The genomic landscape of 2,023 colorectal cancers.

Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2-9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichia colipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11-13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care.

Homopolymer switches mediate adaptive mutability in mismatch repair-deficient colorectal cancer.

Mismatch repair (MMR)-deficient cancer evolves through the stepwise erosion of coding homopolymers in target genes. Curiously, the MMR genes MutS homolog 6 (MSH6) and MutS homolog 3 (MSH3) also contain coding homopolymers, and these are frequent mutational targets in MMR-deficient cancers. The impact of incremental MMR mutations on MMR-deficient cancer evolution is unknown. Here we show that microsatellite instability modulates DNA repair by toggling hypermutable mononucleotide homopolymer runs in MSH6 and MSH3 through stochastic frameshift switching. Spontaneous mutation and reversion modulate subclonal mutation rate, mutation bias and HLA and neoantigen diversity. Patient-derived organoids corroborate these observations and show that MMR homopolymer sequences drift back into reading frame in the absence of immune selection, suggesting a fitness cost of elevated mutation rates. Combined experimental and simulation studies demonstrate that subclonal immune selection favors incremental MMR mutations. Overall, our data demonstrate that MMR-deficient colorectal cancers fuel intratumor heterogeneity by adapting subclonal mutation rate and diversity to immune selection.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer.

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

Immune evasion impacts the landscape of driver genes during cancer evolution.

BACKGROUND: Carcinogenesis is driven by interactions between genetic mutations and the local tumor microenvironment. Recent research has identified hundreds of cancer driver genes; however, these studies often include a mixture of different molecular subtypes and ecological niches and ignore the impact of the immune system. RESULTS: In this study, we compare the landscape of driver genes in tumors that escaped the immune system (escape +) versus those that did not (escape -). We analyze 9896 primary tumors from The Cancer Genome Atlas using the ratio of non-synonymous to synonymous mutations (dN/dS) and find 85 driver genes, including 27 and 16 novel genes, in escape - and escape + tumors, respectively. The dN/dS of driver genes in immune escaped tumors is significantly lower and closer to neutrality than in non-escaped tumors, suggesting selection buffering in driver genes fueled by immune escape. Additionally, we find that immune evasion leads to more mutated sites, a diverse array of mutational signatures and is linked to tumor prognosis. CONCLUSIONS: Our findings highlight the need for improved patient stratification to identify new therapeutic targets for cancer treatment.

Long-term Multimodal Recording Reveals Epigenetic Adaptation Routes in Dormant Breast Cancer Cells.

Patients with estrogen receptor-positive breast cancer receive adjuvant endocrine therapies (ET) that delay relapse by targeting clinically undetectable micrometastatic deposits. Yet, up to 50% of patients relapse even decades after surgery through unknown mechanisms likely involving dormancy. To investigate genetic and transcriptional changes underlying tumor awakening, we analyzed late relapse patients and longitudinally profiled a rare cohort treated with long-term neoadjuvant ETs until progression. Next, we developed an in vitro evolutionary study to record the adaptive strategies of individual lineages in unperturbed parallel experiments. Our data demonstrate that ETs induce nongenetic cell state transitions into dormancy in a stochastic subset of cells via epigenetic reprogramming. Single lineages with divergent phenotypes awaken unpredictably in the absence of recurrent genetic alterations. Targeting the dormant epigenome shows promising activity against adapting cancer cells. Overall, this study uncovers the contribution of epigenetic adaptation to the evolution of resistance to ETs. SIGNIFICANCE: This study advances the understanding of therapy-induced dormancy with potential clinical implications for breast cancer. Estrogen receptor-positive breast cancer cells adapt to endocrine treatment by entering a dormant state characterized by strong heterochromatinization with no recurrent genetic changes. Targeting the epigenetic rewiring impairs the adaptation of cancer cells to ETs. See related commentary by Llinas-Bertran et al., p. 704. This article is featured in Selected Articles from This Issue, p. 695.

Epigenome and early selection determine the tumour-immune evolutionary trajectory of colorectal cancer.

Immune system control is a major hurdle that cancer evolution must circumvent. The relative timing and evolutionary dynamics of subclones that have escaped immune control remain incompletely characterized, and how immune-mediated selection shapes the epigenome has received little attention. Here, we infer the genome- and epigenome-driven evolutionary dynamics of tumour-immune coevolution within primary colorectal cancers (CRCs). We utilise our existing CRC multi-region multi-omic dataset that we supplement with high-resolution spatially-resolved neoantigen sequencing data and highly multiplexed imaging of the tumour microenvironment (TME). Analysis of somatic chromatin accessibility alterations (SCAAs) reveals frequent somatic loss of accessibility at antigen presenting genes, and that SCAAs contribute to silencing of neoantigens. We observe that strong immune escape and exclusion occur at the outset of CRC formation, and that within tumours, including at the microscopic level of individual tumour glands, additional immune escape alterations have negligible consequences for the immunophenotype of cancer cells. Further minor immuno-editing occurs during local invasion and is associated with TME reorganisation, but that evolutionary bottleneck is relatively weak. Collectively, we show that immune evasion in CRC follows a "Big Bang" evolutionary pattern, whereby genetic, epigenetic and TME-driven immune evasion acquired by the time of transformation defines subsequent cancer-immune evolution.

Cancer Evolution: A Multifaceted Affair.

Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery. SIGNIFICANCE: Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.

Phenotypic noise and plasticity in cancer evolution.

Non-genetic alterations can produce changes in a cell's phenotype. In cancer, these phenomena can influence a cell's fitness by conferring access to heritable, beneficial phenotypes. Herein, we argue that current discussions of 'phenotypic plasticity' in cancer evolution ignore a salient feature of the original definition: namely, that it occurs in response to an environmental change. We suggest 'phenotypic noise' be used to distinguish non-genetic changes in phenotype that occur independently from the environment. We discuss the conceptual and methodological techniques used to identify these phenomena during cancer evolution. We propose that the distinction will guide efforts to define mechanisms of phenotype change, accelerate translational work to manipulate phenotypes through treatment, and, ultimately, improve patient outcomes.

Contribution of pks+ E. coli mutations to colorectal carcinogenesis.

The dominant mutational signature in colorectal cancer genomes is C > T deamination (COSMIC Signature 1) and, in a small subgroup, mismatch repair signature (COSMIC signatures 6 and 44). Mutations in common colorectal cancer driver genes are often not consistent with those signatures. Here we perform whole-genome sequencing of normal colon crypts from cancer patients, matched to a previous multi-omic tumour dataset. We analyse normal crypts that were distant vs adjacent to the cancer. In contrast to healthy individuals, normal crypts of colon cancer patients have a high incidence of pks + (polyketide synthases) E.coli (Escherichia coli) mutational and indel signatures, and this is confirmed by metagenomics. These signatures are compatible with many clonal driver mutations detected in the corresponding cancer samples, including in chromatin modifier genes, supporting their role in early tumourigenesis. These results provide evidence that pks + E.coli is a potential driver of carcinogenesis in the human gut.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors.

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.

The co-evolution of the genome and epigenome in colorectal cancer.

Colorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4-7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Phenotypic plasticity and genetic control in colorectal cancer evolution.

Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, we find that the majority of intratumour variation in gene expression is not strongly heritable but rather 'plastic'. Somatic expression quantitative trait loci analysis identified a number of putative genetic controls of expression by cis-acting coding and non-coding mutations, the majority of which were clonal within a tumour, alongside frequent structural alterations. Consistently, computational inference on the spatial patterning of tumour phylogenies finds that a considerable proportion of CRCs did not show evidence of subclonal selection, with only a subset of putative genetic drivers associated with subclone expansions. Spatial intermixing of clones is common, with some tumours growing exponentially and others only at the periphery. Together, our data suggest that most genetic intratumour variation in CRC has no major phenotypic consequence and that transcriptional plasticity is, instead, widespread within a tumour.

Quantification of spatial subclonal interactions enhancing the invasive phenotype of pediatric glioma.

Diffuse midline gliomas (DMGs) are highly aggressive, incurable childhood brain tumors. They present a clinical challenge due to many factors, including heterogeneity and diffuse infiltration, complicating disease management. Recent studies have described the existence of subclonal populations that may co-operate to drive pro-tumorigenic processes such as cellular invasion. However, a precise quantification of subclonal interactions is lacking, a problem that extends to other cancers. In this study, we combine spatial computational modeling of cellular interactions during invasion with co-evolution experiments of clonally disassembled patient-derived DMG cells. We design a Bayesian inference framework to quantify spatial subclonal interactions between molecular and phenotypically distinct lineages with different patterns of invasion. We show how this approach could discriminate genuine interactions, where one clone enhanced the invasive phenotype of another, from those apparently only due to the complex dynamics of spatially restricted growth. This study provides a framework for the quantification of subclonal interactions in DMG.

Immunosuppressive niche engineering at the onset of human colorectal cancer.

The evolutionary dynamics of tumor initiation remain undetermined, and the interplay between neoplastic cells and the immune system is hypothesized to be critical in transformation. Colorectal cancer (CRC) presents a unique opportunity to study the transition to malignancy as pre-cancers (adenomas) and early-stage cancers are frequently resected. Here, we examine tumor-immune eco-evolutionary dynamics from pre-cancer to carcinoma using a computational model, ecological analysis of digital pathology data, and neoantigen prediction in 62 patient samples. Modeling predicted recruitment of immunosuppressive cells would be the most common driver of transformation. As predicted, ecological analysis reveals that progressed adenomas co-localized with immunosuppressive cells and cytokines, while benign adenomas co-localized with a mixed immune response. Carcinomas converge to a common immune "cold" ecology, relaxing selection against immunogenicity and high neoantigen burdens, with little evidence for PD-L1 overexpression driving tumor initiation. These findings suggest re-engineering the immunosuppressive niche may prove an effective immunotherapy in CRC.

Circulating tumour DNA sequencing to determine therapeutic response and identify tumour heterogeneity in patients with paediatric solid tumours.

OBJECTIVE: Clinical diagnostic sequencing of circulating tumour DNA (ctDNA) is well advanced for adult patients, but application to paediatric cancer patients lags behind. METHODS: To address this, we have developed a clinically relevant (67 gene) NGS capture panel and accompanying workflow that enables sensitive and reliable detection of low-frequency genetic variants in cell-free DNA (cfDNA) from children with solid tumours. We combined gene panel sequencing with low pass whole-genome sequencing of the same library to inform on genome-wide copy number changes in the blood. RESULTS: Analytical validity was evaluated using control materials, and the method was found to be highly sensitive (0.96 for SNVs and 0.97 for INDEL), specific (0.82 for SNVs and 0.978 for INDEL), repeatable (>0.93 [95% CI: 0.89-0.95]) and reproducible (>0.87 [95% CI: 0.87-0.95]). Potential for clinical application was demonstrated in 39 childhood cancer patients with a spectrum of solid tumours in which the single nucleotide variants expected from tumour sequencing were detected in cfDNA in 94.4% (17/18) of cases with active extracranial disease. In 13 patients, where serial samples were available, we show a close correlation between events detected in cfDNA and treatment response, demonstrate that cfDNA analysis could be a useful tool to monitor disease progression, and show cfDNA sequencing has the potential to identify targetable variants that were not detected in tumour samples. CONCLUSIONS: This is the first pan-cancer DNA sequencing panel that we know to be optimised for cfDNA in children for blood-based molecular diagnostics in paediatric solid tumours.

Reconstructing single-cell karyotype alterations in colorectal cancer identifies punctuated and gradual diversification patterns.

Central to tumor evolution is the generation of genetic diversity. However, the extent and patterns by which de novo karyotype alterations emerge and propagate within human tumors are not well understood, especially at single-cell resolution. Here, we present 3D Live-Seq-a protocol that integrates live-cell imaging of tumor organoid outgrowth and whole-genome sequencing of each imaged cell to reconstruct evolving tumor cell karyotypes across consecutive cell generations. Using patient-derived colorectal cancer organoids and fresh tumor biopsies, we demonstrate that karyotype alterations of varying complexity are prevalent and can arise within a few cell generations. Sub-chromosomal acentric fragments were prone to replication and collective missegregation across consecutive cell divisions. In contrast, gross genome-wide karyotype alterations were generated in a single erroneous cell division, providing support that aneuploid tumor genomes can evolve via punctuated evolution. Mapping the temporal dynamics and patterns of karyotype diversification in cancer enables reconstructions of evolutionary paths to malignant fitness.

EGFR amplification and outcome in a randomised phase III trial of chemotherapy alone or chemotherapy plus panitumumab for advanced gastro-oesophageal cancers.

OBJECTIVE: Epidermal growth factor receptor (EGFR) inhibition may be effective in biomarker-selected populations of advanced gastro-oesophageal adenocarcinoma (aGEA) patients. Here, we tested the association between outcome and EGFR copy number (CN) in pretreatment tissue and plasma cell-free DNA (cfDNA) of patients enrolled in a randomised first-line phase III clinical trial of chemotherapy or chemotherapy plus the anti-EGFR monoclonal antibody panitumumab in aGEA (NCT00824785). DESIGN: EGFR CN by either fluorescence in situ hybridisation (n=114) or digital-droplet PCR in tissues (n=250) and plasma cfDNAs (n=354) was available for 474 (86%) patients in the intention-to-treat (ITT) population. Tissue and plasma low-pass whole-genome sequencing was used to screen for coamplifications in receptor tyrosine kinases. Interaction between chemotherapy and EGFR inhibitors was modelled in patient-derived organoids (PDOs) from aGEA patients. RESULTS: EGFR amplification in cfDNA correlated with poor survival in the ITT population and similar trends were observed when the analysis was conducted in tissue and plasma by treatment arm. EGFR inhibition in combination with chemotherapy did not correlate with improved survival, even in patients with significant EGFR CN gains. Addition of anti-EGFR inhibitors to the chemotherapy agent epirubicin in PDOs, resulted in a paradoxical increase in viability and accelerated progression through the cell cycle, associated with p21 and cyclin B1 downregulation and cyclin E1 upregulation, selectively in organoids from EGFR-amplified aGEA. CONCLUSION: EGFR CN can be accurately measured in tissue and liquid biopsies and may be used for the selection of aGEA patients. EGFR inhibitors may antagonise the antitumour effect of anthracyclines with important implications for the design of future combinatorial trials.

The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data.

BACKGROUND: The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in the biopsy sample, a fundamental step to determine clonal expansions and their evolutionary trajectories. RESULTS: In a recent work we have developed a new model-based approach to carry out subclonal deconvolution from the site frequency spectrum of somatic mutations. This new method integrates, for the first time, an explicit model for neutral evolutionary forces that participate in clonal expansions; in that work we have also shown that our method improves largely over competing data-driven methods. In this Software paper we present mobster, an open source R package built around our new deconvolution approach, which provides several functions to plot data and fit models, assess their confidence and compute further evolutionary analyses that relate to subclonal deconvolution. CONCLUSIONS: We present the mobster package for tumour subclonal deconvolution from bulk sequencing, the first approach to integrate Machine Learning and Population Genetics which can explicitly model co-existing neutral and positive selection in cancer. We showcase the analysis of two datasets, one simulated and one from a breast cancer patient, and overview all package functionalities.

Evolutionary dynamics of neoantigens in growing tumors.

Cancers accumulate mutations that lead to neoantigens, novel peptides that elicit an immune response, and consequently undergo evolutionary selection. Here we establish how negative selection shapes the clonality of neoantigens in a growing cancer by constructing a mathematical model of neoantigen evolution. The model predicts that, without immune escape, tumor neoantigens are either clonal or at low frequency; hypermutated tumors can only establish after the evolution of immune escape. Moreover, the site frequency spectrum of somatic variants under negative selection appears more neutral as the strength of negative selection increases, which is consistent with classical neutral theory. These predictions are corroborated by the analysis of neoantigen frequencies and immune escape in exome and RNA sequencing data from 879 colon, stomach and endometrial cancers.

Subclonal reconstruction of tumors by using machine learning and population genetics.

Most cancer genomic data are generated from bulk samples composed of mixtures of cancer subpopulations, as well as normal cells. Subclonal reconstruction methods based on machine learning aim to separate those subpopulations in a sample and infer their evolutionary history. However, current approaches are entirely data driven and agnostic to evolutionary theory. We demonstrate that systematic errors occur in the analysis if evolution is not accounted for, and this is exacerbated with multi-sampling of the same tumor. We present a novel approach for model-based tumor subclonal reconstruction, called MOBSTER, which combines machine learning with theoretical population genetics. Using public whole-genome sequencing data from 2,606 samples from different cohorts, new data and synthetic validation, we show that this method is more robust and accurate than current techniques in single-sample, multiregion and longitudinal data. This approach minimizes the confounding factors of nonevolutionary methods, thus leading to more accurate recovery of the evolutionary history of human cancers.