RESUMO
To efficiently tackle certain tumor types, finding new biomarkers for rapid and complete phenotyping of cancer cells is highly demanded. This is especially the case for the most common pediatric solid tumor of the sympathetic nervous system, namely, neuroblastoma (NB). Liquid biopsy is in principle a very promising tool for this purpose, but usually enrichment and isolation of circulating tumor cells in such patients remain difficult due to the unavailability of universal NB cell-specific surface markers. Here, we show that rapid screening and phenotyping of NB cells through stain-free biomarkers supported by artificial intelligence is a viable route for liquid biopsy. We demonstrate the concept through a flow cytometry based on label-free holographic quantitative phase-contrast microscopy empowered by machine learning. In detail, we exploit a hierarchical decision scheme where at first level NB cells are classified from monocytes with 97.9% accuracy. Then we demonstrate that different phenotypes are discriminated within NB class. Indeed, for each cell classified as NB its belonging to one of four NB sub-populations (i.e., CHP212, SKNBE2, SHSY5Y, and SKNSH) is evaluated thus achieving accuracy in the range 73.6%-89.1%. The achieved results solve the realistic problem related to the identification circulating tumor cell, i.e., the possibility to recognize and detect tumor cells morphologically similar to blood cells, which is the core issue in liquid biopsy based on stain-free microscopy. The presented approach operates at lab-on-chip scale and emulates real-world scenarios, thus representing a future route for liquid biopsy by exploiting intelligent biomedical imaging.
RESUMO
BACKGROUND: FGFR1 regulates cell-cell adhesion and extracellular matrix architecture and acts as oncogene in several cancers. Potential cancer driver mutations of FGFR1 occur in neuroblastoma (NB), a neural crest-derived pediatric tumor arising in sympathetic nervous system, but so far they have not been studied experimentally. We investigated the driver-oncogene role of FGFR1 and the implication of N546K mutation in therapy-resistance in NB cells. METHODS: Public datasets were used to predict the correlation of FGFR1 expression with NB clinical outcomes. Whole genome sequencing data of 19 paired diagnostic and relapse NB samples were used to find somatic mutations. In NB cell lines, silencing by short hairpin RNA and transient overexpression of FGFR1 were performed to evaluate the effect of the identified mutation by cell growth, invasion and cologenicity assays. HEK293, SHSY5Y and SKNBE2 were selected to investigate subcellular wild-type and mutated protein localization. FGFR1 inhibitor (AZD4547), alone or in combination with PI3K inhibitor (GDC0941), was used to rescue malignant phenotypes induced by overexpression of FGFR1 wild-type and mutated protein. RESULTS: High FGFR1 expression correlated with low relapse-free survival in two independent NB gene expression datasets. In addition, we found the somatic mutation N546K, the most recurrent point mutation of FGFR1 in all cancers and already reported in NB, in one out of 19 matched primary and recurrent tumors. Loss of FGFR1 function attenuated invasion and cologenicity in NB cells, whereas FGFR1 overexpression enhanced oncogenicity. The overexpression of FGFR1N546K protein showed a higher nuclear localization compared to wild-type protein and increased cellular invasion and cologenicity. Moreover, N546K mutation caused the failure in response to treatment with FGFR1 inhibitor by activation of ERK, STAT3 and AKT pathways. The combination of FGFR1 and PI3K pathway inhibitors was effective in reducing the invasive and colonigenic ability of cells overexpressing FGFR1 mutated protein. CONCLUSIONS: FGFR1 is an actionable driver oncogene in NB and a promising therapy may consist in targeting FGFR1 mutations in patients with therapy-resistant NB.
RESUMO
Noncoding cis-regulatory variants have gained interest as cancer drivers, yet progress in understanding their significance is hindered by the numerous challenges and limitations of variant prioritization. To overcome these limitations, we focused on active cis-regulatory elements (aCRE) to design a customized panel for the deep sequencing of 56 neuroblastoma tumor and normal DNA sample pairs. To search for driver mutations, aCREs were defined by reanalysis of H3K27ac chromatin immunoprecipitation sequencing peaks in 25 neuroblastoma cell lines. These regulatory genomic regions were tested for an excess of somatic mutations and assessed for statistical significance using a global approach that accounted for chromatin accessibility and replication timing. Additional validation was provided by whole genome sequence analysis of 151 neuroblastomas. Analysis of HiC data determined the presence of candidate target genes interacting with mutated regions. An excess of somatic mutations in aCREs of diverse genes were identified, including IPO7, HAND2, and ARID3A. CRISPR-Cas9 editing was utilized to assess the functional consequences of mutations in the IPO7-aCRE. Patients with noncoding mutations in aCREs showed inferior overall and event-free survival independent of age at diagnosis, stage, risk stratification, and MYCN status. Expression of aCRE-interacting genes correlated strongly with negative prognostic markers and low survival rates. Moreover, a convergence between the biological functions of aCRE target genes and transcription factors with mutated binding motifs was associated with embryonic development and immune system response. Overall, this strategy enabled the identification of somatic mutations in regulatory elements that collectively promote neuroblastoma tumorigenesis. SIGNIFICANCE: Assessment of noncoding cis-regulatory variants and long-range interaction data highlight the combined effect of somatic mutations in regulatory elements in driving neuroblastoma.
Assuntos
Regulação Neoplásica da Expressão Gênica , Neuroblastoma , Proteínas de Ligação a DNA/genética , Desenvolvimento Embrionário , Humanos , Sistema Imunitário/patologia , Mutação , Neuroblastoma/patologia , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
Progresses over the past years have extensively improved our capacity to use genome-scale analyses-including high-density genotyping and exome and genome sequencing-to identify the genetic basis of pediatric tumors. In particular, exome sequencing has contributed to the evidence that about 10% of children and adolescents with tumors have germline genetic variants associated with cancer predisposition. In this review, we provide an overview of genetic variations predisposing to solid pediatric tumors (medulloblastoma, ependymoma, astrocytoma, neuroblastoma, retinoblastoma, Wilms tumor, osteosarcoma, rhabdomyosarcoma, and Ewing sarcoma) and outline the biological processes affected by the involved mutated genes. A careful description of the genetic basis underlying a large number of syndromes associated with an increased risk of pediatric cancer is also reported. We place particular emphasis on the emerging view that interactions between germline and somatic alterations are a key determinant of cancer development. We propose future research directions, which focus on the biological function of pediatric risk alleles and on the potential links between the germline genome and somatic changes. Finally, the importance of developing new molecular diagnostic tests including all the identified risk germline mutations and of considering the genetic predisposition in screening tests and novel therapies is emphasized.