Spatially Exploring RNA Biology in Archival Formalin-Fixed Paraffin-Embedded Tissues.

Spatial transcriptomics has emerged as a powerful tool for dissecting spatial cellular heterogeneity but as of today is largely limited to gene expression analysis. Yet, the life of RNA molecules is multifaceted and dynamic, requiring spatial profiling of different RNA species throughout the life cycle to delve into the intricate RNA biology in complex tissues. Human disease-relevant tissues are commonly preserved as formalin-fixed and paraffin-embedded (FFPE) blocks, representing an important resource for human tissue specimens. The capability to spatially explore RNA biology in FFPE tissues holds transformative potential for human biology research and clinical histopathology. Here, we present Patho-DBiT combining in situ polyadenylation and deterministic barcoding for spatial full coverage transcriptome sequencing, tailored for probing the diverse landscape of RNA species even in clinically archived FFPE samples. It permits spatial co-profiling of gene expression and RNA processing, unveiling region-specific splicing isoforms, and high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for five years. Furthermore, genome-wide single nucleotide RNA variants can be captured to distinguish different malignant clones from non-malignant cells in human lymphomas. Patho-DBiT also maps microRNA-mRNA regulatory networks and RNA splicing dynamics, decoding their roles in spatial tumorigenesis trajectory. High resolution Patho-DBiT at the cellular level reveals a spatial neighborhood and traces the spatiotemporal kinetics driving tumor progression. Patho-DBiT stands poised as a valuable platform to unravel rich RNA biology in FFPE tissues to study human tissue biology and aid in clinical pathology evaluation.

Single-Cell Transcriptomics Revealed Subtype-Specific Tumor Immune Microenvironments in Human Glioblastomas.

Human glioblastoma (GBM), the most aggressive brain tumor, comprises six major subtypes of malignant cells, giving rise to both inter-patient and intra-tumor heterogeneity. The interaction between different tumor subtypes and non-malignant cells to collectively shape a tumor microenvironment has not been systematically characterized. Herein, we sampled the cellular milieu of surgically resected primary tumors from 7 GBM patients using single-cell transcriptome sequencing. A lineage relationship analysis revealed that a neural-progenitor-2-like (NPC2-like) state with high metabolic activity was associated with the tumor cells of origin. Mesenchymal-1-like (MES1-like) and mesenchymal-2-like (MES2-like) tumor cells correlated strongly with immune infiltration and chronic hypoxia niche responses. We identified four subsets of tumor-associated macrophages/microglia (TAMs), among which TAM-1 co-opted both acute and chronic hypoxia-response signatures, implicated in tumor angiogenesis, invasion, and poor prognosis. MES-like GBM cells expressed the highest number of M2-promoting ligands compared to other cellular states while all six states were associated with TAM M2-type polarization and immunosuppression via a set of 10 ligand-receptor signaling pathways. Our results provide new insights into the differential roles of GBM cell subtypes in the tumor immune microenvironment that may be deployed for patient stratification and personalized treatment.

Single-cell Analysis Technologies for Immuno-oncology Research: from Mechanistic Delineation to Biomarker Discovery.

The successes with immune checkpoint blockade (ICB) and chimeric antigen receptor (CAR)-T-cell therapy in treating multiple cancer types have established immunotherapy as a powerful curative option for patients with advanced cancers. Unfortunately, many patients do not derive benefit or long-term responses, highlighting a pressing need to perform complete investigation of the underlying mechanisms and the immunotherapy-induced tumor regression or rejection. In recent years, a large number of single-cell technologies have leveraged advances in characterizing immune system, profiling tumor microenvironment, and identifying cellular heterogeneity, which establish the foundations for lifting the veil on the comprehensive crosstalk between cancer and immune system during immunotherapies. In this review, we introduce the applications of the most widely used single-cell technologies in furthering our understanding of immunotherapies in terms of underlying mechanisms and their association with therapeutic outcomes. We also discuss how single-cell analyses help to deliver new insights into biomarker discovery to predict patient response rate, monitor acquired resistance, and support prophylactic strategy development for toxicity management. Finally, we provide an overview of applying cutting-edge single-cell spatial-omics to point out the heterogeneity of tumor-immune interactions at higher level that can ultimately guide to the rational design of next-generation immunotherapies.

High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue.

We present deterministic barcoding in tissue for spatial omics sequencing (DBiT-seq) for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via next-generation sequencing (NGS). Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide, and crossflow of two sets of barcodes, A1-50 and B1-50, followed by ligation in situ, yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10-µm pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology.