Identification of competing endogenous RNA network in laryngeal squamous cell carcinoma

Oral and periodontal manifestation related during human papilloma virus infections: Update on early prognostic factors

Human Papilloma Virus (HPV) is considered one of the most common sexually transmitted infections and has been shown to play an important role in the pathogenesis of squamous cell carcinomas (SCC) of the cervix and head and neck. Manifestations of HPV infections can be manifold, ranging from asymptomatic infections to benign or potentially malignant lesions to intraepithelial neoplasms and invasive carcinomas. The heterogeneity of clinical manifestations from HPV infection depends on the interactions between the viral agent and the host, a direct consequence of the ability on the part of HPV is to remain silent and to evade and convey the action of the host immune system. The oral mucosa represents one of the tissues for which HPV has a distinct tropism and is frequently affected by infection. While much information is available on the role that HPV infection plays in the development of SCC in the oral cavity, there is less information on asymptomatic infections and benign HPV-induced oral lesions. Therefore, the purpose of this review is to analyze, in light of current knowledge, the early clinical and bio-humoral prognostic features related to the risk of HPV malignant transformation, focusing on subclinical conditions, benign lesions, and the correlation between oral infection and infection in other districts. The data show that the main risk associated with HPV infection is related to malignant transformation of lesions. Although HPV-driven OPSCC is associated with a better prognosis than non-HPV-driven OPSCC, primary prevention and early detection of the infection and affected genotype are essential to reduce the risk of malignant neoplastic complications and improve the prognosis.

Characterization of metabolism-associated molecular patterns in prostate cancer

BACKGROUND

Metabolism is a hallmark of cancer and it involves in resistance to antitumor treatment. Therefore, the purposes of this study are to classify metabolism-related molecular pattern and to explore the molecular and tumor microenvironment characteristics for prognosis predicting in prostate cancer.

METHODS

The mRNA expression profiles and the corresponding clinical information for prostate cancer patients from TCGA, cBioPortal, and GEO databases. Samples were classified using unsupervised non-negative matrix factorization (NMF) clustering based on differentially expressed metabolism-related genes (MAGs). The characteristics of disease-free survival (DFS), clinicopathological characteristics, pathways, TME, immune cell infiltration, response to immunotherapy, and sensitivity to chemotherapy between subclusters were explored. A prognostic signature was constructed by LASSO cox regression analysis based on differentially expressed MAGs and followed by the development for prognostic prediction.

RESULTS

A total of 76 MAGs between prostate cancer samples and non-tumorous samples were found, then 489 patients were divided into two metabolism-related subclusters for prostate cancer. The significant differences in clinical characteristics (age, T/N stage, Gleason) and DFS between two subclusters. Cluster 1 was associated with cell cycle and metabolism-related pathways, and epithelial-mesenchymal transition (EMT), etc., involved in cluster 2. Moreover, lower ESTIMATE/immune/stromal scores, lower expression of HLAs and immune checkpoint-related genes, and lower half-maximal inhibitory concentration (IC50) values in cluster 1 compared with cluster 2. The 10 MAG signature was identified and constructed a risk model for DFS predicting. The patients with high-risk scores showed poorer DFS. The area under the curve (AUC) values for 1-, 3-, 5-year DFS were 0.744, 0.731, 0.735 in TCGA-PRAD dataset, and 0.668, 0.712, 0.809 in GSE70768 dataset, 0.763, 0.802, 0.772 in GSE70769 dataset. Besides, risk score and Gleason score were identified as independent factors for DFS predicting, and the AUC values of risk score and Gleason score were respectively 0.743 and 0.738. The nomogram showed a favorable performance in DFS predicting.

CONCLUSION

Our data identified two metabolism-related molecular subclusters for prostate cancer that were distinctly characterized in prostate cancer. Metabolism-related risk profiles were also constructed for prognostic prediction.

Low LINC02147 expression promotes the malignant progression of oral submucous fibrosis

BACKGROUND

Key lncRNAs associated with the malignant progression of oral submucous fibrosis (OSF) to oral squamous cell carcinoma (OSCC) were identified.

METHODS

Key lncRNAs with sequential changes from normal oral mucosa (NOM) to OSF to OSCC were identified based on the GEO database. Kaplan-Meier analysis was used to screen lncRNAs related to OSCC prognosis. Cox regression analysis was used to validate the independent prognostic value. qPCR was used to confirm the expression of the candidate lncRNAs. Gene set enrichment analysis (GSEA), nucleocytoplasmic separation assay, fluorescence in situ hybridization, RNA knockdown, western blot, and cell viability assay were performed to investigate the biological functions of the candidate lncRNA. A nomogram was constructed to quantitatively predict OSCC prognosis based on TCGA.

RESULTS

Bioinformatics methods indicated that LINC02147 was sequentially downregulated from NOM to OSF to OSCC, as confirmed by clinical tissues and cells. Meanwhile, low LINC02147 expression, as an independent prognostic factor, predicted a poor prognosis for OSCC. GSEA and in vitro studies suggested that low LINC02147 expression promoted OSF malignant progression by promoting cell proliferation and differentiation. A LINC02147 signature-based nomogram successfully quantified each indicator's contribution to the overall survival of OSCC.

CONCLUSIONS

Low LINC02147 expression promoted OSF malignant progression and predicted poor OSCC prognosis.

Identification of novel key regulatory lncRNAs in gastric adenocarcinoma

Background

Stomach adenocarcinoma (STAD) is one of the most common and deadly cancers worldwide. Recent evidence has demonstrated that dysregulation of long noncoding RNAs (lncRNA) is associated with different hallmarks of cancer. lncRNAs also were suggested as novel promising biomarkers for cancer diagnosis and prognosis. Despite these previous investigations, the expression pattern, diagnostic role, and hallmark association of lncRNAs in STAD remain unclear.

Results

In this study, The STAD lncRNA-mRNA network was constructed based on RNAs that differentially expressed among tumor and normal samples and had a strong expression correlation with others. The high degree nodes of the network were associated with overall survival. In addition, we found that the hubs’ regulatory roles have previously been confirmed in different types of cancers by literature. For example, the HCG22 hub inhibited cell proliferation and invasion and induced apoptosis in oral squamous cell carcinoma (OSCC) cells. The levels of PCNA, Vimentin, and Bcl2 were decreased and E-cadherin and Bax expression was elevated in OSCC cells after HCG22 overexpression. Additionally, HCG22 overexpression inhibited the Akt, mTOR, and Wnt/β-catenin pathways.

Then lncRNAs were mapped to their related GO terms and cancer hallmarks. Based on these mappings, we predict the hallmarks that might be associated with each lncRNA. Finally, the literature review confirmed our prediction.

Among the 20 lncRNAs of the STAD network, 11 lncRNAs (LINC02560, SOX21-AS1, C5orf66-AS1, HCG22, PGM5-AS1, NALT1, ENSG00000241224.2, TINCR, MIR205HG, HNF4A-AS1, ENSG00000262756) demonstrated expression correlation with overall survival (OS). Based on expression analysis, survival analysis, hallmark associations, and literature review, LINC02560, SOX21-AS1, C5orf66-AS1, HCG22, PGM5-AS1, NALT1, ENSG00000241224.2, TINCR, MIR205HG, HNF4A-AS1 plays a regulatory role in STAD. For example, our prediction of association between C5orf66-AS1 expression dysregulation and “sustaining proliferative signal” and “Activating invasion and metastasis” has been confirmed in STAD, OSCC and cervical cancer. Finally, we developed a lncRNA signature with SOX21-AS1 and LINC02560, which classified patients into high and low-risk subgroups with significantly different survival outcomes. The mortality rate of the high-risk patients was significantly higher compared to the low-risk patients (28/1% vs 60.13).

Conclusion

These findings help in designing more precise and detailed experimental studies to find STAD biomarkers and therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08578-6.