Programmed death-ligand 1 (PD-L1) expression in primary gastric adenocarcinoma and matched metastases.

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). PD-L1 expression was scored separately in tumour cells and immune cells and compared between matched primary GC, LNmet and/or Dmet. CPS was calculated and results for CPS cut-offs 1 and 5 were compared between matched samples. RESULTS 275 PD-L1 stained GC were analysed. 189 primary GC had matched LNmet. CPS cut-off 1 concordance rate between primary GC and LNmet was 77%. 23 primary GC had matched Dmet but no matched LNmet, CPS cut-off 1 concordance rate was 70%. 63 primary GC had both matched LNmet and matched Dmet, CPS cut-off 1 concordance rate of 67%. CPS cut-off 5 results were similar. The proportion of PD-L1 positive tumour cells increased from primary GC (26%) to LNmet (42%) and was highest in Dmet (75%). CONCLUSION Our study showed up to 33% discordance of PD-L1 CPS between primary GC and LNmet and/or Dmet suggesting that multiple biopsies of primary GC and metastatic sites might need to be tested before considering treatment options. Moreover, this is the first study that seems to suggest that tumour cells acquire PD-L1 expression during disease progression

Immunophenotypes of pancreatic ductal adenocarcinoma: Meta-analysis of transcriptional subtypes.

Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5-year survival rate of <5%. Recent studies of PDAC have provided several transcriptomic classifications based on separate analyses of individual patient cohorts. There is a need to provide a unified transcriptomic PDAC classification driven by therapeutically relevant biologic rationale to inform future treatment strategies. Here, we used an integrative meta-analysis of 353 patients from four different studies to derive a PDAC classification based on immunologic parameters. This consensus clustering approach indicated transcriptomic signatures based on immune infiltrate classified as adaptive, innate and immune-exclusion subtypes. This reveals the existence of microenvironmental interpatient heterogeneity within PDAC and could serve to drive novel therapeutic strategies in PDAC including immune modulation approaches to treating this disease.This study was supported by the NIHR Oxford Biomedical Research Centre. CY is supported by a UK Medical Research Council Research Grant (MR/P02646X/1). MLD is funded by Wellcome Trust grant 100262Z/12/Z. SS is funded by a NIHR Academic Clinical Lecturership

Direct prediction of genetic aberrations from pathology images in gastric cancer with swarm learning.

BACKGROUND Computational pathology uses deep learning (DL) to extract biomarkers from routine pathology slides. Large multicentric datasets improve performance, but such datasets are scarce for gastric cancer. This limitation could be overcome by Swarm Learning (SL). METHODS Here, we report the results of a multicentric retrospective study of SL for prediction of molecular biomarkers in gastric cancer. We collected tissue samples with known microsatellite instability (MSI) and Epstein-Barr Virus (EBV) status from four patient cohorts from Switzerland, Germany, the UK and the USA, storing each dataset on a physically separate computer. RESULTS On an external validation cohort, the SL-based classifier reached an area under the receiver operating curve (AUROC) of 0.8092 (± 0.0132) for MSI prediction and 0.8372 (± 0.0179) for EBV prediction. The centralized model, which was trained on all datasets on a single computer, reached a similar performance. CONCLUSIONS Our findings demonstrate the feasibility of SL-based molecular biomarkers in gastric cancer. In the future, SL could be used for collaborative training and, thus, improve the performance of these biomarkers. This may ultimately result in clinical-grade performance and generalizability

Five biopsy specimens from the proximal part of the tumor reliably determine HER2 protein expression status in gastric cancer

Background: National guidelines recommend trastuzumab for treatment of patients with metastatic HER2-positive gastric cancer (GC). There is currently no guideline indicating the number of biopsy specimens and the location from which they should be obtained to reliably determine the human epidermal growth factor receptor 2 (HER2) status in GC. The aim of this pilot study was (a) to quantify HER2-positive tumor cells in different tumor regions to assess the spatial heterogeneity of HER2 expression and (b) to establish the required number of biopsy specimens and the location from which they should be obtained within the tumor to achieve concordance between HER2 expression status in the biopsy specimens and the resection specimen. Methods: HER2 expression was quantified in six different regions of 24 HER2-positive GC and in six virtual biopsy specimens from different luminal regions. Intratumoral regional heterogeneity and concordance between HER2 status in the biopsy specimens and the resection specimen were analyzed. Results: HER2-positive cells were more frequent in the luminal tumor surface compared with deeper layers (p < 0.001). GCs with differentiated histological features were more commonly HER2 positive (p < 0.001). Assessment of HER2 expression status in five biopsy specimens was sufficient to achieve 100 % concordance between the biopsy specimens and the resection specimen. Conclusions: This is the first study to suggest preferential HER2 positivity at the luminal surface in GC and to establish a minimum number of biopsy specimens needed to obtain a biopsy HER2 result which is identical to that from the whole tumor. Our study suggests that HER2 testing in five tumor-containing endoscopic biopsy specimens from the proximal (oral) part of the tumor is advisable. The results from this pilot study require validation in a prospective study

Low levels of IgM antibodies recognizing oxidation-specific epitopes are associated with human non-alcoholic fatty liver disease

Background: Lipid oxidation of membrane phospholipids is accompanied by the formation of oxidation-specific epitopes (OSE). These epitopes are recognized by specific antibodies and represent danger-associated molecular patterns that are generated during chronic inflammatory processes. In a murine model for hepatic inflammation during non-alcoholic fatty liver disease (NAFLD), increased antibody levels targeting OSE were found to be protective. Here, our aim was to determine an association between OSE-specific antibody titers and NAFLD in humans. Methods: IgM and IgG levels with specificity for various OSE were assessed in the plasma of patients with NAFLD (n = 71) and healthy controls (n = 68). Antibody titers were comprehensively analyzed in patients with NAFLD after classification by histological evaluation of liver biopsies. Statistical analysis was performed to determine significant correlations and odds ratios. To study the specificity for NAFLD, plasma antibody titers were measured in patients with hepatitis C (n = 40) and inflammatory bowel disease (n = 62). Results: IgM titers against OSE were lower in patients with NAFLD compared to controls. Further biopsy-based classification of patients with NAFLD did not show any difference in IgM levels. Plasma IgM titers towards the P1 mimotope demonstrated an inverse correlation with markers for obesity, systemic inflammation, and liver damage. In contrast, hepatitis C and increased disease activity during inflammatory bowel disease was not associated with reduced IgM titers. Conclusions: Our data highlight the importance of immune recognition of OSE by IgM antibodies in the pathophysiology of NAFLD

Spatial profiling of gastric cancer patient-matched primary and locoregional metastases reveals principles of tumour dissemination.

OBJECTIVE: Endoscopic mucosal biopsies of primary gastric cancers (GCs) are used to guide diagnosis, biomarker testing and treatment. Spatial intratumoural heterogeneity (ITH) may influence biopsy-derived information. We aimed to study ITH of primary GCs and matched lymph node metastasis (LNmet). DESIGN: GC resection samples were annotated to identify primary tumour superficial (PTsup), primary tumour deep (PTdeep) and LNmet subregions. For each subregion, we determined (1) transcriptomic profiles (NanoString 'PanCancer Progression Panel', 770 genes); (2) next-generation sequencing (NGS, 225 gastrointestinal cancer-related genes); (3) DNA copy number profiles by multiplex ligation-dependent probe amplification (MLPA, 16 genes); and (4) histomorphological phenotypes. RESULTS: NanoString profiling of 64 GCs revealed no differences between PTsup1 and PTsup2, while 43% of genes were differentially expressed between PTsup versus PTdeep and 38% in PTsup versus LNmet. Only 16% of genes were differently expressed between PTdeep and LNmet. Several genes with therapeutic potential (eg IGF1, PIK3CD and TGFB1) were overexpressed in LNmet and PTdeep compared with PTsup. NGS data revealed orthogonal support of NanoString results with 40% mutations present in PTdeep and/or LNmet, but not in PTsup. Conversely, only 6% of mutations were present in PTsup and were absent in PTdeep and LNmet. MLPA demonstrated significant ITH between subregions and progressive genomic changes from PTsup to PTdeep/LNmet. CONCLUSION: In GC, regional lymph node metastases are likely to originate from deeper subregions of the primary tumour. Future clinical trials of novel targeted therapies must consider assessment of deeper subregions of the primary tumour and/or metastases as several therapeutically relevant genes are only mutated, overexpressed or amplified in these regions

Neoadjuvant cisplatin and fluorouracil versus epirubicin, cisplatin, and capecitabine followed by resection in patients with oesophageal adenocarcinoma (UK MRC OE05): an open-label, randomised phase 3 trial.

BACKGROUND: Neoadjuvant chemotherapy before surgery improves survival compared with surgery alone for patients with oesophageal cancer. The OE05 trial assessed whether increasing the duration and intensity of neoadjuvant chemotherapy further improved survival compared with the current standard regimen. METHODS: OE05 was an open-label, phase 3, randomised clinical trial. Patients with surgically resectable oesophageal adenocarcinoma classified as stage cT1N1, cT2N1, cT3N0/N1, or cT4N0/N1 were recruited from 72 UK hospitals. Eligibility criteria included WHO performance status 0 or 1, adequate respiratory, cardiac, and liver function, white blood cell count at least 3 × 10(9) cells per L, platelet count at least 100 × 10(9) platelets per L, and a glomerular filtration rate at least 60 mL/min. Participants were randomly allocated (1:1) using a computerised minimisation program with a random element and stratified by centre and tumour stage, to receive two cycles of cisplatin and fluorouracil (CF; two 3-weekly cycles of cisplatin [80 mg/m(2) intravenously on day 1] and fluorouracil [1 g/m(2) per day intravenously on days 1-4]) or four cycles of epirubicin, cisplatin, and capecitabine (ECX; four 3-weekly cycles of epirubicin [50 mg/m(2)] and cisplatin [60 mg/m(2)] intravenously on day 1, and capecitabine [1250 mg/m(2)] daily throughout the four cycles) before surgery, stratified according to centre and clinical disease stage. Neither patients nor study staff were masked to treatment allocation. Two-phase oesophagectomy with two-field (abdomen and thorax) lymphadenectomy was done within 4-6 weeks of completion of chemotherapy. The primary outcome measure was overall survival, and primary and safety analyses were done in the intention-to-treat population. This trial is registered with the ISRCTN registry (number 01852072) and ClinicalTrials.gov (NCT00041262), and is completed. FINDINGS: Between Jan 13, 2005, and Oct 31, 2011, 897 patients were recruited and 451 were assigned to the CF group and 446 to the ECX group. By Nov 14, 2016, 327 (73%) of 451 patients in the CF group and 302 (68%) of 446 in the ECX group had died. Median survival was 23·4 months (95% CI 20·6-26·3) with CF and 26·1 months (22·5-29·7) with ECX (hazard ratio 0·90 (95% CI 0·77-1·05, p=0·19). No unexpected chemotherapy toxicity was seen, and neutropenia was the most commonly reported event (grade 3 or 4 neutropenia: 74 [17%] of 446 patients in the CF group vs 101 [23%] of 441 people in the ECX group). The proportions of patients with postoperative complications (224 [56%] of 398 people for whom data were available in the CF group and 233 [62%] of 374 in the ECX group; p=0·089) were similar between the two groups. One patient in the ECX group died of suspected treatment-related neutropenic sepsis. INTERPRETATION: Four cycles of neoadjuvant ECX compared with two cycles of CF did not increase survival, and cannot be considered standard of care. Our study involved a large number of centres and detailed protocol with comprehensive prospective assessment of health-related quality of life in a patient population confined to people with adenocarcinomas of the oesophagus and gastro-oesophageal junction (Siewert types 1 and 2). Alternative chemotherapy regimens and neoadjuvant chemoradiation are being investigated to improve outcomes for patients with oesophageal carcinoma. FUNDING: Cancer Research UK and Medical Research Council Clinical Trials Unit at University College London

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study

Background: Deep learning (DL) can extract predictive and prognostic biomarkers from routine pathology slides in colorectal cancer. For example, a DL test for the diagnosis of microsatellite instability (MSI) in CRC has been approved in 2022. Current approaches rely on convolutional neural networks (CNNs). Transformer networks are outperforming CNNs and are replacing them in many applications, but have not been used for biomarker prediction in cancer at a large scale. In addition, most DL approaches have been trained on small patient cohorts, which limits their clinical utility. Methods: In this study, we developed a new fully transformer-based pipeline for end-to-end biomarker prediction from pathology slides. We combine a pre-trained transformer encoder and a transformer network for patch aggregation, capable of yielding single and multi-target prediction at patient level. We train our pipeline on over 9,000 patients from 10 colorectal cancer cohorts. Results: A fully transformer-based approach massively improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training on a large multicenter cohort, we achieve a sensitivity of 0.97 with a negative predictive value of 0.99 for MSI prediction on surgical resection specimens. We demonstrate for the first time that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem. Interpretation: A fully transformer-based end-to-end pipeline trained on thousands of pathology slides yields clinical-grade performance for biomarker prediction on surgical resections and biopsies. Our new methods are freely available under an open source license

High resolution analysis of DNA copy-number aberrations of chromosomes 8, 13, and 20 in gastric cancers

DNA copy-number gains of chromosomes 8q, 13q, and 20q are frequently observed in gastric cancers. Moreover gain of chromosome 20q has been associated with lymph node metastasis. The aim of this study was to correlate DNA copy-number changes of individual genes on chromosomes 8q, 13q, and 20q in gastric adenocarcinomas to clinicopathological data. DNA isolated from 63 formalin-fixed and paraffin-embedded gastric adenocarcinoma tissue samples was analyzed by whole-genome microarray comparative genomic hybridization and by multiplex ligation-dependent probe amplification (MLPA), targeting 58 individual genes on chromosomes 8, 13, and 20. Using array comparative genomic hybridization, gains on 8q, 13q, and 20q were observed in 49 (77.8%), 25 (39.7%), and 49 (77.8%) gastric adenocarcinomas, respectively. Gain of chromosome 20q was significantly correlated with lymph node metastases (p = 0.05) and histological type (p = 0.02). MLPA revealed several genes to be frequently gained in DNA copy number. The oncogene c-myc on 8q was gained in 73% of the cancers, while FOXO1A and ATP7B on 13q were both gained in 28.6% of the cases. Multiple genes on chromosome 20q showed gains in more than 60% of the cancers. DNA copy-number gains of TNFRSF6B (20q13.3) and ZNF217 (20q13.2) were significantly associated with lymph node metastasis (p = 0.02) and histological type (p = 0.02), respectively. In summary, gains of chromosomes 8q, 13q, and 20q in gastric adenocarcinomas harbor DNA copy-number gains of known and putative oncogenes. ZNF217 and TNFRSF6B are associated with important clinicopathological variables, including lymph node status

Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms