| 1. |
- Rawstron, Andy C., et al.
(författare)
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Monoclonal B-cell lymphocytosis in a hospital-based UK population and a rural Ugandan population : a cross-sectional study
- 2017
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Ingår i: The Lancet Haematology. - 2352-3026. ; 4:7, s. E334-E340
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Tidskriftsartikel (refereegranskat)abstract
- Background Reported incidence of B-cell malignancies shows substantial geographical variation, being more common in the Americas and Europe than in Africa. This variation might reflect differences in diagnostic capability, inherited susceptibility, and infectious exposures. Monoclonal B-cell lymphocytosis (MBL) is a precursor lesion that can be screened for in apparently healthy people, allowing comparison of prevalence across different populations independently of health-care provision. We aimed to compare the prevalence and phenotypic characteristics of MBL in age-and-sex-matched populations from rural Uganda and the UK. Methods In this cross-sectional study, we recruited volunteers aged at least 45 years who were seronegative for HIV-1 from the established Ugandan General Population Cohort and obtained their whole-blood samples. We also obtained blood samples from anonymised waste material of age-and-sex-matched individuals (aged >45 years, with a normal blood count and no history of cancer) in the UK. We used flow cytometry to determine the presence of MBL, defined according to standard diagnostic criteria, in the samples and compared differences in the proportion of cases with chronic lymphocytic leukaemia (CLL)-phenotype MBL and CD5-negative MBL, as well as differences in absolute monoclonal B-cell count between the two cohorts. Findings Between Jan 15 and Dec 18, 2012, we obtained samples from 302 Ugandan volunteers and 302 UK individuals who were matched by age and sex to the Ugandan population. Overall MBL prevalence was higher in the Ugandan participants (42 [14%] individuals) than in the UK cohort (25 [8%]; p=0.038). CLL-phenotype MBL was detected in three (1%) Ugandan participants and 21 (7%) UK participants (p=0.00021); all three Ugandan participants had absolute monoclonal B-cell count below one cell per mu L, whereas the 21 UK participants had a median absolute number of circulating neoplastic cells of 4.6 (IQR 2-12) cells per mu L. The prevalence of CD5-negative MBL was higher in the Ugandan cohort (41 [14%], of whom two [5%] also had CLL-phenotype MBL) than in the UK cohort (six [2%], of whom two [33%] also had CLL-phenotype MBL; p<0.0001), but the median absolute B-cell count was similar (227 [IQR 152-345] cells per mu L in the Ugandan cohort vs 135 [105-177] cells per mu L in the UK cohort; p=0.13). Interpretation MBL is common in both Uganda and the UK, but the substantial phenotypic differences might reflect fundamental differences in the pathogenesis of B-cell lymphoproliferative disorders.
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| 2. |
- Clarke, Emily L., et al.
(författare)
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Image analysis of cutaneous melanoma histology: a systematic review and meta-analysis
- 2023
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- The current subjective histopathological assessment of cutaneous melanoma is challenging. The application of image analysis algorithms to histological images may facilitate improvements in workflow and prognostication. To date, several individual algorithms applied to melanoma histological images have been reported with variations in approach and reported accuracies. Histological digital images can be created using a camera mounted on a light microscope, or through whole slide image (WSI) generation using a whole slide scanner. Before any such tool could be integrated into clinical workflow, the accuracy of the technology should be carefully evaluated and summarised. Therefore, the objective of this review was to evaluate the accuracy of existing image analysis algorithms applied to digital histological images of cutaneous melanoma.Database searching of PubMed and Embase from inception to 11th March 2022 was conducted alongside citation checking and examining reports from organisations. All studies reporting accuracy of any image analysis applied to histological images of cutaneous melanoma, were included. The reference standard was any histological assessment of haematoxylin and eosin-stained slides and/or immunohistochemical staining. Citations were independently deduplicated and screened by two review authors and disagreements were resolved through discussion. The data was extracted concerning study demographics; type of image analysis; type of reference standard; conditions included and test statistics to construct 2 x 2 tables. Data was extracted in accordance with our protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Diagnostic Test Accuracy (PRISMA-DTA) Statement. A bivariate random-effects meta-analysis was used to estimate summary sensitivities and specificities with 95% confidence intervals (CI). Assessment of methodological quality was conducted using a tailored version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The primary outcome was the pooled sensitivity and specificity of image analysis applied to cutaneous melanoma histological images. Sixteen studies were included in the systematic review, representing 4,888 specimens. Six studies were included in the meta-analysis. The mean sensitivity and specificity of automated image analysis algorithms applied to melanoma histological images was 90% (CI 82%, 95%) and 92% (CI 79%, 97%), respectively. Based on limited and heterogeneous data, image analysis appears to offer high accuracy when applied to histological images of cutaneous melanoma. However, given the early exploratory nature of these studies, further development work is necessary to improve their performance.
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| 3. |
- Godson, Lucy, et al.
(författare)
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Immune subtyping of melanoma whole slide images using multiple instance learning
- 2024
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Ingår i: Medical Image Analysis. - : ELSEVIER. - 1361-8415 .- 1361-8423. ; 93
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Tidskriftsartikel (refereegranskat)abstract
- Determining early-stage prognostic markers and stratifying patients for effective treatment are two key challenges for improving outcomes for melanoma patients. Previous studies have used tumour transcriptome data to stratify patients into immune subgroups, which were associated with differential melanoma specific survival and potential predictive biomarkers. However, acquiring transcriptome data is a time-consuming and costly process. Moreover, it is not routinely used in the current clinical workflow. Here, we attempt to overcome this by developing deep learning models to classify gigapixel haematoxylin and eosin (H&E) stained pathology slides, which are well established in clinical workflows, into these immune subgroups. We systematically assess six different multiple instance learning (MIL) frameworks, using five different image resolutions and three different feature extraction methods. We show that pathology-specific self-supervised models using 10x resolution patches generate superior representations for the classification of immune subtypes. In addition, in a primary melanoma dataset, we achieve a mean area under the receiver operating characteristic curve (AUC) of 0.80 for classifying histopathology images into 'high' or 'low immune' subgroups and a mean AUC of 0.82 in an independent TCGA melanoma dataset. Furthermore, we show that these models are able to stratify patients into 'high' and 'low immune' subgroups with significantly different melanoma specific survival outcomes (log rank test, P < 0.005). We anticipate that MIL methods will allow us to find new biomarkers of high importance, act as a tool for clinicians to infer the immune landscape of tumours and stratify patients, without needing to carry out additional expensive genetic tests.
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| 4. |
- Tran, Thao Thanh, et al.
(författare)
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Inhibition of the master regulator of Listeria monocytogenes virulence enables bacterial clearance from spacious replication vacuoles in infected macrophages
- 2022
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Ingår i: PLoS Pathogens. - : Public Library Science. - 1553-7366 .- 1553-7374. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- A hallmark of Listeria (L.) monocytogenes pathogenesis is bacterial escape from maturing entry vacuoles, which is required for rapid bacterial replication in the host cell cytoplasm and cell-to-cell spread. The bacterial transcriptional activator PrfA controls expression of key virulence factors that enable exploitation of this intracellular niche. The transcriptional activity of PrfA within infected host cells is controlled by allosteric coactivation. Inhibitory occupation of the coactivator site has been shown to impair PrfA functions, but consequences of PrfA inhibition for L. monocytogenes infection and pathogenesis are unknown. Here we report the crystal structure of PrfA with a small molecule inhibitor occupying the coactivator site at 2.0 Å resolution. Using molecular imaging and infection studies in macrophages, we demonstrate that PrfA inhibition prevents the vacuolar escape of L. monocytogenes and enables extensive bacterial replication inside spacious vacuoles. In contrast to previously described spacious Listeria-containing vacuoles, which have been implicated in supporting chronic infection, PrfA inhibition facilitated progressive clearance of intracellular L. monocytogenes from spacious vacuoles through lysosomal degradation. Thus, inhibitory occupation of the PrfA coactivator site facilitates formation of a transient intravacuolar L. monocytogenes replication niche that licenses macrophages to effectively eliminate intracellular bacteria. Our findings encourage further exploration of PrfA as a potential target for antimicrobials and highlight that intra-vacuolar residence of L. monocytogenes in macrophages is not inevitably tied to bacterial persistence.
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