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Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers.

ABSTRACT: BACKGROUND:Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology. METHODS:We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks. RESULTS:We demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC. CONCLUSIONS:Integrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

SUBMITTER: Hale VL

PROVIDER: S-EPMC6208080 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers.

Hale Vanessa L VL Jeraldo Patricio P Chen Jun J Mundy Michael M Yao Janet J Priya Sambhawa S Keeney Gary G Lyke Kelly K Ridlon Jason J White Bryan A BA French Amy J AJ Thibodeau Stephen N SN Diener Christian C Resendis-Antonio Osbaldo O Gransee Jaime J Dutta Tumpa T Petterson Xuan-Mai XM Sung Jaeyun J Blekhman Ran R Boardman Lisa L Larson David D Nelson Heidi H Chia Nicholas N

Genome medicine 20181031 1

<h4>Background</h4>Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology.<h4>Methods</h4>We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for ...[more]

PMID: 30376889

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Project description:The aim of this study was to investigate immune response and its prognostic significance in colon carcinomas using the previously described Immunoscore (IS). A population-based series of 779 colorectal cancers, operated on between 2000 and 2010, were classified according to tumour, node, metastasis (TNM) status, mismatch repair (MMR), and BRAF mutation status. Rectal cancer cases (n = 203) were excluded as a high proportion of these patients received preoperative neoadjuvant chemoradiotherapy. Tissue microarray (TMA) samples collected from the tumour centre and invasive front were immunostained for CD3 and CD8. Lymphocytes were then digitally calculated to categorize IS from grade 0 to 4. Samples adequate for IS were available from 510 tumours. IS was significantly associated with AJCC/UICC stage, T stage, lymph node and distant metastases, perineural and lymphovascular invasion, MMR status, and BRAF mutation status. For IS0, IS1, IS2, IS3 and IS4, respectively, the 5-year disease-free survival (DFS) rates were 59, 68, 78, 83 and 94% (p < 0.001); 5-year disease-specific survival (DSS) rates were 47, 55, 75, 80, and 89% (p < 0.001); and 5-year overall survival (OS) rates were 40, 44, 66, 61, and 76% (p < 0.001). IS was also prognostic for DFS, DSS, and OS within subsets of microsatellite-stable (MSS) and microsatellite-instable (MSI) disease. Multivariable analysis showed that IS, AJCC/UICC stage, lymphovascular invasion, and lymph node ratio in AJCC/UICC stage III disease were independent prognostic factors for DFS, DSS, and OS. Age was an independent prognostic factor for DSS and OS. Gender and BRAF mutation were independent prognostic factors for OS. In conclusion, IS differentiated patients with poor versus improved prognosis in MSS and MSI disease and across AJCC/UICC stages. IS, AJCC/UICC stage, lymphovascular invasion, and lymph node ratio in AJCC/UICC stage III disease were independent prognostic factors for DFS, DSS, and OS.

Project description:Colorectal cancers (CRCs) with deficient DNA mismatch repair (dMMR) and proficient DNA mismatch repair (pMMR) exhibit heterogeneous tumor characteristics, distinct responses to immunotherapy, and different survival outcomes. However, it is unclear whether gut microbiota is distinct between CRCs with different MMR status. In this study, we used immunohistochemistry for four major MMR proteins to determine the MMR status in 230 CRC patients. The gut microbiota was profiled in cancerous and adjacent normal tissues by using bacterial 16S rRNA sequencing. The differences in microbiota diversity, composition and related metabolic pathways between patients with dMMR and pMMR CRCs were explored. Linear discriminant analysis effect size (LEfSe) analysis was further applied to validate the significant taxonomic differences at the genus level. In our study cohort, dMMR status was identified in 29 of 230 (12.61%) tumors. The richness (alpha-diversity) of gut microbiome in dMMR tumor tissue was higher compared with pMMR tumor tissues. The microbial community composition (beta-diversity) between the two groups was significantly different. The dMMR group was enriched considerably for some microbiota, including Fusobacteria, Firmicutes, Verrucomicrobia, and Actinobacteria at the phylum level and Fusobacterium, Akkermansia, Bifidobacterium, Faecalibacterium, Streptococcus, and Prevotella bacteria at the genus level. However, the pMMR group was dominated by Proteobacteria at the phylum level and Serratia, Cupriavidus and Sphingobium at the genus level. Moreover, a wide variety of microbiota associated functional pathways were observed with different MMR status. KEGG pathway analysis indicated a higher abundance of the biosynthesis and metabolic pathways of glycan and nucleotide, cell growth and death pathways, genetic replication and repair pathways in dMMR samples compared with the pMMR group. These findings demonstrate that CRC patients with different MMR status have distinct gut bacterial community richness, compositions and related metabolic pathways, suggesting basis that may explain the effectiveness of immunotherapy in dMMR tumors.

Project description:The development of cancer vaccines to induce tumor-antigen specific immune responses was sparked by the identification of antigens specific to or overexpressed in cancer cells. However, weak immunogenicity and the mutational heterogeneity in many cancers have dampened cancer vaccine successes. With increasing information about mutational landscapes of cancers, mutational neoantigens can be predicted computationally to elicit strong immune responses by CD8 +cytotoxic T cells as major mediators of anticancer immune response. Neoantigens are potentially more robust immunogens and have revived interest in cancer vaccines. Cancers with deficiency in DNA mismatch repair have an exceptionally high mutational burden, including predictable neoantigens. Lynch syndrome is the most common inherited cancer syndrome and is caused by DNA mismatch repair gene mutations. Insertion and deletion mutations in coding microsatellites that occur during DNA replication include tumorigenesis drivers. The induced shift of protein reading frame generates neoantigens that are foreign to the immune system. Mismatch repair-deficient cancers and Lynch syndrome represent a paradigm population for the development of a preventive cancer vaccine, as the mutations induced by mismatch repair deficiency are predictable, resulting in a defined set of frameshift peptide neoantigens. Furthermore, Lynch syndrome mutation carriers constitute an identifiable high-risk population. We discuss the pathogenesis of DNA mismatch repair deficient cancers, in both Lynch syndrome and sporadic microsatellite-unstable cancers. We review evidence for pre-existing immune surveillance, the three mechanisms of immune evasion that occur in cancers and assess the implications of a preventive frameshift peptide neoantigen-based vaccine. We consider both preclinical and clinical experience to date. We discuss the feasibility of a cancer preventive vaccine for Lynch syndrome carriers and review current antigen selection and delivery strategies. Finally, we propose RNA vaccines as having robust potential for immunoprevention of Lynch syndrome cancers.

Project description:Topoisomerase 1 (TOP1) and 2A (TOP2A) are potential predictive biomarkers for irinotecan and anthracycline treatment, respectively, in colorectal cancer (CRC), and we have recently reported a high frequency of gene gain of the TOP1 and TOP2A genes in CRC. Furthermore, Mismatch Repair (MMR) subtypes of CRC have been associated with benefit from adjuvant chemotherapy of primary CRC. Given the involvement of the topoisomerase enzymes in DNA replication and repair, we raised the hypothesis that an association may exist between TOP gene copy numbers and MMR proficiency/deficiency in CRC.Test cohort: FISH analysis with an in-house TOP1/CEN20 probe mix and a commercially available TOP2A/CEN17 (Dako, Glostrup, Denmark) probe mix was performed on archival formalin fixed paraffin embedded (FFPE) tissue samples from 18 patients with proficient MMR (pMMR) CRC and 18 patients with deficient MMR (dMMR) CRC. TOP1 and TOP2A gene copy numbers and their ratios per nucleus were correlated with MMR status using the Mann-Whitney test. Validation cohort: FFPE samples from 154 patients with primary stage III CRC (originally included in the RANX05 study) were classified according to MMR status by immunohistochemical analysis using validated antibodies for MLH1, MLH2, MSH6 and PMS2, and information on TOP1, CEN20, TOP2A and CEN17 status was previously published for this cohort.The observed TOP1 gene copy numbers in the 36 CRC test cohort were significantly greater (p < 0.01) in the pMMR subgroup (mean: 3.84, SD: 2.03) than in the dMMR subgroup (mean: 1.50, SD: 0.12). Similarly, the TOP2A copy numbers were significantly greater (p < 0.01) in the pMMR subgroup (mean: 1.99, SD: 0.52) than in the dMMR subgroup (mean: 1.52, SD: 0.10). These findings were confirmed in the validation cohort, where in the pMMR subgroup 51% had ≥2 extra TOP1 copies per cell, while all tumors classified as dMMR had diploid TOP1 status and mean TOP2A copy numbers were 2.30 (SD: 1.36) and 1.80 (SD: 0.31) (p = 0.01) in the pMMR subgroup vs. dMMR subgroup, respectively.Our results show that TOP1 and TOP2A gene copy numbers are increased in the pMMR subgroup. We propose that this preference may reflect a selective pressure to gain and/or maintain the gained extra copies of topoisomerase genes whose products are required to cope with high replication stress present in the pMMR tumors, thereby providing a survival advantage selectively in pMMR tumors. Future studies should test this concept and explore potential differences between pMMR and dMMR tumors in response to Top1 and Top2 inhibitors.

Dataset Information

Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers.

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Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers.

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