Citations

Abstract Cell fate conversion by overexpressing defined factors is a powerful tool in regenerative medicine. However, identifying key factors for cell fate conversion requires laborious experimental efforts; thus, many of such conversions have not been achieved yet. Nevertheless, cell fate conversions found in many published studies were incomplete as the expression of important gene sets could not be manipulated thoroughly. Therefore, the identification of master transcription factors for complete and efficient conversion is crucial to render this technology more applicable clinically. In the past decade, systematic analyses on various single-cell and bulk OMICs data have uncovered numerous gene regulatory mechanisms, and made it possible to predict master gene regulators during cell fate conversion. By virtue of the sparse structure of master transcription factors and the group structure of their simultaneous regulatory effects on the cell fate conversion process, this study introduces a novel computational method predicting master transcription factors based on group sparse optimization technique integrating data from multi-OMICs levels, which can be applicable to both single-cell and bulk OMICs data with a high tolerance of data sparsity. When it is compared with current prediction methods by cross-referencing published and validated master transcription factors, it possesses superior performance. In short, this method facilitates fast identification of key regulators, give raise to the possibility of higher successful conversion rate and in the hope of reducing experimental cost.

Abstract Multiple myeloma (MM) is a heterogeneous disease that may be evaluated by a broad array of imaging and laboratory techniques to measure disease activity and predict prognosis. Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) scanning has been shown to be predictive of patient outcomes throughout the disease course. We sought to corroborate these findings by examining the prognostic impact of PET/CT scanning in the posttransplant setting. We retrospectively analyzed PET/CT scans in 229 MM patients receiving an autologous stem cell transplant (ASCT) near day 100, and correlated these findings with time to progression(TTP) and overall survival (OS) to assess the impact of day 100 PET/CT scan findings as an independent prognostic factor. The median OS for the entire cohort was 61.5 months (95% confidence interval [CI], 49-75) and the median TTP was 18.5 months (95% CI, 15.4-21.8). Among patients with abnormal day 100 PET findings (PET+), median TTP was 12.4 months vs 24 months among those with normal PET findings (PET−) (P < .0001). The median OS in the PET+ group was 46 months compared with 99 months in the PET− group (P < .0001). We conclude that an abnormal PET/CT scan near day 100 post-ASCT is predictive of shorter TTP and OS, with prognostic significance retained after adjusting for disease response and other prognostic variables in MM.

Study Design: Prospective single-cohort analysis. Objectives: To compare the outcomes/complications of 2 robotic systems for spine surgery. Methods: Adult patients (≥18-years-old) who underwent robot-assisted spine surgery from 2016-2019 were assessed. A propensity score matching (PSM) algorithm was used to match Mazor X to Renaissance cases. Preoperative CT scan for planning and an intraoperative O-arm for screw evaluation were preformed. Outcomes included screw accuracy, robot time/screw, robot abandonment, and radiation. Screw accuracy was measured using Vitrea Core software by 2 orthopedic surgeons. Screw breach was measured according to the Gertzbein/Robbins classification. Results: After PSA, a total of 65 patients (Renaissance: 22 vs. X: 43) were included. Patient/operative factors were similar between robot systems ( P > .05). The pedicle screw accuracy was similar between robots (Renaissance: 1.1%% vs. X: 1.3%, P = .786); however, the S2AI screw breach rate was significantly lower for the X (Renaissance: 9.5% vs. X: 1.2%, P = .025). Robot time per screw was not statistically different (Renaissance: 4.6 minutes vs. X: 3.9 minutes, P = .246). The X was more reliable with an abandonment rate of 2.3% vs. Renaissance:22.7%, P = .007. Radiation exposure were not different between robot systems. Non-robot related complications including dural tear, loss of motor/sensory function, and blood transfusion were similar between robot systems. Conclusion: This is the first comparative analyses of screw accuracy, robot time/screw, robot abandonment, and radiation exposure between the Mazor X and Renaissance systems. There are substantial improvements in the X robot, particularly in the perioperative planning processes, which likely contribute to the X’s superiority in S2AI screw accuracy by nearly 8-fold and robot reliability by nearly 10-fold.

Personalized treatment of genetically stratified subgroups has the potential to improve outcomes in many malignant tumors. This study distills clinically meaningful prognostic/predictive genomic marker for cervical adenocarcinoma using signature genomic aberrations and single-point nonsynonymous mutation-specific droplet digital PCR (ddPCR). Mutations in PIK3CA E542K, E545K, or H1047R were detected in 41.7% of tumors. PIK3CA mutation detected in the patient’s circulating DNA collected before treatment or during follow-up was significantly associated with decreased progression-free survival or overall survival. PIK3CA mutation in the circulating DNA during follow-up after treatment predicted recurrence with 100% sensitivity and 64.29% specificity. It is the first indication of the predictive power of PIK3CA mutations in cervical adenocarcinoma. The work contributes to the development of liquid biopsies for follow up surveillance and a possibility of tailoring management of this particular women’s cancer.

Background: Real world studies of silent brain infarction (SBI) and white matter disease (WMD) are impeded by challenges in cohort identification. Natural language processing (NLP) from imaging reports may facilitate future studies. However, electronic health records can be heterogeneous and the process of interpreting neuroimages and generating reports can vary. Understanding knowledge representation and relationships between neuroimages and imaging reports is crucial for using NLP to facilitate disease management and cohort identification. Methods: A balanced sample of head neuroimages (CT, MRI) of patients >50 years without clinical histories of symptomatic stroke, TIA, or dementia were obtained at Mayo Clinic and Tufts Medical Center. A team of 4 radiology residents performed report interpretation (RI) on 1000 reports according to a standardized protocol for the presence of SBIs, the presence of WMD, and WMD grade. A random subsample of 400 was doubly read for interrater reliability. For benchmarking, a team of 4 neuroradiologists directly reviewed and described findings on a subsample of 182 images, each doubly read. We assessed interrater reliability for direct review (DR) and RI, and agreement between these 2 information sources. An NLP algorithm was developed to review and extract findings from 1000 imaging reports. Results: For DR, interrater reliability was moderate for SBIs and WMD (k = 0.53, 95% CI 0.43-0.64 and k = 0.47, 95% CI 0.33-0.61) and good for WMD grade (Spearman 0.71, p<0.001). For RI, interrater reliability for SBIs, WMD and WMD grade was good (k = 0.88, 95% CI 0.80-0.97; k = 0.98, 95% CI 0.97-1.00; and Spearman = 0.985, p<0.001, respectively). Agreement between DR and RI was good for SBIs (k = 0.77, 95% CI 0.67-0.86) and WMD (k = 0.65, 95% CI 0.54-0.77). Spearman rank correlations comparing WMD grade interpretation DR to RI was 0.60 (p<0.001). In identifying the presence of SBIs and WMDs, the accuracy of the NLP algorithm was 0.991 and 0.994, respectively. Conclusion: For the presence of SBI and WMD, and WMD grade, agreement between RI and DR was similar to agreement between 2 neuroradiologists directly reviewing neuroimages. It is highly feasible to use NLP to identify patients with SBIs and WMDs for clinical studies.

Activated platelets contribute to atherogenic processes. Experiments were designed to examine the sex distribution of platelet‐associated cytokines in middle aged men and women in whom coronary arterial calcification was defined. Blood was obtained from 17 healthy individuals (11 female, 6 male) between the ages 48–55. Coronary arterial calcification (CAC) was evaluated by electron beam computed tomography. Plasma cholesterol, lipids, and hs‐CRP were analyzed by the Mayo Clinic Clinical Laboratory and were not different between males and females. Serum cytokines were determined using cytokine arrays (Human Atherosclerosis Antibody Array I, RayBiotech, Inc., GA,. USA). Marker intensity was measured using dot blot analysis with the UN‐SCAN‐IT gel 6.1. CAC was detected in only 2 women (scores of 62 and 84%) but in 4 men (scores of 34, 63, 83 and 95%). Correcting for all other risk factors, expression of platelet‐associated cytokines RANTES and PDGF‐BB was 50% greater in females than in males. In conclusion, platelet activation as indicated by increases in RANTES and PDGF‐BB may precede arterial calcification in woman and may be useful in evaluating cardiovascular risk in early menopausal women. (IRB approval 1299‐05 and funded by Dept. Surgery, Mayo Clinic and Fnd.)

AbstractMultiple myeloma (MM) remains an incurable disease despite incorporation of novel agents. Venetoclax, a B‐cell lymphoma 2 (BCL‐2) inhibitor is approved for some hematologic malignancies but not yet for MM, although clinical trials have shown efficacy in patients with MM, particularly those harboring t(11;14). We reviewed the medical records of relapsed and/or refractory MM patients to study the efficacy and safety of venetoclax used outside of clinical trials at Mayo Clinic between December, 2016 and March, 2019. The data cut‐off date was August 06, 2020. We identified 56 patients of whom 42 (75%) harbored t(11;14). The median number of prior therapies was six (range 1–15) and 14% of patients had received ≥10 prior lines of therapy. Fifty‐three (95%) patients were refractory to an immunomodulatory drug and proteasome inhibitor. Venetoclax was used as monotherapy or doublet, in combination with dexamethasone in 55% (n = 31) and a triplet or quadruplet in 45% of patients. No patient experienced tumor lysis syndrome. Overall response rate in 52 evaluable patients was 44%. The median time to best response was 2 months and median duration of response was 13.6 months. The median PFS for the entire cohort was 5.8 (95% CI 4.9–10.3) months and median OS was 28.4 (95% CI 14.6‐not reached) months. The presence of t(11;14) was associated with improved PFS (median 9.7 months vs. 4.2 months, p = 0.019) and OS (median not reached vs. 10.8 9 months, p = 0.015). Venetoclax demonstrates encouraging activity in heavily‐treated patients with relapsed/refractory MM, particularly the t(11;14) patient‐population.