BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

165 related articles for article (PubMed ID: 30135189)

  • 21. Altered oncomodules underlie chromatin regulatory factors driver mutations.
    Frigola J; Iturbide A; Lopez-Bigas N; Peiro S; Gonzalez-Perez A
    Oncotarget; 2016 May; 7(21):30748-59. PubMed ID: 27095575
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Topological network analysis of differentially expressed genes in cancer cells with acquired gefitinib resistance.
    Lee YS; Hwang SG; Kim JK; Park TH; Kim YR; Myeong HS; Kwon K; Jang CS; Noh YH; Kim SY
    Cancer Genomics Proteomics; 2015; 12(3):153-66. PubMed ID: 25977174
    [TBL] [Abstract][Full Text] [Related]  

  • 23. The mRNA related ceRNA-ceRNA landscape and significance across 20 major cancer types.
    Xu J; Li Y; Lu J; Pan T; Ding N; Wang Z; Shao T; Zhang J; Wang L; Li X
    Nucleic Acids Res; 2015 Sep; 43(17):8169-82. PubMed ID: 26304537
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Pan-phylum Comparison of Nematode Metabolic Potential.
    Tyagi R; Rosa BA; Lewis WG; Mitreva M
    PLoS Negl Trop Dis; 2015 May; 9(5):e0003788. PubMed ID: 26000881
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Multiscale network modeling reveals the gene regulatory landscape driving cancer prognosis in 32 cancer types.
    Xu P; Zhang B
    Genome Res; 2023 Oct; 33(10):1806-1817. PubMed ID: 37907329
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Transcriptome Analysis of Recurrently Deregulated Genes across Multiple Cancers Identifies New Pan-Cancer Biomarkers.
    Kaczkowski B; Tanaka Y; Kawaji H; Sandelin A; Andersson R; Itoh M; Lassmann T; Hayashizaki Y; Carninci P; Forrest AR;
    Cancer Res; 2016 Jan; 76(2):216-26. PubMed ID: 26552699
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Metabolic profiling of cancer cells reveals genome-wide crosstalk between transcriptional regulators and metabolism.
    Ortmayr K; Dubuis S; Zampieri M
    Nat Commun; 2019 Apr; 10(1):1841. PubMed ID: 31015463
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Pan-cancer analysis of somatic mutations and transcriptomes reveals common functional gene clusters shared by multiple cancer types.
    Kim H; Kim YM
    Sci Rep; 2018 Apr; 8(1):6041. PubMed ID: 29662161
    [TBL] [Abstract][Full Text] [Related]  

  • 29. TP53 mutations, expression and interaction networks in human cancers.
    Wang X; Sun Q
    Oncotarget; 2017 Jan; 8(1):624-643. PubMed ID: 27880943
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Identifying gene modules of thyroid cancer associated with pathological stage by weighted gene co-expression network analysis.
    Tang X; Huang X; Wang D; Yan R; Lu F; Cheng C; Li Y; Xu J
    Gene; 2019 Jul; 704():142-148. PubMed ID: 30965127
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells.
    Rmaileh AA; Solaimuthu B; Tanna M; Khatib A; Yosef MB; Hayashi A; Lichtenstein M; Shaul YD
    Biomolecules; 2020 Apr; 10(5):. PubMed ID: 32365991
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A favorable role of prolactin in human breast cancer reveals novel pathway-based gene signatures indicative of tumor differentiation and favorable patient outcome.
    Hachim IY; Shams A; Lebrun JJ; Ali S
    Hum Pathol; 2016 Jul; 53():142-52. PubMed ID: 26980025
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Integrating mutation and gene expression cross-sectional data to infer cancer progression.
    Fleck JL; Pavel AB; Cassandras CG
    BMC Syst Biol; 2016 Jan; 10():12. PubMed ID: 26810975
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A genomic strategy to elucidate modules of oncogenic pathway signaling networks.
    Chang JT; Carvalho C; Mori S; Bild AH; Gatza ML; Wang Q; Lucas JE; Potti A; Febbo PG; West M; Nevins JR
    Mol Cell; 2009 Apr; 34(1):104-14. PubMed ID: 19362539
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas.
    Rosario SR; Long MD; Affronti HC; Rowsam AM; Eng KH; Smiraglia DJ
    Nat Commun; 2018 Dec; 9(1):5330. PubMed ID: 30552315
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Gene regulatory networking reveals the molecular cue to lysophosphatidic acid-induced metabolic adaptations in ovarian cancer cells.
    Ray U; Roy Chowdhury S; Vasudevan M; Bankar K; Roychoudhury S; Roy SS
    Mol Oncol; 2017 May; 11(5):491-516. PubMed ID: 28236660
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Conservation of immune gene signatures in solid tumors and prognostic implications.
    Chifman J; Pullikuth A; Chou JW; Bedognetti D; Miller LD
    BMC Cancer; 2016 Nov; 16(1):911. PubMed ID: 27871313
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Co-expression modules construction by WGCNA and identify potential prognostic markers of uveal melanoma.
    Wan Q; Tang J; Han Y; Wang D
    Exp Eye Res; 2018 Jan; 166():13-20. PubMed ID: 29031853
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Metabolic gene alterations impact the clinical aggressiveness and drug responses of 32 human cancers.
    Sinkala M; Mulder N; Patrick Martin D
    Commun Biol; 2019; 2():414. PubMed ID: 31754644
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A network-pathway based module identification for predicting the prognosis of ovarian cancer patients.
    Wang X; Wang SS; Zhou L; Yu L; Zhang LM
    J Ovarian Res; 2016 Nov; 9(1):73. PubMed ID: 27806724
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.