Identification of TLN1 as a prognostic biomarker to effect cell proliferation and differentiation in acute myeloid leukemia

Genome-wide screening and validation of exosome-derived TLN1 as a regulator of epithelial-mesenchymal transition in lung cancer

In addition to embryonic development, wound healing, and tissue fibrosis, epithelial-mesenchymal transition (EMT) is another process that enhances tumor invasiveness and metastatic activity. Exosomes transport a variety of bioactive components between cells and are crucial for cell‒cell communication in multiple complex biological processes, including cancer. Although a few studies have shown that exosomes encapsulate microRNAs that induce a pro-EMT tumor microenvironment, a systematic survey of potential EMT-related regulators in lung cancer exosomes is still lacking. To identify exosome-related EMT signals that could be employed for precise cancer diagnosis, we used a computational approach to generate a list of candidates EMT regulators and performed experimental validation in lung cancer cell lines. Particularly, we focused on exosome-derived differentially expressed genes that were not previously reported to be associated with lung cancer. We identified 25 exosome-derived protein coding regulators associated with EMT with aberrant transcript expression in both lung squamous cell carcinoma and lung adenocarcinoma. By focusing on clinical features such as survival time, smoking status, tumor purity, and primary tumor subtypes, we found that these 25 genes are important for lung cancer development based on a combined cohort of 9781 lung cancer samples from 24 independent genomics studies. By validating two examples of upregulated and downregulated exosome-derived regulators, we confirmed that TLN1 is a potential oncogene in lung cancer progression, which suggests that it may serve as a diagnostic marker. In summary, our results provide a potential exosome-based biomarker for cancer diagnosis that could be used as a therapeutic tool to control the occurrence of EMT and affect cancer progression.

A Novel Disulfidptosis-Related Risk Signature for Prognostic Prediction in Patients With Ewing Sarcoma

Ewing sarcoma (ES) is a malignant bone tumor prevalent among children and adolescents. Disulfidptosis represents a novel form of cell death; however, the mechanism of disulfidptosis in ES remains unclear. Our aim is to explore the disulfidptosis-related prognostic signature in ES. Utilizing transcriptomic and clinical data of ES, disulfidptosis-related hub genes (DRHGs) were identified by differential gene expression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. A disulfidptosis-related risk score model (DRRS) was constructed based on these DRHGs. The performance of DRRS was assessed using survival analysis and receiver operating characteristic curve analysis. Immune cell infiltration in different risk subgroups and correlations between DRRS and antitumor reagents were also analyzed. In this study, we developed a disulfidptosis-related prognostic feature based on LRPPRC (leucine rich pentatricopeptide repeat containing), IQGAP1 (IQ motif containing GTPase activating protein 1), NDUFS1 (NADH:ubiquinone oxidoreductase core subunit S1), and TLN1 (talin 1), which may serve as a predictive and independent risk factor for ES. ES patients in the high-risk group exhibited a poorer prognosis, had a higher proportion of myeloid-derived suppressor cells (MDSCs) and M2 type of tumor-associated macrophages, and showed heightened sensitivity to some antitumor agents such as nilotinib and olaparib. This study is the first to construct a disulfidptosis-related prognostic signature that may predict the prognosis and immune response in ES patients, thereby providing a new reference for understanding the mechanisms of ES and guiding immunotherapy.

Identification of molecular and cellular infection response biomarkers associated with anthrax infection through comparative analysis of gene expression data

Bacillus anthracis, a gram-positive bacillus capable of forming spores, causes anthrax in mammals, including humans, and is recognized as a potential biological weapon agent. The diagnosis of anthrax is challenging due to variable symptoms resulting from exposure and infection severity. Despite the availability of a licensed vaccines, their limited long-term efficacy underscores the inadequacy of current human anthrax vaccines, highlighting the urgent need for next-generation alternatives. Our study aimed to identify molecular biomarkers and essential biological pathways for the early detection and accurate diagnosis of human anthrax infection. Using a comparative analysis of Bacillus anthracis gene expression data from the Gene Expression Omnibus (GEO) database, this cost-effective approach enables the identification of shared differentially expressed genes (DEGs) across separate microarray datasets without additional hybridization. Three microarray datasets (GSE34407, GSE14390, and GSE12131) of B. anthracis-infected human cell lines were analyzed via the GEO2R tool to identify shared DEGs. We identified 241 common DEGs (70 upregulated and 171 downregulated) from cell lines treated similarly to lethal toxins. Additionally, 10 common DEGs (5 upregulated and 5 downregulated) were identified across different treatments (lethal toxins and spores) and cell lines. Network meta-analysis identified JUN and GATAD2A as the top hub genes for overexpression, and NEDD4L and GULP1 for underexpression. Furthermore, prognostic analysis and SNP detection of the two identified upregulated hub genes were carried out in conjunction with machine learning classification models, with SVM yielding the best classification accuracy of 87.5 %. Our comparative analysis of Bacillus anthracis infection revealed striking similarities in gene expression 241 profiles across diverse datasets, despite variations in treatments and cell lines. These findings underscore how anthrax infection activates shared genes across different cell types, emphasizing this approach in the discovery of novel gene markers. These markers offer insights into pathogenesis and may lead to more effective therapeutic strategies. By identifying these genetic indicators, we can advance the development of precise immunotherapies, potentially enhancing vaccine efficacy and treatment outcomes.

Higher Expression of Talin-1 is Associated With Less Aggressive Tumor Behavior in Pancreatic Cancer

Talin-1 is one of the major scaffold proteins in focal adhesions playing a vital role in cell migration, metastasis, and cancer progression. Although studies regarding the importance of Talin-1 in cancer have rapidly developed, its prognostic and diagnostic value still remain unsatisfying in pancreatic cancer (PC). Therefore, the present study aims to investigate the expression, clinical significance, as well as the prognostic and diagnostic value of Talin-1 in different types of PC. Bioinformatic analysis was applied to determine the clinical importance and biological role of Talin-1 expression in PC tumors and the normal adjacent samples. The expression patterns, clinical significance, prognosis, and diagnosis value of Talin-1 were evaluated in tissue microarrays (TMAs) of 190 PC samples including 170 pancreatic ductal adenocarcinoma (PDAC), and 20 pancreatic neuroendocrine tumors (PNET), along with 24 adjacent normal tissues using immunohistochemistry (IHC). The results indicated that the expression of Talin-1 was upregulated in tumor cells compared with adjacent normal tissues. A statistically significant association was observed between the higher cytoplasmic expression of Talin-1 and lower histologic grade ( P <0.001) in PDAC samples. Further, our findings indicated an inverse significant correlation between cytoplasmic expression of Talin-1 and recurrence ( P =0.014) in PNET samples. No significant association was observed between the cytoplasmic expression of Talin-1 and survival outcomes as well as diagnostic accuracy. In conclusion, our observations demonstrated that a higher cytoplasmic level of Talin-1 protein was significantly associated with less aggressive tumor behaviors in PC samples. Nevertheless, further investigations are required to explore the prognostic plus diagnostic value, and mechanism of action of Talin-1 in pancreatic cancer.

CREB1 promotes cholangiocarcinoma metastasis through transcriptional regulation of the LAYN-mediated TLN1/β1 integrin axis: CREB1 promotes cholangiocarcinoma metastasis through regulating LAYN/TLN1/β1 integrin axis

Background

Layilin (LAYN) plays an important role in tumor progression, invasion, and metastasis; however, its role in cholangiocarcinoma (CHOL) has not been elucidated.

Methods

We utilized the GEPIA, STRING, and hTFtarget databases for bioinformatics analysis. Overexpression or knockdown cell lines were constructed by transfecting the cells with different plasmids. Western blot (WB) was performed to detect LAYN, TLN1, and CREB1 expression. Cell proliferation, migration, and invasiveness were assessed using CCK-8 and Transwell assays. Immunofluorescence and WB were used to detect epithelial-mesenchymal transition (EMT) markers. The CHOL metastasis model was established by injecting RBE cells into the tail veins of nude mice. Metastatic lesions were identified using hematoxylin and eosin staining. Co-immunoprecipitation and Chromatin immunoprecipitation were used to validate the interactions.

Results

LAYN was highly expressed in the CHOL cells. Knockdown of LAYN significantly inhibited proliferation, migration, invasion, and EMT in both QBC-939 and RBE human CHOL cells, while overexpression of LAYN had the opposite effect. Furthermore, in a CHOL metastasis model using nude mice, knocking down LAYN expression markedly suppressed CHOL liver and lung metastases. LAYN interacts with TLN1, and CREB1 binds to the LAYN promoter, with all three showing a positive correlation. Additionally, bioinformatics analysis revealed high expression of both TLN1 and CREB1 in CHOL. Knockdown of TLN1 or CREB1 in QBC-939 and RBE cells inhibited cell proliferation, migration, invasion, and EMT, reversing the effects of LAYN overexpression. Moreover, knockdown of TLN1 or CREB1 also suppressed the expression of ITGB1 and the phosphorylation levels of c-Jun, p38 MAPK, and ERK, further reversing the effects of LAYN overexpression.

Conclusion

Our results suggest that CREB1 promotes CHOL metastasis through transcriptional regulation of the LAYN-mediated TLN1/β1 integrin axis.

Exploring the nexus between MYH9 and tumors: novel insights and new therapeutic opportunities

The myosin heavy chain 9 (MYH9) gene, located on human chromosome 22, encodes non-muscle myosin heavy chain IIA (NM IIA). This protein is essential to various cellular events, such as generating intracellular chemomechanical force and facilitating the movement of the actin cytoskeleton. Mutations associated with thrombocytopenia in autosomal dominant diseases first highlighted the significance of the MYH9 gene. In recent years, numerous studies have demonstrated the pivotal roles of MYH9 in various cancers. However, its effects on cancer are intricate and not fully comprehended. Furthermore, the elevated expression of MYH9 in certain malignancies suggests its potential as a target for tumor therapy. Nonetheless, there is a paucity of literature summarizing MYH9's role in tumors and the therapeutic strategies centered on it, necessitating a systematic analysis. This paper comprehensively reviews and analyzes the pertinent literature in this domain, elucidating the fundamental structural characteristics, biological functions, and the nexus between MYH9 and tumors. The mechanisms through which MYH9 contributes to tumor development and its multifaceted roles in the tumorigenic process are also explored. Additionally, we discuss the relationship between MYH9-related diseases (MYH9-RD) and tumors and also summarize tumor therapeutic approaches targeting MYH9. The potential clinical applications of studying the MYH9 gene include improving early diagnosis, clinical staging, and prognosis of tumors. This paper is anticipated to provide novel insights for tumor therapy.

Novel Strategy for Screening Target Proteins by the Common Drugs─Sofosbuvir-Specific Profiling of HCV Patient Serum

It is the scientific basis of precision medicine to study all of the targets of drugs based on the interaction between drugs and proteins. It is worth paying attention to unknown proteins that interact with drugs to find new targets for the design of new drugs. Herein, we developed a protein profiling strategy based on drug-protein interactions and drug-modified magnetic nanoparticles and took hepatitis C virus (HCV) and its corresponding drug sofosbuvir (SOF) as an example. A SOF-modified magnetic separation medium (Fe3O4@POSS@SOF) was prepared, and a gradient elution strategy was employed and optimized to profile specific proteins interacted with SOF. A series of proteomic analyses were performed to profile proteins based on SOF-protein interactions (SPIs) in the serum of HCV patients to evaluate the specificity of the profiling strategy. As a result, five proteins were profiled with strong SPIs and exhibited high relevance with liver tissue, which were potentially new drug targets. Among them, HSP60 was used to confirm the highly specific interactions between the SOF and its binding proteins by Western blotting analysis. Besides, 124 and 29 differential proteins were profiled by SOF material from three HCV patient serum and pooled 20 HCV patient serum, respectively, by comparing with healthy human serum. In comparison with those profiled by the polyhedral oligomeric silsesquioxane (POSS) material, differential proteins profiled by the SOF material were highly associated with liver diseases through GO analysis and pathway analysis. Furthermore, four common differential proteins profiled by SOF material but not by POSS material were found to be identical and expressed consistently in both pooled serum samples and independent serum samples, which might potentially be biomarkers of HCV infection. Taken together, our study proposes a highly specific protein profiling strategy to display distinctive proteomic profiles, providing a novel idea for drug design and development.

The Deep Proteomics Approach Identified Extracellular Vesicular Proteins Correlated to Extracellular Matrix in Type One and Two Endometrial Cancer

Among gynecological cancers, endometrial cancer is the most common in developed countries. Extracellular vesicles (EVs) are cell-derived membrane-surrounded vesicles that contain proteins involved in immune response and apoptosis. A deep proteomic approach can help to identify dysregulated extracellular matrix (ECM) proteins in EVs correlated to key pathways for tumor development. In this study, we used a proteomics approach correlating the two acquisitions-data-dependent acquisition (DDA) and data-independent acquisition (DIA)-on EVs from the conditioned medium of four cell lines identifying 428 ECM proteins. After protein quantification and statistical analysis, we found significant changes in the abundance (p < 0.05) of 67 proteins. Our bioinformatic analysis identified 26 pathways associated with the ECM. Western blotting analysis on 13 patients with type 1 and type 2 EC and 13 endometrial samples confirmed an altered abundance of MMP2. Our proteomics analysis identified the dysregulated ECM proteins involved in cancer growth. Our data can open the path to other studies for understanding the interaction among cancer cells and the rearrangement of the ECM.

Identification of hub genes and potential molecular mechanisms related to drug sensitivity in acute myeloid leukemia based on machine learning

Background: Acute myeloid leukemia (AML) is the most common form of leukemia among adults and is characterized by uncontrolled proliferation and clonal expansion of hematopoietic cells. There has been a significant improvement in the treatment of younger patients, however, prognosis in the elderly AML patients remains poor. Methods: We used computational methods and machine learning (ML) techniques to identify and explore the differential high-risk genes (DHRGs) in AML. The DHRGs were explored through multiple in silico approaches including genomic and functional analysis, survival analysis, immune infiltration, miRNA co-expression and stemness features analyses to reveal their prognostic importance in AML. Furthermore, using different ML algorithms, prognostic models were constructed and validated using the DHRGs. At the end molecular docking studies were performed to identify potential drug candidates targeting the selected DHRGs. Results: We identified a total of 80 DHRGs by comparing the differentially expressed genes derived between AML patients and normal controls and high-risk AML genes identified by Cox regression. Genetic and epigenetic alteration analyses of the DHRGs revealed a significant association of their copy number variations and methylation status with overall survival (OS) of AML patients. Out of the 137 models constructed using different ML algorithms, the combination of Ridge and plsRcox maintained the highest mean C-index and was used to build the final model. When AML patients were classified into low- and high-risk groups based on DHRGs, the low-risk group had significantly longer OS in the AML training and validation cohorts. Furthermore, immune infiltration, miRNA coexpression, stemness feature and hallmark pathway analyses revealed significant differences in the prognosis of the low- and high-risk AML groups. Drug sensitivity and molecular docking studies revealed top 5 drugs, including carboplatin and austocystin-D that may significantly affect the DHRGs in AML. Conclusion: The findings from the current study identified a set of high-risk genes that may be used as prognostic and therapeutic markers for AML patients. In addition, significant use of the ML algorithms in constructing and validating the prognostic models in AML was demonstrated. Although our study used extensive bioinformatics and machine learning methods to identify the hub genes in AML, their experimental validations using knock-out/-in methods would strengthen our findings.

High expression of TBRG4 in relation to unfavorable outcome and cell ferroptosis in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of malignant liver tumor with poor prognosis. In this study, we investigated the expression of transforming growth factor beta regulator 4 (TBRG4) in HCC and its effects on the proliferation, invasion, and metastasis of HCC cells, and analyzed the possible molecular mechanisms.

METHOD

Downloading the expression and clinical information of HCC samples in the TCGA database, analyzing the expression differences of TBRG4 by bioinformatics methods, analyzing the clinical relevance and prognostic significance. Performing GO, KEGG and GSEA enrichment analysis on the TBRG4-related gene set in patient HCC tissues. Applying cell counting, scratch test and Transwell experiment to study the biological function of TBRG4 in HCC. Mitochondrial membrane potential, apoptosis and ROS levels were evaluated to assess cell iron death. Western blot, RT-PCR, laser confocal microscopy and co-immunoprecipitation were used to detect and analyze the downstream signaling pathways and interacting molecules of TBRG4.

RESULTS

Bioinformatics analysis revealed that TBRG4 was abnormally highly expressed in HCC tumor tissues and was associated with poor prognosis and metastasis in HCC patients. GO and KEGG functional enrichment analysis showed that TBRG4 was related to oxidative stress and NADH dehydrogenase (ubiquinone) activity. GSEA enrichment analysis showed that TBRG4 was associated with Beta catenin independent wnt signaling and B cell receptor. Functional experiments confirmed that knocking down TBRG4 could inhibit the proliferation, migration, and invasion of HCC cells. Mechanistically, TBRG4 inhibited the function of HCC cells through the DDX56/p-AKT/GSK3β signaling pathway. In addition, interference with TBRG4 expression could reduce the mitochondrial membrane potential and accumulate ROS in HCC cells, leading to increased ferroptosis. Co-IP analysis showed that TBRG4 specifically bound to Beclin1.

CONCLUSION

TBRG4 is highly expressed in HCC tumor tissues and is associated with poor prognosis. It may regulate the proliferation, invasion, and metastasis of HCC cells through the DDX56/p-AKT/GSK3β signaling pathway. TBRG4 may interact with Beclin1 to regulate the ferroptosis of HCC cells.

Combination of bulk RNA sequencing and scRNA sequencing uncover the molecular characteristics of MAPK signaling in kidney renal clear cell carcinoma

The MAPK signaling pathway significantly impacts cancer progression and resistance; however, its functions remain incompletely assessed across various cancers, particularly in kidney renal clear cell carcinoma (KIRC). Therefore, there is an urgent need for comprehensive pan-cancer investigations of MAPK signaling, particularly within the context of KIRC. In this research, we obtained TCGA pan-cancer multi-omics data and conducted a comprehensive analysis of the genomic and transcriptomic characteristics of the MAPK signaling pathway. For in-depth investigation in KIRC, status of MAPK pathway was quantitatively estimated by ssGSEA and Ward algorithm was utilized for cluster analysis. Molecular characteristics and clinical prognoses of KIRC patients with distinct MAPK activities were comprehensively explored using a series of bioinformatics algorithms. Subsequently, a combination of LASSO and COX regression analyses were utilized sequentially to construct a MAPK-related signature to help identify the risk level of each sample. Patients in the C1 subtype exhibited relatively higher levels of MAPK signaling activity, which were associated with abundant immune cell infiltration and favorable clinical outcomes. Single-cell RNA sequencing (scRNA-seq) analysis of KIRC samples identified seven distinct cell types, and endothelial cells in tumor tissues had obviously higher MAPK scores than normal tissues. The immunohistochemistry results indicated the reduced expression levels of PAPSS1, MAP3K11, and SPRED1 in KIRC samples. In conclusion, our study represents the first integration of bulk RNA sequencing and single-cell RNA sequencing to elucidate the molecular characteristics of MAPK signaling in KIRC, providing a solid foundation for precision oncology.

Talin mechanotransduction in disease

Talin protein (Talin 1/2) is a mechanosensitive cytoskeleton protein. The unique structure of the Talin plays a vital role in transmitting mechanical forces. Talin proteins connect the extracellular matrix to the cytoskeleton by linking to integrins and actin, thereby mediating the conversion of mechanical signals into biochemical signals and influencing disease progression as potential diagnostic indicators, therapeutic targets, and prognostic indicators of various diseases. Most studies in recent years have confirmed that mechanical forces also have a crucial role in the development of disease, and Talin has been found to play a role in several diseases. Still, more studies need to be done on how Talin is involved in mechanical signaling in disease. This review focuses on the mechanical signaling of Talin in disease, aiming to summarize the mechanisms by which Talin plays a role in disease and to provide references for further studies.

Phenotypic and functional characterization of subpopulation of Imatinib resistant chronic myeloid leukemia cell line

PURPOSE

Chronic myeloid leukemia (CML) is a hematological malignancy characterized by the presence of BCR-ABL protein. Imatinib (IMA) is considered as the first line therapy in management of CML which particularly targets the BCR-ABL tyrosine kinase protein. However, emergence of resistance to IMA hinders its clinical efficiency. Hence, identifying novel targets for therapeutic approaches in CML treatment is of great importance. Here, we characterize a new subpopulation of highly adherent IMA-resistant CML cells that express stemness and adhesion markers compared to naive counterparts.

MATERIALS AND METHODS

We performed several experimental assays including FISH, flow cytometry, and gene expression assays. Additionally, bioinformatics analysis was performed by normalized web-available microarray data (GSE120932) to revalidate and introduce probable biomarkers. Protein-protein interactions (PPI) network was analyzed by the STRING database employing Cytoscape v3.8.2.

RESULTS

Our findings demonstrated that constant exposure to 5 ​μM IMA led to development of the adherent phenotype (K562R-adh). FISH and BCR-ABL expression analysis indicated that K562R-adh cells were derived from the original cells (K562R). In order to determine the role of various genes involved in epithelial-mesenchymal transition (EMT) and stem cell characterization, up/down-regulation of various genes including cancer stem cell (CSC), adhesion and cell surface markers and integrins were observed which was similar to the findings of the GSE120932 dataset.

CONCLUSION

Treating CML patients with tyrosine kinase inhibitors (TKIs) as well as targeting adhesion molecules deemed to be effective approaches in prevention of IMA resistance emergence which in turn may provide promising effects in the clinical management of CML patients.