Screening Prospects for Ovarian Cancer: Comparison
View Latest Version
Please note this is a comparison between Version 2 by Ron Wang and Version 1 by Diana Žilovič.

Ovarian cancer (OC) has the highest mortality rate of all gynecologic malignancies. The overall five-year survival is 46% and varies depending on the stage and histological type of the tumor. High-grade serous carcinoma (HGSOC) accounts for 75% of all epithelial ovarian malignancies and is diagnosed mainly at FIGO stage III (51%) or IV (29%), reflecting the aggressive nature.

  • ovarian cancer
  • liquid biopsies
  • uterine lavage
  • high-throughput methods
  • NGS-based multigene panels

1. Introduction

Ovarian cancer (OC) has the highest mortality rate of all gynecologic malignancies [1]. The overall five-year survival is 46% and varies depending on the stage and histological type of the tumor [2]. High-grade serous carcinoma (HGSOC) accounts for 75% of all epithelial ovarian malignancies and is diagnosed mainly at FIGO stage III (51%) or IV (29%), reflecting the aggressive nature [3]. In contrast, nonepithelial and more rare epithelial tumors such as endometrioid, mucinous. and clear-cell carcinomas are more frequently diagnosed at FIGO stages I–II [3]. Consequently, the five-year survival for HGSOC is 43%, compared with 82%, 71%, and 66% for endometrioid, mucinous, and clear-cell carcinoma, respectively. The five-year OS rate is only 9% for FIGO stage IV HGSOC patients [1].

Until recently, OC classification was based on morphology and immunohistochemistry (IHC), but more modern diagnostic approaches take into account molecular genetics, protein post-translational transformations, and immune cell infiltrates [16,17][4][5]. Over the last few decades, two distinct pathogenesis models were defined dividing ovarian malignancies into ovarian-origin OC and extra ovarian-origin OC. Ovarian-origin malignancies are very rare, mostly occurring at a young age or in childhood, and are presented by two main groups: (1) sex-cord stromal tumors tend to manifest as low-grade disease with a nonaggressive clinical course and are usually diagnosed at the early stages; (2) predominantly malignant germ cell tumors stand out due to their very fast tumor growth and the progression of clinical symptoms. Therefore, detailed screening tests do not seem mandatory for this category of tumors. The majority of epithelial ovarian cancers (EOCs) and epithelial–stromal ovarian tumors are suspected to be of extra ovarian origin, as the derivative cell is not ovarian (serous, mucinous, endometrioid, clear cell, and others). For clinical decision making, surface epithelial malignancies were further divided into two categories as a function of their pathogenetic pathways: type I and type II [2,18,19,20][2][6][7][8].

Most malignant tumors of the ovary are surface epithelial (90%). In 2014, the World Health Organization (WHO) recognized five principal epithelial OC histotypes: high-grade serous, low-grade serous, endometrioid, clear cell, and mucinous carcinoma. Other malignancies such as carcinosarcoma, adenosarcoma, and endometrioid stromal sarcoma are very rare; therefore, there is very little data concerning their pathogenesis and molecular features. Moreover, not otherwise specified ovarian tumors such as neuroendocrine, rete ovarii adenocarcinoma, Wilm‘s tumor, and others are exceptionally rare with an incidence of less than 0.1%. The most frequent mutation characteristics according to tumor morphology are presented in Table 1 [18,19,20,21,22,23,24,25,26,27,28,29,30,31][6][7][8][9][10][11][12][13][14][15][16][17][18][19].

Table 1. Discriminatig features of major histotypes of epithelial ovarian cancer.
HistologyCells of OriginPrecursorsMore Frequent Somatic Mutations
Low-Grade Serous CarcinomaFallopian tube progenitor cell or secretory cellSerous cystadenoma, adenofibroma, atypical proliferative serous tumor, noninvasive micropapillary serous borderline tumorKRAS (30%), BRAF (30%), NRAS, EIF1AX, USP9X, ERBB2, FRAR1, NF1, HRAS
Mucinous CarcinomaUnknownMucinous adenoma, mucinous borderline tumorCDKN2A (76%), KRAS and TP53 (both 64%), ERBB2 (26%), RNF43, BRAF, PIK3CA, ARID1A (8–12%)
Endometrioid CarcinomaEndometrial epithelial cellsEndometriosis and endometrial cell-like hyperplasia, endometrioid borderline tumorARID1A (30%), PIK3CA (30%), TERT, CTNNB1, TP53
Clear-Cell CarcinomaEndometrial epithelial cellsEndometriosis, endometrioid borderline tumorsPIK3CA (50%), ARID1A (50%), KRAS, MET, PTEN, CTNNB1, RPL22, TP53
High-Grade Serous CarcinomaFallopian tube progenitor cell or secretory cellSCOUT, P53 signature, STICTP53 (96–98%)

BRCA1/BRCA2 (10%, 25% somatic + germline);

CNAs of CCNE1 amplification, PTEN deletion, RB1 and NF1 loss
CarcinosarcomasUnknownCarcinomatous componentTP53, CTNNB1
STIC—serous tubal intraepithelial carcinomas, SCOUT—secretory cell OUT growth.

Type II tumors are characterized as highly aggressive neoplasms accounting for 75% of all EOCs, which are usually diagnosed at a late stage. They include high-grade serous carcinoma (HGSOC)—the most common type—and rare types such as high-grade endometrioid, undifferentiated carcinomas, and malignant epithelial mesenchymal tumors (carcinosarcomas). Type II ovarian tumors have a high level of genetic instability; the majority harbors TP53 mutations [18,19,20][6][7][8]. Recent data suggest that HGSOC tumors originate from the epithelium of the fallopian tube. Mutation of TP53 is the first known molecular event in the transformation of fallopian tube secretory cells to serous tubal intraepithelial carcinomas (STICs), which leads to HGSOC initiation. Mutated TP53 can be identified as an early tumor precursor of HGSOC. It has been estimated that it takes approximately seven years from STIC to clinically evolve into HGSOC [18,29,32][6][17][20]. Almost 80% of women present with advanced (stages III-IV) disease and poor prognosis (the five-year survival rate is around 25%). Since up to 98% of all HGSOC cases are characterized by TP53 somatic mutations, this biomarker is widely investigated as a potential diagnostic tool for OC diagnostics [18,20,29,31][6][8][17][19].

2. Materials and Methods

We performed a literature search in NCBI PubMed from January 2014 to September 2020 with a specific emphasis on liquid biopsy biomarkers for early OC detection. We used the keywords “ovarian cancer” together with “circulating free DNA”, ”circulating tumor DNA”, ”circulating tumor cells”, “small non coding RNA”, “microRNA”, “PIWI- interactingRNA”, “Transfer-RNA-derivated small RNA”, “liquid biopsy”, “TEPS”, and “uterine lavage”. We identified 2193 abstracts in NCBI PubMed and selected 30 reports considered inclusion criteria—evaluating the efficacy of liquid biopsies as a diagnostic tool for OC detection. We summarize the results of these studies in Table 2 . This work provides deeper understanding of the aspects of OC pathogenesis and existing challenges for liquid biopsy applications in clinical practice.

able 2. Studies on ctDNA, DNA, CTC and microRNA in ovarian cancer.
Author (Year), ReferencesNumber of OC PatientsSpecimenMethodGenetic Marker/AntigenDetection Rate (%)Detection Rate (%) (I-II Stage)Sensitivity (%)Specificity (%)
K.K Lin et al. (2019) [21]112 germline or somatic BRCA-mutant HGOCPlasma (ctDNA)Targeted-NGSBRCA1, BRCA2, TP5396 for TP53NRNRNR
Y. Wang et al. (2018) [22]83 OCPlasma (ctDNA)Pap SEEK-PCR-based error-reduction technology Safe-SeqS18 genes + assay for aneuploidy4335NR100
Y. Wang et al. (2018) [22]83 OCPlasma (ctDNA) + Pap Brush samplesPap SEEK-PCR-based error-reduction technology Safe-SeqS18 genes + assay for aneuploidy6354NR100
P.A. Cohen et al. (2018) [23]54 OCPlasma (ctDNA) + proteinsCancerSEEK

Targeted NGS		16 gene panel + 41 protein biomarkers9838NR>99

AUC = 0.91
J. Phallen et al. (2017) [24]42 OCPlasma (ctDNA)Targeted NGS (TEC-Seq) and ddPCR55 gene panel7168NR100
E. Pereira et al. (2015) [25]22 HGSOCSerum (ctDNA)ddPCR, NGS, WESTP53, PTEN, PIK3CA, MET, KRAS, FBXW7, BRAF93.8NR81-9160-99
A. Piskorz et al. (2016) [25]18 OCPlasma (ctDNA)Targeted NGSTP53100NRNRNR
R.C. Arend et al. (2018) [26]14 OCPlasma (cfDNA)Targeted NGS50 gene100NRNRNR
J.D. Cohen et al. (2016) [27]32 HGSOCPlasma cfDNA

(instability)		WEG (WISECONDOR)CNV3840.6NR93.8
A. Vanderst-ichele et al. [28]57 OC and bordline tumorsPlasma cfDNAWGSCNV67NRNR99.6

AUC = 0.89
Y. Wang et al. (2018) [22]245 OCCervix Pap brush samples (DNA)Pap SEEK-PCR-based error-reduction technology Safe-SeqS,18 genes + assay for aneuploidyNR333499
Tao Brush (DNA)Pap SEEK-PCR-based error-reduction technology Safe-SeqS18 genes + assay for aneuploidyNR4547100
Salk et al. (2019) [29]10 OCUterine lavage (DNA)Duplex SequencingTP5380NR70100
E.Maritschnegg (2018) [30]33 OCUterine lavage (DNA)Deep-sequencingAKT1, APC, BRAF, CDKN2A, CTNNB1, EGFR, FBXW7, FGFR2, KRAS, NRAS, PIK3CA, PIK3R1, POLE, PPP2R1A, PTEN, TP5380 for TP53NRNRNR
E.Maritschnegg (2015) [31]30 OCUterine lavage (DNA)Massively parallel sequencingAKT1, APC, BRAF, CDKN2A, CTNNB1, EGFR, FBXW7, FGFR2,60 for TP53100 for TP53NRNR
With ddPCR and SafeSeqSKRAS, NRAS, PIK3CA, PIK3R1, POLE, PPP2R1A, PTEN, TP5380 for TP53
B.K Erickson et al. (2014) [32]5 OCVaginal tampon (DNA)Massively parallel sequencingNR60NR60NR
Kinde et al. (2013) [33]22 OCLiquid Pap smear tests (DNA)Massively parallel sequencingNR41NRNRNR
N. Li et al (2019) [34]30 EOCPlasma (CTC)Magnetic nanospheres (MNs) + IHCEpCAM, FRα92NR7590

AUC = 0.8
Zhang et al. (2018) [35]109 EOCPlasma (CTC)Imunomagnetic beads (EpCAM, HER2 and MUC1) + multiplex RT-PCREpCAM, HER2, MUC1, WT1, P16, PAX89093NRNR
Q Rao et al. (2017) [36]23 EOCPlasma (CTC)Microfluidic system with immunomagnetic beads (EpCAM) + IHCEpCAM, CK3-6H5, panCK87NRNRNR
M. Lee et al. (2017) [37]54 EOCPlasma (CTC)Incorporating a nanoroughened microfluidic platform + IHCEpCAM, TROP-2, EGFR, Vimentin, N-cadherin98.1NRNRNR
Dong Hoon Suh et al. (2017) [38]87 EOC, bordline, benighPlasma (CTC)Tapered-slit membrane filters + IHCEpCAM, CK956.3NR77.455.8

AUC = 0.61–0.75
I. Chebouti et al. (2017) [39]95 EOCPlasma (CTC)Adna Test Ovarian Cancer and EMT-1 Select/Detect + Multiplex RT-PCREpCAM, ERCC1, MUC1, MUC16, PI3Ka, Akt-2, Twist82NR>90>90
K. Kolostova et al. (2016) [40]40 OCPlasma (CTC)MetaCell + IHC/qPCRICC: NucBlueTM, CelltrackerTM.

EpCAM, MUC1, MUC16, KRT18, KRT19, ERCC1, WT1		58NRNRNR
K. Kolostova et al (2015) [41]118 OCPlasma (CTC)MetaCell + IHC/qPCRICC: NucBlueTM, CelltrackerTM.

EpCAM, MUC1, MUC16, KRT18, KRT19,		65.2NRNRNR
M. Pearl et al. (2015) [42]31 EOCPlasma (CTC)CAM uptake-cell enrichment + IHC/RT-qPCREpCAM, Ca 125, CD44, seprase

EpCAM, CD44, MUC16, FAP		100NR8397
Pearl et al. (2014) [43]129 EOCPlasma (CTCs)CAM uptake – cell enrichment + IHCEpCAM, Ca 125, CD44, seprase88. 641.28395.1
Gao et al. (2015) [44]143 all 74 EOCSerum microRNAqRT-PCRmiR-200cNRNR7270, AUC = 0.79
miR-1416972, AUC = 0.75
Meng et al. (2016) [45]163 EOCSerum microRNATaqMan microRNA assays and ELISAmiR-200aNRNR8390, AUC = 0.91
miR-200b52100, AUC = 0.81
miR-200C31100, AUC = 0.65
3miRNAs set8890, AUC = 0.92
Yokoi et al. in (2017) [46]269 all 155EOCSerum microRNAqRT-PCR + statistical cross-validation methods8 miRNA combinationNR869291, AUC = 0.96
Yokoi et al. in (2018) et al. [47]EOC 333Serum microRNAMicroarrays10 miRNAs set miRNA-320a, -665, -1275, -3184-5p, -3185, -3195, -4459, 4640-5p, -6076, and -6717-5p.

EOS vs. non cancer		NRNR99100, AUC = 0.72–1.0
Kim S. (2019) [48]68 all 39HGOCSerum microRNAqRT-PCRmiRNA-145NRNR91.786.8, AUC = 86.8
miRNA-200C72.990.0, AUC = 77.9
NR: not reported; OC- ovarian cancer; EOC: epithelial ovarian cancer; ddPCR: Droplet digital PCR; RT-PCR: real time PCR technology; qRT-PCR: quantitative real time PCR; NGS: next generation sequencing; CAM: cell adhesion matrix; WES: whole exome sequencing; TGS: targeted gene sequences; HGSOC: high grade serous ovarian cancer; ddPCR: droplet digital PCR; AUC- areas under the ROC curves; IHC: immunocytochemistry staging; CNV: Copy number variation; WES: Whole exome sequencing; Safe-SeqS: Safe-sequencing system; WGS: Whole genome sequencing.

3. Modern Means for Early Detection of OC

An approach for the lavage of the uterine cavity to detect cancer cells that have been shed was developed by Paul Speiser, Professor at Medical College of Vienna, and colleagues [63][49].

A study published by Kinde et al. in 2013 analyzed the liquid Pap test from the uterine cervix for detecting ovarian and uterine cancers. Massively parallel sequencing for tumor-specific mutations using a 12-gene panel was performed on DNA extracted from liquid Pap smear tests. This technique was successfully applied to 100% of patients. Detectible DNA mutations were found in 24 (100%) for endometrial cancer patients and in 9 of 22 (41%) OC, mainly in late stages [45][50]. A pilot study showed that tumor cells and fragments containing tumor DNA can be found and collected in the vagina using a vaginal tampon and studied by using genetic analysis. They succeeded in revealing TP53 mutations in 60% of advanced HGSOCs [44][51]. Y. Wang et al. 2018 published data of DNA analysis in Pap brush samples from 245 OC patients, and the detection sensitivity was 33%, including 34% for patients with stage I–II disease [34][52].

PIWI-interacting RNA (piRNAs) interact with PIWIs—germline-specific Ago family nuclear RNA-binding proteins—and form piRNA-induced silencing complexes (piRISCs). The latest data demonstrate the contribution of piRNAs and PIWI proteins to the main carcinogenesis events: cell proliferation, resisting cell death, genome instability, invasion, and metastasis. PIWIs are essential for germline tissues and gametogenesis. Due to their restricted expression in reproductive tissue and tumors, PIWIs are classified as cancer/testis antigens (CTA). They are considered as excellent objects for diagnostic/prognostic biomarkers and targeted therapies. piRNAs regulate mechanistic RNA-based inhibition of transposable elements in germlines. They can target nontransposable elements as well—such as protein-coding messenger RNAs (mRNAs) —and modulate their expression, not only in germlines, but also in somatic cells, by a mechanism similar to that of miRNAs. piRISCs contribute to cancer development and progression by promoting a stem-like state of cancer cells, or cancer stem cells. The expression of germline genes in cancer reflects the ectopic activation in somatic tissues of a naturally silenced developmental program managing the escape from cell death, immune circumvention, and invasiveness [73,74][53][54]. In gynecologic malignancies, the study of piRNA pathophysiological significance, expression levels, and diagnostic performance remains exploratory.

Extracellular vesicles (EVs) contain cell surface proteins, as well as miRNAs and other molecules. EV-associated proteins and lncRNAs were investigated as potential biomarkers and showed greater sensitivity comparing to conventional biomarkers, but there are no data about the value to OC patients [82,83,84,85][55][56][57][58].

4. Conclusions and Future Prospects

Innovative technologies based on very small samples are likely to drastically change medical practice in the near future. Presently available liquid biopsy assessments are not ready for use in clinical practice. Significant efforts remain to create reliable tests for early OC detection. Uterine lavage techniques are easy to apply and safe, and this approach appears very promising for implementation in daily clinical practice. miRNAs are promising biomarkers for cancer diagnosis and prognosis, and large-scale prospective clinical studies are ongoing. Research efforts directed toward single-cell analysis are likely to shed more light on diagnostic biomarkers and potential therapeutic targets in the future.

References

  1. Lin, K.K.; Harrell, M.I.; Oza, A.M.; Oaknin, A.; Coquard, I.R.; Tinker, A.V.; Helman, E.; Radke, M.R.; Say, C.; Vo, L.T.; et al. BRCA reversion mutations in circulating tumor DNA predict primary and acquired resistance to the PARP inhibitor rucaparib in high-grade ovarian carcinoma. Cancer Discov. 2019, 9, 210–219.
  2. Wang, Y.; Li, L.; Douville, C.; Cohen, J.D.; Yen, T.T.; Kinde, I.; Sundfelt, K.; Kjær, K.S.; Hruban, R.H.; Shih, I.M.; et al. Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers. Sci. Transl. Med. 2018, 10, eaap8793.
  3. Cohen, J.D.; Lu Li, Y.; Wang, C.; Thoburn, B.; Afsari Danilova, L.; Douville, C.; Javed, A.A.; Wong, F.; Mattox, A. Detection and localization of surgically respectable cancers with a multi-analyte blood test. Science 2018, 359, 926–930.
  4. Phallen, J.; Sausen, M.; Adleff, V.; Leal, A.; Hruban, C.; White, J.; Anagnostou, V.; Fiksel, J.; Cristiano, S.; Papp, E. Direct detection of early-stage cancers using circulating tumor DNA. Sci. Transl. Med. 2017, 9, 403.
  5. Pereira, E.; Camacho-Vanegas, O.; Anand, S.; Sebra, R.; Camacho, S.C.; Garnar-Wortzel, L.; Nair, N.; Moshier, E.; Wooten, M.; Uzilov, A.; et al. Personalized circulating tumor DNA biomarkers dynamically predict treatment response and survival in gynecologic cancers. PLoS ONE 2015, 10, 12.
  6. Arend, R.C.; Londoño, A.I.; Montgomery, A.M.; Smith, H.J.; Dobbin, Z.C.; Katre, A.A.; Martinez, A.; Yang, E.S.; Alvarez, R.D.; Huh, W.K.; et al. Molecular Response to Neoadjuvant Chemotherapy in High-Grade Serous Ovarian Carcinoma. Mol. Cancer Res. 2018, 16, 813–824.
  7. Cohen, P.A.; Flowers, N.; Tong, S.; Hannan, N.; Pertile, M.D.; Hui, L. Abnormal plasma DNA profiles in early ovarian cancer using a non-invasive prenatal testing platform: Implications for cancer screening. BMC Med. 2016, 14, 126.
  8. Vanderstichele, A.; Busschaert, P.; Smeets, D.; Landolfo, C.; Nieuwenhuysen, E.V.; Leunen, K.; Neven, P.; Amant, F.; Mahner, S.; Braicu, E.I.; et al. Chromosomal instability in cell-free DNA as a highly specific biomarker for detection of ovarian cancer in women with adnexal masses Clin. Cancer Res. 2016, 23, 2223–2231.
  9. Salk, J.K.; Loubent-Senear, K.; Maritschnegg, E.; Valentine, C.C.; Williams, L.N.; Higgins, J.E.; Horvat, R.; Vanderstichele, A.; Nachmanson, D.; Baker, K.T.; et al. Ultra-Sensitive TP53 Sequencing for Cancer Detection Reveals Progressive Clonal Selection in Normal Tissue over a Century of Human Lifespan. Cell Rep. 2019, 28, 132–144.
  10. Maritschnegg, E.; Heitz, F.; Pecha, N.; Bouda, J.; Trillsch, F.; Grimm, C.; Vanderstichele, A.; Agreiter, C.; Harter, P.; Obermayr, E.; et al. Uterine and Tubal Lavage for Earlier Cancer Detection Using an Innovative Catheter: A Feasibility and Safety Study. Int. J. Gynecol. Cancer 2018, 28, 1692–1698.
  11. Maritschnegg, E.; Wang, Y.; Pecha, N.; Horvat, R.; Van Nieuwenhuysen, E.; Vergote, I.; Heitz, F.; Sehouli, J.; Kinde, I.; Diaz, L.A.; et al. Lavage of the Uterine Cavity for Molecular Detection of Müllerian Duct Carcinomas: A Proof-of-Concept Study. J. Clin. Oncol. 2015, 33, 4293–4300.
  12. Erickson, B.K.; Kinde, I.; Dobbin, Z.C.; Wang, Y.; Martin, J.Y.; Alvarez, R.D.; Conner, M.G.; Huh, W.K.; Roden, R.B.S.; Kinzler, K.W.; et al. Detection of somatic TP53 mutations in tampons of patients with high-grade serous ovarian cancer. Obstet. Gynecol. 2014, 124, 881–885.
  13. Kinde, I.; Bettegowda, C.; Wang, Y.; Wu, J.; Agrawal, N.; Shih, I.M.; Kurman, R.; Dao, F.; Levine, D.A.; Giuntoli, R.; et al. Evaluation of DNA from the papanicolaou test to detect ovarianand endometrial cancers. Sci. Transl Med. 2013, 5, 167ra4.
  14. Li, N.; Cheng, Y.; Chen, L.; Zuo, H.; Weng, Y.; Zhou, J.; Yao, Y.; Xu, B.; Gong, H.; Weng, Y.; et al. 1428P—Circulating tumour cell detection in epithelial ovarian cancer using dual-component antibodies targeting EpCAM and FRα. Ann. Oncol. 2019, 30, 5.
  15. Zhang, X.; Li, H.; Yu, X.; Li, S.; Lei, Z.; Li, C.; Zhang, Q.; Han, Q.; Li, Y.; Zhang, K.; et al. Analysis of Circulating Tumor Cells in Ovarian Cancer and Their Clinical Value as a Biomarker. Cell Physiol. Biochem. 2018, 48, 1983–1994.
  16. Rao, Q.; Zhang, Q.; Zhen, C.; Dai, W.; Zhang, B.; Ionescu-Zanetti, C.; Lin, Z.; Zhang, L. Detection of circulating tumour cells in patients with epithelial ovarian cancer by a microfluidic system. Int. J. Clin. Exp. Pathol. 2017, 10, 9599–9606.
  17. Lee, M.; Kim, E.J.; Cho, Y.; Kim, S.; Chung, H.H.; Park, N.H.; Song, Y.S. Predictive value of circulating tumor cells (CTCs) captured by microfluidic device in patients with epithelial ovarian cancer. Gynecol. Oncol. 2017, 145, 2361–2365.
  18. Dong Hoon, S.; Suh, D.H.; Kim, M.; Choi, J.Y.; Bu, J.; Kang, Y.T.; Lee, B.; Kim, K.; No, J.H.; Kim, Y.B.; et al. Circulating tumor cells in the differential diagnosis of adnexal masses. Oncotarget 2017, 8, 77195–77206.
  19. Issam CheboutiKasimir-Bauer, S.; Buderath, P.; Wimberger, P.; Hauch, S.; Kimmig, R.; Kuhlmann, D. EMT-like circulating tumor cells in ovarian cancer patients are enriched by platinum-based chemotherapy. Oncotarget 2017, 8, 48820.
  20. Kolostova, K.; Pinkas, M.; Jakabova, A.; Pospisilova, E.; Svobodova, P.; Spicka, J.; Cegan, M.; Matkowski, R.; Bobek, V. Molecular characterization of circulating tumor cells in ovarian cancer. Am. J. Canc. Res. 2016, 6, 973.
  21. Kolostova, K.; Pinkas, M.; Jakabova, A.; Pospisilova, E.; Svobodova, P.; Spicka, J.; Cegan, M.; Matkowski, R.; Bobek, V. The added value of circulating tumor cells examination in ovarian cancer staging. Am. J. Canc. Res. 2015, 5, 3363.
  22. Pearl, M.L.; Dong, H.; Tulley, S.; Zhao, Q.; Golightly, M.; Zucker, S.; Chen, W.-T. Treatment monitoring of patients with epithelial ovarian cancer using invasive circulating tumor cells (iCTCs). Gynecol. Oncol. 2015, 137, 229–238.
  23. Pearl, M.; LlZhao, Q.; Yang, Y.; Dong, H.; Tulley, S.; Zhang, Q.; Golightly, M.; Zucker, S.; Chen, W.T. Prognostic analysis of invasive circulating tumor cells (iCTCs) in epithelial ovarian cancer. Gynecol. Oncol. 2014, 134, 581–590.
  24. Gao, Y.-C.; Wu, J. microRNA-200c and microRNA-141 as potential diagnostic and prognostic biomarkers for ovarian cancer. Tumor Biol. 2015, 36, 4843–4850.
  25. Meng, X.; Müller, V.; Milde-Langosch, K.; Trillsch, F.; Pantel, K.; Schwarzenbach, H. Diagnostic and prognostic relevance of circulating exosomal miR-373, miR-200a, miR-200b and miR-200c in patients with epithelial ovarian cancer. Oncotarget 2016, 7, 16923–16935.
  26. Yokoi, A.; Yoshioka, Y.; Hirakawa, A.; Yamamoto, Y.; Ishikawa, M.; Ikeda, S.-I.; Kato, T.; Niimi, K.; Kajiyama, H.; Kikkawa, F.; et al. A combination of circulating miRNAs for the early detection of ovarian cancer. Oncotarget 2017, 8, 89811–89823.
  27. Yokoi, A.; Matsuzaki, J.; Yamamoto, Y.; Yoneoka, Y.; Takahashi, K.; Shimizu, H.; Uehara, T.; Ishikawa, M.; Ikeda, S.; Sonoda, T.; et al. Integrated extracellular microRNA profiling for ovarian cancer screening. Nat. Commun. 2018, 9, 4319.
  28. Kim, S.; Choi, M.C.; Jeong, J.-Y.; Hwang, S.; Jung, S.G.; Joo, W.D.; Park, H.; Song, S.H.; Lee, C.; Kim, T.H.; et al. Serum exosomal miRNA-145 and miRNA-200c as promising biomarkers for preoperative diagnosis of ovarian carcinomas. J. Cancer 2019, 10, 1958–1967.
  29. Peng, H.; Wang, J.; Li, J.; Zhao, M.; Huang, S.H.; Gu, Y.Y.; Li, Y.L.; Sun, X.J.; Yang, L.; Luo, Q. A circulating non-coding RNA panel as an early detection predictor of non-small cell lung cancer. Life Sci. 2016, 151, 235–242.
  30. Chang, L.; Ni, J.; Zhu, Y.; Pang, B.; Graham, P.; Zhang, H.; Li, Y. Liquid biopsy in ovarian cancer: Recent advances in circulating extracellular vesicle detection for early diagnosis and monitoring progression. Theranostics 2019, 9, 4130–4140.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Feedback