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 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 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 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 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 Iatrogenic endometriosis harbors somatic cancer-driver mutations

2018 ◽  
Vol 34 (1) ◽  
pp. 69-78 ◽  
Author(s):  
V Lac ◽  
L Verhoef ◽  
R Aguirre-Hernandez ◽  
T M Nazeran ◽  
B Tessier-Cloutier ◽  
...  
Keyword(s):  
Health Research ◽  
Somatic Mutations ◽  
Single Case ◽  
The Body ◽  
Patient Treatment ◽  
Driver Mutations ◽  
Deep Infiltrating Endometriosis ◽  
Ovarian Carcinomas ◽  
Archival Tissue ◽  
Cancer Driver

Abstract STUDY QUESTION Does incisional endometriosis (IE) harbor somatic cancer-driver mutations? SUMMARY ANSWER We found that approximately one-quarter of IE cases harbor somatic-cancer mutations, which commonly affect components of the MAPK/RAS or PI3K-Akt-mTor signaling pathways. WHAT IS KNOWN ALREADY Despite the classification of endometriosis as a benign gynecological disease, it shares key features with cancers such as resistance to apoptosis and stimulation of angiogenesis and is well-established as the precursor of clear cell and endometrioid ovarian carcinomas. Our group has recently shown that deep infiltrating endometriosis (DE), a form of endometriosis that rarely undergoes malignant transformation, harbors recurrent somatic mutations. STUDY DESIGN, SIZE, DURATION In a retrospective study comparing iatrogenically induced and endogenously occurring forms of endometriosis unlikely to progress to cancer, we examined endometriosis specimens from 40 women with IE and 36 women with DE. Specimens were collected between 2004 and 2017 from five hospital sites in either Canada, Germany or the Netherlands. IE and DE cohorts were age-matched and all women presented with histologically typical endometriosis without known history of malignancy. PARTICIPANTS/MATERIALS, SETTING, METHODS Archival tissue specimens containing endometriotic lesions were macrodissected and/or laser-capture microdissected to enrich endometriotic stroma and epithelium and a hypersensitive cancer hotspot sequencing panel was used to assess for presence of somatic mutations. Mutations were subsequently validated using droplet digital PCR. PTEN and ARID1A immunohistochemistry (IHC) were performed as surrogates for somatic events resulting in functional loss of respective proteins. MAIN RESULTS AND THE ROLE OF CHANCE Overall, we detected somatic cancer-driver events in 11 of 40 (27.5%) IE cases and 13 of 36 (36.1%) DE cases, including hotspot mutations in KRAS, ERBB2, PIK3CA and CTNNB1. Heterogeneous PTEN loss occurred at similar rates in IE and DE (7/40 vs 5/36, respectively), whereas ARID1A loss only occurred in a single case of DE. While rates of detectable somatic cancer-driver events between IE and DE are not statistically significant (P > 0.05), KRAS activating mutations were more prevalent in DE. LIMITATIONS, REASONS FOR CAUTION Detection of somatic cancer-driver events were limited to hotspots analyzed in our panel-based sequencing assay and loss of protein expression by IHC from archival tissue. Whole genome or exome sequencing, or epigenetic analysis may uncover additional somatic alterations. Moreover, because of the descriptive nature of this study, the functional roles of identified mutations within the context of endometriosis remain unclear and causality cannot be established. WIDER IMPLICATIONS OF THE FINDINGS The alterations we report may be important in driving the growth and survival of endometriosis in ectopic regions of the body. Given the frequency of mutation in surgically displaced endometrium (IE), examination of similar somatic events in eutopic endometrium, as well as clinically annotated cases of other forms of endometriosis, in particular endometriomas that are most commonly linked to malignancy, is warranted. STUDY FUNDING/COMPETING INTEREST(S) This study was funded by a Canadian Cancer Society Impact Grant [701603, PI Huntsman], Canadian Institutes of Health Research Transitional Open Operating Grant [MOP-142273, PI Yong], the Canadian Institutes of Health Research Foundation Grant [FDN-154290, PI Huntsman], the Canadian Institutes of Health Research Project Grant [PJT-156084, PIs Yong and Anglesio], and the Janet D. Cottrelle Foundation through the BC Cancer Foundation [PI Huntsman]. D.G. Huntsman is a co-founder and shareholder of Contextual Genomics Inc., a for profit company that provides clinical reporting to assist in cancer patient treatment. R. Aguirre-Hernandez, J. Khattra and L.M. Prentice have a patent MOLECULAR QUALITY ASSURANCE METHODS FOR USE IN SEQUENCING pending and are current (or former) employees of Contextual Genomics Inc. The remaining authors have no competing interests to declare. TRIAL REGISTRATION NUMBER Not applicable.

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.

Is there a Role for Epigenetic Enhancement of Immunomodulatory Approaches to Cancer Treatment?

2017 ◽  
Vol 18 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Kirsty J. Flower ◽  
Sadaf Ghaem-Maghami ◽  
Robert Brown
Keyword(s):  
Expression Patterns ◽  
Immune Surveillance ◽  
Treatment Strategies ◽  
Tumour Microenvironment ◽  
The Body ◽  
Host Cells ◽  
Specific Gene ◽  
Host Immune System ◽  
A Cell ◽  
New Treatment

The efficacy of cancer immunotherapy relies on the ability of the host immune system to recognise the cancer as non-self and eliminate it from the body. Whilst this is an extremely fertile area of medical research, with positive clinical trials showing durable responses, attention must be paid to the subset of patients that do not respond to these treatments. Immune surveillance and immunoediting by the host could itself select for immune-evasive tumour cells during tumour development leading to immunotherapy resistance. One such mechanism of non-efficacy or resistance is the epigenetic silencing of a specific gene required in the immunotherapy response pathway. Epigenetics is the study of the control of expression patterns in a cell via mechanisms not involving a change in DNA sequence. All tumour types show aberrant epigenetic regulation of genes involved in all the hallmarks of cancer, including immunomodulation. Inhibition of key enzymes involved in maintenance of epigenetic states is another important area of research for new treatment strategies for cancer. Could epigenetic therapies be used to successfully enhance the action of immunomodulatory agents in cancer, and are they acting in the way we imagine? An understanding of the effects of epigenetic therapies on immunological pathways in both the tumour and host cells, especially the tumour microenvironment, will be essential to further develop such combination approaches.

scholarly journals Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives

2021 ◽  
Vol 18 (5) ◽  
pp. 6305-6327
Author(s):  
Cassidy K. Buhler ◽  
◽  
Rebecca S. Terry ◽  
Kathryn G. Link ◽  
Frederick R. Adler ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Cancer Treatment ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Allee Effect ◽  
Resource Competition ◽  
Treatment Strategies ◽  
Cell Populations ◽  
Emergence Of Resistance ◽  
Resistant Cells

<abstract><p>When eradication is impossible, cancer treatment aims to delay the emergence of resistance while minimizing cancer burden and treatment. Adaptive therapies may achieve these aims, with success based on three assumptions: resistance is costly, sensitive cells compete with resistant cells, and therapy reduces the population of sensitive cells. We use a range of mathematical models and treatment strategies to investigate the tradeoff between controlling cell populations and delaying the emergence of resistance. These models extend game theoretic and competition models with four additional components: 1) an Allee effect where cell populations grow more slowly at low population sizes, 2) healthy cells that compete with cancer cells, 3) immune cells that suppress cancer cells, and 4) resource competition for a growth factor like androgen. In comparing maximum tolerable dose, intermittent treatment, and adaptive therapy strategies, no therapeutic choice robustly breaks the three-way tradeoff among the three therapeutic aims. Almost all models show a tight tradeoff between time to emergence of resistant cells and cancer cell burden, with intermittent and adaptive therapies following identical curves. For most models, some adaptive therapies delay overall tumor growth more than intermittent therapies, but at the cost of higher cell populations. The Allee effect breaks these relationships, with some adaptive therapies performing poorly due to their failure to treat sufficiently to drive populations below the threshold. When eradication is impossible, no treatment can simultaneously delay emergence of resistance, limit total cancer cell numbers, and minimize treatment. Simple mathematical models can play a role in designing the next generation of therapies that balance these competing objectives.</p></abstract>

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