Abstract 2485
Background
Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality. This study focused on identification of RNA-Seqexpressionsignature for prognosis prediction of Uterine Sarcoma.
Methods
We obtained RNA-Seqexpression profiles from The Cancer Genome Atlas (TCGA) database and differential expressed genes (DEGs) were identified between US tissues and normal tissues. Univariate Cox proportional hazards regression analysis was performed to identify Prognosis associated DEGscorrelated with survival of US patients.The RNA-Seqbased prognostic signature was identified by least absolute shrinkage and selection operator (LASSO) Cox model. The cohort was randomly divided into training and testing groups. Thebiological pathway and processof putative RNA targets was also analyzed by bioinformatics.
Results
This study identified a RNA-Seq signature based on 11 genes, AP000320.1, HNRNPA1P33, RPL21P10, AC067773.1, AC011933.3, STX19, AC091133.4, HIST1H3A, AC004988.1, AL356585.1 and HNRNPA3P1. In the training group, the median OS in the high-risk and low-risk groups were 13.7 vs 88.1 months (HR, 0.204, 95% CI, 0.08589 - 0.4846; P < 0.0001), respectively. In the testing group, the median OS in the high-risk and low-risk groups were 11.9 vs 67.2 months (HR, 0.04315, 95% CI, 0.004845 - 0.3842; P < 0.0001) respectively. Genes in the model were put into gene ontology biological process enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathways analysis, which suggested that these genes might contribute to cancer-associated processes such as the nuclear nucleosome and DNA packaging complex.
Conclusions
This 11-genebased prognostic signature may improve prognosis prediction of US.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Linguistic correction
Resources from the same session
3425 - Feasibility and impact of prospective DPYD screening in the Irish population
Presenter: Mohammed Zameer
Session: Poster Display session 2
Resources:
Abstract
1972 - Diet-derived metabolites and the risk of colorectal cancer: a nested case-control study in a population-based cohort, the Singapore Chinese Health Study
Presenter: Dawn Chong
Session: Poster Display session 2
Resources:
Abstract
4103 - Loss of subcutaneous adipose tissue during chemotherapy predicts reduced survival in patients with incurable colorectal cancer undergoing palliative therapy
Presenter: Erin Stella Sullivan
Session: Poster Display session 2
Resources:
Abstract
4309 - Obese and overweight is associated with better prognosis in metastatic colorectal cancer patients treated with bevacizumab.
Presenter: Bozena Cybulska-Stopa
Session: Poster Display session 2
Resources:
Abstract
3554 - Patient characteristics associated with poor performance status, ECOG 2-3, and effect on survival in 1086 Finnish metastatic colorectal cancers (mCRC) nationwide (prospective RAXO study)
Presenter: Pia Österlund
Session: Poster Display session 2
Resources:
Abstract
4572 - Discovery and Diagnosis of Metastatic Colorectal Cancer (mCRC) in the Real World: Final Results from a European Survey
Presenter: Iga Rawicka
Session: Poster Display session 2
Resources:
Abstract
4783 - Adherence to recommended intake of calcium and colorectal cancer risk in the HEXA study
Presenter: Jeeyoo Lee
Session: Poster Display session 2
Resources:
Abstract
5106 - Body size, sex and sidedness of incident colorectal cancer in a prospective Swedish cohort study
Presenter: Christina Siesing
Session: Poster Display session 2
Resources:
Abstract
3364 - Middle East & North Africa Registry to characterize RAS mutation status and tumor specifications in recently diagnosed patients with metastatic colorectal cancer (MORE-RAS Study)
Presenter: Mohamed Oukkal
Session: Poster Display session 2
Resources:
Abstract
3668 - Patient Demographics and Management Landscape of Metastatic Colorectal Cancer in the Third Line Setting: real-world data in an Australian Population
Presenter: Sandy Tun Min
Session: Poster Display session 2
Resources:
Abstract