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PURPOSE Failure to respond to induction chemotherapy portends a poor outcome in childhood acute lymphoblastic leukemia (ALL) and is more frequent in T-cell ALL (T-ALL) than B-cell ALL. We aimed to address the limited understanding of clinical and genetic factors that influence outcome in a cohort of patients with T-ALL induction failure (IF). METHODS We studied all cases of T-ALL IF on two consecutive multinational randomized trials, UKALL2003 and UKALL2011, to define risk factors, treatment, and outcomes. We performed multiomic profiling to characterize the genomic landscape. RESULTS IF occurred in 10.3% of cases and was significantly associated with increasing age, occurring in 20% of patients age 16 years and older. Five-year overall survival (OS) rates were 52.1% in IF and 90.2% in responsive patients ( P < .001). Despite increased use of nelarabine-based chemotherapy consolidated by hematopoietic stem-cell transplant in UKALL2011, there was no improvement in outcome. Persistent end-of-consolidation molecular residual disease resulted in a significantly worse outcome (5-year OS, 14.3% v 68.5%; HR, 4.10; 95% CI, 1.35 to 12.45; P = .0071). Genomic profiling revealed a heterogeneous picture with 25 different initiating lesions converging on 10 subtype-defining genes. There was a remarkable abundance of TAL1 noncoding lesions, associated with a dismal outcome (5-year OS, 12.5%). Combining TAL1 lesions with mutations in the MYC and RAS pathways produces a genetic stratifier that identifies patients highly likely to fail conventional therapy (5-year OS, 23.1% v 86.4%; HR, 6.84; 95% CI, 2.78 to 16.78; P < .0001) and who should therefore be considered for experimental agents. CONCLUSION The outcome of IF in T-ALL remains poor with current therapy. The lack of a unifying genetic driver suggests alternative approaches, particularly using immunotherapy, are urgently needed.

The frequent acquisition of genomic abnormalities in human preimplantation embryos is a leading cause of pregnancy loss, but does not necessarily prohibit healthy offspring. However, the impact of genomic abnormalities on cellular states and development of the early human embryo remains largely unclear. Here, we characterise aneuploidy and reconstruct gene regulatory networks in human preimplantation embryos, and investigate gene expression and developmental perturbations instigated by aneuploidy using single-cell genome-and-transcriptome sequencing (G&T-seq). At the genomic level, we show that acquired numerical and structural chromosomal aberrations are frequent across all stages of early embryogenesis and in all cell lineages. At the transcriptome level, we identify regulators of cell identity and uncover a network of 248 transcription factors from 10 major gene regulatory modules that characterise the distinct lineages of human preimplantation embryos. By integrating single-cell DNA-with RNA-information, we unveil how expression levels are affected by losses or gains of the corresponding genes in embryonic cells across human preimplantation development, as well as how copy-number aberrant transcription factor genes perturb the expression of their cognate target genes in euploid regions. Furthermore, we reveal a majority of aneuploid cells show a developmental delay and reduced fitness, indicating cell competition within the mosaic diploid-aneuploid embryo, which may contribute to selection against aneuploid cells and the birth of healthy offspring from mosaic diploid-aneuploid embryos. In summary, our multi-modal analyses provide unprecedented insights into early human embryo development.

Single-cell multi-omics methods are enabling the study of cell state diversity, which is largely determined by the interplay of the genome, epigenome, and transcriptome. Here, we describe Gtag&T-seq, a genome-and-transcriptome sequencing (G&T-seq) protocol of the same single cells that omits whole-genome amplification (WGA) by using direct genomic tagmentation (Gtag). Gtag drastically decreases the cost and improves coverage uniformity at both the single-cell and pseudo-bulk level when compared to WGA-based G&T-seq. We also show that transcriptome-based DNA copy number inference has limited resolution and accuracy, underlining the importance of affordable multi-omic approaches. Moreover, applying Gtag&T-seq to a melanoma xenograft model before treatment and at minimal residual disease revealed differential cell state plasticity and treatment response between cancer subclones. In summary, Gtag&T-seq is a low-cost and accurate single-cell multi-omics method enabling the exploration of genetic alterations and their functional consequences in single cells at scale.

Cell type identity is encoded by gene regulatory networks (GRN), in which transcription factors (TFs) bind to enhancers to regulate target gene expression. In the mammalian liver, lineage TFs have been characterized for the main cell types, including hepatocytes. Hepatocytes cover a relatively broad cellular state space, as they differ significantly in their metabolic state, and function, depending on their position with respect to the central or portal vein in a liver lobule. It is unclear whether this spatially defined cellular state space, called zonation, is also governed by a well-defined gene regulatory code. To address this challenge, we have mapped enhancer-GRNs across liver cell types at high resolution, using a combination of single cell multiomics, spatial omics, GRN inference, and deep learning. We found that cell state changes in transcription and chromatin accessibility in hepatocytes, liver sinusoidal endothelial cells and hepatic stellate cells depend on zonation. Enhancer-GRN mapping suggests that zonation states in hepatocytes are driven by the repressors Tcf7l1 and Tbx3, that modulate the core hepatocyte GRN, controlled by Hnf4a, Cebpa, Hnf1a, Onecut1 and Foxa1, among others. To investigate how these TFs cooperate with cell type TFs, we performed anin vivomassively parallel reporter assay on 12,000 hepatocyte enhancers and used these data to train a hierarchical deep learning model (called DeepLiver) that exploits both enhancer accessibility and activity. DeepLiver confirms Cebpa, Onecut, Foxa1, Hnf1a and Hnf4a as drivers of enhancer specificity in hepatocytes; Tcf7l1/2 and Tbx3 as regulators of the zonation state; and Hnf4a, Hnf1a, AP-1 and Ets as activators. Finally, taking advantage ofin silicomutagenesis predictions from DeepLiver and enhancer assays, we confirmed that the destruction of Tcf7l1/2 or Tbx3 motifs in zonated enhancers abrogates their zonation bias. Our study provides a multi-modal understanding of the regulatory code underlying hepatocyte identity and their zonation state, that can be exploited to engineer enhancers with specific activity levels and zonation patterns.

SummaryNeuropeptides are ancient, widespread signaling molecules that underpin almost all brain functions. They constitute a broad ligand-receptor network, mainly by binding to G protein-coupled receptors (GPCRs). However, the organization of the peptidergic network and roles of many neuropeptides remain elusive, as our insight into neuropeptide-receptor interactions is limited and many peptide GPCRs in animal models and humans are still orphan receptors. Here we report a genome-wide neuropeptide-GPCR interaction map inC. elegans. By reverse pharmacology screening of over 55,384 possible interactions, we identify 461 cognate peptide-GPCR couples that uncover a broad signaling network with specific and complex combinatorial interactions encoded across and within single peptidergic genes. These interactions provide insights into neuropeptide functions and evolution. Combining our dataset with phylogenetic analysis supports peptide-receptor co-evolution and conservation of at least 14 bilaterian peptidergic systems inC. elegans. This resource lays a foundation for system-wide analysis of the peptidergic network.HighlightsSystem-wide reverse pharmacology deorphanizes 68C. eleganspeptide GPCRsDiscovery of 461 peptide-GPCR pairs and additional ligands for characterized GPCRsNeuropeptides show specific and complex combinatorial receptor interactionsPeptide-GPCR pairs support long-range conservation and expansion of peptide systems

Development of primary mediastinal B-cell lymphoma (PMBL) is driven by cumulative genomic aberrations. We discovered a unique copy-neutral loss of heterozygosity (CN-LOH) landscape of PMBL which distinguishes this tumor from other B-cell malignancies, including the biologically related diffuse large B-cell lymphoma. Using single nucleotide polymorphism array analysis we identified large-scale CN-LOH lesions in 91% (30/33) of diagnostic PMBLs and both investigated PMBL-derived cell lines. Altogether, the cohort showed 157 extra-large (25.3-248.4 Mb) CN-LOH lesions affecting up to 14 chromosomes per case (mean of 4.4) and resulting in a reduction of heterozygosity an average of 9.9% (range 1.3-51%) of the genome. Predominant involvement of terminal chromosomal segments suggests the implication of B-cell specific crossover events in the pathogenesis of PMBL. Notably, CN-LOH stretches non-randomly clustered on 6p (60%), 15 (37.2%), and 17q (40%), and frequently co-occurred with homozygous mutations in the MHC I (6p21), B2M (15q15), and GNA13 (17q23) genes, respectively, as shown by preliminary whole-exome/genome sequencing data. Altogether, our findings implicate CN-LOH as a novel and distinct mutational process contributing to the molecular pathogenesis of PMBL. The aberration acting as "second hit" in the Knudson hypothesis, ranks as the major mechanism converting to homozygosity the PMBL-related driver genes. Screening of the cohort of 199 B cell leukemia/lymphoma whole-genomes revealed significant differences in the CN-LOH landscape of PMBL and other B-cell malignancies, including the biologically related diffuse large B-cell lymphoma.

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31–32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes. A robust, cost-effective technique based on whole-exome sequencing data can be used to characterize immune infiltrates, relate the extent of these infiltrates to somatic changes in tumours, and enables prediction of tumour responses to immune checkpoint inhibition therapy.

Transmissible cancers are malignant cell clones that spread among individuals through transfer of living cancer cells. Several such cancers, collectively known as bivalve transmissible neoplasia (BTN), are known to infect and cause leukaemia in marine bivalve molluscs. This is the case of BTN clones affecting the common cockle,Cerastoderma edule, which inhabits the Atlantic coasts of Europe and north-west Africa. To investigate the origin and evolution of contagious cancers in common cockles, we collected 6,854C. edulespecimens and diagnosed 390 cases of BTN. We then generated a reference genome for the species and assessed genomic variation in the genomes of 61 BTN tumours. Analysis of tumour-specific variants confirmed the existence of two cockle BTN lineages with independent clonal origins, and gene expression patterns supported their status as haemocyte-derived marine leukaemias. Examination of mitochondrial DNA sequences revealed several mitochondrial capture events in BTN, as well as co-infection of cockles by different tumour lineages. Mutational analyses identified two lineage-specific mutational signatures, one of which resembles a signature associated with DNA alkylation. Karyotypic and copy number analyses uncovered genomes marked by pervasive instability and polyploidy. Whole-genome duplication, amplification of oncogenesCCND3andMDM2, and deletion of the DNA alkylation repair geneMGMT, are likely drivers of BTN evolution. Characterization of satellite DNA identified elements with vast expansions in the cockle germ line, yet absent from BTN tumours, suggesting ancient clonal origins. Our study illuminates the evolution of contagious cancers under the sea, and reveals long-term tolerance of extreme instability in neoplastic genomes.

The infinite sites model of molecular evolution posits that every position in the genome is mutated at most once1. By restricting the number of possible mutation histories, haplotypes and alleles, it forms a cornerstone of tumor phylogenetic analysis2and is often implied when calling, phasing and interpreting variants3,4or studying the mutational landscape as a whole5. Here we identify 18,295 biallelic mutations, where the same base is mutated independently on both parental copies, in 559 (21%) bulk sequencing samples from the Pan-Cancer Analysis of Whole Genomes study. Biallelic mutations reveal ultraviolet light damage hotspots at E26 transformation-specific (ETS) and nuclear factor of activated T cells (NFAT) binding sites, and hypermutable motifs inPOLE-mutant and other cancers. We formulate recommendations for variant calling and provide frameworks to model and detect biallelic mutations. These results highlight the need for accurate models of mutation rates and tumor evolution, as well as their inference from sequencing data.

Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene alteration and intra-tumor genetic heterogeneity as well as by pan-cancer trends in metabolic dysregulation. Taken together, our results indicate that measuring cell-type-specific total mRNA expression in tumor cells predicts tumor phenotypes and clinical outcomes. ispartof: NATURE BIOTECHNOLOGY vol:40 issue:11 pages:1624-+ ispartof: location:United States status: published

Background: The vast majority of cancer deaths can be attributed to tumor metastases. Disseminated tumor cells (DTCs) are thought to act as a reservoir of tumor clones which can lie dormant before causing overt metastases. Their presence has been shown to be a poor prognostic indicator in several tumor types. Despite their importance, the timing and source of DTCs is unclear across most solid cancers and even less is known about them in late-stage disease. The Posthumous Evaluation of the Advanced Cancer Environment (PEACE) post-mortem study enables extensive sampling of malignant lesions but also normal tissues, thereby allowing study of DTCs in patients with advanced cancer. Methods: We performed research autopsy sampling of macroscopically normal bone, lung and liver in 3 patients with advanced clear cell renal cell carcinoma (RCC). In addition, we performed bone marrow aspiration at autopsy from vertebral bodies and the ilium using an anterior approach. Mechanical disaggregation followed by collagenase digestion was used to generate single cell suspensions. Detection of tumor cells was carried out using antibodies against known tumor or epithelial markers carbonic anhydrase IX (CAIX). Epithelial cell adhesion molecule (EpCAM) was also used for bone marrow samples as native bone marrow cells do not express this marker. These sub-populations were then isolated using fluorescence activated cell sorting and DNA was extracted and amplified from single cells. Results: We performed and optimised collagenase-based digestion on all solid tissues collected. The percentage of viable cells generated varied significantly between subjects and tissues with bone marrow samples more viable than lung and liver. Rare and distinct populations of CAIX+ and EpCAM+ cells were detected in normal tissues between 0.5-2%. DNA amplification was successful on single cells isolated from normal lung and liver but not from bone tissue. Pilot shallow coverage whole genome sequencing revealed genomically aberrant cells ranging from single chromosome arm losses to widespread copy number aberrations. Conclusion: We demonstrate feasibility of sequencing single cells from autopsy study subjects. Rare populations of single cells with markers of clear cell RCC were detected and isolated both in normal tissues of patients with advanced disease. Genomic analyses of these cells will lead to insights into their relationship to the primary tumor and overt metastatic lesions. Citation Format: Haixi Yan, Cristina Cotobal Martin, Christie English, Annelien Verfaillie, Jonas Demeulemeester, Andrew Rowan, Annika Fendler, Anne-Laure Cattin, Sucheta Mahapatra, Lewis Au, Scott Shepherd, Ben Shum, Charlotte Spencer, Zayd Tippu, Ula Mahadeva, Anna Green, Eleanor Carlyle, Cristina Naceur-Lombardelli, PEACE consortium, Mariam Jamal-Hanjani, Charles Swanton, Samra Turajlic, Peter Van Loo. Detection of disseminated tumor cells in advanced clear cell renal cell carcinoma through research autopsy [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr A011.

A substantial fraction of the human genome displays high sequence similarity with at least one other genomic sequence, posing a challenge for the identification of somatic mutations from short-read sequencing data. Here we annotate genomic variants in 2,658 cancers from the Pan-Cancer Analysis of Whole Genomes (PCAWG) cohort with links to similar sites across the human genome. We train a machine learning model to use signals distributed over multiple genomic sites to call somatic events in non-unique regions and validate the data against linked-read sequencing in an independent dataset. Using this approach, we uncover previously hidden mutations in ~1,700 coding sequences and in thousands of regulatory elements, including in known cancer genes, immunoglobulins and highly mutated gene families. Mutations in non-unique regions are consistent with mutations in unique regions in terms of mutation burden and substitution profiles. The analysis provides a systematic summary of the mutation events in non-unique regions at a genome-wide scale across multiple human cancers. ispartof: NATURE BIOTECHNOLOGY vol:39 issue:12 pages:1589-+ ispartof: location:United States status: published

Organized by unstructured motifs The high degree of conservation in protein sequences thought to be unstructured has hinted that these regions may have important biological functions. Although unstructured regions are widely viewed to be crucial for protein signaling, localization, and stability, their roles in many other settings have remained mysterious. Cermakova et al . discovered that prominent members of the transcription elongation machinery are linked through a network of interactions involving transcription elongation factor TFIIS N-terminal domains (TNDs) and conserved unstructured sequences called “TND-interacting motifs” (TIMs). The researchers found that mutation of a single TIM in a central organizing protein of this network abolished key protein interactions and induced widespread defects in transcription elongation dynamics. —DJ

Most cancers are characterized by the somatic acquisition of genomic rearrangements during tumour evolution that eventually drive the oncogenesis. Here, using multiplatform sequencing technologies, we identify and characterize a remarkable mutational mechanism in human hepatocellular carcinoma caused by Hepatitis B virus, by which DNA molecules from the virus are inserted into the tumour genome causing dramatic changes in its configuration, including non-homologous chromosomal fusions, dicentric chromosomes and megabase-size telomeric deletions. This aberrant mutational mechanism, present in at least 8% of all HCC tumours, can provide the driver rearrangements that a cancer clone requires to survive and grow, including loss of relevant tumour suppressor genes. Most of these events are clonal and occur early during liver cancer evolution. Real-time timing estimation reveals some HBV-mediated rearrangements occur as early as two decades before cancer diagnosis. Overall, these data underscore the importance of characterising liver cancer genomes for patterns of HBV integration., Hepatitis B virus (HBV) infection and DNA integration is a frequent cause of hepatocellular carcinoma (HCC), but the consequences of this process are not fully understood. Here the authors use whole-genome and long-read sequencing data from HCC patient samples to study the timing and alterations induced by HBV insertions.

Therapy resistance arises from heterogeneous drug-tolerant persister cells or minimal residual disease (MRD) through genetic and nongenetic mechanisms. A key question is whether specific molecular features of the MRD ecosystem determine which of these two distinct trajectories will eventually prevail. We show that, in melanoma exposed to mitogen-activated protein kinase therapeutics, emergence of a transient neural crest stem cell (NCSC) population in MRD concurs with the development of nongenetic resistance. This increase relies on a glial cell line-derived neurotrophic factor-dependent signaling cascade, which activates the AKT survival pathway in a focal adhesion kinase (FAK)-dependent manner. Ablation of the NCSC population through FAK inhibition delays relapse in patient-derived tumor xenografts. Strikingly, all tumors that ultimately escape this treatment exhibit resistance-conferring genetic alterations and increased sensitivity to extracellular signal-regulated kinase inhibition. These findings identify an approach that abrogates the nongenetic resistance trajectory in melanoma and demonstrate that the cellular composition of MRD deterministically imposes distinct drug resistance evolutionary paths. ispartof: CANCER CELL vol:39 issue:8 pages:1135-+ ispartof: location:United States status: published

Understanding how enhancers drive cell type specificity and efficiently identifying them is essential for the development of innovative therapeutic strategies. In melanoma, the melanocytic (MEL) and the mesenchymal-like (MES) states present themselves with different responses to therapy, making the identification of specific enhancers highly relevant. Using massively parallel reporter assay (MPRA) in a panel of patient-derived melanoma lines (MM lines), we set to identify and decipher melanoma enhancers by first focusing on regions with state specific H3K27 acetylation close to differentially expressed genes. A more in-depth evaluation of those regions was then pursued by investigating the activity of ATAC-seq peaks found therein along with a full tiling of the acetylated regions with 190 bp sequences. Activity was observed in more than 60% of the selected regions and we were able to precisely locate the active regions within ATAC-seq peaks. Comparison of sequence content with activity, using the deep learning model DeepMEL2, revealed that AP-1 alone is responsible for the MES enhancer activity, while SOX and MITF both influence MEL enhancer activity with SOX being required to achieve high levels of activity. Overall, our MPRA assays shed light on the relationship between long and short sequences in terms of their sequence content, enhancer activity, and specificity as reporters across melanoma cell states.

Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content have not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data, which performs transcriptomic deconvolution while adjusting for mixed genomes. We used single-cell RNA sequencing data to demonstrate total mRNA expression as a feature of tumor phenotype. We estimated and validated TmS in 5,015 patients across 15 cancer types identifying significant inter-individual variability. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Cancer type-specific patterns of genetic alterations, intra-tumor genetic heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring cell-type specific total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important biological and clinical implications.

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that impact cis-regulatory function, remains a major challenge. Interpretation of noncoding genome variation benefits from explainable artificial intelligence to predict and interpret the impact of a mutation on gene regulation. Here we generate phased whole genomes with matched chromatin accessibility, histone modifications, and gene expression for 10 melanoma cell lines. We find that training a specialized deep learning model, called DeepMEL2, on melanoma chromatin accessibility data can capture the various regulatory programs of the melanocytic and mesenchymal-like melanoma cell states. This model outperforms motif-based variant scoring, as well as more generic deep learning models. We detect hundreds to thousands of allele-specific chromatin accessibility variants (ASCAVs) in each melanoma genome, of which 15%–20% can be explained by gains or losses of transcription factor binding sites. A considerable fraction of ASCAVs are caused by changes in AP-1 binding, as confirmed by matched ChIP-seq data to identify allele-specific binding of JUN and FOSL1. Finally, by augmenting the DeepMEL2 model with ChIP-seq data for GABPA, the TERT promoter mutation, as well as additional ETS motif gains, can be identified with high confidence. In conclusion, we present a new integrative genomics approach and a deep learning model to identify and interpret functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression., SCOPUS: ar.j, info:eu-repo/semantics/published

Most cancers are characterized by the somatic acquisition of genomic rearrangements during tumour evolution that eventually drive the oncogenesis. There are different mutational mechanisms causing structural variation, some of which are specific to particular cancer types. Here, using multiplatform sequencing technologies, we identify and characterize a remarkable mutational mechanism in human hepatocellular carcinoma caused by Hepatitis B virus, by which DNA molecules from the virus are inserted into the tumour genome causing dramatic changes in its configuration, including non-homologous chromosomal fusions and megabase-size telomeric deletions. This aberrant mutational process, present in at least 8% of all HCC tumours, is active early during liver cancer evolution and can provide the driver rearrangements that a cancer clone requires to survive and grow.

Summary Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin, and drivers of ITH across cancer types are poorly understood. To address this, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types and identify cancer type-specific subclonal patterns of driver gene mutations, fusions, structural variants, and copy number alterations as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution and provide a pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data., Graphical abstract, Highlights • Pan-cancer resource of comprehensively annotated intra-tumor heterogeneity (ITH) • ITH is pervasive across cancers and shows cancer type-specific patterns • Branching phylogenies are common • Dynamic changes in mutational processes between subclonal expansions, Dentro et al. provide a comprehensive annotation of intra-tumor heterogeneity and its drivers in cancer evolution.

Background Malignant peripheral nerve sheath tumors (MPNSTs) are rare, highly aggressive soft tissue sarcomas derived from Schwann cells with poor prognosis. Previous studies, although limited in scale and depth, have shown that these tumors are typically genomically complex, with a moderate burden of single nucleotide variants but extensive copy number aberrations (CNAs). Methods We applied a multi-omics approach to scrutinize the evolution and heterogeneity of a primary MPNST and five recurrence regions from one patient with an NF1 phenotype. Techniques utilized included bulk whole genome sequencing (WGS), single-cell DNA sequencing (scDNA-seq), single-cell RNA sequencing (scRNA-seq), simultaneous genome and transcriptome sequencing (G&T-seq), spatial transcriptomics, and laser capture microdissection (LCM)-based spatial genomics. Results We find significant heterogeneity in copy number profiles, suggestive of ongoing chromosomal instability and evolution. We perform in-depth tumor phylogenetic reconstruction from bulk WGS data. scDNA-seq revealed further CNA heterogeneity across and within regions, allowing us to refine the tree down to single-cell resolution. De novo somatic variant calling in scDNA-seq data confirms the reconstructed tree and identifies additional subclonal mutations. We also profile different populations of tumor and non-tumor cells and confirmed this with a genotyping approach. CNA profiles inferred from scRNA-seq reflect the within-region heterogeneity seen in scDNA-seq. We find tumor cells with similar CNA profiles typically cluster together by their gene expression profiles as well, implying that the majority of gene expression heterogeneity in this tumor is underpinned by copy number changes. By using CNA profiles as a native barcoding system, we link genetic subclones to clusters of cells and their transcriptomes to characterize the effects of gene dosage. Finally, we explore the spatial relationships between tumor subclones using LCM. We detect heterogeneity within tissue sections evidencing local clonal expansions and CNA events that follow spatial distributions. Using spatial transcriptomics, we show tumor cells are homogeneously admixed with tumor microenvironment populations. Conclusions Our work demonstrates the power of combining spatial multi-omics at the single-cell and bulk levels to study cancer evolution. This enables a spatio-temporal representation of a tumor’s development with annotation of genetic and transcriptomic events. Citation Format: Haixi Yan, Jonas Demeulemeester, Annelien Verfaillie, Cristina Cotobal Martin, Tom Kaufmann, Roland Schwarz, Thierry Voet, Simone Zaccaria, Adrienne Flanagan, Maxime Tarabichi, Peter Van Loo. Chromosomal instability drives spatial and temporal phenotypic diversity in Schwann cancer cells [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 1606.

Introduction: Lung TRACERx is a prominent study employing multi-region and longitudinal multi-omics sequencing to unravel the evolutionary trajectories of lung cancer. Aberrant DNA methylation patterns have been widely described in nearly all human cancers, yet their interplay with DNA mutations in lung cancer is not well understood. Incorporating the contribution of epigenetic modifications to cancer evolution trajectories within TRACERx could improve our understanding of the intricate relationship between genetic and epigenetic changes in non-small cell lung cancer (NSCLC) evolution. Methods: Multi-region sampling from 38 TRACERx patients including 112 tumor regions and 37 matched normal adjacent tissue samples was performed. Reduced representation bisulfite sequencing (RRBS) was performed to assess DNA methylation and the CAMDAC (Larose-Cadieux et al, 2020) was applied to estimate purified tumor methylation rates and correct for copy number changes. Whole exome sequencing and somatic copy number alterations (SCNAs) were inferred using the ASCAT tool (Van Loo et al, 2010) and Methsig (Pan et al, 2021) was performed to discover new methylation driver genes. Results: Using multi-region sequencing, we identified ubiquitous hypermethylation of 29 known driver genes in both lung adenocarcinoma (LUAD) and squamous cell lung cancer (LUSC), together with an additional 9 and 27 genes exclusive to LUSC and LUAD, respectively. We also identified 13 and 7 driver genes non-ubiquitously hypermethylated exclusively in LUSC and LUAD, respectively. Using a differential methylation based approach, we describe a method to determine the extent of intra-tumor methylation heterogeneity akin to established ITH scores based on genomics data. In addition, we report the identification of novel subtype-specific methylation driver genes enriched in HOX family members which are related to cancer progression. Through integration of DNA methylation and genomic sequencing data, we identify parallel mechanisms contributing towards ubiquitous tumor suppressor gene alterations. At the patient level, multiple driver genes such as NSD1, GATA3 and MGA were subject to repression by both copy number loss and DNA hypermethylation. Finally, we describe dosage-compensation of genes such as the Notch ligands JAG2 and DLK1 that are proximal to amplified oncogenes and hypermethylated during tumor evolution. Conclusion: We describe the contribution of DNA methylation and genomic alterations to altering the landscape of NSCLC. Leveraging DNA methylation, we can determine the extent of convergent repression mechanisms in different regions of the same tumor, assess DNA methylation heterogeneity, and discover DNA methylation-based driver genes in NSCLC. Citation Format: Francisco Gimeno-Valiente, Carla Castignani, Elizabeth Larose-Cadieux, Kezhong Chen, Nana Mensah, Olga Chervova, Thomas Watkins, Pawan Dhami, Heli Vaikkinen, Andrew Feber, TRACERx Consortium, Jonas Demeulemeester, Miljana Tanic, Stephan Beck, Peter Van Loo, Charles Swanton, Nnennaya Kanu. Identification of convergent gene repression mechanisms through integrative genomic and DNA methylation analysis in TRACERx [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 5710.

SummaryThe ability to predict the future behaviour of an individual cancer is crucial for precision cancer medicine and, in particular, for the development of strategies that prevent acquisition of resistance to anti-cancer drugs. Therapy resistance, which often develops from a heterogeneous pool of drug-tolerant cells known as minimal residual disease (MRD), is thought to mainly occur through acquisition of genetic alterations. Increasing evidence, however, indicates that drug resistance might also be acquired though nongenetic mechanisms. A key emerging question is therefore whether specific molecular and/or cellular features of the MRD ecosystem determine which of these two distinct resistance trajectories will eventually prevail. We show herein that, in melanoma exposed to MAPK-therapeutics, the presence of a neural crest stem cell (NCSC) subpopulation in MRD concurred with the rapid development of resistance through nongenetic mechanisms. Emergence of this drug-tolerant population in MRD relies on a GDNF-dependent autocrine and paracrine signalling cascade, which activates the AKT survival pathway in a Focal-adhesion kinase-(FAK) dependent manner. Ablation of this subpopulation through inhibition of FAK/SRC-signalling delayed relapse in patient-derived tumour xenografts. Strikingly, all tumours that eventually escaped this treatment exhibited resistance-conferring genetic alterations and increased sensitivity to ERK-inhibition. These findings firmly establish that nongenetic reprogramming events contribute to therapy resistance in melanoma and identify a clinically-compatible approach that abrogates such a trajectory. Importantly, these data demonstrate that the cellular composition of MRD deterministically imposes distinct drug resistance evolutionary paths and highlight key principles that may permit more effective pre-emptive therapeutic interventions.

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes(1,2). The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution(1,3,4). Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such asBCL9, MCL1,ARNT(also known asHIF1B),TERTandMYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompassesBCL9, MCL1andARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassingMYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassingCCND1) in HER2(+)breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.Chromosomal instability enables the continuous selection of somatic copy number alterations, which are established as ordered events that often occur in parallel, throughout tumour evolution and metastasis.

Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, the significance of differences in tumor cell total mRNA content is poorly understood. Studies using single-cell sequencing or model systems have suggested a role for total mRNA content in regulating cellular phenotypes. However, analytical challenges related to technical artifacts and cellular admixture have impeded examination of total mRNA expression at scale across cancers. To address this, we evaluated total mRNA expression using single cell sequencing, and developed a computational method for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data. We systematically estimated TmS in 5,181 patients across 15 cancer types and observed close correlations with clinicopathologic characteristics and molecular features, where high TmS generally accompanies high-risk disease. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Moreover, TmS captures tumor type-specific effects of somatic mutations, chromosomal instability, and hypoxia, as well as aspects of intratumor heterogeneity. Taken together, our results suggest that measuring total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important clinical and biological implications.

The rare benign giant cell tumour of bone (GCTB) is defined by an almost unique mutation in the H3.3 family of histone genes H3-3A or H3-3B; however, the same mutation is occasionally found in primary malignant bone tumours which share many features with the benign variant. Moreover, lung metastases can occur despite the absence of malignant histological features in either the primary or metastatic lesions. Herein we investigated the genetic events of 17 GCTBs including benign and malignant variants and the methylation profiles of 122 bone tumour samples including GCTBs. Benign GCTBs possessed few somatic alterations and no other known drivers besides the H3.3 mutation, whereas all malignant tumours harboured at least one additional driver mutation and exhibited genomic features resembling osteosarcomas, including high mutational burden, additional driver event(s), and a high degree of aneuploidy. The H3.3 mutation was found to predate the development of aneuploidy. In contrast to osteosarcomas, malignant H3.3-mutated tumours were enriched for a variety of alterations involving TERT, other than amplification, suggesting telomere dysfunction in the transformation of benign to malignant GCTB. DNA sequencing of the benign metastasising GCTB revealed no additional driver alterations; polyclonal seeding in the lung was identified, implying that the metastatic lesions represent an embolic event. Unsupervised clustering of DNA methylation profiles revealed that malignant H3.3-mutated tumours are distinct from their benign counterpart, and other bone tumours. Differential methylation analysis identified CCND1, encoding cyclin D1, as a plausible cancer driver gene in these tumours because hypermethylation of the CCND1 promoter was specific for GCTBs. We report here the genomic and methylation patterns underlying the rare clinical phenomena of benign metastasising and malignant transformation of GCTB and show how the combination of genomic and epigenomic findings could potentially distinguish benign from malignant GCTBs, thereby predicting aggressive behaviour in challenging diagnostic cases. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland. ispartof: JOURNAL OF PATHOLOGY vol:252 issue:4 pages:433-440 ispartof: location:England status: published