Triple negative breast cancer (TNBC) remains an aggressive disease due to the lack of targeted therapies and relatively low rate of response to chemotherapy, which is currently the main treatment modality for TNBC. Breast cancer stem cells (BCSCs) are a small subpopulation of breast tumors and recognized as drivers of tumorigenesis. TNBC tumors are characterized as being enriched for BCSCs. Studies have demonstrated the role of BCSCs as the source of metastatic disease and chemoresistance in TNBC. Multiple targets against BCSCs are now under investigation, with the considerations of either selectively targeting BCSCs or co-targeting BCSCs and non-BCSCs (majority of tumor cells). This review article provides a comprehensive overview of recent advances in the role of BCSCs in TNBC and the identification of cancer stem cell biomarkers, paving the way for the development of new targeted therapies. The review also highlights the resultant discovery of cancer stem cell targets in TNBC and offers summaries of ongoing clinical trials treating chemoresistant breast cancer. We aim to better understand the mutational landscape of BCSCs and explore potential molecular signaling pathways targeting BCSCs to overcome chemoresistance and prevent metastasis in TNBC, ultimately to improve the overall survival of patients with this devastating disease.

Acute myeloid leukemia (AML) with RAM immunophenotype is a rare recently described AML subtype. It is defined by blasts with strong expression of CD56 and weak to absent expression of CD45, HLA-DR....., and CD38 and characterized by significantly worse outcome [1] . Little is known about the clinical presentation and this immunophenotype is not widely recognized in clinical practice. We describe a case of AML with RAM immunophenotype in a 5-year-old male patient with a unique presentation, including extensive mesenteric and retroperitoneal lymphadenopathy. Diagnostic studies included bilateral bone marrow and lymph node biopsies, flow cytometry, cytogenetics, fluorescence in-situ hybridization (FISH), and next generation sequencing. Bone marrow biopsy revealed >90% blasts, positive for CD34, CD117, and CD56 by flow cytometry and immunohistochemistry. Next generation sequencing revealed BCOR loss and CBFA2T3-GLIS2 fusion. Following induction chemotherapy, bone marrow biopsy showed residual disease and a stem cell transplant was performed. The patient relapsed three months after transplant and subsequently passed away eleven months after initial diagnosis. Limited literature is available describing this newly identified AML subset. The RAM immunophenotype has been identified as an independent prognostic factor for relapse rate and overall and disease-free survival [1] . Few case reports are available to characterize the genetic profile, typical presentation, and clinical course of patients with this unique immunophenotype.

Context.— Smart glasses are a wearable technology that enable hands-free data acquisition and entry. Objective.— To develop a surgical pathology grossing application on a smart glass platform. Design.— An existing logistics software for the Google Glass Enterprise smart glass platform was used to create surgical pathology grossing protocols. The 2 grossing protocols were developed to simulate grossing a complex (heart) and a simple (kidney) specimen. For both protocols, users were visually prompted by the smart glass device to perform each task, record measurements, or document the field of view. In addition to measuring the total time of the protocol performance, each substep within the protocol was automatically recorded. Subsequently, a report was generated that contained the dictation, images, voice recordings, and the timing of each step. The application was tested by 3 users using the 2 grossing protocols. The users were tracked across 3 grossing procedures for each protocol. Results.— For the complex specimen grossing the average time across repeated procedures was not significantly different between users ( P = .999). However, when grossing times of the complex specimen were compared for repeated performances of the same user, a significant reduction in grossing times was observed with each repetition ( P = .002). For the simple specimen, the average grossing time across multiple attempts was different among users ( P = .03); however, no improvement in grossing time was observed with repeated performance ( P = .499). Conclusions.— Augmented reality based grossing applications can provide automated data collection to track the changes in grossing performance over time.

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Background: Several instruments intend to measure clinical reasoning capability, yet we lack evidence contextualizing their scores. The authors compared three clinical reasoning instruments [Clinical Reasoning Task (CRT), Patient Note Scoring rubric (PNS), and Summary Statement Assessment Rubric (SSAR)] using Messick's convergent validity framework in pre-clinical medical students. Scores were compared to a validated clinical reasoning instrument, Clinical Data Interpretation (CDI). Method: Authors administered CDI and the first clinical case to 235 students. Sixteen randomly selected students (four from each CDI quartile) wrote a note on a second clinical case. Each note was scored with CRT, PNS, and SSAR. Final scores were compared to CDI. Results: CDI scores did not significantly correlate with any other instrument. A large, significant correlation between PNS and CRT was seen (r = 0.71; p = 0.002). Conclusions: None of the tested instruments outperformed the others when using CDI as a standard measure of clinical reasoning. Differing strengths of association between clinical reasoning instruments suggest they each measure different components of the clinical reasoning construct. The large correlation between CRT and PNS scoring suggests areas of novice clinical reasoning capability, which may not be yet captured in CDI or SSAR, which are weighted toward knowledge synthesis and hypothesis testing.