Skip to main content
Premium Trial:

Request an Annual Quote

Metastatic Melanoma Study Highlights Genetics of Checkpoint Blockade Response

NEW YORK (GenomeWeb) – New research by a University of Texas MD Anderson Cancer Center-led team has untangled some of the factors that influence checkpoint inhibitor treatment response in metastatic melanoma.

As they reported in Science Translational Medicine today, the researchers used a combination of exome sequencing, gene expression profiling, and targeted T cell receptor sequencing on biopsy samples collected over time from 56 individuals with metastatic melanoma. These patients were first treated with drugs targeting the immune checkpoint player CTLA-4 before being treated with an anti-PD-1 immune checkpoint blockade after progression.

While T cell receptor clonality appeared to contribute to anti-PD-1 response, the team reported, tumor features such as mutational load and copy number profiles seemed to influence responses to both PD-1 and CTLA1-4-focused treatments.

"What emerges from this and other works regarding immune checkpoint responder/non-responder identification is a complex picture likely involving the interplay of tumor genomic characteristics, tumor modulation of the local microenvironment, and the extent of immune surveillance in the tumor milieu at the time of initiation of therapy," MD Anderson researchers Andrew Futreal and Jennifer Wargo, the study's co-corresponding authors, and their colleagues wrote. 

Following from prior studies searching for clues to immune checkpoint blockade response, the researchers did a genomic analysis of longitudinal samples collected from 56 individuals with metastatic melanoma who were treated at MD Anderson between the fall of 2011 and the spring of 2015. In each case, patients were treated with an anti-CTLA-4 approach, followed by an anti-PD-1 treatment, which was used after progression or lack of response with the CTLA-4 blockade.

Using Illumina HiSeq 2000 or 2500 instruments, the team sequenced protein-coding portions of the genome captured from matched tumor and normal samples with Agilent SureSelect targeted enrichment kits. Along with mutations identified in the tumor samples using the exome sequence data, the researchers applied software called Sequenza to detect copy number alterations in the tumors, did targeted T-cell receptor sequencing experiments with the Illumina MiSeq, and used NanoString kits to track expression patterns for nearly 800 genes.

When they considered mutational patterns, copy number profiles, expression, and T-cell receptor patterns alongside individuals' responses to the anti-CTLA-4 and anti-PD-1 treatments, the researchers could not pin checkpoint inhibitor response on recurrent copy number changes to specific genes, though they did see beta2-microtubulin gene loss in four individuals who failed to respond to anti-CTLA-4 treatment.

Likewise, individuals who did not respond to the CTLA-4 inhibitor were more apt to have high levels of copy number losses, particularly involving tumor suppressor genes.

In general, the team did not see clear ties between the load of mutations affecting melanoma driver genes and checkpoint blockade response, though a higher overall mutational load, coupled with low copy number losses, did seem to have better survival and clinical benefit from the CTLA-4 or PD-1 checkpoint blockade treatments.

"[T]he effects of low copy number loss burden and high mutational load on clinical response are non-redundant," the authors wrote, "suggesting the possibility of a combinatorial biomarker using copy number loss and mutational load."

Meanwhile, despite seeing similarities in responder and non-responder T-cell receptor clonality before treatment, the team noted that some anti-CTLA-4 treatment responders showed increasing post-treatment T-cell receptor clonality — a pattern that seemed to coincide with subsequent anti-PD-1 treatment response.