Cancer as an evolutionary and ecological process

Polyploidy as an Adaptation against Loss of Heterozygosity in Cancer

Polyploidy is common in cancer cells and has implications for tumor progression and resistance to therapies, but it is unclear whether it is an adaptation of the tumor or the non-adaptive effect of genomic instability. I discuss the possibility that polyploidy reduces the deleterious effects of loss of heterozygosity, which arises as a consequence of mitotic recombination, and which in diploid cells leads instead to the rapid loss of complementation of recessive deleterious mutations. I use computational predictions of loss of heterozygosity to show that a population of diploid cells dividing by mitosis with recombination can be easily invaded by mutant polyploid cells or cells that divide by endomitosis, which reduces loss of complementation, or by mutant cells that occasionally fuse, which restores heterozygosity. A similar selective advantage of polyploidy has been shown for the evolution of different types of asexual reproduction in nature. This provides an adaptive explanation for cyclical ploidy, mitotic slippage and cell fusion in cancer cells.

Dynamic Co-Evolution of Cancer Cells and Cancer-Associated Fibroblasts: Role in Right- and Left-Sided Colon Cancer Progression and Its Clinical Relevance

Simple Summary

The versatile crosstalk between cancer cells and cancer-associated fibroblasts (CAFs) of the tumour microenvironment (TME) drives colorectal carcinogenesis and heterogeneity. Colorectal cancer (CRC) can be classified by the anatomical sites from which the cancer arises, either from the right or left colon. Although the cancer cell–CAF interaction is being widely studied, its role in the progression of cancer in the right and left colon and cancer heterogeneity are still yet to be elucidated. Further insight into the complex interaction between different cellular components in the cancer niche, their evolutionary process and their influence on cancer progression would propel the discovery of effective targeted CRC therapy.

Abstract

Cancer is a result of a dynamic evolutionary process. It is composed of cancer cells and the tumour microenvironment (TME). One of the major cellular constituents of TME, cancer-associated fibroblasts (CAFs) are known to interact with cancer cells and promote colorectal carcinogenesis. The accumulation of these activated fibroblasts is linked to poor diagnosis in colorectal cancer (CRC) patients and recurrence of the disease. However, the interplay between cancer cells and CAFs is yet to be described, especially in relation to the sidedness of colorectal carcinogenesis. CRC, which is the third most commonly diagnosed cancer globally, can be classified according to the anatomical region from which they originate: left-sided (LCRC) and right-sided CRC (RCR). Both cancers differ in many aspects, including in histology, evolution, and molecular signatures. Despite occurring at lower frequency, RCRC is often associated with worse diagnosis compared to LCRC. The differences in molecular profiles between RCRC and LCRC also influence the mode of treatment that can be used to specifically target these cancer entities. A better understanding of the cancer cell–CAF interplay and its association with RCRC and LRCR progression will provide better insight into potential translational aspects of targeted treatment for CRC.

Educational Programme for Cancer Nurses in Genetics, Health Behaviors and Cancer Prevention: A Multidisciplinary Consensus Study

(1) Background: Most common hereditary cancers in Europe have been associated with lifestyle behaviors, and people affected are lacking follow up care. However, access to education programmes to increase knowledge on cancer and genetics and promote healthy lifestyle behaviors in people at high risk of cancer is scarce. This affects the quality of care of people with a hereditary risk of cancer. This study aimed to reach a multidisciplinary consensus on topics and competencies and competencies that cancer nurses need in relation to cancer, genetics, and health promotion. (2) Methods: A two-round online Delphi study was undertaken. Experts in cancer and genetics were asked to assess the relevance of eighteen items and to suggest additional terms. Consensus was defined as an overall agreement of at least 75%. (3) Results: A total of 74 multiprofessional experts from all around the world participated in this study including healthcare professionals working in genetics (39%), researchers in cancer and genetics (31%) and healthcare professionals with cancer patients (30%). Thirteen additional items were proposed. A total of thirty-one items reached consensus. (4) Conclusions: This multidisciplinary consensus study provide the essential elements to build an educational programme to increase cancer nurses’ skills to support the complex care of people living with a higher risk of cancer including addressing lifestyle behaviors. All professionals highlighted the importance of cancer nurses increasing their skills in cancer and genetics.

A "conversion-deterioration-double mutation" theory for the evolution and progression of colorectal cancer

In this study, based on some clinical phenomena and recently published knowledge, we proposed our "conversion-deterioration-double mutation" theory, which provides a possible unifying explanation for the evolutionary process of colorectal cancer cells in the human body. In this theory, we proposed that there is a partial interconversion and a jump conversion relationship among normal colorectal epithelial cells, colorectal cancer cells, stem cells, and cancer stem cells (conversion). This conversion leads to tumor heterogeneity. We also proposed that well-differentiated cancer cells converted from cancer stem cells have a more aggressive pattern than primary cancer cells (deterioration). The deterioration of primary cancer cells leads to differences in treatment responses and prognosis. Finally, we speculate a double mutation theory, indicating that for metastasis to occur, both mutations of cancer cells and mutations of target organs are needed and should match and meet. All these three points constitute the "conversion-deterioration-double mutation" theory.

Application and prospect of single-cell sequencing in cancer metastasis

Cancer metastasis is a complicated process driven by internal genetic variations and developed through interactions with the external environment. This process usually causes therapeutic resistance and results in a low survival rate. In recent years, single-cell sequencing has become a popular method for revealing the tumor evolutionary genetic lineage, intra-tumoral heterogeneity and tumor microenvironment of the metastasis process. So as to find more therapeutic targets for clinical application, the spatial transcriptomics method has become a new rising field of cancer studies, which promotes the combination between clinical medicine and molecular biology. In future prospects, more accurate and personalized treatment models will come into reality.

Scales of Cancer Evolution: Selfish Genome or Cooperating Cells?

Simple Summary

Cancer continuously evolves its ability to survive in time-varying microenvironment, which results, regarding the therapeutic context, in its therapeutic resistance. As it is accepted that the development of resistance is the direct consequence of intratumour heterogeneity, its evolutionary etiology is intensively studied. Models of carinogenesis are often assessed accordingly to how well they fit into the evolutionary scenario. In the paper, the relevant observations and concepts in cancer research, such as intratumour heterogeneity, cell plasticity, and Markov cell state dynamics, are reviewed and integrated into an evolutionary model. The possibility that the interaction between cancer cells can be interpreted as cooperation is proposed.

Abstract

The exploitation of the evolutionary modus operandi of cancer to steer its progression towards drug sensitive cancer cells is a challenging research topic. Integrating evolutionary principles into cancer therapy requires properly identified selection level, the relevant timescale, and the respective fitness of the principal selection unit on that timescale. Interpretation of some features of cancer progression, such as increased heterogeneity of isogenic cancer cells, is difficult from the most straightforward evolutionary view with the cancer cell as the principal selection unit. In the paper, the relation between the two levels of intratumour heterogeneity, genetic, due to genetic instability, and non-genetic, due to phenotypic plasticity, is reviewed and the evolutionary role of the latter is outlined. In analogy to the evolutionary optimization in a changing environment, the cell state dynamics in cancer clones are interpreted as the risk diversifying strategy bet hedging, optimizing the balance between the exploitation and exploration of the cell state space.

GLUT1 production in cancer cells: a tragedy of the commons

The tragedy of the commons occurs when competition among individual members of a group leads to overexploitation of a shared resource to the detriment of the overall population. We hypothesize that cancer cells may engage in a tragedy of the commons when competing for a shared resource such as glucose. To formalize this notion, we create a game theoretic model of glucose uptake based on a cell’s investment in transporters relative to that of its neighboring cells. We show that production of transporters per cell increases as the number of competing cells in a microenvironment increases and nutrient uptake per cell decreases. Furthermore, the greater the resource availability, the more intense the tragedy of the commons at the ESS. Based on our simulations, cancer cells produce 2.2–2.7 times more glucose transporters than would produce optimal fitness for all group members. A tragedy of the commons affords novel therapeutic strategies. By simulating GLUT1 inhibitor and glucose deprivation treatments, we demonstrate a synergistic combination with standard-of-care therapies, while also displaying the existence of a trade-off between competition among cancer cells and depression of their gain function. Assuming cancer cell transporter production is heritable, we then show the potential for a sucker’s gambit therapy by exploiting this trade-off. By strategically changing environmental conditions, we can take advantage of cellular competition and gain function depression.

The foundational framework of tumors: Gametogenesis, p53, and cancer

The completion-of-tumor hypothesis involved in the dynamic interplay between the initiating oncogenic event and progression is essential to better recognize the foundational framework of tumors. Here we review and extend the gametogenesis-related hypothesis of tumors, because high embryonic/germ cell traits are common in tumors. The century-old gametogenesis-related hypothesis of tumors postulated that tumors arise from displaced/activated trophoblasts, displaced (lost) germ cells, and the reprogramming/reactivation of gametogenic program in somatic cells. Early primordial germ cells (PGCs), embryonic stem (ES) cells, embryonic germ cells (EGCs), and pre-implantation embryos at the stage from two-cell stage to blastocysts originating from fertilization or parthenogenesis have the potential to develop teratomas/teratocarcinomas. In addition, the teratomas/teratocarcinomas/germ cells occur in gonads and extra-gonads. Undoubtedly, the findings provide strong support for the hypothesis. However, it was thought that these tumor types were an exception rather than verification. In fact, there are extensive similarities between somatic tumor types and embryonic/germ cell development, such as antigens, migration, invasion, and immune escape. It was documented that embryonic/germ cell genes play crucial roles in tumor behaviors, e.g. tumor initiation and metastasis. Of note, embryonic/germ cell-like tumor cells at different developmental stages including PGC and oocyte to the early embryo-like stage were identified in diverse tumor types by our group. These embryonic/germ cell-like cancer cells resemble the natural embryonic/germ cells in morphology, gene expression, the capability of teratoma formation, and the ability to undergo the process of oocyte maturation and parthenogenesis. These embryonic/germ cell-like cancer cells are derived from somatic cells and contribute to tumor formation, metastasis, and drug resistance, establishing asexual meiotic embryonic life cycle. p53 inhibits the reactivation of embryonic/germ cell state in somatic cells and oocyte-like cell maturation. Based on earlier and our recent studies, we propose a novel model to complete the gametogenesis-related hypothesis of tumors, which can be applied to certain somatic tumors. That is, tumors tend to establish a somatic asexual meiotic embryonic cycle through the activation of somatic female gametogenesis and parthenogenesis in somatic tumor cells during the tumor progression, thus passing on corresponding embryonic/germ cell traits leading to the malignant behaviors and enhancing the cells' independence. This concept may be instrumental to better understand the nature and evolution of tumors. We rationalize that targeting the key events of somatic pregnancy is likely a better therapeutic strategy for cancer treatment than directly targeting cell mitotic proliferation, especially for those tumors with p53 inactivation.

SPF: A spatial and functional data analytic approach to cell imaging data

The tumor microenvironment (TME), which characterizes the tumor and its surroundings, plays a critical role in understanding cancer development and progression. Recent advances in imaging techniques enable researchers to study spatial structure of the TME at a single-cell level. Investigating spatial patterns and interactions of cell subtypes within the TME provides useful insights into how cells with different biological purposes behave, which may consequentially impact a subject's clinical outcomes. We utilize a class of well-known spatial summary statistics, the K-function and its variants, to explore inter-cell dependence as a function of distances between cells. Using techniques from functional data analysis, we introduce an approach to model the association between these summary spatial functions and subject-level outcomes, while controlling for other clinical scalar predictors such as age and disease stage. In particular, we leverage the additive functional Cox regression model (AFCM) to study the nonlinear impact of spatial interaction between tumor and stromal cells on overall survival in patients with non-small cell lung cancer, using multiplex immunohistochemistry (mIHC) data. The applicability of our approach is further validated using a publicly available multiplexed ion beam imaging (MIBI) triple-negative breast cancer dataset.

Varied solutions to multicellularity: The biophysical and evolutionary consequences of diverse intercellular bonds

The diversity of multicellular organisms is, in large part, due to the fact that multicellularity has independently evolved many times. Nonetheless, multicellular organisms all share a universal biophysical trait: cells are attached to each other. All mechanisms of cellular attachment belong to one of two broad classes; intercellular bonds are either reformable or they are not. Both classes of multicellular assembly are common in nature, having independently evolved dozens of times. In this review, we detail these varied mechanisms as they exist in multicellular organisms. We also discuss the evolutionary implications of different intercellular attachment mechanisms on nascent multicellular organisms. The type of intercellular bond present during early steps in the transition to multicellularity constrains future evolutionary and biophysical dynamics for the lineage, affecting the origin of multicellular life cycles, cell-cell communication, cellular differentiation, and multicellular morphogenesis. The types of intercellular bonds used by multicellular organisms may thus result in some of the most impactful historical constraints on the evolution of multicellularity.

Development and validation of a computed tomography-based immune ecosystem diversity index as an imaging biomarker in non-small cell lung cancer

OBJECTIVES

To date, there are no data on the noninvasive surrogate of intratumoural immune status that could be prognostic of survival outcomes in non-small cell lung cancer (NSCLC). We aimed to develop and validate the immune ecosystem diversity index (iEDI), an imaging biomarker, to indicate the intratumoural immune status in NSCLC. We further investigated the clinical relevance of the biomarker for survival prediction.

METHODS

In this retrospective study, two independent NSCLC cohorts (Resec1, n = 149; Resec2, n = 97) were included to develop and validate the iEDI to classify the intratumoural immune status. Paraffin-embedded resected specimens in Resec1 and Resec2 were stained by immunohistochemistry, and the density percentiles of CD3⁺, CD4⁺, and CD8⁺ T cells to all cells were quantified to estimate intratumoural immune status. Then, EDI features were extracted using preoperative computed tomography to develop an imaging biomarker, called iEDI, to determine the immune status. The prognostic value of iEDI was investigated on NSCLC patients receiving surgical resection (Resec1; Resec2; internal cohort Resec3, n = 419; external cohort Resec4, n = 96; and TCIA cohort Resec5, n = 55).

RESULTS

iEDI successfully classified immune status in Resec1 (AUC 0.771, 95% confidence interval [CI] 0.759-0.783; and 0.770 through internal validation) and Resec2 (0.669, 0.647-0.691). Patients with higher iEDI-score had longer overall survival (OS) in Resec3 (unadjusted hazard ratio 0.335, 95%CI 0.206-0.546, p < 0.001), Resec4 (0.199, 0.040-1.000, p < 0.001), and TCIA (0.303, 0.098-0.944, p = 0.001).

CONCLUSIONS

iEDI is a non-invasive surrogate of intratumoural immune status and prognostic of OS for NSCLC patients receiving surgical resection.

KEY POINTS

• Decoding tumour immune microenvironment enables advanced biomarkers identification. • Immune ecosystem diversity index characterises intratumoural immune status noninvasively. • Immune ecosystem diversity index is prognostic for NSCLC patients.

Cancer evolution: special focus on the immune aspect of cancer

Cancer is an evolutionary disease. Intra-tumor heterogeneity (ITH), which describes the diversity within individual tumors, sets the foundation for evolution. The fitness of tumor cells is determined by their microenvironment, which exerts intense selection pressure that generally favors cells with survival and proliferation advantages. It has been revealed that host immunity dramatically influences the evolutionary trajectory of cancer. As technologies advance, a refined map of the immune system's involvement in cancer evolution has gradually come to our knowledge. Here we specifically view cancer through the lens of evolutionary immunological biology. We will cover the neoplastic evolution under immunosurveillance, including how the host immunity shapes the tumor evolutionary trajectory and how progressive tumors modulate the host immunity to survive. A comprehensive understanding of the interplay between cancer evolution and cancer immunity provides clues to combating cancer strategically.

Hallmarks of cancer and hallmarks of aging

A thought-provoking article by Gems and de Magalhães suggests that canonic hallmarks of aging are superficial imitations of hallmarks of cancer. I took their work a step further and proposed hallmarks of aging based on a hierarchical principle and the hyperfunction theory.

To do this, I first reexamine the hallmarks of cancer proposed by Hanahan and Weinberg in 2000. Although six hallmarks of cancer are genuine, they are not hierarchically arranged, i.e., molecular, intra-cellular, cellular, tissue, organismal and extra-organismal. (For example, invasion and angiogenesis are manifestations of molecular alterations on the tissue level; metastasis on the organismal level, whereas cell immortality is observed outside the host).

The same hierarchical approach is applicable to aging. Unlike cancer, however, aging is not a molecular disease. The lowest level of its origin is normal intracellular signaling pathways such as mTOR that drive developmental growth and, later in life, become hyperfunctional, causing age-related diseases, whose sum is aging. The key hallmark of organismal aging, from worms to humans, are age-related diseases. In addition, hallmarks of aging can be arranged as a timeline, wherein initial hyperfunction is followed by dysfunction, organ damage and functional decline.

Attribution of Cancer Origins to Endogenous, Exogenous, and Preventable Mutational Processes

Mutational processes in tumors create distinctive patterns of mutations, composed of neutral "passenger" mutations and oncogenic drivers that have quantifiable effects on the proliferation and survival of cancer cell lineages. Increases in proliferation and survival are mediated by natural selection, which can be quantified by comparing the frequency at which we detect substitutions to the frequency at which we expect to detect substitutions assuming neutrality. Most of the variants detectable with whole-exome sequencing in tumors are neutral or nearly neutral in effect, and thus the processes generating the majority of mutations may not be the primary sources of the tumorigenic mutations. Across 24 cancer types, we identify the contributions of mutational processes to each oncogenic variant and quantify the degree to which each process contributes to tumorigenesis. We demonstrate that the origination of variants driving melanomas and lung cancers is predominantly attributable to the preventable, exogenous mutational processes associated with ultraviolet light and tobacco exposure, respectively, whereas the origination of selected variants in gliomas and prostate adenocarcinomas is largely attributable to endogenous processes associated with aging. Preventable mutations associated with pathogen exposure and apolipoprotein B mRNA-editing enzyme activity account for a large proportion of the cancer effect within head-and-neck, bladder, cervical, and breast cancers. These attributions complement epidemiological approaches-revealing the burden of cancer driven by single-nucleotide variants caused by either endogenous or exogenous, nonpreventable, or preventable processes, and crucially inform public health strategies.

Cancer cell foraging to explain bone-specific metastatic progression

Metastatic cancer is lethal and patients who suffer bone metastases fare especially poorly. Bone-specific metastatic progression in prostate and breast cancers is a highly observed example of organ-specific metastasis, or organotropism. Though research has delineated the sequential steps of the metastatic cascade, the determinants of bone-specific metastasis have remained elusive for decades. Applying fundamental ecological principles to cancer biology models of metastasis provides novel insights into metastatic organotropism. We use critical concepts from foraging theory and movement ecology to propose that observed bone-specific metastasis is the result of habitat selection by foraging cancer cells. Furthermore, we posit that cancer cells can only perform habitat selection if and when they employ a reversible motile foraging strategy. Only a very small percentage of cells in a primary tumor harbor this ability. Therefore, our habitat selection model emphasizes the importance of identifying the rare subset of cancer cells that might exhibit habitat selection, ergo achieve bone-specific metastatic colonization.

Microbiome in cancer: Role in carcinogenesis and impact in therapeutic strategies

Cancer is the world's second-leading cause of death, and the involvement of microbes in a range of diseases, including cancer, is well established. The gut microbiota is known to play an important role in the host's health and physiology. The gut microbiota and its metabolites may activate immunological and cellular pathways that kill invading pathogens and initiate a cancer-fighting immune response. Cancer is a multiplex illness, characterized by the persistence of several genetic and physiological anomalies in malignant tissue, complicating disease therapy and control. Humans have coevolved with a complex bacterial, fungal, and viral microbiome over millions of years. Specific long-known epidemiological links between certain bacteria and cancer have recently been grasped at the molecular level. Similarly, advances in next-generation sequencing technology have enabled detailed research of microbiomes, such as the human gut microbiome, allowing for the finding of taxonomic and metabolomic linkages between the microbiome and cancer. These investigations have found causative pathways for both microorganisms within tumors and bacteria in various host habitats far from tumors using direct and immunological procedures. Anticancer diagnostic and therapeutic solutions could be developed using this review to tackle the threat of anti-cancer medication resistance as well through the wide-ranging involvement of the microbiota in regulating host metabolic and immunological homeostasis. We reviewed the significance of gut microbiota in cancer initiation as well as cancer prevention. We look at certain microorganisms that may play a role in the development of cancer. Several bacteria with probiotic qualities may be employed as bio-therapeutic agents to re-establish the microbial population and trigger a strong immune response to remove malignancies, and further study into this should be conducted.

Dissecting the Genetic and Non-Genetic Heterogeneity of Acute Myeloid Leukemia Using Next-Generation Sequencing and In Vivo Models

Simple Summary

Acute myeloid leukemia (AML) is an extremely aggressive form of blood cancer with high rates of treatment failure. AML arises from the stepwise acquisition of genetic aberrations and is a highly heterogeneous disorder. Recent research has shown that individual AML samples often contain several clones that are defined by a distinct combination of genetic lesions, epigenetic patterns and cell surface marker expression profiles. A better understanding of the clonal dynamics of AML is required to develop novel treatment strategies against this disease. In this review, we discuss the recent developments that have further deepened our understanding of clonal evolution and heterogeneity in AML.

Abstract

Acute myeloid leukemia (AML) is an extremely aggressive and heterogeneous disorder that results from the transformation of hematopoietic stem cells. Although our understanding of the molecular pathology of AML has greatly improved in the last few decades, the overall and relapse free survival rates among AML patients remain quite poor. This is largely due to evolution of the disease and selection of the fittest, treatment-resistant leukemic clones. There is increasing evidence that most AMLs possess a highly complex clonal architecture and individual leukemias are comprised of genetically, phenotypically and epigenetically distinct clones, which are continually evolving. Advances in sequencing technologies as well as studies using murine AML models have provided further insights into the heterogeneity of leukemias. We will review recent advances in the field of genetic and non-genetic heterogeneity in AML.

Heterogeneity of the tumor immune microenvironment and its clinical relevance

During the course of tumorigenesis and subsequent metastasis, malignant cells gradually diversify and become more heterogeneous. Consequently, the tumor mass might be infiltrated by diverse immune-related components, including the cytokine/chemokine environment, cytotoxic activity, or immunosuppressive elements. This immunological heterogeneity is universally presented spatially or varies temporally along with tumor evolution or therapeutic intervention across almost all solid tumors. The heterogeneity of anti-tumor immunity shows a profound association with the progression of disease and responsiveness to treatment, particularly in the realm of immunotherapy. Therefore, an accurate understanding of tumor immunological heterogeneity is essential for the development of effective therapies. Facilitated by multi-regional and -omics sequencing, single cell sequencing, and longitudinal liquid biopsy approaches, recent studies have demonstrated the potential to investigate the complexity of immunological heterogeneity of the tumors and its clinical relevance in immunotherapy. Here, we aimed to review the mechanism underlying the heterogeneity of the immune microenvironment. We also explored how clinical assessments of tumor heterogeneity might facilitate the development of more effective personalized therapies.

Dual-Targeting of Tumor Cells and Tumor-Associated Macrophages by Palmitic Acid Modified Albumin Nanoparticles for Antitumor and Antimetastasis Therapy

Tumor-associated macrophages (TAMs), the most abundant immune cells in the tumor microenvironment (TME), profoundly affect the occurrence and development of tumors. To overcome the common limitations of TAMs-targeted delivery systems, such as off-target toxicity, high cost, and transformation probability, we fabricated pirarubicin (THP)-loaded palmitic acid modified human serum albumin nanoparticles (THP-PSA NPs) for dual-targeting of tumor cells and TAMs via acidic secretory proteins rich in cysteine (SPARC) and scavenger receptor-A (SR-A), respectively. In vitro, the THP-PSA NPs exhibit stronger cytotoxicity against 4T1 and M2 macrophages compared with THP-loaded human serum albumin nanoparticles (THP-HSA NPs). In vivo, the infiltration of myeloid-derived suppressor cells (MDSCs) and the secretion of immunosuppressive cytokines significantly decrease after effective elimination of the TAMs through the THP-PSA NPs treatment; this is accompanied by an increase in the immunostimulatory cytokine expression level. Moreover, the antitumor and antimetastasis experimental results indicate that the tumor volumes in mice treated with the THP-PSA NPs are effectively controlled, resulting in an inhibition rate of 81.0% and almost no metastases in the lung tissues. Finally, in terms of biological safety, the THP-PSA NPs perform similar to THP-HSA NPs, causing no damage to the liver or kidney.

[Lipidomic markers of tumor progress in breast cancer patients]

Research of cancer progression mechanisms and their impact on metabolism of tumor cells and tumor microenvironment cells is an important element in drug development for cancer target therapy. In this study, changes in tumor tissue and margin tissue lipid profiles, were associated with the following clinical and morphological characteristics: tumor size, cancer stage, multifocalite, tumor grade, number of lymph node metastasis, Nottingham prognostic index, total malignancy score, level of Ki67 protein. Lipid profiling was performed by reverse-phase chromato-mass spectrometry analysis of lipid tissue extract with lipid identification by characteristic fragments. In the lipid profile of tumor tissue 13 characteristic lipids were selected. Their levels significantly correlated with at least 5 clinical and morphological features. Eight of 13 belonged to phosphatidylcholines. In lipid profile of tumor microenviroment tissue 13 lipid features were selected. Their levels significantly correlated with at least 5 clinical and morphological features. Four of 13 belonged to oxidized lipids, 4 lipid features belonged to sphingomyelins, four of 13 belonged to phosphatidylethanolamines. The tumor microenvironment tissue lipid profile correlated with tumor size, cancer stage, tumor grade, number of axillary metastases, Nottingham prognostic index. The tumor tissue lipid profile correlated with tumor size, tumor grade, total malignant score, and number of axillary metastases.

MOCA for Integrated Analysis of Gene Expression and Genetic Variation in Single Cells

In cancer, somatic mutations occur continuously, causing cell populations to evolve. These somatic mutations result in the evolution of cellular gene expression patterns that can also change due to epigenetic modifications and environmental changes. By exploring the concordance of gene expression changes with molecular evolutionary trajectories of cells, we can examine the role of somatic variation on the evolution of gene expression patterns. We present Multi-Omics Concordance Analysis (MOCA) software to jointly analyze gene expressions and genetic variations from single-cell RNA sequencing profiles. MOCA outputs cells and genes showing convergent and divergent gene expression patterns in functional genomics.

Network medicine in ovarian cancer: topological properties to drug discovery

Network medicine provides network theoretical tools, methods and properties to study underlying laws governing human interactome to identify disease states and disease complexity leading to drug discovery. Within this framework, we investigated the topological properties of ovarian cancer network (OCN) and the roles of hubs to understand OCN organization to address disease states and complexity. The OCN constructed from the experimentally verified genes exhibits fractal nature in the topological properties with deeply rooted functional communities indicating self-organizing behavior. The network properties at all levels of organization obey one parameter scaling law which lacks centrality lethality rule. We showed that $\langle k\rangle $ can be taken as a scaling parameter, where, power law exponent can be estimated from the ratio of network diameters. The betweenness centrality $C_B$ shows two distinct behaviors one shown by high degree hubs and the other by segregated low degree nodes. The $C_B$ power law exponent is found to connect the exponents of distributions of high and low degree nodes. OCN showed the absence of rich-club formation which leads to the missing of a number of attractors in the network causing formation of weakly tied diverse functional modules to keep optimal network efficiency. In OCN, provincial and connector hubs, which includes identified key regulators, take major responsibility to keep the OCN integrity and organization. Further, most of the key regulators are found to be over expressed and positively correlated with immune infiltrates. Finally, few potential drugs are identified related to the key regulators.

ARCANE-ROG: Algorithm for Reconstruction of Cancer Evolution from single-cell data using Robust Graph Learning

Tumor heterogeneity, marked by the presence of divergent clonal subpopulations of tumor cells, impedes the treatment response in cancer patients. Single-cell sequencing technology provides substantial prospects to gain an in-depth understanding of the cellular phenotypic variability driving tumor progression. A comprehensive insight into the intra-tumor heterogeneity may further assist in dealing with the treatment-resistant clones in cancer patients, thereby improving their overall survival. However, this task is hampered due to the challenges associated with the single-cell data, such as false positives, false negatives and missing bases, and the increase in their size. As a result, the computational cost of the existing methods increases, thereby limiting their usage. In this work, we propose a robust graph learning-based method, ARCANE-ROG (Algorithm for Reconstruction of CANcer Evolution via RObust Graph learning), for inferring clonal evolution from single-cell datasets. The first step of the proposed method is a joint framework of denoising with data imputation for the noisy and incomplete matrix while simultaneously learning an adjacency graph. Both the operations in the joint framework boost each other such that the overall performance of the denoising algorithm is improved. In the second step, an optimal number of clusters are identified via the Leiden method. In the last step, clonal evolution trees are inferred via a minimum spanning tree algorithm. The method has been benchmarked against a state-of-the-art method, RobustClone, using simulated datasets of varying sizes and five real datasets. The performance of our proposed method is found to be significantly superior (p-value < 0.05) in terms of reconstruction error, False Positive to False Negative (FPFN) ratio, tree distance error and V-measure compared to the other method. Overall, the proposed method is an improvement over the existing methods as it enhances cluster assignment and inference on clonal hierarchies.

Comparison between short-term stress and long-term adaptive responses reveal common paths to molecular adaptation

The phenotypic plasticity in responses to short-term stress can provide clues for understanding the adaptive fixation mechanism of genetic variation during long-term exposure to extreme environments. However, few studies have compared short-term stress responses with long-term evolutionary patterns; in particular, no interactions between the two processes have been evaluated in high-altitude environment. We performed RNA sequencing in embryo fibroblasts derived from great tits and mice to explore transcriptional responses after exposure to simulated high-altitude environmental stresses. Transcriptional changes of genes associated with metabolic pathways were identified in both bird and mice cells after short-term stress responses. Genomic comparisons among long-term highland tits and mammals and their lowland relatives revealed similar pathways (e.g., metabolic pathways) with that initiated under short-term stress transcriptional responses in vitro. These findings highlight the indicative roles of short-term stress in the long-term adaptation, and adopt common paths to molecular adaptation in mouse and bird cells.

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Short-term stress and long-term adaptations share the common metabolic pathways

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Phenotypic plasticity can promote adaptive evolution

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Adopt common paths to molecular adaptation in mouse and bird cells

Promotion of tumor progression by exosome transmission of circular RNA circSKA3

We performed in vitro and in vivo experiments to investigate the role of the circular RNA circSKA3 in tumor development. We examined the effects of circSKA3 on mediating breast cancer metastasis. In vitro, we found that the circular RNA circSKA3 was transferred between breast cancer cells, which were decreased by inhibiting exosome secretion. In vivo, circSKA3-containing exosomes potentiated tumor development and invasion that were inhibited by blocking exosome transmission. The ascites isolated from tumor-bearing mice or breast cancer patients showed high levels of circSKA3 and integrin β1. Single-cell culture and single-cell PCR showed that circSKA3 was heterogeneously expressed, the cells expressing higher levels of circSKA3 had a higher potential to form large colonies. This property was similar to c-myc, but circSKA3 expression had no correlation with c-myc levels. The effects of circSKA3 on cell migration and invasion appeared to predominate c-myc functions. By releasing circSKA3-containing exosomes to cancer cells expressing lower levels of circSKA3, the large colonies could regulate the activities of small colonies, enhancing the tumor-forming capacity of the entire population. Thus, we provide evidence that the transmission of circular RNAs in tumor-derived exosomes may allow for the maintenance of advantageous invasive sub-clones in breast cancer.

Bifurcation and chaos analysis of tumor growth

In this paper, a dynamic model given by three-dimensional ordinary differential equations is studied to determine how the dynamics of tumor growth is controlled by some key parameters. By varying the competition coefficient between healthy host cells and tumor cells, a Hopf bifurcation occurs in this system, leading to the creation of a stable limit cycle. Through numerical analysis of the continuity of this limit cycle, we find that the cascade of period-doubling bifurcations leads to the generation of a chaotic attractor. Moreover, the region of attractors is shown in the parameter space. Numerical simulations, bifurcation diagrams, Lyapunov exponent graph and phase portraits permit to highlight the rich and complex phenomena presented by the model.

Combining Evolution and Cancer Therapy: A Review of the Mathematical Approach

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Conventional cancer therapy kills tumors by applying the maximum tolerable dose of therapy. However, it leads to the development of tumoral heterogeneity and resistance, hence leading to therapy failure and progression. It is necessary to design therapies keeping in mind the evolutionary dynamics of tumors to minimize resistance and delay progression. Mathematical models are of great importance in oncology as they assist in the recreation of the tumor microenvironment, predict the outcomes of treatment strategies and elucidate fundamentals of tumor growth and resistance development. The body of literature covering models which incorporate evolutionary dynamics is vast. This paper provides an overview of existing models of “evolutionary therapy”, including ordinary differential equations, fitness, and probability functions.

A bone paradigm challenging the standard model of myeloma oncogenesis

The standard model of multiple myeloma (MM) oncogenesis from monoclonal gammopathy of undetermined significance (MGUS) relies on genetic instability in the normal counterparts of MM cells. However, the importance of both MGUS-associated and MM-induced bone changes has been recently re-appraised, emphasizing the bone microenvironment (BME) as a tissue of significance. In this review, we propose that early BME alterations (bone senescence and inflammation, i.e. bone inflamm'aging) at the pre-MGUS stage could be causal, and not simply permissive, and creative of phenotypic instability and genetic alterations thanks to the concept of tissue disruption-induced cell stochasticity (TiDiS). This article offers a bone scenario challenging the chromosome-and-gene-centric standard model of MM oncogenesis. The high incidence of both MGUS and MM in Gaucher disease supports such a scenario.

Evolutionary dynamics in Barrett oesophagus: implications for surveillance, risk stratification and therapy

Cancer development is a dynamic evolutionary process characterized by marked intratumoural heterogeneity at the genetic, epigenetic and phenotypic levels. Barrett oesophagus, the pre-malignant condition to oesophageal adenocarcinoma (EAC), is an exemplary system to longitudinally study the evolution of malignancy. Evidence has emerged of Barrett oesophagus lesions pre-programmed for progression to EAC many years before clinical detection, indicating a considerable window for therapeutic intervention. In this Review, we explore the mechanisms underlying clonal expansion and contraction that establish the Barrett oesophagus clonal mosaicism over time and space and discuss intrinsic genotypic and extrinsic environmental drivers that direct the evolutionary trajectory of Barrett oesophagus towards a malignant phenotype. We propose that understanding and exploiting the evolutionary dynamics of Barrett oesophagus will identify novel therapeutic targets, improve prognostic tools and offer the opportunity for personalized surveillance programmes geared to prevent progression to EAC.

Metabolic Features of Tumor Dormancy: Possible Therapeutic Strategies

Simple Summary

Tumor recurrence still represents a major clinical challenge for cancer patients. Cancer cells may undergo a dormant state for long times before re-emerging. Both intracellular- and extracellular-driven pathways are involved in maintaining the dormant state and the subsequent awakening, with a mechanism that is still mostly unknown. In this scenario, cancer metabolism is emerging as a critical driver of tumor progression and dissemination and have gained increasing attention in cancer research. This review focuses on the metabolic adaptations characterizing the dormant phenotype and supporting tumor re-growth. Deciphering the metabolic adaptation sustaining tumor dormancy may pave the way for novel therapeutic approaches to prevent tumor recurrence based on combined metabolic drugs.

Abstract

Tumor relapse represents one of the main obstacles to cancer treatment. Many patients experience cancer relapse even decades from the primary tumor eradication, developing more aggressive and metastatic disease. This phenomenon is associated with the emergence of dormant cancer cells, characterized by cell cycle arrest and largely insensitive to conventional anti-cancer therapies. These rare and elusive cells may regain proliferative abilities upon the induction of cell-intrinsic and extrinsic factors, thus fueling tumor re-growth and metastasis formation. The molecular mechanisms underlying the maintenance of resistant dormant cells and their awakening are intriguing but, currently, still largely unknown. However, increasing evidence recently underlined a strong dependency of cell cycle progression to metabolic adaptations of cancer cells. Even if dormant cells are frequently characterized by a general metabolic slowdown and an increased ability to cope with oxidative stress, different factors, such as extracellular matrix composition, stromal cells influence, and nutrient availability, may dictate specific changes in dormant cells, finally resulting in tumor relapse. The main topic of this review is deciphering the role of the metabolic pathways involved in tumor cells dormancy to provide new strategies for selectively targeting these cells to prevent fatal recurrence and maximize therapeutic benefit.

Find the path of least resistance: Adaptive therapy to delay treatment failure and improve outcomes

Cytotoxic chemotherapy and targeted therapies help people with advanced cancers, but for most, treatment fails. Cancer heterogeneity is one cause of treatment failure, but also suggests an opportunity to improve outcomes; reconceptualising cancer therapy as an ecological problem offers the strategy of adaptive therapy. If an agent is active against a patient's cancer, instead of traditional continuous dosing at the maximum tolerated dose until treatment failure, the patient and their oncologist may instead choose to pause treatment as soon as the cancer responds. When tumour burden increases, the cancer is rechallenged with the same agent in hope of delivering another response, ideally before symptoms occur or quality-of-life is impacted. These 'loops' of 'pause/restart' allows an active treatment to be used strategically, to delay the development of evolutionary selection within the cancer, delaying the onset of treatment resistance, controlling the cancer for longer. Modelling predicts patients can navigate several 'loops', potentially increasing the utility of an active treatment by multiples, and early trials suggest at least doubling of progression-free survival. In this narrative review we confront how cancer heterogeneity limits treatment effectiveness, re-examine cancer as an ecological problem, review the data supporting adaptive therapy and outline the challenges and opportunities faced in clinical practice to implement this evolutionary concept. In an era where multiple novel active anti-neoplastic agents are being used with ancient inflexibile maximum tolerated dose for maximum duration approaches, adaptive dosing offers a personalised, n = 1 approach to cancer therapy selection.

Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study

Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution.

Gallbladder adenocarcinomas undergo subclonal diversification and selection from precancerous lesions to metastatic tumors

We aimed to elucidate the evolutionary trajectories of gallbladder adenocarcinoma (GBAC) using multi-regional and longitudinal tumor samples. Using whole-exome sequencing data, we constructed phylogenetic trees in each patient and analyzed mutational signatures. A total of 11 patients including 2 rapid autopsy cases were enrolled. The most frequently altered gene in primary tumors was ERBB2 and TP53 (54.5%), followed by FBXW7 (27.3%). Most mutations in frequently altered genes in primary tumors were detectable in concurrent precancerous lesions (biliary intraepithelial neoplasia [BilIN]), but a substantial proportion was subclonal. Subclonal diversity was common in BilIN (n=4). However, among subclones in BilIN, a certain subclone commonly shrank in concurrent primary tumors. In addition, selected subclones underwent linear and branching evolution, maintaining subclonal diversity. Combined analysis with metastatic tumors (n=11) identified branching evolution in nine patients (81.8%). Of these, eight patients (88.9%) had a total of 11 subclones expanded at least sevenfold during metastasis. These subclones harbored putative metastasis-driving mutations in cancer-related genes such as SMAD4, ROBO1, and DICER1. In mutational signature analysis, six mutational signatures were identified: 1, 3, 7, 13, 22, and 24 (cosine similarity >0.9). Signatures 1 (age) and 13 (APOBEC) decreased during metastasis while signatures 22 (aristolochic acid) and 24 (aflatoxin) were relatively highlighted. Subclonal diversity arose early in precancerous lesions and clonal selection was a common event during malignant transformation in GBAC. However, selected cancer clones continued to evolve and thus maintained subclonal diversity in metastatic tumors.

Clonal populations of a human TNBC model display significant functional heterogeneity and divergent growth dynamics in distinct contexts

Intratumoral heterogeneity has been described for various tumor types and models of human cancer, and can have profound effects on tumor progression and drug resistance. This study describes an in-depth analysis of molecular and functional heterogeneity among subclonal populations (SCPs) derived from a single triple-negative breast cancer cell line, including copy number analysis, whole-exome and RNA sequencing, proteome analysis, and barcode analysis of clonal dynamics, as well as functional assays. The SCPs were found to have multiple unique genetic alterations and displayed significant variation in anchorage independent growth and tumor forming ability. Analyses of clonal dynamics in SCP mixtures using DNA barcode technology revealed selection for distinct clonal populations in different in vitro and in vivo environmental contexts, demonstrating that in vitro propagation of cancer cell lines using different culture conditions can contribute to the establishment of unique strains. These analyses also revealed strong enrichment of a single SCP during the development of xenograft tumors in immune-compromised mice. This SCP displayed attenuated interferon signaling in vivo and reduced sensitivity to the antiproliferative effects of type I interferons. Reduction in interferon signaling was found to provide a selective advantage within the xenograft microenvironment specifically. In concordance with the previously described role of interferon signaling as tumor suppressor, these findings suggest that similar selective pressures may be operative in human cancer and patient-derived xenograft models.

Cell-of-Origin and Genetic, Epigenetic, and Microenvironmental Factors Contribute to the Intra-Tumoral Heterogeneity of Pediatric Intracranial Ependymoma

Intra-tumoral heterogeneity (ITH) is a complex multifaceted phenomenon that posits major challenges for the clinical management of cancer patients. Genetic, epigenetic, and microenvironmental factors are concurrent drivers of diversity among the distinct populations of cancer cells. ITH may also be installed by cancer stem cells (CSCs), that foster unidirectional hierarchy of cellular phenotypes or, alternatively, shift dynamically between distinct cellular states. Ependymoma (EPN), a molecularly heterogeneous group of tumors, shows a specific spatiotemporal distribution that suggests a link between ependymomagenesis and alterations of the biological processes involved in embryonic brain development. In children, EPN most often arises intra-cranially and is associated with an adverse outcome. Emerging evidence shows that EPN displays large intra-patient heterogeneity. In this review, after touching on EPN inter-tumoral heterogeneity, we focus on the sources of ITH in pediatric intra-cranial EPN in the framework of the CSC paradigm. We also examine how single-cell technology has shed new light on the complexity and developmental origins of EPN and the potential impact that this understanding may have on the therapeutic strategies against this deadly pediatric malignancy.

RDAClone: Deciphering Tumor Heterozygosity through Single-Cell Genomics Data Analysis with Robust Deep Autoencoder

Rapid advances in single-cell genomics sequencing (SCGS) have allowed researchers to characterize tumor heterozygosity with unprecedented resolution and reveal the phylogenetic relationships between tumor cells or clones. However, high sequencing error rates of current SCGS data, i.e., false positives, false negatives, and missing bases, severely limit its application. Here, we present a deep learning framework, RDAClone, to recover genotype matrices from noisy data with an extended robust deep autoencoder, cluster cells into subclones by the Louvain-Jaccard method, and further infer evolutionary relationships between subclones by the minimum spanning tree. Studies on both simulated and real datasets demonstrate its robustness and superiority in data denoising, cell clustering, and evolutionary tree reconstruction, particularly for large datasets.

Cancer Evo-Dev: A Theory of Inflammation-Induced Oncogenesis

Chronic inflammation is a prerequisite for the development of cancers. Here, we present the framework of a novel theory termed as Cancer Evolution-Development (Cancer Evo-Dev) based on the current understanding of inflammation-related carcinogenesis, especially hepatocarcinogenesis induced by chronic infection with hepatitis B virus. The interaction between genetic predispositions and environmental exposures, such as viral infection, maintains chronic non-resolving inflammation. Pollution, metabolic syndrome, physical inactivity, ageing, and adverse psychosocial exposure also increase the risk of cancer via inducing chronic low-grade smoldering inflammation. Under the microenvironment of non-resolving inflammation, pro-inflammatory factors facilitate the generation of somatic mutations and viral mutations by inducing the imbalance between the mutagenic forces such as cytidine deaminases and mutation-correcting forces including uracil-DNA glycosylase. Most cells with somatic mutations and mutated viruses are eliminated in survival competition. Only a small percentage of mutated cells survive, adapt to the hostile environment, retro-differentiate, and function as cancer-initiating cells via altering signaling pathways. These cancer-initiating cells acquire stem-ness, reprogram metabolic patterns, and affect the microenvironment. The carcinogenic process follows the law of "mutation-selection-adaptation". Chronic physical activity reduces the levels of inflammation via upregulating the activity and numbers of NK cells and lymphocytes and lengthening leukocyte telomere; downregulating proinflammatory cytokines including interleukin-6 and senescent lymphocytes especially in aged population. Anti-inflammation medication reduces the occurrence and recurrence of cancers. Targeting cancer stemness signaling pathways might lead to cancer eradication. Cancer Evo-Dev not only helps understand the mechanisms by which inflammation promotes the development of cancers, but also lays the foundation for effective prophylaxis and targeted therapy of various cancers.

Theoretical Evaluation of the Impact of Hyperthermia in Combination with Radiation Therapy in an Artificial Immune-Tumor-Ecosystem

Simple Summary

Radio-sensitizing effects of moderate or mild hyperthermia (heating up tumor cells up to 41–43 °C) in combination with radiotherapy (thermoradiotherapy) have been evaluated for decades. However, how this combination might modulate an anti-tumor immune response is not well known. To investigate the dynamic behavior of immune–tumor ecosystems in different scenarios, a model representing an artificial adaptive immune system in silico is used. Such a model may be far removed from the real situation in the patient, but it could serve as a laboratory to investigate fundamental principles of dynamics in such systems under well-controlled conditions and it could be used to generate and refine hypothesis supporting the design of clinical trials. Regarding the results of the presented computer simulations, the main effect is governed by the cellular radio-sensitization. In addition, the application of hyperthermia during the first radiotherapy fractions seems to be more effective.

Abstract

There is some evidence that radiotherapy (RT) can trigger anti-tumor immune responses. In addition, hyperthermia (HT) is known to be a tumor cell radio-sensitizer. How HT could enhance the anti-tumor immune response produced by RT is still an open question. The aim of this study is the evaluation of potential dynamic effects regarding the adaptive immune response induced by different combinations of RT fractions with HT. The adaptive immune system is considered as a trainable unit (perceptron) which compares danger signals released by necrotic or apoptotic cell death with the presence of tumor- and host tissue cell population-specific molecular patterns (antigens). To mimic the changes produced by HT such as cell radio-sensitization or increase of the blood perfusion after hyperthermia, simplistic biophysical models were included. To study the effectiveness of the different RT+HT treatments, the Tumor Control Probability (TCP) was calculated. In the considered scenarios, the major effect of HT is related to the enhancement of the cell radio-sensitivity while perfusion or heat-based effects on the immune system seem to contribute less. Moreover, no tumor vaccination effect has been observed. In the presented scenarios, HT boosts the RT cell killing but it does not fundamentally change the anti-tumor immune response.

The evolution and ecology of benign tumors

Tumors are usually classified into two main categories - benign or malignant, with much more attention being devoted to the second category given that they are usually associated with more severe health issues (i.e., metastatic cancers). Here, we argue that the mechanistic distinction between benign and malignant tumors has narrowed our understanding of neoplastic processes. This review provides the first comprehensive discussion of benign tumors in the context of their evolution and ecology as well as interactions with their hosts. We compare the genetic and epigenetic profiles, cellular activities, and the involvement of viruses in benign and malignant tumors. We also address the impact of intra-tumoral cell composition and its relationship with the tumoral microenvironment. Lastly, we explore the differences in the distribution of benign and malignant neoplasia across the tree of life and provide examples on how benign tumors can also affect individual fitness and consequently the evolutionary trajectories of populations and species. Overall, our goal is to bring attention to the non-cancerous manifestations of tumors, at different scales, and to stimulate research on the evolutionary ecology of host-tumor interactions on a broader scale. Ultimately, we suggest that a better appreciation of the differences and similarities between benign and malignant tumors is fundamental to our understanding of malignancy both at mechanistic and evolutionary levels.

Epithelial-to-Mesenchymal Transition-Derived Heterogeneity in Head and Neck Squamous Cell Carcinomas

Simple Summary

Head and neck squamous cell carcinomas (HNSCC) are common malignancies with considerable morbidity and a high death toll worldwide. Resistance towards multi-modal therapy modalities composed of surgery, irradiation, chemo- and immunotherapy represents a major obstacle in the efficient treatment of HNSCC patients. Patients frequently show nodal metastases at the time of diagnosis and endure early relapses, oftentimes in the form of local recurrences. Differentiation programs such as the epithelial-to-mesenchymal transition (EMT) allow individual tumor cells to adopt cellular functions that are central to the development of metastases and treatment resistance. In the present review article, the molecular basis and regulation of EMT and its impact on the progression of HNSCC will be addressed.

Abstract

Head and neck squamous cell carcinomas (HNSCC) are common tumors with a poor overall prognosis. Poor survival is resulting from limited response to multi-modal therapy, high incidence of metastasis, and local recurrence. Treatment includes surgery, radio(chemo)therapy, and targeted therapy specific for EGFR and immune checkpoint inhibition. The understanding of the molecular basis for the poor outcome of HNSCC was improved using multi-OMICs approaches, which revealed a strong degree of inter- and intratumor heterogeneity (ITH) at the level of DNA mutations, transcriptome, and (phospho)proteome. Single-cell RNA-sequencing (scRNA-seq) identified RNA-expression signatures related to cell cycle, cell stress, hypoxia, epithelial differentiation, and a partial epithelial-to-mesenchymal transition (pEMT). The latter signature was correlated to nodal involvement and adverse clinical features. Mechanistically, shifts towards a mesenchymal phenotype equips tumor cells with migratory and invasive capacities and with an enhanced resistance to standard therapy. Hence, gradual variations of EMT as observed in HNSCC represent a potent driver of tumor progression that could open new paths to improve the stratification of patients and to innovate approaches to break therapy resistance. These aspects of molecular heterogeneity will be discussed in the present review.

Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas

Deconstructing tissue-specific effects of genes and variants on proliferation is critical to understanding cellular transformation and systematically selecting cancer therapeutics. This requires scalable methods for multiplexed genetic screens tracking fitness across time, across lineages, and in a suitable niche, since physiological cues influence functional differences. Towards this, we present an approach, coupling single-cell cancer driver screens in teratomas with hit enrichment by serial teratoma reinjection, to simultaneously screen drivers across multiple lineages in vivo. Using this system, we analyzed population shifts and lineage-specific enrichment for 51 cancer associated genes and variants, profiling over 100,000 cells spanning over 20 lineages, across two rounds of serial reinjection. We confirmed that c-MYC alone or combined with myristoylated AKT1 potently drives proliferation in progenitor neural lineages, demonstrating signatures of malignancy. Additionally, mutant MEK1 S218D/S222D provides a proliferative advantage in mesenchymal lineages like fibroblasts. Our method provides a powerful platform for multi-lineage longitudinal study of oncogenesis.

Identification of Cell Surface Molecules That Determine the Macrophage Activation Threshold Associated With an Early Stage of Malignant Transformation

The ability of immune cells to sense changes associated with malignant transformation as early as possible is likely to be important for the successful outcome of cancer immunosurveillance. In this process, the immune system faces a trade-off between elimination of cells harboring premalignant or malignant changes, and autoimmune pathologies. We hypothesized that the immune system has therefore evolved a threshold for the stage of transformation from normal to fully malignant cells that first provides a threat (danger) signal requiring a response. We co-cultured human macrophages with a unique set of genetically related human cell lines that recapitulate successive stages in breast cancer development: MCF10A (immortalized, normal); MCFNeoT (benign hyperplasia); MCFT1 (atypical hyperplasia); MCFCA1 (invasive cancer). Using cytokines-based assays, we found that macrophages were inert towards MCF10A and MCFNeoT but were strongly activated by MCFT1 and MCFCA1 to produce inflammatory cytokines, placing the threshold for recognition between two premalignant stages, the earlier stage MCFNeoT and the more advanced MCFT1. The cytokine activation threshold paralleled the threshold for enhanced phagocytosis. Using proteomic and transcriptomic approaches, we identified surface molecules, some of which are well-known tumor-associated antigens, that were absent or expressed at low levels in MCF10A and MCFNeoT but turned on or over-expressed in MCFT1 and MCFCA1. Adding antibodies specific for two of these molecules, Annexin-A1 and CEACAM1, inhibited macrophage activation, supporting their role as cancer "danger signals" recognized by macrophages.

Cancer evolution: Darwin and beyond

Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.

High-throughput characterization of mutations in genes that drive clonal evolution using multiplex adaptome capture sequencing

Understanding how cells are likely to evolve can guide medical interventions and bioengineering efforts that must contend with unwanted mutations. The adaptome of a cell-the neighborhood of genetic changes that are most likely to drive adaptation in a given environment-can be mapped by tracking rare beneficial variants during the early stages of clonal evolution. We used multiplex adaptome capture sequencing (mAdCap-seq), a procedure that combines unique molecular identifiers and hybridization-based enrichment, to characterize mutations in eight Escherichia coli genes known to be under selection in a laboratory environment. We tracked 301 mutations at frequencies as low as 0.01% and inferred the fitness effects of 240 of these mutations. There were distinct molecular signatures of selection on protein structure and function for the three genes with the most beneficial mutations. Our results demonstrate how mAdCap-seq can be used to deeply profile a targeted portion of a cell's adaptome.

Bridging Tumorigenesis and Therapy Resistance With a Non-Darwinian and Non-Lamarckian Mechanism of Adaptive Evolution

Although neo-Darwinian (and less often Lamarckian) dynamics are regularly invoked to interpret cancer's multifarious molecular profiles, they shine little light on how tumorigenesis unfolds and often fail to fully capture the frequency and breadth of resistance mechanisms. This uncertainty frames one of the most problematic gaps between science and practice in modern times. Here, we offer a theory of adaptive cancer evolution, which builds on a molecular mechanism that lies outside neo-Darwinian and Lamarckian schemes. This mechanism coherently integrates non-genetic and genetic changes, ecological and evolutionary time scales, and shifts the spotlight away from positive selection towards purifying selection, genetic drift, and the creative-disruptive power of environmental change. The surprisingly simple use-it or lose-it rationale of the proposed theory can help predict molecular dynamics during tumorigenesis. It also provides simple rules of thumb that should help improve therapeutic approaches in cancer.

The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer

Evolutionary game theory mathematically conceptualizes and analyzes biological interactions where one's fitness not only depends on one's own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer's eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. Moreover, we discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with evolutionary game theory has medically useful implications that can inform and create a lockstep between empirical findings and mathematical modeling. We suggest that cancer progression is an evolutionary competition between different cell types and therefore needs to be viewed as an evolutionary game.

Conifer: clonal tree inference for tumor heterogeneity with single-cell and bulk sequencing data

BACKGROUND

Genetic heterogeneity of a cancer tumor that develops during clonal evolution is one of the reasons for cancer treatment failure, by increasing the chance of drug resistance. Clones are cell populations with different genotypes, resulting from differences in somatic mutations that occur and accumulate during cancer development. An appropriate approach for identifying clones is determining the variant allele frequency of mutations that occurred in the tumor. Although bulk sequencing data can be used to provide that information, the frequencies are not informative enough for identifying different clones with the same prevalence and their evolutionary relationships. On the other hand, single-cell sequencing data provides valuable information about branching events in the evolution of a cancerous tumor. However, the temporal order of mutations may be determined with ambiguities using only single-cell data, while variant allele frequencies from bulk sequencing data can provide beneficial information for inferring the temporal order of mutations with fewer ambiguities.

RESULT

In this study, a new method called Conifer (ClONal tree Inference For hEterogeneity of tumoR) is proposed which combines aggregated variant allele frequency from bulk sequencing data with branching event information from single-cell sequencing data to more accurately identify clones and their evolutionary relationships. It is proven that the accuracy of clone identification and clonal tree inference is increased by using Conifer compared to other existing methods on various sets of simulated data. In addition, it is discussed that the evolutionary tree provided by Conifer on real cancer data sets is highly consistent with information in both bulk and single-cell data.

CONCLUSIONS

In this study, we have provided an accurate and robust method to identify clones of tumor heterogeneity and their evolutionary history by combining single-cell and bulk sequencing data.

Evolutionary dynamics of cancer multidrug resistance in response to olaparib and photodynamic therapy

P-glycoprotein (P-gp) is an adenosine triphosphate (ATP)-dependent drug efflux protein commonly associated with multidrug resistance in cancer chemotherapy. In this report, we used a dual-fluorescent co-culture model to study the population dynamics of the drug sensitive human ovarian cancer cell line (OVCAR-8-DsRed2) and its resistant subline that overexpresses P-gp (NCI/ADR-RES-EGFP) during the course of a photodynamic therapy (PDT)-olaparib combination regimen. Without treatment, OVCAR-8-DsRed2 cells grew more rapidly than the NCI/ADR-RES-EGFP cells. Olaparib treatment reduced the total number of cancer cells by 70±4% but selected for the resistant NCI/ADR-RES-EGFP population since olaparib is an efflux substrate for the P-gp pump. This study used the FDA-approved benzoporphyrin derivative (BPD) photosensitizer or its lipidated formulation ((16:0)LysoPC-BPD) to kill OVCAR-8 cells and reduce the likelihood that olaparib-resistant cells would have selective advantage. Three cycles of PDT effectively reduced the total cell number by 66±3%, while stabilizing the population ratio of sensitive and resistant cells at approximately 1:1. The combination of olaparib treatment and PDT enhanced PARP cleavage and deoxyribonucleic acid (DNA) damage, further decreasing the total cancer cell number down to 10±2%. We also showed that the combination of olaparib and (16:0)LysoPC-BPD-based PDT is up to 18-fold more effective in mitigating the selection of resistant NCI/ADR-RES-EGFP cells, compared to using olaparib and BPD-based PDT. These studies suggest that PDT may improve the effectiveness of olaparib, and the use of a lipidated photosensitizer formulation holds promise in overcoming cancer drug resistance.