Tumor Compactness based on CT to predict prognosis after multimodal treatment for esophageal squamous cell carcinoma.
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ABSTRACT:
SUBMITTER: Wang Q
PROVIDER: S-EPMC6642095 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To investigate the capability of computed-tomography (CT) radiomic features to predict the therapeutic response of Esophageal Carcinoma (EC) to chemoradiotherapy (CRT).Pretreatment contrast-enhanced CT images of 49 EC patients (33 responders, 16 nonresponders) who received with CRT were retrospectively analyzed. The region of tumor was contoured by two radiologists. A total of 214 features were extracted from the tumor region. Kruskal-Wallis test and receiver operating characteristic (ROC) analysis were performed to evaluate the capability of each feature on treatment response classification. Support vector machine (SVM) and artificial neural network (ANN) algorithms were used to build models for prediction of the treatment response. The statistical difference between the performances of the models was assessed using McNemar's test.Radiomic-based classification showed significance in differentiating responders from nonresponders. Five features were found to discriminate nonresponders from responders (AUCs from 0.686 to 0.727). Considering these features, two features (Histogram2D_skewness: P = 0.015. Histogram2D_kurtosis: P = 0.039) were significant for differentiating SDs (stable disease) from PRs (partial response) and one feature (Histogram2D_skewness: P = 0.027) for differentiating SDs from CRs (complete response). Both classifiers showed potential in predicting the treatment response with higher accuracy (ANN: 0.972, SVM: 0.891). No statistically significant difference was observed in the performance of the two classifiers (P = 0.250).CT-based radiomic features can be used as imaging biomarkers to predict tumor response to CRT in EC patients.
| S-EPMC5732818 | biostudies-other
Project description:BackgroundSolute carrier family 39 member 4 (SLC39A4) has been reported to play an oncogenic role in several cancers. However, the role of SLC39A4 in esophageal squamous cell carcinoma (ESCC) remains unclear. In this study, we aimed to explore the clinical significance and function of SLC39A4 in ESCC.MethodsThe Cancer Genome Atlas and Gene Expression Omnibus databases were analyzed to assess the level of SLC39A4 in ESCC. The expression level of SLC39A4 was measured by RT-qPCR and immunohistochemistry in a cohort of 73 patients aged 45-65 years with ESCC. Kaplan-Meier analysis was used to identify the correlation between SLC39A4 and the prognosis of ESCC patients. In vitro experiments were conducted to explore the biological function of SLC39A4 in ESCC cell line TE-1 and TE-10.ResultsThe mRNA level of SLC39A4 was significantly enhanced in ESCC specimens, which was in line with the outcome of online databases analysis. Moreover, the aberrant expression of SLC39A4 was positively correlated with clinical stage, T categories and lymph node metastasis. Kaplan-Meier analysis indicated that elevated SLC39A4 expression predicted poor prognosis of patients with ESCC. Furthermore, the in vitro experiments showed that SLC39A4 knockdown not only impaired the proliferation and motility capacities of ESCC cells but also enhanced the sensitivity to cisplatin treatment.ConclusionOur findings suggest that SLC39A4 could serve as a novel prognosis biomarker to promote ESCC progression; however, the mechanism of SLC39A4 in ESCC remains to be further explored.
| S-EPMC7227820 | biostudies-literature
Project description:PurposeTo investigate the association between genetic polymorphisms of growth factor-related genes and prognosis in patients with advanced esophageal squamous cell carcinoma (ESCC).Patients and methodsA total of 334 ESCC patients with advanced tumor stages (stages IIB, III and IV) were enrolled in the study. The genotypes of 14 candidate single nucleotide polymorphisms (SNPs) involved in growth factor-related functions were analyzed using iPLEX Gold technology from the genomic DNA of peripheral leukocytes, and were correlated with the clinical outcome of patients. Serum levels of growth factors were examined by enzyme-linked immunosorbent assay (ELISA).ResultsThe genetic polymorphisms of EGF:rs4444903, EGF:rs2237051 and VEGF:rs2010963 showed significant associations with overall survival (OS) of advanced ESCC patients (A/A+ A/G vs. GG, [HR = 0.77, 95% CI = 0.60-0.99, P = 0.039 for rs4444903; A/G+ G/G vs. A/A, [HR = 0.74, 95% CI = 0.58-0.95, P = 0.019 for rs2237051; G/G+G/C vs. C/C, [HR] inves = 0.69, 95% CI = 0.50-0.95, P = 0.023 for rs2010963). EGFR:rs2227983 and 3 SNPs of PIK3CA also showed borderline significant correlation with OS of advanced ESCC patients (P = 0.058 for rs2227983; P = 0.069, 0.091 and 0.067 for rs6443624, rs7651265 and rs7621329 of PIK3CA respectively). According to cumulative effect analysis of multiple SNPs, patients carrying 4 unfavorable genotypes exhibited more than a 3-fold increased risk of mortality. Finally, both EGF and VEGF expression levels significantly associated with patient mortality.ConclusionThe genetic variants and expression levels of EGF and VEGF can serve as prognostic predictors in patients with advanced ESCC, and thus provide more information for optimizing personalized therapies for patients with ESCC.
| S-EPMC4063891 | biostudies-literature
Project description:Fibroblast growth factor receptor-1 (FGFR1) over-expression was broadly found in squamous cancer, where it induced cellular proliferation, differentiation, and metastasis by activating various signaling pathway. However, the role of FGFR1 gene expression in predicting prognosis of Esophageal Squamous Cell Carcinoma (ESCC) and its regulatory function in the progression of ESCC are not well understood. Therefore, we performed an analysis of FGFR1 mRNA expression by quantitative RT-PCR in tumor tissue of 145 patients with ESCC. The relationships between FGFR1 gene expression and clinicopathological parameters, also the prognosis were further examined. Results suggested that higher FGFR1 gene expression predicted worse overall survival (HR = 1.502, 95%[CI] = 1.005-2.246, P = 0.045). Disease-free survival tends to be shorter in patients with higher FGFR1 expression but without statistical significance (HR = 1.398, 95%[CI] = 0.942-2.074, P = 0.096). FGFR1 was up regulated in multiple ESCC cell lines. Subsequent in vitro experiments demonstrated that anti-FGFR1 treatment by PD173074 inhibited TE-1 and EC9706 cell viability along with the attenuation of MEK-ERK signaling pathway. In vivo, PD173074 administration also had shown potent ESCC growth arresting effect. Overall, our study suggested that FGFR1 gene expression could be an independent prognosis predictive factor in patients with ESCC. Anti-FGFR1 inhibited ESCC growth and could be a potential strategy in ESCC targeted therapy.
| S-EPMC5790345 | biostudies-literature
Project description:No clinically relevant biomarker has been identified for predicting the response of esophageal squamous cell carcinoma (ESCC) to chemoradiotherapy (CRT). Herein, we established a CT-based radiomics model with artificial intelligence (AI) to predict the response and prognosis of CRT in ESCC. A total of 44 ESCC patients (stage I-IV) were enrolled in this study; training (n = 27) and validation (n = 17) cohorts. First, we extracted a total of 476 radiomics features from three-dimensional CT images of cancer lesions in training cohort, selected 110 features associated with the CRT response by ROC analysis (AUC ≥ 0.7) and identified 12 independent features, excluding correlated features by Pearson's correlation analysis (r ≥ 0.7). Based on the 12 features, we constructed 5 prediction models of different machine learning algorithms (Random Forest (RF), Ridge Regression, Naive Bayes, Support Vector Machine, and Artificial Neural Network models). Among those, the RF model showed the highest AUC in the training cohort (0.99 [95%CI 0.86-1.00]) as well as in the validation cohort (0.92 [95%CI 0.71-0.99]) to predict the CRT response. Additionally, Kaplan-Meyer analysis of the validation cohort and all the patient data showed significantly longer progression-free and overall survival in the high-prediction score group compared with the low-prediction score group in the RF model. Univariate and multivariate analyses revealed that the radiomics prediction score and lymph node metastasis were independent prognostic biomarkers for CRT of ESCC. In conclusion, we have developed a CT-based radiomics model using AI, which may have the potential to predict the CRT response as well as the prognosis for ESCC patients with non-invasiveness and cost-effectiveness.
| S-EPMC10806175 | biostudies-literature
Project description:Simple Summary PET/CT is an important staging modality in the baseline assessment of locally advanced esophageal squamous cell carcinoma. Accurate staging and response prediction in these patients is essential for management. The aim of this retrospective study was to assess the usefulness of 18F-FDG PET/CT radiomics features in predicting outcomes such as tumor and nodal categories, PET-based response to induction chemotherapy, progression-free survival, and overall survival. In a final cohort of 74 patients, we found that the developed radiomics models can predict these clinical and prognostic outcomes with reasonable accuracy, similar or better than those derived from conventional imaging. Future studies with a larger cohort would be helpful in establishing the significance of these models. Abstract This study aimed to assess the usefulness of radiomics features of 18F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category—70.4%, 70.4%, and 81.5%, respectively; cN category—69.0%, 86.2%, and 86.2%, respectively; PET response—60.0%, 66.7%, and 70.0%, respectively; PFS—60.7%, 75.0%, and 75.0%, respectively; and OS—51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.
| S-EPMC9221147 | biostudies-literature
Project description:Important evidence indicates the microbiota plays a key role in esophageal squamous cell carcinoma (ESCC). The esophageal microbiota was prospectively investigated in 18 patients with ESCC and 11 patients with physiological normal (PN) esophagus by 16S rRNA gene profiling, using next-generation sequencing. The microbiota composition in tumor tissues of ESCC patients were significantly different from that of patients with PN tissues. The ESCC microbiota was characterized by reduced microbial diversity, by decreased abundance of Bacteroidetes, Fusobacteria, and Spirochaetes. Employing these taxa into a microbial dysbiosis index demonstrated that dysbiosis microbiota had good capacity to discriminate between ESCC and PN esophagus. Functional analysis characterized that ESCC microbiota had altered nitrate reductase and nitrite reductase functions compared with PN group. These results suggest that specific microbes and the microbiota may drive or mitigate ESCC carcinogenesis, and this study will facilitate assigning causal roles in ESCC development to certain microbes and microbiota.
| S-EPMC7930383 | biostudies-literature
Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) has the highest mortality rates in China. The 5-year survival rate of ESCC remains dismal despite improvements in treatments such as surgical resection and adjuvant chemoradiation, and current clinical staging approaches are limited in their ability to effectively stratify patients for treatment options. The aim of the present study, therefore, was to develop an immunohistochemistry-based prognostic model to improve clinical risk assessment for patients with ESCC.MethodsWe developed a molecular prognostic model based on the combined expression of axis of epidermal growth factor receptor (EGFR), phosphorylated Specificity protein 1 (p-Sp1), and Fascin proteins. The presence of this prognostic model and associated clinical outcomes were analyzed for 130 formalin-fixed, paraffin-embedded esophageal curative resection specimens (generation dataset) and validated using an independent cohort of 185 specimens (validation dataset).ResultsThe expression of these three genes at the protein level was used to build a molecular prognostic model that was highly predictive of ESCC survival in both generation and validation datasets (P = 0.001). Regression analysis showed that this molecular prognostic model was strongly and independently predictive of overall survival (hazard ratio = 2.358 [95% CI, 1.391-3.996], P = 0.001 in generation dataset; hazard ratio = 1.990 [95% CI, 1.256-3.154], P = 0.003 in validation dataset). Furthermore, the predictive ability of these 3 biomarkers in combination was more robust than that of each individual biomarker.ConclusionsThis technically simple immunohistochemistry-based molecular model accurately predicts ESCC patient survival and thus could serve as a complement to current clinical risk stratification approaches.
| S-EPMC4143329 | biostudies-literature
Project description:Background: The ubiquitin-conjugating enzyme E2 T (UBE2T) has been shown to contribute to several types of cancer. However, no publication has reported its implication in esophageal squamous cell cancer (ESCC). Methods: We explored several public databases, including The Cancer Genome Atlas (TCGA), Oncomine, and gene expression Omnibus (GEO). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene set enrichment analysis (GSEA) were adopted to explore involved signaling pathways. We used R software to develop prognostic gene signatures with the LASSO and stepwise Cox regression analysis, separately. Immunohistochemistry staining was performed to detect UBE2T in 90 ESCC patients, followed by survival analysis. We also used an R package pRRophetic to evaluate chemotherapy sensitivity for the TCGA-ESCC cohort. Results: We found significantly increased UBE2T transcript levels and DNA copy numbers in ESCC tissues. UBE2T was associated with the p53 signaling pathway, cell cycle, Fanconi anemia pathway, and DNA replication, as indicated by Go, KEGG pathway enrichment analysis. These pathways were also upregulated in ESCC. The prognostic signatures with UBE2T-associated genes could stratify ESCC patients into low- and high-risk groups with significantly different overall survival in the TCGA-ESCC cohort. We also validated the association of UBE2T with unfavorable survival in 90 ESCC patients recruited for this study. Moreover, we found that the low-risk group was significantly more sensitive to chemotherapy than the high-risk group. Conclusions: UBE2T is involved in the development of ESCC, and gene signatures derived from UBE2T-associated genes are predictive of prognosis in ESCC.
| S-EPMC8262217 | biostudies-literature
Project description:PurposeThe degree of benefit from palliative chemotherapy differs widely among patients with metastatic esophageal squamous cell carcinoma (MESCC). The purpose of this study was to develop and validate a prognostic nomogram to predict survival and aid physicians and patients in the decision-making process regarding treatment options.Materials and methodsClinicopathologic variables and treatment outcomes of 239 patients who were diagnosed with MESCC and received either fluorouracil/cisplatin (FP) or capecitabine/cisplatin (XP) as first-line chemotherapy were reviewed. A nomogram was developed as a prognostic scoring system incorporating significant clinical and laboratory variables based on a multivariate Cox proportional hazards regression model. An independent series of 61 MESCC patients treated with FP served as an independent data set for nomogram validation.ResultsNo difference in response rate was observed between the FP group (44.8%) and the XP group (54.2%). Similarly, no significant differences in median progression-free survival and median overall survival were observed between regimen groups. Multivariate analysis showed that poor performance status (Eastern Cooperative Oncology Group [ECOG] status≥2), weight loss (10% of the weight loss for 3 months), low albumin level (≤3.5 g/dL), and absence of previous esophagectomy at the time of chemotherapy were significantly associated with low OS in both groups (p<0.05). Based on these findings, patients were classified into favorable (score, 0 to 90), intermediate (91-134), and poor (>135) prognostic groups. The median survival for those with a favorable ECOG was 13.8 months (95% confidence interval [CI], 10.8 to 18.6 months), for intermediate 11.2 months (95% CI, 8.7 to 11.9 months), and for poor, 7.0 months (95% CI, 3.6 to 10.0 months). External validation of the nomogram in a different patient cohort yielded significantly similar findings.ConclusionThe nomogram described here predicts survival in MESCC patients and could serve as a guide for the use of FP/XP chemotherapy in MESCC patients.
| S-EPMC3893326 | biostudies-literature