Longitudinal tracking of 97 esophageal adenocarcinomas using liquid biopsy sampling.

BACKGROUND: The incidence of esophageal adenocarcinoma (EAC) is rapidly rising and has a 5-year survival rate of <20%. Beyond TNM (tumor-node-metastasis) staging, no reliable risk stratification tools exist and no large-scale studies have profiled circulating tumor DNA (ctDNA) at relapse in EAC. Here we analyze the prognostic potential of ctDNA dynamics in EAC, taking into account clonal hematopoiesis with indeterminate potential (CHIP). PATIENTS AND METHODS: A total of 245 samples from 97 patients treated with neoadjuvant chemotherapy and surgery were identified from the prospective national UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium data set. A pan-cancer ctDNA panel comprising 77 genes was used. Plasma and peripheral blood cell samples were sequenced to a mean depth of 7082× (range 2196-28 524) and ctDNA results correlated with survival. RESULTS: Characteristics of the 97 patients identified were as follows: 83/97 (86%) male, median age 68 years (SD 9.5 years), 100% cT3/T4, 75% cN+. EAC-specific drivers had higher variant allele fractions than passenger mutations. Using stringent quality criteria 16/79 (20%) were ctDNA positive following resection; recurrence was observed in 12/16 (75%) of these. As much as 78/97 (80%) had CHIP analyses that enabled filtering for CHIP variants, which were found in 18/78 (23%) of cases. When CHIP was excluded, 10/63 (16%) patients were ctDNA positive and 9/10 of these (90%) recurred. With correction for CHIP, median cancer-specific survival for ctDNA-positive patients was 10.0 months versus 29.9 months for ctDNA-negative patients (hazard ratio 5.55, 95% confidence interval 2.42-12.71; P = 0.0003). Similar outcomes were observed for disease-free survival. CONCLUSIONS: We demonstrate in a large, national, prospectively collected data set that ctDNA in plasma following surgery for EAC is prognostic for relapse. Inclusion of peripheral blood cell samples can reduce or eliminate false positives from CHIP. In future, post-operative ctDNA could be used to risk stratify patients into high- and low-risk groups for intensification or de-escalation of adjuvant chemotherapy.

Molecular signatures that can be transferred across different omics platforms.

MOTIVATION: Molecular signatures for treatment recommendations are well researched. Still it is challenging to apply them to data generated by different protocols or technical platforms. RESULTS: We analyzed paired data for the same tumors (Burkitt lymphoma, diffuse large B-cell lymphoma) and features that had been generated by different experimental protocols and analytical platforms including the nanoString nCounter and Affymetrix Gene Chip transcriptomics as well as the SWATH and SRM proteomics platforms. A statistical model that assumes independent sample and feature effects accounted for 69-94% of technical variability. We analyzed how variability is propagated through linear signatures possibly affecting predictions and treatment recommendations. Linear signatures with feature weights adding to zero were substantially more robust than unbalanced signatures. They yielded consistent predictions across data from different platforms, both for transcriptomics and proteomics data. Similarly stable were their predictions across data from fresh frozen and matching formalin-fixed paraffin-embedded human tumor tissue. AVAILABILITY AND IMPLEMENTATION: The R-package 'zeroSum' can be downloaded at https://github.com/rehbergT/zeroSum . Complete data and R codes necessary to reproduce all our results can be received from the authors upon request. CONTACT: rainer.spang@ur.de.