Characterization of Small Genetic Variants
in Breast Cancer Cell Line Under Tamoxifen
Therapy
Mahnaz Nezamivand-Chegini1, Hamed Kharrati-Koopaee1, Seyed Taghi Heydari2, Hassan Giahi1, Fatemeh Sabahi3,
Ali Dehshahri4, Kamran Bagheri Lankarani2
1 Institute of Biotechnology, Shiraz University, Shiraz, Iran
2 Health Policy Research Center, Institute of Heath, Shiraz University of Medical Sciences, Shiraz, Iran
3 Department of Plant Protection, College of Agriculture, Shiraz University, Shiraz, Iran
4 Department of Pharmaceutical Biotechnology, Shiraz University of Medical Science, Shiraz, Iran
GMJ.2023;12:e2598
www.gmj.ir
Correspondence to:
Seyed Taghi Heydari, Biostatistics, Health Policy Re-
search Center, Institute of Health, Shiraz University of
Medical Sciences, Shiraz, Iran.
Telephone Number: +989173034420
Email Address: heydari.st@gmail.com
Received 2022-09-03
Revised 2022-12-24
Accepted 2023-01-28
Abstract
Background: Tamoxifen (TAM) is an eective hormone therapy that reduces the risk of cancer
recurrence. According to evidence, TAM contributes to the alterations of genetic variants back-
ground and plays a role in the eectiveness of treatments via alteration of the genetic variants. The
eects of TAM on genomic features were investigated in the current study by discovering genet-
ic variants and nding the answer to the following question: “Is there any association between
the alterations of genetic variants under TAM consumption and an eective treatment process?”
Materials and Methods: Whole-transcriptome (RNA-seq) dataset from four in-
vestigations including 10 TAM-treated samples and 9 untreated samples as the con-
trol groups were derived from European Bioinformatics Institute (EBI). Using the
process of variants calling, the dierential genetic variants between and gene on-
tology enrichment analysis were detected by CLC Genomics Workbench (12).
Results: Current study reported about 5.8 million genetic variants. The outcomes of the chi-
square test showed that distributions of genetic variants between control and treated samples
were signicant (p<0.05). The genetic variants comparison between the control and TAM-treat-
ed samples indicated that there were 67 dierential genetic variants. Gene ontology enrich-
ment analysis indicated that dierential genetic variants were associated with several tumor
suppressors and oncogenes including IL6ST, GEN1, FNTA. HSPA5, NSMCE2, and DDX11.
Conclusion: Most of the candidate genes with dierent genetic variants had dual
roles as oncogenes or tumor suppressors. Therefore, it can be argued that TAM does
not play a signicant role in an eective treatment through alteration of the genet-
ic variants. In other words, it cannot be concluded that the TAM therapy-resulted al-
terations of genetic variants play a positive or negative role in the treatment process.
[GMJ.2023;12:e2598] DOI:10.31661/gmj.v12i0.2598
Keywords: Tamoxifen; Breast Neoplasms; RNA-seq
GMJ
Copyright© 2021, Galen Medical Journal.
This is an open-access article distributed
under the terms of the Creative Commons
Attribution 4.0 International License
(http://creativecommons.org/licenses/by/4.0/)
Email:info@gmj.ir
Nezamivand-Chegini M, et al. Alterations of Small Genetic Variants Under Tamoxifen Therapy
2GMJ.2023;12:e2598
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Introduction
Cancer is one of the leading causes of mor-
tality worldwide and breast cancer is the
second most common disease in women [1].
Hormonal therapy is a medical strategy for
treating breast cancer [2]. Tamoxifen (TAM)
is considered the main non-steroidal drug for
the treatment of breast cancer in postmeno-
pausal women [3], which competitively in-
hibits estrogen activity through binding to the
estrogen receptor [4].
Several investigations have been carried out
to illustrate the hormonal therapy eects and
it will allow us to better understand the drug
response mechanism and select an eective
strategy for the therapeutic period [5-7]. The
appropriate drug response is a complex inter-
dependent procedure that is highly dependent
on multiple factors, including genetic variants
background, lifestyle, climate, smoking, and
alcohol consumption [8].
Genetic variants refer to the genetic dierenc-
es between individuals within a population
[9]. DNA is a vulnerable molecule against
various mutagens including ultraviolet, tox-
ins, chemical agent, and free radicals [10].
Recently, high-throughput sequencing plat-
forms have been applied as powerful tools
to investigate the association between a large
number of genetic variants and drug response
[11,12].
It is shown that TAM has a mutagenic eect
on the endometrium cells and increases the
incidence of endometrial tumors [13]. Re-
sults from an evaluation of rat hepatic tissue
showed that activated TAM could bind to
the guanine N2-position of DNA and conse-
quently, produce pro-mutagenic lesions [14].
More importantly, it was found that the TAM
mutagenicity eect induced DNA damage in
human endometrial cells [15]. Emons et al.
(2020) showed that TAM may play a key role
in tumor progression. It may increase the risk
of uterus cancers, such as endometrial cancer
and uterine sarcoma [16].
In vitro conditions, TAM would lead to gene
mutations and increased incidence of ab-
normal chromosomal structures in rat liver
tissues [17]. All of the mentioned literature
reviews indicated that TAM could play a crit-
ical role in the alterations of genetic variants’
background. Furthermore, vaginal dryness,
sleep problems, weight gain, hot ashes, and
depression have been reported as common
TAM side eects [18]. There are several ex-
amples regarding the role of genetic variants
in drug response. To achieve a therapeutic ef-
fect, there has to be an interaction between the
drug and its target. DNA variations can both
increase and decrease a drug binding anity
to its target. As an example, genetic variations
can change the antagonist role of the drug into
an agonist one; therefore, the most common
problem of treatment procedures is resistant
mutations in drug targets. TAM blocks estro-
gen receptor (ER-positive cancer) in the breast
cancer treatment procedure and consequently,
reduces the risk of cancer recurrence. It is an
anti-estrogen hormone that inhibits the estro-
gen receptors; however, its eciency would
be decreased as a result of mutations in estro-
gen receptors and leads to the conversion of
ER-positive into progesterone-positive cancer
(PR-positive cancer). Consequently, it causes
drug resistance development and a lack of re-
sponse to treatment [19].
It is noteworthy that genetic variations may
contribute to drug metabolism and aect drug
response. For instance, if the drug is rapid-
ly metabolized, its concentration will reduce
due to the weaker drug action or side eects.
Considering slower metabolism procedures,
higher drug levels would result in stronger or
longer-lasting eects and side eects [20].
The current study investigates the eect of
TAM consumption on genetic variants back-
ground in the breast cancer cell line (MCF7).
Since TAMs are mutagenic agents, there may
be a link between genetic variants alterations
and TAM treatment; therefore, it can aect the
treatment process. It can also provide new in-
sights to improve chance of survival, reduce
side eects, and select appropriate strategies
for treatment duration.
Materials and Methods
1. Data Collection
In the current study, the 19 whole-transcrip-
tome (RNA-seq) datasets of four investi-
gations were derived from European Bio-
informatics Institute (EBI) (https://www.
ebi.ac.uk/). The treatment group includes
Alterations of Small Genetic Variants Under Tamoxifen Therapy Nezamivand-Chegini M, et al.
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3
10 MCF7 cell lines treated with TAM and
4-hydroxytamoxifen (4-OHT), as well as 9
untreated MCF7 cell lines considered as the
control groups. More details of collected sam-
ples were provided in Table-1. An overview
of the genetic variants analyses for collected
samples is showed in Figure-1.
2.Quality Control and Trimming
Quality control features of CLC Genomic
Workbench (12) including length distribution,
GC content, ambiguous base content, Phred
score, nucleotide contribution, and duplicate
sequences were applied to achieve prop-
er quality control of the collected data [21].
Since adaptor sequences were cleaned in the
achieved datasets, the adaptor trimming was
not formed.
3.Genetic Variants Analysis
3.1. Reference Genome and Alignments Anal-
ysis
The reference genome (hg38) and all anno-
tations were downloaded from the Ensembl
database (www.ensembl.org). Mapping of
short reads against the reference genome was
performed by CLC Genomics Workbench 12
based on the following parameters: masking
track=mRNA sequence, mismatch cost=2,
cost of insertions and deletions=linear gap
cost, insertion cost=3, deletion cost=3, length
fraction=0.7, and similarity fractio=0.8 [22].
3.2. Variant Calling and Statistical Analysis
CLC genomics workbench 12 was applied for
variant detections; also, there was no constant
Figure 1. The summary of dierential genetic variants analysis between treated breast cancer cell line
(MCF7) by TAM and control group (untreated MCF7).
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Nezamivand-Chegini M, et al. Alterations of Small Genetic Variants Under Tamoxifen Therapy
ploidy level in cancer cell lines. Therefore,
the variant calling procedure was performed
with a low-frequency algorithm based on the
following parameters: required variant prob-
ability (%)=95.0 ignore broken pairs=yes,
minimum coverage=10, minimum count=2,
minimum frequency (%)=30, base quality l-
ter=Yes, neighborhood radius=15, minimum
central quality=30, and minimum neighbor-
hood quality=25 [23]. A Chi-square test was
performed to explain the dierences in genet-
ic variants distribution between control and
treated samples.
3.3. Comparing the Variants and Gene Ontol-
ogy (GO) Enrichment Analysis
After performing the variants calling process,
genetic variants of TAM-treated samples were
compared with the reads from control sam-
ples to remove the common genetic variants
between treated and control samples. The
le of gene ontology association, including
the gene names and associated gene ontology
terms, was downloaded from the gene ontolo-
gy consortium (http://geneontology.org/) and
imported to CLC Genomic Workbench 12.
Moreover, dierential genetic variants were
applied to perform GO enrichment analysis
at the levels of biological process, molecular
function, and cellular component. The signif-
icance of the level of GO analysis was deter-
mined to be 0.01.
Results
Genetic Variants Detection
Results of quality control indicated that there
was no special trimming strategy required
for RNA-seq datasets. The average quality
control factors (per read) of the studied sam-
ples were reported as the following parame-
ters, length distribution=131.5 bp, GC con-
tent=52.35%, ambiguous base content=0.2%,
Phred score=18.12, nucleotide contribution=
0.5% and duplicate sequences=2.10%. How-
ever, trimming was carried out according to
the Phred score and the nucleotide contribu-
tion to minimize the mapping errors. At least
ten primary bases were trimmed from the 3′
side of short reads, and 5% of reads contain-
ing the lowest Phred scores were also ignored.
Results of alignments of short reads against
the reference genome (hg 38) are provided in
Table-2. Furthermore, 66%-89% was reported
for the mapping percentage.
Current research has identied almost 5.8
million genetic variants including single nu-
cleotide variations (SNVs), multi nucleotide
variations (MNVs), insertion, deletion, and
replacement. The highest and lowest frequen-
cies among detected genetic variants were re-
spectively related to SNVs and replacement.
More details of genetic variant frequencies
are depicted in Figure-2.
To investigate the eect of TAM on genetic
variants distribution within control and treated
samples, a statistical analysis was performed
separately for each genetic variant based on a
chi-square test for total genetic variants in the
control and treated samples. Results showed
that the genetic variants distribution between
control and treated samples was signicant
(P≤0.05) (Table-3), which indicated the pos-
sible eects of TAM on the genetic variants
frequency.
A comparison of genetic variants in control
and treated samples indicated that there were
67 dierential genetic variants. Among all
Table 1. More details of RNA-seq Datasets to Discover the Dierential Genetic Variants.
Accession numbers
of experiments
Control
samples
Treated
samples
Drug type
(dosage) Cell line
Duration of
treatment
(hr)
E-MTAB-822 1 2 TAM (1 μM) MCF7 12
E-GEOD-59536 1 1 4-OHT (1 μM) MCF7 24
E-GEOD-62613 1 1 4-OHT(1 μM) MCF7 24
E-GEOD-78199 6 6 TAM (100 nM) MCF7 24
Total 9 10 ---- ----
hr: hours; TAM: Tamoxifen; 4-OHT: 4-hydroxy tamoxifen.
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Alterations of Small Genetic Variants Under Tamoxifen Therapy Nezamivand-Chegini M, et al.
of the dierential variants, 16 genetic vari-
ants were located in the coding regions and
10 variants led to the change of amino acid
sequence within the protein structure. Table-4
shows more details of dierential genetic
variants.
The process of gene ontology enrichment
analysis of dierent genetic variants was car-
ried out at three levels of biological process,
cellular component, and molecular function;
therefore, a total number of 77 signicant GO
terms was reported (Table-5). At the biolog-
ical process level, the most repetitive of re-
ported overlapping gene names were GEN1,
HSPA5, NSMCE2, AURKA, and DDX11
candidate genes.
Results achieved from molecular function
analysis indicated that the most frequently
enriched candidate genes in signicant GO
terms were IL6ST, COX15, and FNTA. The
cellular component analysis showed that the
nucleus and nucleoplasm were the most im-
portant cellular parts that may contribute to
hormonal therapy.
Discussion
Breast cancer is a heterogeneous disease,
which is divided into three groups of ER-pos-
itive, PR-positive and triple-negative breast
cancer (TNBC). Hormone therapy may be
used for ER and PR positive tumors; howev-
Table 2. The Mapping Summary of Short Reads against the Reference Genome.
Accession number Samples Total reads Mapped
reads%
E-GEOD-59536 T1 89713168 68.80
E-GEOD-62613 T2 112247072 85.91
E-GEOD-78199
T3 34981408 81.22
T4 36012214 81.20
T5 40160428 82.10
T6 41384146 82.05
T7 39870210 81.72
T8 41063128 81.74
E-MTAB-822 T9 10069398 87.85
T10 12018685 83.10
E-GEOD-59536 C1 97511228 66.10
E-GEOD-62613 C2 103822108 87.37
E-GEOD-78199
C3 39172180 82.47
C4 40347538 82.44
C5 44328838 80.16
C6 45695050 80.15
C7 36382948 82.53
C8 37484422 82.50
E-MTAB-822 C9 8569125 89.25
T: treated samples; C: control samples.
Table 3. Results of Statistical Analysis of Genetic
Variants Distribution between Control and
Treatment Samples.
Genomic variants P-value
SNV*** <0.001
MNV*** <0.001
Insertion*** <0.001
Deletion*** 0.001
Replacement*** 0.001
SNV: single nucleotide variations, MNV: multi
nucleotide variations
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Nezamivand-Chegini M, et al. Alterations of Small Genetic Variants Under Tamoxifen Therapy
er, TNBC could not respond to common hor-
mone therapy [24]. TAM is a type of hormon-
al therapy implemented to treat ER-positive
breast cancer; it may also reduce the risk of
invasive cancer development.
Our hypothesis regarding the role of TAM in
the treatment process has not been fully con-
rmed. It was found that most of the candidate
genes with dierential genetic variants had
dual roles as oncogenes or tumor suppressors;
moreover, their exact contribution to breast
cancer has not been investigated precisely.
For example, the results of the genetic vari-
ant analysis revealed that dierential genetic
variants between control and treated sam-
ples (under TAM therapy) were overlapped
with GEN1, HSPA5, NSMCE2, AURKA,
and DDX11. GEN1 (Flap endonuclease GEN
homolog 1) encoded a member of Rad2/xero-
derma pigmentosum group G nuclease family.
As it was observed for BRCA1 and BRCA2,
GEN1 contributed to resolve the Holliday
junction in the homologous recombination. It
is noteworthy that the Holliday junction may
play a vital role in the cancer chemo-sensitiv-
ity [25]. Somatic truncating GEN1 mutations
have been reported in breast cancers; there-
fore, it would indicate the fact that GEN1
may be a predisposition gene in breast cancer.
However, it was shown that although it plays
a critical role in the double-strand DNA break
repair, GEN1 would not make any apprecia-
ble contribution to breast cancer susceptibility
through acting as a high- or intermediate-pen-
etrance breast cancer predisposition gene,
such as BRCA1, BRCA2, CHEK2, ATM,
BRIP1, and PALB2 [26]. Sun et al. (2014)
suggested that GEN1 would play a vital role
in DNA damage response; therefore, its alter-
ation could lead to breast cancer [27].
Heat-shock protein 5 (HSPA5) is considered
a marker of poor prognosis in patients with
Table 4. The Classication of Dierential Genetic Variants between Control and Treated Samples
Genetic variants Dierential
variants
Coding region Non-coding
regions
Amino acid
changes
SNV 45 15 30 9
MNV 7 0 7 0
Insertion 5 0 5 0
Deletion 10 1 9 1
Replacement 0 0 0 0
Total 67 16 51 10
SNV: single nucleotide variations; MNV: multi nucleotide variations
Figure 2. Frequencies of reported genetic variants in the control and treated samples. Parts A and B
illustrate the frequencies of detected genetic variants within control and treated samples. A total number of
2,853,482, and 2,988,729 genetic variants were reported for control and treated samples.
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7
Alterations of Small Genetic Variants Under Tamoxifen Therapy Nezamivand-Chegini M, et al.
breast cancer, which plays a critical role in
promoting drug resistance and metastasis [28].
A close association was observed between the
cancer behaviors of the heat shock proteins
(HSP) family; however, all members of the
HSP family have not been studied completely
[29]. NSMCE2 is an E3 SUMO ligase and a
subunit of the SMC5/6 complex that could be
associated with DNA repair [30].
Although SMC5/6 complex functions were
not described precisely, reports indicated that
it could act as a tumor suppressor in mice
[31]. Aurora Kinase A (AURKA) is a serine/
threonine kinase contributing to the regulation
of cell cycle progression; therefore, it could
be a potential cancer susceptibility gene [32].
Furthermore, it is considered a promising tar-
get in the treatment processes of patients with
cancer [33].
DDX11 is a DNA helicase that plays a role
in DNA replication, sister chromatid cohe-
sion establishment, and general chromosome
structure. The eects of DNA helicases among
patients with cancer are dependent upon their
genetic background and tumor type; however,
it has not been illustrated precisely and there
are various reports of their activities. For ex-
ample, it was suggested that DNA helicase
may have a tumor suppressor function, and
the expression level of several DNA helicases
at pre-cancerous stages would increase sig-
nicantly [34].
At the molecular function level, results of GO
analysis indicated that dierent genetic vari-
ants were associated with FNTA, IL-6, and
COX15 candidate genes. FNTA is located on
chromosome 8 and encodes the subunit alpha
of the protein farnesyltransferase (FTase) en-
zyme (UniProtKB: P49354). It was found that
FNTA could be a key gene for tumor progres-
sion; moreover, its abnormal copy numbers
were associated with pathological transforma-
tions of breast cancer.
Therefore, it could be considered as the main
target of developing drugs [35].
Interleukin-6 (IL-6) as a cytokine released by
various cells including cancerous cells con-
tributed to the expansion and dierentiation
of tumor cells [36]. It was also shown that
IL6ST may respectively act as a main factor
and a tumor suppressor gene in TNBC pro-
gression, and diagnosis and treatment proce-
dures [37]. Additionally, the IL6ST candidate
gene was reported as a specic candidate gene
for TNBC [38]. COX15 gene encodes cyto-
chrome C Oxidase subunit 15 and contributes
to the mitochondrial respiratory chain (Uni-
ProtKB: Q7KZN9). Gao et al. (2017) reported
that the high-level expression of the COX5B
gene was associated with a poor prognosis in
breast cancer [39]. It was suggested that the
level of COX5B protein may be related to the
tumor size; also, its up-regulated form showed
a worse disease-free survival. However, there
was not enough evidence to illustrate the clin-
ical implications of COX5B in breast cancer.
Conclusion
Results of dierential genetic variants analy-
sis between control and treated samples indi-
cated that the most reported candidate genes
had dual roles as oncogenes or tumor suppres-
sors. Therefore, it was suggested that TAM
could not have any signicant role in an eec-
tive treatment through changing the genetic
variants’ background.
Acknowledgments
Current study was nancially supported by
National Institute for Medical Research De-
velopment (NIMAD, grant number: 982563).
Conict of Interest
The authors declare no conict of interest.
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