The Biological Function Delineated Across Pan-Cancer Levels Through lncRNA-Based Prognostic Risk Assessment Factors for Pancreatic Cancer

Identifying the role of hypoxia-related lncRNAs in pancreatic cancer

BACKGROUND

Long noncoding RNAs (lncRNAs) play important roles in hypoxia-induced tumor processes. However, the prognostic value of hypoxia-related lncRNAs in pancreatic cancer is limited.

METHODS

Hypoxia-related lncRNAs were identified by coexpression analysis and the LncTarD database. LASSO analysis was performed to develop a prognostic model. The function of TSPOAP1-AS1 was studied in vitro and in vivo.

RESULTS

We recognized a set of fourteen hypoxia-related lncRNAs for the construction of a prognostic model. The prognostic model displayed excellent performance in predicting the prognosis of pancreatic cancer patients. The overexpression of TSPOAP1-AS1, a hypoxia-related lncRNA, attenuated the proliferation and invasion of pancreatic cancer cells. HIF-1α bound to the promoter of TSPOAP1-AS1 and impaired its transcription under hypoxia.

CONCLUSION

The hypoxia-related lncRNA assessment model might be a potential strategy for prognostic prediction in pancreatic cancer. The fourteen lncRNAs contained in the model could be helpful for uncovering the mechanisms of pancreatic tumorigenesis.

The cross-talk between LncRNAs and JAK-STAT signaling pathway in cancer

Long non-coding RNAs (lncRNAs) are non-coding RNAs that were transcribed from the human genome and have become important regulators in a number of cellular activities, mostly via controlling gene expression. A growing body of evidence shows that lncRNAs regulate various factors to impact various biological activities that are related to tumorigenesis, including the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway. lncRNAs influence the JAK-STAT signaling pathway either by directly targeting or via indirectly modulating other upstream or downstream pathways' components like members of the suppressor of cytokine signaling (SOCS) family, and other genes that regulate cell proliferation, apoptosis, migration, invasion, and epithelial-mesenchymal transition. Furthermore, lncRNAs can act as downstream effectors of the JAK-STAT pathway and mediates tumorigenesis. The relationship between JAK-STAT signaling and lncRNAs differs among various types of cancers. Besides, lncRNAs, as biological molecules, have been shown to play a dual role in either tumorigenesis or tumor suppression in various cancers. In this review, we focus on the reciprocated regulation and functions of lncRNAs and the JAK-STAT signaling pathway in cancer, as well as narrate the latest research progress on this association. A deeper understanding of this correlation may simplify the recognition of potential targets for clinical therapeutics.

Construction of anoikis-related lncRNAs risk model: Predicts prognosis and immunotherapy response for gastric adenocarcinoma patients

Background: Anoikis acts as a programmed cell death that is activated during carcinogenesis to remove undetected cells isolated from ECM. Further anoikis based risk stratification is expected to provide a deeper understanding of stomach adenocarcinoma (STAD) carcinogenesis. Methods: The information of STAD patients were acquired from TCGA dataset. Anoikis-related genes were obtained from the Molecular Signatures Database and Pearson correlation analysis was performed to identify the anoikis-related lncRNAs (ARLs). We performed machine learning algorithms, including Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (Lasso) analyses on the ARLs to build the OS-score and OS-signature. Clinical subgroup analysis, tumor mutation burden (TMB) detection, drug susceptibility analysis, immune infiltration and pathway enrichment analysis were further performed to comprehensive explore the clinical significance. Results: We established a STAD prognostic model based on five ARLs and its prognostic value was verified. Survival analysis showed that the overall survival of high-risk score patients was significantly shorter than that of low-risk score patients. The column diagrams show satisfactory discrimination and calibration. The calibration curve verifies the good agreement between the prediction of the line graph and the actual observation. TIDE analysis and drug sensitivity analysis showed significant differences between different risk groups. Conclusion: The novel prognostic model based on anoikis-related lncRNAs we identified could be used for prognosis prediction and precise therapy in gastric adenocarcinoma.

Prognostic significance of the systemic immune inflammation index in patients with metastatic and unresectable pancreatic cancer

Purpose

Systemic inflammatory markers may be predictors of the survival rate of patients with pancreatic cancer (PC). The aim of this work was to investigate the prognostic value of markers, mainly the systemic immune inflammation index (SII), in patients with metastatic and unresectable PC and to explore the relationship between markers and liver metastasis.

Methods

Records of patients with metastatic and unresectable PC at the Affiliated Hospital of Qingdao University from January 2000 to December 2019 and who were followed until December 2020 were retrospectively analyzed. Clinical data and laboratory indexes were collected, and cut-off values for inflammatory markers were determined using median values. The Cox proportional hazard model was used to analyze the prognostic value of the markers through univariate and multivariate survival analysis.

Results

All 253 patients met the inclusion criteria, and 102 (42.0%) patients had liver metastasis. The patients were divided into a high SII group and a low SII group, and the cut-off value was 533. In the multivariate analysis, high SII (HR = 2.151; p < 0.001), chemotherapy (HR = 0.546; p < 0.001), lymph node metastasis (HR = 4.053; p < 0.001), and distant metastasis (HR = 1.725; p = 0.001) were independent risk markers of overall survival (OS). The level of markers, mainly SII, PLR and NLR, were higher in patients with liver metastasis.

Conclusions

A high level of SII is an independent risk factor for short overall survival of patients with metastatic and unresectable PC. Patients with a high level of the inflammatory markers SII, PLR, and NLR, may be more prone to early liver metastasis.

Long non-coding RNA BZRAP1-AS1 functions in malignancy and prognosis for non-small-cell lung cancer

Purpose

The function of BZRAP1-AS1 is unknown in lung cancer. We evaluated the clinicopathologic significance of BZRAP1-AS1, and its role in non-small-cell lung cancer (NSCLC) progression.

Patient and methods

Sixty-three NSCLC patients from Beijing Chest Hospital were included. The expression of BZRAP1-AS1 was detected by real-time quantitative polymerase chain reaction (RT-qPCR) in tumor tissues and adjacent normal tissues. Then, the clinicopathological significance and prognostic value of BZRAP1-AS1 were analyzed by using our cohort and TCGA cohort. Finally, the effect of BZRAP1-AS1 on proliferation and motility of NSCLC cell lines were evaluated by cell growth assay, colony formation assay, xenograft tumorigenesis experiment in nude mice and transwell assays respectively.

Results

Compared with adjacent normal tissues, BZRAP1-AS1 showed lower expression in NSCLC tumor tissues. As for the relationship between BZRAP1-AS1 and clinical characteristics, our results were consistent with those of TCGA data. BZRAP1-AS1 was lower in T1 than T2-T4 patients, N1-N3 than N0 patients. Low level BZRAP1-AS1 was related to shorter overall survival time (OS) in lung adenocarcinoma (LUAD), and poor first progression time (FP) in LUAD and lung squamous cell carcinoma (LUSC) patients. BZRAP1-AS1 was significantly associated with the prognosis of NSCLC patients. Overexpression of BZRAP1-AS1 inhibited proliferation and migration of H1299 and HCC827 cells.

Conclusion

BZRAP1-AS1 expression decreases in tumor tissues with the increase of malignancy grades in NSCLC. BZRAP1-AS1 plays an anticancer role by inhibiting cell proliferation, invasion, and metastasis, and has a potential prognostic value in NSCLC. BZRAP1-AS1 may serve as a diagnostic marker and therapeutic target for NSCLC.

Long noncoding RNAs (lncRNAs) in pancreatic cancer progression

Long noncoding RNAs (lncRNAs) are RNA molecules involved in gene regulation at transcriptional, post-transcriptional, and epigenetic levels. LncRNAs participate in regulating apoptosis and autophagy in pancreatic cancer (PCa) and can promote and/or decrease the proliferation rate of tumor cells. The metastasis of PCa cells is tightly regulated by lncRNAs and they can affect the mechanism of epithelial-mesenchymal transition (EMT) to modulate metastasis. The drug resistance of PCa cells, especially to gemcitabine, can be affected by lncRNAs. In addition, lncRNAs enriched in exosomes can be transferred among tumor cells to regulate their proliferation and metastasis. Antitumor compounds, such as curcumin and ginsenosides, can regulate lncRNA expression in PCa therapy. As we discuss here, the expression level of lncRNAs can be considered as both a diagnostic and prognostic tool in patients with PCa.

Integrated Bioinformatics Analysis of Serine Racemase as an Independent Prognostic Biomarker in Endometrial Cancer

Endometrial cancer (EC) kills about 76,000 women worldwide, with the highest incidence in industrialized countries. Because of the rise in disease mortality and new diagnoses, EC is now a top priority for women’s health. Serine racemase (SRR) is thought to play a role in the central nervous system, but its role in cancers, particularly in EC, is largely unknown. The current study starts with a pan-cancer examination of SRR’s expression and prognostic value before delving into SRR’s potential cancer-suppressing effect in patients with EC. SRR may affect the endometrial tumor immune microenvironment, according to subsequent immune-related analysis. SRR expression is also linked to several genes involved in specific pathways such as ferroptosis, N6-methyladenosine methylation, and DNA damage repair. Finally, we used the expression, correlation, and survival analyses to investigate the upstream potential regulatory non-coding RNAs of SRR. Overall, our findings highlight the prognostic significance of SRR in patients with EC, and we can formulate a reasonable hypothesis that SRR influences metabolism and obstructs key carcinogenic processes in EC.

Integrative Analysis of 5-Hydroxymethylcytosine and Transcriptional Profiling Identified 5hmC-Modified lncRNA Panel as Non-Invasive Biomarkers for Diagnosis and Prognosis of Pancreatic Cancer

Pancreatic adenocarcinoma (PAAD) is the fourth leading cause of cancer-related deaths worldwide. 5-Hydroxymethylcytosine (5hmC)-mediated epigenetic regulation has been reported to be involved in cancer pathobiology and has emerged to be promising biomarkers for cancer diagnosis and prognosis. However, 5hmC alterations at long non-coding RNA (lncRNA) genes and their clinical significance remained unknown. In this study, we performed the genome-wide investigation of lncRNA-associated plasma cfDNA 5hmC changes in PAAD by plotting 5hmC reads against lncRNA genes, and identified six PAAD-specific lncRNAs with abnormal 5hmC modifications compared with healthy individuals. Then we applied machine-learning and Cox regression approaches to develop predictive diagnostic (5hLRS) and prognostic (5hLPS) models using the 5hmC-modified lncRNAs. The 5hLRS demonstrated excellent performance in discriminating PAAD from healthy controls with an area under the curve (AUC) of 0.833 in the training cohort and 0.719 in the independent testing cohort. The 5hLPS also effectively divides PAAD patients into high-risk and low-risk groups with significantly different clinical outcomes in the training cohort (log-rank test p = 0.04) and independent testing cohort (log-rank test p = 0.0035). Functional analysis based on competitive endogenous RNA (ceRNA) and enrichment analysis suggested that these differentially regulated 5hmC modified lncRNAs were associated with angiogenesis, circulatory system process, leukocyte differentiation and metal ion homeostasis that are known important events in the development and progression of PAAD. In conclusion, our study indicated the potential clinical utility of 5hmC profiles at lncRNA loci as valuable biomarkers for non-invasive diagnosis and prognostication of cancers.

Prognostic significance of systemic immune-inflammation index and platelet-albumin-bilirubin grade in patients with pancreatic cancer undergoing radical surgery

BACKGROUND

Systemic inflammatory markers are associated with patient survival in pancreatic cancer (PC). The aim of this study was to investigate the prognostic significance of the systemic immune-inflammation index (SII) in PC patients who underwent radical surgery. Platelet-albumin-bilirubin (PALBI) grade is a composite evaluation index based on liver function. Patients with pancreatic head cancer are prone to obstructive jaundice, which leads to abnormal liver function. Based on this, we also explored the prognostic value of PALBI grade in PC patients.

METHODS

Patients with pathologically confirmed PC who had undergone radical surgery (with negative surgical margin) for the first time at the Affiliated Hospital of Qingdao University from January 2013 to December 2019 and followed up by December 2020 were retrospectively analyzed. Peripheral blood cell count is easily affected by infection or hematological diseases, which affects the results, so it is excluded. Clinical data and laboratory examination indexes were collected. The SII and PALBI grade were calculated. The cutoff values were determined using the Youden index. The Cox proportional hazards regression model was used to analyze the prognostic value of the SII and PALBI grade through univariate and multivariate survival analysis.

RESULTS

A total of 214 patients [median age, 60.29 years; 128 (59.8%) men] met the inclusion criteria. There were 140 patients (65.4%) with pancreatic head cancer according to the tumor location. They were divided into high and low SII or PALBI groups by cutoff values of 705 and -5.6, respectively. According to the multivariate analysis, SII (P<0.001) was an independent factor negatively associated with overall survival (OS) and disease-free survival (DFS). In patients with pancreatic head cancer, PALBI grade was associated with shorter OS (P=0.031). The combination of high SII and high PALBI grade had stronger predictive value for poor prognosis (log-rank test, P<0.001), which the OS was 11.3 months less than the combination of low two groups.

CONCLUSIONS

SII was a promising prognostic biomarker in PC. And PALBI grade also showed predictive value for patients with pancreatic head cancer. Therefore, it can help predict the treatment outcomes in these patients.

A network pharmacology approach to reveal the pharmacological targets and biological mechanism of compound kushen injection for treating pancreatic cancer based on WGCNA and in vitro experiment validation

BACKGROUND

Compound kushen injection (CKI), a Chinese patent drug, is widely used in the treatment of various cancers, especially neoplasms of the digestive system. However, the underlying mechanism of CKI in pancreatic cancer (PC) treatment has not been totally elucidated.

METHODS

Here, to overcome the limitation of conventional network pharmacology methods with a weak combination with clinical information, this study proposes a network pharmacology approach of integrated bioinformatics that applies a weighted gene co-expression network analysis (WGCNA) to conventional network pharmacology, and then integrates molecular docking technology and biological experiments to verify the results of this network pharmacology analysis.

RESULTS

The WGCNA analysis revealed 2 gene modules closely associated with classification, staging and survival status of PC. Further CytoHubba analysis revealed 10 hub genes (NCAPG, BUB1, CDK1, TPX2, DLGAP5, INAVA, MST1R, TMPRSS4, TMEM92 and SFN) associated with the development of PC, and survival analysis found 5 genes (TSPOAP1, ADGRG6, GPR87, FAM111B and MMP28) associated with the prognosis and survival of PC. By integrating these results into the conventional network pharmacology study of CKI treating PC, we found that the mechanism of CKI for PC treatment was related to cell cycle, JAK-STAT, ErbB, PI3K-Akt and mTOR signalling pathways. Finally, we found that CDK1, JAK1, EGFR, MAPK1 and MAPK3 served as core genes regulated by CKI in PC treatment, and were further verified by molecular docking, cell proliferation assay, RT-qPCR and western blot analysis.

CONCLUSIONS

Overall, this study suggests that the optimized network pharmacology approach is suitable to explore the molecular mechanism of CKI in the treatment of PC, which provides a reference for further investigating biomarkers for diagnosis and prognosis of PC and even the clinical rational application of CKI.