| 1. |
- Nesti, Cedric, et al.
(author)
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Hemicolectomy versus appendectomy for patients with appendiceal neuroendocrine tumours 1-2 cm in size : a retrospective, Europe-wide, pooled cohort study
- 2023
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In: The Lancet Oncology. - : Elsevier. - 1470-2045 .- 1474-5488. ; 24:2, s. 187-194
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Journal article (peer-reviewed)abstract
- BackgroundAwareness of the potential global overtreatment of patients with appendiceal neuroendocrine tumours (NETs) of 1–2 cm in size by performing oncological resections is increasing, but the rarity of this tumour has impeded clear recommendations to date. We aimed to assess the malignant potential of appendiceal NETs of 1–2 cm in size in patients with or without right-sided hemicolectomy.MethodsIn this retrospective cohort study, we pooled data from 40 hospitals in 15 European countries for patients of any age and Eastern Cooperative Oncology Group performance status with a histopathologically confirmed appendiceal NET of 1–2 cm in size who had a complete resection of the primary tumour between Jan 1, 2000, and Dec 31, 2010. Patients either had an appendectomy only or an appendectomy with oncological right-sided hemicolectomy or ileocecal resection. Predefined primary outcomes were the frequency of distant metastases and tumour-related mortality. Secondary outcomes included the frequency of regional lymph node metastases, the association between regional lymph node metastases and histopathological risk factors, and overall survival with or without right-sided hemicolectomy. Cox proportional hazards regression was used to estimate the relative all-cause mortality hazard associated with right-sided hemicolectomy compared with appendectomy alone. This study is registered with ClinicalTrials.gov, NCT03852693.Findings282 patients with suspected appendiceal tumours were identified, of whom 278 with an appendiceal NET of 1–2 cm in size were included. 163 (59%) had an appendectomy and 115 (41%) had a right-sided hemicolectomy, 110 (40%) were men, 168 (60%) were women, and mean age at initial surgery was 36·0 years (SD 18·2). Median follow-up was 13·0 years (IQR 11·0–15·6). After centralised histopathological review, appendiceal NETs were classified as a possible or probable primary tumour in two (1%) of 278 patients with distant peritoneal metastases and in two (1%) 278 patients with distant metastases in the liver. All metastases were diagnosed synchronously with no tumour-related deaths during follow-up. Regional lymph node metastases were found in 22 (20%) of 112 patients with right-sided hemicolectomy with available data. On the basis of histopathological risk factors, we estimated that 12·8% (95% CI 6·5 –21·1) of patients undergoing appendectomy probably had residual regional lymph node metastases. Overall survival was similar between patients with appendectomy and right-sided hemicolectomy (adjusted hazard ratio 0·88 [95% CI 0·36–2·17]; p=0·71).InterpretationThis study provides evidence that right-sided hemicolectomy is not indicated after complete resection of an appendiceal NET of 1–2 cm in size by appendectomy, that regional lymph node metastases of appendiceal NETs are clinically irrelevant, and that an additional postoperative exclusion of metastases and histopathological evaluation of risk factors is not supported by the presented results. These findings should inform consensus best practice guidelines for this patient cohort.
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| 2. |
- Bokhorst, John-Melle, et al.
(author)
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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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In: Modern Pathology. - : ELSEVIER SCIENCE INC. - 0893-3952 .- 1530-0285. ; 36:9
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Journal article (peer-reviewed)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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| 3. |
- Bokhorst, John-Melle, et al.
(author)
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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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In: Cancers. - : MDPI. - 2072-6694. ; 15:7
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Journal article (peer-reviewed)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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| 4. |
- Galon, Jerome, et al.
(author)
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Cancer classification using the Immunoscore : a worldwide task force
- 2012
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In: Journal of Translational Medicine. - : Springer Science and Business Media LLC. - 1479-5876 .- 1479-5876. ; 10, s. 205-
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Research review (peer-reviewed)abstract
- Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ` Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).
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| 5. |
- Galon, Jerome, et al.
(author)
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Towards the introduction of the 'Immunoscore' in the classification of malignant tumours
- 2014
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In: Journal of Pathology. - : Wiley-Blackwell. - 0022-3417 .- 1096-9896. ; 232:2, s. 199-209
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Research review (peer-reviewed)abstract
- The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named Immunoscore' has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).
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| 6. |
- Haddad, Tariq Sami, et al.
(author)
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Improving tumor budding reporting in colorectal cancer: a Delphi consensus study
- 2021
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In: Virchows Archiv. - : SPRINGER. - 0945-6317 .- 1432-2307. ; 479:3, s. 459-469
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Journal article (peer-reviewed)abstract
- Tumor budding is a long-established independent adverse prognostic marker in colorectal cancer, yet methods for its assessment have varied widely. In an effort to standardize its reporting, a group of experts met in Bern, Switzerland, in 2016 to reach consensus on a single, international, evidence-based method for tumor budding assessment and reporting (International Tumor Budding Consensus Conference [ITBCC]). Tumor budding assessment using the ITBCC criteria has been validated in large cohorts of cancer patients and incorporated into several international colorectal cancer pathology and clinical guidelines. With the wider reporting of tumor budding, new issues have emerged that require further clarification. To better inform researchers and health-care professionals on these issues, an international group of experts in gastrointestinal pathology participated in a modified Delphi process to generate consensus and highlight areas requiring further research. This effort serves to re-affirm the importance of tumor budding in colorectal cancer and support its continued use in routine clinical practice.
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| 7. |
- Malesci, Alberto, et al.
(author)
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Tumor-associated macrophages and response to 5-fluorouracil adjuvant therapy in stage III colorectal cancer
- 2017
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In: Oncoimmunology. - : Taylor & Francis. - 2162-4011 .- 2162-402X. ; 6:12
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Journal article (peer-reviewed)abstract
- Tumor-associated macrophages (TAMs) play a role in tumor development and progression. We hypothesized that abundance of TAMs might modify efficacy of 5-fluorouracil chemotherapy in colorectal cancer. We measured the density of CD68+ TAMs at the invasive front of primary tumor of colorectal carcinoma (PT-TAMs; n = 208), at available matched metastatic lymph node (LN-TAMs; n = 149), and in an independent set of primary colorectal cancers (PT-TAMs, n = 111). The hazard ratios for disease-free survival were computed by Cox proportional-hazards model. In exploratory analysis, the interaction between TAMs and 5-fluorouracil adjuvant therapy was significant (PT-TAMs, p=0.02; LN-TAMs, p D 0.005). High TAMs were independently associated with better disease-free survival only in 5-fluorouracil-treated patients (PT-TAMs, HR 0.23; 95% CI, 0.08-0.65; p=0.005; LN-TAMs, HR 0.13; 95% CI, 0.04-0.43; p D 0.001). The independent predictive value of PT-TAMs was replicated in the external set (HR, 0.14; 95% CI 0.02-1.00; p=0.05). In an in vitro experiment, 5-fluorouracil and macrophages showed a synergistic effect and increased colorectal cancer cell death. High densities of TAMs, particularly in metastatic lymph-nodes, identify stage III colorectal cancer patients benefitting from 5-fluorouracil adjuvant therapy.
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| 8. |
- Nguyen, Huu-Giao, et al.
(author)
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Image-based assessment of extracellular mucin-to-tumor area predicts consensus molecular subtypes (CMS) in colorectal cancer
- 2022
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In: Modern Pathology. - : Elsevier BV. - 0893-3952 .- 1530-0285. ; 35, s. 240-248
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Journal article (peer-reviewed)abstract
- The backbone of all colorectal cancer classifications including the consensus molecular subtypes (CMS) highlights microsatellite instability (MSI) as a key molecular pathway. Although mucinous histology (generally defined as >50% extracellular mucin-to-tumor area) is a “typical” feature of MSI, it is not limited to this subgroup. Here, we investigate the association of CMS classification and mucin-to-tumor area quantified using a deep learning algorithm, and the expression of specific mucins in predicting CMS groups and clinical outcome. A weakly supervised segmentation method was developed to quantify extracellular mucin-to-tumor area in H&E images. Performance was compared to two pathologists’ scores, then applied to two cohorts: (1) TCGA (n = 871 slides/412 patients) used for mucin-CMS group correlation and (2) Bern (n = 775 slides/517 patients) for histopathological correlations and next-generation Tissue Microarray construction. TCGA and CPTAC (n = 85 patients) were used to further validate mucin detection and CMS classification by gene and protein expression analysis for MUC2, MUC4, MUC5AC and MUC5B. An excellent inter-observer agreement between pathologists’ scores and the algorithm was obtained (ICC = 0.92). In TCGA, mucinous tumors were predominantly CMS1 (25.7%), CMS3 (24.6%) and CMS4 (16.2%). Average mucin in CMS2 was 1.8%, indicating negligible amounts. RNA and protein expression of MUC2, MUC4, MUC5AC and MUC5B were low-to-absent in CMS2. MUC5AC protein expression correlated with aggressive tumor features (e.g., distant metastases (p = 0.0334), BRAF mutation (p < 0.0001), mismatch repair-deficiency (p < 0.0001), and unfavorable 5-year overall survival (44% versus 65% for positive/negative staining). MUC2 expression showed the opposite trend, correlating with less lymphatic (p = 0.0096) and venous vessel invasion (p = 0.0023), no impact on survival.The absence of mucin-expressing tumors in CMS2 provides an important phenotype-genotype correlation. Together with MSI, mucinous histology may help predict CMS classification using only histopathology and should be considered in future image classifiers of molecular subtypes.
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| 9. |
- Swillens, Julie E. M., et al.
(author)
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Pathologists first opinions on barriers and facilitators of computational pathology adoption in oncological pathology: an international study
- 2023
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In: Oncogene. - : SPRINGERNATURE. - 0950-9232 .- 1476-5594. ; 42:38, s. 2816-2827
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Journal article (peer-reviewed)abstract
- Computational pathology (CPath) algorithms detect, segment or classify cancer in whole slide images, approaching or even exceeding the accuracy of pathologists. Challenges have to be overcome before these algorithms can be used in practice. We therefore aim to explore international perspectives on the future role of CPath in oncological pathology by focusing on opinions and first experiences regarding barriers and facilitators. We conducted an international explorative eSurvey and semi-structured interviews with pathologists utilizing an implementation framework to classify potential influencing factors. The eSurvey results showed remarkable variation in opinions regarding attitude, understandability and validation of CPath. Interview results showed that barriers focused on the quality of available evidence, while most facilitators concerned strengths of CPath. A lack of consensus was present for multiple factors, such as the determination of sufficient validation using CPath, the preferred function of CPath within the digital workflow and the timing of CPath introduction in pathology education. The diversity in opinions illustrates variety in influencing factors in CPath adoption. A next step would be to quantitatively determine important factors for adoption and initiate validation studies. Both should include clear case descriptions and be conducted among a more homogenous panel of pathologists based on sub specialization.
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