Identification of robust RT-qPCR reference genes for studying changes in gene expression in response to hypoxia in breast cancer cell lines.

Hypoxia is common in breast tumours and is linked to therapy resistance and advanced disease. To understand hypoxia-driven breast cancer progression, RT-qPCR is a widely used technique to quantify transcriptional changes that occur during malignant transformation. Reference genes (RGs) are endogenous RT-qPCR controls used to normalise mRNA levels, allowing accurate assessment of transcriptional changes.

PU.1 eviction at lymphocyte-specific chromatin domains mediates glucocorticoid response in acute lymphoblastic leukemia.

The epigenetic landscape plays a critical role in cancer progression, yet its therapeutic potential remains underexplored. Glucocorticoids are essential components of treatments for lymphoid cancers, but resistance, driven in part by epigenetic changes at glucocorticoid-response elements, poses a major challenge to effective therapies. Here we show that glucocorticoid treatment induces distinct patterns of chromosomal organization in glucocorticoid-sensitive and resistant acute lymphoblastic leukemia xenograft models.

Hypoxia-induced epigenetic regulation of breast cancer progression and the tumour microenvironment.

The events that control breast cancer progression and metastasis are complex and intertwined. Hypoxia plays a key role both in oncogenic transformation and in fueling the metastatic potential of breast cancer cells. Here we review the impact of hypoxia on epigenetic regulation of breast cancer, by interfering with multiple aspects of the tumour microenvironment.

A novel Na1.5-dependent feedback mechanism driving glycolytic acidification in breast cancer metastasis.

Solid tumours have abnormally high intracellular [Na]. The activity of various Na channels may underlie this Na accumulation. Voltage-gated Na channels (VGSCs) have been shown to be functionally active in cancer cell lines, where they promote invasion.

ZMIZ1 enhances ERα-dependent expression of E2F2 in breast cancer.

The estrogen receptor-α (ER) drives 75% of breast cancers. On activation, the ER recruits and assembles a 1-2 MDa transcriptionally active complex. These complexes can modulate tumour growth, and understanding the roles of individual proteins within these complexes can help identify new therapeutic targets.

Is it possible to measure good science?

Metrics play a vital part in the valuation and funding of research for scientists worldwide. We review the challenges that metrics pose in providing a fair and equitable system for research funding. We highlight the attempts with declarations, including the San Francisco Declaration on Research Assessment (SF-DORA), to improve the research environment and specific impacts that metric choice can have on the evaluation and progression of Early Career Lecturers (ECLs).

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

Background: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patients with breast cancer, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed 'SURFACER'.

Intestinal region-specific Wnt signalling profiles reveal interrelation between cell identity and oncogenic pathway activity in cancer development.

Background: Cancer results from the accumulation of mutations leading to the acquisition of cancer promoting characteristics such as increased proliferation and resistance to cell death. In colorectal cancer, an early mutation leading to such features usually occurs in the APC or CTNNB1 genes, thereby activating Wnt signalling. However, substantial phenotypic differences between cancers originating within the same organ, such as molecular subtypes, are not fully reflected by differences in mutations.

Web tools to fight pandemics: the COVID-19 experience.

The current outbreak of COVID-19 has generated an unprecedented scientific response worldwide, with the generation of vast amounts of publicly available epidemiological, biological and clinical data. Bioinformatics scientists have quickly produced online methods to provide non-computational users with the opportunity of analyzing such data. In this review, we report the results of this effort, by cataloguing the currently most popular web tools for COVID-19 research and analysis.

How Individuals Who Self-Harm Manage Their Own Risk-'I Cope Because I Self-Harm, and I Can Cope with my Self-Harm'.

Self-harm is a complex and idiosyncratic behaviour. This article focuses on how those who self-harm manage their own risk. Utilising opportunity sampling, ten members of a self-harm support group were interviewed about how they risk manage their self-harm and the data analysed using interpretative phenomenological analysis.

Data generation and network reconstruction strategies for single cell transcriptomic profiles of CRISPR-mediated gene perturbations.

Recent advances in single-cell RNA-sequencing (scRNA-seq) in combination with CRISPR/Cas9 technologies have enabled the development of methods for large-scale perturbation studies with transcriptional readouts. These methods are highly scalable and have the potential to provide a wealth of information on the biological networks that underlie cellular response. Here we discuss how to overcome several key challenges to generate and analyse data for the confident reconstruction of models of the underlying cellular network.

Novelty in science should not come at the cost of reproducibility.

The pressures of a scientific career can end up incentivising an all-or-nothing approach to cross the finish line first. While competition can be healthy and drives innovation, the current system fails to encourage scientists to work reproducibility. This sometimes leaves those individuals who come second to correct mistakes in published research without being rewarded.

Correction to: VULCAN integrates ChIP-seq with patient-derived co-expression networks to identify GRHL2 as a key co-regulator of ERa at enhancers in breast cancer.

Following publication of the original article [1], the authors reported that Figs. 4 and 5 had mistakenly been transposed. Please find the correct Figs.

VULCAN integrates ChIP-seq with patient-derived co-expression networks to identify GRHL2 as a key co-regulator of ERa at enhancers in breast cancer.

Background: VirtUaL ChIP-seq Analysis through Networks (VULCAN) infers regulatory interactions of transcription factors by overlaying networks generated from publicly available tumor expression data onto ChIP-seq data. We apply our method to dissect the regulation of estrogen receptor-alpha activation in breast cancer to identify potential co-regulators of the estrogen receptor's transcriptional response.

Results: VULCAN analysis of estrogen receptor activation in breast cancer highlights the key components of the estrogen receptor complex alongside a novel interaction with GRHL2.

Genome-wide Estrogen Receptor-α activation is sustained, not cyclical.

Estrogen Receptor-alpha (ER) drives 75% of breast cancers. Stimulation of the ER by estra-2-diol forms a transcriptionally-active chromatin-bound complex. Previous studies reported that ER binding follows a cyclical pattern.

KHS101 disrupts energy metabolism in human glioblastoma cells and reduces tumor growth in mice.

Pharmacological inhibition of uncontrolled cell growth with small-molecule inhibitors is a potential strategy for treating glioblastoma multiforme (GBM), the most malignant primary brain cancer. We showed that the synthetic small-molecule KHS101 promoted tumor cell death in diverse GBM cell models, independent of their tumor subtype, and without affecting the viability of noncancerous brain cell lines. KHS101 exerted cytotoxic effects by disrupting the mitochondrial chaperone heat shock protein family D member 1 (HSPD1).

A quantitative mass spectrometry-based approach to monitor the dynamics of endogenous chromatin-associated protein complexes.

Understanding the dynamics of endogenous protein-protein interactions in complex networks is pivotal in deciphering disease mechanisms. To enable the in-depth analysis of protein interactions in chromatin-associated protein complexes, we have previously developed a method termed RIME (Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins). Here, we present a quantitative multiplexed method (qPLEX-RIME), which integrates RIME with isobaric labelling and tribrid mass spectrometry for the study of protein interactome dynamics in a quantitative fashion with increased sensitivity.

Parallel factor ChIP provides essential internal control for quantitative differential ChIP-seq.

A key challenge in quantitative ChIP combined with high-throughput sequencing (ChIP-seq) is the normalization of data in the presence of genome-wide changes in occupancy. Analysis-based normalization methods were developed for transcriptomic data and these are dependent on the underlying assumption that total transcription does not change between conditions. For genome-wide changes in transcription factor (TF) binding, these assumptions do not hold true.

XL-MS: Protein cross-linking coupled with mass spectrometry.

With the continuing trend to study larger and more complex systems, the application of protein cross-linking coupled with mass spectrometry (XL-MS) provides a varied toolkit perfectly suited to achieve these goals. By freezing the transient interactions through the formation of covalent bonds, XL-MS provides a vital insight into both the structure and organization of proteins in a wide variety of conditions. This review covers some of the established methods that underpin the field alongside the more recent developments that hold promise to further realize its potential in new directions.

Organization of Subunits in the Membrane Domain of the Bovine F-ATPase Revealed by Covalent Cross-linking.

The F-ATPase in bovine mitochondria is a membrane-bound complex of about 30 subunits of 18 different kinds. Currently, ∼85% of its structure is known. The enzyme has a membrane extrinsic catalytic domain, and a membrane intrinsic domain where the turning of the enzyme's rotor is generated from the transmembrane proton-motive force.

Hekate: software suite for the mass spectrometric analysis and three-dimensional visualization of cross-linked protein samples.

Chemical cross-linking of proteins combined with mass spectrometry provides an attractive and novel method for the analysis of native protein structures and protein complexes. Analysis of the data however is complex. Only a small number of cross-linked peptides are produced during sample preparation and must be identified against a background of more abundant native peptides.

Bicaudal-D uses a parallel, homodimeric coiled coil with heterotypic registry to coordinate recruitment of cargos to dynein.

Cytoplasmic dynein is the major minus end-directed microtubule motor in eukaryotes. However, there is little structural insight into how different cargos are recognized and linked to the motor complex. Here we describe the 2.

Architecture of the Pol III-clamp-exonuclease complex reveals key roles of the exonuclease subunit in processive DNA synthesis and repair.

DNA polymerase III (Pol III) is the catalytic α subunit of the bacterial DNA Polymerase III holoenzyme. To reach maximum activity, Pol III binds to the DNA sliding clamp β and the exonuclease ε that provide processivity and proofreading, respectively. Here, we characterize the architecture of the Pol III-clamp-exonuclease complex by chemical crosslinking combined with mass spectrometry and biochemical methods, providing the first structural view of the trimeric complex.

Conversion of hydroxyphenylpyruvate dioxygenases into hydroxymandelate synthases by directed evolution.

Hydroxymandelate synthase (HmaS) and hydroxyphenylpyruvate dioxygenase (HppD) are non-heme iron-dependent dioxygenases, which share a common substrate and first catalytic step. The catalytic pathways then diverge to yield hydroxymandelate for secondary metabolism, or homogentisate in tyrosine catabolism. To probe the differences between these related active sites that channel a common intermediate down alternative pathways, we attempted to interconvert their activities by directed evolution.