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BACKGROUND: Plasma cell leukemia (PCL) is a rare monoclonal gammopathy, associated with short survival. Because of its very low incidence, only a few cohorts have been reported and thus, information on this disease is scarce. The goal of this study was to better understand the clinical features, prognostic factors, and efficacy of modern treatments in both primary PCL (pPCL) and secondary PCL (sPCL). METHODS: We performed a retrospective, multicenter study of patients diagnosed with PCL, defined as circulating plasma cells ≥20% of total leukocytes and/or ≥2 × 109/L. RESULTS: We identified 99 eligible PCL patients, of whom 33 were pPCL and 66 were sPCL. The median progression-free survival (PFS) to frontline treatment and overall survival (OS) were, respectively, 4.8 (95% CI, 0.4-9.2) and 18.3 months (95% CI, 0.0-39.0) for pPCL and 0.8 (95% CI, 0.5-1.1) and 1.2 months (95% CI, 0.9-1.5) for sPCL (both p < 0.001). We observed no improvement in OS over time (2005-2012 vs. 2013-2020, p = 0.629 for pPCL and p = 0.329 for sPCL). Finally, our data suggested that sPCL originates from a high-risk multiple myeloma (MM) population with a short OS (median 30.2 months), early relapse after stem cell transplant (median 11.9 months) and a high proportion of patients with multiple cytogenetic abnormalities (36% with ≥2 abnormalities). CONCLUSIONS: This study is one of the largest PCL cohorts reported. We are also the first to investigate characteristics of MM before its transformation into sPCL and demonstrate that high-risk biologic features already present at the time of MM diagnosis. Moreover, our data highlights the lack of improvement in PCL survival in recent years and the urgent need for better treatment options.

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Epithelial-mesenchymal transition (EMT) and primary ciliogenesis are two cell-biological programs that are essential for development of multicellular organisms and whose abnormal regulation results in many diseases (i.e., developmental anomalies and cancers). Emerging studies suggest an intricate interplay between these two processes. Here, we discuss physiological and pathological contexts in which their interconnections promote normal development or disease progression. We describe underlying molecular mechanisms of the interplay and EMT/ciliary signaling axes that influence EMT-related processes (i.e., stemness, motility and invasion). Understanding the molecular and cellular mechanisms of the relationship between EMT and primary ciliogenesis may provide new insights in the etiology of diseases related to EMT and cilia dysfunction.

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Background-smoldering multiple myeloma (SMM) risk of progression to multiple myeloma (MM) is highly heterogeneous and several models have been suggested to predict this risk. Lakshman et al. recently proposed a model based on three biomarkers: bone marrow plasma cell (BMPC) percentage > 20%, free light chain ratio (FLCr) > 20 and serum M protein > 20 g/L. The goal of our study was to test this "20/20/20" model in our population and to determine if similar results could be obtained in another cohort of SMM patients. Method-we conducted a retrospective, single center study with 89 patients diagnosed with SMM between January 2008 and December 2019. Results-all three tested biomarkers were associated with an increased risk of progression: BMPC percentage ≥ 20% (hazard ratio [HR]: 4.28 [95%C.I., 1.90-9.61]; p < 0.001), serum M protein ≥ 20 g/L (HR: 4.20 [95%C.I., 1.90-15.53]; p = 0.032) and FLCr ≥ 20 (HR: 3.25 [95%C.I., 1.09-9.71]; p = 0.035). The estimated median time to progression (TTP) was not reached for the low and intermediate risk groups and was 29.1 months (95%C.I., 3.9-54.4) in the high-risk group (p = 0.006). Conclusions-the 20/20/20 risk stratification model adequately predicted progression in our population and is easy to use in various clinical settings.

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Very preterm newborns have an increased risk of developing an inflammatory cerebral white matter injury that may lead to severe neuro-cognitive impairment. In this study we performed functional connectivity (fc) analysis using resting-state optical imaging of intrinsic signals (rs-OIS) to assess the impact of inflammation on resting-state networks (RSN) in a pre-clinical model of perinatal inflammatory brain injury. Lipopolysaccharide (LPS) or saline injections were administered in postnatal day (P3) rat pups and optical imaging of intrinsic signals were obtained 3 weeks later. (rs-OIS) fc seed-based analysis including spatial extent were performed. A support vector machine (SVM) was then used to classify rat pups in two categories using fc measures and an artificial neural network (ANN) was implemented to predict lesion size from those same fc measures. A significant decrease in the spatial extent of fc statistical maps was observed in the injured group, across contrasts and seeds (*p = 0.0452 for HbO2 and **p = 0.0036 for HbR). Both machine learning techniques were applied successfully, yielding 92% accuracy in group classification and a significant correlation r = 0.9431 in fractional lesion volume prediction (**p = 0.0020). Our results suggest that fc is altered in the injured newborn brain, showing the long-standing effect of inflammation.

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OBJECTIVE: This study proposes the DEDE (Door-from-Emergency to Door-to-EVAR [endovascular aneurysm repair]) time as a new metric for ruptured abdominal aortic aneurysm (RAAA) delay time to surgery, permitting coherent centralization in large territories. It demonstrates how the DEDE time can be applied, using data from the province of Quebec, and looks at its potential effect on 30-day mortality. METHODS: We used the Quebec Integrated Chronic Disease Surveillance System (QICDSS), the linkage of five health administrative databases, to build a retrospective cohort of RAAA patients repaired operatively between April 1, 2006, and March 31, 2013. A validated algorithm was used to identify open surgical repair (OSR) and EVAR patients. Hospitals performing these operations were further characterized according to their location, volume of RAAA, types of surgeries (OSR vs EVAR), and surgeon's volume. Logistic and log-binomial regression analyses identified the risk of 30-day mortality with age, sex, hospital volume, and surgical groups as variables. Using the DEDE 90 metric and the attributable fraction, we projected how centralization and increasing the number of EVAR would affect the 30-day mortality. RESULTS: Among patients aged ≥65 years, 895 RAAAs were identified. OSR was performed in 839 patients (93.7%) and EVAR in 56 (6.3%). The overall 30-day mortality was 34.4%, and more specifically, was 35.5% for OSR compared with 17.9% for EVAR (P = .0046). RAAAs were treated in 39 hospitals, including 16 centers averaging less than one RAAA repair per year. Low-volume (39.4%) vs high-volume centers (32.5%) had similar 30-day mortality (P = .2198). In the multivariate analysis, the relative risk for OSR was 1.95 (P = .0211) and was not significant for hospital volume. Applying the DEDE 90 metric and increasing access to EVAR to 50% of patients, the overall 30-day mortality would be 26.8%. CONCLUSIONS: DEDE 90 is a new metric for a coherent centralization model, particularly in large territories, where transport time is crucial. Increasing access to EVAR performed in high-volume centers, with consideration to transport time, could improve the 30-day mortality after a RAAA repair.

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