Evaluation of the Clinical Outcomes of Breast Cancer Patients with Positive and Negative Circulating Tumor DNA: A Meta-analysis and Systematic Review

Document Type : Review Article

Authors

1 Department of Internal Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

2 Department of Internal Medicine, School of Medicine, Iran University of Medical Sciences, Tehran, Iran

Abstract

Background and aim: This research addressed predicting the risk levels of breast cancer recurrence through the Circulating Tumor DNA (ctDNA) diagnostic method. The primary objective of the research was the evaluation of the clinical outcomes of cases suffering from breast cancer who exhibited positive and negative ctDNA.
Material and methods: To achieve the objectives of the study, databases at the international scale, including Web of Science, PubMed, Science Direct, Wiley, Scopus, EBSCO, Web of Knowledge, ISI, Embase, Google Scholar, and Elsevier, were searched according to PRISMA 2020-27-item checklist and respective keywords from 2019 to February 2024. Moreover, the inverse-variance method and the fixed effect model were applied to the research. In addition, we used STATA/MP v17 for statistical analyses of the data (Sig, ˂ 0.05).
Results: Based on the search, 11 articles were chosen, considering the inclusion criteria intended for the research. The odds ratio (OR) of ctDNA measurements with the positive result equaled 47% with a significant p-value compared to the negative ctDNA. Thus, similar overall survival was found in three (3) time points (P = 0.83). Furthermore, the detection rate of the positive versus negative ctDNA was found to be 72% (ES:72% 95% CI; 54%-89%) in the baseline and 44% (ES:44% 95% CI; 12%-100%) during neoadjuvant chemotherapy. Consequently, the negative conversion rate of the positive versus the negative ctDNA in the baseline-during neoadjuvant chemotherapy equaled 52% (ES:0.52 95% CI; -0.30-1.33), but it was 60% during neoadjuvant chemotherapy before the surgical operation (ES:0.60 95% CI; -0.71-1.91). Given testing the group differences, we did not observe any significant differences between the mentioned time points.
Conclusions: The performed meta-analysis revealed the potential of ctDNA to be applied as one of the reference indexes for evaluating the treatment effects during NAT, before and after surgical operation, and at baseline.

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[1] Coughlin SS. Epidemiology of breast cancer in women. Breast Cancer Metastasis and Drug Resistance: Challenges and Progress. 2019:1152:9-29. https://doi.org/10.1007/978-3-030-20301-6_2.
[2] Giaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, et al. Breast cancer statistics, 2022. CA: a cancer journal for clinicians. 2022;72(6):524-41. https://doi.org/10.3322/caac.21754.
[3] Arnold M, Morgan E, Rumgay H, Mafra A, Singh D, Laversanne M, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. The Breast. 2022;66:15-23. https://doi.org/10.1016/j.breast.2022.08.010.
[4] Lei S, Zheng R, Zhang S, Wang S, Chen R, Sun K, et al. Global patterns of breast cancer incidence and mortality: A population‐based cancer registry data analysis from 2000 to 2020. Cancer Communications. 2021;41(11):1183-94. https://doi.org/10.1002/cac2.12207.
[5] Cserni G. Histological type and typing of breast carcinomas and the WHO classification changes over time. Pathologica. 2020;112(1):25-41. https://doi.org/10.32074/1591-951X-1-20.
[6] Zafar T, Naik AQ, Kumar M, Shrivastava VK. Epidemiology and Risk Factors of Breast Cancer. InBreast Cancer: From Bench to Personalized Medicine 2022:3-29. https://doi.org/10.1007/978-981-19-0197-3_1.
[7] Lima SM, Kehm RD, Terry MB. Global breast cancer incidence and mortality trends by region, age-groups, and fertility patterns. EClinicalMedicine. 2021;38:100985. https://doi.org/10.1016/j.eclinm.2021.100985.
[8] Smolarz B, Nowak AZ, Romanowicz H. Breast cancer—epidemiology, classification, pathogenesis and treatment (review of literature). Cancers. 2022;14(10):2569. https://doi.org/10.3390/cancers14102569.
[9] Huber-Keener KJ. Cancer genetics and breast cancer. Best Practice & Research Clinical Obstetrics & Gynaecology. 2022;82:3-11. https://doi.org/10.1016/j.bpobgyn.2022.01.007.
[10] Bhushan A, Gonsalves A, Menon JU. Current state of breast cancer diagnosis, treatment, and theranostics. Pharmaceutics. 2021;13(5):723. https://doi.org/10.3390/pharmaceutics13050723.
[11] Peng Y, Mei W, Ma K, Zeng C. Circulating tumor DNA and minimal residual disease (MRD) in solid tumors: current horizons and future perspectives. Frontiers in oncology. 2021;11:763790. https://doi.org/10.3389/fonc.2021.763790.
[12] Alba-Bernal A, Lavado-Valenzuela R, Domínguez-Recio ME, Jiménez-Rodriguez B, Queipo-Ortuño MI, Alba E, et al. Challenges and achievements of liquid biopsy technologies employed in early breast cancer. EBioMedicine. 2020;62. https://doi.org/10.1016/j.ebiom.2020.103100.
[13] Papakonstantinou A, Gonzalez NS, Pimentel I, Suñol A, Zamora E, Ortiz C, et al. Prognostic value of ctDNA detection in patients with early breast cancer undergoing neoadjuvant therapy: A systematic review and meta-analysis. Cancer Treatment Reviews. 2022;104:102362. https://doi.org/10.1016/j.ctrv.2022.102362.
[14] Cullinane C, Fleming C, O’Leary DP, Hassan F, Kelly L, O’Sullivan MJ, et al. Association of circulating tumor DNA with disease-free survival in breast cancer: a systematic review and meta-analysis. JAMA network open. 2020;3(11):e2026921. 10.1001/jamanetworkopen.2020.26921.
[15] Gögenur M, Hadi NA, Qvortrup C, Andersen CL, Gögenur I. ctDNA for risk of recurrence assessment in patients treated with neoadjuvant treatment: A systematic review and meta-analysis. Annals of Surgical Oncology. 2022;29(13):8666-74. https://doi.org/10.1245/s10434-022-12366-7.
[16] Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bmj. 2021;372. https://doi.org/10.1136/bmj.n71.
[17] Gierisch JM, Beadles C, Shapiro A, McDuffie J, Cunningham N, Bradford D. Newcastle-Ottawa scale coding manual for cohort studies. Health disparities in quality indicators of healthcare among adults with mental illness. Department of Veterans Affairs (US). 2014.
[18] Minozzi S, Cinquini M, Gianola S, Gonzalez-Lorenzo M, Banzi R. The revised Cochrane risk of bias tool for randomized trials (RoB 2) showed low interrater reliability and challenges in its application. Journal of clinical epidemiology. 2020;126:37-44. https://doi.org/10.1016/j.jclinepi.2020.06.015.
[19] Sokouti M, Shafiee-Kandjani AR, Sokouti M, Sokouti B. A meta-analysis of systematic reviews and meta-analyses to evaluate the psychological consequences of COVID-19. BMC psychology. 2023;11(1):279. https://doi.org/10.1186/s40359-023-01313-0.
[20] Magbanua MJ, Swigart LB, Ahmed Z, Sayaman RW, Renner D, Kalashnikova E, et al. Clinical significance and biology of circulating tumor DNA in high-risk early-stage HER2-negative breast cancer receiving neoadjuvant chemotherapy. Cancer cell. 2023;41(6):1091-102. https://doi.org/10.1016/j.ccell.2023.04.008.
[21] Lipsyc-Sharf M, de Bruin EC, Santos K, McEwen R, Stetson D, Patel A, et al. Circulating tumor DNA and late recurrence in high-risk hormone receptor–positive, human epidermal growth factor receptor 2–negative breast cancer. Journal of Clinical Oncology. 2022;40(22):2408-19. https://doi.org/10.1200/JCO.22.00908.
[22] Zhou Q, Gampenrieder SP, Frantal S, Rinnerthaler G, Singer CF, Egle D, et al. Persistence of ctDNA in patients with breast cancer during neoadjuvant treatment is a significant predictor of poor tumor response. Clinical Cancer Research. 2022;28(4):697-707. https://doi.org/10.1158/1078-0432.CCR-21-3231.
[23] Janni W, Huober J, Huesmann S, Pipinikas C, Braun T, Müller V, et al. Abstract P2-01-07: Detection of early-stage breast cancer recurrence using a personalised liquid biopsy-based sequencing approach. Cancer Research. 2022;82(4_Supplement):1-7. https://doi.org/10.1158/1538-7445.SABCS21-P2-01-07.
[24] Lin PH, Wang MY, Lo C, Tsai LW, Yen TC, Huang TY, et al. Circulating tumor DNA as a predictive marker of recurrence for patients with stage II-III breast cancer treated with neoadjuvant therapy. Frontiers in Oncology. 2021;11:736769. https://doi.org/10.3389/fonc.2021.736769.
[25] Chen Y, Huawei Q. Effect of exemestane endocrine therapy for hormone-receptor-positive breast cancer patients with varying levels of ctDNA. Tropical Journal of Pharmaceutical Research. 2021;20(12):2611-7. http://dx.doi.org/10.4314/tjpr.v20i12.22.
[26] Magbanua MJ, Swigart LB, Wu HT, Hirst GL, Yau C, Wolf DM, et al. Circulating tumor DNA in neoadjuvant-treated breast cancer reflects response and survival. Annals of Oncology. 2021;32(2):229-39. https://doi.org/10.1016/j.annonc.2020.11.007.
[27] Ortolan E, Appierto V, Silvestri M, Miceli R, Veneroni S, Folli S, et al. Blood-based genomics of triple-negative breast cancer progression in patients treated with neoadjuvant chemotherapy. ESMO open. 2021;6(2):100086. https://doi.org/10.1016/j.esmoop.2021.100086.
[28] Cavallone L, Aguilar-Mahecha A, Lafleur J, Brousse S, Aldamry M, Roseshter T, et al. Prognostic and predictive value of circulating tumor DNA during neoadjuvant chemotherapy for triple negative breast cancer. Scientific reports. 2020;10(1):14704. https://doi.org/10.1038/s41598-020-71236-y.
[29] Rothé F, Silva MJ, Venet D, Campbell C, Bradburry I, Rouas G, et al. Circulating tumor DNA in HER2-amplified breast cancer: a translational research substudy of the NeoALTTO phase III trial. Clinical cancer research. 2019;25(12):3581-8. https://doi.org/10.1158/1078-0432.CCR-18-2521.
[30] Thierry AR, Mouliere F, El Messaoudi S, Mollevi C, Lopez-Crapez E, Rolet F, et al. Clinical validation of the detection of KRAS and BRAF mutations from circulating tumor DNA. Nature medicine. 2014;20(4):430-5. https://doi.org/10.1038/nm.3511.
[31] Chan KA, Jiang P, Chan CW, Sun K, Wong J, Hui EP, et al. Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing. Proceedings of the National Academy of Sciences. 2013;110(47):18761-8. https://doi.org/10.1073/pnas.1313995110.
[32] Li S, Lai H, Liu J, Liu Y, Jin L, Li Y, et al. Circulating tumor DNA predicts the response and prognosis in patients with early breast cancer receiving neoadjuvant chemotherapy. JCO Precision Oncology. 2020;4:244-57. https://doi.org/10.1200/PO.19.00292.
[33] Garcia-Murillas I, Chopra N, Comino-Méndez I, Beaney M, Tovey H, Cutts RJ, et al. Assessment of molecular relapse detection in early-stage breast cancer. JAMA oncology. 2019;5(10):1473-8. https://doi.org/10.1001/jamaoncol.2019.1838.
[34] Riva F, Bidard FC, Houy A, Saliou A, Madic J, Rampanou A, et al. Patient-specific circulating tumor DNA detection during neoadjuvant chemotherapy in triple-negative breast cancer. Clinical chemistry. 2017;63(3):691-9. https://doi.org/10.1373/clinchem.2016.262337.
[35] McDonald BR, Contente-Cuomo T, Sammut SJ, Odenheimer-Bergman A, Ernst B, Perdigones N, et al. Personalized circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer. Science translational medicine. 2019;11(504):eaax7392. https://doi.org/10.1126/scitranslmed.aax7392.
[36] Derks MG, van de Velde CJ. Neoadjuvant chemotherapy in breast cancer: more than just downsizing. The Lancet Oncology. 2018;19(1):2-3. https://doi.org/10.1016/S1470-2045(17)30914-2.