Background: It has been recognized that depth of invasion (DOI) is closely associated with patient survival for all types of cancer. The purpose of this study was to determine the optimal threshold and prognostic value in laryngeal squamous carcinoma (LSCC). Most importantly, we evaluated the prognostic performance of five candidate modified T-classification models in patients with LSCC. Methods: LSCC patients from Harbin Medical University Cancer Hospital and Chinese Academy of Medical Sciences Cancer Hospital were divided into training group (n=412) and validation group (n=147). The primary outcomes were overall survival (OS) and relapse-free survival (RFS), and the effect of DOI on prognosis was analyzed using a multivariable regression model. We identified the optimal model based on its simplicity, goodness of fit and Harrell's consistency index. Further independent testing was performed on the external validation queue. The nomograms was constructed to predict an individual's OS rate at one, three, and five years.Results: In multivariate analysis, we found significant associations between DOI and OS (Depth of Medium-risk invasion HR, 2.631; P <0.001. Depth of high-risk invasion: HR, 5.287; P <0.001) and RFS(Depth of high-risk invasion: HR, 1.937; P =0.016). Model 5 outperformed the American Joint Committee on Cancer (AJCC) staging system based on a low Akaike information criterion score, improvement in the concordance index, and Kaplan-Meier curves.Conclusions: Inclusion of DOI in the current AJCC staging system can improve the differentiation of T classification in LSCC patients.
Background
Cuproptosis is a novel type of programmed cell death which plays an important role in the development and progression of cancer. However, there is a limited amount of research on cuproptosis-associated long non-coding RNAs (lncRNAs) in head and neck squamous cell carcinomas (HNSCCs). This study aimed to investigate the predictive value of cuproptosis-related lncRNA signature for HNSCC prognosis.
Method
Transcriptomic and clinical data of HNSCC patients were obtained from the Cancer Genome Atlas (TCGA). We established a cuproptosis-related lncRNA signature and then constructed a hybrid nomogram based on risk scores and clinical factors. We also performed differential expression genes (DEGs) function, immune cells infiltration, immune checkpoint analysis based on cuproptosis-associated lncRNA signature.
Results
A signature of 27 cuproptosis-related lncRNAs was performed and the prognosis of patients at high risk is worse compared with patients at low risk based on above signature. A nomogram which integrated risk scores and clinical features also showed favorable predictive power. Furthermore, DEGs in high or low risk group were mainly enriched in immune-related pathways. Anti-tumor immune cells and immune checkpoints were mainly enriched in low risk group compared with high risk group.
Conclusion
Cuproptosis-related lncRNAs could be regarded as independent indicators for HNSCC prognosis which might be effective targets for HNSCC therapy.
Background: Laryngeal squamous cell carcinoma (LSCC) is a heterogeneous disease. In clinical practice, patients with similar clinicopathological characteristics often show different outcomes. This study evaluated the levels of primary LSCC intratumoral infiltrating lymphocytes (iTILs), tumor-infiltrating lymphocyte volume (TILV), frontier tumor-infiltrating lymphocytes (fTILs), and their relations to the patient's clinical outcome. Materials and methods: According to the 2017 study of the International TILs Working Group, hematoxyline and eosin-stained slides from 412 patients were evaluated for their morphology of tumor immune infiltration status.Results: Kaplan-Meier analysis showed that high levels of iTILs, TILV, and fTILs were significantly correlated with OS (all P<0.05). Cox regression model analysis showed that high levels of iTILs, TILV, and fTILs were independently associated with better OS (all P<0.05). Conclusion: Local inflammatory markers in patients with laryngeal squamous cell carcinoma, especially the levels of iTILs, TILV, and fTILs, are reliable prognostic factors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.