Publications by authors named "Grabsch H"
The potential role of the transient receptor potential Vanilloid 1 (TRPV1) non-selective cation channel in gastric carcinogenesis remains unclear. The main objective of this study was to evaluate TRPV1 expression in gastric cancer (GC) and precursor lesions compared with controls. Patient inclusion was based on a retrospective review of pathology records.
View Article and Find Full Text PDFBackground: Long-term energy balance-related factors (i.e., lifestyle and physiologic factors that influence the equilibrium between energy intake and energy expenditure over an extended period) such as body mass index (BMI) are linked to colorectal cancer risk, but their impact on colorectal cancer survival is unclear.
View Article and Find Full Text PDFBackground: Stroma AReactive Invasion Front Areas (SARIFA) is a recently identified haematoxylin & eosin (H&E)based histopathologic biomarker in gastrointestinal cancers, including colorectal cancer (CRC), defined as direct contact between tumour cells and adipocytes at the tumour invasion front. The current study aimed at validating the prognostic relevance of SARIFA in a large population-based CRC series as well as at investigating the relationship between SARIFA-status and previously established Warburg-subtypes, both surrogates of the metabolic state of the tumour cells.
Methods: SARIFA-status (positive versus negative) was determined on H&E slides of 1,727 CRC specimens.
Background: An improved understanding of which gastroesophageal adenocarcinoma (GOA) patients respond to both chemotherapy and immune checkpoint inhibitors (ICI) is needed. We investigated the predictive role and underlying biology of a 44-gene DNA damage immune response (DDIR) signature in patients with advanced GOA.
Materials And Methods: Transcriptional profiling was carried out on pretreatment tissue from 252 GOA patients treated with platinum-based chemotherapy (three dose levels) within the randomized phase III GO2 trial.
Background: Many gastric cancer patients in Western countries are diagnosed as metastatic with a median overall survival of less than twelve months using standard chemotherapy. Innovative treatments, like targeted therapy or immunotherapy, have recently proved to ameliorate prognosis, but a general agreement on managing oligometastatic disease has yet to be achieved. An international multi-disciplinary workshop was held in Bertinoro, Italy, in November 2022 to verify whether achieving a consensus on at least some topics was possible.
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- Surgery combined with chemotherapy is the standard treatment for locally advanced gastric cancer (GC) and gastroesophageal junction cancer (GEJC), but outcomes are often poor, especially in specific genetic subtypes like dMMR/MSI-high.* -
- Analysis from several clinical trials shows that patients with MSI-high tumors generally have better survival rates than those with MSS/MSI-low tumors, and that female patients with MSS/MSI-low tumors tend to live longer than their male counterparts.* -
- The study emphasizes that sex can influence the effectiveness of treatments for both MSI-high and MSS/MSI-low non-metastatic GC/GEJC, with surprisingly higher chemotherapy risks noted in females with MSI-high cancers.*
Background: Stroma AReactive Invasion Front Areas (SARIFA) is a novel prognostic histopathologic biomarker measured at the invasive front in haematoxylin & eosin (H&E) stained colon and gastric cancer resection specimens. The aim of the current study was to validate the prognostic relevance of SARIFA-status in colorectal cancer (CRC) patients and investigate its association with the luminal proportion of tumour (PoT).
Methods: We established the SARIFA-status in 164 CRC resection specimens.
Background: Histological examination of tumor draining lymph nodes (LNs) plays a vital role in cancer staging and prognostication. However, as soon as a LN is classed as metastasis-free, no further investigation will be performed and thus, potentially clinically relevant information detectable in tumor-free LNs is currently not captured.
Objective: To systematically study and critically assess methods for the analysis of digitized histological LN images described in published research.
Background: Artificial intelligence (AI) has numerous applications in pathology, supporting diagnosis and prognostication in cancer. However, most AI models are trained on highly selected data, typically one tissue slide per patient. In reality, especially for large surgical resection specimens, dozens of slides can be available for each patient.
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- Scientists studied a type of immune response in breast cancer by looking at special cells called germinal centers in lymph nodes and comparing them to tumor-related immune indicators.
- They found that patients with high levels of immune cells (sTILs) and specific immune structures had more germinal centers in their lymph nodes.
- The study suggests that examining these germinal centers could help understand how the body fights breast cancer and might be useful for future research.
Objective: In this review, we aim to provide an overview of literature on lymph node (LN) histomorphological features and their relationship with the prognosis in colorectal cancer (CRC).
Background: Lymph nodes play a crucial role in the treatment and prognosis of CRC. The presence of LN metastases considerably worsens the prognosis in CRC patients.
Background: Tumour-associated fat cells without desmoplastic stroma reaction at the invasion front (Stroma AReactive Invasion Front Areas (SARIFA)) is a prognostic biomarker in gastric and colon cancer. The clinical utility of the SARIFA status in oesophagogastric cancer patients treated with perioperative chemotherapy is currently unknown.
Methods: The SARIFA status was determined in tissue sections from patients recruited into the MAGIC (n = 292) or ST03 (n = 693) trials treated with surgery alone (S, MAGIC) or perioperative chemotherapy (MAGIC, ST03).
Background: Precise prognosis prediction in patients with colorectal cancer (ie, forecasting survival) is pivotal for individualised treatment and care. Histopathological tissue slides of colorectal cancer specimens contain rich prognostically relevant information. However, existing studies do not have multicentre external validation with real-world sample processing protocols, and algorithms are not yet widely used in clinical routine.
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- The study looks at the shapes and sizes of sentinel lymph nodes that don't have cancer to see if they can help predict how well breast cancer patients will do.
- Researchers measured different aspects of these lymph nodes, looking at their surface areas and how much fat they had.
- They found that the shape of the lymph nodes could show how the immune system is working and may help doctors understand more about patient outcomes, especially in breast cancer.
Background: Conflicting results about the prognostic relevance of signet ring cell histology in gastric cancer have been reported. We aimed to perform a meta-analysis focusing on the clinicopathological features and prognosis of this subgroup of cancer compared with other histologies.
Methods: A systematic literature search in the PubMed database was conducted, including all publications up to 1 October 2021.
Aim: Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesised that GC primary tissue contains information that is predictive of lymph node status and patient prognosis and that this information can be extracted using deep learning (DL).
View Article and Find Full Text PDFBackground: The status of regional tumour draining lymph nodes (LN) is crucial for prognostic evaluation in gastric cancer (GaC) patients. Changes in lymph node microarchitecture, such as follicular hyperplasia (FH), sinus histiocytosis (SH), or paracortical hyperplasia (PH), may be triggered by the anti-tumour immune response. However, the prognostic value of these changes in GaC patients is unclear.
View Article and Find Full Text PDFDeep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation.
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- This study investigates the impact of pathological lymph node (LN) regression after neoadjuvant chemotherapy on survival rates in patients with esophageal adenocarcinoma, addressing a gap in existing research and defining LN response classifications.
- Conducted across five UK centers, the study analyzed 17,930 LNs from 763 patients, assigning scores based on the extent of residual tumor found in the nodes after treatment, with survival outcomes assessed using advanced statistical methods.
- Results showed that patients with complete or partial LN response had significantly lower mortality rates compared to those with poor or no LN response, highlighting LN regression as a vital prognostic factor that should be considered alongside traditional staging methods.
Background: Combination of immunotherapy and chemotherapy is recommended for first line treatment of gastric adenocarcinoma (GC) patients with locally advanced unresectable disease or metastatic disease. However, data regarding the concordance rate between PD-L1 combined positive score (CPS) in primary GC and matched regional lymph node metastasis (LNmet) or matched distant metastasis (Dmet) is limited.
Methods: Tissue microarray sections from primary resected GC, LNmet and Dmet were immunohistochemically stained with anti-PD-L1 (clone SP263).
Introduction: The Laurén classification is widely used for Gastric Cancer (GC) histology subtyping. However, this classification is prone to interobserver variability and its prognostic value remains controversial. Deep Learning (DL)-based assessment of hematoxylin and eosin (H&E) stained slides is a potentially useful tool to provide an additional layer of clinically relevant information, but has not been systematically assessed in GC.
View Article and Find Full Text PDFBackground/aim: To determine the clinical significance of pre-treatment circumferential tumor location within the esophageal wall in patients with locally advanced esophageal squamous cell carcinoma who underwent curative resection after neoadjuvant chemotherapy.
Patients And Methods: Patients (n=96) with cStage IB-III esophageal squamous cell carcinoma who underwent curative resection after neoadjuvant chemotherapy were categorized into two groups based on the circumferential tumor location within the esophageal wall on diagnostic endoscopy: left or anterior wall group (L/A patients, n=49); right or posterior wall group (R/P patients, n=47). Analyses were conducted to examine the relationship between circumferential tumor location, clinicopathological characteristics, 3-year overall survival (3Y-OS), and 3-year recurrence-free survival (3Y-RFS).