Characterizing the cancer-associated microbiome with small RNA sequencing data

Area of Science:

• Microbiome research
• Cancer biology
• Bioinformatics

Background:

• The human microbiome acts as a quasi-organ, and its dysbiosis is linked to inflammation and neoplastic growth.
• Limited evidence exists on the specific interactions between the microbiome and tumorigenesis.
• Understanding the cancer-associated microbiome is crucial for developing novel therapeutic strategies.

Purpose of the Study:

• To develop and validate a novel analytical approach for characterizing the cancer-associated microbiome.
• To identify microbial genera and their functions associated with colorectal cancer stages.
• To explore the potential of this method for analyzing microbiomes in other cancer types.

Main Methods:

• Utilized microRNA sequencing data from The Cancer Genome Atlas (TCGA) for colon and rectal cancer patients.
• Developed a novel bioinformatics pipeline to extract and align non-human small RNA sequences to the microbial genome.
• Analyzed >1000 microbial genera across 630 colorectal samples to define enterotypes and identify cancer-stage-associated genera.

Main Results:

• Successfully clustered 630 colorectal samples into three distinct enterotypes.
• Identified 12 microbial genera significantly associated with different colorectal cancer stages.
• Revealed the putative functions of these identified cancer-associated microbial genera.

Conclusions:

• The proposed analytical approach effectively characterizes the cancer-associated microbiome in colorectal cancer.
• This method offers a robust tool for microbiome analysis, particularly when direct specimen collection is challenging.
• Findings provide insights into the role of specific microbial communities in colorectal cancer progression.