Clinical and pathological features of “small” GIST (≤2 cm). What is their prognostic value?

Fernández, José Antonio López; Gómez-Ruiz, Álvaro Jesús; Olivares, V; Ferri, Belén; Frutos, María Dolores; Soria, T; Álvarez, Pedro Gil; Torres, Gloria; Parrilla, Pascual

doi:10.1016/j.ejso.2018.01.087

Cited by 11 publications

(6 citation statements)

References 31 publications

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“…Some GISTs grow rapidly or produce liver metastases, which can lead to death 10 . On the other hand, some GISTs are found incidentally without any clinical symptoms, even though they have the same KIT mutations 11 , 12 . The relationships between clinical aggressiveness and gene mutations in GISTs remain unclear.…”

Section: Introductionmentioning

confidence: 99%

Low ETV1 mRNA expression is associated with recurrence in gastrointestinal stromal tumors

Sakamaki

Funasaka

Miyahara

et al. 2020

Sci Rep

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Although the majority of gastrointestinal stromal tumors (GISTs) possess KIT mutations that induce constitutive signal transduction, the clinical outcomes are variable. The ETS translocation variant 1 (ETV1) gene encodes a transcription factor that is reported to cooperate with KIT in GISTs. However, the clinical role of ETV1 is largely unknown. The aim of this study was to examine ETV1 expression and its associations with clinical features in GISTs. We conducted a cohort study involving 64 patients with GISTs who underwent surgical resection between October 2008 and February 2015. ETV1 mRNA expression was compared with that in non-GISTs and was analyzed among risk classifications or clinical outcomes. The GIST samples exhibited significantly higher ETV1 mRNA expression than the non-GIST samples (P < 0.0001). Sixty-four GISTs were stratified into high or low ETV1 mRNA expression groups based on the median relative abundance of ETV1 mRNA. The multivariate analysis showed that low ETV1 expression, as well as tumor size and mitotic index, was an independent factor of recurrence (hazard ratio: 8.1). Patients with high ETV1 expression achieved significantly longer recurrence-free survival (RFS) times than those with low ETV1 expression (P = 0.025). Our study revealed that low ETV1 expression is an independent factor of recurrence after surgery in patients with GISTs, and thus, low ETV1 expression might be a marker of more aggressive malignant GISTs.

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Section: Introductionmentioning

confidence: 99%

Low ETV1 mRNA expression is associated with recurrence in gastrointestinal stromal tumors

Sakamaki

Funasaka

Miyahara

et al. 2020

Sci Rep

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“…However, for high‐risk tumors, some patients need treatment with imatinib before surgery to improve the rate of complete tumor resection, and it is recommended that they continue with adjuvant treatment using such molecular targeted drugs to prevent postoperative recurrence or metastasis 9 . Moreover, although most cases of small GIST are clinically benign or inert, there are still rare cases that do exhibit aggressive behavior, especially those with mitotic counts >5 or 10/50 high‐power field (HPF), which are difficult to detect before surgery 10 . Watch and wait follow‐up is not an appropriate management strategy in this situation.…”

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confidence: 99%

MRITexture‐Based Models for Predicting Mitotic Index and Risk Classification of Gastrointestinal Stromal Tumors

Yang

Zheng

Dong

et al. 2020

Magnetic Resonance Imaging

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Background Treatment regimens and prognoses of gastrointestinal stromal tumors (GIST) are quite different for tumors in different risk categories. Accurate preoperative grading of tumors is important for avoiding under‐ or overtreatment. Purpose To develop and validate an MRI texture‐based model to predict the mitotic index and its risk classification. Study Type Retrospective. Population Ninety‐one patients with histologically‐confirmed GIST; 64 patients in a training cohort, and 27 patients in a test cohort. Field Strength/Sequence T2‐weighted imaging (T2WI), diffusion‐weighted imaging (DWI), and dynamic contrast‐enhanced three‐dimensional volumetric interpolated breath‐hold examination (3D‐VIBE) at 1.5T. Assessment GIST images were manually segmented by two independent radiologists using ITK‐SNAP software and MRI features were extracted using Pyradiomics. Two pathologists reviewed the tissue specimens of the tumors to identify the mitotic index and risk classification in consensus. Statistical Tests The least absolute shrinkage and selection operator (LASSO) regression method was used to select texture features. A logistic regression model was established based on the radiomic score (radscore), tumor location, and maximum diameter to predict tumor classification and develop a nomogram. Receiver operator characteristic (ROC) curves were used to evaluate the ability of the nomogram to distinguish between two tumors with different risk classifications, and a calibration curve was used to evaluate the consistency between the predicted risk and the actual risk. Results The texture signature achieved high efficacy in predicting the mitotic index area under the curve ([AUC], 0.906; 95% confidence interval [CI]: 0.813, 0.961). A nomogram for prediction of the risk classification of GIST, which incorporated this texture signature together with maximum tumor diameter and location, allowed good discrimination in the training cohort (AUC, 0.878; 95% CI: 0.769, 0.960) and the validation cohort (AUC, 0.903; 95% CI: 0.732, 0.922). Data Conclusion The texture‐based model can be used to predict GIST mitotic index and risk classification preoperatively. Level of Evidence 2. Technical Efficacy Stage 3

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“…National Comprehensive Cancer Network (NCCN) guidelines recommend endoscopic ultrasound with fine-needle aspiration and biopsy (EUS-FNAB) as the first choice ( Zhao et al, 2020 ). The expression of tumor markers in tumor tissues was detected by immunohistochemistry ( Fernández et al, 2018 ). c-Kit (stem cell growth factor receptor, CD117) is a protein encoded by the KIT gene in humans.…”

Section: Introductionmentioning

confidence: 99%

Molecular Portrait of GISTs Associated With Clinicopathological Features: A Retrospective Study With Molecular Analysis by a Custom 9-Gene Targeted Next-Generation Sequencing Panel

Qian

Yan

et al. 2022

Front. Genet.

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Objectives: The study aims to investigate genetic characterization of molecular targets and clinicopathological features with gastrointestinal stromal tumors based on targeted next-generation sequencing.Materials and Methods: We selected 106 patients with GISTs from Sir Run Run Shaw Hospital between July 2019 and March 2021. FFPE samples and paired blood samples were obtained from these patients who underwent excision of the tumor. A customized targeted-NGS panel of nine GIST-associated genes was designed to detect variants in the coding regions and the splicing sites of these genes.Results: In total, 106 patients with a GIST were included in the study which presented with various molecular driver alterations in this study. KIT mutations occurred most often in GISTs (94/106, 95.92%), followed by point mutations in PDGFRA. KIT or PDGFRA mutations were detected to be mutually exclusive in the GIST. A total of eight patients with wide-type KIT/PDGFRA were characterized as WT-GISTs, according to clinical diagnosis which included six quadruple-WT GISTs, 1 BRAF-mutant, and 1 NF1-mutant GIST. In KIT exon 11, the most common mutation type was the codon Mutation (in-frame deletion or indels), whereas the missense mutation was the dominant type in KIT exon 13 and KIT exon 17. All variations in KIT exon 11 observed in this study were concentrated at a certain position of codon 550 to codon 576. Mutation in KIT exon 9 was mostly located at codon 502–503. Two germline pathogenic mutations were detected: NF1-R681* and KRAS-T58I. NF1-L591P was a germline mutation to be identified for the first time and is not recorded in the database. The frequency of driving mutations differed between the primary anatomical site in the GIST (p = 0.0206). KIT exon 11 mutants had a lower proliferation index of Ki67 (68.66%,≤5%), while 50.00% of KIT exon 9 mutants had the Ki67 status greater than 10%.Conclusion: The occurrence and development of a GIST is driven by different molecular variations. Resistance to TKIs arises mainly with resistance mutations in KIT or PDGFRA when they are the primary drivers. Targeted NGS can simultaneously and efficiently detect nine GIST-related gene mutations and provide reference for clinicians’ individualized diagnosis and treatment. Our results have important implications for clinical management.

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Clinical and pathological features of “small” GIST (≤2 cm). What is their prognostic value?

Cited by 11 publications

References 31 publications

Low ETV1 mRNA expression is associated with recurrence in gastrointestinal stromal tumors

Low ETV1 mRNA expression is associated with recurrence in gastrointestinal stromal tumors

MRITexture‐Based Models for Predicting Mitotic Index and Risk Classification of Gastrointestinal Stromal Tumors

Molecular Portrait of GISTs Associated With Clinicopathological Features: A Retrospective Study With Molecular Analysis by a Custom 9-Gene Targeted Next-Generation Sequencing Panel

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