The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Development and validation of an immune gene-set based Prognostic signature in ovarian cancer
Open accessAbstract
BACKGROUND: Ovarian cancer (OV) is the most lethal gynecological cancer in women. We aim to develop a generalized, individualized immune prognostic signature that can stratify and predict overall survival for ovarian cancer. METHODS: The gene expression profiles of ovarian cancer tumor tissue samples were collected from 17 public cohorts, including 2777 cases totally. Single sample gene set enrichment (ssGSEA) analysis was used for the immune genes from ImmPort database to develop an immune-based prognostic score for OV (IPSOV). The signature was trained and validated in six independent datasets (n = 519, 409, 606, 634, 415, 194). FINDINGS: ]). Further, we compared IPSOV with nine reported ovarian cancer prognostic signatures as well as the clinical characteristics including stage, grade and debulking status. The IPSOV achieved the highest mean C-index (0.625) compared with the other signatures (0.516 to 0.602) and clinical characteristics (0.555 to 0.583). Further, we integrated IPSOV with stage, grade and debulking, which showed improved prognostic accuracy than clinical characteristics only. INTERPRETATION: The proposed clinical-immune signature is a promising biomarker for estimating overall survival in ovarian cancer. Prospective studies are needed to further validate its analytical accuracy and test the clinical utility. FUND: This work was supported by National Key Research and Development Program of China, National Natural Science Foundation of China and Natural Science Foundation of the Jiangsu Higher Education Institutions of China.
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clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
Siegel, R. L., Miller, K. D., & Jemal, A. (2018) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21442 · Cited by 16,579
Adjusting batch effects in microarray expression data using empirical Bayes methods
Johnson, W. E., Li, C., & Rabinovic, A. (2007) · Biostatistics · doi:10.1093/biostatistics/kxj037 · Cited by 8,658
Immune Checkpoint Blockade: A Common Denominator Approach to Cancer Therapy
Topalian, S. L., Drake, C. G., & Pardoll, D. M. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.03.001 · Cited by 4,229
Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1
Barbie, D. A., Tamayo, P., Boehm, J. S., Kim, S. Y., Moody, S. E., Dunn, I. F., Schinzel, A. C., Sandy, P., Meylan, E., Scholl, C., et al. (2009) · Nature · doi:10.1038/nature08460 · Cited by 3,890
The prognostic landscape of genes and infiltrating immune cells across human cancers
Gentles, A. J., Newman, A. M., Liu, C. L., Bratman, S. V., Feng, W., Kim, D., Nair, V. S., Xu, Y., Khuong, A., Hoang, C. D., et al. (2015) · Nature Medicine · doi:10.1038/nm.3909 · Cited by 3,118
Cancer immunotherapy: moving beyond current vaccines
Rosenberg, S. A., Yang, J. C., & Restifo, N. P. (2004) · Nature Medicine · doi:10.1038/nm1100 · Cited by 2,972
Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy
Nagarsheth, N., Wicha, M. S., & Zou, W. (2017) · Nature Reviews Immunology · doi:10.1038/nri.2017.49 · Cited by 2,206
A cytokine-mediated link between innate immunity, inflammation, and cancer
Lin, W.-W., & Karin, M. (2007) · Journal of Clinical Investigation · doi:10.1172/jci31537 · Cited by 1,940 · cited 1×
“Cytokines and cytokine receptors processes play important roles in inflammatory, angiogenesis and chemotaxis processes [26].”
BackgroundCrosstalk between cancer and immune cells: role of STAT3 in the tumour microenvironment
Yu, H., Kortylewski, M., & Pardoll, D. (2007) · Nature Reviews Immunology · doi:10.1038/nri1995 · Cited by 1,804
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Metadata
- Authors
- Shen, S., Wang, G., Zhang, R., Zhao, Y., Yu, H., Wei, Y., & Chen, F.
- Venue
- EBioMedicine
- Publisher
- Elsevier BV
- Published
- 2019-02
- Volume
- 40
- Pages
- 318-326
- ISSN
- 2352-3964 (ISSN-L)
- OpenAlex
- W2907123184
- Cited by
- 257
- References
- 39
- FWCI
- 27.62
- Type
- journal article
- Language
- en
- Open access
- gold
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