Orchestrating a biomarker panel with lncRNAs and mRNAs for predicting survival in pancreatic ductal adenocarcinoma

Long non-coding RNAs and pancreatic cancer: A multifaceted view

Pancreatic cancer (PC) is a highly malignant disease with a 5-year survival rate of only 10%. Families with PC are at greater risk, as are type 2 diabetes, pancreatitis, and other factors. Insufficient early detection methods make this cancer have a poor prognosis. Additionally, the molecular mechanisms underlying PC development remain unclear. Increasing evidence suggests that long non-coding RNAs (lncRNAs) contribute to PC pathology,which may control gene expression by recruiting histone modification complexes to chromatin and interacting with proteins and RNAs. In recent studies, abnormal regulation of lncRNAs has been implicated in PC proliferation, metastasis, invasion, angiogenesis, apoptosis, and chemotherapy resistance suggesting potential clinical implications. The paper reviews the progress of lncRNA research in PC about diabetes mellitus, pancreatitis, cancer metastasis, tumor microenvironment regulation, and chemoresistance. Furthermore, lncRNAs may serve as potential therapeutic targets and biomarkers for PC diagnosis and prognosis. This will help improve PC patients' survival rate from a lncRNA perspective.

LINC01589 serves as a potential tumor-suppressor and immune-related biomarker in endometrial cancer: A review

Currently, increasing attention is being paid to biomarkers in endometrial cancer. Immune infiltration of the tumor microenvironment has been shown to significantly affect the overall survival (OS) of uterine corpus endometrial carcinoma (UCEC) patients. LINC01589 is a long non-coding RNA (lncRNA) that is rarely reported in cancer and is assumed to play a role in immune regulation. We therefore evaluated the role of LINC01589 in UCEC using the Cancer Genome Atlas (TCGA) database. We analyzed the expression of LINC01589 using the gene expression profiles of LINC01589 in the UCEC projects in TCGA. Comparisons between the differentially expressed genes (DEGs) of the cancer and adjacent normal tissues of the UCEC projects revealed that LINC01589 expression was decreased in UCEC tissues. A multivariate cox regression analysis indicated that LINC01589 upregulation could serve as an independent prognostic factor for survival. Furthermore, there was a positive correlation between LINC01589 expression and B cell, T cell, NK cell, monocytic lineage, and myeloid dendritic cell infiltration in UCEC patients. In addition, 5 clusters of hub genes were detected by comparison of different expression levels of LINC01589 in the UCEC groups. The analysis of the reactome pathway using gene set enrichment analysis (GSEA) revealed immune-related pathways, including CD22-mediated B cell receptor (BCR) regulation and antigen-activated BCRs, leading to the generation of second messengers and complement cascade pathways that were significantly enriched in the high LINC01589 expression group. Thus, LINC01589 may serve as a prognostic biomarker, as it is associated with immune infiltration in UCEC.

5-mRNA-based prognostic signature of survival in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common non-small-cell lung cancer, with a high incidence and a poor prognosis.

AIM

To construct effective predictive models to evaluate the prognosis of LUAD patients.

METHODS

In this study, we thoroughly mined LUAD genomic data from the Gene Expression Omnibus (GEO) (GSE43458, GSE32863, and GSE27262) and the Cancer Genome Atlas (TCGA) datasets, including 698 LUAD and 172 healthy (or adjacent normal) lung tissue samples. Univariate regression and LASSO regression analyses were used to screen differentially expressed genes (DEGs) related to patient prognosis, and multivariate Cox regression analysis was applied to establish the risk score equation and construct the survival prognosis model. Receiver operating characteristic curve and Kaplan-Meier survival analyses with clinically independent prognostic parameters were performed to verify the predictive power of the model and further establish a prognostic nomogram.

RESULTS

A total of 380 DEGs were identified in LUAD tissues through GEO and TCGA datasets, and 5 DEGs (TCN1, CENPF, MAOB, CRTAC1 and PLEK2) were screened out by multivariate Cox regression analysis, indicating that the prognostic risk model could be used as an independent prognostic factor (Hazard ratio = 1.520, P < 0.001). Internal and external validation of the model confirmed that the prediction model had good sensitivity and specificity (Area under the curve = 0.754, 0.737). Combining genetic models and clinical prognostic factors, nomograms can also predict overall survival more effectively.

CONCLUSION

A 5-mRNA-based model was constructed to predict the prognosis of lung adenocarcinoma, which may provide clinicians with reliable prognostic assessment tools and help clinical treatment decisions.

LINC00960 regulates cell proliferation and glycolysis in pancreatic cancer through the miR-326-3p/TUFT1/AKT-mTOR axis

Pancreatic cancer (PC) is a common malignant cancer characterized by high mortality and poor prognosis. LINC00690 was involved in the occurrence and progression of PC, but the underlying mechanisms require further investigation. The goal of this study was to figure out how LINC00960 mediates glycolysis in PC. LINC00960, miR-326-3p, and Tuftelin 1 (TUFT1) expression levels were detected in PC cell lines. LINC00960 and TUFT1 expression levels were increased in PC cells when compared with normal pancreatic cells, whereas miR-326-3p expression levels were decreased. The expression levels of LINC00690 affected glycolysis in PC, and inhibition of LINC00960 inhibited tumor growth in vivo. LINC00690 targeted and suppressed the expression of miR-326-3p. MiR-326-3p bound to TUFT1, and miR-326-3p inhibited AKT-mTOR pathway activation via TUFT1. In conclusion, the depletion of LINC00960 repressed cell proliferation and glycolysis in PC by mediating the miR-326-3p/TUFT1/AKT-mTOR axis. Thus, we present a novel mechanism underlying the progression of PC that suggests LINC00960 is a potential therapeutic target for this cancer.

Long intergenic non-protein coding RNA 960 regulates cancer cell viability, migration and invasion through modulating miR-146a-5p/interleukin 1 receptor associated kinase 1 axis in pancreatic ductal adenocarcinoma

Long non-coding RNAs (lncRNAs) are considered as crucial regulatory factors in cancer biology. However, the biological function of long intergenic non-protein coding RNA 960 (LINC00960) in the tumorigenesis of pancreatic ductal adenocarcinoma (PDAC) is still unknown. The goal of this study is to investigate the role of LINC00960 in PDAC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to examine the expression levels of LINC00960 in PDAC tissues and cell lines. After transfection, the loss-of-function models of LINC00960 or interleukin 1 receptor-associated kinase 1 (IRAK1) were established with BxPC-3 cells and Colo357 cells, and the malignant phenotypes of BxPC-3 cells and Colo357 cells were detected by CCK-8 assay, BrdU assay and Transwell assay, respectively. The interactions among LINC00960, miR-146a-5p and IRAK1 were predicted by bioinformatics analysis, and verified by luciferase reporter assay, RNA immunoprecipitation assay and RNA pull-down assay. The regulatory functions of LINC00960 and miR-146a-5p on IRAK1 were detected by Western blot. We demonstrated that the LINC00960 expression was increased in PDAC tissues and cell lines. Knocking down LINC00960 or IRAK1 could repress the viability, migration, and invasion of BxPC-3 and Colo357 cells. LINC00960 functioned as a molecular sponge for miR-146a-5p, and IRAK1 was verified as a target gene of miR-146a-5p. Additionally, LINC00960 could up-regulate IRAK1 expression via repressing miR-146a-5p, and the oncogenic properties of LINC00960 were partly reversed by miR-146a-5p. Our findings reveal that LINC00960 is a promoter of PDAC progression through regulating miR-146a-5p/IRAK1axis.

Identification of key genes in cutaneous squamous cell carcinoma: a transcriptome sequencing and bioinformatics profiling study

Background

Long-term exposure to ultraviolet (UV) radiation can cause cutaneous squamous cell carcinoma (cSCC), which is one of the most common malignant cancers worldwide. Actinic keratosis (AK) is generally considered a precancerous lesion of cSCC. However, the pathogenesis and oncogenic processes of AK and cSCC remain elusive, especially in the context of photodamage.

Methods

In this study, transcriptome sequencing was performed on AK, cSCC, normal sun-exposed skin (NES) tissues, and normal non-sun-exposed skin (NNS) from 24 individuals. Bioinformatics analysis to identify the differentially expressed genes (DEGs) of 4 groups, and potential key genes of cSCC were validated by real-time quantitative reverse transcription PCR (qRT-PCR).

Results

A total of 46,930 genes were differentially expressed in the 4 groups, including 127 genes that were differentially expressed between NES and NNS, 420 DEGs in AK compared to NES, 1,658 DEGs in cSCC compared to NES, and 1,389 DEGs in cSCC compared to AK. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that the DEGs are involved in multiple pathways, including extracellular matrix (ECM)-receptor interaction, immune, inflammatory, microbial infection, and other related pathways. Finally, 5 new genes (HEPHL1, FBN2, SULF1, SULF2, and TCN1) were confirmed significantly upregulated in cSCC.

Conclusions

Using transcriptome sequencing and integrated bioinformatical analysis, we have identified key DEGs and pathways in cSCC, which could improve our understanding of the cause and underlying molecular events of AK and cSCC. HEPHL1, FBN2, SULF1, SULF2, and TCN1 may be novel potential biomarkers and therapeutic targets of cSCC.

Identification of a ten-long noncoding RNA signature for predicting the survival and immune status of patients with bladder urothelial carcinoma based on the GEO database: a superior machine learning model

Bladder urothelial carcinoma (BLCA) is recognized to be immunogenic and tumorigenic. This study identified a novel long noncoding RNA (lncRNA) signature for predicting survival for patients with BLCA. A univariate Cox regression model and the random survival forest-variable hunting (RSF-VH) algorithm were employed to achieve variable selection. Ten lncRNAs (LOC105375787, CYTOR, URB1-AS1, C21orf91-OT1, CASC15, LOC101928433, FLJ45139, LINC00960, HOTAIR and TTTY19) with the highest prognostic values were identified to establish the prognostic model. The nomogram integrating the signature and clinical factors showed high concordance index values of 0.94, 0.7 and 0.90 in the three datasets, and the calibration curves showed concordance between the predicted and observed 3- and 5-year survival rates. The risk score based on the 10-lncRNA signature accurately distinguished high- and low-risk BLCA patients with different disease-specific survival(DSS) or overall survival(OS) outcomes, which were stratified according to clinical factors, including T stage and tumour grade. Gene set enrichment analysis identified BLCA-specific biological pathways and enriched functional categories, such as the cell cycle, DNA repair and immune system. Furthermore, the increased infiltration of immune cells in the high-risk group indicated that lncRNA-related inflammation may reduce the survival of BLCA patients.

Morphologic and Molecular Landscape of Pancreatic Cancer Variants as the Basis of New Therapeutic Strategies for Precision Oncology

To date, pancreatic cancer is still one of the most lethal cancers in the world, mainly due to the lack of early diagnosis and personalized treatment strategies. In this context, the possibility and the opportunity of identifying genetic and molecular biomarkers are crucial to improve the feasibility of precision medicine. In 2019, the World Health Organization classified pancreatic ductal adenocarcinoma cancer (the most common pancreatic tumor type) into eight variants, according to specific histomorphological features. They are: colloid carcinoma, medullary carcinoma, adenosquamous carcinoma, undifferentiated carcinoma, including also rhabdoid carcinoma, undifferentiated carcinoma with osteoclast-like giant cells, hepatoid carcinoma, and signet-ring/poorly cohesive cells carcinoma. Interestingly, despite the very low incidence of these variants, innovative high throughput genomic/transcriptomic techniques allowed the investigation of both somatic and germline mutations in each specific variant, paving the way for their possible classification according also to specific alterations, along with the canonical mutations of pancreatic cancer (KRAS, TP53, CDKN2A, SMAD4). In this review, we aim to report the current evidence about genetic/molecular profiles of pancreatic cancer variants, highlighting their role in therapeutic and clinical impact.

Unsupervised Hierarchical Clustering of Pancreatic Adenocarcinoma Dataset from TCGA Defines a Mucin Expression Profile that Impacts Overall Survival

Simple Summary

Pancreatic cancer has a dramatic outcome (survival curve < 6 months) that is the consequence of late diagnosis and the lack of efficient therapy. We investigated the relationship between the 22 mucin gene expression and the patient survival in pancreatic cancer datasets that provide a comprehensive mapping of transcriptomic alterations occurring during carcinogenesis. Using unsupervised hierarchical clustering analysis of mucin gene expression patterns, we identified two major clusters of patients: atypical mucin signature (#1; MUC15, MUC14/EMCN, and MUC18/MCAM) and membrane-bound mucin signature (#2; MUC1, -4, -16, -17, -20, and -21). The signature #2 is associated with shorter overall survival, suggesting that the pattern of membrane-bound mucin expression could be a new prognostic marker for PDAC patients.

Abstract

Mucins are commonly associated with pancreatic ductal adenocarcinoma (PDAC) that is a deadly disease because of the lack of early diagnosis and efficient therapies. There are 22 mucin genes encoding large O-glycoproteins divided into two major subgroups: membrane-bound and secreted mucins. We investigated mucin expression and their impact on patient survival in the PDAC dataset from The Cancer Genome Atlas (PAAD-TCGA). We observed a statistically significant increased messenger RNA (mRNA) relative level of most of the membrane-bound mucins (MUC1/3A/4/12/13/16/17/20), secreted mucins (MUC5AC/5B), and atypical mucins (MUC14/18) compared to normal pancreas. We show that MUC1/4/5B/14/17/20/21 mRNA levels are associated with poorer survival in the high-expression group compared to the low-expression group. Using unsupervised clustering analysis of mucin gene expression patterns, we identified two major clusters of patients. Cluster #1 harbors a higher expression of MUC15 and atypical MUC14/MUC18, whereas cluster #2 is characterized by a global overexpression of membrane-bound mucins (MUC1/4/16/17/20/21). Cluster #2 is associated with shorter overall survival. The patient stratification appears to be independent of usual clinical features (tumor stage, differentiation grade, lymph node invasion) suggesting that the pattern of membrane-bound mucin expression could be a new prognostic marker for PDAC patients.

Autophagy-related long noncoding RNAs can predict prognosis in patients with bladder cancer

We investigated whether autophagy-related long noncoding RNAs (lncRNAs) can predict prognosis in bladder cancer. We obtained bladder cancer lncRNA data from The Cancer Genome Atlas and autophagy-related genes from the Human Autophagy Database. Fifteen autophagy-related lncRNAs with prognostic significance were identified. Multivariate Cox analysis was used to construct a risk score model, which divided bladder cancer patients into high-risk and low-risk groups. We found that patients in the low-risk group had better survival than those in the high-risk group. Subgroup analysis showed that patients in the high-risk group also had worse OS than that in the low-risk group in subgroups based on age, gender, clinical stage, and TNM stage. We next established a nomogram according to the results of multivariate Cox regression, which included age, gender, clinical stage, TNM stage, and risk score. The area under the curve for 3- and 5-year overall survival predicted by the nomogram were 0.711 and 0.719, respectively. Bioinformatics analysis demonstrated that the 15 identified lncRNAs are involved in the cell cycle, DNA replication, cell adhesion, cancer pathway, WNT signaling pathway, and oxidative stress. These findings confirm that autophagy-related lncRNAs are predictive of prognosis in bladder cancer patients and may affect tumor progression.

LINC00636 promotes lymph node metastasis and cervical cancer through targeting NM23

BACKGROUND

Metastasis is a major obstacle in treatment of cervical cancer, and long non-coding RNA (lncRNA) mediated regulatory effect on associated genes expression is found to be involved in metastasis. However, its mechanisms have not been fully elucidated.

MATERIALS AND METHODS

Specimens from patients with cervical cancer metastasis and non-metastasis were used to screen out candidate non-coding RNAs (ncRNAs) and possible downstream targets. And then, effects were determined in vitro and in vivo through knockdown and overexpression techniques.

RESULTS

LINC00636 was significantly higher in serum and solid tumor cells of metastatic cervical cancer patients than non-metastatic patients. And knockdown of LINC00636 significantly suppressed invasion, proliferation of cervical cancer cells. NM23 expression was negatively regulated by LINC00636 and it mediated anti-tumor effects was partially blocked by overexpression of LINC00636.

CONCLUSION

LINC00636 might promote metastasis of cervical cancer cells through inhibiting NM23 expression.

Research progress on long non-coding RNAs and their roles as potential biomarkers for diagnosis and prognosis in pancreatic cancer

Pancreatic cancer is one of the main causes of tumor-related deaths worldwide because of its low morbidity but extremely high mortality, and is therefore colloquially known as the "king of cancer." Sudden onset and lack of early diagnostic biomarkers directly contribute to the extremely high mortality rate of pancreatic cancer patients, and also make it indistinguishable from benign pancreatic diseases and precancerous pancreatic lesions. Additionally, the lack of effective prognostic biomarkers makes it difficult for clinicians to formulate precise follow-up strategies based on the postoperative characteristics of the patients, which results in missed early diagnosis of recurrent pancreatic cancer. Long non-coding RNAs (lncRNAs) can influence cell proliferation, invasion/migration, apoptosis, and even chemoresistance via regulation of various signaling pathways, leading to pro- or anti-cancer outcomes. Given the versatile effects of lncRNAs on tumor progression, using a single lncRNA or combination of several lncRNAs may be an effective method for tumor diagnosis and prognostic predictions. This review will give a comprehensive overview of the most recent research related to lncRNAs in pancreatic cancer progression, as targeted therapies, and as biomarkers for the diagnosis and prognosis of pancreatic cancer.

High expression of TCN1 is a negative prognostic biomarker and can predict neoadjuvant chemosensitivity of colon cancer

Transcobalamin (TCN1) is a vitamin B12 (cobalamin)-binding protein that regulates cobalamin homeostasis. Recent studies and bioinformatic analyses have found that TCN1 is highly expressed in cancer tissues and is associated with tumour aggressiveness and poor prognosis. The present study aimed to detect TCN1 as a novel biomarker for prognosis and chemosensitivity of colon cancer. Next-generation sequencing showed that TCN1 was one of several upregulated mRNAs in colon cancer, which was verified by further bioinformatics analyses. Western blotting (n = 9) and quantitative real time polymerase chain reaction (qRT-PCR, n = 30) revealed that TCN1 was highly expressed in colon cancer tissues at both the protein and mRNA level. A total of 194 cases of colon cancer were examined by immunohistochemistry and revealed that TCN1 expression level was related to advanced stages (P < 0.005). Kaplan-Meier analysis verified that patients with lower TCN1 expression usually had longer overall survival (P = 0.008). In addition, TCN1 was highly expressed in pulmonary metastatic tumour tissues (n = 37, P = 0.025) and exhibited higher levels in right-sided colon cancer than in left-sided colon cancer (P = 0.029). TCN1 expression in specimens that had received neoadjuvant chemotherapy decreased compared with that in colonoscopy biopsy tissues (n = 42, P = 0.009). Further bioinformatics analyses verified that apoptosis pathways might have a role in high TCN1 expression. All the studies revealed that TCN1 expression in colon cancer was significantly associated with malignant biological behaviour. Therefore, TCN1 could be used as a novel biomarker for colon cancer aggressiveness and prognosis and might also be a potential biomarker for predicting neoadjuvant chemosensitivity.

lncRNA STEAP3-AS1 Modulates Cell Cycle Progression via Affecting CDKN1C Expression through STEAP3 in Colon Cancer

Previous studies have reported that long noncoding RNAs (lncRNAs) have acted as new players during tumorigenesis. Metallothionein also plays an important role in tumor progression. It is mainly considered to be involved in the process of cell proliferation, oxidative stress, and multidrug resistance. However, the potential involvement of metallothionein-related lncRNAs in colon cancer remains poorly understood. In our study, we found that MT1M affected the expression of lncRNA STEAP3-AS1. STEAP3-AS1 is located in physical contiguity with STEAP3 and notably increased in colon cancer tissues and cell lines. STEAP3-AS1 expression was negatively associated with the expression of STEAP3. High levels of STEPA3-AS1 were associated with poor overall survival in colon cancer patients. In in vitro assays, STEAP3-AS1 knockdown could inhibit colon cancer cell proliferation and migration and arrest colon cancer cells at the G₀-G₁ phase. In tumorigenicity assays, STEAP3-AS1 knockdown could strongly inhibit tumor growth. Mechanistic investigations demonstrated that STEAP3-AS1 downregulation could increase the expression of cyclin-dependent kinase inhibitor 1C (CDKN1C) by STEAP3 upregulation. Overall, we identify the underlying role of MT1M-related lncRNA STEAP3-AS1 in colon cancer progression, which provides a novel strategy for colon cancer therapy.

Low Incidence of High-Grade Pancreatic Intraepithelial Neoplasia Lesions in a Crmp4 Gene-Deficient Mouse Model of Pancreatic Cancer

Pancreatic intraepithelial neoplasia (PanIN), the most common premalignant lesion of the pancreas, is a histologically well-defined precursor to invasive pancreatic ductal adenocarcinoma (PDAC). However, the molecular mechanisms underlying the progression of PanINs have not been fully elucidated. Previously, we demonstrated that the expression of collapsin response mediator protein 4 (CRMP4) in PDAC was associated with poor prognosis. The expression of CRMP4 was also augmented in a pancreatitis mouse model. However, the role of CRMP4 in the progression of PanIN lesions remains uncertain. In the present study, we examined the relationship between CRMP4 expression and progression of PanIN lesions using genetically engineered mouse models. PanIN lesions were induced by peritoneal injection of the cholecystokinin analog caerulein in LSL-KRAS^G12D; Pdx1-Cre (KC-Crmp4 wild-type, WT) mice and LSL-KRAS^G12D; Pdx1-Cre; Crmp4^−/− (KC-Crmp4 knockout, KO) mice. We analyzed pancreatic tissue sections from these mice and evaluated PanIN grade by hematoxylin and eosin staining. CRMP4 expression was examined and the cellular components assessed by immunohistochemistry using antibodies against CRMP4, CD3, and α-smooth muscle actin (SMA). The incidence of high-grade PanIN in KC-Crmp4 WT mice was higher than that in KC-Crmp4 KO animals. CRMP4 was expressed not only in epithelial cells but also in αSMA-positive cells in stromal areas of PanIN lesions. The CRMP4 expression in stromal areas correlated with PanIN grade in WT mice. These results suggested that the expression of CRMP4 in stromal cells may underlie the incidence or progression of PanIN.

Exosomes and Hepatocellular Carcinoma: From Bench to Bedside

As hepatocellular carcinoma (HCC) usually occurs in the background of cirrhosis, which is an end-stage form of liver diseases, treatment options for advanced HCC are limited, due to poor liver function. The exosome is a nanometer-sized membrane vesicle structure that originates from the endosome. Exosome-mediated transfer of proteins, DNAs and various forms of RNA, such as microRNA (miRNA), long noncoding RNA (lncRNA) and messenger RNA (mRNA), contributes to the development of HCC. Exosomes mediate communication between both HCC and non-HCC cells involved in tumor-associated cells, and several molecules are implicated in exosome biogenesis. Exosomes may be potential diagnostic biomarkers for early-stage HCC. Exosomal proteins, miRNAs and lncRNAs could provide new biomarker information for HCC. Exosomes are also potential targets for the treatment of HCC. Notably, further efforts are required in this field. We reviewed recent literature and demonstrated how useful exosomes are for diagnosing patients with HCC, treating patients with HCC and predicting the prognosis of HCC patients.