Expression level of long non-coding RNA colon adenocarcinoma hypermethylated serves as a novel prognostic biomarker in patients with thyroid carcinoma

Identification of m5C-related lncRNAs signature to predict prognosis and therapeutic responses in esophageal squamous cell carcinoma patients

Esophageal squamous cell carcinoma (ESCC) has a dismal prognosis because of atypical early symptoms and heterogeneous therapeutic responses. 5-methylcytosine (m5C) modification plays an important role in the onset and development of many tumors and is widespread in long non-coding RNA (lncRNA) transcripts. However, the functions of m5C and lncRNAs in ESCC have not been completely elucidated. Herein, this study aimed to explore the role of m5C-related lncRNAs in ESCC. The RNA-seq transcriptome profiles and clinical information were downloaded from the TCGA-ESCC database. Pearson analysis was used to identify m5C-related lncRNAs. Then we established the m5C-related lncRNAs prognostic signature (m5C-LPS) using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis. Then, the prognostic value of m5C-LPS was evaluated internally and externally using the TCGA-ESCC and GSE53622 databases through multiple methods. We also detected the expression of these lncRNAs in ESCC cell lines and patient tissues. Fluorescence in situ hybridization (FISH) was used to detect the prognostic value of specific lncRNA. In addition, clinical parameters, immune status, genomic variants, oncogenic pathways, enrichment pathways, and therapeutic response features associated with m5C-LPS were explored using bioinformatics methods. We constructed and validated a prognostic signature based on 9 m5C-related lncRNAs (AC002091.2, AC009275.1, CAHM, LINC02057.1, AC0006329.1, AC037459.3, AC064807.1, ATP2B1-AS1, and UBAC2-AS1). The quantitative real-time polymerase chain reaction (qRT-PCR) revealed that most lncRNAs were upregulated in ESCC cell lines and patient tissues. And AC002091.2 was validated to have significant prognostic value in ESCC patients. A composite nomogram was generated to facilitate clinical practice by integrating this signature with the N stage. Besides, patients in the low-risk group were characterized by good clinical outcomes, favorable immune status, and low oncogenic alteration. Function enrichment analysis indicated that the risk score was associated with mRNA splicing, ncRNA processing, and DNA damage repair response. At the same time, we found significant differences in the responses to chemoradiotherapy between the two groups, proving the value of m5C-LPS in treatment decision-making in ESCC. This study established a novel prognostic signature based on 9 m5C-related lncRNAs, which is a promising biomarker for predicting clinical outcomes and therapeutic response in ESCC.

TAF1D Functions as a Novel Biomarker in Osteosarcoma

Background: The most frequent primary bone cancer in teenagers, osteosarcoma (OS), is particularly aggressive with a high mortality rate. Methods: By combining public databases, OS and non-cancer samples were obtained. The Wilcoxon test and standardized mean difference (SMD) were utilized to evaluate the mRNA expression level of TATA-box binding protein associated factor, RNA polymerase 1 subunit D (TAF1D). The potential of TAF1D to discriminate OS samples from non-cancer samples was revealed by summary receiver operating characteristic curve (sROC). To investigate the prognostic significance, Kaplan‒Meier curve and univariate Cox analysis were performed. Immunohistochemistry (IHC) was used to determine the TAF1D protein expression level. ESTIMATE algorithm and TIMER2.0 database were used to reveal the association between TAF1D expression and the immune microenvironment. Enrichment analysis and potential drug prediction were performed to clarify the underlying molecular mechanisms and possible therapeutic directions of TAF1D. Ultimately, the transcription factors (TFs) and the TAF1D binding site were predicted based on the Cistrome and JASPAR databases. Results: TAF1D was upregulated in OS at the mRNA and protein levels and possessed robust discriminatory power. TAF1D upregulation was suggestive of worse prognosis and enhancement of tumor purity in OS patients. The cell cycle was the most significantly enriched pathway, and NU.1025 was considered to be the potential target agent. Finally, MYC was identified as a TF that regulates the expression of TAF1D. Conclusions: Altogether, TAF1D has the potential to serve as a biological marker and therapeutic target in OS, which could offer new perspectives for OS treatment.

LncRNA model predicts liver cancer drug resistance and validate in vitro experiments

Introduction: Hepatocellular carcinoma (HCC) patients may benefit from chemotherapy, but drug resistance is an important obstacle to favorable prognoses. Overcoming drug resistance is an urgent problem to be solved.

Methods: Differential expression analysis was used to identify long non-coding RNAs (LncRNAs) that differed in chemotherapy-sensitive and chemotherapy-resistant patients. Machine learning algorithms including random forest (RF), lasso regression (LR), and support vector machines (SVMs) were used to identify important chemotherapy-related LncRNAs. A back propagation (BP) network was then used to validate the predictive capacity of important LncRNAs. The molecular functions of hub LncRNAs were investigated via qRT-PCR and cell proliferation assay. Molecular-docking technique was used to explore candidate drug of targets of hub LncRNA in the model.

Results: A total of 125 differentially expressed LncRNAs between sensitive and resistant patients. Seventeen important LncRNAs were identified via RF, and seven factors were identified via LR. With respect to SVM, the top 15 LncRNAs of AvgRank were selected. Five merge chemotherapy-related LncRNAs were used to predict chemotherapy resistance with high accuracy. CAHM was a hub LncRNA of model and expression high in sorafenib resistance cell lines. In addition, the results of CCK8 showed that the sensitivity of HepG2-sorafenib cells to sorafenib was significantly lower than that of HepG2; and the sensitivity of HepG2-sorafenib cells transfected with sh-CAHM was significantly higher than that of Sorafenib. In the non-transfection group, the results of clone formation experiments showed that the number of clones formed by HepG2-sorafenib cells treated with sorafenib was significantly more than that of HepG2; after HepG2-sorafenib cells were transfected with sh-CAHM, the number of clones formed by Sorafenib treatment was significantly higher than that of HepG2 cells. The number was significantly less than that of HepG2-s + sh-NC group. Molecular Docking results indicate that Moschus was candidate drug for target protein of CAHM.

Conclusion: Five chemotherapy-related LncRNAs could predict drug resistance in HCC with high accuracy, and the hub LncRNA CAHM has potential as a new biomarker for HCC chemotherapy resistance.

Bone mesenchymal stem cells deliver exogenous lncRNA CAHM via exosomes to regulate macrophage polarization and ameliorate intervertebral disc degeneration

Exosomes derived from bone marrow mesenchymal stem cells (BMSC-Exos) were reported to have therapeutic potential in degenerative diseases. This study aimed to explore the effects of BMSC-Exos on inhibiting M1 macrophage polarization, reducing excessive nucleus pulposus cells (NPCs) apoptosis, and inhibiting ECM degradation during intervertebral disc degeneration (IDD). Rat IDD models were established by acupuncture. For the co-culture experiment, we used BMSC-Exo or human monocyte leukemia (THP-1) medium to incubate THP-1 or NPCs, respectively. BMSC-Exo was isolated from the BMSC medium, identified by TEM and NTA, and injected into the intervertebral discs of IDD rats. The macrophage infiltration in intervertebral disc tissue was evaluated by immunohistochemistry and immunofluorescence. ELISA was used to measure the levels of TNF-α, IL-6 and IL-10. The ECM degradation was analyzed by Western blot. The cell proportion and apoptosis were measured by flow cytometry. The morphological change of the intervertebral disc was analyzed by HE and safranin O fixation staining. In intervertebral disc tissues of IDD rats, we found the increased infiltration of M1 macrophages, with upregulated iNOS, TNF-α and IL-6 levels. Compared with BMSCs, the expression of CAHM in BMSC-Exo was significantly higher. Using co-cultured experiments, we proved that BMSC-Exo reduced apoptosis and ECM degradation of NPCs by inhibiting M1-type macrophage polarization by delivering CAHM. In addition, BMSC-Exo could improve IDD in vivo, including increased proteoglycan content, reduced macrophage infiltration and ECM degradation, and decrease expression of inflammatory factors by delivering CAHM. In conclusion, BMSC-Exo delivered exogenous CAHM via exosomes to regulate macrophage polarization and ameliorate IDD.

Comprehensive analysis of molecular mechanism and a novel prognostic signature based on small nuclear RNA biomarkers in gastric cancer patients

Small nuclear RNAs (snRNAs) are rarely reported in cancer. This study is based on The Cancer Genome Atlas genome-wide data set to explore the prognostic value and molecular mechanism of snRNAs in gastric cancer (GC). Gene ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analysis were used to explore the molecular mechanism of snRNAs. A total of 351 patients were included in the survival analysis, and 14 prognostic snRNAs were identified using multivariate survival analysis. We constructed a prognostic signature containing nine snRNAs, which can signally classify patients into high- and low-risk phenotypes (adjusted P < 0.0001, hazard ratio = 2.671, 95% confidence interval = 1.850–3.858). Combining the molecular mechanisms obtained by the three functional enrichment approaches, we concluded that this prognostic signature snRNAs participated in classical tumor-related signaling pathways, including Notch, PI3K, toll-like receptor, etc.; cell adhesion; cell cycle; cell proliferation; and other biological processes that affect the biological phenotype of cancer cells. We also found significant downregulation of the abundance of immune cell infiltrates and immune microenvironment scores for high-risk phenotypes of GC patients. In conclusion, this study has identified 14 prognostic snRNAs signally associated with GC overall survival and also constructed a novel prognostic signature containing nine prognostic snRNAs.