HER2 Positive Gastric and Gastroesophageal Adenocarcinoma: A Tertiary Center Experience in (NICRH) Bangladesh

Background: Gastric cancer is the fourth commonest cancer worldwide. It is also recognized as the second commonest cause of cancer related death in the global perspective. Although the incidence of gastric cancer has gradually decreased over the last half of the century, it varies among the different part of the world and different ethnic group. Mortality from gastric cancer extremely high, and it is second only to lung cancer. Gastric cancer occurs more frequently in men than in women. Aim of the study: Aim of the study was to find the clinic-profile outcome HER2 Positive Gastric and Gastroesophageal Adenocarcinoma.Methods:This cross sectional study was conducted in the Department of Surgical Oncology of National Institute of Cancer, Research and Hospital, Mohakhali, Dhaka. The study period was from March, 2014 to April, 2015. A total of 80 patients were included for the study. After receiving the gastrectomy specimen, it was fixed in 10% formaldehyde. Data were compiled and necessary statistical analysis were carried out using computer based software package for social science (SPSS 16.1). Ethical clearance was taken from the ethical committee of NICRH.Results:The highest patients were from 61-70 years’ age group and the lowest were from 71-80 years. The mean age of the patients was 59.71 (±10.19) years. The female to male ratio in this study was 1: 2.48. 66 (82.5%) patients were presented with anemia which was followed by 39 (48.75%) cases with dehydration. Most of the tumors were located in the distal part of the stomach (11.67%). Regarding staging 79(12.65%) patients were in the advanced stage of the disease. The correlation between HER2 overexpression and TNM staging has been tabulated below where it is shown that only Nodal (N) staging has the significant correlation with the HER2 overexpression.Conclusion:It is already mentioned that, in early history of immunohistochemistry, HER2 overexpression in case of carcinoma stomach was highly varied in different studies (from 9-92%). But recently, it was found around 9-32%, in several studies all over the world. It is necessary to conduct further studies with larger samples and long term follow-up in order to draw definite conclusions regarding the role of HER2/neu overexpression.

Pancreatic ductal adenocarcinoma: Prognostic indicators of advanced disease

Background/Objectives Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy associated with high metastatic risk. Prognosis remains poor even after resection. Previously our group identified biomarkers that improved diagnostic accuracy in PDAC beyond the established diagnostic tumour marker, CA19-9. Risk factors, symptoms and circulating biomarkers associated with a PDAC diagnosis may differ from those that alter disease progression and metastasis. This study aimed at assessing the risk factors, presenting symptoms and potential prognostic biomarkers in PDAC and determine their relationship with PDAC stage and/or metastatic status. Methods Seventy-two PDAC patients with imaging available for TNM staging at presentation were enrolled following informed consent. Demographic and clinical data were captured. Blood was collected and 38 cytokines/angiogenic factors measured. Nonparametric association tests, univariate and multivariate logistic regression were performed using STATA version 14.2. A p-value≤0.05 was considered significant and odds ratios reported for effect size. Results Most risk factors and symptoms did not differ across the stages of cancer. Although male gender and smoking are risk factors for PDAC, the majority of study patients with metastatic PDAC were non-smoking females. In addition to CA19-9, the platelet count (p<0.01), IL-15 (p = 0.02) and GM-CSF (p<0.01) were significant, independent negative predictors of metastatic PDAC. Moreover, using specific cut-off values in a combined panel, the odds in a patient with all three biomarker levels below the cut-offs is 21 times more likely to have metastatic PDAC (p<0.0001). Conclusions Platelet count, IL-15 and GM-CSF are potential prognostic indicators of metastatic disease in PDAC patients from our local South African population.

Tumor infiltrating lymphocyte stratification of prognostic staging of early-stage triple negative breast cancer

The importance of integrating biomarkers into the TNM staging has been emphasized in the 8th Edition of the American Joint Committee on Cancer (AJCC) Staging system. In a pooled analysis of 2148 TNBC-patients in the adjuvant setting, TILs are found to strongly up and downstage traditional pathological-staging in the Pathological and Clinical Prognostic Stage Groups from the AJJC 8th edition Cancer Staging System. This suggest that clinical and research studies on TNBC should take TILs into account in addition to stage, as for example patients with stage II TNBC and high TILs have a better outcome than patients with stage I and low TILs.

Concurrence of Marjolin’s Ulcer in the Lower Limb in a Patient with Idiopathic Multicentric Castleman Disease: A Case Report

Idiopathic multicentric Castleman disease (iMCD) is characterized by the benign proliferation of lymphoid cells in multiple regions. However, the co-occurrence of epithelial malignancy and idiopathic multicentric Castleman disease (iMCD) is rarely reported. Herein, we present a case of iMCD mimicking lymph nodal metastasis of Marjolin’s ulcer in the lower extremity. A 53-year-old male presented with an unhealed chronic ulcer on the left lower leg and foot accompanied by an enlarged mass in the left inguinal region. Intralesional biopsy was performed, and pathological examination showed squamous cell carcinoma (SCC). Imaged studies revealed left calcaneus bone invasion, and lymph nodal metastasis was suspected by the cancer TNM staging of T4N2M0 pre-operatively. The patient received below-knee amputation and lymph node dissection; intraoperative histological examination showed no lymphatic nodal malignancy and diagnosed the patient as having iMCD with lymphadenopathy. The patient recovered uneventfully and was referred to a hematologist for further treatment.

CLUSTER ANALYSIS IDENTIFIES VARIABLES RELATED TO PROGNOSIS OF BREAST CANCER DISEASE

This work presents a cluster analysis approach aiming to determine distinct groups based on clinicopathological data from patients with breast cancer (BC). For this purpose, the clinical variables were considered: age at diagnosis, weight, height, lymph nodal invasion (LN), tumor-node-metastasis (TNM) staging and body mass index (BMI). Ward's hierarchical clustering algorithm was used to form specific groups. Based on this, BC patients were separated into four groups. The Kruskal-Wallis test was performed to assess the differences among the clusters. The intensity of the influence of variables on the prognosis of BC was also evaluated by calculating the Spearman's correlation. Positive correlations were obtained between weight and BMI, TNM and LN invasion in all analyzes. Negative correlations between BMI and height were obtained in some of the analyzes. Finally, a new correlation was obtained, based on this approach, between weight and TNM, demonstrating that the trophic-adipose status of BC patients can be directly related to disease staging.

Indication to postoperative radiotherapy for oral cavity squamous cell carcinoma: what’s new in the Depth of Infiltration (DOI) era?

Objectives: The last edition of the American Joint Committee on Cancer (AJCC eighth) has introduced the depth of infiltration (DOI) as a new prognostic parameter in oral cavity squamous cell carcinomas (OCSCCs). Aim of this study is to analyze the impact of stage migration on the indication to postoperative radiotherapy (PORT). Methods: OCSCCs treated at two Institutions between 2014 and 2019 were retrieved. Per the AJCC eighth, only pT3 primarily OCSCCs were considered; availability of the pathologic specimen was a further inclusion criterion. Risk factors considered for PORT were: pT3-pT4, nodal involvement, positive/close surgical margins, perineural and lymph vascular invasion. Results: One-hundred forty-nine patients staged as pT3 AJCC eighth were included. A four-fold increase in the number of patients staged as pT3 from the seventh to the eighth AJCC was found. Stage migration to pT3 was equally due to the downstaging from former pT4 (38%) and upstaging of former pT1-pT2 (35%). Considering the former pT1-pT2 53 patients, 13 (25%) had no risk factors for PORT other than DOI. Among 25 cases with former pT1-pT2 and negative lymph nodes no additional risk factors were found in 11 (44%). Conclusion: Ninety percent of patients had at least one risk factor besides DOI and would have received PORT also according to the AJCC seventh; notably, of former pT1-pT2N0, half of them have been upstaged to pT3 in the current TNM classification. The role of PORT in this cohort of patients has not been clarified yet. Advances in knowledge: Other-than-DOI risk factors leading to PORT indication are highly prevalent in OCSSC patients classified as pT3 per the latest AJCC TNM staging system and should therefore be considered for a comprehensive oncological assessment.

Deep Learning-Based Magnetic Resonance Imaging in the Evaluation of Tumor, Node, and Metastasis Staging of Renal Cancer

This study was aimed to investigate the diagnostic accuracy of magnetic resonance imaging (MRI) based on deep dictionary learning in TNM (tumor, node, and metastasis) staging of renal cell carcinoma. In this study, 82 patients with renal cancer were selected as the research object. The results were diagnosed by deep dictionary learning MRI, and TNM staging was performed by professional imaging personnel. MRI image will be reconstructed after deep dictionary learning to improve its image recognition ability. The pathological diagnosis will be handed over to the physiological pathology laboratory of the hospital for diagnosis. The staging results were compared with the pathological diagnostic staging results, and the results were analyzed by consistency statistics to evaluate the diagnostic value. The results showed that T staging was significantly consistent with the pathological diagnosis. 2 cases were misdiagnosed, and the accuracy rate was 97.56%. Compared with the pathological diagnosis, N staging had less obvious consistency. 10 cases were misdiagnosed, and the accuracy rate was 87.80%. M staging was significantly consistent with the pathological diagnosis. 4 cases were misdiagnosed. The accuracy rate was 95.12%. After laparotomy, it was found that 37 patients had emboli and 45 patients had no emboli, while 40 patients had emboli and 42 patients had no emboli by MRI. The accuracy rate was 96.34%. The results showed that in the evaluation of TNM staging by MRI imaging based on deep dictionary learning in patients with renal cell carcinoma, the diagnostic results of N staging and M staging were highly consistent with the pathological diagnosis, while the diagnostic results of T staging were slightly less accurate, and the diagnostic consistency was good. The results can provide effective support for the clinical application of MRI imaging based on deep dictionary learning as the clinical diagnosis of TNM staging of renal cell carcinoma.

Pathological Features and Prognostication in Colorectal Cancer

The prognostication of colorectal cancer (CRC) has traditionally relied on staging as defined by the Union for International Cancer Control (UICC) and American Joint Committee on Cancer (AJCC) TNM staging classifications. However, clinically, there appears to be differences in survival patterns independent of stage, suggesting a complex interaction of stage, pathological features, and biomarkers playing a role in guiding prognosis, risk stratification, and guiding neoadjuvant and adjuvant therapies. Histological features such as tumour budding, perineural invasion, apical lymph node involvement, lymph node yield, lymph node ratio, and molecular features such as MSI, KRAS, BRAF, and CDX2 may assist in prognostication and optimising adjuvant treatment. This study provides a comprehensive review of the pathological features and biomarkers that are important in the prognostication and treatment of CRC. We review the importance of pathological features and biomarkers that may be important in colorectal cancer based on the current evidence in the literature.

A Model Based on Artificial Intelligence Algorithm for Monitoring Recurrence of HCC after Hepatectomy

Background There is no satisfactory indicator for monitoring recurrence after resection of hepatocellular carcinoma (HCC). This retrospective study aimed to design and validate an HCC monitor recurrence (HMR) model for patients without metastasis after hepatectomy. Methods A training cohort was recruited from 1179 patients with HCC without metastasis after hepatectomy between February 2012 and December 2015. An HMR model was developed using an AdaBoost classifier algorithm. The factors included patient age, TNM staging, tumor size, and pre/postoperative dynamic variations of alpha-fetoprotein (AFP). The diagnostic efficacy of the model was evaluated based on the area under the receiver operating characteristic curves (AUCs). The model was validated using a cohort of 695 patients. Results In preoperative patients with positive or negative AFP, the AUC of the validation cohort in the HMR model was .8877, which indicated better diagnostic efficacy than that of serum AFP (AUC, .7348). The HMR model predicted recurrence earlier than computed tomography/magnetic resonance imaging did by 191.58 ± 165 days. In addition, the HMR model can predict the prognosis of patients with HCC after resection. Conclusions The HMR model established in this study is more accurate than serum AFP for monitoring recurrence after hepatectomy for HCC and can be used for real-time monitoring of the postoperative status in patients with HCC without metastasis.