Predicting survival in patients with buccal cancer: A study based on SEER database and external validation in China.

OBJECTIVE: Buccal mucosa cancer (BMC) is one of the most common oral cancers and has poor prognosis. The study aimed to develop and validate nomograms for predicting the 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) of BMC patients. METHODS: We collected and reviewed information on BMC patients diagnosed between 2004 and 2019 from the Surveillance Epidemiology and End Results database. Two nomograms were developed and validated to predict the OS and CSS based on predictors identified by univariate and multivariate Cox regression. An extra external validation was further performed using data from Sun Yat-sen Memorial Hospital (SYSMH). RESULTS: A total of 3154 BMC patients included in this study were randomly assigned to training and validation groups in a 2:1 ratio. Independent prognostic predictors were identified, confirmed, and fitted into nomograms for OS and CSS, respectively. The C-indices are 0.767 (Training group OS), 0.801 (Training group CSS), 0.763 (Validation group OS), and 0.781 (Validation group OS), respectively. Moreover, the nomograms exhibited remarkable precision in forecasting and significant clinical significance, as evidenced by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA). The final validation using our data from SYSMH also showed high accuracy and substantial clinical benefits within the nomograms. The C-indices are 0.849 (SYSMH group OS) and 0.916 (SYSMH group CSS). These indexes are better than tumor, node, and metastasis stage based on prediction results. CONCLUSIONS: The nomograms developed with great performance predicted 1-, 3-, and 5-year OS and CSS of BMC patients. Use of the nomograms in clinical practices shall bring significant benefits to BMC patients.

Study on Molecular Model Construction and Gas Adsorption Simulation of Anthracite in the Qinshui Basin.

Uncovering gas adsorption characteristics of coal at the molecular scale is of great theoretical significance for the study of gas occurrence, coalbed methane exploitation, and carbon dioxide sequestration. In this study, based on proximate analysis, ultimate analysis, 13C nuclear magnetic resonance, and Fourier-transform infrared spectroscopy experiments, the existence forms and relative contents of elements of anthracite in the Qinshui Basin were tested and analyzed, and a macromolecular structure model was constructed. Besides, three types of acidic oxygen-containing functional groups, namely, carboxyl groups, phenolic hydroxyl groups, and lactone groups, were added to the molecular model. Furthermore, CH4 adsorption simulation was conducted on the original molecular model of anthracite and models with three types of acidic functional groups added. The following research results were obtained. The molecular formula of the constructed macromolecular model of anthracite in the Qinshui Basin is C193H138N2O7. The molecular structure of coal becomes more compact and curved after structural optimization and annealing optimization. For the four models, the CH4 adsorption characteristics of coal molecules all conform to the Langmuir equation under the same simulation conditions. Among them, the original model has the largest CH4 adsorption capacity, while the addition of oxygen-containing functional groups reduces the CH4 adsorption capacity to varying extents. The reduction of CH4 adsorption capacity follows the order: adding carboxyl groups > adding phenolic hydroxyl groups > adding lactone groups, which is mainly attributed to the different adsorption heats and adsorptive potential wells triggered by the addition of acidic functional groups in molecules.

Enhanced nodulation and phosphorus acquisition from sparingly-soluble iron phosphate upon treatment with arbuscular mycorrhizal fungi in chickpea.

The coordination/trade-off among below-ground strategies for phosphorus (P) acquisition, including root morphology, carboxylate exudation and colonisation by arbuscular mycorrhizal fungi (AMF), is not well understood. This is the first study investigating the relationships between root nodulation, morphology, carboxylates and colonisation by an indigenous community of AMF under varying P levels and source. Two chickpea genotypes with contrasting amounts of rhizosheath carboxylates were grown in pots at six P levels (from 0 to 160 µg g-1 ) as KH2 PO4 (KP, highly soluble) or FePO4 (FeP, sparingly soluble), with or without AMF (±AMF) treatment. Under both FeP and KP, the presence of AMF inhibited shoot growth and shoot branching, decreased total root length and specific root length, increased mean root diameter and root tissue density and reduced carboxylates. However, the role of AMF in acquiring P differed between the two P sources, with the enhanced P acquisition under FeP while not under KP. Co-inoculation of AMF and rhizobia enhanced nodulation under FeP, but not under KP. Our results suggest that the effects of AMF on shoot branching were mediated by cytokinins as the reduced shoot branching in FeP40 and KP40 under +AMF relative to -AMF coincided with a decreased concentration of cytokinins in xylem sap for both genotypes.

COL10A1-DDR2 axis promotes the progression of pancreatic cancer by regulating MEK/ERK signal transduction.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant tumors with a poor prognosis. Type X collagen α 1 chain (COL10A1), a member of the collagen family, is a gene associated with the progression of a variety of human tumors, but the specific function and molecular mechanism of COL10A1 in pancreatic cancer remain unclear. Our study found that COL10A1 is highly expressed in pancreatic cancer cells and tissues, and its high expression is related to poor prognosis and some clinicopathological features, such as tumor size and differentiation. Biological functional experiments showed that overexpression of COL10A1 enhanced the proliferation and migration of PDAC cells. Interestingly, discoid protein domain receptor 2 (DDR2), the receptor of COL10A1, is regulated by COL10A1. We found that the COL10A1-DDR2 axis activates the mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway, which leads to epithelial-mesenchymal transformation (EMT) and accelerates the progression of pancreatic cancer. In summary, COL10A1 regulates PDAC cell proliferation and MEK/ERK signaling pathways by binding to DDR2 to promote migration, invasion and EMT. Our study suggested that COL10A1 might be a critical factor in promoting PDAC progression. More research is needed to confirm COL10A1 as a potential biomarker and therapeutic target for PDAC.

LncRNA NEAT1 Promotes Gastric Cancer Progression Through miR-17-5p/TGFßR2 Axis Up-Regulated Angiogenesis.

BACKGROUND: Long non-coding RNAs (lncRNAs) have been indicated to play critical roles in gastric cancer (GC) tumorigenesis and progression. However, their roles in GC remain to be further elucidated. METHODS: RT-qPCR and fluorescence in situ hybridzation (FISH) were conducted to detect the expression of lncRNA NEAT1 in GC tissues and cell lines. Gene Set Enrichment Analysis (GSEA) was performed to screen out potential phenotypes and pathways that NEAT1 may participate in. NEAT1-silenced AGS and MGC803 cells were constructed and a series of functional experiments to investigate the roles of NEAT1 in GC angiogenesis both in vitro and in vivo. RNA pull down and luciferase reporter assays were utilized to illustrate the mechanisms underlying the functions of NEAT1 in GC. RESULTS: We observed that NEAT1 was upregulated in most GC specimens and cell lines. NEAT1 high was correlated with poor prognosis of GC patients. In vitro experiments showed that NEAT1 promoted GC angiogenesis by enhancing proliferation, migration, and tube formation ability of endothelial cells. Mechanism researches revealed that NEAT1 could competitively sponge miR-17-5p which targeted TGFßR2 directly. Subsequently, activate TGFß/Smad pathway by following with upregulation of a series of classical proangiogenic factors especially VEGF. CONCLUSION: The study unveiled that the LncRNA NEAT1/miR-17-5p/TGFßR2 axis is a novel mechanism in GC angiogenesis. Disrupting this axis may be a potential strategy for GC treatment.

Multiple roles for PARP1 in ALC1-dependent nucleosome remodeling.

The SNF2 family ATPase Amplified in Liver Cancer 1 (ALC1) is the only chromatin remodeling enzyme with a poly(ADP-ribose) (PAR) binding macrodomain. ALC1 functions together with poly(ADP-ribose) polymerase PARP1 to remodel nucleosomes. Activation of ALC1 cryptic ATPase activity and the subsequent nucleosome remodeling requires binding of its macrodomain to PAR chains synthesized by PARP1 and NAD+ A key question is whether PARP1 has a role(s) in ALC1-dependent nucleosome remodeling beyond simply synthesizing the PAR chains needed to activate the ALC1 ATPase. Here, we identify PARP1 separation-of-function mutants that activate ALC1 ATPase but do not support nucleosome remodeling by ALC1. Investigation of these mutants has revealed multiple functions for PARP1 in ALC1-dependent nucleosome remodeling and provides insights into its multifaceted role in chromatin remodeling.

Resveratrol induces human colorectal cancer cell apoptosis by activating the mitochondrial pathway via increasing reactive oxygen species.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer­related mortality worldwide according to Global Cancer Statistics 2018. Resveratrol (RSV) is a phenolic compound that possesses anticancer functions against various types of cancer, including breast and gastric cancer. However, the functions and mechanism underlying RSV in CRC are not completely understood. The present study aimed to investigate the anticancer effects and mechanism underlying RSV in CRC cells by conducting Cell Counting Kit­8, apoptosis, reactive oxygen species (ROS) and western blotting assays. The results suggested that RSV dose­dependently inhibited CRC cell viability, and increased cell apoptosis and ROS levels compared with the control group. The protein expression levels of Bax, cytochrome c, cleaved caspase­9 and cleaved caspase­3 were upregulated, whereas Bcl­2 expression levels were downregulated in RSV­treated CRC cells compared with control cells. The results indicated that RSV might activate the mitochondrial apoptotic pathway by increasing ROS release. The present study suggested that RSV possessed antitumour activity against CRC by modulating an ROS­mediated mitochondrial apoptotic pathway.

The ALDH Family Contributes to Immunocyte Infiltration, Proliferation and Epithelial-Mesenchymal Transformation in Glioma.

Gliomas are malignant tumors that originate from the central nervous system. The aldehyde dehydrogenase family has been documented to affect cancer progression; however, its role in gliomas remains largely unexplored. Bulk RNA-seq analysis and single-cell RNA-Seq analysis were performed to explore the role of the aldehyde dehydrogenases family in gliomas. Training cohort contained The Cancer Genome Atlas data, while data from Chinese Glioma Genome Atlas and Gene Expression Omnibus were set as validation cohorts. Our scoring system based on the aldehyde dehydrogenases family suggested that high-scoring samples were associated with worse survival outcomes. The enrichment score of pathways were calculated by AUCell to substantiate the biofunction prediction results that the aldehyde dehydrogenases family affected glioma progression by modulating tumor cell proliferation, migration, and immune landscape. Tumor immune landscape was mapped from high-scoring samples. Moreover, ALDH3B1 and ALDH16A1, two main contributors of the scoring system, could affect glioblastoma cell proliferation and migration by inducing cell-cycle arrest and the epithelial-mesenchymal transition. Taken together, the aldehyde dehydrogenases family could play a significant role in the tumor immune landscape and could be used to predict patient prognosis. ALDH3B1 and ALDH16A1 could influence tumor cell proliferation and migration.

Analyzing microsatellite instability and gene mutation in circulating cell-free DNA to monitor colorectal cancer progression.

BACKGROUND: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. Detection of microsatellite instability (MSI) status and gene mutations may be useful for molecular targeted therapy. The liquid biopsy is a newly developed, non-invasive method for tumor diagnosis and monitoring. In this study, we evaluated the possible clinical value of liquid biopsy by analyzing MSI and gene mutation. METHODS: Next-generation sequencing (NGS) was used to analyze MSI and gene mutation in circulating cell-free DNA (cfDNA) and tissue DNA extracted from 6 CRC patients' plasma and matched primary tumor tissue (MPTT) samples, respectively. RESULTS: A total of 6 patients (4 male, 2 female) were included for analysis, whose stage ranges from stage I through stage III. NGS-based panel of 5 quasi-monomorphic microsatellite markers (MSI-NGS) BAT-25, BAT-26, NR21, NR24 as well as NR27, and 4 mismatch repair (MMR) genes (MSH2, MSH6, PMS2, MLH1) expressions assessed by immunohistochemistry (MMR-IHC) and NGS (MMR-NGS) were used to determine MSI status synergistically. Comprehensive analysis of NGS and IHC results showed that the overall incidences of MSI in plasma and MPTT samples from these patients were 1/6 and 2/6, respectively. 4 patients were defined as microsatellite stable (MSS) in both plasma and MPTT. In the above 6 patients, MSI-NGS detection in cfDNA accurately identified 1/2 of tissue high-level microsatellite instability (MSI-H) and 4/4 of tissue MSS for an overall accuracy of 5/6. Gene mutational profiles in these CRC patients' plasma and MPTT samples were analyzed by NGS. Tumor-specific gene mutations were detected in 2/6 of plasma and 4/4 of MPTT samples. The two mutation-positive plasma samples were from CRC patients at stage IIb and stage IIIc. CONCLUSIONS: Analyzing MSI and gene mutation might be a non-invasive supplementary way to reveal the molecular characteristics of CRC.

Improving label-free quantitative proteomics strategies by distributing shared peptides and stabilizing variance.

In a previous study, we demonstrated that spectral counts-based label-free proteomic quantitation could be improved by distributing peptides shared between multiple proteins. Here, we compare four quantitative proteomic approaches, namely, the normalized spectral abundance factor (NSAF), the normalized area abundance factor (NAAF), normalized parent ion intensity abundance factor (NIAF), and the normalized fragment ion intensity abundance factor (NFAF). We demonstrate that label-free proteomic quantitation methods based on chromatographic peak area (NAAF), parent ion intensity in MS1 (NIAF), and fragment ion intensity (NFAF) are also improved when shared peptides are distributed on the basis of peptides unique to each isoform. To stabilize the variance inherent to label-free proteomic quantitation data sets, we use cyclic-locally weighted scatter plot smoothing (LOWESS) and linear regression normalization (LRN). Again, all four methods are improved when cyclic-LOWESS and LRN are applied to reduce variation. Finally, we demonstrate that absolute quantitative values may be derived from label-free parameters such as spectral counts, chromatographic peak area, and ion intensity when using spiked-in proteins of known amounts to generate standard curves.

Controlling for gene expression changes in transcription factor protein networks.

The development of affinity purification technologies combined with mass spectrometric analysis of purified protein mixtures has been used both to identify new protein-protein interactions and to define the subunit composition of protein complexes. Transcription factor protein interactions, however, have not been systematically analyzed using these approaches. Here, we investigated whether ectopic expression of an affinity tagged transcription factor as bait in affinity purification mass spectrometry experiments perturbs gene expression in cells, resulting in the false positive identification of bait-associated proteins when typical experimental controls are used. Using quantitative proteomics and RNA sequencing, we determined that the increase in the abundance of a set of proteins caused by overexpression of the transcription factor RelA is not sufficient for these proteins to then co-purify non-specifically and be misidentified as bait-associated proteins. Therefore, typical controls should be sufficient, and a number of different baits can be compared with a common set of controls. This is of practical interest when identifying bait interactors from a large number of different baits. As expected, we found several known RelA interactors enriched in our RelA purifications (NFκB1, NFκB2, Rel, RelB, IκBα, IκBß, and IκBε). We also found several proteins not previously described in association with RelA, including the small mitochondrial chaperone Tim13. Using a variety of biochemical approaches, we further investigated the nature of the association between Tim13 and NFκB family transcription factors. This work therefore provides a conceptual and experimental framework for analyzing transcription factor protein interactions.

Refinements to label free proteome quantitation: how to deal with peptides shared by multiple proteins.

Quantitative shotgun proteomics is dependent on the detection, identification, and quantitative analysis of peptides. An issue arises with peptides that are shared between multiple proteins. What protein did they originate from and how should these shared peptides be used in a quantitative proteomics workflow? To systematically evaluate shared peptides in label-free quantitative proteomics, we devised a well-defined protein sample consisting of known concentrations of six albumins from different species, which we added to a highly complex yeast lysate. We used the spectral counts based normalized spectral abundance factor (NSAF) as the starting point for our analysis and compared an exhaustive list of possible combinations of parameters to determine what was the optimal approach for dealing with shared peptides and shared spectral counts. We showed that distributing shared spectral counts based on the number of unique spectral counts led to the most accurate and reproducible results.

Protein sequencing by mass analysis of polypeptide ladders after controlled protein hydrolysis.

The characterization of protein modifications is essential for the study of protein function using functional genomic and proteomic approaches. However, current techniques are not efficient in determining protein modifications. We report an approach for sequencing proteins and determining modifications with high speed, sensitivity and specificity. We discovered that a protein could be readily acid-hydrolyzed within 1 min by exposure to microwave irradiation to form, predominantly, two series of polypeptide ladders containing either the N- or C-terminal amino acid of the protein, respectively. Mass spectrometric analysis of the hydrolysate produced a simple mass spectrum consisting of peaks exclusively from these polypeptide ladders, allowing direct reading of amino acid sequence and modifications of the protein. As examples, we applied this technique to determine protein phosphorylation sites as well as the sequences and several previously unknown modifications of 28 small proteins isolated from Escherichia coli K12 cells. This technique can potentially be automated for large-scale protein annotation.