MYC amplification in subtypes of breast cancers in African American women

BACKGROUND: MYC overexpression is associated with poor prognosis in breast tumors (BCa). The objective of this study was to determine the prevalence of MYC amplification and associated markers in BCa tumors from African American (AA) women and determine the associations between MYC amplification and clinico-pathological characteristics. METHODS: We analyzed 70 cases of well characterized archival breast ductal carcinoma specimens from AA women for MYC oncogene amplification. Utilizing immune histochemical analysis estrogen receptor (ER), progesterone receptor (PR), and (HER2/neu), were assessed. Cases were Luminal A (ER or PR+, Ki-67 \u3c 14%), Luminal B (ER or PR+, Ki-67 = \u3e 14% or ER or PR+ HER2+), HER2 (ER-, PR-, HER2+), and Triple Negative (ER-, PR-, HER2-) with basal-like phenotype. The relationship between MYC amplification and prognostic clinico-pathological characteristics was determined using chi square and logistic regression modeling. RESULTS: Sixty-five (97%) of the tumors showed MYC gene amplification (MYC: CEP8 \u3e 1). Statistically significant associations were found between MYC amplification and HER2-amplified BCa, and Luminal B subtypes of BCa (p \u3c 0.0001), stage (p \u3c 0.001), metastasis (p \u3c 0.001), and positive lymph node status (p = 0.039). MYC amplification was associated with HER2 status (p = 0.01) and tumor size (p = 0.01). High MYC amplification was seen in grade III carcinomas (MYC: CEP8 = 2.42), pre-menopausal women (MYC: CEP8 = 2.49), PR-negative status (MYC: CEP8 = 2.42), and ER-positive status (MYC: CEP8 = 2.4). CONCLUSIONS: HER2 positive BCas in AA women are likely to exhibit MYC amplification. High amplification ratios suggest that MYC drives HER2 amplification, especially in HER2 positive, Luminal B, and subtypes of BCa

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

Fatal Disseminated Fusarium Infection in a Human Immunodeficiency Virus Positive Patient

Systemic mycotic infections have been increasing in incidence in immunocompromised patients. Although yeasts are most often isolated, opportunistic fungal infections may also be caused by filamentous fungi, including Aspergillus and Fusarium. Like Aspergillus, Fusarium is angioinvasive with an ability to disseminate widely. Disseminated fusariosis is most commonly linked to prolonged neutropenia. Disseminated infections due to Fusarium are rare in Human Immunodeficiency Virus (HIV) positive patients but have been reported in HIV positive patients with neutropenia and lymphoma. We describe an HIV positive patient without neutropenia, skin lesions, or concomitant malignancy, who developed fatal disseminated infection with possible endocarditis due to Fusarium solani. Early identification of Fusarium is important because of its high level of resistance to several antifungal drugs, with response often requiring combination therapy

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 science. © The Author(s) 2019. Published by Oxford University Press