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To thrive, cancer cells must navigate acute inflammatory signaling accompanying oncogenic transformation, such as via overexpression of repeat elements. We examined the relationship between immunostimulatory repeat expression, tumor evolution, and the tumor-immune microenvironment. Integration of multimodal data from a cohort of pancreatic ductal adenocarcinoma (PDAC) patients revealed expression of specific Alu repeats predicted to form double-stranded RNAs (dsRNAs) and trigger retinoic-acid-inducible gene I (RIG-I)-like-receptor (RLR)-associated type-I interferon (IFN) signaling. Such Alu-derived dsRNAs also anti-correlated with pro-tumorigenic macrophage infiltration in late stage tumors. We defined two complementary pathways whereby PDAC may adapt to such anti-tumorigenic signaling. In mutant TP53 tumors, ORF1p from long interspersed nuclear element (LINE)-1 preferentially binds Alus and decreases their expression, whereas adenosine deaminases acting on RNA 1 (ADAR1) editing primarily reduces dsRNA formation in wild-type TP53 tumors. Depletion of either LINE-1 ORF1p or ADAR1 reduced tumor growth in vitro. The fact that tumors utilize multiple pathways to mitigate immunostimulatory repeats implies the stress from their expression is a fundamental phenomenon to which PDAC, and likely other tumors, adapt. [Display omitted] • Alu dsRNA "viral mimics" anticorrelate with L1 activity and macrophage infiltration • L1 ORF1p suppresses Alu RNA expression to reduce IFN response in vitro • TP53 -dependent switching between L1 and ADAR1 suppresses younger Alus • Model predicts IFN response from TP53 mutation, Alus expression, L1 activity, and ADAR1 editing Overexpression of transposable elements is a common feature of cancer. Sun, You, et al. show that, in pancreatic ductal adenocarcinoma, tumor cells adapt through different mechanisms to mitigate a specific group of dsRNA-producing repeats in a TP53 -dependent manner. Their work provides insight into how cancer cells escape the innate immune pressure elicited by repeat expression. [ABSTRACT FROM AUTHOR]

The evolution of lung adenocarcinoma is accompanied by a multitude of gene mutations and dysfunctions, rendering its phenotypic state and evolutionary direction highly complex. To interpret the evolution of lung adenocarcinoma, various methods have been developed to elucidate the molecular pathogenesis and functional evolution processes. However, most of these methods are constrained by the absence of cancerous temporal information, and the challenges of heterogeneous characteristics. To handle these problems, in this study, a patient quasi-potential landscape method was proposed to estimate the cancerous time of phenotypic states' emergence during the evolutionary process. Subsequently, a total of 39 different oncogenetic paths were identified based on cancerous time and mutations, reflecting the molecular pathogenesis of the evolutionary process of lung adenocarcinoma. To interpret the evolution patterns of lung adenocarcinoma, three oncogenetic graphs were obtained as the common evolutionary patterns by merging the oncogenetic paths. Moreover, patients were evenly re-divided into early, middle, and late evolutionary stages according to cancerous time, and a feasible framework was developed to construct the functional evolution network of lung adenocarcinoma. A total of six significant functional evolution processes were identified from the functional evolution network based on the pathway enrichment analysis, which plays critical roles in understanding the development of lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Abstract Currently, even the most effective anti-cancer therapies are often limited by the development of drug resistance and tumor relapse, which is a major challenge facing current cancer research. A deep understanding of the molecular and biochemical bases of drug efficacy that can help predict the clinical drug resistance, coupled with the evolution of systematic genomic and proteomic technologies, have facilitated studies identifying and elucidating the underlying mechanisms. In this review, we focus on several important issues on cancer drug resistance and provide a framework for understanding the common ways by which cancers develop resistance to therapeutic agents. With the increasing arsenal of novel anticancer agents and techniques, there are now unprecedented opportunities to understand and overcome drug resistance. The proteolysis targeting chimera (PROTAC) technology, immunotherapy, nanomedicine, and real-time monitoring of drug response all provide effective approaches for combating drug resistance. In addition to the advancement of therapeutic technologies, the revolution of treatment concept is also of great importance. We can take advantage of the interplay between drug sensitive and resistant subclones for combating cancer. However, there remains a long way to go in the protracted war against cancer drug resistance.

Currently, even the most effective anti-cancer therapies are often limited by the development of drug resistance and tumor relapse, which is a major challenge facing current cancer research. A deep understanding of the molecular and biochemical bases of drug efficacy that can help predict the clinical drug resistance, coupled with the evolution of systematic genomic and proteomic technologies, have facilitated studies identifying and elucidating the underlying mechanisms. In this review, we focus on several important issues on cancer drug resistance and provide a framework for understanding the common ways by which cancers develop resistance to therapeutic agents. With the increasing arsenal of novel anticancer agents and techniques, there are now unprecedented opportunities to understand and overcome drug resistance. The proteolysis targeting chimera (PROTAC) technology, immunotherapy, nanomedicine, and real-time monitoring of drug response all provide effective approaches for combating drug resistance. In addition to the advancement of therapeutic technologies, the revolution of treatment concept is also of great importance. We can take advantage of the interplay between drug sensitive and resistant subclones for combating cancer. However, there remains a long way to go in the protracted war against cancer drug resistance. [ABSTRACT FROM AUTHOR]

Hepatitis B virus (HBV) infection remains a major public health concern worldwide, with approximately 296 million individuals chronically infected. The HBV-encoded X protein (HBx) is a regulatory protein of 17 kDa, reportedly responsible for a broad range of functions, including viral replication and oncogenic processes. In this review, we summarize the state of knowledge on the mechanisms underlying HBx functions in viral replication, the antiviral effect of therapeutics directed against HBx, and the role of HBx in liver cancer development (including a hypothetical model of hepatocarcinogenesis). We conclude by highlighting major unanswered questions in the field and the implications of their answers. [ABSTRACT FROM AUTHOR]

Intratumour heterogeneity has been shown to play a role in the malignant progression of cancer. The clonal evolution in primary cancer has been well studied, however, that in metastatic tumorigenesis is not fully understood. In this study, we established human colon cancer-derived organoids and investigated clonal dynamics during liver metastasis development by tracking barcode-labelled subclones. Long-term subclone co-cultures showed clonal drift, with a single subclone becoming dominant in the cell population. Interestingly, the selected subclones were not always the same, suggesting that clonal selection was not based on cell intrinsic properties. Furthermore, liver tumours developed by co-transplantation of organoid subclones into the immunodeficient mouse spleen showed a progressive drastic reduction in clonal diversity, and only one or two subclones predominated in the majority of large metastatic tumours. Importantly, selections were not limited to particular subclones but appeared to be random. A trend towards a reduction in clonal diversity was also found in liver metastases of multiple colour-labelled organoids of mouse intestinal tumours. Based on these results, we propose a novel mechanism of metastasis development, i.e. a subclone population of the disseminated tumour cells in the liver is selected by neutral selection during colonization and constitutes large metastatic tumours. [ABSTRACT FROM AUTHOR]

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

The evolutionary dynamics of cancer, characterized by its profound heterogeneity, demand sophisticated tools for a holistic understanding. This review delves into tumor phylogenetics, an essential approach bridging evolutionary biology with oncology, offering unparalleled insights into cancer's evolutionary trajectory. We provide an overview of the workflow, encompassing study design, data acquisition, and phylogeny reconstruction. Notably, the integration of diverse data sets emerges as a transformative step, enhancing the depth and breadth of evolutionary insights. With this integrated perspective, tumor phylogenetics stands poised to redefine our understanding of cancer evolution and influence therapeutic strategies.

Somatic evolution selects cancer cell phenotypes that maximize survival and proliferation in dynamic environments. Although cancer cells are molecularly heterogeneous, we hypothesized convergent adaptive strategies to common host selection forces can be inferred from patterns of epigenetic and genetic evolutionary selection in similar tumors. We systematically investigated gene mutations and expression changes in lung adenocarcinomas with no common driver genes (n = 313). Although 13,461 genes were mutated in at least one sample, only 376 non-synonymous mutations evidenced positive evolutionary selection with conservation of 224 genes, while 1736 and 2430 genes exhibited ≥ two-fold increased and ≥ 50% decreased expression, respectively. Mutations under positive selection are more frequent in genes with significantly altered expression suggesting they often “hardwire” pre-existing epigenetically driven adaptations. Conserved genes averaged 16-fold higher expression in normal lung tissue compared to those with selected mutations demonstrating pathways necessary for both normal cell function and optimal cancer cell fitness. The convergent LUAD phenotype exhibits loss of differentiated functions and cell–cell interactions governing tissue organization. Conservation with increased expression is found in genes associated with cell cycle, DNA repair, p53 pathway, epigenetic modifiers, and glucose metabolism. No canonical driver gene pathways exhibit strong positive selection, but extensive down-regulation of membrane ion channels suggests decreased transmembrane potential may generate persistent proliferative signals. NCD LUADs perform niche construction generating a stiff, immunosuppressive microenvironment through selection of specific collagens and proteases. NCD LUADs evolve to a convergent phenotype through a network of interconnected genetic, epigenetic, and ecological pathways. [ABSTRACT FROM AUTHOR]

Abstract Background Tumors 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. Results Here, 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. Conclusions Our 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 Background Extension of prostate cancer beyond the primary site by local invasion or nodal metastasis is associated with poor prognosis. Despite significant research on tumour evolution in prostate cancer metastasis, the emergence and evolution of cancer clones at this early stage of expansion and spread are poorly understood. We aimed to delineate the routes of evolution and cancer spread within the prostate and to seminal vesicles and lymph nodes, linking these to histological features that are used in diagnostic risk stratification. Methods We performed whole-genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and lymph nodes of five treatment-naive patients with locally advanced disease. We spatially mapped the clonal composition of cancer across the prostate and the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes in each individual by analysing a total of > 19,000 copy number corrected single nucleotide variants. Results In each patient, we identified sample locations corresponding to the earliest part of the malignancy. In patient 10, we mapped the spread of cancer from the apex of the prostate to the seminal vesicles and identified specific genomic changes associated with the transformation of adenocarcinoma to amphicrine morphology during this spread. Furthermore, we show that the lymph node metastases in this patient arose from specific cancer clones found at the base of the prostate and the seminal vesicles. In patient 15, we observed increased mutational burden, altered mutational signatures and histological changes associated with whole genome duplication. In all patients in whom histological heterogeneity was observed (4/5), we found that the distinct morphologies were located on separate branches of their respective evolutionary trees. Conclusions Our results link histological transformation with specific genomic alterations and phylogenetic branching. These findings have implications for diagnosis and risk stratification, in addition to providing a rationale for further studies to characterise the genetic changes causally linked to morphological transformation. Our study demonstrates the value of integrating multi-region sequencing with histopathological data to understand tumour evolution and identify mechanisms of prostate cancer spread.

Abstract Background The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor’s immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. Methods Here, we applied a visualizing method termed ‘cancer immunogram’ to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. Results We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by ‘hot’ and ‘exhausted’ features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of ‘cold’ tumor. Immunogram-II was characterized by ‘cold’ and ‘radical’ features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by ‘cold’ and ‘recognizable’ features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by ‘cold’ and ‘inert’ features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. Conclusions Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies.

Tumor cells reprogram nutrient acquisition and metabolic pathways to meet their energetic, biosynthetic, and redox demands. Similarly, metabolic processes in immune cells support host immunity against cancer and determine differentiation and fate of leukocytes. Thus, metabolic deregulation and imbalance in immune cells within the tumor microenvironment have been reported to drive immune evasion and to compromise therapeutic outcomes. Interestingly, emerging evidence indicates that anti-tumor immunity could modulate tumor heterogeneity, aggressiveness, and metabolic reprogramming, suggesting that immunosurveillance can instruct cancer progression in multiple dimensions. This review summarizes our current understanding of how metabolic crosstalk within tumors affects immunogenicity of tumor cells and promotes cancer progression. Furthermore, we explain how defects in the metabolic cascade can contribute to developing dysfunctional immune responses against cancers and discuss the contribution of immunosurveillance to these defects as a feedback mechanism. Finally, we highlight ongoing clinical trials and new therapeutic strategies targeting cellular metabolism in cancer. Metabolic deregulation and imbalance in immune cells within the tumor microenvironment drive immune evasion and compromise therapeutic outcomes This review highlights how metabolic crosstalk within tumors affects immunogenicity and promotes cancer progression. [ABSTRACT FROM AUTHOR]

Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their mutation frequency in premalignant tissue is expected to exceed the basal mutation rate. In old terms, that translates to "the survival of the fittest" and implies that a selective process underlies the frequency of cancer driver mutations. In that sense, each tissue is its own niche that creates a molecular selective pressure that may favor the propagation of a mutation or not. At the heart of this stands one of the biggest riddles in cancer biology: the tissue-predisposition to cancer driver mutations. The frequency of cancer driver mutations among tissues is non-uniform: for instance, mutations in APC are particularly frequent in colorectal cancer, and 99% of chronic myeloid leukemia patients harbor the driver BCR-ABL1 fusion mutation, which is rarely found in solid tumors. Here, we provide a mechanistic framework that aims to explain how tissue-specific features, ranging from epigenetic underpinnings to the expression of viral transposable elements, establish a molecular basis for selecting cancer driver mutations in a tissue-specific manner. [ABSTRACT FROM AUTHOR]

Mitotic cell division is tightly monitored by checkpoints that safeguard the genome from instability. Failures in accurate chromosome segregation during mitosis can cause numerical aneuploidy, which was hypothesized by Theodor Boveri over a century ago to promote tumorigenesis. Recent interrogation of pan-cancer genomes has identified unexpected classes of chromosomal abnormalities, including complex rearrangements arising through chromothripsis. This process is driven by mitotic errors that generate abnormal nuclear structures that provoke extensive yet localized shattering of mis-segregated chromosomes. Here, we discuss emerging mechanisms underlying chromothripsis from micronuclei and chromatin bridges, as well as highlight how this mutational cascade converges on the DNA damage response. A fundamental understanding of these catastrophic processes will provide insight into how initial errors in mitosis can precipitate rapid cancer genome evolution. Chromothripsis drives rapid genome evolution through the extensive shattering of mis-segregated chromosomes. This review discusses the cell cycle checkpoints that protect against mitotic errors, how mis-segregated chromosomes entrapped in abnormal nuclear structures undergo shattering, and the DNA damage response mechanisms that reassemble shattered chromosomes to generate complex cancer genome rearrangements. [ABSTRACT FROM AUTHOR]

Abstract Background Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. Methods We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. Results In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis’ potential impact on therapy selection appears positive in these pilot cases. Conclusions PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Abstract Infectious diseases are a major threat for biodiversity conservation and can exert strong influence on wildlife population dynamics. Understanding the mechanisms driving infection rates and epidemic outcomes requires empirical data on the evolutionary trajectory of pathogens and host selective processes. Phylodynamics is a robust framework to understand the interaction of pathogen evolutionary processes with epidemiological dynamics, providing a powerful tool to evaluate disease control strategies. Tasmanian devils have been threatened by a fatal transmissible cancer, devil facial tumour disease (DFTD), for more than two decades. Here we employ a phylodynamic approach using tumour mitochondrial genomes to assess the role of tumour genetic diversity in epidemiological and population dynamics in a devil population subject to 12 years of intensive monitoring, since the beginning of the epidemic outbreak. DFTD molecular clock estimates of disease introduction mirrored observed estimates in the field, and DFTD genetic diversity was positively correlated with estimates of devil population size. However, prevalence and force of infection were the lowest when devil population size and tumour genetic diversity was the highest. This could be due to either differential virulence or transmissibility in tumour lineages or the development of host defence strategies against infection. Our results support the view that evolutionary processes and epidemiological trade‐offs can drive host‐pathogen coexistence, even when disease‐induced mortality is extremely high. We highlight the importance of integrating pathogen and population evolutionary interactions to better understand long‐term epidemic dynamics and evaluating disease control strategies.

Simple Summary: Clear cell renal cell carcinomas (CCRCCs) evolve as dynamic communities of individuals (cells) that are amenable to being studied under sociological rules. Here, the early period of development in CCRCC, progressing from initial homogeneity to high intratumor heterogeneity (ITH) and secondary clonal and sub-clonal diversification, is considered using the hawk-dove game. Fitness is a measure of biological aggressiveness in tumors. The results demonstrate that the fittest clone of a neoplasm in a heterogeneous context is fitter than the clone in a homogeneous environment in the early phases of tumor evolution. This study notes the advantages of a translational multidisciplinary approach in cancer research. Clear cell renal cell carcinoma (CCRCC) is an aggressive form of cancer and a paradigmatic example of intratumor heterogeneity (ITH). The hawk-dove game is a mathematical tool designed to analyze competition in biological systems. Using this game, the study reported here analyzes the early phase of CCRCC development, comparing clonal fitness in homogeneous (linear evolutionary) and highly heterogeneous (branching evolutionary) models. Fitness in the analysis is a measure of tumor aggressiveness. The results show that the fittest clone in a heterogeneous environment is fitter than the clone in a homogeneous context in the early phases of tumor evolution. Early and late periods of tumor evolution in CCRCC are also compared. The study shows the convergence of mathematical, histological, and genomics studies with respect to clonal aggressiveness in different periods of the natural history of CCRCC. Such convergence highlights the importance of multidisciplinary approaches for obtaining a better understanding of the intricacies of cancer. [ABSTRACT FROM AUTHOR]

The later stages of cancer, including the invasion and colonization of new tissues, are actively mysterious compared to earlier stages like primary tumor formation. While we lack many details about both, we do have an apparently successful explanatory framework for the earlier stages: one in which genetic mutations hold ultimate causal and explanatory power. By contrast, on both empirical and conceptual grounds, it is not currently clear thatmutations alone can explain the later stages of cancer. Can a different type of molecular change do better? Here, I introduce the "permissive binding theory" of cancer, which proposes that novel protein binding interactions are the key causal and explanatory entity in invasion and metastasis. It posits that binding is more abundant at baseline than we observe because it is restricted in normal physiology; that any large perturbation to physiological state revives this baseline abundance, unleashing many new binding interactions; and that a subset of these cause the cellular functions at the heart of oncogenesis, especially invasion and metastasis. Significant physiological perturbations occur in cancer cells in very early stages, and generally become more extreme with progression, providing interactions that continually fuel invasion and metastasis. The theory is compatible with, but not limited to, causal roles for the diverse molecular changes observed in cancer (e.g. gene expression or epigenetic changes), as these generally act causally upstream of proteins, and so may exert their effects by changing the protein binding interactions that occur in the cell. This admits the possibility that molecular changes that appear quite different may actually converge in creating the same few protein complexes, simplifying our picture of invasion and metastasis. If correct, the theory offers a concrete therapeutic strategy: targeting the key novel complexes. The theory is straightforwardly testable by large-scale identification of protein interactions in different cancers. [ABSTRACT FROM AUTHOR]

Introduction: In Asians, more than half of non-small cell lung cancers (NSCLC) are induced by epidermal growth factor receptor (EGFR) mutations. Although patients carrying EGFR driver mutations display a good initial response to EGFR-Tyrosine Kinase Inhibitors (EGFR-TKIs), additional mutations provoke drug resistance. Hence, predicting tumor dynamics before treatment initiation and formulating a reasonable treatment schedule is an urgent challenge. Methods: To overcome this problem, we constructed a mathematical model based on clinical observations and investigated the optimal schedules for EGFR-TKI therapy. Results: Based on published data on cell growth rates under different drugs, we found that using osimertinib that are efficient for secondary resistant cells as the first-line drug is beneficial in monotherapy, which is consistent with published clinical statistical data. Moreover, we identified the existence of a suitable drug-switching time; that is, changing drugs too early or too late was not helpful. Furthermore, we demonstrate that osimertinib combined with erlotinib or gefitinib as first-line treatment, has the potential for clinical application. Finally, we examined the relationship between the initial ratio of resistant cells and final cell number under different treatment conditions, and summarized it into a therapy suggestion map. By performing parameter sensitivity analysis, we identified the condition where osimertinib-first therapy was recommended as the optimal treatment option. Discussion: This study for the first time theoretically showed the optimal treatment strategies based on the known information in NSCLC. Our framework can be applied to other types of cancer in the future. [ABSTRACT FROM AUTHOR]

The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution. [ABSTRACT FROM AUTHOR]

Tumor recurrence, driven by the evolution of drug resistance is a major barrier to therapeutic success in cancer. Tumor drug resistance is often caused by genetic alterations such as point mutation, which refers to the modification of a single genomic base pair, or gene amplification, which refers to the duplication of a region of DNA that contains a gene. These mechanisms typically confer varying degrees of resistance, and they tend to occur at vastly different frequencies. Here we investigate the dependence of tumor recurrence dynamics on these mechanisms of resistance, using stochastic multi-type branching process models. We derive tumor extinction probabilities and deterministic estimates for the tumor recurrence time, defined as the time when an initially drug sensitive tumor surpasses its original size after developing resistance. For models of amplification-driven and mutation-driven resistance, we prove law of large numbers results regarding the convergence of the stochastic recurrence times to their mean. Additionally, we prove sufficient and necessary conditions for a tumor to escape extinction under the gene amplification model, discuss behavior under biologically relevant parameters, and compare the recurrence time and tumor composition in the mutation and amplification models both analytically and using simulations. In comparing these mechanisms, we find that the ratio between recurrence times driven by amplification versus mutation depends linearly on the number of amplification events required to acquire the same degree of resistance as a mutation event, and we find that the relative frequency of amplification and mutation events plays a key role in determining the mechanism under which recurrence is more rapid for any specific system. In the amplification-driven resistance model, we also observe that increasing drug concentration leads to a stronger initial reduction in tumor burden, but that the eventual recurrent tumor population is less heterogeneous, more aggressive and harbors higher levels of drug-resistance. [ABSTRACT FROM AUTHOR]

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

ABSTRACTThe evolution of immune profile from primary tumors to distant and local metastases in non-small cell lung cancer (NSCLC), as well as the impact of the immune background of primary tumors on metastatic potential, remains unclear. To address this, we performed whole-exome sequencing and immunohistochemistry for 73 paired primary and metastatic tumor samples from 41 NSCLC patients, and analyzed the change of immune profile from primary tumors to metastases and involved genetic factors. We found that distant metastases tended to have a decreased CD8+ T cell level along with an increased chromosomal instability (CIN) compared with primary tumors, which was partially ascribed to acquired DNA damage repair (DDR) deficiency. Distant metastases were characterized by immunosuppression (low CD8+ T cell level) and immune evasion (high PD-L1 level) whereas local metastases (pleura) were immune-competent with high CD8+ T cell, low CD4+ T cell and low PD-L1 level. Primary tumors with high levels of CD4+ T cells were associated with distant metastases rather than local metastases. Analysis of TCGA data and a single-cell RNA-sequencing dataset revealed a decreasing trend of major immune cells, such as CD8+ T cells, and an increasing trend of CD4 T helper cells (Th2 and Th1) in primary tumors with metastases from local to distant sites. Our study indicates that there are differences in the immune evolution between distant and local metastases, and that acquired DDR deficiency contributes to the immunosuppression in distant metastases of NSCLC. Moreover, the immune background of primary tumors may affect their metastatic potential.

The later stages of cancer, including the invasion and colonization of new tissues, are actively mysterious compared to earlier stages like primary tumor formation. While we lack many details about both, we do have an apparently successful explanatory framework for the earlier stages: one in which genetic mutations hold ultimate causal and explanatory power. By contrast, on both empirical and conceptual grounds, it is not currently clear that mutations alone can explain the later stages of cancer. Can a different type of molecular change do better? Here, I introduce the “permissive binding theory” of cancer, which proposes that novel protein binding interactions are the key causal and explanatory entity in invasion and metastasis. It posits that binding is more abundant at baseline than we observe because it is restricted in normal physiology; that any large perturbation to physiological state revives this baseline abundance, unleashing many new binding interactions; and that a subset of these cause the cellular functions at the heart of oncogenesis, especially invasion and metastasis. Significant physiological perturbations occur in cancer cells in very early stages, and generally become more extreme with progression, providing interactions that continually fuel invasion and metastasis. The theory is compatible with, but not limited to, causal roles for the diverse molecular changes observed in cancer (e.g. gene expression or epigenetic changes), as these generally act causally upstream of proteins, and so may exert their effects by changing the protein binding interactions that occur in the cell. This admits the possibility that molecular changes that appear quite different may actually converge in creating the same few protein complexes, simplifying our picture of invasion and metastasis. If correct, the theory offers a concrete therapeutic strategy: targeting the key novel complexes. The theory is straightforwardly testable by large-scale identification of protein interactions in different cancers.

Cancer genomes are almost invariably complex with genomic alterations cooperating during each step of carcinogenesis. In cancers that lack a single dominant oncogene mutation, cooperation between the inactivation of multiple tumor suppressor genes can drive tumor initiation and growth. Here, we shed light on how the sequential acquisition of genomic alterations generates oncogene-negative lung tumors. We couple tumor barcoding with combinatorial and multiplexed somatic genome editing to characterize the fitness landscapes of three tumor suppressor genes NF1, RASA1, and PTEN, the inactivation of which jointly drives oncogene-negative lung adenocarcinoma initiation and growth. The fitness landscape was surprisingly accessible, with each additional mutation leading to growth advantage. Furthermore, the fitness landscapes remained fully accessible across backgrounds with the inactivation of additional tumor suppressor genes. These results suggest that while predicting cancer evolution will be challenging, acquiring the multiple alterations that drive the growth of oncogene-negative tumors can be facilitated by the lack of constraints on mutational order. [ABSTRACT FROM AUTHOR]

The stepwise accumulation of key driver mutations is responsible for the development and malignant progression of colorectal cancer in primary sites. Genetic mouse model studies have revealed combinations of driver gene mutations that induce phenotypic changes in tumors toward malignancy. However, cancer evolution is regulated by not only genetic alterations but also nongenetic mechanisms. For example, certain populations of metastatic cancer cells show a loss of malignant characteristics even after the accumulation of driver mutations, and such cells are eliminated in a negative selection manner. Furthermore, a polyclonal metastasis model has recently been proposed, in which cell clusters consisting of genetically heterogeneous cells break off from the primary site, disseminate to distant organs, and develop into heterogenous metastatic tumors. Such nongenetic mechanisms for malignant progression have been elucidated using genetically engineered mouse models as well as organoid transplantation experiments. In this review article, we discuss the role of genetic alterations in the malignant progression of primary intestinal tumors and nongenetic mechanisms for negative selection and polyclonal metastasis, which we learned from model studies. [ABSTRACT FROM AUTHOR]

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies. [ABSTRACT FROM AUTHOR]

Background: Gliomas are tumours arising mostly from astrocytic or oligodendrocytic precursor cells. These tumours are classified according to the updated WHO classification from 2021 in 4 grades depending on molecular and histopathological criteria. Despite novel multimodal therapeutic approaches, the vast majority of gliomas (WHO grade III and IV) are not curable. The circadian clock is an important regulator of numerous cellular processes and its dysregulation had been found during the progression of many cancers, including gliomas. Results: In this study, we explore expression patterns of clock-controlled genes in low-grade glioma (LGG) and glioblastoma multiforme (GBM) and show that a set of 45 clock-controlled genes can be used to distinguish GBM from normal tissue. Subsequent analysis identified 17 clock-controlled genes with a significant association with survival. The results point to a loss of correlation strength within elements of the circadian clock network in GBM compared to LGG. We further explored the progression patterns of mutations in LGG and GBM, and showed that tumour suppressor APC is lost late both in LGG and GBM. Moreover, HIF1A, involved in cellular response to hypoxia, exhibits subclonal losses in LGG, and TERT, involved in the formation of telomerase, is lost late in the GBM progression. By examining multi-sample LGG data, we find that the clock-controlled driver genes APC, HIF1A, TERT and TP53 experience frequent subclonal gains and losses. Conclusions: Our results show a higher level of disrgulation at the gene expression level in GBM compared to LGG, and indicate an association between the differentially expressed clock-regulated genes and patient survival in both LGG and GBM. By reconstructing the patterns of progression in LGG and GBM, our data reveals the relatively late gains and losses of clock-regulated glioma drivers. Our analysis emphasizes the role of clock-regulated genes in glioma development and progression. Yet, further research is needed to asses their value in the development of new treatments. [ABSTRACT FROM AUTHOR]

Infectious diseases are a major threat for biodiversity conservation and can exert strong influence on wildlife population dynamics. Understanding the mechanisms driving infection rates and epidemic outcomes requires empirical data on the evolutionary trajectory of pathogens and host selective processes. Phylodynamics is a robust framework to understand the interaction of pathogen evolutionary processes with epidemiological dynamics, providing a powerful tool to evaluate disease control strategies. Tasmanian devils have been threatened by a fatal transmissible cancer, devil facial tumour disease (DFTD), for more than two decades. Here we employ a phylodynamic approach using tumour mitochondrial genomes to assess the role of tumour genetic diversity in epidemiological and population dynamics in a devil population subject to 12 years of intensive monitoring, since the beginning of the epidemic outbreak. DFTD molecular clock estimates of disease introduction mirrored observed estimates in the field, and DFTD genetic diversity was positively correlated with estimates of devil population size. However, prevalence and force of infection were the lowest when devil population size and tumour genetic diversity was the highest. This could be due to either differential virulence or transmissibility in tumour lineages or the development of host defence strategies against infection. Our results support the view that evolutionary processes and epidemiological trade‐offs can drive host‐pathogen coexistence, even when disease‐induced mortality is extremely high. We highlight the importance of integrating pathogen and population evolutionary interactions to better understand long‐term epidemic dynamics and evaluating disease control strategies. [ABSTRACT FROM AUTHOR]

Tumors consist of different genotypically distinct subpopulations—or subclones—of cells. These subclones can influence neighboring clones in a process called "clonal interaction." Conventionally, research on driver mutations in cancer has focused on their cell-autonomous effects that lead to an increase in fitness of the cells containing the driver. Recently, with the advent of improved experimental and computational technologies for investigating tumor heterogeneity and clonal dynamics, new studies have shown the importance of clonal interactions in cancer initiation, progression, and metastasis. In this review we provide an overview of clonal interactions in cancer, discussing key discoveries from a diverse range of approaches to cancer biology research. We discuss common types of clonal interactions, such as cooperation and competition, its mechanisms, and the overall effect on tumorigenesis, with important implications for tumor heterogeneity, resistance to treatment, and tumor suppression. Quantitative models—in coordination with cell culture and animal model experiments—have played a vital role in investigating the nature of clonal interactions and the complex clonal dynamics they generate. We present mathematical and computational models that can be used to represent clonal interactions and provide examples of the roles they have played in identifying and quantifying the strength of clonal interactions in experimental systems. Clonal interactions have proved difficult to observe in clinical data; however, several very recent quantitative approaches enable their detection. We conclude by discussing ways in which researchers can further integrate quantitative methods with experimental and clinical data to elucidate the critical—and often surprising—roles of clonal interactions in human cancers. [ABSTRACT FROM AUTHOR]

Growing tumors are dynamic and nonlinear ecosystems, wherein cancer cells adapt to their local microenvironment, and these adaptations further modify the environment, inducing more changes. From nascent intraductal neoplasms to disseminated metastatic disease, several levels of evolutionary adaptations and selections occur. Here, we focus on one example of such an adaptation mechanism, namely, "niche construction" promoted by adaptation to acidosis, which is a metabolic adaptation to the early harsh environment in intraductal neoplasms. The avascular characteristics of ductal carcinoma in situ (DCIS) make the periluminal volume profoundly acidic, and cancer cells must adapt to this to survive. Based on discovery proteomics, we hypothesized that a component of acid adaptation involves production of collagen by pre-cancer cells that remodels the extracellular matrix (ECM) and stabilizes cells under acid stress. The proteomic data were surprising as collagen production and deposition are commonly believed to be the responsibility of mesenchymally derived fibroblasts, and not cells of epithelial origin. Subsequent experiments in 3D culture, spinning disk and second harmonic generation microscopy of DCIS lesions in patients' samples are concordant. Collagen production assay by acid-adapted cells in vitro demonstrated that the mechanism of induction involves the RAS and SMAD pathways. Secretome analyses show upregulation of ECM remodeling enzymes such as TGM2 and LOXL2 that are collagen crosslinkers. These data strongly indicate that acidosis in incipient cancers induces collagen production by cancer cells and support the hypothesis that this adaptation initiates a tumor-permissive microenvironment promoting survival and growth of nascent cancers.