12 research outputs found
Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling
Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples
Prevalence and associated factors of atopic dermatitis symptoms in rural and urban Ethiopia
Quality of randomized controlled trials reporting in the treatment of melasma conducted in China
Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.
High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between TÂ cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion
Synthetic Biology at the Hand of Cell-Free Systems
International audienceCell-free systems are emerging as membraneless transcriptional and translational tools to study biology and for prototyping, characterization, and engineering novel biological systems. Cell-free systems allow in vitro transcription and translation using the cellular machinery prepared from a variety of prokaryotic and eukaryotic cells. These non-GMO tools enable rapid and high-throughput characterization by their rapid gene expression, simple building of large combinatorial libraries, easier cloning, lower noise, less susceptibility to toxicity, and high tunability. In this chapter, different types of cell-free systems, different techniques to obtain them, and their applications in synthetic biology and bioengineering are presented