SLC7A7 is a prognostic biomarker correlated with immune infiltrates in non-small cell lung cancer

Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis

BACKGROUND

Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely complex biological characteristics. Lysine and its metabolism are closely related to human cancer, but little is known about how lysine metabolism-related genes contribute to gastric carcinogenesis.

METHODS

The roles of lysine metabolism-related genes in GC were investigated by in-depth analysis of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) data via machine learning and multiple bioinformatics methods and confirmed by multiple cell and molecular biology methods.

RESULTS

By systematically analyzing the heterogeneity of GC cells and interactions among cell subtypes, two key genes, solute carrier family 7 member 7 (SLC7A7) and vimentin (VIM), were innovatively identified as lysine metabolism-related genes involved in gastric carcinogenesis. The potential functional mechanisms involved immune infiltration, signaling pathway regulation, drug sensitivity, molecular regulatory networks, tumor regulatory genes, and metabolic pathways. A reliable prognostic risk nomogram was established for GC prognosis prediction. Moreover, the expression of the lysine metabolism-related genes SLC7A7 and VIM and their effect on cellular phenotypes in gastric carcinogenesis were verified in clinical samples and in vitro experiments, including cell proliferation, migration, invasion and cell cycle assays.

CONCLUSIONS

We explored the role of lysine metabolism-related genes and prognostic models in GC with multiple datasets, providing novel metabolic targets.

Exosomes containing miR-152-3p targeting FGFR3 mediate SLC7A7-induced angiogenesis in bladder cancer

Bladder cancer (BCa) is a prevalent malignancy with a poor prognosis. SLC7A7 has been linked to BCa progression and angiogenesis, but its specific role remains unclear. We established a SLC7A7-knockdown BCa cell line to investigate its effects on angiogenesis. In vivo experiments assessed tumor vascularization, while in vitro studies explored exosome involvement. MiRNA sequencing identified miR-152-3p as a key regulator. Further investigation using dual-luciferase reporter assays, qRT-PCR, and Western blot revealed that miR-152-3p inhibits the expression of FGFR3 by binding to its 3' UTR. Meanwhile, functional assays, including angiogenesis assays, Transwell assays, and wound healing assays, were performed to evaluate the effects of miR-152-3p on angiogenesis. We confirmed the significant role of SLC7A7 in BCa progression, specifically in promoting angiogenesis, through the involvement of exosomes and the regulatory axis of miR-152-3p/ FGFR3. Targeting FGFR3 might be a promising strategy to reverse control BCa progression for an improved prognosis.

Genetic insights into therapeutic targets for gout: evidence from a multi-omics mendelian randomization study

BACKGROUND

Considering that the treatment of gout is poor, we performed a Mendelian randomization (MR) study to identify candidate biomarkers and therapeutic targets for gout.

METHODS

A drug-targeted MR study was performed for gout by integrating the gout genome-wide association studies (GWAS) summary data and cis expression quantitative trait loci of 2,633 druggable genes from multiple cohorts. Summary data-based Mendelian randomization (SMR) analyses based on transcript and protein levels were further implemented to validate the reliability of the identified potential therapeutic targets for gout. Phenome-wide MR (Phe-MR) analysis was conducted in 1403 diseases to investigate incidental side effects of potential therapeutic targets for gout.

RESULTS

Eight potential therapeutic targets (ALDH3B1, FCGR2B, IL2RB, NRBP1, RCE1, SLC7A7, SUMF1, THBS3) for gout were identified in the discovery cohort using MR analysis. Replication analysis and meta-analysis implemented in the replication cohort validated the robustness of the MR findings (P < 0.05). Evidence from the SMR analysis (P < 0.05) further strengthened the reliability of the 8 potential therapeutic targets for gout also revealed that high levels of ALDH3B1 reduced the gout risk possibly modified by the methylation site cg25402137. SMR analysis (P < 0.05) at the protein level added emphasis on the impact of the risk genes NRBP1 and SUMF1 on gout. Phe-MR analysis indicated significant causality between 7 gout causal genes and 45 diseases.

CONCLUSION

This study identified several biomarkers associated with gout risk, providing new insights into the etiology of gout and promising targets for the development of therapeutic agents.

N7-methyladenosine-induced SLC7A7 serves as a prognostic biomarker in pan-cancer and promotes CRC progression in colorectal cancer

Solute transport family 7A member 7 (SLC7A7) mutations contribute to lysinuric protein intolerance (LPI), which is the mechanism of action that has been extensively studied. In colorectal cancer (CRC), SLC7A7 appears to play a role, but the features and mechanisms are not yet well understood. Survival was analyzed using the Kaplan-Meier analysis. Enrichment analysis was performed to characterize, immune infiltration, methylation, genetic instability, and crucial pathways of SLC7A7. Afterward, functional experiments were conducted in vitro to investigate how SLC7A7 affects tumor metastasis. Mechanistically, quantitative real-time PCR (qRT-PCR), western blot (WB), and methylated RNA immunoprecipitation (me-RIP) were carried out to confirm the methylation modification of SLC7A7 and related functions. High levels of expression of SLC7A7 are predictive of a worse prognosis for CRC patients. Enrichment analysis showed that SLC7A7 was significantly enriched during EMT and could be enriched in the Wnt/β-catenin signaling pathway, immune infiltration analysis of pan-cancer showed that SLC7A7 was significantly enriched in macrophages, and methylation analysis showed that SLC7A7 methylation modification affected the prognosis of specific cancers. SLC7A7 was indicated to promote the migration and invasion of CRC cells in in vitro functional experiments. Mechanistically, SLC7A7 was observed to potentially interact with the Wnt/β-catenin signaling pathway, possibly by influencing adenomatous polyposis coli (APC) expression. Furthermore, we identified that SLC7A7 undergoes N7-methylguanosine (m7G) modification, which may regulate SLC7A7 mRNA stability, with Quaking (QKI) potentially playing a role in this process by recognizing the m7G modification. Our results indicate that SLC7A7 may promote CRC metastasis through the SLC7A7/APC/Wnt/β-catenin signaling pathway. Moreover, m7G modification might be involved in regulating SLC7A7 mRNA stability, highlighting a novel layer of regulation.

RNA-seq analysis of small intestine transcriptional changes induced by starvation stress in piglets

Piglets may experience a variety of stress injuries, but the molecular regulatory mechanisms underlying these injuries are not well understood. In this study, we analysed the ileum of Large White (LW) and Mashen (MS) piglets at different times of starvation using chemical staining and transcriptome analysis. The intestinal barrier of piglets was damaged after starvation stress, but the intestinal antistress ability of MS piglets was stronger than LW piglets. A total of 8021 differentially expressed genes (DEGs) were identified in two breeds. Interestingly, the immune capacity (CHUK, TLR3) of MS piglets increased significantly after short-term starvation stress, while energy metabolism (NAGS, PLA2G12B, AGCG8) was predominant in LW piglets. After long-term starvation stress, the level of energy metabolism (PLIN5, PLA2G12B) was significantly increased in MS piglets. The expression of immune (HLA-DQB1, IGHG4, COL3A1, CD28, LAT) and disease (HSPA1B, MINPPI, ADH1C, GAL3ST1) related genes were significantly increased in two breeds of piglets. These results suggest that short-term stress mainly enhances immunity and energy metabolism in piglets, while long-term starvation produces greater stress on piglets, making it difficult for them to compensate for the damage to their bodies through self-regulation. This information can help improve the stress resistance of piglets through molecular breeding.

A novel role for WZ3146 in the inhibition of cell proliferation via ERK and AKT pathway in the rare EGFR G719X mutant cells

Mutations in the epidermal growth factor receptor (EGFR) gene are common driver oncogenes in non-small cell lung cancer (NSCLC). Studies have shown that afatinib is beneficial for NSCLC patients with rare EGFR mutations. However, the effectiveness of tyrosine kinase inhibitors (TKIs) against the G719X (G719A, G719C and G719S) mutation has not been fully established. Herein, using the CRISPR method, the EGFR G719X mutant cell lines were constructed to assess the sensitivity of the rare mutation G719X in NSCLC. WZ3146, a novel mutation-selective EGFR inhibitor, was conducted transcriptome sequencing and in vitro experiments. The results showed that WZ3146 induced cytotoxic effects, inhibited growth vitality and proliferation via ERK and AKT pathway in the EGFR G719X mutant cells. Our findings suggest that WZ3146 may be a promising treatment option for NSCLC patients with the EGFR exon 18 substitution mutation G719X.

Role of solute carrier transporters in regulating dendritic cell maturation and function

Dendritic cells (DCs) are specialized antigen-presenting cells that initiate and regulate innate and adaptive immune responses. Solute carrier (SLC) transporters mediate diverse physiological functions and maintain cellular metabolite homeostasis. Recent studies have highlighted the significance of SLCs in immune processes. Notably, upon activation, immune cells undergo rapid and robust metabolic reprogramming, largely dependent on SLCs to modulate diverse immunological responses. In this review, we explore the central roles of SLC proteins and their transported substrates in shaping DC functions. We provide a comprehensive overview of recent studies on amino acid transporters, metal ion transporters, and glucose transporters, emphasizing their essential contributions to DC homeostasis under varying pathological conditions. Finally, we propose potential strategies for targeting SLCs in DCs to bolster immunotherapy for a spectrum of human diseases.

Expression of lymphoid structure-associated cytokine/chemokine gene transcripts in tumor and protein in serum are prognostic of melanoma patient outcomes

Background

Proinflammatory chemokines/cytokines support development and maturation of tertiary lymphoid structures (TLS) within the tumor microenvironment (TME). In the current study, we sought to investigate the prognostic value of TLS-associated chemokines/cytokines (TLS-kines) expression levels in melanoma patients by performing serum protein and tissue transcriptomic analyses, and to then correlate these data with patients clinicopathological and TME characteristics.

Methods

Levels of TLS-kines in patients' sera were quantitated using a custom Luminex Multiplex Assay. The Cancer Genomic Atlas melanoma cohort (TCGA-SKCM) and a Moffitt Melanoma cohort were used for tissue transcriptomic analyses. Associations between target analytes and survival outcomes, clinicopathological variables, and correlations between TLS-kines were statistically analyzed.

Results

Serum of 95 patients with melanoma were evaluated; 48 (50%) female, median age of 63, IQR 51-70 years. Serum levels of APRIL/TNFSF13 were positively correlated with levels of both CXCL10 and CXCL13. In multivariate analyses, high levels of serum APRIL/TNFSF13 were associated with improved event-free survival after adjusting for age and stage (HR = 0.64, 95% CI 0.43-0.95; p = 0.03). High expression of APRIL/TNFSF13 tumor transcripts was significantly associated with improved OS in TCGA-SKCM (HR = 0.69, 95% CI 0.52-0.93; p = 0.01) and in Moffitt Melanoma patients (HR = 0.51, 95% CI: 0.32-0.82; p = 0.006). Further incorporation of CXCL13 and CXCL10 tumor transcript levels in a 3-gene index revealed that high APRIL/CXCL10/CXCL13 expression was associated with improved OS in the TCGA SKCM cohort (HR = 0.42, 95% CI 0.19-0.94; p = 0.035). Melanoma differentially expressed genes positively associated with high APRIL/CXCL10/CXCL13 tumor expression were linked to tumor infiltration by a diverse array of proinflammatory immune cell types.

Conclusion

Serum protein and tumor transcript levels of APRIL/TNFSF13 are associated with improved survival outcomes. Patients exhibiting high coordinate expression of APRIL/CXCL10/CXCL13 transcripts in their tumors displayed superior OS. Further investigation of TLS-kine expression profiles related to clinical outcomes in larger cohort studies is warranted.

Lower SLC7A2 expression is associated with enhanced multidrug resistance, less immune infiltrates and worse prognosis of NSCLC

BACKGROUND

Solute carrier family 7 member 2 (SLC7A2), a cationic amino acid transporter, is lowly expressed in ovarian and hepatocellular cancers, which is associated with their worse prognosis. However, its roles in the prognosis, drug resistance and immune infiltration in non-small-cell lung cancer (NSCLC) are unclear.

METHODS

We chose SLC7A2 from RNA-Seq of paclitaxel/cisplatin-resistant A549 cells, then bioinformatics, cell lines construction, RT-qPCR, and CCK8 were performed to investigate SLC7A2 role.

RESULT

We analyzed the 223 differentially expressed genes (DEGs) from RNA-Seq of paclitaxel/cisplatin-resistant A549 cells and found that SLC7A2 expression was down-regulated in NSCLC. Lower SLC7A2 expression was associated with worse recurrence-free survival (RFS) in NSCLC. SLC7A2 silencing enhanced the proliferation of NSCLC cells and their insensitivity to paclitaxel, cisplatin, and gemcitabine in vitro. Activation of AMPK has up-regulated SLC7A2 expression and enhanced the sensitivity of NSCLC cells to anti-tumor drugs, which could be attributed to E2F1's regulation. In addition, the levels of SLC7A2 expression were correlated to the numbers of infiltrated neutrophils, macrophages, dendritic cells and their marker genes, like CD86, HLA-DPA1 and ITGAM.

CONCLUSIONS

SLC7A2 may act as a tumor suppressor to modulate drug sensitivity, immune infiltration and survival in NSCLC. Video abstract.

Identification of KIF21B as a Biomarker for Colorectal Cancer and Associated with Poor Prognosis

OBJECTIVE

This study is aimed at exploring the function of KIF21B in colorectal cancer.

METHODS

The expression of KIF21B was analyzed by the UALCAN database, GEPIA site, and TIMER site. The survival rate was analyzed by Kaplan-Meier curves, and the prognosis was analyzed by ROC. Relevant signaling pathways and biological processes were analyzed by GO-KEGG enrichment analysis. The correlation between KIF21B and cancer immune infiltrates was analyzed by TIMER. The functional state of KIF21B in various types of cancers was conducted by single-cell RNA-sequencing. Furthermore, the expression of KIF21B was verified by real-time qPCR and Western blotting. The cell proliferation was measured by CCK8 assay. The cell apoptosis was analyzed by flow cytometry. Cell migration and invasion were determined by the transwell assay.

RESULTS

Combination analysis of bioinformatics methods revealed that KIF21B is high expression in CRC, associated with poor survival. KIF21B and associated genes were significantly enriched in covalent chromatin modification. The expression of KIF21B was positively correlated with infiltrating levels of CD4+ T cells and neutrophils, cell apoptosis, and metastasis. KIF21B was upregulated expression in CRC cell lines. KIF21B deficiency reduced cell proliferation, migration, and invasion.

CONCLUSIONS

Our study suggested that KIF21B may be a biomarker in CRC.

The Effect of PD-1 Inhibitor Combined with Chemotherapy on the Level of Peripheral Blood T Lymphocytes among Patients with Non-Small-Cell Lung Cancer and Its Relationship with Prognosis

Objective

To explore the effect of combined treatment of PD-1 inhibitor and chemotherapy on the level of peripheral blood T lymphocytes in non-small-cell lung cancer (NSCLC) patients and its relationship with prognosis.

Methods

Retrospective analysis was conducted on 150 NSCLC patients treated in Guangxi Medical University Affiliated Tumor Hospital from June 2018 to September 2020, including 77 patients treated with PD-1 inhibitor combined with chemotherapy as the observation group (OG) and 73 patients with chemotherapy alone as the control group (CG). Therapeutic efficacy, immune function indexes, serum tumor markers, incidence of adverse reactions during hospitalization, 1-year survival rate, and life quality after 6 months of treatment were observed and compared between two groups.

Results

Compared to the CG, the therapeutic effect of OG was evidently better. Six months after treatment, levels of CD4⁺/CD8⁺, NK cells, and CD4 ⁺ in two groups were elevated markedly, and indexes of OG were notably and comparatively higher than those in the other group. After treatment, OG was observed with a marked decline regarding levels of CYFRA21-1, CEA, and CA125 compared to those in the CG; and there was no notable difference in terms of adverse reaction occurrence between two groups, but the 1-year survival rate and 6-month life quality in OG over ranked those in CG.

Conclusion

For NSCLC patients, the PD-1 inhibitor given on the basis of chemotherapy can further improve the clinical efficacy and improve immune function and long-term survival rate of patients on the premise of ensuring the safety of treatment, which is worth promoting in clinical practice.

Comprehensive analysis of fatty acid and lactate metabolism–related genes for prognosis value, immune infiltration, and therapy in osteosarcoma patients

Osteosarcoma is the most frequent bone tumor. Notwithstanding that significant medical progress has been achieved in recent years, the 5-year overall survival of osteosarcoma patients is inferior. Regulation of fatty acids and lactate plays an essential role in cancer metabolism. Therefore, our study aimed to comprehensively assess the fatty acid and lactate metabolism pattern and construct a fatty acid and lactate metabolism–related risk score system to predict prognosis in osteosarcoma patients. Clinical data and RNA expression data were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We used the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses to construct a prognostic risk score model. Relationships between the risk score model and age, gender, tumor microenvironment characteristics, and drug sensitivity were also explored by correlation analysis. We determined the expression levels of prognostic genes in osteosarcoma cells via Western blotting. We developed an unknown fatty acid and lactate metabolism–related risk score system based on three fatty acid and lactate metabolism–related genes (SLC7A7, MYC, and ACSS2). Survival analysis showed that osteosarcoma patients in the low-risk group were likely to have a better survival time than those in the high-risk group. The area under the curve (AUC) value shows that our risk score model performs well in predicting prognosis. Elevated fatty acids and lactate risk scores weaken immune function and the environment of the body, which causes osteosarcoma patients’ poor survival outcomes. In general, the constructed fatty acid and lactate metabolism–related risk score model can offer essential insights into subsequent mechanisms in available research. In addition, our study may provide rational treatment strategies for clinicians based on immune correlation analysis and drug sensitivity in the future.

Transcriptional patterns reveal tumor histologic heterogeneity and immunotherapy response in lung adenocarcinoma

Tumoral heterogeneity has proven to be a leading cause of difference in prognosis and acquired drug resistance. High intratumor heterogeneity often means poor clinical response and prognosis. Histopathological subtypes suggest tumor heterogeneity evolved during the progression of lung adenocarcinoma, but the exploration of its molecular mechanisms remains limited. In this work, we first verified that transcriptional patterns of a set of differentially expressed genes profoundly revealed the histologic progression of lung adenocarcinoma. Next, a predictive model based on the transcriptional patterns was established to accurately distinguish histologic subtypes. Two crucial genes were identified and used to construct a tumor heterogeneous scoring model (L2SITH) to stratify patients, and we found that patients with low heterogeneity score had better prognosis. Low L2SITH scores implied low tumor purity and beneficial tumor microenvironment. Moreover, L2SITH effectively identified cohorts with better responses to anti–PD-1 immunotherapy.

Prognostic biomarker IL17A correlated with immune infiltrates in head and neck cancer

Background

The underlying functions and mechanisms of the Th17 pathway in Head and neck squamous cell carcinoma (HNSCC) progression and tumor immunology are still unclear. We investigated the correlation between IL17A expression and certain clinical parameters, tumor-infiltrating immune cells (TIICs) in TCGA HNSCC samples.

Methods

HNSCC files from the TCGA database were analyzed to obtain data on immune system infiltrates, gene expression, and related clinical information. R (Version 3.6.3) software, GEPIA, and TIMER online analysis tools were used to profile the relationship between the expression of IL17A and the prognosis, clinical stages, survival status and immune cell tumor-infiltrating levels of HNSCC patients. GEPIA and TIMER online analysis tools were used to verify the data.

Results

The expression of IL17A was significantly decreased in tumor tissues from HNSCC. IL17A expression was associated with M, N stage, lymphovascular invasion, and patients OS event. GSEA revealed that IL17A was closely related to humoral immune response, T cells response, and cytokine signal. TCGA database and TIMER online analysis indicated that the B cells and T cells levels were correlated with IL17A. The correlation between IL17A expression and correlated genes was analyzed.

Conclusions

IL-17A plays a key role in HNSCC. The levels of IL17A are important values for the determination of the occurrence and development of the HNSCC. The IL17A and correlated genes may be potential immunotherapeutic targets for HNSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02703-1.

ESRRG, ATP4A, and ATP4B as Diagnostic Biomarkers for Gastric Cancer: A Bioinformatic Analysis Based on Machine Learning

Based on multiple bioinformatics methods and machine learning techniques, this study was designed to explore potential hub genes of gastric cancer with a diagnostic value. The novel biomarkers were detected through multiple databases of gastric cancer–related genes. The NCBI Gene Expression Omnibus (GEO) database was used to obtain gene expression files. Three hub genes (ESRRG, ATP4A, and ATP4B) were detected through a combination of weighted gene co-expression network analysis (WGCNA), gene–gene interaction network analysis, and supervised feature selection method. GEPIA2 was used to verify the differences in the expression levels of the hub genes in normal and cancer tissues in the RNA-seq levels of Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases. The objectivity of potential hub genes was also verified by immunohistochemistry in the Human Protein Atlas (HPA) database and transcription factor–hub gene regulatory network. Machine learning (ML) methods including data pre-processing, model selection and cross-validation, and performance evaluation were examined on the hub-gene expression profiles in five Gene Expression Omnibus datasets and verified on a GEO external validation (EV) dataset. Six supervised learning models (support vector machine, random forest, k-nearest neighbors, neural network, decision tree, and eXtreme Gradient Boosting) and one semi-supervised learning model (label spreading) were established to evaluate the diagnostic value of biomarkers. Among the six supervised models, the support vector machine (SVM) algorithm was the most effective one according to calculated performance metrics, including 0.93 and 0.99 area under the curve (AUC) scores on the test and external validation datasets, respectively. Furthermore, the semi-supervised model could also successfully learn and predict sample types, achieving a 0.986 AUC score on the EV dataset, even when 10% samples in the five GEO datasets were labeled. In conclusion, three hub genes (ATP4A, ATP4B, and ESRRG) closely related to gastric cancer were mined, based on which the ML diagnostic model of gastric cancer was conducted.

MALDI-TOF/MS Analysis of Extracellular Vesicles Released by Cancer Cells

The direct shedding of extracellular vesicles (EVs) from the plasma membrane is a recognized fundamental method for the intercellular transfer of properties in both physiological and pathological conditions. EVs are classified according to origin, biogenesis, size, content, surface markers, and/or functional properties, and contain various bioactive molecules depending on the physiological state and the type of the cells of origin including lipids, nucleic acids, and proteins. The presence of tumor-derived EVs in body fluids such as blood, ascites, urine, and saliva, together with the important role played in the tumor microenvironment where they intervene at different levels from oncogenesis to metastasis, make EVs a priority target for cancer studies. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) can play a leading role in the analysis and characterization of EVs and their load due to its intrinsic advantages such as high throughput, low sample consumption, speed, the cost-effectiveness of the analysis, and the ease of use. This work reviews the main MALDI-TOF applications for the analysis and characterization of extracellular vesicles in the tumor field.

MALDI-TOF/MS Analysis of Non-Invasive Human Urine and Saliva Samples for the Identification of New Cancer Biomarkers

Cancer represents a group of heterogeneous diseases that are a leading global cause of death. Even though mortality has decreased in the past thirty years for different reasons, most patients are still diagnosed at the advanced stage, with limited therapeutic choices and poor outcomes. Moreover, the majority of cancers are detected using invasive painful methods, such as endoscopic biopsy, making the development of non-invasive or minimally invasive methods for the discovery and fast detection of specific biomarkers a crucial need. Among body fluids, a valuable non-invasive alternative to tissue biopsy, the most accessible and least invasive are undoubtedly urine and saliva. They are easily retrievable complex fluids containing a large variety of endogenous compounds that may provide information on the physiological condition of the body. The combined analysis of these fluids with matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF/MS), a reliable and easy-to-use instrumentation that provides information with relatively simple sample pretreatments, could represent the ideal option to rapidly achieve fast early stage diagnosis of tumors and their real-time monitoring. On this basis, the present review summarizes the recently reported applications relevant to the MALDI analysis of human urine and saliva samples.

A novel bioavailable curcumin-galactomannan complex modulates the genes responsible for the development of chronic diseases in mice: A RNA sequence analysis

BACKGROUND

Chronic diseases or non-communicable diseases are a major burden worldwide due to the lack of highly efficacious treatment modalities and the serious side effects associated with the available therapies.

PURPOSE/STUDY DESIGN

A novel self-emulsifying formulation of curcumin with fenugreek galactomannan hydrogel scaffold as a water-dispersible non-covalent curcumin-galactomannan molecular complex (curcumagalactomannosides, CGM) has shown better bioavailability than curcumin and can be used for the prevention and treatment of chronic diseases. However, the exact potential of this formulation has not been studied, which would pave the way for its use for the prevention and treatment of multiple chronic diseases.

METHODS

The whole transcriptome analysis (RNAseq) was used to identify differentially expressed genes (DEGs) in the liver tissues of mice treated with LPS to investigate the potential of CGM on the prevention and treatment of chronic diseases. Expression analysis using DESeq2 package, GO, and pathway analysis of the differentially expressed transcripts was performed using UniProtKB and KEGG-KAAS server.

RESULTS

The results showed that 559 genes differentially expressed between the liver tissue of control mice and CGM treated mice (100 mg/kg b.wt. for 14 days), with adjusted p-value below 0.05, of which 318 genes were significantly upregulated and 241 were downregulated. Further analysis showed that 33 genes which were upregulated (log2FC > 8) in the disease conditions were significantly downregulated, and 32 genes which were downregulated (log2FC < -8) in the disease conditions were significantly upregulated after the treatment with CGM.

CONCLUSION

Overall, our study showed CGM has high potential in the prevention and treatment of multiple chronic diseases.

Circular RNA-Related CeRNA Network and Prognostic Signature for Patients with Osteosarcoma

Introduction

Osteosarcoma (OSA) is characterized by its relatively high morbidity in children and adolescents. Patients usually have advanced disease at the time of diagnosis, resulting in poor outcomes. This study focused on building a circular RNA-based ceRNA network to develop a reliable model for OSA risk prediction.

Methods

We used the Gene Expression Omnibus (GEO) datasets to explore the expression patterns of circRNA, miRNA, and mRNA in OSA. The prognostic value of circRNA host genes was assessed with data from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database using Kaplan–Meier survival analysis. We established a circRNA-related ceRNA network and annotated its biological functions. Next, we developed a prognostic risk signature based on mRNAs extracted from the ceRNA network. We also developed a prognostic model and constructed a nomogram to enhance the prediction of OSA prognosis.

Results

We identified 166 DEcircRNAs, 233 DEmiRNAs, and 1317 DEmRNAs and used them to create a circRNA-related ceRNA network. We then established a prognostic risk model consisting of four genes (MLLT11, TNFRSF11B, SLC7A7, and PARVA). Moreover, we found that inhibition of MLLT11 and SLC7A7 blocked OSA cell proliferation and migration in in vitro experiments.

Conclusion

Our study identifies crucial prognostic genes and provides a circRNA-related ceRNA network for OSA, which will contribute to the elucidation of the molecular mechanisms underlying the oncogenesis and development of OSA.

The Prognosis and Immune Checkpoint Blockade Efficacy Prediction of Tumor-Infiltrating Immune Cells in Lung Cancer

Backgrounds

The high morbidity and mortality of lung cancer are serious public health problems. The prognosis of lung cancer and whether to apply immune checkpoint blockade (ICB) are currently urgent problems to be solved.

Methods

Using R software, we performed Kaplan–Meier (K-M) analysis, Cox regression analysis, functional enrichment analysis, Spearman correlation analysis, and the single-sample gene set enrichment analysis.

Results

On the Tumor IMmune Estimation Resource (TIMER2.0) website, we calculated the abundance of tumor-infiltrating immune cells (TIICs) of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. B cell and myeloid dendritic cell (DC1) were independent prognostic factors for LUAD and LUSC patients, respectively. Enrichment analysis confirmed that genes highly related to B cell or DC1 were closely related to the immune activation of lung cancer patients. In terms of adaptive immune resistance markers, CD8A, CD8B, immunomodulators (immunostimulants, major histocompatibility complex, receptors, and chemokines), immune-related pathways, tumor microenvironment score, and TIICs, high B cell/DC1 infiltration tissue was inflamed and immune-activated and might benefit more from the ICB. Genes most related to B cell [CD19, toll-like receptor 10 (TLR10), and Fc receptor-like A (FCRLA)] and DC1 (ITGB2, LAPTM5, and SLC7A7) partially clarified the roles of B cell/DC1 in predicting ICB efficacy. Among the 186 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, there were three and four KEGG pathways, which partially explained the molecular mechanisms by which B cell and DC1 simultaneously predicted the prognosis and efficacy of immunotherapy, respectively. Among five immune subtypes, the abundance of B cell/DC1 and expression of six hub genes were higher in immune C2, C3, and C6.

Conclusion

B cell and DC1 could predict the prognosis and ICB efficacy of LUAD and LUSC patients, respectively. The six hub genes and seven KEGG pathways might be novel immunotherapy targets. Immune C2, C3, and C6 subtypes of lung cancer patients might benefit more from ICB therapy.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.