Mathematical modeling links Wnt signaling to emergent patterns of metabolism in colon cancer

Canonical WNT/β-catenin signaling upregulates aerobic glycolysis in diverse cancer types

Despite many efforts, a comprehensive understanding and clarification of the intricate connections within cancer cell metabolism remain elusive. This might pertain to intracellular dynamics and the complex interplay between cancer cells, and cells with the tumor stroma. Almost a century ago, Otto Warburg found that cancer cells exhibit a glycolytic phenotype, which continues to be a subject of thorough investigation. Past and ongoing investigations have demonstrated intricate mechanisms by which tumors modulate their functionality by utilizing extracellular glucose as a substrate, thereby sustaining the essential proliferation of cancer cells. This concept of "aerobic glycolysis," where cancer cells (even in the presence of enough oxygen) metabolize glucose to produce lactate plays a critical role in cancer progression and is regulated by various signaling pathways. Recent research has revealed that the canonical wingless-related integrated site (WNT) pathway promotes aerobic glycolysis, directly and indirectly, thereby influencing cancer development and progression. The present review seeks to gather knowledge about how the WNT/β-catenin pathway influences aerobic glycolysis, referring to relevant studies in different types of cancer. Furthermore, we propose the concept of impeding the glycolytic phenotype of tumors by employing specific inhibitors that target WNT/β-catenin signaling.

Investigation of ENO2 as a promising novel marker for the progression of colorectal cancer with microsatellite instability-high

BACKGROUND

Microsatellite instability-high (MSI-H) has emerged as a significant biological characteristic of colorectal cancer (CRC). Studies reported that MSI-H CRC generally had a better prognosis than microsatellite stable (MSS)/microsatellite instability-low (MSI-L) CRC, but some MSI-H CRC patients exhibited distinctive molecular characteristics and experienced a less favorable prognosis. In this study, our objective was to explore the metabolic transcript-related subtypes of MSI-H CRC and identify a biomarker for predicting survival outcomes.

METHODS

Single-cell RNA sequencing (scRNA-seq) data of MSI-H CRC patients were obtained from the Gene Expression Omnibus (GEO) database. By utilizing the copy number variation (CNV) score, a malignant cell subpopulation was identified at the single-cell level. The metabolic landscape of various cell types was examined using metabolic pathway gene sets. Subsequently, functional experiments were conducted to investigate the biological significance of the hub gene in MSI-H CRC. Finally, the predictive potential of the hub gene was assessed using a nomogram.

RESULTS

This study revealed a malignant tumor cell subpopulation from the single-cell RNA sequencing (scRNA-seq) data. MSI-H CRC was clustered into two subtypes based on the expression profiles of metabolism-related genes, and ENO2 was identified as a hub gene. Functional experiments with ENO2 knockdown and overexpression demonstrated its role in promoting CRC cell migration, invasion, glycolysis, and epithelial-mesenchymal transition (EMT) in vitro. High expression of ENO2 in MSI-H CRC patients was associated with worse clinical outcomes, including increased tumor invasion depth (p = 0.007) and greater likelihood of perineural invasion (p = 0.015). Furthermore, the nomogram and calibration curves based on ENO2 showed potential prognosis predictive performance.

CONCLUSION

Our findings suggest that ENO2 serves as a novel prognostic biomarker and is associated with the progression of MSI-H CRC.

Colorectal Cancer Stem Cell Subtypes Orchestrate Distinct Tumor Microenvironments

Several classification systems have been developed to define tumor subtypes in colorectal cancer (CRC). One system proposes that tumor heterogeneity derives in part from distinct cancer stem cell populations that co-exist as admixtures of varying proportions. However, the lack of single cell resolution has prohibited a definitive identification of these types of stem cells and therefore any understanding of how each influence tumor phenotypes. Here were report the isolation and characterization of two cancer stem cell subtypes from the SW480 CRC cell line. We find these cancer stem cells are oncogenic versions of the normal Crypt Base Columnar (CBC) and Regenerative Stem Cell (RSC) populations from intestinal crypts and that their gene signatures are consistent with the "Admixture" and other CRC classification systems. Using publicly available single cell RNA sequencing (scRNAseq) data from CRC patients, we determine that RSC and CBC cancer stem cells are commonly co-present in human CRC. To characterize influences on the tumor microenvironment, we develop subtype-specific xenograft models and we define their tumor microenvironments at high resolution via scRNAseq. RSCs create differentiated, inflammatory, slow growing tumors. CBCs create proliferative, undifferentiated, invasive tumors. With this enhanced resolution, we unify current CRC patient classification schema with TME phenotypes and organization.

The DUX4-HIF1α Axis in Murine and Human Muscle Cells: A Link More Complex Than Expected

FacioScapuloHumeral muscular Dystrophy (FSHD) is one of the most prevalent inherited muscle disorders and is linked to the inappropriate expression of the DUX4 transcription factor in skeletal muscles. The deregulated molecular network causing FSHD muscle dysfunction and pathology is not well understood. It has been shown that the hypoxia response factor HIF1α is critically disturbed in FSHD and has a major role in DUX4-induced cell death. In this study, we further explored the relationship between DUX4 and HIF1α. We found that the DUX4 and HIF1α link differed according to the stage of myogenic differentiation and was conserved between human and mouse muscle. Furthermore, we found that HIF1α knockdown in a mouse model of DUX4 local expression exacerbated DUX4-mediated muscle fibrosis. Our data indicate that the suggested role of HIF1α in DUX4 toxicity is complex and that targeting HIF1α might be challenging in the context of FSHD therapeutic approaches.

A Systems Biology Approach to Understand the Racial Disparities in Colorectal Cancer

Racial disparities between Black/African Americans (AA) and White patients in colorectal cancer are an ever-growing area of concern. Black/AA show the highest incidence and have the highest mortality among major U.S. racial groups. There is no definite cause other than possible sociodemographic, socioeconomic, education, nutrition, delivery of healthcare, screening, and cultural factors. A primary limitation in this field is the lack of and small sample size of Black/AA studies. Thus, this study aimed to investigate whether differences in gene expression contribute to this ongoing unanswered racial disparity issue. In this study, we examined transcriptomic data of Black/AA and White patient cohorts using a bioinformatic and systems biology approach. We performed a Kaplan-Meier overall survival analysis between both patient cohorts across critical colorectal cancer signal transduction networks (STN), to determine the differences in significant genes across each cohort. Other bioinformatic analyses performed included PROGENy (pathway responsive genes for activity inference), RNA sequencing differential expression using DESeq2, multivariable-adjusted regression, and other associated Kaplan-Meier analyses. These analyses identified novel prognostic genes independent from each cohort, 176 differentially expressed genes, and specific patient cohort STN survival associations. Despite the overarching limitation, the results revealed several novel differences in gene expression between the colorectal cancer Black/AA and White patient cohorts, which allows one to dive deeper into and understand the behavior on a systems level of what could be driving this racial difference across colorectal cancer. Concretely, this information can guide precision medicine approaches tailored specifically for colorectal cancer racial disparities.

SIGNIFICANCE

The purpose of this work is to investigate the racial disparities in colorectal cancer between Black/AA and White patient cohorts using a systems biology and bioinformatic approach. Our study investigates the underlying biology of each patient cohort. Concretely, the findings of this study include disparity-associated genes and pathways, which provide a tangible starting point to guide precision medicine approaches tailored specifically for colorectal cancer racial disparities.

PRI-724 and IWP-O1 Wnt Signaling Pathway Inhibitors Modulate the Expression of Glycolytic Enzymes in Tongue Cancer Cell Lines

The dysregulation of energetic metabolism is one of the hallmarks of cancer cells. Indeed, the growth of head and neck squamous cell carcinoma (HNSCC) cells depends heavily on glycolytic activity, which can be considered a potential therapeutic target. Wnt signaling is one of the pathways that undergoes upregulation in HNSCC. Our previous studies have shown that Wnt signaling inhibitors-PRI-724 and IWP-O1-attenuate tongue SCC survival and reduce glucose uptake and lactate release. The aim of this research was to further evaluate the possible mechanisms of the previously observed effects. We assessed the effect of PRI-724 and IWP-O1 on the expression of selected glycolytic enzymes: phosphofructokinase M, pyruvate kinase M2, and lactate dehydrogenase. Relative transcript expression was assessed by real-time PCR, and protein levels by Western blot. Moreover, clinical data concerning mRNA and protein expression, gene promoter methylation, and HNSCC patients' survival time were analyzed by the UALCAN tool, and protein-protein interaction was assessed using the STRING database. Experimental and bioinformatic data confirmed the relation between Wnt signaling and glycolytic enzymes in tongue cancer cells and HNSCC clinical samples. Overall, the inhibition of glucose metabolism by Wnt signaling inhibitors is a promising mode of action against tongue cancer cells.

Stochastic modeling of the mRNA life process: A generalized master equation

The mRNA life cycle is a complex biochemical process, involving transcription initiation, elongation, termination, splicing, and degradation. Each of these molecular events is multistep and can create a memory. The effect of this molecular memory on gene expression is not clear, although there are many related yet scattered experimental reports. To address this important issue, we develop a general theoretical framework formulated as a master equation in the sense of queue theory, which can reduce to multiple previously studied gene models in limiting cases. This framework allows us to interpret experimental observations, extract kinetic parameters from experimental data, and identify how the mRNA kinetics vary under regulatory influences. Notably, it allows us to evaluate the influences of elongation processes on mature RNA distribution; e.g., we find that the non-exponential elongation time can induce the bimodal mRNA expression and there is an optimal elongation noise intensity such that the mature RNA noise achieves the lowest level. In a word, our framework can not only provide insight into complex mRNA life processes but also bridge a dialogue between theoretical studies and experimental data.

The Role of Genetic Mutations in Mitochondrial-Driven Cancer Growth in Selected Tumors: Breast and Gynecological Malignancies

There is an increasing understanding of the molecular and cytogenetic background of various tumors that helps us better conceptualize the pathogenesis of specific diseases. Additionally, in many cases, these molecular and cytogenetic alterations have diagnostic, prognostic, and/or therapeutic applications that are heavily used in clinical practice. Given that there is always room for improvement in cancer treatments and in cancer patient management, it is important to discover new therapeutic targets for affected individuals. In this review, we discuss mitochondrial changes in breast and gynecological (endometrial and ovarian) cancers. In addition, we review how the frequently altered genes in these diseases (BRCA1/2, HER2, PTEN, PIK3CA, CTNNB1, RAS, CTNNB1, FGFR, TP53, ARID1A, and TERT) affect the mitochondria, highlighting the possible associated individual therapeutic targets. With this approach, drugs targeting mitochondrial glucose or fatty acid metabolism, reactive oxygen species production, mitochondrial biogenesis, mtDNA transcription, mitophagy, or cell death pathways could provide further tailored treatment.

Data-driven spatio-temporal modelling of glioblastoma

Mathematical oncology provides unique and invaluable insights into tumour growth on both the microscopic and macroscopic levels. This review presents state-of-the-art modelling techniques and focuses on their role in understanding glioblastoma, a malignant form of brain cancer. For each approach, we summarize the scope, drawbacks and assets. We highlight the potential clinical applications of each modelling technique and discuss the connections between the mathematical models and the molecular and imaging data used to inform them. By doing so, we aim to prime cancer researchers with current and emerging computational tools for understanding tumour progression. By providing an in-depth picture of the different modelling techniques, we also aim to assist researchers who seek to build and develop their own models and the associated inference frameworks. Our article thus strikes a unique balance. On the one hand, we provide a comprehensive overview of the available modelling techniques and their applications, including key mathematical expressions. On the other hand, the content is accessible to mathematicians and biomedical scientists alike to accommodate the interdisciplinary nature of cancer research.

Targeting cancer-specific metabolic pathways for developing novel cancer therapeutics

Cancer is a heterogeneous disease characterized by various genetic and phenotypic aberrations. Cancer cells undergo genetic modifications that promote their proliferation, survival, and dissemination as the disease progresses. The unabated proliferation of cancer cells incurs an enormous energy demand that is supplied by metabolic reprogramming. Cancer cells undergo metabolic alterations to provide for increased energy and metabolite requirement; these alterations also help drive the tumor progression. Dysregulation in glucose uptake and increased lactate production via "aerobic glycolysis" were described more than 100 years ago, and since then, the metabolic signature of various cancers has been extensively studied. However, the extensive research in this field has failed to translate into significant therapeutic intervention, except for treating childhood-ALL with amino acid metabolism inhibitor L-asparaginase. Despite the growing understanding of novel metabolic alterations in tumors, the therapeutic targeting of these tumor-specific dysregulations has largely been ineffective in clinical trials. This chapter discusses the major pathways involved in the metabolism of glucose, amino acids, and lipids and highlights the inter-twined nature of metabolic aberrations that promote tumorigenesis in different types of cancer. Finally, we summarise the therapeutic interventions which can be used as a combinational therapy to target metabolic dysregulations that are unique or common in blood, breast, colorectal, lung, and prostate cancer.

The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis

The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.

Hypoxia-driven metabolic heterogeneity and immune evasive behaviour of gastrointestinal cancers: Elements of a recipe for disaster

Gastrointestinal (GI) cancers refer to a group of malignancies associated with the GI tract (GIT). Like other solid tumors, hypoxic regions consistently feature inside the GI tumor microenvironment (TME) and contribute towards metabolic reprogramming of tumor-resident cells by modulating hypoxia-induced factors. We highlight here how the metabolic crosstalk between cancer cells and immune cells generate immunosuppressive environment inside hypoxic tumors. Given the fluctuating nature of tumor hypoxia, the metabolic fluxes between immune cells and cancer cells change dynamically. These changes alter cellular phenotypes and functions, resulting in the acceleration of cancer progression. These evolved properties of hypoxic tumors make metabolism-targeting monotherapy approaches or immunotherapy-measures unsuccessful. The current review highlights the advantages of combined immunometabolic treatment strategies to target hypoxic GI cancers and also identifies research areas to develop better combinational therapeutics for future.

Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data

Advances in omic technologies have provided insight into cancer progression and treatment response. However, the nonlinear characteristics of cancer growth present a challenge to bridge from the molecular- to the tissue-scale, as tumor behavior cannot be encapsulated by the sum of the individual molecular details gleaned experimentally. Mathematical modeling and computational simulation have been traditionally employed to facilitate analysis of nonlinear systems. In this study, for the first time tumor metabolomic data are linked via mathematical modeling to the tumor tissue-scale behavior, showing the capability to mechanistically simulate cancer progression personalized to omic information obtainable from patient tumor core biopsy analysis. Generally, a higher degree of metabolic dysregulation has been correlated with more aggressive tumor behavior. Accordingly, key parameters influenced by metabolomic data in this model include tumor proliferation, vascularization, aggressiveness, lactic acid production, monocyte infiltration and macrophage polarization, and drug effect. The model enables evaluating interactions of interest between these parameters which drive tumor growth based on the metabolomic data. The results show that the model can group patients consistently with the clinically observed outcomes of response/non-response to chemotherapy. This modeling approach provides a first step towards evaluation of tumor growth based on tumor-specific metabolomic data.

Targeting Cancer Metabolism Plasticity with JX06 Nanoparticles via Inhibiting PDK1 Combined with Metformin for Endometrial Cancer Patients with Diabetes

Diabetes is closely related to the occurrence of endometrial cancer (EC) and its poor prognosis. However, there is no effective clinical treatment for EC patients with diabetes (patient^EC+/dia+ ). To explore new therapeutic targets, Ishikawa is cultured with high glucose (Ishikawa^HG ) mimicking hyperglycemia in patient^EC+/dia+ . Subsequently, it is discovered that Ishikawa^HG exhibits glucose metabolic reprogramming characterized by increased glycolysis and decreased oxidative phosphorylation. Further, pyruvate dehydrogenase kinase 1 (PDK1) is identified to promote glycolysis of Ishikawa^HG by proteomics. Most importantly, JX06, a novel PDK1 inhibitor combined metformin (Met) significantly inhibits Ishikawa^HG proliferation though Ishikawa^HG is resistant to Met. Furthermore, a reduction-sensitive biodegradable polymer is adopted to encapsulate JX06 to form nanoparticles (JX06-NPs) for drug delivery. It is found that in vitro JX06-NPs have better inhibitory effect on the growth of Ishikawa^HG as well as patient-derived EC cells (PDC) than JX06. Additionally, it is found that JX06-NPs can accumulate to the tumor of EC-bearing mouse with diabetes (mice^EC+/dia+ ) after intravenous injection, and JX06-NPs combined Met can significantly inhibit tumor growth of mice^EC+/dia+ . Taken together, the study demonstrates that the combination of JX06-NPs and Met can target the cancer metabolism plasticity, which significantly inhibits the growth of EC, thereby provides a new adjuvant therapy for patients^EC+/dia+ .

Disruption of beta-catenin dependent Wnt signaling in colon cancer cells remodels the microenvironment to promote tumor invasion

The recent classification of colon cancer into molecular subtypes revealed that patients with the poorest prognosis harbor tumors with the lowest levels of Wnt signaling. This is contrary to the general understanding that overactive Wnt signaling promotes tumor progression from early initiation stages through to the later stages including invasion and metastasis. Here, we directly test this assumption by reducing the activity of ß-catenin-dependent Wnt signaling in colon cancer cell lines at either an upstream or downstream step in the pathway. We determine that Wnt-reduced cancer cells exhibit a more aggressive disease phenotype, including increased mobility in vitro and disruptive invasion into mucosa and smooth muscle in an orthotopic mouse model. RNA sequencing reveals that interference with Wnt signaling leads to an upregulation of gene programs that favor cell migration and invasion and a downregulation of inflammation signatures in the tumor microenvironment. We identify a set of upregulated genes common among the Wnt perturbations that are predictive of poor patient outcomes in early-invasive colon cancer. Our findings suggest that while targeting Wnt signaling may reduce tumor burden, an inadvertent side effect is the emergence of invasive cancer. Implications: Decreased Wnt signaling in colon tumors leads to a more aggressive disease phenotype due to an upregulation of gene programs favoring cell migration in the tumor and downregulation of inflammation programs in the tumor microenvironment; these impacts must be carefully considered in developing Wnt-targeting therapies.

Personalised Medicine for Colorectal Cancer Using Mechanism-Based Machine Learning Models

Gaining insight into the mechanisms of signal transduction networks (STNs) by using critical features from patient-specific mathematical models can improve patient stratification and help to identify potential drug targets. To achieve this, these models should focus on the critical STNs for each cancer, include prognostic genes and proteins, and correctly predict patient-specific differences in STN activity. Focussing on colorectal cancer and the WNT STN, we used mechanism-based machine learning models to identify genes and proteins with significant associations to event-free patient survival and predictive power for explaining patient-specific differences of STN activity. First, we identified the WNT pathway as the most significant pathway associated with event-free survival. Second, we built linear-regression models that incorporated both genes and proteins from established mechanistic models in the literature and novel genes with significant associations to event-free patient survival. Data from The Cancer Genome Atlas and Clinical Proteomic Tumour Analysis Consortium were used, and patient-specific STN activity scores were computed using PROGENy. Three linear regression models were built, based on; (1) the gene-set of a state-of-the-art mechanistic model in the literature, (2) novel genes identified, and (3) novel proteins identified. The novel genes and proteins were genes and proteins of the extant WNT pathway whose expression was significantly associated with event-free survival. The results show that the predictive power of a model that incorporated novel event-free associated genes is better compared to a model focussing on the genes of a current state-of-the-art mechanistic model. Several significant genes that should be integrated into future mechanistic models of the WNT pathway are DVL3, FZD5, RAC1, ROCK2, GSK3B, CTB2, CBT1, and PRKCA. Thus, the study demonstrates that using mechanistic information in combination with machine learning can identify novel features (genes and proteins) that are important for explaining the STN heterogeneity between patients and their association to clinical outcomes.

Metabolic Reprogramming of Colorectal Cancer Cells and the Microenvironment: Implication for Therapy

Colorectal carcinoma (CRC) is one of the most frequently diagnosed carcinomas and one of the leading causes of cancer-related death worldwide. Metabolic reprogramming, a hallmark of cancer, is closely related to the initiation and progression of carcinomas, including CRC. Accumulating evidence shows that activation of oncogenic pathways and loss of tumor suppressor genes regulate the metabolic reprogramming that is mainly involved in glycolysis, glutaminolysis, one-carbon metabolism and lipid metabolism. The abnormal metabolic program provides tumor cells with abundant energy, nutrients and redox requirements to support their malignant growth and metastasis, which is accompanied by impaired metabolic flexibility in the tumor microenvironment (TME) and dysbiosis of the gut microbiota. The metabolic crosstalk between the tumor cells, the components of the TME and the intestinal microbiota further facilitates CRC cell proliferation, invasion and metastasis and leads to therapy resistance. Hence, to target the dysregulated tumor metabolism, the TME and the gut microbiota, novel preventive and therapeutic applications are required. In this review, the dysregulation of metabolic programs, molecular pathways, the TME and the intestinal microbiota in CRC is addressed. Possible therapeutic strategies, including metabolic inhibition and immune therapy in CRC, as well as modulation of the aberrant intestinal microbiota, are discussed.

Pyruvate dehydrogenase kinases (PDKs): an overview toward clinical applications

Pyruvate dehydrogenase kinase (PDK) can regulate the catalytic activity of pyruvate decarboxylation oxidation via the mitochondrial pyruvate dehydrogenase complex, and it further links glycolysis with the tricarboxylic acid cycle and ATP generation. This review seeks to elucidate the regulation of PDK activity in different species, mainly mammals, and the role of PDK inhibitors in preventing increased blood glucose, reducing injury caused by myocardial ischemia, and inducing apoptosis of tumor cells. Regulations of PDKs expression or activity represent a very promising approach for treatment of metabolic diseases including diabetes, heart failure, and cancer. The future research and development could be more focused on the biochemical understanding of the diseases, which would help understand the cellular energy metabolism and its regulation by pharmacological effectors of PDKs.

Effect of heterogeneity and spatial correlations on the structure of a tumor invasion front in cellular environments

Analysis of invasion front has been widely used to decipher biological properties, as well as the growth dynamics of the corresponding populations. Likewise, the invasion front of tumors has been investigated, from which insights into the biological mechanisms of tumor growth have been gained. We develop a model to study how tumors' invasion front depends on the relevant properties of a cellular environment. To do so, we develop a model based on a nonlinear reaction-diffusion equation, the Fisher-Kolmogorov-Petrovsky-Piskunov equation, to model tumor growth. Our study aims to understand how heterogeneity in the cellular environment's stiffness, as well as spatial correlations in its morphology, the existence of both of which has been demonstrated by experiments, affects the properties of tumor invasion front. It is demonstrated that three important factors affect the properties of the front, namely the spatial distribution of the local diffusion coefficients, the spatial correlations between them, and the ratio of the cells' duplication rate and their average diffusion coefficient. Analyzing the scaling properties of tumor invasion front computed by solving the governing equation, we show that, contrary to several previous claims, the invasion front of tumors and cancerous cell colonies cannot be described by the well-known models of kinetic growth, such as the Kardar-Parisi-Zhang equation.

Metabolic pathways regulating colorectal cancer initiation and progression

Colorectal cancer (CRC) is one of the most common types of cancer worldwide. Despite recent advances in the molecular genetics of CRC, poor treatment outcomes highlight the need for a better understanding of the underlying mechanisms accounting for tumor initiation and progression. Recently, deregulation of cellular metabolism has emerged as a key hallmark of cancer. Reprogramming of core cellular metabolic pathways by cancer cells provides energy, anaplerotic precursors and reducing equivalents required to support tumor growth. Here, we review key findings implicating cancer metabolism as a major contributor of tumor initiation, growth and metastatic dissemination in CRC. We summarize the metabolic pathways governing stem cell fate in the intestine, the metabolic adaptations of proliferating colon cancer cells and their crosstalk with oncogenic signaling, and how they fulfill the energetic demands imposed by the metastatic cascade. Lastly, we discuss how some of these metabolic pathways could represent new vulnerabilities of CRC cells with the potential to be targeted.

Quantitative Characterization of CD8+ T Cell Clustering and Spatial Heterogeneity in Solid Tumors

Quantitative characterization of the tumor microenvironment, including its immuno-architecture, is important for developing quantitative diagnostic and predictive biomarkers, matching patients to the most appropriate treatments for precision medicine, and for providing quantitative data for building systems biology computational models able to predict tumor dynamics in the context of immune checkpoint blockade therapies. The intra- and inter-tumoral spatial heterogeneities are potentially key to the understanding of the dose-response relationships, but they also bring challenges to properly parameterizing and validating such models. In this study, we developed a workflow to detect CD8+ T cells from whole slide imaging data, and quantify the spatial heterogeneity using multiple metrics by applying spatial point pattern analysis and morphometric analysis. The results indicate a higher intra-tumoral heterogeneity compared with the heterogeneity across patients. By comparing the baseline metrics with PD-1 blockade treatment outcome, our results indicate that the number of high-density T cell clusters of both circular and elongated shapes are higher in patients who responded to the treatment. This methodology can be applied to quantitatively characterize the tumor microenvironment, including immuno-architecture, and its heterogeneity for different cancer types.

Hypothesis: Caco-2 cell rotational 3D mechanogenomic turing patterns have clinical implications to colon crypts

Colon crypts are recognized as a mechanical and biochemical Turing patterning model. Colon epithelial Caco-2 cell monolayer demonstrated 2D Turing patterns via force analysis of apical tight junction live cell imaging which illuminated actomyosin meshwork linking the actomyosin network of individual cells. Actomyosin forces act in a mechanobiological manner that alters cell/nucleus/tissue morphology. We observed the rotational motion of the nucleus in Caco-2 cells that appears to be driven by actomyosin during the formation of a differentiated confluent epithelium. Single- to multi-cell ring/torus-shaped genomes were observed prior to complex fractal Turing patterns extending from a rotating torus centre in a spiral pattern consistent with a gene morphogen motif. These features may contribute to the well-described differentiation from stem cells at the crypt base to the luminal colon epithelium along the crypt axis. This observation may be useful to study the role of mechanogenomic processes and the underlying molecular mechanisms as determinants of cellular and tissue architecture in space and time, which is the focal point of the 4D nucleome initiative. Mathematical and bioengineer modelling of gene circuits and cell shapes may provide a powerful algorithm that will contribute to future precision medicine relevant to a number of common medical disorders.

New strategies for targeting glucose metabolism-mediated acidosis for colorectal cancer therapy

Colorectal cancer (CRC) is a heterogeneous group of diseases that are the result of abnormal glucose metabolism alterations with high lactate production by pyruvate to lactate conversion, which remodels acidosis and offers an evolutional advantage for tumor cells, even enhancing their aggressive phenotype. This review summarizes recent findings that involve multiple genes, molecules, and downstream signaling in the dysregulated glycolytic pathway, which can allow a tumor to initiate acid byproducts and to progress, thereby resulting in acidosis commonly found in the tumor microenvironment of CRC. Moreover, the relationship between CRC cells and the tumor acidic microenvironment, especially for regulating lactate production and lactate dehydrogenase A levels, is also discussed, as well as comprehensively defining different aspects of glycolytic pathways that affect cancer cell proliferation, invasion, and migration. Furthermore, this review concentrates on glucose metabolism-mediated transduction factors in CRC, which include acid-sensing ion channels, triosephosphate isomerase and key glycolysis-related enzymes that regulate glycolytic metabolites, coupled with the effect on tumor cell glycolysis as well as signaling pathways. In conclusion, glucose metabolism mediated by glycolytic pathways that are integral to tumor acidosis in CRC is demonstrated. Therefore, selective metabolic inhibitors or agents against these targets in glucose metabolism through glycolytic pathways may be clinically useful to regulate the tumor's acidic microenvironment for CRC treatment and to identify specific targets that regulate tumor acidosis through a cancer patient-personalized approach. Furthermore, strategies for modifying the metabolic processes that effectively inhibit cancer cell growth and tumor progression and activate potent anticancer effects may provide more effective antitumor prospects for CRC therapy.

Shift from stochastic to spatially-ordered expression of serine-glycine synthesis enzymes in 3D microtumors

Cell-to-cell differences in protein expression in normal tissues and tumors are a common phenomenon, but the underlying principles that govern this heterogeneity are largely unknown. Here, we show that in monolayer cancer cell-line cultures, the expression of the five metabolic enzymes of serine-glycine synthesis (SGS), including its rate-limiting enzyme, phosphoglycerate dehydrogenase (PHGDH), displays stochastic cell-to-cell variation. By contrast, in cancer cell line-derived three-dimensional (3D) microtumors PHGDH expression is restricted to the outermost part of the microtumors' outer proliferative cell layer, while the four other SGS enzymes display near uniform expression throughout the microtumor. A mathematical model suggests that metabolic stress in the microtumor core activates factors that restrict PHGDH expression. Thus, intracellular enzyme expression in growing cell ecosystems can shift to spatially ordered patterns in 3D structured environments due to emergent cell-cell communication, with potential implications for the design of effective anti-metabolic cancer therapies.

Autophagy promotes metastasis and glycolysis by upregulating MCT1 expression and Wnt/β-catenin signaling pathway activation in hepatocellular carcinoma cells

Background

Autophagy is a dynamic physiological process that can generate energy and nutrients for cell survival during stress. Autophagy can regulate the migration and invasive ability in cancer cells. However, the connection between autophagy and metabolism is unclear. Monocarboxylate transporter 1 (MCT1) plays an important role in lactic acid transport and H⁺ clearance in cancer cells, and Wnt/β-catenin signaling can increase cancer cell glycolysis. We investigated whether autophagy promotes glycolysis in hepatocellular carcinoma (HCC) cells by activating the Wnt/β-catenin signaling pathway, accompanied by MCT1 upregulation.

Methods

Autophagic activity was evaluated using western blotting, immunoblotting, and transmission electron microscopy. The underlying mechanisms of autophagy activation on HCC cell glycolysis were studied via western blotting, and Transwell, lactate, and glucose assays. MCT1 expression was detected using quantitative reverse transcription–PCR (real-time PCR), western blotting, and immunostaining of HCC tissues and the paired adjacent tissues.

Results

Autophagy promoted HCC cell glycolysis accompanied by MCT1 upregulation. Wnt/β-catenin signaling pathway activation mediated the effect of autophagy on HCC cell glycolysis. β-Catenin downregulation inhibited the autophagy-induced glycolysis in HCC cells, and reduced MCT1 expression in the HCC cells. MCT1 was highly expressed in HCC tissues, and high MCT1 expression correlated positively with the expression of microtubule-associated protein light chain 3 (LC3).

Conclusion

Activation of autophagy can promote metastasis and glycolysis in HCC cells, and autophagy induces MCT1 expression by activating Wnt/β-catenin signaling. Our study describes the connection between autophagy and glucose metabolism in HCC cells and may provide a potential therapeutic target for HCC treatment.

Electronic supplementary material

The online version of this article (10.1186/s13046-018-0673-y) contains supplementary material, which is available to authorized users.

Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - part A

Background

Ever since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials, augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues.

Results

This manuscript ∙ explores the strength of contributing factors in the signaling pathway, ∙ analyzes the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and ∙ investigates the deviations in fold changes in the recently found prevalence of psychophysical laws working in the pathway. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors obtained from static and time series expression profiles using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indices.

Conclusion

The results show the advantage of using density based indices over variance based indices mainly due to the former’s employment of distance measures & the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced & contribute to the pathway, as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis & representations in higher dimensional spaces can facilitate in time based administration of target therapeutic drugs & reveal hidden biological information within colorectal cancer samples.

Inhibition of nuclear Wnt signalling: challenges of an elusive target for cancer therapy

The highly conserved Wnt signalling pathway plays an important role in embryonic development and disease pathogenesis, most notably cancer. The 'canonical' or β-catenin-dependent Wnt signal initiates at the cell plasma membrane with the binding of Wnt proteins to Frizzled:LRP5/LRP6 receptor complexes and is mediated by the translocation of the transcription co-activator protein, β-catenin, into the nucleus. β-Catenin then forms a complex with T-cell factor (TCF)/lymphoid enhancer binding factor (LEF) transcription factors to regulate multiple gene programmes. These programmes play roles in cell proliferation, migration, vasculogenesis, survival and metabolism. Mutations in Wnt signalling pathway components lead to constitutively active Wnt signalling that drives aberrant expression of these programmes and development of cancer. It has been a longstanding and challenging goal to develop therapies that can interfere with the TCF/LEF-β-catenin transcriptional complex. This review will focus on the (i) structural considerations for targeting the TCF/LEF-β-catenin and co-regulatory complexes in the nucleus, (ii) current molecules that directly target TCF/LEF-β-catenin activity and (iii) ideas for targeting newly discovered components of the TCF/LEF-β-catenin complex and/or downstream gene programmes regulated by these complexes.

LINKED ARTICLES

This article is part of a themed section on WNT Signalling: Mechanisms and Therapeutic Opportunities. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.24/issuetoc.

Paracrine and autocrine regulation of gene expression by Wnt-inhibitor Dickkopf in wild-type and mutant hepatocytes

Background

Cells are able to communicate and coordinate their function within tissues via secreted factors. Aberrant secretion by cancer cells can modulate this intercellular communication, in particular in highly organised tissues such as the liver. Hepatocytes, the major cell type of the liver, secrete Dickkopf (Dkk), which inhibits Wnt/ β-catenin signalling in an autocrine and paracrine manner. Consequently, Dkk modulates the expression of Wnt/ β-catenin target genes. We present a mathematical model that describes the autocrine and paracrine regulation of hepatic gene expression by Dkk under wild-type conditions as well as in the presence of mutant cells.

Results

Our spatial model describes the competition of Dkk and Wnt at receptor level, intra-cellular Wnt/ β-catenin signalling, and the regulation of target gene expression for 21 individual hepatocytes. Autocrine and paracrine regulation is mediated through a feedback mechanism via Dkk and Dkk diffusion along the porto-central axis. Along this axis an APC concentration gradient is modelled as experimentally detected in liver. Simulations of mutant cells demonstrate that already a single mutant cell increases overall Dkk concentration. The influence of the mutant cell on gene expression of surrounding wild-type hepatocytes is limited in magnitude and restricted to hepatocytes in close proximity. To explore the underlying molecular mechanisms, we perform a comprehensive analysis of the model parameters such as diffusion coefficient, mutation strength and feedback strength.

Conclusions

Our simulations show that Dkk concentration is elevated in the presence of a mutant cell. However, the impact of these elevated Dkk levels on wild-type hepatocytes is confined in space and magnitude. The combination of inter- and intracellular processes, such as Dkk feedback, diffusion and Wnt/ β-catenin signal transduction, allow wild-type hepatocytes to largely maintain their gene expression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0470-9) contains supplementary material, which is available to authorized users.

Metabolic pattern formation in the tumor microenvironment

Metabolic alterations including increased glycolysis are a common feature of many cancers. In their recent study, Lowengrub, Waterman, and colleagues (Lee et al, 2017) report a spatial pattern of glycolysis in solid tumors that occurs within the tumor microenvironment. This spatial organization is linked to gradients derived from Wnt signaling and nutrient availability that mediate a reaction‐diffusion mechanism and is consistent with a Turing‐type model of spatial localization.

Mathematical modeling links Wnt signaling to emergent patterns of metabolism in colon cancer

Cell-intrinsic metabolic reprogramming is a hallmark of cancer that provides anabolic support to cell proliferation. How reprogramming influences tumor heterogeneity or drug sensitivities is not well understood. Here, we report a self-organizing spatial pattern of glycolysis in xenograft colon tumors where pyruvate dehydrogenase kinase (PDK1), a negative regulator of oxidative phosphorylation, is highly active in clusters of cells arranged in a spotted array. To understand this pattern, we developed a reaction-diffusion model that incorporates Wnt signaling, a pathway known to upregulate PDK1 and Warburg metabolism. Partial interference with Wnt alters the size and intensity of the spotted pattern in tumors and in the model. The model predicts that Wnt inhibition should trigger an increase in proteins that enhance the range of Wnt ligand diffusion. Not only was this prediction validated in xenograft tumors but similar patterns also emerge in radiochemotherapy-treated colorectal cancer. The model also predicts that inhibitors that target glycolysis or Wnt signaling in combination should synergize and be more effective than each treatment individually. We validated this prediction in 3D colon tumor spheroids.