Copy Number Alteration Profiles Research Articles

CDKN2A copy number alteration in bladder cancer: Integrative analysis in patient-derived xenografts and cancer patients

Bladder cancer (BlCa) is an extensively heterogeneous disease that leads to great variability in tumor evolution scenarios and lifelong patients’ surveillance, emphasizing the need for modern minimally-invasive precision medicine. Herein, we have explored the clinical significance of copy-number alterations (CNAs) in BlCa. CNAs profiling was performed in 15 patient-derived xenografts (PDXs) and validated in TCGA-BLCA (n=408) and Lindgren et al. (n=143) cohorts. CDKN2A copy-number loss was identified as the most frequent CNA in bladder tumors, associated with reduced CDKN2A expression, tumors of papillary phenotype and prolonged PDX survival. Study’s screening cohort consisted of 243 BlCa patients and CDKN2A copy-number was assessed in genomic DNA and cell-free DNA (cfDNA) from 217 tumors and 189 pre-treatment serum samples, respectively. CDKN2A copy-number loss was correlated with superior disease-free and progression-free survival of non-muscle-invasive bladder cancer (NMIBC) patients. Moreover, higher CDKN2A index (CDKN2A/LEP ratio) in pre-treatment cfDNA was associated with advanced tumor stage, grade and short-term NMIBC progression to invasive disease, while multivariate models fitted for CDKN2A index in pre-treatment cfDNA offered superior risk-stratification of T1/high grade and EORTC high-risk patients, enhancing prediction of treatment outcome. CDKN2A copy-number status could serve as minimally-invasive tool in improving risk-stratification and supporting personalized prognosis in BlCa.

Abstract 7043: Genomic profiling of DLL3-positive and negative CTCs in small cell lung cancer

Abstract BACKGROUND: Delta-like ligand 3 (DLL3), an atypical Notch family protein implicated in neuroendocrine tumorigenesis, has emerged as a promising therapeutic target in small cell lung cancer (SCLC), prompting numerous clinical trials investigating DLL3-targeted treatments. Exploring DLL3 in circulating tumor cells (CTCs) through liquid biopsy, coupled with comprehensive genomic analysis, presents an invaluable and minimally-invasive avenue for monitoring disease progression. This approach holds the potential to tailor personalized treatment strategies, emphasizing the critical need for in-depth investigations into both DLL3-positive and negative cell genomic compositions. METHODS: This study examined blood collected in CellSave preservative tubes from stage I (n=17) and stage IV (n=12) SCLC patients, as well as healthy donors (n=10). The CELLSEARCH® platform was employed to count EpCAM-enriched CTCs and evaluate DLL3 protein expression. Subsequently, individual CTCs were isolated based on the presence and absence of DLL3 expression using the DEPArray™ PLUS. The isolated DLL3-negative and positive CTCs were subjected to low-pass sequencing using the Ampli1™ LowPass Kit to uncover genomic aberrations. RESULTS: CTCs were absent in the healthy control group. In stage I patients, CTCs were identified in 5.8% of blood samples, while in stage IV patients, they were present in 50% of samples, with an average CTC count of 148 in stage IV. Among a total of 2074 detected CTCs, 460 were DLL3-positive, accounting for 6-28% of EpCAM-enriched CTCs in individual patients. Analysis of >300 copy number alteration (CNA) profiles of sorted single cells revealed considerable inter-patient and intra-patient heterogeneity, delineating recurrent clonality and specific genomic alterations in DLL3-negative CTCs. In contrast, DLL3-positive cells showed more stochastic CNA profiles, suggestive of apoptosis-related DNA fragmentation. CONCLUSIONS: Integrating CellSearch, DEPArray, and low-pass sequencing provides a minimally-invasive approach to compare genomic characteristics in DLL3-positive and negative CTCs from SCLC patients. Extension of this approach to a larger patient cohort and employing machine learning algorithms will facilitate identification of patterns within diverse CNA profiles, improving patient stratification and predicting treatment responses for personalized therapeutic strategies in SCLC. Citation Format: Zoltan Simandi, Thai Bui, Alberto Ferrarini, Steven Hepburn, Richard G. Del Mastro. Genomic profiling of DLL3-positive and negative CTCs in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7043.

Abstract 4414: Genome-wide DNA methylation classifier diagnoses pancreatic ductal adenocarcinoma in CUP setting

Abstract Introduction: The metastasis of a pancreatic ductal adenocarcinoma (PAAD) is a diagnosis of exclusion and one of the most common causes of cancer of unknown primary (CUP). We have recently developed a genome-wide DNA methylation-based neural network classifier that can accurately differentiate between liver metastasis of a PAAD and intrahepatic cholangiocarcinoma (iCCA) (PAAD-iCCA-Classifier). Therefore, the aim of our study was to test whether our PAAD-iCCA-Classifier can be extended to be used to correctly diagnose PAAD metastases from other sites in CUP setting. Methods: For this purpose, we enhanced the anomaly detection layer of the classifier by incorporating ten mimicker carcinomas to be excluded by this layer. We used a validation set 1 (n=3786) including primary PAAD (n=242), PAAD liver metastases (n=20), iCCA (n=151) and 10 other mimicker carcinomas (n=3373) and a validation set 2 (n=26) including primary PAAD from a real-life clinical cohort from an independent institution to validate the classifier. Next, we tested the classifier on 16 PAAD initially considered CUP samples (test set) from different sites: peritoneum, lung, liver, and lymph node. The clinical history and diagnostic imaging of these samples were used to confirm PAAD as the most probable origin. We further performed differentially methylated probes (DMP) and copy number alterations (CNA) analysis of primary PAAD and metastatic PAAD from different locations. Results: The improved version of the PAAD-iCCA-Classifier achieved an accuracy of 98.43% on the validation set 1 and was able to exclude most of the mimicker carcinomas. On validation set 2, the classifier achieved an accuracy of 88.46%. Medical history, imaging and immunohistochemical analysis of the test set samples confirmed the diagnosis of PAAD. The DNA methylation classifier correctly labeled 15/16 PAAD metastatic samples as PAAD (93.75% accuracy). We observed that the classifier performance was negatively affected by a high CD3+ immune infiltrate and positively affected by high tumor purity and high proliferation rate. CNA revealed that PAAD liver metastases have a distinct CNA profile characterized by chromosome 6, 9 (CDKN2A/B) and 18q (SMAD4) deletions. DMP analysis showed that PAAD liver metastases have global hypomethylation of both promoter- and enhancer-associated CpGs compared to primary PAAD and PAAD peritoneal carcinomatosis. Finally, gene ontology analysis revealed that different epithelial-mesenchymal transition pathways are activated in PAAD liver metastases compared to PAAD peritoneal carcinomatosis. Conclusion: Our tool performs well in classifying metastatic PAAD samples and could be of great clinical use when a PAAD origin is suspected in the case of a CUP. DMP and CNA profiles show that PAAD liver metastases may have a distinct DNA methylation and copy number profile compared to primary and peritoneal carcinomatosis PAAD. Citation Format: Teodor G. Calina, Eilís Perez, Simon Schallenberg, Horst David, Erik Knutsen, David Capper, Mihnea P. Dragomir. Genome-wide DNA methylation classifier diagnoses pancreatic ductal adenocarcinoma in CUP setting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4414.

Abstract 2296: Liquid biopsy of cerebrospinal fluid in breast to brain metastases

Abstract Up to 30% of patients with breast cancers will develop brain metastases, and this risk is especially high with HER2-positive cancers. For patients with central nervous system metastases, cerebrospinal fluid (CSF) liquid biopsies are a promising opportunity to monitor disease, inform treatment, and predict prognosis. This study explores the CSF liquid biopsy analytes from 3 patients with central nervous system metastases analyzed with the third generation non-enrichment high-definition single cell assay (HDSCA3.0) workflow. The detection of cellular analytes was compared between the CSF and matched peripheral blood (PB) samples. Circulating tumor cells (CTCs) were detected in the CSF but not the PB and were subsequently molecularly characterized by single cell genomics and targeted multiplexed proteomics to reveal a clonal population of phenotypically heterogeneous cells. There was a lack of concordance between CTCs and cfDNA of the CSF in the copy number alteration profiles. In an extracellular vesicle surface marker analysis of the CSF, there was a high signal among tetraspanin CD9/CD63/CD81, with CD81 signal the highest across all 3 patients. The data indicates that the CSF may be used as a diagnostic or potentially prognostic tool to measure and characterize disease burden. Citation Format: Stephanie N. Shishido, Amelia Marvit, Saul Priceman, Jana Portnow, Peter Kuhn. Liquid biopsy of cerebrospinal fluid in breast to brain metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2296.

Abstract 3693: Molecular and functional characterization of circulating CK+/CD45+ cells in breast cancer

Abstract Background: Circulating tumor cells (CTCs) are considered a key element in metastatic progression and represent a validated prognostic biomarker in breast cancer (BC). CTCs in BC are normally defined as epithelial cells (positive for EPCAM or cytokeratin, CK) lacking the expression of the leukocyte marker CD45. Circulating cells expressing both EPCAM/CK and CD45 (dual positive, DPcells) have however been reported in BC but not investigated. It is believed that DPcells derive from the heterotypic cell fusion of tumor and immune cells, but this hypothesis has not been demonstrated yet. We recently reported, for the first time, the association of DPcells with worse survival in a cohort of 341 BC patients (pts) [Reduzzi et al. ASCO 2022] supporting their tumor origin. Here, we further investigated their malignancy and metastatic potential by molecular profiling and functional experiments. Methods: The study consisted of 2 components: A) Single CTCs and DPcells were enriched from the blood of BC patients with the CellSearch platform, and isolated with the DEPArray system. Single cells underwent whole genome amplification and lowpass whole genome sequencing for single cell copy number alteration (CNA) profiling; B) DPcells and CTCs were investigated in the blood of immunodeficient (NSG) and immunocompetent (FVB) mouse models using various cell lines (LM2, 4T1, MVT1). To test their metastatic potential, DPcells from the primary tumor of FVB donor mice were transplanted into recipient NSG mice, and the metastatic burden in the lungs and liver quantified, in comparison with control CD45- tumor cells. Results: We analyzed 73 DPcells and 18 CTCs collected from 16 BC pts: Aberrant genomes were observed in 28% and 93% of evaluable cells, respectively. When collected from the same pt, CTCs showed clonal CNA profiles, while DPcells were highly heterogeneous. In vivo, DPcells could only be detected in the blood of FVB mice but not in NSG mice. They were very rare, comprising of only about 3% of the total CTC count. When DPcells and control tumor cells were isolated from the primary tumor of 10 donor mice and transplanted into the tail vein of 10 recipient mice, we observed no significant differences in the metastatic colonization of the lungs and liver by the two population, indicating that DPcells do in fact possess metastatic ability, and to a similar extent as control cancer cells. Conclusions: DPcells can have an aberrant genome, supporting their malignancy. Contrary to CTCs, DPcells’ CNA profiles are not clonal and, in vivo, they can only be observed in immunocompetent models; both observations support the tumor/immune fusion hypothesis. Finally, DPcells show metastatic potential in mice, in line with the association with worse survival we previously observed in BC pts. Overall DPcells seem a new CTC subpopulation that should not be neglected anymore. More studies are needed to better understand their origin and phenotypic/molecular features. Citation Format: Carolina Reduzzi, Eleonora Nicolo, Lauren L. Ozimski, Marco Silvestri, Lorenzo Gerratana, Mara S. Serafini, Elisabetta Molteni, Nadia Bayou, Amanda K. Strickland, Huiping Liu, Vera Cappelletti, Nicola Aceto, Massimo Cristofanilli. Molecular and functional characterization of circulating CK+/CD45+ cells in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3693.

Abstract 6929: Inter- and intratumoral PIK3CA subclonal diversity in breast cancer contextualized by single-cell multiomics

Abstract Rare clonotypes within pre-cancerous tissues can drive progression to cancer. However, the evolution of rare clonotypes in tumors or normal tissue cannot be defined in the absence of single-cell resolution. At this single-cell level, multiomic interrogation across the Central Dogma of Biology provides enhanced power to reconstruct such evolutionary trajectories, defining the mutational profile, cell identify, and receptor expression within each subpopulation. Leveraging a multiomic approach, we aimed to define how different mutations in the same oncogenic driver observed in the same tumor resection associate with copy number variation (CNV) across the genome. We analyzed individual ductal carcinoma in situ/invasive ductal carcinoma cells using a unified whole-genome and full-transcript RNAseq workflow (ResolveOME™, BioSkryb Genomics) coupled with panel-level extracellular protein information through oligo-conjugated antibodies (BioLegend). We sequenced the exomes and transcriptomes of ResolveOME-amplified single cells from mastectomy samples from twelve patients. At the single nucleotide variant (SNV) level, we identified an allelic series of PIK3CA oncogenic driver mutations in the same tumor resection. A single amino acid, in-frame deletion of E109 dominated the sample, followed by H1047R and K111E in decreasing subclonal abundance. A fourth mutation, E345T, not present in the first sample, was detected as the sole PIK3CA variant in the second tumor sample. Intriguingly, each respective PIK3CA mutation class was associated with a distinct copy number alteration profile revealed by low-coverage whole-genome sequencing: Cells harboring the predominant ΔE109 mutation displayed chromosome 8p,16p, and 17 loss while the less abundant H1047R mutation was in single cells harboring 1q gain, 4q loss, and 22 loss in addition to the 8p and 16q loss present in the ΔE109 cells. PIK3CA K111E had a quiescent, 2n copy number profile. The transcriptomic arm of ResolveOME, containing an oligo-conjugated antibody readout of surface protein expression, jointly confirmed the epithelial identity for the cells harboring the oncogenic PIK3CA mutations. A subpopulation of cells harboring prototypical breast cancer CNV were typed as non-epithelial with increased stemness characteristics, indicative of the ability to resolve phenotypic cellular states. These results suggest a tight interrelationship between CNV and SNV influencing the relative rate of clonal expansion. They also provide the opportunity to explore CNV:SNV signature association with loci exclusive of PIK3CA, and to exploit the power of multiomic integration for lineage reconstruction and for defining common oncogenic signatures of the evolving tumors. Citation Format: Jon Zawistowski, Isai Salas-Gonzalez, Tia Tate, Tatiana Morozova, Katherine Kennedy, Durga Arvapalli, Jamie Remington, Jeffrey Marks, E. Shelley Hwang, Gary Harton, Victor Weigman, Jay A. West. Inter- and intratumoral PIK3CA subclonal diversity in breast cancer contextualized by single-cell multiomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6929.

Profiling of Copy Number Alterations Using Low-Coverage Whole-Genome Sequencing Informs Differential Diagnosis and Prognosis in Primary Cutaneous Follicle Center Lymphoma

Primary cutaneous follicle center lymphoma (PCFCL) has an excellent prognosis using local treatment, whereas nodal follicular lymphoma (nFL), occasionally presenting with cutaneous spread, often requires systemic therapy. Distinction of the 2 diseases based on histopathology alone might be challenging. Copy number alterations (CNAs) have scarcely been explored on a genome-wide scale in PCFCL; however, they might serve as potential biomarkers during differential diagnosis and risk stratification. Low-coverage whole-genome sequencing is a robust, high-throughput method for genome-wide copy number profiling. In this study, we analyzed 28 PCFCL samples from 20 patients and compared the copy number profiles with a cohort of diagnostic samples of 64 nFL patients. Although the copy number profile of PCFCL was similar to that of nFL, PCFCL lacked amplifications of 18q, with the frequency peaking at 18q21.33 in nFL cases involving the BCL2 locus (PCFCL: 5.0% vs nFL: 31.3%, P = .018, Fisher exact test). Development of distant cutaneous spread was significantly associated with higher genomic instability including the proportion of genome altered (0.02 vs 0.13, P = .033) and number of CNAs (2 vs 9 P = .017), as well as the enrichment of 2p22.2-p15 amplification involving REL and XPO1 (6.3% vs 60.0%, P = .005), 3q23-q24 amplification (0.0% vs 50.0%, P = .004), 6q16.1-q23.3 deletion (6.3% vs 50.0%, P = .018), and 9p21.3 deletion covering CDKN2A and CDKN2B loci (0.0% vs 40.0%, P = .014, all Fisher exact test) in PCFCL. Analysis of sequential tumor samples in 2 cases harboring an unfavorable clinical course pointed to the acquisition of 2p amplification in the earliest common progenitor underlining its pivotal role in malignant transformation. By performing genome-wide copy number profiling on the largest patient cohort to date, we identified distinctive CNA alterations conceivably facilitating the differential diagnosis of PCFCL and secondary cutaneous involvement of nFL and potentially aiding the risk stratification of patients with PCFCL in the future.

Tumor Copy Number Alteration Burden as a Predictor for Resistance to Immune Checkpoint Blockade across Different Cancer Types.

Immune checkpoint blockade (ICB) benefits only a subset of advanced cancer patients, and predictive biomarkers for immunotherapy response are needed. Recently, copy number alteration (CNA) burden has been proposed to predict ICB resistance. We assessed this finding using the publicly accessible data for 1661 ICB-treated patients whose tumors were profiled by MSK-IMPACT, an approved targeted assay in clinical care. We tested the hypothesis that the continuous increase in CNA burden is associated with poor overall survival following ICB. In addition, we hypothesized that the combinatorial biomarkers of tumor mutational burden (TMB) and CNA burden would better stratify patients for immune status and ICB response. Of the 1661 cases, 79% (n = 1307) were treated with anti PD-1/PD-L1 and the remaining 21% (n = 354) with anti CTLA-4 or the combination of both. In a multivariate analysis, increase in CNA burden was associated with poor overall survival [HR = 1.52, 95% CI (1.01-2.30), p = 0.04]. The combination of biomarkers TMB and CNA burden stratified patients into four clinically distinct subsets among which "LowTMB/HighCNA" showed the worst survival (p < 0.0001). The four patient subsets had unique CNA profiles and enriched pathways, which could predict transcriptional and phenotypic effects related to immune signaling and CD8+ T-cell abundance in the tumor microenvironment. CNA burden was associated with poor overall survival in patients receiving ICB and could improve patient stratification when incorporated with TMB. These findings may guide patient selection for immunotherapy or alternative strategies.

Refinement of prognostication for IDH-mutant astrocytomas using DNA methylation-based classification.

The 2021 World Health Organization (WHO) grading system of isocitrate dehydrogenase (IDH)-mutant astrocytomas relies on histological features and the presence of homozygous deletion of the cyclin-dependent kinase inhibitor 2A and 2B (CDKN2A/B). DNA methylation profiling has become highly relevant in the diagnosis of central nervous system (CNS) tumors including gliomas, and it has been incorporated into routine clinical diagnostics in some countries. In this study, we, therefore, examined the value of DNA methylation-based classification for prognostication of patients with IDH-mutant astrocytomas. We analyzed histopathological diagnoses, genome-wide DNA methylation array data, and chromosomal copy number alteration profiles from a cohort of 385 adult-type IDH-mutant astrocytomas, including a local cohort of 127 cases and 258 cases from public repositories. Prognosis based on WHO 2021 CNS criteria (histological grade and CDKN2A/B homozygous deletion status), other relevant chromosomal/gene alterations in IDH-mutant astrocytomas and DNA methylation-based subclassification according to the molecular neuropathology classifier were assessed. We demonstrate that DNA methylation-based classification of IDH-mutant astrocytomas can be used to predict outcome of the patients equally well as WHO 2021 CNS criteria. In addition, methylation-based subclassification enabled the identification of IDH-mutant astrocytoma patients with poor survival among patients with grade 3 tumors and patients with grade 4 tumors with a more favorable outcome. In conclusion, DNA methylation-based subclassification adds prognostic information for IDH-mutant astrocytomas that can further refine the current WHO 2021 grading scheme for these patients.

Whole-Genome Comparative Copy Number Alteration Profiling between Malignant Pleural Mesothelioma and Asbestos-Induced Chronic Pleuritis.

Malignant pleural mesothelioma (MPM) is rare and aggressive cancer. The most important risk factor for MPM is exposure to asbestos. In this study, we scanned the genomes of individuals MPM and asbestos-induced chronic pleuritis (AICP) to compare and determine copy number alterations (CNAs) between two asbestos-related diseases. We used high-resolution SNP arrays to compare CNA profiles between MPM (n = 55) and AICP (n = 18). DNAs extracted from pleural tissues in both groups. SNP array analysis revealed common losses at 1p, 3p, 6q, 9p, 13q, 14q, 15q, 16q, 22q and frequent gains at chromosomes 1, 3, 5, 7, 8, and 6p, 12q, 15q, 17p, 20q in MPMs (frequencies max 67%-min 30%; these alterations were not detected in AICPs. Besides detecting well-known MPM-associated CNAs, our high -resolution copy number profiling also detected comparatively rare CNAs for MPMs including losses like 9q33.3, 16q and gains of 1p, 1q, 3p, 3q, 6p, 7q, 15q, 12q, 17p, 20q at significant frequencies in the MPM cohort. We also observed Copy Number gains clustered on the NF2 locus in AICPs, whereas this region was commonly deleted in MPMs. According to this distinct genomic profiles between the two groups, AICPs genomes can be clearly distinguished from highly altered MPM genomes. Hence, we can suggest that SNP arrays can be used as a supporting diagnostic tool in terms of discriminating asbestos-related malignant disease such as MPM and benign pleural lesions, which can be challenging in most instances.

Combination of minimal residual disease on day 15 and copy number alterations results in BCR-ABL1-negative pediatric B-ALL: A powerful tool for prediction of induction failure

The current genomic abnormalities provide prognostic value in pediatric Acute Lymphoblastic Leukemia (ALL). Furthermore, Copy Number Alteration (CNA) has recently been used to improve the genetic risk stratification of patients. This study aimed to evaluate CNA profiles in BCR-ABL1-negative pediatric B-ALL patients and correlate the data with Minimal Residual Disease (MRD) results after induction therapy. We examined 82 bone marrow samples from pediatric BCR-ABL1-negative B-ALL using the MLPA method for the most common CNAs, including IKZF1, CDKN2A/B, PAX5, RB1, BTG1, ETV6, EBF1, JAK2, and PAR1 region. Subsequently, patients were followed-up by multiparameter Flow Cytometry for MRD (MFC-MRD) assessment on days 15 and 33 after induction. Data showed that 58.5 % of patients carried at least one gene deletion, whereas 41.7 % of them carried more than one gene deletion simultaneously. The most frequent gene deletions were CDKN2A/B, ETV6, and IKZF1 (30.5 %, 14.6 %, and 14.6 %, respectively), while the PAR1 region showed predominantly duplication (30.5 %). CDKN2A/B and IKZF1 were related to positive MRD results on day 15 (p = 0.003 and p = 0.007, respectively). The simultaneous presence of more than one deletion was significantly associated with high induction failure (p = 0.001). Also, according to the CNA profile criteria, the CNA with poor risk (CNA-PR) profile was statistically associated with older age and positive MRD results on day 15 (p = 0.014 and p = 0.013, respectively). According to our results, the combined use of CNAs with MRD results on day 15 can predict induction failure and be helpful in ameliorating B-ALL risk stratification and treatment approaches.

Prognostic Impact of Chromosomal Abnormalities in TP53-Mutated Acute Myeloid Leukemia and High-Risk Myelodysplastic Syndromes

Background: Background: Acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) exhibit clinical heterogeneity, and genomic profiles play a crucial role in disease characteristics and survival outcomes. Elli Papaemmanuil et al. classified AML into 11 genomic subgroups (NEJM, 2016), where TP53 mutations and aneuploidy predicted dismal survival. Cases with TP53 mutations are often accompanied by complex chromosomal abnormalities (CAs), but the prognostic impact and target genes of CAs have not been fully studied. Methods: To clarify this issue, specimens of AML and MDS with excess blasts (MDS-EB) were collected from 1,001 patients enrolled at collaborating institutes of Kyoto Hematology Study Group between July 2017 and January 2023. Targeted capture sequencing with 1,216 single nucleotide polymorphism sites was used to analyze primary samples, allowing assessment of copy number alteration (CNA) profiles. The target gene panel included common mutations in myeloid neoplasms. Mutation calling was performed using the established pipeline Genomon 2. Prognostic impact of CNA, single nucleotide variants, and insertion/deletion with 10% or more frequency was evaluated, and the frequencies of CNA were calculated for the short and long arms of chromosomes 1-22 and the X chromosome. Univariate and multivariate analyses were conducted using statistical significance criteria of p &amp;lt; 0.05. Results: The average sequencing depth was 548. Among 1,001 patients, 224 (22.4%) harbored TP53 mutations. TP53-mutated cases had a median age of 70 (24-95) years old at diagnosis, with 117 (52.2%) being AML and 107 (47.8%) MDS-EB. TP53 biallelic mutation, defined by 2 or more mutations in TP53 or loss of heterogeneity of TP53 locus, was present in 200 (89.3%) of cases, more commonly associated with 3 or more CAs or CNA (complex karyotype (CK)-like) than monoallelic mutation (99% vs. 42%, p = 1.9x10 -13). The most frequent affected lesions were del(5q), del(7q), del(7p), del(12p), del(18q), gain(11q), and gain(21q) with frequencies of 76%, 59%, 34%, 33%, 28%, 27%, and 26%, respectively. In survival analysis, gain(21q), gain(19p), del(16q), del(3q), del(19p), del(13q), and del(4q), along with diagnosis of AML ( p = 2.0x10 -2), TP53 biallelic mutation ( p = 6.8x10 -3), and CK-like ( p = 3.4x10 -3), were associated with poor outcomes in univariate analysis. Multivariate analysis revealed gain(19p), del(3q), del(13q), del(4q), diagnosis of AML, and CK-like as independent poor prognostic factors. Here we have defined gain(19p), del(3q), del(13q), and del(4q) as “Risk CNA”. A significant difference in outcomes was observed between patients with and without Risk CNA (n = 110 and n = 114, respectively, Hazard ratio = 2.6, p = 6.0x10 -8): The 6-month survival rate was 70 (95% Confidence interval [60-79]) % for patients without Risk CNA and 42 [31-52] % for those with Risk CNA. Patients with two or more Risk CNAs had worse prognosis than those with one ( p = 2.7x10 -2), indicating independent or additive contributions to outcomes. Similar trends were observed when limiting the analysis to TP53-biallelic cases. Further investigation of Risk CNA target genes was performed by identifying commonly amplified/deleted lesions. Target genes of gain(19p) included DNM2, CARM1, SMARCA4, LDLR, and EPOR, while RB1 and TET2 were potential candidates of del(13q) and del(4q), respectively. Identification of candidate genes for del(3q) was challenging due to broad common deleted lesions. Conclusion: Chromosomal abnormalities stratify the prognosis of AML and MDS-EB with TP53 mutation. The number of Risk CNA also impacts survival. Investigation of target genes of Risk CNA suggests potential therapeutic targets for TP53-mutated myeloid neoplasms, warranting further study for treatment optimization.

Circulating tumor DNA-based copy-number profiles enable monitoring treatment effects during therapy in high-grade serous carcinoma

Circulating tumor DNA (ctDNA) analysis has emerged as a promising tool for detecting and profiling longitudinal genomics changes in cancer. While copy-number alterations (CNAs) play a major role in cancers, treatment effect monitoring using copy-number profiles has received limited attention as compared to mutations. A major reason for this is the insensitivity of CNA analysis for the real-life tumor-fraction ctDNA samples. We performed copy-number analysis on 152 plasma samples obtained from 29 patients with high-grade serous ovarian cancer (HGSC) using a sequencing panel targeting over 500 genes. Twenty-one patients had temporally matched tissue and plasma sample pairs, which enabled assessing concordance with tissues sequenced with the same panel or whole-genome sequencing and to evaluate sensitivity. Our approach could detect concordant CNA profiles in most plasma samples with as low as 5% tumor content and highly amplified regions in samples with ∼1% of tumor content. Longitudinal profiles showed changes in the CNA profiles in seven out of 11 patients with high tumor-content plasma samples at relapse. These changes included focal acquired or lost copy-numbers, even though most of the genome remained stable. Two patients displayed major copy-number profile changes during therapy. Our analysis revealed ctDNA-detectable subclonal selection resulting from both surgical operations and chemotherapy. Overall, longitudinal ctDNA data showed acquired and diminished CNAs at relapse when compared to pre-treatment samples. These results highlight the importance of genomic profiling during treatment as well as underline the usability of ctDNA.

Integrative analysis reveals early epigenetic alterations in high-grade serous ovarian carcinomas.

High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date, the profiles of gene mutations and copy number alterations in HGSOC have been well characterized. However, the patterns of epigenetic alterations and transcription factor dysregulation in HGSOC have not yet been fully elucidated. In this study, we performed integrative omics analyses of a series of stepwise HGSOC model cells originating from human fallopian tube secretory epithelial cells (HFTSECs) to investigate early epigenetic alterations in HGSOC tumorigenesis. Assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and RNA sequencing (RNA-seq) methods were used to analyze HGSOC samples. Additionally, protein expression changes in target genes were confirmed using normal HFTSECs, serous tubal intraepithelial carcinomas (STICs), and HGSOC tissues. Transcription factor motif analysis revealed that the DNA-binding activity of the AP-1 complex and GATA family proteins was dysregulated during early tumorigenesis. The protein expression levels of JUN and FOSL2 were increased, and those of GATA6 and DAB2 were decreased in STIC lesions, which were associated with epithelial-mesenchymal transition (EMT) and proteasome downregulation. The genomic region around the FRA16D site, containing a cadherin cluster region, was epigenetically suppressed by oncogenic signaling. Proteasome inhibition caused the upregulation of chemokine genes, which may facilitate immune evasion during HGSOC tumorigenesis. Importantly, MEK inhibitor treatment reversed these oncogenic alterations, indicating its clinical effectiveness in a subgroup of patients with HGSOC. This result suggests that MEK inhibitor therapy may be an effective treatment option for chemotherapy-resistant HGSOC.

Novel insights into the pathogenesis of follicular lymphoma by molecular profiling of localized and systemic disease forms

Knowledge on the pathogenesis of FL is mainly based on data derived from advanced/systemic stages of FL (sFL) and only small cohorts of localized FL (lFL) have been characterized intensively so far. Comprehensive analysis with profiling of somatic copy number alterations (SCNA) and whole exome sequencing (WES) was performed in 147 lFL and 122 sFL. Putative targets were analyzed for gene and protein expression. Overall, lFL and sFL, as well as BCL2 translocation-positive (BCL2+) and –negative (BCL2−) FL showed overlapping features in SCNA and mutational profiles. Significant differences between lFL and sFL, however, were detected for SCNA frequencies, e.g., in 18q-gains (14% lFL vs. 36% sFL; p = 0.0003). Although rare in lFL, gains in 18q21 were associated with inferior progression-free survival (PFS). The mutational landscape of lFL and sFL included typical genetic lesions. However, ARID1A mutations were significantly more often detected in sFL (29%) compared to lFL (6%, p = 0.0001). In BCL2 + FL mutations in KMT2D, BCL2, ABL2, IGLL5 and ARID1A were enriched, while STAT6 mutations more frequently occurred in BCL2- FL. Although the landscape of lFL and sFL showed overlapping features, molecular profiling revealed novel insights and identified gains in 18q21 as prognostic marker in lFL.

The prognostic impact of IKZF1 deletions and UKALL genetic classifiers in paediatric B-cell precursor acute lymphoblastic leukaemia treated according to NOPHO 2008 protocols.

We investigated 390 paediatric B-cell precursor acute lymphoblastic leukaemia (BCP-ALL) patients treated according to NOPHO ALL 2008, regarding copy number alterations (CNA) of eight loci associated with adverse prognosis, including IKZF1. The impact on outcome was investigated for each locus individually, combined as CNA profiles and together with cytogenetic information. The presence of IKZF1 deletion or a poor-risk CNA profile was associated with poor outcome in the whole cohort. In the standard-risk group, IKZF1-deleted cases had an inferior probability of relapse-free survival (pRFS) (p ≤ 0.001) and overall survival (pOS) (p ≤ 0.001). Additionally, among B-other patients, IKZF1 deletion correlated with poor pRFS (60% vs. 90%) and pOS (65% vs. 89%). Both IKZF1 deletion and a poor-risk CNA profile were independent factors for relapse and death in multivariable analyses adjusting for known risk factors including measurable residual disease. Our data indicate that BCP-ALL patients with high-risk CNA or IKZF1 deletion have worse prognosis despite otherwise low-risk features. Conversely, patients with both a good CNA and cytogenetic profile had a superior relapse-free (p ≤ 0.001) and overall survival (p ≤ 0.001) in the cohort, across all risk groups. Taken together, our findings highlight the potential of CNA assessment to refine stratification in ALL.

CVAM: CNA Profile Inference of the Spatial Transcriptome Based on the VGAE and HMM.

Tumors are often polyclonal due to copy number alteration (CNA) events. Through the CNA profile, we can understand the tumor heterogeneity and consistency. CNA information is usually obtained through DNA sequencing. However, many existing studies have shown a positive correlation between the gene expression and gene copy number identified from DNA sequencing. With the development of spatial transcriptome technologies, it is urgent to develop new tools to identify genomic variation from the spatial transcriptome. Therefore, in this study, we developed CVAM, a tool to infer the CNA profile from spatial transcriptome data. Compared with existing tools, CVAM integrates the spatial information with the spot's gene expression information together and the spatial information is indirectly introduced into the CNA inference. By applying CVAM to simulated and real spatial transcriptome data, we found that CVAM performed better in identifying CNA events. In addition, we analyzed the potential co-occurrence and mutual exclusion between CNA events in tumor clusters, which is helpful to analyze the potential interaction between genes in mutation. Last but not least, Ripley's K-function is also applied to CNA multi-distance spatial pattern analysis so that we can figure out the differences of different gene CNA events in spatial distribution, which is helpful for tumor analysis and implementing more effective treatment measures based on spatial characteristics of genes.

The Prognostic Effect of CDKN2A/2B Gene Deletions in Pediatric Acute Lymphoblastic Leukemia (ALL): Independent Prognostic Significance in BFM-Based Protocols.

One of the most frequent genes affected in pediatric ALL is the CDKN2A/2B gene, acting as a secondary cooperating event and playing an important role in cell-cycle regulation and chemosensitivity. Despite its inclusion in combined CNA (copy-number alterations) classifiers, like the IKZF1plus entity and the UKALL CNA profile, the prognostic impact of the individual gene deletions outside the context of a combined CNA evaluation remains controversial. Addressing the CDKN2A/2B deletions' additive prognostic effect in current risk-stratification algorithms, we present a retrospective study of a Greek pediatric ALL cohort comprising 247 patients studied over a 24-year period (2000-2023). Herein, we provide insight regarding the correlation with disease features, MRD clearance, and independent prognostic significance for this ALL cohort treated with contemporary BFM-based treatment protocols. Within an extended follow-up time of 135 months, the presence of the CDKN2A/2B deletions (biallelic or monoallelic) was associated with inferior EFS rates (65.1% compared to 91.8% for the gene non-deleted subgroup, p < 0.001), with the relapse rate accounting for 22.2% and 5.9%, respectively (p < 0.001). The presence of the biallelic deletion was associated with the worst outcomes (EFS 57.2% vs. 89.6% in the case of any other status, monoallelic or non-deleted, p < 0.001). Survival differences were demonstrated for B-ALL cases (EFS 65.3% vs. 93.6% for the non-deleted B-ALL subgroup, p < 0.001), but the prognostic effect was not statistically significant within the T-ALL cohort (EFS 64.3 vs. 69.2, p = 0.947). The presence of the CDKN2A/2B deletions clearly correlated with inferior outcomes within all protocol-defined risk groups (standard risk (SR): EFS 66.7% vs. 100%, p < 0.001, intermediate risk (IR): EFS 77.1% vs. 97.9%, p < 0.001, high risk (HR): EFS 42.1% vs. 70.5% p < 0.001 for deleted vs non-deleted cases in each patient risk group); additionally, in this study, the presence of the deletion differentiated prognosis within both MRD-positive and -negative subgroups on days 15 and 33 of induction. In multivariate analysis, the presence of the CDKN2A/2B deletions was the most important prognostic factor for relapse and overall survival, yielding a hazard ratio of 5.2 (95% confidence interval: 2.59-10.41, p < 0.001) and 5.96 (95% confidence interval: 2.97-11.95, p < 0.001), respectively, designating the alteration's independent prognostic significance in the context of modern risk stratification. The results of our study demonstrate that the presence of the CDKN2A/2B deletions can further stratify all existing risk groups, identifying patient subgroups with different outcomes. The above biallelic deletions could be incorporated into future risk-stratification algorithms, refining MRD-based stratification. In the era of targeted therapies, future prospective controlled clinical trials will further explore the possible use of cyclin-dependent kinase inhibitors (CDKIs) in CDKN2A/2B-affected ALL pediatric subgroups.

Abstract 1904: Somatic copy number alterations and gene expression signatures are associated with aggressive tumor biology in African Americans and European Americans with renal cell carcinoma

Abstract Background: Renal cell carcinoma (RCC) is the deadliest of all urologic cancers in the US. RCC survival is highly dependent on histology. Survival rates range between 55-60% for clear cell RCC (ccRCC) and 80-90% for papillary RCC (pRCC) patients. African Americans (AAs) have lower survival rates when compared to their European American (EA) counterparts for both histologies (ccRCC 67.1 vs 72.6, pRCC 80.5 vs 87.5). RCC survival disparities may be accredited to population differences in tumor biology, such as somatic copy number alteration (SCNA) profiles of tumor suppressor and oncogenes, and differential gene expression signatures with associated cellular pathway dysregulation. SCNAs are the most common structural change in the human genome and ccRCC and pRCC-specific SCNAs have been associated with clinical outcomes. ClearCode34, a 34 gene expression signature, was developed to classify ccRCC tumors into two distinct ccRCC subtypes (ccA and ccB). The ccB subtype is associated with worse survival and features like increased tumor size, grade, and metastasis rates. We hypothesize there are more aggressive tumor biology phenotypes in AA RCC patients compared to their European counterparts. Methods: Comparative genome-wide, chromosomal, and gene SCNA analyses were performed in AA and EA ccRCC and pRCC patients in TCGA using Partek Genomics Suite 7 (1-way ANOVA, P&amp;lt;0.05). Prediction analysis of microarray in R was used to classify ccRCC patients into ccA and ccB subtypes by race based on the ClearCode34 gene expression signature (t-test, P&amp;lt;0.05). Differentially expressed genes (DEGs) between AA and EA patients were identified using Partek Genomics Suite 7 (1-way ANOVA, P&amp;lt;0.05). Gene Set Enrichment Analysis (GSEA) was performed using a pre-ranked gene list (Fold changes &amp;gt;2 or &amp;lt;-2, P&amp;lt;0.01) and two Molecular Signatures Database collections (C6 oncogenic signatures, C7 immunologic signatures). Results: AA-enriched SCNVs were identified on chromosomes 1, 3, 6, 7, and 12 in ccRCC patients, and chromosomes 1, 4, 6, 7, 8, 10, 16 and 20 in pRCC patients. Six cytobands and genes experienced a SCNV across both histologies (1p21.1, 1p21.3, 6p12.1, 6p12.3, 6p21.1, 6q12), BMP5 (on 6p12.1), CD2AP (on 6p12.3), ENPP4 (on 6p21.1), and SLC44A3-AS1 (on 1p21.3). AAs and EAs had significantly different frequencies of ccA (AA 33.9% vs EA 52.2%) and ccB subtypes (AA 66.1% vs EA 47.8%). Unique DEGs were found between AA and EA ccA and ccB patients (131 ccA only, 165 ccB only), which corresponded with up- and down-regulation in kidney cancer with oncogenic KRAS (C6) and various immunologic pathways (C7). Conclusions: Population-specific SCNAs, ccB subtypes, and pathways may help explain differences in RCC tumor biology amongst AA and EA patients. Future Directions: Replicate these findings in the Cooperative Human Tissue Network/Geisinger validation cohort. Citation Format: Samantha Greenberg, Alex Bart, Destiny Ortiz Fernandez, Heinric Williams, Khadijah A. Mitchell. Somatic copy number alterations and gene expression signatures are associated with aggressive tumor biology in African Americans and European Americans with renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1904.

RcCAE: a convolutional autoencoder method for detecting intra-tumor heterogeneity and single-cell copy number alterations.

Intra-tumor heterogeneity (ITH) is one of the major confounding factors that result in cancer relapse, and deciphering ITH is essential for personalized therapy. Single-cell DNA sequencing (scDNA-seq) now enables profiling of single-cell copy number alterations (CNAs) and thus aids in high-resolution inference of ITH. Here, we introduce an integrated framework called rcCAE to accurately infer cell subpopulations and single-cell CNAs from scDNA-seq data. A convolutional autoencoder (CAE) is employed in rcCAE to learn latent representation of the cells as well as distill copy number information from noisy read counts data. This unsupervised representation learning via the CAE model makes it convenient to accurately cluster cells over the low-dimensional latent space, and detect single-cell CNAs from enhanced read counts data. Extensive performance evaluations on simulated datasets show that rcCAE outperforms the existing CNA calling methods, and is highly effective in inferring clonal architecture. Furthermore, evaluations of rcCAE on two real datasets demonstrate that it is able to provide a more refined clonal structure, of which some details are lost in clonal inference based on integer copy numbers.