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Identification of adipocyte infiltration-related gene subtypes for predicting colorectal cancer prognosis and responses of immunotherapy/chemotherapy.
Fu, Daan; Zhang, Tianhao; Liu, Jia; Chang, Bingcheng; Zhang, Qingqing; Tan, Yuyan; Chen, Xiangdong; Tan, Lulu.
Afiliación
  • Fu D; Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Zhang T; Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education, China.
  • Liu J; Institute of Anesthesia and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Chang B; Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Zhang Q; Research Center for Tissue Engineering and Regenerative Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Tan Y; The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, 550003, China.
  • Chen X; Haiyan County Hospital of Traditional Chinese Medicine, JiaXing, 314399, China.
  • Tan L; Department of Breast and Thyroid Surgery, The First College of Clinical Medical Science, China Three Gorges University, Yichang, 443000, China.
Heliyon ; 10(13): e33616, 2024 Jul 15.
Article en En | MEDLINE | ID: mdl-39050460
ABSTRACT
Colorectal cancer (CRC) is a prevalent and aggressive malignancy characterized by a complex tumor microenvironment (TME). Given the variations in the level of adipocyte infiltration in TME, the prognosis may differ among CRC patients. Thus, there is an urgent need to establish a reliable method for identifying adipocyte subtypes in CRC in order to elucidate the impact of adipocyte infiltration on CRC treatment and prognosis. Herein, 144 adipocyte-infiltration-related genes (AIRGs) were identified as predictive markers for the immune-associated features and prognosis of CRC patients. Based on the 144 genes, the unsupervised clustering algorithm identified two distinct clusters of CRC patients with variations in molecular and signaling pathways, clinicopathological characteristics and responses to CRC chemotherapy and immunotherapy. Furthermore, an AIRG prognostic signature was constructed and validated in independent datasets. Overall, this study developed a prognostic signature based on AIRGs in CRC, which may contribute to the development of personalized treatment strategies and enhance prognostic prediction for CRC patients.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article