Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Microarray-based mutation analysis of the ABCA4 (ABCR) gene in autosomal recessive cone-rod dystrophy and retinitis pigmentosa.

Contains fulltext : 57320.pdf (publisher's version ) (Closed access)Mutations in the ABCA4 gene have been associated with autosomal recessive Stargardt disease (STGD1), cone-rod dystrophy (CRD), and retinitis pigmentosa (RP). We employed a recently developed genotyping microarray, the ABCR400-chip, to search for known ABCA4 mutations in patients with isolated or autosomal recessive CRD (54 cases) or RP (90 cases). We performed detailed ophthalmologic examinations and identified at least one ABCA4 mutation in 18 patients (33%) with CRD and in five patients (5.6%) with RP. Single-strand conformation polymorphism (SSCP) analysis and subsequent DNA sequencing revealed four novel missense mutations (R24C, E161K, P597S, G618E) and a novel 1-bp deletion (5888delG). Ophthalmoscopic abnormalities in CRD patients ranged from minor granular pigmentary changes in the posterior pole to widespread atrophy. In 12 patients with recordable electroretinogram (ERG) tracings, a cone-rod pattern was detected. Three patients demonstrated progression from a retinal dystrophy resembling STGD1 to a more widespread degeneration, and were subsequently diagnosed as CRD. In addition to a variable degree of atrophy, all RP patients displayed ophthalmologic characteristics of classic RP. When detectable, ERG recordings in these patients demonstrated rod-cone patterns of photoreceptor degeneration. In conclusion, in this study, we show that the ABCA4 mutation chip is an efficient first screening tool for arCRD