Validation of Assessment of Bmi-1 on Protein and Molecular Levels in Oral Dysplasia and Squamous Cell Carcinoma: A Diagnostic Study
Phase: NA
Conditions: Oral Squamous Cell Carcinoma
Sponsor: Cairo University

Validation of Assessment of Bmi-1 on Protein and 
Molecular Levels in Oral Dysplasia and Squamous 
Cell Carcinoma: A Diagnostic study  
 
 
 
November, 10 2017 
 
 
 
Presented By: 
 
Asmaa Mohamed Abou Gabal 
 
 
 
 
 
 
 
 
 
 
 
 

I. Title:  
 
Validation of Assessment of Bmi-1 on Protein and Molecular Levels in Oral 
Dysplasia and Squamous Cell Carcinoma: A Diagnostic study 
II. Introduction:  
 
Head and neck squamous cell carcinoma (HNSCC) including oral squamous 
cell carcinoma (OSCC) has been reported as the sixth most common cause of cancer 
mortality in the world and the fifth most commonly occurring cancer [1]. Thus a 
compelling need for investigation of the underlying molecular events associated with 
OSCC tumorigenesis has emerged for better understanding of such lesion. Moreover, 
identification of biomarkers for early detection and prediction of prognosis became of 
extreme importance, as it was reported that early diagnosis has been vital for 
effective treatment of OSCC and improved the survival rate of OSCC patients [2, 3]. 
 
OSCC may originate from malignant transformation of the normal oral 
mucosa, as well as from oral potentially malignant lesions (OPMLs) with different 
degrees of oral epithelial dysplasia (OED) [4]. The approach of a step-wise transition 
from OPMLs to OSCC was well-established, but it could be difficult to predict if and 
when an OPML would undergo full transformation and resulted in a tumor[5]. Thus, 
using specific molecular biomarkers able to identify OED lesions with higher 
potential for malignant transformation would be very beneficial[4].  Unfortunately, 
up to date there has been no tools available to monitor OED lesions or HNSCC 
patients for early stages of local recurrences or distant metastases [6]. 
 
Among the recently introduced biomarkers, B-lymphoma Moloney murine 
leukemia virus insertion region-1 (BMI1), a member of the polycomb group (PcG) 
genes, was considered to be pivotal in regulating stemness-related genes involved in 
maintaining the self-renewal ability of stem cells by promoting chromatin 
modifications. BMI1 was also known to be deregulated in various human types of 
cancer [7] [8] [9] [10]. Previous studies have revealed the capability of BMI1 to be 
used as a prognostic marker in gastric[11], esophageal[12], nasopharyngeal 
cancer[7], prostate[13], breast [9], cervical [14] and ovarian cancer [10], However, 

the role of BMI1 in maintaining self-renewal and tumorigenicity in HNSCC or 
HNSCC-derived cancer stem cells (CSCs) remained to be clarified. 
III. Review of literature: 
 
HNSCC often developed within pre-neoplastic fields of genetically-altered 
cells with different degrees of OED. The presence of OED in OPMLs was generally 
accepted as one of the most reliable predictors of malignant development 
[15], however, histopathologic diagnosis was subjective and lacked sensitivity. No 
approval was reported on which dysplastic features were important in predicting 
progression. In addition, there was both inter- and intra-observer variation in 
illustrating the degree of epithelial dysplasia[5].Thus, several studies have been 
administered to identify objective molecular biomarkers to diagnose and prognose 
OED using different types of markers such as loss of heterozygosity, DNA ploidy, 
telomerase activity, methylation, and gene expression analysis [5]. 
Despite the advances that have been made in HNSCC treatment, prognosis 
remained discouraging. The major cause of recurrence and metastasis, both local and 
distant could be attributed to the diverse architecture of this tumor that consisted of 
functionally heterogeneous lineages of cancer cells that harbour cancer stem cell 
(CSC) properties [16] [17] [18] [19]. This hypothesis has gained support in a variety 
of tumors in addition to cultured cancer cell lines [20] [21] [22]. These CSCs have 
shown to be key contributors to radio- and chemoresistance and were responsible for 
tumor progression and recurrence after conventional therapy [23] [24].  
 
CSCs were defined by their extensive self-renewal, differentiation and tumor 
initiation properties [25]. They were considered as the actual tumor initiating 
subpopulation and could expand depending on its evolutionary landscape during 
cancer development [16]. Recent findings have suggested that the persistent survival 
of CSCs, might contribute to the aggression and recurrence of HNSCC [26] [27] [23, 
28]. Moreover, published studies suggested a direct link between epithelial-
mesenchymal transition (EMT) and the gain of CSC-like properties[29]. The EMT 
process was considered as a critical step in the induction of tumor metastasis and 
malignancy [30]. 
 

 
The acquisition of genetic or epigenetic predisposition to tumorigenicity by 
CSCs has been shown to be a cumulative process [31] that might be evident in 
premalignant lesions [32] [33]  as well as oral epithelial tumorigenicity [34]. This 
increased the importance of unraveling the underlying molecular events associated 
with CSC population, as they could serve as early detectors of malignant potential in 
OED and prognosis of OSCC. Thus, the signaling pathways required for the 
maintenance of CSCs became candidate targets of recent investigations in this field. 
Currently, light was shed on B-lymphoma Moloney murine leukemia virus 
insertion region-1 (BMI-1) which has been implicated in the regulation of CSCs. 
 
  
BMI-1 oncogene is a member of the polycomb-group gene family and a 
transcriptional repressor. BMI-1 was first recognized in a B-cell lymphoma as a 
transcriptional repressor that was a member of the PcG transcription factors [35]. 
Certain studies have revealed that BMI-1 was involved in the self-renewal, 
differentiation and tumor initiation of CSCs [36] [37] [25]. Nevertheless, the 
molecular mechanisms underlying these biological processes remained vague. 
 
 In addition, BMI-1 was known to be upregulated in various human cancer 
tissues and was important in the regulation of malignant transformation, proliferation, 
cell cycle, apoptosis and distant metastasis [38]. Actually, many studies have reported 
that Bmi1 was overexpressed in HNSCC cells when correlated to normal epithelium 
and was thought to impact cell proliferation and survival in HNSCC [39] [40] [41] 
[42]. Song et al 2009., demonstrated that Bmi-1 mRNA and protein expression levels 
were found to correlate with the invasion of nasopharyngeal carcinoma [7]. 
 
In clinical specimens of HNSCC, many researchers have established that the 
overexpression of Bmi-1 correlated with poor overall survival [43] [39] [41]. 
Likewise, He et al 2015., added that the expression of Bmi1 was correlated with poor 
overall survival and was also associated with lymph node metastasis and clinical 
stage.  

Association of Bmi1 overexpression, and stem-like properties in tumor cells 
could be attributed to induction of the EMT that promoted invasion, metastasis, and 
poor prognosis [41]. In the same background, Yang et al., 2010 showed that BMI1 
was necessary for EMT during tumor development in head and neck cancer patients 
[8].  
Strong evidence suggested that Bmi1 was important to invasive potential and 
favored to the maintenance and self-renewal of CSCs in several tumor types, 
including HNSCC [44] [41] [24] [45]. As a stem cell marker, Bmi1 played a key role 
in the functioning of endogenous stem cells and CSCs  [46] [45]. Additionally, it has 
been found to be related to many other CSC markers  such as SOX2 [47], Oct4 [48],  
Nanog [48], ALDH1[32], ABCG2 [2] and CD44 [49] [50]. Seo et al., 2011 found a 
connection between BMI-1 and Sox2 in maintaining self-renewal and identified 
BMI-1 as a key mediator of Sox2 function [47]. 
 
Moreover, recent studies have revealed that Bmi-1 expression was associated 
not only with the development of oral cancer, but also in patients with oral 
leukoplakia (LP)[40], oral erythroplakia[32], and oral lichen planus[42]. 
Furthermore, Bmi-1 overexpression was found in LP, and increased significantly 
from mild to moderate and severe LP. Consistent results were reported in Kang`s 
research, which showed that Bmi-1 overexpression was observed in preneoplastic 
oral mucosal tissues, including mild, moderate or severe OED [51]. Ma L et al., 
2013 suggested that Bmi1 may act as a beneficial marker for the recognition of high 
risk of malignant progression of OLP [42]. 
 
Wang et al., 2015 studies have indicated that silencing BMI-1 can decrease 
the malignant biological behavior of cancer, in addition to the self-renewal and 
differentiation of CSCs. Therefore, BMI-1 was hypothesized to affect the malignant 
biological behavior of human tumors by regulating the self-renewal and 
differentiation of CSCs. In conclusion, BMI-1 might represent a hopeful target for the 
prevention and therapy of various types of human cancer. Further understanding the 
molecular mechanism underlying the regulation of BMI-1 in human cancer and CSCs 
is of extremely huge clinical value [52].  
 

PIRT 
P Diagnostic validity of Bmi-1 levels in archival paraffin embedded tissue samples 
of oral dysplasia and squamous cell carcinoma. 
I 1  Expression of Bmi-1 protein level by immunohistochemistry in oral dysplasia 
and squamous cell carcinoma. 
I 2 Expression of Bmi-1 molecule at RNA level by PCR in oral dysplasia and 
squamous cell carcinoma. 
 R biopsy embedded in paraffin blocks. 
Toral dysplasia and squamous cell carcinoma. 
IV. Researh Question: 
 
Does the expression of Bmi-1 vary from oral epithelial dysplasia to different 
grades of squamous cell carcinoma at protein and molecular levels?  Which one of 
them is more sensitive and specific for Bmi-1 assessment, the protein or molecular 
levels?  
 
 
 

 
V. Methods: 
Source of data:  
Convenient consecutive sampling; it will include all archived blocks in the past 5 
years (2012-2017).  
Study design: Prospective cohort (In vitro validation study test) 
Participants: 
 
The archival paraffin embedded tissue samples which will be included in this 
diagnostic study are 30 samples of oral dysplasia and squamous cell carcinoma. We 
will apply a convenient consecutive sampling; it will include all archived blocks in 
the past 5 years (2012-2017) for this validation study. Excluded are samples of 
sarcomas or benign tumors or any carcinoma other than squamous cell carcinoma or 
any other techniques rather than immunohistochemistry or PCR. Samples that 
fulfilled the eligibility criteria will be included consecutively (consecutive sampling) 
until the target sample size will be reached. Data regarding Bmi-1 antibody  
expression in oral dysplasia and  different grades of squamous cell carcinoma will be 
collected prospectively from both the reference and index tests independently. 
Predictors: 
 
Biopsy embedded in paraffin blocks was selected as reference standard method to 
assess the expression of Bmi-1 antibody at protein and RNA levels by 
immunohistochemistry and PCR respectively.  

 
FIRST , PCR ANALYSIS 
According to Borbély et al 2007 tissue blocks will be prepared as follow: 
1- Tissue of 30 microns will be cut from paraffin blocks using scalpel and was 
put in eppendorf. 
2- 200 ml of tissue lysis buffer (ATL) + 0.6 ml of DNAs inhibitors + 10 ml 
proteinase K will be added to the sample. 
3- Sample will be incubated at 55 ˚C for 20 min. 
4- 250 micron of ethanol will be added and the sample will be left for 5min at 
room temperature. 
5- Sample will be collected by micropipette into spin column and will be 
centrifuged at 8000/ rpm for 1 min. 
6- 500 microlitre of wash buffer 1 will be added and the spin     column will be 
centrifuged at 8000/ rpm for 1 min. 
7- 500 microlitre of wash buffer 2 will be added and the spin column will be 
centrifuged at 8000/ rpm for 1 min. 
8- 500 microlitre of elusion buffer will be added and the spin column will be 
centrifuged at 14,000/ rpm for 3 min. 
9-  490 microlitre of distilled water will be added for each of DNA extracted 
sample. 
10- Spectrophotometer assessment will be done for concentration and 
purification of extracted nucleic acid (measurement of extracted nucleic acid 
260/280 absorbance UV. 

11- The sample will be divided into two portions in 200 ml eppendorfs. 
12- The first portion will be added to SYBERGREEN for amplification and 
quantitation of Bmi-1 gene by real time PCR using APPLIED BIO SYSTEM 
(U S A). 
13- The second portion will be added to SYBERGREEN for amplification and 
quantitation of Bmi-1 receptor gene by real time PCR using APPLIED BIO 
SYSTEM (U S A). 
SECOND, IMMUNOHISTOCHEMISTRY 
A-Reagents:   
1- Primary antibody BMI-1 rabbit polycolonal antibody 
2- The universal immunostaining detection kit (Dako Cytomation Envision+ 
Dual link system, Peroxidase (DAB+) Code K4065, Carpinteria, CA,USA). 
3- Buffer: Phosphate buffer saline (PBS) of pH 7.4 (1.48 gm dibasic sodium 
phosphate anhydrous, 0.43 gm monobasic potassium phosphate anhydrous and 
7.2 gm sodium chloride in one liter of distilled water). 
 
B-Procedures: 
1- Deparraffinization: The paraffin sections will be deparraffinized in three 
changes of xylene, and will be placed for 10 minutes in each change at room 
temperature. 
The excess liquid will be drained and the slides will be transferred to alcohol, 
15 minutes for each descending grades of concentrations (100%, 70% then 
50%). Then the slides will be rinsed under tab water for 5 minutes. 
Immersion of slides in PBS (2changes),5 minutes for each.  
2- Epitope retrieval: Citrate Buffer Epitope Retrieval method will be used in this 
technique. Briefly, a steamer for water bath will be preheated with staining 
dish containing citrate buffer (ph 6.0) until temperature will be reached 95-
100˚C. Slides will be immersed in the staining dish and the lid will be loosely 
placed then will be incubated for 20 minutes and will turn off the steamer. The 

staining dish will be placed at room temperature and will be allowed to cool 
for 20 minutes.  
3- Primary antibody: sections will be incubated in rabbit anti-Bmi-1 individually 
for 1 hour at room temperature. Sections will be rinsed in 2 changes of 
washing buffer, 2 minutes each. 
4- Serum block: sections will be incubated with normal horse serum blocking 
solution for 30 minutes to block non-specific binding of immunoglobulin. The 
best results will be obtained with dilution 1:25. Slides will be rinsed in 
washing buffer for 2×2 min 
5- Peroxidase blocking: sections will be incubated in peroxidase blocking 
solution for 10 minutes to block endogenous peroxidase activity. 
6- Slides will be rinsed in washing buffer 3×2 min 
7- Secondary antibody: sections will be incubated with biotinylated horse Anti-
Mouse IgG diluted in secondary antibody dilution. 
8- Slides will be rinsed in washing buffer 3×2 min. 
9- Chromogen/substrate: sections will be incubated in DAB peroxidase substrate 
solution for 5-10 min and then will be rinsed with distilled water 
10- Slides will be counter stained with Mayer’s haematoxylin solution, then  will 
be rinsed in running tap water for 5 minutes 
11- Slides will be dehydrated through 95% ethanol for 2 minutes, 100% ethanol 
for 2×3 minutes 
12- Finally, they will be cleared in xylene for 2-3 minutes and cover slipped with 
permanent mounting medium. 
Since BMI-1 level is measured objectively then no blnding is required. 
First: 
Calculation 
of 
Relative 
Quantification 
(RQ) 
(relative 
expression): 
After the RT-PCR will run, the data will be expressed in Cycle threshold (Ct).PCR 
data sheets will include Ct values of assessed gene and the house keeping (reference) 
gene which will be continuously expressed in the cell- (β-actin).To measure the gene 
expression of certain gene, -ve control sample shall be used. So target gene 
expression will be assessed and related to reference (internal control) gene as follows: 
Finally, RQ was calculated according to the following equation: 

1. ∆ Ct (Cycle threshold) = Ct assessed gene – Ct reference gene 
2. ∆∆ Ct = ∆ Ct sample – Ct control gene 
3. RQ = 2-(∆∆Ct) 
Second: Image analysis: 
In order to provide more précised data on Bmi-1 immunoexpression in OSCC, 
image analyzer will be used. 
The data will be obtained using the software (SIS, Germany), which comprise a 
light microscope (Olympus B × 60 Japan) capable of performing high speed 
digital image processing for the purpose of cell measurements. It will be 
calibrated automatically to convert the measurement units (pixels) produced by 
image analyzer program into actual micrometer units. In immunohistochemical 
sections, and by using the image analyzer, five specific fields showing maximum 
positivity of Bmi-1 expression will be used in each case; the mean of five values 
of each slide will be calculated and statistically will be ananlyzed. For each field 
of immunostained section, a measuring frame of area 1920000 pixels and then the 
area % will be calculated. The color of immunostaining will be automatically 
selected according to the positive control sections, converted into grey color then 
masked the red and white to allow automatic measurements by the computer 
system. Data obtained will be subjected to statistical analysis using Student-t test. 
Since BMI-1 level is measured objectively then no blnding is required. 
Sample size 
The aim of the current study is to assess the validation of Bmi-1 detection at both 
protein and molecular levels in oral epithelial dysplasia and oral squamous cell 
carcinoma as a biomarker for early cancer detection versus biopsy embedded in 
paraffin blocks. We are going to apply a convenient consecutive sampling; it will 
include all archived blocks in the past 5 years (2012-2017) about 30 samples. 
 
 

Statistical analysis methods:  
 
 Data will be analyzed using IBM SPSS advanced statistics (Statistical Package for 
Social Sciences), version 21 (SPSS Inc., Chicago, IL). Numerical data will be 
described as mean and standard deviation or median and range. Categorical data will 
be described as numbers and percentages. Correlation analysis will be used. 
Agreement between both methods will be analyzed with the use of kappa statistics. 
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