| 1. |
- Bai, Yalai, et al.
(författare)
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An Open Source, Automated Tumor Infiltrating Lymphocyte Algorithm for Prognosis in Triple-Negative Breast Cancer
- 2021
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 27:20, s. 5557-5565
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Although tumor infiltrating lymphocytes (TIL) assessment has been acknowledged to have both prognostic and predictive importance in triple negative breast cancer (TNBC), it is subject to inter and intra-observer variability that has prevented widespread adoption. Here we constructed a machine-learning based breast cancer TIL scoring approach and validated its prognostic potential in multiple TNBC cohorts. Experimental Design: Using the QuPath open source software, we built a neural-network classifier for tumor cells, lymphocytes, fibroblasts and “other” cells on hematoxylin-eosin (H&E) stained sections. We analyzed the classifier-derived TIL measurements with five unique constructed TIL variables. A retrospective collection of 171 TNBC cases was used as the discovery set to identify the optimal association of machine-read TIL variables with patient outcome. For validation we evaluated a retrospective collection of 749 TNBC patients comprised of four independent validation subsets. Results: We found that all five machine TIL variables had significant prognostic association with outcomes (p≤0.01 for all comparisons) but showed cell specific variation in validation sets. Cox regression analysis demonstrated that all five TIL variables were independently associated with improved overall survival after adjusting for clinicopathological factors including stage, age and histological grade (p≤0.003 for all analyses). Conclusions: Neural net driven cell classifier defined TIL variables were robust and independent prognostic factors in several independent validation cohorts of TNBC patients. These objective, open source TIL variables are freely available to download and can now be considered for testing in a prospective setting to assess clinical utility.
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| 2. |
- Cheng, Yu-Ching, et al.
(författare)
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Genome-Wide Association Analysis of Young-Onset Stroke Identifies a Locus on Chromosome 10q25 Near HABP2.
- 2016
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Ingår i: Stroke; a journal of cerebral circulation. - 1524-4628. ; 47:2, s. 307-16
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Tidskriftsartikel (refereegranskat)abstract
- Although a genetic contribution to ischemic stroke is well recognized, only a handful of stroke loci have been identified by large-scale genetic association studies to date. Hypothesizing that genetic effects might be stronger for early- versus late-onset stroke, we conducted a 2-stage meta-analysis of genome-wide association studies, focusing on stroke cases with an age of onset <60 years.
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| 3. |
- Hoshino, Ayuko, et al.
(författare)
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Tumour exosome integrins determine organotropic metastasis
- 2015
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Ingår i: Nature. - : NATURE PUBLISHING GROUP. - 0028-0836 .- 1476-4687. ; 527:7578, s. 329-
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Tidskriftsartikel (refereegranskat)abstract
- Ever since Stephen Pagets 1889 hypothesis, metastatic organotropism has remained one of cancers greatest mysteries. Here we demonstrate that exosomes from mouse and human lung-, liver-and brain-tropic tumour cells fuse preferentially with resident cells at their predicted destination, namely lung fibroblasts and epithelial cells, liver Kupffer cells and brain endothelial cells. We show that tumour-derived exosomes uptaken by organ-specific cells prepare the pre-metastatic niche. Treatment with exosomes from lung-tropic models redirected the metastasis of bone-tropic tumour cells. Exosome proteomics revealed distinct integrin expression patterns, in which the exosomal integrins alpha(6)beta(4) and alpha(6)beta(1) were associated with lung metastasis, while exosomal integrin alpha(v)beta(5) was linked to liver metastasis. Targeting the integrins alpha(6)beta(4) and alpha(v)beta(5) decreased exosome uptake, as well as lung and liver metastasis, respectively. We demonstrate that exosome integrin uptake by resident cells activates Src phosphorylation and pro-inflammatory S100 gene expression. Finally, our clinical data indicate that exosomal integrins could be used to predict organ-specific metastasis.
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