Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations

Model-agnostic interpretation techniques allow us to explain the behavior of any predictive model. Due to different notations and terminology, it is difficult to see how they are related. A unified view on these methods has been missing. We present the generalized SIPA (sampling, intervention, prediction, aggregation) framework of work stages for model-agnostic interpretations and demonstrate how several prominent methods for feature effects can be embedded into the proposed framework. Furthermore, we extend the framework to feature importance computations by pointing out how variance-based and performance-based importance measures are based on the same work stages. The SIPA framework reduces the diverse set of model-agnostic techniques to a single methodology and establishes a common terminology to discuss them in future work

An exploration of the heterogeneity in effects of SGLT2 inhibition on cardiovascular and all-cause mortality in the EMPA-REG OUTCOME, CANVAS Program, DECLARE-TIMI 58, and CREDENCE trials

Background: Large-scale outcome trials of sodium glucose co-transporter 2 (SGLT2) inhibitors in patients with type 2 diabetes have identified consistent effects on major adverse cardiovascular events, heart failure, and progression of kidney disease. However, the magnitude of effects on cardiovascular and all-cause death appeared to vary between some of the studies. Methods: We explored the impact of differences in trial methodologies, participant characteristics, types of deaths, follow-up duration, effects on intermediate markers of risk, and drug selectivity for SGLT2 on the magnitude of the protective effect against fatal events achieved in the 4 trials. Results: The trial populations differed substantively in the proportions with baseline atherosclerotic cardiovascular disease history (99.2% in EMPA-REG OUTCOME to 40.6% in DECLARE-TIMI 58), and macroalbuminuria (88.0% in CREDENCE to 7.6% in the CANVAS Program). Meta-regression analyses identified no clear effect of these (both P > 0.09) or other participant characteristics on mortality benefits (all P > 0.55). Other differences between the trials (duration, selectivity of the SGLT2 inhibitor, or effects on intermediate markers of risk) also did not explain the heterogeneity in effects on mortality observed (all P > 0.30). Conclusion: No clear explanation for the statistical evidence of heterogeneity in effects of SGLT2 inhibition on fatal outcomes between the trials could be identified. While the analyses had limited statistical power, these results raise the possibility that the observed variations in treatment effects on fatal outcomes between trials may be at least partly due to chance

Effect of SGLT2 Inhibitors on Stroke and Atrial Fibrillation in Diabetic Kidney Disease:Results From the CREDENCE Trial and Meta-Analysis

BACKGROUND AND PURPOSE: Chronic kidney disease with reduced estimated glomerular filtration rate or elevated albuminuria increases risk for ischemic and hemorrhagic stroke. This study assessed the effects of sodium glucose cotransporter 2 inhibitors (SGLT2i) on stroke and atrial fibrillation/flutter (AF/AFL) from CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) and a meta-analysis of large cardiovascular outcome trials (CVOTs) of SGLT2i in type 2 diabetes mellitus.METHODS: CREDENCE randomized 4401 participants with type 2 diabetes mellitus and chronic kidney disease to canagliflozin or placebo. Post hoc, we estimated effects on fatal or nonfatal stroke, stroke subtypes, and intermediate markers of stroke risk including AF/AFL. Stroke and AF/AFL data from 3 other completed large CVOTs and CREDENCE were pooled using random-effects meta-analysis.RESULTS: In CREDENCE, 142 participants experienced a stroke during follow-up (10.9/1000 patient-years with canagliflozin, 14.2/1000 patient-years with placebo; hazard ratio [HR], 0.77 [95% CI, 0.55-1.08]). Effects by stroke subtypes were: ischemic (HR, 0.88 [95% CI, 0.61-1.28]; n=111), hemorrhagic (HR, 0.50 [95% CI, 0.19-1.32]; n=18), and undetermined (HR, 0.54 [95% CI, 0.20-1.46]; n=17). There was no clear effect on AF/AFL (HR, 0.76 [95% CI, 0.53-1.10]; n=115). The overall effects in the 4 CVOTs combined were: total stroke (HRpooled, 0.96 [95% CI, 0.82-1.12]), ischemic stroke (HRpooled, 1.01 [95% CI, 0.89-1.14]), hemorrhagic stroke (HRpooled, 0.50 [95% CI, 0.30-0.83]), undetermined stroke (HRpooled, 0.86 [95% CI, 0.49-1.51]), and AF/AFL (HRpooled, 0.81 [95% CI, 0.71-0.93]). There was evidence that SGLT2i effects on total stroke varied by baseline estimated glomerular filtration rate (P=0.01), with protection in the lowest estimated glomerular filtration rate (&lt;45 mL/min/1.73 m2]) subgroup (HRpooled, 0.50 [95% CI, 0.31-0.79]).CONCLUSIONS: Although we found no clear effect of SGLT2i on total stroke in CREDENCE or across trials combined, there was some evidence of benefit in preventing hemorrhagic stroke and AF/AFL, as well as total stroke for those with lowest estimated glomerular filtration rate. Future research should focus on confirming these data and exploring potential mechanisms. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02065791.</p

Kidney, Cardiovascular, and Safety Outcomes of Canagliflozin according to Baseline Albuminuria:A CREDENCE Secondary Analysis

BACKGROUND AND OBJECTIVES: The kidney protective effects of renin-angiotensin system inhibitors are greater in people with higher levels of albuminuria at treatment initiation. Whether this applies to sodium-glucose cotransporter 2 (SGLT2) inhibitors is uncertain, particularly in patients with a very high urine albumin-to-creatinine ratio (UACR; ≥3000 mg/g). We examined the association between baseline UACR and the effects of the SGLT2 inhibitor, canagliflozin, on efficacy and safety outcomes in the Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) randomized controlled trial. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The study enrolled 4401 participants with type 2 diabetes, an eGFR of 30 to 300 to 5000 mg/g. Using Cox proportional hazards regression, we examined the relative and absolute effects of canagliflozin on kidney, cardiovascular, and safety outcomes according to a baseline UACR of ≤1000 mg/g (n=2348), >1000 to 1000 to <3000 mg/g, and 37% (HR, 0.63; 95% CI, 0.47 to 0.84) in the highest subgroup (Pheterogeneity=0.55). Absolute risk reductions for kidney outcomes were greater in participants with higher baseline albuminuria; the number of primary composite events prevented across ascending UACR categories were 17 (95% CI, 3 to 38), 45 (95% CI, 9 to 81), and 119 (95% CI, 35 to 202) per 1000 treated participants over 2.6 years (Pheterogeneity=0.02). Rates of kidney-related adverse events were lower with canagliflozin, with a greater relative reduction in higher UACR categories. CONCLUSIONS: Canagliflozin safely reduces kidney and cardiovascular events in people with type 2 diabetes and severely increased albuminuria. In this population, the relative kidney benefits were consistent over a range of albuminuria levels, with greatest absolute kidney benefit in those with an UACR ≥3000 mg/g. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: ClinicalTrials.gov: CREDENCE, NCT02065791. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_02_22_CJN15260920_final.mp3

Src activation by β-adrenoreceptors is a key switch for tumor metastasis

Norepinephrine (NE) can modulate multiple cellular functions important for cancer progression; however, how this single extracellular signal regulates such a broad array of cellular processes is unknown. Here, we identify Src as a key regulator of phosphoproteomic signaling networks activated in response to beta-adrenergic signaling in cancer cells. These results also identify a new mechanism of Src phosphorylation that mediates beta-adrenergic/PKA regulation of downstream networks, thereby enhancing tumor cell migration, invasion and growth. In human ovarian cancer samples, high tumoral NE levels were correlated with high pSrcY419 levels. Moreover, among cancer patients, the use of beta blockers was significantly associated with reduced cancer-related mortality. Collectively, these data provide a pivotal molecular target for disrupting neural signaling in the tumor microenvironment

A Simple but Highly Effective Approach to Evaluate the Prognostic Performance of Gene Expression Signatures

BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC) in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited

PDK-1 regulates lactate production in hypoxia and is associated with poor prognosis in head and neck squamous cancer

Here we describe the expression and function of a HIF-1-regulated protein pyruvate dehydrogenase kinase-1 (PDK-1) in head and neck squamous cancer (HNSCC). Using RNAi to downregulate hypoxia-inducible PDK-1, we found that lactate and pyruvate excretion after 16–48 h of hypoxia was suppressed to normoxic levels. This indicates that PDK-1 plays an important role in maintaining glycolysis. Knockdown had no effect on proliferation or survival under hypoxia. The immunohistochemical expression of PDK-1 was assessed in 140 cases of HNSCC. PDK-1 expression was not expressed in normal tissues but was upregulated in HNSCC and found to be predominantly cytoplasmic with occasional strong focal nuclear expression. It was strongly related to poor outcome (P=0.005 split by median). These results indicate that HIF regulation of PDK-1 has a key role in maintaining lactate production in human cancer and that the investigation of PDK-1 inhibitors should be investigated for antitumour effects

MetWAMer: eukaryotic translation initiation site prediction

<p>Abstract</p> <p>Background</p> <p>Translation initiation site (TIS) identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations.</p> <p>Results</p> <p>MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the <it>k</it>-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage.</p> <p>Conclusion</p> <p>We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.</p

Unbiased Functional Proteomics Strategy for Protein Kinase Inhibitor Validation and Identification of bona fide Protein Kinase Substrates: Application to Identification of EEF1D as a Substrate for CK2

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