RESUMEN
BACKGROUND: Colorectal cancer (CRC) is a common cancer worldwide. The main cause of death in CRC includes tumor progression and metastasis. At molecular level, these processes may be triggered by epithelial-mesenchymal transition (EMT) and necessitates specific alterations in cell metabolism. Although several EMT-related metabolic changes have been described in CRC, the mechanism is still poorly understood. RESULTS: Using CrossHub software, we analyzed RNA-Seq expression profile data of CRC derived from The Cancer Genome Atlas (TCGA) project. Correlation analysis between the change in the expression of genes involved in glycolysis and EMT was performed. We obtained the set of genes with significant correlation coefficients, which included 21 EMT-related genes and a single glycolytic gene, HK3. The mRNA level of these genes was measured in 78 paired colorectal cancer samples by quantitative polymerase chain reaction (qPCR). Upregulation of HK3 and deregulation of 11 genes (COL1A1, TWIST1, NFATC1, GLIPR2, SFPR1, FLNA, GREM1, SFRP2, ZEB2, SPP1, and RARRES1) involved in EMT were found. The results of correlation study showed that the expression of HK3 demonstrated a strong correlation with 7 of the 21 examined genes (ZEB2, GREM1, TGFB3, TGFB1, SNAI2, TWIST1, and COL1A1) in CRC. CONCLUSIONS: Upregulation of HK3 is associated with EMT in CRC and may be a crucial metabolic adaptation for rapid proliferation, survival, and metastases of CRC cells.
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Neoplasias Colorrectales/genética , Neoplasias Colorrectales/patología , Transición Epitelial-Mesenquimal/genética , Hexoquinasa/genética , Femenino , Perfilación de la Expresión Génica , Genómica , Humanos , Masculino , Persona de Mediana Edad , Regulación hacia ArribaAsunto(s)
Biomarcadores de Tumor , Ácidos Nucleicos Libres de Células , ADN Tumoral Circulante , Biopsia Líquida/métodos , Neoplasias/diagnóstico , Neoplasias/genética , Estudios de Casos y Controles , Manejo de la Enfermedad , Susceptibilidad a Enfermedades , Detección Precoz del Cáncer , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Biopsia Líquida/normas , Especies Reactivas de Oxígeno/metabolismoRESUMEN
Cell-free DNA (cfDNA) testing is the core of most liquid biopsy assays. In particular, cfDNA fragmentation features could facilitate non-invasive cancer detection due to their interconnection with tumor-specific epigenetic alterations. However, the final cfDNA fragmentation profile in a purified sample is the result of a complex interplay between informative biological and artificial technical factors. In this work, we use ddPCR to study cfDNA lengths in colorectal cancer patients and observe shorter and more variable cfDNA fragments in accessible chromatin loci compared to the densely packed pericentromeric region. We also report a convenient qPCR system suitable for screening cfDNA samples for artificial high molecular weight DNA contamination.
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Nucleic acid fragments found in blood circulation originate mostly from dying cells and carry signs pointing to specific features of the parental cell types. Deciphering these clues may be transformative for numerous research and clinical applications but strongly depends on the development and implementation of robust analytical methods. Remarkable progress has been achieved in the reliable detection of sequence alterations in cell-free DNA while decoding epigenetic information from methylation and fragmentation patterns requires more sophisticated approaches. This review discusses the currently available strategies for detecting and analyzing the epigenetic marks in the liquid biopsies.
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Epigenetic alterations represent promising therapeutic targets in cancer treatment. Recently it was revealed that small molecules have the potential to act as microRNA silencers. Capacity to bind the discrete stem-looped structure of pre-miR-21 and prevent its maturation opens opportunities to utilize such compounds for the prevention of initiation, progression, and chemoresistance of cancer. Molecular simulations performed earlier identified 3,3'-diindolylmethane (DIM) as a potent microRNA-21 antagonist. However, data on DIM and microRNA-21 interplay is controversial, which may be caused by the limitations of the cell lines.
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Protocolos de Quimioterapia Combinada Antineoplásica/farmacología , Neoplasias de la Mama/tratamiento farmacológico , Neoplasias de la Mama/metabolismo , Indoles/farmacología , Organoides/efectos de los fármacos , Organoides/metabolismo , Anciano , Neoplasias de la Mama/patología , Ciclofosfamida/farmacología , Femenino , Humanos , Metotrexato/farmacología , MicroARNs/antagonistas & inhibidores , MicroARNs/metabolismo , Organoides/patología , Cultivo Primario de CélulasRESUMEN
Fragmentation of DNA is the very important first step in preparing nucleic acids for next-generation sequencing. Here we report a novel Fragmentation Through Polymerization (FTP) technique, which is a simple, robust, and low-cost enzymatic method of fragmentation. This method generates double-stranded DNA fragments that are suitable for direct use in NGS library construction and allows the elimination of the additional step of reparation of DNA ends.
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Fragmentación del ADN , ADN/química , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Polimerizacion , Análisis de Secuencia de ADN/métodos , Biología Computacional , ADN/genética , Desoxirribonucleasa I/química , Biblioteca de GenesRESUMEN
BACKGROUND: Carotid body tumor (CBT) is a form of head and neck paragangliomas (HNPGLs) arising at the bifurcation of carotid arteries. Paragangliomas are commonly associated with germline and somatic mutations involving at least one of more than thirty causative genes. However, the specific functionality of a number of these genes involved in the formation of paragangliomas has not yet been fully investigated. METHODS: Exome library preparation was carried out using Nextera® Rapid Capture Exome Kit (Illumina, USA). Sequencing was performed on NextSeq 500 System (Illumina). RESULTS: Exome analysis of 52 CBTs revealed potential driver mutations (PDMs) in 21 genes: ARNT, BAP1, BRAF, BRCA1, BRCA2, CDKN2A, CSDE1, FGFR3, IDH1, KIF1B, KMT2D, MEN1, RET, SDHA, SDHB, SDHC, SDHD, SETD2, TP53BP1, TP53BP2, and TP53I13. In many samples, more than one PDM was identified. There are also 41% of samples in which we did not identify any PDM; in these cases, the formation of CBT was probably caused by the cumulative effect of several not highly pathogenic mutations. Estimation of average mutation load demonstrated 6-8 mutations per megabase (Mb). Genes with the highest mutation rate were identified. CONCLUSIONS: Exome analysis of 52 CBTs for the first time revealed the average mutation load for these tumors and also identified potential driver mutations as well as their frequencies and co-occurrence with the other PDMs.