American journal of cancer research最新文献

In Taiwan, approximately half of ovarian cancer cases are diagnosed at an early stage. Although platinum-based adjuvant chemotherapy is recommended for high-risk early-stage epithelial ovarian cancer (EOC), the optimal regimen remains uncertain. Paclitaxel (PTX) is widely used based on evidence from advanced-stage disease, yet data comparing PTX and cyclophosphamide (CTX) in early-stage settings are limited. We retrospectively reviewed medical records of FIGO stage I-II EOC patients with high-risk features who received post-operative platinum-based chemotherapy with either PTX or CTX at Kaohsiung Chang Gung Memorial Hospital from January 2011 to December 2018. We analyzed associations between clinical characteristics, chemotherapy regimen, and survival outcomes. Baseline characteristics were compared using Chi-square tests for categorical variables and independent two-sample t-tests for continuous variables. Survival analysis was conducted using Kaplan-Meier and Cox regression methods. A total of 125 patients were included (mean age: 50.0 years), of whom 27.2%, 48.8%, and 24.0% were diagnosed with FIGO stage IA/IB, IC, and II, respectively. Clear cell (37.6%) and endometrioid (27.2%) carcinomas were the most common histologies. Eighty-one patients (64.8%) received PTX, and 44 (35.2%) received CTX. Multivariate analysis identified FIGO stage as the only independent predictor of disease-free survival (DFS; HR, 3.39; P = 0.046), while the chemotherapy regimen was not significantly associated with DFS (HR 2.58; P = 0.111). Since stage I patients constituted the majority of the cohort, we performed a subgroup analysis restricted to stage I patients, which similarly demonstrated no significant DFS difference between the two chemotherapy regimens (P = 0.377). CTX demonstrated comparable DFS outcomes to PTX in high-risk early-stage EOC. These findings support the use of CTX as a viable adjuvant chemotherapy alternative to PTX, particularly in Asian populations where clear cell and endometrioid histologies are more prevalent.

Anastomotic leakage is one of the most severe postoperative complications following esophagectomy for esophageal carcinoma. This study compared the incidence of postoperative anastomotic leakage after esophagectomy between a novel oblique-to-side esophagogastric anastomosis and the conventional end-to-side esophagogastric anastomosis. Clinical data from 318 patients with esophageal carcinoma (106 cases treated with the new anastomosis and 212 with the conventional approach) who underwent radical esophagectomy between January 2018 and November 2021 were retrospectively collected. Propensity score matching (PSM) was applied to balance baseline characteristics, yielding 188 matched patients (94 in each group). The primary outcome was the incidence of anastomotic leakage, while secondary outcomes included anastomotic stenosis, incisional infection, and pulmonary, cardiovascular, and digestive complications. After PSM, the new anastomosis group showed a significantly lower incidence of anastomotic leakage than the conventional group (6.4% vs. 22.3%, P=0.002). Besides, the incidence of postoperative fever was lower in the new anastomosis (10.6% vs. 27.7%, P=0.003). No significant differences were observed between the groups regarding anastomotic stenosis, incisional infection, or other systemic complications. Multivariate analysis identified the new oblique-to-side esophagogastric anastomosis as an independent protective factor against leak (OR=0.294, P=0.020). In conclusion, the oblique-to-side anastomosis effectively reduces postoperative anastomotic leak after radical esophagectomy without increasing other postoperative complications, demonstrating both safety and clinical efficacy.

Multiple Myeloma (MM) is the second most common hematological malignancy, with its pathogenesis involving complex cytogenetic variations, tumor clonal evolution, and dynamic interactions between tumor cells and bone marrow stromal microenvironment. Recent studies highlight the role of the intestinal microbiota, a key component of the tumor-associated microenvironment, in regulates MM occurrence, progression, and treatment response via the "gut-bone marrow axis". Under physiological conditions, it protects the local microenvironment by regulating host metabolism and maintaining immune homeostasis. However, intestinal dysbiosis causes metabolic disorders and immune surveillance defects, promoting tumor growth, drug resistance, and poor prognosis. Though traditional treatments such as chemotherapy and hematopoietic stem cell transplantation have been optimized, chemotherapy disrupts intestinal mucosal integrity and impairs immunity, significantly increasing post-chemotherapy infections. These infections can interrupt treatment, worsen conditions, and reduce quality of life, leaving MM still intractable. Notably, microbiota-targeted interventions (e.g., probiotics, fecal microbiota transplantation [FMT]) have shown potential to reduce infection risk by restoring microbiota balance and repairing intestinal barriers. These interventions may also exert potential anti-tumor effects through immune microenvironment regulation and alleviate chemo/radiotherapy-related adverse reactions (e.g., nausea, diarrhea), offering a new direction for relapsed/refractory MM. This article summarizes the molecular regulatory network of the intestinal microbiota in the pathogenesis of MM and the research progress of microbiota-based interventions, aiming to provide a foundation for developing novel microbiome-oriented precision treatment regimens and improving chemotherapy tolerance and patient prognosis.

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.].