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Haolong Qi
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P2.02 - Biology/Pathology (ID 616)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P2.02-050 - Weighted Genes Co-expression Network Analysis of Lung Cancers Concerning Patients Overall Survival and Cancer Stage (ID 7538)
09:30 - 09:30 | Presenting Author(s): Haolong Qi
- Abstract
Background:
Among the factors influence the prognosis of patients, cancer metastasis or cancer stage when first diagnosed at hospital is the most important. This article aims at finding the significant gene networks related with lung cancer patients’ overall survival and cancer stage by analyzing big data of gene expression with the algorithm of weighted gene coexpression network analysis (WGCNA).
Method:
A dataset containing 188 lung cancer patients synthesized from TCGA were applied for WGCNA to find the most significantly related modules with overall survival and cancer stage. Then GO and KEGG analysis were performed for further analysis.
Result:
Figure 1 Figure 2 A co-expression network concerning overall survival or cancer stage was constructed respectively. And the significant core genes were determined. The related pathways were also identified.
Conclusion:
Not only have we testified the present classical points concerning cancer progression and patients survival, but also some new discoveries have been identified.The genes of TBL1XR1, ATP11B, DCUN1D1 and ABCC5 played significant roles in deteriorating lung cancer patients overall survival. WNT pathway was significantly related with the patients overall survival. The genes of DUUN1D1, MRPL47, NDUFB5, DNAJC19, PIK3CA, ACTL6Aand ZNF639 promote lung cancer progressing, and lung cancer stage progress was also related with signaling pathways regulating pluripotency of stem cell.
