Exploring the role of microbial communities in cancer treatment studies

NGS-based research continues to explore host-microbiome interactions with the hope of influencing cancer progression and treatment efficacy

Cancer Microbiome Research

Microbes living in the host can influence cancer progression and treatment efficacy. Diet and drugs can disrupt microbiome diversity, and key species in the microbiome can cause local or systemic influences on host immunity.1,2

There is hope that future treatments may combine existing cancer therapies with methods to encourage growth of beneficial microbes or eliminate harmful ones. As NGS-based research continues to explore host-microbiome interactions, Illumina strives to evolve genomic technologies that complement and enable the promise of this field.

Cancer Immunotherapy and the Role of the Microbiome

Effectiveness of modern cancer immunotherapies is influenced by the composition of the gut microbiome.

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NGS methods have revolutionized the study of the microbiome.3 Without the need to culture or clone individual organisms, NGS enables simultaneous analysis of thousands of species within a microbial community. With the development of bioinformatic tools to manage large volumes of new information, this shift from single organism analysis enables accurate assessment of species diversity and measurement of dynamic fluctuations in microbial communities.

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The Microbiome Emerges as a Key Player in Cancer

An overview of how the microbiome influences cancer and immunotherapy, and the role NGS plays to help advance research in this expanding field.

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NGS is Revealing the Mysteries of the Microbiome

Researchers at Microba are investigating the genomes of microbes to improve our understanding of human health, disease, and microbial evolution.

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NGS is Revealing the Mysterious World of Microbes

10x Multiomics Tech Note (ATAC-Seq + RNA) This single-cell multiomics protocol enables simultaneous profiling of gene expression and chromatin accessibility from single cells to help reveal cellular mechanisms driving gene regulation, including gene expression differences in healthy and disease states. This technical note outlines a protocol for simultaneous profiling of the transcriptome (using 3' gene expression) and epigenome (using ATAC-Seq; assay for transposase-accessible chromatin with sequencing) from single cells. [ Read Technical Note ] BioLegend BEN-Seq App Note (RNA & protein) In this paper, we demonstrate how to incorporate protein detection into bulk RNA-Seq and develop a workflow for BEN-Seq. The ability to measure protein expression via sequencing at a single-cell level unifies flow cytometry and RNA-Seq, providing a holistic approach to cell analysis. [ Read App Note ]

With high throughput and high sensitivity, NGS enables the identification of thousands of microbial species in a single sample.

Click on the below to view products for each workflow step.

TruSeq Stranded Total RNA Library Prep Kit

Streamlined, cost-efficient, and scalable solution for total RNA analysis.

Nextera XT Library Prep Kit

Prepare sequencing ready libraries of bacteria, viruses, and other microbes to analyze transcriptome and metatranscriptome information.

TruSeq DNA PCR-Free Library Preparation Kits

Simple, all-inclusive library preparation for whole-genome sequencing applications. Researchers can sequence a wide variety of organisms, from small genomes such as bacteria to whole-human genomes.

Desktop Sequencing Systems
MiSeq System

Speed, accuracy and simplicity for far reaching applications in microbiology.

NextSeq Series

Flexible desktop sequencer for transcriptome and whole-genome sequencing.

High-Throughput Sequencing Systems

Power for high-throughput microbial transcriptomics and flexibility to scale based on your project or workflow needs.

HiSeq 4000 System

High throughput and low cost for production-scale genomics.

16S Metagenomics

Performs taxonomic classification of 16S rRNA targeted amplicon reads using an Illumina-curated version of the GreenGenes taxonomic database.


The Metagenomic Phylogenetic Analysis (MetaPhlAn) tool profiles microbial community composition from metagenomic shotgun sequencing data.

QIIME Preprocessing and QIIME Visualizations

Quantitative Insights into Microbial Ecology (QIIME) is designed to take users from raw sequencing data to publication quality graphics and statistics.

Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy.

Science 350 1084-9 2015

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Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota.

Science 350 1079-84 2015

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Microbiome and Anticancer Immunosurveillance.

Cell 165 276-87 2016

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16S rRNA Sequencing

16S ribosomal RNA (rRNA) sequencing targets a genetic marker found in all bacteria. 16S rRNA sequencing is a well established method for studying phylogeny and taxonomy of samples from complex microbiomes.

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Shotgun Metagenomic Sequencing

Shotgun metagenomic sequencing assesses all genomic content in a microbial sample for species identification and functional analysis. High sequence coverage enables detection of low abundance members of the microbiome.

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Metatranscriptome Analysis

Metatranscriptome analysis applies RNA sequencing (RNA-Seq) to microbial samples to determine which species are there, what they are expressing, and how they respond to changes in the environment.

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The MiSeq System, 16S rRNA Sequencing, and the American Gut Project
The MiSeq System, 16S rRNA Sequencing, and the American Gut Project
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Overview: NGS for Microbiology
Overview: NGS for Microbiology

View an introduction to NGS and its applications for microbiology.

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16S rRNA Sequencing Webinar
16S rRNA Sequencing Webinar
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  1. Zama D, Biagi E, Masetti R, et al. Gut microbiota and hematopoietic stem cell transplantation: where do we stand? Bone Marrow Transplant. 2017;52 (1):7-14.
  2. Schwabe R, Jobin C. The microbiome and cancer. Nat Rev Cancer. 2013;13 (11):800-812.
  3. Franzosa EA, Hsu T, Sirota-Madi A, et al. Sequencing and beyond: integrating molecular 'omics' for microbial community profiling. Nat Rev Microbiol. 2015;13(6):360-372.