Abstract Objectives Serum CA-125 remains a cornerstone biomarker in ovarian cancer surveillance; however, the prognostic significance of serial postoperative CA-125 kinetics across histological subtypes remains incompletely defined. This study evaluated longitudinal CA-125 patterns following adjuvant chemotherapy and their association with progression-free survival (PFS) in patients undergoing cytoreductive surgery. Methods In this retrospective cohort study, 126 women (≥18 years) with histologically confirmed ovarian cancer treated between 2015 and 2024 at a tertiary center (King Abdulaziz University Hospital) were included. All patients underwent primary cytoreductive surgery followed by adjuvant chemotherapy. Residual disease was categorized as optimal (≤1 cm) or suboptimal (>1 cm). Tumor characteristics were classified according to FIGO and WHO criteria. Serum CA-125 was measured at baseline and approximately 3 and 6 months postoperatively. Median CA-125 values were compared across histological subtypes using the Kruskal-Wallis test. PFS was assessed using Kaplan-Meier analysis and multivariable Cox regression, adjusting for key clinicopathological variables. Results The mean age was 53.2 ± 15.5 years, and serous carcinoma was the predominant subtype (46 %). Most patients presented with advanced-stage disease. Baseline CA-125 levels were elevated in 74.6 % of patients and differed significantly across histological groups (p<0.001). CA-125 levels declined substantially by 3 months after chemotherapy, with no significant inter-subtype differences at 3 months (p=0.309) or 6 months (p=0.160). Platinum-taxane combination therapy demonstrated numerically longer PFS compared with carboplatin monotherapy in unadjusted analysis; however, this association was not statistically significant after multivariable adjustment (p=0.102). Conclusions Serial postoperative CA-125 measurements may provide clinically relevant insight into early treatment response following cytoreductive surgery. Prospective studies incorporating standardized kinetic modeling are warranted to refine biomarker-guided surveillance strategies.

Abstract Objectives Quality of life (QoL), fatigue, and pain are poorly described in patients with recurrent or progressive bone and soft tissue sarcomas, whose treatment pathway is often longer and more complex. Previous studies have shown that patients with progressive sarcomas report lower overall QoL scores than those with stable disease. The aim of this study was to describe QoL, cancer-related fatigue, and pain perception in patients with progressive or recurrent malignant bone or soft tissue tumors, and to explore differences by tumor type and time-based outcome trajectories over a 24-month follow-up. Methods This prospective observational study enrolled patients with confirmed disease recurrence or progression between July 2019 and April 2021. QoL was assessed using the EORTC QLQ-C30, fatigue via the Brief Fatigue Inventory (BFI), and pain with the Numeric Rating Scale (NRS). Assessments were performed at baseline and at 6, 12, and 24 months. Linear mixed-effects regression models were used to analyze temporal trends and assess associations with age and tumor type. Results 42 patients were included (mean age 41.3 ± 15.5 years; 45.2 % female). No significant baseline differences were observed between tumor types. Pain and fatigue improved significantly over time. Global QoL declined markedly at 12 and 24 months, while functional and symptom-related QoL remained stable. Age was significantly associated with worse trajectories in pain and QoL, while tumor type was not. Conclusions Patients with recurrent or progressive sarcomas experience similar symptom burden regardless of tumor type. Pain and fatigue tend to improve over time, but global QoL declines. Age appears to be a relevant factor influencing symptom evolution and should be considered in designing supportive interventions.

Abstract Objectives Esophageal cancer (ESCA) is a common malignancy with high morbidity and mortality. Our study aimed to explore the regulatory pathways of CAP1 in ESCA and its effects on tumor immunity. Methods Immune-related differentially expressed genes (DEGs) associated with ESCA prognosis were screened through bioinformatics analysis, and a risk prognosis model was constructed. In addition, we employed a combination of in vitro techniques, including qRT-PCR, Western blot, CCK-8, Transwell, co-culture, CHIP, and dual-luciferase reporter assays, to systematically investigate the expression, function, and transcriptional regulation of CAP1 in ESCA. Furthermore, the role of the ELF1/CAP1 axis was verified using a xenograft tumor model. Results Bioinformatics analysis using LASSO Cox regression demonstrated that CAP1 carried the highest risk coefficient (0.4437) in the prognostic model. The risk score model demonstrated excellent predictive performance in the TCGA cohort and was successfully validated in external GEO datasets. High expression of CAP1 in ESCA cells enhanced their proliferative, migratory, and invasive capabilities (p<0.001). In a co-culture system, silencing CAP1 in ESCA cells enhanced the cytotoxicity of CD8+ T cells and reduced their apoptosis (p<0.001). The transcription factor ELF1 promoted CAP1 expression by binding to its promoter, thereby regulating immune evasion and tumor progression in ESCA. Importantly, in vivo experiments confirmed that knockdown of either ELF1 or CAP1 significantly suppressed tumor growth, enhanced CD8+ T cell infiltration, and downregulated PD-L1 expression (p<0.001), demonstrating that ELF1 promotes tumor progression and immune escape in ESCA via CAP1. Conclusion CAP1 promotes ESCA progression by regulating tumor immunity, cell proliferation, and migration. ELF1 plays a crucial role in ESCA by transcriptionally regulating CAP1 expression. These findings identify the ELF1/CAP1 axis as a promising therapeutic target and prognostic biomarker for ESCC.

Abstract Objectives Clear cell renal cell carcinoma (ccRCC) is characterized by abnormal lipid accumulation, which may influence tumor behavior and imaging appearance. However, the relationship between lipid metabolism–related genes, such as ancient ubiquitous protein 1 ( AUP1 ), and computed tomography (CT) imaging features remains unclear. This study aims to investigate the association between AUP1 expression and CT features in ccRCC patients, using artificial intelligence (AI)-based radiogenomic analysis. Methods Genomic and imaging data from 208 patients were analyzed. Regions of interest (ROIs) were manually placed on solid tumor tissue, excluding necrotic areas. An AI-based workflow, implemented in Python with the scikit-learn library, extracted first-order radiogenomic features, median, minimum, and maximum Hounsfield unit (HU) values, as indirect surrogates of intracellular lipid content, with lower HU values indicating higher lipid accumulation. Distributional descriptors were also computed to capture intra-tumoral heterogeneity. Associations between imaging features, AUP1 expression, and histological grade were tested using non-parametric statistics (Wilcoxon, Kruskal-Wallis tests, Pearson’s Chi-square test, and Fisher’s exact test, p<0.05). Results Among the 208 patients, 25 (12 %) expressed AUP1 . AI-based analysis showed that AUP1-positive tumors exhibited significantly lower median and minimum HU values compared with AUP1-negative tumors (p=0.025), consistent with AUP1-driven intracellular lipid droplet accumulation. In AUP1 -positive patients, high-grade tumors showed significantly higher median HU (p=0.036) and minimum HU values (p=0.037) than low-grade tumors. Interobserver agreement for ROI placement and HU measurement was excellent (k=0.91). Conclusions Radiogenomic feature extraction with AI-supported statistical analysis identified lower HU values as radiogenomic biomarkers of AUP1 expression, suggesting that AUP1 positivity is linked to a lipid-rich metabolic phenotype detectable by CT.

Abstract Post-mastectomy pain syndrome (PMPS) is a prevalent long-term complication after breast cancer surgery, affecting about 25–40 % of survivors. Its causes are diverse, including surgical injury, adjuvant treatment, and individual vulnerability, yet these insights have not translated into consistent management. Conventional pharmacological therapies provide only modest benefit, while nerve blocks, cryoneurolysis, radiofrequency techniques, and surgical innovations such as autologous fat grafting or nerve reconstruction show encouraging but still limited evidence. Neuromodulation strategies and complementary approaches, including rehabilitation and psychosocial support, further illustrate the diversity of available options. Despite these advances, fewer than half of affected patients receive targeted interventions, and clinical practice varies widely across regions. This narrative review aims to raise clinical awareness of PMPS and to provide an evidence-based reference for practicing clinicians, it summarizes the latest findings on risk factors, preventive measures, and therapeutic options. We contend that PMPS should be recognized as a significant oncological and surgical challenge, warranting systematic management in routine follow-up.

Abstract Objectives The APC I1307K variant is a known moderate-risk allele for colorectal cancer (CRC), especially among Ashkenazi Jewish (AJ) individuals. However, its role in other cancers, particularly in male breast cancer (MBC), remains unclear. This study aimed to evaluate whether APC I1307K contributes to MBC risk in the Italian (non-AJ) population. Methods A multicenter case-control study was conducted involving 1028 MBC cases and 2,126 geographically matched healthy male controls. Genotyping was performed via Next Generation Sequencing or TaqMan assays. Associations between APC I1307K and MBC risk were analyzed using logistic regression models, including multivariate adjustments for age, enrollment center, and BRCA1/2 status. Results The APC I1307K variant was detected in 4 MBC cases (0.4 %) and 5 controls (0.2 %). No statistically significant association with MBC risk was observed (multivariate odds ratio [OR]=3.7, 95 % CI: 0.8–17.0, p=0.09). Clinical-pathologic comparisons revealed no distinguishing features among variant carriers. None of the carriers harbored BRCA1/2 pathogenic variants (PVs) or had personal histories of CRC or familial adenomatous polyposis. Conclusions These findings suggest that APC I1307K does not confer a significant risk for MBC in the Italian population.

Abstract The ubiquitin-proteasome system (UPS) is a master regulator of protein homeostasis, and its dysregulation is a well-established driver of oncogenesis, metastasis, and therapeutic resistance. Deubiquitinating enzymes (DUBs), which stabilize proteins by counteracting ubiquitination, have emerged as critical nodal points in cancer signaling networks. This review systematically synthesizes evidence from seminal and recent literature to provide a comprehensive analysis of the UPS, focusing on the classification, structural diversity, and multifaceted roles of DUBs in tumor biology. We examine in detail the intricate interplay between DUBs and key oncogenic pathways, including DNA damage response, apoptosis, and epithelial-to-mesenchymal transition. Our synthesis highlights the profound context-dependent functions of DUBs, which can be either oncogenic or tumor-suppressive depending on their specific substrates and the cellular milieu. Mounting evidence underscores the therapeutic potential of targeting DUBs, with advances in small-molecule inhibitors and emerging DUB-targeting chimeras (DUBTACs) showing promise in restoring proteostatic balance. However, clinical translation faces significant hurdles, primarily the need for high selectivity to minimize off-target effects and manage toxicity, as underscored by the termination of VLX1570s clinical trials. We argue that the successful clinical translation of DUB inhibitors hinges on a precision medicine framework, relying on biomarker-driven patient selection to define therapeutic context and minimize toxicity. By synthesizing these intricate regulatory mechanisms, this review aims to catalyze the development of novel, targeted intervention strategies, ultimately improving cancer treatment outcomes and patient survival.

Abstract Cancer is widely recognized as a genetic disease based on the somatic mutation theory (SMT). This theory posits that cancer is a complex genetic disease arising from inherited or random somatic mutations in proto-oncogenes or tumor suppressor genes, leading to dysregulated cell growth. Hereditary cancer syndromes (HCSs) are genetic conditions with an underlying germline mutation that increases the risk of developing specific cancers. Numerous HCSs have been documented, and it is assumed that the inherited mutations responsible for these syndromes are the primary causes of cancers when they occur, reinforcing the SMT. In contrast, the mitochondrial metabolic theory (MMT) suggests that cancer develops due to a gradual disruption of ATP production through mitochondrial oxidative phosphorylation (OXPHOS). This leads to compensatory ATP production through substrate-level phosphorylation (SLP). Our findings indicate that no inherited mutations are fully penetrant for cancer. Therefore, these inherited mutations should be considered secondary risk factors rather than primary causes of cancer. Furthermore, we found that most, if not all, HCSs impair OXPHOS, induce oxidative stress, and exhibit increased reliance on SLP. Consequently, the heightened risk of cancer associated with HCSs likely stems from mitochondrial respiratory insufficiency and oxidative distress prevalent in these syndromes, thereby supporting the MMT.

Abstract Endocrine therapy continues to be a fundamental treatment for estrogen receptor-positive (ER+) breast cancer; however, its long-term effectiveness is often hindered by the development of acquired resistance. This resistance poses a significant challenge in clinical management, limiting the durability of treatment responses. Recently, new clinical data have emerged showing promise with combination therapies that integrate endocrine agents and pathway inhibitors, offering renewed hope for patients. Nevertheless, resistance to these combination therapies still occurs, emphasizing the urgent need for further investigation into the underlying mechanisms. Preclinical models, including cell lines and animal studies, play a crucial role in advancing this research. Various in vitro models have been developed to mimic resistance to different endocrine therapies, such as long-term estrogen deprivation models that simulate aromatase inhibitor treatment, as well as models resistant to tamoxifen and selective estrogen receptor degraders like fulvestrant. This review systematically examines these preclinical models used to study the multifactorial mechanisms that drive antiestrogen resistance, highlighting their relevance and utility in improving therapeutic strategies. Understanding resistance pathways through these models is essential to developing more effective interventions for overcoming endocrine therapy resistance in ER+ breast cancer.