by Li Yuan, Chinese Academy of Sciences

The cellular and molecular profiles of different histologic patterns in MPLC-LUAD. a Pathological classification of malignant regions into histologic patterns including lepidic type (PR1), acinar type (PR2), micropapillary type (PR3), minimally invasive (PRm) and adenocarcinoma in situ (PRa). b The main cell type compositions of the pathological regions across the four investigated samples. c Boxplot of the proportions of different epithelial cell sub-populations in the pathological regions across all the investigated samples. t test, unpaired. AT2 and CLDN2⁺ AT2 are, respectively, compared to the other sub-populations. d Violin plot of the spatially resolved high expression of PDZK1IP1 in the region PR1. e KM-plot of the survival curves of patients in GSE30219. The patients were separated into two groups based on the expression of PDZK1IP1. f Bar plot of the mean fold change of PR3 marker genes shared by the three observed samples. g, h KM-plot of the survival curves of TCGA-LUAD patients. The patients were separated into two groups according to whether the expression of RANBP1 (g) and MDH2 (h) was higher than the median level. i. Spatial neighbors (the nearest three circles of spots) of the malignant regions. Colors represent different malignant regions. Sample TM_R_P3 is displayed as one example. j Box plot of the difference of cell compositions between the malignant regions and corresponding spatial neighbors. t test, unpaired. Credit: Cell Death & Disease (2023). DOI: 10.1038/s41419-023-05992-w

A research group led by Prof. Piao Hailong from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) and their collaborators have characterized the cellular composition and spatial architecture of tumor microenvironment in human multiple primary lung cancers (MPLCs) by integrating single cell RNA-seq and spatial transcriptomics. The study was published in Cell Death & Disease on July 25.

MPLCs refer to several primary tumors growing synchronously in the lung. With the widespread use of high-resolution computed tomography, MPLCs are being diagnosed more frequently. However, it is still difficult to distinguish MPLC and intrapulmonary metastasis (IPM) in clinic, especially in cases of similar histologies.

In this study, the researchers conducted an integrative analysis of both single-cell transcriptome and spatial transcriptome data based on bioinformatics and machine learning methods.

They identified a previously undescribed sub-population of epithelial cells termed as CLDN2⁺ alveolar type II (AT2), specifically enriched in MPLCs. Possessing a relatively stationary state, this subtype played an important role in cellular communication, aggregating spatially in tumor tissues and dominating the malignant histopathological patterns.

The researchers verified that the CLDN2 protein expression could help distinguish MPLCs from intrapulmonary metastasis and solitary lung cancer.

In addition, they found a cell surface receptor TNFRSF18/GITR highly expressed in T cells of MPLCs, which suggested that TNFRSF18 was one potential immunotherapeutic target in MPLCs.

More information: Yawei Wang et al, Multidirectional characterization of cellular composition and spatial architecture in human multiple primary lung cancers, Cell Death & Disease (2023). DOI: 10.1038/s41419-023-05992-w

Provided by Chinese Academy of Sciences