DNArepairK: An Interactive Database for Exploring the Impact of Anticancer Drugs onto the Dynamics of DNA Repair Proteins

Diffusion of activated ATM explains γH2AX and MDC1 spread beyond the DNA damage site

During DNA repair, ATM-induced H2AX histone phosphorylation and MDC1 recruitment spread megabases beyond the damage site. While loop extrusion has been suggested to drive this spread, the underlying mechanism remains unclear. Herein, we provide two lines of evidence that loop extrusion is not the only driver of damage-induced γH2AX spread. First, cohesin loader NIPBL and cohesin subunit RAD21 accumulate considerably later than the phosphorylation of H2AX and MDC1 recruitment at micro-IR-induced damage. Second, auxin-induced RAD21 depletion does not affect γH2AX/MDC1 spread following micro-irradiation or DSB induction by zeocin. To determine if diffusion of activated ATM could account for the observed behavior, we measured the exchange rate and diffusion constants of ATM and MDC1 within damaged and unperturbed chromatin. Using these measurements, we introduced a quantitative model in which the freely diffusing activated ATM phosphorylates H2AX. This model faithfully describes the dynamics of ATM and subsequent γH2AX/MDC1 spread at complex DNA lesions.

PARP1 roles in DNA repair and DNA replication: The basi(c)s of PARP inhibitor efficacy and resistance

Genome integrity is under constant insult from endogenous and exogenous sources. In order to cope, eukaryotic cells have evolved an elaborate network of DNA repair that can deal with diverse lesion types and exhibits considerable functional redundancy. PARP1 is a major sensor of DNA breaks with established and putative roles in a number of pathways within the DNA repair network, including repair of single- and double-strand breaks as well as protection of the DNA replication fork. Importantly, PARP1 is the major target of small-molecule PARP inhibitors (PARPi), which are employed in the treatment of homologous recombination (HR)-deficient tumors, as the latter are particularly susceptible to the accumulation of DNA damage due to an inability to efficiently repair highly toxic double-strand DNA breaks. The clinical success of PARPi has fostered extensive research into PARP biology, which has shed light on the involvement of PARP1 in various genomic transactions. A major goal within the field has been to understand the relationship between catalytic inhibition and PARP1 trapping. The specific consequences of inhibition and trapping on genomic stability as a basis for the cytotoxicity of PARP inhibitors remain a matter of debate. Finally, PARP inhibition is increasingly recognized for its capacity to elicit/modulate anti-tumor immunity. The clinical potential of PARP inhibition is, however, hindered by the development of resistance. Hence, extensive efforts are invested in identifying factors that promote resistance or sensitize cells to PARPi. The current review provides a summary of advances in our understanding of PARP1 biology, the mechanistic nature, and molecular consequences of PARP inhibition, as well as the mechanisms that give rise to PARPi resistance.

Exploring DNA Damage and Repair Mechanisms: A Review with Computational Insights

DNA damage is a critical factor contributing to genetic alterations, directly affecting human health, including developing diseases such as cancer and age-related disorders. DNA repair mechanisms play a pivotal role in safeguarding genetic integrity and preventing the onset of these ailments. Over the past decade, substantial progress and pivotal discoveries have been achieved in DNA damage and repair. This comprehensive review paper consolidates research efforts, focusing on DNA repair mechanisms, computational research methods, and associated databases. Our work is a valuable resource for scientists and researchers engaged in computational DNA research, offering the latest insights into DNA-related proteins, diseases, and cutting-edge methodologies. The review addresses key questions, including the major types of DNA damage, common DNA repair mechanisms, the availability of reliable databases for DNA damage and associated diseases, and the predominant computational research methods for enzymes involved in DNA damage and repair.

Comprehensive assessment of base excision repair (BER)-related lncRNAs as prognostic and functional biomarkers in lung adenocarcinoma: implications for personalized therapeutics and immunomodulation

BACKGROUND

Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer, and comprehending its molecular mechanisms is pivotal for advancing treatment efficacy. This study aims to explore the prognostic and functional significance of base excision repair (BER)-related long non-coding RNAs (BERLncs) in LUAD.

METHODS

A risk score model for BERLncs was developed using the least absolute shrinkage and selection operator regression and Cox regression analysis. Model validation and prognostic evaluation were performed using Kaplan-Meier and receiver-operating characteristic curve analyses. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted to elucidate the potential biological functions of BERLncs. Comparative analyses were carried out to investigate disparities in tumor mutation burden (TMB), immune infiltration, tumor immune dysfunction and exclusion (TIDE) score, chemosensitivity, and immune checkpoint gene expression between the two risk groups.

RESULTS

A predictive risk score model comprising 19 BERLncs was successfully developed. Patients were divided into high-risk and low-risk groups according to the median risk score. The high-risk subgroup exhibited significantly inferior overall survival. Functional enrichment analysis revealed pathways associated with lung cancer development, notably the neuroactive ligand-receptor interaction pathway. High-risk patients demonstrated elevated TMB, diminished TIDE scores, and an immunosuppressive tumor microenvironment, while low-risk patients displayed potential benefits from immunotherapy. Additionally, the risk model identified potential anticancer agents.

CONCLUSION

The risk score model based on BERLncs shows promise as a prognostic biomarker for LUAD patients, providing valuable insights for clinical decision-making, therapeutic strategies, and understanding of underlying biological mechanisms.

CellTool: An Open-Source Software Combining Bio-Image Analysis and Mathematical Modeling for the Study of DNA Repair Dynamics

Elucidating the dynamics of DNA repair proteins is essential to understanding the mechanisms that preserve genomic stability and prevent carcinogenesis. However, the measurement and modeling of protein dynamics at DNA lesions via currently available image analysis tools is cumbersome. Therefore, we developed CellTool-a stand-alone open-source software with a graphical user interface for the analysis of time-lapse microscopy images. It combines data management, image processing, mathematical modeling, and graphical presentation of data in a single package. Multiple image filters, segmentation, and particle tracking algorithms, combined with direct visualization of the obtained results, make CellTool an ideal application for the comprehensive analysis of DNA repair protein dynamics. This software enables the fitting of obtained kinetic data to predefined or custom mathematical models. Importantly, CellTool provides a platform for easy implementation of custom image analysis packages written in a variety of programing languages. Using CellTool, we demonstrate that the ALKB homolog 2 (ALKBH2) demethylase is excluded from DNA damage sites despite recruitment of its putative interaction partner proliferating cell nuclear antigen (PCNA). Further, CellTool facilitates the straightforward fluorescence recovery after photobleaching (FRAP) analysis of BRCA1 associated RING domain 1 (BARD1) exchange at complex DNA lesions. In summary, the software presented herein enables the time-efficient analysis of a wide range of time-lapse microscopy experiments through a user-friendly interface.

Temporal recruitment of base excision DNA repair factors in living cells in response to different micro-irradiation DNA damage protocols

Laser micro-irradiation across the nucleus rapidly generates localized chromatin-associated DNA lesions permitting analysis of repair protein recruitment in living cells. Recruitment of three fluorescently-tagged base excision repair factors [DNA polymerase β (pol β), XRCC1 and PARP1], known to interact with one another, was compared in gene-deleted mouse embryonic fibroblasts and in those expressing the endogenous factor. A low energy micro-irradiation (LEMI) forming direct single-strand breaks and a moderate energy (MEMI) protocol that additionally creates oxidized bases were compared. Quantitative characterization of repair factor recruitment and sensitivity to clinical PARP inhibitors (PARPi) was dependent on the micro-irradiation protocol. PARP1 recruitment was biphasic and generally occurred prior to pol β and XRCC1. After LEMI, but not after MEMI, pol β and XRCC1 recruitment was abolished by the PARPi veliparib. Consistent with this, pol β and XRCC1 recruitment following LEMI was considerably slower in PARP1-deficient cells. Surprisingly, the recruitment half-times and amplitudes for pol β were less affected by PARPi than were XRCC1 after MEMI suggesting there is a XRCC1-independent component for pol β recruitment. After LEMI, but not MEMI, pol β dissociation was more rapid than that of XRCC1. Unexpectedly, PARP1 dissociation was slowed in the absence of XRCC1 as well with a PARPi after LEMI but not MEMI, suggesting that XRCC1 facilitates PARP1 dissociation from specific DNA lesions. XRCC1-deficient cells showed pronounced hypersensitivity to the PARPi talazoparib correlating with its known cytotoxic PARP1 trapping activity. In contrast to DNA methylating agents, PARPi only minimally sensitized pol β and XRCC1-deficient cells to oxidative DNA damage suggesting differential binding of PARP1 to alternate repair intermediates. In summary, pol β, XRCC1, and PARP1 display recruitment kinetics that exhibit correlated and unique properties that depend on the DNA lesion and PARP activity revealing that there are multiple avenues utilized in the repair of chromatin-associated DNA.

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10-3, there are gains of -10 [dB], -3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.