The invasive lobular carcinoma as a prototype luminal A breast cancer: A retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>Although the invasive lobular carcinoma (ILC) is the second most frequent histologic subtype in Western countries, its incidence is much lower in Asia, and its characteristics are less well known.</p> <p>Methods</p> <p>We assessed the clinical characteristics and outcomes of 83 Korean patients (2.8%) with ILC for comparison with 2,833 (97.2%) with the invasive ductal carcinoma (IDC), including 1,088 (37.3%) with the luminal A subtype (LA-IDC).</p> <p>Results</p> <p>The mean age of all patients was 48.2 years, with no significant differences among the groups. Compared to IDC, ILC showed a larger tumor size (≥T2, 59.8% vs. 38.8%, <it>P </it>= 0.001), a lower histologic grade (HG 1/2, 90.4% vs. 64.4%, <it>P </it>< 0.001), more frequent estrogen receptor positive (90.4% vs. 64.4%, <it>P </it>< 0.001), progesterone receptor positive (71.1% vs. 50.1%, <it>P </it>< 0.001) and HER2 negative (97.5% vs. 74.6%, <it>P </it>< 0.001) status, and lower Ki-67 expression (10.3% ± 10.6% vs. 20.6% ± 19.8%, <it>P </it>< 0.001), as well as being more likely to be of the luminal A subtype (91.4% vs. 51.2%, <it>P </it>< 0.001). Six (7.2%) ILC and 359 (12.7%) IDC patients developed disease recurrence, with a median follow-up of 56.4 (range 4.9-136.6) months. The outcome of ILC was close to LA-IDC (HR 0.77 for recurrence, 95% CI 0.31-1.90, <it>P </it>= 0.57; HR 0.75 for death, 95% CI 0.18-3.09, <it>P </it>= 0.70) and significantly better than for the non-LA-IDC (HR 1.69 for recurrence, 95% CI 1.23-2.33, <it>P </it>= 0.001; HR 1.50 for death, 95% CI 0.97-2.33, <it>P </it>= 0.07).</p> <p>Conclusions</p> <p>ILC, a rare histologic type of breast cancer in Korea, has distinctive clinicopathological characteristics similar to those of LA-IDC.</p

Cinnamon extract induces tumor cell death through inhibition of NFκB and AP1

<p>Abstract</p> <p>Background</p> <p><it>Cinnamomum cassia </it>bark is the outer skin of an evergreen tall tree belonging to the family Lauraceae containing several active components such as essential oils (cinnamic aldehyde and cinnamyl aldehyde), tannin, mucus and carbohydrate. They have various biological functions including anti-oxidant, anti-microbial, anti-inflammation, anti-diabetic and anti-tumor activity. Previously, we have reported that anti-cancer effect of cinnamon extracts is associated with modulation of angiogenesis and effector function of CD8⁺T cells. In this study, we further identified that anti-tumor effect of cinnamon extracts is also link with enhanced pro-apoptotic activity by inhibiting the activities NFκB and AP1 in mouse melanoma model.</p> <p>Methods</p> <p>Water soluble cinnamon extract was obtained and quality of cinnamon extract was evaluated by HPLC (High Performance Liquid Chromatography) analysis. In this study, we tested anti-tumor activity and elucidated action mechanism of cinnamon extract using various types of tumor cell lines including lymphoma, melanoma, cervix cancer and colorectal cancer <it>in vitro </it>and <it>in vivo </it>mouse melanoma model.</p> <p>Results</p> <p>Cinnamon extract strongly inhibited tumor cell proliferation <it>in vitro </it>and induced active cell death of tumor cells by up-regulating pro-apoptotic molecules while inhibiting NFκB and AP1 activity and their target genes such as <it>Bcl-2</it>, <it>BcL-xL </it>and <it>survivin</it>. Oral administration of cinnamon extract in melanoma transplantation model significantly inhibited tumor growth with the same mechanism of action observed <it>in vitro</it>.</p> <p>Conclusion</p> <p>Our study suggests that anti-tumor effect of cinnamon extracts is directly linked with enhanced pro-apoptotic activity and inhibition of NFκB and AP1 activities and their target genes <it>in vitro </it>and <it>in vivo </it>mouse melanoma model. Hence, further elucidation of active components of cinnamon extract could lead to development of potent anti-tumor agent or complementary and alternative medicine for the treatment of diverse cancers.</p

Regulation of Inhibitors of Differentiation Family Proteins by Thyroid-Stimulating Hormone in FRTL-5 Thyroid Cells

Members of the inhibitors of differentiation (Id) family of helix-loop-helix (HLH) proteins are known to play important roles in the proliferation and differentiation of many cell types. Thyroid-stimulating hormone (TSH) regulates proliferation and differentiation by activating TSH receptor (TSHR) in thyrocytes. In this study, we found that Id2, one of the Id family proteins, is a major target for regulation by TSH in FRTL-5 thyroid cells. TSH rapidly increases the Id2 mRNA level in FRTL-5 thyroid cells but the Id2 protein showed biphasic regulatory patterns, being transiently reduced and subsequently induced by TSH treatment. Transient reduction of Id2 protein was noted within 2 hr of TSH treatment and was mediated by proteasomal degradation. Moreover, reduced Id2 expression correlated with the activity of the phosphatidylinositol 3 kinase pathway, which is activated by TSH. Although TSH increases the activity of the Id2 promoter, TSH-induced activation of this promoter was independent of c-Myc. Id2 did not alter TTF-1- and Pax-8-mediated effects on the regulation of the Tg promoter. Thus, in summary, we found that TSH regulates Id2 expression, but that Id2 does not alter the expression of thyroid-specific genes, such as Tg, in FRTL-5 thyroid cells

Protein and lipid MALDI profiles classify breast cancers according to the intrinsic subtype

<p>Abstract</p> <p>Background</p> <p>Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) has been demonstrated to be useful for molecular profiling of common solid tumors. Using recently developed MALDI matrices for lipid profiling, we evaluated whether direct tissue MALDI MS analysis on proteins and lipids may classify human breast cancer samples according to the intrinsic subtype.</p> <p>Methods</p> <p>Thirty-four pairs of frozen, resected breast cancer and adjacent normal tissue samples were analyzed using histology-directed, MALDI MS analysis. Sinapinic acid and 2,5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify lipid profiles, and mass spectra were acquired using a MALDI-time of flight instrument.</p> <p>Results</p> <p>Protein and lipid profiles distinguish cancer from adjacent normal tissue samples with the median prediction accuracy of 94.1%. Luminal, HER2+, and triple-negative tumors demonstrated different protein and lipid profiles, as evidenced by permutation <it>P </it>values less than 0.01 for 0.632+ bootstrap cross-validated misclassification rates with all classifiers tested. Discriminatory proteins and lipids were useful for classifying tumors according to the intrinsic subtype with median prediction accuracies of 80.0-81.3% in random test sets.</p> <p>Conclusions</p> <p>Protein and lipid profiles accurately distinguish tumor from adjacent normal tissue and classify breast cancers according to the intrinsic subtype.</p

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Background: Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. // Methods: We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung's disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. // Findings: We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung's disease) from 264 hospitals (89 in high-income countries, 166 in middle-income countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in low-income countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. // Interpretation: Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between low-income, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Predicting delirium and the effects of medications in hospitalized COVID-19 patients using machine learning: A retrospective study within the Korean Multidisciplinary Cohort for Delirium Prevention (KoMCoDe)

Objective Delirium is commonly reported from the inpatients with Coronavirus disease 2019 (COVID-19) infection. As delirium is closely associated with adverse clinical outcomes, prediction and prevention of delirium is critical. We developed a machine learning (ML) model to predict delirium in hospitalized patients with COVID-19 and to identify modifiable factors to prevent delirium. Methods The data set (n = 878) from four medical centers was constructed. Total of 78 predictors were included such as demographic characteristics, vital signs, laboratory results and medication, and the primary outcome was delirium occurrence during hospitalization. For analysis, the extreme gradient boosting (XGBoost) algorithm was applied, and the most influential factors were selected by recursive feature elimination. Among the indicators of performance for ML model, the area under the curve of the receiver operating characteristic (AUROC) curve was selected as the evaluation metric. Results Regarding the performance of developed delirium prediction model, the accuracy, precision, recall, F1 score, and the AUROC were calculated (0.944, 0.581, 0.421, 0.485, 0.873, respectively). The influential factors of delirium in this model included were mechanical ventilation, medication (antipsychotics, sedatives, ambroxol, piperacillin/tazobactam, acetaminophen, ceftriaxone, and propacetamol), and sodium ion concentration (all p  < 0.05). Conclusions We developed and internally validated an ML model to predict delirium in COVID-19 inpatients. The model identified modifiable factors associated with the development of delirium and could be clinically useful for the prediction and prevention of delirium in COVID-19 inpatients