Clinical and Functional Characterization of Atypical KRAS/NRAS Mutations in Metastatic Colorectal Cancer.

PURPOSE: Mutations in KRAS/NRAS (RAS) predict lack of anti-EGFR efficacy in metastatic colorectal cancer (mCRC). However, it is unclear if all RAS mutations have similar impact, and atypical mutations beyond those in standard guidelines exist. EXPERIMENTAL DESIGN: We reviewed 7 tissue and 1 cell-free DNA cohorts of 9,485 patients to characterize atypical RAS variants. Using an in vitro cell-based assay (functional annotation for cancer treatment), Ba/F3 transformation, and in vivo xenograft models of transduced isogenic clones, we assessed signaling changes across mutations. RESULTS: KRAS exon 2, extended RAS, and atypical RAS mutations were noted in 37.8%, 9.5%, and 1.2% of patients, respectively. Among atypical variants, KRAS L19F, Q22K, and D33E occurred at prevalence ≥0.1%, whereas no NRAS codon 117/146 and only one NRAS codon 59 mutation was noted. Atypical RAS mutations had worse overall survival than RAS/BRAF wild-type mCRC (HR, 2.90; 95% confidence interval, 1.24-6.80; P = 0.014). We functionally characterized 114 variants with the FACT assay. All KRAS exon 2 and extended RAS mutations appeared activating. Of 57 atypical RAS variants characterized, 18 (31.6%) had signaling below wild-type, 23 (40.4%) had signaling between wild-type and activating control, and 16 (28.1%) were hyperactive beyond the activating control. Ba/F3 transformation (17/18 variants) and xenograft model (7/8 variants) validation was highly concordant with FACT results, and activating atypical variants were those that occurred at highest prevalence in clinical cohorts. CONCLUSIONS: We provide best available evidence to guide treatment when atypical RAS variants are identified. KRAS L19F, Q22K, D33E, and T50I are more prevalent than many guideline-included RAS variants and functionally relevant.

Functional measurement of mitogen-activated protein kinase pathway activation predicts responsiveness of RAS-mutant cancers to MEK inhibitors.

BACKGROUND: RAS variant-related functional impact on the mitogen-activated protein kinase (MAPK) pathway, and correlation between MAPK activation and MAPK/ERK kinase (MEK) inhibitor responsiveness, is not established. PATIENTS AND METHODS: Of 1,693 tumours sequenced, 576 harboured a RAS alteration; 62 patients received an MEK inhibitor (MEKi) and had RAS mutations that were functionally characterised. We report that RAS mutants have variable levels of MAPK activity, as measured by a functional cell-based assay that quantified MAPK pathway activation after transfection with a variety of RAS mutations. RESULTS: Patients with tumours harbouring RAS alterations with high versus low MAPK activity who were treated with an MEKi showed significantly longer median progression-free survival (PFS) (5.0 vs. 2.3 months; p = 0.0034) and overall survival (20.0 vs. 5.0 months; p = 0.0146) and a trend towards higher rates of clinical benefit (stable disease ≥6 months or partial/complete remission) (38% versus 15%; p = 0.095) (p-values as per univariate analysis). PFS remained statistically significant after the multivariate analysis (p = 0.003). CONCLUSIONS: These results support a correlation between RAS-mutant cancers with greater MAPK signalling and PFS after MEKi treatment.

A Novel System for Functional Determination of Variants of Uncertain Significance using Deep Convolutional Neural Networks.

Many drugs are developed for commonly occurring, well studied cancer drivers such as vemurafenib for BRAF V600E and erlotinib for EGFR exon 19 mutations. However, most tumors also harbor mutations which have an uncertain role in disease formation, commonly called Variants of Uncertain Significance (VUS), which are not studied or characterized and could play a significant role in drug resistance and relapse. Therefore, the determination of the functional significance of VUS and their response to Molecularly Targeted Agents (MTA) is essential for developing new drugs and predicting response of patients. Here we present a multi-scale deep convolutional neural network (DCNN) architecture combined with an in-vitro functional assay to investigate the functional role of VUS and their response to MTA's. Our method achieved high accuracy and precision on a hold-out set of examples (0.98 mean AUC for all tested genes) and was used to predict the oncogenicity of 195 VUS in 6 genes. 63 (32%) of the assayed VUS's were classified as pathway activating, many of them to a similar extent as known driver mutations. Finally, we show that responses of various mutations to FDA approved MTAs are accurately predicted by our platform in a dose dependent manner. Taken together this novel system can uncover the treatable mutational landscape of a drug and be a useful tool in drug development.

Identification of osimertinib-resistant EGFR L792 mutations by cfDNA sequencing: oncogenic activity assessment and prevalence in large cfDNA cohort.

Cell-free DNA (cfDNA) next-generation sequencing has the potential to capture tumor heterogeneity and genomic evolution under treatment pressure in a non-invasive manner. Here, we report the detection of EGFR L792 mutations, a non-covalent mechanism of osimertinib resistance, using Guardant360 cfDNA testing in a patient with metastatic EGFR-mutant non-small cell lung cancer (NSCLC) whose disease progressed on osimertinib. We subsequently analyzed a large cohort of over 1800 additional patient samples harboring an EGFR T790M mutation and identified a concomitant L792 mutation in a total of 22 (1.2%) cases. In vitro functional assays demonstrated that the EGFR L858R/T790M/L792F/H mutations conferred intermediate-level resistance to osimertinib. Further understanding of potential acquired resistance mechanisms to targeted therapy may help inform treatment strategy in EGFR-mutant NSCLC.

Novel Biomarker Proteins in Chronic Lymphocytic Leukemia: Impact on Diagnosis, Prognosis and Treatment.

In many cancers, cells undergo re-programming of metabolism, cell survival and anti-apoptotic defense strategies, with the proteins mediating this reprogramming representing potential biomarkers. Here, we searched for novel biomarker proteins in chronic lymphocytic leukemia (CLL) that can impact diagnosis, treatment and prognosis by comparing the protein expression profiles of peripheral blood mononuclear cells from CLL patients and healthy donors using specific antibodies, mass spectrometry and binary logistic regression analyses and other bioinformatics tools. Mass spectrometry (LC-HR-MS/MS) analysis identified 1,360 proteins whose expression levels were modified in CLL-derived lymphocytes. Some of these proteins were previously connected to different cancer types, including CLL, while four other highly expressed proteins were not previously reported to be associated with cancer, and here, for the first time, DDX46 and AK3 are linked to CLL. Down-regulation expression of two of these proteins resulted in cell growth inhibition. High DDX46 expression levels were associated with shorter survival of CLL patients and thus can serve as a prognosis marker. The proteins with modified expression include proteins involved in RNA splicing and translation and particularly mitochondrial proteins involved in apoptosis and metabolism. Thus, we focused on several metabolism- and apoptosis-modulating proteins, particularly on the voltage-dependent anion channel 1 (VDAC1), regulating both metabolism and apoptosis. Expression levels of Bcl-2, VDAC1, MAVS, AIF and SMAC/Diablo were markedly increased in CLL-derived lymphocytes. VDAC1 levels were highly correlated with the amount of CLL-cancerous CD19+/CD5+ cells and with the levels of all other apoptosis-modulating proteins tested. Binary logistic regression analysis demonstrated the ability to predict probability of disease with over 90% accuracy. Finally, based on the changes in the levels of several proteins in CLL patients, as revealed from LC-HR-MS/MS, we could distinguish between patients in a stable disease state and those who would be later transferred to anti-cancer treatments. The over-expressed proteins can thus serve as potential biomarkers for early diagnosis, prognosis, new targets for CLL therapy, and treatment guidance of CLL, forming the basis for personalized therapy.