MYBL1 Knockdown in a Triple Negative Breast Cancer Line: Evidence of Down-Regulation of MYBL2, TCF19 and KIF18b Expression

Research Article

Austin J Cancer Clin Res. 2021; 8(1): 1090.

MYBL1 Knockdown in a Triple Negative Breast Cancer Line: Evidence of Down-Regulation of MYBL2, TCF19 and KIF18b Expression

Player A*, Abraham N, Abdulrahman N, Nsende E, Cunningham S and Rogers S

Department of Biology, Texas Southern University Houston TX, USA

*Corresponding author: Audrey Player, Department of Biology, Texas Southern University, Houston Texas, USA

Received: May 21, 2021; Accepted: June 12, 2021; Published: June 19, 2021


Purpose: The MYBL1 gene is a strong transcriptional activator, associated with cell cycle signaling and differentiation. Data show the gene is overexpressed in triple negative breast cancers. Considering the possibility that MYBL1 might be involved in events associated with the pathogenesis of these cancers, we sought to identify genes associated with MYBL1 expression in triple negative breast cancer.

Methods: shRNA lentiviral knockdown was used to down-regulate the MYBL1 gene. Microarray analyses were used to identify genes either directly or indirectly affected by targeting MYBL1 knockdown. Data analyses was performed utilizing Affymetrix TAC 4.0, Chip X transcription factor analyses, Target Scan miRNA analyses, and STRING analyses was used to determine protein: protein interaction and pathway analyses. Web Gestalt and Gene Ontology were used to determine pathway and gene-set enrichments. Publicly available patient and cell line datasets were retrieved and processed using resources available in Gene Expression Omnibus and Oncomine. The polymerase chain reaction and western analyses were used to determine transcript and protein levels, respectively.

Results: Knockdown of MYBL1 in a triple negative breast cell line led to down-regulation of MYBL2, TCF19, KIF18b along with an enrichment of cell cycle signaling genes. Gene expression analyses show that MYBL1, MYBL2, TCF19 and KIF18b display a similar pattern of expression in breast cell lines and many of the archival patient datasets examined.

Conclusion: TNBC is a heterogeneous subtype, so these data suggest that cancers that over-express MYBL1, express MYBL2, TCF19 and KIF18b. Bioinformatic analyses suggest MYBL1 regulates MYBL2 which leads to regulation of TCF19 and KIF18b.

Keywords: Triple negative breast cancer; MYBL1 knockdown; Microarray


CCNB1-cyclin B1; CEL-microarray cell intensity file; Chipchromatin immunoprecipitation; DMEM: Dulbecco’s Modified Eagle Minimum Essential Media; E2F-E2F: Transcription Factors; ERBB2-Erb-B2: Receptor Tyrosine Kinase 2; ER: Estrogen Receptor; GAPDH: Glyceraldehyde-3-Phosphate Dehydrogenase; GEO: Gene Expression Omnibus; GSE: Gene Set Expression; FOXM1: Foxhead Box M1; KIF18b: Kinesin Family Protein18b; LIN: Linc Complex; LV: Lentiviral Particles; miRNA: microRNA; MYBL: Myeloblastosis Viral Oncogene-Like Protein; PCR: Polymerase Chain Reaction; PGR: Progesterone Receptor; RBL: Retinoblastoma-Like Proteins; RBBP4: Retinoblastoma Binding Protein 4; shRNA: small hairpin RNA; STRING: Search Tool for the Retrieval of Interacting Genes/ Proteins; TCF19: Transcription Factor 19; TFDP: Transcription Factor Dp; TNBC: Triple Negative Breast Cancer


Triple Negative Breast Cancer (TNBC) is characterized as negative for three molecular signature genes, Estrogen Receptor (ER), Progesterone Receptor (PGR) and ERRB2. Even though the cancer is classified as an individual subtype, it is incredibly heterogeneous. Analyses of TNBC show that the sub type can be further classified into seven sub-categories [1]. Mostly, the TNBC are aggressive, they grow quickly, have a high recurrence rate and there are a limited number of treatment options for patients compared to patients with receptor positive breast cancers. Patients presenting with receptor positive gene expression are treated with hormone or targeted gene therapies; because TNBC slack the positive receptors, they do not respond to these therapies [2]. TNBC patients basically rely upon chemotherapy and radiation therapies. For this reason, the cancers are studied with the aim of identifying genes that might eventually be considered as potential targets for therapy.

The goal of our studies is to make a contribution towards characterizing TNBC. In an effort to characterize TNBC we performed comparative analyses of microarray datasets generated using cell lines and patient samples. Results from an earlier study [3] showed a differential pattern of expression of the MYBL1 gene in a subpopulation of TNBC compared to some luminal and most non-tumor breast samples. MYBL1 belongs to the MYB family of genes which includes c-MYB and MYBL2. The genes are protooncogenes that function as strong transcriptional activators involved in proliferation, differentiation and cell cycle signaling processes, all of which are associated with tumor progression [4-7]. The MYB proteins share substantial homology in their DNA binding domains [8] which allow for regulation of some of the same gene targets. The genes also contain distinctly different regions which allow for variations in post-translational modifications, which can ultimately lead to recognition and subsequent activation of different gene targets and biological activities [9]. Unique to MYBL1, the gene is a master regulator in the meiosis phase of the cell cycle in testis, demonstrating high levels in normal testes undergoing spermatogenesis [10]. Our studies have focused on characterizing MYBL1 in TNBC in an effort to ultimately determine the role of the gene in the pathogenesis of the cancers.

In addition to our studies, others show MYBL1 over-expression in luminal breast cancers [9] and the rare triple negative Breast Adenoid cystic carcinomas [11]. In one particular study, Liu et al [12] examined breast cancers via microarray and performed Supervised Network Analyses with the goal of determining the prognostic significance of over-expression of c-MYB and MYBL1 in receptor positive cancers. The investigators identified MYBL1 and nine other genes associated with poor prognosis in the receptor positive samples. In addition to breast cancers, MYBL1 is identified as over-expressed in colon cancers [13], uterine leiomyomas [14], murine B-cell lymphomas [15] and Burkitt’s lymphoma cells [16]. Considered together, these data support the study of MYBL1 for a possible role in cancers. Data show that changes in MYBL1 expression is caused by amplification, rearrangement and translocation events, with translocations involving NFIB and yet unspecified genes and mechanisms [11].

Based on our earlier observations and those by other investigators, we chose to study the MYBL1 gene in TNBC, with a focus on defining genes affected by its expression. Our immediate approach was to knockdown the MYBL1 gene in TNBC, followed by microarray and data analyses to identify genes coordinately dysregulated by the process. Preliminary results from this study are presented here. As expected, a significant portion of the candidate genes affected by decreasing MYBL1 expression were enriched in cell cycle signaling. Knockdown of MYBL1 led to a substantial decrease in MYBL2 expression as well. This observation is consistent with those by Rushton et al [9], which show that MYBL1 and MYBL2 are coexpressed and can activate some of the same genes more-so than any combination including the other family member, c-MYB.

A list of novel genes is identified as affected by the MYBL1 knockdown in the current study, the focus will describe the experimental validation of MYBL1, MYBL2 and two other genes, Transcription Factor 19 (TCF19) and Kinesin family protein 18b (KIF18B) genes.TCF19 and KIF18b are down-regulated following targeted knockdown of MYBL1 and down-regulation of MYBL2. Both TCF19and KIF18b have documented involvement with cell cycle signaling [17,18], in addition, data suggest the genes are involved in tumor progression which make them intriguing candidates to study in breast cancers as they relate to MYBL1. To our knowledge, this is the study to describe knockdown of MYBL1 in TNBC and the first documentation of a possible relationship between MYBL1, MYBL2, TCF19 and KIF18B. The relationship between the genes is unclear, although preliminary interpretations of the data suggest a close associationbetweenMYBL1 and MYBL2, and between MYBL2, TCF19 and KIF18b. Three miRNAs were up-regulated after MYBL1 knockdown and chosen as differentially expressed candidates as well. The miRNAs are selected based on differential expression and following Target Scan analyses [19] which predicts binding to either MYBL1 or MYBL2 transcripts. The small RNA results are presented in the current study, along with the experimental validation of the pattern of expression of MYBL1, MYBL2, TCF19 and KIF18b in a panel of breast cancer samples. The data show that similar to the results in the knockdown microarray, MYBL1, MYBL2, TCF19 and KIF18b show a co-ordinate pattern of expression in many of the breast cancer cell lines and patient samples.

Materials and Methods

Cell Lines, cell culture and patient sample datasets

MDA MB231, MCF7 and MCF10A cell lines were obtained from (Manassas, VA, USA) and used within one year of purchase. MDA MB231 represents an aggressive TNBC, MCF7 cells represent the luminal A subtype, and MCF10A cells represent a non-tumor triple negative (TN) cell type. The cells are cultured in Dulbecco’s Modified Eagle Minimum essential media (DMEM) (Millipore, Sigma, St. Louis, MO, USA) supplemented with 1% penicillin and 10 % serum (FBS) in a 37°C and 5% CO2 as suggested by the supplier. The cells were feed twice weekly and passaged when the cultures reached 90% confluence using a 0.25% trypsin solution (Millipore, Sigma, St. Louis, MO, USA). Patient and cell line datasets were retrieved from Gene Expression Omnibus (GEO; GSE65194, GDS2250, GSE12777, GSE29327)[20] and [21]. The MCF10a controls were extracted from the GSE29327 dataset and combined with the GSE12777 dataset. The Affymetrix spiked controls in both datasets were compared and found to generate an almost exact correlation, allowing for the samples in the two datasets to be combined.

shRNA knockdown of MYBL1 in MDA MB231 cells

The MYBL1 shRNA Lentiviral particles and the scramble control particles were purchased from Origene (Cat # TL303089V; Rockville Md, USA). Four MYBL1 target specific particles (packaged from the pGFP-C-shLenti vector; labeled LVA, LVB, LVC, LVD) were supplied by Origene and screened for their efficiency to suppress expression of the MYBL1 transcript. The lentiviral particles were transduced into MDA MB231 TNBC cells (at a MOI of 10:1) and screened to determine the sequence most effective at down-regulating the MYBL1 transcript. MDA MB231 cells were incubated with the targeted or scrambled viral particles for 72 hours in the presence of polybrene (sc-134220; Santa Cruz Biotechnology, Dallas TX, USA) in the complete cell culture media. Lentiviral particles were removed and fresh media was added to the cells. The transduced cells were selected following growth in 1ug/ml puromycin (CAS 53792; Santa Cruz Biotechnology, Dallas TX, USA). LVA particles, identified by the TCTGATCCTGTAGCATGGAGTGACGTTAC sequence, demonstrated the most significant down-regulation of MYBL1 mRNA, as a result this preparation was used for the future experiments. Cells transduced with LVA and the scrambled control sequence were maintained in the presence of puromycin.

RNA extraction and cDNA generation

In order to screen for the knockdown of MYBL1, total RNA was extracted from cells previously transduced with scrambled control or the MYBL1 sequences, and compared to RNA extracted from untreated cells. Total RNA was isolated using the Trizol reagent (Life Technologies Inc., Grand Island, NY) as suggested by the manufacturer. The quantity and quality of the RNA was determined via spectrophotometer and 3-N-Morpholinopropanesulfonic acid (MOPS) gel electrophoresis, respectively.

The cDNA was generated using the iScriptTM Reverse Transcriptase kit supplied by BioRad (Hercules, CA, USA) according to the manufacturer’s suggestion. This material was used for the down-stream Polymerase Chain Reaction (PCR) to determine the relative difference in gene expression levels between the various samples.

Primer design and PCR analyses

The current laboratory has access to breast cancer cell line transcriptomes processed using the Affymetrix U133 plus 2.0 microarrays. Information from these datasets were used as an indication of the gene expression levels of genes that were not treated with the lentivirus. These data along with GEO archival data and data generated from the knockdown datasets were crosscompared and utilized as part of the screening process used to identify candidate genes for the current study. Nucleotide sequences for the genes were retrieved from the NetAffxTM resources (http:// available at (Thermo Fisher Scientific, Waltham Mass). The PCR primers were designed using the Primer 3TM software [22], using the default program conditions. The gene specific primer are GAPDH (forward) TCCCTGAGCTGAACGGGAAG and (reverse) GGAGGAGTGGGTGTCGCTGT; MYBL1 (Affymetrix probe-set 213906_at) (forward) TGGATAAGTCTGGGCTTATTGG and (reverse) CCATGCAAGTATGGCTGCTA; MYBL2 (Affymetrix probe-set (201710_at) (forward) GAGGGGGTCTGTGAATCTGA and (reverse) CCATCCTAAGCAGGGTCTGA;TCF19(Affymetrix probe-set (223274_at) (forward) TCTTAGGGGAAGGGGAGAGA and (reverse) GTCACAGCCATCACACTGGT; KIF18b (Affymetrix probe-set 222039_at) (forward) GCTCTTTTCCCCACCTGTCT and (reverse) TTGGAAATCAAGGCACCATT. The PCR reaction was performed using the AmpliTaqGoldTM master mix reagent following the instructions outlined by the manufacturer (Thermo Fisher, Waltham Mass, USA). The PCR products were analyzed on a 2% agarose gel, and image analyses were performed using the LiCor (Lincoln NE, USA) gel analysis system.

Microarray and Data analyses

Microarray hybridizations of the knockdown preparations were performed at the University of Texas Southwest Core Facility (UTSW; Dallas Texas, USA). Total RNA samples were shipped overnight to UTSW. aRNA was prepared and hybridized to the Affymetrix Clarion microarray gene-chip. The CEL intensity files were made available, and data analyses was performed in our laboratory using the Affymetrix TAC 4.0 software (Thermo Fisher Scientific, Waltham Mass). CEL intensity results were normalized using RMA and the differentially expressed genes were generated following Limma Bioconductor analyses. Coding transcripts that displayed at least a 4-folddifference in expression between the targeted compared to the scrambled sequence were selected for analyses. A lower differential expression threshold (of 2x) was used for selection of the miRNAs, as the miRNAs were also screened via Target Scan analyses [19] to identify their predicted nucleotide targets. The p-values were not generated by the TAC 4.0 program as two Clarion microarrays were hybridized and subsequently processed to identify the differentially expressed genes. Web Gelstalt [23] and Gene Ontology [24] analyses were used to determine gene-set enrichment, pathway and functional analyses of differentially expressed genes identified in cell lines and patient samples. Transcript plots and analyses were performed using Microsoft Excel. was used to compare the gene lists ( factor enrichment analyses was performed using the multi-omics Chip-X Enrichment Analyses 3.0 (ChEA3) [25] platform which combines Chip-Seq evidence from ENCODE, ReMap, publications, GTEx, ARCHS4 and Enrichr libraries. Transcription factor binding was also assessed using the Signaling Pathway Project [26]. Protein: Protein Interactive (PPI) Network analyses were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRINGTM; [27]).

Western Blotting

Whole cells were prepared in Ripalysis buffer (Santa Cruz Biotechnology, Dallas TX, USA) and the supernatants were processed, electrophoresed and probed for detection of specific proteins using protocols available at Novus Biologics (Novus Biologics Littleton CO). The primary antibody concentrations and incubation times were determined following the recommendation of the suppliers.

Antibodies: Actin was used at a 1:100 dilution (NB600-501SS; Novus Biologicals LLC, Littleton CO), and MYBL1 was used at a 1:500 dilution (sc-514682; Santa Cruz Biotechnology, Santa Cruz CA). MYBL2 was used at a 1:500 dilution (sc-81192; Santa Cruz Biotechnology, Santa Cruz CA), TCF19 was used at a 1:100 dilution (sc-390923; Santa Cruz Biotechnology, Santa Cruz CA), andKIF18b was used at a dilution of 1:1000 (A303-982A; Bethyl Laboratories, Montogomery TX, USA).Secondary HRP conjugated Anti mouse (HAF007; R and D Systems, Minneapolis, MN) and Anti Rabbit (NBP-2-30348H; Novus Biologicals LLC, Littleton CO) antibodies were used at a dilution of 1:4000. Western blotting results were visualized with the Clarity Western ECL substrate (Bio-Rad, Hercules, CA, USA) on a LICOR digital imaging system (LI-COR Biotechnology, Lincoln, NE).


Screening and validation of MYBL1 shRNA lentiviral preparations

The aim of this current study is twofold. The first aim is to further characterize TNBC and because of an interest in MYBL1, the second is to identify genes directly or indirectly associated with MYBL1 expression in TNBC. In order to accomplish these aims, our approach was to knockdown the MYBL1 gene and examine the genes affected by this process. Four shRNA lentiviral sequences targeted for MYBL1, corresponding to different regions of the transcript, were purchased from, and screened to determine the sequence that effectively decreased MYBL1 transcript levels. The LVA sequence was the most effective at down-regulating the MYBL1 gene (Figure 1), as a result, this preparation was used for all of the future experiments. Before committing to the microarray analyses, the LVA MYBL1 and scrambled control sequences were examined further for their effect in MDA MB231 cells. The LVA particles were effective at knockdown of both the MYBL1 transcript (Figure 2a) which ultimately led to downregulation of the protein (Figure 2b) in MDA MB231 cells compared to the scrambled and untreated sample preparations.