Systematic expression analysis of WEE family kinases reveals the importance of PKMYT1 in breast carcinogenesis

Three-dimensional chromatin landscapes in hepatocellular carcinoma associated with hepatitis B virus

BACKGROUND

Three-dimensional (3D) chromatin architecture frequently altered in cancer. However, its changes during the pathogenesis of hepatocellular carcinoma (HCC) remained elusive.

METHODS

Hi-C and RNA-seq were applied to study the 3D chromatin landscapes and gene expression of HCC and ANHT. Hi-C Pro was used to generate genome-wide raw interaction matrices, which were normalized via iterative correction (ICE). Moreover, the chromosomes were divided into different compartments according to the first principal component (E1). Furthermore, topologically associated domains (TADs) were visualized via WashU Epigenome Browser. Furthermore, differential expression analysis of ANHT and HCC was performed using the DESeq2 R package. Additionally, dysregulated genes associated with 3D genome architecture altered were confirmed using TCGA, qRT-PCR, immunohistochemistry (IHC), etc. RESULTS: First, the intrachromosomal interactions of chr1, chr2, chr5, and chr11 were significantly different, and the interchromosomal interactions of chr4-chr10, chr13-chr21, chr15-chr22, and chr16-chr19 are remarkably different between ANHT and HCC, which resulted in the up-regulation of TP53I3 and ZNF738 and the down-regulation of APOC3 and APOA5 in HCC. Second, 49 compartment regions on 18 chromosomes have significantly switched (A-B or B-A) during HCC tumorigenesis, contributing to up-regulation of RAP2A. Finally, a tumor-specific TAD boundary located on chr5: 6271000-6478000 and enhancer hijacking were identified in HCC tissues, potentially associated with the elevated expression of MED10, whose expression were associated with poor prognosis of HCC patients.

CONCLUSION

This study demonstrates the crucial role of chromosomal structure variation in HCC oncogenesis and potential novel biomarkers of HCC, laying a foundation for cancer precision medicine development.

Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification

BACKGROUND

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

MATERIALS AND METHODS

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the identified genes as breast cancer biomarkers.

RESULTS

The study identified four overexpressed genes (CACNG4, PKMYT1, EPYC, and CHRNA6) among 100 genes with higher importance scores. qRT-PCR analysis confirmed the significant upregulation of these genes in breast cancer patients compared to normal samples.

CONCLUSIONS

These findings suggest that CACNG4, PKMYT1, EPYC, and CHRNA6 may serve as valuable biomarkers for breast cancer diagnosis, and PKMYT1 may also have prognostic significance. Furthermore, CACNG4, CHRNA6, and PKMYT1 show promise as potential therapeutic targets. These findings have the potential to advance diagnostic methods and therapeutic approaches for breast cancer.

PKMYT1 induced by YAP/TEAD1 gives rise to the progression and worse prognosis of bladder cancer

Protein kinase, membrane-associated tyrosine/threonine 1 (PKMYT1), which is associated with progression of tumor, is upregulated in a variety of cancers. However, its expression and the underlying molecular mechanisms in the context of bladder cancer (BLCA) remain elusive. Here we found that PKMYT1 expression was markedly higher expression in BLCA, which was correlated with poorer prognosis compared with low expression. Knockdown of PKMYT1 significantly inhibited the BLCA cells proliferation in vivo and in vitro, and migration and invasion, reduced G2/M phase in cell cycle and induced apoptosis. Mechanically, YAP and TEAD1 knockdown suppressed PKMYT1 expression in BLCA cells, whereas overexpression of YAP upregulated PKMYT1 expression and YAP prompted PKMYT1 transcriptional expression via TEAD1-mediated direct binding to PKMYT1 promotor. Collectively, these findings suggest that PKMYT1, functioning as a direct gene target regulated by YAP/TEAD1, could serve as a potential indicator of progression and prognosis in BLCA. Further, PKMYT1 could serve as a novel therapeutic target for BLCA.

BrcaDx: precise identification of breast cancer from expression data using a minimal set of features

Background: Breast cancer is the foremost cancer in worldwide incidence, surpassing lung cancer notwithstanding the gender bias. One in four cancer cases among women are attributable to cancers of the breast, which are also the leading cause of death in women. Reliable options for early detection of breast cancer are needed. Methods: Using public-domain datasets, we screened transcriptomic profiles of breast cancer samples, and identified progression-significant linear and ordinal model genes using stage-informed models. We then applied a sequence of machine learning techniques, namely, feature selection, principal components analysis, and k-means clustering, to train a learner to discriminate "cancer" from "normal" based on expression levels of identified biomarkers. Results: Our computational pipeline yielded an optimal set of nine biomarker features for training the learner, namely, NEK2, PKMYT1, MMP11, CPA1, COL10A1, HSD17B13, CA4, MYOC, and LYVE1. Validation of the learned model on an independent test dataset yielded a performance of 99.5% accuracy. Blind validation on an out-of-domain external dataset yielded a balanced accuracy of 95.5%, demonstrating that the model has effectively reduced the dimensionality of the problem, and learnt the solution. The model was rebuilt using the full dataset, and then deployed as a web app for non-profit purposes at: https://apalania.shinyapps.io/brcadx/. To our knowledge, this is the best-performing freely available tool for the high-confidence diagnosis of breast cancer, and represents a promising aid to medical diagnosis.

Transcriptome analysis reveals differences in cell cycle, growth and migration related genes that distinguish fibroblasts derived from pre-invasive and invasive breast cancer

Background/Introduction

As the most common form of pre-invasive breast cancer, ductal carcinoma in situ (DCIS) affects over 50,000 women in the US annually. Despite standardized treatment involving lumpectomy and radiation therapy, up to 25% of patients with DCIS experience disease recurrence often with invasive ductal carcinoma (IDC), indicating that a subset of patients may be under-treated. As most DCIS cases will not progress to invasion, many patients may experience over-treatment. By understanding the underlying processes associated with DCIS to IDC progression, we can identify new biomarkers to determine which DCIS cases may become invasive and improve treatment for patients. Accumulation of fibroblasts in IDC is associated with disease progression and reduced survival. While fibroblasts have been detected in DCIS, little is understood about their role in DCIS progression.

Goals

We sought to determine 1) whether DCIS fibroblasts were similar or distinct from normal and IDC fibroblasts at the transcriptome level, and 2) the contributions of DCIS fibroblasts to breast cancer progression.

Methods

Fibroblasts underwent transcriptome profiling and pathway analysis. Significant DCIS fibroblast-associated genes were further analyzed in existing breast cancer mRNA databases and through tissue array immunostaining. Using the sub-renal capsule graft model, fibroblasts from normal breast, DCIS and IDC tissues were co-transplanted with DCIS.com breast cancer cells.

Results

Through transcriptome profiling, we found that DCIS fibroblasts were characterized by unique alterations in cell cycle and motility related genes such as PKMYT1, TGF-α, SFRP1 and SFRP2, which predicted increased cell growth and invasion by Ingenuity Pathway Analysis. Immunostaining analysis revealed corresponding increases in expression of stromal derived PKMYT1, TGF-α and corresponding decreases in expression of SFRP1 and SFRP2 in DCIS and IDC tissues. Grafting studies in mice revealed that DCIS fibroblasts enhanced breast cancer growth and invasion associated with arginase-1+ cell recruitment.

Conclusion

DCIS fibroblasts are phenotypically distinct from normal breast and IDC fibroblasts, and play an important role in breast cancer growth, invasion, and recruitment of myeloid cells. These studies provide novel insight into the role of DCIS fibroblasts in breast cancer progression and identify some key biomarkers associated with DCIS progression to IDC, with important clinical implications.

Identification and validation of a five-gene prognostic signature based on bioinformatics analyses in breast cancer

Background

This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data.

Methods

The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma". Secondly, the DEGs were used to construct a polygenic risk scoring model by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator Cox regression (Lasso-cox) analysis method. Thirdly, survival analysis was performed to investigate the risk score values in the TCGA cohort. And the enrichment analysis, immune cell infiltration levels analysis, and protein-protein internet (PPI) analysis were performed. Simultaneously, the GEO cohort was used to validate the model. Lastly, we constructed a nomogram to explore the influence of polygenic risk score and other clinical factors on the survival probability of patients with BRCA.

Results

A total of 1000 DEGs including 396 upregulated genes and 604 downregulated genes were identified from the TCGA-BRCA dataset. We obtained 5 prognosis-related genes, as the key biomarkers by Lasso-cox analysis (FBXL19, HAGHL, PHKG2, PKMYT1, and TXNDC17), all of which were significantly upregulated in breast tumors. The prognostic prediction of the 5 genes model was great in training and validation cohorts. Moreover, the high-risk group had a poorer prognosis. The Cox regression analysis showed that the comprehensive risk score for 5 genes was an independent prognosis factor.

Conclusion

The 5 genes risk model constructed in this study had an independent predictive ability to distinguish patients with a high risk of death from those with a low-risk score, and it can be used as a practical and reliable prognostic tool for BRCA.

Construction of a novel molecular typing and scoring system for anoikis distinguishes between different prognostic risks and treatment responsiveness in low-grade glioma

Background

The main factors responsible for low-grade glioma (LGG)s' poor prognosis and treatment effectiveness include recurrence and malignant progression. A specific type of programmed cell death, known as anoikis, which is crucial for tumor invasion and metastasis, however, has not yet been investigated in LGGs.

Methods

We downloaded data of 509 samples from the TCGA-LGG cohort, carried out cluster analysis for typing twice on the basis of 19 anoikis-associated genes, and the subtypes were evaluated the differences in clinicopathological and biological features. ESTIMATE and single-sample gene set enrichment analysis were employed to examine the immunological milieu of LGGs, and enrichment analysis was used to look into the underlying biological mechanisms in LGGs. Cox regression analysis and the Least Absolute Shrinkage and Selection Operator regression algorithm were used to create a prediction scoring system. The scoring system was used for classifying LGG into high- and low- anoikis riskscore (anoiS) groups. The impact of the anoiS on the prognosis, standard treatment, and immunotherapy of patients with LGG was assessed using survival analysis and drug sensitivity analysis. Cell experiments were employed for the verification of the differential expression between LGG cells and normal cells of the anoikis gene team that regard CCT5 as the core.

Results

Based on the expression profiles of the 19 anoikis-associated genes, all individuals with LGG were classified into four subtypes and two macrosubtypes. The different macrosubtypes had significantly different biological characteristics, and the anoirgclusterBD subtype manifested a significantly bad prognosis and a high immune level of infiltration. And subsequent secondary genotyping also showed good prognostic discrimination. We further constructed an anoikis scoring system, anoiS. LGG patients having a high anoiS had a worse prognosis in comparison to those having a low anoiS. The high anoiS group exhibited larger levels of immune infiltration and superior immunotherapy efficacy than the low anoiS group. The high anoiS group was also more susceptible to temozolomide (TMZ) than the low anoiS group, according to a drug sensitivity analysis of TMZ.

Conclusion

This study constructed a scoring system for predicting the prognosis of patients with LGG and their responsive to TMZ and immunotherapy.

Transcriptomics indicate nuclear division and cell adhesion not recapitulated in MCF7 and MCF10A compared to luminal A breast tumours

Breast cancer (BC) cell lines are useful experimental models to understand cancer biology. Yet, their relevance to modelling cancer remains unclear. To better understand the tumour-modelling efficacy of cell lines, we performed RNA-seq analyses on a combined dataset of 2D and 3D cultures of tumourigenic MCF7 and non-tumourigenic MCF10A. To our knowledge, this was the first RNA-seq dataset comprising of 2D and 3D cultures of MCF7 and MCF10A within the same experiment, which facilitates the elucidation of differences between MCF7 and MCF10A across culture types. We compared the genes and gene sets distinguishing MCF7 from MCF10A against separate RNA-seq analyses of clinical luminal A (LumA) and normal samples from the TCGA-BRCA dataset. Among the 1031 cancer-related genes distinguishing LumA from normal samples, only 5.1% and 15.7% of these genes also distinguished MCF7 from MCF10A in 2D and 3D cultures respectively, suggesting that different genes drive cancer-related differences in cell lines compared to clinical BC. Unlike LumA tumours which showed increased nuclear division-related gene expression compared to normal tissue, nuclear division-related gene expression in MCF7 was similar to MCF10A. Moreover, although LumA tumours had similar cell adhesion-related gene expression compared to normal tissues, MCF7 showed reduced cell adhesion-related gene expression compared to MCF10A. These findings suggest that MCF7 and MCF10A cell lines were limited in their ability to model cancer-related processes in clinical LumA tumours.

Downregulation of the enhancer of zeste homolog 1 transcriptional factor predicts poor prognosis of triple-negative breast cancer patients

Background

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer and lacks effective biomarkers. This study seeks to unravel the expression status and the prospective transcriptional mechanisms of EZH1/EZH2 in TNBC tissue samples. Moreover, another objective of this study is to reveal the prognostic molecular signatures for risk stratification in TNBC patients.

Methods

To determine the expression status of EZH1/EZH2 in TNBC tissue samples, microarray analysis and immunohistochemistry were performed on in house breast cancer tissue samples. External mRNA expression matrices were used to verify its expression patterns. Furthermore, the prospective transcriptional mechanisms of EZH1/EZH2 in TNBC were explored by performing differential expression analysis, co-expression analysis, and chromatin immunoprecipitation sequencing analysis. Kaplan-Meier survival analysis and univariate Cox regression analysis were utilized to detect the prognostic molecular signatures in TNBC patients. Nomogram and time-dependent receiver operating characteristic curves were plotted to predict the risk stratification ability of the prognostic-signatures-based Cox model.

Results

In-house TMAs (66 TNBC vs. 106 non-TNBC) and external gene microarrays, as well as RNA-seq datasets (1,135 TNBC vs. 6,198 non-TNBC) results, confirmed the downregulation of EZH1 at both the protein and mRNA levels (SMD = -0.59 [-0.80, -0.37]), as is opposite to that of EZH2 (SMD = 0.74 [0.40, 1.08]). The upregulated transcriptional target genes of EZH1 were significantly aggregated in the cell cycle pathway, where CCNA2, CCNB1, MAD2L1, and PKMYT1 were determined as key transcriptional targets. Additionally, the downregulated transcriptional targets of EZH2 were enriched in response to the hormone, where ESR1 was identified as the hub gene. The six-signature-based prognostic model produced an impressive performance in this study, with a training AUC of 0.753, 0.981, and 0.977 at 3-, 5-, and 10-year survival probability, respectively.

Conclusion

EZH1 downregulation may be a key modulator in the progression of TNBC through negative transcriptional regulation by targeting CCNA2, CCNB1, MAD2L1, and PKMYT1.

DNA Damage Response Inhibitors in Cholangiocarcinoma: Current Progress and Perspectives

Cholangiocarcinoma (CCA) is a poorly treatable type of cancer and its incidence is dramatically increasing. The lack of understanding of the biology of this tumor has slowed down the identification of novel targets and the development of effective treatments. Based on next generation sequencing profiling, alterations in DNA damage response (DDR)-related genes are paving the way for DDR-targeting strategies in CCA. Based on the notion of synthetic lethality, several DDR-inhibitors (DDRi) have been developed with the aim of accumulating enough DNA damage to induce cell death in tumor cells. Observing that DDRi alone could be insufficient for clinical use in CCA patients, the combination of DNA-damaging regimens with targeted approaches has started to be considered, as evidenced by many emerging clinical trials. Hence, novel therapeutic strategies combining DDRi with patient-specific targeted drugs could be the next level for treating cholangiocarcinoma.

Identification of Survival-Associated Hub Genes in Pancreatic Adenocarcinoma Based on WGCNA

Pancreatic adenocarcinoma is one of the leading causes of cancer-related death worldwide. Since little clinical symptoms were shown in the early period of pancreatic adenocarcinoma, most patients were found to carry metastases when diagnosis. The lack of effective diagnosis biomarkers and therapeutic targets makes pancreatic adenocarcinoma difficult to screen and cure. The fundamental problem is we know very little about the regulatory mechanisms during carcinogenesis. Here, we employed weighted gene co-expression network analysis (WGCNA) to build gene interaction network using expression profile of pancreatic adenocarcinoma from The Cancer Genome Atlas (TCGA). STRING was used for the construction and visualization of biological networks. A total of 22 modules were detected in the network, among which yellow and pink modules showed the most significant associations with pancreatic adenocarcinoma. Dozens of new genes including PKMYT1, WDHD1, ASF1B, and RAD18 were identified. Further survival analysis yielded their valuable effects on the diagnosis and treatment of pancreatic adenocarcinoma. Our study pioneered network-based algorithm in the application of tumor etiology and discovered several promising regulators for pancreatic adenocarcinoma detection and therapy.

PKMYT1 regulates the proliferation and epithelial‑mesenchymal transition of oral squamous cell carcinoma cells by targeting CCNA2

Oral squamous cell carcinoma (OSCC) has gradually become a global public health issue in recent years. Therefore, the current study aimed to explore the mechanism of OSCC development and to identify a potential target that may be used in its treatment. The expression of protein kinase, membrane-associated tyrosine/threonine 1 (PKMYT1) and cyclin A2 (CCNA2) in SCC-9 cells was determined prior to and following transfection with short hairpin RNA targeting PKMYT1. Cell proliferation, colony-forming ability, migration and invasion were determined using Cell Counting Kit-8, colony formation, wound healing and Transwell assays, respectively. Furthermore, the expression of epithelial-mesenchymal transition (EMT)- and migration-related proteins were evaluated using western blot analysis. Additionally, co-immunoprecipitation was used to verify the binding of PKMYT1 and CCNA2. The results revealed that PKMYT1 was highly expressed in OSCC cells and that PKMYT1 knockdown could inhibit proliferation, colony formation, migration, invasion, EMT and CCNA2 expression in SCC-9 cells. In addition, PKMYT1 was demonstrated to bind to CCNA2, and knocking down PKMYT1 resulted in inhibitory effects on cell proliferation, colony formation ability, migration, invasion and EMT by downregulating CCNA2 expression. PKMYT1 was observed to regulate the proliferation, migration and EMT of OSCC cells by targeting CCNA2, which may be used in the future to improve OSCC treatment.

PKMYT1, exacerbating the progression of clear cell renal cell carcinoma, is implied as a biomarker for the diagnosis and prognosis

Clear cell renal cell carcinoma (ccRCC) is one of the most lethal urological malignancies with high tumor heterogeneity, and reliable biomarkers are still needed for its diagnosis and prognosis. WEE family kinases function as key regulators of the G2/M transition, have essential roles in maintaining cellular genomic stability and have the potential to be promising therapeutic targets in various tumors. However, the roles of WEE family kinases in ccRCC remain undetermined. In the present study, we first explored multiple public datasets and found that PKMYT1 was up-regulated in both RCC tumors and cell lines. Expression levels of PKMYT1 were highly associated with pathological stage and grade. Kaplan-Meier curves showed that high PKMYT1 expression was associated with lower overall survival and disease-free survival. Receiver operating characteristic curves revealed that the expression of PKMYT1 could better distinguish ccRCC from normal samples. Functional enrichment analysis demonstrated that cell cycle- related pathways and epithelial to mesenchymal transition (EMT) might be potential mechanisms of PKMYT1 in ccRCC tumorigenesis. Moreover, knockdown of PKMYT1 in vitro attenuated the proliferation, migration and invasion of RCC cell lines, promoted cell apoptosis and prevented the EMT phenotype in vitro. In conclusion, our study demonstrated that PKMYT1 has the potential to act as a diagnostic and prognostic biomarker for RCC patients. Targeting PKMYT1 may be considered as a new potential therapeutic method and direction in RCCs.

Exosomal miR-21-5p derived from bone marrow mesenchymal stem cells promote osteosarcoma cell proliferation and invasion by targeting PIK3R1

Mesenchymal stem cells (MSCs) are a class of pluripotent cells that can release a large number of exosomes which act as paracrine mediators in tumour-associated microenvironment. However, the role of MSC-derived exosomes in pathogenesis and progression of cancer cells especially osteosarcoma has not been thoroughly clarified until now. In this study, we established a co-culture model for human bone marrow-derived MSCs with osteosarcoma cells, then extraction of exosomes from induced MSCs and study the role of MSC-derived exosomes in the progression of osteosarcoma cell. The aim of this study was to address potential cell biological effects between MSCs and osteosarcoma cells. The results showed that MSC-derived exosomes can significantly promote osteosarcoma cells' proliferation and invasion. We also found that miR-21-5p was significantly over-expressed in MSCs and MSC-derived exosomes by quantitative real-time polymerase chain reaction (qRT-PCR), compared with human foetal osteoblastic cells hFOB1.19. MSC-derived exosomes transfected with miR-21-5p could significantly enhance the proliferation and invasion of osteosarcoma cells in vitro and in vivo. Bioinformatics analysis and dual-luciferase reporter gene assays validated the targeted relationship between exosomal miR-21-5p and PIK3R1; we further demonstrated that miR-21-5p-abundant exosomes derived human bone marrow MSCs could activate PI3K/Akt/mTOR pathway by suppressing PIK3R1 expression in osteosarcoma cells. In summary, our study provides new insights into the interaction between human bone marrow MSCs and osteosarcoma cells in tumour-associated microenvironment.

Potential Prognostic Biomarkers of NIMA (Never in Mitosis, Gene A)-Related Kinase (NEK) Family Members in Breast Cancer

Breast cancer remains the most common malignant cancer in women, with a staggering incidence of two million cases annually worldwide; therefore, it is crucial to explore novel biomarkers to assess the diagnosis and prognosis of breast cancer patients. NIMA-related kinase (NEK) protein kinase contains 11 family members named NEK1-NEK11, which were discovered from Aspergillus Nidulans; however, the role of NEK family genes for tumor development remains unclear and requires additional study. In the present study, we investigate the prognosis relationships of NEK family genes for breast cancer development, as well as the gene expression signature via the bioinformatics approach. The results of several integrative analyses revealed that most of the NEK family genes are overexpressed in breast cancer. Among these family genes, NEK2/6/8 overexpression had poor prognostic significance in distant metastasis-free survival (DMFS) in breast cancer patients. Meanwhile, NEK2/6 had the highest level of DNA methylation, and the functional enrichment analysis from MetaCore and Gene Set Enrichment Analysis (GSEA) suggested that NEK2 was associated with the cell cycle, G2M checkpoint, DNA repair, E2F, MYC, MTORC1, and interferon-related signaling. Moreover, Tumor Immune Estimation Resource (TIMER) results showed that the transcriptional levels of NEK2 were positively correlated with immune infiltration of B cells and CD4+ T Cell. Collectively, the current study indicated that NEK family genes, especially NEK2 which is involved in immune infiltration, and may serve as prognosis biomarkers for breast cancer progression.

ONC201 induces the unfolded protein response (UPR) in high- and low-grade ovarian carcinoma cell lines and leads to cell death regardless of platinum sensitivity

Objectives

Treatment of both platinum resistant high grade (HG) and low‐grade (LG) ovarian cancer (OVCA) poses significant challenges as neither respond well to conventional chemotherapy leading to morbidity and mortality. Identification of novel agents that can overcome chemoresistance is therefore critical. Previously, we have demonstrated that OVCA has basal upregulated unfolded protein response (UPR) and that targeting cellular processes leading to further and persistent upregulation of UPR leads to cell death. ONC201 is an orally bioavailable Dopamine Receptor D2 inhibitor demonstrating anticancer activity and was found to induce UPR. Given its unique properties, we hypothesized that ONC201 would overcome platinum resistance in OVCA.

Methods

Cisplatin sensitive and resistant HG OVCA and two primary LG OVCA cell lines were studied. Cell viability was determined using MTT assay. Cell migration was studied using wound healing assay. Apoptosis and mitochondrial membrane potential were investigated using flow cytometry. Analysis of pathway inhibition was performed by Western Blot. mRNA expression of UPR related genes were measured by qPCR. In vivo studies were completed utilizing axillary xenograft models. Co‐testing with conventional chemotherapy was performed to study synergy.

Results

ONC201 significantly inhibited cell viability and migration in a dose dependent manner with IC50’s from 1‐20 µM for both cisplatin sensitive and resistant HG and LG‐OVCA cell lines. ONC201 lead to upregulation of the pro‐apoptotic arm of the UPR, specifically ATF‐4/CHOP/ATF3 and increased the intrinsic apoptosispathway. The compensatory, pro‐survival PI3K/AKT/mTOR pathway was downregulated. In vivo, weekly dosing of single agent ONC201 decreased xenograft tumor size by ~50% compared to vehicle. ONC201 also demonstrated significant synergy with paclitaxel in a highly platinum resistant OVCA cell‐line (OV433).

Conclusions

Our findings demonstrate that ONC201 can effectively overcome chemoresistance in OVCA cells by blocking pro‐survival pathways and inducing the apoptotic arm of the UPR. This is a promising, orallybioavailable therapeutic agent to consider in clinical trials for patients with both HG and LG OVCA.

Targeting WEE1 by adavosertib inhibits the malignant phenotypes of hepatocellular carcinoma

Targeting the cell cycle checkpoints and DNA damage response are promising therapeutic strategies for cancer. Adavosertib is a potent inhibitor of WEE1 kinase, which plays a critical role in regulating cell cycle checkpoints. However, the effect of adavosertib on hepatocellular carcinoma (HCC) treatment, including sorafenib-resistant HCC, has not been thoroughly studied. In this study, we comprehensively investigated the efficacy and pharmacology of adavosertib in HCC therapy. Adavosertib effectively inhibited the proliferation of HCC cells in vitro and suppressed tumor growth in HCC xenografts and patient-derived xenograft (PDX) models in vivo. Additionally, adavosertib treatment effectively inhibited the motility of HCC cells by impairing pseudopodia formation. Further, we revealed that adavosertib induced DNA damage and premature mitosis entrance by disturbing the cell cycle. Thus, HCC cells accumulating DNA damage underwent mitosis without G2/M checkpoint arrest, thereby leading to mitotic catastrophe and apoptosis under adavosertib administration. Given that sorafenib resistance is common in HCC in clinical practice, we also explored the efficacy of adavosertib in sorafenib-resistant HCC. Notably, adavosertib still showed a desirable inhibitory effect on the growth of sorafenib-resistant HCC cells. Adavosertib markedly induced G2/M checkpoint arrest and cell apoptosis in a dose-dependent manner, confirming the similar efficacy of adavosertib in sorafenib-resistant HCC. Collectively, our results highlight the treatment efficacy of adavosertib in HCC regardless of sorafenib resistance, providing insights into exploring novel strategies for HCC therapy.

Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer

Although research into immunotherapy is growing, its use in the treatment of breast cancer remains limited. Thus, identification and evaluation of prognostic biomarkers of tissue microenvironments will reveal new immune-based therapeutic strategies for breast cancer. Using an in silico bioinformatic approach, we investigated the tumor microenvironmental and genetic factors related to breast cancer. We calculated the Immune score, Stromal score, Estimate score, Tumor purity, TMB (Tumor mutation burden), and MATH (Mutant-allele tumor heterogeneity) of Breast cancer patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and Maftools. Significant correlations between Immune/Stromal scores with breast cancer subtypes and tumor stages were established. Importantly, we found that the Immune score, but not the Stromal score, was significantly related to the patient's prognosis. Weighted correlation network analysis (WGCNA) identified a pattern of gene function associated with Immune score, and that almost all of these genes (388 genes) are significantly upregulated in the higher Immune score group. Protein-protein interaction (PPI) network analysis revealed the enrichment of immune checkpoint genes, predicting a good prognosis for breast cancer. Among all the upregulated genes, FPR3, a G protein-coupled receptor essential for neutrophil activation, is the sole factor that predicts poor prognosis. Gene set enrichment analysis analysis showed FRP3 upregulation synergizes with the activation of many pathways involved in carcinogenesis. In summary, this study identified FPR3 as a key immune-related biomarker predicting a poor prognosis for breast cancer, revealing it as a promising intervention target for immunotherapy.

Overexpression of PKMYT1 Facilitates Tumor Development and Is Correlated with Poor Prognosis in Clear Cell Renal Cell Carcinoma

BACKGROUND Protein kinase membrane-associated tyrosine/threonine (PKMYT1) has been found in many tumors, but its association with clear cell renal cell carcinoma (ccRCC) remains unclear. MATERIAL AND METHODS PKMYT1 expression in ccRCC was examined in the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Tumor Immune Estimation Resource databases. The correlation between PKMYT1 expression and clinicopathological parameters was explored via the chi-square test. Receiver operating characteristic curves were used to estimate the diagnostic performance of PKMYT1. Kaplan-Meier curves, a Cox model, nomogram, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA) were used to evaluate the prognostic value and clinical utility of PKMYT1. Genes coexpressed with PKMYT1 in ccRCC were identified based on TCGA, the gene expression profiling interactive, and cBioPortal. Gene Set Enrichment Analysis revealed biological pathways associated with PKMYT1 in ccRCC. RESULTS Weighted gene coexpression network analysis identified PKMYT1 as one of the genes most significantly correlated with progression of histological grade. PKMYT1 was significantly upregulated in ccRCC compared with normal tissue (P<0.001), with a trend toward differentiating between individuals with ccRCC and those who were healthy (area under the curve=0.942). High PKMYT1 expression was correlated with unsatisfactory survival (hazard ratio=1.67, P=0.001), indicating that it is a risk factor for ccRCC. A nomogram incorporating PKMYT1 level was created and showed a clinical net benefit. PKMYT1 was strongly positively correlated with the anti-silencing function of 1B histone chaperone (ASF1B) gene in ccRCC. CONCLUSIONS PKMYT1 is upregulated in ccRCC and its presence indicates poor prognosis, making it a potential therapeutic target for ccRCC.

A WEE1 family business: regulation of mitosis, cancer progression, and therapeutic target

The inhibition of the DNA damage response (DDR) pathway in the treatment of cancer has recently gained interest, and different DDR inhibitors have been developed. Among them, the most promising ones target the WEE1 kinase family, which has a crucial role in cell cycle regulation and DNA damage identification and repair in both nonmalignant and cancer cells. This review recapitulates and discusses the most recent findings on the biological function of WEE1/PKMYT1 during the cell cycle and in the DNA damage repair, with a focus on their dual role as tumor suppressors in nonmalignant cells and pseudo-oncogenes in cancer cells. We here report the available data on the molecular and functional alterations of WEE1/PKMYT1 kinases in both hematological and solid tumors. Moreover, we summarize the preclinical information on 36 chemo/radiotherapy agents, and in particular their effect on cell cycle checkpoints and on the cellular WEE1/PKMYT1-dependent response. Finally, this review outlines the most important pre-clinical and clinical data available on the efficacy of WEE1/PKMYT1 inhibitors in monotherapy and in combination with chemo/radiotherapy agents or with other selective inhibitors currently used or under evaluation for the treatment of cancer patients.

PKMYT1 Promotes Gastric Cancer Cell Proliferation and Apoptosis Resistance

Background

Abnormal expression of protein kinase membrane associated tyrosine/threonine 1 (PKMYT1) is closely associated with multiple types of cancers. In the present study, we examined the roles of PKMYT1 in gastric cancer (GC) progression.

Methods

We examined the expression status of PKMYT1 in GC tissues and cell lines. Meanwhile, short hairpin RNA (shRNA) was used to inhibit the endogenous expression of PKMYT1 in GC cells. Then we analyzed the effect of PKMYT1 on the malignant biological behavior of GC cells by in vitro and in vivo experiments.

Results

The findings showed high PKMYT1 expressions in GC tissues as well as a positive correlation between PKMYT1 expression and prognosis of patients with GC. Additional findings also revealed that PKMYT1 silencing significantly enhanced apoptosis and inhibited GC cell proliferation. In vivo, the silence of PKMYT1 inhibits tumor growth. Further analysis showed that the increase in PKMYT1 expressions led to malignant biological behavior through activation of the MAPK signaling pathway.

Conclusion

Our data suggested that PKMYT1 promotes cell proliferation and apoptosis resistance in GC cells by activating the MAPK signaling pathway, making it a potential therapeutic target for GC.

Systematic expression analysis of WEE family kinases reveals the importance of PKMYT1 in breast carcinogenesis

OBJECTIVES

Many cancer cells depend on G2 checkpoint mechanism regulated by WEE family kinases to maintain genomic integrity. The PKMYT1 gene, as a member of WEE family kinases, participates in G2 checkpoint surveillance and probably links with tumorigenesis, but its role in breast cancer remains largely unclear.

MATERIALS AND METHODS

In this study, we used a set of bioinformatic tools to jointly analyse the expression of WEE family kinases and investigate the prognostic value of PKMYT1 in breast cancer.

RESULTS

The results indicated that PKMYT1 is the only frequently overexpressed member of WEE family kinases in breast cancer. KM plotter data suggests that abnormally high expression of PKMYT1 predicts poor prognosis, especially for some subtypes, such as luminal A/B and triple-negative (TNBC) types. Moreover, the up-regulation of PKMYT1 was associated with HER2-positive (HER2+), basal-like (Basal-like), TNBC statuses and increased classifications of Scarff, Bloom and Richardson (SBR). Co-expression analysis showed PKMYT1 has a strong positive correlation with Polo-like kinase 1 (PLK1), implying they may cooperate in regulating cancer cell proliferation by synchronizing rapid cell cycle with high quality of genome maintenance.

CONCLUSIONS

Collectively, this study demonstrates that overexpression of PKMYT1 is always found in breast cancer and predicts unfavourable prognosis, implicating it as an appealing therapeutic target for breast carcinoma.