A Single-Cell Atlas of the Multicellular Ecosystem of Primary and Metastatic Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) represents a paradigm of the relation between tumor microenvironment and tumor development. Here, we generated > 70,000 single-cell transcriptomes for 10 HCC patients from four relevant sites: primary tumor, portal vein tumor thrombus (PVTT), metastatic lymph node and non-tumor liver. We discovered a cluster of antitumor central memory T cells enriched in intratumoral tertiary lymphoid structures (TLSs) of HCC. We found chronic HBV/HCV infection increases the infiltration of CD8+ T cells in tumors but aggravates the exhaustion of tumor-infiltrating lymphocytes. We identified MMP9+ macrophages to be terminally differentiated tumor-associated macrophages (TAMs) and two distinct differentiation trajectories are related to their accumulation. We further demonstrated MMP9+ TAMs can promote HCC cells migration, invasion and angiogenesis. Our data also revealed the heterogeneous population of malignant hepatocytes and found they might play multifaceted roles in shaping the immune microenvironment of HCC. Finally, we identified seven TME subtypes of HCC that can predict patient prognosis. Collectively, this large-scale, single-cell atlas deepens our understanding of the ecosystem in primary and metastatic HCCs, might facilitating identification of new immune therapy strategies for this malignancy. Single-cell suspensions were converted to barcoded scRNA-seq libraries by using the Chromium Single Cell 3’ Library, Gel Bead & Multiplex Kit and Chip Kit (10x Genomics), aiming for an estimated 5,000 cells per library and following the manufacturer’s instructions. Samples were processed using kits pertaining to V2 barcoding chemistry of 10x Genomics. Single samples are always processed in a single well of a PCR plate, allowing all cells from a sample to be treated with the same master mix and in the same reaction vessel. For each patient, all samples (NTL, PT, PVTT and MLN) were processed in parallel in the same thermal cycler. The generated scRNA-seq libraries were sequenced on an Illumina NovaSeq sequencer. The Cell Ranger software (version 2.2.0) was used to perform sample demultiplexing, barcode processing and single-cell 3’ counting. Cell Ranger’s mkfastq function was used to demultiplex raw base call files from the sequencer, into sample-specific fastq files. Afterward, fastq files for each sample were processed with Cell Ranger’s count function, which was used to align reads to human genome (build hg38) and quantify gene expression levels in single cells. Raw data access provided at: European Genome-phenome Archive (EGA) under accession EGAS00001004468.