# Bresesti_Cell_Reports_2025

**Reprogramming liver metastasis-associated macrophages towards an anti-tumoral phenotype through enforced miR-342 expression**

Bresesti C, Monti M, Beretta S, Merelli I, Squadrito M, _et al._; 2025

Corresponding Author: Mario Leonardo Squadrito. Email: squadrito.mario@hsr.it.  [![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/wouter_decoster.svg?style=social&label=Follow%20%40Mariosqua)](https://x.com/Mariosqua)

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)  


## 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
- 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)
    - 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)


## 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).