Secretory SERPINE1 Expression Is Increased by Antiplatelet Therapy, Inducing MMP1 Expression and Increasing Colon Cancer Metastasis

Ubiquitin-specific protease 1 facilitates hepatocellular carcinoma progression by modulating mitochondrial fission and metabolic reprogramming via cyclin-dependent kinase 5 stabilization

Although deubiquitinases (DUBs) have been well described in liver tumorigenesis, their potential roles and mechanisms have not been fully understood. In this study, we identified ubiquitin-specific protease 1 (USP1) as an oncogene with essential roles during hepatocellular carcinoma (HCC) progression. USP1, with elevated expression levels and clinical significance, was identified as a hub DUB for HCC in multiple bioinformatics datasets. Functionally, USP1 overexpression significantly enhanced the malignant behaviors in HCC cell lines and spheroids in vitro, as well as the zebrafish model and the xenograft model in vivo. In contrast, genetic ablation or pharmacological inhibition of USP1 dramatically impaired the phenotypes of HCC cells. Specifically, ectopic USP1 enhanced aggressive properties and metabolic reprogramming of HCC cells by modulating mitochondrial dynamics. Mechanistically, USP1 induced mitochondrial fission by enhancing phosphorylation of Drp1 at Ser616 via deubiquitination and stabilization of cyclin-dependent kinase 5 (CDK5), which could be degraded by the E3 ligase NEDD4L. The USP1/CDK5 modulatory axis was activated in HCC tissues, which was correlated with poor prognosis of HCC patients. Furthermore, Prasugrel was identified as a candidate USP1 inhibitor for targeting the phenotypes of HCC by an extensive computational study combined with experimental validations. Taken together, USP1 induced malignant phenotypes and metabolic reprogramming by modulating mitochondrial dynamics in a CDK5-mediated Drp1 phosphorylation manner, thereby deteriorating HCC progression.

Role and recent progress of P2Y12 receptor in cancer development

P2Y12 receptor (P2Y12R) is an adenosine-activated G protein-coupled receptor (GPCR) that plays a central role in platelet function, hemostasis, and thrombosis. P2Y12R activation can promote platelet aggregation and adhesion to cancer cells, promote tumor angiogenesis, and affect the tumor immune microenvironment (TIME) and tumor drug resistance, which is conducive to the progression of cancers. Meanwhile, P2Y12R inhibitors can inhibit this effect, suggesting that P2Y12R may be a potential therapeutic target for cancer. P2Y12R is involved in cancer development and metastasis, while P2Y12R inhibitors are effective in inhibiting cancer. However, a new study suggests that long-term use of P2Y12R inhibitors may increase the risk of cancer and the mechanism remains to be explored. In this paper, we reviewed the structural and functional characteristics of P2Y12R and its role in cancer. We explored the role of P2Y12R inhibitors in different tumors and the latest advances by summarizing the basic and clinical studies on the effects of P2Y12R inhibitors on tumors.

MiRNA-145-5p inhibits gastric cancer progression via the serpin family E member 1- extracellular signal-regulated kinase-1/2 axis

BACKGROUND

MicroRNAs (miRNAs) regulate gene expression and play a critical role in cancer physiology. However, there is still a limited understanding of the function and regulatory mechanism of miRNAs in gastric cancer (GC).

AIM

To investigate the role and molecular mechanism of miRNA-145-5p (miR145-5p) in the progression of GC.

METHODS

Real-time polymerase chain reaction (RT-PCR) was used to detect miRNA expression in human GC tissues and cells. The ability of cancer cells to migrate and invade was assessed using wound-healing and transwell assays, respectively. Cell proliferation was measured using cell counting kit-8 and colony formation assays, and apoptosis was evaluated using flow cytometry. Expression of the epithelial-mesenchymal transition (EMT)-associated protein was determined by Western blot. Targets of miR-145-5p were predicated using bioinformatics analysis and verified using a dual-luciferase reporter system. Serpin family E member 1 (SERPINE1) expression in GC tissues and cells was evaluated using RT-PCR and immunohistochemical staining. The correlation between SERPINE1 expression and overall patient survival was determined using Kaplan-Meier plot analysis. The association between SERPINE1 and GC progression was also tested. A rescue experiment of SERPINE1 overexpression was conducted to verify the relationship between this protein and miR-145-5p. The mechanism by which miR-145-5p influences GC progression was further explored by assessing tumor formation in nude mice.

RESULTS

GC tissues and cells had reduced miR-145-5p expression and SERPINE1 was identified as a direct target of this miRNA. Overexpression of miR-145-5p was associated with decreased GC cell proliferation, invasion, migration, and EMT, and these effects were reversed by forcing SERPINE1 expression. Kaplan-Meier plot analysis revealed that patients with higher SERPINE1 expression had a shorter survival rate than those with lower SERPINE1 expression. Nude mouse tumorigenesis experiments confirmed that miR-145-5p targets SERPINE1 to regulate extracellular signal-regulated kinase-1/2 (ERK1/2).

CONCLUSION

This study found that miR-145-5p inhibits tumor progression and is expressed in lower amounts in patients with GC. MiR-145-5p was found to affect GC cell proliferation, migration, and invasion by negatively regulating SERPINE1 levels and controlling the ERK1/2 pathway.

Mesenchymal Stem Cells Increase Drug Tolerance of A431 Cells Only in 3D Spheroids, Not in 2D Co-Cultures

Mesenchymal stem cells (MSCs) are an integral part of the tumor microenvironment (TME); however, their role is somewhat controversial: conflicting reports suggest that, depending on the stage of tumor development, MSCs can either support or suppress tumor growth and spread. Additionally, the influence of MSCs on drug resistance is also ambiguous. Previously, we showed that, despite MSCs proliferating significantly more slowly than cancer cells, there are chemotherapeutic drugs which proved to be similarly toxic to both cell types. Here we established 2D co-cultures and 3D co-culture spheroids from different ratios of GFP-expressing, adipose tissue-derived MSCs and A431 epidermoid carcinoma cells tagged with mCherry to investigate the effect of MSCs on cancer cell growth, survival, and drug sensitivity. We examined the cytokine secretion profile of mono- and co-cultures, explored the inner structure of the spheroids, applied MSC-(nutlin-3) and cancer cell-targeting (cisplatin) treatments separately, monitored the response with live-cell imaging and identified a new, double-fluorescent cell type emerging from these cultures. In 2D co-cultures, no effect on proliferation or drug sensitivity was observed, regardless of the changes in cytokine secretion induced by the co-culture. Conversely, 3D spheroids developed a unique internal structure consisting of MSCs, which significantly improved cancer cell survival and resilience to treatment, suggesting that physical proximity and cell-cell connections are required for MSCs to considerably affect nearby cancer cells. Our results shed light on MSC-cancer cell interactions and could help design new, better treatment options for tumors.

Unraveling a novel hippo-associated immunological prognostic signature: The contribution of SERPINE1 in facilitating colorectal cancer progression via the notch signaling pathway

BACKGROUND

Accumulating evidence demonstrated that Hippo signaling pathway is implicated in tumor initiation and progression. However, there have been limited studies on establishing signatures utilizing genes related to the Hippo pathway to evaluate prognosis and clinical efficacy in colorectal cancer (CRC) patients.

METHODS

Hippo pathway-associated genes with prognostic significance were identified in the TCGA database. Subsequently, a prognostic signature associated with the Hippo pathway was constructed using Cox and LASSO regression analyses. Survival analysis, ROC analysis, and stratified analyses were conducted to appraise the performance effect of our prognostic model. We also explored the relationship between the risk score and tumor immune microenvironment. Furthermore, GO analyses and GSEA were performed for SERPINE1. Additional experiments were conducted to illuminate the underlying function and possible mechanism of SERPINE1 in CRC cell proliferation and migration.

RESULTS

We identified 58 differentially expressed genes associated with Hippo pathway that have prognostic significance in CRC. Among them, five genes (PPP2CB, SERPINE1, WNT5A, TCF7L1, and LEF1) were selected to establish a prognostic signature for CRC. Multivariate analysis demonstrated that this signature exhibited excellent diagnostic and prognostic performance, providing maximum benefits for CRC patients. In accordance with the prognostic signatures, the cases were divided into low-risk and high-risk groups. Remarkably, the high-risk group displayed lower immune scores, reduced immune cell infiltration, and decreased expression of immune checkpoints. Low-risk group could more possibly benefit from conventional chemotherapeutic and targeted therapies. CRC exhibited significantly elevated expression of SERPINE1, which was linked to worst overall survival. Moreover, inhibition of SERPINE1 suppressed proliferation, invasion, and migration of CRC cells via Notch pathway.

CONCLUSIONS

To sum up, we established a novel immunological prognostic signature utilizing genes associated with the Hippo pathway. This signature offers accurate prognostic prediction and can guide individualized therapy for patients with CRC.

P2 purinergic receptors regulate the progression of colorectal cancer

More and more studies have revealed that P2 purinergic receptors play a key role in the progression of colorectal cancer (CRC). P2X and P2Y purinergic receptors can be used as promoters and regulators of CRC and play a dual role in the progression of CRC. CRC microenvironment is rich in ATP and its cleavage products (ADP, AMP, Ado), which act as activators of P2X and P2Y purinergic receptors. The activation of P2X and P2Y purinergic receptors regulates the progression of CRC mainly by regulating the function of immune cells and mediating different signal pathways. In this paper, we focus on the specific mechanisms and functional roles of P2X7, P2Y12, and P2Y2 receptors in the growth and progression of CRC. The antagonistic effects of these selective antagonists of P2X purinergic receptors on the growth, invasion, and metastasis of CRC were further discussed. Moreover, different studies have reported that P2X7 receptor can be used as an effective predictor of patients with CRC. All these indicate that P2 purinergic receptors are a key regulator of CRC. Therefore, antagonizing P2 purinergic receptors may be an innovative treatment for CRC.

Novel diagnostic biomarkers of oxidative stress, immune- infiltration characteristics and experimental validation of SERPINE1 in colon cancer

BACKGROUND

Colon cancer (CC) is a prevalent malignant tumor that affects the colon in the gastrointestinal tract. Its aggressive nature, strong invasiveness, and rapid progression make it a significant health concern. In addition, oxidative stress can lead to the production of reactive oxygen species (ROS) that surpass the body's antioxidant defense capacity, causing damage to proteins, lipids, and DNA, potentially promoting tumor development. However, the relationship between CC and oxidative stress requires further investigation.

METHODS

We collected gene expression data and clinical data from 473 CC patients from The Cancer Genome Atlas (TCGA) dataset. Additionally, we obtained 433 oxidative stress genes from Genecards ( https://www.genecards.org/ ). Using univariate, multivariate, and LASSO Cox regression analyses, we developed predictive models for oxidative stress-related genes in CC patients. To validate the models, we utilized data from the Gene Expression Omnibus (GEO) database. We assessed the accuracy of the models through various techniques, including the creation of a nomogram, receiver operating characteristic curve (ROC) analysis, and principal component analysis (PCA). The Cytoscape program was utilized to identify hub genes among differentially expressed genes (DEGs) in tumor patients using the TCGA dataset. Subsequently, we conducted survival analysis, clinical relevance analysis, and immune cell relevance analysis for the intersected genes obtained by combining the hub genes with the genes from the predictive models. Moreover, we investigated the mRNA expression and potential functions of these intersected genes using a range of experimental approaches.

RESULTS

In both the TCGA and GSE17538 datasets, patients classified as high-risk had significantly shorter overall survival compared to those in the low-risk group (TCGA: p < 0.001; GSE17538: p = 0.010). As a result, we decided to further investigate the role of SERPINE1. Our survival analysis revealed that patients with high expression of SERPINE1 had a significantly lower probability of survival compared to those with low expression (p < 0.05). Additionally, our clinical correlation analysis showed a significant relationship between SERPINE1 expression and T, N, and M stages, as well as tumor grade. Furthermore, our immune infiltration correlation analysis demonstrated notable differences in multiple immune cells between the high- and low-expression groups of SERPINE1. To validate our findings, we conducted experimental tests and observed that knocking down SERPINE1 in colon cancer cells resulted in significant reductions in cell viability and proliferation. Interestingly, we also noticed an increase in oxidative stress parameters, such as ROS and MDA levels, while the levels of reduced GSH decreased upon SERPINE1 knockdown. These findings suggest that the antineoplastic effect of silencing SERPINE1 may be associated with the induction of oxidative stress.

CONCLUSION

In conclusion, this study introduces a new approach for the early diagnosis and treatment of CC, and further exploration of SERPINE1 could potentially lead to a significant advancement.

Establishment of a 6-signature risk model associated with cellular senescence for predicting the prognosis of breast cancer

This study focused on screening novel markers associated with cellular senescence for predicting the prognosis of breast cancer. The RNA-seq expression profile of BRCA and clinical data were obtained from TCGA. The pam algorithm was used to cluster patients based on senescence-related genes. The weighted gene co-expression network analysis was used to identify co-expressed genes, and LASSO-Cox analysis was performed to build a risk prognosis model. The performance of the model was also evaluated. We additionally explored the role of senescence in cancer development and possible regulatory mechanism. The patients were clustered into 2 subtypes. A total of 5259 genes significantly related to senescence were identified by weighted gene co-expression network analysis. LASSO-Cox finally established a 6-signature risk model (ADAMTS8, DCAF12L2, PCDHA10, PGK1, SLC16A2, and TMEM233) that exhibited favorable and stable performance in our training, validation, and whole BRCA datasets. Furthermore, the superiority of our model was also observed after comparing it to other published models. The 6-signature was proved to be an independent risk factor for prognosis. In addition, mechanism prediction implied the activation of glycometabolism processes such as glycolysis and TCA cycle under the condition of senescence. Glycometabolism pathways were further found to negatively correlate with the infiltration level of CD8 T-cells and natural killer cells but positively correlate with M2 macrophage infiltration and expressions of tissue degeneration biomarkers, which suggested the deficit immune surveillance and risk of tumor migration. The constructed 6-gene model based on cellular senescence could be an effective indicator for predicting the prognosis of BRCA.

PRKRA promotes pancreatic cancer progression by upregulating MMP1 transcription via the NF-κB pathway

Objective

Pancreatic cancer (PC) is highly malignant, but the underlying mechanisms of cancer progression remain unclear. PRKRA is involved in cellular stress response, but its role in PC was unknown.

Methods

The expression of PRKRA between normal and tumor tissues were compared, and the prognostic value of PRKRA was evaluated. SiRNA and plasmids were applied to investigate the effects of PRKRA on PC cells. Organoids and cell lines with knockout and overexpression of PRKRA were established by CRISPR/Cas9 and lentivirus. The effects of PRKRA on PC were evaluated in vivo by cell-derived xenografts. The downstream genes of PRKRA were screened by transcriptome sequencing. The regulation of the target gene was validated by RT-qPCR, western blot, ChIP and dual luciferase reporter assay. Besides, the correlation between PRKRA and gemcitabine sensitivity was investigated by PC organoids.

Results

PRKRA was significantly overexpressed in PC tissues and independently associated with poor prognosis. PRKRA promoted the proliferation, migration, and chemoresistance of PC cells. The proliferation of PC organoids was decreased by PRKRA knockout. The growth and chemoresistance of xenografts were increased by PRKRA overexpression. Mechanistically, PRKRA upregulated the transcription of MMP1 via NF-κB pathway. ChIP and dual luciferase reporter assay showed that NF-κB subunit P65 could bind to the promoter of MMP1. The sensitivity of PC organoids to gemcitabine was negatively correlated with the expression of PRKRA and MMP1.

Conclusions

Our study indicated that the PRKRA/NF-κB/MMP1 axis promoted the progression of PC and may serve as a potential therapeutic target and prognosis marker.

Seven bacterial response-related genes are biomarkers for colon cancer

BACKGROUND

Colon cancer (CC) is a common tumor that causes significant harm to human health. Bacteria play a vital role in cancer biology, particularly the biology of CC. Genes related to bacterial response were seldom used to construct prognosis models. We constructed a bacterial response-related risk model based on three Molecular Signatures Database gene sets to explore new markers for predicting CC prognosis.

METHODS

The Cancer Genome Atlas (TCGA) colon adenocarcinoma samples were used as the training set, and Gene Expression Omnibus (GEO) databases were used as the test set. Differentially expressed bacterial response-related genes were identified for prognostic gene selection. Univariate Cox regression analysis, least absolute shrinkage and selection operator-penalized Cox regression analysis, and multivariate Cox regression analysis were performed to construct a prognostic risk model. The individual diagnostic effects of genes in the prognostic model were also evaluated. Moreover, differentially expressed long noncoding RNAs (lncRNAs) were identified. Finally, the expression of these genes was validated using quantitative polymerase chain reaction (qPCR) in cell lines and tissues.

RESULTS

A prognostic signature was constructed based on seven bacterial response genes: LGALS4, RORC, DDIT3, NSUN5, RBCK1, RGL2, and SERPINE1. Patients were assigned a risk score based on the prognostic model, and patients in the TCGA cohort with a high risk score had a poorer prognosis than those with a low risk score; a similar finding was observed in the GEO cohort. These seven prognostic model genes were also independent diagnostic factors. Finally, qPCR validated the differential expression of the seven model genes and two coexpressed lncRNAs (C6orf223 and SLC12A9-AS1) in 27 pairs of CC and normal tissues. Differential expression of LGALS4 and NSUN5 was also verified in cell lines (FHC, COLO320DM, SW480).

CONCLUSIONS

We created a seven-gene bacterial response-related gene signature that can accurately predict the outcomes of patients with CC. This model can provide valuable insights for personalized treatment.

Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms

PURPOSE

Anaplastic thyroid cancer (ATC) is a rare and lethal malignant cancer. In recent years, the application of molecular-driven targeted therapy and immunotherapy has markedly improved the prognosis of ATC. This study aimed to identify characteristic genes for ATC diagnosis and revealed the role of ATC characteristic genes in drug sensitivity and immune cell infiltration.

METHODS

We downloaded ATC RNA-sequencing data from the GEO database. Following the combination and normalization of the dataset, we first divided the combined datasets into the training cohort and the validation cohort. We identified differentially expressed genes (DEGs) in ATC by differential expression analysis in the training cohort. We used two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) to identify ATC characteristic genes. The CIBERSORT algorithm was performed to calculate the abundance of various immune cells in ATC. Finally, we validated the expression of ATC characteristic genes by quantitative RT-PCR (RT-qPCR) in ATC cell lines and immunohistochemistry (IHC).

RESULTS

A total of 425 DEGs were identified in the training cohort, including 240 upregulated genes and 185 downregulated genes. Four ATC characteristic genes (ADM, PXDN, MMP1, and TFF3) were identified, and their diagnostic value was validated in the validation cohort (AUC in ROC analysis > 0.75). We established a practical gene expression-based nomogram to accurately predict the probability of ATC. We also found that ATC characteristic biomarkers are associated with the tumor immune microenvironment and drug sensitivity.

CONCLUSION

ADM, PXDN, MMP1, and TFF3 might serve as potential ATC diagnostic biomarkers and may be helpful for ATC molecular targeted therapy and immunotherapy.

Identification and validation of a prognostic risk-scoring model based on sphingolipid metabolism-associated cluster in colon adenocarcinoma

Colon adenocarcinoma (COAD) is the primary factor responsible for cancer-related mortalities in western countries, and its development and progression are affected by altered sphingolipid metabolism. The current study aimed at investigating the effects of sphingolipid metabolism-related (SLP) genes on multiple human cancers, especially on COAD. We obtained 1287 SLP genes from the GeneCard and MsigDb databases along with the public transcriptome data and the related clinical information. The univariate Cox regression analysis suggested that 26 SLP genes were substantially related to the prognosis of COAD, and a majority of SLP genes served as the risk genes for the tumor, insinuating a potential pathogenic effect of SLP in COAD development. Pan-cancer characterization of SLP genes summarized their expression traits, mutation traits, and methylation levels. Subsequently, we focused on the thorough research of COAD. With the help of unsupervised clustering, 1008 COAD patients were successfully divided into two distinct subtypes (C1 and C2). C1 subtype is characterized by a poor prognosis, activation of SLP pathways, high expression of SLP genes, disordered carcinogenic pathways, and immune microenvironment. Based on the clusters of SLP, we developed and validated a novel prognostic model, consisting of ANO1, C2CD4A, EEF1A2, GRP, HEYL, IGF1, LAMA2, LSAMP, RBP1, and TCEAL2, to quantitatively evaluate the clinical outcomes of COAD. The Kaplain-Meier survival curves and ROC curves highlighted the accuracy of our SLP model in both internal and external cohorts. Compared to normal colon tissues, expression of C2CD4A was detected to be significantly higher in COAD; whereas, expression levels of EEF1A2, IGF1, and TCEAL2 were detected to be significantly lower in COAD. Overall, our research emphasized the pathogenic role of SLP in COAD and found that targeting SLP might help improve the clinical outcomes of COAD. The risk model based on SLP metabolism provided a new horizon for prognosis assessment and customized patient intervention.