TRACERx as an Optimized Paradigm for Understanding Cancer Evolution

ES 04.03 Tumor Heterogeneity

Background: Genomic intra-tumor heterogeneity (ITH) drives tumor evolution, leading to immune evasion and resistance to therapy. Emerging evidence implicates the transcriptome as a source of important variation that impacts tumor phenotype. Here, we perform a genomic-transcriptomic analysis of intra-tumor transcriptomic diversity upon 941 tumor regions taken from 357 TRACERx non-small cell lung cancers (NSCLC) across primary and metastatic disease subjected to high-depth bulk DNA and RNA sequencing, as well as 91 tumor-adjacent normal tissue samples. Results: Genomic and transcriptomic diversity are linked across primary and metastatic disease, with expression signatures of proliferation being enriched in the metastasis seeding subclone of the primary tumor relative to non-metastasis seeding subclones. Copy-number independent allele-specific expression (CN-independent ASE), a source of transcriptome-specific diversity, affects 1% (± 0.5%) of genes and is underpinned by aberrant allele-specific methylation (OR=7.58, p≤2.2x10-16), thus providing a window to the NSCLC epigenomic landscape. Driver mutations in chromatin remodellers and histone modifiers, in particular SETD2 and KDM5C, are associated with increased global levels of CN-independent ASE (p=0.0001). In genomically stable tumors, high levels of CN-independent ASE are linked to expression signatures consistent with genomic instability and proliferation (R=0.58, p=0.001), highlighting convergence between the genome and transcriptome in tumor evolution. For the first time, we uncover mutational signatures of RNA editing. Analysis of their activity links the expression of ADAR and APOBEC enzymes to editing processes revealing otherwise hidden APOBEC activity within tumors at sampling (RNA APOBEC activity identified in 188 tumor regions (32%) without evidence of DNA APOBEC activity). RNA editing activity is shared between primary tumors and paired metastasis, but not paired tumor-adjacent normal tissue, suggestive of heritability of this somatic transcriptional process. Finally, we combine multiple measures of genomic and transcriptomic variation in a multi-region approach to define important variation within cancer genes. We illustrate examples that would be missed with a purely genomic focus and demonstrate genomic-transcriptomic parallel evolution, converging on disruption to single cancer genes, such as FAT1 and APC, in different regions of a tumor. Conclusions: This work highlights the importance of the transcriptome during tumor evolution, as well as the power of integrative multi-omic assessments of ITH, and provides novel insight into the role of transcriptomic variation in lung cancer. Citation Format: James R. M. Black, Carlos Martinez-Ruiz, Clare Puttick, Jonas Demeulemeester, Elizabeth Larose Cadieux, Kerstin Thol, Thomas P. Jones, Selvaraju Veeriah, Cristina Naceur-Lombardelli, Andrew Rowan, Sophia Ward, Michelle Dietzen, Ariana Huebner, Maise Al Bakir, Miljana Tanic, Thomas B. Watkins, Emilia L. Lim, Ali M. Al Rashed, Daniel E. Cook, Rachel Rosenthal, Gareth Wilson, Alexander M. Frankell, Nnennaya Kanu, Kevin Litchfield, Nicolai J. Birkbak, Allan Hackshaw, Stephan Beck, Peter Van Loo, Mariam Jamal-Hanjani, the lung TRACERx Consortium, Charles Swanton, Nicholas McGranahan. Genomic transcriptomic evolution in TRACERx lung cancer and metastasis [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 1603.

Tumors are typically mosaics of mutant clones that have evolved from a common ancestral cell1–3. This intra-tumor heterogeneity (ITH) is thought to drive both neoplastic progression and acquired therapeutic resistance4–6. Availability of just one sample per tumor and moderate sequencing depth have limited systematic analysis of ITH during previous TCGA pan-cancer analyses7–9, confining the study of ITH to a small numbers of tumor samples and cancer types10–13. The molecular and histopathological causes of ITH and its prognostic significance have thus far remained uncertain14–17. To overcome these limitations, we used an analysis method called EXPANDS18 that estimates the proportion of cells harboring specific mutations from exome sequencing data, as well as other methods that quantify ITH15,19. We extrapolate the number of genetically diverse clonal subpopulations in 1,165 primary tumors among 12 different cancer types from TCGA and investigate mechanisms underpinning ITH as well as the correlation of ITH and genomic instability with prognosis. Lastly we validate the prognostic significance of genomic instability in an independent, high-density SNP-array dataset consisting of 2010 tumor samples, across seven additional cancer types. We found evidence of ITH in the vast majority of tumors. Driver gene mutations, prevalence of copy number gains and tumor microenvironment composition were significantly associated with increased ITH. Mutations in driver genes tended to have a characteristic clone size, suggesting differential fitness effects of those mutations. The detection of a mutation in a driver gene that typically appears in a small clone was a predictor of poor survival. In general, ITH was a universal biomarker of prognosis: across cancer types poor prognosis was associated with intermediate, rather than very low or high, levels of ITH. This was also true for the fraction of tumor genome affected by copy number alterations16,20: tumors with intermediate copy number burden (50 to 75% of the genome affected by copy number alterations) progressed faster than tumors with higher copy number burden, independent of cancer type. Chemo-radiation therapy administration was more efficient in decelerating tumor progression among patients with intermediate copy number burden than among patients with low or high copy number burden. These results were validated and confirmed in the independent SNP-array dataset. This study suggests a tradeoff exists between the costs and benefits of genomic instability21,22 that impacts both the evolvability and fitness of the tumor cell population. In the future, this tradeoff might be exploited to improve survival. In summary, we have shown that ITH is a universal feature of human cancers that predicts survival.

Lung cancer continues to be a leading cause of cancer-related incidence and mortality worldwide. High genomic intratumour heterogeneity (ITH) has been identified as a driving mechanism of therapeutic resistance and treatment failure, and hence presents a clinical challenge. In lung cancer, genomic ITH as the result of tumour evolution has been shown to be associated with poor outcome and decreased overall survival. Tracking non-small-cell lung cancer (NSCLC) evolution through therapy (Rx) (TRACERx) is a prospective multi-center longitudinal study designed to delineate tumour evolution from surgical resection to disease recurrence or cure. Since recruitment began in April 2014, preliminary findings from the TRACERx cohort have been presented for the first 100 patients and for an interim cohort of 421 patients. With follow-up of the last patients due to conclude at the end of 2025, we now present the completed TRACERx cohort with high-depth multi-region whole-exome sequencing of over 3, 000 regions from over 700 patients with early-stage NSCLC. Patient ethnicity, age, sex, smoking status are largely reflective of the United Kingdom early-stage NSCLC patient population, and surgically-resected tumours constitute stages I to III across adenocarcinoma, squamous cell carcinoma and other non-small-cell histologies. The completed TRACERx cohort also includes over 200 patients with sequencing of metastatic disease. This large cohort of paired primary-metastasis whole-exome sequencing enables further in-depth study of the timing and mode of metastatic divergence and dissemination in lung cancer. Our preliminary results replicating prior findings from TRACERx give insights on the influence of clonal tumour evolution on patient outcome. To this end, we investigated mutational and copy number differences between regions of the same primary lesion and constructed phylogenetic trees that enabled the recapitulation of tumour evolution. We traced mutations shared by or unique to individual subclones in primary and metastatic lesions, and examined their potential impact on subclonal immune evasion capabilities. We also characterised the contribution of mutational signatures to primary- and metastasis-unique mutations to evaluate the influence of mutational processes on tumour evolution and disease relapse. The completion of the TRACERx cohort will enable the reporting of the primary objectives of TRACERx prospective observational clinical trial on the association of ITH and clinical endpoints and the impact of adjuvant therapy upon ITH in relapsed disease. These data will also power the investigation of the drivers and correlates of lung cancer evolution, metastasis and immune evasion, and inform strategies for developing evolutionary biomarkers for lung cancer prognosis. Citation Format: Lydia Y. Liu, Kerstin Haase, Aino-Maija Leppä, Alexander Azizi, Emma Hazelwood, Takahiro Karasaki, Woody Z. Zhang, Charlotte Grieco, Katherine Honan, Olivia Lucas, Carlos Martinez Ruiz, Ariana Huebner, Selvaraju Veeriah, Cristina Naceur-Lombardelli, Andrew Rowan, Sophia Ward, Maise Al Bakir, Nnennaya Kanu, Crispin T. Hiley, Allan Hackshaw, David A. Moore, TRACERx Consortium, Simone Zaccaria, Nicholas McGranahan, Alexander M. Frankell, Mariam Jamal-Hanjani, Charles Swanton. Tracking the evolution of non-small-cell lung cancer: Completion of the TRACERx longitudinal cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6421.

Selection-driven tumor evolution with public goods leads to patterns of clonal expansion consistent with neutral growth.

Chromosomal instability (CIN) is a poor prognostic feature with high prevalence in breast cancer and is responsible for driving Somatic Copy Number Aberrations and Intratumour Heterogeneity (ITH) within subclones during breast cancer evolution. We have observed that SCNAs are enriched in metastatic samples, including gains in chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. However, there have thus far been no prospective, comprehensive studies of intratumor heterogeneity in breast cancer. We will present data from TRACERx Breast/SCANDARE a prospective, multicentre study of triple-negative breast cancer (TNBC) in which multi-region biopsies have been collected from primary TNBC prior to neoadjuvant treatment, and at longitudinal time points including surgery and relapse. We find prevalent intratumor heterogeneity in somatic mutations and SCNAs in the primary tumor prior to treatment. We have leveraged the rich clinical annotation in this cohort to correlate intratumor heterogeneity scores with key clinical outcomes, including treatment response (pathological complete response to neoadjuvant chemotherapy) and survival. We find that CIN manifests as oncogenic amplification on extrachromosomal DNA (ecDNA), which plays a pivotal role in driving drug resistance and tumor evolution. Through analysis of Whole Genome Sequencing data from 2936 breast tumors from the Genomics England breast cancer cohort, we have identified focal amplifications driven by ecDNA in 46.4% of HER2+ breast cancers. EcDNA were enriched in metastatic tumors and was associated with poor clinical outcomes. In addition to oncogenic amplifications such as HER2 derived from ecDNA during cancer evolution, ecDNAs contained immunomodulatory genes associated with reduced T cell infiltration. Further Immune-modulation by CIN results from loss of heterozygosity of the HLA locus (HLA LOH) and is a prevalent subclonal event in breast cancer. CIN is further drives haploid LOH, resulting in the high prevalence of whole genome doubling and further CIN in TNBC. Tumors are heterogeneous compositions of distinct clones with different compliments of SCNAs and varying levels of fitness, hence measuring the proliferation of individual clones to predict future evolutionary outcomes is likely to be critical. We have developed SPRINTER (Single-cell Proliferation Rate Inference in Non-homogeneous Tumours through Evolutionary Routes), a novel computational method to measure proliferation rates in individual tumour clones using single-cell whole-genome DNA sequencing data. We applied SPRINTER to 42,009 triple negative breast cancer cells, demonstrating significant proliferative heterogeneity between distinct tumor clones. Importantly, we show a correlation between higher proliferation rates and increased rates of somatic variants, suggesting proliferation links to clone evolvability. Taken together, these complimentary analyses provide evidence for the importance of CIN in driving ITH, selection, metastasis and immune evasion and provide a framework to determine recurrent evolutionary patterns in breast cancer evolution. Citation Format: C. Swanton. Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PL-01.

Background: Intra-tumor heterogeneity (ITH) plays a pivotal role in driving breast cancer progression and therapeutic resistance. Emerging evidence has indicated that the extent of genetic heterogeneity may serve as a clinically useful biomarker. While several studies have suggested the prognostic value of ITH in several cancer types, the clinical significance of genetic ITH and molecular portraits that correlated with different ITH levels were poorly understood in breast cancer. The establishment of algorithms estimating genetic ITH based on sequencing of bulk tumor DNA offered us an opportunity to explore the clinical implication of ITH in large breast cancer cohorts and, for the first time, to use integrative genomic analyses to reveal molecular portraits related to intra-tumor genetic heterogeneity. Methods: We assessed 916 female breast cancer patients from The Cancer Genome Atlas. Mutant-allele tumor heterogeneity (MATH) values were calculated from whole-exome sequencing data. We used integers nearest to the tertiles of the MATH values as cutoff points to divide the patients into three groups nearly equal in size. The association between MATH value and clinical characteristics was evaluated, followed by survival analyses in these different MATH groups. We then compared the rates of total non-silent somatic mutations among the different MATH groups, and further determined the mutations independently associated with high MATH by logistic regression adjusting for T classification and clinical subtypes. Similar methods, superadding somatic copy number alteration (SCNA) burden in logistic model, were used to evaluate SCNA events that were significantly associated with high MATH level. Gene enrichment between the high and rest MATH groups was analyzed using Gene Set Enrichment Analysis. Results: The patients were divided into low (MATH value lower than 33), intermediate (MATH between 33 and 46) and high (MATH higher than 46) MATH groups. High T stage, African American race, and triple-negative or basal-like subtype were associated with a higher MATH level (all P<0.001). In hormone receptor-positive and human epidermal growth factor receptor-negative patients, the high MATH group showed a tendency toward a worse overall survival (P=0.052); however, while in triple-negative breast cancer, both high and low MATH indicated a worse outcome (P=0.032). Furthermore, the TP53 mutation rate increased as MATH was elevated (P<0.001), whereas CDH1 mutations were correlated with a lower level of MATH (P=0.002). Several focal and arm-level SCNA events were more common in the high MATH group, including Chr8q24 with only the MYC gene in the “peak” region. Similarly, high MATH was associated with gene set enrichment related to the MYC pathway and proliferation. Conclusion: Our study extended the knowledge concerning the clinical role of ITH in breast cancer, especially the distinct pattern of prognostic values in different clinical subtypes, which may help promote the clinical utilization of genetic ITH. Our attempt at exploring the molecular features related to ITH might provide clues for the source and consequences of ITH, inspiring subsequent experiments investigating the laws underling tumor heterogeneity. Citation Format: Ma D, Jiang Y-Z, Liu X-Y, Liu Y-R, Yu K-D, Shao Z-M. Clinical and molecular relevance of intra-tumor genetic heterogeneity in breast cancer: Integrative analysis of data from The Cancer Genome Atlas [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-06-07.

Intratumor heterogeneity represents a major obstacle to effective cancer treatment and personalized medicine. However, investigators are now elucidating intratumor heterogeneity at the single-cell level due to improvements in technologies. Better understanding of the composition of tumors, and monitoring changes in cell populations during disease progression and treatment, will improve cancer diagnosis and therapeutic design. Measurements of intratumor heterogeneity may also be used as biomarkers to predict the risk of progression and therapeutic resistance. We summarize important considerations related to intratumor heterogeneity during tumor evolution. We also discuss experimental approaches that are commonly used to infer intratumor heterogeneity and describe how these methodologies can be translated into clinical practice.

The observation and analysis of intra-tumour heterogeneity (ITH), particularly in genomic studies, has advanced our understanding of the evolutionary forces that shape cancer growth and development. However, only a subset of the variation observed in a single tumour will have an impact on cancer evolution, highlighting the need to distinguish between functional and non-functional ITH. Emerging studies highlight a role for the cancer epigenome, transcriptome and immune microenvironment in functional ITH. Here, we consider the importance of both genetic and non-genetic ITH and their role in tumour evolution, and present the rationale for a broad research focus beyond the cancer genome. Systems-biology analytical approaches will be necessary to outline the scale and importance of functional ITH. By allowing a deeper understanding of tumour evolution this will, in time, encourage development of novel therapies and improve outcomes for patients.

Emerging trends and converging evidence in tumor evolution: A comprehensive review.

Mismatch repair deficient (MMRd) CRCs have high mutation/neo-antigen loads, leading to high immunogenicity and good immunotherapy response rates. We reasoned that the MMRd hypermutator phenotype should also promote intratumor heterogeneity (ITH) and evolvability; and investigated the genetic and immunological co-evolution in 69 regions from 6 localized and 13 metastatic MMRd CRCs by multi-region DNA-, RNA-sequencing and immunohistochemistry. All tumors had high truncal mutation loads (median: 44 mutations in 191 sequenced genes; whole exome equivalent: 1870 mutations). A median of 16.1% mutations per region were heterogeneous, indicating pervasive ITH. Phylogenetic analyses showed that metastases had diverged before subclonal diversification of the primary tumor in 75% of assessable cases. Thus, the ability to metastasize was frequently acquired early during tumor evolution. Driver aberrations evolved with a clear hierarchy: those in the WNT and RTK-MAPK pathways and in TGFbR-family members were almost always truncal (87.0%, 86.4% and 83.7%), indicating a critical role for cancer initiation. In contrast, genetic aberrations that are known to confer immune evasion (IE) were predominantly subclonal (71.4%) and parallel evolution of IE drivers occurred in 4/6 tumors that harboured any subclonal IE driver. This substantiates immune selection pressure as the main driver of Darwinian evolution during tumor progression. These IE drivers are known to confer resistance to checkpoint-inhibitor immunotherapy. ITH therefore needs to be addressed for predictive biomarker development. We quantified CD8 T-cell infiltrates as a surrogate measure of tumor immunogenicity; distinguishing tumors with low CD8 T-cell infiltrates (mean: 3.9% T-cells of all nucleated cells) and those with high infiltrates (mean: 12.2%). T-cell infiltrates showed high ITH in the latter group. This suggested a tumor-intrinsic setpoint, accompanied by marked variability in tumors with dense infiltrates. T-cell densities did not correlate with truncal mutation loads or heterogeneity metrics, questioning how immunogenicity is regulated. Phylogenetic analysis defined three patterns of IE evolution: tumors with subclonal, with pan-tumor, or without any identifiable IE drivers. CD8 T-cell abundance was highest in tumors with subclonal IE, supporting selection pressure from high CD8 T-cell infiltrates as the proximate cause for IE evolution. Tumors with pan-tumor IE showed low CD8 T-cell infiltrates. Surprisingly, tumors without IE drivers had the lowest CD8 T-cell abundance, indicating an alternative mechanism of immune escape. Low densities of CD8 T-cells at the tumor margin and low expression of T-cell chemo-attractants suggested impaired T-cell recruitment in these. Together, we show that immune recognition is a major driver of Darwinian evolution in MMRd CRCs and that immune infiltrates and IE drivers co-evolve interdependently. Whether sensitivity to checkpoint-inhibitor immunotherapy differs between the three phylogenetic MMRd CRC subtypes needs to be assessed in clinical trials. Citation Format: Benjamin R. Challoner, Andrew Woolston, David Lau, Marta Buzzetti, Louise J. Barber, Tom Lund, Harold B. Sansano, Katharina von Loga, Héctor Lázare-Iglesias, Ruwaida Begum, Richard Crux, David Cunningham, Ian Chau, Naureen Starling, Juan Ruiz-Bañobre, Tony Dhillon, Marco Gerlinger. Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR012.

Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death worldwide [1], generally arising on the background of chronic liver diseases such as chronic viral hepatitis, alcohol-induced liver injury, or fatty liver disease. So far, classification proposals for HCC based on molecular markers are not yet routinely applied in surgical pathology or clinical management of HCC patients. This stands in contrast to the classification of hepatocellular adenoma (HCA), which has been included in the latest WHO classification [2], and is the basis for a stratified management of HCA patients. Phenotypic intratumor heterogeneity in HCC with respect to morphology and differentiation grades within the same tumor is a well-known phenomenon to surgical pathologists. So far, genetic heterogeneity and the heterogeneity of biomarker expression in the surgical HCC specimens have not been systematically analyzed. However, to improve clinico-pathological classification systems and for the stratification of targeted therapies, it seems crucial to comprehensively characterize intratumor heterogeneity. In a systematic analysis of 23 treatment-naive unifocal HCC, we investigated individual tumors for morphologic, immunohistochemical and genetic intratumor heterogeneity as well as the association of these three features [3]. We found morphologic hetero-geneity in 87% of the tumors. Immunohistochemical heterogeneity with respect to five markers (CK7, CD44, AFP, EpCAM and glutamine synthethase) was present in 39% of cases and was always accompanied by morphologic heterogeneity. Clonal, i.e. genetic diversification was determined by sequencing the two most important HCC driver genes (TP53 and CTNNB1). Combining Sanger sequencing with deep sequencing techniques facilitated the discovery of low frequency mutations and mitigated the effect of wild-type contamination. A mean of 7 regions per tumor was sequenced (120 areas in total), and genetic intratumor heterogeneity was found in 22% of cases. Thus, already analysis of the two main HCC driver genes clearly revealed that mutations are not homogeneously present in all regions of an individual tumor. This was found especially for CTNNB1 mutations, but also for TP53 mutations. The thorough dissection of morphologic, immunohistochemical and genomic intratumor hetero-geneity in our study illustrates that the primary co-existence of different growth patterns can be associated with divers biomarker expression and TP53 or CTNNB1 gene mutations among wild type tumor cells. Somatic mutations of various other genes are described in liver cancer, e.g. AXIN1 (WNT signaling), ARID and MLL genes (epigenetic modifiers), CDKN2A and IRF2 (cell cycle regulators interrelated with TP53) or TERT promoter mutations [4]. Although not comprehensively analyzed so far, it can be expected that the picture of subclonality within single liver lesions is even more complex. Tracking the expansion of certain tumor clones might also elucidate the development of multifocal liver cancer or disease progression favoring intra- and extrahepatic metastasis. Intratumor heterogeneity has major implications for diagnosis and therapy of many solid cancers, indicating that a single tumor biopsy might not provide sufficient informative value regarding the molecular characteristics of the whole tumor. Primary renal cell cancer, as has been shown by Gerlinger et al. [5], displays common and private mutations throughout different, grossly demarcated tumor regions. Intratumor heterogeneity also limits the informative value of the widely used tissue microarray technique for studies on novel prognostic or predictive biomarkers. The histopathologic and molecular classification of a tumor, often determined by the mutational status of a certain target, has therapeutic implications, e.g. in colorectal cancer (EGFR) or gastrointestinal stroma tumors (c-KIT). In the era of targeted therapies, intratumor heterogeneity is a major challenge to successful cancer therapy since it may result in primary resistance or early evasion of treatment to chemotherapeutic or molecular targeted substances. In melanoma, resistant tumor clones tend to evade chemotherapies and overgrow due to a forced selection process as well as an adaption process during tumor evolution. Therapy-induced inflammatory processes result not only in phenotypic plasticity of the tumor and its genomic landscape, but also alter the composition of tumor-associated immune cells. This recomposition of the microenviroment can contribute to cancer evolution and therapy resistance [6]. In conclusion, determining the degree of intratumor heterogeneity might be seen as a biomarker by itself and have prognostic value for disease progression [7]. With the high-throughput techniques widely available now, we envision the systematic investigation of intratumor heterogeneity in different types of cancer in order to pinpoint its clinical relevance. We expect that intratumor tumor heterogeneity with clinical relevance for molecular targeted therapy approaches will be present probably not in all, but in many tumor entities. Figure 1 Implications of HCC intratumor heterogeneity for tumor classification and targeted therapy. A biopsy taken from tumor area 2 does not necessarily represent the whole tumor. This may result in a short falling tumor classification as type B, and potentially ...

Mismatch repair-deficient (MMRd) colorectal cancers (CRCs) have high mutation burdens, which make these tumours immunogenic and many respond to immune checkpoint inhibitors. The MMRd hypermutator phenotype may also promote intratumour heterogeneity (ITH) and cancer evolution. We applied multiregion sequencing and CD8 and programmed death ligand 1 (PD-L1) immunostaining to systematically investigate ITH and how genetic and immune landscapes coevolve. All cases had high truncal mutation burdens. Despite pervasive ITH, driver aberrations showed a clear hierarchy. Those in WNT/β-catenin, mitogen-activated protein kinase, and TGF-β receptor family genes were almost always truncal. Immune evasion (IE) drivers, such as inactivation of genes involved in antigen presentation or IFN-γ signalling, were predominantly subclonal and showed parallel evolution. These IE drivers have been implicated in immune checkpoint inhibitor resistance or sensitivity. Clonality assessments are therefore important for the development of predictive immunotherapy biomarkers in MMRd CRCs. Phylogenetic analysis identified three distinct patterns of IE driver evolution: pan-tumour evolution, subclonal evolution, and evolutionary stasis. These, but neither mutation burdens nor heterogeneity metrics, significantly correlated with T-cell densities, which were used as a surrogate marker of tumour immunogenicity. Furthermore, this revealed that genetic and T-cell infiltrates coevolve in MMRd CRCs. Low T-cell densities in the subgroup without any known IE drivers may indicate an, as yet unknown, IE mechanism. PD-L1 was expressed in the tumour microenvironment in most samples and correlated with T-cell densities. However, PD-L1 expression in cancer cells was independent of T-cell densities but strongly associated with loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and may contribute to a higher recurrence risk of MMRd CRCs with impaired CDX2 expression. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer characterized by extensive genomic complexity, rapid metastasis, and resistance to therapy. Our research focuses on the role of APOBEC3A (A3A), a cytidine deaminase enzyme, in promoting chromosomal instability (CIN) and intratumoral heterogeneity (ITH) as mechanisms driving PDAC progression and metastasis. Preliminary findings reveal that A3A drives CIN in a deaminase-independent manner, as demonstrated by dose-dependent increases in structural variants, micronuclei formation, and chromosomal aberrations. Furthermore, A3A expression significantly correlates with early tumor dissemination, enhanced metastatic colonization, and reduced survival, as shown in both human and murine models. While previous studies have highlighted A3A's molecular effects, they lack copy number signature analysis to systematically characterize CIN. Addressing this gap, our study aims to define A3A-driven copy number signatures in PDAC, providing critical insights into its role in tumor evolution and vulnerability to therapeutic interventions. Using a multi-modal approach, we integrate data from genetically engineered mouse models, human PDAC tissues, and cancer cell lines, employing bulk whole-genome sequencing (WGS) and advanced bioinformatics pipelines to uncover the full scope of A3A’s contributions to tumor evolution. We aim to demonstrate how A3A-mediated genomic instability accelerates the transition from pre-neoplastic lesions to advanced PDAC. Our findings will elucidate how A3A-mediated genomic instability accelerates the progression from pre-neoplastic lesions to advanced PDAC. By addressing critical gaps in the understanding of CIN and ITH, this study positions A3A as a compelling therapeutic target to mitigate genomic instability, reduce tumor heterogeneity, and ultimately improve clinical outcomes for patients with pancreatic cancer. Citation Format: Zhihui Zhang, Chunxu Gao, Sonja Wörmann, Peter Van Loo. APOBEC3A drives chromosomal instabilityand tumor evolution in pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7501.