Role of Circulating Biomarkers in Platinum-Resistant Ovarian Cancer
Abstract
:1. Introduction
2. Methods
3. Circulating Biomarkers
3.1. Glycoprotein Biomarkers
3.1.1. CA125
3.1.2. HE4
3.1.3. Mesothelin
3.2. Liquid Biopsy
3.2.1. Circulating Tumor DNA
3.2.2. Circulating Tumor Cells
3.2.3. Extracellular Vesicles
3.3. Epigenetic and Genetic Biomarkers
3.3.1. Epigenetic Alteration Markers
MicroRNAs
DNA Methylation
Histone Modifications and Involved Enzymes
3.3.2. Genetic Alteration Markers
TP53 Mutations
Homologous Recombination and BRCA Genes
3.4. Angiogenic Biomarkers
3.5. Immune-Related Biomarkers
4. Conclusions and Future Directions
Author Contributions
Funding
Conflicts of Interest
References
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Circulating Biomarkers and Liquid Biopsy | Tumor Biopsy |
---|---|
Material derived from cancer detectable in bloodstream, urine, or peritoneal fluid | Material obtained from a sampling of tissue lesion |
Non-invasive procedure | High invasive procedure |
Real-time follow up | Impracticable for real-time follow up |
Quick and easily repeatable procedure for obtaining the samples | Difficult to repeat and depend on the correctness of the procedure |
No surgical complication or pain | Risk of surgical complication and pain |
Lack of well-defined practice rules and standardizing protocols | Clinically validated and standard for histologic diagnosis |
Less cost (with some exceptions) | High cost |
Assessment of tumor heterogeneity in different phases of the disease | Failure to reflect tumor heterogeneity |
Low concentrations and easily degradable material | Higher concentration and fixed material |
Less specificity | Higher specificity |
Specialized laboratory | Histology laboratory |
Type of Circulating Biomarker | |
---|---|
Glycoprotein Biomarkers | CA 125 |
HE4 | |
Mesothelin | |
Liquid Biopsy | ctDNA |
CTCs | |
EVs | |
Epigenetic and Genetic Markers | miRNA |
DNA methylation | |
Histone modification | |
TP53 mutation | |
HRD-BRCA1/2 mutation | |
Immune-Related Biomarkers | NLR |
PLR | |
Circulating T-cell | |
Circulating B-cell | |
sPD-1/sPD-L1 | |
MDSC4 | |
NMLR | |
Angiogenic Markers | sVEGF |
Author, Year | Material and Methods | Results | Conclusions |
---|---|---|---|
Kuhlmann JD. 2014 [66] |
| Platinum resistance ERCC1+ CTCs vs. ERCC1−CTC OR, 8.5 (1.7–43.6), p = 0.01 | The presence of CTCs expressing ERCC1 is an independent predictor of platinum resistance |
Obermayr E. 2013 [67] |
| Frequency of CTCs with overexpression of PPIC gene in PtR vs. platinum sensible patients at follow up: 35.7% vs. 10.1%, p = 0.024 | CTCs with overexpression of PPIC gene correlate with platinum resistance |
Poveda A. 2011 [68] |
| -PFS ≥2 CTCs vs. <2 CTCs: 3.2 months vs. 6.6 months; p = 0.0024. -OS ≥ 2 CTCs vs. <2 CTCs: 12.4 months vs. 20.6 months; p = 0.0017. -Multivariate analysis: PFS HR 1.58 (0.99–2.53) p = 0.058 -Multivariate analysis: OS HR 1.54 (0.93–2.54) p = 0.096 | Levels of CTCs seem to correlate with platinum resistance and worse survival, but data are inconsistent |
Lee M. 2017 [69] |
| -OS pts with CTCs cluster vs. pts without CTCs cluster: 21 vs. 74 months, p = 0.008. -Multivariate analysis OS: HR 1.3 (0.94–17.149) p = 0.94 −65.2% of patients with CTCs cluster showed platinum resistance (p = 0.001). | Levels of CTCs seem to correlate with platinum resistance and worse survival, but data are inconsistent |
Author, Year | Material and Methods | Results | Conclusions |
---|---|---|---|
Benson EA. 2015 [106] |
|
| miRNA analysis predicts the response to chemotherapy and prognosis. |
Vigneron N. 2020 [107] |
| OS miRNA > 0.34 zmol/mL vs. <0.34 zmol/mL: 7.9 months vs. 20.6 months, HR 3.15, p = 0.006 | miRNA analysis predicts prognosis |
Author, Year | Material and Methods | Results | Conclusions |
---|---|---|---|
Losi L. 2018 [111] |
| % of hypermethylated promoter genes:
| OC is characterized by a slight increase of hypermethylation |
De Caceres II. 2004 [110] |
| % of hypermethylated BRCA 1 and/or RASSF1A: 68% (regardless FIGO stage) vs. 0% in control group. | Promoter hypermethylation is a common and relatively early event in ovarian tumorigenesis |
Cacan E. 2016 [112] |
| The expression of positive co-stimulatory molecules of T cell, OX-40L and 4-1BBL, is suppressed due to DNA hypermethylation and histone deacetylation in chemo-resistant cells compared to parental chemo-sensitive OC cells. | Hypermethylation correlates with chemo-resistance in OC |
Gifford G. 2004 [113] |
|
| The acquisition of hMLH1 methylation in plasma DNA after chemotherapy predicts poor survival for ovarian cancer patients |
Teschendorff AE. 2009 [109] |
|
| Hypomethylation is correlated with OC |
Liao P. 2014 [114] |
| In case of hypomethylation of ATG4A and HIST1H2BN in OTICs:
| In OTICs, hypomethylation of ATG4A and HIST1H2BN is associated with poor prognosis |
Author, Year | Material and Methods | Results | Conclusions |
---|---|---|---|
Zhu Y. 2018 [198] |
| PLR > cut off - OS: metaHR 2.53 (2.16–2.96) - PFS: metaHR 2.48, (2.10–2.96) NLR > cut off - OS: metaHR 2.21 (1.95–2.52) - PFS: metaHR 1.36 (1.17–1.57) | Higher value of PLR and NLR are associated with worse ovarian cancer survival |
Miao Y. 2016 [199] |
| Predictive values for platinum resistance: - PLR > 207: SN 60.42%, SP 85.48%, p < 0.001 - NLR > 3.02: SN 75%, SP 81.45%, p < 0.001 | Assessment of NLR and PLR has potential clinical value in predicting platinum resistance in patients with EOC |
Kim HS. 2016 [200] | 109 pts with CCOC (18.3% PtR) | PLR ≥ 205.4 predicted non-CR (accuracy, 71.6%) Predictive values for platinum resistance: - NLR ≥ 2.8: SN 68.4%, SP 65.1%, p < 0.01 - PLR ≥ 178.3: SN 68.4, SP 55.4%, p = 0.02 | NLR and PLR value correlate with platinum resistance in patients with CCOC |
Diagnostic Value | Prognostic Value | Predictive Value | Currently Used in Clinical Practice | Limits | |
---|---|---|---|---|---|
Glicoprotein markers | Low specificity | ||||
ctDNA | High fragmentation, low stability, and low quantity in bloodstream | ||||
CTCs | Controversial data, scarcity in the bloodstream. Short half-life after blood draw | ||||
EVs | Need of clinically validated test | ||||
Micro RNAs | High cost and scarce availability of the test | ||||
DNA methilation | Less sensitive test | ||||
Histone modification | Need of further investigation about treatment efficacy | ||||
TP53 (Ab and ctDNA) | Scarce data from PtR OC | ||||
BRCA (somatic and germinal) | Reversion mutation | ||||
Immune related biomarkers | Low specificity, not universally established cut off, scarce data from PtR OC | ||||
Angiogenic markers | Scarce and controversial data |
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Sassu, C.M.; Palaia, I.; Boccia, S.M.; Caruso, G.; Perniola, G.; Tomao, F.; Di Donato, V.; Musella, A.; Muzii, L. Role of Circulating Biomarkers in Platinum-Resistant Ovarian Cancer. Int. J. Mol. Sci. 2021, 22, 13650. https://doi.org/10.3390/ijms222413650
Sassu CM, Palaia I, Boccia SM, Caruso G, Perniola G, Tomao F, Di Donato V, Musella A, Muzii L. Role of Circulating Biomarkers in Platinum-Resistant Ovarian Cancer. International Journal of Molecular Sciences. 2021; 22(24):13650. https://doi.org/10.3390/ijms222413650
Chicago/Turabian StyleSassu, Carolina Maria, Innocenza Palaia, Serena Maria Boccia, Giuseppe Caruso, Giorgia Perniola, Federica Tomao, Violante Di Donato, Angela Musella, and Ludovico Muzii. 2021. "Role of Circulating Biomarkers in Platinum-Resistant Ovarian Cancer" International Journal of Molecular Sciences 22, no. 24: 13650. https://doi.org/10.3390/ijms222413650
APA StyleSassu, C. M., Palaia, I., Boccia, S. M., Caruso, G., Perniola, G., Tomao, F., Di Donato, V., Musella, A., & Muzii, L. (2021). Role of Circulating Biomarkers in Platinum-Resistant Ovarian Cancer. International Journal of Molecular Sciences, 22(24), 13650. https://doi.org/10.3390/ijms222413650