Skip to main content
SpringerLink
Log in

Molecular Characterization of Single Circulating Tumor Cells in Breast and Ovarian Cancer

  • Chapter
  • First Online:
Circulating Tumor Cells

Part of the book series: Current Cancer Research ((CUCR))

  • 396 Accesses

Abstract

Epithelial ovarian cancer (EOC) still has the highest mortality rate of all gynecological malignancies, diagnosed following the onset of symptoms, mostly at advanced stages, resulting in a challenging treatment situation and a generally poor outcome. Radical tumor debulking, followed by platinum-based chemotherapy with/without bevacizumab, is the treatment of choice; however, the majority of patients will ultimately relapse due to the development of platinum resistance. Thus, for the management of EOC, validated biomarkers are of need to identify patients at high risk for relapse. Since primary tumor tissue is often only available at the time of first diagnosis and, even if available, is only a single snapshot in time which does not always mirror the characteristics of the disease, biological fluids such as blood would be an ideal “surrogate tissue” to identify and monitor prognostic and predictive factors. Promising candidates are circulating tumor cells (CTCs), circulating DNA, microRNAs, as well as extracellular vesicles, all discussed to reflect the “real-time biopsy” at a certain time point of the disease. Liquid biopsy analysis allows rapid and repeated sampling and sequential monitoring of treatment response and disease progression, enabling for earlier intervention and treatment management in the follow-up of disease evolution. Here we provide an overview of the current state of the art of the value of liquid biopsy analysis in EOC with regard to prognosis, resistance, and treatment response.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

AGO:

Arbeitsgemeinschaft Gynäkologische Onkologie

BM:

Bone marrow

BRCA:

Breast cancer gene

CEC:

Circulating endothelial cells

cfDNA:

Cell-free DNA

CK:

Cytokeratin

CNV:

Copy number variation

CTC:

Circulating tumor cells

ctDNA:

Circulating tumor DNA

CTLA-4:

Cytotoxic T lymphocyte-associated protein 4

ddPCR:

Droplet digital PCR

DTC:

Disseminated tumor cells

ECOG:

Eastern Cooperative Oncology Group

EMA:

European Medicines Agency

EMT:

Epithelial-mesenchymal transition

EOC:

Epithelial ovarian cancer

ERCC1:

Excision repair cross-complementation group 1

ESR1:

Estrogen receptor 1

EVs:

Extracellular vesicles

FIGO:

Fédération Internationale de Gynécologie et d’Obstétrique

FISH:

Fluorescence in situ hybridization

HAP:

Hypoxic isolated abdominal perfusion therapy

HGSOC:

High-grade serous ovarian carcinoma

HLA-G:

Human leukocyte antigen G “gestation”

HRD:

Homologous recombination deficit

LNE:

Lymphadenectomy

LOH:

Loss of heterozygosity

miR:

microRNA

MSP:

Methylation-specific PCR

NGS:

Next-generation sequencing

OS:

Overall survival

PARP:

Poly-ADP-ribose-polymerase

PD-1:

Programmed cell death protein 1

PDL-1:

Programmed cell death ligand 1

PFS:

Progression-free survival

PLD:

Pegylated liposomal doxorubicin

PLGA:

Poly[lactic-co-glycolic acid]

RASSF:

Ras-association domain family

Tam-Seq:

Tagged-amplicon deep sequencing

Tregs:

Regulatory T cells

VEGF:

Vascular endothelial growth factor

VEGF-R:

Vascular endothelial growth factor receptor

WGS:

Whole genome sequencing

References

  1. International Agency for Research on Cancer, Lyon, France. (2016) Cancer Today. http://gco.iarc.fr/today. Accessed 09/June/2018

  2. Heintz AP, Odicino F, Maisonneuve P et al. (2006) Carcinoma of the Ovary. International Journal of Gynecology & Obstetrics 95:S161-S192. https://doi.org/10.1016/S0020-7292(06)60033-7

    Article  Google Scholar 

  3. Du Bois A, Reuss A, Pujade-Lauraine E et al. (2009) Role of surgical outcome as prognostic factor in advanced epithelial ovarian cancer: a combined exploratory analysis of 3 prospectively randomized phase 3 multicenter trials: by the Arbeitsgemeinschaft Gynaekologische Onkologie Studiengruppe Ovarialkarzinom (AGO-OVAR) and the Groupe d’Investigateurs Nationaux Pour les Etudes des Cancers de l’Ovaire (GINECO). Cancer 115:1234–1244. https://doi.org/10.1002/cncr.24149.

    Article  CAS  PubMed  Google Scholar 

  4. Harter P, Sehouli J, Lorusso D et al. (2019) A Randomized Trial of Lymphadenectomy in Patients with Advanced Ovarian Neoplasms. N Engl J Med 380:822–832. https://doi.org/10.1056/NEJMoa1808424.

    Article  PubMed  Google Scholar 

  5. Du Bois A, Neijt JP, Thigpen JT (1999) First line chemotherapy with carboplatin plus paclitaxel in advanced ovarian cancer--a new standard of care? Ann Oncol 10 Suppl 1:35–41. https://doi.org/10.1023/a:1008355317514

  6. Burger RA, Brady MF, Bookman MA et al. (2011) Incorporation of bevacizumab in the primary treatment of ovarian cancer. N Engl J Med 365:2473–2483. https://doi.org/10.1056/NEJMoa1104390.

    Article  CAS  PubMed  Google Scholar 

  7. Oza AM, Cook AD, Pfisterer J et al. (2015) Standard chemotherapy with or without bevacizumab for women with newly diagnosed ovarian cancer (ICON7): overall survival results of a phase 3 randomised trial. The Lancet Oncology 16:928–936. https://doi.org/10.1016/S1470-2045(15)00086-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Pujade-Lauraine E, Ledermann JA, Selle F et al. (2017) Olaparib tablets as maintenance therapy in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a double-blind, randomised, placebo-controlled, phase 3 trial. The Lancet Oncology 18:1274–1284. https://doi.org/10.1016/S1470-2045(17)30469-2

    Article  CAS  PubMed  Google Scholar 

  9. Mirza MR, Monk BJ, Herrstedt J et al. (2016) Niraparib Maintenance Therapy in Platinum-Sensitive, Recurrent Ovarian Cancer. N Engl J Med 375:2154–2164. https://doi.org/10.1056/NEJMoa1611310.

    Article  CAS  PubMed  Google Scholar 

  10. Coleman RL, Oza AM, Lorusso D et al. (2017) Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial. The Lancet 390:1949–1961. https://doi.org/10.1016/S0140-6736(17)32440-6

    Article  CAS  Google Scholar 

  11. Poveda A, Floquet A, Ledermann JA et al. (2021) Olaparib tablets as maintenance therapy in patients with platinum-sensitive relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a final analysis of a double-blind, randomised, placebo-controlled, phase 3 trial. The Lancet Oncology. https://doi.org/10.1016/S1470-2045(21)00073-5

  12. Moore K, Colombo N, Scambia G et al. (2018) Maintenance Olaparib in Patients with Newly Diagnosed Advanced Ovarian Cancer. N Engl J Med 379:2495–2505. https://doi.org/10.1056/NEJMoa1810858

    Article  CAS  PubMed  Google Scholar 

  13. Ray-Coquard I, Pautier P, Pignata S et al. (2019) Olaparib plus Bevacizumab as First-Line Maintenance in Ovarian Cancer. N Engl J Med 381:2416–2428. https://doi.org/10.1056/NEJMoa1911361

    Article  CAS  PubMed  Google Scholar 

  14. González-Martín A, Pothuri B, Vergote I et al. (2019) Niraparib in Patients with Newly Diagnosed Advanced Ovarian Cancer. N Engl J Med 381:2391–2402. https://doi.org/10.1056/NEJMoa1910962

    Article  PubMed  Google Scholar 

  15. Coleman RL, Fleming GF, Brady MF et al. (2019) Veliparib with First-Line Chemotherapy and as Maintenance Therapy in Ovarian Cancer. N Engl J Med 381:2403–2415. https://doi.org/10.1056/NEJMoa1909707

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Harter P, Sehouli J, Reuss A et al. (2011) Prospective validation study of a predictive score for operability of recurrent ovarian cancer: the Multicenter Intergroup Study DESKTOP II. A project of the AGO Kommission OVAR, AGO Study Group, NOGGO, AGO-Austria, and MITO. Int J Gynecol Cancer 21:289–295. https://doi.org/10.1097/IGC.0b013e31820aaafd

    Article  PubMed  Google Scholar 

  17. Du Bois A, Sehouli J, Vergote I et al. (2020) Randomized phase III study to evaluate the impact of secondary cytoreductive surgery in recurrent ovarian cancer: Final analysis of AGO DESKTOP III/ENGOT-ov20

    Google Scholar 

  18. Romero-Laorden N, Olmos D, Fehm T et al. (2014) Circulating and disseminated tumor cells in ovarian cancer: a systematic review. Gynecol Oncol 133:632–639. https://doi.org/10.1016/j.ygyno.2014.03.016

    Article  PubMed  Google Scholar 

  19. Cain JM, Ellis GK, Collins C et al. (1990) Bone marrow involvement in epithelial ovarian cancer by immunocytochemical assessment. Gynecol Oncol 38:442–445. https://doi.org/10.1016/0090-8258(90)90088-3

    Article  CAS  PubMed  Google Scholar 

  20. Marth C, Kisic J, Kaern J et al. (2002) Circulating tumor cells in the peripheral blood and bone marrow of patients with ovarian carcinoma do not predict prognosis. Cancer 94:707–712. https://doi.org/10.1002/cncr.10250

    Article  PubMed  Google Scholar 

  21. Braun S, Schindlbeck C, Hepp F et al. (2001) Occult tumor cells in bone marrow of patients with locoregionally restricted ovarian cancer predict early distant metastatic relapse. J Clin Oncol 19:368–375. https://doi.org/10.1200/JCO.2001.19.2.368

    Article  CAS  PubMed  Google Scholar 

  22. Banys M, Solomayer E-F, Becker S et al. (2009) Disseminated tumor cells in bone marrow may affect prognosis of patients with gynecologic malignancies. Int J Gynecol Cancer 19:948–952. https://doi.org/10.1111/IGC.0b013e3181a23c4c

    Article  PubMed  Google Scholar 

  23. Fehm T, Banys M, Rack B et al. (2013) Pooled analysis of the prognostic relevance of disseminated tumor cells in the bone marrow of patients with ovarian cancer. Int J Gynecol Cancer 23:839–845. https://doi.org/10.1097/IGC.0b013e3182907109

    Article  PubMed  Google Scholar 

  24. Cui L, Kwong J, Wang CC (2015) Prognostic value of circulating tumor cells and disseminated tumor cells in patients with ovarian cancer: a systematic review and meta-analysis. J Ovarian Res 8:38. https://doi.org/10.1186/s13048-015-0168-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wimberger P, Heubner M, Otterbach F et al. (2007) Influence of platinum-based chemotherapy on disseminated tumor cells in blood and bone marrow of patients with ovarian cancer. Gynecol Oncol 107:331–338. https://doi.org/10.1016/j.ygyno.2007.07.073

    Article  CAS  PubMed  Google Scholar 

  26. Wimberger P, Heubner M, Lindhofer H et al. (2009) Influence of catumaxomab on tumor cells in bone marrow and blood in ovarian cancer. Anticancer Res 29:1787–1791

    CAS  PubMed  Google Scholar 

  27. Cormio G, Rossi C, Cazzolla A et al. (2003) Distant metastases in ovarian carcinoma. Int J Gynecol Cancer 13:125–129. https://doi.org/10.1046/j.1525-1438.2003.13054.x

    Article  CAS  PubMed  Google Scholar 

  28. Sehouli J, Olschewski J, Schotters V et al. (2013) Prognostic role of early versus late onset of bone metastasis in patients with carcinoma of the ovary, peritoneum and fallopian tube. Ann Oncol 24:3024–3028. https://doi.org/10.1093/annonc/mdt398

    Article  CAS  PubMed  Google Scholar 

  29. Chebouti I, Blassl C, Wimberger P et al. (2016) Analysis of disseminated tumor cells before and after platinum based chemotherapy in primary ovarian cancer. Do stem cell like cells predict prognosis? Oncotarget 7:26454–26464. https://doi.org/10.18632/oncotarget.8524

    Article  PubMed  PubMed Central  Google Scholar 

  30. Monteiro J, Fodde R (2010) Cancer stemness and metastasis: therapeutic consequences and perspectives. Eur J Cancer 46:1198–1203. https://doi.org/10.1016/j.ejca.2010.02.030

    Article  CAS  PubMed  Google Scholar 

  31. Pastushenko I, Blanpain C (2019) EMT Transition States during Tumor Progression and Metastasis. Trends Cell Biol 29:212–226. https://doi.org/10.1016/j.tcb.2018.12.001

    Article  CAS  PubMed  Google Scholar 

  32. Zheng H, Bae Y, Kasimir-Bauer S et al. (2017) Therapeutic Antibody Targeting Tumor- and Osteoblastic Niche-Derived Jagged1 Sensitizes Bone Metastasis to Chemotherapy. Cancer Cell 32:731-747.e6. https://doi.org/10.1016/j.ccell.2017.11.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Abreu M, Cabezas-Sainz P, Alonso-Alconada L et al. (2020) Circulating Tumor Cells Characterization Revealed TIMP1 as a Potential Therapeutic Target in Ovarian Cancer. Cells 9. https://doi.org/10.3390/cells9051218

  34. Eva Obermayr, Natalia Bednarz-Knoll, Beatrice Orsetti et al. (2017) Circulating tumor cells: potential markers of minimal residual disease in ovarian cancer? a study of the OVCAD consortium. Oncotarget:106415–106428. https://doi.org/10.18632/oncotarget.22468

  35. Cristofanilli, Massimo, Budd, G. Thomas, Ellis, Matthew J. et al. (2004) Circulating Tumor Cells, Disease Progression, and Survival in Metastatic Breast Cancer. N Engl J Med:781–791. https://doi.org/10.1056/NEJMoa040766

  36. Aktas B, Kasimir-Bauer S, Heubner M et al. (2011) 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 21:822–830. https://doi.org/10.1097/IGC.0b013e318216cb91

    Article  PubMed  Google Scholar 

  37. Kuhlmann JD, Wimberger P, Bankfalvi A et al. (2014) ERCC1-positive circulating tumor cells in the blood of ovarian cancer patients as a predictive biomarker for platinum resistance. Clin Chem 60:1282–1289. https://doi.org/10.1373/clinchem.2014.224808

    Article  CAS  PubMed  Google Scholar 

  38. Issam Chebouti, Jan Dominik Kuhlmann, Paul Buderath et al. (2017) ERCC1-expressing circulating tumor cells as a potential diagnostic tool for monitoring response to platinum-based chemotherapy and for predicting post-therapeutic outcome of ovarian cancer. Oncotarget:24303–24313. https://doi.org/10.18632/oncotarget.13286.

  39. Zhang X, Li H, Yu X et al. (2018) Analysis of Circulating Tumor Cells in Ovarian Cancer and Their Clinical Value as a Biomarker. Cell Physiol Biochem 48:1983–1994. https://doi.org/10.1159/000492521

    Article  CAS  PubMed  Google Scholar 

  40. Issam Chebouti, Sabine Kasimir-Bauer, Paul Buderath et al. (2017) EMT-like circulating tumor cells in ovarian cancer patients are enriched by platinum-based chemotherapy. Oncotarget:48820–48831. https://doi.org/10.18632/oncotarget.16179

  41. Eva Obermayr, Fatima Sanchez-Cabo, Muy-Kheng M Tea et al. (2010) Assessment of a six gene panel for the molecular detection of circulating tumor cells in the blood of female cancer patients. BMC Cancer:1–12. https://doi.org/10.1186/1471-2407-10-666

  42. Obermayr E, Castillo-Tong DC, Pils D et al. (2013) Molecular characterization of circulating tumor cells in patients with ovarian cancer improves their prognostic significance — a study of the OVCAD consortium. Gynecol Oncol 128:15–21. https://doi.org/10.1016/j.ygyno.2012.09.021

  43. Katarina Kolostova, Michael Pinkas, Anna Jakabova et al. (2016) Molecular characterization of circulating tumor cells in ovarian cancer. American journal of translational research:973

    Google Scholar 

  44. Guadagni S, Clementi M, Masedu F et al. (2020) A Pilot Study of the Predictive Potential of Chemosensitivity and Gene Expression Assays Using Circulating Tumour Cells from Patients with Recurrent Ovarian Cancer. Int J Mol Sci 21. https://doi.org/10.3390/ijms21134813

  45. Yan-Xiu Guo, Kuang Hong Neoh, Xiao-Hong Chang et al. (2018) Diagnostic value of HE4+ circulating tumor cells in patients with suspicious ovarian cancer. Oncotarget. 2018 Jan 26:7522–7533. 10.18632/oncotarget.23943

    Google Scholar 

  46. Kim H, Lim M, Kim JY et al. (2020) Circulating Tumor Cells Enumerated by a Centrifugal Microfluidic Device as a Predictive Marker for Monitoring Ovarian Cancer Treatment: A Pilot Study. Diagnostics (Basel) 10. https://doi.org/10.3390/diagnostics10040249

  47. Po JW, Roohullah A, Lynch D et al. (2018) Improved ovarian cancer EMT-CTC isolation by immunomagnetic targeting of epithelial EpCAM and mesenchymal N-cadherin. J Circ Biomark 7:1849454418782617. https://doi.org/10.1177/1849454418782617

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wu Z, Pan Y, Wang Z et al. (2021) A PLGA nanofiber microfluidic device for highly efficient isolation and release of different phenotypic circulating tumor cells based on dual aptamers. J Mater Chem B. https://doi.org/10.1039/d0tb02988b

  49. Pradeep S, Kim SW, Wu SY et al. (2014) Hematogenous metastasis of ovarian cancer: rethinking mode of spread. Cancer Cell 26:77–91. https://doi.org/10.1016/j.ccr.2014.05.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Liu JF, Ray-Coquard I, Selle F et al. (2016) Randomized Phase II Trial of Seribantumab in Combination With Paclitaxel in Patients With Advanced Platinum-Resistant or -Refractory Ovarian Cancer. J Clin Oncol 34:4345–4353. https://doi.org/10.1200/JCO.2016.67.1891

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Lorusso D, Hilpert F, González Martin A et al. (2019) Patient-reported outcomes and final overall survival results from the randomized phase 3 PENELOPE trial evaluating pertuzumab in low tumor human epidermal growth factor receptor 3 (HER3) mRNA-expressing platinum-resistant ovarian cancer. International Journal of Gynecologic Cancer 29:1141–1147. https://doi.org/10.1136/ijgc-2019-000370

    Article  Google Scholar 

  52. The Cancer Genome Atlas Research Network (2011) Integrated genomic analyses of ovarian carcinoma. Nature 474:609–615. https://doi.org/10.1038/nature10166

    Article  CAS  PubMed Central  Google Scholar 

  53. Lee S, Zhao L, Rojas C et al. (2020) Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer. Cell Rep 31:107502. https://doi.org/10.1016/j.celrep.2020.03.066

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Macintyre G, Goranova TE, Silva D de et al. (2018) Copy number signatures and mutational processes in ovarian carcinoma. Nat Genet:1262–1270. https://doi.org/10.1038/s41588-018-0179-8

  55. David T. Miyamoto, Yu Zheng, Ben S. Wittner et al. (2015) RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance. Science:1351–1356. https://doi.org/10.1126/science.aab0917

  56. Gao Y, Ni X, Guo H et al. (2017) Single-cell sequencing deciphers a convergent evolution of copy number alterations from primary to circulating tumor cells. Genome Res 27:1312–1322. https://doi.org/10.1101/gr.216788.116

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Gorges TM, Kuske A, Röck K et al. (2016) Accession of Tumor Heterogeneity by Multiplex Transcriptome Profiling of Single Circulating Tumor Cells. Clin Chem 62:1504–1515. https://doi.org/10.1373/clinchem.2016.260299

    Article  CAS  PubMed  Google Scholar 

  58. Polzer B, Medoro G, Pasch S et al. (2014) Molecular profiling of single circulating tumor cells with diagnostic intention. EMBO Mol Med 6:1371–1386. https://doi.org/10.15252/emmm.201404033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Ramsköld D, Luo S, Wang Y-C et al. (2012) Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 30:777–782. https://doi.org/10.1038/nbt.2282

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Sinkala E, Sollier-Christen E, Renier C et al. (2017) Profiling protein expression in circulating tumour cells using microfluidic western blotting. Nat Commun 8:14622. https://doi.org/10.1038/ncomms14622

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Blassl C, Kuhlmann JD, Webers A et al. (2016) Gene expression profiling of single circulating tumor cells in ovarian cancer - Establishment of a multi-marker gene panel. Mol Oncol 10:1030–1042. https://doi.org/10.1016/j.molonc.2016.04.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. HERCULES Project Comprehensive characterization and effective combinatorial targeting of high-grade serous ovarian cancer via single-cell analysis. https://project-hercules.eu/. Accessed 03 Mar 2021

  63. Chen Q, Zhang Z-H, Wang S et al. (2019) Circulating Cell-Free DNA or Circulating Tumor DNA in the Management of Ovarian and Endometrial Cancer. Onco Targets Ther 12:11517–11530. https://doi.org/10.2147/OTT.S227156

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Asante D-B, Calapre L, Ziman M et al. (2020) Liquid biopsy in ovarian cancer using circulating tumor DNA and cells: Ready for prime time? Cancer Lett 468:59–71. https://doi.org/10.1016/j.canlet.2019.10.014

    Article  CAS  PubMed  Google Scholar 

  65. Giannopoulou L, Lianidou ES (2020) Liquid biopsy in ovarian cancer. Adv Clin Chem 97:13–71. https://doi.org/10.1016/bs.acc.2020.01.001

    Article  CAS  PubMed  Google Scholar 

  66. Harris FR, Kovtun IV, Smadbeck J et al. (2016) Quantification of Somatic Chromosomal Rearrangements in Circulating Cell-Free DNA from Ovarian Cancers. Sci Rep 6:29831. https://doi.org/10.1038/srep29831

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Wan JCM, Massie C, Garcia-Corbacho J et al. (2017) Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer 17:223–238. https://doi.org/10.1038/nrc.2017.7

    Article  CAS  PubMed  Google Scholar 

  68. Diaz LA, Bardelli A (2014) Liquid biopsies: genotyping circulating tumor DNA. J Clin Oncol 32:579–586. https://doi.org/10.1200/JCO.2012.45.2011

    Article  PubMed  PubMed Central  Google Scholar 

  69. Jiang P, Chan CWM, Chan KCA et al. (2015) Lengthening and shortening of plasma DNA in hepatocellular carcinoma patients. Proc Natl Acad Sci U S A 112:E1317-25. https://doi.org/10.1073/pnas.1500076112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Underhill HR, Kitzman JO, Hellwig S et al. (2016) Fragment Length of Circulating Tumor DNA. PLoS Genet 12:e1006162. https://doi.org/10.1371/journal.pgen.1006162

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Bettegowda C, Sausen M, Leary RJ et al. (2014) Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med 6:224ra24. https://doi.org/10.1126/scitranslmed.3007094

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Tug S, Helmig S, Deichmann ER et al. (2015) Exercise-induced increases in cell free DNA in human plasma originate predominantly from cells of the haematopoietic lineage. Exerc Immunol Rev 21:164–173

    PubMed  Google Scholar 

  73. Pandoh PK, Corbett RD, McDonald H et al. (2019) A high-throughput protocol for isolating cell-free circulating tumor DNA from peripheral blood. Biotechniques 66:85–92. https://doi.org/10.2144/btn-2018-0148

    Article  CAS  PubMed  Google Scholar 

  74. Fettke H, Kwan EM, Azad AA (2019) Cell-free DNA in cancer: current insights. Cell Oncol (Dordr) 42:13–28. https://doi.org/10.1007/s13402-018-0413-5

    Article  CAS  PubMed  Google Scholar 

  75. Lu J-L, Liang Z-Y (2016) Circulating free DNA in the era of precision oncology: Pre- and post-analytical concerns. Chronic Dis Transl Med 2:223–230. https://doi.org/10.1016/j.cdtm.2016.12.001

    Article  PubMed  PubMed Central  Google Scholar 

  76. Franczak C, Filhine-Tresarrieu P, Gilson P et al. (2019) Technical considerations for circulating tumor DNA detection in oncology. Expert Rev Mol Diagn 19:121–135. https://doi.org/10.1080/14737159.2019.1568873

    Article  CAS  PubMed  Google Scholar 

  77. Butler TM, Johnson-Camacho K, Peto M et al. (2015) Exome Sequencing of Cell-Free DNA from Metastatic Cancer Patients Identifies Clinically Actionable Mutations Distinct from Primary Disease. PLoS ONE 10:e0136407. https://doi.org/10.1371/journal.pone.0136407

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Mouliere F, Chandrananda D, Piskorz AM et al. (2018) Enhanced detection of circulating tumor DNA by fragment size analysis. Sci Transl Med 10. https://doi.org/10.1126/scitranslmed.aat4921

  79. Pereira E, Camacho-Vanegas O, Anand S et al. (2015) Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers. PLoS ONE 10:e0145754. https://doi.org/10.1371/journal.pone.0145754

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Lin KK, Harrell MI, Oza AM et al. (2019) BRCA Reversion Mutations in Circulating Tumor DNA Predict Primary and Acquired Resistance to the PARP Inhibitor Rucaparib in High-Grade Ovarian Carcinoma. Cancer Discov 9:210–219. https://doi.org/10.1158/2159-8290.CD-18-0715

    Article  CAS  PubMed  Google Scholar 

  81. Guo XM, Miller H, Matsuo K et al. (2021) Circulating Cell-Free DNA Methylation Profiles in the Early Detection of Ovarian Cancer: A Scoping Review of the Literature. Cancers (Basel) 13. https://doi.org/10.3390/cancers13040838

  82. Bondurant AE, Huang Z, Whitaker RS et al. (2011) Quantitative detection of RASSF1A DNA promoter methylation in tumors and serum of patients with serous epithelial ovarian cancer. Gynecol Oncol 123:581–587. https://doi.org/10.1016/j.ygyno.2011.08.029

    Article  CAS  PubMed  Google Scholar 

  83. Zhang Q, Hu G, Yang Q et al. (2013) A multiplex methylation-specific PCR assay for the detection of early-stage ovarian cancer using cell-free serum DNA. Gynecol Oncol 130:132–139. https://doi.org/10.1016/j.ygyno.2013.04.048

    Article  CAS  PubMed  Google Scholar 

  84. Wu Y, Zhang X, Lin L et al. (2014) Aberrant methylation of RASSF2A in tumors and plasma of patients with epithelial ovarian cancer. Asian Pac J Cancer Prev 15:1171–1176. https://doi.org/10.7314/apjcp.2014.15.3.1171

    Article  PubMed  Google Scholar 

  85. Wang B, Yu L, Yang G-Z et al. (2015) Application of multiplex nested methylated specific PCR in early diagnosis of epithelial ovarian cancer. Asian Pac J Cancer Prev 16:3003–3007. https://doi.org/10.7314/apjcp.2015.16.7.3003

    Article  PubMed  Google Scholar 

  86. Widschwendter M, Zikan M, Wahl B et al. (2017) The potential of circulating tumor DNA methylation analysis for the early detection and management of ovarian cancer. Genome Med 9:116. https://doi.org/10.1186/s13073-017-0500-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Giannopoulou L, Chebouti I, Pavlakis K et al. (2017) RASSF1A promoter methylation in high-grade serous ovarian cancer: A direct comparison study in primary tumors, adjacent morphologically tumor cell-free tissues and paired circulating tumor DNA. Oncotarget 8:21429–21443. https://doi.org/10.18632/oncotarget.15249

    Article  PubMed  PubMed Central  Google Scholar 

  88. Giannopoulou L, Mastoraki S, Buderath P et al. (2018) ESR1 methylation in primary tumors and paired circulating tumor DNA of patients with high-grade serous ovarian cancer. Gynecol Oncol 150:355–360. https://doi.org/10.1016/j.ygyno.2018.05.026

    Article  CAS  PubMed  Google Scholar 

  89. Dong R, Yu J, Pu H et al. (2012) Frequent SLIT2 promoter methylation in the serum of patients with ovarian cancer. J Int Med Res 40:681–686. https://doi.org/10.1177/147323001204000231

    Article  CAS  PubMed  Google Scholar 

  90. Teschendorff AE, Menon U, Gentry-Maharaj A et al. (2009) An epigenetic signature in peripheral blood predicts active ovarian cancer. PLoS ONE 4:e8274. https://doi.org/10.1371/journal.pone.0008274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Flanagan JM, Wilson A, Koo C et al. (2017) Platinum-Based Chemotherapy Induces Methylation Changes in Blood DNA Associated with Overall Survival in Patients with Ovarian Cancer. Clin Cancer Res 23:2213–2222. https://doi.org/10.1158/1078-0432.CCR-16-1754

    Article  CAS  PubMed  Google Scholar 

  92. Iwasa H, Hossain S, Hata Y (2018) Tumor suppressor C-RASSF proteins. Cell Mol Life Sci 75:1773–1787. https://doi.org/10.1007/s00018-018-2756-5

    Article  CAS  PubMed  Google Scholar 

  93. Schmidt ML, Hobbing KR, Donninger H et al. (2018) RASSF1A Deficiency Enhances RAS-Driven Lung Tumorigenesis. Cancer Res 78:2614–2623. https://doi.org/10.1158/0008-5472.CAN-17-2466

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Vanderstichele A, Busschaert P, Smeets D et al. (2017) Chromosomal Instability in Cell-Free DNA as a Highly Specific Biomarker for Detection of Ovarian Cancer in Women with Adnexal Masses. Clin Cancer Res 23:2223–2231. https://doi.org/10.1158/1078-0432.CCR-16-1078

    Article  CAS  PubMed  Google Scholar 

  95. Gifford G, Paul J, Vasey PA et al. (2004) The acquisition of hMLH1 methylation in plasma DNA after chemotherapy predicts poor survival for ovarian cancer patients. Clin Cancer Res 10:4420–4426. https://doi.org/10.1158/1078-0432.CCR-03-0732

    Article  CAS  PubMed  Google Scholar 

  96. Park YR, Kim Y-M, Lee SW et al. (2018) Optimization to detect TP53 mutations in circulating cell-free tumor DNA from patients with serous epithelial ovarian cancer. Obstet Gynecol Sci 61:328–336. https://doi.org/10.5468/ogs.2018.61.3.328

    Article  PubMed  PubMed Central  Google Scholar 

  97. Weigelt B, Comino-Méndez I, de Bruijn I et al. (2017) Diverse BRCA1 and BRCA2 Reversion Mutations in Circulating Cell-Free DNA of Therapy-Resistant Breast or Ovarian Cancer. Clin Cancer Res 23:6708–6720. https://doi.org/10.1158/1078-0432.CCR-17-0544

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Parkinson CA, Gale D, Piskorz AM et al. (2016) Exploratory Analysis of TP53 Mutations in Circulating Tumour DNA as Biomarkers of Treatment Response for Patients with Relapsed High-Grade Serous Ovarian Carcinoma: A Retrospective Study. PLoS Med 13:e1002198. https://doi.org/10.1371/journal.pmed.1002198

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Christie EL, Fereday S, Doig K et al. (2017) Reversion of BRCA1/2 Germline Mutations Detected in Circulating Tumor DNA From Patients With High-Grade Serous Ovarian Cancer. J Clin Oncol 35:1274–1280. https://doi.org/10.1200/JCO.2016.70.4627

    Article  CAS  PubMed  Google Scholar 

  100. Kamat AA, Baldwin M, Urbauer D et al. (2010) Plasma cell-free DNA in ovarian cancer: an independent prognostic biomarker. Cancer 116:1918–1925. https://doi.org/10.1002/cncr.24997

    Article  CAS  PubMed  Google Scholar 

  101. Wimberger P, Roth C, Pantel K et al. (2011) Impact of platinum-based chemotherapy on circulating nucleic acid levels, protease activities in blood and disseminated tumor cells in bone marrow of ovarian cancer patients. Int J Cancer 128:2572–2580. https://doi.org/10.1002/ijc.25602

    Article  CAS  PubMed  Google Scholar 

  102. Steffensen KD, Madsen CV, Andersen RF et al. (2014) Prognostic importance of cell-free DNA in chemotherapy resistant ovarian cancer treated with bevacizumab. Eur J Cancer 50:2611–2618. https://doi.org/10.1016/j.ejca.2014.06.022

    Article  CAS  PubMed  Google Scholar 

  103. Du Z-H, Bi F-F, Wang L et al. (2018) Next-generation sequencing unravels extensive genetic alteration in recurrent ovarian cancer and unique genetic changes in drug-resistant recurrent ovarian cancer. Mol Genet Genomic Med. https://doi.org/10.1002/mgg3.414

  104. Kuhlmann JD, Schwarzenbach H, Wimberger P et al. (2012) LOH at 6q and 10q in fractionated circulating DNA of ovarian cancer patients is predictive for tumor cell spread and overall survival. BMC Cancer 12:325. https://doi.org/10.1186/1471-2407-12-325

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Giannopoulou L, Zavridou M, Kasimir-Bauer S et al. (2019) Liquid biopsy in ovarian cancer: the potential of circulating miRNAs and exosomes. Transl Res 205:77–91. https://doi.org/10.1016/j.trsl.2018.10.003

    Article  CAS  PubMed  Google Scholar 

  106. Satapathy S, Kumar C, Singh RK (2019) MicroRNAs as Key Regulators of Ovarian Cancers. Cell Med 11:2155179019873849. https://doi.org/10.1177/2155179019873849

    Article  PubMed  PubMed Central  Google Scholar 

  107. Alshamrani AA (2020) Roles of microRNAs in Ovarian Cancer Tumorigenesis: Two Decades Later, What Have We Learned? Front Oncol 10:1084. https://doi.org/10.3389/fonc.2020.01084

    Article  PubMed  PubMed Central  Google Scholar 

  108. Aboutalebi H, Bahrami A, Soleimani A et al. (2020) The diagnostic, prognostic and therapeutic potential of circulating microRNAs in ovarian cancer. Int J Biochem Cell Biol 124:105765. https://doi.org/10.1016/j.biocel.2020.105765

    Article  CAS  PubMed  Google Scholar 

  109. Nguyen VHL, Yue C, Du KY et al. (2020) The Role of microRNAs in Epithelial Ovarian Cancer Metastasis. Int J Mol Sci 21. https://doi.org/10.3390/ijms21197093

  110. Yoshida K, Yokoi A, Kato T et al. (2020) The clinical impact of intra- and extracellular miRNAs in ovarian cancer. Cancer Sci 111:3435–3444. https://doi.org/10.1111/cas.14599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Kumar V, Gupta S, Varma K et al. (2020) MicroRNA as Biomarker in Ovarian Cancer Management: Advantages and Challenges. DNA Cell Biol. https://doi.org/10.1089/dna.2020.6024

  112. Kozomara A, Birgaoanu M, Griffiths-Jones S (2019) miRBase: from microRNA sequences to function. Nucleic Acids Res 47:D155-D162. https://doi.org/10.1093/nar/gky1141

    Article  CAS  PubMed  Google Scholar 

  113. Valadi H, Ekström K, Bossios A et al. (2007) Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 9:654–659. https://doi.org/10.1038/ncb1596

    Article  CAS  PubMed  Google Scholar 

  114. Chou J, Shahi P, Werb Z (2013) microRNA-mediated regulation of the tumor microenvironment. Cell Cycle 12:3262–3271. https://doi.org/10.4161/cc.26087

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Yokoi A, Matsuzaki J, Yamamoto Y et al. (2018) Integrated extracellular microRNA profiling for ovarian cancer screening. Nat Commun 9:4319. https://doi.org/10.1038/s41467-018-06434-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Suryawanshi S, Vlad AM, Lin H-M et al. (2013) Plasma microRNAs as novel biomarkers for endometriosis and endometriosis-associated ovarian cancer. Clin Cancer Res 19:1213–1224. https://doi.org/10.1158/1078-0432.CCR-12-2726

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Zhao L, Wang W, Xu L et al. (2019) Integrative network biology analysis identifies miR-508-3p as the determinant for the mesenchymal identity and a strong prognostic biomarker of ovarian cancer. Oncogene 38:2305–2319. https://doi.org/10.1038/s41388-018-0577-5

    Article  CAS  PubMed  Google Scholar 

  118. Huang G-L, Sun J, Lu Y et al. (2019) MiR-200 family and cancer: From a meta-analysis view. Mol Aspects Med 70:57–71. https://doi.org/10.1016/j.mam.2019.09.005

    Article  CAS  PubMed  Google Scholar 

  119. Zuberi M, Mir R, Das J et al. (2015) Expression of serum miR-200a, miR-200b, and miR-200c as candidate biomarkers in epithelial ovarian cancer and their association with clinicopathological features. Clin Transl Oncol 17:779–787. https://doi.org/10.1007/s12094-015-1303-1

    Article  CAS  PubMed  Google Scholar 

  120. Dongre A, Weinberg RA (2019) New insights into the mechanisms of epithelial-mesenchymal transition and implications for cancer. Nat Rev Mol Cell Biol 20:69–84. https://doi.org/10.1038/s41580-018-0080-4

    Article  CAS  PubMed  Google Scholar 

  121. Feng W, Dean DC, Hornicek FJ et al. (2019) Exosomes promote pre-metastatic niche formation in ovarian cancer. Mol Cancer 18:124. https://doi.org/10.1186/s12943-019-1049-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Taylor DD, Gercel-Taylor C (2008) MicroRNA signatures of tumor-derived exosomes as diagnostic biomarkers of ovarian cancer. Gynecol Oncol 110:13–21. https://doi.org/10.1016/j.ygyno.2008.04.033

    Article  CAS  PubMed  Google Scholar 

  123. Vaksman O, Stavnes HT, Kaern J et al. (2011) miRNA profiling along tumour progression in ovarian carcinoma. J Cell Mol Med 15:1593–1602. https://doi.org/10.1111/j.1582-4934.2010.01148.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Pan C, Stevic I, Müller V et al. (2018) Exosomal microRNAs as tumor markers in epithelial ovarian cancer. Mol Oncol 12:1935–1948. https://doi.org/10.1002/1878-0261.12371

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Li Y, Liu C, Liao Y et al. (2019) Characterizing the landscape of peritoneal exosomal microRNAs in patients with ovarian cancer by high-throughput sequencing. Oncol Lett 17:539–547. https://doi.org/10.3892/ol.2018.9558

    Article  CAS  PubMed  Google Scholar 

  126. Weiner-Gorzel K, Dempsey E, Milewska M et al. (2015) Overexpression of the microRNA miR-433 promotes resistance to paclitaxel through the induction of cellular senescence in ovarian cancer cells. Cancer Med 4:745–758. https://doi.org/10.1002/cam4.409

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Cheng W, Liu T, Wan X et al. (2012) MicroRNA-199a targets CD44 to suppress the tumorigenicity and multidrug resistance of ovarian cancer-initiating cells. FEBS J 279:2047–2059. https://doi.org/10.1111/j.1742-4658.2012.08589.x

    Article  CAS  PubMed  Google Scholar 

  128. Cao Y, Shi H, Ren F et al. (2017) Long non-coding RNA CCAT1 promotes metastasis and poor prognosis in epithelial ovarian cancer. Exp Cell Res 359:185–194. https://doi.org/10.1016/j.yexcr.2017.07.030

    Article  CAS  PubMed  Google Scholar 

  129. Yu R, Cai L, Chi Y et al. (2018) miR-377 targets CUL4A and regulates metastatic capability in ovarian cancer. Int J Mol Med 41:3147–3156. https://doi.org/10.3892/ijmm.2018.3540

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Huang Z, Li Q, Luo K et al. (2019) miR-340-FHL2 axis inhibits cell growth and metastasis in ovarian cancer. Cell Death Dis 10:372. https://doi.org/10.1038/s41419-019-1604-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Hu X, Macdonald DM, Huettner PC et al. (2009) A miR-200 microRNA cluster as prognostic marker in advanced ovarian cancer. Gynecol Oncol 114:457–464. https://doi.org/10.1016/j.ygyno.2009.05.022

    Article  CAS  PubMed  Google Scholar 

  132. Pecot CV, Rupaimoole R, Da Yang et al. (2013) Tumour angiogenesis regulation by the miR-200 family. Nat Commun 4:2427. https://doi.org/10.1038/ncomms3427

    Article  CAS  PubMed  Google Scholar 

  133. Suo H-B, Zhang K-C, Zhao J (2018) MiR-200a promotes cell invasion and migration of ovarian carcinoma by targeting PTEN. Eur Rev Med Pharmacol Sci 22:4080–4089. https://doi.org/10.26355/eurrev_201807_15398

    Article  PubMed  Google Scholar 

  134. Salem M, O’Brien JA, Bernaudo S et al. (2018) miR-590-3p Promotes Ovarian Cancer Growth and Metastasis via a Novel FOXA2-Versican Pathway. Cancer Res 78:4175–4190. https://doi.org/10.1158/0008-5472.CAN-17-3014

    Article  CAS  PubMed  Google Scholar 

  135. Yang L, Wei Q-M, Zhang X-W et al. (2017) MiR-376a promotion of proliferation and metastases in ovarian cancer: Potential role as a biomarker. Life Sci 173:62–67. https://doi.org/10.1016/j.lfs.2016.12.007

    Article  CAS  PubMed  Google Scholar 

  136. Xie J, Liu M, Li Y et al. (2014) Ovarian tumor-associated microRNA-20a decreases natural killer cell cytotoxicity by downregulating MICA/B expression. Cell Mol Immunol 11:495–502. https://doi.org/10.1038/cmi.2014.30

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Langhe R, Norris L, Saadeh FA et al. (2015) A novel serum microRNA panel to discriminate benign from malignant ovarian disease. Cancer Lett 356:628–636. https://doi.org/10.1016/j.canlet.2014.10.010

    Article  CAS  PubMed  Google Scholar 

  138. Zuberi M, Khan I, Gandhi G et al. (2016) The conglomeration of diagnostic, prognostic and therapeutic potential of serum miR-199a and its association with clinicopathological features in epithelial ovarian cancer. Tumour Biol 37:11259–11266. https://doi.org/10.1007/s13277-016-4993-2

    Article  CAS  PubMed  Google Scholar 

  139. van Jaarsveld MTM, Helleman J, Boersma AWM et al. (2013) miR-141 regulates KEAP1 and modulates cisplatin sensitivity in ovarian cancer cells. Oncogene 32:4284–4293. https://doi.org/10.1038/onc.2012.433

    Article  CAS  PubMed  Google Scholar 

  140. Sun C, Li N, Yang Z et al. (2013) miR-9 regulation of BRCA1 and ovarian cancer sensitivity to cisplatin and PARP inhibition. J Natl Cancer Inst 105:1750–1758. https://doi.org/10.1093/jnci/djt302

    Article  CAS  PubMed  Google Scholar 

  141. Brozovic A, Duran GE, Wang YC et al. (2015) The miR-200 family differentially regulates sensitivity to paclitaxel and carboplatin in human ovarian carcinoma OVCAR-3 and MES-OV cells. Mol Oncol 9:1678–1693. https://doi.org/10.1016/j.molonc.2015.04.015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Liu G, Da Yang, Rupaimoole R et al. (2015) Augmentation of response to chemotherapy by microRNA-506 through regulation of RAD51 in serous ovarian cancers. J Natl Cancer Inst 107. https://doi.org/10.1093/jnci/djv108

  143. Sun C, Cao W, Qiu C et al. (2020) MiR-509-3 augments the synthetic lethality of PARPi by regulating HR repair in PDX model of HGSOC. J Hematol Oncol 13:9. https://doi.org/10.1186/s13045-020-0844-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. He J, Jing Y, Li W et al. (2013) Roles and mechanism of miR-199a and miR-125b in tumor angiogenesis. PLoS ONE 8:e56647. https://doi.org/10.1371/journal.pone.0056647

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Dai J, Wei R, Zhang P et al. (2019) Overexpression of microRNA-195-5p reduces cisplatin resistance and angiogenesis in ovarian cancer by inhibiting the PSAT1-dependent GSK3β/β-catenin signaling pathway. J Transl Med 17:190. https://doi.org/10.1186/s12967-019-1932-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Chan JK, Kiet TK, Blansit K et al. (2014) MiR-378 as a biomarker for response to anti-angiogenic treatment in ovarian cancer. Gynecol Oncol 133:568–574. https://doi.org/10.1016/j.ygyno.2014.03.564

    Article  CAS  PubMed  Google Scholar 

  147. Santoiemma PP, Powell DJ (2015) Tumor infiltrating lymphocytes in ovarian cancer. Cancer Biol Ther 16:807–820. https://doi.org/10.1080/15384047.2015.1040960

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Gov E, Kori M, Arga KY (2017) Multiomics Analysis of Tumor Microenvironment Reveals Gata2 and miRNA-124-3p as Potential Novel Biomarkers in Ovarian Cancer. OMICS 21:603–615. https://doi.org/10.1089/omi.2017.0115

    Article  CAS  PubMed  Google Scholar 

  149. Chen X, Zhou J, Li X et al. (2018) Exosomes derived from hypoxic epithelial ovarian cancer cells deliver microRNAs to macrophages and elicit a tumor-promoted phenotype. Cancer Lett 435:80–91. https://doi.org/10.1016/j.canlet.2018.08.001

    Article  CAS  PubMed  Google Scholar 

  150. Curiel TJ, Coukos G, Zou L et al. (2004) Specific recruitment of regulatory T cells in ovarian carcinoma fosters immune privilege and predicts reduced survival. Nat Med 10:942–949. https://doi.org/10.1038/nm1093

    Article  CAS  PubMed  Google Scholar 

  151. Milne K, Köbel M, Kalloger SE et al. (2009) Systematic analysis of immune infiltrates in high-grade serous ovarian cancer reveals CD20, FoxP3 and TIA-1 as positive prognostic factors. PLoS ONE 4:e6412. https://doi.org/10.1371/journal.pone.0006412

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Okazaki T, Chikuma S, Iwai Y et al. (2013) A rheostat for immune responses: the unique properties of PD-1 and their advantages for clinical application. Nat Immunol 14:1212–1218. https://doi.org/10.1038/ni.2762

    Article  CAS  PubMed  Google Scholar 

  153. Buderath P, Mairinger F, Mairinger E et al. (2019) Prognostic significance of PD-1 and PD-L1 positive tumor-infiltrating immune cells in ovarian carcinoma. Int J Gynecol Cancer 29:1389–1395. https://doi.org/10.1136/ijgc-2019-000609

    Article  PubMed  Google Scholar 

  154. Hamanishi J, Mandai M, Iwasaki M et al. (2007) Programmed cell death 1 ligand 1 and tumor-infiltrating CD8+ T lymphocytes are prognostic factors of human ovarian cancer. Proc Natl Acad Sci U S A 104:3360–3365. https://doi.org/10.1073/pnas.0611533104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  155. Webb JR, Milne K, Kroeger DR et al. (2016) PD-L1 expression is associated with tumor-infiltrating T cells and favorable prognosis in high-grade serous ovarian cancer. Gynecol Oncol 141:293–302. https://doi.org/10.1016/j.ygyno.2016.03.008

    Article  CAS  PubMed  Google Scholar 

  156. Ghisoni E, Imbimbo M, Zimmermann S et al. (2019) Ovarian Cancer Immunotherapy: Turning up the Heat. Int J Mol Sci 20. https://doi.org/10.3390/ijms20122927

  157. Buderath P, Schwich E, Jensen C et al. (2019) Soluble Programmed Death Receptor Ligands sPD-L1 and sPD-L2 as Liquid Biopsy Markers for Prognosis and Platinum Response in Epithelial Ovarian Cancer. Front Oncol 9:1015. https://doi.org/10.3389/fonc.2019.01015

    Article  PubMed  PubMed Central  Google Scholar 

  158. Chatterjee J, Dai W, Aziz NHA et al. (2017) Clinical Use of Programmed Cell Death-1 and Its Ligand Expression as Discriminatory and Predictive Markers in Ovarian Cancer. Clin Cancer Res 23:3453–3460. https://doi.org/10.1158/1078-0432.CCR-16-2366

    Article  CAS  PubMed  Google Scholar 

  159. Sheu JJ-C, Shih I-M (2007) Clinical and biological significance of HLA-G expression in ovarian cancer. Semin Cancer Biol 17:436–443. https://doi.org/10.1016/j.semcancer.2007.06.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Yie S, Hu Z (2011) Human leukocyte antigen-G (HLA-G) as a marker for diagnosis, prognosis and tumor immune escape in human malignancies. Histol Histopathol 26:409–420. https://doi.org/10.14670/HH-26.409

    Article  CAS  PubMed  Google Scholar 

  161. Paul P, Rouas-Freiss N, Khalil-Daher I et al. (1998) HLA-G expression in melanoma: a way for tumor cells to escape from immunosurveillance. Proc Natl Acad Sci U S A 95:4510–4515. https://doi.org/10.1073/pnas.95.8.4510

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Carosella ED, Paul P, Moreau P et al. (2000) HLA-G and HLA-E: fundamental and Pathophysiological aspects. Immunol Today 21:532–534

    Article  CAS  PubMed  Google Scholar 

  163. Rebmann V, LeMaoult J, Rouas-Freiss N et al. (2007) Quantification and identification of soluble HLA-G isoforms. Tissue Antigens 69 Suppl 1:143–149. https://doi.org/10.1111/j.1399-0039.2006.763_5.x

    Article  CAS  PubMed  Google Scholar 

  164. Rebmann V, König L, Da Nardi FS et al. (2016) The Potential of HLA-G-Bearing Extracellular Vesicles as a Future Element in HLA-G Immune Biology. Front Immunol 7:173. https://doi.org/10.3389/fimmu.2016.00173

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Ullah M, Azazzen D, Kaci R et al. (2019) High Expression of HLA-G in Ovarian Carcinomatosis: The Role of Interleukin-1β. Neoplasia 21:331–342. https://doi.org/10.1016/j.neo.2019.01.001

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Menier C, Prevot S, Carosella ED et al. (2009) Human leukocyte antigen-G is expressed in advanced-stage ovarian carcinoma of high-grade histology. Hum Immunol 70:1006–1009. https://doi.org/10.1016/j.humimm.2009.07.021

    Article  CAS  PubMed  Google Scholar 

  167. Rolland P, Deen S, Scott I et al. (2007) Human leukocyte antigen class I antigen expression is an independent prognostic factor in ovarian cancer. Clin Cancer Res 13:3591–3596. https://doi.org/10.1158/1078-0432.CCR-06-2087

    Article  CAS  PubMed  Google Scholar 

  168. Han LY, Fletcher MS, Urbauer DL et al. (2008) HLA class I antigen processing machinery component expression and intratumoral T-Cell infiltrate as independent prognostic markers in ovarian carcinoma. Clin Cancer Res 14:3372–3379. https://doi.org/10.1158/1078-0432.CCR-07-4433

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Rutten MJ, Dijk F, Savci-Heijink CD et al. (2014) HLA-G expression is an independent predictor for improved survival in high grade ovarian carcinomas. J Immunol Res 2014:274584. https://doi.org/10.1155/2014/274584

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Schwich E, Rebmann V, Michita RT et al. (2019) HLA-G 3’ untranslated region variants +3187G/G, +3196G/G and +3035T define diametrical clinical status and disease outcome in epithelial ovarian cancer. Sci Rep 9:5407. https://doi.org/10.1038/s41598-019-41900-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Schwich E, Rebmann V, Horn PA et al. (2019) Vesicular-Bound HLA-G as a Predictive Marker for Disease Progression in Epithelial Ovarian Cancer. Cancers (Basel) 11. https://doi.org/10.3390/cancers11081106

  172. König L, Kasimir-Bauer S, Hoffmann O et al. (2016) The prognostic impact of soluble and vesicular HLA-G and its relationship to circulating tumor cells in neoadjuvant treated breast cancer patients. Hum Immunol 77:791–799. https://doi.org/10.1016/j.humimm.2016.01.002

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Gynecology and Obstetrics, University Hospital of Essen, Essen, Germany

    Carolin Salmon, Paul Buderath, Rainer Kimmig & Sabine Kasimir-Bauer

Authors
  1. Carolin Salmon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paul Buderath
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rainer Kimmig
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sabine Kasimir-Bauer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sabine Kasimir-Bauer .

Editor information

Editors and Affiliations

  1. Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, MO, USA

    Richard J. Cote

  2. ACTC Lab, Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Athens, Greece

    Evi Lianidou

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Salmon, C., Buderath, P., Kimmig, R., Kasimir-Bauer, S. (2023). Molecular Characterization of Single Circulating Tumor Cells in Breast and Ovarian Cancer. In: Cote, R.J., Lianidou, E. (eds) Circulating Tumor Cells. Current Cancer Research. Springer, Cham. https://doi.org/10.1007/978-3-031-22903-9_13

Download citation

Publish with us

Policies and ethics

Search

Navigation