scholarly journals Why is cancer not more common? A changing microenvironment may help to explain why, and suggests strategies for anti-cancer therapy

Open Biology ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 190297
Author(s):  
Xiaowei Jiang ◽  
Ian P. M. Tomlinson
Keyword(s):  
Cancer Cell ◽  
Cancer Biology ◽  
Immune Cell ◽  
Treatment Strategies ◽  
Tumour Microenvironment ◽  
The Body ◽  
Driver Mutations ◽  
Cell Populations ◽  
Cancer Evolution ◽  
Anti Cancer

One of the great unsolved puzzles in cancer biology is not why cancers occur, but rather explaining why so few cancers occur compared with the theoretical number that could occur, given the number of progenitor cells in the body and the normal mutation rate. We hypothesized that a contributory explanation is that the tumour microenvironment (TME) is not fixed due to factors such as immune cell infiltration, and that this could impair the ability of neoplastic cells to retain a high enough fitness to become a cancer. The TME has implicitly been assumed to be static in most cancer evolution models, and we therefore developed a mathematical model of spatial cancer evolution assuming that the TME, and thus the optimum cancer phenotype, changes over time. Based on simulations, we show how cancer cell populations adapt to diverse changing TME conditions and fitness landscapes. Compared with static TMEs, which generate neutral dynamics, changing TMEs lead to complex adaptations with characteristic spatio-temporal heterogeneity involving variable fitness effects of driver mutations, subclonal mixing, subclonal competition and phylogeny patterns. In many cases, cancer cell populations fail to grow or undergo spontaneous regression, and even extinction. Our analyses predict that cancer evolution in a changing TME is challenging, and can help to explain why cancer is neither inevitable nor as common as expected. Should cancer driver mutations with effects dependent of the TME exist, they are likely to be selected. Anti-cancer prevention and treatment strategies based on changing the TME are feasible and potentially effective.

scholarly journals Why is cancer not more common? A changing microenvironment may help to explain why, and suggests strategies for anti-cancer therapy

2018 ◽  
Author(s):  
Xiaowei Jiang ◽  
Ian P.M. Tomlinson
Keyword(s):  
Cancer Cell ◽  
Cancer Biology ◽  
Treatment Strategies ◽  
Tumour Microenvironment ◽  
The Body ◽  
Driver Mutations ◽  
Cell Populations ◽  
Cancer Evolution ◽  
Cancer Driver ◽  
Anti Cancer

AbstractOne of the great unsolved puzzles in cancer biology is not why cancers occur, but rather, explaining why so few cancers occur compared with the theoretical number that could occur given the number of progenitor cells in the body and the normal mutation rate. We hypothesised that a contributory explanation is that the tumour microenvironment (TME) is not fixed, and that this could impair the ability of neoplastic cells to retain a high enough fitness to become a cancer. The TME has implicitly been assumed to be static in most cancer evolution models, and we therefore developed a mathematical model of spatial cancer evolution assuming that the TME, and thus the optimum cancer phenotype, change over time. Based on simulations, we show how cancer cell populations adapt to diverse changing TME conditions and fitness landscapes. Compared with static TMEs which generate neutral dynamics, changing TMEs lead to complex adaptations with spatio-temporal heterogeneity involving variable sub-clonal fitness, mixing, competition and phylogeny patterns. In many cases, cancer cell populations fail to grow or undergo spontaneous regression, and even extinction. Our analyses predict that cancer evolution in a changing TME is challenging, and can help to explain why cancer is neither inevitable nor as common as expected. Should cancer driver mutations with effects dependent of the TME exist, they are likely to be selected. Anti-cancer prevention and treatment strategies based on changing the TME are feasible and potentially effective.

scholarly journals Molecular Biology and Evolution of Cancer: From Discovery to Action

2019 ◽  
Vol 37 (2) ◽  
pp. 320-326 ◽  
Author(s):  
Jason A Somarelli ◽  
Heather Gardner ◽  
Vincent L Cannataro ◽  
Ella F Gunady ◽  
Amy M Boddy ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Cancer Biology ◽  
Circulatory System ◽  
Evolutionary Process ◽  
Deep Understanding ◽  
The Body ◽  
Ecological Niches ◽  
Cell Populations ◽  
Cancer Evolution ◽  
Metastatic Sites

Abstract Cancer progression is an evolutionary process. During this process, evolving cancer cell populations encounter restrictive ecological niches within the body, such as the primary tumor, circulatory system, and diverse metastatic sites. Efforts to prevent or delay cancer evolution—and progression—require a deep understanding of the underlying molecular evolutionary processes. Herein we discuss a suite of concepts and tools from evolutionary and ecological theory that can inform cancer biology in new and meaningful ways. We also highlight current challenges to applying these concepts, and propose ways in which incorporating these concepts could identify new therapeutic modes and vulnerabilities in cancer.

scholarly journals The role of the circadian clock in cancer hallmark acquisition and immune-based cancer therapeutics

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Elizabeth Cash ◽  
Sandra Sephton ◽  
Cassandra Woolley ◽  
Attia M. Elbehi ◽  
Anu R. I. ◽  
...  
Keyword(s):  
Adverse Effects ◽  
Paradigm Shift ◽  
Cancer Biology ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Cancer Therapeutics ◽  
The Body ◽  
Anti Cancer ◽  
Biological Determinants

AbstractThe circadian system temporally regulates physiology to maintain homeostasis. Co-opting and disrupting circadian signals appear to be distinct attributes that are functionally important for the development of a tumor and can enable or give rise to the hallmarks that tumors use to facilitate their initiation, growth and progression. Because circadian signals are also strong regulators of immune cell proliferation, trafficking and exhaustion states, they play a role in how tumors respond to immune-based cancer therapeutics. While immuno-oncology has heralded a paradigm shift in cancer therapeutics, greater accuracy is needed to increase our capability of predicting who will respond favorably to, or who is likely to experience the troubling adverse effects of, immunotherapy. Insights into circadian signals may further refine our understanding of biological determinants of response and help answer the fundamental question of whether certain perturbations in circadian signals interfere with the activity of immune checkpoint inhibitors. Here we review the body of literature highlighting circadian disruption as a cancer promoter and synthesize the burgeoning evidence suggesting circadian signals play a role in how tumors respond to immune-based anti-cancer therapeutics. The goal is to develop a framework to advance our understanding of the relationships between circadian markers, cancer biology, and immunotherapeutics. Bolstered by this new understanding, these relationships may then be pursued in future clinical studies to improve our ability to predict which patients will respond favorably to, and avoid the adverse effects of, traditional and immune-based cancer therapeutics.

scholarly journals Fibroblasts as a Biological Marker for Curative Resection in Pancreatic Ductal Adenocarcinoma

2020 ◽  
Vol 21 (11) ◽  
pp. 3890 ◽  
Author(s):  
Eriko Katsuta ◽  
Omar M. Rashid ◽  
Kazuaki Takabe
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cell ◽  
Cancer Biology ◽  
Curative Resection ◽  
Biological Marker ◽  
Ductal Adenocarcinoma ◽  
R0 Resection ◽  
Small Subset ◽  
Inverse Association ◽  
Anti Cancer

Achievement of microscopic tumor clearance (R0) after pancreatic ductal adenocarcinoma (PDAC) surgery is determined by cancer biology rather than operative technique. Fibroblasts are known to play pro-cancer roles; however, a small subset was recently found to play anti-cancer roles. Therefore, we hypothesized that intratumor fibroblasts contribute to curative resection and a better survival of PDAC. Utilizing a large, publicly available PDAC cohort, we found that fibroblast composition was associated with R0 curative resection. A high amount of fibroblasts in PDACs was significantly associated with a higher amount of mature vessels, but not with blood angiogenesis. A high amount of fibroblasts was also associated with a higher infiltration of anti-cancer immune cells, such as CD8+ T-cells and dendritic cells, together with higher inflammatory signaling, including IL2/STAT5 and IL6/JAK/STAT3 signaling. Further, the fibroblast composition was inversely associated with cancer cell composition in the bulk tumor, along with an inverse association with proliferative characteristics, such as MYC signaling and glycolysis. The patients with high-fibroblast PDACs showed an improved prognosis. In conclusion, we found that PDACs with high fibroblasts were associated with a higher R0 resection rate, resulting in a better prognosis. These findings may be due to less aggressive biology with a higher vascularity and anti-cancer immunity, and a low cancer cell component.

scholarly journals Mutant Allele Imbalance in Cancer

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Craig M. Bielski ◽  
Barry S. Taylor
Keyword(s):  
Cancer Biology ◽  
Mutant Allele ◽  
Tumor Biology ◽  
Cellular Level ◽  
Driver Mutations ◽  
Annual Review ◽  
Publication Date ◽  
Cancer Evolution ◽  
Allele Imbalance ◽  
And Function

The search for somatic mutations that drive the initiation and progression of human tumors has dominated recent cancer research. While much emphasis has been placed on characterizing the prevalence and function of driver mutations, comparatively less is known about their serial genetic evolution. Indeed, study of this phenomenon has largely focused on tumor-suppressor genes recessive at the cellular level or mechanisms of resistance in tumors with mutant oncogenes targeted by therapy. There is, however, a growing appreciation that despite a decades-old presumption of heterozygosity, changes in mutant oncogene zygosity are common and drive dosage and stoichiometry changes that lead to selective growth advantages. Here, we review the recent progress in understanding mutant allele imbalance and its implications for tumor biology, cancer evolution, and response to anticancer therapy. Expected final online publication date for the Annual Review of Cancer Biology, Volume 5 is March 4, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Simulation Framework for Generating Intratumor Heterogeneity Patterns in a Cancer Cell Population

2017 ◽  
Author(s):  
Watal M. Iwasaki ◽  
Hideki Innan
Keyword(s):  
Cell Division ◽  
Cancer Cell ◽  
General Framework ◽  
Hexagonal Lattice ◽  
Driver Mutations ◽  
Intratumor Heterogeneity ◽  
Cell Populations ◽  
Simulation Studies ◽  
Regular Lattice ◽  
Tumor Morphology

AbstractAs cancer cell populations evolve, they accumulate a number of somatic mutations, resulting in heterogeneous subclones in the final tumor. Understanding the mechanisms that produce intratumor heterogeneity (ITH) is important for selecting the best treatment. Although some studies have involved ITH simulations, their model settings differed substantially. Thus, only limited conditions were explored in each. Herein, we developed a general framework for simulating ITH patterns and a simulator (tumopp). Tumopp offers many setting options so that simulations can be carried out under various settings. Setting options include how the cell division rate is determined, how daughter cells are placed, and how driver mutations are treated. Furthermore, to account for the cell cycle, we introduced a gamma function for the waiting time involved in cell division. Tumopp also allows simulations in a hexagonal lattice, in addition to a regular lattice that has been used in previous simulation studies. A hexagonal lattice produces a more biologically reasonable space than a regular lattice. Using tumopp, we investigated how model settings affect the growth curve and ITH pattern. It was found that, even under neutrality (with no driver mutations), tumopp produced dramatically variable patterns of ITH and tumor morphology, from tumors in which cells with different genetic background are well intermixed to irregular shapes of tumors with a cluster of closely related cells. This result suggests a caveat in analyzing ITH data with simulations with limited settings, and tumopp will be useful to explore ITH patterns in various conditions.Author SummaryUnderstanding the mechanisms that produce intratumor heterogeneity (ITH) is important for selecting the best treatment. Despite a growing body of data and tools for analyzing ITH, the spatial structure and its evolution are poorly understood because of the lack of well established theoretical framework. Herein, we provide a general framework for simulating ITH patterns, under which a simulator (tumopp) is developed. Tumopp offers many setting options so that simulations can be carried out under various settings. Simulations using tumopp demonstrate that dramatically variable patterns of ITH and tumor morphology can be produced depending on the model setting. The present work provides a guideline for future simulation studies of cancer cell populations.

scholarly journals The Role of Immune Escape and Immune Cell Infiltration in Breast Cancer

Breast Care ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. 16-21 ◽  
Author(s):  
André Steven ◽  
Barbara Seliger
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Cancer Biology ◽  
Breast Cancer Cells ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Altered Expression

While detailed analysis of aberrant cancer cell signaling pathways and changes in cancer cell DNA has dominated the field of breast cancer biology for years, there now exists increasing evidence that the tumor microenvironment (TME) including tumor-infiltrating immune cells support the growth and development of breast cancer and further facilitate invasion and metastasis formation as well as sensitivity to drug therapy. Furthermore, breast cancer cells have developed different strategies to escape surveillance from the adaptive and innate immune system. These include loss of expression of immunostimulatory molecules, gain of expression of immunoinhibitory molecules such as PD-L1 and HLA-G, and altered expression of components involved in apoptosis. Furthermore, the composition of the TME plays a key role in breast cancer development and treatment response. In this review we will focus on i) the different immune evasion mechanisms used by breast cancer cells, ii) the role of immune cell infiltration in this disease, and (iii) implication for breast cancer-based immunotherapies.

scholarly journals Emerging organoid models: leaping forward in cancer research

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Han Fan ◽  
Utkan Demirci ◽  
Pu Chen
Keyword(s):  
Cancer Research ◽  
Cancer Therapy ◽  
Cancer Biology ◽  
Model Systems ◽  
Cancer Evolution ◽  
Clinical Cancer Research ◽  
Cancer Heterogeneity ◽  
Cancer Models ◽  
Anti Cancer

AbstractCancer heterogeneity is regarded as the main reason for the failure of conventional cancer therapy. The ability to reconstruct intra- and interpatient heterogeneity in cancer models is crucial for understanding cancer biology as well as for developing personalized anti-cancer therapy. Cancer organoids represent an emerging approach for creating patient-derived in vitro cancer models that closely recapitulate the pathophysiological features of natural tumorigenesis and metastasis. Meanwhile, cancer organoids have recently been utilized in the discovery of personalized anti-cancer therapy and prognostic biomarkers. Further, the synergistic combination of cancer organoids with organ-on-a-chip and 3D bioprinting presents a new avenue in the development of more sophisticated and optimized model systems to recapitulate complex cancer-stroma or multiorgan metastasis. Here, we summarize the recent advances in cancer organoids from a perspective of the in vitro emulation of natural cancer evolution and the applications in personalized cancer theranostics. We also discuss the challenges and trends in reconstructing more comprehensive cancer models for basic and clinical cancer research.

scholarly journals Early and multiple origins of metastatic lineages within primary tumors

2016 ◽  
Vol 113 (8) ◽  
pp. 2140-2145 ◽  
Author(s):  
Zi-Ming Zhao ◽  
Bixiao Zhao ◽  
Yalai Bai ◽  
Atila Iamarino ◽  
Stephen G. Gaffney ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Cancer Biology ◽  
Tumor Development ◽  
Evolutionary Process ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Driver Genes ◽  
Genetic Changes ◽  
Primary Tumors ◽  
Multiple Origins

Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression, metastases can originate from divergent lineages within primary tumors. Evolved genetic changes in cancer lineages likely affect only the proclivity toward metastasis. Single genetic changes are unlikely to be necessary or sufficient for metastasis. Second, metastatic lineages can arise early in tumor development, sometimes long before diagnosis. The early genetic divergence of some metastatic lineages directs attention toward research on driver genes that are mutated early in cancer evolution. Last, the temporal order of occurrence of driver mutations can be inferred from phylogenetic analysis of cancer chronograms, guiding development of targeted therapeutics effective against primary tumors and metastases.

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