Identification and Characterization of Immunogene-Related Alternative Splicing Patterns and Tumor Microenvironment Infiltration Patterns in Breast Cancer

被引:3
作者
Guo, Shuang [1 ]
Wang, Xinyue [1 ]
Zhou, Hanxiao [1 ]
Gao, Yue [1 ]
Wang, Peng [1 ]
Zhi, Hui [1 ]
Sun, Yue [1 ]
Hao, Yangyang [1 ]
Gan, Jing [1 ]
Zhang, Yakun [1 ]
Sun, Jie [1 ]
Zheng, Wen [1 ]
Zhao, Xiaoxi [1 ]
Xiao, Yun [1 ]
Ning, Shangwei [1 ]
机构
[1] Harbin Med Univ, Coll Bioinformat Sci & Technol, Harbin 150081, Peoples R China
基金
中国国家自然科学基金;
关键词
immunogene-related alternative splicing; tumor microenvironment; prognosis signatures; immuno; chemotherapy; breast cancer; IMMUNE CHECKPOINT BLOCKADE; LYMPHOCYTES; EXPRESSION; DATABASE;
D O I
10.3390/cancers14030595
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Simple Summary Aberrant immunogene-related alternative splicing (IGAS) pattern plays a pivotal role in pathogenesis, progression, and tumor microenvironment. However, the IGAS pattern of post-transcriptional mechanisms in breast cancer remains limited. Here, we performed a systematic analysis of IGAS patterns in breast cancer to assess the association between aberrant IGAS events, prognosis signatures, AS regulatory network, immune cell infiltration level and its marker gene expression, sensitivity to immunotherapy and chemotherapy, and heterogeneity of IGAS clusters. Generally, we demonstrated the prognostic signatures for IGAS events and immune cells, which were valuable information for breast cancer patients in predicting survival and directing immunotherapy and chemotherapy. Alternative splicing (AS) plays a crucial role in tumor development and tumor microenvironment (TME) formation. However, our current knowledge about AS, especially immunogene-related alternative splicing (IGAS) patterns in cancers, remains limited. Herein, we identified and characterized post-transcriptional mechanisms of breast cancer based on IGAS, TME, prognosis, and immuno/chemotherapy. We screened the differentially spliced IGAS events and constructed the IGAS prognostic model (p-values < 0.001, AUC = 0.939), which could be used as an independent prognostic factor. Besides, the AS regulatory network suggested a complex cooperative or competitive relationship between splicing factors and IGAS events, which explained the diversity of splice isoforms. In addition, more than half of the immune cells displayed varying degrees of infiltration in the IGAS risk groups, and the prognostic characteristics of IGAS demonstrated a remarkable and consistent trend correlation with the infiltration levels of immune cell types. The IGAS risk groups showed substantial differences in the sensitivity of immunotherapy and chemotherapy. Finally, IGAS clusters defined by unsupervised cluster analysis had distinct prognostic patterns, suggesting an essential heterogeneity of IGAS events. Significant differences in immune infiltration and unique prognostic capacity of immune cells were also detected in each IGAS cluster. In conclusion, our comprehensive analysis remarkably enhanced the understanding of IGAS patterns and TME in breast cancer, which may help clarify the underlying mechanisms of IGAS in neoplasia and provide clues to molecular mechanisms of oncogenesis and progression.
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页数:17
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共 47 条
[1]   Alternative splicing as a regulator of development and tissue identity [J].
Baralle, Francisco E. ;
Giudice, Jimena .
NATURE REVIEWS MOLECULAR CELL BIOLOGY, 2017, 18 (07) :437-451
[2]   Spatiotemporal Dynamics of Intratumoral Immune Cells Reveal the Immune Landscape in Human Cancer [J].
Bindea, Gabriela ;
Mlecnik, Bernhard ;
Tosolini, Marie ;
Kirilovsky, Amos ;
Waldner, Maximilian ;
Obenauf, Anna C. ;
Angell, Helen ;
Fredriksen, Tessa ;
Lafontaine, Lucie ;
Berger, Anne ;
Bruneval, Patrick ;
Fridman, Wolf Herman ;
Becker, Christoph ;
Pages, Franck ;
Speicher, Michael R. ;
Trajanoski, Zlatko ;
Galon, Jerome .
IMMUNITY, 2013, 39 (04) :782-795
[3]   Proteomic identification of differentially expressed proteins associated with the multiple drug resistance in methotrexate-resistant human breast cancer cells [J].
Chen, Siying ;
Cai, Jiangxia ;
Zhang, Weipeng ;
Zheng, Xiaowei ;
Hu, Sasa ;
Lu, Jun ;
Xing, Jianfeng ;
Dong, Yalin .
INTERNATIONAL JOURNAL OF ONCOLOGY, 2014, 45 (01) :448-458
[4]   DOCETAXEL [J].
CORTES, JE ;
PAZDUR, R .
JOURNAL OF CLINICAL ONCOLOGY, 1995, 13 (10) :2643-2655
[5]   Tumor-Associated Lymphocytes As an Independent Predictor of Response to Neoadjuvant Chemotherapy in Breast Cancer [J].
Denkert, Carsten ;
Loibl, Sibylle ;
Noske, Aurelia ;
Roller, Marc ;
Mueller, Berit Maria ;
Komor, Martina ;
Budczies, Jan ;
Darb-Esfahani, Silvia ;
Kronenwett, Ralf ;
Hanusch, Claus ;
von Toerne, Christian ;
Weichert, Wilko ;
Engels, Knut ;
Solbach, Christine ;
Schrader, Iris ;
Dietel, Manfred ;
von Minckwitz, Gunter .
JOURNAL OF CLINICAL ONCOLOGY, 2010, 28 (01) :105-113
[6]   Prognostic and predictive value of tumor-infiltrating lymphocytes in two phase III randomized adjuvant breast cancer trials [J].
Dieci, M. V. ;
Mathieu, M. C. ;
Guarneri, V. ;
Conte, P. ;
Delaloge, S. ;
Andre, F. ;
Goubar, A. .
ANNALS OF ONCOLOGY, 2015, 26 (08) :1698-1704
[7]   The immune contexture in human tumours: impact on clinical outcome [J].
Fridman, Wolf Herman ;
Pages, Franck ;
Sautes-Fridman, Catherine ;
Galon, Jerome .
NATURE REVIEWS CANCER, 2012, 12 (04) :298-306
[8]   Pembrolizumab for the Treatment of Non-Small-Cell Lung Cancer [J].
Garon, Edward B. ;
Rizvi, Naiyer A. ;
Hui, Rina ;
Leighl, Natasha ;
Balmanoukian, Ani S. ;
Eder, Joseph Paul ;
Patnaik, Amita ;
Aggarwal, Charu ;
Gubens, Matthew ;
Horn, Leora ;
Carcereny, Enric ;
Ahn, Myung-Ju ;
Felip, Enriqueta ;
Lee, Jong-Seok ;
Hellmann, Matthew D. ;
Hamid, Omid ;
Goldman, Jonathan W. ;
Soria, Jean-Charles ;
Dolled-Filhart, Marisa ;
Rutledge, Ruth Z. ;
Zhang, Jin ;
Lunceford, Jared K. ;
Rangwala, Reshma ;
Lubiniecki, Gregory M. ;
Roach, Charlotte ;
Emancipator, Kenneth ;
Gandhi, Leena .
NEW ENGLAND JOURNAL OF MEDICINE, 2015, 372 (21) :2018-2028
[9]   pRRophetic: An R Package for Prediction of Clinical Chemotherapeutic Response from Tumor Gene Expression Levels [J].
Geeleher, Paul ;
Cox, Nancy ;
Huang, R. Stephanie .
PLOS ONE, 2014, 9 (09)
[10]   SpliceAid-F: a database of human splicing factors and their RNA-binding sites [J].
Giulietti, Matteo ;
Piva, Francesco ;
D'Antonio, Mattia ;
De Meo, Paolo D'Onorio ;
Paoletti, Daniele ;
Castrignano, Tiziana ;
D'Erchia, Anna Maria ;
Picardi, Ernesto ;
Zambelli, Federico ;
Principato, Giovanni ;
Pavesi, Giulio ;
Pesole, Graziano .
NUCLEIC ACIDS RESEARCH, 2013, 41 (D1) :D125-D131