Evolutionary dependency of cancer mutations in gene pairs inferred by nonsynonymous-synonymous mutation ratios.

BACKGROUND: Determining the impact of somatic mutations requires understanding the functional relationship of genes acquiring mutations; however, it is largely unknown how mutations in functionally related genes influence each other. METHODS: We employed non-synonymous-to-synonymous or dNdS ratios to evaluate the evolutionary dependency (ED) of gene pairs, assuming a mutation in one gene of a gene pair can affect the evolutionary fitness of mutations in its partner genes as mutation context. We employed PanCancer- and tumor type-specific mutational profiles to infer the ED of gene pairs and evaluated their biological relevance with respect to gene dependency and drug sensitivity. RESULTS: We propose that dNdS ratios of gene pairs and their derived cdNS (context-dependent dNdS) scores as measure of ED distinguishing gene pairs either as synergistic (SYN) or antagonistic (ANT). Mutation contexts can induce substantial changes in the evolutionary fitness of mutations in the paired genes, e.g., IDH1 and IDH2 mutation contexts lead to substantial increase and decrease of dNdS ratios of ATRX indels and IDH1 missense mutations corresponding to SYN and ANT relationship with positive and negative cdNS scores, respectively. The impact of gene silencing or knock-outs on cell viability (genetic dependencies) often depends on ED, suggesting that ED can guide the selection of candidates for synthetic lethality such as TCF7L2-KRAS mutations. Using cell line-based drug sensitivity data, the effects of targeted agents on cell lines are often associated with mutations of genes exhibiting ED with the target genes, informing drug sensitizing or resistant mutations for targeted inhibitors, e.g., PRSS1 and CTCF mutations as resistant mutations to EGFR and BRAF inhibitors for lung adenocarcinomas and melanomas, respectively. CONCLUSIONS: We propose that the ED of gene pairs evaluated by dNdS ratios can advance our understanding of the functional relationship of genes with potential biological and clinical implications.

A Probabilistic Approach to Estimate the Temporal Order of Pathway Mutations Accounting for Intra-Tumor Heterogeneity.

The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types.

Tumor-Agnostic Therapy-The Final Step Forward in the Cure for Human Neoplasms?

Cancer accounted for 10 million deaths in 2020, nearly one in every six deaths annually. Despite advancements, the contemporary clinical management of human neoplasms faces a number of challenges. Surgical removal of tumor tissues is often not possible technically, while radiation and chemotherapy pose the risk of damaging healthy cells, tissues, and organs, presenting complex clinical challenges. These require a paradigm shift in developing new therapeutic modalities moving towards a more personalized and targeted approach. The tumor-agnostic philosophy, one of these new modalities, focuses on characteristic molecular signatures of transformed cells independently of their traditional histopathological classification. These include commonly occurring DNA aberrations in cancer cells, shared metabolic features of their homeostasis or immune evasion measures of the tumor tissues. The first dedicated, FDA-approved tumor-agnostic agent's profound progression-free survival of 78% in mismatch repair-deficient colorectal cancer paved the way for the accelerated FDA approvals of novel tumor-agnostic therapeutic compounds. Here, we review the historical background, current status, and future perspectives of this new era of clinical oncology.

κB-Ras proteins are fast-exchanging GTPases and function via nucleotide-independent binding of Ral GTPase-activating protein complexes.

κB-Ras (NF-κB inhibitor-interacting Ras-like protein) GTPases are small Ras-like GTPases but harbor interesting differences in important sequence motifs. They act in a tumor-suppressive manner as negative regulators of Ral (Ras-like) GTPase and NF-κB signaling, but little is known about their mode of function. Here, we demonstrate that, in contrast to predictions based on primary structure, κB-Ras GTPases possess hydrolytic activity. Combined with low nucleotide affinity, this renders them fast-cycling GTPases that are predominantly GTP-bound in cells. We characterize the impact of κB-Ras mutations occurring in tumors and demonstrate that nucleotide binding affects κB-Ras stability but is not strictly required for RalGAP (Ral GTPase-activating protein) binding. This demonstrates that κB-Ras control of RalGAP/Ral signaling occurs in a nucleotide-binding- and switch-independent fashion.

In Vitro Cross-Linking MS Reveals SMG1-UPF2-SMG7 Assembly as Molecular Partners within the NMD Surveillance.

mRNAs containing premature stop codons are responsible for various genetic diseases as well as cancers. The truncated proteins synthesized from these aberrant mRNAs are seldom detected due to the nonsense-mediated mRNA decay (NMD) pathway. Such a surveillance mechanism detects most of these aberrant mRNAs and rapidly destroys them from the pool of mRNAs. Here, we implemented chemical cross-linking mass spectrometry (CLMS) techniques to trace novel biology consisting of protein-protein interactions (PPIs) within the NMD machinery. A set of novel complex networks between UPF2 (Regulator of nonsense transcripts 2), SMG1 (Serine/threonine-protein kinase SMG1), and SMG7 from the NMD pathway were identified, among which UPF2 was found as a connection bridge between SMG1 and SMG7. The UPF2 N-terminal formed most interactions with SMG7, and a set of residues emerged from the MIF4G-I, II, and III domains docked with SMG1 or SMG7. SMG1 mediated interactions with initial residues of UPF2, whereas SMG7 formed very few interactions in this region. Modelled structures highlighted that PPIs for UPF2 and SMG1 emerged from the well-defined secondary structures, whereas SMG7 appeared from the connecting loops. Comparing the influence of cancer-derived mutations over different CLMS sites revealed that variants in the PPIs for UPF2 or SMG1 have significant structural stability effects. Our data highlights the protein-protein interface of the SMG1, UPF2, and SMG7 genes that can be used for potential therapeutic approaches. Blocking the NMD pathway could enhance the production of neoantigens or internal cancer vaccines, which could provide a platform to design potential peptide-based vaccines.

Cancer-associated polybromo-1 bromodomain 4 missense variants variably impact bromodomain ligand binding and cell growth suppression.

The polybromo, brahma-related gene 1-associated factors (PBAF) chromatin remodeling complex subunit polybromo-1 (PBRM1) contains six bromodomains that recognize and bind acetylated lysine residues on histone tails and other nuclear proteins. PBRM1 bromodomains thus provide a link between epigenetic posttranslational modifications and PBAF modulation of chromatin accessibility and transcription. As a putative tumor suppressor in several cancers, PBRM1 protein expression is often abrogated by truncations and deletions. However, ∼33% of PBRM1 mutations in cancer are missense and cluster within its bromodomains. Such mutations may generate full-length PBRM1 variant proteins with undetermined structural and functional characteristics. Here, we employed computational, biophysical, and cellular assays to interrogate the effects of PBRM1 bromodomain missense variants on bromodomain stability and function. Since mutations in the fourth bromodomain of PBRM1 (PBRM1-BD4) comprise nearly 20% of all cancer-associated PBRM1 missense mutations, we focused our analysis on PBRM1-BD4 missense protein variants. Selecting 16 potentially deleterious PBRM1-BD4 missense protein variants for further study based on high residue mutational frequency and/or conservation, we show that cancer-associated PBRM1-BD4 missense variants exhibit varied bromodomain stability and ability to bind acetylated histones. Our results demonstrate the effectiveness of identifying the unique impacts of individual PBRM1-BD4 missense variants on protein structure and function, based on affected residue location within the bromodomain. This knowledge provides a foundation for drawing correlations between specific cancer-associated PBRM1 missense variants and distinct alterations in PBRM1 function, informing future cancer personalized medicine approaches.

Community analysis of large-scale molecular dynamics simulations elucidated dynamics-driven allostery in tyrosine kinase 2.

TYK2 is a nonreceptor tyrosine kinase, member of the Janus kinases (JAK), with a central role in several diseases, including cancer. The JAKs' catalytic domains (KD) are highly conserved, yet the isolated TYK2-KD exhibits unique specificities. In a previous work, using molecular dynamics (MD) simulations of a catalytically impaired TYK2-KD variant (P1104A) we found that this amino acid change of its JAK-characteristic insert (αFG), acts at the dynamics level. Given that structural dynamics is key to the allosteric activation of protein kinases, in this study we applied a long-scale MD simulation and investigated an active TYK2-KD form in the presence of adenosine 5'-triphosphate and one magnesium ion that represents a dynamic and crucial step of the catalytic cycle, in other protein kinases. Community analysis of the MD trajectory shed light, for the first time, on the dynamic profile and dynamics-driven allosteric communications within the TYK2-KD during activation and revealed that αFG and amino acids P1104, P1105, and I1112 in particular, hold a pivotal role and act synergistically with a dynamically coupled communication network of amino acids serving intra-KD signaling for allosteric regulation of TYK2 activity. Corroborating our findings, most of the identified amino acids are associated with cancer-related missense/splice-site mutations of the Tyk2 gene. We propose that the conformational dynamics at this step of the catalytic cycle, coordinated by αFG, underlie TYK2-unique substrate recognition and account for its distinct specificity. In total, this work adds to knowledge towards an in-depth understanding of TYK2 activation and may be valuable towards a rational design of allosteric TYK2-specific inhibitors.

Targeted Mass Spectrometry Analyses of Somatic Mutations in Colorectal Cancer Specimens Using Differential Ion Mobility.

Identification of K-Ras and B-Raf mutations in colorectal cancer (CRC) is essential to predict patients' response to anti-EGFR therapy and formulate appropriate therapeutic strategies to improve prognosis and survival. Here, we combined parallel reaction monitoring (PRM) with high-field asymmetric waveform ion mobility (FAIMS) to enhance mass spectrometry sensitivity and improve the identification of low-abundance K-Ras and B-Raf mutations in biological samples without immunoaffinity enrichment. In targeted LC-MS/MS analyses, FAIMS reduced the occurrence of interfering ions and enhanced precursor ion purity, resulting in a 3-fold improvement in the detection limit for K-Ras and B-Raf mutated peptides. In addition, the ion mobility separation of isomeric peptides using FAIMS facilitated the unambiguous identification of K-Ras G12D and G13D peptides. The application of targeted LC-MS/MS analyses using FAIMS is demonstrated for the detection and quantitation of B-Raf V600E, K-Ras G12D, G13D, and G12V in CRC cell lines and primary specimens.

Discovery of oncogenic ROS1 missense mutations with sensitivity to tyrosine kinase inhibitors.

ROS1 is the largest receptor tyrosine kinase in the human genome. Rearrangements of the ROS1 gene result in oncogenic ROS1 kinase fusion proteins that are currently the only validated biomarkers for targeted therapy with ROS1 TKIs in patients. While numerous somatic missense mutations in ROS1 exist in the cancer genome, their impact on catalytic activity and pathogenic potential is unknown. We interrogated the AACR Genie database and identified 34 missense mutations in the ROS1 tyrosine kinase domain for further analysis. Our experiments revealed that these mutations have varying effects on ROS1 kinase function, ranging from complete loss to significantly increased catalytic activity. Notably, Asn and Gly substitutions at Asp2113 in the ROS1 kinase domain were found to be TKI-sensitive oncogenic variants in cell-based model systems. In vivo experiments showed that ROS1 D2113N induced tumor formation that was sensitive to crizotinib and lorlatinib, FDA-approved ROS1-TKIs. Collectively, these findings highlight the tumorigenic potential of specific point mutations within the ROS1 kinase domain and their potential as therapeutic targets with FDA-approved ROS1-TKIs.

FUBP1 is a general splicing factor facilitating 3' splice site recognition and splicing of long introns.

Splicing of pre-mRNAs critically contributes to gene regulation and proteome expansion in eukaryotes, but our understanding of the recognition and pairing of splice sites during spliceosome assembly lacks detail. Here, we identify the multidomain RNA-binding protein FUBP1 as a key splicing factor that binds to a hitherto unknown cis-regulatory motif. By collecting NMR, structural, and in vivo interaction data, we demonstrate that FUBP1 stabilizes U2AF2 and SF1, key components at the 3' splice site, through multivalent binding interfaces located within its disordered regions. Transcriptional profiling and kinetic modeling reveal that FUBP1 is required for efficient splicing of long introns, which is impaired in cancer patients harboring FUBP1 mutations. Notably, FUBP1 interacts with numerous U1 snRNP-associated proteins, suggesting a unique role for FUBP1 in splice site bridging for long introns. We propose a compelling model for 3' splice site recognition of long introns, which represent 80% of all human introns.

Mutation in the Common Docking Domain Affects MAP Kinase ERK2 Catalysis and Stability.

The extracellular-signal-regulated kinase 2 (ERK2), a mitogen-activated protein kinase (MAPK) located downstream of the Ras-Raf-MEK-ERK signal transduction cascade, is involved in the regulation of a large variety of cellular processes. The ERK2, activated by phosphorylation, is the principal effector of a central signaling cascade that converts extracellular stimuli into cells. Deregulation of the ERK2 signaling pathway is related to many human diseases, including cancer. This study reports a comprehensive biophysical analysis of structural, function, and stability data of pure, recombinant human non-phosphorylated (NP-) and phosphorylated (P-) ERK2 wild-type and missense variants in the common docking site (CD-site) found in cancer tissues. Because the CD-site is involved in interaction with protein substrates and regulators, a biophysical characterization of missense variants adds information about the impact of point mutations on the ERK2 structure-function relationship. Most of the P-ERK2 variants in the CD-site display a reduced catalytic efficiency, and for the P-ERK2 D321E, D321N, D321V and E322K, changes in thermodynamic stability are observed. The thermal stability of NP-ERK2 and P-ERK2 D321E, D321G, and E322K is decreased with respect to the wild-type. In general, a single residue mutation in the CD-site may lead to structural local changes that reflects in alterations in the global ERK2 stability and catalysis.

How Do Cancer-Related Mutations Affect the Oligomerisation State of the p53 Tetramerisation Domain?

Tumour suppressor p53 plays a key role in the development of cancer and has therefore been widely studied in recent decades. While it is well known that p53 is biologically active as a tetramer, the tetramerisation mechanism is still not completely understood. p53 is mutated in nearly 50% of cancers, and mutations can alter the oligomeric state of the protein, having an impact on the biological function of the protein and on cell fate decisions. Here, we describe the effects of a number of representative cancer-related mutations on tetramerisation domain (TD) oligomerisation defining a peptide length that permits having a folded and structured domain, thus avoiding the effect of the flanking regions and the net charges at the N- and C-terminus. These peptides have been studied under different experimental conditions. We have applied a variety of techniques, including circular dichroism (CD), native mass spectrometry (MS) and high-field solution NMR. Native MS allows us to detect the native state of complexes maintaining the peptide complexes intact in the gas phase; the secondary and quaternary structures were analysed in solution by NMR, and the oligomeric forms were assigned by diffusion NMR experiments. A significant destabilising effect and a variable monomer population were observed for all the mutants studied.

DNA Fragility and Repair: Some Personal Recollections.

In this autobiographical article, I reflect on my Swedish background. Then I discuss endogenous DNA alterations and the base excision repair pathway and alternative repair strategies for some unusual DNA lesions. Endogenous DNA damage, such as loss of purine bases and cytosine deamination, is proposed as a major source of cancer-causing mutations.

A frequent PLCγ1 mutation in adult T-cell leukemia/lymphoma determines functional properties of the malignant cells.

BACKGROUND: Development of adult T-cell leukemia/lymphoma (ATL) involves human T-cell leukemia virus type 1 (HTLV-1) infection and accumulation of somatic mutations. The most frequently mutated gene in ATL (36 % of cases) is phospholipase C gamma1 (PLCG1). PLCG1 is also frequently mutated in other T-cell lymphomas. However, the functional consequences of the PLCG1 mutations in cancer cells have not been characterized. METHODS: We compared the activity of the wild-type PLCγ1 with that of a mutant carrying a hot-spot mutation of PLCγ1 (S345F) observed in ATL, both in cells and in cell-free assays. To analyse the impact of the mutation on cellular properties, we quantified cellular proliferation, aggregation, chemotaxis and apoptosis by live cell-imaging in an S345F+ ATL-derived cell line (KK1) and a KK1 cell line in which we reverted the mutation to the wild-type sequence using CRISPR/Cas9 and homology-directed repair. FINDINGS: The PLCγ1 S345F mutation results in an increase of basal PLC activity in vitro and in different cell types. This higher basal activity is further enhanced by upstream signalling. Reversion of the S345F mutation in the KK1 cell line resulted in reduction of the PLC activity, lower rates of proliferation and aggregation, and a marked reduction in chemotaxis towards CCL22. The PLCγ1-pathway inhibitors ibrutinib and ritonavir reduced both the PLC activity and the tested functions of KK1 cells. INTERPRETATION: Consistent with observations from clinical studies, our data provide direct evidence that activated variants of the PLCγ1 enzyme contribute to the properties of the malignant T-cell clone in ATL. FUNDING: MRC (UK) Project Grant (P028160).

The Binding Specificity of PAB1 with Poly(A) mRNA, Regulated by Its Structural Folding.

The poly(A)-binding protein cytoplasmic 1 (PAB1 or PABPC1) protein is associated with the long poly(A) mRNA tails, inducing stability. Herein, we investigated the dynamics of the PABPC1 protein, along with tracing its mRNA binding specificity. During molecular dynamics simulations (MDS), the R176-Y408 amino acids (RRM3-4 domains; RNA recognition motifs) initiated a folded structure that resulted in the formation of different conformations. The RRM4 domain formed high-frequency intramolecular interactions, despite such induced flexibility. Residues D45, Y54, Y56, N58, Q88, and N100 formed long-lasting interactions, and specifically, aromatic residues (Y14, Y54, Y56, W86, and Y140) gained a unique binding pattern with the poly(A) mRNA. In addition, the poly(A) mRNA motif assembled a PABPC1-specific conformation, by inducing movement of the center three nucleotides to face towards RRM1-2 domains. The majority of the high-frequency cancer mutations in PAB1 reside within the RRM4 domain and amino acids engaging in high-frequency interactions with poly(A) mRNA were found to be preserved in different cancer types. Except for the G123C variant, other studied cancer-derived mutants hindered the stability of the protein. Molecular details from this study will provide a detailed understanding of the PABPC1 structure, which can be used to modulate the activity of this gene, resulting in production of mutant peptide or neoantigens in cancer.

Computed cancer interactome explains the effects of somatic mutations in cancers.

Protein-protein interactions (PPIs) are involved in almost all essential cellular processes. Perturbation of PPI networks plays critical roles in tumorigenesis, cancer progression, and metastasis. While numerous high-throughput experiments have produced a vast amount of data for PPIs, these data sets suffer from high false positive rates and exhibit a high degree of discrepancy. Coevolution of amino acid positions between protein pairs has proven to be useful in identifying interacting proteins and providing structural details of the interaction interfaces with the help of deep learning methods like AlphaFold (AF). In this study, we applied AF to investigate the cancer protein-protein interactome. We predicted 1,798 PPIs for cancer driver proteins involved in diverse cellular processes such as transcription regulation, signal transduction, DNA repair, and cell cycle. We modeled the spatial structures for the predicted binary protein complexes, 1,087 of which lacked previous 3D structure information. Our predictions offer novel structural insight into many cancer-related processes such as the MAP kinase cascade and Fanconi anemia pathway. We further investigated the cancer mutation landscape by mapping somatic missense mutations (SMMs) in cancer to the predicted PPI interfaces and performing enrichment and depletion analyses. Interfaces enriched or depleted with SMMs exhibit different preferences for functional categories. Interfaces enriched in mutations tend to function in pathways that are deregulated in cancers and they may help explain the molecular mechanisms of cancers in patients; interfaces lacking mutations appear to be essential for the survival of cancer cells and thus may be future targets for PPI modulating drugs.

Annotating Cancer-Related Variants at Protein-Protein Interface with Structure-PPi.

A comprehensive analysis of germline and somatic variants requires complex computational approaches that combine next-generation sequencing (NGS)-based omics data with curated annotations from public repositories. Here, we describe Structure-PPi, which facilitates the analysis of cancer-related variants onto protein 3D structures, interaction interfaces, and other important functional sites (i.e., catalytic, ligand-binding, posttranslational modification). Our approach relies on features extracted from Interactome3D, UniProtKB, InterPro, APPRIS, dbNSFP, and COSMIC databases and provides complementary information to pathogenicity prediction methods. Thus, Structure-PPi helps in the discrimination of false-positive predictions and adds both mechanistic and biological insights into the role of variants in a given cancer. An online version of the tools is available at https://rbbt.bsc.es/StructurePPI/ .

How often is each gene mutated within the cancer patient population?

Genome sequenced samples from cancer patients helped identify roles of different mutation types and enabled targeted therapy development. However, critical questions like what are the gene mutation rates among the patients? or what genes are most commonly mutated, pan-cancer? have only been recently answered. Here, we highlight this recent advance.