# Bresesti_Cell_Reports_2025 **Reprogramming liver metastasis-associated macrophages towards an anti-tumoral phenotype through enforced miR-342 expression** [Chiara Bresesti](https://orcid.org/0000-0002-1840-9774), [Marco Monti](https://orcid.org/0000-0003-1266-4325), [Stefano Beretta](https://orcid.org/0000-0003-4375-004X), [Ivan Merelli](https://orcid.org/0000-0003-3587-3680), [Mario Leonardo Squadrito](https://orcid.org/0000-0002-1188-0299), *et al.*; Cell Reports, 2025 Corresponding Author: Mario Leonardo Squadrito. Email: [squadrito.mario\@hsr.it](mailto:squadrito.mario@hsr.it){.email}. [![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/wouter_decoster.svg?style=social&label=Follow%20%40Mariosqua)](https://x.com/Mariosqua) Raw data are on GEO: [GSE274043](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274043) (single-cell RNA-seq)\ [GSE274044](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274044) (RNA-seq on iKCs)\ [GSE274045](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274045) (small RNA-seq on splenic and hepatic cell populations)\ [GSE274046](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE274046) (bulk RNA-seq on splenic and hepatic cell populations) Other input data are on Open Research Data Repository (ORDR): [DOI: 10.17632/4gpbv5vpcr.1](https://data.mendeley.com/datasets/4gpbv5vpcr/1) ## Directories and Files - environment_singlecell5.yml: contains the conda virtual environment that can be used to install all the dependencies. - scripts: folder with R scripts used for the analyses - CB2025_figure_1_RNAseq.R - CB2025_figure_3_RNAseq.R - CB2025_figure_5_scRNAseq.R - TCGA_analysis.R - Output: results of the analyses - CB_Annotation.final.CB_Fig.5A.csv: snRNAseq source data to reproduce UMAP in figure 5A - Input: input files required to generate the figures - miRNA_QIAseq_1509_QIAseqUltraplexRNA_181342.xlsx: UMI and gene count data from RNA-seq (Figure 1B) - miRNA_QIAseq_1509_181342_edgeR_results.xlsx: Summary data for miRNA and piRNA (Figure 1C.dx & 1D) - miRNA_QIAseq_1510_173308.all_samples.summary.xlsx: Differential expression analysis results (Figure 1C.sx) - miRNA_Family.xlsx: miRNA family information (Figure 1D) - miDB_sig5.MLS.rds: reference files for GSEA analysis (Figure 3 & 5) - RNAseq_90-857433247_edgeR_results.xlsx: Differential gene expression analysis for miR-342 vs. control and spongeBT vs. control (Figure 3A & 3B & 3C & 3D) - TargetScan8.0_miR-342-3p.predicted_targets.xlsx: Predicted target genes for miR-342-3p from TargetScan (Figure 3A & 3B) - CB1_CB3_CB4_final.rds: Seurat object containing scRNA-seq data (Figure 5 & S5) (present on ORDR) - TCGA_phenotype.tsv.gz: TCGA patient phenotype data (metadata) with clinical and demographic information (TCGA Analysis) - Survival_SupplementalTable_S1_20171025_xena_sp: TCGA patient survival data, providing overall survival (OS) status and time (TCGA Analysis) - pancanMiRs_EBadjOnProtocolPlatformWithoutRepsWithUnCorrectMiRs_08_04_16.xena.gz: TCGA pancancer miRNA expression data (FPKM values) across different tumor samples (TCGA Analysis) (present on ORDR) ## scRNAseq analysis The initial preprocessing of the data, including mapping against the *Mus musculus* GRCm38 reference genome and gene counting, was done using the 10x Genomics Cell Ranger Software (v7.2.0) using default parameters. The resulting data were imported into R and analyzed with the Seurat package (v5.0.1).