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JAK2 Loss Arising From Tumor-Spread-Through-Air-Spaces (STAS) Promotes Tumor Progression by Suppressing CD8+ T Cells in Lung Adenocarcinoma: A Machine Learning Approach.
Choi, Soohwan; Kim, Hyung Suk; Min, Kyueng-Whan; Noh, Yung-Kyun; Lee, Jeong-Yeon; Moon, Ji-Yong; Jung, Un Suk; Kwon, Mi Jung; Kim, Dong-Hoon; Son, Byoung Kwan; Pyo, Jung Soo; Ro, Sun Kyun.
Affiliation
  • Choi S; Department of Thoracic and Cardiovascular Surgery, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea.
  • Kim HS; Division of Breast Surgery, Department of Surgery, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea.
  • Min KW; Department of Pathology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, Korea. kyueng@hanyang.ac.kr.
  • Noh YK; Department of Computer Science, Hanyang University, Seoul, Korea.
  • Lee JY; School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea. nohyung@hanyang.ac.kr.
  • Moon JY; Department of Pathology, College of Medicine, Hanyang University, Seoul, Korea.
  • Jung US; Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea.
  • Kwon MJ; Department of Obstetrics and Gynecology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Korea.
  • Kim DH; Department of Pathology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Korea.
  • Son BK; Department of Pathology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Pyo JS; Department of Internal Medicine, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, Korea.
  • Ro SK; Department of Pathology, Uijeongbu Eulji Medical Center, Eulji University School of Medicine, Uijeongbu, Korea.
J Korean Med Sci ; 39(2): e16, 2024 Jan 15.
Article de En | MEDLINE | ID: mdl-38225784
ABSTRACT

BACKGROUND:

Tumor spread through air spaces (STAS) is a recently discovered risk factor for lung adenocarcinoma (LUAD). The aim of this study was to investigate specific genetic alterations and anticancer immune responses related to STAS. By using a machine learning algorithm and drug screening in lung cancer cell lines, we analyzed the effect of Janus kinase 2 (JAK2) on the survival of patients with LUAD and possible drug candidates.

METHODS:

This study included 566 patients with LUAD corresponding to clinicopathological and genetic data. For analyses of LUAD, we applied gene set enrichment analysis (GSEA), in silico cytometry, pathway network analysis, in vitro drug screening, and gradient boosting machine (GBM) analysis.

RESULTS:

The patients with STAS had a shorter survival time than those without STAS (P < 0.001). We detected gene set-related downregulation of JAK2 associated with STAS using GSEA. Low JAK2 expression was related to poor prognosis and a low CD8+ T-cell fraction. In GBM, JAK2 showed improved survival prediction performance when it was added to other parameters (T stage, N stage, lymphovascular invasion, pleural invasion, tumor size). In drug screening, mirin, CCT007093, dihydroretenone, and ABT737 suppressed the growth of lung cancer cell lines with low JAK2 expression.

CONCLUSION:

In LUAD, low JAK2 expression linked to the presence of STAS might serve as an unfavorable prognostic factor. A relationship between JAK2 and CD8+ T cells suggests that STAS is indirectly related to the anticancer immune response. These results may contribute to the design of future experimental research and drug development programs for LUAD with STAS.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Adénocarcinome pulmonaire / Tumeurs du poumon Type d'étude: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: J Korean Med Sci Sujet du journal: MEDICINA Année: 2024 Type de document: Article Pays de publication:

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Adénocarcinome pulmonaire / Tumeurs du poumon Type d'étude: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: En Journal: J Korean Med Sci Sujet du journal: MEDICINA Année: 2024 Type de document: Article Pays de publication: