• Users Online: 145
  • Print this page
  • Email this page


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 8  |  Issue : 1  |  Page : 44-51

In silico BRCA1 pathway analysis in breast invasive carcinoma


1 Department of Bioinformatics, Hazara University, Mansehra, Pakistan
2 School of Biological Sciences, Quaid-e-Azam Campus, University of the Punjab, Lahore, Pakistan

Date of Submission23-Oct-2020
Date of Acceptance15-Dec-2020
Date of Web Publication16-Mar-2021

Correspondence Address:
Dr. Asima Tayyeb
School of Biological Sciences, Quaid-e-Azam Campus, University of the Punjab, Lahore
Pakistan
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mgmj.mgmj_88_20

Rights and Permissions
  Abstract 

Recent developments in clinical patient-based personalized genomics explored a variety of biomarkers for diagnosis, prognosis, and therapy in breast invasive carcinoma (BRIC). BRCA1 mutations mediated a catastrophic situation for a damage-repairing apparatus that induced malignant transformation of breast tissue. To identify an association between BRCA1 regulatory behavior and the pathway-level proteome for determining drug discovery channels, here we developed a computational scheme for BRCA1 pathway dataset retrieval from PathCards: PATHWAY UNIFICATION DATABASE (1,073 superpaths of 3,215 human pathways from 12 sources), BRCA1 pathway regulation analysis from cBioPortal for Cancer Genomics (more than 40 datasets of above 13,000 cancer samples), and BRC1 network construction from STRING v11.0 database (24,584,628 proteins of 5,090 organisms). Our study reveals about 700 alterations of 64 pathway components in 482 BRIC samples, in which there were 422 loss-of-function (LOF) mutations and 278 amplifications. We found 19 members (BRCA1, BRCA2, FANCA, ATM, NBN, SMARCD2, HDAC9, PLK1, SMARCA4, POU2F1, TP53, HDAC2, HLTF, BLM, E2F4, UBC, E2F5, MRE11, and RB1) based on a minimum 2% participation that showed 541 alterations in which there were 193 amplifications and 348 LOF mutations. From 19 components, BRCA1, BRCA2, FANCA, ATM, and TP53 have high-level LOF mutations whereas E2F5, NBN, SMARCD2, and POU2F1 have prominent amplifications. We developed three modules in which the BRCA1 module has 12 members that are involved in damage sensing and repairing processes as hot spots showing overexpression and LOF mutations. This in silico approach uniquely addressed BRCA1 mutations’ influence on BRIC at the pathway proteome level, with module identification as a hub for drug designing. We proposed these proteins as biomarkers for first-class diagnosis and clinical investigations. In the future, BRCA1 pathway-related therapeutic markers are used for further experimental investigations regarding drug development in breast cancer biology.

Keywords: BRIC, cell cycle checkpoints, cell death, DNA damage repairing, proliferation


How to cite this article:
Shah ZA, Nouroz F, Tayyeb A. In silico BRCA1 pathway analysis in breast invasive carcinoma. MGM J Med Sci 2021;8:44-51

How to cite this URL:
Shah ZA, Nouroz F, Tayyeb A. In silico BRCA1 pathway analysis in breast invasive carcinoma. MGM J Med Sci [serial online] 2021 [cited 2021 Apr 14];8:44-51. Available from: http://www.mgmjms.com/text.asp?2021/8/1/44/311391




  Introduction Top


BRCA1 as a tumor suppressor protein is involved in genetic stability, chromosome remodeling, cell cycle control, and transcriptional regulation of DNA damage repair genes.[1] BRCA1 mutations in breast cancer lead to reduced expression, nonfunctional protein synthesis, and abnormal localization in subcellular regions.[2] BRCA1 mutations are observed in breast and ovarian carcinoma as a hereditary cancer biomarker.[3] BRCA1-deficient women have a more than 80% risk of breast cancer development.[4] In breast carcinoma, the overexpression of miRNA-182 and promoter hypermethylation caused BRCA1 downregulation.[5] BRCA1 subcellular localization alteration is a significant factor in aberrant signaling pathways that manages the repairing of genomic damage sites.[6] BRCA1 has important protein interactions via Really Interesting New Gene (RING), N-terminal domain, exon 11–13 encoded region and BRCT (BRCA1 C-terminal) repeats domain. The RING domain has two significant interactions with BARD1 and E2 ligase enzymes, which are responsible for ubiquitination. BRCA1 RING domain mutations, including I26A and C61G, caused inhibition toward protein interactions, which leads to genome instability and cancer promotion.[7],[8],[9] BRCA1 exon 11–13 mutations disturbed the coiled-coil domain-PALB2 interaction that bridges multiple tumor suppressor proteins, that is, BRCA2 with BRCA1 as a supercomplex for the homologous recombination process of damage repairing.[10],[11],[12] The BRCA1 BRCT domain mutations prevent the formation of essential tumor suppressor complexes, including ABRAXAS, BRIP1, CTIP, and other double-strand breaks (DSBs) phosphoproteins.[13],[14] Multiomics approaches revolutionized BRCA1 understanding in large-scale patient-level cancer genome datasets, which reveals more than 1700 mutations with clinical significance but still there is a wide vacuum for targeted precise therapeutic strategy in BRCA1-deficient tumors. There is an inevitable need to analyze BRCA1 regulation at the pathway level to identify co-oncotargets for combinatorial therapy.


  Protocol Top


BRCA1 pathway dataset retrieval

We retrieved the BRCA1 pathway dataset from PathCards: PATHWAY UNIFICATION DATABASE (www.pathcards.genecards,org) from GeneCardsSuite platform. The database contains 1,073 superpaths of 3,215 human pathways from 12 sources. The PathCards database is an ideal resource for system analysis regarding BRCA1-mediated breast cancer biology. We selected “PathCards” from the main bar of GeneCardsSuite and queried “BRCA1” in the search box that displayed a comprehensive pathway dataset of BRCA1.

BRCA1 pathway regulation analysis in BRIC

We performed BRCA1 pathway regulatory analysis in BRIC from a user-friendly web-based cBioPortal for Cancer Genomics (www.cbioportal.org) server that contains more than 40 datasets of more than 13,000 cancer samples. This genomic toolkit is developed by Memorial Sloan Kettering Cancer Centre’s Computational Biology Centre (cBio) from raw large-scale cancer genomics datasets with a powerful set of analytical and visualization tools. We selected the “TCGA” dataset source from the main search box that displayed a list of cancer datasets; we also selected the “BRIC TCGA Nature 2012” dataset. We queried the whole BRCA1 pathway dataset in the gene box and pressed the “submit” option, which ultimately provides an OncoPrint coloring presentation of genomic-level regulation.

BRCA1 network and module construction

We used the STRING v11.0 database (www.string-db.org) for network construction of BRCA1 pathway breast cancer-related proteins. STRING v11.0 database contains 24,584,628 proteins of 5,090 organisms and known/ predicted protein interactions with physical or functional relationships. We entered BRCA1 pathway breast cancer-related proteins in multiple protein search boxes with a selection of Homo sapiens as a species and pressed the “search” option, which displayed a list of input proteins for mapping. We pressed the “continue” function for further operations that gave us a network view of the BRCA1 pathway. We selected the “clusters” tab for the generation of functional associated modules and the “analysis” tab for enrichment analysis.


  Results Top


BRCA1 pathway dataset retrieval

We retrieved a comprehensive BRCA1 pathway dataset that consisted of 64 members that shared diverse functions, including cell cycle progression, cell cycle arrest, DNA damage repairing, differentiation, migration, cytoskeleton stability, and sensitivity response toward foreign viral invaders. In the BRCA1 pathway, the majority of members (SMARCC2, SMARCA1, SMARCD1, SMARCA5, SMARCAD1, SMARCA2, SMARCD2, SMARCA4, SMARCB1, and SMARCC1) belonged to the SWI/SNF-Related Matrix-Associated Actin-Dependent Regulator of Chromatin Subfamilies, which are highly involved in growth inhibition-mediated apoptosis. The Fanconi Anemia Complementation Groups contains FANCA, FANCE, FANCC, FANCG, FANCD2, FANCF, and FANCL, which are involved in post-replication repairing. The Histone Deacetylase family (HDAC6, HDAC7, HDAC1, HDAC8, HDAC9, HDAC10, HDAC11, HDAC2, HDAC3, and HDAC5) is involved in the differentiation and prevention of cellular proliferation. The Growth Arrest and DNA Damage Inducible Alpha Family members (GADD45B, GADD45G, and GADD45A) have a significant role in p38/JNK pathway activation. The E2F Transcription Factor Family members (E2F1, E2F2, E2F3, E2F4, and E2F5) participate in tumor suppressor protein regulation. There are also important members of the RAD and MSH family that are important players of mismatch repairing pathways and damage-sensing/repairing cascades. There are a few members of the ubiquitin family (UBB, UBC, and UBD) that are essential for enzymatic reactions of ligase activity [Table 1].
Table 1: BRCA1 pathway dataset

Click here to view


BRCA1 pathway regulation analysis in BRIC

We analyzed the BRCA1 pathway dataset in the BRIC TCGA Nature 2012 dataset that contains 482 samples. Due to the huge number of components and precise visual understanding, we entered 16 members for regulation analysis in which BRCA2, FANCA, MSH6, and SMARCC2 showed significant alterations in maximum samples whereas 12 components exerted little influence on breast cancer progression in this dataset. Here, 26 samples showed amplification and 63 samples showed mutations, that is, deep deletions, truncating mutations, and missense mutations. The majority of mutations occur in BRCA2, MSH6, and FANCA whereas interestingly GADD45A has the majority of amplification [Figure 1].
Figure 1: BRCA1 pathway 16 member’s regulation analysis showed 15% participation in 73 samples out of 482

Click here to view


In these 16 components pertaining to regulation analysis, ATM, NBN, SMARCD2, HDAC, PLK1, and SMARCA4 showed significant alterations in a higher number of samples; whereas the other 10 members showed less influence on breast cancer. In the dataset, 16 members of the BRCA1 pathway showed amplification in 126 samples and 68 samples showed mutations. The SMARCD2 and NBN have a maximum number of amplification samples whereas ATM has a higher number of mutation samples. Here, CHEK2, FANCD2, SMARCA2, ATR, E2F1, and STAT1 also gain attention due to both amplifications and mutations that are found in an inappropriate number of samples [Figure 2].
Figure 2: BRCA1 pathway 16 member’s regulation analysis showed 31% participation in 149 samples out of 482

Click here to view


In these 16 components, regulation analyses TP53, POU2F1, HDAC2, and HLTF showed significant alterations in a higher number of samples whereas the other 12 members had a lower influence on breast cancer. In the dataset, 16 members of the BRCA1 pathway showed amplification in 68 samples and 218 samples showed mutations. The TP53 has a higher number of mutations in the whole BRCA1 pathway dataset, and POU2F1 has a maximum number of amplification samples. Here, BACH1, HDAC11, SMARCA5, BARD1, E2F3, FANC4, and UBB also gain attention due to both amplifications and mutations in an appropriate number of samples [Figure 3].
Figure 3: BRCA1 pathway 16 member’s regulation analysis showed 45% participation in 216 samples out of 482

Click here to view


In these 16 components, regulation analyses of BLM, E2F4, UBC, BRCA1, E2F5, MRE11, and RB1 showed significant alterations in a higher number of samples whereas the other nine members showed less influence on breast cancer. In a dataset, 16 members of the BRCA1 pathway showed amplification in 67 samples and mutation in 71 samples. The BLM and E2F5 have a maximum number of amplification samples whereas E2F4, UBC, BRCA1, and RB1 have a higher number of mutation samples. Here, HDAC5 also gains attention due to both amplifications and mutations in a suitable number of samples [Figure 4].
Figure 4: BRCA1 pathway 16 member’s regulation analysis showed 25% participation in 119 samples out of 482

Click here to view


BRCA1 network and module construction

We selected 19 members that showed a minimum of 2% participation in BRIC from the overall BRCA1 pathway for network construction. Our main query was whether BRCA1 protein resides in the center and associated proteins occur at the periphery. BRCA1 has a majority of inward interactions that indicate its significance as a signal transducer in the damage-repairing system. In the BRCA1-mediated pathway ATM protein is a single entity that shows positive activation of BRCA1, BRCA2, TP53, and NBN whereas PLK1 and TP53 are involved in negative regulation [Figure 5].
Figure 5: BRCA1 pathway proteins related with breast invasive carcinoma. Here, round nodes show proteins and lines indicates edges or interactions. ATM has a positive active regulatory interaction with BRCA1, BRCA2, NBN, and TP53. The TP53 has two negative interactions with PLK1 and BRCA2. The majority of BRCA1 pathway components show unspecified interactions by round edges

Click here to view


We draw three modules (a cluster of functionally associated proteins is known as a module) from BRCA1 pathway breast cancer-related protein data. BRCA1 has the largest module consisting of 12 members, that is BRCA1, BRCA2, NBN, PLK1, TP53, MRE11A, BLM, FANCA, UBC, ATM, HLTF, and POU2F1, that are involved in DNA damage sensing, repairing, and apoptosis. The RB1 cluster has four members, that is, RB1, E2F4, E2F5, and HDAC2, that are involved in cell cycle regulation and differentiation. SMARCA4 cluster has three members, that is, SMARCA4, HDAC9, and SMARCD2, that are involved in apoptosis [Figure 6].
Figure 6: BRCA1 pathway has three protein modules that show functionally associated interactions inside clusters as intramodule interactions by straight lines, whereas interactions among different clusters are depicted as intermodules by dotted lines. The TP53 and SMARCA4 are trafficking agents between diverse modules as connectors

Click here to view



  Discussion Top


This is a large-scale comprehensive approach regarding BRCA1-mediated breast cancer biology due to the selection of 64 members containing the BRCA1 pathway dataset. This dataset has more than 700 alterations, that is, 278 copy number gain amplifications and 422 LOF mutations. We selected 19 members, including BRCA1, BRCA2, FANCA, ATM, NBN, SMARCD2, HDAC9, PLK1, SMARCA4, POU2F1, TP53, HDAC2, HLTF, BLM, E2F4, UBC, E2F5, MRE11, and RB1, based on each member having a minimum of 2% participation in the BRIC dataset as a hot spot zone. These 19 hot spot members showed 541 alterations, among which there were 193 amplifications and 348 LOF mutations in 489 BRIC samples. Here, BRCA1, BRCA2, FANCA, ATM, and TP53 have high-level LOF mutations whereas E2F5, NBN, SMARCD2, and POU2F1 have prominent amplifications in the hot spot zone.

In our study, both BRCA1 (5%) and BRCA2 (6%) showed LOF due to missense mutations, truncating mutations, and deep deletions. Both BRCA1 proteins are highly involved in error-free repairing of genomic damaged DNA in breast tissue. In the case of mutations, the repairing process is inhibited and tumor suppression activity is unable to arrest the cell cycle pathway that leads to breast cancer development.[15],[16] BRCA1 mutations are sensitive toward the orientation of the BRCA1-associated genome surveillance complex (BASC) that integrates genome damage sensors, signal transducers, and tumor suppressor proteins.[17] The FANCA (4%) showed LOF that is involved in the regulation of cell-cycle checkpoints by repairing of post-replication inter-strand cross-link errors that lead to chromosomal stability and differentiation of the stem cell population.[18] The FANCA gene mutations caused acute myeloid leukemia, squamous cell carcinoma, aplastic anemia, and Fanconi anemia.[19] The ATM (5%) showed LOF that is usually activated in DSBs, which leads to phosphorylation of the TP53 pathway by checkpoint 1 (CHK1) protein. The ATM-mediated TP53 pathway activities are involved in all cell cycle phases for regulation of genome stability and integrity. The ATM mutations caused cancer, cardiovascular diseases, and immunodeficiency syndrome diseases via deregulations in cell homeostasis, apoptosis, and cell arresting checkpoints.[20],[21] The NBN (9%) showed an amplification that has influential activity in telomere sustainment and meiotic recombination. Its polymorphism elevates the risk of urinary system cancer, lung cancer, and breast cancer development.[22] SMARCD2 (9%) and SMARCA4 (2.3%) showed amplifications that are SWI-SNF complex members of ATP-dependent helicases involved in cellular proliferation and self-renewal capability of a leukemic cell.[23]

HDAC9 (9%) and HDAC2 (2.3%) showed amplification that played a positive progressive role in the prostate, lungs, pancreas, gastric, breast, kidney, and soft tissue malignancies.[24] PLK1 (2.3%) showed amplification that was involved in the verity of worse prognosis malignancies by having significant participation in mitosis maintenance and completion. PLK1 inhibition as ideal targeted therapy at diverse phases of mitosis leads to cancer cell apoptosis.[25] POU2F1 (4%) showed amplification that was involved in the invasive mode of carcinoma by speeding cellular proliferation, migration, and colony formation.[26] E2F5 (6%) showed amplification that was involved in various human malignancies, including liver cancer, which by overexpression increases proliferation of cellular growth with E2F5 inhibition and reduces liver cells’ overgrowth that leads to cell death.[27] The SWI/SNF family member HLTF (2.3%) showed amplification that was involved in estrogen-induced neoplastic transformation in kidney cancer as an oncogene.[28] The RecQ helicase family member BLM (3%) showed both amplifications and mutations that were involved in fork stability, restoration of replication, and damage repairing in breast tissue.[29] The E2F transcription factors’ family member E2F4 (2.1%) showed LOF that was involved in the suppression of proliferating genes as a tumor suppressor protein.[30] UBC (2.1%) showed LOF that was involved in damage repairing, endocytosis, modification of kinases, and regulation of cell cycle processes.[31] MRE11 (2.1%) showed amplification that was involved in the STAT3 pathway-mediated promotion of cellular proliferation, migration, invasion, and inhibition of apoptosis by excessive repairing performance.[32] RB1 (3%) as a tumor suppressor showed LOF that was involved in the management of diverse cellular processes, including apoptosis, proliferation, and differentiation.[33] TP53 (39%) is a highly mutated gene in our findings that was involved in genome repairing, aging, apoptosis, and senescence. TP53 LOF mutations are a significant biomarker of cancer progression and an invasive mode of metastasis.[34]

We identified three functionally associated modules, that is, the BRCA1 module is the largest module and it consists of 12 members, including BRCA1, BRCA2, FANCA, ATM, NBN, PLK1, POU2F1, TP53, HLTF, BLM, UBC, and MRE11. The RB1 module has three members (RB1, HDAC2, and E2F4), and the HDAC9 module has three members (HDAC9, SMARCD2, and SMARCA4). The majority of BRCA1 module members showed amplification-mediated overexpression, that is, active participants of cellular proliferation and migration induced invasiveness. The BRCA1 module is an ideal therapeutic target for inhibition of neoplastic transformation and cancer progression. The RB1 module has an LOF that is involved in the suppression of cell growth and induction of apoptosis. The HDAC9 module has amplification-based overexpression that resulted in the progression of the self-renewal of neoplastic cells. In the BRCA1 pathway, 19 highly associated proteins are adjusted in a network form, which consists of protein–protein interactions. In a proteomic network, the majority of interactions are an unspecified way of action and ATM is the only protein that has a positive regulatory relationship with various genome-repairing proteins.


  Conclusion Top


Human breast carcinoma has frequent alterations in damage-repairing proteins, including BRCA1, BRCA2, and TP53, which are prominent tumor suppressor proteins. However, the BRCA1 regulatory behavior at the pathway level is enigmatic in breast cancer; so, we designed a rational strategy that displayed a holistic view of BRCA1 mutations with a comprehensive pathway of 64 members. Interestingly the majority of BRCA1 pathway BRIC-related members showed overexpression, and these are activators of proliferation with validation of LOF mutations about genome damage sensors and repairing apparatus. In the BRCA1 proteome network, BRCA1 module and HDAC9 module constitute an active hub for therapeutic strategies for inhibition of cellular proliferation. BRCA1 pathway mutational status creates novel opportunities for advancing clinical treatment in breast malignancy. In the future, our findings will provide multiple cotargets of pathway medicines for the effective prevention of BRIC.

Financial support and sponsorship

Nil.

Conflict of interest

There are no conflicts of interest.



 
  References Top

1.
Jiang Q, Greenberg RA Deciphering the BRCA1 tumor suppressor network. J Biol Chem 2015;290:17724-32.  Back to cited text no. 1
    
2.
Chen Y, Chen CF, Riley DJ, Allred DC, Chen PL, Von Hoff D, et al. Aberrant subcellular localization of BRCA1 in breast cancer. Science 1995;270:789-91.  Back to cited text no. 2
    
3.
Goodwin PJ, Phillips KA, West DW, Ennis M, Hopper JL, John EM, et al. Breast cancer prognosis in BRCA1 and BRCA2 mutation carriers: An international prospective breast cancer family registry population-based cohort study. J Clin Oncol 2012;30:19-26.  Back to cited text no. 3
    
4.
Fraser JA, Reeves JR, Stanton PD, Black DM, Going JJ, Cooke TG, et al. A role for BRCA1 in sporadic breast cancer. Br J Cancer 2003;88: 1263-70.  Back to cited text no. 4
    
5.
Downs B, Wang SM Epigenetic changes in BRCA1-mutated familial breast cancer. Cancer Genet 2015;208:237-40.  Back to cited text no. 5
    
6.
Henderson BR The BRCA1 breast cancer suppressor: Regulation of transport, dynamics, and function at multiple subcellular locations. Scientifica (Cairo) 2012;2012:796808.  Back to cited text no. 6
    
7.
Shakya R, Reid LJ, Reczek CR, Cole F, Egli D, Lin CS, et al. BRCA1 tumor suppression depends on BRCT phosphoprotein binding, but not its E3 ligase activity. Science 2011;334:525-8.  Back to cited text no. 7
    
8.
Drost R, Bouwman P, Rottenberg S, Boon U, Schut E, Klarenbeek S, et al. BRCA1 RING function is essential for tumor suppression but dispensable for therapy resistance. Cancer Cell 2011;20:797-809.  Back to cited text no. 8
    
9.
Wu LC, Wang ZW, Tsan JT, Spillman MA, Phung A, Xu XL, et al. Identification of a RING protein that can interact in vivo with the BRCA1 gene product. Nat Genet 1996;14:430-40.  Back to cited text no. 9
    
10.
Xu X, Weaver Z, Linke SP, Li C, Gotay J, Wang XW, et al. Centrosome amplification, and a defective G2-M cell cycle checkpoint induce genetic instability in BRCA1 exon 11 isoform-deficient cells. Mol Cell 1999;3:389-95.  Back to cited text no. 10
    
11.
Xu X, Wagner KU, Larson D, Weaver Z, Li C, Ried T, et al. Conditional mutation of brca1 in mammary epithelial cells results in blunted ductal morphogenesis and tumour formation. Nat Genet 1999;22:37-43.  Back to cited text no. 11
    
12.
Antoniou AC, Casadei S, Heikkinen T, Barrowdale D, Pylkäs K, Roberts J, et al. Breast-cancer risk in families with mutations in PALB2. N Engl J Med 2014;371:497-506.  Back to cited text no. 12
    
13.
Greenberg RA, Sobhian B, Pathania S, Cantor SB, Nakatani Y, Livingston DM Multifactorial contributions to an acute DNA damage response by BRCA1/BARD1-containing complexes. Genes Dev 2006;20:34-46.  Back to cited text no. 13
    
14.
Yu X, Chini CC, He M, Mer G, Chen J The BRCT domain is a phospho-protein binding domain. Science 2003;302:639-42.  Back to cited text no. 14
    
15.
Irminger-Finger I, Ratajska M, Pilyugin M New concepts on BARD1: Regulator of BRCA pathways and beyond. Int J Biochem Cell Biol 2016;72:1-17.  Back to cited text no. 15
    
16.
O’Donovan PJ, Livingston DM BRCA1 and BRCA2: Breast/ovarian cancer susceptibility gene products and participants in DNA double-strand break repair. Carcinogenesis 2010;31:961-7.  Back to cited text no. 16
    
17.
Friedenson B The BRCA1/2 pathway prevents hematologic cancers in addition to breast and ovarian cancers. BMC Cancer 2007;7:152.  Back to cited text no. 17
    
18.
Yuan F, Qian L, Zhao X, Liu JY, Song L, D’Urso G, et al. Fanconi anemia complementation group A (FANCA) protein has intrinsic affinity for nucleic acids with preference for single-stranded forms. J Biol Chem 2012;287:4800-7.  Back to cited text no. 18
    
19.
Thomashevski A, High AA, Drozd M, Shabanowitz J, Hunt DF, Grant PA, et al. The fanconi anemia core complex forms four complexes of different sizes in different subcellular compartments. J Biol Chem 2004;279:26201-9.  Back to cited text no. 19
    
20.
Espach Y, Lochner A, Strijdom H, Huisamen B ATM protein kinase signaling, type 2 diabetes and cardiovascular disease. Cardiovasc Drugs Ther 2015;29:51-8.  Back to cited text no. 20
    
21.
Fokas E, Prevo R, Hammond EM, Brunner TB, McKenna WG, Muschel RJ Targeting ATR in DNA damage response and cancer therapeutics. Cancer Treat Rev 2014;40:109-17.  Back to cited text no. 21
    
22.
Lu CS, Truong LN, Aslanian A, Shi LZ, Li Y, Hwang PY, et al. The RING finger protein RNF8 ubiquitinates nbs1 to promote DNA double-strand break repair by homologous recombination. J Biol Chem 2012;287:43984-94.  Back to cited text no. 22
    
23.
Cruickshank VA, Sroczynska P, Sankar A, Miyagi S, Rundsten CF, Johansen JV, et al. SWI/SNF subunits SMARCA4, SMARCD2 and DPF2 collaborate in MLL-rearranged leukaemia maintenance. PLoS One 2015;10:e0142806.  Back to cited text no. 23
    
24.
Hassell KN Histone deacetylases and their inhibitors in cancer epigenetics. Diseases 2019;7:57. doi: 10.3390/diseases7040057  Back to cited text no. 24
    
25.
Liu Z, Sun Q, Wang X PLK1, A potential target for cancer therapy. Transl Oncol 2017;10:22-32.  Back to cited text no. 25
    
26.
Zhu HY, Cao GY, Wang SP, Chen Y, Liu GD, Gao YJ, et al. POU2F1 promotes growth and metastasis of hepatocellular carcinoma through the FAT1 signaling pathway. Am J Cancer Res 2017;7:1665-79.  Back to cited text no. 26
    
27.
Jiang Y, Yim SH, Xu HD, Jung SH, Yang SY, Hu HJ, et al. A potential oncogenic role of the commonly observed E2F5 overexpression in hepatocellular carcinoma. World J Gastroenterol 2011;17:470-7.  Back to cited text no. 27
    
28.
Debauve G, Capouillez A, Belayew A, Saussez S The helicase-like transcription factor and its implication in cancer progression. Cell Mol Life Sci 2008;65:591-604.  Back to cited text no. 28
    
29.
Kluźniak W, Wokołorczyk D, Rusak B, Huzarski T, Kashyap A, Stempa K, et al. Inherited variants in BLM and the risk and clinical characteristics of breast cancer. Cancers (Basel)2019;11:1548.  Back to cited text no. 29
    
30.
Sun CC, Li SJ, Hu W, Zhang J, Zhou Q, Liu C, et al. Comprehensive analysis of the expression and prognosis for e2fs in human breast cancer. Mol Ther 2019;27:1153-65.  Back to cited text no. 30
    
31.
Marinovic AC, Zheng B, Mitch WE, Price SR Ubiquitin (ubc) expression in muscle cells is increased by glucocorticoids through a mechanism involving sp1 and MEK1. J Biol Chem 2002;277:16673-81.  Back to cited text no. 31
    
32.
Yuan SS, Hou MF, Hsieh YC, Huang CY, Lee YC, Chen YJ, et al. Role of MRE11 in cell proliferation, tumor invasion, and DNA repair in breast cancer. J Natl Cancer Inst 2012;104:1485-502.  Back to cited text no. 32
    
33.
Indovina P, Pentimalli F, Casini N, Vocca I, Giordano A RB1 dual role in proliferation and apoptosis: Cell fate control and implications for cancer therapy. Oncotarget 2015;6:17873-90.  Back to cited text no. 33
    
34.
Barbosa K, Li S, Adams PD, Deshpande AJ The role of TP53 in acute myeloid leukemia: Challenges and opportunities. Genes Chromosomes Cancer 2019;58:875-88.  Back to cited text no. 34
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Protocol
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed160    
    Printed20    
    Emailed0    
    PDF Downloaded15    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]