Relating L-Resilience and Wait-Freedom via Hitting Sets

The condition of t-resilience stipulates that an n-process program is only obliged to make progress when at least n-t processes are correct. Put another way, the live sets, the collection of process sets such that progress is required if all the processes in one of these sets are correct, are all sets with at least n-t processes. We show that the ability of arbitrary collection of live sets L to solve distributed tasks is tightly related to the minimum hitting set of L, a minimum cardinality subset of processes that has a non-empty intersection with every live set. Thus, finding the computing power of L is NP-complete. For the special case of colorless tasks that allow participating processes to adopt input or output values of each other, we use a simple simulation to show that a task can be solved L-resiliently if and only if it can be solved (h-1)-resiliently, where h is the size of the minimum hitting set of L. For general tasks, we characterize L-resilient solvability of tasks with respect to a limited notion of weak solvability: in every execution where all processes in some set in L are correct, outputs must be produced for every process in some (possibly different) participating set in L. Given a task T, we construct another task T_L such that T is solvable weakly L-resiliently if and only if T_L is solvable weakly wait-free

Strong Equivalence Relations for Iterated Models

The Iterated Immediate Snapshot model (IIS), due to its elegant geometrical representation, has become standard for applying topological reasoning to distributed computing. Its modular structure makes it easier to analyze than the more realistic (non-iterated) read-write Atomic-Snapshot memory model (AS). It is known that AS and IIS are equivalent with respect to \emph{wait-free task} computability: a distributed task is solvable in AS if and only if it solvable in IIS. We observe, however, that this equivalence is not sufficient in order to explore solvability of tasks in \emph{sub-models} of AS (i.e. proper subsets of its runs) or computability of \emph{long-lived} objects, and a stronger equivalence relation is needed. In this paper, we consider \emph{adversarial} sub-models of AS and IIS specified by the sets of processes that can be \emph{correct} in a model run. We show that AS and IIS are equivalent in a strong way: a (possibly long-lived) object is implementable in AS under a given adversary if and only if it is implementable in IIS under the same adversary. %This holds whether the object is one-shot or long-lived. Therefore, the computability of any object in shared memory under an adversarial AS scheduler can be equivalently investigated in IIS

Changes in epithelial proportions and transcriptional state underlie major premenopausal breast cancer risks

The human breast undergoes lifelong remodeling in response to estrogen and progesterone, but hormone exposure also increases breast cancer risk. Here, we use single-cell analysis to identify distinct mechanisms through which breast composition and cell state affect hormone signaling. We show that prior pregnancy reduces the transcriptional response of hormone-responsive (HR+) epithelial cells, whereas high body mass index (BMI) reduces overall HR+ cell proportions. These distinct changes both impact neighboring cells by effectively reducing the magnitude of paracrine signals originating from HR+ cells. Because pregnancy and high BMI are known to protect against hormone-dependent breast cancer in premenopausal women, our findings directly link breast cancer risk with person-to-person heterogeneity in hormone responsiveness. More broadly, our findings illustrate how cell proportions and cell state can collectively impact cell communities through the action of cell-to-cell signaling networks

Distinct immune signatures in directly treated and distant tumors result from TLR adjuvants and focal ablation.

Both adjuvants and focal ablation can alter the local innate immune system and trigger a highly effective systemic response. Our goal is to determine the impact of these treatments on directly treated and distant disease and the mechanisms for the enhanced response obtained by combinatorial treatments. Methods: We combined RNA-sequencing, flow cytometry and TCR-sequencing to dissect the impact of immunotherapy and of immunotherapy combined with ablation on local and systemic immune components. Results: With administration of a toll-like receptor agonist agonist (CpG) alone or CpG combined with same-site ablation, we found dramatic differences between the local and distant tumor environments, where the directly treated tumors were skewed to high expression of F4/80, Cd11b and Tnf and the distant tumors to enhanced Cd11c, Cd3 and Ifng. When ablation was added to immunotherapy, 100% (n=20/20) of directly treated tumors and 90% (n=18/20) of distant tumors were responsive. Comparing the combined ablation-immunotherapy treatment to immunotherapy alone, we find three major mechanistic differences. First, while ablation alone enhanced intratumoral antigen cross-presentation (up to ~8% of CD45+ cells), systemic cross-presentation of tumor antigen remained low. Combining same-site ablation with CpG amplified cross-presentation in the draining lymph node (~16% of CD45+ cells) compared to the ablation-only (~0.1% of CD45+ cells) and immunotherapy-only cohorts (~10% of CD45+ cells). Macrophages and DCs process and present this antigen to CD8+ T-cells, increasing the number of unique T-cell receptor rearrangements in distant tumors. Second, type I interferon (IFN) release from tumor cells increased with the ablation-immunotherapy treatment as compared with ablation or immunotherapy alone. Type I IFN release is synergistic with toll-like receptor activation in enhancing cytokine and chemokine expression. Expression of genes associated with T-cell activation and stimulation (Eomes, Prf1 and Icos) was 27, 56 and 89-fold higher with ablation-immunotherapy treatment as compared to the no-treatment controls (and 12, 32 and 60-fold higher for immunotherapy-only treatment as compared to the no-treatment controls). Third, we found that the ablation-immunotherapy treatment polarized macrophages and dendritic cells towards a CD169 subset systemically, where CD169+ macrophages are an IFN-enhanced subpopulation associated with dead-cell antigen presentation. Conclusion: While the local and distant responses are distinct, CpG combined with ablative focal therapy drives a highly effective systemic immune response

Multiplexed Illumina sequencing libraries from picogram quantities of DNA

Background: High throughput sequencing is frequently used to discover the location of regulatory interactions on chromatin. However, techniques that enrich DNA where regulatory activity takes place, such as chromatin immunoprecipitation (ChIP), often yield less DNA than optimal for sequencing library preparation. Existing protocols for picogram-scale libraries require concomitant fragmentation of DNA, pre-amplification, or long overnight steps. Results: We report a simple and fast library construction method that produces libraries from sub-nanogram quantities of DNA. This protocol yields conventional libraries with barcodes suitable for multiplexed sample analysis on the Illumina platform. We demonstrate the utility of this method by constructing a ChIP-seq library from 100 pg of ChIP DNA that demonstrates equivalent genomic coverage of target regions to a library produced from a larger scale experiment. Conclusions: Application of this method allows whole genome studies from samples where material or yields are limiting

Satb1 overexpression drives tumor-promoting activities in cancer-associated dendritic cells

Special AT-rich sequence-binding protein 1 (Satb1) governs genome-wide transcriptional programs. Using a conditional knockout mouse, we find that Satb1 is required for normal differentiation of conventional dendritic cells (DCs). Furthermore, Satb1 governs the differentiation of inflammatory DCs by regulating major histocompatibility complex class II (MHC II) expression through Notch1 signaling. Mechanistically, Satb1 binds to the Notch1 promoter, activating Notch expression and driving RBPJ occupancy of the H2-Ab1 promoter, which activates MHC II transcription. However, tumor-driven, unremitting expression of Satb1 in activated Zbtb46(+) inflammatory DCs that infiltrate ovarian tumors results in an immunosuppressive phenotype characterized by increased secretion of tumor-promoting Galectin-1 and IL-6. In vivo silencing of Satb1 in tumor-associated DCs reverses their tumorigenic activity and boosts protective immunity. Therefore, dynamic fluctuations in Satb1 expression govern the generation and immunostimulatory activity of steady-state and inflammatory DCs, but continuous Satb1 overexpression in differentiated DCs converts them into tolerogenic/pro-inflammatory cells that contribute to malignant progression.Fil: Tesone, Amelia J.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Rutkowski, Melanie R.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Brencicova, Eva. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Svoronos, Nikolaos. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Perales Puchal, Alfredo. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Stephen, Tom L.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Allegrezza, Michael J.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Payne, Kyle K.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Nguyen, Jenny M.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados UnidosFil: Wickramasinghe, Jayamanna. The Wistar Institute. Center for Systems and Computational Biology; Estados UnidosFil: Tchou, Julia. University of Pennsylvania; Estados UnidosFil: Borowsky, Mark E.. Christiana Care Health System. Helen F. Graham Cancer Center; Estados UnidosFil: Rabinovich, Gabriel Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Kossenkov, Andrew V.. The Wistar Institute. Center for Systems and Computational Biology; Estados UnidosFil: Conejo Garcia, José R.. The Wistar Institute. Tumor Microenvironment and Metastasis Program; Estados Unido

Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders' titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was "intersections between informatics, data science, and population science." We conclude with a discussion on "hot topics" on the horizon for cancer informatics

Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

Cryptic pockets expand the scope of drug discovery by enabling targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. However, identifying cryptic pockets is labor-intensive and slow. The ability to accurately and rapidly predict if and where cryptic pockets are likely to form from a structure would greatly accelerate the search for druggable pockets. Here, we present PocketMiner, a graph neural network trained to predict where pockets are likely to open in molecular dynamics simulations. Applying PocketMiner to single structures from a newly curated dataset of 39 experimentally confirmed cryptic pockets demonstrates that it accurately identifies cryptic pockets (ROC-AUC: 0.87) \u3e1,000-fold faster than existing methods. We apply PocketMiner across the human proteome and show that predicted pockets open in simulations, suggesting that over half of proteins thought to lack pockets based on available structures likely contain cryptic pockets, vastly expanding the potentially druggable proteome

ROR-γ drives androgen receptor expression and represents a therapeutic target in castration-resistant prostate cancer.

The androgen receptor (AR) is overexpressed and hyperactivated in human castration-resistant prostate cancer (CRPC). However, the determinants of AR overexpression in CRPC are poorly defined. Here we show that retinoic acid receptor-related orphan receptor γ (ROR-γ) is overexpressed and amplified in metastatic CRPC tumors, and that ROR-γ drives AR expression in the tumors. ROR-γ recruits nuclear receptor coactivator 1 and 3 (NCOA1 and NCOA3, also known as SRC-1 and SRC-3) to an AR-ROR response element (RORE) to stimulate AR gene transcription. ROR-γ antagonists suppress the expression of both AR and its variant AR-V7 in prostate cancer (PCa) cell lines and tumors. ROR-γ antagonists also markedly diminish genome-wide AR binding, H3K27ac abundance and expression of the AR target gene network. Finally, ROR-γ antagonists suppressed tumor growth in multiple AR-expressing, but not AR-negative, xenograft PCa models, and they effectively sensitized CRPC tumors to enzalutamide, without overt toxicity, in mice. Taken together, these results establish ROR-γ as a key player in CRPC by acting upstream of AR and as a potential therapeutic target for advanced PCa