Value-based genomics

Abstract

Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.

Next‐generation sequencing in precision oncology: Patient understanding and expectations

“…In fact, the most common concern of participants was that sequencing would not yield clinically useful findings, which seems well-justified given that precision oncology studies have not yet demonstrated general effectiveness of molecular profiling in cancer treatment. 27 Our findings should be interpreted in light of several study limitations. The study sample of cancer patients was disproportionately white and college-educated, limiting generalizability of study results.…”

“…Although literature on the ethical, legal, and social implications of genetic testing has often highlighted the potential harms of learning personal genetic information, relatively few patients in the study expressed concerns regarding the possibility of psychological distress or unwanted information as a result of undergoing sequencing. In fact, the most common concern of participants was that sequencing would not yield clinically useful findings, which seems well‐justified given that precision oncology studies have not yet demonstrated general effectiveness of molecular profiling in cancer treatment …”

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

“…It is important to carefully consider the panel size and composition for accurate TMB assessment. Supporting this concept, it has been observed that confidence intervals for TMB estimation increase with the use of gene panels that assess a smaller area of the genome compared with those that assess a larger area, which suggests that using smaller coverage gene panels could lead to the overestimation or underestimation of TMB . Depth of sequencing also differs between WES and targeted gene panel assays; sequencing depth is greater for targeted gene panels (~500×) than for WES (~100×) .…”

“…47,48 To date, most of the published studies have assessed TMB in solid tumor samples; however, blood TMB assessment assays are increasingly being used to assess TMB association with response to immune checkpoint inhibitors ( Preanalytical Sample type FFPE samples may harbor artefactual deamination alterations that may impact mutation calling and TMB calculation 56,57 Tumor purity Infiltration of tumor with immune or TME cells may impact TMB score (lower tumor purity is associated with reduced sensitivity) 32 Sequencing parameters Genomic region covered TMB score will depend on panel size and genomic region covered. Greater panel sizes are associated with more precise TMB estimated values 4,[62][63][64][65][66][67][68][69] Genes included in panel Gene selection in panels is biased toward frequently mutated cancerassociated genes, and mutation patterns of these genes are often nonrandom. 33 TMB scores may depend on whether the panel contains specific genes that harbor frequent mutations in specific tumor types…”

“…Supporting this concept, it has been observed that confidence intervals for TMB estimation increase with the use of gene panels that assess a smaller area of the genome compared with those that assess a larger area, which suggests that using smaller coverage gene panels could lead to the overestimation or underestimation of TMB. 4,[62][63][64][65][66][67][68][69] Depth of sequencing also differs between WES and targeted gene panel assays; sequencing depth is greater for targeted gene panels (~500×) than for WES (~100×). 4,61,64 Genome coverage and sequencing depth together determine assay sensitivity and specificity, and therefore, influence TMB estimation output.…”