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Tumor Aneuploidy Analysis Suggests New Avenue for Predicting Immunotherapy Response


NEW YORK (GenomeWeb) – As excitement around cancer immunotherapy has grown, so has the development of diagnostics that can predict which patients will respond and which may not.

To date, diagnostic strategies advancing to the clinic have focused on specific biomarkers associated with immune checkpoint targets, or more recently, on the number of mutations and associated neoantigens produced by a tumor. Results of a new study published in Science last week suggest another molecular feature could be a predictive signal for sensitivity to immunotherapeutic cancer drugs — tumor aneuploidy, or chromosomal copy number.

In the study, investigators from Harvard Medical School, Brigham and Women's Hospital, and the Dana-Farber Cancer Institute, probed data from 5,255 tumor and normal samples making up 12 cancer types, which were analyzed as part of The Cancer Genome Atlas. Specifically, they looked  at different patterns of somatic copy number alterations (SCNA), which affected whole chromosomes, large sections of chromosome arms, or just focal regions.

The group then assigned each tumor an overall SCNA-level score, defined as the sum of scores for chromosome SCNA level, arm SCNA level, and focal SCNA level.

In contrast with previous research that found that SCNAs were more abundant in tumors with a low mutation burden, the Harvard team found the opposite, except in two cancer types: colorectal carcinoma and uterine corpus endometrial carcinoma.The team also found that increased incidence of structural changes appears to adversely affect the body's immune response against cancer, as well as influence cell proliferation.

More specifically, the researchers developed a scoring method and found that high levels of aneuploidy were linked not only to expression signatures that are associated with cancer development and spread, but also signatures that indicate reduced numbers of T cells and greater numbers of immune-suppressing M2 macrophages.

When the researchers looked at different types of aneuploidy separately — focal, arm, and chromosome SCNA — they found that arm and chromosome SCNAs were a stronger predictor of the immune-related gene expression signature, while focal SCNAs were more strongly associated with cell cycle and proliferation-associated expression.

Finally, the team compared its SCNA scoring approach with tumor neoantigen burden in data from previous trials of anti–CTLA-4 immunotherapy in metastatic melanoma, showing that mutation burden and low SCNA levels both distinguished the patients who had the best outcomes.

Interestingly, the authors wrote, SCNA level appeared to predict patients’ survival independently

of mutation burden, suggesting that combining the SCNA level with the number of mutations could result in improved patient selection.

In a commentary accompanying the Science study, Maurizio Zanetti, director of the laboratory of immunology at the University of California San Diego  Moores Cancer Center, wrote that the results suggest that assessing tumor SCNA level, "alone or in combination with neoantigen burden may help select patients that can benefit from immune checkpoint blockade treatment."

Moreover, he said, "because immune checkpoint blockade works in certain tumor types only, and tumor types vary with respect to the number of somatic mutations, assessing the level of aneuploidy [could] be more generally informative for predicting the status of local tumor immunity, which may be relevant to other forms of immunotherapy as well."

Stephen Elledge, a professor of genetics at Harvard Medical School and the study's senior author, said in an interview that he and his colleagues didn't have in mind that aneuploidy could predict immune cell infiltration and immunotherapy response when they set out to study if and how aneuploidy drives cancer evolution.

The group wanted to look at transcriptomes to see if there was anything they could pick out that was associated with either more aneuploidy or less aneuploidy in tumors.

"We found two things. First, with more aneuploidy, you have more cell cycle gene expression, so cells that are mitotic. Second, there are a lot fewer immune cells, so the immune cells can't seem to get into the tumor.

"People had found before that with more point mutations, you see more infiltration, but it’s a relatively weak correlation, and only works for some tumor types. We found that aneuploidy is a much stronger [predictor]," he added.

In terms of diagnostic development, the race is definitely on to develop methods to pick out patients who are likely to respond to new and emerging immunotherapy drugs.

Despite the dramatic responses seen in some patients, and the resulting enthusiasm for this area of therapy, not all cancers, and not all individuals with the same type of cancer, respond equally.

A number of PD-L1 protein assays have been developed alongside particular therapies, and the field has now turned its attention to trying to compare and harmonize these different tests so they can be used across the field of existing and emerging drugs.

More recently, evidence has grown that tumors with high numbers of nonsynonymous mutations, and therefore high levels of neoantigen epitopes that the immune system might target, are more likely to respond to immunotherapy.

While determining tumor mutation burden (TMB) has initially required broad genome sequencing, Foundation Medicine has been working to demonstrate that it can predict overall TMB using computational analyses of the mutation patterns present in only the genes covered by its comprehensive targeted sequencing test FoundationOne.

In last week’s study by Elledge and colleagues, results  suggest that mutation burden and aneuploidy may reflect different aspects of the biology of cancer immune response.

Tumors with a high mutation burden showed an increase in their SCNA-derived immune signature score. In contrast, tumors with high-level aneuploidy showed a substantial decrease in the score.

Checking their results to see if there might be patterns other than aneuploidy that are also predictive of either cell proliferation or immune-associated gene expression, the group went back to compare the contribution of SCNA level to the total number of point mutations, TP53 mutations, patient age, patient gender, and tumor stage.

Overall, the results maintained that aneuploidy, and in some cases aneuploidy together with mutation number, represented the most important parameter for predicting the immune-related gene expression signature.

Elledge and his co-authors highlighted in the study that both point mutations and copy number changes can be simultaneously derived from tumor tissue sequencing results. This suggests that adding SNCA analysis to measurement of tumor mutational burden could be relatively simple.

As they continue to study tumor aneuploidy, Elledge said he and his team are hoping to extend the findings that they had from studying patients treated with CTLA-4 drugs to immunotherapy more broadly.

"There is more than one kind of drug out there now, so we'd like to see if this is a general phenomenon with PD-1, PD-L1, etc," he said.

In addition, the team is hopeful that as it further elucidates the way aneuploidy affects immune cell infiltration, it could help inform new treatment strategies that can improve the efficacy of current drugs.

"We are really unravelling the mechanism here, so if we learn how this affects the tumor and can undo that, it would really improve immunotherapies," Elledge said.

"We have some info on that already, but we are not there yet," he added.