Microenvironmental regulation of tumor progression and metastasis

Nature Medicine, Journal Year: 2013, Volume and Issue: 19(11), P. 1423 - 1437

Published: Nov. 1, 2013

Language: Английский

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Computational Radiomics System to Decode the Radiographic Phenotype

Cancer Research, Journal Year: 2017, Volume and Issue: 77(21), P. e104 - e107

Published: Oct. 31, 2017

Radiomics aims to quantify phenotypic characteristics on medical imaging through the use of automated algorithms. Radiomic artificial intelligence (AI) technology, either based engineered hard-coded algorithms or deep learning methods, can be used develop noninvasive imaging-based biomarkers. However, lack standardized algorithm definitions and image processing severely hampers reproducibility comparability results. To address this issue, we developed PyRadiomics, a flexible open-source platform capable extracting large panel features from images. PyRadiomics is implemented in Python standalone using 3D Slicer. Here, discuss workflow architecture demonstrate its application characterizing lung lesions. Source code, documentation, examples are publicly available at www.radiomics.io With platform, aim establish reference standard for radiomic analyses, provide tested maintained resource, grow community developers addressing critical needs cancer research. Cancer Res; 77(21); e104-7. ©2017 AACR.

Language: Английский

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Emerging Biological Principles of Metastasis

Cell, Journal Year: 2017, Volume and Issue: 168(4), P. 670 - 691

Published: Feb. 1, 2017

Language: Английский

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Tumour heterogeneity and cancer cell plasticity

Nature, Journal Year: 2013, Volume and Issue: 501(7467), P. 328 - 337

Published: Sept. 17, 2013

Language: Английский

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The causes and consequences of genetic heterogeneity in cancer evolution

Nature, Journal Year: 2013, Volume and Issue: 501(7467), P. 338 - 345

Published: Sept. 17, 2013

Language: Английский

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Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

Cell, Journal Year: 2015, Volume and Issue: 162(1), P. 184 - 197

Published: June 18, 2015

Language: Английский

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Evolution of the Cancer Stem Cell Model

Cell stem cell, Journal Year: 2014, Volume and Issue: 14(3), P. 275 - 291

Published: March 1, 2014

Language: Английский

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Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry

Nature Methods, Journal Year: 2014, Volume and Issue: 11(4), P. 417 - 422

Published: March 2, 2014

Language: Английский

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Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics

Proceedings of the National Academy of Sciences, Journal Year: 2013, Volume and Issue: 110(10), P. 4009 - 4014

Published: Feb. 14, 2013

Glioblastoma (GB) is the most common and aggressive primary brain malignancy, with poor prognosis a lack of effective therapeutic options. Accumulating evidence suggests that intratumor heterogeneity likely key to understanding treatment failure. However, extent as result tumor evolution still poorly understood. To address this, we developed unique surgical multisampling scheme collect spatially distinct fragments from 11 GB patients. We present an integrated genomic analysis uncovers extensive heterogeneity, patients displaying different subtypes within same tumor. Moreover, reconstructed phylogeny for each patient, identifying copy number alterations in EGFR CDKN2A/B/p14ARF early events, aberrations PDGFRA PTEN later events during cancer progression. also characterized clonal organization fragment at single-molecule level, detecting multiple coexisting cell lineages. Our results reveal genome-wide architecture variability across spatial scales patient-specific patterns evolution, consequences design.

Language: Английский

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The Cancer Stem Cell Niche: How Essential Is the Niche in Regulating Stemness of Tumor Cells?

Cell stem cell, Journal Year: 2015, Volume and Issue: 16(3), P. 225 - 238

Published: March 1, 2015

Language: Английский

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