The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.
Gastric Cancer: Epidemiology, Risk Factors, Classification, Genomic Characteristics and Treatment Strategies
Open accessAbstract
Gastric cancer (GC) is one of the most common malignancies worldwide and it is the fourth leading cause of cancer-related death. GC is a multifactorial disease, where both environmental and genetic factors can have an impact on its occurrence and development. The incidence rate of GC rises progressively with age; the median age at diagnosis is 70 years. However, approximately 10% of gastric carcinomas are detected at the age of 45 or younger. Early-onset gastric cancer is a good model to study genetic alterations related to the carcinogenesis process, as young patients are less exposed to environmental carcinogens. Carcinogenesis is a multistage disease process specified by the progressive development of mutations and epigenetic alterations in the expression of various genes, which are responsible for the occurrence of the disease.
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Cites
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Molecular analysis of gastric cancer identifies subtypes associated with distinct clinical outcomes
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Cited by
Baj, J., Forma, A., Sitarz, M., Portincasa, P., Garruti, G., Krasowska, D., & Maciejewski, R. (2020) · Cells · doi:10.3390/cells10010027 · Cited by 369
Self-citationGao, W., & Yang, M. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.881015 · Cited by 13
Metadata
- Authors
- Machlowska, J., Baj, J., Sitarz, M., Maciejewski, R., & Sitarz, R.
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2020-06-04
- Volume
- 21
- Issue
- 11
- Pages
- 4012
- ISSN
- 1422-0067 (ISSN-L)
- OpenAlex
- W3033366394
- Cited by
- 1,520
- References
- 111
- FWCI
- 91.00
- Type
- journal article
- Language
- en
- Open access
- gold
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- Machlowska, J., Baj, J., Sitarz, M., Maciejewski, R., & Sitarz, R. (2020). Gastric Cancer: Epidemiology, Risk Factors, Classification, Genomic Characteristics and Treatment Strategies. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms21114012
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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.
