Autoantibody Response to ZRF1 and KRR1 SEREX Antigens in Patients with Breast Tumors of Different Histological Types and Grades

UTP23 Is a Promising Prognostic Biomarker and Is Associated with Immune Infiltration in Breast Cancer

Breast cancer is one of the malignant tumors with a high incidence and mortality rate among women worldwide, and its prevalence is increasing year by year, posing a serious health risk to women. UTP23 (UTP23 Small Subunit Processome Component) is a nucleolar protein that is essential for ribosome production. As we all know, disruption of ribosome structure and function results in improper protein function, affecting the body's normal physiological processes and promoting cancer growth. However, little research has shown a connection between UTP23 and cancer. We analyzed the mRNA expression of UTP23 in normal tissue and breast cancer using The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, and the protein expression of UTP23 using The Human Protein Atlas (HPA) database. Next, we examined the relationship between UTP23 high expression and Overall Survival (OS) using Kaplan-Meier Plotters and enriched 980 differentially expressed genes in UTP23 high and low expression samples using GO/KEGG and GSEA to identify potential biological functions of UTP23 and signaling pathways that it might influence. Finally, we also investigated the relationship between UTP23 and immune infiltration and examined the effect of UTP23 on the proliferation of human breast cancer cell lines by knocking down UTP23. We found that UTP23 levels in breast cancer patient samples were noticeably greater than those in healthy individuals and that high UTP23 levels were strongly linked with poor prognoses (P = 0.008). Functional enrichment analysis revealed that UTP23 expression was connected to the humoral immune response. Besides, UTP23 expression was found to be positively correlated with immune cell infiltration. Furthermore, UTP23 knockdown has been shown to inhibit the proliferation of human breast cancer cells MDA-MB-231 and HCC-1806. Taken together, our study demonstrated that UTP23 is a promising target in detecting and treating breast cancer and is intimately linked to immune infiltration.

Identification of Cancer Driver Genes by Integrating Multiomics Data with Graph Neural Networks

Cancer is a heterogeneous disease that is driven by the accumulation of both genetic and nongenetic alterations, so integrating multiomics data and extracting effective information from them is expected to be an effective way to predict cancer driver genes. In this paper, we first generate comprehensive instructive features for each gene from genomic, epigenomic, transcriptomic levels together with protein–protein interaction (PPI)-networks-derived attributes and then propose a novel semisupervised deep graph learning framework GGraphSAGE to predict cancer driver genes according to the impact of the alterations on a biological system. When applied to eight tumor types, experimental results suggest that GGraphSAGE outperforms several state-of-the-art computational methods for driver genes identification. Moreover, it broadens our current understanding of cancer driver genes from multiomics level and identifies driver genes specific to the tumor type rather than pan-cancer. We expect GGraphSAGE to open new avenues in precision medicine and even further predict drivers for other complex diseases.

A Master Autoantigen-ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases

Chronic and debilitating autoimmune sequelae pose a grave concern for the post-COVID-19 pandemic era. Based on our discovery that the glycosaminoglycan dermatan sulfate (DS) displays peculiar affinity to apoptotic cells and autoantigens (autoAgs) and that DS-autoAg complexes cooperatively stimulate autoreactive B1 cell responses, we compiled a database of 751 candidate autoAgs from six human cell types. At least 657 of these have been found to be affected by SARS-CoV-2 infection based on currently available multi-omic COVID data, and at least 400 are confirmed targets of autoantibodies in a wide array of autoimmune diseases and cancer. The autoantigen-ome is significantly associated with various processes in viral infections, such as translation, protein processing, and vesicle transport. Interestingly, the coding genes of autoAgs predominantly contain multiple exons with many possible alternative splicing variants, short transcripts, and short UTR lengths. These observations and the finding that numerous autoAgs involved in RNA-splicing showed altered expression in viral infections suggest that viruses exploit alternative splicing to reprogram host cell machinery to ensure viral replication and survival. While each cell type gives rise to a unique pool of autoAgs, 39 common autoAgs associated with cell stress and apoptosis were identified from all six cell types, with several being known markers of systemic autoimmune diseases. In particular, the common autoAg UBA1 that catalyzes the first step in ubiquitination is encoded by an X-chromosome escape gene. Given its essential function in apoptotic cell clearance and that X-inactivation escape tends to increase with aging, UBA1 dysfunction can therefore predispose aging women to autoimmune disorders. In summary, we propose a model of how viral infections lead to extensive molecular alterations and host cell death, autoimmune responses facilitated by autoAg-DS complexes, and ultimately autoimmune diseases. Overall, this master autoantigen-ome provides a molecular guide for investigating the myriad of autoimmune sequalae to COVID-19 and clues to the rare but reported adverse effects of the currently available COVID vaccines.

DNAJC2 is reversely regulated by miR‑627‑3p, promoting the proliferation of colorectal cancer

Colorectal cancer (CRC) is one of the most common malignancies among human, which is often connected with increased incidence and mortality rate. DnaJ Heat Shock Protein Family (Hsp40) Member C2 (DNAJC2) is an epigenetic factor, which is involved in a number of cytological functions, such as transcriptional regulation and ubiquitination. A number of studies reveal that DNAJC2 is closely associated with several tumors. However, the function and mechanism of DNAJC2 in CRC remains to be elucidated. In the present study, the expression of DNAJC2 was detected in CRC tissues and adjacent normal tissues. The results indicated that DNAJC2 was increased in CRC tissues and the expression level of DNAJC2 was significantly associated with tumor size. Cell function was detected via Cell Counting Kit-8, 5-ethynyl-2′-deoxyuridine, colony formation assays and flow cytometry by upregulating or knocking down of DNAJC2. Overexpression of DNAJC2 could accelerate cell proliferation while suppression of DNAJC2 decreased cell proliferation, possibly via the regulation of cell cycle regulation in vitro. It was also found that the function of DNAJC2 was reversely regulated by miR-672-3p, causing the promoting of cell proliferation through the activation of AKT/P21 signal pathway in CRC cells. These results suggested that DNAJC2 is a tumor-regulated protein in the progression of CRC and may represent a novel target for CRC detection and therapy.

An Autoantigen Profile of Human A549 Lung Cells Reveals Viral and Host Etiologic Molecular Attributes of Autoimmunity in COVID-19

We aim to establish a comprehensive COVID-19 autoantigen atlas in order to understand autoimmune diseases caused by SARS-CoV-2 infection. Based on the unique affinity between dermatan sulfate and autoantigens, we identified 348 proteins from human lung A549 cells, of which 198 are known targets of autoantibodies. Comparison with current COVID data identified 291 proteins that are altered at protein or transcript level in SARS-CoV-2 infection, with 191 being known autoantigens. These known and putative autoantigens are significantly associated with viral replication and trafficking processes, including gene expression, ribonucleoprotein biogenesis, mRNA metabolism, translation, vesicle and vesicle-mediated transport, and apoptosis. They are also associated with cytoskeleton, platelet degranulation, IL-12 signaling, and smooth muscle contraction. Host proteins that interact with and that are perturbed by viral proteins are a major source of autoantigens. Orf3 induces the largest number of protein alterations, Orf9 affects the mitochondrial ribosome, and they and E, M, N, and Nsp proteins affect protein localization to membrane, immune responses, and apoptosis. Phosphorylation and ubiquitination alterations by viral infection define major molecular changes in autoantigen origination. This study provides a large list of autoantigens as well as new targets for future investigation, e.g., UBA1, UCHL1, USP7, CDK11A, PRKDC, PLD3, PSAT1, RAB1A, SLC2A1, platelet activating factor acetylhydrolase, and mitochondrial ribosomal proteins. This study illustrates how viral infection can modify host cellular proteins extensively, yield diverse autoantigens, and trigger a myriad of autoimmune sequelae.

Immunoproteomics Methods and Techniques

The varied landscape of the adaptive immune response is determined by the peptides presented by immune cells, derived from viral or microbial pathogens or cancerous cells. The study of immune biomarkers or antigens is not new, and classical methods such as agglutination, enzyme-linked immunosorbent assay, or Western blotting have been used for many years to study the immune response to vaccination or disease. However, in many of these traditional techniques, protein or peptide identification has often been the bottleneck. Recent progress in genomics and mass spectrometry have led to many of the rapid advances in proteomics approaches. Immunoproteomics describes a rapidly growing collection of approaches that have the common goal of identifying and measuring antigenic peptides or proteins. This includes gel-based, array-based, mass spectrometry-based, DNA-based, or in silico approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers. This review gives an overview of immunoproteomics and closely related technologies that are used to define the full set of protein antigens targeted by the immune system during disease.

Role for the transcriptional activator ZRF1 in early metastatic events in breast cancer progression and endocrine resistance

Breast cancer is one of the most common malignancies among women which is often treated with hormone therapy and chemotherapy. Despite the improvements in detection and treatment of breast cancer, the vast majority of breast cancer patients are diagnosed with metastatic disease either at the beginning of the disease or later during treatment. Still, the molecular mechanisms causing a therapy resistant metastatic breast cancer are still elusive. In the present study we addressed the function of the transcriptional activator ZRF1 during breast cancer progression. We provide evidence that ZRF1 plays an essential role for the early metastatic events in vitro and acts like a tumor suppressor protein during the progression of breast invasive ductal carcinoma into a more advanced stage. Hence, depletion of ZRF1 results in the acquisition of metastatic behavior by facilitating the initiation of the metastatic cascade, notably for cell adhesion, migration and invasion. Furthermore absence of ZRF1 provokes endocrine resistance via misregulation of cell death and cell survival related pathways. Taken together, we have identified ZRF1 as an important regulator of breast cancer progression that holds the potential to be explored for new treatment strategies in the future.

Screening for implicated genes in colorectal cancer using whole‑genome gene expression profiling

To identify biologically relevant genes associated with the pathogenesis of colorectal cancer (CRC), genome wide expression profiles of 17 pairs of CRC tumor and adjacent tissues, previously published in a DNA microarray study, were analyzed. Cytoscape, String tools and DAVID tools were used to investigate the biological pathways encoded by the genes identified as being either upregulated or downregulated in CRC, to determine protein-protein interactions and to identify potential hub genes associated with CRC. As a result, a total of 3,264 genes were identified as being differentially expressed in CRC and adjacent tissues, including 1,594 downregulated and 1,670 upregulated genes. Furthermore, 306 genes were revealed to be clustered in a complex interaction network, and the top 20 hub genes in this network were determined by application of the Matthews Correlation Coefficient algorithm. In addition, the patterns of the expression levels of the 20 hub genes were investigated using reverse transcription-quantitative polymerase chain reaction. Gene Ontology analysis revealed that four of the 20 hub genes encoded small subunit processome components (UTP3 small subunit processome component; UTP14 small subunit processome component; UTP 18 small subunit processome component; and UTP20 small subunit processome component) and a further four encoded WD repeat domains (WD repeat-containing protein 3, WD repeat domain 12, WD repeat-containing protein 43 and WD repeat-containing protein 75). In conclusion, the present DNA microarray study identified genes involved in the pathogenesis of CRC. Furthermore, it was revealed that hub genes identified from among the total identified upregulated and downregulated genes in CRC encoding subunit processome components and WD repeat domains may represent novel target molecules for future treatments of CRC.