Article Data

  • Views 552
  • Dowloads 142

Reviews

Open Access

The prognostic role of circulating tumor cells and disseminated tumor cells in patients with ovarian cancer: a systematic review and meta-analysis

  • C. Zeng1
  • X.Q. Zhang1
  • W.D. Fan1,*,
  • T. Ting2

1Department of Oncology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing

2Department of physiology, Chongqing Medical University, Chongqing (China)

DOI: 10.12892/ejgo3396.2017 Vol.38,Issue 4,August 2017 pp.504-510

Published: 10 August 2017

*Corresponding Author(s): W.D. Fan E-mail: weidongfan2015@126.com

Abstract

Background: Observational studies have demonstrated an association between circulating tumor cells (CTCs) or disseminated tumor cells (DTCs) expression levels and clinical outcomes in patients with ovarian cancer, The purpose of this study was to evaluate the correlation between survival outcome and CTCs or DTCs counts in patients with ovarian cancer. Materials and Methods: A literature search was conducted among PubMed, Embase, and Cochrane library from inception to April 2015. Studies’ quality was assessed by Newcastle-Ottawa Scale, the meta-analysis was performed using hazard ratios (HRs), odds ratios (ORs), and 95% confidence intervals (CIs) as effect measures. Subgroup and sensitivity analyses were also performed. Results: Fourteen eligible studies were included. The estimated HRs for the effect of CTCs/DTCs on overall survival (OS) and relapse-free survival (RFS) or disease-free survival (DFS) or progression-free survival (PFS) were 1.91 (1.53, 2.39) and 1.83 (1.47, 2.27), respectively. It did not show significant difference (OR=1.59; 95% CI [0.79, 3.20], p = 0.20) between the detection of CTCs/DTCs and International Federation of Gynecology and Obstetrics (FIGO) stage. Additionally, subgroup analyses indicated strong prognostic powers of CTCs and DTCs, irrespective of methodological, detection time, and sample size differences of the studies. Conclusion: This meta-analysis showed that CTCs and DTCs can predict the survival of ovarian cancer patients. Future studies are needed to determine the best sampling time points and detection methods in these patients.

Keywords

Ovarian cancer; Circulating tumor cells; Disseminated tumor cells; Prognostic; Meta-analysis.

Cite and Share

C. Zeng,X.Q. Zhang,W.D. Fan,T. Ting. The prognostic role of circulating tumor cells and disseminated tumor cells in patients with ovarian cancer: a systematic review and meta-analysis. European Journal of Gynaecological Oncology. 2017. 38(4);504-510.

References

[1] Siegel R.L., Miller K.D., Jemal A.: “Cancer statistics, 2015”. CA. Cancer. J. Clin., 2015, 65, 5.

[2] Badgwell D., Bast R.C.Jr.: “Early detection of ovarian cancer”. Dis. Markers, 2007, 23, 397.

[3] Ashworth T.R: “A case of cancer in which cells similar to those in the tumours were seen in the blood after death”. Aust. Med. J., 1869, 14, 146.

[4] Allard W.J., Matera J., Miller M.C., Repollet M., Connelly M.C., Rao C., et al.: “Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases”. Clin. Cancer Res., 2004, 10, 6897.

[5] Cain J.M., Ellis G.K., Collins C., Greer B.E., Tamimi H.K., Figge D.C., et al.: “Bone marrow involvement in epithelial ovarian cancer by immunocytochemical assessment”. Gynecol. Oncol., 1990, 38, 442.

[6] Sastre J., Maestro M.L., Gomez-Espana A., Rivera F., Valladares M., Massuti B., et al.: “Circulating tumor cell count is a prognostic factor in metastatic colorectal cancer patients receiving first-line chemotherapy plus bevacizumab: a Spanish Cooperative Group for the Treatment of Digestive Tumors study”. Oncologist, 2012, 17, 947.

[7] Krebs M.G., Sloane R., Priest L., Lancashire L., Hou J.M., Greystoke A., et al.: “Evaluation and prognostic significance of circulating tumor cells in patients with non-small-cell lung cancer”. J. Clin. Oncol., 2011, 29, 1556.

[8] Cui L., Lou Y., Zhang X., Zhou H., Deng H., Song H., et al.: “Detection of circulating tumor cells in peripheral blood from patients with gastric cancer using piRNAs as markers”. Clin. Biochem., 2011, 44, 1050.

[9] Braun S., Vogl F.D., Naume B., Janni W., Osborne M.P., Coombes R.C., et al.: “A pooled analysis of bone marrow micrometastasis in breast cancer”. N. Engl. J. Med., 2005, 353, 793.

[10] GA Wells BS, D. O'Connell, J. Peterson, V. Welch, M. Losos, P. Tugwell: “The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Laboratory Investigation. 2000”. Available at: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp".

[11] Parmar M.K., Torri V., Stewart L.: “Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints”. Stat. Med., 1998, 17, 2815.

[12] Tierney J.F., Stewart L.A., Ghersi D., Burdett S., Sydes M.R.: “Practical methods for incorporating summary time-to-event data into meta-analysis”. Trials, 2007, 8, 16.

[13] Begg C.B., Mazumdar M.: “Operating characteristics of a rank correlation test for publication bias”. Biometrics, 1994, 50, 1088.

[14] Egger M., Davey S.G., Schneider M., Minder C.: “Bias in metaanalysis detected by a simple, graphical test”. BMJ, 1997, 315, 629.

[15] Aktas B., Kasimir-Bauer S., Heubner M., Kimmig R., Wimberger P.: “Molecular profiling and prognostic relevance of circulating tumor cells in the blood of ovarian cancer patients at primary diagnosis and after platinum-based chemotherapy”., Int. J. Gynecol. Cancer., 2011, 21, 822-830.

[16] Banys M., Solomayer E.F., Becker S., Krawczyk N., Gardanis K., Staebler A., et al.: “Disseminated tumor cells in bone marrow may affect prognosis of patients with gynecologic malignancies”. Int. J. Gynecol. Cancer, 2009, 19, 948.

[17] Braun S., Schindlbeck C., Hepp F., Janni W., Kentenich C., Riethmuller G., et al.: “Occult tumor cells in bone marrow of patients with locoregionally restricted ovarian cancer predict early distant metastatic relapse”. J. Clin Oncol., 2001, 19, 368.

[18] Fan T., Zhao Q., Chen J.J., Chen W.T., Pearl M.L.: “Clinical significance of circulating tumor cells detected by an invasion assay in peripheral blood of patients with ovarian cancer”. Gynecol. Oncol., 2009, 112, 185.

[19] Fehm T., Banys M., Rack B., Janni W., Marth C., Blassl C., et al.: “Pooled analysis of the prognostic relevance of disseminated tumor cells in the bone marrow of patients with ovarian cancer”. Int. J. Gynecol Cancer, 2013, 23, 839.

[20] Judson P.L., Geller M.A., Bliss R.L., Boente M.P., Downs L.S. Jr., Argenta P.A., et al.: “Preoperative detection of peripherally circulating cancer cells and its prognostic significance in ovarian cancer”. Gynecol. Oncol., 2003, 91, 389.

[21] Marth C., Kisic J., Kaern J., Trope C., Fodstad O.: “Circulating tumor cells in the peripheral blood and bone marrow of patients with ovarian carcinoma do not predict prognosis”. Cancer, 2002, 94, 707.

[22] Poveda A., Kaye S.B., McCormack R., Wang S., Parekh T., Ricci D., et al.: “Circulating tumor cells predict progression free survival and overall survival in patients with relapsed/recurrent advanced ovarian cancer”. Gynecol. Oncol., 2011, 122, 567.

[23] Liu J.F., Kindelberger D., Doyle C., Lowe A., Barry W.T., Matulonis U.A.: “Predictive value of circulating tumor cells (CTCs) in newly-diagnosed and recurrent ovarian cancer patients”. Gynecol. Oncol., 2013, 131, 352.

[24] Pearl M.L., Zhao Q., Yang J., Dong H., Tulley S., Zhang Q., et al.: “Prognostic analysis of invasive circulating tumor cells (iCTCs) in epithelial ovarian cancer”. Gynecol. Oncol., 2014, 134, 581.

[25] Schindlbeck C., Hantschmann P., Zerzer M., Jahns B., Rjosk D., Janni W., et al.: “Prognostic impact of KI67, p53, human epithelial growth factor receptor 2, topoisomerase II(alpha), epidermal growth factor receptor, and nm23 expression of ovarian carcinomas and disseminated tumor cells in the bone marrow”. Int. J. Gynecol. Cancer, 2007, 17, 1047.

[26] Wimberger P., Heubner M., Kimmig R., Kasimir-Bauer S.: “Impact of disseminated tumor cells in bone marrow on clinical outcome in ovarian cancer patients”. Arch. Gynecol. Obstet., 2010, 282, 203.

[27] Wimberger P., Heubner M., Otterbach F., Fehm T., Kimmig R., Kasimir-Bauer S.: “Influence of platinum-based chemotherapy on disseminated tumor cells in blood and bone marrow of patients with ovarian cancer”. Gynecol. Oncol., 2007, 107, 331.

[28] Obermayr E., Castillo-Tong D.C., Pils D., Speiser P., Braicu I., Van Gorp T., et al.: “Molecular characterization of circulating tumor cells in patients with ovarian cancer improves their prognostic significance - A study of the OVCAD consortium”. Gynecol. Oncol., 2013, 128, 15.

[29] Ma X., Xiao Z., Li X., Wang F., Zhang J., Zhou R., et al.: “Prognostic role of circulating tumor cells and disseminated tumor cells in patients with prostate cancer: a systematic review and meta-analysis”. Tumour. Biol., 2014, 35, 5551.

[30] Zhao S., Liu Y., Zhang Q., Li H., Zhang M., Ma W., et al.: “The prognostic role of circulating tumor cells (CTCs) detected by RT-PCR in breast cancer: a meta-analysis of published literature”. Breast Cancer Res. Treat., 2011, 130, 809-816.

[31] Huang X., Gao P., Song Y., Sun J., Chen X., Zhao J., et al.: “Relationship between circulating tumor cells and tumor response in colorectal cancer patients treated with chemotherapy: a meta-analysis”. BMC Cancer, 2014, 14, 976.

[32] Mocellin S., Hoon D., Ambrosi A., Nitti D., Rossi C.R.: “The prognostic value of circulating tumor cells in patients with melanoma: a systematic review and meta-analysis”. Clin. Cancer. Res., 2006, 12, 4605.

[33] Nagrath S., Sequist L.V., Maheswaran S., Bell D.W., Irimia D., Ulkus L., et al.: “Isolation of rare circulating tumour cells in cancer patients by microchip technology”. Nature, 2007, 450, 1235.

Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,500 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Biological Abstracts Easily discover critical journal coverage of the life sciences with Biological Abstracts, produced by the Web of Science Group, with topics ranging from botany to microbiology to pharmacology. Including BIOSIS indexing and MeSH terms, specialized indexing in Biological Abstracts helps you to discover more accurate, context-sensitive results.

Google Scholar Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.

JournalSeek Genamics JournalSeek is the largest completely categorized database of freely available journal information available on the internet. The database presently contains 39226 titles. Journal information includes the description (aims and scope), journal abbreviation, journal homepage link, subject category and ISSN.

Current Contents - Clinical Medicine Current Contents - Clinical Medicine provides easy access to complete tables of contents, abstracts, bibliographic information and all other significant items in recently published issues from over 1,000 leading journals in clinical medicine.

BIOSIS Previews BIOSIS Previews is an English-language, bibliographic database service, with abstracts and citation indexing. It is part of Clarivate Analytics Web of Science suite. BIOSIS Previews indexes data from 1926 to the present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Submission Turnaround Time

Conferences

Top