CoChat
Sign Up
Cited by 97Ovarian cancer diagnosis and treatmentGene expression and cancer classificationBreast Cancer Treatment Studies

Gene Expression Analysis in Ovarian Cancer – Faults and Hints from DNA Microarray Study

Open access
Lisowska, Katarzyna Marta, Olbryt, Magdalena, Dudaladava, Volha, Pamuła-Piłat, Jolanta, Kujawa, Katarzyna, Grzybowska, Ewa, Jarząb, Michał, Student, Sebastian +3 more·2014·Frontiers in Oncology
DOI 10.3389/fonc.2014.00006PMC PMC3904181
Open this paper in CoChat — free accountOpen PDF

Abstract

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients' treatment; however, the results of such studies are poorly reproducible and critical analyses of these methods are rare. In this study, we examined global gene expression in 97 ovarian cancer samples. Also, validation of results by quantitative RT-PCR was performed on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients' prognosis. We found that histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints [tumor response to chemotherapy, overall survival, disease-free survival (DFS)] brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found to be important for DFS in the independent group, whereas in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worthy of further testing. Our results confirm that histological tumor type may be a strong confounding factor and we conclude that gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Among the reasons of poor reproducibility of statistical results may be the fact that despite relatively large patients' group, in some analyses one has to compare small and unequal classes of samples. In addition, arbitrarily performed division of samples into classes compared may not always reflect their true biological diversity. And finally, we think that clinical endpoints of the tumor probably depend on subtle changes in many and, possibly, alternative molecular pathways, and such changes may be difficult to demonstrate.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3389/fonc.2014.00006

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In a cohort of 75 ovarian cancer patients treated with a platinum-containing regimen, there was a trend towards higher SLFN11 expression in patients with CR vs. non-CR (p = 0.057).

    “Comparison of SLFN11 transcript levels in these tumors, while statistically limited by sample size, also demonstrated a trend towards higher levels of SLFN11 expression in patients with CR vs. non-CR (p = 0.057) (Fig 4B).”

    From Integrated pan-cancer gene expression and drug sensitivity analysis reveals SLFN11 mRNA as a solid tumor biomarker predictive of sensitivity to DNA-damaging chemotherapy (2019) · cites this paper as [15]

    The Materials and Methods (Clinical samples; page unavailable) describe an ovarian-cancer cohort treated with platinum-containing regimens, and the Results (Response to chemotherapy; page unavailable) classify patients by chemotherapy response. But the clinical analyses use 72 samples, not 75, and the paper does not report a SLFN11 comparison between CR and non-CR patients or p = 0.057. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 42

  1. [1]Golub TR Slonim DK Tamayo P Huard C Gaasenbeek M Mesirov JP Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science (1999) 286(5439): 531– 7 10.1126/science.286.5439.531 10521349 · DOI · Paper page
  2. [2]McCarthy JJ McLeod HL Ginsburg GS Genomic medicine: a decade of successes, challenges and opportunities. Sci Transl Med (2013) 5: 189sr4 10.1126/scitranslmed.3005785 23761042 · DOI
  3. [3]Welsh JB Zarrinkar PP Sapinoso LM Kern SG Behling CA Monk BJ Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer. Proc Natl Acad Sci U S A (2001) 98: 1176– 81 10.1073/pnas.98.3.1176 11158614 PMC14728 · DOI
  4. [4]Donninger H Bonome T Radonovich M Pise-Masison CA Brady J Shih JH Whole genome expression profiling of advance stage papillary serous ovarian cancer reveals activated pathways. Oncogene (2004) 23: 8065– 77 10.1038/sj.onc.1207959 15361855 · DOI
  5. [5]Lee BC Cha K Avraham S Avraham HK Microarray analysis of differentially expressed genes associated with human ovarian cancer. Int J Oncol (2004) 4: 847– 51 15010821
  6. [6]Lu KH Patterson AP Wang L Marquez RT Atkinson EN Baggerly KA Selection of potential markers for epithelial ovarian cancer with gene expression arrays and recursive descent partition analysis. Clin Cancer Res (2004) 10: 3291– 300 10.1158/1078-0432.CCR-03-0409 15161682 · DOI
  7. [7]Hibbs K Skubitz KM Pambuccian SE Casey RC Burleson KM Oegema TR Jr. Differential gene expression in ovarian carcinoma: identification of potential biomarkers. Am J Pathol (2004) 165: 397– 414 10.1016/S0002-9440(10)63306-8 15277215 PMC1618570 · DOI
  8. [8]Santin AD Zhan F Bellone S Palmieri M Cane S Bignotti E Gene expression profiles in primary ovarian serous papillary tumors and normal ovarian epithelium: identification of candidate molecular markers for ovarian cancer diagnosis and therapy. Int J Cancer (2004) 112: 14– 25 10.1002/ijc.20408 15305371 · DOI
  9. [9]Bignotti E Tassi RA Calza S Ravaggi A Romani C Rossi E Differential gene expression profiles between tumor biopsies and short-term primary cultures of ovarian serous carcinomas: identification of novel molecular biomarkers for early diagnosis and therapy. Gynecol Oncol (2006) 103: 405– 16 10.1016/j.ygyno.2006.03.056 16725184 · DOI
  10. [11]Le PC Ouellet V Madore J Hudson TJ Tonin PN Provencher DM From gene profiling to diagnostic markers: IL-18 and FGF-2 complement CA125 as serum-based markers in epithelial ovarian cancer. Int J Cancer (2006) 118: 1750– 8 10.1002/ijc.21521 16217764 · DOI
  11. [12]Pyle-Chenault RA Stolk JA Molesh DA Boyle-Harlan D McNeill PD Repasky EA VSGP/F-spondin: a new ovarian cancer marker. Tumour Biol (2005) 26: 245– 57 10.1159/000087379 16103746 · DOI
  12. [13]Mor G Visintin I Lai Y Zhao H Schwartz P Rutherford T Serum protein markers for early detection of ovarian cancer. Proc Natl Acad Sci U S A (2005) 102: 7677– 82 10.1073/pnas.0502178102 15890779 PMC1140439 · DOI
  13. [14]Peters DG Kudla DM Deloia JA Chu TJ Fairfull L Edwards RP Comparative gene expression analysis of ovarian carcinoma and normal ovarian epithelium by serial analysis of gene expression. Cancer Epidemiol Biomarkers Prev (2005) 14: 1717– 23 10.1158/1055-9965.EPI-04-0704 16030107 · DOI
  14. [15]Heinzelmann-Schwarz VA Gardiner-Garden M Henshall SM Scurry J Scolyer RA Davies MJ Overexpression of the cell adhesion molecules DDR1, Claudin 3, and Ep-CAM in metaplastic ovarian epithelium and ovarian cancer. Clin Cancer Res (2004) 10: 4427– 36 10.1158/1078-0432.CCR-04-0073 15240533 · DOI
  15. [16]Davidson B Zhang Z Kleinberg L Li M Florenes VA Wang TL Gene expression signatures differentiate ovarian/peritoneal serous carcinoma from diffuse malignant peritoneal mesothelioma. Clin Cancer Res (2006) 12: 5944– 50 10.1158/1078-0432.CCR-06-1059 17062665 · DOI
  16. [17]Kim JH Skates SJ Uede T Wong KK Schorge JO Feltmate CM Osteopontin as a potential diagnostic biomarker for ovarian cancer. JAMA (2002) 287: 1671– 9 10.1001/jama.287.13.1671 11926891 · DOI
  17. [18]Buehler M Tse B Leboucq A Jacob F Caduff R Fink D Meta-analysis of microarray data identifies GAS6 expression as an independent predictor of poor survival in ovarian cancer. Biomed Res Int (2013) 2013: 238284 10.1155/2013/238284 23878800 PMC3710590 · DOI
  18. [19]Chon HS Lancaster JM Microarray-based gene expression studies in ovarian cancer. Cancer Control (2011) 18(1): 8– 15 21273975
  19. [20]Tavassoli FA Devilee P Pathology and Genetics of Tumours of the Breast and Female Genital Organs World Health Organisation Classification of Tumours. Lyon: IARC Press (2003).
  20. [21]Barber HR Sommers SC Snyder R Kwon TH Histologic and nuclear grading and stromal reactions as indices for prognosis in ovarian cancer. Am J Obstet Gynecol (1975) 121: 795– 807 1092171
  21. [22]Rzepecka IK Szafron L Stys A Bujko M Plisiecka-Halasa J Madry R High frequency of allelic loss at the BRCA1 locus in ovarian cancers: clinicopathologic and molecular associations. Cancer Genet (2012) 205(3): 94– 100 10.1016/j.cancergen.2011.12.005 22469508 · DOI
  22. [23]Kupryjanczyk J Kraszewska E Ziolkowska-Seta I Madry R Timorek A Markowska J TP53 status and taxane-platinum versus platinum-based therapy in ovarian cancer patients: a non-randomized retrospective study. BMC Cancer (2008) 29(8): 27 10.1186/1471-2407-8-27 18230133 PMC2268700 · DOI
  23. [24]Lisowska KM Dudaladava V Jarzab M Huzarski T Chmielik E Stobiecka E BRCA1-related gene signature in breast cancer: the role of ER status and molecular type. Front Biosci (Elite Ed) (2011) 3: 125– 36 10.2741/e227 21196292 · DOI
  24. [25]Goeman JJ van de Geer SA de Kort F van Houwelingen HC A global test for groups of genes: testing association with a clinical outcome. Bioinformatics (2004) 20: 93– 9 10.1093/bioinformatics/btg382 14693814 · DOI
  25. [26]Berchuck A Iversen ES Lancaster JM Dressman HK West M Nevins JR Prediction of optimal versus suboptimal cytoreduction of advanced-stage serous ovarian cancer with the use of microarrays. Am J Obstet Gynecol (2004) 190: 910– 25 10.1016/j.ajog.2004.02.005 15118612 · DOI
  26. [27]Byrski T Dent R Blecharz P Foszczynska-Kloda M Gronwald J Huzarski T Results of a phase II open-label, non-randomized trial of cisplatin chemotherapy in patients with BRCA1-positive metastatic breast cancer. Breast Cancer Res (2012) 14(4): R110 10.1186/bcr3231 22817698 PMC3680929 · DOI
  27. [28]Kurman RJ Shih IeM Pathogenesis of ovarian cancer: lessons from morphology and molecular biology and their clinical implications. Int J Gynecol Pathol (2008) 27(2): 151– 60 10.1097/PGP.0b013e318161e4f5 18317228 PMC2794425 · DOI
  28. [29]Vang R Shih IeM Kurman RJ Ovarian low-grade and high-grade serous carcinoma: pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems. Adv Anat Pathol (2009) 16(5): 267– 82 10.1097/PAP.0b013e3181b4fffa 19700937 PMC2745605 · DOI
  29. [30]Dubeau L The cell of origin of ovarian epithelial tumors and the ovarian surface epithelium dogma: does the emperor have no clothes? Gynecol Oncol (1999) 72(3): 437– 42 10.1006/gyno.1998.5275 10053122 · DOI
  30. [31]Kurman RJ Shih IeM The origin and pathogenesis of epithelial ovarian cancer: a proposed unifying theory. Am J Surg Pathol (2010) 34(3): 433– 43 10.1097/PAS.0b013e3181cf3d79 20154587 PMC2841791 · DOI
  31. [32]Kuhn E Kurman RJ Shih IM Ovarian cancer is an imported disease: fact or fiction? Curr Obstet Gynecol Rep (2012) 1(1): 1– 9 10.1007/s13669-011-0004-1 22506137 PMC3322388 · DOI
  32. [33]Marquez RT Baggerly KA Patterson AP Liu J Broaddus R Frumovitz M Patterns of gene expression in different histotypes of epithelial ovarian cancer correlate with those in normal fallopian tube, endometrium, and colon. Clin Cancer Res (2005) 11: 6116– 26 10.1158/1078-0432.CCR-04-2509 16144910 · DOI
  33. [34]Schwartz DR Kardia SL Shedden KA Kuick R Michailidis G Taylor JM Gene expression in ovarian cancer reflects both morphology and biological behavior, distinguishing clear cell from other poor-prognosis ovarian carcinomas. Cancer Res (2002) 62: 4722– 9 12183431
  34. [35]Schaner ME Ross DT Ciaravino G Sorlie T Troyanskaya O Diehn M Gene expression patterns in ovarian carcinomas. Mol Biol Cell (2003) 14: 4376– 86 10.1091/mbc.E03-05-0279 12960427 PMC266758 · DOI
  35. [36]Santin AD Zhan F Bellone S Palmieri M Cane S Gokden M Discrimination between uterine serous papillary carcinomas and ovarian serous papillary tumours by gene expression profiling. Br J Cancer (2004) 90: 1814– 24 10.1038/sj.bjc.6601791 15208622 PMC2409747 · DOI
  36. [37]Shedden KA Kshirsagar MP Schwartz DR Wu R Yu H Misek DE Histologic type, organ of origin, and Wnt pathway status: effect on gene expression in ovarian and uterine carcinomas. Clin Cancer Res (2005) 11: 2123– 31 10.1158/1078-0432.CCR-04-2061 15788657 · DOI
  37. [38]Zorn KK Bonome T Gangi L Chandramouli GV Awtrey CS Gardner GJ Gene expression profiles of serous, endometrioid, and clear cell subtypes of ovarian and endometrial cancer. Clin Cancer Res (2005) 11: 6422– 30 10.1158/1078-0432.CCR-05-0508 16166416 · DOI
  38. [39]Wamunyokoli FW Bonome T Lee JY Feltmate CM Welch WR Radonovich M Expression profiling of mucinous tumors of the ovary identifies genes of clinicopathologic importance. Clin Cancer Res (2006) 12: 690– 700 10.1158/1078-0432.CCR-05-1110 16467078 · DOI
  39. [40]Heinzelmann-Schwarz VA Gardiner-Garden M Henshall SM Scurry JP Scolyer RA Smith AN A distinct molecular profile associated with mucinous epithelial ovarian cancer. Br J Cancer (2006) 94: 904– 13 10.1038/sj.bjc.6603003 16508639 PMC2361366 · DOI
  40. [42]Zhang B Cai FF Zhong XY An overview of biomarkers for the ovarian cancer diagnosis. Eur J Obstet Gynecol Reprod Biol (2011) 158(2): 119– 23 10.1016/j.ejogrb.2011.04.023 21632171 · DOI
  41. [43]Logarinho E Maffini S Barisic M Marques A Toso A Meraldi P CLASPs prevent irreversible multipolarity by ensuring spindle-pole resistance to traction forces during chromosome alignment. Nat Cell Biol (2012) 14(3): 295– 303 10.1038/ncb2423 22307330 · DOI
  42. [44]Patel K Nogales E Heald R Multiple domains of human CLASP contribute to microtubule dynamics and organization in vitro and in Xenopus egg extracts. Cytoskeleton (Hoboken) (2012) 69(3): 155– 65 10.1002/cm.21005 22278908 PMC3315288 · DOI

Cited by

Sorted by citations

Authors
Lisowska, K. M., Olbryt, M., Dudaladava, V., Pamuła-Piłat, J., Kujawa, K., Grzybowska, E., Jarząb, M., Student, S., Rzepecka, I. K., Jarząb, B., & Kupryjańczyk, J.
Affiliations
  • The Maria Sklodowska-Curie National Research Institute of Oncology (PL)
  • Grodno State Medical University (BY)
  • Silesian University of Technology (PL)
Corresponding author
Lisowska, Katarzyna Marta
ORCID
Venue
Frontiers in Oncology
Publisher
Frontiers Media SA
Published
2014
Volume
4
Pages
6-6
ISSN
2234-943X (ISSN-L)
DOI
10.3389/fonc.2014.00006
PMC
PMC3904181
OpenAlex
W2078344435
Cited by
97
References
2
Citations by year
2026: 8 · 2025: 4 · 2024: 5 · 2023: 5 · 2022: 9 · 2021: 9 · 2020: 15 · 2019: 15 · 2018: 9 · 2017: 5 · 2016: 6 · 2015: 7
FWCI
7.29
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Frontiers in Oncology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
European Social Fund
Topics
  • Health Sciences › Medicine › Reproductive Medicine › Ovarian cancer diagnosis and treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
ovarian cancer, global gene expression, DNA microarrays, reproducibility, biomarkers, chemoresistance, tumor histological type, CLASP1, BRCA1 mutation, prognosis, disease-free survival, serous tumors, undifferentiated tumors, confounding factors

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review