The Human Protein Atlas--a tool for pathology

Soluble isoforms of the DC-SIGN receptor can increase the dengue virus infection in immature dendritic cells

Dengue is a disease with a high-impact on public health worldwide. Many researches have focused on the cell receptors involved in its pathogenesis. The role of soluble isoforms of DC-SIGN (Dendritic Cell-Specific ICAM-3 Grabbing Non-integrin) receptor in the process of Dengue Virus (DENV) infection is not well understood. This work proposes to evaluate changes in the infection process of Immature Dendritic Cells (iDCs) by DENV in the presence of DC-SIGN recombinant soluble isoforms 8, 10, and 12. The recombinant isoforms were built by heterologous expression, the DENV-2 was multiplied in the Aedes albopictus C6/36 cells and quantified in BHK-21 cells, and the iDCs were produced from the THP-1 strain. Infection assays were performed in the presence of iDCs, DENV-2, and isoforms 8, 10, and 12 separately at 25, 50 and 100 ng/mL. The final viral load was estimated by qPCR and statistical analysis was performed by Kruskal-Wallis and ANOVA tests. The iDC profile was confirmed by increasing expression of CD11c, CD86, and CD209 surface markers and maintaining CD14 expression. Infection assays demonstrated a 23-fold increase in DENV viral load in the presence of isoforms 8 and 10 at 100 ng/mL compared to the viral control (p < 0.05), while isoform 12 did not alter the viral load. It was possible to conclude that at 100 ng/mL isoforms (8 and 10) can interact with DENV, increasing viral infection, and potentially acting as opsonins.

Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given that abnormal reprogramming of asparagine metabolism (AM) has emerged as an emerging therapeutic target for anti-tumor therapy. However, the clinical significance of abnormal reprogramming of AM in LUAD patients is unclear. In this study, we collected 864 asparagine metabolism-related genes (AMGs) and used a machine-learning computational framework to develop an asparagine metabolism immunity index (AMII) for LUAD patients. Through the utilization of median AMII scores, LUAD patients were segregated into either a low-AMII group or a high-AMII group. We observed outstanding performance of AMII in predicting survival prognosis in LUAD patients in the TCGA-LUAD cohort and in three externally independently validated GEO cohorts (GSE72094, GSE37745, and GSE30219), and poorer prognosis for LUAD patients in the high-AMII group. The results of univariate and multivariate analyses showed that AMII can be used as an independent risk factor for LUAD patients. In addition, the results of C-index analysis and decision analysis showed that AMII-based nomograms had a robust performance in terms of accuracy of prognostic prediction and net clinical benefit in patients with LUAD. Excitingly, LUAD patients in the low-AMII group were more sensitive to commonly used chemotherapeutic drugs. Consequently, AMII is expected to be a novel diagnostic tool for clinical classification, providing valuable insights for clinical decision-making and personalized management of LUAD patients.

Characterisation of Kürsteiner canals of parathyroid: imparting relevance to a one-and-a-quarter-century-old concept

AIMS

Kürsteiner canals (KC) were described at least 125 years ago as pharyngeal pouch embryological remnants of parathyroid and thymic development. While considered precursors for a subset of parathyroid cysts and salivary heterotopias (SH), they remain enigmatic. We now define a comprehensive phenotype of KC remnants and investigate their role in a spectrum of parathyroid lesions.

METHODS AND RESULTS

`Sixty-two cystic and 22 non-cystic parathyroid lesions (73 patients) were retrieved from our institutional archive (2011-23) and evaluated for the presence of KC and prevalence of KC phenotype in parathyroid hormone (PTH)-positive and PTH-negative cysts. KC phenotype was defined as: cysts and tubules with surrounding sclerosis; bland, unilayered lining with frequent nuclear indentation of lumina; vesicular chromatin relative to chief cells; attenuated eosinophilic to 'hyper-cleared' cytoplasm; and staining pattern PTH-negative, SOX-10-positive, CK7-positive, GATA-3-positive and PAX-9 dim, a subset with oestrogen/progesterone receptor (ER/PR) positivity. Thirty PTH-negative cysts were identified in the neck/mediastinum; 14 of this group also showed SH. Thirty-two PTH-positive cysts included: 11 cystic parathyroid adenomas, 17 hyperplastic parathyroids, and four carcinomas. KC showed two distinct subtypes and were often found near PTH-negative cysts. PTH-negative cysts were associated with inferior parathyroids, SOX-10 positivity, fibrosclerosis, vesicular nuclei indenting cyst lumina and hyper-cleared or attenuated eosinophilic cytoplasm.

CONCLUSIONS

KC are common in parathyroids and show a distinct histological and immunohistochemical profile, with an inferior predilection favouring branchial cleft III distribution. Diagnostically, the high prevalence of this phenotype in PTH-negative cysts and salivary heterotopia supports derivation of non-functioning cysts from KC. Conversely, PTH-positive cysts are more compatible with cystic change within hyperfunctioning glands.

Development and validation of a mitotic catastrophe-related genes prognostic model for breast cancer

Background

Breast cancer has become the most common malignant tumor in women worldwide. Mitotic catastrophe (MC) is a way of cell death that plays an important role in the development of tumors. However, the exact relationship between MC-related genes (MCRGs) and the development of breast cancer is still unclear, and further research is needed to elucidate this complexity.

Methods

Transcriptome data and clinical data of breast cancer were downloaded from the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. We identified differential expression of MCRGs by comparing tumor tissue with normal tissue. Subsequently, we used COX regression analysis and LASSO regression analysis to construct the prognosis risk model of MCRGs. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the predictive ability of prognostic model. Moreover, the clinical relevance, gene set enrichment analysis (GSEA), immune landscape, tumor mutation burden (TMB), and immunotherapy and drug sensitivity analysis between high-risk and low-risk groups were systematically investigated. Finally, we validated the expression levels of genes involved in constructing the prognostic model through real-time quantitative polymerase chain reaction (RT-qPCR) at the cellular and tissue levels.

Results

We identified 12 prognostic associated MCRGs, four of which were selected to construct prognostic model. The Kaplan-Meier analysis suggested that patients in the high-risk group had a shorter overall survival (OS). The Cox regression analysis and ROC analysis indicated that risk model had independent and excellent ability in predicting prognosis of breast cancer patients. Mechanistically, a remarkable difference was observed in clinical relevance, GSEA, immune landscape, TMB, immunotherapy response, and drug sensitivity analysis. RT-qPCR results showed that genes involved in constructing the prognostic model showed significant abnormal expressions and the expression change trends were consistent with the bioinformatics results.

Conclusions

We established a prognosis risk model based on four MCRGs that had the ability to predict clinical prognosis and immune landscape, proposing potential therapeutic targets for breast cancer.

Deciphering the role of FOXP4 in long COVID: exploring genetic associations, evolutionary conservation, and drug identification through bioinformatics analysis

Long COVID (LC) refers to a condition characterized by a variety of lingering symptoms that persist for more than 4 to 12 weeks following the initial acute SARS-CoV-2 infection. Recent research has suggested that the FOXP4 gene could potentially be a significant factor contributing to LC. Owing to that, this study investigates FOXP4's role in LC by analyzing public datasets to understand its evolution and expression in diverse human populations and searching for drugs to reduce LC symptoms. Population genetic analysis of FOXP4 across human populations unmasks distinct genetic diversity patterns and positive selection signatures, suggesting potential population-specific susceptibilities to conditions like LC. Further, we also observed that FOXP4 experiences high expression during LC. To identify potential inhibitors, drug screening analysis identifies synthetic drugs like Glisoxepide, and natural compounds Kapurimycin A3 produced from Streptomyces sp, and Cucurbitacin B from Begonia nantoensis as promising candidates. Overall, our research contributes to understanding how FOXP4 may serve as a therapeutic target for mitigating the impact of LC.

Combinatory Effects of Acrylamide and Deoxynivalenol on In Vitro Cell Viability and Cytochrome P450 Enzymes of Human HepaRG Cells

Acrylamide (AA) can be formed during the thermal processing of carbohydrate-rich foods. Deoxynivalenol (DON), a mycotoxin produced by Fusarium spp., contaminates many cereal-based products. In addition to potential co-exposure through a mixed diet, co-occurrence of AA and DON in thermally processed cereal-based products is also likely, posing the question of combinatory toxicological effects. In the present study, the effects of AA (0.001-3 mM) and DON (0.1-30 µM) on the cytotoxicity, gene transcription, and expression of major cytochrome P450 (CYP) enzymes were investigated in differentiated human hepatic HepaRG cells. In the chosen ratios of AA-DON (10:1; 100:1), cytotoxicity was clearly driven by DON and no overadditive effects were observed. Using quantitative real-time PCR, about twofold enhanced transcript levels of CYP1A1 were observed at low DON concentrations (0.3 and 1 µM), reflected by an increase in CYP1A activity in the EROD assay. In contrast, CYP2E1 and CYP3A4 gene transcription decreased in a concentration-dependent manner after incubation with DON (0.01-0.3 µM). Nevertheless, confocal microscopy showed comparably constant protein levels. The present study provided no indication of an induction of CYP2E1 as a critical step in AA bioactivation by co-occurrence with DON. Taken together, the combination of AA and DON showed no clear physiologically relevant interaction in HepaRG cells.

Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Cleanup Techniques

The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identifications. Single-pot, solid-phase-enhanced sample preparation (SP3) is a cleanup technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. Recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer cleanup technique that employs protein aggregation to capture proteins without modified particles. We hypothesize that differences in capture mechanisms of SP3 and SP4 affect which proteins are identified by each cleanup technique. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. Ultimately, we demonstrate that protein-capture mechanisms are distinct, and the selection of a cleanup technique that yields high proteome coverage is dependent on protein-sample hydrophobicity. Data has been deposited into MassIVE (MSV000094130) and ProteomeXchange (PXD049965).

Schistosoma japonicumsja-let-7 Inhibits the Growth of Hepatocellular Carcinoma Cells via Cross-Species Regulation of Col1α2

Liver fibrosis, a critical precursor to hepatocellular carcinoma (HCC), results from chronic liver injury and significantly contributes to HCC progression. Schistosomiasis, a neglected tropical disease, is known to cause liver fibrosis; however, this process can be modulated by schistosome-derived miRNAs. Previous studies from our laboratory have demonstrated that Schistosoma japonicum extracellular vesicles (EVs) deliver sja-let-7 to hepatic stellate cells, leading to the inhibition of Col1α2 expression and alleviation of liver fibrosis. Given the well-documented antifibrotic and antiproliferative properties of the let-7 miRNA family, this study aims to preliminarily investigate the effects of the sja-let-7/Col1α2 axis on BALB/c mice and HCC cell line SNU387, providing a basis for the potential application of parasite-derived molecules in HCC therapy. In the present study, schistosome-induced fibrosis datasets were analyzed to identify the role of Col1α2 in extracellular matrix organization. Pan-cancer analysis revealed that Col1α2 is upregulated in various cancers, including HCC, with significant associations with immune cell infiltration and clinical parameters, highlighting its diagnostic importance. Functional assays demonstrated that transfection with sja-let-7 mimics significantly reduced Col1α2 expression, inhibited HCC cell proliferation, migration, and colony formation. These findings suggest that sja-let-7, by targeting Col1α2, has the potential to serve as a therapeutic agent in HCC treatment. This study indicates the pivotal role of Col1α2 in liver fibrosis and HCC, and the promising therapeutic application of helminth-derived miRNAs.

RIT2 regulates autophagy lysosomal pathway induction and protects against α-synuclein pathology in a cellular model of Parkinson's disease

Substantial work has been devoted to better understand the contribution of the myriad of genes that may underly the development of Parkinson's disease (PD) and their role in disease etiology. The small GTPase Ras-like without CAAX2 (RIT2) is one such genetic risk factor, with one single nucleotide polymorphism in the RIT2 locus, rs12456492, having been associated with PD risk in multiple populations. While RIT2 has previously been shown to influence signaling pathways, dopamine transporter trafficking, and LRRK2 activity, its cellular function remains unclear. In the current study, we have situated RIT2 to be upstream of various diverse processes associated with PD. In cellular models, we have shown that RIT2 is necessary for activity-dependent changes in the expression of genes related to the autophagy-lysosomal pathway (ALP) by regulating the nuclear translocation of MiT/TFE3-family transcription factors. RIT2 is also associated with lysosomes and can regulate autophagic flux and clearance by regulating lysosomal hydrolase expression and activity. Interestingly, upregulation of RIT2 can augment ALP flux and protect against α-synuclein aggregation in cortical neurons. Taken together, the present study suggests that RIT2 can regulates gene expression upstream of ALP function and that enhancing RIT2 activity may provide therapeutic benefit in PD.

ZBTB46 coordinates angiogenesis and immunity to control tumor outcome

Tumor angiogenesis and immunity show an inverse correlation in cancer progression and outcome1. Here, we report that ZBTB46, a repressive transcription factor and a widely accepted marker for classical dendritic cells (DCs)2,3, controls both tumor angiogenesis and immunity. Zbtb46 was downregulated in both DCs and endothelial cells by tumor-derived factors to facilitate robust tumor growth. Zbtb46 downregulation led to a hallmark pro-tumor microenvironment (TME), including dysfunctional vasculature and immunosuppressive conditions. Analysis of human cancer data revealed a similar association of low ZBTB46 expression with an immunosuppressive TME and a worse prognosis. In contrast, enforced Zbtb46 expression led to TME changes to restrict tumor growth. Mechanistically, Zbtb46-deficient endothelial cells were highly angiogenic, and Zbtb46-deficient bone marrow progenitors upregulated Cebpb and diverted the DC program to immunosuppressive myeloid lineage output, potentially explaining the myeloid lineage skewing phenomenon in cancer4. Conversely, enforced Zbtb46 expression normalized tumor vessels and, by suppressing Cebpb, skewed bone marrow precursors toward immunostimulatory myeloid lineage output, leading to an immune-hot TME. Remarkably, Zbtb46 mRNA treatment synergized with anti-PD1 immunotherapy to improve tumor management in preclinical models. These findings identify ZBTB46 as a critical factor for angiogenesis and for myeloid lineage skewing in cancer and suggest that maintaining its expression could have therapeutic benefits.

A TNIP1-driven systemic autoimmune disorder with elevated IgG4

Whole-exome sequencing of two unrelated kindreds with systemic autoimmune disease featuring antinuclear antibodies with IgG4 elevation uncovered an identical ultrarare heterozygous TNIP1Q333P variant segregating with disease. Mice with the orthologous Q346P variant developed antinuclear autoantibodies, salivary gland inflammation, elevated IgG2c, spontaneous germinal centers and expansion of age-associated B cells, plasma cells and follicular and extrafollicular helper T cells. B cell phenotypes were cell-autonomous and rescued by ablation of Toll-like receptor 7 (TLR7) or MyD88. The variant increased interferon-β without altering nuclear factor kappa-light-chain-enhancer of activated B cells signaling, and impaired MyD88 and IRAK1 recruitment to autophagosomes. Additionally, the Q333P variant impaired TNIP1 localization to damaged mitochondria and mitophagosome formation. Damaged mitochondria were abundant in the salivary epithelial cells of Tnip1Q346P mice. These findings suggest that TNIP1-mediated autoimmunity may be a consequence of increased TLR7 signaling due to impaired recruitment of downstream signaling molecules and damaged mitochondria to autophagosomes and may thus respond to TLR7-targeted therapeutics.

Role of Lipopolysaccharides in the Inflammation and Pyroptosis of Alveolar Epithelial Cells in Acute Lung Injury and Acute Respiratory Distress Syndrome

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) represent a spectrum of common critical respiratory conditions characterized by damage and death of alveolar epithelial cells (AECs). Pyroptosis is a form of programmed cell death with inflammatory characteristics, and activation of pyroptosis markers has been observed in AECs of patients with ALI/ARDS. Lipopolysaccharides (LPS) possess strong pro-inflammatory effects and are a crucial pathological factor leading to ALI in patients and animals. In LPS-induced ALI models, AECs undergo pyroptosis. However, physiologically and pathologically relevant concentrations of LPS lead to minor effects on AEC cell viability and minimal induction of cytokine release in vitro and do not induce classical pyroptosis. Nevertheless, LPS can enter the cytoplasm directly and induce non-classical pyroptosis in AECs when assisted by extracellular vesicles from bacteria, HMGB1, and pathogens. In this review, we have explored the effects of LPS on AECs concerning inflammation, cell viability, and pyroptosis, analyzing key factors that influence LPS actions. Notably, we highlight the intricate response of AECs to LPS within the framework of ALI and ARDS, emphasizing the variable induction of pyroptosis. Despite the minimal effects of LPS on AEC viability and cytokine release in vitro, LPS can induce non-classical pyroptosis under specific conditions, presenting potential pathways for therapeutic intervention. Collectively, understanding these mechanisms is crucial for the development of targeted treatments that mitigate the inflammatory responses in ALI/ARDS, thereby enhancing patient outcomes in these severe respiratory conditions.

Switch-like Gene Expression Modulates Disease Susceptibility

A fundamental challenge in biomedicine is understanding the mechanisms predisposing individuals to disease. While previous research has suggested that switch-like gene expression is crucial in driving biological variation and disease susceptibility, a systematic analysis across multiple tissues is still lacking. By analyzing transcriptomes from 943 individuals across 27 tissues, we identified 1,013 switch-like genes. We found that only 31 (3.1%) of these genes exhibit switch-like behavior across all tissues. These universally switch-like genes appear to be genetically driven, with large exonic genomic structural variants explaining five (~18%) of them. The remaining switch-like genes exhibit tissue-specific expression patterns. Notably, tissue-specific switch-like genes tend to be switched on or off in unison within individuals, likely under the influence of tissue-specific master regulators, including hormonal signals. Among our most significant findings, we identified hundreds of concordantly switched-off genes in the stomach and vagina that are linked to gastric cancer (41-fold, p<10-4) and vaginal atrophy (44-fold, p<10-4), respectively. Experimental analysis of vaginal tissues revealed that low systemic levels of estrogen lead to a significant reduction in both the epithelial thickness and the expression of the switch-like gene ALOX12. We propose a model wherein the switching off of driver genes in basal and parabasal epithelium suppresses cell proliferation therein, leading to epithelial thinning and, therefore, vaginal atrophy. Our findings underscore the significant biomedical implications of switch-like gene expression and lay the groundwork for potential diagnostic and therapeutic applications.

Transmembrane channel-like 4 and 5 proteins at microvillar tips are potential ion channels and lipid scramblases

Microvilli-membrane bound actin protrusions on the surface of epithelial cells-are sites of critical processes including absorption, secretion, and adhesion. Increasing evidence suggests microvilli are mechanosensitive, but underlying molecules and mechanisms remain unknown. Here, we localize transmembrane channel-like proteins 4 and 5 (TMC4 and 5) and calcium and integrin binding protein 3 (CIB3) to microvillar tips in intestinal epithelial cells, near glycocalyx insertion sites. We find that TMC5 colocalizes with CIB3 in cultured cells and that a TMC5 fragment forms a complex with CIB3 in vitro. Homology and AlphaFold2 models reveal a putative ion permeation pathway in TMC4 and 5, and molecular dynamics simulations predict both proteins can conduct ions and perform lipid scrambling. These findings raise the possibility that TMC4 and 5 interact with CIB3 at microvillar tips to form a mechanosensitive complex, akin to TMC1 and 2, and CIB2 and 3, within the mechanotransduction channel complex at the tips of inner ear stereocilia.

Interpretable representation learning for 3D multi-piece intracellular structures using point clouds

A key challenge in understanding subcellular organization is quantifying interpretable measurements of intracellular structures with complex multi-piece morphologies in an objective, robust and generalizable manner. Here we introduce a morphology-appropriate representation learning framework that uses 3D rotation invariant autoencoders and point clouds. This framework is used to learn representations of complex multi-piece morphologies that are independent of orientation, compact, and easy to interpret. We apply our framework to intracellular structures with punctate morphologies (e.g. DNA replication foci) and polymorphic morphologies (e.g. nucleoli). We systematically compare our framework to image-based autoencoders across several intracellular structure datasets, including a synthetic dataset with pre-defined rules of organization. We explore the trade-offs in the performance of different models by performing multi-metric benchmarking across efficiency, generative capability, and representation expressivity metrics. We find that our framework, which embraces the underlying morphology of multi-piece structures, facilitates the unsupervised discovery of sub-clusters for each structure. We show how our approach can also be applied to phenotypic profiling using a dataset of nucleolar images following drug perturbations. We implement and provide all representation learning models using CytoDL, a python package for flexible and configurable deep learning experiments.

TransTEx: novel tissue-specificity scoring method for grouping human transcriptome into different expression groups

MOTIVATION

Although human tissues carry out common molecular processes, gene expression patterns can distinguish different tissues. Traditional informatics methods, primarily at the gene level, overlook the complexity of alternative transcript variants and protein isoforms produced by most genes, changes in which are linked to disease prognosis and drug resistance.

RESULTS

We developed TransTEx (Transcript-level Tissue Expression), a novel tissue-specificity scoring method, for grouping transcripts into four expression groups. TransTEx applies sequential cut-offs to tissue-wise transcript probability estimates, subsampling-based P-values and fold-change estimates. Application of TransTEx on GTEx mRNA-seq data divided 199 166 human transcripts into different groups as 17 999 tissue-specific (TSp), 7436 tissue-enhanced, 36 783 widely expressed (Wide), 79 191 lowly expressed (Low), and 57 757 no expression (Null) transcripts. Testis has the most (13 466) TSp isoforms followed by liver (890), brain (701), pituitary (435), and muscle (420). We found that the tissue specificity of alternative transcripts of a gene is predominantly influenced by alternate promoter usage. By overlapping brain-specific transcripts with the cell-type gene-markers in scBrainMap database, we found that 63% of the brain-specific transcripts were enriched in nonneuronal cell types, predominantly astrocytes followed by endothelial cells and oligodendrocytes. In addition, we found 61 brain cell-type marker genes encoding a total of 176 alternative transcripts as brain-specific and 22 alternative transcripts as testis-specific, highlighting the complex TSp and cell-type specific gene regulation and expression at isoform-level. TransTEx can be adopted to the analysis of bulk RNA-seq or scRNA-seq datasets to find tissue- and/or cell-type specific isoform-level gene markers.

AVAILABILITY AND IMPLEMENTATION

TransTEx database: https://bmi.cewit.stonybrook.edu/transtexdb/ and the R package is available via GitHub: https://github.com/pallavisurana1/TransTEx.

The human retroviral-like aspartic protease 1 (ASPRV1): From in vitro studies to clinical correlations

The human retroviral-like aspartic protease 1 (ASPRV1) is a retroviral-like protein that was first identified in the skin due to its expression in the stratum granulosum layer of the epidermis. Accordingly, it is also referred to as skin-specific aspartic protease. Similar to the retroviral polyproteins, the full-length ASPRV1 also undergoes self-proteolysis, the processing of the precursor is necessary for the autoactivation of the protease domain. ASPRV1's functions are well-established at the level of the skin: it is part of the epidermal proteolytic network and has a significant contribution to skin moisturization via the limited proteolysis of filaggrin; it is only natural protein substrate identified so far. Filaggrin and ASPRV1 are also specific for mammalians, these proteins provide unique features for the skins of these species, and the importance of filaggrin processing in hydration is proved by the fact that some ASPRV1 mutations are associated with skin diseases such as ichthyosis. ASPRV1 was also found to be expressed in macrophage-like neutrophil cells, indicating that its functions are not limited to the skin. In addition, differential expression of ASPRV1 was detected in many diseases, with yet unknown significance. The currently known enzymatic characteristics-that had been revealed mainly by in vitro studies-and correlations with pathogenic phenotypes imply potentially important functions in multiple cell types, which makes the protein a promising target of functional studies. In this review we describe the currently available knowledge and future perspective in regard to ASPRV1.

Vesicle-associated membrane protein 8 knockdown exerts anti-proliferative, pro-apoptotic, anti-autophagic, and pro-ferroptotic effects on colorectal cancer cells by inhibition of the JAK/STAT3 pathway

Vesicle-associated membrane protein 8 (VAMP8), a soluble n-ethylmaleimide-sensitive factor receptor protein, acts as an oncogenic gene in the progression of several malignancies. Nevertheless, the roles and mechanisms of VAMP8 in colorectal cancer (CRC) progression remain unknown. The expression and prognostic significance of VAMP8 in CRC samples were analyzed through bioinformatics analyses. Cell proliferation was detected using CCK-8 and EdU incorporation assays and apoptosis was evaluated via flow cytometry. Western blot analysis was conducted to examine the protein expression. Ferroptosis was evaluated by measurement of iron metabolism, lipid peroxidation, and glutathione (GSH) content. VAMP8 was increased in CRC samples relative to normal samples on the basis of GEPIA and HPA databases. CRC patients with high level of VAMP8 had a worse overall survival. VAMP8 depletion led to a suppression of proliferation and promotion of apoptosis in CRC cells. Additionally, VAMP8 knockdown suppressed beclin1 expression and LC3-II/LC3-I ratio, elevated p62 expression, increased Fe2+, labile iron pool, lipid reactive oxygen species, and malondialdehyde levels, and repressed GSH content and glutathione peroxidase activity. Moreover, VAMP8 knockdown inhibited the activation of janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) pathway in CRC cells. Mechanistically, activation of the JAK/STAT3 pathway by JAK1 or JAK2 overexpression attenuated VAMP8 silencing-mediated anti-proliferative, pro-apoptotic, anti-autophagic, and pro-ferroptotic effects on CRC cells. In conclusion, VAMP8 knockdown affects the proliferation, apoptosis, autophagy, and ferroptosis by the JAK/STAT3 pathway in CRC cells.

Determining expression changes of ANO7 and SLC38A4 membrane transporters in colorectal cancer

Membrane transporters are proteins responsible for facilitating the movement of molecules within biological membranes. They play a vital role in maintaining cellular homeostasis by regulating the transport of nutrients, ions, and other molecules into and out of cells. Our aim is to identify biomarkers in colorectal cancer using membrane transporter proteins. We utilized COAD TCGA data for this purpose. Subsequently, we conducted differential gene analysis and feature selection using membrane transporter proteins. Furthermore, we identified two potential genes, including ANO7 and SLC38A4. To validate the expression profiles of ANO7 and SLC38A4, key genes in this context, RT-qPCR was employed on colorectal cancer samples and adjacent normal tissues. Additionally, utilizing GEPIA2, Kaplan-Meier survival analysis, and cBioPortal, we assessed the status of these genes in various cancers, examining their methylation and mutation patterns. In conclusion, we suggest that ANO7 and SLC38A4 serve as prognostic biomarkers in colorectal cancer.

Scinderin is a potential prognostic biomarker and correlated with immunological regulation: from pan-cancer analysis to liver hepatocellular carcinoma

Aim

This study aimed to systematically dissect the role of Scinderin (SCIN) in tumorigenesis.

Methods

Bioinformatics techniques were employed based on cancer data from TCGA, ENCORI, HPA, GEPIA2, UALCAN, Kaplan-Meier plotter, TIMER, TISIDB, cBioPortal, HCCDB, GeneMANIA and LinkedOmics database. Experiments in vitro and in vivo were conducted to dissect the role of SCIN in liver hepatocellular carcinoma (LIHC).

Results

Significantly differential expression of SCIN was found in nine types of cancers, including LIHC. Through pan-cancer analysis, the correlations between SCIN expression with prognosis and immune cell infiltration were proven, especially in LIHC, ovarian serous cystadenocarcinoma and lung adenocarcinoma. The highest frequency of alteration in SCIN (6.81%) was seen in patients with uterine corpus endometrial carcinoma, in which "mutation" was the predominant type, with a frequency of about 5.29%; meanwhile, S673F and S381Y were the two most frequent mutation sites. Furthermore, the abnormal expression of SCIN exhibited a strong relationship with immune cell subtypes, immune checkpoint genes, tumor mutation burden, microsatellite instability, neoantigen, molecular subtypes, mismatch repair signatures and DNA methyl-transferase in different cancer types. Through comparative analysis, we discovered that SCIN was dramatically up-regulated in LIHC, and associated with poor survival. Experiments in vitro and in vivo suggested the knockdown of SCIN could suppress tumor cell proliferation and improve the survival rate partly in animal models.

Conclusion

This study reveals SCIN may be a promising biomarker for prognosis and treatment in certain cancers, especially in LIHC.

The Beak of Eukaryotic Ribosomes: Life, Work and Miracles

Ribosomes are not totally globular machines. Instead, they comprise prominent structural protrusions and a myriad of tentacle-like projections, which are frequently made up of ribosomal RNA expansion segments and N- or C-terminal extensions of ribosomal proteins. This is more evident in higher eukaryotic ribosomes. One of the most characteristic protrusions, present in small ribosomal subunits in all three domains of life, is the so-called beak, which is relevant for the function and regulation of the ribosome's activities. During evolution, the beak has transitioned from an all ribosomal RNA structure (helix h33 in 16S rRNA) in bacteria, to an arrangement formed by three ribosomal proteins, eS10, eS12 and eS31, and a smaller h33 ribosomal RNA in eukaryotes. In this review, we describe the different structural and functional properties of the eukaryotic beak. We discuss the state-of-the-art concerning its composition and functional significance, including other processes apparently not related to translation, and the dynamics of its assembly in yeast and human cells. Moreover, we outline the current view about the relevance of the beak's components in human diseases, especially in ribosomopathies and cancer.

Key extracellular proteins and TF-miRNA co-regulatory network in diabetic foot ulcer: Bioinformatics and experimental insights

BACKGROUND

Diabetic foot ulcers (DFUs), a serious complication of diabetes, are associated with abnormal extracellular protein (EP) metabolism. The identification of key EPs and their regulatory networks is crucial for the understanding of DFU formation and development of effective treatments. In this study, a large-scale bioinformatics analysis was conducted to identify potential therapeutic targets and experimental validation was performed to ensure the reliability and biological relevance of the findings.

METHODS

Due to the comprehensive profiling of DFU samples provided by the GSE80178 dataset, we initially selected it to derive differentially expressed genes (DEGs) associated with DFU. Subsequently, utilizing the UniProt database and annotated EP list from the Human Protein Atlas annotation database, we screened for extracellular protein-related differentially expressed genes (EP-DEGs) due to their crucial role in the pathogenesis and healing of DFU. We examined EP-DEG pathway enrichment and protein-protein interaction networks, analyzed paired full-thickness skin tissue samples from 24 patients with DFUs and healthy controls, and performed polymerase chain reaction (PCR) experiments to validate candidate genes. Ultimately, we constructed a transcription factor (TF)-microRNA (miRNA)-hub gene co-regulatory network to explore upstream and downstream regulatory connections based on validated DEGs.

RESULTS

Four crucial candidate genes (FMOD, LUM, VCAN, and S100A12) were identified and verified via PCR analysis. The TF-miRNA-hub EP-DEG regulatory network contained the pivotal TFs TRIM28 and STAT3 and the miRNAs hsa-mir-20a-5p, hsa-miR-21, and hsa-miR-203.

CONCLUSION

The findings of this study advance our understanding of the pathology of DFU by defining key roles of specific EPs and elucidating a comprehensive regulatory network. These insights pave the way for novel approaches to improve DFU treatment outcomes.

Airway specific deregulation of asthma-related serpins impairs tracheal architecture and oxygenation in D. melanogaster

Serine proteases are important regulators of airway epithelial homeostasis. Altered serum or cellular levels of two serpins, Scca1 and Spink5, have been described for airway diseases but their function beyond antiproteolytic activity is insufficiently understood. To close this gap, we generated fly lines with overexpression or knockdown for each gene in the airways. Overexpression of both fly homologues of Scca1 and Spink5 induced the growth of additional airway branches, with more variable results for the respective knockdowns. Dysregulation of Scca1 resulted in a general delay in fruit fly development, with increases in larval and pupal mortality following overexpression of this gene. In addition, the morphological changes in the airways were concomitant with lower tolerance to hypoxia. In conclusion, the observed structural changes of the airways evidently had a strong impact on the airway function in our model as they manifested in a lower physical fitness of the animals. We assume that this is due to insufficient tissue oxygenation. Future work will be directed at the identification of key molecular regulators following the airway-specific dysregulation of Scca1 and Spink5 expression.

Comprehensive pan-cancer analysis of the C2ORF40 expression: Infiltration associations and prognostic implications

In recent years, C2ORF40 has been identified as a tumor suppressor gene with multiple functions, including roles in cell proliferation, migration, and senescence. To explore the role of the C2ORF40 gene in different tumors, we used multiple databases for analysis. Compared to adjacent normal tissues, C2ORF40 is downregulated in a variety of malignant tumors, including tumors such as breast cancer, colorectal cancer, bladder cancer, hepatocellular carcinoma and prostate cancer. Notably, low expression of the gene is significantly associated with poor overall survival and relapse-free survival rates. In specific cancers including colon cancer and prostate cancer, the expression of C2ORF40 is correlated with the infiltration of CAFs. C2ORF40 is also involved in biological processes such as cell apoptosis and regulation of protein stability. In conclusion, C2ORF40 can hold promise as a prognostic marker for pan-cancer analysis.

Identification of Candidate Protein Biomarkers Associated with Domoic Acid Toxicosis in Cerebrospinal Fluid of California Sea Lions (Zalophus californianus)

Since 1998, California sea lion (Zalophus californianus) stranding events associated with domoic acid toxicosis (DAT) have consistently increased. Outside of direct measurement of domoic acid in bodily fluids at the time of stranding, there are no practical nonlethal clinical tests for the diagnosis of DAT that can be utilized in a rehabilitation facility. Proteomics analysis was conducted to discover candidate protein markers of DAT using cerebrospinal fluid from stranded California sea lions with acute DAT (n = 8), chronic DAT (n = 19), or without DAT (n = 13). A total of 2005 protein families were identified experiment-wide. A total of 83 proteins were significantly different in abundance across the three groups (adj. p < 0.05). MDH1, PLD3, ADAM22, YWHAG, VGF, and CLSTN1 could discriminate California sea lions with or without DAT (AuROC > 0.75). IGKV2D-28, PTRPF, KNG1, F2, and SNCB were able to discriminate acute DAT from chronic DAT (AuROC > 0.75). Proteins involved in alpha synuclein deposition were over-represented as classifiers of DAT, and many of these proteins have been implicated in a variety of neurodegenerative diseases. These proteins should be considered potential markers for DAT in California sea lions and should be prioritized for future validation studies as biomarkers.

Exploring variations in glycolytic and gluconeogenic enzymes and isoforms across breast cancer cell lines and tissues

It is well established that tumour cells undergo metabolic changes to acquire biological advantage over normal cells with activation of the glycolytic pathway, a process termed "Warburg effect". Enzyme isoforms are alternative enzymatic forms with the same function but with different biochemical or epigenetic features. Moreover, isoforms may have varying impacts on different metabolic pathways. We challenge ourselves to analyse the glycolytic and gluconeogenic enzymes and isoforms in breast cancer, a complex and heterogeneous pathology, associated with high incidence and mortality rates especially among women. We analysed epithelial and tumour cell lines by RT-PCR and compared values to a publicly available database for the expression profile of normal and tumour tissues (Gepia) of enzymes and enzymatic isoforms from glycolytic and gluconeogenic pathways. Additionally, GeneMANIA was used to evaluate interactions, pathways, and attributes of each glycolytic/gluconeogenic steps. The findings reveal that the enzymes and enzymatic isoforms expressed in cell culture were somewhat different from those in breast tissue. We propose that the tumor microenvironment plays a crucial role in the expression of glycolytic and gluconeogenic enzymes and isoforms in tumour cells. Nonetheless, they not only participate in glycolytic and gluconeogenic enzymatic activities but may also influence other pathways, such as the Pentose-Phosphate-Pathway, TCA cycle, as well as other carbohydrate, lipid, and amino acid metabolism.

A novel bioinformatics strategy to uncover the active ingredients and molecular mechanisms of Bai Shao in the treatment of non-alcoholic fatty liver disease

Introduction: As a new discipline, network pharmacology has been widely used to disclose the material basis and mechanism of Traditional Chinese Medicine in recent years. However, numerous researches indicated that the material basis of TCMs identified based on network pharmacology was the mixtures of beneficial and harmful substances rather than the real material basis. In this work, taking the anti-NAFLD (non-alcoholic fatty liver disease) effect of Bai Shao (BS) as a case, we attempted to propose a novel bioinformatics strategy to uncover the material basis and mechanism of TCMs in a precise manner. Methods: In our previous studies, we have done a lot work to explore TCM-induced hepatoprotection. Here, by integrating our previous studies, we developed a novel computational pharmacology method to identify hepatoprotective ingredients from TCMs. Then the developed method was used to discover the material basis and mechanism of Bai Shao against Non-alcoholic fatty liver disease by combining with the techniques of molecular network, microarray data analysis, molecular docking, and molecular dynamics simulation. Finally, literature verification method was utilized to validate the findings. Results: A total of 12 ingredients were found to be associated with the anti-NAFLD effect of BS, including monoterpene glucosides, flavonoids, triterpenes, and phenolic acids. Further analysis found that IL1-β, IL6, and JUN would be the key targets. Interestingly, molecular docking and molecular dynamics simulation analysis showed that there indeed existed strong and stable binding affinity between the active ingredients and the key targets. In addition, a total of 23 NAFLD-related KEGG pathways were enriched. The major biological processes involved by these pathways including inflammation, apoptosis, lipid metabolism, and glucose metabolism. Of note, there was a great deal of evidence available in the literature to support the findings mentioned above, indicating that our method was reliable. Discussion: In summary, the contributions of this work can be summarized as two aspects as follows. Firstly, we systematically elucidated the material basis and mechanism of BS against NAFLD from multiple perspectives. These findings further enhanced the theoretical foundation of BS on NAFLD. Secondly, a novel computational pharmacology research strategy was proposed, which would assist network pharmacology to uncover the scientific connotation TCMs in a more precise manner.

Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model

Background

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear.

Methods

ARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions.

Results

In our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies.

Conclusion

The predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.

Knowledge Graph Convolutional Network with Heuristic Search for Drug Repositioning

Drug repositioning is a strategy of repurposing approved drugs for treating new indications, which can accelerate the drug discovery process, reduce development costs, and lower the safety risk. The advancement of biotechnology has significantly accelerated the speed and scale of biological data generation, offering significant potential for drug repositioning through biomedical knowledge graphs that integrate diverse entities and relations from various biomedical sources. To fully learn the semantic information and topological structure information from the biological knowledge graph, we propose a knowledge graph convolutional network with a heuristic search, named KGCNH, which can effectively utilize the diversity of entities and relationships in biological knowledge graphs, as well as topological structure information, to predict the associations between drugs and diseases. Specifically, we design a relation-aware attention mechanism to compute the attention scores for each neighboring entity of a given entity under different relations. To address the challenge of randomness of the initial attention scores potentially impacting model performance and to expand the search scope of the model, we designed a heuristic search module based on Gumbel-Softmax, which uses attention scores as heuristic information and introduces randomness to assist the model in exploring more optimal embeddings of drugs and diseases. Following this module, we derive the relation weights, obtain the embeddings of drugs and diseases through neighborhood aggregation, and then predict drug-disease associations. Additionally, we employ feature-based augmented views to enhance model robustness and mitigate overfitting issues. We have implemented our method and conducted experiments on two data sets. The results demonstrate that KGCNH outperforms competing methods. In particular, case studies on lithium and quetiapine confirm that KGCNH can retrieve more actual drug-disease associations in the top prediction results.

The RNA secondary structure of androgen receptor-FL and V7 transcripts reveals novel regulatory regions

The androgen receptor (AR) is a ligand-dependent nuclear transcription factor belonging to the steroid hormone nuclear receptor family. Due to its roles in regulating cell proliferation and differentiation, AR is tightly regulated to maintain proper levels of itself and the many genes it controls. AR dysregulation is a driver of many human diseases including prostate cancer. Though this dysregulation often occurs at the RNA level, there are many unknowns surrounding post-transcriptional regulation of AR mRNA, particularly the role that RNA secondary structure plays. Thus, a comprehensive analysis of AR transcript secondary structure is needed. We address this through the computational and experimental analyses of two key isoforms, full length (AR-FL) and truncated (AR-V7). Here, a combination of in-cell RNA secondary structure probing experiments (targeted DMS-MaPseq) and computational predictions were used to characterize the static structural landscape and conformational dynamics of both isoforms. Additionally, in-cell assays were used to identify functionally relevant structures in the 5' and 3' UTRs of AR-FL. A notable example is a conserved stem loop structure in the 5'UTR of AR-FL that can bind to Poly(RC) Binding Protein 2 (PCBP2). Taken together, our results reveal novel features that regulate AR expression.

PRAMEF12, a novel cancer/testis gene, regulates proliferation and apoptosis to promote progression of glioma

Aim: To evaluate whether PRAMEF12 can serve as a diagnostic biomarker for glioma. Methods: We examined PRAMEF12 expression in multiple normal and glioma tissues. The diagnostic value of PRAMEF12 was evaluated using receiver operating characteristic curve analysis. The effect of PRAMEF12 ablation on proliferation, cell cycle and apoptosis was investigated. Database analyses were utilized for functional enrichment analysis. Results: PRAMEF12 expression in normal tissue was restricted to the human testis. PRAMEF12 displayed significant diagnostic value in glioma. PRAMEF12 knockdown inhibited cell proliferation, induced apoptosis and resulted in induction of S-phase cell cycle arrest. Pathway enrichment analysis indicated that PRAMEF12 may participate in cancer. Conclusion: PRAMEF12, a novel cancer/testis gene, may be a potential new diagnostic biomarker for glioma.

Frontiers in plasma proteome profiling platforms: innovations and applications

Biomarkers play a crucial role in advancing precision medicine by enabling more targeted and individualized approaches to diagnosis and treatment. Various biofluids, including serum, plasma, cerebrospinal fluid (CSF), saliva, tears, pancreatic cyst fluids, and urine, have been identified as rich sources of potential for the early detection of disease biomarkers in conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. The analysis of plasma and serum in proteomics research encounters challenges due to their high complexity and the wide dynamic range of protein abundance. These factors impede the sensitivity, coverage, and precision of protein detection when employing mass spectrometry, a widely utilized technology in discovery proteomics. Conventional approaches such as Neat Plasma workflow are inefficient in accurately quantifying low-abundant proteins, including those associated with tissue leakage, immune response molecules, interleukins, cytokines, and interferons. Moreover, the manual nature of the workflow poses a significant hurdle in conducting large cohort studies. In this study, our focus is on comparing workflows for plasma proteomic profiling to establish a methodology that is not only sensitive and reproducible but also applicable for large cohort studies in biomarker discovery. Our investigation revealed that the Proteograph XT workflow outperforms other workflows in terms of plasma proteome depth, quantitative accuracy, and reproducibility while offering complete automation of sample preparation. Notably, Proteograph XT demonstrates versatility by applying it to various types of biofluids. Additionally, the proteins quantified widely cover secretory proteins in peripheral blood, and the pathway analysis enriched with relevant components such as interleukins, tissue necrosis factors, chemokines, and B and T cell receptors provides valuable insights. These proteins, often challenging to quantify in complex biological samples, hold potential as early detection markers for various diseases, thereby contributing to the improvement of patient care quality.

Prediction, screening and characterization of novel bioactive tetrapeptide matrikines for skin rejuvenation

BACKGROUND

Extracellular matrices play a critical role in tissue structure and function and aberrant remodelling of these matrices is a hallmark of many age-related diseases. In skin, loss of dermal collagens and disorganization of elastic fibre components are key features of photoageing. Although the application of some small matrix-derived peptides to aged skin has been shown to beneficially affect in vitro cell behaviour and, in vivo, molecular architecture and clinical appearance, the discovery of new peptides has lacked a guiding hypothesis.

OBJECTIVES

To identify, using protease cleavage site prediction, novel putative matrikines with beneficial activities for skin composition and structure.

METHODS

Here, we present an in silico (peptide cleavage prediction) to in vitro (proteomic and transcriptomic activity testing in cultured human dermal fibroblasts) to in vivo (short-term patch test and longer-term split-face clinical study) discovery pipeline, which enables the identification and characterization of peptides with differential activities.

RESULTS

Using this pipeline we showed that cultured fibroblasts were responsive to all applied peptides, but their associated bioactivity was sequence-dependent. Based on bioactivity, toxicity and protein source, we further characterized a combination of two novel peptides, GPKG (glycine-proline-lysine-glycine) and LSVD (leucine-serine-valine-aspartate), that acted in vitro to enhance the transcription of matrix -organization and cell proliferation genes and in vivo (in a short-term patch test) to promote processes associated with epithelial and dermal maintenance and remodelling. Prolonged use of a formulation containing these peptides in a split-face clinical study led to significantly improved measures of crow's feet and firmness in a mixed population.

CONCLUSIONS

This approach to peptide discovery and testing can identify new synthetic matrikines, providing insights into biological mechanisms of tissue homeostasis and repair and new pathways to clinical intervention.

Immunotherapy, prognostic, and tumor biomarker based on pancancer analysis, SMARCD3

BACKGROUND

SMARCD3 has recently been shown to be an important gene affecting cancer, playing an important role in medulloblastoma and pancreatic ductal adenocarcinoma. Therefore, we conducted this research to investigate the potential involvement of SMARCD3 across cancers and to offer recommendations for future studies.

METHODS

Utilizing information on 33 malignancies in the UCSC Xena database, SMARCD3 expression and its prognostic value were assessed. The tumor microenvironment was evaluated with the "CIBERSORT" and "ESTIMATE" algorithms. SMARCD3 and immune-related genes were analyzed using the TISIDB website. The pathways related to the target genes were examined using GSEA. MSI (microsatellite instability), TMB (tumor mutational burden), and immunotherapy analysis were used to evaluate the impact of target genes on the response to immunotherapy.

RESULTS

There is heterogeneity in terms of the expression and prognostic value of SMARCD3 among various cancers, but it is a risk factor for many cancers including uterine corpus endometrial cancer (UCEC), renal clear cell carcinoma (KIRC), and gastric adenocarcinoma (STAD). GSEA revealed that SMARCD3 is related to chromatin remodeling and transcriptional activation, lipid metabolism, and the activities of various immune cells. The TMB and MSI analyses suggested that SMARCD3 affects the immune response efficiency of KIRC, LUAD and STAD. Immunotherapy analysis suggested that SMARCD3 may be a potential immunotherapy target. RT-qPCR demonstrated the variation in SMARCD3 expression in KIRC, LUAD, and STAD.

CONCLUSION

Our study revealed that SMARCD3 affects the prognosis and immunotherapy response of some tumors, providing a direction for further research on this gene.

DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes

Motivation

Although transcriptomics data is typically used to analyse mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g., healthy vs. diseased). Furthermore, this kind of inference is challenging, because spliced and unspliced mRNA abundance is characterized by a high degree of quantification uncertainty, due to the prevalence of multi-mapping reads, i.e., reads compatible with multiple transcripts (or genes), and/or with both their spliced and unspliced versions.

Results

Here, we present DifferentialRegulation, a Bayesian hierarchical method to discover changes between experimental conditions with respect to the relative abundance of unspliced mRNA (over the total mRNA). We model the quantification uncertainty via a latent variable approach, where reads are allocated to their gene/transcript of origin, and to the respective splice version. We designed several benchmarks where our approach shows good performance, in terms of sensitivity and error control, versus state-of-the-art competitors. Importantly, our tool is flexible, and works with both bulk and single-cell RNA-sequencing data.

Availability and implementation

DifferentialRegulation is distributed as a Bioconductor R package.

HLA-DM and HLA-DO interplay for the peptide editing of HLA class II in healthy tissues and leukemia

HLA class II antigen presentation is modulated by the activity of the peptide editor HLA-DM and its antagonist HLA-DO, with their interplay controlling the peptide repertoires presented by normal and malignant cells. The role of these molecules in allogeneic hematopoietic cell transplantation (alloHCT) is poorly investigated. Balanced expression of HLA-DM and HLA-DO can influence the presentation of leukemia-associated antigens and peptides targeted by alloreactive T cells, therefore affecting both anti-leukemia immunity and the potential onset of Graft versus Host Disease. We leveraged on a large collection of bulk and single cell RNA sequencing data, available at different repositories, to comprehensively review the level and distribution of HLA-DM and HLA-DO in different cell types and tissues of the human body. The resulting expression atlas will help future investigations aiming to dissect the dual role of HLA class II peptide editing in alloHCT, and their potential impact on its clinical outcome.

A bird's eye view of the potential role of NFKBIA in pan-cancer

In the 21st century, cancer remains a serious threat to people's health and has become a prominent public health problem. NFKBIA is involved in the pathological process of many diseases including cancer, but its specific role in pan-cancer has not yet been fully elucidated. This study aims to deepen the understanding of cancer pathology by analyzing the potential functions of NFKBIA in pan-cancer. We used TCGA data to analyze differences of expression of NFKBIA in pan-cancer. We explored the prognostic value, clinical relevance, immune relevance, potential biological function, and diagnosis and treatment value of NFKBIA in pan-cancer through bioinformatics analysis. This study found that in pan-cancer, NFKBIA exhibits differences in expression, which correlate with the prognosis, diagnosis, treatment value and clinical and immune parameters. We have identified that Aspirin, Astaxanthin and Bardoxolone methyl are expected to play a potential therapeutic role in pan-cancer. The results of this study will help to improve our understanding of the role and potential mechanism of NFKBIA in cancer pathology, which may provide guidance for cancer-related research and clinical diagnosis and treatment.

Genetic variants in C1GALT1 are associated with gastric cancer risk by influencing immune infiltration

Core 1 synthase glycoprotein-N-acetylgalactosamine 3-β-galactosyltransferase 1 (C1GALT1) is known to play a critical role in the development of gastric cancer, but few studies have elucidated associations between genetic variants in C1GALT1 and gastric cancer risk. By using the genome-wide association study data from the database of Genotype and Phenotype (dbGAP), we evaluated such associations with a multivariable logistic regression model and identified that the rs35999583 G>C in C1GALT1 was associated with gastric cancer risk (odds ratio, 0.83; 95% confidence interval [CI], 0.75-0.92; P = 3.95 × 10 -4). C1GALT1 mRNA expression levels were significantly higher in gastric tumor tissues than in normal tissues, and gastric cancer patients with higher C1GALT1 mRNA levels had worse overall survival rates (hazards ratio, 1.33; 95% CI, 1.05-1.68; P log-rank = 1.90 × 10 -2). Furthermore, we found that C1GALT1 copy number differed in various immune cells and that C1GALT1 mRNA expression levels were positively correlated with the infiltrating levels of CD4 + T cells and macrophages. These results suggest that genetic variants of C1GALT1 may play an important role in gastric cancer risk and provide a new insight for C1GALT1 into a promising predictor of gastric cancer susceptibility and immune status.

Anticancer Effects of the Trivalent Organoarsenical 2-Amino-4-(dihydroxyarsinoyl) Butanoate

According to the National Cancer Institute, breast cancer is a leading cause of death in women. The lack of progesterone and estrogen receptors in triple-negative breast cancer (TNBC) cells results in a lack of response to hormonal, monoclonal, or tyrosine kinase inhibitor therapies. Despite intensive drug discovery, there is still no approved targeted treatment for TNBC. The metalloid arsenic has been used in herbal medicines, antibiotics, and chemotherapeutic drugs for centuries. This paper demonstrates that a trivalent arsenic-containing, nonproteogenic amino acid, R-AST-OH (2-amino-4-(dihydroxyarsinoyl) butanoate), inhibits kidney-type glutaminase (KGA), the enzyme that controls glutamine metabolism and is correlated with tumor malignancy. Cell-based assays using the TNBC MDA-MB-231 and HCC1569 cell lines showed that R-AST-OH kills TNBC cells and is not cytotoxic to a control cell line. The results of in silico molecular docking predictions indicate that R-AST-OH binds to the glutamine binding site and forms a covalent bond with an active site cysteine residue. We hypothesize that R-AST-OH is a single warhead for KGA that irreversibly binds to KGA through the formation of an As-S bond. We propose that R-AST-OH is a promising lead compound for the design of new drugs for the treatment of TNBC.

Influence of Aldehyde Dehydrogenase Inhibition on Stemness of Endometrial Cancer Stem Cells

Endometrial cancer is one of the most common gynaecological malignancies. Although often diagnosed at an early stage, there is a subset of patients with recurrent and metastatic disease for whom current treatments are not effective. Cancer stem cells (CSCs) play a pivotal role in triggering tumorigenesis, disease progression, recurrence, and metastasis, as high aldehyde dehydrogenase (ALDH) activity is associated with invasiveness and chemotherapy resistance. Therefore, this study aimed to evaluate the effects of ALDH inhibition in endometrial CSCs. ECC-1 and RL95-2 cells were submitted to a sphere-forming protocol to obtain endometrial CSCs. ALDH inhibition was evaluated through ALDH activity and expression, sphere-forming capacity, self-renewal, projection area, and CD133, CD44, CD24, and P53 expression. A mass spectrometry-based proteomic study was performed to determine the proteomic profile of endometrial cancer cells upon N,N-diethylaminobenzaldehyde (DEAB). DEAB reduced ALDH activity and expression, along with a significant decrease in sphere-forming capacity and projection area, with increased CD133 expression. Additionally, DEAB modulated P53 expression. Endometrial cancer cells display a distinct proteomic profile upon DEAB, sharing 75 up-regulated and 30 down-regulated proteins. In conclusion, DEAB inhibits ALDH activity and expression, influencing endometrial CSC phenotype. Furthermore, ALDH18A1, SdhA, and UBAP2L should be explored as novel molecular targets for endometrial cancer.

Analyzing the Functional Roles and Immunological Features of Chemokines in COAD

Chemokines are key proteins that regulate cell migration and immune responses and are essential for modulating the tumor microenvironment. Despite their close association with colon cancer, the expression patterns, prognosis, immunity, and specific roles of chemokines in colon cancer are still not fully understood. In this study, we investigated the mutational features, differential expression, and immunological characteristics of chemokines in colon cancer (COAD) by analyzing the Tumor Genome Atlas (TCGA) database. We clarified the biological functions of these chemokines using Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. By univariate and multivariate COX regression analyses, we developed chemokine-based prognostic risk models. In addition, using Gene Set Enrichment Analysis (GSEA) and Gene Set Variant Analysis (GSVA), we analyzed the differences in immune responses and signaling pathways among different risk groups. The results showed that the mutation rate of chemokines was low in COAD, but 25 chemokines were significantly differentially expressed. These chemokines function in several immune-related biological processes and play key roles in signaling pathways including cytokine-cytokine receptor interactions, NF-kappa B, and IL-17. Prognostic risk models based on CCL22, CXCL1, CXCL8, CXCL9, and CXCL11 performed well. GSEA and GSVA analyses showed significant differences in immune responses and signaling pathways across risk groups. In conclusion, this study reveals the potential molecular mechanisms of chemokines in COAD and proposes a new prognostic risk model based on these insights.

A ferroptosis-related signature predicts the clinical diagnosis and prognosis, and associates with the immune microenvironment of lung cancer

Targeting ferroptosis-related pathway is a potential strategy for treatment of lung cancer (LC). Consequently, exploration of ferroptosis-related markers is important for treating LC. We collected LC clinical data and mRNA expression profiles from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained through FerrDB database. Expression analysis was performed to obtain differentially expressed FRGs. Diagnostic and prognostic models were constructed based on FRGs by LASSO regression, univariate, and multivariate Cox regression analysis, respectively. External verification cohorts GSE72094 and GSE157011 were used for validation. The interrelationship between prognostic risk scores based on FRGs and the tumor immune microenvironment was analyzed. Immunocytochemistry, Western blotting, and RT-qPCR detected the FRGs level. Eighteen FRGs were used for diagnostic models, 8 FRGs were used for prognostic models. The diagnostic model distinguished well between LC and normal samples in training and validation cohorts of TCGA. The prognostic models for TCGA, GSE72094, and GSE157011 cohorts significantly confirmed lower overall survival (OS) in high-risk group, which demonstrated excellent predictive properties of the survival model. Multivariate Cox regression analysis further confirmed risk score was an independent risk factor related with OS. Immunoassays revealed that in high-risk group, a significantly higher proportion of Macrophages_M0, Neutrophils, resting Natural killer cells and activated Mast cells and the level of B7H3, CD112, CD155, B7H5, and ICOSL were increased. In conclusion, diagnostic and prognostic models provided superior diagnostic and predictive power for LC and revealed a potential link between ferroptosis and TIME.

Peripheral Blood Gene Expression Profiling Reveals Molecular Pathways Associated with Cervical Artery Dissection

Cervical artery dissection (CeAD) is the primary cause of ischemic stroke in young adults. Monogenic heritable connective tissue diseases account for fewer than 5% of cases of CeAD. The remaining sporadic cases have known risk factors. The clinical, radiological, and histological characteristics of systemic vasculopathy and undifferentiated connective tissue dysplasia are present in up to 70% of individuals with sporadic CeAD. Genome-wide association studies identified CeAD-associated genetic variants in the non-coding genomic regions that may impact the gene transcription and RNA processing. However, global gene expression profile analysis has not yet been carried out for CeAD patients. We conducted bulk RNA sequencing and differential gene expression analysis to investigate the expression profile of protein-coding genes in the peripheral blood of 19 CeAD patients and 18 healthy volunteers. This was followed by functional annotation, heatmap clustering, reports on gene-disease associations and protein-protein interactions, as well as gene set enrichment analysis. We found potential correlations between CeAD and the dysregulation of genes linked to nucleolar stress, senescence-associated secretory phenotype, mitochondrial malfunction, and epithelial-mesenchymal plasticity.

Expression of fibroblast growth factor receptor 1 correlates inversely with the efficacy of single-agent fibroblast growth factor receptor-specific inhibitors in pancreatic cancer

BACKGROUND AND PURPOSE

Elevated fibroblast growth factor receptor (FGFR) activity correlates with pancreatic adenocarcinoma (PDAC) progression and poor prognosis. However, its potential as a therapeutic target remains largely unexplored.

EXPERIMENTAL APPROACH

The mechanisms of action and therapeutic effects of selective pan-FGFR inhibitors (pan-FGFRi) were explored using in vitro and in vivo PDAC models ranging from gemcitabine-sensitive to highly gemcitabine-resistant (GemR). Gain-/loss-of-function investigations were employed to define the role of individual FGFRs in cell proliferation, migration, and treatment response and resistance.

RESULTS

The pan-FGFRi NVP-BGJ398 significantly inhibited cell proliferation, migration, and invasion, and downregulated key cell survival- and invasiveness markers in multiple PDAC cell lines. Gemcitabine is a standard-of-care for PDAC, but development of resistance to gemcitabine (GemR) compromises its efficacy. Acquired GemR was modelled experimentally by developing highly GemR cells using escalating gemcitabine exposure in vitro and in vivo. FGFRi treatment inhibited GemR cell proliferation, migration, GemR marker expression, and tumour progression. FGFR2 or FGFR3 loss-of-function by shRNA knockdown failed to decrease cell growth, whereas FGFR1 knockdown was lethal. FGFR1 overexpression promoted cell migration more than proliferation, and reduced FGFRi-mediated inhibition of proliferation and migration. Single-agent FGFRi suppressed the viability and growth of multiple patient-derived xenografts inversely with respect to FGFR1 expression, underscoring the influence of FGFR1-dependent tumour responses to FGFRi. Importantly, secondary data analysis showed that PDAC tumours expressed FGFR1 at lower levels than in normal pancreas tissue.

CONCLUSIONS AND IMPLICATIONS

Single-agent FGFR inhibitors mediate selective, molecularly-targeted suppression of PDAC proliferation, and their effects are greatest in PDAC tumours expressing low-to-moderate levels of FGFR1.

Vislocas: Vision transformers for identifying protein subcellular mis-localization signatures of different cancer subtypes from immunohistochemistry images

Proteins must be sorted to specific subcellular compartments to perform their functions. Abnormal protein subcellular localizations are related to many diseases. Although many efforts have been made in predicting protein subcellular localization from various static information, including sequences, structures and interactions, such static information cannot predict protein mis-localization events in diseases. On the contrary, the IHC (immunohistochemistry) images, which have been widely applied in clinical diagnosis, contains information that can be used to find protein mis-localization events in disease states. In this study, we create the Vislocas method, which is capable of finding mis-localized proteins from IHC images as markers of cancer subtypes. By combining CNNs and vision transformer encoders, Vislocas can automatically extract image features at both global and local level. Vislocas can be trained with full-sized IHC images from scratch. It is the first attempt to create an end-to-end IHC image-based protein subcellular location predictor. Vislocas achieved comparable or better performances than state-of-the-art methods. We applied Vislocas to find significant protein mis-localization events in different subtypes of glioma, melanoma and skin cancer. The mis-localized proteins, which were found purely from IHC images by Vislocas, are in consistency with clinical or experimental results in literatures. All codes of Vislocas have been deposited in a Github repository (https://github.com/JingwenWen99/Vislocas). All datasets of Vislocas have been deposited in Zenodo (https://zenodo.org/records/10632698).

Mammalian Diaphanous1 signalling in neurovascular complications of diabetes

Over the past few decades, diabetes gradually has become one of the top non-communicable disorders, affecting 476.0 million in 2017 and is predicted to reach 570.9 million people in 2025. It is estimated that 70 to 100% of all diabetic patients will develop some if not all, diabetic complications over the course of the disease. Despite different symptoms, mechanisms underlying the development of diabetic complications are similar, likely stemming from deficits in both neuronal and vascular components supplying hyperglycaemia-susceptible tissues and organs. Diaph1, protein diaphanous homolog 1, although mainly known for its regulatory role in structural modification of actin and related cytoskeleton proteins, in recent years attracted research attention as a cytoplasmic partner of the receptor of advanced glycation end-products (RAGE) a signal transduction receptor, whose activation triggers an increase in proinflammatory molecules, oxidative stressors and cytokines in diabetes and its related complications. Both Diaph1 and RAGE are also a part of the RhoA signalling cascade, playing a significant role in the development of neurovascular disturbances underlying diabetes-related complications. In this review, based on the existing knowledge as well as compelling findings from our past and present studies, we address the role of Diaph1 signalling in metabolic stress and neurovascular degeneration in diabetic complications. In light of the most recent developments in biochemical, genomic and transcriptomic research, we describe current theories on the aetiology of diabetes complications, highlighting the function of the Diaph1 signalling system and its role in diabetes pathophysiology.

ALDH2 as an immunological and prognostic biomarker: Insights from pan-cancer analysis

Aldehyde dehydrogenase 2 (ALDH2) plays a critical role in safeguarding cells against acetaldehyde toxicity and is closely linked to human metabolism. Nevertheless, the involvement of ALDH2 in cancer remains enigmatic. This investigation seeks to comprehensively assess ALDH2's significance in pan-cancer. We conducted an all-encompassing analysis of pan-cancer utilizing multiple databases, including TCGA, linkedomicshs, UALCAN, and Kaplan-Meier plotter. We employed diverse algorithms such as EPIC, MCPCOUNTER, TIDTIMER, xCell, MCP-counter, CIBERSORT, quanTIseq, and EPIC to examine the connection between ALDH2 expression and immune cell infiltration. Single-cell sequencing analysis furnished insights into ALDH2's functional status in pan-cancer. Immunohistochemical staining was performed to validate ALDH2 expression in cancer tissues. In a comprehensive assessment, we observed that tumor tissues demonstrated diminished ALDH2 expression levels compared to normal tissues across 16 different cancer types. ALDH2 expression exhibited a significant positive correlation with the infiltration of immune cells, including CD4 + T cells, CD8 + T cells, neutrophils, B cells, and macrophages, in various tumor types. Moreover, this study explored the association between ALDH2 and patient survival, examined the methylation patterns of ALDH2 in normal and primary tumor tissues, and delved into genetic variations and mutations of ALDH2 in tumors. The findings suggest that ALDH2 could serve as a valuable prognostic biomarker in pan-cancer, closely linked to the tumor's immune microenvironment.

ALKBH5 modulates macrophages polarization in tumor microenvironment of ovarian cancer

BACKGROUND

Macrophages play an essential role in regulating ovarian cancer immune microenvironment. Studies have shown that m6A methylation could influence immune microenvironment in cancer. In this study, we investigated the roles of m6A demethylase ALKBH5 and m6A recognition protein IGF2BP2 played in regulating macrophages polarization in ovarian cancer.

METHODS

In this study, we first explored the differentially expressed m6A methylation enzymes in M0 and M2 macrophages according to two independent GEO datasets. TIMER2.0 and GSCA database were used to explore the immune analysis of ALKBH5 and IGF2BP2 in ovarian cancer. K-M plotter and TIMER2.0 databases were used to evaluate the prognostic role of ALKBH5 and IGF2BP2 in ovarian cancer. For CNV mutation analysis of ALKBH5 and IGF2BP2, cBioPortal and GSCA databases were used. For single-cell analysis, sc-TIME and HPA softwares were used to analyze the roles of ALKBH5 and IGF2BP2 played in immune cells in ovarian cancer. To identify the role of ALKBH5 played in macrophage polarization, RT-PCR was used to verify the macrophage polarization related markers in vitro study. The function of ALKBH5 played in ovarian cancer was further analyzed through GO and KEGG analysis.

FINDINGS

In this study, we found that ALKBH5 and IGF2BP2 were up-regulated in M2 macrophages, which showed closely correlation with immune cells expressions in ovarian cancer, especially with macrophages. Ovarian cancer patients with higher expression of ALKBH5 and IGF2BP2 showed worse prognosis, possibly because of their close correlation with immune response. ALKBH5 also correlated with macrophage phenotypes in single-cell levels analysis. However, the expression level of IGF2BP2 in ovarian cancer immune microenvironment was very low. The results of RT-PCR indicated the potential role of ALKBH5 in M2 polarization of macrophages.

INTERPRETATION

ALKBH5 participated in regulating macrophage M2 polarization in ovarian cancer immune microenvironment.

Fibroblasts in the Aged Pancreas Drive Pancreatic Cancer Progression

Pancreatic cancer is more prevalent in older individuals and often carries a poorer prognosis for them. The relationship between the microenvironment and pancreatic cancer is multifactorial, and age-related changes in nonmalignant cells in the tumor microenvironment may play a key role in promoting cancer aggressiveness. Because fibroblasts have profound impacts on pancreatic cancer progression, we investigated whether age-related changes in pancreatic fibroblasts influence cancer growth and metastasis. Proteomics analysis revealed that aged fibroblasts secrete different factors than young fibroblasts, including increased growth/differentiation factor 15 (GDF-15). Treating young mice with GDF-15 enhanced tumor growth, whereas aged GDF-15 knockout mice showed reduced tumor growth. GDF-15 activated AKT, rendering tumors sensitive to AKT inhibition in an aged but not young microenvironment. These data provide evidence for how aging alters pancreatic fibroblasts and promotes tumor progression, providing potential therapeutic targets and avenues for studying pancreatic cancer while accounting for the effects of aging.

SIGNIFICANCE

Aged pancreatic fibroblasts secrete GDF-15 and activate AKT signaling to promote pancreatic cancer growth, highlighting the critical role of aging-mediated changes in the pancreatic cancer microenvironment in driving tumor progression. See related commentary by Isaacson et al., p. 1185.

Mitochondrial ribosomal protein S24 is associated with immunosuppressive microenvironment and cold tumor in lung adenocarcinoma

Objective

MRPS24 (Mitochondrial Ribosomal Protein S24) belongs to the mitochondrial ribosomal protein family, which participates in the protein synthesis of the mitochondrion. However, the relationship of MRPS24 with lung adenocarcinoma (LUAD) remained unknown. We aimed to identify its immunological and functional mechanisms in LUAD.

Methods

The analysis of MRPS24 expression, clinical features, diagnosis, prognosis, function analysis, genetic alteration, copy number variations, methylation, and tumor microenvironment was investigated by the TCGA, UCSC Xena, GEO, HPA, GEPIA, cBioPortal, MethSurv, TIMER, TIMER2.0, and TISIDB databases.

Results

MRPS24 was found to be more abundant in LUAD tumor tissue than in normal tissue. High levels of MRPS24 expression were found to be an independent prognostic factor by multivariate analysis. Functional analysis revealed that MRPS24 expression was associated with the immune, cell cycle and methylation. MRPS24 methylation level was inversely linked with its expression (p < 0.001). Patients with low MRPS24 methylation had a worse prognosis than those with high methylation (p < 0.05). In addition, the result revealed that the MRPS24 expression was inversely linked to the immune cell infiltration in LUAD. Finally, the validations of the expression level, prognosis, and immune cell infiltration of MRPS24 were in accordance with our previous results.

Conclusions

This study systematically explored that MRPS24 expression was significantly correlated with prognosis, tumorigenesis, genetic alteration, copy number variations, methylation, and immune cell infiltration in LUAD. MRPS24 might be a potential immune-related biomarker in the development and treatment of LUAD, thereby acting as a promising predictor of immunotherapy response in LUAD.