Smoking patients with laryngeal cancer screened with a novel immunogenomics-based prognostic signature

Circular RNAs in laryngeal cancer

Laryngeal cancer remains a significant global health concern, with poor prognosis for advanced-stage disease highlighting the need for novel diagnostic, prognostic, and therapeutic approaches. Circular RNAs (circRNAs), a class of covalently closed non-coding RNAs, have emerged as important regulators of gene expression and cellular processes in various cancers, including laryngeal cancer. This review summarizes the current understanding of circRNAs in laryngeal cancer, covering their biogenesis, regulatory mechanisms, and potential clinical applications. We explore the diverse functions of circRNAs, including their roles as miRNA sponges, protein interactors, and direct mRNA regulators, and their influence on key cellular processes such as proliferation, invasion, and metastasis. The review highlights promising circRNAs as diagnostic and prognostic biomarkers, as well as potential therapeutic targets. We also outline current strategies for circRNA modulation, including suppression techniques like RNA interference and CRISPR/Cas systems, and overexpression methods using vectors and synthetic circRNAs.

Tobacco Cessation Following Laryngeal Cancer Diagnosis Predicts Response to Treatment and Laryngectomy-Free Survival

OBJECTIVE

To determine the effect of tobacco cessation following laryngeal cancer diagnosis on response to first-line therapy, laryngectomy-free survival, and overall survival in patients who were current smokers at the time of diagnosis.

STUDY DESIGN

Retrospective, case-control study.

SETTING

OU Stephenson Cancer Center, National Cancer Institute-Designated Cancer Center.

METHODS

We included 140 patients diagnosed with laryngeal squamous cell carcinoma, who were current smokers at the time of diagnosis, and were treated with first-line definitive radiation or chemo/radiation with the intent to cure. The association between patient characteristics and treatment response was assessed using the χ2 test and logistic regression analysis. Survival outcomes were analyzed using Kaplan-Meier methods and Cox proportional-hazards models.

RESULTS

Of the 140 current smokers, 61 patients (45%) quit smoking prior to treatment initiation. In adjusted logistic regression analysis, quitters had 3.7 times higher odds of achieving a complete response to first-line therapy than active smokers (odds ratio: 3.694 [1.575-8.661]; P = .003). In the adjusted Cox proportional-hazards model, quitters were 54% less likely to require salvage laryngectomy within 7 years of diagnosis than active smokers (hazard ratio: 0.456 [0.246-0.848]; P = .013). Quitters had a statistically significant increase in 7-year overall survival compared to active smokers (P = .02).

CONCLUSION

This is the first study to show that in newly diagnosed laryngeal cancer patients who are current smokers at the time of diagnosis, tobacco cessation significantly increases therapy response, laryngectomy-free survival, and overall survival. These data stress the importance of systematically incorporating tobacco cessation programs into laryngeal cancer treatment plans.

Upregulation of CCNB2 and a novel lncRNAs-related risk model predict prognosis in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the main type of renal cell carcinoma. Cyclin B2 (CCNB2) is a subtype of B-type cyclin that is associated with the prognosis of several cancers. This study aimed to identify the relationship between CCNB2 and progression of ccRCC and construct a novel lncRNAs-related model to predict prognosis of ccRCC patients.

METHODS

The data were obtained from public databases. We identified CCNB2 in ccRCC using Kaplan-Meier survival analysis, univariate and multivariate Cox regression, and Gene Ontology analysis. External validation was then performed. The risk model was constructed based on prognostic lncRNAs by the LASSO algorithm and multivariate Cox regression. Receiver operating characteristics (ROC) curves were used to evaluate the model. Consensus clustering analysis was performed to re-stratify the patients. Finally, we analyzed the tumor-immune microenvironment and performed screening of potential drugs.

RESULTS

CCNB2 associated with late clinicopathological parameters and poor prognosis in ccRCC and was an independent predictor for disease-free survival. In addition, CCNB2 shared the same expression pattern with known suppressive immune checkpoints. A risk model dependent on the expression of three prognostic CCNB2-related lncRNAs (SNHG17, VPS9D1-AS1, and ZMIZ1-AS1) was constructed. The risk signature was an independent predictor of ccRCC. The area under the ROC (AUC) curve for overall survival at 1-, 3-, 5-, and 8-year was 0.704, 0.702, 0.741, and 0.763. The high-risk group and cluster 2 had stronger immunogenicity and were more sensitive to immunotherapy.

CONCLUSION

CCNB2 could be an important biomarker for predicting prognosis in ccRCC patients. Furthermore, we developed a novel lncRNAs-related risk model and identified two CCNB2-related molecular clusters. The risk model performed well in predicting overall survival and immunological microenvironment of ccRCC.

HPV-Related Prognostic Signature Predicts Survival in Head and Neck Squamous Cell Carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers, worldwide. Considering the role of human papilloma virus (HPV) in tumor development and sensitivity to treatment of HNSCC, we aimed to explore the prognostic classification ability of HPV-related signatures in head and neck cancer.

METHODS

HPV-related signatures were screened out based on Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. HPV-related signatures with prognostic value were identified through univariate Cox regression analysis and a risk signature was established by least absolute shrinkage and selection operator (LASSO). Further, we developed a nomogram by integrating independent prognostic factors.

RESULTS

A total of 55 HPV-associated signatures were differentially expressed and ten of them were associated with prognosis of HNSCC patients. The prognostic signature based on CDKN2A, CELSR3, DMRTA2, SERPINE1, TJP3, FADD, and IGF2BP2 expression was constructed. Univariate and multivariate regression analyses demonstrated that the novel prognostic signature was an independent prognostic factor of HNSCC. The nomogram integrating the prognostic signature and other independent prognostic factors was developed.

CONCLUSION

In summary, the prognostic signature of the HPV-related signatures might serve as an important prognostic biomarker for patients with HNSCC.