Association of 17q22 Amplicon Via Cell-Free DNA With Platinum Chemotherapy Response in Metastatic Triple-Negative Breast Cancer

Dynamic analysis of circulating tumor DNA to predict the prognosis and monitor the treatment response of patients with metastatic triple-negative breast cancer: A prospective study

Background

Limited data are available on applying circulating tumor DNA (ctDNA) in metastatic triple-negative breast cancer (mTNBC) patients. Here, we investigated the value of ctDNA for predicting the prognosis and monitoring the treatment response in mTNBC patients.

Methods

We prospectively enrolled 70 Chinese patients with mTNBC who had progressed after ≤2 lines of chemotherapy and collected blood samples to extract ctDNA for 457-gene targeted panel sequencing.

Results

Patients with ctDNA+, defined by 12 prognosis-relevant mutated genes, had a shorter progression-free survival (PFS) than ctDNA- patients (5.16 months vs. 9.05 months, p=0.001), and ctDNA +was independently associated with a shorter PFS (HR, 95% CI: 2.67, 1.2-5.96; p=0.016) by multivariable analyses. Patients with a higher mutant-allele tumor heterogeneity (MATH) score (≥6.316) or a higher ctDNA fraction (ctDNA%≥0.05) had a significantly shorter PFS than patients with a lower MATH score (5.67 months vs.11.27 months, p=0.007) and patients with a lower ctDNA% (5.45 months vs. 12.17 months, p<0.001), respectively. Positive correlations with treatment response were observed for MATH score (R=0.24, p=0.014) and ctDNA% (R=0.3, p=0.002), but not the CEA, CA125, or CA153. Moreover, patients who remained ctDNA +during dynamic monitoring tended to have a shorter PFS than those who did not (3.90 months vs. 6.10 months, p=0.135).

Conclusions

ctDNA profiling provides insight into the mutational landscape of mTNBC and may reliably predict the prognosis and treatment response of mTNBC patients.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 81902713), Natural Science Foundation of Shandong Province (Grant No. ZR2019LZL018), Breast Disease Research Fund of Shandong Provincial Medical Association (Grant No. YXH2020ZX066), the Start-up Fund of Shandong Cancer Hospital (Grant No. 2020-PYB10), Beijing Science and Technology Innovation Fund (Grant No. KC2021-ZZ-0010-1).

Potential predictive value of circulating tumor DNA (ctDNA) mutations for the efficacy of immune checkpoint inhibitors in advanced triple-negative breast cancer

Background: In recent years, tumor immunotherapy has become a viable treatment option for triple negative breast cancer (TNBC). Among these, immune checkpoint inhibitors (ICIs) have demonstrated good efficacy in advanced TNBC patients with programmed death-ligand 1 (PD-L1) positive expression. However, only 63% of PD-L1-positive individuals showed any benefit from ICIs. Therefore, finding new predictive biomarkers will aid in identifying patients who are likely to benefit from ICIs. In this study, we used liquid biopsies and next-generation sequencing (NGS) to dynamically detect changes in circulating tumor DNA (ctDNA) in the blood of patients with advanced TNBC treated with ICIs and focused on its potential predictive value.

Methods: From May 2018 to October 2020, patients with advanced TNBC treated with ICIs at Shandong Cancer Hospital were included prospectively. Patient blood samples were obtained at the pretreatment baseline, first response evaluation, and disease progression timepoints. Furthermore, 457 cancer-related genes were evaluated by NGS, and patients’ ctDNA mutations, gene mutation rates, and other indicators were determined and coupled with clinical data for statistical analysis.

Results: A total of 11 TNBC patients were included in this study. The overall objective response rate (ORR) was 27.3%, with a 6.1-month median progression-free survival (PFS) (95% confidence interval: 3.877–8.323 months). Of the 11 baseline blood samples, 48 mutations were found, with the most common mutation types being frame shift indels, synonymous single-nucleotide variations (SNVs), frame indel missenses, splicing, and stop gains. Additionally, univariate Cox regression analysis revealed that advanced TNBC patients with one of 12 mutant genes (CYP2D6 deletion and GNAS, BCL2L1, H3F3C, LAG3, FGF23, CCND2, SESN1, SNHG16, MYC, HLA-E, and MCL1 gain) had a shorter PFS with ICI treatment (p &lt; 0.05). To some extent, dynamic changes of ctDNA might indicate the efficacy of ICIs.

Conclusion: Our data indicate that ICI efficacy in patients with advanced TNBC may be predicted by 12 mutant ctDNA genes. Additionally, dynamic alterations in peripheral blood ctDNA might be used to track the effectiveness of ICI therapy in those with advanced TNBC.

An Overview of Circulating Cell-Free Nucleic Acids in Diagnosis and Prognosis of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer due to its molecular heterogeneity and poor clinical outcomes. Analysis of circulating cell-free tumor nucleic acids (ctNAs) can improve our understanding of TNBC and provide efficient and non-invasive clinical biomarkers that may be representative of tumor heterogeneity. In this review, we summarize the potential of ctNAs to aid TNBC diagnosis and prognosis. For example, tumor fraction of circulating cell-free DNA (TFx) may be useful for molecular prognosis of TNBC: high TFx levels after neoadjuvant chemotherapy have been associated with shorter progression-free survival and relapse-free survival. Mutations and copy number variations of TP53 and PIK3CA/AKT genes in plasma may be important markers of TNBC onset, progression, metastasis, and for clinical follow-up. In contrast, the expression profile of circulating cell-free tumor non-coding RNAs (ctncRNAs) can be predictive of molecular subtypes of breast cancer and thus aid in the identification of TBNC. Finally, dysregulation of some circulating cell-free tumor miRNAs (miR17, miR19a, miR19b, miR25, miR93, miR105, miR199a) may have a predictive value for chemotherapy resistance. In conclusion, a growing number of efforts are highlighting the potential of ctNAs for future clinical applications in the diagnosis, prognosis, and follow-up of TNBC.

Role of ctDNA in Breast Cancer

Breast cancer is currently classified by immunohistochemistry. However, technological advances in the detection of circulating tumor DNA (ctDNA) have made new options available for diagnosis, classification, biological knowledge, and treatment selection. Breast cancer is a heterogeneous disease and ctDNA can accurately reflect this heterogeneity, allowing us to detect, monitor, and understand the evolution of the disease. Breast cancer patients have higher levels of circulating DNA than healthy subjects, and ctDNA can be used for different objectives at different timepoints of the disease, ranging from screening and early detection to monitoring for resistance mutations in advanced disease. In early breast cancer, ctDNA clearance has been associated with higher rates of complete pathological response after neoadjuvant treatment and with fewer recurrences after radical treatments. In metastatic disease, ctDNA can help select the optimal sequencing of treatments. In the future, thanks to new bioinformatics tools, the use of ctDNA in breast cancer will become more frequent, enhancing our knowledge of the biology of tumors. Moreover, deep learning algorithms may also be able to predict breast cancer evolution or treatment sensitivity. In the coming years, continued research and the improvement of liquid biopsy techniques will be key to the implementation of ctDNA analysis in routine clinical practice.