Metabolic reprogramming is closely associated with the development and progression of cancer and is considered an emerging hallmark of cancer. To meet the bioenergetic and biosynthetic demands, tumor cells tend to initiate the metabolic reprogramming process, creating a tumor microenvironment that is adaptable for cancer cell growth and further promote oncogenic signaling, cell proliferation and metastasis. As a final byproduct of purine metabolism, the uric acid (UA) concentration rises in the quickly growing tumor microenvironment. However, whether elevated UA affects the development and prognosis of patients with tumors has not been demonstrated. In the present study, Cell Counting Kit‑8 and scratch healing test were used to investigate the effects of UA on the proliferation and migration of breast cancer cells. The effects of UA on nucleotide de novo synthesis genes in breast cells were validated using quantitative PCR (qPCR) and western blotting (WB). The activation of stemness in breast cancer cells by UA was validated using colony formation assays, ELISA, qPCR and WB. Finally, clinical data and The Cancer Genome Atlas database were analyzed to examine the expression of de novo nucleotide synthesis genes in cancerous and adjacent tissues, as well as in different types of breast cancer tissues. The present study investigated the potential effect of UA on the function of breast cancer; it also determined how UA affected the genes involved in nucleotide de novo synthesis, as well as how it contributes to tumor stemness. It was discovered that UA could enhance tumor stemness in breast cancer cells through the upregulation of guanosine 5'‑monophosphate synthase (GMPS). It was notable that GMPS expression in patients with breast cancer may be strongly associated with the course of the disease and the prognosis of patients. In conclusion, the present study demonstrated that elevated UA upregulates GMPS and stimulates the migration and proliferation of breast cancer cells through the cyclic guanosine monophosphate/protein kinase G/mitogen‑activated protein kinase pathway axis.

Breast cancer is the most abundant cancer type in female. Genome-wide association study suggests that rs2016394, one SNP at the intron of DLX2 divergent transcript (DLX2-DT), is significantly associated with this disease. Through 1000 genomes project data analysis, it is observed that another three SNPs, rs743605, rs2357322, and rs17726078, show strong linkage disequilibrium with rs2016394. However, the functional SNP(s) and mechanism are still unknown.

Mutant KRAS inhibition has revolutionized the treatment of lung adenocarcinoma. Unfortunately, responses to this form of targeted therapy are often of limited duration because of the development of resistance. Targeted protein degradation, including using PROTACs (PROteolysis-TArgeting Chimeras), presents an alternative approach to targeting oncogenic drivers in cancer. In this issue of Cancer Research, Martín and colleagues developed a dTAG-KRASG12V syngeneic mouse model that allows for the study of the effects of degrading the KRASG12V oncoprotein in vivo. The authors discovered that degrading the KRASG12V oncoprotein leads to regression of the resulting lung adenocarcinoma tumors. Most of the regression was based on cancer cell-intrinsic responses, although the tumor microenvironment also underwent substantial remodeling. Despite the initial efficacy of the treatment, the authors found that prolonged PROTAC KRAS degrader treatment eventually resulted in relapse. Resistance to PROTAC treatment seemed to be driven by dysregulation of the ubiquitin-proteasome system that is required for the activity of the PROTAC degraders. Despite developing resistance to the PROTAC degraders, the resulting tumors were still dependent on the KRAS oncoprotein, meaning that they were still sensitive to conventional KRAS inhibitors. Thus, PROTACs that degrade the KRAS oncoprotein are a promising modality for the treatment of lung adenocarcinomas. Resistance to PROTACs may differ from conventional KRAS inhibitors, suggesting potential strategies for overcoming such resistance. See related article by Martín et al., p. 4115.

Programmed death-ligand 1 (PD-L1) expression is widely used to guide immune checkpoint inhibitor (ICI) therapy in advanced nonsmall cell lung cancer (NSCLC); however, substantial heterogeneity in clinical outcomes persists among patients with high PD-L1 expression. Reliable biomarkers for further stratifying this population are still lacking. This study investigated whether genomic alterations and features of the tumor immune microenvironment could explain this variability.

Adult thalamic gliomas (ATGs) are rare and biologically heterogeneous tumors. Although the 2021 World Health Organization (WHO) classification designates all diffuse midline gliomas (DMGs), H3-altered, as grade 4, accumulating evidence suggests that adult thalamic DMGs may exhibit more indolent clinical behavior, compared with glioblastomas or pediatric DMGs. In this study, we aimed to characterize the clinical, radiological, pathological, and molecular features of ATGs and identify clinically relevant prognostic markers, with particular focus on H3K27M and TERT promoter (TERTp) mutations.

KRAS mutations, particularly KRAS G12C, pose significant therapeutic challenges in non-small cell lung cancer (NSCLC) due to limited inhibitor efficacy and rapid resistance. Drug repurposing offers a time and cost-effective strategy to identify alternative therapeutic options targeting KRAS-driven signalling. A structure-based drug repurposing approach was employed to screen FDA-approved compounds targeting key regulators to the MAPK signalling pathway and computationally modelled for potential engagement with the KRAS G12C switch-II pocket. Computational analyses including virtual screening, molecular docking, and molecular dynamics simulations were used to evaluate binding affinity, stability and potential protein-ligand interactions. Lead candidates were subsequently validated using in vitro functional assays, ex ovo chorioallantoic membrane (CAM) and in vivo chemical induced lung carcinoma model. Computational analyses identified nilotinib and risperidone as high affinity candidates across MAPK pathway targets. Functional assays confirmed that nilotinib markedly reduced NSCLC cell viability, colony formation and angiogenesis, while inhibiting cell migration and inducing apoptosis. In vivo, nilotinib significantly lowered tumor burden and modulated immune and inflammatory profiles in a chemically induced murine lung carcinoma. These findings support nilotinib as a promising therapeutic candidate for KRAS-mutant NSCLC. Further studies involving target-engagement assays, pathway-validation experiments and genetically defined KRAS-G12C driven models are warranted to establish its precise mechanism of action.

Perturbation of macropinocytosis triggers methuosis, a non-apoptotic cell death characterized by cytoplasmic vacuolization. However, the regulatory mechanisms of methuosis remain poorly defined. Lipid metabolism dysregulation is implicated in various cell death pathways, while its role in methuosis has remained elusive. Herein, LXX-8250, an isopropanolamine derivative of β-elemene, induced a vacuolization-associated cell death in breast and liver cancer cell lines. This process was accompanied by massive macropinocytosis, thereby confirming the occurrence of methuosis. Mechanistically, hypoxia-inducible lipid droplet-associated protein (HILPDA), a key regulator that promotes intracellular triacylglycerol (TAG) accumulation, was identified as the direct target of LXX-8250. By suppressing HILPDA, LXX-8250 inhibited diacylglycerol O-acyltransferase 1 (DGAT1) and activated adipose triglyceride lipase (ATGL). Consequently, lipid droplets and cellular TAG levels were reduced, while the subsequent increased diacylglycerol (DAG) stimulated macropinosome formation, leading to methuosis in these cells. In this study, we discover a novel methuosis agonist LXX-8250, and elucidate the critical role of HILPDA repression-dysregulated lipid metabolism in methuosis. Our study highlighted the potential of targeting this pathway as a therapeutic strategy to trigger cancer cell death.

Objective: To investigate the clinical value of dynamic monitoring of plasma circulating tumor DNA (ctDNA) in evaluating the efficacy of immunotherapy for esophageal squamous cell carcinoma (ESCC). Methods: Plasma samples were collected at baseline and after every 2-3 treatment cycles from 94 patients with advanced ESCC receiving second-line sintilimab monotherapy in the ORIENT-2 study. Targeted sequencing was performed to analyze somatic variants in ctDNA, and the molecular tumor burden index (mTBI) was calculated to assess dynamic changes in ctDNA. Imaging examinations were conducted synchronously with plasma sample collection, and treatment response was evaluated according to the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1). Results: A total of 614 somatic mutations were detected in 93 eligible baseline plasma samples, with a median of 6 mutations per sample. Missense mutations were the most frequent mutation type. The baseline mutational profile revealed frequently mutated genes including TP53 (82%), CDKN2B (23%), and NOTCH1 (22%). In the 68 patients with both baseline and post-2-cycle plasma samples, no significant changes were observed in the variant allele frequencies (VAFs) of core driver genes before and after treatment (all P＞0.05), and no newly emerged core driver gene mutations were identified. CCND1 copy number variation was associated with shorter progression-free survival (PFS) (HR=1.88, 95% CI: 1.08-3.27), while mutations in other genes, including TP53 and NOTCH1, showed no association with PFS (all P＞0.05). None of the frequently mutated genes were associated with overall survival (OS) (all P＞0.05). Among the 68 patients, 11 (15.9%) achieved ctDNA clearance, none of whom showed tumor progression on concurrent imaging evaluation. The remaining 57 patients had ctDNA that became positive or remained persistently positive, of whom 30 (52.6%) showed tumor progression on imaging, with a statistically significant difference between groups (P=0.002). Compared with patients whose ctDNA became or remained positive, those with ctDNA clearance exhibited significantly delayed tumor progression (HR=2.05, 95% CI: 1.06-3.96), but ctDNA status after 2 cycles did not significantly affect OS (HR=1.38, 95% CI: 0.62-3.09). After 2 cycles of treatment, patients in the low mTBI group had a higher disease control rate (DCR) than those in the high mTBI group [73.5% (25/34) vs. 38.2% (13/34), P=0.007], as well as superior PFS (HR=2.80, 95% CI: 1.65-4.75) and OS (HR=3.54, 95% CI: 1.95-6.42). Dynamic changes in mTBI were highly consistent with concurrent imaging response assessments. The molecular response group had a significantly higher DCR than the non-response group [87.5% (21/24) vs. 42.2% (19/45), P＜0.001], as well as superior PFS (HR=2.39, 95% CI: 1.41-4.06) and OS (HR=2.77, 95% CI: 1.46-5.22). Among 32 patients with stable disease (SD) at the first imaging evaluation after 2 cycles, those in the molecular response group had comparable PFS with the non-response group (HR=1.03, 95% CI: 0.51-2.08, P=0.942), but significantly longer OS (HR=3.12, 95% CI: 1.20-8.06). Conclusion: Dynamic monitoring of the ctDNA-based molecular tumor burden index (mTBI) provides real-time and sensitive molecular information for evaluating the efficacy of immunotherapy in advanced ESCC, demonstrating definite clinical value for personalized treatment management.

Objective: To investigate the expression profile of Centromere Protein N (CENPN) in invasive breast cancer (BRCA), evaluate its prognostic significance, and assess its involvement in immune regulation. Methods: The expression, prognostic value, and correlation with tumor immunogenicity of CENPN in BRCA tissues were analyzed based on The Cancer Genome Atlas (TCGA) database. Verification was conducted using cancerous and adjacent normal tissues from BRCA patients who underwent surgical treatment at Yantai Mountain Hospital between January 2022 and April 2023. CENPN expression in various immune cells in the blood was examined using the Human Protein Atlas (HPA) database. Genetic alterations of CENPN in breast cancer tissues were analyzed via the cBioPortal database. CENPN-related genes were screened using the GEPIA 2.0 database, and the interaction network between CENPN and similar genes was visualized with the STRING database. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA) were employed to explore the potential biological functions of CENPN. The correlation between CENPN expression and immune cell infiltration, as well as immune cell markers in BRCA tissues, was assessed using the TIMER 2.0 database. The effect of CENPN on the proliferation ability of breast cancer MCF-7 cells was detected by the CCK-8 assay, and its impact on the migration ability of MCF-7 cells was evaluated by a wound healing assay. Results: Analysis of TCGA database data revealed that CENPN expression was significantly higher in BRCA tissues compared to adjacent normal tissues (P＜0.05). Validation in our institutional cohort demonstrated a significantly higher positivity rate for CENPN in the 17 breast cancer tissues (82.4%) than in the paired paracancerous tissues (5.9%, P＜0.001). According to the HPA database, elevated CENPN expression was observed in T-reg cells, naïve B cells, and myeloid dendritic cells. Kaplan-Meier survival analysis indicated that patients with high CENPN expression had poorer overall survival (HR=1.39, P＜0.001), recurrence-free survival (HR=1.31, P＜0.001), post-progression survival (HR=1.28, P=0.036), and distant metastasis-free survival (HR=1.6, P＜0.001). Correlation analysis revealed a negative association between CENPN expression and tumor mutational burden in BRCA patients (r=-0.196, P＜0.001). Furthermore, CENPN expression was positively correlated with 5 out of 20 common immune checkpoint genes and negatively correlated with the remaining 15, suggesting its potential for predicting immunotherapy response. Analysis via the cBioPortal database showed that invasive lobular breast carcinoma had the highest CENPN alteration frequency, with amplification being the most common alteration in BRCA. Invasive mixed mucinous breast carcinoma exhibited the highest mutation frequency, and a key missense mutation (K329N) was identified as a potential driver in BRCA.GO enrichment analysis demonstrated that CENPN-related genes were primarily involved in cell cycle, DNA metabolic processes, cell division, nuclear lumen, chromosomes, nucleoplasm, and functions related to ATP, nucleotide, and small molecule binding. KEGG pathway analysis indicated significant enrichment in DNA replication, cellular senescence, mismatch repair, homologous recombination, p53 signaling pathway, and FOXO signaling pathway. Correlation analysis using the TIMER 2.0 database established associations between CENPN expression and the infiltration levels of B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells in BRCA. Positive correlations were also found with markers for CD8+ T cells, B cells, T cells, and T-cell exhaustion.CCK-8 assay and wound healing experiments confirmed that CENPN knockdown significantly suppressed malignant phenotypes, including proliferation and migration, in MCF-7 cells. Additionally, CENPN knockdown was found to enhance the chemosensitivity of MCF-7 cells to the anti-tumor agents 5-fluorouracil and gemcitabine. Conclusion: CENPN serves as a potential prognostic biomarker and a novel target for immunotherapy in BRCA.

Objective: This study aims to investigate the expression characteristics of GLUT10 in breast cancer and its role in mediating cisplatin resistance, with the goal of providing a new molecular target for personalized breast cancer treatment. Methods: Data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases were analyzed using the GEPIA2 platform to assess pan-cancer expression, while the UALCAN platform was used to analyze expression differences between breast cancer and normal breast tissues. In vitro, SK-BR-3 cells were divided into three groups: shScr (transfected with non-targeting scrambled shRNA), shSLC2A10#1, and shSLC2A10#2. MDA-MB-231 cells were divided into a vector control group and an SLC2A10 overexpression group. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect SLC2A10 mRNA expression. Western blotting was used to detect GLUT10 and cleaved caspase-3 protein expression. The CM-H2DCFDA probe was used to measure intracellular reactive oxygen species (ROS) levels. Drug sensitivity and colony formation assays were performed to evaluate cisplatin sensitivity, and flow cytometry was used to detect apoptosis rates. Results: GEPIA2 analysis showed that GLUT10 expression was downregulated in adrenocortical carcinoma, cervical squamous cell carcinoma and adenocarcinoma, and kidney chromophobe tumor tissues compared to normal tissues, whereas it was upregulated in invasive breast cancer, glioma, skin melanoma, and thymoma. UALCAN analysis revealed that SLC2A10 mRNA levels in breast cancer tissues were 1.85-fold higher than in normal breast tissues (P＜0.001). RT-qPCR results showed that SLC2A10 mRNA expression levels in breast cancer cell lines, ranked from high to low, were Hs 578T (160.5±12.3), SK-BR-3 (115.2±10.5), MDA-MB-468 (50.1±5.2), T-47D (35.4±4.1), and MCF7 (25.6±3.8), all significantly higher than in normal breast epithelial cells (P＜0.001). In SK-BR-3 cells, compared with the shScr group, the shSLC2A10#1 and shSLC2A10#2 groups exhibited increased intracellular ROS levels (relative fluorescence intensity: 1.78±0.12 and 2.05±0.15, respectively; P＜0.05), increased cisplatin sensitivity, reduced colony numbers, and promoted cisplatin-induced ROS accumulation and apoptosis. In MDA-MB-231 cells, compared with the vector control group, the SLC2A10 overexpression group showed decreased intracellular ROS levels (relative fluorescence intensity: 0.58±0.09, P＜0.05), decreased cisplatin sensitivity, and inhibited cisplatin-induced ROS accumulation and apoptosis. Conclusion: GLUT10 is highly expressed in breast cancer and mediates cisplatin resistance by regulating ROS levels, suggesting it may serve as a novel therapeutic target for reversing drug resistance in breast cancer.

Immunotherapeutic approaches for cutaneous squamous cell carcinoma (cSCC) remain limited to programmed cell death protein 1 (PD-1) blockade. Although genomics studies have characterized key driver mutations in cSCC, preclinical models that faithfully recapitulate both the genetic landscape and immune microenvironment of the human disease, that could drive the development of novel, effective therapies, are lacking.

HLA-G is a non-classical MHC class I molecule with potent immunoregulatory functions that is aberrantly expressed in multiple malignancies, yet its tumor-intrinsic role remains poorly defined. To characterize this potential oncogenic role of HLA-G in clear cell renal cell carcinoma (ccRCC), we utilized integrated transcriptomic, in vitro, and in vivo approaches. Analysis of the Cancer Genome Atlas (TCGA) ccRCC cohort revealed that elevated HLA-G expression was associated with immunosuppressive programs and cell populations. Interrogation of a publicly available ccRCC single-cell RNA sequencing dataset revealed that HLA-G expression within tumor epithelial clusters is associated with hypoxia-driven, metabolic transcriptional programs. Multiplex immunofluorescence of human ccRCC specimens confirmed the presence of tumor cell-intrinsic HLA-G expression in advanced disease. Functional studies using RCC7 cells expressing the full-length canonical HLA-G isoform (RCC7/HLA-G1) demonstrated increased proliferation, migration, clonogenicity, cell-cycle progression, and resistance to apoptosis compared with HLA-G-negative RCC7wt cells. RCC7/HLA-G1 xenografts exhibited accelerated tumor growth accompanied by the activation of proliferative, stemness-related, and metabolic programs. Multi-omics analyses further revealed enhanced mitochondrial activity and redox metabolic adaptation in HLA-G-expressing tumors. Mechanistically, HLA-G expression was associated with increased VEGF-C expression and enhanced VEGFR3 signaling, suggesting the activation of a VEGF-C/VEGFR3-associated pro-survival pathway. In three-dimensional tumor spheroid immune cell co-culture models, HLA-G expression reduced CD8⁺ T-cell-mediated cytotoxicity while promoting regulatory T-cell expansion and macrophage polarization toward an immunosuppressive M2-like phenotype. Collectively, these findings establish HLA-G as a key contributor to tumor progression and immune suppression in ccRCC and support HLA-G as a promising therapeutic target.

Homologous recombination repair (HRR) pathway defects are critical drivers of hereditary cancers, yet population-specific prevalence data from India remain limited. Current testing practices disproportionately focus on BRCA1/2, potentially underidentifying patients with other HRR gene variants who could benefit from targeted therapies.

This review shares the ongoing work of the global Worldwide Innovative Network (WIN) Consortium for Precision Medicine to synthesize emerging cancer treatment data and to define the requirements for a common global cancer database that can truly support precision oncology. We performed a narrative review of emerging cancer treatment data, molecular profiling technologies, and existing clinicogenomic databases, focusing on how tumors are characterized, how subgroups are defined, and how demographic, lifestyle, and environmental factors are captured. The growth in molecular profiling technologies and the development of new targeted therapies are transforming cancer care. Tumors, regardless of tissue origin, are increasingly defined as composites of multiple, often rare, subgroups, each with distinct biology and likely response to specific therapies, based on multidimensional profiling of the tumor and its microenvironment. The solution lies in building vast databases that capture racial and ethnic diversity, reflected in genomic data, as well as diet and lifestyle factors that may have epigenetic impact on gene expression and post-translational modifications. A truly inclusive and informative data set must reflect global diversity, and there are multiple examples of demography-dependent differences in genomic signals. With members caring for and studying patients with cancer across five continents, WIN is actively exploring pathways to create a global cancer database, rich in clinical and molecular detail, granular enough for precise analysis, and large enough to power artificial intelligence-driven insights, provided appropriate data quality, validation, and governance frameworks are in place. This review surveys the current landscape and outlines practical paths forward to achieve this goal.

Primary breast neuroendocrine carcinomas (NECs) are rare, high-grade malignancies that are frequently grouped with invasive breast carcinomas with neuroendocrine differentiation (IBC-NED), despite uncertain biological equivalence. We sought to define the clinicopathologic, immunophenotypic, and genomic features of breast NEC and to determine whether they represent a biologically distinct entity.

Diffuse midline gliomas (DMGs) are highly aggressive, WHO grade 4 glial tumors that arise in midline central nervous system structures and are defined by K27M mutations in histone H3 genes. These K27M mutations shape intratumoral myeloid cell composition in DMG. In H3.1K27M DMGs, genetic ablation of monocyte recruitment reshapes the tumor microenvironment (TME) by reducing monocyte-derived macrophages (MDMs) and increasing microglia and neutrophil presence, with overall survival remaining unchanged, indicating compensatory myeloid remodeling is occurring. Here, by using CRISPR/Cas9-based genome editing, we generated a mouse model deficient for CCR1/CCR2/CCR3/CCR5 (Δ1235). Using this strain, we effectively abolished monocyte and MDM infiltration and reversed compensatory recruitment of CCR1+ neutrophils. Abolishing MDMs in tumors skewed remaining neutrophils and microglia toward a homeostatic state, reduced expression of immune checkpoint molecules on T cells, and extended the survival of H3.1K27M DMG-bearing mice. In contrast, H3.3K27M DMG showed independence from MDM recruitment, suggesting reliance on other TME-driven signaling. Last, H3.1K27M DMGs exhibited reduced microglia presence and a dose-dependent increase in MDM infiltration postirradiation. MDM depletion did not further enhance radiation efficacy, potentially due to compensatory recruitment of classical neutrophils. Collectively, these data reveal histone mutation-specific myeloid dependencies in DMG, highlighting MDM-independent mechanisms in H3.3K27M tumors and MDM-dependent pathways in H3.1K27M tumors.

Learning to Rank (LeToR) methods have gained increasing attention in drug response prediction, offering a direct way to prioritize effective treatments for cancer cell lines. In this study, we systematically benchmark six ranking loss functions, including state-of-the-art listwise methods, and five types of molecular representations across two large-scale drug screening datasets, CTRP and PRISM. Using high-dimensional gene expression profiles and various drug fingerprints and descriptors, we evaluated models under multiple validation setups and ranking metrics. Our results demonstrate that listwise loss functions such as LambdaLoss and LambdaRank consistently excel in both early and overall ranking quality. Additionally, combining molecular fingerprints with physicochemical descriptors yielded improved performance. A novel attention-based mechanism and a modified version of RankingSHAP were integrated to enhance interpretability, uncovering key genes and substructures aligned with known biological insights. The explainability pipeline successfully distinguished estrogen receptor-positive (ER⁺) and estrogen receptor-negative (ER-) breast cancer subtypes. The model successfully identified critical substructures in docetaxel, an FDA-approved therapy, and triptolide, which is currently undergoing clinical evaluation for breast cancer. These findings are consistent with established structure-activity relationship (SAR) data. Overall, this study presents a comprehensive evaluation framework and underscores the importance of carefully selecting loss functions and feature representations when developing robust and interpretable drug-ranking systems.

Breast cancer is the most common cancer in women and a leading cause of death. Traditional risk assessment models, such as the Gail model, lack molecular insight, limiting their usefulness for personalized prevention strategies. We developed a computational framework that integrates individual transcriptomic data with dynamic modeling of cell signaling to create personalized models for 30 subjects (including 15 who later developed breast cancer). Using features extracted from the dynamic simulation, we stratified individuals into four risk clusters with significantly different disease-free periods. The highest-risk group had a median disease-free period of 6.05 years, which is significantly shorter than that of the other clusters. This high-risk phenotype was characterized by hyperactive MAPK signaling (high phosphorylated ERK, phosphorylated RSK, and c-Fos). This approach demonstrates that interactions among pathway components provide additional information beyond static gene expression profiles in risk assessment and may serve as a promising tool for guiding personalized prevention strategies.

Smoking cessation decreases lung cancer progression; however, its effects on precancerous lesions and the underlying mechanisms remain unclear. This study established a mouse model of precancerous pulmonary nodules and employed single-cell RNA sequencing (scRNA-seq) and immune repertoire sequencing (IR-seq) to elucidate the regulatory mechanisms by which smoking cessation influences the development of lung precancerous lesions.

This study aimed to links between ATP7B, CTR1, GPX4, 53BP1, p-H2AX and p-ATM expression, platinum sensitivity and prognosis in patients with epithelial ovarian cancer (EOC).