Circulating Tumor DNA Is a Variant of Liquid Biopsy with Predictive and Prognostic Clinical Value in Breast Cancer Patients
Abstract
:1. Introduction
1.1. The Current State of the Problem of Breast Cancer around the World
1.2. Determination of Circulating Tumor DNA Is a New Approach
2. Circulating Tumor DNA: What Is It?
2.1. Circulating Tumor DNA Is a Variant of Liquid Biopsy
2.2. Circulating Tumor DNA and Its Main Features
2.3. Basic Methods for Studying ctDNA
2.3.1. PCR-Based Methods
2.3.2. NGS-Based Methods
2.3.3. Combined and New Approaches
2.4. Possible Applications of ctDNA in Oncology
3. Clinical Value of ctDNA in Breast Cancer Patients
3.1. Application of ctDNA for Early Detection/Screening of Breast Cancer
3.2. ctDNA as a Predictive and Prognostic Marker in Breast Cancer Treatment
3.2.1. Two Main Approaches to Determining ctDNA in Breast Cancer
3.2.2. Clinical Value of ctDNA Determination for Breast Cancer Treatment
Early Detection of Recurrence/Progression of Breast Cancer
ctDNA as a Surrogate Marker for Minimal Residual Disease after Primary Treatment for Breast Cancer
ctDNA Mutations as Prognostic and Predictive Factors for the Effectiveness of Therapy
4. Conclusions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
BC | Breast Cancer |
BEAMing | Beads, Emulsion, Amplification, Magnetics |
CAPP-Seq | CAncer Personalized Profiling by deep Sequencing |
cfDNA | Cell-Free DNA |
cfNA | Cell-Free Nucleic Acids |
CTC | Circulating tumor cells |
ctDNA | Circulating tumor DNA |
dPCR | Digital Polymerase Chain Reaction |
ddPCR | digital droplet Polymerase Chain Reaction |
DFS | Disease-Free Survival |
HR | Hazard Ratio |
MAF | Mutant Allele Fraction |
MS-ddPCR | Methylation-Specific digital droplet PCR |
MRD | Minimal Residual Disease |
mTBI | Molecular Tumor Burden Index |
NAC | Neoadjuvant Chemotherapy |
NGS | Next Generation Sequencing |
OS | Overall Survival |
PCR | Polymerase Chain Reaction |
pCR | Pathological Complete Response |
PFS | Progression-Free Survival |
SNV | Single Nucleotide Variants |
WGS | Whole Genome Sequencing |
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Target | Method | Example Assay | Sensitivity (%) | Advantages | Limitations |
---|---|---|---|---|---|
Single locus | Digital PCR | ddPCR, BEAMing | 0.01 | High sensitivity | Detects only known mutations |
Low DNA input | |||||
Provides quantification and monitoring of recurrent mutations | |||||
Gene panel | Targeted panel sequencing | TAM-Seq, Safe-SeqS | 0.01–1 | High sensitivity | Less comprehensive than other NGS methods |
Fast | |||||
Cost-effective compared with other NGS methods | |||||
Targeted digital sequencing | TARDIS | 0.03–1 | High sensitivity | More complex workflow | |
Hybrid capture sequencing | CAPP-Seq | 0.02 | Able to detect copy number variations and rearrangements | Requires high cfDNA input | |
Less comprehensive | |||||
More complex workflow | |||||
Comprehensive | Whole-exome sequencing Whole-genome sequencing | 1–10 | Identifies novel mutations | Less sensitive | |
Does not require prior information about the tumor mutation | Expensive | ||||
Longer turnaround time |
Authors | Date of Publication | Analysis | Reference |
---|---|---|---|
ctDNA Studies Using Point Mutation Analysis | |||
Fribbens, C. et al. | 2016 | ESR1 mutations | [20] |
Riva, F. et al. | 2017 | TP53 mutations | [54] |
Tolaney, S. et al. | 2022 | PIK3CA and ESR1 mutations | [56] |
Sabatier, R. et al. | 2022 | PI3KCA, AKT1, and TP53 mutations | [57] |
Di Leo, A. et al. | 2018 | PIK3CA mutations | [59] |
Chin, Y. et al. | 2021 | 57 SNV * the majority were in TP53 (37%), PIK3CA (21%), AKT1 (7%), EGFR (5%) and KRAS (5%) | [61] |
Yi, Z. et al. | 2020 | TP53 mutations | [70] |
Visvanathan, K. et al. | 2017 | Cumulative methylation index (CMI) of a 6-gene panel (AKR1B1, HOXB4, RASGRF2, RASSF1, HIST1H3C and TM6SF1) | [128] |
Fackler, M. et al. | 2021 | 9-gene panel of breast-cancer-specific DNA methylation markers | [129] |
Gerratana, L. et al. | 2020 | Methylation status of ESR1 main promoters (promA and promB) | [131] |
Turner, N. et al. | 2023 | One or two mutations from panel of genes | [132] |
Chen, Y. et al. | 2017 | TP53, PIK3CA, CDKN2A from panel of genes | [133] |
Takahashi, H. et al. | 2017 | Methylation of the promoter region of RASSF1A | [134] |
Connolly, R. et al. | 2018 | 10-gene panel; cumulative methylation index (CMI) | [135] |
Han, Z. et al. | 2017 | Methylation of RASSF1A and WIF-1 | [136] |
Jank, P. et al. | 2020 | Methylation of 5 CpG islands of MGMT promoter | [137] |
Lin, P. et al. | 2021 | Target gene panel (14 genes) | [138] |
Liu, B. et al. | 2022 | TP53 mutations | [139] |
Guan, X. et al. | 2020 | HER2 amplification | [140] |
Rothé, F. et al. | 2019 | PIK3CA and/or TP53 mutations | [141] |
Li, X. et al. | 2020 | ESR1 mutations | [142] |
Cristofanilli, M. et al. | 2022 | ESR1, PIK3CA, and TP53 mutations | [143] |
Bidard, F. et al. Berger, F. et al. | 2022 2022 | ESR1 mutations | [55,144] |
Turner, N. et al. | 2020 | PIK3CA, ESR1, HER2, PTEN, and AKT1 mutations | [145] |
Lyu, D., et al. | 2022 | Mutations in PI3K/AKT/mTOR signaling pathway, ESR1, HER2 mutations | [146] |
Mastoraki, S. et al. | 2018 | ESR1 methylation | [147] |
Chimonidou, M. et al. | 2017 | Methylation of the promoter region of SOX17 | [148] |
Panagopoulou, M. et al. | 2019 | Methylation status of a panel of cancer-related genes (KLK10, SOX17, WNT5A, MSH2, GATA3) | [149] |
ctDNA studies using whole-genome sequencing | |||
Parsons, H. et al. | 2020 | Exome sequencing to identify patient-specific SNVs, design custom minimal residual disease tests | [18] |
Magbanua, M. et al. | 2021 | Whole-exome sequencing, design of individual mutation panels | [19] |
Moss, J. et al. | 2020 | 3 target regions specifically hypermethylated or hypomethylated uniquely in breast cancer from whole-genome bioinformatic analysis | [43] |
Widschwendter, M. et al. | 2017 | Representation bisulfite sequencing (RRBS), found specific region EFC#93 analysis via ultra-high coverage bisulfite sequencing | [48] |
McDonald, B. et al. | 2019 | Exome sequencing of tumor biopsies and analysis of dozens to hundreds of mutations in serial plasma samples | [69] |
Garcia-Murillas, I. et al. | 2015 | Targeted NGS of exons of 273 genes | [150] |
Coombes, R. et al. | 2019 | Ultra-deep sequencing | [151] |
Garcia-Murillas, I. et al. | 2019 | Identify somatic mutations by breast cancer driver gene panel, design of individual mutation panels | [152] |
Radovich, M. et al. | 2020 | Big commercial platform covering multiple genes | [153] |
Yi, Z. et al. | 2021 | Target-capture deep sequencing of 1021 genes, calculation of molecular tumor burden index | [154] |
Author, Year [Reference] | Number of Patients | Characteristic of Patients, Trial | Studied Parameter | Method, Tumor/ctDNA | Main Results |
---|---|---|---|---|---|
Parsons, H., 2020 [18] | 158 | Metastatic breast cancer ER + HER2- (n = 16) and non-metastatic breast cancer 0-III stage (n = 142) | Exome sequencing to identify patient-specific SNVs 2, custom test | NGS | Whole-exome sequencing of tumors was performed and individualized MRD 3 tests were designed. MRD detection at 1 year was strongly associated with distant recurrence (HR = 20.8; 95% CI 7.3–58.9). Median lead time from first positive sample to recurrence was 18.9 months (range = 3.4–39.2 months) |
Fackler, M., 2021 [42] | 72 | Metastatic breast cancer (n = 46), benign breast disease (n = 17), healthy normal controls (n = 9) | 9-gene panel of breast-cancer-specific DNA methylation markers | Methylation specific-PCR in automated Liquid Biopsy for Breast Cancer Methylation (LBx-BCM) prototype | 9-gene panel of methylated DNA markers that discriminates stage IV BC from benign breast disease and healthy normal subjects using ctDNA was identified. This assay has potential clinical utility in monitoring therapeutic response and predicting disease recurrence. |
Widschwendter, M., 2017 [48] | 419 | Breast cancer, SUCCESS trial | Representation bisulfite sequencing (RRBS) in tissue, ultra-high coverage bisulfite sequencing in serum; specific region EFC#93 (a pattern of five, linked CpGs methylated in BC) analysis | NGS | EFC#93 was an independent poor prognostic marker in pre-chemotherapy samples (HR for death = 7.689) and superior to circulating tumor cells (CTCs) (HR for death = 5.681). More than 70% of patients with both CTCs and EFC#93 serum DNAme positivity in their pre-chemotherapy samples relapsed within five years. EFC#93 positivity after chemotherapy is significantly (p = 0.014) less frequently observed in early stage (T1) compared to late stage (T2–4) cancers. EFC#93 serum positivity before chemotherapy was a very strong marker of poor prognosis, for both DFS and OS 4. |
Riva, F., 2017, [54] | 46 | Nonmetastatic triple-negative breast cancer | TP53 | NGS/ddPCR | Correlation with mitotic index (p = 0.003), tumor grade (p = 0.003), and stage (p = 0.03) |
Chin, Y., 2021 [61] | 109 | I–IV stages; 83%—luminal HER2 negative, 6%—HER2 positive, 11%—triple-negative | Oncomine Pan-Cancer Cell-Free Assay panel (52 genes) TP53, PIK3CA, AKT1, EGFR, KRAS | NGS | Correlation of the frequency of detection of ctDNA with the prevalence of the disease: stage (p = 0.00026), involvement of lymph nodes (p = 0.00649) and presence of distant metastases (p = 0.0005) |
Gerratana, L., 2020 [131] | 49 | Metastatic breast cancer ER + HER2- | ESR1 epigenetic status was defined by assessing the methylation of its main promoters (promA and promB) in ct DNA | Methylation- specific digital droplet PCR (MS-ddPCR) | No significant impact on PFS was observed for main promoters of ESR1: promA (p = 0.3777) and promB (p = 0.7455) dichotomized at the median while a ≥2-fold increase in promB or in either promA or promB after 3 months hormonotherapy resulted in a significantly worse prognosis (p = 0.0189, p = 0.0294, respectively). A significant increase after 3 months hormonotherapy was observed for promB among patients with PIK3CA mutation (p = 0.0173). Significantly lower promA levels at baseline were observed in patients with liver metastases (p = 0.0212). |
Turner, N., 2023 [132] | 208 | Triple-negative breast cancer after primary treatment, c-TRAK TN trial | RMH200 gene panel (200 cancer genes), or the ABC-BIO panel (41 gene) for tumor, using one or two mutations in cfDNA | NGS/dPCR | 71.9% patients (23/32, 95% CI 53.3–86.3%) had metastatic disease on staging at the time of ctDNA detection. Median lead time between ctDNA detection and disease recurrence in the intervention group was 1.6 months (95% CI 1.2–4.9 months) |
Chen, Y., 2017 [133] | 38 | Triple-negative breast cancer after primary treatment | Oncomine Research Panel consisting of 134 cancer genes (TP53, PIK3CA, CDKN2A) | NGS | ctDNA mutations in the plasma were detected of four patients (three TP53 mutations, one AKT1 mutation, one CDKN2A mutation). All four patients had recurrence of their disease (100% specificity), but sensitivity was limited to detecting only 4 of 13 patients who clinically relapsed (31% sensitivity). The analysis did not identify any de novo mutations exclusively in the plasma, suggesting that only mutations first identified in the primary tumor were detectable in the plasma Patients with detectable circulating tumor DNA had an inferior DFS (p < 0.0001; median DFS: 4.6 mos. vs. not reached; HR = 12.6, 95% CI: 3.06–52.2) |
Garcia-Murillas, I., 2015 [150] | 55 | Early breast cancer | Panel targeting 14 breast cancer driver genes for tumor, mutation-specific dPCR assays for cfDNA | NGS/ddPCR | Detection of ctDNA in patients who received therapy before surgery was predictive of early relapse (HR = 12.0): the median DFS 1 was 13.6 months (ctDNA detected) versus median not reached (ctDNA not detected). In total, 50% of the patients who relapsed in the study had ctDNA detected in a single postsurgical sample and 80% had ctDNA detected in serial samples. Of the patients who did not relapse, 96% did not have ctDNA detected in either a single postsurgical sample (p = 0.0038) or serial samples (p < 0.0001) |
Coombes, R., 2019 [151] | 49 | Breast cancer after primary treatment | Whole genome sequencing of tumor, ultra-deep sequencing of 16 individual somatic variants in cfDNA | NGS | Plasma ctDNA was detected ahead of clinical or radiologic relapse in 16 of the 18 relapsed patients (sensitivity of 89%); metastatic relapse was predicted with a lead time of up to 2 years (median 8.9 months; range 0.5–24.0 months). None of the 31 non-relapsing patients were ctDNA-positive at any time point across 156 plasma samples (specificity of 100%) |
Author, Year [Reference] | Number of Patients | Characteristics of Patients, Trial | Studied Parameter | Method, Tumor/ctDNA | Main Results |
---|---|---|---|---|---|
Magbanua, M., 2021 [19] | 84 | Early breast cancer | Whole-exome sequencing, design patient-specific custom test | NGS | Patients who remained ctDNA positive at T1 (3 week after initiation of paclitaxel) were significantly more likely to have residual disease after NAC (83% non-pCR) compared with those who cleared ctDNA (52% non-pCR; OR = 4.33, p = 0.012). After NAC, all patients who achieved pCR were ctDNA negative (n = 17, 100%). Patients who did not achieve pCR but were ctDNA negative (86%) had excellent outcomes, similar to those who achieved pCR (HR = 1.4; 95% CI 0.15–13.5). |
Moss, J., 2020 [43] | 29 | stage IIA–IIIC | 3 target regions specifically hypermethylated or hypomethylated uniquely in breast cancer received via bioinformatic analysis | NGS | Levels of methylation of ctDNA during the last month of NAC could predict the presence of residual disease (p = 0.006) and were significantly lower than at the start of treatment for patients with a pCR but not for patients with residual disease (p = 0.008 and p = 0.58, respectively). The association between methylation of ctDNA and residual disease is strong even when taking into account other factors such as age, receptor status, and stage. |
Riva, F., 2017 [54] | 46 | Nonmetastatic triple-negative breast cancer | TP53 | NGS | ctDNA positivity after 1 cycle of NAC 1 was correlated with shorter DFS 2 (p < 0.001) and overall (p = 0.006) survival. |
McDonald, B., 2019 [69] | 33 | Nonmetastatic breast cancer | Exome sequencing of tumor biopsies and analysis of dozens to hundreds of mutations in serial plasma samples | Targeted digital sequencing (TARDIS) | TARDIS results were informative in 100% of the samples. Patients with pCR 4 showed a large decrease in ctDNA concentration during therapy. |
Turner, N., 2023 [132] | 208 | Triple-negative breast cancer after primary treatment, c-TRAK TN trial | RMH200 gene panel (200 cancer genes), or the ABC-BIO panel (41 gene) for tumor, using one or two mutations in cfDNA | NGS/dPCR | 71.9% patients (23/32, 95% CI 53.3–86.3%) had metastatic disease on staging at the time of ctDNA detection. Median lead time between ctDNA detection and disease recurrence in the intervention group was 1.6 months (95% CI 1.2–4.9 months). The rapid relapsing nature of high-risk triple-negative BC challenged implementation of MRD 3 detection. |
Takahashi, H., 2017 [134] | 87 | Breast cancer II–III stage | Methylated ctDNA (met-ctDNA) for the promoter region of RASSF1A | One-step methylation-specific PCR (OS-MSP) | In the patients with positive met-ctDNA before NAC, met-ctDNA significantly decreased after NAC in those with disease that responded to therapy (p = 0.006), but not in patients whose disease did not respond to therapy. Met-ctDNA after NAC was found to be significantly (p = 0.008) correlated to the extent of residual tumor burden. |
Connolly, R., 2018 [135] | 62 | Breast cancer | 10-gene panel; cumulative methylation index (CMI) | Methylation- specific PCR | High tissue CMI levels at 15th day of treatment may predict poor response. Increase in tissue CMI levels at 15th day of treatment was associated with 40% lower chance of obtaining pCR (OR = 0.60, 95% CI 0.37–0.97; p = 0.037). |
Han, Z., 2017 [136] | 126 | Advanced breast cancer | Methylation of RASSF1A and WIF-1 | Methylation- specific PCR | Positive rates of RASSF1A methylation and WIF-1 in serum of the patients in the effective group were significantly lower than those in the ineffective group (p = 0.002 and p = 0.001, respectively), the mRNA of RASSF1A and WIF-mRNA was significantly higher than the ineffective group (p < 0.05). |
Jank, P., 2020 [137] | 174 | Triple-negative breast cancer II-III stage, GeparSixto trial | Methylation of 5 CpG islands of MGMT promoter | Pyrosequencing | MGMT promoter methylation was not significantly associated with pCR rate, and was not related to different chemotherapy response rates in the triple-negative BC. |
Lin, P., 2021 [138] | 60 | Breast cancer II–III stage | Deep sequencing of a target gene panel (14 genes) | NGS | The presence of ctDNA after NAC was a robust marker for predicting relapse in stage II-to-III BC patients (HR = 4.29, 95% CI 2.06–8.92, p < 0.0001) |
Garcia-Murillas, I., 2015 [150] | 55 | Early breast cancer | Panel targeting 14 breast cancer driver genes for tumor, mutation-specific dPCR assays for cfDNA | NGS/ddPCR | Detection of ctDNA in patients who received NAC before surgery in serial samples was predictive of early relapse (HR = 12.0): the median disease-free survival was 13.6 months (ctDNA detected) versus median not reached (ctDNA not detected). In total, 50% of the patients who relapsed in the study had ctDNA detected in a single postsurgical sample and 80% had ctDNA detected in serial samples. Of the patients who did not relapse, 96% did not have ctDNA detected in either a single postsurgical sample (p = 0.0038) or serial samples (p < 0.0001). |
Garcia-Murillas, I., 2019 [152] | 101 | Early breast cancer | Breast cancer driver gene panel, design of individual mutation panels | NGS | ctDNA detection during follow-up was associated with a high rate of relapse. |
Radovich, M., 2020 [153] | 142 | Early triple-negative breast cancer, BRE12-158 | Commercial platform covering multiple genes (FoundationACT® or FoundationOneLiquid Assay®) | NGS | Detection of ctDNA and circulating tumor cells in triple-negative BC patients after NAC was associated with disease recurrence. |
Author, Year [Reference] | Number of Patients | Characteristics of Patients, Trial | Studied Parameter | Method | Main Results |
---|---|---|---|---|---|
Fribbens, C., 2016 [20] | 161 + 360 | Metastatic ER+ breast cancer, SoFEA trial, PALOMA3 trial | ESR1 mutation | ddPCR | SoFEA: ESR1 mutations were detected in the ctDNA of 39.1% of the patients (63 of 161). ESR1 mutation in their ctDNA had worse PFS than those with the ESR1 wild type when treated with aromatase inhibitor exemestane (2.6 months versus 8.0 months, HR = 2.12; p = 0.01), but not fulvestrant. In ESR1 mutations, fulvestrant resulted in higher PFS compared to exemestane (HR 0.52; 95% CI 0.30–0.92; p = 0.02). PALOMA3: ESR1 mutations were detected in the ctDNA of 25.3% of the patients (91 of 360). Presence of ESR1 mutations in ctDNA of advanced BC patients showed worse PFS compared with those with the ESR1 wild type (HR = 1.46, p = 0.02). |
Bidard, F., 2022 [55] | 1017 | Metastatic ER+ HER2- breast cancer, PADA-1 trial | ESR1 | ddPCR | Earlier detection of ESR1 mutation growth as a marker of progression and early (before the appearance of traditional clinical and radiological signs) change in therapy ensured a gain in PFS: 11.9 and 5.7 months. (HR = 0.61, 95% CI 0.43–0.86; p = 0.004). |
Tolaney, S., 2022 [56] | 669 | Advanced ER+ HER2- breast cancer, MONARCH 2 trial | Mutations PIK3CA, ESR1 | ddPCR | Increase in median PFS with the addition of abemaciclib to fulvestrant (vs. placebo + fulvestrant) in both wild-type PIK3CA (median 16.9 vs. 12.3 months; HR = 0.51, 95% CI 0.33–0.78) and PIK3CA mutation (median 17.1 vs. 5.7 months, HR = 0.53; 95% CI 0.33–0.84); as well as with wild-type ESR1 (median 15.3 vs. 11.2 months, HR = 0.44, 95% CI 0.27–0.71) and with ESR1 mutation (median 20.7 vs. 13.1 months; HR 0.54; 95% CI 0.37–0.79). |
Sabatier, R., 2022 [57] | HER2-negative advanced breast cancer, TAKTIC trial | Low-coverage whole-genome sequencing for all plasma samples; ddPCR for some patients with driver mutations of PI3KCA, AKT1, and TP53 in their tumors | NGS + ddPCR | The presence of ctDNA upon inclusion was correlated with PFS (6-month PFS was 92% for ctDNA-negative patients versus 68% for ctDNA-positive cases (HR = 3.45, p = 0.007)). Copy number alterations were associated with disease progression under paclitaxel-LY2780301. Therefore, ctDNA detection at baseline was associated with shorter PFS, while plasma-based copy number analysis helped to identify alterations involved in resistance to AKT/p70S6K inhibitor plus paclitaxel treatment. | |
Di Leo, A., 2018 [59] | 348 | Locally advanced and metastatic ER+ HER2- breast cancer, BELLE-3 trial | PIK3CA mutation | Inostics BEAMing assay | Median PFS was significantly longer in the buparlisib versus placebo group (3.9 months vs. 1.8 month (HR = 0.67, 95% CI 0.53–0.84, p = 0.0003) in patients with PIK3CA mutations detected in tumor tissue or ctDNA isolated upon study entry. |
Yi, Z., 2020 [70] | 804 | Metastatic breast cancer | TP53 | NGS | TP53 mutations were associated with a shorter DFS vs. wild-type TP53 (HR = 1.32, 95% CI = 1.09–1.61, p = 0.005); TP53 mutations in exons 5–8 were associated with worse outcome (HR = 1.50, 95% CI = 1.11–2.03, p = 0.009); TP53 mutation status was not significantly associated with PFS in HER2-positive patients who received first-line trastuzumab-based therapy (p = 0.966). In the taxane combination group, patients with TP53 mutations exhibited longer PFS than those without TP53 mutations (HR = 0.08, 95% CI = 0.02–0.30, p < 0.001). In the non-taxane combination group, patients with TP53 mutations displayed shorter PFS than those with wild-type TP53 (HR = 4.84, p = 0.005). |
Visvanathan, K., 2017 [128] | 141 | Metastatic breast cancer | Cumulative methylation index (CMI) of a minimal 6-gene subset (AKR1B1, HOXB4, RASGRF2, RASSF1, HIST1H3C and TM6SF1) | Quantitative multiplex assay based on multiplex nested real-time PCR (cMethDNA) | Median PFS and OS were significantly shorter in women with a high CMI (PFS = 2.1 months; OS = 12.3 months) versus a low CMI (PFS = 5.8 months; OS = 21.7 months). In multivariable models, among women with metastatic BC, a high versus low CMI at week 4 was independently associated with worse PFS (HR = 1.79; 95% CI 1.23–2.60; p = 0.002) and OS (HR = 1.75; 95% CI 1.21–2.54; p = 0.003). |
Chen, Y., 2017 [133] | 38 | Triple-negative breast cancer after primary treatment | Oncomine Research Panel consisting of 134 cancer genes for tumor; TP53, AKT, CDKN2A in cfDNA | NGS | Patients with detectable ctDNA had an inferior DFS (p < 0.0001; median DFS: 4.6 mos. vs. not reached; HR = 12.6, 95% CI: 3.06–52.2). |
Liu, B., 2022 [139] | 1184 | HER2-positive breast cancer, Geneplus cohort | TP53 | NGS | TP53 mutations were associated with a shorter PFS 1 (p = 0.004) on anti-HER2 antibody therapy; the value of TP53 mutation in predicting HER2 tyrosine kinase inhibitor response was inconsistent. |
Guan, X., 2020 [140] | 105 | HER2-positive breast cancer | HER2 copy numbers | NGS | Correlation of the number of copies of the HER2 gene before treatment with the frequency of objective effects (p = 0.010); consistently high copy number after 6 weeks was associated with a decrease in DFS 2 (p < 0.001). |
Rothé, F., 2019 [141] | 69 | Early HER2+ breast cancer, NeoALTTO trial | PIK3CA and/or TP53 mutations | ddPCR | ctDNA detection before neoadjuvant anti-HER2 therapy was associated with low pCR 3 rates. Patients with HER2-enriched tumors and undetectable ctDNA at baseline had the highest pCR rates. |
Li, X., 2020 [142] | 45 | Metastatic ER+ breast cancer | Targeted NGS panel of 425 genes; TP53 mutation; ESR1 mutation | NGS | Six genes: TP53 (64.4%), PIK3CA (46.7%), ESR1 (20%), ERBB2 (15.6%), ATM (15.6%), and BRCA1 (13.3%), were mutated in more than 13% of the patients. Patients with TP53 mutations (29 patients of 45) had significantly worse OS 4 than the carriers of wild-type alleles (p = 0.0094). ESR1 mutations were recurrently enriched in ER+ metastatic BC patients but were rarely present in primary tumor tissues. The median time from aromatase inhibitor endocrine therapy to the first detection of ESR1 mutations was 39 months (95% CI 21.3–57.6). The change in allele frequency of ESR1 mutations (observed in 9 of 45 patients) was an important biomarker, which could predict endocrine resistance of ER+ BC. Therapy with everolimus in four cases with acquired ESR1 mutations showed longer PFS. |
Cristofanilli, M., 2022 [143] | 331 | Metastatic ER+ HER2- breast cancer, PALOMA3 trial | Panel of 17 driver and CDK4/6-related genes; analysis of ESR1, PIK3CA, TP53 mutations | NGS | Favorable OS in the palbociclib (+fulvestrant) vs. placebo (+fulvestrant) group was observed regardless of ESR1, PIK3CA, or TP53 mutation status; ESR1, PIK3CA and or TP53 mutations were prognostic for OS (HR = 1.58, 1.44 and 2.19, consequently). |
Turner, N., 2020 [145] | 1034 | Advanced breast cancer, PlasmaMATCH trial | Mutations PIK3CA, ESR1, HER2, PTEN, and AKT1 | dPCR + NGS | Neratinib for HER2-mutant BC and capivasertib for AKT1-mutant BC identified by ctDNA testing had comparable activity to that observed when guided by tissue testing in previous study, respectively. ctDNA testing enables the selection of mutation-directed therapies for patients with BC. |
Lyu, D., 2022 [146] | 113 | Metastatic ER+ breast cancer | Whole genome sequencing, PI3K/AKT/mTOR signaling pathway, ESR1, HER2 mutations | NGS | The risk of progression was lower in groups of patients who received treatment in accordance with the mutational status (HR = 0.55, p = 0.023) |
Mastoraki, S., 2018 [147] | 58 | ER+ HER2- metastatic breast cancer | ESR1 methylation in CTCs and paired plasma ctDNA | Methylation- specific PCR | ESR1 methylation in CTCs and a high concordance with paired plasma ctDNA were reported. In serial peripheral blood samples of patients treated with everolimus/exemestane, ESR1 methylation was observed in 10/36 (27.8%) CTC-positive samples, and was associated with lack of response to treatment (p = 0.023). |
Chimonidou, M., 2017 [148] | 153 | Breast cancer patients and healthy individuals | DNA methylation status of SOX17, CST6 and BRMS1 promoters in CTCs and ctDNA | Methylation- specific PCR | Association between the EpCAM (epithelial cell adhesion molecule)-positive CTC-fraction and ctDNA for SOX17 promoter methylation both for patients with early (p = 0.001) and metastatic BC (p = 0.046) was reported but not for CST6 and BRMS1. In early BC, SOX17 promoter methylation in the EpCAM-positive CTC-fraction was associated with CK-19 mRNA expression (p = 0.006) and worse OS (p = 0.044). In the metastatic setting, SOX17 promoter methylation in ctDNA was highly correlated with CK-19 (p = 0.04) and worse OS (p = 0.016). |
Panagopoulou, M., 2019 [149] | 235 | 150 and 16 breast cancer patients under adjuvant and neoadjuvant therapy, respectively, 34 patients with metastatic disease and 35 healthy volunteers | Methylation status of a panel of cancer-related genes (KLK10, SOX17, WNT5A, MSH2, GATA3) | Methylation- specific PCR | Methylation of at least 3 or 4 genes was significantly correlated to shorter OS and no pharmacotherapy response, respectively. Classification analysis by a fully automated, machine learning software (JADBio software, Gnosis Data Analysis) produced a single-parametric linear model using cfDNA plasma concentration values, with great discriminating power to predict response to therapy (AUC 0.803, 95% CI 0.606–1.000) in the metastatic group. Two more multi-parametric signatures were produced for the metastatic group, predicting survival and disease outcome. A multiple logistic regression model was constructed, discriminating between patient groups and healthy individuals. cfDNA emerged as a highly potent predictive classifier in metastatic BC. |
Yi, Z., 2021 [154] | 125 | Metastatic breast cancer, CAMELLIA trial | Target-capture deep sequencing of 1021 genes to detect somatic variants in ctDNA; determining the molecular tumor burden index (mTBI) | NGS | High-level pretreatment mTBI was correlated with shorter OS (p = 0.011). Patients with an mTBI decrease to less than 0.02% at the first tumor evaluation had longer PFS and OS (p < 0.001 and p = 0.007, respectively). The patients classified as molecular responders had longer PFS and OS than the nonmolecular responders (p < 0.001 and p = 0.036, respectively). |
Murtaza, M., 2015 [172] | 1 | Metastatic ER+ HER2+ breast cancer | Genomic architecture and infer clonal evolution in eight tumor biopsies and nine plasma samples collected over 1193 days of clinical follow-up were characterized using exome and targeted amplicon sequencing | NGS | Ubiquitous stem mutations (common to all tumor biopsies) have the highest circulating levels in plasma followed by metastatic-clade and private mutations. In addition, serial changes during treatment in circulating levels of private somatic mutations correlate with disease progression in their respective tumor lesions on imaging. |
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Zavarykina, T.M.; Lomskova, P.K.; Pronina, I.V.; Khokhlova, S.V.; Stenina, M.B.; Sukhikh, G.T. Circulating Tumor DNA Is a Variant of Liquid Biopsy with Predictive and Prognostic Clinical Value in Breast Cancer Patients. Int. J. Mol. Sci. 2023, 24, 17073. https://doi.org/10.3390/ijms242317073
Zavarykina TM, Lomskova PK, Pronina IV, Khokhlova SV, Stenina MB, Sukhikh GT. Circulating Tumor DNA Is a Variant of Liquid Biopsy with Predictive and Prognostic Clinical Value in Breast Cancer Patients. International Journal of Molecular Sciences. 2023; 24(23):17073. https://doi.org/10.3390/ijms242317073
Chicago/Turabian StyleZavarykina, Tatiana M., Polina K. Lomskova, Irina V. Pronina, Svetlana V. Khokhlova, Marina B. Stenina, and Gennady T. Sukhikh. 2023. "Circulating Tumor DNA Is a Variant of Liquid Biopsy with Predictive and Prognostic Clinical Value in Breast Cancer Patients" International Journal of Molecular Sciences 24, no. 23: 17073. https://doi.org/10.3390/ijms242317073
APA StyleZavarykina, T. M., Lomskova, P. K., Pronina, I. V., Khokhlova, S. V., Stenina, M. B., & Sukhikh, G. T. (2023). Circulating Tumor DNA Is a Variant of Liquid Biopsy with Predictive and Prognostic Clinical Value in Breast Cancer Patients. International Journal of Molecular Sciences, 24(23), 17073. https://doi.org/10.3390/ijms242317073