COMPARATIVE STUDY OF CLINICOPATHOLOGICAL FEATURES AND PROGNOSIS IN TRIPLE NEGATIVE AND NON-TRIPLE NEGATIVE BREAST CANCER IN THE NORTH OF MOROCCO

Breast cancer is a heterogeneous disease that can be classified into diverse subtypes with distinct biology and prognosis. The purpose of this study is to compare clinicopathological features and prognostic of patients with Triple Negative Breast Cancer (TNBC) and non-TNBC. Clinicopathological features and prognosis of 266 patients from north Morocco (56 TNBC and 210 non-TNBC) were evaluated using SPSS 20 software. The incidence of TNBC was 21%. Comparedwith non-TNBC, TNBC patients tend to be younger at diagnosis and had slightly larger tumors and higher stage. Higher histological grade was strongly associated with TNBC. Lymph nodes and histological type were similar in the two groups. Bone was the most frequently metastatic site in all breast cancers, but TNBC was strongly associated with liver metastases.No significant difference was observed in 5-year Disease-Free Survival (DFS) and 5-year Overall Survival (OS) between TNBC and non-TNBC. In conclusion, TNBC is associated with particular clinicopathological features and poor prognosis compared to non-TNBC

Implementation of breast cancer continuum of care in low- and middle-income countries during the COVID-19 pandemic

Breast cancer is the most common malignancy among women worldwide. The current COVID-19 pandemic represents an unprecedented challenge leading to care disruption, which is more severe in low- and middle-income countries (LMIC) due to existing economic obstacles. This review presents the global perspective and preparedness plans for breast cancer continuum of care amid the COVID-19 outbreak and discusses challenges faced by LMIC in implementing these strategies. Prioritization and triage of breast cancer patients in a multidisciplinary team setting are of paramount importance. Deescalation of systemic and radiation therapy can be utilized safely in selected clinical scenarios. The presence of a framework and resource-adapted recommendations exploiting available evidence-based data with judicious personalized use of current resources is essential for breast cancer care in LMIC during the COVID-19 pandemic

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Salivary Biomarkers in Systemic Sclerosis Disease

Scleroderma or systemic sclerosis (SSc) is frequently detected at an advanced stage due to diagnosis difficulties. Salivary biomarkers, if existing, could be used for predictive diagnosis of this disease. Human saliva contains a large number of proteins that can be used for diagnosis and are of great potential in clinical research. The use of proteomic analysis to characterize whole saliva (WS) in SSc has gained an increasing attention in the last years and the identification of salivary proteins specific for SSc could lead to early diagnosis or new therapeutic targets. This review will present an overview about the use of WS in SSc studies. The proteomic technologies currently used for global identification of salivary proteins in SSc, as well as the advantages and limitations for the use of WS as a diagnostic tool, will be presented

Antimicrobial Resistance Trends in Staphylococcus aureus Strains Carried by Poultry in North of Morocco: A Preliminary Analysis

The transmission of antibiotic resistance to human population through food consumption is a global public health threat. This study aimed to assess the nasopharyngeal carriage of S. aureus in poultry and to investigate antimicrobial susceptibility and virulence-associated genes. Nasopharyngeal swabs were collected from chickens at the slaughterhouse of Tangier and immediately transported to the microbiological laboratory for phenotypic identification and assessment of antibiotic susceptibility. The presence of 16S rRNA, nuc, mecA, mecC, Panton–Valentine leukocidin (PVL), and the toxic shock syndrome toxin 1 (TSST-1) genes were detected by PCR analysis for all isolates. Overall, 548 nasopharyngeal swabs were collected, of which 17 (3.4%) were S. aureus positive. More than half of the strains (54%) were resistant to penicillin, 29.4% to tetracycline, 23.5% to erythromycin, and 17% showed resistance to ciprofloxacin. The mecA and mecC were not identified in any of the recovered isolates. Of the S. aureus recovered, 29.41% of the isolates were found to be toxinogenic; 17.64% and 11.76% were positive for PVL and TSST-1 encoding genes, respectively. The trends of antibiotic resistance and the toxinogenic S. aureus carried by the poultry intended for consumption in Tangier present a huge concern. Preventive and containment measures should be implemented in order to limit the dissemination of resistance genes through the food chain and to reduce their increased rate

Clinicopathologic and prognostic features of breast cancer in young women: a series from North of Morocco

Abstract Background Literature data reported a higher frequency of breast cancer in young women (BCYW) in developing countries. BCYW is associated with delayed diagnosis, aggressive biology and poor prognosis. However, our knowledge of biological profile, treatment received and outcome of young patients is still limited in Morocco. We propose to analyze clinicopathologic, therapeutic and prognostic features of BCYW among a series of patients native and/or inhabitant of North of Morocco. Methods We carried out a retro-prospective study of 331 infiltrating breast cancer cases registered between January 2010 and December 2015. Details of tumor pathology, treatment and outcome were collected. Disease-Free Survival (DFS) and Overall Survival (OS) were assessed by Kaplan-Meier analysis. Results A total of 82 patients were diagnosed with breast cancer at the age of 40 or younger (24.8%). Median age was 36 years. More than one quarter (26%) of patients had family history of breast or ovarian cancer. Advanced stages accounted for 34.2% of cases. Median tumor diameter was 2.8 cm. Intermediate and high-grade tumors represented 47.6% and 40.2%, respectively. Nodal involvement was present in 58.5% and lymphovascular invasion was found in 47.7% of the patients. About two thirds (66.2%) of tumors were hormone receptor positive, 29.2% over-expressed HER2 receptor and 23% were triple negative. Patients underwent breast conserving surgery in 38.2% of cases, 61.7% were offered adjuvant chemotherapy and 84.6% received hormone therapy. Five-year DFS and OS were respectively 88.9% and 75.6%. Locoregional recurrence occurred in 2.8% of cases and 8.3% of patients developed distant metastases. Conclusion Our findings are in accordance with previous studies that have shown a higher frequency of breast cancer among Moroccan young women. In line with literature data, clinicopathologic profile seems to be aggressive and prognosis is pejorative in our series

Decoding Diabetes Biomarkers and Related Molecular Mechanisms by Using Machine Learning, Text Mining, and Gene Expression Analysis

The molecular basis of diabetes mellitus is yet to be fully elucidated. We aimed to identify the most frequently reported and differential expressed genes (DEGs) in diabetes by using bioinformatics approaches. Text mining was used to screen 40,225 article abstracts from diabetes literature. These studies highlighted 5939 diabetes-related genes spread across 22 human chromosomes, with 112 genes mentioned in more than 50 studies. Among these genes, HNF4A, PPARA, VEGFA, TCF7L2, HLA-DRB1, PPARG, NOS3, KCNJ11, PRKAA2, and HNF1A were mentioned in more than 200 articles. These genes are correlated with the regulation of glycogen and polysaccharide, adipogenesis, AGE/RAGE, and macrophage differentiation. Three datasets (44 patients and 57 controls) were subjected to gene expression analysis. The analysis revealed 135 significant DEGs, of which CEACAM6, ENPP4, HDAC5, HPCAL1, PARVG, STYXL1, VPS28, ZBTB33, ZFP37 and CCDC58 were the top 10 DEGs. These genes were enriched in aerobic respiration, T-cell antigen receptor pathway, tricarboxylic acid metabolic process, vitamin D receptor pathway, toll-like receptor signaling, and endoplasmic reticulum (ER) unfolded protein response. The results of text mining and gene expression analyses used as attribute values for machine learning (ML) analysis. The decision tree, extra-tree regressor and random forest algorithms were used in ML analysis to identify unique markers that could be used as diabetes diagnosis tools. These algorithms produced prediction models with accuracy ranges from 0.6364 to 0.88 and overall confidence interval (CI) of 95%. There were 39 biomarkers that could distinguish diabetic and non-diabetic patients, 12 of which were repeated multiple times. The majority of these genes are associated with stress response, signalling regulation, locomotion, cell motility, growth, and muscle adaptation. Machine learning algorithms highlighted the use of the HLA-DQB1 gene as a biomarker for diabetes early detection. Our data mining and gene expression analysis have provided useful information about potential biomarkers in diabetes

Clinico-pathological relationship between androgen receptor and tumour infiltrating lymphocytes in triple negative breast cancer

BackgroundTriple negative breast cancer (TNBC) is an aggressive subtype of breast cancer (BC) with ill-defined therapeutic targets. Androgen receptor (AR) and tumour-infiltrating lymphocytes (TILs) had a prognostic and predictive value in TNBC. The relationship between AR, TILs and clinical behaviour is still not fully understood.MethodsThirty-six TNBC patients were evaluated for AR (positive if ≥1% expression), CD3, CD4, CD8 and CD20 by immunohistochemistry. Stromal TILs were quantified following TILs Working Group recommendations. Lymphocyte-predominant breast cancer (LPBC) was defined as stromal TILs ≥ 50%, whereas lymphocyte-deficient breast cancer (LDBC) was defined as <50%.ResultsThe mean age was 52.5 years and 27.8% were ≥60 years. Seven patients (21.2%) were AR+. All AR+ cases were postmenopausal (≥50 years old). LPBC was 32.2% of the whole cohort. Median TILs were 37.5% and 10% (p = 0.1) and median CD20 was 20% and 7.5% (p = 0.008) in AR- and AR+, respectively. Mean CD3 was 80.7% and 93.3% (p = 0.007) and CD8 was 75% and 80.8% (p= 0.41) in AR- and AR+, respectively. All patients who were ≥60 years old expressed CD20. LDBC was found to be significantly higher in N+ versus N- patients (p = 0.03) with median TILs of 20% versus 50% in N+ versus N-, respectively (p = 0.03). LDBC was associated with higher risk of lymph node (LN) involvement (odds ratio = 6; 95% CI = 1.05-34.21; p = 0.04).ConclusionsAR expression was evident in older age (≥50 years). Median CD20 was higher in AR- TNBC, while mean CD3 was higher in AR+ tumours. LDBC was associated with higher risk of LN involvement. Larger studies are needed to focus on the clinical impact of the relation between AR and TILs in TNBC