Table 1. Genetic and evolutionary principles for early detection and prevention biomarkers using genomic data.

Best practices for translating genomic and evolutionary alterations. A few cautionary comments are in order about the development and use of somatic genetic and genomic alterations as biomarkers for cancer risk management. Multiple studies have embraced some aspects of the approach outlined here, such as using normal constitutive DNA as a control to be certain that changes are due to genomic alterations in BE, whereas other aspects, such as examining multiple samples obtained at multiple time points, are rarely used. For example, prominent studies from TCGA (in EA and in other cancer types), while accomplishing their goals of generating a valuable catalog of mutations that develop in within tumors, are not well suited for identifying biomarkers of risk progression since they did not examine patients who don’t progress to cancer or examine samples at multiple positions in space within the esophagus and/or multiple time points ^{136, 137}. Incorporating multiple measures of genomic alterations as they evolve in space and time within BE is one of the two greatest and easiest advances that can be made in current BE research. The second greatest need is use of an EA outcome because many BE studies rely upon surrogate dysplasia endpoints. Formal criteria for using surrogate markers in clinical studies have been well described ^{138, 139}. Surrogate endpoints must be reproducible, accurately represent the true endpoint (EA), and have strong predictive ability to distinguish patients who will progress to cancer from those who will not ¹³⁸. The current dysplasia classification system does not meet these criteria because it is not reproducible ^140–142, does not accurately represent the true endpoint EA ^{69, 143, 144}, and has highly variable outcomes in predicting future progression to EA ^{3, 69, 143, 144}. The current practice of normalizing genetic biomarkers to dysplasia grade guarantees that the genetic markers will be just as irreproducible as histopathology when they are used in other centers. Changing this practice is a second advance that, combined with the ability to study genetic and genomic alterations in BE as it does or does not evolve to EA in space and time, can provide a more robust analysis of how the cancer develops and evolves as well as providing more effective use of limited numbers of cancer outcomes ^{31, 44}. Some problems can begin to be overcome by determining the spatial distribution/evolution of genetic alterations surrounding EAs at the time they are diagnosed ^{44, 145}. This practice will likely increase as diversity within EAs becomes increasingly recognized as essential for planning therapeutic strategies. Other challenges will likely be overcome as technologies advance to allow robust analysis to be performed on archived FFPE material. Biorepositories of fresh frozen material obtained prospectively are very rare, but biopsies taken for histologic assessment may be repurposed to allow analysis of the evolution of EA over space and time in a larger set of patients. Where applicable, we have included in Table 1 examples of studies that illustrate use of these principles.

Base genomic biomarkers on fundamental genetic and evolutionary principles 44, 105 Use normal constitutive DNA as a control 45, 47 Well-accepted study designs including patients who do and do not progress to EA 44, 105 Track genomic evolution in esophageal space 45, 65, 101 Track genomic evolution in time 44, 116 Use EA endpoints 44, 143, 144 Be aware of accepted standards for surrogate endpoints 139, 148, 149 Avoid surrogate endpoints that do not meet accepted standards 2