Novel lncRNA Panel as for Prognosis in Esophageal Squamous Cell Carcinoma Based on ceRNA Network Mechanism

Knockdown of LINC01087 inhibits gastric cancer malignant behavior by regulating the miR-135a-5p/CAAP1 axis

Long noncoding RNAs play important roles in the occurrence and development of many malignant cancers. This study focuses on the effects of LINC01087 on gastric cancer and its underlying mechanism. In the present study, LINC01087 and CAAP1 were found to be upregulated, and miR-135a-5p was diminished in gastric cancer specimens and cells. Inhibition of LINC01087 resulted in cell proliferation inhibition and induced cell apoptosis through the intrinsic apoptosis signaling pathway, as evidenced by the activation of caspase-3 and caspase-9. An investigation of the signaling pathway revealed that the effects on proliferation and apoptosis following LINC01087 knockdown were mediated by suppression of CAAP1. Furthermore, application of a miR-135a-5p inhibitor or overexpression of CAAP1 could attenuate the apoptotic effect achieved by LINC01087 inhibition, confirming the involvement of miR-135a-5p/CAAP1 signaling in the occurrence of gastric cancer. In conclusion, the LINC01087/miR-135a-5p/CAAP1 axis modulates gastric cancer tumorigenesis and pathogenesis and presents new insight into gastric cancer targeted therapy.

Use of exosome transcriptome-based analysis to identify novel biomarkers in patients with locally advanced esophageal squamous cell carcinoma undergoing neoadjuvant chemoradiotherapy

Background

The prognosis of esophageal squamous cell carcinoma (ESCC) is improved by neoadjuvant chemoradiotherapy (nCRT), especially for patients with pathologic complete response (pCR). Despite the efforts to predict treatment response using multimodality, no molecule has proven to be a strong biomarker. This study aimed to profile the expression of exosome transcriptome that could predict pCR in ESCC before and after nCRT.

Methods

We collected paired blood samples of 15 patients with ESCC who received nCRT and radical surgery. They were divided into 3 groups: (A) residual tumor in the first clinical response evaluation (CRE-1), (B) no residual tumor in CRE-1 but with residual tumor in CRE-2 which was performed after 5-6 weeks, and (C) no residual tumor in CRE-1 or CRE-2. For each patient, the blood sample was collected before nCRT (time point 0); and then 6 weeks after nCRT, the clinical response was evaluated, and another blood sample was collected (time point 1).

Results

Using the intersection of different sets, we found 23 progression-associated messenger RNAs (mRNAs) and 67 remission-associated mRNAs. Between remission-associated mRNAs and the targets of progression-associated (carcinogenic) microRNAs (miRNAs), the intersection was acquired, and 2 miRNA-mRNA networks (IFIT2-miR-3615-IFIT2-miR-484 and BTN3A3-miR-6803-3p) were identified. Among the intersection of progression-associated (carcinogenic) mRNAs and the targets of remission-associated miRNAs, there is a network with miR-132-3p (remission-associated miRNA) located at the core, matched with DICER1, KLHL8, ANKRD12, ASH1L, and IMP4.

Conclusions

Our findings identified altered plasma exosome RNAs among the different groups and between different time points of nCRT, as well as the corresponding enrichments and regulatory networks, which may serve as potentially predictors of treatment response for patients with ESCC after nCRT.

Systematic Investigation of the Diagnostic and Prognostic Impact of LINC01087 in Human Cancers

(1) Background: Long non-coding RNAs may constitute epigenetic biomarkers for the diagnosis, prognosis, and therapeutic response of a variety of tumors. In this context, we aimed at assessing the diagnostic and prognostic value of the recently described long intergenic non-coding RNA 01087 (LINC01087) in human cancers. (2) Methods: We studied the expression of LINC01087 across 30 oncological indications by interrogating public resources. Data extracted from the TCGA and GTEx databases were exploited to plot receiver operating characteristic curves (ROC) and determine the diagnostic performance of LINC01087. Survival data from TCGA and KM-Plotter directories allowed us to graph Kaplan-Meier curves and evaluate the prognostic value of LINC01087. To investigate the function of LINC01087, gene ontology (GO) annotation and Kyoto Encyclopedia of Gene and Genomes (KEGG) enrichment analyses were performed. Furthermore, interactions between LINC01087 and both miRNA and mRNA were studied by means of bioinformatics tools. (3) Results: LINC01087 was significantly deregulated in 7 out of 30 cancers, showing a predominant upregulation. Notably, it was overexpressed in breast (BC), esophageal (ESCA), and ovarian (OV) cancers, as well as lung squamous cell carcinoma (LUSC), stomach adenocarcinoma (STAD), and uterine carcinosarcoma (UCS). By contrast, LINC01087 displayed downregulation in testicular germ cell tumors (TGCT). ROC curve analyses identified LINC01087 as a potential diagnostic indicator in BC, ESCA, OV, STAD, and TGCT. Moreover, high and low expression of LINC01087 predicted a favorable prognosis in BC and papillary cell carcinoma, respectively. In silico analyses indicated that deregulation of LINC01087 in cancer was associated with a modulation of genes related to ion channel, transporter, and peptide receptor activity. (4) Conclusions: the quantification of an altered abundance of LINC01087 in tissue specimens might be clinically useful for the diagnosis and prognosis of some hormone-related tumors, including BC, OV, and TGCT, as well as other cancer types such as ESCA and STAD. Moreover, our study revealed the potential of LINC01087 (and perhaps other lncRNAs) to regulate neuroactive molecules in cancer.

Identification of a key ceRNA network associated with ferroptosis in gastric cancer

Ferroptosis, a newly discovered irondependent form of regulated cell death caused by excessive accumulation of lipid peroxides, is linked to the development and treatment response of various types of cancer, including gastric cancer (GC). Noncoding RNAs (ncRNAs), as key regulators in cancer, have both oncogenic and tumor suppressive roles. However, studies on ferroptosis-related ncRNA networks in GC are still lacking. Here, we first identified 61 differentially expressed genes associated with ferroptosis in GC by computing and analyzing gene expression profile of tumor and normal tissues for GC. Then, upstream lncRNAs and miRNAs interacting with them were found through miRNet and miRBase databases, and hub lncRNAs and miRNAs were obtained through topological analysis. Finally, the ceRNA regulatory network linked to ferroptosis in GC was established, which includes two ferroptosis marker genes (TXNIP and TSC22D3), one driver gene (GABARAPL1), and one suppressor gene (CAV1). Kaplan-Meier survival analysis showed that changes in the expression of these genes were associated with the survival of GC patients. Furthermore, our study revealed that this ceRNA network may influence the progression of GC by regulating ferroptosis process. These results will help experimental researchers to design an experiment study to further explore the roles of this regulatory network in GC ferroptosis.

Identification of novel lactate metabolism signatures and molecular subtypes for prognosis in hepatocellular carcinoma

Background: Evidence has shown that lactate, an immune signaling molecule, is associated with hepatocellular carcinoma (HCC) progression and immune suppression. Therefore, identifying lactate metabolism-related molecules is a promising therapeutic strategy to inhibit the development of HCC and overcome chemotherapy resistance. Long noncoding RNAs (lncRNAs) are related to tumorigenesis and metastasis. Hence, verifying the molecular subtypes of lncRNAs related to lactate metabolism will play a critical role in managing HCC.

Methods: Based on HCC data in The Cancer Genome Atlas (TCGA), lactate metabolic pathway-related genes were enriched by gene collection and enrichment analysis (GSEA). Lactate metabolism-related lncRNAs (LM_lncRNAs) were identified by correlation analysis, HCC molecular subtypes were determined using nonnegative matrix factorization (NMF) clustering, and the response of the three subtypes to chemotherapeutics was further evaluated using the Genomic Tumor Sensitive Cell Line (GDSC) dataset. LM_lncRNAs were examined via Lasso-Cox regression analysis to determine prognosis for patients. A Nomagram plot was used to predict patient survival time.

Results: Three molecular subtypes of HCC were identified. The survival rate of patients with C1 subtype was higher than that of those with C2 and C3. Additionally, patients with C3 subtype have higher levels of immune cell infiltration and high expression of genes related to immune checkpoints. The GDSC results indicated that patients with C3 subtypes were more sensitive to chemotherapy drugs such as sorafenib and sunitinib. The prognostic risk assessment model consisted of six risk factors (AC034229.4, AC131009.1, MYOSLID, AC008667.1, AC012073.1, AC068025.1) and two protective factors (LINC00402 and AC103858.1). Based on Kaplan-Meier analysis, low-risk HCC patients had a high survival rate, and the receiver operating characteristic curve (ROC), calibration curve, and C-index confirmed good prediction ability.

Conclusion: In this study, the molecular subtyping method and prediction model of lactate metabolism-related lncRNAs (LM_lncRNAs) were constructed for the prognosis of HCC patients. This work demonstrated the potential targets of LM_lncRNAs and provided a novel perspective and therapeutic paradigm for future clinical translation.

Prognostic Roles of ceRNA Network-Based Signatures in Gastrointestinal Cancers

Gastrointestinal cancers (GICs) are high-incidence malignant tumors that seriously threaten human health around the world. Their complexity and heterogeneity make the classic staging system insufficient to guide patient management. Recently, competing endogenous RNA (ceRNA) interactions that closely link the function of protein-coding RNAs with that of non-coding RNAs, such as long non-coding RNA (lncRNA) and circular RNA (circRNA), has emerged as a novel molecular mechanism influencing miRNA-mediated gene regulation. Especially, ceRNA networks have proven to be powerful tools for deciphering cancer mechanisms and predicting therapeutic responses at the system level. Moreover, abnormal gene expression is one of the critical breaking events that disturb the stability of ceRNA network, highlighting the role of molecular biomarkers in optimizing cancer management and treatment. Therefore, developing prognostic signatures based on cancer-specific ceRNA network is of great significance for predicting clinical outcome or chemotherapy benefits of GIC patients. We herein introduce the current frontiers of ceRNA crosstalk in relation to their pathological implications and translational potentials in GICs, review the current researches on the prognostic signatures based on lncRNA or circRNA-mediated ceRNA networks in GICs, and highlight the translational implications of ceRNA signatures for GICs management. Furthermore, we summarize the computational approaches for establishing ceRNA network-based prognostic signatures, providing important clues for deciphering GIC biomarkers.

Establishment of Prognostic Signatures of N6-Methyladenosine-Related lncRNAs and Their Potential Functions in Hepatocellular Carcinoma Patients

N6-methyladenosine (m6a)-related mRNAs and lncRNAs have been explored for their functions in several cancers. The present study aimed to identify potential signatures of m6a-related lncRNAs in hepatocellular carcinoma (HCC). We downloaded the expression and clinical data from The Cancer Genome Atlas (TCGA) database. The interacted mRNAs and lncRNAs, prognosis-related lncRNAs, potential metabolic pathways of lncRNAs, immune infiltration of various cells, and CD274 (PD-L1) -related lncRNAs were analyzed. Then, in vitro experiments explored the role of AC012073.1 (LOC105377626) in HCC cell lines. We found that candidate 14 lncRNA signatures play functions in HCC maybe by affecting immune infiltration, cell cycle, Notch signaling pathway, etc. LncRNA AC012073.1 (LOC105377626) functions as oncogenic roles in affecting HCC prognosis.