PMID- 36938730
OWN - NLM
STAT- MEDLINE
DCOM- 20230412
LR  - 20230412
IS  - 1875-8592 (Electronic)
IS  - 1574-0153 (Linking)
VI  - 36
IP  - 4
DP  - 2023
TI  - Construction and validation of a prognostic model based on ten signature cell 
      cycle-related genes for early-stage lung squamous cell carcinoma.
PG  - 313-326
LID - 10.3233/CBM-220227 [doi]
AB  - BACKGROUND: We performed a bioinformatics analysis to screen for cell 
      cycle-related differentially expressed genes (DEGs) and constructed a model for 
      the prognostic prediction of patients with early-stage lung squamous cell 
      carcinoma (LSCC). METHODS: From a gene expression omnibus (GEO) database, the 
      GSE157011 dataset was randomly divided into an internal training group and an 
      internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and 
      GSE73403 datasets were merged as the external validation group. We performed 
      single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and 
      difference analysis, and identified 372 cell cycle-related genes. Additionally, 
      we combined LASSO/Cox regression analysis to construct a prognostic model. Then, 
      patients were divided into high-risk and low-risk groups according to risk 
      scores. The internal testing group, discovery set, and external verification set 
      were used to assess model reliability. We used a nomogram to predict patient 
      prognoses based on clinical features and risk values. Clinical relevance analysis 
      and the Human Protein Atlas (HPA) database were used to verify signature gene 
      expression. RESULTS: Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, 
      HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on 
      the internal training group constructed. From this, patients in the low-risk 
      group had a higher survival rate when compared with the high-risk group. 
      Time-dependent receiver operating characteristic (tROC) and Cox regression 
      analyses showed the model was efficient and accurate. Clinical relevance analysis 
      and the HPA database showed that DEGs were significantly dysregulated in LSCC 
      tissue. CONCLUSION: Our model predicted the prognosis of early-stage LSCC 
      patients and demonstrated potential applications for clinical decision-making and 
      individualized therapy.
FAU - Zhang, Chengpeng
AU  - Zhang C
AD  - Department of Thoracic Surgery, Suzhou Ninth People's Hospital, Suzhou, Jiangsu, 
      China.
FAU - Huang, Yong
AU  - Huang Y
AD  - Department of Thoracic Surgery, Haimen People's Hospital, Nantong, Jiangsu, 
      China.
FAU - Fang, Chen
AU  - Fang C
AD  - Department of Thoracic Surgery, The First Affiliated Hospital of Soochow 
      University, Suzhou, Jiangsu, China.
FAU - Liang, Yingkuan
AU  - Liang Y
AD  - Department of Thoracic Surgery, The First Affiliated Hospital of Soochow 
      University, Suzhou, Jiangsu, China.
FAU - Jiang, Dong
AU  - Jiang D
AD  - Department of Thoracic Surgery, The First Affiliated Hospital of Soochow 
      University, Suzhou, Jiangsu, China.
FAU - Li, Jiaxi
AU  - Li J
AD  - Department of Thoracic Surgery, The First Affiliated Hospital of Soochow 
      University, Suzhou, Jiangsu, China.
FAU - Ma, Haitao
AU  - Ma H
AD  - Department of Thoracic Surgery, The First Affiliated Hospital of Soochow 
      University, Suzhou, Jiangsu, China.
FAU - Jiang, Wei
AU  - Jiang W
AD  - Department of Thoracic Surgery, Dushu Lake Hospital Affiliated to Soochow 
      University, Suzhou, Jiangsu, China.
FAU - Feng, Yu
AU  - Feng Y
AD  - Department of Thoracic Surgery, The First Affiliated Hospital of Soochow 
      University, Suzhou, Jiangsu, China.
LA  - eng
PT  - Journal Article
PL  - Netherlands
TA  - Cancer Biomark
JT  - Cancer biomarkers : section A of Disease markers
JID - 101256509
RN  - EC 2.1.1.- (SETD6 protein, human)
RN  - EC 2.1.1.- (Protein Methyltransferases)
RN  - 0 (Fstl3 protein, human)
RN  - 0 (Follistatin-Related Proteins)
SB  - IM
MH  - Humans
MH  - Prognosis
MH  - Reproducibility of Results
MH  - *Carcinoma, Non-Small-Cell Lung
MH  - *Carcinoma, Squamous Cell/genetics
MH  - Cell Cycle
MH  - *Lung Neoplasms/genetics
MH  - Lung
MH  - Protein Methyltransferases
MH  - *Follistatin-Related Proteins
OTO - NOTNLM
OT  - Lung squamous cell carcinoma
OT  - cell cycle-related differentially expressed genes
OT  - prognostic signature
OT  - survival
EDAT- 2023/03/21 06:00
MHDA- 2023/04/12 06:42
CRDT- 2023/03/20 05:03
PHST- 2023/04/12 06:42 [medline]
PHST- 2023/03/21 06:00 [pubmed]
PHST- 2023/03/20 05:03 [entrez]
AID - CBM220227 [pii]
AID - 10.3233/CBM-220227 [doi]
PST - ppublish
SO  - Cancer Biomark. 2023;36(4):313-326. doi: 10.3233/CBM-220227.