The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Non-small-cell lung cancers: a heterogeneous set of diseases
Open accessAbstract
Non-small-cell lung cancers (NSCLCs), the most common lung cancers, are known to have diverse pathological features. During the past decade, in-depth analyses of lung cancer genomes and signalling pathways have further defined NSCLCs as a group of distinct diseases with genetic and cellular heterogeneity. Consequently, an impressive list of potential therapeutic targets was unveiled, drastically altering the clinical evaluation and treatment of patients. Many targeted therapies have been developed with compelling clinical proofs of concept; however, treatment responses are typically short-lived. Further studies of the tumour microenvironment have uncovered new possible avenues to control this deadly disease, including immunotherapy.
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Cites
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Cited by
Long‐term expanding human airway organoids for disease modeling
Sachs, N., Papaspyropoulos, A., Zomer‐van Ommen, D. D., Heo, I., Böttinger, L., Klay, D., Weeber, F., Huelsz‐Prince, G., Iakobachvili, N., Amatngalim, G. D., et al. (2019) · The EMBO Journal · doi:10.15252/embj.2018100300 · Cited by 1,082
Patient-derived lung cancer organoids as in vitro cancer models for therapeutic screening
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Immune Cell Composition in Human Non-small Cell Lung Cancer
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Self-citation
Metadata
- Authors
- Chen, Z., Fillmore, C. M., Hammerman, P. S., Kim, C. F., & Wong, K.-K.
- Venue
- Nature Reviews Cancer
- Published
- 2014-07-24
- Volume
- 14
- Issue
- 8
- Pages
- 535-546
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- OpenAlex
- W1989734503
- Cited by
- 1,942
- References
- 45
- FWCI
- 16.42
- Type
- journal article
- Language
- en
- Open access
- green
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- Chen, Z., Fillmore, C. M., Hammerman, P. S., Kim, C. F., & Wong, K.-K. (2014). Non-small-cell lung cancers: a heterogeneous set of diseases. Nature Reviews Cancer. https://doi.org/10.1038/nrc3775
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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.