We conducted a pilot study to assess the feasibility and the potential implications of detecting promoter (p)-mutant cell-free tumor-derived DNA (tDNA) in the cerebrospinal fluid (CSF) and plasma of glioblastoma patients. Matched CSF and plasma samples were collected in 60 patients with glial tumors. The CSF collection was obtained during surgery, before any surgical manipulation of the tumor. The extracted tDNA and corresponding tumor DNA samples were analyzed for p and isocitrate dehydrogenase ( hotspot mutations. In addition, the variant allele frequency (VAF) of p mutation in the CSF-tDNA was correlated with tumor features and patients' outcome. Thirty-eight patients had p-mutant/ wild-type glioblastomas. The matched p mutation in the CSF-tDNA was successfully detected with 100% specificity (95% CI, 87.6-100%) and 92.1% sensitivity (95% CI, 78.6-98.3%) ( = 35/38). In contrast, the sensitivity in the plasma-tDNA was far lower [ = 3/38, 7.9% (95% CI, 1.6-21.4%)]. We concordantly observed a longer overall survival of patients with low VAF in the CSF-tDNA when compared with patients with high VAF, irrespective of using the lower quartile VAF [11.45%; 14.0 mo. (95% confidence interval, CI, 10.3-17.6) vs. 8.6 mo. (95% CI, 4.1-13.2), = 0.035], the lower third VAF [13%; 15.4 mo. (95% CI, 11.6-19.2) vs. 8.3 mo. (95% CI, 2.3-14.4), = 0.008], or the median VAF [20.3%; 14.0 mo. (95% CI, 9.2-18.7) vs. 8.6 mo. (95% CI, 7.5-9.8), = 0.062] to dichotomize the patients. This pilot study highlights the value of CSF-tDNA for an accurate and reliable detection of p mutations. Furthermore, our findings suggest that highp mutation VAF levels in the CSF-tDNA may represent a suitable predictor of poor survival in glioblastoma patients. Further studies are needed to complement the findings of our exploratory analysis. .
There is growing recognition that cell deformability can play an important role in cancer metastasis and diagnostics. Advancement of methods to characterize cell deformability in a high throughput manner and the capacity to process numerous samples can impact cancer-related applications ranging from analysis of patient samples to discovery of anti-cancer compounds to screening of oncogenes. In this study, we report a microfluidic technique called multi-sample deformability cytometry (MS-DC) that allows simultaneous measurement of flow-induced deformation of cells in multiple samples at single-cell resolution using a combination of on-chip reservoirs, distributed pressure control, and data analysis system. Cells are introduced at rates of O(100) cells per second with a data processing speed of 10 min per sample. To validate MS-DC, we tested more than 50 cell-samples that include cancer cell lines with different metastatic potential and cells treated with several cytoskeletal-intervention drugs. Results from MS-DC show that (i) the cell deformability correlates with metastatic potential for both breast and prostate cancer cells but not with their molecular histotype, (ii) the strongly metastatic breast cancer cells have higher deformability than the weakly metastatic ones; however, the strongly metastatic prostate cancer cells have lower deformability than the weakly metastatic counterparts, and (iii) drug-induced disruption of the actin network, microtubule network, and actomyosin contractility increased cancer cell deformability, but stabilization of the cytoskeletal proteins does not alter deformability significantly. Our study demonstrates the capacity of MS-DC to mechanically phenotype tumor cells simultaneously in many samples for cancer research.
HighlightsNGS based detection of low-level SNVs is feasible with sensitivities up to 10−4.PCR-induced bias could be significantly reduced by the choice of adequate enzymes.The prevalent transition vs. transversion bias affects site-specific detection limits.Results from clinical data validated the feasibility of NGS-based MRD detection.Results help to select suitable biomarkers for MRD quantification.
Patients frequently ask about the cause of their breast cancer. To answer, physicians refer to breast cancer risk factors based on medical reports. We aim to assess these risk factors for the point of view of survivors, a point of view which seems to differ from that of medical references. We ran a survey with open- and closed-ended questionnaires on patients' opinions about risks factors both for women in general and for their own case. We also collected data on their sources of information on this subject. Most patients had no opinion. The most frequently cited risk factors were stress, then genetic causes, and poor diet. Internet was the leading source of information for patients, followed by physicians and magazines. Our study highlights the mismatch between breast cancer risk factors as perceived by scientists and by survivors. Survivors tend to focus on non-controllable risk factors. Taking into account attribution theories of life events, an awareness of patient opinion may be valuable for psychological support of survivors, and it may be informative to record the way in which patients attribute causality for life events such as breast cancer and, more generally, all type of cancer.
Major obstacles in current breast cancer treatment efficacy include the ability of breast cancer cells to develop resistance to chemotherapeutic drugs and the off-target cytotoxicity of these drugs on normal cells, leading to debilitating side effects. One major difference between cancer and normal cells is their metabolism, as cancer cells acquire glycolytic and mitochondrial metabolism alterations throughout tumorigenesis. In this study, we sought to exploit this metabolic difference by investigating alternative breast cancer treatment options based on the application of phytochemicals. Herein, we investigated three phytochemicals, namely cinnamaldehyde (CA), chlorogenic acid (CGA), and arctigenin (Arc), regarding their anti-breast-cancer properties. These phytochemicals were administered alone or in combination to MCF-7, MDA-MB-231, and HCC1419 breast cancer or normal MCF-10A and MCF-12F breast cells. Overall, our results indicated that the combination treatments showed stronger inhibitory effects on breast cancer cells versus single treatments. However, only treatments with CA (35 μM), CGA (250 μg/mL), and the combination of CA + CGA (35 μM + 250 μg/mL) showed no significant cytotoxic effects on normal mammary epithelial cells, suggesting that Arc was the driver of normal cell cytotoxicity in all other treatments. CA + CGA and, to a lesser extent, CGA alone effectively induced breast cancer cell death accompanied by decreases in mitochondrial membrane potential, increased mitochondrial superoxide, reduced mitochondrial and glycolytic ATP production, and led to significant changes in cellular and mitochondrial morphology. Altogether, the combination of CA + CGA was determined as the best anti-breast-cancer treatment strategy due to its strong anti-breast-cancer effects without strong adverse effects on normal mammary epithelial cells. This study provides evidence that targeting the mitochondria may be an effective anticancer treatment, and that using phytochemicals or combinations thereof offers new approaches in treating breast cancer that significantly reduce off-target effects on normal cells.
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