Characterization of the diversity of type IV secretion system-encoding plasmids in .

The multi-drug resistant pathogen has gained global attention as an important clinical challenge. Owing to its ability to survive on surfaces, its capacity for horizontal gene transfer, and its resistance to front-line antibiotics, has established itself as a successful pathogen. Bacterial conjugation is a central mechanism for pathogen evolution.

Differential DNA damage repair and PARP inhibitor vulnerability of the mammary epithelial lineages.

It is widely assumed that all normal somatic cells can equally perform homologous recombination (HR) and non-homologous end joining in the DNA damage response (DDR). Here, we show that the DDR in normal mammary gland inherently depends on the epithelial cell lineage identity. Bioinformatics, post-irradiation DNA damage repair kinetics, and clonogenic assays demonstrated luminal lineage exhibiting a more pronounced DDR and HR repair compared to the basal lineage.

Large-scale phenogenomic analysis of human cancers uncovers frequent alterations affecting SMC5/6 complex components in breast cancer.

Cancer cells often experience large-scale alterations in genome architecture because of DNA damage and replication stress. Whether mutations in core regulators of chromosome structure can also lead to cancer-promoting loss in genome stability is not fully understood. To address this question, we conducted a systematic analysis of mutations affecting a global regulator of chromosome biology -the SMC5/6 complex- in cancer genomics cohorts.

Bimodal Gene Expression in Patients with Cancer Provides Interpretable Biomarkers for Drug Sensitivity.

Unlabelled: Identifying biomarkers predictive of cancer cell response to drug treatment constitutes one of the main challenges in precision oncology. Recent large-scale cancer pharmacogenomic studies have opened new avenues of research to develop predictive biomarkers by profiling thousands of human cancer cell lines at the molecular level and screening them with hundreds of approved drugs and experimental chemical compounds. Many studies have leveraged these data to build predictive models of response using various statistical and machine learning methods.

IPO11 regulates the nuclear import of BZW1/2 and is necessary for AML cells and stem cells.

AML cells are arranged in a hierarchy with stem/progenitor cells giving rise to more differentiated bulk cells. Despite the importance of stem/progenitors in the pathogenesis of AML, the determinants of the AML stem/progenitor state are not fully understood. Through a comparison of genes that are significant for growth and viability of AML cells by way of a CRISPR screen, with genes that are differentially expressed in leukemia stem cells (LSC), we identified importin 11 (IPO11) as a novel target in AML.

Ontogeny and Vulnerabilities of Drug-Tolerant Persisters in HER2+ Breast Cancer.

Unlabelled: Resistance to targeted therapies is an important clinical problem in HER2-positive (HER2+) breast cancer. "Drug-tolerant persisters" (DTP), a subpopulation of cancer cells that survive via reversible, nongenetic mechanisms, are implicated in resistance to tyrosine kinase inhibitors (TKI) in other malignancies, but DTPs following HER2 TKI exposure have not been well characterized. We found that HER2 TKIs evoke DTPs with a luminal-like or a mesenchymal-like transcriptome.

PharmacoDB 2.0: improving scalability and transparency of in vitro pharmacogenomics analysis.

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair.

Assessing therapy response in patient-derived xenografts.

Quantifying response to drug treatment in mouse models of human cancer is important for treatment development and assignment, yet remains a challenging task. To be able to translate the results of the experiments more readily, a preferred measure to quantify this response should take into account more of the available experimental data, including both tumor size over time and the variation among replicates. We propose a theoretically grounded measure, KuLGaP, to compute the difference between the treatment and control arms.

Novel subtypes of -mutated AML with distinct outcome.

Acute myeloid leukemia (AML) is heterogeneous with one common subtype recognized by the presence of recurrent mutation of nucleophosmin-1 (). Emerging evidence indicates that within mutated AML there is variation in outcome which challenges how best to characterize and treat the individual patient. Our recent findings show that there are two distinct (primitive and committed) subtypes within mutated AML patients.

Orchestrating and sharing large multimodal data for transparent and reproducible research.

Reproducibility is essential to open science, as there is limited relevance for findings that can not be reproduced by independent research groups, regardless of its validity. It is therefore crucial for scientists to describe their experiments in sufficient detail so they can be reproduced, scrutinized, challenged, and built upon. However, the intrinsic complexity and continuous growth of biomedical data makes it increasingly difficult to process, analyze, and share with the community in a FAIR (findable, accessible, interoperable, and reusable) manner.

Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications.

Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models.

The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets such as cancer cell lines are among the most valuable resources for drug sensitivity prediction, a crucial task of precision oncology. Machine learning methods have been employed to predict drug sensitivity based on the multiple omics data available for large panels of cancer cell lines.

Highlights from the 16th International Society for Computational Biology Student Council Symposium 2020.

In this meeting overview, we summarise the scientific program and organisation of the 16th International Society for Computational Biology Student Council Symposium in 2020 (ISCB SCS2020). This symposium was the first virtual edition in an uninterrupted series of symposia that has been going on for 15 years, aiming to unite computational biology students and early career researchers across the globe.

Biological and therapeutic implications of a unique subtype of NPM1 mutated AML.

In acute myeloid leukemia (AML), molecular heterogeneity across patients constitutes a major challenge for prognosis and therapy. AML with NPM1 mutation is a distinct genetic entity in the revised World Health Organization classification. However, differing patterns of co-mutation and response to therapy within this group necessitate further stratification.

Organoid Cultures as Preclinical Models of Non-Small Cell Lung Cancer.

Purpose: Non-small cell lung cancer (NSCLC) is the most common cause of cancer-related deaths worldwide. There is an unmet need to develop novel clinically relevant models of NSCLC to accelerate identification of drug targets and our understanding of the disease.

Experimental Design: Thirty surgically resected NSCLC primary patient tissue and 35 previously established patient-derived xenograft (PDX) models were processed for organoid culture establishment.

Integrative Pharmacogenomics Analysis of Patient-Derived Xenografts.

Identifying robust biomarkers of drug response constitutes a key challenge in precision medicine. Patient-derived tumor xenografts (PDX) have emerged as reliable preclinical models that more accurately recapitulate tumor response to chemo- and targeted therapies. However, the lack of computational tools makes it difficult to analyze high-throughput molecular and pharmacologic profiles of PDX.

Expression levels of long non-coding RNAs are prognostic for AML outcome.

Background: Long non-coding RNA (lncRNA) expression has been implicated in a range of molecular mechanisms that are central in cancer. However, lncRNA expression has not yet been comprehensively characterized in acute myeloid leukemia (AML). Here, we assess to what extent lncRNA expression is prognostic of AML patient overall survival (OS) and determine if there are indications of lncRNA-based molecular subtypes of AML.

Software for the Integration of Multiomics Experiments in Bioconductor.

Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data.

Study design requirements for RNA sequencing-based breast cancer diagnostics.

Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care.

mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data.

Background: Over-representation of predicted miRNA targets in sets of genes regulated by a given transcription factor (e.g. as defined by ChIP-sequencing experiments) helps to identify biologically relevant miRNA targets and is useful to get insight into post-transcriptional regulation.