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Background/Aim: The Kaplan-Meier curves for patients treated with immune checkpoint inhibitors (ICIs) display a small group of potentially-cured patients with longterm survival, creating a 'kangaroo-tail' shape of the survival curve. However, the mechanistic basis of this phenomenon and what occurs in patients whose cancer is resistant to ICIs remain unclear. The present study aimed to answer these questions. Materials and Methods: We analyzed mutations in mouse 4T1 mammary-gland-derived cancer cells expressing the hemagglutinin antigen (4T1-HA), which were grown in either wild-type mice or cytotoxic T-lymphocyte (CTL)-loaded immunocompromised mice (RAG-/- + ACT) under immune stress. These mutations were compared to those in 4T1-HA cells grown in RAG-/- mice without immune stress as a control. Results: The number of gene mutations, the tumor mutation burden (TMB) and microsatellite instability (MSI) scores were increased in the cancer cells under immune stress. The mutations in the antigen protein were such that the protein retained its immunogenicity and could still function as a neoantigen. Repeated immune recognition of additional neoantigens may lead to the kangaroo-tail survival phenomenon. The common genetic mutations of the analyzed 4T1-HA cells under immune stress included genes related to immune response. Analysis of alternative splicing of genes showed that are accumulated gene alterations under immune stress related to cancer-cell proliferation. Copy-number variation (CNV) analysis indicated that normal-antigen presentation and immune responses may be impaired under immune stress. Conclusion: Cancer cells, under immune stress, may acquire both immune escape capabilities and increased immunogenicity. This dual effect could lead to either resistance or response to ICIs, respectively. [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]

Cancer is ranked as the top cause of premature mortality. Volatile organic compounds (VOCs) are produced from catalytic peroxidation by reactive oxygen species (ROS) and have become a highly attractive non-invasive cancer screening approach. For future clinical applications, however, the correlation between cancer hallmarks and cancer-specific VOCs requires further study. This review discusses and compares cellular metabolism, signal transduction as well as mitochondrial metabolite translocation in view of cancer evolution and the basic biology of VOCs production. Certain cancerous characteristics as well as the origin of the ROS removal system date back to procaryotes and early eukaryotes and share commonalities with non-cancerous proliferative cells. This calls for future studies on metabolic cross talks and regulation of the VOCs production pathway.

A central goal of cancer genomics is to identify, in each patient, all the cancer-driving mutations. Among them, point mutations are referred to as cancer-driving nucleotides (CDNs), which recur in cancers. The companion study shows that the probability of i recurrent hits in n patients would decrease exponentially with i; hence, any mutation with i ≥ 3 hits in The Cancer Genome Atlas (TCGA) database is a high-probability CDN. This study characterizes the 50–150 CDNs identifiable for each cancer type of TCGA (while anticipating 10 times more undiscovered ones) as follows: (i) CDNs tend to code for amino acids of divergent chemical properties. (ii) At the genic level, far more CDNs (more than fivefold) fall on noncanonical than canonical cancer-driving genes (CDGs). Most undiscovered CDNs are expected to be on unknown CDGs. (iii) CDNs tend to be more widely shared among cancer types than canonical CDGs, mainly because of the higher resolution at the nucleotide than the whole-gene level. (iv) Most important, among the 50–100 coding region mutations carried by a cancer patient, 5–8 CDNs are expected but only 0–2 CDNs have been identified at present. This low level of identification has hampered functional test and gene-targeted therapy. We show that, by expanding the sample size to 105, most CDNs can be identified. Full CDN identification will then facilitate the design of patient-specific targeting against multiple CDN-harboring genes.

Tumorigenesis, like most complex genetic traits, is driven by the joint actions of many mutations. At the nucleotide level, such mutations are cancer-driving nucleotides (CDNs). The full sets of CDNs are necessary, and perhaps even sufficient, for the understanding and treatment of each cancer patient. Currently, only a small fraction of CDNs is known as most mutations accrued in tumors are not drivers. We now develop the theory of CDNs on the basis that cancer evolution is massively repeated in millions of individuals. Hence, any advantageous mutation should recur frequently and, conversely, any mutation that does not is either a passenger or deleterious mutation. In the TCGA cancer database (sample size n=300–1000), point mutations may recur in i out of n patients. This study explores a wide range of mutation characteristics to determine the limit of recurrences (i*) driven solely by neutral evolution. Since no neutral mutation can reach i*=3, all mutations recurring at i≥3 are CDNs. The theory shows the feasibility of identifying almost all CDNs if n increases to 100,000 for each cancer type. At present, only

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.

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.

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.

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]

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.

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.

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]

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]

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.

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.

The 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.

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]

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]

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.

Abstract Background Despite having been extensively studied, it remains largely unclear why humans bear a particularly high risk of cancer. The antagonistic pleiotropy hypothesis predicts that primate-specific genes (PSGs) tend to promote tumorigenesis, while the molecular atavism hypothesis predicts that PSGs involved in tumors may represent recently derived duplicates of unicellular genes. However, these predictions have not been tested. Results By taking advantage of pan-cancer genomic data, we find the upregulation of PSGs across 13 cancer types, which is facilitated by copy-number gain and promoter hypomethylation. Meta-analyses indicate that upregulated PSGs (uPSGs) tend to promote tumorigenesis and to play cell cycle-related roles. The cell cycle-related uPSGs predominantly represent derived duplicates of unicellular genes. We prioritize 15 uPSGs and perform an in-depth analysis of one unicellular gene-derived duplicate involved in the cell cycle, DDX11. Genome-wide screening data and knockdown experiments demonstrate that DDX11 is broadly essential across cancer cell lines. Importantly, non-neutral amino acid substitution patterns and increased expression indicate that DDX11 has been under positive selection. Finally, we find that cell cycle-related uPSGs are also preferentially upregulated in the highly proliferative embryonic cerebrum. Conclusions Consistent with the predictions of the atavism and antagonistic pleiotropy hypotheses, primate-specific genes, especially those PSGs derived from cell cycle-related genes that emerged in unicellular ancestors, contribute to the early proliferation of the human cerebrum at the cost of hitchhiking by similarly highly proliferative cancer cells.

Abstract Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Abstract Comparative studies of cancer‐related genes not only provide novel information about their evolution and function but also an understanding of cancer as a driving force in biological systems and species’ life histories. So far, these studies have focused on mammals. Here, we provide the first comparative study of cancer‐related gene copy number variation in fish. Fishes are a paraphyletic group whose last common ancestor is also an ancestor of the tetrapods, and accordingly, their tumour suppression mechanisms should include most of the mammalian mechanisms and also reveal novel (but potentially phylogenetically older) previously undetected mechanisms. We have matched the sequenced genomes of 65 fish species from the Ensemble database with the cancer gene information from the COSMIC database. By calculating the number of gene copies across species using the Ensembl CAFE data (providing species trees for gene copy number counts), we used a less resource‐demanding method for homolog identification. Our analysis demonstrates a masked relationship between cancer‐related gene copy number variation (CNV) and maximum lifespan in fish species, suggesting that a higher number of copies of tumour suppressor genes lengthens and the number of copies of oncogenes shortens lifespan. Based on the positive correlation between the number of copies of tumour suppressors and oncogenes, we show which species have more tumour suppressors in relation to oncogenes. It could be suggested that these species have stronger genetic defences against oncogenic processes. Fish studies could be a largely unexplored treasure trove for understanding the evolution and ecology of cancer, providing novel insights into the study of cancer and tumour suppression, in addition to fish evolution, life‐history trade‐offs, and ecology.

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]

Stackelberg evolutionary game (SEG) theory combines classical and evolutionary game theory to frame interactions between a rational leader and evolving followers. In some of these interactions, the leader wants to preserve the evolving system (e.g. fisheries management), while in others, they try to drive the system to extinction (e.g. pest control). Often the worst strategy for the leader is to adopt a constant aggressive strategy (e.g. overfishing in fisheries management or maximum tolerable dose in cancer treatment). Taking into account the ecological dynamics typically leads to better outcomes for the leader and corresponds to the Nash equilibria in game-theoretic terms. However, the leader's most profitable strategy is to anticipate and steer the eco-evolutionary dynamics, leading to the Stackelberg equilibrium of the game. We show how our results have the potential to help in fields where humans try to bring an evolutionary system into the desired outcome, such as, among others, fisheries management, pest management and cancer treatment. Finally, we discuss limitations and opportunities for applying SEGs to improve the management of evolving biological systems. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'. [ABSTRACT FROM AUTHOR]

A current challenge in cancer treatment is drug resistance. Even the most effective therapies often fail to produce a complete and durable tumor response and ultimately give rise to therapy resistance and tumor relapse. However, how resistance arises in cancer remains incompletely understood. While drug resistance in cancer is thought to be driven by irreversible genetic mutations, emerging evidence also implicates reversible proteomic and epigenetic mechanisms in the development of drug resistance. Tumor microenvironment-mediated mechanisms and tumor heterogeneity can significantly contribute to cancer treatment resistance. Here, we discuss the diverse and dynamic strategies that cancers use to evade drug response, the promise of upfront combination and intermittent therapies and therapy switching in forestalling resistance, and epigenetic reprogramming to combat resistance.

Abstract Background Central conventional chondrosarcoma (CS) is the most common subtype of primary malignant bone tumour in adults. Treatment options are usually limited to surgery, and prognosis is challenging. These tumours are characterised by the presence and absence of IDH1 and IDH2 mutations, and recently, TERT promoter alterations have been reported in around 20% of cases. The effect of these mutations on clinical outcome remains unclear. The purpose of this study was to determine if prognostic accuracy can be improved by the addition of genomic data, and specifically by examination of IDH1, IDH2, and TERT mutations. Methods In this study, we combined both archival samples and data sourced from the Genomics England 100,000 Genomes Project (n = 356). Mutations in IDH1, IDH2, and TERT were profiled using digital droplet PCR (n = 346), whole genome sequencing (n=68), or both (n = 64). Complex events and other genetic features were also examined, along with methylation array data (n = 84). We correlated clinical features and patient outcomes with our genetic findings. Results IDH2-mutant tumours occur in older patients and commonly present with high-grade or dedifferentiated disease. Notably, TERT mutations occur most frequently in IDH2-mutant tumours, although have no effect on survival in this group. In contrast, TERT mutations are rarer in IDH1-mutant tumours, yet they are associated with a less favourable outcome in this group. We also found that methylation profiles distinguish IDH1- from IDH2-mutant tumours. IDH wild-type tumours rarely exhibit TERT mutations and tend to be diagnosed in a younger population than those with tumours harbouring IDH1 and IDH2 mutations. A major genetic feature of this group is haploidisation and subsequent genome doubling. These tumours evolve less frequently to dedifferentiated disease and therefore constitute a lower risk group. Conclusions Tumours with IDH1 or IDH2 mutations or those that are IDHwt have significantly different genetic pathways and outcomes in relation to TERT mutation. Diagnostic testing for IDH1, IDH2, and TERT mutations could therefore help to guide clinical monitoring and prognostication.

An increase in centrosome number is commonly observed in cancer cells, but the role centrosome amplification plays along with how and when it occurs during cancer development is unclear. One mechanism for generating cancer cells with extra centrosomes is whole genome doubling (WGD), an event that occurs in over 30% of human cancers and is associated with poor survival. Newly formed tetraploid cells can acquire extra centrosomes during WGD, and a generally accepted model proposes that centrosome amplification in tetraploid cells promotes cancer progression by generating aneuploidy and chromosomal instability. Recent findings, however, indicate that newly formed tetraploid cells in vitro lose their extra centrosomes to prevent multipolar cell divisions. Rather than persistent centrosome amplification, this evidence raises the possibility that it may be advantageous for tetraploid cells to initially restore centrosome number homeostasis and for a fraction of the population to reacquire additional centrosomes in the later stages of cancer evolution. In this review, we explore the different evolutionary paths available to newly formed tetraploid cells, their effects on centrosome and chromosome number distribution in daughter cells, and their probabilities of long-term survival. We then discuss the mechanisms that may alter centrosome and chromosome numbers in tetraploid cells and their relevance to cancer progression following WGD.

Macrophages are versatile and heterogeneous innate immune cells undertaking central functions in balancing immune responses and tissue repair to maintain homeostasis. This plasticity, once co-opted by malignant outgrowth, orchestrates manifold reciprocal interactions within the tumor microenvironment, fueling the evolution of the cancer ecosystem. Here, we review the multilayered sources of influence that jointly underpin and longitudinally shape tumor-associated macrophage (TAM) phenotypic states in solid neoplasms. We discuss how, in response to these signals, TAMs steer tumor evolution in the context of natural selection, biological dispersion, and treatment resistance. A number of research frontiers to be tackled are laid down in this review to therapeutically exploit the complex roles of TAMs in cancer. Building upon knowledge obtained from currently applied TAM-targeting strategies and using next generation technologies, we propose conceptual advances and novel therapeutic avenues to rewire TAM multifaceted regulation of the co-evolving cancer ecosystem. Tumor-associated macrophages (TAMs) fuel the evolution of the cancer ecosystem. This review discusses recent advances in our knowledge of macrophages in the tumor microenvironment, broadly covering TAM functions, factors that shape macrophage heterogeneity, macrophage and tumor co-evolution, and therapeutic opportunities. [ABSTRACT FROM AUTHOR]