Convergent Science Physical Oncology

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.

Rheology of living cells has developed an increasing need for high throughput measurements. Diseases such as cancer heavily remodel the cytoskeleton and impinge on cellular functions. Cells affected by such diseases show altered rheologic responses on many different levels rendering cells' mechanical fingerprints—a potential target for diagnostics. To counteract naturally occurring distributions of properties in samples of living cells and foster the validity of experiments, high numbers of single cell measurements are necessary. Here, we present the 'in flow optical stretcher' (IFOS), a concept of non-invasive optical cytometry capable of high throughput rates, while working in a regime of long measurement times and low frequencies. The setup deforms whole cells in a continuous flow by optical forces, bypassing steps of cell positioning that are unavoidable in state-of-the-art optical stretcher devices. A prototype was built using polydimethylsiloxane soft lithography. In a proof of premise experiment, we show that in the IFOS it is possible to deform cells of mammalian origin which have been treated with cytochalasin. All recorded successful experiments took place in less than 2 s each, as opposed to 10–20 s in state-of-the-art optical stretcher devices. Although other microfluidic rheology devices achieve significantly higher throughput rates, they operate in different frequency regimes and probe different mechanical responses. The IFOS still captures viscoelastic properties and active responses of cells while aiming to maximize the throughput at creep times on the order of seconds. It can be assumed that an automatic IFOS reaches a throughput an order of magnitude higher than current devices that are based on optical stretching for cell rheology.

The majority of cancers are diagnosed using excised biopsy specimens. These are graded, using a gold-standard histopathology protocol based on haemotoxylin and eosin ('H  +  E') chemical staining. However the grading is done by eye and if the same biopsy is graded by different practitioners, they typically only agree ~70% of the time.

The resulting overtreatment problem constitutes a massive unmet need worldwide.

Our new "Digistain" technology, uses mid-infrared imaging to map the fractional concentration of nucleic acids, i.e. the nuclear-to-cytoplasmic chemical ratio (NCR) across an unstained biopsy section. It allows a quantitative 'Digistain index' (DI) score, corresponding to the NCR, to be reproducibly extracted from an objective physical measurement of a cancer. Our objective here is to evaluate its potential for aiding cancer diagnosis for the first time. We correlate the DI scores with H  +  E grades in a double-blind clinical pilot trial.

Two adjacent slices were taken from 75 breast cancer FFPE blocks; one was graded with the standard H  +  E protocol, and also used to define a 'region of interest' (RoI). Digistain was then used to acquire a DI value averaged over the corresponding RoI on the other (unstained) slice and the results were statistically analysed.

We find the DI score correlates significantly (p  =  0.0007) with tumor grade in a way that promises to significantly reduce the inherent subjectivity and variability in biopsy grading.

The NCR is elevated by increased mitotic activity because cells divide when they are younger and, on average, become smaller as the disease progresses. Also, extra DNA and RNA is generated as the nuclear transcription machinery goes awry and nuclear pleomorphism occurs. Both effects make the NCR a recognized biomarker for a wide range of tumors, so we expect Digistain will find application in a very wide range of cancers.

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.

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.

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.

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.

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.

Tumor heterogeneity is prevalent in both treatment-naïve and end-stage metastatic castration-resistant prostate cancer (PCa), and may contribute to the broad range of clinical presentation, treatment response, and disease progression. To characterize molecular heterogeneity associated with de novo metastatic PCa, multiplatform single cell profiling was performed using high definition single cell analysis (HD-SCA). HD-SCA enabled morphoproteomic and morphogenomic profiling of single cells from touch preparations of tissue cores (prostate and bone marrow biopsies) as well as liquid samples (peripheral blood and bone marrow aspirate). Morphology, nuclear features, copy number alterations, and protein expression were analyzed. Tumor cells isolated from prostate tissue touch preparation (PTTP) and bone marrow touch preparation (BMTP) as well as metastatic tumor cells (MTCs) isolated from bone marrow aspirate were characterized by morphology and cytokeratin expression. Although peripheral blood was examined, circulating tumor cells were not definitively observed. Targeted proteomics of PTTP, BMTP, and MTCs revealed cell lineage and luminal prostate epithelial differentiation associated with PCa, including co-expression of EpCAM, PSA, and PSMA. Androgen receptor expression was highest in MTCs. Hallmark PCa copy number alterations, including PTEN and ETV6 deletions and NCOA2 amplification, were observed in cells within the primary tumor and bone marrow biopsy samples. Genomic landscape of MTCs revealed to be a mix of both primary and bone metastatic tissue. This multiplatform analysis of single cells reveals several clonal origins of metastatic PCa in a newly diagnosed, untreated patient with polymetastatic disease. This case demonstrates that real-time molecular profiling of cells collected through prostate and bone marrow biopsies is feasible and has the potential to elucidate the origin and evolution of metastatic tumor cells. Altogether, biological and genomic data obtained through longitudinal biopsies can be used to reveal the properties of PCa and can impact clinical management.

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.