A comparison on predicting functional impact of genomic variants

ABSTRACT Single-nucleotide polymorphism (SNPs) may cause the diverse functional impact on RNA or protein changing genotype and phenotype, which may lead to common or complex diseases like cancers. Accurate prediction of the functional impact of SNPs is crucial to discover the ‘influential’ (deleterious, pathogenic, disease-causing, and predisposing) variants from massive background polymorphisms in the human genome. Increasing computational methods have been developed to predict the functional impact of variants. However, predictive performances of these computational methods on massive genomic variants are still unclear. In this regard, we systematically evaluated 14 important computational methods including specific methods for one type of variant and general methods for multiple types of variants from several aspects; none of these methods achieved excellent (AUC ≥ 0.9) performance in both data sets. CADD and REVEL achieved excellent performance on multiple types of variants and missense variants, respectively. This comparison aims to assist researchers and clinicians to select appropriate methods or develop better predictive methods.

A Human Factors Study Exploring the Experience of Participants Using VEGA, a Smartphone Migraine Management Application

Background and objectives: There is increasing interest by patients and healthcare providers in using digital tools such as smartphone applications to log migraine days, potential triggers and medication use. However, there are opportunities to optimize the learnability and ease of use of these applications. In this human factors study, we evaluated the experience of individuals with migraine using the VEGA mobile application. Material and methods: For 4 weeks, individuals diagnosed with migraine used the VEGA application, which generated a migraine report containing 4 weeks of data, where migraine days were reported based on functional impact, pain severity, and medication use. Participants also responded to a survey and rated the ease of use of the application using a 6-point Likert scale, with “very easy” being the highest ranking. Results: A total of 22 participants completed this study, ranged between 22 to 57 years old, and 54% were males. Eighteen participants completed the migraine report and logged 160 total migraine days. Participants reported the functional impact of migraine as "mild," "moderate," or "severe" for respectively 2, 44, and 50 of the logged migraine days. The pain severity was scored as “mild” for 24 days, “moderate” for 65 days, and “severe” for 63 days. Moreover, 20 participants reported it was “easy” or “very easy” to learn how to use the application, and 19 participants found it “simple” or “extremely simple” to use. Conclusions: In this human factors study, the VEGA application was easy to use, providing real-time patient-reported data.

Functional impact and targetability of PI3KCA, GNAS, and PTEN mutations in a spindle cell rhabdomyosarcoma with MYOD1 L122R mutation

Spindle cell/sclerosing rhabdomyosarcoma (ssRMS) is a rare subtype of rhabdomyosarcoma, commonly harboring a gain-of-function L122R mutation in the muscle-specific master transcription factor MYOD1. MYOD1-mutated ssRMS is almost invariably fatal, and development of novel therapeutic approaches based on the biology of the disease is urgently needed. MYOD1 L122R affects the DNA-binding domain and is believed to confer MYC-like properties to MYOD1, driving oncogenesis. Moreover, the majority of the MYOD1-mutated ssRMS harbor additional alterations activating the PI3K/AKT pathway. It is postulated that the PI3K/AKT pathway cooperates with MYOD1 L122R. To address this biological entity, we established and characterized a new patient-derived ssRMS cell line OHSU-SARC001, harboring MYOD1 L122R as well as alterations in PTEN, PIK3CA, and GNAS. We explored the functional impact of these aberrations on oncogenic signaling with gain-of-function experiments in C2C12 murine muscle lineage cells. These data reveal that PIK3CAI459_T462del, the novel PIK3CA variant discovered in this patient specimen, is a constitutively active kinase, albeit to a lesser extent than PI3KCAE545K, a hotspot oncogenic mutation. Furthermore, we examined the effectiveness of molecularly targeted PI3K/AKT/mTOR and RAS/MAPK inhibitors to block oncogenic signaling and suppress the growth of OHSU-SARC001 cells. Dual PI3K/mTOR (LY3023414, bimiralisib) and AKT inhibitors (ipatasertib, afuresertib) induced dose-dependent reductions in cell growth. However, mTOR-selective inhibitors (everolimus, rapamycin) alone did not exert cytotoxic effects. The MEK1/2 inhibitor trametinib did not impact proliferation even at the highest doses tested. Our data suggest that molecularly targeted strategies may be effective in PI3K/AKT/mTOR-activated ssRMS. Taken together, these data highlight the importance of utilizing patient-derived models to assess molecularly targetable treatments and their potential as future treatment options.

Predicting the Functional Impact of KCNQ1 Variants with Artificial Neural Networks

Predicting the functional impact of KCNQ1 variants of uncertain significance (VUS) can assist physicians in taking appropriate treatment decision for patients with genetic heart rhythm disorder. This work presents three artificial neural network (ANN)-based predictive models that classify four key functional parameters of KCNQ1 variants as normal or dysfunctional using evolutionary and/or biophysical descriptors. Recent advances in predicting protein structure and variant properties with artificial intelligence (AI) rely heavily on the availability of evolutionary features and thus fail to directly assess the biophysical underpinnings of a change in structure and/or function. The central goal of this work was to develop an ANN model based on structure and physiochemical properties of KCNQ1, that performs better or comparable with algorithms only on evolutionary features. These biophysical features highlight the structure-function relationships that govern protein stability, function, and regulation. The input sensitivity algorithm incorporates the roles of hydrophobicity, polarizability, and functional densities on key functional parameters of the KCNQ1 channel. Inclusion of the biophysical features outperforms exclusive use of evolutionary features in predicting variant activation voltage and deactivation time. As AI is increasing applied to problems in biology, biophysical understanding will be critical with respect to 'explainable AI', i.e., understanding the relation of sequence, structure, and function of proteins. Our model is available at www.kcnq1predict.org.

Probing Isoform Switching Events in Various Cancer Types: Lessons From Pan-Cancer Studies

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. In cancer, alternative splicing is frequently disturbed, leading to changes in the expression of alternatively spliced protein isoforms. Advances in sequencing technologies and analysis methods led to new insights into the extent and functional impact of disturbed alternative splicing events. In this review, we give a brief overview of the molecular mechanisms driving alternative splicing, highlight the function of alternative splicing in healthy tissues and describe how alternative splicing is disrupted in cancer. We summarize current available computational tools for analyzing differential transcript usage, isoform switching events, and the pathogenic impact of cancer-specific splicing events. Finally, the strategies of three recent pan-cancer studies on isoform switching events are compared. Their methodological similarities and discrepancies are highlighted and lessons learned from the comparison are listed. We hope that our assessment will lead to new and more robust methods for cancer-specific transcript detection and help to produce more accurate functional impact predictions of isoform switching events.

Cell Painting predicts impact of lung cancer variants

Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding gene is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance (VUS) as impactful vs. neutral in an approach called expression-based variant-impact phenotyping (eVIP). We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cell's image, we found that cell morphological profiling (cmVIP) can predict variants' functional impact and, particularly at the single-cell level, reveals biological insights into variants which can be explored in our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene-specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

Fast improvements in functional status after osteopathic manipulative treatment based on myofascial release in patients with moderate or severe fibromyalgia: a retrospective study

Objectives Fibromyalgia (FM) is a chronic pain syndrome characterized by a large variety of symptoms. Evidence suggests that an alteration of central nervous system processing of pain could be involved. The purpose of this study is to analyze clinical records of patients affected by FM who underwent osteopathic manipulative treatment (OMT), predominantly based on a myofascial release approach (MFR). Methods This retrospective study considered records of 21 FM patients with moderate or severe functional impact, who consented to OMT in addition to their usual care. The assessment considered the following measures: FIQ (functional status), SF36 (quality of life), VAS (pain), TSK (kinesiophobia) and PSQI (quality of sleeping). Patients were preliminarily assessed over a 1 month run-in phase, then after 1, 2 and 4 months; a 1 month follow-up was also considered. Results After one month, 71% of patients reported a decrease in functional impact and scores remained stable until follow-up (from 69.8 to 52.37, p≤0.001). Overall, after four months, patients improved their quality of life, with a score ranging from 33.47 to 42.6 (p≤0.05). We also observed a reduction of pain (p≤0.05). Conclusions A series of OMT sessions based on MFR could play a therapeutic role in improving functional status, pain and quality of life over a period of 4 months.

A modular toolbox to generate complex polymeric ubiquitin architectures using orthogonal sortase enzymes

The post-translational modification of proteins with ubiquitin (Ub) and Ub-like modifiers (Ubls) represents one of the most important regulators in eukaryotic biology. Polymeric Ub/Ubl chains of distinct topologies control the activity, stability, interaction and localization of almost all cellular proteins and elicit a variety of biological outputs. Our ability to characterize the roles of distinct Ub/Ubl topologies and to identify enzymes and receptors that create, recognize and remove these modifications is however hampered by the difficulty to prepare them. Here we introduce a modular toolbox (Ubl-tools) that allows the stepwise assembly of Ub/Ubl chains in a flexible and user-defined manner facilitated by orthogonal sortase enzymes. We demonstrate the universality and applicability of Ubl-tools by generating distinctly linked Ub/Ubl hybrid chains, and investigate their role in DNA damage repair. Importantly, Ubl-tools guarantees straightforward access to target proteins, site-specifically modified with distinct homo- and heterotypic (including branched) Ub chains, providing a powerful approach for studying the functional impact of these complex modifications on cellular processes.