An All-In-One Transcriptome-Based Assay to Identify Therapy-Guiding Genomic Aberrations in Nonsmall Cell Lung Cancer Patients

MET alterations detection platforms and clinical implications in solid tumors: a comprehensive review of literature

MET alterations, including MET exon 14 skipping variants, MET amplification, MET overexpression, and MET fusion, play pivotal roles in primary tumorigenesis and acquired resistance to targeted therapies, especially EGFR tyrosine kinase inhibitors. They represent important diagnostic, prognostic, and predictive biomarkers in many solid tumor types. However, the detection of MET alterations is challenging due to the complexity of MET alterations and the diversity of platform technologies. Therefore, techniques with high sensitivity, specificity, and reliable molecular detection accuracy are needed to overcome such hindrances and aid in biomarker-guided therapies. The current review emphasizes the role of MET alterations as oncogenic drivers in a variety of cancers and their involvement in the development of resistance to targeted therapies. Moreover, our review provides an overview of and recommendations on the selection of various cross-platform technologies for the detection of MET exon 14 skipping variants, MET amplification, MET overexpression, and MET fusion. Furthermore, challenges and hurdles underlying these common detection platforms are discussed.

Analytic and Clinical Validation of a Pan-Cancer NGS Liquid Biopsy Test for the Detection of Copy Number Amplifications, Fusions and Exon Skipping Variants

Liquid biopsies are an integral part of the diagnosis of cancer. Here, we have extended previous validation studies of a new targeted NGS panel to include the detection of copy number amplifications (CNAs), fusions, and exon skipping variants. Detection of these gene classes included specimens from clinical and healthy donors and cell lines (fusions: ROS1, EML4-ALK, NTRK1; exon skipping: MET exon 14; CNAs: HER2, CDK6, EGFR, MYC, and MET). The limit of detection (LOD) for fusion/skipping was 42 copies (QC threshold was three copies) and was verified using three additional fusion/skipping variants. LOD for CNAs was 1.40-fold-change (QC threshold = 1.15-fold change) and was verified with three additional CNAs. In repeatability and intermediate precision (within lab) studies, all fusion/skipping variants were detected in all runs and all days of testing (n = 18/18; 100%); average CV for repeatability was 20.5% (range 8.7–34.8%), and for intermediate precision it was 20.8% (range 15.7–30.5%). For CNAs, 28/29 (96.6%) copy gains were detected. For CNAs, the average CV was 1.85% (range 0% to 5.49%) for repeatability and 6.59% (range 1.65% to 9.22%) for intermediate precision. The test panel meets the criteria for being highly sensitive and specific and extends its utility for the serial detection of clinically relevant variants in cancer.

Overexpression of lncRNA AFAP1-AS1 as a diagnostic biomarker in non-small cell lung cancer

Background

Long non-coding RNAs (lncRNAs) play important roles in lung tumorigenesis. Among different lncRNAs, overexpression of the lncRNA actin filament‐associated protein 1‐antisense RNA 1 (AFAP1-AS1) in lung tumors has been reported in different studies. In the current study, we aimed to investigate the potential value of lncRNA AFAP1-AS1 as a diagnostic biomarker in lung cancer. Ninety samples from patients with lung cancer were collected from Noor-E-Nejat hospital, Tabriz, Iran. The expression of AFAP1-AS1 was assessed using quantitative reverse transcriptase-PCR (qRT-PCR), followed by the ROC curve analysis to investigate the biomarker potency of AFAP1-AS1.

Results

Our results revealed an upregulation of AFAP1-AS1 in tumor samples as compared to the adjacent non-tumor tissues. We found a significant positive association between AFAP1-AS1 expression and tumor size, as well as tumor stage.

Conclusions

Our results showed overexpression of AFAP1-AS1 and its capacity as a diagnostic biomarker in lung cancer.

New Therapeutic Strategies for Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for approximately 27% of all cancer-related deaths worldwide, thus representing a major health problem [...].

An Automated Correction Algorithm (ALPACA) for ddPCR Data Using Adaptive Limit of Blank and Correction of False Positive Events Improves Specificity of Mutation Detection

BACKGROUND

Bio-Rad droplet-digital PCR is a highly sensitive method that can be used to detect tumor mutations in circulating cell-free DNA (cfDNA) of patients with cancer. Correct interpretation of ddPCR results is important for optimal sensitivity and specificity. Despite its widespread use, no standardized method to interpret ddPCR data is available, nor have technical artifacts affecting ddPCR results been widely studied.

METHODS

False positive rates were determined for 6 ddPCR assays at variable amounts of input DNA, revealing polymerase induced false positive events (PIFs) and other false positives. An in silico correction algorithm, known as the adaptive LoB and PIFs: an automated correction algorithm (ALPACA), was developed to remove PIFs and apply an adaptive limit of blank (LoB) to individual samples. Performance of ALPACA was compared to a standard strategy (no PIF correction and static LoB = 3) using data from commercial reference DNA, healthy volunteer cfDNA, and cfDNA from a real-life cohort of 209 patients with stage IV nonsmall cell lung cancer (NSCLC) whose tumor and cfDNA had been molecularly profiled.

RESULTS

Applying ALPACA reduced false positive results in healthy cfDNA compared to the standard strategy (specificity 98 vs 88%, P = 10-5) and stage IV NSCLC patient cfDNA (99 vs 93%, P = 10-11), while not affecting sensitivity in commercial reference DNA (70 vs 68% P = 0.77) or patient cfDNA (82 vs 88%, P = 0.13). Overall accuracy in patient samples was improved (98 vs 92%, P = 10-7).

CONCLUSIONS

Correction of PIFs and application of an adaptive LoB increases specificity without a loss of sensitivity in ddPCR, leading to a higher accuracy in a real-life cohort of patients with stage IV NSCLC.