198 related articles for article (PubMed ID: 29685151)
1. Digital gene expression profiling analysis and its application in the identification of genes associated with improved response to neoadjuvant chemotherapy in breast cancer.
Liu X; Jin G; Qian J; Yang H; Tang H; Meng X; Li Y
World J Surg Oncol; 2018 Apr; 16(1):82. PubMed ID: 29685151
[TBL] [Abstract][Full Text] [Related]
2. Transcriptomic Analysis of Breast Cancer Patients Sensitive and Resistant to Chemotherapy: Looking for Overall Survival and Drug Resistance Biomarkers.
Barrón-Gallardo CA; Garcia-Chagollán M; Morán-Mendoza AJ; Delgadillo-Cristerna R; Martínez-Silva MG; Aguilar-Lemarroy A; Jave-Suárez LF
Technol Cancer Res Treat; 2022; 21():15330338211068965. PubMed ID: 34981997
[TBL] [Abstract][Full Text] [Related]
3. The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.
Zhang C; Peng L; Zhang Y; Liu Z; Li W; Chen S; Li G
Med Oncol; 2017 Jun; 34(6):101. PubMed ID: 28432618
[TBL] [Abstract][Full Text] [Related]
4. Investigating the therapeutic potential and mechanism of curcumin in breast cancer based on RNA sequencing and bioinformatics analysis.
Wang R; Li J; Zhao Y; Li Y; Yin L
Breast Cancer; 2018 Mar; 25(2):206-212. PubMed ID: 29139094
[TBL] [Abstract][Full Text] [Related]
5. PPAR signaling pathway may be an important predictor of breast cancer response to neoadjuvant chemotherapy.
Chen YZ; Xue JY; Chen CM; Yang BL; Xu QH; Wu F; Liu F; Ye X; Meng X; Liu GY; Shen ZZ; Shao ZM; Wu J
Cancer Chemother Pharmacol; 2012 Nov; 70(5):637-44. PubMed ID: 22903535
[TBL] [Abstract][Full Text] [Related]
6. Identification of Methylation Markers and Differentially Expressed Genes with Prognostic Value in Breast Cancer.
Wu J; Zhang Y; Li M
J Comput Biol; 2019 Dec; 26(12):1394-1408. PubMed ID: 31290690
[TBL] [Abstract][Full Text] [Related]
7. Identification of breast cancer hub genes and analysis of prognostic values using integrated bioinformatics analysis.
Fang E; Zhang X
Cancer Biomark; 2017 Dec; 21(1):373-381. PubMed ID: 29081411
[TBL] [Abstract][Full Text] [Related]
8. Identification of differently expressed genes with specific SNP Loci for breast cancer by the integration of SNP and gene expression profiling analyses.
Yuan P; Liu D; Deng M; Liu J; Wang J; Zhang L; Liu Q; Zhang T; Chen Y; Jin G
Pathol Oncol Res; 2015 Apr; 21(2):469-75. PubMed ID: 25408372
[TBL] [Abstract][Full Text] [Related]
9. SIRT5 as a biomarker for response to anthracycline-taxane-based neoadjuvant chemotherapy in triple-negative breast cancer.
Xu L; Che X; Wu Y; Song N; Shi S; Wang S; Li C; Zhang L; Zhang X; Qu X; Teng Y
Oncol Rep; 2018 May; 39(5):2315-2323. PubMed ID: 29565454
[TBL] [Abstract][Full Text] [Related]
10. Screening of the prognostic targets for breast cancer based co-expression modules analysis.
Liu H; Ye H
Mol Med Rep; 2017 Oct; 16(4):4038-4044. PubMed ID: 28731166
[TBL] [Abstract][Full Text] [Related]
11. Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer.
Yang C; Gong A
Int J Med Sci; 2021; 18(3):792-800. PubMed ID: 33437215
[No Abstract] [Full Text] [Related]
12. Correlating transcriptional networks with pathological complete response following neoadjuvant chemotherapy for breast cancer.
Liu R; Lv QL; Yu J; Hu L; Zhang LH; Cheng Y; Zhou HH
Breast Cancer Res Treat; 2015 Jun; 151(3):607-18. PubMed ID: 25981901
[TBL] [Abstract][Full Text] [Related]
13. Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).
Huan J; Wang L; Xing L; Qin X; Feng L; Pan X; Zhu L
Gene; 2014 Jan; 533(1):346-55. PubMed ID: 23978611
[TBL] [Abstract][Full Text] [Related]
14. High-efficient Screening Method for Identification of Key Genes in Breast Cancer Through Microarray and Bioinformatics.
Liu Z; Liang G; Tan L; Su AN; Jiang W; Gong C
Anticancer Res; 2017 Aug; 37(8):4329-4335. PubMed ID: 28739725
[TBL] [Abstract][Full Text] [Related]
15. RNA Sequencing Uncovers Molecular Mechanisms Underlying Pathological Complete Response to Chemotherapy in Patients with Operable Breast Cancer.
Li Y; Liu X; Tang H; Yang H; Meng X
Med Sci Monit; 2017 Sep; 23():4321-4327. PubMed ID: 28880852
[TBL] [Abstract][Full Text] [Related]
16. Identification of miRNA Signature in Breast Cancer to Predict Neoadjuvant Chemotherapy Response.
Xing AY; Wang B; Li YH; Chen X; Wang YW; Liu HT; Gao P
Pathol Oncol Res; 2021; 27():1609753. PubMed ID: 34257614
[No Abstract] [Full Text] [Related]
17. Identification of significant genes as prognostic markers and potential tumor suppressors in lung adenocarcinoma via bioinformatical analysis.
Lu M; Fan X; Liao W; Li Y; Ma L; Yuan M; Gu R; Wei Z; Wang C; Zhang H
BMC Cancer; 2021 May; 21(1):616. PubMed ID: 34039311
[TBL] [Abstract][Full Text] [Related]
18. Combined Analysis of ChIP Sequencing and Gene Expression Dataset in Breast Cancer.
Liu P; Jiang W; Zhou S; Gao J; Zhang H
Pathol Oncol Res; 2017 Apr; 23(2):361-368. PubMed ID: 27654269
[TBL] [Abstract][Full Text] [Related]
19. Ratio of proliferation markers and HSP90 gene expression as a predictor of pathological complete response in breast cancer neoadjuvant chemotherapy.
Jarzab M; Kowal M; Bal W; Oczko-Wojciechowska M; Rembak-Szynkiewicz J; Kowalska M; Stobiecka E; Chmielik E; Tyszkiewicz T; Kaszuba M; Nowicka E; Lange B; Czarniecka A; Krajewska J; Dyla A; Dobrut M; Lange D; Jarzab B; Bobek-Billewicz B; Tarnawski R
Folia Histochem Cytobiol; 2016; 54(4):202-209. PubMed ID: 28051275
[TBL] [Abstract][Full Text] [Related]
20. Identification of Hub Genes Using Co-Expression Network Analysis in Breast Cancer as a Tool to Predict Different Stages.
Fu Y; Zhou QZ; Zhang XL; Wang ZZ; Wang P
Med Sci Monit; 2019 Nov; 25():8873-8890. PubMed ID: 31758680
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
