Biology subjects

Nawy, T.

Publications and source records attributed to Nawy, T..

3 recordsLinked to original sources

bioRxiv2021

Sparcle: assigning transcripts to cells in multiplexed images

BackgroundImaging-based spatial transcriptomics has the power to reveal patterns of single-cell gene expression by detecting mRNA transcripts as individually resolved spots in multiplexed images. However, molecular quantification has been severely limited by the computational challenges of segmenting poorly outlined, overlapping cells, and of overcoming technical noise; the majority of transcripts are routinely discarded because they fall outside the segmentation boundaries. This lost information leads to less accurate gene count matrices and weakens downstream analyses, such as cell type or gene program identification. ResultsHere, we present Sparcle, a probabilistic model that reassigns transcripts to cells based on gene covariation patterns and incorporates spatial features such as distance to nucleus. We demonstrate its utility on both multiplexed error-robust fluorescence in situ hybridization (MERFISH) and single-molecule FISH (smFISH) data. ConclusionsSparcle improves transcript assignment, providing more realistic per-cell quantification of each gene, better delineation of cell boundaries, and improved cluster assignments. Critically, our approach does not require an accurate segmentation and is agnostic to technological platform.

bioinformatics↗

bioRxiv2020

Single cell profiling reveals novel tumor and myeloid subpopulations in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), which are associated with distinct therapeutic vulnerabilities. To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 54,523 cellular transcriptomes from 21 human biospecimens. Our single-cell SCLC atlas reveals tumor diversity exceeding lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discovered a PLCG2-high tumor cell population with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival, and manipulation of PLCG2 expression in cells confirms correlation with key metastatic markers. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than SCLC-A. Moreover, the recurrent, PLCG2-high subclone is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis.

cancer biology↗

bioRxiv2020

Counterfactual Hypothesis Testing of Tumor Microenvironment Scenarios Through Semantic Image Synthesis

AO_SCPLOWBSTRACTC_SCPLOWRecent multiplexed protein imaging technologies characterize cells, their spatial organization, and interactions within microenvironments at an unprecedented resolution. Although observational data can reveal spatial associations, it does not allow users to infer salient biological relationships and cellular interactions. To address this challenge, we develop a generative model that allows users to test hypotheses about the effect of cell-cell interactions on protein expression through in silico perturbation. Our Cell-Cell Interaction GAN (CCIGAN) model employs a generative adversarial network (GAN) architecture to generate high fidelity synthetic multiplexed images from semantic cell segmentations. Our approach is unique in that it learns relationships between all imaging channels simultaneously and yields biological insights from multiple imaging technologies in silico, capturing known tumor-immune cell interactions missed by other state-of-the-art GAN models.

cancer biology↗