Blood- and Urine-Based Liquid Biopsy for Early-Stage Cancer Investigation: Taken Clear Renal Cell Carcinoma as a Model.

Liquid biopsy is a noninvasive technique that can provide valuable information for disease characterization by using biofluids as a source of biomarkers. Proteins found in biofluids can offer a wealth of information for understanding pathological processes. In this study, we used early-stage clear cell renal cell carcinoma (ccRCC) as a model to explore the proteomic relationships among tissue, plasma, and urine. We analyzed samples of tumor tissue, plasma, and urine from a cohort of 27 ccRCC patients with T1-2 stage and 27 matched healthy controls, using liquid chromatography-mass spectrometry (LC-MS) for proteomic analysis. We integrated the differential proteins found in the three types of samples to explore ccRCC-associated molecular changes. Our results showed that both plasma and urine proteomes could reflect functional changes in tumor tissue. In plasma, cytoskeletal proteins and metabolic enzymes were differentially expressed, while in urine, adhesion molecules and defense proteins showed differential levels. The differential proteins found in plasma and urine both reflect the binding and catalytic activity of tumor tissue. Additionally, proteins only changed in biofluids could reflect body immune response changes, with plasma proteins involved in actin cytoskeleton and oxidative stress, and urine proteins involved in granulocyte adhesion and leukocyte extravasation signaling. Plasma and urine proteins could effectively distinguish RCC from control, with good performances (plasma/urine: 92.6%/92.6% specificity, 96.3%/92.6% sensitivity, and an area under the curve of 0.981/0.97). In conclusion, biofluids could not only reflect functional changes in tumor tissue but also reflect changes in the body's immune response. These findings will benefit the understanding of body biomarkers in tumors and the discovery of potential disease biomarkers.

Characterization of the proteome of stable and unstable carotid atherosclerotic plaques using data-independent acquisition mass spectrometry.

BACKGROUND: Currently, noninvasive imaging techniques and circulating biomarkers are still insufficient to accurately assess carotid plaque stability, and an in-depth understanding of the molecular mechanisms that contribute to plaque instability is still lacking. METHODS: We established a clinical study cohort containing 182 patients with carotid artery stenosis. After screening, 39 stable and 49 unstable plaques were included in the discovery group, and quantitative proteomics analysis based on data independent acquisition was performed for these plaque samples. Additionally, 35 plaques were included in the validation group to validate the proteomics results by immunohistochemistry analysis. RESULTS: A total of 397 differentially expressed proteins were identified in stable and unstable plaques. These proteins are primarily involved in ferroptosis and lipid metabolism-related functions and pathways. Plaque validation results showed that ferroptosis- and lipid metabolism-related proteins had different expression trends in stable plaques versus unstable fibrous cap regions and lipid core regions. Ferroptosis- and lipid metabolism-related mechanisms in plaque stability were discussed. CONCLUSIONS: Our results may provide a valuable strategy for revealing the mechanisms affecting plaque stability and will facilitate the discovery of specific biomarkers to broaden the therapeutic scope.

Metaproteomics Characterizes the Human Gingival Crevicular Fluid Microbiome Function in Periodontitis.

Periodontitis is the leading cause of tooth loss in adults worldwide. The human proteome and metaproteome characterization of periodontitis is not clearly understood. Gingival crevicular fluid samples were collected from eight periodontitis and eight healthy subjects. Both the human and microbial proteins were characterized by liquid chromatography coupled with high-resolution mass spectrometry. A total of 570 human proteins were found differentially expressed, which were primarily associated with inflammatory response, cell death, cellular junction, and fatty acid metabolism. For the metaproteome, 51 genera were identified, and 10 genera were found highly expressed in periodontitis, while 11 genera were downregulated. The analysis showed that microbial proteins related to butyrate metabolism were upregulated in periodontitis cases. In particular, correlation analysis showed that the expression of host proteins related to inflammatory response, cell death, cellular junction, and lipid metabolism correlates with the alteration of metaproteins, which reflect the changes of molecular function during the occurrence of periodontitis. This study showed that the gingival crevicular fluid human proteome and metaproteome could reflect the characteristics of periodontitis. This might benefit the understanding of the periodontitis mechanism.

Proteome Characterization of Glaucoma Aqueous Humor.

Glaucoma is the leading cause of irreversible blindness worldwide. The proteome characterization of glaucoma is not clearly understood. A total of 175 subjects, including 57 primary acute angle-closure glaucoma (PAACG), 50 primary chronic angle-closure glaucoma (PCACG), 35 neovascular glaucoma (NVG), and 33 cataract patients, were enrolled and comparison proteomic analysis was provided. The samples were randomly divided into discovery group or validation group, whose aqueous humor proteome was analyzed by data-independent acquisition or by parallel reaction monitoring. The common proteome features of three types of glaucoma were immune response, lipid metabolism, and cell death. Three proteins, VTN, SERPIND1, and CD14, showed significant upregulation in glaucoma and could discriminate glaucoma from cataract. Mutual differential proteomic analysis of PAACG, PCACG, and NVG showed different proteome characterization of the three types of glaucoma. NVG was characterized with activated angiogenesis. PAACG was characterized with activation of inflammation response. SERPIND1 was discovered to play vital role in glaucoma occurrences, which is associated with eye transparency decrease and glucose metabolism. This study would provide insights in understanding proteome characterization of glaucoma and benefit the clinical application of AH proteome.

A qualitative and quantitative analysis of the human gingival crevicular fluid proteome and metaproteome.

Gingival crevicular fluid (GCF) is an integral part of oral fluid that plays a special role in maintaining the structure of junctional epithelium and defending against bacterial infection. In this study, we comprehensively analysed the composition of the human GCF proteome and metaproteome simultaneously to obtain multidimensional information about GCF. A total of 3680 human proteins (2540 with at least two unique peptides) were identified in the normal GCF sample, and their functions were mainly associated with immune function and inflammation. Among these proteins, 1874 proteins could be quantified by the iBAQ algorithm, and their abundances spanned a dynamic range of six orders of magnitude. For the GCF metaproteome, a total of 3082 proteins and 69 genera were found. In addition, 16 genera were not identified by GCF metagenomic analysis. Compared to the saliva metaproteome, 32 genera were found to be in common. The protein quantitative analysis showed that the abundance of GCF metaproteome contributed to approximately 4.17% of the total GCF proteome. The top three most abundant genera were Fusobacterium, Corynebacterium, and Leptotrichia. The above data will be useful for future research on GCF-related diseases.

Comprehensive Analysis of Individual Variation in the Urinary Proteome Revealed Significant Gender Differences.

Disease biomarkers are the measurable changes associated with a pathophysiological process. Without homeostatic control, urine accumulates systematic changes in the body. Thus, urine is an attractive biological material for the discovery of disease biomarkers. One of the major bottlenecks in urinary biomarker discovery is that the concentration and composition of urinary proteins are influenced by many physiological factors. To elucidate the individual variation and related factors influencing the urinary proteome, we comprehensively analyzed the urine samples from healthy adult donors (aged 20-69 years). Co-expression network analysis revealed protein clusters representing the metabolic status, gender-related differences and age-related differences in urinary proteins. In particular, we demonstrated that gender is a crucial factor contributing to individual variation. Proteins that were increased in the male urine samples include prostate-secreted proteins and TIMP1, a protein whose abundance alters under various cancers and renal diseases; however, the proteins that were increased in the female urine samples have known functions in the immune system. Nine gender-related proteins were validated on 85 independent samples by multiple reaction monitoring. Five of these proteins were further used to build a model that could accurately distinguish male and female urine samples with an area under curve value of 0.94. Based on the above results, we strongly suggest that future biomarker investigations should consider gender as a crucial factor in experimental design and data analysis. Finally, reference intervals of each urinary protein were estimated, providing a baseline for the discovery of abnormalities.

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma.

BACKGROUND: To discover biomarker panels that could distinguish cancers (BC and RCC) from healthy controls (HCs) and bladder cancers (BC) from renal cell carcinoma (RCC), regardless of whether the patients have haematuria. In addition, we also explored the altered metabolomic pathways of BC and RCC. METHODS: In total, 403 participants were enrolled in our study, which included 146 BC patients (77 without haematuria and 69 with haematuria), 115 RCC patients (94 without haematuria and 21 with haematuria) and 142 sex- and age-matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. RESULTS: The panel of α-CEHC, ß-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the patients with cancer from the HCs (the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N'-formylkynurenine could differentiate BC from RCC without haematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with haematuria (AUC was 0.913). Pathway analyses revealed altered lipid and purine metabolisms between cancer patients and HCs, together with disordered amino acid and purine metabolisms between BC and RCC with haematuria. CONCLUSIONS: UPLC-MS urine metabolomic analyses could not only differentiate cancers from HCs but also discriminate BC from RCC. In addition, pathway analyses demonstrated a deeper metabolic mechanism of BC and RCC.

Differential urinary proteins to diagnose coronary heart disease based on iTRAQ quantitative proteomics.

Coronary artery disease (CAD) is a manifestation of systemic atherosclerotic disease. It is assessed by intervention or traditional scoring risk factors. Diagnosis is limited by inaccurate and invasive methods. Developing noninvasive methods to screen for the risk of CAD is a major challenge. We aimed to identify urinary proteins associated with CAD. We utilized iTRAQ labeling followed by 2D LC-MS/MS to compare the urinary proteome of CAD patients to healthy cohorts. The multiple reaction monitoring (MRM) was used to verify the differential proteins. ROC analysis based on MRM data was used to evaluate the diagnostic application. A total of 876 proteins were quantified, and 100 differential proteins were found. Functional analysis revealed that the differential proteins were mainly associated with Liver X Receptor/Retinoid X Receptor (LXR/RXR) pathway activation, atherosclerosis signaling, production of nitric oxide and reactive oxygen species, and the top upstream regulator of the differential proteins by IPA analysis indicated to the APOE. Nineteen differential proteins were verified by MRM analysis. ROC based on MRM data revealed that the combination of two proteins (APOD and TFF1) could diagnose CAD with 85% sensitivity and 99% specificity (AUC 0.95). The urinary proteome might reflect the pathophysiological changes in CAD and be used for the clinical study of CAD.

Peptide Biosynthesis with Stable Isotope Labeling from a Cell-free Expression System for Targeted Proteomics with Absolute Quantification.

Because of its specificity and sensitivity, targeted proteomics using mass spectrometry for multiple reaction monitoring is a powerful tool to detect and quantify pre-selected peptides from a complex background and facilitates the absolute quantification of peptides using isotope-labeled forms as internal standards. How to generate isotope-labeled peptides remains an urgent challenge for accurately quantitative targeted proteomics on a large scale. Herein, we propose that isotope-labeled peptides fused with a quantitative tag could be synthesized through an expression system in vitro, and the homemade peptides could be enriched by magnetic beads with tag-affinity and globally quantified based on the corresponding multiple reaction monitoring signals provided by the fused tag. An Escherichia coli cell-free protein expression system, protein synthesis using recombinant elements, was adopted for the synthesis of isotope-labeled peptides fused with Strep-tag. Through a series of optimizations, we enabled efficient expression of the labeled peptides such that, after Strep-Tactin affinity enrichment, the peptide yield was acceptable in scale for quantification, and the peptides could be completely digested by trypsin to release the Strep-tag for quantification. Moreover, these recombinant peptides could be employed in the same way as synthetic peptides for multiple reaction monitoring applications and are likely more economical and useful in a laboratory for the scale of targeted proteomics. As an application, we synthesized four isotope-labeled glutathione S-transferase (GST) peptides and added them to mouse sera pre-treated with GST affinity resin as internal standards. A quantitative assay of the synthesized GST peptides confirmed the absolute GST quantification in mouse sera to be measurable and reproducible.

Analysis of the differential urinary protein profile in IgA nephropathy patients of Uygur ethnicity.

BACKGROUND: IgA nephropathy (IgAN) is one of the most common forms of idiopathic glomerular diseases and might lead to end-stage kidney disease. Accurate and non-invasive biomarkers for early diagnosis are required for early intervention and consequent therapy for IgAN patients. Because variance in the disease incidence and predisposing genes of IgAN has been detected among different ethnicities, the ethnicity factor should be considered in IgAN biomarker discovery. The differences in the protein profiles and pathological mechanisms of IgAN in patients of Uygur ethnicity need to be clearly illustrated. METHODS: In this study, we used urinary proteomics to discover candidate biomarkers of IgAN in patients of Uygur ethnicity. The urinary proteins from Uygur normal control and Uygur IgAN patients were extracted and analyzed using 2D-LC-MS/MS and isobaric tags for relative and absolute quantitation (iTRAQ) analysis. RESULTS: A total of 277 proteins were found to be differentially represented in Uygur IgAN compared with the respective normal controls. The bioinformatics analysis revealed that the immune response, cell survival, and complement system were activated in Uygur IgAN. Many differentially expressed proteins were found to be related to nephropathy and kidney injuries. Four candidate biomarkers were validated by Western blot, and these results were consistent with the iTRAQ results. ICAM1, TIMP1, SERPINC1 and ADIPOQ were upregulated in Uygur IgAN. Bioinformatic analysis revealed that the increase of ICAM1 and TIMP1 might be caused by IgAN, but the increase of SERPINC1 and ADIPOQ might be caused by proteinuria. SERPINC1 and ICAM1 were identified as the candidate biomarkers with excellent area-under-the-curve (AUC) values (0.84) for distinguishing Uygur IgAN from normal controls. CONCLUSIONS: Using urinary proteomic analysis, we identified several candidate biomarkers for IgAN in patients of Uygur ethnicity. These results will prove helpful for exploring the pathological mechanism of IgAN in patients of Uygur ethnicity and for developing better treatments for these patients.

Comprehensive Map and Functional Annotation of Human Pituitary and Thyroid Proteome.

Knowledge about human tissue proteome will provide insights into health organ physiology. To construct a comprehensive data set of human pituitary and thyroid proteins, post-mortem pituitaries and thyroids from 10 normal individuals were used. The pooled samples were prepared using two methods. One part of the sample was processed using 14 high-abundance proteins immunoaffinity column. The other part was directly subjected to digestion. Finally, a total of 7596 proteins in pituitary and 5602 proteins in thyroid with high confidence were identified, with 6623 and 4368 quantified, respectively. A total of 5781 of pituitary and 3178 of thyroid proteins have not been previously reported in the normal pituitary and thyroid proteome. Comparison of pituitary and thyroid proteome indicated that thyroid prefers to be involved in nerve system regeneration and metabolic regulation, while pituitary mainly performs functions of signal transduction and cancer modulation. Our results, for the first time, comprehensively profiled and functionally annotated the largest high-confidence data set of proteome of two important endocrine glands, pituitary and thyroid, which is important for further studies on biomarker identification and molecular mechanisms of pituitary and thyroid disorders. The mapping results can be freely downloaded at http://www.urimarker.com/pituitary/ and http://www.urimarker.com/thyroid/ . The raw data are available via ProteomeXchange with identifier PXD006471.

The serum protein responses to treatment with Xiaoke Pill and Glibenclamide in type 2 diabetes patients.

AIM: The Xiaoke Pill containing Chinese herb extracts and Glibenclamide, is used in therapy for type 2 diabetes mellitus (T2DM), and is effective in reducing the risk of hypoglycemia and improving diabetes symptoms compared with Glibenclamide. We describe a quantitative proteomics project to measure the T2DM serum proteome response to the Xiaoke Pill and Glibenclamide. METHODS: Based on a recently conducted 48-week clinical trial comparing the safety and efficacy of Glibenclamide (n = 400) and Xiaoke Pill (n = 400), after matching for age, sex, BMI, drug dose and whether hypoglycemia occurred, 32 patients were selected for the serum based proteomic analysis and divided into four groups (with/without hypoglycemia treated with Xiaoke Pill or Glibenclamide, n = 8 for each group). We screened the differential serum proteins related to treatments and the onset of hypoglycemia using the iTRAQ labeling quantitative proteomics technique. Baseline and follow-up samples were used. RESULTS: The quantitative proteomics experiments demonstrated that 25 and 21 proteins differed upon treatment with the Xiaoke Pill in patients without and with hypoglycemia, respectively, while 24 and 25 proteins differed upon treatment with Glibenclamide in patients without and with hypoglycemia, respectively. The overlap of different proteins between the patients with and without hypoglycemia given the same drug treatment was much greater than between the patients given different drug treatments. CONCLUSIONS: We conclude that the serum proteins response to the two different anti-diabetic drug treatments may serve as a sensitive biomarker for evaluation of the therapeutic effects and continue investigations into the mechanism.

A qualitative and quantitative evaluation of the peptide characteristics of microwave- and ultrasound-assisted digestion in discovery and targeted proteomic analyses.

RATIONALE: Fast digestion methods can dramatically accelerate enzyme digestion and increase the throughput of proteomic analysis. However, the peptide characteristics of fast digestion methods and their performance in discovery and targeted proteomic analysis must be systematically evaluated. METHODS: Three digestion methods, including overnight digestion, microwave-assisted protein enzymatic digestion (MAPED), and high-intensity focused ultrasonic-assisted enzymatic digestion (HIFUSAED), in trypsin or in trypsin/Lys-C were comprehensively compared in both discovery and targeted proteomics analysis using the HeLa cell proteome. In discovery proteomic analysis, the highest numbers of peptides and proteins were identified when the sample was digested via the MAPED method with trypsin/Lys-C. RESULTS: The fast digestion methods showed a higher mis-cleavage rate and a lower semi-tryptic rate than the overnight digestion method. In both label-free quantitative analysis and targeted proteomic analysis, both fully cleaved peptides (FCPs) and mis-cleaved peptides (MCPs) from the fast digestion methods and the overnight digestion method showed good reproducibility if they showed good abundance. CONCLUSIONS: When both the FCPs and MCPs were included in the analysis, the MAPED with trypsin/Lys-C method showed the best results for both discovery proteomic analysis and relative quantitative targeted proteomic analysis. These results will be beneficial for the application of fast digestion methods to proteomics.

Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines.

Cancer genomics unveils many cancer-related mutations, including some chromosome 20 (Chr.20) genes. The mutated messages have been found in the corresponding mRNAs; however, whether they could be translated to proteins still requires more evidence. Herein, we proposed a transomics strategy to profile the expression status of human Chr.20 genes (555 in Ensembl v72). The data of transcriptome and translatome (the mRNAs bound with ribosome, translating mRNAs) revealed that ∼80% of the coding genes on Chr.20 were detected with mRNA signals in three liver cancer cell lines, whereas of the proteome identified, only ∼45% of the Chr.20 coding genes were detected. The high amount of overlapping of identified genes in mRNA and RNC-mRNA (ribosome nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent distribution of the abundance averages of mRNA and RNC-mRNA along the Chr.20 subregions in three liver cancer cell lines indicate that the mRNA information is efficiently transmitted from transcriptional to translational stage, qualitatively and quantitatively. Of the 457 genes identified in mRNAs and RNC-mRNA, 136 were found to contain SNVs with 213 sites, and >40% of these SNVs existed only in metastatic cell lines, suggesting them as the metastasis-related SNVs. Proteomics analysis showed that 16 genes with 20 SNV sites were detected with reliable MS/MS signals, and some SNVs were further validated by the MRM approach. With the integration of the omics data at the three expression phases, therefore, we are able to achieve the overall view of the gene expression of Chr.20, which is constructive in understanding the potential trend of encoding genes in a cell line and exploration of a new type of markers related to cancers.

LC-MS-based urine metabolomics analysis of chronic subdural hematoma for biomarker discovery.

BACKGROUND: Chronic subdural hematoma (CSDH) is one of the most common neurosurgical diseases with atypical manifestations. The aim of this study was to utilize urine metabolomics to explore potential biomarkers for the diagnosis and prognosis of CSDH. METHODS: Seventy-seven healthy controls and ninety-two patients with CSDH were enrolled in our study. In total, 261 urine samples divided into the discovery group and validation group were analyzed by LC-MS. The statistical analysis and functional annotation were applied to discover potential biomarker panels and altered metabolic pathways. RESULTS: A total of 53 differential metabolites were identified in this study. And the urinary metabolic profiles showed apparent separation between patients and controls. Further functional annotation showed that the differential metabolites were associated with lipid metabolism, fatty acid metabolism, amino acid metabolism, biotin metabolism, steroid hormone biosynthesis, and pentose and glucuronate interconversions. Moreover, one panel of Capryloylglycine, cis-5-Octenoic acid, Ethisterone, and 5,6-DiHETE showed good predictive performance in the diagnosis of CSDH, with an AUC of 0.89 in discovery group and an AUC of 0.822 in validation group. Another five metabolites (Trilobinol, 3'-Hydroxyropivacaine, Ethisterone, Arginyl-Proline, 5-alpha-Dihydrotestosterone glucuronide) showed the levels of them returned to a healthy state after surgery, showing good possibility to monitor the recovery of CSDH patients. CONCLUSION AND CLINICAL RELEVANCE: The findings of the study revealed urine metabolomic differences between CSDH and controls. The potentially diagnostic and prognostic biomarker panels of urine metabolites were established, and functional analysis demonstrated deeper metabolic disorders of CSDH, which might conduce to improve early diagnose of CSDH clinically.

Serum metabolism alteration behind different etiology, diagnosis, and prognosis of disorders of consciousness.

BACKGROUND: Patients with disorders of consciousness (DoC) exhibit varied revival outcomes based on different etiologies and diagnoses, the mechanisms of which remain largely unknown. The fluctuating clinical presentations in DoC pose challenges in accurately assessing consciousness levels and prognoses, often leading to misdiagnoses. There is an urgent need for a deeper understanding of the physiological changes in DoC and the development of objective diagnostic and prognostic biomarkers to improve treatment guidance. METHODS: To explore biomarkers and understand the biological processes, we conducted a comprehensive untargeted metabolomic analysis on serum samples from 48 patients with DoC. Patients were categorized based on etiology (TBI vs. non-TBI), CRS-R scores, and prognosis. Advanced analytical techniques, including PCA and OPLS-DA models, were employed to identify differential metabolites. RESULTS: Our analysis revealed a distinct separation in metabolomic profiles among the different groups. The primary differential metabolites distinguishing patients with varying etiologies were predominantly phospholipids, with a notable decrease in glycerophospholipids observed in the TBI group. Patients with higher CRS-R scores exhibited a pattern of impaired carbohydrate metabolism coupled with enhanced lipid metabolism. Notably, serum concentrations of both LysoPE and PE were reduced in patients with improved outcomes, suggesting their potential as prognostic biomarkers. CONCLUSIONS: Our study underscores the critical role of phospholipid metabolism in the brain's metabolic alterations in patients with DoC. It identifies key biomarkers for diagnosis and prognosis, offering insights that could lead to novel therapeutic targets. These findings highlight the value of metabolomic profiling in understanding and potentially treating DoC.

Quantitative analysis of the human AKR family members in cancer cell lines using the mTRAQ/MRM approach.

Members of human aldo-keto reductase (AKR) superfamily have been reported to be involved in cancer progression, whereas the final conclusion is not generally accepted. Herein, we propose a quantitative method to measure human AKR proteins in cells using mTRAQ-based multiple reaction monitoring (MRM). AKR peptides with multiple transitions were carefully selected upon tryptic digestion of the recombinant AKR proteins, while AKR proteins were identified by SDS-PAGE fractionation coupled with LC-MS/MS. Utilizing mTRAQ triplex labeling to produce the derivative peptides, calibration curves were generated using the mixed lysate as background, and no significantly different quantification of AKRs was elicited from the two sets of calibration curves under the mixed and single lysate as background. We employed this approach to quantitatively determine the 6 AKR proteins, AKR1A1, AKR1B1, AKR1B10, AKR1C1/C2, AKR1C3, and AKR1C4, in 7 different cancer cell lines and for the first time to obtain the absolute quantities of all the AKR proteins in each cell. The cluster plot revealed that AKR1A and AKR1B were widely distributed in most cancer cells with relatively stable abundances, whereas AKR1Cs were unevenly detected among these cells with diverse dynamic abundances. The AKR quantitative distribution in different cancer cells, therefore, may assist further exploration toward how the AKR proteins are involved in tumorigenesis.

Qualitative and quantitative expression status of the human chromosome 20 genes in cancer tissues and the representative cell lines.

Under the guidance of the Chromosome-centric Human Proteome Project (C-HPP), (1, 2) we conducted a systematic survey of the expression status of genes located at human chromosome 20 (Chr.20) in three cancer tissues, gastric, colon, and liver carcinoma, and their representative cell lines. We have globally profiled proteomes in these samples with combined technology of LC-MS/MS and acquired the corresponding mRNA information upon RNA-seq and RNAchip. In total, 323 unique proteins were identified, covering 60% of the coding genes (323/547) in Chr.20. With regards to qualitative information of proteomics, we overall evaluated the correlation of the identified Chr.20 proteins with target genes of transcription factors or of microRNA, conserved genes and cancer-related genes. As for quantitative information, the expression abundances of Chr.20 genes were found to be almost consistent in both tissues and cell lines of mRNA in all individual chromosome regions, whereas those of Chr.20 proteins in cells are different from tissues, especially in the region of 20q13.33. Furthermore, the abundances of Chr.20 proteins were hierarchically evaluated according to tissue- or cancer-related distribution. The analysis revealed several cancer-related proteins in Chr.20 are tissue- or cell-type dependent. With integration of all the acquired data, for the first time we established a solid database of the Chr.20 proteome.

Continuously released Zn2+ in 3D-printed PLGA/ß-TCP/Zn scaffolds for bone defect repair by improving osteoinductive and anti-inflammatory properties.

Long-term nonunion of bone defects has always been a major problem in orthopedic treatment. Artificial bone graft materials such as Poly (lactic-co-glycolic acid)/ß-tricalcium phosphate (PLGA/ß-TCP) scaffolds are expected to solve this problem due to their suitable degradation rate and good osteoconductivity. However, insufficient mechanical properties, lack of osteoinductivity and infections after implanted limit its large-scale clinical application. Hence, we proposed a novel bone repair bioscaffold by adding zinc submicron particles to PLGA/ß-TCP using low temperature rapid prototyping 3D printing technology. We first screened the scaffolds with 1 wt% Zn that had good biocompatibility and could stably release a safe dose of zinc ions within 16 weeks to ensure long-term non-toxicity. As designed, the scaffold had a multi-level porous structure of biomimetic cancellous bone, and the Young's modulus (63.41 ± 1.89 MPa) and compressive strength (2.887 ± 0.025 MPa) of the scaffold were close to those of cancellous bone. In addition, after a series of in vitro and in vivo experiments, the scaffolds proved to have no adverse effects on the viability of BMSCs and promoted their adhesion and osteogenic differentiation, as well as exhibiting higher osteogenic and anti-inflammatory properties than PLGA/ß-TCP scaffold without zinc particles. We also found that this osteogenic and anti-inflammatory effect might be related to Wnt/ß-catenin, P38 MAPK and NFkB pathways. This study lay a foundation for the follow-up study of bone regeneration mechanism of Zn-containing biomaterials. We envision that this scaffold may become a new strategy for clinical treatment of bone defects.

Cerebrospinal fluid metabolite alterations in patients with different etiologies, diagnoses, and prognoses of disorders of consciousness.

INTRODUCTION: Medical management of disorders of consciousness (DoC) is a growing issue imposing a major burden on families and societies. Recovery rates vary widely among patients with DoC, and recovery predictions strongly influence decisions on medical care. However, the specific mechanisms underlying different etiologies, consciousness levels, and prognoses are still unclear. METHODS: We analyzed the comprehensive cerebrospinal fluid (CSF) metabolome through liquid chromatography-mass spectrometry. Metabolomic analyses were used to identify the metabolic differences between patients with different etiologies, diagnoses, and prognoses. RESULTS: We found that the CSF levels of multiple acylcarnitines were lower in patients with traumatic DoC, suggesting mitochondrial function preservation in the CNS, which might contribute to the better consciousness outcomes of these patients. Metabolites related to glutamate and GABA metabolism were altered and showed a good ability to distinguish the patients in the minimally conscious state and the vegetative state. Moreover, we identified 8 phospholipids as potential biomarkers to predict the recovery of consciousness. CONCLUSIONS: Our findings shed light on the differences in physiological activities underlying DoC with different etiologies and identified some potential biomarkers used for DoC diagnosis and prognosis.