Deep learning based digital pathology for predicting treatment response to first-line PD-1 blockade in advanced gastric cancer.

BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemotherapy alone as the first-line therapy. However, with the Food and Drug Administration's (FDA) 2022 approval of programmed cell death protein 1 (PD-1) inhibitor combined with chemotherapy as the first-li ne treatment for advanced unresectable GC, patients have significantly benefited. However, the significant costs and potential adverse effects necessitate precise patient selection. In recent years, the advent of deep learning (DL) has revolutionized the medical field, particularly in predicting tumor treatment responses. Our study utilizes DL to analyze pathological images, aiming to predict first-line PD-1 combined chemotherapy response for advanced-stage GC. METHODS: In this multicenter retrospective analysis, Hematoxylin and Eosin (H&E)-stained slides were collected from advanced GC patients across four medical centers. Treatment response was evaluated according to iRECIST 1.1 criteria after a comprehensive first-line PD-1 immunotherapy combined with chemotherapy. Three DL models were employed in an ensemble approach to create the immune checkpoint inhibitors Response Score (ICIsRS) as a novel histopathological biomarker derived from Whole Slide Images (WSIs). RESULTS: Analyzing 148,181 patches from 313 WSIs of 264 advanced GC patients, the ensemble model exhibited superior predictive accuracy, leading to the creation of ICIsNet. The model demonstrated robust performance across four testing datasets, achieving AUC values of 0.92, 0.95, 0.96, and 1 respectively. The boxplot, constructed from the ICIsRS, reveals statistically significant disparities between the well response and poor response (all p-values < = 0.001). CONCLUSION: ICIsRS, a DL-derived biomarker from WSIs, effectively predicts advanced GC patients' responses to PD-1 combined chemotherapy, offering a novel approach for personalized treatment planning and allowing for more individualized and potentially effective treatment strategies based on a patient's unique response situations.

YAP1-CPNE3 positive feedback pathway promotes gastric cancer cell progression.

Hippo-Yes-associated protein 1 (YAP1) plays an important role in gastric cancer (GC) progression; however, its regulatory network remains unclear. In this study, we identified Copine III (CPNE3) was identified as a novel direct target gene regulated by the YAP1/TEADs transcription factor complex. The downregulation of CPNE3 inhibited proliferation and invasion, and increased the chemosensitivity of GC cells, whereas the overexpression of CPNE3 had the opposite biological effects. Mechanistically, CPNE3 binds to the YAP1 protein in the cytoplasm, inhibiting YAP1 ubiquitination and degradation mediated by the E3 ubiquitination ligase ß-transducin repeat-containing protein (ß-TRCP). Thereby activating the transcription of YAP1 downstream target genes, which creates a positive feedback cycle to facilitate GC progression. Immunohistochemical analysis demonstrated significant upregulation of CPNE3 in GC tissues. Survival and Cox regression analyses indicated that high CPNE3 expression was an independent prognostic marker for GC. This study elucidated the pivotal involvement of an aberrantly activated CPNE3/YAP1 positive feedback loop in the malignant progression of GC, thereby uncovering novel prognostic factors and therapeutic targets in GC.

TMEM160 promotes tumor immune evasion and radiotherapy resistance via PD-L1 binding in colorectal cancer.

BACKGROUND: The effectiveness of anti-programmed cell death protein 1(PD-1)/programmed cell death 1 ligand 1(PD-L1) therapy in treating certain types of cancer is associated with the level of PD-L1. However, this relationship has not been observed in colorectal cancer (CRC), and the underlying regulatory mechanism of PD-L1 in CRC remains unclear. METHODS: Binding of TMEM160 to PD-L1 was determined by co-immunoprecipitation (Co-IP) and GST pull-down assay.The ubiquitination levels of PD-L1 were verified using the ubiquitination assay. Phenotypic experiments were conducted to assess the role of TMEM160 in CRC cells. Animal models were employed to investigate how TMEM160 contributes to tumor growth.The expression and clinical significance of TMEM160 and PD-L1 in CRC tissues were evaluated by immunohistochemistry(IHC). RESULTS: In our study, we made a discovery that TMEM160 interacts with PD-L1 and plays a role in stabilizing its expression within a CRC model. Furthermore, we demonstrated that TMEM160 hinders the ubiquitination-dependent degradation of PD-L1 by competing with SPOP for binding to PD-L1 in CRC cells. Regarding functionality, the absence of TMEM160 significantly inhibited the proliferation, invasion, metastasis, clonogenicity, and radioresistance of CRC cells, while simultaneously enhancing the cytotoxic effect of CD8 + T cells on tumor cells. Conversely, the upregulation of TMEM160 substantially increased these capabilities. In severely immunodeficient mice, tumor growth derived from lentiviral vector shTMEM160 cells was lower compared with that derived from shNC control cells. Furthermore, the downregulation of TMEM160 significantly restricted tumor growth in immune-competent BALB/c mice. In clinical samples from patients with CRC, we observed a strong positive correlation between TMEM160 expression and PD-L1 expression, as well as a negative correlation with CD8A expression. Importantly, patients with high TMEM160 expression exhibited a worse prognosis compared with those with low or no TMEM160 expression. CONCLUSIONS: Our study reveals that TMEM160 inhibits the ubiquitination-dependent degradation of PD-L1 that is mediated by SPOP, thereby stabilizing PD-L1 expression to foster the malignant progress, radioresistance, and immune evasion of CRC cells. These findings suggest that TMEM160 holds potential as a target for the treatment of patients with CRC.

Unleashing the potential of combining FGFR inhibitor and immune checkpoint blockade for FGF/FGFR signaling in tumor microenvironment.

BACKGROUND: Fibroblast growth factors (FGFs) and their receptors (FGFRs) play a crucial role in cell fate and angiogenesis, with dysregulation of the signaling axis driving tumorigenesis. Therefore, many studies have targeted FGF/FGFR signaling for cancer therapy and several FGFR inhibitors have promising results in different tumors but treatment efficiency may still be improved. The clinical use of immune checkpoint blockade (ICB) has resulted in sustained remission for patients. MAIN: Although there is limited data linking FGFR inhibitors and immunotherapy, preclinical research suggest that FGF/FGFR signaling is involved in regulating the tumor microenvironment (TME) including immune cells, vasculogenesis, and epithelial-mesenchymal transition (EMT). This raises the possibility that ICB in combination with FGFR-tyrosine kinase inhibitors (FGFR-TKIs) may be feasible for treatment option for patients with dysregulated FGF/FGFR signaling. CONCLUSION: Here, we review the role of FGF/FGFR signaling in TME regulation and the potential mechanisms of FGFR-TKI in combination with ICB. In addition, we review clinical data surrounding ICB alone or in combination with FGFR-TKI for the treatment of FGFR-dysregulated tumors, highlighting that FGFR inhibitors may sensitize the response to ICB by impacting various stages of the "cancer-immune cycle".

Pan-cancer analysis reveals potential of FAM110A as a prognostic and immunological biomarker in human cancer.

Background: Despite great success, immunotherapy still faces many challenges in practical applications. It was previously found that family with sequence similarity 110 member A (FAM110A) participate in the regulation of the cell cycle and plays an oncogenic role in pancreatic cancer. However, the prognostic value of FAM110A in pan-cancer and its involvement in immune response remain unclear. Methods: The Human Protein Atlas (HPA) database was used to detect the expression of FAM110A in human normal tissues, the Tumor Immune Estimation Resource (TIMER) and TIMER 2.0 databases were used to explore the association of FAM110A expression with immune checkpoint genes and immune infiltration, and the Gene Set Cancer Analysis (GSCA) database was used to explore the correlation between FAM110A expression and copy number variations (CNV) and methylation. The LinkedOmics database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Statistical analysis and visualization of data from the The Cancer Genome Atlas (TCGA) or the Genotype-Tissue Expression (GTEx) databases were performed using the R software (version 3.6.3). Clinical samples were validated using immunohistochemistry. Results: FAM110A expression was elevated in most tumor tissues compared with that in normal tissues. CNV and methylation were associated with abnormal FAM110A mRNA expression in tumor tissues. FAM110A affected prognosis and was associated with the expression of multiple immune checkpoint genes and abundance of tumor-infiltrating immune cells across multiple types of cancer, especially in liver hepatocellular carcinoma (LIHC). FAM110A-related genes were involved in multiple immune-related processes in LIHC. Conclusion: FAM110A participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in LIHC. FAM110A may serve as a prognostic and immunological biomarker for human cancer.