MicroRNA-216a targets WT1 expression and regulates KRT7 transcription to mediate the progression of pancreatic cancer-A transcriptome analysis

A prognostic binary classifier comprised of five critical mRNAs stratified pancreatic cancer patients following resection

Background

Pancreatic cancer is characterized by an extremely poor prognosis, even following potentially curative resection. Classical prognostic markers such as histopathological or clinical parameters have limited predictive power. The present study aimed to establish a prognostic model combining mRNA expression data with histopathological and clinical data to better predict survival and stratify pancreatic cancer patients following resection. We pioneered three models in one study and systematically evaluated the clinical benefits of all three models.

Methods

To identify differentially expressed genes in pancreatic cancer, mRNA data from normal (GTEx database) and pancreatic cancer (TCGA database) tissues were used. Survival analysis was carried out to identify prognosis-relevant genes from the identified differentially expressed genes and LASSO regression was used to filter out hub genes. The risk score of several hub genes was calculated according to gene expression and coefficients. Validation was carried out using an independent set of GEO microarray data. Multivariate COX regression was used for identifying independent clinical and pathological risk factors related to patient's survival in the TCGA database and a prognostic model combining mRNA expression data with histopathological and clinical data was established. Another prognostic model using clinicopathological factors from the SEER database was conceived based on multivariate COX regression. NRI (net reclassification improvement) and IDI (integrated discrimination index) were used to compare the predictive capabilities of the different models.

Results

We identified 1589 differentially expressed genes (DEGs) through the comparison of normal and pancreatic cancer tissues, of whom 317 were associated with prognosis(p < 0.05). LASSO regression identified five hub genes, MYEOV, ANXA2P2, MET, CEP55, and KRT7, that were used for the five-mRNA-classifier prognostic model. The classifier could stratify patients into a short and long survival group: 5-year overall survival in the training set (TCGA, 6 % vs 52 %, p < 0.001), test set (TCGA, 18 % vs 55 %,p < 0.01) and external validation set (GEO, 0 % vs 25 %, p < 0.05). Sensitivity analysis showed that the mRNA model (model 1) was better than the clinicopathological no-mRNA model (model 2) in predicting 5-year survival in the TCGA database (AUC: 0.877 vs 0.718, z = 3.165, p < 0.01) and better than the multi-factor prognostic model (model 3) from the SEER database (AUC: 0.754, z = 2.637, p < 0.01). On predictive performance, model 1 improved model 2 (NRI = 0.084, z = 1.288, p = 0.198; IDI = 0.055, z = 1.041,p = 0.298) and model 3 (NRI = 0.167,z = 1.961,p = 0.05; IDI = 0.086, z = 1.427, p = 0.154).

Conclusion

The five-mRNA-classifier is a reliable and feasible instrument to predict the prognosis of pancreatic cancer patients following resection. It might help in patiens counseling and assist clinicians in providing individualized treatment for patients in different risk groups.

Clinical significance of KRT7 in bladder cancer prognosis

BACKGROUND

Typically, the overexpressed keratin 7 (KRT7) is considered a validated therapeutic target and prognosis marker in bladder cancer. However, the crucial roles of KRT7 in the clinical prognosis and immune microenvironment in bladder cancer remain unclear.

METHODS

Initially, the expression levels of KRT7 in public databases were analyzed that is,Tumor Immune Estimation Resource (TIMER) 2.0 and Gene Expression Profiling Interactive Analysis (GEPIA). Further, the clinical tissue samples from patients (n = 10 pairs) were collected to confirm the expression trends of KRT7 and detected by immunohistochemistry (IHC) analysis. Meanwhile, the relationship between KRT7 and the prognosis of bladder cancer patients was analyzed by Kaplan-Meier plotter estimation and Cox regression analysis. Finally, TIMER 2.0 and IHC staining analyses were performed to calculate the infiltration abundances of three kinds of immune cells in eligible bladder tumor samples.

RESULTS

The TIMER 2.0 and GEPIA datasets suggested the differences in the expression levels of KRT7 in tumors, in which KRT7 was significantly upregulated in bladder cancer. The KRT7 expression was closely associated with patients' gender, tumor histologic subtypes, T status, and American Joint Committee on Cancer stages. Notably, the increased KRT7 indicated poor overall survival and disease-free survival rates. Moreover, KRT7 expression could be responsible for immune infiltration in the cancer microenvironment of the bladder. Finally, the high expression level of KRT7 increased the presence of regulatory T cells (Tregs) but reduced the infiltration of CD8+ T and natural killer cells.

CONCLUSION

KRT7 as a biomarker potentiated the prediction of bladder cancer prognosis and the immune microenvironment.

Integrated analysis of scRNA-seq and bulk RNA-seq reveals that GPRC5A is an important prognostic gene in pancreatic cancer and is associated with B-cell Infiltration in pancreatic cancer

Introduction

Pancreatic cancer (PC) is a malignancy with poor prognosis. This investigation aimed to determine the relevant genes that affect the prognosis of PC and investigate their relationship with immune infiltration.

Methods

: First, we acquired PC single-cell chip data from the GEO database to scrutinize dissimilarities in immune cell infiltration and differential genes between cancerous and adjacent tissues. Subsequently, we combined clinical data from TCGA to identify genes relevant to PC prognosis. Employing Cox and Lasso regression analyses, we constructed a multifactorial Cox prognostic model, which we subsequently confirmed. The prognostic gene expression in PC was authenticated using RT-PCR. Moreover, we employed the TIMER online database to examine the relationship between the expression of prognostic genes and T and B cell infiltration. Additionally, the expression of GPRC5A and its correlation with B cells infiltration and patient prognosis were ascertained in tissue chips using multiple immune fluorescence staining.

Results

The single-cell analysis unveiled dissimilarities in B-cell infiltration between cancerous and neighboring tissues. We developed a prognostic model utilizing three genes, indicating that patients with high-risk scores experienced a more unfavorable prognosis. Immune infiltration analysis revealed a significant correlation among YWHAZ, GPRC5A, and B cell immune infiltration. In tissue samples, GPRC5A exhibited substantial overexpression and a robust association with an adverse prognosis, demonstrating a positive correlation with B cell infiltration.

Conclusion

GPRC5A is an independent risk factor in PC and correlated with B cell immune infiltration in PC. These outcomes indicated that GPRC5A is a viable target for treating PC.

Predicting the prognosis of glioma patients with TERT promoter mutations and guiding the specific immune profile of immune checkpoint blockade therapy

The telomerase reverse transcriptase promoter (TERTp) is frequently mutated in gliomas. This study sought to identify immune biomarkers of gliomas with TERTp mutations. Data from TCGA were used to identify and validate survival-associated gene signatures, and immune and stromal scores were calculated using the ESTIMATE algorithm. High stromal or immune scores in patients with TERTp-mutant gliomas correlated with shorter overall survival compared to cases with low stromal or immune scores. Among TERTp-mutant gliomas with both high immune and high stromal scores, 213 commonly shared DEGs were identified. Among 71 interacting DEGs representing candidate hub genes in a PPI network, HOXC6, WT1, CD70, and OTP showed significant ability in establishing subgroups of high- and low-risk patients. A risk model based on these 4 genes showed strong prognostic potential for gliomas with mutated TERTp, but was inapplicable for TERTp-wild-type gliomas. TERTp-mutant gliomas with high-risk scores displayed a greater percentage of naïve B cells, plasma cells, naïve CD4 T cells, and activated mast cells than low-risk score gliomas. TIDE analysis indicated that immune checkpoint blockade (ICB) therapy may benefit glioma patients with TERTp mutations. The present risk model can help predict prognosis of glioma patients with TERTp mutations and aid ICB treatment options.

Emerging insights into keratin 7 roles in tumor progression and metastasis of cancers

Keratin 7 (KRT7), also known as cytokeratin-7 (CK-7) or K7, constitutes the principal constituent of the intermediate filament cytoskeleton and is primarily expressed in the simple epithelia lining the cavities of the internal organs, glandular ducts, and blood vessels. Various pathological conditions, including cancer, have been linked to the abnormal expression of KRT7. KRT7 overexpression promotes tumor progression and metastasis in different human cancers, although the mechanisms of these processes caused by KRT7 have yet to be established. Studies have indicated that the suppression of KRT7 leads to rapid regression of tumors, highlighting the potential of KRT7 as a novel candidate for therapeutic interventions. This review aims to delineate the various roles played by KRT7 in the progression and metastasis of different human malignancies and to investigate its prognostic significance in cancer treatment. Finally, the differential diagnosis of cancers based on the KRT7 is emphasized.

Circulating microRNAs as Potential Biomarkers in Pancreatic Cancer-Advances and Challenges

There is an urgent unmet need for robust and reliable biomarkers for early diagnosis, prognosis, and prediction of response to specific treatments of many aggressive and deadly cancers, such as pancreatic cancer, and liquid biopsy-based miRNA profiling has the potential for this. MiRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many cancers, functioning as either oncomes or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling of dysregulated miRNAs in pancreatic cancer has been shown to correlate with disease diagnosis, indicate optimal treatment options and predict response to a specific therapy. Specific miRNA signatures can track the stages of pancreatic cancer and hold potential as diagnostic, prognostic, and predictive markers, as well as therapeutics such as miRNA mimics and miRNA inhibitors (antagomirs). Furthermore, identified specific miRNAs and genes they regulate in pancreatic cancer along with downstream pathways can be used as potential therapeutic targets. However, a limited understanding and validation of the specific roles of miRNAs, lack of tissue specificity, methodological, technical, or analytical reproducibility, harmonization of miRNA isolation and quantification methods, the use of standard operating procedures, and the availability of automated and standardized assays to improve reproducibility between independent studies limit bench-to-bedside translation of the miRNA biomarkers for clinical applications. Here I review recent findings on miRNAs in pancreatic cancer pathogenesis and their potential as diagnostic, prognostic, and predictive markers.

Molecular mechanisms of microRNA-216a during tumor progression

MicroRNAs (miRNAs) as the members of non-coding RNAs family are involved in post-transcriptional regulation by translational inhibiting or mRNA degradation. They have a critical role in regulation of cell proliferation and migration. MiRNAs aberrations have been reported in various cancers. Considering the importance of these factors in regulation of cellular processes and their high stability in body fluids, these factors can be suggested as suitable non-invasive markers for the cancer diagnosis. MiR-216a deregulation has been frequently reported in different cancers. Therefore, in the present review we discussed the molecular mechanisms of the miR-216a during tumor progression. It has been reported that miR-216a mainly functioned as a tumor suppressor through the regulation of signaling pathways and transcription factors. This review paves the way to suggest the miR-216a as a probable therapeutic and diagnostic target in cancer patients.

Construction of a novel model based on cell-in-cell-related genes and validation of KRT7 as a biomarker for predicting survival and immune microenvironment in pancreatic cancer

Background

Pancreatic cancer (PC) is a highly malignant tumor featured with high intra-tumoral heterogeneity and poor prognosis. Cell-in-cell (CIC) structures have been reported in multiple cancers, and their presence is associated with disease progression. Nonetheless, the prognostic values and biological functions of CIC-related genes in PC remain poorly understood.

Methods

The sequencing data, as well as corresponding clinicopathological information of PC were collected from public databases. Random forest screening, least absolute shrinkage, and selection operator (LASSO) regression and multivariate Cox regression analysis were performed to construct a prognostic model. The effectiveness and robustness of the model were evaluated using receiver operating characteristic (ROC) curves, survival analysis and establishing the nomogram model. Functional enrichment analyses were conducted to annotate the biological functions. The immune infiltration levels were evaluated by ESTIMATE and CIBERSORT algorithms. The expression of KRT7 (Keratin 7) was validated by quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry (IHC) staining. The CIC formation, cell clusters, cell proliferation, migration and invasion assays were applied to investigate the effects of silencing the expression of KRT7.

Results

A prognostic model based on four CIC-related genes was constructed to stratify the patients into the low- and high-risk subgroups. The high-risk group had a poorer prognosis, higher tumor mutation burden and lower immune cell infiltration than the low-risk group. Functional enrichment analyses showed that numerous terms and pathways associated with invasion and metastasis were enriched in the high-risk group. KRT7, as the most paramount risk gene in the prognostic model, was significantly associated with a worse prognosis of PC in TCGA dataset and our own cohort. High expression of KRT7 might be responsible for the immunosuppression in the PC microenvironment. KRT7 knockdown was significantly suppressed the abilities of CIC formation, cell cluster, cell proliferation, migration, and invasion in PC cell lines.

Conclusions

Our prognostic model based on four CIC-related genes has a significant potential in predicting the prognosis and immune microenvironment of PC, which indicates that targeting CIC processes could be a therapeutic option with great interests. Further studies are needed to reveal the underlying molecular mechanisms and biological implications of CIC phenomenon and related genes in PC progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09983-6.

Syntenin Regulated by miR-216b Promotes Cancer Progression in Pancreatic Cancer

Outcomes for patients with pancreatic cancer (PC) are poor; therefore, there is an urgent need to identify novel therapeutic targets involved in the progression of PC. We previously identified 161 differentially expressed proteins (DEPs) in PC. Syntenin (SDCBP) was identified as a survival-related protein through integrated, survival, and Cox analyses. High expression of SDCBP was associated with a poor prognosis in PC tissue and promoted the proliferation, migration, and invasion of PC cells, and induced epithelial–mesenchymal transition (EMT) via the PI3K/AKT pathway. Additionally, we elucidated the regulatory mechanism underlying these roles of SDCBP at the post-transcriptional level. microRNAs (miRNAs) of SDCBP were predicted using bioinformatics. Low levels of miR-216b expression were confirmed in PC tissues and were negatively correlated with SDCBP expression. miR-216b was found to directly regulate SDCBP expression through luciferase reporter assays. Furthermore, agomiR-216b restrained PC proliferation, migration, invasion, and EMT via the PI3K/AKT pathway, whereas antagomiR-216b facilitated this process. Notably, the knockout of SDCBP counteracted the effect of antagomiR-216b in PC, which suggested that miR-216b and SDCBP represent molecular targets underlying PC progression and EMT. Finally, the results were validated in in vivo studies. These findings indicated that low expression of miR-216b and the oncogene SDCBP contributes to PC migration, invasion, and EMT, and that they have potential as future therapeutic targets for patients with PC.