Clinicopathological significance and immunotherapeutic outcome of claudin 18.2 expression in advanced gastric cancer: A retrospective study.

Objective: Immunotherapeutic outcomes and clinical characteristics of claudin 18 isoform 2 positive (CLDN18.2-positive) gastric cancer (GC) vary in different clinical studies, making it difficult to optimize anti-CLDN18.2 therapy. We conducted a retrospective analysis to explore the association of CLDN18.2 expression with clinicopathological characteristics and immunotherapeutic outcomes in GC. Methods: A total of 536 advanced GC patients from 2019 to 2021 in the CT041-CG4006 and CT041-ST-01 clinical trials were included in the analysis. CLDN18.2 expression on ≥40% of tumor cells (2+, 40%) and CLDN18.2 expression on ≥70% of tumor cells (2+, 70%) were considered the two levels of positively expressed GC. The clinicopathological characteristics and immunotherapy outcomes of GC patients were analyzed according to CLDN18.2 expression status. Results: CLDN18.2 was expressed in 57.6% (cut-off: 2+, 40%) and 48.9% (cut-off: 2+, 70%) of patients. Programmed death-ligand 1 (PD-L1) and CLDN18.2 were co-expressed in 19.8% [combined positive score (CPS)≥1, CLDN18.2 (cut-off: 2+, 40%)] and 17.2% [CPS≥5, CLDN18.2 (cut-off: 2+, 70%)] of patients. CLDN18.2 expression positively correlated with younger age, female sex, non-gastroesophageal junction (non-GEJ), and diffuse phenotype (P<0.001). HER2 and PD-L1 expression were significantly lower in CLDN18.2-positive GC (both P<0.05). Uterine adnexa metastasis (P<0.001) was more frequent and liver metastasis (P<0.001) was less common in CLDN18.2-positive GC. Overall survival and immunotherapy-related progression-free survival (irPFS) were inferior in the CLDN18.2-positive group. Conclusions: CLDN18.2-positive GC is associated with poor prognosis and worse immunotherapeutic outcomes. The combination of anti-CLDN18.2 therapy, anti-PD-L1/PD-1 therapy, and chemotherapy for GC requires further investigation.

Tracking circulating PD-L1-positive cells to monitor the outcome of patients with gastric cancer receiving anti-HER2 plus anti-PD-1 therapy.

Dual blockade of HER2 and PD-1/PD-L1 is the most promising regimen for HER2-positive patients with gastric cancer (GC); PD-L1 combined positive score, rather than HER2 status, indicates potential benefit. Circulating tumor cells (CTCs) and circulating endothelial cells (CECs) derived from the tumor microenvironment provide platforms for the dynamic evaluation of PD-L1 expression. Whether PD-L1 positive CTCs/CECs (PD-L1+CTCs/CECs) can serve as biomarkers for evaluating the efficacy of combination therapy remains unknown. Therefore, this study investigated PD-L1 expression and heterogeneous karyotypic features of CTCs/CECs and their involvement in the clinical response to treatment in 72 patients with advanced GC by applying a pre-established surface molecule-independent subtraction enrichment (SE)-iFISH strategy. In the captured PD-L1 positive cells, there were 42.80% and 57.20% of CTCs and CECs, respectively. PD-L1+ CTCs were pre-therapeutically detected in 0% (0/11) of HER2-negative patients and 14.75% (9/61) of HER2-positive patients. The presence of baseline PD-L1+CTCs was relevant to inferior prognosis (mPFS: 14.40 months vs 5.00 months, P = 0.065); post-treatment PD-L1+ CECs were associated with longer irPFS (immunotherapeutic-related PFS) (mPFS: 15.57 months vs 6.73 months, P = 0.053). Further dynamic karyotype-based profiling of PD-L1+ CTCs/CECs indicated that multiploidy and triploidy were the dominant subtypes of baseline PD-L1+ CTCs, and that triploidy was specifically associated with therapeutic resistance. Intratherapeutically detected multiploid PD-L1+ CECs demonstrated a superior clinical response; triploidy and tetraploidy contributed to acquired resistance. The karyotypic features of PD-L1+CTCs/CECs should be dynamically profiled in patients with GC treated with anti-HER2 plus anti-PD-1 therapy. Triploid-PD-L1+ CTCs and multiploid-PD-L1+ CECs are potential indicators of therapeutic response.

Multidimensional immune profiling in Gastric Cancer Multiplex Immunohistochemistry Atlas from Peking University Cancer Hospital project informs PD-1/PD-L1 blockade efficacy.

BACKGROUND: Immunotherapy has resulted in impressive objective response rates and durable tumour remission, but only in a subset of gastric cancer (GC) patients. The PD-L1 combined positive score is the most widely used tissue-based biomarker for anti-PD-1/PD-L1 therapy; however, this unidimensional method has limitations. Next-generation exploration of tissue-based biomarkers for GC requires characterisation of various cellular markers and key immunoregulatory molecule expression in situ. Thus, a complete, stepwise solution covering the entire process from staining samples to cross-site utilisation of pathomics data is urgently needed. METHODS: With the advanced multispectral imaging analysis method, web-based data repository, and interactive sharing technology, we conducted a project entitled Gastric Cancer Multiplex Immunohistochemistry Atlas from Peking University Cancer Hospital (GMAP). We propose a standard pipeline covering sample collection, staining, scanning multispectral images, constructing a spectral library, identifying and phenotyping cells, positioning each element, and quantitatively extracting immune features. We designed an open-access relational database to explore tissue-based biomarkers to determine PD-1/PD-L1 blockade efficacy. RESULTS: The GMAP project detected the functional status and spatial location of more than 50 million cells using 15 markers in 80 GC patients, based on which billions of cell pairs were recognised, highlighting the rich spatial arrangement information and the fine tumour microenvironment structure. We generated a tumour-immune atlas using the count and spatial features of 65 immune cell types. We eventually selected the indicators and built a comprehensive risk-scoring system. Patients with higher risk score showed superior immunotherapy-related progression-free survival (irPFS) (hazard ratio [HR]: 3.19; P < 0.001; median irPFS: 4.87 versus 19.87months, respectively) and immunotherapy-related overall survival (HR: 3.10; P = 0.001; median irPFS: 10.03 versus 24.87months, respectively) compared with lower risk patients, demonstrating their potential for guiding anti-PD-1/PD-L1-based immunotherapy. Importantly, an easy-to-use and versatile web server was built to promote tissue-based biomarker exploration in GC. CONCLUSION: The GMAP project highlighted the clinical value of tissue-based immune features as biomarkers for immunotherapeutic decision-making. We present a well-designed, detailed workflow for the orderly generation and use of a high-quality, spatially resolved pathological database.

ANO1-Mediated Inhibition of Cancer Ferroptosis Confers Immunotherapeutic Resistance through Recruiting Cancer-Associated Fibroblasts.

The application of immunotherapy in gastrointestinal (GI) cancers remains challenging because of the limited response rate and emerging therapeutic resistance. Combining clinical cohorts, multi-omics study, and functional/molecular experiments, it is found that ANO1 amplification or high-expression predicts poor outcomes and resistance to immunotherapy for GI cancer patients. Knocking-down or inhibiting ANO1 suppresses the growth/metastasis/invasion of multiple GI cancer cell lines, cell-derived xenograft, and patient-derived xenograft models. ANO1 contributes to an immune-suppressive tumor microenvironment and induces acquired resistance to anti-PD-1 immunotherapy, while ANO1 knockdown or inhibition enhances immunotherapeutic effectiveness and overcomes resistance to immunotherapy. Mechanistically, through inhibiting cancer ferroptosis in a PI3K-Akt signaling-dependent manner, ANO1 enhances tumor progression and facilitates cancer-associated fibroblast recruitment by promoting TGF-ß release, thus crippling CD8+ T cell-mediated anti-tumor immunity and generating resistance to immunotherapy. This work highlights ANO1's role in mediating tumor immune microenvironment remodeling and immunotherapeutic resistance, and introduces ANO1 as a promising target for GI cancers' precision treatment.

Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade.

BACKGROUND: Systemic Immune-inflammation Index (SII) and body composition parameters are easily assessed, and can predict overall survival (OS) in various cancers, allowing early intervention. This study aimed to assess the correlation between CT-derived body composition parameters and SII and OS in patients with advanced gastric cancer receiving dual programmed death-1 (PD-1) and human epidermal growth factor receptor 2 (HER2) blockade. MATERIALS AND METHODS: This retrospective study enrolled patients with advanced gastric cancer treated with dual PD-1 and HER2 blockade from March 2019 to June 2022. We developed a deep learning model based on nnU-Net to automatically segment skeletal muscle, subcutaneous fat and visceral fat at the third lumbar level, and calculated the corresponding Skeletal Muscle Index, skeletal muscle density, subcutaneous fat area (SFA) and visceral fat area. SII was computed using the formula that total peripheral platelet count×neutrophil/lymphocyte ratio. Univariate and multivariate Cox regression analysis were used to determine the associations between SII, body composition parameters and OS. RESULTS: The automatic segmentation deep learning model was developed to efficiently segment body composition in 158 patients (0.23 s/image). Multivariate Cox analysis revealed that high SII (HR=2.49 (95% CI 1.54 to 4.01), p<0.001) and high SFA (HR=0.42 (95% CI 0.24 to 0.73), p=0.002) were independently associated with OS, whereas sarcopenia was not an independent prognostic factor for OS (HR=1.41 (95% CI 0.86 to 2.31), p=0.173). In further analysis, patients with high SII and low SFA had worse long-term prognosis compared with those with low SII and high SFA (HR=8.19 (95% CI 3.91 to 17.16), p<0.001). CONCLUSION: Pretreatment SFA and SII were significantly associated with OS in patients with advanced gastric cancer. A comprehensive analysis of SII and SFA may improve the prognostic stratification of patients with gastric cancer receiving dual PD-1 and HER2 blockade.

Extracellular Vesicle-Derived Protein File from Peripheral Blood Predicts Immune-Related Adverse Events in Gastric Cancer Patients Receiving Immunotherapy.

Immune checkpoint inhibitors (ICIs) initiate a new stage for gastric cancer (GC) therapeutics, and plenty of patients have already benefited from ICIs. Liquid biopsy promotes the development of precision medicine of GC. However, due to the lack of precision biomarkers of immune-related adverse events (irAEs), the safety of ICIs-treated GC patients cannot be guaranteed. In our study, GC patients treated with ICIs were included for investigating the correlation between irAEs of ICIs and corresponding outcomes. We also explored the potential of biomarkers of irAEs via EV-derived proteins. Dynamic plasma was taken from 102 ICIs-treated GC patients generated retrospectively or prospectively, who were divided into discovery and validating cohorts. Plasma EV-derived protein profiles were described, and two EV-proteins, inducible T-cell co-stimulator (EV-ICOS) and indoleamine 2,3-dioxygenase 1(EV-IDO1), from 42 vital proteins were screened to predict the prognosis of ICIs with irAEs. Our work is the first to propose that EV-proteins can predict ICIs-corresponding irAEs, which can be conducive to the diagnosis and treatment of GC patients, and to facilitate the screening of beneficiaries.

Plasma extracellular vesicle derived protein profile predicting and monitoring immunotherapeutic outcomes of gastric cancer.

Immune checkpoint inhibitor (ICI)-based immunotherapy brought new hope for gastric cancer (GC) treatment. However, due to the lack of proper biomarkers, patient selection and outcome prediction for GC's immunotherapy remain unsatisfying. In this study, through applying an extracellular vesicle (EV) protein expression array, we assessed the correlation of plasma EV-derived protein spectrum with outcomes of ICI-related therapeutic combinations. Plasma from 112 GC patients received ICI-related therapies were investigated retrospectively/prospectively as three cohorts. We identified four plasma EV-derived proteins (ARG1/CD3/PD-L1/PD-L2) from 42 crucial candidate proteins and combined them as an EV-score that robustly predicting immunotherapeutic outcomes at baseline and dynamically monitoring disease progression along with treatment. High EV-score reflected microenvironmental features of stronger antitumour immunity, characterized by more activated CD8+ T/NK cells, higher TH1/TH2 ratio and higher expressions of IFN-γ/perforin/granzymes in paired peripheral blood, which were verified by dataset analysis and in vivo experiments. EV-score≥1 GC received more therapeutic benefits from ICIs, while EV-score < 1 GC potentially benefited more from ICIs combining HER2-targeted therapies. Collectively, through proposing a plasma EV-score on protein level that powerfully predicting and monitoring GC's immunotherapeutic outcomes, our work facilitated clinical patient selection and decision-makings, and provided mechanistical insights for immunotherapy-related microenvironmental changes and improvements for current ICI-regimens.

Integrative analysis of genomic, epigenomic and transcriptomic data identified molecular subtypes of esophageal carcinoma.

Esophageal cancer (EC) involves many genomic, epigenetic and transcriptomic disorders, which play key roles in the heterogeneous progression of cancer. However, the study of EC with multi-omics has not been conducted. This study identified a high consistency between DNA copy number variations and abnormal methylations in EC by analyzing genomics, epigenetics and transcriptomics data and investigating mutual correlations of DNA copy number variation, methylation and gene expressions, and stratified copy number variation genes (CNV-Gs) and methylation genes (MET-Gs). The methylation, CNVs and expression profiles of CNV-Gs and MET-Gs were analyzed by consistent clustering using iCluster integration, here, we determined three subtypes (iC1, iC2, iC3) with different molecular traits, prognostic characteristics and tumor immune microenvironment features. We also identified 4 prognostic genes (CLDN3, FAM221A, GDF15 and YBX2) differentially expressed in the three subtypes, and could therefore be used as representative biomarkers for the three subtypes of EC. In conclusion, by performing comprehensive analysis on genomic, epigenetic and transcriptomic regulations, the current study provided new insights into the multilayer molecular and pathological traits of EC, and contributed to the precision medication for EC patients.

Ultrasensitive Gastric Cancer Circulating Tumor Cellular CLDN18.2 RNA Detection Based on a Molecular Beacon.

Gastric cancer (GC) is a major global cancer burden, and only HER2-targeted therapies have been approved in first line clinical therapy. CLDN18.2 has been regarded as a potential therapeutic target for gastrointestinal tumors, and global clinical trials have been in process. Hence, the precise, efficient, and noninvasive detection of CLDN18.2 expression is important for the effective application of this attractive target. A high similarity of protein sequence between CLDN18.1 and -18.2 made RNA become more suitable for the detection of CLDN18.2 expression. In this study, CLDN18.2 molecular beacon (MB) with a stem-loop hairpin structure was optimized by phosphorothioate and 2'-O-methyl for stability and efficiency. The MB could recognize CLDN18.2 RNA rapidly. Its resolution and selectivity has been verified in several model cells, demonstrating that MB can distinguish CLDN18.2 expression in several model cells. Furthermore, it was applied successfully to the circulating tumor cell (CTC) assay. The concordance in the expression of CLDN18.2 between CTCs and tissue biopsy is 100% (negative: 3 vs 3; positive: 7 vs 7), indicating that CLDN18.2 RNA detection in CTCs based on a MB will be a promising approach for searching potential patients to CLDN 18.2 targeted drug.

Clinical implications of plasma ctDNA features and dynamics in gastric cancer treated with HER2-targeted therapies.

BACKGROUND: Gastric cancer (GC) is confronted with limited options for precision medicine. Human epidermal growth factor receptor 2 (HER2) is the principal druggable target of GC, yet proper biomarkers for response/resistance prediction remain unveiled. METHODS: From 40 GC patients received HER2-targeted therapy, a total of 327 peripheral blood plasma specimens was collected including baseline and treatment time points. Circulating tumor DNA (ctDNA) was extracted and sequenced with a target panel of 425 genes. Experimental validation of resistant mutations was carried out in NIH-3T3 cell line. RESULTS: Genomic features, including ERBB2 copy number variation (CNV), total copy number load, and tumor mutation burdens (TMBs), dynamically changed along with the treatment process and correlated with disease progression. Plasma ctDNA-based diagnosis was more sensitive than conventional computed tomography scanning in 40% of investigated patients, gaining additional time for clinical management. Compared to baseline, new gene alterations were emerged in 12 patients who developed drug resistance during treatment. ERBB2 mutations potentially related to Pyrotinib resistance were identified in plasma ctDNA of one patient and functional analysis of their downstream signaling pathways was carried out in NIH-3T3 cell line. TMB exhibited more power than ERBB2 CNV in predicting treatment responses and prognosis for HER2-targeted therapy in GC patients. Interestingly, survival analysis indicated that patients harboring both HER2 (ERBB2) positivity and high TMB might gain more therapeutic benefits from immune checkpoint inhibitors instead of HER2-targeted regimens that required further studies and validations CONCLUSIONS: Our work showed that the dynamic surveillance of plasma ctDNA genomic features provided instructive information for the precision medication of GC patients.