Tumor evolution in epidermal growth factor receptor mutated non-small cell lung cancer

Transcriptional background effects on a tumor driver gene in different pigment cell types of medaka

The Xiphophorus melanoma receptor kinase gene, xmrk, is a bona fide oncogene driving melanocyte tumorigenesis of Xiphophorus fish. When ectopically expressed in medaka, it not only induces development of several pigment cell tumor types in different strains of medaka but also induces different tumor types within the same animal, suggesting its oncogenic activity has a transcriptomic background effect. Although the central pathways that xmrk utilizes to lead to melanomagenesis are well documented, genes and genetic pathways that modulate the oncogenic effect and alter the course of disease have not been studied so far. To understand how the genetic networks between different histocytes of xmrk-driven tumors are composed, we isolated two types of tumors, melanoma and xanthoerythrophoroma, from the same xmrk transgenic medaka individuals, established the transcriptional profiles of both xmrk-driven tumors, and compared (1) genes that are co-expressed with xmrk in both tumor types, and (2) differentially expressed genes and their associated molecular functions, between the two tumor types. Transcriptomic comparisons between the two tumor types show melanoma and xanthoerythrophoroma are characterized by transcriptional features representing varied functions, indicating distinct molecular interactions between the driving oncogene and the cell-type-specific transcriptomes. Melanoma tumors exhibit gene signatures that are relevant to proliferation and invasion, while xanthoerythrophoroma tumors are characterized by expression profiles related to metabolism and DNA repair. We conclude the transcriptomic backgrounds, exemplified by cell-type-specific genes that are downstream of xmrk effected signaling pathways, contribute the potential to change the course of tumor development and may affect overall tumor outcomes.

Pairwise and higher-order epistatic effects among somatic cancer mutations across oncogenesis

Cancer occurs as a consequence of multiple somatic mutations that lead to uncontrolled cell growth. Mutual exclusivity and co-occurrence of mutations imply-but do not prove-that mutations exert synergistic or antagonistic epistatic effects on oncogenesis. Knowledge of these interactions, and the consequent trajectories of mutation and selection that lead to cancer has been a longstanding goal within the cancer research community. Recent research has revealed mutation rates and scaled selection coefficients for specific recurrent variants across many cancer types. However, there are no current methods to quantify the strength of selection incorporating pairwise and higher-order epistatic effects on selection within the trajectory of likely cancer genotoypes. Therefore, we have developed a continuous-time Markov chain model that enables the estimation of mutation origination and fixation (flux), dependent on somatic cancer genotype. Coupling this continuous-time Markov chain model with a deconvolution approach provides estimates of underlying mutation rates and selection across the trajectory of oncogenesis. We demonstrate computation of fluxes and selection coefficients in a somatic evolutionary model for the four most frequently variant driver genes (TP53, LRP1B, KRAS and STK11) from 565 cases of lung adenocarcinoma. Our analysis reveals multiple antagonistic epistatic effects that reduce the possible routes of oncogenesis, and inform cancer research regarding viable trajectories of somatic evolution whose progression could be forestalled by precision medicine. Synergistic epistatic effects are also identified, most notably in the somatic genotype TP53 LRP1B for mutations in the KRAS gene, and in somatic genotypes containing KRAS or TP53 mutations for mutations in the STK11 gene. Large positive fluxes of KRAS variants were driven by large selection coefficients, whereas the flux toward LRP1B mutations was substantially aided by a large mutation rate for this gene. The approach enables inference of the most likely routes of site-specific variant evolution and estimation of the strength of selection operating on each step along the route, a key component of what we need to know to develop and implement personalized cancer therapies.

Detection of EGFR mutations in liquid biopsy samples using allele-specific quantitative PCR: A comparative real-world evaluation of two popular diagnostic systems

PURPOSE

The detection of epidermal growth factor receptor (EGFR) mutations in plasma cell-free DNA (cfDNA) is an auxiliary tool for the molecular diagnosis of non-small cell lung cancer (NSCLC), especially when an adequate tumor tissue specimen cannot be obtained. We compared the diagnostic accuracy of two commonly used in vitro diagnostic-certified allele-specific quantitative PCR assays for detecting plasma cfDNA EGFR mutations.

METHODS

We analyzed EGFR mutations in plasma cfDNA from 90 NSCLC patients (stages I-IV) before treatment (n ​= ​60) and after clinical progression on EGFR tyrosine kinase inhibitors (n ​= ​30) using the cobas EGFR mutation test v2 (Roche Molecular Systems, Inc.) and therascreen EGFR Plasma RGQ PCR kit (Qiagen GmbH).

RESULTS

There was higher concordance between plasma cfDNA and matched tumor tissue EGFR mutations with cobas (66.67%) compared with therascreen (55.93%). The concordance rate increased to 90.00% with cobas (Cohen's kappa coefficient, κ ​= ​0.80; p ​< ​0.0001) and 73.33% with therascreen (κ ​= ​0.49; p ​= ​0.0009) in advanced NSCLC patients. In treatment-naïve patients, cobas was superior to therascreen (sensitivity: 82.35% vs. 52.94%; specificity: 100% vs. 100%). In patients with clinical progression on EGFR tyrosine kinase inhibitors, EGFR exon 20 p.T790M was detected in 30% and 23% of cfDNA samples by cobas and therascreen, respectively.

CONCLUSIONS

Cobas was superior to therascreen for detection of plasma EGFR mutations in advanced NSCLC. Plasma cfDNA EGFR mutation analysis is complex; therefore, the diagnostic accuracy of commercially available assays should be validated.