Proteomic analysis of apoptosis induction in human lung cancer cells by recombinant MVL

Cyanometabolites: molecules with immense antiviral potential

Cyanometabolites are active compounds derived from cyanobacteria that include small low molecular weight peptides, oligosaccharides, lectins, phenols, fatty acids, and alkaloids. Some of these compounds may pose a threat to human and environment. However, majority of them are known to have various health benefits with antiviral properties against pathogenic viruses including Human immunodeficiency virus (HIV), Ebola virus (EBOV), Herpes simplex virus (HSV), Influenza A virus (IAV) etc. Cyanometabolites classified as lectins include scytovirin (SVN), Oscillatoria agardhii agglutinin (OAAH), cyanovirin-N (CV-N), Microcystis viridis lectin (MVL), and microvirin (MVN) also possess a potent antiviral activity against viral diseases with unique properties to recognize different viral epitopes. Studies showed that a small linear peptide, microginin FR1, isolated from a water bloom of Microcystis species, inhibits angiotensin-converting enzyme (ACE), making it useful for the treatment of coronavirus disease 2019 (COVID-19). Our review provides an overview of the antiviral properties of cyanobacteria from the late 90s till now and emphasizes the significance of their metabolites in combating viral diseases, particularly severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has received limited attention in previous publications. The enormous medicinal potential of cyanobacteria is also emphasized in this review, which justifies their use as a dietary supplement to fend off pandemics in future.

Identifying complex gene-gene interactions: a mixed kernel omnibus testing approach

Genes do not function independently; rather, they interact with each other to fulfill their joint tasks. Identification of gene-gene interactions has been critically important in elucidating the molecular mechanisms responsible for the variation of a phenotype. Regression models are commonly used to model the interaction between two genes with a linear product term. The interaction effect of two genes can be linear or nonlinear, depending on the true nature of the data. When nonlinear interactions exist, the linear interaction model may not be able to detect such interactions; hence, it suffers from substantial power loss. While the true interaction mechanism (linear or nonlinear) is generally unknown in practice, it is critical to develop statistical methods that can be flexible to capture the underlying interaction mechanism without assuming a specific model assumption. In this study, we develop a mixed kernel function which combines both linear and Gaussian kernels with different weights to capture the linear or nonlinear interaction of two genes. Instead of optimizing the weight function, we propose a grid search strategy and use a Cauchy transformation of the P-values obtained under different weights to aggregate the P-values. We further extend the two-gene interaction model to a high-dimensional setup using a de-biased LASSO algorithm. Extensive simulation studies are conducted to verify the performance of the proposed method. Application to two case studies further demonstrates the utility of the model. Our method provides a flexible and computationally efficient tool for disentangling complex gene-gene interactions associated with complex traits.

Anticancer potentiality and mode of action of low-carbohydrate proteins and peptides from mushrooms

Severe side effects of chemotherapy as well as drug resistance highlight the ongoing need to discover novel natural bioactive compounds with anticancer potentiality. Mushroom-derived proteins are among the naturally occurring compounds that have been the subject of a body of research on their potentiality in cancer therapy. The greatest attention in relevant review articles has been paid to well-known mushroom-derived glycoproteins such as lectins and protein-bound polysaccharide complexes such as polysaccharide-K (PSK) or krestin and polysaccharopeptide (PSP), which contain substantial amounts of carbohydrates (50-90%). These complex compounds exert their anticancer activity mainly by binding to cell membranes leading to extrinsic (death receptor) apoptosis or intrinsic (mitochondrial) apoptotic pathways. However, several other research studies have reported pure, well-characterized, proteins or peptides from mushrooms, which are carbohydrate-free or have very low amounts of carbohydrate. These proteins may fall into four categories including fungal immunomodulatory proteins, ubiquitin-like proteins, enzymes, and unclassified proteins. Well-defined chemical structure, elucidated full amino acid or N-terminal sequences, purity, and having some distinct and specific pathways compared to glycoproteins have made these low-carbohydrate proteins attractive for cancer research. The aim of this review was therefore to improve the current understanding of mushroom-derived low-carbohydrate proteins and to consolidate the existing knowledge of the most promising mushroom species from which low-carbohydrate proteins have been derived, characterized, and examined for their anticancer activity. In addition, molecular targets and mechanisms of action of these proteins have been discussed. Key points • Mushroom-derived low-carbohydrate proteins lack or have low carbohydrate. • Low-carbohydrate proteins show potent anticancer activities in vitro and in vivo. • There are specific pathways for low-carbohydrate proteins to inhibit cancer cells.

Single Cell Proteomics for Molecular Targets in Lung Cancer: High-Dimensional Data Acquisition and Analysis

In the proteomic and genomic era, lung cancer researchers are increasingly under challenge with traditional protein analyzing tools. High output, multiplexed analytical procedures are in demand for disclosing the post-translational modification, molecular interactions and signaling pathways of proteins precisely, specifically, dynamically and systematically, as well as for identifying novel proteins and their functions. This could be better realized by single-cell proteomic methods than conventional proteomic methods. Using single-cell proteomic tools including flow cytometry, mass cytometry, microfluidics and chip technologies, chemical cytometry, single-cell western blotting, the quantity and functions of proteins are analyzed simultaneously. Aside from deciphering disease mechanisms, single-cell proteomic techniques facilitate the identification and screening of biomarkers, molecular targets and promising compounds as well. This review summarized single-cell proteomic tools and their use in lung cancer.

Data from a comparative proteomic analysis of tumor-derived lung-cancer CD105(+) endothelial cells

Increasing evidence indicates that tumor-derived endothelial cells (TECs) are more relevant for the study of tumor angiogenesis and for screening antiangiogenic drugs than normal ECs (NECs). In this data article, high-purity (>98%) primary CD105⁺ NECs and TECs purified from a mouse Lewis lung carcinoma model bearing 0.5 cm tumors were identified using 2D-PAGE and Matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS). All the identified proteins were categorized functionally by Gene Ontology (GO) analysis, and gene-pathway annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, protein–protein interaction networks were also built. The proteomics and bioinformatics data presented here provide novel insights into the molecular characteristics and the early modulation of the TEC proteome in the tumor microenvironment.

Identification and verification of transgelin-2 as a potential biomarker of tumor-derived lung-cancer endothelial cells by comparative proteomics

To investigate heterogeneity of endothelial cells (ECs) in the tumor microenvironment and biomarkers for antitumor angiogenesis therapy, high-purity (>98%) normal (NECs) and tumor-derived CD105(+) ECs (TECs) were purified from a mouse Lewis lung carcinoma model bearing 0.5 cm tumors by immunomagnetic separation. Proteomics analysis revealed that 48 proteins (28 upregulated and 20 downregulated) were differentially regulated by at least 1.5-fold in TECs, and that these proteins were involved in metabolism, energy pathways, protein folding, cell growth and/or functioned as structural constituents of the cytoskeleton. Upregulation of heat shock protein 60 (Hspd1) and transgelin-2 (Tagln2) was revealed in TECs, and by immunohistochemistry (IHC) in paired tissues from 30 consecutive lung cancer (LC) patients. Higher expression levels of Hspd1, Tagln2 were detected in microvascular ECs of paratumor and tumor tissues than in paired normal counterparts. Stronger Tagln2 staining was associated with clinical stage, tumor size, and histological neural invasion. Higher Hspd1 (area under the curve [AUC], 0.82) and lower Tagln2 (AUC, 0.90) levels were detected in LC patient sera. Pearson correlation analysis revealed a positive correlation between serum Hspd1 and Tagln2 levels. In conclusion, higher Tagln2 levels were associated with tumor development, lymph node metastasis, and neural invasion in LC and may thus serve as a potential biomarker of tumor angiogenesis.

SIGNIFICANCE

High-purity endothelial cells (normal and tumor derived) were prepared to characterize ECs heterogeneity in the tumor microenvironment and to explore biomarkers of early stages of tumor development by proteomics. Candidate proteins Hspd1 and Tagln2, were further verification in the sera and tumor tissues of lung cancer patients. Moreover, higher Tagln2 was significantly associated with clinical tumor development, metastasis, and neural invasion. All these results indicated a crucial role for Tagln2 in TECs for tumor development and metastasis.

Label-free quantitative mass spectrometry reveals a panel of differentially expressed proteins in colorectal cancer

To identify potential biomarkers involved in CRC, a shotgun proteomic method was applied to identify soluble proteins in three CRCs and matched normal mucosal tissues using high-performance liquid chromatography and mass spectrometry. Label-free protein profiling of three CRCs and matched normal mucosal tissues were then conducted to quantify and compare proteins. Results showed that 67 of the 784 identified proteins were linked to CRC (28 upregulated and 39 downregulated). Gene Ontology and DAVID databases were searched to identify the location and function of differential proteins that were related to the biological processes of binding, cell structure, signal transduction, cell adhesion, and so on. Among the differentially expressed proteins, tropomyosin-3 (TPM3), endoplasmic reticulum resident protein 29 (ERp29), 18 kDa cationic antimicrobial protein (CAMP), and heat shock 70 kDa protein 8 (HSPA8) were verified to be upregulated in CRC tissue and seven cell lines through western blot analysis. Furthermore, the upregulation of TPM3, ERp29, CAMP, and HSPA8 was validated in 69 CRCs byimmunohistochemistry (IHC) analysis. Combination of TPM3, ERp29, CAMP, and HSPA8 can identify CRC from matched normal mucosal achieving an accuracy of 73.2% using IHC score. These results suggest that TPM3, ERp29, CAMP, and HSPA8 are great potential IHC diagnostic biomarkers for CRC.