American journal of cancer research最新文献

This study retrospectively analyzed trends in smoking-attributable lung cancer burden among Chinese adults aged 65 years and above from 1990 to 2021 and projected future trends from 2021 to 2050. Data on deaths and disability-adjusted life years (DALYs) were extracted from the Global Burden of Disease Study (GBD 2021). Statistical analysis was performed using R software (4.1.3) to estimate estimated annual percentage changes (EAPC) in disease burden trends. A Bayesian age-period-cohort (BAPC) model was applied to forecast smoking-attributable lung cancer burden from 2021 to 2050. From 1990 to 2021, the burden of lung cancer attributable to smoking among older adults in China showed an upward trend, in contrast to the global decline. The DALY rate increased from 2,948.7 to 3,384.46 per 100,000 population (EAPC = 0.62%, 95% CI: 0.4%, 0.85%), while the mortality rate rose from 150.12 to 186.36 per 100,000 population (EAPC = 0.93%, 95% CI: 0.67%, 1.19%). Both DALY and mortality rates increased across all age groups (65-69, 70-74, 75-79, 80-84, and ≥85 years), with males exhibiting significantly higher burden levels and growth rates than females. Projections indicate that between 2021 and 2050, both the absolute number of DALYs and deaths from smoking-attributable lung cancer in this population will continue to rise, and their share of the total national burden will progressively increase. In conclusion, the smoking-attributable lung cancer burden among elderly Chinese adults has risen continuously since 1990 and is expected to grow further. Strengthened tobacco control policies, targeted public health interventions, and enhanced early screening among high-risk groups, including the elderly and women, are urgently needed to mitigate this growing burden.

Objective: To assess the diagnostic performance of serum prostate-specific antigen (PSA), the Prostate Health Index (PHI), and peripheral blood inflammatory markers (neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), neutrophil-apolipoprotein A1 ratio (NAR) apolipoprotein A1 (ApoA1)) in differentiating prostate cancer (PCa) from biopsy-negative benign prostatic hyperplasia (BPH), and to construct an optimized machine learning diagnostic model.

Methods: A retrospective analysis was conducted on 701 patients referred for prostate biopsy between March 2018 and January 2024, including 421 PCa and 280 BPH cases. Patients were divided into training (60%; n=421), validation (20%; n=140), and test (20%; n=140) cohorts. LASSO regression identified key predictors, which were used to develop five machine learning models-logistic regression, decision tree, random forest, support vector machine, and XGBoost. model performance was evaluated using ROC and precision-recall curves, calibration plots, Brier Scores, and decision curve analysis (DCA). AUCs were compared using the DeLong test.

Results: PCa patients exhibited higher PSA, Neu, MONO, NLR, NAR, and PHI but lower ApoA1 and LMR than BPH patients (all P<0.05). XGBoost achieved the best performance (AUC: training 0.994; validation 0.953; test 0.979), significantly surpassing PSA (AUC difference: 0.055-0.118, P<0.001) and PHI (AUC difference: 0.077-0.084, P<0.007). Calibration curves indicated low Brier Scores (0.0326-0.0751) and excellent model fit. DCA confirmed superior clinical benefit. NLR and NAR were major contributors to PCa risk prediction.

Conclusions: The XGBoost model integrating NLR, LMR, and NAR demonstrates superior diagnostic accuracy and clinical utility compared with PSA and PHI, potentially improving pre-biopsy risk stratification and reducing unnecessary invasive procedures.

Objectives: To develop and validate a Cox regression-based nomogram model for predicting recurrence risk in early-stage endometrial cancer.

Methods: We retrospectively analyzed 1,540 patients with FIGO stage I-II disease treated between January 2013 and December 2021, of whom 247 (16.04%) experienced recurrence and 1,293 did not. Key predictive factors were identified using Lasso-Cox regression, and a nomogram was constructed and evaluated in training (n=924), validation (n=308), and testing (n=308) cohorts.

Results: The model demonstrated strong discriminative ability, with C-index values of 0.748, 0.684, and 0.677, and AUCs of 0.767, 0.701, and 0.694 across the three cohorts. Compared with the traditional Naples Prognostic Score, the nomogram showed significantly better performance in both the training cohort (AUC 0.767 vs. 0.687, P=0.009) and the validation cohort (AUC 0.701 vs. 0.580, P=0.041). Calibration curves showed good agreement between predicted and observed outcomes, and decision curve analysis confirmed substantial net clinical benefit, with net reclassification improvement supporting superior accuracy.

Conclusions: The developed nomogram provides a reliable and effective tool for individualized recurrence risk assessment in early-stage endometrial cancer, demonstrating significant clinical potential for improved risk prediction and treatment planning.

Background: Limb-salvage surgery is the preferred treatment for primary bone tumors, yet postoperative imaging and functional outcomes remain variable. This study aims to identify factors affecting postoperative imaging and functional recovery outcomes in patients undergoing limb-salvage surgery for primary bone tumors.

Methods: A retrospective case-control study was conducted on 231 adult patients with primary bone tumors who underwent limb-salvage surgery at a single institution between January 2016 and January 2024. Patients were categorized into favorable and adverse outcome groups based on postoperative imaging, local recurrence, and Musculoskeletal Tumor Society scores. Data were collected on demographics, tumor characteristics, surgical methods, nutritional status, adjuvant treatments, supportive care, and complications. Univariate and multivariate logistic regression analyses were performed to identify factors independently associated with favorable outcomes.

Results: Significant differences were found between outcome groups in age, lymphocyte count, preoperative chemotherapy, tumor margin clarity, tumor size, resection method, adjuvant treatment, rehabilitation, and infection rates. Patients with favorable outcomes were younger, had higher lymphocyte counts and albumin levels, received more preoperative chemotherapy and adjuvant treatments, displayed clearer tumor margins, underwent wide resection more often, had smaller tumors, and participated more in rehabilitation. The adverse group had higher rates of infection and marginal resections. No significant differences were observed in tumor type, location, reconstruction method, prealbumin and hemoglobin levels, or rates of pain management, psychological support, delayed wound healing, joint stiffness, or muscle atrophy. Multivariate analysis identified younger age, wide resection, and adjuvant treatment as independent predictors of favorable imaging and functional recovery.

Conclusion: Younger age, wide surgical resection, and receipt of adjuvant treatment independently predict improved postoperative imaging and functional outcomes following limb-salvage surgery for primary bone tumors. Optimizing perioperative management and surgical strategies may enhance patient recovery and long-term outcomes.

Tumor drug resistance is a major factor in cancer treatment failure. SLC7A11 is characterized as a light-chain subunit antiporter of the Xc^- system, responsible for exchanging extracellular cystine with intracellular glutamate. SLC7A11 has been shown to critically modulate tumor progression through regulation of intracellular cysteine homeostasis and redox balance, thereby governing ferroptosis and disulfidptosis. Ferroptosis and disulfidptosis are closely associated with tumor drug resistance, and SLC7A11 demonstrates a dual regulatory role in this process. This review summarized the structure and function of SLC7A11 and the mechanisms underlying tumor drug resistance. It then analyzed the potential regulatory effects of SLC7A11 on ferroptosis, disulfidptosis, and autophagy in the context of tumor chemotherapy, targeted therapy, immunotherapy resistance, and prognosis. Finally, this review delineated the therapeutic opportunities and translational challenges in targeting SLC7A11 to overcome tumor drug resistance, serving as a foundation for future mechanistic exploration and clinical development.

[This corrects the article on p. 1922 in vol. 9, PMID: 31598395.].

[This corrects the article on p. 4141 in vol. 11, PMID: 34659881.].

[This corrects the article on p. 275 in vol. 7, PMID: 28337376.].

Disulfidptosis is a novel Nicotinamide Adenine Dinucleotide Phosphate (NADPH) deficiency-driven cell death pathway characterized by cystine overload and aberrant disulfide bond formation in actin cytoskeletal proteins, distinct from apoptosis, ferroptosis, and other programmed cell death modalities. In gynecological tumors (ovarian, cervical, and endometrial cancers), this process is orchestrated by dysregulated SLC7A11 expression, impaired thioredoxin system function, and Rac-WRC-Arp2/3-mediated actin network collapse. Bioinformatic analyses of The Cancer Genome Atlas (TCGA)/Gene Expression Omnibus (GEO) datasets have revealed that disulfidptosis-related genes (e.g., SLC7A11, GYS1, NCKAP1) and lncRNAs (e.g., PRDX6-AS1, EMSLR) correlate with patient prognosis, chemoresistance, and tumor immune microenvironment (TME) remodeling. Therapeutic strategies to induce disulfidptosis include glucose deprivation to limit NADPH supply, inhibition of NADPH-generating enzymes (e.g., G6PD inhibition), and nanodelivery systems (e.g., FeOOH@Fe-Ap@Au) that synchronize disulfidptosis with ferroptosis. Preliminary evidence proposes that disulfidptosis inducers may synergize with immune checkpoint inhibitors (ICIs) through TME modulation, though experimental validation remains ongoing. Beyond malignancies, disulfidptosis-related pathways have been implicated in endometriosis, where disulfidptosis-related genes (DRGs; e.g., PDLIM1, ACTB) regulate ectopic lesion progression via immune-metabolic crosstalk. This review comprehensively summarizes the molecular mechanisms, disease associations, and translational potential of disulfidptosis in gynecological disorders, proposing targeted therapeutic paradigms and future research directions.

The oxidative modification of proteins induced by hydrogen peroxide (H₂O₂) results in the formation of disulfide bond between two cysteines and affects protein conformation and biological function. Transcription factor FOXM1 participates in the development and progression of cancers and its levels are upregulated by the oxidative stress of H₂O₂-treated condition. In this study, we found that Peroxiredoxin-1 (PRDX1), one of the most H₂O₂-reactive antioxidant enzymes, interacted with FOXM1 and led to its oxidation under H₂O₂ stimulation through generating an intermolecular disulfide bond with FOXM1 C539, which was subsequently transferred to form an intramolecular disulfide bond between C167 and C175 in the oxidized FOXM1. The PRDX1-mediated oxidative modification enhanced the protein stability and transcriptional activity of FOXM1, which stimulated the transcription of FOXM1 target gene X-ray cross-complementing protein 1 (XRCC1) and improved the repair of H₂O₂-induced DNA damage in cancer cells. The disruption of PRDX1-mediated FOXM1 oxidation impaired the colony formation ability of cancer cells in vitro and the growth and DNA damage repair ability of cancer cells in vivo. The analysis of The Cancer Genome Atlas (TCGA) breast cancer patient data confirmed that PRDX1 and FOXM1 together facilitated clinical cancer progression. Overall, we established an H₂O₂-PRDX1-FOXM1 oxidation pathway that likely contribute to the development and progression of cancers.