Association of tumor budding with clinicopathological features and prognostic value in stage III-IV colorectal cancer

BACKGROUND Tumor budding(TB)has emerged as a promising independent prognostic biomarker in colorectal cancer(CRC).The prognostic role of TB has been extensively studied and currently affects clinical decision making in patients with stage I and II CRC.However,existing prognostic studies on TB in stage III CRC have been confined to small retrospective cohort studies.Consequently,this study investigated the correlation among TB categories,clinicopathological features,and prognosis in stage III-IV CRC to further enhance the precision and individualization of treatment through refined prognostic risk stratification.AIM To analyze the relationship between TB categories and clinicopathological characteristics and assess their prognostic value in stage III-IV CRC to further refine the prognostic risk stratification of stage III-IV CRC.METHODS The clinical data of 547 CRC patients were collected for this retrospective study.Infiltration at the front edge of the tumor buds was counted according to the 2016 International Tumor Budding Consensus Conference guidelines.RESULTS Multivariate Cox proportional hazards regression analysis demonstrated that chemotherapy(P=0.004),clinical stage IV(P<0.001),≥4 regional lymph node metastases(P=0.004),left-sided colonic cancer(P=0.040),and Bd 2-3(P=0.002)were independent prognostic factors in patients with stage III-IV CRC.Moreover,the density of tumor infiltrating lymphocytes was higher in Bd 1 than in Bd 2-3,both in the tumor stroma and its invasive margin.CONCLUSION TB has an independent predictive prognostic value in patients with stage III-IV CRC.It is recommended to complete the TB report of stage III-IV CRC cases in the standardized pathological report to further refine risk stratification.

Prognostic significance of tumor budding,desmoplastic reaction,and lymphocytic infiltration in patients with gastric adenocarcinoma

BACKGROUND Recent studies have shown that the tumor microenvironment significantly influences the behavior of solid tumors.In this context,Accumulated data suggests that pathological evaluation of tumor budding(TB),desmoplastic reaction(DR),and tumor-infiltrating lymphocytes(TILs)may be crucial in determining tumor behavior in the gastrointestinal tract.Regarding gastric adenocarcinoma(GAC),although some results suggest that TB and TILs may be effective in determining the course of the disease,the data do not agree.Moreover,very few studies have investigated the relationship between DR and survival.At present,the associations between tumor TB,DR and TILs in GAC patients have not been determined.AIM To establish the relationships between TB,DR,and TILs in patients with GAC and to assess their influence on prognosis.METHODS Our study group comprised 130 patients diagnosed with GAC.The definition of TB was established based on the International TB Consensus Conference.The DR was categorized into three groups according to the level of tumor stroma maturation.The assessment of TILs was conducted using a semiquantitative approach,employing a cutoff value of 5%.The statistical analysis of the whole group and 100 patients with an intestinal subtype of GAC was performed using SPSS version 27.RESULTS A significant correlation between peritumoral budding(PTB)and intratumoral budding(ITB)was noted(r=0.943).Tumors with high PTBs and ITBs had a greater incidence of immature DRs and low TILs(P<0.01).PTB and ITB were associated with histological subtype,lymph node metastasis(LNM),and stage(P<0.01).ITB,PTB,LNM,DR,and stage were significant risk factors associated with poor prognosis.The multivariate Cox regression analysis identified ITB,PTB,and LNM as independent prognostic variables(P<0.05).In intestinal-type adenocarcinomas,a positive correlation between PTB and ITB was noted(r=0.972).While univariate analysis revealed that LNM,stage,PTB,ITB,and DR were strong parameters for predicting survival(P<0.05),only PTB and ITB were found to be independent prognostic factors(P<0.001).CONCLUSION TB may be a potential prognostic marker in GAC.However,further studies are needed to delineate its role in pathology reporting protocols and the predictive effects of DR and TILs.

Artificial intelligence-based comprehensive analysis of immune-stemness-tumor budding profile to predict survival of patients with pancreatic adenocarcinoma

Objective:Pancreatic ductal adenocarcinoma(PDAC)is an aggressive malignancy.CD8^(+)T cells,cancer stem cells(CSCs),and tumor budding(TB)have been significantly correlated with the outcome of patients with PDAC,but the correlations have been independently reported.In addition,no integrated immune-CSC-TB profile for predicting survival in patients with PDAC has been established.Methods:Multiplexed immunofluorescence and artificial intelligence(AI)-based comprehensive analyses were used for quantification and spatial distribution analysis of CD8^(+)T cells,CD133^(+)CSCs,and TB.In vivo humanized patient-derived xenograft(PDX)models were established.Nomogram analysis,calibration curve,time-dependent receiver operating characteristic curve,and decision curve analyses were performed using R software.Results:The established‘anti-/pro-tumor’models showed that the CD8^(+)T cell/TB,CD8^(+)T cell/CD133^(+)CSC,TB-adjacent CD8^(+)T cell,and CD133^(+)CSC-adjacent CD8^(+)T cell indices were positively associated with survival of patients with PDAC.These findings were validated using PDX-transplanted humanized mouse models.An integrated nomogram-based immune-CSC-TB profile that included the CD8^(+)T cell/TB and CD8^(+)T cell/CD133^(+)CSC indices was established and shown to be superior to the tumor-nodemetastasis stage model in predicting survival of patients with PDAC.Conclusions:‘Anti-/pro-tumor’models and the spatial relationship among CD8^(+)T cells,CSCs,and TB within the tumor microenvironment were investigated.Novel strategies to predict the prognosis of patients with PDAC were established using AI-based comprehensive analysis and machine learning workflow.The nomogram-based immune-CSC-TB profile can provide accurate prognosis prediction for patients with PDAC.

Tumor budding in gastric cancer

The tumor,nodes,metastasis(TNM)staging system has long been the gold standard for the classification and prognosis of solid tumors.However,the TNM staging system is not without limitations.Prognostic heterogeneity exists within patients at the same stage.Therefore,the pursuit of other biomarkers with the potential to classify patients with cancer has never stopped.One of them,tumor budding(TB),has gained much success in colorectal cancer.In recent years,TB in gastric cancer has attracted much attention from researchers,beginning to reveal the molecular and biological aspects of this phenomenon in gastric cancer,and has emerged as a promising prognostic biomarker in gastric cancer,predicting disease progression and unfavorable survival.Therefore,it is time and essential to provide a holistic overview of TB in gastric cancer,which has not been achieved and is the aim of this review.

Tumor budding as a potential prognostic marker in determining the behavior of primary liver cancers

Hepatocellular(HCC)and intrahepatic cholangiocarcinoma(ICC),the most common primary tumors of the liver,are among the most important causes of cancer deaths worldwide.Because patients with primary liver tumors are frequently diagnosed at an advanced stage and have high mortality,many efforts have been made to identify new markers to determine their behavior and treatment,similar to those in other solid organ tumors.Recently,morphological assessment of tumor budding(TB)has been revealed as a promising prognostic finding to predict tumor behavior and survival across several different tumor types.Currently,the TB score in colorectal cancer has been revealed as an important parameter in pathology report protocols to determine the course of the disease.Regarding the liver,despite enormous data showing that many mechanisms involved in TB are associated with tumor behavior in both HCC and ICC,studies focusing on the role of TB in predicting the behavior and prognosis of these tumors have started to be investigated very recently.The purpose of this review is to present data about TB in primary tumors of the liver,pointing out the potential role of this parameter in determining the course of the disease,and emphasize the need to increase the number of further studies focusing on the evaluation of this parameter with an overview of the mechanisms involved in TB.

Parasympathetic neurogenesis is strongly associated with tumor budding and correlates with an adverse prognosis in pancreatic ductal adenocarcinoma

Objective： To investigate the frequency of parasympathetic neurogenesis and determine its association with tumor budding and prognosis in pancreatic ductal adenocarcinoma （PDAC）. Methods： Parasympathetic neurogenesis was defined as the distribution of abnormal parasympathetic nerves in the stroma tissue. Staining of vesicular acetylcholine transporter （VAChT）, as a marker for parasympathetic neurogenesis, was performed on a representative specimen of the tumor for 59 PDAC patients with available clinical, pathologic, and follow-up information. Three specimens containing normal pancreatic tissues were stained in parallel. The number of parasympathetic nerve fibers was counted in five high-power microscopic fields （5×0.785 mm2）. Cut-offvalues were calculated by receiver operating characteristic curve analysis. Results： VAChT-positive parasympathetic nerve fibers were not seen in the stroma of 3 cases of normal pancreatic tissues. In 59 PDAC cases, the range of parasympathetic neurogenesis was 4-38 fibers/（5×0.785） mm2, with a median of 18 fibers/（5×0.785） mm2. Patients with parasympathetic neurogenesis 〉 15 fibers/（5×0.785） mm2 were defined as the high-density group （39 patients, 66.1%）, and those with parasympathetic neurogenesis 〈15 fibers/（5×0.785） mm2 as the low-density group （20 patients, 33.9%）. The high-density group had a higher occurrence of tumor budding （P=0.001） and a higher rate of early recurrence （P=0.035）. Parasympathetic neurogenesis appeared to be an independent adverse prognostic factor [hazard ratio （HR）=2.45, 95% confidence interval （95% CI）： 1.25-4.81, P=0.009], in addition to American Joint Committee on Cancer （AJCC） stage （P=0.010） and tumor budding （P=0.009）. Conclusions： Parasympathetic neurogenesis is strongly associated with tumor budding and correlates with an adverse prognosis in PDAC.

Tumor budding predicts response to anti-EGFR therapies in metastatic colorectal cancer patients

AIM:To investigate whether the evaluation of tumor budding can complement K-RAS analysis to improve the individualized prediction of response to anti-epidermal growth factor receptor based therapies in metastatic colorectal cancer (mCRC) patients. METHODS:Forty-three patients with mCRC treated with cetuximab or panitumumab were entered into this study. According to the Response Evaluation Criteria in Solid Tumors criteria, 30 patients had stable or progressive disease (non-responsive), while 13 patients had a partial response. Tumor buds were evaluated from whole tissue sections stained for pan-cytokeratin, evaluated in the densest region using a 40 × objective and "high-grade" tumor budding was defi ned as 15 buds/high-power f ield.RESULTS: Tumor buds and K-RAS mutation both correctly classif ied 68% of patients. All patients with K-RAS mutation (n=7) or high-grade tumor budding (n=11) were non-responsive, of which 4 patients had both features. All 13 partial responders were K-RAS wild-type with low-grade tumor budding. Combined, the predictive value of K-RAS and tumor budding was 80%. Additionally, high-grade tumor budding was significantly related to worse progression-free survival [HR (95% CI): 2.8 (1.3-6.0, P=0.008)].CONCLUSION: If confirmed in larger cohorts, the addition of tumor budding to K-RAS analysis may represent an effective approach for individualized patient management in the metastatic setting.

Research Progress on Molecular Mechanisms of Tumor Budding in Colorectal Cancer

Tumor buds are usually defined as isolated single cancer cells or clusters of up to four cancer cells located at the front of invasive tumors which play an important role in the clinical pathological study of colorectal cancer.The prognostic value of tumor budding in colorectal cancer has been supported by a large amount of evidence.However,its molecular mechanism remains unclear,and it is also a research hotspot now.This paper reviews the latest research progress on the molecular mechanisms of tumor budding in colorectal cancer.

Risk factors for lymph node metastasis in superficial esophageal squamous cell carcinoma

In this editorial,we comment on the article by Wang et al published in the recent issue of the World Journal of Gastroenterology in 2023.We focused on identifying risk factors for lymph node metastasis(LNM)in superficial esophageal squamous cell carcinoma(SESCC)patients and how to construct a simple and reliable clinical prediction model to assess the risk of LNM in SESCC patients,thereby helping to guide the selection of an appropriate treatment plan.The current standard treatment for SESCC is radical esophagectomy with lymph node dissection.However,esophagectomy is associated with considerable morbidity and mortality.Endoscopic resection(ER)offers a safer and less invasive alternative to surgical resection and can enable the patient's quality of life to be maintained while providing a satisfactory outcome.However,since ER is a localized treatment that does not allow for lymph node dissection,the risk of LNM in SESCC limits the effectiveness of ER.Understanding LNM status can aid in determining whether patients with SESCC can be cured by ER without the need for additional esophagectomy.Previous studies have shown that tumor size,macroscopic type of tumor,degree of differentiation,depth of tumor invasion,and lymphovascular invasion are factors associated with LNM in patients with SESCC.In addition,tumor budding is commonly associated with LNM,recurrence,and distant metastasis,but this topic has been less covered in previous studies.By comprehensively evaluating the above risk factors for LNM,useful evidence can be obtained for doctors to select appropriate treatments for SESCC patients.

ABCG5-positivity in tumor buds is an indicator of poor prognosis in node-negative colorectal cancer patients

AIM:To analyze the expression of 8 putative cancer stem cell(CSC) markers within colorectal cancer tumor buds and to determine their prognostic impact in patients with this disease. METHODS:Immunohistochemistry was performed on 101 colorectal cancer resections for CK22(to identify tumor buds) as well as CD133,CD166,CD24,CD44s,CD90,EpCAM,ALDH1,and ABCG5,and their expression within tumor buds was evaluated. RESULTS:CD90,CD44s,and CD133 expression in tumor buds was found in less than 5%of all cases. ALDH1,CD24,CD166 were expressed in 16.5%,16.2%,and 34%cases,respectively,while ABCG5 and EpCAM expression was more frequent and found in 35%and 69%of cases,respectively.Of the 8 markers studied,EpCAM and ABCG5 positivity in tumor buds were significantly associated with poor prognosis(P=0.023,P=0.038,respectively) in multivariable analysis with pT and pN classificationP=0.048;hazard ratio(HR) :2.64;95%CI:1.0-6.9,for EpCAM and P=0.029;HR:2.22;95%CI:1.0-4.5,for ABCG5.Poor survival time was particularly striking for lymph node-negative patients with ABCG5-positive buds(P<0.001) . CONCLUSION:Expression of putative stem cell markers EpCAM and ABCG5 within the tumor buds of colorectal cancer are frequently noted and are associated with poor prognosis.

Tumor budding is a meaningful prognostic marker in patients with hepatocellular carcinoma after curative hepatectomy

Aim:Tumor budding(TB)has excellent prognostic value in many solid tumors,but there is little research on it in hepatocellular carcinoma(HCC).This study assessed the prognostic value of TB in patients with HCC who received hepatectomy.Methods:This retrospective study included 210 patients with HCC who received curative hepatectomy at the First Affiliated Hospital of Xi'an Jiaotong University,between 2016 and 2018.TB was evaluated on hematoxylin-and eosin-stained slides according to the criteria established by the 2016 International Tumor Budding Consensus Conference.t-tests,Chi-squared tests,and rank-sum tests were used to correlate the extent of TB with clinicopathological parameters.Prognostic analysis was performed using Cox regression models and the Kaplan–Meier method.Results:The positive detection rate of TB was 45.2%(95/210)in 210 patients with HCC.Patients positive for TB always exhibit lower tumor differentiation,higher hepatitis B virus DNA levels,and more severe liver fibrosis.Multivariate Cox analysis identified TB(hazard ratio[HR]:2.232,95%confidence interval[CI]:1.479–3.368,p<0.001)as an independent prognostic factor for patients'recurrence-free survival(RFS),similar to tumor size(HR:1.070,95%CI:1.070–1.142,p=0.042)and satellite nodule(HR:2.266,95%CI:1.298–3.956,p=0.004).Kaplan–Meier analysis also demonstrated that TB-positive patients had a significantly worse RFS.Interestingly,subgroup analysis revealed that among HCC patients with negative microvascular invasion(MVI),TB was also strongly associated with RFS(HR:3.206,95%CI:1.667–6.168,p<0.001).These findings suggest that TB may serve as a supplemental prognostic biomarker for HCC-negative MVI.Conclusions:TB is an adverse prognostic biomarker for HCC,particularly in patients negative for MVI.TB evaluation should be considered in the postoperative pathological examination of HCC in clinical practice.

Development and application of a detection platform for colorectal cancer tumor sprouting pathological characteristics based on artificial intelligence

Objective Tumor sprouting can reflect independent risk factors for tumor malignancy and a poor clinical progno-sis.However,there are significant differences and difficulties associated with manually identifying tumor sprout-ing.This study used the Faster region convolutional neural network(RCNN)model to build a colorectal cancer tumor sprouting artificial intelligence recognition framework based on pathological sections to automatically identify the budding area to assist in the clinical diagnosis and treatment of colorectal cancer.Methods We retrospectively collected 100 surgical pathological sections of colorectal cancer from January 2019 to October 2019.The pathologists used LabelImg software to identify tumor buds and to count their numbers.Finally,1,000 images were screened,and the total number of tumor buds was approximately 3,226;the images were randomly divided into a training set and a test set at a ratio of 6:4.After the images in the training set were manually identified,the identified buds in the 600 images were used to train the Faster RCNN identification model.After the establishment of the artificial intelligence identification detection platform,400 images in the test set were used to test the identification detection system to identify and predict the area and number of tumor buds.Finally,by comparing the results of the Faster RCNN system and the identification information of pathologists,the performance of the artificial intelligence automatic detection platform was evaluated to determine the area and number of tumor sprouting in the pathological sections of the colorectal cancers to achieve an auxiliary diagnosis and to suggest appropriate treatment.The selected performance indicators include accuracy,precision,specificity,etc.ROC(receiver operator characteristic)and AUC(area under the curve)were used to quantify the performance of the system to automatically identify tumor budding areas and numbers.Results The AUC of the receiver operating characteristic curve of the artificial intelligence detection and identi-fication system was 0.96,the image diagnosis accuracy rate was 0.89,the precision was 0.855,the sensitivity was 0.94,the specificity was 0.83,and the negative predictive value was 0.933.After 400 test sets,pathological image verification showed that there were 356 images with the same positive budding area count,and the difference between the positive area count and the manual detection count in the remaining images was less than 3.The detection system based on tumor budding recognition in pathological sections is comparable to that of patholo-gists’accuracy;however,it took significantly less time(0.03±0.01)s for the pathologist(13±5)s to diagnose the sections with the assistance of the AI model.Conclusion This system can accurately and quickly identify the tumor sprouting area in the pathological sections of colorectal cancer and count their numbers,which greatly improves the diagnostic efficacy,and effectively avoids the need for confirmation by different pathologists.The use of the AI reduces the burden of pathologists in reading sections and it has a certain clinical diagnosis and treatment value.