Chapter 7: Tumor Mutational Burden (TMB) & Microsatellite Instability (MSI)
Chapter 7: Tumor Mutational Burden (TMB) & Microsatellite Instability (MSI)
Beyond individual single-gene mutations, global genome-wide biomarkers predict patient response to immune checkpoint inhibitors (e.g. anti-PD-1 / anti-PD-L1 pembrolizumab, nivolumab). Tumor Mutational Burden (TMB) and Microsatellite Instability (MSI) reflect high neoantigen production, rendering tumors visible to the host immune system.
Tumors with thousands of somatic mutations express numerous mutant peptide fragments (neoantigens) presented on cell-surface HLA molecules. Cytotoxic CD8+ T-cells recognize these foreign neoantigens, driving tumor regression when checkpoint suppression is relieved.
1. Tumor Mutational Burden (TMB) Quantification
TMB measures the number of somatic non-synonymous mutations per megabase (mut/Mb) of sequenced genomic territory:
\text{TMB} = \frac{\text{Count of Somatic Non-Synonymous Coding Variants}}{\text{Size of Sequenced Coding Territory (in Mb)}}
An FDA-approved tumor-agnostic threshold of TMB \(\ge 10 \text{ mut/Mb}\) qualifies patients with unresectable solid tumors for pembrolizumab therapy.
2. Microsatellite Instability Calling with MSIsensor-pro
Defects in DNA mismatch repair machinery (MLH1, MSH2, MSH6, PMS2) cause replication slippage at homopolymeric short tandem repeats (microsatellites). MSIsensor-pro evaluates somatic length distributions across thousands of microsatellite loci without requiring a matched normal control.
# 1. Scan reference genome for microsatellite tracts
msisensor-pro scan -d ref_genome.fasta -o microsatellites.list
# 2. Score tumor BAM file for MSI percentage
msisensor-pro pro -d microsatellites.list -t tumor.bam -o msi_output.txt
# Interpretation:
# % Somatic Unstable Sites >= 20%: MSI-High (MSI-H / dMMR) -> Strong Immunotherapy Candidate
# % Somatic Unstable Sites < 20%: Microsatellite Stable (MSS)