Overexpression of PSMC2 promotes the tumorigenesis and development of human breast cancer via regulating plasminogen activator urokinase (PLAU)

Revealing the role of cancer-associated fibroblast senescence in prognosis and immune landscape in pancreatic cancer

Cancer-associated fibroblasts (CAFs) represent a major contributor to tumor growth. Cellular senescence is a state of cell-cycle arrest characterized by a pro-inflammatory phenotype. The potential impact of CAF senescence on tumor progression and the tumor microenvironment (TME) remains to be elucidated. Here, we systematically investigated the relationship between CAF senescence and the TME of pancreatic ductal adenocarcinoma (PDAC) based on multi-omics analysis and functional experiments. CAF senescence promotes tumor progression in vitro and in vivo and contributes to the formation of immunosuppressive TME. A CAF-senescence-related risk score was developed to predict overall survival, immune landscape, and treatment sensitivity in patients with PDAC. Further experiments revealed that plasminogen activator urokinase (PLAU) derived from senescent CAFs (SCAFs) promoted PDAC progression and was involved in immunosuppression. Together, these findings suggested that CAF senescence was correlated with tumor progression, and the CAF-senescence-based machine learning model could potentially predict prognosis in patients with PDAC.

PSMC2 promotes resistance against temozolomide in glioblastoma via suppressing JNK-mediated autophagic cell death

Temozolomide is universally used to treat glioblastoma due to its unique ability to cross the blood-brain barrier and inhibit tumor growth through DNA alkylation. However, over time, the inevitable emergence of resistance to temozolomide impedes successful treatment of this cancer. As a result, there is an urgent need to identify new therapeutic targets to improve treatment outcomes for this malignancy. In this work, acquired temozolomide-resistant glioblastoma cell lines LN18 (LN18-TR) and T98G (T98G-TR) exhibited stronger aggressiveness and lower endoplasmic reticulum (ER) stress than their parental cells.. Besides, temozolomide resistance was associated with elevated proteasome activity that suppressed ER stress, which was restored upon inhibition of the proteasome with MG132. Specifically, our study revealed that the 19S proteasomal regulatory subunit PSMC2, which was overexpressed in adapted temozolomide-resistant glioblastoma cells, reduced pro-death autophagy and decreased temozolomide sensitivity in parental cells when overexpressed. While autophagy increased in parental cells following temozolomide treatment, it was not elevated in temozolomide-resistant glioblastoma cells. Genetic suppression of PSMC2 triggered the JNK signalling pathway causing phosphorylation of BCL2, allowing Beclin1 to be released from the BCL2-Beclin1 complex. This boosted autophagosome nucleation, increased pro-death autophagy, and restored apoptosis in temozolomide-resistant glioblastoma cells. Finally, targeting PSMC2 provided a unique method for interrupting autophagy-mediated ER stress maintenance and temozolomide resistance in glioblastoma.

Association of Proteasome Activity and Pool Heterogeneity with Markers Determining the Molecular Subtypes of Breast Cancer

BACKGROUND

Proteasomes degrade intracellular proteins. Different proteasome forms were identified. Proteasome inhibitors are used in cancer therapy, and novel drugs directed to specific proteasome forms are developed. Breast cancer (BC) therapy depends on the subtype of the tumor, determined by the expression level of Ki67, HER-2, estrogen and progesterone receptors. Relationships between the presence of specific proteasome forms and proteins that determine the BC subtype remain unclear. Here, using gene expression data in 19,145 tumor samples from 144 datasets and tissues from 159 patients with different subtypes of BC, we investigated the association between the activity and expression of proteasomes and levels of BC subtype markers.

METHODS

Bioinformatic analysis of proteasome subunit (PSMB1-10) gene expression in BC was performed. Proteasome heterogeneity in BC cell lines was investigated by qPCR. By Western blotting, proteasome composition was assessed in cells and patient tissue lysates. Proteasome activities were studied using fluorogenic substrates. BC molecular subtypes were determined by immunohistochemistry.

RESULTS

BC subtypes demonstrate differing proteasome subunit expression pattern and strong PSMB8-10 co-correlation in tumors. A significant increase in chymotrypsin- and caspase-like proteasome activities in BC compared to adjacent tissues was revealed. The subunit composition of proteasomes in tumor tissues of BC subtypes varied. Regression analysis demonstrated a positive correlation between proteasome activities and the expression of Ki67, estrogen receptors and progesterone receptors.

CONCLUSION

BC subtypes demonstrate differences within the proteasome pool. Correlations between the proteasome activity, hormone receptors and Ki67 indicate possible mutual influence. Obtained results facilitate development of novel drug combinations for BC therapy.

Hsa_circ_0007718 facilitates the progression of colorectal cancer by regulating the miR-1299/PSMC2 axis

Colorectal cancer (CRC) represents one of the most prevalent forms of malignant tumors, characterized by a notably high rate of mortality among affected individuals. The primary objective of this investigation is to delve into the functional role of Hsa_circ_0007718 in the context of colorectal cancer and to elucidate its impact on the progression of CRC by modulating the interaction between the miR-1299 microRNA and its target gene, PSMC2. To assess the expression levels of Hsa_circ_0007718, along with miR-1299 and PSMC2, real-time quantitative fluorescent PCR (qRT-PCR) assays were meticulously performed using both CRC cell lines and clinical samples derived from patients. A cellular model was established to investigate the interactions occurring between miR-1299 and Hsa_circ_0007718, as well as the connections to PSMC2, thereby providing a comprehensive understanding of these molecular interactions. The findings of this research revealed a significant upregulation of Hsa_circ_0007718 in both colorectal cancer cell lines and tissue samples. Importantly, the data indicated that the suppression of Hsa_circ_0007718 led to a marked decrease in the proliferation rates, migratory potential, and invasive capabilities of CRC cells. Furthermore, the study confirmed that Hsa_circ_0007718 acts as a downstream target of miR-1299, exerting its regulatory effects by inhibiting miR-1299 and thereby promoting the expression of PSMC2.

Identification of basement membrane-related prognostic model associated with the immune microenvironment and synthetic therapy response in pancreatic cancer: integrated bioinformatics analysis and clinical validation

Pancreatic cancer (PC) is a common and highly malignant tumor. Basement membrane (BM) is formed by the crosslinking of extracellular matrix macromolecules and acts as a barrier against tumor cell metastasis. However, the role of BM in PC prognosis, immune infiltration, and treatment remains unclear. This study collected transcriptome and clinical survival data of PC via TCGA, GEO, and ICGC databases. PC patients (PCs) from the First Affiliated Hospital of Dalian Medical University were obtained as the clinical validation cohort. BM-related genes (BMRGs) were acquired from GeneCards and basement membraneBASE databases. A total of 46 differential-expressed BMRGs were identified. Then the BM-related prognostic model (including DSG3, MET, and PLAU) was built and validated. PCs with a low BM-related score had a better outcome and were more likely to benefit from oxaliplatin, irinotecan, and KRAS(G12C) inhibitor-12, and immunotherapy. Immune analysis revealed that BM-related score was positively correlated with neutrophils, cancer-associated fibroblasts, and macrophages infiltration, but negatively correlated with CD8+ T cells, NK cells, and B cells infiltration. PCs from the clinical cohort further verified that BM-related model could accurately predict PCs' outcomes. DSG3, MET, and PLAU were notably up-regulated within PC tissues and linked to a poor prognosis. In vitro experiments showed that DSG3 knockdown markedly suppressed the proliferation, migration, and invasion of PC cells. Molecular docking indicated that epigallocatechin gallate had a strong binding activity with DSG3, MET, and PLAU and may be used as a potential therapeutic agent for PC. In conclusion, this study developed a BM-related model associated with PC prognosis, immune infiltration, and treatment, which provided new insights into PC stratification and drug intervention.

Investigation of the Proteasome 26S Subunit, ATPase Family Genes as Potential Prognostic Biomarkers and Therapeutic Targets for Hepatocellular Carcinoma

Background

Several studies suggest that Proteasome 26S Subunit, ATPase (PSMC) family genes are of great importance in tumor progression and spreading, but the study for systematic evaluation of the function of PSMC genes in hepatocellular carcinoma (HCC) is currently lacking.

Methods

The functions of PSMC genes in HCC were analyzed using multiple online databases, including the TCGA database, GEO database, HPA database, cBioPortal database, DAVID, and KEGG pathway. Experiments were later conducted to verify PSMC expression.

Results

High levels of PSMC gene expression were detected in HCC tissues and PSMCs exhibited potentially powerful abilities in diagnosing HCC patients. All PSMC proteins are expressed to varying degrees in HCC tissues and high expression of the PSMC genes lead to poor prognosis in patients with HCC. Moreover, DNA methylation involves the regulation of the expression of PSMC2 and PSMC5 in HCC, and the levels of methylation of PSMC2 or PSMC5 correlate positively with patient overall survival in HCC patients. The copy number alteration and mutation of PSMC genes were observed and related to the expression of PSMCs in HCC. Functional enrichment analysis showed that many highly co-expressed genes of PSMCs had a potential role in tumor progression and metastasis, which merited further in-depth study. Functional network analysis also suggests that the primary biological function of PSMC genes is the regulation of protein homeostasis and energy metabolism in HCC. Moreover, the expression levels of PSMCs are related to immune cell infiltrates and immunomodulatory factors in HCC.

Conclusion

Our study indicates that PSMC genes are the potential target for precision immunotherapy and novel prognostic biomarkers for HCC.

PLAU promotes growth and attenuates cisplatin chemosensitivity in ARID1A-depleted non-small cell lung cancer through interaction with TM4SF1

Loss of ARID1A, a subunit of the SWI/SNF chromatin remodeling complex, contributes to malignant progression in multiple cancers including non-small cell lung cancer (NSCLC). In the search for key genes mediating the aggressive phenotype caused by ARID1A loss, we analyzed 3 Gene Expression Omnibus (GEO) datasets that contain RNA sequencing data from ARID1A-depleted cancer cells. PLAU was identified as a common gene that was induced in different cancer cells upon ARID1A depletion. Overexpression of PLAU positively modulated NSCLC cell growth, colony formation, cisplatin resistance, and survival under serum deprivation. Moreover, enforced expression of PLAU enhanced tumorigenesis of NSCLC cells in nude mice. Mechanistically, PLAU interacted with TM4SF1 to promote the activation of Akt signaling. TM4SF1-overexpressing NSCLC cells resembled those with PLAU overepxression. Knockdown of TM4SF1 inhibited the growth and survival and increased cisplatin sensitivity in NSCLC cells. The interaction between PLAU and TM4SF1 led to the activation of Akt signaling that endowed ARID1A-depleted NSCLC cells with aggressive properties. In addition, treatment with anti-TM4SF1 neutralizing antibody reduced the growth, cisplatin resistance, and tumorigenesis of ARID1A-depleted NSCLC cells. Taken together, PLAU serves as a target gene of ARID1A and promotes NSCLC growth, survival, and cisplatin resistance by stabilizing TM4SF1. Targeting TM4SF1 may be a promising therapeutic strategy for ARID1A-mutated NSCLC.

PSMC2 is a Novel Prognostic Biomarker and Predicts Immunotherapeutic Responses: From Pancreatic Cancer to Pan-Cancer

Background

Proteasome 26S subunit ATPase 2 (PSMC2) is a part of the 19S regulatory complex, which catalyzes the unfolding and transport of substrates into the 20S proteasome. Our previous research demonstrated that PSMC2 participates in the tumorigenesis and progression of pancreatic cancer (PC). However, no systematic analysis has been conducted to conclude its expression pattern and correlation with tumor immunity.

Aim

To investigate the expression level of PSMC2 in PC, its prognostic value and its relationship with tumor immunity.

Methods

In numerous public and internal cohorts, the expression, prognostic significance, and immunological connections of PSMC2 in PC were investigated. Additionally, using data from The Cancer Genome Atlas (TCGA), a pan-cancer analysis was carried out to examine PSMC2's immunological assocaition, and the predictive power of PSMC2 for immunotherapy was also evaluated in numerous public cohorts.

Results

PSMC2 was overexpressed in tumor tissues and linked to unfavorable prognosis in PC. PSMC2 was not only positively correlated with TIICs, also positively correlated with immune checkpoints in PC. In addition to PC, PSMC2 was expected to be an indicator of high immunogenicity in most cancer types. Importantly, PSMC2 could predict the immunotherapeutic responses in various cancer types, including urothelial carcinoma and breast cancer.

Conclusion

From PC to pan-cancer analysis, we report that PSMC2 is a novel prognostic biomarker in multiple cancer types. PSMC2 is related to the immuno-hot phenotype and predicts the outcome of immunotherapy. Therefore, the current study emphasizes that cancer patients with high PMSC2 expression should actively receive immunotherapy to improve their prognosis.

Construction and validation of an aging-related gene signature for prognosis prediction of patients with breast cancer

BACKGROUND

Breast cancer (BC) is an aging-related disease. Aging-related genes (ARGs) participate in the initiation and development of lung and colon cancer, but the prognosis signature of ARGs in BC has not been clearly studied.

AIMS

This study aimed to construct an ARGs signature to predict the prognosis of patients with breast cancer.

METHOD

Firstly, the expression data of ARGs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were collected. Then COX and least absolulute shrinkage and selection operator(LASSO) were performed to construct the ARGs prognostic signature. The correlation between the signature and immune cell infiltration, immunotherapeutic response and drug sensitivity were subsequently analysed. The TCGA nomogram was constructed by combining the signature with other clinical features, and was validated by using GEO database.

RESULTS

After LASSO and COX regression analyses, a prognostic signature based on nine ARGs, namely, HSP90AA1, NFKB2, PLAU, PTK2, RECQL4, CLU, JAK2, MAP3K5, and S100B, was built by using the TCGA dataset. Moreover, this risk signature is closely related to immune cell infiltration, immunotherapeutic response, and responses to chemotherapy and targeted therapy. Subsequently, The calibration curve demonstrates that the nomogram agrees well with practical prediction results. The receiver operating characteristic curve and decision-making curve analysis demonstrate that ARG signature has the better prognosis diagnosis ability and clinical net benefits.

CONCLUSIONS

Therefore, the proposed ARG prognosis signature is a new prognosis molecular marker of patients with BC, and it can provide good references to individual clinical therapy.

Pan-cancer analysis identifies proteasome 26S subunit, ATPase (PSMC) family genes, and related signatures associated with prognosis, immune profile, and therapeutic response in lung adenocarcinoma

Background: Proteasome 26S subunit, ATPase gene (PSMC) family members play a critical role in regulating protein degradation and are essential for tumor development. However, little is known about the integrative function and prognostic significance of the PSMC gene family members in lung cancer. Methods: First, we assessed the expression and prognostic features of six PSMC family members in pan-cancer from The Cancer Genome Atlas (TCGA) dataset. Hence, by focusing on the relationship between PSMC genes and the prognostic, genomic, and tumor microenvironment features in lung adenocarcinoma (LUAD), a PSMC-based prognostic signature was established using consensus clustering and multiple machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO) Cox regression, CoxBoost, and survival random forest analysis in TCGA and GSE72094. We then validated it in three independent cohorts from GEO and estimated the correlation between risk score and clinical features: genomic features (alterations, tumor mutation burden, and copy number variants), immune profiles (immune score, TIDE score, tumor-infiltrated immune cells, and immune checkpoints), sensitivity to chemotherapy (GDSC, GSE42127, and GSE14814), and immunotherapy (IMvigor210, GSE63557, and immunophenoscore). Twenty-one patients with LUAD were included in our local cohort, and tumor samples were submitted for evaluation of risk gene and PD-L1 expression. Results: Nearly all six PSMC genes were overexpressed in pan-cancer tumor tissues; however, in LUAD alone, they were all significantly correlated with overall survival. Notably, they all shared a positive association with increased TMB, TIDE score, expression of immune checkpoints (CD276 and PVR), and more M1 macrophages but decreased B-cell abundance. A PSMC-based prognostic signature was established based on five hub genes derived from the differential expression clusters of PSMC genes, and it was used to dichotomize LUAD patients into high- and low-risk groups according to the median risk score. The area under the curve (AUC) values for predicting survival at 1, 3, and 5 years in the training cohorts were all >.71, and the predictive accuracy was also robust and stable in the GSE72094, GSE31210, and GSE13213 datasets. The risk score was significantly correlated with advanced tumor, lymph node, and neoplasm disease stages as an independent risk factor for LUAD. Furthermore, the risk score shared a similar genomic and immune feature as PSMC genes, and high-risk tumors exhibited significant genomic and chromosomal instability, a higher TIDE score but lower immune score, and a decreased abundance of B and CD8⁺ T cells. Finally, high-risk patients were suggested to be less sensitive to immunotherapy but had a higher possibility of responding to platinum-based chemotherapy. The LUAD samples from the local cohort supported the difference in the expression levels of these five hub genes between tumor and normal tissues and the correlation between the risk score and PD-L1 expression. Conclusion: Overall, our results provide deep insight into PSMC genes in LUAD, especially the prognostic effect and related immune profile that may predict therapeutic responses.

Gene expressions and their significance in organoid cultures obtained from breast cancer patient-derived biopsies

Gene expression changes are one of the hallmarks of malignant cells and such changes in specific genes have been identified for a variety of human cancers. Such an association in gene expression changes becomes very significant for breast cancers due to the genetic heterogeneity seen in such cancers. It is due to such genetic implication that breast cancers are classified into several subtypes; based on the expression and the magnitude of expression of estrogen and progesterone receptor genes. Changes in the expression of ERBB2, ESR1, PLAU, MUC1, PGR, and TP53 are implicated in breast cancers. Of the various models available for cancer research, organoid cultures from patient-derived biopsies are being considered as the most relevant for invitro testing. Organoid cultures derived from patient biopsies mitigate several limitations of other commonly available models such as cancer cell lines. Such organoids retain the functional physiology of solid tumors which include gene expression. Also, utilizing patient derived organoids for in vitro testing paves way for personalized medicine which greatly enhances the effectiveness of cancer therapy for individuals. We present the genes implicated in breast cancers, the ways in which organoids can be derived from breast cancer biopsies and their applications for gene expression studies.

Lactate is a potential promoter of tamoxifen resistance in MCF7 cells

BACKGROUND

Tamoxifen is a widely used estrogen receptor inhibitor, whose clinical success is limited by the development of acquired resistance. This compound was also found to inhibit mitochondrial function, causing increased glycolysis and lactate production. Lactate has been widely recognized as a signaling molecule, showing the potential of modifying gene expression. These metabolic effects of tamoxifen can by hypothesized to contribute in driving drug resistance.

METHODS

To test this hypothesis, we used MCF7 cells together with a tamoxifen resistant cell line (MCF7-TAM). Experiments were aimed at verifying whether enhanced lactate exposure can affect the phenotype of MCF7 cells, conferring them features mirroring those observed in the tamoxifen resistant culture.

RESULTS

The obtained results suggested that enhanced lactate in MCF7 cells medium can increase the expression of tafazzin (TAZ) and telomerase complex (TERC, TERT) genes, reducing the cells' attitude to undergo senescence. In long term lactate-exposed cells, signs of EGFR activation, a pathway related to acquired tamoxifen resistance, was also observed.

CONCLUSIONS

The obtained results suggested lactate as a potential promoter of tamoxifen resistance. The off-target effects of this compound could play a role in hindering its therapeutic efficacy.

GENERAL SIGNIFICANCE

The features of acquired tamoxifen resistance have been widely characterized at the molecular level; in spite of their heterogeneity, poorly responsive cells were often found to display upregulated glycolysis. Our results suggest that this metabolic asset is not simply a result of neoplastic progression, but can play an active part in driving this process.

Current insights of applying MRI in Graves' ophthalmopathy

Graves' ophthalmopathy (GO) is an autoimmune disease related to Grave's disease (GD). The therapeutic strategies for GO patients are based on precise assessment of the activity and severity of the disease. However, the current assessment systems require development to accommodate updates in treatment protocols. As an important adjunct examination, magnetic resonance imaging (MRI) can help physicians evaluate GO more accurately. With the continuous updating of MRI technology and the deepening understanding of GO, the assessment of this disease by MRI has gone through a stage from qualitative to precise quantification, making it possible for clinicians to monitor the microstructural changes behind the eyeball and better integrate clinical manifestations with pathology. In this review, we use orbital structures as a classification to combine pathological changes with MRI features. We also review some MRI techniques applied to GO clinical practice, such as disease classification and regions of interest selection.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer

BACKGROUND

Aging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC.

METHODS

RNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort.

RESULTS

A six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations.

CONCLUSION

A novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.