Relapses in early-stage follicular lymphoma frequently develop via a divergent evolution from their clonally related precursor cells.

Follicular lymphoma (FL) develops through a stepwise acquisition of cooperative genetic changes with t(14;18)(q32;q21)/IGH::BCL2 occurring early at the pre-B stage of B-cell development. Patients with FL typically show an indolent clinical course, remitting and relapsing with the eventual development of resistance to treatments. Interestingly, the majority of transformed FL do not progress directly from FL but originate from their clonally related lymphoma precursor (CLP) cells. To examine whether such divergent tumour evolution also underpins the relapses in patients with early-stage FL, we investigated by targeted next-generation sequencing 13 cases (stage I = 9, stage II = 4), who showed complete remission (mean: 5 years; range: 1-11.5 years) following local radiotherapy but subsequently relapsed (≥2 in 5). A clonal relationship between the diagnostic FL and relapses was confirmed in 11 cases. In six cases, common and distinct variants were seen between the paired diagnostic and relapsed lymphomas, indicating their divergent evolution from a CLP. In two cases, different B-cell clones were involved in the diagnostic and relapsed lymphomas, including one case involving two different BCL2 translocations. In the remaining five cases, the relapsed lymphoma developed via a linear progression (n = 4) or a mixed evolutionary path (n = 1). These findings may bear important implications in the routine diagnosis and management of relapsed FL. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The evolutionary history of metastatic pancreatic neuroendocrine tumours reveals a therapy driven route to high-grade transformation.

Tumour evolution with acquisition of more aggressive disease characteristics is a hallmark of disseminated cancer. Metastatic pancreatic neuroendocrine tumours (PanNETs) in particular may progress from a low/intermediate to a high-grade disease. The aim of this work was to understand the molecular mechanisms underlying metastatic progression as well as PanNET transformation from a low/intermediate to a high-grade disease. We performed multi-omics analysis (genome/exome sequencing, total RNA-sequencing and methylation array) of 32 longitudinal samples from six patients with metastatic low/intermediate grade PanNET. The clonal composition of tumour lesions and underlying phylogeny of each patient were determined with bioinformatics analyses. Findings were validated in post-alkylating chemotherapy samples from 24 patients with PanNET using targeted next generation sequencing. We validate the current PanNET evolutionary model with MEN1 inactivation that occurs very early in tumourigenesis. This was followed by pronounced genetic diversity on both spatial and temporal levels, with parallel and convergent tumour evolution involving the ATRX/DAXX and mechanistic target of the rapamycin (mTOR) pathways. Following alkylating chemotherapy treatment, some PanNETs developed mismatch repair deficiency and acquired a hypermutational phenotype. This was validated among 16 patients with PanNET who had high-grade progression after alkylating chemotherapy, of whom eight had a tumour mutational burden >50 (50%). In comparison, among the eight patients who did not show high-grade progression, 0 had a tumour mutational burden >50 (0%; odds ratio 'infinite', 95% confidence interval 1.8 to 'infinite', p = 0.02). Our findings contribute to broaden the understanding of metastatic/high-grade PanNETs and suggests that therapy driven disease evolution is an important hallmark of this disease. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Breast cancer patient-derived organoids for the investigation of patient-specific tumour evolution.

BACKGROUND: A reliable preclinical model of patient-derived organoids (PDOs) was developed in a case study of a 69-year-old woman diagnosed with breast cancer (BC) to investigate the tumour evolution before and after neoadjuvant chemotherapy and surgery. The results were achieved due to the development of PDOs from tissues collected before (O-PRE) and after (O-POST) treatment. METHODS: PDO cultures were characterized by histology, immunohistochemistry (IHC), transmission electron microscopy (TEM), scanning electron microscopy (SEM), confocal microscopy, flow cytometry, real-time PCR, bulk RNA-seq, single-cell RNA sequencing (scRNA-seq) and drug screening. RESULTS: Both PDO cultures recapitulated the histological and molecular profiles of the original tissues, and they showed typical mammary gland organization, confirming their reliability as a personalized in vitro model. Compared with O-PRE, O-POST had a greater proliferation rate with a significant increase in the Ki67 proliferation index. Moreover O-POST exhibited a more stem-like and aggressive phenotype, with increases in the CD24low/CD44low and EPCAMlow/CD49fhigh cell populations characterized by increased tumour initiation potential and multipotency and metastatic potential in invasive lobular carcinoma. Analysis of ErbB receptor expression indicated a decrease in HER-2 expression coupled with an increase in EGFR expression in O-POST. In this context, deregulation of the PI3K/Akt signalling pathway was assessed by transcriptomic analysis, confirming the altered transcriptional profile. Finally, transcriptomic single-cell analysis identified 11 cell type clusters, highlighting the selection of the luminal component and the decrease in the number of Epithelial-mesenchymal transition cell types in O-POST. CONCLUSION: Neoadjuvant treatment contributed to the enrichment of cell populations with luminal phenotypes that were more resistant to chemotherapy in O-POST. PDOs represent an excellent 3D cell model for assessing disease evolution.

Disentangling the roles of aneuploidy, chromosomal instability and tumour heterogeneity in developing resistance to cancer therapies.

Aneuploidy is defined as the cellular state of having a number of chromosomes that deviates from a multiple of the normal haploid chromosome number of a given organism. Aneuploidy can be present in a static state: Down syndrome individuals stably maintain an extra copy of chromosome 21 in their cells. In cancer cells, however, aneuploidy is usually present in combination with chromosomal instability (CIN) which leads to a continual generation of new chromosomal alterations and the development of intratumour heterogeneity (ITH). The prevalence of cells with specific chromosomal alterations is further shaped by evolutionary selection, for example, during the administration of cancer therapies. Aneuploidy, CIN and ITH have each been individually associated with poor prognosis in cancer, and a wealth of evidence suggests they contribute, either alone or in combination, to cancer therapy resistance by providing a reservoir of potential resistant states, or the ability to rapidly evolve resistance. A full understanding of the contribution and interplay between aneuploidy, CIN and ITH is required to tackle therapy resistance in cancer patients. However, these characteristics often co-occur and are intrinsically linked, presenting a major challenge to defining their individual contributions. Moreover, their accurate measurement in both experimental and clinical settings is a technical hurdle. Here, we attempt to deconstruct the contribution of the individual and combined roles of aneuploidy, CIN and ITH to therapy resistance in cancer, and outline emerging approaches to measure and disentangle their roles as a step towards integrating these principles into cancer therapeutic strategy.

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis.

Structural variants (SVs) represent a major source of aberration in tumour genomes. Given the diversity in the size and type of SVs present in tumours, the accurate detection and interpretation of SVs in tumours is challenging. New classes of complex structural events in tumours are discovered frequently, and the definitions of the genomic consequences of complex events are constantly being refined. Detailed analyses of short-read whole-genome sequencing (WGS) data from large tumour cohorts facilitate the interrogation of SVs at orders of magnitude greater scale and depth. However, the inherent technical limitations of short-read WGS prevent us from accurately detecting and investigating the impact of all the SVs present in tumours. The expanded use of long-read WGS will be critical for improving the accuracy of SV detection, and in fully resolving complex SV events, both of which are crucial for determining the impact of SVs on tumour progression and clinical outcome. Despite the present limitations, we demonstrate that SVs play an important role in tumourigenesis. In particular, SVs contribute significantly to late-stage tumour development and to intratumoural heterogeneity. The evolutionary trajectories of SVs represent a window into the clonal dynamics in tumours, a comprehensive understanding of which will be vital for influencing patient outcomes in the future. Recent findings have highlighted many clinical applications of SVs in cancer, from early detection to biomarkers for treatment response and prognosis. As the methods to detect and interpret SVs improve, elucidating the full breadth of the complex SV landscape and determining how these events modulate tumour evolution will improve our understanding of cancer biology and our ability to capitalise on the utility of SVs in the clinical management of cancer patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Leveraging single-cell sequencing to unravel intratumour heterogeneity and tumour evolution in human cancers.

Intratumour heterogeneity (ITH) and tumour evolution are well-documented phenomena in human cancers. While the advent of next-generation sequencing technologies has facilitated the large-scale capture of genomic data, the field of single-cell genomics is nascent but rapidly advancing and generating many new insights into the complex molecular mechanisms of tumour biology. In this review, we provide an overview of current single-cell DNA sequencing technologies, exploring how recent methodological advancements have enumerated new insights into ITH and tumour evolution. Areas highlighted include the potential power of single-cell genome sequencing studies to explore evolutionary dynamics contributing to tumourigenesis through to progression, metastasis, and therapy resistance. We also explore the use of in situ sequencing technologies to study ITH in a spatial context, as well as examining the use of single-cell genomics to perform lineage tracing in both normal and malignant tissues. Finally, we consider the use of multimodal single-cell sequencing technologies. Taken together, it is hoped that these many facets of single-cell genome sequencing will improve our understanding of tumourigenesis, progression, and lethality in cancer, leading to the development of novel therapies. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Recent Advances in Pathology: the 2022 Annual Review Issue of The Journal of Pathology.

The 2022 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 15 invited reviews on research areas of growing importance in pathology. This year, the articles include those that focus on digital pathology, employing modern imaging techniques and software to enable improved diagnostic and research applications to study human diseases. This subject area includes the ability to identify specific genetic alterations through the morphological changes they induce, as well as integrating digital and computational pathology with 'omics technologies. Other reviews in this issue include an updated evaluation of mutational patterns (mutation signatures) in cancer, the applications of lineage tracing in human tissues, and single cell sequencing technologies to uncover tumour evolution and tumour heterogeneity. The tissue microenvironment is covered in reviews specifically dealing with proteolytic control of epidermal differentiation, cancer-associated fibroblasts, field cancerisation, and host factors that determine tumour immunity. All of the reviews contained in this issue are the work of invited experts selected to discuss the considerable recent progress in their respective fields and are freely available online (https://onlinelibrary.wiley.com/journal/10969896). © 2022 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Extrachromosomal DNA-relieving heredity constraints, accelerating tumour evolution.

Oncogene amplification on extrachromosomal DNA (ecDNA) provides a mechanism by which cancer cells can rapidly adapt to changes in the tumour microenvironment. These circular structures contain oncogenes and their regulatory elements, and, lacking centromeres, they are subject to unequal segregation during mitosis. This non-Mendelian mechanism of inheritance results in increased tumour heterogeneity with daughter cells that can contain increasingly amplified oncogene copy number. These structures also contain favourable epigenetic modifications including transcriptionally active chromatin, further fuelling positive selection. ecDNA drives aggressive tumour behaviour, is related to poorer survival outcomes and provides mechanisms of drug resistance. Recent evidence suggests one in four solid tumours contain cells with ecDNA structures. The concept of tumour evolution is one in which cancer cells compete to survive in a diverse tumour microenvironment under the Darwinian principles of variation and fitness heritability. Unconstrained by conventional segregation constraints, ecDNA can accelerate intratumoral heterogeneity and cellular fitness. In this review, we highlight some of the recent discoveries underpinning this process.

Multiregion human bladder cancer sequencing reveals tumour evolution, bladder cancer phenotypes and implications for targeted therapy.

We present an evolutionary analysis of the relative time of genetic events underlying tumorigenesis in human bladder cancers from 10 whole cystectomy specimens using multiregional whole-exome sequencing. We timed bladder cancer drivers, mutational signatures, ploidy and copy number alterations, provided evidence for kataegis and correlated alterations with tumour areas and histological phenotypes. We found that: (1) heterogeneous tumour areas/phenotypes had distinct driver mutations, (2) papillary-invasive tumours divided early into two parallel evolving branches and (3) parallel evolution of subclonal driver mutations occurred. APOBEC mutational signatures were found to be very early events, active in carcinoma in situ, and often remained a dominant source of mutations throughout tumour evolution. Genetic progression from carcinoma in situ followed driver mutations in NA13/FAT1, ZBTB7B or EP300/USP28/KMT2D. Our results point towards a more diverse mutational trajectory of bladder tumorigenesis and underpin the importance of timing of mutational processes and clonal architecture in bladder cancer as important aspects for successful prognostication and therapy. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data.

BACKGROUND: A large number of algorithms is being developed to reconstruct evolutionary models of individual tumours from genome sequencing data. Most methods can analyze multiple samples collected either through bulk multi-region sequencing experiments or the sequencing of individual cancer cells. However, rarely the same method can support both data types. RESULTS: We introduce TRaIT, a computational framework to infer mutational graphs that model the accumulation of multiple types of somatic alterations driving tumour evolution. Compared to other tools, TRaIT supports multi-region and single-cell sequencing data within the same statistical framework, and delivers expressive models that capture many complex evolutionary phenomena. TRaIT improves accuracy, robustness to data-specific errors and computational complexity compared to competing methods. CONCLUSIONS: We show that the application of TRaIT to single-cell and multi-region cancer datasets can produce accurate and reliable models of single-tumour evolution, quantify the extent of intra-tumour heterogeneity and generate new testable experimental hypotheses.

How to analyse the spatiotemporal tumour samples needed to investigate cancer evolution: A case study using paired primary and recurrent glioblastoma.

Many traits of cancer progression (e.g., development of metastases or resistance to therapy) are facilitated by tumour evolution: Darwinian selection of subclones with distinct genotypes or phenotypes that enable such progression. Characterising these subclones provide an opportunity to develop drugs to better target their specific properties but requires the accurate identification of somatic mutations shared across multiple spatiotemporal tumours from the same patient. Current best practices for calling somatic mutations are optimised for single samples, and risk being too conservative to identify shared mutations with low prevalence in some samples. We reasoned that datasets from multiple matched tumours can be used for mutual validation and thus propose an adapted two-stage approach: (1) low-stringency mutation calling to identify mutations shared across samples irrespective of the weight of evidence in a single sample; (2) high-stringency mutation calling to further characterise mutations present in a single sample. We applied our approach to three-independent cohorts of paired primary and recurrent glioblastoma tumours, two of which have previously been analysed using existing approaches, and found that it significantly increased the amount of biologically relevant shared somatic mutations identified. We also found that duplicate removal was detrimental when identifying shared somatic mutations. Our approach is also applicable when multiple datasets e.g. DNA and RNA are available for the same tumour.

Chronic lymphocytic leukaemia genomics and the precision medicine era.

Massive genomic analyses have underscored the diversity of chronic lymphocytic leukaemia (CLL) between patients. Genetic heterogeneity of tumour clones within a patient may fuel tumour evolution. Several recurrently deregulated intra-cellular pathways are candidates for targeted therapies that are very promising and are dramatically changing clinical patients' perspectives. In this review we present an overview of the genetic and epigenetic features of CLL and their clinical and biological implications.

Cutting edge genomics reveal new insights into tumour development, disease progression and therapeutic impacts in multiple myeloma.

Multiple Myeloma (MM) is a haematological malignancy characterised by the clonal expansion of plasma cells (PCs) within the bone marrow. Despite advances in therapy, MM remains a largely incurable disease with a median survival of 6 years. In almost all cases, the development of MM is preceded by the benign PC condition Monoclonal Gammopathy of Undetermined Significance (MGUS). Recent studies show that the transformation of MGUS to MM is associated with complex genetic changes. Understanding how these changes contribute to evolution will present targets for clinical intervention. We discuss three models of MM evolution; the linear, the expansionist and the intraclonal heterogeneity models. Of particular interest is the intraclonal heterogeneity model. Here, distinct populations of MM PCs carry differing combinations of genetic mutations. Acquisition of additional mutations can contribute to subclonal lineages where "driver" mutations may influence selective pressure and dominance, and "passenger" mutations are neutral in their effects. Furthermore, studies show that clinical intervention introduces additional selective pressure on tumour cells and can influence subclone survival, leading to therapy resistance. This review discusses how Next Generation Sequencing approaches are revealing critical insights into the genetics of MM development, disease progression and treatment. MM disease progression will illuminate possible mechanisms underlying the tumour.

Constraints in cancer evolution.

Next-generation deep genome sequencing has only recently allowed us to quantitatively dissect the extent of heterogeneity within a tumour, resolving patterns of cancer evolution. Intratumour heterogeneity and natural selection contribute to resistance to anticancer therapies in the advanced setting. Recent evidence has also revealed that cancer evolution might be constrained. In this review, we discuss the origins of intratumour heterogeneity and subsequently focus on constraints imposed upon cancer evolution. The presence of (1) parallel evolution, (2) convergent evolution and (3) the biological impact of acquiring mutations in specific orders suggest that cancer evolution may be exploitable. These constraints on cancer evolution may help us identify cancer evolutionary rule books, which could eventually inform both diagnostic and therapeutic approaches to improve survival outcomes.

Clonality analysis of multifocal papillary thyroid carcinoma by using genetic profiles.

Papillary thyroid carcinoma (PTC) is the most common adult thyroid malignancy and often presents with multiple anatomically distinct foci within the thyroid, known as multifocal papillary thyroid carcinoma (MPTC). The widespread application of the next-generation sequencing technologies in cancer genomics research provides novel insights into determining the clonal relationship between multiple tumours within the same thyroid gland. For eight MPTC patients, we performed whole-exome sequencing and targeted region sequencing to identify the non-synonymous point mutations and gene rearrangements of distinct and spatially separated tumour foci. Among these eight MPTCs, completely discordant mutational spectra were observed in the distinct cancerous nodules of patients MPTC1 and 5, suggesting that these nodules originated from independent precursors. In another three cases (MPTC2, 6, and 8), the distinct MPTC foci of these patients had no other shared mutations except BRAF V600E, also indicating likely independent origins. Two patients (MPTC3 and 4) shared almost identical mutational spectra amongst their separate tumour nodules, suggesting a common clonal origin. MPTC patient 7 had seven cancer foci, of which two foci shared 66.7% of mutations, while the remaining cancer foci displayed no common non-synonymous mutations, indicating that MPTC7 has multiple independent origins accompanied by intraglandular disease dissemination. In this study, we found that 75% of MPTC cases arose as independent tumours, which supports the field cancerization hypothesis describing multiple malignant lesions. MPTC may also arise from intrathyroidal metastases from a single malignant clone, as well as multiple independent origins accompanied by intrathyroidal metastasis.

Whole-genome sequencing reveals complex mechanisms of intrinsic resistance to BRAF inhibition.

BACKGROUND: BRAF is mutated in ∼42% of human melanomas (COSMIC. http://www.sanger.ac.uk/genetics/CGP/cosmic/) and pharmacological BRAF inhibitors such as vemurafenib and dabrafenib achieve dramatic responses in patients whose tumours harbour BRAF(V600) mutations. Objective responses occur in ∼50% of patients and disease stabilisation in a further ∼30%, but ∼20% of patients present primary or innate resistance and do not respond. Here, we investigated the underlying cause of treatment failure in a patient with BRAF mutant melanoma who presented primary resistance. METHODS: We carried out whole-genome sequencing and single nucleotide polymorphism (SNP) array analysis of five metastatic tumours from the patient. We validated mechanisms of resistance in a cell line derived from the patient's tumour. RESULTS: We observed that the majority of the single-nucleotide variants identified were shared across all tumour sites, but also saw site-specific copy-number alterations in discrete cell populations at different sites. We found that two ubiquitous mutations mediated resistance to BRAF inhibition in these tumours. A mutation in GNAQ sustained mitogen-activated protein kinase (MAPK) signalling, whereas a mutation in PTEN activated the PI3 K/AKT pathway. Inhibition of both pathways synergised to block the growth of the cells. CONCLUSIONS: Our analyses show that the five metastases arose from a common progenitor and acquired additional alterations after disease dissemination. We demonstrate that a distinct combination of mutations mediated primary resistance to BRAF inhibition in this patient. These mutations were present in all five tumours and in a tumour sample taken before BRAF inhibitor treatment was administered. Inhibition of both pathways was required to block tumour cell growth, suggesting that combined targeting of these pathways could have been a valid therapeutic approach for this patient.

Parallel evolution of tumour subclones mimics diversity between tumours.

Intratumour heterogeneity (ITH) may foster tumour adaptation and compromise the efficacy of personalized medicine approaches. The scale of heterogeneity within a tumour (intratumour heterogeneity) relative to genetic differences between tumours (intertumour heterogeneity) is unknown. To address this, we obtained 48 biopsies from eight stage III and IV clear cell renal cell carcinomas (ccRCCs) and used DNA copy-number analyses to compare biopsies from the same tumour with 440 single tumour biopsies from the Cancer Genome Atlas (TCGA). Unsupervised hierarchical clustering of TCGA and multi-region ccRCC samples revealed segregation of samples from the same tumour into unrelated clusters; 25% of multi-region samples appeared more similar to unrelated samples than to any other sample originating from the same tumour. We found that the majority of recurrent DNA copy number driver aberrations in single biopsies were not present ubiquitously in late-stage ccRCCs and were likely to represent subclonal events acquired during tumour progression. Such heterogeneous subclonal genetic alterations within individual tumours may impair the identification of robust ccRCC molecular subtypes classified by distinct copy number alterations and clinical outcomes. The co-existence of distinct subclonal copy number events in different regions of individual tumours reflects the diversification of individual ccRCCs through multiple evolutionary routes and may contribute to tumour sampling bias and impact upon tumour progression and clinical outcome.

Spatial intra-tumour heterogeneity and treatment-induced genomic evolution in oesophageal adenocarcinoma: implications for prognosis and therapy.

BACKGROUND: Oesophageal adenocarcinoma (OAC) is a highly heterogeneous cancer with poor survival. Standard curative treatment is chemotherapy with or without radiotherapy followed by oesophagectomy. Genomic heterogeneity is a feature of OAC and has been linked to treatment resistance. METHODS: Whole-genome sequencing data from 59 treatment-naïve and 18 post-treatment samples from 29 OAC patients was analysed. Twenty-seven of these were enrolled in the DOCTOR trial, sponsored by the Australasian Gastro-Intestinal Trials Group. Two biopsies from each treatment-naïve tumour were assessed to define 'shared' (between both samples) and 'private' (present in one sample) mutations. RESULTS: Mutational signatures SBS2/13 (APOBEC) and SBS3 (BRCA) were almost exclusively detected in private mutation populations of treatment-naïve tumours. Patients presenting these signatures had significantly worse disease specific survival. Furthermore, mutational signatures associated with platinum-based chemotherapy treatment as well as high platinum enrichment scores were only detected in post-treatment samples. Additionally, clones with high putative neoantigen binding scores were detected in some treatment-naïve samples suggesting immunoediting of clones. CONCLUSIONS: This study demonstrates the high intra-tumour heterogeneity in OAC, as well as indicators for treatment-induced changes during tumour evolution. Intra-tumour heterogeneity remains a problem for successful treatment strategies in OAC.

Ecological and evolutionary dynamics to design and improve ovarian cancer treatment.

Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.