Synergistic and antagonistic effects of deterministic and stochastic cell-cell variations.

By diversifying, cells in a clonal population can together overcome the limits of individuals. Diversity in single-cell growth rates allows the population to survive environmental stresses, such as antibiotics, and grow faster than the undiversified population. These functional cell-cell variations can arise stochastically, from noise in biochemical reactions, or deterministically, by asymmetrically distributing damaged components. While each of the mechanisms is well understood, the effect of the combined mechanisms is unclear. To evaluate the contribution of the deterministic component we developed a mathematical model by mapping the growing population to the Ising model. To analyze the combined effects of stochastic and deterministic contributions we introduced the analytical results of the Ising-mapping into an Euler-Lotka framework. Model results, confirmed by simulations and experimental data, show that deterministic cell-cell variations increase near-linearly with stress. As a consequence, we predict that the gain in population doubling time from cell-cell variations is primarily stochastic at low stress but may cross over to deterministic at higher stresses. Furthermore, we find that while the deterministic component minimizes population damage, stochastic variations antagonize this effect. Together our results may help identifying stress-tolerant pathogenic cells and thus inspire novel antibiotic strategies.

Changes in the immune landscape of TNBC after neoadjuvant chemotherapy: correlation with relapse.

Introduction: Patients with high-risk, triple negative breast cancer (TNBC) often receive neoadjuvant chemotherapy (NAC) alone or with immunotherapy. Various single-cell and spatially resolved techniques have demonstrated heterogeneity in the phenotype and distribution of macrophages and T cells in this form of breast cancer. Furthermore, recent studies in mice have implicated immune cells in perivascular (PV) areas of tumors in the regulation of metastasis and anti-tumor immunity. However, little is known of how the latter change during NAC in human TNBC or their impact on subsequent relapse, or the likely efficacy of immunotherapy given with or after NAC. Methods: We have used multiplex immunofluorescence and AI-based image analysis to compare the immune landscape in untreated and NAC-treated human TNBCs. We quantified changes in the phenotype, distribution and intercellular contacts of subsets of tumor-associated macrophages (TAMs), CD4+ and CD8+ T cells, and regulatory T cells (Tregs) in PV and non-PV various areas of the stroma and tumor cell islands. These were compared in tumors from patients who had either developed metastases or were disease-free (DF) after a three-year follow up period. Results: In tumors from patients who remained DF after NAC, there was a marked increase in stromal CD163+ TAMs, especially those expressing the negative checkpoint regulator, T-cell immunoglobulin and mucin domain 3 (TIM-3). Whereas CD4+ T cells preferentially located to PV areas in the stroma of both untreated and NAC-treated tumors, specific subsets of TAMs and Tregs only did so only after NAC. Distinct subsets of CD4+ and CD8+ T cells formed PV clusters with CD163+ TAMs and Tregs. These were retained after NAC. Discussion: Quantification of stromal TIM-3+CD163+ TAMs in tumor residues after NAC may represent a new way of identifying patients at high risk of relapse. PV clustering of immune cells is highly likely to regulate the activation and function of T cells, and thus the efficacy of T cell-based immunotherapies administered with or after NAC.

Genetic Subtyping and Phenotypic Characterization of the Immune Microenvironment and MYC/BCL2 Double Expression Reveal Heterogeneity in Diffuse Large B-cell Lymphoma.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors. RESULTS: We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1-high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases. CONCLUSIONS: Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

Genomic complexity is associated with epigenetic regulator mutations and poor prognosis in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma with high mutation burdens but a low response rate to immune checkpoint inhibitors. In this study, we performed targeted next-generation sequencing and fluorescent multiplex immunohistochemistry, and investigated the clinical significance and immunological effect of mutation numbers in 424 DLBCL patients treated with standard immunochemotherapy. We found that KMT2D and TP53 nonsynonymous mutations (MUT) were significantly associated with increased nonsynonymous mutation numbers, and that high mutation numbers (MUThigh) were associated with significantly poorer clinical outcome in germinal center B-cell-like DLBCL with wild-type TP53. To understand the underlying mechanisms, we identified a gene-expression profiling signature and the association of MUThigh with decreased T cells in DLBCL patients with wild-type TP53. On the other hand, in overall cohort, MUThigh was associated with lower PD-1 expression in T cells and PD-L1 expression in macrophages, suggesting a positive role of MUThigh in immune responses. Analysis in a whole-exome sequencing dataset of 304 patients deposited by Chapuy et al. validated the correlation of MUT-KMT2D with genomic complexity and the significantly poorer survival associated with higher numbers of genomic single nucleotide variants in activated B-cell-like DLBCL with wild-type TP53. Together, these results suggest that KMT2D inactivation or epigenetic dysregulation has a role in driving DLBCL genomic instability, and that genomic complexity has adverse impact on clinical outcome in DLBCL patients with wild-type TP53 treated with standard immunochemotherapy. The oncoimmune data in this study have important implications for biomarker and therapeutic studies in DLBCL.

Signaling pathways as linear transmitters.

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfß pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior.

Two-Element Transcriptional Regulation in the Canonical Wnt Pathway.

The canonical Wnt pathway regulates numerous fundamental processes throughout development and adult physiology and is often disrupted in diseases [1-4]. Signal in the pathway is transduced by ß-catenin, which in complex with Tcf/Lef regulates transcription. Despite the many processes that the Wnt pathway governs, ß-catenin acts primarily on a single cis element in the DNA, the Wnt-responsive element (WRE), at times potentiated by a nearby Helper site. In this study, working with Xenopus, mouse, and human systems, we identified a cis element, distinct from WRE, upon which ß-catenin and Tcf act. The element is 11 bp long, hundreds of bases apart from the WRE, and exhibits a suppressive effect. In Xenopus patterning, loss of the 11-bp negative regulatory elements (11-bp NREs) broadened dorsal expression of siamois. In mouse embryonic stem cells, genomic deletion of the 11-bp NREs in the promoter elevated Brachyury expression. This reveals a previously unappreciated mechanism within the Wnt pathway, where gene response is not only driven by WREs but also tuned by 11-bp NREs. Using electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP), we found evidence for the NREs binding to ß-catenin and Tcf-suggesting a dual action by ß-catenin as a signal and a feedforward sensor. Analyzing ß-catenin ChIP sequencing in human cells, we found the 11-bp NREs co-localizing with the WRE in 45%-71% of the peaks, suggesting a widespread role for the mechanism. This study presents an example of a more complex cis regulation by a signaling pathway, where a signal is processed through two distinct cis elements in a gene circuitry.

Sensing relative signal in the Tgf-ß/Smad pathway.

How signaling pathways function reliably despite cellular variation remains a question in many systems. In the transforming growth factor-ß (Tgf-ß) pathway, exposure to ligand stimulates nuclear localization of Smad proteins, which then regulate target gene expression. Examining Smad3 dynamics in live reporter cells, we found evidence for fold-change detection. Although the level of nuclear Smad3 varied across cells, the fold change in the level of nuclear Smad3 was a more precise outcome of ligand stimulation. The precision of the fold-change response was observed throughout the signaling duration and across Tgf-ß doses, and significantly increased the information transduction capacity of the pathway. Using single-molecule FISH, we further observed that expression of Smad3 target genes (ctgf, snai1, and wnt9a) correlated more strongly with the fold change, rather than the level, of nuclear Smad3. These findings suggest that some target genes sense Smad3 level relative to background, as a strategy for coping with cellular noise.

Asymmetric Damage Segregation Constitutes an Emergent Population-Level Stress Response.

Asymmetric damage segregation (ADS) is a mechanism for increasing population fitness through non-random, asymmetric partitioning of damaged macromolecules at cell division. ADS has been reported across multiple organisms, though the measured effects on fitness of individuals are often small. Here, we introduce a cell-lineage-based framework that quantifies the population-wide effects of ADS and then verify our results experimentally in E. coli under heat and antibiotic stress. Using an experimentally validated mathematical model, we find that the beneficial effect of ADS increases with stress. In effect, low-damage subpopulations divide faster and amplify within the population acting like a positive feedback loop whose strength scales with stress. Analysis of protein aggregates shows that the degree of asymmetric inheritance is damage dependent in single cells. Together our results indicate that, despite small effects in single cell, ADS exerts a strong beneficial effect on the population level and arises from the redistribution of damage within a population, through both single-cell and population-level feedback.