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1.
Br J Cancer ; 125(11): 1561-1569, 2021 11.
Article En | MEDLINE | ID: mdl-34599295

BACKGROUND: Tumour heterogeneity impacts the efficacy of metastatic cancer treatment even if actionable mutations are identified. Clinicians need to understand if assessing one lesion provides reliable information to drive a therapeutic decision in non-small-cell lung cancer (NSCLC) patients. METHODS: We analysed inter-tumour heterogeneity from five autopsied individuals with NSCLC-harbouring mutations in the epidermal growth factor receptor (EGFR), treated with EGFR tyrosine kinase inhibitors (TKIs). Through a comprehensive next-generation sequencing (NGS) oncopanel, and an EGFR panel for digital droplet PCR (ddPCR), we compared metastases within individuals, longitudinal biopsies from the same lesions and, whenever possible, the primary naive tumour. RESULTS: Analysis of 22 necropsies from five patients revealed homogeneity in pathogenic mutations and TKI-resistance mechanisms within each patient in four of them. In-depth analysis by whole-exome sequencing from patient 1 confirmed homogeneity in clonal mutations, but heterogeneity in passenger subclonal alterations. Different resistance mechanisms were detected depending on the patient and line of treatment. Three patients treated with a c-MET inhibitor in combination with TKI lost MET amplification upon progression. CONCLUSION: At a given point and under selective TKI pressure, a single metastasis biopsy in disseminated tumours from EGFR-mutated NSCLC patients could provide a reasonable assessment of actionable alterations useful for therapeutic decisions.


Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/genetics , Lung Neoplasms/drug therapy , Lung Neoplasms/genetics , Protein Kinase Inhibitors/therapeutic use , Carcinoma, Non-Small-Cell Lung/enzymology , ErbB Receptors/antagonists & inhibitors , ErbB Receptors/genetics , Evolution, Molecular , High-Throughput Nucleotide Sequencing , Humans , Lung Neoplasms/enzymology , Protein Kinase Inhibitors/pharmacology
2.
Methods Mol Biol ; 2318: 321-336, 2021.
Article En | MEDLINE | ID: mdl-34019300

Clinical tumor specimens are routinely formalin-fixed and paraffin-embedded (FFPE) in Pathology departments worldwide. FFPE blocks are convenient, long-term stable, and easy to archive and manipulate. However, nucleic acids extracted from FFPE tissues generally show a high degree of fragmentation as well as chemical modifications, mainly due to the fixation process. Methods to determine copy number alterations (CNAs) from FFPE clinical samples have proven challenging, in the fact that they are low-plex, only able to profile single genes or gene clusters (such as in situ hybridization-based methods), and/or show a low degree of robustness with partially degraded samples (array-based, NGS-based) as well as being time-consuming, costly, and with limitations in resolution. The NanoString nCounter® System is a medium-plex, extremely FFPE-robust system, that overcomes several of the frequent issues when dealing with clinical samples. The technique is based on hybridization of molecular barcoded probes directly to FFPE-derived DNA, followed by single molecule imaging to detect hundreds of unique molecules in a single reaction without any amplification steps that might introduce undesired biases. Here we describe nCounter v2 Cancer Copy Number Assay, a robust and highly reproducible method for detecting the copy number status of 87 genes commonly amplified or deleted in cancer, including the MYC proto-oncogene.


DNA Copy Number Variations , Nucleic Acid Hybridization/methods , Proto-Oncogene Proteins c-myc/genetics , DNA/genetics , DNA Probes , Formaldehyde/chemistry , Genes, myc/genetics , Genes, myc/physiology , Humans , In Situ Hybridization, Fluorescence/methods , Neoplasms/genetics , Paraffin Embedding/methods , Proto-Oncogene Mas , Proto-Oncogene Proteins c-myc/metabolism , Tissue Fixation/methods
3.
Mol Oncol ; 13(9): 1827-1835, 2019 09.
Article En | MEDLINE | ID: mdl-31322322

Despite major advances in the treatment of metastatic colorectal cancer (mCRC), the survival rate remains very poor. This study aims at exploring the prognostic value of RAS-mutant allele fraction (MAF) in plasma in mCRC. Forty-seven plasma samples from 37 RAS-mutated patients with nonresectable metastases were tested for RAS in circulating tumor DNA using BEAMing before first- and/or second-line treatment. RAS MAF was correlated with several clinical parameters (number of metastatic sites, hepatic volume, carcinoembryonic antigen, CA19-9 levels, primary site location, and treatment line) and clinical outcome [progression-free survival (PFS) and overall survival (OS)]. An independent cohort of 32 patients from the CAPRI-GOIM trial was assessed for clinical outcome based on plasma baseline MAF. RAS MAF analysis at baseline revealed a significant correlation with longer OS [Hazard ratios (HR) = 3.514; P = 0.00066]. Patients with lower MAF also showed a tendency to longer PFS, although not statistically significant. Multivariate analysis showed RAS MAFs as an independent prognostic factor in both OS (HR = 2.73; P = 0.006) and first-line PFS (HR = 3.74; P = 0.049). Tumor response to treatment in patients with higher MAF was progression disease (P = 0.007). Patients with low MAFs at baseline in the CAPRI-GOIM group also showed better OS [HR = 3.84; 95% confidence intervals (CI) 1.5-9.6; P = 0.004] and better PFS (HR = 2.5; 95% CI: 1.07-5.62; P = 0.033). This minimally invasive test may help in adding an independent factor to better estimate outcomes before initiating treatment. Further prospective studies using MAF as a stratification factor could further validate its utility in clinical practice.


Alleles , Circulating Tumor DNA , Colorectal Neoplasms , Mutation , Oncogene Protein p21(ras)/genetics , Aged , Circulating Tumor DNA/blood , Circulating Tumor DNA/genetics , Colorectal Neoplasms/blood , Colorectal Neoplasms/genetics , Colorectal Neoplasms/mortality , Disease-Free Survival , Female , Humans , Male , Middle Aged , Prospective Studies , Retrospective Studies , Survival Rate
4.
Sci Rep ; 7(1): 15661, 2017 Nov 15.
Article En | MEDLINE | ID: mdl-29142197

AL amyloidosis is characterized by widespread deposition of immunoglobulin light chains (LCs) as amyloid fibrils. Cardiac involvement is frequent and leads to life-threatening cardiomyopathy. Besides the tissue alteration caused by fibrils, clinical and experimental evidence indicates that cardiac damage is also caused by proteotoxicity of prefibrillar amyloidogenic species. As in other amyloidoses, the damage mechanisms at cellular level are complex and largely undefined. We have characterized the molecular changes in primary human cardiac fibroblasts (hCFs) exposed in vitro to soluble amyloidogenic cardiotoxic LCs from AL cardiomyopathy patients. To evaluate proteome alterations caused by a representative cardiotropic LC, we combined gel-based with label-free shotgun analysis and performed bioinformatics and data validation studies. To assess the generalizability of our results we explored the effects of multiple LCs on hCF viability and on levels of a subset of cellular proteins. Our results indicate that exposure of hCFs to cardiotropic LCs translates into proteome remodeling, associated with apoptosis activation and oxidative stress. The proteome alterations affect proteins involved in cytoskeletal organization, protein synthesis and quality control, mitochondrial activity and metabolism, signal transduction and molecular trafficking. These results support and expand the concept that soluble amyloidogenic cardiotropic LCs exert toxic effects on cardiac cells.


Amyloidogenic Proteins/metabolism , Immunoglobulin Light Chains/metabolism , Immunoglobulin Light-chain Amyloidosis/metabolism , Myocytes, Cardiac/metabolism , Amyloid/metabolism , Cardiomyopathies/genetics , Cardiomyopathies/metabolism , Cardiomyopathies/pathology , Cardiotoxicity , Cytoplasm/metabolism , Fibroblasts/metabolism , Fibroblasts/pathology , Heart/physiopathology , Humans , Immunoglobulin Light-chain Amyloidosis/genetics , Immunoglobulin Light-chain Amyloidosis/pathology , Mitochondria/metabolism , Mitochondria/pathology , Myocardium/metabolism , Myocardium/pathology , Myocytes, Cardiac/pathology , Oxidative Stress/genetics , Primary Cell Culture
5.
Nucleic Acids Res ; 35(7): 2343-55, 2007.
Article En | MEDLINE | ID: mdl-17389643

Gene expression technology has become a routine application in many laboratories and has provided large amounts of gene expression signatures that have been identified in a variety of cancer types. Interpretation of gene expression signatures would profit from the availability of a procedure capable of assigning differentially regulated genes or entire gene signatures to defined cancer signaling pathways. Here we describe a graph-based approach that identifies cancer signaling pathways from published gene expression signatures. Published gene expression signatures are collected in a database (PubLiME: Published Lists of Microarray Experiments) enabled for cross-platform gene annotation. Significant co-occurrence modules composed of up to 10 genes in different gene expression signatures are identified. Significantly co-occurring genes are linked by an edge in an undirected graph. Edge-betweenness and k-clique clustering combined with graph modularity as a quality measure are used to identify communities in the resulting graph. The identified communities consist of cell cycle, apoptosis, phosphorylation cascade, extra cellular matrix, interferon and immune response regulators as well as communities of unknown function. The genes constituting different communities are characterized by common genomic features and strongly enriched cis-regulatory modules in their upstream regulatory regions that are consistent with pathway assignment of those genes.


Computer Graphics , Databases, Genetic , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Neoplasms/genetics , Signal Transduction/genetics , Animals , Humans , Mice , Neoplasms/metabolism , Oligonucleotide Array Sequence Analysis , Promoter Regions, Genetic , Sequence Analysis, DNA
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