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

Neoplastic transformation of porcine mammary epithelial cells in vitro and tumor formation in vivo.

BackgroundThe mammary glands of pigs share many functional and morphological similarities with the breasts of humans, raising the potential of their utility for research into the mechanisms underlying normal mammary function and breast carcinogenesis. Here we sought to establish a model for the efficient manipulation and transformation of porcine mammary epithelial cells (pMEC) in vitro and tumor growth in vivo.MethodsWe utilized a vector encoding the red florescent protein tdTomato to transduce populations of pMEC from Yorkshire -Hampshire crossbred female pigs in vitro and in vivo. Populations of primary pMEC were then separated by FACS using markers to distinguish epithelial cells (CD140a-) from stromal cells (CD140a+), with or without further enrichment for basal and luminal progenitor cells (CD49f+). These separated pMEC populations were transduced by lentivirus encoding murine polyomavirus T antigens (Tag) and tdTomato and engrafted to orthotopic or ectopic sites in immunodeficient NOD.Cg-Prkdc (scid) Il2rg (tm1Wjl) /SzJ (NSG) mice.ResultsWe demonstrated that lentivirus effectively transduces pMEC in vitro and in vivo. We further established that lentivirus can be used for oncogenic-transformation of pMEC ex vivo for generating mammary tumors in vivo. Oncogenic transformation was confirmed in vitro by anchorage-independent growth, increased cell proliferation, and expression of CDKN2A, cyclin A2 and p53 alongside decreased phosphorylation of Rb. Moreover, Tag-transformed CD140a- and CD140a-CD49f + pMECs developed site-specific tumors of differing histopathologies in vivo.ConclusionsHerein we establish a model for the transduction and oncogenic transformation of pMEC. This is the first report describing a porcine model of mammary epithelial cell tumorigenesis that can be applied to the study of human breast cancers

MolBioLib: A C++11 Framework for Rapid Development and Deployment of Bioinformatics Tasks

Summary: We developed MolBioLib to address the need for adaptable next-generation sequencing analysis tools. The result is a compact, portable and extensively tested C++11 software framework and set of applications tailored to the demands of next-generation sequencing data and applicable to many other applications. MolBioLib is designed to work with common file formats and data types used both in genomic analysis and general data analysis. A central relational-database-like Table class is a flexible and powerful object to intuitively represent and work with a wide variety of tabular datasets, ranging from alignment data to annotations. MolBioLib has been used to identify causative single-nucleotide polymorphisms in whole genome sequencing, detect balanced chromosomal rearrangements and compute enrichment of messenger RNAs (mRNAs) on microtubules, typically requiring applications of under 200 lines of code. MolBioLib includes programs to perform a wide variety of analysis tasks, such as computing read coverage, annotating genomic intervals and novel peak calling with a wavelet algorithm. Although MolBioLib was designed primarily for bioinformatics purposes, much of its functionality is applicable to a wide range of problems. Complete documentation and an extensive automated test suite are provided

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

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

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

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