Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine

Abstract

Translating whole-exome sequencing (WES) for prospective clinical use may have an impact on the care of patients with cancer; however, multiple innovations are necessary for clinical implementation. These include rapid and robust WES of DNA derived from formalin-fixed, paraffin-embedded tumor tissue, analytical output similar to data from frozen samples and clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival formalin-fixed, paraffin-embedded tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a 'long tail' of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15 out of 16 patients. In one patient, previously undetected findings guided clinical trial enrollment, leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.

Figure 1. FFPE and Frozen sequencing metrics

The percentage of target bases covered at 20X, percent selected bases, and percent of zero coverage targets in FFPE (n = 99) and non-FFPE tissue (n = 768) (1A–C). Additional quality control metrics for all 867 cases are available in Supplementary Table 1. No statistically significant difference between FFPE and non-FFPE tissue is observed in these three metrics (P > 0.05; two-sided Mann-Whitney test).

Figure 2. FFPE and frozen data yield comparable alteration data

FFPE and frozen tissue were extracted from identical tumor samples and analyzed for cross-validation of mutations where there was sufficient power to detect the mutation in the validation sample (A). FFPE to frozen and frozen to FFPE validation rates binned by allelic fractions demonstrate similar validation and false positive rates between the two groups (B–C). Copy number profiles derived from exomes of the same tumor in either FFPE or frozen tissue yield comparable results (R² (Pearson) = 0.89; P < 0.001) (D–E). When comparing the FFPE and frozen segment means for all exons across 11 patients, the R² (Pearson) = 0.79 (P < 0.001) (F).

Figure 3. PHIAL reveals the “long tail” of clinically relevant events

PHIAL takes as input somatic alterations and uses heuristics to assign clinical and biological significance to each alteration (A). PHIAL uses the TARGET database, a curated set of genes that are linked to predictive, prognostic, and/or diagnostic clinical actions when somatically altered in cancers. (B). PHIAL utilizes additional rules to maximize exome data for individuals, including knowledge about kinase domains, copy number directionality, and two-hit pathway events (C). The resulting data is visualized for individual or cohort-level information with this demonstrative PHIAL “gel”. Each alteration is a point sorted by PHIAL score (top are of highest clinical relevance), color coded by potential clinical relevance (red), biological relevance (orange), pathway relevance (yellow), or synonymous variants (gray) (D). A PHIAL “gel” for 511 patient exomes spanning six different disease types (n = 258,226 total somatic alterations). The size of the point is proportional to the number of times a given gene arises at that PHIAL score level. (E). This approach highlights the “long tail” of potentially clinically relevant alterations in TARGET genes (n = 121) that may be present in an individual patient but does not occur sufficiently to be labeled a biological driver across a cohort. The majority of events occur in genes that individually are altered in less than 2% of the overall cohort (F). New cancer clinical trials with TARGET genes specifically integrated into the study per ClinicalTrials.gov over a seven-year period (G).

Figure 4. Clinically relevant findings from individual patients

PHIAL results for 14 patients with a spectrum of malignancies, highlighting nominated clinically actionable alterations in 13 of 14 patients (A). Using the level of evidence schematic (Table 1), all nominated alterations for patients in this study were manually curated and assigned a level of evidence (B, Supplementary Table 7). *Denotes patient sequencing data that predated the rapid WES protocol.

Figure 5. Clinical sequencing informs clinical trial enrollment and experimental discovery

The PHIAL output and treatment course for a patient with metastatic lung adenocarcinoma is shown, with the integration of clinical WES occurring during the patient’s first-line therapy allowing subsequent clinical trial enrollment (A). The patient’s time to relapse data for the three treatment regimens received demonstrate that the best and only clinical response occurred with the CDK4 inhibitor (B). Radiographic imaging demonstrates a small reduction in a representative metastatic focus for the patient on the CDK4 inhibitor trial after two cycles of therapy consistent with stable disease (cm: centimeter; measurement is 1.7 × 1.5 cm for baseline mass and 1.3 × 1.3 cm for two month interval scan of the same mass). Per RECIST criteria, overall tumor reduction was 7.9% (C). For another patient, PHIAL nominated a JAK3 missense mutation (D), and given its location in the kinase domain near alterations previously defined as activating, was considered to have inferential evidence (Level E) for being clinically actionable. The crystal structure of JAK3 demonstrates that the arginine at residue 870 directly coordinates the phosphate group of the primary activating tyrosine phosphorylation site (E). To better characterize this alteration, experimental follow-up of this alteration was performed in a Ba/F3 system. Overexpression of the patient’s JAK3 mutation did not suggest an activating phenotype or further consideration of JAK3 inhibitor clinical trial enrollment (F).