Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation

Bioinformatics and experimental insights into F2RL1 as a key biomarker in cervical cancer diagnosis and prognosis

Cervical cancer(CCa) remains a significant global public health concern, with early diagnosis and treatment being crucial. Moreover, the molecular mechanisms underlying its pathogenesis remain incompletely elucidated. F2RL1 is closely associated with various tumors. However, its relationship with CCa is poorly understood. We accessed data from 309 patients diagnosed with CCa from TCGA database. The Limma package facilitated differential expression analysis to identify differentially expressed mRNAs (DEmRNAs). Survival analysis and ROC analysis were conducted via the XIANTAO database. Immune-related genes were identified with F2RL1-related genes through ImmPort database analysis. Functional enrichment analysis was carried out using GO, KEGG, and GSEA. We gathered cervical cells and serum from participants to test for HPV and TCT, and then used qPCR to check the levels of F2RL1 mRNA expression. We also verified the expression of F2RL1 protein through WB and ELISA techniques. Our investigation has unveiled a fascinating discovery-the levels of F2RL1 expression in CCa tissues are notably elevated when compared to normal tissues, showcasing intriguing variations among various pathological types. Moreover, the presence of high F2RL1 expression is linked to reduce Overall Survival (OS), Progression Free Interval (PFI), Progression Free Survival (PFS). F2RL1 rocked the ROC analysis with an AUC of 0.996. Furthermore, F2RL1 expression levels significantly impact CCa in different N stages, pathological tissue types, treatment statuses, and racial groups, allowing us to develop a predictive model. Additionally, we identified 43 immune-related genes. Enrichment analysis highlighting their association with pathways related to cell movement and T cell activation. Through analysis, we discovered an inverse proportion between F2RL1 expression and the infiltration of most immune cells, particularly TFH and cytotoxic cells, suggesting a potential link to immune evasion in CCa. Molecular biology experiments also confirmed a significant increase in F2RL1 expression in cervical exfoliated cells and serum. Our research uncovers the predictive and early detection significance of F2RL1 in CCa and its correlation with immune infiltration for the first time. F2RL1 is strongly linked to the progression of CCa and could serve as a biomarker for the early diagnosis and prognosis of CCa patients.

Integrated View of Baseline Protein Expression in Human Tissues Using Public Data Independent Acquisition Data Sets

The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse. We have reanalyzed 15 public label-free DIA data sets across various healthy human tissues to provide a state-of-the-art view of the human proteome in baseline conditions (without any perturbations). We computed baseline protein abundances and compared them across various tissues, samples, and data sets. Our second aim was to compare protein abundances obtained here from the results of previous analyses using human baseline data-dependent acquisition (DDA) data sets. We observed a good correlation across some tissues, especially in the liver and colon, but weak correlations were found in others, such as the lung and pancreas. The reanalyzed results including protein abundance values and curated metadata are made available to view and download from the resource Expression Atlas.

The PRIDE database at 20 years: 2025 update

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's leading mass spectrometry (MS)-based proteomics data repository and one of the founding members of the ProteomeXchange consortium. This manuscript summarizes the developments in PRIDE resources and related tools for the last three years. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 534 datasets per month. This has been possible thanks to continuous improvements in infrastructure such as a new file transfer protocol for very large datasets (Globus), a new data resubmission pipeline and an automatic dataset validation process. Additionally, we will highlight novel activities such as the availability of the PRIDE chatbot (based on the use of open-source Large Language Models), and our work to improve support for MS crosslinking datasets. Furthermore, we will describe how we have increased our efforts to reuse, reanalyze and disseminate high-quality proteomics data into added-value resources such as UniProt, Ensembl and Expression Atlas.

Integrated Proteomics Analysis of Baseline Protein Expression in Pig Tissues

The availability of an increasingly large amount of public proteomics data sets presents an opportunity for performing combined analyses to generate comprehensive organism-wide protein expression maps across different organisms and biological conditions. Sus scrofa, a domestic pig, is a model organism relevant for food production and for human biomedical research. Here, we reanalyzed 14 public proteomics data sets from the PRIDE database coming from pig tissues to assess baseline (without any biological perturbation) protein abundance in 14 organs, encompassing a total of 20 healthy tissues from 128 samples. The analysis involved the quantification of protein abundance in 599 mass spectrometry runs. We compared protein expression patterns among different pig organs and examined the distribution of proteins across these organs. Then, we studied how protein abundances were compared across different data sets and studied the tissue specificity of the detected proteins. Of particular interest, we conducted a comparative analysis of protein expression between pig and human tissues, revealing a high degree of correlation in protein expression among orthologs, particularly in brain, kidney, heart, and liver samples. We have integrated the protein expression results into the Expression Atlas resource for easy access and visualization of the protein expression data individually or alongside gene expression data.

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Precision medicine is transforming colorectal cancer treatment through the integration of advanced technologies and biomarkers, enhancing personalized and effective disease management. Identification of key driver mutations and molecular profiling have deepened our comprehension of the genetic alterations in colorectal cancer, facilitating targeted therapy and immunotherapy selection. Biomarkers such as microsatellite instability (MSI) and DNA mismatch repair deficiency (dMMR) guide treatment decisions, opening avenues for immunotherapy. Emerging technologies such as liquid biopsies, artificial intelligence, and machine learning promise to revolutionize early detection, monitoring, and treatment selection in precision medicine. Despite these advancements, ethical and regulatory challenges, including equitable access and data privacy, emphasize the importance of responsible implementation. The dynamic nature of colorectal cancer, with its tumor heterogeneity and clonal evolution, underscores the necessity for adaptive and personalized treatment strategies. The future of precision medicine in colorectal cancer lies in its potential to enhance patient care, clinical outcomes, and our understanding of this intricate disease, marked by ongoing evolution in the field. The current reviews focus on providing in-depth knowledge on the various and diverse approaches utilized for precision medicine against colorectal cancer, at both molecular and biochemical levels.

The role and mechanism of TXNDC5 in disease progression

Thioredoxin domain containing protein-5 (TXNDC5), also known as endothelial protein-disulfide isomerase (Endo-PDI), is confined to the endoplasmic reticulum through the structural endoplasmic reticulum retention signal (KDEL), is a member of the PDI protein family and is highly expressed in the hypoxic state. TXNDC5 can regulate the rate of disulfide bond formation, isomerization and degradation of target proteins through its function as a protein disulfide isomerase (PDI), thereby altering protein conformation, activity and improving protein stability. Several studies have shown that there is a significant correlation between TXNDC5 gene polymorphisms and genetic susceptibility to inflammatory diseases such as rheumatoid, fibrosis and tumors. In this paper, we detail the expression characteristics of TXNDC5 in a variety of diseases, summarize the mechanisms by which TXNDC5 promotes malignant disease progression, and summarize potential therapeutic strategies to target TXNDC5 for disease treatment.