Whole-genome Doubling Research Articles

High-Throughput Empirical and Virtual Screening to Discover Novel Inhibitors of Polyploid Giant Cancer Cells in Breast Cancer.

Therapy resistance in breast cancer is increasingly attributed to polyploid giant cancer cells (PGCCs), which arise through whole-genome doubling and exhibit heightened resilience to standard treatments. Characterized by enlarged nuclei and increased DNA content, these cells tend to be dormant under therapeutic stress, driving disease relapse. Despite their critical role in resistance, strategies to effectively target PGCCs are limited, largely due to the lack of high-throughput methods for assessing their viability. Traditional assays lack the sensitivity needed to detect PGCC-specific elimination, prompting the development of novel approaches. To address this challenge, we developed a high-throughput single-cell morphological analysis workflow designed to differentiate compounds that selectively inhibit non-PGCCs, PGCCs, or both. Using this method, we screened a library of 2,726 FDA Phase 1-approved drugs, identifying promising anti-PGCC candidates, including proteasome inhibitors, FOXM1, CHK, and macrocyclic lactones. Notably, RNA-Seq analysis of cells treated with the macrocyclic lactone Pyronaridine revealed AXL inhibition as a potential strategy for targeting PGCCs. Although our single-cell morphological analysis pipeline is powerful, empirically testing all existing compounds is impractical and inefficient. To overcome this limitation, we trained a machine learning model to predict anti-PGCC efficacy in silico, integrating chemical fingerprints and compound descriptions from prior publications and databases. The model demonstrated a high correlation with experimental outcomes and predicted efficacious compounds in an expanded library of over 6,000 drugs. Among the top-ranked predictions, we experimentally validated two compounds as potent PGCC inhibitors. These findings underscore the synergistic potential of integrating high-throughput empirical screening with machine learning-based virtual screening to accelerate the discovery of novel therapies, particularly for targeting therapy-resistant PGCCs in breast cancer.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer.

Whole-genome doubling (WGD) is a critical driver of tumor development and is linked to drug resistance and metastasis in solid malignancies. Here, we demonstrate that WGD is an ongoing mutational process in tumor evolution. Using single-cell whole-genome sequencing, we measured and modeled how WGD events are distributed across cellular populations within tumors and associated WGD dynamics with properties of genome diversification and phenotypic consequences of innate immunity. We studied WGD evolution in 65 high-grade serous ovarian cancer (HGSOC) tissue samples from 40 patients, yielding 29,481 tumor cell genomes. We found near-ubiquitous evidence of WGD as an ongoing mutational process promoting cell-cell diversity, high rates of chromosomal missegregation, and consequent micronucleation. Using a novel mutation-based WGD timing method, doubleTime , we delineated specific modes by which WGD can drive tumor evolution: (i) unitary evolutionary origin followed by significant diversification, (ii) independent WGD events on a pre-existing background of copy number diversity, and (iii) evolutionarily late clonal expansions of WGD populations. Additionally, through integrated single-cell RNA sequencing and high-resolution immunofluorescence microscopy, we found that inflammatory signaling and cGAS-STING pathway activation result from ongoing chromosomal instability and are restricted to tumors that remain predominantly diploid. This contrasted with predominantly WGD tumors, which exhibited significant quiescent and immunosuppressive phenotypic states. Together, these findings establish WGD as an evolutionarily 'active' mutational process that promotes evolvability and dysregulated immunity in late stage ovarian cancer.

The Variable Genomic Landscape During Osteosarcoma Progression: Insights From a Longitudinal WGS Analysis.

Osteosarcoma is a primary bone tumor that exhibits a complex genomic landscape characterized by gross chromosomal abnormalities. Osteosarcoma patients often develop metastatic disease, resulting in limited therapeutic options and poor survival rates. To gain knowledge on the mechanisms underlying osteosarcoma heterogeneity and metastatic process, it is important to obtain a detailed profile of the genomic alterations that accompany osteosarcoma progression. We performed WGS on multiple tissue samples from six patients with osteosarcoma, including the treatment naïve biopsy of the primary tumor, resection of the primary tumor after neoadjuvant chemotherapy, local recurrence, and distant metastases. A comprehensive analysis of single-nucleotide variants (SNVs), structural variants, copy number alterations (CNAs), and chromothripsis events revealed the genomic heterogeneity during osteosarcoma progression. SNVs and structural variants were found to accumulate over time, contributing to an increased complexity of the genome of osteosarcoma during disease progression. Phylogenetic trees based on SNVs and structural variants reveal distinct evolutionary patterns between patients, including linear, neutral, and branched patterns. The majority of osteosarcomas showed variable copy number profiles or gained whole-genome doubling in later occurrences. Large proportions of the genome were affected by loss of heterozygosity (LOH), although these regions remain stable during progression. Additionally, chromothripsis is not confined to a single early event, as multiple other chromothripsis events may appear in later occurrences. Together, we provide a detailed analysis of the complex genome of osteosarcomas and show that five of six osteosarcoma genomes are highly dynamic and variable during progression.

Mixed responses to targeted therapy driven by chromosomal instability through p53 dysfunction and genome doubling

The phenomenon of mixed/heterogenous treatment responses to cancer therapies within an individual patient presents a challenging clinical scenario. Furthermore, the molecular basis of mixed intra-patient tumor responses remains unclear. Here, we show that patients with metastatic lung adenocarcinoma harbouring co-mutations of EGFR and TP53, are more likely to have mixed intra-patient tumor responses to EGFR tyrosine kinase inhibition (TKI), compared to those with an EGFR mutation alone. The combined presence of whole genome doubling (WGD) and TP53 co-mutations leads to increased genome instability and genomic copy number aberrations in genes implicated in EGFR TKI resistance. Using mouse models and an in vitro isogenic p53-mutant model system, we provide evidence that WGD provides diverse routes to drug resistance by increasing the probability of acquiring copy-number gains or losses relative to non-WGD cells. These data provide a molecular basis for mixed tumor responses to targeted therapy, within an individual patient, with implications for therapeutic strategies.

Adjuvant mFOLFIRINOX (mFFX) for resected pancreatic cancer (PC): Long term clinical and genomic outcomes.

4170 Background: Adjuvant chemotherapy with mFFX is the standard for pts with ECOG 0-1 (1) after pancreatectomy for resectable PC. Herein, we report long-term survival data on an expanded cohort and present comprehensive genomic analyses. Methods: Pts with resected PC who received >1 dose of adjuvant mFFX identified from institutional databases. Primary endpoints: Recurrence Free Survival (mRFS) and Overall Survival (mOS) calculated from start of treatment until recurrence or death. Key secondary endpoints: clinical factors, genomic descriptors ( KRAS status, whole genome doubling (WGD), and homologous recombination deficiency (HRD)) associated with outcome. Kaplan-Meier method used to estimate RFS and OS. Univariate Cox proportional hazards model correlated clinico-genomic characteristics with RFS and OS. Results: N=147 identified between 01/2015-01/2022. Median age: 67 years; N= 22 (15%) > 75 years. Several prognostically unfavorable groups; N=52 (36%) stage III disease/ N2 nodal status; N=115 (78%) lymphovascular invasion (LVI); N=133 (90%) perineural invasion (PNI). Median time from surgery to start mFFX: 1.78m (IQR; 1.45, 2.12). Median CA 19-9 at start mFFX: 21 (range 0-1,124). N=124 (84%) pts completed 12 doses mFFX (+/- 12 doses oxaliplatin). N=98 pts (67%) stopped oxaliplatin early for neuropathy. With the median follow up 35.1m (range 5.1, 73.0), mRFS 27m (95% CI 20, 39) and OS not reached (NR). For >75 cohort, mRFS 12m (95% CI 9.6, NR) and mOS 30m (95% CI 19, NR). mFFX started <8 weeks from resection associated with improved RFS (HR 0.62; 95% CI 0.41, 0.96; p= 0.033) and OS (HR 0.53; 95% CI 0.3, 0.94; p= 0.030). T3 tumors associated with worse RFS (HR 2.82, 95% CI 1.28, 6.20; p=0.010) and OS (HR 5.10, 95% CI 1.45, 18; p=0.011). Genomic variables summarized (Table). KRASmutation (+), WGD (+), and higher KRAS CNV trended to shorter RFS and OS; statistical significance limited by small subgroups. HRD status did not confer differences in OS. Conclusions: Adjuvant mFFX is an effective therapy and results in long-term OS outcome in resected PC in a non-trial setting, including for pts >75 years. Early initiation of adjuvant mFFX may optimize outcome. Trends observed for improved outcome in select genomic subsets, which require large-scale validation. 1. Conroy, JAMA Onc, 2022. [Table: see text]

CDK4/6 activity is required during G2 arrest to prevent stress-induced endoreplication.

Cell cycle events are coordinated by cyclin-dependent kinases (CDKs) to ensure robust cell division. CDK4/6 and CDK2 regulate the growth 1 (G1) to synthesis (S) phase transition of the cell cycle by responding to mitogen signaling, promoting E2F transcription and inhibition of the anaphase-promoting complex. We found that this mechanism was still required in G2-arrested cells to prevent cell cycle exit after the S phase. This mechanism revealed a role for CDK4/6 in maintaining the G2 state, challenging the notion that the cell cycle is irreversible and that cells do not require mitogens after passing the restriction point. Exit from G2 occurred during ribotoxic stress and was actively mediated by stress-activated protein kinases. Upon relief of stress, a significant fraction of cells underwent a second round of DNA replication that led to whole-genome doubling.

Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes.

The extent of cell-to-cell variation in tumor mitochondrial DNA (mtDNA) copy number and genotype, and the phenotypic and evolutionary consequences of such variation, are poorly characterized. Here we use amplification-free single-cell whole-genome sequencing (Direct Library Prep (DLP+)) to simultaneously assay mtDNA copy number and nuclear DNA (nuDNA) in 72,275 single cells derived from immortalized cell lines, patient-derived xenografts and primary human tumors. Cells typically contained thousands of mtDNA copies, but variation in mtDNA copy number was extensive and strongly associated with cell size. Pervasive whole-genome doubling events in nuDNA associated with stoichiometrically balanced adaptations in mtDNA copy number, implying that mtDNA-to-nuDNA ratio, rather than mtDNA copy number itself, mediated downstream phenotypes. Finally, multimodal analysis of DLP+ and single-cell RNA sequencing identified both somatic loss-of-function and germline noncoding variants in mtDNA linked to heteroplasmy-dependent changes in mtDNA copy number and mitochondrial transcription, revealing phenotypic adaptations to disrupted nuclear/mitochondrial balance.

Gene expression analysis of drought tolerance and cuticular wax biosynthesis in diploid and tetraploid induced wallflowers

Whole-genome doubling leads to cell reprogramming, upregulation of stress genes, and establishment of new pathways of drought stress responses in plants. This study investigated the molecular mechanisms of drought tolerance and cuticular wax characteristics in diploid and tetraploid-induced Erysimum cheiri. According to real-time PCR analysis, tetraploid induced wallflowers exhibited increased expression of several genes encoding transcription factors (TFs), including AREB1 and AREB3; the stress response genes RD29A and ERD1 under drought stress conditions. Furthermore, two cuticular wax biosynthetic pathway genes, CER1 and SHN1, were upregulated in tetraploid plants under drought conditions. Leaf morphological studies revealed that tetraploid leaves were covered with unique cuticular wax crystalloids, which produced a white fluffy appearance, while the diploid leaves were green and smooth. The greater content of epicuticular wax in tetraploid leaves than in diploid leaves can explain the decrease in cuticle permeability as well as the decrease in water loss and improvement in drought tolerance in wallflowers. GC‒MS analysis revealed that the wax components included alkanes, alcohols, aldehydes, and fatty acids. The most abundant wax compound in this plant was alkanes (50%), the most predominant of which was C29. The relative abundance of these compounds increased significantly in tetraploid plants under drought stress conditions. These findings revealed that tetraploid-induced wallflowers presented upregulation of multiple drought-related and wax biosynthesis genes; therefore, polyploidization has proved useful for improving plant drought tolerance.

Abstract LB243: Deep learning-based molecular characterization of lung cancers from never smokers using hematoxylin and eosin-stained whole slide images

Abstract Purpose: This study employs cutting-edge deep learning techniques to comprehensively analyze hematoxylin and eosin-stained (H&E) whole slide images (WSIs) to predict which tumors carry driver gene alterations, mutational signatures, and additional molecular features among lung cancers from never-smokers (LCINS)— the seventh leading cause of cancer death worldwide. Method: A total of 464 H&E-stained WSIs of lung adenocarcinomas from the Sherlock-Lung study were utilized, with 325 WSIs for model training and 139 for testing. Alongside the WSIs, genomic data, including mutations (overall nonsynonymous mutations and driver mutations only), fusions, or copy numbers in driver genes (TP53, KRAS, EGFR, CDKN2A, MDM2, ALK, RBM10), mutational signatures (APOBEC), molecular features (Kataegies, Whole Genome Doubling (WGD) status, Tumor Mutational Burden (TMB)), and specific hotspot driver mutation in EGFR (p.L858R and p.E746_A750del) and KRAS (p.G12C, p.G12V, and p.G12D), were included for all tumors. Each WSI was assigned different labels based on the presence or absence of these genomic alterations or features. We used a customized multilabel binary deep learning model based on ResNet50, a residual convolutional neural network, for analyzing the data. The network was trained from scratch, with an initial epoch set to 100. Results: Our methodology demonstrated high predictive performance, measured by the area under the receiver operating characteristic (AUROC). In the presence or absence category, we achieved high AUROC for detecting any alterations in these driver genes: TP53 (0.81), KRAS (0.92), EGFR (0.93), CDKN2A deletion (0.88), MDM2 amplification (0.94), and ALK fusion (0.86). We also evaluated molecular features, obtaining AUROC scores of 0.79 for WGD status and 0.86 for Kataegies. Moderate AUROC scores were observed for tumors with RBM10 mutations (0.67), high TMB (0.64), and APOBEC signatures (0.56). When focusing on driver mutations only, we achieved high AUROC scores for EGFR (0.88), KRAS (0.84), TP53 (0.93), and RBM10 (0.78). In addition, our model successfully predicted tumors with specific mutations in EGFR (p.L858R = 0.79; p.E746_A750del = 0.77) and KRAS (p.G12C = 0.77). Performance was suboptimal for KRAS p.G12V (0.41) and KRAS p.G12D (0.47). Conclusions: Our deep learning network achieves high prediction scores in identifying tumors with critical driver gene alterations and actionable mutations, holding promise for potential clinical use. In the future, the model could be optimized as a screening assay to guide molecular testing and therapeutic management of patients with LCINS. Citation Format: Monjoy Saha, Tongwu Zhang, Praphulla Bhawsar, Wei Zhao, Jianxin Shi, Soo Ryum Yang, Jonas Almeida, Maria Teresa Landi. Deep learning-based molecular characterization of lung cancers from never smokers using hematoxylin and eosin-stained whole slide images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB243.

Differential whole-genome doubling based signatures for improvement on clinical outcomes and drug response in patients with breast cancer

Whole genome doublings (WGD), a hallmark of human cancer, is pervasive in breast cancer patients. However, the molecular mechanism of the complete impact of WGD on survival and treatment response in breast cancer remains unclear. To address this, we performed a comprehensive and systematic analysis of WGD, aiming to identify distinct genetic alterations linked to WGD and highlight its improvement on clinical outcomes and treatment response for breast cancer. A linear regression model along with weighted gene co-expression network analysis (WGCNA) was applied on The Cancer Genome Atlas (TCGA) dataset to identify critical genes related to WGD. Further Cox regression models with random selection were used to optimize the most useful prognostic markers in the TCGA dataset. The clinical implication of the risk model was further assessed through prognostic impact evaluation, tumor stratification, functional analysis, genomic feature difference analysis, drug response analysis, and multiple independent datasets for validation. Our findings revealed a high aneuploidy burden, chromosomal instability (CIN), copy number variation (CNV), and mutation burden in breast tumors exhibiting WGD events. Moreover, 247 key genes associated with WGD were identified from the distinct genomic patterns in the TCGA dataset. A risk model consisting of 22 genes was optimized from the key genes. High-risk breast cancer patients were more prone to WGD and exhibited greater genomic diversity compared to low-risk patients. Some oncogenic signaling pathways were enriched in the high-risk group, while primary immune deficiency pathways were enriched in the low-risk group. We also identified a risk gene, ANLN (anillin), which displayed a strong positive correlation with two crucial WGD genes, KIF18A and CCNE2. Tumors with high expression of ANLN were more prone to WGD events and displayed worse clinical survival outcomes. Furthermore, the expression levels of these risk genes were significantly associated with the sensitivities of BRCA cell lines to multiple drugs, providing valuable insights for targeted therapies. These findings will be helpful for further improvement on clinical outcomes and contribution to drug development in breast cancer.

Abstract 4340: Profiling the evolutionary history of giant cancer cells in sarcomas: Hopeful monsters or an evolutionary dead end

Abstract Background: As tumors evolve, they accumulate somatic mutations that serve as an archeological record of their evolutionary past. Undifferentiated pleomorphic sarcomas (USARCs) are malignant soft tissue tumors that often contain scattered giant cancer cells, or potential ‘hopeful monster cells’, histologically. As USARCs frequently undergo whole genome doubling (WGD) and chromothripsis (Steele et al, 2019), both mutational events are likely to contribute to the formation of giant cancer cells, which frequently display atypical nuclear features such as polyploidy, micronuclei and extrachromosomal DNA. Giant cancer cells are also a common histological finding in other sarcoma types, such as dedifferentiated liposarcomas. Aims: This study aims to leverage single cell sequencing approaches to determine the evolutionary history and genomic landscape of giant cancer cells in sarcomas. Methods: 112 giant cancer cells identified in 8 USARCs, 1 dedifferentiated liposarcoma (DDLPS) and 1 myxofibrosarcoma by histology (i.e. nuclear size and shape, as well as multi-nucleation) were isolated via laser capture microdissection thereby retaining important spatial and morphological information. Once isolated, single cell DNA was extracted and amplified using the Ampli1 whole genome amplification (WGA) kit and underwent WGS. DNA was also estimated at a single cell level in one USARC using FACS. Once sorted into different ploidy populations, single nuclei also underwent WGS. Allele specific copy number aberrations (CNAs) were inferred in all single cells. Bulk tumour and normal WGS was also performed. Results: LCM isolated giant cancer cells exhibited extreme sub-clonal heterogeneity with some demonstrating de novo chromothripsis events that was not present in bulk WGS. FACS analysis and copy number inference of single cancer cells in one USARC also revealed the presence of three ploidy populations, including a haploid, a near diploid and a WGD population. Single cell WGS and copy number profiling demonstrated that following near genome scale haploidisation, multiple haploid cells underwent successive rounds of WGD. Conclusions: Chromothripsis and WGD emerges as major contributors to intra-tumor heterogeneity in sarcoma giant cancer cells. Single cell LCM and WGS revealed that some giant cancer cells contained de novo chromothripsis events that were not observed in bulk WGS. Multiple sub-clonal WGD events also permitted one USARC to continue to explore its fitness landscape contributing to ongoing tumor heterogeneity and lethality. Citation Format: Amy Bowes, Tom Lesluyes, Sara Waise, Annelien Verfaillie, Adrienne Flanagan, Jonas Demeulemeester, Maxime Tarabichi, Nischalan Pillay, Peter Van Loo. Profiling the evolutionary history of giant cancer cells in sarcomas: Hopeful monsters or an evolutionary dead end [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 4340.

Abstract 419: Evolutionary trajectories of complex genome rearrangements in osteosarcoma

Abstract Whole-genome sequencing (WGS) studies have revealed that osteosarcoma genomes are riddled by remarkably intricate forms of structural variants (SV), collectively known as complex genomic rearrangements (CGR). Yet, most CGR detected in osteosarcoma remain unexplained, hinting at the possibility of undiscovered mechanisms that might lead to novel therapeutic strategies. To elucidate the mechanisms underpinning cancer genome complexity in osteosarcomas and the downstream consequences of CGR during tumor evolution, we uniformly processed exiting osteosarcoma WGS data sets and performed high-depth (>120x) multi-regional short- and long-read WGS for hundreds of osteosarcomas. We found that whole genome doubling and diverse types of CGR are frequent clonal events in most osteosarcomas. Through the integration of multi-regional WGS data, we discovered that in tumors with whole-genome doubling, cancer genome evolution and oncogene amplification are the consequence of multi-generational CGR triggered by whole-genome doubling and involving multiple mechanisms, especially chromothripsis and breakage-fusion-bridge cycles. By contrast, in tumors without whole-genome doubling, biallelic inactivation of TP53 and oncogene amplification frequently occur as part of a cascade of genomic instability initiated by a single double-strand break upstream of the TP53 locus. This process results in clonal diversification and rapid tumor growth suggestive of punctuated evolution. In addition, we found that subclonal CGRs are also frequent events. Indeed, clonal expansions triggered by the acquisition of subclonal CGR often colonize distant tumor regions, suggesting that CGR act as subclonal driver events. Finally, we show that some recurrent genomic alterations are prognostic of poor survival, which we validate in independent cohorts. In sum, using WGS data, we have elucidated the mechanisms underpinning the complexity and evolution of osteosarcoma genomes. Our results indicate that diverse types of CGR, such as chromothripsis, are triggered by whole genome doubling and occur throughout tumor evolution, which primes the cancer genome for ongoing genomic instability, rapid karyotype evolution and clonal diversification. These results have implications for our understanding of the molecular basis of intra-tumor heterogeneity and drug resistance in osteosarcomas and other cancers driven by genomic instability. Citation Format: Isidro Cortes Ciriano, Jose Espejo Valle-Inclán, Solange de Noon, Katherine Trevers, Hillary Elrick, Adrienne M. Flanagan. Evolutionary trajectories of complex genome rearrangements in osteosarcoma [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 419.

Abstract 5211: Somatic copy number variation as prognostic marker for recurrence in never-smokers with early-stage lung adenocarcinoma

Abstract Objective: Lung cancer in never-smokers has a distinct genomic profile with low tumor mutation burden, more tumor promotor mutations and fewer somatic copy number variations (CNV) than smokers. CNVs have shown to be associated with poor outcome in advanced stage disease. However, the relationship between CNV and clinicopathologic features on prognosis in early-stage lung cancer is undefined. To address this knowledge gap, we assessed the impact of CNV on recurrence in never-smokers who underwent curative resection for pathological stage I-II lung adenocarcinoma using an integrated genomic and clinicopathological analysis. Methods: We analyzed a cohort of 210 never-smokers with stage I-II lung adenocarcinoma treated from 2014 to 2022 who met the inclusion criteria (no neoadjuvant therapy, pathological stage I-II, complete resection, next-generation sequencing available). The patient cohort was stratified using unsupervised hierarchical clustering of arm-level CNVs. We assessed cumulative incidence of recurrence (CIR) between CNV groups using competing risk regression analysis, adjusting for SUVmax, pathologic stage, lymphovascular invasion, IASLC grade, and tumor mutation burden. Results: Of the 210 patients, 159 patients were female (76%), and patients were primarily from Caucasian (n=140, 67%) or Asian decent (n=50, 24%). Based on arm-level CNV clustering, the cohort was stratified into three groups: CNV low (n=86, 41%), CNV moderate (n=75, 36%) and CNV high (n=49, 23%). The CNV low tumors were characterized by a low CNV burden. Conversely, the CNV moderate tumors primarily exhibited gains in chromosomes 1q, 5p and 7p, along with loss of heterozygosity in chromosome 9p, 9q and 13. CNV high tumors were characterized by whole-genome doubling. Whole-genome doubling was significantly more common in CNV high tumors (n=33, 66%) compared to CNV low (n=2, 2.3%) and CNV moderate tumors (n=2, 2.7%) (p<.001). EGFR (n=145, 69%) and TP53 (n=61, 29%) were the most frequently altered genes, with EGFR alterations being significantly more prevalent in CNV high tumors (n=41, 84%) compared to CNV low tumors (n=46, 53%) (p<.001). In total, 42 patients (20%) developed recurrences. The CIR was lower in the CNV low group (5y-CIR, 14%, 95%CI: 6.5%-25%) compared to the CNV moderate (5y-CIR, 31%, 95%CI: 18%-44%) and CNV high group (5y-CIR, 48%, 95%CI: 27%-66%) (p=.004), with adjusted hazard ratios of 2.3 (95%CI: 0.93-5.71; p=0.074) and 2.65 (95%CI: 1.07-6.60; p=.037), respectively. The CIR for locoregional (n=11, 5%) and distant recurrence (n=31, 15%) remained lower in the CNV low group compared to the combined CNV moderate & high groups (Gray test p=.020 and p=.049, respectively). Conclusion: In never-smokers who underwent curative treatment of pathological stage I-II lung adenocarcinoma, copy number status seems a predictor of recurrence, with CNV low tumors associated with the best prognosis. Citation Format: Stijn Vanstraelen, Allison Reiner, Brooke H. Mastrogiacomo, Kay See Tan, Joseph Dycoco, Bernard J. Park, Prasad S. Adusumilli, Matthew J. Bott, David R. Jones, Gaetano Rocco. Somatic copy number variation as prognostic marker for recurrence in never-smokers with early-stage lung adenocarcinoma [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 5211.

Abstract 4338: A pan-cancer single-cell analysis of intratumoral copy number diversity and evolution

Abstract Aneuploidy is a hallmark of human cancers and studies have shown that cancer patients harbor many differences in their copy number aberrations (CNAs) reflecting interpatient heterogeneity (IPH). While IPH has been studied extensively, the intratumoral heterogeneity (ITH) of CNAs within a tumor remains understudied. Here, we conducted a pan-cancer analysis of 94 human tumor samples at single cell genomic resolution, representing seven major cancer types: bladder, breast, colon, glioblastoma, kidney, lung, and ovary. In total, 62,646 aneuploid cells were analyzed by single cell copy number profiling and bulk exome sequencing was performed. In most cancer types, increased subclonal diversity was associated with higher CNA burden, whole genome doubling (WGD) events, and TP53 mutations. In all tumors, our data show that cancer cells share a clonal set of truncal CNAs or mutations, suggesting these tumors evolved from a single ancestral cell. In 18/94 cases we identified subclonal WGD events, which resulted in a higher number of copy number losses after tetraploidization. Macro-spatial sampling showed that increased clonal diversity also correlated with increased spatial geographical diversity. We found that many cancers evolved CNAs in short punctuated bursts of evolution, and that this was not restricted to a specific cancer type. Collectively, these data show that copy number ITH is universally associated with molecular features across these human cancer types. Citation Format: Hanghui Ye, Thomas McDonald, Emi Sei, Darlan Conterno Minussi, Min Hu, Chenling Tang, Junke Wang, Kaile Wang, Anna Casasent, Hui Chen, Franziska Michor, Nicholas Navin. A pan-cancer single-cell analysis of intratumoral copy number diversity and evolution [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 4338.

Abstract 910: Clinical inference and biological dissection of tumor ploidy and heterogeneity in cutaneous melanoma for immunotherapy response using deep learning

Abstract Background: Tumor ploidy and heterogeneity demonstrated to be pivotal in predicting immunotherapy response in cutaneous melanoma in several independent cohorts (Liu NatMed2019, Tarantino BioRXiv2022). Their estimation can guide more personalized and rational utilization of these immunotherapies. However, 1) the biology underpinning ploidy and heterogeneity is unknown; and 2) these findings were derived in patients using retrospective research tumor-normal paired whole exome sequencing which is not performed for clinical management. Methods: This study addresses this gap by employing deep learning models to predict these crucial markers using routinely available clinical assays, including H&E images. Attention-based computer vision models enable the identification of key morphological features in H&E slides. Segmentation of tumor tissue to perform automated masking, enhances ploidy inference.Moreover, biologically informed neural networks (P-Net, Elmarakeby Nature2021) uncover transcriptional and genomic features linked to ploidy and tumor heterogeneity. Our models are trained on publicly available data (e.g., Liu et al Nature Medicine 2019; TCGA SKCM) from melanoma cohorts and further validated in independent cohorts to ensure robustness. Results: We developed and validated automated tumor tissue masking, enabling the prediction of Whole Genome Doubling (WGD) from H&E Slides with an AUC > 0.75. Attention-based models identify distinct Tumor Microenvironment (TME) structures predictive of high tumor heterogeneity. P-Net application revealed the Calmodulin pathway, previously associated with regulating proliferation in cancer and targeted with chemotherapy, as intricately linked to high tumor heterogeneity, providing valuable insights into underlying mechanisms. Conclusion: In conclusion, our study strategically harnesses and integrates existing datasets to rigorously test, refine, and validate hypotheses concerning the biological and therapeutic implications of genomic heterogeneity and ploidy. Notably, our predictive models with automated tumor masking demonstrate a remarkable AUC >0.75 for biomarkers traditionally challenging to derive from clinical assays. This breakthrough opens avenues for novel therapeutic strategies targeting genomic heterogeneity and ploidy, providing a transformative potential to enhance patient care and outcomes. Citation Format: Marc Glettig, Giuseppe Tarantino, Tyler Aprati, Haitham Elmarakeby, David Liu. Clinical inference and biological dissection of tumor ploidy and heterogeneity in cutaneous melanoma for immunotherapy response using deep learning [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 910.

Abstract 5671: Profiling intra-tumor heterogeneity and chromosomal instability in malignant peripheral nerve sheath tumors

Abstract Malignant peripheral nerve sheath tumors (MPNSTs) are rare soft-tissue sarcomas that manifest on peripheral nerves, constituting 2% of all sarcomas. While previous genomic analyses of MPNSTs have been conducted on small cohorts, often limited to single samples per patient and lacking comprehensive resolution, the extent of intra-tumor heterogeneity and the contribution of chromosomal instability to MPNST development remains unclear. To address these limitations, we developed a multi-omics integration pipeline and applied it to bulk Whole Genome Sequencing (WGS), single-cell RNA sequencing(scRNA-seq), single-cell DNA sequencing (scDNA-seq), spatial transcriptomics (ST), and Laser Capture Microsection (LCM) sequencing data. 60 tumor samples were collected from 17 patients with MPNST, and the above five techniques were applied to each sample. Overall, tumors harbor a high degree of chromosomal instability and evidence of whole-genome doubling (WGD). We reconstructed tumor phylogenetic trees from WGS data using Dirichlet Process-based methods. Intriguingly, our findings indicated that for patient 2.3, primary tumor samples PT_1 and PT_2 displayed a close phylogenetic relationship, while local recurrences LR_2 and LR_3 represented a different branch of the phylogenetic tree. Moreover, scRNA-seq analysis of patient 2.16 highlighted an enrichment of immune cells, including macrophages, B cells, and T cells. To infer copy number alterations (CNA) of tumor cells from scRNA-seq data, we leveraged inferCNV, with normal cells identified within the same sample as controls. Significant copy number gains were identified on chromosomes 5, 7, 8, and 15 in patient 2.16. The inferred copy number changes derived from scRNA-seq were validated against copy number profiles obtained through WGS using Battenberg, revealing a remarkable congruence. In the scDNA analysis of patient 2.12, we observed that all tumor cells exhibited biallelic loss of CDKN2A, with a majority showcasing WGD and chromosome 7 amplification. This finding underscored the potential significance of CDKN2A in the pathogenesis of this tumor, in keeping with the observation that CDKN2A is recurrently mutated and lost in MPNSTs. Our research profiled the tumors' evolutionary histories and intra-tumor heterogeneity down to single-cell resolution, highlighting the genotype and phenotype differences between tumor subclones. By shedding light on the genomic landscape of MPNSTs, we aspire to make profound contributions to the field of sarcoma research, ultimately improving patient outcomes. Citation Format: Yixiao Cheng, Haixi Yan, Maxime Tarabichi, Zhihui Zhang, Chunxu Gao, Tom Lesluyes, Adrienne Flanagan, Peter Van Loo. Profiling intra-tumor heterogeneity and chromosomal instability in malignant peripheral nerve sheath tumors [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 5671.

Novel molecular subtypes of intracranial germ cell tumors expand therapeutic opportunities.

Intracranial germ cell tumors (IGCTs) are a rare group of malignancies that are clinically classified as germinomas and nongerminomatous germ cell tumors (NGGCTs). Previous studies have found that somatic mutations involving the mitogen-activated protein kinase/mTOR signaling pathway are common early events. However, a comprehensive genomic understanding of IGCTs is still lacking. We established a cohort including over 100 IGCTs and conducted genomic and transcriptomic sequencing. We identified novel recurrent driver genomic aberrations, including USP28 truncation mutations and high-level copy number amplification of KRAS and CRKL caused by replication of extrachromosomal DNA. Three distinct subtypes associated with unique genomic and clinical profiles were identified with transcriptome analysis: Immune-hot, MYC/E2F, and SHH. Both immune-hot and MYC/E2F were predominantly identified in germinomas and shared similar mutations involving the RAS/MAPK signaling pathway. However, the immune-hot group showed an older disease onset age and a significant immune response. MYC/E2F was characterized by a younger disease onset age and increased genomic instability, with a higher proportion of tumors showing whole-genome doubling. Additionally, the SHH subtype was mostly identified in NGGCTs. Novel genomic aberrations and molecular subtypes were identified in IGCTs. These findings provide molecular basis for the potential introduction of new treatment strategies in this setting.

Whole-genome doubling is a double-edged sword: the heterogeneous role of whole-genome doubling in various cancer types

Whole-genome doubling is a double-edged sword: the heterogeneous role of whole-genome doubling in various cancer types

Abstract B053: The role of whole genome doubling in immune escape in TNBC

Abstract Triple-negative breast cancers (TNBC) account for 10-15% of all breast cancers. The combination of chemotherapy and immune checkpoint inhibitor (ICI) therapy is now a standard in stage II-III TNBC while this regimen is used only in a subset of advanced TNBC tumors with high expression of PD-L1. Whole exome sequencing of solid tumors (other than breast cancer) in clinical trials investigating ICI determined that tumors which undergone a WGD (whole genome doubling) are more sensitive to immune checkpoints inhibitors, but the underlying mechanisms have not been defined. WGD occurs in 44% of breast cancers and it has been associated with advanced stage, poor survival, and higher risk of resistance to chemotherapies and targeted therapies. However, its role in response to ICI treatment in TNBC has not been investigated. To investigate the functional relevance of WGD in therapeutic responses in TNBC, we generated isogenic cell line pairs (3 murine and 1 human) that are diploid/euploid (WGD-) or tetraploid (WGD+) using somatic cell fusion. To explore the impact of WGD on tumor growth, we injected parental (WGD-) and fusion (WGD+) cells into mammary fat pads of syngeneic immunocompetent or immunocompromised (NSG) mice. We found that while there was no difference in growth between parental (WGD-) and fusion (WGD+) cells in immune deficient mice, in immunocompetent mice tumors derived from fusion (WGD+) cells grew significantly faster compared to parental (WGD-). We have been analyzing differences between parantel and fusion cell-derived tumos using FACS, immunofluorescence, and single cell RNA-seq (scRNA-seq) and found significant immune-related differences implying a more immune suppressive environment in fusion tumors. These data suggest that WGD in TNBC may be a predictor of response to ICI therapies. Citation Format: Pierre Foidart, Zheqi Li, Marco Seehawer, Jun Nishida, Ernesto Rojas, Triet Bui, Pengze Yan, Marie-Anne Goyette, Laura Stevens, Xiao-Yun Huang, Jayati Anand, Gouri Nanjangud, Yingtian Xie, Xintao Qiu, Paloma Cejas, Henry Long, Kornelia Polyak. The role of whole genome doubling in immune escape in TNBC [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B053.

Abstract PR012: Evolutionary dynamics of whole-genome doubling in ovarian cancer

Abstract Chromosomal instability (CIN) is a major driver of tumor progression and treatment resistance in many cancers. CIN is characterized by ongoing chromosome missegregation, segmental aneuploidy and whole-genome doubling (WGD), generating copy number heterogeneity that provides a substrate for natural selection. Although well characterized in model systems, the evolutionary dynamics and genomic impact of WGD is underexplored in primary tumors and metastases. Newly developed single-cell genomics assays now allow for the measurement of the whole genomes of single cells obtained from patient tissues, thus providing a direct view into the evolution of tumor genomes undergoing WGD. We performed multi-region single-cell whole genome sequencing (scWGS) in a cohort of patients with high-grade serous ovarian cancer (HGSOC), an archetype of high CIN cancers. We profiled a total of 70,644 single cells from 63 pre-treatment samples obtained for 36 HGSOC patients. For each patient, we computed total and allele-specific copy number per cell, and inferred the evolutionary history of each patient’s tumor, including clonal and subclonal WGD events and cell-specific whole-chromosome or arm-level copy number changes indicative of missegregations. To determine the role of CIN-associated micronuclei (MN) formation, we used high-resolution cGAS immunofluorescence (IF) microscopy to profile FFPE tissues site-matched to scWGS, and quantify spatially-resolved rates of MN formation and rupture across 120 samples. A majority of tumors were characterized by early clonal WGD (61%, 22/36 cases). The remaining patients exhibited subclonal WGD subpopulations averaging 10% of cancer cells in total. To understand the interplay between recent WGD and CIN across the cohort, we subset all patients cells into non-WGD, subclonal WGD, and clonal WGD and computed mis-segregation rates for these subsets. Non-WGD cells showed the lowest levels of mis-segregation. Subclonal WGD exhibited the highest CIN rates, including mis-segregation and multipolar cells indicative of CIN following a recent WGD event. Clonal WGD exhibited intermediate levels of mis-segregation indicative of stabilization following a historical WGD event. CIN following WGD often resulted in a reduction in ploidy relative to the ancestral WGD cell. Micronucleus rupture was ubiquitously detected in IF across HGSOC tumors, and MN rates varied widely between patients and across primary and metastatic sites. Micronucleus rupture commonly resulted from the impact of WGD, which increased sequestration of missegregated chromosomes into MN. Through multimodal single cell measurements of HGSOC tumors, we were able to characterize genomic complexity from individual cell division errors in HGSOC, and shed light into how the transient processes governing ovarian cancer cell evolution impact the genomes of cell populations. Citation Format: Ignacio Vázquez-García, Matthew Myers, Marc J. Williams, Samuel S. Freeman, Jun Li, Hongyu Shi, Gryte Satas, Nicholas Ceglia, Florian Uhlitz, MSK SPECTRUM Consortium, Britta Weigelt, Dmitriy Zamarin, Andrew McPherson, Samuel F. Bakhoum, Sohrab P. Shah. Evolutionary dynamics of whole-genome doubling in ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR012.