Skip to main content
Hauptrubriken
CME Facharzt-Training Webinare Zeitschriften Bücher e.Medpedia Podcast
Service
Jobbörse Info & Hilfe
Fachgebiete
Anästhesiologie Allgemeinmedizin Arbeitsmedizin Augenheilkunde Chirurgie Dermatologie Gynäkologie und Geburtshilfe HNO Innere Medizin Kardiologie Neurologie Onkologie und Hämatologie Orthopädie und Unfallchirurgie Pädiatrie Pathologie Psychiatrie Radiologie Rechtsmedizin Urologie Zahnmedizin
Themen
Typ-2-Diabetes und Adipositas Klimawandel und Gesundheit Neues aus dem Markt COVID-19 Praxis und Beruf Seltene Erkrankungen GOÄ & EBM Panorama
Sammlungen
Kasuistiken Algorithmen & Infografiken Blickdiagnosen Arthropedia FlapFinder (für Dermatochirurgen) Videos Kongressberichterstattung Medizin für Apothekerinnen und Apotheker Für Ärztinnen und Ärzte in Weiterbildung Für Medizinstudierende

Die Highlights vom Kongress des American College of Cardiology 2024

Im April diskutierten die Herz-Kreislauf-Spezialisten aus der ganzen Welt auf dem  Kongress des American College of Cardiology (ACC) u.a. neue Therapieansätze bei akutem Myokardinfarkt, koronarer Herzerkrankung, kardiogenem Schock oder Aortenklappenstenose. In unserem Kongress-Dossier haben wir für Sie Berichte über die „Late-Breaking Trials“ und andere wichtige Studien zusammengestellt. 
Erweiterte Suche
Anmelden
nach oben
Pathology & Oncology Research
Erschienen in: Pathology & Oncology Research 3/2020

17.12.2019 | Original Article

Identification of Key Genes and Signaling Pathways Associated with the Progression of Gastric Cancer

verfasst von: Chaoran Yu, Jie Chen, Junjun Ma, Lu Zang, Feng Dong, Jing Sun, Minhua Zheng

Erschienen in: Pathology & Oncology Research | Ausgabe 3/2020

Einloggen, um Zugang zu erhalten

Abstract

Genomic features have been gradually regarded as part of the fundamentals to the clinical diagnosis and treatment for gastric cancer. However, the molecular alterations taking place during the progression of gastric cancer remain unclear. Therefore, identification of potential key genes and pathways in the gastric cancer progression is crucial to clinical practices. The gene expression profile, GSE103236, was retrieved for the identification of the differentially expressed genes (DEGs), followed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments, gene set enrichment analysis (GSEA) and the protein-protein interaction (PPI) networks. Multiple bioinformatics platforms were employed for expression and prognostic analysis. Fresh frozen gastric cancer tissues were used for external validation. A total of 161 DEGs were identified from GSE103236. The PPI network-derived hub genes included collagen type I alpha 1 chain (COL1A1), tissue inhibitor of the metalloproteinases (TIMP1), Secreted Phosphoprotein 1 (SPP1), somatostatin (SST), neuropeptide Y (NPY), biglycan (BGN), matrix metallopeptidase 3 (MMP3), apolipoprotein E (APOE), ATPase H+/K+ transporting alpha subunit (ATP4A), lysyl oxidase (LOX). SPP1 (log rank p = 0.0048, HR = 1.39 [1.1–1.75]) and MMP3 (log rank p < 0.0001, HR = 1.77 [1.44–2.19]) were significantly associated with poor overall survival. Stage-specifically, both COL1A1 and BGN were correlated with significant in stage III and IV gastric cancer cases. LOX showed significant correlation with prognosis in stage I and stage II gastric cancer cases. Furthermore, cg00583003 of SPP1 and cg16466334 of MMP3 exhibited highly methylation level and significant prognostic values (SPP1: HR = 1.625, p = 0.013; MMP3: HR = 0.647, p = 0.011). Hub genes signature displayed a favorable prognostic value (p value = 5.227e-05). APOE demonstrated the highest correlation with CD8+ T cells, neutrophils, and dendritic cells whereas BGN had the highest correlation with macrophages. This study systematically explored the key genes and pathways involved in PGC and AGC, providing insights into therapeutic individualized management.
Literatur
1.
Siegel RL, Miller KD, Jemal A (2016) Cancer statistics, 2016[J]. CA Cancer J Clin 66(1):7–30PubMedCrossRef
2.
Chen W, Zheng R, Baade P D, et al. (2015) Cancer statistics in China[J]
3.
Ajani JA, Bentrem DJ, Besh S, D'Amico TA, Das P, Denlinger C, Fakih MG, Fuchs CS, Gerdes H, Glasgow RE, Hayman JA, Hofstetter WL, Ilson DH, Keswani RN, Kleinberg LR, Korn WM, Lockhart AC, Meredith K, Mulcahy MF, Orringer MB, Posey JA, Sasson AR, Scott WJ, Strong VE, Varghese TK Jr, Warren G, Washington MK, Willett C, Wright CD, McMillian N, Sundar H, National Comprehensive Cancer Network (2013) Gastric cancer, version 2.2013[J]. J Natl Compr Cancer Netw 11(5):531–546CrossRef
4.
Edge SB, Compton CC (2010) The American joint committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM[J]. Ann Surg Oncol 17(6):1471–1474PubMedCrossRef
5.
Cristescu R, Lee J, Nebozhyn M, Kim KM, Ting JC, Wong SS, Liu J, Yue YG, Wang J, Yu K, Ye XS, Do IG, Liu S, Gong L, Fu J, Jin JG, Choi MG, Sohn TS, Lee JH, Bae JM, Kim ST, Park SH, Sohn I, Jung SH, Tan P, Chen R, Hardwick J, Kang WK, Ayers M, Hongyue D, Reinhard C, Loboda A, Kim S, Aggarwal A (2015) Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes[J]. Nat Med 21(5):449–456PubMedCrossRef
6.
Cancer Genome Atlas Research Network (2014) Comprehensive molecular characterization of gastric adenocarcinoma[J]. Nature 513(7517):202–209CrossRef
7.
Chivu EM, Necula LG, Dragu D et al (2010) Identification of potential biomarkers for early and advanced gastric adenocarcinoma detection[J]. Hepato-Gastroenterol 57(104):1453
8.
Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository[J]. Nucleic Acids Res 30(1):207–210PubMedPubMedCentralCrossRef
9.
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, Yefanov A, Lee H, Zhang N, Robertson CL, Serova N, Davis S, Soboleva A (2013) NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res 41(Database issue):​D991-5
10.
Davis S, Meltzer PS (2007) GEOquery: a bridge between the gene expression omnibus (GEO) and BioConductor[J]. Bioinformatics 23(14):1846–1847PubMedCrossRef
11.
Pathan M, Keerthikumar S, Ang CS, Gangoda L, Quek CY, Williamson NA, Mouradov D, Sieber OM, Simpson RJ, Salim A, Bacic A (2015) FunRich: an open access standalone functional enrichment and interaction network analysis tool. Proteomics 15(15):2597–2601PubMedCrossRef
12.
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G (2000) Gene ontology: tool for the unification of biology[J]. Nat Genet 25(1):25–29PubMedPubMedCentralCrossRef
13.
14.
Huang DW, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[J]. Nat Protoc 4(1):44–57CrossRef
15.
Subramanian A, Tamayo P, Mootha VK et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles[J]. Proc Natl Acad Sci 102(43):15545–15550PubMedPubMedCentralCrossRef
16.
Szklarczyk D, Franceschini A, Wyder S et al (2014) STRING v10: protein–protein interaction networks, integrated over the tree of life[J]. Nucleic Acids Res 43(D1):D447–D452PubMedPubMedCentralCrossRef
17.
Tang Z, Li C, Kang B, et al. (2017) GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses[J]. Nucleic Acids Res
18.
Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML, Larsson E, Antipin Y, Reva B, Goldberg AP, Sander C, Schultz N (2012) The cBio Cancer genomics portal: an open platform for exploring multidimensional Cancer genomics data. Cancer Discov 2(5):401–404PubMedCrossRef
19.
20.
Cho JY, Lim JY, Cheong JH, Park YY, Yoon SL, Kim SM, Kim SB, Kim H, Hong SW, Park YN, Noh SH, Park ES, Chu IS, Hong WK, Ajani JA, Lee JS (2011) Gene expression signature-based prognostic risk score in gastric cancer. Clin Cancer Res 17(7):1850–1857PubMedPubMedCentralCrossRef
21.
Cui J, Chen Y, Chou WC, Sun L, Chen L, Suo J, Ni Z, Zhang M, Kong X, Hoffman LL, Kang J, Su Y, Olman V, Johnson D, Tench DW, Amster IJ, Orlando R, Puett D, Li F, Xu Y (2011) An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucleic Acids Res 39(4):1197–1207PubMedCrossRef
22.
Uhlen M, Oksvold P, Fagerberg L, Lundberg E, Jonasson K, Forsberg M, Zwahlen M, Kampf C, Wester K, Hober S, Wernerus H, Björling L, Ponten F (2010) Towards a knowledge-based human protein atlas. Nat Biotechnol 28(12):1248–1250PubMedCrossRef
23.
Spandidos A, Wang X, Wang H, Seed B (2010) PrimerBank: a resource of human and mouse PCR primer pairs for gene expression detection and quantification. Nucleic Acids Res 38:D792–D799PubMedCrossRef
24.
Lanczky A, Nagy A, Bottai G, Munkacsy G, Paladini L, Szabo A, Santarpia L, Gyorffy B (2016) miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2,178 breast cancer patients. Breast Cancer Res Treat 160(3):439–446PubMedCrossRef
25.
Modhukur V, Iljasenko T, Metsalu T, Lokk K, Laisk-Podar T, Vilo J (2018 Mar) MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data. Epigenomics. 10(3):277–288PubMedCrossRef
26.
Aguirre-Gamboa R, Gomez-Rueda H, Martínez-Ledesma E, Martínez-Torteya A, Chacolla-Huaringa R, Rodriguez-Barrientos A, Tamez-Pena JG, Trevino V (2013) SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis. PLoS One 8(9):e74250PubMedPubMedCentralCrossRef
27.
Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, Li B, Liu XS (2017 Nov 1) TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res 77(21):e108–e110PubMedPubMedCentralCrossRef
28.
Hwang SH, Park DJ, Jee YS, Kim MC, Kim HH, Lee HJ, Yang HK, Lee KU (2009) Actual 3-year survival after laparoscopy-assisted gastrectomy for gastric cancer[J]. Arch Surg 144(6):559–564PubMedCrossRef
29.
Hu Y, Ying M, Huang C, Wei H, Jiang Z, Peng X, Hu J, du X, Wang B, Lin F, Xu J, Dong G, Mou T, Li G, Chinese Laparoscopic Gastrointestinal Surgery Study (CLASS) Group (2014) Oncologic outcomes of laparoscopy-assisted gastrectomy for advanced gastric cancer: a large-scale multicenter retrospective cohort study from China[J]. Surg Endosc 28(7):2048–2056PubMedCrossRef
30.
Rugge M, Fassan M, Graham D Y (2015) Epidemiology of gastric cancer[M]//gastric Cancer. Springer International Publishing, 23–34
31.
Strong VE, Song KY, Park CH, Jacks LM, Gonen M, Shah M, Coit DG, Brennan MF (2010) Comparison of gastric cancer survival following R0 resection in the United States and Korea using an internationally validated nomogram[J]. Ann Surg 251(4):640–646PubMedCrossRef
32.
33.
Liaw L, Birk DE, Ballas CB, Whitsitt JS, Davidson JM, Hogan BL (1998) Altered wound healing in mice lacking a functional osteopontin gene (spp1)[J]. J Clin Investig 101(7):1468–1478PubMedCrossRefPubMedCentral
34.
Spiegel S, Milstien S (2003) Sphingosine-1-phosphate: an enigmatic signalling lipid[J]. Nat Rev Mol Cell Biol 4(5):397–407CrossRefPubMed
35.
Junnila S, Kokkola A, Mizuguchi T, Hirata K, Karjalainen-Lindsberg ML, Puolakkainen P, Monni O (2010) Gene expression analysis identifies over-expression of CXCL1, SPARC, SPP1, and SULF1 in gastric cancer[J]. Genes Chromosom Cancer 49(1):28–39PubMedCrossRef
36.
Zhuo C, Li X, Zhuang H, Tian S, Cui H, Jiang R, Liu C, Tao R, Lin X (2016) Elevated THBS2, COL1A2, and SPP1 expression levels as predictors of gastric Cancer prognosis[J]. Cell Physiol Biochem 40(6):1316–1324PubMedCrossRef
37.
Sternlicht MD, Lochter A, Sympson CJ, Huey B, Rougier JP, Gray JW, Pinkel D, Bissell MJ, Werb Z (1999) The stromal proteinase MMP3/stromelysin-1 promotes mammary carcinogenesis[J]. Cell 98(2):137–146PubMedPubMedCentralCrossRef
38.
Kubota E, Imamura H, Kubota T et al (1997) Interleukin 1β and stromelysin (MMP3) activity of synovial fluid as possible markers of osteoarthritis in the temporomandibular joint[J]. J Oral Maxillofac Surg 55(1):20–27PubMedCrossRef
39.
Stamenkovic I (2003) Extracellular matrix remodelling: the role of matrix metalloproteinases[J]. J Pathol 200(4):448–464PubMedCrossRef
40.
Yeh YC, Sheu BS, Cheng HC, Wang YL, Yang HB, Wu JJ (2010) Elevated serum matrix metalloproteinase-3 and-7 in H. pylori-related gastric cancer can be biomarkers correlating with a poor survival[J]. Dig Dis Sci 55(6):1649–1657PubMedCrossRef
41.
Xu J, Yao Y, Ren S et al (2016) Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer[J]. Oncol Lett 12(4):2403–2408PubMedPubMedCentralCrossRef
42.
Fernandez-Capetillo O, Chen HT, Celeste A, Ward I, Romanienko PJ, Morales JC, Naka K, Xia Z, Camerini-Otero RD, Motoyama N, Carpenter PB, Bonner WM, Chen J, Nussenzweig A (2002) DNA damage-induced G2–M checkpoint activation by histone H2AX and 53BP1[J]. Nat Cell Biol 4(12):993–997PubMedCrossRef
43.
Sun C, Yuan Q, Wu D et al (2017) Identification of core genes and outcome in gastric cancer using bioinformatics analysis[J]. Oncotarget 8(41):70271PubMedPubMedCentralCrossRef
44.
Guo L, Song C, Wang P, Dai L, Zhang J, Wang K (2015) A systems biology approach to detect key pathways and interaction networks in gastric cancer on the basis of microarray analysis[J]. Mol Med Rep 12(5):7139–7145PubMedCrossRef
45.
Rong L, Huang W, Tian S, Chi X, Zhao P, Liu F (2018) COL1A2 is a novel biomarker to improve clinical prediction in human gastric Cancer: integrating bioinformatics and meta-analysis[J]. Pathol Oncol Res 24(1):129–134PubMedCrossRef
Metadaten
Titel
Identification of Key Genes and Signaling Pathways Associated with the Progression of Gastric Cancer
verfasst von
Chaoran Yu
Jie Chen
Junjun Ma
Lu Zang
Feng Dong
Jing Sun
Minhua Zheng
Publikationsdatum
17.12.2019
Verlag
Springer Netherlands
Erschienen in
Pathology & Oncology Research / Ausgabe 3/2020
Print ISSN: 1219-4956
Elektronische ISSN: 1532-2807
DOI
https://doi.org/10.1007/s12253-019-00781-3

Weitere Artikel der Ausgabe 3/2020

Pathology & Oncology Research 3/2020 Zur Ausgabe

Original Article

External Quality Assurance of Current Technology for the Testing of Cancer-Associated Circulating Free DNA Variants

Original Article

Clinical Effect of CD25 on the Prognosis of Diffuse Large B Cell Lymphoma with Secondary Central Nervous System Relapse

Original Article

Clinical Application of Long Non-Coding RNA-UCA1 as a Candidate Gene in Progression of Esophageal Cancer

Review

Prognostic Differences in ISUP Grade Group 4: a Systematic Review and Meta-Analysis

Original Article

Local Inflammatory Response Can Predict Clinical Outcome in Patients with Curatively Resected Stage-IIB Colon Cancer: An Advanced Methodological Study

Correction

Correction to: Phloretin Inhibits the Human Prostate Cancer Cells through the Generation of Reactive Oxygen Species

Neu im Fachgebiet Onkologie

Mammakarzinom: Brustdichte beeinflusst rezidivfreies Überleben

26.05.2024 Mammakarzinom Nachrichten

Frauen, die zum Zeitpunkt der Brustkrebsdiagnose eine hohe mammografische Brustdichte aufweisen, haben ein erhöhtes Risiko für ein baldiges Rezidiv, legen neue Daten nahe.

Mehr Lebenszeit mit Abemaciclib bei fortgeschrittenem Brustkrebs?

24.05.2024 Mammakarzinom Nachrichten

In der MONARCHE-3-Studie lebten Frauen mit fortgeschrittenem Hormonrezeptor-positivem, HER2-negativem Brustkrebs länger, wenn sie zusätzlich zu einem nicht steroidalen Aromatasehemmer mit Abemaciclib behandelt wurden; allerdings verfehlte der numerische Zugewinn die statistische Signifikanz.

ADT zur Radiatio nach Prostatektomie: Wenn, dann wohl länger

24.05.2024 Prostatakarzinom Nachrichten

Welchen Nutzen es trägt, wenn die Strahlentherapie nach radikaler Prostatektomie um eine Androgendeprivation ergänzt wird, hat die RADICALS-HD-Studie untersucht. Nun liegen die Ergebnisse vor. Sie sprechen für länger dauernden Hormonentzug.

Das sind die führenden Symptome junger Darmkrebspatienten

23.05.2024 Leitsymptome in der Hausarztpraxis Nachrichten

Darmkrebserkrankungen in jüngeren Jahren sind ein zunehmendes Problem, das häufig längere Zeit übersehen wird, gerade weil die Patienten noch nicht alt sind. Welche Anzeichen Ärzte stutzig machen sollten, hat eine Metaanalyse herausgearbeitet.

Update Onkologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen
Bildnachweise