Artificial intelligence in cancer imaging: Clinical challenges and applications

CA A Cancer Journal for Clinicians, Год журнала: 2019, Номер 69(2), С. 127 - 157

Опубликована: Фев. 5, 2019

Abstract Judgement, as one of the core tenets medicine, relies upon integration multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms evolution disease but also need to take into account individual condition patients, their ability receive treatment, and responses treatment. Challenges remain in accurate detection, characterization, monitoring cancers despite improved technologies. Radiographic assessment most commonly visual evaluations, interpretations which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises make great strides qualitative interpretation cancer imaging expert clinicians, including volumetric delineation tumors over time, extrapolation tumor genotype biological course from radiographic phenotype, prediction clinical outcome, impact treatment on adjacent organs. AI automate processes initial images shift workflow management whether or administer an intervention, subsequent observation yet envisioned paradigm. Here, authors review current state applied describe advances 4 types (lung, brain, breast, prostate) illustrate how common problems are being addressed. Although studies evaluating applications oncology date have been vigorously validated reproducibility generalizability, results do highlight increasingly concerted efforts pushing technology use future directions care.

Язык: Английский

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Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells

Cell, Год журнала: 2020, Номер 181(7), С. 1643 - 1660.e17

Опубликована: Май 28, 2020

Язык: Английский

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A peptide encoded by circular form of LINC-PINT suppresses oncogenic transcriptional elongation in glioblastoma

Nature Communications, Год журнала: 2018, Номер 9(1)

Опубликована: Окт. 22, 2018

Circular RNAs (circRNAs) are a large class of transcripts in the mammalian genome. Although translation circRNAs was reported, additional coding and functions their translated products remain elusive. Here, we demonstrate that an endogenous circRNA generated from long noncoding RNA encodes regulatory peptides. Through ribosome nascent-chain complex-bound sequencing (RNC-seq), discover several peptides potentially encoded by circRNAs. We identify 87-amino-acid peptide circular form intergenic non-protein-coding p53-induced transcript (LINC-PINT) suppresses glioblastoma cell proliferation vitro vivo. This directly interacts with polymerase associated factor complex (PAF1c) inhibits transcriptional elongation multiple oncogenes. The expression this its corresponding decreased compared levels normal tissues. Our results establish existence potential tumorigenesis.

Язык: Английский

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Glioblastoma stem cells: lessons from the tumor hierarchy in a lethal cancer

Genes & Development, Год журнала: 2019, Номер 33(11-12), С. 591 - 609

Опубликована: Июнь 1, 2019

Glioblastoma ranks among the most lethal of all human cancers. Glioblastomas display striking cellular heterogeneity, with stem-like glioblastoma stem cells (GSCs) at apex. Although original identification GSCs dates back more than a decade, purification and characterization remains challenging. Despite these challenges, evidence that play important roles in tumor growth response to therapy has grown. Like normal cells, are functionally defined distinguished from their differentiated progeny core transcriptional, epigenetic, metabolic regulatory levels, suggesting no single therapeutic modality will be universally effective against heterogenous GSC population. induce systemic immunosuppression mixed responses oncoimmunologic modalities, potential for augmentation deeper consideration GSCs. Unfortunately, literature been complicated by frequent use inferior cell lines lack proper functional analyses. Collectively, offers reliable cancer study better model disease inform improved biologic understanding design novel therapeutics.

Язык: Английский

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Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis

IEEE Transactions on Medical Imaging, Год журнала: 2020, Номер 41(4), С. 757 - 770

Опубликована: Сен. 3, 2020

Cancer diagnosis, prognosis, mymargin and therapeutic response predictions are based on morphological information from histology slides molecular profiles genomic data. However, most deep learning-based objective outcome prediction grading paradigms or genomics alone do not make use of the complementary in an intuitive manner. In this work, we propose Pathomic Fusion, interpretable strategy for end-to-end multimodal fusion image (mutations, CNV, RNA-Seq) features survival prediction. Our approach models pairwise feature interactions across modalities by taking Kronecker product unimodal representations, controls expressiveness each representation via a gating-based attention mechanism. Following supervised learning, able to interpret saliently localize modality, understand how importance shifts when conditioning input. We validate our using glioma clear cell renal carcinoma datasets Genome Atlas (TCGA), which contains paired whole-slide image, genotype, transcriptome data with ground truth histologic grade labels. 15-fold cross-validation, results demonstrate that proposed paradigm improves prognostic determinations subtyping, as well networks trained alone. The method establishes insight theory train biomedical manner, will be useful other problems medicine seek combine heterogeneous streams understanding diseases predicting resistance treatment. Code made available at: https://github.com/mahmoodlab/PathomicFusion.

Язык: Английский

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Glioblastoma hijacks neuronal mechanisms for brain invasion

Cell, Год журнала: 2022, Номер 185(16), С. 2899 - 2917.e31

Опубликована: Июль 31, 2022

Язык: Английский

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Harnessing multimodal data integration to advance precision oncology

Nature reviews. Cancer, Год журнала: 2021, Номер 22(2), С. 114 - 126

Опубликована: Окт. 18, 2021

Язык: Английский

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Neutrophil-induced ferroptosis promotes tumor necrosis in glioblastoma progression

Nature Communications, Год журнала: 2020, Номер 11(1)

Опубликована: Окт. 27, 2020

Abstract Tumor necrosis commonly exists and predicts poor prognoses in many cancers. Although it is thought to result from chronic ischemia, the underlying nature mechanisms driving involved cell death remain obscure. Here, we show that glioblastoma (GBM) involves neutrophil-triggered ferroptosis. In a hyperactivated transcriptional coactivator with PDZ-binding motif-driven GBM mouse model, neutrophils coincide temporally spatially. Neutrophil depletion dampens necrosis. Neutrophils isolated brain tumors kill cocultured tumor cells. Mechanistically, induce iron-dependent accumulation of lipid peroxides within cells by transferring myeloperoxidase-containing granules into Inhibition or myeloperoxidase suppresses neutrophil-induced cytotoxicity. Intratumoral glutathione peroxidase 4 overexpression acyl-CoA synthetase long chain family member diminishes aggressiveness tumors. Furthermore, analyses human GBMs support ferroptosis are associated predict survival. Thus, our study identifies as reveals pro-tumorigenic role Together, propose certain damage(s) occurring during early progression (i.e. ischemia) recruits site tissue damage thereby results positive feedback loop, amplifying development its fullest extent.

Язык: Английский

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Outer Radial Glia-like Cancer Stem Cells Contribute to Heterogeneity of Glioblastoma

Cell stem cell, Год журнала: 2020, Номер 26(1), С. 48 - 63.e6

Опубликована: Янв. 1, 2020

Glioblastoma is a devastating form of brain cancer. To identify aspects tumor heterogeneity that may illuminate drivers invasion, we created glioblastoma cell atlas with single-cell transcriptomics cancer cells mapped onto reference framework the developing and adult human brain. We find multiple GSC subtypes exist within single tumor. Within these GSCs, an invasive population similar to outer radial glia (oRG), fetal type expands stem niche in normal cortex. Using live time-lapse imaging primary resected tumors, discover tumor-derived oRG-like undergo characteristic mitotic somal translocation behavior previously only observed development, suggesting reactivation developmental programs. In addition, show PTPRZ1 mediates both invasion. These data suggest presence heterogeneous GSCs underlie glioblastoma's rapid progression

Язык: Английский

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Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology

Nature Cancer, Год журнала: 2022, Номер 3(4), С. 505 - 517

Опубликована: Апрель 25, 2022

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), method predict cellular composition individual types RNA-seq, patient-derived, scRNA-seq as prior information. We conduct integrative analyses primary glioblastoma, head neck squamous carcinoma skin cutaneous melanoma correlate type with clinical outcomes across tumor types, explore spatial heterogeneity malignant nonmalignant states. refine current cancer subtypes annotation after exclusion of confounding cells. Finally, identify genes whose cells correlates macrophage infiltration, T cells, fibroblasts endothelial multiple types. Our work introduces new lens accurately infer large cohorts RNA-seq data.

Язык: Английский

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