Identification of a distinctive immunogenomic gene signature in stage-matched colorectal cancer

被引:0
|
作者
Ahluwalia, Pankaj [1 ]
Mondal, Ashis K. [1 ]
Vashisht, Ashutosh [1 ]
Singh, Harmanpreet [1 ]
Alptekin, Ahmet [1 ]
Ballur, Kalyani [1 ]
Omar, Nivin [1 ]
Ahluwalia, Meenakshi [2 ]
Jones, Kimya [1 ]
Barrett, Amanda [1 ]
Kota, Vamsi [2 ,3 ]
Kolhe, Ravindra [1 ]
机构
[1] Augusta Univ, Dept Pathol, Med Coll Georgia, 1120 15th St,BF-207, Augusta, GA 30912 USA
[2] Augusta Univ, Georgia Canc Ctr, Augusta, GA 30912 USA
[3] Augusta Univ, Dept Med, Med Coll Georgia, Augusta, GA 30912 USA
关键词
Personalized medicine; Colorectal cancer; Gene signature; Prognostic genes; Colon; Immune infiltration; Precision medicine; Stratified medicine; Immunotherapy responsiveness; NF-KAPPA-B; PROGNOSTIC-SIGNIFICANCE; EXPRESSION; CELLS; MICROENVIRONMENT; HETEROGENEITY; INFLAMMATION; MECHANISMS; THERAPIES; NETWORKS;
D O I
10.1007/s00432-024-06034-4
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundColorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Despite advances in diagnosis and treatment, including surgery, chemotherapy, and immunotherapy, accurate clinical markers are still lacking. The development of prognostic and predictive indicators, particularly in the context of personalized medicine, could significantly improve CRC patient management. MethodIn this retrospective study, we used FFPE blocks of tissue samples from CRC patients at Augusta University (AU) to quantify a custom 15-gene panel. To differentiate the tumor and adjacent normal regions (NAT), H&E staining was utilized. For the quantification of transcripts, we used the NanoString nCounter platform. Kaplan-Meier and Log-rank tests were used to perform survival analyses. Several independent datasets were explored to validate the gene signature. Orthogonal analyses included single-cell profiling, differential gene expression, immune cell deconvolution, neoantigen prediction, and biological pathway assessment. ResultsA 3-gene signature (GTF3A, PKM, and VEGFA) was found to be associated with overall survival in the AU cohort (HR = 2.26, 95% CI 1.05-4.84, p = 0.02, 93 patients), TCGA cohort (HR = 1.57, 95% CI 1.05-2.35, p < 0.02, 435 patients) and four other GEO datasets. Independent single-cell analysis identified relatively higher expression of the 3-gene signature in the tumor region. Differential analysis revealed dysregulated tissue inflammation, immune dysfunction, and neoantigen load of cell cycle processes among high-risk patients compared to low-risk patients. ConclusionWe developed a 3-gene signature with the potential for prognostic and predictive clinical assessment of CRC patients. This gene-based stratification offers a cost-effective approach to personalized cancer management. Further research using similar methods could identify therapy-specific gene signatures to strengthen the development of personalized medicine for CRC patients.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Identification of a prognostic gene signature based on an immunogenomic landscape analysis of bladder cancer
    Luo, Yongwen
    Chen, Liang
    Zhou, Qiang
    Xiong, Yaoyi
    Wang, Gang
    Liu, Xuefeng
    Xiao, Yu
    Ju, Lingao
    Wang, Xinghua
    JOURNAL OF CELLULAR AND MOLECULAR MEDICINE, 2020, 24 (22) : 13370 - 13382
  • [2] Identification of a cytokine-cytokine receptor interaction gene signature for predicting clinical outcomes in patients with colorectal cancer
    Dong, Chuanpeng
    Wang, Xing
    Xu, Huilin
    Zhan, Xiaohui
    Ren, He
    Liu, Zhenhao
    Liu, Gang
    Liu, Lei
    INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, 2017, 10 (06): : 9009 - +
  • [3] Immunogenomic Gene Signature of Cell-Death Associated Genes with Prognostic Implications in Lung Cancer
    Ahluwalia, Pankaj
    Ahluwalia, Meenakshi
    Mondal, Ashis K.
    Sahajpal, Nikhil
    Kota, Vamsi
    Rojiani, Mumtaz, V
    Rojiani, Amyn M.
    Kolhe, Ravindra
    CANCERS, 2021, 13 (01) : 1 - 18
  • [4] Identification of a 6-gene signature predicting prognosis for colorectal cancer
    Zuo, Shuguang
    Dai, Gongpeng
    Ren, Xuequn
    CANCER CELL INTERNATIONAL, 2019, 19 (1)
  • [5] Identification of a gene signature and prediction of overall survival of patients with stage IV colorectal cancer using a novel machine learning approach
    Altaf, Abdullah
    Kawashima, Jun
    Khalil, Mujtaba
    Stecko, Hunter
    Rashid, Zayed
    Kalady, Matthew
    Pawlik, Timothy M.
    EJSO, 2025, 51 (05):
  • [6] Identification of glutamine metabolism-related gene signature to predict colorectal cancer prognosis
    Xie, Yang
    Li, Jun
    Tao, Qing
    Wu, Yonghui
    Liu, Zide
    Zeng, Chunyan
    Chen, Youxiang
    JOURNAL OF CANCER, 2024, 15 (10): : 3199 - 3214
  • [7] Identification of a 3-gene signature for predicting the prognosis of stage II colon cancer based on microsatellite status
    Huang, Xiangxiong
    Xu, Heyang
    Zeng, Yujie
    Lan, Qiusheng
    Liu, Lu
    Lai, Wei
    Chu, Zhonghua
    JOURNAL OF GASTROINTESTINAL ONCOLOGY, 2021, 12 (06) : 2749 - 2762
  • [8] Identification of a 6-gene signature predicting prognosis for colorectal cancer
    Shuguang Zuo
    Gongpeng Dai
    Xuequn Ren
    Cancer Cell International, 19
  • [9] Identification of a five-gene signature with prognostic value in colorectal cancer
    Sun, Guangwei
    Li, Yalun
    Peng, Yangjie
    Lu, Dapeng
    Zhang, Fuqiang
    Cui, Xueyang
    Zhang, Qingyue
    Li, Zhuang
    JOURNAL OF CELLULAR PHYSIOLOGY, 2019, 234 (04) : 3829 - 3836
  • [10] Identification of gene-specific DNA methylation signature for Colorectal Cancer
    Li, Kaixue
    Zeng, Li
    Wei, Hong
    Hu, Jingjing
    Jiao, Lu
    Zhang, Juan
    Xiong, Ying
    CANCER GENETICS, 2018, 228 : 5 - 11