Molecular cloning and expression of collagenase-3, a novel human matrix metalloproteinase produced by breast carcinomas

Esta publicación detalla los experimentos realizados para la clonación de un ADNc que codifica una nueva metaloproteasa de matriz extracelular a partir de una biblioteca de ADNc procedente de un carcinoma mamario. Este trabajo es de gran interés en la investigación del cáncer, ya que describe la identificación de una nueva colagenasa en los carcinomas mamarios proponiendo un posible papel en el proceso tumoral. Hay evidencia de que las metaloproteasas participan en el proceso de degradación proteolítica de los diferentes componentes de la membrana basal, favoreciendo así la invasión tumoral y las metástasis. El ADNc de la colagenasa-3 se expresó en un sistema de virus vaccinia, y la proteína recombinante fue capaz de degradar los colágenos fibrilares, lo que apoya la hipótesis de que el ADNc aislado codifica para una colagenasa auténtica. El análisis por Northern blot del ARN de tejidos normales y patológicos demostró la existencia de tres especies diferentes de ARNm en los tumores de mama, que parecen ser el resultado de la utilización de distintos sitios de poliadenilación presentes en la región 3'-no codificante del gen. Por el contrario, no se detectó ARNm de la colalagenasa-3 por Northern blot ni por PCR en otros tejidos humanos como mama normal, fibroadenomas mamarios, hígado, placenta, ovario, útero, próstata y glándula parótida. Sobre la base del aumento de la expresión de la colagenasa-3 en los carcinomas de mama y la ausencia de expresión detectable en los tejidos normales, se propone un posible papel de esta metaloproteinasa en el proceso tumoral

Predictors of Nodal and Metastatic Failure in Early Stage Non-Small Cell Lung Cancer after Stereotactic Body Radiation Therapy

Introduction/Background Many early-stage non-small cell lung cancer (ES-NSCLC) patients undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive of metastases after lung SBRT and created a risk stratification tool. Materials and Methods We included 363 patients with ES-NSCLC who received SBRT; median follow-up was 5.8 years. The following patient and tumor factors were retrospectively analyzed for their association with metastases (defined as nodal and/or distant failure): sex; age; lobe involved; centrality; previous NSCLC; smoking status; gross tumor volume (GTV); T-stage; histology; dose; minimum, maximum, and mean GTV dose; and parenchymal lung failure. A metastasis risk-score linear-model using beta coefficients from a multivariate Cox model was built. Results A total of 111/406 (27.3%) lesions metastasized. GTV volume and dose were significantly associated with metastases on univariate and multivariate Cox proportional hazards modeling (p<0.001 and HR=1.02 per mL, p<0.05 and HR=0.99 per Gy, respectively). Histology, T-stage, centrality, lung parenchymal failures, and previous NSCLC were not associated with development of metastasis. A metastasis risk-score model using GTV volume and prescription dose was built: [risk score=(0.01611 x GTV)–(0.00525 x dose (BED10))]. Two risk-score cutoffs separating the cohort into low-, medium-, and high-risk subgroups were examined. The risk-score identified significant differences in time to metastases between low-, medium-, and high-risk patients (p<0.001), with 3-year estimates of 81.1%, 63.8%, and 38%, respectively. Conclusion GTV volume and radiation dose are associated with time to metastasis and may be used to identify patients at higher risk of metastasis after lung SBRT

GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes

<p>Abstract</p> <p>Background</p> <p>Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine.</p> <p>Results</p> <p>We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework.</p> <p>Conclusions</p> <p>GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision-making. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.</p

A role for the collagen I/III and MMP-1/-13 genes in primary inguinal hernia?

BACKGROUND: Abnormal collagen metabolism is thought to play an important role in the development of primary inguinal hernia. This is underlined by detection of altered collagen metabolism and structural changes of the tissue in patients with primary inguinal hernia. However, it is still unknown whether these alterations reflect a basic dysfunction of the collagen synthesis, or of collagen degradation. METHODS: In the present study, we analysed type I and type III procollagen messenger ribonucleic acid (mRNA) and MMP-1 and MMP-13 mRNA in cultured fibroblasts from the skin of patients with primary inguinal hernia, and from patients without hernia (controls) by reverse transcription polymerase chain reaction (RT-PCR) and Northern Blot. RESULTS: The results indicated that the ratio of type I to type III procollagen mRNA was decreased in patients with primary hernia, showing significant differences as compared to controls (p = 0.01). This decrease was mainly due to the increase of type III procollagen mRNA. Furthermore, RT-PCR analysis revealed that the expression of MMP-1 mRNA in patients with primary hernia is equivalent to that of controls (p > 0.05). In addition, MMP-13 mRNA is expressed neither in patients with primary hernia nor in controls. CONCLUSION: We concluded that abnormal change of type I and type III collagen mRNAs contribute to the development of primary inguinal hernia, whereas the expressions of MMP-1 and MMP-13 mRNA appears not to be involved in the development of primary inguinal hernia. Thus, the knowledge on the transcriptional regulation of collagen in patients with primary inguinal hernia may help to understand the pathogenesis of primary inguinal hernia, and implies new therapeutic strategies for this disease

Molecular biology of breast cancer metastasis: Genetic regulation of human breast carcinoma metastasis

The present is an overview of recent data that describes the genetic underpinnings of the suppression of cancer metastasis. Despite the explosion of new information about the genetics of cancer, only six human genes have thus far been shown to suppress metastasis functionally. Not all have been shown to be functional in breast carcinoma. Several additional genes inhibit various steps of the metastatic cascade, but do not necessarily block metastasis when tested using in vivo assays. The implications of this are discussed. Two recently discovered metastasis suppressor genes block proliferation of tumor cells at a secondary site, offering a new target for therapeutic intervention

APRIL is overexpressed in cancer: link with tumor progression

<p>Abstract</p> <p>Background</p> <p>BAFF and APRIL share two receptors – TACI and BCMA – and BAFF binds to a third receptor, BAFF-R. Increased expression of BAFF and APRIL is noted in hematological malignancies. BAFF and APRIL are essential for the survival of normal and malignant B lymphocytes, and altered expression of BAFF or APRIL or of their receptors (BCMA, TACI, or BAFF-R) have been reported in various B-cell malignancies including B-cell non-Hodgkin's lymphoma, chronic lymphocytic leukemia, Hodgkin's lymphoma, multiple myeloma, and Waldenstrom's macroglobulinemia.</p> <p>Methods</p> <p>We compared the expression of <it>BAFF, APRIL, TACI and BAFF-R </it>gene expression in 40 human tumor types – brain, epithelial, lymphoid, germ cells – to that of their normal tissue counterparts using publicly available gene expression data, including the Oncomine Cancer Microarray database.</p> <p>Results</p> <p>We found significant overexpression of <it>TACI </it>in multiple myeloma and thyroid carcinoma and an association between TACI expression and prognosis in lymphoma. Furthermore, <it>BAFF and APRIL </it>are overexpressed in many cancers and we show that <it>APRIL </it>expression is associated with tumor progression. We also found overexpression of at least one proteoglycan with heparan sulfate chains (HS), which are coreceptors for APRIL and TACI, in tumors where APRIL is either overexpressed or is a prognostic factor. APRIL could induce survival or proliferation directly through HS proteoglycans.</p> <p>Conclusion</p> <p>Taken together, these data suggest that APRIL is a potential prognostic factor for a large array of malignancies.</p

Identification of Novel SNPs in Glioblastoma Using Targeted Resequencing

High-throughput sequencing opens avenues to find genetic variations that may be indicative of an increased risk for certain diseases. Linking these genomic data to other “omics” approaches bears the potential to deepen our understanding of pathogenic processes at the molecular level. To detect novel single nucleotide polymorphisms (SNPs) for glioblastoma multiforme (GBM), we used a combination of specific target selection and next generation sequencing (NGS). We generated a microarray covering the exonic regions of 132 GBM associated genes to enrich target sequences in two GBM tissues and corresponding leukocytes of the patients. Enriched target genes were sequenced with Illumina and the resulting reads were mapped to the human genome. With this approach we identified over 6000 SNPs, including over 1300 SNPs located in the targeted genes. Integrating the genome-wide association study (GWAS) catalog and known disease associated SNPs, we found that several of the detected SNPs were previously associated with smoking behavior, body mass index, breast cancer and high-grade glioma. Particularly, the breast cancer associated allele of rs660118 SNP in the gene SART1 showed a near doubled frequency in glioblastoma patients, as verified in an independent control cohort by Sanger sequencing. In addition, we identified SNPs in 20 of 21 GBM associated antigens providing further evidence that genetic variations are significantly associated with the immunogenicity of antigens

Gene expression profiling of gliomas: merging genomic and histopathological classification for personalised therapy

The development of DNA microarray technologies over the past decade has revolutionised translational cancer research. These technologies were originally hailed as more objective, comprehensive replacements for traditional histopathological cancer classification systems, based on microscopic morphology. Although DNA microarray-based gene expression profiling (GEP) remains unlikely in the near term to completely replace morphological classification of primary brain tumours, specifically the diffuse gliomas, GEP has confirmed that significant molecular heterogeneity exists within the various morphologically defined gliomas, particularly glioblastoma (GBM). Herein, we provide a 10-year progress report on human glioma GEP, with focus on development of clinical diagnostic tests to identify molecular subtypes, uniquely responsive to adjuvant therapies. Such progress may lead to a more precise classification system that accurately reflects the cellular, genetic, and molecular basis of gliomagenesis, a prerequisite for identifying subsets uniquely responsive to specific adjuvant therapies, and ultimately in achieving individualised clinical care of glioma patients