Targeting ESE3/EHF With Nifurtimox Inhibits CXCR2+ Neutrophil Infiltration and Overcomes Pancreatic Cancer Resistance to Chemotherapy and Immunotherapy.

BACKGROUND & AIMS: Because pancreatic cancer responds poorly to chemotherapy and immunotherapy, it is necessary to identify novel targets and compounds to overcome resistance to treatment. METHODS: This study analyzed genomic single nucleotide polymorphism sequencing, single-cell RNA sequencing, and spatial transcriptomics. Ehf-knockout mice, KPC (LSL-KrasG12D/+, LSL-Trp53R172H/+ and Pdx1-Cre) mice, CD45.1+ BALB/C nude mice, and CD34+ humanized mice were also used as subjects. Multiplexed immunohistochemistry and flow cytometry were performed to investigate the proportion of tumor-infiltrated C-X-C motif chemokine receptor 2 (CXCR2)+ neutrophils. In addition, multiplexed cytokines assays and chromatin immunoprecipitation assays were used to examine the mechanism. RESULTS: The TP53 mutation-mediated loss of tumoral EHF increased the recruitment of CXCR2+ neutrophils, modulated their spatial distribution, and further induced chemo- and immunotherapy resistance in clinical cohorts and preclinical syngeneic mice models. Mechanistically, EHF deficiency induced C-X-C motif chemokine ligand 1 (CXCL1) transcription to enhance in vitro and in vivo CXCR2+ neutrophils migration. Moreover, CXCL1 or CXCR2 blockade completely abolished the effect, indicating that EHF regulated CXCR2+ neutrophils migration in a CXCL1-CXCR2-dependent manner. The depletion of CXCR2+ neutrophils also blocked the in vivo effects of EHF deficiency on chemotherapy and immunotherapy resistance. The single-cell RNA-sequencing results of PDAC treated with Nifurtimox highlighted the therapeutic significance of Nifurtimox by elevating the expression of tumoral EHF and decreasing the weightage of CXCL1-CXCR2 pathway within the microenvironment. Importantly, by simultaneously inhibiting the JAK1/STAT1 pathway, it could significantly suppress the recruitment and function of CXCR2+ neutrophils, further sensitizing PDAC to chemotherapy and immunotherapies. CONCLUSIONS: The study demonstrated the role of EHF in the recruitment of CXCR2+ neutrophils and the promising role of Nifurtimox in sensitizing pancreatic cancer to chemotherapy and immunotherapy.

Triple-negative breast cancer survival prediction using artificial intelligence through integrated analysis of tertiary lymphoid structures and tumor budding.

BACKGROUND: Triple-negative breast cancer (TNBC) is a highly heterogeneous and clinically aggressive disease. Accumulating evidence indicates that tertiary lymphoid structures (TLSs) and tumor budding (TB) are significantly correlated with the outcomes of patients who have TNBC, but no integrated TLS-TB profile has been established to predict their survival. The objective of this study was to investigate the relationship between the TLS/TB ratio and clinical outcomes of patients with TNBC using artificial intelligence (AI)-based analysis. METHODS: The infiltration levels of TLSs and TB were evaluated using hematoxylin and eosin staining, immunohistochemistry staining, and AI-based analysis. Various cellular subtypes within TLS were determined by multiplex immunofluorescence. Subsequently, the authors established a nomogram model, conducted calibration curve analyses, and performed decision curve analyses using R software. RESULTS: In both the training and validation cohorts, the antitumor/protumor model established by the authors demonstrated a positive correlation between the TLS/TB index and the overall survival (OS) and relapse-free survival (RFS) of patients with TNBC. Notably, patients who had a high percentage of CD8-positive T cells, CD45RO-positive T cells, or CD20-positive B cells within the TLSs experienced improved OS and RFS. Furthermore, the authors developed a comprehensive TLS-TB profile nomogram based on the TLS/TB index. This novel model outperformed the classical tumor-lymph node-metastasis staging system in predicting the OS and RFS of patients with TNBC. CONCLUSIONS: A novel strategy for predicting the prognosis of patients with TNBC was established through integrated AI-based analysis and a machine-learning workflow. The TLS/TB index was identified as an independent prognostic factor for TNBC. This nomogram-based TLS-TB profile would help improve the accuracy of predicting the prognosis of patients who have TNBC.

Irbesartan overcomes gemcitabine resistance in pancreatic cancer by suppressing stemness and iron metabolism via inhibition of the Hippo/YAP1/c-Jun axis.

BACKGROUND: Chemoresistance is the main reason for the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Thus, there is an urgent need to screen out new targets and compounds to reverse chemotherapeutic resistance. METHODS: We established a bio-bank of human PDAC organoid models, covering a representative range of PDAC tumor subtypes. We screened a library of 1304 FDA-approved compounds to identify candidates efficiently overcoming chemotherapy resistance. The effects of the compounds were evaluated with a CellTiter-Glo-3D assay, organoid apoptosis assay and in vivo patient-derived xenograft (PDX), patient-derived organoid (PDO) and LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre (KPC) genetically engineered mouse models. RNA-sequencing, genome editing, sphere formation assays, iron assays and luciferase assays were conducted to elucidate the mechanism. RESULTS: High-throughput drug screening of chemotherapy-resistant PDOs identified irbesartan, an angiotensin ‖ type 1 (AT1) receptor antagonist, which could synergistically enhance the ability of chemotherapy to kill PDAC cells. In vitro and in vivo validation using PDO, PDX and KPC mouse models showed that irbesartan efficiently sensitized PDAC tumors to chemotherapy. Mechanistically, we found that irbesartan decreased c-Jun expression by inhibiting the Hippo/YAP1 pathway and further overcame chemotherapy resistance in PDAC. We also explored c-Jun, a potential target of irbesartan, which can transcriptionally upregulate the expression of key genes involved in stemness maintenance (SOX9/SOX2/OCT4) and iron metabolism (FTH1/FTL/TFRC). More importantly, we observed that PDAC patients with high levels of c-Jun expression demonstrated poor responses to the current standard chemotherapy regimen (gemcitabine plus nab-paclitaxel). Moreover, patients with PDAC had significant survival benefits from treatment with irbesartan plus a standard chemotherapy regimen in two-center retrospective clinical cohorts and patients with high c-Jun expression exhibited a better response to combination chemotherapy. CONCLUSIONS: Irbesartan could be used in combination with chemotherapy to improve the therapeutic efficacy in PDAC patients with high levels of c-Jun expression. Irbesartan effectively inhibited chemotherapy resistance by suppressing the Hippo/YAP1/c-Jun/stemness/iron metabolism axis. Based on our findings, we are designing an investigator-initiated phase II clinical trial on the efficacy and safety of irbesartan plus a standard gemcitabine/nab-paclitaxel regimen in the treatment of patients with advanced III/IV staged PDAC and are hopeful that we will observe patient benefits.

Artificial intelligence-based comprehensive analysis of immune-stemness-tumor budding profile to predict survival of patients with pancreatic adenocarcinoma.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy. CD8+ T cells, cancer stem cells (CSCs), and tumor budding (TB) have been significantly correlated with the outcome of patients with PDAC, but the correlations have been independently reported. In addition, no integrated immune-CSC-TB profile for predicting survival in patients with PDAC has been established. METHODS: Multiplexed immunofluorescence and artificial intelligence (AI)-based comprehensive analyses were used for quantification and spatial distribution analysis of CD8+ T cells, CD133+ CSCs, and TB. In vivo humanized patient-derived xenograft (PDX) models were established. Nomogram analysis, calibration curve, time-dependent receiver operating characteristic curve, and decision curve analyses were performed using R software. RESULTS: The established 'anti-/pro-tumor' models showed that the CD8+ T cell/TB, CD8+ T cell/CD133+ CSC, TB-adjacent CD8+ T cell, and CD133+ CSC-adjacent CD8+ T cell indices were positively associated with survival of patients with PDAC. These findings were validated using PDX-transplanted humanized mouse models. An integrated nomogram-based immune-CSC-TB profile that included the CD8+ T cell/TB and CD8+ T cell/CD133+ CSC indices was established and shown to be superior to the tumor-node-metastasis stage model in predicting survival of patients with PDAC. CONCLUSIONS: 'Anti-/pro-tumor' models and the spatial relationship among CD8+ T cells, CSCs, and TB within the tumor microenvironment were investigated. Novel strategies to predict the prognosis of patients with PDAC were established using AI-based comprehensive analysis and machine learning workflow. The nomogram-based immune-CSC-TB profile can provide accurate prognosis prediction for patients with PDAC.

SDCBP promotes pancreatic cancer progression by preventing YAP1 from ß-TrCP-mediated proteasomal degradation.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal tumour with limited treatment options. Here, we identified syndecan binding protein (SDCBP), also known as syntenin1, as a novel targetable factor in promoting PDAC tumour progression. We also explored a therapeutic strategy for suppressing SDCBP expression. DESIGN: We used samples from patients with PDAC, human organoid models, LSL-KrasG12D/+mice, LSL-Trp53R172H/+ and Pdx1-Cre (KPC) mouse models, and PDX mouse models. Immunostaining, colony formation assay, ethynyl-2-deoxyuridine incorporation assay, real-time cell analysis, cell apoptosis assay, automated cell tracking, invadopodia detection and gelatin degradation assays, coimmunoprecipitation, and pull-down assays were performed in this study. RESULTS: The median overall survival and recurrence-free survival rates in the high-SDCBP group were significantly shorter than those in the low-SDCBP group. In vitro and in vivo studies have demonstrated that SDCBP promotes PDAC proliferation and metastasis. Mechanically, SDCBP inhibits CK1δ/ε-mediated YAP-S384/S387 phosphorylation, which further suppresses ß-TrCP-mediated YAP1 ubiquitination and proteasome degradation by directly interacting with YAP1. SDCBP interacts with the TAD domain of YAP1, mainly through its PDZ1 domain. Preclinical KPC mouse cohorts demonstrated that zinc pyrithione (ZnPT) suppresses PDAC tumour progression by suppressing SDCBP. CONCLUSIONS: SDCBP promotes the proliferation and metastasis of PDAC by preventing YAP1 from ß-TrCP-mediated proteasomal degradation. Therefore, ZnPT could be a promising therapeutic strategy to inhibit PDAC progression by suppressing SDCBP.