| 1. |
- Hess, Timo, et al.
(författare)
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Dissecting the genetic heterogeneity of gastric cancer
- 2023
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 92
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture.Methods: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO.Findings: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level.Interpretation: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO.
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| 2. |
- Spak, Emma, 1977, et al.
(författare)
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Angiotensin II receptor expression following intestinal transplantation in mice.
- 2006
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Ingår i: The Journal of surgical research. - : Elsevier BV. - 0022-4804. ; 135:1, s. 144-9
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: To further improve the success rate of intestinal transplantation there is a need to find early appearing indicators of rejection. The specific aim of this study was to compare Angiotensin (Ang) II type 1 receptor and Ang II type 2 receptor expression in relation to histological signs of rejection. METHODS: Mice of the C57BL6 strain with syngeneic intestinal grafts were compared to mice subjected to allogeneic intestinal transplantation with BalbC strain as donors. Local expression of Ang II type 1 and 2 receptor was evaluated using rt-PCR and Western blot and compared to histological picture in grafts and native intestine. RESULTS: The Ang II type 2 receptor protein expression was markedly up-regulated in the allogeneically transplanted graft from day 1 postoperatively. Histological signs of rejection were not seen until day 6. CONCLUSION: Intestinal allograft transplantation in mice is associated with a marked up-regulation of the Ang II type 2 receptor. However, the detailed role of the renin-angiotensin system in the immune rejection following intestinal transplantation remains to be clarified.
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| 3. |
- Agreus, Lars, et al.
(författare)
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Towards a healthy stomach? : Helicobacter pylori prevalence has dramatically decreased over 23 years in adults in a Swedish community
- 2016
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Ingår i: United European Gastroenterology journal. - : Wiley. - 2050-6406 .- 2050-6414. ; 4:5, s. 686-696
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Tidskriftsartikel (refereegranskat)abstract
- Background In Western countries the prevalence of Helicobacter pylori (H. pylori) infection may be declining but there is a lack of recent longitudinal population studies. We evaluated the changing epidemiology over a 23-year period in Sweden.Materials and methods In 1989, the validated Abdominal Symptom Questionnaire (ASQ) was mailed to a random sample of inhabitants (ages 22-80 years) in a Swedish community, and 1097 (87%) responded. H. pylori serology was analysed in a representative subsample (n=145). Twenty-three years later, the ASQ was mailed again using similar selection criteria, and 388 out of 1036 responders had an upper endoscopy with assessment of H. pylori and corpus atrophy status.Results The prevalence of positive H. pylori serology decreased from 37.9% (1989) to 15.8% (2012), corresponding to a decrease in odds of 75% per decade (odds ratio (OR): 0.25; 95% confidence interval (CI): 0.11-0.59, p=0.001) independent of age, gender, body mass index (BMI) and level of education, with a pattern consistent with a birth cohort effect. The prevalence increased with increasing age (p=0.001). The prevalence of H. pylori on histology in 2012 was 11.4% (95% CI 8.6-15.0). The prevalence of corpus atrophy on serology and/or histology in 2012 was 3.2% (95% CI 1.8-5.5); all cases were 57 years old.Conclusion The stomach is healthier in 2012 compared with 1989. H. pylori prevalence in adults has decreased over the last two decades to a level where clinical management might be affected.
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| 4. |
- Aro, Pertti, et al.
(författare)
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Use of tobacco products and gastrointestinal morbidity : an endoscopic population-based study (the Kalixanda study)
- 2010
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Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 25:10, s. 741-750
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Tidskriftsartikel (refereegranskat)abstract
- The impact of snus (smokeless tobacco or snuff) on gastrointestinal symptoms and pathological findings is largely unknown. The authors aimed to investigate whether the exposure to different forms of tobacco influences upper gastrointestinal symptoms, histology and frequency of Helicobacter pylori infection. A random sample (n = 2,860) of the adult population of two northern Swedish municipalities Kalix and Haparanda (n = 21,610) was surveyed between December 1998 and June 2001 using a validated postal questionnaire assessing gastrointestinal symptoms (response rate 74.2%, n = 2,122) (The Kalixanda Study). A random sub-sample (n = 1,001) of the responders was invited to undergo an esophagogastroduodenoscopy (participation rate 73.3%) including biopsies, Helicobacter pylori culture and serology and symptom assessment and exploration of present and past use of tobacco products. No symptom groups were associated with snus use. Snus users had a significantly higher prevalence of macroscopic esophagitis univariately but snus use was not associated with esophagitis in multivariate analysis. Snus use was associated with basal cell hyperplasia (OR = 1.74, 95% CI: 1.02, 3.00) and with elongation of papillae (OR = 1.79, 95% CI: 1.05-3.05) of the squamous epithelium at the esophago-gastric junction. Current smoking cigarettes was associated with overall peptic ulcer disease (OR = 2.32, 95% CI: 1.04, 5.19) whereas snus use was not. There were no significant association between current Helicobacter pylori infection and different tobacco product user groups. Snus significantly alters the histology of the distal esophagus but does not impact on gastrointestinal symptoms or peptic ulcer disease.
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| 5. |
- Baldaque-Silva, Francisco, et al.
(författare)
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Endoscopic assessment and grading of Barrett's esophagus using magnification endoscopy and narrow band imaging: Impact of structured learning and experience on the accuracy of the Amsterdam classification system
- 2013
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Ingår i: Scandinavian Journal of Gastroenterology. - : Informa UK Limited. - 1502-7708 .- 0036-5521. ; 48:2, s. 160-167
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Tidskriftsartikel (refereegranskat)abstract
- Objective. Several classification systems have been launched to characterize Barrett's esophagus (BE) mucosa using magnification endoscopy with narrow band imaging (ME-NBI). The good accuracy and interobserver agreement described in the early reports were not reproduced subsequently. Recently, we reported somewhat higher accuracy of the classification developed by the Amsterdam group. The critical question then formulated was whether a structured learning program and the level of experience would affect the clinical usefulness of this classification. Material & methods: Two hundred and nine videos were prospectively captured from patients with BE using ME-NBI. From these, 70 were randomly selected and evaluated by six endoscopists with different levels of expertise, using a dedicated software application. First, an educational set was studied. Thereafter, the 70 test videos were evaluated. After classification of each video, the respective histological feedback was automatically given. Results. Within the learning process, there was a decrease in the time needed for evaluation and an increase in the certainty of prediction. The accuracy did not increase with the learning process. The sensitivity for detection of intestinal metaplasia ranged between 39% and 57%, and for neoplasia between 62% and 90%, irrespective of assessor's expertise. The kappa coefficient for the interobserver agreement ranged from 0.25 to 0.30 for intestinal metaplasia, and from 0.39 to 0.48 for neoplasia. Conclusion: Using a dedicated learning program, the ME-NBI Amsterdam classification system is suboptimal in terms of accuracy and inter- and intraobserver agreements. These results reiterate the questionable utility of corresponding classification system in clinical routine practice.
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| 6. |
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| 7. |
- Bokhorst, John-Melle, et al.
(författare)
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Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images
- 2023
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of characterization and reporting on resected biopsies, including polyps, the numbers of which are increasing as a result of CRC population screening programs ongoing in many countries all around the globe. Here, we present an approach to address two major challenges in the automated assessment of CRC histopathology whole-slide images. We present an AI-based method to segment multiple (n=14 ) tissue compartments in the H &E-stained whole-slide image, which provides a different, more perceptible picture of tissue morphology and composition. We test and compare a panel of state-of-the-art loss functions available for segmentation models, and provide indications about their use in histopathology image segmentation, based on the analysis of (a) a multi-centric cohort of CRC cases from five medical centers in the Netherlands and Germany, and (b) two publicly available datasets on segmentation in CRC. We used the best performing AI model as the basis for a computer-aided diagnosis system that classifies colon biopsies into four main categories that are relevant pathologically. We report the performance of this system on an independent cohort of more than 1000 patients. The results show that with a good segmentation network as a base, a tool can be developed which can support pathologists in the risk stratification of colorectal cancer patients, among other possible uses. We have made the segmentation model available for research use on .
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| 8. |
- Bokhorst, John-Melle, et al.
(författare)
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Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer
- 2023
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Ingår i: Modern Pathology. - : ELSEVIER SCIENCE INC. - 0893-3952 .- 1530-0285. ; 36:9
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Tidskriftsartikel (refereegranskat)abstract
- Tumor budding (TB), the presence of single cells or small clusters of up to 4 tumor cells at the invasive front of colorectal cancer (CRC), is a proven risk factor for adverse outcomes. International definitions are necessary to reduce interobserver variability. According to the current international guidelines, hotspots at the invasive front should be counted in hematoxylin and eosin (H & E)-stained slides. This is time-consuming and prone to interobserver variability; therefore, there is a need for computer-aided diagnosis solutions. In this study, we report an artificial intelligence-based method for detecting TB in H & E-stained whole slide images. We propose a fully automated pipeline to identify the tumor border, detect tumor buds, characterize them based on the number of tumor cells, and produce a TB density map to identify the TB hotspot. The method outputs the TB count in the hotspot as a computational biomarker. We show that the proposed automated TB detection workflow performs on par with a panel of 5 pathologists at detecting tumor buds and that the hotspot-based TB count is an independent prognosticator in both the univariate and the multivariate analysis, validated on a cohort of n 1/4 981 patients with CRC. Computer-aided detection of tumor buds based on deep learning can perform on par with expert pathologists for the detection and quantification of tumor buds in H & E-stained CRC histopathology slides, strongly facilitating the introduction of budding as an independent prognosticator in clinical routine and clinical trials. & COPY; 2023 THE AUTHORS. Published by Elsevier Inc. on behalf of the United States & Canadian Academy of Pathology. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).
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| 9. |
- Bokhorst, John-Melle, et al.
(författare)
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Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer
- 2023
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Ingår i: Cancers. - : MDPI. - 2072-6694. ; 15:7
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Tidskriftsartikel (refereegranskat)abstract
- Tumor budding is a histopathological biomarker associated with metastases and adverse survival outcomes in colorectal carcinoma (CRC) patients. It is characterized by the presence of single tumor cells or small clusters of cells within the tumor or at the tumor-invasion front. In order to obtain a tumor budding score for a patient, the region with the highest tumor bud density must first be visually identified by a pathologist, after which buds will be counted in the chosen hotspot field. The automation of this process will expectedly increase efficiency and reproducibility. Here, we present a deep learning convolutional neural network model that automates the above procedure. For model training, we used a semi-supervised learning method, to maximize the detection performance despite the limited amount of labeled training data. The model was tested on an independent dataset in which human- and machine-selected hotspots were mapped in relation to each other and manual and machine detected tumor bud numbers in the manually selected fields were compared. We report the results of the proposed method in comparison with visual assessment by pathologists. We show that the automated tumor bud count achieves a prognostic value comparable with visual estimation, while based on an objective and reproducible quantification. We also explore novel metrics to quantify buds such as density and dispersion and report their prognostic value. We have made the model available for research use on the grand-challenge platform.
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| 10. |
- Elfvin, Anders, 1971, et al.
(författare)
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Helicobacter pylori induces gastritis and intestinal metaplasia but no gastric adenocarcinoma in Mongolian gerbils.
- 2005
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Ingår i: Scandinavian journal of gastroenterology. - : Informa UK Limited. - 0036-5521 .- 1502-7708. ; 40:11, s. 1313-20
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: The Mongolian gerbil is considered as the model of choice when studying adenocarcinoma related to Helicobacter pylori infection. The purpose of this study was to compare two different H. pylori strains and elucidate whether adenocarcinomas developed in gerbils. MATERIAL AND METHODS: Male gerbils were separated into three groups: one control and two groups infected with two different strains of H. pylori, TN2GF4 and SS1. At 3, 6, 12 or 18 months after inoculation 5 animals from each group were sacrificed. The stomach was used for culture, and for histology. RESULTS: Inflammation was seen after 3 months in all the infected animals. In the controls no pathology was found at any time. Intestinal metaplasia was found in both the infected groups. Glands buried in the submucusal layer, changes that might be misinterpreted as adenocarcinoma, were found in 10% of the SS1 and in 65% of the TN2GF4 animals. Adenocarcinoma was not found in any of the gerbils. CONCLUSIONS: All studies claiming to have found H. pylori-induced adenocarcinomas in gerbils describe atypical glands penetrating into the muscularis propria and interpret these as invasive growths due to cancer. An alternative interpretation is that the deranged glandular structures grow in and below the submucosa. It is suggested that atypical glands in the muscularis layer are not enough as a diagnostic criterion for gastric adenocarcinoma. It is concluded that adenocarcinoma has not yet been shown convincingly to develop in Mongolian gerbils infected with H. pylori. Nevertheless, it is a model well suited for studying gastritis, gastric ulcer and premalignant changes such as metaplasia.
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