Cancer Lett. 2025 Feb 17:217565. doi: 10.1016/j.canlet.2025.217565. Online ahead of print.

ABSTRACT

Over 50% of patients with high-grade serous carcinoma (HGSC) are homologous recombination proficient, making them refractory to platinum-based drugs and poly (ADP-ribose) polymerase (PARP) inhibitors. These patients often develop progressive resistance within 6 months after primary treatment and tend to die early, thus new therapies are urgently needed. In this study, we comprehensively investigated this tumor type by leveraging a combination of machine learning analysis of a large published dataset and newly developed genetically engineered HGSC organoid models from murine fallopian tubes. Aberrant activation of RAS/PI3K signaling was a signature of poor prognosis in BRCA1/2 wild-type ovarian cancer, and mTOR-induced elevated p62 expression was a robust marker of chemotherapy-induced mTOR-p62-NRF2 signal activation. mTOR inhibition with everolimus decreased p62 and enhanced sensitivity to conventional chemotherapy, indicating that p62 serves as an important biomarker for therapeutic intervention. Combination therapy with conventional chemotherapy and mTOR inhibitors is a promising therapeutic strategy for refractory HGSC, with p62 as a biomarker.

PMID:39971122 | DOI:10.1016/j.canlet.2025.217565

J Appl Biomech. 2025 Feb 18:1-10. doi: 10.1123/jab.2024-0104. Online ahead of print.

ABSTRACT

The calf raise test (CRT) is commonly used to assess triceps surae muscle-tendon unit function. Often, a metronome set to 60 beats/min (30 repetitions/min) is used to set the cadence of calf raise repetitions, but studies report using cadences ranging from 30 to 120 beats/min. We investigated the effect of cadence on CRT outcomes, accounting for the potential confounders of sex, age, body mass index, and physical activity. Thirty-six healthy individuals (50% female) performed single-leg calf raise repetitions to volitional exhaustion in 3 randomized cadence conditions, 7 days apart: 30, 60, and 120 beats/min. Repetitions, total vertical displacement, total work, peak height, and peak power were recorded using the validated Calf Raise application. Cadence significantly affected all CRT outcomes (P ≤ .008), except repetitions (P = .200). Post hoc analysis revealed 60 beats/min resulted in significantly greater total vertical displacement and work than 30 and 120 beats/min. Peak height was greater at 60 and 120 than 30 beats/min, and peak power was greater at 120 beats/min. Males generated greater work and peak power (P ≤ .001), whereas individuals with greater body mass index completed less repetitions (P = .008), achieved lower total vertical displacements (P = .003), and generated greater peak power (P = .005). CRT cadence is important to consider when interpreting CRT outcomes and comparing data between studies.

PMID:39970923 | DOI:10.1123/jab.2024-0104

Am J Hum Genet. 2025 Feb 13:S0002-9297(25)00020-5. doi: 10.1016/j.ajhg.2025.01.020. Online ahead of print.

ABSTRACT

Africa's environmental, cultural, and genetic diversity can profoundly shape population responses to infectious diseases, including malaria caused by Plasmodium falciparum. Differences in malaria susceptibility among populations are documented, but the underlying mechanisms remain poorly understood. Notably, the Fulani ethnic group in Africa is less susceptible to malaria compared to other sympatric groups, such as the Mossi. They exhibit lower disease rates and parasite load as well as enhanced serological protection. However, elucidating the molecular and cellular basis of this protection has been challenging in part due to limited immunological characterization at the cellular level. To address this question, we performed single-cell transcriptomic profiling of peripheral blood mononuclear cells from 126 infected and non-infected Fulani and Mossi children in rural Burkina Faso. This analysis generated over 70,000 single-cell transcriptomes and identified 30 distinct cell subtypes. We report a profound effect of ethnicity on the transcriptional landscape, particularly within monocyte populations. Differential expression analysis across cell subtypes revealed ethnic-specific immune signatures under both infected and non-infected states. Specifically, monocytes and T cell subtypes of the Fulani exhibited reduced pro-inflammatory responses, while their B cell subtypes displayed stronger activation and inflammatory profiles. Furthermore, single-cell expression quantitative trait locus (eQTL) analysis in monocytes of infected children revealed several significant regulatory variants with ethnicity-specific effects on immune-related genes, including CD36 and MT2A. Overall, we identify ethnic, cell-type-specific, and genetic regulatory effects on host immune responses to malaria and provide valuable single-cell eQTL and transcriptomic datasets from under-represented populations.

PMID:39970911 | DOI:10.1016/j.ajhg.2025.01.020

Hamostaseologie. 2025 Feb;45(1):49-62. doi: 10.1055/a-2486-6758. Epub 2025 Feb 19.

ABSTRACT

Binding of platelet activators to their receptors initiates a signal transduction network, where intracellular signal is filtered, amplified, and transformed. Computational systems biology methods could be a powerful tool to address and analyze dynamics and regulation of the crucial steps in this cascade. Here we review these approaches and show the logic of their use for a relatively simple case of SFLLRN-induced procoagulant activity. Use of a typical model is employed to track signaling events along the main axis, from the binding of the peptide to PAR1 receptor down to the mPTP opening. Temporal dynamics, concentration dependence, formation of calcium oscillations and their deciphering, and role of stochasticity are quantified for all essential signaling molecules and their complexes. The initial step-wise activation stimulus is transformed to a peak at the early stages, then to oscillation calcium spikes, and then back to a peak shape. The model can show how both amplitude and width of the peak encode the information about the activation level, and show the principle of decoding calcium oscillations via integration of the calcium signal by the mitochondria. Use of stochastic algorithms can reveal that the complexes of Gq, in particular the complex of phospholipase C with Gq, which are the limiting steps in the cascade with their numbers not exceeding several molecules per platelet at any given time; it is them that cause stochastic appearance of the signals downstream. Application of reduction techniques to simplify the system is demonstrated.

PMID:39970901 | DOI:10.1055/a-2486-6758

Mar Pollut Bull. 2025 Feb 18;213:117689. doi: 10.1016/j.marpolbul.2025.117689. Online ahead of print.

ABSTRACT

Small benthic scavengers and carnivores, such as polychaetes, are very interesting to assess the accumulation and transfer of microplastics (MPs) to higher trophic levels in marine ecosystems. In this study we evaluate the presence, accumulation and impacts of MPs in the North-Atlantic deep-sea polychaete Laetmonice filicornis. Three types of MPs were identified: fishing lines, fibres and fragments, mostly black in colour, followed by red and blue ones. The average number of MPs was 4.10 ± 1.90 particles/g tissue. Fibres were the most abundant. They were composed of Polypropylene, Rayon, Polyethyleneimine Cellulose and Polyester. The histological analysis revealed the presence of microfibres embedded in muscles, peritoneum, nephridia, gonads and blood vessels, which can have a direct impact on vital functions, such as feeding and reproduction. This species occupies both predator and prey roles, bioaccumulate MPs and can transfer them to higher trophic links, representing a significant threat to all marine species, including humans.

PMID:39970794 | DOI:10.1016/j.marpolbul.2025.117689

Sci Rep. 2025 Feb 19;15(1):6022. doi: 10.1038/s41598-025-90135-8.

ABSTRACT

Hepatitis B vaccines (HBVs) are widely used duo to their high clinical use and mild effects. However, as post-marketing data accumulate, several serious adverse events (SAEs) following HBV have been reported. Currently, quantitative studies based on real-world data are lacking, and information on their adverse events is limited. Adverse reaction signals of the HBV were mined and analyzed using the U.S. Vaccine Adverse Event Reporting System (VAERS) to provide a reference for the safe clinical use of this vaccine. Multiple statistical methods, including the reporting odds ratio (ROR) method, the Medicines and Healthcare Products Regulatory Agency (MHRA) method, and the Bayesian Confidence Propagation Neural Network (BCPNN) method, were utilized to identify signals of HBV-associated adverse reactions, and positive signals consistent with designated medical events (DMEs) were singled out for focused comparison and discussion. Analysis of 54,136 HBV-related adverse events (AEs) identified 254 positive signals across 22 System Organ Classifications (SOCs), with General disorders and administration site conditions being the most common. Three potential positive new signals consistent with Preferred Terms (PTs) were identified in DME: Aplastic anaemia, Dermatitis exfoliative, and Haemolytic anaemia. This study suggests that HBV has a potential risk in terms of causing Aplastic anaemia, Dermatitis exfoliative, and Haemolytic anaemia. Some subtypes of Aplastic anaemia, Dermatitis exfoliative, Haemolytic anaemia are autoimmune diseases, and immunization may stimulate potential autoimmune genetic predisposition, people with autoimmune diseases or a family history of hereditary immune diseases should be monitored after receiving HBV. Health professionals should be contacted to take measures to help if anaemia, palpitations, and high fever occur.

PMID:39972053 | DOI:10.1038/s41598-025-90135-8

Basic Clin Pharmacol Toxicol. 2025 Mar;136(3):e70009. doi: 10.1111/bcpt.70009.

ABSTRACT

Precision medicine has significantly advanced through the development of predictive biomarkers based on pharmacogenetic (PGx) testing. These tests identify interactions between drugs and genetic variants that influence patient responses to treatments. Understanding genetic variations in drug-metabolizing enzymes, receptors and transporters and their impact on pharmacokinetics and pharmacodynamics allows for the prediction of drug effects and side effects, enabling tailored treatments for different patient groups. This review focuses on drugs metabolized by cytochrome P450 (CYP450) enzymes, for example, citalopram and clopidogrel or transported by the solute carrier organic anion transporter family member 1B1 (SLCO1B1), for example, atorvastatin and simvastatin, with PGx dosing guidelines, in the context of consumption in Scandinavian countries. A major barrier to the widespread adoption of PGx tests in clinical practice has been healthcare professionals' uncertainty about their efficacy, complexity in result interpretation and questions regarding the evidence base. However, recent studies have demonstrated PGx testing has the potential to improve treatment outcomes, reduce adverse drug reactions and achieve cost savings. These findings underscore the potential of PGx testing as a valuable tool in clinical decision making, promoting its use in a pre-emptive manner to enhance patient care.

PMID:39971612 | DOI:10.1111/bcpt.70009

Drug Ther Bull. 2025 Feb 19:dtb-2025-000008. doi: 10.1136/dtb.2025.000008. Online ahead of print.

NO ABSTRACT

PMID:39971479 | DOI:10.1136/dtb.2025.000008

Reg Anesth Pain Med. 2025 Feb 19:rapm-2024-106152. doi: 10.1136/rapm-2024-106152. Online ahead of print.

NO ABSTRACT

PMID:39971388 | DOI:10.1136/rapm-2024-106152

Intern Med. 2025 Feb 18. doi: 10.2169/internalmedicine.4431-24. Online ahead of print.

ABSTRACT

The causes of hypercalcemia vary. There are high-calcium-containing preparations in Chinese herbal medicine, which may contribute to drug-induced hypercalcemia. We encountered a case of hypercalcemia following the simultaneous administration of an active vitamin D3 preparation and several Chinese herbal medicines. The patient had been treated at several medical institutions, with one institution administering eldecalcitol and another institution administering Keishikaryukotsuboreito, Borei powder, and Goreisan. The patient presented with drug-induced hypercalcemia due to an unexpected synergistic effect. Confirmation of prescriptions for patients with multiple medical visits and recognition of the components and side effects of Chinese herbal medicines is thus considered to be extremely important.

PMID:39971300 | DOI:10.2169/internalmedicine.4431-24

PLoS One. 2025 Feb 19;20(2):e0316900. doi: 10.1371/journal.pone.0316900. eCollection 2025.

ABSTRACT

In the field of earth sciences and remote exploration, the classification and identification of surface materials on earth have been a significant research area that poses considerable challenges in recent times. Although deep learning technology has achieved certain results in remote sensing image classification, it still has certain challenges for multi-modality remote sensing data classification. In this paper, we propose a fusion network based on transformer and gist convolutional neural network (CNN), namely TGF-Net. To minimize the duplication of information in multimodal data, the TGF-Net network incorporates a feature reconstruction module (FRM) that employs matrix factorization and self-attention mechanism for decomposing and evaluating the similarity of multimodal features. This enables the extraction of distinct as well as common features. Meanwhile, the transformer-based spectral feature extraction module (TSFEM) was designed by combining the different characteristics of remote sensing images and considering the problem of orderliness of the sequence between hyperspectral image (HSI) channels. In order to address the issue of representing the relative positions of spatial targets in synthetic aperture radar (SAR) images, we proposed a spatial feature extraction module called gist-based spatial feature extraction module (GSFEM). To assess the efficacy and superiority of the proposed TGF-Net, we performed experiments on two datasets comprising HSI and SAR data.

PMID:39970154 | DOI:10.1371/journal.pone.0316900

Comput Methods Biomech Biomed Engin. 2025 Feb 19:1-23. doi: 10.1080/10255842.2025.2466081. Online ahead of print.

ABSTRACT

The accurate prediction of cardiovascular disease (CVD) or heart disease is an essential and challenging task to treat a patient efficiently before occurring a heart attack. Many deep learning and machine learning frameworks have been developed recently to predict cardiovascular disease in intelligent healthcare. However, a lack of data-recognized and appropriate prediction methodologies meant that most existing strategies failed to improve cardiovascular disease prediction accuracy. This paper presents an intelligent healthcare framework based on a deep learning model to detect cardiovascular heart disease, motivated by present issues. Initially, the proposed system compiles data on heart disease from multiple publicly accessible data sources. To improve the quality of the dataset, effective pre-processing techniques are used including (i) the interquartile range (IQR) method used to identify and eliminate outliers; (ii) the data standardization technique used to handle missing values; (iii) and the 'K-Means SMOTE' oversampling method is used to address the issue of class imbalance. Using the Enhanced Binary Grasshopper Optimization Algorithm (EBHOA), the dataset's appropriate features are chosen. Finally, the presence and absence of CVD are predicted using the Enhanced MobileNetV2 (EMobileNetV2) model. Training and evaluation of the proposed approach were conducted using the UCI Heart Disease and Framingham Heart Study datasets. We obtained excellent results by comparing the results with the most recent methods. The proposed approach beats the current approaches concerning performance evaluation metrics, according to experimental results. For the UCI Heart Disease dataset, the proposed research achieves a higher accuracy of 98.78%, precision of 99%, recall of 99% and F1 score of 99%. For the Framingham dataset, the proposed research achieves a higher accuracy of 99.39%, precision of 99.50%, recall of 99.50%, and F1 score of 99%. The proposed deep learning-based classification model combined with an effective feature selection technique yielded the best results. This innovative method has the potential to enhance the accuracy and consistency of heart disease prediction, which would be advantageous for clinical practice and patient care.

PMID:39970065 | DOI:10.1080/10255842.2025.2466081

Gigascience. 2025 Jan 6;14:giaf011. doi: 10.1093/gigascience/giaf011.

ABSTRACT

BACKGROUND: Melanoma is an aggressive form of skin cancer in which tumor-infiltrating lymphocytes (TILs) are a biomarker for recurrence and treatment response. Manual TIL assessment is prone to interobserver variability, and current deep learning models are not publicly accessible or have low performance. Deep learning models, however, have the potential of consistent spatial evaluation of TILs and other immune cell subsets with the potential of improved prognostic and predictive value. To make the development of these models possible, we created the Panoptic Segmentation of nUclei and tissue in advanced MelanomA (PUMA) dataset and assessed the performance of several state-of-the-art deep learning models. In addition, we show how to improve model performance further by using heuristic postprocessing in which nuclei classes are updated based on their tissue localization.

RESULTS: The PUMA dataset includes 155 primary and 155 metastatic melanoma hematoxylin and eosin-stained regions of interest with nuclei and tissue annotations from a single melanoma referral institution. The Hover-NeXt model, trained on the PUMA dataset, demonstrated the best performance for lymphocyte detection, approaching human interobserver agreement. In addition, heuristic postprocessing of deep learning models improved the detection of noncommon classes, such as epithelial nuclei.

CONCLUSION: The PUMA dataset is the first melanoma-specific dataset that can be used to develop melanoma-specific nuclei and tissue segmentation models. These models can, in turn, be used for prognostic and predictive biomarker development. Incorporating tissue and nuclei segmentation is a step toward improved deep learning nuclei segmentation performance. To support the development of these models, this dataset is used in the PUMA challenge.

PMID:39970004 | DOI:10.1093/gigascience/giaf011

Plant Dis. 2025 Feb 19. doi: 10.1094/PDIS-11-24-2523-RE. Online ahead of print.

ABSTRACT

Yellow dwarf viruses (YDVs) are transmitted by aphids and can significantly reduce grain yield in cereals worldwide. While barley yellow dwarf virus PAV (BYDV PAV) has long been present in Australia, the YDV species barley virus G (BVG) and barley yellow dwarf virus PAS (BYDV PAS) were reported for the first time more recently. Little data about the transmission and host range of BVG has been published worldwide, while epidemiological information about BVG and BYDV PAS in an Australian context is limited. Therefore, glasshouse experiments were conducted to examine the efficiency of the bird cherry-oat aphid (Rhopalosiphum padi), corn leaf aphid (Rhopalosiphum maidis), rose grain aphid (Metopolophium dirhodum) and Russian wheat aphid (Diuraphis noxia) to transmit BVG, BYDV PAS and BYDV PAV. BYDV PAS and BYDV PAV were transmitted at similar rates by each of the four aphid species. Although BVG was most efficiently transmitted by the corn leaf aphid, it was also transmitted, albeit less efficiently, by the bird cherry-oat aphid. Significantly, in our study, the corn leaf aphid transmitted BVG at a much higher rate (63%) using single-aphid inoculations than had previously been reported by others (7%). Varying levels of susceptibility were observed in host range experiments, and four additional BVG hosts were identified. Russian wheat aphid did not transmit any of the viruses examined. These results have implications for YDV management while also demonstrating the complexity and specificity of the relationships between YDVs, the aphids that transmit them and the plant hosts that they infect.

PMID:39970339 | DOI:10.1094/PDIS-11-24-2523-RE

Nucleic Acids Res. 2025 Feb 8;53(4):gkaf058. doi: 10.1093/nar/gkaf058.

ABSTRACT

Transcription factors (TFs) are often classified as activators or repressors, yet these context-dependent labels are inadequate to predict quantitative profiles that emerge across different promoters. A mechanistic understanding of how different regulatory sequences shape TF function is challenging due to the lack of systematic genetic control in endogenous genes. To address this, we use a library of Escherichia coli strains with precise control of TF copy number, measuring the quantitative regulatory input-output function of 90 TFs on synthetic promoters that isolate the contributions of TF binding sequence, location, and basal promoter strength to gene expression. We interpret the measured regulation of these TFs using a thermodynamic model of gene expression and uncover stabilization of RNA polymerase as a pervasive regulatory mechanism, common to both activating and repressing TFs. This property suggests ways to tune the dynamic range of gene expression through the interplay of stabilizing TF function and RNA polymerase basal occupancy, a phenomenon we confirm by measuring fold change for stabilizing TFs across synthetic promoter sequences spanning over 100-fold basal expression. Our work deconstructs TF function at a mechanistic level, providing foundational principles on how gene expression is realized across different promoter contexts, with implications for decoding the relationship between sequence and gene expression.

PMID:39970288 | DOI:10.1093/nar/gkaf058

Sci Adv. 2025 Feb 21;11(8):eado2830. doi: 10.1126/sciadv.ado2830. Epub 2025 Feb 19.

ABSTRACT

The mutational landscape of phylogenetically ultraconserved elements (UCEs), especially those in noncoding DNAs (ncUCEs), and their functional relevance in cancers remain poorly characterized. Here, we perform a systematic analysis of whole-genome and in-house targeted UCE sequencing datasets from more than 3000 patients with cancer of 13,736 UCEs and demonstrate that ncUCE somatic alterations are common. Using a multiplexed CRISPR knockout screen in colorectal cancer cells, we show that the loss of several altered ncUCEs significantly affects cell proliferation. In-depth functional studies in vitro and in vivo further reveal that specific ncUCEs can be enhancers of tumor suppressors (such as ARID1B) and silencers of oncogenic proteins (such as RPS13). Moreover, several miRNAs located in ncUCEs are recurrently mutated. Mutations in miR-142 locus can affect the Drosha-mediated processing of precursor miRNAs, resulting in the down-regulation of the mature transcript. These results provide systematic evidence that specific ncUCEs play diverse regulatory roles in cancer.

PMID:39970212 | DOI:10.1126/sciadv.ado2830

PLoS Comput Biol. 2025 Feb 19;21(2):e1012364. doi: 10.1371/journal.pcbi.1012364. Online ahead of print.

ABSTRACT

For many infectious diseases, the risk of outbreaks varies seasonally. If a pathogen is usually absent from a host population, a key public health policy question is whether the pathogen's arrival will initiate local transmission, which depends on the season in which arrival occurs. This question can be addressed by estimating the "probability of a major outbreak" (the probability that introduced cases will initiate sustained local transmission). A standard approach for inferring this probability exists for seasonal pathogens (involving calculating the Case Epidemic Risk; CER) based on the mathematical theory of branching processes. Under that theory, the probability of pathogen extinction is estimated, neglecting depletion of susceptible individuals. The CER is then one minus the extinction probability. However, as we show, if transmission cannot occur for long periods of the year (e.g., over winter or over summer), the pathogen will most likely go extinct, leading to a CER that is equal (or very close) to zero even if seasonal outbreaks can occur. This renders the CER uninformative in those scenarios. We therefore devise an alternative approach for inferring outbreak risks for seasonal pathogens (involving calculating the Threshold Epidemic Risk; TER). Estimation of the TER involves calculating the probability that introduced cases will initiate a local outbreak in which a threshold number of cumulative infections is exceeded before outbreak extinction. For simple seasonal epidemic models, such as the stochastic Susceptible-Infectious-Removed model, the TER can be calculated numerically (without model simulations). For more complex models, such as stochastic host-vector models, the TER can be estimated using model simulations. We demonstrate the application of our approach by considering chikungunya virus in northern Italy as a case study. In that context, transmission is most likely in summer, when environmental conditions promote vector abundance. We show that the TER provides more useful assessments of outbreak risks than the CER, enabling practically relevant risk quantification for seasonal pathogens.

PMID:39970184 | DOI:10.1371/journal.pcbi.1012364

Cell Rep. 2025 Feb 18;44(2):115317. doi: 10.1016/j.celrep.2025.115317. Online ahead of print.

ABSTRACT

Cancer cells are often aneuploid and frequently display elevated rates of chromosome mis-segregation, called chromosomal instability (CIN). CIN is caused by hyperstable kinetochore-microtubule (K-MT) attachments that reduce the correction efficiency of erroneous K-MT attachments. UMK57, a chemical agonist of the protein MCAK (mitotic centromere-associated kinesin), improves chromosome segregation fidelity in CIN cancer cells by destabilizing K-MT attachments, but cells rapidly develop resistance. To determine the mechanism, we performed unbiased screens, which revealed increased phosphorylation in cells adapted to UMK57 at Aurora kinase A phosphoacceptor sites on BOD1L1 (protein biorientation defective 1-like-1). BOD1L1 depletion or Aurora kinase A inhibition eliminated resistance to UMK57. BOD1L1 localizes to spindles/kinetochores during mitosis, interacts with the PP2A phosphatase, and regulates phosphorylation levels of kinetochore proteins, chromosome alignment, mitotic progression, and fidelity. Moreover, the BOD1L1 gene is mutated in a subset of human cancers, and BOD1L1 depletion reduces cell growth in combination with clinically relevant doses of Taxol or Aurora kinase A inhibitor.

PMID:39970043 | DOI:10.1016/j.celrep.2025.115317

Proc Natl Acad Sci U S A. 2025 Feb 25;122(8):e2405379122. doi: 10.1073/pnas.2405379122. Epub 2025 Feb 19.

ABSTRACT

Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, as in other examples where selection acts on multiple traits, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+ T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical dataset. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses and could be adapted to study the evolution of quantitative traits in other contexts.

PMID:39970000 | DOI:10.1073/pnas.2405379122

Cancer Med. 2025 Feb;14(4):e70681. doi: 10.1002/cam4.70681.

ABSTRACT

BACKGROUND: Ovarian cancer (OC) is the most lethal gynecological malignancy and a major global health concern, often diagnosed at advanced stages with poor survival rates. Despite advancements in treatment, resistance to standard chemotherapy remains a critical challenge with limited treatment options available. In recent years, the role of metabolic reprogramming in OC has emerged as a key factor driving tumor progression, therapy resistance, and poor clinical outcomes.

METHODS: This review explores the intricate connections between metabolic syndrome, enhanced glycolysis, and altered lipid metabolism within OC cells, which fuel the aggressive nature of the disease. We discuss how metabolic pathways are rewired in OC to support uncontrolled cell proliferation, survival under hypoxic conditions, and evasion of cell death mechanisms, positioning metabolic alterations as central to disease progression. The review also highlights the potential of repurposed metabolic-targeting drugs, such as metformin and statins, which have shown promise in preclinical studies for their ability to disrupt these altered metabolic pathways.

CONCLUSION: Drug repurposing offers a promising strategy to overcome chemoresistance and improve patient outcomes. Future research should focus on unraveling the complex metabolic networks in OC to develop innovative, targeted therapies that can enhance treatment efficacy and patient survival.

PMID:39969135 | DOI:10.1002/cam4.70681