Aneuploidy Patterns Research Articles

Genomic Determinants of Outcome in Acute Lymphoblastic Leukemia.

Although cure rates for childhood acute lymphoblastic leukemia (ALL) exceed 90%, ALL remains a leading cause of cancer death in children. Half of relapses arise in children initially classified with standard-risk (SR) disease. To identify genomic determinants of relapse in children with SR ALL, we performed genome and transcriptome sequencing of diagnostic and remission samples of children with SR (n = 1,381) or high-risk B-ALL with favorable cytogenetic features (n = 115) enrolled on Children's Oncology Group trials. We used a case-control study design analyzing 439 patients who relapsed and 1,057 who remained in complete remission for at least 5 years. Genomic subtype was associated with relapse, which occurred in approximately 50% of cases of PAX5-altered ALL (odds ratio [OR], 3.31 [95% CI, 2.17 to 5.03]; P = 3.18 × 10-8). Within high-hyperdiploid ALL, gain of chromosome 10 with disomy of chromosome 7 was associated with favorable outcome (OR, 0.27 [95% CI, 0.17 to 0.42]; P = 8.02 × 10-10; St Jude Children's Research Hospital validation cohort: OR, 0.22 [95% CI, 0.05 to 0.80]; P = .009), and disomy of chromosomes 10 and 17 with gain of chromosome 6 was associated with relapse (OR, 7.16 [95% CI, 2.63 to 21.51]; P = 2.19 × 10-5; validation cohort: OR, 21.32 [95% CI, 3.62 to 119.30]; P = .0004). Genomic alterations were associated with relapse in a subtype-dependent manner, including alterations of INO80 in ETV6::RUNX1 ALL, IKZF1, and CREBBP in high-hyperdiploid ALL and FHIT in BCR::ABL1-like ALL. Genomic alterations were also associated with the presence of minimal residual disease, including NRAS and CREBBP in high-hyperdiploid ALL. Genetic subtype, patterns of aneuploidy, and secondary genomic alterations determine risk of relapse in childhood ALL. Comprehensive genomic analysis is required for optimal risk stratification.

Patterns of Aneuploidy and Signaling Consequences in Cancer.

Aneuploidy, or a change in the number of whole chromosomes or chromosome arms, is a near-universal feature of cancer. Chromosomes affected by aneuploidy are not random, with observed cancer-specific and tissue-specific patterns. Recent advances in genome engineering methods have allowed the creation of models with targeted aneuploidy events. These models can be used to uncover the downstream effects of individual aneuploidies on cancer phenotypes including proliferation, apoptosis, metabolism, and immune signaling. Here, we review the current state of research into the patterns of aneuploidy in cancer and their impact on signaling pathways and biological processes.

Machine-learning analysis reveals an important role for negative selection in shaping cancer aneuploidy landscapes

BackgroundAneuploidy, an abnormal number of chromosomes within a cell, is a hallmark of cancer. Patterns of aneuploidy differ across cancers, yet are similar in cancers affecting closely related tissues. The selection pressures underlying aneuploidy patterns are not fully understood, hindering our understanding of cancer development and progression.ResultsHere, we apply interpretable machine learning methods to study tissue-selective aneuploidy patterns. We define 20 types of features corresponding to genomic attributes of chromosome-arms, normal tissues, primary tumors, and cancer cell lines (CCLs), and use them to model gains and losses of chromosome arms in 24 cancer types. To reveal the factors that shape the tissue-specific cancer aneuploidy landscapes, we interpret the machine learning models by estimating the relative contribution of each feature to the models. While confirming known drivers of positive selection, our quantitative analysis highlights the importance of negative selection for shaping aneuploidy landscapes. This is exemplified by tumor suppressor gene density being a better predictor of gain patterns than oncogene density, and vice versa for loss patterns. We also identify the importance of tissue-selective features and demonstrate them experimentally, revealing KLF5 as an important driver for chr13q gain in colon cancer. Further supporting an important role for negative selection in shaping the aneuploidy landscapes, we find compensation by paralogs to be among the top predictors of chromosome arm loss prevalence and demonstrate this relationship for one paralog interaction. Similar factors shape aneuploidy patterns in human CCLs, demonstrating their relevance for aneuploidy research.ConclusionsOur quantitative, interpretable machine learning models improve the understanding of the genomic properties that shape cancer aneuploidy landscapes.

Human Papillomavirus-Induced Chromosomal Instability and Aneuploidy in Squamous Cell Cancers.

Chromosomal instability (CIN) and aneuploidy are hallmarks of cancer. CIN is defined as a continuous rate of chromosome missegregation events over the course of multiple cell divisions. CIN causes aneuploidy, a state of abnormal chromosome content differing from a multiple of the haploid. Human papillomavirus (HPV) is a well-known cause of squamous cancers of the oropharynx, cervix, and anus. The HPV E6 and E7 oncogenes have well-known roles in carcinogenesis, but additional genomic events, such as CIN and aneuploidy, are often required for tumor formation. HPV+ squamous cancers have an increased frequency of specific types of CIN, including polar chromosomes. CIN leads to chromosome gains and losses (aneuploidies) specific to HPV+ cancers, which are distinct from HPV- cancers. HPV-specific CIN and aneuploidy may have implications for prognosis and therapeutic response and may provide insight into novel therapeutic vulnerabilities. Here, we review HPV-specific types of CIN and patterns of aneuploidy in squamous cancers, as well as how this impacts patient prognosis and treatment.

Abstract 5665: Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine osteosarcoma

Abstract Osteosarcoma (OS) is an aggressive bone malignancy affecting children and young adults. Implementation and optimization of neoadjuvant chemotherapy led to significant improvements in outcome, but patients with recurrence or metastases at diagnosis continue to have poor prognosis. Whole genome sequencing (WGS) revealed that a hallmark of OS is a highly rearranged genome with complex copy number aberrations rather than point mutations. A better understanding of the key genomic and epigenetic factors driving clonal evolution may provide insights into the tumor progression and the therapy response. Canine OS recapitulates the majority of the hallmark genetic and molecular factors of human OS and is recognized as an informative model. A significant difference is that initial surgery in canine OS allows us to explore tumor evolution unperturbed by treatment, providing invaluable resources to study the genetic and molecular landscape of tumor evolution. Here, we present the first study to date in which we performed bulk WGS of multiple tumor sites and distal normal tissue in two dogs using nanopore long-read sequencing to analyze the genetic and epigenetic evolution of OS. In both subjects, somatic structural variation detection using Severus revealed chromothripsis-like rearrangements in chr11, leading to the deletion of Cdkn2a, a known cell cycle regulator and tumor suppressor. Interestingly, in one of the subjects, the majority of the SVs (n = 131) shared across all the samples were localized on chr5, coinciding with perturbed copy number profiles and bi-allelic frequency of the SNVs, with all mutations identified using complementary bioinformatics analysis of the same native nanopore reads. The multi-site sample analysis identified subclonal structural alterations in TP53 and ATRX genes. With phased nanopore reads, we observed subject-specific copy-neutral loss-of-heterozygosity events and long identical-by-descent blocks. Haplotype-specific copy-number analysis of tumors showed different aneuploidy patterns in both subjects, highlighted clonal compositions of samples from distinct sites, and identified regions of copy-number heterogeneity. Furthermore, phased nanopore reads also revealed haplotype-specific 5mC and 5hmC methylation differences across tumor samples, where samples from different sites of the same tumor demonstrate distinct methylation patterns that overlap DLG2, RUNX2, KDR, and other genes known as mutational hotspots in canine/human OS. Overall, we showcase how a single sequencing assay allows for a joint analysis of genetic and epigenetic tumor alterations, thus providing a richer understanding of the drivers of somatic evolution and their association with the molecular landscape in the canine OS. These findings can be translated into human disease and shed light on tumor progression and therapy response. Citation Format: Ayse Keskus, Sergey Aganezov, Tanveer Ahmad, Xiaoguang Dai, Robert Walker, John Beaulaurier, Scott Hickey, Sissel Juul, Amy Kathleen LeBlanc, Paul S. Meltzer, Mikhail Kolmogorov. Native nanopore sequencing of multiple tumor sites reveals genetic and epigenetic intra-tumor heterogeneity in canine 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 5665.

Abstract 409: Deciphering chromosomal instability in consensus molecular subtypes (CMS) in CRC: Insights from an integrative multi-omics approach

Abstract CRC is a heterogeneous disease with different molecular subtypes, which can have a profound impact on treatment response and patient outcomes. CMS classification based on gene expression profiles has been shown to differentiate patients into clinically relevant sub-groups. However, deep multi-omics characterization of the CMS classes based on high quality patient data is lacking. Through the integration of multi-omics data, we aim to enhance our understanding of CRC’s molecular heterogeneity and thereby facilitate the development of personalized therapeutic strategies. We performed a multi-omics analysis of CRC patients to identify potential new features of CMS groups. 890 fresh-frozen, surgically resected CRC tumor and adjacent normal samples were used to analyze whole genome and RNA sequencing data. DNA and RNA was prepared using Qiagen AllPrep Universal and KAPA Hyper Prep kit (DNA), as well as TruSeq Stranded Total mRNA kits and sequenced on a NovaSeq6000 system. We identified CMS subtypes based on RNA-Seq data and performed all statistical analyses using R. Our analysis revealed distinct molecular characteristics across the four CMS subtypes, including unique driver mutations, signaling cascades, and immune cell infiltration profiles. The poor prognosis associated with CMS4 patients was corroborated by our clinical data. Notably, we observed high global chromosomal instability (CIN) profiles for both CMS2 and CMS4 and identified recurrent global aneuploidy patterns within these subtypes that link alterations of known cancer genes to these large-scale structural events. We found higher levels of CIN in CMS2 compared to CMS4, which appears to be predominantly driven by numerical, rather than structural CIN. Specifically, in CMS2, SMAD2/4 is commonly impacted by deletion on chromosome arm 18q, while PLCG1 is more influenced by amplifications on 20q respectively, suggesting potential values as CRC CMS biomarkers. In conclusion, our integrative multi-omics analysis offers a comprehensive understanding of CRC molecular subtypes, which can inform personalized treatment strategies. Our findings underscore the importance of considering not only specific driver mutations but also large-scale structural rearrangements in the context of CMS subtypes. Citation Format: Julia Bischof, Jonathan Woodsmith, David Church. Deciphering chromosomal instability in consensus molecular subtypes (CMS) in CRC: Insights from an integrative multi-omics approach [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 409.

Chromosome evolution screens recapitulate tissue-specific tumor aneuploidy patterns.

Whole chromosome and arm-level copy number alterations occur at high frequencies in tumors, but their selective advantages, if any, are poorly understood. Here, utilizing unbiased whole chromosome genetic screens combined with in vitro evolution to generate arm- and subarm-level events, we iteratively selected the fittest karyotypes from aneuploidized human renal and mammary epithelial cells. Proliferation-based karyotype selection in these epithelial lines modeled tissue-specific tumor aneuploidy patterns in patient cohorts in the absence of driver mutations. Hi-C-based translocation mapping revealed that arm-level events usually emerged in multiples of two via centromeric translocations and occurred more frequently in tetraploids than diploids, contributing to the increased diversity in evolving tetraploid populations. Isogenic clonal lineages enabled elucidation of pro-tumorigenic mechanisms associated with common copy number alterations, revealing Notch signaling potentiation as a driver of 1q gain in breast cancer. We propose that intrinsic, tissue-specific proliferative effects underlie tumor copy number patterns in cancer.

Aneuploidy Landscape in Precursors of Ovarian Cancer.

Serous tubal intraepithelial carcinoma (STIC) is now recognized as the main precursor of ovarian high-grade serous carcinoma (HGSC). Other potential tubal lesions include p53 signatures and tubal intraepithelial lesions. We aimed to investigate the extent and pattern of aneuploidy in these epithelial lesions and HGSC to define the features that characterize stages of tumor initiation and progression. We applied RealSeqS to compare genome-wide aneuploidy patterns among the precursors, HGSC (cases, n = 85), and histologically unremarkable fallopian tube epithelium (HU-FTE; control, n = 65). On the basis of a discovery set (n = 67), we developed an aneuploidy-based algorithm, REAL-FAST (Repetitive Element AneupLoidy Sequencing Fallopian Tube Aneuploidy in STIC), to correlate the molecular data with pathology diagnoses. We validated the result in an independent validation set (n = 83) to determine its performance. We correlated the molecularly defined precursor subgroups with proliferative activity and histology. We found that nearly all p53 signatures lost the entire Chr17, offering a "two-hit" mechanism involving both TP53 and BRCA1 in BRCA1 germline mutation carriers. Proliferatively active STICs harbor gains of 19q12 (CCNE1), 19q13.2, 8q24 (MYC), or 8q arm, whereas proliferatively dormant STICs show 22q loss. REAL-FAST classified HU-FTE and STICs into 5 clusters and identified a STIC subgroup harboring unique aneuploidy that is associated with increased proliferation and discohesive growth. On the basis of a validation set, REAL-FAST showed 95.8% sensitivity and 97.1% specificity in detecting STIC/HGSC. Morphologically similar STICs are molecularly distinct. The REAL-FAST assay identifies a potentially "aggressive" STIC subgroup harboring unique DNA aneuploidy that is associated with increased cellular proliferation and discohesive growth. REAL-FAST offers a highly reproducible adjunct technique to assist the diagnosis of STIC lesions.

Genomic determinants of outcome in acute lymphoblastic leukemia: A Children’s Oncology Group study.

10015 Background: While cure rates for childhood acute lymphoblastic leukemia (ALL) exceed 90%, half of relapses arise in those originally classified with standard risk (SR) disease. Methods: We performed genome/transcriptome sequencing of diagnostic and germline samples of children with SR (n=1381) B-ALL or high-risk (HR) B-ALL with favorable cytogenetics ( ETV6: RUNX1 or double trisomy (DT) of chromosomes (chr) 4+10; n=115) to identify predictors of relapse. We used a case-control study to analyze 439 patients who relapsed and 1057 who remained in complete remission for > 5 years. Results: Genomic subtype was associated with relapse. Unbalanced ETV6:RUNX1 translocations were more common than balanced in relapse patients (OR=2.01, CI=1.25-3.20, P=0.002). Conversely, balanced TCF3:PBX1 translocations were more often associated with relapse than unbalanced in TCF3:PBX1 ALL (OR=0.11, CI=0.01-0.50, P=0.003). A striking finding was the high relapse rate in PAX5 altered ALL (57 of 116 cases (49%); OR=3.29, CI=2.16-5.01, P=3.49x10-8). The nature of the heterogeneous PAX5 driver alterations of this subtype influenced relapse risk, with internal PAX5 amplifications and biallelic PAX5 alterations associated with the highest risk. Specific chr gains influenced outcome in hyperdiploid ALL, with gain of chr 10 and disomy of chr 7 associated with favorable outcome (OR=0.27, CI=0.17-0.42, P=8.02x10-10, St Jude Children’s Research Hospital (SJCRH) validation cohort: OR=0.22, CI=0.05-0.80, P=0.009), while disomy of chr 10 and 17 and gain of chr 6 were enriched in patients that relapsed (OR=7.16, CI=2.63-21.51, P=2.19x10-5; SJCRH cohort: OR=21.32, CI=3.62-119.30, P=0.0004). Genomic alterations were also associated with relapse in a subtype-dependent manner, including alterations of INO80 in ETV6:RUNX1, IKZF1 and CREBBP in hyperdiploid, and FHIT in Ph-like ALL. Conclusions: Genetic subtype, aneuploidy patterns, and secondary genomic alterations influence risk of relapse in children otherwise classified with SR ALL, or HR ALL with favorable genetics. Comprehensive genomic analysis is required for optimal risk stratification and treatment allocation, and particularly to study reduction of therapy in the lowest risk patients. [Table: see text]

A kinesin‐based approach for inducing chromosome‐specific mis‐segregation in human cells

Various cancer types exhibit characteristic and recurrent aneuploidy patterns. The origins of these cancer type‐specific karyotypes are still unknown, partly because introducing or eliminating specific chromosomes in human cells still poses a challenge. Here, we describe a novel strategy to induce mis‐segregation of specific chromosomes in different human cell types. We employed Tet repressor or nuclease‐dead Cas9 to link a microtubule minus‐end‐directed kinesin (Kinesin14VIb) from Physcomitrella patens to integrated Tet operon repeats and chromosome‐specific endogenous repeats, respectively. By live‐ and fixed‐cell imaging, we observed poleward movement of the targeted loci during (pro)metaphase. Kinesin14VIb‐mediated pulling forces on the targeted chromosome were counteracted by forces from kinetochore‐attached microtubules. This tug‐of‐war resulted in chromosome‐specific segregation errors during anaphase and revealed that spindle forces can heavily stretch chromosomal arms. By single‐cell whole‐genome sequencing, we established that kinesin‐induced targeted mis‐segregations predominantly result in chromosomal arm aneuploidies after a single cell division. Our kinesin‐based strategy opens the possibility to investigate the immediate cellular responses to specific aneuploidies in different cell types; an important step toward understanding how tissue‐specific aneuploidy patterns evolve.

Abstract 109: Multi-modal single-cell analysis of immunotherapy-experienced cutaneous and mucosal melanoma

Abstract Immune checkpoint blockade (ICB) targeting CTLA-4 or the PD1/PD-L1 axis have become a standard of care therapy for most patients with metastatic melanoma. However, for patients with resistance to front-line ICB, especially those with BRAFWT tumors who received combination therapy, subsequent therapeutic options remain limited. Thus, understanding how ICB alters the tumor ecosystem, and thereby may create new vulnerabilities, is key to understanding effective therapies for ICB-experienced patients. Here, enabled through innovations in biospecimen research, we performed multi-modal single-cell RNA, T-cell receptor and single-cell spatial transcriptomics, coupled with whole-genome sequencing (WGS) of 42 melanoma patient biopsies. This cohort includes 7 patients with paired before- and on-/post-treatment biopsies, and spanned treatment-naïve metastatic cutaneous melanoma patients (n=10), on-ICB (aPD-1, n=7; aCTLA-4, n=1; combination therapy, n=2; total, n=10), and post-ICB (aPD-1, n=10; aCTLA-4, n=5; combination therapy, n=6; L19IL2+L16TNF, n=1; total, n=22). This cohort further includes 6 rare samples of mucosal melanoma (oral, n=4; rectal, n=2). In total, we profiled >320,000 transcriptomes, including >240,000 malignant and ~80,000 non-malignant cells, and 14,714 matched TCRs. We used a series of novel analytical approaches, including KINOMO to mitigate biases introduced by differences in gene dosage, and novel artificial intelligence frameworks, to discover differentially expressed genes and gene programs associated with treatment exposures and treatment sites. Compared to untreated specimens, there is an increase in antigen presentation (Wilcoxon rank-sum test, P=0) and reduction in lineage expression (Wilcoxon rank-sum test, P=0) in ICB-experienced tumors. Furthermore, mucosal melanomas harbor unique gene regulatory networks characterized by expression of immune evasive programs (e.g. SOX4; MAST, P=0) and exhibit lower expression of oxidative phosphorylation (Wilcoxon rank-sum test, P=0). Together, these data indicate a high degree of cellular adaption and plasticity. Through integration of single-cell, spatial and WGS, we further identify cancer clones defined by their aneuploidy patterns that confer geographically restricted immune evasion with a distinctly cold tumor microenvironment (TME), despite global T cell activation and clonal expansion. This suggest significant intralesional heterogeneity with respect to response to ICB, which may be explained by cancer cell-intrinsic factors rather than insufficient T cell responses to ICB. This work provides initial insights into spatio-temporal changes induced by ICB in cancer cells and the TME in a relatively large patient cohort. Our results indicate that functional and spatial variability exists in these tumors and may provide avenues for novel therapeutic development in ICB-experienced patients. Citation Format: Jana Biermann, Yiping Wang, Linyue Fan, Patricia Ho, Amit D. Amin, Johannes C. Melms, Somnath Tagore, Kevin Hoffer-Hawlik, Parin Shah, Neha Shaikh, Priyanka Ramaradj, Mingxuan Zhang, Antoni Ribas, Caroline Robert, Elham Azizi, Benjamin Izar. Multi-modal single-cell analysis of immunotherapy-experienced cutaneous and mucosal melanoma [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 109.

Abstract 1414: The role of chromosome arm 3p and human papillomavirus on proliferation, differentiation, and metastasis in squamous cancers

Abstract Squamous Cell Carcinoma (SCC) is an aggressive form of cancer that develops in the mucosal epithelium of the digestive and respiratory tracts as well as on the skin. Two major risk factors for development of SCC are carcinogen exposures, such as alcohol and tobacco, and Human Papillomavirus (HPV) infection. Viral- and carcinogen-driven SCCs have differential responses to radiation, chemotherapy, and immunotherapy, with HPV+ SCCs responding better to these treatments than HPV- carcinomas. Analysis of aneuploidy patterns of genomic samples from The Cancer Genome Atlas (TCGA) have shown that squamous cancers cluster together and are characterized by gain of chromosome arm 3q gain and loss of chromosome arm 3p. However, while HPV+ SCCs show similar rates of 3q gain, they have significantly lower rates of 3p loss, suggesting that 3p deletion and HPV infection might have overlapping roles in cancer initiation and/or progression. In addition, the degree to which these two paths of tumor development contribute to differences in disease progression and outcome has been largely unexplored. We have identified a strong correlation between 3p deletion and high epithelial-mesenchymal transition (EMT) gene signature across all cancer types. Interestingly, interferon signaling has been found to be upregulated in non-squamous cancers upon 3p deletion but downregulated in squamous cancers with 3p deletion. SCCs positive for HPV infection show decreased expression of EMT genes and increased expression of genes in interferon signaling and cell cycle checkpoint pathways. Together, the results of these TCGA analyses suggest mechanisms by which chromosome 3p deletion and HPV infection may affect cancer progression and are currently being validated in vitro in a panel of squamous cancer cell lines. Additionally, we will use a targeted CRISPR-Cas9 system developed in our lab to delete chromosome 3p, as well as transfect HPV oncoproteins, in normal keratinocytes to create isogenic models. With these models, we will study the role of individual aneuploidy events in tumorigenesis, tumor development, and metastasis in the context of HPV positive and negative SCC. Citation Format: Samyukta Mallick, Alison M. Taylor. The role of chromosome arm 3p and human papillomavirus on proliferation, differentiation, and metastasis in squamous 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 1414.

Adaptation to spindle assembly checkpoint inhibition through the selection of specific aneuploidies.

Both the presence of an abnormal complement of chromosomes (aneuploidy) and an increased frequency of chromosome missegregation (chromosomal instability) are hallmarks of cancer. Analyses of cancer genome data have identified certain aneuploidy patterns in tumors; however, the bases behind their selection are largely unexplored. By establishing time-resolved long-term adaptation protocols, we found that human cells adapt to persistent spindle assembly checkpoint (SAC) inhibition by acquiring specific chromosome arm gains and losses. Independently adapted populations converge on complex karyotypes, which over time are refined to contain ever smaller chromosomal changes. Of note, the frequencies of chromosome arm gains in adapted cells correlate with those detected in cancers, suggesting that our cellular adaptation approach recapitulates selective traits that dictate the selection of aneuploidies frequently observed across many cancer types. We further engineered specific aneuploidies to determine the genetic basis behind the observed karyotype patterns. These experiments demonstrated that the adapted and engineered aneuploid cell lines limit CIN by extending mitotic duration. Heterozygous deletions of key SAC and APC/C genes recapitulated the rescue phenotypes of the monosomic chromosomes. We conclude that aneuploidy-induced gene dosage imbalances of individual mitotic regulators are sufficient for altering mitotic timing to reduce CIN.

Chromosome Inequality: Causes and Consequences of Non-Random Segregation Errors in Mitosis and Meiosis.

Aneuploidy is a hallmark of cancer and a major cause of miscarriages in humans. It is caused by chromosome segregation errors during cell divisions. Evidence is mounting that the probability of specific chromosomes undergoing a segregation error is non-random. In other words, some chromosomes have a higher chance of contributing to aneuploid karyotypes than others. This could have important implications for the origins of recurrent aneuploidy patterns in cancer and developing embryos. Here, we review recent progress in understanding the prevalence and causes of non-random chromosome segregation errors in mammalian mitosis and meiosis. We evaluate its potential impact on cancer and human reproduction and discuss possible research avenues.

HMMploidy: inference of ploidy levels from short-read sequencing data

The inference of ploidy levels from genomic data is important to understand molecular mechanisms underpinning genome evolution. However, current methods based on allele frequency and sequencing depth variation do not have power to infer ploidy levels at low- and mid-depth sequencing data, as they do not account for data uncertainty. Here we introduce HMMploidy, a novel tool that leverages the information from multiple samples and combines the information from sequencing depth and genotype likelihoods. We demonstrate that HMMploidy outperforms existing methods in most tested scenarios, especially at low-depth with large sample size. We apply HMMploidy to sequencing data from the pathogenic fungus Cryptococcus neoformans and retrieve pervasive patterns of aneuploidy, even when artificially downsampling the sequencing data. We envisage that HMMploidy will have wide applicability to low-depth sequencing data from polyploid and aneuploid species.

Abstract PR006: Multi-modal single-cell profiling of sarcomas from archival tissue reveals mechanisms of resistance to immune checkpoint inhibitors

Abstract Single-cell genomics is an enabling technology that may inform the molecular underpinnings of drug response and resistance in patient biopsies. These methods are difficult to implement in the study of rare diseases such as sarcomas due to specimen requirements and technical limitations. Here, we evolved novel methods that we recently reported in melanoma (Wang, Fan, et al., bioRxiv, 2022) which enable single-nucleus RNA, T cell receptor (snRNA/TCR-seq), and pool-matched whole-genome sequencing (WGS) from archival frozen sarcoma tissue. This enabled profiling of 75,716 cells and 788 matched TCR clonotypes from six patients with intimal sarcoma (INS) and undifferentiated pleomorphic sarcoma (UPS), including two matched pair samples from pre/post-immune checkpoint inhibitor (ICI). Our analysis revealed substantial transcriptional cancer cell heterogeneity driven by varying copy number alterations (CNAs). In one patient with INS with a complete response to ICI followed by an isolated recurrence, we identified a rare cancer cell clone defined by CNA (confirmed with WGS) and resulting transcriptional outputs that pre-existed and emerged during resistance. Furthermore, in a UPS patient with intrinsic resistance to ICI, we find adequate T cell clonal expansion, activation, and differentiation, suggesting appropriate T cell response to ICI dampened by intrinsic mechanisms of ICI resistance within the cancer cells. Non-negative matrix factorization (NMF) analysis identified cell states associated with either intrinsic or adaptive resistance to ICI that was distinct from resistance to doxorubicin. These observations are consistent with those previously reported from sequential biopsies obtained from KEYNOTE-001 in metastatic melanoma (Wang, Fan, et al., bioRxiv, 2022), which also revealed emergence of pre-existing populations of resistant clones defined by their underlying aneuploidy patterns. Together, these results demonstrate feasibility of implementing single-cell genomics from archival tissue to study sarcoma and propel our understanding of drug resistance. Conceptually, this work suggests that large-scale CNAs may allow us to identify cell sub-populations associated with ICI resistance in sarcoma and in other diseases. Citation Format: Sminu Bose, Blake Caldwell, Amit Dipak Amin, Johannes Melms, Somnath Tagore, Matthew Ingham, Benjamin Izar, Gary K. Schwartz. Multi-modal single-cell profiling of sarcomas from archival tissue reveals mechanisms of resistance to immune checkpoint inhibitors [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr PR006.

BSCI-23 ANEUPLOIDY PROFILING IN GLIOBLASTOMA IDENTIFIES MECHANISMS OF DISEASE PROGRESSION AND TREATMENT VULNERABILITIES

Glioblastoma (GBM) is the most common and malignant adult brain tumor. Despite years of research, few advancements have been made in its management. One challenging area of glioblastoma research is patient stratification in clinical trials based on genomic features. Although several regions of aneuploidy have been known to drive disease progression in GBM, the degree of aneuploidy across the genome varies widely and the significance of regions of aneuploidy has not been assessed. Using whole genome sequencing profiles for matched tumor and non-tumor samples, we were able to accurately determine the degree of aneuploidy and loss of heterozygosity for a set of primary GBM tumors. Next, using machine learning techniques, distinct patterns of aneuploidy and loss of heterozygosity emerged among a set of GBM tumors, allowing us to define distinct aneuploidy subgroups. Interestingly, these aneuploidy subgroups showed distinctly different rates of patient survival, suggesting that regions of aneuploidy may be driving disease progression. Differing rates of various GBM genomic subtypes including IDH mutation, EGFR mutation, MGMT methylation, and tumor subtypes was also seen among the aneuploidy subgroups. We were able to derive a gene expression signature for each of these aneuploidy subgroups and revealed distinct pathways that were driving tumor growth. Furthermore, using a perturbagen-response dataset we were able to predict compounds to distinctly target each subgroup. Collectively, this suggests that aneuploidy profiling provides important clues to varying mechanisms of disease progression and is a promising approach for targeted therapy in a patient-specific manner.

Abstract 5699: Overexpression of KMT2A is associated with worse prognosis and specific immune signatures in patients with TP53-mutated hepatocellular carcinomas

Abstract Background: Aberrant expression of epigenetic regulators is often associated with pathogenesis. Histone H3K4 methyltransferase, known as KMT2A, has been implicated in regulation of chromosome segregation, mitosis and DNA replication in pediatric leukemia and myeloma. However, the role of KMT2A expression in solid tumors is under-investigated. Here we examine the implications of KMT2A overexpression in prognosis, gene pathway enrichment, aneuploidy and immune infiltration patterns using a large, real-world clinical HCC dataset. Methods: A total of 403 HCC samples underwent comprehensive molecular profiling at Caris Life Sciences, including DNA-(592 Gene Panel, NextSeq, or whole exome sequencing, NovaSeq) and RNA- (NovaSeq, whole transcriptome sequencing, WTS) sequencing. Wilcoxon, Fisher’s exact test were used to determine statistical significance (p value without and q value with multi comparison correction). Aneuploidy scores were generated from CNVkit. Apoptotic index (AI), GSEA were assessed using mRNA levels (FDR<0.25 as cutoff). Overall survival was calculated from date of tissue collection to date of last contact from insurance claims data and used for Kaplan-Meier method. Results: Overexpression of KMT2A predicts poor survival in patients with HCC (HR 2.6, 95% CI [1.4 - 5.2], p<.01). KMT2Ahigh HCC has higher TP53 (57.9% vs 28.8%, p<.001) and lower CTNNB1 (14.1% vs 34.6%, p <.01) mutation rates (mt). GSEA analysis showed that pathways such as mitotic spindle (NES = 2.1), DNA repair (NES = 2.0), E2F regulation (NES = 2.0) and MYC (NES = 1.9) are significantly enriched in KMT2Ahigh HCC. Interestingly, in KMT2Ahigh HCC, TP53 mutation status is a stratification factor for several HCC features: 1) TP53 mt HCC displayed significantly lower aneuploidy score (median 6 vs 13.5, p<.01) and higher apoptotic index (median 1.1 vs 1.2, p<.05); 2) inflammatory response pathways (NES = 2.1) and IL6 JAK STAT3 signaling (NES = 2.1) are specifically enriched in TP53 mt HCC and 3) TP53 mt HCC has more infiltration of B cells (5.3% vs 3.3%, q<.05), Macrophage M1 (6.4% vs 2.9%, q<.01), CD8 + T cells and myeloid dendritic cells (1.1% vs 1%, q<.01) while TP53 wt is associated with more infiltration of Macrophage M2 (5.5% vs 3.3%, q<.05) cells. Conclusions: KMT2A could act as an independent prognostic marker in HCC. The negative correlation between KMT2A expression and aneuploidy scores in TP53 mt indicates potential roles of KMT2A in maintaining genome stability. Furthermore, our results suggest TP53 status is an important stratification factor for HCC with KMT2A overexpression. Our results warrant further investigation on the impact of KMT2A level on immune modulation and may define a subset of HCC that responds most effectively to immune checkpoint inhibition. Citation Format: Liang Sha, Jun Yin, Sungming Kim, Woojin An, Jian Zhang, Alex Farrell, Joanne Xiu, David Spetzler, Shuanzeng Wei, Dave S. Hoon, Stephen V. Liu, Emil Lou, Misako Nagasaka, Wafik S. El-Deiry, Benedito A. Carneiro, Wolfgang Michael Korn, Heinz-Josef Lenz, Yali Dou. Overexpression of KMT2A is associated with worse prognosis and specific immune signatures in patients with TP53-mutated hepatocellular carcinomas [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 5699.

Multi-modal single-cell profiling of sarcomas from archival tissue reveals mechanisms of resistance to immune checkpoint inhibitors.

e23518 Background: Single-cell RNA-seq is an enabling technology that may inform the molecular underpinnings of drug response and resistance in patient biopsies. This method is difficult to implement in the study of rare diseases such as sarcomas due to specimen requirements and technical limitations. Methods: Here, we evolved novel methods that we recently reported in melanoma ( Wang, Fan, et al., bioRxiv, 2022), which enable single-nucleus RNA, T cell receptor (snRNA/TCR)-seq, and pool-matched whole-genome sequencing (WGS) from archival, frozen sarcoma tissue. Results: This enabled profiling of 75,716 cells and 788 matched TCR clonotypes from six patients with intimal sarcoma (INS) and undifferentiated pleomorphic sarcomas (UPS), including two matched pair samples from pre/post-immune checkpoint inhibitor (ICI). Our analysis revealed substantial transcriptional cancer cell heterogeneity driven by varying copy number alterations (CNAs). In one patient with INS with a complete response to ICI followed by an isolated recurrence, we identified a rare cancer cell clone defined by CNA (confirmed with WGS) and resulting transcriptional outputs that pre-existed and emerged during resistance. Furthermore, in a patient with UPS with intrinsic resistance to ICI, we find adequate T cell clonal expansion and activation, suggesting appropriate T cell response to ICI dampened by intrinsic mechanisms of ICI resistance within the cancer cells. Non-negative matrix factorization (NMF) analysis identified cell states associated with either intrinsic or adaptive resistance to ICI that was distinct from resistance to doxorubicin. These observations are consistent with those previously reported from sequential biopsies obtained from KEYNOTE-001 in metastatic melanoma ( Wang, Fan, et al., bioRxiv, 2022), which also revealed emergence of pre-existing populations of resistant clones defined by their underlying aneuploidy patterns. Conclusions: Together, these results demonstrate feasibility of implementing single-cell genomics from archival tissue to study sarcoma and propel our understanding of drug resistance. Conceptually, this work suggests that large-scale CNAs may drive cell sub-populations associated with ICI resistance in sarcoma and in other diseases.

SWAN pathway-network identification of common aneuploidy-based oncogenic drivers.

Haploinsufficiency drives Darwinian evolution. Siblings, while alike in many aspects, differ due to monoallelic differences inherited from each parent. In cancer, solid tumors exhibit aneuploid genetics resulting in hundreds to thousands of monoallelic gene-level copy-number alterations (CNAs) in each tumor. Aneuploidy patterns are heterogeneous, posing a challenge to identify drivers in this high-noise genetic environment. Here, we developed Shifted Weighted Annotation Network (SWAN) analysis to assess biology impacted by cumulative monoallelic changes. SWAN enables an integrated pathway-network analysis of CNAs, RNA expression, and mutations via a simple web platform. SWAN is optimized to best prioritize known and novel tumor suppressors and oncogenes, thereby identifying drivers and potential druggable vulnerabilities within cancer CNAs. Protein homeostasis, phospholipid dephosphorylation, and ion transport pathways are commonly suppressed. An atlas of CNA pathways altered in each cancer type is released. These CNA network shifts highlight new, attractive targets to exploit in solid tumors.