Radiation-induced liver damage (RILD) significantly limits the clinical application of radiotherapy for upper abdominal malignancies. Radiation can induce metabolic disorder in liver tissues. However, there is no systematic research on the effects of radiation on liver metabolism. In this study, we collected time-series liver tissue samples from irradiated rats at multiple time points, from 3 days to 4 weeks after exposure, to reveal dynamic alterations in metabolic profiles throughout RILD progression. Acetylcholic acid, p-hydroxyphenyl-lactic acid, ascorbic acid, daidzein, and glutamine (Gln) were identified as potential biomarkers, demonstrating good diagnostic sensitivity and specificity. As a metabolomic biomarker, Gln emerged as a potential metabolic target based on pathway enrichment analysis, which could modulate the radiosensitivity of both mouse (JS-1) and human (LX-2) hepatic stellate cells. Transcriptomics, co-immunoprecipitation (Co-IP) and functional rescue experiments demonstrated that the regulation of radiosensitivity by Gln is mediated through the Col1α2/ITGB1/AKT signaling axis. In the mouse RILD model, Gln prevented irradiation-induced body weight loss, preserved liver structure, and reduced TGF-β and TNF-α expression as well as collagen deposition. L-alanyl-glutamine (Ala-Gln) and liposomes were introduced to further enhance the radioprotective effects of Gln. This study provides the necessary theoretical and experimental basis for diagnosis and intervention of RILD.

Rac1 is a small GTPase of the Rho family. It is a central regulator of cytoskeletal remodeling, cell adhesion, migration, and secretion. Dysregulation of Rac1 activity drives tumorigenesis, with the cancer-associated P29S mutation ranking as the third most frequently mutated proto-oncogene in sun-exposed melanoma. P29S is a prototypical gain-of-function, fast-cycling variant that destabilizes GDP binding and accelerates nucleotide exchange. Another cancer-associated mutant, F28L, produces cellular phenotypes strikingly similar to those of P29S yet has been proposed to act through a distinct local structural perturbation, raising the question of whether they share a common activation mechanism. Defining this shared mechanism is critical for understanding Rac1-driven oncogenesis and for guiding the rational design of inhibitors that effectively target these activating mutations. Here, integrating molecular dynamics simulations, potential of mean force calculations, and biochemical assays, we show that P29S, F28L, and the structurally distinct L160C mutant all weaken GDP binding while enhancing GTP affinity─revealing an oncogenic mechanism beyond fast cycling. Structural dynamic analyses uncover a shared "teeter-totter-like" redistribution of the Switch I region, in which destabilization of its N-terminal hydrophobic core is coupled to reinforcement of its C-terminal contact network. This dynamic shift strengthens effector binding, as validated by GTPase pull-down assays, and is also reproduced by other cancer-associated mutants in Rac1 (I21S, P34S, D57E). Our findings identify the β6-α5 loop as an allosteric hub linking nucleotide binding to effector engagement and suggest that rebalancing the Switch I region may provide a therapeutic strategy to counteract Rac1-driven oncogenic signaling.

HER2-positive breast cancer exhibits marked genomic instability and heterogeneity, yet the clonal architecture and copy number variation (CNV) dynamics between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC), remain poorly understood. We analyzed single-cell RNA sequencing data from 14 HER2-positive breast cancer patients and spatial transcriptomics from 8 patients. CNVs were inferred to evaluate genomic alterations and reconstruct tumor subclone evolutionary trajectories. Survival analyses were performed on CNV-correlated transcripts. We identified 68,064 cells and 4,764 spatial transcriptomic spots, and observed early and pervasive CNV events in DCIS. IDC exhibiting a higher CNV burden supported the hypothesis of progressive genomic instability during tumor evolution. Shared CNV regions across DCIS and IDC suggested the common clonal origin, favoring a multi-threaded evolutionary model. Amplifications in chromosome 17q12-21 were associated with poor prognosis. CNV-driven clonal evolution probably originates at early stages of HER2-positive breast cancer and persists through disease progression. Early CNV events may serve as predictive biomarkers and potential intervention targets to prevent disease advancement.

Radiation-induced lung injury (RILI) is a critical dose-limiting toxicity that occurs during thoracic tumor radiotherapy, and the mechanisms underlying RILI remain incompletely understood. As previously reported, there is a demonstrable correlation between metabolic changes and RILI. To further investigate the regulatory mechanisms underlying RILI, the metabolomic analysis of bronchoalveolar lavage fluid (BALF) and transcriptomic analysis of lung tissue post ionizing radiation (IR) were performed. The results of the study revealed that the sphingolipid signaling pathway was activated in response to IR, characterized by a substantial decrease in sphingomyelin (SM) and an increase in ceramide (Cer). SM treatment significantly mitigated radiation-induced cell damage in BEAS-2B and RLE-6TN cells and reduced inflammatory infiltration in lung tissues of C57BL/6 mice, while C16-Cer showed the opposite effect. Furthermore, we identified that the ceramide transporter (CERT), a lipid transfer protein delivering Cer from the endoplasmic reticulum (ER) to the Golgi apparatus for SM synthesis, plays an indispensable protective role against RILI. Mechanistically, CERT expression is associated with protection against RILI, concomitant with an elevated SM/Cer ratio and alterations in PP2A abundance and AKT phosphorylation. This study provided a reliable theoretical and experimental foundation for developing novel therapeutic strategies that target CERT-mediated sphingolipid homeostasis in the progression of acute RILI.

Given the potential of polyphenols to mitigate neurodegenerative diseases (NDDs), this meta-analysis investigated whether clinical evidence supports the use of polyphenols for neuroprotection and as nutritional strategies in NDDs. We analyzed different polyphenol types across seven NDDs, 13 studies involving 849 participants were included. Prespecified outcomes comprised global cognition (Mini-Mental State Examination, MMSE), domain-specific cognition (Alzheimer's Disease Cooperative Study-Cognitive Subscale, ADCS-Cog), activities of daily living (Alzheimer's Disease Cooperative Study-Activities of Daily Living, ADCS-ADL), neuropsychiatric symptoms (Neuropsychiatric Inventory, NPI), and selected biomarkers (plasma amyloid-β40 and brain-derived neurotrophic factor, BDNF). Reporting followed PRISMA 2020 guidelines, methods conformed to the Cochrane Handbook, and certainty of evidence was assessed using GRADE. Overall, polyphenol supplementation was associated with improved global cognition (pooled MD in MMSE = 2.06; 95% CI 0.62-3.49). In subgroup analyses, flavonoids were associated with a modest but significant improvement in MMSE scores, whereas stilbenes produced a significant benefit in daily functioning (ADCS-ADL) without clear gains in MMSE or ADCS-Cog and no consistent effects on NPI. Anthocyanidins, phenolic acids, and lignans did not significantly affect cognitive outcomes (MMSE or ADCS-Cog), and polyphenol subclasses did not yield robust or consistent changes in NPI or biomarker endpoints (Aβ40 and BDNF). Specific polyphenol subclasses therefore appear to confer selective cognitive and functional benefits, with stilbenes primarily supporting functional outcomes and flavonoids potentially enhancing global cognition.

The selection of appropriate machine learning (ML) methods for clinical research remains challenging, particularly when both predictive performance and model explainability are required in small-sample datasets. Conventional approaches often rely on limited variables and expert-driven choices, whereas many ML models remain difficult to justify clinically. This study aimed to develop an explainable ML model selection pipeline and demonstrate its application in predicting neoadjuvant chemoradiotherapy (nCRT) response in locally advanced rectal cancer (LARC). We proposed a six-stage explainable ML model selection pipeline comprising data selection and preprocessing, algorithm pool construction, model training, model evaluation, model explanation, and an internal clinical logic consistency check (non-deployable sanity check). The workflow was applied to a retrospective cohort of 128 patients with LARC treated with nCRT. Four ML algorithms, including support vector machine (SVM), decision tree (DT), random forest (RF), and logistic regression (LR), were evaluated. Model performance was assessed using accuracy, F1-score, AUROC, AUPRC, bootstrap confidence intervals, and five-fold cross-validation, followed by explainability screening using SHAP. Under predefined screening criteria, DT models achieved the most favorable balance between predictive performance and explainability. Using pretreatment tumor markers alone, the selected DT models achieved an accuracy of 0.82 and F1-score of 0.71 for pathological complete response (pCR) prediction, and an accuracy of 0.76 and F1-score of 0.72 for tumor regression grade (TRG) prediction. SHAP analysis consistently identified carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19-9) as the most influential predictors, and lower baseline levels of these markers were associated with better pathological response. This study provides a practical and reproducible framework for selecting interpretable ML models in small clinical datasets. In the present LARC case study, DT-based models showed acceptable discrimination and transparent decision logic, while tumor markers emerged as clinically plausible predictors of nCRT response. The proposed workflow may support future multi-center validation and broader application in clinically interpretable predictive modeling.

Radiotherapy is a central modality in cancer management, yet intrinsic and acquired radioresistance and dose-limiting normal tissue toxicities continue to constrain durable tumor control. Beyond genetic and transcriptional programs, post-translational modifications (PTMs) provide rapid and reversible regulation that can rewire radiation responses across tumor and stromal compartments. This review synthesizes recent advances defining how major PTM axes, including ADP-ribosylation, ubiquitination and deubiquitination, neddylation, SUMOylation, methylation, acetylation, and lactylation, shape tumor radiosensitivity and radiation-induced injury. We highlight mechanistic links to DNA damage recognition and repair pathway choice, chromatin remodeling, checkpoint control, and cell-fate decisions encompassing apoptosis and ferroptosis. We further discuss how PTM-driven metabolic and redox adaptation influences post-irradiation signaling, and how PTMs modulate anti-tumor immunity by affecting immunogenic cell death, antigen presentation, cytokine networks, and immune checkpoint regulation within the tumor microenvironment. In addition, we summarize emerging evidence for reciprocal crosstalk between PTM enzymes and non-coding RNAs, which can act as upstream regulators, scaffolds, or effectors to reinforce context-specific modification patterns and therapeutic vulnerabilities. Viewing radioresponse through a PTM-network lens reveals actionable nodes for radiosensitization and radioprotection. Targeting PTM writers, erasers, and readers, alone or in rational combinations with radiotherapy, DNA damage response inhibitors, epigenetic agents, and immunotherapy, may overcome resistance while improving the therapeutic window. Future efforts should prioritize context-specific biomarkers, on-target toxicity management, and mechanism-informed trial designs to translate PTM-guided strategies into clinically meaningful gains.

Kupffer cells (KCs) make up the predominant population of resident innate immune cells in the liver, serving as key immune sentinels that maintain local immune surveillance and immunoregulatory homeostasis. However, their functional involvement and phenotypic dynamics during radiation-induced liver damage (RILD) remain insufficiently explored. Therefore, we established a mouse model of RILD and, through systematic single-cell-level profiling of hepatic immune cell populations, found that KCs play a critical role in hepatic immune responses and undergo a pronounced radiation-induced shift toward a pro-inflammatory M1 phenotype. Further KC depletion/reconstitution, molecular assays, and coculture experiments consistently demonstrated that M1-polarized KCs exacerbate liver damage, with secretory leukocyte protease inhibitor (SLPI) being identified as a key molecular mediator driving this polarization and its pathogenic effects. To further substantiate these findings, we designed a liposome-based delivery strategy to selectively inhibit SLPI in KCs, which effectively suppressed M1 polarization and alleviated radiation-induced liver damage, underscoring the therapeutic relevance and translational potential of this approach in RILD. Overall, these findings demonstrate that radiation drives KCs toward an SLPI-dependent pro-inflammatory M1 state, thereby exacerbating liver injury. Moreover, targeted liposomal suppression of SLPI effectively reverses this polarization and protects against RILD, highlighting SLPI-modulated KC reprogramming as a promising therapeutic approach.

An orchestra of molecular mechanisms endows radiation-resistant extremophiles with extraordinary survival capabilities under extreme ionizing radiation. This review systematically explores the arsenal of key molecular strategies underpinning extreme radioresistance, including efficient DNA damage response and repair pathways, robust reactive oxygen species (ROS) scavenging systems, specialized protective proteins (e.g., Dsup, PprI), and coordinated regulatory networks. This review extensively examines species-specific adaptations in a diverse range of radioresistant organisms, such as Deinococcus radiodurans, archaea, lichens, bdelloid rotifers, Drosophila melanogaster, cockroaches, Caenorhabditis elegans, and tardigrades. Despite the conservation of core mechanisms such as DNA repair machinery, significant interspecies variations exist in antioxidant defense systems and cellular structure remodeling strategies. Based on the available data, this review further conducts an analysis of convergent vs. divergent evolution and quantitative efficiency metrics across species. Finally, translational applications of these mechanisms in radiobiology, medicine and space science are discussed, with future research directions highlighted that aim to exploit these natural radioprotective systems for technological and therapeutic innovations.

BACKGROUND:Radiotherapy (RT) provides meaningful local control for hepatocellular carcinoma (HCC) but is limited by radio-resistance. Preclinical and clinical data suggest that adding programmed death receptor-1 (PD-1) blockade may enhance radiosensitivity in various malignancies. We compared outcomes of stereotactic body radiotherapy (SBRT) plus PD-1 inhibitors vs SBRT alone in unresectable HCC. METHODS:We retrospectively analyzed consecutive patients treated with SBRT (January 2019-December 2024) from 3 centers. Key exclusions removed confounding from recent systemic/locoregional therapies. Propensity score matching (PSM, 1:1) balanced demographics, liver function, tumor characteristics, and prior therapy. Tumor responses were assessed by RECIST 1.1, while survival was estimated by Kaplan-Meier and Cox models. RESULTS:Of 540 eligible patients, 157 received RT+PD-1 and 383 received RT alone; after PSM, 314 patients remained (157/157). Median follow-up was 29.9 months (IQR 21-36). After matching, RT+PD-1 showed a higher objective response rate (ORR) that approached significance (48.4% vs 37.6%, P = .053). Progression-free survival (PFS) was significantly prolonged with RT+PD-1 (median 11.0 vs 8.5 months; 1-year 69.9% vs 54.1%; HR 0.75, 95% CI 0.58-0.96, P = .024). OS also favored RT+PD-1 (median 33.9 vs 26.3 months; 3-year 41.9% vs 23.0%; HR 0.74, 95% CI 0.54-1.02, P = .066). On multivariable analysis after PSM, RT+PD-1 independently reduced risks of progression (HR 0.69, P = .005) and death (HR 0.70, P = .029). Adverse events (AEs) were similar overall, but grade ≥3 AEs were more frequent with RT+PD-1 (15.2% vs 7.0%, P = .020). CONCLUSIONS:In unresectable HCC, adding PD-1 blockade to SBRT enhances anti-tumor activity and improves long-term survival outcomes.

Radioresistance in esophageal squamous cell carcinoma limits the benefit of radiotherapy. The role of N6 methyladenosine readers in this phenotype remains incompletely defined. We identify a YTHDF2 centered mechanism that links RNA modification to organelle redox control. Analyses of public transcriptomes and an immunohistochemistry cohort showed that higher YTHDF2 expression associates with unfavorable outcomes after radiotherapy, and ionizing radiation transiently increases YTHDF2 in cell models. Loss of YTHDF2 sensitized esophageal squamous cell carcinoma cells to irradiation, with more apoptosis, DNA damage, reactive oxygen species, and reduced clonogenic survival. YTHDF2 overexpression conferred protection in vitro and preserved tumor growth in xenografts after irradiation. Integrated MeRIP-seq and MeRIP-qPCR, together with reporter assays, indicated that YTHDF2 recognizes an m6A-modified site within the DHRS3 3' untranslated region and is required to maintain DHRS3 protein expression after irradiation. DHRS3 depletion phenocopied radiosensitization, elevated reactive oxygen species, and disrupted redox balance with altered NADP+ to nicotinamide adenine dinucleotide phosphate (NADPH) ratios, and abrogated the radioprotective effects of YTHDF2 overexpression. Spatial imaging and perturbation analyses suggested that lecithin retinol acyltransferase (LRAT) enriches DHRS3 at endoplasmic-reticulum-lipid-droplet regions juxtaposed to mitochondria after irradiation. LRAT loss dispersed these interfaces, mislocalized DHRS3, and impaired retinoid and NADPH buffering, whereas enforced mitochondrial targeting of DHRS3 partially restored redox control. Collectively, these findings support a model in which an irradiation-responsive YTHDF2-DHRS3-LRAT axis assembles a retinoid-coupled NADPH module at endoplasmic reticulum (ER)-lipid-droplet (LD)-mitochondria interfaces to limit oxidative stress and contribute to radioresistance. Mechanistic experiments illustrate how this pathway buffers irradiation-induced oxidative stress across transcriptomic, biochemical, and imaging readouts, suggesting that targeting YTHDF2 or the DHRS3-LRAT node may offer a tractable strategy to improve radiotherapy in esophageal squamous cell carcinoma.

Radiation-induced lung injury (RILI) is a life-threatening complication of thoracic radiation therapy for malignancies. It poses 2 challenges in clinical management: the progression from acute radiation pneumonitis to irreversible pulmonary fibrosis and the limitations of current therapies, such as glucocorticoids and antifibrotic drugs, because of efficacy constraints and adverse effects. Recent studies have revealed that pulmonary macrophages form a spatiotemporally regulated inflammatory-fibrotic coupling network through phenotypic switching. Specifically, alveolar macrophages exhibit M1 proinflammatory polarization during the acute phase, whereas interstitial macrophages transition to M2 profibrotic phenotypes in the chronic phase. This biphasic alveolar macrophages/interstitial macrophages regulatory mechanism provides critical insights for the selection of therapeutic targets. Using this information, drug delivery systems based on nanotechnology-with surface modifications for targeting and drug release-have the potential to change macrophages and related signals in the body, overcoming current treatment limits. This review methodically elucidates recent breakthroughs in radiation-induced lung injury molecular mechanisms and highlights advances in nanomedicine-driven cell-targeted therapies, to provide theoretical foundations for developing multimodal precision intervention strategies.

Gut microbiota have been associated with C-reactive protein (CRP) levels and colorectal cancer (CRC), but their causal relationships in humans remain unclear. We performed Mendelian randomization (MR) analyses to investigate causal relationships among gut microbiota, CRP, and CRC using genome-wide association studies (GWAS) summary data. The inverse variance weighted method was prespecified as the primary estimator, with complementary MR methods and sensitivity analyses used to assess robustness. Multiple-testing correction was applied across 209 gut microbial taxa. External validation and targeted replication were conducted using independent CRC GWAS datasets. An exploratory prerequisite-based analysis evaluated whether CRP might represent a potential inflammatory pathway linking CRC-associated gut microbial taxa to CRC. Five gut microbial taxa showed nominal associations with CRC. Genus Eubacterium brachy group id.11296 (odds ratio [OR] = 1.13, 95% confidence intervals [CI] = 1.04-1.22, P = .002) and genus Ruminococcaceae UCG004 id.11362 (OR = 1.15, 95% CI = 1.03-1.29, P = .016) were positively associated with CRC risk. Family Enterobacteriaceae id.3469 (OR = 0.83, 95% CI = 0.69-1.00, P = .048), genus Oscillibacter id.2063 (OR = 0.88, 95% CI = 0.77-1.00, P = .045), and order Enterobacteriales id.3468 (OR = 0.83, 95% CI = 0.69-1.00, P = .048) showed inverse associations. However, none survived Bonferroni or Benjamini-Hochberg false discovery rate correction. Targeted replication provided partial support in BioBank Japan, with 3 taxa showing nominal replication, whereas no nominal replication was observed in FinnGen. For CRP, the weighted median method suggested a nominal inverse association with CRC risk, but this was not supported by the primary inverse variance weighting analysis or other complementary methods. The exploratory pathway analysis did not support CRP as a mediator linking the identified microbial taxa to CRC. This MR study identified 5 gut microbial taxa showing nominal associations with CRC risk, but these findings did not survive multiple-testing correction and should be interpreted as suggestive. Current evidence did not support a robust direct causal effect of CRP on CRC or a CRP-mediated microbiota-CRC pathway. Larger ancestry-matched GWAS datasets, strain-resolved microbiome analyses, and experimental studies are needed.

Phase space files can store the particle information in one or more planes of radiation particles simulated by the Monte Carlo (MC) method. The secondary calculation method based on phase space files is commonly used to improve the efficiency of MC simulations. However, it is still unclear whether phase space files are applicable for microdosimetric evaluations. In this study, voxel-type and mesh-type monolayer cell population models of different sizes were constructed, and phase space files of secondary electrons generated by photons with different initial energies were obtained using the MC software - PHITS. The overall average dose caused by the secondary electron phase space files in the region of interest and their microdosimetric distribution within cells were calculated and compared with the results caused by the initial photons under the same geometric conditions. The results showed that the adoption of secondary electron phase space files had almost no impact on the evaluation of macroscopic average dose, with deviations lower than 3% compared to the overall dose caused by the initial photons in the Petri dish. For microdosimetric distributions of the voxel-type model and the two different morphologies of mesh-type cell models, with a macroscopic accumulated dose of 1 mGy, the relative deviation of the cell dose distribution generated by the initial photons and the phase space files was below 10% and the total computation time of phase space files was below 2% of initial photon's. For accumulated doses of 10, 50, and 100 mGy, the relative deviation of the cell nucleus specific energy obtained by secondary electrons and initial photons was greater than 10%. As the size of the culture dish increased, the differences in cell dose distributions also increased, with the root mean square error (RMSE) and coefficient of variation (Cv) of dose distributions both exceeding 30%. In conclusion, this study assessed the effectiveness of the secondary calculation method utilizing phase space files for dose evaluation at the cellular scale. This research offers essential technical support and theoretical foundations for the utilization of this approach in microdosimetric investigations at the cellular level.

Radiation-associated hematopoietic recovery (RAHR) is critical for mitigating lethal complications of acute radiation syndrome (ARS), yet therapeutic strategies remain limited. Through integrated multi-omics analysis of a total body irradiation (TBI) mouse model, we identify Bacteroides acidifaciens-dominated gut microbiota as key mediators of RAHR impairment. 16S ribosomal rRNA sequencing revealed TBI-induced dysbiosis characterized by Bacteroidaceae enrichment, while functional metagenomics identified raffinose metabolism as the most significantly perturbed pathway. Notably, raffinose supplementation (10% w/v) recapitulated radiation-induced microbiota shifts and delayed bone marrow recovery. Fecal microbiota transplantation (FMT) revealed a causative role for raffinose-metabolizing microbiota, particularly Bacteroides acidifaciens, in delaying RAHR progression. Mechanistically, B. acidifaciens-mediated bile acid deconjugation activated FXR, subsequently suppressing NF-κB-dependent hematopoietic recovery. Therapeutic FXR inhibition via ursodeoxycholic acid (UDCA) had been shown to be a viable method for rescuing RAHR. Our results delineated a microbiome-bile acid-FXR axis as a master regulator of post-irradiation hematopoiesis. Targeting B. acidifaciens or its metabolic derivatives could represent a translatable strategy to mitigate radiation-induced hematopoietic injury.

This study aimed to assess the clinical utility of deep hyperthermia in elderly patients with esophageal cancer(EC) who underwent intensity-modulated radiotherapy(IMRT). This retrospective analysis included 177 elderly patients with EC who underwent IMRT between 2017 and 2023, 42 of whom had combined deep hyperthermia (HT). Propensity score matching (PSM) was used to balance the covariates between the thermoradiotherapy (HTRT) group and IMRT-alone groups. Treatment outcomes and toxicities were compared between the two groups. We used the Kaplan-Meier method to estimate survival curves and the log-rank test to compare survival curves. Cox multivariate analysis was performed to analyze the prognostic factors in these patients. After PSM (42 patients in each group), the HTRT group had a greater objective response rate (ORR) than the IMRT-alone group (83

Radiotherapy (RT) is a promising treatment for hepatocellular carcinoma (HCC), but resistance limits its efficacy. This study reveals that Rac family small GTPase 1 (RAC1) is overexpressed in radioresistant HCC patients and promotes resistance by directly phosphorylating pyruvate kinase M2 (PKM2) and fructose-1,6-bisphosphatase 1 (FBP1), leading to enhanced glycolytic flux. Introducing mutations in PKM2 (S172A) and FBP1 (T309A) effectively inhibits tumor growth. Additionally, combining RT with the US Food and Drug Administration-approved drug foscarnet sodium, which inhibits RAC1 activity, significantly improves therapeutic outcomes in vivo. These findings identify RAC1 as a key regulator of radioresistance and a potential therapeutic target in HCC.

Hormone receptor-positive breast cancer is characterized by the expression of estrogen receptor (ER) or progesterone receptor (PR), it is generally associated with less aggressive clinical features and more favorable prognostic outcomes, primarily due to the effectiveness of endocrine therapy. However, the loss of PR expression has been correlated with endocrine resistance and poorer prognosis. To date, there is limited research elucidating the underlying mechanisms distinguishing ER-positive/PR-positive from ER-positive/PR-negative breast cancer. This study aims to investigate the molecular mechanisms associated with these two subtypes and to propose recommendations for precision therapy. Fresh tumor tissues from ER + /PR + patients (n = 5) and ER + /PR- patients (n = 5) were subjected to proteomic analysis to identify differentially expressed proteins. Transcriptomic data were obtained from the TCGA database, encompassing 937 breast cancer patients divided into three subgroups: ER + /PR + (n = 627), ER + /PR- (n = 112), and ER-/PR- (n = 198). Clinical characteristics and prognostic data were collected to analyze disease-specific survival (DSS) and overall survival (OS) across the three subtypes. Differential expression data for both transcripts and proteins were extracted, and Cox regression along with Least Absolute Shrinkage and Selection Operator (LASSO) regression were applied to identify key regulatory genes. A risk scoring formula was employed to classify patients into high-risk and low-risk groups. Kaplan–Meier curves, Gene Set Enrichment Analysis (GSEA), immune cell infiltration analysis, and OncoPredict drug sensitivity predictions were conducted to provide insights into the underlying mechanisms and clinical treatment strategies for this patient cohort. The accuracy of this model was further validated using external GEO datasets (GSE21653, GSE20685, and GSE42568). Additionally, we collected data from 97 hormone receptor-positive breast cancer patients who underwent neoadjuvant chemotherapy at our center between January 2021 and December 2023, assessing their response to chemotherapy using the Miller-Payne score. In the TCGA database, patients with ER + /PR- breast cancer exhibited poorer 5-year DSS and OS compared to those with ER + /PR + status (DSS: P = 0.038; OS: P = 0.052), which was similar to those with ER-/PR- status (DSS: P = 0.47; OS: P = 0.77). 186 differentially expressed proteins (110 up-regulated and 76 down-regulated) were identified based on proteomic analysis. After COX regression and Lasso regression, five key differential genes with prognostic and diagnostic value of ER + /PR + and ER + /PR- patients were finally included, that is HPN, FSCN1, FGD3, LRIG1, and TBC1D7. HPN, FSCN1 and FGD3 can be regarded as a tumor suppressor gene. And LRIG1, and TBC1D7 can be regarded as a risk-associated gene. Patients with high-risk scores had significantly lower survival probabilities compared to those with low-risk scores. Additionally, there were differences in functional pathway enrichment analysis (galactose_metabolism, glycolysis_gluconeogenesis, jak_stat_signaling_pathway, pentose_phosphate_pathway, et al.) and immune cell infiltration (CD8 T cell, Macrophages M1, et al.) between the high-risk and low-risk groups. Drug sensitivity analysis indicated that the low-risk patients may be more sensitive to endocrine drug like fulvestrant, while high-risk patients may be more sensitive to chemotherapy drugs like docetaxel, paclitaxel, and vinorelbine. Of the 97 patients underwent neoadjuvant chemotherapy in our center, the proportion of patients achieving Miller-Payne (MP) score 4 and 5 was higher in ER + /PR- patients (44

BackgroundLung cancer is the leading cause of cancer-related death in the worldwide. Although cisplatin and other platinum-based drugs are widely used as radiosensitizers in radiotherapy and considered the first-line treatment for advanced lung cancer, their clinical utility is often limited by drug resistance and severe cytotoxic side effects. In recent years, iridium-based complexes and other transition metal cation complexes with similar structural properties have garnered increasing research interest due to their potential anticancer properties.MethodsRecently, we synthesized a novel iridium (III) complex (Ir-1) and evaluated its safety and stability. The present study aimed to identify Ir-1 with potent anticancer activity by assessing its cytotoxic effects on lung cancer cells in vitro. Additionally, it investigated Ir-1's radiosensitizing efficacy and the underlying mechanisms.ResultsThe results demonstrated that Ir-1 exhibited significant radiosensitizing effects on lung cancer cells. Ir-1 effectively reduced cell viability and colony formation, arrested the cell cycle at the G2/M phase, inhibited cell migration and invasion, decreased mitochondrial membrane potential, and increased reactive oxygen species (ROS) generation in lung cancer cells. Importantly, these cytotoxic effects were selective, with minimal impact on normal cells. Mechanistic studies showed that Ir-1 enhanced radiation-induced cancer cell death by disrupting mitochondrial function and activating the mitochondrial apoptotic pathway. This was evidenced by upregulated expression levels of Bax, Cytochrome c (Cyt-C), and Caspase9 proteins, along with reduced level of Bcl-2 protein. Notably, the addition of a Cyt-C inhibitor significantly reduced the expression of Cyt-C and Caspase9 proteins. Similarly, treatment with the Caspase9 inhibitor Z-LEHD-FMK also reduced Caspase9 protein level.ConclusionThis study provides robust evidence that Ir-1 is a promising and safe radiosensitizer for lung cancer therapy. Its ability to enhance radiation-induced cytotoxicity through mitochondrial dysfunction and activation of apoptotic pathways highlights its potential for clinical application.