The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
IL-6 and ovarian cancer: inflammatory cytokines in promotion of metastasis
Open accessAbstract
Ovarian cancer is the most fatal gynecological cancer in the USA and the fifth most common cancer-related cause of death in women. Inflammation has been shown to play many roles in ovarian cancer tumor growth, with the proinflammatory cytokine interleukin-6 (IL-6) having been established as a key immunoregulatory cytokine. Ovarian cancer cells continuously secrete cytokines that promote tumorigenicity in both autocrine and paracrine fashions while also receiving signals from the tumor microenvironment (TME). The TME contains many cells including leukocytes and fibroblasts, which respond to proinflammatory cytokines and secrete their own cytokines, which can produce many effects including promotion of chemoresistance, resistance to apoptosis, invasion, angiogenesis by way of overexpression of vascular endothelial growth factor, and promotion of metastatic growth at distant sites. IL-6 and its proinflammatory family members, including oncostatin M, have been found to directly stimulate enhanced invasion of cancer cells through basement membrane degradation caused by the overexpression of matrix metalloproteinases, stimulate promotion of cell cycle, enhance resistance to chemotherapy, and cause epithelial-to-mesenchymal transition (EMT). IL-6 has been shown to activate signaling pathways that lead to tumor proliferation, the most studied of which being the Janus kinase (JAK) and STAT3 pathway. IL-6-induced JAK/STAT activation leads to constitutive activation of STAT3, which has been correlated with enhanced tumor cell growth and resistance to chemotherapy. IL-6 has also been shown to act as a trigger of the EMT, the hypothesized first step in the metastatic cascade. Understanding the important role of IL-6 and its family members' effects on the pathogenesis of ovarian cancer tumor growth and metastasis may lead to more novel treatments, detection methods, and improvement of overall clinical outcomes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Siegel, R. L., Miller, K. D., & Jemal, A. (2016) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21332 · Cited by 16,003
Principles of interleukin (IL)-6-type cytokine signalling and its regulation
HEINRICH, P. C., BEHRMANN, I., HAAN, S., HERMANNS, H. M., MÜLLER-NEWEN, G., & SCHAPER, F. (2003) · Biochemical Journal · doi:10.1042/bj20030407 · Cited by 3,272 · cited 1×
“signal transducer subunit gp130, it can activate multiple signaling pathways.(34) These pathways include the Janus tyrosine kinase (JAK), STAT3 pathway, the mitogenactivated protein kinase pathway,(34) and the phosphoinositide 3-kinase/AKT pathway.”
BackgroundRegulatory networks defining EMT during cancer initiation and progression
Craene, B. D., & Berx, G. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3447 · Cited by 2,487
Biologic sequelae of interleukin-6 induced PI3-K/Akt signaling in multiple myeloma
Hideshima, T., Nakamura, N., Chauhan, D., & Anderson, K. C. (2001) · Oncogene · doi:10.1038/sj.onc.1204833 · Cited by 478
Interleukin-6 Stimulates Defective Angiogenesis
Gopinathan, G., Milagre, C., Pearce, O. M. T., Reynolds, L. E., Hodivala-Dilke, K., Leinster, D. A., Zhong, H., Hollingsworth, R. E., Thompson, R., Whiteford, J. R., et al. (2015) · Cancer Research · doi:10.1158/0008-5472.can-15-1227 · Cited by 249
Interleukin‐6 promotes tumorigenesis by altering DNA methylation in oral cancer cells
Gasche, J. A., Hoffmann, J., Boland, C. R., & Goel, A. (2011) · International Journal of Cancer · doi:10.1002/ijc.25764 · Cited by 178
Cited by
The Role of Tumor-Associated Macrophages in the Progression and Chemoresistance of Ovarian Cancer
Nowak, M., & Klink, M. (2020) · Cells · doi:10.3390/cells9051299 · Cited by 287
Impact of Age-, Cancer- and Treatment-Driven Inflammation on T Cell Function and Immunotherapy
Quinn, K. M., Kartikasari, A. E. R., Cooke, R. E., Koldej, R. M., Ritchie, D. S., & Plebanski, M. (2020) · Journal of Leukocyte Biology · doi:10.1002/jlb.5mr0520-466r · Cited by 31
Metadata
- Authors
- Browning, L., Patel, M., Bring Horvath, E., Tawara, K., & Jorcyk, C. L.
- Venue
- Cancer Management and Research
- Publisher
- Informa UK Limited
- Published
- 2018-12
- Volume
- Volume 10
- Pages
- 6685-6693
- ISSN
- 1179-1322 (ISSN-L)
- OpenAlex
- W2902023274
- Cited by
- 286
- References
- 6
- FWCI
- 7.84
- Type
- journal article
- Language
- en
- Open access
- gold
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.