An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study

2021 ◽  
Author(s):  
Juan Chen ◽  
Shanhong Lu ◽  
Yitao Mao ◽  
Lei Tan ◽  
Guo Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cohort Study ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Survival Prediction ◽  
Hypopharyngeal Squamous Cell Carcinoma ◽  
Overall Survival Prediction

scholarly journals A riskscore-based nomogram for the prediction of overall survival in cervical squamous cell carcinoma

2020 ◽  
Author(s):  
Lingling Li ◽  
Sujie Zhang ◽  
Lijie Wang ◽  
Haitao Tao ◽  
Yaping Long ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Roc Curve ◽  
Statistical Tests ◽  
Cervical Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Lasso Regression

Abstract Background:Cervical cancer is still the major cause of cancer-related death among women. However, the prognosis of cervical cancer varies even in the same stage. Thus, exploring prognostic biomarkers that could reflect its biological heterogeneity may contribute to identify patients with a poor prognosis.Methods:Based on the ESTIMATE algorithm, we acquired the immune/stromal scores of cervical squamous cell carcinoma (CSCC) patients collected from The Cancer Genome Atlas (TCGA) dataset. Subsequently, we analyzed the DEGs between high- and low immune score groups using R package edgeR and performed K-M analysis to illustrate the relationship between differentially expressed genes (DEGs) and the overall survival to select survival-related DEGs. Then the LASSO regression model was constructed with the package “glmnet” in R to evaluate the riskscore of each patient. Finally, we developed a nomogram composing riskscore and clinicopathological characteristics to predict the overall survival (OS) of CSCC patients. The R software v3.6.1 was used for statistical analyses. All statistical tests were two-tailed.Results:We established a riskscore model composed of two genes including FOXP3 and ZAP70. The receiver operating characteristic (ROC) curve demonstrated a good potency of the riskscore model. Ultimately, we constructed a nomogram composing riskscore, age and stage to predict the overall survival (OS) of CSCC patients. The area under the ROC curve (AUC) of the nomogram for OS was 0.805, 0.723 and 0.748 for the first, third, and fifth years, respectively. The concordance index (C-index) was 0.746. The calibration curves also showed optimal accuracy of the nomogram for survival prediction. Conclusion:The nomogram based on riskscore could predict overall survival in CSCC and may benefit those patients through individualized immunotherapy.

scholarly journals Development and Validation of a Three-Gene-Based Prognostic Model for Predicting the Overall Survival of Head and Neck Squamous Cell Carcinoma Through Bioinformatics Analysis

2022 ◽  
Vol 12 ◽  
Author(s):  
Yiyuan Han ◽  
Xiaolin Cao ◽  
Xuemei Wang ◽  
Qing He
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Neck Squamous Cell Carcinoma ◽  
Joint Analysis ◽  
Individual Treatment ◽  
Survival Prediction

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancer worldwide and seriously threats public health safety. Despite the improvement of diagnostic and treatment methods, the overall survival for advanced patients has not improved yet. This study aimed to sort out prognosis-related molecular biomarkers for HNSCC and establish a prognostic model to stratify the risk hazards and predicate the prognosis for these patients, providing a theoretical basis for the formulation of individual treatment plans. We firstly identified differentially expressed genes (DEGs) between HNSCC tissues and normal tissues via joint analysis based on GEO databases. Then a total of 11 hub genes were selected for single-gene prognostic analysis to identify the prognostic genes. Later, the clinical information and transcription information of HNSCC were downloaded from the TCGA database. With the application of least absolute shrinkage and selection operator (LASSO) algorithm analyses for the prognostic genes on the TCGA cohort, a prognostic model consisting of three genes (COL4A1, PLAU and ITGA5) was successfully established and the survival analyses showed that the prognostic model possessed a robust performance in the overall survival prediction. Afterward, the univariate and multivariate regression analysis indicated that the prognostic model could be an independent prognostic factor. Finally, the predicative efficiency of this model was well confirmed in an independent external HNSCC cohort.

scholarly journals Development and validation of an individualized immune prognostic model in stage I–III lung squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi-Fan Yang ◽  
Di Wu ◽  
Jian Wang ◽  
Li Ba ◽  
Chen Tian ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Model ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Stage I ◽  
Tissue Samples ◽  
Mutation Burden

AbstractLung squamous cell carcinoma (LUSC) possesses a poor prognosis even for stages I–III resected patients. Reliable prognostic biomarkers that can stratify and predict clinical outcomes for stage I–III resected LUSC patients are urgently needed. Based on gene expression of LUSC tissue samples from five public datasets, consisting of 687 cases, we developed an immune-related prognostic model (IPM) according to immune genes from ImmPort database. Then, we comprehensively analyzed the immune microenvironment and mutation burden that are significantly associated with this model. According to the IPM, patients were stratified into high- and low-risk groups with markedly distinct survival benefits. We found that patients with high immune risk possessed a higher proportion of immunosuppressive cells such as macrophages M0, and presented higher expression of CD47, CD73, SIRPA, and TIM-3. Moreover, When further stratified based on the tumor mutation burden (TMB) and risk score, patients with high TMB and low immune risk had a remarkable prolonged overall survival compared to patients with low TMB and high immune risk. Finally, a nomogram combing the IPM with clinical factors was established to provide a more precise evaluation of prognosis. The proposed immune relevant model is a promising biomarker for predicting overall survival in stage I–III LUSC. Thus, it may shed light on identifying patient subset at high risk of adverse prognosis from an immunological perspective.

Proton beam radiotherapy of locally advanced or recurrent conjunctival squamous cell carcinoma: experience of the CATANA Centre

2020 ◽  
pp. 1-8
Author(s):  
Roberto Milazzotto ◽  
Rocco Luca Emanuele Liardo ◽  
Giuseppe Privitera ◽  
Luigi Raffaele ◽  
Vincenzo Salamone ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Proton Beam ◽  
Squamous Cell ◽  
Locally Advanced ◽  
Disease Free Survival ◽  
Proton Beam Radiotherapy ◽  
Conjunctival Squamous Cell Carcinoma ◽  
The Impact

Abstract Aim: Conjunctival squamous cell carcinoma (SCC) is a rare tumour of the ocular region and microscopic radical surgical is difficult. There are no single guidelines for therapeutic management and the role of radiation therapy is not clearly defined although conventionally photon or electron beams are used. Proton beam radiotherapy (PBRT) is a new option for a conservative approach and allows good sparing of the organs at risk. Materials and methods: After surgical resection, we collected 15 cases treated at our institution with PBRT. The dose delivered was between 48 and 60 Gy relative biological effectiveness (RBE), with fractions of 12–15 Gy RBE. Results: After an average period of 48 months, the patients achieved excellent disease control (overall survival and disease-free survival: 86·6%), with minimal acute and late toxicity. Findings: In this work, we present our experience on the use of PBRT technique in SCC treatment. A larger sample of patients is needed to draw conclusions about the impact of this treatment on disease recurrence and overall survival.

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