CINP is a novel cofactor of KLF5 required for its role in the promotion of cell proliferation, survival and tumor growth

Systematic Analysis of Tumor Stem Cell-related Gene Characteristics to Predict the PD-L1 Immunotherapy and Prognosis of Gastric Cancer

AIMS

We aimed to develop a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in gastric cancer (GC).

BACKGROUND

Tumor stemness is related to intratumoral heterogeneity, immunosuppression, and anti-tumor resistance. We developed a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in GC.

OBJECTIVE

We aimed to develop a prognostic model with stemness-correlated genes to evaluate prognosis and immunotherapy responsiveness in GC.

METHODS

We downloaded single-cell RNA sequencing (scRNA-seq) data of GC patients from the Gene-Expression Omnibus (GEO) database and screened GC stemness- related genes using CytoTRACE. We characterized the association of tumor stemness with immune checkpoint blockade (ICB) and immunity. Thereafter, a 9-stemness signature-based prognostic model was developed using weighted gene co-expression network analysis (WGCNA), univariate Cox regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis. The model predictive value was evaluated with a nomogram.

RESULTS

Early GC patients had significantly higher levels of stemness. The stemness score showed a negative relationship to tumor immune dysfunction and exclusion (TIDE) score and immune infiltration, especially T cells and B cells. A stemness-based signature based on 9 genes (ERCC6L, IQCC, NKAPD1, BLMH, SLC25A15, MRPL4, VPS35, SUMO3, and CINP) was constructed with good performance in prognosis prediction, and its robustness was validated in GSE26942 cohort. Additionally, nomogram and risk score exhibited the most powerful ability for prognosis prediction. High-risk patients exhibited a tendency to develop immune escape and low response to PD-L1 immunotherapy.

CONCLUSION

We developed a stemness-based gene signature for prognosis prediction with accuracy and reliability. This signature also helps clinical decision-making of immunotherapy for GC patients.

Promoter-Specific Variants in NeuroD1 and H3K4me3 Coincident Regions and Clinical Outcomes of Small Cell Lung Cancer

BACKGROUND

Neurogenic differentiation 1 (NeuroD1) is a representative small cell lung cancer (SCLC) transcription regulator involved in the carcinogenesis and behavior of SCLC. Histone modifications play an important role in transcription, and H3 lysine 4 trimethylation (H3K4me3) is primarily associated with promoter regions.

METHODS

We investigated the association between single nucleotide polymorphisms (SNPs) in NeuroD1 and H3K4me3 coincident regions, selected using ChIP sequencing (ChIP-seq), and the clinical outcomes of 261 patients with SCLC.

RESULTS

Among 230 SNPs, two were significantly associated with both the chemotherapy response and overall survival (OS) of patients with SCLC. RNF145 rs2043268A>G was associated with worse chemotherapy response and OS (under a recessive model, adjusted odds ratio [aOR], 0.50, 95% confidence interval [CI], 0.26-0.94, P = 0.031, and adjusted hazard ratio [aHR], 1.88, 95% CI, 1.38-2.57, P < 0.001). CINP rs762105A>G was also associated with worse chemotherapy response and OS (under a dominant model, aOR, 0.47, 95% CI, 0.23-0.99, P = 0.046, and aHR, 2.03, 95% CI, 1.47-2.82, P < 0.001). ChIP-quantitative polymerase chain reaction and luciferase assay confirmed that the two SNPs were located in the active promoter regions and influenced the promoter activity of each gene.

CONCLUSION

To summarize, among SNPs selected using ChIP-seq in promoter regions with high peaks in both NeuroD1 and H3K4me3, RNF145 rs2043268A>G and CINP rs762105A>G were associated with clinical outcomes in patients with SCLC and also affected the promoter activity of each gene.

siAKR1C3@PPA complex nucleic acid nanoparticles inhibit castration-resistant prostate cancer in vitro

Introduction

AKR1C3, as a crucial androgenic enzyme, implicates the androgen biosynthesis and promoting prostate cancer cell growth in vitro. This study provides a new gene therapy strategy for targeting AKR1C3 to treat castration-resistant prostate cancer.

Methods

siAKR1C3@PPA is assembled from PEG3500, PAMAM, Aptamer-PSMA, and siRNA for AKR1C3. We analyzed the relationship between AKR1C3 expression and the survival rate of prostate cancer patients based on the GEPIA online database to perform disease-free survival, and found that AKR1C3 may be an important factor leading to poor prognosis in prostate cancer. Considering AKR1C3 as a therapeutic target for castration-resistant prostate cancer, we constructed a complex nucleic acid nanoparticle, siAKR1C3@PPA to investigate the inhibitory effect on castration-resistant prostate cancer.

Results

Aptamer-PSMA acts as a target to guide siAKR1C3@PPA into PSMA-positive prostate cancer cells and specifically down regulate AKR1C3. Cyclin D1 was decreased as a result of siAKR1C3@PPA treatment. Changes in Cyclin D1 were consistent with decreased expression of AKR1C3 in LNCaP-AKR1C3 cells and 22RV1 cells. Furthermore, in the LNCaP-AKR1C3 group, 1070 proteins were upregulated and 1015 proteins were downregulated compared to the LNCaP group according to quantitative 4D label-free proteomics. We found 42 proteins involved in cell cycle regulation. In a validated experiment, we demonstrated that PCNP and CINP were up-regulated, and TERF2 and TP53 were down-regulated by western blotting.

Conclusion

We concluded that siAKR1C3@PPA may arrest the cell cycle and affect cell proliferation.

Krüppel-like factor 5 regulates wound repair and the innate immune response in human airway epithelial cells

A complex network of transcription factors regulates genes involved in establishing and maintaining key biological properties of the human airway epithelium. However, detailed knowledge of the contributing factors is incomplete. Here we characterize the role of Krüppel-like factor 5 (KLF5), in controlling essential pathways of epithelial cell identity and function in the human lung. RNA-seq following siRNA-mediated depletion of KLF5 in the Calu-3 lung epithelial cell line identified significant enrichment of genes encoding chemokines and cytokines involved in the proinflammatory response and also components of the junctional complexes mediating cell adhesion. To determine direct gene targets of KLF5, we defined the cistrome of KLF5 using ChIP-seq in both Calu-3 and 16HBE14o⁻ lung epithelial cell lines. Occupancy site concordance analysis revealed that KLF5 colocalized with the active histone modification H3K27ac and also with binding sites for the transcription factor CCAAT enhancer-binding protein beta (C/EBPβ). Depletion of KLF5 increased both the expression and secretion of cytokines including IL-1β, a response that was enhanced following exposure to Pseudomonas aeruginosa lipopolysaccharide. Calu-3 cells exhibited faster rates of repair after KLF5 depletion compared with negative controls in wound scratch assays. Similarly, CRISPR-mediated KLF5-null 16HBE14o⁻ cells also showed enhanced wound closure. These data reveal a pivotal role for KLF5 in coordinating epithelial functions relevant to human lung disease.

The roles and regulation of the KLF5 transcription factor in cancers

Krüppel‐like factor 5 (KLF5) is a member of the KLF family. Recent studies have suggested that KLF5 regulates the expression of a large number of new target genes and participates in diverse cellular functions, such as stemness, proliferation, apoptosis, autophagy, and migration. In response to multiple signaling pathways, various transcriptional modulation and posttranslational modifications affect the expression level and activity of KLF5. Several transgenic mouse models have revealed the physiological and pathological functions of KLF5 in different cancers. Studies of KLF5 will provide prognostic biomarkers, therapeutic targets, and potential drugs for cancers.

Derivation and Validation of a Prognostic Model for Cancer Dependency Genes Based on CRISPR-Cas9 in Gastric Adenocarcinoma

As a CRISPR-Cas9-based tool to help scientists to investigate gene functions, Cancer Dependency Map genes (CDMs) include an enormous series of loss-of-function screens based on genome-scale RNAi. These genes participate in regulating survival and growth of tumor cells, which suggests their potential as novel therapeutic targets for malignant tumors. By far, studies on the roles of CDMs in gastric adenocarcinoma (GA) are scarce and only a small fraction of CDMs have been investigated. In the present study, datasets of the differentially expressed genes (DEGs) were extracted from the TCGA-based (The Cancer Genome Atlas) GEPIA database, from which differentially expressed CDMs were determined. Functions and prognostic significance of these verified CDMs were evaluated using a series of bioinformatics methods. In all, 246 differentially expressed CDMs were determined, with 147 upregulated and 99 downregulated. Ten CDMs (ALG8, ATRIP, CCT6A, CFDP1, CINP, MED18, METTL1, ORC1, TANGO6, and PWP2) were identified to be prognosis-related and subsequently a prognosis model based on these ten CDMs was constructed. In comparison with that of patients with low risk in TCGA training, testing and GSE84437 cohort, overall survival (OS) of patients with high risk was significantly worse. It was then subsequently demonstrated that for this prognostic model, area under the ROC (receiver operating characteristic) curve was 0.771 and 0.697 for TCGA training and testing cohort respectively, justifying its reliability in predicting survival of GA patients. With the ten identified CDMs, we then constructed a nomogram to generate a clinically practical model. The regulatory networks and functions of the ten CDMs were then explored, the results of which demonstrated that as the gene significantly associated with survival of GA patients and Hazard ratio (HR), PWP2 promoted in-vitro invasion and migration of GA cell lines through the EMT signaling pathway. Therefore, in conclusion, the present study might help understand the prognostic significance and molecular functions of CDMs in GA.

Elevated Heterogeneous Nuclear Ribonucleoprotein C Expression Correlates With Poor Prognosis in Patients With Surgically Resected Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD), as the most common histological subtype of lung cancer, is a high-grade malignancy and a leading cause of cancer-related death globally. Identification of biomarkers with prognostic value is of great significance for the diagnosis and treatment of LUAD. Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an RNA-binding protein “reader” of N6-methyladenosine (m⁶A) methylation, and is related to the progression of various cancers; however, its role in LUAD is unclear. The aims of this study aims were to study the expression and prognostic value of HNRNPC in LUAD.

Methods

The Oncomine database and gene expression profiling interactive analysis (GEPIA) were used for preliminary exploration of HNRNPC expression and prognostic value in LUAD. LUAD cases from The Cancer Genome Atlas (TCGA) (n = 416) and the Kaplan-Meier plotter database (n = 720) were extracted to study the differential expression and prognostic value of HNRNPC. HNRNPC expression in the National Cancer Center of China (NCC) cohort was analyzed by immunohistochemical staining, and the relationship between HNRNPC expression and survival rate evaluated using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. Several pathways that were significantly enriched in the HNRNPC high expression group were identified by Gene Set Enrichment Analysis (GSEA).

Results

Five data sets from the Oncomine and GEPIA databases all supported that HNRNPC expression is significantly higher in LUAD than in normal lung tissue. In TCGA cohort, HNRNPC was highly expressed in LUAD tissues and significantly related to age, sex, smoking history, ethnicity, lymph node metastasis, and TNM staging (P < 0.001). High HNRNPC expression was significantly correlated with poor prognosis in the three cohorts (NCC, TCGA, and K-M plotter) (P < 0.05). Multivariate Cox regression analysis showed that HNRNPC expression was an independent prognostic factor in both TCGA and NCC cohorts (P < 0.05). Further, 10 significantly enriched pathways were identified from TCGA data and 118 lung cancer cell lines in CCLE, respectively.

Conclusions

High HNRNPC expression is significantly related to poor overall survival in patients with LUAD, suggesting that HNRNPC may be a cancer-promoting factor and a potential prognostic biomarker in LUAD.

Development of prognostic signature based on immune-related genes in muscle-invasive bladder cancer: bioinformatics analysis of TCGA database

Background: Muscle-invasive bladder cancer (MIBC) with high tumor stages accounts for most bladder cancer patient mortality. Platinum-based chemotherapy provides insufficient survival benefits; however, immunotherapy is a promising option for MIBC.

Results: There were 31 differentially expressed IRGs that significantly correlated with the clinical outcomes of MIBC patients. A prognostic signature based on 12 IRGs (MMP9, RBP7, ADIPOQ, AHNAK, OAS1, RAC3, SLIT2, EDNRA, IL34, PDGFD, PPY, IL17RD) performed moderately in prognostic predictions with area under the curve (AUC) equal to 0.76. The high-risk patient group presented worse survival outcomes (hazard ratio 1.197, 95% confidence interval 1.103–1.299, p < 0.001). Furthermore, immune cell infiltration analysis showed increased tumor infiltration of macrophages in the high-risk group.

Conclusion: This novel prognostic signature can effectively divide MIBC patients into different risk groups, allowing for intensive treatment of high-risk individuals who have worse predicted survival outcomes.

Methods: Bioinformatics analyses were conducted using the Cancer Genome Atlas (TCGA) database. Differentially expressed genes and survival-associated immune-related genes (IRGs) were analyzed through a computational algorithm and Cox regression. The potential mechanisms of IRG expression were explored with transcription factors, and a prognosis classification based on IRG expression was developed to stratify patients into distinct risk groups.

Metapristone (RU486-derivative) inhibits endometrial cancer cell progress through regulating miR-492/Klf5/Nrf1 axis

Background

Endometrial cancer is an invasive gynecological cancer prevalent in the world. The pathogenesis of endometrial cancer is related to multiple levels of regulation, referring to oestrogen, tumor-suppressor gene (e.g. PTEN) or microRNAs (e.g. miR-23a and miR-29b). Metapristone is a hormone-related drug, which is widely used in clinical treatment of endometrial cancer. However, the underlying regulatory mechanism of metapristone on endometrial cancer is still unclear, especially the regulatory effect on microRNAs. The aim of this study is to investigate the specific molecular mechanism of metapristone regulating microRNAs in the treatment of endometrial cancer.

Methods

RL95-2 cells and Ishikawa cells were used as the endometrial cancer models. MiR-492 or si-miR-492 was transfected into RL95-2 cells and Ishikawa cells to explore the role of miR-492 in endometrial cancer. The cell cancer model and mice cancer model were used to confirm the function and mechanism of metapristone affected on endometrial cancer in vitro and in vivo. Mechanically, cell proliferation was monitored using MTT assay, cell colony formation assay and EdU assay. Luciferase reporter assay was used to identify the downstream target gene of miR-492. The protein expression and RNA expression were respectively measured by western blot and qRT-PCR for cell signaling pathway research, subsequently, were verified in the mice tumor model via immunohistochemistry.

Results

Metapristone as a kind of hormone-related drug significantly inhibited the endometrial cancer cell growth through regulating cell apoptosis-related gene expression. Mechanically, miR-492 and its target genes Klf5 and Nrf1 were highly expressed in the endometrial cancer cell lines, which promoted cell proliferation and inhibited cell apoptosis. Metapristone decreased the expression of miR-492 and its target genes Klf5 and Nrf1, leading to endometrial cancer cell growth inhibition in vitro and in vivo.

Conclusion

Metapristone inhibited the endometrial cancer cell growth through regulating the cell apoptosis-related signaling pathway and decreasing the expression of miR-492 and its downstream target genes (Klf5 and Nrf1), which provided the theoretical basis in clinical treatment of endometrial cancer.

Identification of a novel immune microenvironment signature predicting survival and therapeutic options for bladder cancer

Few studies have investigated the potential of tumor immune microenvironment genes as indicators of urinary bladder cancer. Here, we sought to establish an immune-related gene signature for determining prognosis and treatment options. We developed a ten-gene tumor immune microenvironment signature and evaluated its prognostic capacity on internal and external cohorts. Multivariate Cox regression and nomogram analyses revealed the prognostic risk model as an independent and effective indicator of prognosis. We observed lower proportions of CD8+ T cells, dendritic cells, regulatory T cells, higher proportions of macrophages and neutrophils in high UBC risk group. UBC tissues with high-risk score tend to exhibit high TP53 and RB1 mutation rates, high PD1/PD-L1 expression and poor-survival basal squamous subtypes, while those with low-risk score tend to have high FGFR3 mutation rates and luminal papillary subtypes. Unexpectedly, we found a highly significant positive correlation between glycolytic genes and risk score, highlighting metabolic competition in tumor ecosystem and potential therapeutic avenues. Our study thus revealed a tumor immune microenvironment signature for predicting prognostic and response to immune checkpoint inhibitors against bladder cancer. Prospective studies are required to further test the predictive capacity of this model.

Identification and Validation of an Individualized Prognostic Signature of Bladder Cancer Based on Seven Immune Related Genes

BACKGROUND

There has been no report of prognostic signature based on immune-related genes (IRGs). This study aimed to develop an IRG-based prognostic signature that could stratify patients with bladder cancer (BLCA).

METHODS

RNA-seq data along with clinical information on BLCA were retrieved from the Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO). Based on TCGA dataset, differentially expressed IRGs were identified via Wilcoxon test. Among these genes, prognostic IRGs were identified using univariate Cox regression analysis. Subsequently, we split TCGA dataset into the training (n = 284) and test datasets (n = 119). Based on the training dataset, we built a least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression model with multiple prognostic IRGs. It was validated in the training dataset, test dataset, and external dataset GSE13507 (n = 165). Additionally, we accessed the six types of tumor-infiltrating immune cells from Tumor Immune Estimation Resource (TIMER) website and analyzed the difference between risk groups. Further, we constructed and validated a nomogram to tailor treatment for patients with BLCA.

RESULTS

A set of 47 prognostic IRGs was identified. LASSO regression and identified seven BLCA-specific prognostic IRGs, i.e., RBP7, PDGFRA, AHNAK, OAS1, RAC3, EDNRA, and SH3BP2. We developed an IRG-based prognostic signature that stratify BLCA patients into two subgroups with statistically different survival outcomes [hazard ratio (HR) = 10, 95% confidence interval (CI) = 5.6-19, P < 0.001]. The ROC curve analysis showed acceptable discrimination with AUCs of 0.711, 0.754, and 0.772 at 1-, 3-, and 5-year follow-up respectively. The predictive performance was validated in the train set, test set, and external dataset GSE13507. Besides, the increased infiltration of CD4+ T cells, CD8+ T cells, macrophage, neutrophil, and dendritic cells in the high-risk group (as defined by the signature) indicated chronic inflammation may reduce the survival chances of BLCA patients. The nomogram demonstrated to be clinically-relevant and effective with accurate prediction and positive net benefit.

CONCLUSION

The present immune-related signature can effectively classify BLCA patients into high-risk and low-risk groups in terms of survival rate, which may help select high-risk BLCA patients for more intensive treatment.

An RNAi Screen for Genes Required for Growth of Drosophila Wing Tissue

Cell division and tissue growth must be coordinated with development. Defects in these processes are the basis for a number of diseases, including developmental malformations and cancer. We have conducted an unbiased RNAi screen for genes that are required for growth in the Drosophila wing, using GAL4-inducible short hairpin RNA (shRNA) fly strains made by the Drosophila RNAi Screening Center. shRNA expression down the center of the larval wing disc using dpp-GAL4, and the central region of the adult wing was then scored for tissue growth and wing hair morphology. Out of 4,753 shRNA crosses that survived to adulthood, 18 had impaired wing growth. FlyBase and the new Alliance of Genome Resources knowledgebases were used to determine the known or predicted functions of these genes and the association of their human orthologs with disease. The function of eight of the genes identified has not been previously defined in Drosophila The genes identified included those with known or predicted functions in cell cycle, chromosome segregation, morphogenesis, metabolism, steroid processing, transcription, and translation. All but one of the genes are similar to those in humans, and many are associated with disease. Knockdown of lin-52, a subunit of the Myb-MuvB transcription factor, or βNACtes6, a gene involved in protein folding and trafficking, resulted in a switch from cell proliferation to an endoreplication growth program through which wing tissue grew by an increase in cell size (hypertrophy). It is anticipated that further analysis of the genes that we have identified will reveal new mechanisms that regulate tissue growth during development.