POLE2 facilitates the malignant phenotypes of glioblastoma through promoting AURKA-mediated stabilization of FOXM1

Identification of estrogen response-associated STRA6+ granulosa cells within high-grade serous ovarian carcinoma by single-cell sequencing

Background

High-grade serous ovarian carcinoma (HGSOC) is a pathologic subtype of ovarian cancer (OC) with a more lethal prognosis. Extensive heterogeneity results in HGSOC being more susceptible to treatment resistance and adverse treatment effects. Revealing the heterogeneity involved is crucial.

Methods

We downloaded the single-cell RNA-seq (scRNA) data from GEO database and performed a scRNA analysis for cell landscape of HGSOC by using the Seurat package. The highly expressed genes were uploaded into the DAVID and KEGG database for enrichment analysis, and the AUCell package was used to calculate cancer-associated hallmark score. The SCENIC analysis was used for key regulons, the estrogen response enrichment scores in TCGA-OV RNA-seq dataset were calculated by using the GSVA package. Besides, the expression of STRA6 and IRF1 and the cell invasion and migration in si-STRA6 OC cells were detected by using the quantitative reverse transcription (qRT)-PCR method and Transwell assay respectively.

Results

We successfully constructed a single-cell atlas of HGSOC and delineated the heterogeneity of epithelial cells therein. There were five epithelial cell subpopulations, GLDC + Epithelial cells, PEG3+ leydig cells, STRA6+ granulosa cells, POLE2+ Epithelial cells, and AURKA + Epithelial cells. STRA6+ granulosa cells have the potential to promote tumor growth as well as the highest estrogen response early activity through the biological pathways analysis of highly expressed genes and estrogen response score of ssGSEA. We found that IRF1 and STRA6 expression was remarkably upregulated in the OC cancer cell line HEY. Silencing of STRA6 markedly decreased the invasion and migration ability of the OC cancer cell line HEY.

Conclusion

There is extreme heterogeneity of epithelial cells in HGSOC, and STRA6+ granulosa cells may be able to promote cancer progression. Our findings are benefit to the heterogeneity identification of HGSOC and develop targeted therapy strategy for HGSOC patients.

POLE2 knockdown suppresses lymphoma progression via downregulating Wnt/β-catenin signaling pathway

Lymphoma is the most common malignant tumor arising from immune system. Recently, DNA polymerase epsilon subunit 2 (POLE2) was identified to be a tumor promotor in a variety of malignant tumors. However, the biological role of POLE2 in lymphoma is still largely unclear. In our present study, the expression patterns of POLE2 in lymphoma tissues were identified by immunohistochemistry (IHC) staining of human tissue microarray. Cell viability was determined by CCK-8 assay. Cell apoptosis and cycle distribution were evaluated by Annexin V and PI staining, respectively. Cell migration was analyzed by transwell assay. Tumor growth in vivo was observed by a xenograft model of mice. The potential signaling was explored by human phospho-kinase array and immunoblotting. POLE2 was significantly upregulated in human lymphoma tissues and cells. POLE2 knockdown attenuated the proliferation, migration capabilities of lymphoma cells, as well as induced cell apoptosis and cycle arrest. Moreover, POLE2 depletion impaired the tumor growth in mice. Furthermore, POLE2 knockdown apparently inhibited the activation of β-Catenin and downregulated the expression of Wnt/β-Catenin signaling-related proteins. POLE2 knockdown suppressed the proliferation and migration of lymphoma cells by inhibiting Wnt/β-Catenin signaling pathway. POLE2 may serve as a novel therapeutic target for lymphoma.

Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance

Background: Bladder cancer (BLCA) is the most common genitourinary malignancy. Proliferation essential genes (PEGs) are crucial to the survival of cancer cells. This study aimed to build a PEG signature to predict BLCA prognosis and treatment efficacy. Methods: BLCA PEGs and differentially expressed PEGs were identified using DepMap and TCGA-BLCA datasets, respectively. Based on the prognostic analysis of the differentially expressed PEGs, a PEG model was constructed. Subsequently, we analyzed the relationship between the PEG signature and prognosis of BLCA patients as well as their response to chemotherapy. Finally, we performed random forest analysis to target and functional experiments to validate the most significant PEG which is associated with BLCA progression. CCK-8, invasion, migration, and chemosensitivity assays were performed to assess effects of gene knockdown on BLCA cell proliferation, invasion and migration abilities, and cisplatin chemosensitivity. Results: We screened 10 prognostic PEGs from 201 differentially expressed PEGs and used them to construct a PEG signature model. Patients with high PEG signature score (PEGs-high) exhibited worse OS and lower sensitivity to chemotherapy than those with PEGs-low. We also found significant correlations between the PEG score and previously defined BLCA molecular subtypes. This suggests that the PEG score may effectively predict the molecular subtypes which have distinct clinical outcomes. Random forest analysis revealed that POLE2 (DNA polymerase epsilon subunit 2) was the most significant PEG differentiating BLCA tissue and normal tissue. Bioinformatic analysis and an immunohistochemistry staining assay confirmed that POLE2 was significantly up-regulated in tumor tissues and was associated with poor survival in BLCA patients. Moreover, POLE2 knockdown inhibited the ability of cell clone formation, proliferation, invasion, immigration and IC50 of cisplatin. Conclusion: The PEG signature acts as a potential predictor for prognosis and chemotherapy response in BLCA patients. POLE2 is a key PEG and plays a remarkable role in promoting the malignant progression and cisplatin resistance of BLCA.

Myricetin, a natural inhibitor of CD147, increases sensitivity of cisplatin in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is the most lethal gynecological tumor, but it currently lacks effective therapeutic targets. CD147, which is overexpressed in OC, plays a crucial role in promoting malignant progression and is associated with poor prognosis in patients. Therefore, CD147 has been identified as a potential therapeutic target. However, there is a limited amount of research on the development of CD147 inhibitors.

METHODS

Surface plasmon resonance (SPR) assay and virtual molecular docking analysis were performed to identify potential natural compounds targeting CD147. The anti‑tumor effects of myricetin were evaluated using various assays, including CCK8, Alkaline comet, immunofluorescence and xenograft mouse models. The underlying mechanism was investigated through western blot analysis and lentivirus short hairpin RNA (LV-shRNA) transfection.

RESULTS

Myricetin, a flavonoid commonly found in plants, was discovered to be a potent inhibitor of CD147. Our findings demonstrated that myricetin exhibited a strong affinity for CD147 and down-regulated the protein level of CD147 by facilitating its proteasome-dependent degradation. Additionally, we observed synergistic antitumor effects of myricetin and cisplatin both in vivo and in vitro. Mechanistically, myricetin suppressed the expression of FOXM1 and its downstream DNA damage response (DDR) genes E×O1and BRIP1, thereby enhancing the DDR induced by cisplatin.

CONCLUSION

Our data demonstrate that myricetin, a natural inhibitor of CD147, may have clinical utility in the treatment of OC due to its ability to increase genomic toxicity when combined with cisplatin.

Inhibition of ferroptosis by POLE2 in gastric cancer cells involves the activation of NRF2/GPX4 pathway

Gastric cancer results in great cancer mortality worldwide, and inducing ferroptosis dramatically improves the malignant phenotypes of gastric cancer. DNA polymerase epsilon subunit 2 (POLE2) plays indispensable roles in tumorigenesis; however, its involvement and molecular basis in ferroptosis and gastric cancer are not clear. Human gastric cancer cells were infected with lentiviral vectors to knock down or overexpress POLE2, and cell ferroptosis was detected. To further validate the involvement of nuclear factor erythroid 2-related factor 2 (NRF2) and glutathione peroxidase 4 (GPX4), lentiviral vectors were used. POLE2 expression was elevated in human gastric cancer cells and tissues and closely correlated with clinicopathological features in gastric cancer patients. POLE2 knockdown was induced, while POLE2 overexpression inhibited ferroptosis of human gastric cancer cells, thereby modulating the malignant phenotypes of gastric cancer. Mechanistic studies revealed that POLE2 overexpression elevated NRF2 expression and activity and subsequently activated GPX4, which then prevented lipid peroxidation and ferroptosis in human gastric cancer cells. In contrast, either NRF2 or GPX4 silence significantly prevented POLE2 overexpression-mediated inductions of cell proliferation, migration, invasion and inhibition of ferroptosis. POLE2 overexpression inhibits ferroptosis in human gastric cancer cells through activating NRF2/GPX4 pathway, and inhibiting POLE2 may be a crucial strategy to treat gastric cancer.

Selinexor Synergistically Promotes the Antileukemia Activity of Venetoclax in Acute Myeloid Leukemia by Inhibiting Glycolytic Function and Downregulating the Expression of DNA Replication Genes

Introduction

The BCL-2 inhibitor venetoclax has been widely used in the treatment of acute myeloid leukemia (AML); however, AML patients treated with venetoclax gradually develop resistance. The exportin-1 (XPO1) inhibitor selinexor can synergistically promote the antileukemia activity of venetoclax, but the mechanism remains unclear.

Methods and Results

Annexin V/7-aminoactinomycin D assays were used to examine the effects of a combination of venetoclax and selinexor (VEN+SEL) on AML cell lines and primary AML cells. RNA sequencing and oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) determinations by a Seahorse XF analyzer were employed to investigate the molecular mechanism of the toxicity of the VEN+SEL combination to AML cells. The cytotoxicity of NK cell combined with VEN+SEL combination was assessed in vitro using flow cytometry. VEN+SEL enhanced the apoptosis of AML cells (KG-1A and THP-1) and primary AML samples in vitro. The ECAR and OCR results demonstrated that the VEN+SEL combination significantly inhibited glycolytic function. RNA sequencing of THP-1 cells demonstrated that DNA replication-related genes were downregulated after treatment with the VEN+SEL combination.

Conclusion

This study indicated that selinexor can synergistically enhance the antileukemia activity of venetoclax in AML cells in vitro by inhibiting glycolytic function and downregulating DNA replication-related genes. Based on our experimental data, combining selinexor with venetoclax is an appropriate advanced treatment option for AML patients.

Construction and validation of a metabolism-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer

Tumor Metabolism is strongly correlated with prognosis. Nevertheless, the prognostic and therapeutic value of metabolic-associated genes in BCa patients has not been fully elucidated. First, in this study, metabolism-related differential expressed genes DEGs with prognostic value in BCa were determined. Through the consensus clustering algorithm, we identified two molecular clusters with significantly different clinicopathological features and survival prognosis. Next, a novel metabolism-related prognostic model was established. Its reliable predictive performance in BCa was verified by multiple external datasets. Multivariate Cox analysis exhibited that risk score were independent prognostic factors. Interestingly, GSEA enrichment analysis of GO, KEGG, and Hallmark gene sets showed that the biological processes and pathways associated with ECM and collagen binding in the high-risk group were significantly enriched. Notely, the model was also significantly correlated with drug sensitivity, immune cell infiltration, and immunotherapy efficacy prediction by the wilcox rank test and chi-square test. Based on the 7 immune infiltration algorithm, we found that Neutrophils, Myeloid dendritic cells, M2 macrophages, Cancer-associated fibroblasts, etc., were more concentrated in the high-risk group. Additionally, in the IMvigor210, GSE111636, GSE176307, or our Truce01 (registration number NCT04730219) cohorts, the expression levels of multiple model genes were significantly correlated with objective responses to anti-PD-1/anti-PD-L1 immunotherapy. Finally, the expression of interested model genes were verified in 10 pairs of BCa tissues and para-carcinoma tissues by the HPA and real-time fluorescent quantitative PCR. Altogether, the signature established and validated by us has high predictive power for the prognosis, immunotherapy responsiveness, and chemotherapy sensitivity of BCa.

Forkhead box transcription factors (FOXOs and FOXM1) in glioma: from molecular mechanisms to therapeutics

Glioma is the most aggressive and malignant type of primary brain tumor, comprises the majority of central nervous system deaths, and is categorized into different subgroups according to its histological characteristics, including astrocytomas, oligodendrogliomas, glioblastoma multiforme (GBM), and mixed tumors. The forkhead box (FOX) transcription factors comprise a collection of proteins that play various roles in numerous complex molecular cascades and have been discovered to be differentially expressed in distinct glioma subtypes. FOXM1 and FOXOs have been recognized as crucial transcription factors in tumor cells, including glioma cells. Accumulating data indicates that FOXM1 acts as an oncogene in various types of cancers, and a significant part of studies has investigated its function in glioma. Although recent studies considered FOXO subgroups as tumor suppressors, there are pieces of evidence that they may have an oncogenic role. This review will discuss the subtle functions of FOXOs and FOXM1 in gliomas, dissecting their regulatory network with other proteins, microRNAs and their role in glioma progression, including stem cell differentiation and therapy resistance/sensitivity, alongside highlighting recent pharmacological progress for modulating their expression.

LncRNA TIALD contributes to hepatocellular carcinoma metastasis via inducing AURKA lysosomal degradation

The N6-methyladenosine (m6A) RNA methyltransferase METTL16 is an emerging player in RNA modification landscape and responsible for the deposition of m6A in a few transcripts. AURKA (aurora kinase A) has been confirmed as an oncogene in cancer development including hepatocellular carcinoma (HCC). Nevertheless, it remains unclear whether METTL16 mediated m6A modification of lncRNAs can regulate AURKA activation in cancer progression. Here we aimed to investigate the functional links between lncRNAs and the m6A modification in AURKA signaling and HCC progression. Here we show that LncRNA TIALD (transcript that induced AURKA Lysosomal degradation) was down-regulated in HCC tissues by METTL16 mediated m6A methylation to facilitate its RNA degradation, and correlates with poor prognosis. Functional assays reveal that TIALD inhibits HCC metastasis both in vitro and in vivo. Mechanistically, TIALD directly interacts with AURKA and facilitate its degradation through the lysosomal pathway to inhibited EMT and metastasis of HCC. AURKA's specific inhibitor alisertib exerts effective therapeutic effect on liver cancer with low TIALD expression, which might provide a new insight into HCC therapy. Our study uncovers a negative functional loop of METTL16-TIALD-AURKA axis, and identifies a new mechanism for METTL16 mediated m6A-induced decay of TIALD on AURKA signaling in HCC progression, which may provide potential prognostic and therapeutic targets for HCC.

Identification and characterization of putative biomarkers and therapeutic axis in Glioblastoma multiforme microenvironment

Non-cellular secretory components, including chemokines, cytokines, and growth factors in the tumor microenvironment, are often dysregulated, impacting tumorigenesis in Glioblastoma multiforme (GBM) microenvironment, where the prognostic significance of the current treatment remains unsatisfactory. Recent studies have demonstrated the potential of post-translational modifications (PTM) and their respective enzymes, such as acetylation and ubiquitination in GBM etiology through modulating signaling events. However, the relationship between non-cellular secretory components and post-translational modifications will create a research void in GBM therapeutics. Therefore, we aim to bridge the gap between non-cellular secretory components and PTM modifications through machine learning and computational biology approaches. Herein, we highlighted the importance of BMP1, CTSB, LOX, LOXL1, PLOD1, MMP9, SERPINE1, and SERPING1 in GBM etiology. Further, we demonstrated the positive relationship between the E2 conjugating enzymes (Ube2E1, Ube2H, Ube2J2, Ube2C, Ube2J2, and Ube2S), E3 ligases (VHL and GNB2L1) and substrate (HIF1A). Additionally, we reported the novel HAT1-induced acetylation sites of Ube2S (K211) and Ube2H (K8, K52). Structural and functional characterization of Ube2S (8) and Ube2H (1) have identified their association with protein kinases. Lastly, our results found a putative therapeutic axis HAT1-Ube2S(K211)-GNB2L1-HIF1A and potential predictive biomarkers (CTSB, HAT1, Ube2H, VHL, and GNB2L1) that play a critical role in GBM pathogenesis.

Machine learning to improve interpretability of clinical, radiological and panel-based genomic data of glioma grade 4 patients undergoing surgical resection

BACKGROUND

Glioma grade 4 (GG4) tumors, including astrocytoma IDH-mutant grade 4 and the astrocytoma IDH wt are the most common and aggressive primary tumors of the central nervous system. Surgery followed by Stupp protocol still remains the first-line treatment in GG4 tumors. Although Stupp combination can prolong survival, prognosis of treated adult patients with GG4 still remains unfavorable. The introduction of innovative multi-parametric prognostic models may allow refinement of prognosis of these patients. Here, Machine Learning (ML) was applied to investigate the contribution in predicting overall survival (OS) of different available data (e.g. clinical data, radiological data, or panel-based sequencing data such as presence of somatic mutations and amplification) in a mono-institutional GG4 cohort.

METHODS

By next-generation sequencing, using a panel of 523 genes, we performed analysis of copy number variations and of types and distribution of nonsynonymous mutations in 102 cases including 39 carmustine wafer (CW) treated cases. We also calculated tumor mutational burden (TMB). ML was applied using eXtreme Gradient Boosting for survival (XGBoost-Surv) to integrate clinical and radiological information with genomic data.

RESULTS

By ML modeling (concordance (c)- index = 0.682 for the best model), the role of predicting OS of radiological parameters including extent of resection, preoperative volume and residual volume was confirmed. An association between CW application and longer OS was also showed. Regarding gene mutations, a role in predicting OS was defined for mutations of BRAF and of other genes involved in the PI3K-AKT-mTOR signaling pathway. Moreover, an association between high TMB and shorter OS was suggested. Consistently, when a cutoff of 1.7 mutations/megabase was applied, cases with higher TMB showed significantly shorter OS than cases with lower TMB.

CONCLUSIONS

The contribution of tumor volumetric data, somatic gene mutations and TBM in predicting OS of GG4 patients was defined by ML modeling.

Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment

Background: The only curative option for patients with locally or locally advanced adrenocortical carcinoma is primary tumor curative sexual resection (ACC). However, overall survival remains low, with most deaths occurring within the first 2 years following surgery. The 5-year survival rate after surgery is less than 30%. As a result, more accurate prognosis-related predictive biomarkers must be investigated urgently to detect patients' disease status after surgery. Methods: Data from FerrDb were obtained to identify ferroptosis-related genes, and ACC gene expression profiles were collected from the GEO database to find differentially expressed ACC ferroptosis-related genes using differential expression analysis. The DEFGs were subjected to Gene Ontology gene enrichment analysis and KEGG signaling pathway enrichment analysis. PPI network building and predictive analysis were used to filter core genes. The expression of critical genes in ACC pathological stage and pan-cancer was then investigated. In recent years, immune-related factors, DNA repair genes, and methyltransferase genes have been employed in diagnosing and prognosis of different malignancies. Cancer cells are mutated due to DNA repair genes, and highly expressed DNA repair genes promote cancer. Dysregulation of methyltransferase genes and Immune-related factors, which are shown to be significantly expressed in numerous malignancies, also plays a crucial role in cancer. As a result, we investigated the relationship of AURKA with immunological checkpoints, DNA repair genes, and methyltransferases in pan-cancer. Result: The DEGs found in the GEO database were crossed with ferroptosis-related genes, yielding 42 differentially expressed ferroptosis-related genes. Six of these 42 genes, particularly AURKA, are linked to the prognosis of ACC. AURKA expression was significantly correlated with poor prognosis in patients with multiple cancers, and there was a significant positive correlation with Th2 cells. Furthermore, AURKA expression was positively associated with tumor immune infiltration in Lung adenocarcinoma (LUAD), Liver hepatocellular carcinoma (LIHC), Sarcoma (SARC), Esophageal carcinoma (ESCA), and Stomach adenocarcinoma (STAD), but negatively correlated with the immune score, matrix score, and calculated score in these tumors. Further investigation into the relationship between AURKA expression and immune examination gene expression revealed that AURKA could control the tumor-resistant pattern in most tumors by regulating the expression level of specific immune examination genes. Conclusion: AURKA may be an independent prognostic marker for predicting ACC patient prognosis. AURKA may play an essential role in the tumor microenvironment and tumor immunity, according to a pan-cancer analysis, and it has the potential to be a predictive biomarker for multiple cancers.

A Novel Prognostic Signature Associated With the Tumor Microenvironment in Kidney Renal Clear Cell Carcinoma

Background

The tumor microenvironment (TME) is a complex and evolving environment, and the tumor immune microenvironment in kidney renal clear cell carcinoma (KIRC) has a strong suppressive profile. This study investigates the potential prognostic role and value of genes of the tumor microenvironment in KIRC.

Methods

The transcriptome sequencing data of 530 cases and 39 cases of KIRC and the corresponding clinical prognosis information were downloaded from TCGA data and GEO data, respectively, and TME-related gene expression profiles were extracted. A prognostic signature was constructed and evaluated using univariate Cox regression analysis and LASSO regression analysis. Gene set enrichment analysis (GSEA) was used to obtain the biological process of gene enrichment in patients with high and low-risk groups.

Results

A prognostic signature consisting of eight TME-related genes (LRFN1, CSF1, UCN, TUBB2B, SERPINF1, ADAM8, ABCB4, CCL22) was constructed. Kaplan-Meier survival analysis yielded significantly lower survival times for patients in the high-risk group than in the low-risk group, and the AUC values for the ROC curves of this prognostic signature were essentially greater than 0.7, and univariate and multifactorial Cox regression analyses indicated that the risk score was independent risk factors for KIRC prognosis. GSEA analysis showed that immune-related biological processes were enriched in the high-risk group and that risk values were strongly associated with multiple immune cell scores and immune checkpoint-related genes (PDCD1, CTLA4).

Conclusions

The prognostic signature can accurately predict the prognosis of KIRC patients, which may provide new ideas for future precision immunotherapy of KIRC.