Spatial maps of hepatocellular carcinoma transcriptomes reveal spatial expression patterns in tumor immune microenvironment

Abstract

Rationale: Hepatocellular carcinoma (HCC) is a highly heterogeneous and malignant disease with the complex immune microenvironment, which ultimately influence clinic outcomes of patients. However, the spatial expression patterns of diverse immune cells among tumor microenvironment remain to be further deciphered. Methods: Spatial transcriptomics sequencing (ST) was implemented on two portions of HCC specimens. Differentially expressed genes, cell cycle phases, epithelial-mesenchymal features, pseudo-time and immune infiltration analysis were applied to demonstrate the intratumor heterogeneity and define the specific immune-related regions, and the results were further validated by a second analysis on another ST study. In vitro and in vivo experiments were conducted to confirm the functional mechanisms of key molecules such as CCL15, CCL19 and CCL21. Clinical tissue samples were used to assess their potential prognostic and therapeutic values. Results: Totally, 7553 spots were categorized into 15 subsets by hierarchical clustering, and malignant subsets with intratumor heterogeneity phenotypes were identified. Spatial heterogeneity from distinct sectors highlights specific chemokines: CCL15 is remarkable in the core region of the carcinoma sector and facilitates the immunosuppressive microenvironment by recruiting and polarizing M2-like macrophages in vitro and in vivo ; High expression of CCL15 and CD163 respectively predicts poor prognosis of HCC patients, and the combined application of them has better predictive value. CCL19 and CCL21, sharing similar spatial expression patterns, are highly-correlated and prominent in the immune infiltration enrichment and recruit CD3 + T cells and CD20 + B cells to inhibit the growth of HCC, indicating a good prognosis of HCC patients. Conclusions: Taken together, our studies preliminarily reveal intratumor heterogeneity of HCC based on ST techniques and unravel the previously unexplored spatial expression patterns in the immune microenvironment. We also highlight the clinical significance and spatial discrepancy of key molecules, providing novel insight for further developing therapeutic strategies in HCC.

Integrating single‐cell RNA sequencing with spatial transcriptomics reveals an immune landscape of human myometrium during labour

“…The Visium Spatial Gene Expression Slide and Reagent Kit (10 × Visium) were used to process the spatial gene expression data. 77 , 78 To prepare the sections for gene expression analysis, they were incubated with permeabilization enzyme for 20 min at 37°C for pre‐permeabilization. After washing the sections with saline sodium citrate, a reverse transcription master mix was added to synthesize cDNA.…”

“…The tissue blocks were cryosectioned at a thickness of 10 μm and attached to the capture areasbefore proceeding to the next step, followed by H&E staining. The Visium Spatial Gene Expression Slide and Reagent Kit (10 × Visium) were used to process the spatial gene expression data 77,78 . To prepare the sections for gene expression analysis, they were incubated with permeabilization enzyme for 20 min at 37°C for pre‐permeabilization.…”

Spatial RNA sequencing methods show high resolution of single cell in cancer metastasis and the formation of tumor microenvironment

“…It was found that M2 macrophages, CAFs, and some T lymphocytes were always located in the center of the tumor, and these T lymphocytes were identified as exhausted CD8+T cells [57] and unconventional CD4+T cells [58]. Exhausted CD8+T cells are often found in cancers, which are a type of T cell lacking effector functions [59], and the unconventional CD4+T cells are a type of T cell subtype similar to regulatory T cells [60], which are related to the immunosuppressive and tissue repair systems [58,61]. These two cell types are very close to the localization of M2 macrophages and CAFs, thus they might be regulated by these tumor-related stromal and myeloid cells, resulting in loss of their anti-tumor functions to help tumor cells escape immune response.…”

Spatial transcriptomics technology in cancer research

“…In ICC, hepatocytes close to invasive fronts with high expression level of SAA1 and SAA2 were correlated with worse prognoses ( 19 ). Moreover, many gene markers were identified in PDAC, liver cancer, BC, bladder cancer, SCC and GC ( 53 , 92 , 112 , 114 , 121 , 126 , 133 ). Cell subpopulations were also potential markers of prognosis.…”