CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods

BACKGROUND

The Critical Assessment of Genome Interpretation (CAGI) aims to advance the state-of-the-art for computational prediction of genetic variant impact, particularly where relevant to disease. The five complete editions of the CAGI community experiment comprised 50 challenges, in which participants made blind predictions of phenotypes from genetic data, and these were evaluated by independent assessors.

RESULTS

Performance was particularly strong for clinical pathogenic variants, including some difficult-to-diagnose cases, and extends to interpretation of cancer-related variants. Missense variant interpretation methods were able to estimate biochemical effects with increasing accuracy. Assessment of methods for regulatory variants and complex trait disease risk was less definitive and indicates performance potentially suitable for auxiliary use in the clinic.

CONCLUSIONS

Results show that while current methods are imperfect, they have major utility for research and clinical applications. Emerging methods and increasingly large, robust datasets for training and assessment promise further progress ahead.

RNF43 truncations trap CK1 to drive niche-independent self-renewal in cancer

Wnt/β-catenin signaling is a primary pathway for stem cell maintenance during tissue renewal and a frequent target for mutations in cancer. Impaired Wnt receptor endocytosis due to loss of the ubiquitin ligase RNF43 gives rise to Wnt-hypersensitive tumors that are susceptible to anti-Wnt-based therapy. Contrary to this paradigm, we identify a class of RNF43 truncating cancer mutations that induce β-catenin-mediated transcription, despite exhibiting retained Wnt receptor downregulation. These mutations interfere with a ubiquitin-independent suppressor role of the RNF43 cytosolic tail that involves Casein kinase 1 (CK1) binding and phosphorylation. Mechanistically, truncated RNF43 variants trap CK1 at the plasma membrane, thereby preventing β-catenin turnover and propelling ligand-independent target gene transcription. Gene editing of human colon stem cells shows that RNF43 truncations cooperate with p53 loss to drive a niche-independent program for self-renewal and proliferation. Moreover, these RNF43 variants confer decreased sensitivity to anti-Wnt-based therapy. Our data demonstrate the relevance of studying patient-derived mutations for understanding disease mechanisms and improved applications of precision medicine.

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.

BRCA1- and BRCA2-specific in silico tools for variant interpretation in the CAGI 5 ENIGMA challenge

BRCA1 and BRCA2 (BRCA1/2) germline variants disrupting the DNA protective role of these genes increase the risk of hereditary breast and ovarian cancers. Correct identification of these variants then becomes clinically relevant, because it may increase the survival rates of the carriers. Unfortunately, we are still unable to systematically predict the impact of BRCA1/2 variants. In this article, we present a family of in silico predictors that address this problem, using a gene-specific approach. For each protein, we have developed two tools, aimed at predicting the impact of a variant at two different levels: Functional and clinical. Testing their performance in different datasets shows that specific information compensates the small number of predictive features and the reduced training sets employed to develop our models. When applied to the variants of the BRCA1/2 (ENIGMA) challenge in the fifth Critical Assessment of Genome Interpretation (CAGI 5) we find that these methods, particularly those predicting the functional impact of variants, have a good performance, identifying the large compositional bias towards neutral variants in the CAGI sample. This performance is further improved when incorporating to our prediction protocol estimates of the impact on splicing of the target variant.

HIV infection is influenced by dynamin at 3 independent points in the viral life cycle

CD4 T cells are important cellular targets for HIV-1, yet the primary site of HIV fusion remains unresolved. Candidate fusion sites are either the plasma membrane or from within endosomes. One area of investigation compounding the controversy of this field, is the role of the protein dynamin in the HIV life cycle. To understand the role of dynamin in primary CD4 T cells we combined dynamin inhibition with a series of complementary assays based on single particle tracking, HIV fusion, detection of HIV DNA products and active viral transcription. We identify 3 levels of dynamin influence on the HIV life cycle. Firstly, dynamin influences productive infection by preventing cell cycle progression. Secondly, dynamin influences endocytosis rates and increases the probability of endosomal fusion. Finally, we provide evidence in resting CD4 T cells that dynamin directly regulates the HIV fusion reaction at the plasma membrane. We confirm this latter observation using 2 divergent dynamin modulating compounds, one that enhances dynamin conformations associated with dynamin ring formation (ryngo-1-23) and the other that preferentially targets dynamin conformations that appear in helices (dyngo-4a). This in-depth understanding of dynamin's roles in HIV infection clarifies recent controversies and furthermore provides evidence for dynamin regulation specifically in the HIV fusion reaction.