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Wei S, Gou X, Zhang Y, Cui J, Liu X, Hong N, Sheng W, Cheng J, Wang Y. Prediction of transformation in the histopathological growth pattern of colorectal liver metastases after chemotherapy using CT-based radiomics. Clin Exp Metastasis 2024; 41:143-154. [PMID: 38416301 DOI: 10.1007/s10585-024-10275-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/24/2024] [Indexed: 02/29/2024]
Abstract
Chemotherapy alters the prognostic biomarker histopathological growth pattern (HGP) phenotype in colorectal liver metastases (CRLMs) patients. We aimed to develop a CT-based radiomics model to predict the transformation of the HGP phenotype after chemotherapy. This study included 181 patients with 298 CRLMs who underwent preoperative contrast-enhanced CT followed by partial hepatectomy between January 2007 and July 2022 at two institutions. HGPs were categorized as pure desmoplastic HGP (pdHGP) or non-pdHGP. The samples were allocated to training, internal validation, and external validation cohorts comprising 153, 65, and 29 CRLMs, respectively. Radiomics analysis was performed on pre-enhanced, arterial phase, portal venous phase (PVP), and fused images. The model was used to predict prechemotherapy HGPs in 112 CRLMs, and HGP transformation was analysed by comparing these findings with postchemotherapy HGPs determined pathologically. The prevalence of pdHGP was 19.8% (23/116) and 45.8% (70/153) in chemonaïve and postchemotherapy patients, respectively (P < 0.001). The PVP radiomics signature showed good performance in distinguishing pdHGP from non-pdHGPs (AUCs of 0.906, 0.877, and 0.805 in the training, internal validation, and external validation cohorts, respectively). The prevalence of prechemotherapy pdHGP predicted by the radiomics model was 33.0% (37/112), and the prevalence of postchemotherapy pdHGP according to the pathological analysis was 47.3% (53/112; P = 0.029). The transformation of HGP was bidirectional, with 15.2% (17/112) of CRLMs transforming from prechemotherapy pdHGP to postchemotherapy non-pdHGP and 30.4% (34/112) transforming from prechemotherapy non-pdHGP to postchemotherapy pdHGP (P = 0.005). CT-based radiomics method can be used to effectively predict the HGP transformation in chemotherapy-treated CRLM patients, thereby providing a basis for treatment decisions.
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Affiliation(s)
- Shengcai Wei
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China
| | - Xinyi Gou
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China
| | - Yinli Zhang
- Department of Pathology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China
| | - Jingjing Cui
- Department of Research and Development, United Imaging Intelligence (Beijing) Co., Ltd, Yongteng North Road, Haidian District, Beijing, 100094, China
| | - Xiaoming Liu
- Department of Research and Development, Beijing United Imaging Research Institute of Intelligent Imaging, Yongteng North Road, Haidian District, Beijing, 100089, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China
| | - Weiqi Sheng
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
| | - Jin Cheng
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China.
| | - Yi Wang
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St, Beijing, 100044, China.
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Ren H, Su Z, Yang J, Cao J, Zhang Y, Sheng K, Guo K, Wang Y. High Expression Level of TRIP6 is Correlated with Poor Prognosis in Colorectal Cancer and Promotes Tumor Cell Proliferation and Migration. Biochem Genet 2024:10.1007/s10528-024-10711-x. [PMID: 38430448 DOI: 10.1007/s10528-024-10711-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 01/20/2024] [Indexed: 03/03/2024]
Abstract
Globally, colorectal cancer (CRC) is one of the leading causes of health problems. More reliable molecular biomarkers for early diagnosis in CRC patients are needed. A crucial role for thyroid hormone receptor interacting protein 6 (TRIP6) is played in tumorigenesis and tumor growth. Our study aims to determine the diagnostic and prognostic roles of TRIP6 at CRC. TRIP6 gene expression levels were analyzed in this study from public databases. The relationship between TRIP6 expression and clinicopathological characteristics was explored by logistic regression analysis. Based on Kaplan-Meier (K-M) survival curves and receiver operating characteristic curves (ROC) analysis, the prognostic and diagnostic values of TRIP6 were determined. Protein-protein interaction (PPI) networks analysis were performed using the STRING database. A Spearman's correlation analysis applied for examining the correlation between TRIP6 expression, immune cell infiltration, and immune checkpoint genes. Moreover, colony formation assay and transwell assay were used to investigate the functions of TRIP6. TRIP6 was highly expressed in CRC cancer tissues and cells. K-M survival analysis indicated that a high expression of TRIP6 was associated with poor prognosis. TRIP6 expression was obviously associated with immune cell infiltration and immune checkpoint gene expression. For validation, the results of collected clinical CRC samples show that TRIP6 levels in CRC tumor tissue were higher than those of paired adjacent colorectal tissues. Additionally, in vitro experiments suggested that TRIP6 knockdown suppressed proliferation and migration in CRC cell line RKO. TRIP6 overexpression promoted the proliferation and migration of normal colon cell line NCM460. High TRIP6 expression is associated with poor prognosis in colorectal cancer and promotes tumor cell proliferation and migration which may be a potential diagnostic and prognostic biomarker and a promising therapeutic target for CRC, providing new insights into its role in CRC.
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Affiliation(s)
- Huijuan Ren
- School of Life Sciences, Anhui University, Hefei, Anhui, China
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China
| | - Ziwei Su
- School of Life Sciences, Anhui University, Hefei, Anhui, China
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China
| | - Jian Yang
- School of Life Sciences, Anhui University, Hefei, Anhui, China
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China
| | - Jialing Cao
- School of Life Sciences, Anhui University, Hefei, Anhui, China
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China
| | - Yihan Zhang
- School of Life Sciences, Anhui University, Hefei, Anhui, China
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China
| | - Kangliang Sheng
- School of Life Sciences, Anhui University, Hefei, Anhui, China.
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China.
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China.
| | - Kun Guo
- Department of Surgery, The First Affiliated Hospital of USTC, Hefei, Anhui, China.
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
| | - Yongzhong Wang
- School of Life Sciences, Anhui University, Hefei, Anhui, China.
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China.
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China.
- Institute of Physical Science and Information Technology, Anhui University, Hefei, Anhui, China.
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Mou M, Gao R, Wu Y, Lin P, Yin H, Chen F, Huang F, Wen R, Yang H, He Y. Endoscopic Rectal Ultrasound-Based Radiomics Analysis for the Prediction of Synchronous Liver Metastasis in Patients With Primary Rectal Cancer. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024; 43:361-373. [PMID: 37950599 DOI: 10.1002/jum.16369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 09/26/2023] [Accepted: 10/22/2023] [Indexed: 11/12/2023]
Abstract
OBJECTIVES To develop and validate an ultrasound-based radiomics model to predict synchronous liver metastases (SLM) in rectal cancer (RC) patients preoperatively. METHODS Two hundred and thirty-nine RC patients were included in this study and randomly divided into training and validation cohorts. A total of 5936 radiomics features were calculated on the basis of ultrasound images to build a radiomic model and obtain a radiomics score (Rad-score) using logistic regression. Meanwhile, clinical characteristics were collected to construct a clinical model. The radiomics-clinical model was developed and validated by integrating the radiomics features with the selected clinical characteristics. The performances of three models were evaluated and compared through their discrimination, calibration, and clinical usefulness. RESULTS The radiomics model was developed based on 13 radiomic features. The radiomics-clinical model, which incorporated Rad-score, CEA, and CA199, exhibited favorable discrimination and calibration with areas under the receiver operating characteristic curve (AUC) of 0.920 (95% CI: 0.874-0.965) in the training cohorts and 0.855 (95% CI: 0.759-0.951) in the validation cohorts. And the AUC of the radiomics-clinical model was 0.849 (95% CI: 0.771-0.927) for the training cohorts and 0.780 (95% CI: 0.655-0.905) for the validation cohorts, the clinical model was 0.811 (95% CI: 0.718-0.905) for the training cohorts and 0.805 (95% CI: 0.645-0.965) for the validation cohorts. Moreover, decision curve analysis (DCA) further confirmed the clinical utility of the radiomics-clinical model. CONCLUSIONS The radiomics-clinical model performed satisfactory predictive performance, which can help improve clinical diagnosis performance and outcome prediction for SLM in RC patients.
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Affiliation(s)
- Meiyan Mou
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Department of Medical Ultrasound, Yulin No. 1 People's Hospital of Guangxi Zhuang Autonomous Region, Yulin, China
| | - Ruizhi Gao
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yuquan Wu
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Peng Lin
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Hongxia Yin
- Department of Medical Ultrasound, Yulin No. 1 People's Hospital of Guangxi Zhuang Autonomous Region, Yulin, China
| | - Fenghuan Chen
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Fen Huang
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Rong Wen
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Hong Yang
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yun He
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Carrera-Aguado I, Marcos-Zazo L, Carrancio-Salán P, Guerra-Paes E, Sánchez-Juanes F, Muñoz-Félix JM. The Inhibition of Vessel Co-Option as an Emerging Strategy for Cancer Therapy. Int J Mol Sci 2024; 25:921. [PMID: 38255995 PMCID: PMC10815934 DOI: 10.3390/ijms25020921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/09/2024] [Accepted: 01/09/2024] [Indexed: 01/24/2024] Open
Abstract
Vessel co-option (VCO) is a non-angiogenic mechanism of vascularization that has been associated to anti-angiogenic therapy. In VCO, cancer cells hijack the pre-existing blood vessels and use them to obtain oxygen and nutrients and invade adjacent tissue. Multiple primary tumors and metastases undergo VCO in highly vascularized tissues such as the lungs, liver or brain. VCO has been associated with a worse prognosis. The cellular and molecular mechanisms that undergo VCO are poorly understood. Recent studies have demonstrated that co-opted vessels show a quiescent phenotype in contrast to angiogenic tumor blood vessels. On the other hand, it is believed that during VCO, cancer cells are adhered to basement membrane from pre-existing blood vessels by using integrins, show enhanced motility and a mesenchymal phenotype. Other components of the tumor microenvironment (TME) such as extracellular matrix, immune cells or extracellular vesicles play important roles in vessel co-option maintenance. There are no strategies to inhibit VCO, and thus, to eliminate resistance to anti-angiogenic therapy. This review summarizes all the molecular mechanisms involved in vessel co-option analyzing the possible therapeutic strategies to inhibit this process.
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Affiliation(s)
- Iván Carrera-Aguado
- Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, 37007 Salamanca, Spain; (I.C.-A.); (L.M.-Z.); (P.C.-S.); (E.G.-P.); (F.S.-J.)
- Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Laura Marcos-Zazo
- Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, 37007 Salamanca, Spain; (I.C.-A.); (L.M.-Z.); (P.C.-S.); (E.G.-P.); (F.S.-J.)
- Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Patricia Carrancio-Salán
- Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, 37007 Salamanca, Spain; (I.C.-A.); (L.M.-Z.); (P.C.-S.); (E.G.-P.); (F.S.-J.)
- Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Elena Guerra-Paes
- Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, 37007 Salamanca, Spain; (I.C.-A.); (L.M.-Z.); (P.C.-S.); (E.G.-P.); (F.S.-J.)
- Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain
| | - Fernando Sánchez-Juanes
- Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, 37007 Salamanca, Spain; (I.C.-A.); (L.M.-Z.); (P.C.-S.); (E.G.-P.); (F.S.-J.)
- Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain
| | - José M. Muñoz-Félix
- Departamento de Bioquímica y Biología Molecular, Universidad de Salamanca, 37007 Salamanca, Spain; (I.C.-A.); (L.M.-Z.); (P.C.-S.); (E.G.-P.); (F.S.-J.)
- Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain
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Søreide K. Liver transplantation for non-resectable colorectal liver metastases: the thin red line. Br J Cancer 2023; 128:1794-1796. [PMID: 36959377 PMCID: PMC10147914 DOI: 10.1038/s41416-023-02234-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 02/28/2023] [Accepted: 03/10/2023] [Indexed: 03/25/2023] Open
Affiliation(s)
- Kjetil Søreide
- Department of Gastrointestinal Surgery, Stavanger University Hospital, Stavanger, Norway.
- Gastrointestinal Translational Research Unit, Stavanger University Hospital, Stavanger, Norway.
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.
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