Genomic Alterations as Predictors of Immunotherapy Response

The field of immuno-oncology (IO) continues to expand and evolve, delivering unprecedented clinical benefit to patients across a growing number of tumor types. However, IO therapies are not effective in all patients and can be associated with autoimmune side effects, which can be severe. Given this, it is becoming increasingly important for pathologists involved in solid tumor testing to be aware of the growing number of biomarkers with an established or emerging role in the prediction of IO benefit. With the wide clinical adoption and application of large next generation sequencing (NGS) panels, more and more biomarkers based on the detection of genomic alterations are being discovered as predictors of IO therapy response. This article will focus on and discuss how these genomic biomarkers are tested and their value in the era of IO.

Microsatellite Instability (MSI)

Deficient MMR (dMMR) and microsatellite instability-high (MSI-H) were the first tissue agnostic predictive biomarkers approved by the U.S. Food and Drug Administration (FDA) in association with the anti-PD-1 agent, pembrolizumab. The assessment of MSI has been incorporated into most large NGS panels offered by commercial laboratories and academic centers, typically as part of solid tumor comprehensive genomic profiling, which also typically includes single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV).

dMMR or MSI-H has been known to be prevalent in colorectal cancer (CRC) and uterine endometrioid cancer (UEC).⁴ The predictive value of dMMR/MSI-H for IO therapy was demonstrated by clinical trial including not only CRC but also 14 other tumor types.⁵ FDA approved pembrolizumab for first tissue agnostic indication and dMMR and MSI-H as its biomarker for all unresectable or metastatic solid tumors that have progressed following treatment, which made MSI testing an essential in all solid tumors.⁶

Microsatellites are 1- to 6-base pair long short-tandem repeats scattered throughout the human genome. They are prone to replication errors induced by DNA polymerase slippage, which are corrected by the MMR proteins MLH1, PMS2, MSH2, and MSH6. MSI-H tumors result from dMMR and are usually hypermutated with a particularly elevated number of frame-shift indels.

There are three main methodologies to test MSI status: immunohistochemistry (IHC), polymerase chain reaction (PCR), and NGS. IHC evaluates MMR protein expression; PCR based MSI testing works by assessing the number of nucleotide repeats in the tumor in comparison with a normal control, typically blood or nontumor FFPE tissue. Most NGS large panels today incorporate MSI-status evaluation into the panel design. Depending on the panel design and validation, NGS-based MSI may or may not require a normal control.

These three methods are all accepted for MSI status evaluation. Because the result is visualized morphologically rather than being diluted by normal DNA in genomic methods, MMR-IHC works better with low-tumor purity samples than PCR or NGS, which requires a minimal tumor content of 20% to reach optimal evaluation. MMR IHC has a fast turnaround time (TAT) of approximately 1 to 2 days and uses only 4-5 unstained slides, whereas PCR or NGS requires more tissue material.

The sensitivity of MMR IHC and MSI PCR is approximately 94%.⁷ It has been documented that tumors with apparently normal MMR protein expression by IHC occasionally are MSI-H, and this is usually associated with pathogenic missense mutations in MMR genes (as opposed to truncating mutations resulting in loss of protein expression). One common situation leading to false loss of MSH6 expression is the use of neoadjuvant chemotherapy. The sensitivity of NGS usually is higher than 95% and the TAT is 1 to 2 weeks but provides other important data, such as MAPK pathway alterations and TMB.⁷

Tumor Mutation Burden (TMB)

TMB is defined as the total number of nonsynonymous mutations per megabase of tumor genome. It is a continuous, quantitative variable, associated with the tumor neoantigen generation. Although not all mutations generate neoantigens, the total number of mutations in a given tumor correlates with the odds of developing neoantigens and responding to IO therapy.^8,9 Therefore, TMB has emerged as a promising biomarker of response to IO therapies in several prospective trials, including multiple tumor types.

In 2020, the FDA issued second tumor-agnostic approval for pembrolizumab, to treat adults and children with TMB-high (TMB-H) [≥10 mutations/megabase (mut/Mb)] unresectable or metastatic solid tumors, based on the ongoing phase 2 KEYNOTE-158 trial, which showed that the overall response rate was 28.3% for TMB-H and 6.5% for TMB-low tumors.¹⁰

TMB can be tested by targeted panel or whole-exome sequencing.¹¹ The clinical testing of TMB is typically conducted by targeted large NGS panels, which have demonstrated comparable performance to the gold standard, whole exome sequencing. However, the value of TMB varies among different panels and is impacted by assay design (tumor-normal, matched sequencing or tumor only), panel size, genome coverage, and the chosen bioinformatics pipeline to calculate TMB (non-synonymous only or both non-synonymous and synonymous, etc.). Tumor-normal matched sequencing can eliminate rare germline variants and somatic mutations from white blood cells (clonal hematopoiesis), while the value of TMB, based on tumor only sequencing, may be confounded by these alterations.

Other Genomic Alterations Associated with IO Therapies

Besides MSI and TMB, other genomic variant information obtained from large panel testing can also predict cancer immunotherapy responses, including positive predictors such as mutations in POLE (DNA polymerase epsilon) and delta 1 (POLD1); 1 and negative predictors such as mutations in PTEN, JAK1/2, STK11, DNMT3A, EGFR, MDM2, MDM4, and B2M.^2,3

IO therapy responses can be affected by other factors. In general, host response or genomic aberrations affecting specific immune-signaling pathways or leading to immune dysregulation, such as loss-of-function mutations in beta-2 microglobulin (B2M) or loss of human leukocyte antigen (HLA) genes, PTEN loss, or mutations in JAK or other IFNγ-related genes have been associated with resistance to IO therapies.^2,3 In NSCLC, mutations of EGFR and STK11 are also associated with poor response to IO therapy.¹² This is in contrast to POLE and POLD1 mutations, which, as described above, are biomarkers associated with improved response.¹

These additional genetic alterations should be evaluated and considered when selecting patients for IO therapy.

Conclusion

In summary, IO therapy is rapidly becoming a standard treatment option across a broad spectrum of cancer types. In keeping with the precision medicine model, it is critical to select the patients who are most likely to benefit from IO therapies and spare those patients unlikely to respond from experiencing toxicity. This brief article has summarized the major genomic profiling IO predictive biomarkers including MSI, TMB and others, which should be considered as part of a comprehensive testing model.

References

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Jinjuan Yao, MD, PhD, FCAP, is a molecular pathologist from Memorial Sloan Kettering Cancer Center (MSK) with subspecialty training in molecular pathology and hematopathology. Dr. Yao also serves as the Quality Assurance Chair of Diagnostic Molecular Pathology at MSK.

Dr. Yao is a lifetime member of Chinese American Pathologists Association (CAPA) and the chair for CAPA molecular pathology subcommittee. She is also a CAP New York House of Delegates and CAP Personalized Health Care Committee (PHC) member.

Dr. Yao’s clinical work has focused on the large-scale, prospective genotyping of solid tumors and hematologic malignancies using a variety of NGS technologies. Her research interests include the pathogenesis of leukemias and lymphomas, genetic alterations, and therapies of solid tumors.