MT1-matrix metalloproteinase (MT1-MMP) is one of the most critical factors in the invasion machinery of tumor cells. Subcellular localization to invasive structures is key for MT1-MMP proinvasive activity. However, the mechanism driving this polarized distribution remains obscure. We now report that polarized exocytosis of MT1-MMP occurs during MDA-MB-231 adenocarcinoma cell migration into collagen type I three-dimensional matrices. Polarized trafficking of MT1-MMP is triggered by b1 integrin-mediated adhesion to collagen, and is required for protease localization at invasive structures. Localization of MT1-MMP within VSV-G/Rab8-positive vesicles, but not in Rab11/Tf/TfRc-positive compartment in invasive cells, suggests the involvement of the exocytic traffic pathway. Furthermore, constitutively active Rab8 mutants induce MT1-MMP exocytic traffic, collagen degradation and invasion, whereas Rab8-but not Rab11-knockdown inhibited these processes. Altogether, these data reveal a novel pathway of MT1-MMP redistribution to invasive structures, exocytic vesicle trafficking, which is crucial for its role in tumor cell invasiveness. Mechanistically, MT1-MMP delivery to invasive structures, and therefore its proinvasive activity, is regulated by Rab8 GTPase.

Tumor-derived exosomes are emerging as local and systemic cell-to-cell mediators of oncogenic information through the horizontal transfer of mRNAs, microRNAs and proteins during tumorigenesis. The exosomal content has been described as biologically active when taken up by the recipient cell. Identifying the specific molecular cargo of exosomes will help to determine their function in specific steps of the tumorigenic process. Here we evaluate whether ΔNp73 is selectively packaged in tumor-derived exosomes, its function in the acceptor cells in vitro and in vivo and its prognosis potential in cancer. ΔNp73 messenger is enriched in tumor-derived exosomes, suggesting its active sorting in these microvesicles. We observed the transmission of this exosome cargo to different cell types and how it confers proliferation potential and chemoresistance to the acceptor cells in vitro and in animal models. Finally, our data support the potential prognostic value of exosomal ΔNp73 in colon cancer patients.

No abstract

No abstract

APRIL (a proliferation-inducing ligand) is a cytokine of the tumor necrosis factor family associated mainly with hematologic malignancies. APRIL is also overexpressed in breast carcinoma tissue lesions, although neither its role in breast tumorigenesis nor the underlying molecular mechanism is known. Here, we show that several breast cancer cell lines express APRIL and both its receptors, B cell maturation antigen (BCMA) and transmembrane activator and CAML-interactor (TACI), independently of luminal or basal tumor cell phenotype, and that the mitogen-activated protein kinases p38, ERK1/2, and JNK1/2 are activated in response to APRIL. The inflammatory stimulus poly I:C, a toll-like receptor (TLR) 3 ligand, enhanced APRIL secretion. Silencing experiments decreased cell proliferation, demonstrating that APRIL is a critical autocrine factor for breast tumor growth. Studies of 4T1 orthotopic breast tumors in APRIL transgenic mice showed that an APRIL-enriched environment increased tumor growth and promoted lung metastasis associated with enhanced tumor cell proliferation; BCMA and TACI expression suggests that both participate in these processes. We detected APRIL, BCMA and TACI in human luminal, triple-negative breast carcinomas and HER2 breast carcinomas, with increased levels in more aggressive basal tumors. APRIL was observed near Ki67(+) nuclei and was distributed heterogeneously in the cancer cells, in the leukocyte infiltrate, and in the myoepithelial layer adjacent to the tumor area; these results imply that APRIL provides proliferation signals to tumor cells through paracrine and autocrine signaling. Our study identifies participation of APRIL signaling in breast cancer promotion; we propose impairment of this pathway as a potential therapeutic strategy.

BackgroundFingolimod is a functional sphingosine-1-phosphate antagonist approved for the treatment of multiple sclerosis (MS). Fingolimod affects lymphocyte subpopulations and regulates gene expression in the lymphocyte transcriptome. Translational studies are necessary to identify cellular and molecular biomarkers that might be used to predict the clinical response to the drug. In MS patients, we aimed to clarify the differential effects of fingolimod on T, B, and natural killer (NK) cell subsets and to identify differentially expressed genes in responders and non-responders (NRs) to treatment.Materials and methodsSamples were obtained from relapsing–remitting multiple sclerosis patients before and 6 months after starting fingolimod. Forty-eight lymphocyte subpopulations were measured by flow cytometry based on surface and intracellular marker analysis. Transcriptome sequencing by next-generation technologies was used to define the gene expression profiling in lymphocytes at the same time points. NEDA-3 (no evidence of disease activity) and NEDA-4 scores were measured for all patients at 1 and 2 years after beginning fingolimod treatment to investigate an association with cellular and molecular characteristics.ResultsFingolimod affects practically all lymphocyte subpopulations and exerts a strong effect on genetic transcription switching toward an anti-inflammatory and antioxidant response. Fingolimod induces a differential effect in lymphocyte subpopulations after 6 months of treatment in responder and NR patients. Patients who achieved a good response to the drug compared to NR patients exhibited higher percentages of NK bright cells and plasmablasts, higher levels of FOXP3, glucose phosphate isomerase, lower levels of FCRL1, and lower Expanded Disability Status Scale at baseline. The combination of these possible markers enabled us to build a probabilistic linear model to predict the clinical response to fingolimod.ConclusionMS patients responsive to fingolimod exhibit a recognizable distribution of lymphocyte subpopulations and a different pretreatment gene expression signature that might be useful as a biomarker.

BackgroundCirculating tumor DNA (ctDNA) levels correlate well with tumor bulk. In this paper we aim to estimate the prognostic value of the dynamic quantification of ctDNA levels.Materials and MethodsA total of 251 serial plasma samples from 41 non-small-cell lung cancer patients who carried an activating EGFR mutation were analysed by digital PCR. For survival analysis, ctDNA levels were computed as a time-dependent covariate.ResultsDynamic ctDNA measurements had prognostic significance (hazard ratio for overall survival and progression free survival according to p.T790M mutant allele frequency; 2.676 and 2.71 respectively; P < 0.05). In the same way, patients with p.T790M-negative or unchanging or decreasing plasma levels of sensitizing EGFR mutation were 12 and 4.8 times more likely to maintain response or stable disease, respectively, than patients in which the opposite occurred (P < 0.05).On average, the p.T790M mutation was detected in plasma 51 days before the assessment of progression disease by CT-scan. Finally, ctDNA outperformed CTCs for assessing tumor progression (P = 0.021).ConclusionsThe appearance or increase in a unit of the p.T790M allele frequency almost triples the risk of death and progression. This information can be used to design clinical trials aiming to estimate whether T790M positive patients should start second line treatment based on molecular data rather than imaging data.

We report a highly specific, sensitive, and robust method for analyzing fluorescence resonance energy transfer (FRET) based on spectral laser scanning confocal microscopy imaging. The lambda FRET (lambdaFRET) algorithm comprises imaging of a FRET sample at multiple emission wavelengths rendering a FRET spectrum, which is separated into its donor and acceptor components to obtain a pixel-based calculation of FRET efficiency. The method uses a novel off-line precalibration procedure for spectral bleed-through correction based on the acquisition of reference reflection images, which simplifies the method and reduces variability. LambdaFRET method was validated using structurally characterized FRET standards with variable linker lengths and stoichiometries designed for this purpose. LambdaFRET performed better than other well-established methods, such as acceptor photobleaching and sensitized emission-based methods, in terms of specificity, reproducibility, and sensitivity to distance variations. Moreover, lambdaFRET analysis was unaffected by high fluorochrome spectral overlap and cellular autofluorescence. The lambdaFRET method demonstrated outstanding performance in intra- and intermolecular FRET analysis in both fixed and live cell imaging studies.