Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease refractory to all targeted and immune therapies. However, our understanding of PDAC microenvironment especially the metastatic microenvironment is very limited partly due to the inaccessibility to metastatic tumor tissues. Here, we present the single-cell transcriptomic landscape of synchronously resected PDAC primary tumors and matched liver metastases. We perform comparative analysis on both cellular composition and functional phenotype between primary and metastatic tumors. Tumor cells exhibit distinct transcriptomic profile in liver metastasis with clearly defined evolutionary routes from cancer cells in primary tumor. We also identify specific subtypes of stromal and immune cells critical to the formation of the pro-tumor microenvironment in metastatic lesions, including RGS5⁺ cancer-associated fibroblasts, CCL18⁺ lipid-associated macrophages, S100A8⁺ neutrophils and FOXP3⁺ regulatory T cells. Cellular interactome analysis further reveals that the lack of tumor-immune cell interaction in metastatic tissues contributes to the formation of the immunosuppressive microenvironment. Our study provides a comprehensive characterization of the transcriptional landscape of PDAC liver metastasis.

Chromatin accessibility is critical for tumor development, whose mechanisms remain unclear. As a crucial regulator for chromatin remodeling, BRD4 promotes tumor progression by regulating multiple genes. As a small-molecule inhibitor of BRD4, JQ1 has potent chemotherapeutic activity against various human cancers. However, whether JQ1 has potential anti-tumor effects and how JQ1 regulates global transcription in gastric cancer (GC) remain largely unknown. In this research, we found BRD4 was highly expressed in GC tissues and was significantly associated with poor prognosis. JQ1 inhibited the proliferation and induced apoptosis of GC cells in vitro. Besides, JQ1 suppressed the migration and invasion of cancer cells by inducing MET. Notably, an assay for transposase-accessible chromatin using sequencing (ATAC-seq) data showed that JQ1 obviously downregulated the chromatin accessibility of GC cells and differentially accessible regions were highly enriched for RUNX2-binding motifs. Combinational analysis of ATAC-seq and RNA-seq data discovered NID1 as the downstream target of JQ1 and JQ1 reduced NID1 expression in GC cells. Chromatin immunoprecipitation, luciferase reporter gene assay, and rescue experiments all confirmed that RUNX2/NID1 axis was responsible for JQ1-inhibiting metastasis of GC cells. What’s more, high expression of NID1 in GC tissues also predicted poor survival outcome of cancer patients and NID1 knockdown prohibited migration and invasion of cancer cells via partially inducing MET. Finally, in vivo models showed that JQ1 prevented GC growth and suppressed cancer metastasis. In conclusion, JQ1 inhibits the malignant progression of GC by downregulating chromatin accessibility and inactivating RUNX2/NID1 signaling. In addition, NID1 is also a novel therapeutic target for progressive GC patients.

We aimed to develop a deep learning-based segmentation system for rapid on-site cytopathology evaluation (ROSE) to improve the diagnostic efficiency of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) biopsy. A retrospective, multicenter, diagnostic study was conducted using 5345 cytopathological slide images from 194 patients who underwent EUS-FNA. These patients were from Nanjing Drum Tower Hospital (109 patients), Wuxi People's Hospital (30 patients), Wuxi Second People's Hospital (25 patients), and The Second Affiliated Hospital of Soochow University (30 patients). A deep convolutional neural network (DCNN) system was developed to segment cell clusters and identify cancer cell clusters with cytopathological slide images. Internal testing, external testing, subgroup analysis, and human–machine competition were used to evaluate the performance of the system. The DCNN system segmented stained cells from the background in cytopathological slides with an F1-score of 0·929 and 0·899–0·938 in internal and external testing, respectively. For cancer identification, the DCNN system identified images containing cancer clusters with AUCs of 0·958 and 0·948–0·976 in internal and external testing, respectively. The generalizable and robust performance of the DCNN system was validated in sensitivity analysis (AUC > 0·900) and was superior to that of trained endoscopists and comparable to cytopathologists on our testing datasets. The DCNN system is feasible and robust for identifying sample adequacy and pancreatic cancer cell clusters. Prospective studies are warranted to evaluate the clinical significance of the system. Jiangsu Natural Science Foundation; Nanjing Medical Science and Technology Development Funding; National Natural Science Foundation of China.

Background: Pancreatic cancer (PC) has a dismal prognosis due to its insidious early symptoms and poor early detection rate. Exosomes can be released by various cell types and tend to be a potential novel biomarker for PC detection. In this study, we explored the proteomic profiles of plasma exosomes collected from patients with PC at different stages and other pancreatic diseases.Methods: Plasma samples were collected from six groups of patients, including PC at stage I/II, PC at stage III/IV, well-differentiated pancreatic neuroendocrine tumor (P-NET), pancreatic cystic lesions (PCLs), chronic pancreatitis (CP), and healthy controls (HCs). Plasma-derived exosomes were isolated by ultracentrifugation and identified routinely. Isobaric tags for relative and absolute quantification (iTRAQ) based proteomic analysis along with bioinformatic analysis were performed to elucidate the biological functions of proteins. The expression of exosomal ALIX was further confirmed by enzyme-linked immunosorbent assay in a larger cohort of patients. Furthermore, receiver operating characteristic curve analysis was applied to evaluate the potential of ALIX as a novel diagnostic biomarker.Results: The proteomic profile revealed a total of 623 proteins expressed among the six groups, and 16 proteins with differential degrees of abundance were found in PC vs. other pancreatic diseases (including P-NET, PCLs, and CP). Based on the results of proteomic and bioinformatic analyses, exosomal ALIX was subsequently selected as a novel biomarker for PC detection and validated in another clinical cohort. We noticed that ALIX expression was elevated in PC patients compared with patients with other pancreatic diseases or HC, and it was also closely associated with TNM stage and distant metastasis. Interestingly, the combination of exosomal ALIX and serum CA199 has greater values in differentiating both early vs. late PC (AUC value 0.872) and PC vs. other pancreatic diseases (AUC value 0.910) than either ALIX or CA199 alone.Conclusion: In summary, our study demonstrated that based on proteomic profiling, proteins isolated from the plasma-derived exosomes may function as ideal non-invasive biomarkers for the clinical diagnosis of PC. Importantly, exosomal ALIX combined with CA199 has great potentials in detection of PC, especially in distinguishing PC patients at early stages from advanced stages.

BRD4 is a member of the BET protein family involved in chromatin remodeling and transcriptional regulation. Several BET inhibitors (BETi) have entered clinical trials, demonstrating potential in inducing cancer cell apoptosis and tumor regression. However, resistance to BETi is common in solid tumors. In pancreatic cancer, it is found that cancer‐associated fibroblasts (CAFs) in the tumor microenvironment reduce the BET inhibitor JQ1 sensitivity by inducing BRD4 expression. Moreover, CAFs play a crucial role in the formation of a dense stromal barrier. Therefore, targeting CAFs in the tumor microenvironment of pancreatic cancer not only enhances cancer cells sensitivity to JQ1 but also increases drug perfusion and improves oxygen supply, thus reducing glycolysis and limiting energy supply. To address this challenge, a homologous targeting mechanism utilizing activated fibroblast membrane‐coated liposomes is proposed for specific drug precise target to CAFs‐rich pancreatic cancer. Additionally, TAT peptides enable liposomes penetration, delivering PFD for targeted anti‐fibrotic therapy, reducing extracellular matrix generation and glycolysis, and enhancing JQ1 delivery and sensitivity. In conclusion, the findings indicate the tremendous potential of this CAFs‐targeting liposomal delivery system in pancreatic cancer.