PMID- 35127816
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220208
IS  - 2296-889X (Print)
IS  - 2296-889X (Electronic)
IS  - 2296-889X (Linking)
VI  - 8
DP  - 2021
TI  - Development of Personalized Signature Based on the Immune Landscape to Predict 
      the Prognosis of Osteosarcoma and the Response to Immunotherapy and Targeted 
      Therapy.
PG  - 783915
LID - 10.3389/fmolb.2021.783915 [doi]
LID - 783915
AB  - As a heterogeneous and aggressive disease, osteosarcoma (OS) faces great 
      challenges to prognosis and individualized treatment. Hence, we explore the role 
      of immune-related genes in predicting prognosis and responsiveness to 
      immunotherapy and targeted therapies in patients with OS based on the 
      immunological landscape of osteosarcoma. Based on the database of the 
      Therapeutical Applicable Research to Generate Effective Treatments (TARGET), 
      single-sample gene set enrichment analysis (ssGSEA) was used to obtain the 
      enrichment scores of 29 immune characteristics. A series of bioinformatics 
      methods were performed to construct the immune-related prognostic signature 
      (IRPS). Gene set enrichment analysis and gene set variation analysis were used to 
      explore the biological functions of IRPS. We also analyzed the relationship 
      between IRPS and tumor microenvironment. Lastly, the reactivity of IRPS to immune 
      checkpoint therapy and targeted drugs was explored. The ssGSEA algorithm was used 
      to define two immune subtypes, namely Immunity_High and Immunity_Low. 
      Immunity_High was associated with a good prognosis and was an independent 
      prognostic factor of OS. The IRPS containing 7 genes was constructed by the least 
      absolute shrinkage and selection operator Cox regression. The IRPS can divide 
      patients into low- and high-risk patients. Compared with high-risk patients, 
      low-risk patients had a better prognosis and were positively correlated with 
      immune cell infiltration and immune function. Low-risk patients benefited more 
      from immunotherapy, and the sensitivity of targeted drugs in high- and low-risk 
      groups was determined. IRPS can be used to predict the prognosis of OS patients, 
      and provide therapeutic responsiveness to immunotherapy and targeted therapy.
CI  - Copyright (c) 2022 Feng, Zhao, Zhao, Song, Ma and Wang.
FAU - Feng, Xiaofei
AU  - Feng X
AD  - Department of Orthopedics, The First Clinical Medical College of Lanzhou 
      University, Gansu, China.
FAU - Zhao, Zhenrui
AU  - Zhao Z
AD  - Department of Orthopedics, The First Clinical Medical College of Lanzhou 
      University, Gansu, China.
FAU - Zhao, Yuhao
AU  - Zhao Y
AD  - Department of Orthopedics, The First Clinical Medical College of Lanzhou 
      University, Gansu, China.
FAU - Song, Zhengdong
AU  - Song Z
AD  - Department of Orthopedics, The First Clinical Medical College of Lanzhou 
      University, Gansu, China.
FAU - Ma, Yao
AU  - Ma Y
AD  - Clinical Laboratory Center, Gansu Provincial Maternity and Child-Care Hospital, 
      Gansu, China.
FAU - Wang, Wenji
AU  - Wang W
AD  - Department of Orthopedics, Lanzhou University First Affiliated Hospital, Gansu, 
      China.
LA  - eng
PT  - Journal Article
DEP - 20220120
PL  - Switzerland
TA  - Front Mol Biosci
JT  - Frontiers in molecular biosciences
JID - 101653173
PMC - PMC8811188
OTO - NOTNLM
OT  - immune checkpoint
OT  - osteosarcoma
OT  - prognosis
OT  - targeted therapy
OT  - tumor microenvironment
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- 2022/02/08 06:00
MHDA- 2022/02/08 06:01
PMCR- 2021/01/01
CRDT- 2022/02/07 05:35
PHST- 2021/09/27 00:00 [received]
PHST- 2021/12/30 00:00 [accepted]
PHST- 2022/02/07 05:35 [entrez]
PHST- 2022/02/08 06:00 [pubmed]
PHST- 2022/02/08 06:01 [medline]
PHST- 2021/01/01 00:00 [pmc-release]
AID - 783915 [pii]
AID - 10.3389/fmolb.2021.783915 [doi]
PST - epublish
SO  - Front Mol Biosci. 2022 Jan 20;8:783915. doi: 10.3389/fmolb.2021.783915. 
      eCollection 2021.