Adenosine-to-inosine (A-to-I) RNA editing is an important post-transcriptional modification that affects the information encoded from DNA to RNA to protein. RNA editing can generate a multitude of ...transcript isoforms and can potentially be used to optimize protein function in response to varying conditions. In light of this and the fact that millions of editing sites have been identified in many different species, it is interesting to examine the extent to which these sites have evolved to be functionally important. In this review, we discuss results pertaining to the evolution of RNA editing, specifically in humans, cephalopods, and Drosophila. We focus on how comparative genomics approaches have aided in the identification of sites that are likely to be advantageous. The use of RNA editing as a mechanism to adapt to varying environmental conditions will also be reviewed.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Adenosine-to-inosine RNA editing diversifies the transcriptome and promotes functional diversity, particularly in the brain. A plethora of editing sites has been recently identified; however, how ...they are selected and regulated and which are functionally important are largely unknown. Here we show the cis-regulation and stepwise selection of RNA editing during Drosophila evolution and pinpoint a large number of functional editing sites. We found that the establishment of editing and variation in editing levels across Drosophila species are largely explained and predicted by cis-regulatory elements. Furthermore, editing events that arose early in the species tree tend to be more highly edited in clusters and enriched in slowly-evolved neuronal genes, thus suggesting that the main role of RNA editing is for fine-tuning neurological functions. While nonsynonymous editing events have been long recognized as playing a functional role, in addition to nonsynonymous editing sites, a large fraction of 3'UTR editing sites is evolutionarily constrained, highly edited, and thus likely functional. We find that these 3'UTR editing events can alter mRNA stability and affect miRNA binding and thus highlight the functional roles of noncoding RNA editing. Our work, through evolutionary analyses of RNA editing in Drosophila, uncovers novel insights of RNA editing regulation as well as its functions in both coding and non-coding regions.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
ADAR RNA editing enzymes are high-affinity dsRNA-binding proteins that deaminate adenosines to inosines in pre-mRNA hairpins and also exert editing-independent effects. We generated a Drosophila Adar
...mutant strain encoding a catalytically inactive Adar with CRISPR/Cas9. We demonstrate that Adar adenosine deamination activity is necessary for normal locomotion and prevents age-dependent neurodegeneration. The catalytically inactive protein, when expressed at a higher than physiological level, can rescue neurodegeneration in Adar mutants, suggesting also editing-independent effects. Furthermore, loss of Adar RNA editing activity leads to innate immune induction, indicating that Drosophila Adar, despite being the homolog of mammalian ADAR2, also has functions similar to mammalian ADAR1. The innate immune induction in fly Adar mutants is suppressed by silencing of Dicer-2, which has a RNA helicase domain similar to MDA5 that senses unedited dsRNAs in mammalian Adar1 mutants. Our work demonstrates that the single Adar enzyme in Drosophila unexpectedly has dual functions.
This study presents a roadmap for converting California's all-purpose (electricity, transportation, heating/cooling, and industry) energy infrastructure to one derived entirely from wind, water, and ...sunlight (WWS) generating electricity and electrolytic hydrogen. California's available WWS resources are first evaluated. A mix of WWS generators is then proposed to match projected 2050 electric power demand after all sectors have been electrified. The plan contemplates all new energy from WWS by 2020, 80–85% of existing energy converted by 2030, and 100% by 2050. Electrification plus modest efficiency measures may reduce California's end-use power demand ∼44% and stabilize energy prices since WWS fuel costs are zero. Several methods discussed should help generation to match demand. A complete conversion in California by 2050 is estimated to create ∼220,000 more 40-year jobs than lost, eliminate ∼12,500 (3800–23,200) state air-pollution premature mortalities/yr, avoid $103 (31–232) billion/yr in health costs, representing 4.9 (1.5–11.2)% of California's 2012 gross domestic product, and reduce California's 2050 global climate cost contribution by $48 billion/yr. The California air-pollution health plus global climate cost benefits from eliminating California emissions could equal the $1.1 trillion installation cost of 603 GW of new power needed for a 100% all-purpose WWS system within ∼7 (4–14) years.
•Roadmap to repower California’s all-purpose energy with wind, water, sunlight (WWS).•All new energy WWS by 2020, 80–85% existing energy WWS by 2030, 100% by 2050.•Creates ∼220,000 more 40-year jobs than are lost.•Avoids 12,500 pollution deaths/yr, $103 bil/yr health costs, $48 bil/yr climate costs.•Electrification reduces power demand by ∼44%, and WWS stabilizes energy prices.
•This study investigated SRE risk factors after densomuab treatment discontinuation.•An unbiased machine learning approach was developed toevaluate >60 variables.•Prior SREs and short denosumab ...treatment duration were primary risk factors.•The results can guide denosumab persistence decisions and improve patient outcomes.
Clinical practice guidelines recommend the use of bone-targeting agents for preventing skeletal-related events (SREs) among patients with bone metastases from solid tumors. The anti-RANKL monoclonal antibody denosumab is approved for the prevention of SREs in patients with bone metastases from solid tumors. However, real-world data are lacking on the impact of individual risk factors for SREs, specifically in the context of denosumab discontinuation.
We aim to identify risk factors associated with SRE incidence following denosumab discontinuation using a machine learning approach to help profile patients at a higher risk of developing SREs following discontinuation of denosumab treatment.
Using the Optum PanTher Electronic Health Record repository, patients diagnosed with incident bone metastases from primary solid tumors between January 1, 2007, and September 1, 2019, were evaluated for inclusion in the study. Eligible patients received ≥ 2 consecutive 120 mg denosumab doses on a 4-week (± 14 days) schedule with a minimum follow-up of ≥ 1 year after the last denosumab dose, or an SRE occurring between days 84 and 365 after denosumab discontinuation. Extreme gradient boosting was used to develop an SRE risk prediction model evaluated on a test dataset. Multiple variables associated with patient demographics, comorbidities, laboratory values, treatments, and denosumab exposures were examined as potential factors for SRE risk using Shapley Additive Explanations (SHAP). Univariate analyses on risk factors with the highest importance from pooled and tumor-specific models were also conducted.
A total of 1,414 adult cancer patients (breast: 40%, prostate: 30%, lung: 13%, other: 17%) were eligible, of whom 1,133 (80%) were assigned to model training and 281 (20%) to model evaluation. The median age at inclusion was 67 (range, 19–89) years with a median duration of denosumab treatment of 253 (range, 88–2,726) days; 490 (35%) patients experienced ≥ 1 SRE 83 days after denosumab discontinuation. Meaningful model performance was evaluated by an area under the receiver operating curve score of 77% and an F1 score of 62%; model precision was 60%, with 63% sensitivity and 78% specificity. SHAP identified several significant factors for the tumor-agnostic and tumor-specific models that predicted an increased SRE risk following denosumab discontinuation, including prior SREs, shorter denosumab treatment duration, ≥ 4 clinic visits per month with at least one hospitalization (all-cause) event from the baseline period up to discontinuation of denosumab, younger age at bone metastasis, shorter time to denosumab initiation from bone metastasis, and prostate cancer.
This analysis showed a higher cumulative number of SREs, prior SREs relative to denosumab initiation, a higher number of hospital visits, and a shorter denosumab treatment duration as significant factors that are associated with an increased SRE risk after discontinuation of denosumab, in both the tumor-agnostic and tumor-specific models. Our machine learning approach to SRE risk factor identification reinforces treatment guidance on the persistent use of denosumab and has the potential to help clinicians better assess a patient’s need to continue denosumab treatment and improve patient outcomes.
Abstract
Background: The anti-RANKL monoclonal antibody denosumab has been demonstrated to be superior to the bisphosphonate zoledronate in preventing skeletal-related events (SREs) among patients ...with incident bone metastases (BMs) from solid tumors (STs), including breast cancer. Clinical guidelines recommend the use of a bone-targeting agent for SRE prevention for ≥2 years. However, the denosumab treatment duration is often <1 year in the US. We applied a supervised machine learning approach using real-world data to estimate patient-level SRE risk following cessation of denosumab and determine risk factors associated with increased SRE risk. The method selected prior SREs, shorter denosumab treatment duration, and higher number of clinic visits as the top-ranked risk factors among a diverse group of patients with BMs from STs (Stopeck et al., ASCO 2021). Here, we report the top-ranked risk factors for the subgroup of patients with BMs from breast cancer. Methods: Using the Optum PanTher Electronic Health Record repository, patients diagnosed with incident BMs from a primary ST between January 1, 2007, and September 1, 2019, were evaluated for inclusion in the study. Eligible patients must have received ≥2 consecutive 120 mg denosumab doses on every 4-week (±14 days) schedule and had a minimum follow-up ≥1 year after the last denosumab dose or an SRE occurrence between days 84 and 365 following denosumab cessation. An SRE risk prediction model was developed using extreme gradient boosting and evaluated on an independent test dataset. Multiple variables associated with patient demographics, comorbidities, laboratory values, treatments, and denosumab exposures were examined as potential risk factors for SREs. After denosumab cessation, the impact and relative importance of these factors were extracted from the model using Shapley Additive Explanations (SHAP). In addition, findings from univariate analyses on risk factors with high importance from the breast cancer model were reported. Results: Of 1414 patients who met the inclusion criteria, 563 (40%) had BMs from breast cancer. Following denosumab cessation, 167 (30%) patients in the breast cancer subgroup experienced ≥1 SRE. The breast cancer model performance was meaningful, as evidenced by the area under the receiver operating characteristic (AUROC) score of 73%. SHAP resulted in several significant factors that predicted an increased SRE risk for the subgroup following denosumab cessation, including denosumab treatment duration of ≤8 months, prior SREs, and an average of >2 clinic visits per month (Table). Univariate analyses showed a positive correlation between increased SRE risk and prior SREs, while they revealed an inverse relationship between increased SRE risk and longer durations of denosumab. Conclusion: Shorter denosumab treatment duration, prior SREs, and higher number of clinic visits are top-ranked risk factors associated with SREs after discontinuation of denosumab treatment in patients with BMs from STs, including breast cancer. A machine learning approach to SRE risk factor identification may help clinicians assess the risks of discontinuing denosumab treatment and improve clinical outcomes for patients with BMs from breast cancer.
SHAP Risk Factors That Increase SRE Risk 3-12 Months After Denosumab Cessation in Patients With BMsDenosumab therapy decisions: denosumab duration ≤8 months, time to denosumab initiation ≤2 months after BM diagnosisPrior SREs: ≥2 cumulative number of SREs since baseline up to cessationa, SRE occurrence (from denosumab initiation to cessation)Comorbidities: patients with anxietyVisits: >2 average number of visits per month (hospitalization, emergency room, and other visits excluding nonphysician interaction), ≥1 hospitalization, ≥1 emergency room visitaBaseline was defined as 180 days before the date of initial BM diagnosis. BM, bone metastasis; SHAP, Shapley Additive Explanations; SRE, skeletal-related event
Citation Format: Alison Stopeck, Celestia Higano, David Henry, Basia Bachmann, Marko Rehn, Dionna Jacobson, Benoit Cadieux, Hossam Saad. A machine learning approach to identify risk factors associated with skeletal-related events following denosumab cessation among patients with bone metastases from breast cancer abstract. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-20-02.
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Background: The anti-RANKL monoclonal antibody denosumab has been shown to be superior to the bisphosphonate zoledronate for the prevention of skeletal-related events (SREs) in ...patients with incident bone metastases (BM) from solid tumors (ST). Clinical guidelines recommend the use of a bone-targeting agent for SRE prevention for ≥ 2 years. However, real-world treatment patterns in the U.S. suggest that the denosumab treatment duration is often < 1 year. Applying a machine learning approach, we sought to identify risk factors associated with SRE incidence following cessation of denosumab to help inform optimal clinical SRE prevention strategies. Methods: Using the Optum PanTher Electronic Health Record repository, patients diagnosed with incident BM from a primary ST between 1 Jan 2007 and 1 Sep 2019 were evaluated for inclusion in the study. Eligible patients had to receive ≥ 2 consecutive 120 mg denosumab doses on an every 4-week (± 14 days) schedule and have a minimum follow-up ≥ 1 year after the last denosumab dose or an SRE occurring between days 84 and 365 after denosumab cessation. Extreme gradient boosting was used to develop an SRE risk prediction model evaluated on a test dataset. Impact and relative importance of available medical, clinical, and treatment factors on SRE risk following denosumab cessation were extracted from the model using Shapley additive explanations (SHAP). Univariate analyses on risk factors with the highest importance from pooled and tumor-specific models were also conducted. Results: A total of 1,414 patients (breast, n = 563 40%; prostate, 421 30%; lung, 180 13%; other cancers, 250 17%) met inclusion criteria, with a median of 253 (min, 88; max, 2726) days of denosumab treatment; 490 (35%) experienced ≥ 1 SRE following denosumab cessation. With a meaningful model performance based on an area under the receiver operating characteristic (AUROC) score of 77%, SHAP identified several significant factors that predicted an increased SRE risk following denosumab cessation, including prior SREs, shorter denosumab treatment duration, and a higher number of clinic visits as the top-ranked factors (Table). Conclusions: A machine learning approach to SRE risk factor identification may help clinicians better assess the individualized patient’s need for denosumab treatment persistence and improve patient outcomes. Results from tumor-specific groups will be presented at the meeting.Table: see text
Mass azithromycin distributions have been shown to reduce mortality in preschool children, although the factors mediating this mortality reduction are not clear. This study was performed to determine ...whether mass distribution of azithromycin, which has modest antimalarial activity, reduces the community burden of malaria.
In a cluster-randomized trial conducted from 23 November 2014 until 31 July 2017, 30 rural communities in Niger were randomized to 2 years of biannual mass distributions of either azithromycin (20 mg/kg oral suspension) or placebo to children aged 1 to 59 months. Participants, field staff, and investigators were masked to treatment allocation. The primary malaria outcome was the community prevalence of parasitemia on thick blood smear, assessed in a random sample of children from each community at study visits 12 and 24 months after randomization. Analyses were performed in an intention-to-treat fashion. At the baseline visit, a total of 1,695 children were enumerated in the 15 azithromycin communities, and 3,029 children were enumerated in the 15 placebo communities. No communities were lost to follow-up. The mean prevalence of malaria parasitemia at baseline was 8.9% (95% CI 5.1%-15.7%; 52 of 552 children across all communities) in the azithromycin-treated group and 6.7% (95% CI 4.0%-12.6%; 36 of 542 children across all communities) in the placebo-treated group. In the prespecified primary analysis, parasitemia was lower in the azithromycin-treated group at month 12 (mean prevalence 8.8%, 95% CI 5.1%-14.3%; 51 of 551 children across all communities) and month 24 (mean 3.5%, 95% CI 1.9%-5.5%; 21 of 567 children across all communities) than it was in the placebo-treated group at month 12 (mean 15.3%, 95% CI 10.8%-20.6%; 81 of 548 children across all communities) and month 24 (mean 4.8%, 95% CI 3.3%-6.4%; 28 of 592 children across all communities) (P = 0.02). Communities treated with azithromycin had approximately half the odds of parasitemia compared to those treated with placebo (odds ratio OR 0.54, 95% CI 0.30 to 0.97). Parasite density was lower in the azithromycin group than the placebo group at 12 and 24 months (square root-transformed outcome; density estimates were 7,540 parasites/μl lower 95% CI -350 to -12,550 parasites/μl; P = 0.02 at a mean parasite density of 17,000, as was observed in the placebo arm). No significant difference in hemoglobin was observed between the 2 treatment groups at 12 and 24 months (mean 0.34 g/dL higher in the azithromycin arm, 95% CI -0.06 to 0.75 g/dL; P = 0.10). No serious adverse events were reported in either group, and among children aged 1 to 5 months, the most commonly reported nonserious adverse events (i.e., diarrhea, vomiting, and rash) were less common in the azithromycin-treated communities. Limitations of the trial include the timing of the treatments and monitoring visits, both of which took place before the peak malaria season, as well as the uncertain generalizability to areas with different malaria transmission dynamics.
Mass azithromycin distributions were associated with a reduced prevalence of malaria parasitemia in this trial, suggesting one possible mechanism for the mortality benefit observed with this intervention.
The trial was registered on ClinicalTrials.gov (NCT02048007).
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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