Cancer Investigation最新文献

Background: Non-small cell lung cancer (NSCLC) treatment often involves a combination of first-line immunotherapy (IO) and chemotherapy, with platinum-based regimens as alternatives. Nivolumab monotherapy is a widely used second-line treatment post-platinum chemotherapy. This is the first study to explore the immunomodulatory effects of cisplatin in advanced NSCLC patients receiving nivolumab.

Methods: This retrospective study included 186 metastatic NSCLC patients from four centers in Turkey. All patients received nivolumab after progression on platinum-based chemotherapy. Multivariate Cox regression was performed to identify independent prognostic factors for progression-free survival (PFS) and overall survival (OS).

Results: Patients treated with cisplatin-based chemotherapy (n = 91) had significantly longer median PFS (7.2 months vs. 4.9 months, p = 0.034) and OS (16.0 months vs. 9.9 months, p = 0.014) compared to those treated with carboplatin (n = 95). Cisplatin-based chemotherapy and ECOG performance status were identified as independent prognostic factors for both PFS and OS.

Conclusion: This study highlights the potential immunomodulatory effects of cisplatin, demonstrating improved survival outcomes in NSCLC patients treated with nivolumab. Specifically, our results reveal cisplatin's unique capacity to modulate the tumor microenvironment, offering a novel avenue for optimizing checkpoint inhibitor therapy. These findings underscore the importance of platinum selection in enhancing immunotherapy efficacy and provide a basis for prospective studies to refine clinical guidelines.

Osteosarcoma is an aggressive bone cancer primarily affecting children and adolescents, with low survival rates in advanced stages. A systematic review and meta-analysis were conducted following PRISMA guidelines to evaluate the impact of ICIs on survival and toxicity in advanced osteosarcoma. ICIs show potential in treating advanced osteosarcoma but are associated with significant toxicity and uncertain survival benefits. Further research is needed to define their role and identify biomarkers for predicting response. Close monitoring for adverse events is essential.

This study investigated the mechanism of action and in vitro efficacy of an anti-hormonal combination drug regimen in treating adult-type granulosa cell tumors of the ovary (AGCT). Using patient-derived and commercial AGCT cell lines, the IC₅₀ values of bicalutamide, anastrozole, and leuprolide acetate were established alone and in combination via cell proliferation assays. Averaged across cell lines, IC₅₀ was determined for bicalutamide (IC₅₀: 7.3 µM) and anastrozole (IC₅₀: 6.2 µM). Minimal effect was seen with leuprolide acetate alone. Suppression of proliferation was increased with the combination of an antiandrogen and an aromatase inhibitor. RNA was extracted from treated and untreated cells. RNA sequencing of cells treated with both anastrozole and darolutamide suggested downregulation of pathways involved in DNA synthesis, cell cycle regulation, and chromosomal organization. MHC I activity and DNA damage response were upregulated. This anti-hormonal drug regimen for AGCT merits prospective investigation.

Acute myeloid leukemia (AML)'s treatment and remission remains unsatisfactory. A prognostic risk-scoring model containing seven signature genes (POU3F1, RPGR, PTP4A3, SOCS1, FAM83G, GREB1 and COL2A1), was developed by LASSO-Cox regression analysis. In the training set, the test group, area under the curve values of 1, 3, and 5 years were 0.876, 0.877, 0.937, and 0.974, 0.878, 0.976 respectively, which indicates a good predictive efficacy. In the two external GEO (GSE71014 and GSE6891) datasets, area under the curve values of 1, 3, 5 years were 0.847, 0.857, 0.822, and 0.830, 0.863, 0.891 respectively. Our seven signature genes containing risk-scoring model performed excellently in evaluating the OS of AML patients.

Given the aggressive symptomatic nature of Cancer of Unknown Primary (CUP) and non-standardized diagnostic approaches, it is expected that the cost of CUP diagnosis is higher than other cancers. This study aims to investigate the diagnostic costs of CUP as compared to other types of metastatic cancer and non-metastatic cancers over a 5-year period in the provincial health authority of Alberta, Canada. Health service utilization (inpatient, outpatient, physician services) and associated costs were compared in the 6-months prior to the diagnostic date, to the baseline period for CUP and non-CUP patients. Costs were estimated using claims amounts paid to physicians and by multiplying the resource intensity weight with the cost per standard hospital stay in Alberta. Diagnostics for CUP cost $9005 per-patient, which were 1.8x more costly than other metastatic cancers ($5027). These higher costs were driven by a large proportion of patients being diagnosed in hospital. Our findings revealed that the per-patient cost of a CUP hospital diagnosis ($13,925) was 10x that of a CUP community diagnosis ($1225) and community diagnosis of a stage IV cancer ($1426). Potential benefits exist in streamlining efforts to diagnose early, improve patient health outcomes, and reduce overall system costs of diagnosing CUP.

The BK polyomavirus (BKPyV), a ubiquitous human pathogen, has garnered significant attention for its potential oncogenic role, particularly in immunocompromised populations such as transplant recipients. This review synthesizes current evidence on the molecular mechanisms underlying BKPyV-associated carcinogenesis, with a focus on the viral Large T antigen (LT-Ag). LT-Ag drives oncogenic transformation primarily by inactivating tumor suppressor proteins p53 and pRb, disrupting cell cycle regulation, and inhibiting apoptosis. Additionally, it dysregulates critical signaling pathways, including Wnt/β-catenin, PI3K/Akt/mTOR, Ras/Raf/MAPK, and STAT-3, which collectively promote uncontrolled proliferation, survival, and genomic instability. A hallmark of BKPyV's oncogenicity is its capacity to integrate into the host genome, often near tumor suppressor loci, further amplifying chromosomal damage. Clinically, BKPyV has been implicated in urothelial carcinoma, renal cell carcinoma, and prostate cancer, with viral DNA and LT-Ag detected in 20-50% of tumor specimens from kidney transplant recipients (KTRs). However, epidemiological data remain contentious, as studies in immunocompetent cohorts report inconsistent associations, and viral presence in non-neoplastic tissues complicates causal interpretations. This duality BKPyV as both a latent commensal and a potential oncogenic driver underscores the need for nuanced investigation into host-virus interactions, particularly in the context of immunosuppression. Emerging diagnostic approaches, such as next-generation sequencing to map viral integration sites, and therapeutic strategies targeting LT-Ag-mediated pathways hold promise for early detection and intervention. By bridging molecular insights with clinical observations, this review advocates for longitudinal studies to clarify BKPyV's role in carcinogenesis and to refine management protocols for high-risk populations, ultimately mitigating the burden of virus-associated malignancies.

CHEK2 is a moderate-penetrance tumor suppressor gene primarily linked to hereditary breast cancer, yet growing evidence implicates it in a wider tumor spectrum. Data from underrepresented populations, such as Türkiye, remains limited. We retrospectively analyzed 895 individuals referred for hereditary cancer evaluation between 2019 and 2025 who underwent multigene panel testing. Germline CHEK2 variants were identified using the Hereditary Cancer Solution Kit (Sophia Genetics) and classified per ACMG guidelines. Clinical, tumor, and histopathological data were reviewed. Twenty-four carriers (83.3% female) were detected: 45.8% harbored pathogenic, 41.6% likely pathogenic, and 12.5% variant of uncertain significance. Breast cancer was the most frequent (66.6%), followed by bladder cancer (8.3%), with isolated cases of ovarian, cervical, lung, papillary thyroid cancers, parathyroid adenoma, and thymoma. Missense variants predominated (75%), clustering in the FHA (66.6%) and kinase (33.4%) domains. Recurrent c.470T > C and c.1427C > T variants comprised 41.6% of all cases. Our findings highlight variant- and sex-specific patterns and underscore the relevance of population-based data in refining cancer risk assessment and management of CHEK2 carriers.

Background: Tazemetostat is an oral inhibitor of enhancer of zeste homolog 2 (EZH2) and is used for the treatment of epithelioid sarcoma (ES) and follicular lymphoma (FL). In this study, we investigated the adverse events (AEs) of tazemetostat based on real data from the U.S Food and Drug Administration(FDA) Adverse Event Reporting System (FAERS).

Methods: To quantify the signals of AEs associated with tazemetostat, we employed disproportionality analyze, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms.

Results: A total of 7,133,678 reports of AEs were collected from the FAERS database, of which 1,110 reports were identified with tazemetostat as the "primary suspect (PS)". A total of 32 significant disproportionality preferred terms(PTs) conforming to the four algorithms were simultaneously retained. There were multiple unexpected AEs caused by tazemetostat that were not mentioned in the label yet, including pleural effusion (ROR = 3.84, PRR = 3.83, IC = 3.83, IBGM = 1.94), lymphadenopathy (ROR = 3.88, PRR = 3.88, IC = 3.87, IBGM = 1.95) and taste disorder(ROR = 20.48, PRR = 20.23, IC = 20.16, IBGM = 4.33). Additionally, the majority of tazemetostat-associated AEs occurred within the first month of treatment initiation (n = 126, 49.8%).

Conclusion: Clinicians need to monitor safety for tazemetostat during the first 30 days and pay more attention to new AE signals.

Breast cancer remains a significant global health concern, emphasizing the need for advanced and accurate diagnostic tools. This research paper focuses on the application of a Transfer Learning model for the detection of breast cancer in mammography images. Leveraging the power of deep learning, Transfer Learning enables the utilization of pre-trained models on large datasets, optimizing performance even with limited data availability. The study employs a diverse dataset comprising mammography images from various sources, ensuring a comprehensive representation of breast cancer cases. A Convolutional Neural Network (CNN) architecture, pre-trained on a vast dataset, is fine-tuned using the mammography dataset to harness its feature extraction capabilities for breast cancer detection. This approach allows the model to learn intricate patterns and abnormalities indicative of malignancies. Key steps involve the pre-processing of mammography images to enhance the quality and extraction of relevant features through the Transfer Learning model. The research investigates the model's efficacy in distinguishing between benign and malignant cases, evaluating its accuracy, sensitivity, specificity, and precision. The research proposed EfficientNet B3 with a DenseNet transfer learning model for classifying mammography images into benign or malignant categories. Also, the impact of varying architectures and hyperparameters on the model's performance is explored for optimization. Results demonstrate promising outcomes, with the Transfer Learning model exhibiting a high degree of accuracy in breast cancer detection. The model's ability to generalize across diverse datasets underscores its robustness and potential for real-world clinical applications. Visions gained from this research contribute to the ongoing discourse on the integration of advanced technologies in breast cancer diagnostics. This research signifies a crucial step towards enhancing the accuracy and efficiency of breast cancer detection, emphasizing the potential of Transfer Learning in revolutionizing mammography-based diagnostic approaches. Findings show that the EfficientNet-B3 and DenseNet have loss values ranging between 0.9, while VGG16's loss values are significantly higher, ranging from 7. The findings hold implications for improving early detection, facilitating timely interventions, and ultimately advancing outcomes for individuals at risk of breast cancer.

Esophageal cancer remains a leading cause of cancer-related morbidity and mortality worldwide, with East and South Asia bearing a disproportionate burden. Despite global declines in age-standardized rates, these regions continue to face challenges due to sociodemographic and behavioral factors. Using Global Burden of Disease 2021 data, we analyzed trends in prevalence, incidence, mortality, and Disability-Adjusted Life Years (DALYs) from 1990 to 2021, emphasizing gender disparities and risk factor contributions. East Asia showed notable progress, with China reporting a 33.96% decrease in age-standardized incidence rate (ASIR) and a 45.78% decline in age-standardized mortality rate (ASMR). Korea also demonstrated improvements, whereas Taiwan recorded only a 4.69% reduction in ASIR but a striking 141.62% rise in ASMR. In South Asia, Bangladesh achieved a 32.74% fall in ASIR and Nepal a 19.01% decline, while Pakistan reported increases in both ASIR (+8.47%) and ASMR (+8.52%). Gender analyses revealed higher ASIR and ASMR among men, except in Pakistan where chewing tobacco drove higher female rates. Tobacco use accounted for 53.1% of the burden in South Asia and 55.2% in East Asia, dominated by smoking in East Asia and chewing tobacco in South Asia. These findings highlight the need for gender-sensitive interventions, stronger tobacco control, dietary improvement, and enhanced screening.