YY1 enhances HIF-1α stability in tumor-associated macrophages to suppress anti-tumor immunity of prostate cancer
Data files
Jun 06, 2025 version files 234.78 MB
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NC_DcTACs.tar.gz
120.27 MB
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NCm2pep_TENm2pep_genes.reads.count.csv
4.04 MB
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OE-YY1_THP1_RNA_seq_FPKM.csv
1.11 MB
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README.md
8.30 KB
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YY1_DcTACs.tar.gz
109.16 MB
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YY1_IP_MS.csv
192.74 KB
Abstract
Prostate cancer, as an immune-cold tumor, shows poor response to immune checkpoint inhibitors, but the underlying mechanisms are not fully understood. Through YY1 proteomics experiments and RNA sequencing of THP-1 cells overexpressing YY1, combined with other biomolecular experiments, we demonstrated that hypoxia promotes the phosphorylation of YY1, thereby enhancing its binding to NUSAP1 and stabilizing HIF-1α, which in turn regulates the tumor microenvironment. Through bioinformatics techniques and in vitro protein IP experiments, we clarified that in tumor-associated macrophages, Tenapanor can competitively bind to the site to block the interaction between YY1 and NUSAP1, thereby affecting the stability of HIF-1α. To verify the therapeutic effects and mechanisms of Tenapanor on prostate cancer, we used the prostate cancer cell line RM1 to induce subcutaneous tumors in C57BL/6 mice. One week after tumor implantation, we administered TEN-M2pep or NC-M2pep (Tenapanor or control solvent linked to TAM-targeting peptide M2pep) via tail vein injection to the experimental group (n=3) and control group mice (n=3). After 24 days, we harvested the subcutaneous tumors, ground them, and digested them into single-cell suspensions. We then performed bulk RNA sequencing on the CD45-selected cells. Additionally, to degrade YY1, we constructed YY1-targeted tetrahedral DNA-caged PROTACs (YY1-DcTACs) and performed single-cell sequencing on subcutaneous tumors from mice injected with YY1-DcTACs and NC-DcTACs via tail vein injection. The combination of both sequencing results, along with further studies using immunohistochemistry and flow cytometry, demonstrated that inhibiting the YY1-NUSAP1 interaction or targeting the degradation of YY1 can promote T cell proliferation and activation, as well as the enrichment of immune response-related pathways in subcutaneous tumors, and enhance the infiltration of CD8+ T cells. These research findings demonstrate that targeting macrophage YY1 is a potential therapeutic strategy for treating prostate cancer and promoting tumor immunity.
Dataset DOI: 10.5061/dryad.rr4xgxdkn
Description of the data and file structure
To elucidate the interactions of YY1 in macrophages, we conducted immunoprecipitation experiments in THP-1 cells followed by mass spectrometry analysis to identify proteins that interact with YY1.
Additionally, we performed bulk RNA sequencing on THP-1 cells overexpressing YY1 and those overexpressing a negative control (NC) to identify pathways regulated by YY1 in macrophages.
To investigate the therapeutic effects and mechanisms of Tenapanor on prostate cancer, and to specifically target tumor-associated macrophages (TAMs) in the tumor microenvironment, we utilized a liposome carrier conjugated with the TAM-targeting peptide M2pep (sequence: YEQDPWGVKWWY) to deliver Tenapanor (TEN-M2pep) or a control solvent (NC-M2pep). This delivery system was applied in a subcutaneous prostate cancer tumor mouse model induced by the RM1 cell line in C57BL/6 mice. One week post-tumor implantation, experimental mice (n=3) received TEN-M2pep, while control mice (n=3) received NC-M2pep via tail vein injection. After 24 days, the subcutaneous tumors were harvested, mechanically dissociated, and enzymatically digested into single-cell suspensions. Bulk RNA sequencing was performed on cells selected for CD45 expression.
Furthermore, we developed YY1-targeted tetrahedral DNA-caged PROTACs (YY1-DcTACs) to degrade YY1. In another set of experiments, one week after RM1-induced subcutaneous tumor implantation in C57BL/6 mice, we administered YY1-DcTACs (n=3) or NC-DcTACs (n=3) via tail vein injection, with two injections per week for three consecutive weeks. Three weeks later, the tumors were harvested and processed into cell suspensions. CD45+ cells were magnetically labeled and isolated using CD45 MicroBeads, then mixed with CD45- cells at a 6:4 ratio. Single-cell sequencing was performed on each group to analyze the cellular and molecular changes.
Files and variables
File: YY1_IP_MS.xlsx
Description: We conducted immunoprecipitation experiments in the THP-1 cells, followed by mass spectrometry analysis to identify proteins that interact with YY1. The results include the names and related descriptive information of the proteins, as well as the number of detected peptides and the percentage of peptide coverage, among other mass spectrometry data.
Variables
- Accession: This refers to the unique identifier assigned to a protein sequence in the FASTA database, which is a primary database of nucleotide sequences and their protein translations.
- Gene Name: This is the name of the gene associated with the protein. It is displayed based on the annotation in the Fasta header; if the database lacks complete annotation or gene names, this field may be left blank.
- Description: This provides a description of the protein's function based on the information available in the protein sequence database.
- Coverage [%]: This indicates the percentage of the protein sequence that has been covered by identified peptides.
- # Peptides: This denotes the number of distinct peptide sequences identified within the protein group, representing the total count of peptide sequences detected.
- # PSMs (Peptide Spectrum Matches): This is the total number of peptide sequences that have been matched to the entire spectrum of the mass spectrometry data, including those identified more than once.
- # Unique Peptides: This represents the number of unique peptide sequences identified within a protein group.
- # AAs (Amino Acids): This is the total count of amino acids in the protein, reflecting the length of the protein sequence.
- MW [kDa] (Molecular Weight): This is the theoretical molecular weight of the protein, calculated based on the amino acid sequence. If the protein sequence is incomplete, such as a translated sequence from a cDNA library, the calculated molecular weight may be smaller than the actual molecular weight of the full-length protein.
- calc. pI (Calculated Isoelectric Point): This is the theoretical isoelectric point of the protein, which is the pH at which the protein carries no net electrical charge. It is calculated based on the amino acid composition of the protein.
File: NCm2pep_TENm2pep_genes.reads.count.xlsx
Description: To verify the therapeutic effects and mechanisms of Tenapanor on prostate cancer and to target tumor-associated macrophages (TAMs) in the tumor microenvironment, we loaded Tenapanor or the control solvent onto a liposome carrier using the TAM-targeting peptide (M2pep, with the peptide sequence YEQDPWGVKWWY) (namely TEN-M2pep or NC-M2pep) and used it for the treatment of subsequent subcutaneous prostate cancer tumor mice. Subcutaneous tumors were induced in C57BL/6 mice using the prostate cancer cell line RM1. One week after tumor implantation, TEN-M2pep or NC-M2pep was administered via tail vein injection to the experimental group (n=3) and control group mice (n=3). After 24 days, the subcutaneous tumors were harvested, ground, and digested into single-cell suspensions. Bulk RNA sequencing was performed on the CD45-selected cells. The results include general information such as the names of the measured genes, as well as the corresponding counts matrix information.
Variables
- Geneid: A unique identifier for the gene.
- GeneName: The common name or symbol for the gene.
- Chr: The chromosome on which the gene is located.
- Start: The starting position of the gene on the chromosome
- End: The ending position of the gene on the chromosome.
- Strand: The strand of the DNA on which the gene is located. This can be either the positive strand ( + ) or the negative strand ( - ).
- Length: The length of the gene, typically measured in base pairs (bp).
- NC_m2pep_1: The expression counts of the gene in samples #1 treated with the negative control (NC) M2pep
- NC_m2pep_2: The expression counts of the gene in samples #2 treated with the negative control (NC) M2pep
- NC_m2pep_3: The expression counts of the gene in samples #3 treated with the negative control (NC) M2pep
- TEN_m2pep_1: The expression counts of the gene in samples #1 treated with TEN-M2pep.
- TEN_m2pep_2: The expression counts of the gene in samples #2 treated with TEN-M2pep.
- TEN_m2pep_3: The expression counts of the gene in samples #3 treated with TEN-M2pep.
File: OE-YY1_THP1_RNA_seq_FPKM.xlsx
Description: We performed bulk RNA sequencing on THP-1 cells overexpressing YY1 and those overexpressing a negative control (NC) to identify pathways regulated by YY1 in macrophages. The results include Gene Information and the corresponding FPKM (Fragments Per Kilobase of exon model per Million mapped fragments) values for two groups.
Variables
- Track_id: The database name in gene level.
- Gene_Name: The name of gene.
- Locus: The genomic coordinate of gene.
- Strand: The strand of gene.
- Gene_Type: The biological type of gene.
- OE-YY1: Fragments per kilobase of transcript per million fragments mapped (FPKM) of indicated genes in the THP-1 cells overexpressing YY1.
- NC-YY1: Fragments per kilobase of transcript per million fragments mapped (FPKM) of indicated genes in the negative control (NC) THP-1 cells.
File: YY1_DcTACs.tar.gz
Description: matrix file from the single RNA sequencing of YY1-DcTACs treated mice subcuteneous tumor. 10X Genomics-typed matrix files, which are generated from SpaceRanger pipeline: matrix.mtx.gz, features.tsv.gz, and barcodes.tsv.gz.
File: NC_DcTACs.tar.gz
Description: matrix file from the single RNA sequencing of NC-DcTACs treated mice subcuteneous tumor. 10X Genomics-typed matrix files, which are generated from SpaceRanger pipeline: matrix.mtx.gz, features.tsv.gz, and barcodes.tsv.gz.
Code/software
Seurat pipeline based on R software. The single-cell RNA sequencing matrix (each for three files including “barcodes.tsv.gz”, “features.tsv.gz”, “matrix.mtx.gz”) should be read with “Read10X()”, and the spatial transcriptomic data (each for a “filtered_feature_bc_matrix.h5” file) should be read with “Read10X_h5()”.