Abstract 129: An integrated multi-omic cellular atlas of human breast cancers

Breast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of the cellular composition and organization of breast cancer remains limited. We present a comprehensive single cell and spatially resolved transcriptomic atlas of human breast cancers.

The 10X Genomics Chromium platform was used to generate single cell transcriptomic data (scRNA-Seq) from more than 120,000 cells sampled from 26 breast cancers. CITE-Seq was employed to simultaneously generate protein measurements using a panel of 157 antibodies against immune, stromal and epithelial cell surface markers and analysed using Seurat. Using single cell signatures, we estimated the cellular composition of more than 2000 breast cancers in the Metabric cohort using deconvolution methods. Spatial transcriptomics was conducted on 12 frozen tissues (Luminal, Her2+ and triple negative breast cancer (TNBC)) using the 10X genomics Visium solution. We also used a novel Spatial Whole Transcriptome Panel, targeting 18,000+ genes on the Nanostring GeoMX platform, to profile T cells and malignant cells across multiple tissue niches from 16 TNBC FFPE cases.

Integrative scRNA-Seq analysis identifies recurrent gene modules driving neoplastic cell heterogeneity, including interferon signaling, estrogen receptor function and mutually exclusive patterns of proliferation versus EMT. We also develop a single cell classifier of intrinsic subtype (scSubtype) to reveal frequent intra-tumoral heterogeneity for breast cancer intrinsic subtypes.

CITE-Seq revealed immune profiles at high resolution, leading to the identification of novel macrophage populations with high expression of PD-L1 and PD-L2 immune checkpoint ligands and associations with clinical outcome. We also observe enrichment of exhausted and proliferative CD8 T cells in TNBC, with unique patterns of cell-surface checkpoint protein expression when compared to other subtypes. Targeted analysis using the GeoMX revealed spatial segregation of T cell phenotypes, with exhausted and proliferative CD8 T cells forming small clusters adjacent to tumor cells with high interferon pathway activity.

Analysis of scRNA-Seq data revealed that stromal cells generate diverse functions and cell surface protein expression through differentiation within 3 major lineages: fibroblast, endothelial and perivascular-like. Subsets of stromal cells had features associated with immune regulation and Visium data revealed that stromal-immune niches were spatially organized in tumors, offering insights into anti-tumor immune suppression by stromal cells.

Finally, deconvolution stratified >2000 breast cancer cases in Metabric into nine clusters, termed ‘ecotypes', with distinct cellular compositions and clinical outcomes. This study provides a comprehensive atlas of the cellular architecture of breast cancer.

Citation Format: Sunny Z. Wu, Daniel Roden, Ghamdan Al Eryani, Simon Junankar, Elgene Lim, Aatish Thennavan, Alma Andersson, Stephen Williams, Jingjing Gong, Robin Fropf, Kit Fuhrman, Joakim Lundeberg, Chuck Perou, Alexander Swarbrick. An integrated multi-omic cellular atlas of human breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 129.

Using single cell genomics to change the treatment of lung cancer

e20563

Background: Lung cancer (LC) is common with a dismal prognosis. Although treatment with immunotherapy (IO) has improved survival outcomes, these therapies remain expensive. Even using biomarker selection, response rates still fall short of 50%. The majority of immune cell profiling done previously uses samples taken from early stage patients focusing on a single immune cell subtype. Here we use single cell RNA sequencing (scRNA-seq) and Cellular Indexing of Transcriptome and Epitopes by sequencing (CITE-seq) to characterise the innate and adaptive immune cell activation state and assess the response to exposure to IO in vitro from patients with advanced LC. Methods: Patients with locally advanced or metastatic LC having an Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) have biopsies collected for analysis. Cells are grown in culture +/- nivolumab for 48 hours. scRNA-seq and CITE-seq is conducted using established protocols. Transcriptomic and proteomic data on the innate and adaptive immune cell subsets assess markers of immune activation and/or suppression and the changes after nivolumab are quantified. Results are correlated with clinical outcomes. Results: In a locally advanced/metastatic population, EBUS-TBNA biopsies yield highly cellular samples with a heterogeneous population of immune cells able to be cultured +/- IO using novel, inclusive techniques. Transcriptomic clustering reveals distinct sub-populations within the T-cell, B-cell and innate immune cell compartments. Within these clusters, CITE-seq shows protein expression on individual cells can determine states of exhaustion, cytolytic ability, migratory potential and innate immune activation. Conclusions: Single cell genomics is feasible and informative in patients with advanced LC. This work will form the basis of a functional, real-time assay to assess individualised responses to IO therapy that has the potential to predict IO response.