Molecular Biomarkers of Disease Outcomes and Mechanisms of Acquired Resistance to First-Line Osimertinib in Advanced EGFR-Mutant Lung Cancers

INTRODUCTION

Preferred first-line treatment for patients with metastatic EGFR-mutant lung cancer is osimertinib, yet it is not known whether patient outcomes may be improved by identifying and intervening on molecular markers associated with therapeutic resistance.

METHODS

All patients with metastatic EGFR-mutant lung cancer treated with first-line osimertinib at the Memorial Sloan Kettering Cancer Center (n = 327) were identified. Available pretreatment and postprogression tumor samples underwent targeted gene panel sequencing and mutational signature analysis using SigMA algorithm. Progression-free survival (PFS) and overall survival were estimated using the Kaplan-Meier method.

RESULTS

Using multivariate analysis, baseline atypical EGFR (median PFS = 5.8 mo, p < 0.001) and concurrent TP53/RB1 alterations (median PFS = 10.5 mo, p = 0.015) were associated with shorter PFS on first-line osimertinib. Of 95 patients with postprogression biopsies, acquired resistance mechanisms were identified in 52% (off-target, n = 24; histologic transformation, n = 14; on-target, n = 12), with MET amplification (n = 9), small cell lung transformation (n = 7), and acquired EGFR amplification (n = 7), the most frequently identified mechanisms. Although there was no difference in postprogression survival on the basis of identified resistance (p = 0.07), patients with subsequent second-line therapy tailored to postprogression biopsy results had improved postprogression survival (hazard ratio = 0.09, p = 0.006). The paired postprogression tumors had higher tumor mutational burden (p = 0.008) and further dominant APOBEC mutational signatures (p = 0.07) compared with the pretreatment samples.

CONCLUSIONS

Patients with EGFR-mutant lung cancer treated with first-line osimertinib have improved survival with treatment adaptation on the basis of identified mechanisms of resistance at time of progression using tissue-based genomic analysis. Further survival gains may be achieved using risk-based treatment adaptation of pretreatment genomic alterations.

Liquid Biopsy: A Multi-Parametric Analysis of Mutation Status, Circulating Tumor Cells and Inflammatory Markers in EGFR-Mutated NSCLC

The liquid biopsy has the potential to improve patient care in the diagnostic and therapeutic setting in non-small cell lung cancer (NSCLC). Consented patients with epidermal growth factor receptor (EGFR) positive disease (n = 21) were stratified into two cohorts: those currently receiving EGFR tyrosine kinase inhibitor (TKI) therapy (n = 9) and newly diagnosed EGFR TKI treatment-naïve patients (n = 12). Plasma genotyping of cell-free DNA was carried out using the FDA-approved cobas® EGFR mutation test v2 and compared to next generation sequencing (NGS) cfDNA panels. Circulating tumor cell (CTC) numbers were correlated with treatment response and EGFR exon 20 p.T790M. The prognostic significance of the neutrophil to lymphocyte ratio (NLR) and lactate dehydrogenase (LDH) was also investigated. Patients in cohort 1 with an EGFR exon 20 p.T790M mutation progressed more rapidly than those with an EGFR sensitizing mutation, while patients in cohort 2 had a significantly longer progression-free survival (p = 0.04). EGFR exon 20 p.T790M was detected by liquid biopsy prior to disease progression indicated by computed tomography (CT) imaging. The cobas® EGFR mutation test detected a significantly greater number of exon 20 p.T790M mutations (p = 0.05). High NLR and derived neutrophil to lymphocyte ratio (dNLR) were associated with shorter time to progression and worse survival outcomes (p < 0.05). High LDH levels were significantly associated with shorter time to disease progression (p = 0.03). These data support the use of liquid biopsy for monitoring EGFR mutations and inflammatory markers as prognostic indicators in NSCLC.

Altered expression of ACOX2 in non-small cell lung cancer

Peroxisomes are organelles that play essential roles in many metabolic processes, but also play roles in innate immunity, signal transduction, aging and cancer. One of the main functions of peroxisomes is the processing of very-long chain fatty acids into metabolites that can be directed to the mitochondria. One key family of enzymes in this process are the peroxisomal acyl-CoA oxidases (ACOX1, ACOX2 and ACOX3), the expression of which has been shown to be dysregulated in some cancers. Very little is however known about the expression of this family of oxidases in non-small cell lung cancer (NSCLC). ACOX2 has however been suggested to be elevated at the mRNA level in over 10% of NSCLC, and in the present study using both standard and bioinformatics approaches we show that expression of ACOX2 is significantly altered in NSCLC. ACOX2 mRNA expression is linked to a number of mutated genes, and associations between ACOX2 expression and tumour mutational burden and immune cell infiltration were explored. Links between ACOX2 expression and candidate therapies for oncogenic driver mutations such as KRAS were also identified. Furthermore, levels of acyl-CoA oxidases and other associated peroxisomal genes were explored to identify further links between the peroxisomal pathway and NSCLC. The results of this biomarker driven study suggest that ACOX2 may have potential clinical utility in the diagnosis, prognosis and stratification of patients into various therapeutically targetable options.

Detection of MET Exon 14 Skipping Alterations in Lung Cancer Clinical Samples Using a PCR-Based Approach

The receptor tyrosine kinase (RTK) c-MET plays important roles in cancer, yet despite being frequently overexpressed, clinical responses to targeting this receptor have been limited in the clinical setting. A singular significant challenge has been the accurate identification of biomarkers for the selection of responsive patients. However, recently mutations which result in the loss of exon 14 (called METex14 skipping) have emerged as novel biomarkers in non-small cell lung carcinomas (NSCLC) to predict for responsiveness to targeted therapy with c-MET inhibitors. Currently, the diverse genomic alterations responsible for METex14 skipping pose a challenge for routine clinical diagnostic testing. Next generation sequencing (NGS) is the current gold standard for identifying the diverse mutations associated with METex14, but the cost for such a procedure remains to some degree prohibitive as often NGS is requested on a case-by-case basis, and many hospitals may not even have the capacity or resources to conduct NGS.However, PCR-based approaches to detect METex14 have been developed which can be conducted in most routine hospital laboratories and may therefore allow a cost-effective approach to pre-screen patients that may respond to c-MET inhibitors prior to conducting NGS, or until all patients will have NGS conducted as routine practise. In this chapter, we describe one such PCR-based approach for screening samples for the detection of METex14 in NSCLC.

Pre-clinical models of small cell lung cancer and the validation of therapeutic targets

Introduction: Small-cell lung cancer (SCLC) is an aggressive form of lung cancer that has a dismal prognosis. One of the factors hindering therapeutic developments for SCLC is that most SCLC is not surgically resected resulting in a paucity of material for analysis. To address this, significant efforts have been made by investigators to develop pre-clinical models of SCLC allowing for downstream target identification in this difficult to treat cancer.Areas covered: In this review, we describe the current pre-clinical models that have been developed to interrogate SCLC, and outline the benefits and limitations associated with each. Using examples we show how each has been used to (i) improve our knowledge of this intractable cancer, and (ii) identify and validate potential therapeutic targets that (iii) are currently under development and testing within the clinic.Expert opinion: The large numbers of preclinical models that have been developed have dramatically improved the ways in which we can examine SCLC and test therapeutic targets/interventions. The newer models are rapidly providing novel avenues for the design and testing of new therapeutics. Despite this many of these models have inherent flaws that limit the possibility of their use for individualized therapy decision-making for SCLC.