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In antitumor immunity and immunotherapy, quality and fitness count.

Specifically, the quality and fitness of neoantigens – tumor-specific mutated peptides on the surface of cancer cells – can influence a patient’s response to immune checkpoint inhibitors, and mathematical models of neoantigen fitness can serve as biomarkers for response to immunotherapy, according to investigators of two separate but related studies published in Nature.

In one study, Marta Łuksza, PhD, from the Simons Center for Systems Biology at the Institute for Advanced Study in Princeton, N.J., and colleagues propose a neoantigen fitness model that can predict tumor response to checkpoint blockade immunotherapy.

“Our model predicts survival in anti-CTLA4–treated melanoma patients and anti-PD-1–treated lung cancer patients. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies,” they wrote (Nature. 2017 Nov 8. doi: 10.1038/nature24473).

In a related study, Vinod P. Balachandran, MD, from the David M. Rubinstein Center for Pancreatic Cancer Research at Memorial Sloan Kettering Cancer Center in New York and colleagues, including Dr. Łuksza and others, looked at T-cell antigens in long-term survivors of pancreatic cancer and identified specific neoantigens as T-cell targets.

“More broadly, we identify neoantigen quality as a biomarker for immunogenic tumors that may guide the application of immunotherapies,” Dr. Balachandran and colleagues wrote (Nature. 2017 Nov 8. doi: 10.1038/nature24462).
 

Proof of concept

The studies provide a proof of concept that mathematical modeling of tumor evolution and the interactions of tumors with the immune system may soon provide clinicians with valuable and actionable information about responses to immunotherapy, Benjamin Greenbaum, PhD, senior author on the study by Łuksza et al., and a coauthor on the pancreatic cancer study said in an interview.

“We’re trying to come up with measures that take into account what we think the underlying processes are and what lies behind therapy response, and that should lead to better predictive models associated with response in the future,” said Dr. Greenbaum, of the Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai Medical Center, New York.

One of the key findings of the studies is that neoantigen quality – the ability of neoantigens to spark T-cell recognition – seems to be as or more important than neoantigen quantity for influencing immune responses during tumor evolution.

“The general logic behind the idea that mutational burden can be a good predictor of response is that the more mutations you have, the more likely that you have a neoantigen, a peptide generated by a tumor mutation, that elicits productive T-cell recognition. We tried to model that process that might lead to productive T-cell recognition, to assign a kind of number to every neoantigen to provide some estimate of how likely it was to undergo a productive process,” Dr. Greenbaum explained.
 

Melanoma and lung cancer survivors

In the study by Łuksza et al., the investigators created a mathematical fitness model that can predict how tumors respond to immunotherapy based on how neoantigens interact with the immune system and applied the model to data on three previously reported patient cohorts, including two groups of patients with malignant melanoma treated with a cytotoxic T-lymphocyte associated protein 4 (CTLA4) immune checkpoint such as ipilimumab (Yervoy), and one group of patients with non–small cell lung cancer treated with a programmed death-1 (PD-1) inhibitor (for example, nivolumab [Opdivo]).

They found that their proposed model is more accurate than genomic biomarkers for predicting how a specific tumor may respond to immunotherapy.

“Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumors and rapidly evolving pathogens,” they wrote.
 

Pancreatic cancer survivors

Fewer than 7% of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) survive more than 5 years, despite the best surgical and medical therapy. But a few lucky patients are long-term survivors, and Dr. Balachandran and associates sought to examine what aspects of T-cell immunity contributed to their longevity.

Rather than relying on genomic analysis of tumor samples, however, they used a combination of genetic, immunohistochemical, and transcriptional immunoprofiling, as well as computational biophysics and function to identify T-cell antigens in the long-term survivors.

When they compared surgically resected patients matched by tumor stage, they found that tumors from those with a median overall survival (OS) of 6 years had a 3-fold greater density of CD8-positive T cells and a 12-fold greater density of cytolytic CD8-positive cells, as well as more mature dendritic cells, regulatory T cells, and macrophages, but decreased numbers of CD4-positive T cells, compared with patients with a more typical course of survival (median OS, 0.8 years). There were no differences between long- and short-term survivors in either B cells or major histocompatibility complex (MHC) class I–positive cells.

They then performed whole-exome sequencing on tumor samples to determine the frequency of neoantigens and found a median of 38 predicted neoantigens per tumor.

“Notably, patients with both the highest predicted neoantigen number and either the greatest CD3+, CD8+, or polyclonal T-cell repertoire, but neither alone, exhibited the longest survival,” they wrote.

When they looked for qualities of neoantigens responsible for promoting T-cell activation in the long-term survivors, they found that the tumors from the survivors, compared with others, were enriched in neoantigen qualities that could be described by a mathematical fitness model.

“Our results provide insight into the heterogeneous immunobiology of PDAC, a presumed poorly immunogenic and checkpoint blockade–refractory tumor, demonstrating that neoantigens may be T-cell targets in [long-term survivors]”, they wrote.

The investigators propose that immunity to neoantigens that are generated during the outgrowth of a primary tumor could at least partially explain the lower incidence of relapse and prolonged survival of a small minority of patients with pancreatic cancer.

“Our findings support the development of strategies to harness neoantigen-specific immunity to treat checkpoint blockade–refractory cancers, and the identification of immunogenic hot spots for directed neoantigen targeting,” they concluded.

The studies were supported by grants from Stand Up to Cancer, American Cancer Society, National Science Foundation, Lustgarten Foundation, Janssen Research & Development, the STARR Cancer Consortium, the Pershing Square Sohn Cancer Research Alliance, the National Institutes of Health, the V Foundation, Swim Across America, Ludwig Institute for Cancer Research, the Parker Institute for Cancer Immunotherapy, a National Cancer Institute Career Development Award, and a Memorial Sloan Kettering Cancer Center core grant. Dr. Łuksza and Dr. Greenbaum disclosed consulting for Merck. Dr. Balachandran disclosed research funding from Bristol-Myers Squibb.

 

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In antitumor immunity and immunotherapy, quality and fitness count.

Specifically, the quality and fitness of neoantigens – tumor-specific mutated peptides on the surface of cancer cells – can influence a patient’s response to immune checkpoint inhibitors, and mathematical models of neoantigen fitness can serve as biomarkers for response to immunotherapy, according to investigators of two separate but related studies published in Nature.

In one study, Marta Łuksza, PhD, from the Simons Center for Systems Biology at the Institute for Advanced Study in Princeton, N.J., and colleagues propose a neoantigen fitness model that can predict tumor response to checkpoint blockade immunotherapy.

“Our model predicts survival in anti-CTLA4–treated melanoma patients and anti-PD-1–treated lung cancer patients. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies,” they wrote (Nature. 2017 Nov 8. doi: 10.1038/nature24473).

In a related study, Vinod P. Balachandran, MD, from the David M. Rubinstein Center for Pancreatic Cancer Research at Memorial Sloan Kettering Cancer Center in New York and colleagues, including Dr. Łuksza and others, looked at T-cell antigens in long-term survivors of pancreatic cancer and identified specific neoantigens as T-cell targets.

“More broadly, we identify neoantigen quality as a biomarker for immunogenic tumors that may guide the application of immunotherapies,” Dr. Balachandran and colleagues wrote (Nature. 2017 Nov 8. doi: 10.1038/nature24462).
 

Proof of concept

The studies provide a proof of concept that mathematical modeling of tumor evolution and the interactions of tumors with the immune system may soon provide clinicians with valuable and actionable information about responses to immunotherapy, Benjamin Greenbaum, PhD, senior author on the study by Łuksza et al., and a coauthor on the pancreatic cancer study said in an interview.

“We’re trying to come up with measures that take into account what we think the underlying processes are and what lies behind therapy response, and that should lead to better predictive models associated with response in the future,” said Dr. Greenbaum, of the Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai Medical Center, New York.

One of the key findings of the studies is that neoantigen quality – the ability of neoantigens to spark T-cell recognition – seems to be as or more important than neoantigen quantity for influencing immune responses during tumor evolution.

“The general logic behind the idea that mutational burden can be a good predictor of response is that the more mutations you have, the more likely that you have a neoantigen, a peptide generated by a tumor mutation, that elicits productive T-cell recognition. We tried to model that process that might lead to productive T-cell recognition, to assign a kind of number to every neoantigen to provide some estimate of how likely it was to undergo a productive process,” Dr. Greenbaum explained.
 

Melanoma and lung cancer survivors

In the study by Łuksza et al., the investigators created a mathematical fitness model that can predict how tumors respond to immunotherapy based on how neoantigens interact with the immune system and applied the model to data on three previously reported patient cohorts, including two groups of patients with malignant melanoma treated with a cytotoxic T-lymphocyte associated protein 4 (CTLA4) immune checkpoint such as ipilimumab (Yervoy), and one group of patients with non–small cell lung cancer treated with a programmed death-1 (PD-1) inhibitor (for example, nivolumab [Opdivo]).

They found that their proposed model is more accurate than genomic biomarkers for predicting how a specific tumor may respond to immunotherapy.

“Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumors and rapidly evolving pathogens,” they wrote.
 

Pancreatic cancer survivors

Fewer than 7% of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) survive more than 5 years, despite the best surgical and medical therapy. But a few lucky patients are long-term survivors, and Dr. Balachandran and associates sought to examine what aspects of T-cell immunity contributed to their longevity.

Rather than relying on genomic analysis of tumor samples, however, they used a combination of genetic, immunohistochemical, and transcriptional immunoprofiling, as well as computational biophysics and function to identify T-cell antigens in the long-term survivors.

When they compared surgically resected patients matched by tumor stage, they found that tumors from those with a median overall survival (OS) of 6 years had a 3-fold greater density of CD8-positive T cells and a 12-fold greater density of cytolytic CD8-positive cells, as well as more mature dendritic cells, regulatory T cells, and macrophages, but decreased numbers of CD4-positive T cells, compared with patients with a more typical course of survival (median OS, 0.8 years). There were no differences between long- and short-term survivors in either B cells or major histocompatibility complex (MHC) class I–positive cells.

They then performed whole-exome sequencing on tumor samples to determine the frequency of neoantigens and found a median of 38 predicted neoantigens per tumor.

“Notably, patients with both the highest predicted neoantigen number and either the greatest CD3+, CD8+, or polyclonal T-cell repertoire, but neither alone, exhibited the longest survival,” they wrote.

When they looked for qualities of neoantigens responsible for promoting T-cell activation in the long-term survivors, they found that the tumors from the survivors, compared with others, were enriched in neoantigen qualities that could be described by a mathematical fitness model.

“Our results provide insight into the heterogeneous immunobiology of PDAC, a presumed poorly immunogenic and checkpoint blockade–refractory tumor, demonstrating that neoantigens may be T-cell targets in [long-term survivors]”, they wrote.

The investigators propose that immunity to neoantigens that are generated during the outgrowth of a primary tumor could at least partially explain the lower incidence of relapse and prolonged survival of a small minority of patients with pancreatic cancer.

“Our findings support the development of strategies to harness neoantigen-specific immunity to treat checkpoint blockade–refractory cancers, and the identification of immunogenic hot spots for directed neoantigen targeting,” they concluded.

The studies were supported by grants from Stand Up to Cancer, American Cancer Society, National Science Foundation, Lustgarten Foundation, Janssen Research & Development, the STARR Cancer Consortium, the Pershing Square Sohn Cancer Research Alliance, the National Institutes of Health, the V Foundation, Swim Across America, Ludwig Institute for Cancer Research, the Parker Institute for Cancer Immunotherapy, a National Cancer Institute Career Development Award, and a Memorial Sloan Kettering Cancer Center core grant. Dr. Łuksza and Dr. Greenbaum disclosed consulting for Merck. Dr. Balachandran disclosed research funding from Bristol-Myers Squibb.

 

 

In antitumor immunity and immunotherapy, quality and fitness count.

Specifically, the quality and fitness of neoantigens – tumor-specific mutated peptides on the surface of cancer cells – can influence a patient’s response to immune checkpoint inhibitors, and mathematical models of neoantigen fitness can serve as biomarkers for response to immunotherapy, according to investigators of two separate but related studies published in Nature.

In one study, Marta Łuksza, PhD, from the Simons Center for Systems Biology at the Institute for Advanced Study in Princeton, N.J., and colleagues propose a neoantigen fitness model that can predict tumor response to checkpoint blockade immunotherapy.

“Our model predicts survival in anti-CTLA4–treated melanoma patients and anti-PD-1–treated lung cancer patients. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies,” they wrote (Nature. 2017 Nov 8. doi: 10.1038/nature24473).

In a related study, Vinod P. Balachandran, MD, from the David M. Rubinstein Center for Pancreatic Cancer Research at Memorial Sloan Kettering Cancer Center in New York and colleagues, including Dr. Łuksza and others, looked at T-cell antigens in long-term survivors of pancreatic cancer and identified specific neoantigens as T-cell targets.

“More broadly, we identify neoantigen quality as a biomarker for immunogenic tumors that may guide the application of immunotherapies,” Dr. Balachandran and colleagues wrote (Nature. 2017 Nov 8. doi: 10.1038/nature24462).
 

Proof of concept

The studies provide a proof of concept that mathematical modeling of tumor evolution and the interactions of tumors with the immune system may soon provide clinicians with valuable and actionable information about responses to immunotherapy, Benjamin Greenbaum, PhD, senior author on the study by Łuksza et al., and a coauthor on the pancreatic cancer study said in an interview.

“We’re trying to come up with measures that take into account what we think the underlying processes are and what lies behind therapy response, and that should lead to better predictive models associated with response in the future,” said Dr. Greenbaum, of the Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai Medical Center, New York.

One of the key findings of the studies is that neoantigen quality – the ability of neoantigens to spark T-cell recognition – seems to be as or more important than neoantigen quantity for influencing immune responses during tumor evolution.

“The general logic behind the idea that mutational burden can be a good predictor of response is that the more mutations you have, the more likely that you have a neoantigen, a peptide generated by a tumor mutation, that elicits productive T-cell recognition. We tried to model that process that might lead to productive T-cell recognition, to assign a kind of number to every neoantigen to provide some estimate of how likely it was to undergo a productive process,” Dr. Greenbaum explained.
 

Melanoma and lung cancer survivors

In the study by Łuksza et al., the investigators created a mathematical fitness model that can predict how tumors respond to immunotherapy based on how neoantigens interact with the immune system and applied the model to data on three previously reported patient cohorts, including two groups of patients with malignant melanoma treated with a cytotoxic T-lymphocyte associated protein 4 (CTLA4) immune checkpoint such as ipilimumab (Yervoy), and one group of patients with non–small cell lung cancer treated with a programmed death-1 (PD-1) inhibitor (for example, nivolumab [Opdivo]).

They found that their proposed model is more accurate than genomic biomarkers for predicting how a specific tumor may respond to immunotherapy.

“Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumors and rapidly evolving pathogens,” they wrote.
 

Pancreatic cancer survivors

Fewer than 7% of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) survive more than 5 years, despite the best surgical and medical therapy. But a few lucky patients are long-term survivors, and Dr. Balachandran and associates sought to examine what aspects of T-cell immunity contributed to their longevity.

Rather than relying on genomic analysis of tumor samples, however, they used a combination of genetic, immunohistochemical, and transcriptional immunoprofiling, as well as computational biophysics and function to identify T-cell antigens in the long-term survivors.

When they compared surgically resected patients matched by tumor stage, they found that tumors from those with a median overall survival (OS) of 6 years had a 3-fold greater density of CD8-positive T cells and a 12-fold greater density of cytolytic CD8-positive cells, as well as more mature dendritic cells, regulatory T cells, and macrophages, but decreased numbers of CD4-positive T cells, compared with patients with a more typical course of survival (median OS, 0.8 years). There were no differences between long- and short-term survivors in either B cells or major histocompatibility complex (MHC) class I–positive cells.

They then performed whole-exome sequencing on tumor samples to determine the frequency of neoantigens and found a median of 38 predicted neoantigens per tumor.

“Notably, patients with both the highest predicted neoantigen number and either the greatest CD3+, CD8+, or polyclonal T-cell repertoire, but neither alone, exhibited the longest survival,” they wrote.

When they looked for qualities of neoantigens responsible for promoting T-cell activation in the long-term survivors, they found that the tumors from the survivors, compared with others, were enriched in neoantigen qualities that could be described by a mathematical fitness model.

“Our results provide insight into the heterogeneous immunobiology of PDAC, a presumed poorly immunogenic and checkpoint blockade–refractory tumor, demonstrating that neoantigens may be T-cell targets in [long-term survivors]”, they wrote.

The investigators propose that immunity to neoantigens that are generated during the outgrowth of a primary tumor could at least partially explain the lower incidence of relapse and prolonged survival of a small minority of patients with pancreatic cancer.

“Our findings support the development of strategies to harness neoantigen-specific immunity to treat checkpoint blockade–refractory cancers, and the identification of immunogenic hot spots for directed neoantigen targeting,” they concluded.

The studies were supported by grants from Stand Up to Cancer, American Cancer Society, National Science Foundation, Lustgarten Foundation, Janssen Research & Development, the STARR Cancer Consortium, the Pershing Square Sohn Cancer Research Alliance, the National Institutes of Health, the V Foundation, Swim Across America, Ludwig Institute for Cancer Research, the Parker Institute for Cancer Immunotherapy, a National Cancer Institute Career Development Award, and a Memorial Sloan Kettering Cancer Center core grant. Dr. Łuksza and Dr. Greenbaum disclosed consulting for Merck. Dr. Balachandran disclosed research funding from Bristol-Myers Squibb.

 

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Key clinical point: Proof-of-concept studies show that mathematical modeling of neoantigens can be used to predict tumor responses to immune checkpoint inhibitors.

Major finding: Neoantigen quality may be a better biomarker for guiding immunotherapy than tumor genomic profiling.

Data source: Basic science reports focusing on neoantigens and their potential influence on tumor interactions with the immune system.

Disclosures: The studies were supported by grants from Stand Up to Cancer, American Cancer Society, National Science Foundation, Lustgarten Foundation, Janssen Research & Development, the STARR Cancer Consortium, the Pershing Square Sohn Cancer Research Alliance, the National Institutes of Health, the V Foundation, Swim Across America, Ludwig Institute for Cancer Research, the Parker Institute for Cancer Immunotherapy, a National Cancer Institute Career Development Award, and a Memorial Sloan Kettering Cancer Center core grant. Dr. Łuksza and Dr. Greenbaum disclosed consulting for Merck. Dr. Balachandran disclosed research funding from Bristol-Myers Squibb.

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