Intrahepatic Biliary Cystadenoma Presenting with Obstructive Jaundice

Biliary cystadenoma (BCA) is a rare neoplasm of the bile duct with malignant potential. We report a case of intrahepatic BCA with an unusual presentation of obstructive jaundice. Computed tomography scan of the abdomen revealed a dilated common bile duct and intrahepatic ducts with internal septa. Endoscopic retrograde cholangiography showed an oval filling defect in the bile duct causing the obstruction. At laparotomy, this proved to be a multiloculated mucinous polyp in the common bile duct, with its origin in the left intrahepatic duct, detected using intraoperative choledochoscopy. A left hemihepatectomy was performed, and histology confirmed intrahepatic mucinous BCA with mesenchymal stroma. The imaging process and surgical options for BCA are discussed

Brain-derived neurotrophic factor genetic polymorphism (rs6265) is protective against chemotherapy-associated cognitive impairment in patients with early-stage breast cancer.

BackgroundBrain-derived neurotrophic factor (BDNF), a neurotrophin that regulates neuronal function and development, is implicated in several neurodegenerative conditions. Preliminary data suggest that a reduction of BDNF concentrations may lead to postchemotherapy cognitive impairment. We hypothesized that a single nucleotide polymorphism (rs6265) of the BDNF gene may predispose patients to cognitive impairment. This study aimed to evaluate the effect of BDNF gene polymorphism on chemotherapy-associated cognitive impairment.MethodsOverall, 145 patients receiving chemotherapy for early-stage breast cancer (mean age: 50.8 ± 8.8 y; 82.1% Chinese) were recruited. Patients' cognitive functions were assessed longitudinally using the validated Functional Assessment of Cancer Therapy-Cognitive Function (v.3) and an objective computerized tool, Headminder. Genotyping was performed using Sanger sequencing. Logistic regression was used to evaluate the association between BDNF Val66Met polymorphism and cognition after adjusting for ethnicity and clinically important covariates.ResultsOf the 145 patients, 54 (37%) reported cognitive impairment postchemotherapy. The Met/Met genotype was associated with statistically significant lower odds of developing cognitive impairment (odds ratio [OR] = 0.26; 95% CI: 0.08-0.92; P = .036). The Met carriers were less likely to experience impairment in the domains of verbal fluency (OR = 0.34; 95% CI: 0.12-0.90; P = .031) and multitasking ability (OR = 0.37; 95% CI: 0.15-0.91; P = .030) compared with the Val/Val homozygote. No associations were observed between Headminder and the BDNF Val66Met polymorphism.ConclusionsThis is the first study to provide evidence that carriers of the BDNF Met allele are protected against chemotherapy-associated cognitive impairment. Further studies are required to validate the findings

Brain-derived neurotrophic factor genetic polymorphism (rs6265) is protective against chemotherapy-associated cognitive impairment in patients with early-stage breast cancer

BACKGROUND: Brain-derived neurotrophic factor (BDNF), a neurotrophin that regulates neuronal function and development, is implicated in several neurodegenerative conditions. Preliminary data suggest that a reduction of BDNF concentrations may lead to postchemotherapy cognitive impairment. We hypothesized that a single nucleotide polymorphism (rs6265) of the BDNF gene may predispose patients to cognitive impairment. This study aimed to evaluate the effect of BDNF gene polymorphism on chemotherapy-associated cognitive impairment. METHODS: Overall, 145 patients receiving chemotherapy for early-stage breast cancer (mean age: 50.8 ± 8.8 y; 82.1% Chinese) were recruited. Patients' cognitive functions were assessed longitudinally using the validated Functional Assessment of Cancer Therapy–Cognitive Function (v.3) and an objective computerized tool, Headminder. Genotyping was performed using Sanger sequencing. Logistic regression was used to evaluate the association between BDNF Val66Met polymorphism and cognition after adjusting for ethnicity and clinically important covariates. RESULTS: Of the 145 patients, 54 (37%) reported cognitive impairment postchemotherapy. The Met/Met genotype was associated with statistically significant lower odds of developing cognitive impairment (odds ratio [OR] = 0.26; 95% CI: 0.08–0.92; P = .036). The Met carriers were less likely to experience impairment in the domains of verbal fluency (OR = 0.34; 95% CI: 0.12–0.90; P = .031) and multitasking ability (OR = 0.37; 95% CI: 0.15–0.91; P = .030) compared with the Val/Val homozygote. No associations were observed between Headminder and the BDNF Val66Met polymorphism. CONCLUSIONS: This is the first study to provide evidence that carriers of the BDNF Met allele are protected against chemotherapy-associated cognitive impairment. Further studies are required to validate the findings

A Circulating miRNA Signature for Stratification of Breast Lesions among Women with Abnormal Screening Mammograms

Although mammography is the gold standard for breast cancer screening, the high rates of false-positive mammograms remain a concern. Thus, there is an unmet clinical need for a non-invasive and reliable test to differentiate between malignant and benign breast lesions in order to avoid subjecting patients with abnormal mammograms to unnecessary follow-up diagnostic procedures. Serum samples from 116 malignant breast lesions and 64 benign breast lesions were comprehensively profiled for 2,083 microRNAs (miRNAs) using next-generation sequencing. Of the 180 samples profiled, three outliers were removed based on the principal component analysis (PCA), and the remaining samples were divided into training (n = 125) and test (n = 52) sets at a 70:30 ratio for further analysis. In the training set, significantly differentially expressed miRNAs (adjusted p < 0.01) were identified after correcting for multiple testing using a false discovery rate. Subsequently, a predictive classification model using an eight-miRNA signature and a Bayesian logistic regression algorithm was developed. Based on the receiver operating characteristic (ROC) curve analysis in the test set, the model could achieve an area under the curve (AUC) of 0.9542. Together, this study demonstrates the potential use of circulating miRNAs as an adjunct test to stratify breast lesions in patients with abnormal screening mammograms

Multi-center evaluation of artificial intelligent imaging and clinical models for predicting neoadjuvant chemotherapy response in breast cancer

Background: Neoadjuvant chemotherapy (NAC) plays an important role in the management of locally advanced breast cancer. It allows for downstaging of tumors, potentially allowing for breast conservation. NAC also allows for in-vivo testing of the tumors’ response to chemotherapy and provides important prognostic information. There are currently no clearly defined clinical models that incorporate imaging with clinical data to predict response to NAC. Thus, the aim of this work is to develop a predictive AI model based on routine CT imaging and clinical parameters to predict response to NAC. Methods: The CT scans of 324 patients with NAC from multiple centers in Singapore were used in this study. Four different radiomics models were built for predicting pathological complete response (pCR): first two were based on textural features extracted from peri-tumoral and tumoral regions, the third model based on novel space-resolved radiomics which extract feature maps using voxel-based radiomics and the fourth model based on deep learning (DL). Clinical parameters were included to build a final prognostic model. Results: The best performing models were based on space-resolved and DL approaches. Space-resolved radiomics improves the clinical AUCs of pCR prediction from 0.743 (0.650 to 0.831) to 0.775 (0.685 to 0.860) and our DL model improved it from 0.743 (0.650 to 0.831) to 0.772 (0.685 to 0.853). The tumoral radiomics model performs the worst with no improvement of the AUC from the clinical model. The peri-tumoral combined model gives moderate performance with an AUC of 0.765 (0.671 to 0.855). Conclusions: Radiomics features extracted from diagnostic CT augment the predictive ability of pCR when combined with clinical features. The novel space-resolved radiomics and DL radiomics approaches outperformed conventional radiomics techniques.W.L.N. is supported by the National Medical Research Council Fellowship (NMRC/MOH-000166-00)

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer

10.3390/cancers13092130CANCERS13