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Loss of Cadherin-11 in pancreatic ductal adenocarcinoma alters tumor-immune microenvironment
Pancreatic ductal adenocarcinoma (PDAC) is one of the top five deadliest forms of cancer with very few treatment options. The 5-year survival rate for PDAC is 10% following diagnosis. Cadherin 11 (Cdh11), a cell-to-cell adhesion molecule, has been suggested to promote tumor growth and immunosuppression in PDAC, and Cdh11 inhibition significantly extended survival in mice with PDAC. However, the mechanisms by which Cdh11 deficiency influences PDAC progression and anti-tumor immune responses have yet to be fully elucidated. To investigate Cdh11-deficiency induced changes in PDAC tumor microenvironment (TME), we crossed p48-Cre; LSL-Kras G12D/+ ; LSLTrp53 R172H/+ (KPC) mice with Cdh11 +/- mice and performed single-cell RNA sequencing (scRNA-seq) of the non-immune (CD45 - ) and immune (CD45 + ) compartment of KPC tumor-bearing Cdh11 proficient (KPC-Cdh11 +/+ ) and Cdh11 deficient (KPC-Cdh11 +/- ) mice. Our analysis showed that Cdh11 is expressed primarily in cancer-associated fibroblasts (CAFs) and at low levels in epithelial cells undergoing epithelial-to-mesenchymal transition (EMT). Cdh11 deficiency altered the molecular profile of CAFs, leading to a decrease in the expression of myofibroblast markers such as Acta2 and Tagln and cytokines such as Il6, Il33 and Midkine (Mdk). We also observed a significant decrease in the presence of monocytes/macrophages and neutrophils in KPC-Cdh11 +/- tumors while the proportion of T cells was increased. Additionally, myeloid lineage cells from Cdh11-deficient tumors had reduced expression of immunosuppressive cytokines that have previously been shown to play a role in immune suppression. In summary, our data suggests that Cdh11 deficiency significantly alters the fibroblast and immune microenvironments and contributes to the reduction of immunosuppressive cytokines, leading to an increase in anti-tumor immunity and enhanced survival.
Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma
Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC.
Terahertz time-domain spectroscopy imaging of pancreatic ductal adenocarcinoma tissues
Pancreatic ductal adenocarcinoma (PDAC) ranks among the malignancies with the highest fatality and morbidity rates. This is predominantly attributable to an absence of understanding the intricate and diverse microenvironment of the tumor. We use terahertz time-domain spectroscopy (THz-TDS) imaging in transmission geometry to probe ex-vivo the heterogenous microenvironment of the genetically modified murine PDAC tissue that closely resembles the PDAC heterogeneity in human malignancy. We introduced a maximum a-posteriori probability estimation algorithm to objectively the tumor’s heterogenous microenvironment using the average values of refractive index and absorption coefficient within the useable terahertz bandwidth as imaging markers. Furthermore, direct comparison of stained histopathologic images and the refractive index and the absorption coefficient high-resolution, two dimensional maps of the same PDAC samples confirms the high potential of the THz-TDS method for tumor tissue characterization.
Deep near-infrared survey of the Southern Sky (DENIS)
DENIS (Deep Near-Infrared Survey of the Southern Sky) will be the first complete census of astronomical sources in the near-infrared spectral range. The challenges of this novel survey are both scientific and technical. Phenomena radiating in the near-infrared range from brown dwarfs to galaxies in the early stages of cosmological evolution, the scientific exploitation of data relevant over such a wide range requires pooling expertise from several of the leading European astronomical centers. The technical challenges of a project which will provide an order of magnitude more sources than given by the IRAS space mission, and which will involve advanced data-handling and image-processing techniques, likewise require pooling of hardware and software resources, as well as of human expertise. The DENIS project team is composed of some 40 scientists, computer specialists, and engineers located in 5 European Community countries (France, Germany, Italy, The Netherlands, and Spain), with important contributions from specialists in Australia, Brazil, Chile, and Hungary. DENIS will survey the entire southern sky in 3 colors, namely in the I band at a wavelength of 0.8 micron, in the 1.25 micron J band, and in the 2.15 micron K' band. The sensitivity limits will be 18th magnitude in the I band, 16th in the J band, and 14.5th in the K' band. The angular resolution achieved will be 1 arcsecond in the I band, and 3.0 arcseconds in the J and K' bands. The European Southern Observatory 1 m telescope on La Silla will be dedicated to survey use during operations expected to last four years, commencing in late 1993. DENIS aims to provide the astronomical community with complete digitized infrared images of the full southern sky and a catalogue of extracted objects, both of the best quality and in readily accessible form. This will be achieved through dedicated software packages and specialized catalogues, and with assistance from the Leiden and Paris Data Analysis Centers. The data will be mailed on DAT tapes from La Silla to the two Data Analysis Centers for further processing. Two centers are necessary because of the shear quantity of data and because of the complementary roles the Centers will develop, each exploiting its own particular expertise. The Leiden Data Analysis Center (LDAC) will extract objects, establish their parameters, and archive them into a source catalogue. The LDAC will collaborate with the Groningen Space Research group that has gained experience in infrared image handling from the IRAS satellite. The Paris Data Analysis Center (PDAC) will be responsible for archiving and preprocessing the raw data to provide a homogeneous set of data suitable for further reduction in both the Leiden and Paris data analysis streams. The PDAC will also extract and archive images for the sources flagged by the LDAC as extended, and create a catalogue of galaxies. In exploiting the DENIS data we foresee the collaboration with other data analysis centers, such as the Observatoire de Lyon where the relevant DENIS catalogue of galaxies can be incorporated into their extragalactic database. The Point Sources and the Small Extended Sources catalogues could be incorporated in the Late Type Star database at Montpellier, and in the SIMBAD database as CDS. At Groningen the IRAS Point Source catalogue and/or image data can be merged with the DENIS catalogues. At Meudon algorithms and software will be developed with main goal assessing the limits reachable for the homogeneity and intrinsic consistency between the ensemble of the images in the data base (flat-fielding, relative positioning of the fields, bootstrapped flux calibration) but also for the data analysis.
Spatiotemporal Adaptive Passive Direct Air Capture
Carbon Collect Inc., along with Arizona State University, the Electric Power Research Institute (EPRI), PM Group, and Trimeric Corporation, completed an initial design of a commercial-scale, passive direct air capture (DAC) system termed “carbon trees” that will capture, separate, and store at least 100,000 tonnes/year of carbon dioxide (CO2) from air (net basis). Passive DAC is unique among DAC technologies in that passive air delivery by wind avoids the energy penalty of forced convection. Carbon Collect Inc.’s sorbent-agnostic approach offers the flexibility to choose sorbents for a wide range of climates. A combination of steam, low-grade heat, and vacuum releases the CO2 from the sorbent, which is extracted from the chamber and purified and compressed for geological storage. A commercial carbon tree forest combines the output of several thousand trees for compression and purification with high heat and energy integration. The project team prepared an initial engineering design package for each of three geographically diverse host sites throughout the United States to better understand the effect of local/regional ambient conditions on DAC system performance and project costs. A techno-economic analysis, life cycle analysis, business case analysis, and an environmental, health, and safety risks assessment were also completed for each of the three geographically diverse host sites.