DrugRepo: a novel approach to repurposing drugs based on chemical and genomic features

The drug development process consumes 9-12 years and approximately one billion US dollars in costs. Due to the high finances and time costs required by the traditional drug discovery paradigm, repurposing old drugs to treat cancer and rare diseases is becoming popular. Computational approaches are mainly data-driven and involve a systematic analysis of different data types leading to the formulation of repurposing hypotheses. This study presents a novel scoring algorithm based on chemical and genomic data to repurpose drugs for 669 diseases from 22 groups, including various cancers, musculoskeletal, infections, cardiovascular, and skin diseases. The data types used to design the scoring algorithm are chemical structures, drug-target interactions (DTI), pathways, and disease-gene associations. The repurposed scoring algorithm is strengthened by integrating the most comprehensive manually curated datasets for each data type. At DrugRepo score ≥ 0.4, we repurposed 516 approved drugs across 545 diseases. Moreover, hundreds of novel predicted compounds can be matched with ongoing studies at clinical trials. Our analysis is supported by a web tool available at: http://drugrepo.org/ .

Oesophagectomy following noncurative endoscopic resection for oesophageal carcinoma: does interval matter?

OBJECTIVES

Oesophagectomy was always recommended after noncurative endoscopic resection (ER). And the optimal time interval from ER to oesophagectomy remains unclear. This study was to explore the effect of interval on pathologic stage and prognosis.

METHODS

We included 155 patients who underwent ER for cT1N0M0 oesophageal cancer and then received subsequent oesophagectomy from 2009 to 2019. Overall survival and disease-free survival (DFS) were analysed to find an optimal cut-off of interval from ER to oesophagectomy. In addition, pathologic stage after ER was compared to that of oesophagectomy. Logistic regression model was built to identify risk factors for pathological upstage.

RESULTS

The greatest difference of DFS was found in the groups who underwent oesophagectomy before and after 30 days (P = 0.016). Among total 155 patients, 106 (68.39%) received oesophagectomy within 30 days, while 49 (31.61%) had interval over 30 days. Comparing the pathologic stage between ER and oesophagectomy, 26 patients had upstage and thus had worse DFS (hazard ratio = 3.780, P = 0.042). T1b invasion, lymphovascular invasion and interval >30-day group had a higher upstage rate (P = 0.014, P < 0.001 and P < 0.001, respectively). And they were independent risk factors for pathologic upstage (odds ratio = 3.782, 4.522 and 2.844, respectively).

CONCLUSIONS

It was the first study exploring the relationship between time interval and prognosis in oesophageal cancer. The longer interval between noncurative ER and additional oesophagectomy was associated with a worse DFS, so oesophagectomy was recommended performed within 1 month after ER. Older age, T1b stage, lymphovascular invasion and interval >30 days were significantly associated with pathologic upstage, which is related to the worse outcome too.

Synthetic lethal gene pairs: Experimental approaches and predictive models

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

Emerging role of chemokines in small cell lung cancer: Road signs for metastasis, heterogeneity, and immune response

Small cell lung cancer (SCLC) is a recalcitrant, relatively immune-cold, and deadly subtype of lung cancer. SCLC has been viewed as a single or homogenous disease that includes deletion or inactivation of the two major tumor suppressor genes (TP53 and RB1) as a key hallmark. However, recent sightings suggest the complexity of SCLC tumors that comprises highly dynamic multiple subtypes contributing to high intratumor heterogeneity. Furthermore, the absence of targeted therapies, the understudied tumor immune microenvironment (TIME), and subtype plasticity are also responsible for therapy resistance. Secretory chemokines play a crucial role in immunomodulation by trafficking immune cells to the tumors. Chemokines and cytokines modulate the anti-tumor immune response and wield a pro-/anti-tumorigenic effect on SCLC cells after binding to cognate receptors. In this review, we summarize and highlight recent findings that establish the role of chemokines in SCLC growth and metastasis, and sophisticated intratumor heterogeneity. We also discuss the chemokine networks that are putative targets or modulators for augmenting the anti-tumor immune responses in targeted or chemo-/immuno-therapeutic strategies, and how these combinations may be utilized to conquer SCLC.

Cornulin as a Prognosticator for Lymph Node Involvement in Cutaneous Squamous Cell Carcinoma

Background Cornulin is an epidermal differentiation marker and a stress-related protein. Its expression patterns are likely to reflect the multi-step tumorigenesis process of cSCC, given its role as a tumor suppressor. The aim of this study is to evaluate the utility of Cornulin as a prognosticator for cutaneous squamous cell carcinoma (cSCC). Specifically, the correlation between Cornulin expression and the clinicopathological parameter of lymph node involvement (nodal status), which plays a major role in determining cSCC prognosis and recurrence. We predicted that Cornulin expression declines as cSCC tumors metastasize to regional lymph nodes. Methodology Tissue samples of cSCC lesions of variable nodal involvement status were stained using immunohistochemistry, and high-resolution images were acquired. Aperio ImageScope software (Leica Biosystems) equipped with a positive-pixel-counting algorithm was used to quantify the staining intensity. Subsequently, Cornulin immunoreactivity was calculated as a Histo-score (H-score) value, which is based on the staining intensity and the percentage of positively stained cells. Mean H-scores were compared between groups using an unpaired t-test. Results A significant inverse correlation was found between Cornulin expression levels and metastasis to the lymph nodes. Specifically, primary tumors with metastasis to regional lymph nodes (N1) exhibited 9.5-fold decrease in Cornulin immunoreactivity compared to the primary tumor samples without lymph node involvement (N0). Conclusion Cornulin was found to be significantly downregulated in primary tumors with lymph node metastases. Detection assays to measure Cornulin expression in cSCC primary tumors might aid in determining the nodal status in these patients and possibly help determine cases of occult lymph node metastasis or micrometastasis. Future clinical studies are needed to help establish Cornulin's role in enhancing the predictive power of histopathological examination and improving survival rates for patients suffering from this type of skin cancer.

Characterization of Cornulin as a Molecular Biomarker for the Progression of Oral Squamous Cell Carcinoma

Introduction It has been shown that the expression of the epidermal differentiation marker, Cornulin, declines with the progression of squamous cell carcinomas of several tissue types. Objectives This study aims to examine Cornulin expression at the cellular level in various cell lines representative of the successive progression steps of oral squamous cell carcinoma (OSCC), a major type of head and neck cancer. This can pave the way for the utilization of this novel biomarker as a diagnostic and prognostic indicator for oral cancer and help guide treatment options. Study design Western blotting was performed to measure Cornulin expression levels using standardized cell lysates from four different cell lines representing the successive steps of OSCC progression. Specifically, primary gingival keratinocytes, dysplastic oral keratinocytes (DOK), squamous cell carcinoma 25 (SCC25) cells, and Detroit 562 cells were used to represent normal oral keratinocytes, DOKs, locally invasive OSCC cells, and metastatic OSCC cells, respectively. Results Cornulin expression was found to be downregulated with the progression from normal to premalignant to malignant cells. Quantitative analysis revealed that Cornulin is significantly downregulated by 3.4 folds in DOK cells, by 23.7 folds in SCC25 cells, and by 5.2 folds in Detroit 562 cells compared to normal gingival keratinocytes. Interestingly, Cornulin was upregulated by 4.5 folds in the metastatic Detroit 562 cell line compared to the locally invasive SCC25 cells. Conclusion Altogether, Cornulin proved to be differentially expressed at the cellular level in cell lines representative of the successive steps of OSCC progression. Specifically, we documented a gradual decrease in Cornulin expression with the progression from normal to premalignant to malignant cells. Notably, there is a significant increase in the expression of Cornulin in the metastatic cell line Detroit 562 compared to the locally invasive cell line SCC25, suggesting a possible correlation with the biological behavior and unique characteristics of these two different phenotypes.

PABPC1--mRNA stability, protein translation and tumorigenesis

Mammalian poly A-binding proteins (PABPs) are highly conserved multifunctional RNA-binding proteins primarily involved in the regulation of mRNA translation and stability, of which PABPC1 is considered a central regulator of cytoplasmic mRNA homing and is involved in a wide range of physiological and pathological processes by regulating almost every aspect of RNA metabolism. Alterations in its expression and function disrupt intra-tissue homeostasis and contribute to the development of various tumors. There is increasing evidence that PABPC1 is aberrantly expressed in a variety of tumor tissues and cancers such as lung, gastric, breast, liver, and esophageal cancers, and PABPC1 might be used as a potential biomarker for tumor diagnosis, treatment, and clinical application in the future. In this paper, we review the abnormal expression, functional role, and molecular mechanism of PABPC1 in tumorigenesis and provide directions for further understanding the regulatory role of PABPC1 in tumor cells.

Potential use of the S-protein-Angiotensin converting enzyme 2 binding pathway in the treatment of coronavirus disease 2019

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), infects humans through a strong interaction between the viral spike protein (S-protein) and angiotensin converting enzyme 2 (ACE2) receptors on the cell surface. The infection of host lung cells by SARS-CoV-2 leads to clinical symptoms in patients. However, ACE2 expression is not restricted to the lungs; altered receptors have been found in the nasal and oral mucosa, vessel, brain, pancreas, gastrointestinal tract, kidney, and heart. The future of COVID-19 is uncertain, however, new viral variants are likely to emerge. The SARS-CoV-2 Omicron variant has a total of 50 gene mutations compared with the original virus; 15 of which occur in the receptor binding domain (RBD). The RBD of the viral S-protein binds to the human ACE2 receptor for viral entry. Mutations of the ACE2-RBD interface enhance tight binding by increasing hydrogen bond interactions and expanding the accessible surface area. Extracorporeal membrane oxygenation, hyperbaric oxygen, and aggressive dialysis for the treatment of COVID-19 have shown various degrees of clinical success. The use of decoy receptors based on the ACE2 receptor as a broadly potent neutralizer of SARS-CoV-2 variants has potential as a therapeutic mechanism. Drugs such as 3E8 could block binding of the S1-subunit to ACE2 and restrict the infection of ACE2-expressing cells by a variety of coronaviruses. Here, we discuss the development of ACE2-targeted strategies for the treatment and prevention of COVID-19.

Emerging roles of alternative RNA splicing in oral squamous cell carcinoma

Alternative RNA splicing (ARS) is an essential and tightly regulated cellular process of post-transcriptional regulation of pre-mRNA. It produces multiple isoforms and may encode proteins with different or even opposite functions. The dysregulated ARS of pre-mRNA contributes to the development of many cancer types, including oral squamous cell carcinoma (OSCC), and may serve as a biomarker for the diagnosis and prognosis of OSCC and an attractive therapeutic target. ARS is mainly regulated by splicing factors, whose expression is also often dysregulated in OSCC and involved in tumorigenesis. This review focuses on the expression and roles of splicing factors in OSCC, the alternative RNA splicing events associated with OSCC, and recent advances in therapeutic approaches that target ARS.

Integrative network analysis interweaves the missing links in cardiomyopathy diseasome

Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy's genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, including NOS3, MMP2 and SIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.

Towards future directions in data-integrative supervised prediction of human aging-related genes

Motivation

Identification of human genes involved in the aging process is critical due to the incidence of many diseases with age. A state-of-the-art approach for this purpose infers a weighted dynamic aging-specific subnetwork by mapping gene expression (GE) levels at different ages onto the protein-protein interaction network (PPIN). Then, it analyzes this subnetwork in a supervised manner by training a predictive model to learn how network topologies of known aging- versus non-aging-related genes change across ages. Finally, it uses the trained model to predict novel aging-related gene candidates. However, the best current subnetwork resulting from this approach still yields suboptimal prediction accuracy. This could be because it was inferred using outdated GE and PPIN data. Here, we evaluate whether analyzing a weighted dynamic aging-specific subnetwork inferred from newer GE and PPIN data improves prediction accuracy upon analyzing the best current subnetwork inferred from outdated data.

Results

Unexpectedly, we find that not to be the case. To understand this, we perform aging-related pathway and Gene Ontology term enrichment analyses. We find that the suboptimal prediction accuracy, regardless of which GE or PPIN data is used, may be caused by the current knowledge about which genes are aging-related being incomplete, or by the current methods for inferring or analyzing an aging-specific subnetwork being unable to capture all of the aging-related knowledge. These findings can potentially guide future directions towards improving supervised prediction of aging-related genes via -omics data integration.

Availability and implementation

All data and code are available at zenodo, DOI: 10.5281/zenodo.6995045.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Implications and Emerging Therapeutic Avenues of Inflammatory Response in HPV+ Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinomas (HNSCC) are a heterogeneous group of malignancies which have shown exponential incidence in the last two decades especially due to human papillomavirus (HPV) infection. The HPV family comprises more than 100 types of viruses with HPV16 and HPV18 being the most prevalent strains in HNSCC. Literature data reveal that the mutation profile as well as the response to chemotherapy and radiotherapy are distinct among HPV+ versus HPV-negative tumors. Furthermore, the presence of the virus induces activation of an immune response, in particular the recruitment of specific antiviral T lymphocytes to tumor sites. These T cells when activated produce soluble factors including cytokines and chemokines capable of modifying the local immune tumor microenvironment and impact on tumor response to the treatment. In this comprehensive review we investigated current knowledge on how the presence of an HPV can modify the inflammatory response systemically and within the tumor microenvironment's immunological responses, thereby impacting on disease prognosis and survival. We highlighted the research gaps and emerging approaches necessary to discover novel immunotherapeutic targets for HPV-associated HNSCC.

Cornulin as a Potential Novel Biomarker for Cutaneous Squamous Cell Carcinoma

Background This study aimed to evaluate the expression of an epidermal differentiation marker, cornulin, in cutaneous squamous cell carcinoma (cSCC). Cornulin has been found to be downregulated in various squamous cell carcinomas of other tissues; however, its expression in cSCC has never been studied. We predicted that cornulin expression in cSCC is reduced compared to the normal epidermis. Moreover, we hypothesized that an inverse relationship exists between cornulin expression and the loss of differentiation, as defined by histopathological grading of cSCC lesions. Methodology Samples of normal skin and cSCC lesions of variable histopathological grades were stained using immunohistochemistry. High-resolution tissue images were analyzed with Aperio ImageScope (Leica Biosystems) utilizing a positive-pixel-counting algorithm to quantify the staining intensity. Histo-score (H-score) was calculated based on staining intensity and percentage of positive cell staining. Mean H-scores were compared using an unpaired t-test. Results We documented cornulin expression in cSCC for the first time. Cornulin levels were downregulated by more than two-fold in cSCC compared to the normal epidermis. Additionally, we observed a 4.5-fold downregulation in cornulin expression in tumors with high histopathological grades when compared to low histopathological grade tumors. Conclusions Cornulin expression levels measured through immunohistochemistry staining can help distinguish among the different histopathological grades of cSCC. Therefore, we propose that cornulin detection can be an adjunct to pathological examination to evaluate the differentiation status of cSCC specimens. Longitudinal studies are needed to establish the utility of cornulin as a diagnostic and prognostic biomarker for cSCC.

Analysis of exosomal competing endogenous RNA network response to paclitaxel treatment reveals key genes in advanced gastric cancer

Background

Exosome is an important component of the tumor immune microenvironment and plays critical role in cancer pathogenesis. The exosome transcriptome of gastric cancer (GC) response to paclitaxel chemotherapy has not been investigated in the past.

Methods

ceRNA microarrays were performed in exosomes from six advanced GC patients before and after paclitaxel treatment. Bioinformatics tools were used to identify differential expressing genes and construct competing endogenous RNA (ceRNA) networks. The importance of hub genes in the ceRNA network was confirmed by survival analysis and functional analysis.

Results

A total of 213 differential mRNAs, 370 lncRNAs, and 376 circRNAs were identified, and hub genes in ceRNA networks were screened. The differential genes were associated with GO terms SNAP complex, gap junction, protein transporter activity, cytokine receptor, and KEGG pathways synaptic vesicle cycle, propanoate metabolism, Epstein–Barr virus infection, heparin, and steroid biosynthesis, and beta-alanine metabolism. ULK2, CYP2R1, BTLA, and miR-105-5p are prognostic genes for overall survival. Paclitaxel may target ULK2 which is involved in mitosis and cell cycle. miR-105-5p may target ULK2 3’UTR.

Conclusion

The work for the first time identified exosomal RNA biomarkers and constructed a ceRNA network in GC response to paclitaxel, revealed novel molecular mechanisms of GC, and provided new candidates for GC diagnosis and treatment.

Neoplastic cell enrichment of tumor tissues using coring and laser microdissection for proteomic and genomic analyses of pancreatic ductal adenocarcinoma

BACKGROUND

The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses.

METHODS

Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations.

RESULTS

The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity.

CONCLUSIONS

In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Targeting CXCR4 and CD47 Receptors: An Overview of New and Old Molecules for a Biological Personalized Anticancer Therapy

Biological therapy, with its multifaceted applications, has revolutionized the treatment of tumors, mainly due to its ability to exclusively target cancer cells and reduce the adverse effects on normal tissues. This review focuses on the therapies targeting the CXCR4 and CD47 receptors. We surveyed the results of early clinical trials testing compounds classified as nonpeptides, small peptides, CXCR4 antagonists or specific antibodies whose activity reduces or completely blocks the intracellular signaling pathways and cell proliferation. We then examined antibodies and fusion proteins against CD47, the receptor that acts as a “do not eat me” signal to phagocytes escaping immune surveillance. Despite these molecules being tested in early clinical trials, some drawbacks are emerging that impair their use in practice. Finally, we examined the ImmunoGenic Surrender mechanism that involves crosstalk and co-internalization of CXCR4 and CD47 upon engagement of CXCR4 by ligands or other molecules. The favorable effect of such compounds is dual as CD47 surface reduction impact on the immune response adds to the block of CXCR4 proliferative potential. These results suggest that a combination of different therapeutic approaches has more beneficial effects on patients’ survival and may pave the way for new accomplishments in personalized anticancer therapy.

Case Report: Anlotinib combined with PD-1 inhibitor and sequential GA regimen or FOLFIRINOX Chemotherapy in treatment of KRAS G12V mutated pancreatic ductal adenocarcinoma with liver metastasis: A case and literature review

There is a high mortality rate associated with pancreatic cancer, and the incidence has been rising globally in recent decades. When patients are diagnosed, there is little chance that surgery will be beneficial. Systemic chemotherapy is the currently accepted treatment option for patients with metastatic advanced pancreatic cancer. However, a very limited survival improvement is possible with chemotherapy for advanced pancreatic cancer, and chemotherapy resistance plays a significant role in poor prognosis. Despite the fact that targeting growth factor receptor inhibitors such as anti-vascular endothelial growth factor (VEGFR) antibodies significantly improves survival in pancreatic cancer, only a very small number of patients benefit from the treatment. As emerging drugs, immune checkpoint inhibitors (ICIs) have demonstrated significant therapeutic effects in several tumor types, but monotherapy is not effective in pancreatic cancer. In the first-line treatment of solid tumors, combination therapy may result in remarkable outcomes. Here in, we have reported a younger patient with pancreatic ductal adenocarcinoma with liver metastasis (PDACLM) who had a long-term partial response and good tolerance to the combination of anlotinib and programmed cell death protein 1 (PD-1) inhibitor and chemotherapy. Gene analysis suggested only one mutation in the Kirsten rat sarcoma viral oncogene (KRAS) G12V gene. Consequently, there is some hope for patients with pancreatic cancer, especially for KRAS G12V gene mutated patients. Upon reviewing the literature, this patient’s combination therapy is the first to have been reported.

RNA Sequencing Reveals the Regulation Mechanism of Yunnan Baiyao in Treating Skin Infection Caused by Staphylococcus aureus

Yunnan Baiyao is a well-known traditional Chinese medicine that can be formulated into a powder or capsule form. The mechanism by which it exerts its anti-inflammation effect, which is used in skin care products, needs to be further explored. In this study, we established the Staphylococcus aureus-induced mouse skin inflammatory model to investigate the effects of Yunnan Baiyao by the method of RNA-sequencing technology. The mice were randomly assigned to three groups, and those were control, model, and the Yunnan Baiyao-treated (YNtreated) group. Key genes and pathways were identified using bioinformatics analyses. In the study, we obtained 1,053 differentially expressed genes (DEGs) induced by Yunnan Baiyao. The 233 upregulated genes were enriched in 32 GO terms and 5 KEGG pathways, focused on the items, such as wound healing, cell metabolism, and proliferation, indicating the accelerating effects of Yunnan Baiyao on these aspects. The 820 downregulated genes were enriched mainly in the items, including the regulation of inflammation factor production, immune responses, and regulation of structure dermal components. Besides, Yunnan Baiyao reversed the expressions of 277 (201 decreased and 76 increased DEGs, respectively) induced by S. aureus. Ten key regulatory nodes (MMP2, PLK1, CCNB1, TLR4, CDK1, CCNA2, CDC25C, PDGFRA, MYOC, and KNG1) were identified by the construction of the protein interaction network, half of which were related to cell proliferation. VAV1 was another hub node that was affected by Yunnan Baiyao (Top 20). In the study, VAV1 and TLR4 can be considered key module genes in inflammation regulation. In conclusion, this study found that Yunnan Baiyao can significantly relieve inflammatory symptoms by regulating genes and pathways involved in the regulation of inflammation and immune response and also helped to deepen our understanding of the associated molecular mechanisms.

SF3B1 Mutations in Hematological Malignancies

Recently, mutations in the genes involved in the spliceosome have attracted considerable interest in different neoplasms. Among these, SF3B1 mutations have acquired great interest, especially in myelodysplastic syndromes, as they identify a subgroup of patients who can benefit from personalized therapy. The SF3B1 gene encodes the largest subunit of the splicing factor 3b protein complex and is critical for spliceosome assembly and mRNA splicing. The mutated SF3B1 gene encodes for a protein with a different mRNA processing mechanism that results in the aberrant splicing of many mRNAs, which can be downregulated. Although there are many mRNAs affected by a splicing alteration, only a few of these have been directly related to the pathogenesis of several diseases. In this review, we took a snapshot of the current knowledge on the implications of SF3B1 mutations in different hematological malignancies.

Targeting epiregulin in the treatment-damaged tumor microenvironment restrains therapeutic resistance

The tumor microenvironment (TME) represents a milieu enabling cancer cells to develop malignant properties, while concerted interactions between cancer and stromal cells frequently shape an "activated/reprogramed" niche to accelerate pathological progression. Here we report that a soluble factor epiregulin (EREG) is produced by senescent stromal cells, which non-cell-autonomously develop the senescence-associated secretory phenotype (SASP) upon DNA damage. Genotoxicity triggers EREG expression by engaging NF-κB and C/EBP, a process supported by elevated chromatin accessibility and increased histone acetylation. Stromal EREG reprograms the expression profile of recipient neoplastic cells in a paracrine manner, causing upregulation of MARCHF4, a membrane-bound E3 ubiquitin ligase involved in malignant progression, specifically drug resistance. A combinational strategy that empowers EREG-specific targeting in treatment-damaged TME significantly promotes cancer therapeutic efficacy in preclinical trials, achieving response indices superior to those of solely targeting cancer cells. In clinical oncology, EREG is expressed in tumor stroma and handily measurable in circulating blood of cancer patients post-chemotherapy. This study establishes EREG as both a targetable SASP factor and a new noninvasive biomarker of treatment-damaged TME, thus disclosing its substantial value in translational medicine.

High expression of PDIA4 promotes malignant cell behavior and predicts reduced survival in cervical cancer

The protein disulfide isomerase (PDI) gene family plays important roles in the maintenance of several cellular functions. Previous studies have showed that protein disulfide isomerase family A member 4 (PDIA4) is aberrantly expressed in several types of cancer, and correlates with prognosis of patients. However, the role of PDIA4 in cervical cancer remains unclear. In the present study, the expression pattern of PDIA4 from both public database and immunohistochemical analysis in cervical samples was analyzed. Cell Counting Kit-8 and Transwell assays were performed to determine the effect of PDIA4 on cervical cancer cell proliferation and migration. Gene set enrichment analysis (GSEA) was used to provide the associated enriched pathways of PDIA4 in regulating cervical tumorigenesis. It was observed that mRNA expression and protein level of PDIA4 were upregulated in cervical cancer tissues. High expression of PDIA4 was significantly associated with poor overall survival (P=0.0095) and relapse-free survival (P=0.0019) in The Cancer Genome Atlas cohort. Knockdown of PDIA4 inhibited cervical cancer cell proliferation and migration. Moreover, PDIA4 affected the expression of proliferation-related molecules (cyclin D1 and PCNA) and migration-related molecules (E-cadherin and Vimentin). Additionally, GSEA revealed that PDIA4 was significantly associated with gene signatures involving glycan biosynthesis, glycosaminoglycan degradation and protein export. In conclusion, the present findings highlighted the importance of PDIA4 in cervical oncogenesis, and suggested that targeting PDIA4 may be a potential therapeutic application for cervical cancer.

Role of computational and structural biology in the development of small-molecule modulators of the spliceosome

INTRODUCTION

RNA splicing is a pivotal step of eukaryotic gene expression during which the introns are excised from the precursor (pre-)RNA and the exons are joined together to form mature RNA products (i.e a protein-coding mRNA or long non-coding (lnc)RNAs). The spliceosome, a complex ribonucleoprotein machine, performs pre-RNA splicing with extreme precision. Deregulated splicing is linked to cancer, genetic, and neurodegenerative diseases. Hence, the discovery of small-molecules targeting core spliceosome components represents an appealing therapeutic opportunity.

AREA COVERED

Several atomic-level structures of the spliceosome and distinct splicing-modulators bound to its protein/RNA components have been solved. Here, we review recent advances in the discovery of small-molecule splicing-modulators, discuss opportunities and challenges for their therapeutic applicability, and showcase how structural data and/or all-atom simulations can illuminate key facets of their mechanism, thus contributing to future drug-discovery campaigns.

EXPERT OPINION

This review highlights the potential of modulating pre-RNA splicing with small-molecules, and anticipates how the synergy of computer and wet-lab experiments will enrich our understanding of splicing regulation/deregulation mechanisms. This information will aid future structure-based drug-discovery efforts aimed to expand the currently limited portfolio of selective splicing-modulators.

Attenuating effect of magnesium on pulmonary arterial calcification in rodent models of pulmonary hypertension

OBJECTIVE

Vascular calcification has been considered as a potential therapeutic target in pulmonary hypertension. Mg2+ has a protective role against calcification. This study aimed to investigate whether Mg2+ could alleviate pulmonary hypertension by reducing medial calcification of pulmonary arteries.

METHODS

Monocrotaline (MCT)-induced and chronic hypoxia-induced pulmonary hypertension rats were given an oral administration of 10% MgSO4 (10 ml/kg per day). Additionally, we administered Mg2+ in calcified pulmonary artery smooth muscle cells (PASMCs) after incubating with β-glycerophosphate (β-GP, 10 mmol/l).

RESULTS

In vivo, MCT-induced and chronic hypoxia-induced pulmonary hypertension indexes, including right ventricular systolic pressure, right ventricular mass index, and arterial wall thickness, as well as Alizarin Red S (ARS) staining-visualized calcium deposition, high calcium levels, and osteochondrogenic differentiation in pulmonary arteries, were mitigated by dietary Mg2+ intake. In vitro, β-GP-induced calcium-rich deposits stained by ARS, calcium content, as well as the detrimental effects of calcification to proliferation, migration, and resistance to apoptosis of PASMCs were alleviated by high Mg2+ but exacerbated by low Mg2+. Expression levels of mRNA and protein of β-GP-induced osteochondrogenic markers, RUNX Family Transcription Factor 2, and Msh Homeobox 2 were decreased by high Mg2+ but increased by low Mg2+; however, Mg2+ did not affect β-GP-induced expression of SRY-Box Transcription Factor 9. Moreover, mRNA expression and protein levels of β-GP-reduced calcification inhibitor, Matrix GLA protein was increased by high Mg2+ but decreased by low Mg2+.

CONCLUSION

Mg2+ supplement is a powerful strategy to treat pulmonary hypertension by mitigating pulmonary arterial calcification as the calcification triggered physiological and pathological changes to PASMCs.

Drug repositioning for esophageal squamous cell carcinoma

Esophageal cancer (EC) remains a significant challenge globally, having the 8th highest incidence and 6th highest mortality worldwide. Esophageal squamous cell carcinoma (ESCC) is the most common form of EC in Asia. Crucially, more than 90% of EC cases in China are ESCC. The high mortality rate of EC is likely due to the limited number of effective therapeutic options. To increase patient survival, novel therapeutic strategies for EC patients must be devised. Unfortunately, the development of novel drugs also presents its own significant challenges as most novel drugs do not make it to market due to lack of efficacy or safety concerns. A more time and cost-effective strategy is to identify existing drugs, that have already been approved for treatment of other diseases, which can be repurposed to treat EC patients, with drug repositioning. This can be achieved by comparing the gene expression profiles of disease-states with the effect on gene-expression by a given drug. In our analysis, we used previously published microarray data and identified 167 differentially expressed genes (DEGs). Using weighted key driver analysis, 39 key driver genes were then identified. These driver genes were then used in Overlap Analysis and Network Analysis in Pharmomics. By extracting drugs common to both analyses, 24 drugs are predicted to demonstrate therapeutic effect in EC patients. Several of which have already been shown to demonstrate a therapeutic effect in EC, most notably Doxorubicin, which is commonly used to treat EC patients, and Ixazomib, which was recently shown to induce apoptosis and supress growth of EC cell lines. Additionally, our analysis predicts multiple psychiatric drugs, including Venlafaxine, as repositioned drugs. This is in line with recent research which suggests that psychiatric drugs should be investigated for use in gastrointestinal cancers such as EC. Our study shows that a drug repositioning approach is a feasible strategy for identifying novel ESCC therapies and can also improve the understanding of the mechanisms underlying the drug targets.

qPTM: an updated database for PTM dynamics in human, mouse, rat and yeast

Post-translational modifications (PTMs) are critical molecular mechanisms that regulate protein functions temporally and spatially in various organisms. Since most PTMs are dynamically regulated, quantifying PTM events under different states is crucial for understanding biological processes and diseases. With the rapid development of high-throughput proteomics technologies, massive quantitative PTM proteome datasets have been generated. Thus, a comprehensive one-stop data resource for surfing big data will benefit the community. Here, we updated our previous phosphorylation dynamics database qPhos to the qPTM (http://qptm.omicsbio.info). In qPTM, 11 482 553 quantification events among six types of PTMs, including phosphorylation, acetylation, glycosylation, methylation, SUMOylation and ubiquitylation in four different organisms were collected and integrated, and the matched proteome datasets were included if available. The raw mass spectrometry based false discovery rate control and the recurrences of identifications among datasets were integrated into a scoring system to assess the reliability of the PTM sites. Browse and search functions were improved to facilitate users in swiftly and accurately acquiring specific information. The results page was revised with more abundant annotations, and time-course dynamics data were visualized in trend lines. We expected the qPTM database to be a much more powerful and comprehensive data repository for the PTM research community.

SID-4/NCK-1 is important for dsRNA import in Caenorhabditis elegans

RNA interference is sequence-specific gene silencing triggered by double-stranded RNA. Systemic RNA interference is where double-stranded RNA, expressed or introduced into 1 cell, is transported to and initiates RNA interference in other cells. Systemic RNA interference is very efficient in Caenorhabditis elegans and genetic screens for systemic RNA interference-defective mutants have identified RNA transporters (SID-1, SID-2, and SID-5) and a signaling protein (SID-3). Here, we report that SID-4 is nck-1, a C. elegans NCK-like adaptor protein. sid-4 null mutations cause a weak, dose-sensitive, systemic RNA interference defect and can be effectively rescued by SID-4 expression in target tissues only, implying a role in double-stranded RNA import. SID-4 and SID-3 (ACK-1 kinase) homologs interact in mammals and insects, suggesting that they may function in a common signaling pathway; however, a sid-3; sid-4 double mutants showed additive resistance to RNA interference, suggesting that these proteins likely interact with other signaling pathways as well. A bioinformatic screen coupled to RNA interference sensitivity tests identified 23 additional signaling components with weak RNA interference-defective phenotypes. These observations suggest that environmental conditions may modulate systemic RNA interference efficacy, and indeed, sid-3 and sid-4 are required for growth temperature effects on systemic RNA interference silencing efficiency.

Therapeutic Approaches in COVID-19 Patients: The Role of the Renin-Angiotensin System

Two and a half years after COVID-19 was first reported in China, thousands of people are still dying from the disease every day around the world. The condition is forcing physicians to adopt new treatment strategies while emphasizing continuation of vaccination programs. The renin-angiotensin system plays an important role in the development and progression of COVID-19 patients. Nonetheless, administration of recombinant angiotensin-converting enzyme 2 has been proposed for the treatment of the disease. The catalytic activity of cellular ACE2 (cACE2) and soluble ACE2 (sACE2) prevents angiotensin II and Des-Arg-bradykinin from accumulating in the body. On the other hand, SARS-CoV-2 mainly enters cells via cACE2. Thus, inhibition of ACE2 can prevent viral entry and reduce viral replication in host cells. The benefits of bradykinin inhibitors (BKs) have been reported in some COVID-19 clinical trials. Furthermore, the effects of cyclooxygenase (COX) inhibitors on ACE2 cleavage and prevention of viral entry into host cells have been reported in COVID-19 patients. However, the administration of COX inhibitors can reduce innate immune responses and have the opposite effect. A few studies suggest benefits of low-dose radiation therapy (LDR) in treating acute respiratory distress syndrome in COVID-19 patients. Nonetheless, radiation therapy can stimulate inflammatory pathways, resulting in adverse effects on lung injury in these patients. Overall, progress is being made in treating COVID-19 patients, but questions remain about which drugs will work and when. This review summarizes studies on the effects of a recombinant ACE2, BK and COX inhibitor, and LDR in patients with COVID-19.

Phosphoproteomics of extracellular vesicles integrated with multiomics analysis reveals novel kinase networks for lung cancer

Phosphorylation regulates the functions of proteins and aberrant phosphorylation often leads to a variety of diseases, including cancers. Extracellular vesicles (EVs) are important messengers in the microenvironment and their proteome contributes to cancer genesis and metastasis, while the kinases that driving EVs proteins' phosphorylation are less known. Clinical tissue samples from 13 patients with non-small-cell lung cancer (NSCLC) were utilized to isolate cancer EVs and adjacent normal EVs. Through quantitative phosphoproteomics analysis, 2473 phosphorylation sites on 1567 proteins were successfully identified and quantified. Accordingly, 152 kinases were identified, and 25 of them were differentially expressed. Based on Tied Diffusion through Interacting Events (TieDIE) algorithm, we integrated genomic and transcriptomic data sets of NSCLC from TCGA with our phosphoproteome data set to construct signaling networks. Through database integration and multiomics enrichment analysis, a compact network of 234 nodes with 1599 edges was constructed, which consisted of 34 transcription factors, 33 kinases, 63 aberrant genes, and 172 linking proteins. Rarely studied phosphorylation sites were specifically enriched. Key phosphoproteins of network nodes were validated in patients' EVs, including MAPK6^S189 , IKBKE^S172 , SRC^Y530 , CDK7^S164 , and CDK1^T14 . These networks depict intrinsic signal-regulation derived from EVs' phosphoproteins, providing a comprehensive and pathway-based strategy for in-depth lung cancer research.

Exploiting the Molecular Basis of Oesophageal Cancer for Targeted Therapies and Biomarkers for Drug Response: Guiding Clinical Decision-Making

Worldwide, oesophageal cancer is the sixth leading cause of deaths related to cancer and represents a major health concern. Sub-Saharan Africa is one of the regions of the world with the highest incidence and mortality rates for oesophageal cancer and most of the cases of oesophageal cancer in this region are oesophageal squamous cell carcinoma (OSCC). The development and progression of OSCC is characterized by genomic changes which can be utilized as diagnostic or prognostic markers. These include changes in the expression of various genes involved in signaling pathways that regulate pathways that regulate processes that are related to the hallmarks of cancer, changes in the tumor mutational burden, changes in alternate splicing and changes in the expression of non-coding RNAs such as miRNA. These genomic changes give rise to characteristic profiles of altered proteins, transcriptomes, spliceosomes and genomes which can be used in clinical applications to monitor specific disease related parameters. Some of these profiles are characteristic of more aggressive forms of cancer or are indicative of treatment resistance or tumors that will be difficult to treat or require more specialized specific treatments. In Sub-Saharan region of Africa there is a high incidence of viral infections such as HPV and HIV, which are both risk factors for OSCC. The genomic changes that occur due to these infections can serve as diagnostic markers for OSCC related to viral infection. Clinically this is an important distinction as it influences treatment as well as disease progression and treatment monitoring practices. This underlines the importance of the characterization of the molecular landscape of OSCC in order to provide the best treatment, care, diagnosis and screening options for the management of OSCC.

Characterization of Various Honey Samples from Different Regions of Morocco Using Physicochemical Parameters, Minerals Content, Antioxidant Properties, and Honey-Specific Protein Pattern

Honey is a bee product relatively expensive; therefore, it has been a target of adulteration by many sweeteners. In this work, we evaluated the good quality, authenticity, and content in bioactive molecules of twenty-two Moroccan honey from different botanical origins and geographical areas. For that, the following analyses were determined: the content in total protein and especially the major royal jelly protein (apalbumin 1), the analysis of total acidity, free acidity, lactonic acidity, pH, ash, Pfund, electrical conductivity, and moisture. In addition, the content of sodium, potassium, calcium, and magnesium, the dosage of polyphenols, flavones, and flavonols, and the antioxidant activities were assessed. All analyzed samples had good antioxidant activities and present a source of antioxidant compounds, the predominant mineral in all honey samples was potassium, and the physicochemical parameters are in line with the standards’ recommended limits. The content of honey samples in total protein and apalbumin 1 ranged between 212 μg/g and 4121.2 μg/g and between 27.4 μg/g and 790.82 μg/g, respectively. Overall, the detection of apalbumin 1 in all honey samples and the results of physicochemical parameters, minerals, bioactive compounds, and antioxidant activities confirm the authenticity and no adulteration of Moroccan honey.

Protein-protein interaction prediction with deep learning: A comprehensive review

Most proteins perform their biological function by interacting with themselves or other molecules. Thus, one may obtain biological insights into protein functions, disease prevalence, and therapy development by identifying protein-protein interactions (PPI). However, finding the interacting and non-interacting protein pairs through experimental approaches is labour-intensive and time-consuming, owing to the variety of proteins. Hence, protein-protein interaction and protein-ligand binding problems have drawn attention in the fields of bioinformatics and computer-aided drug discovery. Deep learning methods paved the way for scientists to predict the 3-D structure of proteins from genomes, predict the functions and attributes of a protein, and modify and design new proteins to provide desired functions. This review focuses on recent deep learning methods applied to problems including predicting protein functions, protein-protein interaction and their sites, protein-ligand binding, and protein design.

Pharmacologic Targeting of TFIIH Suppresses KRAS-Mutant Pancreatic Ductal Adenocarcinoma and Synergizes with TRAIL

Pancreatic ductal adenocarcinoma (PDAC) typically presents as metastatic disease at diagnosis and remains refractory to treatment. Next-generation sequencing efforts have described the genomic landscape, classified molecular subtypes, and confirmed frequent alterations in major driver genes, with coexistent alterations in KRAS and TP53 correlating with the highest metastatic burden and poorest outcomes. However, translating this information to guide therapy remains a challenge. By integrating genomic analysis with an arrayed RNAi druggable genome screen and drug profiling of a KRAS/TP53 mutant PDAC cell line derived from a patient-derived xenograft (PDCL), we identified numerous targetable vulnerabilities that reveal both known and novel functional aspects of pancreatic cancer biology. A dependence on the general transcription and DNA repair factor TFIIH complex, particularly the XPB subunit and the CAK complex (CDK7/CyclinH/MAT1), was identified and further validated utilizing a panel of genomically subtyped KRAS mutant PDCLs. TFIIH function was inhibited with a covalent inhibitor of CDK7/12/13 (THZ1), a CDK7/CDK9 kinase inhibitor (SNS-032), and a covalent inhibitor of XPB (triptolide), which led to disruption of the protein stability of the RNA polymerase II subunit RPB1. Loss of RPB1 following TFIIH inhibition led to downregulation of key transcriptional effectors of KRAS-mutant signaling and negative regulators of apoptosis, including MCL1, XIAP, and CFLAR, initiating caspase-8 dependent apoptosis. All three drugs exhibited synergy in combination with a multivalent TRAIL, effectively reinforcing mitochondrial-mediated apoptosis. These findings present a novel combination therapy, with direct translational implications for current clinical trials on metastatic pancreatic cancer patients. Significance: This study utilizes functional genetic and pharmacological profiling of KRAS-mutant pancreatic adenocarcinoma to identify therapeutic strategies and finds that TFIIH inhibition synergizes with TRAIL to induce apoptosis in KRAS-driven pancreatic cancer.

Zhuifeng tougu capsules inhibit the TLR4/MyD88/NF-κB signaling pathway and alleviate knee osteoarthritis: In vitro and in vivo experiments

Background: Knee osteoarthritis (KOA), a chronic degenerative disease, is mainly characterized by destruction of articular cartilage and inflammatory reactions. At present, there is a lack of economical and effective clinical treatment. Zhuifeng Tougu (ZFTG) capsules have been clinically approved for treatment of OA as they relieve joint pain and inflammatory manifestations. However, the mechanism of ZFTG in KOA remains unknown.

Purpose: This study aimed to investigate the effect of ZFTG on the TLR4/MyD88/NF-κB signaling pathway and its therapeutic effect on rabbits with KOA.

Study design:In vivo, we established a rabbit KOA model using the modified Videman method. In vitro, we treated chondrocytes with IL-1β to induce a pro-inflammatory phenotype and then intervened with different concentrations of ZFTG. Levels of IL-1β, IL-6, TNF-α, and IFN-γ were assessed with histological observations and ELISA data. The effect of ZFTG on the viability of chondrocytes was detected using a Cell Counting Kit-8 and flow cytometry. The protein and mRNA expressions of TLR2, TLR4, MyD88, and NF-κB were detected using Western blot and RT-qPCR and immunofluorescence observation of NF-κB p65 protein expression, respectively, to investigate the mechanism of ZFTG in inhibiting inflammatory injury of rabbit articular chondrocytes and alleviating cartilage degeneration.

Results: The TLR4/MyD88/NF-κB signaling pathway in rabbits with KOA was inhibited, and the levels of IL-1β, IL-6, TNF-α, and IFN-γ in blood and cell were significantly downregulated, consistent with histological results. Both the protein and mRNA expressions of TLR2, TLR4, MyD88, NF-κB, and NF-κB p65 proteins in that nucleus decreased in the ZFTG groups. Moreover, ZFTG promotes the survival of chondrocytes and inhibits the apoptosis of inflammatory chondrocytes.

Conclusion: ZFTG alleviates the degeneration of rabbit knee joint cartilage, inhibits the apoptosis of inflammatory chondrocytes, and promotes the survival of chondrocytes. The underlying mechanism may be inhibition of the TLR4/MyD88/NF-kB signaling pathway and secretion of inflammatory factors.

Unveiling the m6A Methylation Regulator Links between Prostate Cancer and Periodontitis by Transcriptomic Analysis

Objective

To identify the N6-methyladenosine (m6A) methylation regulator genes linking prostate adenocarcinoma (PRAD) and periodontitis (PD).

Materials and Methods

PD and TCGA-PRAD GEO datasets were downloaded and analyzed through differential expression analysis to determine the differentially expressed genes (DEGs) deregulated in both conditions. Twenty-three m6A RNA methylation-related genes were downloaded in total. The m6A-related genes that overlapped between PRAD and PD were identified as crosstalk genes. Survival analysis was performed on these genes to determine their prognostic values in the overall survival outcomes of prostate cancer. The KEGG pathways were the most significantly enriched by m6A-related crosstalk genes. We also performed lasso regression analysis and univariate survival analysis to identify the most important m6A-related crosstalk genes, and a protein-protein interaction (PPI) network was built from these genes.

Results

Twenty-three m6A methylation-related regulator genes were differentially expressed and deregulated in PRAD and PD. Among these, seven (i.e., ALKBH5, FMR1, IGFBP3, RBM15B, YTHDF1, YTHDF2, and ZC3H13) were identified as m6A-related cross-talk genes. Survival analysis showed that only the FMR1 gene was a prognostic indicator for PRAD. All other genes had no significant influence on the overall survival of patients with PRAD. Lasso regression analysis and univariate survival analysis identified four m6A-related cross-talk genes (i.e., ALKBH5, IGFBP3, RBM15B, and FMR1) that influenced risk levels. A PPI network was constructed from these genes, and 183 genes from this network were significantly enriched in pathogenic Escherichia coli infection, p53 signaling pathway, nucleocytoplasmic transport, and ubiquitin-mediated proteolysis.

Conclusion

Seven m6A methylation-related genes (ALKBH5, FMR1, IGFBP3, RBM15B, YTHDF1, YTHDF2, and ZC3H13) were identified as cross-talk genes between prostate cancer and PD.

Monomerization of Homodimeric Trefoil Factor 3 (TFF3) by an Aminonitrile Compound Inhibits TFF3-Dependent Cancer Cell Survival

Trefoil factor 3 (TFF3) is a secreted protein with an established oncogenic function and a highly significant association with clinical progression of various human malignancies. Herein, a novel small molecule that specifically targets TFF3 homodimeric functions was identified. Utilizing the concept of reversible covalent interaction, 2-amino-4-(4-(6-fluoro-5-methylpyridin-3-yl)phenyl)-5-oxo-4H,5H-pyrano[3,2-c]chromene-3-carbonitrile (AMPC) was identified as a molecule that interacted with TFF3. AMPC monomerized the cellular and secreted TFF3 homodimer at the cysteine (Cys)57-Cys57 residue with subsequent more rapid degradation of the generated TFF3 monomers. Hence, AMPC treatment also resulted in cellular depletion of TFF3 with consequent decreased cell viability in various human carcinoma-derived TFF3 expressing cell lines, including estrogen receptor positive (ER+) mammary carcinoma (MC). AMPC treatment of TFF3 expressing ER+ MC cells significantly suppressed total cell number in a dose-dependent manner. Consistently, exposure of TFF3 expressing ER+ MC cells to AMPC decreased soft agar colony formation, foci formation, and growth in suspension culture and inhibited growth of preformed colonies in 3D Matrigel. AMPC increased apoptosis in TFF3 expressing ER+ MC cells associated with decreased activity of EGFR, p38, STAT3, AKT, and ERK, decreased protein levels of CCND1, CCNE1, BCL2, and BCL-XL, and increased protein levels of TP53, CDKN1A, CASP7, and CASP9. siRNA-mediated depletion of TFF3 expression in ER+ MC cells efficiently abrogated AMPC-stimulated loss of cell viability and CASPASE 3/7 activities. Furthermore, in mice bearing ER+ MC cell-generated xenografts, AMPC treatment significantly impeded xenograft growth. Hence, AMPC exemplifies a novel mechanism by which small molecule drugs may inhibit a dimeric oncogenic protein and provides a strategy to impede TFF3-dependent cancer progression.

Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context

At the heart of the cellular machinery through the regulation of cellular functions, protein-protein interactions (PPIs) have a significant role. PPIs can be analyzed with network approaches. Construction of a PPI network requires prediction of the interactions. All PPIs form a network. Different biases such as lack of data, recurrence of information, and false interactions make the network unstable. Integrated strategies allow solving these different challenges. These approaches have shown encouraging results for the understanding of molecular mechanisms, drug action mechanisms, and identification of target genes. In order to give more importance to an interaction, it is evaluated by different confidence scores. These scores allow the filtration of the network and thus facilitate the representation of the network, essential steps to the identification and understanding of molecular mechanisms. In this review, we will discuss the main computational methods for predicting PPI, including ones confirming an interaction as well as the integration of PPIs into a network, and we will discuss visualization of these complex data.

Multiple similarity drug-target interaction prediction with random walks and matrix factorization

The discovery of drug-target interactions (DTIs) is a very promising area of research with great potential. The accurate identification of reliable interactions among drugs and proteins via computational methods, which typically leverage heterogeneous information retrieved from diverse data sources, can boost the development of effective pharmaceuticals. Although random walk and matrix factorization techniques are widely used in DTI prediction, they have several limitations. Random walk-based embedding generation is usually conducted in an unsupervised manner, while the linear similarity combination in matrix factorization distorts individual insights offered by different views. To tackle these issues, we take a multi-layered network approach to handle diverse drug and target similarities, and propose a novel optimization framework, called Multiple similarity DeepWalk-based Matrix Factorization (MDMF), for DTI prediction. The framework unifies embedding generation and interaction prediction, learning vector representations of drugs and targets that not only retain higher order proximity across all hyper-layers and layer-specific local invariance, but also approximate the interactions with their inner product. Furthermore, we develop an ensemble method (MDMF2A) that integrates two instantiations of the MDMF model, optimizing the area under the precision-recall curve (AUPR) and the area under the receiver operating characteristic curve (AUC), respectively. The empirical study on real-world DTI datasets shows that our method achieves statistically significant improvement over current state-of-the-art approaches in four different settings. Moreover, the validation of highly ranked non-interacting pairs also demonstrates the potential of MDMF2A to discover novel DTIs.

PIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest

Protein kinase-mediated phosphorylation plays a critical role in many biological processes. However, the identification of key regulatory kinases is still a great challenge. Here, we develop a trans-omics-based method, central kinase inference, to predict potentially key kinases by integrating quantitative transcriptomic and phosphoproteomic data. Using known kinases associated with anti-cancer drug resistance, the accuracy of our method denoted by the area under the curve is 5.2% to 29.5% higher than Kinase-Substrate Enrichment Analysis. We further use this method to analyze trans-omic data in hepatocyte maturation and hepatic reprogramming of human dermal fibroblasts, uncovering 5 kinases as regulators in the two processes. Further experiments reveal that a serine/threonine kinase, PIM1, promotes hepatic conversion and protects human dermal fibroblasts from reprogramming-induced ferroptosis and cell cycle arrest. This study not only reveals new regulatory kinases, but also provides a helpful method that might be extended to predict central kinases involved in other biological processes.

MicroRNA-18a regulates the metastatic properties of oral squamous cell carcinoma cells via HIF-1α expression

BACKGROUND

Rapid metastasis of oral squamous cell carcinoma (OSCC) is associated with a poor prognosis and a high mortality rate. However, the molecular mechanisms underlying OSCC metastasis have not been fully elucidated. Although deregulated expression of microRNA (miRNA) has a crucial role in malignant cancer progression, the biological function of miRNA in OSCC progression remains unclear. This study aimed to investigate the function of miRNA-18a in OSCC metastatic regulation via hypoxia-inducible factor 1α (HIF-1α).

METHODS

miRNA-18a-5p (miRNA-18a) expressions in patients with OSCC (n = 39) and in OSCC cell lines (e.g., YD-10B and HSC-2 cells) were analyzed using quantitative real-time polymerase chain reaction. HIF-1α protein expressions in OSCC cells treated with miRNA-18a mimics or combined with cobalt chloride were analyzed using western blotting. The miRNA-18a expression-dependent proliferation and invasion abilities of OSCC cells were analyzed using MTT assay, EdU assay, and a Transwell® insert system.

RESULTS

miRNA-18a expression was significantly lower in OSCC tissue than in the adjacent normal tissue. In OSCC cell lines, HIF-1α expression was significantly decreased by miRNA-18a mimic treatment. Furthermore, the migration and invasion abilities of OSCC cells were significantly decreased by miRNA-18a mimics and significantly increased by the overexpression of HIF-1α under hypoxic conditions relative to those abilities in cells treated only with miRNA-18a mimics.

CONCLUSIONS

miRNA-18a negatively affects HIF-1α expression and inhibits the metastasis of OSCC, thereby suggesting its potential as a therapeutic target for antimetastatic strategies in OSCC.

Microfluidic immuno-serology assay revealed a limited diversity of protection against COVID-19 in patients with altered immunity

The immune response to SARS-CoV-2 for patients with altered immunity such as hematologic malignancies and autoimmune disease may differ substantially from that in general population. These patients remain at high risk despite wide-spread adoption of vaccination. It is critical to examine the differences at the systems level between the general population and the patients with altered immunity in terms of immunologic and serological responses to COVID-19 infection and vaccination. Here, we developed a novel microfluidic chip for high-plex immuno-serological assay to simultaneously measure up to 50 plasma or serum samples for up to 50 soluble markers including 35 plasma proteins, 11 anti-spike/RBD IgG antibodies spanning all major variants, and controls. Our assay demonstrated the quintuplicate test in a single run with high throughput, low sample volume input, high reproducibility and high accuracy. It was applied to the measurement of 1,012 blood samples including in-depth analysis of sera from 127 patients and 21 healthy donors over multiple time points, either with acute COVID infection or vaccination. The protein association matrix analysis revealed distinct immune mediator protein modules that exhibited a reduced degree of diversity in protein-protein cooperation in patients with hematologic malignancies and patients with autoimmune disorders receiving B cell depletion therapy. Serological analysis identified that COVID infected patients with hematologic malignancies display impaired anti-RBD antibody response despite high level of anti-spike IgG, which could be associated with limited clonotype diversity and functional deficiency in B cells and was further confirmed by single-cell BCR and transcriptome sequencing. These findings underscore the importance to individualize immunization strategy for these high-risk patients and provide an informative tool to monitor their responses at the systems level.

Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models

Since the problem proposed in late 2000s, microRNA-disease association (MDA) predictions have been implemented based on the data fusion paradigm. Integrating diverse data sources gains a more comprehensive research perspective, and brings a challenge to algorithm design for generating accurate, concise and consistent representations of the fused data. After more than a decade of research progress, a relatively simple algorithm like the score function or a single computation layer may no longer be sufficient for further improving predictive performance. Advanced model design has become more frequent in recent years, particularly in the form of reasonably combing multiple algorithms, a process known as model fusion. In the current review, we present 29 state-of-the-art models and introduce the taxonomy of computational models for MDA prediction based on model fusion and non-fusion. The new taxonomy exhibits notable changes in the algorithmic architecture of models, compared with that of earlier ones in the 2017 review by Chen et al. Moreover, we discuss the progresses that have been made towards overcoming the obstacles to effective MDA prediction since 2017 and elaborated on how future models can be designed according to a set of new schemas. Lastly, we analysed the strengths and weaknesses of each model category in the proposed taxonomy and proposed future research directions from diverse perspectives for enhancing model performance.

GCHN-DTI: Predicting drug-target interactions by graph convolution on heterogeneous networks

Determining the interaction of drug and target plays a key role in the process of drug development and discovery. The calculation methods can predict new interactions and speed up the process of drug development. In recent studies, the network-based approaches have been proposed to predict drug-target interactions. However, these methods cannot fully utilize the node information from heterogeneous networks. Therefore, we propose a method based on heterogeneous graph convolutional neural network for drug-target interaction prediction, GCHN-DTI (Predicting drug-target interactions by graph convolution on heterogeneous net-works), to predict potential DTIs. GCHN-DTI integrates network information from drug-target interactions, drug-drug interactions, drug-similarities, target-target interactions, and target-similarities. Then, the graph convolution operation is used in the heterogeneous network to obtain the node embedding of the drugs and the targets. Furthermore, we incorporate an attention mechanism between graph convolutional layers to combine node embedding from each layer. Finally, the drug-target interaction score is predicted based on the node embedding of the drugs and the targets. Our model uses fewer network types and achieves higher prediction performance. In addition, the prediction performance of the model will be significantly improved on the dataset with a higher proportion of positive samples. The experimental evaluations show that GCHN-DTI outperforms several state-of-the-art prediction methods.

Regulation of Signaling from the Epidermal Growth Factor Family

The epidermal growth factor (EGF) system has allowed chemists, biologists, and clinicians to improve our understanding of cell production and cancer therapy. The discovery of EGF led to the recognition of cell surface receptors capable of controlling the proliferation and survival of cells. The detailed structures of the EGF-like ligand and the responses of their receptors (EGFR-family) has revealed the conformational and aggregation changes whereby ligands activate the intracellular kinase domains. Biophysical analysis has revealed the preformed clustering of different EGFR-family members and the processes which occur on ligand binding. Understanding these receptor activation processes and the consequential cytoplasmic signaling has allowed the development of inhibitors which are revolutionizing cancer therapy. This Review describes the recent progress in our understanding of the activation of the EGFR-family, the effects of signaling from the EGFR-family on cell proliferation, and the targeting of the EGFR-family in cancer treatment.

Identification of novel early pancreatic cancer biomarkers KIF5B and SFRP2 from “first contact” interactions in the tumor microenvironment

Background

Pancreatic cancer is one of the most difficult cancers to detect early and most patients die from complications arising due to distant organ metastases. The lack of bona fide early biomarkers is one of the primary reasons for late diagnosis of pancreatic cancer. It is a multifactorial disease and warrants a novel approach to identify early biomarkers.

Methods

In order to characterize the proteome, Extracellular vesicles (EVs) isolated from different in vitro conditions mimicking tumor-microenvironment interactions between pancreatic cancer epithelial and stromal cells were analyzed using high throughput mass spectrometry. The biological activity of the secreted EVome was analyzed by investigating changes in distant organ metastases and associated early changes in the microbiome. Candidate biomarkers (KIF5B, SFRP2, LOXL2, and MMP3) were selected and validated on a mouse-human hybrid Tissue Microarray (TMA) that was specifically generated for this study. Additionally, a human TMA was used to analyze the expression of KIF5B and SFRP2 in progressive stages of pancreatic cancer.

Results

The EVome of co-cultured epithelial and stromal cells is different from individual cells with distinct protein compositions. EVs secreted from stromal and cancer cells cultures could not induce significant changes in Pre-Metastatic Niche (PMN) modulation, which was assessed by changes in the distant organ metastases. However, they did induce significant changes in the early microbiome, as indicated by differences in α and β-diversities. KIF5B and SFRP2 show promise for early detection and investigation in progressive pancreatic cancer. These markers are expressed in all stages of pancreatic cancer such as low grade PanINs, advanced cancer, and in liver and soft tissue metastases.

Conclusions

Proteomic characterization of EVs derived from mimicking conditions of epithelial and stromal cells in the tumor-microenvironment resulted in the identification of several proteins, some for the first time in EVs. These secreted EVs cannot induce changes in distant organ metastases in in vivo models of EV education, but modulate changes in the early murine microbiome. Among all the proteins that were analyzed (MMP3, KIF5B, SFRP2, and LOXL2), KIF5B and SFRP2 show promise as bona fide early pancreatic cancer biomarkers expressed in progressive stages of pancreatic cancer.

Pan-Cancer Analysis of PDIA3: Identifying It as a Potential Biomarker for Tumor Prognosis and Immunotherapy

Protein disulfide isomerase A3 (PDIA3) is a kind of thiol oxidoreductase with a wide range of functions, and its expression is elevated in a variety of tumors, which is closely related to the invasion and metastasis of tumor cells, and has a significant impact on the immunogenicity of tumor cells. Although more and more studies have shown that PDIA3 plays an important role in the occurrence and development of many tumors, there is no systematic pan-cancer study on PDIA3. Therefore, in this study, the differential expression of PDIA3 in 33 kinds of tumors was analyzed to explore its ability to regulate tumor immunity as a biomarker and evaluate its role in different cancer onset stages or clinical prognosis. In this paper, by analyzing the multilevel data including 33 kinds of cancers in the databases of Cancer Genome Atlas (TCGA), UCSC Xena, Cancer Cell Encyclopedia (CCLE), Genotypic Tissue Expression (GTEx), Human Protein Atlas (HPA), cBioPortal, and GDC; the differential expression level of PDIA3 in different types of malignant tumors and its relationship with prognosis and the potential correlation between PDIA3 expression and microsatellite instability (MSI), tumor mutation load (TMB), mismatch repair gene (MMR), DNA methylation level, and immune infiltration level were analyzed with bioinformatics. The results showed that PDIA3 was highly expressed in 19 types of cancers, but downregulated only in THCA. Next, PDIA3 in different tumors was positively or negatively correlated with patient outcome, Kaplan-Meier survival analysis showed that PDIA3 plays an important role in the prognosis of patients with KIRP, KICH, and CESC and may be used as a prognostic biomarker, and the methylation level of PDIA3 promoter region was closely related to patient outcome in eight tumors. The expression level of PDIA3 was correlated with TMB in 13 tumors and MSI in 9 tumors. Among them, the expression level of PDIA3 in THYM has the strongest correlation with TMB, and the expression level of PDIA3 in READ has the strongest correlation with MSI. In addition, the expression of PDIA3 in eight kinds of tumors, including BRCA, HNSC, THYM, LGG, LUAD, LUSC, PRAD, and THCA, had the highest correlation with the infiltration degree of immune cells, and the expression of PDIA3 had the highest correlation with the infiltration degree of 11 kinds of immune cells, including regulatory T cell and macrophages. And LGG is the tumor most likely to be affected by the tumor microenvironment to affect its development and prognosis. To sum up, this study suggests that PDIA3 plays an important role in the occurrence and development of KIRP, KICH, and CESC and in the immunotherapeutic response of THYM, READ, and LGG and can be used as a prognostic biomarker for these tumors.

Therapeutic and anti-inflammatory effects of baricitinib on mortality, ICU transfer, clinical improvement, and CRS-related laboratory parameters of hospitalized patients with moderate to severe COVID-19 pneumonia: a systematic review and meta-analysis

BACKGROUND

Due to the high incidence and mortality of the worldwide COVID-19 pandemic, beneficial effects of effective antiviral and anti-inflammatory drugs used in other diseases, especially rheumatic diseases, were observed in the treatment of COVID-19.

METHODS

Clinical and laboratory parameters of eight included cohort studies and five Randomized Control Trials between the baricitinib group and the control group were analyzed on the first day of admission and days 7, 14, and 28 during hospitalization.

RESULTS

According to the meta-analysis result of eight included cohort studies with 2088 patients, the Pooled Risk Ratios were 0.46 (P<0.001) for mortality, 6.14 (P< 0.001) for hospital discharge, and the mean differences of 76.78 (P< 0.001) for PaO₂/FiO₂ ratio was -47.32 (P= 0.02) for CRP, in the baricitinib group vs. control group on the seventh or fourteenth day of the treatment compared to the first day. Based on the meta-analysis of five RCT studies with 11825 patients, the pooled RR was 0.84 (P= 0.001) for mortality and 1.07 (P= 0.014) for patients' recovery. The mean differences were -0.80 (P<0.001) for hospitalization days, -0.51(P= 0.33) for time to recovery in the baricitinib group vs. control group.

CONCLUSIONS

Baricitinib prescription is strongly recommended in moderate to severe COVID-19.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number: CRD42021254541.