Abstract
Background
Tumor necrosis has been identified as an independent adverse prognostic factor in various human malignancies; however, its prognostic value in gastric gastrointestinal stromal tumors (gGISTs) remains uncertain. This study aimed to investigate the association between tumor necrosis and overall survival (OS) in patients with gGIST who underwent radical surgical resection.
Methods
In this retrospective cohort study, clinical and pathological data from 1,463 patients with gGIST were analyzed. The association between tumor necrosis and OS was assessed using univariate analysis with log-rank tests and multivariate analysis with Cox proportional hazards regression models.
Results
Tumor necrosis was observed in 238 patients (16.3%) and was significantly associated with tumor location (P=0.044), tumor size (P<0.001), mitotic count (P<0.001), and modified National Institutes of Health (NIH) risk categories (P<0.001). Multivariate analysis confirmed tumor necrosis as an independent unfavorable predictor of OS (P=0.02). Incorporating tumor necrosis into the modified NIH risk classification enabled the stratification of patients into five prognostically distinct groups (P<0.001).
Conclusions
Tumor necrosis was identified as an independent adverse prognostic factor in gGIST, and its integration into the modified NIH classification improves prognostic accuracy, supporting a refined risk stratification system for enhanced clinical decision-making and patient management.
Keywords: Tumor necrosis, gastric gastrointestinal stromal tumors (gGISTs), prognosis, risk stratification
Highlight box.
Key findings
• Tumor necrosis should be considered as a potential prognostic marker in gastrointestinal stromal tumors (GIST).
• Histopathological evaluation of tumor necrosis should be routinely included in GIST assessment protocols.
What is known and what is new?
• Previous prognostic models mainly relied on tumor size, mitotic rate, and location.
• The current recommendation includes tumor necrosis as an additional, independent prognostic factor.
What is the implication, and what should change now?
• Incorporating tumor necrosis into risk stratification may improve the accuracy of prognosis prediction in GIST patients.
• Clinical guidelines should consider adding tumor necrosis to existing risk assessment systems to guide postoperative surveillance and adjuvant therapy decisions.
Introduction
Gastrointestinal stromal tumors (GISTs) represent approximately only about 1% of all gastrointestinal (GI) malignancies, yet, they are the most common mesenchymal tumors of the GI tract, with the stomach being the most frequent site of occurrence (60%) (1-3), with radical excision remaining the gold-standard treatment for resectable gastric GISTs (gGISTs) (4,5). The accurate assessment of clinical prognosis is crucial for the effective management of gGISTs. Several studies on mesenchymal tumors have identified various prognostic factors for GISTs (6,7). Based on these findings, the National Institutes of Health (NIH) classification, modified NIH classification, and Armed Forces Institute of Pathology (AFIP) classification (8-10) have established prognostic criteria for the risk stratification of GISTs, which incorporate mitotic activity and tumor size as key prognostic variables, with the main difference being that the tumor site is included as a prognostic factor in the modified NIH and AFIP classifications but not in the original NIH criteria.
Despite these established risk classifications, clinical outcomes often differ among patients within the same risk category, underscoring the need for additional prognostic markers, which would be valuable not only for optimizing the frequency and intensity of postoperative surveillance but, more importantly, for improving the selection of candidates for potential adjuvant therapy.
Tumor necrosis, which reflects intratumoral hypoxia and may indicate a more aggressive tumor phenotype, has been proposed as an independent prognostic marker in several malignancies, including colorectal, pancreatic, renal, breast, and lung cancers (11-13). However, its prognostic significance in gastric gGISTs remains controversial (14,15). To address this, we conducted a multicenter, large-cohort retrospective study to evaluate the prognostic relevance of tumor necrosis in gGIST patients who underwent radical surgical resection. We present this article in accordance with the REMARK reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-89/rc).
Methods
Ethical approval
The study was approved by the Ethics Committee of Guangdong Provincial People’s Hospital (approval No. KY2025-003-02) and was conducted in accordance with the principles outlined in the Declaration of Helsinki and its subsequent amendments. All the other nine participating institutions were informed of the study and provided consent to participate. All included patients provided both oral and written informed consent.
Patient enrollment and data collection
The data for this retrospective analysis were collected from ten medical centers in China: Guangdong General Hospital; Sun Yat-sen University Cancer Center; Union Hospital, Tongji Medical College of Huazhong University of Science and Technology; Nanfang Hospital, Southern Medical University; Fujian Medical University Union Hospital; Fudan University Shanghai Cancer Center; West China Hospital, Sichuan University; Peking University Cancer Hospital and Institute; People’s Liberation Army (PLA) Cancer Center, 81st Hospital of PLA; and the Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute.
A total of 1,463 consecutive patients with gGIST who underwent radical excision between January 1998 and January 2016 were included in the analysis. Patients with synchronous malignancies, incomplete clinical data, or those who received neoadjuvant imatinib or chemoradiotherapy were excluded.
All clinical data were collected using standardized case report forms (CRFs) across all the participating institutions. Follow-up information was obtained through outpatient visits or telephone interviews and was subsequently integrated into a centralized multicenter database for gGIST.
Pathological evaluation and tumor necrosis definition
Clinicopathological data, including patient age, sex, tumor necrosis, tumor size, tumor site, and mitotic count, were obtained from medical records and pathology reports. Tumor necrosis was defined as the presence of microscopic coagulative necrosis without accompanying inflammation or fibrosis, irrespective of the extent of necrosis relative to the tumor mass; gross necrosis was excluded from this definition (16). Pathologists recorded tumor necrosis as either present or absent based on histological evaluation of all available tumor blocks. The presence of necrosis was defined as any identifiable microscopic coagulative necrosis, regardless of its size or frequency (Figure 1).
Figure 1.
Representative histological images of coagulative tumor necrosis in GISTs. (A) Low-power view (magnification ×100; HE staining); (B) high-power view (magnification ×400; HE staining). GIST, gastrointestinal stromal tumor; HE, hematoxylin and eosin.
Follow-up and surveillance protocol
Routine follow-up consisted of physical examinations, laboratory tests, chest radiography, abdominopelvic ultrasonography, and computed tomography (CT). Postoperative follow-up schedules included clinical and laboratory examinations every 3 months for the first 2 years, every 6 months between the third and fifth years, and annually thereafter until at least 5 years post-surgery. Overall survival (OS) was defined as the time from the date of surgery to either death or the last follow-up.
Statistical analysis
Statistical analyses were conducted using the SPSS software (version 16.0, SPSS, Chicago, IL, USA). The χ2 test was employed to assess the association between tumor necrosis and other clinicopathological variables. Survival analysis was performed using the Kaplan-Meier method, and differences in survival between groups were compared using the log-rank test. Univariate and multivariate analyses were conducted using Cox proportional hazards regression models to identify independent prognostic factors associated with OS. All statistical tests were two-sided, with statistical significance set at P<0.05.
To compare the modified NIH classification with the newly proposed classification (which incorporates tumor necrosis), we used the likelihood ratio χ2 test within the context of Cox regression models to assess the homogeneity of the two models. The discriminatory power and monotonicity of the new classification system were evaluated using the linear trend χ2 test. Additionally, to evaluate potential bias arising from the differing number of risk groups between the two systems, the Akaike information criterion (AIC) was used, calculated as AIC = −2 × log(likelihood) + 2 × number of model parameters, with a lower AIC indicating a superior model for predicting outcomes (17-19).
Results
Patients’ characteristics
A total of 1,463 patients diagnosed with gGIST were included in this study. The clinicopathological characteristics of the cohort are summarized in Table 1. The study population comprised 732 males (50%) and 731 females (50%), with a male-to-female ratio of 1:1. The median age of the cohort was 59 years (range, 20–95 years), and the median tumor size was 4.0 cm (range, 1–29 cm).
Table 1. Relationship between tumor necrosis and clinicopathological characteristics/surgical outcomes.
| Variables | Total (n=1,463) | Tumor necrosis | P value | |
|---|---|---|---|---|
| Presence (n=238) | Absence (n=1,225) | |||
| Age (years) | 0.14 | |||
| <60 | 768 (52.5) | 109 (14.2) | 659 (85.8) | |
| ≥60 | 695 (47.5) | 129 (18.6) | 566 (81.4) | |
| Gender | 0.96 | |||
| Male | 732 (50.0) | 119 (16.3) | 613 (83.7) | |
| Female | 731 (50.0) | 119 (16.2) | 612 (83.8) | |
| Tumor location | 0.044 | |||
| Gastric cardia | 94 (6.4) | 2 (2.1) | 92 (97.9) | |
| Gastric fundus | 570 (39.0) | 114 (20.0) | 456 (80.0) | |
| Gastric body | 635 (43.4) | 102 (16.1) | 533 (83.9) | |
| Gastric antrum | 164 (11.2) | 20 (12.2) | 144 (87.8) | |
| Tumor size (cm) | <0.001 | |||
| ≤2 | 339 (23.2) | 5 (1.5) | 334 (98.5) | |
| >2, ≤5 | 586 (40.0) | 50 (8.5) | 536 (91.5) | |
| >5, ≤10 | 389 (26.6) | 109 (28.0) | 280 (72.0) | |
| >10 | 149 (10.2) | 74 (49.7) | 75 (50.3) | |
| Mitotic count (HPF) | <0.001 | |||
| ≤5/50 | 1,118 (76.4) | 121 (10.8) | 997 (89.2) | |
| >5, ≤10/50 | 219 (15.0) | 67 (30.6) | 152 (69.4) | |
| >10/50 | 126 (8.6) | 50 (39.7) | 76 (60.3) | |
| NIH risk categories | <0.001 | |||
| Very low-risk | 310 (21.2) | 3 (1.0) | 307 (99.0) | |
| Low-risk | 456 (31.2) | 36 (7.9) | 420 (92.1) | |
| Intermediate-risk | 344 (23.5) | 67 (19.5) | 277 (80.5) | |
| High-risk | 353 (24.1) | 132 (37.4) | 221 (62.6) | |
Data are presented as n (%). HPF, high-power field; NIH, National Institutes of Health.
Association between tumor necrosis and clinicopathological features
Tumor necrosis, which was observed in 238 patients (16.3%), was significantly correlated with tumor location (P=0.044), tumor size (P<0.001), mitotic count (P<0.001), and the modified NIH classification (P<0.001) (Table 1).
Prognostic significance of histopathological variables
Univariate analysis demonstrated that tumor necrosis, tumor size, and mitotic count were significantly associated with OS. To control for potential confounding factors, a multivariate Cox proportional hazards regression analysis was conducted, incorporating tumor necrosis alongside other relevant prognostic variables (Table 2). The results identified tumor necrosis [hazard ratio (HR), 1.986; 95% confidence interval (CI): 1.112–3.544; P=0.02], tumor size (HR, 1.800; 95% CI: 1.282–2.527; P=0.001), and mitotic count (HR, 2.189; 95% CI: 1.560–3.071; P<0.001) as independent prognostic factors for OS.
Table 2. Univariate and multivariate analyses of 1,463 gGIST patients for OS.
| Variables | Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|---|
| HR (95% CI) | P value | HR (95% CI) | P value | ||
| Age | 0.614 (0.371–1.014) | 0.057 | |||
| Gender | 0.776 (0.484–1.245) | 0.29 | |||
| Tumor location | 1.222 (0.832–1.795) | 0.31 | |||
| Tumor size | 2.377 (1.828–3.092) | <0.001 | 1.800 (1.282–2.527) | 0.001 | |
| Mitotic count | 2.747 (2.094–3.604) | <0.001 | 2.189 (1.560–3.071) | <0.001 | |
| Tumor necrosis | 0.260 (0.152–0.445) | <0.001 | 1.986 (1.112–3.544) | 0.02 | |
| NIH risk categories | 3.433 (2.470–4.771) | <0.001 | |||
CI, confidence interval; gGIST, gastric gastrointestinal stromal tumor; HR, hazard ratio; NIH, National Institutes of Health; OS, overall survival.
Stratification by the modified NIH classification and tumor necrosis
When stratified according to the modified NIH classification, the presence of tumor necrosis was identified in 1.0%, 7.9%, 19.5%, and 37.4% of patients with very low-, low-, intermediate-, and high-risk tumors, respectively. Importantly, the prognostic significance of tumor necrosis was retained only within the high-risk group (P=0.004; Table 3, Figure 2), but not among patients classified as very low-, low-, or intermediate-risk (P=0.61 and P=0.46, respectively; Table 3). Within the high-risk subgroup, patients without tumor necrosis exhibited a significantly higher 5-year OS rate compared to those with tumor necrosis (84.9% vs. 55.3%, respectively; P=0.004; Table 3).
Table 3. Relationship between NIH risk categories and tumor necrosis.
| NIH risk categories | Tumor necrosis | No. of patients (%) | Five-year survival rate (%) | P value |
|---|---|---|---|---|
| Very low-risk | Presence | 3 (1.0) | – | – |
| Absence | 307 (99.0) | 100.0 | ||
| Low-risk | Presence | 36 (7.9) | 100.0 | 0.61 |
| Absence | 420 (92.1) | 98.7 | ||
| Intermediate-risk | Presence | 67 (19.5) | 97.2 | 0.46 |
| Absence | 277 (80.5) | 93.5 | ||
| High-risk | Presence | 132 (37.4) | 55.3 | 0.004 |
| Absence | 221 (62.6) | 84.9 |
NIH, National Institutes of Health; No., number.
Figure 2.
Kaplan-Meier survival curves comparing risk stratification systems in gGIST patients. (A) Survival curves based on the modified NIH classification, stratifying patients into four risk groups. (B) Survival curves based on the proposed classification incorporating tumor necrosis, stratifying patients into five prognostically distinct groups. gGIST, gastric gastrointestinal stromal tumor; NIH, National Institutes of Health.
Survival analysis based on modified NIH classification and tumor necrosis
Survival analysis revealed that the 5-year OS rates for patients stratified by the modified NIH classification were 100.0%, 97.9%, 91.2%, and 78.7% for the very low-, low-, intermediate-, and high-risk groups, respectively (P<0.001; Figure 2).
Given the prognostic impact of tumor necrosis within the high-risk group, this category was further subdivided into high-risk and extremely high-risk subgroups. Accordingly, the entire cohort was reclassified into five groups based on the modified NIH classification combined with tumor necrosis status: very low-, low-, intermediate-, high-, and extremely high-risk. The corresponding 5-year OS rates were 100.0%, 97.9%, 91.2%, 85.9%, and 55.3%, respectively (P<0.001; Figure 2).
Comparison of the modified NIH classification and our proposed classification
The prognostic performance of the modified NIH classification and the proposed classification, integrating tumor necrosis into the modified NIH system, was evaluated using the linear trend χ2 test, likelihood ratio χ2 test, and AIC. Compared with the original model, the proposed classification demonstrated superior homogeneity, enhanced discriminatory power, and improved monotonicity of risk gradients (Table 4), indicating better prognostic stratification.
Table 4. Comparison of the performance of the modified NIH classification and the new classification (modified NIH classification plus tumor necrosis).
| Risk classification | Figure | Subgroups | Linear trend χ2 | Likelihood ratio χ2 | AIC |
|---|---|---|---|---|---|
| Modified NIH classification | Figure 1A | Very low-, low-, intermediate-, and high-risk | 37.55 | 86.17 | 825.8 |
| New classification | Figure 1B | Very low-, low-, intermediate-, high-, and very high-risk | 53.73 | 96.8 | 817.1 |
AIC, Akaike information criterion; NIH, National Institutes of Health.
Discussion
GISTs originating from the stomach account for approximately 50% to 60% of all GIST cases, making gGISTs the most common subtype compared to those arising in other organs, such as the small intestine, colorectum, and esophagus (20). Currently, the diagnosis and management of gGISTs rely on three primary risk-prediction classifications: the NIH classification, the modified NIH classification, and the AFIP classification. These systems use parameters such as tumor size, mitotic index, tumor location, and tumor rupture to stratify patients into very low-, low-, intermediate-, or high-risk categories (21,22). This risk stratification is crucial, not only for identifying high-risk patients with a higher likelihood of disease recurrence, but also for guiding decisions regarding adjuvant treatments following surgery (23).
Despite the utility of current classification systems, prognostic variability persists among patients within the same risk category, particularly among those classified as high-risk. For example, the SSGXVIII cohort study demonstrated that 3 years of adjuvant imatinib therapy significantly improved survival outcomes compared to 1 year of treatment in high-risk GIST patients. However, analysis of the survival curves from the SSGXVIII trial revealed that some patients experienced early recurrence after discontinuation of therapy, regardless of whether they had received 1 or 3 years of adjuvant treatment (24). These findings suggest the existence of a subset of patients within the high-risk category who may be more appropriately classified as “very high risk”, but are not adequately identified by current risk stratification models. In light of these observations, there is an increasing need for a more refined classification system capable of more precisely identifying these patients. Such a system could improve prognostic accuracy and support the development of individualized treatment strategies, particularly in selecting candidates for extended or alternative therapeutic interventions.
Tumor necrosis has been proposed as an independent prognostic marker in several malignancies, including colorectal cancer (13), as well as in renal, breast, and lung carcinoma, where it is generally associated with poor prognosis (11-13). In GISTs, attempts have been made to incorporate tumor necrosis into existing risk classifications. A subgroup analysis within high-risk GIST patients suggested that the presence of tumor necrosis might be linked to a worse prognosis (24). However, the role of tumor necrosis in GIST remains controversial, with differing results across studies (16). Moreover, there is a lack of research addressing the stratification of high-risk GIST patients based on the presence of tumor necrosis.
In our study, the incidence of tumor necrosis among gGIST patients was 16.3%, consistent with findings from other published studies (14,25,26). The association between tumor necrosis and prognosis remains contentious. Some researchers hypothesize that tumor necrosis may result from rapid tumor proliferation, where the tumor outgrows its blood supply (27), while others suggest that it could occur in regions of high microvessel density (28). Additionally, the host immune response may also contribute to the development of tumor necrosis (29). In our cohort, the incidence of tumor necrosis increased progressively with higher risk stratification, suggesting a potential relationship between tumor necrosis and prognosis. Correlation analyses revealed significant associations between tumor necrosis and factors such as tumor size and mitotic index, further supporting its prognostic relevance. Both univariate and multivariate analyses identified tumor necrosis as an independent prognostic factor for OS. Furthermore, in subgroup analyses, patients with pathological tumor necrosis within the high-risk category were found to have a worse prognosis. Based on these findings, we propose that tumor necrosis could be a valuable addition to current risk stratification models. Upon further validation, it demonstrated potential as a prognostic marker for identifying very high-risk patients, enabling more accurate outcome prediction and facilitating the selection of appropriate adjuvant therapeutic strategies.
Recent evidence suggests that tumor necrosis may not only be a marker of aggressive biological behavior but also a structural risk factor for tumor rupture. A study by Liu et al. (30) using multivariate logistic regression analysis reported that necrosis was significantly associated with rupture risk in gGISTs [odds ratio (OR) =18.75; 95% CI: 3.40–103.34; P<0.01], together with other imaging features such as tumor diameter ≥10 cm, irregular contour, and gas-liquid interface. These findings support the hypothesis that necrotic degeneration may compromise the mechanical stability of the tumor, thereby increasing its susceptibility to rupture. Since rupture is independently linked to adverse outcomes, the association between necrosis and rupture further reinforces the dual prognostic value of necrosis in gGISTs, both as a marker of poor survival and a predictor of rupture-related risk, which hence underscores the potential of necrosis as a radiologic or histopathologic surrogate for refining preoperative risk stratification.
Biological insights may further shed light on the association between tumor necrosis and adverse prognosis in gGISTs. Tumor necrosis typically arises in rapidly proliferating tumors as a consequence of inadequate vascularization, leading to the development of a hypoxic microenvironment. This hypoxia stabilizes hypoxia-inducible factors (HIFs), particularly HIF-1α, which then activate the transcription of genes involved in angiogenesis [e.g., vascular endothelial growth factor (VEGF)], epithelial-mesenchymal transition, glucose metabolism, and anti-apoptotic signaling pathways, all of which contribute to increased tumor aggressiveness and resistance to therapy (31,32). In parallel, necrotic regions release damage-associated molecular patterns (DAMPs), interleukin (IL)-6, and tumor necrosis factor (TNF)-α, which recruit tumor-associated macrophages and neutrophils, thereby promoting a proinflammatory tumor microenvironment that enhances invasive and metastatic behavior (33,34). Moreover, the persistent hypoxic and necrotic conditions exert selective pressure on tumor cells, facilitating clonal evolution and the emergence of subpopulations with improved survival, metastatic capabilities, and resistance to treatment (35). Together, these interrelated mechanisms may account for the poorer clinical outcomes observed in gGIST patients exhibiting tumor necrosis.
Furthermore, patients in the cohort were initially classified into four groups according to the modified NIH risk stratification criteria: very low-, low-, intermediate-, and high-risk. We then introduced a revised classification system by incorporating tumor necrosis into the modified NIH criteria, resulting in five distinct categories: very low-, low-, intermediate-, high-, and very high-risk groups. According to current guidelines based on the modified NIH classification, intermediate-risk patients are generally recommended to receive 1 year of adjuvant imatinib mesylate following resection of localized primary GISTs, while high-risk patients are advised to undergo 3 years of therapy. However, findings from the SSGXVIII study indicated that even 3 years of adjuvant imatinib may be insufficient for some high-risk patients, highlighting the need for a more individualized treatment approach. Based on our revised stratification system, we propose that patients classified as very high-risk may benefit from an extended duration of adjuvant therapy to achieve improved clinical outcomes (36).
There were several limitations that should be addressed in this study. First, OS was used as the primary endpoint, and in future studies, additional survival metrics, such as disease-free survival, could provide a more comprehensive understanding of the treatment outcomes. Second, while many studies have classified tumor necrosis as a degree of extent (e.g., extensive or focal), we chose to categorize it as simply present or absent. We believe this binary classification could be more practical for clinical use, particularly in settings where advanced imaging techniques or pathological assessments may not be readily available. Lastly, molecular data such as the mutational status of KIT and PDGFRA, which are known to influence GIST behavior and response to therapy, were not collected in this retrospective study. This was primarily due to the variability in molecular testing availability across participating centers during the study period and the study’s focus on evaluating pathological tumor necrosis as a prognostic marker.
Conclusions
In conclusion, our findings indicate that tumor necrosis is an independent predictor of reduced OS in patients with gGISTs. Among high-risk patients, the presence of tumor necrosis was associated with significantly poorer prognosis compared to those without necrosis. By incorporating tumor necrosis into the modified NIH classification, we established a revised risk stratification system that delineates five prognostically distinct groups and demonstrates superior predictive performance compared to the original model. Nevertheless, further validation using larger datasets or prospective clinical studies is required to confirm its applicability in routine clinical practice. Overall, tumor necrosis represents a simple, reproducible, and effective prognostic marker for postoperative outcome prediction in gGIST patients.
Supplementary
The article’s supplementary files as
Acknowledgments
None.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was approved by the Ethics Committee of Guangdong Provincial People’s Hospital (approval No. KY2025-003-02) and was conducted in accordance with the principles outlined in the Declaration of Helsinki and its subsequent amendments. All the other nine participating institutions were informed of the study and provided consent to participate. All included patients provided both oral and written informed consent.
Footnotes
Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-89/rc
Funding: This study was supported by the National Key Clinical Specialty Construction Project [2021–2024] (No. 2022YW030009) and the Beijing Xisike Clinical Oncology Research Foundation (No. Y-HR2022QN-0383).
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-89/coif). The authors have no conflicts of interest to declare.
Data Sharing Statement
Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-89/dss
References
- 1.Alvarez CS, Piazuelo MB, Fleitas-Kanonnikoff T, et al. Incidence and Survival Outcomes of Gastrointestinal Stromal Tumors. JAMA Netw Open 2024;7:e2428828. 10.1001/jamanetworkopen.2024.28828 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Burch J, Ahmad I. Gastrointestinal Stromal Tumors. In: StatPearls. Treasure Island: StatPearls Publishing; 2022. [PubMed] [Google Scholar]
- 3.Li J, Khajoueinejad N, Sarpel U. Surgical Management of Gastric Gastrointestinal Stromal Tumors. Surg Clin North Am 2025;105:109-24. 10.1016/j.suc.2024.06.009 [DOI] [PubMed] [Google Scholar]
- 4.Maeda C, Yamaoka Y, Shiomi A, et al. Short-term and long-term outcomes after robotic radical surgery for rectal gastrointestinal stromal tumor. BMC Surg 2024;24:141. 10.1186/s12893-024-02434-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Thibaut F, Veziant J, Warlaumont M, et al. Prognostic impact of positive microscopic margins (R1 resection) in patients with GIST (gastrointestinal stromal tumours): Results of a multicenter European study. Eur J Surg Oncol 2024;50:108310. 10.1016/j.ejso.2024.108310 [DOI] [PubMed] [Google Scholar]
- 6.Li J, Huang Z, Zhou H, et al. Survival outcomes and prognostic factors of advanced gastrointestinal stromal tumors: in the era of multiple tyrosine kinase inhibitors. J Gastrointest Oncol 2024;15:931-45. 10.21037/jgo-24-63 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Teranishi R, Takahashi T, Sato S, et al. The impact of contour maps on estimating the risk of gastrointestinal stromal tumor recurrence: indications for adjuvant therapy: an analysis of the Kinki GIST registry. Gastric Cancer 2024;27:355-65. 10.1007/s10120-023-01444-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Wang A, Niu Q, Chen Y, et al. Efficacy and safety of endoscopic subserosal dissection treatment for gastrointetinal submucosal tumors in the upper gastrointestinal tract. BMC Surg 2024;24:301. 10.1186/s12893-024-02592-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Toulmonde M, Dinart D, Brahmi M, et al. Evolution of Patterns of Care and Outcomes in the Real-Life Setting for Patients with Metastatic GIST Treated in Three French Expert Centers over Three Decades. Cancers (Basel) 2023;15:4306. 10.3390/cancers15174306 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Nguyen Cuong P, Thanh Xuan N, Xuan Tien T, et al. Histopathological Characteristics of Gastrointestinal Stromal Tumors in a Cohort of Vietnamese Patients. Clin Pathol 2020;13:2632010X20972405. [DOI] [PMC free article] [PubMed]
- 11.Luconi M, Cantini G, van Leeuwaarde RS, et al. Prognostic Value of Microscopic Tumor Necrosis in Adrenal Cortical Carcinoma. Endocr Pathol 2023;34:224-33. 10.1007/s12022-023-09760-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Tancoš V, Farkašová A, Kviatkovská Z, et al. Expression of programmed death-ligand 1 protein in pulmonary squamous cell carcinoma correlates with tumour necrosis but not with tumour differentiation. J Clin Pathol 2022;75:373-8. 10.1136/jclinpath-2020-207171 [DOI] [PubMed] [Google Scholar]
- 13.Kastinen M, Sirniö P, Elomaa H, et al. Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer. Am J Surg Pathol 2024;48:1284-92. 10.1097/PAS.0000000000002286 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Sun Q, Wu J, Wang G, et al. Investigation of unfavorable prognostic factors for survival in Chinese patients with gastric gastrointestinal stromal tumors. Transl Cancer Res 2024;13:6782-92. 10.21037/tcr-24-1042 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Liang SQ, Cui YT, Hu GB, et al. Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors. J Gastrointest Surg 2025;29:101864. 10.1016/j.gassur.2024.10.019 [DOI] [PubMed] [Google Scholar]
- 16.Luo X, Chen J, Fang Y, et al. Association between calcification and risk stratification in gastric gastrointestinal stromal tumors. Abdom Radiol (NY) 2025;50:579-88. 10.1007/s00261-024-04544-w [DOI] [PubMed] [Google Scholar]
- 17.Wu Z, Shang G, Zhang K, et al. A nomogram incorporating treatment data for predicting overall survival in gastroenteropancreatic neuroendocrine tumors: a population-based cohort study. Int J Surg 2024;110:2178-86. 10.1097/JS9.0000000000001080 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Liu Q, Charleston MA, Richards SA, et al. Performance of Akaike Information Criterion and Bayesian Information Criterion in Selecting Partition Models and Mixture Models. Syst Biol 2023;72:92-105. 10.1093/sysbio/syac081 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Fang C, Wang W, Deng JY, et al. Proposal and validation of a modified staging system to improve the prognosis predictive performance of the 8th AJCC/UICC pTNM staging system for gastric adenocarcinoma: a multicenter study with external validation. Cancer Commun (Lond) 2018;38:67. 10.1186/s40880-018-0337-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Hu S, Alpert L, Cates JMM, et al. Gastrointestinal stromal tumors (GISTs) arising in uncommon locations: clinicopathologic features and risk assessment of esophageal, colonic, and appendiceal GISTs. Mod Pathol 2022;35:554-63. 10.1038/s41379-021-00949-w [DOI] [PubMed] [Google Scholar]
- 21.Do IG, Jung KU, Koo DH, et al. Clinicopathological characteristics and outcomes of gastrointestinal stromal tumors with high progranulin expression. PLoS One 2021;16:e0245153. 10.1371/journal.pone.0245153 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Zhaojun X, Xiaobin C, Pengfei L, et al. Analysis of risk factors and prognostic factors for gastrointestinal stromal tumors with gastrointestinal hemorrhage: Based on propensity score matching method. Surgery 2023;173:383-91. 10.1016/j.surg.2022.10.001 [DOI] [PubMed] [Google Scholar]
- 23.Rutkowski P. Why We Still Need the Better Risk Classification for GIST. Ann Surg Oncol 2021;28:2425-7. 10.1245/s10434-021-09620-9 [DOI] [PubMed] [Google Scholar]
- 24.Bang YH, Ryu MH, Kim HD, et al. Clinical outcomes and prognostic factors for patients with high-risk gastrointestinal stromal tumors treated with 3-year adjuvant imatinib. Int J Cancer 2022;151:1770-7. 10.1002/ijc.34157 [DOI] [PubMed] [Google Scholar]
- 25.Zhao L, Cao G, Shi Z, et al. Preoperative differentiation of gastric schwannomas and gastrointestinal stromal tumors based on computed tomography: a retrospective multicenter observational study. Front Oncol 2024;14:1344150. 10.3389/fonc.2024.1344150 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Yi M, Xia L, Zhou Y, et al. Prognostic value of tumor necrosis in gastrointestinal stromal tumor: A meta-analysis. Medicine (Baltimore) 2019;98:e15338. 10.1097/MD.0000000000015338 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Tyler R, Davies E, Tan D, et al. Tumor necrosis is significantly associated with reduced recurrence-free survival after curative resection of gastrointestinal stromal tumors. J Surg Oncol 2021;123:432-8. 10.1002/jso.26294 [DOI] [PubMed] [Google Scholar]
- 28.Marie MA, Sanderlin EJ, Hoffman AP, et al. GPR4 Knockout Attenuates Intestinal Inflammation and Forestalls the Development of Colitis-Associated Colorectal Cancer in Murine Models. Cancers (Basel) 2023;15:4974. 10.3390/cancers15204974 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hänggi K, Ruffell B. Cell death, therapeutics, and the immune response in cancer. Trends Cancer 2023;9:381-96. 10.1016/j.trecan.2023.02.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Liu JZ, Jia ZW, Sun LL. Factors associated with gastrointestinal stromal tumor rupture and pathological risk: A single-center retrospective study. World J Radiol 2023;15:350-8. 10.4329/wjr.v15.i12.350 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Zhao Y, Xing C, Deng Y, et al. HIF-1α signaling: Essential roles in tumorigenesis and implications in targeted therapies. Genes Dis 2024;11:234-51. 10.1016/j.gendis.2023.02.039 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Rahman MA, Jalouli M, Bhajan SK, et al. The Role of Hypoxia-Inducible Factor-1α (HIF-1α) in the Progression of Ovarian Cancer: Perspectives on Female Infertility. Cells 2025;14:437. 10.3390/cells14060437 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Wang M, Chen S, He X, et al. Targeting inflammation as cancer therapy. J Hematol Oncol 2024;17:13. 10.1186/s13045-024-01528-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Lei ZN, Tian Q, Teng QX, et al. Understanding and targeting resistance mechanisms in cancer. MedComm (2020) 2023;4:e265. [DOI] [PMC free article] [PubMed]
- 35.Zhang M, Zhang Y, Ding Y, et al. Regulating the Expression of HIF-1α or lncRNA: Potential Directions for Cancer Therapy. Cells 2022;11:2811. 10.3390/cells11182811 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Nishida T, Sato S, Ozaka M, et al. Long-term adjuvant therapy for high-risk gastrointestinal stromal tumors in the real world. Gastric Cancer 2022;25:956-65. 10.1007/s10120-022-01310-z [DOI] [PubMed] [Google Scholar]