Circulating Tumour DNA for Ovarian Cancer Diagnosis and Treatment Monitoring: What Perspectives for Clinical Use?
Abstract
1. Introduction
2. CtDNA in Ovarian Cancer
2.1. Diagnostic and Predictive Potential of ctDNA
2.2. Prognosis and Monitoring of Treatment Response Using ctDNA
2.3. Identifying Therapeutic Resistance Using ctDNA
2.4. Detection Techniques of ctDNA and Challenges in Ovarian Cancer
3. Discussion
4. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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---|---|---|---|---|---|---|---|---|---|
EOC/I–IV | P= 63 | 30–80 | Plasma | 21 gene panel, including TP53, CLDN19, ARID4B, etc. | NGS | Diagnosis = 93 Progression = 100 | NR | Prognostic: OS: HR = 6.60, p < 0.001 TTP: HR = 4.69, p < 0.001 | (Kallio et al., 2024) [13] |
High- and low-grade serous EOC/I–IV | P = 15 (Low grade = 1; High grade = 14) | 47–82 | Plasma | 275 cancer-associated genes, including TP53, KMT2A, NOTCH1, KDM5C, ARID1B, etc. | NGS | 100 | - | Diagnostic/Predictive/Longitudinal monitoring | (Kutz et al., 2024) [14] |
HGSOC/II–IV | P = 29 (Platinum resistant = 14; Platinum sensitive = 15) | Platinum resistant = 57–80 Platinum sensitive = 59–81 | Plasma | 700 cancer-associated genes, including TP53, KCNH2, JAK2, GRIN2A, FGFR3, ARID1B, etc. | NGS | Pre-treatment = 82.8, Relapse = 89.5 | NR | Prognostic: PFS: R = −0.72, p = 0.008 OS: R = −0.74, p = 0.005 | (Marchi et al., 2024) [15] |
EOC/I–IV | P = 296 B = 95 | 58.1 ± 12.3 (median) | Plasma | 9 gene panel, including TP53, BRCA1/2, PTEN, etc. | NGS | 89.9 | Sn = 92% Sp = 84% | Prognostic: PFS: HR = 10.71, 95% CI: 4.43–25.9 | (Heo et al., 2024) [16] |
EOC/I–IV | P = 591 HC = 204 B = 253 | P = 37–85 HC = 47–75 B = 19–92 | Plasma | cfDNA fragmentomes | WGS | NR | Sn = 72%, 69%, 87%, 100% Sp > 99% | Diagnostic | (Medina et al., 2024) [17] |
HGSOC/III–IV | P = 10 | NR | Plasma | 10 gene panel, including TP53, AKT1, KRAS, PIK3CA EGFR, etc. | Two NGS platforms plus ddPCR | Accel = 60 Oncomine = 100 | Oncomine: Sn ≥ 90%, Sp ≥ 99% Accel: Sn = 90% Sp ≥ 99% | Longitudinal monitoring/Predictive | (Calapre et al., 2023) [18] |
EOC/I–IV | P = 29 | 18–85 | Plasma | 50 gene panel, including TP53, KRAS, PIK3CA, etc. | NGS | 82.8 | NR | Prognostic: OS: HR = 6.56, 95% CI: 1.07–40.17 | (Chao et al., 2023) [19] |
EOC/I–IV | P = 41 B = 6 BOT = 9 | NR | Plasma | Mutant genes, including TP53, KRAS, PIK3CA, etc. | dPCR | 58 | NR | Prognostic: Log-rank test: OS (p = 0.008) | (Dobilas et al., 2023) [20] |
EOC/I–IV | P = 54 | 43–79 | Plasma | 531 gene panel, including TP53, BRCA1/2, CHEK2, etc. | NGS | 89.7 | NR | Prognostic: PFS (p = 0.0003) | (Kim et al., 2023) [21] |
HGSOC | P = 30 | 63 (median) | Plasma | BRCA1/2, TP53, TP53, PALB2, CCNE1, etc. | NGS | 74.4 | NR | Prognostic: DFS: HR = 4.79, 95% CI: 1.84–12.5 | (Lheureux et al., 2023) [22] |
HGSOC, LGSOC/I–III | P = 48 | 58.9 (median) | Plasma | 59 gene panel, including BRCA1/2, TP53, BRAF, RB1, etc. | NGS | 77.4 | NR | Prognostic: RFS: HR = 2.06, 95% CI: 0.60–7.10, p = 0.23 | (Zhu et al., 2023) [23] |
EOC/II–IV | P = 44 HC = 17 | NR | Plasma | CNV | LC-WGS | NR | NR | Diagnostic/Predictive | (Chen et al., 2023) [24] |
EOC/I–IV | P = 59 HC = 100 | 27–82 | Plasma | OC score (CNV, nucleosome footprint, 5′ end motifs, fragmentation profiles) | Low-pass WGS | I–II = 85.7 | Sn = 97.7% Sp = 94.7% | Diagnostic | (Zhou et al., 2023) [25] |
HGSOC/I–IV | P = 80 HC = 11 | <39 and ≥41 (median) | Plasma | ESR1 mutations | ddPCR | 13.8 | NR | Diagnostic | (Stergiopoulou et al., 2022) [26] |
EOC and non-EOC/I–IV | P = 271 B = 130 BOT = 41 Invasive = 92 Metastatic = 8 | B = 43–64, BOT = 37–63, Invasive = 57–73, Metastatic = 52–69 | Plasma | Nucleosome footprint and CNA | LC-WGS | NR | Nucleosome footprint: AUC = 0.71 (95% CI: 0.65–0.77) CNA: AUC = 0.72 (95% CI: 0.66–0.78) | Diagnostic | (Vanderstichele et al., 2022) [27] |
EOC/I–IV | P = 69 (Cohort A, pre-surgical = 44; Cohort B, post-surgical and/or after therapy = 12; Cohort C, after completed treatments = 13) | 29–82 (55.5 median) | Plasma | TP53, ARID1A, KRAS, etc. | Tumour-informed multiplex PCR NGS | Cohort A = 73 Cohort B = 33 Cohort B and C = 23 | Sn = 100 Sp = 100 | Prognostic: RFS: HR = 7.34, 95% CI: 0.75–72.3, p = 0.087 | (Hou et al., 2022) [28] |
EOC/II–IV | P = 18 (6 paired ascites and 8 paired tumour tissues) | 24–70 | Plasma | 333 cancer-related genes, including TGFBR2, ARID1A, ATR, BCR, KMT2C, etc. | NGS | 94.4 | NR | Diagnostic/Predictive | (Jie et al., 2022) [29] |
HGSOC/III–IV | P = 18 | 48–79 | Plasma | 65 cancer-related genes, including TP53, BRCA1/2, POLE, MSH3, ATR, etc. | NGS | NR | NR | Diagnostic/Predictive | (Paracchini et al., 2022) [30] |
EOC/II–IV | P = 6 | 38–78 | Plasma | CNA | WGS | NR | NR | Prognostic: OS (p < 0.0001) | (Sharbatoghli et al., 2022) [31] |
HGSOC, LGSOC, Clear cell, endometrioid, carcinosarcoma | P = 24 | 21–71 | Plasma | Identified CNAs and mutations in other cancer-related genes such as TP53 | WGS, WES | 88 | NR | Prognostic: PFS (TMB: HR = 8.6, 95% CI: 1.4–52; GAF: HR = 8.9, 95% CI: 0.91–87) | (Sabatier et al., 2022) [32] |
EOC/III–IV | P = 109 (Upfront group = 23; CTX group = 9; Follow-up group = 13) | 22–84 | Plasma | CNV (CNI scores) | WGS | Chemo naive = 78, Platinum-eligible recurrent = 83.3, Non-platinum-eligible recurrent = 82.6 | Sn: primary and recurrent = 87%, primary only = 78–91% Sp = 95–100% | Diagnostic | (Braicu et al., 2021) [33] |
SOC/I, III, and IV | P = 138 | 31–81 | Plasma | 150 cancer gene panel, including TP53, KRAS, LRP1B, ZNF703, NF1, etc. | Hybrid capture-based NGS | 83 | NR | Diagnostic | (Shen et al., 2021) [34] |
HGSOC/III–IV | P = 46 | 21–81 | Plasma | CNA | Shallow WGS | 14.47 | NR | Prognostic: PFS: HR = 3.31, 95% CI: 1.33–9.13, p = 0.011 | (Paracchini et al., 2021) [35] |
EOC and non-EOC/I–IV | P = 80 (Malignant = 58 B = 66; BOT = 10) HC = 82 | Malignant = 12–77, B = 21–82, BOT = 27–62, HC = 22–36 | Plasma | CNA | WGS | NR | NR | Diagnostic | (Zhang et al., 2021) [36] |
HGSOC/III–IV | P = 20 | 37–75 | Serum | Total of 51 genes: 41 for Ampliseq and 10 for Oncomine, including TP53, PIK3CA, ESR1, etc. | NGS, ddPCR | 85 | NR | Diagnostic/Predictive | (Vitale et al., 2020) [37] |
EOCs/III–IV | P = 39 | NR | Plasma | ALU | qPCR | NR | NR | Diagnostic | (Waki et al., 2020) [38] |
EOC/I–IV | P = 51 | 28–82 | Plasma | 197 cancer-related genes, including TP53, APC, KRAS, EGFR, MET, PIK3CA, etc. | Deep NGS (CAPP-Seq) | 94 | NR | Prognostic: PFS (p = 0.048) | (Noguchi, Iwahashi, et al., 2020) [39] |
HGSOC and mucinous/III–IV | P = 10 | 44–74 | Plasma | 197 cancer-related genes, including TP53, APC, KRAS, EGFR, MET, PIK3CA, etc. | Deep NGS (CAPP-Seq) | 100 | NR | Diagnostic | (Noguchi, Sakai, et al., 2020) [40] |
HGSOC/III–IV | P = 7 | 54–78 | Plasma | 26 genes, including TP53, APC, KRAS, PTEN, PIK3CA, etc. | NGS | 86 | NR | Diagnostic/Predictive | (Jagelkova et al., 2020) [41] |
HGSOC/III–IV | P = 10 | 44–65 | Plasma | 88 genes, including TP53, PIK3CA, MYC, etc. | NGS | 60 | NR | Diagnostic | (Han et al., 2020) [42] |
EOC/I–IV | P = 306 | 33–80 | Plasma | 2 genes: KRAS and PIK3CA | ddPCR | 27.1 | NR | Prognostic: PFS (p = 0.0001) OS (p = 0.017) | (Ogasawara et al., 2020) [43] |
High- and low-grade serous EOC/I–IV | P = 70 | NR | Plasma | CNV | WGS | Stage (I and II) = 55.56 Stage (III and IV) = 85.71 | NR | Diagnostic/Predictive | (Wang et al., 2020) [44] |
EOC/I–IV | P = 37 HC = 28 | HC = 30–63 OC = 37–80 | Plasma | ALU, LINE 1 | qRT-PCR | NR | NR | Diagnostic | (Stamenkovic et al., 2020) [45] |
EOCs (96% HGSOC) | P = 112 | 33–82 | Plasma | 54 cancer-related genes, including BRAC1, BRAC2, TP53, etc. | NGS | TP53 = 96 | NR | Prognostic: PFS: HR = 0.12 (p < 0.0001) | (Lin et al., 2019) [46] |
HGSOC/II–IV | P = 12 | 68 (median) | Plasma | CNV and >500 cancer-related genes, including TP53, PTEN, BRCA2, etc. | NGS | 100 for TP53 and variable for the other genes | NR | PFS (p < 0.01) | (Oikkonen et al., 2019) [47] |
OC Subtype & Stage | Patient/ Controls | Age (yrs) | Plasma/ Serum | Biomarker | Detection Method | Detection Rate (%) | Sensitivity and Specificity | Clinical Value | Refs |
---|---|---|---|---|---|---|---|---|---|
EOC/I–IV | P = 70 B = 39 HC = 4 | OC = 52–64, Controls = 48–66 | Plasma | ZNF154, C2CD4D, and WNT6 | Bisulphite sequencing | 82.8 | Sn = 80% Sp = 97.6% | Diagnostic | (Herzog et al., 2024) [48] |
EOCs | P = 19 | 38–86 | Plasma | Alu115, IFFO1, and CDH5 promoters | Methylation-specific qPCR | Alu115 = 100, IFFO1Me = 66, CDH5UM = 86 | NR | Prognostic: PFI: HR = 3.21, 95% CI: 1.15–9.00, p = 0.008 | (Werner, Sjoquist, et al., 2024) [49] |
EOC/I–IV | P = 125 HC = 72 | Non-malignant = 25–85, Cancer = 21–83 | Plasma | miR-200c and miR-141 genes | Methylation-specific PCR | NR | NR | Prognostic: OS: HR = 1.53, 95% CI: 1.0–2.35, p = 0.049 | (Gahlawat et al., 2023) [50] |
EOC/II–III | P = 5 HC = 12 | P = 66.2 ± 18.14; HC: 67.8 ± 12.96 (median) | Plasma | ANO2, ATP11A, AGAP1, ARFGEF2, BBS9, etc. | AI and GW-DMP | 100 | GW-DMP: Sn = 95%, Sp = 100%; AI: Sn = 100%, Sp = 88% | Diagnostic | (Bahado-Singh et al., 2022) [51] |
EOC/I–IV | P = 79 HC = 64 | 25–86 | Plasma | HOXA9 | Methylation-specific ddPCR | 59.5 | Sn = 37.5–59.5% Sp = 95.3% | Diagnostic | (Faaborg et al., 2021) [52] |
EOC/I–IV | P = 85 | 20–65 | Serum | RASSF1A, DAPK1, SOX1, HOXA9, HIC1, SPARC, and SFRP1 | Multiplex methylation-specific qPCR | 82.3–61.3 | Varies with each gene. Sn = 85.88–72.94% Sp = 88.57–77.14% | Diagnostic | (Singh et al., 2021) [53] |
EOC/I–IV, platinum resistant | P = 32 | 46–70 | Plasma | HOXA9 | Methylation-specific ddPCR | 62 | NR | Prognostic: PFS (p < 0.0001) OS (p = 0.002) | (Rusan et al., 2020) [54] |
EOC/I–IV | P = 44 | 18–70 | Serum | HOXA9 and HLC1 | Multiplex methylation-specific qPCR | HOXA9 = 62.2 HLC1 = 71.1 | Sn = 88.9% Sp = 100% | Diagnostic | (Singh et al., 2020) [55] |
EOC/I–III | P = 17 B = 15 HC = 15 A = OC group (P) B = Control group (B and HC) | 32–68 | Plasma | hTERT | Methylation-specific PCR | Group A = 70.6 Group B = 20 | Group A: Sn = 76.9% Sp = 50%; Group B: Sn = 50% Sp = 90.9% | Diagnostic | (Li et al., 2020) [56] |
EOC/I, III, and IV, platinum resistant | P = 23 | 41–81 | Plasma | HOXA9 | Methylation-specific dPCR | NR | NR | Prognostic: OS (p = 0.01) | (Thomsen et al., 2019) [57] |
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Asante, D.-B.; Tierno, D.; Grassi, G.; Scaggiante, B. Circulating Tumour DNA for Ovarian Cancer Diagnosis and Treatment Monitoring: What Perspectives for Clinical Use? Int. J. Mol. Sci. 2025, 26, 1889. https://doi.org/10.3390/ijms26051889
Asante D-B, Tierno D, Grassi G, Scaggiante B. Circulating Tumour DNA for Ovarian Cancer Diagnosis and Treatment Monitoring: What Perspectives for Clinical Use? International Journal of Molecular Sciences. 2025; 26(5):1889. https://doi.org/10.3390/ijms26051889
Chicago/Turabian StyleAsante, Du-Bois, Domenico Tierno, Gabriele Grassi, and Bruna Scaggiante. 2025. "Circulating Tumour DNA for Ovarian Cancer Diagnosis and Treatment Monitoring: What Perspectives for Clinical Use?" International Journal of Molecular Sciences 26, no. 5: 1889. https://doi.org/10.3390/ijms26051889
APA StyleAsante, D.-B., Tierno, D., Grassi, G., & Scaggiante, B. (2025). Circulating Tumour DNA for Ovarian Cancer Diagnosis and Treatment Monitoring: What Perspectives for Clinical Use? International Journal of Molecular Sciences, 26(5), 1889. https://doi.org/10.3390/ijms26051889