Biology subjects

Ribas, A.

Publications and source records attributed to Ribas, A..

At least 19 recordsLinked to original sources

bioRxiv2026

CytoRipple: Mapping Tissue Polarization through Subcellular Cytoskeleton Dynamics

Spatial multi-omic technologies entail simultaneous measurement of tens-to-thousands of molecular features (e.g. RNA, protein). While cell type and state profiling is the major focus of spatial multi-omic analyses, cytoskeletal proteins are often solely utilized for cell segmentation and quality control. Here, we introduce a new computational framework, CytoRipple, that leverages these concomitant spatially-resolved single-cell measurements of cytoskeleton proteins to identify tissue-level vector fields. Polarization vectors are known to associate with cell movement and phenotype, inferring their physical orientation. We validate these associations across biological contexts and reveal how polarization vector fields can be harnessed to discover multi-cellular structures (e.g. "streams" of cells with similar polarizations). These multi-cellular cytoskeleton dynamics associate with distinct phenomena, such as vector "divergence" with CD8+ T cell activation and "streams" with spatially segmented stages of the anti-tumor immune response. Together, these data support a role for CytoRipple in revealing a dynamic layer across spatial multi-omic platforms.

bioinformatics↗

bioRxiv2026

SpaceBender: Denoising Spatial Transcriptomics Data to Enhance Biological Signals

Spatial transcriptomics (ST) allows for the simultaneous profiling of cell phenotype (e.g. transcriptome) and physical position. Although ST data has brought about numerous new biological insights, it remains limited by noise, largely in the form of RNA diffusion. Here, we introduce SpaceBender which leverages spatial-specific information (e.g. spatial ambient RNA niches) to build upon single-cell denoising strategies. SpaceBender outperforms current ST denoising methods in simulations and in vivo chimeric tissues. Through case studies, we demonstrate how SpaceBender unveils hidden biological insights and increases the significance of said insights as evaluated by statistical testing. Finally, we reveal how SpaceBender may also be applied to subcellular resolution data where it removes off-target expression of neighboring cell type specific marker genes. In all, we present SpaceBender as an ST denoising method, freely available as an open-source package, that may enhance the insights the field may draw from various ST data types.

bioinformatics↗

bioRxiv2025

Whole-Proteome Screening and Multi-Modal Profiling of Antigen-Specific CD4+ T Cells at Single-Cell Resolution

Systematic whole-proteome screening and comprehensive profiling of antigen-specific CD4+ T cells are crucial for advancing our understanding of CD4+ T cell immunity, yet such efforts remain technically challenging. Here, we present a high-throughput platform that employs large-scale class II single-chain trimer libraries to detect antigen-specific CD4+ T cells, while simultaneously profiling their antigen specificity, TCR/{beta} sequences, MHC restriction, whole transcriptomes, and patient/timepoint origins at single-cell resolution. We benchmarked SCTs against conventional pMHCs and validated the SCT library-based approach in direct ex vivo identification of antigen-specific CD4+ T cells in healthy donors. We then applied the platform to screen the entire SARS-CoV-2 receptor-binding domain in a longitudinal patient cohort, identifying 2,188 antigen-specific CD4+ T cells and revealing key features that define antigen immunogenicity. Extending to cancer, we performed whole-proteome screening of HPV-16 E6/E7 for TCR repertoire profiling in a precancerous cohort, uncovering functional heterogeneity of HPV-specific TCRs. By integrating high-throughput antigen screening with high-dimensional, multi-modal cellular characterization, our approach offers an unprecedented window into CD4+ T cell immunity across diverse disease contexts and empowers the development of new therapies.

bioengineering↗

bioRxiv2025

Overcoming myeloid-driven resistance to CAR T therapy by targeting SPP1

Chimeric antigen receptor (CAR) T cell therapy faces notable limitations in treatment of solid tumors. The suppressive tumor microenvironment (TME), characterized by complex interactions among immune and stromal cells, is gaining recognition in conferring resistance to CAR T cell therapy. Despite the abundance and diversity of macrophages in the TME, their intricate involvement in modulating responses to CAR T cell therapies remains poorly understood. Here, we conducted single-cell RNA sequencing (scRNA-seq) on tumors from 41 glioma patients undergoing IL13R2-targeted CAR T cell therapy, identifying elevated suppressive SPP1 signatures predominantly in macrophages from patients who were resistant to treatment. Further integrative scRNA-seq analysis of high-grade gliomas as well as an interferon-signaling deficient syngeneic mouse model--both resistant to CAR T therapy--demonstrated the role of congruent suppressive pathways in mediating resistance to CAR T cells and a dominant role for SPP1+ macrophages. SPP1 blockade with an anti-SPP1 antibody abrogates the suppressive TME effects and substantially prolongs survival in IFN signaling-deficient and glioma syngeneic mouse models resistant to CAR T cell therapy. These findings illuminate the role of SPP1+ macrophages in fueling a suppressive TME and driving solid tumor resistance to CAR cell therapies. Targeting SPP1 may serve as a universal strategy to reprogram immune dynamics in solid tumors mitigating resistance to CAR T cell therapies.

cancer biology↗

bioRxiv2024

A Spatial Omnibus Test (SPOT) for Spatial Proteomic Data

Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripleys K or Besags L, to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific. We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus p-value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to an ovarian cancer study. An R package and tutorial is provided at https://github.com/sarahsamorodnitsky/SPOT.

bioinformatics↗

bioRxiv2022

Clonally-Expanded, Thyrotoxic Autoimmune Mediator CD8+ T cells Driven by IL21 Contribute to Checkpoint Inhibitor Thyroiditis

Autoimmune toxicity occurs in up to 60% of patients treated with immune checkpoint inhibitor (ICI) cancer therapy and is an increasing clinical challenge with the expanding use of these treatments. To date, human immunopathogenic studies of immune related adverse events (IRAEs) have relied upon sampling of circulating peripheral blood cells rather than affected tissues. Here, we directly obtained thyroid specimens from subjects with ICI-thyroiditis, one of the most common IRAEs, and compared immune infiltrates to those from subjects with spontaneous autoimmune Hashimotos thyroiditis (HT) or no thyroid disease. Single cell RNA sequencing revealed a dominant, clonally expanded population of thyroid-infiltrating cytotoxic CXCR6+ CD8+ T cells ("CD8+ autoimmune mediators) present in ICI-thyroiditis, but not HT or healthy controls. Furthermore, we identified a crucial role for interleukin 21, a cytokine secreted by intrathyroidal T follicular (Tfh) and T peripheral helper (Tph) cells, as a driver of these thyrotoxic CD8+ autoimmune mediators. In the presence of IL21, human CD8+ T cells acquired the autoimmune mediator phenotype with upregulation of cytotoxic molecules (IFN{gamma}, granzyme); the chemokine receptor CXCR6; and thyrotoxic capacity. We validated these findings in vivo using a novel mouse model of IRAEs, and further demonstrated that genetic blockade of IL21 signaling protected ICI-treated mice from thyroid immune infiltration. Taken together these studies reveal novel mechanisms and therapeutic targets by which IL21+ Tfh/Tph cells drive thyrotoxic CD8+ autoimmune mediators for the development of IRAEs in humans. One Sentence SummaryScRNAseq reveals a novel role for CD8+ autoimmune mediators and IL21+ T helper cells in the pathogenesis of human checkpoint inhibitor thyroiditis.

immunology↗

bioRxiv2022

Multi-modal single-cell and whole-genome sequencing of minute, frozen specimens to propel clinical applications

Single-cell genomics are enabling technologies, but their broad clinical application remains challenging. We report an easily adaptable approach for single-cell transcriptome and T cell receptor (TCR)-sequencing, and matched whole-genome sequencing from tiny, frozen clinical specimens. We achieve similar quality and biological outputs while reducing artifactual signals compared to data from matched fresh tissue samples. Profiling sequentially collected melanoma samples from the KEYNOTE-001 trial, we resolve cellular, genomic, and clonotype dynamics that encapsulate molecular patterns of tumor evolution during anti-PD-1 therapy. To demonstrate applicability to banked biospecimens of rare diseases, we generate a large uveal melanoma liver metastasis single-cell and matched WGS atlas, which revealed niche-specific impairment of clonal T cell expansion. This study provides a foundational framework for propelling single-cell genomics to the clinical arena.

genomics↗

bioRxiv2022

Inhibition of the IL-17A axis Protects against Immune-related Adverse Events while Supporting Checkpoint Inhibitor Anti-tumor Efficacy

Checkpoint inhibitor (ICI) immunotherapy leverages the bodys own immune system to attack cancer cells but leads to unwanted autoimmune side effects in up to 60% of patients. Such immune related adverse events (IrAE) may lead to treatment interruption, permanent organ dysfunction, hospitalization and premature death. Thyroiditis is one of the most common IrAE, but the cause of thyroid IrAE remains unknown. Here we present a novel mouse model in which checkpoint inhibitor therapy leads to multi-organ autoimmune infiltrates and show that activation and infiltration of Type 3 immune cells including IL17A+ ROR{gamma}t+ CD4+ (T helper 17 or Th17) and gamma delta 17 ({gamma}{delta}T17) T cells promote thyroid IrAE development. IL-17A+ T cells were similarly found in thyroid specimens from cancer patients treated with ICI who developed thyroid IrAE. Furthermore, antibody-based inhibition of IL-17A, a clinically available therapy, significantly reduced thyroid IrAE development in ICI-treated mice. Finally, combination of IL-17A neutralization with ICI treatment in multiple tumor models did not reduce ICI anti-tumor efficacy. These studies suggest that targeting Th17 and {gamma}{delta}17 function may reduce IrAE without impairing ICI anti-tumor efficacy and may be a generalizable strategy to address IL17-mediated IrAE.

immunology↗

bioRxiv2020

Differential effects of PD-1 and CTLA-4 blockade on the melanoma-reactive CD8 T cell response

Immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) have revolutionized the treatment of melanoma patients. Based on early studies addressing the mechanism of action, it was assumed that PD-1 blockade mostly influences T cell responses at the tumor site. However, recent work has demonstrated that PD-1 blockade can influence the T cell compartment in peripheral. blood. If activation of circulating tumor-reactive T cells would form an important mechanism of action of PD-1 blockade, it may be predicted that such blockade would alter either the frequency and/or the breadth of the tumor-reactive CD8 T cell response. To address this question, we analyzed CD8 T cell responses towards 71 melanoma associated epitopes in peripheral blood of 24 melanoma patients. We show that both the frequency and the breadth of the melanoma-reactive CD8 T cell response in peripheral blood was unaltered upon PD-1 blockade. In contrast, a broadening of the melanoma-reactive CD8 T cell response was observed upon CTLA-4 blockade, in concordance with our prior data. On the basis of these results, we conclude that PD-1 and CTLA-4 blockade impact the tumor-reactive CD8 T cell response in a distinct manner. In addition, the data provide an argument in favor of the hypothesis that anti-PD-1 therapy may primarily act at the tumor site. One sentence summaryWe demonstrate that, contrary to CTLA-4 blockade, PD-1 blockade in melanoma patients does not lead to an increase in the breadth or magnitude of the melanoma-reactive CD8 T cell response in peripheral blood, thereby arguing for a dominant effect of PD-1 blockade at the tumor site.

immunology↗

bioRxiv2020

Accurate neoantigen prediction depends on mutation position relative to patient allele-specific MHC anchor location

Neoantigens are novel peptide sequences resulting from sources such as somatic mutations in tumors. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. As the majority of somatic mutations are single nucleotide variants, changes between wildtype and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen-prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patients specific MHC molecules. While a subset of peptide positions are presented to the T-cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T-cell responses. We computationally predicted high probability anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6-38% of neoantigen candidates are potentially misclassified and can be rescued using allelespecific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline and improve the identification process for relevant clinical studies. One Sentence SummaryNeoantigen prediction accuracy is significantly influenced by the mutation position within the neoantigen and its relative position to the patients allele-specific MHC anchor locations.

bioinformatics↗

bioRxiv2020

Optimizing nucleic acid extraction and transcriptome evaluation from low-input, fixed clinical samples

Tumor biopsies are commonly formalin-fixed and paraffin-embedded (FFPE) for long-term and efficient storage. However, FFPE preservation can greatly compromise the quality of samples, the extraction of nucleic acids, and feasibility of downstream studies, including RNA sequencing. These challenges are especially evident in the studies of clinical trial samples, where the sizes of biopsies often limit the amount of material available for study. Here, we evaluate two nucleic acid extraction kits (Covaris truXTRAC FFPE tNA Plus, QIAGEN miRNeasy FFPE) and three hybridized-capture-based RNA sequencing library preparations (Agilent SureSelect XT RNA Direct, Agilent SureSelect XT HS, and Illumina TruSeq RNA Exome) to evaluate the impact of these sample processing steps on transcriptome evaluation in a melanoma biopsy procured in a clinical setting and preserved by FFPE. While there exist many options for extraction and library preparation that are appropriate for RNA sequencing from FFPE samples, we observed that combinations of experimental approaches may have subtle impacts on downstream analysis, including gene expression quantification and fusion detection.

genomics↗

bioRxiv2020

Autoantibody landscape of advanced prostate cancer

Although the importance of T-cell immune responses is well appreciated in cancer, autoantibody responses are less well-characterized. Nevertheless, autoantibody responses are of great interest, as they may be concordant with T-cell responses to cancer antigens or predictive of response to cancer immunotherapies. We performed serum epitope repertoire analysis (SERA) on a total of 1,229 serum samples obtained from a cohort of 72 men with metastatic castration-resistant prostate cancer (mCRPC) and 1,157 healthy control patients to characterize the autoantibody landscape of mCRPC. Using whole-genome sequencing results from paired solid-tumor metastasis biopsies and germline specimens, we identified tumor-specific epitopes in 29 mutant and 11 non-mutant proteins. Autoantibody enrichments for the top candidate autoantigen (NY-ESO-1) were validated using ELISA performed on the prostate cancer cohort and an independent cohort of 106 patients with melanoma. Our study recovers antigens of known importance and identifies novel tumor-specific epitopes of translational interest in advanced prostate cancer. Statement of significanceAutoantibodies have been shown to inform treatment response and candidate drug targets in various cancers. We present the first large-scale profiling of autoantibodies in advanced prostate cancer, utilizing a new next-generation sequencing-based approach to antibody profiling to reveal novel cancer-specific antigens and epitopes. Disclosure of Potential Conflicts of InterestJJA reports receiving consulting income from Janssen Biotech and Merck and honoraria from Astellas for speakers fees. MR reports receiving commercial research support from Novartis, Johnson & Johnson, Merck, Astellas, and Medivation, and is a consultant/advisory board member for Constellation Pharmaceuticals, Amgen, Ambrx, Johnson & Johnson, and Bayer. A.R. has received honoraria from consulting with Amgen, Bristol-Myers Squibb, Chugai, Dynavax, Genentech, Merck, Nektar, Novartis, Roche and Sanofi, is or has been a member of the scientific advisory board and holds stock in Advaxis, Arcus Biosciences, Bioncotech Therapeutics, Compugen, CytomX, Five Prime, RAPT, ImaginAb, Isoplexis, Kite-Gilead, Lutris Pharma, Merus, PACT Pharma, Rgenix and Tango Therapeutics. FYF serves on the advisory board for Dendreon, EMD Serono, Janssen Oncology, Ferring, Sanofi, Blue Earth Diagnostics, Celgene, consults for Bayer, Medivation/Astellas, Genetech, and Nutcracker Therapeutics, has honoraria from Clovis Oncology, and is a founder and has an ownership stake in PFS Genomics. SGZ and FYF have patent applications with Decipher Biosciences. SGZ and FYF have a patent application licensed to PFS Genomics. SGZ and FYF have patent applications with Celgene. WAH, RW, KK, PSD, and JCS have ownership of stocks or shares at Serimmune, paid employment at Serimmune, board membership at Serimmune, and patent applications on behalf of Serimmune.

cancer biology↗

bioRxiv2020

Prediction of SARS-CoV-2 epitopes across 9360 HLA class I alleles

SummarySARS-CoV-2 T cell response assessment and vaccine development may benefit from an approach that considers the global landscape of the human leukocyte antigen (HLA) proteins. We predicted the binding affinity between 9-mer and 15-mer peptides from the SARS-CoV-2 peptidome for 9,360 class I and 8,445 class II HLA alleles, respectively. We identified 368,145 unique combinations of peptide-HLA complexes (pMHCs) with a predicted binding affinity less than 500nM, and observed significant overlap between class I and II predicted pMHCs. Using simulated populations derived from worldwide HLA frequency data, we identified sets of epitopes predicted in at least 90% of the population in 57 countries. We also developed a method to prioritize pMHCs for specific populations. Collectively, this public dataset and accessible user interface (Shiny app: https://rstudio-connect.parkerici.org/content/13/) can be used to explore the SARS-CoV-2 epitope landscape in the context of diverse HLA types across global populations.Competing Interest StatementK.M.C is a shareholder in Geneoscopy LLC. D.K.W. is a founder, equity holder and receives consulting fees from Immunai. A.R. is supported by the National Institute of Health (R35 CA197633), the Ressler Family Fund, the Agilent Thought Leader Award, a Stand Up to Cancer- Bristol-Meyer Squibb Catalyst Research Grant (Grant Number: SU2C-AACR-CT06-17). This research grant is administered by the American Association for Cancer Research, the scientific partner of SU2C. A.R. is a member researcher at the Parker Institute for Cancer Immunotherapy.View Full Text

immunology↗

bioRxiv2019

IRIS: Big data-informed discovery of cancer immunotherapy targets arising from pre-mRNA alternative splicing

Aberrant alternative splicing (AS) is widespread in cancer, leading to an extensive but largely unexploited repertoire of potential immunotherapy targets. Here we describe IRIS, a computational platform leveraging large-scale cancer and normal transcriptomics data to discover AS-derived tumor antigens for T-cell receptor (TCR) and chimeric antigen receptor T-cell (CAR-T) therapies. Applying IRIS to RNA-Seq data from 22 glioblastomas resected from patients, we identified candidate epitopes and validated their recognition by patient T cells, demonstrating IRISs utility for expanding targeted cancer immunotherapy.

bioinformatics↗

bioRxiv2019

Defective Nucleotide Catabolism Defines a Subset of Cancers Sensitive to Purine Nucleoside Phosphorylase Inhibition

Small molecule inhibitors of purine nucleoside phosphorylase (PNP) have been explored as a treatment strategy for leukemia and lymphoma, however, the determinants of response to this class of drugs are incompletely understood. PNP inhibitors impair cell proliferation by preventing catabolism of the nucleoside deoxyguanosine (dG) which induces toxic imbalances amongst intracellular deoxyribonucleotide triphosphate (dNTP) pools following its phosphorylation and trapping by nucleoside kinases. We hypothesized that differential nucleoside uptake or catabolism defines cancer cell lines as either sensitive or resistant to PNP inhibition. Among cancer cell lines we found that T-cell acute lymphoblastic leukemia (T-ALL) cells are uniquely and acutely sensitive to PNP inhibition whereas the B-cell leukemia and solid tumor models are completely resistant. We determined that although the nucleoside scavenging kinase deoxycytidine kinase (dCK) was active in all cells tested, PNP inhibitors only induced dGTP pool increases in sensitive models. By evaluating the expression of key genes involved in nucleotide scavenging, biosynthesis, and phosphohydrolysis in a panel of sensitive and resistant cell lines we found that the dNTP phosphohydrolase SAM histidine aspartate containing protein 1 (SAMHD1) was exclusively expressed in resistant models. Using CRISPR/Cas9 SAMHD1 knockout cell lines, we verified that PNP inhibitor sensitivity is a function of SAMHD1 expression and determined that the pharmacological inhibition of dCK or genetic restoration of SAMHD1 conferred resistance to PNP inhibition. Importantly, we determined that low expression of SAMHD1 is not limited to T-ALL as subset of established and primary solid tumors models are SAMHD1-deficient. These solid tumor models were consistently acutely sensitive to PNP inhibitors which indicates that the utility of PNP inhibitors extends beyond hematological malignancies. Additionally, we found that deoxycytidine (dC) can limit the anti-proliferative effects of PNP inhibitors by competing with dG for phosphorylation by dCK but this effect can be overcome by expression of dC-catabolizing gene cytidine deaminase (CDA). Collectively, these results indicate that SAMHD1, dCK and CDA are critical biomarkers that must be used to stratify patients in clinical trials evaluating pharmacological PNP inhibition.

cancer biology↗

bioRxiv2019

Trajectories from Snapshots: Integrated proteomic and metabolic single-cell assays reveal multiple independent adaptive responses to drug tolerance in a BRAF-mutant melanoma cell line

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge, with relevance towards understanding biological changes ranging from cellular differentiation to epigenetic (adaptive) responses of diseased cells to drugging. We report on a combined experimental and theoretic method for determining the trajectories that specific highly plastic BRAFV600E mutant patient-derived melanoma cancer cells take between drug-naive and drug-tolerant states. Recent studies have implicated non-genetic, fast-acting resistance mechanisms are activated in these cells following BRAF inhibition. While single-cell highly multiplex omics tools can yield snapshots of the cell state space landscape sampled at any given time point, individual cell trajectories must be inferred from a kinetic series of snapshots, and that inference can be confounded by stochastic cell state switching. Using a microfludic-based single-cell integrated proteomic and metabolic assay, we assayed for a panel of signaling, phenotypic, and metabolic regulators at four time points during the first five days of drug treatment. Dimensional reduction of the resultant data set, coupled with information theoretic analysis, uncovered a complex cell state landscape and identified two distinct paths connecting drug-naive and drug-tolerant states. Cells are shown to exclusively traverse one of the two pathways depending on the level of the lineage restricted transcription factor MITF in the drug-naive cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities, and are independently druggable. Our results update the paradigm of adaptive resistance development in an isogenic cell population and offer insight into the design of more effective combination therapies.

bioengineering↗

bioRxiv2019

Kinetic Inference Resolves Epigenetic Mechanism of Drug Resistance in Melanoma

Drug-induced dedifferentiation towards a drug-tolerant persister state is a common mechanism cancer cells exploit to escape therapies, posing a significant obstacle to sustained therapeutic efficacy. The dynamic coordination of epigenomic and transcriptomic programs at the early-stage of drug exposure, which initiates and orchestrates these reversible dedifferentiation events, remains largely unexplored. Here we employ high-temporal-resolution multi-omics profiling, information-theoretic approaches, and dynamic system modeling to probe these processes in BRAF-mutant melanoma models and patient specimens. We uncover a hysteretic transition trajectory of melanoma cells in response to oncogene inhibition and subsequent release, driven by the sequential operation of two tightly coupled transcriptional waves, which orchestrate genome-scale chromatin state reconfiguration. Modeling of the transcriptional wave interactions predicts NF-{kappa}B/RelA-driven chromatin remodeling as the underlying mechanism of cell-state dedifferentiation, a finding we validate experimentally. Our results identify critical RelA-target genes that are epigenetically modulated to drive this process, establishing a quantitative epigenome gauge to measure cell-state plasticity in melanomas, which supports the potential use of drugs targeting epigenetic machineries to potentiate oncogene inhibition. Extending our investigation to other cancer models, we identify oxidative stress-mediated NF-{kappa}B/RelA activation as a common mechanism driving cellular transitions towards drug-tolerant persister states, revealing a novel and pivotal role for the NF-{kappa}B signaling axis in linking cellular oxidative stress to cancer progression.

cancer biology↗

bioRxiv2019

Characterisation of gastrointestinal helminths and their impact in commercial small-scale chicken flocks in the Mekong Delta of Vietnam

Commercial small-scale chicken farms using all-in-all-out production but operating with low standards of hygiene/biosecurity are increasingly common in Vietnam. These conditions facilitate transmission of gastrointestinal helminths. However there are no published data on these parasites in these systems. The aims were: (1) to determine the prevalence/burden of gastrointestinal helminths in small-scale commercial flocks in commercial small-scale flocks in the Mekong Delta region; and (2) to investigate the association between worm burdens and birds weight and disease status. Randomly selected chickens (n=120) ( normal flocks) were investigated at the end of their production cycle ([~]18 weeks), as well as 90 chickens with signs of respiratory and/or severe disease. The gastrointestinal tract of chickens was dissected and all visible helminths were identified. 54.2% and 54.4% healthy and diseased chickens contained helminths. Diseased, colonized chickens harboured a higher mass of helminth worms (3.8 {+/-}SD 8.6g) than colonized, healthy chickens (1.9 {+/-}6.3g). Eight species were identified, three nematodes (Ascaridia galli, Cheilospirura hamulosa and Heterakis gallinarum), four cestodes (Hymenolepis, Raillietina cesticillus, Raillietina echinobothrida, Raillietina tetragona,) and one trematode (Echinostomatidae). Heterakis gallinarum was the most prevalent helminth (43.3% and 42.2% in healthy and sick chickens, respectively), followed by A. galli (26.7% and 41.1%). Colonized chickens weighed 101.5g less than non-colonized birds. Colonisation was significantly higher during the rainy months (May-November) for both H. gallinarum and A. galli. Anthelminthic usage was not associated with reduced helminth burdens. We recommend upgrading cleaning and disinfection and limiting access to ranging areas to control helminth infections in small-scale commercial chicken flocks.

systems biology↗