Clonal Sweeps Research Articles

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancers

BackgroundThe encoding of cell intrinsic drug resistance states in breast cancer reflects the contributions of genomic and non-genomic variations and requires accurate estimation of clonal fitness from co-measurement of transcriptomic and genomic data. Somatic copy number (CN) variation is the dominant mutational mechanism leading to transcriptional variation and notably contributes to platinum chemotherapy resistance cell states. Here, we deploy time series measurements of triple negative breast cancer (TNBC) single-cell transcriptomes, along with co-measured single-cell CN fitness, identifying genomic and transcriptomic mechanisms in drug-associated transcriptional cell states.ResultsWe present scRNA-seq data (53,641 filtered cells) from serial passaging TNBC patient-derived xenograft (PDX) experiments spanning 2.5 years, matched with genomic single-cell CN data from the same samples. Our findings reveal distinct clonal responses within TNBC tumors exposed to platinum. Clones with high drug fitness undergo clonal sweeps and show subtle transcriptional reversion, while those with weak fitness exhibit dynamic transcription upon drug withdrawal. Pathway analysis highlights convergence on epithelial-mesenchymal transition and cytokine signaling, associated with resistance. Furthermore, pseudotime analysis demonstrates hysteresis in transcriptional reversion, indicating generation of new intermediate transcriptional states upon platinum exposure.ConclusionsWithin a polyclonal tumor, clones with strong genotype-associated fitness under platinum remained fixed, minimizing transcriptional reversion upon drug withdrawal. Conversely, clones with weaker fitness display non-genomic transcriptional plasticity. This suggests CN-associated and CN-independent transcriptional states could both contribute to platinum resistance. The dominance of genomic or non-genomic mechanisms within polyclonal tumors has implications for drug sensitivity, restoration, and re-treatment strategies.

Abstract 6931: Characterization of cancer evolution landscape based on accurate detection of somatic mutations in single tumor cells

Abstract Accurate detection of somatic mutations in single tumor cells is greatly desired as it allows us to quantify the single-cell mutation burden and construct the mutation-based phylogenetic tree. Here we developed scNanoSeq chemistry and profiled 842 single cells from 21 human breast cancer samples. The majority of the mutation-based phylogenetic trees comprise a characteristic stem evolution followed by the clonal sweep. We observed the subtype-dependent lengths in the stem evolution. To explain this phenomenon, we propose that the differences are related to different reprogramming required for different subtypes of breast cancer. Furthermore, we reason that the time that the tumor-initiating cell took to acquire the critical clonal-sweep-initiating mutation by random chance set the time limit for the reprogramming process. We refer to this model as a reprogramming and critical mutation co-timing (RCMC) subtype model. Next, in the sweeping clone, we observed that tumor cells undergo a branched evolution with rapidly decreasing selection. In the most recent clades, effectively neutral evolution has been reached, resulting in a substantially large number of mutational heterogeneities. Integrative analysis with 522-713X ultra-deep bulk whole genome sequencing (WGS) further validated this evolution mode. Mutation-based phylogenetic trees also allow us to identify the early branched cells in a few samples, whose phylogenetic trees support the gradual evolution of copy number variations (CNVs). Overall, the development of scNanoSeq allows us to unveil novel insights into breast cancer evolution. Citation Format: Muchun Niu, Yang Zhang, Jiayi Luo, Jefferson C. Sinson, Alastair M. Thompson, Chenghang Zong. Characterization of cancer evolution landscape based on accurate detection of somatic mutations in single tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6931.

Abstract 2286: Clonal sweep dynamics: A marker of tumor fitness and predictor of clinical outcomes

Abstract Cancer evolution is a complex process driven by cellular adaptations to environmental pressures. Understanding a tumor's evolutionary path is crucial for tailoring therapeutic strategies based on its genomic profile. We developed a method that estimates tumor 'fitness' (w) by analyzing the time of every clonal sweep. This is quantified by driver copy number or point mutations through analytical solutions derived from the branching process of tumor evolution. The method incorporates tumor size and growth rate, assessed through in-vivo BrdU staining, to determine the tumor's age, diversity, and aggressiveness. Using our method in the Yates et al. 2015 multi-region study, we analyzed 303 breast cancer tumors from 45 patients using whole-genome and exome sequencing (WES), focusing on ER+ (N=26) and ER- (N=19) subtypes. A negative correlation was observed between clonal cytoband alterations and fitness (ER+, R=-0.41; P=0.04; ER-, R=-0.72; P<0.001). Expanding the analysis with the METABRIC study (Curtis et al. 2012), clonal cytoband alterations (CA) were linked to survival outcomes for both ER+ and ER- subtypes. Additionally, in the TRACERx NSCLC study (Jamal-Hanjani et al. 2017) of 327 tumors from 100 patients who underwent WES, the median tumor fitness was associated with a higher risk of recurrence or death. Survival analyses are detailed in Table 1 below. Multivariate analysis was adjusted for tumor size, nodal status, and CD8α expression in the breast cancer study, and according to the authors' methodology in the TRACERx study, respectively. The observed tumor growth rates in both studies align with known doubling times, demonstrating our method's accuracy. This approach successfully identifies tumor profiles linked to worse outcomes in breast and NSCLC cancers. Our findings suggest that analyzing clonal composition in tumors can improve patient stratification, particularly in infiltrated tumors, potentially enhancing immunotherapy response due to increased neoantigen exposure. Table 1 Survival Analysis Study and Endpoint Parameter Univariate HR (95% CI) Multivariate HR (95% CI) METABRIC: ER- (N=128) on RFS CA > 3 (Ref: CA ≤ 3) 0.61 (0.40, 0.93), P=0.02 0.49 (0.32, 0.75), P<0.001 METABRIC: ER- (N=128) on OS CA > 3 (Ref: CA ≤ 3) 0.68 (0.47, 1), P=0.05 0.60 (0.4, 0.88), P=0.01 METABRIC: ER+ (N=458) on RFS CA > 3 (Ref: CA ≤ 3) 1.61 (1.33, 1.94), P<0.001 1.51 (1.25, 1.82), P<0.001 METABRIC: ER+ (N=458) on OS CA > 3 (Ref: CA ≤3) 1.44 (1.23, 1.68), P<0.001 1.38 (1.18, 1.61), P<0.001 TRACERx NSCLC (N=43) on RFS Med. w > 1.031 (Ref: w ≤ 1.031) 3.24 (1.38, 7.62),P=0.007 4.11 (1.12, 15.1), P=0.033 Citation Format: Luis E. Lara Gonzalez, Sherene Loi, Anthony T. Papenfuss, David L. Goode. Clonal sweep dynamics: A marker of tumor fitness and predictor of clinical outcomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2286.

Abstract 6243: Rapid autopsy reveals the interplay of tumor heterogeneity at genomic, transcriptomic, and spatial dimensions

Abstract Incomplete understanding of tumor heterogeneity across primary and metastatic sites often lead to ineffective cancer treatments. To comprehensively interrogate tumor heterogeneity at genomic, transcriptomic, and spatial levels, we established a novel rapid autopsy protocol to obtain multiregional tri-omic data consisted of whole exome sequencing, mRNA-sequencing, and multiplexed immunohistochemistry on primary and metastatic tumors and associated microenvironments (TMEs). We applied this protocol to six patients with various primary tumor types: non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), urothelial cancer, and one mixed case with both NSCLC and SCLC. A total of 50 tumor samples with paired tri-omic data were obtained across 16 different primary and metastatic organs to interrogate heterogeneities underlying tumor evolution and treatment resistance mechanisms. We constructed mutation-based phylogeny trees to reveal structural differences in tumor evolution trajectories across patients and infer heterogeneous tumor antigen landscape. We uncovered highly entropic phylogenetic structures having unique variants gained at each metastasis as well as low entropic structures with high sharing across sites. The mixed case had a clonal sweep structure with two metastases developed prior to the rest of the metastasis. In this case, older clones were shown to have strong association with APOBEC mutation signatures, enhanced subclonal mutation burden and loss of human leukocyte antigen heterozygosity as mechanisms of immune evasion. Integrating transcriptome and spatial profiles, we revealed that tumor intrinsic expressions and extrinsic immune infiltration levels covary with tissue types rather than with mutation-based phylogenetic clusters. Across patients, samples that had high similarities in mutational landscape varied in their pro-tumor expression programs and the cellular composition of TMEs. In particular, lung samples across patients had the highest effector T cell population and major histocompatibility complex (MHC) class I, II presentations compared to other tissue types. Contrasting small cell carcinoma (SCC) and adenocarcinoma (Adeno) samples from lung tissues further revealed that SCC had more immunosuppressive TMEs with downregulation of MHC class II. Liver metastasis samples were further characterized to have the most aggressive phenotypes enriched in genomic instability measured by aneuploidy compared to other metastatic sites. In sum, we present a novel technology and computational framework that enables a three-dimensional profiling of tumor heterogeneity. This work suggests that single-site biopsies are insufficient to capture tumor heterogeneity and calls for multi-modal integrations to design treatments that can overcome tumor-specific resistance mechanisms. Citation Format: Ning Yao, Rami Vanguri, Juber Patel, Jayon Lihm, Andrew Fisher, Irene Jarchum, Shigeaki Umeda, Hao Li, Scott Ely, Travis Hollmann, Christine Iacobuzio-Donahue, Benjamin Greenbaum. Rapid autopsy reveals the interplay of tumor heterogeneity at genomic, transcriptomic, and spatial dimensions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6243.

Abstract 6927: A refined view of pancreatic cancer genomic evolution through single-nucleus DNA sequencing

Abstract Numerous next-generation sequencing studies have provided an overview pancreatic ductal adenocarcinoma (PDAC)’s genomic evolution. But how its genome evolves through treatment and metastasis has not been extensively studied due to lack of samples and technical limitation of bulk sequencing on low-tumor purity samples. Herein we applied targeted single-nucleus DNA sequencing (snDNA-seq) to a cohort of 18 patients, each with >= 2 multiregional/longitudinal samples, totaling 65 samples. These included 5 early-stage resections, 11 stage IV autopsies and 2 biopsy-derived organoids taken pre- and post-treatment. We also developed a set of computational methods for this new datatype to delineate genomic evolution at high resolution. Despite higher sensitivity than bulk, snDNA-seq did not uncover significant subclonal single-nucleotide variations (SNVs) on our panel targeting 253 select genes for PDAC. But it detected a higher frequency of CDKN2A (72% against 30%) and SMAD4 (56% against 32%) alterations, mostly attributed to chromosomal deletions. Many were subclonal or only affected a few hundred base-pairs of the gene, making them elusive to bulk sequencing. Except for one case driven by BRCA2 mutations rather than the canonical KRAS oncogene, other patients had mostly linear phylogenies with more SNVs occurring before the most recent common ancestor (MRCA) of clones, for early/late-stage and longitudinal cases alike. This early fixation of drivers and rapid clonal sweep afterwards likely correlates with the particular aggressiveness of PDAC. Metastatic clones almost always fell towards the end of phylogenies and were shared among spatially separated sites, indicating late metastatic dissemination in molecular evolution time. Metastases to the liver and diaphragm appeared to be more genetically evolved than other sites, likely due to harsher selective pressure cast by the metastatic routes/distal microenvironments. 16 of 18 PDACs were observed to converge towards tumor cell-intrinsic TGF-β unresponsiveness by mutating various components of the pathway. Such convergent evolution usually happened at the primary site, indicating a strong selective advantage of the phenotype in the desmoplastic, nutrient-poor pancreas microenvironment. Continuous evolution was seen through treatment and metastasis, driven by seemingly random genome-scale copy number variations (CNVs) and focal amplification/deletions to genes such as KRAS, CDKN2A, SMAD4, MYC. These insights on PDAC’s genomic evolution inform more precision medicine efforts to come. Early fixation of driver SNVs sculpts a largely homogeneous disease that could be uniformly targeted. But special care should be taken to obviate resistance mechanisms conferred by continuously evolving CNV events- compared to SNVs, these mechanisms provide faster remodeling of the genome, and thus faster generation of new phenotypes and adaptation. Citation Format: Haochen Zhang, Palash Sashittal, Elias-Ramzey Karnoub, Akhil Jakatdar, Shigeaki Umeda, Nicolas Lecomte, Jungeui Hong, Katelyn Mullen, Akimasa Hayashi, Caitlin A. McIntyre, Benjamin J. Raphael, Christine A. Iacobuzio-Donahue. A refined view of pancreatic cancer genomic evolution through single-nucleus DNA sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6927.

Joint analysis of mutational and transcriptional landscapes in human cancer reveals key perturbations during cancer evolution

BackgroundTumors are able to acquire new capabilities, including traits such as drug resistance and metastasis that are associated with unfavorable clinical outcomes. Single-cell technologies have made it possible to study both mutational and transcriptomic profiles, but as most studies have been conducted on model systems, little is known about cancer evolution in human patients. Hence, a better understanding of cancer evolution could have important implications for treatment strategies.ResultsHere, we analyze cancer evolution and clonal selection by jointly considering mutational and transcriptomic profiles of single cells acquired from tumor biopsies from 49 lung cancer samples and 51 samples with chronic myeloid leukemia. Comparing the two profiles, we find that each clone is associated with a preferred transcriptional state. For metastasis and drug resistance, we find that the number of mutations affecting related genes increases as the clone evolves, while changes in gene expression profiles are limited. Surprisingly, we find that mutations affecting ligand-receptor interactions with the tumor microenvironment frequently emerge as clones acquire drug resistance.ConclusionsOur results show that lung cancer and chronic myeloid leukemia maintain a high clonal and transcriptional diversity, and we find little evidence in favor of clonal sweeps. This suggests that for these cancers selection based solely on growth rate is unlikely to be the dominating driving force during cancer evolution.

Abstract A027: Detecting and modeling frequency-dependent evolution in serially passaged primary triple negative breast cancer patient derived xenografts

Abstract Tumor evolution is a contributing factor to most failed cancer treatments. The intratumor heterogeneity of cellular phenotypes found in the tumor microenvironment acts as an evolutionary substate for cancer cells during tumorigenesis, subsequent growth, and after the patient is in the clinic. Selective forces imposed by certain medications can cause the emergence of a tumor with a resistant phenotype. Chemotherapies that target rapidly dividing cells will select for slower dividing ones which are less sensitive to such agents. However, many selective pressures acting on the tumor microenvironment are yet to be elucidated. For example, the effect one cancer cell has on another’s growth through competitive (i.e., the struggle for resources) or cooperative (e.g., exchange of growth factors) interactions remains poorly understood. Our central hypothesis is that cancer cells with distinct karyotypes will have a varying growth rate influenced by the karyotype landscape of the entire tumor. That is, we expect the fitness of a cancer cell to be largely determined by its karyotype and the karyotypes of its neighbors. Thus, we predict that frequency-dependent selection has a significant impact on clonal evolution in cancer. To test this, we have developed two novel methods for respectively identifying likely instances of frequency-dependent selection and modeling the long-term evolutionary trajectory in such cases. To detect frequency-dependent effects, we investigate the relationship between the frequency of one clone and the growth rate of all others (including itself). If a statistically significant correlation can be found, we proceed to modeling clonal evolution. To do this, we use a penalized least squares method and find the best-fitting parameterization of the replicator equation to the clonally resolved frequency data. This provides us with a payoff matrix describing the intensity of competition between each pair of clones. Furthermore, it allows us to model the long-term evolutionary dynamics of the tumor and to make predictions regarding co-existence of clones or clonal sweeps. Recently, investigators serially passaged primary triple negative breast cancer (TNBC) patient derived xenograft (PDX) tumors in NRG mice for over a year, inferring clonal frequencies at multiple timepoints using single cell whole genome (scWGS) and RNA sequencing (scRNA-seq). From this data, we were able to detect statistically significant frequency-dependent effects in the majority of serially passaged PDX tumors. Of these, most are predicted to result in a clonal sweep. Three of the PDX tumors were treated with cisplatin which revealed clone-specific drug response. This presents an opportunity for adaptive therapy scheduling which takes advantage of fitness tradeoffs under different contexts. A greater understanding of the effects frequency-dependent selection has on tumor evolution will contribute to the design of therapies intended to preclude or delay the emergence of resistance to treatment. Citation Format: Thomas A. Veith, Richard Beck, Noemi Andor. Detecting and modeling frequency-dependent evolution in serially passaged primary triple negative breast cancer patient derived xenografts [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A027.

Mutations, Bottlenecks, and Clonal Sweeps: How Environmental Carcinogens and Genomic Changes Shape Clonal Evolution during Tumor Progression.

The transition from a single, initiated cell to a full-blown malignant tumor involves significant genomic evolution. Exposure to carcinogens-whether directly mutagenic or not-can drive progression toward malignancy, as can stochastic acquisition of cancer-promoting genetic events. Mouse models using both carcinogens and germline genetic manipulations have enabled precise inquiry into the evolutionary dynamics that take place as a tumor progresses from benign to malignant to metastatic stages. Tumor progression is characterized by changes in somatic point mutations and copy-number alterations, even though any single tumor can itself have a high or low burden of genomic alterations. Further, lineage-tracing, single-cell analyses and CRISPR barcoding have revealed the distinct clonal dynamics within benign and malignant tumors. Application of these tools in a range of mouse models can shed unique light on the patterns of clonal evolution that take place in both mouse and human tumors.

The Relapse Mechanisms and Genomic Landscape Differ in KMT2A-r Pediatric Leukemia in Relation to Relapse Time

The genomic landscape and mechanisms driving relapse in KMT2A-rearranged ( KMT2A-r) infant and childhood acute lymphoblastic (ALL) and acute myeloid leukemia (AML) are not completely understood. We therefore studied 36 KMT2A-r ALL (n=19) and AML (n=17) patients of which 25 relapsed and 11 remained in remission. Twenty diagnose-relapse-germline trios and 5 multiple relapse samples were analyzed by whole genome (WGS) and whole exome sequencing (WES) and 30 patients longitudinally by using patient-specific mutations identified by WGS/WES, including the KMT2A-r (average coverage 3300X). The mutational burden increased from diagnosis to relapse and relapse evolved through branching evolution. Relapse was seeded by multiple diagnostic clones in 56%, by a single sweeping clone detected at diagnosis in 22%, and by a single sweeping clone not detected at diagnosis in 22%. Notably, the evolutionary patterns correlated to relapse time, where multiple diagnostic clones seeding relapse were connected to an earlier relapse with all very early relapse ALL (3/3, relapse <9 months from diagnosis) and half of the early AML relapse showing this pattern (2/4, relapse <1 year in complete remission, CR1). By contrast, later relapse was connected to a sweeping clone at relapse with 67% of early relapse ALL (>9 months from diagnosis) and 40% of late relapse AML (>1 year in CR1) showing this pattern. Pathway analysis showed that cell cycle genes, glucocorticoid signalling, purine metabolism, mismatch repair, and B-cell differentiation, were enriched in early relapse ALL (83%, 5/6) and included TP53, CREBBP, NT5C2 PMS2, PRPS2, NR3C1, IKZF1, with none of the very early relapse infant ALL harboring such alterations (n=4). Further, TP53 and IKZF1alterationsco-occurred (n=4/4). These results were validated in public data sets of 98 KMT2A-r ALL infants (n=84) and children (n=14) at diagnosis and relapse (n=24) and showed that 50% of early relapse ALL, and none of the 8 very early relapse ALL, had such alterations. Ultra-deep sequencing did not detect the CREBBP, NT5C2, PRPS2or TP53 mutations at diagnosis and manual inspection of the WGS reads failed to detect the PMS2 and NR3C1 deletions. In AML, TP53 and CCND3 alterations were maintained, and gain of WT1 was seen in late relapse AML. Signalling mutations were the most common type of mutations at diagnosis (64%) and relapse (56%) and the frequency was similar in patients that remained in remission and in those that relapsed (55% versus 60%). One infant ALL and four AML patients had multiple relapses, allowing us to study how the genetic landscape evolved across consecutive relapses. This showed a stepwise replacement of clones during treatment in agreement with a fitter clone that evolves under chemotherapeutic selective pressure. Longitudinal analysis allowed sensitive detection of residual leukemia cells and showed that the relapse clone could be detected at diagnosis in 64% of patients. Further, infants with >10% of molecularly detectable leukemia cells after induction therapy, had a high risk of a very early relapse. Ultra-deep sequencing allowed detection of the relapse clone up to 4 months before relapse. In 11 of the 30 patients (3 remission and 8 relapse), low-frequency KMT2A-fusion positive leukemic cells were found at remission outside of the MRD time points. Our longitudinal data also provided unique insights into clonal response to treatment by showing that 1) a change in therapy can favour the eradication of one clone and expansion of another, 2) a clone that initially was the most sensitive clone to therapy, was the one that eventually caused relapse, and 3), a diagnostic clone can be undetectable for a long time before expanding to cause relapse, suggesting that molecular monitoring with personal mutations is a powerful tool to follow response to therapy. These results provide new biological insights into the relapse mechanisms in KMT2A-r leukemia. The data shows different clonal evolution patters depending on when in time the patient relapsed, with very early relapse ALL being seeded by multiple diagnostic subclones and a paucity of acquired genetic alterations at relapse. By contrast, early relapse ALL was characterized by a single diagnostic clone seeding relapse by a clonal sweep along with acquired mutations in chemoresistance-associated genes. To validate and extend these findings, we are currently analyzing 11 additional infant relapse samples with WGS.

Longitudinal Analyses of Mutational Subclonal Architecture and Tumor Subtypes in Recurrent Bladder Cancer.

Longitudinal tumor sequencing of recurrent bladder cancer (BC) can facilitate the investigation of BC progression-associated genomic and transcriptomic alterations. In this study, we analyzed 18 tumor specimens including distant and locoregional metastases obtained during tumor progression for five BC patients using whole-exome and transcriptome sequencing. Along with the substantial level of intratumoral mutational heterogeneity across the cases, we observed that clonal mutations were enriched with known BC driver genes and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC)-associated mutation signatures compared with subclonal mutations, suggesting the genetic makeup for BC tumorigenesis associated with APOBEC deaminase activity was accomplished early in the cancer evolution. Mutation-based phylogenetic analyses also revealed temporal dynamics of mutational clonal architectures in which the number of mutational clones varied along the BC progression and notably was often punctuated by clonal sweeps associated with chemotherapy. The bulk-level transcriptome sequencing revealed frequent subtype switching in which transcriptionally defined BC subtypes may vary during tumor progression. Longitudinal whole-exome and transcriptome sequencing of recurrent BC may advance our understanding into the BC heterogeneity in terms of somatic mutations, cell clones and transcriptome-based tumor subtypes during disease progression.

Resolving the Pathogenesis of Anaplastic Wilms Tumors through Spatial Mapping of Cancer Cell Evolution.

While patients with intermediate-risk (IR) Wilms tumors now have an overall survival (OS) rate of almost 90%, those affected by high-stage tumors with diffuse anaplasia have an OS of only around 50%. We here identify key events in the pathogenesis of diffuse anaplasia by mapping cancer cell evolution over anatomic space in Wilms tumors. We spatially mapped subclonal landscapes in a retrospective cohort of 20 Wilms tumors using high-resolution copy-number profiling and TP53 mutation analysis followed by clonal deconvolution and phylogenetic reconstruction. Tumor whole-mount sections (WMS) were utilized to characterize the distribution of subclones across anatomically distinct tumor compartments. Compared with non-diffuse anaplasia Wilms tumors, tumors with diffuse anaplasia showed a significantly higher number of genetically distinct tumor cell subpopulations and more complex phylogenetic trees, including high levels of phylogenetic species richness, divergence, and irregularity. All regions with classical anaplasia showed TP53 alterations. TP53 mutations were frequently followed by saltatory evolution and parallel loss of the remaining wild-type (WT) allele in different regions. Morphologic features of anaplasia increased with copy-number aberration (CNA) burden and regressive features. Compartments demarcated by fibrous septae or necrosis/regression were frequently (73%) associated with the emergence of new clonal CNAs, although clonal sweeps were rare within these compartments. Wilms tumors with diffuse anaplasia display significantly more complex phylogenies compared with non-diffuse anaplasia Wilms tumors, including features of saltatory and parallel evolution. The subclonal landscape of individual tumors was constrained by anatomic compartments, which should be considered when sampling tissue for precision diagnostics.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

Abstract 5593: Clonal mutation burden and evolutionary dynamics analysis in metastatic gastro-esophageal adenocarcinoma (GEA) by error corrected whole-exome circulating tumor DNA sequencing

Abstract Introduction: The evolution of metastatic cancers over time can be assessed in circulating tumor DNA (ctDNA) but sequencing and bioinformatics tools for ultra-deep ctDNA whole-exome sequencing (WES) analysis are lacking. Methods: We developed ctDNA WES that only requires 15ng DNA to achieve sequencing depths of 1000-2000x. Error correction with molecular barcodes and duplex DNA detection allowed calling of mutations ≥0.5% variant frequency (VF). This pilot study applied ctDNA WES to plasma from 20 EGA patients (pts) and standard WES to matched biopsies in order to assess ctDNA WES performance and whether clonal mutation burden (cMB), a critical immunotherapy biomarker and important for neoantigen vaccine designs, differed between ctDNA and biopsies. We furthermore established a mutation and copy number data analysis pipeline using Bayesian clustering to define subclones and track their evolution during therapy in 3pts. Results: The median age of pts was 71y, 95% had distant metastases and 5% locally advanced EGAs. At a median sequencing depth of ????x after de-duplication, VFs of mutations in pre-treatment ctDNA was low (<2% VF) in 8 pts, and intermediate (2-10%) to high (>10%) in 12. Whether cMB differed in biopsies vs ctDNA was assessed in 7 pts with high VFs in ctDNA and good cancer purity in matching biopsy WES. The median cMB was 82 in biopsies and 111 in ctDNA. The increase was driven by 3 cases with 30%, 35% and 59% higher cMB in ctDNA vs biopsies. In two pts, most mutations that only appeared clonal in ctDNA were subclonal rather than absent in the primary tumor, indicating the subclonal presence of the metastasis progenitor clone. Subclonal intermixing in primary tumors hence limits the accurate identification of mutations that are clonal in metastatic disease. Evolutionary dynamics analyses in 3 pts who had good responses to chemotherapy before progression showed a major clonal sweep in one, supporting monoclonal resistance, and evolution of small subclones in two, indicating polyclonal resistance. A MEK1 K57T mutation evolved at resistance in a HER2 amplified EGA treated with trastuzumab+chemotherapy, demonstrating the utility to identify mechanisms of acquired resistance. Conclusions: ctDNA WES can assess the genetics of entire metastatic cancer cell populations over time and deconvolute their evolutionary trajectories. 43% pts had higher cMB in ctDNA compared to biopsies. Liquid biopsy analyses by WES may be superior to tissue-based WES for mutation burden analysis and neoantigen vaccine designs. ctDNA WES identified distinct evolutionary modes of resistance. A larger cohort is being analyzed to define how these differ clinically and whether they can be predicted from pre-treatment ctDNA WES. Efforts to increase the ctDNA WES sensitivity are ongoing as 8 pts had low ctDNA VFs which increased false negative rates. Citation Format: Neil McCafferty, Caroline Fong, Louise J. Barber, Andrew Woolston, Dimitrios Kleftogiannis, Taqia Rana, Susan Cromarty, Shannon Kidd, Ruwaida Begum, Ian Chau, Naureen Starling, David Cunningham, Marco Gerlinger. Clonal mutation burden and evolutionary dynamics analysis in metastatic gastro-esophageal adenocarcinoma (GEA) by error corrected whole-exome circulating tumor DNA sequencing. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5593.

OGC P04 Spatial sampling of Barrett's oesophagus reveals that tumour heterogeneity is not a useful predictor of progression to cancer

Abstract Background Intra-tumour heterogeneity has been well-described in oesophageal adenocarcinoma and Barrett's oesophagus (BE) segments also consist of multiple clones (groups of cells which share mutations). In BE there is some suggestion that the number of individual genetic clones within the segment and the diversity of the segment can be predictors of progression to cancer. However, this was with pre- whole genome sequencing (WGS) methods. In this study we consider the detailed spatial maps of ten patients with different disease trajectories, using WGS, to determine the heterogeneity and correlate it with their progression. Methods We performed WGS (50x) on 35 high-quality, frozen, endoscopic biopsies taken spatially from ten cases (8 males, 2 females, median age 75 (range 31–83). This included 4 long-term non-dysplastic (ND) patients with long BE segments and 6 patients with dysplasia. We used the copy number and purity information (from Battenberg) and the somatic mutation clustering information (from DPClust) to infer the clonal and subclonal architecture of individual biopsies and looked at the spatial relationship between biopsies within the segment. Results In both ND and dysplastic BE we saw cells with unrelated patterns of mutations, or clones, implying completely separate origins for different parts of the segments. This suggests independent or parallel evolution. There was a higher burden of shared (truncal) mutations in the dysplastic biopsies (p=0.049), indicating a more recent clonal sweep with some clones being outcompeted. Dysplastic samples had more subclonal copy number aberrations and more clonal driver mutations. In addition, most of the driver gene alterations in the dysplastic trees occurred early, whereas CDKN2A, the p16 locus, was the only truncal mutation found on the ND clone trees. We did not find the number of clones or the diversity of the segment to differ between the two groups. Conclusions Each individual patient showed complex, distinct genomic features and evolutionary trajectories. Some cases arose from a single ancestral clone, while others had few shared mutational variants suggesting multiple clones. Importantly, in this sample of cases we did not see any trend that the clonal diversity or number of clones correlated with progression to cancer. This is different to previous studies and highlights the importance of multiple sampling to determine the propensity for cancer progression even if the samples look similar histologically.

Correlation of changes in subclonal architecture with progression in the MMRF CoMMpass study

Multiple myeloma (MM) is a heterogeneous plasma cell proliferative disorder that arises from its premalignant precursor stages through a complex cascade of interactions between clonal mutations and co-evolving microenvironment. The temporo-spatial evolutionary trajectories of MM are established early during myelomatogenesis in precursor stages and retained in MM. Such molecular events impact subsequent disease progression and clinical outcomes. Identification of clonal sweeps of actionable gene targets in MM could reveal potential vulnerabilities that may exist in early stages and thus potentiate prognostication and customization of early therapeutic interventions. We have evaluated clonal evolution at multiple time points in 76 MM patients enrolled in the MMRF CoMMpass study. The major findings of this study are (a) MM progresses predominantly through branching evolution, (b) there is a heterogeneous spectrum of mutational landscapes that include unique actionable gene targets at diagnosis compared to progression, (c) unique clonal gains/ losses of mutant driver genes can be identified in patients with different cytogenetic aberrations, (d) there is a significant correlation between co-occurring oncogenic mutations/ co-occurring subclones e.g., with mutated TP53+SYNE1, NRAS+MAGI3, and anticorrelative dependencies between FAT3+FCGBP gene pairs. Such co-trajectories may synchronize molecular events of drug response, myelomatogenesis and warrant future studies to explore their potential for early prognostication and development of risk stratified personalized therapies in MM.

Abstract 3792: TRACERx: Mapping the evolution of metastases in non-small cell lung cancer

Abstract Background: Primary lung cancer is the leading cause of cancer-related mortality, with metastatic disease being responsible for the majority of deaths. To gain insight into the lethal process of metastasis, we report on the longitudinal evolutionary analysis of the TRACERx 421 paired primary-metastasis cohort. Methods: 712 tumor samples, of which 485 were primary tumor and 227 were metastatic samples, from 129 metastatic non-small cell lung cancer (NSCLC) patients with detailed clinical annotation were collected from 18 UK hospital sites and whole exome sequenced. Mutations and copy number events were integrated to resolve the evolutionary history of each tumor. Results: We observe that metastases generally diverge relatively late in molecular time, after the majority of mutations in the primary tumor have accumulated, with a substantial minority (33%) diverging prior to the last clonal sweep in the primary tumor. For this minority of cases, divergence is estimated to have occurred at tumor volumes below the limit of computed tomography (CT) detection. Our extensively sampled cohort reveals that sampling bias may result in erroneous inference of metastatic trajectories. 79% of metastases diverging after the last clonal sweep in the primary tumor would be misclassified as diverging prior to the last clonal sweep if only a single region of the primary tumor is considered. Patterns of dissemination range from monoclonal, involving a single metastatic clone (68% - where metastatic potential is likely acquired once in the life-history of the tumor), to polyclonal and polyphyletic (17%), where metastatic potential may have arisen multiple times during lung cancer development, or at a single time point early in the development of the tumor. We find that thoracic lymph node disease resected at surgery was responsible for less than 20% of subsequent disease dissemination, suggesting that lymph nodes likely represent a hallmark of metastatic potential rather than a gateway to further metastases. Furthermore, we observe that clones which seed the metastases are generally dominant within the primary, reflecting positive selection and acquisition of subclonal mutations in specific cancer genes (e.g. RB1, PIK3CA). In squamous cell carcinomas, we find that non-metastatic primary tumors show no significant evidence of positive subclonal selection. We find that 35% of metastases harbor driver mutations not identified in the primary tumor and identify somatic copy number alterations that are enriched in metastases (e.g. CCND1 gains in lung adenocarcinoma). Conclusions: These data highlight the potential to apply evolutionary measures to primary tumors to predict metastatic risk, the limitations to current screening approaches particularly for early tumor divergence, and the importance of future precision adjuvant therapies to target disseminated micro-metastatic clones. Citation Format: Ariana Huebner, Maise Al Bakir, Carlos Martinez Ruiz, Kristiana Grigoriadis, Thomas B. Watkins, Oriol Pich, David A. Moore, Selvaraju Veeriah, Sophia Ward, Joanne Laycock, Diana Johnson, Andrew Rowan, Maryam Razaq, Mita Akther, Cristina Naceur-Lombardelli, Sonya Hessey, Michelle Dietzen, Emma Colliver, Alexander M. Frankell, Emilia Lim, Takahiro Karasaki, Christopher Abbosh, Crispin T. Hiley, Mark S. Hill, Daniel Cook, Gareth Wilson, TRACERx consortium, Allan Hackshaw, Nicolai J. Birkbak, Simone Zaccaria, Mariam Jamal-Hanjani, Charles Swanton, Nicholas McGranahan. TRACERx: Mapping the evolution of metastases in non-small cell lung cancer [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 3792.

Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

Quantifying bacterial evolution in the wild: A birthday problem for Campylobacter lineages.

Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the ‘birthday problem’. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10−6 s/s/y) and Campylobacter jejuni (3.4 x 10−6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time frame–analogous to a shared birthday–and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species.

Abstract 3123: Lung cancer evolutionary trajectories in PEACE

Abstract Introduction: Studies of cancer evolution have relied on archival tissue surplus to diagnostic requirements from living patients obtained in early stage disease and less commonly relapsed/metastatic disease. PEACE (Posthumous Evaluation of Advanced Cancer Environment) is a national research autopsy study aiming to understand the biological processes driving metastatic disease and cancer evolution. Experimental procedures: Patients recruited into the national TRACERx (TRAcking Cancer Evolution through therapy (Rx)) lung study who subsequently developed metastatic disease were enrolled into PEACE. Here we present a cohort of 15 TRACERx/PEACE patients in whom multi-region tumor sampling was performed at diagnosis +/- relapse and at autopsy. Fresh frozen tissue was subjected to whole-exome sequencing (mean depth 390) and germline DNA from blood was used for reference. Single nucleotide variants (SNVs) were identified using VarScan2 and the subclonal composition of each tumor was inferred using PyClone and used to reconstruct phylogenetic trees. Summary of data: Disease progression was associated with increased genomic complexity. Different patterns of progression occurred; monoclonal/monophyletic, polyclonal/monophyletic and polyclonal/polyphyletic dissemination. Both early and late divergence relative to the last clonal sweep were observed. Putative drivers were found to occur both clonally and subclonally. SNVs and copy number aberrations were used to reconstruct migration patterns. Conclusions: Preliminary analysis in this cohort demonstrates increasing genomic complexity with disease progression and variation in patterns of metastatic dissemination. We are yet to establish the impact of the tumor and immune microenvironment on such patterns as well as clinical presentation and outcome. Ongoing PEACE analysis includes study of the somatic copy number landscape and the characterisation of subclones that seed metastases. Patient & sample characteristicsN (%)Total patients15Median age (IQR)73 (65 - 80)Female sex (%)6 (40%)Histological subtypeAdenocarcinoma7 (47%)Squamous cell carcinoma5 (33%)Large cell carcinoma2 (13%)Adenosquamous carcinoma1 (7%)Treatment receivedRadiotherapy8 (53%)Chemotherapy6 (40%)Immunotherapy5 (33%)Targeted therapy4 (27%)Smoking statusCurrent smoker2 (13%)Ex-smoker12 (80%)Never smoker1 (7%)Total metastases sampled289Median samples per patient (range)19 (5 - 41)Number of samples per patient5-104 (27%)11-205 (33%)>206 (40%)Number of tissue types sampled17 Citation Format: Ariana Huebner, Sonya Hessey, Cristina Naceur-Lombardelli, Mita Akther, Selvaraju Veeriah, Maise Al Bakir, David Moore, Simone Zaccaria, Nicholas McGranahan, Charles Swanton, Mariam Jamal-Hanjani, TRACERx and PEACE consortium. Lung cancer evolutionary trajectories in PEACE [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3123.

Spatial Genomic Heterogeneity in Multiple Myeloma: Surrogate Markers and Its Significance for Understanding the Evolutionary Processes Leading to Relapse

IntroductionMultiple Myeloma (MM) frequently presents with genomic variation between individual cancer foci, which is also termed spatial heterogeneity (SH). However, the extent of SH differs considerably between patients with some having extensive SH while others show homogeneous mutational profiles within the bone marrow (BM). Since SH poses a significant challenge to personalized therapy, surrogate markers for its extent would be useful clinically. In this respect an understanding of the spatial evolutionary patterns taking place during MM treatment and the clonal architecture they give rise to at relapse would also be of fundamental importance. To address these important points we have analyzed paired samples from multiple BM sites collected at baseline (n=52 patients) or in a longitudinal fashion during treatment (n=30).Patients and MethodsA genomic analysis was performed on iliac crest BM and CT-guided fine needle aspirates from distinct anatomical sites from 52 newly diagnosed patients. The impact of treatment on SH was analyzed in 30 patients with a median number of 6 samples per patient (range 4-14). Plasma cells were CD138-enriched and underwent whole exome sequencing using an Illumina HiSeq 2500. Sequencing data were aligned using BWA. Mutations were identified using MuTect. Copy number aberrations were derived from Illumina HumanOmni 2.5 bead chip data using ASCAT. Subclonal reconstruction was performed using SciClone. Statistical analyses were carried out using R packages.ResultsWe investigated whether the extent of SH was associated with clinical features and found that age, an adverse prognostic factor, was positively correlated with SH (P=0.01). Patients over the age of 60 had a 3-fold higher proportion of private mutations compared to younger patients (median 15 vs. 5%). Hypothetically, this could reflect the longer evolutionary time period to MM arising at older ages. The size of the biopsied FLs was also significantly associated with the proportion of private mutations (P <0.001), with large FLs (>2.5 cm) having the highest values. Of note, a linear model including age and FL size explained 49% of the variation in SH. In contrast, neither the ISS, adverse molecular markers identified at the iliac crest, the number of FLs, nor the anatomical distance between investigated sites correlated with SH. In summary, we show that SH is increased in elderly patients and/or patients with large FLs.Next, we investigated the impact of treatment on the spatial clonal architecture. For patients who had achieved a CR, we expected relapse to be dominated by a limited number of selected clones and as a result less SH. Indeed, analyzing samples derived from multiple sites at baseline and at subsequent relapses, the predominant pattern was characterized by sweeps of advanced clones resulting in BM-wide replacement of previous clones. Of note, evidence for clonal sweeps was also seen in patients with stable disease according to IMWG criteria, which is a perplexing observation since stable serological parameters do not seem to be consistent with major sub-clonal changes.In contrast to cases with clonal sweeps, there were also patients with multiple site-specific clones at relapse. On the one hand, “mixed responses” of FLs, which are frequently seen in medical imaging after multiple relapses, could be related to this pattern of pronounced SH. On the other hand, we found private mutations affecting the same genes or pathways in patients with site-specific subclones, indicating parallel evolution. In this context, one patient showed distinct KRAS mutations which affected the exact same amino acid (Gly12Val vs. Gly12Asp), emphasizing that treatment could select for multiple clones with similar or even identical features. This observation may explain, why individual patients still respond to MAPK pathway inhibitors despite pronounced SH.ConclusionsWe provide new insights into the biology of MM progression, which has implications for diagnostic and treatment strategies. The strong association of private mutations with age and FL size may allow for the identification of patients with increased levels of SH for whom treatment approaches can be modified. The existence of clonal sweeps of aggressive clones, which replace previously dominant clones, even in poorly responding patients, highlights the need for regular molecular testing, especially if personalized treatment is intended. DisclosuresBarlogie:Millenium Pharmaceuticals: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding. Davies:Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Morgan:Takeda: Consultancy, Honoraria; Bristol Myers: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding.