Novel method for highly multiplexed gene expression profiling of circulating tumor cells (CTCs) captured from the blood of women with metastatic breast cancer.

BACKGROUND: Enumeration of circulating tumor cells (CTCs) has proven clinical significance for monitoring patients with metastatic cancers. Multiplexed gene expression profiling of CTCs is a potential tool for assessing disease status and monitoring treatment response. The Parsortix® technology enables the capture and harvest of CTCs from blood based on cell size and deformability. The HyCEAD™ (Hybrid Capture Enrichment Amplification and Detection) assay enables simultaneous amplification of short amplicons for up to 100 mRNA targets, and the Ziplex™ instrument quantifies the amplicons for highly sensitive gene expression profiling down to single cell levels. The aim of the study was to functionally assess this system. METHODS: The HyCEAD/Ziplex platform was used to quantify the expression levels for 72 genes using as little as 20 pg of total RNA or a single cultured tumor cell. Assay performance was evaluated using cells or total RNA spiked into Parsortix harvests of healthy donor blood. The assay was also evaluated using total RNA obtained from Parsortix harvests of blood from metastatic breast cancer (MBC) patients or healthy volunteers (HVs). RESULTS: Using genes with low expression in WBC RNA and/or in unspiked Parsortix harvests from HVs, the assay distinguished between the different breast cancer and ovarian cancer cell lines with as little as 20 pg of total RNA (equivalent to a single cell) in the presence of 1 ng of WBC RNA. Single cultured cells spiked into Parsortix harvests from 10 mL of HV blood were also detected and distinguished from each other. CVs from repeatability experiments were less than 20%. Hierarchical clustering of clinical samples differentiated most MBC patients from HVs. CONCLUSION: HyCEAD/Ziplex provided sensitive quantification of expression of 72 genes from 20 pg of total RNA from cultured tumor cell lines or from single cultured tumor cells spiked into lysates from Parsortix harvests of HV blood. The HyCEAD/Ziplex platform enables the quantification of selected genes in the presence of residual nucleated blood cells in Parsortix harvests. The HyCEAD/Ziplex platform is an effective tool for multiplexed molecular characterization of mRNA in small numbers of tumor cells harvested from blood.

Transcriptome Profiling of Circulating Tumor Cells to Predict Clinical Outcomes in Metastatic Castration-Resistant Prostate Cancer.

The clinical utility of circulating tumor cells (CTC) as a non-invasive multipurpose biomarker is broadly recognized. The earliest methods for enriching CTCs from whole blood rely on antibody-based positive selection. The prognostic utility of CTC enumeration using positive selection with the FDA-approved CellSearchTM system has been demonstrated in numerous studies. The capture of cells with specific protein phenotypes does not fully represent cancer heterogeneity and therefore does not realize the prognostic potential of CTC liquid biopsies. To avoid this selection bias, CTC enrichment based on size and deformability may provide better fidelity, i.e., facilitate the characterization of CTCs with any phenotype. In this study, the recently FDA-approved Parsortix® technology was used to enrich CTCs from prostate cancer (PCa) patients for transcriptome analysis using HyCEADTM technology. A tailored PCa gene panel allowed us to stratify metastatic castration-resistant prostate cancer (mCRPC) patients with clinical outcomes. In addition, our findings suggest that targeted CTC transcriptome profiling may be predictive of therapy response.

Malignancy Assessment Using Gene Identification in Captured Cells Algorithm for the Prediction of Malignancy in Women With a Pelvic Mass.

OBJECTIVE: To evaluate the detection of malignancy in women with a pelvic mass by using multiplexed gene expression analysis of cells captured from peripheral blood. METHODS: This was an IRB-approved, prospective clinical study. Eligible patients had a pelvic mass and were scheduled for surgery or biopsy. Rare cells were captured from peripheral blood obtained preoperatively by using a microfluidic cell capture device. Isolated mRNA from the captured cells was analyzed for expression of 72 different gene transcripts. Serum levels for several commonly assayed biomarkers were measured. All patients had a tissue diagnosis. Univariate and multivariate logistic regression analyses for the prediction of malignancy using gene expression and serum biomarker levels were performed, and receiver operating characteristic curves were constructed and compared. RESULTS: A total of 183 evaluable patients were enrolled (average age 56 years, range 19-91 years). There were 104 benign tumors, 17 low malignant potential tumors, and 62 malignant tumors. Comparison of the area under the receiver operating characteristic curve for individual genes and various combinations of genes with or without serum biomarkers to differentiate between benign conditions (excluding low malignant potential tumors) and malignant tumors showed that a multivariate model combining the expression levels of eight genes and four serum biomarkers achieved the highest area under the curve (AUC) (95.1%, 95% CI 92.0-98.2%). The MAGIC (Malignancy Assessment using Gene Identification in Captured Cells) algorithm significantly outperformed all individual genes (AUC 50.2-65.2%; all P <.001) and a multivariate model combining 14 different genes (AUC 88.0%, 95% CI 82.9-93.0%; P =.005). Further, the MAGIC algorithm achieved an AUC of 89.5% (95% CI 81.3-97.8%) for stage I-II and 98.9% (95% CI 96.7-100%) for stage III-IV patients with epithelial ovarian cancer. CONCLUSION: Multiplexed gene expression evaluation of cells captured from blood, with or without serum biomarker levels, accurately detects malignancy in women with a pelvic mass. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT02781272. FUNDING SOURCE: This study was funded by ANGLE Europe Limited (Surrey Research Park, Guildford, Surrey, United Kingdom).

Bridging the gap between theory and practice in elucidating modular gene regulatory sequence organisation within genomes.

Changes to promoter regions probably have been responsible for many morphological evolutionary transitions, especially in animals. This idea is becoming testable, as data from genome projects amass and enable bioinformaticians to conduct comparative sequence analyses and test for correlations between genotypic similarities or differences and phenotypic likeness or disparity. Although such practical pursuits have initiated some theoretical considerations, a conceptual framework for understanding promoter region evolution, potentially effecting morphological evolution, is only starting to emerge, predominantly resulting from computational research. We contribute to this framework by specifying three big problems for promoter region research; reviewing computational research on promoter region evolution; and exemplifying a topic for future promoter region research - module evolution.

Atypical protein kinase C zeta: potential player in cell survival and cell migration of ovarian cancer.

Ovarian cancer is one of the most aggressive gynaecological cancers, thus understanding the different biological pathways involved in ovarian cancer progression is important in identifying potential therapeutic targets for the disease. The aim of this study was to investigate the potential roles of Protein Kinase C Zeta (PRKCZ) in ovarian cancer. The atypical protein kinase C isoform, PRKCZ, is involved in the control of various signalling processes including cell proliferation, cell survival, and cell motility, all of which are important for cancer development and progression. Herein, we observe a significant increase in cell survival upon PRKCZ over-expression in SKOV3 ovarian cancer cells; additionally, when the cells are treated with small interference RNA (siRNA) targeting PRKCZ, the motility of SKOV3 cells decreased. Furthermore, we demonstrate that over-expression of PRKCZ results in gene and/or protein expression alterations of insulin-like growth factor 1 receptor (IGF1R) and integrin beta 3 (ITGB3) in SKOV3 and OVCAR3 cells. Collectively, our study describes PRKCZ as a potential regulatory component of the IGF1R and ITGB3 pathways and suggests that it may play critical roles in ovarian tumourigenesis.

Non-molecular-clock-like evolution following viral origins in homo sapiens.

Researchers routinely adopt molecular clock assumptions in conducting sequence analyses to estimate dates for viral origins in humans. We used computational methods to examine the extent to which this practice can result in inaccurate 'retrodiction.' Failing to account for dynamic molecular evolution can affect greatly estimating index case dates, resulting in an overestimated age for the SARS-CoV-human infection, for instance.

hCDC4 variation in osteosarcoma.

The hCDC4 gene (also known as Fbw7 or Archipelago) encodes an F-box protein that is responsible for targeting cyclin E for Skp1-cullin-F box protein (SCF) ubiquitination and proteosomal degradation. Disruption of this pathway has been associated with chromosomal instability and aneuploidy in several cancer cell lines and primary tumors. This study aimed to examine whether hCDC4 mutations contribute to aneuploidy in osteosarcoma. We analyzed 147 primary high-grade osteosarcoma specimens and 6 osteosarcoma cell lines. The protein truncation test (PTT) and single-strand conformation polymorphism (SSCP) analysis with subsequent sequencing were performed to detect alterations of the hCDC4 gene. All specimens exhibited the same PTT pattern of normal bands with less intense common bands. Two shifts were detected by SSCP, and subsequent DNA analysis identified one in-frame three-base GAG (424-426) deletion and one silent nucleotide substitution (C1261T). We conclude that somatic hCDC4 mutations are infrequent in osteosarcoma, and are unlikely to play an important role in aneuploidy of this tumor.