Copy Number Alteration Profiles Research Articles

Abstract 3916: Patient-derived organoid and cell culture models from the NCI Patient-Derived Models Repository (NCI PDMR) preserve genomic stability and heterogeneity of patient tumor specimens

Abstract Background: The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov) of preclinical models including patient-derived xenografts (PDX), organoids (PDOrg) and patient-derived cell cultures (PDC). Extensive clinical annotation and genomic datasets are available for these preclinical models. However, it is unclear if the molecular profiles of the corresponding patient tumors are stably propagated in these models. We have previously demonstrated that PDX models from the NCI PDMR faithfully represent the patient tumors both in terms of genomic stability and tumor heterogeneity. Here, we conduct an in-depth investigation of genomic representation of patient tumors in the PDOrgs and PDCs. Methods: PDOrgs (n=64) and PDCs (n=94) were established from tumor fragments (i.e., initiator specimens) obtained either from patient specimens or from PDX specimens of early passage. For some models (n=19), both PDOrgs and PDCs were generated from the same tumor tissue; in fewer cases (n=4), PDCs were established from organoids derived from patient specimens. Whole Exome Sequencing and RNA-Seq were performed on all PDCs and PDOrgs, and data were compared with patient specimens or early passage PDXs. Results: A majority of the PDOrgs and PDCs have stably inherited the genome of the corresponding patient specimens based on the following observations: (1) >87% of PDOrgs and PDCs maintained similar copy number alteration profiles compared with the initiator specimens of the preclinical model; (2) the variant allele frequency (VAF) of clinically relevant mutations remained consistent between the PDOrgs, PDCs, and the initiator specimens, with none of the PDCs or PDOrgs deviating by >15% VAF; and (3) clinically relevant biomarkers (e.g., MSI, LOH, mutational signatures etc.) are concordant amongst the PDOrgs, PDCs, and the initiator specimens. We observed that the majority of SNVs and indels present in the initiator specimens were also found in the PDOrgs and PDCs, suggesting almost all the tumor heterogeneity was preserved in these preclinical models. Conclusions: This large and histologically diverse set of PDOrgs and PDCs from the NCI PDMR exhibited genomic stability and faithfully represented the tumor heterogeneity observed in corresponding patient specimens. These preclinical models thus represent a valuable resource for researchers interested in pre-clinical drug or other studies. Citation Format: Biswajit Das, Yvonne A. Evrard, Li Chen, Rajesh Patidar, Tomas Vilimas, Justine N. McCutcheon, Amanda L. Peach, Nikitha V. Nair, Thomas D. Forbes, Brandie A. Fullmer, Anna J. Lee Fong, Luis E. Romero, Alyssa K. Chapman, Kelsey A. Conley, Robin D. Harrington, Shahanawaz S. Jiwani, Peng Wang, Michelle M. Gottholm-Ahalt, Erin N. Cantu, Gloryvee Rivera, Lindsay M. Dutko, Kelly M. Benauer, Vishnuprabha R. Kannan, Carrie A. Bonomi, Kelly M. Dougherty, Joseph P. Geraghty, Marion V. Gibson, Savanna S. Styers, Abigail J. Walke, Jenna E. Moyer, Anna Wade, Mariah L. Baldwin, Kaitlyn A. Arthur, Kevin J. Plater, Luke Stockwin, Matthew R. Murphy, Michael E. Mullendore, Dianne L. Newton, Melinda G. Hollingshead, Chris A. Karlovich, Paul M. Williams, James H. Doroshow. Patient-derived organoid and cell culture models from the NCI Patient-Derived Models Repository (NCI PDMR) preserve genomic stability and heterogeneity of patient tumor specimens [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 3916.

Abstract 1308: CDK12 alterations define a distinct molecular subtype of prostate cancers with unique genomic and clinical characteristics

Abstract Background: CDK12 alterations are present in several tumor types but little is known regarding their oncogenic role and their clinical significance. Here we sought to describe the landscape of CDK12 alterations across solid cancers and the clinical features of CDK12-altered prostate cancer. Methods: A total of 26,743 patients across 25 solid tumor types with available targeted sequencing data from MSK-IMPACT as part of their clinical care were included. Clinicopathological features and outcomes were assessed in prostate cancer. CDK12 alterations and association with genomic characteristics are described. For prostate cancer patients, overall survival from the date of metastasis and time to castration-resistance from the start of androgen deprivation therapy were assessed using univariable and multivariable Cox regression analysis. Results: CDK12 alterations were identified in 404/26,743 (1.5%) patients overall, but were most frequent in prostate (100/1875, 5.3%) and ovarian cancer (43/1034, 4.2%) where they were associated with a high prevalence of truncating variants and biallelic inactivation. CDK12 alterations defined a distinct subtype of prostate cancer with more aggressive clinical features, a unique copy number alteration profile and involvement of distinct oncogenic pathway alterations, including cell cycle pathway genes. Independent of standard clinical factors and genomic instability, CDK12-altered prostate cancer patients were associated with shorter overall survival (median 64.4 vs 74.9 months, adjusted hazard ratio [aHR] 1.65, 95% CI 1.07-2.53, p = 0.03) and shorter time to the development of castration-resistant disease (median 10.8 months vs 13.1, aHR 1.43, 95%CI 1.07-1.8, p = 0.02). Conclusions: CDK12 loss of function is a rare event across solid cancers but defines a distinct molecular subtype of prostate cancer that is associated with more aggressive clinical features and unique genomic alterations. Citation Format: Bastien Nguyen, Jose Mauricio Mota, Subhiksha Nandakumar, Konrad H. Stopsack, Emily Weg, Dana Rathkopf, Michael J. Morris, Howard Scher, Philip W. Kantoff, Anuradha Gopalan, Dmitriy Zamarin, David B. Solit, Nikolaus Schultz, Wassim Abida. CDK12 alterations define a distinct molecular subtype of prostate cancers with unique genomic and clinical characteristics [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 1308.

Genomic Analysis of Localized High-Risk Prostate Cancer Circulating Tumor Cells at the Single-Cell Level.

Accurate risk classification of men with localized high-risk prostate cancer directly affects treatment management decisions and patient outcomes. A wide range of risk assessments and classifications are available. However, each one has significant limitations to distinguish between indolent and aggressive prostate cancers. Circulating tumor cells (CTCs) may provide an alternate additional source, beyond tissue biopsies, to enable individual patient-specific clinical assessment, simply because CTCs can reveal both tumor-derived and germline-specific genetic information more precisely than that gained from a single diagnostic biopsy. In this study, we combined a filtration-based CTC isolation technology with prostate cancer CTC immunophenotyping to identify prostate cancer CTCs. Next, we performed 3-D telomere profiling prior to laser microdissection and single-cell whole-exome sequencing (WES) of 21 CTCs and 4 lymphocytes derived from 10 localized high-risk prostate cancer patient samples. Localized high-risk prostate cancer patient CTCs present a high number of telomere signals with lower signal intensities (short telomeres). To capture the genetic diversity/heterogeneity of high-risk prostate cancer CTCs, we carried out whole-exome sequencing. We identified 202,241 single nucleotide variants (SNVs) and 137,407 insertion-deletions (indels), where less than 10% of these genetic variations were within coding regions. The genetic variation (SNVs + indels) and copy number alteration (CNAs) profiles were highly heterogeneous and intra-patient CTC variation was observed. The pathway enrichment analysis showed the presence of genetic variation in nine telomere maintenance pathways (patients 3, 5, 6, and 7), including an important gene for telomere maintenance called telomeric repeat-binding factor 2 (TRF2). Using the PharmGKB database, we identified nine genetic variations associated with response to docetaxel. A total of 48 SNVs can affect drug response for 24 known cancer drugs. Gene Set Enrichment Analysis (GSEA) (patients 1, 3, 6, and 8) identified the presence of CNAs in 11 different pathways, including the DNA damage repair (DDR) pathway. In conclusion, single-cell approaches (WES and 3-D telomere profiling) showed to be useful in unmasking CTC heterogeneity. DDR pathway mutations have been well-established as a target pathway for cancer therapy. However, the frequent CNA amplifications found in localized high-risk patients may play critical roles in the therapeutic resistance in prostate cancer.

Characterization of circulating breast cancer cells with tumorigenic and metastatic capacity

Functional studies giving insight into the biology of circulating tumor cells (CTCs) remain scarce due to the low frequency of CTCs and lack of appropriate models. Here, we describe the characterization of a novel CTC‐derived breast cancer cell line, designated CTC‐ITB‐01, established from a patient with metastatic estrogen receptor‐positive (ER+) breast cancer, resistant to endocrine therapy. CTC‐ITB‐01 remained ER+ in culture, and copy number alteration (CNA) profiling showed high concordance between CTC‐ITB‐01 and CTCs originally present in the patient with cancer at the time point of blood draw. RNA‐sequencing data indicate that CTC‐ITB‐01 has a predominantly epithelial expression signature. Primary tumor and metastasis formation in an intraductal PDX mouse model mirrored the clinical progression of ER+ breast cancer. Downstream ER signaling was constitutively active in CTC‐ITB‐01 independent of ligand availability, and the CDK4/6 inhibitor Palbociclib strongly inhibited CTC‐ITB‐01 growth. Thus, we established a functional model that opens a new avenue to study CTC biology.

Meningiomas: An Overview of the Landscape of Copy Number Alterations in Samples from an Admixed Population.

Meningiomas are considered the most common intracranial tumors, affecting mainly women. Studies in mixed populations can be of great importance to clarify issues related to the genetic diversity of tumors and their development. Considering that data obtained from analyses of the profile of copy number alterations (CNA) have been a useful diagnostic indicator for many types of tumors and that meningiomas show a complex pattern of gains and losses in the number of copies, our objective was to analyze the CNA profile in 33 samples of meningiomas of different histological grades (WHO Grade I-III) from patients in a city located in the Amazon region of Brazil, using aCGH. We found that the female to male ratio was 3 : 1. The aCGH analysis revealed a total of 2304 CNA, with an average of 69.8 ± 57.4 per case, of which 1197 were gains (52%), 926 were losses (40.2%), 105 were amplifications (4. 5%), and 76 were deletions (3.3%). A significant relationship was observed between the type of CNA and the degree of the tumor (chi-square test: χ2 = 65,844; p < 0.0001; contingency coefficient: C = 0.1772; p < 0.0001). Evaluating the recurrent changes in at least 50% of the samples, we observe as the most frequent losses of the segments 22q13.1-q13.2 (82%), 1p35.3 (76%), and 14q13.1-q13.2 (67%), involving all histopathological grades. The analysis of these regions showed the inclusion of genes with functions such as regulation, maintenance of cell survival, reorganization of the cytoskeleton, cell signaling, and DNA repair, among others. However, overall, the profiles observed in meningiomas of this admixed population were very similar to the ones observed in Caucasian groups. An interesting finding was a recurrent gain of 8p22 observed only in grade I meningiomas, a region which includes DLC1, a suppressor candidate gene probably implicated in the developments or progression of meningiomas, usually found deleted, when related to CNAs.

Treatment-driven selection of chemoresistant Ewing sarcoma tumors with limited drug distribution

Ewing sarcoma is a bone and soft tissue tumor predominantly affecting adolescents and young adults. To characterize changes in anticancer drug activity and intratumor drug distribution during the evolution of Ewing sarcomas, we used immunodeficient mice to establish pairs of patient-derived xenografts (PDX) at early (initial diagnosis) and late (relapse or refractory progression) stages of the disease from three patients. Analysis of copy number alterations (CNA) in early passage PDX tissues showed that two tumor pairs established from patients which responded initially to therapy and relapsed more than one year later displayed similar CNAs at early and late stages. For these two patients, PDX established from late tumors were more resistant to chemotherapy (irinotecan) than early counterparts. In contrast, the tumor pair established at refractory progression showed highly dissimilar CNA profiles, and the pattern of response to chemotherapy was discordant with those of relapsed cases. In mice receiving irinotecan infusions, the level of SN-38 (active metabolite of irinotecan) in the intracellular tumor compartment was reduced in tumors at later stages compared to earlier tumors for those pairs bearing similar CNAs, suggesting that distribution of anticancer drug shifted toward the extracellular compartment during clonal tumor evolution. Overexpression of the drug transporter P-glycoprotein in late tumor was likely responsible for this shift in drug distribution in one of the cases.

Endometrial stromal sarcomas with BCOR-rearrangement harbor MDM2 amplifications.

Recently a novel subtype of endometrial stromal sarcoma (ESS) defined by recurrent genomic alterations involving BCOR has been described (HGESS‐BCOR). We identified a case of HGESS‐BCOR with a ZC3H7B‐BCOR gene fusion, which harbored an amplification of the MDM2 locus. This index case prompted us to investigate MDM2 amplification in four additional cases of HGESS‐BCOR. Tumors were analyzed for MDM2 amplification by array‐based profiling of copy number alterations (CNAs) and fluorescence in situ hybridization (FISH), as well as for MDM2 expression by immunohistochemistry (IHC). Additionally, a cohort of other mesenchymal uterine neoplasms, including 17 low‐grade ESS, 6 classical high‐grade ESS with YWHAE‐rearrangement, 16 uterine tumors resembling ovarian sex cord tumors, 7 uterine leiomyomas and 8 uterine leiomyosarcomas, was analyzed for CNAs in MDM2. Copy number profiling identified amplification of the 12q15 region involving the MDM2 locus in all five HGESS‐BCOR. Subsequent validation analyses of three tumors confirmed MDM2 amplification using MDM2 FISH. Accordingly, IHC showed MDM2 overexpression in all analyzed cases. None of the other uterine neoplasms in our series, including tumors that are in the histopathological differential diagnoses of HGESS‐BCOR, showed copy number gains of MDM2. Together, our results indicate that HGESS‐BCOR carries MDM2 amplifications, which has diagnostic implications and could potentially be used for targeted therapies in these clinically aggressive tumors.

ShallowHRD: detection of homologous recombination deficiency from shallow whole genome sequencing.

SummaryWe introduce shallowHRD, a software tool to evaluate tumor homologous recombination deficiency (HRD) based on whole genome sequencing (WGS) at low coverage (shallow WGS or sWGS; ∼1X coverage). The tool, based on mining copy number alterations profile, implements a fast and straightforward procedure that shows 87.5% sensitivity and 90.5% specificity for HRD detection. shallowHRD could be instrumental in predicting response to poly(ADP-ribose) polymerase inhibitors, to which HRD tumors are selectively sensitive. shallowHRD displays efficiency comparable to most state-of-art approaches, is cost-effective, generates low-storable outputs and is also suitable for fixed-formalin paraffin embedded tissues.Availability and implementation shallowHRD R script and documentation are available at https://github.com/aeeckhou/shallowHRD.Supplementary information Supplementary data are available at Bioinformatics online.

Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes

BackgroundDetection of DNA copy number alterations (CNAs) is critical to understand genetic diversity, genome evolution and pathological conditions such as cancer. Cancer genomes are plagued with widespread multi-level structural aberrations of chromosomes that pose challenges to discover CNAs of different length scales, and distinct biological origins and functions. Although several computational tools are available to identify CNAs using read depth (RD) signal, they fail to distinguish between large-scale and focal alterations due to inaccurate modeling of the RD signal of cancer genomes. Additionally, RD signal is affected by overdispersion-driven biases at low coverage, which significantly inflate false detection of CNA regions.ResultsWe have developed CNAtra framework to hierarchically discover and classify ‘large-scale’ and ‘focal’ copy number gain/loss from a single whole-genome sequencing (WGS) sample. CNAtra first utilizes a multimodal-based distribution to estimate the copy number (CN) reference from the complex RD profile of the cancer genome. We implemented Savitzky-Golay smoothing filter and Modified Varri segmentation to capture the change points of the RD signal. We then developed a CN state-driven merging algorithm to identify the large segments with distinct copy numbers. Next, we identified focal alterations in each large segment using coverage-based thresholding to mitigate the adverse effects of signal variations. Using cancer cell lines and patient datasets, we confirmed CNAtra’s ability to detect and distinguish the segmental aneuploidies and focal alterations. We used realistic simulated data for benchmarking the performance of CNAtra against other single-sample detection tools, where we artificially introduced CNAs in the original cancer profiles. We found that CNAtra is superior in terms of precision, recall and f-measure. CNAtra shows the highest sensitivity of 93 and 97% for detecting large-scale and focal alterations respectively. Visual inspection of CNAs revealed that CNAtra is the most robust detection tool for low-coverage cancer data.ConclusionsCNAtra is a single-sample CNA detection tool that provides an analytical and visualization framework for CNA profiling without relying on any reference control. It can detect chromosome-level segmental aneuploidies and high-confidence focal alterations, even from low-coverage data. CNAtra is an open-source software implemented in MATLAB®. It is freely available at https://github.com/AISKhalil/CNAtra.

Sex disparities in head & neck cancer driver genes: An analysis of the TCGA dataset.

Survival in head and neck squamous cell carcinoma (HNSCC) has been associated with patient sex, typically with males experiencing poorer outcomes. It is unclear if this disparity is based in divergent tumor biology. We analyzed the TCGA HNSCC cohort to uncover disparities in the somatic single nucleotide variation (SNV), copy number alteration (CNA) and mRNA abundance profiles between males and females. Critically, we stratified our results by tumor HPV status to control for this significant confounder. SNV, CNA and mRNA abundance differences between males and females were compared separately for the HPV-positive (n=67) and negative (n=431) TCGA HNSCC cohorts. Overall survival outcomes were compared in males and females in both HPV-positive and HPV-negative subsets of patients. Females were found to have poorer overall survival than males (p=0.048), largely due to higher rates of HPV-positive disease among men. SNV analysis revealed that in HPV-positive disease, there were no differences by sex after accounting for the false discovery rate (FDR). In HPV-negative tumors, BRWD3 mutations occurred more frequently in the tumors of female patients compared to males after adjusting for the FDR (p=0.02). Further, HPV-negative BRWD3 mutant tumors were found to have significantly worse 5-year overall survival compared to wildtype on multivariate analysis (p=0.02). There were 88 heterozygous deletions and 14 amplifications that were differentially altered between male and female HPV-negative tumors and associated with expression changes. Pathway analysis of these genes revealed that tumors from males were enriched in five pathways including chemokine and phosphophatidylinositol signaling. Reanalysis of the TCGA HNSCC dataset stratified by sex revealed that males in this cohort had a significant survival advantage, due to a higher proportion of HPV-positive disease. Mutations in BRWD3 were more frequent in HPV-negative tumors of females and were associated with poorer overall survival. BRWD3 may represent a novel biomarker of patient outcomes, but will require additional validation.

Transcriptional effects of copy number alterations in a large set of human cancers

Copy number alterations (CNAs) can promote tumor progression by altering gene expression levels. Due to transcriptional adaptive mechanisms, however, CNAs do not always translate proportionally into altered expression levels. By reanalyzing >34,000 gene expression profiles, we reveal the degree of transcriptional adaptation to CNAs in a genome-wide fashion, which strongly associate with distinct biological processes. We then develop a platform-independent method—transcriptional adaptation to CNA profiling (TACNA profiling)—that extracts the transcriptional effects of CNAs from gene expression profiles without requiring paired CNA profiles. By applying TACNA profiling to >28,000 patient-derived tumor samples we define the landscape of transcriptional effects of CNAs. The utility of this landscape is demonstrated by the identification of four genes that are predicted to be involved in tumor immune evasion when transcriptionally affected by CNAs. In conclusion, we provide a novel tool to gain insight into how CNAs drive tumor behavior via altered expression levels.

Urothelial Carcinoma Detection Based on Copy Number Profiles of Urinary Cell-Free DNA by Shallow Whole-Genome Sequencing.

Current noninvasive assays for urothelial carcinoma (UC) lack clinical sensitivity and specificity. Given the utility of plasma cell-free DNA (cfDNA) biomarkers, the development of urinary cfDNA biomarkers may improve the diagnostic sensitivity. We assessed copy number alterations (CNAs) by shallow genome-wide sequencing of urinary cfDNA in 95 cancer-free individuals and 65 patients with UC, 58 with kidney cancer, and 45 with prostate cancer. We used a support vector machine to develop a diagnostic classifier based on CNA profiles to detect UC (UCdetector). The model was further validated in an independent cohort (52 patients). Genome sequencing data of tumor specimens from 90 upper tract urothelial cancers (UTUCs) and CNA data for 410 urothelial carcinomas of bladder (UCBs) from The Cancer Genome Atlas were used to validate the classifier. Genome sequencing data for urine sediment from 32 patients with UC were compared with cfDNA. To monitor the treatment efficacy, we collected cfDNA from 7 posttreatment patients. Urinary cfDNA was a more sensitive alternative to urinary sediment. The UCdetector could detect UC at a median clinical sensitivity of 86.5% and specificity of 94.7%. UCdetector performed well in an independent validation data set. Notably, the CNA features selected by UCdetector were specific markers for both UTUC and UCB. Moreover, CNA changes in cfDNA were consistent with the treatment effects. Meanwhile, the same strategy could localize genitourinary cancers to tissue of origin in 70.1% of patients. Our findings underscore the potential utility of urinary cfDNA CNA profiles as a basis for noninvasive UC detection and surveillance.

Comprehensive identification and characterization of somatic copy number alterations in triple‑negative breast cancer.

Triple-negative breast cancer (TNBC) accounts for ~15% of all breast cancer diagnoses each year. Patients with TNBC tend to have a higher risk for early relapse and a worse prognosis. TNBC is characterized by extensive somatic copy number alterations (CNAs). However, the DNA CNA profile of TNBC remains to be extensively investigated. The present study assessed the genomic profile of CNAs in 201 TNBC samples, aiming to identify recurrent CNAs that may drive the pathogenesis of TNBC. In total, 123 regions of significant amplification and deletion were detected using the Genomic Identification of Significant Targets in Cancer algorithm, and potential driver genes for TNBC were identified. A total of 31 samples exhibited signs of chromothripsis and revealed chromosome pulverization hotspot regions. The present study further determined 199 genomic locations that were significantly enriched for breakpoints, which indicated TNBC-specific genomic instability regions. Unsupervised hierarchical clustering of tumors resulted in three main subgroups that exhibited distinct CNA profiles, which may reveal the heterogeneity of molecular mechanisms in TNBC subgroups. These results will extend the molecular understanding of TNBC and will facilitate the discovery of therapeutic and diagnostic target candidates.

MPC-04 MOLECULAR FEATURES AND CLINICAL OUTCOMES OF ELDERLY GLIOBLASTOMA PATIENTS: ANALYSES OF KANSAI NETWORK AND TCGA COHORTS

INTRODUCTIONAging is a negative prognostic factor in glioblastoma (GB) and the genetic background in clinical outcome of elderly GB could exist. This study investigates the difference of elderly patients from younger ones regarding molecular characteristics as well as clinical outcomes in IDH-wildtype GB.METHODSWe collected adult cases diagnosed with IDH-wildtype GB and enrolled in Kansai Molecular Diagnosis Network for CNS Tumors (Kansai Network) (212 cases) and The Cancer Genome Atlas (TCGA) project (359 cases). Clinical and pathological characteristics were analyzed retrospectively and compared between elderly cases (≥70 years) and younger ones (≤50 years). Molecular analysis included copy number alterations (CNAs) of eight genes (EGFR, PDGFRA, PTEN, CDKN2A, CDK4, MDM2, TP53, NFKBIA).RESULTSIncluded in the study were 92 (≥70 years)/33 (≤50 years) cases of Kansai Network and 88 (≥70 years)/69 (≤50 years) cases of TCGA. Median overall survival was 12.8 (≥70 years)/ 21.0 (≤50 years) months in Kansai Network cohort and 8.8 (≥70 years)/ 21.09 (≤50 years) months in TCGA cohort. MGMT promoter was methylated in 50 (54.3%) (≥70 years)/14 (42.4%) (≤50 years) tumors in Kansai Network and 34 (48.6%) (≥70 years)/16 (36.4%) (≤50 years) tumors in TCGA. TERT promoter was mutated in 51 (55.4%) (≥70 years)/13 (39.4%) (≤50 years) tumors in Kansai Network and unknown in TCGA. Significant difference of CNA profiles between ≥70 years and ≤50 years was as follows: PTEN del, 43 (46.7%)/8 (24.2%); CDK4 amp, 17 (18.5%)/1 (3.0%) in Kansai Network and CDKN2A del, 69 (78.4%)/ 42 (60.9%) in TCGA.CONCLUSIONElderly patients have several potential factors for poor prognosis and different molecular profiles might explain the survival differences among generations.

Molecular Characterization of Locally Relapsed Head and Neck Cancer after Concomitant Chemoradiotherapy.

To investigate the pathobiological origin of local relapse after chemoradiotherapy, we studied genetic relationships of primary tumors (PT) and local relapses (LR) of patients treated with chemoradiotherapy. First, low-coverage whole genome sequencing was performed on DNA from 44 biopsies of resected head and neck squamous cell carcinoma (HNSCC) specimens (median 3 biopsies/tumor) to assess suitability of copy number alterations (CNAs) as biomarker for genetic relationships. CNAs were compared within and between tumors and an algorithm was developed to assess genetic relationships with consideration of intratumor heterogeneity. Next, this CNA-based algorithm was combined with target enrichment sequencing of genes frequently mutated in HNSCC to assess the genetic relationships of paired tumors and LRs of patients treated with chemoradiotherapy. Genetic relationship analysis using CNAs could accurately (96%) predict tumor biopsy pairs as patient-matched or independent. However, subsequent CNA analysis of PTs and LRs after chemoradiotherapy suggested genetic relationships in only 20% of cases, and absence in 80%. Target enrichment sequencing for mutations confirmed absence of any genetic relationship in half of the paired PTs and LRs. There are minor variations in CNA profiles within different areas of HNSCC tumors and many between independent tumors, suggesting that CNA profiles could be exploited as a marker of genetic relationship. Using CNA profiling and mutational analysis of cancer driver genes, relapses after chemoradiotherapy appear to be partially genetically related to the corresponding PTs, but seem often genetically unrelated. This remarkable observation warrants further studies and will impact therapeutic innovations and prognostic modeling when using index tumor characteristics.

Mutational Landscape, Copy Number Alterations and Tumor Burden Assessed By Cell-Free DNA in Diffuse Large B-Cell Lymphoma

Introduction: Previous studies have highlighted the potential of cell-free DNA (cfDNA) to assess the mutational profile and copy number alterations (CNA) in diffuse large B-cell lymphoma (DLBCL), usually performed in tissue biopsies, both at diagnosis and relapse. In addition, the quantitative levels of cfDNA might be a surrogate of the lymphoma tumor burden and could therefore predict response to therapy, progression-free survival (PFS) and overall survival (OS). The aim of this study was to analyze the mutational profile and CNA at diagnosis using cfDNA, to compare these results with those obtained from formalin-fixed paraffin-embedded (FFPE) biopsies, and to estimate the correlation of pre-treatment levels of cfDNA with FDG-PET/CT Total Metabolic Tumor Volume (TMTV) and their impact in the outcome of DLBCL patients. Methods: We included 79 patients (41M/38F , median age 63 years) diagnosed with DLBCL according to the WHO criteria in a single institution between 2016 and 2018. All patients received chemoimmunotherapy. After frontline treatment, 56 patients achieved a complete (CR) response, 4 partial response, 16 were refractory, including 7 early deaths, and in 3 cases the response was not yet evaluable. Samples were obtained at diagnosis before starting treatment. cfDNA extraction was performed from 2-4 mL of plasma collected in PAXgene Blood ccfDNA tubes (Qiagen) and size distribution of DNA fragments was analyzed using the Agilent 2100 Bioanalyzer. Tumor genomic DNA (gDNA) was isolated from FFPE diagnostic tissue biopsies. A panel of 115 genes was enriched using a hybridization capture-based protocol from 10-30 ng of cfDNA and 150 ng of gDNA (ThruPlex Tag-seq kit and SureSelectXT enrichment reagents, Agilent Technologies) and sequenced in a MiSeq instrument (Illumina). CNA were examined using CNVkit software toolkit. cfDNA levels were reported as haploid genome equivalents per mL of plasma and expressed as a base 10 logarithm (log hGE/mL). Quantitative analysis of TMTV was performed using the semiautomatic MIM software, with a fixed SUV&gt;2.5 thresholding method for segmentation. Results: A median of 15.6 ng/mL (range: 4-754 ng/mL) of cfDNA was obtained. At least one mutation could be detected in 69/79 cases (87.3%). The median number of mutations per sample was 6 (range: 0-41 mutations). The genes most frequently mutated at diagnosis in plasma samples were KMT2D, TP53, TNFRSF14, MYD88, BCL2, SOCS1, CREBBP, MYC and EP300. In 45 cases, paired FFPE samples were available. Sensitivity of cfDNA to detect mutations in baseline FFPE samples was 69% (95%CI: 64.1-73.9). In 28 of the 45 cases, &gt;70% of the mutations were observed both in the cfDNA and FFPE samples. In the remaining 17 cases, the number of mutations identified in cfDNA was lower than the one observed in the FFPE sample (Figure 1a). Of note, most of the cases in which mutations were not detected in the cfDNA corresponded to localized stages (11/17, 65%) and/or primary extranodal DLBCL (12/17, 71%). The CNA profile in cfDNA was similar to that reported in tissue, with recurrent deletions of TNSFRS14 (11%), TNFAIP3 (14%), CDKN2A (7%), or TP53 (7%), as well as gains of REL (7%) or BCL2 (5%), among others (Figure 1b). Median pre-treatment TMTV (N=48) was 292 cm3 (0-4,171 cm3). Higher TMTV predicted for a poorer PFS (HR 4.85; p=0.005). cfDNA concentration significantly correlated with TMTV (R=0.546, p&lt;0.001), confirming that cfDNA measurements are related to the tumor burden of the lymphoma. In addition, patients with high pretreatment cfDNA levels (&gt;3 log hGE/mL) had a significantly lower CR rate, PFS, and OS than those with low levels (CR rate, 47% vs. 92%, p&lt;0.001; 24-month PFS 37 vs. 76%, p=0.0004; and 24-month OS 50 vs. 88%, p=0.001) (Figure 1c). Conclusions: cfDNA represents a valuable tool to easily assess the genomic landscape and tumor burden in DLBCL, as well as to predict response to therapy and outcome in these patients. Figure 1 Disclosures Gine: Janssen: Other: Travel expenses, Research Funding; Roche: Other: Travel expenses, Research Funding; Gilead: Other: Travel expenses, Research Funding. Lopez-Guillermo:Gilead: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Janssen: Research Funding.

Novel Molecular Pathogenesis and Therapeutic Target in Acute Erythroid Leukemia

Acute erythroid leukemia (AEL) is a unique subtype of acute myeloid leukemia (AML) characterized by erythroid predominance and dysplasia, which is morphologically classified into two subtypes: pure erythroid and myeloid/erythroid leukemias (PEL and MEL). Clinically, AEL exhibits aggressive and rapid clinical course, which is considered to be linked to frequent TP53 mutations and complex karyotypes found in this subtype. Although multiple sequencing studies were conducted to explain such phenotypic variety and to search promising therapeutic targets, neither the diagnostic discrimination of PEL and MEL subtypes nor the establishment of standard therapeutic strategy has fully been successful. To clarify genetic characteristics and to identify novel therapeutic targets, we comprehensively characterized the mutation and copy number alteration (CNA) profiles and assessed differential impacts of the frequent driver genetic abnormalities on disease phenotypes and clinical outcomes. We initially analyzed 105 cases with AEL (PEL; n=10, MEL; n=69, and unspecified; n=26). Among these, 9 cases were serially analyzed at 2-6 time points. All samples were obtained according to protocols approved by the ethics board of each participating institution. As control, 907 cases with non-erythroid AML (NEL) distinguished by the low fraction (&amp;lt;50%) of erythroid cells in bone marrow were enrolled. Publicly available information on clinical and genetic findings was collected from previous publications, including The Cancer Genome Atlas and BeatAML datasets. In total, 1,012 cases with AML were enrolled in this study. The genetic profile in PEL and MEL were also compared with that of NEL. Finally, we recognized biological significance of the molecular defects by functional analysis of xenograft model, and showed novel therapeutic possibilities targeting pathogenic pathways. Most frequently observed were mutations in TP53 (39%), STAG2 (20%), and NPM1 (15%), and KMT2A-partial tandem duplication (PTD) (18%) in AEL. On the basis of mutational profiles, consensus clustering divided AEL into 4 subgroups. Group A (n=41, 39%) was defined by TP53 mutations into which all PELs were categorized. In CNA analysis, amplification in 9p, 19p, and 21q were significantly more enriched in PEL than NEL. Intriguingly, amplification of 9p, 19p, and 21q lesions commonly included JAK2, EPOR, and ERG loci, respectively. These genes were affected by amplification or mutations more frequently in AEL than NEL (Figure 1). Group B (n=19, 18%) was enriched for mutations in STAG2, which was significantly more frequent in MEL than in PEL (P&amp;lt;0.05). Compared to STAG2-mutated cases in NEL, those in MEL showed significantly higher frequency of KMT2A-PTD. Group C (n=16, 15%) was defined by NPM1 mutations frequently accompanied by PTPN11 mutations (50% in Group C). This combination was also distinct in MEL and was significantly more frequent than in NPM1-mutated NEL cohort (P&amp;lt;0.05). In Group D (n=29, 28%) without any TP53, STAG2, or NPM1 mutations (triple-negative), RUNX1, ASXL1, BCOR, PHF6, and U2AF1 mutations were enriched compared to triple-negative NEL. In addition, novel loss-of-function USP9X mutations were exclusively identified in Group D AEL (P&amp;lt;0.05, compared to triple-negative NEL), which has been implicated in erythroid leukemogenesis through the TGF beta pathway. Serial sample sequencing analysis revealed that JAK2 mutation positive myeloproliferative neoplasms evolved into PEL. Clinically, patients in Group A showed shorter overall survival time compared to those in any other group. To further search for a novel therapeutic target to the most severe type of AEL, JAK2 inhibitor was administered to xenograft models (from 2 cases) having JAK2 and EPOR amplifications and TP53 mutations. Engrafted cells showed in vitro activation of STAT5 and proliferative capacity enhanced with erythropoietin. In vivo analysis showed that inhibition of JAK/STAT pathway significantly suppressed cell growth and prolonged overall survival. In summary, our findings suggest that AEL is classified into 4 major subgroups having unique genetic and clinical features. PEL and MEL are genetically distinct subtypes, which was also highlighted by comparison to NEL. Frequent involvement of EPOR/JAK/STAT pathway suggests therapeutic indication of JAK inhibition for AEL especially in the most aggressive type of AEL cases with TP53 mutations. Disclosures Yoda: Chordia Therapeutics Inc.: Research Funding. Miyazaki:Kyowa-Kirin: Honoraria; Dainippon-Sumitomo: Honoraria; Nippon-Shinyaku: Honoraria; Chugai: Research Funding; Otsuka: Honoraria; Novartis: Honoraria. Takaori-Kondo:Pfizer: Honoraria; Chugai: Research Funding; Janssen: Honoraria; Kyowa Kirin: Research Funding; Takeda: Research Funding; Ono: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria. Nakagawa:Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Usuki:Astellas Pharma Inc: Research Funding, Speakers Bureau; Daiichi Sankyo Co., Ltd.: Research Funding, Speakers Bureau. Heuser:Bayer Pharma AG, Berlin: Research Funding; Synimmune: Research Funding. Maciejewski:Novartis: Consultancy; Alexion: Consultancy. Ogawa:Qiagen Corporation: Patents &amp; Royalties; RegCell Corporation: Equity Ownership; Kan Research Laboratory, Inc.: Consultancy; ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; Asahi Genomics: Equity Ownership; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding.

Detection of Circulating Tumor DNA in Patients With Uterine Leiomyomas.

PURPOSEThe preoperative distinction between uterine leiomyoma (LM) and leiomyosarcoma (LMS) is difficult, which may result in dissemination of an unexpected malignancy during surgery for a presumed benign lesion. An assay based on circulating tumor DNA (ctDNA) could help in the preoperative distinction between LM and LMS. This study addresses the feasibility of applying the two most frequently used approaches for detection of ctDNA: profiling of copy number alterations (CNAs) and point mutations in the plasma of patients with LM.PATIENTS AND METHODSBy shallow whole-genome sequencing, we prospectively examined whether LM-derived ctDNA could be detected in plasma specimens of 12 patients. Plasma levels of lactate dehydrogenase, a marker suggested for the distinction between LM and LMS by prior studies, were also determined. We also profiled 36 LM tumor specimens by exome sequencing to develop a panel for targeted detection of point mutations in ctDNA of patients with LM.RESULTSWe identified tumor-derived CNAs in the plasma DNA of 50% (six of 12) of patients with LM. The lactate dehydrogenase levels did not allow for an accurate distinction between patients with LM and patients with LMS. We identified only two recurrently mutated genes in LM tumors (MED12 and ACLY).CONCLUSIONOur results show that LMs do shed DNA into the circulation, which provides an opportunity for the development of ctDNA-based testing to distinguish LM from LMS. Although we could not design an LM-specific panel for ctDNA profiling, we propose that the detection of CNAs or point mutations in selected tumor suppressor genes in ctDNA may favor a diagnosis of LMS, since these genes are not affected in LM.

Rapid Identification of Key Copy Number Alterations in B- and T-Cell Acute Lymphoblastic Leukemia by Digital Multiplex Ligation-Dependent Probe Amplification.

Recurrent clonal genetic alterations are the hallmark of Acute Lymphoblastic Leukemia (ALL) and govern the risk stratification, response to treatment and clinical outcome. In this retrospective study conducted on ALL patient samples, the purpose was to estimate the copy number alterations (CNAs) in ALL by digitalMLPA (dMLPA), validation of the dMLPA data by conventional MLPA and RT-PCR, and correlation of CNAs with Minimal Residual Disease (MRD) status. The ALL patient samples (n = 151; B-ALL, n = 124 cases and T-ALL, n = 27 cases) were assessed for CNAs by dMLPA for detection of sub-microscopic CNAs and ploidy status. This assay allowed detection of ploidy changes and CNAs by multiplexing of karyotyping probes and probes covering 54 key gene targets implicated in ALL. Using the dMLPA assay, CNAs were detected in ~89% (n = 131) of the cases with 66% of the cases harboring ≥3 CNAs. Deletions in CDKN2A/B, IKZF1, and PAX5 genes were detectable in a quarter of these cases. Heterozygous and homozygous gene deletions, and duplications were observed in genes involved in cell cycle control, tumor suppression, lineage differentiation, lymphoid signaling, and transcriptional regulators with implications in treatment response and survival outcome. Distinct CNAs profiles were evident in B-ALL and T-ALL cases. Additionally, the dMLPA assay could reliably identify ploidy status and copy number-based gene fusions (SIL-TAL1, NUP214-ABL, EBF1-PDGFRB). Cases of B-ALL with no detectable recurrent genetic abnormalities could potentially be risk stratified based on the CNA profile. In addition to the commonly used gene deletions for risk assessment (IKZF1, EBF1, CDKN2A/B), we identified a broader spectrum of gene alterations (gains of- RUNX1, LEF1, NR3C2, PAR1, PHF6; deletions of- NF1, SUZ12, MTAP) that significantly correlated with the status of MRD clearance. The CNAs detected by dMLPA were validated by conventional MLPA and showed high concordance (r = 0.99). Our results demonstrated dMLPA to be a robust and reliable alternative for rapid detection of key CNAs in newly diagnosed ALL patients. Integration of ploidy status and CNAs detected by dMLPA with cytogenetic and clinical risk factors holds great potential in further refinement of patient risk stratification and response to treatment in ALL.

DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells.

Genome-wide profiling of copy number alterations and DNA methylation in single cells could enable detailed investigation into the genomic and epigenomic heterogeneity of complex cell populations. However, current methods to do this require complex sample processing and cleanup steps, lack consistency, or are biased in their genomic representation. Here, we describe a novel single-tube enzymatic method, DNA Analysis by Restriction Enzyme (DARE), to perform deterministic whole genome amplification while preserving DNA methylation information. This method was evaluated on low amounts of DNA and single cells, and provides accurate copy number aberration calling and representative DNA methylation measurement across the whole genome. Single-cell DARE is an attractive and scalable approach for concurrent genomic and epigenomic characterization of cells in a heterogeneous population.