A 17-molecule set as a predictor of complete response to neoadjuvant chemotherapy with docetaxel, cisplatin, and 5-fluorouracil in esophageal cancer

Fujishima, Hajime; Fumoto, Shoichi; Shibata, Tomotaka; Nishiki, Kohei; Tsukamoto, Yoshiyuki; Etoh, Tsuyoshi; Moriyama, Masatsugu; Shiraishi, Naoki; Ito, Masafumi

doi:10.1371/journal.pone.0188098

Cited by 12 publications

(19 citation statements)

References 45 publications

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“…GSE93756, GSE94012, GSE104958, and GSE143822 datasets are selected from National Center for Biotechnology Information's (NCBI) Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) [16]. GSE93756 dataset has four samples based on platform [17]. GSE143822 dataset has eight samples, and it is based on platform GPL20844 Agilent-072363 SurePrint G3 Human GE v3 8x60K Microarray 039494.…”

Section: Methodsmentioning

confidence: 99%

Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach

Islam

Alam

Paul

et al. 2022

BioMed Research International

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Esophageal carcinoma (EsC) is a member of the cancer group that occurs in the esophagus; globally, it is known as one of the fatal malignancies. In this study, we used gene expression analysis to identify molecular biomarkers to propose therapeutic targets for the development of novel drugs. We consider EsC associated four different microarray datasets from the gene expression omnibus database. Statistical analysis is performed using R language and identified a total of 1083 differentially expressed genes (DEGs) in which 380 are overexpressed and 703 are underexpressed. The functional study is performed with the identified DEGs to screen significant Gene Ontology (GO) terms and associated pathways using the Database for Annotation, Visualization, and Integrated Discovery repository (DAVID). The analysis revealed that the overexpressed DEGs are principally connected with the protein export, axon guidance pathway, and the downexpressed DEGs are principally connected with the L13a-mediated translational silencing of ceruloplasmin expression, formation of a pool of free 40S subunits pathway. The STRING database used to collect protein-protein interaction (PPI) network information and visualize it with the Cytoscape software. We found 10 hub genes from the PPI network considering three methods in which the interleukin 6 (IL6) gene is the top in all methods. From the PPI, we found that identified clusters are associated with the complex I biogenesis, ubiquitination and proteasome degradation, signaling by interleukins, and Notch-HLH transcription pathway. The identified biomarkers and pathways may play an important role in the future for developing drugs for the EsC.

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Section: Methodsmentioning

confidence: 99%

Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach

Islam

Alam

Paul

et al. 2022

BioMed Research International

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“…In the present study, PET-negative LNs after NAC were an independent prognostic factor in the univariate and multivariate analyses. We previously reported that some molecular biomarkers might be predictive factors for esophageal cancer in patients treated with NAC[ 28 ]. If these predictive molecular biomarkers can be clarified further, it is possible that patients with PET-negative LNs after NAC could avoid esophagectomy and undergo strict surveillance.…”

Section: Discussionmentioning

confidence: 99%

Positron emission tomography complete metabolic response as a favorable prognostic predictor in esophageal cancer following neoadjuvant chemotherapy with docetaxel/cisplatin/5-fluorouracil

Suzuki¹,

Etoh²,

Shibata³

et al. 2021

WJCO

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BACKGROUND 18 F-fluorodeoxyglucose-positron emission tomography (PET)/computed tomography is useful in diagnosing lymph node and distant metastases of esophageal cancer. However, its value for predicting survival is controversial. AIM To evaluate the value of PET complete metabolic response (CMR) as a prognostic predictor for esophageal cancer. METHODS Between June 2013 and December 2017, 58 patients with squamous cell esophageal cancer who underwent neoadjuvant chemotherapy (NAC) in Oita University were enrolled in this retrospective cohort study. Tumors were clinically staged using fluorodeoxyglucose-PET/computed tomography before and after NAC. After NAC, maximal standardized uptake value ≤ 2.5 was defined as PET-CMR, and maximal standardized uptake value > 2.5 was defined as non-PET-CMR. We compared short-term outcomes between the PET-CMR group and non-PET-CMR group and evaluated prognostic factors by univariate and multivariate analyses. RESULTS The PET-CMR group included 22 patients, and the non-PET-CMR group included 36 patients. There were no significant differences in intraoperative and postoperative complications between the two groups. Five-year relapse-free survival and overall survival in the PET-CMR group were significantly more favorable than those in the non-PET-CMR group (38.6 mo vs 20.8 mo, P = 0.021; 42.8 mo vs 25.1 mo, P = 0.011, respectively). PET-CMR was a significant prognostic factor in terms of relapse-free survival by univariate analysis (hazard ratio: 2.523; 95% confidence interval: 1.034–7.063; P < 0.041). Particularly, PET-computed tomography negative N was an independent prognostic factor of relapse-free survival and overall survival by multivariate analysis. CONCLUSION PET-CMR after NAC is considered a favorable prognostic factor for esophageal cancer. Evaluation by PET-computed tomography could be useful in clinical decision making for esophageal cancer.

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“…Others utilized cross-validation approaches in a single data set; this approach can be helpful if seeking to evaluate a marker combination, particularly where sample sizes are small [ 36 , 50 , 61 , 90 ]. Seven studies used independent data sets for validation [ 53–55 , 60 , 93 , 95 , 96 ]. Ultimately, the highest level of evidence of validity comes from using an independent sample set that is not used to generate the initial computational model and this is widely recommended [ 36 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

“…Four studies examined mRNA biomarkers in OSCC alone and, similarly to OAC, they varied significantly [ 53–56 ]. Motoori et al .…”

Section: Predictive Biomarkers In Oesophageal Cancermentioning

confidence: 99%

“…Fujishima et al . used microarray data and molecular expression analysis to identify 17 molecules as predictors of pathological complete response, which were associated with pathways including transcriptional regulation by STAT , SMAD , and RB/E2F [ 53 ]. In a separate study focusing on the TGF-β pathway, known to be involved in cell-cycle arrest and apoptotic cell death, increased SMAD4 expression was significantly higher in tumours with total or partial regression compared to those with little or no regression [ 56 , 74 ].…”

Section: Predictive Biomarkers In Oesophageal Cancermentioning

confidence: 99%

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Transcriptomic biomarkers for predicting response to neoadjuvant treatment in oesophageal cancer

Lavery

Turkington

2020

Gastroenterology Report

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Oesophageal cancer is a devastating disease with poor outcomes and is the sixth leading cause of cancer death worldwide. In the setting of resectable disease, there is clear evidence that neoadjuvant chemotherapy and chemoradiotherapy result in improved survival. Disappointingly, only 15%–30% of patients obtain a histopathological response to neoadjuvant therapy, often at the expense of significant toxicity. There are no predictive biomarkers in routine clinical use in this setting and the ability to stratify patients for treatment could dramatically improve outcomes. In this review, we aim to outline current progress in evaluating predictive transcriptomic biomarkers for neoadjuvant therapy in oesophageal cancer and discuss the challenges facing biomarker development in this setting. We place these issues in the wider context of recommendations for biomarker development and reporting. The majority of studies focus on messenger RNA (mRNA) and microRNA (miRNA) biomarkers. These studies report a range of different genes involved in a wide variety of pathways and biological processes, and this is explained to a large extent by the different platforms and analysis methods used. Many studies are also vastly underpowered so are not suitable for identifying a candidate biomarker. Multiple molecular subtypes of oesophageal cancer have been proposed, although little is known about how these relate to clinical outcomes. We anticipate that the accumulating wealth of genomic and transcriptomic data and clinical trial collaborations in the coming years will provide unique opportunities to stratify patients in this poor-prognosis disease and recommend that future biomarker development incorporates well-designed retrospective and prospective analyses.

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A 17-molecule set as a predictor of complete response to neoadjuvant chemotherapy with docetaxel, cisplatin, and 5-fluorouracil in esophageal cancer

Cited by 12 publications

References 45 publications

Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach

Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach

Positron emission tomography complete metabolic response as a favorable prognostic predictor in esophageal cancer following neoadjuvant chemotherapy with docetaxel/cisplatin/5-fluorouracil

Transcriptomic biomarkers for predicting response to neoadjuvant treatment in oesophageal cancer

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