Copy Number Variation Profiles Research Articles

Abstract 2312: Single-cell low pass whole genome sequencing for copy-number profiling in circulating tumor cells from prostate, non-small cell lung and breast cancers

Abstract Background: Circulating tumor cells (CTCs) have been considered as an alternative to tissue biopsy for providing both germline-specific and tumor-derived genetic variants. Copy number variations (CNVs) play an important role in molding the genomes of cancers and have been shown the clinical value for prognostic signature and therapeutic target. The current study aimed to evaluate CNVs at single-cell resolution and explore the potential clinical utility of tracking this key mechanism of cancer progression. Methods: Blood samples were collected in Streck tubes from 40 stage II-IV cancer patients (5 prostate cancer, 15 non-small lung cancer (NSCLC), 20 breast cancer (BC)) before treatment. CTCs was identified as cells containing an intact nucleus, without CD45 expression, and with cytokeratin expression. Genomic analysis of chromosomal CNVs by low pass whole genome sequencing (Lp-WGS) and number of large-scale transitions (LSTs) calculation was performed in the CTCs. Results: A total of 9 CTCs from 4 prostate cancer, 70 CTCs from 7 NSCLC, 22 CTCs from 9 breast cancer patients, representing a range of sizes, shapes, and protein expression levels of cytokeratin were identified. A total of 84 individual CTCs were successfully sequenced from 20 patients (1-6 CTCs/patient). The selected highlights for gene CNVs include: 1) CXCR4 and ATM were detected as loss on single cell CTC (scCTC) level in BC; 2) MED12, an important regulator for maintaining accurate cytokinesis and survival, was detected as loss on scCTC level in NSCLC. A wide range of LST scores were observed among the 20 patient samples. Cell morphology analysis, phenotypic heterogeneity biomarker analysis and homologous recombination deficiency (HRD) biomarker analysis using a previously developed HRD classifier1 trained on genomic markers is still ongoing. Conclusion: Our data demonstrated that Lp-WGS of DNA from CTCs can detect CNVs loss and assess disease heterogeneity at the single-cell level. Since genome-wide CNV profiles can be used to characterize genomic instability, it is anticipated that the integrative analysis of morphology and genomics in CTCs can potentially complement tissue and/or ctDNA analysis to determine HRD, enabling in-depth investigation of tumor heterogeneity and individualized clinical assessment. Citation Format: Danyi Wang, Giuseppe Locatelli, Ioannis Gounaris, Juergen Scheuenpflug, Zheng Feng. Single-cell low pass whole genome sequencing for copy-number profiling in circulating tumor cells from prostate, non-small cell lung and breast cancers [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 2312.

An immune infiltration-related prognostic model of kidney renal clear cell carcinoma with two valuable markers: CAPN12 and MSC.

Since its discovery, clear cell renal cell carcinoma (ccRCC) has been the most prevalent and lethal kidney malignancy. Our research aims to identify possible prognostic genes of ccRCC and to develop efficient prognostic models for ccRCC patients based on multi-omics investigations to shed light on the treatment and prognosis of ccRCC. To determine a risk score for each patient, we screened out differentially expressed genes using data from tumor samples, and control samples mined from The Cancer Genome Atlas (TCGA) and GTEx datasets. Somatic mutation and copy number variation profiles were analyzed to look for specific genomic changes connected to risk scores. To investigate potential functional relationships of prognostic genes, gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were carried out. We created a prognostic model by fusing risk ratings with other clinical variables. For validation, the 786-O cell line was used to carry out the dual-gRNA approach to knock down CAPN12 and MSC. This was followed by qRT-PCR to verify the knockdown of CAPN12 and MSC. For ccRCC, seven predictive genes were discovered: PVT1, MSC, ALDH6A1, TRIB3, QRFPR, CYS1, and CAPN12. The most enriched pathways in the GSVA study and GSEA analysis promote tumorigenesis and immune system modulation. The risk score derived from prognostic genes corresponds with immune infiltration cells and helps predict how well a medicine will work. The mutation of numerous oncogenes was also linked to a high-risk score. A prognostic model with a high ROC value was created for the risk score. An in vitro study demonstrates that the suppression of CAPN12 and MSC dramatically reduced the ability of 786-O cells to proliferate in the CCK-8 proliferation assay and plate clonality assays. A thorough prognostic model with good performance has been developed for ccRCC patients using seven prognostic genes that were discovered to be related to ccRCC prognosis. In ccRCC, CAPN12 and MSC were significant indicators and would make good therapeutic targets.

A crowdsourcing database for the copy-number variation of the Spanish population

BackgroundDespite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants.ResultsHere, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/.ConclusionSPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.

Resequencing of durian genomes reveals large genetic variations among different cultivars.

Durian (Durio zibethinus), which yields the fruit known as the "King of Fruits," is an important economic crop in Southeast Asia. Several durian cultivars have been developed in this region. In this study, we resequenced the genomes of three popular durian cultivars in Thailand, including Kradumthong (KD), Monthong (MT), and Puangmanee (PM) to investigate genetic diversities of cultivated durians. KD, MT, and PM genome assemblies were 832.7, 762.6, and 821.6 Mb, and their annotations covered 95.7, 92.4, and 92.7% of the embryophyta core proteins, respectively. We constructed the draft durian pangenome and analyzed comparative genomes with related species in Malvales. Long terminal repeat (LTR) sequences and protein families in durian genomes had slower evolution rates than that in cotton genomes. However, protein families with transcriptional regulation function and protein phosphorylation function involved in abiotic and biotic stress responses appeared to evolve faster in durians. The analyses of phylogenetic relationships, copy number variations (CNVs), and presence/absence variations (PAVs) suggested that the genome evolution of Thai durians was different from that of the Malaysian durian, Musang King (MK). Among the three newly sequenced genomes, the PAV and CNV profiles of disease resistance genes and the expressions of methylesterase inhibitor domain containing genes involved in flowering and fruit maturation in MT were different from those in KD and PM. These genome assemblies and their analyses provide valuable resources to gain a better understanding of the genetic diversity of cultivated durians, which may be useful for the future development of new durian cultivars.

Pediatric BCOR-Altered Tumors From Soft Tissue/Kidney Display Specific DNA Methylation Profiles

In the pediatric population, BCL6-correpresor gene (BCOR)–upregulated tumors include primitive myxoid mesenchymal tumors/undifferentiated sarcomas (PMMTI/UND), clear cell sarcomas of the kidney (CCSK), and high-grade neuroepithelial tumors (HG-NET). We investigated DNA methylation (DNAm) and copy number variation (CNV) profiling in these tumors (N = 34) using an Illumina EPIC BeadChip to better define the potential use of these tools to confirm diagnosis and predict outcomes. Twenty-seven tumors from 25 patients (age range, 0-10 years), showed molecular confirmation of genetic abnormalities as follows: BCOR internal tandem duplication in 14 PMMTI/UND, 8 CCSK, and 3 HG-NET and YWHAE fusions in 2 PMMTI/UND. The remaining 7 cases lacking informative molecular data were analyzed by immunophenotyping and were included in the study as a training cohort, clearly separated from the main study group. These were 4 PMMTI, 1 HG-NET, and 1 CCSK in which poor RNA preservation precluded the confirmation of BCOR rearrangements and 1 CCSK in which no rearrangements were found. DNAm data were compared with those of brain tumor and/or sarcoma classifier. Differentially methylated regions (DMRs) were analyzed in the 3 groups. Twenty-two cases of the 24 molecularly confirmed PMMTI/UND and CCSK and 3 of 6 of those with only immunophenotyping were classified within the methylation class “BCOR-altered sarcoma family” with optimal calibrated scores. PMMTI/UND and CCSK showed similar methylation profiles, whereas thousands of DMRs and significantly enriched pathways were evident between soft tissue/kidney tumors and HG-NET. The CNV analysis showed an overall flat profile in 19 of the 31 evaluable tumors (8/10 CCSK; 9/18 PMMTI/UND; 2/4 HG-NET). The most frequent CNVs were 1q gain and 9p and 10q loss. Follow-up time data were available for 20 patients: ≥2 CNV significantly correlated with a worse overall survival rate. In conclusion, soft tissue and kidney BCOR sarcomas matched with BCOR-altered sarcoma methylation class, whereas those from the brain matched with the central nervous system tumor classifier HG-NET BCOR, supporting the notion that DNAm profiling is an informative diagnostic tool. CNV alterations were associated with a more aggressive clinical behavior.

Reference on copy number variations in pleomorphic xanthoastrocytoma: Implications for diagnostic approach.

Pleomorphic xanthoastrocytoma (PXA) poses a diagnostic challenge. The present study relies on methylation-based predictions and focuses on copy number variations (CNV) in PXA. We identified 551 tumors from patients having received the histologic diagnosis or differential diagnosis pleomorphic xanthoastrocytoma (PXA) uploaded to the web page www.molecularneuropathology.org. Of these 551 tumors, 165 received the prediction "methylation class (anaplastic) pleomorphic xanthoastrocytoma" with a calibrated score >=0.9 by the brain tumor classifier version v12.8 and, therefore, were defined the PXA reference set designated mcPXAref. In addition to these 165 mcPXAref, 767 other tumors received the prediction mcPXA with a calibrated score >=0.9 but without a histological PXA diagnosis. The total number of individual tumors predicted by histology and/or by methylome based classification as PXA, mcPXA or both was 1318, and these were designated the study cohort. The selection of a control cohort was guided by methylation-based predictions recurrently observed for the other 386/551 tumors diagnosed as histologic PXA. 131/386 received predictions for another entity besides PXA with a score >=0.9. Control tumors corresponding to the 11 most common other predictions were selected, adding up to 1100 reference cases. CNV profiles were calculated from all methylation datasets of the study and control cohorts. Special attention was given to the 7/10 signature, gene amplifications and homozygous deletion of CDKN2A/B. Comparison of CNV in the subsets of the study cohort and the control cohort were used to establish relations independent of histological diagnoses. Tumors in mcPXA were highly homogenous in regard to CNV alterations, irrespective of the histological diagnoses. The 7/10 signature commonly present in glioblastoma, IDH-wildtype, was present in 15-20% of mcPXA, whereas amplification of oncogenes (likewise common in glioblastoma) was very rare in mcPXA (<1%). In contrast, the histology-based PXA group exhibited high variance in regard to methylation classes as well as to CNVs. Our data add to the notion, that histologically defined PXA likely only represent a subset of the biological disease.

Implementation of Copy Number Variations-Based Diagnostics in Morphologically Challenging EWSR1/FUS::NFATC2 Neoplasms of the Bone and Soft Tissue.

In the last decade, new tumor entities have been described, including EWSR1/FUS::NFATC2-rearranged neoplasms of different biologic behavior. To gain further insights into the behavior of these tumors, we analyzed a spectrum of EWSR1/FUS::NFATC2-rearranged neoplasms and discuss their key diagnostic and molecular features in relation to their prognosis. We report five patients with EWSR1/FUS::NFATC2-rearranged neoplasms, including one simple bone cyst (SBC), two complex cystic bone lesions lacking morphological characteristics of SBC, and two sarcomas. In three cases, fluorescence in situ hybridization (FISH) and in all cases copy number variation (CNV) profiling and fusion analyses were performed. All patients were male, three cystic lesions occurred in children (aged 10, 14, and 17 years), and two sarcomas in adults (69 and 39 years). Fusion analysis revealed two FUS::NFATC2 rearrangements in two cystic lesions and three EWSR1::NFATC2 rearrangements in one complex cystic lesion and two sarcomas. EWSR1 FISH revealed tumor cells with break-apart signal without amplification in one complex cystic lesion and EWSR1 amplification in both sarcomas was documented. CNV analysis showed simple karyotypes in all cystic lesions, while more complex karyotypes were found in NFATC2-rearranged sarcomas. Our study supports and expands previously reported molecular findings of EWSR1/FUS::NFATC2-rearranged neoplasms. The study highlights the importance of combining radiology and morphologic features with molecular aberrations. The use of additional molecular methods, such as CNV and FISH in the routine diagnostic workup, can be crucial in providing a correct diagnosis and avoiding overtreatment.

Hub Genes in Non-Small Cell Lung Cancer Regulatory Networks.

There are currently no accurate biomarkers for optimal treatment selection in early-stage non-small cell lung cancer (NSCLC). Novel therapeutic targets are needed to improve NSCLC survival outcomes. This study systematically evaluated the association between genome-scale regulatory network centralities and NSCLC tumorigenesis, proliferation, and survival in early-stage NSCLC patients. Boolean implication networks were used to construct multimodal networks using patient DNA copy number variation, mRNA, and protein expression profiles. T statistics of differential gene/protein expression in tumors versus non-cancerous adjacent tissues, dependency scores in in vitro CRISPR-Cas9/RNA interference (RNAi) screening of human NSCLC cell lines, and hazard ratios in univariate Cox modeling of the Cancer Genome Atlas (TCGA) NSCLC patients were correlated with graph theory centrality metrics. Hub genes in multi-omics networks involving gene/protein expression were associated with oncogenic, proliferative potentials and poor patient survival outcomes (p < 0.05, Pearson's correlation). Immunotherapy targets PD1, PDL1, CTLA4, and CD27 were ranked as top hub genes within the 10th percentile in most constructed multi-omics networks. BUB3, DNM1L, EIF2S1, KPNB1, NMT1, PGAM1, and STRAP were discovered as important hub genes in NSCLC proliferation with oncogenic potential. These results support the importance of hub genes in NSCLC tumorigenesis, proliferation, and prognosis, with implications in prioritizing therapeutic targets to improve patient survival outcomes.

Accurate Detection of Clinically Actionable Copy Number Variants in Diverse Hematological Neoplasms By Routine Targeted Sequencing: A Comparative Performance Study

Background: Accurate genotyping of Copy Number Variations (CNVs) is an essential part of the clinical evaluation of diverse hematologic malignancies. Conventional karyotyping and FISH are current gold standards to assess CNVs, but both have some limitations. Next-generation targeted sequencing panels are commonly incorporated into current clinical practice in most cancer centers. We examined the utility of CANARy (Copy number ANomaly Assessment and Recovery), a CNV profiling method for three hematological malignancies using targeted panel sequencing data. Patients and Methods: We studied patients with myelodysplastic syndrome (MDS), chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), and plasma cell disorders (PCD) identified from a cohort of 4752 hematological specimens profiled at Stanford University by conventional cytogenetics and next-generation sequencing (NGS) between 2018 and 2021. We curated a cohort of 200 patients diagnosed with MDS (n=72), CLL (n=46), and PCDs including MM, AL amyloidosis, and MGUS (PCD, n=82), along with 50 cytogenetically normal controls. Specimens were bone marrow aspirates, peripheral blood, or FFPE tissue. All samples were characterized by conventional metaphase karyotyping and/or FISH and we focused on the analysis of clinically relevant CNV (-5q, -7/-7q, -20q, +8 for MDS; -11q22, -13q14, -17p13, +12 for CLL; and +1q21, -1p32, -13q14, -17p.13 for PCD). The specimens separately had clinical NGS (164 genes, Heme-STAMP) performed no more than four weeks from standard cytogenetic analysis. We applied multiple CNV enumeration tools to sequencing data for CNV genotyping at these loci, including our recently developed method CANARy (Chabon et al, Nature 2020). CANARy is a read depth-based, genome-wide CNV caller from targeted sequencing data that combines information from on-target and off-target fragments to assign a final Z-score and copy number index to a set of pre-defined genomic regions. We benchmarked CANARy alongside three others publicly available CNV callers: CNVkit (Talevich et al, PLoS Comput Biol. 2016), ichorCNA (Adalsteinsson et al, Nat Commun. 2017), and WISECONDOR (Straver et al, Nucleic Acids Res. 2014). All tools were run using the default parameters and following author recommendations. We calculated the accuracy and other statistics parameters for each CNV caller, considering karyotype/FISH as the true reference. We estimated tumor fraction using two strategies: the variant allele fraction (VAF) of disease-related driver mutations and using the ichorCNA estimate. Results: A total of 211 CNVs were identified by karyotype and/or FISH, with disease-specific distribution summarized in Fig. A. CANARy detected 148/211 (70.1%), CNVkit 88/211 (41.7%), ichorCNA 116/211 (55%) and WISECONDOR 158/211 (74.9%). The overall accuracy for CANARy, CNVkit, ichorCNA and WISECONDOR was 86.3%, 81.8%, 84.3% and 83.1% respectively. CANARy had both the highest overall accuracy (86.3%) and overall F1-score (0.73) (Fig.B). WISECONDOR had the highest number of false positives (83 vs. CANARy = 48). Interestingly, all CNV tools performed better in MDS specimens, with 92% accuracy for CANARy in MDS samples, likely related to the higher neoplastic purity of these samples. The median ichorCNA tumor fraction estimates for MDS, CLL and PCD were 22% (0-99%), 14% (0-70%), and 7% (0-94%), respectively. In addition, CNV calling was inferior in PCD tumors than other tumor types. Within CLL, -11q22 and -13q14 lesions were more challenging to detect with any of the four methods, with CANARy sensitivity of 50% and 31.3% respectively, likely related to the smaller minimal deletion regions of these lesions. The 17p deletion in CLL cases, known for its poor prognostic impact, was best identified by CANARy; with a 100% sensitivity and a 97.6% specificity. The only non-concordant result for -17p was a false positive that was detected by all 4 NGS CNV genotypers but not FISH, possibly suggesting a false negative FISH result. Conclusions: CANARy accurately identifies clinically significant CNVs in common hematologic neoplasms and could thus serve as a complementary approach to the current cytogenetic evaluation. CANARy uses data already generated from targeted sequencing panels and therefore does not impose additional work or cost. Low tumor fraction could be a limitation for CNV calling. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Single-Cell Multi-Omics of Peripheral Blood Reveals Tiding and Evolution of Responsive and Resistant Clones upon Daratumumab-Based Treatments in Multiple Myeloma and Plasma Cell Leukemia

Background: Treatment with anti-CD38 antibodies is a standard of care in newly diagnosed and relapsed/refractory multiple myeloma (MM). Clonal tiding and evolution as well as genomic heterogeneity are major drivers towards drug-resistant disease. However, modes of resistance to anti-CD38 directed therapies are currently unknown and might include loss of antigen expression and/or exhaustion of the immune system. We performed longitudinal single-cell multi-omic analyses of circulating tumor cells (CTC) and non-malignant cells to decipher clonal heterogeneity and tiding upon response and resistance to daratumumab (Dara)-based therapies in MM and plasma cell leukemia (PCL). Methods: Peripheral blood mononuclear cells (MNCs) were isolated from 7 patients (PCL n=5, MM n=2) before and after exposure to Dara. Samples were collected at four different time points: 1. before administration of Dara (CD38-naïve). 2. Four days after first application of Dara (CD38-exposed). 3. After relapse from Dara (CD38-refractory). 4. After an additional line of non-CD38 targeted therapy following relapse from Dara. In total, we analyzed 17 PB samples. To demonstrate that results from PB are comparable to bone marrow (BM), four paired PB and BM samples were included (21 samples in total). MNCs were subjected to single cell RNA (scRNAseq), B-cell (scBCRseq), and T-cell receptor sequencing (scTCRseq). Surface protein expression was measured using a custom panel of 57 DNA-barcoded antibodies. Sequencing files were processed with CellRanger (10x Genomics) and data were analyzed with the Seurat toolkit for single cell sequencing. Cell types were annotated with SingleR based on the Human Primary Cell Atlas built-in references. ScRepertoire was used for longitudinal scTCRseq and scBCRseq data. Copy number variations (CNVs) in CTCs were detected with inferCNV, and cellular interactions were investigated with CellPhoneDB. Results: In total, we sequenced 130.038 MNCs (PB: 108.236, range 414-8700/patient; BM: 21802, range 3375-8516/patient, Figure 1A). Malignant plasma cells were identified using scBCRseq and restricted light chain expression from scRNAseq. Even in MM patients without morphological evidence for CTC, we could identify and characterize single malignant plasma cells in PB. By inferring genome-wide CNVs from scRNAseq, we were able to characterize intra-patient genomic heterogeneity. Longitudinal tracking of CTC revealed tiding of clones characterized by distinct CNV profiles and transcriptomes upon Dara-exposure and resistance. Early transcriptional changes in CTCs upon Dara-exposure included inflammatory signaling (e.g. upregulation of IFI6, IFI35, IFIT1, IFITM1). Analysis of CD38 protein surface expression using DNA-barcoded antibodies showed significantly decreased levels after Dara exposure. To rule out that this might have resulted from competitive binding of the diagnostic antibody and Dara, we repeated analyses after discontinuing Dara and after application of a further line of therapy. In contrast to CD38 RNA expression, surface protein expression decreased significantly upon exposure and relapse, but recovered after an additional line of therapy. Expression of other druggable antigens (BCMA, SLAMF7, GPRCD5, FcRL5, Figure 1B) was not affected by treatment with Dara. Next, we investigated co-evolution of non-malignant cells. Longitudinal scTCRseq showed concomitant expansion and stagnation of TCRs. Receptor-ligand interaction analyses demonstrated that exposure to Dara resulted in significant differences in CD38-PECAM1-mediated interactions between CTCs with non-malignant B-cells and CD8+ T-cells. We detected recurrently increased immunosuppressive receptor-ligand interactions between malignant plasma cells and CD4+, CD8+, and regulatory T-cells via CD86-CTLA4 and NECTIN3-TIGIT axis upon Dara exposure. Conclusion: We demonstrate that single-cell multi-omic analyses of PB provide a minimal invasive approach to study genomic heterogeneity and evolution of malignant plasma cells and non-malignant cells of the immune system. Longitudinal analyses reveal different patterns of response and resistance to targeted myeloma therapies and might affect future therapeutic decision-making. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

The first comprehensive genomic characterization of rectal squamous cell carcinoma

BackgroundRectal cancers represent 35% of colorectal cancers; 90% are adenocarcinomas, while squamous cell carcinoma accounts for 0.3% of them. Given its rarity, little is known concerning its pathogenesis, molecular profile and therapeutic management. The current treatment trend is to treat rectal squamous cell carcinoma by analogy to anal squamous cell carcinoma with definitive chemo-radiotherapy, setting aside surgery in case of local recurrence.MethodsWe performed an in-depth genomic analysis (next-generation sequencing, copy number variation, and human papilloma virus characterization) on 10 rectal squamous cell carcinoma samples and compared them in silico to those of anal squamous cell carcinoma and rectal adenocarcinoma.ResultsRectal squamous cell carcinoma shows 100% HPV positivity. It has a mutational (PIK3CA, PTEN, TP53, ATM, BCL6, SOX2) and copy number variation profile (3p, 10p, 10q, 16q deletion and 1q, 3q, 5p, 8q, 20p gain) similar to anal squamous cell carcinoma. PI3K/Akt/mTOR is the most commonly affected signaling pathway similarly to anal squamous cell carcinoma. Most commonly gained or lost genes seen in rectal adenocarcinoma (FLT3, CDX2, GNAS, BCL2, SMAD4, MALT1) are not found in rectal squamous cell carcinoma.ConclusionThis study presents the first comprehensive genomic characterization of rectal squamous cell carcinoma. We confirm the existence of this rare histology and its molecular similarity with anal squamous cell carcinoma. This molecular proximity confirms the adequacy of therapeutic management based on histology and not localization, suggesting that rectal squamous cell carcinoma should be treated like anal squamous cell carcinoma and not as a rectal adenocarcinoma.

Washout DNA copy number analysis by low-coverage whole genome sequencing for assessment of thyroid FNAs.

BackgroundPapillary thyroid microcarcinoma (PTMC) is defined as a papillary carcinoma measuring ≤ 10 mm. The current management of PTMC has become more conservative; however, there are high-risk tumor features that can be revealed only postoperatively. For thyroid cancer, BRAF mutations and somatic copy number variation (CNV) are the most common genetic events. Molecular testing may contribute to clinical decision-making by molecular risk stratification, for example predicting lymph node (LN) metastasis. Here, we build a risk stratification model based on molecular profiling of thyroid fine needle aspiration (FNA) washout DNA (wDNA) for the differential diagnosis of thyroid nodules.MethodsFifty-eight patients were recruited, FNA wDNA samples were analyzed using CNV profiling through low-coverage whole genome sequencing (LC-WGS) and BRAF mutation was analyzed using quantitative PCR. FNA pathology was reported as a Bethesda System for Reporting Thyroid Cytopathology (BSRTC) score. Ultrasound examination produced a Thyroid Imaging Reporting and Data System (TIRADS) score.ResultsIn total, 37 (63.8%) patients with a TIRADS score of 4A, 13 (22.4%) patients with a TIRADS score of 4B, and 8 (13.8%) patients with a TIRADS score of 4C were recruited after ultrasound examination. All patients underwent FNA with wDNA profiling. CNVs were identified in 17 (29.3%) patients. CNVs were frequent in patients with a BSRTC score of V or VI, including eight (47.1%) patients with a score of VI and five (29.4%) with a score of V, but not in patients with a score of III, II, or I (0%). BRAF mutation was not significantly correlated with BSRTC score. LN metastasis was found more frequently in CNV-positive (CNV+) than in CNV-negative (CNV–) patients (85.7% vs. 34.6%, odds ratio = 11.33, p = 0.002). In total, three molecular subtypes of thyroid nodules were identified in this study: 1) CNV+, 2) CNV– and BRAF positive (BRAF+), and 3) CNV– and BRAF negative (BRAF–). For the CNV+ subtype, 10 (83.3%) lesions with LN metastasis were found, including four (100%) small lesions (i.e. ≤ 5 mm). For the CNV– and BRAF+ nodules, LN metastases were detected in only seven (60.0%) larger tumors (i.e. > 5 mm). For CNV– and BRAF– tumors, LN metastasis was also frequently found in larger tumors only.ConclusionsIt is feasible to identify high-risk LN metastasis thyroid cancer from FNA washout samples preoperatively using wDNA CNV profiling using LC-WGS.

279. CLONAL RELATIONSHIP AND ALCOHOL CONSUMPTION-ASSOCIATED MUTATIONAL SIGNATURE IN SYNCHRONOUS HYPOPHARYNGEAL TUMORS AND ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract The patients with dual esophageal squamous cell carcinoma (ESCC) and head and neck cancers have poor prognosis, but the underlying genetic pathogenesis is unclear. We hypothesize that independent origin rather than multifocality, which means local or lateral spreading involves the development of synchronous ESCC and hypopharyngeal cancer (HPC). We also hypothesize that multi-regional assessment provides better understanding of the evolution of tumor subclones and assessment of intra-tumor heterogeneity to guide personalized treatment with prognostic implications. Multiple region whole-exome sequencing (M-WES) and clonality analysis were used to assess clonal relationship and spatial inter- or intra-tumor heterogeneity (ITH) in 62 tumor regions, six normal tissues, and 15 blood samples from eight dual ESCC/HPC and ten ESCC patients. All synchronous ESCC/HPC patients had COSMIC 16 mutation signature compared to only 40% ESCC in the current study (p = 0.013) and public ESCC dataset (n = 165, p = 0.003). The mutational landscape and copy number variation (CNV) profiles were completely distinct between the ESCC/HPC; clonality analysis further suggested the two primary tumors shared no or only one clone accompanying independent subclone evolution. The M-WES strategy demonstrated higher sensitivity and accuracy for detection of mutational prevalence and the late branch mutations among different regions in the ESCC tumors compared to traditional single biopsy strategy. Patients with high ITH was significantly associated with both relapse and survival. Our hypothesis-generating M-WES ITH assessment data have implications for prognostication. We are the first to show a distinctive CNV and genetic mutation profile, the predominant alcohol-related COSMIC 16 mutational signature in synchronous ESCC/HPC, providing genetic evidence for a multi-centric independent origin for clonal evolution and the theory of field cancerization implicating an etiologic role of alcohol metabolism in dual ESCC/HPC carcinogenesis.

P12.12.A Resolving the cellular architecture of infiltration zones in glioblastoma

Abstract Background Therapy resistance and infiltration still pose major challenges in the treatment of glioma. In the tumour border niche, an interaction between different healthy cell types and malignant cells leads to therapy resistance, acquisition of stem-cell like features, and recurrence. However, studying the tumour border is quite challenging due to the lack of specific glioma markers. Although single cell datasets contain information about the abundance of different cell types, they still lack the spatial arrangement at the border niche. Spatial transcriptomic approaches might overcome these problems, but are still limited by a low resolution or a limited number of detectable transcripts. Material and Methods We applied the Visium spatial transcriptomics platform on 18 FFPE and 11 fresh frozen gliomas to image the cellular architecture of the tumour border niche. In addition, the transcriptome of single nuclei isolated from the fresh frozen sections was also analysed. Using Seurat and a single cell reference set from Darmanis et al. (2017) the cell types were mapped onto the section and the copy number variation profile (CNV) was determined. Results Using a single cell reference set we were able to map different cell types onto different areas of the tumour border niche of gliomas. To control the mapping the expression of cellular markers was used to detect healthy brain cells and the CNV profile was used to identify the tumour. The mapping matched the expression of markers and the CNV profile and only showed minor differences. First analysis confirmed distinct distribution of oligodendrocytes and neurons at the tumour border. We could not detect an enrichment of any tumour subtypes at the tumour border so far. However, one sample showed an enrichment of the mesenchymal subtype at the perinecrotic region. CNVs also showed low intratumoural heterogeneity for most sections. Conclusion Although the first results of the mapping of different cell types look promising, a larger reference set including a larger variety of cell types and tumour subtypes could improve the mapping even further. Nevertheless, we were able to show the cell type distribution at the tumour border and generate robust CNVs for most sections using spatial transcriptomics.

P04.03.B Rapid DNA methylation-based classification of pediatric brain tumors from ultrasonic aspirate specimens

Abstract Background Cavitating ultrasonic aspirator (CUSA) devices are commonly used in neurosurgical procedures to carefully debulk tumor from adjacent healthy brain tissue. Here, we explore the feasibility of using ultrasonic minced tumor tissue to classify otherwise discarded sample material by DNA methylation according to the respective World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) using low pass nanopore whole genome sequencing. Material and Methods 21 ultrasonic aspirated specimens from patients undergoing surgery in the department of pediatric neurosurgery at the Charité-Universitätsmedizin Berlin with either newly diagnosed cerebral lesions or pre-treated lesions were processed by nanopore sequencing to generate copy number profiles and ad-hoc random forest classification. Results were compared to microarray-based routine profiling. Tumor purity was assessed. Results In 19/21 (90.5 %) samples the minimum amount of 1,000 CpG sites were sequenced. In 20/21 (95.2 %) cases copy number variation profiles could be generated and matched microarray derived copy number profiles, allowing for identification of diagnostically or therapeutically relevant pathognomonic alterations. 12/17 (70.6 %) samples were concordantly classified to the corresponding microarray-based diagnosis by routine neuropathological workup. Applying recently defined thresholds for nanopore-based classification resulted in sensitivity of 64.7 % and specificity of 100 %. Conclusion CUSA referred sample material of pediatric brain tumors allows for methylation-based classification according to the respective WHO classification of CNS tumors with acceptable sensitivity and high specificity. Hereby, a promising opportunity for accurate classification of pediatric brain tumors by a time- and cost-efficient advanced molecular technique is offered using otherwise discarded tumor tissue.

Single-cell genomic and transcriptomic landscapes of primary and metastatic colorectal cancer tumors

BackgroundColorectal cancer (CRC) ranks as the second-leading cause of cancer-related death worldwide with metastases being the main cause of cancer-related death. Here, we investigated the genomic and transcriptomic alterations in matching adjacent normal tissues, primary tumors, and metastatic tumors of CRC patients.MethodsWe performed whole genome sequencing (WGS), multi-region whole exome sequencing (WES), simultaneous single-cell RNA-Seq, and single-cell targeted cDNA Sanger sequencing on matching adjacent normal tissues, primary tumors, and metastatic tumors from 12 metastatic colorectal cancer patients (n=84 for genomes, n=81 for exomes, n=9120 for single cells). Patient-derived tumor organoids were used to estimate the anti-tumor effects of a PPAR inhibitor, and self-renewal and differentiation ability of stem cell-like tumor cells.ResultsWe found that the PPAR signaling pathway was prevalently and aberrantly activated in CRC tumors. Blocking of PPAR pathway both suppressed the growth and promoted the apoptosis of CRC organoids in vitro, indicating that aberrant activation of the PPAR signaling pathway plays a critical role in CRC tumorigenesis. Using matched samples from the same patient, distinct origins of the metastasized tumors between lymph node and liver were revealed, which was further verified by both copy number variation and mitochondrial mutation profiles at single-cell resolution. By combining single-cell RNA-Seq and single-cell point mutation identification by targeted cDNA Sanger sequencing, we revealed important phenotypic differences between cancer cells with and without critical point mutations (KRAS and TP53) in the same patient in vivo at single-cell resolution.ConclusionsOur data provides deep insights into how driver mutations interfere with the transcriptomic state of cancer cells in vivo at a single-cell resolution. Our findings offer novel knowledge on metastatic mechanisms as well as potential markers and therapeutic targets for CRC diagnosis and therapy. The high-precision single-cell RNA-seq dataset of matched adjacent normal tissues, primary tumors, and metastases from CRCs may serve as a rich resource for further studies.

Integrated Workflow for the Label-Free Isolation and Genomic Analysis of Single Circulating Tumor Cells in Pancreatic Cancer.

As pancreatic cancer is the third deadliest cancer in the U.S., the ability to study genetic alterations is necessary to provide further insight into potentially targetable regions for cancer treatment. Circulating tumor cells (CTCs) represent an especially aggressive subset of cancer cells, capable of causing metastasis and progressing the disease. Here, we present the Labyrinth–DEPArray pipeline for the isolation and analysis of single CTCs. Established cell lines, patient-derived CTC cell lines and freshly isolated CTCs were recovered and sequenced to reveal single-cell copy number variations (CNVs). The resulting CNV profiles of established cell lines showed concordance with previously reported data and highlight several gains and losses of cancer-related genes such as FGFR3 and GNAS. The novel sequencing of patient-derived CTC cell lines showed gains in chromosome 8q, 10q and 17q across both CTC cell lines. The pipeline was used to process and isolate single cells from a metastatic pancreatic cancer patient revealing a gain of chromosome 1q and a loss of chromosome 5q. Overall, the Labyrinth-DEPArray pipeline offers a validated workflow combining the benefits of antigen-free CTC isolation with single cell genomic analysis.

Abstract 2704: Resolving clone-and haplotype-specific copy number variation and DNA methylation in heterogeneous tumors with nanopore sequencing

Abstract Large-scale somatic genomic copy number variations (CNV) accumulate during cancer progression, resulting in a tumor comprised of collections of cells, or clones, with distinct CNV profiles. Untangling intra-tumor heterogeneity and inferring clone- and haplotype-specific CNV profiles is important for cancer research and can help inform treatment. We present a computational workflow to infer clone- and haplotype-specific cancer CNV profiles by processing long nanopore reads obtained with high-throughput bulk sequencing of a tumor and matching normal sample. The workflow first identifies and phases heterozygous germline single nucleotide polymorphisms (SNPs) in the normal sample. Nanopore reads from the tumor sample are then haplotagged with presence/absence of the phased germline SNPs. Both the overall and the haplotype-specific read counts from the tumor are then tallied over fixed-size bins tiled across the reference genome. Finally, we use the state-of-the art HATCHet matrix factorization algorithm to process the total- and allele-specific read counts and get integer clone- and allele-specific copy number profiles, as well as the clonal cellular fractions of the tumor sample. To test the proposed approach, we have nanopore sequenced to 100x average read-depth coverage a COLO829 tumor and a COLO829BL matching normal cell line. Previous NGS-based bulk and single-cell analyses of the COLO829 cell-line have revealed it to be highly aneuploid and heterogeneous. We show that the proposed nanopore-based workflow identifies clone- and haplotype-specific cancer CNV profiles in concordance with previously published results, with regions of heterogeneity in full agreement with earlier bulk and single-cell studies. Inferred CNV profiles and their clonal fractions are further supported by observed allele-frequencies of somatic SNPs. We demonstrate the stability of the obtained results across lower tumor sample sequencing coverage levels, with CNVs remaining consistent down to 40x tumor coverage, putting the proposed approach on par with the industry standard NGS-based experiments. Notably, because of the unique ability of long nanopore reads to retain single-molecule methylation signals, we were further able to identify haplotype-specific differentially methylated regions both within the tumor sample, as well as in a tumor vs normal comparison, thus shedding light on acquisition/loss of DNA modifications during tumor growth. These results show how nanopore sequencing can be used to resolve some of the complexity that characterizes structurally aberrant heterogeneous cancer samples, while also revealing the previously inaccessible dimension of haplotype-specific tumor methylation. Oxford Nanopore Technologies products are not intended for use for health assessment or to diagnose, treat, mitigate, cure, or prevent any disease or condition. Citation Format: Sergey Aganezov, John Beaulaurier, Eoghan Harrington, Sissel Juul. Resolving clone-and haplotype-specific copy number variation and DNA methylation in heterogeneous tumors with nanopore sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2704.

DNA-methylome-assisted classification of patients with poor prognostic subventricular zone associated IDH-wildtype glioblastoma

Glioblastoma (GBM) derived from the “stem cell” rich subventricular zone (SVZ) may constitute a therapy-refractory subgroup of tumors associated with poor prognosis. Risk stratification for these cases is necessary but is curtailed by error prone imaging-based evaluation. Therefore, we aimed to establish a robust DNA methylome-based classification of SVZ GBM and subsequently decipher underlying molecular characteristics. MRI assessment of SVZ association was performed in a retrospective training set of IDH-wildtype GBM patients (n = 54) uniformly treated with postoperative chemoradiotherapy. DNA isolated from FFPE samples was subject to methylome and copy number variation (CNV) analysis using Illumina Platform and cnAnalysis450k package. Deep next-generation sequencing (NGS) of a panel of 130 GBM-related genes was conducted (Agilent SureSelect/Illumina). Methylome, transcriptome, CNV, MRI, and mutational profiles of SVZ GBM were further evaluated in a confirmatory cohort of 132 patients (TCGA/TCIA). A 15 CpG SVZ methylation signature (SVZM) was discovered based on clustering and random forest analysis. One third of CpG in the SVZM were associated with MAB21L2/LRBA. There was a 14.8% (n = 8) discordance between SVZM vs. MRI classification. Re-analysis of these patients favored SVZM classification with a hazard ratio (HR) for OS of 2.48 [95% CI 1.35–4.58], p = 0.004 vs. 1.83 [1.0–3.35], p = 0.049 for MRI classification. In the validation cohort, consensus MRI based assignment was achieved in 62% of patients with an intraclass correlation (ICC) of 0.51 and non-significant HR for OS (2.03 [0.81–5.09], p = 0.133). In contrast, SVZM identified two prognostically distinct subgroups (HR 3.08 [1.24–7.66], p = 0.016). CNV alterations revealed loss of chromosome 10 in SVZM– and gains on chromosome 19 in SVZM– tumors. SVZM– tumors were also enriched for differentially mutated genes (p < 0.001). In summary, SVZM classification provides a novel means for stratifying GBM patients with poor prognosis and deciphering molecular mechanisms governing aggressive tumor phenotypes.

P-146 The first comprehensive genomic characterization of rectal squamous cell carcinoma

Rectal cancers represent 35% of colorectal cancers; 90% are adenocarcinomas while rectal squamous cell carcinomas represents 0.3% of them. Given its rarity, little is known concerning its pathogenesis, molecular profile and therapeutic management. The current treatment trend is to treat rectal squamous cell carcinoma by analogy with anal squamous cell carcinoma with definitive chemoradiotherapy setting aside surgery in case of local recurrence. We performed an in-depth genomic analysis (Next Generation Sequencing – 400 gene panel, Oncoscan, Human Papilloma Virus characterization) on 10 rectal squamous cell carcinoma samples and compared them in silico to those of anal squamous cell carcinoma and rectal adenocarcinoma. Rectal squamous cell carcinoma shows 100% HPV positivity. It has a similar mutational (PIK3CA, PTEN, TP53, ATM, BCL6, SOX2) and copy number variations profiles (3p deletion and 3q, 5p, 8q, 20p gain) to anal squamous cell carcinomas. PI3K/Akt/mTOR is the most commonly affected signaling pathway similarly to anal squamous cell carcinoma. In addition, common genomic alterations seen in rectal adenocarcinoma (FLT3, CDX2, GNAS BCL2, SMAD4, MALT1 mutations) were not found in these rectal squamous cases. This study presents the first comprehensive genomic characterization of rectal squamous cell carcinoma. We confirm the existence of this rare histology and its molecular similarity with anal squamous cell carcinoma. This molecular proximity confirms the adequacy of therapeutic management based on histology and not localization.