Characterization of the consensus mucosal microbiome of colorectal cancer

Abstract Dysbioisis is an imbalance of an organ's microbiome and plays a role in colorectal cancer pathogenesis. Characterizing the bacteria in the microenvironment of a cancer through genome sequencing has advantages compared to culture-based profiling. However, there are notable technical and analytical challenges in characterizing universal features of tumor microbiomes. Colorectal tumors demonstrate microbiome variation among different studies and across individual patients. To address these issues, we conducted a computational study to determine a consensus microbiome for colorectal cancer, analyzing 924 tumors from eight independent RNA-Seq data sets. A standardized meta-transcriptomic analysis pipeline was established with quality control metrics. Microbiome profiles across different cohorts were compared and recurrently altered microbial shifts specific to colorectal cancer were determined. We identified cancer-specific set of 114 microbial species associated with tumors that were found among all investigated studies. Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were among the four most abundant phyla for the colorectal cancer microbiome. Member species of Clostridia were depleted and Fusobacterium nucleatum was one of the most enriched bacterial species in tumors. Associations between the consensus species and specific immune cell types were noted. Our results are available as a web data resource for other researchers to explore (https://crc-microbiome.stanford.edu).

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Characterization of the consensus mucosal microbiome of colorectal cancer

10.1101/2021.06.02.446807 ◽

2021 ◽

Author(s):

Lan Zhao ◽

Susan M Grimes ◽

Stephanie U Greer ◽

Matthew Kubit ◽

HoJoon Lee ◽

...

Keyword(s):

Colorectal Cancer ◽

Immune Cell ◽

Bacterial Species ◽

Fusobacterium Nucleatum ◽

Cell Types ◽

Data Sets ◽

Data Resource ◽

Bacterial Contaminants ◽

Increased Risk ◽

Tumor Biopsies

Recent evidence suggests that dysbiosis, an imbalance of microbiota, is associated with increased risk of colorectal cancer. Diverse microbial organisms are physically associated with the cells found in tumor biopsies. Characterizing this mucosa-associated microbiome through genome sequencing has advantages compared to culture-based profiling. However, there are notable challenges in accurately characterizing the features of tumor microbiomes with methods like transcriptome sequencing. Most sequence reads originate from the host. Moreover, there is a high likelihood of bacterial contaminants being introduced. Another major challenge is the microbiome diversity among different studies. Colorectal tumors demonstrate a significant extent of microbiome variation among individuals from different geographic and ethnic origins. To address these challenges, we identified a consensus microbiome for colorectal cancer through analyzing 924 tumors from eight independent RNA-Seq data sets. A standardized meta-transcriptomic analysis pipeline was established and applied to the complete CRC cohort. Common contaminants were filtered out. Our study involved taxonomic investigation of non-human sequences, linked microbial signatures to phenotypes and the association of microbiome with tumor microenvironment components. Microbiome profiles across different CRC cohorts were compared, and recurrently altered microbial shifts specific to CRC were determined. We identified cancer-specific set of 114 microbial species associated with tumors that were found among all investigated studies. Validating our approach, we found that Fusobacterium nucleatum was one of the most enriched bacterial species in CRC. Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria were among the four most abundant phyla for CRC microbiome. Signficant associations between the consensus species and specific immune cell types were noted. Our results are available as a web data resource for other researchers to explore (https://crc-microbiome.stanford.edu).

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Identified and Validated the Characterization of the Colorectal Cancer Tumor Immune Microenvironment

10.21203/rs.3.rs-28243/v1 ◽

2020 ◽

Author(s):

Peng Han ◽

yu De Chen ◽

Feng Yang

Keyword(s):

Colorectal Cancer ◽

Immune Cell ◽

Expression Profiles ◽

Cell Types ◽

Small Subset ◽

Data Sets ◽

Immune Microenvironment ◽

Tumor Immune Microenvironment ◽

Cancer Tumor ◽

Microsatellite Stability

Abstract Background While the administration of immunotherapy can facilitate the development of durable anti-tumor immunity in certain colorectal cancer (CRC) patients.This study was therefore designed to conduct a robust analysis of the CRC immune microenvironment to identify specific genes and pathways that can be targeted in an effort to achieve more effective immunotherapy outcomes. Methods Using five Independent data sets, we analyzed expression profiles associated with 29 different immune signatures, and we used these profiles to guide the hierarchical clustering of CRC samples based on their immune microenvironmental composition. Results We were able to cluster our CRC samples based on whether they had exhibited high, medium, or low levels of infiltration by immune cell types associated with tumor clearance (Immunity_H, Immunity_M, and Immunity_L, respectively). Samples in the Immunity_H subset exhibited a “hot” immune microenvironment, with higher stromal scores, higher immune scores, and lower tumor purity. The microsatellite instability (MSI) group included the majority of the Immunity_H samples, whereas most Immunity_M and Immunity_L samples were incorporated into the microsatellite stability (MSS) .The vast majority of patients with KRAS mutations were in the Immunity_L and MSS groups, whereas the majority of patients exhibiting BRAF V600E mutations were found in the Immunity_H and MSI-H samples. TMB high samples included a majority of the Immunity_H samples and a small subset of the Immunity_M samples. Conclusions Our results identify three reproducibly validated immune subtypes of CRC tumor samples, potentially offering valuable insights that may guide the immunotherapeutic treatment of these patients.

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Pharmacologically targeting tribbles gene expression in colorectal cancer

European Journal of Public Health ◽

10.1093/eurpub/ckab120.088 ◽

2021 ◽

Vol 31 (Supplement_2) ◽

Author(s):

Victor Yassuda ◽

Ana Luísa De Sousa-Coelho

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Cell Types ◽

Disease Recurrence ◽

Rosemary Extract ◽

Acid Oxidation ◽

Data Sets ◽

Compensatory Mechanism ◽

Dependent Manner ◽

Pharmacological Potential

Abstract Background TRIB1, TRIB2 and TRIB3 belong to the mammalian Tribbles family of pseudokinases proteins. Several studies reported Tribbles oncogenic role in different types of cancer, including colorectal cancer (CRC). Though current CRC treatment can be curative, patients are in risk of disease recurrence, meaning novel pharmacological targets and strategies are required. Our goal was to analyze Tribbles gene expression in CRC in response to different drugs. Methods Tribbles transcript levels were obtained from GEO profiles database (NCBI). Gene data sets (GDS) were selected based on experimental drug treatment description. Statistical analysis was performed at GraphPadPrism. Results Compared to non-treated control, TRIB2 expression was ∼2-fold increased in colorectal adenocarcinoma samples from patients treated with cyclooxygenase-2 inhibitor celecoxib (GDS3384), though not statistically significant (P < 0.1). TRIB1 was unaltered and data for TRIB3 was not available. By contrast, all Tribbles showed differential expression after treatment of SW620 colon cancer cells with supercritical rosemary extract in progressive increasing doses (0, 30, 60, 100 μg/mL) (P < 0.01;GDS5416). While both TRIB1 and TRIB3 were moderately increased in a dose-dependent manner (∼18% and 13%, respectively), TRIB2 was maximally down-regulated by ∼15% after 60 μg/mL. Conclusions Although celecoxib exhibits antiproliferative effects in different cancer cell types, TRIB2 gene expression showed a trend to be induced after treatment, in contrast to several genes involved in fatty acid oxidation that were down-regulated, which could result from a compensatory mechanism based on a metabolic shift. Since TRIB1/TRIB3 and TRIB2 were oppositely modulated in response to rosemary extract, additional studies are needed to validate its specific pharmacological potential interest for CRC treatment.

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MIXTURE: an improved algorithm for immune tumor microenvironment estimation based on gene expression data

10.1101/726562 ◽

2019 ◽

Cited By ~ 3

Author(s):

Elmer A. Fernández ◽

Yamil D. Mahmoud ◽

Florencia Veigas ◽

Darío Rocha ◽

Mónica Balzarini ◽

...

Keyword(s):

Tumor Microenvironment ◽

Immune Cell ◽

Therapy Response ◽

Cell Types ◽

Gene Signature ◽

Response To Therapy ◽

Support Vector ◽

Data Sets ◽

Cell Type ◽

Before And After

AbstractRNA sequencing has proved to be an efficient high-throughput technique to robustly characterize the presence and quantity of RNA in tumor biopsies at a given time. Importantly, it can be used to computationally estimate the composition of the tumor immune infiltrate and to infer the immunological phenotypes of those cells. Given the significant impact of anti-cancer immunotherapies and the role of the associated immune tumor microenvironment (ITME) on its prognosis and therapy response, the estimation of the immune cell-type content in the tumor is crucial for designing effective strategies to understand and treat cancer. Current digital estimation of the ITME cell mixture content can be performed using different analytical tools. However, current methods tend to over-estimate the number of cell-types present in the sample, thus under-estimating true proportions, biasing the results. We developed MIXTURE, a noise-constrained recursive feature selection for support vector regression that overcomes such limitations. MIXTURE deconvolutes cell-type proportions of bulk tumor samples for both RNA microarray or RNA-Seq platforms from a leukocyte validated gene signature. We evaluated MIXTURE over simulated and benchmark data sets. It overcomes competitive methods in terms of accuracy on the true number of present cell-types and proportions estimates with increased robustness to estimation bias. It also shows superior robustness to collinearity problems. Finally, we investigated the human immune microenvironment of breast cancer, head and neck squamous cell carcinoma, and melanoma biopsies before and after anti-PD-1 immunotherapy treatment revealing associations to response to therapy which have not seen by previous methods.

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Stratification of chemotherapy-treated stage III colorectal cancer patients using multiplexed imaging and single-cell analysis of T-cell populations

Modern Pathology ◽

10.1038/s41379-021-00953-0 ◽

2021 ◽

Author(s):

Xanthi Stachtea ◽

Maurice B. Loughrey ◽

Manuela Salvucci ◽

Andreas U. Lindner ◽

Sanghee Cho ◽

...

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

Single Cell ◽

Immune Cell ◽

Single Cell Analysis ◽

Cell Types ◽

Cell Segmentation ◽

Stage Iii ◽

Cell Analysis ◽

Increased Risk

AbstractColorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits <20% of patients, while more than 50% will develop distant metastases. Biomarkers for identification of patients at increased risk of disease recurrence following adjuvant chemotherapy are currently lacking. In this study, we assessed immune signatures in the tumor and tumor microenvironment (TME) using an in situ multiplexed immunofluorescence imaging and single-cell analysis technology (Cell DIVETM) and evaluated their correlations with patient outcomes. Tissue microarrays (TMAs) with up to three 1 mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin (FOLFOX) chemotherapy. Single sections underwent multiplexed immunofluorescence staining for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and tumor/cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase, and S6). We used annotations and a probabilistic classification algorithm to build statistical models of immune cell types. Images were also qualitatively assessed independently by a Pathologist as ‘high’, ‘moderate’ or ‘low’, for stromal and total immune cell content. Excellent agreement was found between manual assessment and total automated scores (p < 0.0001). Moreover, compared to single markers, a multi-marker classification of regulatory T cells (Tregs: CD3+/CD4+FOXP3+/PD1−) was significantly associated with disease-free survival (DFS) and overall survival (OS) (p = 0.049 and 0.032) of FOLFOX-treated patients. Our results also showed that PD1− Tregs rather than PD1+ Tregs were associated with improved survival. These findings were supported by results from an independent FOLFOX-treated cohort of 191 stage III CRC patients, where higher PD1− Tregs were associated with an increase overall survival (p = 0.015) for CD3+/CD4+/FOXP3+/PD1−. Overall, compared to single markers, multi-marker classification provided more accurate quantitation of immune cell types with stronger correlations with outcomes.

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Comprehensive analysis of ceRNA networks reveals prognostic lncRNAs related to immune infiltration in colorectal cancer

BMC Cancer ◽

10.1186/s12885-021-07995-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jingyi Chen ◽

Yuxuan Song ◽

Mei Li ◽

Yu Zhang ◽

Tingru Lin ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Target Genes ◽

Immune Cell ◽

Pearson Correlation ◽

Enrichment Analysis ◽

Cell Types ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cerna Network

Abstract Background Competing endogenous RNA (ceRNA) represents a class of RNAs (e.g., long noncoding RNAs [lncRNAs]) with microRNA (miRNA) binding sites, which can competitively bind miRNA and inhibit its regulation of target genes. Increasing evidence has underscored the involvement of dysregulated ceRNA networks in the occurrence and progression of colorectal cancer (CRC). The purpose of this study was to construct a ceRNA network related to the prognosis of CRC and further explore the potential mechanisms that affect this prognosis. Methods RNA-Seq and miRNA-Seq data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs), and a prognosis-related ceRNA network was constructed based on DElncRNA survival analysis. Subsequently, pathway enrichment, Pearson correlation, and Gene Set Enrichment Analysis (GSEA) were performed to determine the function of the genes in the ceRNA network. Gene Expression Profiling Interactive Analysis (GEPIA) and immunohistochemistry (IHC) were also used to validate differential gene expression. Finally, the correlation between lncRNA and immune cell infiltration in the tumor microenvironment was evaluated based on the CIBERSORT algorithm. Results A prognostic ceRNA network was constructed with eleven key survival-related DElncRNAs (MIR4435-2HG, NKILA, AFAP1-AS1, ELFN1-AS1, AC005520.2, AC245884.8, AL354836.1, AL355987.4, AL591845.1, LINC02038, and AC104823.1), 54 DEmiRNAs, and 308 DEmRNAs. The MIR4435-2HG- and ELFN1-AS1-associated ceRNA subnetworks affected and regulated the expression of the COL5A2, LOX, OSBPL3, PLAU, VCAN, SRM, and E2F1 target genes and were found to be related to prognosis and tumor-infiltrating immune cell types. Conclusions MIR4435-2HG and ELFN1-AS1 are associated with prognosis and tumor-infiltrating immune cell types and could represent potential prognostic biomarkers or therapeutic targets in colorectal carcinoma.

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Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms22115763 ◽

2021 ◽

Vol 22 (11) ◽

pp. 5763

Author(s):

Vartika Bisht ◽

Katrina Nash ◽

Yuanwei Xu ◽

Prasoon Agarwal ◽

Sofie Bosch ◽

...

Keyword(s):

Colorectal Cancer ◽

Single Cell ◽

Rna Sequencing ◽

Therapeutic Targets ◽

Data Sets ◽

Cancer Pathogenesis ◽

Oxidative Phosphorylation Pathway ◽

Transcriptomics Data ◽

Pathway Regulation ◽

Potential Interactions

Integrative multiomics data analysis provides a unique opportunity for the mechanistic understanding of colorectal cancer (CRC) in addition to the identification of potential novel therapeutic targets. In this study, we used public omics data sets to investigate potential associations between microbiome, metabolome, bulk transcriptomics and single cell RNA sequencing datasets. We identified multiple potential interactions, for example 5-aminovalerate interacting with Adlercreutzia; cholesteryl ester interacting with bacterial genera Staphylococcus, Blautia and Roseburia. Using public single cell and bulk RNA sequencing, we identified 17 overlapping genes involved in epithelial cell pathways, with particular significance of the oxidative phosphorylation pathway and the ACAT1 gene that indirectly regulates the esterification of cholesterol. These findings demonstrate that the integration of multiomics data sets from diverse populations can help us in untangling the colorectal cancer pathogenesis as well as postulate the disease pathology mechanisms and therapeutic targets.

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Analysis ofFusobacteriumpersistence and antibiotic response in colorectal cancer

Science ◽

10.1126/science.aal5240 ◽

2017 ◽

Vol 358 (6369) ◽

pp. 1443-1448 ◽

Cited By ~ 326

Author(s):

Susan Bullman ◽

Chandra S. Pedamallu ◽

Ewa Sicinska ◽

Thomas E. Clancy ◽

Xiaoyang Zhang ◽

...

Keyword(s):

Colorectal Cancer ◽

Bacterial Species ◽

Complex Mixture ◽

Fusobacterium Nucleatum ◽

Colorectal Cancers ◽

Metastatic Lesions ◽

Antimicrobial Interventions ◽

Antibiotic Response ◽

Cancer Tissues

Colorectal cancers comprise a complex mixture of malignant cells, nontransformed cells, and microorganisms.Fusobacterium nucleatumis among the most prevalent bacterial species in colorectal cancer tissues. Here we show that colonization of human colorectal cancers withFusobacteriumand its associated microbiome—includingBacteroides,Selenomonas, andPrevotellaspecies—is maintained in distal metastases, demonstrating microbiome stability between paired primary and metastatic tumors. In situ hybridization analysis revealed thatFusobacteriumis predominantly associated with cancer cells in the metastatic lesions. Mouse xenografts of human primary colorectal adenocarcinomas were found to retain viableFusobacteriumand its associated microbiome through successive passages. Treatment of mice bearing a colon cancer xenograft with the antibiotic metronidazole reducedFusobacteriumload, cancer cell proliferation, and overall tumor growth. These observations argue for further investigation of antimicrobial interventions as a potential treatment for patients withFusobacterium-associated colorectal cancer.

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Invasion by Fusobacterium nucleatum Causes Upregulation of dll4 and klf4 Expression in Caco2 Cells

10.1101/2020.10.26.354910 ◽

2020 ◽

Author(s):

Kyla Cochrane ◽

Avery V. Robinson ◽

Jacqueline Powers ◽

Scott D. Brown ◽

Robert A. Holt ◽

...

Keyword(s):

Colorectal Cancer ◽

Transcriptional Profiling ◽

Bacterial Species ◽

Disease Patient ◽

Fusobacterium Nucleatum ◽

Non Invasive ◽

Human Genes ◽

Klf4 Expression ◽

Host Genes

AbstractFusobacterium nucleatum is an emerging microbe of importance in the pathogenesis of colorectal cancer. Strains of this enigmatic bacterial species vary in their capacity to invade human epithelial cells, a virulence determinant which has important implications in disease. Here, we infected human colorectal epithelial (Caco-2) cells in vitro with a known, highly invasive strain of F. nucleatum isolated from a Crohn’s Disease patient, as well as a further invasive isolate of F. nucleatum derived from a colorectal cancer tumour. We used transcriptional profiling to determine the human genes upregulated during the invasion process compared to exposure to a non-invasive E.coli control strain. Infection with F. nucleatum strains resulted in the upregulation of several host genes, including two associated with tumorigenesis: dll4 and klf4.

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Fusobacterium nucleatum in biopsied tissues from colorectal cancer patients and alcohol consumption in Korea

Scientific Reports ◽

10.1038/s41598-020-76467-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Myungsook Kim ◽

Seung-Tae Lee ◽

Songyi Choi ◽

Hyukmin Lee ◽

Sun Sung Kwon ◽

...

Keyword(s):

Colorectal Cancer ◽

Alcohol Consumption ◽

16S Rrna ◽

Bacterial Species ◽

Fusobacterium Nucleatum ◽

Integrated Analysis ◽

Cancer Tissue ◽

16S Rrna Analysis ◽

Associated Bacteria ◽

Epidemiological Characteristics

AbstractThe roles of individual bacteria and their relationship in the development of colorectal cancer (CRC) remain unclear. We aimed to determine the prevalence of CRC-associated bacteria using quantitative real-time PCR (qPCR) or 16S rRNA analysis and the statistical correlations of patient demographics and clinical characteristics comprising alcohol consumption with CRC-associated bacteria. We determined the prevalence of five CRC-associated bacterial species in 38 CRC patients (39 samples) and 21 normal individuals using qPCR, and the relative abundance of bacterial taxa in the gut microbiome was assessed using 16S rRNA analysis. Fusobacterium nucleatum was the only bacterium that was significantly (P < 0.0001) more prevalent in the cancer tissue (82.1%) than in the normal tissue (0%) by qPCR. 16S rRNA analysis showed a significant correlation between six operational taxonomic units (OTUs), namely, the genera Fusobacterium, Peptostreptococcus, Collinsella, Prevotella, Parvimonas, and Gemella, in patients with CRC. An integrated analysis using 16S rRNA data and epidemiological characteristics showed that alcohol consumption was significantly correlated with the abundance of Fusobacterium OTUs. The correlation of alcohol consumption with the abundance of Fusobacterium OTUs in cancer tissue discovered using 16S rRNA analysis suggests a possible link between alcohol metabolism and subsequent tumorigenesis caused by F. nucleatum.

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