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Genome-wide survey of adjacent gene rearrangements in breast cancer identifies triple-negative specific BCL2L14-ETV6 fusions

ABSTRACT: Purpose: We investigated the function of overexpressed BCL2L14-ETV6 fusion variants in triple-negative breast cancer using high-throughput mRNA sequencing (RNA-Seq) analysis in BT20 human basal-like breast cancer cell line. Methods: The BCL2L14-ETV6 fusion variants or wildtype ETV6 cDNA containing the full-length ORFs were subcloned into the lentiviral pLenti7.3 vector, and later transduced into the BT20 cell line. BT20 cells were cultured in EMEM (ATCC) with 10 % fetal bovine serum (Hyclone). Total RNA was extracted from cells in individual confluent 10 cm dish, using the standard procedure of Qiagen RNeasy kit. The NovaSeq 6000 library for DNA sequencing was prepared using TruSeq Stranded mRNA Library Prep Kit (Illumina) following the protocol provided by the manufacturer. The final libraries were normalized by quantification with LightCycler 480 II (Roche Applied Science, Indianapolis, IN, USA) and qualification with Bioanalyzer (Agilent, Palo Alto, CA, USA). The final loading concentration was adjusted to 10 pM following the NovaSeq 6000 loading protocol. The NovaSeq 6000 S2 Reagent Kit (Illumina) was used for paired-end reads (2×150 bp) sequencing reactions. Sequencing data was given as raw data with a Phred Q30 score of 80 or better. Results: Confirming the overexpression of BCL2L14-ETV6 fusion variants, the reads that match to partial of BCL2L14 and ETV6 mRNA transcripts were 32~256 fold higher in the stable BT20 cell lines expressing BCL2L14-ETV6 fusion, compared to the cells the express the vector control. We found some key genes in cell migration and invasion are up-regulated in these stable BT20 cells compared with the cells the express the vector control and the wildtype ETV6. Conclusions: BCL2L14-ETV6 fusions endow enhanced cell migration and invasion in breast cancer.

ORGANISM(S): Homo sapiens

PROVIDER: GSE120919 | GEO | 2020/03/28

REPOSITORIES: GEO

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Project description:A high percentage of potential oncology drugs fail in clinical trials, partly because preclinical models used to test them are inadequate. Breast cancer is the leading cause of cancer-related death among women worldwide but we lack appropriate in vivo models for the ER+ subtypes, which represent more than 75% of all cases. We address these issues by xenografting tumor cells to their site of origin, the milk ducts. All ER+ cell lines and patient-derived xenografts grow mimicking their clinical counterparts. Disease progresses with invasion and metastasis, which become amenable to study. The action of hormones, important in breast carcinogenesis, can now be studied in a relevant context. Importantly, these open opportunities for development and evaluation of therapies. Eight- to twelve-week-old female SCID Beige mice (Charles River) were injected with 5x10e5 BT20-GFP/luc2 cells (n=3) or 5x10e5 HCC1806-GFP/luc2 cells (n=3) either into the mammary fat pad or 2x10e5 BT20-GFP/luc2 cells (n=3) or 2x10e5 HCC1806-GFP/luc2 cells intraductally (n=3). Xenografted BT20 and HCC1806 basal breast cancer cells were sorted by FACS based on GFP expression; total RNA was extracted using Trizol Reagent (Invitrogen), purified with the miRNeasy Mini Kit (Qiagen), quantity and quality were assessed by NanoDropÂ®ND-1000 spectrophotometer and RNA 6000 NanoChips with the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, USA). Only samples with RIN score >7.0 were included. For each sample, 300 ng of total RNA were amplified using the message amp II enhanced kit (AM1791, Ambion). 12.5 Î¼g of biotin-labelled cRNA were chemically fragmented. Affymetrix GeneChip Human Genome U133A 2.0 Arrays (Affymetrix, Santa Clara, CA, USA) were hybridized with 11Î¼g of fragmented target, at 45Â°C for 17 hours, washed and stained according to Affymetrix GeneChipÂ® Expression Analysis Manual (Fluidics protocol FS450_0007). Arrays were scanned using the GeneChipÂ® Scanner 3000 7G (Affymetrix) and raw data was extracted from the scanned images and analyzed with the Affymetrix Power Tools software package (Affymetrix). All statistical analyses were performed using R and Bioconductor packages (http://www.Bioconductor.org). Hybridization quality was assessed using the Expression Console software (Affymetrix). Normalized expression signals were calculated from Affymetrix CEL files using RMA. Differential hybridized features were identified using Bioconductor package â??limmaâ?? that implements linear models for microarray data (Smyth, 2004). P values were adjusted for multiple testing with Benjamini and Hochbergâ??s method to control false discovery rate (FDR) (Benjamini et al., 2001). Probe sets showing â?¥2-fold change and a FDR â?¤0.05 were considered significant.

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Genome-wide survey of adjacent gene rearrangements in breast cancer identifies triple-negative specific BCL2L14-ETV6 fusions

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