The DOI matches its Crossref record; 130 of the 130 references it cites were found in a registry or an index.
Heterogeneity in Lung Cancer
Abstract
Lung cancer diagnosis is a challenge since it is also one of the most frequently diagnosed cancers. Diagnostic challenges are deeply related to the development of personalized therapy and molecular and precise histological characterizations of lung cancer. When addressing these features, it is very important to acknowledge the issue of tumour heterogeneity, as it imposes several questions. First of all, lung cancer is a very heterogeneous disease, at a cellular and histological level. Cellular and histological heterogeneity are addressed with emphasis on the diagnosis, pre-neoplastic lesions, and cell origin, trying to contribute to a better knowledge of carcinogenesis. Molecular intra-tumour and inter-tumour heterogeneity are also addressed as temporal heterogeneity. Lung cancer heterogeneity has implications in pathogenesis understanding, diagnosis, selection of tissue for molecular diagnosis, as well as therapeutic decision. The understanding of tumour heterogeneity is crucial and we must be aware of the implications and future developments regarding this field.
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Intra-tumour heterogeneity: a looking glass for cancer?
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Pathology and genetics of tumours of the lung , pleura, thymus and heart
Travis, W. D. (2004) · Cited by 1,955
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Cited by
Mitochondrial CPT1A: Insights into structure, function, and basis for drug development
Liang, K. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1160440 · Cited by 156
Metadata
- Authors
- de Sousa, V. M. L., & Carvalho, L.
- Venue
- Pathobiology
- Publisher
- S. Karger AG
- Published
- 2018
- Volume
- 85
- Issue
- 1-2
- Pages
- 96-107
- ISSN
- 1015-2008 (ISSN-L)
- 1423-0291
- OpenAlex
- W2796573946
- Cited by
- 364
- References
- 130
- FWCI
- 12.68
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
