<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY accession="ERP127208" alias="ena-STUDY-APC Microbiome Institute-23-02-2021-11:44:37:700-1175" center_name="APC Microbiome Institute">
    <IDENTIFIERS>
      <PRIMARY_ID>ERP127208</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject">PRJEB43259</EXTERNAL_ID>
      <SUBMITTER_ID namespace="APC Microbiome Institute">ena-STUDY-APC Microbiome Institute-23-02-2021-11:44:37:700-1175</SUBMITTER_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>The study investigates the effect of different microbial consortia in tumor progression in a mice model. This contains the 16S datasets for the mouse study undertaken in this study.</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>Patients with colorectal cancer (CRC) harbor gut microbiomes that differ in structure and function from those of healthy individuals, suggesting this altered microbiome could contribute to carcinogenesis. Despite the increasing evidence implicating the gut microbiome in CRC, the collective role of different microbial consortia in CRC carcinogenesis is unclear. We have previously described these consortia as co-abundance groups that co-exist at different abundance levels in the same patient. Here, we report that tumor biopsy tissue from patients with a “high-risk” Pathogen-type microbiome had a different immune transcriptome from those with a “low-risk” Lachnospiraceae-type microbiome. Transplantation from patients of the two fecal microbiome types into mice with an orthotopic tumor differentially affected tumor growth and the systemic anti-tumor immune response. The differences in tumor volume and immunophenotype between mice receiving the high-risk and the low-risk microbiome correlated with differences in the engrafted human microbial species and predicted microbiome-encoded metabolites in the two groups. Of twelve taxa whose abundance in recipient mice correlated positively with tumor volume, seven corresponded with differentially abundant taxa in a global dataset of 325 CRC patients versus 310 healthy controls. These data suggest that the configuration of the gut microbiome may influence colon cancer progression and disease outcome by modulating the anti-tumor immune response.</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>Fiber-associated Lachnospiraceae reduce colon tumorigenesis by modulation of the tumor-immune microenvironment</CENTER_PROJECT_NAME>
      <STUDY_DESCRIPTION>Patients with colorectal cancer (CRC) harbor gut microbiomes that differ in structure and function from those of healthy individuals, suggesting this altered microbiome could contribute to carcinogenesis. Despite the increasing evidence implicating the gut microbiome in CRC, the collective role of different microbial consortia in CRC carcinogenesis is unclear. We have previously described these consortia as co-abundance groups that co-exist at different abundance levels in the same patient. Here, we report that tumor biopsy tissue from patients with a “high-risk” Pathogen-type microbiome had a different immune transcriptome from those with a “low-risk” Lachnospiraceae-type microbiome. Transplantation from patients of the two fecal microbiome types into mice with an orthotopic tumor differentially affected tumor growth and the systemic anti-tumor immune response. The differences in tumor volume and immunophenotype between mice receiving the high-risk and the low-risk microbiome correlated with differences in the engrafted human microbial species and predicted microbiome-encoded metabolites in the two groups. Of twelve taxa whose abundance in recipient mice correlated positively with tumor volume, seven corresponded with differentially abundant taxa in a global dataset of 325 CRC patients versus 310 healthy controls. These data suggest that the configuration of the gut microbiome may influence colon cancer progression and disease outcome by modulating the anti-tumor immune response.</STUDY_DESCRIPTION>
    </DESCRIPTOR>
    <STUDY_ATTRIBUTES>
      <STUDY_ATTRIBUTE>
        <TAG>ENA-FIRST-PUBLIC</TAG>
        <VALUE>2021-10-23</VALUE>
      </STUDY_ATTRIBUTE>
      <STUDY_ATTRIBUTE>
        <TAG>ENA-LAST-UPDATE</TAG>
        <VALUE>2021-10-23</VALUE>
      </STUDY_ATTRIBUTE>
    </STUDY_ATTRIBUTES>
  </STUDY>
</STUDY_SET>
