3.1 Genetic variants detection
Results of quality control indicated that there was not any necessary special trimming strategy for RNA-seq datasets. To minimize the alignment errors, 5% of the short reads with the lowest Phred scores were removed. Results of alignments of short reads against reference genome (hg 38) are provided in Table2. Furthermore, 66%-89% was reported for the mapping percentage.
Table2. The mapping summary of short reads against 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
There were almost 5.8 million genetic variants identified in current study including single nucleotide variations (SNVs), multi nucleotide variations (MNVs), insertion, deletion, and replacement. The highest and lowest frequencies among detected genetic variants were respectively related to SNVs and replacement. More details of genetic variants frequencies are provided in Figure 2.
To investigate the effect of Tamoxifen on genetic variants distribution within control and treated samples, a statistical analysis was separately carried out for each genetic variant on the basis of chi-square test for total genetic variants in the control and treatment samples. Results showed that genetic variants distribution within control and treated samples was significant (P≤0.05). Also, it was found that all of the genetic variants distributions in control and treatment samples were significant (Table 3), which indicated the possible effects of Tamoxifen on the genetic variants frequency.
Table3. Results of statistical analysis of genetic variants distribution in control and treatment samples
Genomic variants
|
P-value
|
SNV***
|
0.00006
|
MNV***
|
0.0001
|
Insertion***
|
0.0003
|
Deletion***
|
0.0012
|
Replacement***
|
0.001
|
Results of the comparison between genetic variants of control and treatment samples indicated that there were 117 differential genetic variants. Among all of the differential variants, 13 genetic variants were located in the coding regions and 12 variants led to the amino acid sequence transformation within the protein structure. Table 4 shows more details of differential genetic variants.
Table 4. The classification of differential genetic variants within control and treatment samples
Genetic variants
|
Differential variants
|
Coding region
|
Non-coding regions
|
Amino acid changes
|
SNV
|
93
|
12
|
81
|
11
|
MNV
|
9
|
1
|
8
|
1
|
Insertion
|
2
|
0
|
2
|
0
|
Deletion
|
13
|
0
|
13
|
0
|
Replacement
|
0
|
0
|
0
|
0
|
Total
|
117
|
13
|
104
|
12
|
The process of gene ontology enrichment analysis of differential genetic variants was carried out at three levels of biological process, cellular component, and molecular function; therefore, a total number of 77 significant GO terms were reported (Table 5). At the biological process level, the most repetitive of reported overlapping gene names were GEN1, HSPA5, NSMCE2, AURKA, and DDX11 candidate genes. GEN1 (Flap endonuclease GEN homolog 1) encoded a member of Rad2/xeroderma pigmentosum group G nuclease family. As it was observed for BRCA1 and BRCA2, findings showed that GEN1 contributed to resolve the Holliday junction in the homologous recombination. It is noteworthy that Holliday junction can play a vital role in the cancer chemo-sensitivity (Wu et al., 2016). Somatic truncating GEN1 mutations have been reported in breast cancers; therefore, 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 appreciable contribution to breast cancer susceptibility through acting as a high- or intermediate-penetrance breast cancer predisposition gene such as BRCA1, BRCA2, CHEK2, ATM, BRIP1, and PALB2 (Turnbull et al., 2010). Sun et al. (2014) suggested that GEN1 would play a vital role in DNA damage response; therefore, its alteration could lead to the breast cancer. HSPA5 (Heat-shock protein 5) is considered as a marker of poor prognosis in breast cancer patients, and plays a critical role in promoting the drug resistance and metastasis (Chang et al., 2014). A close association was observed between the cancer behaviors of heat shock proteins family; however, all members of HSP family have not been studied completely (Zoppino et al., 2018). NSMCE2 is an E3 SUMO ligase and a subunit of SMC5/6 complex that could be associated with DNA repair (Pond et al., 2019). Although SMC5/6 complex functions were not described precisely, it was reported that it could act as a tumor suppressor in mice (Jacome et al., 2015). AURKA (Aurora Kinase A) is a serine/threonine kinase that contributes to the regulation of cell cycle progression; therefore, it could be a potential cancer susceptibility gene (Cox et al., 2006). Furthermore, it is considered as a promising target in the treatment processes of patients with cancer (Staff et al., 2010). DDX11 is a DNA helicase that plays a role in DNA replication, sister chromatid cohesion establishment, and general chromosome structure. The effects 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 example, 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 be increased significantly (Mahtab.et al., 2021)
Results achieved from molecular function analysis indicated that the most frequent enriched candidate genes in significant GO term were IL6ST, COX15, and FNTA.
Interleukin-6 (IL-6) is a cytokine released by various cells such as cancerous cells, and plays a vital role in the expansion and differentiation of tumor cells (Masjedi et al., 2018). It was also shown that IL6ST may respectively act as a main factor and a tumor suppressor gene in triple-negative breast (TBC) progression, and diagnosis and treatment procedures (Jia et al., 2021). Additionally, IL6ST was reported as a specific candidate gene for TBC. Therefore, the expression of IL6ST and other three genes (ANKRD30A, ANP32E, and DSC2) classified TBC from non-TBC (Mathe.et l., 2015). COX15 encodes cytochrome C Oxidase subunit 15 and contributes to mitochondrial respiratory chain (UniProtKB: Q7KZN9). Gao.et al. (2017) reported that the high-level expression of COX5B candidate gene was associated with a poor prognosis in breast cancer. 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 explain the clinical implications of COX5B in breast cancer. FNTA is located on chromosome 8 and encodes the subunit alpha of protein farnesyltransferase (FTase) enzyme (UniProtKB: P49354). It was found that FNTA could be a key gene for tumor progression; moreover, its abnormal copy numbers were associated with pathological transformations of breast cancer. Therefore, it could be considered as a main target of developing drugs (Tian et al., 2020). The cellular component analysis showed that nucleus and nucleoplasm were the most important cellular parts that may contribute to the hormone therapy.
Table5. Results of gene ontology enrichment analysis of differential genetic variants between control and treated samples
GO type
|
GO term
|
Description
|
Overlapping gene name
|
Biological process
|
0000722
|
Telomere maintenance via recombination
|
NSMCE2, SMC6
|
0007052
|
Mitotic spindle organization
|
AURKA, RAN, TTK
|
0007051
|
Spindle organization
|
AURKA, TTK
|
0007041
|
Lysosomal transport
|
IGF2R, VPS54
|
0090398
|
Cellular senescence
|
NSMCE2, SMC6
|
0000724
|
Double-strand break repair via homologous recombination
|
GEN1, NSMCE2, YY1
|
0034612
|
Response to tumor necrosis factor
|
ADAM10, GGT1
|
0001315
|
Age-dependent response to reactive oxygen species
|
SOD2
|
0003069
|
Vasodilation by acetylcholine involved in regulation of systemic arterial blood pressure
|
SOD2
|
0033316
|
Meiotic spindle assembly checkpoint
|
TTK
|
0036316
|
SREBP-SCAP complex retention in endoplasmic reticulum
|
INSIG1
|
0051089
|
Constitutive protein ectodomain proteolysis
|
ADAM10
|
0060904
|
Regulation of protein folding in endoplasmic reticulum
|
HSPA5
|
0061015
|
snRNA import into nucleus
|
RAN
|
0070862
|
Negative regulation of protein exit from endoplasmic reticulum
|
INSIG1
|
0071139
|
Resolution of recombination intermediates
|
GEN1
|
0090044
|
Positive regulation of tubulin deacetylation
|
FNTA
|
1901303
|
Negative regulation of cargo loading into COPII-coated vesicle
|
INSIG1
|
1901668
|
Regulation of superoxide dismutase activity
|
SZT2
|
1903891
|
Regulation of ATF6-mediated unfolded protein response
|
HSPA5
|
1903897
|
Regulation of PERK-mediated unfolded protein response
|
HSPA5
|
1904426
|
positive regulation of GTP binding
|
CLN5
|
0060271
|
cilium assembly
|
IFT80, INTU, SEPT7, WDR19
|
0031297
|
Replication fork processing
|
DDX11, GEN1
|
0018279
|
Protein N-linked glycosylation via asparagine
|
MAGT1, MCFD2
|
0000303
|
Response to superoxide
|
SOD2
|
0000768
|
Syncytium formation by plasma membrane fusion
|
ERVW-1
|
0006784
|
Heme a biosynthetic process
|
COX15
|
0006949
|
Syncytium formation
|
ERVW-1
|
0031179
|
Peptide modification
|
GGT1
|
0034085
|
Establishment of sister chromatid cohesion
|
DDX11
|
0035281
|
Pre-miRNA export from nucleus
|
RAN
|
0035437
|
Maintenance of protein localization in endoplasmic reticulum
|
HSPA5
|
0070085
|
Glycosylation
|
CLN5
|
0071140
|
Resolution of mitotic recombination intermediates
|
GEN1
|
0072369
|
Regulation of lipid transport by positive regulation of transcription from RNA polymerase II promoter
|
HNRNPK
|
0090045
|
Positive regulation of deacetylase activity
|
FNTA
|
0097421
|
Liver regeneration
|
AURKA
|
Table5. Continued
GO type
|
GO term
|
Description
|
Overlapping gene name
|
Biological process
|
0035437
|
Maintenance of protein localization in endoplasmic reticulum
|
HSPA5
|
0070085
|
Glycosylation
|
CLN5
|
0071140
|
Resolution of mitotic recombination intermediates
|
GEN1
|
0072369
|
Regulation of lipid transport by positive regulation of transcription from RNA polymerase II promoter
|
HNRNPK
|
0090045
|
Positive regulation of deacetylase activity
|
FNTA
|
0097421
|
Liver regeneration
|
AURKA
|
1901980
|
Positive regulation of inward rectifier potassium channel activity
|
ALG10B
|
1990700
|
Nucleolar chromatin organization
|
DDX11
|
2001076
|
Positive regulation of metanephric ureteric bud development
|
BASP1
|
0006631
|
Fatty acid metabolic process
|
GGT1, MSMO1
|
Molecular function
|
0016740
|
transferase activity
|
ALG10B, UHMK1
|
0004712
|
protein serine/threonine/tyrosine kinase activity
|
AURKA, TTK
|
0000400
|
four-way junction DNA binding
|
GEN1, YY1
|
0005537
|
mannose binding
|
CLN5, IGF2R
|
0004569
|
glycoprotein endo-alpha-1,2-mannosidase activity
|
MANEA
|
0016627
|
oxidoreductase activity, acting on the CH-CH group of donors
|
COX15
|
0033781
|
cholesterol 24-hydroxylase activity
|
CYP46A1
|
1902945
|
metalloendopeptidase activity involved in amyloid precursor protein catabolic process
|
ADAM10
|
0003865
|
3-oxo-5-alpha-steroid 4-dehydrogenase activity
|
SRD5A1
|
0004661
|
protein geranylgeranyltransferase activity
|
FNTA
|
0004662
|
CAAX-protein geranylgeranyltransferase activity
|
FNTA
|
0004915
|
interleukin-6 receptor activity
|
IL6ST
|
0004923
|
leukemia inhibitory factor receptor activity
|
IL6ST
|
0016653
|
oxidoreductase activity, acting on NAD(P)H, heme protein as acceptor
|
COX15
|
0019981
|
interleukin-6 binding
|
IL6ST
|
0045509
|
interleukin-27 receptor activity
|
IL6ST
|
Table5. Continued
GO type
|
GO term
|
Description
|
Overlapping gene name
|
Cellular component
|
0000803
|
Sex chromosome
|
SMC6
|
0005634
|
Nucleus
|
ADAM10, ANP32A, AURKA, BASP1, COA7, COX15, CUTC, DDX11, DECR1, FBXL3, FGF13, GJB4, GTF2H3, HNRNPK, HSPA5, NSMCE2, PSMD8, RAN, RPAP2, SEPT7, SMC6, SNRPD3, TMPO, TTK, UHMK1, XAF1, YY1, ZNF37A, ZNF471, ZNF480, ZNF550
|
0005654
|
Nucleoplasm
|
ANP32A, ARPP19, AURKA, CUTC, DDX11, DECR1, GEN1, GTF2H3, HNRNPK, NSMCE2, PSMD8, RAN, RPAP2, RXYLT1, SMC6, SNRPD3, UBXN8, UHMK1, VPS54, WDR19, YY1, ZNF480
|
0005783
|
Endoplasmic reticulum
|
ALG10B, ANP32A, CLN5, CYP46A1, HSPA5, INSIG1, LCLAT1, MAGT1, MSMO1, RCN1, TECRL, UBXN8
|
0005789
|
Endoplasmic reticulum membrane
|
CYP46A1, HSPA5, INSIG1, LCLAT1, MCFD2, MSMO1, PIGC, SRD5A1
|
0005900
|
Oncostatin-M receptor complex
|
IL6ST
|
0005953
|
CAAX-protein geranylgeranyltransferase complex
|
FNTA
|
0008180
|
COP9 signalosome
|
BASP1, HSPA5
|
0030496
|
midbody
|
AURKA, DDX11, HSPA5, RAN
|
0030915
|
Smc5-Smc6 complex
|
NSMCE2, SMC6
|
0042565
|
RNA nuclear export complex
|
RAN
|
0070069
|
Cytochrome complex
|
COX15
|
0071598
|
Neuronal ribonucleoprotein granule
|
UHMK1
|
3.2 RNA-seq analysis
PCA results derived from the findings of performing RNA-seq analysis for all samples indicated that control and treated samples were clustered separately (Fig. 3). Therefore, it could be said that Tamoxifen therapy may impact on gene expression profiles at the transcriptome level among treated and control samples.
The visualization of RNA-seq analysis results derived from control and treated samples were shown in a heat map (Fig 4). It was also shown that mitochondrial respiratory genes were expressed at lower levels within treated samples compared to control ones. In current study, it was reported that MT-CO1, MT-CO3, MT-ND2, MT-ND4, MT-ND5, MT-ND6, and MT-ATP6 were the mitochondrion respiratory genes. MT-ND genes provide NADH dehydrogenase. This protein is a part of a large enzyme complex encoded by the mitochondrial genome. Moreover, the dysfunction of MT-ND proteins would lead to the electron transport chain disruption and ATP production. MT-CO genes encode Cytochrome C Oxidase subunits within mitochondria. It is found that they were the last enzyme in the mitochondrial electron transport chain for ATP synthesis (Kharrati-Koopaee et al., 2019). Findings derived from heat map analysis suggested that several candidate genes including ALDOA, RPL13, HSPB1, GATA3, KRT18, IGFBP4, and SULF2 were associated with the lowest gene expression level in treated samples. Aldolase (ALDOA) is known as an oncogene, which is a glycolytic enzyme that promotes the metastatic progression of cancers (Chang et al., 2019; Ji et al., 2016). It was shown that there was an association between ALDOA knock down and proliferation reduction of breast cancer cells (Zhang et al., 2017). RPL13 encodes a ribosomal protein, which is a component of 60S subunit. Ribosomal proteins (RP) expression patterns were implemented as a diagnostic strategy in human cancers. Reports of several cancers indicated the dysregulation of RP expression (e.g.RPL13) (Dolezal et al., 2018); therefore, it could be said that RPL13 would be expressed at significantly higher levels in benign breast lesions compared to that of breast carcinomas (GeneCards: GC16P089674). HSPB1 is a member of heat shock proteins, which are considered as a large family of proteins with breast cancer behavior (Zoppino et al., 2018). It was reported that the down-regulation of HSPB1 protein may induce the expression of phosphatase and tensin homologue (PTEN) as a tumor suppressor gene. In other words, PTEN stabilization depends upon HSPB1 low-level expression (Cayado-Gutiérrez et al., 2013).
GATA binding protein 3 (GATA3) is a highly conserved transcription factor that belongs to GATA family and leads to the expression of a large number of important genes (Voduc.et al., 2008). Furthermore, it contributes to the human growth and differentiation cells including the mammary tissue. Lower levels of GATA3 expression in breast tumors are associated with larger tumors. Therefore, GATA3 is considered as an important gene in breast cancer development; however, its exact role as an oncogene or tumor suppressor is unclear (Afzaljavan.et al., 2021; Takaku.et al., 2015). Keratin 18 (KRT18) is a member of the intermediate filament family of cytoskeletal protein that is involved in the tissue integrity, and its over-expression has been reported in many cancers (Zhang et al., 2019). It was also reported that KT18 was over-expressed in breast cancer and played a vital role in the breast tumorigenesis and tumor dedifferentiation (HA et al., 2011). Insulin-like growth factor binding proteins (IGFBPs) would regulate many cellular processes such as cell proliferation. IGFBPs act as binding proteins for insulin-like growth factor (IGF); furthermore, it is evidenced that they play a critical role in the cancer progression, especially in breast cancer (Hermani.et al., 2013). However, there are various reports regarding their activities as oncogenes or tumor suppressors. IGFBP5 may be considered as an oncogene due to its contribution to metastasis, proliferation, and limited responses to endocrine treatment; also, it acts as a tumor suppressor because of its apoptotic role, anti-metastatic function, and anti-migratory effects (Akkiprik et al., 2015)
Sulfatase family, which includes sulfatase1 (SULF1) and sulfatase 2 (SULF2), plays an important role in the multiple biological pathways through regulating the sulfation status (Jiang.et.al, 2020). It was confirmed that SULF2 would promote the breast cancer progression and regulate the tumor-related genes expression in breast cancer (Zhu.et.al, 2016).
Results of the whole transcriptome analysis showed that there were 21515 DGEs among control and treated samples, while findings of Volcano plot indicated that most of DGEs were classified as the down-regulated genes. At significant levels (P<0.01, -Log10 (P-value)>2), there were 910 and 3 candidate genes reported as the significant down- and up-regulated ones (Fig.5).
Results of Volcano plot showed that three candidate genes including GREB1, EGR3, and XAF1 were clustered as the up-regulated genes. It was also found that the estrogen-based growth regulation in breast cancer 1 (GREB1) was an early estrogen-responsive gene, and there was a close association between GREB1 expression and estrogen levels in breast cancer patients. In fact, GREB1 was an ESR1 (estrogen receptor 1) that could mediate the estrogen action. It was reported that the optimal level of GREB1 expression was required for breast cancer cells proliferation (Cheng.et al, 2018). However, GREB1 knockdown could prevent the breast cancer cell lines proliferation; therefore, it was found that targeting GREB1 could provide a possible treatment strategy through inhibiting the tumor-promoting pathways (Hodgkinson.et al., 2018). Early growth response (EGR) is a family of transcription factors that contributes to various biological pathways (Pio.et al., 2013). It was reported that EGR3 could be induced by estrogen in breast cancer MCF-7 cells and consequently, become involved in the estrogen-signaling pathway (Inoue.et al., 2004). Moreover, EGR3 levels were significantly higher within tissue samples derived from patients with recurrent breast cancer compared to those with primary tumors (Knudsen.et al., 2020). XIAP-associated factor 1 (XAF1) is a tumor suppressor observed in the multiple human neoplasms (Shin et al., 2017). It was shown that XAF1 loss expression would be resulted from tumor staging and its dysfunction was associated with tumor progression. Moreover, its appropriate expression could play a critical role in the apoptosis inductions and tumor growth inhibition in the gastric cancer (Tu.et al., 2009). Pinto.et al. (2020) reported that XAF1 may be considered as a TP53 function modifier through increasing the transcriptional activity of hypomorphic TP53 variants. TP53 is one of the most significant tumor suppressor genes, which is commonly mutated in various cancers such as breast cancer (Børresen-Dale, 2003).
It is noteworthy that PROM1, FBN2, and KLHL14 were highly down-regulated (Fig.5). Prominin 1 (PROM1orCD133) is known as a biomarker of cancer stem cells; however, its biological role is not illustrated perfectly (Saha et al., 2020). Findings showed that there was an association between PROM1 levels and malignancy properties stages including initiation, progression, and metastasis. Moreover, it was reported that PROM1 would contribute to the cell motility and invasion, and may affect the malignancy of breast tumors. Also, PROM1 genes were highly expressed in TNBC cell lines (Brugnoli et al., 2019; Guo et al., 2017). Fibrillin-2 (FBN2) is an extracellular calcium-binding microfibril that contributes to several biological pathways including the bone mineralization, osteoblast maturation, and calcium binding (UniProtKB: P35556). FBN2 is considered as a biomarker of cancers early diagnosis. For example, Promotor hypermethylation of FBN2 is associated with colorectal cancer as an early event. In fact, Methylation may lead to FBN2 down-regulation in primary tumors (Yi.et al., 2012), while Kelch-like protein 14 (KLHL14) belongs to Kelch family genes and interacts with torsin-1A (UniProtKB: Q9P2G3). It was shown that KLHL14 was significantly overexpressed in breast cancer compared to normal breast tissues, and had a positive relationship with tumor aggressiveness (Fritzsche.et al, 2006). Moreover, findings indicated the vital role of KLHL14 in the development of various cancers including ovarian cancer (Chen.et.al, 2020).
Results derived from GO enrichment analysis of DGEs showed that most of DGEs were enriched in the regulations of apoptosis and cell death pathways (Table 6). Cell cycle damage is considered as the main cause of cancer incidence; therefore, the balance between proliferation and cell death is disrupted in cancers (Robert and David, 2005). It was shown that apoptosis inactivation would play a vital role in the process of cancer development (Brown and Attardi, 2005). Therefore, it could be said that significant GO term of apoptosis pathways could contribute to cancerous cell death under Tamoxifen therapy. Proteolysis is a hydrolysis reaction that occurs when peptide bonds and proteins are broken down into smaller polypeptides or amino acids. There is an association between the metastasis of malignancy tumor and overexpression of proteolytic enzyme. More importantly, proteolysis inactivation in cancerous tissue plays a critical role in the inhibition of tumor invasion, angiogenesis, and migration (Wyganowska‑Świątkowska et al., 2019). Interestingly, our findings suggested that negative proteolysis regulation and consequent regulations of proteolytic pathways could be regarded as considerable GO terms that control the cancer under Tamoxifen treatment (Table 6).
Table6. Results of GO enrichment analysis of DGEs
GO type
|
GO term
|
Reference genes in category
|
Description
|
DGEs count
|
Gene names
|
Biological process
|
0051248
|
20
|
Negative regulation of protein metabolic process
|
8
|
CTSZ, GPX1, GSTP1, IGFBP3, ITM2C, MAGEA2, MAGEA3, MECOM
|
0010941
|
30
|
Regulation of cell death
|
10
|
CTSZ, GPX1, GSTP1, IGFBP3, MAGEA3, MALT1, MECOM, MSX1, PAX8, TRIM2
|
0030162
|
6
|
Regulation of proteolysis
|
4
|
CTSZ, GPX1, MAGEA3, MALT1
|
0032269
|
17
|
Negative regulation of cellular protein metabolic process
|
7
|
CTSZ, GPX1, GSTP1, IGFBP3, MAGEA2, MAGEA3, MECOM
|
0043281
|
4
|
Regulation of cysteine-type endopeptidase activity involved in apoptotic process
|
7
|
GPX1, MAGEA3, MALT1
|
0045861
|
4
|
Negative regulation of proteolysis
|
3
|
CTSZ, GPX1, MAGEA3
|
0052548
|
4
|
Regulation of endopeptidase activity
|
3
|
GPX1, MAGEA3, MALT1
|
2000116
|
4
|
Regulation of cysteine-type endopeptidase activity
|
3
|
GPX1, MAGEA3, MALT1
|
0043067
|
29
|
Regulation of programmed cell death
|
9
|
GPX1, GSTP1, IGFBP3, MAGEA3, MALT1, MECOM, MSX1, PAX8, TRIM2
|
Molecular function
|
0019904
|
12
|
Protein domain specific binding
|
5
|
CCN1, CXADR, GPX1, SCNN1A, TCEAL9
|
0004602
|
2
|
Glutathione peroxidase activity
|
2
|
GPX1, GSTP1
|
Cellular component
|
0070062
|
49
|
Extracellular exosome
|
14
|
ACSL4, AKR1B1, CRISPLD1, CTSZ, FSTL1, GREB1, GSTP1, IGFBP7, ITM2C, LDHB, MSN, PSAT1, RAB34, SCNN1A
|
0043230
|
50
|
Extracellular organelle
|
14
|
ACSL4, AKR1B1, CRISPLD1, CTSZ, FSTL1, GREB1, GSTP1, IGFBP7, ITM2C, LDHB, MSN, PSAT1, RAB34, SCNN1A
|
1903561
|
50
|
Extracellular vesicle
|
14
|
ACSL4, AKR1B1, CRISPLD1, CTSZ, FSTL1, GREB1, GSTP1, IGFBP7, ITM2C, LDHB, MSN, PSAT1, RAB34, SCNN1A
|
0044432
|
28
|
Endoplasmic reticulum part
|
9
|
ACSL4, COL9A2, CTSZ, FADS2, FSTL1, GJA1, IGFBP3, IGFBP7, RCN1
|