Identify Copy Number Alterations Research Articles

DEK Regulates B-Cell Proliferative Capacity and Is Associated with Aggressive Disease in Low-Grade B-Cell Lymphoma

Introduction: Non-Follicular Low-Grade B-Cell Lymphomas (LGBCL) are a subset of lymphomas that share overlapping clinical and histologic features. While most cases of LGBCL have an indolent course, some experience aggressive disease with no definitive biomarkers to identify aggressive cases at diagnosis. Significant advances have been made in the molecular classification of other lymphomas, yet molecular profiling and identification of mechanisms driving aggressive disease in LGBCL remain an unmet need. We previously used a multi-omic approach to characterize the molecular and immune landscapes of LGBCL tumors and identified a transcriptomic signature associated with cell proliferation and inferior overall survival (OS) in two independent cohorts (HR 7.82; 95% CI 2.4-25.4; p < 0.001 & HR 10.07; 95% CI 2.00-50.61; p = 0.005) and cases that transformed to DLBCL (Hopper et al., 2023). Here, we identify the oncoprotein DEK as a novel transcriptional regulator of this signature and use a functional genomic approach to further interrogate the role of DEK in B-cell lymphoma. Methods: Tumors from 64 newly-diagnosed/untreated LGBCL cases enrolled in the University of Iowa/Mayo Clinic Molecular Epidemiology Resource were included in this study (SMZL = 48, NMZL = 6, LPL = 5, B-NOS = 3, EMZL = 2). Tumor RNA-seq and paired tumor-normal WES were used to assess DEK expression and identify copy number alterations (CNAs), respectively. DEK deficient (KO) cell line models were generated using CRIPSR/Cas9. DEK expression was assessed by western blot (WB) and immunofluorescence (IF) using standard techniques. Proliferation was assessed by MTT assay. Results: To identify transcriptional regulators of our previously identified signature, we used the tool MAGIC to mine publicly available ChIP-seq data and identified DEK, an oncoprotein associated with tumorigenesis and poor prognosis in several cancers, as a key regulator of genes in our signature (p = 0.008). RNA-seq indicated that high levels of DEK expression associated with inferior OS in LGBCL (HR 2.99; 95% CI 1.21-7.36; p = 0.02). Additionally, we identified DEK as a target of copy number gains/amps in LGBCL (7% of cases), which corresponded to significantly higher DEK expression (p = 0.04). The association of DEK with aggressive lymphoma was confirmed when we assessed its expression in public cell line RNA-seq data and observed the highest expression in lines derived from aggressive lymphomas, which we further validated at the protein level in a panel of B-cell lymphoma cell lines by WB and IF confocal microscopy. Additionally, we detected nuclear localization of DEK, consistent with its role as a transcriptional regulator. As a model of DEK overexpression for functional characterization, we used the SUDHL6 lymphoma cell line, which has an amplification of DEK at 6p22.3 and expresses high levels of DEK protein. Using CRISPR technology, we generated DEK deficient SUDHL6 and tested the impact of loss of DEK expression. DEK KO cells proliferated significantly slower than WT SUDHL6 cells in vitro (p < 0.0001)(Panel A), indicating DEK plays a role in regulating proliferative capacity in lymphoma. To identify mechanisms responsible for reduced proliferation in DEK KOs, we assessed baseline protein expression levels of apoptosis proteins in WT versus KO cells. We found near complete abrogation of anti-apoptotic protein Bcl-2 and reduction of Bcl-xL expression in DEK KO cells (Panel B). These results indicate DEK may contribute to tumor proliferative capacity by regulating susceptibility to apoptosis. Conclusion: DEK has been implicated in regulation of gene expression, but its precise role has remained elusive, with little known about its role in lymphoma. Using an integrative molecular and functional genomics approach, we identified DEK as a novel oncoprotein in LGBCL that is upregulated in cases with inferior clinical outcome and is regulated by copy number gains/amps. DEK plays a role in regulating tumor proliferative capacity by altering susceptibility to apoptosis through regulation of Bcl-2 and Bcl-xL. Collectively, this data suggests high-risk LGBCL tumors may enrich for cells with DEK overexpression or CNAs as a mechanism driving oncogene addiction, highlighting DEK, and its downstream targets, as potential therapeutic targets in a subset of high-risk LGBCL.

Circulating tumor cells (CTCs) in patients with metastatic castration resistant prostate cancer (mCRPC) treated with olaparib plus 177lutetium-prostate specific membrane antigen-617 (177Lu-PSMA-617) in the LuPARP trial.

5064 Background: LuPARP (NCT03874884) is evaluating the safety and efficacy of olaparib in combination with 177Lu-PSMA-617 in patients (pts) with mCRPC who have progressed on an androgen receptor pathway inhibitors and docetaxel. We aim to identify potential prognostic and predictive biomarkers from serial CTC profiling. Methods: Twenty-six pts with high PSMA expression on PSMA-PET received 7.4 GBq of 177Lu-PSMA-617 every 6 weeks (wk) together with an escalating dose-schedule of olaparib (50mg BD – 300mg BD, days 2 to 14 or days -4 to 14) for up to 6 cycles. For CTC analysis, 10 mls of blood was collected at baseline, 12-weekly for 48 wk, and thereafter every 24 wk and at disease progression. CK+, CD45-, and DAPI+ CTCs were enumerated from 3 mls of blood and immunoassayed for PSMA expression using the Epic Sciences platform. Correlations between total and PSMA+ CTC counts and PSA50 response (PSA reduction of ≥ 50%) were evaluated. Low pass whole genome sequencing (lpWGS) was performed on baseline and longitudinal CTC samples to identify copy number alterations. Results: At baseline, 23 of 26 pts (88%) had detectable CTCs (median 2.9 CTC/ml, range 0-30), and of these 23 pts, 17 (74%) had detectable PSMA+ CTCs (median 0.9 CTC/ml, range 0.3-27), indicating heterogeneity of PSMA expression in CTCs. The CTC positivity rates (% of cases ≥1 CTC) at week (w)12, w24, w36, w48 and at disease progression were 57%, 58%, 75%, 36% and 100%, and the PSMA positivity rates (% of cases ≥1 PSMA+ CTC) were 38%, 36%, 22%, 50% and 56%, respectively. Fifteen of 20 (75%) evaluable pts with paired baseline and w12 CTCs had a ≥50% decline in total CTC count, of which 9/15 (60%) pts also achieved a PSA50 response. Five of these 9 (56%) pts had 100% CTC clearance at w12. In terms of PSMA+ CTCs, 14/15 (93%) evaluable pts had ≥50% PSMA+ CTC decline with 13 pts (93%) achieving complete CTC clearance by w12. Six of the 13 pts with complete PSMA+ CTC clearance at w12 also achieved a PSA50 response. Beyond PSMA expression, genomic heterogeneity was evident in baseline and on-treatment CTCs, including recurrent loss of PTEN, TP53, BRCA2, ATM, and RB1, and gain of AR and MYC. lpWGS in 10 baseline samples identified 5 cases with BRCA2 loss and 5 cases with ATM loss. Two pts with BRCA2 loss and 3 pts with ATM loss had a PSA50 response by w12. Conclusions: We observed high rates of total and PSMA+ CTCs in PSMA-expressing mCRPC. Total and PSMA+ CTCs decline with combined olaparib and 177Lu-PSMA-617 treatment. Early declines in total and PSMA+ CTCs including 12w CTC clearance paralleled PSA responses. Notably, total and PSMA+ CTCs rise again in the setting of disease progression. Serial CTC profiling may assist in tracking response to 177Lu-PSMA-617 therapy. Clinical trial information: NCT03874884 .

Performance of a blood-based liquid biopsy test to detect PSMA expression on circulating tumor cells in men with metastatic prostate cancer.

256 Background: PSMA-targeted radioligand therapy has dramatically improved clinical outcomes in men with mCRPC. A blood-based liquid biopsy assay to detect PSMA expression on circulating tumor cells (CTCs) could be helpful to optimize therapeutic decisions and identify patients most likely to benefit from PSMA-targeted therapies. Here we describe the development of this PSMA blood-based assay and the application of the single cell sequencing (SCS) pipeline to identify copy number alterations and further characterize heterogeneity in late-stage disease. Methods: A 4-color immunofluorescence (IF) assay was developed to detect PSMA expression on CTCs on the Epic Sciences liquid biopsy platform. CTCs were identified as DAPI+, cytokeratin (CK)+, and CD45- with appropriate cell morphology. Cells were plated onto glass slides and subjected to IF staining followed by CTC identification using a high throughput scanning platform with digital pathology machine learning algorithms. Cell line cells (LNCaP, PC3s, 22Rv1) of varying PSMA expression levels were spiked into normal blood (CLC/WBC; 1:10000) to create laboratory derived slides. Assay specificity, sensitivity, limit of detection (LOD), precision, and overall accuracy, as well as subcellular localization of biomarker expression were reported. Clinical validation was performed in a cohort of high-risk mCRPC patients (N=24) with previously demonstrated PSMA expression by tissue biopsy, utilizing 3ml of blood. Additionally, a subset of CTCs (36 cells from 11 patients) underwent single-cell low-pass whole genome sequencing to identify copy number alterations. Results: The PSMA CTC assay (Epic Sciences) achieved analytical specificity, sensitivity, and overall accuracy of over 99%. Precision was evaluated using intra-class correlation (ICC) (0.98). The assay showed an LOD of 1 CLC/technical replicate. PSMA expression was specific to staining outside the nucleus and distinguished from CK cytoplasmic staining. Analysis of 24 mCRPC samples revealed that 21/24 (88%) had at least one conventional CTC/mL (range: 0-30 CTCs/mL), of which 16/21 (76%) were PSMA positive (range: 0-27 CTCs/mL) with considerable tumor heterogeneity. 36 sequenced CTCs (N=11 pts) exhibited genomic heterogeneity and frequent AR (3/11), MYC (7/11), and MYCN (5/11) gains or losses of PTEN (4/11), TP53 (7/11), BRCA2 (5/11), CHD1 (6/11), and/or RB1(5/11 pts). Conclusions: The PSMA CTC assay analytical results firmly support its feasibility to detect PSMA expression in CTCs from mCRPC patient samples. The assay demonstrates high sensitivity, specificity, and overall accuracy. Many ongoing trials are designed to target PSMA-positive tumors, positioning this assay as a robust research tool to identify and longitudinally monitor PSMA expression and explore heterogeneity, response, and resistance in these patient populations.

A Methodologically Updated De-Novo Extraction of Copy Number Signatures in Multiple Myeloma: Clinical Significance and Putative Aetiologies

BACKGROUND: The tumor genomes of most Multiple Myeloma (MM) patients are heavily burdened with highly heterogenous copy number (CN) alterations, as detected by multiple molecular methods including whole genome sequencing (WGS), and have been shown to have a strong prognostic and predictive significance for patients' survival. Cutting-edge computational developments have made it possible to analyze complex genomic CN changes by identifying CN alterations' recurrent patterns among large cohorts of patients, named CN signatures (CNS), that are the result of cumulative chromosomic instability (CIN) processes throughout the course of cancer cells evolution. In fact, a robust methodological framework for CNS computation, along with a large compendium of CNS aetiologies have been recently published for many cancer types, notably not including MM (Drews 2022). To our knowledge, the only study that analyzes CNS in MM focused on the role of CNS in predicting chromothripsis events, but remarkably it did not include neither CNS aetiologies nor complete CNS characterization for all the discovered CNS (Maclachlan 2021). AIM: To define a novel methodological framework, based on previous studies, aimed at the identification of CNS in MM, in order to assess both the aetiologies and the biological significance of MM CNS and to evaluate their prognostic impact on MM clinical outcome. The newly extracted CNS defined at diagnosis will be also used as novel disease biomarkers, to develop an improved, aetiology-based MM patients' stratification in different molecular subtypes. METHODS: We calculated the MM genomic distributions of the six essential CN features (segment length, breakpoint per 10 Mb, breakpoint per chromosome arm, segment CN change, CN value, length of oscillating CN states) that have been previously shown to encode patterns of CN alterations, underlying the observed tumor CIN. Starting from 886 WGS generated CN profiles, included in the CoMMpass study, the above mentioned features were computed. Features were then categorized into components, by using mixture models' decomposition and CNS were finally extracted from the components, by using both a Hierarchical Dirichlet Process (HDP) and a Non-Negative Matrix Factorization (NNMF) approach. RESULTS: The main novel characteristics of the developed methodological framework aimed at CNS assessment were 1) the use of a "continuous CN value" feature, which enabled the evaluation of sub-clonal events and 2) the use of a logarithmic scale in "segment length" feature, which favored a higher resolution for categorizing focal and/or gene level CN events, that are very common in MM. Thanks to these implementations, 33 Gaussian mixture components were identified (as compared to 28 detected in Maclachlan 2021). After deriving a Sample x Component - Sum of Posteriors Matrix, the signatures were extracted by applying two parallel state-of-art approaches, namely HDP and NNMF. This allowed the extraction of 9 CNS that were characterized by their component's composition. The signature's exposure levels were correlated to well-known MM biomarkers (e.g. TP53 mut and/or del, 1q CN gain, 13q CN loss, t-IgH, hyperdiploidy), showing that all signatures correlated to at least one of the well known MM biomarkers; in particular, CN.SIG5 exposures was found to correlate to high-risk MM biomarkers (TP53 p<0.001, 1q CN gain p<0.001, t(4;14) p<0.001), thus suggesting its possible involvement in the aetiology of this peculiar genomic configuration. Finally, a survival analysis was performed in patients characterized by high exposure (4th quartile) to the CN.SIG5 (75 patients), as compared to the others (811 patients), showing a significant negative impact of this CNS on both overall (OS p<0.001)) and progression free survivals (PFS p<0.001). Cox-analysis revealed an OS HR= 1.37 p<0.001, PFS HR= 1.16, p<0.001, per 5% increase in exposure. CONCLUSION: By employing a novel bio-informatic approach, based on the use of continuous CN data for CNS extraction, 33 feature's components were identified. We observed that CN.SIG5 significantly affected patients carrying well-known high-risk genomic features, and patients highly exposed to this CNS had decreased PFS and OS. Additional characterizations are needed to unveil the biological meaning of CNS exposure; however, MM CNS, while informing on disease outcome, might be considered as new comprehensive biomarkers in this disease. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Feasibility and clinical utility of comprehensive genomic profiling of hematological malignancies.

Identification of genetic alterations through next‐generation sequencing (NGS) can guide treatment decision‐making by providing information on diagnosis, therapy selection, and prognostic stratification in patients with hematological malignancies. Although the utility of NGS‐based genomic profiling assays was investigated in hematological malignancies, no assays sufficiently cover driver mutations, including recently discovered ones, as well as fusions and/or pathogenic germline variants. To address these issues, here we have devised an integrated DNA/RNA profiling assay to detect various types of somatic alterations and germline variants at once. Particularly, our assay can successfully identify copy number alterations and structural variations, including immunoglobulin heavy chain translocations, IKZF1 intragenic deletions, and rare fusions. Using this assay, we conducted a prospective study to investigate the feasibility and clinical usefulness of comprehensive genomic profiling for 452 recurrently altered genes in hematological malignancies. In total, 176 patients (with 188 specimens) were analyzed, in which at least one alteration was detected in 171 (97%) patients, with a median number of total alterations of 7 (0–55). Among them, 145 (82%), 86 (49%), and 102 (58%) patients harbored at least one clinically relevant alteration for diagnosis, treatment, and prognosis, respectively. The proportion of patients with clinically relevant alterations was the highest in acute myeloid leukemia, whereas this assay was less informative in T/natural killer‐cell lymphoma. These results suggest the clinical utility of NGS‐based genomic profiling, particularly for their diagnosis and prognostic prediction, thereby highlighting the promise of precision medicine in hematological malignancies.

RNAseqCNV: analysis of large-scale copy number variations from RNA-seq data.

Transcriptome sequencing (RNA-seq) is widely used to detect gene rearrangements and quantitate gene expression in acute lymphoblastic leukemia (ALL), but its utility and accuracy in identifying CNVs has not been well described. CNV information inferred from RNA-seq can be highly informative to guide disease classification and risk stratification in ALL due to the high incidence of aneuploid subtypes within this disease. Here we describe RNAseqCNV, a method to detect large scale copy number variations from RNA-seq data. We used models based on normalized gene expression and minor allele frequency to classify arm level CNVs with high accuracy in ALL (99.1% overall and 98.3% for non-diploid chromosome arms, respectively), and the model was further validated with excellent performance in acute myeloid leukemia (accuracy 99.8% overall and 99.4% for non-diploid chromosome arms). RNAseqCNV outperforms alternative RNA-seq based algorithms in calling CNVs in the ALL dataset, especially in samples with a high proportion of CNVs. The CNV calls were highly concordant with DNA-based CNV results and more reliable than conventional cytogenetic-based karyotypes. RNAseqCNV provides a method to robustly identify copy number alterations in the absence of DNA-based analyses, further enhancing the ability of RNA-seq to classify ALL subtype.

Abstract PD15-03: Overlapping molecular features (proliferation, immune signatures andTP53mutations) associated with palbociclib resistance inER+HER2- primary breast cancer

Abstract Background: Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors in combination with anti-hormone therapy are highly effective treatments for oestrogen receptor positive (ER+) and HER2 negative (HER2-) advanced breast cancer. Pre-clinical and clinical studies have reported mechanisms of resistance to CDK4/6 inhibitors to include interferon signalling, high CCNE1 expression and loss of RB1 expression. The PALLET phase II randomized neoadjuvant trial of letrozole (LET) ± palbociclib (PALBO) in postmenopausal ER+HER2- primary breast cancer showed that suppression of proliferation as measured by Ki67 was significantly greater with addition of PALBO to LET but did not result in all patients achieving complete cell-cycle arrest, indicating intrinsic resistance in some patients. We report phenotypes/genotypes associated with that resistance. Methods: In the PALLET trial, 307 patients were randomized to LET+PALBO (n=204) or LET (n=103) for 14wks. For the first 2wks of LET+PALBO patients were randomised to LET, PALBO or LET+PALBO. RNA-seq of baseline samples from consented patients was performed on fresh frozen biopsies for 224 patients (LET-only n=77; LET+PALBO n=147); whole exome sequencing was performed on 188 tumors and matched blood samples (LET-only n=61; LET+PALBO n=127). After 14wks of treatment, those patients with Ki67% &amp;lt; 2.7% were classified as having complete cell-cycle arrest (CCCA). Differentially expressed genes (DEGs) were identified between patients sensitive (CCCA) and resistant (non-CCCA) to treatments with or without PALBO at 14wks by DESeq2. Mutect2 and VarScan was used to identify somatic mutations and CNVkit was used to identify copy number alterations in whole exome sequencing (WES). Results: In LET+PALBO treated patients, higher expression of E2F targets, interferon gamma response and mTORC1 signalling genes were observed in baseline gene expression of non-CCCA patients at 14wks (FDR&amp;lt;0.05, GSEA). Similar results were also observed if using 2wk Ki67 data. In LET-only non-CCCA patients, higher expression of mTORC1 signalling and lower expression of oestrogen response genes (FDR&amp;lt;0.05, GSEA) were observed. Additional analysis of baseline gene expression for non-CCCA at 14wks LET+PALBO patients showed higher expression of immune checkpoint inhibition associated genes including IFNG, IDO1, PD-L1 (FDR&amp;lt;0.05, DESeq2), higher expression of genes expressed only in immune cells and two gene signatures related to interferon signalling and immune checkpoint blockade (FDR&amp;lt;0.05, GSEA). Somatic mutation analysis showed a trend for enrichment of mutations in TP53 for both LET-only and LET+PALBO non-CCCA patients (p=0.02 and p=0.06, respectively, Fisher-exact) and significant enrichment of MAP3K1 mutations in LET-only CCCA patients (p&amp;lt;0.05, Fisher-exact). TP53 mutations were also associated with higher proliferation, mTORC1 and immune related signatures (all p&amp;lt;0.01, Mann-Whitney). Change at 14wks Ki67 was significantly different (p=0.02, Mann-Whitney) between TP53wt and TP53MUT for LET-only patients (median WT = -92%, MUT = -66%, p=0.02, Mann-Whitney ) but not for LET+PALBO (median WT = -99% MUT = -95%, p=0.13, Mann-Whitney). No copy number alterations were significantly enriched in LET+PALBO non-CCCA patients. Conclusion: We observe, confirming previous studies, an association of CDK4/6 inhibitor resistance, high expression of CCNE1 and genes related to interferon gamma signalling. We show that there is an overlap between resistance mechanisms and TP53 mutations. However, ER+HER2- patients with TP53 mutations may still benefit from PALBO adding to suppression of proliferation compared to LET-only treatment. Citation Format: Eugene F Schuster, Hui Xiao, Maggie Cheang, Elena Lopez-Knowles, Lucy Kilburn, Viktoriya Korchina, Sejal Salvi, Samuel A Jacobs, Melanie Finnigan, David A Wheeler, Shannon Puhalla, Donna Muzny, Harsha Doddapaneni, Katherine Pogue-Geile, Yuan Liu, Judith Bliss, Stephen Johnston, Mitch Dowsett, Mothaffar Rimawi, On behalf of the PALLET Trialists. Overlapping molecular features (proliferation, immune signatures andTP53mutations) associated with palbociclib resistance inER+HER2- primary 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 PD15-03.

A Risk Score Incorporating Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

A Risk Score Incorporating Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

Utilization of a Targeted Next Generation Sequencing Assay to Identify Copy Number Alterations in Chronic Lymphocytic Leukemia and Monoclonal B-Cell Lymphocytosis

Utilization of a Targeted Next Generation Sequencing Assay to Identify Copy Number Alterations in Chronic Lymphocytic Leukemia and Monoclonal B-Cell Lymphocytosis

Abstract 571: Detection of somatic copy number alterations from on-target and off-target sequencing data

Abstract Background: Several computational methods have been developed to identify copy number alterations (CNA) leading to or associated with cancer development and shown in recent studies to precede cancer diagnosis by many years. Current methods involving cell-free DNA (cfDNA) targeted sequencing data are based on the depth of coverage of on-target or off-target regions, whereas computational methods incorporating germline SNP information for making inferences on copy number alterations and tumor fraction remain underdeveloped. Methods: Using sequencing data from a large database of more than 100k clinical cell-free DNA (cfDNA) patient samples (Guardant Health, CA), we developed a probabilistic model to simultaneously normalize molecular coverage, segment the genome, predict copy number alterations, and estimate the tumor content in cfDNA samples, while accounting for mixtures of cell populations. The model is using off-target and on-target coverage. Copy number status, including loss of heterozygosity (LoH), is inferred in order to predict gene level somatic CNAs or genome wide instability/LoH. Results: We demonstrated the improvement from the off-target incorporation in three aspects. First, to estimate sensitivity improvement in detections of CNAs, we simulated deletions and amplifications of regions exceeding 40 Mb, using coverage and MAF variability observed in existing data. Combining coverage of on-target and off-target regions is expected to improve the LoD for detection of CNAs by 20%, when compared to CNA detection from on-target coverage. Next, we obtained samples from 15,618 cancer patients of different cancer types processed on GuardantOMNI® RUO and determined human leukocyte antigen (HLA) allele-specific copy number using this off-target assisted method. We observed a high prevalence (more than 15%) of LoH in HLA in bladder cancer, prostate cancer, NSCLC and HNSC, consistent with previous studies that HLA LOH is a common feature of several cancer types and diminishes immunotherapy efficacy. Finally, tumor fraction (TF) estimate was validated by comparing the TF against the maximum variant allele fraction of known oncogenic driver mutations in 6,000 cancer cases of various types. High concordance was observed in CRC samples (R2=0.75), gastric cancer (R2=0.63) and bladder cancer (R2=0.6), which suggest the use of this metric to better estimate tumor shedding levels in cfDNA in cases when driver mutations are not represented on a targeting panel. Conclusion: Our results show that probabilistic modeling of coverage data generated from both on-target and off-target cfDNA sequencing can detect gene specific or whole genome level somatic copy number alterations and LoH. This method may enable improvements in CNA detection accuracy, sensitivity, and specificity in plasma and provides more precise interrogation of LoH status and tumor fraction. Citation Format: Catalin Barbacioru, Han-Yu Chuang, Rebecca Nagy, Darya Chudova, AmirAli Talasaz. Detection of somatic copy number alterations from on-target and off-target sequencing data [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 571.

Clofarabine-Based Consolidation Improves Relapse-Free Survival of Patients with Acute Myeloid Leukemia with Complex or Micro-Complex Karyotype: Results from the Randomized ALFA-0702 Study

Introduction. Acute myeloid leukemia (AML) encompasses heterogeneous entities, but global outcome remains poor. Among genetic AML subgroups, complex karyotypes represent one of the most difficult-to-treat. Genomic alterations arising from recent approaches in molecular genetics have allowed describing new subsets with potential therapeutic implications. Besides, the latter AML classification (“2017 European LeukemiaNet (ELN) risk stratification”) integrates both molecular alterations and conventional cytogenetics. High-resolution single-nucleotide polymorphism array (SNP-Array) identifies copy number alterations (CNA) and copy-neutral losses of heterozygosity (CN-LOH). In the randomized ALFA-0702 study (NCT 00932412), we have recently reported the effects of a CLARA combination (clofarabine + intermediate-dose cytarabine) as compared to standard high-dose cytarabine (HDAC) regimen as consolidation chemotherapy in younger adults with AML. Here, we aimed at evaluating the effects of the CLARA regimen according to patient subsets defined by SNP-array abnormalities.Methods. A total of 221 patients aged 18-59 years old with intermediate- or adverse-risk de novo AML in first complete remission (CR/CRp) after a common intensive induction course were randomized in the ALFA-0702 trial (Thomas et al. JCO 2017). The primary endpoint was relapse-free survival (RFS). Bone marrow or peripheral blood samples at diagnosis were analyzed by Cytoscan HD array (Affymetrix) according to the manufacturer's instructions. Data were screened according to the ChAS 3.1 algorithm, with stringent filter retaining CNA larger than 20 kb - 20 markers, telomeric CN-LOH > 3Mb and interstitial CN-LOH > 10Mb.Results. SNP-array was successfully performed in 187 out of the 221 randomized patients (92 CLARA arm, 95 HDAC arm). Twenty-three patients could not be analyzed in SNP-array for the following reasons: DNA sample was not available (15 patients) or in insufficient quantity (8 patients). SNP-array analysis failed in 11 patients. Median number of genomic SNP-Array abnormalities reached 2 per patient (range, 0-46) and did not significantly differ between both randomization arms (p=0.41). CNA accounted for the most common SNP-Array abnormalities (Loss=54%, Gain=38%, vs. CN-LOH=8%). Conventional cytogenetic analysis showed a complex karyotype (defined by at least 3 chromosomal abnormalities) in 37 patients (11 CLARA, 16 HDAC). In such patients, CLARA consolidation improved RFS (median RFS, 22 vs. 8 months; p=0.027). Interestingly, a similar impact was observed in the 56 patients (27 CLARA, 29 HDAC) with micro-complex karyotypes defined by 4 or more SNP-Array abnormalities. Notably, 7 patients with complex karyotype did not display micro-complex karyotype because of low bone marrow/blood blast infiltration and/or balanced alterations. In patients with micro-complex karyotypes, median RFS was 22 months in the CLARA arm compared to 10 months in the HDAC arm (p<.0001). The rate of patients who received allogeneic stem cell transplantation in first CR did not differ between the two arms (p=0.99). Importantly, CLARA consolidation tended to overcome the poor prognostic impact of patients with micro-complex karyotype. Indeed, patients with such lesions had similar 4-years RFS than other patients in the CLARA arm (44% vs. 47%) while it remained a poor prognosis factor in the HDAC arm (14% vs. 47%; Figure 1).Conclusion. As compared to conventional cytogenetics, SNP-array represents a high-resolution approach to better characterize molecular profile of AML patients by pointing out cryptic molecular abnormalities. Our results suggest that clofarabine-based consolidation benefits both patients with complex karyotypes and micro-complex karyotypes defined by 4 and more SNP-Array abnormalities. Therefore by delineating micro-complex karyotypes in SNP-array, we have defined a new subset of AML patients that could potentially benefit from a clofarabine-based consolidation regimen (21 additional patients in comparison with complex karyotypes). SNP-array could thus help to improve AML management by refining adverse patient subgroups that could potentially benefit from new alternative consolidation regimen. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Genomic Landscapes in Elderly AML

Acute Myeloid Leukemia (AML) in patients over the age of 60 (elderly AML) remains a clinical challenge. Despite advances in the field, outcomes for elderly AML patients remains poor regardless of treatment administered. We hypothesize that elderly AML is characterized by the acquisition of somatic mutations that enhance leukemogenic potential and associate with worse clinical outcomes. To test this hypothesis, we determined the landscape of somatic mutations in de novo AML patient samples from the phase III prospective ECOG-ACRIN Cancer Research Group clinical trial 3999 (E3999; NCT00046930; ages 60-93). DNA was isolated from patient specimens processed to isolate blast-enriched cells (CD3 and CD19 depletion using Miltenyi magnetic beads) and patient-matched CD3-positive cells (flow cytometry) as germline controls. Exome capture was performed in paired disease and germline samples from 210 patients. Samples were sequenced on a HiSeq 2500 obtaining a median coverage of 150x bases per position. Low-coverage whole genome sequencing was used to identify copy number alterations (CNAs) in 202 of the samples. Indexed Illumina libraries were sequenced to a coverage of approximately 3 million reads per sample.The Cancer Genome Project pipeline guidelines were utilized to determine somatic mutation events in the whole exome data. We aligned the reads with BWA mem, determined somatic copy number aberrations using CNVKit, short insertions and deletions (including FLT3 Internal Tandem Duplication) using Pindel, and substitutions using CaVEMan. We then used classical heuristics including strand bias, mapping quality and high rate of presence in the ExAC database to remove artifacts and non-somatic variants. Finally, we used COSMIC and published data in the literature to triage events into known oncogenic events, unknown but likely oncogenic events and variants of unknown significance. CNAs were determined from the whole genome sequencing data by partitioning the human genome into 60 thousands bins (i.e. resolution of 50kb) and counting uniquely mapped reads within the genomic bins/intervals. Read counts within bins were subsequently processed and transformed into integer copy number states.We found a range of 1 to 37 mutational events per sample (median of 15), including 0 to 7 oncogenic or likely oncogenic events (median of 2). Most commonly mutated genes were NPM1 (25.7%); epigenetic modifier genes: TET2 (24.7%), DNMT3A (20.5%), ASXL1 (12.9%), and IDH2 (11.4%); FLT3 (20%); spliceosome complex genes: SRSF2 (19.5%), U2AF1 (10%) and STAG2 (10%); RUNX1 (15.7%); TP53 (12.4%), and NRAS (11.9%). Comparing our AML cohort to the mutation landscape reported by Papaemmanuil et. al., NEJM 2016 (age range: 18 to 84 years), we found that the elderly group was enriched in oncogenic mutations in the SRSF2, TET2, U2AF1 and ASXL1 and depleted for IDH1 and FLT3 (Fisher exact test adjusted p-value <0.05) genes. Furthermore, the elderly AML patient cohort was enriched in spliceosome/cohesin modifier and TP53-complex karyotype subtypes (Fisher exact test: p<2.8*10^-8 and p<10^-5 respectively).Detailed analyses of the mutational spectra in the E3999 clinical trial suggests enrichment for mutations in epigenetic modifiers, spliceosome factors, and cytogenetic events associated with poor prognosis in AML. These may be underlying the aggressive phenotype in this age range and contribute to disease pathogenesis.Authors contributed equally: Ari Melnick and Ross LevineCo-corresponding authors: Maria Kleppe and Francine E. Garrett-Bakelman DisclosuresLowe:Mirimus Inc.: Consultancy. Neuberg:Synta Pharmaceuticals: Other: Stock shares. Levine:Roche: Research Funding; Roche: Research Funding; Qiagen: Equity Ownership; Celgene: Research Funding; Celgene: Research Funding; Qiagen: Equity Ownership.

Definition of a Prognostic Risk-Classifier Based on SNPs Array Analysis of Copy Number Alterations in Newly Diagnosed Transplant-Eligible Multiple Myeloma Patients

BACKGROUND. The genomic heterogeneity that characterizes all Multiple Myeloma (MM) patients (pts) is the consequence of an evolutionary process operating during the pre-neoplastic phase of the disease. Whatever genomic event occurs, it accounts for the de-regulated expression of either one of the cyclin D or other key regulators of cell cycle progression. Therefore, a deficient regulation of cell cycle control is considered as a hallmark of MM. Moreover, among the MM genomic heterogeneity, several lesions are recurrent and their presence significantly impacts the prognosis.AIM. To deeply characterize the MM clone of newly diagnosed MM pts by means of a genomic approach, aimed to identify Copy Number Alterations (CNAs) affecting clinical outcomes.PATIENTS AND METHODS. We analyzed 247 pts who were enrolled in the EMN02/HO95 phase III study and were eligible for randomization to receive standard dose intensification therapy with bortezomib-melphalan-prednisone (VMP) (n=93) or high dose intensification therapy with autologous stem cell transplantation (ASCT) (n=154) after a V-based induction. Genomic data were obtained from all the pts, whose highly purified CD138+ BM plasma cells were profiled by SNPs array. Any CNA ≥50kb was evaluated. At a median follow-up of 34 months (m), the estimated progression-free (PFS) and overall survival (OS) was 63% and 85%, respectively.RESULTS. In order to identify genetically homogeneous subgroups of pts, we first dissected the genomic complexity observed in the overall population. As expected, most pts had a complex genomic background, while occasionally few of them (23/247, 9%) carried only one of the following alterations: CN losses (L) on chr. 13q, CN gains (G) on chr.1q, hyperdiploidy and any IgH translocations. Remarkably, these 4 alterations were also the most frequently observed across the overall pt population, and their combination identified 16 subgroups harbouring a progressively more complex genomic profile. This suggests that these 4 alterations - either combined or alone - are both necessary and sufficient to describe the genomic background of the whole population. Indeed, all the other observed CNAs have a lower frequency and were randomly scattered among the 16 subgroups.When the clinical outcomes of these subgroups were analyzed, it was found that those with inferior outcomes carried at the same time both CN-L on chr.13q and CN-G on chr.1q, regardless of others genomic lesions. Based on this, we re-stratified pts according to the absence or presence of 1 or both of these lesions, to define the following 3 groups: group 1 (64 pts), carrying both CN-L on chr.13q and CN-G on chr.1q; group 2 (94 pts), carrying either CN-L on chr.13q or CN-G on chr.1q; group 3 (89 pts), lacking both these lesions.Providing that pts included in these groups were correctly randomized in a 1:1 ratio to receive either VMP or ASCT, we observed that the 34-m estimates of PFS was significantly shorter in group 1 (48%, 61% and 72% respectively; p=0.0021). OS rates were 72% in group 1 vs 88% in group 2 and 91% in group 3 (p=0.0001).PFS hazard ratio (HR) of pts in group 1 (HR=2,51, 95%CI: 1.48-4.25, p=0.0006) was comparable to that of pts carrying either del(17p) (HR=2.09, 95%CI: 1.20-3.65) or t(4;14) (HR=1.84, 95%CI: 1.14-2.99), resulting as an independent factor in predicting PFS in a Cox multivariate analysis (both from del(17p) and t(4;14), p=0.01). PFS benefit correlated with ASCT in comparison with VMP was statistically significant in groups 2 and 3, while only a trend was observed in group 1 (table 1).The genomic background of pts belonging to group 1 was characterized by the presence of several genomic aberrations, which overall severely compromise genes involved in the control of cell cycle progression (Rb1, CKS1B, MDM4, MCL1, genes coding for the DREAM-complex components, YAP1, MYC, FANCA).CONCLUSIONS. Based on an evolutionary rationale, we proposed a simply, CNAs-based risk-classifier, which was able to segregate our cohort of pts with newly diagnosed MM into 3 well-populated groups, thus recapitulating most of the genomic aberrations commonly described in MM. The 3 groups have different clinical outcomes and PFS benefit imparted from ASCT as compared to VMP. According to the observed genomic background, a strong de-regulation of cell cycle control might be responsible of the dismal outcome of pts carrying both CN-L on chr.13 and CN-G on chr. 1q.Supported by AIRC, Fond. del Monte Bo e Ra [Display omitted] DisclosuresLarocca:Janssen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Amgen: Honoraria. Martinelli:Ariad/Incyte: Consultancy; Pfizer: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Johnson&Johnson: Consultancy; Roche: Consultancy. Sonneveld:Celgene, Amgen, Janssen, Karyopharm, Takeda: Consultancy, Honoraria, Research Funding; Celgene Corporation, Amgen, Janssen, Karyopharm, PharmaMar, SkylineDx: Honoraria; Celgene Corporation, Amgen, Janssen, Karyopharm, SkylineDx, PharmaMar: Consultancy.

Whole-exome sequencing in eccrine porocarcinoma indicates promising therapeutic strategies

Malignant sweat gland tumours are rare, with the most common form being Eccrine porocarcinoma (EP). To investigate the mutational landscape of EP, we performed whole-exome sequencing (WES) on 14 formalin-fixed paraffin-embedded samples of matched primary EP and healthy surrounding tissue. Mutational profiling revealed a high overall median mutation rate. This was attributed to signatures of mutational processes related to ultraviolet (UV) exposure, APOBEC enzyme dysregulation, and defective homologous double-strand break repair. All of these processes cause genomic instability and are implicated in carcinogenesis. Recurrent driving somatic alterations were detected in the EP candidate drivers TP53, FAT2, CACNA1S, and KMT2D. The analyses also identified copy number alterations and recurrent gains and losses in several chromosomal regions including that containing BRCA2, as well as deleterious alterations in multiple HRR components. In accordance with this reduced or even a complete loss of BRCA2 protein expression was detected in 50% of the investigated EP tumours. Our results implicate crucial oncogenic driver pathways and suggest that defective homologous double-strand break repair and the p53 pathway are involved in EP aetiology. Targeting of the p53 axis and PARP inhibition, and/or immunotherapy may represent promising treatment strategies.

Tumor Evolution and Therapeutic Choice Seen through a Prism of Circulating Tumor Cell Genomic Instability.

Circulating tumor cells (CTCs) provide an accessible tool for investigating tumor heterogeneity and cell populations with metastatic potential. Although an in-depth molecular investigation is limited by the extremely low CTC count in circulation, significant progress has been made recently in single-cell analytical processes. Indeed, CTC monitoring through molecular and functional characterization may provide an understanding of genomic instability (GI) molecular mechanisms, which contribute to tumor evolution and emergence of resistant clones. In this review, we discuss the sources and consequences of GI seen through single-cell analysis of CTCs in different types of tumors. We present a detailed overview of chromosomal instability (CIN) in CTCs assessed by fluorescence in situ hybridization (FISH), and we reveal utility of CTC single-cell sequencing in identifying copy number alterations (CNA) oncogenic drivers. We highlight the role of CIN in CTC-driven metastatic progression and acquired resistance, and we comment on the technical obstacles and challenges encountered during single CTC analysis. We focus on the DNA damage response and depict DNA-repair-related dynamic biomarkers reported to date in CTCs and their role in predicting response to genotoxic treatment. In summary, the suggested relationship between genomic aberrations in CTCs and prognosis strongly supports the potential utility of GI monitoring in CTCs in clinical risk assessment and therapeutic choice.

Abstract 676A: Overcoming PARP inhibitor resistance with molecularly guided rational combinations in triple-negative breast cancer patient-derived xenograft models

Abstract Introduction: A constant challenge in the field of cancer therapeutics is the presence of intrinsic resistance or the development of acquired resistance to chemotherapeutic and targeted agents. One of the approaches to overcome drug resistance is the utilization of combination therapies that simultaneously target several molecules involved in cancer development, progression, and metastasis. Numerous methods are utilized to guide the selection of the appropriate combination therapy. We propose a molecularly guided approach for therapy selection to overcome PARP inhibitor resistance. Methods: We used a multipronged strategy to characterize triple-negative breast cancer (TNBC) patient-derived xenograft (PDX) models. We identified copy number alterations and pathogenic germline and somatic variants obtained from genomic sequencing. Proteomic and transcriptomic data were analyzed to evaluate gene expression affected by PARP inhibitor therapy. ATM expression status was also determined by immunohistochemistry. Additionally, a comprehensive literature review was performed focused on PARP inhibitor resistance mechanisms to support our rationale for combination therapy selections. We tested selected combination therapies using a cell viability screening assay in PARP inhibitor-resistant TNBC cell lines. Synergistic combinations were tested in vivo in PARP inhibitor-resistant TNBC PDX models. Results: Model specific pathogenic genomic alterations in PARP inhibitor-resistant TNBC PDX models included genes in the PI3K/AKT/mTOR, DNA damage response, MAPK, and apoptosis signaling pathways. Reverse phase protein array analysis demonstrated differential expression and upregulation of proteins involved in the PI3K/AKT/mTOR and MAPK signaling pathways. Differential gene expression data obtained by RNA sequencing analysis was aggregated to further enhance the individual molecular characterization of PDX models. Subsequently, the antitumor efficacy of selected rational combination therapies was tested in vitro and in vivo. Conclusions: Our study underscores the importance of a detailed analysis of key molecular biomarkers for therapy selection and proposal of rational combinations to overcome resistance to PARP inhibitors. The translational relevance of this method relies on the potential to recapitulate this approach in patient tumor samples and the opportunity to generate and expand PDX resistant models to test the antitumor efficacy of several rational combinations. Our ultimate goal is to identify the right personalized therapy for the individual cancer patient. Citation Format: Christian X. Cruz Pico, Kurt W. Evans, Ken Chen, Xiaofeng Zheng, Argun Akcakanat, Ming Zhao, Coya Tapia, Stephen M. Scott, Erkan Yuca, Funda Meric-Bernstam. Overcoming PARP inhibitor resistance with molecularly guided rational combinations in triple-negative breast cancer patient-derived xenograft models [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 676A.

Copy Number Alterations of Depressed Colorectal Neoplasm Predict the Survival and Response to Oxaliplatin in Proximal Colon Cancer.

Depressed colorectal neoplasm exhibits high malignant potential and shows rapid invasiveness. We investigated the genomic profile of depressed neoplasms and clarified the survival outcome and treatment response of the cancers arising from them. We examined 20 depressed and 13 polypoid neoplasms by genome-wide copy number analysis. Subsequently, we validated the identified copy number alterations (CNAs) in an independent cohort of 37 depressed and 42 polypoid neoplasms. Finally, the CNAs were tested as biomarkers in 530 colorectal cancers (CRCs) to clarify the clinical outcome of depressed neoplasms. CNAs in MYC, CCNA1, and BIRC7 were significantly enriched in depressed neoplasms and designated as the D-marker panel. CRCs with a D-marker panel have significantly shorter progression-free survival compared with those without (p = 0.012), especially in stage I (p = 0.049), stages T1+2 (p = 0.027), and proximal cancers (p = 0.002). The positivity of the D-marker panel was an independent risk factor of cancer progression (hazard ratio (95% confidence interval) = 1.52 (1.09–2.11)). Furthermore, the proximal CRCs with D-marker panels had worse overall and progression-free survival when taking oxaliplatin as chemotherapy than those that did not. The D-marker panel may help to optimize treatment and surveillance in proximal CRC and develop a molecular test. However, the current result remains preliminary, and further validation in prospective trials is warranted in the future.

Copy Number Alterations Predict the Survival of Early Colorectal Cancer with Depressed Morphology

Background: Depressed colorectal neoplasms exhibit a high malignant potential and may become invasive rapidly but their genomic alterations remain unknown. We investigated the genomic alterations of depressed neoplasms and potential implications on long-term survival. Methods: We examined 20 depressed neoplasms and 15 polypoid neoplasms by genome-wide copy number analysis. Subsequently, we validated the identified copy number alterations in an independent sample of 37 depressed and 42 polypoid neoplasms. Specific copy number alterations were tested in 530 colorectal cancers in order to clarify the clinical outcome of depressed colorectal neoplasms. Findings: Copy number alterations in MYC, CCNA1, and BIRC7 were significantly enriched in depressed neoplasms and designated as the D-marker panel. In the validation set, the panel presented a positive predictive value, sensitivity and accuracy of 80·0%, 75·7% and 79·7% respectively for discriminating the depressed neoplasms. colorectal cancers developing from depressed neoplasms account for 22·1% of all colorectal cancers and have a significantly more unfavorable progression-free survival compared with colorectal cancer without those biomarkers, especially in stage I, T1+2, and proximal cancers. Interpretation: In this article, we characterize the genome-wide landscape in the depressed neoplasm and its specific biosignature. The D-marker panel may help to optimize the treatment of depressed neoplasms and surveillance strategies, and develop more effective molecular screening tests in the future. Funding Statement: Funding by the National Taiwan University Hospital (Grand Number: NTUH 107-M3990, NTUH 108-M4209), Ministry of Science and Technology, Taiwan (Grant Number: MOST-105-2314-B-002-047, MOST106-2319-B-002-002, MOST107-2319-B-002-002), and as well as the “Center of Precision Medicine” from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan. Declaration of Interests: The authors declare that they have no conflicts of interest. Ethics Approval Statement: Before initiation, this study received approval (No. 201712033RINC) from the Institutional Review Board and Ethical Committee of National Taiwan University Hospital.

Integrated analyses of murine breast cancer models reveal critical parallels with human disease

Mouse models have an essential role in cancer research, yet little is known about how various models resemble human cancer at a genomic level. Here, we complete whole genome sequencing and transcriptome profiling of two widely used mouse models of breast cancer, MMTV-Neu and MMTV-PyMT. Through integrative in vitro and in vivo studies, we identify copy number alterations in key extracellular matrix proteins including collagen 1 type 1 alpha 1 (COL1A1) and chondroadherin (CHAD) that drive metastasis in these mouse models. In addition to copy number alterations, we observe a propensity of the tumors to modulate tyrosine kinase-mediated signaling through mutation of phosphatases such as PTPRH in the MMTV-PyMT mouse model. Mutation in PTPRH leads to increased phospho-EGFR levels and decreased latency. These findings underscore the importance of understanding the complete genomic landscape of a mouse model and illustrate the utility this has in understanding human cancers.

Micropapillary variant of mucinous carcinoma of the breast shows genetic alterations intermediate between those of mucinous carcinoma and micropapillary carcinoma.

Micropapillary variant of mucinous carcinoma of the breast (MPMC) is a rare histological form of oestrogen receptor (ER)-positive invasive carcinoma that is characterised by micropapillary clusters of tumour cells in lakes of extracellular mucin. The aims of this study were to determine the genetic alterations underpinning MPMCs, and to determine whether they overlap with those of mucinous carcinomas and/or invasive micropapillary carcinomas. DNA from five MPMCs was subjected to whole-exome sequencing. Somatic mutations, copy number alterations and mutational signatures were determined with state-of-the-art bioinformatics methods. No mutations in genes significantly mutated in breast cancer, including TP53, PIK3CA, GATA3, and MAP3K1, were detected. We identified copy number alterations that have been reported in invasive micropapillary carcinomas, such as recurrent gains in 1q, 6p, 8q, and 10q, and recurrent losses in 16q, 11q, and 13q, as well as a recurrent 8p12-8p11.2 amplification encompassing FGFR1. Like mucinous carcinomas, three of the five MPMCs analysed lacked PIK3CA mutations, 1q gains, and 16q losses, which are the hallmark genetic alterations of ER-positive breast cancers, whereas two MPMCs harboured 16q losses and/or a complex pattern of copy number alterations similar to those found in breast-invasive micropapillary carcinomas. MPMCs are heterogeneous at the genetic level; some tumours show a pattern of somatic genetic alterations similar to those of mucinous carcinomas, whereas others resemble invasive micropapillary carcinomas at the genetic level. These findings suggest that MPMCs may not constitute one histological subtype, but rather a convergent phenotype that can stem from mucinous carcinomas or invasive micropapillary carcinomas.