Background: PD-1/PD-L1-Immunotherapy has been approved for gastric carcinoma. PD-L1 assessment by immunohistochemistry is the principle biomarker. Are biopsies able to map the actual PD-L1 status of the entire tumor? Methods: Whole tumor slides of 56 gastric carcinoma were analyzed to determine the distribution of PD-L1 positive cells in the entire tumor areas. Tissue micro arrays with four cores of the tumor surface, which represents the endoscopically accessible biopsy zone, were built from the same tumors. The PD-L1 CPS value was determined separately for each core. Preoperative diagnostic biopsies were available for 22 of the tumors. PD-L1 prevalence, sensitivity and specificity were analyzed using the whole tumor slides as reference scores. Molecular subtyping was performed and related to the PD-L1 status. Results: 27.3% of cases were PD-L1 negative (CPS < 1), 43.6% showed low PD-L1 expression (CPS ≥ 1 to < 5), 12.7% moderate (CPS ≥ 5 to < 10) and 16.4% strong expression (CPS ≥ 10). The biopsies showed best test characteristics if four surface biopsies were analyzed combined, i.e., the CPS was calculated across all four biopsies. The prevalence showed a distribution similar to the resection specimens, sensitivity was 0.73 and specificity 1.0. Using fewer surface biopsies decreased sensitivity and specificity and caused false-negative classifications. Compared to the TMAs, the preoperative biopsies showed reduced sensitivity (0.412). Conclusions: This is the first comprehensive study to optimize PD-L1 assessment in gastric cancer using endoscopically available tissue. The obtained PD-L1 prevalence is consistent with data of current clinical studies. Calculation of the test characteristics shows that surface biopsies can be indicative of the true PD-L1 status based on the resection specimen. However, an adequate number of biopsies is required. In this study, n = 4 biopsies yielded best results.

Oesophageal adenocarcinoma and adenocarcinoma of the oesophagogastric junction are among the most common malignant epithelial tumours. Most patients receive neoadjuvant therapy before complete tumour resection. Histological assessment after resection includes identification of residual tumour tissue and areas of regressive tumour, data which are used to calculate a clinically relevant regression score. We developed an artificial intelligence (AI) algorithm for tumour tissue detection and tumour regression grading in surgical specimens from patients with oesophageal adenocarcinoma or adenocarcinoma of the oesophagogastric junction. We used one training cohort and four independent test cohorts to develop, train, and validate a deep learning tool. The material consisted of histological slides from surgically resected specimens from patients with oesophageal adenocarcinoma and adenocarcinoma of the oesophagogastric junction from three pathology institutes (two in Germany, one in Austria) and oesophageal cancer cohort of The Cancer Genome Atlas (TCGA). All slides were from neoadjuvantly treated patients except for those from the TCGA cohort, who were neoadjuvant-therapy naive. Data from training cohort and test cohort cases were extensively manually annotated for 11 tissue classes. A convolutional neural network was trained on the data using a supervised principle. First, the tool was formally validated using manually annotated test datasets. Next, tumour regression grading was assessed in a retrospective cohort of post-neoadjuvant therapy surgical specimens. The grading of the algorithm was compared with that of a group of 12 board-certified pathologists from one department. To further validate the tool, three pathologists processed whole resection cases with and without AI assistance. Of the four test cohorts, one included 22 manually annotated histological slides (n=20 patients), one included 62 sides (n=15), one included 214 slides (n=69), and the final one included 22 manually annotated histological slides (n=22). In the independent test cohorts the AI tool had high patch-level accuracy for identifying both tumour and regression tissue. When we validated the concordance of the AI tool against analyses by a group of pathologists (n=12), agreement was 63·6% (quadratic kappa 0·749; p<0·0001) at case level. The AI-based regression grading triggered true reclassification of resected tumour slides in seven cases (including six cases who had small tumour regions that were initially missed by pathologists). Use of the AI tool by three pathologists increased interobserver agreement and substantially reduced diagnostic time per case compared with working without AI assistance. Use of our AI tool in the diagnostics of oesophageal adenocarcinoma resection specimens by pathologists increased diagnostic accuracy, interobserver concordance, and significantly reduced assessment time. Prospective validation of the tool is required. North Rhine-Westphalia state, Federal Ministry of Education and Research of Germany, and the Wilhelm Sander Foundation.

HER2 (ERBB2 or HER2/neu) is a tyrosine-kinase increasing cell proliferation. Overexpression/amplification of HER2 is correlated with worse prognosis in solid malignancies. Consequently, HER2 targeting is established in breast and upper gastrointestinal tract cancer. There are conflicting data concerning the impact of HER2 overexpression on esophageal adenocarcinoma (EAC), as most studies do not differ between cancers of the esophagus/gastroesophageal junction and the stomach. The aim of this study was to analyze the expression/amplification of HER2 in EAC in correlation to clinicopathological data to verify its prognostic impact. We analyzed 428 EAC patients that underwent transthoracic thoraco-abdominal esophagectomy between 1997 and 2014. We performed HER2 immunohistochemistry (IHC) according to the guidelines and fluorescence-in-situ-hybridization (FISH) for IHC score2+, using tissue micro arrays (TMA) with up to eight biopsies from the surface and infiltration area of a single tumor for evaluating HER2-heterogeneity and single-spot TMA. The HER2-status was correlated with clinicopathological data. HER2-positivity was found in up to 14.9% in our cohort (IHC score 3+ or IHC score 2+ with gene amplification) and demonstrated a significantly better overall survival (OS) in correlation to HER2-negative tumors (median OS 70.1 vs. 24.6 months, p = 0.006). HER2-overexpression was more frequently seen in lower tumor stages (pT1/pT2, p = 0.038), in the absence of lymphatic metastases (pN0/pN+, p = 0.020), and was significantly associated with better histological grading (G1/G2) (p = 0.041). We demonstrated a positive prognostic impact of HER2 overexpression in a large cohort of EAC, contrary to other solid malignancies including gastric cancer and breast cancer, but consistent to the results of a large study on EAC from 2012.

Tumor growth and survival requires a particularly effective immunosuppressant tumor microenvironment (TME) to escape destruction by the immune system. While immunosuppressive checkpoint markers like programmed cell death 1 ligand (PD-L1) are already being targeted in clinical practice, lymphocyte-activation-protein 3 (LAG-3), T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) and V-domain Ig suppressor of T cell activation (VISTA) inhibitors are currently under investigation in clinical trials. Reliable findings on the expression status of those immune checkpoint inhibitors on tumor-infiltrating lymphocytes (TILs) in the TME of oropharyngeal squamous cell carcinoma (OPSCC) are lacking. This work aims to describe the expression of LAG-3, TIM-3, and VISTA expression in the TME of OPSCC. We created a tissue microarray of paraffin-embedded tumor tissue of 241 OPSCC. Expression of the immune checkpoint protein LAG-3, TIM-3, and VISTA in OPSCC was evaluated using immunohistochemistry and results were correlated with CD8+ T-cell inflammation and human papillomavirus (HPV)-status. 73 OPSCC stained positive for LAG-3 (31%; HPV+:44%; HPV-:26%, p = 0.006), 122 OPSCC stained positive for TIM-3 (51%; HPV+:70%; HPV-:44%, p < 0.001) and 168 OPSCC (70%; HPV+:75%; HPV-:68%, p = 0.313) for VISTA. CD8+ T-cells were significantly associated with LAG-3, TIM-3 and VISTA expression (p < 0.001, p < 0.001, p = 0.007). Immune checkpoint therapy targeting LAG-3, TIM-3, and/or VISTA could be a promising treatment strategy especially in HPV-related OPSCC. Future clinical trials investigating the efficacy of a checkpoint blockade in consideration of LAG-3, TIM-3, and VISTA expression are required.

The tumor microenvironment comprises multiple cell types, like cancer cells, endothelial cells, fibroblasts, and immune cells. In recent years, there have been massive research efforts focusing not only on cancer cells, but also on other cell types of the tumor microenvironment, thereby aiming to expand and determine novel treatment options. Fibroblasts represent a heterogenous cell family consisting of numerous subtypes, which can alter immune cell fractions, facilitate or inhibit tumor growth, build pre-metastatic niches, or stabilize vessels. These effects can be achieved through cell–cell interactions, which form the extracellular matrix, or via the secretion of cytokines or chemokines. The pro- or antitumorigenic fibroblast phenotypes show variability not only among different cancer entities, but also among intraindividual sites, including primary tumors or metastatic lesions. Commonly prescribed for arterial hypertension, the inhibitors of the renin–angiotensin system have recently been described as having an inhibitory effect on fibroblasts. This inhibition leads to modified immune cell fractions and increased tissue stiffness, thereby contributing to overcoming therapy resistance and ultimately inhibiting tumor growth. However, it is important to note that the inhibition of fibroblasts can also have the opposite effect, potentially resulting in increased tumor growth. We aim to summarize the latest state of research regarding fibroblast heterogeneity and its intricate impact on the tumor microenvironment and extracellular matrix. Specifically, we focus on highlighting recent advancements in the comprehension of intraindividual heterogeneity and therapy options within this context.

Tertiary lymphoid structures (TLS) in cancer are considered ectopic hotspots for immune activation that are similar to lymphoid follicles in secondary lymphoid organs (SLO). This study elucidates shared and TLS/SLO-specific features in pancreatic ductal adenocarcinoma (PDAC). TLS abundance was related to superior survival and T-cell abundance in 110 treatment-naïve PDAC samples, underlining their clinical relevance. Immunofluorescence microscopy identified structural homologies between TLSs and SLOs. In RNA expression analyses of laser-microdissected TLSs and paired SLOs, we observed largely overlapping expression patterns of immune-related gene clusters but distinct expression patterns of T-cell and complement-associated genes. Immune cells in TLS expressed essential markers of germinal center formation. Increased activation of tumor-draining lymph nodes in patients with high numbers of TLSs highlights the relevance of these tumor-related structures to systemic immune response. In line with this, we identified an overlap of expanded B-cell receptor clonotypes in TLSs and SLOs, which suggests a vivid cross-talk between the two compartments. We conclude that combined therapeutic approaches exploiting TLS-mediated antitumor immune responses may improve susceptibility of PDAC to immunotherapy.