Tumor deposits in axillary adipose tissue in patients with breast cancer:Do they matter?

Tumor deposits(TDs)are defined as discrete,irregular clusters of tumor cells lying in the soft tissue adjacent to but separate from the primary tumor,and are usually found in the lymphatic drainage area of the primary tumor.By definition,no residual lymph node structure should be identified in these tumor masses.At present,TDs are mainly reported in colorectal cancer,with a few reports in gastric cancer.There are very few reports on breast cancer(BC).For TDs,current dominant theories suggest that these are the result of lymph node metastasis of the tumor with complete destruction of the lymph nodes by the tumor tissue.Even some pathologists classify a TD as two lymph node metastases for calculation.Some pathologists also believe that TDs belong to the category of disseminated metastasis.Therefore,regardless of the origin,TDs are an indicator of poor prognosis.Moreover,for BC,sentinel lymph node biopsy is generally used at present.Whether radical axillary lymph node dissection should be adopted for BC with TDs in axillary lymph nodes is still inconclusive.The present commentary of this clinical issue has certain guiding significance.It is aimed to increase the awareness of the scientific community towards this under-recognized problem in BC pathology.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer

BACKGROUND Ferroptosis has recently been associated with multiple degenerative diseases.Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases.However,the association of iron proliferation-related genes with prognosis in HER2+breast cancer(BC)patients is unclear.AIM To identify and evaluate fresh ferroptosis-related biomarkers for HER2+BC.METHODS First,we obtained the mRNA expression profiles and clinical information of HER2+BC patients from the TCGA and METABRIC public databases.A four gene prediction model comprising PROM2,SLC7A11,FANCD2,and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort.Patients were stratified into high-risk and low-risk groups based on their median risk score,an independent predictor of overall survival(OS).Based on these findings,immune infiltration,mutations,and medication sensitivity were analyzed in various risk groupings.Additionally,we assessed patient prognosis by combining the tumor mutation burden(TMB)with risk score.Finally,we evaluated the expression of critical genes by analyzing single-cell RNA sequencing(scRNA-seq)data from malignant vs normal epithelial cells.RESULTS We found that the higher the risk score was,the worse the prognosis was(P<0.05).We also found that the immune cell infiltration,mutation,and drug sensitivity were different between the different risk groups.The highrisk subgroup was associated with lower immune scores and high TMB.Moreover,we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses.HRisk-HTMB patients had the worst prognosis,whereas LRisk-LTMB patients had the best prognosis(P<0.0001).Analysis of the scRNAseq data showed that PROM2,SLC7A11,and FANCD2 were significantly differentially expressed,whereas FH was not,suggesting that these genes are expressed mainly in cancer epithelial cells(P<0.01).CONCLUSION Our model helps guide the prognosis of HER2+breast cancer patients,and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Decreased LDHB expression in breast tumor cells causes NK cell activation and promotes tumor progression

Objective: Abnormal metabolism is the underlying reason for breast cancer progression. Decreased lactate dehydrogenase B(LDHB) has been detected in breast cancer but the function of LDHB remains unknown.Methods: Western blot was used to analyze LDHB expression in breast cancer cells. The impact of LDHB on tumor cell migration and invasion was determined using Transwell assays, wound healing assays, and a mouse lung metastasis model. Subcutaneous tumor formation, a natural killer(NK) cell cytotoxicity assay, and flow cytometry evaluated NK cell activation. Immunofluorescence and quantitative real-time PCR detected NK cell activation markers. Kaplan-Meier analysis evaluated the effect of immune cell infiltration on prognosis. Single-sample gene set enrichment analysis determined NK cell activation scores. A support vector machine predicted the role of LDHB in NK cell activation.Results: In this study we showed that LDHB inhibits the breast cancer cell metastasis and orchestrates metabolic reprogramming within tumor cells. Our results revealed that LDHB-mediated lactic acid clearance in breast cancer cells triggers NK cell activation within the tumor microenvironment. Our findings, which were confirmed in a murine model, demonstrated that LDHB in tumor cells promotes NK cell activation and ultimately results in the eradication of malignant cells. Clinically, our study further validated that LDHB affects immune cell infiltration and function. Specifically, its expression has been linked to enhanced NK cell-mediated cytotoxicity and improved patient survival. Furthermore, we identified LDHB expression in tumors as an important predictor of NK cell activation, with strong predictive ability in some cancers.Conclusions: Our results suggest that LDHB is a promising target for activating the tumor immune microenvironment in breast cancer, where LDHB-associated lactic acid clearance leads to increased NK cell activity. This study highlights the critical role of LDHB in regulating immune responses and its potential as a therapeutic target for breast cancer.

A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effectivetreatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breastcancer fromultrasound images. The primary challenge is accurately distinguishing between malignant and benigntumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentationand classification. The main objective of the research paper is to develop an advanced methodology for breastultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, andmachine learning-based classification. A unique approach is introduced that combines Enhanced Speckle ReducedAnisotropic Diffusion (SRAD) filters for speckle noise reduction, U-NET-based segmentation, Genetic Algorithm(GA)-based feature selection, and Random Forest and Bagging Tree classifiers, resulting in a novel and efficientmodel. To test and validate the hybrid model, rigorous experimentations were performed and results state thatthe proposed hybrid model achieved accuracy rate of 99.9%, outperforming other existing techniques, and alsosignificantly reducing computational time. This enhanced accuracy, along with improved sensitivity and specificity,makes the proposed hybrid model a valuable addition to CAD systems in breast cancer diagnosis, ultimatelyenhancing diagnostic accuracy in clinical applications.

Research progress in tumor angiogenesis and drug resistance in breast cancer

Angiogenesis is considered a hallmark pathophysiological process in tumor development. Aberrant vasculature resulting from tumor angiogenesis plays a critical role in the development of resistance to breast cancer treatments, via exacerbation of tumor hypoxia, decreased effective drug concentrations within tumors, and immune-related mechanisms. Antiangiogenic therapy can counteract these breast cancer resistance factors by promoting tumor vascular normalization. The combination of antiangiogenic therapy with chemotherapy, targeted therapy, or immunotherapy has emerged as a promising approach for overcoming drug resistance in breast cancer. This review examines the mechanisms associated with angiogenesis and the interactions among tumor angiogenesis, the hypoxic tumor microenvironment, drug distribution, and immune mechanisms in breast cancer. Furthermore, this review provides a comprehensive summary of specific antiangiogenic drugs, and relevant studies assessing the reversal of drug resistance in breast cancer. The potential mechanisms underlying these interventions are discussed, and prospects for the clinical application of antiangiogenic therapy to overcome breast cancer treatment resistance are highlighted.

Correlation and predictive value of pathological complete response and ultrasound characteristic parameters in neoadjuvant chemotherapy for breast

BACKGROUND Breast cancer ranks as one of the most prevalent malignant tumors among women,significantly endangering their health and lives.While radical surgery has been a pivotal method for halting disease progression,it alone is insufficient for enhancing the quality of life for patients.AIM To investigate the correlation between ultrasound characteristic parameters of breast cancer lesions and clinical efficacy in patients undergoing neoadjuvant chemotherapy(NAC).METHODS Employing a case-control study design,this research involved 178 breast cancer patients treated with NAC at our hospital from July 2019 to June 2022.According to the Miller-Payne grading system,the pathological response,i.e.efficacy,of the NAC in the initial breast lesion after NAC was evaluated.Of these,59 patients achieved a pathological complete response(PCR),while 119 did not(non-PCR group).Ultrasound characteristics prior to NAC were compared between these groups,and the association of various factors with NAC efficacy was analyzed using univariate and multivariate approaches.RESULTS In the PCR group,the incidence of posterior echo attenuation,lesion diameter≥2.0 cm,and Alder blood flow grade≥II were significantly lower compared to the non-PCR group(P<0.05).The area under the curve values for predicting NAC efficacy using posterior echo attenuation,lesion diameter,and Alder grade were 0.604,0.603,and 0.583,respectively.Also,rates of pathological stage II,lymph node metastasis,vascular invasion,and positive Ki-67 expression were significantly lower in the PCR group(P<0.05).Logistic regression analysis identified posterior echo attenuation,lesion diameter≥2.0 cm,Alder blood flow grade≥II,pathological stage III,vascular invasion,and positive Ki-67 expression as independent predictors of poor response to NAC in breast cancer patients(P<0.05).CONCLUSION While ultrasound characteristics such as posterior echo attenuation,lesion diameter≥2.0 cm,and Alder blood flow grade≥II exhibit limited predictive value for NAC efficacy,they are significantly associated with poor response to NAC in breast cancer patients.

Two Stages Segmentation Algorithm of Breast Tumor in DCE-MRI Based on Multi-Scale Feature and Boundary Attention Mechanism

Nuclearmagnetic resonance imaging of breasts often presents complex backgrounds.Breast tumors exhibit varying sizes,uneven intensity,and indistinct boundaries.These characteristics can lead to challenges such as low accuracy and incorrect segmentation during tumor segmentation.Thus,we propose a two-stage breast tumor segmentation method leveraging multi-scale features and boundary attention mechanisms.Initially,the breast region of interest is extracted to isolate the breast area from surrounding tissues and organs.Subsequently,we devise a fusion network incorporatingmulti-scale features and boundary attentionmechanisms for breast tumor segmentation.We incorporate multi-scale parallel dilated convolution modules into the network,enhancing its capability to segment tumors of various sizes through multi-scale convolution and novel fusion techniques.Additionally,attention and boundary detection modules are included to augment the network’s capacity to locate tumors by capturing nonlocal dependencies in both spatial and channel domains.Furthermore,a hybrid loss function with boundary weight is employed to address sample class imbalance issues and enhance the network’s boundary maintenance capability through additional loss.Themethod was evaluated using breast data from 207 patients at RuijinHospital,resulting in a 6.64%increase in Dice similarity coefficient compared to the benchmarkU-Net.Experimental results demonstrate the superiority of the method over other segmentation techniques,with fewer model parameters.

Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

The Role of MSCT in Evaluating Tumor Size,Density,Immunohistochemical Classification,and Pathological Risk in GIST Patients

Objective:To investigate the role of multilayer spiral CT(MSCT)in evaluating patients with gastrointestinal stromal tumors(GIST),particularly its utility in determining tumor size,immunohistochemical classification,and pathological risk.Methods:A retrospective analysis was conducted on 22 GIST patients,confirmed by surgical pathology between January 2019 and December 2023.All patients underwent MSCT examination prior to surgery.Tumor size,density,and immunohistochemical classification from the MSCT results were compared with the postoperative pathological findings.Additionally,the ability of MSCT to predict GIST risk grade was evaluated in combination with immunohistochemical analysis results.Results:No significant differences were found between the preoperative MSCT findings and postoperative pathological results in terms of tumor size,density,or immunohistochemical classification in GIST patients.MSCT also enhanced the ability to predict GIST risk grades.Conclusion:MSCT demonstrates significant clinical value in the diagnosis and risk assessment of GIST,aiding in the prediction of the tumor’s biological behavior and patients’treatment responses.

Analysis of the Clinical Value of Immunohistochemical Testing in the Pathological Diagnosis of Breast Cancer

Objective:To investigate the clinical value of immunohistochemistry(IHC)detection in the pathological diagnosis of breast cancer.Methods:Eighty breast cancer patients admitted to Baoding No.1 Central Hospital from June 2022 to June 2023 were selected as study subjects.The samples were divided into a positive group(40 cases)and a negative group(40 cases)according to ER and PR test results.Immunohistochemistry was performed on all patients to compare the differences between the two groups in C-erbB-2 positive expression and axillary lymph node metastasis.Results:The positive expression rate of C-erbB-2 in the positive group(35.00%)was significantly lower than that in the negative group(80.00%),with a highly significant difference(P<0.001).The axillary lymph node metastasis rate in the positive group(40.00%)was significantly lower than that in the negative group(75.00%),with a significant difference(P<0.05).Conclusion:Immunohistochemical detection in breast cancer pathology enhances diagnostic accuracy,predicts prognosis,and supports personalized treatment by identifying ER,PR,and C-erbB-2.It is worth being widely adopted in clinical practice.

A Swin Transformer and Residualnetwork Combined Model for Breast Cancer Disease Multi-Classification Using Histopathological Images

Breast cancer has become a killer of women's health nowadays.In order to exploit the potential representational capabilities of the models more comprehensively,we propose a multi-model fusion strategy.Specifically,we combine two differently structured deep learning models,ResNet101 and Swin Transformer(SwinT),with the addition of the Convolutional Block Attention Module(CBAM)attention mechanism,which makes full use of SwinT's global context information modeling ability and ResNet101's local feature extraction ability,and additionally the cross entropy loss function is replaced by the focus loss function to solve the problem of unbalanced allocation of breast cancer data sets.The multi-classification recognition accuracies of the proposed fusion model under 40X,100X,200X and 400X BreakHis datasets are 97.50%,96.60%,96.30 and 96.10%,respectively.Compared with a single SwinT model and ResNet 101 model,the fusion model has higher accuracy and better generalization ability,which provides a more effective method for screening,diagnosis and pathological classification of female breast cancer.

Collision tumor of primary malignant lymphoma and adenocarcinoma in the colon diagnosed by molecular pathology:A case report and literature review

BACKGROUND Collision tumors of primary malignant lymphoma and adenocarcinoma in the colon are rare.Primary diffuse large B-cell lymphoma(DLBCL)–adenocarcinoma collision tumors are especially rare.CASE SUMMARY A 74-year-old woman presented with abdominal pain of 1 mo duration.Biopsy under colonoscopy revealed adenocarcinoma of the ascending colon.Subsequently,the patient underwent laparoscopic radical resection of right colon cancer with lymph node dissection.A collision tumor was found incidentally through postoperative pathological sampling.Genetic analysis showed a collision tumor of DLBCL with germinal center B-cell subtype and TP53 mutation,and adenocarcinoma arising in a tubulovillous adenoma in the colon,with BRAF mutation and mutL homolog 1 promoter methylation.The patient died 3 mo after surgery.To our knowledge,this is the 23rd reported case of collision tumor of colorectal adenocarcinoma and lymphoma.The mean age of the 23 patients was 73 years.The most common site was the cecum.There were 15 cases with followup data including 11 living and four dead with a 3-year overall survival rate of 71.5%.CONCLUSION Based on pathological and genetic analysis,surgery combined with chemotherapy or chemoradiotherapy may have good therapeutic effects for collision tumor.

A pulmonary metastatic breast phyllodes tumor and clinicopathology analysis

Objective Breast phyllodes tumors(PTs) are rare fibroepithelial tumors that are characterized by formation of foliation patterns. Behaviorally, only relatively poor prediction of PTs is possible based on their histological appearance. PTs are frequently misdiagnosed because they are difficult to differentiate from soft tissue tumors. In this report, we describe the pathological features of a rare case of PT and review the relevant literature, summarizing the essentials of the diagnosis and differential diagnosis, while attempting to avoid misdiagnosis or missed diagnosis of the tumor to the best of our abilities.Methods We present a case of pulmonary metastatic lobular tumor, analyzing the morphological [hematoxylin-eosin(HE) staining] and immunohistochemical(streptavidin perosidase method, SP) features of the tissue.Results Long spindle-shaped tumor cells were observed using microscopy. The cells were arranged in bundles, with a whirlpool pattern, and braided. The proliferation of the spindle cells was markedly atypical and karyokinesis was elevated. Residual ductal epithelium was detected in some areas, and the margins of the tumor tissues showed invasive growth. Immunohistochemical studies of the spindle-shaped tumor cells were positive for actin, PR, CD10, SMA, Bcl-2, and negative for CKP, S-100, CD34, ER. The Ki-67 index was 40%.Conclusion The spindle cell tumor identified in the lung should first be considered as a metastatic neosplasm, because most soft-tissue sarcomas commonly metastasize through the bloodstream to the lungs. Although malignant breast PTs are rare, a detailed medical history that includes prior surgical history is required to avoid wrongful or missed diagnosis.

Understanding the mechanisms underlying obesity in remodeling the breast tumor immune microenvironment:from the perspective of inflammation

Obesity is a well-known modifiable risk factor for breast cancer and is considered a poor prognostic factor in pre-and post-menopausal women.While the systemic effects of obesity have been extensively studied,less is known about the mechanisms underlying obesityassociated cancer risk and the local consequences of obesity.Thus,obesity-induced inflammation has become the focus of research interest.Biologically,the development of cancer involves a complex interaction with numerous components.As the tumor immune microenvironment changes due to obesity-triggered inflammation,an increase in infiltration occurs for proinflammatory cytokines and adipokines,as well as adipocytes,immune cells,and tumor cells in the expanded adipose tissue.Complicated cellular-molecular crosstalk networks change critical pathways,mediate metabolic and immune function reprogramming,and have a significant role in tumor metastasis,proliferation,resistance,angiogenesis,and tumorigenesis.This review summarizes recent research findings on how inflammatory mediators in the in situ tumor microenvironment regulate the occurrence and development of breast cancer in the context of obesity.We analyzed the heterogeneity and potential mechanisms of the breast cancer immune microenvironment from the perspective of inflammation to provide a reference for the clinical transformation of precision targeted cancer therapy.

Circulating tumor cells and circulating tumor DNA in breast cancer diagnosis and monitoring

Liquid biopsy,including both circulating tumor cells and circulating tumor DNA,is becoming more popular as a diagnostic tool in the clinical management of breast cancer.Elevated concentrations of these biomarkers during cancer treatment may be used as markers for cancer progression as well as to understand the mechanisms underlying metastasis and treatment resistance.Thus,these circulating markers serve as tools for cancer assessing and monitoring through a simple,non-invasive blood draw.However,despite several study results currently noting a potential clinical impact of ctDNA mutation tracking,the method is not used clinically in cancer diagnosis among patients and more studies are required to confirm it.This review focuses on understanding circulating tumor biomarkers,especially in breast cancer.

Proposed Framework for Detection of Breast Tumors

Computer vision is one of the significant trends in computer science.It plays as a vital role in many applications,especially in the medical field.Early detection and segmentation of different tumors is a big challenge in the medical world.The proposed framework uses ultrasound images from Kaggle,applying five diverse models to denoise the images,using the best possible noise-free image as input to the U-Net model for segmentation of the tumor,and then using the Convolution Neural Network(CNN)model to classify whether the tumor is benign,malignant,or normal.The main challenge faced by the framework in the segmentation is the speckle noise.It’s is a multiplicative and negative issue in breast ultrasound imaging,because of this noise,the image resolution and contrast become reduced,which affects the diagnostic value of this imaging modality.As result,speckle noise reduction is very vital for the segmentation process.The framework uses five models such as Generative Adversarial Denoising Network(DGAN-Net),Denoising U-Shaped Net(D-U-NET),Batch Renormalization U-Net(Br-UNET),Generative Adversarial Network(GAN),and Nonlocal Neutrosophic ofWiener Filtering(NLNWF)for reducing the speckle noise from the breast ultrasound images then choose the best image according to peak signal to noise ratio(PSNR)for each level of speckle-noise.The five used methods have been compared with classical filters such as Bilateral,Frost,Kuan,and Lee and they proved their efficiency according to PSNR in different levels of noise.The five diverse models are achieved PSNR results for speckle noise at level(0.1,0.25,0.5,0.75),(33.354,29.415,27.218,24.115),(31.424,28.353,27.246,24.244),(32.243,28.42,27.744,24.893),(31.234,28.212,26.983,23.234)and(33.013,29.491,28.556,25.011)forDGAN,Br-U-NET,D-U-NET,GANand NLNWF respectively.According to the value of PSNR and level of speckle noise,the best image passed for segmentation using U-Net and classification usingCNNto detect tumor type.The experiments proved the quality ofU-Net and CNN in segmentation and classification respectively,since they achieved 95.11 and 95.13 in segmentation and 95.55 and 95.67 in classification as dice score and accuracy respectively.

Granular cell tumor of the breast:A case report and review of literature

BACKGROUND Granular cell tumor(GCT)of the breast(GCTB)is a rare neoplasm that can exhibit malignant characteristics both clinically and radiologically.This tumor can also coexist and colocalize with breast carcinoma.CASE SUMMARY We present a patient with this uncommon tumor and discuss the diagnostic and therapeutic approaches in order to further the knowledge of GCTB and prevent misdiagnosis and overtreatment.The characteristics of the tumor,methods of diagnosis,therapy and postoperative pathological outcomes were analyzed,and relevant literatures of GCTs were reviewed.The patient underwent surgery after core needle biopsy,and the excised neoplasm was sent for pathological examination.Histological analysis revealed nests of cells with abundant pink granular cytoplasm,confirming the diagnosis of GCTB.CONCLUSION As manifestations of GCT and malignancy can mimic each other,a careful histological examination is essential before major surgery.Treatment consisting of complete excision with close clinical follow-up is recommended.

Isolated axillary tumor deposit consistent with primary breast carcinoma:A case report

BACKGROUND We all know that lymph-node metastasis is an important factor for poor clinical outcome in breast cancer prognosis.Tumor deposit refers to a discrete collection of cancer cells that is found in the lymph nodes or other tissues adjacent to the primary tumor site.These tumor deposits are separate from the primary tumor and are often considered as a manifestation of lymph node metastasis.In gastric and colorectal cancer,tumor deposits in the lymph node drainage area have been included as independent prognostic factors.The question arises whether tumor deposits should also be considered as prognostic factors in breast cancer patients.This article aims to provoke some thoughts on this matter through a case study and literature review.CASE SUMMARY A 70-year-old female patient was found to have a right breast lump for over 2 years.On January 3,2023,a core needle biopsy of the right breast lump was performed,and the pathology report indicated invasive carcinoma.Subsequently,on January 17,2023,the patient underwent right breast-conserving surgery,sentinel lymph node biopsy,and right axillary lymph node dissection.The postoperative pathological staging was determined as stage IIB.The patient received chemotherapy,radiotherapy,and endocrine therapy.At present,nearly one year after the surgery,no obvious signs of metastasis have been observed in the follow-up examinations,but the long-term prognosis is still unknown.CONCLUSION There is a need for increased focus on the matter of tumor deposits in the lymph node drainage region,as well as a requirement for further clinical investigation to ascertain the relevance of tumor deposits in the prognosis of individuals with breast carcinoma.

Esophageal mesenchymal tumors:Endoscopy,pathology and immunohistochemistry

AIM： To study the endoscopic, pathological and immunoo histochemical features of esophageal mesenchymal tumors. METHODS： Twenty-nine patients diagnosed as esophageal rnysenchymal tumors by electronic endoscopy and endoscopic ultrasound （EUS） were observed under light microscopes, and all tissues were stained by the immunohistochemical method. The expression of CD117, CD34, SMA and desmin were measured by staining intensity of cells and positive cell ratios. RESULTS： Endoscopically, esophageal gastrointestinal stromal tumors （GISTs） and leiomyomas （LMs） had similar appearances, showing submucosal protuberant lesions. They all showed low echo images originated from the muscularis propria or muscularis mucosa on EUS. Endoscopy and EUS could not exactly differentiate esophageal GISTs from LMs. Microscopically, there were two kinds of cells： spindle cell type and epitheloid cell type in esophageal GISTs. Leiomyomas and leiomyosarcornas were only of spindle cell type. One malignancy was found in five cases of esophageal GISTs, and one malignancy in 24 cases of leiomyomas and leiomyosarcomas. Using Fisher＇s exact method, the differences of malignant lesion proportion were not significant between esophageal LMs and GISTs, 1/5 vs 1/24 （P 〉 0.05）. All cases of esophageal GISTs were positive for CD117, and 3 cases were also positive for CD34. The 24 cases of leiomyomas and leiomyosarcomas were all negative for CD117 and CD34. The differences of positive rates of CD117 and CD34 were significant between esophageal GISTs and LMs, 5/5 vs 0/24, 3/5 vs 0/24 （P 〈 0.005）. All leiomyomas and leiomyosarcomas were positive for SMA, and desmin. Among 5 cases of esophageal GISTs, 2 cases were SMA positive, and 1 case was desmin positive. The differences in positive rates and expression intensity of SMA and desmin were significant between esophageal LMs and GISTs, 24/24 vs 2/5, 24/24 vs 115 （P 〈 0.005）. CONCLUSION： The most common esophageal mesenchymal tumors are leiomyomas, and esophageal GISTs are less common. Most of esophageal LMs and GISTs are benign. Endoscopy and EUS are the effective methods to diagnose esophageal mesenchymal tumors and they can provide useful information for the treatment of these tumors. However, they cannot exactly differentiate esophageal GISTs from LMs. Pathological, especially immunohistochemical features are useful to differentiate GISTs from leiomyomas.

Development and validation of an online calculator to predict the pathological nature of colorectal tumors

BACKGROUND No single endoscopic feature can reliably predict the pathological nature of colorectal tumors(CRTs).AIM To establish and validate a simple online calculator to predict the pathological nature of CRTs based on white-light endoscopy.METHODS This was a single-center study.During the identification stage,530 consecutive patients with CRTs were enrolled from January 2015 to December 2021 as the derivation group.Logistic regression analysis was performed.A novel online calculator to predict the pathological nature of CRTs based on white-light images was established and verified internally.During the validation stage,two series of 110 images obtained using white-light endoscopy were distributed to 10 endoscopists[five highly experienced endoscopists and five less experienced endoscopists(LEEs)]for external validation before and after systematic training.RESULTS A total of 750 patients were included,with an average age of 63.6±10.4 years.Early colorectal cancer(ECRC)was detected in 351(46.8%)patients.Tumor size,left semicolon site,rectal site,acanthosis,depression and an uneven surface were independent risk factors for ECRC.The C-index of the ECRC calculator prediction model was 0.906(P=0.225,Hosmer-Lemeshow test).For the LEEs,significant improvement was made in the sensitivity,specificity and accuracy(57.6%vs 75.5%;72.3%vs 82.4%;64.2%vs 80.2%;P<0.05),respectively,after training with the ECRC online calculator prediction model.CONCLUSION A novel online calculator including tumor size,location,acanthosis,depression,and uneven surface can accurately predict the pathological nature of ECRC.