The effect of single nucleotide variants (SNVs) in coding and noncoding regions is of great interest in genetics. Although many computational methods aim to elucidate the effects of SNVs on cellular ...mechanisms, it is not straightforward to comprehensively cover different molecular effects. To address this, we compiled and benchmarked sequence and structure‐based variant effect predictors and we computed the impact of nearly all possible amino acid and nucleotide variants in the reference genomes of Homo sapiens, Saccharomyces cerevisiae and Escherichia coli. Studied mechanisms include protein stability, interaction interfaces, post‐translational modifications and transcription factor binding sites. We apply this resource to the study of natural and disease coding variants. We also show how variant effects can be aggregated to generate protein complex burden scores that uncover protein complex to phenotype associations based on a set of newly generated growth profiles of 93 sequenced S. cerevisiae strains in 43 conditions. This resource is available through mutfunc (www.mutfunc.com), a tool by which users can query precomputed predictions by providing amino acid or nucleotide‐level variants.
Synopsis
This study presents mutfunc, a resource that includes the pre‐computed impact of genetic variants in three model organisms (human, yeast and E. coli). These predictions can be used to prioritize genetic variants and compute gene burden scores.
Mutfunc is a resource that includes predictions on the impact of single nucleotide substitution across three organisms.
Genetic variants can be prioritized by their likely impact on various molecular processes.
A gene/complex burden score can be computed from these predictions and used to associate genotype with phenotype.
This study presents mutfunc, a resource that includes the pre‐computed impact of genetic variants in three model organisms (human, yeast and E. coli). These predictions can be used to prioritize genetic variants and compute gene burden scores.
Since the start of 2020, the world has been upended by the pandemic caused by the severe acute respiratory coronavirus type 2 (SARS‐CoV‐2), the causative agent of coronavirus disease 2019 (COVID‐19). ...It has not only led to a tragic loss of life and terrible economic costs but has also been met with an unprecedented response of the scientific and medical communities. In an effort to better understand this viral infection, scientists around the world generated the largest surge in research in documented history for any topic (Lever & Altman, 2021). A part of this work has included the need to better understand the impact of the virus on human proteins—the key machinery of the cell—and human physiology. In their recent study, Geyer and colleagues (Geyer et al, 2021) analyzed a total of 720 proteomes from longitudinal serum samples of 31 hospitalized COVID‐19 patients and control individuals with COVID‐19‐like symptoms but not infected with SARS‐CoV‐2, providing a comprehensive characterization of the plasma proteome changes along the time course of infection.
D. Memon, I. Barrio‐Hernandez, and P. Beltrao discuss the study by Geyer et al (in this issue of EMBO Mol Med) that analyzes the plasma proteome changes for a longitudinal cohort of COVID‐19 patients.
Genetic alterations in cancer cells trigger oncogenic transformation, a process largely mediated by the dysregulation of kinase and transcription factor (TF) activities. While the mutational profiles ...of thousands of tumours have been extensively characterised, the measurements of protein activities have been technically limited until recently. We compiled public data of matched genomics and (phospho)proteomics measurements for 1,110 tumours and 77 cell lines that we used to estimate activity changes in 218 kinases and 292 TFs. Co‐regulation of kinase and TF activities reflects previously known regulatory relationships and allows us to dissect genetic drivers of signalling changes in cancer. We find that loss‐of‐function mutations are not often associated with the dysregulation of downstream targets, suggesting frequent compensatory mechanisms. Finally, we identified the activities most differentially regulated in cancer subtypes and showed how these can be linked to differences in patient survival. Our results provide broad insights into the dysregulation of protein activities in cancer and their contribution to disease severity.
Synopsis
Estimation of activity changes for over 500 kinases and transcription factors in more than 1,000 cancer samples and cell lines identifies signalling regulators often dysregulated in cancer associated with patient survival.
Matched data for changes in DNA, RNA and (phospho)proteins are compiled from publicly available data across 1,000 tumour samples.
Changes in activity for over 500 kinases and transcription factors identify often dysregulated activities in cancer.
Recurrent mutations in kinases and transcription factors are not often associated with significant changes in their known targets
Signalling regulators within the same pathway tend to be co‐regulated, and activities can be used as predictors of patient survival.
Estimation of activity changes for over 500 kinases and transcription factors in more than 1,000 cancer samples and cell lines identifies signalling regulators often dysregulated in cancer associated with patient survival.
Prioritising long intergenic noncoding RNAs (lincRNAs) for functional characterisation is a significant challenge. Here we applied computational approaches to discover lincRNAs expected to play a ...critical housekeeping (HK) role within the cell. Using the Illumina Human BodyMap RNA sequencing dataset as a starting point, we first identified lincRNAs ubiquitously expressed across a panel of human tissues. This list was then further refined by reference to conservation score, secondary structure and promoter DNA methylation status. Finally, we used tumour expression and copy number data to identify lincRNAs rarely downregulated or deleted in multiple tumour types. The resulting list of candidate essential lincRNAs was then subjected to co-expression analyses using independent data from ENCODE and The Cancer Genome Atlas (TCGA). This identified a substantial subset with a predicted role in DNA replication and cell cycle regulation. One of these, HKlincR1, was selected for further characterisation. Depletion of HKlincR1 affected cell growth in multiple lung cancer cell lines, and led to disruption of genes involved in cell growth and viability. In addition, HKlincR1 expression was correlated with overall survival in lung adenocarcinoma patients. Our in silico studies therefore reveal a set of housekeeping noncoding RNAs of interest both in terms of their role in normal homeostasis, and their relevance in tumour growth and maintenance.
Diagnosis of isolated total anomalous pulmonary venous connections (TAPVCs) is relatively rare in fetal life, especially in early gestation. We report a case of a fetus diagnosed with the ...supracardiac type of TAPVC at 23 weeks gestation, with evidence of obstruction to connection of the common vertical vein to the superior vena cava. The neonate had a critical presentation at birth and underwent an emergency surgical repair immediately after birth with excellent outcome on short term follow-up with the resolution of pulmonary artery hypertension.
Phosphorylation is a critical post-translational modification involved in the regulation of almost all cellular processes. However, fewer than 5% of thousands of recently discovered phosphosites have ...been functionally annotated. In this study, we devised a chemical genetic approach to study the functional relevance of phosphosites in Saccharomyces cerevisiae. We generated 474 yeast strains with mutations in specific phosphosites that were screened for fitness in 102 conditions, along with a gene deletion library. Of these phosphosites, 42% exhibited growth phenotypes, suggesting that these are more likely functional. We inferred their function based on the similarity of their growth profiles with that of gene deletions and validated a subset by thermal proteome profiling and lipidomics. A high fraction exhibited phenotypes not seen in the corresponding gene deletion, suggestive of a gain-of-function effect. For phosphosites conserved in humans, the severity of the yeast phenotypes is indicative of their human functional relevance. This high-throughput approach allows for functionally characterizing individual phosphosites at scale.
Clinical patterns and the associated optimal management of acquired resistance to PD-(L)1 blockade are poorly understood.
All cases of metastatic lung cancer treated with PD-(L)1 blockade at Memorial ...Sloan Kettering were reviewed. In acquired resistance (complete/partial response per RECIST, followed by progression), clinical patterns were distinguished as oligo (OligoAR ≤ 3 lesions of disease progression) or systemic (sAR). We analyzed the relationships between patient characteristics, burden/location of disease, outcomes, and efficacy of therapeutic interventions.
Of 1,536 patients, 312 (20%) had an initial response and 143 developed AR (9% overall, 46% of responders). OligoAR was the most common pattern (80/143, 56%). Baseline tumor mutational burden, depth of response, and duration of response were significantly increased in oligoAR compared with sAR (P < 0.001, P = 0.03, P = 0.04, respectively), whereas baseline PD-L1 and tumor burden were similar. Post-progression, oligoAR was associated with improved overall survival (median 28 months vs. 10 months, P < 0.001) compared with sAR. Within oligoAR, post-progression survival was greater among patients treated with locally-directed therapy (e.g., radiation, surgery; HR, 0.41; P = 0.039). Fifty-eight percent of patients with oligoAR treated with locally-directed therapy alone are progression-free at last follow-up (median 16 months), including 13 patients who are progression-free more than 2 years after local therapy.
OligoAR is a common and distinct pattern of acquired resistance to PD-(L)1 blockade compared with sAR. OligoAR is associated with improved post-progression survival and some cases can be effectively managed with local therapies with durable benefit.
Somatic DNA copy number variations (CNVs) are prevalent in cancer and can drive cancer progression, albeit with often uncharacterized roles in altering cell signaling states. Here, we integrate ...genomic and proteomic data for 5,598 tumor samples to identify CNVs leading to aberrant signal transduction. The resulting associations recapitulate known kinase-substrate relationships, and further network analysis prioritizes likely causal genes. Of the 303 significant associations we identify from the pan-tumor analysis, 43% are replicated in cancer cell lines, including 44 robust gene-phosphosite associations identified across multiple tumor types. Several predicted regulators of hippo signaling are experimentally validated. Using RNAi, CRISPR, and drug screening data, we find evidence of kinase addiction in cancer cell lines, identifying inhibitors for targeting of kinase-dependent cell lines. We propose copy number status of genes as a useful predictor of differential impact of kinase inhibition, a strategy that may be of use in the future for anticancer therapies.
Display omitted
•Alterations in copy number and in signaling pathways are robustly associated in cancer•Differences in essentiality of phosphoproteins show evidence of kinase addiction•Copy number markers of dysregulated signaling suggest treatment stratification options
Memon et al. show that copy number alterations can be used as molecular fingerprints to predict the activity of signaling pathways in cancer. Kinase dependencies of cancer cells can be exploited for targeted anticancer therapy.
PDF
