The biological function of tumor-derived extracellular vesicles on metabolism.

Multiple studies have shown that extracellular vesicles (EVs) play a key role in the process of information transfer and material transport between cells. EVs are classified into different types according to their sizes, which includes the class of exosomes. In comparison to normal EVs, tumor-derived EVs (TDEs) have both altered components and quantities of contents. TDEs have been shown to help facilitate an environment conducive to the occurrence and development of tumor by regulation of glucose, lipids and amino acids. Furthermore, TDEs can also affect the host metabolism and immune system. EVs have been shown to have multiple clinically useful properties, including the use of TDEs as biomarkers for the early diagnosis of diseases and using the transport properties of exosomes for drug delivery. Targeting the key bioactive cargoes of exosomes could be applied to provide new strategies for the treatment of tumors. In this review, we summarize the finding of studies focused on measuring the effects of TDE on tumor-related microenvironment and systemic metabolism. Video Abstract.

Increasing the Capture Rate of Circulating Tumor DNA in Unaltered Plasma Using Passive Microfluidic Mixer Flow Cells.

A limiting factor in using blood-based liquid biopsies for cancer detection is the volume of extracted blood required to capture a measurable number of circulating tumor DNA (ctDNA). To overcome this limitation, we developed a technology named the dCas9 capture system to capture ctDNA from unaltered flowing plasma, removing the need to extract the plasma from the body. This technology has provided the first opportunity to investigate whether microfluidic flow cell design can affect the capture of ctDNA in unaltered plasma. With inspiration from microfluidic mixer flow cells designed to capture circulating tumor cells and exosomes, we constructed four microfluidic mixer flow cells. Next, we investigated the effects of these flow cell designs and the flow rate on the rate of captured spiked-in BRAF T1799A (BRAFMut) ctDNA in unaltered flowing plasma using surface-immobilized dCas9. Once the optimal mass transfer rate of ctDNA, identified by the optimal ctDNA capture rate, was determined, we investigated whether the design of the microfluidic device, flow rate, flow time, and the number of spiked-in mutant DNA copies affected the rate of capture by the dCas9 capture system. We found that size modifications to the flow channel had no effect on the flow rate required to achieve the optimal capture rate of ctDNA. However, decreasing the size of the capture chamber decreased the flow rate required to achieve the optimal capture rate. Finally, we showed that, at the optimal capture rate, different microfluidic designs using different flow rates could capture DNA copies at a similar rate over time. In this study, the optimal capture rate of ctDNA in unaltered plasma was identified by adjusting the flow rate in each of the passive microfluidic mixer flow cells. However, further validation and optimization of the dCas9 capture system are required before it is ready to be used clinically.

Detecting aberrant DNA methylation in Illumina DNA methylation arrays: a toolbox and recommendations for its use.

In this study, our goal was to determine probe-specific thresholds for identifying aberrant, or outlying, DNA methylation and to provide guidance on the relative merits of using continuous or outlier methylation data. To construct a reference database, we downloaded Illumina Human 450K array data for more than 2,000 normal samples, characterized the distribution of DNA methylation and derived probe-specific thresholds for identifying aberrations. We made the decision to restrict our reference database to solid normal tissue and morphologically normal tissue found adjacent to solid tumours, excluding blood which has very distinctive patterns of DNA methylation. Next, we explored the utility of our outlier thresholds in several analyses that are commonly performed on DNA methylation data. Outliers are as effective as the full continuous dataset for simple tasks, like distinguishing tumour tissue from normal, but becomes less useful as the complexity of the problem increases. We developed an R package called OutlierMeth containing our thresholds, as well as functions for applying them to data.

Capturing ctDNA from Unaltered Stationary and Flowing Plasma with dCas9.

Many studies have established that blood-based liquid biopsies can be used to detect cancer in its early stages. However, the limiting factor for early cancer detection is the volume of blood required to capture the small amount of circulating tumor DNA (ctDNA). An apheresis machine is a device that can draw whole blood, separate the blood components, and infuse the blood components back into the individual. This device provides the opportunity to screen large volumes of plasma without extracting it from the body. However, current DNA capture technologies require the plasma to be altered before the ctDNA can be captured. Our goal was to develop the first technology that can capture ctDNA from flowing unaltered plasma. To simulate cancer patient plasma, we spiked BRAF T1799A (BRAFMut) DNA into plasma from healthy individuals. We used catalytically dead Cas9 (dCas9), guide RNA, and allele-specific quantitative polymerase chain reaction (qPCR) to capture and measure the number of captured BRAFMut DNA copies. We found that dCas9 captured BRAFMut alleles with equal efficiency at room temperature (25 °C) and body temperature (37 °C). Next, we showed that, in stationary unaltered plasma, dCas9 was as efficient in capturing BRAFMut as a commercial cell-free DNA (cfDNA) capture kit. However, in contrast to the cfDNA capture kit, dCas9 enriched BRAFMut by 1.8-3.3-fold. We then characterized the dCas9 capture system in laminar and turbulent flowing plasma. We showed that the capture rate using turbulent flow was greater than that in laminar flow and stationary plasma. With turbulent flow, the number of captured BRAFMut copies doubles with time (slope = -1.035 Ct) and is highly linear (R2 = 0.874). While we showed that the dCas9 capture system can capture ctDNA from unaltered flowing plasma, further optimization and validation of this technology is required before its clinical utility can be determined.

HOXA5-Mediated Stabilization of IκBα Inhibits the NF-κB Pathway and Suppresses Malignant Transformation of Breast Epithelial Cells.

HOXA5 is a transcription factor and tumor suppressor that promotes differentiation of breast epithelial cells and is frequently lost during malignant transformation. HOXA5 loss alone, however, does not confer tumorigenicity. To determine which molecular alterations combined with loss of HOXA5 expression can transform cells, we examined isogenic derivatives of a nonmalignant breast epithelial cell line containing knock-in or knockout mutations in key breast cancer genes. Knockdown (KD) of HOXA5 in cells harboring double knock-in (DKI) of mutated PIK3CA (E545K) and HER2 (V777L) induced epithelial-mesenchymal transition and migration and promoted invasive tumor outgrowth within mouse mammary ducts. The NF-κB pathway was significantly upregulated in DKI cells following HOXA5 KD. HOXA5 KD upregulated multiple NF-κB target genes, including IL6. IκBα protein, but not RNA, expression was reduced in HOXA5-KD cells. HOXA5 bound and stabilized IκBα, forming a nuclear HOXA5-IκBα complex. Chromatin immunoprecipitation sequencing database queries revealed that HOXA5 and IκBα are co-enriched at 528 genomic loci. In patients with breast cancer, high coexpression of HOXA5 and IκBα conferred a significantly better overall and progression-free survival. Collectively, these data suggest that HOXA5 suppresses malignancy in breast epithelial cells by blunting NF-κB action via stabilization of its inhibitor IκBα. SIGNIFICANCE: Loss of HOXA5 reduces IκBα stability and increases NF-κB signaling to exacerbate breast cancer aggressiveness, providing new insights into the tumor suppressor functions of HOXA5.

Development of an automated liquid biopsy assay for methylated markers in advanced breast cancer.

Current molecular liquid biopsy assays to detect recurrence or monitor response to treatment require sophisticated technology, highly trained personnel, and a turnaround time of weeks. We describe the development and technical validation of an automated Liquid Biopsy for Breast Cancer Methylation (LBx-BCM) prototype, a DNA methylation detection cartridge assay that is simple to perform and quantitatively detects nine methylated markers within 4.5 h. LBx-BCM demonstrated high interassay reproducibility when analyzing exogenous methylated DNA (75-300 DNA copies) spiked into plasma (Coefficient of Variation, CV = 7.1 - 10.9%) and serum (CV = 19.1 - 36.1%). It also demonstrated high interuser reproducibility (Spearman r = 0.887, P < 0.0001) when samples of metastatic breast cancer (MBC, N = 11) and normal control (N = 4) were evaluated independently by two users. Analyses of interplatform reproducibility indicated very high concordance between LBx-BCM and the reference assay, cMethDNA, among 66 paired plasma samples (MBC N = 40, controls N = 26; Spearman r = 0.891; 95% CI = 0.825 - 0.933, P< 0.0001). LBx-BCM achieved a ROC AUC = 0.909 (95% CI = 0.836 - 0.982), 83% sensitivity and 92% specificity; cMethDNA achieved a ROC AUC = 0.896 (95% CI = 0.817 - 0.974), 83% sensitivity and 92% specificity in test set samples. The automated LBx-BCM cartridge prototype is fast, with performance levels equivalent to the highly sensitive, manual cMethDNA method. Future prospective clinical studies will evaluate LBx-BCM detection sensitivity and its ability to monitor therapeutic response during treatment for advanced breast cancer.

Methylated markers accurately distinguish primary central nervous system lymphomas (PCNSL) from other CNS tumors.

BACKGROUND: Definitive diagnosis of primary central nervous system lymphoma (PCNSL) requires invasive surgical brain biopsy, causing treatment delays. In this paper, we identified and validated tumor-specific markers that can distinguish PCNSL from other CNS tumors in tissues. In a pilot study, we tested these newly identified markers in plasma. RESULTS: The Methylation Outlier Detector program was used to identify markers in TCGA dataset of 48 diffuse large B-cell lymphoma (DLBCL) and 656 glioblastomas and lower-grade gliomas. Eight methylated markers clearly distinguished DLBCL from gliomas. Marker performance was verified (ROC-AUC of ≥ 0.989) in samples from several GEO datasets (95 PCNSL; 2112 other primary CNS tumors of 11 types). Next, we developed a novel, efficient assay called Tailed Amplicon Multiplexed-Methylation-Specific PCR (TAM-MSP), which uses two of the methylation markers, cg0504 and SCG3 triplexed with ACTB. FFPE tissue sections (25 cases each) of PCNSL and eight types of other primary CNS tumors were analyzed using TAM-MSP. TAM-MSP distinguished PCNSL from the other primary CNS tumors with 100% accuracy (AUC = 1.00, 95% CI 0.95-1.00, P < 0.001). The TAM-MSP assay also detected as few as 5 copies of fully methylated plasma DNA spiked into 0.5 ml of healthy plasma. In a pilot study of plasma from 15 PCNSL, 5 other CNS tumors and 6 healthy individuals, methylation in cg0504 and SCG3 was detectable in 3/15 PCNSL samples (20%). CONCLUSION: The Methylation Outlier Detector program identified methylated markers that distinguish PCNSL from other CNS tumors with accuracy. The high level of accuracy achieved by these markers was validated in tissues by a novel method, TAM-MSP. These studies lay a strong foundation for a liquid biopsy-based test to detect PCNSL-specific circulating tumor DNA.

Automated and rapid detection of cancer in suspicious axillary lymph nodes in patients with breast cancer.

Preoperative staging of suspicious axillary lymph nodes (ALNs) allows patients to be triaged to ALN dissection or to sentinel lymph node biopsy (SLNB). Ultrasound-guided fine needle aspiration (FNA) and cytology of ALN is moderately sensitive but its clinical utility relies heavily on the cytologist's experience. We proposed that the 5-h automated GeneXpert system-based prototype breast cancer detection assay (BCDA) that quantitatively measures DNA methylation in ten tumor-specific gene markers could provide a facile, accurate test for detecting cancer in FNA of enlarged lymph nodes. We validated the assay in ALN-FNA samples from a prospective study of patients (N = 230) undergoing SLNB. In a blinded analysis of 218 evaluable LN-FNAs from 108 malignant and 110 benign LNs by histology, BCDA displayed a sensitivity of 90.7% and specificity of 99.1%, achieving an area under the ROC curve, AUC of 0.958 (95% CI: 0.928-0.989; P < 0.0001). Next, we conducted a study of archival FNAs of ipsilateral palpable LNs (malignant, N = 72, benign, N = 53 by cytology) collected in the outpatient setting prior to neoadjuvant chemotherapy (NAC). Using the ROC-threshold determined in the prospective study, compared to cytology, BCDA achieved a sensitivity of 94.4% and a specificity of 92.5% with a ROC-AUC = 0.977 (95% CI: 0.953-1.000; P < 0.0001). Our study shows that the automated assay detects cancer in suspicious lymph nodes with a high level of accuracy within 5 h. This cancer detection assay, scalable for analysis to scores of LN FNAs, could assist in determining eligibility of patients to different treatment regimens.

DNA Methylation Markers for Breast Cancer Detection in the Developing World.

PURPOSE: An unmet need in low-resource countries is an automated breast cancer detection assay to prioritize women who should undergo core breast biopsy and pathologic review. Therefore, we sought to identify and validate a panel of methylated DNA markers to discriminate between cancer and benign breast lesions using cells obtained by fine-needle aspiration (FNA).Experimental Design: Two case-control studies were conducted comparing cancer and benign breast tissue identified from clinical repositories in the United States, China, and South Africa for marker selection/training (N = 226) and testing (N = 246). Twenty-five methylated markers were assayed by Quantitative Multiplex-Methylation-Specific PCR (QM-MSP) to select and test a cancer-specific panel. Next, a pilot study was conducted on archival FNAs (49 benign, 24 invasive) from women with mammographically suspicious lesions using a newly developed, 5-hour, quantitative, automated cartridge system. We calculated sensitivity, specificity, and area under the receiver-operating characteristic curve (AUC) compared with histopathology for the marker panel. RESULTS: In the discovery cohort, 10 of 25 markers were selected that were highly methylated in breast cancer compared with benign tissues by QM-MSP. In the independent test cohort, this panel yielded an AUC of 0.937 (95% CI = 0.900-0.970). In the FNA pilot, we achieved an AUC of 0.960 (95% CI = 0.883-1.0) using the automated cartridge system. CONCLUSIONS: We developed and piloted a fast and accurate methylation marker-based automated cartridge system to detect breast cancer in FNA samples. This quick ancillary test has the potential to prioritize cancer over benign tissues for expedited pathologic evaluation in poorly resourced countries.