Clinical pathological characteristics of“crawling-type”gastric adenocarcinoma cancer:A case report

BACKGROUND Gastric cancer(GC)is a significant health problem worldwide,and early detection and accurate diagnosis are crucial for improving patient outcomes.Crawling-type gastric adenocarcinoma is a rare subtype of GC that has unique histopathological and clinical characteristics,and its diagnosis and management can be challenging.This pathological type of GC is also rare.CASE SUMMARY Here,we report the case of a patient who underwent ordinary endoscopy,na-rrow-band imaging,and endoscopic ultrasonography intending to determine the extent of tumor invasion and upper abdominal enhanced computed tomography and whether there was tumor metastasis.Then,endoscopic submucosal dissection was performed.After pathological and immunohistochemical examination,the pathological diagnosis was crawling-type gastric adenocarcinoma.This is a very rare and special pathological type of tumor.This case highlights the importance of using advanced endoscopic techniques and pathological examination in diagnosing and managing gastric crawling-type adenocarcinoma.Moreover,the findings underscore the need for continued research and clinical experience in this rare subtype of GC to improve patient outcomes.CONCLUSION The“crawling-type”GC is a rare and specific tumor pathology.It is difficult to identify and diagnose gliomas via endoscopy.The tumor is ill-defined,with a flat appearance and indistinct borders due to the lack of contrast against the background mucosa.Pathology revealed that the tumor cells were hand-like,so the patient has diagnosed with“crawling-type”gastric adenocarcinoma.

Mesenchymal-epithelial transition factor amplification correlates with adverse pathological features and poor clinical outcome in colorectal cancer

BACKGROUND Colorectal cancer(CRC)is the third most common cancer and the second most common cause of cancer-related mortality worldwide.Mesenchymal-epithelial transition factor(MET)gene participates in multiple tumor biology and shows clinical potential for pharmacological manipulation in tumor treatment.MET amplification has been reported in CRC,but data are very limited.Investigating pathological values of MET in CRC may provide new therapeutic and genetic screening options in future clinical practice.AIM To determine the pathological significance of MET amplification in CRC and to propose a feasible screening strategy.METHODS A number of 205 newly diagnosed CRC patients undergoing surgical resection without any preoperative therapy at Shenzhen Cancer Hospital of Chinese Academy of Medical Sciences were recruited.All patients were without RAS/RAF mutation or microsatellite instability-high.MET amplification and c-MET protein expression were analyzed using fluorescence in situ hybridization(FISH)and immunohistochemistry(IHC),respectively.Correlations between MET aberration and pathological features were detected using the chi-squared test.Progression free survival(PFS)during the two-year follow-up was detected using the Kaplan-Meier method and log rank test.The results of MET FISH and IHC were com pared using one-way ANOVA.RESULTS Polysomy-induced MET amplification was observed in 14.4%of cases,and focal MET amplification was not detected.Polysomy-induced MET amplification was associated with a higher frequency of lymph node metastasis(LNM)(P<0.001)and higher tumor budding grade(P=0.02).In the survival analysis,significant difference was detected between patients with amplified-and non-amplified MET in a two-year follow-up after the first diagnosis(P=0.001).C-MET scores of 0,1+,2+,and 3+were observed in 1.4%,24.9%,54.7%,and 19.0%of tumors,respectively.C-MET overexpression correlated with higher frequency of LNM(P=0.002),but no significant difference of PFS was detected between patients with different protein levels.In terms of concordance between MET FISH and IHC results,MET copy number showed no difference in c-MET IHC 0/1+(3.35±0.18),2+(3.29±0.11)and 3+(3.58±0.22)cohorts,and the MET-to-CEP7 ratio showed no difference in three groups(1.09±0.02,1.10±0.01,and 1.09±0.03).CONCLUSION In CRC,focal MET amplification was a rare event.Polysomy-induced MET amplification correlated with adverse pathological characteristics and poor prognosis.IHC was a poor screening tool for MET amplification.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer

BACKGROUND Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide.Neoadjuvant chemoradiotherapy(nCRT)is standard for locally advanced rectal cancer(LARC).Except for pathological examination after resection,it is not known exactly whether LARC patients have achieved pathological complete response(pCR)before surgery.To date,there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes.AIM To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC.METHODS Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed.Patients were categorized into pCR and non-pCR groups.Univariate analysis(using the χ^(2) test or Fisher’s exact test)and logistic multivariate regression analysis were used to study clinical predictors affecting pCR.The 5-year disease-free survival(DFS)and overall survival(OS)rates were calculated using Kaplan-Meier analysis,and differences in survival curves were assessed with the log-rank test.RESULTS Univariate analysis showed that pretreatment carcinoembryonic antigen(CEA)level,lymphocyte-monocyte ratio(LMR),time interval between neoadjuvant therapy completion and total mesorectal excision,and tumor size were correlated with pCR.Multivariate results showed that CEA≤5 ng/mL(P=0.039),LMR>2.73(P=0.023),and time interval>10 wk(P=0.039)were independent predictors for pCR.Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates(94.7%vs 59.7%,P=0.002)and 5-year OS rates(95.8%vs 80.1%,P=0.019)compared to the non-pCR group.Tumor deposits(TDs)were significantly correlated with shorter DFS(P=0.002)and OS(P<0.001).CONCLUSION Pretreatment CEA,LMR,and time interval contribute to predicting nCRT efficacy in LARC patients.Achieving pCR demonstrates longer DFS and OS.TDs correlate with poor prognosis.

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.

Research Progress on the Relationship between Magnetic Resonance Imaging and Clinical Pathological Characteristics of Liver Cancer

Liver cancer is one of the main malignant tumors in the digestive system.Early detection and treatment have positive significance in improving patient prognosis and reducing mortality.MRI is the main method for liver cancer examination,which mainly uses computers to compare imaging of different energy regions of tumors,observe the density and signal changes of liver cancer,and the degree of tumor enhancement.In particular,various new MRI functional imaging technologies,such as diffusion-weighted imaging,perfusion weighted imaging,delayed imaging,liver cell specific contrast agent enhanced imaging,etc.,can be used at the molecular level Multiple aspects such as cell function provide clinicians with richer diagnostic information.Therefore,further comparative analysis of MRI manifestations and pathological results of liver cancer can help to gain a deeper understanding of the biological behavior of tumors and provide a basis for treatment decision-making and prognosis evaluation.

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.

Sclerosing Mucoepidermoid Cancer: A Unique Entity

Sclerosing mucoepidermoid thyroid cancer (SMECE) is a rare entity with less than 100 cases reported in the literature. Previously considered to have an indolent course, however, recent evidence has reported an aggressive nature ranging from local invasion to distant metastasis. We present a 66-year-old Caucasian female with SMECE who initially presented neck compressive symptoms. A thyroid ultrasound (US) revealed a solid hypoechoic mass replacing the left thyroid lobe. Fine needle aspiration cytology (FNAC) of the nodule resulted in suspicion of Papillary Thyroid Cancer, Bethesda category 5. The patient underwent total thyroidectomy and surgical pathology showed SMECE. Post-therapy whole-body scan following treatment with 150 mCi I-131 showed no residual or metastatic disease. SMECE is more common in females, between the third to eighth decade of life. Preoperative diagnosis may not be accurate given variable cytopathologic features. Differential diagnoses include primary squamous cell carcinoma of the thyroid, squamous differentiation of other thyroid malignancies, anaplastic thyroid cancer and nodular sclerosing variety of Hodgkin’s lymphoma. Due to its rarity, treatment of SMECE has ranged from thyroid surgery without or with radioactive iodine therapy, to surgery and external beam radiation and even chemotherapy.

Prognostic and predictive role of immune microenvironment in colorectal cancer

Colorectal cancer(CRC)represents a molecularly heterogeneous disease and one of the most frequent causes of cancer-related death worldwide.The traditional classification of CRC is based on pathomorphological and molecular character-istics of tumor cells(mucinous,ring-cell carcinomas,etc.),analysis of mechanisms of carcinogenesis involved(chromosomal instability,microsatellite instability,CpG island methylator phenotype)and mutational statuses of commonly altered genes(KRAS,NRAS,BRAF,APC,etc.),as well as expression signatures(CMS 1-4).It is also suggested that the tumor microenvironment is a key player in tumor progression and metastasis in CRC.According to the latest data,the immune microenvironment can also be predictive of the response to immune checkpoint inhibitors.In this review,we highlight how the immune environment influences CRC prognosis and sensitivity to systemic therapy.

Bibliometric analysis of phosphoglycerate kinase 1 expression in breast cancer and its distinct upregulation in triple-negative breast cancer

BACKGROUND Phosphoglycerate kinase 1(PGK1)has been identified as a possible biomarker for breast cancer(BC)and may play a role in the development and advancement of triple-negative BC(TNBC).AIM To explore the PGK1 and BC research status and PGK1 expression and mecha-nism differences among TNBC,non-TNBC,and normal breast tissue.METHODS PGK1 and BC related literature was downloaded from Web of Science Core Co-llection Core Collection.Publication counts,key-word frequency,cooperation networks,and theme trends were analyzed.Normal breast,TNBC,and non-TNBC mRNA data were gathered,and differentially expressed genes obtained.Area under the summary receiver operating characteristic curves,sensitivity and specificity of PGK1 expression were determined.Kaplan Meier revealed PGK1’s prognostic implication.PGK1 co-expressed genes were explored,and Gene Onto-logy,Kyoto Encyclopedia of Genes and Genomes,and Disease Ontology applied.Protein-protein interaction networks were constructed.Hub genes identified.RESULTS PGK1 and BC related publications have surged since 2020,with China leading the way.The most frequent keyword was“Expression”.Collaborative networks were found among co-citations,countries,institutions,and authors.PGK1 expression and BC progression were research hotspots,and PGK1 expression and BC survival were research frontiers.In 16 TNBC vs non-cancerous breast and 15 TNBC vs non-TNBC datasets,PGK1 mRNA levels were higher in 1159 TNBC than 1205 non-cancerous breast cases[standardized mean differences(SMD):0.85,95%confidence interval(95%CI):0.54-1.16,I²=86%,P<0.001].PGK1 expression was higher in 1520 TNBC than 7072 non-TNBC cases(SMD:0.25,95%CI:0.03-0.47,I²=91%,P=0.02).Recurrence free survival was lower in PGK1-high-expression than PGK1-low-expression group(hazard ratio:1.282,P=0.023).PGK1 co-expressed genes were concentrated in ATP metabolic process,HIF-1 signaling,and glycolysis/gluconeogenesis pathways.CONCLUSION PGK1 expression is a research hotspot and frontier direction in the BC field.PGK1 may play a strong role in promoting cancer in TNBC by mediating metabolism and HIF-1 signaling pathways.

Endoscopic and pathological characteristics of de novo colorectal cancer:Retrospective cohort study

BACKGROUND Endoscopy has rapidly developed in recent years and has enabled further investigation into the origin and features of intestinal tumors.The small size and concealed position of these tumors make it difficult to distinguish them from nonneoplastic polyps and carcinoma in adenoma(CIA).The invasive depth and metastatic potential determine the operation regimen,which in turn affects the overall survival and distant prognosis.The previous studies have confirmed the malignant features and clinicopathological features of de novo colorectal cancer(CRC).AIM To provide assistance for diagnosis and treatment,but the lack of a summary of endoscopic features and assessment of risk factors that differ from the CIA prompted us to conduct this retrospective study.METHODS In total,167 patients with small-sized CRCs diagnosed by endoscopy were reviewed.The patients diagnosed as advanced CRCs and other malignant cancers or chronic diseases that could affect distant outcomes were excluded.After screening,63 cases were excluded,including 33 de novo and 30 CIA cases.Patient information,including their follow-up information,was obtained from an electronic His-system.The characteristics between two group and risk factors for invasion depth were analyzed with SPSS 25.0 software.RESULTS Nearly half of the de novo CRCs were smaller than 1 cm(n=16,48.5%)and the majority were located in the distal colon(n=26,78.8%).The IIc type was the most common macroscopic type of de novo CRC.In a Pearson analysis,the differential degree,Sano,JNET,and Kudo types,surrounding mucosa,and chicken skin mucosa(CSM)were correlated with the invasion depth(P<0.001).CSM was a significant risk factor for deep invasion and disturbed judgment of endoscopic ultrasound.A high degree of tumor budding and tumor-infiltrating lymphocytes are accompanied by malignancy.Finally,de novo CRCs have worse outcomes than CIA CRCs.CONCLUSION This is the first comprehensive study to analyze the features of de novo CRCs to distinguish them from nonneoplastic polyps.It is also the first study paying attention to CSM invasive depth measurement.This study emphasizes the high metastatic potential of de novo CRCs and highlights the need for more research on this tumor type.

Identification of a four-miRNA signature predicts the prognosis of papillary thyroid cancer

BACKGROUND In recently diagnosed patients with thyroid cancer,papillary thyroid cancer(PTC),as the most common histological subtype,accounts for 90%of all cases.Although PTC is known as a relatively adolescent malignant disease,there still is a high possibility of recurrence in PTC patients with a poor prognosis.Therefore,new biomarkers are necessary to guide more effective stratification of PTC patients and personalize therapy to avoid overtreatment or inadequate treatment.Accumulating evidence demonstrates that microRNAs(miRNAs)have broad application prospects as diagnostic biomarkers in cancer.AIM To explore novel markers consisting of miRNA-associated signatures for PTC prognostication.METHODS We obtained and analyzed the data of 497 PTC patients from The Cancer Genome Atlas.The patients were randomly assigned to either a training or testing cohort.RESULTS We discovered 237 differentially expressed miRNAs in tumorous thyroid tissues compared with normal tissues,which contained 172 up-regulated and 65 downregulated miRNAs.The evaluation of differently expressed miRNAs was conducted using our risk score model.We then successfully generated a fourmiRNA potential prognostic signature[risk score=(-0.001×hsa-miR-181a-2-3p)+(0.003×hsa-miR-138-5p)+(-0.018×hsa-miR-424-3p)+(0.284×hsa-miR-612)],which reliably distinguished patients from high and low risk with a significant difference in the overall survival(P<0.01)and was effective in predicting the five-year disease survival rate with the area under the receiver operating characteristic curve of 0.937 and 0.812 in the training and testing cohorts,respectively.Additionally,there was a trend indicated that high-risk patients had shorter relapse-free survival,although statistical significance was not reached(P=0.082)in our sequencing cohort.CONCLUSION Our results indicated a four-miRNA signature that has a robust predictive effect on the prognosis of PTC.Accordingly,we would recommend more radical therapy and closer follow-ups for highrisk groups.

Efficacy of anlotinib combined with radioiodine to treat scalp metastasis of papillary thyroid cancer:A case report and review of literature

BACKGROUND Papillary thyroid cancer(PTC)is one of the well-differentiated thyroid tumors.Cutaneous metastasis from differentiated thyroid cancers occurs in<1%of primary thyroid carcinomas but produces the worst survival prognosis.The multi-targeting tyrosine kinase inhibitor anlotinib has been approved to treat refractory advanced non-small-cell lung cancer as well as advanced soft-tissue and clear cell sarcomas in China.CASE SUMMARY In a patient with scalp metastasis caused by PTC,thyroid and skull metastasis tumor sizes were significantly reduced after a trial of neoadjuvant anlotinib therapy for 3 cycles.Anlotinib maintenance medication after thyroidectomy further reduced the metastatic skull tumor size thereby preventing the requirement for craniotomy.CONCLUSION The outcome of the present trial confirmed the potential of anlotinib therapy to treat scalp metastasis induced by PTC and point the way for the treatment of similar diseases in the future.

Artificial intelligence applications in predicting the behavior of gastrointestinal cancers in pathology

Recent research has provided a wealth of data supporting the application of artificial intelligence(AI)-based applications in routine pathology practice.Indeed,it is clear that these methods can significantly support an accurate and rapid diagnosis by eliminating errors,increasing reliability,and improving workflow.In addition,the effectiveness of AI in the pathological evaluation of prognostic parameters associated with behavior,course,and treatment in many types of tumors has also been noted.Regarding gastrointestinal system(GIS)cancers,the contribution of AI methods to pathological diagnosis has been investigated in many studies.On the other hand,studies focusing on AI applications in evaluating parameters to determine tumor behavior are relatively few.For this purpose,the potential of AI models has been studied over a broad spectrum,from tumor subtyping to the identification of new digital biomarkers.The capacity of AI to infer genetic alterations of cancer tissues from digital slides has been demonstrated.Although current data suggest the merit of AI-based approaches in assessing tumor behavior in GIS cancers,a wide range of challenges still need to be solved,from laboratory infrastructure to improving the robustness of algorithms,before incorporating AI applications into real-life GIS pathology practice.This review aims to present data from AI applications in evaluating pathological parameters related to the behavior of GIS cancer with an overview of the opportunities and challenges encountered in implementing AI in pathology.

Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning

BACKGROUND Identifying genetic mutations in cancer patients have been increasingly important because distinctive mutational patterns can be very informative to determine the optimal therapeutic strategy. Recent studies have shown that deep learning-based molecular cancer subtyping can be performed directly from the standard hematoxylin and eosin(H&E) sections in diverse tumors including colorectal cancers(CRCs). Since H&E-stained tissue slides are ubiquitously available, mutation prediction with the pathology images from cancers can be a time-and cost-effective complementary method for personalized treatment.AIM To predict the frequently occurring actionable mutations from the H&E-stained CRC whole-slide images(WSIs) with deep learning-based classifiers.METHODS A total of 629 CRC patients from The Cancer Genome Atlas(TCGA-COAD and TCGA-READ) and 142 CRC patients from Seoul St. Mary Hospital(SMH) were included. Based on the mutation frequency in TCGA and SMH datasets, we chose APC, KRAS, PIK3CA, SMAD4, and TP53 genes for the study. The classifiers were trained with 360 × 360 pixel patches of tissue images. The receiver operating characteristic(ROC) curves and area under the curves(AUCs) for all the classifiers were presented.RESULTS The AUCs for ROC curves ranged from 0.693 to 0.809 for the TCGA frozen WSIs and from 0.645 to 0.783 for the TCGA formalin-fixed paraffin-embedded WSIs.The prediction performance can be enhanced with the expansion of datasets. When the classifiers were trained with both TCGA and SMH data, the prediction performance was improved.CONCLUSION APC, KRAS, PIK3CA, SMAD4, and TP53 mutations can be predicted from H&E pathology images using deep learning-based classifiers, demonstrating the potential for deep learning-based mutation prediction in the CRC tissue slides.

Intratumoral Bacteria Dysbiosis Is Associated with Human Papillary Thyroid Cancer and Correlated with Oncogenic Signaling Pathways

Emerging evidence suggests that microbial dysbiosis plays vital roles in many human cancers.However,knowledge of whether the microbial community in thyroid tumor is related to tumorigenesis remains elusive.In this study,we aimed to explore the microbial community in thyroid tissues and its contribution to papillary thyroid cancer(PTC).In parallel,we performed microbial profiling and transcriptome sequencing in the tumor and adjacent normal tissues of a large cohort of 340 PTC and benign thyroid nodule(BTN)patients.Distinct microbial signatures were identified in PTC,BTN,and their adjacent nontumor tissues.Intra-thyroid tissue bacteria were verified by means of bacteria staining,fluorescence in situ hybridization,and immunoelectron microscopy.We found that 17 bacterial taxa were differentially abundant in PTC compared with BTN,which included enrichment in PTC of the pathobionts Rhodococcus,Neisseria,Streptococcus,Halomonas,and Devosia,and depletion of the beneficial bacteria Amycolatopsis.These differentially abundant bacteria could differentiate PTC tumor tissues(PTC-T)from BTN tissues(BTN-T)with an area under the curve(AUC)of 81.66%.Microbial network analysis showed increased correlation strengths among the bacterial taxa in PTC-T in comparison with BTN-T.Immunefunction-corresponding bacteria(i.e.,Erwinia,Bacillus,and Acinetobacter)were found to be enriched in PTC with Hashimoto’s thyroiditis.Moreover,our integrative analysis revealed that the PTC-enriched bacteria had a positive association with key PTC-oncogenic pathway-related genes,including BRAF,KRAS,IRAK4,CTNNB1,PIK3CA,MAP3K7,and EGFR.In conclusion,our results suggest that intratumor bacteria dysbiosis is associated with the thyroid tumorigenesis and oncogenic signaling pathways of PTC.

Synchronous manifestation of colorectal cancer and intraductal papillary mucinous neoplasms

High rates of extrapancreatic malignancies,in particular colorectal cancer(CRC),have been detected in patients with intraductal papillary mucinous neoplasm(IPMN).So far,there is no distinct explanation in the literature for the development of secondary or synchronous malignancies in patients with IPMN.In the past few years,some data related to common genetic alterations in IPMN and other affiliated cancers have been published.This review elucidated the association between IPMN and CRC,shedding light on the most relevant genetic alterations that may explain the possible relationship between these entities.In keeping with our findings,we suggested that once the diagnosis of IPMN is made,special consideration of CRC should be undertaken.Presently,there are no specific guidelines regarding colorectal screening programs for patients with IPMN.We recommend that patients with IPMNs are at high-risk for CRC,and a more rigorous colorectal surveillance program should be implemented.

Detecting circulating tumor material and digital pathology imaging during pancreatic cancer progression

Pancreatic cancer(PC) is a leading cause of cancerrelated death worldwide. Clinical symptoms typically present late when treatment options are limited and survival expectancy is very short. Metastatic mutations are heterogeneous and can accumulate up to twenty years before PC diagnosis. Given such genetic diversity, detecting and managing the complex states of disease progression may be limited to imaging modalities and markers present in circulation. Recent developments in digital pathology imaging show potential for early PC detection, making a differential diagnosis, and predicting treatment sensitivity leading to long-term survival in advanced stage patients. Despite large research efforts, the only serum marker currently approved for clinical use is CA 19-9. Utility of CA 19-9 has been shown to improve when it is used in combination with PC-specific markers. Efforts are being made to develop early-screening assays that can detect tumor-derived material, present in circulation, before metastasis takes a significant course. Detection of markers that identify circulating tumor cells and tumor-derived extracellular vesicles(EVs) in biofluid samples offers a promising non-invasive method for this purpose. Circulating tumor cells exhibit varying expression of epithelial and mesenchymal markers depending on the state of tumor differentiation. This offers a possibility for monitoring disease progression using minimally invasive procedures. EVs also offer the benefit of detecting molecular cargo of tumor origin and add the potential to detect circulating vesicle markers from tumors that lack invasive properties. This review integrates recent genetic insights of PC progression with developments in digitalpathology and early detection of tumor-derived circulating material.

Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach

BACKGROUND Studies correlating specific genetic mutations and treatment response are ongoing to establish an effective treatment strategy for gastric cancer(GC).To facilitate this research,a cost-and time-effective method to analyze the mutational status is necessary.Deep learning(DL)has been successfully applied to analyze hematoxylin and eosin(H and E)-stained tissue slide images.AIM To test the feasibility of DL-based classifiers for the frequently occurring mutations from the H and E-stained GC tissue whole slide images(WSIs).METHODS From the GC dataset of The Cancer Genome Atlas(TCGA-STAD),wildtype/mutation classifiers for CDH1,ERBB2,KRAS,PIK3CA,and TP53 genes were trained on 360×360-pixel patches of tissue images.RESULTS The area under the curve(AUC)for the receiver operating characteristic(ROC)curves ranged from 0.727 to 0.862 for the TCGA frozen WSIs and 0.661 to 0.858 for the TCGA formalin-fixed paraffin-embedded(FFPE)WSIs.The performance of the classifier can be improved by adding new FFPE WSI training dataset from our institute.The classifiers trained for mutation prediction in colorectal cancer completely failed to predict the mutational status in GC,indicating that DL-based mutation classifiers are incompatible between different cancers.CONCLUSION This study concluded that DL could predict genetic mutations in H and E-stained tissue slides when they are trained with appropriate tissue data.

Breast Cancer in a Supernumerary Breast at the Yaoundé Gynaeco-Obstetric and Paediatric Hospital: About a Case

Accessory or ectopic breast tissue is an anomaly in the development of the breast. It is a rare condition that occurs along the embryological mammary line. In less than 1% of all breast cancers, supernumerary breast cancer is reported, with the axillary location being the most common in 60% to 90% of cases. Cancerous degeneration of this supernumerary breast tissue can pose a dual diagnostic and therapeutic problem. We report the case of locally advanced adenocarcinoma in a right supernumerary breast. This is a 75-year-old, grand-multiparous, postmenopausal, and known hypertensive patient on treatment. Family history was remarkable for brain cancer in her sister and oesophageal cancer in her mother. She consulted for a mass in the right axillary cavity on supernumerary breast evolving for a year. Clinical examination revealed a large, fixed, budding and haemorrhagic-ulcerated mass of the right axilla, with long axis measuring about 15 cm. There was as wella supernumerary breast on the left, but without particularity. A soft tissue ultrasound showed a large hypoechoicmass in the right axillary region of 116 mm with areas of central necrobiosis. Morphologically, the breasts were normal. A breast MRI revealed a subcutaneous mass in the right axillary cavity with skin ulceration and satellite lymphadenopathy. The extension assessment revealed liver metastases, and a biopsy of the mass revealed a breast adenocarcinoma. The case was the subject of a multidisciplinary consultation meeting following which a wide excision of the mass was indicated. The histo-pathology analysis results of the surgical specimen were in favour of a triple negative papillary adenocarcinoma. After a post-operative multidisciplinary consultation meeting, adjuvant chemotherapy was indicated. The development of supernumerary breasts depends on hormones, just like normal breasts. Breast cancer in accessory breast tissue is quite rare with the incidence being 6%. The most common pathology is invasive carcinoma (50% - 75%). It is usually located in the armpit (60% - 70%) although it can be present in other less common locations such as the inframammary region (5% - 10%) and rarely the thighs, perineum, groin and the vulva. Since accessory axillary breast tissue is not considered during breast screening examination, it is necessary for clinicians to be aware of this entity and associated pathologies. Their preventive excision in women at high risk can also be considered.

What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?

The present study aimed to explore the potential of artificial intelligence(AI)methodology based on magnetic resonance(MR)images to aid in the management of prostate cancer(PCa).To this end,we reviewed and summarized the studies comparing the diagnostic and predictive performance for PCa between AI and common clinical assessment methods based on MR images and/or clinical characteristics,thereby investigating whether AI methods are generally superior to common clinical assessment methods for the diagnosis and prediction fields of PCa.First,we found that,in the included studies of the present study,AI methods were generally equal to or better than the clinical assessment methods for the risk assessment of PCa,such as risk stratification of prostate lesions and the prediction of therapeutic outcomes or PCa progression.In particular,for the diagnosis of clinically significant PCa,the AI methods achieved a higher summary receiver operator characteristic curve(SROC-AUC)than that of the clinical assessment methods(0.87 vs.0.82).For the prediction of adverse pathology,the AI methods also achieved a higher SROC-AUC than that of the clinical assessment methods(0.86 vs.0.75).Second,as revealed by the radiomics quality score(RQS),the studies included in the present study presented a relatively high total average RQS of 15.2(11.0–20.0).Further,the scores of the individual RQS elements implied that the AI models in these studies were constructed with relatively perfect and standard radiomics processes,but the exact generalizability and clinical practicality of the AI models should be further validated using higher levels of evidence,such as prospective studies and open-testing datasets.