Doxorubicin (Dox) is widely used in the treatment of triple-negative breast cancer cells (TNBCs), however resistance limits its effectiveness. Cancer stem cells (CSCs) are associated with Dox resistance in MCF-7 estrogen receptor positive breast cancer cells. Signal transducer and activator of transcription 3 (Stat3) may functionally shift non-CSCs towards CSCs. However, whether Stat3 drives the formation of CSCs during the development of resistance in TNBC, and whether a Stat3 inhibitor reverses CSC-mediated Dox resistance, remains to be elucidated. In the present study, human MDA-MB-468 and murine 4T1 mammary carcinoma cell lines with the typical characteristics of TNBCs, were compared with estrogen receptor-positive MCF-7 cells as a model system. The MTT assay was used to detect cytotoxicity of Dox. In addition, the expression levels of CSC-specific markers and transcriptional factors were measured by western blotting, immunofluorescence staining and flow cytometry. The mammosphere formation assay was used to detect stem cell activity. Under long-term continuous treatment with Dox at a low concentration, TNBC cultures not only exhibited a drug-resistant phenotype, but also showed CSC properties. These Dox-resistant TNBC cells showed activation of Stat3 and high expression levels of pluripotency transcription factors octamer-binding transcription factor-4 (Oct-4) and c-Myc, which was different from the high expression of superoxide dismutase 2 (Sox2) in Dox-resistant MCF-7 cells. WP1066 inhibited the phosphorylation of Stat3, and decreased the expression of Oct-4 and c-Myc, leading to a reduction in the CD44-positive cell population, and restoring the sensitivity of the cells to Dox. Taken together, a novel signal circuit of Stat3/Oct-4/c-Myc was identified for regulating stemness-mediated Dox resistance in TNBC. The Stat3 inhibitor WP1066 was able to overcome the resistance to Dox through decreasing the enrichment of CSCs, highlighting the therapeutic potential of WP1066 as a novel sensitizer of Dox-resistant TNBC.

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Background: Circulating tumor DNA in plasma may present a minimally invasive approach to identify tumor-derived mutations that could be used to inform the selection of targeted therapies for individual patients, particularly in cases of metastatic disease where biopsy is often difficult. We hypothesized that plasma DNA will genetically reflect DNA derived from multiple tumors in patients with metastatic breast cancer. To test this hypothesis and assess the utility of plasma DNA obtained as a “liquid biopsy” for precision medicine, we sought to determine whether massively parallel sequencing of plasma DNA is a reliable surrogate for sequencing of DNA from tissue biopsies in patients with metastatic breast cancer. Methods: Blood samples were obtained from 7 patients with multiple advanced breast cancer lesions (recurrent breast and metastatic tumors), and tumor specimens were obtained thereafter by biopsy or surgical excision. DNA extracted from plasma, buffy coat of blood, and tumor tissues was used for probe-directed capture of all exons in 196 genes followed by massively parallel sequencing with an average coverage of 3000x for plasma DNA. Tumor and plasma DNA sequences were bioinformatically compared to buffy coat controls, and high-confidence somatic mutations were called. One patient with extensive metastatic disease was evaluated in further detail to study the contribution of different tumors to the overall plasma DNA pool. In this patient, 9 metastatic tumors were sampled in an axillary lymph node, heart, kidney (2), liver, omentum (3), and ovary by biopsy or at autopsy. Results: Mutations were found in plasma that were represented in one or more tumors in each patient. Three classes of mutations were discovered: 1) mutations overlapping between both plasma and tumors (e.g., TP53 p.R273C and SRC p.E527K); 2) mutations found in plasma but not tumors (e.g., AKT p.E17K and multiple known and novel ESR1 mutations); 3) mutations found in tumors but not plasma (e.g., PIK3CA p.H1047R, p.D350G, and p.N345K). The presence of mutations in each of these classes was validated in plasma and/or tumors using mutation-specific droplet digital PCR (ddPCR). In the patient with extensive metastatic disease, DNA sequencing revealed heterogeneity of tumor contribution to plasma DNA, with some tumors better represented than others. No correlation was found between tumor size (measured by CT scan) and mutational burden in plasma. Interestingly, a significant correlation was found between blood perfusion to the organ where the tumor resides and mutational burden in plasma, with the greatest tumor contribution coming from the heart metastasis (Pearson's r = 0.835, p=0.039). Conclusions: Plasma DNA sequencing adds a layer of depth to sequencing analysis of tumor biopsy samples, and serves to both confirm tumor-derived mutations as well as detect new mutations. However, plasma DNA profiling does not comprehensively reflect the mutational profiles of tumors in patients with metastatic breast cancer, and thus is unlikely to serve as a surrogate for tumor biopsy as a source of DNA for genetic profiling. Furthermore, plasma DNA contains many mutations not found in tumors, which will confound treatment decision-making and precision medicine.Background: Circulating tumor DNA in plasma may present a minimally invasive approach to identify tumor-derived mutations that could be used to inform the selection of targeted therapies for individual patients, particularly in cases of metastatic disease where biopsy is often difficult. We hypothesized that plasma DNA will genetically reflect DNA derived from multiple tumors in patients with metastatic breast cancer. To test this hypothesis and assess the utility of plasma DNA obtained as a “liquid biopsy” for precision medicine, we sought to determine whether massively parallel sequencing of plasma DNA is a reliable surrogate for sequencing of DNA from tissue biopsies in patients with metastatic breast cancer. Methods: Blood samples were obtained from 7 patients with multiple advanced breast cancer lesions (recurrent breast and metastatic tumors), and tumor specimens were obtained thereafter by biopsy or surgical excision. DNA extracted from plasma, buffy coat of blood, and tumor tissues was used for probe-directed capture of all exons in 196 genes followed by massively parallel sequencing with an average coverage of 3000x for plasma DNA. Tumor and plasma DNA sequences were bioinformatically compared to buffy coat controls, and high-confidence somatic mutations were called. One patient with extensive metastatic disease was evaluated in further detail to study the contribution of different tumors to the overall plasma DNA pool. In this patient, 9 metastatic tumors were sampled in an axillary lymph node, heart, kidney (2), liver, omentum (3), and ovary by biopsy or at autopsy. Results: Mutations were found in plasma that were represented in one or more tumors in each patient. Three classes of mutations were discovered: 1) mutations overlapping between both plasma and tumors (e.g., TP53 p.R273C and SRC p.E527K); 2) mutations found in plasma but not tumors (e.g., AKT p.E17K and multiple known and novel ESR1 mutations); 3) mutations found in tumors but not plasma (e.g., PIK3CA p.H1047R, p.D350G, and p.N345K). The presence of mutations in each of these classes was validated in plasma and/or tumors using mutation-specific droplet digital PCR (ddPCR). In the patient with extensive metastatic disease, DNA sequencing revealed heterogeneity of tumor contribution to plasma DNA, with some tumors better represented than others. No correlation was found between tumor size (measured by CT scan) and mutational burden in plasma. Interestingly, a significant correlation was found between blood perfusion to the organ where the tumor resides and mutational burden in plasma, with the greatest tumor contribution coming from the heart metastasis (Pearson's r = 0.835, p=0.039). Conclusions: Plasma DNA sequencing adds a layer of depth to sequencing analysis of tumor biopsy samples, and serves to both confirm tumor-derived mutations as well as detect new mutations. However, plasma DNA profiling does not comprehensively reflect the mutational profiles of tumors in patients with metastatic breast cancer, and thus is unlikely to serve as a surrogate for tumor biopsy as a source of DNA for genetic profiling. Furthermore, plasma DNA contains many mutations not found in tumors, which will confound treatment decision-making and precision medicine. Citation Format: Shee K, Chamberlin MD, Varn FS, Bean JR, Marotti JD, Wells WA, Trask HW, Hamilton JS, West RJ, Kaufman PA, Schwartz GN, Gemery JM, McNulty NJ, Tsapakos MJ, Barth RJ, Arrick BA, Gui J, Cheng C, Miller TW. Broken promise of liquid biopsy: Plasma DNA does not accurately reflect tumor DNA in metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-07-03.

This paper is based on the general principle of beamforming algorithm of array signal processing. It gives a kind of high precision adaptive time-domain beamforming algorithm, uses ultra-wide band (UWB) microwave signal as an emission source applied to the human body in early breast cancer detection. In this paper, we build a two-dimensional, semicircle breast tissue model, use numerical simulation with finite-difference time-domain (FDTD) method for detection. The result shows the superiority of beamforming algorithm compared with that of confocal imaging algorithms and beamforming algorithms, especially to the Capon beamforming algorithm.

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