal carcinoma in situ (DCIS) of the breast is heterogeneous in terms of the risk of progression to invasive ductal carcinoma (IDC). To treat DCIS appropriately for its progression risk, we classified individual DCIS by its profile of genomic changes into 2 groups and correlated them with clinicopathological progression factors. Methods: We used surgically resected, formalin-fixed, paraffin-embedded tissues of 22 DCIS and 30 IDC lesions. We performed immunohistochemical intrinsic subtyping, array-based comparative genomic hybridization, and unsupervised clustering. Results: The samples were divided into 2 major clusters, A and B. Cluster A showed a greater number of gene and chromosome copy number alterations, a larger IDC/DCIS ratio, a higher frequency of nonluminal subtype, a lower frequency of luminal subtype, and a higher nuclear grade, when compared with cluster B. However, there was no difference in the frequencies of lymph node metastasis between clusters A and B. We identified 9 breast-cancer-related genes, including TP53 and GATA3, that highly contributed to the discrimination of A and B clusters. Conclusion: Classification of breast tumors into rapidly progressive cluster A and the other (cluster B) may contribute to select the treatment appropriate for their progression risk.

Genomic Profiles of Neuroblastoma Associated With Opsoclonus Myoclonus Syndrome.

Opsoclonus myoclonus syndrome (OMS), often called "dancing eyed syndrome," is a rare neurological condition associated with neuroblastoma in the majority of all childhood cases. Genomic copy number profiles have shown to be of prognostic significance for neuroblastoma patients. The aim of this retrospective multicenter study was to analyze the genomic copy number profiles of tumors from children with neuroblastoma presenting with OMS at diagnosis. In 44 cases of neuroblastoma associated with OMS, overall genomic profiling by either array-comparative genomic hybridization or single nucleotide polymorphism array proved successful in 91% of the cases, distinguishing tumors harboring segmental chromosome alterations from those with numerical chromosome alterations only. A total of 23/44 (52%) tumors showed an segmental chromosome alterations genomic profile, 16/44 (36%) an numerical chromosome alterations genomic profile, and 1 case displayed an atypical profile (12q amplicon). No recurrently small interstitial copy number alterations were identified. With no tumor relapse nor disease-related deaths, the overall genomic profile was not of prognostic impact with regard to the oncological outcome in this series of patients. Thus, the observation of an excellent oncological outcome, even for those with an unfavorable genomic profile of neuroblastoma, supports the hypothesis that an immune response might be involved in tumor control in these patients with OMS.

Multiclonal Invasion in Breast Tumors Identified by Topographic Single Cell Sequencing

Ductal carcinoma in situ (DCIS) is an early-stage breast cancer that infrequently progresses to invasive ductal carcinoma (IDC). Genomic evolution has been difficult to delineate during invasion due to intratumor heterogeneity and the low number of tumor cells in the ducts. To overcome these challenges, wedeveloped Topographic Single Cell Sequencing (TSCS) to measure genomic copy number profiles of single tumor cells while preserving their spatial context in tissue sections. We applied TSCS to 1,293 single cells from 10 synchronous patients with both DCIS and IDC regions in addition to exome sequencing. Our data reveal a direct genomic lineage between in situ and invasive tumor subpopulations and further show that most mutations and copy number aberrations evolved within the ducts prior to invasion. These results support a multiclonal invasion model, in which one or more clones escape the ducts and migrate into the adjacent tissues to establish the invasive carcinomas.

Genomic Copy Number Profiling Using Circulating Free Tumor DNA Highlights Heterogeneity in Neuroblastoma

The tumor genomic copy number profile is of prognostic significance in neuroblastoma patients. We have studied the genomic copy number profile of cell-free DNA (cfDNA) and compared this with primary tumor arrayCGH (aCGH) at diagnosis. In 70 patients, cfDNA genomic copy number profiling was performed using the OncoScan platform. The profiles were classified according to the overall pattern, including numerical chromosome alterations (NCA), segmental chromosome alterations (SCA), and MYCN amplification (MNA). Interpretable and dynamic cfDNA profiles were obtained in 66 of 70 and 52 of 70 cases, respectively. An overall identical genomic profile between tumor aCGH and cfDNA was observed in 47 cases (3 NCAs, 22 SCAs, 22 MNAs). In one case, cfDNA showed an additional SCA not detected by tumor aCGH. In 4 of 8 cases with a silent tumor aCGH profile, cfDNA analysis revealed a dynamic profile (3 SCAs, 1 NCA). In 14 cases, cfDNA analysis did not reveal any copy number changes. A total of 378 breakpoints common to the primary tumor and cfDNA of any given patient were identified, 27 breakpoints were seen by tumor aCGH, and 54 breakpoints were seen in cfDNA only, including two cases with interstitial IGFR1 gains and two alterations targeting TERT CONCLUSIONS: These results demonstrate the feasibility of cfDNA copy number profiling in neuroblastoma patients, with a concordance of the overall genomic profile in aCGH and cfDNA dynamic cases of 97% and a sensitivity of 77%, respectively. Furthermore, neuroblastoma heterogeneity is highlighted, suggesting that cfDNA might reflect genetic alterations of more aggressive cell clones. Clin Cancer Res; 22(22); 5564-73. ©2016 AACRSee related commentary by Janku and Kurzrock, p. 5400.

CNARA: reliability assessment for genomic copy number profiles.

BackgroundDNA copy number profiles from microarray and sequencing experiments sometimes contain wave artefacts which may be introduced during sample preparation and cannot be removed completely by existing preprocessing methods. Besides, large derivative log ratio spread (DLRS) of the probes correlating with poor DNA quality is sometimes observed in genome screening experiments and may lead to unreliable copy number profiles. Depending on the extent of these artefacts and the resulting misidentification of copy number alterations/variations (CNA/CNV), it may be desirable to exclude such samples from analyses or to adapt the downstream data analysis strategy accordingly.ResultsHere, we propose a method to distinguish reliable genomic copy number profiles from those containing heavy wave artefacts and/or large DLRS. We define four features that adequately summarize the copy number profiles for reliability assessment, and train a classifier on a dataset of 1522 copy number profiles from various microarray platforms. The method can be applied to predict the reliability of copy number profiles irrespective of the underlying microarray platform and may be adapted for those sequencing platforms from which copy number estimates could be computed as a piecewise constant signal. Further details can be found at https://github.com/baudisgroup/CNARA.ConclusionsWe have developed a method for the assessment of genomic copy number profiling data, and suggest to apply the method in addition to and after other state-of-the-art noise correction and quality control procedures. CNARA could be instrumental in improving the assessment of data used for genomic data mining experiments and support the reliable functional attribution of copy number aberrations especially in cancer research.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3074-7) contains supplementary material, which is available to authorized users.

Genomic Alterations in Cell-Free DNA and Enzalutamide Resistance in Castration-Resistant Prostate Cancer

The molecular landscape underpinning response to the androgen receptor (AR) antagonist enzalutamide in patients with metastatic castration-resistant prostate cancer (mCRPC) is undefined. Consequently, there is an urgent need for practical biomarkers to guide therapy selection and elucidate resistance. Although tissue biopsies are impractical to perform routinely in the majority of patients with mCRPC, the analysis of plasma cell-free DNA (cfDNA) has recently emerged as a minimally invasive method to explore tumor characteristics. To reveal genomic characteristics from cfDNA associated with clinical outcomes during enzalutamide treatment. Plasma samples were obtained from August 4, 2013, to July 31, 2015, at a single academic institution (British Columbia Cancer Agency) from 65 patients with mCRPC. We collected temporal plasma samples (at baseline, 12 weeks, end of treatment) for circulating cfDNA and performed array comparative genomic hybridization copy number profiling and deep AR gene sequencing. Samples collected at end of treatment were also subjected to targeted sequencing of 19 prostate cancer-associated genes. Enzalutamide, 160 mg, daily orally. Prostate-specific antigen response rate (decline ≥50% from baseline confirmed ≥3 weeks later). Radiographic (as per Prostate Cancer Working Group 2 Criteria) and/or clinical progression (defined as worsening disease-related symptoms necessitating a change in anticancer therapy and/or deterioration in Eastern Cooperative Group performance status ≥2 levels). The 65 patients had a median (interquartile range) age of 74 (68-79) years. Prostate-specific antigen response rate to enzalutamide treatment was 38% (25 of 65), while median clinical/radiographic progression-free survival was 3.5 (95% CI, 2.1-5.0) months. Cell-free DNA was isolated from 122 of 125 plasma samples, and targeted sequencing was successful in 119 of 122. AR mutations and/or copy number alterations were robustly detected in 48% (31 of 65) and 60% (18 of 30) of baseline and progression samples, respectively. Detection of AR amplification, heavily mutated AR (≥2 mutations), and RB1 loss were associated with worse progression-free survival, with hazard ratios of 2.92 (95% CI, 1.59-5.37), 3.94 (95% CI, 1.46-10.64), and 4.46 (95% CI, 2.28-8.74), respectively. AR mutations exhibited clonal selection during treatment, including an increase in glucocorticoid-sensitive AR L702H and promiscuous AR T878A in patients with prior abiraterone treatment. At the time of progression, cfDNA sequencing revealed mutations or copy number changes in all patients tested, including clinically actionable alterations in DNA damage repair genes and PI3K pathway genes, and a high frequency (4 of 14) of activating CTNNB1 mutations. Clinically informative genomic profiling of cfDNA was feasible in nearly all patients with mCRPC and can provide important insights into enzalutamide response and resistance.

The fetal thymus has a unique genomic copy number profile resulting from physiological T cell receptor gene rearrangement.

Somatic mosaicism, the presence of genetically distinct cells within an organism, has been increasingly associated with human morbidity, ranging from being a cause of rare syndromes to a risk factor for common disorders such as malignancy and cardiovascular disease. Previous studies interrogating the normal prevalence of somatic mosaicism have focused on adults. We here present an estimate of the baseline frequency of somatic mosaic copy number variation (CNV) at the time around birth, by sampling eight different organs from a total of five fetuses and newborns. Overall we find a significantly lower frequency of organ specific (i.e. mosaic) CNVs as compared to adults (p = 0.003; Mann-Whitney U-test). The rate of somatic CNV in adults has been estimated to around 2.2 CNV per organ assayed. In contrast, after stringent filtering, we found no organ-private CNVs in fetuses or newborns with exception of the thymus. This organ exhibited a specific genome profile in the form of deletions resulting from polyclonal T-cell receptor rearrangements. This implies that somatic non-immune related CNVs, if present at birth, are typically confined to very small cell populations within organs.

Abstract A2-09: Oncogenic dysregulations in neuroblastoma are associated with distal large chromosomal aberrations

Abstract Neuroblastoma (NB) is a prenatal malignancy diagnosed in infants, arising from neural crest cells, with heterogeneous etiology and prognosis. High risk tumors harbor large chromosomal alterations that substantially impact the expression of approximately one quarter of the genome; this challenges the distinction between driver and passenger copy number mutations, hindering the discovery of new therapeutic targets. Our lab has established a paradigm known as the bottleneck hypothesis in which multiple disease driver genetic elements integrate their aberrant signal through regulatory bottleneck, typically formed by a few transcriptional regulators, responsible of maintaining aggressive phenotypes. A new algorithm developed in our lab DIGGIT (Driver-Gene Inference by Genetical-Genomic Information Theory) has been able to successfully identify the impact of deletions in KLHL9 on the transcriptional activity of C/EBPβ and C/EBPδ, established master regulators of mesenchymal subtype in glioblastoma(1). To gain understanding of the association between genetics and the molecular phenotype which drives NB disease we analyze genome wide expression and copy number profiles from primary tumors from two independent cohorts with clinical information available; TARGET (n=250) and SIOPEN (n2=278); first, we identify genomic regions that prevalently suffer gain/loss aberrations which genetic dosage is associated with patient survival using a Cox hazards model. The main covariates are chromosome 1p (P=2.3e-9), 3p (P = 1.1e-2), 6q (P=), 11q (P=9.7e-7), 17p(P=5.3e-4) and 17q(P=4.5e-3). Also, we observed a multiplicative affect of chromosome 17 imbalance between p and q arms (P=7.8e-6). All measured with independence of MYCN amplification (the main hallmark of NB aggressive tumors). We used the above-mentioned dosage of these regions as trait loci to perform trans-aQTL analysis using the algorithm DIGGIT. We also included p and q arms combined cox linear model of chromosomes 11 and 17 to study the imbalance effect. The LIM domain only 1 protein (LMO1) is a validated NB oncogene which expression is increased in 9% of patients due to duplication events of its chromosome 11p15 locus. These events only partially explain LMO1 de-regulation. Our findings show that deletions on the distal arm 11q are implicated in LMO1 increased activity (P=4.3e-8), this effect is significantly stronger than its own loci duplication acting in cis (P=7.07e-5). The linear combination of p and q arms strikes with a p-value P=7.8e-10 supporting the additive effect of chromosome 11 imbalance. In addition to this finding, which confirms the oncogenic role of LMO1 in this disease, our integrated analysis also identified a plethora of additional findings providing plausible hypotheses for genetic alterations that contribute to dysregulation of driver genes in NB. The approach presented here is especially well suited to study tumors characterized by genomic instabilities leading to large chromosomal rearrangements, despite a paucity of recurrent point mutations. 1. James C. Chen, et al. Identification of Causal Genetic Drivers of Human Disease through Systems-Level Analysis of Regulatory Networks. Cell, Volume 159, Issue 2, p402–414, 9 October 2014. Citation Format: Gonzalo Lopez, Mariano Alvarez, James Chen, Presha Rajbhandari, Kristina A. Cole, Edward F. Attiyeh, Sharon Diskin, Pieter Mestdagh, Jo Vandesompele, John M. Maris, Andrea Califano. Oncogenic dysregulations in neuroblastoma are associated with distal large chromosomal aberrations. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-09.