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Advanced Science (Weinheim,... Jun 2024Organoid tumor models have emerged as a powerful tool in the fields of biology and medicine as such 3D structures grown from tumor cells recapitulate better tumor...
Organoid tumor models have emerged as a powerful tool in the fields of biology and medicine as such 3D structures grown from tumor cells recapitulate better tumor characteristics, making these tumoroids unique for personalized cancer research. Assessment of their functional behavior, particularly protein secretion, is of significant importance to provide comprehensive insights. Here, a label-free spectroscopic imaging platform is presented with advanced integrated optofluidic nanoplasmonic biosensor that enables real-time secretion analysis from single tumoroids. A novel two-layer microwell design isolates tumoroids, preventing signal interference, and the microarray configuration allows concurrent analysis of multiple tumoroids. The dual imaging capability combining time-lapse plasmonic spectroscopy and bright-field microscopy facilitates simultaneous observation of secretion dynamics, motility, and morphology. The integrated biosensor is demonstrated with colorectal tumoroids derived from both cell lines and patient samples to investigate their vascular endothelial growth factor A (VEGF-A) secretion, growth, and movement under various conditions, including normoxia, hypoxia, and drug treatment. This platform, by offering a label-free approach with nanophotonics to monitor tumoroids, can pave the way for new applications in fundamental biological studies, drug screening, and the development of therapies.
PubMed: 38924371
DOI: 10.1002/advs.202401539 -
Journal of Cellular and Molecular... Jun 2024Despite remarkable advancements in the treatment of multiple myeloma (MM), relapse remains a challenge. However, the mechanisms underlying this disease remain unclear....
Despite remarkable advancements in the treatment of multiple myeloma (MM), relapse remains a challenge. However, the mechanisms underlying this disease remain unclear. This study aimed to identify potential biomarkers that could open new avenues for MM treatment. Microarray data and clinical characteristics of patients with MM were obtained from the Gene Expression Omnibus database. Differential expression analysis and protein-protein interaction (PPI) network construction were used to identify hub genes associated with MM. Predictive performance was further assessed using receiver operating characteristic curves and nomogram construction. Functional enrichment analysis was conducted to investigate possible mechanisms. Mendelian randomization (MR) was used to evaluate the causal relationship between the crucial gene and MM risk. Topological analysis of the PPI network revealed five hub genes associated with MM, with myeloperoxidase (MPO) being the key gene owing to its highest degree and area under the curve values. MPO showed significant differences between patients with MM and controls across all datasets. Functional enrichment analysis revealed a strong association between MPO and immune-related pathways in MM. MR analysis confirmed a causal relationship between MPO and the risk of MM. By integrating microarray analysis and MR, we successfully identified and validated MPO as a promising biomarker for MM that is potentially implicated in MM pathogenesis and progression through immune-related pathways.
Topics: Multiple Myeloma; Humans; Mendelian Randomization Analysis; Protein Interaction Maps; Biomarkers, Tumor; Peroxidase; Gene Expression Regulation, Neoplastic; Gene Expression Profiling; Gene Regulatory Networks; ROC Curve; Microarray Analysis; Nomograms
PubMed: 38923838
DOI: 10.1111/jcmm.18504 -
Molecular Oncology Jun 2024Endometrioid ovarian cancers (EOvC) are usually managed as serous tumors. In this study, we conducted a comprehensive molecular investigation to uncover the distinct...
Endometrioid ovarian cancers (EOvC) are usually managed as serous tumors. In this study, we conducted a comprehensive molecular investigation to uncover the distinct biological characteristics of EOvC. This retrospective multicenter study involved patients from three European centers. We collected clinical data and formalin-fixed paraffin-embedded (FFPE) samples for analysis at the DNA level using panel-based next-generation sequencing and array-comparative genomic hybridization. Additionally, we examined mRNA expression using NanoString nCounter® and protein expression through tissue microarray. We compared EOvC with other ovarian subtypes and uterine endometrioid tumors. Furthermore, we assessed the impact of molecular alterations on patient outcomes, including progression-free survival (PFS) and overall survival (OS). Preliminary analysis of clinical data from 668 patients, including 86 (12.9%) EOvC, revealed more favorable prognosis for EOvC compared with serous ovarian carcinoma (5-year OS of 60% versus 45%; P = 0.001) driven by diagnosis at an earlier stage. Immunohistochemistry and copy number alteration (CNA) profiles of 43 cases with clinical data and FFPE samples available indicated that EOvC protein expression and CNA profiles were more similar to endometrioid endometrial tumors than to serous ovarian carcinomas. EOvC exhibited specific alterations, such as lower rates of PTEN loss, mutations in DNA repair genes, and P53 abnormalities. Survival analysis showed that patients with tumors harboring loss of PTEN expression had worse outcomes (median PFS 19.6 months vs. not reached; P = 0.034). Gene expression profile analysis confirmed that EOvC differed from serous tumors. However, comparison to other rare subtypes of ovarian cancer suggested that the EOvC transcriptomic profile was close to that of ovarian clear cell carcinoma. Downregulation of genes involved in the PI3K pathway and DNA methylation was observed in EOvC. In conclusion, EOvC represents a distinct biological entity and should be regarded as such in the development of specific clinical approaches.
PubMed: 38923749
DOI: 10.1002/1878-0261.13679 -
Cancer Medicine Jun 2024A neurotrophic tropomyosin receptor kinase (NTRK)-tyrosine kinase inhibitor (TKI) has shown dramatic efficacy against malignant tumors harboring an NTRK fusion gene....
INTRODUCTION
A neurotrophic tropomyosin receptor kinase (NTRK)-tyrosine kinase inhibitor (TKI) has shown dramatic efficacy against malignant tumors harboring an NTRK fusion gene. However, almost all tumors eventually acquire resistance to NTRK-TKIs.
METHOD
To investigate the mechanism of resistance to NTRK-TKIs, we established cells resistant to three types of NTRK-TKIs (larotrectinib, entrectinib, and selitrectinib) using KM12 colon cancer cells with a TPM3-NTRK1 rearrangement.
RESULT
Overexpression of 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) was observed in three resistant cells (KM12-LR, KM12-ER, and KM12-SR) by microarray analysis. Lower expression of sterol regulatory element-binding protein 2 (SREBP2) and peroxisome proliferator activated receptor α (PPARα) was found in two cells (KM12-ER and KM12-SR) in which HMGCS2 was overexpressed compared to the parental KM12 and KM12-LR cells. In resistant cells, knockdown of HMGCS2 using small interfering RNA improved the sensitivity to NTRK-TKI. Further treatment with mevalonolactone after HMGCS2 knockdown reintroduced the NTRK-TKI resistance. In addition, simvastatin and silibinin had a synergistic effect with NTRK-TKIs in resistant cells, and delayed tolerance was observed after sustained exposure to clinical concentrations of NTRK-TKI and simvastatin in KM12 cells. In xenograft mouse models, combination treatment with entrectinib and simvastatin reduced resistant tumor growth compared with entrectinib alone.
CONCLUSION
These results suggest that HMGCS2 overexpression induces resistance to NTRK-TKIs via the mevalonate pathway in colon cancer cells. Statin inhibition of the mevalonate pathway may be useful for overcoming this mechanistic resistance.
Topics: Humans; Animals; Drug Resistance, Neoplasm; Mice; Cell Line, Tumor; Protein Kinase Inhibitors; Mevalonic Acid; Xenograft Model Antitumor Assays; Colonic Neoplasms; Receptor, trkA; Hydroxymethylglutaryl-CoA Synthase; Benzamides; Pyrimidines; Pyrazoles; Indazoles
PubMed: 38923428
DOI: 10.1002/cam4.7393 -
Oral Diseases Jun 2024Porphyromonas gingivalis-LPS regulated bone metabolism by triggering dysfunction of osteoblasts directly, and affecting activity of osteoclasts through intracellular...
OBJECTIVES
Porphyromonas gingivalis-LPS regulated bone metabolism by triggering dysfunction of osteoblasts directly, and affecting activity of osteoclasts through intracellular communication. Exosome, as the mediator of intercellular communication, was important vesicle to regulate osteogenesis and osteoclastogenesis. This research was designed for investigating the mechanism of BMSCs-EXO in modulating osteoclastic activity under the P. gingivalis-LPS.
MATERIALS AND METHODS
The cytotoxicity and osteogenic effects of P. gingivalis-LPS on BMSCs was evaluated, and then osteoclastic activity of RAW264.7 co-cultured with exosomes was detected. Besides, Affymetrix miRNA array and luciferase reporter assay were used to identify the target exosomal miRNA signal pathway.
RESULTS
BMSCs' osteogenic differentiation and proliferation were decreased under 1 and 10 μg/mL P. gingivalis-LPS. Osteoclastic-related genes and proteins levels were promoted by P. gingivalis-LPS-stimulated BMSCs-EXO. Based on the miRNA microarray analysis, exosomal miR-151-3p was lessened in BMExo-LPS group, which facilitated osteoclastic differentiation through miR-151-3p/PAFAH1B1.
CONCLUSIONS
Porphyromonas gingivalis-LPS could regulated bone metabolism by inhibiting proliferation and osteogenesis of BMSCs directly. Also, P. gingivalis-LPS-stimulated BMSCs-EXO promoted osteoclastogenesis via activating miR-151-3p/PAFAH1B1 signal pathway.
PubMed: 38923332
DOI: 10.1111/odi.15031 -
Biosensors May 2024In this study, we report a multiplexed platform for the simultaneous determination of five marine toxins. The proposed biosensor is based on a disposable electrical...
In this study, we report a multiplexed platform for the simultaneous determination of five marine toxins. The proposed biosensor is based on a disposable electrical printed (DEP) microarray composed of eight individually addressable carbon electrodes. The electrodeposition of gold nanoparticles on the carbon surface offers high conductivity and enlarges the electroactive area. The immobilization of thiolated aptamers on the AuNP-decorated carbon electrodes provides a stable, well-orientated and organized binary self-assembled monolayer for sensitive and accurate detection. A simple electrochemical multiplexed aptasensor based on AuNPs was designed to synchronously detect multiple cyanotoxins, namely, microcystin-LR (MC-LR), Cylindrospermopsin (CYL), anatoxin-α, saxitoxin and okadaic acid (OA). The choice of the five toxins was based on their widespread presence and toxicity to aquatic ecosystems and humans. Taking advantage of the conformational change of the aptamers upon target binding, cyanotoxin detection was achieved by monitoring the resulting electron transfer increase by square-wave voltammetry. Under the optimal conditions, the linear range of the proposed aptasensor was estimated to be from 0.018 nM to 200 nM for all the toxins, except for MC-LR where detection was possible within the range of 0.073 to 150 nM. Excellent sensitivity was achieved with the limits of detection of 0.0033, 0.0045, 0.0034, 0.0053 and 0.0048 nM for MC-LR, CYL, anatoxin-α, saxitoxin and OA, respectively. Selectivity studies were performed to show the absence of cross-reactivity between the five analytes. Finally, the application of the multiplexed aptasensor to tap water samples revealed very good agreement with the calibration curves obtained in buffer. This simple and accurate multiplexed platform could open the window for the simultaneous detection of multiple pollutants in different matrices.
Topics: Marine Toxins; Biosensing Techniques; Microcystins; Gold; Aptamers, Nucleotide; Electrochemical Techniques; Saxitoxin; Metal Nanoparticles; Cyanobacteria Toxins; Bacterial Toxins; Uracil; Tropanes; Alkaloids; Okadaic Acid; Electrodes; Limit of Detection
PubMed: 38920572
DOI: 10.3390/bios14060268 -
Frontiers in Genetics 2024Periodontitis, a common chronic inflammatory disease, significantly impacted oral health. To provide novel biological indicators for the diagnosis and treatment of...
INTRODUCTION
Periodontitis, a common chronic inflammatory disease, significantly impacted oral health. To provide novel biological indicators for the diagnosis and treatment of periodontitis, we analyzed public microarray datasets to identify biomarkers associated with periodontitis.
METHOD
The Gene Expression Omnibus (GEO) datasets GSE16134 and GSE106090 were downloaded. We performed differential analysis and robust rank aggregation (RRA) to obtain a list of differential genes. To obtain the core modules and core genes related to periodontitis, we evaluated differential genes through enrichment analysis, correlation analysis, protein-protein interaction (PPI) network and competing endogenous RNA (ceRNA) network analysis. Potential biomarkers for periodontitis were identified through comparative analysis of dual networks (PPI network and ceRNA network). PPI network analysis was performed in STRING. The ceRNA network consisted of RRA differentially expressed messenger RNAs (RRA_DEmRNAs) and RRA differentially expressed long non-coding RNAs (RRA_DElncRNAs), which regulated each other's expression by sharing microRNA (miRNA) target sites.
RESULTS
RRA_DEmRNAs were significantly enriched in inflammation-related biological processes, osteoblast differentiation, inflammatory response pathways and immunomodulatory pathways. Comparing the core ceRNA module and the core PPI module, C1QA, CENPK, CENPU and BST2 were found to be the common genes of the two core modules, and C1QA was highly correlated with inflammatory functionality. C1QA and BST2 were significantly enriched in immune-regulatory pathways. Meanwhile, LINC01133 played a significant role in regulating the expression of the core genes during the pathogenesis of periodontitis.
CONCLUSION
The identified biomarkers C1QA, CENPK, CENPU, BST2 and LINC01133 provided valuable insight into periodontitis pathology.
PubMed: 38919957
DOI: 10.3389/fgene.2024.1398582 -
Asian Pacific Journal of Cancer... Jun 2024Breast cancer represents one of the leading causes of death worldwide. Apart from genetic factors, the sex hormone estrogen plays a pivotal role in breast cancer...
BACKGROUND
Breast cancer represents one of the leading causes of death worldwide. Apart from genetic factors, the sex hormone estrogen plays a pivotal role in breast cancer development. We are exposed to a plethora of estrogen mimics on a daily basis via various routes. Nevertheless, how xenoestrogens, the exogenous estrogen mimics, modulate cancer-associated signaling pathways and interact with specific genes is still underexplored. Hence, this study aims to explore the direct or indirect binding partners of xenoestrogens and their expression upon exposure to these estrogenic compounds.
METHODS
The collection of genes linked to the xenoestrogens Octylphenol, Nonylphenol, Bisphenol-A, and 2,2-bis(4-hydroxyphenyl)-1,1,1-trichloroethane were gathered from the Comparative Toxicogenomics Database. Venny 2.1 was utilized to pinpoint the genes shared by these xenoestrogens. Subsequently, the shared genes underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resource. A xenoestrogen-protein interaction network was constructed using Search Tool for Interactions of Chemicals. The expressions of common genes were studied with the microarray dataset GSE5200 from the Gene Expression Omnibus database. Also, the expression of a common gene set within different breast cancer subtypes was identified using the University of California, Santa Cruz Xena.
RESULTS
The genes linked to xenoestrogens were identified, and 13 genes were found to interact with all four xenoestrogens. Through DAVID analysis, the genes chosen are found to be enriched for various functions and pathways, including pathways in cancer, chemical carcinogenesis-receptor activation, and estrogen signaling pathways. The results of the Comparative Toxicogenomics Database and the chemical-protein interaction network derived from STITCH were similar. Microarray data analysis showed significantly high expression of all 13 genes in another study, with Bisphenol-A and Nonylphenol treated MCF-7 cells, most of the genes are expressed in luminal A or basal breast cancer subtype.
CONCLUSION
In summary, the genes associated with the four xenoestrogens were mostly linked to pathways related to tumorigenesis, and the expression of these genes was found to be higher in breast cancer.
Topics: Humans; Breast Neoplasms; Estrogens; Female; Computational Biology; Computer Simulation; Protein Interaction Maps; Signal Transduction; Gene Expression Regulation, Neoplastic; Benzhydryl Compounds
PubMed: 38918670
DOI: 10.31557/APJCP.2024.25.6.2077 -
Bone Jun 2024Spinal stenosis (SS) is frequently caused by spinal ligament abnormalities, such as ossification and hypertrophy, which narrow the spinal canal and compress the spinal...
Spinal stenosis (SS) is frequently caused by spinal ligament abnormalities, such as ossification and hypertrophy, which narrow the spinal canal and compress the spinal cord or nerve roots, leading to myelopathy or sciatic symptoms; however, the underlying pathological mechanism is poorly understood, hampering the development of effective nonsurgical treatments. Our study aims to investigate the role of co-expression hub genes in patients with spinal ligament ossification and hypertrophy. To achieve this, we conducted an integrated analysis by combining RNA-seq data of ossification of the posterior longitudinal ligament (OPLL) and microarray profiles of hypertrophy of the ligamentum flavum (HLF), consistently pinpointing CTSD as an upregulated hub gene in both OPLL and HLF. Subsequent RT-qPCR and IHC assessments confirmed the heightened expression of CTSD in human OPLL, ossification of the ligamentum flavum (OLF), and HLF samples. We observed an increase in CTSD expression in human PLL and LF primary cells during osteogenic differentiation, as indicated by western blotting (WB). To assess CTSD's impact on osteogenic differentiation, we manipulated its expression levels in human PLL and LF primary cells using siRNAs and lentivirus, as demonstrated by WB, ALP staining, and ARS. Our findings showed that suppressing CTSD hindered the osteogenic differentiation potential of PLL and LF cells, while overexpressing CTSD activated osteogenic differentiation. These findings identify CTSD as a potential therapeutic target for treating spinal stenosis associated with spinal ligament abnormalities.
PubMed: 38917962
DOI: 10.1016/j.bone.2024.117174 -
EBioMedicine Jun 2024DNA methylation biomarkers in colorectal cancer (CRC) tissue hold potential as prognostic indicators. However, individual studies have yielded heterogeneous results, and...
BACKGROUND
DNA methylation biomarkers in colorectal cancer (CRC) tissue hold potential as prognostic indicators. However, individual studies have yielded heterogeneous results, and external validation is largely absent. We conducted a comprehensive external validation and meta-analysis of previously suggested gene methylation biomarkers for CRC prognosis.
METHODS
We performed a systematic search to identify relevant studies investigating gene methylation biomarkers for CRC prognosis until March 2024. Our external validation cohort with long-term follow-up included 2303 patients with CRC from 22 hospitals in southwest Germany. We used Cox regression analyses to assess associations between previously suggested gene methylation biomarkers and prognosis, adjusting for clinical variables. We calculated pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) using random-effects models.
FINDINGS
Of 151 single gene and 29 multiple gene methylation biomarkers identified from 121 studies, 37 single gene and seven multiple gene biomarkers were significantly associated with CRC prognosis after adjustment for clinical variables. Moreover, the directions of these associations with prognosis remained consistent between the original studies and our validation analyses. Seven single biomarkers and two multi-biomarker signatures were significantly associated with CRC prognosis in the meta-analysis, with a relatively strong level of evidence for CDKN2A, WNT5A, MLH1, and EVL.
INTERPRETATION
In a comprehensive evaluation of the so far identified gene methylation biomarkers for CRC prognosis, we identified candidates with potential clinical relevance for further investigation.
FUNDING
The German Research Council, the Interdisciplinary Research Program of the National Center for Tumor Diseases (NCT), Germany, the German Federal Ministry of Education and Research.
PubMed: 38917511
DOI: 10.1016/j.ebiom.2024.105223