Evaluation of Circulating Tumor DNA as a Biomarker for Gynecological Tumors
Circulating tumor DNA (ctDNA) has emerged as a promising biomarker in the field of oncology, particularly for gynecological tumors. ctDNA refers to DNA fragments released into the peripheral blood by apoptotic or necrotic tumor cells. These fragments carry genetic information that reflects the mutations present in the tumor, providing valuable insights into tumor size, development, and progression. The detection and analysis of ctDNA offer a non-invasive method for monitoring cancer progression, recurrence, and response to treatment. Despite its potential, the isolation and analysis of ctDNA present challenges due to its low abundance, the presence of background cell-free DNA (cfDNA), and the variability between individuals. To address these challenges, advanced detection methods such as amplification refractory mutation system PCR (ARMS-PCR), digital PCR (dPCR), and high-throughput sequencing have been developed. Among these, dPCR stands out for its ability to achieve absolute quantification of single-molecule DNA, making it a reliable tool for clinical monitoring of tumor recurrence and minimal residual disease.
Breast Cancer and ctDNA
Breast cancer, one of the most common gynecological malignancies, often lacks specific clinical symptoms in its early stages. This makes early detection and monitoring of the disease particularly challenging. In 2015, Olsson et al. conducted a study involving 20 postoperative breast cancer patients, demonstrating that ctDNA had a specificity of 100% and a sensitivity of 93% for predicting disease recurrence. Notably, ctDNA predicted breast cancer recurrence an average of 11 months earlier than imaging methods in 86% of the patients. Another study by Saliou et al. focused on the PIK3CA gene, a common mutation in breast cancer. They found that ctDNA detection of this mutated gene in plasma allowed for earlier tumor detection compared to surgery, with a 93% consistency with preoperative plasma samples. Riva et al. utilized droplet digital PCR (ddPCR) to track TP53 mutations during neoadjuvant chemotherapy, observing that decreased ctDNA levels in plasma were associated with significant clinical efficacy. Patients with no detectable ctDNA after surgery had better outcomes, while those with elevated ctDNA levels had poor prognoses. These findings highlight the potential of ctDNA as a biomarker for predicting the efficacy of neoadjuvant chemotherapy and monitoring disease progression in breast cancer patients.
Triple-Negative Breast Cancer (TNBC)
Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer characterized by a high recurrence rate and low overall survival. In a study involving 50 TNBC patients who underwent neoadjuvant therapy (NAT), researchers used next-generation sequencing (NGS) and ddPCR to analyze TP53 mutations in plasma ctDNA and biopsy tissues. The study found that increased ctDNA levels were associated with tumor progression during neoadjuvant chemotherapy, indicating a poor prognosis. Another study involving 40 early non-metastatic TNBC patients with TP53 mutations revealed similar results, further supporting the role of ctDNA in dynamically monitoring tumor development and predicting early recurrence in TNBC patients. These findings suggest that ctDNA detection during NAT can provide valuable insights into tumor gene mutations and help predict patient outcomes.
Ovarian Cancer and ctDNA
Early detection is crucial for improving the survival rate of ovarian cancer patients, with the 5-year survival rate reaching up to 90% when detected early, compared to only about 20% in advanced stages. ctDNA has shown high specificity and sensitivity in the early diagnosis of ovarian cancer. Bettegowda et al. studied 640 ovarian cancer patients and found that 96% of them had mutations in one or more genes involved in the mitogen-activated protein kinase pathway. These findings suggest that ctDNA methylation or mutation testing could be useful in the diagnosis of ovarian cancer and in guiding the selection of chemotherapy regimens. Phallen et al. detected somatic mutations in 68% of early-stage ovarian cancer tissues, with a high consistency between tissue and ctDNA detection. Zhang et al. studied the Alu repeat sequence in plasma samples from 48 ovarian cancer cases, ovarian cyst patients, and healthy women, finding that the integrity index and Alu fragment levels were significantly higher in the ovarian cancer group compared to the control group. These results indicate that ctDNA concentration and integrity index could serve as valuable biomarkers for ovarian cancer diagnosis and risk stratification.
In a study focusing on adult ovarian granulosa cell tumors (AGCTs), Farkkila et al. tested the plasma Forkhead Box L2 (FOXL2) gene in 33 AGCT patients and found that 36% of the patients had positive mutations, providing preliminary evidence that ctDNA could be used for the diagnosis of AGCTs. Additionally, BRCA1/2 and TP53 mutations, which are common in ovarian cancer, have been studied extensively. Ratajska et al. detected BRCA1/2 somatic mutations in ctDNA and tumor tissues of 121 ovarian cancer patients, finding a high consistency between the two. Patients with BRCA reverse mutation-negative status had significantly longer progression-free survival (PFS) compared to those with mutation-positive status. Kim et al. detected TP53 mutations in high-grade serous ovarian carcinoma (HGSC) tissues and plasma, with a 100% coincidence rate. They found that the allele count of the mutant gene (TP53MAC) was positively correlated with the degree of surgical tumor reduction. Patients with high TP53MAC levels had a shorter time to disease progression (TTP), indicating that TP53MAC could be a useful biomarker for monitoring treatment response and predicting prognosis in ovarian cancer patients.
Cervical Cancer and ctDNA
Cervical cancer remains one of the most common gynecological malignancies. In 2019, Liao et al. investigated the relationship between ctDNA in plasma and the clinicopathology, efficacy, and prognosis of cervical cancer. The study included 188 cervical cancer patients and 200 controls, finding that the ctDNA content in the cervical cancer group was significantly higher than in the control group (15.76 ± 3.18 ng/mL vs. 7.82 ± 1.63 ng/mL). Furthermore, ctDNA content varied significantly with histological grade, infiltration depth, lymphatic metastasis, and FIGO stage. These findings suggest that ctDNA could serve as a valuable biomarker for assessing the severity and prognosis of cervical cancer.
Endometrial Cancer and ctDNA
Endometrial cancer has also been the subject of ctDNA research. Huang and Zhang suggested that ctDNA has a sensitivity similar to cancer antigen 125 (CA-125) for the diagnosis of endometrial cancer but with higher specificity. By comparing ctDNA levels before and after surgery, researchers observed a significant correlation between the loss of ctDNA after surgery and patient prognosis. Among 10 patients with follow-up data, those with an average ctDNA level of >10 copies/mL all died of the disease, while those with undetectable ctDNA after surgery survived, with two patients surviving for more than 5 years. However, preoperative ctDNA levels were not associated with patient survival. These results indicate that accurate ctDNA testing can predict patient prognosis and serve as an indicator for postoperative follow-up monitoring, guiding early detection of recurrence and metastasis.
Conclusion
In conclusion, ctDNA detection and analysis offer a non-invasive and effective approach for the diagnosis, prognosis, and treatment of gynecological tumors. While ctDNA testing is still in the scientific research stage and lacks standardized management, its clinical effectiveness and practicality are increasingly being recognized. Advanced detection methods such as dPCR and NGS have enhanced the sensitivity and specificity of ctDNA analysis, making it a promising tool for personalized therapy and precision medicine. As research continues to progress, ctDNA is expected to become a standard clinical biomarker, improving the management and outcomes of patients with gynecological tumors.
doi.org/10.1097/CM9.0000000000001140
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