Gastrointestinal Stromal Tumors Patients Research Articles

Clinical and Biomarker Analysis of a Phase I/II Study of PDR001 plus Imatinib for Advanced Treatment-refractory Gastrointestinal Stromal Tumors.

In this phase Ib/II study, we aimed to evaluate the safety and efficacy of PDR001, an anti-PD-1 antibody, in combination with imatinib in patients with treatment-refractory gastrointestinal stromal tumor (GIST). Advanced GIST patients whose disease had progressed on imatinib, sunitinib, and regorafenib were enrolled. In phase Ib, the standard 3+3 dose escalation scheme was applied. PDR001 400 mg intravenously every 4 weeks plus imatinib (300 mg and 400 mg daily for dose levels I and II, respectively) was given. The primary outcome for phase II was the disease control rate (DCR) at 12 weeks. Exploratory biomarker analysis was performed based on PD-L1 immunohistochemistry, next-generation sequencing, and multiplexed immunohistochemistry. No dose-limiting toxicity was observed in the phase Ib part (n=10), and dose level 2 was selected as the recommended phase II dose. In the phase II part (n=29), there was no objective response and the DCR at 12 weeks was 37.9%, not meeting the primary efficacy endpoint. For patients in phase Ib-dose level II and phase II (n=36), the median progression-free survival (PFS) and overall survival were 2.3 and 9.5 months, respectively. The most common grade 3-4 adverse event was anemia. Exploratory biomarker analysis indicated that a higher CD8+ T cell density was associated with a favorable PFS, but to a limited degree. Tumor mutation burden and PD-L1 were not associated with better PFS. In patients with treatment-refractory GIST, PDR001 in combination with imatinib was generally tolerable, but it was not effective.

Monitoring advanced gastrointestinal stromal tumor with circulating tumor DNA.

This review explores the role of circulating tumor (ct)DNA as a biomarker for clinical decision-making and monitoring purposes in metastatic gastrointestinal stromal tumor (GIST) patients. We discuss key insights from recent clinical trials and anticipate the future perspectives of ctDNA profiling within the clinical landscape of GIST. The identification and molecular characterization of KIT/platelet-derived growth factor receptor alpha (PDGFRA) mutations from ctDNA in metastatic GIST is feasible and reliable. Such identification through ctDNA serves as a predictor of clinical outcomes to tyrosine-kinase inhibitors (TKIs) in metastatic patients. Additionally, conjoined ctDNA analysis from clinical trials reveal the evolving mutational landscapes and increase in intratumoral heterogeneity across treatment lines. Together, this data positions ctDNA determination as a valuable tool for monitoring disease progression and guiding therapy in metastatic patients. These collective efforts culminated in the initiation of a ctDNA-based randomized clinical trial in GIST, marking a significant milestone in integrating ctDNA testing into the clinical care of GIST patients. The dynamic field of ctDNA technologies is rapidly evolving and holds significant promise for research. Several trials have successfully validated the clinical utility of ctDNA in metastatic GIST, laying the foundations for its prospective integration into the routine clinical management of GIST patients.

Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor.

Preoperative knowledge of mutational status of gastrointestinal stromal tumors (GISTs) is essential to guide the individualized precision therapy. To develop a combined model that integrates clinical and contrast-enhanced computed tomography (CE-CT) features to predict gastric GISTs with specific genetic mutations, namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions. A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio. The models were constructed using selected clinical features, conventional CT features, and radiomics features extracted from abdominal CE-CT images. Three models were developed: ModelCT sign, modelCT sign + rad, and model CTsign + rad + clinic. The diagnostic performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis and the Delong test. The ROC analyses revealed that in the training cohort, the area under the curve (AUC) values for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic for predicting KIT exon 11 mutation were 0.743, 0.818, and 0.915, respectively. In the validation cohort, the AUC values for the same models were 0.670, 0.781, and 0.811, respectively. For predicting KIT exon 11 codons 557-558 deletions, the AUC values in the training cohort were 0.667, 0.842, and 0.720 for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic, respectively. In the validation cohort, the AUC values for the same models were 0.610, 0.782, and 0.795, respectively. Based on the decision curve analysis, it was determined that the modelCT sign + rad + clinic had clinical significance and utility. Our findings demonstrate that the combined modelCT sign + rad + clinic effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions. This combined model has the potential to be valuable in assessing the genotype of GISTs.

Comparable long‑term survival outcomes of endoscopic treatment versus surgical treatment for gastrointestinal stromal tumors with a diameter of 5–10 cm

Currently, endoscopic treatment for small gastrointestinal stromal tumors (GIST) has been widely accepted. However, for tumors larger than 5 cm, endoscopic treatment has not been recognized by national guidelines as the standard therapy due to concerns about safety and adverse tumor outcomes. Therefore, this study compares the long-term survival outcomes of endoscopic treatment and surgical treatment for GIST in the range of 5–10 cm. We selected patients with GIST from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Kaplan–Meier analysis and the log-rank test were employed to compare the long-term survival outcomes between endoscopic treatment and surgical treatment. A multivariate Cox proportional hazards model was used for analysis to identify risk factors influencing patient prognosis. To balance baseline data, we performed 1:1 propensity score matching (PSM). A total of 1223 GIST patients were included, with 144 patients (11.8%) received endoscopic treatment and 1079 patients (88.2%) received surgical treatment. Before PSM, there was no significant difference in the long-term survival rates between the two groups [5-year OS (86.5% vs. 83.5%, P = 0.42), 10-year OS (70.4% vs. 66.7%, P = 0.42)]. After adjusting for covariates, we found that the overall survival (HR = 1.26, 95% CI 0.89–1.77, P = 0.19) and cancer-specific survival (HR = 1.69, 95% CI 0.99–2.89, P = 0.053) risks were comparable between the endoscopic treatment group and the surgical treatment group. In the analysis after PSM, there was no significant difference between the endoscopic treatment group and the surgical treatment group. Our study found that for GIST patients with tumor sizes between 5 and 10 cm, the long-term OS and CSS outcomes were similar between the endoscopic treatment group and the surgical treatment group.

Financial difficulties experienced by patients with gastrointestinal stromal tumours (GIST) in the Netherlands: data from a cross-sectional multicentre study

PurposeThis study aims to (1) explore the prevalence of patient-reported financial difficulties among GIST patients, differentiating between those currently undergoing tyrosine kinase inhibitor (TKI) treatment and those who are not; (2) investigate associations between financial difficulties and sociodemographic and clinical characteristics, work, cancer-related concerns, anxiety and depression and (3) study the impact of financial difficulties on health-related quality of life.MethodsA cross-sectional study was conducted among Dutch GIST patients diagnosed between 2008 and 2018, who were invited to complete a one-time survey between September 2020 and June 2021. Patients completed nine items of the EORTC item bank regarding financial difficulties, seven work-related questions, the Hospital Anxiety and Depression Scale, Cancer Worry Scale and EORTC QLQ-C30.ResultsIn total, 328 GIST patients participated (response rate 63.0%), of which 110 (33.8%) were on TKI treatment. Patients currently treated with TKIs reported significantly more financial difficulties compared to patients not on TKIs (17.3% vs 8.7%, p = 0.03). The odds of experiencing financial difficulties was 18.9 (95% CI 1.7–214.7, p = 0.02) times higher in patients who were less able to work due to their GIST diagnosis. Patients who experienced financial difficulties had significantly lower global quality of life and functioning, and more frequently reported psychological symptoms as compared to patients who did not report financial difficulties.ConclusionEven in a country where the costs of TKIs and follow-up care are covered by health insurance, financial difficulties can be present in GIST patients, especially in patients on TKI treatment, and may negatively influence the quality of life.

The development of a prediction model based on deep learning for prognosis prediction of gastrointestinal stromal tumor: a SEER-based study

Accurately predicting the prognosis of Gastrointestinal stromal tumor (GIST) patients is an important task. The goal of this study was to create and assess models for GIST patients' survival patients using the Surveillance, Epidemiology, and End Results Program (SEER) database based on the three different deep learning models. Four thousand five hundred thirty-eight patients were enrolled in this study and divided into training and test cohorts with a 7:3 ratio; the training cohort was used to develop three different models, including Cox regression, RSF, and DeepSurv model. Test cohort was used to evaluate model performance using c-index, Brier scores, calibration, and the area under the curve (AUC). The net benefits at risk score stratification of GIST patients based on the optimal model was compared with the traditional AJCC staging system using decision curve analysis (DCA). The clinical usefulness of risk score stratification compared to AJCC tumor staging was further assessed using the Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI). The DeepSurv model predicted cancer-specific survival (CSS) in GIST patients showed a higher c-index (0.825), lower Brier scores (0.142), and greater AUC of receiver operating characteristic (ROC) analysis (1-year ROC:0.898; 3-year:0.853, and 5-year ROC: 0.856). The calibration plots demonstrated good agreement between the DeepSurv model's forecast and actual results. The NRI values ( training cohort: 0.425 for 1-year, 0.329 for 3-year and 0.264 for 5-year CSS prediction; test cohort:0.552 for 1-year,0.309 for 3-year and 0.255 for 5-year CSS prediction) and IDI (training cohort: 0.130 for 1-year,0.141 for 5-year and 0.155 for 10-year CSS prediction; test cohort: 0.154 for 1-year,0.159 for 3-year and 0.159 for 5-year CSS prediction) indicated that the risk score stratification performed significantly better than the AJCC staging alone (P < 0.001). DCA demonstrated the risk score stratification as more clinically beneficial and discriminatory than AJCC staging. Finally, an interactive native web-based prediction tool was constructed for the survival prediction of GIST patients. This study established a high-performance prediction model for projecting GIST patients based on deep learning, which has advantages in predicting each person's prognosis and risk stratification.

Identification and validation of protein biomarkers for predicting gastrointestinal stromal tumor recurrence

We conducted a proteomic analysis using mass spectrometry to identify and validate protein biomarkers for accurately predicting recurrence risk in gastrointestinal stromal tumors (GIST) patients, focusing on differentially expressed proteins in metastatic versus primary GIST tissues. We selected five biomarkers—GPX4, RBM4, TPM3, PFKFB2, and PGAM5—and validated their expressions in primary tumors of recurrent and non-recurrent GIST patients via immunohistochemistry. Our analysis of the association between these biomarkers with recurrence-free survival (RFS) and overall survival (OS), along with their interrelationships, revealed that immunohistochemistry confirmed significantly higher expressions of these biomarkers in primary GIST tissues of recurrent patients. Kaplan-Meier survival analysis showed that high expressions of GPX4, RBM4, TPM3, PFKFB2, and PGAM5 correlated with lower RFS, and GPX4 and RBM4 with lower OS. All biomarker pairs showed positive associations, with high expressions correlating with increased recurrence rates, and GPX4 and RBM4 with higher mortality rates. In conclusion, the biomarkers GPX4, RBM4, TPM3, PFKFB2, and PGAM5 are clinically relevant for predicting GIST recurrence, with their high expressions in primary tumors linked to poorer RFS and OS. They serve as potential prognostic indicators, enabling early treatment and improved outcomes. The observed interrelationships among these biomarkers further validate their accuracy in predicting GIST recurrence.

Referral patterns of GIST patients: data from a nationwide study.

This study compares the characteristics, referral and treatment patterns and overall survival (OS) of gastrointestinal stromal tumor (GIST) patients treated in reference and non-reference centers in the Netherlands. This retrospective cohort study on patients diagnosed between 2016 and 2019, utilises data from the Netherlands Cancer Registry and the Dutch Nationwide Pathology Database. Patients were categorized into two groups: patients diagnosed in or referred to reference centers and patients diagnosed in non-reference centers without referral. This study included 1,550 GIST patients with a median age of 67.0 in reference and 68.0 years in non-reference centers. Eighty-seven per cent of patients were diagnosed in non-reference centers, of which 36.5% (493/1,352) were referred to a reference center. Referral rates were higher for high-risk (62.2% [74/119]) and metastatic patients (67.2% [90/134]). Mutation analysis was performed in 96.9% and 87.6% of these cases in reference and in non-reference centers (p < 0.01), respectively. Systemic therapy was given in reference centers versus non-reference in 89.5% versus 82.0% (p < 0.01) of high-risk and in 94.1% versus 65.9% (p < 0.01) of metastatic patients, respectively. The proportion of positive resection margins and tumor rupture did not differ between reference and non-reference centers. Median OS was not reached. A substantial amount of metastatic GIST patients in non-reference centers did not receive systemic treatment. This might be due to valid reasons. However, optimisation of the referral strategy of GIST patients in the Netherlands could benefit patients. Further research is needed to explore reasons for not starting systemic treatment in metastatic GIST patients.

Development and validation of a preoperative risk nomogram prediction model for gastric gastrointestinal stromal tumors.

Gastrointestinal stromal tumors (GIST) carry a potential risk of malignancy, and the treatment of GIST varies for different risk levels. However, there is no systematic preoperative assessment protocol to predict the malignant potential of GIST. The aim of this study was to develop a reliable and clinically applicable preoperative nomogram prediction model to predict the malignant potential of gastric GIST. Patients with a pathological diagnosis of gastric GIST from January 2015 to December 2021 were screened retrospectively. Univariate and multivariate logistic analyses were used to identify independent risk factors for gastric GIST with high malignancy potential. Based on these independent risk factors, a nomogram model predicting the malignant potential of gastric GIST was developed and the model was validated in the validation group. A total of 494 gastric GIST patients were included in this study and allocated to a development group (n = 345) and a validation group (n = 149). In the development group, multivariate logistic regression analysis revealed that tumor size, tumor ulceration, CT growth pattern and monocyte-to- lymphocyte ratio (MLR) were independent risk factors for gastric GIST with high malignancy potential. The AUC of the model were 0.932 (95% CI 0.890-0.974) and 0.922 (95% CI 0.868-0.977) in the development and validation groups, respectively. The best cutoff value for the development group was 0.184, and the sensitivity and specificity at this value were 0.895 and 0.875, respectively. The calibration curves indicated good agreement between predicted and actual observed outcomes, while the DCA indicated that the nomogram model had clinical application. Tumor size, tumor ulceration, CT growth pattern and MLR are independent risk factors for high malignancy potential gastric GIST, and a nomogram model developed based on these factors has a high ability to predict the malignant potential of gastric GIST.

Development and validation of a computed tomography-based radiomics signature to predict "highest-risk" from patients with high-risk gastrointestinal stromal tumor.

Some patients with high-risk gastrointestinal stromal tumor (GIST) experience disease progression after complete resection and adjuvant therapy. It is of great significance to distinguish these patients among those with high-risk GIST. Radiomics has been demonstrated as a promising tool to predict various tumors prognosis. From January 2006 to December 2018, a total of 100 high-risk GIST patients (training cohort: 60; validation cohort: 40) from Guangdong Provincial People's Hospital with preoperative enhanced computed tomography (CT) images were enrolled. The radiomics features were extracted and a risk score was built using least absolute shrinkage and selection operator-Cox model. The clinicopathological factors were analyzed and a nomogram was established with and without radiomics risk score. The concordance index (C-index), calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the radiomics nomograms. We selected 11 radiomics features associated with recurrence or metastasis. The risk score was calculated and significantly associated with disease-free survival (DFS) in both the training and validation group. Cox regression analysis showed that Ki67 was an independent risk factor for DFS [P=0.004, hazard ratio 4.615, 95% confidence interval (CI): 1.624-13.114]. The combined radiomics nomogram, which integrated the radiomics risk score and significant clinicopathological factors, showed good performance in predicting DFS, with a C-index of 0.832 (95% CI: 0.761-0.903), which was better than the clinical nomogram (C-index 0.769, 95% CI: 0.679-0.859) in training cohort. The calibration curves and the DCA plot suggested satisfying accuracy and clinical utility of the model. The CT-based radiomics nomogram, combined with the clinicopathological factors and risk score, has good potential to assess the recurrence or metastasis of patients with high-risk GIST.

TRIM21/USP15 balances ACSL4 stability and the imatinib resistance of gastrointestinal stromal tumors.

Imatinib has become an exceptionally effective targeted drug for treating gastrointestinal stromal tumors (GISTs). Despite its efficacy, the resistance to imatinib is common in GIST patients, posing a significant challenge to the effective treatment. The expression profiling of TRIM21, USP15, and ACSL4 in GIST patients was evaluated using Western blot and immunohistochemistry. To silence gene expression, shRNA was utilized. Biological function of TRIM21, USP15, and ACSL4 was examined through various methods, including resistance index calculation, colony formation, shRNA interference, and xenograft mouse model. The molecular mechanism of TRIM21 and USP15 in GIST was determined by conducting Western blot, co-immunoprecipitation, and quantitative real-time PCR (qPCR) analyses. Here we demonstrated that downregulation of ACSL4 is associated with imatinib (IM) resistance in GIST. Moreover, clinical data showed that higher levels of ACSL4 expression are positively correlated with favorable clinical outcomes. Mechanistic investigations further indicated that the reduced expression of ACSL4 in GIST is attributed to excessive protein degradation mediated by the E3 ligase TRIM21 and the deubiquitinase USP15. These findings demonstrate that the TRIM21 and USP15 control ACSL4 stability to maintain the IM sensitive/resistant status of GIST.

Molecular and clinicopathological features of KIT/PDGFRA wild-type gastrointestinal stromal tumors.

Approximately 10% of gastrointestinal stromal tumors (GISTs) harbor reportedly no KIT and PDGFRA mutations (wild-type GISTs). The clinicopathological features and oncologic outcomes of wild-type GISTs based on molecular profiles are unknown. We recruited 35 wild-type GIST patients from the two registry studies of high-risk GISTs between 2012 and 2015 and primary GISTs between 2003 and 2014. Molecular profiling of wild-type GISTs was performed by targeted next-generation sequencing (NGS) using formalin-fixed paraffin-embedded tumor samples. Among 35 wild-type GISTs, targeted NGS analysis detected NF1, SDH, or BRAF mutation: 16 NF1-GISTs with various NF1 mutations, 12 SDH-GISTs (4 with SDHA mutations, 4 with SDHB mutations, and 4 with SDHB-negative staining), and 5 BRAF-GISTs with the V600E mutation. Two GISTs showed no mutations based on our targeted NGS analysis. Additional gene mutations were infrequent in primary wild-type GISTs and found in TP53, CREBBP, CDKN2A, and CHEK2. Most NF1-GISTs were located in the small intestine (N = 12; 75%) and showed spindle cell features (N = 15; 94%) and multiple tumors (N = 6, 38%) with modest proliferation activities. In contrast, SDH-GISTs were predominantly found in the stomach (N = 11; 92%), exhibiting epithelioid cell (N = 6; 50%) and multiple (N = 6, 50%) features. The overall survival of patients with SDH-GISTs appeared to be better than that of BRAF-GISTs (p = 0.0107) or NF1-GISTs (p = 0.0754), respectively. In conclusion, major molecular changes in wild-type GISTs include NF1, SDH, and BRAF. NF1-GISTs involved multifocal spindle cell tumors in the small intestine. SDH-GISTs occurred in young patients and were multifocal in the stomach and clinically indolent.

A case-matched study of imatinib mesylate between different formulations on plasma trough concentration, adverse events, quality of life and outcomes in gastrointestinal stromal tumor patients.

Genike, the imatinib (IM)-alpha form is widely used in the treatment of gastrointestinal stromal tumor (GIST) patients in China. We wanted to investigate whether there are differences in IM plasma concentrations, adverse events, health-related quality of life (QOL) and outcomes between patients treated with Genike and Glivec. Thirty included GIST patients receiving IM treatment were matched to either Genike or Glivec according to gastrectomy, body weight, body surface area and sex. There was no statistically significant difference in IM trough plasma levels between the two groups. There were no significant differences in very common adverse events of IM between the Genike and Glivec groups. IM was well tolerated, although it was associated with a significant change in cognitive function (P < 0.001), fatigue (P = 0.015), pain (P = 0.015), nausea/vomiting (P = 0.029), insomnia (P = 0.019), diarrhea (P = 0.003) and financial difficulties (P < 0.001). Physical functioning, financial burden and insomnia were significantly different between the two groups (P = 0.026). Until Aug. 2022, there was no significant difference in time to imatinib treatment failure (TTF) between the two groups. In conclusion, there was no difference in IM plasma concentration and adverse events between Genike and Glivec. Both Genike and Glivec could partially decrease the QOL of GIST patients. Physical functioning was worse in Genike group than in Glivec group, while the economic burden and symptoms of insomnia in Glivec patients were worse. There was no significant difference in TTF between the two groups.

Using machine learning models to predict synchronous genitourinary cancers among gastrointestinal stromal tumor patients.

Gastrointestinal stromal tumors (GISTs) can occur synchronously with other neoplasms, including the genitourinary (GU) system. Machine learning (ML) may be a valuable tool in predicting synchronous GU tumors in GIST patients, and thus improving prognosis. This study aims to evaluate the use of ML algorithms to predict synchronous GU tumors among GIST patients in a specialist research center in Saudi Arabia. We analyzed data from all patients with histopathologically confirmed GIST at our facility from 2003 to 2020. Patient files were reviewed for the presence of renal cell carcinoma, adrenal tumors, or other GU cancers. Three supervised ML algorithms were used: logistic regression, XGBoost Regressor, and random forests (RFs). A set of variables, including independent attributes, was entered into the models. A total of 170 patients were included in the study, with 58.8% (n = 100) being male. The median age was 57 (range: 9-91) years. The majority of GISTs were gastric (60%, n = 102) with a spindle cell histology. The most common stage at diagnosis was T2 (27.6%, n = 47) and N0 (20%, n = 34). Six patients (3.5%) had synchronous GU tumors. The RF model achieved the highest accuracy with 97.1%. Our study suggests that the RF model is an effective tool for predicting synchronous GU tumors in GIST patients. Larger multicenter studies, utilizing more powerful algorithms such as deep learning and other artificial intelligence subsets, are necessary to further refine and improve these predictions.

Fear, anxiety and depression in gastrointestinal stromal tumor (GIST) patients in the Netherlands: Data from a cross-sectional multicenter study

BackgroundThis study aims to (1) investigate the prevalence of anxiety, depression and severe fear of cancer recurrence or progression in gastrointestinal stromal tumor (GIST) patients treated in a curative or palliative setting, (2) compare their prevalence with a norm population, (3) identify factors associated with anxiety, depression and severe fear, and (4) study the impact of these psychological symptoms on health-related quality of life (HRQoL). MethodsIn a cross-sectional study, GIST patients completed the Hospital Anxiety and Depression Scale, Cancer Worry Scale, and EORTC QLQ-C30. ResultsOf the 328 patients, 15% reported anxiety, 13% depression, and 43% had severe fear. Anxiety and depression levels were comparable between the norm population and patients in the curative setting, but significantly higher for patients in the palliative setting. Having other psychological symptoms was associated with anxiety, while current TKI treatment and anxiety were associated with depression. Severe fear was associated with age, female sex, palliative treatment setting, anxiety, and GIST-related concerns. ConclusionGIST patients treated in a palliative setting are more prone to experience psychological symptoms, which can significantly impair their HRQoL. These symptoms deserve more attention in clinical practice, in which regular screening can be helpful, and appropriate interventions should be offered.

Effects of surgical management for gastrointestinal stromal tumor patients with liver metastasis on survival outcomes.

To investigate the effect of surgical resection on survival in gastrointestinal stromal tumors synchronous liver metastasis (GIST-SLM) and to develop clinically usable predictive models for overall survival (OS) and cancer-specific survival (CSS) in patients. We identified patients in the SEER database diagnosed with GISTs from 2010 to 2019. We used propensity score matching (PSM) to balance the bias between the Surgery and No surgery groups. Kaplan-Meier(K-M) analysis was used to detect differences in OS and CSS between the two groups. The nomogram to predict 1, 3, and 5-year OS and CSS were developed and evaluated. After PSM, 228 patients were included in this study. There were significant differences in 1, 3, and 5-year OS and CSS between the two groups (OS: 93.5% vs. 84.4%, 73.2% vs. 55.3%, 60.9% vs. 36.9%, P=0.014; CSS: 3.5% vs.86.2%,75.3% vs.57.9%, 62.6% vs. 42.9%, P=0.02). We also found that patients who received surgery combined with targeted therapy had better OS and CSS at 1, 3, and 5 years than those who received surgery only (OS: 96.6% vs.90.9%, 74.9% vs. 56.8%, 61.7% vs. 35.5%, P=0.022; CSS: 96.6% vs. 92.1%, 77.4% vs.59.2%,63.8% vs. 42.0%, P=0.023). The area under the curve (AUC) was 0.774, 0.737, and 0.741 for 1, 3, and 5-year OS, respectively, with 0.782 and 0.742 for 1, 3, and 5-year CSS. In the model, C-index was 0.703 for OS and 0.705 for CSS and showed good consistency. Surgical treatment can improve the OS and CSS of patients with GIST-SLM. In addition, the combination with chemotherapy may be more favorable for the long-term survival of patients. Meanwhile, we constructed the nomograms for predicting OS and CSS at 1, 3, and 5-year, and validated them internally. Our model can contribute to clinical management and treatment strategy optimization.

FBXW7 regulates the sensitivity of imatinib in gastrointestinal stromal tumors by targeting MCL1.

Imatinib contributes to improving prognosis of high-risk or unresectable gastrointestinal stromal tumors (GISTs). As therapeutic efficacy is limited by imatinib resistance and toxicity, the exploration of predictive markers of imatinib therapeutic efficacy that enables patients to utilize more effective therapeutic strategies remains urgent. The correlation between FBXW7 and imatinib resistance via FBXW7-MCL1 axis was evaluated in vitro and in vivo experiments. The significance of FBXW7 as a predictor of imatinib treatment efficacy was examined in 140 high-risk patients with GISTs. The ability of FBXW7 to predict therapeutic efficacy of adjuvant imatinib in high-risk GIST patients was determined through 5-year recurrence-free survival (RFS) rates analysis and multivariate analysis. FBXW7 affects imatinib sensitivity by regulating apoptosis in GIST-T1 cells. FBXW7 targets MCL1 to regulate apoptosis. MCL1 involves in the regulation of imatinib sensitivity through inhibiting apoptosis in GIST-T1 cells. FBXW7 regulates imatinib sensitivity by down-regulating MCL1 to enhance imatinib-induced apoptosis in vitro. FBXW7 regulates imatinib sensitivity of GIST cells by targeting MCL1 to predict efficacy of imatinib treatment in vivo. FBXW7 regulates imatinib sensitivity by inhibiting MCL1 to enhance imatinib-induced apoptosis in GIST, and predicts efficacy of imatinib treatment in high-risk GIST patients treated with imatinib.

Imatinib induces ferroptosis in gastrointestinal stromal tumors by promoting STUB1-mediated GPX4 ubiquitination

Imatinib (IM) has significantly improved the prognosis of gastrointestinal stromal tumor (GIST) patients, but some patients still have primary resistance to IM, and approximately half of patients develop acquired drug resistance within 2 years of treatment, necessitating exploration of new treatment strategies. Targeting ferroptosis as a novel approach to tumor treatment has gained attention. Yet, there is limited research on ferroptosis in GIST, and the underlying mechanism remains unclear. In this study, we revealed that IM increased lipid reactive oxygen species and intracellular Fe2+ levels, and decreased glutathione levels in GIST. This effect could be partially inhibited by Ferrostatin-1. Additionally, knocking down STUB1 and overexpressing GPX4 reversed the IM-induced ferroptosis effect. Moreover, STUB1 was identified as a novel E3 ubiquitin ligase of GPX4, promoting the ubiquitination at site K191 of GPX4. The combination of the GPX4 inhibitor RSL3 and IM synergistically induces ferroptosis, inhibiting GIST proliferation both in vivo and in vitro. Furthermore, STUB1 and GPX4 expression serve as independent prognostic factors for GIST. In conclusion, This study is the first to demonstrate that IM induces ferroptosis by promoting STUB1-mediated GPX4 ubiquitination in GIST, and the combination of RSL3 and IM emerges as a promising therapeutic strategy for GIST.

CT features combined with RECIST 1.1 criteria improve progression assessments of sunitinib-treated gastrointestinal stromal tumors.

To explore the auxiliary value of combining CT features with existing response evaluation criteria in the prediction of progressive disease (PD) in gastrointestinal stromal tumors (GIST) patients treated with sunitinib. Eighty-one patients with GISTs who received sunitinib were included in this retrospective multicenter study and divided into training and external validation cohorts. Progression at six months was determined as a reference standard. The predictive performance of the RECIST 1.1 and Choi criteria was compared. CT features at baseline and the first follow-up were analyzed. Logistic regression analyses were used to determine the most significant predictors and develop modified criteria. A total of 216 lesions showed a good response and 107 showed a poor response in 81 patients. The RECIST 1.1 criteria performed better than the Choi criteria in predicting progression (AUC, 0.75 vs. 0.69, p= 0.04). The expanded/intensified high-enhancement area, blurred tumor-tissue interface, and progressive enlarged vessels feeding or draining the mass (EVFDM) differed significantly between lesions with good and poor responses in the training cohort (p= 0.001, 0.003, and 0.000, respectively). Multivariate analysis revealed that the expanded/intensified high-enhancement area (p= 0.001), progressive EVFDM (p= 0.000), and RECIST PD (p= 0.000) were independent predictive factors. Modified RECIST (mRECIST) criteria were developed and showed significantly higher AUCs in the training and external validation cohorts than the RECIST 1.1 criteria (training: 0.81 vs. 0.73, p= 0.002; validation: 0.82 vs. 0.77, p= 0.04). The mRECIST criteria, combining CT features with the RECIST 1.1 criteria, demonstrated superior performance in the prediction of early progression in GIST patients receiving sunitinib. The mRECIST criteria, which combine CT features with the RECIST 1.1 criteria, may facilitate the early detection of progressive disease in GIST patients treated with sunitinib, thereby potentially guiding the timely switch to late-line medications or combination with surgical excision. • The RECIST 1.1 criteria outperformed the Choi criteria in identifying progression of GISTs in patients treated with sunitinib. • GISTs displayed different morphologic features on CT depending on how they responded to sunitinib. • Combining CT morphologic features with the RECIST 1.1 criteria allowed for the prompt and accurate identification of progressing GIST lesions.

The association of having a monitoring or blunting coping style with psychological distress, health-related quality of life and satisfaction with healthcare in gastrointestinal stromal tumour (GIST) patients

Background There are two main coping styles regarding information seeking under medical threat; monitoring (information-seeking) and blunting (information-avoiding). The aim of this study is to (1) determine factors associated with a monitoring or blunting coping style in gastro-intestinal stromal tumour (GIST) patients and (2) investigate its association with psychological distress, cancer-related concerns, health-related quality of life and satisfaction with healthcare. Methods In a cross-sectional study, Dutch GIST patients completed the shortened version of the Threatening Medical Situations Inventory to determine their coping style, the Hospital Anxiety and Depression Scale, Cancer Worry Scale, EORTC QLQ-C30 and part of the EORTC QLQ-INFO25. Results A total of 307 patients were classified as blunters (n = 175, 57%) or monitors (n = 132, 43%). Coping style was not associated with tumour or treatment variables, but being a female (OR 2.5; 95%CI 1.5–4.1; p= <.001) and higher educated (OR 5.5; 95%CI 2.5–11.9, p= <.001) were associated with higher odds of being a monitor. Monitors scored significantly lower on emotional functioning (mean = 86.8 vs mean = 90.9, p=.044), which is considered a trivial difference, more often experienced severe fear of cancer recurrence or progression (53.0% vs 37.7%, p=.007), and had more concerns about dying from GIST in the future (60.6% vs 47.4%, p=.025). Compared to blunters, monitors were less satisfied with the received healthcare and information, and would have liked to receive more information. Conclusion GIST patients with a monitoring coping style experience a higher emotional burden. Additionally, monitors exhibit a greater need for information. Although this need for information could potentially result in fears and concerns, recognising it may also create an opening for tailored communication and information.