FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithms Article Swipe
Wei Lu
,
Dongliang Fu
,
Xiangxing Kong
,
Zhiheng Huang
,
Maxwell Hwang
,
Yingshuang Zhu
,
Liubo Chen
,
Kai Jiang
,
Xinlin Li
,
Yihua Wu
,
Jun Li
,
Ying Yuan
,
Kefeng Ding
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1002/cam4.2786
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1002/cam4.2786
Early identification of metastatic or recurrent colorectal cancer (CRC) patients who will be sensitive to FOLFOX (5‐FU, leucovorin and oxaliplatin) therapy is very important. We performed microarray meta‐analysis to identify differentially expressed genes (DEGs) between FOLFOX responders and nonresponders in metastatic or recurrent CRC patients, and found that the expression levels of WASHC4, HELZ, ERN1, RPS6KB1, and APPBP2 were downregulated, while the expression levels of IRF7, EML3, LYPLA2, DRAP1, RNH1, PKP3, TSPAN17, LSS, MLKL, PPP1R7, GCDH, C19ORF24, and CCDC124 were upregulated in FOLFOX responders compared with nonresponders. Subsequent functional annotation showed that DEGs were significantly enriched in autophagy, ErbB signaling pathway, mitophagy, endocytosis, FoxO signaling pathway, apoptosis, and antifolate resistance pathways. Based on those candidate genes, several machine learning algorithms were applied to the training set, then performances of models were assessed via the cross validation method. Candidate models with the best tuning parameters were applied to the test set and the final model showed satisfactory performance. In addition, we also reported that MLKL and CCDC124 gene expression were independent prognostic factors for metastatic CRC patients undergoing FOLFOX therapy.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1002/cam4.2786
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cam4.2786
- OA Status
- gold
- Cited By
- 43
- References
- 50
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2998706172
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2998706172Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/cam4.2786Digital Object Identifier
- Title
-
FOLFOX treatment response prediction in metastatic or recurrent colorectal cancer patients via machine learning algorithmsWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Wei Lu, Dongliang Fu, Xiangxing Kong, Zhiheng Huang, Maxwell Hwang, Yingshuang Zhu, Liubo Chen, Kai Jiang, Xinlin Li, Yihua Wu, Jun Li, Ying Yuan, Kefeng DingList of authors in order
- Landing page
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https://doi.org/10.1002/cam4.2786Publisher landing page
- PDF URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cam4.2786Direct link to full text PDF
- Open access
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YesWhether a free full text is available
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-
goldOpen access status per OpenAlex
- OA URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/cam4.2786Direct OA link when available
- Concepts
-
FOLFOX, Oxaliplatin, Colorectal cancer, Oncology, Medicine, Predictive marker, Internal medicine, Cancer, Cancer research, Algorithm, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
43Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 8, 2023: 8, 2022: 10, 2021: 5Per-year citation counts (last 5 years)
- References (count)
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50Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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