Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
4,282
result(s) for
"Simpson, Peter"
Sort by:
Invasive lobular carcinoma of the breast: the increasing importance of this special subtype
Invasive lobular carcinoma (ILC) is the most common of the breast cancer special types, accounting for up to 15% of all breast cancer cases. ILCs are noted for their lack of E-cadherin function, which underpins their characteristic discohesive growth pattern, with cells arranged in single file and dispersed throughout the stroma. Typically, tumours are luminal in molecular subtype, being oestrogen and progesterone receptor positive, and HER2 negative. Since last reviewing the lobular literature (McCart Reed et al., Breast Cancer Res 17:12, 2015), there has been a considerable increase in research output focused on this tumour type, including studies into the pathology and management of disease, a high-resolution definition of the genomic landscape of tumours as well as the evolution of several potential therapeutic avenues. There abounds a huge amount of new data, which we will review herein.
Journal Article
Crime in progress : inside the Steele dossier and the Fusion GPS investigation of Donald Trump
\"The never-before-told inside story of the high-stakes, four-year-long investigation into Donald Trump's Russia ties--culminating in the Steele dossier, and sparking the Mueller report--from the founders of political opposition research company Fusion GPS\"-- From publisher's website.
Book
Metal-based antitumor compounds: beyond cisplatin
Despite improvements in the 5-year survival rate to over 80% in cancers, such as Hodgkin lymphoma and testicular cancer, more aggressive tumors including pancreatic and brain cancer still have extremely low survival rates. The establishment of chemoresistance, responsible for the reduction in treatment efficiency and cancer relapse, is one possible explanation for this setback. Metal-based compounds, a class of anticancer drugs, are largely used in the treatment of cancer. Herein, we will review the use of metal-based small molecules in chemotherapy, focusing on recent studies, and we will discuss how new nonplatinum-based agents are prompting scientists to increase drug specificity to overcome chemoresistance in cancer cells.
Journal Article
Invasive lobular carcinoma of the breast: morphology, biomarkers and ’omics
Invasive lobular carcinoma of the breast is the most common ‘special’ morphological subtype of breast cancer, comprising up to 15% of all cases. Tumours are generally of a good prognostic phenotype, being low histological grade and low mitotic index, hormone receptor positive and HER2, p53 and basal marker negative, and with a generally good response to endocrine therapy. Despite this, clinicians face countless challenges in the diagnosis and long-term management of patients, as they encounter a tumour that can be difficult to detect through screening, elicits a very invasive nature, a propensity for widespread metastatic colonisation and, consequently, in some studies a worse long-term poor outcome compared with invasive carcinoma of no special type. Here we review the morphological and molecular features that underpin the disparate biological and clinical characteristics of this fascinating tumour type.
Journal Article
HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures
HRDetect represents a model integrating whole-genome sequencing mutation signatures associated with
BRCA1
and
BRCA2
deficiency. The implementation of this predictor across different tumor types identifies a larger proportion of patients displaying ‘BRCAness’ than previously recognized; they might derive benefit from platinum and PARP-inhibitor therapies.
Approximately 1–5% of breast cancers are attributed to inherited mutations in
BRCA1
or
BRCA2
and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in
BRCA1
and/or
BRCA2
(
BRCA1
/
BRCA2
) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect
BRCA1
/
BRCA2
-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with
BRCA1
/
BRCA2
dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of
BRCA1
/
BRCA2
deficiency. A weighted model called HRDetect was developed to accurately detect
BRCA1
/
BRCA2
-deficient samples. HRDetect identifies
BRCA1
/
BRCA2
-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline
BRCA1
or
BRCA2
mutation, allowed us to identify an additional 22 tumors with somatic loss of
BRCA1
or
BRCA2
and 47 tumors with functional
BRCA1
/
BRCA2
deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring
BRCA1
/
BRCA2
deficiency (up to 22%) than hitherto appreciated (∼1–5%) who could have selective therapeutic sensitivity to PARP inhibition.
Journal Article
A Molecular Probe for the Detection of Polar Lipids in Live Cells
Lipids have an important role in many aspects of cell biology, including membrane architecture/compartment formation, intracellular traffic, signalling, hormone regulation, inflammation, energy storage and metabolism. Lipid biology is therefore integrally involved in major human diseases, including metabolic disorders, neurodegenerative diseases, obesity, heart disease, immune disorders and cancers, which commonly display altered lipid transport and metabolism. However, the investigation of these important cellular processes has been limited by the availability of specific tools to visualise lipids in live cells. Here we describe the potential for ReZolve-L1™ to localise to intracellular compartments containing polar lipids, such as for example sphingomyelin and phosphatidylethanolamine. In live Drosophila fat body tissue from third instar larvae, ReZolve-L1™ interacted mainly with lipid droplets, including the core region of these organelles. The presence of polar lipids in the core of these lipid droplets was confirmed by Raman mapping and while this was consistent with the distribution of ReZolve-L1™ it did not exclude that the molecular probe might be detecting other lipid species. In response to complete starvation conditions, ReZolve-L1™ was detected mainly in Atg8-GFP autophagic compartments, and showed reduced staining in the lipid droplets of fat body cells. The induction of autophagy by Tor inhibition also increased ReZolve-L1™ detection in autophagic compartments, whereas Atg9 knock down impaired autophagosome formation and altered the distribution of ReZolve-L1™. Finally, during Drosophila metamorphosis fat body tissues showed increased ReZolve-L1™ staining in autophagic compartments at two hours post puparium formation, when compared to earlier developmental time points. We concluded that ReZolve-L1™ is a new live cell imaging tool, which can be used as an imaging reagent for the detection of polar lipids in different intracellular compartments.
Journal Article
Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data
Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict spatial gene expression and classify cell types directly from standard H&E images. STimage enhances robustness by estimating gene expression distributions and quantifying both data-driven (aleatoric) and model-based (epistemic) uncertainty using an ensemble approach with foundation models. Interpretability is achieved through attribution analysis at single-cell resolution integrated with histopathological annotations, functional genes, and latent representations. We validated STimage across diverse datasets, demonstrating its performance across various platforms. STimage-predicted gene expression can stratify patient survival and predict drug response. By enabling molecular and cellular prediction from routine histology, STimage offers a powerful tool to advance digital pathology.
Spatial transcriptomics (ST) technologies link tissue morphology with gene expression, but remain expensive to use; furthermore, models that predict ST data from histopathology images possess considerable limitations. Here, the authors develop STimage, a deep learning probabilistic framework for ST prediction from histopathology images while prioritising robustness and interpretability.
Journal Article
Molecular classification of breast cancer
Breast cancer is a complex, multifaceted disease encompassing a great variety of entities that show considerable variation in clinical, morphological and molecular attributes. Traditional classifications including histological assessment and clinical staging are used to guide patient management. In recent years, there has been exponential progress in molecular analysis with profound implications for our understanding of breast cancer biology and, hence, classification. There are now genome-based frameworks for the molecular categorisation of breast cancer including the development of prognostic and predictive signatures that potentially allow individualisation of treatment. Here we review the current state of the molecular classifications of in situ and invasive breast cancer including special subtypes. Future perspectives are also provided.
Journal Article
What makes a drug discovery consortium successful?
Consortia are enabling drug discovery in areas that individual organizations are unable to support alone because of the high risk or the need to pool information. This article discusses desirable features that can underpin the success of such consortia.Consortia are enabling drug discovery in areas that individual organizations are unable to support alone because of the high risk or the need to pool information. This article discusses desirable features that can underpin the success of such consortia.
Journal Article