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Sas jmp cox proportional
Sas jmp cox proportional











Received: JanuAccepted: ApPublished: June 24, 2021Ĭopyright: © 2021 Takashima et al. PLoS ONE 16(6):Įditor: Hiroyoshi Ariga, Hokkaido Daigaku, JAPAN (2021) Survival prediction based on the gene expression associated with cancer morphology and microenvironment in primary central nervous system lymphoma. These results would not only facilitate the understanding of biology of PCNSL but also consider targeting pathways for anti-cancer treatment in personalized precision medicine in PCNSL.Ĭitation: Takashima Y, Kawaguchi A, Fukai J, Iwadate Y, Kajiwara K, Hondoh H, et al. Besides, these genes could also diagnose PCNSL cell types with MTX resistances in vitro. Finally, the comprehensive balance of morphology and microenvironment enabled prognosis prediction by a combinatorial expression of 8 representative genes, including KRT17, CDH10, CDH18, COL8A2, ADAM22, ADAM28, MMP11, and MMP24. Furthermore, collagen genes contributed to gene network formation in glasso, suggesting that the ECM balance controls the PCNSL microenvironment. Prognosis prediction formulas with the gene expression values and the Cox regression model clearly divided survival curves of the subgroups in each status. Next-generation sequencing (NGS) on 31 PCNSL samples revealed gene signatures as follows: ACTA2, ACTR10, CAPG, CORO1C, KRT17, and PALLD in cytoskeleton, CDH5, CLSTN1, ITGA10, ITGAX, ITGB7, ITGA8, FAT4, ITGAE, CDH10, ITGAM, ITGB6, and CDH18 in adhesion, COL8A2, FBN1, LAMB3, and LAMA2 in ECM, ADAM22, ADAM28, MMP11, and MMP24 in MMP. Here, we determined gene signatures associated with the morphology and microenvironment of primary central nervous system lymphoma (PCNSL) to enable prognosis prediction. Besides, a balance between the extracellular matrix (ECM) and matrix metalloprotease (MMP) is required for cancer cell morphology and angiogenesis. Dysregulation of cell morphology and cell-cell interaction results in cancer cell growth, migration, invasion, and metastasis.













Sas jmp cox proportional