Optimized PD-L1 scoring of gastric cancer

Predictive biomarkers in the era of immunotherapy for gastric cancer: current achievements and future perspectives

Gastric cancer (GC) is one of the primary contributors to cancer-related mortality on a global scale. It holds a position within the top five most prevalent malignancies both in terms of occurrence and fatality rates. Immunotherapy, as a breakthrough cancer treatment, brings new hope for GC patients. Various biomarkers, such as the expression of programmed death ligand-1 (PD-L1), the microsatellite instability (MSI) status, tumor mutational burden (TMB), and Epstein-Barr virus (EBV) infection, demonstrate potential to predict the effectiveness of immunotherapy in treating GC. Nevertheless, each biomarker has its own limitations, which leads to a significant portion of patients continue to be unresponsive to immunotherapy. With the understanding of the tumor immune microenvironment (TIME), genome sequencing technology, and recent advances in molecular biology, new molecular markers, such as POLE/POLD1mutations, circulating tumor DNA, intestinal flora, lymphocyte activation gene 3 (LAG-3), and lipid metabolism have emerged. This review aims to consolidate clinical evidence to offer a thorough comprehension of the existing and emerging biomarkers. We discuss the mechanisms, prospects of application, and limitations of each biomarker. We anticipate that this review will open avenues for fresh perspectives in the investigation of GC immunotherapy biomarkers and promote the precise choice of treatment modalities for gastric cancer patients, thereby advancing precision immuno-oncology endeavors.

Triglyceride-glucose index in predicting gastric cancer prognosis: A need for caution

Gastric cancer (GC) remains one of the leading causes of cancer-related mortality worldwide. Accurate prognostic assessment, which is essential for enhancing overall survival (OS), currently depends on pathologic and clinical staging. This underscores the urgent need for reliable and real-time prognostic biomarkers. The triglyceride-glucose (TyG) index, a readily available marker of insulin resistance, has recently emerged as a potential prognostic tool in GC. Numerous studies have consistently shown a significant association between elevated TyG levels and inferior OS as well as progression-free survival. Despite these promising findings, several challenges must be addressed before the TyG index can be widely adopted in clinical practice. Firstly, the TyG index lacks cancer-specificity, reflecting broader metabolic disturbances commonly observed in conditions such as obesity, diabetes, and cardiovascular disease. This lack of specificity complicates its interpretation in oncological settings. Additionally, the cutoff values for TyG index vary across studies, hindering the establishment of a standardized threshold for clinical application. While the TyG index provides valuable insights into a patient's metabolic health, its limited cancer specificity necessitates cautious use when evaluating the prognosis of GC treatment.

An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer

BACKGROUND

Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy outcomes, is a reliable biomarker for screening patients who may benefit from immunotherapy. Here, we developed and validated an interpretable machine learning (ML) model based on contrast-enhanced computed tomography (CECT) radiomics for preoperatively predicting PD-L1 expression status in patients with gastric cancer (GC).

METHODS

We retrospectively recruited 285 GC patients who underwent CECT and PD-L1 detection from two medical centers. A PD-L1 combined positive score (CPS) of ≥ 5 was considered to indicate a high PD-L1 expression status. Patients from center 1 were divided into training (n = 143) and validation sets (n = 62), and patients from center 2 were considered a test set (n = 80). Radiomics features were extracted from venous-phase CT images. After feature reduction and selection, 11 ML algorithms were employed to develop predictive models, and their performance in predicting PD-L1 expression status was evaluated using areas under receiver operating characteristic curves (AUCs). SHapley Additive exPlanations (SHAP) were used to interpret the optimal model and visualize the decision-making process for a single individual.

RESULTS

Nine features significantly associated with PD-L1 expression status were ultimately selected to construct the predictive model. The light gradient-boosting machine (LGBM) model demonstrated the best performance for PD-L1 high expression status prediction in the training, validation, and test sets, with AUCs of 0.841(95% CI: 0.773, 0.908), 0.834 (95% CI:0.729, 0.939), and 0.822 (95% CI: 0.718, 0.926), respectively. The SHAP summary and bar plots illustrated that a feature's value affected the feature's impact attributed to the model. The SHAP waterfall plots were used to visualize the decision-making process for a single individual.

CONCLUSION

Our CT radiomics-based LGBM model may aid in preoperatively predicting PD-L1 expression status in GC patients, and the SHAP method may improve the interpretability of this model.

Deeper Analysis to Identify the True Benefit of ICIs Immunotherapy in First-Line Treatment for Non-HER2-Positive/HER2-Negative Advanced or Metastatic Advanced or Metastatic Gastric Cancer (GC) or Gastroesophageal Junction Cancer (GEJC)

Gastric cancer (GC) has a high global incidence and mortality rate [...].

Clinicopathologic and molecular characterization of stages II-IV gastric cancer with Claudin 18.2 expression

BACKGROUND

Claudin 18.2 (CLDN18.2) is a promising target for targeted therapies in gastric cancer (GC). This study investigated the prevalence of CLDN18.2 expression in patients with stages II-IV GC or gastroesophageal junction (GEJ) adenocarcinoma and its correlation with clinicopathologic features and other crucial GC biomarkers.

METHODS

We enrolled 1000 patients diagnosed with stages II-IV GC after surgical treatment. Immunohistochemistry for CLDN18 (43-14A clone), PD-L1 (22C3 pharmDx), HER2, and FGFR2 was performed. CLDN18.2 positivity was defined as moderate-to-strong (2+/3+) membranous staining in ≥75% of tumor cells. CLDN18.2 expression was compared with biomarker expression, Epstein-Barr virus (EBV) association and microsatellite instability status, and clinicopathologic features.

RESULT

CLDN18.2 was positive in 34.4% of the patients. CLDN18.2 positivity was significantly higher in the middle and upper thirds than in the lower third gastric location (P < .001), but there was no correlation with age, sex, or stage (P > .05). CLDN18.2 positivity was rare (2.8%) in mucinous adenocarcinoma but frequent (90.9%) in a majority of gastric carcinomas with lymphoid stroma. CLDN18.2 positivity was higher in EBV-associated (P < .001) and PD-L1-positive (PD-L1 CPS ≥ 5) GC (P = .014) but lower in HER2 positive GC (P = .005). CLDN18.2 positivity was not significantly associated with overall survival and disease-free survival.

CONCLUSION

This study provides a comprehensive evaluation of CLDN18.2 status and its correlation with the clinicopathologic characteristics of patients with stages II-IV GC in Korea and with crucial biomarkers. It may be valuable for guiding future drug development, expanding treatment options, and ultimately improving patient outcomes in GC.

Current Landscape of Molecular Biomarkers in Gastroesophageal Tumors and Potential Strategies for Co-Expression Patterns

The treatment of metastasized gastroesophageal adenocarcinoma largely depends on molecular profiling based on immunohistochemical procedures. Therefore, the examination of HER2, PD-L1, and dMMR/MSI is recommended by the majority of clinical practice guidelines, as positive expression leads to different treatment approaches. Data from large phase-III trials and consequent approvals in various countries enable physicians to offer their patients several therapy options including immunotherapy, targeted therapy, or both combined with chemotherapy. The introduction of novel therapeutic targets such as CLDN18.2 leads to a more complex decision-making process as a significant number of patients show positive results for the co-expression of other biomarkers besides CLDN18.2. The aim of this review is to summarize the current biomarker landscape of patients with metastatic gastroesophageal tumors, its direct clinical impact on daily decision-making, and to evaluate current findings on biomarker co-expression. Furthermore, possible treatment strategies with multiple biomarker expression are discussed.

Spatial and Temporal Tumor Heterogeneity in Gastric Cancer: Discordance of Predictive Biomarkers

Gastric cancer (GC) is a highly heterogeneous disease that varies in both histological presentation and genetic characteristics. Recent advances in the treatment of metastatic and unresectable GC have made several biomarker tests essential for patient management. Predictive biomarkers such as human epidermal growth factor receptor 2 (HER2), programmed death-ligand 1 (PD-L1), mismatch-repair (MMR) proteins, claudin 18.2, and fibroblast growth factor receptor 2b (FGFR2b) are commonly evaluated using immunohistochemistry. However, the expression levels of these biomarkers may vary across different tumor areas, and the accuracy of biomarker diagnosis can be affected by sample quantity, sample location, and collection method. Therefore, tumor heterogeneity presents substantial challenges for accurate biomarker-based diagnosis and prediction of therapeutic responses. Tumor heterogeneity can be categorized into spatial heterogeneity, which refers to variations within the primary tumor (intra-tumoral) or between primary and metastatic sites, and temporal heterogeneity, which encompasses changes over time. This review addresses the tumor heterogeneity in predictive biomarker expression in GC, focusing on HER2, PD-L1, MMR, the Epstein-Barr virus, claudin 18.2, and FGFR2b.

Prevalence of FGFR2b Protein Overexpression in Advanced Gastric Cancers During Prescreening for the Phase III FORTITUDE-101 Trial

PURPOSE

Fibroblast growth factor receptor 2 isoform IIIb (FGFR2b) protein overexpression is an emerging biomarker in gastric cancer and gastroesophageal junction cancer (GC). We assessed FGFR2b protein overexpression prevalence in nearly 3,800 tumor samples as part of the prescreening process for a global phase III study in patients with newly diagnosed advanced or metastatic GC.

METHODS

As of June 28, 2024, 3,782 tumor samples from prescreened patients from 37 countries for the phase III FORTITUDE-101 trial (ClinicalTrials.gov identifier: NCT05052801) were centrally tested for FGFR2b protein overexpression by immunohistochemistry (IHC) and had evaluable results. FGFR2b positivity was defined as both any % tumor cells (TC) and ≥10% TC exhibiting moderate-to-strong (2+/3+) membranous FGFR2b staining. Prevalence was analyzed across patient and sample characteristics.

RESULTS

FGFR2b protein overexpression at any % and ≥10%, 2+/3+ TC positivity was 37.8% (1,428/3,782 [95% CI, 36.2 to 39.3]) and 16.2% (612/3,782 [95% CI, 15 to 17.4]), respectively. Of any %, 2+/3+ TC-positive tumors, 42.9% (612/1,428 [95% CI, 40.3 to 45.4]) were FGFR2b ≥10%, 2+/3+ TC positive. FGFR2b prevalence was not notably different within multiple patient and sample characteristics examined (age, sex, collection method [biopsy v resection], collection site, location of primary tumor, and geographic region).

CONCLUSION

As of the data cutoff date, we report the largest prevalence assessment of FGFR2b protein overexpression in GC with more than one third (37.8%) of patients with GC exhibiting FGFR2b protein overexpression (any % TC, 2+/3+) by a validated IHC assay. Approximately 16% of patients had FGFR2b protein overexpression in ≥10% of TC. FGFR2b prevalence was similar across geographic regions and within defined patient and sample variables regardless of the level of expression.

Clinicopathological analysis of claudin 18.2 focusing on intratumoral heterogeneity and survival in patients with metastatic or unresectable gastric cancer

BACKGROUND

This study aimed to investigate the prevalence of claudin 18.2 (CLDN18.2) positivity, with a particular focus on intratumoral heterogeneity, and its association with clinicopathological features in metastatic or unresectable gastric cancer (GC).

PATIENTS AND METHODS

We investigated 400 patients who received systemic chemotherapy for unresectable, metastatic, or recurrent GC. Immunohistochemistry for CLDN18 (43-14A), human epidermal growth factor receptor 2 (HER2), programmed death-ligand 1 (PD-L1), and fibroblast growth factor receptor 2, as well as HER2 silver in situ hybridization (ISH), Epstein-Barr virus (EBV) ISH, and microsatellite instability testing were carried out. CD3+, CD8+, CD4+, and Foxp3-positive immune cell densities were calculated using digital image analysis.

RESULTS

In GC cases with any CLDN18.2 expression, more than half of the cases (61.3%) showed different expression results between four different tissue microarray (TMA) cores. When comparing CLDN18.2 status between whole tissue sections and the combined results from the four TMA cores, discrepancies were observed in only 2 out of 85 GC cases (2.4%), with 1 false positive and 1 false negative. After considering intratumoral heterogeneity, a CLDN18.2 positivity rate of 31.3% was observed among the 400 GC patients. CLDN18.2 positivity was rare in GCs located in the antrum (or lower third) and in HER2-positive cases but was common in EBV-positive GCs (P < 0.05). No differences in overall survival (OS) were observed according to CLDN18.2 positivity (P = 0.116). Additionally, there was no association between OS and CLDN18.2 positivity in patients treated with fluoropyrimidine plus platinum, chemotherapy plus trastuzumab, paclitaxel with or without ramucirumab, and immuno-oncologic agents. CLDN18.2-positive/PD-L1-high GCs showed statistically significantly longer OS than others (P = 0.025) and higher CD8+ T-cell densities in both the tumor center and periphery (P < 0.001).

CONCLUSIONS

Characterizing unresectable, metastatic, or recurrent GC with positive CLDN18.2 expression and evaluating intratumoral heterogeneity and prognostic implications of various therapeutics help advance treatment strategies and develop new therapies for patients with GC.

Vascular endothelial growth factor pathway's influence on bevacizumab efficacy in metastatic colorectal cancer treatment

In this article, an article published in the World Journal of Gastrointestinal Oncology, which focuses on whether the expression of programmed death-ligand 1 (PD-L1) affects the effectiveness of chemotherapy regimens, including bevacizumab, in treating patients with colorectal cancer (CRC). Through neutralization of vascular endothelial growth factor (VEGF), bevacizumab inhibits tumor angiogenesis, impairing neovascularization and thereby depriving the tumor of essential nutrients and oxygen. Conversely, PD-L1 binding to VEGF receptor 2 promotes angiogenesis, supporting tumor vasculature. The interplay between these pathways complicates the assessment of bevacizumab's efficacy in cancer therapy, notably in CRC, where VEGF and PD-L1 significantly affect treatment response. This review examines metastatic CRC treatment strategies, focusing on bevacizumab's mechanism of action and the role of PD-L1 in this therapeutic context.

Programmed death receptor-1/programmed death-ligand 1 inhibitors: Clinical progress and biomarker exploration in gastric cancer

Gastric cancer is one of the most common malignant tumours, with limited treatment options and poor prognosis in its advanced stages. In recent years, breakthroughs in tumour immunotherapy have led to immune checkpoint inhibitors becoming a new class of clinical oncology drugs. Programmed death receptor-1 (PD-1) and programmed death-ligand 1 (PD-L1) play significant roles in inhibiting T cell responses and tumour immune escape. PD-1/PD-L1 inhibitors can significantly improve the prognosis of patients with advanced gastric cancer. Moreover, the combination of administering PD-1/PD-L1 inhibitors along with chemotherapy, radiotherapy, targeted therapy, and other immunotherapies may further enhance therapeutic efficacy. However, some scientific issues need to be urgently resolved in the immunotherapy of gastric cancer, including the suboptimal efficacy of PD-1/PD-L1 inhibitor monotherapy, high incidence of immune-related adverse events, and the absence of definitive biomarkers for effectively screening treatment-sensitive populations. This article reviews the mechanism of action, therapeutic advances, adverse effects, and putative predictive biomarkers of PD-1/PD-L1 inhibitors in the treatment of advanced gastric cancer.

A biopsy-based Immunoscore in patients with treatment-naïve resectable gastric cancer

Background

The prognostic significance of T-cell densities in gastric cancer (GC) was previously demonstrated in surgical resection specimens. For prognosis or response prediction, it is preferable to identify biomarkers in pre-treatment biopsies; yet, its representativeness of the tumor immune microenvironment is unclear.

Objectives

This study aimed to evaluate the concordance and prognostic value of T-cell densities in paired biopsies and resections.

Methods

Paired diagnostic biopsies and surgical resections were available for 131 patients with resectable GC who were treated with surgery alone in the D1/D2 trial. T-cell markers such as CD3, CD45RO, CD8, FOXP3, and Granzyme B were assessed by immunohistochemistry and digitally quantified. Tumors were categorized into high and low subgroups for each marker. The concordance between biopsies and resections was determined for each marker with Cohen's κ. To determine the prognostic value of T cells in biopsies, Cox regression was performed.

Results

The concordance of T-cell high and low tumors was moderate for CD8 (κ = 0.58) and weak for other markers (κ < 0.3). CD8 and FOXP3 densities in biopsies were significantly associated with cancer-specific survival. Multivariable analysis showed that an Immunoscore incorporating CD8 and FOXP3 served as an independent prognostic marker (low vs high: hazard ratio 3.40, 95% confidence interval: 1.27-9.10; p = 0.015).

Conclusion

Although the concordance in T-cell densities between biopsy and resection specimens is modest, a biopsy-based Immunoscore identified distinct biological subgroups with prognostic potential. To fully evaluate the prognostic performance of this biopsy Immunoscore, additional studies are warranted.

ConvNext Mitosis Identification-You Only Look Once (CNMI-YOLO): Domain Adaptive and Robust Mitosis Identification in Digital Pathology

In digital pathology, accurate mitosis detection in histopathological images is critical for cancer diagnosis and prognosis. However, this remains challenging due to the inherent variability in cell morphology and the domain shift problem. This study introduces ConvNext Mitosis Identification-You Only Look Once (CNMI-YOLO), a new 2-stage deep learning method that uses the YOLOv7 architecture for cell detection and the ConvNeXt architecture for cell classification. The goal is to improve the identification of mitosis in different types of cancers. We utilized the Mitosis Domain Generalization Challenge 2022 data set in the experiments to ensure the model's robustness and success across various scanners, species, and cancer types. The CNMI-YOLO model demonstrates superior performance in accurately detecting mitotic cells, significantly outperforming existing models in terms of precision, recall, and F1 score. The CNMI-YOLO model achieved an F1 score of 0.795 on the Mitosis Domain Generalization Challenge 2022 and demonstrated robust generalization with F1 scores of 0.783 and 0.759 on the external melanoma and sarcoma test sets, respectively. Additionally, the study included ablation studies to evaluate various object detection and classification models, such as Faster-RCNN and Swin Transformer. Furthermore, we assessed the model's robustness performance on unseen data, confirming its ability to generalize and its potential for real-world use in digital pathology, using soft tissue sarcoma and melanoma samples not included in the training data set.

The current status of immunotherapy and future horizon in the treatment of metastatic and locally advanced gastroesophageal adenocarcinoma

INTRODUCTION

Immunochemotherapy with PD-1 blockade has been established as the current standard first-line therapy for patients with mGEA. Reviewing the history of clinical trials offers valuable insight into the evolution of immune oncology in mGEA, paving the way for future advancements in this field.

AREAS COVERED

This review summarizes the findings of previous clinical trials related to immunotherapy for patients with GEA in the metastatic and locally advanced setting. We also introduce ongoing clinical trials to address the current challenging issues in clinical practice.

EXPERT OPINION

In general, GEA exhibits intermediate immunogenic characteristics with heterogeneous expressions, and responders to anti-PD-(L)1 therapy are mostly enriched to patients with specific genomic profiles such as MSI-H, high PD-L1 expression, high TMB, and EBV-associated type. Co-administration with anti-angiogenic agents or simultaneous blockade of immune checkpoint molecules is being explored to offer benefit of immunotherapy for more patients. We hope that CLDN18.2 and upcoming targets like FGFR2b will complement the treatment niche of immunotherapy in the field of mGEA. Bispecific antibodies, antibody drug conjugates, CAR-T, and vaccine are anticipated to enhance efficacy and expand the scope of immunotherapy.

Efficacy of chemotherapy containing bevacizumab in patients with metastatic colorectal cancer according to programmed cell death ligand 1

BACKGROUND

Bevacizumab, an anti-vascular endothelial growth factor (VEGF) monoclonal antibody, inhibits angiogenesis and reduces tumor growth. Serum VEGF-C, lactate dehydrogenase, and inflammatory markers have been reported as predictive markers related to bevacizumab treatment. Programmed cell death ligand 1 (PD-L1) could act upon VEGF receptor 2 to induce cancer cell angiogenesis and metastasis.

AIM

To investigate the efficacy of bevacizumab-containing chemotherapy in patients with metastatic colorectal cancer (CRC) according to the expression of PD-L1.

METHODS

This analysis included CRC patients who received bevacizumab plus FOLFOX or FOLFIRI as first-line therapy between June 24, 2014 and February 28, 2022, at Samsung Medical Center (Seoul, South Korea). Analysis of patient data included evaluation of PD-L1 expression by the combined positive score (CPS). We analyzed the efficacy of bevacizumab according to PD-L1 expression status in patients with CRC.

RESULTS

A total of 124 patients was included in this analysis. Almost all patients were treated with bevacizumab plus FOLFIRI or FOLFOX as the first-line chemotherapy. While 77% of patients received FOLFOX, 23% received FOLFIRI as backbone first-line chemotherapy. The numbers of patients with a PD-L1 CPS of 1 or more, 5 or more, or 10 or more were 105 (85%), 64 (52%), and 32 (26%), respectively. The results showed no significant difference in progression-free survival (PFS) and overall survival (OS) with bevacizumab treatment between patients with PD-L1 CPS less than 1 and those with PD-L1 CPS of 1 or more (PD-L1 < 1% vs PD-L1 ≥ 1%; PFS: P = 0.93, OS: P = 0.33), between patients with PD-L1 CPS less than 5 and of 5 or more (PD-L1 < 5% vs PD-L1 ≥ 5%; PFS: P = 0.409, OS: P = 0.746), and between patients with PD-L1 CPS less than 10 and of 10 or more (PD-L1 < 10% vs PD-L1 ≥ 10%; PFS: P = 0.529, OS: P = 0.568).

CONCLUSION

Chemotherapy containing bevacizumab can be considered as first-line therapy in metastatic CRC irrespective of PD-L1 expression.

The tumor immune composition of mismatch repair deficient and Epstein-Barr virus-positive gastric cancer: A systematic review

BACKGROUND

Gastric cancer (GC), known for its unfavorable prognosis, has been classified in four distinct molecular subtypes. These subtypes not only exhibit differences in their genome and transcriptome but also in the composition of their tumor immune microenvironment. The microsatellite instable (MSI) and Epstein-Barr virus (EBV) positive GC subtypes show clear clinical benefits from immune checkpoint blockade, likely due to a neoantigen-driven and virus-driven antitumor immune response and high expression of immune checkpoint molecule PD-L1. However, even within these subtypes response to checkpoint inhibition is variable, which is potentially related to heterogeneity in the tumor immune microenvironment (TIME) and expression of co-inhibitory molecules. We conducted a systematic review to outline the current knowledge about the immunological features on the TIME of MSI and EBV + GCs.

METHODS

A systematic search was performed in PubMed, EMBASE and Cochrane Library. All articles from the year 1990 and onwards addressing immune features of gastric adenocarcinoma were reviewed and included based on predefined in- and exclusion criteria.

RESULTS

In total 5962 records were screened, of which 139 were included that reported immunological data on molecular GC subtypes. MSI and EBV + GCs were reported to have a more inflamed TIME compared to non-MSI and EBV- GC subtypes. Compared to microsatellite stable (MSS) tumors, MSI tumors were characterized by higher numbers of CD8 + and FoxP3 + T cells, and tumor infiltrating pro- and anti-inflammatory macrophages. HLA-deficiency was most common in MSI tumors compared to other molecular GC subtypes and associated with lower T and B cell infiltrates compared to HLA-proficient tumors. EBV + was associated with a high number of CD8 + T cells, Tregs, NK cells and macrophages. Expression of PD-L1, CTLA-4, Granzyme A and B, Perforin and interferon-gamma was enriched in EBV + tumors. Overall, MSI tumors harbored a more heterogeneous TIME in terms of immune cell composition and immune checkpoints compared to the EBV + tumors.

DISCUSSION AND CONCLUSION

MSI and EBV + GCs are highly Handbook for Conducting a Literature-Based Health Assessment Using OHAT Approach for Systematic Review and Evidence Integration.; 2019pro-inflammatory immune cell populations. Although studies on the direct comparison of EBV + and MSI tumors are limited, EBV + tumors show less intra-subgroup heterogeneity compared to MSI tumors. More studies are needed to identify how Intra-subgroup heterogeneity impacts response to immunotherapy efficacy.

Molecular classification and intratumoral heterogeneity of gastric adenocarcinoma

Gastric cancers frequently harbor striking histological complexity and diversity between lesions as well as within single lesions, known as inter- and intratumoral heterogeneity, respectively. The latest World Health Organization Classification of Tumors designated more than 30 histological subtypes for gastric epithelial tumors, assigning 12 subtypes for gastric adenocarcinoma (GAD). Meanwhile, recent advances in genome-wide analyses have provided molecular aspects to the histological classification of GAD, and consequently revealed different molecular traits underlying these histological subtypes. Moreover, accumulating knowledge of comprehensive molecular profiles has led to establishing molecular classifications of GAD, which are often associated with clinical biomarkers for therapeutics and prognosis. However, most of our knowledge of GAD molecular profiles is based on inter-tumoral heterogeneity, and the molecular profiles underlying intratumoral heterogeneity are yet to be determined. In this review, recently established molecular classifications of GAD are introduced in the aspect of pathological diagnosis and are discussed in the context of intratumoral heterogeneity.

Current and Future Biomarkers in Esophagogastric Adenocarcinoma

PURPOSE

Biomarker-based therapies have shown improved patient outcomes across various cancer types. The purpose of this review to summarize our knowledge of current and future biomarkers in esophagogastric adenocarcinoma (EGA).

METHODS

In this publication, we will review current standard biomarkers in patients with upper GI cancers. We will also discuss novel biomarkers that are under investigations and their associated therapies that are currently in clinical trials.

RESULTS

EGAa are a group of heterogeneous diseases, both anatomically and molecularly. There are several established biomarkers (HER2, PD-L1, microsattelite instability or mismatch repair protein expression) that allow for individualized treatments for patients with these cancers. There are also several emerging biomarkers for EGA, some of which have clinically relevant associated therapies. Claudin 18.2 is the furthest along among these. Anti-claudin antibody, zolbetuximab, improved overall survival in biomarker select patients with advanced GEA in two phase 3 studies. Other novel biomarkers, such as FGFR2b and DKN01, are also in the process of validation, and treatments based on the presence of these biomarkers are currently in clinical studies.

CONCLUSION

Ongoing efforts to identify novel biomarkers in EGA have led to enhanced subclassification of upper GI cancers. These advances, coupled with the strategic application of targeted therapies and immunotherapy when appropriate, hold promise to further improve patients outcomes.

Analyzing the Impact of Oncological Data at Different Time Points and Tumor Biomarkers on Artificial Intelligence Predictions for Five-Year Survival in Esophageal Cancer

AIM: In this study, we use Artificial Intelligence (AI), including Machine (ML) and Deep Learning (DL), to predict the long-term survival of resectable esophageal cancer (EC) patients in a high-volume surgical center. Our objective is to evaluate the predictive efficacy of AI methods for survival prognosis across different time points of oncological treatment. This involves comparing models trained with clinical data, integrating either Tumor, Node, Metastasis (TNM) classification or tumor biomarker analysis, for long-term survival predictions. METHODS: In this retrospective study, 1002 patients diagnosed with EC between 1996 and 2021 were analyzed. The original dataset comprised 55 pre- and postoperative patient characteristics and 55 immunohistochemically evaluated biomarkers following surgical intervention. To predict the five-year survival status, four AI methods (Random Forest RF, XG Boost XG, Artificial Neural Network ANN, TabNet TN) and Logistic Regression (LR) were employed. The models were trained using three predefined subsets of the training dataset as follows: (I) the baseline dataset (BL) consisting of pre-, intra-, and postoperative data, including the TNM but excluding tumor biomarkers, (II) clinical data accessible at the time of the initial diagnostic workup (primary staging dataset, PS), and (III) the PS dataset including tumor biomarkers from tissue microarrays (PS + biomarkers), excluding TNM status. We used permutation feature importance for feature selection to identify only important variables for AI-driven reduced datasets and subsequent model retraining. RESULTS: Model training on the BL dataset demonstrated similar predictive performances for all models (Accuracy, ACC: 0.73/0.74/0.76/0.75/0.73; AUC: 0.78/0.82/0.83/0.80/0.79 RF/XG/ANN/TN/LR, respectively). The predictive performance and generalizability declined when the models were trained with the PS dataset. Surprisingly, the inclusion of biomarkers in the PS dataset for model training led to improved predictions (PS dataset vs. PS dataset + biomarkers; ACC: 0.70 vs. 0.77/0.73 vs. 0.79/0.71 vs. 0.75/0.69 vs. 0.72/0.63 vs. 0.66; AUC: 0.77 vs. 0.83/0.80 vs. 0.85/0.76 vs. 0.86/0.70 vs. 0.76/0.70 vs. 0.69 RF/XG/ANN/TN/LR, respectively). The AI models outperformed LR when trained with the PS datasets. The important features shared after AI-driven feature selection in all models trained with the BL dataset included histopathological lymph node status (pN), histopathological tumor size (pT), clinical tumor size (cT), age at the time of surgery, and postoperative tracheostomy. Following training with the PS dataset with biomarkers, the important predictive features included patient age at the time of surgery, TP-53 gene mutation, Mesothelin expression, thymidine phosphorylase (TYMP) expression, NANOG homebox protein expression, and indoleamine 2,3-dioxygenase (IDO) expressed on tumor-infiltrating lymphocytes, as well as tumor-infiltrating Mast- and Natural killer cells. CONCLUSION: Different AI methods similarly predict the long-term survival status of patients with EC and outperform LR, the state-of-the-art classification model. Survival status can be predicted with similar predictive performance with patient data at an early stage of treatment when utilizing additional biomarker analysis. This suggests that individual survival predictions can be made early in cancer treatment by utilizing biomarkers, reducing the necessity for the pathological TNM status post-surgery. This study identifies important features for survival predictions that vary depending on the timing of oncological treatment.

Assessment of programmed death-ligand 1 expression in primary tumors and paired lymph node metastases of gastric adenocarcinoma

BACKGROUND

Anti-programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) immunotherapy has demonstrated promising results on gastric cancer (GC). However, PD-L1 can express differently between metastatic sites and primary tumors (PT).

AIM

To compare PD-L1 status in PT and matched lymph node metastases (LNM) of GC patients and to determine the correlation between the PD-L1 status and clinicopathological characteristics.

METHODS

We retrospectively reviewed 284 GC patients who underwent D2-gastrectomy. PD-L1 was evaluated by immunohistochemistry (clone SP142) using the combined positive score. All PD-L1+ PT staged as pN+ were also tested for PD-L1 expression in their LNM. PD-L1(-) GC with pN+ served as the comparison group.

RESULTS

Among 284 GC patients included, 45 had PD-L1+ PT and 24 of them had pN+. For comparison, 44 PD-L1(-) cases with pN+ were included (sample loss of 4 cases). Of the PD-L1+ PT, 54.2% (13/24 cases) were also PD-L1+ in the LNM. Regarding PD-L1(-) PT, 9.1% (4/44) had PD-L1+ in the LNM. The agreement between PT and LNM had a kappa value of 0.483. Larger tumor size and moderate/severe peritumoral inflammatory response were associated with PD-L1 positivity in both sites. There was no statistical difference in overall survival for PT and LNM according to the PD-L1 status (P = 0.166 and P = 0.837, respectively).

CONCLUSION

Intra-patient heterogeneity in PD-L1 expression was observed between the PT and matched LNM. This disagreement in PD-L1 status may emphasize the importance of considering different tumor sites for analyses to select patients for immunotherapy.

[Standardized and quality-assured predictive PD-L1 testing in the upper gastrointestinal tract. German version]

As a result of the high approval dynamics and the growing number of immuno-oncological therapy concepts, the complexity of therapy decisions and control in the area of carcinomas of the esophagus, gastroesophageal junction and stomach is constantly increasing. Since the treatment indication for PD‑1 inhibitors that are currently approved in the European Union is often linked to the expression of PD-L1 (programmed cell death-ligand 1), the evaluation of tissue-based predictive markers by the pathologist is of crucial importance for treatment stratification. Even though the immunohistochemical analysis of the PD-L1 expression status is one of the best studied, therapy-relevant biomarkers for an immuno-oncological treatment, due to the high heterogeneity of carcinomas of the upper gastrointestinal tract, there are challenges in daily clinical diagnostic work with regard to implementation, standardization and interpretation of testing. An interdisciplinary group of experts from Germany has taken a position on relevant questions from daily pathological and clinical practice, which concern the starting material, quality-assured testing and the interpretation of pathological findings, and has developed recommendations for structured reporting.

Effect of ramucirumab plus paclitaxel in advanced gastric cancer according to the status of programmed cell death-ligand 1 (PD-L1) expression

Background

Ramucirumab, an anti-vascular endothelial growth factor receptor (VEGFR) monoclonal antibody (mAb), inhibits angiogenesis and reduces tumor activity. Programmed cell death-ligand 1 (PD-L1) might act upon VEGFR2 to induce cancer cell angiogenesis and metastasis. Herein, we investigated the efficacy of combining ramucirumab and paclitaxel according to the status of PD-L1 expression in patients with advanced gastric cancer (AGC).

Methods

This analysis included AGC patients who received ramucirumab plus paclitaxel as 2nd line therapy between December 1, 2018, and February 28, 2022, at Samsung Medical Center. All patient data analyses included an evaluation of PD-L1 expression using the combined positive score (CPS). We analyzed the efficacy and the survival of patients according to their PD-L1 expression.

Results

We included 117 patients in this analysis, and 80 patients (68.4%) had a PD-L1 CPS of one or more, 37 (31.6%) had five or more, and 19 (16.2%) had ten or more scores. Progression-free survival (PFS) and overall survival (OS) did not differ significantly between patients with a PD-L1 CPS of less than one and one or more {PD-L1 <1% vs. PD-L1 ≥1%; PFS: median 3.6 months [95% confidence interval (CI): 2.4-4.8 months] vs. median 4.1 months (95% CI: 3.5-4.7 months), P=0.93; PD-L1 <1% vs. PD-L1 ≥1%; OS: median 7.0 months (95% CI: 5.4-8.6 months) vs. median 8.1 months (95% CI: 6.4-9.8 months), P=0.32}. PFS and OS did not differ significantly between patients with a PD-L1 CPS of less than 5 and 5 or more [PD-L1 <5% vs. PD-L1 ≥5%; PFS: 3.9 months (95% CI: 3.3-4.5 months) vs. 4.4 months (95% CI: 3.0-5.8 months), P=0.57; OS: 7.4 months (95% CI: 6.5-8.3 months) vs. 10.0 months (95% CI: 1.1-18.9 months), P=0.07]. Interestingly, with a PD-L1 CPS cutoff of 10, PFS and OS did differ significantly [PD-L1 <10% vs. PD-L1 ≥10%; PFS: 3.8 months (95% CI: 3.3-4.3 months) vs. 5.7 months (95% CI: 4.1-7.3 months), P=0.05; OS: 7.2 months (95% CI: 6.5-7.9 months) vs. 18.9 months (95% CI: 6.5-31.3 months), P=0.04].

Conclusions

No biomarkers have been established to predict survival times after ramucirumab plus paclitaxel treatment. This analysis suggests that a PD-L1 CPS cutoff of 10 might be novel a biomarker to predict the survival of AGC patients treated with ramucirumab and paclitaxel.

The role of ramucirumab plus paclitaxel as second-line therapy after failure of nivolumab plus doublet chemotherapy in patients with advanced gastric cancer

Background

Adding nivolumab to fluoropyrimidines and platinum agents has been considered a new standard first-line treatment in previously untreated human epidermal growth factor receptor 2 (HER2)-negative advanced gastric cancer (AGC). However, there were few data on the role of ramucirumab plus paclitaxel as second-line treatment after failure of nivolumab plus doublet chemotherapy. Herein, we analyzed the efficacy and safety of second-line ramucirumab plus paclitaxel in AGC patients refractory to nivolumab plus chemotherapy.

Methods

This analysis included AGC patients with ramucirumab plus paclitaxel as second-line therapy after failing to respond to nivolumab plus doublet chemotherapy [capecitabine plus oxaliplatin (XELOX) or 5-fluorouracil plus oxaliplatin (FOLFOX)] at Samsung Medical Center, Korea. Twenty patients who progressed on nivolumab plus chemotherapy as first-line therapy were treated with ramucirumab plus paclitaxel between December 2021 and September 2022.

Results

The median age was 56 (range, 24-76) years, and 13 (65.0%) were men. Of the 20 patients, 15 (75.0%) patients received nivolumab plus capecitabine, and oxaliplatin, while 5 (25.0%) patients received nivolumab plus 5-fluorouracil, and oxaliplatin. Two showed a partial response (PR) to ramucirumab plus paclitaxel, a response rate of 10%. Patients with stable disease (SD) accounted for a disease control rate (DCR) of 55.0%. The median progression-free survival (PFS) to ramucirumab plus paclitaxel was 2.7 months [95% confidence interval (CI): 1.7-3.7]. Subgroup analysis showed that responders (n=7) to first-line therapy had a PFS of 6.9 months compared to 2.3 months in non-responders (n=13) to first-line therapy. The median overall survival (OS) was 6.3 months (95% CI: 5.5-8.3), representing 6.9 months (95% CI: not calculated) in responders and 6.3 months (95% CI: 3.7-8.9) in non-responders (P=0.401).

Conclusions

This analysis suggested that ramucirumab plus paclitaxel as second-line therapy might be further studied in AGC patients after failure of nivolumab plus chemotherapy. A new second-line therapy is needed in AGC patients after nivolumab plus chemotherapy.

Standardized and quality-assured predictive PD-L1 testing in the upper gastrointestinal tract

As a result of the high approval dynamics and the growing number of immuno-oncological concepts, the complexity of treatment decisions and control in the area of cancers of the esophagus, gastroesophageal junction and stomach is constantly increasing. Since the treatment indication for PD-1 inhibitors that are currently approved in the European Union is often linked to the expression of PD-L1 (programmed cell death-ligand 1), the evaluation of tissue-based predictive markers by the pathologist is of crucial importance for treatment stratification. Even though the immunohistochemical analysis of the PD-L1 expression status is one of the best studied, therapy-relevant biomarkers for an immuno-oncological treatment, due to the high heterogeneity of carcinomas of the upper gastrointestinal tract, there are challenges in daily clinical diagnostic work with regard to implementation, standardization and interpretation of testing. An interdisciplinary group of experts from Germany has taken a position on relevant questions from daily pathological and clinical practice, which concern the starting material, quality-assured testing and the interpretation of pathological findings, and has developed recommendations for structured reporting.

Predictive Biomarkers for Immunotherapy in Gastric Cancer: Current Status and Emerging Prospects

Gastric cancer presents substantial management challenges, and the advent of immunotherapy has ignited renewed hope among patients. Nevertheless, a significant proportion of patients do not respond to immunotherapy, and adverse events associated with immunotherapy also occur on occasion, underscoring the imperative to identify suitable candidates for treatment. Several biomarkers, including programmed death ligand-1 expression, tumor mutation burden, mismatch repair status, Epstein-Barr Virus infection, circulating tumor DNA, and tumor-infiltrating lymphocytes, have demonstrated potential in predicting the effectiveness of immunotherapy in gastric cancer. However, the quest for the optimal predictive biomarker for gastric cancer immunotherapy remains challenging, as each biomarker carries its own limitations. Recently, multi-omics technologies have emerged as promising platforms for discovering novel biomarkers that may help in selecting gastric cancer patients likely to respond to immunotherapy. The identification of reliable predictive biomarkers for immunotherapy in gastric cancer holds the promise of enhancing patient selection and improving treatment outcomes. In this review, we aim to provide an overview of clinically established biomarkers of immunotherapy in gastric cancer. Additionally, we introduce newly reported biomarkers based on multi-omics studies in the context of gastric cancer immunotherapy, thereby contributing to the ongoing efforts to refine patient stratification and treatment strategies.

Tumour area infiltration and cell count in endoscopic biopsies of therapy-naive upper GI tract carcinomas by QuPath analysis: implications for predictive biomarker testing

Guidelines regulate how many (tumour-bearing) tissue particles should be sampled during gastric cancer biopsy to obtain representative results in predictive biomarker testing. Little is known about how well these guidelines are applied, how the number of tissue particles correlates with the actual tumour-infiltrated area and how many absolute tumour cells are captured. The study included endoscopic biopsies of untreated carcinomas of the upper gastrointestinal (GI)-tract during the 2016-2020 review period. Archival (H&E)-stained histological sections were digitised and the tumour areas were manually annotated. The tumour-bearing tissue area and absolute carcinoma cell count per case were determined by image analysis and compared with a reference primary surgical specimen. Biopsies from 253 patients were analysed. The following mean values were determined: (a) tumour tissue particle number: 6.5 (range: 1-25, standard deviation (SD) = 3.33), (b) number of tumour-bearing tissue particles: 4.7 (range: 1-20, SD = 2.80), (c) tumour-infiltrated area: 7.5 mm2 (range: 0.18-59.46 mm2, SD = 6.67 mm2), (d) absolute tumour cell count: 13,492 (range: 193-92,834, SD = 14,185) and (e) tumour cell count in a primary surgical specimen (tumour size: 6.7 cm): 105,200,176. The guideline-recommended tissue particle count of 10 was not achieved in 208 patients (82.2%) and the required tumour-bearing tissue particle count of 5 was not achieved in 133 patients (52.6%). Tissue particle count, tumour-infiltrated area and tumour cell count were only weakly correlated. Most cases featured an infiltrated area ≥ 4.5 mm2 (156, 61.7%). Cases with more tissue particles showed only a moderate increase in infiltrated area and tumour cells compared to cases with fewer particles. Biopsies are often used to determine predictive biomarkers, particularly Her2/neu and PD-L1. Diagnostic standards to ensure representative material have been suggested in guidelines to reduce false-negative predictions. However, the real-world practice seems to substantially deviate from recommended standards. To the best of our knowledge, this is the first systematic study describing the relationships between endoscopic tissue fragment number, actual infiltrated tumour area and carcinoma cell number. The data question the tissue particle number as a quality assessment parameter. We advocate histopathological reports indicating on which basis statements on therapy-relevant biomarkers were made. Digital pathology has the potential to objectively quantify the tissue for documentation, quality assessment and future clinical studies.

Role of Endoscopic Biopsies and Morphologic Features in Predicting Microsatellite Instability Status in Gastric Cancer: A Multicenter Comparative Study of Endoscopic Biopsies and Surgical Specimens

Evaluation of mismatch repair (MMR) protein and microsatellite instability (MSI) status plays a pivotal role in the management of gastric cancer (GC) patients. In this study, we aimed to evaluate the accuracy of gastric endoscopic biopsies (EBs) in predicting MMR/MSI status and to uncover histopathologic features associated with MSI. A multicentric series of 140 GCs was collected retrospectively, in which EB and matched surgical specimens (SSs) were available. Laurén and WHO classifications were applied and detailed morphologic characterization was performed. EB/SS were analyzed by immunohistochemistry (IHC) for MMR status and by multiplex polymerase chain reaction (mPCR) for MSI status. IHC allowed accurate evaluation of MMR status in EB (sensitivity: 97.3%; specificity: 98.0%) and high concordance rates between EB and SS (Cohen κ=94.5%). By contrast, mPCR (Idylla MSI Test) showed lower sensitivity in evaluating MSI status (91.3% vs. 97.3%), while maintaining maximal specificity (100.0%). These results suggest a role of IHC as a screening method for MMR status in EB and the use of mPCR as a confirmatory test. Although Laurén/WHO classifications were not able to discriminate GC cases with MSI, we identified specific histopathologic features that are significantly associated with MMR/MSI status in GC, despite the morphologic heterogeneity of GC cases harboring this molecular phenotype. In SS, these features included the presence of mucinous and/or solid components ( P =0.034 and <0.001) and the presence of neutrophil-rich stroma, distant from tumor ulceration/perforation ( P <0.001). In EB, both solid areas and extracellular mucin lakes were also discriminating features for the identification of MSI-high cases ( P =0.002 and 0.045).

Biomarkers for Predicting Response to Personalized Immunotherapy in Gastric Cancer

Despite advances in diagnostic imaging, surgical techniques, and systemic therapy, gastric cancer (GC) is the third leading cause of cancer-related death worldwide. Unfortunately, molecular heterogeneity and, consequently, acquired resistance in GC are the major causes of failure in the development of biomarker-guided targeted therapies. However, by showing promising survival benefits in some studies, the recent emergence of immunotherapy in GC has had a significant impact on treatment-selectable procedures. Immune checkpoint inhibitors (ICIs), widely indicated in the treatment of several malignancies, target inhibitory receptors on T lymphocytes, including the programmed cell death protein (PD-1)/programmed death-ligand 1 (PD-L1) axis and cytotoxic T-lymphocyte-associated protein 4 (CTLA4), and release effector T-cells from negative feedback signals. In this article, we review currently available predictive biomarkers (including PD-L1, microsatellite instability, Epstein-Barr virus, and tumor mutational burden) that affect the ICI treatment response, focusing on PD-L1 expression. We further briefly describe other potential biomarkers or mechanisms for predicting the response to ICIs in GC. This review may facilitate the expansion of the understanding of biomarkers for predicting the response to ICIs and help select the appropriate therapeutic approaches for patients with GC.

CLDN18.2 expression and its impact on prognosis and the immune microenvironment in gastric cancer

BACKGROUND

The investigational use of zolbetuximab (IMAB362), a groundbreaking monoclonal antibody medication targeting claudin 18.2 (CLDN18.2), for treatment of advanced gastrointestinal cancers is currently underway. The unclear clinicopathological characteristics and tumour immune microenvironment of CLDN18.2-positive gastric cancer (GC) make it difficult to develop and optimize CLDN18.2-targeted therapies.

METHODS

A total of 451 tumour tissues, 342 matched paraneoplastic tissues, and 107 matched metastatic lymph nodes were collected from GC patients. These specimens were stained for CLDN18.2 expression and quantified using immunohistochemistry (IHC). Correlations between CLDN18.2 expression and clinicopathological features as well as immune-related factors were analysed. Survival curves were drawn using the Kaplan‒Meier approach, and independent factors affecting GC prognosis were identified using Cox regression analysis. Information from relevant databases was used for corroboration.

RESULTS

Expression of the CLDN18.2 gene was significantly lower in gastric tumour tissues than in normal tissues (p < 0.001) but comparable in metastatic lymph nodes (p = 0.851). CLDN18.2 expression was significantly associated with Borrmann type, degree of differentiation, PD-L1 expression, and survival in GC patients and was identified as an independent risk factor for patient prognosis (HR = 1.57, 95% CI 1.16-2.11, p = 0.003). There was no correlation between CLDN18.2 expression and HER2, Lauren type, tumour size, TNM stage, or any other clinicopathological characteristic. In CLDN18.2-positive tumours, fractions of CD4 + T cells and CD8 + T cells were significantly higher than those in CLDN18.2-negative tumours. Patients with CLDN18.2-negative expression and significant CD4 + T-cell or CD8 + T-cell infiltration had the best prognosis (5-year OS: 61.0%, P = 0.036; 5-year OS: 62.2%, P = 0.034).

CONCLUSIONS

CLDN18.2 is expressed at a low level in tumour tissues and serves as an independent prognostic factor for patients with GC. Furthermore, CLDN18.2 correlates with immune infiltrating cells and PD-L1 expression.

FGFR2-amplified tumor clones are markedly heterogeneously distributed in carcinomas of the upper gastrointestinal tract

BACKGROUND

FGFR2 is a therapy-relevant target in tumors of the upper gastrointestinal tract (GIT), and clinical trials are currently underway to test the efficacy of FGFR2 inhibitors. Tumor heterogeneity is one of the relevant causes of treatment failure. Almost nothing is known about the heterogeneous distribution of FGFR2-amplified clones in adenocarcinomas of the upper GIT.

PATIENTS AND METHODS

To assess FGFR2 gene copy number alteration and intratumoral heterogeneity of upper GIT adenocarcinomas, we analyzed 893 patient-derived formalin-fixed paraffin-embedded tumor specimens, including primary operated and neoadjuvant-treated tumors (462 gastric carcinomas and 429 esophageal adenocarcinomas) as well as complementary lymph node and distant metastasis by fluorescence in situ hybridization.

RESULTS

Twenty-six gastric tumors (5.6%) and 21 esophageal adenocarcinomas (4.9%) showed FGFR2 amplification. Overall, 93% of gastric carcinomas and 83% of esophageal carcinomas showed heterogeneous amplification. FGFR2 amplification was found in different histological growth patterns, including intestinal and diffuse type according to the Lauren classification. In the primary gastric carcinoma group, FGFR2 amplification was associated with poor prognosis (p = 0.005).

CONCLUSION

Homogeneous FGFR2 amplification in tumors of the upper GIT is the exception. This has highly relevant implications in the nature of FGFR2 diagnostics (sufficient tumor cell number, determination of amplification at metastasis versus primary tumor, etc.) and on the response probability of appropriate inhibitors. It is relevant that the often poorly treatable and aggressive subtype of diffuse carcinomas (poorly cohesive carcinomas) also shows FGFR2 amplification and that an individualized therapy option with FGFR2 inhibitors could be an option in this group.

The Comprehensive Analysis of Specific Proteins as Novel Biomarkers Involved in the Diagnosis and Progression of Gastric Cancer

Gastric cancer (GC) cases are predicted to rise by 2040 to approximately 1.8 million cases, while GC-caused deaths to 1.3 million yearly worldwide. To change this prognosis, there is a need to improve the diagnosis of GC patients because this deadly malignancy is usually detected at an advanced stage. Therefore, new biomarkers of early GC are sorely needed. In the present paper, we summarized and referred to a number of original pieces of research concerning the clinical significance of specific proteins as potential biomarkers for GC in comparison to well-established tumor markers for this malignancy. It has been proved that selected chemokines and their specific receptors, vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR), specific proteins such as interleukin 6 (IL-6) and C-reactive protein (CRP), matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs), a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS), as well as DNA- and RNA-based biomarkers, and c-MET (tyrosine-protein kinase Met) play a role in the pathogenesis of GC. Based on the recent scientific literature, our review indicates that presented specific proteins are potential biomarkers in the diagnosis and progression of GC as well as might be used as prognostic factors of GC patients' survival.

The potential clinical utility of cell-free DNA for gastric cancer patients treated with nivolumab monotherapy

To assess the potential clinical utility of cell-free DNA (cfDNA)-based biomarkers for identifying gastric cancer (GC) patients who benefit from nivolumab. From 31 GC patients treated with nivolumab monotherapy (240 mg/body, Bi-weekly) in 3rd or later line setting, we prospectively collected blood samples at baseline and before the 3rd dose. We compared cfDNA-based molecular findings, including microsatellite instability (MSI) status, to tissue-based biomarkers. We assessed the clinical value of blood tumor mutation burden (bTMB) and copy number alterations (CNA) as well as the cfDNA dynamics. The concordance between deficient-MMR and cfDNA-based MSI-high was 100% (3/3). Patients with bTMB ≥ 6 mut/Mb had significantly better progression-free survival (PFS) and overall survival (OS); however, such significance disappeared when excluding MSI-High cases. The combination of bTMB and CNA positivity identified patients with survival benefit regardless of MSI status (both PFS and OS, P < 0.001), with the best survival in those with bTMB^≥6mut/Mb and CNA^negative. Moreover, patients with decreased bTMB during treatment had a better disease control rate (P = 0.04) and longer PFS (P = 0.04). Our results suggest that a combination of bTMB and CNA may predict nivolumab efficacy for GC patients regardless of MSI status. bTMB dynamics have a potential utility as an on-treatment biomarker.

ACTA2 Expression Predicts Survival and Is Associated with Response to Immune Checkpoint Inhibitors in Gastric Cancer

PURPOSE

We sought to identify biomarkers that predict overall survival (OS) and response to immune checkpoint inhibitors (ICI) for patients with gastric cancer.

EXPERIMENTAL DESIGN

This was a retrospective study of multiple independent cohorts of patients with gastric cancer. The association between tumor ACTA2 expression and OS and ICI response were determined in patients whose tumors were analyzed with bulk mRNA sequencing. Single-cell RNA sequencing (scRNA-seq) and digital spatial profiling data were used to compare tumors from patients with gastric cancer who did and did not respond to ICI.

RESULTS

Increasing tumor ACTA2 expression was independently associated with worse OS in a 567-patient discovery cohort [HR, 1.28 per unit increase; 95% confidence interval (CI), 1.02-1.62]. This finding was validated in three independent cohorts (n = 974; HR, 1.52 per unit increase; 95% CI, 1.34-1.73). Of the 108 patients treated with ICI, 56% of patients with low ACTA2 expression responded to ICI versus 25% of patients with high ACTA2 expression (P = 0.004). In an analysis of a publicly available scRNA-seq dataset of 5 microsatellite instability-high patients treated with ICI, the patient who responded to ICI had lower tumor stromal ACTA2 expression than the 4 nonresponders. Digital spatial profiling of tumor samples from 4 ICI responders and 5 ICI nonresponders revealed that responders may have lower ACTA2 expression in α-SMA-positive cancer-associated fibroblasts (CAF) than nonresponders (median: 5.00 vs. 5.50).

CONCLUSIONS

ACTA2 expression is associated with survival and ICI response in patients with gastric cancer. ACTA2 expression in CAFs, but not in other cellular compartments, appears to be associated with ICI response.

Recent Progress in Immunotherapy for Gastric Cancer

Gastric cancer (GC) is the fourth leading cause of cancer-related deaths worldwide. Under the standard of care, patients with advanced GC (AGC) have a median survival time of approximately 12-15 months. With the emergence of immunotherapy as a key therapeutic strategy in medical oncology, relevant changes are expected in the systemic treatment of GC. In the phase III ATTRACTION-2 trial, nivolumab, a monoclonal anti-programmed cell death 1 (PD-1) antibody, as a third- or later-line treatment improved overall survival (OS) compared with placebo in patients with AGC. Furthermore, nivolumab in combination with 5-fluorouracil and platinum as a first-line treatment improved OS in patients with human epidermal growth factor receptor-2 (HER2)-negative AGC in the global phase III CheckMate-649 study. Another anti-PD-1 antibody, pembrolizumab, in combination with trastuzumab and cytotoxic chemotherapy as a first-line treatment, significantly improved the overall response rate in patients with HER2-positive AGC. Therefore, immune checkpoint inhibitors (ICIs) are essential components of the current treatment of GC. Subsequent treatments after ICI combination therapy, such as ICI rechallenge or combination therapy with agents having other modes of action, are being actively investigated to date. On the basis of the success of immunotherapy in the treatment of AGC, various clinical trials are underway to apply this therapeutic strategy in the perioperative and postoperative settings for patients with early GC. This review describes recent progress in immunotherapy and potential immunotherapy biomarkers for GC.

Correlation between imaging features on computed tomography and combined positive score of PD-L1 expression in patients with gastric cancer

OBJECTIVE

To explore the correlation between computed tomography (CT) features and combined positive score (CPS) of programmed cell death ligand 1 (PD-L1) expression in patients with gastric cancer (GC).

METHODS

This study reviewed an institutional database of patients who underwent GC operation without neoadjuvant chemotherapy between December 2019 and September 2020. The CPS results of PD-L1 expression of postoperative histological examination were recorded by pathology. Baseline CT features were measured, and their correlation with CPS 5 or 10 score groups of PD-L1 expression was analyzed.

RESULTS

Data for 153 patients with GC were collected. Among them, 124 were advanced GC patients, and 29 were early GC patients. None of the CT features significantly differed between CPS groups with a cutoff score of 5 and a score of 10 in patients with early GC. In advanced GC, the presence of lymph nodes with short diameters >10 mm was significantly different (P=0.024) between the CPS<5 and CPS≥5 groups. CT features such as tumor attenuation in the arterial phase, long and short diameter of the largest lymph node, the sum of long diameter of the two largest lymph nodes, the sum of short diameter of the two largest lymph nodes, and the presence of lymph nodes with short diameters >10 mm significantly differed between the CPS<10 and CPS≥10 groups in advanced GC. The sensitivity, specificity and area under receiver operating characteristic (ROC) curve of logistic regression model for predicting CPS≥10 was 71.7%, 50.0% and 0.671, respectively. Microsatellite instability (MSI) status was significantly different in CPS groups with cutoff score of 5 and 10 in advanced GC patients.

CONCLUSIONS

CT findings of advanced GC patients with CPS≥10 showed greater arterial phase enhancement and larger lymph nodes. CT has the potential to help screen patients suitable for immunotherapy.

Artificial Intelligence-Powered Whole-Slide Image Analyzer Reveals a Distinctive Distribution of Tumor-Infiltrating Lymphocytes in Neuroendocrine Neoplasms

Despite the importance of tumor-infiltrating lymphocytes (TIL) and PD-L1 expression to the immune checkpoint inhibitor (ICI) response, a comprehensive assessment of these biomarkers has not yet been conducted in neuroendocrine neoplasm (NEN). We collected 218 NENs from multiple organs, including 190 low/intermediate-grade NENs and 28 high-grade NENs. TIL distribution was derived from Lunit SCOPE IO, an artificial intelligence (AI)-powered hematoxylin and eosin (H&E) analyzer, as developed from 17,849 whole slide images. The proportion of intra-tumoral TIL-high cases was significantly higher in high-grade NEN (75.0% vs. 46.3%, p = 0.008). The proportion of PD-L1 combined positive score (CPS) ≥ 1 case was higher in high-grade NEN (85.7% vs. 33.2%, p < 0.001). The PD-L1 CPS ≥ 1 group showed higher intra-tumoral, stromal, and combined TIL densities, compared to the CPS < 1 group (7.13 vs. 2.95, p < 0.001; 200.9 vs. 120.5, p < 0.001; 86.7 vs. 56.1, p = 0.004). A significant correlation was observed between TIL density and PD-L1 CPS (r = 0.37, p < 0.001 for intra-tumoral TIL; r = 0.24, p = 0.002 for stromal TIL and combined TIL). AI-powered TIL analysis reveals that intra-tumoral TIL density is significantly higher in high-grade NEN, and PD-L1 CPS has a positive correlation with TIL densities, thus showing its value as predictive biomarkers for ICI response in NEN.

Esophagogastric Cancers: Integrating Immunotherapy Therapy Into Current Practice

Immunotherapy (IO) agents have led to significant improvements in patient outcomes across many tumor types. There have been great efforts to introduce immune checkpoint inhibitors into the treatment paradigm of esophagogastric cancers as well. A number of randomized phase III trials, which will be reviewed here, established the role of these agents in both early-stage and advanced-stage disease. Adjuvant nivolumab is US Food and Drug Administration-approved after neoadjuvant chemoradiation and resection of esophageal and gastroesophageal junction cancers on the basis of the phase III CheckMate 577 trial. In the advanced setting, patients with programmed death receptor ligand-1-positive tumors should be recommended IO in combination with chemotherapy in the first-line setting on the basis of the results from KEYNOTE 590, CheckMate 649, and CheckMate 648. Across trials, chemotherapy continues to play a critical role in the first-line setting and should be offered to all patients who are eligible for systemic therapy, including those with biomarker select tumors. In the later lines of treatment, IO has modest activity, and prior studies have grown largely irrelevant because of the enrollment of IO-naive patients. Similar to other disease types, patients with microsatellite unstable (microsatellite instability high) tumors represent a unique cohort that is more sensitive to IO. However, there are no randomized studies evaluating how best to apply IO in early or advanced stages specifically for the treatment of patients with microsatellite instability high upper GI tumors. Questions remain how to best select patients who benefit from IO treatments, how to augment IO activity in programmed death receptor ligand-1-negative tumors, and how to incorporate IO in late-line settings or for recurrent disease that has been treated with IO-containing regimens during early stages.

SFRP4 Is a Potential Biomarker for the Prognosis and Immunotherapy for Gastric Cancer

Purpose

Secreted frizzled-related protein 4 (SFRP4) is a member of the SFRP family, which functions as either a tumor suppressor or a prooncogenic factor in distinct tumor types. Our research aimed to explore the expression of SFRP4 in gastric cancer, its prognostic significance, and its relationship with immune cell infiltration.

Materials and Methods

Gastric cancer and paracancerous tissue specimens from surgically resected gastric cancer patients were collected to construct tissue microarrays, and immunohistochemistry was used to detect the expression of SFRP4, PD-L1, CD3⁺T, CD4⁺T, and CD8⁺T in these microarrays. The differential expression of SFRP4 and its relationship with the immune microenvironment were evaluated using the TIMER and TISIDB databases. Finally, patient survival was assessed.

Results

SFRP4 expression was elevated in gastric cancer tissues and linked to a poor prognosis (P=0.021). The 5-year survival rate for patients with high SFRP4 expression was only 39.81% but reached 60.02% for patients with low SFRP4 expression. Increased SFRP4 expression correlated with high CD8⁺ T-cell infiltration (P=0.015) and positive PD-L1 expression (P=0.036). High SFRP4 expression was an independent predictor of overall survival (P=0.024 in univariable analysis, P=0.011 in multivariable analysis). Using online databases, we found that SFRP4 expression was higher in gastric cancer tissues and substantially was associated with the immune microenvironment.

Conclusion

SFRP4 is an oncogenic driver that can predict patient survival time in gastric cancer, as well as an important immune-related factor. SFRP4 may be important for guiding immunotherapy in gastric cancer patients.

Inhibition of MACC1-Induced Metastasis in Esophageal and Gastric Adenocarcinomas

Simple Summary

Esophageal and Gastric Adenocarcinomas (AGE/S) are characterized by early metastasis and poor survival. MACC1 (Metastasis Associated in Colon Cancer 1) acts in colon cancer as a metastasis inducer and is linked to reduced survival. In this study, we analyzed the prognostic role of MACC1 in a large AGE/S cohort and the potential of MACC1 inhibition in vitro and in vivo. MACC1 is an independent negative prognostic marker in our cohort. In vitro, migration was enhanced by MACC1 in overexpressing cells. This MACC1-related effect could be inhibited by using selumetinib in vitro. In vivo, MACC1 induced faster and larger metastasis development, which could be inhibited by selumetinib. In conclusion, MACC1 is a strong negative prognostic factor in AGE/S and is a potential target for therapy with selumetinib.

Abstract

Esophageal and Gastric Adenocarcinomas (AGE/S) are characterized by early metastasis and poor survival. MACC1 (Metastasis Associated in Colon Cancer 1) acts in colon cancer as a metastasis inducer and is linked to reduced survival. This project illuminates the role and potential for the inhibition of MACC1 in AGE/S. Using 266 of 360 TMAs and survival data of AGE/S patients, we confirm the value of MACC1 as an independent negative prognostic marker in AGE/S patients. MACC1 gene expression is correlated with survival and morphological characteristics. In vitro analysis of lentivirally MACC1-manipulated subclones of FLO-1 and OE33 showed enhanced migration induced by MACC1 in both cell line models, which could be inhibited by the MEK1 inhibitor selumetinib. In vivo, the efficacy of selumetinib on tumor growths and metastases of MACC1-overexpressing FLO-1 cells xenografted intrasplenically in NOG mice was tested. Mice with high-MACC1-expressing cells developed faster and larger distant metastases. Treatment with selumetinib led to a significant reduction in metastasis exclusively in the MACC1-positive xenografts. MACC1 is an enhancer of tumor aggressiveness and a predictor of poor survival in AGE/S. This effect can be inhibited by selumetinib.

Combined Positive Score for Programmed Death Ligand-1 Expression and Inflammatory Microenvironment in Gastrointestinal Stromal Tumors

Background and Objectives: GISTs are the most frequent type of mesenchymal neoplasm of the digestive tract. The prognosis is mainly determined by tumor dimensions, mitotic rate and location, but other less well-documented factors can influence evolution and survival. The immune microenvironment and checkpoint molecule expression were proven to impact the prognosis in different types of cancer. The aim of this study was to determine PD-L1 expression in GISTs and to evaluate the level of intratumoral immune infiltration in relation to prognostic variables and survival. Materials and Methods: Sixty-five GISTs diagnosed in the same institution between 2015 and 2018 were immunohistochemically tested for PD-L1 and evaluated using CPS. Immune cells were emphasized, with CD3, CD4, CD8, CD20 and CD68 antibodies and quantified. All data were processed using statistical tools. Results: The median age was 61 years (range, 28-78) and 36 patients (55.4%) were males. The location of the tumors was predominantly gastric (46%), followed by the small bowel (17%) and colorectal (6%). In addition, 11% were EGISTs and 20% were secondary tumors (11% metastases and 9% local recurrences). PD-L1 had a variable expression in tumor and inflammatory cells, with a CPS ranging from 0 to 100. Moreover, 64.6% of cases were PD-L1 positive with no significant differences among categories of variables, such as the age and the sex of the patient, tumor location, the primary or secondary character of the tumor, dimensions, mitotic rate, the risk of disease progression and tumor cell type. Immune cells had a variable distribution throughout the tumors. CD3+ lymphocytes were the most frequent type. CD20+ cells were identified in a larger number in tumors ≤5 cm (p = 0.038). PD-L1-positive tumors had a higher number of immune cells, particularly CD3+, CD20+ and CD68+, in comparison to PD-L1-negative ones (p = 0.032, p = 0.051, p = 0.008). Epithelioid and mixed cell-type tumors had a higher number of CD68+ cells. Survival was not influenced by PD-L1 expression; instead, it was decreased in multifocal tumors (p = 0.0001) and in cases with Ki67 ≥ 50% (p = 0.008). Conclusions: PD-L1-positive expression and the presence of different immune cell types, in variable quantities, can contribute to a better understanding of the complex interactions between tumor cells and the microenvironment, with a possible therapeutic role in GISTs.