An anoikis-related lncRNA signature is a useful tool for predicting the prognosis of patients with lung adenocarcinoma

被引:1
|
作者
Jiang, Xin [1 ,2 ]
Gao, Yu-lu [4 ]
Li, Jia-yan [1 ,2 ]
Tong, Ying-ying [1 ]
Meng, Zhao-yang [3 ]
Yang, Shi-gui [5 ]
Zhu, Chang -tai [2 ]
机构
[1] Shanghai Ocean Univ, Coll Fisheries & Life Sci, Shanghai 201306, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Transfus Med, Shanghai Peoples Hosp 6, Sch Med, Shanghai 200233, Peoples R China
[3] Shanghai Jiao Tong Univ, Dept Pharm, Shanghai Peoples Hosp 6, Sch Med, Shanghai 200233, Peoples R China
[4] Nanjing Univ Chinese Med, Dept Lab Med, Kunshan Affiliated Hosp, Dept Neurosurg, Kunshan 215300, Peoples R China
[5] Zhejiang Univ, Sch Med, Dept Publ Hlth, Hangzhou 310000, Peoples R China
关键词
Lung adenocarcinoma; LncRNA; Anoikis; Prognostic signature; CANCER; RESISTANCE; MIGRATION;
D O I
10.1016/j.heliyon.2023.e22200
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Anoikis-related long non-coding RNAs (ARLs) play a critical role in tumor metastasis and progression, suggesting that they may serve as risk markers for cancer. This study aimed to investigate the prognostic value of ARLs in patients with lung adenocarcinoma (LUAD).Methods: Clinical data, RNA sequencing (RNA-seq) data, and mutation data from the LUAD project were obtained from The Cancer Genome Atlas (TCGA) database. The Molecular Signatures Database (MSigDB) and the GeneCard database were used to collect an anoikis-related gene (ARG) set. Pearson correlation analysis was performed to identify ARLs. LASSO and Cox regression were then used to establish a prognostic risk signature for ARLs. The median risk score served as the basis for categorizing patients into high and low-risk groups. Kaplan-Meier analysis was utilized to compare the prognosis between these two groups. The study also examined the associations between risk scores and prognosis, clinicopathological characteristics, immune status, tumor mutation burden (TMB), and chemotherapeutic agents. LncRNA expression was assessed using quantitative real-time PCR (qRT-PCR).Results: A total of 480 RNA expression profiles, 501 ARGs, and 2698 ARLs were obtained from the database. A prognostic ARL signature for LUAD was established, consisting of 9 lncRNAs. Patients in the low-risk group exhibited significantly better prognosis compared to those in the high-risk group (P < 0.001). The 9 lncRNAs from the ARL signature were identified as independent prognostic factors (P < 0.001). The signature demonstrated high accuracy in predicting LUAD prognosis, with area under the curve values exceeding 0.7. The risk scores for ARLs showed strong negative correlations with stroma score (P = 5.9E-07, R = -0.23), immune score (P = 9.7E-09, R = -0.26), and microenvironment score (P = 8E-11, R = -0.29). Additionally, the low-risk group exhibited significantly higher TMB compared to the high-risk group (P = 4.6E-05). High-risk status was significantly associated with lower half-maximal inhibitory concentrations for most chemotherapeutic drugs.Conclusion: This newly constructed signature based on nine ARLs is a useful instrument for the risk stratification of LUAD patients. The signature has potential clinical significance for predicting the prognosis of LUAD patients and guiding personalized immunotherapy.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] The study of an anoikis-related signature to predict glioma prognosis and immune infiltration
    Zhang, Dongdong
    Wang, Yu
    Zhou, Huandi
    Han, Xuetao
    Hou, Liubing
    Lv, Zhongqiang
    Xue, Xiaoying
    JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2023, 149 (14) : 12659 - 12676
  • [22] The study of an anoikis-related signature to predict glioma prognosis and immune infiltration
    Dongdong Zhang
    Yu Wang
    Huandi Zhou
    Xuetao Han
    Liubing Hou
    Zhongqiang Lv
    Xiaoying Xue
    Journal of Cancer Research and Clinical Oncology, 2023, 149 : 12659 - 12676
  • [23] Identification and validation of a novel anoikis-related signature for predicting prognosis and immune landscape in ovarian serous cystadenocarcinoma
    Zhu, Yu -Ting
    Wu, Shuang-Yue
    Yang, Song
    Ying, Jie
    Tian, Lu
    Xu, Hong-Liang
    Zhang, He-Ping
    Yao, Hui
    Zhang, Wei-Yu
    Jin, Qin-Qin
    Yang, Yin-Ting
    Jiang, Xi-Ya
    Zhang, Nan
    Yao, Shun
    Zhou, Shu-Guang
    Chen, Guo
    HELIYON, 2023, 9 (08)
  • [24] Identification and experimental verification of an anoikis and immune related signature in prognosis for lung adenocarcinoma
    Zhang, Jia-Le
    Dong, Yan-Xin
    Di, Shou-Yin
    Fan, Bo-Shi
    Gong, Tai-Qian
    TRANSLATIONAL CANCER RESEARCH, 2023, 12 (04) : 887 - 903
  • [25] A Novel m6A-Related LncRNA Signature for Predicting Prognosis, Chemotherapy and Immunotherapy Response in Patients with Lung Adenocarcinoma
    Shen, Yefeng
    Wang, Shaochun
    Wu, Yuanzhou
    CELLS, 2022, 11 (15)
  • [26] A novel anoikis-related gene signature predicts prognosis in patients with sepsis and reveals immune infiltration
    Wang, Yonghua
    Chi, Yanqi
    Zhu, Cheng
    Zhang, Yuxuan
    Li, Ke
    Chen, Jiajia
    Jiang, Xiying
    Chen, Kejie
    Li, Shuping
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [27] A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma
    Zhang, Xiaoyan
    Wen, Zhenxing
    Wang, Qi
    Ren, Lijuan
    Zhao, Shengli
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [28] Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer
    Jiani Yang
    Yue Zhang
    Shanshan Cheng
    Yanna Xu
    Meixuan Wu
    Sijia Gu
    Shilin Xu
    Yongsong Wu
    Chao Wang
    Yu Wang
    Cancer Cell International, 24
  • [29] Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model
    Wang, Mingwei-
    Ying, Qiaohui-
    Ding, Ru
    Xing, Yuncan-
    Wang, Jue
    Pan, Yiming-
    Pan, Bo
    Xiang, Guifen-
    Liu, Zhong
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [30] A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma
    Zipei Song
    Xincen Cao
    Xiaokun Wang
    Yuting Li
    Weiran Zhang
    Yuheng Wang
    Liang Chen
    Scientific Reports, 14