The ecology of cancer differentiation therapy

Novel small molecule DMAMCL induces differentiation in rhabdomyosarcoma by downregulating of DLL1

Rhabdomyosarcoma (RMS), a mesenchymal tumor occurring in the soft tissue of children, is associated with a defect in differentiation. This study unveils a novel anti-tumor mechanism of dimethylaminomicheliolide (DMAMCL), which is a water-soluble derivative of Micheliolide. First, we demonstrate that DMAMCL inhibits RMS cell growth without obvious cell death, leading to morphological alterations, enhanced expression of muscle differentiation markers, and a shift from a malignant to a more benign metabolic phenotype. Second, we detected decreased expression of DLL1 in RMS cells after DMAMCL treatment, known as a pivotal ligand in the Notch signaling pathway. Downregulation of DLL1 inhibits RMS cell growth and induces morphological changes similar to the effects of DMAMCL. Furthermore, DMAMCL treatment or loss of DLL1 expression also inhibits RMS xenograft tumor growth and augmented the expression of differentiation markers. Surprisingly, in C2C12 cells DMAMCL treatment or DLL1 downregulation also induces cell growth inhibition and an elevation in muscle differentiation marker expression. These data indicated that DMAMCL induced RMS differentiation and DLL1 is an important factor for RMS differentiation, opening a new window for the clinical use of DMAMCL as an agent for differentiation-inducing therapy for RMS treatment.

Modeling tumors as species-rich ecological communities

Many advanced cancers resist therapeutic intervention. This process is fundamentally related to intra-tumor heterogeneity: multiple cell populations, each with different mutational and phenotypic signatures, coexist within a tumor and its metastatic nodes. Like species in an ecosystem, many cancer cell populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity nor are able to predict its consequences. Here we propose that the Generalized Lotka-Volterra model (GLV), a standard tool to describe complex, species-rich ecological communities, provides a suitable framework to describe the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties, such as outgrowth and multistability, provide a new understanding of the disease. Additionally, we discuss potential extensions of the model and their application to three active areas of cancer research, namely phenotypic plasticity, the cancer-immune interplay and the resistance of metastatic tumors to treatment. Our work outlines a set of questions and a tentative road map for further research in cancer ecology.

Cancer Stem Cells are Actually Stem Cells with Disordered Differentiation: the Monophyletic Origin of Cancer

Cancer stem cells (CSCs) play an important role in cancer development. Based on advancements in CSC research, we propose a monophyletic model of cancer. This model is based on the idea that CSCs are stem cells with disordered differentiation whose original purpose was to repair damaged tissues. Inflammatory responses and damage repair signals are crucial for the creation and maintenance of CSCs. Normal quiescent stem cells are activated by environmental stimulation, such as an inflammatory response, and undergo cell division and differentiation. In the initial stage of cancer development, stem cell differentiation leads to heteromorphism due to the accumulation of gene mutations, resulting in the development of metaplasia or precancerosis. In the second stage, accumulated mutations induce poor differentiation and lead to cancer development. The monophyletic model illustrates the evolution, biological behavior, and hallmarks of CSCs, proposes a concise understanding of the origin of cancer, and may encourage a novel therapeutic approach.

NDRG1 in Cancer: A Suppressor, Promoter, or Both?

N-myc downregulated gene-1 (NDRG1) has been variably reported as a metastasis suppressor, a biomarker of poor outcome, and a facilitator of disease progression in a range of different cancers. NDRG1 is poorly understood in cancer due to its context-dependent and pleiotropic functions. Within breast cancer, NDRG1 is reported to be either a facilitator of, or an inhibitor of tumour progression and metastasis. The wide array of roles played by NDRG1 are dependent on post-translational modifications and subcellular localization, as well as the cellular context, for example, cancer type. We present an update on NDRG1, and its association with hallmarks of cancer such as hypoxia, its interaction with oncogenic proteins such as p53 as well its role in oncogenic and metastasis pathways in breast and other cancers. We further comment on its functional implications as a metastasis suppressor and promoter, its clinical relevance, and discuss its therapeutic targetability in different cancers.

Hepatogenesis and hepatocarcinogenesis: Alignment of the main signaling pathways

Development is a symphony of cells differentiation in which different signaling pathways are orchestrated at specific times and periods to form mature and functional cells from undifferentiated cells. The similarity of the gene expression profile in malignant and undifferentiated cells is an interesting topic that has been proposed for many years and gave rise to the differentiation-therapy concept, which appears a rational insight and should be reconsidered. Hepatocellular carcinoma (HCC), as the sixth common cancer and the third leading cause of cancer death worldwide, is one of the health-threatening complications in communities where hepatotropic viruses are endemic. Sedentary lifestyle and high intake of calories are other risk factors. HCC is a complex condition in which various dimensions must be addressed, including heterogeneity of cells in the tumor mass, high invasiveness, and underlying diseases that limit the treatment options. Under these restrictions, recognizing, and targeting common signaling pathways during liver development and HCC could expedite to a rational therapeutic approach, reprograming malignant cells to well-differentiated ones in a functional state. Accordingly, in this review, we highlighted the commonalities of signaling pathways in hepatogenesis and hepatocarcinogenesis, and comprised an update on the current status of targeting these pathways in laboratory studies and clinical trials.

Ecology of Human Medical Enterprises: From Disease Ecology of Zoonoses, Cancer Ecology Through to Medical Ecology of Human Microbiomes

In nature, the interaction between pathogens and their hosts is only one of a handful of interaction relationships between species, including parasitism, predation, competition, symbiosis, commensalism, and among others. From a non-anthropocentric view, parasitism has relatively fewer essential differences from the other relationships; but from an anthropocentric view, parasitism and predation against humans and their well-beings and belongings are frequently related to heinous diseases. Specifically, treating (managing) diseases of humans, crops and forests, pets, livestock, and wildlife constitute the so-termed medical enterprises (sciences and technologies) humans endeavor in biomedicine and clinical medicine, veterinary, plant protection, and wildlife conservation. In recent years, the significance of ecological science to medicines has received rising attentions, and the emergence and pandemic of COVID-19 appear accelerating the trend. The facts that diseases are simply one of the fundamental ecological relationships in nature, and the study of the relationships between species and their environment is a core mission of ecology highlight the critical importance of ecological science. Nevertheless, current studies on the ecology of medical enterprises are highly fragmented. Here, we (i) conceptually overview the fields of disease ecology of wildlife, cancer ecology and evolution, medical ecology of human microbiome-associated diseases and infectious diseases, and integrated pest management of crops and forests, across major medical enterprises. (ii) Explore the necessity and feasibility for a unified medical ecology that spans biomedicine, clinical medicine, veterinary, crop (forest and wildlife) protection, and biodiversity conservation. (iii) Suggest that a unified medical ecology of human diseases is both necessary and feasible, but laissez-faire terminologies in other human medical enterprises may be preferred. (iv) Suggest that the evo-eco paradigm for cancer research can play a similar role of evo-devo in evolutionary developmental biology. (v) Summarized 40 key ecological principles/theories in current disease-, cancer-, and medical-ecology literatures. (vi) Identified key cross-disciplinary discovery fields for medical/disease ecology in coming decade including bioinformatics and computational ecology, single cell ecology, theoretical ecology, complexity science, and the integrated studies of ecology and evolution. Finally, deep understanding of medical ecology is of obvious importance for the safety of human beings and perhaps for all living things on the planet.

Transition Therapy: Tackling the Ecology of Tumor Phenotypic Plasticity

Phenotypic switching in cancer cells has been found to be present across tumor types. Recent studies on Glioblastoma report a remarkably common architecture of four well-defined phenotypes coexisting within high levels of intra-tumor genetic heterogeneity. Similar dynamics have been shown to occur in breast cancer and melanoma and are likely to be found across cancer types. Given the adaptive potential of phenotypic switching (PHS) strategies, understanding how it drives tumor evolution and therapy resistance is a major priority. Here we present a mathematical framework uncovering the ecological dynamics behind PHS. The model is able to reproduce experimental results, and mathematical conditions for cancer progression reveal PHS-specific features of tumors with direct consequences on therapy resistance. In particular, our model reveals a threshold for the resistant-to-sensitive phenotype transition rate, below which any cytotoxic or switch-inhibition therapy is likely to fail. The model is able to capture therapeutic success thresholds for cancers where nonlinear growth dynamics or larger PHS architectures are in place, such as glioblastoma or melanoma. By doing so, the model presents a novel set of conditions for the success of combination therapies able to target replication and phenotypic transitions at once. Following our results, we discuss transition therapy as a novel scheme to target not only combined cytotoxicity but also the rates of phenotypic switching.