| Literature DB >> 34948446 |
Carolina Maria Sassu1, Innocenza Palaia1, Serena Maria Boccia1, Giuseppe Caruso1, Giorgia Perniola1, Federica Tomao1, Violante Di Donato1, Angela Musella1, Ludovico Muzii1.
Abstract
Ovarian cancer (OC) is the second most common cause of death in women with gynecological cancer. Considering the poor prognosis, particularly in the case of platinum-resistant (PtR) disease, a huge effort was made to define new biomarkers able to help physicians in approaching and treating these challenging patients. Currently, most data can be obtained from tumor biopsy samples, but this is not always available and implies a surgical procedure. On the other hand, circulating biomarkers are detected with non-invasive methods, although this might require expensive techniques. Given the fervent hope in their value, here we focused on the most studied circulating biomarkers that could play a role in PtR OC.Entities:
Keywords: circulating biomarker; drug response biomarker; liquid biopsy; platinum-resistant ovarian cancer; prognosis
Mesh:
Substances:
Year: 2021 PMID: 34948446 PMCID: PMC8707281 DOI: 10.3390/ijms222413650
Source DB: PubMed Journal: Int J Mol Sci ISSN: 1422-0067 Impact factor: 5.923
Figure 1Potential values of biomarkers in PtR OC.
Characteristics of circulating biomarkers and tumor biopsy.
| Circulating Biomarkers | 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 |
Discussed circulating biomarkers in OC.
| Type of Circulating Biomarker | |
|---|---|
|
| CA 125 |
| HE4 | |
| Mesothelin | |
|
| ctDNA |
| CTCs | |
| EVs | |
|
| miRNA |
| DNA methylation | |
| Histone modification | |
| TP53 mutation | |
| HRD-BRCA1/2 mutation | |
|
| NLR |
| PLR | |
| Circulating T-cell | |
| Circulating B-cell | |
| sPD-1/sPD-L1 | |
| MDSC4 | |
| NMLR | |
|
| sVEGF |
Abbreviations: BRCA Breast Cancer susceptibility gene, CTCs Circulating Tumor Cells, ctDNA Circulating Tumor DNA, EVs Extracellular Vesicles, HE Human Epididymis Protein 4, HRD Homologous Recombination Deficiency, MDSC4 Circulating Myeloid-Derived Suppressor Cells type 4, miRNAs Micro RNAs, NLR Neutrophil-Lymphocyte ratio, NMLR Neutrophil-and-Monocyte to Lymphocyte Ratio, PLR Platelet-Lymphocyte Ratio, sPD-1 soluble form of Programmed Cell Death Protein 1, sPD-L1 soluble form of Programmed cell Death Protein Ligand 1, sVEGF soluble form of Vascular Endothelial Growth Factor.
Figure 2Circulating biomarkers in PtR OC.
Figure 3Liquid Biopsy: what is assessed and methods of detection.
Most relevant evidence about the role of CTCs in PtR OC.
| Author, Year | Material and Methods | Results | Conclusions |
|---|---|---|---|
| Kuhlmann JD. |
143 new diagnosed EOC pts. Immunomagnetic CTCs enrichment targeting EPCAM and mucin 1 followed by multiplex reverse transcription PCR. Classified according to the presence of CTCs expressing ERCC1 (ERCC1+ CTCs vs. ERCC1−CTCs). | The presence of CTCs expressing ERCC1 is an independent predictor of platinum resistance | |
| Obermayr E. |
216 pts with EOC. RT-qPCR analysis of EpCAM in CTCs at follow up. | CTCs with overexpression of PPIC gene correlate with platinum resistance | |
| Poveda A. |
216 pts ROC (PtR 34%) treated with PLD ± trabectedine CTCs isolated from blood using Cell Search system and reagents (Veridex) Classified according to CTCs at baseline: CTCs ≥ 2 vs. CTCs < 2. | - | Levels of CTCs seem to correlate with platinum resistance and worse survival, but data are inconsistent |
| Lee M. |
30 pts with ROC (PtR 60%) Fresh peripheral blood samples collected in EDTA vacutainer tubes, engaging of biotin-doped PPy-deposited microfluid device, polydimethylsiloxane microchannels coniugated with streptavidin and exposed to antibodies against EpCAM, TROP2, EGFR, vimentin, and N cadherin. Classified according to CTCs cluster positivity. | - | Levels of CTCs seem to correlate with platinum resistance and worse survival, but data are inconsistent |
Abbreviations: CTCs Circulating Tumor Cells, EDTA Ethylenediaminetetraacetic acids, EGFR Epidermal Growth Factor Receptor, EOC Epithelial Ovarian Cancer, EpCAM Epithelial Cellular Adhesion Molecule, ERCC Excision Repair 1 protein, HR Hazard Ratio, OR Odds Ratio, OS Overall Survival, PFS Progression Free Survival, PLD Pegylated Liposomal Doxorubicin, PPIC Cyclophilin C gene, PtR Platinum resistant, Pts Patients, ROC Recurrent Ovarian Cancer, RT-qPCR Real-Time quantitative Polymerase Chain Reaction, TRP-2 Tyrosinase-related protein 2.
Most relevant evidence about the potential value of miRNA in PtR OC.
| Author, Year | Material and Methods | Results | Conclusions |
|---|---|---|---|
| Benson EA. |
14 pts with PtR ROC Evaluation of plasma miRNAs in predicting the response to carboplatin and decitabine |
10 miRNAs changed in concentration at the end of the first cycle of treatment (ranging from 2.9 to 4, Lower concentrations miR-148b-5p predicted worse PFS ( | miRNA analysis predicts the response to chemotherapy and prognosis. |
| Vigneron N. |
35 pts with ROC (16.9% PtR) Evaluation of miR-622 levels at relapse Classification according to Levels: >0.34 zmol/mL vs. <0.34 zmol/mL | OS miRNA > 0.34 zmol/mL vs. <0.34 zmol/mL: | miRNA analysis predicts prognosis |
Abbreviations: miRNA micro Ribonucleic Acid, OS Overall Survival, PFS Progression-Free Survival, PtR Platinum-Resistant, Pts Patients, ROC Recurrent Ovarian Cancer.
Most relevant evidence about the value of methylation alteration in OC.
| Author, Year | Material and Methods | Results | Conclusions |
|---|---|---|---|
| Losi L. |
102 OC vs. 17 normal ovarian samples Analysis of promoter regions of 41 genes DNA methylation profiling through the MLM | % of hypermethylated promoter genes: In normal ovarian tissues: 29% In serous, endometrioid, and mucinous carcinomas: 32%, 34%, and 45%, respectively. | OC is characterized by a slight increase of hypermethylation |
| De Caceres II. |
50 pts with new diagnosed OC or PPC (Stage I-IV) vs. 40 healthy women (control group) Specimens/serum/peritoneal fluid Sensitive methylation-specific PCR | % of hypermethylated BRCA 1 and/or RASSF1A: | Promoter hypermethylation is a common and relatively early event in ovarian tumorigenesis |
| Cacan E. |
Chemo-resistant OC cells vs. chemo-sensitive OC cells Cell-surface staining through primary labeled antibodies: phycoerythrin-conjugated OX-40L, 4-1BBL, PD-L1, MHC-I | 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. |
138 OC pts from SCOTROC1 trial (paired samples) Evaluation of methylation of the hMLH1 in plasma before the chemotherapy and at recurrence |
Methylation of hMLH1 is increased at relapse 25% (34 of 138) of relapse samples have hMLH1 methylation that is not detected in matched pre-chemotherapy plasma samples hMLH1 methylation in cfDNA at relapse correlated with poor survival: HR 1.83, Patients with hMLH1 methylation and PFS < 6 months from last platinum were more in percentage than patients without the epigenetic alteration (45% vs. 39%) | The acquisition of hMLH1 methylation in plasma DNA after chemotherapy predicts poor survival for ovarian cancer patients |
| Teschendorff AE. |
113 OC pts (vs. 148 healthy controls) 27,000 CpGs screened |
2714 cancer-related CpGs were identified 56% of cancer-related CpGs were hypomethylated Amongst the 50 CpGs with the highest correlation to cancer, as much as 87% were hypomethylated. | Hypomethylation is correlated with OC |
| Liao P. |
168 tissue samples from patients with OC Evaluation of DNA methylation in OTICs through qRT–PCR, quantitative methylation-specific PCR, and pyrosequencing | In case of hypomethylation of ATG4A and HIST1H2BN in OTICs:
PFS: HR, 1.8 (1.0–3.6) OS: HR, 1.7 (1.0–3.0) [ | In OTICs, hypomethylation of ATG4A and HIST1H2BN is associated with poor prognosis |
Abbreviations: ATG4A Autophagy Related 4A Cysteine Peptidase gene, BRCA Breast Cancer gene, cfDNA cell-free DNA, DNA Deoxyribonucleic acid, HIST1H2BN Histone H2B type 1-N, hMLH1 MutL homolog 1, HR Hazard Ratio, MHC-I Major Histocompatibility Complex Class I, MLM Methylation Ligation-dependent Macroarray, OC Ovarian Cancer, OS Overall Survival, OTICs ovarian tumor-initiating cells, OX-40L OX40 Ligand, PCR Polymerase Chain Reaction, PD-L1 Programmed cell Death Protein Ligand 1, PFS Progression-Free Survival, PPC Primary Peritoneal Cancer, Pts patients, RASSF1A Ras Association Domain Family 1 Isoform A, RT-qPCR Real-Time quantitative Polymerase Chain Reaction, SCOTROC1 Scottish Randomised Trial in Ovarian Cancer 1, 4-1BBL 4-1BB Ligand.
Figure 4HRD and BRCA1/2 mutation in HGSOC. Approximately 50% of HGSOCs have homologous recombination deficiency (HRD). Among genes, BRCA1/2 are the most common involved: about 14% of HGSOC patients were reported to have BRCA1/2 mutation detectable in a blood sample (germinal mutation, analysis of peripheral Lymphocytes). While a BRCA1/2 mutation found only in a tissue sample is present in about 20% of the affected women (somatic mutation). Other genes with a role in HRD are CDK12 (3% of cases), RAD51C (2%), EMSY (6%), and PTEN (7%).
Most relevant evidence about the potential role of PLR and NLR in PtR OC.
| Author, Year | Material and Methods | Results | Conclusions |
|---|---|---|---|
| Zhu Y. |
2919 pts with OC (meta-analysis) * Correlation between level of PLR and NLR > cut off and survival | Higher value of PLR and NLR are associated with worse ovarian cancer survival | |
| Miao Y. |
344 pts with OC (28% PtR) * (216 serous OC) Evaluation of NLR and PLR | Assessment of NLR and PLR has potential clinical value in predicting platinum resistance in patients with EOC | |
| Kim HS. | 109 pts with CCOC (18.3% PtR) | PLR ≥ 205.4 predicted non-CR (accuracy, 71.6%) | NLR and PLR value correlate with platinum resistance in patients with CCOC |
* The meta-analysis also includes 344 OC pts from Miao Y et al., 2016 [199]. Abbreviations: CCOC Clear Cell Ovarian Cancer, CR Complete response, EOC Epithelial Ovarian Cancer, HR Hazard Ratio, NLR Neutrophil-Lymphocyte Ratio, OC Ovarian Cancer, OS Overall Survival, PFS Progression-Free Survival, PLR Platelet-Lymphocyte Ratio, PtR Platinum resistant, Pts Patients, SN Sensitivity, SP Specificity.
Circulating biomarkers in PtR OC, their potential role and limits.
| Diagnostic Value | Prognostic Value | Predictive Value | Currently Used in Clinical Practice | Limits | |
|---|---|---|---|---|---|
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| Low specificity | |
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| High fragmentation, low stability, and low quantity in bloodstream | ||
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| Controversial data, scarcity in the bloodstream. | ||
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| Need of clinically validated test | ||
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| High cost and scarce availability of the test | |
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| Less sensitive test | ||
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| Need of further investigation about treatment efficacy | |||
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| Scarce data from PtR OC | ||
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| Reversion mutation | |
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| Low specificity, not universally established cut off, scarce data from PtR OC | |
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| Scarce and controversial data |
Abbreviations: Ab Antibodies, BRCA Breast Cancer gene, CTCs Circulating Tumor Cells, ctDNA Circulating Tumor DNA, EVs Extracellular Vesicles, OC Ovarian Cancer, PtR Platinum-Resistant.