Integrating multiple omics data for the discovery of potential Beclin-1 interactions in breast cancer
Abstract
Breast cancer has been reported as one of the most frequently diagnosed malignant diseases and the leading cause of cancer death in women all around the world. Furthermore, this complicated cancer is divided into multiple subtypes which present different clinical symptoms and need correspondingly directed therapy. We took BECN1, a core gene in autophagy performing a tumor inhibitory effect, as a starting point. The study in this paper aims to identify genes related to breast cancer and its multiple subtypes by integrating multiple omics data using the least absolute shrinkage and selection operator (LASSO), which is a statistical method that can integrate more than two types of omics data. All the data is obtained from The Cancer Genome Atlas (TCGA) platform which stores clinical and molecular tumor data. The model constructed is based on three kinds of data including mRNA-gene expression with a dependent variable level, DNA methylation and copy number alterations as independent variables. Finally, we propose four subnets of four subtypes of breast cancer, and consider as a result of microarray analysis that AFF3 is associated with BECN1 in breast cancer, and may be a potential therapeutic target. This finding may provide some potential targeted therapeutics for the four different subtypes of breast cancer at the genetic level. In conclusion, finding out the major role Beclin-1 plays in breast cancer subtypes is of great value. The results obtained are instructive for further research and may provide excellent results in clinical applications, as well as testing in animal experiments, and may also indicate a new method to perform bioinformatics analysis.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Many multi-omics studies related to breast and ovarian cancer highlight research thrust by the scientific community in these domains.
“In particular, the presence of many multi-omics studies related to breast (Chen et al., 2017;Lee et al., 2017;List et al., 2014;Ma et al., 2016;Nam et al., 2009) and ovarian (Anděl et al., 2015;Mankoo et al., 2011;Paik et al., 2017;Zhang et al., 2014) cancer highlights the research thrust by the scientific community in these domains.”
From Using machine learning approaches for multi-omics data analysis: A review (2021) · cites this paper as Chen et al., 2017
Cites
Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method
Livak, K. J., & Schmittgen, T. D. (2001) · Methods · doi:10.1006/meth.2001.1262 · Cited by 180,860 · see citing works
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890 · see citing works
Regression Shrinkage and Selection via The Lasso: A Retrospective
Tibshirani, R. J. (2011) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2011.00771.x · Cited by 3,601 · see citing works
Promotion of tumorigenesis by heterozygous disruption of the beclin 1 autophagy gene
Qu, X., Yu, J., Bhagat, G., Furuya, N., Hibshoosh, H., Troxel, A., Rosen, J., Eskelinen, E.-L., Mizushima, N., Ohsumi, Y., et al. (2003) · Journal of Clinical Investigation · doi:10.1172/jci20039 · Cited by 2,311 · see citing works
Yue, Z., Jin, S., Yang, C., Levine, A. J., & Heintz, N. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2436255100 · Cited by 2,116 · see citing works
Autophagy promotes tumor cell survival and restricts necrosis, inflammation, and tumorigenesis
Degenhardt, K., Mathew, R., Beaudoin, B., Bray, K., Anderson, D., Chen, G., Mukherjee, C., Shi, Y., Gélinas, C., Fan, Y., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.06.001 · Cited by 2,013 · see citing works
Cloning and Genomic Organization of Beclin 1, a Candidate Tumor Suppressor Gene on Chromosome 17q21
Aita, V. M., Liang, X. H., Murty, V. V. V. S., Pincus, D. L., Yu, W., Cayanis, E., Kalachikov, S. M., Gilliam, T. C., & Levine, B. (1999) · Genomics · doi:10.1006/geno.1999.5851 · Cited by 800 · see citing works
Molecular Characterization of Basal-Like and Non-Basal-Like Triple-Negative Breast Cancer
Prat, A., Adamo, B., Cheang, M. C. U., Anders, C. K., Carey, L., & Perou, C. M. (2013) · The Oncologist · doi:10.1634/theoncologist.2012-0397 · Cited by 568 · see citing works
Autophagy negatively regulates Wnt signalling by promoting Dishevelled degradation
Gao, C., Cao, W., Bao, L., Zuo, W., Xie, G., Cai, T., Fu, W., Zhang, J., Wu, W., Zhang, X., et al. (2010) · Nature Cell Biology · doi:10.1038/ncb2082 · Cited by 385 · see citing works
Fratini, M., Bukreeva, I., Campi, G., Brun, F., Tromba, G., Modregger, P., Bucci, D., Battaglia, G., Spanò, R., Mastrogiacomo, M., et al. (2015) · Scientific Reports · doi:10.1038/srep10771 · Cited by 377 · see citing works
The use of principal component analysis and discriminant analysis in differential sensing routines
Stewart, S., Ivy, M. A., & Anslyn, E. V. (2013) · Chemical Society Reviews · doi:10.1039/c3cs60183h · Cited by 369 · see citing works
Margariti, A., Li, H., Chen, T., Martin, D., Vizcay‐Barrena, G., Alam, S., Karamariti, E., Xiao, Q., Zampetaki, A., Zhang, Z., et al. (2012) · Journal of Biological Chemistry · doi:10.1074/jbc.m112.412783 · Cited by 284 · see citing works
Kametaka, S., Okano, T., Ohsumi, M., & Ohsumi, Y. (1998) · Journal of Biological Chemistry · doi:10.1074/jbc.273.35.22284 · Cited by 275 · see citing works
Wu, F., Fang, T., Yu, L., Lv, G., Lv, H., Dong, L., Li, T., Wang, C., Tan, Y., Ding, J., et al. (2016) · Journal of Hepatology · doi:10.1016/j.jhep.2016.04.019 · Cited by 244 · see citing works
Beclin-1: Autophagic regulator and therapeutic target in cancer
Fu, L., Cheng, Y., & Liu, B. (2013) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2013.02.007 · Cited by 201 · see citing works
Web-TCGA: an online platform for integrated analysis of molecular cancer data sets
Deng, M. C.-H. K., Brägelmann, J., Schultze, J. L., & Perner, S. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-0917-9 · Cited by 191 · see citing works
Targeting Programmed Cell Death Using Small‐Molecule Compounds to Improve Potential Cancer Therapy
Ke, B., Tian, M., Li, J., Liu, B., & He, G. (2016) · Medicinal Research Reviews · doi:10.1002/med.21398 · Cited by 188 · see citing works
Zhao, Q., Shi, X., Xie, Y., Huang, J., Shia, B., & Ma, S. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbu003 · Cited by 154 · see citing works
Shin, S. Y., Lee, K. S., Choi, Y., Lim, H. J., Lee, M. H., Lim, Y., & Lee, Y. H. (2013) · Carcinogenesis · doi:10.1093/carcin/bgt169 · Cited by 149 · see citing works
Role of Autophagy in Breast Cancer
Karantza, V., & White, E. (2007) · Autophagy · doi:10.4161/auto.4867 · Cited by 138 · see citing works
Chadeau‐Hyam, M., Campanella, G., Jombart, T., Bottolo, L., Portengen, L., Vineis, P., Liquet, B., & Vermeulen, R. C. H. (2013) · Environmental and Molecular Mutagenesis · doi:10.1002/em.21797 · Cited by 133 · see citing works
Tang, H., Sebti, S., Titone, R., Zhou, Y., Isidoro, C., Ross, T. S., Hibshoosh, H. H., Xiao, G., Packer, M., Xie, Y., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.01.008 · Cited by 129 · see citing works
Survival or death: disequilibrating the oncogenic and tumor suppressive autophagy in cancer
Liu, B., Wen, X., & Cheng, Y. (2013) · Cell Death and Disease · doi:10.1038/cddis.2013.422 · Cited by 124 · see citing works
de Tayrac, M., Lê, S., Aubry, M., Mosser, J., & Husson, F. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-32 · Cited by 123 · see citing works
Atg1 family kinases in autophagy initiation
Noda, N. N., & Fujioka, Y. (2015) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-015-1917-z · Cited by 121 · see citing works
BECN1 is involved in the initiation of mitophagy
Choubey, V., Cagalinec, M., Liiv, J., Safiulina, D., Hickey, M. A., Kuum, M., Liiv, M., Anwar, T., Eskelinen, E., & Kaasik, A. (2014) · Autophagy · doi:10.4161/auto.28615 · Cited by 114 · see citing works
Wang, Q., Guo, W., Hao, B., Shi, X., Lü, Y., Wong, C. W. M., Ma, V. W. S., Yip, T. T. C., Au, J. S. K., Hao, Q., et al. (2016) · Autophagy · doi:10.1080/15548627.2016.1187365 · Cited by 105 · see citing works
Serizawa, R., Ralfkiær, U., Steven, K. E., Lam, G. W., Schmiedel, S., Schüz, J., Hansen, A., Horn, T. D., & Guldberg, P. (2010) · International Journal of Cancer · doi:10.1002/ijc.25651 · Cited by 97 · see citing works
Yuan, J., Zhang, Y., Sheng, Y., Fu, X., Cheng, H., & Zhou, R. (2015) · Autophagy · doi:10.1080/15548627.2015.1040970 · Cited by 94 · see citing works
Unraveling the roles of Atg4 proteases from autophagy modulation to targeted cancer therapy
Zhang, L., Li, J., Ouyang, L., Liu, B., & Cheng, Y. (2016) · Cancer Letters · doi:10.1016/j.canlet.2016.01.022 · Cited by 89 · see citing works
Autophagy and mTORC1 regulate the stochastic phase of somatic cell reprogramming
Wu, Y., Li, Y., Zhang, H., Huang, Y., Zhao, P., Tang, Y., Qiu, X., Yue, Y., Li, W., Ni, S., et al. (2015) · Nature Cell Biology · doi:10.1038/ncb3172 · Cited by 85 · see citing works
Markers of autophagy are adapted to hyperglycaemia in skeletal muscle in type 2 diabetes
Kruse, R., Vind, B. F., Petersson, S. J., Kristensen, J. M., & Højlund, K. (2015) · Diabetologia · doi:10.1007/s00125-015-3654-0 · Cited by 67 · see citing works
Pineda, S., Real, F. X., Kogevinas, M., Carrato, A., Chanock, S. J., Malats, N., & Steen, K. V. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005689 · Cited by 61 · see citing works
AMBRA1 and BECLIN 1 interplay in the crosstalk between autophagy and cell proliferation
Cianfanelli, V., D’Orazio, M., & Cecconi, F. (2015) · Cell Cycle · doi:10.1080/15384101.2015.1021526 · Cited by 38 · see citing works
Greenawalt, D. M., Sieberts, S. K., Cornelis, M. C., Girman, C. J., Zhong, H., Yang, X., Guinney, J., Qi, L., & Hu, F. B. (2012) · American Journal of Epidemiology · doi:10.1093/aje/kws123 · Cited by 35 · see citing works
Fu, L., Zhang, S., Zhang, L., Tong, X., Zhang, J. C., Zhang, Y., Ouyang, L., Liu, B., & Huang, J. (2015) · Oncotarget · doi:10.18632/oncotarget.3513 · Cited by 34 · see citing works
Chen, Y., Wang, S., Zhang, L., Xie, T., Song, S., Huang, J., Zhang, Y., Ouyang, L., & Liu, B. (2015) · Scientific Reports · doi:10.1038/srep11035 · Cited by 34 · see citing works
The BECN1 N-terminal domain is intrinsically disordered
Lee, E. F., Perugini, M. A., Pettikiriarachchi, A., Evangelista, M., Keizer, D. W., Yao, S., & Fairlie, W. D. (2016) · Autophagy · doi:10.1080/15548627.2016.1140292 · Cited by 32 · see citing works
Liu, B., Fu, L., Zhang, C., Zhang, L., Zhang, Y., Ouyang, L., He, G., & Huang, J. (2015) · Oncotarget · doi:10.18632/oncotarget.3105 · Cited by 25 · see citing works
Integration and comparison of different genomic data for outcome prediction in cancer
Gómez-Rueda, H., Martínez-Ledesma, E., Martínez‐Torteya, A., Palacios‐Corona, R., & Treviño, V. (2015) · BioData Mining · doi:10.1186/s13040-015-0065-1 · Cited by 23 · see citing works
Multi-step process of human breast carcinogenesis: A role for BRCA1, BECN1, CCND1, PTEN and UVRAG
Wang, J.-Q. (2011) · Molecular Medicine Reports · doi:10.3892/mmr.2011.634 · Cited by 21 · see citing works
Zhao, J., Chen, C., Chen, Y., Han, J., Riley, J., & Zhou, C. (2014) · Neuroscience Letters · doi:10.1016/j.neulet.2014.02.066 · Cited by 20 · see citing works
Xie, T., Zhang, L., Zhang, S., Ouyang, L., Cai, H., & Liu, B. (2016) · Oncotarget · doi:10.18632/oncotarget.7015 · Cited by 19 · see citing works
Rui, Y., Xu, Z., Chen, Z., & Zhang, S. (2015) · Autophagy · doi:10.1080/15548627.2015.1034402 · Cited by 15 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Using machine learning approaches for multi-omics data analysis: A review
Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903 · see citing works
Liao, M., Zhang, J. C., Wang, G., Wang, L., Liu, J., Ouyang, L., & Liu, B. (2021) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c01180 · Cited by 119 · see citing works
Sabino, A. P. L., Eustáquio, L. M. S., Miranda, A. C. F., Biojone, C., Mariosa, T. N., & Gouvêa, C. M. C. P. (2017) · Applied Biochemistry and Biotechnology · doi:10.1007/s12010-017-2632-z · Cited by 38 · see citing works
Jones, E. J., Matthews, Z. J., Gul, L., Sudhakar, P., Treveil, A., Divekar, D. P., Buck, J., Wrzesiński, T., Jefferson, M. A., Armstrong, S. D., et al. (2019) · Disease Models & Mechanisms · doi:10.1242/dmm.037069 · Cited by 25 · see citing works
What We Learned From Big Data for Autophagy Research
Jacomin, A., Gul, L., Sudhakar, P., Korcsmaros, T. D., & Nezis, I. P. (2018) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2018.00092 · Cited by 16 · see citing works
Downregulation of CYB5D2 is associated with breast cancer progression
Ojo, D., Rodriguez, D. A., Wei, F., Bane, A. L., & Tang, D. (2019) · Scientific Reports · doi:10.1038/s41598-019-43006-y · Cited by 14 · see citing works
Du, H., Chen, L., Luo, F., Chen, X., Li, Y. H., & Cheng, Q. (2020) · Oncology Letters · doi:10.3892/ol.2020.11870 · Cited by 13 · see citing works
Liu, Z., Li, L., Li, X., Hua, M., Sun, H., & Zhang, S. (2021) · Journal of Gastrointestinal Oncology · doi:10.21037/jgo-21-508 · Cited by 9 · see citing works
Li, M., Cai, Y., Zhang, M., Deng, S., & Wang, L. (2024) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2024.108291 · Cited by 7 · see citing works
Liu, Z., Lin, Y., Gao, X., Mai, R., Piao, X., Ye, J., & Liang, R. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00634 · Cited by 7 · see citing works
Han, B., Zhang, H., Zhu, Y., Han, X., Wang, Z., Gao, Z., Yuan, Y., Tian, R., Zhang, F., & Niu, R. (2020) · Aging · doi:10.18632/aging.103437 · Cited by 7 · see citing works
Li, M., Cai, Y., Chen, J., Deng, S., & Wang, L. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128777 · Cited by 6 · see citing works
Jones, E. J., Matthews, Z. J., Gul, L., Sudhakar, P., Treveil, A., Divekar, D., Buck, J., Wrzesinski, T., Jefferson, M., Armstrong, S. D., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/410027 · Cited by 4 · see citing works
AMER, M. D. S. M. N. E.-Z. R. Z., & AGINA, M. D. M. A. E.-K. H. A. (2019) · The Medical Journal of Cairo University/The Medical Journal of Cairo University · doi:10.21608/mjcu.2019.53334 · Cited by 1 · see citing works
- Authors
- Chen, Y., Wang, X., Wang, G., Li, Z., Wang, J., Huang, L., Qin, Z., Yuan, X., Cheng, Z., Zhang, S., Yin, Y., & He, J.
- Affiliations
- Sichuan University (CN)
- Corresponding author
- Yin, Yiqiong
- He, Jun
- Venue
- Molecular BioSystems
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-01-27
- Volume
- 13
- Issue
- 5
- Pages
- 991-999
- ISSN
- 1742-2051 (ISSN-L)
- 1742-206X
- OpenAlex
- W2582637393
- Cited by
- 14
- References
- 44
- Citations by year
- 2025: 1 · 2024: 1 · 2021: 3 · 2020: 3 · 2019: 3 · 2018: 2 · 2017: 1
- FWCI
- 0.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Molecular BioSystems (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (81602130)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- breast cancer, Beclin-1, breast cancer subtypes, genetic interactions, autophagy, DNA methylation, copy number alterations, gene expression, AFF3, therapeutic target, multi-omics integration
- MeSH terms
- Beclin-1, Algorithms, Breast Neoplasms, Female, Humans, Nuclear Proteins, Protein Binding, Genetic Variation, Models, Statistical, Gene Expression Regulation, Neoplastic, Gene Dosage, DNA Methylation, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Genomics, DNA Copy Number Variations, Epigenomics, Protein Interaction Maps, MCF-7 Cells
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
