PMID- 37575253
OWN - NLM
STAT- MEDLINE
DCOM- 20230816
LR  - 20230817
IS  - 1664-3224 (Electronic)
IS  - 1664-3224 (Linking)
VI  - 14
DP  - 2023
TI  - A novel stratification framework based on anoikis-related genes for predicting 
      the prognosis in patients with osteosarcoma.
PG  - 1199869
LID - 10.3389/fimmu.2023.1199869 [doi]
LID - 1199869
AB  - BACKGROUND: Anoikis resistance is a prerequisite for the successful development 
      of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes 
      (ARGs) correlates with OS prognosis remains unclear. This study aimed to 
      investigate the feasibility of using ARGs as prognostic tools for the risk 
      stratification of OS. METHODS: The Cancer Genome Atlas (TCGA) and Gene Expression 
      Omnibus (GEO) databases provided transcriptome information relevant to OS. The 
      GeneCards database was used to identify ARGs. Differentially expressed ARGs 
      (DEARGs) were identified by overlapping ARGs with common differentially expressed 
      genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and 
      GSE99671 datasets. Anoikis-related clusters of patients were obtained by 
      consistent clustering, and gene set variation analysis (GSVA) of the different 
      clusters was completed. Next, a risk model was created using Cox regression 
      analyses. Risk scores and clinical features were assessed for independent 
      prognostic values, and a nomogram model was constructed. Subsequently, a 
      functional enrichment analysis of the high- and low-risk groups was performed. In 
      addition, the immunological characteristics of OS samples were compared between 
      the high- and low-risk groups, and their sensitivity to therapeutic agents was 
      explored. RESULTS: Seven DEARGs between OS and normal samples were obtained by 
      intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly 
      differentially expressed between both clusters (P<0.05) and were identified as 
      prognosis-related genes. The risk model showed that the risk score and tumor 
      metastasis were independent prognostic factors of patients with OS. A nomogram 
      combining risk score and tumor metastasis effectively predicted the prognosis. In 
      addition, patients in the high-risk group had low immune scores and high tumor 
      purity. The levels of immune cell infiltration, expression of human leukocyte 
      antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower 
      in the high-risk group than those in the low-risk group. The low-risk group was 
      sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group 
      exhibited lower inhibitory concentration values by 50% for 24 drugs, including 
      AG.014699, AMG.706, and AZD6482. CONCLUSION: The prognostic stratification 
      framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead 
      to more efficient clinical management.
CI  - Copyright (c) 2023 Zhang, Wen, Wang, Ren and Zhao.
FAU - Zhang, Xiaoyan
AU  - Zhang X
AD  - Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-Sen 
      University, Guangzhou, China.
AD  - Department of Nutrition, College of Public Health of Sun Yat-Sen University, 
      Guangzhou, China.
FAU - Wen, Zhenxing
AU  - Wen Z
AD  - Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-Sen 
      University, Guangzhou, China.
AD  - Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, Guangzhou, 
      China.
FAU - Wang, Qi
AU  - Wang Q
AD  - Department of Oncology, Nanyang Central Hospital, Nanyang, China.
FAU - Ren, Lijuan
AU  - Ren L
AD  - Molecular Diagnosis and Gene Testing Center, The First Affiliated Hospital of Sun 
      Yat-Sen University, Guangzhou, China.
FAU - Zhao, Shengli
AU  - Zhao S
AD  - Department of Spine Surgery, The First Affiliated Hospital of Sun Yat-Sen 
      University, Guangzhou, China.
AD  - Guangdong Provincial Key Laboratory of Orthopaedics and Traumatology, Guangzhou, 
      China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20230727
PL  - Switzerland
TA  - Front Immunol
JT  - Frontiers in immunology
JID - 101560960
SB  - IM
MH  - Humans
MH  - Anoikis/genetics
MH  - *Osteosarcoma/genetics
MH  - Prognosis
MH  - Nomograms
MH  - *Bone Neoplasms/genetics
PMC - PMC10413143
OTO - NOTNLM
OT  - anoikis
OT  - immune microenvironment
OT  - immunotherapy
OT  - osteosarcoma
OT  - prognosis
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2023/08/14 06:41
MHDA- 2023/08/16 06:43
PMCR- 2023/01/01
CRDT- 2023/08/14 04:26
PHST- 2023/04/04 00:00 [received]
PHST- 2023/07/13 00:00 [accepted]
PHST- 2023/08/16 06:43 [medline]
PHST- 2023/08/14 06:41 [pubmed]
PHST- 2023/08/14 04:26 [entrez]
PHST- 2023/01/01 00:00 [pmc-release]
AID - 10.3389/fimmu.2023.1199869 [doi]
PST - epublish
SO  - Front Immunol. 2023 Jul 27;14:1199869. doi: 10.3389/fimmu.2023.1199869. 
      eCollection 2023.