Thermodynamic energetics underlying genomic instability and whole-genome doubling in cancer.

Genomic instability contributes to tumorigenesis through the amplification and deletion of cancer driver genes. DNA copy number (CN) profiling of ensembles of tumors allows a thermodynamic analysis of the profile for each tumor. The free energy of the distribution of CNs is found to be a monotonically increasing function of the average chromosomal ploidy. The dependence is universal across several cancer types. Surprisal analysis distinguishes two main known subgroups: tumors with cells that have or have not undergone whole-genome duplication (WGD). The analysis uncovers that CN states having a narrower distribution are energetically more favorable toward the WGD transition. Surprisal analysis also determines the deviations from a fully stable-state distribution. These deviations reflect constraints imposed by tumor fitness selection pressures. The results point to CN changes that are more common in high-ploidy tumors and thus support altered selection pressures upon WGD.

T cell-derived interferon-γ programs stem cell death in immune-mediated intestinal damage.

Despite the importance of intestinal stem cells (ISCs) for epithelial maintenance, there is limited understanding of how immune-mediated damage affects ISCs and their niche. We found that stem cell compartment injury is a shared feature of both alloreactive and autoreactive intestinal immunopathology, reducing ISCs and impairing their recovery in T cell-mediated injury models. Although imaging revealed few T cells near the stem cell compartment in healthy mice, donor T cells infiltrating the intestinal mucosa after allogeneic bone marrow transplantation (BMT) primarily localized to the crypt region lamina propria. Further modeling with ex vivo epithelial cultures indicated ISC depletion and impaired human as well as murine organoid survival upon coculture with activated T cells, and screening of effector pathways identified interferon-γ (IFNγ) as a principal mediator of ISC compartment damage. IFNγ induced JAK1- and STAT1-dependent toxicity, initiating a proapoptotic gene expression program and stem cell death. BMT with IFNγ-deficient donor T cells, with recipients lacking the IFNγ receptor (IFNγR) specifically in the intestinal epithelium, and with pharmacologic inhibition of JAK signaling all resulted in protection of the stem cell compartment. In addition, epithelial cultures with Paneth cell-deficient organoids, IFNγR-deficient Paneth cells, IFNγR-deficient ISCs, and purified stem cell colonies all indicated direct targeting of the ISCs that was not dependent on injury to the Paneth cell niche. Dysregulated T cell activation and IFNγ production are thus potent mediators of ISC injury, and blockade of JAK/STAT signaling within target tissue stem cells can prevent this T cell-mediated pathology.

Intracellular redox potential is correlated with miRNA expression in MCF7 cells under hypoxic conditions.

Hypoxia is a ubiquitous feature of cancers, encouraging glycolytic metabolism, proliferation, and resistance to therapy. Nonetheless, hypoxia is a poorly defined term with confounding features described in the literature. Redox biology provides an important link between the external cellular microenvironment and the cell's response to changing oxygen pressures. In this paper, we demonstrate a correlation between intracellular redox potential (measured using optical nanosensors) and the concentrations of microRNAs (miRNAs) involved in the cell's response to changes in oxygen pressure. The correlations were established using surprisal analysis (an approach derived from thermodynamics and information theory). We found that measured redox potential changes reflect changes in the free energy computed by surprisal analysis of miRNAs. Furthermore, surprisal analysis identified groups of miRNAs, functionally related to changes in proliferation and metastatic potential that played the most significant role in the cell's response to changing oxygen pressure.

The covalent binding story of the complement proteins C3 and C4 (I) 1972-1981.

Alex Law and Paul Levine recall their work to establish the covalent bond between C3 and target surfaces. It started with a naive experiment by analyzing the membrane polypeptides of sheep erythrocytes bound with 125I-labelled C3. They found complexes with molecular weight higher than the individual C3 polypeptides. These complexes survived all conditions designed to disrupt non-covalent interactions. They then showed that the bond was an ester, with an active acyl group on C3 which reacted with a hydroxyl group on the acceptor molecule. With the discovery of an internal thioester by Jim Prahl, Jamila Janatova, Brian Tack and their colleagues, it became clear that the reaction was by an acyl transfer from the thioester of C3 to the target hydroxyl group. Later on they showed that C4 also bound covalently to target molecules. By establishing a fluid phase system to study the kinetics of the binding reactions of C3 and C4, Alex was able to continue the work in the MRC Immunochemistry Unit in Oxford from 1981, to eventually determine the chemical mechanism of the binding reaction. In order to give some sense of reality, this article is written as a narrative from Alex, who did the experiments. Both Alex and Paul are retired. Pauls lives on Martha's Vineyard where he writes occasional articles on science for one of the Island's newspapers. Alex lives in Hong Kong and tries to make some sense of the local politics.

Personalized disease signatures through information-theoretic compaction of big cancer data.

Every individual cancer develops and grows in its own specific way, giving rise to a recognized need for the development of personalized cancer diagnostics. This suggested that the identification of patient-specific oncogene markers would be an effective diagnostics approach. However, tumors that are classified as similar according to the expression levels of certain oncogenes can eventually demonstrate divergent responses to treatment. This implies that the information gained from the identification of tumor-specific biomarkers is still not sufficient. We present a method to quantitatively transform heterogeneous big cancer data to patient-specific transcription networks. These networks characterize the unbalanced molecular processes that deviate the tissue from the normal state. We study a number of datasets spanning five different cancer types, aiming to capture the extensive interpatient heterogeneity that exists within a specific cancer type as well as between cancers of different origins. We show that a relatively small number of altered molecular processes suffices to accurately characterize over 500 tumors, showing extreme compaction of the data. Every patient is characterized by a small specific subset of unbalanced processes. We validate the result by verifying that the processes identified characterize other cancer patients as well. We show that different patients may display similar oncogene expression levels, albeit carrying biologically distinct tumors that harbor different sets of unbalanced molecular processes. Thus, tumors may be inaccurately classified and addressed as similar. These findings highlight the need to expand the notion of tumor-specific oncogenic biomarkers to patient-specific, comprehensive transcriptional networks for improved patient-tailored diagnostics.

Patient-derived xenotransplants can recapitulate the genetic driver landscape of acute leukemias.

Genomic studies have identified recurrent somatic mutations in acute leukemias. However, current murine models do not sufficiently encompass the genomic complexity of human leukemias. To develop preclinical models, we transplanted 160 samples from patients with acute leukemia (acute myeloid leukemia, mixed lineage leukemia, B-cell acute lymphoblastic leukemia, T-cell ALL) into immunodeficient mice. Of these, 119 engrafted with expected immunophenotype. Targeted sequencing of 374 genes and 265 frequently rearranged RNAs detected recurrent and novel genetic lesions in 48 paired primary tumor (PT) and patient-derived xenotransplant (PDX) samples. Overall, the frequencies of 274 somatic variant alleles correlated between PT and PDX samples, although the data were highly variable for variant alleles present at 0-10%. Seventeen percent of variant alleles were detected in either PT or PDX samples only. Based on variant allele frequency changes, 24 PT-PDX pairs were classified as concordant while the other 24 pairs showed various degree of clonal discordance. There was no correlation of clonal concordance with clinical parameters of diseases. Significantly more bone marrow samples than peripheral blood samples engrafted discordantly. These data demonstrate the utility of developing PDX banks for modeling human leukemia, and emphasize the importance of genomic profiling of PDX and patient samples to ensure concordance before performing mechanistic or therapeutic studies.

Intercellular signaling through secreted proteins induces free-energy gradient-directed cell movement.

Controlling cell migration is important in tissue engineering and medicine. Cell motility depends on factors such as nutrient concentration gradients and soluble factor signaling. In particular, cell-cell signaling can depend on cell-cell separation distance and can influence cellular arrangements in bulk cultures. Here, we seek a physical-based approach, which identifies a potential governed by cell-cell signaling that induces a directed cell-cell motion. A single-cell barcode chip (SCBC) was used to experimentally interrogate secreted proteins in hundreds of isolated glioblastoma brain cancer cell pairs and to monitor their relative motions over time. We used these trajectories to identify a range of cell-cell separation distances where the signaling was most stable. We then used a thermodynamics-motivated analysis of secreted protein levels to characterize free-energy changes for different cell-cell distances. We show that glioblastoma cell-cell movement can be described as Brownian motion biased by cell-cell potential. To demonstrate that the free-energy potential as determined by the signaling is the driver of motion, we inhibited two proteins most involved in maintaining the free-energy gradient. Following inhibition, cell pairs showed an essentially random Brownian motion, similar to the case for untreated, isolated single cells.

A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes.

We describe a thermodynamic-motivated, information theoretic analysis of proteomic data collected from a series of 8 glioblastoma multiforme (GBM) tumors. GBMs are considered here as prototypes of heterogeneous cancers. That heterogeneity is viewed here as manifesting in different unbalanced biological processes that are associated with thermodynamic-like constraints. The analysis yields a molecular description of a stable steady state that is common across all tumors. It also resolves molecular descriptions of unbalanced processes that are shared by several tumors, such as hyperactivated phosphoprotein signaling networks. Further, it resolves unbalanced processes that provide unique classifiers of tumor subgroups. The results of the theoretical interpretation are compared against those of statistical multivariate methods and are shown to provide a superior level of resolution for identifying unbalanced processes in GBM tumors. The identification of specific constraints for each GBM tumor suggests tumor-specific combination therapies that may reverse this imbalance.

Dnmt3a regulates myeloproliferation and liver-specific expansion of hematopoietic stem and progenitor cells.

DNA methyltransferase 3A (DNMT3A) mutations are observed in myeloid malignancies, including myeloproliferative neoplasms (MPN), myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). Transplantation studies have elucidated an important role for Dnmt3a in stem cell self-renewal and in myeloid differentiation. Here, we investigated the impact of conditional hematopoietic Dnmt3a loss on disease phenotype in primary mice. Mx1-Cre-mediated Dnmt3a ablation led to the development of a lethal, fully penetrant MPN with myelodysplasia (MDS/MPN) characterized by peripheral cytopenias and by marked, progressive hepatomegaly. We detected expanded stem/progenitor populations in the liver of Dnmt3a-ablated mice. The MDS/MPN induced by Dnmt3a ablation was transplantable, including the marked hepatomegaly. Homing studies showed that Dnmt3a-deleted bone marrow cells preferentially migrated to the liver. Gene expression and DNA methylation analyses of progenitor cell populations identified differential regulation of hematopoietic regulatory pathways, including fetal liver hematopoiesis transcriptional programs. These data demonstrate that Dnmt3a ablation in the hematopoietic system leads to myeloid transformation in vivo, with cell-autonomous aberrant tissue tropism and marked extramedullary hematopoiesis (EMH) with liver involvement. Hence, in addition to the established role of Dnmt3a in regulating self-renewal, Dnmt3a regulates tissue tropism and limits myeloid progenitor expansion in vivo.

Statistical thermodynamics of transcription profiles in normal development and tumorigeneses in cohorts of patients.

Experimental biology is providing the distribution of numerous different biological molecules inside cells and in body fluids of patients. Statistical methods of analysis have very successfully examined these rather large databases. We seek to use a thermodynamic analysis to provide a physical understanding and quantitative characterization of human cancers and other pathologies within a molecule-centered approach. The key technical development is the introduction of a Lagrangian. By imposing constraints the minimal value of the Lagrangian defines a thermodynamically stable state of the cellular system. The minimization also allows using experimental data measured at a number of different conditions to evaluate the steady-state distribution of biomolecules such as messenger RNAs. Thereby the number of effectively accessible quantum states of biomolecules is determined from the experimentally measured expression levels. With the increased resolution provided by the minimization of the Lagrangian one can differentiate between normal and diseased patients and further between disease subtypes. Each such refinement corresponds to imposing an additional constraint of biological origin. The constraints are the unbalanced ongoing biological processes in the system. MicroRNA expression level data for control and diseased lung cancer patients are analyzed as an example.

Mutated Ptpn11 alters leukemic stem cell frequency and reduces the sensitivity of acute myeloid leukemia cells to Mcl1 inhibition.

PTPN11 encodes the Shp2 non-receptor protein-tyrosine phosphatase implicated in several signaling pathways. Activating mutations in Shp2 are commonly associated with juvenile myelomonocytic leukemia but are not as well defined in other neoplasms. Here we report that Shp2 mutations occur in human acute myeloid leukemia (AML) at a rate of 6.6% (6/91) in the ECOG E1900 data set. We examined the role of mutated Shp2 in leukemias harboring MLL translocations, which co-occur in human AML. The hyperactive Shp2E76K mutant, commonly observed in leukemia patients, significantly accelerated MLL-AF9-mediated leukemogenesis in vivo. Shp2E76K increased leukemic stem cell frequency and affords MLL-AF9 leukemic cells IL3 cytokine hypersensitivity. As Shp2 is reported to regulate anti-apoptotic genes, we investigated Bcl2, Bcl-xL and Mcl1 expression in MLL-AF9 leukemic cells with and without Shp2E76K. Although the Bcl2 family of genes was upregulated in Shp2E76K cells, Mcl1 showed the highest upregulation in MLL-AF9 cells in response to Shp2E76K. Indeed, expression of Mcl1 in MLL-AF9 cells phenocopies expression of Shp2E76K, suggesting Shp2 mutations cooperate through activation of anti-apoptotic genes. Finally, we show Shp2E76K mutations reduce sensitivity of AML cells to small-molecule-mediated Mcl1 inhibition, suggesting reduced efficacy of drugs targeting MCL1 in patients with hyperactive Shp2.

Computational surprisal analysis speeds-up genomic characterization of cancer processes.

Surprisal analysis is increasingly being applied for the examination of transcription levels in cellular processes, towards revealing inner network structures and predicting response. But to achieve its full potential, surprisal analysis should be integrated into a wider range computational tool. The purposes of this paper are to combine surprisal analysis with other important computation procedures, such as easy manipulation of the analysis results--e.g. to choose desirable result sub-sets for further inspection--, retrieval and comparison with relevant datasets from public databases, and flexible graphical displays for heuristic thinking. The whole set of computation procedures integrated into a single practical tool is what we call Computational Surprisal Analysis. This combined kind of analysis should facilitate significantly quantitative understanding of different cellular processes for researchers, including applications in proteomics and metabolomics. Beyond that, our vision is that Computational Surprisal Analysis has the potential to reach the status of a routine method of analysis for practitioners. The resolving power of Computational Surprisal Analysis is here demonstrated by its application to a variety of cellular cancer process transcription datasets, ours and from the literature. The results provide a compact biological picture of the thermodynamic significance of the leading gene expression phenotypes in every stage of the disease. For each transcript we characterize both its inherent steady state weight, its correlation with the other transcripts and its variation due to the disease. We present a dedicated website to facilitate the analysis for researchers and practitioners.

Surprisal analysis characterizes the free energy time course of cancer cells undergoing epithelial-to-mesenchymal transition.

The epithelial-to-mesenchymal transition (EMT) initiates the invasive and metastatic behavior of many epithelial cancers. Mechanisms underlying EMT are not fully known. Surprisal analysis of mRNA time course data from lung and pancreatic cancer cells stimulated to undergo TGF-ß1-induced EMT identifies two phenotypes. Examination of the time course for these phenotypes reveals that EMT reprogramming is a multistep process characterized by initiation, maturation, and stabilization stages that correlate with changes in cell metabolism. Surprisal analysis characterizes the free energy time course of the expression levels throughout the transition in terms of two state variables. The landscape of the free energy changes during the EMT for the lung cancer cells shows a stable intermediate state. Existing data suggest this is the previously proposed maturation stage. Using a single-cell ATP assay, we demonstrate that the TGF-ß1-induced EMT for lung cancer cells, particularly during the maturation stage, coincides with a metabolic shift resulting in increased cytosolic ATP levels. Surprisal analysis also characterizes the absolute expression levels of the mRNAs and thereby examines the homeostasis of the transcription system during EMT.

Glioblastoma cellular architectures are predicted through the characterization of two-cell interactions.

To understand how pairwise cellular interactions influence cellular architectures, we measured the levels of functional proteins associated with EGF receptor (EGFR) signaling in pairs of U87EGFR variant III oncogene receptor cells (U87EGFRvIII) at varying cell separations. Using a thermodynamics-derived approach we analyzed the cell-separation dependence of the signaling stability, and identified that the stable steady state of EGFR signaling exists when two U87EGFRvIII cells are separated by 80-100 µm. This distance range was verified as the characteristic intercellular separation within bulk cell cultures. EGFR protein network signaling coordination for the U87EGFRvIII system was lowest at the stable state and most similar to isolated cell signaling. Measurements of cultures of less tumorigenic U87PTEN cells were then used to correctly predict that stable EGFR signaling occurs for those cells at smaller cell-cell separations. The intimate relationship between functional protein levels and cellular architectures explains the scattered nature of U87EGFRvIII cells relative to U87PTEN cells in glioblastoma multiforme tumors.

Valvular dystrophy associated filamin A mutations reveal a new role of its first repeats in small-GTPase regulation.

Filamin A (FlnA) is a ubiquitous actin binding protein which anchors various transmembrane proteins to the cell cytoskeleton and provides a scaffold to many cytoplasmic signaling proteins involved in actin cytoskeleton remodeling in response to mechanical stress and cytokines stimulation. Although the vast majority of FlnA binding partners interact with the carboxy-terminal immunoglobulin like (Igl) repeats of FlnA, little is known on the role of the amino-N-terminal repeats. Here, using cardiac mitral valvular dystrophy associated FlnA-G288R and P637Q mutations located in the N-terminal Igl repeat 1 and 4 respectively as a model, we identified a new role of FlnA N-terminal repeats in small Rho-GTPases regulation. Using FlnA-deficient melanoma and HT1080 cell lines as expression systems we showed that FlnA mutations reduce cell spreading and migration capacities. Furthermore, we defined a signaling network in which FlnA mutations alter the balance between RhoA and Rac1 GTPases activities in favor of RhoA and provided evidences for a role of the Rac1 specific GTPase activating protein FilGAP in this process. Together our work ascribed a new role to the N-terminal repeats of FlnA in Small GTPases regulation and supports a conceptual framework for the role of FlnA mutations in cardiac valve diseases centered around signaling molecules regulating cellular actin cytoskeleton in response to mechanical stress.

miRNA and mRNA cancer signatures determined by analysis of expression levels in large cohorts of patients.

Toward identifying a cancer-specific gene signature we applied surprisal analysis to the RNAs expression behavior for a large cohort of breast, lung, ovarian, and prostate carcinoma patients. We characterize the cancer phenotypic state as a shared response of a set of mRNA or microRNAs (miRNAs) in cancer patients versus noncancer controls. The resulting signature is robust with respect to individual patient variability and distinguishes with high fidelity between cancer and noncancer patients. The mRNAs and miRNAs that are implicated in the signature are correlated and are known to contribute to the regulation of cancer-signaling pathways. The miRNA and mRNA networks are common to the noncancer and cancer patients, but the disease modulates the strength of the connectivities. Furthermore, we experimentally assessed the cancer-specific signatures as possible therapeutic targets. Specifically we restructured a single dominant connectivity in the cancer-specific gene network in vitro. We find a deflection from the cancer phenotype, significantly reducing cancer cell proliferation and altering cancer cellular physiology. Our approach is grounded in thermodynamics augmented by information theory. The thermodynamic reasoning is demonstrated to ensure that the derived signature is bias-free and shows that the most significant redistribution of free energy occurs in programming a system between the noncancer and cancer states. This paper introduces a platform that can elucidate miRNA and mRNA behavior on a systems level and provides a comprehensive systematic view of both the energetics of the expression levels of RNAs and of their changes during tumorigenicity.

AKT is a therapeutic target in myeloproliferative neoplasms.

The majority of patients with BCR-ABL1-negative myeloproliferative neoplasms (MPN) harbor mutations in JAK2 or MPL, which lead to constitutive activation of the JAK/STAT, PI3K and ERK signaling pathways. JAK inhibitors by themselves are inadequate in producing selective clonal suppression in MPN and are associated with hematopoietic toxicities. MK-2206 is a potent allosteric AKT inhibitor that was well tolerated, including no evidence of myelosuppression, in a phase I study of solid tumors. Herein, we show that inhibition of PI3K/AKT signaling by MK-2206 affected the growth of both JAK2V617F- or MPLW515L-expressing cells via reduced phosphorylation of AKT and inhibition of its downstream signaling molecules. Moreover, we demonstrate that MK-2206 synergizes with ruxolitinib in suppressing the growth of JAK2V617F-mutant SET2 cells. Importantly, MK-2206 suppressed colony formation from hematopoietic progenitor cells in patients with primary myelofibrosis and alleviated hepatosplenomegaly and reduced megakaryocyte burden in the bone marrows, livers and spleens of mice with MPLW515L-induced MPN. Together, these findings establish AKT as a rational therapeutic target in the MPNs.