dbDEPC 3.0: the database of differentially expressed proteins in human cancer with multi-level annotation and drug indication

Circular RNA discovery with emerging sequencing and deep learning technologies

Circular RNA (circRNA) represents a type of RNA molecule characterized by a closed-loop structure that is distinct from linear RNA counterparts. Recent studies have revealed the emerging role of these circular transcripts in gene regulation and disease pathogenesis. However, their low expression levels and high sequence similarity to linear RNAs present substantial challenges for circRNA detection and characterization. Recent advances in long-read and single-cell RNA sequencing technologies, coupled with sophisticated deep learning-based algorithms, have revolutionized the investigation of circRNAs at unprecedented resolution and scale. This Review summarizes recent breakthroughs in circRNA discovery, characterization and functional analysis algorithms. We also discuss the challenges associated with integrating large-scale circRNA sequencing data and explore the potential future development of artificial intelligence (AI)-driven algorithms to unlock the full potential of circRNA research in biomedical applications.

Comparative Analysis of Molecular Functions and Biological Role of Proteins from Cell-Free DNA-Protein Complexes Circulating in Plasma of Healthy Females and Breast Cancer Patients

Cell-free DNA (cfDNA) circulates in the bloodstream packed in membrane-coated structures (such as apoptotic bodies) or bound to proteins. To identify proteins involved in the formation of deoxyribonucleoprotein complexes circulating in the blood, native complexes were isolated using affinity chromatography with immobilized polyclonal anti-histone antibodies from plasma of healthy females (HFs) and breast cancer patients (BCPs). It was found that the nucleoprotein complexes (NPCs) from HF plasma samples contained shorter DNA fragments (~180 bp) than BCP NPCs. However, the share of DNA in the NPCs from cfDNA in blood plasma in HFs and BCPs did not differ significantly, as well as the share of NPC protein from blood plasma total protein. Proteins were separated by SDS-PAGE and identified by MALDI-TOF mass spectrometry. Bioinformatic analysis showed that in the presence of a malignant tumor, the proportion of proteins involved in ion channels, protein binding, transport, and signal transduction increased in the composition of blood-circulating NPCs. Moreover, 58 (35%) proteins are differentially expressed in a number of malignant neoplasms in the NPCs of BCPs. Identified NPC proteins from BCP blood can be recommended for further testing as breast cancer diagnostic/prognostic biomarkers or as being useful in developing gene-targeted therapy approaches.

Application of Proteomics in Cancer: Recent Trends and Approaches for Biomarkers Discovery

Proteomics has become an important field in molecular sciences, as it provides valuable information on the identity, expression levels, and modification of proteins. For example, cancer proteomics unraveled key information in mechanistic studies on tumor growth and metastasis, which has contributed to the identification of clinically applicable biomarkers as well as therapeutic targets. Several cancer proteome databases have been established and are being shared worldwide. Importantly, the integration of proteomics studies with other omics is providing extensive data related to molecular mechanisms and target modulators. These data may be analyzed and processed through bioinformatic pipelines to obtain useful information. The purpose of this review is to provide an overview of cancer proteomics and recent advances in proteomic techniques. In particular, we aim to offer insights into current proteomics studies of brain cancer, in which proteomic applications are in a relatively early stage. This review covers applications of proteomics from the discovery of biomarkers to the characterization of molecular mechanisms through advances in technology. Moreover, it addresses global trends in proteomics approaches for translational research. As a core method in translational research, the continued development of this field is expected to provide valuable information at a scale beyond that previously seen.

dbGENVOC: database of GENomic Variants of Oral Cancer, with special reference to India

Oral cancer is highly prevalent in India and is the most frequent cancer type among Indian males. It is also very common in southeast Asia. India has participated in the International Cancer Genome Consortium (ICGC) and some national initiatives to generate large-scale genomic data on oral cancer patients and analyze to identify associations and systematically catalog the associated variants. We have now created an open, web-accessible database of these variants found significantly associated with Indian oral cancer patients, with a user-friendly interface to enable easy mining. We have value added to this database by including relevant data collated from various sources on other global populations, thereby providing opportunities of comparative geographical and/or ethnic analyses. Currently, no other database of similar nature is available on oral cancer. We have developed Database of GENomic Variants of Oral Cancer, a browsable online database framework for storage, retrieval and analysis of large-scale data on genomic variants and make it freely accessible to the scientific community. Presently, the web-accessible database allows potential users to mine data on ∼24 million clinically relevant somatic and germline variants derived from exomes (n = 100) and whole genomes (n = 5) of Indian oral cancer patients; all generated by us. Variant data from The Cancer Genome Atlas and data manually curated from peer-reviewed publications were also incorporated into the database for comparative analyses. It allows users to query the database by a single gene, multiple genes, multiple variant sites, genomic region, patient ID and pathway identities.

Database URL: http://research.nibmg.ac.in/dbcares/dbgenvoc/

Secretome Proteomic Approaches for Biomarker Discovery: An Update on Colorectal Cancer

Searching for new cancer-related biomarkers is a key priority for the early detection of solid tumors, such as colorectal cancer (CRC), in clinically relevant biological fluids. The cell line and/or tumor tissue secretome represents a valuable resource for discovering novel protein markers secreted by cancer cells. The advantage of a secretome analysis is the reduction of the large dynamic range characterizing human plasma/serum, and the simultaneous enrichment of low abundance cancer-secreted proteins, thereby overcoming the technical limitations underlying the direct search in blood samples. In this review, we provided a comprehensive overview of recent studies on the CRC secretome for biomarker discovery, focusing both on methodological and technical aspects of secretome proteomic approaches and on biomarker-independent validation in CRC patient samples (blood and tissues). Secretome proteomics are mainly based on LC-MS/MS analyses for which secretome samples are either in-gel or in-solution trypsin-digested. Adequate numbers of biological and technical replicates are required to ensure high reproducibility and robustness of the secretome studies. Moreover, another major challenge is the accuracy of proteomic quantitative analysis performed by label-free or labeling methods. The analysis of differentially expressed proteins in the CRC secretome by using bioinformatic tools allowed the identification of potential biomarkers for early CRC detection. In this scenario, this review may help to follow-up the recent secretome studies in order to select promising circulating biomarkers to be validated in larger screenings, thereby contributing toward a complete translation in clinical practice.

Proteomic Analysis of Blood Exosomes from Healthy Females and Breast Cancer Patients Reveals an Association between Different Exosomal Bioactivity on Non-tumorigenic Epithelial Cell and Breast Cancer Cell Migration in Vitro

Exosomes are important intercellular communication vehicles, secreted into body fluids by multiple cell types, including tumor cells. They contribute to the metastatic progression of tumor cells through paracrine signalling. It has been recently discovered that blood circulating exosomes contain distinguishable fractions of free and cell-surface-associated vesicles. We evaluated the influence of protein cargoes from exosomes from plasma, and exosomes from the total blood of healthy females (HFs) and breast cancer patients (BCPs), on cell motility. We conducted a mass spectrometric analysis of exosomal contents isolated from samples using ultrafiltration and ultracentrifugation approaches and verified their nature using transmission electron microscopy, nanoparticle tracking analysis and flow cytometry. We observed that malignant neoplasm-associated proteins in exosomes from BCP total blood were detected more often than in plasma (66% vs. 59%). FunRich analysis to assess Gene Ontology (GO) enrichment revealed that proteins with catalytic activities, transporter functions and protein metabolism activities were increased in exosomes from BCP blood. Finally, GO analysis revealed that proteomic profiles of exosomes from HF total blood were enriched with proteins inhibiting cell migration and invasion, which explains the low stimulating activity of exosomes from HF total blood on SKBR-3 cancer cell migration velocity. This allows exosomes to act as intermediaries providing intercellular communications through horizontal transfer of RNA and functionally active proteins, potentially affecting the development of both primary neoplasms and distant metastases.

Identification of ALDH6A1 as a Potential Molecular Signature in Hepatocellular Carcinoma via Quantitative Profiling of the Mitochondrial Proteome

Various liver diseases, including hepatocellular carcinoma (HCC), have been linked to mitochondrial dysfunction, reduction of reactive oxygen species (ROS), and elevation of nitric oxide (NO). In this study, we subjected the human liver mitochondrial proteome to extensive quantitative proteomic profiling analysis and molecular characterization to identify potential signatures indicative of cancer cell growth and progression. Sequential proteomic analysis identified 2452 mitochondrial proteins, of which 1464 and 2010 were classified as nontumor and tumor (HCC) mitochondrial proteins, respectively, with 1022 overlaps. Further metabolic mapping of the HCC mitochondrial proteins narrowed our biological characterization to four proteins, namely, ALDH4A1, LRPPRC, ATP5C1, and ALDH6A1. The latter protein, a mitochondrial methylmalonate semialdehyde dehydrogenase (ALDH6A1), was most strongly suppressed in HCC tumor regions (∼10-fold decrease) in contrast to LRPPRC (∼6-fold increase) and was predicted to be present in plasma. Accordingly, we selected ALDH6A1 for functional analysis and engineered Hep3B cells to overexpress this protein, called ALDH6A1-O/E cells. Since ALDH6A1 is predicted to be involved in mitochondrial respiration, we assessed changes in the levels of NO and ROS in the overexpressed cell lines. Surprisingly, in ALDH6A1-O/E cells, NO was decreased nearly 50% but ROS was increased at a similar level, while the former was restored by treatment with S-nitroso-N-acetyl-penicillamine. The lactate levels were also decreased relative to control cells. Propidium iodide and Rhodamine-123 staining suggested that the decrease in NO and increase in ROS in ALDH6A1-O/E cells could be caused by depolarization of the mitochondrial membrane potential (ΔΨ). Taken together, our results suggest that hepatic neoplastic transformation appears to suppress the expression of ALDH6A1, which is accompanied by a respective increase and decrease in NO and ROS in cancer cells. Given the close link between ALDH6A1 suppression and abnormal cancer cell growth, this protein may serve as a potential molecular signature or biomarker of hepatocarcinogenesis and treatment responses.

Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics

Knowledge of therapeutic targets and early drug candidates is useful for improved drug discovery. In particular, information about target regulators and the patented therapeutic agents facilitates research regarding druggability, systems pharmacology, new trends, molecular landscapes, and the development of drug discovery tools. To complement other databases, we constructed the Therapeutic Target Database (TTD) with expanded information about (i) target-regulating microRNAs and transcription factors, (ii) target-interacting proteins, and (iii) patented agents and their targets (structures and experimental activity values if available), which can be conveniently retrieved and is further enriched with regulatory mechanisms or biochemical classes. We also updated the TTD with the recently released International Classification of Diseases ICD-11 codes and additional sets of successful, clinical trial, and literature-reported targets that emerged since the last update. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp. In case of possible web connectivity issues, two mirror sites of TTD are also constructed (http://db.idrblab.org/ttd/ and http://db.idrblab.net/ttd/).