Assessment of a Novel VEGF Targeted Agent Using Patient-Derived Tumor Tissue Xenograft Models of Colon Carcinoma with Lymphatic and Hepatic Metastases

The lack of appropriate tumor models of primary tumors and corresponding metastases that can reliably predict for response to anticancer agents remains a major deficiency in the clinical practice of cancer therapy. It was the aim of our study to establish patient-derived tumor tissue (PDTT) xenograft models of colon carcinoma with lymphatic and hepatic metastases useful for testing of novel molecularly targeted agents. PDTT of primary colon carcinoma, lymphatic and hepatic metastases were used to create xenograft models. Hematoxylin and eosin staining, immunohistochemical staining, genome-wide gene expression analysis, pyrosequencing, qRT-PCR, and western blotting were used to determine the biological stability of the xenografts during serial transplantation compared with the original tumor tissues. Early passages of the PDTT xenograft models of primary colon carcinoma, lymphatic and hepatic metastases revealed a high degree of similarity with the original clinical tumor samples with regard to histology, immunohistochemistry, genes expression, and mutation status as well as mRNA expression. After we have ascertained that these xenografts models retained similar histopathological features and molecular signatures as the original tumors, drug sensitivities of the xenografts to a novel VEGF targeted agent, FP3 was evaluated. In this study, PDTT xenograft models of colon carcinoma with lymphatic and hepatic metastasis have been successfully established. They provide appropriate models for testing of novel molecularly targeted agents

Sensing the multi-scale landscape functions heterogeneity by big geodata from parcel to urban agglomerations-a case of the Greater Bay Area, China

ABSTRACTMulti-scale landscape functions play a critical role in revealing intricate functional structures within large regions. However, previous studies on landscape functions have predominantly focused on a single macro or micro scale, impeding a holistic multi-scale understanding of the spatial distribution and heterogeneity of landscape functions. To address this gap, this study proposes a framework leveraging the power of big geodata to mine multi-scale landscape functions from parcel to entire urban agglomerations, as well as non-administrative divisions. Our study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. Firstly, we integrated multi-source big geodata to derive parcel-scale landscape functions. Subsequently, we employed the Normalized Revealed Comparative Advantage index to derive landscape functions at broader scales, including towns, counties and cities. The effectiveness of our approach is validated through in-field investigations and comparisons with established policy planning positions. The outcomes not only offer distinctive planning insights at various scales but also highlight the versatility of big geodata in extracting landscape functions across scales. This study demonstrates that big geodata is adept at uncovering multi-scale landscape functions irrespective of administrative boundaries, providing valuable insights for fostering multi-scale regional coordinated development

Searching Missing Proteins Based on the Optimization of Membrane Protein Enrichment and Digestion Process

A membrane protein enrichment method composed of ultracentrifugation and detergent-based extraction was first developed based on MCF7 cell line. Then, in-solution digestion with detergents and eFASP (enhanced filter-aided sample preparation) with detergents were compared with the time-consuming in-gel digestion method. Among the in-solution digestion strategies, the eFASP combined with RapiGest identified 1125 membrane proteins. Similarly, the eFASP combined with sodium deoxycholate identified 1069 membrane proteins; however, the in-gel digestion characterized 1091 membrane proteins. Totally, with the five digestion methods, 1390 membrane proteins were identified with ≥1 unique peptides, among which 1345 membrane proteins contain unique peptides ≥2. This is the biggest membrane protein data set for MCF7 cell line and even breast cancer tissue samples. Interestingly, we identified 13 unique peptides belonging to 8 missing proteins (MPs). Finally, eight unique peptides were validated by synthesized peptides. Two proteins were confirmed as MPs, and another two proteins were candidate detections

Baicalein Accelerates Tendon-Bone Healing via Activation of Wnt/β-Catenin Signaling Pathway in Rats

Background. Tendon-bone healing is a reconstructive procedure which requires a tendon graft healing to a bone tunnel or to the surface of bone after the junction injury between tendon, ligament, and bone. The surgical reattachment of tendon to bone often fails due to regeneration failure of the specialized tendon-bone junction. Materials and Methods. An extra-articular tendon-bone healing rat model was established to discuss the effect of the baicalein 10 mg/(kg·d) in accelerating tendon-bone healing progress. Also, tendon-derived stem cells (TDSCs) were treated with various concentrations of baicalein or dickkopf-1 (DKK-1) to stimulate differentiation for 14 days. Results. In vivo, tendon-bone healing strength of experiment group was obviously stronger than the control group in 3 weeks as well as in 6 weeks. And there were more mature fibroblasts, more Sharpey fibers, and larger new bone formation area treated intragastrically with baicalein compared with rats that were treated with vehicle for 3 weeks and 6 weeks. In vitro, after induction for 14 days, the expressions of osteoblast differentiation markers, that is, alkaline phosphatase (ALP), runt-related transcription factor 2 (Runx2), osteocalcin (OCN), osterix (OSX), and collagen I, were upregulated and Wnt/β-catenin signaling pathway was enhanced in TDSCs. The effect of DKK-1 significantly reduced the effect of baicalein on the osteogenic differentiation. Conclusion. These data suggest that baicalein may stimulate TDSCs osteogenic differentiation via activation of Wnt/β-catenin signaling pathway to accelerate tendon-bone healing

Deep Coverage Proteomics Identifies More Low-Abundance Missing Proteins in Human Testis Tissue with Q‑Exactive HF Mass Spectrometer

Since 2012, missing proteins (MPs) investigation has been one of the critical missions of Chromosome-Centric Human Proteome Project (C-HPP) through various biochemical strategies. On the basis of our previous testis MPs study, faster scanning and higher resolution mass-spectrometry-based proteomics might be conducive to MPs exploration, especially for low-abundance proteins. In this study, Q-Exactive HF (HF) was used to survey proteins from the same testis tissues separated by two separating methods (tricine- and glycine-SDS-PAGE), as previously described. A total of 8526 proteins were identified, of which more low-abundance proteins were uniquely detected in HF data but not in our previous LTQ Orbitrap Velos (Velos) reanalysis data. Further transcriptomics analysis showed that these uniquely identified proteins by HF also had lower expression at the mRNA level. Of the 81 total identified MPs, 74 and 39 proteins were listed as MPs in HF and Velos data sets, respectively. Among the above MPs, 47 proteins (43 neXtProt PE2 and 4 PE3) were ranked as confirmed MPs after verifying with the stringent spectra match and isobaric and single amino acid variants filtering. Functional investigation of these 47 MPs revealed that 11 MPs were testis-specific proteins and 7 MPs were involved in spermatogenesis process. Therefore, we concluded that higher scanning speed and resolution of HF might be factors for improving the low-abundance MP identification in future C-HPP studies. All mass-spectrometry data from this study have been deposited in the ProteomeXchange with identifier PXD004092

Special Enrichment Strategies Greatly Increase the Efficiency of Missing Proteins Identification from Regular Proteome Samples

As part of the Chromosome-Centric Human Proteome Project (C-HPP) mission, laboratories all over the world have tried to map the entire missing proteins (MPs) since 2012. On the basis of the first and second Chinese Chromosome Proteome Database (CCPD 1.0 and 2.0) studies, we developed systematic enrichment strategies to identify MPs that fell into four classes: (1) low molecular weight (LMW) proteins, (2) membrane proteins, (3) proteins that contained various post-translational modifications (PTMs), and (4) nucleic acid-associated proteins. Of 8845 proteins identified in 7 data sets, 79 proteins were classified as MPs. Among data sets derived from different enrichment strategies, data sets for LMW and PTM yielded the most novel MPs. In addition, we found that some MPs were identified in multiple-data sets, which implied that tandem enrichments methods might improve the ability to identify MPs. Moreover, low expression at the transcription level was the major cause of the “missing” of these MPs; however, MPs with higher expression level also evaded identification, most likely due to other characteristics such as LMW, high hydrophobicity and PTM. By combining a stringent manual check of the MS₂ spectra with peptides synthesis verification, we confirmed 30 MPs (neXtProt PE2 ∼ PE4) and 6 potential MPs (neXtProt PE5) with authentic MS evidence. By integrating our large-scale data sets of CCPD 2.0, the number of identified proteins has increased considerably beyond simulation saturation. Here, we show that special enrichment strategies can break through the data saturation bottleneck, which could increase the efficiency of MP identification in future C-HPP studies. All 7 data sets have been uploaded to ProteomeXchange with the identifier PXD002255