Citations

Flow cytometric (FC) immunophenotyping is critical but time-consuming in diagnosing minimal residual disease (MRD). We evaluated whether human-in-the-loop artificial intelligence (AI) could improve the efficiency of clinical laboratories in detecting MRD in chronic lymphocytic leukemia (CLL). We developed deep neural networks (DNN) that were trained on a 10-color CLL MRD panel from treated CLL patients, including DNN trained on the full cohort of 202 patients (F-DNN) and DNN trained on 138 patients with low-event cases (MRD < 1000 events) (L-DNN). A hybrid DNN approach was utilized, with F-DNN and L-DNN applied sequentially to cases. “Ground truth” classification of CLL MRD was confirmed by expert analysis. The hybrid DNN approach demonstrated an overall accuracy of 97.1% (95% CI: 84.7–99.9%) in an independent cohort of 34 unknown samples. When CLL cells were reported as a percentage of total white blood cells, there was excellent correlation between the DNN and expert analysis [r > 0.999; Passing–Bablok slope = 0.997 (95% CI: 0.988–0.999) and intercept = 0.001 (95% CI: 0.000–0.001)]. Gating time was dramatically reduced to 12 s/case by DNN from 15 min/case by the manual process. The proposed DNN demonstrated high accuracy in CLL MRD detection and significantly improved workflow efficiency. Additional clinical validation is needed before it can be fully integrated into the existing clinical laboratory practice.

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70–180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70–180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: −1% to +6%], P = 0.22). Median time <70 mg/dL improved from 3.0% with SAP to 1.6% with AID (−1.5% [−2.4% to −0.5%], P = 0.002). The adaptation system decreased initial basal rates by a median of 4% (−8%, 16%) and increased initial carbohydrate ratios by a median of 45% (32%, 59%) after 13 weeks. Conclusions: Automated adaptation of insulin delivery settings with AID use did not significantly improve time-in-range in this very well-controlled population. Additional study and further refinement of the adaptation system are needed, especially in populations with differing degrees of baseline glycemic control, who may show larger benefits from adaptation.

AbstractIdentifying biomarkers associated with disease progression and drug resistance are important for personalized care. We investigated the expression of 121 curated genes, related to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs) responsiveness. We analyzed 28 human multiple myeloma (MM) cell lines with known drug sensitivities and 130 primary MM patient samples collected at different disease stages, including newly diagnosed (ND), on therapy (OT), and relapsed and refractory (RR, collected within 12 months before the patients’ death) timepoints. Our findings led to the identification of a subset of genes linked to clinical drug resistance, poor survival, and disease progression following combination treatment containing IMIDs and/or PIs. Finally, we built a seven‐gene model (MM‐IMiD and PI sensitivity‐7 genes [IP‐7]) using digital gene expression profiling data that significantly separates ND patients from IMiD‐ and PI‐refractory RR patients. Using this model, we retrospectively analyzed RNA sequcencing (RNAseq) data from the Mulltiple Myeloma Research Foundation (MMRF) CoMMpass (n = 578) and Mayo Clinic MM patient registry (n = 487) to divide patients into probabilities of responder and nonresponder, which subsequently correlated with overall survival, disease stage, and number of prior treatments. Our findings suggest that this model may be useful in predicting acquired resistance to treatments containing IMiDs and/or PIs.

SummaryProgression‐free survival (PFS) has been the regulatory primary end‐point for recent phase III trials in first‐line follicular lymphoma (FL), but requires prolonged follow‐up. Complete response (CR) at 30 months after initiation of induction treatment was validated as surrogate end‐point for PFS. Our objective was to further evaluate surrogacy of CR measured by [18F] fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging at the end of induction (EoI). Individual patient data were analysed from 1505 patients from five randomized trials. Trial‐level surrogacy examining the association between treatment effects on EoI‐PET‐CR and PFS was evaluated using linear regression () and bivariate Copula () models. Although EoI‐PET‐CR strongly predicted PFS at a prognostic level, the trial‐level assessment did not show strong correlation (, confidence interval [CI]: 0.20–0.88; , CI: 0.0–0.82). The high uncertainty in estimation was possibly due to the small number of trials and the population of patients with available PET data. Maintenance therapy affecting PFS beyond induction treatment, but not EoI‐PET‐CR end‐point, may have distorted the association between treatment effects. However, there will probably be a number of additional trials approaching completion with available PET response data. Refined evaluation of PET‐CR based surrogate end‐points is still warranted.

Abstract Background: Stem cell senescence and depletion are major causes of organismal aging and aging-related diseases. The NAD–SIRT1–PARP1 axis has garnered remarkable interest owing to its significant role in regulating stem cell senescence and organismal aging. Event though our recent study showes that PBX1 overexpression attenuates hair follicle-derived mesenchymal stem cell (HF-MSC) senescence and apoptosis by regulating ROS-mediated DNA damage via downregulation of PARP1 expression, suggesting PARP1 downregulation is a common manifestation of the roles of both PBX1 and SIRT1 in the attenuation of HF-MSC senescence, and implying a potential link between PBX1 and SIRT1 via PARP1. Methods: HF-MSCs overexpressing PBX1, overexpressing both PBX1 and PARP1, downregulating SIRT1, and overexpressing PBX1 and downregulating SIRT1 were generated, and biomarkers related to cell senescence, apoptosis, DNA damage, and repair were detected at the cellular and protein levels. Results: (1) PBX1 overexpression alleviated HF-MSC senescence and apoptosis accompanied by upregulation of SIRT1 expression, downregulation of PARP1 expression, and increased intracellular NAD and ATP levels. (2) SIRT1 knockdown or PARP1 overexpression enhanced cellular senescence and apoptosis, accompanied by increased ROS accumulation and DNA damage aggravation and decreased intracellular NAD and ATP levels. (3) PBX1 overexpression rescued HF-MSC senescence and apoptosis induced by SIRT1 knockdown or PARP1 overexpression. (4) Dual luciferase reporter showed PBX1 enhanced SIRT1 expression by activating SIRT1 promoter. Conclusions: Our results reveal that a positive interaction feedback loop exists between PBX1 and SIRT1, that PBX1 is the upstream of SIRT1. To the best of our knowledge we are the first to report that there is a PBX1-SIRT1-PARP1 axis and this axis plays a critical role in alleviation of HF-MSC senescence and apoptosis. The results provide a new perspective on the mechanism of stem cell senescence and age-related disease prevention and treatment.

BackgroundThe feasibility and reproducibility of multifrequency MR elastography (MRE) for diagnosing pancreatic ductal adenocarcinoma (PDAC) have not been reported.PurposeTo determine the feasibility and reproducibility of multifrequency MRE for assessing pancreatic stiffness in healthy and diseased pancreases.Study typeProspective.SubjectsA total of 40 healthy volunteers and 10 patients with PDAC were prospectively recruited between March 2018 and October 2021.Field strength/sequenceA 3.0‐T pancreatic MRE at frequencies in the order of 30, 40, 60, 80, and 100 Hz.AssessmentBody mass index (BMI) and wave distance of the healthy pancreas and PDAC were measured. Image quality was assessed using the image quality score (IQS: 1–4, ≥3 were considered diagnostic quality). Three readers independently performed the pancreatic stiffness and IQS assessments to evaluate reproducibility.Statistical testsLogistic regression analyses were performed to determine variables that influenced IQS. Statistical significance was set at P <0.05. Levels of inter‐ and intrarater agreement were assessed using intraclass correlation coefficients (ICC) and Cohen's kappa coefficient (κ). Good reproducibility was set at ICC and κ ≥ 0.8.ResultsIn logistic regression analysis, a diagnostic IQS in healthy volunteers was independently associated with a lower BMI (odds ratio [OR] = 0.89 kg/m−2), shorter wave distance (OR = 0.70 cm−1), and lower frequency (30 and 40 Hz: OR = 170.01 and 96.02). In PDAC, frequency was the only independent factor for diagnostic IQS (30–60 Hz: OR = 46.18, 46.18, and 17.20, respectively) with 100 Hz as a reference. In healthy volunteers, good reproducibility was observed at 30 and 40 Hz. In PDAC, good reproducibility was observed at 30–60 Hz.Data conclusionMRE at 30 and 40 Hz provides diagnostic wave images and reliable measurements of pancreatic stiffness in healthy volunteers. MRE at 30–60 Hz is acceptable for PDACs (IQS ≥ 3, ICC and κ ≥ 0.80).Evidence Level1Technical EfficacyStage 2

Abstract Objective Leucocyte immunoglobulin-like receptor A3 (LILRA3) belongs to a family of leucocyte receptors. Our previous study reported LILRA3 transcripts were markedly upregulated in neutrophils from patients with APS. We undertook this study to investigate clinical implications of LILRA3 in APS and its potential role in APS-associated thrombosis. Methods Two independent cohorts were studied. The first consisted of 294 APS patients, 48 asymptomatic aPL carriers and 150 healthy controls (HCs) from Peking University People’s Hospital. The second included 99 APS patients, 25 aPL carriers and 40 HCs from United States APS centres. Serum or plasma concentrations of LILRA3 and MPO-DNA complexes were measured. Additionally, 35 patients with thrombotic APS (tAPS) were evaluated to determine potential effects of immunosuppressive therapy on serum concentrations of LILRA3 and MPO-DNA complexes. Results Both positivity and serum concentration of LILRA3 were significantly increased in APS patients, especially in those with tAPS. LILRA3-positive tAPS patients displayed more severe thrombotic manifestations. Serum LILRA3 was positively correlated with MPO-DNA complexes in LILRA3-positive tAPS. After immunosuppressive treatment, LILRA3 and MPO-DNA complexes were consistently decreased in tAPS patients. Key findings from the Peking cohort were confirmed in the United States cohort. Conclusion Our study provides first evidence that LILRA3 is aberrantly expressed in APS, especially in patients with tAPS. Serum LILRA3 correlated with MPO-DNA complexes, and the two indices were consistently decreased in tAPS patients after treatment. LILRA3 may play a role in thrombosis of APS and may serve as a biomarker and/or therapeutic target in tAPS.

Abstract Observational studies and stand-alone trials indicate that patients with follicular lymphoma (FL) who experience disease progression within 24 months of front-line chemoimmunotherapy (POD24), have poor outcomes. We performed a pooled analysis of 13 randomized clinical trials of patients with FL in the pre- and postrituximab eras to identify clinical factors that predict POD24. Logistic regression models evaluated the association between clinical factors and POD24. Cox regression evaluated the association between POD24 as a time-dependent factor and subsequent overall survival (OS). A landmark analysis evaluated the association of POD24 with OS for the subset of patients who were alive at 24 months after trial registration. Patients without progression at 24 months at baseline had favorable performance status (PS), limited-stage (I/II) disease, low-risk FL International Prognostic Index (FLIPI) score, normal baseline hemoglobin, and normal baseline β2 microglobulin (B2M) level. In a multivariable logistic regression model, male sex (odds ratio [OR], 1.30), PS ≥2 (OR, 1.63), B2M (≥3 mg/L; OR, 1.43), and high-risk FLIPI score (3-5; OR, 3.14) were associated with increased risk of progression before 24 months. In the time-dependent Cox model and the 24-month landmark analysis, POD24 was associated with poor subsequent OS (hazard ratio, 4.85 and 3.06, respectively). This is the largest pooled analysis of clinical trials data validating POD24 as a robust indicator of poor FL survival and identified clinical predictors of early death and progression that can aid in building comprehensive prognostic models incorporating clinical and molecular predictors of POD24.