Paper - Review

DOI: 10.1038/s41597-019-0117-3

Abstract

Colorectal cancer
→ heterogenous
→ mostly sporadic disease

To understand (potential relationships)
→ (subtypes of colorectal cancer) & (composition of gut microbial community)
→ 34 tumor samples (→ into molecular subtypes) (← using RNA-sequencing gene expression profiles)

16S rRNA amplicon metabarcoding
→ to identify bacterial community composition

∴ Cancer with environmental impact of microbial community

Background & Summary

CRC
← Colorectal cancer
→ high incidence & mortality
→ most case have NO ❌ (known genetic link)
∴ Environmental factors → play (a critical role) (← in the development of the disease)

❗Importance (← of microbiome in gut)
❓Role (← of the microbiome in CRC) will have profound
∵ Microbiome is potentially relatively easily to manipulate

CRC
→ a highly heterogeneous disease
→ association between (CMS: Consensus Molecular Subtypes) & (Gut microbiome patterns)
→ gene expression profiles (← using RNA sequencing & 16S rRNA meta-barcoding)

Methods

Sample collection & handling

Tumor tissue
← was collected from 34 patients
← for resection of colorectal tumors
→ avoid inter-batch variation → all tumor samples in a single batch by one operator

RNA-seq

(Library preparation) & (Ribosomal RNA depletion)
→ carried out using Illumina TruSeq

Ribosomal RNA depletion step
→ removed a portion of (bacterial ribosomal RNA)
∴ Losing some information (← on bacteria)

RNA sequencing
→ carried out using Illumia HiSeq
→ Each sample library was split equally

Read mapping, Gene expression quantification, and Profile classification

(Adapters) & (Low quality segments)
→ were removed from the sequenced reads (← using fastq-mcf)
→ mapped to hg38 with STAR

Read counts
→ were transformed to (gene expression profiles) in TPM (← Transcripts-per-million)

Assignment of reads to bacterial taxa

Kraken database
← was built with (all NCBI Refseq) & (chromosome-level genomes)

All RNA-seq reads
← were NOT ❌ uniquely mapped to human reference genome

Differential analysis of bacterial species in CMS

The (enrichment & depletion) (← of bacterial species)
→ compared to the other subtypes ← which employing a strategy similar to differential expression analysis

All samples are treated as
→ replicates belonging to the subtype
→ ran differential analysis of each CMS subtype (← against all the other classified samples)

---