Citations

The process by which tumor cells mechanically invade through surrounding stroma into peripheral tissues is an essential component of metastatic dissemination. The directed recruitment of the metalloproteinase MT1-MMP to invadopodia plays a critical role in this invasive process. Here, we provide mechanistic insight into MT1-MMP cytoplasmic tail binding protein 1 (MTCBP-1) with respect to invadopodia formation, matrix remodeling, and invasion by pancreatic tumor cells. MTCBP-1 localizes to invadopodia and interacts with MT1-MMP. We find that this interaction displaces MT1-MMP from invadopodia, thereby attenuating their number and function and reducing the capacity of tumor cells to degrade matrix. Further, we observe an inverse correlation between MTCBP-1 and MT1-MMP expression both in cultured cell lines and human pancreatic tumors. Consistently, MTCBP-1–expressing cells show decreased ability to invade in vitro and metastasize in vivo. These findings implicate MTCBP-1 as an inhibitor of the metastatic process.

ABSTRACT The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell‐released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV‐associated functional activities. Finally, a checklist is provided with summaries of key points.

Intracellular delivery is a critical step in biological discoveries and has been widely utilized in biomedical research. A variety of molecular tools have been developed for cell-based gene therapies, including FDA approved CAR-T immunotherapy, iPSC, cell reprogramming and gene editing. Despite the inspiring results of these applications, intracellular delivery of foreign molecules including nucleic acids and proteins remains challenging. Efficient yet non-invasive delivery of biomolecules in a high-throughput manner has thus long fascinates the scientific community. As one of the most popular non-viral technologies for cell transfection, electroporation has gone through enormous development with the assist of nanotechnology and microfabrication. Emergence of miniatured electroporation system brought up many merits over the weakness of traditional electroporation system, including precise dose control and high cell viability. These new generation of electroporation systems are of considerable importance to expand the biological applications of intracellular delivery, bypassing the potential safety issue of viral vectors. In this review, we will go over the recent progresses in the electroporation-based intracellular delivery and several potential applications of cutting-edge research on the miniatured electroporation, including gene therapy, cellular reprogramming and intracellular probe.

Abstract The clinical success of immune checkpoint inhibitors in treating metastatic and refractory cancers has generated significant interest in investigating their role in treating locally advanced diseases, thus requiring them to be combined with standard treatments in the hope of producing synergistic antitumor responses. Radiotherapy, in particular, has long been hypothesized to have actions complementary to those of immune checkpoint blockade, and a growing body of evidence indicates that cancer immunotherapy may also have radiosensitizing effects, which would provide unique benefit for locoregional treatments. Recent studies have demonstrated that when immune cells are activated by immunotherapeutics, they can reprogram the tumor microenvironment in ways that may potentially increase the radiosensitivity of the tumor. In this review, we highlight the evidence that supports reciprocal interactions between cancer immunotherapy and radiotherapy, where in addition to the traditional notion that radiation serves to enhance the activation of antitumor immunity, an alternative scenario also exists in which T-cell activation by cancer immunotherapy may sensitize tumors to radiation treatment through mechanisms that include normalization of the tumor vasculature and tissue hypoxia. We describe the empirical observations from preclinical models that support such effects and discuss their implications for future research and trial design.

Background: Due to its ability to provide quantitative and dynamic information on tumor genesis and development by directly profiling protein expression, the proteomics has become intensely popular for characterizing the functional proteins driving the transformation of malignancy, tracing the large-scale protein alterations induced by anticancer drug, and discovering the innovative targets and first-in-class drugs for oncologic disorders. Objective: To quantify cancer proteomics data, the label-free quantification (LFQ) is frequently employed. However, low precision, poor reproducibility and inaccuracy of the LFQ of proteomics data have been recognized as the key “technical challenge” in the discovery of anticancer targets and drugs. In this paper, the recent advances and development in the computational perspective of LFQ in cancer proteomics were therefore systematically reviewed and analyzed. Methods: PubMed and Web of Science database were searched for label-free quantification approaches, cancer proteomics and computational advances. Results: First, a variety of popular acquisition techniques and state-of-the-art quantification tools are systematically discussed and critically assessed. Then, many processing approaches including transformation, normalization, filtering and imputation are subsequently discussed, and their impacts on improving LFQ performance of cancer proteomics are evaluated. Finally, the future direction for enhancing the computation-based quantification technique for cancer proteomics are also proposed. Conclusion: There is a dramatic increase in LFQ approaches in recent year, which significantly enhance the diversity of the possible quantification strategies for studying cancer proteomics.

Abstract Context Previous epidemiological studies had inconsistent results regarding the relationship between blood lead level (BLL) and adiposity. Objective We aimed to investigate the associations of BLL with body mass index (BMI) particularly using Mendelian randomization analyses and examine the interaction between obesity-predisposing genes and BLL on the associations. Design and Setting A total of 3922 participants were enrolled from 16 sites in East China in 2014 from the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors (ChiCTR-ECS-14005052, www.chictr.org.cn). We calculated the weighted BMI genetic risk score (GRS) based on 29 variants that were identified and validated in East Asians. BLL was measured by atomic absorption spectrometry. Main Outcome Measure BMI was calculated, and BMI ≥25 kg/m2 was defined as overweight. Results Multivariable logistic regression analysis demonstrated significant associations between BMI with each unit increase in lnBLL (β = 0.24; 95% CI, 0.08 to 0.40; P < 0.001) and each 1-point increase in BMI-GRS (β = 0.08; 95% CI, 0.05 to 0.11; P < 0.001). The causal regression coefficients of genetically determined BMI for lnBLL were −0.003 (95% CI, −0.075 to 0.070), which showed no significance. The GRS modified the association of BLL with BMI and overweight (BMI ≥25 kg/m2; P for interaction = 0.031 and 0.001, respectively). Each unit of lnBLL was associated with 63% higher odds of overweight (OR 1.63; 95% CI, 1.30 to 2.05) in the highest quartile of GRS, but no significant associations were found in the lower three quartiles. Conclusions The associations of BLL with BMI and overweight (BMI ≥25 kg/m2) were significantly modulated by BMI genetic susceptibility.

e15626 Background: FGFR2 fusions are found in 10-15% of intrahepatic cholangiocarcinomas. Individuals with FGFR2 fusions have a better prognosis and more indolent natural history. More recently FGFR2 fusions have been described as a predictive marker for tyrosine kinase inhibitors targeting the FGFR2 pathway. Texture analysis from CT imaging has been used in the past to estimate degree of fibrosis and angiogenesis in various tumors types; however, texture analysis has not been used in the past to detect FGFR2 rearrangements. Methods: This is a retrospective study of 33 patients with intrahepatic cholangiocarcinoma who were previously tested for FGFR2 fusions with either a FISH break apart assay or with clinically available next generation sequencing assays. All patients had a contrast enhanced CT performed. To address physiological and pathological variations, matched-size regions of interest (ROIs) over areas of non-necrotic tumor and unaffected liver during the portal venous phase were drawn. The paired ROIs for each patient were then processed via an imaging analytic pipeline for (1) ROI normalization, (2) texture panel creation, and (3) machine learning predictive model development. Results: Fifteen patients with FGFR2 fusions and 18 patients without FGFR2 fusions were included in the study. Using the developed predictive model, accurate FGFR2 fusion classification in 90% of cases was achieved (sensitivity = 87%, specificity = 94%). Conclusions: Utilizing advanced analytics with machine learning techniques, multi-textural data obtained from conventional CT images has the capability to detect genetic aberrations in intrahepatic cholangiocarcinoma, including FGFR2 gene fusions. Radiogenomic evaluation has several attractive benefits including the cost effective and expeditious detection of actionable mutations such as FGFR2 fusions as well as avoidance of invasive procedures such as percutaneous core biopsies. [Table: see text]