Ongoing replication stress tolerance and clonal T cell responses distinguish liver and lung recurrence and outcomes in pancreatic cancer.

Patients with metastatic pancreatic ductal adenocarcinoma survive longer if disease spreads to the lung but not the liver. Here we generated overlapping, multi-omic datasets to identify molecular and cellular features that distinguish patients whose disease develops liver metastasis (liver cohort) from those whose disease develops lung metastasis without liver metastases (lung cohort). Lung cohort patients survived longer than liver cohort patients, despite sharing the same tumor subtype.

Exceptional Response to Trastuzumab Deruxtecan in a Patient With Recurrent Ovarian Clear Cell Carcinoma With Human Epidermal Growth Factor Receptor 2 Expression.

Case report of a HER2-expressed ovarian clear cell carcinoma with exceptional response to trastuzumab deruxtecan.

Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging.

Multiplex tissue imaging are a collection of increasingly popular single-cell spatial proteomics and transcriptomics assays for characterizing biological tissues both compositionally and spatially. However, several technical issues limit the utility of multiplex tissue imaging, including the limited number of molecules (proteins and RNAs) that can be assayed, tissue loss, and protein probe failure. In this work, we demonstrate how machine learning methods can address these limitations by imputing protein abundance at the single-cell level using multiplex tissue imaging datasets from a breast cancer cohort.

Addressing persistent challenges in digital image analysis of cancerous tissues.

The National Cancer Institute (NCI) supports many research programs and consortia, many of which use imaging as a major modality for characterizing cancerous tissue. A trans-consortia Image Analysis Working Group (IAWG) was established in 2019 with a mission to disseminate imaging-related work and foster collaborations. In 2022, the IAWG held a virtual hackathon focused on addressing challenges of analyzing high dimensional datasets from fixed cancerous tissues.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer.

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy.

MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging.

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data.

Multiomics analysis of serial PARP inhibitor treated metastatic TNBC inform on rational combination therapies.

In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition.

Galaxy-ML: An accessible, reproducible, and scalable machine learning toolkit for biomedicine.

Supervised machine learning is an essential but difficult to use approach in biomedical data analysis. The Galaxy-ML toolkit (https://galaxyproject.org/community/machine-learning/) makes supervised machine learning more accessible to biomedical scientists by enabling them to perform end-to-end reproducible machine learning analyses at large scale using only a web browser.

Phytopathogenic Have Diverse Plasmids With Few Conserved Virulence Functions.

is a genus of Gram-positive bacteria with species that can cause growth deformations to a large number of plant species. This ability to cause disease is hypothesized to be dependent on a cluster of three gene loci on an almost 200 kb-sized linear plasmid. To reevaluate the roles of some of the genes in pathogenicity, we constructed and characterized deletion mutants of and four genes.

Reproducible biomedical benchmarking in the cloud: lessons from crowd-sourced data challenges.

Challenges are achieving broad acceptance for addressing many biomedical questions and enabling tool assessment. But ensuring that the methods evaluated are reproducible and reusable is complicated by the diversity of software architectures, input and output file formats, and computing environments. To mitigate these problems, some challenges have leveraged new virtualization and compute methods, requiring participants to submit cloud-ready software packages.

Preconception Carrier Screening by Genome Sequencing: Results from the Clinical Laboratory.

Advances in sequencing technologies permit the analysis of a larger selection of genes for preconception carrier screening. The study was designed as a sequential carrier screen using genome sequencing to analyze 728 gene-disorder pairs for carrier and medically actionable conditions in 131 women and their partners (n = 71) who were planning a pregnancy. We report here on the clinical laboratory results from this expanded carrier screening program.

Evolutionary transitions between beneficial and phytopathogenic challenge disease management.

Understanding how bacteria affect plant health is crucial for developing sustainable crop production systems. We coupled ecological sampling and genome sequencing to characterize the population genetic history of and the distribution patterns of virulence plasmids in isolates from nurseries. Analysis of chromosome sequences shows that plants host multiple lineages of , and suggested that these bacteria are transmitted due to independent introductions, reservoir populations, and point source outbreaks.

The Pseudomonas syringae Type III Effector HopG1 Induces Actin Remodeling to Promote Symptom Development and Susceptibility during Infection.

The plant cytoskeleton underpins the function of a multitude of cellular mechanisms, including those associated with developmental- and stress-associated signaling processes. In recent years, the actin cytoskeleton has been demonstrated to play a key role in plant immune signaling, including a recent demonstration that pathogens target actin filaments to block plant defense and immunity. Herein, we quantified spatial changes in host actin filament organization after infection with Pseudomonas syringae pv.

Genome Sequencing and Transposon Mutagenesis of Burkholderia seminalis TC3.4.2R3 Identify Genes Contributing to Suppression of Orchid Necrosis Caused by B. gladioli.

From a screen of 36 plant-associated strains of Burkholderia spp., we identified 24 strains that suppressed leaf and pseudobulb necrosis of orchid caused by B. gladioli.

Use of whole genome sequences to develop a molecular phylogenetic framework for Rhodococcus fascians and the Rhodococcus genus.

The accurate diagnosis of diseases caused by pathogenic bacteria requires a stable species classification. Rhodococcus fascians is the only documented member of its ill-defined genus that is capable of causing disease on a wide range of agriculturally important plants. Comparisons of genome sequences generated from isolates of Rhodococcus associated with diseased plants revealed a level of genetic diversity consistent with them representing multiple species.

Analysis of genome sequences from plant pathogenic Rhodococcus reveals genetic novelties in virulence loci.

Members of Gram-positive Actinobacteria cause economically important diseases to plants. Within the Rhodococcus genus, some members can cause growth deformities and persist as pathogens on a wide range of host plants. The current model predicts that phytopathogenic isolates require a cluster of three loci present on a linear plasmid, with the fas operon central to virulence.

The ABCs and 123s of bacterial secretion systems in plant pathogenesis.

Bacteria have many export and secretion systems that translocate cargo into and across biological membranes. Seven secretion systems contribute to pathogenicity by translocating proteinaceous cargos that can be released into the extracellular milieu or directly into recipient cells. In this review, we describe these secretion systems and how their complexities and functions reflect differences in the destinations, states, functions, and sizes of the translocated cargos as well as the architecture of the bacterial cell envelope.

An improved, high-quality draft genome sequence of the Germination-Arrest Factor-producing Pseudomonas fluorescens WH6.

Background: Pseudomonas fluorescens is a genetically and physiologically diverse species of bacteria present in many habitats and in association with plants. This species of bacteria produces a large array of secondary metabolites with potential as natural products. P.