9 maart 2024: Bron:  2024; 9: 19. Published online 2024 Mar 5

Uit een zogeheten Genome studie (GWAS studie)  (DNA en erfelijkheidstudie) blijkt dat enkele specifieke genmutaties een grote rol spelen bij al of niet succesvolle post operatieve behandelingen bij patiënten met operabele eierstokkanker. MGMT en PPP2R5C zijn de twee erfelijke genmutaties die er daarbij uitsprongen. 
Patiënten waarbij een complete resectie zonder restziekte werd bereikt hebben over het algemeen grotere kans op genezing dan patiënten waarbij later sprake blijkt van restziekte en een recidief. Enkele specifieke genmutaties spelen daarbij dus ook een grote rol. Blijkt uit grote Genome studie (GWAS studie).

Uit het abstract: De meest significante associatie met de resectiestatus werd waargenomen voor rs72845444, in verlengde  van MGMT, in High-grade serous ovarian cancer (HGSOC) (p = 3,9 × 10−8). In gengebaseerde analyses was PPP2R5C het sterkst geassocieerde gen in HGSOC na stadiumaanpassing.

In een vervolgstudie werd bij 378 eierstoktumoren uit de AGO-OVAR 11-studie opgezet en correleerden varianten in verlengde van MGMT en PPP2R5C  met methylering en transcriptniveaus, en PPP2R5C-mRNA-niveaus voorspelden de duur van progressievrije overleving bij patiënten met restziekte.

In onderstaande afbeelding Fig. 1 het schemo zoals de studie is opgezet en uitgevoerd:

An external file that holds a picture, illustration, etc.
Object name is 41525_2024_395_Fig1_HTML.jpg

Fig. 1
Workflow of the GWAS and follow-up study.

a Study workflow combining three analyses of OCAC GWAS data for overall, invasive-only and high-grade serous ovarian cancer (left) with AGO-OVAR 11 and TCGA gene expression and clinical datasets. b Manhattan plot depicting GWAS results in high-grade serous ovarian cancer (unadjusted for stage) with rs72845444 as the top hit. Blue line: p = 1 × 10−5, red line: p = 5 × 10−8c Locus Zoom regional association plot for variant rs72845444, close to MGMT.

Dat PPP2R5C en FAM35A alleen geassocieerd waren na aanpassing voor het stadium van de ziekte suggereert dat ze onafhankelijke voorspellers van resterende recidiverende ziekte zouden kunnen zijn. De samenvattende GWAS-statistieken van de belangrijkste SNP's die ten grondslag liggen aan deze MAGMA-genassociaties zijn aanvullend te zien in Table 2

Samenvattend, schrijven de onderzoekers, leverde onze Genome studie (GWAS studie) sterk bewijs voor kandidaat-genomische loci geassocieerd met resectiestatus bij patiënten met operabele eierstokkanker (EOC) die een primaire debulking-operatie ondergaan en identificeerde een potentiële rol voor erfelijke varianten bij twee genen die betrokken zijn bij DNA-reparatie, MGMT en PPP2R5C , bij het moduleren van genexpressie en debulking, uitkomst en progressievrije overleving.

Toekomstige prospectieve studies zouden genomische markers voor deze genen moeten testen als voorspellende factoren voor de resectiestatus en prognostische factoren voor overleving bij patiënten met epitheliale eierstokkanker.

Het volledige studieverslag is gratis in te zien maar is wel ingewikkeld, al zijn de vele grafieken wel verhelderend.

 2024; 9: 19.
Published online 2024 Mar 5. doi: 10.1038/s41525-024-00395-y
PMCID: PMC10915171
PMID: 38443389

Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease

Abstract

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10−8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

In summary, our GWAS provided strong evidence for candidate genomic loci associated with resection status in patients with EOC undergoing primary debulking surgery and identified a potential role for inherited variants at two genes involved in DNA repair, MGMT and PPP2R5C, in modulating gene expression, debulking outcome and progression-free survival. Future prospective studies should test genomic markers at these genes as predictive factors for resection status and prognostic factors for survival in patients with epithelial ovarian cancer.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Supplementary information

Acknowledgements

We thank all the study participants who contributed to this study and all the researchers, clinicians, technical and administrative staff who have made this work possible. Acknowledgements for individual studies: AUS: The AOCS also acknowledges the cooperation of the participating institutions in Australia, and the contribution of the study nurses, research assistants and all clinical and scientific collaborators. The complete AOCS Study Group can be found at www.aocstudy.org. We would like to thank all of the women who participated in this research programme; BEL: We would like to thank Gilian Peuteman, Thomas Van Brussel, Annick Van den Broeck and Joke De Roover for technical assistance; MOF: the Total Cancer Care™ Protocol and the Collaborative Data Services and Tissue Core Facilities at the H. Lee Moffitt Cancer Center & Research Institute, an NCI designated Comprehensive Cancer Center (P30-CA076292), Merck Pharmaceuticals and the state of Florida; OPL: Members of the OPAL Study Group (http://opalstudy.qimrberghofer.edu.au/); SRO: To thank all members of Scottish Gynaecological Clinical Trails group and SCOTROC1 investigators; UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; WMH: We thank the Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group. The Ovarian Cancer Association Consortium is funded by generous contributions from its research investigators and through anonymous donations. OCAC was funded by a grant from the Ovarian Cancer Research Fund (OCRF). The OCAC OncoArray genotyping project was funded through grants from the U.S. National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.) and R01-CA058598 (M.T.G.); Canadian Institutes of Health Research (MOP-86727 (L.E.K.) and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission’s Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175) and in part by the US National Cancer Institute GAME-ON Post-GWAS Initiative (U19-CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium that was funded by the Wellcome Trust under award 076113. The results published are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). Funding for individual studies: AUS: The Australian Ovarian Cancer Study (AOCS) was supported by the U.S. Army Medical Research and Materiel Command (DAMD17-01-1-0729), National Health & Medical Research Council of Australia (199600, 400413 and 400281), Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tasmania and Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182). AOCS gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation; BAV: ELAN Funds of the University of Erlangen-Nuremberg; BEL: National Kankerplan; CNI: Instituto de Salud Carlos III (PI 19/01730); Ministerio de Economía y Competitividad (SAF2012); HAW: U.S. National Institutes of Health (R01-CA58598, N01-CN-55424 and N01-PC-67001); HOP: University of Pittsburgh School of Medicine Dean’s Faculty Advancement Award (F. Modugno), Department of Defense (DAMD17-02-1-0669, OC20085) and United States National Cancer Institute (R21-CA267050, K07-CA080668, R01-CA95023, MO1-RR000056); LAX: American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124; MAC: National Institutes of Health (R01-CA2482288, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by research grant R01- CA61107 from the National Cancer Institute, Bethesda, MD, research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark, the Mermaid I project; and the Mermaid III project; MAY: National Institutes of Health (R01-CA248288, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MOF: Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County, and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01-CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway; OPL: National Health and Medical Research Council (NHMRC) of Australia (APP1025142, APP1120431) and Brisbane Women’s Club; ORE: Sherie Hildreth Ovarian Cancer (SHOC) Foundation; PVD: Canadian Cancer Society and Cancer Research Society GRePEC Program; SRO: Cancer Research UK (C536/A13086, C536/A6689) and Imperial Experimental Cancer Research Centre (C1312/A15589); UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16. The AGO-OVAR 11 study was funded by Roche Pharma AG.

Author contributions

The study was conceptualised by F.H., T.D., P.D.P., G.C-T., S.J.R., and A.B. GWAS analysis was performed by J.P.T. Further genotyping, data analysis and post-GWAS analysis were performed by D.R., P.Sc., and L-M.Spei. RNA sequencing and methylation data were generated by S.Ko., B.Wi. and J.Pf. OCAC database was maintained and coordinated by M.J.R. Authors on behalf of OCAC contributed samples and clinical data to OCAC. Authors on behalf of the AGO contributed samples and clinical data to the AGO-OVAR 11 study. The manuscript was drafted by D.R., F.H. and T.D., with critical input from members of the writing group (J.T., A.DF., M.J.R., A.B., P.D.P, G.C-T., S.J.R.). All authors were involved in the further editing of the manuscript and agreed with this version of the manuscript.

Funding

Open Access funding enabled and organized by Projekt DEAL.

Data availability

Summary statistics from the six GWASs in this study will be available at GWAS Catalogue (accession GCP ID: GCP000727; GCST IDs for each GWAS: All_OC_FIGO GCST90292521, All_OC_no_FIGO GCST90292522, HGSOC_FIGO GCST90292523, HGSOC_no_FIGO GCST90292524, Invasive_EOC_FIGO GCST90292525, Invasive_EOC_no_FIGO GCST90292526). OCAC summary results are available from the combined iCOGS, Oncoarray, GWAS meta-analyses and can be looked up at the OCAC website https://ocac.ccge.medschl.cam.ac.uk/data-projects/results-lookup-by-region/. Individual-level genotyping data generated in this study are not publicly available due to patient privacy requirements but can be applied for through established OCAC procedures. Derived data supporting the findings of this study are available from the corresponding author upon reasonable request.

Competing interests

U.C. received honoraria for lectures from Lilly and AstraZeneca and is on the advisory board of AstraZeneca. J.P. received honoraria from Roche Pharma AG, AstraZeneca, Amgen, Clovis Oncology, MSD Oncology, GSK, Chugai Pharma, Teva, Medupdate, SAI MedPartners, Decision Resources, Simon-Kucher and partners, Juniper, Bionest partners, Vox Bio, Axiom healthcare strategies, Prosapient, iMed Institut, Lilly, and is a consultant/advisor for AstraZeneca, Roche, Pharma AG, Tesaro, Clovis Oncology, MSD Oncology. P.A.F. conducts research funded by Amgen, Novartis and Pfizer and received Honoraria from Roche, Novartis and Pfizer. None of these sponsors had any role in the design, data acquisition or interpretation of results in the present study.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Lists of authors and their affiliations appear at the end of the paper.

Contributor Information

Thilo Dörk, ed.revonnah-hm@oliht.kreod.

Florian Heitz, moc.dem-mek@ztieH.Ften.xmg@ztieh.nairolf.

AOCS Group:

OPAL Study Group:

Supplementary information

The online version contains supplementary material available at 10.1038/s41525-024-00395-y.

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J. Clin. 2020;70:7–30. doi: 10.3322/caac.21590. [PubMed] [CrossRef[]
2. Jelovac D, Armstrong DK. Recent progress in the diagnosis and treatment of ovarian cancer. CA Cancer J. Clin. 2011;61:183–203. doi: 10.3322/caac.20113. [PMC free article] [PubMed] [CrossRef[]
3. Freimund AE, Beach JA, Christie EL, Bowtell DDL. Mechanisms of drug resistance in high-grade serous ovarian cancer. Hematol. Oncol. Clin. North Am. 2018;32:983–996. doi: 10.1016/j.hoc.2018.07.007. [PubMed] [CrossRef[]
4. Rochon J, du Bois A. Clinical research in epithelial ovarian cancer and patients’ outcome. Ann. Oncol. 2011;22:vii16–vii19. doi: 10.1093/annonc/mdr421. [PubMed] [CrossRef[]
5. Tseng JH, et al. Continuous improvement in primary Debulking surgery for advanced ovarian cancer: do increased complete gross resection rates independently lead to increased progression-free and overall survival? Gynecol. Oncol. 2018;151:24–31. doi: 10.1016/j.ygyno.2018.08.014. [PMC free article] [PubMed] [CrossRef[]
6. Norppa N, Staff S, Helminen M, Auranen A, Saarelainen S. Improved survival after implementation of ultra-radical surgery in advanced epithelial ovarian cancer: Results from a tertiary referral center. Gynecol. Oncol. 2022;165:478–485. doi: 10.1016/j.ygyno.2022.03.023. [PubMed] [CrossRef[]
7. Chang S-J, Bristow RE. Evolution of surgical treatment paradigms for advanced-stage ovarian cancer: Redefining ‘optimal’ residual disease. Gynecol. Oncol. 2012;125:483–492. doi: 10.1016/j.ygyno.2012.02.024. [PubMed] [CrossRef[]
8. du Bois A, et al. Role of surgical outcome as prognostic factor in advanced epithelial ovarian cancer: a combined exploratory analysis of 3 prospectively randomized phase 3 multicenter trials. Cancer. 2009;115:1234–1244. doi: 10.1002/cncr.24149. [PubMed] [CrossRef[]
9. Kommoss S, et al. Prognostic impact of additional extended surgical procedures in advanced-stage primary ovarian cancer. Ann. Surg. Oncol. 2010;17:279–286. doi: 10.1245/s10434-009-0787-8. [PubMed] [CrossRef[]
10. Eisenhauer EL, et al. The addition of extensive upper abdominal surgery to achieve optimal cytoreduction improves survival in patients with stages IIIC–IV epithelial ovarian cancer. Gynecol. Oncol. 2006;103:1083–1090. doi: 10.1016/j.ygyno.2006.06.028. [PubMed] [CrossRef[]
11. Chi DS, et al. Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm. Gynecol. Oncol. 2009;114:26–31. doi: 10.1016/j.ygyno.2009.03.018. [PubMed] [CrossRef[]
12. Harter P, et al. Impact of a structured quality management program on surgical outcome in primary advanced ovarian cancer. Gynecol. Oncol. 2011;121:615–619. doi: 10.1016/j.ygyno.2011.02.014. [PubMed] [CrossRef[]
13. Manning-Geist BL, et al. A novel classification of residual disease after interval debulking surgery for advanced-stage ovarian cancer to better distinguish oncologic outcome. Am. J. Obstet. Gynecol. 2019;221:326.e1–326.e7. doi: 10.1016/j.ajog.2019.05.006. [PubMed] [CrossRef[]
14. Heitz F, et al. Pattern of and reason for postoperative residual disease in patients with advanced ovarian cancer following upfront radical debulking surgery. Gynecol. Oncol. 2016;141:264–270. doi: 10.1016/j.ygyno.2016.03.015. [PubMed] [CrossRef[]
15. Riester M, et al. Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples. JNCI J. Natl Cancer Inst. 2014;106:1–12. doi: 10.1093/jnci/dju048. [PMC free article] [PubMed] [CrossRef[]
16. Liu Z, et al. Suboptimal cytoreduction in ovarian carcinoma is associated with molecular pathways characteristic of increased stromal activation. Gynecol. Oncol. 2015;139:394–400. doi: 10.1016/j.ygyno.2015.08.026. [PMC free article] [PubMed] [CrossRef[]
17. Kenny HA, et al. Mesothelial cells promote early Ovarian cancer metastasis through fibronectin secretion. J. Clin. Investig. 2014;124:4614–4628. doi: 10.1172/JCI74778. [PMC free article] [PubMed] [CrossRef[]
18. Brieger KK, et al. Menopausal hormone therapy prior to the diagnosis of ovarian cancer is associated with improved survival. Gynecol. Oncol. 2020;158:702–709. doi: 10.1016/j.ygyno.2020.06.481. [PMC free article] [PubMed] [CrossRef[]
19. Phelan CM, et al. Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer. Nat. Genet. 2017;49:680–691. doi: 10.1038/ng.3826. [PMC free article] [PubMed] [CrossRef[]
20. Heitz F, et al. Dilution of molecular-pathologic gene signatures by medically associated factors might prevent prediction of resection status after debulking surgery in patients with advanced ovarian cancer. Clin. Cancer Res. 2020;26:213–219. doi: 10.1158/1078-0432.CCR-19-1741. [PMC free article] [PubMed] [CrossRef[]
21. Kommoss S, et al. Bevacizumab may differentially improve ovarian cancer outcome in patients with proliferative and mesenchymal molecular subtypes. Clin. Cancer Res. 2017;23:3794–3801. doi: 10.1158/1078-0432.CCR-16-2196. [PMC free article] [PubMed] [CrossRef[]
22. Glubb DM, et al. Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci. Oncotarget. 2017;8:64670–64684. doi: 10.18632/oncotarget.18501. [PMC free article] [PubMed] [CrossRef[]
23. Talhouk A, et al. Development and validation of the gene expression predictor of high-grade serous ovarian carcinoma molecular SubTYPE (PrOTYPE) Clin. Cancer Res. 2020;26:5411–5423. doi: 10.1158/1078-0432.CCR-20-0103. [PMC free article] [PubMed] [CrossRef[]
24. Quinn MCJ, et al. Identification of a locus near ULK1 associated with progression-free survival in ovarian cancer. Cancer Epidemiol. Biomark. Prev. 2021;30:1669–1680. doi: 10.1158/1055-9965.EPI-20-1817. [PMC free article] [PubMed] [CrossRef[]
25. Bonome T, et al. A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer. Cancer Res. 2008;68:5478–5486. doi: 10.1158/0008-5472.CAN-07-6595. [PMC free article] [PubMed] [CrossRef[]
26. Tucker SL, et al. Molecular biomarkers of residual disease after surgical debulking of high-grade serous ovarian cancer. Clin. Cancer Res. 2014;20:3280–3288. doi: 10.1158/1078-0432.CCR-14-0445. [PMC free article] [PubMed] [CrossRef[]
27. Berchuck A, et al. Prediction of optimal versus suboptimal cytoreduction of advanced-stage serous ovarian cancer with the use of microarrays. Am. J. Obstet. Gynecol. 2004;190:910–923. doi: 10.1016/j.ajog.2004.02.005. [PubMed] [CrossRef[]
28. Borley J, Wilhelm-Benartzi C, Brown R, Ghaem-Maghami S. Does tumour biology determine surgical success in the treatment of epithelial ovarian cancer? A systematic literature review. Br. J. Cancer. 2012;107:1069–1074. doi: 10.1038/bjc.2012.376. [PMC free article] [PubMed] [CrossRef[]
29. Kim SR, et al. Maximizing cancer prevention through genetic navigation for Lynch syndrome detection in women with newly diagnosed endometrial and nonserous/nonmucinous epithelial ovarian cancer. Cancer. 2021;127:3082–3091. doi: 10.1002/cncr.33625. [PMC free article] [PubMed] [CrossRef[]
30. Ataseven B, et al. Clinical outcome in patients with primary epithelial ovarian cancer and germline BRCA1/2-mutation—real life data. Gynecol. Oncol. 2021;163:569–577. doi: 10.1016/j.ygyno.2021.09.004. [PubMed] [CrossRef[]
31. Hegi ME, et al. Clinical trial substantiates the predictive value of O-6-Methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide. Clin. Cancer Res. 2004;10:1871–1874. doi: 10.1158/1078-0432.CCR-03-0384. [PubMed] [CrossRef[]
32. Della Monica R, et al. MGMT and whole‐genome DNA methylation impacts on diagnosis, prognosis and therapy of glioblastoma multiforme. Int. J. Mol. Sci. 2022;23:7148. doi: 10.3390/ijms23137148. [PMC free article] [PubMed] [CrossRef[]
33. Gessler F, et al. Surgery for glioblastoma in light of molecular markers: impact of resection and MGMT promoter methylation in newly diagnosed IDH-1 wild-type glioblastomas. Neurosurgery. 2019;84:190–197. doi: 10.1093/neuros/nyy049. [PMC free article] [PubMed] [CrossRef[]
34. Incekara F, et al. The association between the extent of glioblastoma resection and survival in light of MGMT promoter methylation in 326 patients with newly diagnosed IDH-wildtype glioblastoma. Front. Oncol. 2020;10:1–8. [PMC free article] [PubMed[]
35. Shouse GP, Nobumori Y, Panowicz MJ, Liu X. ATM-mediated phosphorylation activates the tumor-suppressive function of B56γ–PP2A. Oncogene. 2011;30:3755–3765. doi: 10.1038/onc.2011.95. [PubMed] [CrossRef[]
36. Ambjørn SM, et al. A complex of BRCA2 and PP2A-B56 is required for DNA repair by homologous recombination. Nat. Commun. 2021;12:5748. doi: 10.1038/s41467-021-26079-0. [PMC free article] [PubMed] [CrossRef[]
37. Perrotti D, Neviani P. Protein phosphatase 2A: a target for anticancer therapy. Lancet Oncol. 2013;14:e229–e238. doi: 10.1016/S1470-2045(12)70558-2. [PMC free article] [PubMed] [CrossRef[]
38. Ruvolo PP. The broken “Off” switch in cancer signaling: PP2A as a regulator of tumorigenesis, drug resistance, and immune surveillance. BBA Clin. 2016;6:87–99. doi: 10.1016/j.bbacli.2016.08.002. [PMC free article] [PubMed] [CrossRef[]
39. Avelar, R. A. et al. Small molecule-mediated stabilization of PP2A modulates the Homologous Recombination pathway and potentiates DNA damage-induced cell death. Mol. Cancer Ther. 10.1158/1535-7163.MCT-21-0880 (2023). [PMC free article] [PubMed]
40. Perren TJ, et al. A phase 3 trial of bevacizumab in ovarian cancer. N. Engl. J. Med. 2011;365:2484–2496. doi: 10.1056/NEJMoa1103799. [PubMed] [CrossRef[]
41. Therasse P, et al. New guidelines to evaluate the response to treatment in solid tumors. J. Natl Cancer Inst. 2000;92:205–216. doi: 10.1093/jnci/92.3.205. [PubMed] [CrossRef[]
42. D. Turner S. qqman: an R package for visualizing GWAS results using Q-Q and Manhattan plots. J. Open Source Softw. 2018;3:731. doi: 10.21105/joss.00731. [CrossRef[]
43. Zhao JH. Gap: genetic analysis package. J. Stat. Softw. 2007;23:1–18. doi: 10.18637/jss.v023.i08. [CrossRef[]
44. Watanabe K, Taskesen E, Van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 2017;8:1–10. doi: 10.1038/s41467-017-01261-5. [PMC free article] [PubMed] [CrossRef[]
45. de Leeuw CA, Mooij JM, Heskes T, Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 2015;11:1–19. doi: 10.1371/journal.pcbi.1004219. [PMC free article] [PubMed] [CrossRef[]
46. Arnold M, Raffler J, Pfeufer A, Suhre K, Kastenmüller G. SNiPA: An interactive, genetic variant-centered annotation browser. Bioinformatics. 2015;31:1334–1336. doi: 10.1093/bioinformatics/btu779. [PMC free article] [PubMed] [CrossRef[]
47. Lánczky A, Győrffy B. Web-based survival analysis tool tailored for medical research (KMplot): development and implementation. J. Med. Internet Res. 2021;23:e27633. doi: 10.2196/27633. [PMC free article] [PubMed] [CrossRef[]

Articles from NPJ Genomic Medicine are provided here courtesy of Nature Publishing Group


Plaats een reactie ...

Reageer op "Enkele genmutaties bepalen behandelingsopties en overleving van patienten met operabele eierstokkanker blijkt uit genome studie bij duizenden patienten"


Gerelateerde artikelen
 

Gerelateerde artikelen

Enkele genmutaties bepalen >> Diagnose technieken eierstokkanker: >> Diagnose technieken: een nieuwe >> Diagnose technieken bij eierstokkanker: >> Diagnose technieken bij eierstokkanker: >> Diagnose technieken bij eierstokkanker: >> Diagnose technieken bij eierstokkanker: >>