Cell Reports Medicine · 2024 · 64 citations · 100 references
MedicineCancer BiologyOncologyCancer ImmunologyTumor ImmunologyTumor MicroenvironmentCancer ImmunotherapyCancer TranscriptomicsCheckpoint Inhibitor TherapyImmune Checkpoint InhibitorsImmune HeterogeneitySingle-cell TranscriptomicsBreast Cancer Tumor MicroenvironmentCell Heterogeneity AnalysisCheckpoint Inhibitor Response PredictionImmune Microenvironment HeterogeneityIntratumoral Immune HeterogeneitySingle-cell Gene Expression ProfilingSingle-cell Rna SequencingSingle-cell Tumor Analysis
We present an integrated single-cell RNA sequencing atlas of the primary breast tumor microenvironment (TME) containing 236,363 cells from 119 biopsy samples across eight datasets. In this study, we leverage this resource for multiple analyses of immune and cancer epithelial cell heterogeneity. We define natural killer (NK) cell heterogeneity through six subsets in the breast TME. Because NK cell heterogeneity correlates with epithelial cell heterogeneity, we characterize epithelial cells at the level of single-gene expression, molecular subtype, and 10 categories reflecting intratumoral transcriptional heterogeneity. We develop InteractPrint, which considers how cancer epithelial cell heterogeneity influences cancer-immune interactions. We use T cell InteractPrint to predict response to immune checkpoint inhibition (ICI) in two breast cancer clinical trials testing neoadjuvant anti-PD-1 therapy. T cell InteractPrint was predictive of response in both trials versus PD-L1 (AUC = 0.82, 0.83 vs. 0.50, 0.72). This resource enables additional high-resolution investigations of the breast TME.
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HTSeq—a Python framework to work with high-throughput sequencing data
Simon Anders, Paul Theodor Pyl, Wolfgang Huber · Bioinformatics · 2014 · 22.7K citations · Full text
Rebecca L. Siegel, Kimberly D. Miller, Hannah E. Fuchs et al. · CA A Cancer Journal for Clinicians · 2022 · 18.2K citations · Full text