Publication: Development of gene panels to complement clinical decision support systems for evaluating the efficacy of cancer therapies
Abstract
Kanser dünya çapında milyonlarca insanı etkileyen karmaşık bir hastalıktır. Bu hastalığın stesinden gelebilmek iin kanser biyobelirteleri zerinden kişiselleştirilmiş kanser tedavileri uygulanabilmektedir. Gen panelleri klinik karar destek sistemlerini tamamlayarak kanser mutasyonlarının tespitine, uygun tedavilerin eşleştirilmesine ve klinikte rutin kullanıma olanak sağlamaktadır. Bu çalışmada, kişiselleştirilmiş kanser tedavisine ynelik bir pan-kanser gen paneli (n=502) geliştirilmiş ve Kanser Genom Atlası'ndan elde edilen 22 kanser trne ait Tm Ekzom Dizileme (WES) verileri kullanılarak test edilmiştir. Tümör mutasyon yükü (TMB), kişiselleştirilmiş kanser tedavisi, zellikle immnoterapi iin bir biyobelirtetir. Ancak panelin boyutu ve TMB’nin tam olarak belirlenebilmesi için eşik değerleri hala tartışmalıdır. Bir pan-kanser analizi ile, farklı boyutlardaki gen panellerinin etkinliği ve eşik değerlerinin doğru TMB belirlemedeki etkisi, altın standart olarak WES verileri (n=9929) kullanılarak değerlendirildi. Karşılaştırmalı analizler için dört farklı boyutta (0,44-2,54 Mb) gen panelleri seçildi. TMB'nin kanser türleri içindeki ve arasındaki heterojenliği olduka yksektir. Panel boyutu arttıkça tam olarak TMB değerini elde etmek mmkn hale gelmektedir. Dar boyutlu panellerde TMB değeri düşük olan hastaları tanımak özellikle zordur. Ayrıca genel bir TMB eşik değerinin kullanılması oldukça yanıltıcı olabilir. Optimum eşik değeri, tümör tiplerinin TMB dağılımına bağlı olarak 5 ile 20 arasında değişmektedir. Kapsamlı bir gen panelinin kullanılması ve farklı kanser türleri için TMB eşik değerlerinin optimizasyonu, TMB’yi hassas onkolojide gl bir biyobelirte haline getirebilir ve kişiselleştirilmiş kanser tedavilerinin sunulmasını destekleyebilir.
Cancer is a complex disease that affects millions of people worldwide. Personalized cancer therapies using cancer biomarkers can help defeat this disease. Gene panels complement clinical decision support systems and enable the detection of cancer mutations, the matching of appropriate treatments and routine use in the clinic. In this study, a pan-cancer gene panel (n=502) for personalized cancer therapy was developed and tested using Whole Exome Sequencing (WES) data of 22 cancer types from the Cancer Genome Atlas. Tumor mutation burden (TMB) is a biomarker for personalized cancer therapy, particularly immunotherapy. However, the size of the panel and the cutoff values for an accurate determination of TMB are still controversial. In a pan-cancer analysis, the efficiency of gene panels of different sizes and the effect of cut-off values in accurate TMB determination was evaluated using WES data (n=9929 patients) as the gold standard. Gene panels of four different sizes (i.e. 0.44-2.54 Mb) were selected for the comparative analyses. The heterogeneity of TMB within and between cancer types is very high. As the size of the panel increases, it becomes possible to obtain the exact TMB value. In panels of limited size, it is particularly difficult to recognize patients with a low TMB value. In addition, the use of a general TMB cut-off value can be quite misleading. The optimal cut-off value varies between 5 and 20, depending on the TMB distribution of the tumor types. The use of a comprehensive gene panel and the optimization of TMB cut-off values for the different cancer types can make TMB a robust biomarker in precision oncology and support the delivery of personalized cancer therapies.
Cancer is a complex disease that affects millions of people worldwide. Personalized cancer therapies using cancer biomarkers can help defeat this disease. Gene panels complement clinical decision support systems and enable the detection of cancer mutations, the matching of appropriate treatments and routine use in the clinic. In this study, a pan-cancer gene panel (n=502) for personalized cancer therapy was developed and tested using Whole Exome Sequencing (WES) data of 22 cancer types from the Cancer Genome Atlas. Tumor mutation burden (TMB) is a biomarker for personalized cancer therapy, particularly immunotherapy. However, the size of the panel and the cutoff values for an accurate determination of TMB are still controversial. In a pan-cancer analysis, the efficiency of gene panels of different sizes and the effect of cut-off values in accurate TMB determination was evaluated using WES data (n=9929 patients) as the gold standard. Gene panels of four different sizes (i.e. 0.44-2.54 Mb) were selected for the comparative analyses. The heterogeneity of TMB within and between cancer types is very high. As the size of the panel increases, it becomes possible to obtain the exact TMB value. In panels of limited size, it is particularly difficult to recognize patients with a low TMB value. In addition, the use of a general TMB cut-off value can be quite misleading. The optimal cut-off value varies between 5 and 20, depending on the TMB distribution of the tumor types. The use of a comprehensive gene panel and the optimization of TMB cut-off values for the different cancer types can make TMB a robust biomarker in precision oncology and support the delivery of personalized cancer therapies.