Gastrointestinal stromal tumor (GIST) is the most common soft tissue sarcoma of the gastrointestinal tract. With the increasing awareness of this disease, the reported incidence of GIST has been on the rise in recent years. The annual incidence of GIST has increased from 0.55 per 100,000 in 2001 to 0.78 per 100,000 in 2011 in the most recent epidemiological studies in the United States, and is as high as 1.28 per 100,000 in domestic epidemiological studies. liver or pelvic metastases. Surgical resection is the most fundamental treatment for GIST, and adjuvant therapy with the small molecule-targeted drug imatinib for tumors with high recurrence potential after surgical resection can significantly reduce tumor recurrence or metastasis. Currently, the concept of adjuvant therapy after surgery for high-risk GIST has been widely accepted, and more and more GIST patients are treated with imatinib. However, have some of these patients actually been cured by surgery alone? Are there other patients with a potential risk of recurrence who are missing out on the best time to receive adjuvant therapy? These questions all point to a key clinical challenge: how to accurately determine the risk of tumor recurrence. In response to these clinical questions, several GIST recurrence risk assessment systems have been proposed and applied in clinical practice. The earliest accepted and widely used GIST risk assessment method is the National Institutes of Health (NIH) risk stratification criteria (NIH criteria) proposed by Fletcher et al. in 2002, which is based on two indicators of GIST biology: maximum tumor diameter and nuclear split count. After the NIH criteria were proposed, based on the clinical observation that gastric GIST is less aggressive than intestinal GIST, Miettinen et al. proposed another risk stratification criterion based on the follow-up data of large GIST cases, namely the Armed Forces Institute of Pathology (AFIP). Forces Institute of Pathology (AFIP) criteria (AFIP criteria), this stratification criterion introduced the effect of different tumor sites on the risk of recurrence and metastasis in GIST patients and predicted the likelihood of recurrence separately in terms of percentages (%) for GISTs with different tumor sites, with different sizes and different nuclear schwannoma counts. Although the introduction of the parameter of tumor site has improved the accuracy of risk stratification, the AFIP criteria are less intuitive than the NIH criteria, thus limiting its wide application to some extent. In response to the shortcomings of the two aforementioned criteria, Joensuu proposed a modified NIH criterion in 2008, which introduced two parameters of tumor site and tumor rupture based on the original NIH criterion, which greatly improved the accuracy of the risk of GIST recurrence and became a more practical stratification criterion. Subsequently, new methods of GIST risk stratification and grading were also proposed, such as the nomogram and the TNM staging method of the American Joint Committee on Cancer (AJCC). The former uses multiple clinicopathological parameters as continuous variable parameters to directly predict survival in the form of columnar line graphs; the latter integrates the risk grading of GIST into the TNM staging system of cancer based on AFIP criteria. However, in terms of practicality, these new risk assessment methods do not have significant advantages over the modified NIH criteria, so they have not been widely accepted and applied. Recently, Joensuu, who proposed the modified NIH criteria, suggested, based on a cohort study of a large population, that while the modified NIH criteria could select patients in the GIST population who needed adjuvant therapy, a nonlinear model of prognostic heat map could be used to more accurately predict the prognosis of each individual patient. However, not all biological behavior and clinical regression of GIST can be explained by these aforementioned risk assessment methods; for example, a proportion of very small GISTs can rapidly progress and develop liver metastases, and there is no shortage of large GISTs (high risk) that remain disease-free for a long time even without postoperative adjuvant therapy patients. In the era of targeted drug therapy represented by imatinib, clinicians need to develop treatment strategies that prevent both over- and under-treatment, while taking into account other factors such as adverse drug reactions and health economics. Although the existing GIST risk assessment methods provide useful clues for clinicians to accomplish this task, there seems to be room for improvement. Although there are various methods for GIST risk assessment, most of them are based on parameters such as maximum tumor diameter, nuclear split count, and tumor site. To improve the existing GIST risk assessment methods, there are only two aspects: first, to introduce new parameters for risk assessment; second, to improve the assessment methods of existing parameters. It is encouraging to note that a number of studies have been conducted and some results have been obtained for these two levels of work. On the basis of the existing risk classification, Hou et al. combined the common nature of malignant tumor invasion and metastasis and proposed new pathomorphological indicators for assessing the risk of GIST, namely, two visual dissemination indicators (liver metastasis and peritoneal dissemination), five microscopic indicators (lymph node metastasis, vascular infiltration, fatty infiltration, nerve infiltration, and mucosal infiltration). The remaining GISTs were classified as low-, moderate-, and highly malignant GISTs according to the number of the above-mentioned parameters. The risk classification based on the above 12 pathomorphological parameters was found to be more accurate in predicting the prognosis of GIST than the NIH and AFIP schemes. Compared with other grading criteria, this risk assessment method dilutes the influence of tumor size and tumor site on the risk of GIST recurrence, and brings the risk assessment of GIST back to the level of pure pathomorphological observation, which has the advantage of being more objective and accurate. surgeons. Therefore, the practicality of this grading method has yet to be further validated by clinical application. The author’s research team has also carried out some work on the pathomorphology of GIST in recent years. It has been found that nuclear schwannoma count and plasma membrane invasion are independent risk factors for recurrence-free survival in GIST patients after surgery. Using plasma membrane invasion as a pathomorphological parameter allows for subgroup classification of high-risk GISTs, and GISTs with plasma membrane invasion showed a worse clinical prognosis in both the test cohort (test cohort, n=212) and validation cohort (validation cohort, n=158), suggesting that this index can be used to improve the traditional risk classification methods accuracy. Foreign scholars have also carried out work on the use of GIST pathomorphological indicators to assess the risk of GIST recurrence. For example, Yamamoto et al. proposed that blood vessel invasion (BVI) is a factor closely associated with liver metastasis in GIST, and liver metastasis occurs in approximately 80% of primary limited GIST with detectable BVI. The incidence of liver metastasis is significantly higher in high-risk GISTs with BVI than in BVI-negative GISTs (83% vs. 50%), thus suggesting that high-risk GISTs with BVI can actually be referred to as “very high-risk” GISTs. This parameter can effectively predict the occurrence of liver metastases in GIST and improve the accuracy of traditional risk grading criteria. The application of genotyping in the assessment of GIST risk. c-kit/PDGFRA gene functionally acquired mutation is the driver of GIST development, which has become the consensus and the theoretical basis of GIST targeted therapy. Different genotypes of GIST have completely different drug responses. For example, GISTs with exon 11 of the c-kit gene are the most sensitive to Gleevec treatment, GISTs with exon 9 of the c-kit gene respond second, wild-type GISTs respond worse, and the D842V mutation in exon 18 of the PDGFRA gene is completely resistant to Gleevec. However, does the difference in mutation site and type itself determine the prognosis of GIST? A series of studies have been conducted nationally and internationally to address this question. Lasota et al. showed that GIST with PDGFRA mutations occur mostly in the stomach, and this part of GIST tends to have benign or low-grade malignant biological behavior, although it can develop into larger tumors. More studies have found that GIST with duplication mutations in c-kit gene exon 9 Ala502_Tyr503 and deletion mutations in c-kit gene exon 11 Tyr557_Lys558 have a poor clinical prognosis. The authors examined and analyzed the mutations in nearly 300 GIST cases admitted to their unit in recent years and found that the prognosis of GIST with large fragment deletion mutations (involving ≥3 codons) in exon 11 of the c-kit gene was significantly worse than that with small fragment deletions (involving less than 3 codons), suggesting that the phenotypic characteristics of this gene are an indicator of poor prognosis of GIST. In a recent genetic analysis of GIST in a large sample, Joensuu et al. found that duplicative mutations in exon 11 of the c-kit gene and deletion mutations involving only a single codon were positively correlated indicators of GIST prognosis. The effectiveness of mutational features in assessing the prognosis of patients with GIST was reduced after the introduction of traditional risk assessment indicators such as karyotype count. This suggests that mutational features should not be used in isolation from other prognostic factors to assess the risk of GIST recurrence, but the identification of specific mutation types that predict a benign prognosis (e.g., duplication of exon 11 of the c-kit gene) can often exclude some patients with GIST as an indication for adjuvant therapy. The use of ki-67 in GIST risk assessment An increasing number of studies have confirmed that ki-67 has the highest impact among the three traditional parameters used in GIST risk assessment (maximum tumor diameter, karyotype count, and tumor site). However, what has always troubled clinicians, especially pathologists, is that karyotype counting is a labor-intensive and time-consuming task: the tester needs to observe and count 50 consecutive high magnification views of the hot spots of nuclear division. This results in nuclear split counts often being easily underestimated, a phenomenon that is even more serious in primary care units. More importantly, the traditional karyotype counting technique has poor reproducibility. The reasons for this include: 1. The identification of nuclear division images is highly subjective. The nuclear division images of cells in pre-, mid-, and post-division are morphologically diverse, and some nuclear division images are not easily identified even under high magnification, and observers with different experience may make different counts of nuclear division images in the same high magnification field of view; 2. The selection of nuclear division hot spots may be biased. It is well known that tumor heterogeneity is a universal phenomenon, and the proliferative activity of various parts within the same tumor may be completely different, with some regions often rich in nuclear division images, similar to the tumor’s germinal center, while other parts may have rare nuclear division images. Deviations in the selection of the region to be observed may lead to great differences in karyotype counts, ultimately influencing the GIST risk classification. These problems have led to poor inter-observer reproducibility of the conventional nuclear split count technique and are therefore often criticized. In response to these problems, domestic and international researchers have been trying to find new techniques that can replace karyotype counting for assessing the proliferative activity and risk of recurrence of GIST. The most studied is the ki-67 index, a proliferating cell marker technique based on immunohistochemical staining, in which the nuclei of proliferating cells are stained brown, while the nuclei of non-proliferating cells are not colored, thus eliminating the bias in morphological observation and allowing easier identification of the proliferative activity of cells. The study by S?zütek et al. found that the ki-67 index correlated with the clinicopathological characteristics and prognosis of GIST patients and suggested that the ki-67 index could be used as an alternative to conventional nuclear schizogram counting. Kemmerling et al. examined three hotspot areas in ki-67 immunohistochemically stained sections and found that cell proliferation activity assays using ki-67 staining markers were more accurate in predicting the risk of recurrence and metastasis in GIST patients than traditional H&E stained nuclear schizogram counts. ki-67 assays were performed on 418 GIST specimens by the author’s research team, and by setting We found that ki-67 index >8% can be used as a supplement to the modified NIH classification criteria to define patients with significant adverse prognosis in high-risk GIST, which can help improve the accuracy of the traditional classification criteria and select the population for Gleevec adjuvant therapy. However, some studies have also found that the ki-67 index is not superior to nuclear split count for GIST risk assessment. Moreover, the ki-67 assay has certain shortcomings of its own, such as the selection of hot spot areas and the method of positive cell counting. Therefore, to replace the traditional karyotype count, ki-67 needs to be supported by data from large prospective studies. IV. Other indicators that may be valuable for GIST risk assessment In addition to these previously mentioned parameters, many other indicators have been found to be potentially useful for GIST risk assessment, most of which are in the exploratory stage, such as P53, EGFR, COX2, Pfetin, HER4, etc. Although these indicators have been found to have similar or even better efficacy than traditional risk assessment indicators in scattered single-center studies, their exact clinical application value needs to be confirmed in further studies with large samples, so they will not be discussed here. In summary, the risk assessment method of GIST has undergone several changes, and the modified NIH criteria is the most clinically useful assessment method at present. However, there is still room for improvement of the criteria. Various pathomorphological indicators, gene mutation characteristics and other molecular markers are expected to be enriched into the risk assessment system of GIST in the near future, and under the new situation of individualized tumor treatment, the risk assessment of GIST will be more and more diversified. In the near future, the information provided to clinicians by the new GIST risk assessment method may not only be “high risk or low risk”, but also “whether adjuvant therapy is needed” and “how to perform adjuvant therapy”. “.