Deciphering the Immune Microenvironment at the Forefront of Tumor Aggressiveness by Constructing a Regulatory Network with Single-Cell and Spatial Transcriptomic Data.

The heterogeneity and intricate cellular architecture of complex cellular ecosystems play a crucial role in the progression and therapeutic response of cancer. Understanding the regulatory relationships of malignant cells at the invasive front of the tumor microenvironment (TME) is important to explore the heterogeneity of the TME and its role in disease progression. In this study, we inferred malignant cells at the invasion front by analyzing single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data of ER-positive (ER+) breast cancer patients. In addition, we developed a software pipeline for constructing intercellular gene regulatory networks (IGRNs), which help to reduce errors generated by single-cell communication analysis and increase the confidence of selected cell communication signals. Based on the constructed IGRN between malignant cells at the invasive front of the TME and the immune cells of ER+ breast cancer patients, we found that a high expression of the transcription factors FOXA1 and EZH2 played a key role in driving tumor progression. Meanwhile, elevated levels of their downstream target genes (ESR1 and CDKN1A) were associated with poor prognosis of breast cancer patients. This study demonstrates a bioinformatics workflow of combining scRNA-seq and ST data; in addition, the study provides the software pipelines for constructing IGRNs automatically (cIGRN). This strategy will help decipher cancer progression by revealing bidirectional signaling between invasive frontline malignant tumor cells and immune cells, and the selected signaling molecules in the regulatory network may serve as biomarkers for mechanism studies or therapeutic targets.

Single-Cell RNA Sequencing Analysis of Gene Regulatory Network Changes in the Development of Lung Adenocarcinoma.

Lung cancer is a highly heterogeneous disease. Cancer cells and other cells within the tumor microenvironment interact to determine disease progression, as well as response to or escape from treatment. Understanding the regulatory relationship between cancer cells and their tumor microenvironment in lung adenocarcinoma is of great significance for exploring the heterogeneity of the tumor microenvironment and its role in the genesis and development of lung adenocarcinoma. This work uses public single-cell transcriptome data (distant normal, nLung; early LUAD, tLung; advanced LUAD, tL/B), to draft a cell map of lung adenocarcinoma from onset to progression, and provide a cell-cell communication view of lung adenocarcinoma in the different disease stages. Based on the analysis of cell populations, it was found that the proportion of macrophages was significantly reduced in the development of lung adenocarcinoma, and patients with lower proportions of macrophages exhibited poor prognosis. We therefore constructed a process to screen an intercellular gene regulatory network that reduces any error generated by single cell communication analysis and increases the credibility of selected cell communication signals. Based on the key regulatory signals in the macrophage-tumor cell regulatory network, we performed a pseudotime analysis of the macrophages and found that signal molecules (TIMP1, VEGFA, SPP1) are highly expressed in immunosuppression-associated macrophages. These molecules were also validated using an independent dataset and were significantly associated with poor prognosis. Our study provides an effective method for screening the key regulatory signals in the tumor microenvironment and the selected signal molecules may serve as a reference to guide the development of diagnostic biomarkers for risk stratification and therapeutic targets for lung adenocarcinoma.