282 results on '"Whetton AD"'
Search Results
2. A combined biomarker panel shows improved sensitivity for the early detection of ovarian cancer allowing the identification of the most aggressive Type II tumours.
- Author
-
Russell, MR, Graham, C, D’Amato, A, Gentry-Maharaj, A, Ryan, A, Kalsi, JK, Ainley, C, Whetton, AD, Menon, U, Jacobs, I, Graham, RLJ, Russell, MR, Graham, C, D’Amato, A, Gentry-Maharaj, A, Ryan, A, Kalsi, JK, Ainley, C, Whetton, AD, Menon, U, Jacobs, I, and Graham, RLJ
- Abstract
Background: There is an urgent need for biomarkers for the early detection of ovarian cancer (OC). The purpose of this study was to assess whether changes in serum levels of lecithin-cholesterol acyltransferase (LCAT), sex hormone-binding globulin (SHBG), glucoseregulated protein, 78 kDa (GRP78), calprotectin and insulin-like growth factor-binding protein 2 (IGFBP2) are observed before clinical presentation and to assess the performance of these markers alone and in combination with CA125 for early detection. Methods: This nested case–control study used samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening trial. The sample set consisted of 482 serum samples from 49 OC subjects and 31 controls, with serial samples spanning up to 7 years pre-diagnosis. The set was divided into the following: (I) a discovery set, which included all women with only two samples from each woman, the first ato14 months and the second at 432 months to diagnosis; and (ii) a corroboration set, which included all the serial samples from the same women spanning the 7-year period. Lecithin-cholesterol acyltransferase, SHBG, GRP78, calprotectin and IGFBP2 were measured using ELISA. The performance of the markers to detect cancers pre-diagnosis was assessed. Results: A combined threshold model IGFBP2 478.5 ng ml 1 : LCAT o8.831 mg ml 1 : CA125 435 Uml 1 outperformed CA125 alone for the earlier detection of OC. The threshold model was able to identify the most aggressive Type II cancers. In addition, it increased the lead time by 5–6 months and identified 26% of Type I subjects and 13% of Type II subjects that were not identified by CA125 alone. Conclusions: Combined biomarker panels (IGFBP2, LCAT and CA125) outperformed CA125 up to 3 years pre-diagnosis, identifying cancers missed by CA125, providing increased diagnostic lead times for Type I and Type II OC. The model identified more aggressive Type II cancers, with women crossing the threshold dying earlier, indicating
- Published
- 2017
3. Novel Risk Models for early detection and screening of Ovarian Cancer
- Author
-
Russell, MR, D’Amato, A, Graham, C, Crosbie, EJ, Gentry-Maharaj, A, Ryan, A, Kalsi, JK, Fourkala, EO, Dive, C, Walker, M, Whetton, AD, Menon, U, Jacobs, I, Graham, RLJ, Russell, MR, D’Amato, A, Graham, C, Crosbie, EJ, Gentry-Maharaj, A, Ryan, A, Kalsi, JK, Fourkala, EO, Dive, C, Walker, M, Whetton, AD, Menon, U, Jacobs, I, and Graham, RLJ
- Abstract
Purpose: Ovarian cancer (OC) is the most lethal gynaecological cancer. Early detection is required to improve patient survival. Risk estimation models were constructed for Type I (Model I) and Type II (Model II) OC from analysis of Protein Z, Fibronectin, C-reactive protein and CA125 levels in prospectively collected samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Results: Model I identifies cancers earlier than CA125 alone, with a potential lead time of 3-4 years. Model II detects a number of high grade serous cancers at an earlier stage (Stage I/II) than CA125 alone, with a potential lead time of 2-3 years and assigns high risk to patients that the ROCA Algorithm classified as normal. Materials and Methods: This nested case control study included 418 individual serum samples serially collected from 49 OC cases and 31 controls up to six years pre-diagnosis. Discriminatory logit models were built combining the ELISA results for candidate proteins with CA125 levels. Conclusions: These models have encouraging sensitivities for detecting pre-clinical ovarian cancer, demonstrating improved sensitivity compared to CA125 alone. In addition we demonstrate how the models improve on ROCA for some cases and outline their potential future use as clinical tools.
- Published
- 2017
4. Comparative quantification of the surfaceome of human multipotent mesenchymal progenitor cells
- Author
-
Holley RJ, Tai G, Williamson AJK, Taylor S, Cain SA, Richardson SR, Merry CLR, Whetton AD, Kielty CM, Canfield AE
- Abstract
Mesenchymal progenitor cells have great therapeutic potential, yet incomplete characterisation of their cell surface interface limits their clinical exploitation. We have employed subcellular fractionation with quantitative discovery proteomics to define the cell surface interface proteome of human bone marrow mesenchymal stromal/stem cells (MSCs) and human umbilical cord perivascular cells (HUCPVCs). We compared cell surface-enriched fractions from MSCs and HUCPVCs (3 donors each) with adult mesenchymal fibroblasts using 8-channel isobaric-tagging mass spectrometry, yielding relative quantification on >6000 proteins with high confidence. This approach identified 186 up-regulated proteins as mesenchymal progenitor biomarkers. Validation of 10 of these cell surface markers, including ROR2, EPHA2and PLXNA2, confirmed up-regulated expression in mesenchymal progenitor populations and distinct roles in progenitor cell proliferation, migration and differentiation. Thus cell surface protein enrichment plus isobaric-tag labelling prior to MS has delivered a comprehensive cell surface proteome repository that now enables improved selection and functional characterisation of human mesenchymal progenitor populations.
- Published
- 2015
- Full Text
- View/download PDF
5. Novel Risk Models for early detection and screening of Ovarian Cancer
- Author
-
Russell, MR, D’Amato, A, Graham, C, Crosbie, EJ, Gentry-Maharaj, A, Ryan, A, Kalsi, JK, Fourkala, EO, Dive, C, Walker, M, Whetton, AD, Menon, U, Jacobs, I, Graham, RLJ, Russell, MR, D’Amato, A, Graham, C, Crosbie, EJ, Gentry-Maharaj, A, Ryan, A, Kalsi, JK, Fourkala, EO, Dive, C, Walker, M, Whetton, AD, Menon, U, Jacobs, I, and Graham, RLJ
- Abstract
Purpose: Ovarian cancer (OC) is the most lethal gynaecological cancer. Early detection is required to improve patient survival. Risk estimation models were constructed for Type I (Model I) and Type II (Model II) OC from analysis of Protein Z, Fibronectin, C-reactive protein and CA125 levels in prospectively collected samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Results: Model I identifies cancers earlier than CA125 alone, with a potential lead time of 3-4 years. Model II detects a number of high grade serous cancers at an earlier stage (Stage I/II) than CA125 alone, with a potential lead time of 2-3 years and assigns high risk to patients that the ROCA Algorithm classified as normal. Materials and Methods: This nested case control study included 418 individual serum samples serially collected from 49 OC cases and 31 controls up to six years pre-diagnosis. Discriminatory logit models were built combining the ELISA results for candidate proteins with CA125 levels. Conclusions: These models have encouraging sensitivities for detecting pre-clinical ovarian cancer, demonstrating improved sensitivity compared to CA125 alone. In addition we demonstrate how the models improve on ROCA for some cases and outline their potential future use as clinical tools.
- Published
- 2016
6. Dual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells
- Author
-
Abraham, SA, Hopcroft, LEM, Carrick, E, Drotar, ME, Dunn, K, Williamson, AJK, Korfi, K, Baquero, P, Park, LE, Scott, MT, Pellicano, F, Pierce, A, Copland, M, Nourse, C, Grimmond, SM, Vetrie, D, Whetton, AD, Holyoake, TL, Abraham, SA, Hopcroft, LEM, Carrick, E, Drotar, ME, Dunn, K, Williamson, AJK, Korfi, K, Baquero, P, Park, LE, Scott, MT, Pellicano, F, Pierce, A, Copland, M, Nourse, C, Grimmond, SM, Vetrie, D, Whetton, AD, and Holyoake, TL
- Abstract
Chronic myeloid leukaemia (CML) arises after transformation of a haemopoietic stem cell (HSC) by the protein-tyrosine kinase BCR-ABL. Direct inhibition of BCR-ABL kinase has revolutionized disease management, but fails to eradicate leukaemic stem cells (LSCs), which maintain CML. LSCs are independent of BCR-ABL for survival, providing a rationale for identifying and targeting kinase-independent pathways. Here we show--using proteomics, transcriptomics and network analyses--that in human LSCs, aberrantly expressed proteins, in both imatinib-responder and non-responder patients, are modulated in concert with p53 (also known as TP53) and c-MYC regulation. Perturbation of both p53 and c-MYC, and not BCR-ABL itself, leads to synergistic cell kill, differentiation, and near elimination of transplantable human LSCs in mice, while sparing normal HSCs. This unbiased systems approach targeting connected nodes exemplifies a novel precision medicine strategy providing evidence that LSCs can be eradicated.
- Published
- 2016
7. Phosphorylation of the Leukemic Oncoprotein EVI1 on Serine 196 Modulates DNA Binding, Transcriptional Repression and Transforming Ability
- Author
-
White, DJ, Unwin, RD, Bindels, Eric, Pierce, A, Teng, HY, Muter, J, Greystoke, B, Somerville, TD, Griffiths, J, Lovell, S, Somervaille, TCP, Delwel, Ruud, Whetton, AD, Meyer, S (Silke), White, DJ, Unwin, RD, Bindels, Eric, Pierce, A, Teng, HY, Muter, J, Greystoke, B, Somerville, TD, Griffiths, J, Lovell, S, Somervaille, TCP, Delwel, Ruud, Whetton, AD, and Meyer, S (Silke)
- Published
- 2013
8. Genome-Wide Analysis of Transcriptional Reprogramming in Mouse Models of Acute Myeloid Leukaemia
- Author
-
Imhof, A, Bonadies, N, Foster, SD, Chan, W-I, Kvinlaug, BT, Spensberger, D, Dawson, MA, Spooncer, E, Whetton, AD, Bannister, AJ, Huntly, BJ, Goettgens, B, Imhof, A, Bonadies, N, Foster, SD, Chan, W-I, Kvinlaug, BT, Spensberger, D, Dawson, MA, Spooncer, E, Whetton, AD, Bannister, AJ, Huntly, BJ, and Goettgens, B
- Abstract
Acute leukaemias are commonly caused by mutations that corrupt the transcriptional circuitry of haematopoietic stem/progenitor cells. However, the mechanisms underlying large-scale transcriptional reprogramming remain largely unknown. Here we investigated transcriptional reprogramming at genome-scale in mouse retroviral transplant models of acute myeloid leukaemia (AML) using both gene-expression profiling and ChIP-sequencing. We identified several thousand candidate regulatory regions with altered levels of histone acetylation that were characterised by differential distribution of consensus motifs for key haematopoietic transcription factors including Gata2, Gfi1 and Sfpi1/Pu.1. In particular, downregulation of Gata2 expression was mirrored by abundant GATA motifs in regions of reduced histone acetylation suggesting an important role in leukaemogenic transcriptional reprogramming. Forced re-expression of Gata2 was not compatible with sustained growth of leukaemic cells thus suggesting a previously unrecognised role for Gata2 in downregulation during the development of AML. Additionally, large scale human AML datasets revealed significantly higher expression of GATA2 in CD34+ cells from healthy controls compared with AML blast cells. The integrated genome-scale analysis applied in this study represents a valuable and widely applicable approach to study the transcriptional control of both normal and aberrant haematopoiesis and to identify critical factors responsible for transcriptional reprogramming in human cancer.
- Published
- 2011
9. A proof-of-principle gel-free proteomics strategy for the identification of predictive biomarkers for the onset of pre-eclampsia
- Author
-
Blankley, RT, primary, Gaskell, SJ, additional, Whetton, AD, additional, Dive, C, additional, Baker, PN, additional, and Myers, JE, additional
- Published
- 2009
- Full Text
- View/download PDF
10. Macrophage inflammatory protein-1 alpha receptors are present on cells enriched for CD34 expression from patients with chronic myeloid leukemia
- Author
-
Chasty, RC, primary, Lucas, GS, additional, Owen-Lynch, PJ, additional, Pierce, A, additional, and Whetton, AD, additional
- Published
- 1995
- Full Text
- View/download PDF
11. Inositol Phosphates and Calcium Signalling
- Author
-
Whetton, AD, primary
- Published
- 1993
- Full Text
- View/download PDF
12. Protein kinase C activators can interact synergistically with granulocyte colony-stimulating factor or interleukin-6 to stimulate colony formation from enriched granulocyte-macrophage colony-forming cells
- Author
-
Heyworth, CM, primary, Dexter, TM, additional, Nicholls, SE, additional, and Whetton, AD, additional
- Published
- 1993
- Full Text
- View/download PDF
13. Stem cell factor directly stimulates the development of enriched granulocyte-macrophage colony-forming cells and promotes the effects of other colony-stimulating factors
- Author
-
Heyworth, CM, primary, Whetton, AD, additional, Nicholls, S, additional, Zsebo, K, additional, and Dexter, TM, additional
- Published
- 1992
- Full Text
- View/download PDF
14. Interferon-gamma stimulates the survival and influences the development of bipotential granulocyte-macrophage colony-forming cells
- Author
-
Kan, O, primary, Heyworth, CM, additional, Dexter, TM, additional, Maudsley, PJ, additional, Cook, N, additional, Vallance, SJ, additional, and Whetton, AD, additional
- Published
- 1991
- Full Text
- View/download PDF
15. Inhibitors of cholera toxin-induced adenosine diphosphate ribosylation of membrane-associated proteins block stem cell differentiation
- Author
-
Dexter, TM, Whetton, AD, and Heyworth, CM
- Abstract
Two potent inhibitors of mono-adenosine diphosphate (ADP) ribosylation have recently been described and characterized, named p- methoxylbenzylaminodecamethylene guanidine sulfate (MBAMG) and benzylaminododecylguanine hydrochloride (BADGH). We have used these agents to investigate the role of ADP ribosylation in hematopoiesis using long-term marrow cultures. The addition of MBAMG (10(-6) mol/L) or BADGH (5 X 10(-4) mol/L) led to both an inhibition of mature cell production and the development of colony-stimulating factor (CSF-1)- responsive GM-CFC, but had no effect upon spleen colony-forming units (CFU-S) or on progenitor cells which respond to the multilineage stimulating factor present in WEHI-3B cell-conditioned medium. These data indicate that these inhibitors of mono-ADP ribosylation can block the commitment and/or differentiation of stem cells and infers that ADP ribosylation may be of some importance in the hematopoietic process.
- Published
- 1985
- Full Text
- View/download PDF
16. Artificial intelligence driven definition of food preference endotypes in UK Biobank volunteers is associated with distinctive health outcomes and blood based metabolomic and proteomic profiles.
- Author
-
Navratilova HF, Whetton AD, and Geifman N
- Subjects
- Humans, United Kingdom, Male, Female, Middle Aged, Metabolome, Adult, Aged, Surveys and Questionnaires, Health, UK Biobank, Food Preferences, Biological Specimen Banks, Proteomics methods, Metabolomics, Artificial Intelligence
- Abstract
Background: Specific food preferences can determine an individual's dietary patterns and therefore, may be associated with certain health risks and benefits., Methods: Using food preference questionnaire (FPQ) data from a subset comprising over 180,000 UK Biobank participants, we employed Latent Profile Analysis (LPA) approach to identify the main patterns or profiles among participants. blood biochemistry across groups/profiles was compared using the non-parametric Kruskal-Wallis test. We applied the Limma algorithm for differential abundance analysis on 168 metabolites and 2923 proteins, and utilized the Database for Annotation, Visualization and Integrated Discovery (DAVID) to identify enriched biological processes and pathways. Relative risks (RR) were calculated for chronic diseases and mental conditions per group, adjusting for sociodemographic factors., Results: Based on their food preferences, three profiles were termed: the putative Health-conscious group (low preference for animal-based or sweet foods, and high preference for vegetables and fruits), the Omnivore group (high preference for all foods), and the putative Sweet-tooth group (high preference for sweet foods and sweetened beverages). The Health-conscious group exhibited lower risk of heart failure (RR = 0.86, 95%CI 0.79-0.93) and chronic kidney disease (RR = 0.69, 95%CI 0.65-0.74) compared to the two other groups. The Sweet-tooth group had greater risk of depression (RR = 1.27, 95%CI 1.21-1.34), diabetes (RR = 1.15, 95%CI 1.01-1.31), and stroke (RR = 1.22, 95%CI 1.15-1.31) compared to the other two groups. Cancer (overall) relative risk showed little difference across the Health-conscious, Omnivore, and Sweet-tooth groups with RR of 0.98 (95%CI 0.96-1.01), 1.00 (95%CI 0.98-1.03), and 1.01 (95%CI 0.98-1.04), respectively. The Health-conscious group was associated with lower levels of inflammatory biomarkers (e.g., C-reactive Protein) which are also known to be elevated in those with common metabolic diseases (e.g., cardiovascular disease). Other markers modulated in the Health-conscious group, ketone bodies, insulin-like growth factor-binding protein (IGFBP), and Growth Hormone 1 were more abundant, while leptin was less abundant. Further, the IGFBP pathway, which influences IGF1 activity, may be significantly enhanced by dietary choices., Conclusions: These observations align with previous findings from studies focusing on weight loss interventions, which include a reduction in leptin levels. Overall, the Health-conscious group, with preference to healthier food options, has better health outcomes, compared to Sweet-tooth and Omnivore groups., (© 2024. The Author(s).)
- Published
- 2024
- Full Text
- View/download PDF
17. Evaluation of a proteomic signature coupled with the kidney failure risk equation in predicting end stage kidney disease in a chronic kidney disease cohort.
- Author
-
Ramírez Medina CR, Ali I, Baricevic-Jones I, Saleem MA, Whetton AD, Kalra PA, and Geifman N
- Abstract
Background: The early identification of patients at high-risk for end-stage renal disease (ESRD) is essential for providing optimal care and implementing targeted prevention strategies. While the Kidney Failure Risk Equation (KFRE) offers a more accurate prediction of ESRD risk compared to static eGFR-based thresholds, it does not provide insights into the patient-specific biological mechanisms that drive ESRD. This study focused on evaluating the effectiveness of KFRE in a UK-based advanced chronic kidney disease (CKD) cohort and investigating whether the integration of a proteomic signature could enhance 5-year ESRD prediction., Methods: Using the Salford Kidney Study biobank, a UK-based prospective cohort of over 3000 non-dialysis CKD patients, 433 patients met our inclusion criteria: a minimum of four eGFR measurements over a two-year period and a linear eGFR trajectory. Plasma samples were obtained and analysed for novel proteomic signals using SWATH-Mass-Spectrometry. The 4-variable UK-calibrated KFRE was calculated for each patient based on their baseline clinical characteristics. Boruta machine learning algorithm was used for the selection of proteins most contributing to differentiation between patient groups. Logistic regression was employed for estimation of ESRD prediction by (1) proteomic features; (2) KFRE; and (3) proteomic features alongside KFRE., Results: SWATH maps with 943 quantified proteins were generated and investigated in tandem with available clinical data to identify potential progression biomarkers. We identified a set of proteins (SPTA1, MYL6 and C6) that, when used alongside the 4-variable UK-KFRE, improved the prediction of 5-year risk of ESRD (AUC = 0.75 vs AUC = 0.70). Functional enrichment analysis revealed Rho GTPases and regulation of the actin cytoskeleton pathways to be statistically significant, inferring their role in kidney function and the pathogenesis of renal disease., Conclusions: Proteins SPTA1, MYL6 and C6, when used alongside the 4-variable UK-KFRE achieve an improved performance when predicting a 5-year risk of ESRD. Specific pathways implicated in the pathogenesis of podocyte dysfunction were also identified, which could serve as potential therapeutic targets. The findings of our study carry implications for comprehending the involvement of the Rho family GTPases in the pathophysiology of kidney disease, advancing our understanding of the proteomic factors influencing susceptibility to renal damage., (© 2024. The Author(s).)
- Published
- 2024
- Full Text
- View/download PDF
18. Single-Cell Untargeted Lipidomics Using Liquid Chromatography and Data-Dependent Acquisition after Live Cell Selection.
- Author
-
von Gerichten J, Saunders KDG, Kontiza A, Newman CF, Mayson G, Beste DJV, Velliou E, Whetton AD, and Bailey MJ
- Subjects
- Humans, Animals, Chromatography, Liquid, Mice, Cell Line, Tumor, Mass Spectrometry, Macrophages metabolism, Macrophages cytology, Single-Cell Analysis, Lipidomics methods, Lipids analysis, Lipids chemistry
- Abstract
We report the development and validation of an untargeted single-cell lipidomics method based on microflow chromatography coupled to a data-dependent mass spectrometry method for fragmentation-based identification of lipids. Given the absence of single-cell lipid standards, we show how the methodology should be optimized and validated using a dilute cell extract. The methodology is applied to dilute pancreatic cancer and macrophage cell extracts and standards to demonstrate the sensitivity requirements for confident assignment of lipids and classification of the cell type at the single-cell level. The method is then coupled to a system that can provide automated sampling of live, single cells into capillaries under microscope observation. This workflow retains the spatial information and morphology of cells during sampling and highlights the heterogeneity in lipid profiles observed at the single-cell level. The workflow is applied to show changes in single-cell lipid profiles as a response to oxidative stress, coinciding with expanded lipid droplets. This demonstrates that the workflow is sufficiently sensitive to observing changes in lipid profiles in response to a biological stimulus. Understanding how lipids vary in single cells will inform future research into a multitude of biological processes as lipids play important roles in structural, biophysical, energy storage, and signaling functions.
- Published
- 2024
- Full Text
- View/download PDF
19. Detection of endometrial cancer in cervico-vaginal fluid and blood plasma: leveraging proteomics and machine learning for biomarker discovery.
- Author
-
Njoku K, Pierce A, Chiasserini D, Geary B, Campbell AE, Kelsall J, Reed R, Geifman N, Whetton AD, and Crosbie EJ
- Subjects
- Humans, Female, Biomarkers, Plasma, Machine Learning, Proteomics, Endometrial Neoplasms diagnosis, Endometrial Neoplasms pathology
- Abstract
Background: The anatomical continuity between the uterine cavity and the lower genital tract allows for the exploitation of uterine-derived biomaterial in cervico-vaginal fluid for endometrial cancer detection based on non-invasive sampling methodologies. Plasma is an attractive biofluid for cancer detection due to its simplicity and ease of collection. In this biomarker discovery study, we aimed to identify proteomic signatures that accurately discriminate endometrial cancer from controls in cervico-vaginal fluid and blood plasma., Methods: Blood plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from symptomatic post-menopausal women with (n = 53) and without (n = 65) endometrial cancer. Digitised proteomic maps were derived for each sample using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins. The best diagnostic model was determined based on accuracy and model parsimony., Findings: A protein signature derived from cervico-vaginal fluid more accurately discriminated cancer from control samples than one derived from plasma. A 5-biomarker panel of cervico-vaginal fluid derived proteins (HPT, LG3BP, FGA, LY6D and IGHM) predicted endometrial cancer with an AUC of 0.95 (0.91-0.98), sensitivity of 91% (83%-98%), and specificity of 86% (78%-95%). By contrast, a 3-marker panel of plasma proteins (APOD, PSMA7 and HPT) predicted endometrial cancer with an AUC of 0.87 (0.81-0.93), sensitivity of 75% (64%-86%), and specificity of 84% (75%-93%). The parsimonious model AUC values for detection of stage I endometrial cancer in cervico-vaginal fluid and blood plasma were 0.92 (0.87-0.97) and 0.88 (0.82-0.95) respectively., Interpretation: Here, we leveraged the natural shed of endometrial tumours to potentially develop an innovative approach to endometrial cancer detection. We show proof of principle that endometrial cancers secrete unique protein signatures that can enable cancer detection via cervico-vaginal fluid assays. Confirmation in a larger independent cohort is warranted., Funding: Cancer Research UK, Blood Cancer UK, National Institute for Health Research., Competing Interests: Declaration of interests The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
20. Correction: Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.
- Author
-
Ramírez Medina CR, Ali I, Baricevic-Jones I, Odudu A, Saleem MA, Whetton AD, Kalra PA, and Geifman N
- Published
- 2024
- Full Text
- View/download PDF
21. Associations of Diet with Health Outcomes in the UK Biobank: A Systematic Review.
- Author
-
Navratilova HF, Lanham-New S, Whetton AD, and Geifman N
- Subjects
- Female, Humans, Male, Middle Aged, Colorectal Neoplasms epidemiology, Colorectal Neoplasms etiology, Colorectal Neoplasms prevention & control, Diet, Healthy statistics & numerical data, Neoplasms epidemiology, Neoplasms etiology, Risk Factors, UK Biobank statistics & numerical data, United Kingdom epidemiology, Cardiovascular Diseases epidemiology, Cardiovascular Diseases etiology, Diabetes Mellitus, Type 2 epidemiology, Diabetes Mellitus, Type 2 etiology, Diet statistics & numerical data, Diet adverse effects
- Abstract
The UK Biobank is a cohort study that collects data on diet, lifestyle, biomarkers, and health to examine diet-disease associations. Based on the UK Biobank, we reviewed 36 studies on diet and three health conditions: type 2 diabetes (T2DM), cardiovascular disease (CVD), and cancer. Most studies used one-time dietary data instead of repeated 24 h recalls, which may lead to measurement errors and bias in estimating diet-disease associations. We also found that most studies focused on single food groups or macronutrients, while few studies adopted a dietary pattern approach. Several studies consistently showed that eating more red and processed meat led to a higher risk of lung and colorectal cancer. The results suggest that high adherence to "healthy" dietary patterns (consuming various food types, with at least three servings/day of whole grain, fruits, and vegetables, and meat and processed meat less than twice a week) slightly lowers the risk of T2DM, CVD, and colorectal cancer. Future research should use multi-omics data and machine learning models to account for the complexity and interactions of dietary components and their effects on disease risk.
- Published
- 2024
- Full Text
- View/download PDF
22. Prospective study design and data analysis in UK Biobank.
- Author
-
Allen NE, Lacey B, Lawlor DA, Pell JP, Gallacher J, Smeeth L, Elliott P, Matthews PM, Lyons RA, Whetton AD, Lucassen A, Hurles ME, Chapman M, Roddam AW, Fitzpatrick NK, Hansell AL, Hardy R, Marioni RE, O'Donnell VB, Williams J, Lindgren CM, Effingham M, Sellors J, Danesh J, and Collins R
- Subjects
- Humans, Prospective Studies, Research Design, Data Analysis, UK Biobank, Biological Specimen Banks
- Abstract
Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.
- Published
- 2024
- Full Text
- View/download PDF
23. Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia.
- Author
-
Spick M, Muazzam A, Pandha H, Michael A, Gethings LA, Hughes CJ, Munjoma N, Plumb RS, Wilson ID, Whetton AD, Townsend PA, and Geifman N
- Abstract
There is an unmet need for improved diagnostic testing and risk prediction for cases of prostate cancer (PCa) to improve care and reduce overtreatment of indolent disease. Here we have analysed the serum proteome and lipidome of 262 study participants by liquid chromatography-mass spectrometry, including participants diagnosed with PCa, benign prostatic hyperplasia (BPH), or otherwise healthy volunteers, with the aim of improving biomarker specificity. Although a two-class machine learning model separated PCa from controls with sensitivity of 0.82 and specificity of 0.95, adding BPH resulted in a statistically significant decline in specificity for prostate cancer to 0.76, with half of BPH cases being misclassified by the model as PCa. A small number of biomarkers differentiating between BPH and prostate cancer were identified, including proteins in MAP Kinase pathways, as well as in lipids containing oleic acid; these may offer a route to greater specificity. These results highlight, however, that whilst there are opportunities for machine learning, these will only be achieved by use of appropriate training sets that include confounding comorbidities, especially when calculating the specificity of a test., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests., (© 2023 The Authors.)
- Published
- 2023
- Full Text
- View/download PDF
24. Proteomic analysis identifies subgroups of patients with active systemic lupus erythematosus.
- Author
-
Su KYC, Reynolds JA, Reed R, Da Silva R, Kelsall J, Baricevic-Jones I, Lee D, Whetton AD, Geifman N, McHugh N, and Bruce IN
- Abstract
Objective: Systemic lupus erythematosus (SLE) is a clinically and biologically heterogenous autoimmune disease. We aimed to investigate the plasma proteome of patients with active SLE to identify novel subgroups, or endotypes, of patients., Method: Plasma was collected from patients with active SLE who were enrolled in the British Isles Lupus Assessment Group Biologics Registry (BILAG-BR). The plasma proteome was analysed using a data-independent acquisition method, Sequential Window Acquisition of All theoretical mass spectra mass spectrometry (SWATH-MS). Unsupervised, data-driven clustering algorithms were used to delineate groups of patients with a shared proteomic profile., Results: In 223 patients, six clusters were identified based on quantification of 581 proteins. Between the clusters, there were significant differences in age (p = 0.012) and ethnicity (p = 0.003). There was increased musculoskeletal disease activity in cluster 1 (C1), 19/27 (70.4%) (p = 0.002) and renal activity in cluster 6 (C6) 15/24 (62.5%) (p = 0.051). Anti-SSa/Ro was the only autoantibody that significantly differed between clusters (p = 0.017). C1 was associated with p21-activated kinases (PAK) and Phospholipase C (PLC) signalling. Within C1 there were two sub-clusters (C1A and C1B) defined by 49 proteins related to cytoskeletal protein binding. C2 and C6 demonstrated opposite Rho family GTPase and Rho GDI signalling. Three proteins (MZB1, SND1 and AGL) identified in C6 increased the classification of active renal disease although this did not reach statistical significance (p = 0.0617)., Conclusions: Unsupervised proteomic analysis identifies clusters of patients with active SLE, that are associated with clinical and serological features, which may facilitate biomarker discovery. The observed proteomic heterogeneity further supports the need for a personalised approach to treatment in SLE., (© 2023. The Author(s).)
- Published
- 2023
- Full Text
- View/download PDF
25. Identification of curaxin as a potential new therapeutic for JAK2 V617F mutant patients.
- Author
-
Pearson S, Blance R, Yan F, Hsieh YC, Geary B, Amaral FMR, Somervaille TCP, Kirschner K, Whetton AD, and Pierce A
- Subjects
- Humans, Mice, Animals, Proteomics, Quality of Life, Janus Kinase 2 metabolism, Chromatin, Mutation, Primary Myelofibrosis drug therapy, Primary Myelofibrosis genetics, Myeloproliferative Disorders drug therapy, Myeloproliferative Disorders genetics, Myeloproliferative Disorders metabolism
- Abstract
Myelofibrosis is a myeloproliferative neoplasm (MPN) which typically results in reduced length and quality of life due to systemic symptoms and blood count changes arising from fibrotic changes in the bone marrow. While the JAK2 inhibitor ruxolitinib provides some clinical benefit, there remains a substantial unmet need for novel targeted therapies to better modify the disease process or eradicate the cells at the heart of myelofibrosis pathology. Repurposing drugs bypasses many of the hurdles present in drug development, such as toxicity and pharmacodynamic profiling. To this end we undertook a re-analysis of our pre-existing proteomic data sets to identify perturbed biochemical pathways and their associated drugs/inhibitors to potentially target the cells driving myelofibrosis. This approach identified CBL0137 as a candidate for targeting Jak2 mutation-driven malignancies. CBL0137 is a drug derived from curaxin targeting the Facilitates Chromatin Transcription (FACT) complex. It is reported to trap the FACT complex on chromatin thereby activating p53 and inhibiting NF-kB activity. We therefore assessed the activity of CBL0137 in primary patient samples and murine models of Jak2-mutated MPN and found it preferentially targets CD34+ stem and progenitor cells from myelofibrosis patients by comparison with healthy control cells. Further we investigate its mechanism of action in primary haemopoietic progenitor cells and demonstrate its ability to reduce splenomegaly and reticulocyte number in a transgenic murine model of myeloproliferative neoplasms., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Pearson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
- Full Text
- View/download PDF
26. Quantitative SWATH-based proteomic profiling of urine for the identification of endometrial cancer biomarkers in symptomatic women.
- Author
-
Njoku K, Pierce A, Geary B, Campbell AE, Kelsall J, Reed R, Armit A, Da Sylva R, Zhang L, Agnew H, Baricevic-Jones I, Chiasserini D, Whetton AD, and Crosbie EJ
- Subjects
- Humans, Female, Case-Control Studies, Proteomics methods, Biomarkers, Mass Spectrometry methods, Fatty Acid-Binding Proteins, Extracellular Matrix Proteins, Biomarkers, Tumor, Endometrial Neoplasms diagnosis
- Abstract
Background: A non-invasive endometrial cancer detection tool that can accurately triage symptomatic women for definitive testing would improve patient care. Urine is an attractive biofluid for cancer detection due to its simplicity and ease of collection. The aim of this study was to identify urine-based proteomic signatures that can discriminate endometrial cancer patients from symptomatic controls., Methods: This was a prospective case-control study of symptomatic post-menopausal women (50 cancers, 54 controls). Voided self-collected urine samples were processed for mass spectrometry and run using sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning techniques were used to identify important discriminatory proteins, which were subsequently combined in multi-marker panels using logistic regression., Results: The top discriminatory proteins individually showed moderate accuracy (AUC > 0.70) for endometrial cancer detection. However, algorithms combining the most discriminatory proteins performed well with AUCs > 0.90. The best performing diagnostic model was a 10-marker panel combining SPRR1B, CRNN, CALML3, TXN, FABP5, C1RL, MMP9, ECM1, S100A7 and CFI and predicted endometrial cancer with an AUC of 0.92 (0.96-0.97). Urine-based protein signatures showed good accuracy for the detection of early-stage cancers (AUC 0.92 (0.86-0.9))., Conclusion: A patient-friendly, urine-based test could offer a non-invasive endometrial cancer detection tool in symptomatic women. Validation in a larger independent cohort is warranted., (© 2023. The Author(s).)
- Published
- 2023
- Full Text
- View/download PDF
27. Proteomic signature associated with chronic kidney disease (CKD) progression identified by data-independent acquisition mass spectrometry.
- Author
-
Ramírez Medina CR, Ali I, Baricevic-Jones I, Odudu A, Saleem MA, Whetton AD, Kalra PA, and Geifman N
- Abstract
Background: Halting progression of chronic kidney disease (CKD) to established end stage kidney disease is a major goal of global health research. The mechanism of CKD progression involves pro-inflammatory, pro-fibrotic, and vascular pathways, but pathophysiological differentiation is currently lacking., Methods: Plasma samples of 414 non-dialysis CKD patients, 170 fast progressors (with ∂ eGFR-3 ml/min/1.73 m
2 /year or worse) and 244 stable patients (∂ eGFR of - 0.5 to + 1 ml/min/1.73 m2 /year) with a broad range of kidney disease aetiologies, were obtained and interrogated for proteomic signals with SWATH-MS. We applied a machine learning approach to feature selection of proteins quantifiable in at least 20% of the samples, using the Boruta algorithm. Biological pathways enriched by these proteins were identified using ClueGo pathway analyses., Results: The resulting digitised proteomic maps inclusive of 626 proteins were investigated in tandem with available clinical data to identify biomarkers of progression. The machine learning model using Boruta Feature Selection identified 25 biomarkers as being important to progression type classification (Area Under the Curve = 0.81, Accuracy = 0.72). Our functional enrichment analysis revealed associations with the complement cascade pathway, which is relevant to CKD as the kidney is particularly vulnerable to complement overactivation. This provides further evidence to target complement inhibition as a potential approach to modulating the progression of diabetic nephropathy. Proteins involved in the ubiquitin-proteasome pathway, a crucial protein degradation system, were also found to be significantly enriched., Conclusions: The in-depth proteomic characterisation of this large-scale CKD cohort is a step toward generating mechanism-based hypotheses that might lend themselves to future drug targeting. Candidate biomarkers will be validated in samples from selected patients in other large non-dialysis CKD cohorts using a targeted mass spectrometric analysis., (© 2023. The Author(s).)- Published
- 2023
- Full Text
- View/download PDF
28. Identifying developments over a decade in the digital health and telemedicine landscape in the UK using quantitative text mining.
- Author
-
Geifman N, Armes J, and Whetton AD
- Abstract
The use of technologies that provide objective, digital data to clinicians, carers, and service users to improve care and outcomes comes under the unifying term Digital Health. This field, which includes the use of high-tech health devices, telemedicine and health analytics has, in recent years, seen significant growth in the United Kingdom and worldwide. It is clearly acknowledged by multiple stakeholders that digital health innovations are necessary for the future of improved and more economic healthcare service delivery. Here we consider digital health-related research and applications by using an informatics tool to objectively survey the field. We have used a quantitative text-mining technique, applied to published works in the field of digital health, to capture and analyse key approaches taken and the diseases areas where these have been applied. Key areas of research and application are shown to be cardiovascular, stroke, and hypertension; although the range seen is wide. We consider advances in digital health and telemedicine in light of the COVID-19 pandemic., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Geifman, Armes and Whetton.)
- Published
- 2023
- Full Text
- View/download PDF
29. HOXA9 forms a repressive complex with nuclear matrix-associated protein SAFB to maintain acute myeloid leukemia.
- Author
-
Agrawal-Singh S, Bagri J, Giotopoulos G, Azazi DMA, Horton SJ, Lopez CK, Anand S, Bach AS, Stedham F, Antrobus R, Houghton JW, Vassiliou GS, Sasca D, Yun H, Whetton AD, and Huntly BJP
- Subjects
- Humans, Proteomics, Homeodomain Proteins genetics, Homeodomain Proteins metabolism, Transcription Factors genetics, Nuclear Matrix-Associated Proteins, Chromatin, Receptors, Estrogen genetics, Receptors, Estrogen therapeutic use, Leukemia, Myeloid, Acute drug therapy, Matrix Attachment Region Binding Proteins genetics
- Abstract
HOXA9 is commonly upregulated in acute myeloid leukemia (AML), in which it confers a poor prognosis. Characterizing the protein interactome of endogenous HOXA9 in human AML, we identified a chromatin complex of HOXA9 with the nuclear matrix attachment protein SAFB. SAFB perturbation phenocopied HOXA9 knockout to decrease AML proliferation, increase differentiation and apoptosis in vitro, and prolong survival in vivo. Integrated genomic, transcriptomic, and proteomic analyses further demonstrated that the HOXA9-SAFB (H9SB)-chromatin complex associates with nucleosome remodeling and histone deacetylase (NuRD) and HP1γ to repress the expression of factors associated with differentiation and apoptosis, including NOTCH1, CEBPδ, S100A8, and CDKN1A. Chemical or genetic perturbation of NuRD and HP1γ-associated catalytic activity also triggered differentiation, apoptosis, and the induction of these tumor-suppressive genes. Importantly, this mechanism is operative in other HOXA9-dependent AML genotypes. This mechanistic insight demonstrates the active HOXA9-dependent differentiation block as a potent mechanism of disease maintenance in AML that may be amenable to therapeutic intervention by targeting the H9SB interface and/or NuRD and HP1γ activity., (© 2023 by The American Society of Hematology.)
- Published
- 2023
- Full Text
- View/download PDF
30. A Novel Blood Proteomic Signature for Prostate Cancer.
- Author
-
Muazzam A, Spick M, Cexus ONF, Geary B, Azhar F, Pandha H, Michael A, Reed R, Lennon S, Gethings LA, Plumb RS, Whetton AD, Geifman N, and Townsend PA
- Abstract
Prostate cancer is the most common malignant tumour in men. Improved testing for diagnosis, risk prediction, and response to treatment would improve care. Here, we identified a proteomic signature of prostate cancer in peripheral blood using data-independent acquisition mass spectrometry combined with machine learning. A highly predictive signature was derived, which was associated with relevant pathways, including the coagulation, complement, and clotting cascades, as well as plasma lipoprotein particle remodeling. We further validated the identified biomarkers against a second cohort, identifying a panel of five key markers (GP5, SERPINA5, ECM1, IGHG1, and THBS1) which retained most of the diagnostic power of the overall dataset, achieving an AUC of 0.91. Taken together, this study provides a proteomic signature complementary to PSA for the diagnosis of patients with localised prostate cancer, with the further potential for assessing risk of future development of prostate cancer. Data are available via ProteomeXchange with identifier PXD025484.
- Published
- 2023
- Full Text
- View/download PDF
31. THOC5 complexes with DDX5, DDX17, and CDK12 to regulate R loop structures and transcription elongation rate.
- Author
-
Polenkowski M, Allister AB, Burbano de Lara S, Pierce A, Geary B, El Bounkari O, Wiehlmann L, Hoffmann A, Whetton AD, Tamura T, and Tran DDH
- Abstract
THOC5, a member of the THO complex, is essential for the 3'processing of some inducible genes, the export of a subset of mRNAs and stem cell survival. Here we show that THOC5 depletion results in altered 3'cleavage of >50% of mRNAs and changes in RNA polymerase II binding across genes. THOC5 is recruited close to high-density polymerase II sites, suggesting that THOC5 is involved in transcriptional elongation. Indeed, measurement of elongation rates in vivo demonstrated decreased rates in THOC5-depleted cells. Furthermore, THOC5 is preferentially recruited to its target genes in slow polymerase II cells compared with fast polymerase II cells. Importantly chromatin-associated THOC5 interacts with CDK12 (a modulator of transcription elongation) and RNA helicases DDX5, DDX17, and THOC6 only in slow polymerase II cells. The CDK12/THOC5 interaction promotes CDK12 recruitment to R-loops in a THOC6-dependent manner. These data demonstrate a novel function of THOC5 in transcription elongation., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)
- Published
- 2022
- Full Text
- View/download PDF
32. High Throughput LC-MS Platform for Large Scale Screening of Bioactive Polar Lipids in Human Plasma and Serum.
- Author
-
Munjoma N, Isaac G, Muazzam A, Cexus O, Azhar F, Pandha H, Whetton AD, Townsend PA, Wilson ID, Gethings LA, and Plumb RS
- Subjects
- Male, Humans, Chromatography, Liquid methods, Reproducibility of Results, Phospholipids, Tandem Mass Spectrometry methods, Lipidomics
- Abstract
Lipids play a key role in many biological processes, and their accurate measurement is critical to unraveling the biology of diseases and human health. A high throughput HILIC-based (LC-MS) method for the semiquantitative screening of over 2000 lipids, based on over 4000 MRM transitions, was devised to produce an accessible and robust lipidomic screen for phospholipids in human plasma/serum. This methodology integrates many of the advantages of global lipid analysis with those of targeted approaches. Having used the method as an initial "wide class" screen, it can then be easily adapted for a more targeted analysis and quantification of key, dysregulated lipids. Robustness was assessed using 1550 continuous injections of plasma extracts onto a single column and via the evaluation of columns from 5 different batches of stationary phase. Initial screens in positive (239 lipids, 431 MRM transitions) and negative electrospray ionization (ESI) mode (232 lipids, 446 MRM transitions) were assessed for reproducibility, sensitivity, and dynamic range using analysis times of 8 min. The total number of lipids monitored using these screening methods was 433 with an overlap of 38 lipids in both modes. A polarity switching method for accurate quantification, using the same LC conditions, was assessed for intra- and interday reproducibility, accuracy, dynamic range, stability, carryover, dilution integrity, and matrix interferences and found to be acceptable. This polarity switching method was then applied to lipids important in the stratification of human prostate cancer samples.
- Published
- 2022
- Full Text
- View/download PDF
33. Multi-Omics Reveals Mechanisms of Partial Modulation of COVID-19 Dysregulation by Glucocorticoid Treatment.
- Author
-
Spick M, Campbell A, Baricevic-Jones I, von Gerichten J, Lewis HM, Frampas CF, Longman K, Stewart A, Dunn-Walters D, Skene DJ, Geifman N, Whetton AD, and Bailey MJ
- Subjects
- Humans, Proteomics methods, Hydrocortisone, Metabolomics methods, Amino Acids metabolism, Tyrosine, Arginine, Bile Acids and Salts, Glucocorticoids pharmacology, Glucocorticoids therapeutic use, COVID-19 Drug Treatment
- Abstract
Treatments for COVID-19 infections have improved dramatically since the beginning of the pandemic, and glucocorticoids have been a key tool in improving mortality rates. The UK's National Institute for Health and Care Excellence guidance is for treatment to be targeted only at those requiring oxygen supplementation, however, and the interactions between glucocorticoids and COVID-19 are not completely understood. In this work, a multi-omic analysis of 98 inpatient-recruited participants was performed by quantitative metabolomics (using targeted liquid chromatography-mass spectrometry) and data-independent acquisition proteomics. Both 'omics datasets were analysed for statistically significant features and pathways differentiating participants whose treatment regimens did or did not include glucocorticoids. Metabolomic differences in glucocorticoid-treated patients included the modulation of cortisol and bile acid concentrations in serum, but no alleviation of serum dyslipidemia or increased amino acid concentrations (including tyrosine and arginine) in the glucocorticoid-treated cohort relative to the untreated cohort. Proteomic pathway analysis indicated neutrophil and platelet degranulation as influenced by glucocorticoid treatment. These results are in keeping with the key role of platelet-associated pathways and neutrophils in COVID-19 pathogenesis and provide opportunity for further understanding of glucocorticoid action. The findings also, however, highlight that glucocorticoids are not fully effective across the wide range of 'omics dysregulation caused by COVID-19 infections.
- Published
- 2022
- Full Text
- View/download PDF
34. HMG20B stabilizes association of LSD1 with GFI1 on chromatin to confer transcription repression and leukemia cell differentiation block.
- Author
-
Maiques-Diaz A, Nicosia L, Basma NJ, Romero-Camarero I, Camera F, Spencer GJ, Amaral FMR, Simeoni F, Wingelhofer B, Williamson AJK, Pierce A, Whetton AD, and Somervaille TCP
- Subjects
- Humans, Cell Differentiation genetics, Chromatin genetics, DNA-Binding Proteins genetics, DNA-Binding Proteins metabolism, Transcription Factors genetics, Transcription Factors metabolism, Histone Demethylases metabolism, Leukemia, Myeloid, Acute genetics, Leukemia, Myeloid, Acute metabolism
- Abstract
Pharmacologic inhibition of LSD1 induces molecular and morphologic differentiation of blast cells in acute myeloid leukemia (AML) patients harboring MLL gene translocations. In addition to its demethylase activity, LSD1 has a critical scaffolding function at genomic sites occupied by the SNAG domain transcription repressor GFI1. Importantly, inhibitors block both enzymatic and scaffolding activities, in the latter case by disrupting the protein:protein interaction of GFI1 with LSD1. To explore the wider consequences of LSD1 inhibition on the LSD1 protein complex we applied mass spectrometry technologies. We discovered that the interaction of the HMG-box protein HMG20B with LSD1 was also disrupted by LSD1 inhibition. Downstream investigations revealed that HMG20B is co-located on chromatin with GFI1 and LSD1 genome-wide; the strongest HMG20B binding co-locates with the strongest GFI1 and LSD1 binding. Functional assays demonstrated that HMG20B depletion induces leukemia cell differentiation and further revealed that HMG20B is required for the transcription repressor activity of GFI1 through stabilizing LSD1 on chromatin at GFI1 binding sites. Interaction of HMG20B with LSD1 is through its coiled-coil domain. Thus, HMG20B is a critical component of the GFI1:LSD1 transcription repressor complex which contributes to leukemia cell differentiation block., (© 2022. The Author(s).)
- Published
- 2022
- Full Text
- View/download PDF
35. Metabolomics Markers of COVID-19 Are Dependent on Collection Wave.
- Author
-
Lewis HM, Liu Y, Frampas CF, Longman K, Spick M, Stewart A, Sinclair E, Kasar N, Greener D, Whetton AD, Barran PE, Chen T, Dunn-Walters D, Skene DJ, and Bailey MJ
- Abstract
The effect of COVID-19 infection on the human metabolome has been widely reported, but to date all such studies have focused on a single wave of infection. COVID-19 has generated numerous waves of disease with different clinical presentations, and therefore it is pertinent to explore whether metabolic disturbance changes accordingly, to gain a better understanding of its impact on host metabolism and enable better treatments. This work used a targeted metabolomics platform (Biocrates Life Sciences) to analyze the serum of 164 hospitalized patients, 123 with confirmed positive COVID-19 RT-PCR tests and 41 providing negative tests, across two waves of infection. Seven COVID-19-positive patients also provided longitudinal samples 2-7 months after infection. Changes to metabolites and lipids between positive and negative patients were found to be dependent on collection wave. A machine learning model identified six metabolites that were robust in diagnosing positive patients across both waves of infection: TG (22:1_32:5), TG (18:0_36:3), glutamic acid (Glu), glycolithocholic acid (GLCA), aspartic acid (Asp) and methionine sulfoxide (Met-SO), with an accuracy of 91%. Although some metabolites (TG (18:0_36:3) and Asp) returned to normal after infection, glutamic acid was still dysregulated in the longitudinal samples. This work demonstrates, for the first time, that metabolic dysregulation has partially changed over the course of the pandemic, reflecting changes in variants, clinical presentation and treatment regimes. It also shows that some metabolic changes are robust across waves, and these can differentiate COVID-19-positive individuals from controls in a hospital setting. This research also supports the hypothesis that some metabolic pathways are disrupted several months after COVID-19 infection.
- Published
- 2022
- Full Text
- View/download PDF
36. RadBone: bone toxicity following pelvic radiotherapy - a prospective randomised controlled feasibility study evaluating a musculoskeletal health package in women with gynaecological cancers undergoing pelvic radiotherapy.
- Author
-
Chatzimavridou Grigoriadou V, Barraclough LH, Baricevic-Jones I, Bristow RG, Eden M, Haslett K, Johnson K, Kochhar R, Merchant Z, Moore J, O'Connell S, Taylor S, Westwood T, Whetton AD, Yorke J, and Higham CE
- Subjects
- Diphosphonates, Feasibility Studies, Female, Humans, Prospective Studies, Research Design, Genital Neoplasms, Female radiotherapy
- Abstract
Introduction: Patients receiving radiotherapy are at risk of developing radiotherapy-related insufficiency fractures, which are associated with increased morbidity and pose a significant burden to patients' quality of life and to the health system. Therefore, effective preventive techniques are urgently required. The RadBone randomised controlled trial (RCT) aims to determine the feasibility and acceptability of a musculoskeletal health package (MHP) intervention in women undergoing pelvic radiotherapy for gynaecological malignancies and to preliminary explore clinical effectiveness of the intervention., Methods and Analysis: The RadBone RCT will evaluate the addition to standard care of an MHP consisting of a physical assessment of the musculoskeletal health, a 3-month prehabilitation personalised exercise package, as well as an evaluation of the fracture risk and if required the prescription of appropriate bone treatment including calcium, vitamin D and-for high-risk individuals-bisphosphonates. Forty participants will be randomised in each group (MHP or observation) and will be followed for 18 months. The primary outcome of this RCT will be feasibility, including the eligibility, screening and recruitment rate, intervention fidelity and attrition rates; acceptability and health economics. Clinical effectiveness and bone turnover markers will be evaluated as secondary outcomes., Ethics and Dissemination: This study has been approved by the Greater Manchester East Research Ethics Committee (Reference: 20/NW/0410, November 2020). The results will be published in peer-reviewed journals, will be presented in national and international conferences and will be communicated to relevant stakeholders. Moreover, a plain English report will be shared with the study participants, patients' organisations and media., Trial Registration Number: NCT04555317., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)
- Published
- 2022
- Full Text
- View/download PDF
37. Combination of curaxin and tyrosine kinase inhibitors display enhanced killing of primitive Chronic Myeloid Leukaemia cells.
- Author
-
Pearson S, Whetton AD, and Pierce A
- Subjects
- Drug Resistance, Neoplasm, Fusion Proteins, bcr-abl genetics, Humans, Neoplastic Stem Cells, Oncogenes, Protein Kinase Inhibitors pharmacology, Protein Kinase Inhibitors therapeutic use, Protein-Tyrosine Kinases, Leukemia, Myelogenous, Chronic, BCR-ABL Positive drug therapy, Leukemia, Myelogenous, Chronic, BCR-ABL Positive genetics
- Abstract
Despite the big increase in precision medicine targeted therapies developing curative treatments for many cancers is still a major challenge due mainly to the development of drug resistance in cancer stem cells. The cancer stem cells are constantly evolving to survive and targeted drug treatment often increases the selective pressure on these cells from which the disease develops. Chronic myeloid leukaemia is a paradigm of cancer stem cell research. Targeted therapies to the causative oncogene, BCR/ABL, have been developed but drug resistance remains a problem. The introduction of tyrosine kinase inhibitors targeting BCR/ABL were transformative in the management of CML. However, patients are rarely cured as the tyrosine kinase inhibitors fail to eradicate the leukaemic stem cell which often leads to loss of response to therapy as drug resistance develops and progression to more fatal forms of acute leukaemia occurs. New treatment strategies targeting other entities within the leukemic stem cell either alone or in combination with tyrosine kinase are therefore required. Drawing on our previous published work on the development of potential novel targets in CML and other myeloproliferative diseases along with analysis of the facilitates chromatin transcription (FACT) complex in CML we hypothesised that curaxin, a drug that targets the FACT complex and is in clinical trial for the treatment of other cancers, could be of use in the treatment of CML. We therefore assessed the curaxin CBL0137 as a new agent to extinguish CML primitive cells and show its ability to preferentially target CML cells compared to healthy control cells, especially in combination with clinically relevant tyrosine kinase inhibitors., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2022
- Full Text
- View/download PDF
38. Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.
- Author
-
Salie MT, Yang J, Ramírez Medina CR, Zühlke LJ, Chishala C, Ntsekhe M, Gitura B, Ogendo S, Okello E, Lwabi P, Musuku J, Mtaja A, Hugo-Hamman C, El-Sayed A, Damasceno A, Mocumbi A, Bode-Thomas F, Yilgwan C, Amusa GA, Nkereuwem E, Shaboodien G, Da Silva R, Lee DCH, Frain S, Geifman N, Whetton AD, Keavney B, and Engel ME
- Abstract
Background: Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics., Methods: We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case-control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses., Results: Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls., Conclusions: These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity., (© 2022. The Author(s).)
- Published
- 2022
- Full Text
- View/download PDF
39. A Prostate Cancer Proteomics Database for SWATH-MS Based Protein Quantification.
- Author
-
Muazzam A, Chiasserini D, Kelsall J, Geifman N, Whetton AD, and Townsend PA
- Abstract
Prostate cancer is the most frequent form of cancer in men, accounting for more than one-third of all cases. Current screening techniques, such as PSA testing used in conjunction with routine procedures, lead to unnecessary biopsies and the discovery of low-risk tumours, resulting in overdiagnosis. SWATH-MS is a well-established data-independent (DI) method requiring prior knowledge of targeted peptides to obtain valuable information from SWATH maps. In response to the growing need to identify and characterise protein biomarkers for prostate cancer, this study explored a spectrum source for targeted proteome analysis of blood samples. We created a comprehensive prostate cancer serum spectral library by combining data-dependent acquisition (DDA) MS raw files from 504 patients with low, intermediate, or high-grade prostate cancer and healthy controls, as well as 304 prostate cancer-related protein in silico assays. The spectral library contains 114,684 transitions, which equates to 18,479 peptides translated into 1227 proteins. The robustness and accuracy of the spectral library were assessed to boost confidence in the identification and quantification of prostate cancer-related proteins across an independent cohort, resulting in the identification of 404 proteins. This unique database can facilitate researchers to investigate prostate cancer protein biomarkers in blood samples. In the real-world use of the spectrum library for biomarker detection, using a signature of 17 proteins, a clear distinction between the validation cohort's pre- and post-treatment groups was observed. Data are available via ProteomeXchange with identifier PXD028651.
- Published
- 2021
- Full Text
- View/download PDF
40. Changes in the Proteome Profile of People Achieving Remission of Type 2 Diabetes after Bariatric Surgery.
- Author
-
Iqbal Z, Fachim HA, Gibson JM, Baricevic-Jones I, Campbell AE, Geary B, Donn RP, Hamarashid D, Syed A, Whetton AD, Soran H, and Heald AH
- Abstract
Bariatric surgery (BS) results in metabolic pathway recalibration. We have identified potential biomarkers in plasma of people achieving type 2 diabetes mellitus (T2DM) remission after BS. Longitudinal analysis was performed on plasma from 10 individuals following Roux-en-Y gastric bypass ( n = 7) or sleeve gastrectomy ( n = 3). Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was done on samples taken at 4 months before (baseline) and 6 and 12 months after BS. Four hundred sixty-seven proteins were quantified by SWATH-MS. Principal component analysis resolved samples from distinct time points after selection of key discriminatory proteins: 25 proteins were differentially expressed between baseline and 6 months post-surgery; 39 proteins between baseline and 12 months. Eight proteins (SHBG, TF, PRG4, APOA4, LRG1, HSPA4, EPHX2 and PGLYRP) were significantly different to baseline at both 6 and 12 months post-surgery. The panel of proteins identified as consistently different included peptides related to insulin sensitivity (SHBG increase), systemic inflammation (TF and HSPA4-both decreased) and lipid metabolism (APOA4 decreased). We found significant changes in the proteome for eight proteins at 6- and 12-months post-BS, and several of these are key components in metabolic and inflammatory pathways. These may represent potential biomarkers of remission of T2DM.
- Published
- 2021
- Full Text
- View/download PDF
41. Chd1 protects genome integrity at promoters to sustain hypertranscription in embryonic stem cells.
- Author
-
Bulut-Karslioglu A, Jin H, Kim YK, Cho B, Guzman-Ayala M, Williamson AJK, Hejna M, Stötzel M, Whetton AD, Song JS, and Ramalho-Santos M
- Subjects
- Animals, Chromatin metabolism, DNA Breaks, Double-Stranded, DNA Repair, DNA Topoisomerases, Type II metabolism, DNA, Ribosomal metabolism, DNA-Binding Proteins genetics, Mice, Poly-ADP-Ribose Binding Proteins metabolism, Signal Transduction, Transcription Initiation Site, DNA-Binding Proteins metabolism, Mouse Embryonic Stem Cells metabolism, Promoter Regions, Genetic, Transcription, Genetic
- Abstract
Stem and progenitor cells undergo a global elevation of nascent transcription, or hypertranscription, during key developmental transitions involving rapid cell proliferation. The chromatin remodeler Chd1 mediates hypertranscription in pluripotent cells but its mechanism of action remains poorly understood. Here we report a novel role for Chd1 in protecting genome integrity at promoter regions by preventing DNA double-stranded break (DSB) accumulation in ES cells. Chd1 interacts with several DNA repair factors including Atm, Parp1, Kap1 and Topoisomerase 2β and its absence leads to an accumulation of DSBs at Chd1-bound Pol II-transcribed genes and rDNA. Genes prone to DNA breaks in Chd1 KO ES cells are longer genes with GC-rich promoters, a more labile nucleosomal structure and roles in chromatin regulation, transcription and signaling. These results reveal a vulnerability of hypertranscribing stem cells to accumulation of endogenous DNA breaks, with important implications for developmental and cancer biology., (© 2021. The Author(s).)
- Published
- 2021
- Full Text
- View/download PDF
42. Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.
- Author
-
Njoku K, Chiasserini D, Geary B, Pierce A, Jones ER, Whetton AD, and Crosbie EJ
- Abstract
Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.
- Published
- 2021
- Full Text
- View/download PDF
43. Discovery and Evaluation of Protein Biomarkers as a Signature of Wellness in Late-Stage Cancer Patients in Early Phase Clinical Trials.
- Author
-
Geary B, Peat E, Dransfield S, Cook N, Thistlethwaite F, Graham D, Carter L, Hughes A, Krebs MG, and Whetton AD
- Abstract
TARGET (tumour characterisation to guide experimental targeted therapy) is a cancer precision medicine programme focused on molecular characterisation of patients entering early phase clinical trials. Performance status (PS) measures a patient's ability to perform a variety of activities. However, the quality of present algorithms to assess PS is limited and based on qualitative clinician assessment. Plasma samples from patients enrolled into TARGET were analysed using the mass spectrometry (MS) technique: sequential window acquisition of all theoretical fragment ion spectra (SWATH)-MS. SWATH-MS was used on a discovery cohort of 55 patients to differentiate patients into either a good or poor prognosis by creation of a Wellness Score (WS) that showed stronger prediction of overall survival ( p = 0.000551) compared to PS ( p = 0.001). WS was then tested against a validation cohort of 77 patients showing significant ( p = 0.000451) prediction of overall survival. WS in both sets had receiver operating characteristic curve area under the curve (AUC) values of 0.76 ( p = 0.002) and 0.67 ( p = 0.011): AUC of PS was 0.70 ( p = 0.117) and 0.55 ( p = 0.548). These signatures can now be evaluated further in larger patient populations to assess their utility in a clinical setting.
- Published
- 2021
- Full Text
- View/download PDF
44. Generation of a mouse SWATH-MS spectral library to quantify 10148 proteins involved in cell reprogramming.
- Author
-
Ulanga U, Russell M, Patassini S, Brazzatti J, Graham C, Whetton AD, and Graham RLJ
- Subjects
- Animals, Mass Spectrometry methods, Protein Array Analysis methods, Proteomics methods, Cellular Reprogramming, Databases, Protein, Mice genetics, Mice metabolism, Mice physiology, Proteome
- Abstract
Murine models are amongst the most widely used systems to study biology and pathology. Targeted quantitative proteomic analysis is a relatively new tool to interrogate such systems. Recently the need for relative quantification on hundreds to thousands of samples has driven the development of Data Independent Acquisition methods. One such technique is SWATH-MS, which in the main requires prior acquisition of mass spectra to generate an assay reference library. In stem cell research, it has been shown pluripotency can be induced starting with a fibroblast population. In so doing major changes in expressed proteins is inevitable. Here we have created a reference library to underpin such studies. This is inclusive of an extensively documented script to enable replication of library generation from the raw data. The documented script facilitates reuse of data and adaptation of the library to novel applications. The resulting library provides deep coverage of the mouse proteome. The library covers 29519 proteins (53% of the proteome) of which 7435 (13%) are supported by a proteotypic peptide.
- Published
- 2021
- Full Text
- View/download PDF
45. OptiMissP: A dashboard to assess missingness in proteomic data-independent acquisition mass spectrometry.
- Author
-
Arioli A, Dagliati A, Geary B, Peek N, Kalra PA, Whetton AD, and Geifman N
- Subjects
- Bias, Computer Simulation, Data Interpretation, Statistical, Humans, Models, Statistical, Mass Spectrometry methods, Proteomics methods, Software
- Abstract
Background: Missing values are a key issue in the statistical analysis of proteomic data. Defining the strategy to address missing values is a complex task in each study, potentially affecting the quality of statistical analyses., Results: We have developed OptiMissP, a dashboard to visually and qualitatively evaluate missingness and guide decision making in the handling of missing values in proteomics studies that use data-independent acquisition mass spectrometry. It provides a set of visual tools to retrieve information about missingness through protein densities and topology-based approaches, and facilitates exploration of different imputation methods and missingness thresholds., Conclusions: OptiMissP provides support for researchers' and clinicians' qualitative assessment of missingness in proteomic datasets in order to define study-specific strategies for the handling of missing values. OptiMissP considers biases in protein distributions related to the choice of imputation method and helps analysts to balance the information loss caused by low missingness thresholds and the noise introduced by selecting high missingness thresholds. This is complemented by topological data analysis which provides additional insight to the structure of the data and their missingness. We use an example in Chronic Kidney Disease to illustrate the main functionalities of OptiMissP., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2021
- Full Text
- View/download PDF
46. An Esrrb and Nanog Cell Fate Regulatory Module Controlled by Feed Forward Loop Interactions.
- Author
-
Sevilla A, Papatsenko D, Mazloom AR, Xu H, Vasileva A, Unwin RD, LeRoy G, Chen EY, Garrett-Bakelman FE, Lee DF, Trinite B, Webb RL, Wang Z, Su J, Gingold J, Melnick A, Garcia BA, Whetton AD, MacArthur BD, Ma'ayan A, and Lemischka IR
- Abstract
Cell fate decisions during development are governed by multi-factorial regulatory mechanisms including chromatin remodeling, DNA methylation, binding of transcription factors to specific loci, RNA transcription and protein synthesis. However, the mechanisms by which such regulatory "dimensions" coordinate cell fate decisions are currently poorly understood. Here we quantified the multi-dimensional molecular changes that occur in mouse embryonic stem cells (mESCs) upon depletion of Estrogen related receptor beta (Esrrb), a key pluripotency regulator. Comparative analyses of expression changes subsequent to depletion of Esrrb or Nanog, indicated that a system of interlocked feed-forward loops involving both factors, plays a central part in regulating the timing of mESC fate decisions. Taken together, our meta-analyses support a hierarchical model in which pluripotency is maintained by an Oct4-Sox2 regulatory module, while the timing of differentiation is regulated by a Nanog-Esrrb module., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Sevilla, Papatsenko, Mazloom, Xu, Vasileva, Unwin, LeRoy, Chen, Garrett-Bakelman, Lee, Trinite, Webb, Wang, Su, Gingold, Melnick, Garcia, Whetton, MacArthur, Ma’ayan and Lemischka.)
- Published
- 2021
- Full Text
- View/download PDF
47. Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer.
- Author
-
Njoku K, Campbell AE, Geary B, MacKintosh ML, Derbyshire AE, Kitson SJ, Sivalingam VN, Pierce A, Whetton AD, and Crosbie EJ
- Abstract
Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥30kg/m
2 and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC > 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m2 .- Published
- 2021
- Full Text
- View/download PDF
48. Proteomics and Informatics for Understanding Phases and Identifying Biomarkers in COVID-19 Disease.
- Author
-
Whetton AD, Preston GW, Abubeker S, and Geifman N
- Subjects
- Artificial Intelligence, Biomarkers analysis, COVID-19, Diagnosis, Computer-Assisted, Humans, Prognosis, SARS-CoV-2, Betacoronavirus, Coronavirus Infections blood, Coronavirus Infections diagnosis, Coronavirus Infections metabolism, Coronavirus Infections physiopathology, Pandemics, Pneumonia, Viral blood, Pneumonia, Viral diagnosis, Pneumonia, Viral metabolism, Pneumonia, Viral physiopathology, Proteomics
- Abstract
The emergence of novel coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has necessitated the urgent development of new diagnostic and therapeutic strategies. Rapid research and development, on an international scale, has already generated assays for detecting SARS-CoV-2 RNA and host immunoglobulins. However, the complexities of COVID-19 are such that fuller definitions of patient status, trajectory, sequelae, and responses to therapy are now required. There is accumulating evidence-from studies of both COVID-19 and the related disease SARS-that protein biomarkers could help to provide this definition. Proteins associated with blood coagulation (D-dimer), cell damage (lactate dehydrogenase), and the inflammatory response (e.g., C-reactive protein) have already been identified as possible predictors of COVID-19 severity or mortality. Proteomics technologies, with their ability to detect many proteins per analysis, have begun to extend these early findings. To be effective, proteomics strategies must include not only methods for comprehensive data acquisition (e.g., using mass spectrometry) but also informatics approaches via which to derive actionable information from large data sets. Here we review applications of proteomics to COVID-19 and SARS and outline how pipelines involving technologies such as artificial intelligence could be of value for research on these diseases.
- Published
- 2020
- Full Text
- View/download PDF
49. Urinary Biomarkers and Their Potential for the Non-Invasive Detection of Endometrial Cancer.
- Author
-
Njoku K, Chiasserini D, Jones ER, Barr CE, O'Flynn H, Whetton AD, and Crosbie EJ
- Abstract
Endometrial cancer is the most common malignancy of the female genital tract and its incidence is rising in parallel with the mounting prevalence of obesity. Early diagnosis has great potential to improve outcomes as treatment can be curative, especially for early stage disease. Current tests and procedures for diagnosis are limited by insufficient accuracy in some and unacceptable levels of invasiveness and discomfort in others. There has, therefore, been a growing interest in the search for sensitive and specific biomarkers for endometrial cancer detection based on non-invasive sampling methodologies. Urine, the prototype non-invasive sample, is attractive for biomarker discovery as it is easily accessible and can be collected repeatedly and in quantity. Identification of urinary biomarkers for endometrial cancer detection relies on the excretion of systemic biomarkers by the kidneys or urinary contamination by biomarkers shed from the uterus. In this review, we present the current standing of the search for endometrial cancer urinary biomarkers based on cytology, genomic, transcriptomic, proteomic, and metabolomic platforms. We summarize the biomarker candidates and highlight the challenges inherent in urinary biomarker discovery. We review the various technologies with promise for biomarker detection and assess these novel approaches for endometrial cancer biomarker research., (Copyright © 2020 Njoku, Chiasserini, Jones, Barr, O’Flynn, Whetton and Crosbie.)
- Published
- 2020
- Full Text
- View/download PDF
50. Novel manifestations of immune dysregulation and granule defects in gray platelet syndrome.
- Author
-
Sims MC, Mayer L, Collins JH, Bariana TK, Megy K, Lavenu-Bombled C, Seyres D, Kollipara L, Burden FS, Greene D, Lee D, Rodriguez-Romera A, Alessi MC, Astle WJ, Bahou WF, Bury L, Chalmers E, Da Silva R, De Candia E, Deevi SVV, Farrow S, Gomez K, Grassi L, Greinacher A, Gresele P, Hart D, Hurtaud MF, Kelly AM, Kerr R, Le Quellec S, Leblanc T, Leinøe EB, Mapeta R, McKinney H, Michelson AD, Morais S, Nugent D, Papadia S, Park SJ, Pasi J, Podda GM, Poon MC, Reed R, Sekhar M, Shalev H, Sivapalaratnam S, Steinberg-Shemer O, Stephens JC, Tait RC, Turro E, Wu JKM, Zieger B, Kuijpers TW, Whetton AD, Sickmann A, Freson K, Downes K, Erber WN, Frontini M, Nurden P, Ouwehand WH, Favier R, and Guerrero JA
- Subjects
- Biopsy, Blood Proteins genetics, Case-Control Studies, Cohort Studies, Cytoplasmic Granules metabolism, Diagnosis, Differential, Gene Frequency, Genetic Association Studies, Humans, Immune System physiology, Immune System Diseases blood, Immune System Diseases diagnosis, Immune System Diseases genetics, Immune System Diseases pathology, Mutation, Cytoplasmic Granules pathology, Genetic Heterogeneity, Gray Platelet Syndrome classification, Gray Platelet Syndrome genetics, Gray Platelet Syndrome immunology, Gray Platelet Syndrome pathology, Immune System pathology, Phenotype
- Abstract
Gray platelet syndrome (GPS) is a rare recessive disorder caused by biallelic variants in NBEAL2 and characterized by bleeding symptoms, the absence of platelet α-granules, splenomegaly, and bone marrow (BM) fibrosis. Due to the rarity of GPS, it has been difficult to fully understand the pathogenic processes that lead to these clinical sequelae. To discern the spectrum of pathologic features, we performed a detailed clinical genotypic and phenotypic study of 47 patients with GPS and identified 32 new etiologic variants in NBEAL2. The GPS patient cohort exhibited known phenotypes, including macrothrombocytopenia, BM fibrosis, megakaryocyte emperipolesis of neutrophils, splenomegaly, and elevated serum vitamin B12 levels. Novel clinical phenotypes were also observed, including reduced leukocyte counts and increased presence of autoimmune disease and positive autoantibodies. There were widespread differences in the transcriptome and proteome of GPS platelets, neutrophils, monocytes, and CD4 lymphocytes. Proteins less abundant in these cells were enriched for constituents of granules, supporting a role for Nbeal2 in the function of these organelles across a wide range of blood cells. Proteomic analysis of GPS plasma showed increased levels of proteins associated with inflammation and immune response. One-quarter of plasma proteins increased in GPS are known to be synthesized outside of hematopoietic cells, predominantly in the liver. In summary, our data show that, in addition to the well-described platelet defects in GPS, there are immune defects. The abnormal immune cells may be the drivers of systemic abnormalities such as autoimmune disease., (© 2020 by The American Society of Hematology.)
- Published
- 2020
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.