Copy Number Variation Profiles Research Articles

DNA Mutational and Copy Number Variation Profiling of Primary Craniofacial Osteosarcomas by Next-Generation Sequencing.

Craniofacial osteosarcomas (CFOS) are uncommon malignant neoplasms of the head and neck with different clinical presentation, biological behavior and prognosis from conventional osteosarcomas of long bones. Very limited genetic data have been published on CFOS. In the current study, we performed comprehensive genomic studies in 15 cases of high-grade CFOS by SNP array and targeted next generation sequencing. Our study shows high-grade CFOS demonstrate highly complex and heterogenous genomic alterations and harbor frequently mutated tumor suppressor genes TP53, CDKN2A/B, and PTEN, similar to conventional osteosarcomas. Potentially actionable gene amplifications involving CCNE1, AKT2, MET, NTRK1, PDGFRA, KDR, KIT, MAP3K14, FGFR1, and AURKA were seen in 43% of cases. GNAS hotspot activating mutations were also identified in a subset of CFOS cases, with one case representing malignant transformation from fibrous dysplasia, suggesting a role for GNAS mutation in the development of CFOS. High-grade CFOS demonstrate highly complex and heterogenous genomic alterations, with amplification involving receptor tyrosine kinase genes, and frequent mutations involving tumor suppressor genes.

Mutational landscape of HSP family on human breast cancer

Breast cancer (BRCA) is a prevalent malignancy with the highest incidence among females. BRCA can be categorized into five intrinsic molecular subtypes (LumA, LumB, HER2, Basal, and Normal), each characterized by varying molecular and clinical features determined by the expression of intrinsic genes (PAM50). The Heat Shock Protein (HSP) family is composed of 95 genes evolutionary conservated, they have critical roles in proteostasis in both normal and cancerous processes. Many studies have linked HSP to the development and spread of cancer. They modulate the activity of multiple proteins expressed by oncogenes and anti-oncogenes through a range of interactions. In this study, we evaluate the mutational changes that HSP undergoes in BRCA mainly from the TCGA database. We observe that Copy Number Variations (CNV) are the more frequent events analyzed surpassing the occurrence of point mutations, indels, and translation start site mutations. The Basal subtype showcased the highest count of amplified CNV, including subtype-specific changes, whereas the Luminals tumors accumulated the greatest number of deletion CNV. Meanwhile, the HER2 subtype exhibited a comparatively lower frequency of CNV alterations when compared to the other subtypes. This study integrates CNV and expression data, finding associations between these two variables and the influence of CNV on the deregulation of HSP expression. To enhance the role of HSP as a risk predictor in BRCA, we succeeded in identifying CNV profiles as a prognostic marker. We included Artificial Intelligence to improve the clustering of patients, and we achieved a molecular CNV signature as a significant risk factor independent of known classic markers, including molecular subtypes PAM50. This research enhances the comprehension of HSP DNA alterations in BRCA and its relation with predicting the risk of affected individuals providing insights to develop guide personalized treatment strategies.

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

Although cavitating ultrasonic aspirators are commonly used in neurosurgical procedures, the suitability of ultrasonic aspirator-derived tumor material for diagnostic procedures is still controversial. Here, we explore the feasibility of using ultrasonic aspirator-resected tumor tissue to classify otherwise discarded sample material by fast DNA methylation-based analysis using low pass nanopore whole genome sequencing. Ultrasonic aspirator-derived specimens from pediatric patients undergoing brain tumor resection were subjected to low-pass nanopore whole genome sequencing. DNA methylation-based classification using a neural network classifier and copy number variation analysis were performed. Tumor purity was estimated from copy number profiles.Results were compared to microarray (EPIC)-based routine neuropathological histomorphological and molecular evaluation. 19 samples with confirmed neuropathological diagnosis were evaluated. All samples were successfully sequenced and passed quality control for further analysis. DNA and sequencing characteristics from ultrasonic aspirator-derived specimens were comparable to routinely processed tumor tissue. Classification of both methods was concordant regarding methylation class in 17/19 (89%) cases. Application of a platform-specific threshold for nanopore-based classification ensured a specificity of 100%, whereas sensitivity was 79%. Copy number variation profiles were generated for all cases and matched EPIC results in 18/19 (95%) samples, even allowing the identification of diagnostically or therapeutically relevant genomic alterations. Methylation-based classification of pediatric CNS tumors based on ultrasonic aspirator-reduced and otherwise discarded tissue is feasible using time- and cost-efficient nanopore sequencing.

Mutation of SIVA, a candidate metastasis gene identified from clonally related bilateral breast cancers, promotes breast cancer cell spread in vitro and in vivo.

Metastasis is the most dreaded outcome after a breast cancer diagnosis, and little is known regarding what triggers or promotes breast cancer to spread distally, or how to prevent or eradicate metastasis effectively. Bilateral breast cancers are an uncommon form of breast cancers. In our study, a percentage of bilateral breast cancers were clonally related based on copy number variation profiling. Whole exome sequencing and comparative sequence analysis revealed that a limited number of somatic mutations were acquired in this "breast-to-breast" metastasis that might promote breast cancer distant spread. One somatic mutation acquired was SIVA-D160N that displayed pro-metastatic phenotypes in vivo and in vitro. Over-expression of SIVA-D160N promoted migration and invasion of human MB-MDA-231 breast cancer cells in vitro, consistent with a dominant negative interfering function. When introduced via tail vein injection, 231 cells over-expressing SIVA-D160N displayed enhanced distant spread on IVIS imaging. Over-expression of SIVA-D160N promoted invasion and anchorage independent growth of mouse 4T1 breast cancer cells in vitro. When introduced orthotopically via mammary fat pad injection in syngeneic Balb/c mice, over-expression of SIVA-D160N in 4T1 cells increased orthotopically implanted mammary gland tumor growth as well as liver metastasis. Clonally related bilateral breast cancers represented a novel system to investigate metastasis and revealed a role of SIVA-D160N in breast cancer metastasis. Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets.

Evaluating cell culture reliability in pediatric brain tumor primary cells through DNA methylation profiling

In vitro models of pediatric brain tumors (pBT) are instrumental for better understanding the mechanisms contributing to oncogenesis and testing new therapies; thus, ideally, they should recapitulate the original tumor. We applied DNA methylation (DNAm) and copy number variation (CNV) profiling to characterize 241 pBT samples, including 155 tumors and 86 pBT-derived cell cultures, considering serum vs serum-free conditions, late vs early passages, and dimensionality (2D vs 3D cultures). We performed a t-SNE classification and identified differentially methylated regions in tumors compared to cell models. Early cell cultures recapitulate the original tumor, but serum media and 2D culturing were demonstrated to significantly contribute to the divergence of DNAm profiles from the parental ones. All divergent cells clustered together acquiring a common deregulated epigenetic signature suggesting a shared selective pressure. We identified a set of hypomethylated genes shared among unfaithful cells converging on response to growth factors and migration pathways, such as signaling cascade activation, tissue organization, and cellular migration. In conclusion, DNAm and CNV are informative tools that should be used to assess the recapitulation of pBT-cells from parental tumors.

Abstract 940: Integrated analysis of cfDNA fragmentomics, DNA methylation and cfRNA transcription in metastatic castration-resistant prostate cancer (mCRPC)

Abstract Background Liquid biopsies based on cell-free DNA (cfDNA) analysis provide non-invasive clinical diagnostic insights. Recently, cfDNA fragmentomics has emerged as a tool for inferring epigenomic and transcriptional information from tumor-derived cfDNA. We conducted a comprehensive profiling of cfDNA fragmentomics, whole transcriptome sequencing (WTS), and genome-wide DNA methylation on two metastatic castration-resistant prostate cancer (mCRPC) samples to systematically investigate molecular aberrations in mCRPC. Methods Two mCRPC patient plasma samples were extensively profiled using high-depth 150x whole-genome sequencing (WGS), 30x whole-genome methylation, and cfRNA WTS. CfDNA fragmentomics analysis was performed to assess androgen receptor (AR) transcriptional activity. We calculated fragment coverage around AR binding sites (ARBS) and quantified ARBS nucleosome profiling abnormality scores (ARBS scores) by comparing centric fragment coverage with normal plasma background. Additionally, we calculated fragment size entropy around AR promoter and enhancer regions to reflect AR gene expression activity. Fragmentomics-inferred gene activity was validated through promoter-targeted panels and WTS profiling of matched mCRPC samples. Results Both mCRPC plasma samples exhibited significant ARBS nucleosome depletion. Sample A showed a higher ARBS score compared to Sample B. Interestingly, AR enhancer activity inferred from high-depth WGS and targeted panels was high in both samples, while AR promoter activity was high only in Sample A. Genome-wide DNA methylation revealed hypo-methylation in AR enhancer and ARBS regions in both samples, with Sample A showing more pronounced hypo-methylation. Copy number variation analysis indicated AR amplification in Sample A and RB1 loss in Sample B. Collectively, these findings suggest that Sample A may represent androgen receptor-dependent prostate cancer (ARPC), while Sample B may have developed resistance to androgen therapy, possibly indicating neuroendocrine prostate cancer (NEPC). Conclusions This study, to our knowledge, is the first to combine high-depth WGS, promoter-targeted panels, WTS, and genome-wide DNA methylation to systematically study epigenomic and transcriptional dysregulation in mCRPC. The integration of mutation, copy number variation, fragmentomics, and DNA methylation profiling holds potential clinical utility for inferring prostate cancer subtypes, facilitating patient stratification, and guiding treatment selection. Citation Format: Chao Dai, Lisha Zhu, Yong Huang, Giancarlo Bonora, Kemin Zhou, Shidong Jia, Pan Du. Integrated analysis of cfDNA fragmentomics, DNA methylation and cfRNA transcription in metastatic castration-resistant prostate cancer (mCRPC) [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 940.

Abstract 2291: Bravo automation of Agilent Avida targeted enrichment for high-throughput detection of genomic alteration and DNA methylation

Abstract Background: Current genomic and epigenomic profiling of cancer tissue DNA or cfDNA (cell-free DNA) in liquid biopsy relies upon separate, time- and sample-consuming technologies for somatic variant detection or methylation analysis. Here we describe workflow and performance of the Agilent Bravo automated liquid handling platform with the Agilent Avida targeted enrichment solution for next generation sequencing of somatic variants and methylation profiling. This solution can effectively analyze low-input tumor DNA or cfDNA samples. The Avida Duo workflow enables highly sensitive detection of single nucleotide variant (SNV), insertions and deletions (INDEL), copy number variation (CNV) and DNA methylation profiles from a single sample, without any sample splitting. Methods and Results: Panels, reagents, and automated workflows for Avida DNA, Avida Methyl, and Avida Duo Methyl (combined DNA & methylation) kits were developed to accommodate up to 96 samples on the Bravo NGS workstation. The automated solution supports independent single-day workflows for somatic variants or methylation sample preparation. The Avida Duo analysis combines both workflows without sample splitting, streamlining the process and reducing sample consumption. Leveraging a focused cancer hotspot panel, we demonstrate excellent reproducibility and low allele frequency (SNV at sub 1%) variant detection in cfDNA samples and reference standards with as little as 10ng DNA input. We exhibit similar performance with a larger ~300 kb target region tumor profiling panel. Finally, we demonstrate DNA methylation detection in the standalone or combined (“Duo”) workflows across differentially methylated regions (DMRs) with a panel of ~3400 targets. Conclusions: Automation of the Avida targeted enrichment solution with the Bravo NGS workstation enables a sensitive, high-throughput, end-to-end analysis for detection of genomic alterations and DNA methylation changes from a single low-input cfDNA or tumor DNA sample. Citation Format: Ashraf Wahba, Tony Ho, Sarah Johns, Aswati Aravind, Heng Wang, Neelima V. Mehendale, Gilbert P. Amparo, Khine Win, Manuel Gomez, Grace Zhao, Douglas N. Roberts. Bravo automation of Agilent Avida targeted enrichment for high-throughput detection of genomic alteration and DNA methylation [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 2291.

Abstract 3704: Whole genome and targeted proteome analysis of single cancer cells

Abstract The simultaneous genome and proteome analysis of very rare single cells would enable addressing important biological and diagnostic questions particularly in cancer. Here, we introduce a novel genome and proteome (G&P) analytic workflow, a method allowing comprehensive analysis of single-cell DNA and targeted profiling of protein expression in single cells. As a proof of concept, we demonstrate the capability of the method by quantifying copy number of the ERBB2 gene alongside with protein expression levels of HER2 and phospho-HER2 in single cells. The G&P workflow utilizes antibodies conjugated with DNA oligonucleotides designed to enable their amplification alongside the single-cell genome facilitating parallel genome and proteome profiling by either quantitative PCR (qPCR) or sequencing. We utilized antibodies targeting cytokeratin 8/18/19, HER2 and phospho-HER (Tyr1248). Performance of each DNA-conjugated antibody was assessed by immunofluorescence staining in a variety of breast cancer cell lines (MDA-MB231, MDA-MB453, BT474 and MCF7) and sample types. Stained cells were isolated by manual micromanipulation and subjected to whole genome amplification (WGA). Protein expression levels, derived from quantification of the amplified DNA tags, were measured by qPCR. Shallow whole genome sequencing was employed to facilitate genome-wide profiling of copy number variations (CNVs), including the ERBB2 locus. We successfully developed and tested a G&P workflow allowing parallel genome-wide CNV profiling and quantification of three target proteins. G&P measurement yielded concordant results to immunofluorescence quantification for all tested markers. Furthermore, the workflow allowed direct correlation of copy numbers of the ERBB2 gene with HER2 expression in single cancer cells. Notably, the method enabled measurements of cellular and molecular responses at the single-cell level to lapatinib treatment, i.e. monitoring of the HER2 pathway activation level. Our novel multiplex G&P technique is capable of generating multiparametric measurements linking DNA copy numbers and expression levels of selected genes of interest. The method is optimized for analysis of single cells from rare cell populations and is readily translatable to study circulating tumor cells (CTCs) and disseminated cancer cells (DCCs), enabling for the first time pathway analysis via phosphoprotein analyses of these cells. Citation Format: Atieh Alyasin, Kathrin Weidele, Catherine Botteron, Christoph A. Klein, Zbigniew T. Czyż. Whole genome and targeted proteome analysis of single cancer cells [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 3704.

Abstract 893: Studying the impact of CNVs on expression at single-cell resolution in HGSOC using autoencoders

Abstract High-grade serous ovarian cancer (HGSOC) is one of the most lethal gynecological malignancies. Lack of common targetable oncogenic mutations has complicated the development of directed therapies to combat emerging resistance. This malignancy is mainly characterized by the mutation of gene TP53, which promotes genome instability for the emergence of extensive copy number variations (CNVs). However its impact on gene expression at the single-cell level is not well understood. In this study, we aim to investigate the effect of CNVs on transcriptomic signatures by taking advantage of variational autoencoders (VAE) ability for dimensionality reduction, unsupervised learning and feature extraction. The use of VAEs is becoming more popular for the analysis of scRNAseq data, and scVI is one of the most versatile VAE applications performing wide variety of tasks. Here, we used single-cell RNA sequencing (scRNA-seq) data from 90 longitudinal samples of 64 HGSOC patients and inferred CNVs in each cell using inferCNV, an established computational pipeline. Then, we modified scVI algorithm to allow the VAE to reconstruct CNVs from a latent space originated from gene expression profiles and viceversa. Our models were capable of reconstructing CNV profiles accurately from expression data and also remove batch effect. From these models we could observe how, after the integration of genomic information, the latent clusters produced from the transcriptomic space were influenced by the amplifications or deletions of certain genomic regions. Moreover, some of these clusters were characterized by the alteration of important oncogenes in HGSOC, such as KRAS and CCNE1, and allowed us to focus on the transcriptomic consequences of their amplifications. With the results from the approach presented here, we gained a more comprehensive picture of the impact of genomic alterations on HGSOC. As future work, we plan to validate of this results on external cohorts and link the identified signatures to clinically relevant features such as prognosis or chemotherapy response. Citation Format: Matias Marin Falco, Teemu Närhi, Erdogan Pekcan Erkan, Johanna Hynninen, Anna Vähärautio. Studying the impact of CNVs on expression at single-cell resolution in HGSOC using autoencoders [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 893.

Clinicopathological and molecular landscape of 5-year IDH-wild-type glioblastoma survivors: A multicentric retrospective study

Five-year glioblastoma (GBM) survivors (LTS) are the minority of the isocitrate dehydrogenase (IDH)-wild-type GBM patients, and their molecular fingerprint is still largely unexplored. This multicenter retrospective study analyzed a large LTS-GBM cohort from nine Italian institutions and molecularly characterized a subgroup of patients by mutation, DNA methylation (DNAm) and copy number variation (CNV) profiling, comparing it to standard survival GBM. Mutation scan allowed the identification of pathogenic variants in most cases, showing a similar mutational spectrum in both groups, and highlighted TP53 as the most commonly mutated gene in the LTS group. We confirmed DNAm as a valuable tool for GBM classification with a diagnostic refinement by using brain tumor classifier v12.5. LTS were more heterogeneous with more cases classified as diffuse pediatric high-grade glioma subtypes and having peculiar CNVs. We observed a global higher methylation in CpG islands and in gene promoters of LTS with methylation levels of distinct gene promoters correlating with prognosis.

Comparative epigenomics indicate a common origin of ectopic and intrasellar corticotroph pituitary neuroendocrine tumors/adenomas: a case report.

Ectopic pituitary neuroendocrine tumors (PitNET)/adenomas are rare and diagnostically challenging extra-sellar tumors. Previous studies have demonstrated the impact of epigenomic analyses in the diagnostics of sellar neoplasms and characterized the close relationship of epigenomic signatures and cellular origins of PitNET/adenomas. As of today, little is known about the pathogenesis of ectopic PitNET/adenomas, and epigenomic analyses have not been performed in these rare tumors. We report on the clinical course of an 81-year-old patient with sphenoid ectopic sparsely granulated corticotroph PitNET/adenoma and deploy genome-wide DNA methylation analysis to compare its methylation profile to a reference cohort of sellar neoplasms. Genome-wide methylation analysis revealed an epigenomic profile analogous to reference sellar corticotroph PitNET/adenomas, and the copy number variation profile showed loss of chromosomes 18 and 22. The methylation profile shows concordance with sellar corticotroph PitNET/adenomas suggesting a common cellular origin and confirming the reliability of methylation analyses as a diagnostic method in these rare tumors. This is the first data suggesting that epigenetic profiles of ectopic PitNET/adenoma do not differ from their sellar counterparts.

Evaluation of Circulating Tumor DNA as a Liquid Biomarker in Uveal Melanoma.

Uveal melanoma (UM) has a high propensity to metastasize. Prognosis is associated with specific driver mutations and copy number variations (CNVs), but limited primary tumor tissue is available for molecular characterization due to eye-sparing irradiation treatment. This study aimed to assess the rise in circulating tumor DNA (ctDNA) levels in UM and evaluate its efficacy for CNV-profiling of patients with UM. In a pilot study, we assessed ctDNA levels in the blood of patients with UM (n = 18) at various time points, including the time of diagnosis (n = 13), during fractionated stereotactic radiotherapy (fSRT) treatment (n = 6), and upon detection of metastatic disease (n = 13). Shallow whole-genome sequencing (sWGS) combined with in silico size-selection was used to identify prognostically relevant CNVs in patients with UM (n = 26) from peripheral blood retrieved at the time of diagnosis (n = 9), during fSRT (n = 5), during post-treatment follow-up (n = 4), metastasis detection (n = 6), and metastasis follow-up (n = 4). A total of 34 patients had blood analyzed for ctDNA detection (n = 18) and/or CNV analysis (n = 26) at various time points. At the time of diagnosis, 5 of 13 patients (38%) had detectable ctDNA (median = 0 copies/mL). Upon detection of metastatic disease, ctDNA was detected in 10 of 13 patients (77%) and showed increased ctDNA levels (median = 24 copies/mL, P < 0.01). Among the six patients analyzed during fSRT, three (50%) patients had detectable ctDNA at baseline and three of six (50%) patients had undetectable levels of ctDNA. During the fSRT regimen, ctDNA levels remained unchanged (P > 0.05). The ctDNA fractions were undetectable to low in localized disease, and sWGS did not elucidate chromosome 3 status from blood samples. However, in 7 of 10 (70%) patients with metastases, the detection of chromosome 3 loss corresponded to the high metastatic-risk class. The rise in ctDNA levels observed in patients with UM harboring metastases suggests its potential utility for CNV profiling. These findings highlight the potential of using ctDNA for metastasis detection and patient inclusion in therapeutic studies targeting metastatic UM.

Nucleosome profiling at AR binding sites (ARBS) to provide a prognostic tool for metastatic castration-resistant prostate cancer (mCRPC).

42 Background: Prostate cancer is the second leading cause of cancer death for men in the U.S., and metastatic castration-resistant prostate cancer (mCRPC) is the most advanced form. In previous work, we have reported prognostic significance of PTEN-PI3K-AKT pathway and DNA damage response aberrations detected in cell-free DNA (cfDNA) of mCRPC. Here we utilized nucleosome profiling pattern at androgen receptor (AR) binding sites to further investigate AR signaling pathway dysregulation of mCRPC. Methods: Using the next-generation sequencing PredicineScore liquid biopsy assay (low-pass whole genome sequencing, LP-WGS), we profiled cfDNA fragment coverage centered around AR binding sites (ARBS). For 118 mCRPC patient samples, we quantified sample-level ARBS nucleosome profiling abnormality score (ARBS score) by comparing its centric fragment coverage with normal plasma background using standard Z-score. ARBS score was correlated with clinical outcomes including PSA response rate (PSA RR), progression-free survival and overall survival (OS). Results: By comparing ARBS nucleosome profiling and normal plasma background, we found that mCRPC plasma samples had significant ARBS nucleosome depletion, reflective of transcription factor binding and persistent AR signaling. Notably, ARBS nucleosome depletion was prostate cancer specific, and did not occur in other examined cancer types. ARBS score was highly correlated with tumor fraction (R=0.82), indicating that high tumor fraction mCRPC sample had higher AR binding. Importantly, we found that high ARBS score (&gt;2) in pre-treatment samples (n=86) was associated with significantly shorter OS and lower PSA RR compared with low ARBS (≤2) group for patients receiving AR pathway inhibitor (ARPI) or taxane chemotherapy (13.4 vs. 19.4 months, p=7.3×10-3, 45.7% vs. 77.5%, p=5.2×10-3). By integrating genome-wide DNA methylation profiling, we further found that ARBS was hypo-methylated in mCRPC patients, and identified a strong negative correlation between DNA methylation beta value and ARBS score (R=-0.83). Conclusions: ARBS nucleosome profiling abnormality inferred from LP-WGS can serve as a key prognostic tool for mCRPC patients. Patients with high ARBS score had worse clinical outcomes, highlighting the potential clinical utility of cfDNA fragmentomics analysis for mCRPC patient stratification. Integration of mutation, copy number variation and fragmentomics profiling of ARBS may further enhance our understanding of molecular aberrations and treatment outcomes in mCRPC.

Abstract A034: Development of a novel class of genomic biomarkers through mathematical modeling of cancer genome contiguity

Abstract Introduction: Chromosomal instability (CIN) is a hallmark of cancer aggressiveness. However, in lung adenocarcinoma (LUAD) the most common methods for measuring genomic instability, such as the weighted Genome Instability Index (wGII), are not reliable predictors of patient outcomes. The wGII measures the portion of the genome altered by copy number variation (CNV). The wGII quantifies aneuploidy but ignores other properties of CNVs such as their length distribution. We hypothesized that quantification of genome contiguity may overcome the limitations of wGII and help identify novel prognostic biomarkers. Method: We develop a novel measure of CIN based on mathematical modeling of genome breakage patterns. Utilizing segmented CNV profiles we infer two properties of the genome breakage process – its intensity and dispersion. Intensity is proportional to the number of genome breakpoints and is estimated by the total number of CNV segments. Dispersion quantifies spatial dependence of breakpoints over a wide range of genomic scales. It is computed by Ripley’s K-function which compares the distribution of breakpoints with a random Poisson point process. Jointly, intensity and dispersion, which we term the weighted Genome Contiguity Index (wGCI), estimate the contiguity of the genome. We contrast the wGCI with a heuristic score based on quantiles of segment lengths. Results: We sought to evaluate the association between the wGCI and patients’ survival in a proteogenomic cohort of 215 primary LUAD tumors profiled using whole-genome sequencing (WGS). In support of our hypothesis, we observed that patients had significantly better outcomes if their tumor genomes had longer segments compared to those with a high degree of fragmentation (P=0.014). Utilizing the wGCI, we found that tumor genomes with dispersed breakage (and low contiguity) were associated with worst outcomes (P=0.01). To identify mechanisms associated with dispersed breakage patterns we compared genomic features of the two groups. We found that LUAD tumors with highly fragmented genomes have a higher rate of TERT amplifications (P=0.005) and increased TERT RNA expression (P=2e-6). These tumors are also enriched for TP53 mutations (P=2e-16) and MYC amplifications (P=0.01). Given the cost and practical challenges of clinical WGS we leveraged mass-spectrometry proteomics to identify protein biomarkers. We found IGF2BP3 to be significantly upregulated (P=0.0006) in highly fragmented tumors and to be associated with worse outcomes (P=0.011). We use immunohistochemistry (IHC) to develop and validate IGF2BP3 as a prognostic biomarker in independent lung cancer cohorts. Conclusion: We introduced a novel quantitative measure of CIN that uniquely captures the impact of chromosome breakage on LUAD patients' clinical outcomes. Further, we identified upregulation of IGF2BP3 as a proxy to identify fragmented genomes using IHC. Our work underscores the value of mathematical modeling of genome breakage patterns to develop complex genomic biomarkers. Citation Format: Noshad Hosseini, Rahul Mannan, Alexey Nesvizhskii, Saravana Dhanasekaran, Marcin Cieslik. Development of a novel class of genomic biomarkers through mathematical modeling of cancer genome contiguity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr A034.

Single-cell RNA sequencing reveals the mechanism of PI3K/AKT/mTOR signaling pathway activation in lung adenocarcinoma by KRAS mutation.

Aberrant activation of the phosphatidlinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway has been shown to play an important role in lung adenocarcinoma (LUAD). The effect of KRAS mutations, one of the important signatures of LUAD, on the PI3K/AKT/mTOR pathway in LUAD remains unclear. The Seurat package and principal component analysis were used for cell categorization of single-cell RNA sequencing data of LUAD. The AUCell score was used to assess the activity of the PI3K/AKT/mTOR pathway. Meanwhile, using the gene expression profiles and mutation profiles in the The Cancer Genome Atlas dataset, LUAD patients were categorized into KRAS-mutant (KRAS-MT) and KRAS-wild-types (KRAS-WT), and the corresponding enrichment scores were calculated using gene set enrichment analysis analysis. Finally, the subpopulation of cells with the highest pathway activity was identified, the copy number variation profile of this subpopulation was inscribed using the inferCNV package and the CMap database was utilized to make predictions for drugs targeting this subpopulation. There is higher PI3K/AKT/mTOR pathway activity in LUAD epithelial cells with KRAS mutations, and high expression of KRAS, PIK3CA, AKT1 and PDPK1. In particular, we found significantly higher levels of pathway activity and associated gene expression in KRAS-MT than in KRAS-WT. We identified the highest pathway activity on a subpopulation of GRB2+ epithelial cells and the presence of amplified genes within its pathway. Finally, drugs were able to target GRB2+ epithelial cell subpopulations, such as wortmannin, palbociclib and angiogenesis inhibitor. The present study provides a basic theory for the activation of the PI3K/AKT/mTOR signaling pathway as a result of KRAS mutations.

High overall copy number variation burden by genome-wide methylation profiling holds negative prognostic value in surgically treated pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive type of cancer with an overall 5-year survival of around 10 %. New prognostic tools to stratify patients are needed. Our main aim was to evaluate the prognostic value of overall copy number variation (CNV) burden in surgically treated PDAC. DNA extracted from 108 surgical PDAC specimens was examined to collect data on the genome-wide DNA methylation status of >850,000 CpG sites in promoter, gene body, and enhancer regions (Illumina Infinium Methylation EPIC BeadChip Kit). CNV profiles were obtained and all PDACs were stratified into one of three groups: Low, moderate, or high overall CNV burden. Tumors histologically showing a dominant conventional and/or tubulopapillary pattern in 60 %–100 % and 0–59 % were categorized as Group A and Group B as per Kalimuthu. We also performed targeted next-generation sequencing (NGS) and immunohistochemistry. High overall CNV burden held independent negative prognostic value with poor survival (HR 4.01 (95%CI 1.96–8.19), p = 0.00014) and was more frequent in Group B (p = 0.0003). Most frequent chromosomal arm-level aberrations were gains of 8q (29 %) and 1q (19 %) and losses of 17p (55 %), 18q (43 %), 6q (37 %), 9p (36 %), 6p (26 %), 19p (26 %), and 8p (25 %). Most frequent mutations found were in KRAS (95 %), TP53 (62 %), CDKN2A (24 %), SMAD4 (23 %), ATM (9 %), ARID1A (7 %), RNF43 (7 %), GNAS (6 %), and KDM6A (6 %). Group A PDACs showed more frequently KRAS variants other than Gly12Val and Gly12Asp (p = 0.012). Our data indicate that overall CNV burden using genome-wide methylation profiling may be a useful prognostic tool in surgically treated PDAC. Importantly, our approach, using data from genome-wide methylation profiling for analysis of overall CNV burden, can be performed on formalin-fixed and paraffin embedded PDAC tissues. Future studies should examine the prognostic value of overall CNV burden in unresectable PDAC.

PATH-13. APPLICATIONS OF SPATIAL TRANSCRIPTOMICS FOR THE DIAGNOSTICS OF GLIOMAS

Abstract Due to their infiltrative growth, diffuse gliomas can pose a major challenge for neuropathologists. Lack of specific immunohistochemistry markers for some gliomas like IDH-wildtype glioblastoma can make it hard to identify the tumour cell content or distinguish between tumour and reactive gliosis. Other hurdles are high fractions of DNA from healthy cells in molecular diagnostic analysis, or scarce tissue, which can result in a failed DNA extraction. To overcome these limitations, we evaluated the application of spatial transcriptomics on 14 glioblastoma bulk resections and 18 stereotactic biopsies of 7 glioblastoma, IDH wildtype, 4 oligodendroglioma IDH-mutant and 7 astrocytoma IDH-mutant samples with the aim to generate a diagnostic report containing all information needed by the neuropathologist and clinician. Using the SPATA2 R package, we were able to infer the copy number variation (CNV) profiles for each spot. When comparing the inferred CNVs to the CNVs calculated by the 850K methylome analysis, a correlation between CNVs identified from the 850K data and the inferred CNVs could be seen. For diagnostic relevant CNVs of chr. 7, 10, 1p and 19q, the inferred CNVs were concordant with the 850K data in 100% of the cases with confirmed tumour tissue. CNVs from spatial transcriptomics were able to reveal sub-clones, which could not be detected by the 850K array data. The CNVs could then be used in combination with a deconvolution approach to determine the tumour burden of the tissue. Using RNA expression, the immunohistochemistry staining of important diagnostic markers like NeuN, GFAP and Ki67 was predicted. In addition, the spatial gene expression could be used to identify the glioblastoma subtype based on the gene expression of different methylation subtypes. All the above-mentioned analysis also generated meaningful results for tissue fragments smaller than 1mm in diameter, which are too small for molecular diagnostic analysis.

Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer

BackgroundProstate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients’ well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer. MethodsThe study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs. ResultsSix molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024). ConclusionsOur study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Case Series of Soft Tissue Sarcoma Patients with Brain Metastasis with Implications from Genomic and Transcriptomic Analysis.

Brain metastasis rarely occurs in soft tissue sarcoma (STS). Here, we present five cases of STS with brain metastases with genetic profiles. We included five patients from Seoul National University Hospital who were diagnosed with STS with metastasis to the brain. Tissue from the brain metastasis along with that from the primary site or other metastases were used for DNA and RNA sequencing to identify genetic profiles. Gene expression profiles were compared with sarcoma samples from The Cancer Genome Atlas. The overall survival after diagnosis of brain metastasis ranged from 2.2 to 34.3 months. Comparison of mutational profiles between brain metastases and matched primary or other metastatic samples showed similar profiles. In two patients, copy number variation profiles between brain metastasis and other tumors showed several differences including MYCL, JUN, MYC, and DDR2 amplification. Gene ontology analysis showed that the group of genes significantly highly expressed in the brain metastasis samples was enriched in the G-protein coupled receptor activity, structural constituent of chromatin, protein heterodimerization activity, and binding of DNA, RNA, and protein. Gene set enrichment analysis showed enrichment in the pathway of neuroactive ligand-receptor interaction and systemic lupus erythematosus. The five patients had variable ranges of clinical courses and outcomes. Genomic and transcriptomic analysis of STS with brain metastasis implicates possible involvement of complex expression modification and epigenetic changes rather than the addition of single driver gene alteration.

P07.05.B DNA-METHYLATION PROFILING IS AN EFFECTIVE ASSET FOR IDENTIFICATION OF TUMORS IN SUSPECTED, YET IMMUNOHISTOCHEMICALLY UNSPECIFIABLE, NEURO-ONCOLOGICAL CASES

Abstract BACKGROUND Patients with a suspected neurooncological disease on radiographic images and no histopathological evidence of a tumor on the surgically retrieved tissue, pose a great challenge for clinicians and neuropathologists. DNA methylation-based classifications and copy number variation (CNV) analysis allow robust brain tumor classification. Here, we aim to evaluate their diagnostic properties in histopathologically unspecifiable or negative cases. MATERIAL AND METHODS We screened all neurosurgical cases, which underwent surgery at our institution between 2009 and 2021, with suspected neurooncological, but negative or unspecific histopathological diagnosis. We differentiated two groups: cases with cell-enriched, reactive tissue (+/- single tumor cells), insufficient to fully classify the lesion according to criteria of WHO for CNS tumors (group 1) and cases without histological evidence of tumor cells (group 2). In both groups, DNA methylation profiling was applied. Endpoints were diagnostic results of DNA methylation profiling (classifier Score ≥0.9) and evidence/no evidence of tumorigenic CNV alterations and eventually feasibility to make a diagnosis according to WHO 2021 criteria for brain tumors. RESULTS 23 cases with unspecifiable histopathological diagnosis were identified, out of whom 5 (21.7%) were confirmed as healthy brain tissue via DNA-methylation profiling, whereas the eventual diagnosis of tumorigenic tissue was provided in 18 (78.3%) cases. 14 of these were assigned to group 1, 4 cases to group 2. In 6 cases of group 1 (42.9%) DNA-methylation profiling resulted in a successful tumor classification (score ≥0.9) compared to 1 case (25%) in group 2. CNV indicated tumorigenic alterations in 9 (64.3%) patients in group 1 and 2 (50%) patients in group 2. Specific tumor alterations in the CNV were found in 8 (57.1%) patients in group 1 and in 1 (25%) patient in group 2. Combining CNV and DNA-methylation profiling, a final tumor diagnosis according to WHO 2021 criteria was feasible in 9 (64.3%) cases in group 1 and 3 (75%) cases in group 2. Median time from surgery to histopathological diagnosis was 6 and 7 days and 32.5 and 31 days for integrated diagnosis (group 1 vs. group 2). CONCLUSION Molecular diagnostics with DNA-methylation profiling and CNV analysis substantially increases the likelihood of a definitive diagnosis according to 2021 WHO criteria for these challenging cases.