LncRNA HMGA1P4 promotes cisplatin-resistance in gastric cancer

The strict regulation of HIF-1α by non-coding RNAs: new insight towards proliferation, metastasis, and therapeutic resistance strategies

The hypoxic environment is prominently witnessed in most solid tumors and is associated with the promotion of cell proliferation, epithelial-mesenchymal transition (EMT), angiogenesis, metabolic reprogramming, therapeutic resistance, and metastasis of tumor cells. All the effects are mediated by the expression of a transcription factor hypoxia-inducible factor-1α (HIF-1α). HIF-1α transcriptionally modulates the expression of genes responsible for all the aforementioned functions. The stability of HIF-1α is regulated by many proteins and non-coding RNAs (ncRNAs). In this article, we have critically discussed the crucial role of ncRNAs [such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), Piwi-interacting RNAs (piRNAs), and transfer RNA (tRNA)-derived small RNAs (tsRNAs)] in the regulation of stability and expression of HIF-1α. We have comprehensively discussed the molecular mechanisms and relationship of HIF-1α with each type of ncRNA in either promotion or repression of human cancers and therapeutic resistance. We have also elaborated on ncRNAs that are in clinical examination for the treatment of cancers. Overall, the majority of aspects concerning the relationship between HIF-1α and ncRNAs have been discussed in this article.

A novel marker based on necroptosis-related long non-coding RNA for forecasting prognostic in patients with clear cell renal cell carcinoma

Background: The incidence of clear cell renal cell carcinoma (ccRCC) is high and has increased gradually in recent years. At present, due to the lack of effective prognostic indicators, the prognosis of ccRCC patients is greatly affected.Necroptosis is a type of cell death, and along with cell necrosis is considered a new cancer treatment strategy. The aim of this study was to construct a new marker for predicting the prognosis of ccRCC patients based on long non-coding RNA (nrlncRNAs) associated with necroptosis.

Methods: RNA sequence data and clinical information of ccRCC patients from the Cancer Genome Atlas database (TCGA) were downloaded. NrlncRNA was identified by Pearson correlation study. The differentially expressed nrlncRNA and nrlncRNA pairs were identified by univariate Cox regression and Lasso-Cox regression. Finally, a Kaplan-Meier survival study, Cox regression, clinicopathological features correlation study, and receiver operating characteristic (ROC) spectrum were used to evaluate the prediction ability of 25-nrlncrnas for markers. In addition, correlations between the risk values and sensitivity to tumor-infiltrating immune cells, immune checkpoint inhibitors, and targeted drugs were also investigated.

Results: In the current research, a novel marker of 25-nrlncRNAs pairs was developed to improve prognostic prediction in patients with ccRCC. Compared with clinicopathological features, nrlncRNAs had a higher diagnostic validity for markers, with the 1-year, 3-years, and 5-years operating characteristic regions being 0.902, 0.835, and 0.856, respectively, and compared with the stage of 0.868, an increase of 0.034. Cox regression and stratified survival studies showed that this marker could be an independent predictor of ccRCC patients. In addition, patients with different risk scores had significant differences in tumor-infiltrating immune cells, immune checkpoint, and semi-inhibitory concentration of targeted drugs. The feature could be used to evaluate the clinical efficacy of immunotherapy and targeted drug therapy.

Conclusion: 25-nrlncRNAs pair markers may help to evaluate the prognosis and molecular characteristics of ccRCC patients, which improve treatment methods and can be more used in clinical practice.

Long Non-Coding RNA in Gastric Cancer: Mechanisms and Clinical Implications for Drug Resistance

Gastric cancer (GC) is the third leading cause of cancer-related deaths worldwide, with high recurrence and mortality rate. Chemotherapy, including 5-fluorouracil (5-FU), adriamycin (ADR), vincristine (VCR), paclitaxel (PTX), and platinum drugs, remains one of the fundamental methods of GC treatment and has efficiently improved patients’ prognosis. However, most patients eventually develop resistance to chemotherapeutic agents, leading to the failure of clinical treatment and patients’ death. Recent studies suggest that long non-coding RNAs (lncRNAs) are involved in the drug resistance of GC by modulating the expression of drug resistance-related genes via sponging microRNAs (miRNAs). Moreover, lncRNAs also play crucial roles in GC drug resistance via a variety of mechanisms, such as the regulation of the oncogenic signaling pathways, inhibition of apoptosis, induction of autophagy, modulation of cancer stem cells (CSCs), and promotion of the epithelial-to-mesenchymal transition (EMT) process. Some of lncRNAs exhibit great potential as diagnostic and prognostic biomarkers, as well as therapeutic targets for GC patients. Therefore, understanding the role of lncRNAs and their mechanisms in GC drug resistance may provide us with novel insights for developing strategies for individual diagnosis and therapy. In this review, we summarize the recent findings on the mechanisms underlying GC drug resistance regulated by lncRNAs. We also discuss the potential clinical applications of lncRNAs as biomarkers and therapeutic targets in GC.

LncRNA FOXP4-AS1 Promotes the Progression of Esophageal Squamous Cell Carcinoma by Interacting With MLL2/H3K4me3 to Upregulate FOXP4

Malignant tumors are a grave threat to human health. Esophageal squamous cell carcinoma (ESCC) is a common gastrointestinal malignant tumor. China has a high incidence of ESCC, and its morbidity and mortality are higher than the global average. Increasingly, studies have shown that long noncoding RNAs (lncRNAs) play a vital function in the occurrence and development of tumors. Although the biological function of FOXP4-AS1 has been demonstrated in various tumors, the potential molecular mechanism of FOXP4-AS1 in ESCC is still poorly understood. The expression of FOXP4 and FOXP4-AS1 was detected in ESCC by quantitative real-time PCR (qRT–PCR) or SP immunohistochemistry (IHC). shRNA was used to silence gene expression. Apoptosis, cell cycle, MTS, colony formation, invasion and migration assays were employed to explore the biological functions of FOXP4 and FOXP4-AS1. The potential molecular mechanism of FOXP4-AS1 in ESCC was determined by dual-luciferase reporter, RNA immunoprecipitation (RIP) and chromatin immunoprecipitation (ChIP). Here, we demonstrated that FOXP4-AS1 was significantly increased in ESCC tissues and cell lines, associated with lymph node metastasis and TNM staging. Cell function experiments showed that FOXP4-AS1 promoted the proliferation, invasion and migration ability of ESCC cells. The expression of FOXP4-AS1 and FOXP4 in ESCC tissues was positively correlated. Further research found that FOXP4-AS1, upregulated in ESCC, promotes FOXP4 expression by enriching MLL2 and H3K4me3 in the FOXP4 promoter through a “molecular scaffold”. Moreover, FOXP4, a transcription factor of β-catenin, promotes the transcription of β-catenin and ultimately leads to the malignant progression of ESCC. Finally, FOXP4-AS1 may be a new therapeutic target for ESCC.

The Molecular Roles and Clinical Implications of Non-Coding RNAs in Gastric Cancer

Gastric cancer (GC) is one of the most common malignancies in the world. It is also the fifth most common cancer in China. In recent years, a large number of studies have proved that non-coding RNAs (ncRNAs) can regulate cell proliferation, invasion, metastasis, apoptosis, and angiogenesis. NcRNAs also influence the therapeutic resistance of gastric cancer. NcRNAs mainly consist of miRNAs, lncRNAs and circRNAs. In this paper, we summarized ncRNAs as biomarkers and therapeutic targets for gastric cancer, and also reviewed their role in clinical trials and diagnosis. We sum up different ncRNAs and related moleculars and signaling pathway in gastric cancer, like Bcl-2, PTEN, Wnt signaling. In addition, the potential clinical application of ncRNAs in overcoming chemotherapy and radiotherapy resistance in GC in the future were also focused on.

Identification of new proteins related with cisplatin resistance in Saccharomyces cerevisiae

The aim of this study is to select a cisplatin-resistant Saccharomyces cerevisiae strain to look for new molecular markers of resistance and the identification of mechanisms/interactions involved. A resistant strain was obtained after 80 days of cisplatin exposure. Then, total protein extraction, purification, and identification were carried out, in wild-type (wt) and resistant strains, by tandem mass spectrometry using a "nano HPLC-ESI-MS/MS" ion trap system. The increase in the exponentially modified protein abundance index (emPAI) (resistant vs wt strains) was calculated to study the increase in protein expression. "Genemania" software ( http://www.Genemania.org/ ) was used to compare the effects, functions, and protein interactions. KEGG tool was used for metabolic pathway analysis. Data are available via ProteomeXchange with identifier PXD020665. The cisplatin-resistant strain showed 2.5 times more resistance than the wt strain for the inhibitory dose 50% (ID50) value (224 μg/ml vs 89.68 μg/ml) and 2.78 times more resistant for the inhibitory dose 90% (ID90) value (735.2 μg/ml vs 264.04 μg/ml). Multiple deregulated proteins were found in the glutathione and carbon metabolism, oxidative phosphorylation, proteasome, glycolysis and gluconeogenesis, glyoxylate metabolism, fatty acid degradation pathway, citric acid cycle, and ribosome. The most overexpressed proteins in the cisplatin-resistant strain were related to growth and metabolism (QCR2, QCR1, ALDH4, ATPB, ATPA, ATPG, and PCKA), cell structure (SCW10), and thermal shock (HSP26). The results suggest that these proteins could be involved in cisplatin resistance. The resistance acquisition process is complex and involves the activation of multiple mechanisms that interact together. KEY POINTS: • Identification of new proteins/genes related to cisplatin resistance • Increased expression of QCR2/QCR1/ALDH4/ATPB/ATPA/SCW10/HSP26/ATPG and PCKA proteins • Multiple molecular mechanisms that interact together are involved in resistance.