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Journal of Cancer 2024Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model...
Triple-negative breast cancer (TNBC) poses significant diagnostic challenges due to its aggressive nature. This research develops an innovative deep learning (DL) model based on the latest multi-omics data to enhance the accuracy of TNBC subtype and prognosis prediction. The study focuses on addressing the constraints of prior studies by showcasing a model with substantial advancements in data integration, statistical performance, and algorithmic optimization. Breast cancer-related molecular characteristic data, including mRNA, miRNA, gene mutations, DNA methylation, and magnetic resonance imaging (MRI) images, were retrieved from the TCGA and TCIA databases. This study not only compared single-omics with multi-omics machine learning models but also applied Bayesian optimization to innovatively optimize the neural network structure of a DL model for multi-omics data. The DL model for multi-omics data significantly outperformed single-omics models in subtype prediction, achieving a 98.0% accuracy in cross-validation, 97.0% in the validation set, and 91.0% in an external test set. Additionally, the MRI radiomics model showed promising performance, especially with the training set; however, a decrease in performance during transfer testing underscored the advantages of the DL model for multi-omics data in data consistency and digital processing. Our multi-omics DL model presents notable innovations in statistical performance and transfer learning capability, bearing significant clinical relevance for TNBC classification and prognosis prediction. While the MRI radiomics model proved effective, it requires further optimization for cross-dataset application to enhance accuracy and consistency. Our findings offer new insights into improving TNBC classification and prognosis through multi-omics data and DL algorithms.
PubMed: 38911381
DOI: 10.7150/jca.93215 -
Cell Reports. Physical Science May 2024Recreating tissue environments with precise control over mechanical, biochemical, and cellular organization is essential for next-generation tissue models for drug...
Recreating tissue environments with precise control over mechanical, biochemical, and cellular organization is essential for next-generation tissue models for drug discovery, development studies, and the replication of disease environments. However, controlling these properties at cell-scale lengths remains challenging. Here, we report the development of printing approaches that leverage polyethylene glycol diacrylate (PEGDA) hydrogels containing photocaged oligonucleotides to spatially program material characteristics with non-destructive, non-ultraviolet light. We further integrate this system with a perfusion chamber to allow us to alter the composition of PEGDA hydrogels while retaining common light-activatable photocaged DNAs. We demonstrate that the hydrogels can capture DNA functionalized materials, including cells coated with complementary oligonucleotides with spatial control using biocompatible wavelengths. Overall, these materials open pathways to orthogonal capture of any DNA functionalized materials while not changing the sequences of the DNA.
PubMed: 38911357
DOI: 10.1016/j.xcrp.2024.101922 -
International Immunopharmacology Jun 2024The occurrence and progression of hepatocellular carcinoma (HCC) are significantly affected by DNA damage response (DDR). Exploring DDR-related biomarkers can help...
BACKGROUND
The occurrence and progression of hepatocellular carcinoma (HCC) are significantly affected by DNA damage response (DDR). Exploring DDR-related biomarkers can help predict the prognosis and immune characteristics of HCC.
METHODS
First, the single-cell RNA sequencing (scRNA-seq) dataset GSE242889 was processed and performed manual annotation. Then we found the marker genes of DDR-active subgroups based on "AUCell" algorithm. The "Limma" R package was used to identify differentially expressed genes (DEGs) between tumor and normal samples of HCC. The risk prognostic model was constructed by filtering genes using univariate Cox and LASSO regression analyses. Finally, the signatures were analyzed for immune infiltration, gene mutation, and drug sensitivity. Last but not least, KPNA2, which had the largest coefficient in our model was validated by experiments including western blot, MTT, colony formation and γ-H2AX assays.
RESULTS
We constructed a prognostic model based on 5 DDR marker genes including KIF2C, CDC20, KPNA2, UBE2S and ADH1B for HCC. We also proved that the model had an excellent performance in both training and validation cohorts. Patients in the high-risk group had a poorer prognosis, different immune features, gene mutation frequency, immunotherapy response and drug sensitivity compared with the low-risk group. Besides, our experimental results proved that KPNA2 was up-regulated in liver cancer cells than in hepatocytes. More importantly, the knockdown of KPNA2 significantly inhibited cell variability, proliferation and promoted DNA damage.
CONCLUSIONS
We innovatively integrated scRNA-seq and bulk RNA sequencing to construct the DDR-related prognostic model. Our model could effectively predict the prognosis, immune landscape and therapy response of HCC.
PubMed: 38909498
DOI: 10.1016/j.intimp.2024.112475 -
Medicina Oral, Patologia Oral Y Cirugia... Jun 2024The DNA mismatch repair (MMR) system serves as a sophisticated guardian of the precise functioning of the human genome. Dysregulation within this system is linked to the...
BACKGROUND
The DNA mismatch repair (MMR) system serves as a sophisticated guardian of the precise functioning of the human genome. Dysregulation within this system is linked to the oncogenesis process. Reduced expression of MMR system proteins identified in salivary gland tumors (SGTs) suggests an increased risk of tumoral occurrence. This study aims to analyze the expression of MMR proteins in SGTs and discuss the relevance of this association to the development of these neoplasms.
MATERIAL AND METHODS
This review was conducted following the PRISMA guidelines and was registered in PROSPERO (CRD42023465590). A comprehensive search of the PubMed/MEDLINE, Web of Science, Scopus, Embase, and ProQuest (non-peer reviewed platform) was performed to answer the question "Do DNA MMR system proteins exhibit expression in SGTs?". The methodological quality of the selected studies was assessed using the JBI's Critical Appraisal Tool.
RESULTS
A total of 142 patients with benign SGTs and 84 with malignant SGTs were included in this review. The literature analysis showed a notable reduction in the expression of DNA MMR system proteins (hHMS2, hMLH1, hMSH3 and hMSH6) in the percentage of marked cells.
CONCLUSIONS
The reduction in the expression of the DNA MMR system proteins suggests an interesting correlation with the development of malignant and benign SGTs. Nevertheless, further investigations are warranted to better clarify the precision of measuring biomarker protein expression.
PubMed: 38907641
DOI: 10.4317/medoral.26647 -
NPJ Systems Biology and Applications Jun 2024Combination therapy is well established as a key intervention strategy for cancer treatment, with the potential to overcome monotherapy resistance and deliver a more...
Combination therapy is well established as a key intervention strategy for cancer treatment, with the potential to overcome monotherapy resistance and deliver a more durable efficacy. However, given the scale of unexplored potential target space and the resulting combinatorial explosion, identifying efficacious drug combinations is a critical unmet need that is still evolving. In this paper, we demonstrate a network biology-driven, simulation-based solution, the Simulated Cell™. Integration of omics data with a curated signaling network enables the accurate and interpretable prediction of 66,348 combination-cell line pairs obtained from a large-scale combinatorial drug sensitivity screen of 684 combinations across 97 cancer cell lines (BAC = 0.62, AUC = 0.7). We highlight drug combination pairs that interact with DNA Damage Response pathways and are predicted to be synergistic, and deep network insight to identify biomarkers driving combination synergy. We demonstrate that the cancer cell 'avatars' capture the biological complexity of their in vitro counterparts, enabling the identification of pathway-level mechanisms of combination benefit to guide clinical translatability.
Topics: Humans; DNA Damage; Cell Line, Tumor; Neoplasms; Signal Transduction; Biomarkers, Tumor; Drug Discovery; Antineoplastic Agents; Drug Synergism; Systems Biology; Antineoplastic Combined Chemotherapy Protocols; Computer Simulation; Avatar
PubMed: 38906870
DOI: 10.1038/s41540-024-00394-w -
Clinical and Experimental Medicine Jun 2024Homeodomain transcription factor A9 (HOXA9) is a member of the HOX cluster family of transcription factors that are crucially involved in embryo implantation,...
Homeodomain transcription factor A9 (HOXA9) is a member of the HOX cluster family of transcription factors that are crucially involved in embryo implantation, morphogenesis, body axis development, and endothelial cell differentiation. Despite numerous reports on its aberrant expression in a few malignancies, the molecular and functional complexity of HOXA9 across cancers remains obscure. We aimed to analyze the dynamic role of HOXA9 across cancers by identifying, analyzing, and understanding its multiple modes of regulation and functional implications and identifying possible therapeutic avenues. We conducted a comprehensive analysis to determine the role of HOXA9 across cancers. This approach involved the integration of large-scale datasets from public repositories such as the Genomic Data Commons, specifically the Cancer Genome Atlas (GDC-TCGA), across 33 different cancer types. The multiple modes of HOXA9 regulation by genetic and epigenetic factors were determined using online tools, which comprised experimentally validated observations. Furthermore, downstream pathways were identified by predicting the targets of HOXA9 and by performing functional enrichment analysis. We also assessed the clinical significance of HOXA9 in terms of prognosis and stage stratification. This study evaluated the correlation between HOXA9 and tumor-infiltrating molecules and discussed its association with therapeutically approved antineoplastic drugs. HOXA9 was significantly upregulated in 9 tumors and downregulated in 2 cancers. The deregulation of HOXA9 is primarily attributed to epigenetic factors, including promoter DNA methylation and noncoding RNAs (ncRNAs). The HOXA9 transcription factor interacts with PBX/MEIS cofactors and regulates multiple genes involved in cancer-associated EMT, autophagy, the cell cycle, metabolic pathways, Wnt signaling, TGF-β signaling, the AMPK pathway, PI3K/AKT signaling, and NF-κB signaling, thereby establishing control over downstream mechanisms. Differential expression in various clinical stages across cancers was shown to have prognostic significance and to be correlated with tumor-infiltrating immune molecules. The assessment of the correlation of HOXA9 expression with approved antineoplastic drugs revealed that targeting HOXA9 could be the most reliable strategy for preventing cancer progression. HOXA9 is upregulated in the majority of malignancies and drives cancer progression by regulating multiple signaling mechanisms. Hence, HOXA9 could be a reliable diagnostic indicator and a potential therapeutic candidate for solid cancer types.
Topics: Humans; Homeodomain Proteins; Neoplasms; Carcinogenesis; Gene Expression Regulation, Neoplastic; Prognosis; Biomarkers, Tumor
PubMed: 38904676
DOI: 10.1007/s10238-024-01389-x -
Frontiers in Endocrinology 2024Thyroid cancer rarely occurs in children and adolescents. Molecular markers such as , , and have been widely used in adult PTC. It is currently unclear whether these...
OBJECTIVES
Thyroid cancer rarely occurs in children and adolescents. Molecular markers such as , , and have been widely used in adult PTC. It is currently unclear whether these molecular markers have equivalent potential for application in pediatric patients. This study aims to explore the potential utility of a multi-gene conjoint analysis based on next-generation targeted sequencing for pediatric papillary thyroid carcinoma (PTC).
MATERIALS AND METHODS
The patients diagnosed with PTC (aged 18 years or younger) in the pediatrics department of Lishui District Hospital of Traditional Chinese Medicine were retrospectively screened. A targeted enrichment and sequencing analysis of 116 genes associated with thyroid cancer was performed on paraffin-embedded tumor tissues and paired paracancerous tissue of fifteen children (average age 14.60) and nine adults (average age 49.33) PTC patients. Demographic information, clinical indicators, ultrasonic imaging information and pathological data were collected. The Kendall correlation test was used to establish a correlation between molecular variations and clinical characteristics in pediatric patients.
RESULTS
A sample of 15 pediatric PTCs revealed a detection rate of 73.33% (11/15) for driver gene mutations and fusion. Compared to adult PTCs, the genetic mutation landscape of pediatric PTCs was more complex. Six mutant genes overlap between the two groups, and an additional seventeen unique mutant genes were identified only in pediatric PTCs. There was only one unique mutant gene in adult PTCs. The tumor diameter of pediatric PTCs tended to be less than 4cm (p<0.001), and the number of lymph node metastases was more than five (p<0.001). Mutations in specific genes unique to pediatric PTCs may contribute to the onset and progression of the disease by adversely affecting hormone synthesis, secretion, and action mechanisms, as well as the functioning of thyroid hormone signaling pathways. But, additional experiments are required to validate this hypothesis.
CONCLUSION
mutation and fusion are involved in the occurrence and development of adolescent PTC. For pediatric thyroid nodules that cannot be determined as benign or malignant by fine needle aspiration biopsy, multiple gene combination testing can provide a reference for personalized diagnosis and treatment by clinical physicians.
Topics: Humans; Female; Adolescent; Thyroid Cancer, Papillary; Male; Child; Thyroid Neoplasms; Mutation; Retrospective Studies; Proto-Oncogene Proteins B-raf; Adult; Middle Aged; Biomarkers, Tumor; Proto-Oncogene Proteins c-ret; High-Throughput Nucleotide Sequencing; DNA Mutational Analysis
PubMed: 38904052
DOI: 10.3389/fendo.2024.1405142 -
Frontiers in Cellular and Infection... 2024Ceftazidime/avibactam (CZA) is indicated against multidrug-resistant , particularly those that are carbapenem resistant. CZA resistance in producing PER, a class A...
INTRODUCTION
Ceftazidime/avibactam (CZA) is indicated against multidrug-resistant , particularly those that are carbapenem resistant. CZA resistance in producing PER, a class A extended-spectrum β-lactamase, has been well documented . However, data regarding clinical isolates are scarce. Our aim was to analyze the contribution of PER to CZA resistance in non-carbapenemase-producing clinical isolates that were ceftazidime and/or carbapenem non-susceptible.
METHODS
Antimicrobial susceptibility was determined through agar dilution and broth microdilution, while gene was screened through PCR. All PER-positive isolates and five PER-negative isolates were analyzed through Whole Genome Sequencing. The mutational resistome associated to CZA resistance was determined through sequence analysis of genes coding for PBPs 1b, 3 and 4, MexAB-OprM regulators MexZ, MexR, NalC and NalD, AmpC regulators AmpD and AmpR, and OprD porin. Loss of gene was induced in a PER-positive isolate by successive passages at 43°C without antibiotics.
RESULTS
Twenty-six of 287 isolates studied (9.1%) were CZA-resistant. Thirteen of 26 CZA-resistant isolates (50%) carried . One isolate carried but was CZA-susceptible. PER-producing isolates had significantly higher MICs for CZA, amikacin, gentamicin, ceftazidime, meropenem and ciprofloxacin than non-PER-producing isolates. All PER-producing isolates were ST309 and their gene was associated to ISCR1, an insertion sequence known to mobilize adjacent DNA. PER-negative isolates were classified as ST41, ST235 (two isolates), ST395 and ST253. PER-negative isolates carried genes for narrow-spectrum β-lactamases and the mutational resistome showed that all isolates had one major alteration in at least one of the genes analyzed. Loss of gene restored susceptibility to CZA, ceftolozane/tazobactam and other β-lactamsin the evolved isolate.
DISCUSSION
PER-3-producing ST309 is a successful multidrug-resistant clone with gene implicated in resistance to CZA and other β-lactams.
Topics: Ceftazidime; Pseudomonas aeruginosa; Azabicyclo Compounds; Microbial Sensitivity Tests; Humans; Drug Combinations; beta-Lactamases; Anti-Bacterial Agents; Pseudomonas Infections; Bacterial Proteins; Drug Resistance, Multiple, Bacterial; Chile; Whole Genome Sequencing; Mutation
PubMed: 38903939
DOI: 10.3389/fcimb.2024.1410834 -
F1000Research 2023Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is...
BACKGROUND
Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) can access the nervous system and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma.
METHODS
Here, we perform extensive data mining, integration and re-analysis of ZIKV infection datasets to highlight molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We collate infection data of multiple neuroblastoma cell lines by different ZIKV strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection.
RESULTS
Through data mining of published literature, we observed most paediatric neuroblastoma cell lines to be highly susceptible to ZIKV infection and propose the PRVABC59 ZIKV strain to be the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV non-structural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon.
CONCLUSIONS
Our work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials.
Topics: Humans; Neuroblastoma; Oncolytic Virotherapy; Zika Virus; Proteomics; Cell Line, Tumor; Zika Virus Infection; Transcriptome
PubMed: 38903860
DOI: 10.12688/f1000research.132627.3 -
Frontiers in Genetics 2024The recognition of DNA Binding Proteins (DBPs) plays a crucial role in understanding biological functions such as replication, transcription, and repair. Although...
The recognition of DNA Binding Proteins (DBPs) plays a crucial role in understanding biological functions such as replication, transcription, and repair. Although current sequence-based methods have shown some effectiveness, they often fail to fully utilize the potential of deep learning in capturing complex patterns. This study introduces a novel model, LGC-DBP, which integrates Long Short-Term Memory (LSTM), Gated Inception Convolution, and Improved Channel Attention mechanisms to enhance the prediction of DBPs. Initially, the model transforms protein sequences into Position Specific Scoring Matrices (PSSM), then processed through our deep learning framework. Within this framework, Gated Inception Convolution merges the concepts of gating units with the advantages of Graph Convolutional Network (GCN) and Dilated Convolution, significantly surpassing traditional convolution methods. The Improved Channel Attention mechanism substantially enhances the model's responsiveness and accuracy by shifting from a single input to three inputs and integrating three sigmoid functions along with an additional layer output. These innovative combinations have significantly improved model performance, enabling LGC-DBP to recognize and interpret the complex relationships within DBP features more accurately. The evaluation results show that LGC-DBP achieves an accuracy of 88.26% and a Matthews correlation coefficient of 0.701, both surpassing existing methods. These achievements demonstrate the model's strong capability in integrating and analyzing multi-dimensional data and mark a significant advancement over traditional methods by capturing deeper, nonlinear interactions within the data.
PubMed: 38903752
DOI: 10.3389/fgene.2024.1411847