Xupeng Hou

Tianjin Medical University Cancer Institute and Hospital

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Jing Liu

Third Xiangya Hospital

Xueyang Li

Tianjin Medical University Cancer Institute and Hospital

Tianxing Zhou

Shanghai Jiao Tong University

Jingrui Yan

Tianjin Medical University Cancer Institute and Hospital

Yongjie Xie

Tianjin Medical University Cancer Institute and Hospital

Weiwei Bai

Zhengzhou University

Wenna Jiang

Tianjin Medical University Cancer Institute and Hospital

Jihui Hao

Tianjin Medical University Cancer Institute and Hospital

Chongbiao Huang

Tianjin Medical University Cancer Institute and Hospital

Ziyun Liu

North China Electric Power University

Cooperative Institutions

Tianjin Medical University Cancer Institute and Hospital

National Clinical Research

Tianjin Medical University

Yahoo (United Kingdom)

Shandong University

Ministry of Education of the People's Republic of China

Nankai University

Shanghai Jiao Tong University

Chinese Academy of Sciences

Wuhan University

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

Cancer (2024)

Xupeng Hou Xueyang Li Yunwei Han Hua Xu Yongjie Xie

Abstract 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.

Triple-negative breast cancer

Nomogram

Multiplex

10.1002/cncr.35261

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Citations (7)

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

Cancer Biology and Medicine (2023)

Tianxing Zhou Quan Man Xueyang Li Yongjie Xie Xupeng Hou

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.

Nomogram

10.20892/j.issn.2095-3941.2022.0569

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Citations (8)

KLF15 suppresses stemness of pancreatic cancer by decreasing USP21-mediated Nanog stability

Cellular and Molecular Life Sciences (2024)

Wenna Jiang Lin Liu Meng Wang Xueyang Li Tianxing Zhou

Homeobox protein NANOG

10.1007/s00018-024-05442-6

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

Journal of Experimental & Clinical Cancer Research (2023)

Tianxing Zhou Yongjie Xie Xupeng Hou Weiwei Bai Xueyang Li

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.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.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.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.

Irbesartan

YAP1

Survivin

10.1186/s13046-023-02671-8

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Citations (48)

CD64⁺fibroblast-targeted vilanterol and a STING agonist augment CLDN18.2 BiTEs efficacy against pancreatic cancer by reducing desmoplasia and enriching stem-like CD8⁺T cells

Gut (2024)

Tianxing Zhou Xupeng Hou Jingrui Yan Li Lin Yongjie Xie

The objective of this study is to improve the efficacy of CLDN18.2/CD3 bispecific T-cell engagers (BiTEs) as a promising immunotherapy against pancreatic ductal adenocarcinoma (PDAC).

Sting

10.1136/gutjnl-2024-332371

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Citations (1)

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

Gut (2023)

Jing Liu Weiwei Bai Tianxing Zhou Yongjie Xie Bo Yang

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.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.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 β-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.SDCBP promotes the proliferation and metastasis of PDAC by preventing YAP1 from β-TrCP-mediated proteasomal degradation. Therefore, ZnPT could be a promising therapeutic strategy to inhibit PDAC progression by suppressing SDCBP.

YAP1

Invadopodia

Protein Degradation

10.1136/gutjnl-2022-327492

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Citations (15)

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

Gastroenterology (2024)

Yongjie Xie Tianxing Zhou Xueyang Li Kaili Zhao Weiwei Bai

CXC chemokine receptors

10.1053/j.gastro.2024.02.046

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Citations (4)