Aberrantly reduced expression of miR-342-5p contributes to CCND1-associated chronic myeloid leukemia progression and imatinib resistance.

Chronic myeloid leukemia (CML) is a myeloproliferative disorder associated with the Philadelphia chromosome, and the current standard of care is the use of tyrosine kinase inhibitors (TKI). However, some patients will not achieve a molecular response and may progress to blast crisis, and the underlying mechanisms remain to be clarified. In this study, next-generation sequencing was used to explore endogenous miRNAs in CML patients versus healthy volunteers, and miR-342-5p was identified as the primary target. We found that miR-342-5p was downregulated in CML patients and had a significant inhibitory effect on cell proliferation in CML. Through a luciferase reporter system, miR-342-5p was reported to target the 3'-UTR domain of CCND1 and downregulated its expression. Furthermore, overexpression of miR-342-5p enhanced imatinib-induced DNA double-strand breaks and apoptosis. Finally, by analyzing clinical databases, we further confirmed that miR-342-5p was associated with predicted molecular responses in CML patients. In conclusion, we found that both in vivo and in vitro experiments and database cohorts showed that miR-342-5p plays a key role in CML patients, indicating that miR-342-5p may be a potential target for future CML treatment or prognostic evaluation.

A Hematologist-Level Deep Learning Algorithm (BMSNet) for Assessing the Morphologies of Single Nuclear Balls in Bone Marrow Smears: Algorithm Development.

BACKGROUND: Bone marrow aspiration and biopsy remain the gold standard for the diagnosis of hematological diseases despite the development of flow cytometry (FCM) and molecular and gene analyses. However, the interpretation of the results is laborious and operator dependent. Furthermore, the obtained results exhibit inter- and intravariations among specialists. Therefore, it is important to develop a more objective and automated analysis system. Several deep learning models have been developed and applied in medical image analysis but not in the field of hematological histology, especially for bone marrow smear applications. OBJECTIVE: The aim of this study was to develop a deep learning model (BMSNet) for assisting hematologists in the interpretation of bone marrow smears for faster diagnosis and disease monitoring. METHODS: From January 1, 2016, to December 31, 2018, 122 bone marrow smears were photographed and divided into a development cohort (N=42), a validation cohort (N=70), and a competition cohort (N=10). The development cohort included 17,319 annotated cells from 291 high-resolution photos. In total, 20 photos were taken for each patient in the validation cohort and the competition cohort. This study included eight annotation categories: erythroid, blasts, myeloid, lymphoid, plasma cells, monocyte, megakaryocyte, and unable to identify. BMSNet is a convolutional neural network with the YOLO v3 architecture, which detects and classifies single cells in a single model. Six visiting staff members participated in a human-machine competition, and the results from the FCM were regarded as the ground truth. RESULTS: In the development cohort, according to 6-fold cross-validation, the average precision of the bounding box prediction without consideration of the classification is 67.4%. After removing the bounding box prediction error, the precision and recall of BMSNet were similar to those of the hematologists in most categories. In detecting more than 5% of blasts in the validation cohort, the area under the curve (AUC) of BMSNet (0.948) was higher than the AUC of the hematologists (0.929) but lower than the AUC of the pathologists (0.985). In detecting more than 20% of blasts, the AUCs of the hematologists (0.981) and pathologists (0.980) were similar and were higher than the AUC of BMSNet (0.942). Further analysis showed that the performance difference could be attributed to the myelodysplastic syndrome cases. In the competition cohort, the mean value of the correlations between BMSNet and FCM was 0.960, and the mean values of the correlations between the visiting staff and FCM ranged between 0.952 and 0.990. CONCLUSIONS: Our deep learning model can assist hematologists in interpreting bone marrow smears by facilitating and accelerating the detection of hematopoietic cells. However, a detailed morphological interpretation still requires trained hematologists.

The Clinical Efficacy and Cardiotoxicity of Fixed-Dose Monthly Trastuzumab in HER2-Positive Breast Cancer: A Single Institutional Analysis.

OBJECTIVE: Trastuzumab-containing treatment regimens have been shown to improve survival outcomes in HER2-positive breast cancer (BC). It is much easier to infuse a fixed one-vial dose to every patient on a regular schedule in the general clinical setting. The aims of this study were evaluating the efficacy of a 440 mg fixed-dose of trastuzumab administered on a monthly infusion schedule, and the risk factors for cardiac events. PATIENTS AND METHODS: We retrospectively reviewed data from 300 HER2-positive BC patients in our institute: 208 were early-stage BC patients undergoing adjuvant trastuzumab treatment, and 92 were metastatic BC patients treated with trastuzumab infusions until disease progression. There were 181 patients receiving regular trastuzumab infusions every 3 weeks (Q3W; 8 mg/kg loading dose followed by 6 mg/kg every 3 weeks), and the other 119 patients were treated monthly with a fixed 440 mg dose (QM; fixed 440 mg every 4 weeks). RESULTS: The medians of progression-free survival (PFS) and overall survival (OS) in the adjuvant setting were not reached in both treatment groups. In the metastatic setting, there was no significant difference between groups in PFS or OS. The median time to significant cardiovascular (CV) dysfunction was 4.54 months. The incidence of congestive heart failure requiring medication in our cohort was 3.4%. CONCLUSION: In our study, we found that fixed-dose monthly trastuzumab was feasible and effective. In addition, the CV risk was not higher with the fixed-dose protocol. This treatment modality could lower the cost and was easier to implement in clinical practice. Larger prospective randomized studies with longer-term follow up are needed to confirm our results.

Discrimination index of microcytic anemia in young soldiers: a single institutional analysis.

BACKGROUND: The common differential diagnosis of microcytic anemia in young Asian men includes iron deficiency anemia (IDA), α-thalassemia (αT) and ß-thalassemia (ßT). In this study, we aimed to distinguish between these diseases in a distinct population of young men using a specific index. PATIENTS AND METHODS: We retrospectively reviewed the laboratory data of young men with microcytic anemia. The clinical, characteristic and laboratory data, including complete blood cell counts, serum ferritin and hemoglobin electrophoresis results, were collected; genomic DNA mutations were also evaluated. Based on these data, ten discrimination indices were used to differentiate thalassemia from IDA. The sensitivity, specificity, positive and negative predictive values, Youden's index and receiver operating characteristic (ROC) curves were also calculated. RESULTS: A total of 877 patients (92 patients with IDA, 332 with αT and 453 with ßT) were enrolled; the Shine and Lal (S&L) formula was the best method with which to discriminate IDA from thalassemia (100% sensitivity, 91% specificity). The new cut-off values were evaluated, and the approaches used in our study cohort, particularly the Green & King (G&K) formula, significantly increased the accuracies of red cell distribution width-containing indices (cut-off value: 58.66; 89.62% sensitivity and 96.2% specificity; AUC: 0.9716). In addition, when applied properly, these indices could differentiate IDA patients from αT patients, especially Huber-Herklotz index (HH). CONCLUSIONS: The sensitivity and specificity differed among ethnic and age groups. We concluded that when using the original cut-off value, the S&L formula was the best discriminating index for differentiating between IDA and thalassemia in young Asian men. However, when using the G&K formula, the newly obtained cut-off value must be applied to increase accuracy based on the results from our cohort.

Necrotizing fasciitis in two patients with myelodysplastic syndrome treated with azacitidine.

Azacitidine is a novel agent for treating myelodysplastic syndromes (MDS). It has a relatively safe toxicity profile with very few reported skin toxicities. Patients with MDS were prone to get severe infections, especially via respiratory tract, urinary system, and bloodstream. However, necrotizing fasciitis (NF) is a relatively rare event in patients with MDS, and it is hard to diagnose early. Here, we report two MDS cases that developed NF in lower extremities while receiving azacitidine treatment. One of them survives after emergent fasciotomy along with the administration of broad-spectrum antibiotics and intravenous immunoglobulin.

Disseminated Fusarium infection in a patient with acute lymphoblastic leukemia: A case report and review of the literature.

Fusarium is a common soil mold. In severely immunocompromised patients, this fungus may cause disseminated disease and is often confused with Aspergillus, as the two pathogens have similar histopathological appearances. Disseminated Fusarium infection may cause significant morbidity and mortality in immunocompromised patients. The current case report presents a 20-year-old male with acute lymphoblastic leukemia who developed disseminated Fusarium infection during induction chemotherapy. Early diagnosis and treatment is extremely important since the mortality rate is extremely high in such patients. The clinician must consider that the clinical presentation of Fusarium infection resembles that of Aspergillus. There is no optimal treatment for patients with Fusarium infection; however, combination antifungal therapy may have benefit without significant toxicity.

Near Total Regression of Diffuse Brain Metastases in Adenocarcinoma of the Lung with an EGFR Exon 19 Mutation: A Case Report and Review of the Literature.

We report the case of a woman with diffuse brain metastases from lung cancer who experienced total regression of the metastases under gefitinib treatment. The 58-year-old woman was referred to our hospital with a complaint of severe headache. A brain MRI revealed diffuse metastatic lesions in the cerebra and cerebellum. Adenocarcinoma of the lung with multiple brain metastases was diagnosed. The tumor was positive for an epidermal growth factor receptor (EGFR) exon 19 deletion mutation. She was treated with gefitinib 250 mg per day. One year later, the diffuse brain metastases had totally resolved. EGFR-tyrosine kinase inhibitor therapy could be a first-line treatment for patients with advanced adenocarcinoma of the lung with EGFR mutation, especially in those with brain metastases.