Literature DB >> 26098665

Prognostic Value of Circulating Tumor Cells in Ovarian Cancer: A Meta-Analysis.

Yunlan Zhou1, Bingxian Bian1, Xiangliang Yuan1, Guohua Xie1, Yanhui Ma1, Lisong Shen1.   

Abstract

BACKGROUND: The prognostic value of circulating tumor cells (CTCs) in ovarian cancer has been investigated in previous studies, but the results are controversial. Therefore we performed a meta-analysis to systematically review these data and evaluate the value of CTCs in ovarian cancer.
MATERIALS AND METHODS: A literary search for relevant studies was performed on Embase, Medline and Web of Science databases. Then pooled hazard ratios (HRs) for survival with 95% confidence intervals (CIs), subgroup analyses, sensitivity analyses, meta-regression analyses and publication bias were conducted.
RESULTS: This meta-analysis is based on 11 publications and comprises a total of 1129 patients. The prognostic value of the CTC status was significant in overall survival (OS) (HR, 1.61;95% CI,1.22-2.13) and progression-free survival (PFS)/disease-free survival (DFS) (HR, 1.44; 95%CI, 1.18-1.75). Furthermore, subgroup analysis revealed that the value of CTC status in OS was significant in "RT-PCR" subgroup (HR, 2.02; 95% CI, 1.34-3.03), whereas it was not significant in "CellSearch" subgroup (HR, 1.15; 95% CI 0.45-2.92) and "other ICC" subgroup (HR, 1.09; 95% CI 0.62-1.90). The presence of CTC was also associated with an increased CA-125 (OR, 4.07; 95%CI, 1.87-8.85).
CONCLUSION: Our study demonstrates that CTC status is associated with OS and PFS/DFS in ovarian cancer.

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Year:  2015        PMID: 26098665      PMCID: PMC4476582          DOI: 10.1371/journal.pone.0130873

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Ovarian cancer is the second leading cause of death among gynecologic malignancies in the world [1] owing to the fact that a majority of patients are diagnosed in late stages of the disease [2]. In such a setting, identifying prognostic indicators for patients with ovarian cancer is crucial. CA-125 is a frequently used biomarker in ovarian cancer, but some non-malignant conditions also cause elevated serum CA-125 concentrations [3]. Thus additional prognostic markers are urgently needed for ovarian cancer. CTCs are tumor cells that have shed into bloodstream from the primary tumors, recurrences, or metastases, and possess antigenic and genetic tumor-specific characteristics. Two major detection methods have been used to identify CTC, including immunocytochemistry (ICC), reverse-transcriptase polymerase chain reaction (RT-PCR). US Food and Drug Administration (FDA) only approved the CellSearch system for clinical use currently, which enriches and detects CTC of epithelial origin by means of ICC methods. There is no published polymorphism studies associated with CTCs in ovarian cancer in previous studies. CTCs have been demonstrated to have prognostic value among patients with breast, colorectal, gastric, lung and pancreatic cancers in previous meta-analyses [4-8]. However, the value of CTCs in ovarian cancer still remains controversial. Some studies did not observe any correlation between CTC status and prognosis. In contrast, other studies revealed association between CTC status and prognosis. After considering the conflicting results from previous studies, we performed the first meta-analysis to investigate the prognostic value of CTCs on OS and DFS/PFS in patients with ovarian cancer confirmed by histopathologic examinations. Furthermore, subgroup analyses were conducted to evaluate whether the detection method and treatment methods influence the prognostic value of CTCs.

Methods

Search strategy

A literary search for potential studies was performed on Embase (from 1974 to November 1, 2014), Medline (from 1966 to November 1, 2014) and Web of Science databases including Science Citation Index Expanded, Social Sciences Citation Index, Arts & Humanities Citation Index, Conference Proceedings Citation Index—Science, Conference Proceedings Citation Index—Social Science & Humanities, Current Chemical Reactions (from 1985 to November 1, 2014). Search term combinations were”ovarian cancer,”“ovary cancer,”“ovarian carcinoma,”“ovary carcinoma,”“ovarium carcinoma,”“circulating tumor cells,”“circulating tumor cell,”“circulating cancer cells,”“circulating cancer cell,”“CTCs” and”CTC” in title/abstract. Relevant articles were also screened manually to prevent omission of any research. If the data in studies were insufficient, we contacted authors by e-mail. And we subsequently excluded the studies when authors couldn’t be contacted.

Selection criteria and quality assessment

Studies were selected from initial search using following inclusion criteria: (1) survival data were analyzed for the prognostic value of CTCs in ovarian cancer; (2) sufficient data were provided to determine HR with 95% confidence interval (CI); (3) when the same study population was published at several reports, only the most complete one was selected for our meta-analysis; (4) more than 30 patients were enrolled in each study; (5) reports in English were eligible. Studies with reviews, letters, editorials, abstracts, comments and case reports were also excluded. Two investigators independently evaluated the quality of included studies using the Newcastle-Ottawa Scale (NOS). A score of zero points meant the study had the worst quality, whereas a score of nine points meant the study had the best quality. When disagreements occured, they were solved by discussion. We also conducted subgroup and sensitivity analyses to assess study quality.

Data extraction

Following details were extracted from included study: name of first author, year of publication, patients’ country, number of patients, disease stage, CTC detection methods, target antigen/target gene, cutoff defining positivity of CTC, HRs with 95% CIs for PFS, DFS, OS. HRs and 95% CIs were extracted from multivariable analyses. When they were not directly extracted from the original study, they were calculated by the method of Tierney et al.[9]. When more than 1 blood sample per patient was detected at different time points such as baseline, mid-therapy and post-therapy, we only investigated baseline value of CTC in ovarian cancer.

Statistical analysis

As the detection methods of CTCs, and detection rates of CTC in patients were very different across studies, a random effect model was used for calculating the pooled HR [10,11]. In order to evaluate potential sources of heterogeneity, subgroup analyses were performed by detection methods and treatment methods. Stratified analysis with respect to population was not conducted because most of the included studies were from Caucasian countries. Meta-regression analyses were also used to evaluate potential causes of heterogeneity (a p-value<0.05 was considered statistically significant). To evaluate the influence of single studies on the pooled HRs, we performed a sensitivity analysis by estimating the average HR in the absence of each study. To investigate whether a publication bias might have affected the validity of the estimates [12], we performed Begg’s funnel plot and Egger’s linear regression test (a p-value<0.05 was considered statistically significant). STATA version 12.0 was performed to process all of the data.

Results

Characteristics of identified studies

The study followed the criterions for systematic review and meta-analysis of genetic association studies (S1 and S2 Checklists). The flowchart of search strategy for articles is presented in Fig 1 and S1 Table. 295 articles related to the keywords were initially reviewed. Of these articles, 280 were excluded after screening of titles, keywords and abstracts because they were obviously irrelevant studies, duplicates, reviews, abstracts and comments. Another 4 articles were excluded after reviewing the full texts because of insufficient data, multiple publications and small sample size, leaving 11 eligible studies [13-23]. published between 2002 and 2014. As shown in Table 1, a total of 1129 patients (ranging from 30 to 216 for individual study) were included in our meta-analysis. The detection rate of CTCs in these patients ranged from 12% to 83%. Most of studies were from Caucasian countries [13-16,18,20-23]. One study was from Asian countries [17] and the other one was from multi-country[19]. Methods used to detect CTCs were CellSearch system, other ICC and the RT-PCR. 64 women with cancer were included in Judson’s study [15], but only 51 patients with new diagnosis were included in the Kaplan–Meier distributions. 60 patients were enrolled in Behbakh’s study, whereas only 43 patients were included in the Kaplan–Meier PFS distributions for pre-treatment CTCs [14]. HRs with 95% CIs were directly extracted from original articles in three studies [17,19,23]. HRs with 95% CIs were not directly reported in eight studies [13-16,18,20-22] and calculated from Kaplan–Meier curves suggested by Tierney et al.[9]. Quality assessment of included studies is shown in Table 2.
Fig 1

PRISMA flow Chart of literature search and study selection.

Table 1

Main characteristics of the eligible studies.

StudyNo. of patientsTumor stage a Detection MethodTarget antigen/target geneDetection rate,%Cutoff of CTCs
Marth 2002[13] (Norway)90Ⅰ-Ⅳ (77.8)Other ICCPancarcinoma/epithelial glycoprotein12%
Judson 2003[15] (America)51Ⅰ-Ⅳ (NR)Other ICCKeratin 8 and 18,TFS-2,CK-7,CK-20,EGFR21.6%
Fan 2009[20] (America)66Ⅰ-Ⅳ (78.8)Other ICCCAM,Epi34.8%1 CTC/3mL
Poveda 2011[19] (Multi-country)216NR (NR)CellsearchCK,EpCAM14.4%2 CTC/7.5 mL
Behbakht 2011[14] (America)43NR (NR)CellsearchCK,EpCAM44%2 CTC/7.5 mL
Aktas 2011[21] (Germany)122Ⅰ-Ⅳ (NR)RT-PCREpCAM, MUC-1, HER2, CA 12519%
Obermayr 2013[22] (Europe)200Ⅱ-Ⅳ (96)RT-PCRPPIC17%
Liu 2013[16] (America)30Ⅰ-Ⅳ (100)CellsearchCK,EpCAM60%2 CTC/7.5 mL
Sang 2014[17] (China)80Ⅰ-Ⅳ (88.8)RT-PCRMAGE-A47.5%
Pearl 2014[18] (America)88Ⅰ-Ⅳ (80.7)Other ICCEpi,HL83.0%5 CTC/1mL
Kuhlmann 2014[23] (Germany)143Ⅰ-Ⅲ (52)RT-PCREpCAM, MUC1, MUC1614%

aTumor stage and percentage of advanced stage(%); NR, Not Reported; CTCs, circulating tumor cells; ICC, immunocytochemistry; RT-PCR, reverse-transcriptase polymerase chain reaction.

Table 2

Main results.

AuthorOutcomeHR95%CINOS score
Marth 2002OS1.990.23–17.166
PFS2.190.84–5.74
Judson 2003OS2.140.37–12.297
PFS1.450.55–3.83
Fan 2009OS0.890.40–1.957
DFS1.440.78–2.64
Poveda 2011OS1.540.93–2.547
PFS1.580.99–2.53
Behbakht 2011PFS1.610.79–3.296
Aktas 2011OS4.561.94–10.736
PFS1.580.86–2.88
Obermayr 2013OS2.041.17–3.547
DFS1.350.90–2.03
Liu 2013OS0.530.12–2.407
PFS0.710.30–1.69
Sang 2014OS1.400.87–2.276
Pearl 2014OS1.060.41–2.736
PFS1.210.49–2.97
Kuhlmann 2014OS1.851.03–3.327
PFS1.50.81–2.79

HR, hazard ratio; CI, confidence intervals; NOS, Newcastle-Ottawa Scale; OS, overall survival; PFS,progression-free survival; DFS,disease-free survival.

aTumor stage and percentage of advanced stage(%); NR, Not Reported; CTCs, circulating tumor cells; ICC, immunocytochemistry; RT-PCR, reverse-transcriptase polymerase chain reaction. HR, hazard ratio; CI, confidence intervals; NOS, Newcastle-Ottawa Scale; OS, overall survival; PFS,progression-free survival; DFS,disease-free survival.

CTC and OS

Pooled HR

HRs for PFS/DFS were available in ten studies[13,15-23]. The pooled HR showed a significantly increased risk of mortality in patients with CTC positive group (HR, 1.61; 95% CI,1.22–2.13; Fig 2). Heterogeneity among studies was not noted (P = 0.207 and I2 = 25.7%).
Fig 2

Forest plot showing the meta-analysis of hazard ratio estimates for OS in overall patients.

OS = overall survival.

Forest plot showing the meta-analysis of hazard ratio estimates for OS in overall patients.

OS = overall survival.

Subgroup analyses

When it comes to the CTC detection methods, patients present with CTC showed a significantly increased risk of mortality in the "RT-PCR" subgroup (HR, 2.02; 95% CI, 1.34–3.03; Fig 3), whereas it was not significant in the "CellSearch" subgroup (HR, 1.15; 95% CI 0.45–2.92) and "other ICC" subgroup (HR, 1.09; 95% CI 0.62–1.90). Statistical heterogeneity was not found in "RT-PCR" subgroup, "CellSearch" subgroup and "other ICC" subgroup (I2 = 46.7%, P = 0.131; I2 = 42.9%, P = 0.186 and I2 = 0.0%, P = 0.771, respectively). In addition, we also investigated the prognostic value of CTCs for patients who received different treatment methods. Patients received chemotherapy alone in two studies and surgery (surgery alone or surgery and chemotherapy) in the other eight studies. The results showed the prognostic value of CTCs for OS was significant in the "Surgery" subgroup (HR, 1.70; 95% CI, 1.23–2.36; Fig 4) and it was not significant in the "Chemotherapy" subgroup (HR, 1.15; 95% CI 0.45–2.92). Statistical heterogeneity was not found in both "Surgery" subgroup and "Chemotherapy" subgroup (I2 = 28.8%, P = 0.199 and I2 = 42.9%, P = 0.186, respectively).
Fig 3

Forest plot showing the meta-analysis of hazard ratio estimates for OS in “Other ICC” subgroup, “Cellsearch” subgroup and “RT-PCR” subgroup.

Subgroup analysis based on different CTC detection methods. OS = overall survival; ICC = immunocytochemistry; RT-PCR = reverse-transcriptase polymerase chain reaction; CTC = circulating tumor cell.

Fig 4

Forest plot showing the meta-analysis of hazard ratio estimates for OS in “Surgery” subgroup and “Chemotherapy” subgroup.

Subgroup analysis based on different treatment methods. OS = overall survival.

Forest plot showing the meta-analysis of hazard ratio estimates for OS in “Other ICC” subgroup, “Cellsearch” subgroup and “RT-PCR” subgroup.

Subgroup analysis based on different CTC detection methods. OS = overall survival; ICC = immunocytochemistry; RT-PCR = reverse-transcriptase polymerase chain reaction; CTC = circulating tumor cell.

Forest plot showing the meta-analysis of hazard ratio estimates for OS in “Surgery” subgroup and “Chemotherapy” subgroup.

Subgroup analysis based on different treatment methods. OS = overall survival.

CTC and PFS/DFS

HRs for PFS/DFS were available in ten studies [13-16,18-23]. The estimated pooled HR showed an increased risk of disease progression in patients with CTC positive group (HR, 1.44; 95%CI, 1.18–1.75; Fig 5). The heterogeneity among studies was not noted (P = 0.918, I2 = 0.0%).
Fig 5

Forest plot showing the meta-analysis of hazard ratio estimates for DFS/PFS in overall patients.

DFS = disease-free survival; PFS = progression-free survival.

Forest plot showing the meta-analysis of hazard ratio estimates for DFS/PFS in overall patients.

DFS = disease-free survival; PFS = progression-free survival.

Meta-regression analyses

We conducted the meta-regression analysis based on the following covariates: percentage of advanced stage (stage IV or stage III), detection method (ICC vs. RT-PCR), publication year, treatment type (Surgery vs. Chemotherapy) and sample size (> = 90 vs. <90). As shown in S2 Table, no significant association could be observed in percentage of advanced stage (p = 0.645), detection method (0.118), publication year (0.619), treatment type(0.469) and sample size (0.059).

CTC and CA-125

CA-125 is also a useful prognostic tumor marker for survival in ovarian cancer. Five studies reported data on correlation between the presence of CTC and elevated CA-125. Of these, one study [17] confirmed the correlation between CTC and CA-125. Conversely, four studies [18-20,22] suggested no correlation between CTC and CA-125. Pooled outcome from the five studies demonstrated a strong correlation between presence of CTC and increased CA-125 (OR, 4.07; 95%CI, 1.87–8.85; Fig 6).
Fig 6

Forest plots of the association between CTCs and CA-125.

CTCs = circulating tumor cells.

Forest plots of the association between CTCs and CA-125.

CTCs = circulating tumor cells.

Sensitivity analyses and publication bias

In order to evaluate the influence of single studies on the pooled HRs, we performed a sensitivity analysis by estimating the average HR in the absence of each study. The results indicated that no individual studies significantly influenced the pooled HRs (Fig 7). Begg’s funnel plot (P = 1, Fig 8) and Egger’s linear regression test (P = 0.806) did not show evidence for publication bias.
Fig 7

Sensitivity analysis for the pooled HRs in OS.

The analysis was conducted by estimating the average HR in the absence of each study. HRs = hazard ratios; OS = overall survival.

Fig 8

Begg’s funnel plots of the prognostic role of CTCs in OS.

CTCs = circulating tumor cells; OS = overall survival.

Sensitivity analysis for the pooled HRs in OS.

The analysis was conducted by estimating the average HR in the absence of each study. HRs = hazard ratios; OS = overall survival.

Begg’s funnel plots of the prognostic role of CTCs in OS.

CTCs = circulating tumor cells; OS = overall survival.

Discussion

Many studies have reported the prognostic value of CTCs in patients with ovarian cancer, and this is the first meta-analysis evaluating the value of CTCs in these patients. Overall, our results demonstrated that patients in CTC-positive group had a worse OS and PFS/DFS compared with CTC- negative group; moreover, the presence of CTCs was associated with elevated CA-125. Subgroup analysis showed that “RT-PCR” subgroup presented significant association between CTCs and OS, whereas it was not significant in the "CellSearch" subgroup and “Other ICC” subgroup. But the detection method didn’t influence HR estimates in the meta-regression (P = 0.118). Though the CellSearch system which uses EpCAM for cell isolation is the only CTC test approved by US FDA for clinical use currently, it has some limitations. EpCAM can be downregulated by cancer stem cells in the procedure of epithelial mesenchymal transition [24]. Thus this system suffers from relatively low sensitivity, additional innovative detection methods may reveal more tumor cells [25]. On the other hand, CellSearch system may also present poor specificity because of biologic nonspecificity [26]. Therefore the methodologies which do not use epithelial markers alone for cell isolation may be more likely to associate with OS according to our subgroup analysis. In addition, subgroup analysis based on treatment methods showed the prognostic value of CTCs for OS was significant in the "Surgery" subgroup, while it was not significant in the "Chemotherapy" subgroup. However, it is difficult to determine whether treatment methods influence the prognostic value of CTCs. The reason for the drawback is that there was a notable difference in timing for CTCs detection, response to treatment, chemotherapy regimens and operative plans. Further studies are required to investigate the prognostic relevant factor. To explore potential causes of heterogeneity, we performed meta-regression to evaluate whether percentage of advanced stage patients (stage IV or stage III) would influence the prognostic value of CTCs. No association could be observed (p = 0.645), which meant the prognostic value of CTCs was not associated with disease stage. Moreover, no significant association could be observed in publication year (0.619) treatment type (0.469) and sample size (0.059). Our meta-analysis also confirmed the presence of CTC was closely associated with elevated CA-125, both of which are known to be prognostic tool in ovarian cancer. Our study has some limitations. First, CTC detection methods were different among included studies, which may partly influence the significance in survival analyses. Second, there is no consensus on the optimal cutoff of CTCs for predicting the clinical outcome in ovarian cancer. The low cutoff of ≥2 CTC/7.5 ml of blood with the CellSearch system was used in three studies [14,16,19], and other studies used different cutoffs. Though Fan et al. showed higher CTC counts could reflect later stage disease and higher CA-125 levels [20], few trials had evaluated by the prognostic value of different numbers of enumerating CTCs in patients with ovarian cancer. Further studies are required to assess prognostic relevant CTC cutoff levels. Third, some studies included in the meta-analysis were small case-series, thus more large prospective studies should be performed. In conclusion, this meta-analysis indicates that CTC status is associated with OS and PFS/DFS in patients with ovarian cancer. To achieve clinical utility of CTCs in ovarian cancer, more large prospective studies should be conducted before CTC detection can be applied to clinical use as a prognostic indication.

PRISMA checklist.

(DOC) Click here for additional data file.

Meta-analysis on genetic association studies checklist.

(DOC) Click here for additional data file.

The excluded articles and the reasons for exclusion.

(DOC) Click here for additional data file.

Results of meta-regression analysis exploring source of heterogeneity with overall survival.

(DOC) Click here for additional data file.
  23 in total

1.  Phase II trial of the mTOR inhibitor, temsirolimus and evaluation of circulating tumor cells and tumor biomarkers in persistent and recurrent epithelial ovarian and primary peritoneal malignancies: a Gynecologic Oncology Group study.

Authors:  Kian Behbakht; Michael W Sill; Kathleen M Darcy; Stephen C Rubin; Robert S Mannel; Steven Waggoner; Russell J Schilder; Kathy Q Cai; Andrew K Godwin; R Katherine Alpaugh
Journal:  Gynecol Oncol       Date:  2011-07-12       Impact factor: 5.482

2.  Prognostic value of circulating tumor cells in patients with pancreatic cancer: a meta-analysis.

Authors:  Lu Han; Wei Chen; Qicheng Zhao
Journal:  Tumour Biol       Date:  2013-11-12

3.  Circulating tumor cells: not all detected cells are bad and not all bad cells are detected.

Authors:  Max S Wicha; Daniel F Hayes
Journal:  J Clin Oncol       Date:  2011-03-21       Impact factor: 44.544

Review 4.  Circulating tumor cells and prognosis of patients with resectable colorectal liver metastases or widespread metastatic colorectal cancer: a meta-analysis.

Authors:  Bas Groot Koerkamp; Nuh N Rahbari; Markus W Büchler; Moritz Koch; Jürgen Weitz
Journal:  Ann Surg Oncol       Date:  2013-03-02       Impact factor: 5.344

5.  Predictive value of circulating tumor cells (CTCs) in newly-diagnosed and recurrent ovarian cancer patients.

Authors:  Joyce F Liu; David Kindelberger; Courtney Doyle; Alarice Lowe; William T Barry; Ursula A Matulonis
Journal:  Gynecol Oncol       Date:  2013-08-13       Impact factor: 5.482

6.  Circulating tumor cells in the peripheral blood and bone marrow of patients with ovarian carcinoma do not predict prognosis.

Authors:  Christian Marth; Jelena Kisic; Janne Kaern; Claes Tropé; Øystein Fodstad
Journal:  Cancer       Date:  2002-02-01       Impact factor: 6.860

7.  Prognostic analysis of invasive circulating tumor cells (iCTCs) in epithelial ovarian cancer.

Authors:  Michael L Pearl; Qiang Zhao; Jie Yang; Huan Dong; Shaun Tulley; Qiao Zhang; Marc Golightly; Stanley Zucker; Wen-Tien Chen
Journal:  Gynecol Oncol       Date:  2014-06-24       Impact factor: 5.482

Review 8.  Circulating tumor cells: approaches to isolation and characterization.

Authors:  Min Yu; Shannon Stott; Mehmet Toner; Shyamala Maheswaran; Daniel A Haber
Journal:  J Cell Biol       Date:  2011-02-07       Impact factor: 10.539

Review 9.  Progress and challenges in screening for early detection of ovarian cancer.

Authors:  Ian J Jacobs; Usha Menon
Journal:  Mol Cell Proteomics       Date:  2004-02-05       Impact factor: 5.911

10.  Practical methods for incorporating summary time-to-event data into meta-analysis.

Authors:  Jayne F Tierney; Lesley A Stewart; Davina Ghersi; Sarah Burdett; Matthew R Sydes
Journal:  Trials       Date:  2007-06-07       Impact factor: 2.279

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  21 in total

1.  Gene expression profiling of single circulating tumor cells in ovarian cancer - Establishment of a multi-marker gene panel.

Authors:  Christina Blassl; Jan Dominik Kuhlmann; Alessandra Webers; Pauline Wimberger; Tanja Fehm; Hans Neubauer
Journal:  Mol Oncol       Date:  2016-04-20       Impact factor: 6.603

2.  Establishment of an optimized CTC detection model consisting of EpCAM, MUC1 and WT1 in epithelial ovarian cancer and its correlation with clinical characteristics.

Authors:  Tongxia Wang; Yan Gao; Xi Wang; Junrui Tian; Yuan Li; Bo Yu; Cuiyu Huang; Hui Li; Huamao Liang; David M Irwin; Huanran Tan; Hongyan Guo
Journal:  Chin J Cancer Res       Date:  2022-04-30       Impact factor: 4.026

Review 3.  EpCAM-based assays for epithelial tumor cell detection in cerebrospinal fluid.

Authors:  Mark T J van Bussel; Dick Pluim; Mijke Bol; Jos H Beijnen; Jan H M Schellens; Dieta Brandsma
Journal:  J Neurooncol       Date:  2017-11-30       Impact factor: 4.130

Review 4.  Circulating tumor cells as trigger to hematogenous spreads and potential biomarkers to predict the prognosis in ovarian cancer.

Authors:  Maria Luisa Gasparri; Delia Savone; Raad Aris Besharat; Ammad Ahmad Farooqi; Filippo Bellati; Ilary Ruscito; Pierluigi Benedetti Panici; Andrea Papadia
Journal:  Tumour Biol       Date:  2015-10-26

5.  Assessment of Circulating Tumor Cells as a Predictive Biomarker of Histology in Women With Suspected Ovarian Cancer.

Authors:  Emil Lou; Rachel I Vogel; Deanna Teoh; Spencer Hoostal; Aaron Grad; Matthew Gerber; Minnu Monu; Tomasz Lukaszewski; Jaai Deshpande; Michael A Linden; Melissa A Geller
Journal:  Lab Med       Date:  2018-03-21

Review 6.  Reducing Ovarian Cancer Mortality Through Early Detection: Approaches Using Circulating Biomarkers.

Authors:  Camille V Trinidad; Ashley L Tetlow; Leonidas E Bantis; Andrew K Godwin
Journal:  Cancer Prev Res (Phila)       Date:  2020-03

7.  Circulating and disseminated tumor cells in pancreatic cancer and their role in patient prognosis: a systematic review and meta-analysis.

Authors:  David Stephenson; Christopher Nahm; Terence Chua; Anthony Gill; Anubhav Mittal; Philip de Reuver; Jaswinder Samra
Journal:  Oncotarget       Date:  2017-08-04

8.  Review article: Novel technologies in the treatment and monitoring of advanced and relapsed epithelial ovarian cancer.

Authors:  Paula Cunnea; Sally Gowers; James E Moore; Emmanuel Drakakis; Martyn Boutelle; Christina Fotopoulou
Journal:  Converg Sci Phys Oncol       Date:  2017-02-23

Review 9.  Detecting Tumor Metastases: The Road to Therapy Starts Here.

Authors:  M E Menezes; S K Das; I Minn; L Emdad; X-Y Wang; D Sarkar; M G Pomper; P B Fisher
Journal:  Adv Cancer Res       Date:  2016-08-17       Impact factor: 6.242

10.  Combined detection and subclass characteristics analysis of CTCs and CTECs by SE-iFISH in ovarian cancer.

Authors:  Hongyan Cheng; Shang Wang; Wenqing Luan; Xue Ye; Sha Dou; Zhijian Tang; Honglan Zhu; Peter Ping Lin; Yi Li; Heng Cui; Xiaohong Chang
Journal:  Chin J Cancer Res       Date:  2021-04-30       Impact factor: 5.087

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