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A new tumor neoantigenicity metric may improve prediction of response to immunotherapy in patients with melanoma, lung cancer, and kidney cancer, a retrospective analysis suggests.
The new metric, known as the Cauchy-Schwarz index of neoantigens (CSiN) score, incorporates both immunogenicity and clonality, according to lead study author Tianshi Lu, a PhD candidate at the University of Texas Southwestern Medical Center in Dallas, and colleagues.
“The major biological insight from this study is that the neoantigen clonal structure in each tumor specimen and the immunogenicity of the neoantigens (represented by the MHC-binding strength in our study) are predictive of response to checkpoint inhibitors and prognosis,” the investigators wrote in Science Immunology.
The study involved 2,479 patients with various cancers, including immunogenic types such as renal cell carcinoma (RCC), and nonimmunogenic types, such as pediatric acute lymphocytic leukemia.
The investigators first evaluated CSiN in relation to clinical outcome among patients with immunogenic cancers who received immunotherapy. Drawing data from multiple cohorts, the investigators found that patients who had better responses to therapy were significantly more likely to have above average CSiN scores than those who had worse responses.
In one cohort of patients with melanoma who received anti–CTLA-4 therapy, those with better responses were more likely to have high CSiN scores (P = .009). In another cohort of melanoma patients who received anti–CTLA-4 therapy, those with higher CSiN scores were more likely to achieve durable clinical benefit (response or stable disease for more than 6 months), compared with patients who had lower CSiN scores (P = .033).
Among patients with clear cell RCC treated with anti-PD-1/PD-L1 therapy, there was a significant positive association between higher CSiN scores and better response (P = .036). Among T effector-high patients with metastatic clear cell RCC, there was a significant association between higher CSiN scores and better response to atezolizumab (P = .028) but not sunitinib (P = .890).
In a cohort of patients with non–small cell lung cancer treated with checkpoint inhibitors, those with sustained responses were more likely to have higher CSiN scores than were patients with short-term progression (P = .015).
The investigators also compared the predictive power of CSiN with existing neoantigenicity metrics, ultimately concluding that CSiN was superior.
“Overall, the neoantigen load and neoantigen fitness models were not as strongly predictive of treatment response as CSiN,” the investigators wrote.
Again using data from patients with immunogenic cancers, the investigators looked for an association between CSiN score and overall survival. Indeed, patients with higher-than-average CSiN scores had significantly better survival than that of those with lower scores (P less than .001). This finding was maintained in a multivariate analysis that accounted for disease type, stage, sex, and age.
In contrast with the above findings, CSiN did not predict survival among patients with nonimmunogenic cancer types.
“Overall, our work offers a rigorous methodology of predicting response to immunotherapy and prognosis from routine patient samples and should be useful for personalizing medicine in the modern era of immunotherapy,” the investigators concluded.
The study was funded by the National Institutes of Health, the Cancer Prevention Research Institute of Texas, and the American Cancer Society. The investigators reported no conflicts of interest.
SOURCE: Lu et al. Sci Immunol. 2020 Feb 21. doi: 10.1126/sciimmunol.aaz3199.
A new tumor neoantigenicity metric may improve prediction of response to immunotherapy in patients with melanoma, lung cancer, and kidney cancer, a retrospective analysis suggests.
The new metric, known as the Cauchy-Schwarz index of neoantigens (CSiN) score, incorporates both immunogenicity and clonality, according to lead study author Tianshi Lu, a PhD candidate at the University of Texas Southwestern Medical Center in Dallas, and colleagues.
“The major biological insight from this study is that the neoantigen clonal structure in each tumor specimen and the immunogenicity of the neoantigens (represented by the MHC-binding strength in our study) are predictive of response to checkpoint inhibitors and prognosis,” the investigators wrote in Science Immunology.
The study involved 2,479 patients with various cancers, including immunogenic types such as renal cell carcinoma (RCC), and nonimmunogenic types, such as pediatric acute lymphocytic leukemia.
The investigators first evaluated CSiN in relation to clinical outcome among patients with immunogenic cancers who received immunotherapy. Drawing data from multiple cohorts, the investigators found that patients who had better responses to therapy were significantly more likely to have above average CSiN scores than those who had worse responses.
In one cohort of patients with melanoma who received anti–CTLA-4 therapy, those with better responses were more likely to have high CSiN scores (P = .009). In another cohort of melanoma patients who received anti–CTLA-4 therapy, those with higher CSiN scores were more likely to achieve durable clinical benefit (response or stable disease for more than 6 months), compared with patients who had lower CSiN scores (P = .033).
Among patients with clear cell RCC treated with anti-PD-1/PD-L1 therapy, there was a significant positive association between higher CSiN scores and better response (P = .036). Among T effector-high patients with metastatic clear cell RCC, there was a significant association between higher CSiN scores and better response to atezolizumab (P = .028) but not sunitinib (P = .890).
In a cohort of patients with non–small cell lung cancer treated with checkpoint inhibitors, those with sustained responses were more likely to have higher CSiN scores than were patients with short-term progression (P = .015).
The investigators also compared the predictive power of CSiN with existing neoantigenicity metrics, ultimately concluding that CSiN was superior.
“Overall, the neoantigen load and neoantigen fitness models were not as strongly predictive of treatment response as CSiN,” the investigators wrote.
Again using data from patients with immunogenic cancers, the investigators looked for an association between CSiN score and overall survival. Indeed, patients with higher-than-average CSiN scores had significantly better survival than that of those with lower scores (P less than .001). This finding was maintained in a multivariate analysis that accounted for disease type, stage, sex, and age.
In contrast with the above findings, CSiN did not predict survival among patients with nonimmunogenic cancer types.
“Overall, our work offers a rigorous methodology of predicting response to immunotherapy and prognosis from routine patient samples and should be useful for personalizing medicine in the modern era of immunotherapy,” the investigators concluded.
The study was funded by the National Institutes of Health, the Cancer Prevention Research Institute of Texas, and the American Cancer Society. The investigators reported no conflicts of interest.
SOURCE: Lu et al. Sci Immunol. 2020 Feb 21. doi: 10.1126/sciimmunol.aaz3199.
A new tumor neoantigenicity metric may improve prediction of response to immunotherapy in patients with melanoma, lung cancer, and kidney cancer, a retrospective analysis suggests.
The new metric, known as the Cauchy-Schwarz index of neoantigens (CSiN) score, incorporates both immunogenicity and clonality, according to lead study author Tianshi Lu, a PhD candidate at the University of Texas Southwestern Medical Center in Dallas, and colleagues.
“The major biological insight from this study is that the neoantigen clonal structure in each tumor specimen and the immunogenicity of the neoantigens (represented by the MHC-binding strength in our study) are predictive of response to checkpoint inhibitors and prognosis,” the investigators wrote in Science Immunology.
The study involved 2,479 patients with various cancers, including immunogenic types such as renal cell carcinoma (RCC), and nonimmunogenic types, such as pediatric acute lymphocytic leukemia.
The investigators first evaluated CSiN in relation to clinical outcome among patients with immunogenic cancers who received immunotherapy. Drawing data from multiple cohorts, the investigators found that patients who had better responses to therapy were significantly more likely to have above average CSiN scores than those who had worse responses.
In one cohort of patients with melanoma who received anti–CTLA-4 therapy, those with better responses were more likely to have high CSiN scores (P = .009). In another cohort of melanoma patients who received anti–CTLA-4 therapy, those with higher CSiN scores were more likely to achieve durable clinical benefit (response or stable disease for more than 6 months), compared with patients who had lower CSiN scores (P = .033).
Among patients with clear cell RCC treated with anti-PD-1/PD-L1 therapy, there was a significant positive association between higher CSiN scores and better response (P = .036). Among T effector-high patients with metastatic clear cell RCC, there was a significant association between higher CSiN scores and better response to atezolizumab (P = .028) but not sunitinib (P = .890).
In a cohort of patients with non–small cell lung cancer treated with checkpoint inhibitors, those with sustained responses were more likely to have higher CSiN scores than were patients with short-term progression (P = .015).
The investigators also compared the predictive power of CSiN with existing neoantigenicity metrics, ultimately concluding that CSiN was superior.
“Overall, the neoantigen load and neoantigen fitness models were not as strongly predictive of treatment response as CSiN,” the investigators wrote.
Again using data from patients with immunogenic cancers, the investigators looked for an association between CSiN score and overall survival. Indeed, patients with higher-than-average CSiN scores had significantly better survival than that of those with lower scores (P less than .001). This finding was maintained in a multivariate analysis that accounted for disease type, stage, sex, and age.
In contrast with the above findings, CSiN did not predict survival among patients with nonimmunogenic cancer types.
“Overall, our work offers a rigorous methodology of predicting response to immunotherapy and prognosis from routine patient samples and should be useful for personalizing medicine in the modern era of immunotherapy,” the investigators concluded.
The study was funded by the National Institutes of Health, the Cancer Prevention Research Institute of Texas, and the American Cancer Society. The investigators reported no conflicts of interest.
SOURCE: Lu et al. Sci Immunol. 2020 Feb 21. doi: 10.1126/sciimmunol.aaz3199.
FROM SCIENCE IMMUNOLOGY