DOI: 10.5061/dryad.rr4xgxdkn
title: YY1 enhances HIF-1α stability in tumor-associated macrophages to suppress anti-tumor immunity of prostate cancer

description: 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.
description: # YY1 enhances HIF-1α stability in tumor-associated macrophages to
 suppress anti-tumor immunity of prostate cancer Dataset DOI:
 [10.5061/dryad.rr4xgxdkn](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()”.