AIM:To evaluate associations between psychosocial and sociodemographic factors and perceived barriers to physical activity among hospitalized patients receiving chemotherapy. MATERIALS AND METHODS:This cross-sectional study included 163 patients hospitalized for chemotherapy. Anxiety, depressive symptoms, self-efficacy, and perceived barriers were assessed using validated instruments. Spearman and partial Spearman correlations examined associations between psychosocial variables and perceived barriers, and exploratory analyses examined individual barriers. Multiple linear regression evaluated independent associations with the mean score of the 21-item barrier questionnaire, adjusting for age, sex, body mass index, and self-reported race/color. RESULTS:The most frequently reported barriers were the perception that disease prevented engagement in physical activity, physical limitations, and lack of energy. Overall perceived barriers were positively associated with anxiety and depressive symptoms and inversely associated with self-efficacy. In the multivariable analysis, higher anxiety symptoms, older age, and self-reported Black race/color were independently associated with greater perceived barriers. Depressive symptoms and self-efficacy were not independently associated after adjustment. CONCLUSIONS:Perceived barriers to physical activity were common among hospitalized patients receiving chemotherapy. Anxiety, older age, and self-reported Black race/color were independently associated with greater perceived barriers. These findings highlight the importance of individualized approaches addressing physical and psychosocial barriers during cancer treatment.
Body image dissatisfaction is a significant concern for young adults with cancer (YAC), yet little is known about the views of clinical, allied health, research, and advocacy professionals who support them. This study aimed to understand their perspectives on body image challenges for YAC, and how best to provide support. Individuals working with YAC were recruited internationally via snowball sampling. Online semi-structured qualitative interviews were conducted, and data were analysed using the Framework Method. Thirteen participants were interviewed. Three themes were identified: (1) Constructing meaning around body changes; (2) Engaging with body image support: barriers and facilitators; and (3) Structural constraints and inequities in BI support/care. Participants identified the need for tailored, patient centred care, peer support and better professional training to address BI distress in YAC. Support should be timely, adaptable to individual needs and sustained across the care pathway.
Immune checkpoint inhibitors (ICIs) targeting PD-1, PD-L1, CTLA-4, and LAG-3 have transformed cancer therapy, but resistance limits durable benefit. This integrative review summarizes primary, adaptive, and acquired resistance driven by tumor-intrinsic defects, suppressive tumor microenvironmental programs, and host-related factors. We discuss mechanism-based strategies to overcome resistance, including combination immunotherapy, antiangiogenic treatment, TGF-β targeting, myeloid reprogramming, epigenetic and metabolic interventions, microbiome modulation, and cellular or vaccine-based approaches. The findings support a precision immuno-oncology framework based on composite biomarkers, longitudinal monitoring, and adaptive treatment selection matched to dominant resistance mechanisms.
OBJECTIVE:To evaluate the reliability, validity and responsiveness of the Memorial Symptom Assessment Scale (MSAS) in adult patients undergoing chemotherapy. METHODS:Longitudinal study including 61 patients hospitalised for chemotherapy for gastrointestinal, lung or breast cancer. The MSAS (total score and subscales: psychological symptoms-PSYCH, physical symptoms-PHYS, and global distress-GDI) was administered at three time points: baseline to test convergent validity with Brief Fatigue Inventory-BFI, 24 hours later to test reliability, and 72 hours after the start of chemotherapy to assess responsiveness. RESULTS:The MSAS showed validity with the BFI (PSYCH: r = 0.41, p = 0.001; PHYS: r = 0.44, p < 0.001; GDI: r = 0.52, p < 0.001; total: r = 0.54, p < 0.001). Reliability was substantial (ICC PSYCH = 0.87; PHYS = 0.86; GDI = 0.86; total = 0.82) and measurement error was classified as very good (SEM PSYCH = 0.12; PHYS = 0.30; GDI = 0.23; total = 0.54). The effect size for change over time ranged from small to moderate (d PSYCH = 0.27; PHYS = 0.27; GDI = 0.38; total = 0.58). External responsiveness by ROC curve analysis was absent for PSYCH (0.53), GDI (0.50), PHYS (0.37) and total score (0.62). CONCLUSION:The MSAS demonstrated substantial reliability, adequate validity and limited to moderate responsiveness, supporting its use for the assessment of physical and psychological. However, the MSAS is limited in its ability to detect clinical change over time.
Cardiovascular adverse event (CVAE) profiles across ALK-TKI generations remain incompletely characterized in real-world practice. A retrospective study of 235 ALK-rearranged NSCLC patients receiving first-, second-, or third-generation ALK-TKIs assessed CVAE incidence, severity, timing, management, and impact on progression-free survival (PFS). Sixty patients (25.5%; 95% CI, 20.4-31.5) experienced 72 CVAEs. Bradycardia (12.8%) was most common. Overall CVAE incidence did not differ between first- (26.9%) and second-/third-generation (25.0%) agents. Hypertension was numerically more frequent with later-generation agents (9.5% vs. 1.5%; uncorrected P = 0.047), but this difference did not remain significant after correction for multiple comparisons and should be regarded as exploratory; in agent-level analysis hypertension was most frequent with lorlatinib (35.0%). Median time to onset was 44 days. Thromboembolic events were the most severe category (71.4% grade ≥3) with the lowest resolution rate (57.1%), whereas 87.5% of all CVAEs resolved or improved. CVAE occurrence was not significantly associated with PFS (time-dependent adjusted HR 1.05; 95% CI, 0.74-1.48), a finding robust across fully adjusted and switch-excluded sensitivity models. ALK-TKIs carry a meaningful CVAE burden with generation- and agent-specific profiles. Risk-adapted monitoring aligned with temporal and pharmacological characteristics may improve management without compromising oncologic outcomes.
Personalized cancer care depends on the seamless integration of genetic profiles, medical histories, and continuous patient monitoring to optimize therapeutic outcomes. Current clinical strategies struggle to combine these disparate, highly heterogeneous data streams, frequently resulting in incomplete diagnostic evaluations and suboptimal treatment selections. Factors such as poor cross-platform compatibility, low prediction precision, and the omission of real-time clinical parameters limit the practical deployment of precision medicine. To address these limitations, this study introduces BigCancerNet (BCN), a robust big data framework that merges multi-source information and uses a Graph Neural Network for Cancer Treatment Optimization (GNN-CTO) to accurately forecast individual drug responses and patient survival trajectories. This initiative is driven by the aspiration to boost treatment success, reduce toxic side effects, and permit flexible, patient-centric therapeutic adaptations. The processing pipeline comprises collecting genomic, clinical, and real-time biometric data from numerous repositories, including The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Cancer Dependency Map (DepMap), and hospital Electronic Health Records (EHRs). Data preprocessing applies Deep Embedding Networks (D2EN) to regularize genomic sequences, handle missing values, and standardize clinical features. The Hybrid Multi-Omics Fusion Algorithm (HMOFA) integrates these diverse datasets, harmonizing genomic, clinical, and wearable information while minimizing batch effects. The GNN-CTO model captures complex, nonlinear relationships among mutations, clinical factors, and drug responses, while Real-Time Model Adaptation with Dynamic Feedback Loop (RT-MADFL) continuously updates predictions. Results demonstrate reduced RMSE (0.160-0.245) and MAE (0.110-0.180), high stability with fold accuracy variance below 0.3%, fast training (12-15s per epoch), and prediction metrics exceeding 91%. Future work includes expanding to multi-cancer cohorts and integrating explainable AI to support transparent clinical decision-making.
The present study aims to compare the diagnostic performance of two ultrasound classifications of thyroid nodules: 2015 American Thyroid Association (ATA) guidelines and 2017 American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS). This comparison evaluates the association of these classifications with the Bethesda system regarding the malignancy of thyroid nodules. A total of 166 patients who met the study's inclusion criteria were enrolled. Ultrasound examinations of the thyroid nodules were conducted, along with fine-needle aspiration (FNA) from the thyroid nodules, with subsequent submission to pathology. The mean age of the patients was 49.79 ± 15.61 years, and 84.3% of participants were female. The Bethesda category 2, with a frequency of 55.42%, was the most observed. 78.3% had solid nodules, with 48.2% showing isoechogenicity. The average nodule size was 22.56 ± 11.05 mm. The most frequent ATA and TI-RADS classifications were low (50.6% and 47.6%, respectively). Significant correlations were found between the Bethesda and TI-RADS scores (p < 0.001), the Bethesda and ATA scores (p < 0.001), and the ATA and TI-RADS scores (p < 0.001). The sensitivity of ATA and TI-RADS was 43% and 47%, respectively, with specificities of 98% and 98%. Both classification systems represent valuable tools for assessing thyroid nodule malignancy.
Multiple myeloma (MM) is a hematologic malignancy of monoclonal plasma cells. Black individuals have a higher incidence of MM than other races, and numerous studies have described potential disparities in myeloma care. In this retrospective study, we investigated outcomes of MM within a single academic institution with a dedicated myeloma Center of Excellence in a rural state. Data from a single academic institution's cancer registry was analyzed for patients diagnosed with MM between 2015 and 2024. Demographic, treatment, and outcome data were collected. The association between survival and race was examined using bivariate analyses, a log-rank test, and both univariable and multivariable Cox proportional hazards modeling. No statistically significant differences in 1-, 3-, and 5-year survival rates between the racial groups were observed. Medicaid insurance, higher age at diagnosis, active cancer status, negative family history of cancer, decreased alcohol use, and higher comorbidity burden were found to be significantly associated with increased mortality, independent of race. Our study found that Black patients with MM treated at this single academic institution with a dedicated myeloma center had similar survival rates when compared to White patients. Centralized care and dedicated Centers of Excellence may help mitigate racial disparities in myeloma care.
BACKGROUND:Given the dismal prognosis of metastatic pancreatic ductal adenocarcinoma, oligometastatic disease (OM-PDAC) has emerged as a distinct clinical entity, challenging systemic-only paradigms via advanced multimodal therapies. RECENT FINDINGS:Retrospective data indicate that anatomical burden alone inadequately guides patient selection. Optimal management requires integrating high-quality imaging, liquid biopsies, and molecular profiling to identify biologically favorable disease. Patients achieving durable responses to induction chemotherapy show improved survival following local interventions like conversion surgery, stereotactic radiotherapy, or ablation. CONCLUSION:OM-PDAC management must transition from anatomy-based criteria toward biologically driven, precision multidisciplinary therapy validated by prospective trials.
The elevated incidence of second primary tumors (SPTs) has been reported in certain subtypes of cutaneous T-cell lymphomas (CTCLs) and cutaneous B-cell lymphomas (CBCLs), but remains unclear for overall primary cutaneous lymphomas (PCLs). Using Surveillance, Epidemiology and End Results (SEER) data, we analyzed 20,970 patients with PCLs and evaluated standardized incidence ratios (SIRs) and survival outcomes of SPTs stratified by lymphoma subtype (indolent vs. aggressive). A total of 2,589 SPTs were identified (SIR = 1.40, 95% CI 1.35-1.45), with significantly elevated risks across sex, ethnicity, stage, latency, year of diagnosis, and treatment. Both indolent and aggressive CTCLs were associated with increased SPT risk, with SIRs of 1.27 (1.16-1.39) and 1.38 (1.11-1.69), respectively. Lymphatic and hematopoietic malignancies predominated in indolent CTCLs, along with thyroid cancer, whereas aggressive CTCLs were mainly associated with extranodal non-Hodgkin lymphoma and myeloma. Increased SPT incidence was also observed in indolent and aggressive CBCLs (SIR = 1.49 and 1.38), with indolent CBCLs showing a broad SPT spectrum including lung cancer and cutaneous melanoma. Patients younger than 30 years, with stage I disease or aggressive PCLs, had decreased age-adjusted overall and disease-specific survival, indicating a need for more intensive surveillance.
Background: Clear cell renal cell carcinoma (ccRCC) exhibits extensive immune infiltration, yet the influence of immunological heterogeneity on clinical outcomes remains poorly elucidated. Objectives: Addressing the formidable challenge of metastasis suppression in ccRCC treatment. Methods: Use scRNA-seq analysis and immunofluorescent imaging to categorize B cells into sub-clusters based on distinct gene expression profiles. Results: Identify two significant B cell subpopulations, B cell (HLA-DRA) and B cell (FKBP11); show the upregulation of six genes (DERL3, FKBP11, MZB1, TNFSF13B, MYO9B, and ACAP1) in infiltrating B lymphocytes associated with poor prognosis of ccRCC; find that B cell (HLA-DRA) displays a noteworthy association with ccRCC metastasis and demonstrates relevance to tumor immunity across diverse cancers. Conclusions: The heterogeneity within B-cell subpopulations may substantially contribute to the metastatic potential of clear cell renal cell carcinoma. The findings provide insights into targeted interventions and improved clinical outcomes.
Nasopharyngeal cancer (NPC) is a major health burden in Indonesia, and reliable prognostic biomarkers are needed to guide treatment decisions. This study examined associations between lymphocyte-monocyte ratio (LMR), tumor-infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and 3-year progression-free survival (PFS) in advanced-stage NPC. A retrospective cohort was assembled at a national referral hematology-oncology clinic, including patients diagnosed from January 2015 to 2020. TIL and TAM expression were assessed by immunohistochemistry, and cutoffs for LMR, CD8, and CD163 were derived using receiver operating characteristic analysis. Kaplan-Meier methods with log-rank testing and Cox proportional hazards regression (univariable and multivariable) were applied. Median 3-year PFS was 24 months (95% CI: 19.44-25.04), with 46.7% event-free at 3 years. High LMR (>1.82) and high CD8+ TIL (>47.5%) were associated with higher 3-year PFS (56.3% and 59.3%) than low groups (31.7% and 30.4%). High CD163+ TAM (≥196) was associated with worse 3-year PFS (9.1% vs 73.8%; p < 0.001). In multivariable models, associations remained significant: LMR aHR 1.844 (p = 0.026), CD8 aHR 2.222 (p = 0.008), and CD163 aHR 5.680 (p < 0.0001). After adjustment for age, ECOG, body mass index, treatment type, sex, and stage (CD163 model), effect estimates were consistent with univariable findings. These biomarkers may aid risk stratification in advanced NPC.
The treatment landscape for multiple myeloma (MM) has evolved significantly over the years; however, the disease remains incurable. Heavily pretreated patients with refractory disease to anti-CD38 therapies, proteasome inhibitors (PIs), and immunomodulatory drugs (IMiDs) face a very poor prognosis. Bispecific antibodies (BsAbs) are the newest, and most promising available therapy for heavily pretreated patients with relapsed refractory multiple myeloma (RRMM). BsAbs primarily rely on T cell activation to target cancer cells by binding malignant plasma cells to cytotoxic T cells via surface antigens. BsAbs consist of two binding sites: one that targets a specific antigen on the surface of MM cells, such as B-cell maturation antigen (BCMA), G-protein-coupled receptor class C group 5 member D (GPRC5D), or fragment crystallizable receptor-like 5 (FcRH5), and another that binds to CD3, a T-cell receptor. Ongoing research aimed at optimizing sequencing strategies, mitigating toxicity, and evaluating combination approaches will be critical to maximizing the durability of response and improving long-term outcomes in this high-risk population.
Anti-tumor agent, docetaxel (DTX), was incorporated into novel pre-synthesized pH-triggered folate-targeted polymeric micelles to overcome insufficient drug accumulation at the tumor site and to reduce side effects in healthy tissues. Tumor growth inhibition rate (87.8%), elimination half-life (7.15 h), and tumor targeting efficiency (74.3%) for the targeted micellar formulation were significantly improved compared to those of free DTX (52.14%, 4.98 h, and 52.92% respectively). Overall, the findings of the current study showed that folate-targeted micelle is a potential targeting drug delivery system improving the efficacy of anticancer drugs through selective targeting of tumor tissues.
BACKGROUND:Some breast cancer patients experience the devastating effects of brain metastases. The metastasis-associated fibroblasts (MAFs), the most abundant cells in the metastatic microenvironment, have an important role in chemoresistance. The MAFs' roles in paclitaxel resistance of brain metastatic tumor cells were evaluated in metastatic organoids. METHODS:Brain metastatic cells, known as 4T1B, were isolated and expanded from the brains of cancerous mice. Alginate-based metastatic organoids were prepared from the culture of 4T1B and 3T3 fibroblasts in an alginate solution. Cytotoxic activity of paclitaxel against 4T1B in 3D (3-Dimensional) culture was evaluated by MTT. For molecular analysis, real-time PCR was done. RESULTS:Our results proved that in brain metastatic organoids, fibroblasts cause a significant increase in paclitaxel resistance. Molecular analysis showed that the expression level of α-smooth muscle actin (α-SMA) increased in MAF compared to normal fibroblasts. Surprisingly, the expression level of fibroblast-specific protein 1 (FSP-1) decreased compared to normal fibroblasts. CONCLUSION:Here, we reveal the pivotal roles of MAFs in chemoresistance and discuss their molecular properties. Our approach involves exploring various therapeutic techniques to comprehend MAFs and presenting therapeutic perspectives for metastatic cancer treatment.
INTRODUCTION:The relationship between cancer and dementia remains complex, and evidence regarding non-central nervous system (CNS) cancers such as non-small cell lung cancer (NSCLC) is inconsistent. This population-based cohort study examined the association between stage II-III NSCLC and the risk of dementia in Taiwan. MATERIALS/METHODS:National Health Insurance Research Database (NHIRD) was used in this study. The primary outcome was incident dementia, defined by ≥2 outpatient visits or ≥1 hospitalization. Cox proportional hazards models were applied to estimate crude and adjusted hazard ratios (HR). Kaplan-Meier curves and Schoenfeld residual tests were used to assess cumulative incidence and proportional hazards assumptions. The median follow-up time was 3.1 years in the NSCLC cohort and 4.7 years in the non-cancer cohort. RESULTS:Overall, stage II-III NSCLC was not associated with an increased risk of dementia compared with matched non-cancer individuals (adjusted HR = 1.11, 95% Confidence Interval (CI): 0.98-1.26). However, Patients with stage II NSCLC showed a borderline significance toward increased dementia risk (adjusted HR = 1.20, 95% CI: 1.01-1.43), although this association was not maintained in sensitivity analyses. Age, hypertension, diabetes mellitus, and cerebrovascular diseases were also associated with elevated dementia risk. CONCLUSIONS:This large, nationwide cohort study found no overall association between stage II-III NSCLC and dementia.
BACKGROUND:Hepatocellular carcinoma (HCC) frequently develops in the setting of chronic liver disease, making its management uniquely complex and historically centered on surgery. RECENT FINDINGS:Advances in locoregional therapies, molecular targeted agents, and immune checkpoint inhibitors have profoundly transformed treatment algorithms. Immunotherapy-based combinations achieve deep and durable responses, enabling downstaging, conversion surgery, and perioperative strategies previously considered unfeasible. CONCLUSION:In the contemporary era, surgeons serve not only as technical operators but as strategic leaders within multidisciplinary teams, integrating evolving systemic and local therapies to achieve durable oncologic outcomes.
BACKGROUND:High body-mass index (BMI) defined in the Global Burden of Disease Study as BMI above the theoretical minimum risk exposure level, is an established modifiable risk factor for ovarian cancer, particularly among older women. However, a comprehensive assessment of the global disease burden attributable to high BMI, including its spatiotemporal evolution and underlying drivers, remains lacking, particularly for older women. METHODS:Using data from the Global Burden of Disease Study 2021, we analyzed disability-adjusted life years (DALYs) and deaths from ovarian cancer attributable to high BMI among women aged ≥55 years from 1990 to 2021. We examined temporal trends, geographic disparities by Socio-Demographic Index (SDI), region, and nation, and performed decomposition analyses to identify contributions from population growth, aging, and epidemiological changes. RESULTS:Globally, the attributable burden increased from 1990 to 2021, with population growth as the main driver. of rising absolute DALYs (86.72) and deaths (85.17). Marked socioeconomic disparities were observed. While high-SDI regions had the highest age-standardized rates in 2021, they showed declining trends., whereas low-middle and low-SDI regions experienced the most rapid increases. Regionally, the fastest increases occurred in South Asia, Southeast Asia, and East Asia, while nationally the largest rises were observed in Timor-Leste, Viet Nam, and Bangladesh. In these settings, epidemiological changes were the dominant contributor to increasing burden. CONCLUSIONS:The global burden of ovarian cancer due to high BMI is rising and unequally distributed across SDI regions. While population growth drives the overall increase, escalating obesity prevalence is the key driver in rapidly developing regions. Targeted obesity prevention, improved early detection, and strengthened health-care systems should be prioritized, particularly in high-growth regions. Future studies should improve data quality in low-resource settings and explore cost-effective interventions.
INTRODUCTION:Triple-negative breast cancer (TNBC) is associated with high recurrence and mortality. Liquid biopsy biomarkers, such as circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), and microRNAs (miRNAs), offer noninvasive tools for monitoring TNBC. METHODS:A systematic review on liquid biopsy in TNBC was conducted and analyzed using PRISMA guidelines and later assessed via the EPHPP tool. RESULTS:Across 20 studies, ctDNA was a strong predictor for poorer disease-free survival (DFS) and relapse-free survival (RFS). Other biomarkers, including cfDNA and miRNAs, also showed prognostic value. CONCLUSION:Liquid biopsy, particularly ctDNA, is a valuable predictor of TNBC recurrence, supporting noninvasive monitoring and prognosis.
Spatial transcriptomics (ST) is revolutionizing pan-cancer analysis by enabling the in situ integration of spatial architecture with molecular profiles. This review synthesizes key advances, including deciphering conserved and divergent spatial ecosystems across cancers, mapping the heterogeneity of driver genes, tracing metastatic evolution, and establishing novel spatial molecular classifications. It further discusses how these insights inform clinical translation for diagnosis and therapy stratification. While integration of multi-cancer datasets and translational efficiency remain challenges, ST is a pivotal bridge toward spatially informed, broad-spectrum oncological strategies.
