Biology subjects

Nikolova, T.

Publications and source records attributed to Nikolova, T..

3 recordsLinked to original sources

bioRxiv2026

HIPK2 regulates homology-directed DNA repair and PARP inhibitor sensitivity

Repair of DNA double-strand breaks (DSBs) by homologous recombination (HR) counteracts genome instability and carcinogenesis. Cancer cells frequently show defects in HR which can be therapeutically exploited by hypersensitivity to poly(ADP-ribose) polymerase inhibitor (PARPi) treatment. Here we identify an unforeseen function of HIPK2 in HR repair and PARPi sensitivity. HIPK2 accumulates at DSBs and associates with DSB repair factors at DNA damage foci. DSB recruitment of HIPK2 requires checkpoint kinase ATM activity. DNA repair pathway analysis revealed that HIPK2 depletion specifically impairs HR. Mechanistically, we found that HIPK2 binds BRCA1 and phosphorylates BRCA1 at Ser1191, a site that regulates damage-induced BRCA1 protein stability. Consistently, HIPK2 depletion or pharmacological inhibition of HIPK2 results in reduced BRCA1 protein levels, and sensitizes BRCA1-proficient cancer cells to IR damage and PARPi treatment. In sum, our results identify a role for HIPK2 in HR through regulating BRCA1 protein levels, and propose HIPK2 inhibition as a novel strategy to sensitize BRCA1-proficient cancer cells to PARPi treatment.

cell biology↗

bioRxiv2026

Role of a childhood cancer-linked BRIP1/FANCJ germline variant in genomic instability and cancer cell vulnerability

Childhood cancer is frequently associated with inherited pathogenic variants of cancer predisposition genes. Using Whole-Exome Sequencing, we identified an inherited, monoallelic pediatric cancer-linked germline variant of DNA helicase FANCJ/BRIP1, BRIP1R162Q of unclear clinical significance. Intriguingly, in vitro helicase assays demonstrated that BRIP1R162Q encodes a hyperactive DNA helicase. In cells, stable expression of BRIP1R162Q in BRIP1-proficient cells selectively sensitized to ectopic DNA replication stress. Moreover, BRIP1R162Q expressing cells showed chronic, steady-state activation of DNA replication stress indicated by decreased fork speed, fork stalling and impaired fork symmetry. Moreover, BRIP1R162Q expression triggered genomic instability indicated by elevated {gamma}H2AX foci numbers and chromosomal aberrations, suggesting BRIP1R162Q as a variant driving genomic instability. Mechanistically, BRIP1R162Q mislocalizes upon replication stress, and leads to accumulation of DNA secondary G-quadruplex (G4) structures and R-loops. RNaseH1 expression, which resolves R-loops, also reduced G4 levels and relieved BRIP1R162Q-induced replication stress. Finally, BRIP1R162Q introduces exploitable vulnerabilities for targeted therapies using G4-ligand Pyridostatin and DNA damage kinase ATR and DNA-PK inhibition. Our findings propose a mechanistic framework of how a childhood cancer-linked monoallic, hypermorphic BRIP1 germline variant participates in cancer development, and suggest potential therapeutic treatment strategies.

cancer biology↗

bioRxiv2022

LambdaPP: Fast and accessible protein-specific phenotype predictions

The availability of accurate and fast Artificial Intelligence (AI) solutions predicting aspects of proteins are revolutionizing experimental and computational molecular biology. The webserver LambdaPP aspires to supersede PredictProtein, the first internet server making AI protein predictions available in 1992. Given a protein sequence as input, LambdaPP provides easily accessible visualizations of protein 3D structure, along with predictions at the protein level (GeneOntology, subcellular location), and the residue level (binding to metal ions, small molecules, and nucleotides; conservation; intrinsic disorder; secondary structure; alpha-helical and beta-barrel transmembrane segments; signal-peptides; variant effect) in seconds. The structure prediction provided by LambdaPP - leveraging ColabFold and computed in minutes - is based on MMseqs2 multiple sequence alignments. All other feature prediction methods are based on the pLM ProtT5. Queried by a protein sequence, LambdaPP computes protein and residue predictions almost instantly for various phenotypes, including 3D structure and aspects of protein function. Accessibility StatementLambdaPP is freely available for everyone to use under embed.predictprotein.org, the interactive results for the case study can be found under https://embed.predictprotein.org/o/Q9NZC2. The frontend of LambdaPP can be found on GitHub (github.com/sacdallago/embed.predictprotein.org), and can be freely used and distributed under the academic free use license (AFL-2). For high-throughput applications, all methods can be executed locally via the bio-embeddings (bioembeddings.com) python package, or docker image at ghcr.io/bioembeddings/bio_embeddings, which also includes the backend of LambdaPP. Impact StatementWe introduce LambdaPP, a webserver integrating fast and accurate sequence-only protein feature predictions based on embeddings from protein Language Models (pLMs) available in seconds along with high-quality protein structure predictions. The intuitive interface invites experts and novices to benefit from the latest machine learning tools. LambdaPPs unique combination of predicted features may help in formulating hypotheses for experiments and as input to bioinformatics pipelines.

bioinformatics↗