Convergent Science Physical Oncology

In the tumour microenvironment, cancer cells directly interact with both the immune system and the stroma. It is firmly established that the immune system, historically believed to be a major part of the body's defence against tumour progression, can be reprogrammed by tumour cells to be ineffective, inactivated, or even acquire tumour promoting phenotypes. Likewise, stromal cells and extracellular matrix can also have pro- and anti-tumour properties. However, there is strong evidence that the stroma and immune system also directly interact, therefore creating a tripartite interaction that exists between cancer cells, immune cells and tumour stroma. This interaction contributes to the maintenance of a chronically inflamed tumour microenvironment with pro-tumorigenic immune phenotypes and facilitated metastatic dissemination. A comprehensive understanding of cancer in the context of dynamical interactions of the immune system and the tumour stroma is therefore required to truly understand the progression toward and past malignancy.

The current paradigm views cancer as arising clonally from a degradation of genetic information in single cells. A complementary perspective, originating at the dawn of modern developmental biology, is that cancer is the result of a system disorder of algorithms that normally orchestrate individual cell activities toward specific anatomical structures and away from tumorigenesis. A view of cancer as a disease of geometry focuses on the pathways that allow cells to cooperate to build and maintain large-scale anatomical patterning. Cancer may result when cells stop maintaining higher-order structures and reduce the boundary of their computational selves to a single-cell level, reverting to a unicellular lifestyle in which the rest of the organism is merely part of the environment at the expense of which all living things survive. While this view has been widely discussed, little progress has been made in providing a quantitative, mechanistic framework within which this perspective's specific and unique implications for treatment strategies can be tested and biomedically exploited. Here, we highlight two recent areas of progress which may facilitate much-needed progress on the cancer problem. First, we review the roles that endogenous bioelectrical networks, operating across many tissues in vivo, play as a medium of information processing in tumor suppression, progression, and reprogramming. Second, we provide a primer to the development of computational theory and tools for quantifying the information and causal control structures in cancer and other complex biological systems. Rigorous mathematical formalisms now exist to measure and analyze the extent to which 'a whole is more than the sum of its parts', applications of which could lead to new strategies for cancer reprogramming. Here, we review the basic landscape of these related subfields, and sketch specific ways in which a synthesis of novel integrative biophysics and mathematical analysis may contribute to novel ways to understand and address cancer in vivo.

Lung cancer is often classified by the presence of oncogenic drivers, such as epidermal growth factor receptor (EGFR), rather than patterns of anatomical distribution. While metastatic spread may seem a random and unpredictable process, we explored the possibility of using its quantifiable nature as a measure of describing and comparing different subsets of disease. We constructed a database of 664 non-small cell lung cancer (NSCLC) patients treated at the University of Southern California Norris Comprehensive Cancer Center and the Los Angeles County Medical Center. Markov mathematical modeling was employed to assess metastatic sites in a spatiotemporal manner through every time point in progression of disease. Our findings identified a preferential pattern of primary lung disease progressing through lung metastases to the brain amongst EGFR mutated (EGFR^m) NSCLC patients, with exon 19 deletions or exon 21 L858R mutations, as compared to EGFR wild type (EGFR^wt). The brain was classified as an anatomic 'sponge', with a higher ratio of incoming to outgoing spread, for EGFR^m NSCLC. Bone metastases were more commonly identified in EGFR^wt patients. Our study supports a link between the anatomical and molecular characterization of metastatic lung cancer. Improved understanding of the differential biology that drives discordant patterns of anatomic spread, based on genotype specific profiling, has the potential to improve personalized oncologic care.

Cellular motility and invasion in connective tissue is a basic and fundamental process during normal physiological tissue developments and assemblies, prevention of inflammation after tissue injury through wound healing and malignant progression of cancer such as metastasis. Cell invasion usually requires cell adhesion via cell–matrix receptors to the extracellular matrix which are coupled to the cell's actomyosin cytoskeleton. In many tumors, matrix and hence tissue mechanics are altered and increased tissue stiffness is associated with increased malignancy and metastasis. Moreover, cellular mechanical properties are altered in invasive cancer cells compared to less invasive cancer cells. Here, we have studied the invasion of human breast cancer cells into loose and dense 3D engineered matrices consisting of a collagen type I fiber network and determined the cellular mechanical properties such as stiffness. As expected, the cellular stiffness correlates with the invasiveness of the cancer cells in loose and dense 3D matrices. We hypothesized that the matrix and cellular mechanical properties regulate the motility (invasiveness) of cancer cells in 3D engineered matrices, which has been shown to be to be regulated by the actomyosin cytoskeleton and is in 3D constrictions possibly also regulated by the small Rho GTPase Rac1's activity as demonstrated for cellular motility on 2D substrates. Pharmacological interventions indicate that in 3D matrices, invasive cancer cells behave similarly as non-invasive cancer cells, when treated with inhibitors of the small Rho GTPase Rac1 or the actomyosin-contractility. Matrix fiber displacement analysis in 3D engineered matrices revealed that the invasive MDA-MB-231cancer cells generated significantly higher and long-raged matrix fiber displacements by contraction of the matrix environment than non-invasive MCF-7 and MCF-10A breast cancer cells, which seems to be the main prerequisite for their increased invasion through the 3D extracellular matrix environment. In addition, a decrease in adhesion-dependent and adhesion-independent cellular stiffness of invasive MDA-MB-231 cancer cells after addition of the actin polymerization inhibitor Latrunculin A leads to reduced 3D invasiveness and significantly reduced matrix fiber displacements. Besides cellular mechanical properties, a 18-fold increase in matrix stiffness increased the invasiveness of all three cell types suggesting that matrix stiffness may have an invasion-enhancing effect. Finally, our findings demonstrate that mechanical properties of breast cancer cells and the 3D matrix environment facilitate 3D matrix invasion through increased actomyosin-dependent cellular stiffness and transmission of contractile force in dense 3D engineered collagen matrices.

Initiation and development of cancer are usually accompanied by alterations in the cellular mechanical properties such as its stiffness and viscosity. Understanding the viscoelasticity of cancer cells can provide a better insight into the mechanics of the metastasis of cancer cells. Here, we use atomic force microscopy to compare the viscoelasticity of mammary epithelial cells with different metastatic potentials in their adherent and suspended states. We measure cell elasticity through the spatial mapping of Young's modulus using the force-indentation technique and cell viscosity using stress relaxation. The viscoelastic properties of cancer cells are associated with their malignancy and intrinsic cytoskeletal structures. Our results suggest that the Young's modulus of adherent cells inversely correlates to their malignancy and that the F-actin arrangement and intensity support the mechanical phenotype. For suspended cells, we observe that they exhibit lower elasticity than adhered cells due to the distribution of actin filaments at the cell cortex as well as reduced polymerization. Our viscosity results suggest that in both adhered and suspended cases, normal breast epithelial cells exhibit higher viscosity than that of cancer cells. Actin distribution and higher nucleus to cytoplasmic ratio in cancer cells are observed to be the two main factors in determining cell viscosity.

The question of the existence of cancer is inadequately answered by invoking somatic mutations or the disruptions of cellular and tissue control mechanisms. As such uniformly random events alone cannot account for the almost inevitable occurrence of an extremely complex process such as cancer. In the different epistemic realm, an ultimate explanation of cancer is that cancer is a reversion of a cell to an ancestral pre-Metazoan state, i.e. a cellular form of atavism. Several studies have suggested that genes involved in cancer have evolved at particular evolutionary time linked to the unicellular-multicellular transition. Here we used a refined phylostratigraphic analysis of evolutionary ages of the known genes/pathways associated with cancer and the genes differentially expressed between normal and cancer tissue as well as between embryonic and mature (differentiated) cells. We found that cancer-specific transcriptomes and cancer-related pathways were enriched for genes that evolved in the pre-Metazoan era and depleted of genes that evolved in the post-Metazoan era. By contrast an opposite relation was found for cell maturation: the age distribution frequency of the genes expressed in differentiated epithelial cells were enriched for post-Metazoan genes and depleted of pre-Metazoan ones. These findings support the atavism theory that cancer cells manifest the reactivation of an ancient ancestral state featuring unicellular modalities. Thus our bioinformatics analyses suggest that not only does oncogenesis recapitulate ontogenesis, and ontogenesis recapitulates phylogenesis, but also oncogenesis recapitulates phylogenesis. This more encompassing perspective may offer a natural organizing framework for genetic alterations in cancers and point to new treatment options that target the genes controlling the atavism transition.

One sentence summary: Tracing cancer gene evolutionary ages revealed that cancer reverts to a pre-existing early Metazoan state.

With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility. This work explores challenges in how different experimental design decisions can influence results using a specific example of breast cancer patients undergoing excision and reconstruction surgeries from EMRs in an academic hospital and the Veterans Health Administration (VHA). We discuss emerging strategies that will mitigate these limitations, including data sharing, application of natural language processing, and improved EMR user design.

Recent developments in biotechnology have enabled scientists to modulate DNA sequences in a precise way. These genome engineering technologies also open new possibilities to alter the epigenetic composition of the genome at any given genomic location thereby changing gene expression patterns, while leaving the primary DNA sequence intact. This new approach, so-called epigenetic editing, holds great promise to permanently reprogram cell identity. As reprogramming the epigenetic composition, and hence gene expression patterns is now technically feasible, the society needs to consider to what extent interference at the epigenetic level can be accepted. In this review, we discuss the potential epigenetic editing holds for research and therapy, and also touch upon societal implications of this rapidly growing research field.

The dismal prognosis of pancreatic cancer has motivated research into identifying non-invasive 'liquid biopsy' biomarkers for early detection when treatment is most effective. Recently, exosomes—nanoscale membranous vesicles shed from tumour cells and which can be found circulating in the blood (and most bodily fluids)—have been discovered to contain a wealth of proteomic and genetic information, showing promise for pre-symptomatic screening and monitoring of disease. Here we examine recent findings highlighting the diagnostic value of exosomes in pancreatic cancer as well as the emerging use of lab-on-a-chip (LOC) technologies aiming to streamline exosome isolation and analysis.

Vascular endothelial growth factor (VEGF) can mediate endothelial cell migration, proliferation, and angiogenesis. During cancer progression, VEGF production is often increased to stimulate the growth of new blood vessels to supply growing tumors with the additional oxygen and nutrients they require. Extracellular matrix stiffening also occurs during tumor progression, however, the crosstalk between tumor mechanics and VEGF signaling remains poorly understood. Here, we show that matrix stiffness heightens downstream endothelial cell response to VEGF by altering VEGF receptor-2 (VEGFR-2) internalization, and this effect is influenced by cell confluency. In sub-confluent endothelial monolayers, VEGFR-2 levels, but not VEGFR-2 phosphorylation, are influenced by matrix rigidity. Interestingly, more compliant matrices correlated with increased expression and clustering of VEGFR-2; however, stiffer matrices induced increased VEGFR-2 internalization. These effects are most likely due to actin-mediated contractility, as inhibiting ROCK on stiff substrates increased VEGFR-2 clustering and decreased internalization. Additionally, increasing matrix stiffness elevates ERK 1/2 phosphorylation, resulting in increased cell proliferation. Moreover, cells on stiff matrices generate more actin stress fibers than on compliant substrates, and the addition of VEGF stimulates an increase in fiber formation regardless of stiffness. In contrast, once endothelial cells reached confluency, stiffness-enhanced VEGF signaling was no longer observed. Together, these data show a complex effect of VEGF and matrix mechanics on VEGF-induced signaling, receptor dynamics, and cell proliferation that is mediated by cell confluency.

A rapid increase in the volume and availability of electronic medical record (EMR) data and its potential to positively impact patient care, led to a collaboration between the Department of Veterans Affairs (VA) and the National Cancer Institute (NCI). The result of the collaboration, the big data scientist training enhancement program (BD-STEP) was launched in 2015 with the objective of enabling a transition from the traditional healthcare model of observe and treat to a desired future state of predict and prevent. The BD-STEP Program brings together expertise of clinicians, researchers and data scientists to use EMR data to directly impact patient decision-making. This program represents a first time collaboration in VA of the Office of Academic Affiliations, Employee Education System, and the Office of Research and Development with the intended outcome of bridging the gap between the administrative, clinical, and research worlds to achieving a common goal—to train the next generation of data scientists to understand data in the context of health care delivery. As an interdisciplinary program, BD-STEP will provide data scientists trained to use EMR data to: (1) accelerate learning (2) inform healthcare systems administrators and; (3) empower clinicians to translate findings to improve patient care. This review will provide an overview of the intersection of precision medicine, data science, and patient engagement, and share a vision for how BD-STEP will use a team science approach to deliver personalized care for patients to reduce cost and improve outcomes.

The current paradigm views cancer as arising clonally from a degradation of genetic information in single cells. A complementary perspective, originating at the dawn of modern developmental biology, is that cancer is the result of a system disorder of algorithms that normally orchestrate individual cell activities toward specific anatomical structures and away from tumorigenesis. A view of cancer as a disease of geometry focuses on the pathways that allow cells to cooperate to build and maintain large-scale anatomical patterning. Cancer may result when cells stop maintaining higher-order structures and reduce the boundary of their computational selves to a single-cell level, reverting to a unicellular lifestyle in which the rest of the organism is merely part of the environment at the expense of which all living things survive. While this view has been widely discussed, little progress has been made in providing a quantitative, mechanistic framework within which this perspective's specific and unique implications for treatment strategies can be tested and biomedically exploited. Here, we highlight two recent areas of progress which may facilitate much-needed progress on the cancer problem. First, we review the roles that endogenous bioelectrical networks, operating across many tissues in vivo, play as a medium of information processing in tumor suppression, progression, and reprogramming. Second, we provide a primer to the development of computational theory and tools for quantifying the information and causal control structures in cancer and other complex biological systems. Rigorous mathematical formalisms now exist to measure and analyze the extent to which 'a whole is more than the sum of its parts', applications of which could lead to new strategies for cancer reprogramming. Here, we review the basic landscape of these related subfields, and sketch specific ways in which a synthesis of novel integrative biophysics and mathematical analysis may contribute to novel ways to understand and address cancer in vivo.

Platelets are anucleate cells in the blood at concentrations of 150 000–400 000 cells µl⁻¹ and play a key role in hemostasis. Several studies have suggested that platelets contribute to cancer progression and cancer-associated thrombosis. In this review, we provide an overview of the biochemical and biophysical mechanisms by which platelets interact with cancer cells and review the evidence supporting a role for platelet-enhanced metastasis of cancer, and venous thromboembolism (VTE) in patients with cancer. We discuss the potential for and limitations of platelet counts to discriminate cancer disease burden and prognosis. Lastly, we consider more advanced diagnostic approaches to improve studies on the interaction between the hemostatic system and cancer cells.

Recent developments in biotechnology have enabled scientists to modulate DNA sequences in a precise way. These genome engineering technologies also open new possibilities to alter the epigenetic composition of the genome at any given genomic location thereby changing gene expression patterns, while leaving the primary DNA sequence intact. This new approach, so-called epigenetic editing, holds great promise to permanently reprogram cell identity. As reprogramming the epigenetic composition, and hence gene expression patterns is now technically feasible, the society needs to consider to what extent interference at the epigenetic level can be accepted. In this review, we discuss the potential epigenetic editing holds for research and therapy, and also touch upon societal implications of this rapidly growing research field.

The dismal prognosis of pancreatic cancer has motivated research into identifying non-invasive 'liquid biopsy' biomarkers for early detection when treatment is most effective. Recently, exosomes—nanoscale membranous vesicles shed from tumour cells and which can be found circulating in the blood (and most bodily fluids)—have been discovered to contain a wealth of proteomic and genetic information, showing promise for pre-symptomatic screening and monitoring of disease. Here we examine recent findings highlighting the diagnostic value of exosomes in pancreatic cancer as well as the emerging use of lab-on-a-chip (LOC) technologies aiming to streamline exosome isolation and analysis.