The immunogenomic landscape of resected intrahepatic cholangiocarcinoma.

BACKGROUND AND AIMS: Cholangiocarcinoma (CCA) is a deadly and highly therapy-refractory cancer of the bile ducts, with early results from immune checkpoint blockade trials showing limited responses. Whereas recent molecular assessments have made bulk characterizations of immune profiles and their genomic correlates, spatial assessments may reveal actionable insights. APPROACH AND RESULTS: Here, we have integrated immune checkpoint-directed immunohistochemistry with next-generation sequencing of resected intrahepatic CCA samples from 96 patients. We found that both T-cell and immune checkpoint markers are enriched at the tumor margins compared to the tumor center. Using two approaches, we identify high programmed cell death protein 1 or lymphocyte-activation gene 3 and low CD3/CD4/inducible T-cell costimulator specifically in the tumor center as associated with poor survival. Moreover, loss-of-function BRCA1-associated protein-1 mutations are associated with and cause elevated expression of the immunosuppressive checkpoint marker, B7 homolog 4. CONCLUSIONS: This study provides a foundation on which to rationally improve and tailor immunotherapy approaches for this difficult-to-treat disease.

Physical-chemical mechanisms of pattern formation during gastrulation.

Gastrulation is a fundamental phase during the biological development of most animals when a single layer of identical embryo cells is transformed into a three-layer structure, from which the organs start to develop. Despite a remarkable progress in quantifying the gastrulation processes, molecular mechanisms of these processes remain not well understood. Here we theoretically investigate early spatial patterning in a geometrically confined colony of embryonic stem cells. Using a reaction-diffusion model, a role of Bone-Morphogenetic Protein 4 (BMP4) signaling pathway in gastrulation is specifically analyzed. Our results show that for slow diffusion rates of BMP4 molecules, a new length scale appears, which is independent of the size of the system. This length scale separates the central region of the colony with uniform low concentrations of BMP molecules from the region near the colony edge where the concentration of signaling molecules is elevated. The roles of different components of the signaling pathway are also explained. Theoretical results are consistent with recent in vitro experiments, providing microscopic explanations for some features of early embryonic spatial patterning. Physical-chemical mechanisms of these processes are discussed.

Theoretical analysis of degradation mechanisms in the formation of morphogen gradients.

Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

Fluctuation-driven anisotropic assembly in nanoscale systems.

We demonstrate that the self-assembly of spherical nanoparticles (NPs), grafted isotropically with polymeric ligands, into anisotropic structures is a manifestation of the fluctuations inherent in small number statistics. Computer simulations show that the organization of ligand atoms around an individual NP is not spatially isotropic for small numbers of grafts and ligand monomers. This inherent, spatially asymmetric ligand distribution causes the effective, two-body inter-NP potential to have a strong orientational dependence, which reproduces the anisotropic assembly observed ubiquitously for these systems. In contrast, ignoring this angular dependence does not permit us to capture NP self-assembly. This idea of fluctuation-driven behavior should be broadly relevant, and, for example, it should be important for the assembly of ligand-decorated quantum dots into arrays.

A prognostic matrix gene expression signature defines functional glioblastoma phenotypes and niches.

Background: Interactions among tumor, immune, and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Methods: Here, through computational genomics and proteomics approaches, we analyzed the functional and clinical relevance of CMP expression in GBM at bulk, single cell, and spatial anatomical resolution. Results: We identified genes encoding CMPs whose expression levels categorize GBM tumors into CMP expression-high (M-H) and CMP expression-low (M-L) groups. CMP enrichment is associated with worse patient survival, specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells, and immune checkpoint gene expression. Anatomical and single-cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative niches that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene CMP expression signature, termed Matrisome 17 (M17) signature that further refines the prognostic value of CMP genes. The M17 signature is a significantly stronger prognostic factor compared to MGMT promoter methylation status as well as canonical subtypes, and importantly, potentially predicts responses to PD1 blockade. Conclusion: The matrisome gene expression signature provides a robust stratification of GBM patients by survival and potential biomarkers of functionally relevant GBM niches that can mediate mesenchymal-immune cross talk. Patient stratification based on matrisome profiles can contribute to selection and optimization of treatment strategies.

Mapping the functional interactions at the tumor-immune checkpoint interface.

The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses suggest that CD86-CD70 and CD274-CD70 immunoregulatory interactions are significantly associated with IFNγ expression in uterine corpus endometrial carcinoma and basal-like breast cancer, respectively. The open-source ImogiMap software and user-friendly web application will enable future applications of ImogiMap. Such applications may guide the discovery of previously unknown tumor-immune interactions and immunotherapy targets.

A prognostic matrix code defines functional glioblastoma phenotypes and niches.

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better patient survival, respectively. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles provide potential biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification which could be applied to optimize treatment responses.

A prognostic matrix code defines functional glioblastoma phenotypes and niches.

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a "matrix code" for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better survival, respectively, of patients. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles may provide biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification to optimize treatment responses.

Precision Combination Therapies Based on Recurrent Oncogenic Coalterations.

Cancer cells depend on multiple driver alterations whose oncogenic effects can be suppressed by drug combinations. Here, we provide a comprehensive resource of precision combination therapies tailored to oncogenic coalterations that are recurrent across patient cohorts. To generate the resource, we developed Recurrent Features Leveraged for Combination Therapy (REFLECT), which integrates machine learning and cancer informatics algorithms. Using multiomic data, the method maps recurrent coalteration signatures in patient cohorts to combination therapies. We validated the REFLECT pipeline using data from patient-derived xenografts, in vitro drug screens, and a combination therapy clinical trial. These validations demonstrate that REFLECT-selected combination therapies have significantly improved efficacy, synergy, and survival outcomes. In patient cohorts with immunotherapy response markers, DNA repair aberrations, and HER2 activation, we have identified therapeutically actionable and recurrent coalteration signatures. REFLECT provides a resource and framework to design combination therapies tailored to tumor cohorts in data-driven clinical trials and preclinical studies. SIGNIFICANCE: We developed the predictive bioinformatics platform REFLECT and a multiomics- based precision combination therapy resource. The REFLECT-selected therapies lead to significant improvements in efficacy and patient survival in preclinical and clinical settings. Use of REFLECT can optimize therapeutic benefit through selection of drug combinations tailored to molecular signatures of tumors. See related commentary by Pugh and Haibe-Kains, p. 1416. This article is highlighted in the In This Issue feature, p. 1397.

BET inhibition induces vulnerability to MCL1 targeting through upregulation of fatty acid synthesis pathway in breast cancer.

Therapeutic options for treatment of basal-like breast cancers remain limited. Here, we demonstrate that bromodomain and extra-terminal (BET) inhibition induces an adaptive response leading to MCL1 protein-driven evasion of apoptosis in breast cancer cells. Consequently, co-targeting MCL1 and BET is highly synergistic in breast cancer models. The mechanism of adaptive response to BET inhibition involves the upregulation of lipid synthesis enzymes including the rate-limiting stearoyl-coenzyme A (CoA) desaturase. Changes in lipid synthesis pathway are associated with increases in cell motility and membrane fluidity as well as re-localization and activation of HER2/EGFR. In turn, the HER2/EGFR signaling results in the accumulation of and vulnerability to the inhibition of MCL1. Drug response and genomics analyses reveal that MCL1 copy-number alterations are associated with effective BET and MCL1 co-targeting. The high frequency of MCL1 chromosomal amplifications (>30%) in basal-like breast cancers suggests that BET and MCL1 co-targeting may have therapeutic utility in this aggressive subtype of breast cancer.

Free energy of alternating two-component polymer brushes on cylindrical templates.

We use computer simulations to investigate the stability of a two-component polymer brush de-mixing on a curved template into phases of different morphological properties. It has been previously shown via molecular dynamics simulations that immiscible chains having different length and anchored to a cylindrical template will phase separate into stripes of different widths oriented perpendicularly to the cylindrical axis. We calculate free energy differences for a variety of stripe widths, and extract simple relationships between the sizes of the two polymers, N(1) and N(2), and the free energy dependence on the stripe width. We explain these relationships using simple physical arguments based upon previous theoretical work on the free energy of polymer brushes.

Crystallization of hard aspherical particles.

We use numerical simulations to study the crystallization of monodisperse systems of hard aspherical particles. We find that particle shape and crystallizability can be easily related to each other when particles are characterized in terms of two simple and experimentally accessible order parameters: one based on the particle surface-to-volume ratio and the other on the angular distribution of the perturbations away from the ideal spherical shape. We present a phase diagram obtained by exploring the crystallizability of 487 different particle shapes across the two-order-parameter spectrum. Finally, we consider the physical properties of the crystalline structures accessible to aspherical particles and discuss limits and relevance of our results.

Phase behavior of repulsive polymer-tethered colloids.

We report molecular dynamics simulations of a system of repulsive, polymer-tethered colloidal particles. We use an explicit polymer model to explore how the length and the behavior of the polymer (ideal or self-avoiding) affect the ability of the particles to organize into ordered structures when the system is compressed to moderate volume fractions. We find a variety of different phases whose origin can be explained in terms of the configurational entropy of polymers and colloids. Finally, we discuss and compare our results to those obtained for similar systems using simplified coarse-grained polymer models, and set the limits of their applicability.

A finite-cluster phase in λ-DNA-coated colloids.

We studied the aggregation of 1 µm colloids bridged by DNA with 32 µm contour length. We mixed two species of particles with grafted double-stranded λ-DNA displaying short, complementary single-stranded 'overhangs' as free binding-ends. Confocal microscopy showed the formation of stable, size-limited clusters in which the two species of particles were at touching contact. Simulations suggest that the observed close contact and the limitation to grow both result from entropic exclusion of the bridging DNA from the space between nearby particle surfaces.

Lattice-based Monte Carlo method for telechelic chain molecules.

We present a Monte Carlo (MC) scheme that makes it possible to perform efficient simulations of dense systems of self-avoiding polymers on a lattice. We show that the method is particularly useful to simulate dense systems of polymers with functionalized end groups. We compare the efficiency of the scheme with the configurational bias MC method and indicate the regime where the present approach is the method of choice.

Development of Morphogen Gradients with Spatially Varying Degradation Rates.

Successful biological development via spatial and temporal regulations of cell differentiation relies on the action of multiple signaling molecules that are known as morphogens. It is now well established that biological signaling molecules create nonuniform concentration profiles, called morphogen gradients, that activate different genes, leading to patterning in the developing organisms. The current view of the formation of morphogen gradients is that it is a result of complex reaction-diffusion processes that include production, diffusion, and degradation of signaling molecules. Recent studies also suggest that the degradation of morphogens is a critically important step in the whole process. We develop a theoretical model that allows us to investigate the role of a spatially varying degradation in the formation of morphogen gradients. Our analysis shows that the spatial inhomogeneities in degradation might strongly influence the dynamics of formation of signaling profiles. Physical-chemical mechanisms of the underlying processes are discussed.

Packing of soft asymmetric dumbbells.

We use numerical simulations to study the phase behavior of a system of purely repulsive soft dumbbells as a function of size ratio of the two components and their relative degree of deformability. We find a plethora of different phases, which includes most of the mesophases observed in self-assembly of block copolymers but also crystalline structures formed by asymmetric, hard binary mixtures. Our results detail the phenomenological behavior of these systems when softness is introduced in terms of two different classes of interparticle interactions: (a) the elastic Hertz potential, which has a finite energy cost for complete overlap of any two components, and (b) a generic power-law repulsion with tunable exponent. We discuss how simple geometric arguments can be used to account for the large structural variety observed in these systems and detail the similarities and differences in the phase behavior for the two classes of potentials under consideration.

Liquid-vapor transition driven by bond disorder.

We report grand-canonical Monte Carlo simulations of an equimolar mixture of hard colloids coated with long polymers that have a complementary functionalization. Such systems have the potential to function as self-healing materials. Under conditions where the complementary polymer ends are strongly associated, we observe a first-order vapor-liquid transition from a dilute gas of colloidal dimers to a dense, liquid-like phase. This transition is driven exclusively by the increase in entropy associated with bond disorder-an effect that was predicted theoretically by Zilman et al. [Phys. Rev. Lett. 91, 015901 (2003)10.1103/PhysRevLett.91.015901]. Our simulations rationalize experimental observations by Schmatko et al. [Soft Matter 03 (2007) 703.].

Unexpected relaxation dynamics of a self-avoiding polymer in cylindrical confinement.

We report extensive simulations of the relaxation dynamics of a self-avoiding polymer confined inside a cylindrical pore. In particular, we concentrate on examining how confinement influences the scaling behavior of the global relaxation time of the chain, tau, with the chain length N and pore diameter D. An earlier scaling analysis based on the de Gennes blob picture led to tau approximately N(2)D(13). Our numerical effort that combines molecular dynamics and Monte Carlo simulations, however, consistently produces different tau results for N up to 2000. We argue that the previous scaling prediction is only asymptotically valid in the limit N"D(53)"1, which is currently inaccessible to computer simulations and, more interestingly, is also difficult to reach in experiments. Our results are thus relevant for the interpretation of recent experiments with DNA in nano- and microchannels.