The Human Protein Atlas-Spatial localization of the human proteome in health and disease

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

The systematic identification of survival-related alternative splicing events and splicing factors in glioblastoma

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, making it one of the most life-threatening human cancers. Nevertheless, research on the mechanism of action between alternative splicing (AS) and splicing factor (SF) or biomarkers in GBM is limited. AS is a crucial post-transcriptional regulatory mechanism. More than 95% of human genes undergo AS events. AS can diversify the expression patterns of genes, thereby increasing the diversity of proteins and playing a significant role in the occurrence and development of tumors. In this study, we downloaded 599 clinical data and 169 transcriptome analysis data from The Cancer Genome Atlas (TCGA) database. Besides, we collected AS data about GBM from TCGA-SpliceSeq. The overall survival (OS) related AS events in GBM were determined through least absolute shrinkage and selection operator (Lasso) and Cox analysis. Subsequently, the association of these 1825 OS-related AS events with patient survival was validated using the Kaplan-Meier survival analysis, receiver operating characteristic curve, risk curve analysis, and independent prognostic analysis. Finally, we depicted the AS-SF regulatory network, illustrating the interactions between splicing factors and various AS events in GBM. Additionally, we identified three splicing factors (RNU4-1, SEC31B, and CLK1) associated with patient survival. In conclusion, based on AS occurrences, we developed a predictive risk model and constructed an interaction network between GBM-related AS events and SFs, aiming to shed light on the underlying mechanisms of GBM pathogenesis and progression.

Integrated multi-omics analyses revealed the association between rheumatoid arthritis and colorectal cancer: MYO9A as a shared gene signature and an immune-related therapeutic target

BACKGROUND

Our study aims to explore the relationship, shared gene signature, and the underlying mechanisms that connect rheumatoid arthritis (RA) to colorectal cancer (CRC).

METHODS

Mendelian randomization (MR) analysis was conducted to assess the causality between RA and CRC. Summary statistic data-based Mendelian randomization (SMR) leveraging eQTL data was employed to identify the CRC-related causal genes. Integrated analyses of single-cell RNA sequencing and bulk RNA sequencing were employed to comprehensively investigate the shared gene signature and potential mechanisms underlying the pathogenesis of both RA and CRC. Predictive analysis of the shared hub gene in CRC immunotherapy response was performed. Pan-cancer analyses were conducted to explore the potential role of MYO9A in 33 types of human tumors.

RESULTS

MR analysis suggested that RA might be associated with a slight increased risk of CRC (Odds Ratio = 1.04, 95% Confidence Interval = 1.01-1.07, P = 0.005). SMR analysis combining transcriptome analyses identified MYO9A as a causal gene in CRC and a shared gene signature in both RA and CRC. MYO9A may contribute to tumor suppression, while downregulation of MYO9A may impact CRC tumorigenesis by disrupting epithelial polarity and architecture, resulting in a worse prognosis in CRC. Additionally, MYO9A shows promise as a powerful predictive biomarker for cancer prognosis and immunotherapy response in CRC. Pan-cancer analyses demonstrated MYO9A may have a protective role in the occurrence and progression of various human cancers.

CONCLUSION

RA might be associated with a slight increased risk of CRC. MYO9A is a shared gene signature and a potential immune-related therapeutic target for both CRC and RA. Targeting the MYO9A-mediated loss of polarity and epithelial architecture could be a novel therapeutic approach for CRC.

Derivation of human primary prostate epithelial cell lines by differentially targeting the CDKN2A locus along with expression of hTERT

Prostate cancer (PCa) is the most common cancer diagnosed in men worldwide and the second leading cause of cancer-related deaths in US males in 2022. Prostate cancer also represents the second highest cancer mortality disparity between non-Hispanic blacks and whites. However, there is a relatively small number of prostate normal and cancer cell lines compared to other cancers. To identify the molecular basis of PCa progression, it is important to have prostate epithelial cell (PrEC) lines as karyotypically normal as possible. Our lab recently developed a novel methodology for the rapid and efficient immortalization of normal human PrEC that combines simultaneous CRISPR-directed inactivation of CDKN2A exon 2 (which directs expression of p16INK4A and p14ARF) and ectopic expression of an hTERT transgene. To optimize this methodology to generate immortalized lines with minimal genetic alterations, we sought to target exon 1α of the CDKN2A locus so that p16INK4A expression is ablated while p14ARF expression remains unaltered. Here we describe the establishment of two cell lines: one with the above-mentioned p16INK4A only loss, and a second line targeting both products in the CDKN2A locus. We characterize the potential lineage origin of these new cell lines along with our previously obtained clones, revealing distinct gene expression signatures. Based on the analyses of protein markers and RNA expression signatures, these cell lines are most closely related to a subpopulation of basal prostatic cells. Given the simplicity of this one-step methodology and the fact that it uses only the minimal genetic alterations necessary for immortalization, it should also be suitable for the establishment of cell lines from primary prostate tumor samples, an urgent need given the limited number of available prostate cancer cell lines.

Endothelial cell expression of a STING gain-of-function mutation initiates pulmonary lymphocytic infiltration

Patients afflicted with Stimulator of interferon gene (STING) gain-of-function mutations frequently present with debilitating interstitial lung disease (ILD) that is recapitulated in mice expressing the STINGV154M mutation (VM). Prior radiation chimera studies revealed an unexpected and critical role for non-hematopoietic cells in initiating ILD. To identify STING-expressing non-hematopoietic cell types required for the development of ILD, we use a conditional knockin (CKI) model and direct expression of the VM allele to hematopoietic cells, fibroblasts, epithelial cells, or endothelial cells. Only endothelial cell-targeted VM expression results in enhanced recruitment of immune cells to the lung associated with elevated chemokine expression and the formation of bronchus-associated lymphoid tissue, as seen in the parental VM strain. These findings reveal the importance of endothelial cells as instigators of STING-driven lung disease and suggest that therapeutic targeting of STING inhibitors to endothelial cells could potentially mitigate inflammation in the lungs of STING-associated vasculopathy with onset in infancy (SAVI) patients or patients afflicted with other ILD-related disorders.

Transcriptomics of Marburg virus-infected primary proximal tubular cells reveals negative correlation of immune response and energy metabolism

Marburg virus, a member of the Filoviridae, is the causative agent of Marburg virus disease (MVD), a hemorrhagic fever with a case fatality rate of up to 90 %. Acute kidney injury is common in MVD and is associated with increased mortality, but its pathogenesis in MVD remains poorly understood. Interestingly, autopsies show the presence of viral proteins in different parts of the nephron, particularly in proximal tubular cells (PTC). These findings suggest a potential role for the virus in the development of MVD-related kidney injury. To shed light on this effect, we infected primary human PTC with Lake Victoria Marburg virus and conducted transcriptomic analysis at multiple time points. Unexpectedly, infection did not induce marked cytopathic effects in primary tubular cells at 20 and 40 h post infection. However, gene expression analysis revealed robust renal viral replication and dysregulation of genes essential for different cellular functions. The gene sets mainly downregulated in PTC were associated with the targets of the transcription factors MYC and E2F, DNA repair, the G2M checkpoint, as well as oxidative phosphorylation. Importantly, the downregulated factors comprise PGC-1α, a well-known factor in acute and chronic kidney injury. By contrast, the most highly upregulated gene sets were those related to the inflammatory response and cholesterol homeostasis. In conclusion, Marburg virus infects and replicates in human primary PTC and induces downregulation of processes known to be relevant for acute kidney injury as well as a strong inflammatory response.

Discordant gene expression in subcutaneous adipose and skeletal muscle tissues in response to exercise training

Exercise has different effects on different tissues in the body, the sum of which may determine the response to exercise and the health benefits. In the present study, we aimed to investigate whether physical training regulates transcriptional network communites common to both skeletal muscle (SM) and subcutaneous adipose tissue (SAT). Eight such shared transcriptional communities were found in both tissues. Eighteen young overweight adults voluntarily participated in 7 weeks of combined strength and endurance training (five training sessions per week). Biopsies were taken from SM and SAT before and after training. Five of the network communities were regulated by training in SM but showed no change in SAT. One community involved in insulin- AMPK signaling and glucose utilization was upregulated in SM but downregulated in SAT. This diverging exercise regulation was confirmed in two independent studies and was also associated with BMI and diabetes in an independent cohort. Thus, the current finding is consistent with the differential responses of different tissues and suggests that body composition may influence the observed individual whole-body metabolic response to exercise training and help explain the observed attenuated whole-body insulin sensitivity after exercise training, even if it has significant effects on the exercising muscle.

Inhibition of palmitoyltransferase ZDHHC12 sensitizes ovarian cancer cells to cisplatin through ROS-mediated mechanisms

Platinum-based therapies have revolutionized the treatment of high-grade serous ovarian cancer (HGSOC). However, high rates of disease recurrence and progression remain a major clinical concern. Impaired mitochondrial function and dysregulated reactive oxygen species (ROS), hallmarks of cancer, hold potential as therapeutic targets for selectively sensitizing cisplatin treatment. Here, we uncover an oncogenic role of the palmitoyltransferase ZDHHC12 in regulating mitochondrial function and ROS homeostasis in HGSOC cells. Analysis of The Cancer Genome Atlas (TCGA) ovarian cancer data revealed significantly elevated ZDHHC12 expression, demonstrating the strongest positive association with ROS pathways among all ZDHHC enzymes. Transcriptomic analysis of independent ovarian cancer datasets and the SNU119 cell model corroborated this association, highlighting a strong link between ZDHHC12 expression and signature pathways involving mitochondrial oxidative metabolism and ROS regulation. Knockdown of ZDHHC12 disrupted this association, leading to increased cellular complexity, ATP levels, mitochondrial activity, and both mitochondrial and cellular ROS. This dysregulation, achieved by the siRNA knockdown of ZDHHC12 or treatment with the general palmitoylation inhibitor 2BP or the fatty acid synthase inhibitor C75, significantly enhanced cisplatin cytotoxicity in 2D and 3D spheroid models of HGSOC through ROS-mediated mechanisms. Markedly, ZDHHC12 inhibition significantly augmented the anti-tumor activity of cisplatin in an ovarian cancer xenograft tumor model, as well as in an ascites-derived organoid line of platinum-resistant ovarian cancer. Our data suggest the potential of ZDHHC12 as a promising target to improve the outcome of HGSOCs in response to platinum-based chemotherapy.

Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images

Knowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, several studies have been conducted to analyze protein expression in mouse brains. However, labeling protein expression using biotechnology is costly and time-consuming. Therefore, automated models that can accurately recognize protein expression are needed. Here, we constructed machine learning models to automatically annotate the protein expression intensity and cellular location in different mouse brain regions from immunofluorescence images. The brain regions and sub-regions were segmented through learning image features using an autoencoder and then performing K-means clustering and registration to align with the anatomical references. The protein expression intensities for those segmented structures were computed on the basis of the statistics of the image pixels, and patch-based weakly supervised methods and multi-instance learning were used to classify the cellular locations. Results demonstrated that the models achieved high accuracy in the expression intensity estimation, and the F1 score of the cellular location prediction was 74.5%. This work established an automated pipeline for analyzing mouse brain images and provided a foundation for further study of protein expression and functions.

A Review for Artificial Intelligence Based Protein Subcellular Localization

Proteins need to be located in appropriate spatiotemporal contexts to carry out their diverse biological functions. Mislocalized proteins may lead to a broad range of diseases, such as cancer and Alzheimer's disease. Knowing where a target protein resides within a cell will give insights into tailored drug design for a disease. As the gold validation standard, the conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, and fluorescent biomarker tags for protein subcellular location identification. However, the booming era of proteomics and high-throughput sequencing generates tons of newly discovered proteins, making protein subcellular localization by wet-lab experiments a mission impossible. To tackle this concern, in the past decades, artificial intelligence (AI) and machine learning (ML), especially deep learning methods, have made significant progress in this research area. In this article, we review the latest advances in AI-based method development in three typical types of approaches, including sequence-based, knowledge-based, and image-based methods. We also elaborately discuss existing challenges and future directions in AI-based method development in this research field.

BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer

OBJECTIVE

The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment.

PATIENTS AND METHODS

Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis.

RESULTS

The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC.

CONCLUSION

The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.

Pla2g12b drives expansion of triglyceride-rich lipoproteins

Vertebrates transport hydrophobic triglycerides through the circulatory system by packaging them within amphipathic particles called Triglyceride-Rich Lipoproteins. Yet, it remains largely unknown how triglycerides are loaded onto these particles. Mutations in Phospholipase A2 group 12B (PLA2G12B) are known to disrupt lipoprotein homeostasis, but its mechanistic role in this process remains unclear. Here we report that PLA2G12B channels lipids within the lumen of the endoplasmic reticulum into nascent lipoproteins. This activity promotes efficient lipid secretion while preventing excess accumulation of intracellular lipids. We characterize the functional domains, subcellular localization, and interacting partners of PLA2G12B, demonstrating that PLA2G12B is calcium-dependent and tightly associated with the membrane of the endoplasmic reticulum. We also detect profound resistance to atherosclerosis in PLA2G12B mutant mice, suggesting an evolutionary tradeoff between triglyceride transport and cardiovascular disease risk. Here we identify PLA2G12B as a key driver of triglyceride incorporation into vertebrate lipoproteins.

Exploring the potential biological function of GRK2 in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a malignant tumor of the gastrointestinal tract with high morbidity and mortality. There is growing evidence that GRK2 plays a key role in the development and progression of several human cancers. However, the role and potential mechanisms of GRK2 in colon cancer (COAD) are unclear.

METHODS

The expression data of GRK2 was downloaded from The Cancer Genome Atlas database (TCGA). Variation in GRK2 was explored based on the cBioPortal database. The TIMER and TISCH2 databases were used to analyse the relationship between GRK2 expression and tumor immune microenvironment (TME). A log-rank test was used to compare the prognosis of high and low expression of GRK2 groups. Detecting the effect of GRK2 on cell cycle and apoptosis induced by 5-Fluorouracil (5-FU) through the flow cytometry and detection of apoptosis-related molecules by Western blot.

RESULTS

We demonstrated that GRK2 has a potential oncogenic role. GRK2 expression was upregulated in COAD, which predicted poorer overall survival in COAD patients. The cellular assays showed that GRK2 plays a role in the growth and proliferation of colon cancer cells, also the expression of GRK2 have relationship with the sensitivity of 5-FU and cell cycle progression.

CONCLUSIONS

Our results suggest that high GRK2 expression is closely associated with the development of tumor and affects the 5-FU sensitivity.

The Importance, Challenges, and Possible Solutions for Sharing Proteomics Data While Safeguarding Individuals' Privacy

Proteomics data sharing has profound benefits at the individual level as well as at the community level. While data sharing has increased over the years, mostly due to journal and funding agency requirements, the reluctance of researchers with regard to data sharing is evident as many shares only the bare minimum dataset required to publish an article. In many cases, proper metadata is missing, essentially making the dataset useless. This behavior can be explained by a lack of incentives, insufficient awareness, or a lack of clarity surrounding ethical issues. Through adequate training at research institutes, researchers can realize the benefits associated with data sharing and can accelerate the norm of data sharing for the field of proteomics, as has been the standard in genomics for decades. In this article, we have put together various repository options available for proteomics data. We have also added pros and cons of those repositories to facilitate researchers in selecting the repository most suitable for their data submission. It is also important to note that a few types of proteomics data have the potential to re-identify an individual in certain scenarios. In such cases, extra caution should be taken to remove any personal identifiers before sharing on public repositories. Data sets that will be useless without personal identifiers need to be shared in a controlled access repository so that only authorized researchers can access the data and personal identifiers are kept safe.

Identification of Hydroxysteroid Dehydrogenase Type 1 As a Potential Bladder Tumor Marker

Background

The 17beta-hydroxysteroid dehydrogenase type 1 (HSD17B) family has been implicated in the prognosis and treatment prediction of various malignancies; however, its association with bladder cancer (BLCA) remains unclear. This study aimed to evaluate the potential of HSD17B1, as a prognostic biomarker, for the survival of patients with BLCA and to determine its effectiveness as a supplemental biomarker for BLCA.

Methods

A series of bioinformatics techniques were applied to investigate the expression of HSD17B1 in different types of cancer and its potential association with the prognosis of BLCA patients using diverse databases. The UALCAN, Human Protein Atlas, cBioPortal, Metascape, GEPIA, MethSurv, and TIMER were employed to analyze expression differences, mutation status, enrichment analysis, overall survival, methylation, and immune-infiltrating cells. The real-time reverse transcription-PCR (qRT-PCR) was implemented to detect the messenger ribonucleic acid (mRNA) expression levels of HSD17B1 in vitro.

Results

Elevated mRNA and protein levels of HSD17B1, surpassing normal levels, were observed in BLCA samples. In addition, the BLCA patients with higher mRNA expression level of HSD17B1 significantly reduced the overall survival. Also, several immune infiltrating cells, including mast cell resting CIBERSORT-ABS, have been identified as tumor-associated biomarker genes, with the potential to significantly influence the immunological environment. Finally, qRT-PCR analysis revealed a significant upregulation of HSD17B1 mRNA expression level in the cancer cells compared to the human 293T cells, which was consistent with the bioinformatics data.

Conclusion

There is a strong correlation between the elevated HSD17B1 expression and positive prognosis in patients with BLCA. Therefore, HSD17B1 can be used as a prognostic biomarker in these patients.

Biophysical Analysis of Potential Inhibitors of SARS-CoV-2 Cell Recognition and Their Effect on Viral Dynamics in Different Cell Types: A Computational Prediction from In Vitro Experimental Data

Recent reports have suggested that the susceptibility of cells to SARS-CoV-2 infection can be influenced by various proteins that potentially act as receptors for the virus. To investigate this further, we conducted simulations of viral dynamics using different cellular systems (Vero E6, HeLa, HEK293, and CaLu3) in the presence and absence of drugs (anthelmintic, ARBs, anticoagulant, serine protease inhibitor, antimalarials, and NSAID) that have been shown to impact cellular recognition by the spike protein based on experimental data. Our simulations revealed that the susceptibility of the simulated cell systems to SARS-CoV-2 infection was similar across all tested systems. Notably, CaLu3 cells exhibited the highest susceptibility to SARS-CoV-2 infection, potentially due to the presence of receptors other than ACE2, which may account for a significant portion of the observed susceptibility. Throughout the study, all tested compounds showed thermodynamically favorable and stable binding to the spike protein. Among the tested compounds, the anticoagulant nafamostat demonstrated the most favorable characteristics in terms of thermodynamics, kinetics, theoretical antiviral activity, and potential safety (toxicity) in relation to SARS-CoV-2 spike protein-mediated infections in the tested cell lines. This study provides mathematical and bioinformatic models that can aid in the identification of optimal cell lines for compound evaluation and detection, particularly in studies focused on repurposed drugs and their mechanisms of action. It is important to note that these observations should be experimentally validated, and this research is expected to inspire future quantitative experiments.

Assessment the value of Pyroptosis-Associated Gasdermin family genes in hepatocellular carcinoma: A Multi-Omics Comprehensive Analysis

Background: Hepatocellular carcinoma (HCC) is one of the common primary cancers of the liver worldwide and leading cause of mortality. Gasdermins (GSDMs) family genes play an important role in the regulation of the normal physiological processes and have been implicated in multiple diseases. However, little is known about the relationship between different GSDMs proteins and HCC. The aim of this study was to explore the potential relationship between the expression, prognosis, genetic variation and immune infiltration of GSDMs family genes and HCC. Methods: We used different bioinformatics common public databases such as GSCA, GEPIA, UALCAN, HPA, Kaplan-Meier Plotter, LinkedOmics, GeneMANIA, STRING, cBioPortal, TIMER and TISIDB to analyze the differential expression of the different GSDMs, prognostic value, genetic alterations, immune cell infiltration and their functional networks in HCC patients. Results: All the members of the GSDMs family exhibited elevated mRNA expression levels in LIHC compared to the normal tissues, while only GSDMB, GSDMD and GSDME showed enhanced protein expression. The mRNA expression of most GSDMs members was found to be elevated in HCC patients at stages I-III (clinical stage) compared to the normal subjects. The expression of GSDMD was correlated with OS and DSS of patients, whereas GSDME was correlated with OS, DSS and RFS of patients. Gene amplification was observed to be main mode of variation in members of the GSDMs family. KEGG pathway analysis showed that genes associated with different members of the GSDMs family were enriched in the pathways of S. aureus infection, intestinal immunity, ribosome and protein assembly, oxidative phosphorylation, osteoclast differentiation and Fc gamma (γ) R-mediated phagocytosis. In addition, expression of both GSDMA and GSDME were found to be correlated most significantly with infiltration of immune cells, while GSDMA and GSDME somatic cell copy number alteration (CAN) were correlated significantly with the infiltration of immune cells. All GSDMs were noted to be associated with distinct subtypes of immune cells, except GSDMC. Conclusions: Our findings have provided useful insights to better understand the roles and functions of GSDMs in HCC that can provide novel direction for developing therapeutic modalities for HCC, including immunotherapy.

Understanding apoptotic induction by Sargentodoxa cuneata-Patrinia villosa herb pair via PI3K/AKT/mTOR signalling in colorectal cancer cells using network pharmacology and cellular studies

ETHNOPHARMACOLOGICAL RELEVANCE

Sargentodoxa cuneata (Sargentodoxa cuneata (Oliv.) Rehder & E.H.Wilson, DXT)-Patrinia villosa(Patrinia villosa (Thunb.) Dufr, BJC) constitutes a commonly employed herb pair in Chinese medicine for colorectal cancer (CRC) treatment. Modern pharmacological investigations have revealed the anticancer activities of both Sargentodoxa cuneata and Patrinia villosa. Nevertheless, comprehensive studies are required to discern the specific antitumor active ingredients and mechanism of action when these two herbs are used in combination.

AIM OF THE STUDY

Through the integration of network pharmacology, molecular docking techniques, experimental assays, and bioinformatics analysis, our study aims to forecast the active ingredients, potential targets, and molecular mechanisms underlying the therapeutic efficacy of this herb pair against CRC.

MATERIALS AND METHODS

Plant names (1, Sargentodoxa cuneata (Oliv.) Rehder & E.H.Wilson; 2, Patrinia villosa (Thunb.) Dufr.) have been verified through WorldFloraOnline (www.worldFloraonline.org) and MPNs (http://mpns.kew.org). The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) were utilized for screening the active ingredients of the herb pair. The PharmMapper database was employed to predict the target proteins for each active ingredient. CRC-related targets were obtained from the Genecards database, Online Mendelian Inheritance in Man (OMIM) database, Disease Gene Network (DisGeNET) database, and Therapeutic Target Database (TTD). Common targets were identified by intersecting the target proteins of all active ingredients with CRC-related targets. Protein-protein interactions (PPI) for the common target proteins were constructed using the String database and Cytoscape 3.9.1 software. Network topology analysis facilitated the identification of core targets. These core targets were subjected to enrichment analysis of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) using the Metascape database. Molecular docking was performed using Discovery Studio 2019 to investigate the interactions between the active ingredients and core target proteins. The core targets were validated through bioinformatics analysis using GEPIA, HPA, and the cBioPortal database. Finally, a series of experiments were conducted to further validate the results in vitro.

RESULT

A total of 15 active ingredients and 255 herb targets were identified, resulting in 66 common targets in conjunction with 6113 disease targets. The PPI analysis highlighted AKT1, EGFR, CASP3, SRC, and ESR1 as core targets. KEGG enrichment analysis indicated significant enrichment in the PI3K-AKT signaling pathway, a pathway associated with cancer. Molecular docking experiments confirmed favorable interactions between dihydroguaiaretic acid and the core target proteins (AKT1, EGFR, CASP3, and ESR1). Bioinformatics analysis revealed differential expression of EGFR and CASP3 in normal and CRC tissues. Cellular experiments further verified that dihydroguaiaretic acid induces apoptosis in colorectal cancer cells through the PI3K-AKT signaling pathway.

CONCLUSION

Our network pharmacology study has elucidated that the Sargentodoxa cuneata-Patrinia villosa herb pair exerts the negative regulation of the PI3K/AKT/mTOR signaling pathway, ultimately leading to the induction of apoptosis in colorectal cancer cells. This research has predicted and validated the active ingredients, potential targets, and molecular mechanisms of Sargentodoxa cuneata-Patrinia villosa in the treatment of CRC, providing scientific evidence for the use of traditional Chinese medicine in managing CRC.

CLEC11A expression as a prognostic biomarker in correlation to immune cells of gastric cancer

Gastric cancer (GC) is a prevalent malignant cancer characterized by a poor survival rate. The C-type lectin domain family 11 member A (CLEC11A) is part of the C-type lectin superfamily, and its dysregulation has been implicated in the progression of several cancers. The specific role of CLEC11A and its association with immune infiltration in GC, however, remains unclear. In this study, we employed The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Tumor IMmune Estimation Resource (TIMER) database, Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier plotter databases, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and the CIBERSORT algorithm to investigate CLEC11A expression, its prognostic significance, its association with tumor immune infiltration, and gene function enrichment in GC. We conducted western blotting, Cell Counting Kit-8 (CCK-8), wound healing, and transwell assays to validate CLEC11A's function. We found that CLEC11A expression was significantly elevated in GC when compared to adjacent non-tumor tissues. Elevated CLEC11A expression was strongly associated with poor survival outcomes and advanced clinicopathological stages.  Moreover, heightened CLEC11A expression positively correlated with immunomodulators, chemokines, and the infiltration of immune cells, especially M2 macrophages, in GC. Additionally, CLEC11A silencing suppressed GC cells proliferation, migration and invasion in vitro. Our results elucidate the functions of CLEC11A in GC, suggesting its potential as a valuable prognostic biomarker and therapeutic target for GC immunotherapy.

Research on the Regulatory Mechanism of Ginseng on the Tumor Microenvironment of Colorectal Cancer based on Network Pharmacology and Bioinformatics Validation

BACKGROUND

A network pharmacology study on the biological action of ginseng in the treatment of colorectal cancer (CRC) by regulating the tumor microenvironment (TME).

OBJECTIVES

To investigate the potential mechanism of action of ginseng in the treatment of CRC by regulating TME.

METHODS

This research employed network pharmacology, molecular docking techniques, and bioinformatics validation. Firstly, the active ingredients and the corresponding targets of ginseng were retrieved using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Integrated Database (TCMID), and the Traditional Chinese Medicine Database@Taiwan (TCM Database@Taiwan). Secondly, the targets related to CRC were retrieved using Genecards, Therapeutic Target Database (TTD), and Online Mendelian Inheritance in Man (OMIM). Tertiary, the targets related to TME were derived from screening the GeneCards and National Center for Biotechnology Information (NCBI)-Gene. Then the common targets of ginseng, CRC, and TME were obtained by Venn diagram. Afterward, the Protein-protein interaction (PPI) network was constructed in the STRING 11.5 database, intersecting targets identified by PPI analysis were introduced into Cytoscape 3.8.2 software cytoHubba plugin, and the final determination of core targets was based on degree value. The OmicShare Tools platform was used to analyze the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the core targets. Autodock and PyMOL were used for molecular docking verification and visual data analysis of docking results. Finally, we verified the core targets by Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases in bioinformatics.

RESULTS

A total of 22 active ingredients and 202 targets were identified to be closely related to the TME of CRC. PPI network mapping identified SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 as possible core targets. Go enrichment analysis showed that it was mainly involved in T cell co-stimulation, lymphocyte co-stimulation, growth hormone response, protein input, and other biological processes; KEGG pathway analysis found 123 related signal pathways, including EGFR tyrosine kinase inhibitor resistance, chemokine signaling pathway, VEGF signaling pathway, ErbB signaling pathway, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. The molecular docking results showed that the main chemical components of ginseng have a stable binding activity to the core targets. The results of the GEPIA database showed that the mRNA levels of PIK3R1 were significantly lowly expressed and HSP90AA1 was significantly highly expressed in CRC tissues. Analysis of the relationship between core target mRNA levels and the pathological stage of CRC showed that the levels of SRC changed significantly with the pathological stage. The HPA database results showed that the expression levels of SRC were increased in CRC tissues, while the expression of STAT3, PIK3R1, HSP90AA1, and AKT1 were decreased in CRC tissues.

CONCLUSION

Ginseng may act on SRC, STAT3, PIK3R1, HSP90AA1, and AKT1 to regulate T cell costimulation, lymphocyte costimulation, growth hormone response, protein input as a molecular mechanism regulating TME for CRC. It reflects the multi-target and multi-pathway role of ginseng in modulating TME for CRC, which provides new ideas to further reveal its pharmacological basis, mechanism of action and new drug design and development.

Imaging Mass Cytometry for In Situ Immune Profiling

The complexities and cellular heterogeneity associated with tissues necessitate the concurrent detection of markers beyond the limitations of conventional imaging approaches in order to spatially resolve the relationships between immune cell populations and their environments. This is a necessary complement to single-cell suspension-based methods to inform a better understanding of the events that may underlie pathological conditions. Imaging mass cytometry is a high-dimensional imaging modality that allows for the concurrent detection of up to 40 protein markers of interest across tissues at subcellular resolution. Here, we present an optimized staining protocol for imaging mass cytometry with modifications that integrate RNAscope. This unique addition enables combined protein and single-molecule RNA detection, thereby expanding the utility of imaging mass cytometry to researchers investigating low abundance or noncoding targets. In general, the procedure described is broadly applicable for comprehensive immune profiling of host-pathogen interactions, tumor microenvironments and inflammatory conditions, all within the tissue contexture.

Association of Blood MicroRNA Expression and Polymorphisms with Cognitive and Biomarker Changes in Older Adults

BACKGROUND

Identifying individuals before the onset of overt symptoms is key in the prevention of Alzheimer's disease (AD).

OBJECTIVES

Investigate the use of miRNA as early blood-biomarker of cognitive decline in older adults.

DESIGN

Cross-sectional.

SETTING

Two observational cohorts (CHARIOT-PRO, Alzheimer's Disease Neuroimaging Initiative (ADNI)).

PARTICIPANTS

830 individuals without overt clinical symptoms from CHARIOT-PRO and 812 individuals from ADNI.

MEASUREMENTS

qPCR analysis of a prioritised set of 38 miRNAs in the blood of individuals from CHARIOT-PRO, followed by a brain-specific functional enrichment analysis for the significant miRNAs. In ADNI, genetic association analysis for polymorphisms within the significant miRNAs' genes and CSF levels of phosphorylated-tau, total-tau, amyloid-β42, soluble-TREM2 and BACE1 activity using whole genome sequencing data. Post-hoc analysis using multi-omics datasets.

RESULTS

Six miRNAs (hsa-miR-128-3p, hsa-miR-144-5p, hsa-miR-146a-5p, hsa-miR-26a-5p, hsa-miR-29c-3p and hsa-miR-363-3p) were downregulated in the blood of individuals with low cognitive performance on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The pathway enrichment analysis indicated involvement of apoptosis and inflammation, relevant in early AD stages. Polymorphisms within genes encoding for hsa-miR-29c-3p and hsa-miR-146a-5p were associated with CSF levels of amyloid-β42, soluble-TREM2 and BACE1 activity, and 21 variants were eQTL for hippocampal MIR29C expression.

CONCLUSIONS

six miRNAs may serve as potential blood biomarker of subclinical cognitive deficits in AD. Polymorphisms within these miRNAs suggest a possible interplay between the amyloid cascade and microglial activation at preclinical stages of AD.

Transgelin 2 guards T cell lipid metabolic programming and anti-tumor function

Mounting effective immunity against pathogens and tumors relies on the successful metabolic programming of T cells by extracellular fatty acids1-3. During this process, fatty-acid-binding protein 5 (FABP5) imports lipids that fuel mitochondrial respiration and sustain the bioenergetic requirements of protective CD8+ T cells4,5. Importantly, however, the mechanisms governing this crucial immunometabolic axis remain unexplored. Here we report that the cytoskeletal organizer Transgelin 2 (TAGLN2) is necessary for optimal CD8+ T cell fatty acid uptake, mitochondrial respiration, and anti-cancer function. We found that TAGLN2 interacts with FABP5, enabling the surface localization of this lipid importer on activated CD8+ T cells. Analysis of ovarian cancer specimens revealed that endoplasmic reticulum (ER) stress responses elicited by the tumor microenvironment repress TAGLN2 in infiltrating CD8+ T cells, enforcing their dysfunctional state. Restoring TAGLN2 expression in ER-stressed CD8+ T cells bolstered their lipid uptake, mitochondrial respiration, and cytotoxic capacity. Accordingly, chimeric antigen receptor T cells overexpressing TAGLN2 bypassed the detrimental effects of tumor-induced ER stress and demonstrated superior therapeutic efficacy in mice with metastatic ovarian cancer. Our study unveils the role of cytoskeletal TAGLN2 in T cell lipid metabolism and highlights the potential to enhance cellular immunotherapy in solid malignancies by preserving the TAGLN2-FABP5 axis.

In vivo tracing of the Cytokeratin 14 lineages using self-cleaving guide RNAs and CRISPR/Cas9

The current gold-standard for genetic lineage tracing in transgenic mice is based on cell-type specific expression of Cre recombinase. As an alternative, we developed a cell-type specific CRISPR/spCas9 system for lineage tracing. This method relies on RNA polymerase II promoter driven self-cleaving guide RNAs (scgRNA) to achieve tissue-specificity. To demonstrate proof-of-principle for this approach a transgenic mouse was generated harbouring a knock-in of a scgRNA into the Cytokeratin 14 (Krt14) locus. Krt14 expression marks the stem cells of squamous epithelium in the skin and oral mucosa. The scgRNA targets a Stop cassette preceding a fluorescent reporter in the Ai9-tdtomato mouse. Ai9-tdtomato reporter mice harbouring this allele along with a spCas9 transgene demonstrated precise marking of the Krt14 lineage. We conclude that RNA polymerase II promoter driven scgRNAs enable the use of CRISPR/spCas9 for genetic lineage tracing.

Promoter Hypomethylation Upregulates ANXA2 Expression in Pancreatic Cancer and is Associated with Poor Prognosis

Pancreatic cancer (PC) is one of the world's most aggressive and deadly cancers, owing to non-specific early clinical symptoms, late-stage diagnosis, and poor survival. Therefore, it is critical to identify specific biomarkers for its early diagnosis. Annexin A2 (ANXA2) is a calcium-dependent phospholipid-binding protein that has been reported to be upregulated in several cancer types, making it an emerging biomarker and potential cancer therapeutic target. However, the mechanism underlying the regulation of ANXA2 overexpression is still unclear. It is well established that genetic and epigenetic alterations may lead to widespread dysregulation of gene expression. Hence, in this study, we focused on exploring the regulatory mechanism of ANXA2 by investigating the transcriptional profile, methylation pattern, somatic mutation, and prognostic value of ANXA2 in PC using several bioinformatics databases. Our results revealed that the expression levels of ANXA2 were remarkably increased in PC tissues comparing to normal tissues. Furthermore, the high expression of ANXA2 was significantly related to the poor prognosis of PC patients. More importantly, we demonstrated for the first time that the ANXA2 promoter is hypomethylated in PC tissues compared to normal tissues which may result in ANXA2 overexpression in PC. However, more experimental research is required to corroborate our findings.

Integrated single-cell and bulk sequencing analyses with experimental validation identify the prognostic and immunological implications of CD226 in pan-cancer

PURPOSE

CD226 (DNAM-1) is an activating receptor mainly expressed in CD8 + and NK cells. CD226 deficiency and blockade have been shown to impair tumor suppression, while enhanced CD226 expression positively correlated with the increased efficacy of immune checkpoint blockade (ICB) therapies. However, the detailed function and role of CD226 in pan-cancer are largely unknown and require further in-depth investigation. Therefore, this study aims to investigate the biological functions of CD226, its role in tumor immunity, and its potential to predict prognosis and immunotherapy response in pan-cancer.

METHODS

By taking advantage of single-cell and bulk sequencing analyses, we analyzed the expression profile of CD226, its correlation with patient prognosis, immune infiltration level, immune-related genes, tumor heterogeneity, and stemness in pan-cancer. We also investigated the biological functions of CD226 using gene set enrichment analysis (GSEA) and evaluated its predictive value in response to immunotherapy and small-molecule targeted drugs. In addition, we validated the expression of CD226 in tumor-infiltrating CD8 + and NK cells and studied its association with their functions using a murine B16F10 melanoma model.

RESULTS

CD226 exhibited differential expression across most tumor types, and its elevated expression was associated with improved clinical outcomes in multiple cancer types. CD226 is closely correlated with numerous tumor-infiltrating immune cells, tumor stemness, and heterogeneity in most cancers. Furthermore, based on single-cell sequencing analysis, CD226 expression was found to be higher on effector CD4 + T cells than naïve CD4 + T cells, and its expression level was decreased in exhausted CD8 + T cells relative to effector CD8 + T cells in multiple cancer types. Additionally, flow cytometric analysis demonstrated that CD226 was highly correlated with the function of tumor-infiltrating NK and CD8 + T cells in murine B16F10 melanoma. Moreover, GSEA analysis revealed that CD226 was closely associated with T cell activation, natural killer cell mediated immunity, natural killer cell-mediated cytotoxicity, and T cell receptor signaling pathway. Finally, CD226 showed promising predictive potential for responsiveness to both ICB therapies and various small-molecule targeted drugs.

CONCLUSION

CD226 has shown great potential as an innovative biomarker for predicting patient prognosis, immune infiltration levels, and the function of tumor-infiltrating CD8 + T cells, as well as immunotherapy response. Additionally, our findings suggest that the optimal modification of CD226 expression and function, combined with current ICBs, could be a promising strategy for tumor immunotherapy.

Identification of TMEM178 as a Potential Prognostic Biomarker and Therapeutic Target for Breast Cancer

Background

The transmembrane protein (TMEM) family plays important roles in cancer. However, the expression pattern and biological roles of TMEM178, a member of TMEM family, remains unclear in breast cancer (BRCA).

Methods

Methylation and RNA-seq data were obtained to explore methylation level. Expression of TMEM178, methylation inhibitor 5-Aza-CdR was used to verify the effect of methylation status on the expression of TMEM178. We comprehensively investigated the prognostic outcomes, biological functions and effects on immune cell infiltration of the TMEM178 in BRCA using multiple bioinformatics methods.

Results

The expression of TMEM178 was downregulated and negatively correlated with the level of DNA methylation and DNA methyltransferase (DNMT1, DNMT3A, and DNMT3B) in BRCA. Consistently, TMEM178 mRNA were confirmed to be downregulated, while upregulated in response to treatment with methylation inhibitor 5-Aza-CdR by RT-qPCR. Patients with high expression of TMEM178 have better prognosis and are more sensitive to targeted drug Pazopanib. Immune infiltration analysis showed that the infiltration levels of CD4+ T cell subsets were reduced in BRAC tissues with high TMEM178 expression, and immunosuppressive molecules of T-cell exhaustion were lower expression level.

Conclusion

Hypermethylation of the TMEM178 promoter region was a contributing factor to the downregulation of its expression, and TMEM178 may reflect a prognostic and immunosuppressive situation in BRCA.

SLC31A1 Identifying a Novel Biomarker with Potential Prognostic and Immunotherapeutic Potential in Pan-Cancer

Solute carrier family 31 member 1 (SLC31A1) encodes a protein that functions as a homotrimer for the uptake of dietary copper. As a vital member of the cuproptosis gene family, it plays an essential role in both normal tissues and tumors. In this study, we analyzed SLC31A1 across human cancer types to gain a better understanding of SLC31A1's role in cancer development. We searched for information using online databases to analyze, systematically and comprehensively, the role of SLC31A1 in tumors. Amongst nine cancer types, the expression of SLC31A1 was significantly different between tumors and normal tissues. According to further analysis, pancreatic cancer had the highest mutation rate of the SLC31A1 gene, and the methylation levels of the gene were significantly reduced in seven tumors. The expression of SLC31A1 is also linked to the infiltration of tumors by immune cells, the expression of immune checkpoint genes, and immunotherapy markers (TMB and MSI), suggesting that SLC31A1 may be of particular relevance in immunotherapy. This thorough analysis of SLC31A1 across different types of cancer gives us a clear and comprehensive insight into its role in causing cancer on a systemic level.

Network Pharmacology and Bioinformatics Study of Geniposide Regulating Oxidative Stress in Colorectal Cancer

This study aims to identify the mechanism of geniposide regulating oxidative stress in colorectal cancer (CRC) through network pharmacology and bioinformatics analysis. Targets of geniposide, oxidative stress-related targets and targets related to CRC were applied from databases. The hub genes for geniposide regulating oxidative stress in CRC were identified with the protein-protein interaction (PPI) network. Furthermore, we applied Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment to analyze the hub genes from a macro perspective. We verified the hub genes by molecular docking, GEPIA, HPA and starBase database. We identified five hub genes: IL1B, GSK3B, NOS3, RELA and CDK4. GO analysis results suggested that the anti-colorectal cancer effect of geniposide by regulating oxidative stress is possibly related to the influence of multiple biological processes, including response to temperature stimulus, response to alkaloid, nitric oxide biosynthetic process, nitric oxide metabolic process, reactive nitrogen species metabolic process, cellular response to peptide, etc. KEGG enrichment analysis results indicated that the PI3K-Akt signaling pathway, IL-17 signaling pathway, p53 signaling pathway, NF-κB signaling pathway and NOD-like receptor signaling pathway are likely to be the significant pathways. Molecular docking results showed that the geniposide had a good binding activity with the hub genes. This study demonstrates that geniposide can regulate oxidative stress in CRC, and induction of oxidative stress is one of the possible mechanisms of anti-recurrence and metastasis effects of geniposide against CRC.

Identification of two immune subtypes and four hub immune-related genes in ovarian cancer through multiple analysis

Immune classification of ovarian cancer (OV) becomes more and more influential for its immunotherapy. However, current studies had few immune subtypes of OV. It is urgent to explore the immune subtypes and deeper hub immune-related genes (IRGs) of OV for follow-up treatment. A total number of 379 OV samples were obtained from UCSC online website. Single sample gene set enrichment analysis of 29 immune gene sets was used for identifying immune subtypes of OV and gene set variation analysis were used for exploring the hallmarks and Kyoto Encyclopedia of Genes and Genomes pathways of immune types. Two immunity subtypes (Immunity_H and Immunity_L) were identified by single sample gene set enrichment analysis. The OV patients in Immunity_H group had longer overall survival compared with those in Immunity_L group. The Immunity_H had higher stromal score, immune score and estimate score and the tumor purity had the adverse tendency. Besides, the gene set variation analysis enrichment results showed positive relationship between improved immunoreaction and pathways correlated to classical signaling pathway (PI3K/AKT/MTOR, P53, TNFA/NFkB signaling pathways) and immune responses (T/B cell receptor signaling pathways and primary immunodeficiency). Furthermore, 4 hub IRGs (CCR5, IL10RA, ITGAL and PTPRC) were jointly dug by weighted gene co-expression network construction and Cytoscape. Our team also explored the mutations of 4 hub IRGs and PTPRC showed nearly 7% amplification. Besides, 8 immune-checkpoint genes had higher expression in Immuity_H group compared with Immuity_L group, except CD276. The correlation between PD-1/PD-L1 and 4 hub IRGs were explored and gene set enrichment analysis were conducted to explore the underlying mechanisms of PTPRC in OV. Finally, western-blotting showed PTPRC could regulate immune checkpoint PD-L1 expression via JAK-STAT signaling pathway. In a word, 2 immune subtypes and 4 hub IRGs of OV were identified by multiple analysis.

Integrative bioinformatics analysis of WDHD1: a potential biomarker for pan-cancer prognosis, diagnosis, and immunotherapy

BACKGROUND

Although WD repeat and high-mobility group box DNA binding protein 1 (WDHD1) played an essential role in DNA replication, chromosome stability, and DNA damage repair, the panoramic picture of WDHD1 in human tumors remains unclear. Hence, this study aims to comprehensively characterize WDHD1 across 33 human cancers.

METHODS

Based on publicly available databases such as TCGA, GTEx, and HPA, we used a bioinformatics approach to systematically explore the genomic features and biological functions of WDHD1 in pan-cancer.

RESULTS

WDHD1 mRNA levels were significantly increased in more than 20 types of tumor tissues. Elevated WDHD1 expression was associated with significantly shorter overall survival (OS) in 10 tumors. Furthermore, in uterine corpus endometrial carcinoma (UCEC) and liver hepatocellular carcinoma (LIHC), WDHD1 expression was significantly associated with higher histological grades and pathological stages. In addition, WDHD1 had a high diagnostic value among 16 tumors (area under the ROC curve [AUC] > 0.9). Functional enrichment analyses suggested that WDHD1 probably participated in many oncogenic pathways such as E2F and MYC targets (false discovery rate [FDR] < 0.05), and it was involved in the processes of DNA replication and DNA damage repair (p.adjust < 0.05). WDHD1 expression also correlated with the half-maximal inhibitory concentrations (IC50) of rapamycin (4 out of 10 cancers) and paclitaxel (10 out of 10 cancers). Overall, WDHD1 was negatively associated with immune cell infiltration and might promote tumor immune escape. Our analysis of genomic alterations suggested that WDHD1 was altered in 1.5% of pan-cancer cohorts and the "mutation" was the predominant type of alteration. Finally, through correlation analysis, we found that WDHD1 might be closely associated with tumor heterogeneity, tumor stemness, mismatch repair (MMR), and RNA methylation modification, which were all processes associated with the tumor progression.

CONCLUSIONS

Our pan-cancer analysis of WDHD1 provides valuable insights into the genomic characterization and biological functions of WDHD1 in human cancers and offers some theoretical support for the future use of WDHD1-targeted therapies, immunotherapies, and chemotherapeutic combinations for the management of tumors.

CrMP-Sol database: classification, bioinformatic analyses and comparison of cancer-related membrane proteins and their water-soluble variant designs

Membrane proteins are critical mediators for tumor progression and present enormous therapeutic potentials. Although gene profiling can identify their cancer-specific signatures, systematic correlations between protein functions and tumor-related mechanisms are still unclear. We present here the CrMP-Sol database ( https://bio-gateway.aigene.org.cn/g/CrMP ), which aims to breach the gap between the two. Machine learning was used to extract key functional descriptions for protein visualization in the 3D-space, where spatial distributions provide function-based predictive connections between proteins and cancer types. CrMP-Sol also presents QTY-enabled water-soluble designs to facilitate native membrane protein studies despite natural hydrophobicity. Five examples with varying transmembrane helices in different categories were used to demonstrate the feasibility. Native and redesigned proteins exhibited highly similar characteristics, predicted structures and binding pockets, and slightly different docking poses against known ligands, although task-specific designs are still required for proteins more susceptible to internal hydrogen bond formations. The database can accelerate therapeutic developments and biotechnological applications of cancer-related membrane proteins.

Identification of Genes and miRNAs Associated with TAFI-Related Thrombosis: An in Silico Study

Thrombin-Activatable Fibrinolysis Inhibitor (TAFI) is a carboxypeptidase B-like proenzyme encoded by the CPB2 gene. After thrombin activation, TAFI downregulates fibrinolysis, thus linking the latter with coagulation. TAFI has been shown to play a role in venous and arterial thrombotic diseases, yet, data regarding the molecular mechanisms underlying its function have been conflicting. In this study, we focused on the prediction and functional enrichment analysis (FEA) of the TAFI interaction network and the microRNAs (miRNAs) targeting the members of this network in an attempt to identify novel components and pathways of TAFI-related thrombosis. To this end, we used nine bioinformatics software tools. We found that the TAFI interactome consists of 28 unique genes mainly involved in hemostasis. Twenty-four miRNAs were predicted to target these genes. Co-annotation analysis of the predicted interactors with respect to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and transcription factors (TFs) pointed to the complement and coagulation cascades as well as neutrophil extracellular trap formation. Cancer, stroke, and intracranial aneurysm were among the top 20 significant diseases related to the identified miRNAs. We reason that the predicted biomolecules should be further studied in the context of TAFI-related thrombosis.

Exploring the diagnostic value, prognostic value, and biological functions of NPC gene family members in hepatocellular carcinoma based on a multi-omics analysis

Liver cancer is a cunning malignancy with a high incidence and mortality rate among cancers worldwide. The NPC gene family members (NPCs: NPC1, NPC2, and NPC1L1) are closely linked to the development of multiple cancers, but their role in liver cancer remains unclear. As a result, we must investigate their functions in liver hepatocellular carcinoma (LIHC). NPCs were significantly differentially expressed between normal and LIHC tissues, with a high mutation frequency in LIHC. The ROC curve analysis revealed that NPC1/NPC2 had high diagnostic and prognostic values in LIHC. NPC1 expression was also found to be negatively correlated with its methylation level. The differentially expressed genes between high and low NPC1 expression groups in LIHC were mainly related to channel activity, transporter complexes, and plasma membrane adhesion molecules. Additionally, NPC1 expression was significantly associated with multiple immune cells and immunization checkpoints. It was hypothesized that a TUG1/SNHG4-miR-148a-3p-NPC1 regulatory axis is associated with hepatocarcinogenesis. Finally, the protein expression of NPC1 in LIHC tissues and paraneoplastic tissues was detected, and NPC1-knockdown HepG2 cells (NPC1KO) inhibited the proliferation, migration, and invasion. This study helped to identify new prognostic markers and potential immunotherapeutic targets for LIHC and revealed the molecular mechanisms underlying NPC1 regulation in LIHC. The NPCs play a key role in the prognosis and diagnosis of LIHC and may be an important indicator for LIHC prognosis and diagnosis; NPC1 might be a potential therapeutic target in LIHC.

Six-transmembrane epithelial antigen of prostate 3 (STEAP3) is a potential prognostic biomarker in clear cell renal cell carcinoma that correlates with M2 macrophage infiltration and epithelial-mesenchymal

BACKGROUND

The six-transmembrane epithelial antigen of the prostate 3 (STEAP3) is a metalloreductase, which is essential for iron uptake. Existing literature has shown that STEAP3 may perform an important role in the onset and progression of tumors. Nonetheless, a complete pan-cancer investigation of the prognostic significance and immune properties of STEAP3 is currently unavailable.

AIMS

As part of our investigation into the possible functions of STEAP3 in malignancies, we conducted a comprehensive analysis to examine the prognostic value and immune features of STEAP3 in human pan-cancer.

METHODS AND RESULTS

R and Cytoscape programs were applied to analyze and visualize the data. The expression of STEAP3 in both cell lines and tissues was measured utilizing a variety of approaches. Using the shRNA knockdown technique, we tested the viability of the A498 and 786-O cell lines and validated their functions. Both CCK-8 and transwell assays were conducted to estimate cell proliferation and invasion. The expression of STEAP3 was substantially elevated and was shown to be linked to prognosis in the majority of malignancies, notably in clear cell renal cell carcinoma (ccRCC). In addition, the expression of STEAP3 was shown to have a strong correlation with immune infiltrates, which in turn triggered the recruitment and polarization of M2 macrophages in ccRCC. The protein STEAP3 shows promise as a predictor of responses to immune-checkpoint blockade (ICB) therapy. Positive links between STEAP3 and the epithelial-mesenchymal transition (EMT), the p53 pathway, and the immune-associated pathways were also found in the enrichment analysis. Our results illustrated that the STEAP3 expression level was substantially elevated in ccRCC tissues and suggested that it could stimulate EMT in ccRCC by downregulating CDH1.

CONCLUSION

In a diverse range of cancers, STEAP3 might serve as a biomarker for determining the prognosis as well as a predictor of immunotherapy responsiveness. STEAP3 is a novel biological marker for determining prognosis, and it also performs a remarkable function in the promotion of tumor growth in ccRCC by enhancing invasion and EMT, as well as by triggering the recruitment and polarization of M2 macrophages.

Initial experience of the treatment of large glioma with microwave ablation-assisted surgical resection

Aim

This study aimed to investigate the preliminary clinical outcomes of microwave ablation (MWA)-assisted surgical treatment for large glioma.

Materials and Methods

In total, six cases of large glioma (diameter >4 cm) were described. All cases were treated with MWA-assisted surgical resection, which was performed using ultrasound to guide the accurate placement of the antenna in the central region of the tumor. The MWA power was 40-45 W, and 6 min was applied. Changes in the ablation area were observed using intraoperative Doppler ultrasound and contrast-enhanced ultrasound (CEUS). Ten patients treated with surgical resection alone were included in the control group. Data on surgical times (i.e., the time from the incision of the dura to the removal of the tumor), intraoperative blood loss, and complications were recorded.

Results

The median patient age was 45 years (range: 36.5-60.3 years). The median lesion diameter was 4.9 cm (range: 4.3-5.8). The microwave power was 40-45 W, and the median ablation time was 240 s (range: 208-297 s). The intra-tumoral vascular flow was significantly reduced after MWA. The median surgical time was shorter (38.5 min [range: 34.3-42.8 min]) and the median intraoperative blood loss was less (400 mL, [range: 400-450 mL]) in the combination treatment group than in the surgery-alone group. During the ablation process, no obvious additional neurological deficits were detected; however, a tube-shaped carbonide was found after the operation.

Conclusion

MWA may be a useful complement to conventional techniques for the surgical resection of large glioma.

Expression of a STING Gain-of-function Mutation in Endothelial Cells Initiates Lymphocytic Infiltration of the Lungs

Patients afflicted with STING gain-of-function mutations frequently present with debilitating interstitial lung disease ( ILD ) that is recapitulated in mice expressing the STING V154M mutation ( VM ). Prior radiation chimera studies revealed an unexpected and critical role for non-hematopoietic cells in the initiation of ILD. To identify STING-expressing non-hematopoietic cell types relevant to ILD, we generated a conditional knock-in ( CKI ) model in which expression of the VM allele was directed to hematopoietic cells, fibroblasts, epithelial cells, or endothelial cells. Only endothelial cell-targeted expression of the mutant allele resulted in the recruitment of immune cells to the lung and the formation of bronchus-associated lymphoid tissue, as seen in the parental VM strain. These findings reveal the importance of endothelial cells as instigators of STING-driven lung disease and suggest that therapeutic targeting of STING inhibitors to endothelial cells could potentially mitigate inflammation in the lungs of SAVI patients or patients afflicted with other ILD-related disorders.

Summary

Patients with STING gain-of-function (GOF) mutations develop life-threatening lung autoinflammation. In this study, Gao et al. utilize a mouse model of conditional STING GOF to demonstrate a role for endothelial STING GOF in initiating immune cell recruitment into lung tissues of SAVI mice.

Comprehensive Analysis to Identify LINC00511-hsa-miR-625-5p-SEMA6A Pathway Fuels Progression of Skin Cutaneous Melanoma

Objective

Skin cutaneous melanoma (SKCM) is a highly lethal malignancy that poses a significant threat to human health. Recent research has shown that competing endogenous RNA (ceRNA) regulatory networks play a critical role in the development and progression of various types of cancer, including SKCM. The objective of this study is to investigate the ceRNA regulatory network associated with the transmembrane protein semaphorin 6A (SEMA6A) and identify the underlying molecular mechanisms involved in SKCM.

Methods

Expression profiles of four RNAs, including pseudogenes, long non-coding RNAs, microRNAs, and mRNAs were obtained from The Cancer Genome Atlas database. The analysis was completed by bioinformatics methods, and the expression levels of the selected genes were verified by cell experiments.

Results

Bioinformatics analysis revealed that the LINC00511-hsa-miR-625-5p-SEMA6A ceRNA network was associated with SKCM prognosis. Furthermore, immune infiltration analysis indicated that the LINC00511-hsa-miR-625-5p-SEMA6A axis may have an impact on changes in the tumor immune microenvironment of SKCM.

Conclusion

The LINC00511-hsa-miR-625-5p-SEMA6A axis could be a promising therapeutic target and a prognostic biomarker for SKCM.

CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases

T-cell-based immunotherapies hold tremendous potential in the fight against cancer, thanks to their capacity to specifically targeting diseased cells. Nevertheless, this potential has been tempered with safety concerns regarding the possible recognition of unknown off-targets displayed by healthy cells. In a notorious example, engineered T-cells specific to MAGEA3 (EVDPIGHLY) also recognized a TITIN-derived peptide (ESDPIVAQY) expressed by cardiac cells, inducing lethal damage in melanoma patients. Such off-target toxicity has been related to T-cell cross-reactivity induced by molecular mimicry. In this context, there is growing interest in developing the means to avoid off-target toxicity, and to provide safer immunotherapy products. To this end, we present CrossDome, a multi-omics suite to predict the off-target toxicity risk of T-cell-based immunotherapies. Our suite provides two alternative protocols, i) a peptide-centered prediction, or ii) a TCR-centered prediction. As proof-of-principle, we evaluate our approach using 16 well-known cross-reactivity cases involving cancer-associated antigens. With CrossDome, the TITIN-derived peptide was predicted at the 99+ percentile rank among 36,000 scored candidates (p-value < 0.001). In addition, off-targets for all the 16 known cases were predicted within the top ranges of relatedness score on a Monte Carlo simulation with over 5 million putative peptide pairs, allowing us to determine a cut-off p-value for off-target toxicity risk. We also implemented a penalty system based on TCR hotspots, named contact map (CM). This TCR-centered approach improved upon the peptide-centered prediction on the MAGEA3-TITIN screening (e.g., from 27th to 6th, out of 36,000 ranked peptides). Next, we used an extended dataset of experimentally-determined cross-reactive peptides to evaluate alternative CrossDome protocols. The level of enrichment of validated cases among top 50 best-scored peptides was 63% for the peptide-centered protocol, and up to 82% for the TCR-centered protocol. Finally, we performed functional characterization of top ranking candidates, by integrating expression data, HLA binding, and immunogenicity predictions. CrossDome was designed as an R package for easy integration with antigen discovery pipelines, and an interactive web interface for users without coding experience. CrossDome is under active development, and it is available at https://github.com/AntunesLab/crossdome.

Analysis of active components and molecular mechanism of action of Rubia cordifolia L. in the treatment of nasopharyngeal carcinoma based on network pharmacology and experimental verification

The aim of this study is to explore the active components and potential molecular mechanism of action of Rubia cordifolia L. against nasopharyngeal carcinoma (NPC). We used network pharmacology, molecular docking, and bioinformatics analysis to identify the active components and their role against NPC. The experimental verification was detected by MTT, AnnexinV-FITC/PI double fluorescence staining and Western blotting method. Network pharmacology identified that mollugin is one of the most effective components inRubia cordifolia L. Important NPC targets included HSP90AA1, CDK1, EGFR, PIK3CA, MAPK14, and CDK2. Molecular docking revealed considerable binding activity of mollugin with either of the 6 important NPC targets. Bioinformatics analysis showed that these 6 important targets were mutated in NPC, and the expression of HSP90AA1, PIK3CA, and CDK2 in cancer tissues was significantly different from that in normal tissues. MTT detection and AnnexinV-FITC/PI double fluorescence staining showed that mollugin inhibited the proliferation and induced apoptosis of NPC cells. Western blotting indicated that the molecular mechanism of mollugin against NPC was related to the regulation of the expression of Survivin and XIAP. This study predicted and partially verified the pharmacological and molecular mechanism of action of Rubia cordifolia L. against NPC. Mollugin was identified as a potential active ingredient against NPC. These results prove the reliability of network pharmacology approaches and provide a basis for further research and application of Rubia cordifolia L. against NPC.

Exploring the Correlation Between GPR176, a Potential Target Gene of Gastric Cancer, and Immune Cell Infiltration

Introduction

GPR176, an orphan G protein-coupled receptor (GPCR), is essential for the progression of gastrointestinal cancers. However, it is still unclear how GPR176 affects tumor immunity and patient prognosis in gastric cancer (GC).

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were searched in this investigation to assess the expression patterns of GPR176 in GC tissues and normal gastric mucosa. The findings were further verified using immunohistochemical tests and quantitative Real-Time Polymerase Chain Reaction (qRT-PCR). The Kaplan-Meier method, univariate logistic regression, and Cox regression were then used to investigate the relationship between GPR176 and clinical traits. Additionally, the potential correlation between GPR176, immune checkpoint genes, and immune cell infiltration levels was investigated.

Results

As per the research findings, GC tissues had higher levels of GPR176 than normal tissues. Additionally, individuals with high expression of GPR176 had a worse 10-year overall survival (OS), in contrast with those having a low expression of GPR176 (p < 0.001). The OS of GC can be predicted using a validated nomogram model. The expression of GPR176 demonstrated a negative correlation with CD8+ T cells. When compared to the low-expression group of GPR176, Tumor Immune Dysfunction and Exclusion (TIDE) analysis demonstrated that the high-expression group had a considerably higher risk of immune evasion. A remarkable difference (variation) was observed in the levels of GPR176 expression across both groups, ie, low and high-risk groups, as determined by the immune phenomenon scores (IPS) immunotherapy assessment.

Conclusion

By examining GPR176 from various biological perspectives, it was determined that GPR176 can act as a predictive biomarker for poor patient prognosis in GC. Additionally, it was observed that GPR176 is capable of suppressing the proliferation of CD8+ T cells and facilitating immune evasion.

Construction of a prognostic signature of RFC5 immune-related genes in patients with cervical cancer

BACKGROUND

Cervical cancer (CC) is a malignant tumor threatening women's health. Replication factor C (RFC) 5 is significantly highly expressed in CC tissues, and the immune microenvironment plays a crucial role in tumor initiation, progression, and metastasis.

OBJECTIVE

To determine the prognostic role of RFC5 in CC, analyze the immune genes significantly associated with RFC5, and establish a nomogram to evaluate the prognosis of patients with CC.

METHODS

High RFC5 expression in patients with CC was analyzed and verified through TCGA GEO, TIMER2.0, and HPA databases. A risk score model was constructed using RFC5-related immune genes identified using R packages. Combining the risk score model and clinical information of patients with CC, a nomogram was constructed to evaluate the prognosis of patients with CC.

RESULTS

Comprehensive analysis showed that the risk score was a prognostic factor for CC. The nomogram could predict the 3-year overall survival of patients with CC.

CONCLUSIONS

RFC5 was validated as a biomarker for CC. The RFC5 related immune genes were used to establish a new prognostic model of CC.

Untargeted metabolomic analysis of ischemic injury in human umbilical vein endothelial cells reveals the involvement of arginine metabolism

OBJECTIVE

In this study, differentially expressed metabolites of vascular endothelial cells were examined to further understand the metabolic regulation of ischemic injury by untargeted metabolomics.

METHOD

Human umbilical vein endothelial cells (HUVECs) were selected to construct an ischemia model using oxygen-glucose deprivation (OGD) and 0, 3, 6, and 9 h of treatment. After that, cell survival levels were determined by CCK8 detection. Flow cytometry, ROS detection, JC-1 detection, and western blotting were used to measure apoptosis and oxidative stress in cells. Then, combined with UPLC Orbitrap/MS, we verified the impacted metabolism pathways by western blotting and RT‒PCR.

RESULTS

CCK8 assays showed that the survival of HUVECs was decreased with OGD treatment. Flow cytometry and the expression of cleaved caspase 3 showed that the apoptosis levels of HUVECs increased following OGD treatment. The ROS and JC-1 results further suggested that oxidative stress injury was aggravated. Then, combined with the heatmap, KEGG and IPA, we found that arginine metabolism was differentially altered during different periods of OGD treatment. Furthermore, the expression of four arginine metabolism-related proteins, ASS1, ARG2, ODC1 and SAT1, was found to change during treatment.

CONCLUSION

Arginine metabolism pathway-related proteins were significantly altered by OGD treatment, which suggests that they may have a potential role in ischemic injury.

A large-scale proteogenomic atlas of pear

Pear is an important fruit tree that is widely distributed around the world. The first pear genome map was reported from our laboratory approximately 10 years ago. To further study global protein expression patterns in pear, we generated pear proteome data based on 24 major tissues. The tissue-resolved profiles provided evidence of the expression of 17 953 proteins. We identified 4294 new coding events and improved the pear genome annotation via the proteogenomic strategy based on 18 090 peptide spectra with peptide spectrum matches >1. Among the eight randomly selected new short coding open reading frames that were expressed in the style, four promoted and one inhibited the growth of pear pollen tubes. Based on gene coexpression module analysis, we explored the key genes associated with important agronomic traits, such as stone cell formation in fruits. The network regulating the synthesis of lignin, a major component of stone cells, was reconstructed, and receptor-like kinases were implicated as core factors in this regulatory network. Moreover, we constructed the online database PearEXP (http://www.peardb.org.cn) to enable access to the pear proteogenomic resources. This study provides a paradigm for in-depth proteogenomic studies of woody plants.

Stage-dependent localization of F-actin and Na+ /K+ -ATPase in zebrafish embryos detected using optimized cryosectioning immunostaining protocol

The increasing use of the zebrafish model in biomedical and (eco)toxicological studies aimed at understanding the function of various proteins highlight the importance of optimizing existing methods to study gene and protein expression and localization in this model. In this context, zebrafish cryosections are still underutilized compared with whole-mount preparations. In this study, we used zebrafish embryos (24-120 hpf) to determine key factors for the preparation of high-quality zebrafish cryosections and to determine the optimal protocol for (immuno)fluorescence analyses of Na⁺ /K⁺ -ATPase and F-actin, across developmental stages from 1 to 5 dpf. The results showed that the highest quality zebrafish cryosections were obtained after the samples were fixed in 4% paraformaldehyde (PFA) for 1 h, incubated in 2.5% bovine gelatin/25% sucrose mixture, embedded in OCT, and then sectioned to 8 μm thickness at -20°C. Fluorescence microscopy analysis of phalloidin-labeled zebrafish skeletal muscle revealed that 1-h-4% PFA-fixed samples allowed optimal binding of phalloidin to F-actin. Further immunofluorescence analyses revealed detailed localization of F-actin and Na⁺ /K⁺ -ATPase in various tissues of the zebrafish and a stage-dependent increase in their respective expression in the somitic muscles and pronephros. Finally, staining of zebrafish cryosections and whole-mount samples revealed organ-specific and zone-dependent localizations of the Na⁺ /K⁺ -ATPase α1-subunit. RESEARCH HIGHLIGHTS: This study brings optimization of existing protocols for preparation and use of zebrafish embryos cryosections in (immuno)histological analyses. It reveals stage-dependent localization/expression of F-actin and Na⁺ /K⁺ -ATPase in zebrafish embryos.

Roadmap to the study of gene and protein phylogeny and evolution-A practical guide

Developments in sequencing technologies and the sequencing of an ever-increasing number of genomes have revolutionised studies of biodiversity and organismal evolution. This accumulation of data has been paralleled by the creation of numerous public biological databases through which the scientific community can mine the sequences and annotations of genomes, transcriptomes, and proteomes of multiple species. However, to find the appropriate databases and bioinformatic tools for respective inquiries and aims can be challenging. Here, we present a compilation of DNA and protein databases, as well as bioinformatic tools for phylogenetic reconstruction and a wide range of studies on molecular evolution. We provide a protocol for information extraction from biological databases and simple phylogenetic reconstruction using probabilistic and distance methods, facilitating the study of biodiversity and evolution at the molecular level for the broad scientific community.

HetIG-PreDiG: A Heterogeneous Integrated Graph Model for Predicting Human Disease Genes based on gene expression

Graph analytical approaches permit identifying novel genes involved in complex diseases, but are limited by (i) inferring structural network similarity of connected gene nodes, ignoring potentially relevant unconnected nodes; (ii) using homogeneous graphs, missing gene-disease associations' complexity; (iii) relying on disease/gene-phenotype associations' similarities, involving highly incomplete data; (iv) using binary classification, with gene-disease edges as positive training samples, and non-associated gene and disease nodes as negative samples that may include currently unknown disease genes; or (v) reporting predicted novel associations without systematically evaluating their accuracy. Addressing these limitations, we develop the Heterogeneous Integrated Graph for Predicting Disease Genes (HetIG-PreDiG) model that includes gene-gene, gene-disease, and gene-tissue associations. We predict novel disease genes using low-dimensional representation of nodes accounting for network structure, and extending beyond network structure using the developed Gene-Disease Prioritization Score (GDPS) reflecting the degree of gene-disease association via gene co-expression data. For negative training samples, we select non-associated gene and disease nodes with lower GDPS that are less likely to be affiliated. We evaluate the developed model's success in predicting novel disease genes by analyzing the prediction probabilities of gene-disease associations. HetIG-PreDiG successfully predicts (Micro-F1 = 0.95) gene-disease associations, outperforming baseline models, and is validated using published literature, thus advancing our understanding of complex genetic diseases.

The human protein atlas-Integrated omics for single cell mapping of the human proteome

Studying the spatial distribution of proteins provides the basis for understanding the biology, molecular repertoire, and architecture of every human cell. The Human Protein Atlas (HPA) has grown into one of the world's largest biological databases, and in the most recent version, a major update of the structure of the database was performed. The data has now been organized into 10 different comprehensive sections, each summarizing different aspects of the human proteome and the protein-coding genes. In particular, large datasets with information on the single cell type level have been integrated, refining the tissue and cell type specificity and detailing the expression in cell states with an increased resolution. The multi-modal data constitute an important resource for both basic and translational science, and hold promise for integration with novel emerging technologies at the protein and RNA level.

Type-1 interferon-dependent and -independent mechanisms in cyclic GMP-AMP synthase-stimulator of interferon genes-driven auto-inflammation

The cyclic cyclic gaunosine monophosphate adenosine monophosphate (GMP-AMP) synthase-stimulator of interferon genes (cGAS-STING) pathway senses cytosolic dsDNA and initiates immune responses against pathogens. It is also implicated in several auto-inflammatory diseases known as monogenic interferonopathies, specifically Three prime repair exonuclease 1 (Trex1) loss-of-function (LOF), Dnase2 LOF, and stimulator of interferon genes-associated-vasculopathy-with-onset-in-infancy (SAVI). Although monogenic interferonopathies have diverse clinical presentations, they are distinguished by the elevation of type-1 interferons (T1IFNs). However, animal models have demonstrated that T1IFNs contribute to only some disease outcomes and that cGAS-STING activation also promotes T1IFN-independent pathology. For example, while T1IFNs drive the immunopathology associated with Trex1 LOF, disease in Dnase2 LOF is partially independent of T1IFNs, while disease in SAVI appears to occur entirely independent of T1IFNs. Additionally, while the cGAS-STING pathway is well characterized in hematopoietic cells, these animal models point to important roles for STING activity in nonhematopoietic cells in disease. Together, these models illustrate the complex role that cGAS-STING-driven responses play in the pathogenesis of inflammatory diseases across tissues.