Search Results (2,238)

Background: The risk of recurrence of early-stage cervical cancer (CC) is associated with prognostic factors such as tumor size, lymphovascular space invasion (LVSI), and deep stromal invasion (DSI). However, the adjuvant pelvic radiotherapy (RT) following surgery to reduce the risk of recurrence in “intermediate risk” remains controversial. This study aims to evaluate the role of adjuvant RT in the recurrence and identify prognostic factors. Methods: A systematic search of PubMed, Embase, and Cochrane databases was performed to identify studies comparing adjuvant RT versus no adjuvant treatment in early-stage CC patients with intermediate-risk factors defined by GOG-92 criteria. Outcomes were recurrence, local recurrence, death, 5-year overall survival (5y-OS), and 5-year disease-free survival (5y-DFS). Tumor size ≥ 4 cm, LVSI, and DSI were also evaluated as prognostic factors for recurrence. Statistical analysis was performed using Review Manager 7.2.0. Heterogeneity was assessed with I² statistics. Results: A total of 1504 patients from nine studies were included; only one study was a randomized controlled trial, while the others were retrospective cohorts. Adjuvant RT was used to treat 781 patients (52%). Median follow-up ranged from 48 to 120 months. Recurrence (OR 0.75; 95% CI 0.38–1.46; p = 0.39), local recurrence (OR 0.73; 95% CI 0.44–1.20; p = 0.22), death (OR 0.97; 95% CI 0.52–1.80; p = 0.91), 5y-OS (OR 1.22; 95% CI 0.36–4.18; p = 0.75), and 5y-DFS (OR 0.78; 95% CI 0.42–1.43 p = 0.42) revealed no statistically significant differences between adjuvant RT and observation groups. TS ≥ 4 cm was an independent prognostic risk factor for recurrence (HR 1.83; 95% CI 1.12–2.97; p = 0.02). Conclusions: Our findings suggest that adjuvant RT does not reduce recurrence risk in early-stage cervical cancer. Consider TS ≥ 4 cm as a significant prognostic factor for recurrence. Adjuvant RT in intermediate-risk patients should be considered with caution due the lack of significant improvement in recurrence until the CERVANTES and GOG-0263 trial results become available. Full article

Endometrial stromal sarcoma (ESS) is a rare malignant tumor of uterine mesenchyme, accounting for 15–20% of uterine sarcomas. It is classified into low-grade (LG-ESS) and high-grade (HG-ESS) subtypes, each defined by distinct histopathological and molecular features. LG-ESS exhibits slow progression, resembling proliferative-phase endometrial stroma, with genetic alterations like JAZF1-SUZ12 fusions. HG-ESS is more aggressive, characterized by high mitotic activity, necrosis, and genetic markers such as BCOR internal tandem duplication, often leading to advanced-stage diagnosis. Surgical resection is the cornerstone for managing early-stage ESS. A total hysterectomy with bilateral salpingo-oophorectomy (BSO) is recommended to prevent recurrence. Fertility-preserving approaches may be considered in LG-ESS but are associated with high recurrence rates. Lymphadenectomy is not routinely performed, given its limited prognostic value. HG-ESS, due to its aggressiveness, often requires additional treatment, including chemotherapy. Adjuvant therapy varies by subtype. LG-ESS responds well to hormonal treatments such as aromatase inhibitors and progestins, while tamoxifen is contraindicated. HG-ESS, lacking hormonal receptor expression, is managed with chemotherapy, often incorporating doxorubicin-based regimens. Radiotherapy may improve local control in select cases but shows limited impact on overall survival. Advanced-stage ESS treatment focuses on complete cytoreduction, supplemented by systemic therapies. Hormonal therapy remains the standard for advanced LG-ESS, whereas HG-ESS relies on chemotherapy. Prognosis depends on the subtype and stage. LG-ESS has favorable outcomes, with five-year survival exceeding 90% in early stages, but recurrent disease remains common. HG-ESS is associated with poorer survival due to its aggressive nature. Advances in molecular profiling offer promising avenues for personalized therapies, integrating genomic insights with targeted treatments to improve outcomes in this rare malignancy. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains among the most aggressive malignancies in the United States. Advances in treatments have slowly increased survival rates; however, outcomes remain dismal, largely due to the insidious onset of the disease and lack of screening tests leading to diagnosis at more advanced disease stages. As we better understand the molecular mechanisms that drive PDAC, we can leverage this technology for early detection of new PDAC or recurrences and find more effective methods to track treatment response. Liquid biopsies are increasingly common for the treatment of many malignancies, leveraging better technology to detect scant quantities of circulating tumor cells (CTCs) or byproducts of tumor biology (e.g., exosomes and microRNA [miRNA]) in the blood stream. When combined with existing biomarkers like CA 19-9, there is promising research that improved diagnostic modalities may be available in the future. Furthermore, these technologies are being leveraged to better prognosticate patients with PDAC and potentially monitor treatment responses not captured by cross-sectional imaging, which may allow for real-time changes in therapeutic strategy. This manuscript will review the molecular mechanisms that drive PDAC development and the biomarkers available for diagnosis and prognostication. Much of the data presented is still investigational, though many trials are ongoing to translate these studies for clinical use. Full article

Background/Objectives: The early detection of high levels of CBC-derived inflammatory biomarkers and cellular lines, as well as their variations across different histological subtypes of lung cancer, may aid in the early identification of high-risk lung cancer patients and further guide their clinical approach. Methods: A retrospective descriptive study was conducted and included 202 patients diagnosed with lung carcinoma at the Clinical County Hospital Mureș. The main analyzed parameters were the histological subtype and the stage of the tumor at diagnosis, white blood cell counts, and platelet counts, as well as nine CBC-derived inflammatory indexes like neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (d-NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), eosinophil-to-neutrophil ratio (ENR), eosinophil-to-monocyte ratio (EMR), systemic inflammatory index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI). The statistical analysis was performed using the MedCalc software, version 23.0.2. Logarithmic ANOVA was used to compare groups. Normality was tested using the Shapiro–Wilk test. The Chi-square test compared categorical variables, while the independent Mann-Whitney test was used for continuous variables. Results: The inflammatory response increased as disease severity progressed, with NSCLC-NOS being the histological subtype with the most numerous patients outside the normal ranges. Eosinophil count differed significantly across the histologic subtypes of NSCLC, with adenocarcinoma and adenosquamous patients exhibiting the highest values. In adenocarcinoma patients, we observed that NLR and MLR levels increased progressively as the tumor stage advanced. Based on severity, differences were observed across the histological subtypes of lung cancer in stage III patients for ENR, EMR, AISI, eosinophil count, and platelet count, as well as in stage IV patients for AISI, SIRI, and SII. Disease severity impacts the associated inflammatory response in all histologic subtypes of lung cancer to varying degrees. Conclusions: Histological subtype might have a decisive role in shaping the systemic inflammatory profile of lung cancer patients. CBC-derived indices serve as accessible, cost-effective biomarkers for early risk assessment, aiding in the prognosis evaluation and monitoring of therapeutic response. Future studies are needed to further evaluate the histology-specific inflammatory profiles as adjunctive tools in precision oncology. Full article

Introduction: Accurate staging is essential in pancreatic adenocarcinoma due to its aggressive nature and poor prognosis. The 8th edition of the AJCC TNM staging system introduced changes in tumor size criteria and nodal classification. This study compares the prognostic performance of the 7th and 8th editions in resected patients. Material and Methods: A retrospective analysis was conducted on 214 patients with pancreatic adenocarcinoma who underwent curative surgery. TNM staging was assigned according to both AJCC editions. Kaplan–Meier analysis and multivariate Cox regression, stratified by adjuvant therapy, were used to assess disease-free survival (DFS) and overall survival (OS). Results: The 8th edition TNM staging was significantly associated with lower risk of recurrence, with TNM stages I and II independently predicting better DFS (p < 0.05). In contrast, the 7th edition TNM stage I remained the only independent predictor of OS (HR = 0.376; p = 0.023). Reclassification between editions altered stage distribution, particularly within stage II. Conclusions: The 8th edition improves early recurrence stratification, while the 7th edition retains stronger prognostic value for overall survival. Both systems offer complementary insights, supporting outcome-specific staging use. Full article

Background/Objectives: Lung cancer recurrence, particularly in NSCLC, remains a major challenge, with 30–70% of patients relapsing post-treatment. Traditional predictors like TNM staging and histopathology fail to account for tumor heterogeneity and immune dynamics. This review evaluates AI models integrating gene biomarkers (TP53, KRAS, FOXP3, PD-L1, and CD8) to enhance the recurrence prediction and improve the personalized risk stratification. Methods: Following the PRISMA guidelines, we systematically reviewed AI-driven recurrence prediction models for lung cancer, focusing on genomic biomarkers. Studies were selected based on predefined criteria, emphasizing AI/ML approaches integrating gene expression, radiomics, and clinical data. Data extraction covered the study design, AI algorithms (e.g., neural networks, SVM, and gradient boosting), performance metrics (AUC and sensitivity), and clinical applicability. Two reviewers independently screened and assessed studies to ensure accuracy and minimize bias. Results: A literature analysis of 18 studies (2019–2024) from 14 countries, covering 4861 NSCLC and small cell lung cancer patients, showed that AI models outperformed conventional methods. AI achieved AUCs of 0.73–0.92 compared to 0.61 for TNM staging. Multi-modal approaches integrating gene expression (PDIA3 and MYH11), radiomics, and clinical data improved accuracy, with SVM-based models reaching a 92% AUC. Key predictors included immune-related signatures (e.g., tumor-infiltrating NK cells and PD-L1 expression) and pathway alterations (NF-κB and JAK-STAT). However, small cohorts (41–1348 patients), data heterogeneity, and limited external validation remained challenges. Conclusions: AI-driven models hold potential for recurrence prediction and guiding adjuvant therapies in high-risk NSCLC patients. Expanding multi-institutional datasets, standardizing validation, and improving clinical integration are crucial for real-world adoption. Optimizing biomarker panels and using AI trustworthily and ethically could enhance precision oncology, enabling early, tailored interventions to reduce mortality. Full article

Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) represent a rare and varied class of neoplasms, characterized by diverse clinical presentations and prognostic trajectories. Accurate and prompt diagnosis is vital to inform and optimize therapeutic decisions. Ultrasound, including standard B-mode imaging and advanced methods such as contrast-enhanced ultrasound (CEUS) and endoscopic ultrasound (EUS), serves as a key component in the diagnostic evaluation of these tumors. B-mode US and CEUS provide non-invasive, accessible methods for early detection and characterization. On B-mode imaging, GEP-NETs typically present as well-defined, hyperechoic, or iso-echoic lesions, while CEUS highlights their characteristic vascularity, marked by arterial-phase hyperenhancement and venous-phase washout. Compared to CT and MRI, ultrasound offers real-time, dynamic imaging without ionizing radiation or nephrotoxic contrast agents, making it particularly advantageous for patients requiring frequent monitoring or with contraindications to other imaging modalities. CT and MRI are widely regarded as the preferred methods for staging and surgical planning due to their detailed anatomical visualization. However, ultrasound, especially CEUS, provides a significant adjunctive role in both early detection and the follow-up on GEP-NETs. This analysis delves into the strengths, challenges, and innovations in ultrasound technology for diagnosing pancreatic NETs, focusing on its contribution to comprehensive imaging strategies and its impact on patient care decisions. Full article

Background: A novel and highly effective strategy for tumor immunotherapy involves enhancing host immune responses against tumors through the blockade of checkpoint molecules. The most common toxicities associated with checkpoint blockade therapies include autoimmune damage to various organs. Purpose: This study aims to investigate hematological markers derived from complete blood counts (CBCs)—including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), derived neutrophil-to-lymphocyte ratio (dNLR), white blood cell-to-hemoglobin ratio (WHR), neutrophils, lymphocytes, platelets, hemoglobin, red blood cell (RBC) count, neutrophil-to-RBC ratio (NRR), and neutrophil-to-hemoglobin ratio (NHR)—as potential prognostic biomarkers for the early identification of hypothyroidism in patients receiving PD-1 or PD-1/CTLA-4 immune checkpoint inhibitors. Materials and Methods: A prospective observational study was conducted on 44 patients with stage III-IV solid tumors treated with immune checkpoint (PD-1 or PD-1/CTLA-4) inhibitors. Thyroid function tests and CBC-derived biomarkers were collected at baseline, before immunotherapy. In the immunotherapy cohort, 15 of the 44 patients developed immune-related hypothyroidism, defined as overt autoimmune thyroiditis (TSH > 4.0, FT4 < 12, and anti-TPO antibodies > 30 IU/mL and/or anti-TG antibodies > 95 IU/mL) (Group 1). In comparison, 29 patients maintained normal thyroid function (Group 2). The control group comprised 14 age- and sex-matched healthy volunteers (Group 3). Statistical analyses were performed using analysis of variance (ANOVA) to compare blood parameters among the three groups (Group 1, Group 2, and Group 3) before treatment, with statistical significance set at a p-value < 0.05. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic power of the potential prognostic biomarkers areas. The area under the curve (AUC), sensitivity, and specificity were calculated for the 44 immunotherapy patients. Results: The PLR was significantly higher (262.25 ± 162.95), while WBCs-neutrophils, the WHR, the NRR, the NHR, WBCs, neutrophils, and lymphocytes were lower (2.07 ± 0.66, 0.54 ± 0.19, 0.96 ± 0.28, 0.36 ± 0.14, 6.36 ± 2.07, 4.29 ± 1.55, and 1.23 ± 0.41, respectively) at baseline in Group 1 in comparison to Group 2. ROC curve analysis revealed that the areas under the curve (AUC) for WBCs, neutrophils, lymphocytes, WBCs-neutrophils, the PLR, the WHR, the NRR, and the NHR were 0.9, 0.87, 0.83, 0.85, 0.84, 0.92, 0.89, and 0.87, respectively. These values exceeded the threshold, indicating the high prognostic potential of each marker. Conclusions: Lower baseline levels of WBCs-neutrophils, the WHR, the NRR, the NHR, WBCs, neutrophils, and lymphocytes, along with a higher PLR, were associated with an increased risk of hypothyroidism in patients receiving PD-1 or PD-1/CTLA-4 inhibitors. These CBC-derived biomarkers represent simple, accessible, and potentially useful tools for predicting hypothyroidism in cancer patients undergoing immunotherapy. Further studies in bigger cohorts are needed to validate our findings. Full article

Structural biomarkers determined by X-ray scattering of the tissues can complement conventional diagnostics and provide a pathway for early detection of diseases. In the present study, mouse models were utilized to observe the progression of prostate cancer. We induced cancer in the left lobe of the mouse prostate, whilst the right lobe was left uninoculated. The mice were sacrificed at increasing systematic time points, and lobe samples were subsequently analyzed using X-ray scattering. Control samples were also collected from healthy mice sacrificed at the same time points. This investigation revealed that the ratio between the X-ray scattering peaks associated with the lipids and water can serve as a structural biomarker of cancer, and this biomarker develops as the tumor advances. The obtained cancer trajectory can serve as a baseline for the determination of the disease stage, and the biomarker movement along the trajectory can be evidence of the healing or disease progression. Full article

Background/Objectives: RNA-binding motif protein 3 (RBM3) is a cold-shock protein associated with a favorable prognosis in various malignancies. However, its role in epithelial ovarian cancer (OC) remains unclear. This study aimed to evaluate the prognostic significance of RBM3 expression in OC and its association with clinicopathological features. Methods: We retrospectively analyzed 183 cases of OC. Tissue microarrays were constructed using paired 2 mm tumor cores, and RBM3 expression was assessed by immunohistochemistry. Nuclear staining was semi-quantitatively scored based on intensity and proportion, generating a nuclear score (NS). Cases were classified as high (NS > 1) or low (NS ≤ 1) expression. Associations with clinicopathological parameters and survival outcomes were analyzed using chi-square tests, Kaplan–Meier survival curves, and Cox regression models. Results: High RBM3 expression was observed in 51.4% of cases and was significantly associated with favorable histologic subtypes (mucinous, endometrioid, clear cell), early International Federation of Gynecology and Obstetrics (FIGO) stage, and the absence of distant metastasis. Subgroup survival analyses stratified by histologic subtype revealed no significant differences in survival outcomes. RBM3 expression was correlated with prolonged disease-free and overall survival, although it did not retain significance in multivariate analysis. Conclusions: RBM3 expression is strongly associated with favorable pathological features in epithelial ovarian cancer. Although not an independent prognostic marker, RBM3 may serve as a complementary biomarker for risk stratification and prognosis in clinical practice. Full article

Cholangiocarcinoma (CCA) is an aggressive tumor that originates from the epithelial cells of the bile duct and has the ability to metastasize to the liver or lymph nodes at an early stage. CCA metastasis represents a complex, multi-stage cascade process. Among these stages, the acquisition of invasiveness by CCA cells is a critical prerequisite for metastatic progression. Elucidating the molecular mechanisms driving CCA cell invasiveness is critical for advancing our knowledge in this field. Emerging evidence highlights the critical role of non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). These molecules orchestrate key processes such as the epithelial–mesenchymal transition (EMT), as well as the migration and invasion of CCA cells. Collectively, these processes ultimately drive tumor progression. This review comprehensively synthesizes the expression, biogenesis, interactions, signaling pathways, and functional mechanisms of ncRNAs in the invasiveness of CCA. Furthermore, the review discusses potential clinical applications of ncRNAs, including their roles as diagnostic tools, therapeutic targets, and prognostic markers. These investigations offer novel insights and evidence for identifying early metastasis in CCA, developing specific therapeutic strategies, and enhancing drug resistance. Full article

In recent years, tumor-infiltrating inflammatory cells within the tumor microenvironment have been extensively studied. However, much less is known about inflammatory cells in the normal tissue surrounding tumors. In this study, we assess the prognostic significance of tumor-associated macrophages (TAMs) in relation to disease-free survival (DFS) in patients with early-stage breast cancer. Our cohorts included patients from the APBI and BBCC trials, with eligible tumors being small in size and showing no signs of metastasis. We analyzed eight distinct inflammatory cell types in the normal tissue surrounding tumors, with a particular focus on the various macrophage subsets. There were clear differences in the frequencies of the different inflammatory cells, with a higher abundance of cells being found in the intraepithelial compartment compared to the stromal compartment. Notably, we found that M2-type macrophages located in the stromal compartment of tumor distant normal tissue exhibited a positive prognostic impact, in contrast to the M2-type macrophages found within the tumor itself. In the normal tissue surrounding tumors, there are surprisingly clear prognostic predictions for DFS. Normal tissue surrounding breast cancer tumors is clearly influenced by the tumor and could also influence the tumor in terms of growth and metastasis. Tumor-influenced inflammatory cells in the surrounding normal tissue could prevent the immune system from acting against the tumor and promote tumor growth through inflammation. Full article

Lung cancer is the leading cause of cancer-related death worldwide, ranking first among men and second among women for both incidence and mortality. Surgery remains the primary treatment for early-stage, resectable non-small cell lung cancer (NSCLC), encompassing stages I and selected cases of stage IIIB. For patients with stage II to III disease, as well as some stage IB tumors, neoadjuvant or adjuvant systemic therapies are recommended. It is well recognized that specific driver gene mutations play a critical role in tumor progression and aggressiveness, and patients with these genetic alterations may benefit from targeted treatment approaches. These alterations are referred to as “druggable”, “targetable”, or “actionable”, representing specific targets for personalized treatments. Tyrosine kinase inhibitors (TKIs) are now the preferred first-line treatment for patients harboring mutations in EGFR, ALK, ROS1, and BRAF. Additionally, targeted therapies exist for patients with alterations in RET, ERBB2, KRAS, MET, and NTRK, either for those who have received prior treatments or as part of ongoing clinical trials. The success of targeted therapies is reshaping treatment approaches for NSCLC with targetable driver gene alterations, both in early-stage and locally advanced settings. This review focuses on current therapeutic strategies that combine targeted therapies with surgical resection in patients with resectable non-small cell lung cancer (NSCLC) harboring actionable driver gene alterations. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor prognosis, and its progression is driven by epithelial plasticity and tumor microenvironment remodeling. Finding biomarkers that are responsible for the turning point from the early stage to the aggressive phase would facilitate clinical management. Method: In this study, we employed single-cell RNA sequencing to characterize a distinct subpopulation of highly proliferative epithelial cells undergoing a transitional phase during PDAC progression. By linking to cell cycle dysregulation, epithelial differentiation, and clinical staging, we constructed a gene-based risk score model using Lasso Cox regression. The expression of selected genes within the model was further validated using qPCR. Results: The model demonstrated robust predictive power for patient prognosis, TNM staging, and chemotherapy sensitivity. Further analysis of the tumor microenvironment revealed intensified crosstalk between a specific fibroblast subpopulation and transitional epithelial cells, mediated largely by collagen signaling. This stromal–epithelial interaction was found to contribute to the fibrotic barrier characteristic of PDAC. Additionally, immune profiling uncovered altered infiltration patterns, particularly involving natural killer (NK) cells in high-risk patients, suggesting mechanisms of immune tolerance and inhibition. Conclusions: These findings offer potential avenues for early detection, risk stratification, and targeted therapeutic strategies in PDAC. Full article

Background/Objectives: Endometrial cancer (EC) is the most common malignancy of the female genital tract. In 2013, The Cancer Genome Atlas analyzed the molecular profile of endometrial tumors identifying four risk classes (POLE ultramutated, mismatch repair-deficient, copy-number low-microsatellite stable, and copy-number high-serous-like. This classification is reshaping the current understanding of EC, enabling more refined risk stratification and uncovering potential therapeutic targets tailored to specific molecular subgroups. In the context of these four categories, it is possible to identify different molecular alterations that correlate with different prognoses. Methods and Results: We retrospectively analyzed tissue samples from eighty-five EC patients, performing multigene profiling using a 50-gene next-generation sequencing (NGS) panel to categorize them into distinct molecular subtypes; we observed the following distribution: 5.9% POLE, 25.8% mismatch repair-deficient/microsatellite instability (MMRd/MSI), 11.8% p53abn/TP53mut, and 56.5% NSMP. A favorable concordance (97.6%) was shown in MSI NGS-based analysis and MMR IHC results, and the agreement rate of p53 IHC and TP53 mutation was 92.3%. When we analyzed the correlation between molecular subtypes and clinicopathological features, we found that molecular subtypes significantly differentiated by grade, FIGO stage, and lymphovascular invasion (LVSI). These findings seem to support the effectiveness of our NGS-based classifier and its reliability in distinguishing both MSI and TP53 mutated cancers. This study also explored mutations in PIK3CA, PTEN, KRAS, ERBB2, and ESR1 genes, noting their potential as targets for treatments. PIK3CA mutations were linked to favorable features, such as early disease stage and absence of LVSI. Conclusions: Our study highlights the potential of a medium-complexity NGS panel for supporting the molecular classification of endometrial cancer, complementing the existing diagnostic algorithms. By identifying additional biomarkers, we provided valuable insights into the genomic landscape of EC. However, further exploration of the molecular profiles is needed to validate these findings and improve the identification of patients at a higher risk of unfavorable outcomes. Full article