Found: 10
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Angiosarcoma heterogeneity and potential therapeutic vulnerability to immune checkpoint blockade: insights from genomic sequencing.
- Published in:
- Genome Medicine, 2020, v. 12, n. 1, p. 1, doi. 10.1186/s13073-020-00753-2
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- Article
Therapeutic implications of cancer gene amplifications without mRNA overexpression: silence may not be golden.
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- Journal of Hematology & Oncology, 2021, v. 14, n. 1, p. 1, doi. 10.1186/s13045-021-01211-1
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- Article
Role of ultraviolet mutational signature versus tumor mutation burden in predicting response to immunotherapy.
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- Molecular Oncology, 2020, v. 14, n. 8, p. 1680, doi. 10.1002/1878-0261.12748
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- Article
Concordance between HER-2 status determined by qPCR in Fine Needle Aspiration Cytology (FNAC) samples compared with IHC and FISH in Core Needle Biopsy (CNB) or surgical specimens in breast cancer patients.
- Published in:
- Molecular Oncology, 2016, v. 10, n. 9, p. 1430, doi. 10.1016/j.molonc.2016.07.009
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- Article
Real-world data from a molecular tumor board demonstrates improved outcomes with a precision N-of-One strategy.
- Published in:
- Nature Communications, 2020, v. 11, n. 1, p. N.PAG, doi. 10.1038/s41467-020-18613-3
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- Article
Overexpression of genes involved in miRNA biogenesis in medullary thyroid carcinomas with RET mutation.
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- Endocrine (1355008X), 2014, v. 47, n. 2, p. 528, doi. 10.1007/s12020-014-0204-3
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- Article
BRAF<sup>V600E</sup> hot spot mutation in thyroid carcinomas: first Moroccan experience from a single-institution retrospective study.
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- African Health Sciences, 2020, v. 20, n. 4, p. 1849, doi. 10.4314/ahs.v20i4.40
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- Article
The Crossroads of Precision Medicine and Therapeutic Decision-Making: Use of an Analytical Computational Platform to Predict Response to Cancer Treatments.
- Published in:
- Cancers, 2020, v. 12, n. 1, p. 166, doi. 10.3390/cancers12010166
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- Article
High prevalence of clonal hematopoiesis‐type genomic abnormalities in cell‐free DNA in invasive gliomas after treatment.
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- International Journal of Cancer, 2021, v. 148, n. 11, p. 2839, doi. 10.1002/ijc.33481
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- Article
Machine learning model to predict oncologic outcomes for drugs in randomized clinical trials.
- Published in:
- International Journal of Cancer, 2020, v. 147, n. 9, p. 2537, doi. 10.1002/ijc.33240
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- Publication type:
- Article