Extracellular Matrix-Related Six-lncRNA Signature as a Novel Prognostic Biomarker for Bladder Cancer

A novel LINC02321 promotes cell proliferation and decreases cisplatin sensitivity in bladder cancer by regulating RUVBL2

Bladder cancer (BC) has a high incidence and is prone to recurrence. In most instances, the low 5-year survival rate of advanced BC patients results from postoperative recurrence and drug resistance. Long noncoding RNAs (lncRNAs) can participate in numerous biological functions by regulating the expression of genes to affect tumorigenesis. Our previous work had demonstrated that a novel lncRNA, LINC02321, was associated with BC prognosis. In this study, A high expression of LINC02321 was found in BC tissues, which was associated with poor prognosis in patients. LINC02321 promoted both proliferation and G1-G0 progression in BC cells, while also inhibited sensitivity to cisplatin. Mechanistically, LINC02321 can bind to RUVBL2 and regulate the expression levels of RUVBL2 protein by affecting its half-life. RUVBL2 is involved in the DNA damage response. The potential of DNA damage repair pathways to exert chemosensitization has been demonstrated in vivo. The rescue experiment demonstrated that RUVBL2 overexpression can markedly abolish the decreased cell proliferation and the increased sensitivity of BC cells to cisplatin caused by LINC02321 knockdown. The results indicate that LINC02321 functions as an oncogene in BC, and may serve as a novel potential target for controlling BC progression and addressing cisplatin resistance in BC therapy.

A combination of cuproptosis and lncRNAs predicts the prognosis and tumor immune microenvironment in cervical cancer

BACKGROUND

Cuproptosis induces proteotoxic stress and eventually leads to cell death. However, the relationship between cuproptosis and lncRNAs in cervical cancer has not been fully elucidated. Therefore, we aim to explore the association among lncRNAs, cuproptosis and clinical features in cervical cancer.

METHODS

RNA sequencing, genetic mutations, and clinical data of CESC patients were obtained from TCGA. Cuproptosis-associated genes were gathered. WGCNA was used to cluster important modules, and KEGG, GO, GSEA and GSVA were used to explore functional and pathway enrichment. The association between immune microenvironment and cuproptosis-related lncRNAs was performed by using cibersort algorithm and other platforms, including XCELL, TIMER, QUANTISEQ, MCPCOUNTER and EPIC. Fluorescence quantitative PCR was employed to detect the expression of LINC01833 and LINC02321, and CCK-8 and cell scratch assays were used to assess cell proliferation and migration capabilities after LINCRNA interference.

RESULTS

202 upregulated and 45 downregulated lncRNAs were selected. The survival analysis showed that there was a statistically significant difference in survival rates between the high-risk and low-risk groups. The prognosis of tumour mutation burden and the degree of immune infiltration were differed noticeably between the high-risk and low-risk groups. BHG712, TL-2-105, FR-180204, Masitinib, TAK-715, ODI-027, JW-7-24-2, and OSI-930 had substantially higher IC50 values in the high-risk group. Notably, we found AL360178.1 was associated with RNF44 E3 ubiquitin ligase expression. In cervical cancer cell lines, LINC01833 and LINC02321 displayed significant upregulation. Efficient siRNA transfection led to a decreased expression of LINC01833 and LINC02321. This knockdown significantly hindered both cell proliferation and migration capabilities in cervical cancer cells compared to the negative control.

CONCLUSION

In conclusion, we constructed five cuprotosis-related lncRNA prognostic models, which may be new tumor therapeutic targets for the prevention and treatment of cervical cancer.

Identification and validation of LINC01322 as a potential prognostic biomarker and oncogene promoting tumor progression in lung adenocarcinoma

Our study identified a novel long noncoding RNA, LINC01322, that acts as an oncogene in lung adenocarcinoma progression. Cytoplasmic and nuclear RNA purification assays indicated that LINC01322 was localized in the cytoplasm and nucleus. Gene set enrichment analysis revealed the involvement of LINC01322 in the regulation of cell proliferation, migration, and the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway. LINC01322 may promote lung adenocarcinoma proliferation and migration through the Janus kinase/signal transducer and activator of transcription signaling pathway. In vitro experiments demonstrated that the knockdown of LINC01322 significantly suppressed lung adenocarcinoma cell proliferation, migration, and activation of the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway, whereas overexpression had the opposite effects. Inhibition of the Janus kinase 2/signal transducer and activator of transcription 3 pathway activity partially reversed the enhancement of cell proliferation and migration caused by LINC01322 overexpression. In vivo experiments further verified the oncogene role of LINC01322. Altogether, our findings suggest that LINC01322 promotes lung adenocarcinoma progression by activating the Janus kinase 2/signal transducer and activator of transcription 3 signaling pathway and that it could be a therapeutic target.

Carcinogenic roles of MAFG-AS1 in human cancers

The MAF bZIP transcription factor G-antisense RNA 1 (MAFG-AS1) is located on chromosome 17. MAFG-AS1 was upregulated in 15 human cancers. MAFG-AS1 not only suppresses 16 miRNAs but also directly impacts 22 protein-coding genes' expression. Notably, abnormal MAFG-AS1 expression is connected to clinicopathological characteristics and a worse prognosis in a variety of cancers. Moreover, MAFG-AS1 takes its part in the tumorigenesis and progression of various human malignancies by suppressing apoptosis and promoting proliferation, migration, invasion, aerobic glycolysis, ferroptosis, angiogenesis, EMT, and metastasis. Besides, it can predict treatment effectiveness in ER + breast cancer, urothelial bladder carcinoma, and liver cancer by functioning as a trigger of resistance to tamoxifen, sorafenib, and cisplatin. This study systematically presents the functions of MAFG-AS1 in various cancers, as well as the findings of bioinformatics analyses of the MAFG-AS1, which should give clear advice for future research.

LncRNA MAFG-AS1 is involved in human cancer progression

Long noncoding RNAs (lncRNAs) refer to a type of non-protein-coding transcript of more than 200 nucleotides. LncRNAs play fundamental roles in disease development and progression, and lncRNAs are dysregulated in many pathophysiological processes. Thus, lncRNAs may have potential value in clinical applications. The lncRNA, MAF BZIP Transcription Factor G (MAFG)-AS1, is dysregulated in several cancer, including breast cancer, lung cancer, liver cancer, bladder cancer, colorectal cancer, gastric cancer, esophagus cancer, prostate cancer, pancreatic cancer, ovarian cancer, and glioma. Altered MAFG-AS1 levels are also associated with diverse clinical characteristics and patient outcomes. Mechanistically, MAFG-AS1 mediates a variety of cellular processes via the regulation of target gene expression. Therefore, the diagnostic, prognostic, and therapeutic aspects of MAFG-AS1 have been widely explored. In this review, we discuss the expression, major roles, and molecular mechanisms of MAFG-AS1, the relationship between MAFG-AS1 and clinical features of diseases, and the clinical applications of MAFG-AS1.

A new marker constructed from immune-related lncRNA pairs can be used to predict clinical treatment effects and prognosis: in-depth exploration of underlying mechanisms in HNSCC

BACKGROUND

Long non-coding RNA (lncRNA) plays a vital role in tumor proliferation, migration, and treatment. Since it is challenging to standardize the gene expression levels detected by different platforms, the signatures composed of many immune-related single lncRNAs are still inaccurate. Utilizing a gene pair formed of two immune-related lncRNAs and strategically assigning values can effectively meet the demand for a higher-accuracy dual biomarker combination.

METHODS

Co-expression and differential expression analyses were performed on immune genes and lncRNAs data from The Cancer Genome Atlas and the ImmPort database to obtain differentially expressed immune-related lncRNAs for pairwise pairing. The prognostic-related differentially expressed immune-related lncRNAs (PR-DE-irlncRNAs) pairs were then identified by univariate Cox regression and used for lasso regression to construct a prognostic model. Various methods were used to validate the predictive prognostic performance of the model. Additionally, we explored the potential guiding value of the model in immunotherapy and chemotherapy and constructed a nomogram suitable for efficient prognosis prediction. Mechanistic exploration of anti-tumor immunity and mutational perspectives are also included. We also analyzed the correlation between the model and immune checkpoint inhibitors (ICIs)-related, N6-methyadenosine (m6A)-related, and multidrug resistance genes.

RESULTS

We used a total of 20 pairs of PR-DE-irlncRNAs to create a prognosis model. Quantitative real-time polymerase chain reaction experiments further verified the abnormal expression of 11 lncRNAs in HNSCC cells. Various methods have confirmed the excellent performance of the model in predicting patient prognosis. We reasoned that lncRNAs/TP53 mutation might play a positive/negative anti-tumor role through the immune system by multi-perspective analyses. Finally, it was found that the prognostic model was closely related to immunotherapy and chemotherapy as well as the expression of ICIs/m6A/multidrug resistance-related genes.

CONCLUSION

The prognostic model performs excellently in predicting the prognosis of patients and provides the potential value of practical guidance for treatment.

Ursolic acid-downregulated long noncoding RNA ASMTL-AS1 inhibits renal cell carcinoma growth via binding to HuR and reducing vascular endothelial growth factor expression

It has been reported ursolic acid (UA), one of the naturally abundant pentacyclic triterpenes, possesses a wide range of biological activities including anti-inflammatory, anti-atherosclerotic, and anticancer properties. Renal cell carcinoma (RCC) is a severe malignancy due to its asymptomatically spreading ability. Our study aimed to investigate the role and molecular mechanism of UA in RCC. RCC cell proliferation, migration, invasion, and angiogenesis were assessed using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, Transwell, and tube formation assays. Xenograft tumor models were established to confirm the role of UA and long noncoding RNA ASMTL antisense RNA 1 (ASMTL-AS1) in vivo. Expression levels of ASMTL-AS1 and vascular endothelial growth factor (VEGF) were measured using reverse transcriptase quantitative polymerase chain reaction and western blot analysis. The interaction probabilities of ASMTL-AS1 or VEGF with RNA-binding protein human antigen R (HuR) were verified by RNA immunoprecipitation experiment. The half-life period of messenger RNA (mRNA) was determined using actinomycin D. UA inhibited RCC cell growth in vivo and tumorigenesis in vitro. ASMTL-AS1 was highly expressed in RCC cell lines. Of note, UA downregulated ASMTL-AS1 expression, and overexpressed ASMTL-AS1 reversed the UA-induced suppression on RCC cell migration, invasion, and tube formation. Additionally, ASMTL-AS1 bound to HuR to maintain the stability of VEGF mRNA. Rescue experiments showed that the suppressed malignancy of RCC cells mediated by ASMTL-AS1 knockdown was counteracted by overexpression of VEGF. Moreover, silenced ASMTL-AS1 inhibited RCC tumor growth and metastasis in vivo. The obtained data suggest UA as a promising therapeutic agent to attenuate the development of RCC via regulation of the targeted molecules.

A review on the roles and molecular mechanisms of MAFG-AS1 in oncogenesis

Long non-coding RNAs (lncRNAs) have more than 200 nucleotides and do not encode proteins. At the same time, they can regulate various biological functions and therefore play an essential role as oncogenes or tumor suppressors in human cancers. MAFG-AS1 is an antisense RNA of MAF BZIP Transcription Factor G (MAFG) located at chromosome 17q25.3 head-to-head with the MAFG encoding gene containing a transcript size of 1895 bp. Accumulating evidence shows that MAFG-AS1 is overexpressed in many cancers, functions as an oncogene, and is significantly associated with poor clinical characteristics and prognosis. In this review, we first discuss the recent literature regarding the role of MAFG-AS1 in different cancers as well as its diagnostic and prognostic values. Then we will provide insights into its biological functions, such as its role in cancer progression, competing endogenous RNA (ceRNA) activity, regulation of EMT, glycolysis, energy metabolism, transcription factors, proteasomal degradation, and signaling pathways.

An angiogenesis‑related lncRNA signature for the prognostic prediction of patients with bladder cancer and LINC02321 promotes bladder cancer progression via the VEGFA signaling pathway

The mechanism underlying bladder cancer metastasis is associated with tumor angiogenesis. The present study aimed to evaluate the predictive role and value of an angiogenesis‑associated long non‑coding (lnc)RNA signature in patients with bladder cancer and the role of long intergenic non‑coding RNA (LINC)02321 in the progression of this malignancy. Angiogenesis‑related lncRNAs were screened using Pearson correlation analysis and the signaturewas constructed using Cox regression analysis and evaluated using the receiver operating characteristic curve. LINC02321, which expressed the largest difference in bladder cancer, was screened using reverse transcription‑quantitative PCR. The role of LINC02321 in the malignant progression of bladder cancer was evaluated using Transwell, wound healing and Cell Counting Kit 8 assays. A total of six angiogenesis‑associated lncRNAs (USP30‑AS1, LINC02321, PSMB8‑AS1, KRT7‑AS, LINC01767 and OCIAD1‑AS1) were identified as candidates for the prognostic signature using Cox regression analysis. The overall survival of patients in the low‑risk group was significantly longer compared with that in the high‑risk group, with the highest area under the curve value being 0.807. A nomogram was constructed based on the traditional clinical indicators (age, sex, grade, American Joint Committee on Cancer stage) and risk score of patients. Compared with the traditional clinical indicators, the risk score demonstrated better clinical prediction capacity for predicting the prognosis of patients with bladder cancer. The Cancer Genome Atlas prediction and RT‑qPCR experimental results demonstrated that only LINC02321 was highly expressed in bladder cancer tissue and promoted the proliferation, invasion, migration and cisplatin resistance of the malignancy. Gene set enrichment, Pearson's correlation analysis and experimental results demonstrated that the VEGFA signalling pathway may be involved in the LINC02321‑regulated progression of bladder cancer. In conclusion, the six angiogenesis‑associated lncRNA signatures reported in the present study may be used to predict the prognosis of patients with bladder cancer, and LINC02321 promoted malignant progression of bladder cancer via the VEGFA signalling pathway.

Prognostic significance and identification of basement membrane-associated lncRNA in bladder cancer

Based on the importance of basement membrane (BM) in cancer invasion and metastasis, we constructed a BM-associated lncRNA risk model to group bladder cancer (BCa) patients. Transcriptional and clinical data of BCa patients were downloaded from The Cancer Genome Atlas (TCGA), and the expressed genes of BM-related proteins were obtained from the BM-BASE database. We download the GSE133624 chip data from the GEO database as an external validation dataset. We screened for statistically different BM genes between tumors and adjacent normal tissues. Co-expression analysis of lncRNAs and differentially expressed BM genes was performed to identify BM-related lncRNAs. Then, differentially expressed BM-related lncRNAs (DEBMlncRNAs) between tumor and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select lncRNAs for risk assessment. LASSO analysis was performed to build a prognostic model. We constructed a model containing 8 DEBMlncRNAs (AC004034.1, AL662797.1, NR2F1-AS1, SETBP1-DT, AC011503.2, AC093010.2, LINC00649 and LINC02321). The prognostic risk model accurately predicted the prognosis of BCa patients and revealed that tumor aggressiveness and distant metastasis were associated with higher risk scores. In this model, we constructed a nomogram to assist clinical decision-making based on clinicopathological characteristics such as age, T, and N. The model also showed good predictive power for the tumor microenvironment and mutational burden. We validated the expression of eight lncRNAs using the dataset GSE133624 and two human bladder cancer cell lines (5637, BIU-87) and examined the expression and cellular localization of LINC00649 and AC011503.2 using a human bladder cancer tissue chip. We found that knockdown of LINC00649 expression in 5637 cells promoted the proliferation of 5637 cells.Our eight DEBMlncRNA risk models provide new insights into predicting prognosis, tumor invasion, and metastasis in BCa patients.

Downregulation of lncRNA ASMTL-AS1 in Epithelial Ovarian Cancer Correlates with Worse Prognosis and Cancer Progression

Given the characters of "Silent killer", epithelial ovarian cancer (EOC) usually suffered late diagnosis and poor prognosis. Therefore, this study aimed to explore the prognostic significance of ASMTL-AS1 in EOC and investigated the effect of lncRNA ASMTL-AS1 dysregulation on tumor cellular function. ASMTL-AS1 expression was analyzed in 133 EOC tissues and five kinds of cell lines by RT-qPCR. The expression of ASMTL-AS1 was tested for correlation with clinical data using the chi-square test and clinical follow-up using Kaplan-Meier method with log-rank test. Further, the prognostic parameters in predicting EOC overall survival were assessed by using multivariate Cox proportional hazards analysis. In vitro assays, including MTT assay and transwell assay, were conducted using EOC cell lines with overexpression of ASMTL-AS1. In tumorous tissues and cell lines, ASMTL-AS1 was lowly expressed compared with normal ones. This downregulation was associated with the advanced FIGO stage, positive ascites cytology, and lymph node. In particular, low levels of ASMTL-AS1 were revealed to have a high prognostic impact on EOC. ASMTL-AS1 overexpression strongly decreased cell proliferation, migration, and invasion in vitro partly by moderating miR-1228-3p. This study demonstrates a significant role for lowly expressed ASMTL-AS1 in EOC allowing for the prediction of prognosis for EOC. Considering that ASMTL-AS1 is strongly involved in cell growth and invasion, ASMTL-AS1 may be a promising marker for EOC prognosis and therapy.

KMT2B promotes the growth of renal cell carcinoma via upregulation of SNHG12 expression and promotion of CEP55 transcription

Background

This study aims to clarify the mechanistic action of long non-coding RNA (lncRNA) SNHG12 in the development of renal cell carcinoma (RCC), which may be associated with promoter methylation modification by KMT2B and the regulation of the E2F1/CEP55 axis.

Methods

TCGA and GEO databases were used to predict the involvement of SNHG12 in RCC. Knockdown of SNHG12/E2F1/CEP55 was performed. Next, SNHG12 expression and other mRNAs were quantified by RT-qPCR. Subsequently, CCK-8 was used to detect cell proliferation. Wound healing assay and Transwell assay were used to detect cell migration and invasion, respectively. The in vitro angiogenesis of human umbilical vein endothelial cells (HUVECs) was explored by matrigel-based capillary-like tube formation assay. ChIP assay was used to detect H3K4me3 in SNHG12 promoter region. The binding of E2F1 to CEP55 promoter region was analyzed with ChIP and dual luciferase reporter assays. RIP assay was used to detect the binding of SNHG12 to E2F1. Finally, the effect of SNHG12 on the tumor formation and angiogenesis of RCC was assessed in nude mouse xenograft model.

Results

SNHG12 was highly expressed in RCC tissues and cells, and it was related to the poor prognosis of RCC patients. SNHG12 knockdown significantly inhibited RCC cell proliferation, migration, and invasion and HUVEC angiogenesis. KMT2B up-regulated SNHG12 expression through modifying H3K4me3 in its promoter region. In addition, SNHG12 promoted CEP55 expression by recruiting the transcription factor E2F1. Knockdown of SNHG12 blocked E2F1 recruitment and down-regulated the expression of CEP55, thereby inhibiting tumor formation and angiogenesis in nude mice.

Conclusion

The evidence provided by our study highlighted the involvement of KMT2B in up-regulation of lncRNA as well as the transcription of CEP55, resulting in the promotion of angiogenesis and growth of RCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02607-w.

Identification of immune-related lncRNA panel for predicting immune checkpoint blockade and prognosis in head and neck squamous cell carcinoma

Purpose

Immunotherapy is changing head and neck squamous cell carcinoma (HNSCC) treatment pattern. According to the Chinese Society of Clinical Oncology (CSCO) guidelines, immunotherapy has been deemed as first‐line recommendation for recurrent/metastatic HNSCC, marking that advanced HNSCC has officially entered the era of immunotherapy. Long non‐coding RNAs (lncRNAs) impact every step of cancer immunity. Therefore, reliable immune‐lncRNAs able to accurately predict the immune landscape and survival of HNSCC are crucial to clinical management.

Methods

In the current study, we downloaded the transcriptomic and clinical data of HNSCC from The Cancer Genome Atlas and identified differentially expressed immune‐related lncRNAs (DEir‐lncRNAs). Further then, Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify proper DEir‐lncRNAs to construct optimal risk model. Low‐risk and high‐risk groups were classified based on the optimal cut‐off value generated by the areas under curve for receiver operating characteristic curves (AUC), and Kaplan–Meier survival curves were utilized to validate the prediction model. We then evaluated the model based on the clinical factors, immune cell infiltration, and chemotherapeutic and immunotherapeutic efficacy between two groups.

Results

In our study, we identified 256 Deir‐lncRNAs in HNSCC. A total of 18 Deir‐lncRNA pairs (consisting of 35 Deir‐lncRNAs) were used to construct a risk model significantly associated with survival of HNSCC. Cox proportional hazard regression analysis confirmed that our risk model could be served as an independent prognostic indicator. Besides, HNSCC patients with low‐risk score significantly enriched of CD8⁺ T cell, and corelated with high chemosensitivity and immunotherapeutic sensitivity.

Conclusion

Our risk model could be served as a promising clinical prediction indicator, effective discoursing of the immune cell infiltration of HNSCC patients, and distinguishing patients who could benefit from chemotherapy and immunotherapy.

Upregulated LINC00922 Promotes Epithelial-Mesenchymal Transition and Indicates a Dismal Prognosis in Gastric Cancer

Background. LINC00922 has been found to promote epithelial-mesenchymal transition (EMT) in a variety of tumors. But its functions in gastric cancer (GC) remain unclear. We attempt to investigate the correlation between LINC00922 and GC via bioinformatics analysis, in vitro and in vivo experiments. Methods. TCGA and GTEx databases were utilized to obtain the RNAseq and clinical data of GC, and then, identified the correlation of LINC00922 with patients’ clinicopathological characteristics and prognosis. GSEA and GO/KEGG enrichment analyses were performed to explore the potential functions or signaling pathways that LINC00922 participated in GC. Infiltration levels of immune cells were employed by ssGSEA algorithm, and then Wilcoxon rank sum test was applied to analyze their correlations with LINC00922. Scratch and transwell assays were conducted to detect the invasion and migration abilities of GC cells. Western blot was performed to explore the expression level of EMT-related proteins. Furthermore, we constructed the xenograft tumor model and metastatic tumor model in nude mice to explore the effect of LINC00922 downregulating on metastasis of GC cells in vivo. Results. Compared with normal tissues, LINC00922 was highly expressed in GC tissues and positively correlated with poor prognosis. The correlation existed between LINC00922 and immune infiltration in GC. Downregulation of LINC00922 inhibited the EMT process of GC cells. In addition, both in vitro and in vivo experiments showed that LINC00922 affects the invasion and migration abilities of GC. Conclusions. LINC00922 promotes the migration, invasion, and EMT in GC and has the potential to be used as a prognostic biomarker and therapeutic target for GC.

Exosomal LncRNAs and hepatocellular Carcinoma: From basic research to clinical practice

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with poor prognosis. The incidences of HCC and HCC-related deaths have increased over the last several decades. However, the treatment options for advanced HCC are very limited. Long noncoding RNAs (lncRNAs) wrapped in exosomes can change the expression of their target genes in recipient cells, thereby regulating the behavior of recipient cells. Increasing evidence has demonstrated that there is a correlation between the activation of exosomal lncRNAs and the development of HCC. In this review article, we highlighted the functions of exosomal lncRNAs in the development of HCC, showing that exosomal lncRNAs play a vital role in the growth and progression of HCC and are targets for HCC.

Integrative Analyses of Circulating mRNA and lncRNA Expression Profile in Plasma of Lung Cancer Patients

Circulating-free RNAs (cfRNAs) have been regarded as potential biomarkers for “liquid biopsy” in cancers. However, the circulating messenger RNA (mRNA) and long noncoding RNA (lncRNA) profiles of lung cancer have not been fully characterized. In this study, we profiled circulating mRNA and lncRNA profiles of 16 lung cancer patients and 4 patients with benign pulmonary nodules. Compared with benign pulmonary nodules, 806 mRNAs and 1,762 lncRNAs were differentially expressed in plasma of lung adenocarcinoma patients. For lung squamous cell carcinomas, 256 mRNAs and 946 lncRNAs were differentially expressed. A total of 231 mRNAs and 298 lncRNAs were differentially expressed in small cell lung cancer. Eleven mRNAs, 51 lncRNAs, and 207 canonical pathways were differentially expressed in lung cancer in total. Forty-five blood samples were collected to verify our findings via performing qPCR. There are plenty of meaningful mRNAs and lncRNAs that were found. MYC, a transcription regulator associated with the stemness of cancer cells, is overexpressed in lung adenocarcinoma. Transforming growth factor beta (TGFB1), which plays pleiotropic roles in cancer progression, was found to be upregulated in lung squamous carcinoma. MALAT1, a well-known oncogenic lncRNA, was also found to be upregulated in lung squamous carcinoma. Thus, this study provided a systematic resource of mRNA and lncRNA expression profiles in lung cancer plasma.

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LncRNA ASMTL-AS1/microRNA-1270 differentiate prognostic groups in gastric cancer and influence cell proliferation, migration and invasion

The objective of this study was to determine the expression levels of ASMTL-AS1 and miR-1270 in gastric cancer, and to explore whether ASMTL-AS1 and miR-1270 is associated with cancer prognosis and progression or not. ASMTL-AS1 and miR-1270 expression were quantified in gastric cancer tissues and adjacent normal tissues (n = 167) and cell lines. The potential of ASMTL-AS1 and miR-1270 as prognostic biomarkers was evaluated by the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox regression analyses. The binding between ASMTL-AS1 and miR-1270 was verified by the Luciferase reporter assay and RNA pull-down assay. Functional roles of ASMTL-AS1/miR-1270 on cells were investigated in HGC-27 and NCI-N87 cells by MTS viability, Transwell migration, and Matrigel invasion assay. ASMTL-AS1 was significantly downregulated while miR-1270 was upregulated in gastric cancer tissues as compared with normal tissue and cell lines. According to the studies, ASMTL-AS1 and miR-1270 were related to unfavorable clinical parameters, such as the advanced TNM stage. Downregulated ASMTL-AS1 and upregulated miR-1270 were associated with reduced 5-year overall survival. Functional studies suggested that ASMTL-AS1 inhibits proliferation, migration, and invasion of HGC-27 and NCI-N87 cells by regulation of miR-1270. In summary, ASMTL-AS1 and miR-1270 are associated with poor prognosis of patients with gastric cancer. ASMTL-AS1 inhibited gastric cancer progression by regulating miR-1270. Therefore, ASMTL-AS1/miR-1270 may be a potential prognostic biomarker and novel strategy for gastric cancer targeted therapy.

Recognition of Glycometabolism-Associated lncRNAs as Prognosis Markers for Bladder Cancer by an Innovative Prediction Model

The alteration of glycometabolism is a characteristic of cancer cells. Long non-coding RNAs (lncRNAs) have been documented to occupy a considerable position in glycometabolism regulation. This research aims to construct an effective prediction model for the prognosis of bladder cancer (BC) based on glycometabolism-associated lncRNAs (glyco-lncRNAs). Pearson correlation analysis was applied to get glyco-lncRNAs, and then, univariate cox regression analysis was employed to further filtrate survival time-associated glyco-lncRNAs. Multivariate cox regression analysis was utilized to construct the prediction model to divide bladder cancer (BC) patients into high- and low-risk groups. The overall survival (OS) rates of these two groups were analyzed using the Kaplan-Meier method. Next, gene set enrichment analysis and Cibersortx were used to explore the enrichment and the difference in immune cell infiltration, respectively. pRRophetic algorithm was applied to explore the relation between chemotherapy sensitivity and the prediction model. Furthermore, reverse transcriptase quantitative polymerase chain reaction was adopted to detect the lncRNAs constituting the prediction signature in tissues and urine exosomal samples of BC patients. A powerful model including 6 glyco-lncRNAs was proposed, capable of suggesting a risk score for each BC patient to predict prognosis. Patients with high-risk scores demonstrated a shorter survival time both in the training cohort and testing cohort, and the risk score could predict the prognosis without depending on the traditional clinical traits. The area under the receiver operating characteristic curve of the risk score was higher than that of other clinical traits (0.755 > 0.640, 0.485, 0.644, or 0.568). The high- and low-risk groups demonstrated very distinct immune cells infiltration conditions and gene set enriched terms. Besides, the high-risk group was more sensitive to cisplatin, docetaxel, and sunitinib. The expression of lncRNA AL354919.2 featured with an increase in low-grade patients and a decrease in T3-4 and Stage III-IV patients. Based on the experiment results, lncRNA AL355353.1, AC011468.1, and AL354919.2 were significantly upregulated in tumor tissues. This research furnishes a novel reference for predicting the prognosis of BC patients, assisting clinicians with help in the choice of treatment.

ECM-Receptor Regulatory Network and Its Prognostic Role in Colorectal Cancer

Interactions of the extracellular matrix (ECM) and cellular receptors constitute one of the crucial pathways involved in colorectal cancer progression and metastasis. With the use of bioinformatics analysis, we comprehensively evaluated the prognostic information concentrated in the genes from this pathway. First, we constructed a ECM-receptor regulatory network by integrating the transcription factor (TF) and 5'-isomiR interaction databases with mRNA/miRNA-seq data from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD). Notably, one-third of interactions mediated by 5'-isomiRs was represented by noncanonical isomiRs (isomiRs, whose 5'-end sequence did not match with the canonical miRBase version). Then, exhaustive search-based feature selection was used to fit prognostic signatures composed of nodes from the network for overall survival prediction. Two reliable prognostic signatures were identified and validated on the independent The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) cohort. The first signature was made up by six genes, directly involved in ECM-receptor interaction: AGRN, DAG1, FN1, ITGA5, THBS3, and TNC (concordance index 0.61, logrank test p = 0.0164, 3-years ROC AUC = 0.68). The second hybrid signature was composed of three regulators: hsa-miR-32-5p, NR1H2, and SNAI1 (concordance index 0.64, logrank test p = 0.0229, 3-years ROC AUC = 0.71). While hsa-miR-32-5p exclusively regulated ECM-related genes (COL1A2 and ITGA5), NR1H2 and SNAI1 also targeted other pathways (adhesion, cell cycle, and cell division). Concordant distributions of the respective risk scores across four stages of colorectal cancer and adjacent normal mucosa additionally confirmed reliability of the models.

Gender Differences in Urothelial Bladder Cancer: Effects of Natural Killer Lymphocyte Immunity

Men are more likely to develop cancer than women. In fact, male predominance is one of the most consistent cancer epidemiology findings. Additionally, men have a poorer prognosis and an increased risk of secondary malignancies compared to women. These differences have been investigated in order to better understand cancer and to better treat both men and women. In this review, we discuss factors that may cause this gender difference, focusing on urothelial bladder cancer (UBC) pathogenesis. We consider physiological factors that may cause higher male cancer rates, including differences in X chromosome gene expression. We discuss how androgens may promote bladder cancer development directly by stimulating bladder urothelium and indirectly by suppressing immunity. We are particularly interested in the role of natural killer (NK) cells in anti-cancer immunity.

Bioinformatics analysis based on immune-autophagy-related lncRNAs combined with immune infiltration in bladder cancer

Background

To construct a prognostic model based on immune-autophagy-related long noncoding RNA (IArlncRNAs), mainly to predict the overall survival rate (OS) of bladder cancer patients and investigate its possible mechanisms.

Methods

Transcriptome and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We identified the IArlncRNA by co-expression analysis, differential expression analysis, and Venn analysis. Then, we identified the independent prognostic IArlncRNAs by univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. Moreover, we constructed the prognostic model based on the independent prognostic IArlncRNAs and clinical features. The proportion of 22 immune cell subtypes was analyzed by the CIBERSORT algorithm. Besides, we identified the differential proportion of 22 immune cell subtypes between the high- and low-risk groups. In addition, we identified the correlation between immune-infiltrating cells (screened by univariate Cox regression and multivariate Cox regression analysis) and IArlncRNAs by Pearson correlation analysis. Finally, we estimated the half-maximal inhibitory concentration (IC₅₀) of chemotherapeutic drugs in patients with bladder cancer based on the pRRophetic algorithm.

Results

Four IArlncRNAs were identified as independent prognostic factors, including AL136084.3, AC006270.1, Z84484.1, and AL513218.1. The OS of patients in the high-risk group was significantly worse compared to the low-risk group. The nomogram showed an excellent predictive effect with the C-index of 0.64. The calibration chart showed a good actual vs. predicted probability. B cells naïve, T cells CD8, T cells CD4 memory resting, T cells follicular helper, macrophages M1, dendritic resting and activated cells had higher infiltrations in the low-risk group and lower infiltration of macrophages M2. The fraction of macrophages M2 was positively associated with AL136084.3. The fraction of T cells CD8 was positively associated with Z84484.1. The fraction of M + macrophages M0 was negatively associated with Z84484.1. Further, we identified the differential IC₅₀ of 24 chemotherapeutic drugs between the high- and low-risk groups.

Conclusions

The prognostic model based on 4 IArlncRNAs showed an excellent predictive effect. Furthermore, we reasonably speculated that IArlncRNAs are directly or indirectly involved in the immune regulation of the tumor microenvironment (TME), as well as autophagy.

Identification of a Nomogram from Ferroptosis-Related Long Noncoding RNAs Signature to Analyze Overall Survival in Patients with Bladder Cancer

Purpose

This study aimed to establish a nomogram to predict the overall survival (OS) of patients with bladder cancer (BC) by ferroptosis-related long noncoding RNAs (FRlncRNAs) signature.

Methods

We obtained FRlncRNAs expression profiles and clinical data of patients with BC from the Cancer Genome Atlas database. The patients were divided into the training set, testing set, and overall set. Lasso regression and multivariate Cox regression were used to establish the FRlncRNAs signature, the prognosis of each group was compared by Kaplan–Meier (K-M) analysis, and the receiver operating characteristic (ROC) curve evaluated the accuracy of the model. The Gene Set Enrichment Analysis (GSEA) was used for the visualization of the functional enrichment for FRlncRNAs. The databases of GEPIA and K-M Plotter were used for subsequent functional analysis of major FRlncRNAs.

Results

Thirteen prognostic FRlncRNAs (LINC00942, MAFG-DT, AL049840.3, AL136084.3, OCIAD1-AS1, AC062017.1, AC008074.2, AC018653.3, AL031775.1, USP30-AS1, LINC01767, AC132807.2, and AL354919.2) were identified to be significantly different, constituting an FRlncRNAs signature. Patients with BC were divided into low-risk group and high-risk group by this signature in the training, testing, and overall sets. K-M analysis showed that the prognosis of patients in the high-risk group was poor and the difference in the subgroup analyses was statistically significant. ROC analysis revealed that the predictive ability of the model was more accurate than traditional assessment methods. A risk score based on FRlncRNAs signature was an independent prognostic factor for the patients with BC (HR = 1.388, 95%CI = 1.228–1.568, P < 0.001). Combining the FRlncRNAs signature and clinicopathological factors, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients and had high clinical practicability. The GSEA analysis showed that the primary pathways were WNT, MAPK, and cell-matrix adhesion signaling pathways. The major FRlncRNAs (MAFG-DT) were associated with poor prognosis in the GEPIA and K-M Plotter database.

Conclusion

Thirteen prognostic FRlncRNAs and their nomogram were accurate tools for predicting the OS of BC, which might be molecular biomarkers and therapeutic targets.

A novel immune-related long non-coding RNA signature improves the prognosis prediction in the context of head and neck squamous cell carcinoma

The tumor immune microenvironment plays an important role in head and neck squamous cell carcinoma (HNSCC). Reliable prognostic signatures able to accurately predict the immune landscape and survival rate of HNSCC patients are crucial to ensure an individualized/effective treatment. Here, we used HNSCC transcriptomic and clinical data retrieved from The Cancer Genome Atlas and identified differentially expressed immune-related long non-coding RNAs (DEirlncRNAs). DEirlncRNA pairs were recognized using univariate analysis. Cox and Lasso regression analyses were used to determine the association between DEirlncRNA pairs and the patients’ overall survival and build the prediction model. Receiver operating characteristic curves and Kaplan–Meier survival curves were used to validate the prediction model. We then reevaluated the model based on the clinical factors, tumor-infiltrating immune cells, chemotherapeutic efficacy, and immunosuppression biomarkers. We built a risk score model based on 18 DEirlncRNA pairs, closely related to the overall survival of patients (hazard ratio: 1.376; 95% confidence interval: 1.302–1.453; P < 0.0001). Compared with two recently published lncRNA signatures, our DEirlncRNA pair signature had a higher area under the curve, indicating better prognostic performance. Additionally, the signature score positively correlated with aggressive HNSCC outcomes (low immunity score, significantly reduced CD8 + T cell infiltration, and low expression of immunosuppression biomarkers). However, high-risk patients might have high chemosensitivity. Overall, the lncRNAs signature established here shows promising clinical prediction and the effective disclosure of the tumor immune microenvironment in HNSCC patients; therefore, such signature might help distinguish patients that could benefit from immunotherapy.

A novel tumor suppressor ASMTL-AS1 regulates the miR-1228-3p/SOX17/β-catenin axis in triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is a special type of breast cancer that lacks effective therapeutic targets. There is a significant need to clarify its pathogenesis, so as to bring new targeted approaches for TNBC management. Here, we identified a long-non coding RNA (lncRNA) ASMTL-AS1 that linked to TNBC development and progression.

METHODS

Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot assays were used to test gene and protein levels, respectively. The regulatory axis of miR-1228-3p/SOX17/β-catenin was determined by luciferase reporter and RNA pull-down assays. In vivo assay was conducted by using the nude mice model via subcutaneous transplantation of tumor cells.

RESULTS

ASMTL-AS1 was significantly downregulated in TNBC tissues compared to normal tissues, which was closely associated with aggressive clinical features and unfavorable prognosis. Lentivirus-mediated ASMTL-AS1 overexpression evidently reduced the ability of TNBC cell colony formation, activity and invasion by more than 2.5 times. RNA pull-down and luciferase reporter assays revealed that miR-1228-3p directly bound to ASMTL-AS1, ASMTL-AS1 increased SOX17 expression via sponging and repressing miR-1228-3p. Subsequently, the upregulated SOX17 trans-suppressed β-catenin expression, resulting in the inactivation of carcinogenic Wnt/β-catenin signaling, thereby restraining TNBC cell growth and dissemination. Importantly, the xenograft tumor model showed that the ASMTL-AS1 overexpression significantly retarded tumor growth, and negatively regulated Wnt/β-catenin pathway.

CONCLUSIONS

Our data characterize a novel tumor suppressor in TNBC, restoration of ASMTL-AS1 may be a candidate therapeutic intervention for TNBC patients.

Prediction of bladder cancer outcome by identifying and validating a mutation-derived genomic instability-associated long noncoding RNA (lncRNA) signature

Bladder cancer is one of the most common malignant tumors worldwide. Accordingly, its incidence and mortality are high. One of the characteristics of cancer is genomic instability. New studies suggest that long non-coding RNAs (lncRNAs) play an important role in maintaining genomic instability. This study aimed to identify a genomic instability-associated lncRNA signature to predict the outcome of patients with bladder cancer. We downloaded data for bladder cancer patients from The Cancer Genome Atlas database to obtain lncRNA expression profiles as well as somatic mutation profiles. Using the lncRNA computational framework, a genomic instability-related lncRNA signature (GIlncSig) was established and the prognostic value of this signature was assessed and validated. A five-lncRNA signature based on genomic instability (CFAP58-DT, MIR100HG, LINC02446, AC078880.3, and LINC01833) was obtained from 58 differentially expressed lncRNAs. Patients were divided into high-risk and low-risk groups, with the high-risk group having a substantially worse prognosis than the low-risk group. Univariate and multivariate Cox analyses indicated that GIlncSig may be an independent prognostic factor; this finding was subsequently validated. In addition, enrichment analysis indicated that GIlncSig is associated with genomic instability in bladder cancer. GIlncSig has a predictive value for the prognosis of bladder cancer patients and provides guidance for the clinical treatment of these patients.