Quantitative global proteome and phosphorylome analyses reveal potential biomarkers in kidney cancer

Proteomic Analysis of Tear Films in Healthy Female and Male Dogs Using MALDI-TOF (Matrix Assisted Laser Desortion/Ionization Time-of-Flight) Mass Spectrometry

This study investigates sex-related differences in the tear film proteomes of healthy male and female dogs using MALDI-TOF mass spectrometry. Tear samples from 22 dogs (11 males, 11 females) were analyzed using 2D electrophoresis, revealing 446 protein spots, with 8 showing statistically significant differential expression. Seven proteins, including TIMP-2, PFK, and Annexin A13, were upregulated in females, while IL-33 was higher in males. These differences indicate potential hormonal influences on tear film composition. The results highlight molecular variations that may be relevant to ocular physiology and could contribute to identifying non-invasive diagnostic biomarkers. This study provides baseline data for future research on sex-related differences in tear film composition in dogs.

Insights on post-translational modifications in fatty liver and fibrosis progression

Metabolic dysfunction-associated steatotic liver disease [MASLD] is a pervasive multifactorial health burden. Post-translational modifications [PTMs] of amino acid residues in protein domains demonstrate pivotal roles for imparting dynamic alterations in the cellular micro milieu. The crux of identifying novel druggable targets relies on comprehensively studying the etiology of metabolic disorders. This review article presents how different chemical moieties of various PTMs like phosphorylation, methylation, ubiquitination, glutathionylation, neddylation, acetylation, SUMOylation, lactylation, crotonylation, hydroxylation, glycosylation, citrullination, S-sulfhydration and succinylation presents the cause-effect contribution towards the MASLD spectra. Additionally, the therapeutic prospects in the management of liver steatosis and hepatic fibrosis via targeting PTMs and regulatory enzymes are also encapsulated. This review seeks to understand the function of protein modifications in progression and promote the markers discovery of diagnostic, prognostic and drug targets towards MASLD management which could also halt the progression of a catalogue of related diseases.

Multi-omics profiling combined with molecular docking reveals immune-inflammatory proteins as potential drug targets in colorectal cancer

Colorectal cancer is globally ranked as the third most common malignant tumor. Its development involves a complex biological process driven by various genetic and epigenetic alterations. To elucidate the biological significance of the extensive omics data, we conducted comparative multi-omics studies on colorectal cancer patients at different clinical stages. Bioinformatics methods were applied to analyze multi-omics datasets and explore the molecular landscape. Drug prediction and molecular docking also were conducted to assess potential therapeutic interventions. In vitro experiments were used to validate the inhibitory effect on the migration and proliferation of cell lines. The results indicate up-regulated proteins involved in immune-inflammatory related pathways, while biomarkers related to muscular contraction and cell adhesion are significantly down-regulated. Drug prediction, coupled with in vitro experiments, suggests that AZ-628 may act as a potential drug to inhibit the proliferation and migration of CRC cell lines HCT-116 and HT-29 by regulating the aforementioned key biological pathways or proteins. Complementing these findings, metabolomics analysis unveiled a down-regulation of key carbon metabolism pathways, alongside an up-regulation in amino acid metabolism, particularly proline metabolism. This metabolic shift may reflect an adaptive response in cancer cells, favoring specific amino acids to support their growth. Together, these integrated results provide valuable insights into the intricate landscape of tumor development, highlighting the crossroads of immune regulation, cellular structure, and metabolic reprogramming in the tumorigenic process and providing valuable insights into cancer pathology.

In-depth analysis of lymph node metastasis-related sialylated protein profiling and their clinical and biological significance in colorectal cancer using mass spectrometry and multi-omics technologies

Colorectal cancer (CRC) lymph node metastasis (LNM) is a crucial factor affecting the prognosis and treatment outcomes of CRC patients. It has been confirmed that altered glycosylation is a key event during CRC lymphatic metastases. Sialylation is one of the most significant glycosylation alterations in tumors. However, the predictive role of sialylation and sialylated protein in CRC remains elusive, especially in CRC-LNM. In this study, we explored and identified 1102 sialylated glycoproteins in CRC-LNM using metabolic labeling strategy and proteomics analysis. Combined with comprehensive analysis with bioinformatics and machine learning algorithms, we screened 25 prognostic sialylation-related genes (SRGs) to construct a new molecular phenotype (LRSRGs-Phenotype) and a prognostic SRG signature (LRSRGs-related Gene Signature) in CRC. Then, we further confirmed that patients in different phenotypes had different prognosis, molecular biological characteristics, immune cell infiltration and could be closely linked to three previously reported immune phenotypes: immune-excluded (Phenotype A), immune-desert (Phenotype B), and immune-inflamed (Phenotype C). Besides, we evaluated and validated the LRSRGs-related gene (ACADM, EHD4, FLOT1, GPC1, GSR, LRRC8A, NGFR, SDHB, and SEC61G) signature and found the risk score was an independent risk factor for CRC prognosis. CRC patients in different risk groups had different somatic mutation, tumor microenvironment and immunotherapy response. Finally, we also identified the potential therapeutic agents for CRC patients in different risk groups. In conclusion, we explored the key sialylated glycoproteins, which may play a key role in tumor LNM and clinical outcomes. And constructed the LRSRGs-phenotype and signature with prognostic and therapeutic predictive value in CRC, hoping to provide reliable scientific basis for future treatments in CRC patients.

Advances in the Clinical Application of High-throughput Proteomics

High-throughput proteomics has become an exciting field and a potential frontier of modern medicine since the early 2000s. While significant progress has been made in the technical aspects of the field, translating proteomics to clinical applications has been challenging. This review summarizes recent advances in clinical applications of high-throughput proteomics and discusses the associated challenges, advantages, and future directions. We focus on research progress and clinical applications of high-throughput proteomics in breast cancer, bladder cancer, laryngeal squamous cell carcinoma, gastric cancer, colorectal cancer, and coronavirus disease 2019. The future application of high-throughput proteomics will face challenges such as varying protein properties, limitations of statistical modeling, technical and logistical difficulties in data deposition, integration, and harmonization, as well as regulatory requirements for clinical validation and considerations. However, there are several noteworthy advantages of high-throughput proteomics, including the identification of novel global protein networks, the discovery of new proteins, and the synergistic incorporation with other omic data. We look forward to participating in and embracing future advances in high-throughput proteomics, such as proteomics-based single-cell biology and its clinical applications, individualized proteomics, pathology informatics, digital pathology, and deep learning models for high-throughput proteomics. Several new proteomic technologies are noteworthy, including data-independent acquisition mass spectrometry, nanopore-based proteomics, 4-D proteomics, and secondary ion mass spectrometry. In summary, we believe high-throughput proteomics will drastically shift the paradigm of translational research, clinical practice, and public health in the near future.

M6A-mediated-upregulation of lncRNA BLACAT3 promotes bladder cancer angiogenesis and hematogenous metastasis through YBX3 nuclear shuttling and enhancing NCF2 transcription

Lymphatic metastasis is recognized as the leading manner of metastasis in bladder cancer (BLCa), but hematogenous metastasis accounts for a majority of cancer-associated deaths. The past two decades have witnessed tremendous attention in long non-coding RNAs (lncRNAs), which are a new hope for the development of targeted drug therapy for metastatic cancers; however, the underlying mechanism of lncRNAs involved in BLCa hematogenous metastasis remains to be elucidated. Here, we identified BLCa-associated transcript 3 (BLACAT3), a lncRNA, which was aberrantly upregulated in BLCa and corelated with poor prognosis of patients with muscle-invasive bladder cancer. Methodologically, m6A epitranscriptomic microarray, RNA sequencing and mass spectrometry (MS) were used to screen the key molecules of the regulatory axis. Functional assays, animal models and clinical samples were used to explore the roles of BLACAT3 in BLCa in vitro and in vivo. Mechanistically, m6A modification contributes to BLACAT3 upregulation by stabilizing RNA structure. BLACAT3 recruits YBX3 to shuttle into the nucleus, synergistically enhances NCF2 transcription, and promotes BLCa angiogenesis and hematogenous metastasis by activating downstream NF-κB signaling. Our findings will develop prognosis prediction tools for BLCa patients and discover novel therapeutic biological targets for metastatic BLCa.

Phosphorylated Proteins from Serum: A Promising Potential Diagnostic Biomarker of Cancer

Cancer is a fatal disease worldwide. Each year ten million people are diagnosed around the world, and more than half of patients eventually die from it in many countries. A majority of cancer remains asymptomatic in the earlier stages, with specific symptoms appearing in the advanced stages when the chances of adequate treatment are low. Cancer screening is generally executed by different imaging techniques like ultrasonography (USG), mammography, CT-scan, and magnetic resonance imaging (MRI). Imaging techniques, however, fail to distinguish between cancerous and non-cancerous cells for early diagnosis. To confirm the imaging result, solid and liquid biopsies are done which have certain limitations such as invasive (in case of solid biopsy) or missed early diagnosis due to extremely low concentrations of circulating tumor DNA (in case of liquid biopsy). Therefore, it is essential to detect certain biomarkers by a noninvasive approach. One approach is a proteomic or glycoproteomic study which mostly identifies proteins and glycoproteins present in tissues and serum. Some of these studies are approved by the Food and Drug Administration (FDA). Another non-expensive and comparatively easier method to detect glycoprotein biomarkers is by ELISA, which uses lectins of diverse specificities. Several of the FDA approved proteins used as cancer biomarkers do not show optimal sensitivities for precise diagnosis of the diseases. In this regard, expression of phosphoproteins is associated with a more specific stage of a particular disease with high sensitivity and specificity. In this review, we discuss the expression of different serum phosphoproteins in various cancers. These phosphoproteins are detected either by phosphoprotein enrichment by immunoprecipitation using phosphospecific antibody and metal oxide affinity chromatography followed by LC-MS/MS or by 2D gel electrophoresis followed by MALDI-ToF/MS analysis. The updated knowledge on phosphorylated proteins in clinical samples from various cancer patients would help to develop these serum phophoproteins as potential diagnostic/prognostic biomarkers of cancer.

A Fatty Acid Metabolism Signature Associated With Clinical Therapy in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma is one of the most common tumors in the urinary system, among which clear cell renal cell carcinoma is the most common subtype with poor prognosis. As one of the tumors closely related to lipid metabolism, the role of fatty acid metabolism in ccRCC was investigated to predict the prognosis and guide treatment strategies. RNA-seq and clinical information of patients with ccRCC and expression microarray of human renal cell carcinoma cell lines were obtained from TCGA and GEO databases. Fatty acid metabolism–related risk signature was established by the univariate Cox regression and LASSO analysis to predict patient prognosis and response to different treatment modalities. Using the fatty acid metabolism risk signature, the risk score for each sample in the TCGA cohort was calculated and divided into high-risk and low-risk groups, with the cutoff point being the median. Patients with higher risk scores had a poorer prognosis than those with lower risk scores. The response of each sample to immunotherapy was predicted from the “TIDE” algorithm, while the sensitivity of each sample to sunitinib was obtained using the “pRRophetic” R package. Patients with lower risk scores had higher expression of PD-L1 and better efficacy for sunitinib than those in the high-risk group and were less likely to develop drug resistance, while patients with high-risk scores had a strong response to the anti-CTLA4 antibody therapy. A nomogram was constructed by independent prognostic factors to predict the 1-, 3-, and 5-year survival. According to the calibration curves, the nomogram had an excellent ability to predict survival for patients with ccRCC. Therefore, the fatty acid metabolism risk signature we established can not only predict the survival of patients with ccRCC but also predict patient response to targeted therapy and immunotherapy to provide optimal treatment strategies for patients.