Copy Number Alteration Profiles Research Articles

Liquid Biopsy-Based Accurate Diagnosis and Genomic Profiling of Hard-to-Biopsy Tumors via Parallel Single-Cell Genomic Sequencing of Exfoliated Tumor Cells.

Liquid biopsy provides a convenient and safer procedure for the diagnosis and genomic profiling of tumors that are inaccessible to biopsy by analyzing exfoliated tumor cells (ETCs) or tumor-derived cell-free DNA (cfDNA). However, its primary challenge lies in its limited accuracy in comparison to tissue-based approaches. We report a parallel single-ETC genomic sequencing (Past-Seq) method for the accurate diagnosis and genomic profiling of hard-to-biopsy tumors such as cholangiocarcinoma (CCA) and upper tract urothelial carcinoma (UTUC). For CCA, a prospective cohort of patients with suspicious biliary strictures (n = 36) was studied. Parallel single-cell whole genome sequencing and whole exome sequencing were performed on bile ETCs for CCA diagnosis and resolving mutational profiles, respectively, along with bile cfDNA sequenced for comparison. Concordant single-cell copy number alteration (CNA) profiles in multiple ETCs provided compelling evidence for generating a malignant diagnosis. Past-Seq yielded bile-based accurate CCA diagnosis (96% sensitivity, 100% specificity, and positive predictive value), surpassing pathological evaluation (56% sensitivity) and bile cfDNA CNA analysis (13% sensitivity), and generated the best performance in the retrieval tissue mutations. To further explore the applicability of Past-Seq, 10 suspicious UTUC patients were investigated with urine specimens, and Past-Seq exhibited 90% sensitivity in diagnosing UTUC, demonstrating its broad applicability across various liquid biopsies and cancer types.

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: Copy Number Alteration Gene Identification and cfDNA Detection

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis revealed widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer data sets. Subsequent validation of 5 candidate markers via ddPCR underscored the efficacy of combined predictive models encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1 in early ESCC screening, as evidenced by the area-under-the-curve values exceeding 0.92 (P < .0001) across various detection contexts. The findings highlighted the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

Binary classification of copy number alteration profiles in liquid biopsy with potential clinical impact in advanced NSCLC

Liquid biopsy has recently emerged as an important tool in clinical practice particularly for lung cancer patients. We retrospectively evaluated cell-free DNA analyses performed at our Institution by next generation sequencing methodology detecting the major classes of genetic alterations. Starting from the graphical representation of chromosomal alterations provided by the analysis software, we developed a support vector machine classifier to automatically classify chromosomal profiles as stable (SCP) or unstable (UCP). High concordance was found between our binary classification and tumor fraction evaluation performed using shallow whole genome sequencing. Among clinical features, UCP patients were more likely to have ≥ 3 metastatic sites and liver metastases. Longitudinal assessment of chromosomal profiles in 33 patients with lung cancer receiving immune checkpoint inhibitors (ICIs) showed that only patients that experienced early death or hyperprogressive disease retained or acquired an UCP within 3 weeks from the beginning of ICIs. UCP was not observed following ICIs among patients that experienced progressive disease or clinical benefit. In conclusion, our binary classification, applied to whole copy number alteration profiles, could be useful for clinical risk stratification during systemic treatment for non-small cell lung cancer patients.

Using Copy Number Variation Data and Neural Networks to Predict Cancer Metastasis Origin Achieves High Area under the Curve Value with a Trade-Off in Precision.

The accurate identification of the primary tumor origin in metastatic cancer cases is crucial for guiding treatment decisions and improving patient outcomes. Copy number alterations (CNAs) and copy number variation (CNV) have emerged as valuable genomic markers for predicting the origin of metastases. However, current models that predict cancer type based on CNV or CNA suffer from low AUC values. To address this challenge, we employed a cutting-edge neural network approach utilizing a dataset comprising CNA profiles from twenty different cancer types. We developed two workflows: the first evaluated the performance of two deep neural networks-one ReLU-based and the other a 2D convolutional network. In the second workflow, we stratified cancer types based on anatomical and physiological classifications, constructing shallow neural networks to differentiate between cancer types within the same cluster. Both approaches demonstrated high AUC values, with deep neural networks achieving a precision of 60%, suggesting a mathematical relationship between CNV type, location, and cancer type. Our findings highlight the potential of using CNA/CNV to aid pathologists in accurately identifying cancer origins with accessible clinical tests.

Endometrioid ovarian carcinoma landscape: pathological and molecular characterization.

Endometrioid ovarian cancers (EOvC) are usually managed as serous tumors. In this study, we conducted a comprehensive molecular investigation to uncover the distinct biological characteristics of EOvC. This retrospective multicenter study involved patients from three European centers. We collected clinical data and formalin-fixed paraffin-embedded (FFPE) samples for analysis at the DNA level using panel-based next-generation sequencing and array-comparative genomic hybridization. Additionally, we examined mRNA expression using NanoString nCounter® and protein expression through tissue microarray. We compared EOvC with other ovarian subtypes and uterine endometrioid tumors. Furthermore, we assessed the impact of molecular alterations on patient outcomes, including progression-free survival (PFS) and overall survival (OS). Preliminary analysis of clinical data from 668 patients, including 86 (12.9%) EOvC, revealed more favorable prognosis for EOvC compared with serous ovarian carcinoma (5-year OS of 60% versus 45%; P = 0.001) driven by diagnosis at an earlier stage. Immunohistochemistry and copy number alteration (CNA) profiles of 43 cases with clinical data and FFPE samples available indicated that EOvC protein expression and CNA profiles were more similar to endometrioid endometrial tumors than to serous ovarian carcinomas. EOvC exhibited specific alterations, such as lower rates of PTEN loss, mutations in DNA repair genes, and P53 abnormalities. Survival analysis showed that patients with tumors harboring loss of PTEN expression had worse outcomes (median PFS 19.6 months vs. not reached; P = 0.034). Gene expression profile analysis confirmed that EOvC differed from serous tumors. However, comparison to other rare subtypes of ovarian cancer suggested that the EOvC transcriptomic profile was close to that of ovarian clear cell carcinoma. Downregulation of genes involved in the PI3K pathway and DNA methylation was observed in EOvC. In conclusion, EOvC represents a distinct biological entity and should be regarded as such in the development of specific clinical approaches.

Genomic instability in advanced non-small cell lung cancer (NSCLC) treated with maintenance durvalumab in the UNICANCER SAFIR02-Lung/ IFCT1301 trial.

2632 Background: Genomic instability is a hallmark of cancer that has been associated to immune evasion, cancer progression and multidrug resistance. In SAFIR02-Lung, advanced NSCLC pts were enrolled to receive a platinum-based chemotherapy. After 4 cycles, pts with no targetable alterations were oriented to the immunotherapy sub-study, and if stable or in response, were randomized between maintenance durvalumab or Standard of Care (SoC) (PMID 35802649). Durvalumab prolonged survival only in the PD-L1 ≥ 1% subgroup. In this study we investigated a genomic instability score based on somatic copy number alterations as determined by Comparative Genomic Hybridization (CGH) array as a biomarker for maintenance immunotherapy. Methods: SAFIR02-Lung (NCT02117167) is a multicentric, randomized phase 2 clinical trial. Tissue samples were obtained before induction chemotherapy. Extracted DNA from fresh frozen tumor was analyzed using high-resolution Affymetrix Cytoscan arrays, DNA from FFPE samples was analyzed using the Affymetrix Oncoscan CNV platform. The absolute copy-number (ACN) profile was generated by ASCAT v3.1 through EaCoN v0.3.6 ( https://github.com/gustaveroussy/EaCoN , PMID 36669143 ) on R v4.1.1 and then the genomic instability score was estimated as the sum of the segment length multiplied by the absolute difference between segment copy number and the ASCAT estimated sample ploidy. This sum is reported to the reference genome length. Progression Free Survival (PFS) was the primary endpoint, defined as the time from randomization until the date of objective radiological disease progression, clinical progression or death. The secondary endpoint was Overall Survival (OS). Results: CGH array data were available for 79 patients out of 183, 56 randomized to durvalumab and 23 to SoC. 47 were men, 72 had non-squamous histology and 12 had brain and 10 had liver metastasis. We divided patients in tertiles according to instability (INS) score. No correlation was seen between INS score and PD-L1 positivity (p = 0.5), or liver and brain metastasis. Pts with high INS had lower median PFS of 2.5 months (m) (95% CI 1.4 – 5.2) vs 4.3m (95% CI 2.6 – 13.7) for those with intermediate INS and 6.1m for those with low INS (95% CI 1.9 – 21.2), p 0.012. Similarly, low INS patients had longer OS of 29.6 m (95% CI 15.4 – NR) vs 17.9m for intermediate INS (95% CI 10 – NA) and 12.1m for high INS (95% CI 10.2 – 19.5), p = 0.039. No difference was seen in the control group (p=0.25 for PFS and p=0.4 for OS). A multivariable model showed that high INS was independently associated worse PFS (HR 2.60, 95% CI 1.36 - 4.98, p 0.004) and OS (HR 2.90, 95% CI 1.33 - 6.35, p 0.008). Conclusions: Genomic instability score based on CGH array-based copy number alterations profile is associated with worse PFS and OS in patients under response to chemotherapy who received durvalumab maintenance. Clinical trial information: NCT02117167 .

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 &amp;gt;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.