Simultaneous identification of clinically relevant single nucleotide variants, copy number alterations and gene fusions in solid tumors by targeted next-generation sequencing

Abstract

In this study, we have set-up a routine pipeline to evaluate the clinical application of Oncomine™ Focus Assay, a panel that allows the simultaneous detection of single nucleotide hotspot mutations in 35 genes, copy number alterations (CNAs) in 19 genes and gene fusions involving 23 genes in cancer samples. For this study we retrospectively selected 106 patients that were submitted to surgical resection for lung, gastric, colon or rectal cancer.We found that 56 patients out of 106 showed at least one alteration (53%), with 47 patients carrying at least one relevant nucleotide variant, 10 patients carrying at least one CNA and 3 patients carrying one gene fusion. On the basis of the mutational profiles obtained, we have identified 22 patients (20.7%) that were potentially eligible for targeted therapy.The most frequently mutated genes across all tumor types included KRAS (30 patients), PIK3CA (16 patients), BRAF (6 patients), EGFR (5 patients), NRAS (4 patients) and ERBB2 (3 patients) whereas CCND1, ERBB2, EGFR and MYC were the genes most frequently subjected to copy number gain. Finally, gene fusions were identified only in lung cancer patients and involved MET [MET(13)–MET(15) fusion] and FGFR3 [FGFR3(chr 17)–TACC3(chr 11)].In conclusion, we demonstrate that the analysis with a multi-biomarker panel of cancer patients after surgery, may present several potential advantages in clinical daily practice, including the simultaneous detection of different potentially druggable alterations, reasonable costs, short time of testing and automated interpretation of results.

ALK (D5F3) CDx: an immunohistochemistry assay to identify ALK-positive NSCLC patients

“…However, turnaround time for NGS is typically 2 weeks or longer and that may be too long for patients with advanced NSCLC to wait. 35 , 36 Needless to say, NGS is much more expensive than other methods at this time.…”

Oncogenic driver FGFR3-TACC3 is dependent on membrane trafficking and ERK signaling

“…These mutations are often chromosomal rearrangements resulting in fusion proteins [ 1 ]. A recently identified fusion protein is FGFR3-TACC3, which has been discovered in glioblastoma, lung cancer, bladder cancer, oral cancer, head and neck squamous cell carcinoma, gallbladder cancer, and cervical cancer [ 2 – 4 ]. This fusion protein is formed by tandem duplication on chromosome 4 resulting in a fusion of the fibroblast growth factor receptor 3 (FGFR3) gene with transforming acidic coiled-coil containing protein 3 (TACC3) gene [ 5 ].…”

Integrating clinical, molecular, proteomic and histopathological data within the tissue context: tissunomics

“…Different platforms are emerging, with different quantitative multispectral fluorescence approaches, or with mass spectrometry in situ , to allow the study and quantification of several dozen markers. Also, new next‐generation sequencing technologies are being implemented in routine testing combining DNA and RNA analysis from the same slide reducing the amount of tissue and also the ITH …”

“…Also, new next-generation sequencing technologies are being implemented in routine testing combining DNA and RNA analysis from the same slide reducing the amount of tissue and also the ITH. 121,122 An interpretative and holistic data assessment with 'deep learning' (artificial intelligence with automatic learning) The main objective for the use of deep learning in pathology is to improve existing algorithms for biomarker quantification and to develop smart and robust algorithms. It can be based on three main areas or objectives: (i) tumour type classification, (ii) tumour prognosis (prediction system, learning from experience) and (iii) personalised treatment allocation system (also a reinforcement learning system).…”