Tumor Characteristics Research Articles

Patient and tumour characteristics in older patients (70 years or older) undergoing transperineal prostate biopsy: a retrospective cohort study.

PSA screening is advocated in men with a life expectancy of >10 years. With a rising mean life expectancy of 81 years in Australia, many men in their 70s have life expectancies of >10 years. Additionally, advanced age is an independent risk factor for high grade prostate cancer. Hence, we aimed to identify patient and disease characteristics and outcomes of men >70 years undergoing transperineal prostate biopsies (TPB) for suspected prostate cancer. All patients aged 70 years old and above who underwent TPB for suspected prostate cancer between 1st January 2019 and 1st July 2022 at a large tertiary centre were identified. Data including patient Charlson Comorbidity Indices (CCI), pre-operative PSA, Multiparametric prostate MRI (mpMRI), histopathological results, subsequent intervention, and treatment intent (curative vs palliative) were obtained via scanned and electronic medical records. Of 229 patients, median age was 74 years and 72.5% patients had a CCI of ≤4 (>53% estimated 10-year survival). 80.8% were diagnosed with prostate cancer and 65.9% had ISUP ≥ 2 disease. 86.4% of patients with PIRADS 4 or 5 lesions resulted in clinically significant prostate cancer. 3.9% had mild biopsy complications. 76.8% of those with prostate cancer underwent treatment with curative intent. Men >70 years of age have a higher risk of clinically significant prostate cancer and low biopsy risk. Hence, many may benefit from early diagnosis and treatment. Decision on screening and further investigation should be based on assessment of individual risks, benefits and life expectancy.

Radiomic signatures derived from baseline 18F FDG PET/CT imaging can predict tumor-infiltrating lymphocyte values in patients with primary breast cancer.

To determine the value of radiomics data extraction from baseline 18F FDG PET/CT in the prediction of tumor-infiltrating lymphocytes (TILs) among patients with primary breast cancer (BC).We retrospectively evaluated 74 patients who underwent baseline 18F FDG PET/CT scans for BC evaluation between October 2020 and April 2022. Radiomics data extraction resulted in a total of 131 radiomic features from primary tumors. TILs status was defined based on histological analyses of surgical specimens and patients were categorized as having low TILs or moderate & high TILs. The relationships between TILs groups and tumor features, patient characteristics and molecular subtypes were examined. Features with a correlation coefficient of less than 0.6 were analyzed by logistic regression to create a predictive model. The diagnostic performance of the model was calculated via receiver operating characteristics (ROC) analysis.Menopausal status, histological grade, nuclear grade, and four radiomics features demonstrated significant differences between the two TILs groups. Multivariable logistic regression revealed that nuclear grade and three radiomics features (Morphological COMShift, GLCM Correlation, and GLSZM Small Zone Emphasis) were independently associated with TIL grouping. The diagnostic performance analysis of the model showed an AUC of 0.864 (95% CI: 0.776-0.953; p < 0.001). The sensitivity, specificity, PPV, NPV and accuracy values of the model were 69.6%, 82.4%, 64%, 85.7% and 78.4%, respectivelyThe pathological TIL scores of BC patients can be predicted by using radiomics feature extraction from baseline 18F FDG PET/CT scans.

Epigenetic mechanisms underlying endometrial cancer (EC) outcomes: race-specific patterns of DNA methylation associated with molecular subtypes and survival.

Endometrial cancer [EC] is the fourth most common cancer in women in the United States. Stark racial disparities are present in EC outcomes in which Black women have significantly higher EC-related mortality than White women. The social and biologic factors that contribute to these disparities are complex, and may include racial differences in epigenetic landscapes. To investigate race-specific epigenetic differences in EC tumor characteristics and outcomes, we utilized the most recent data within the Cancer Genome Atlas (TCGA). Genome-wide CpG methylation data for more than 850 000 CpG sites were analyzed across 245 tumor samples, including 52 from Black women and 181 from White women. Race-adjusted and race-stratified associations among CpG methylation in ECs and molecular subtypes and disease-free survival (DFS) were examined. Race-specific analysis identified subtype-associated CpGs within 9572 genes in tumors from White women, and only 10 genes in tumors that were from Black women. Race-specific analyses also identified survival-associated CpGs with 1119 unique genes identified in tumors from White women, and none identified in tumors from Black women. Genes identified with differential methylation among subtypes included those involved in oxidative stress (HIF3A), and DNA repair (MLH1). Replication cohort data highlighted genes overlapping with those identified within the TCGA, such as G Protein Subunit Beta 1 (GNB1), involved in G-protein signaling, and Interleukin 37 (IL37), involved in cytokine signaling. Identification of these racial differences in EC tumor epigenetic landscapes and associated changes in gene expression may provide insight into strategies to improve outcomes and reduce disparities.

Palliative Radiotherapy in Metastatic Breast Cancer Patients on CDK4/6 Inhibitors: Safety Analysis

Purpose: CDK4/6 inhibitors require meticulous monitoring due to their potential to cause hematological toxicities and hepatotoxicity. This study evaluates the safety of combining CDK4/6 inhibitors with palliative radiotherapy in patients with metastatic hormone receptor-positive and HER2-negative breast cancer. Patients and Methods: This study included 188 patients treated with CDK4/6 inhibitors between January 2021 and June 2024. Data on patient demographics, tumor characteristics, and treatment interventions were extracted from medical records. The primary focus was on the incidence of grade ≥ 3 hematologic toxicities and hepatotoxicity, assessed according to CTCAE 5.0 criteria, in those receiving concurrent palliative radiotherapy. Results: With a median follow-up of 18.5 months, the 18-month PFS and OS rates were 67% and 85%, respectively. The median age was 57.5 years, and 79% of patients were post-menopausal. Bone and liver metastases were present in 66% and 23% of patients, respectively. Concurrent palliative radiotherapy was administered in 25% of the cohort. The incidence of grade ≥ 3 hematologic toxicity was comparable between those who received radiotherapy and those who did not. Ribociclib use was associated with lower rates of grade 3 hematologic toxicity (OR: 0.37), neutropenia (OR: 0.41), dose interruptions (OR: 0.30), and dose reductions (OR: 0.37). Pre-menopausal status was linked to fewer dose reductions (OR: 0.17). Rates of treatment interruption, dose reduction, and withdrawal were 55%, 24%, and 2%, respectively. Conclusions: The concurrent use of CDK4/6 inhibitors and palliative radiotherapy does not increase the incidence of hematological adverse events in patients with metastatic breast cancer.

Penalized landmark supermodels (penLM) for dynamic prediction for time-to-event outcomes in high-dimensional data

BackgroundTo effectively monitor long-term outcomes among cancer patients, it is critical to accurately assess patients’ dynamic prognosis, which often involves utilizing multiple data sources (e.g., tumor registries, treatment histories, and patient-reported outcomes). However, challenges arise in selecting features to predict patient outcomes from high-dimensional data, aligning longitudinal measurements from multiple sources, and evaluating dynamic model performance.MethodsWe provide a framework for dynamic risk prediction using the penalized landmark supermodel (penLM) and develop novel metrics ( and ) to evaluate and summarize model performance across different timepoints. Through simulations, we assess the coverage of the proposed metrics’ confidence intervals under various scenarios. We applied penLM to predict the updated 5-year risk of lung cancer mortality at diagnosis and for subsequent years by combining data from SEER registries (2007–2018), Medicare claims (2007–2018), Medicare Health Outcome Survey (2006–2018), and U.S. Census (1990–2010).ResultsThe simulations confirmed valid coverage (~ 95%) of the confidence intervals of the proposed summary metrics. Of 4,670 lung cancer patients, 41.5% died from lung cancer. Using penLM, the key features to predict lung cancer mortality included long-term lung cancer treatments, minority races, regions with low education attainment or racial segregation, and various patient-reported outcomes beyond cancer staging and tumor characteristics. When evaluated using the proposed metrics, the penLM model developed using multi-source data (of 0.77 [95% confidence interval: 0.74–0.79]) outperformed those developed using single-source data (range: 0.50–0.74).ConclusionsThe proposed penLM framework with novel evaluation metrics offers effective dynamic risk prediction when leveraging high-dimensional multi-source longitudinal data.

Histopathological Features of Hepatocellular Carcinoma in Patients with Hepatitis B and D Virus Infection: A Single-Institution Study in Mongolia

Background: Viral hepatitis, particularly hepatitis B (HBV) and hepatitis C (HCV), is highly prevalent in Mongolia. Moreover, Mongolia has the highest prevalence of hepatitis delta virus (HDV) globally, with over 60% of HBV-infected individuals also co-infected with HDV. Since HBV/HDV infections accelerate liver disease progression more compared to HBV infection alone, urgent national health measures are required. Method: This study presents a clinicopathological analysis of 49 hepatocellular carcinoma cases surgically resected at the Mongolia–Japan Hospital of the Mongolian National University of Medical Sciences. Results: HBV infection was found in 27 (55.1%) cases of all HCC cases. Immunohistochemical staining of the liver revealed that 14 (28.6%) cases were HDV antigen-positive in the HCC cases. HDV-positive cases exhibited significantly higher inflammatory activity compared to HDV-negative cases, with lymphocytic infiltrates predominantly composed of CD4-positive cells. Furthermore, HDV-positive cells were spatially distinct from HBs antigen-positive cells, suggesting that HDV-infected cells may interfere with HBV replication. No significant differences in fibrosis or in tumor characteristics were observed between the HDV-positive and negative cases. Early diagnosis of HBV/HDV infections is essential for appropriate treatment and to prevent further domestic transmission of the virus. However, routine testing for HDV infection is rarely conducted in Mongolia. Since HDV-positive cells are morphologically indistinguishable from surrounding HDV-negative cells, routine histopathological analysis may not be sufficient enough to detect HDV infection. Conclusions: Based on this clinicopathological study, CD4 and CD8 immunostaining can be considered an adjunctive diagnostic tool in cases with significant lymphocytic infiltration and hepatocellular damage. Additionally, HDV screening using blood and tissue samples may be recommended to ensure accurate diagnosis.

Survival Impact of Robotic-Assisted Laparoscopy (RAL) vs. Conventional Laparoscopy (LPS) in the Treatment of Endometrial Cancer

Objective: This study aimed to assess the impact of minimally invasive surgery (MIS) on survival rates in women diagnosed with endometrial cancer (EC). Methods: A retrospective cohort of 723 women who underwent MIS for EC was analyzed, with 468 having conventional laparoscopy (LPS) and 255 undergoing robotic-assisted laparoscopy (RAL). Sociodemographic features, tumor characteristics, and survival rates were examined for the entire cohort and in a propensity score-matched model. Results: In the overall sample, women who underwent RAL were older, had higher BMI, more comorbidities, and more aggressive tumors. After matching for age, BMI, comorbidities, ASA score, histological type, grade, myometrial invasion, LVSI, and FIGO stage, 482 patients (241 matched pairs) were selected. Disease-free survival (DFS) HR: 1, overall survival (OS) HR: 0.9, and specific survival related to EC (SS) HR: 0.15 were similar between the LPS and RAL groups. Conclusions: These findings suggest that the choice of surgical approach (robotic or laparoscopic) does not impact survival outcomes when matched in homogeneous groups.

Historical redlining and survival among children, adolescents, and young adults with cancer diagnosed between 2000-2019 in Seattle and Tacoma, Washington.

Historical redlining has been associated with inferior survival in adult-onset cancers. However, its relationship with pediatric, adolescent, and young-adult-onset cancer outcomes is unknown. This study identified incident cancer among individuals <40 years of age living in Seattle and Tacoma between 2000-2019 via the population-based Cancer Surveillance System. The authors determined case redlining status using Home Owners' Loans Corporation data overlaid with 2000 and 2010 census tracts. Kaplan-Meier methods and multivariable Cox proportional hazards models were used to determine 5- and 10-year overall survival and hazard ratio (HR) of death according to redlined status. Cox models adjusted for patient and tumor characteristics and area-level poverty; interaction between redlining and area-level poverty was also assessed. Among 4355 cases (median age at diagnosis 32 years), overall survival at 5 years was lower (85.1%; 95% confidence interval [CI], 83.5%-86.5%) among individuals residing in redlined neighborhoods compared with those in unexposed neighborhoods (90.3%; 95% CI, 89.0%-91.5%). Survival differences persisted at 10 years. The unadjusted hazard of death for redlined exposed individuals with cancer was higher than redlined unexposed (hazard ratio [HR], 1.62; 95% CI, 1.39-1.89). In the fully adjusted model, mortality remained higher for redlined cases (HR, 1.32; 95% CI, 1.12-1.56). There did not appear to be effect modification from area-level poverty in the relationship between redlining and death (p=.49). Among young individuals with cancer, residence at diagnosis in previously redlined neighborhoods was associated with lower survival compared with those residing in nonredlined neighborhoods, supporting the hypothesis that structural racism exerts persistent effects on contemporary health outcomes.

Evaluating the predictive value of endoscopic findings for residual colorectal cancer following neoadjuvant combination immunotherapy.

Endoscopy allows for the direct observation of primary tumor characteristics and responses after neoadjuvant treatment. However, reports on endoscopic evaluation following neoadjuvant immunotherapy remain limited. To examine the predictive value of endoscopic findings of primary tumors for responses to neoadjuvant immunotherapy. This retrospective study, conducted at a tertiary center in China, evaluated 74 patients with colorectal cancer, including 17 with deficient mismatch repair (dMMR) and 15 with proficient mismatch repair (pMMR) tumors. Patients underwent neoadjuvant immunotherapy followed by surgery. Endoscopic findings before and after neoadjuvant immunotherapy were reviewed and compared with the pathology of the resected specimens. In the pMMR group (n = 57 evaluable patients), endoscopy identified 11/17 patients who achieved a complete response (CR), while misidentifying 1/40 patients with residual disease as CR (64.7% vs 2.5%, P < 0.01). Conversely, 22/40 patients with residual disease were accurately identified as achieving a partial response (PR), with 1/17 patients who achieved CR misclassified as PR (55.0% vs 5.9%, P < 0.01). The sensitivity, specificity, and accuracy of endoscopic diagnosis for pathological CR were 64.7%, 97.5%, and 87.7%, respectively. In the dMMR cohort, endoscopy classified 9/17 patients as CR and 2 of the remaining patients with residual tumors as PR (64.3% vs 66.7%, P = 0.73). The method demonstrated 100% sensitivity and 82.4% accuracy in diagnosing pathological CR. Endoscopic evidence of CR or PR was well correlated with postoperative pathological outcomes in the pMMR cohort. Despite endoscopic indications of tumor residue, a complete pathological response post-surgery was possible in the dMMR cohort.

The Involvement of the NEAT1-1/miR-873-5p/GalNAcT-I Axis in the Development of Neuroblastoma.

The most prevalent extracranial solid tumor in childhood is neuroblastoma (NB), which arises from undifferentiated neural crest cells. However, the prognosis of this condition remains unfavorable, and the underlying mechanisms of its origin are still elusive. Therefore, this study aimed to investigate the specific mechanism underlying NEAT1-1 in NB. In this study, the expressions of NEAT1-1, miR-873-5p, and GalNAcT-I were analyzed by real-time quantitative polymerase chain reaction (qRTPCR) and Western blot (WB). Then, CCK-8 assays were conducted to evaluate the proliferation of NB cells. The Transwell assay was then performed to evaluate the invasion and migration of NB cells. Further, flow cytometry was utilized for the detection of cell apoptosis. Furthermore, the luciferase reporter gene assay was carried out to investigate the relationship between NEAT1-1 and miR-873-5p, as well as between miR-873-5p and GalNAcT-I. In contrast, an RNA-pull-down assay was conducted to confirm the regulatory relationship between NEAT1-1 and miR-873-5p. The effect of NEAT1-1 on tumor growth in vivo was detected in the BALB/c nude mice model. The qRT-PCR analysis revealed a significantly upregulated expression of NEAT1-1 in NB tumors compared to adjacent non-tumor tissue specimens. Suppression of NEAT1-1 resulted in the inhibition of tumor characteristics and induction of apoptosis in NB cells through the targeted regulation of miR-873-5p. Moreover, NEAT1-1 exerted its regulatory effect on GalNAcT-I protein levels by acting as a sponge for miR-873-5p in NB cells. Importantly, the downregulation of NEAT1-1 effectively suppressed tumor growth in vivo. Collectively, our findings suggest that the down-regulation of NEAT1-1 exerts a suppressive effect on NB progression by modulating the miR-873-5p/GalNAcT-I pathway, thereby providing novel insights into elucidating the underlying mechanisms of NB.

Abstract B019: Mathematical modeling-based optimization of gamma knife surgery after checkpoint blockade in melanoma brain metastases

Abstract Gamma knife radiotherapy (RT) treatment is often used as a salvage therapy after progression of melanoma brain metastasis (MBM) lesions under immune checkpoint inhibitor (ICI) blockade therapy; however, waiting until progression of nonresponsive lesions can result in significant symptomatic progression, and the toxicity of RT is greater for larger lesions as it is directly proportional to lesion volume. Robust and reliable standards for consistently maximizing the benefit of combination ICI + RT therapy remain elusive, likely in part due to the complexity of mechanistic interactions between each therapy. Addressing this clinical need will require optimizing the effects of their reported synergistic interactions such as tumor microenvironment modulation and immune activation while mitigating inhibitory effects such as immunosuppressive radiation effects. The ability to identify lesions unlikely to respond to ICI shortly after start of treatment would offer immediate clinical benefit by enabling earlier RT delivery, reduce the volume-dependent toxicities of RT, and reduce symptoms from lesion progression. To address the unmet clinical need for methods to optimize outcomes of combination ICI and RT therapy, we have developed a mechanistic mathematical model based on the biological and physical underpinnings of these complex therapies, and their interactions, which is able to describe and quantify interactions between ICI and RT and their interactions on the tumor. This builds upon our previous ICI modeling work by expanding the model based on the assumption that therapeutic outcome is not only a result of direct interaction between the treatment and disease, but is also a result of complex interplay between heterogeneous tumor populations that may be sensitive or resistant to treatment and their unique interactions with the immune system that serve to maintain or disrupt the tumor-immune equilibrium. RT further modulates this tumor-immune dynamic both by killing T cells in the tumor interior and by stimulating release of T cell activating antigens which can alter T cell activation exterior to the tumor, thereby affecting T cell recruitment into the tumor. By capturing how the complex time-dependent dynamics of tumor-immune interaction and recruitment influences – and is influenced by – transient shifts in treatment sensitive and resistant populations, our model aims to describe and quantify long-term tumor dynamics after ICI + RT therapy. This platform provides a consistent framework for systematically evaluating various proposed mechanisms underlying treatment interactions and how these may determine treatment failure or success. By applying the model to a retrospective, in-house generated melanoma brain metastasis data set, we are examining and refining our model structure with a goal of capturing a wide range of observed tumor dynamics using only clinically available data. This may lead to robust, quantitative methods to maximize treatment outcomes based on the unique characteristics of individual tumors. Citation Format: Alexander R. J. Silalahi, Caroline Chung, James W. Welsh, Zhihui Wang, Joseph D. Butner. Mathematical modeling-based optimization of gamma knife surgery after checkpoint blockade in melanoma brain metastases. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr B019.

Patient-Derived Organoid Models for NKT Cell-Based Cancer Immunotherapy

Invariant Natural Killer T (iNKT) cells are a unique subset of T cells that bridge innate and adaptive immunity, displaying potent anti-tumor properties through cytokine secretion, direct cytotoxicity, and recruitment of immune effector cells such as CD8+ T cells and NK cells. Despite their therapeutic potential, the immunosuppressive tumor microenvironment (TME), characterized by regulatory T cells, myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs), limits iNKT cell efficacy. Patient-derived organoid (PDO) platforms provide an innovative model for dissecting these complex interactions and evaluating strategies to reinvigorate iNKT cell functionality within the TME. PDOs closely mimic the genetic, phenotypic, and structural characteristics of primary tumors, enabling the study of tumor–immune dynamics. Integrating iNKT cells into PDOs offers a robust platform for investigating CD1d-mediated interactions, Th1-biased immune responses driven by glycolipid analogs like α-GalCer, and combination therapies such as immune checkpoint inhibitors. Additionally, PDO systems can assess the effects of metabolic modulation, including reducing lactic acid accumulation or targeting glutamine pathways, on enhancing iNKT cell activity. Emerging innovations, such as organoid-on-a-chip systems, CRISPR-Cas9 gene editing, and multi-omics approaches, further expand the potential of PDO–iNKT platforms for personalized immunotherapy research. Although the application of iNKT cells in PDOs is still undeveloped, these systems hold immense promise for bridging preclinical studies and clinical translation. By addressing the challenges of the TME and optimizing therapeutic strategies, PDO–iNKT platforms offer a transformative avenue for advancing cancer immunotherapy and personalized medicine.

Selective resection of the medial wall of the cavernous sinus in pituitary surgery: results of a prospective single center analysis.

Pituitary adenomas, despite their histologically benign nature, can severely impact patients' quality of life due to hormone hypersecretion. Invasion of the medial wall of the cavernous sinus (MWCS) by these tumors complicates surgical outcomes, lowering biochemical remission rates and increasing recurrence. This study aims to share our institutional experience with the selective resection of the MWCS in endoscopic pituitary surgery. This prospective study included patients diagnosed with pituitary adenomas who underwent endoscopic endonasal surgery at Mayo Clinic, Jacksonville. Inclusion criteria encompassed confirmed pituitary adenomas, selective MWCS resection, and availability of histopathological data. Patient demographics, tumor characteristics, surgical outcomes, and postoperative complications were analyzed using descriptive statistics. Twenty-six cases met the inclusion criteria. Functional adenomas and macroadenomas constituted 80.8% of cases. Recurrent adenomas represented 19.2% of cases. Tumor invasion of the MWCS was confirmed in 76.9% of cases and patients with acromegaly had the highest rate of confirmed invasion of the MW (88.8%). Initial disease control was achieved in 88.5% of the patients, and disease remission at last follow up was observed in those with acromegaly, Cushing's disease and prolactinomas in 87.5%, 83.3% and 66.6% of cases, respectively. Complete resection was achieved in 5/5 nonfunctioning adenomas. There were no carotid injuries, cranial deficits or fatalities observed. Resection of the MWCS is an effective strategy for improving surgical outcomes in pituitary adenomas with potential invasion into this area, especially in patients with functional and/or recurrent adenomas. The procedure demonstrates a positive balance of efficacy and safety, when performed by teams with high level of experience in endoscopic skull base surgery and in selected patients.

Design of an Optimal Convolutional Neural Network Architecture for MRI Brain Tumor Classification by Exploiting Particle Swarm Optimization

The classification of brain tumors using MRI scans is critical for accurate diagnosis and effective treatment planning, though it poses significant challenges due to the complex and varied characteristics of tumors, including irregular shapes, diverse sizes, and subtle textural differences. Traditional convolutional neural network (CNN) models, whether handcrafted or pretrained, frequently fall short in capturing these intricate details comprehensively. To address this complexity, an automated approach employing Particle Swarm Optimization (PSO) has been applied to create a CNN architecture specifically adapted for MRI-based brain tumor classification. PSO systematically searches for an optimal configuration of architectural parameters—such as the types and numbers of layers, filter quantities and sizes, and neuron numbers in fully connected layers—with the objective of enhancing classification accuracy. This performance-driven method avoids the inefficiencies of manual design and iterative trial and error. Experimental results indicate that the PSO-optimized CNN achieves a classification accuracy of 99.19%, demonstrating significant potential for improving diagnostic precision in complex medical imaging applications and underscoring the value of automated architecture search in advancing critical healthcare technology.

Association of blood group types and clinico-pathological features of gynecological cancers (GCs)

BackgroundGynecological cancers (GCs) affect the reproductive system of females, and are of multiple types depending on the affected organ most common of which are cervical, endometrial, ovarian cancers. Among different risk factors for GCs, ABO blood group system is considered as one of the pivotal contributing factors for increased susceptibility of GCs. The aim of our study was to report on the demographics of GC patients and to investigate the relationship between the ABO blood group system and the risk of acquiring GC in our population.MethodsThe current retrospective cross-sectional study was carried out between the years of 2016 and 2023. The sample included all the patients having age > 18 with a record of blood group and confirmed histological or cytological diagnosis as per International Federation of Gynecology and Obstetrics (FIGO) guidelines. A comprehensive review of the charts was conducted to gather data including demographics, tumor characteristics, comorbidities, adverse effects, and treatment methods.ResultsA total of 543 female patients were included in the study. The mean age of patients was 61.6. The three most common BG in our GC cases were as O + (43.8%), followed by A + (26%), and B + (15.5%). Among comorbidities, hypertension (HTN), diabetes mellitus (DM), dyslipidemia were the top three affecting GC patients. A significant association (p < 0.05) between ABO BG and serous histology in endometrial cancer was found. ABO blood group and fallopian cancer showed a significant relationship between serous histology and B blood group (p < 0.05). For ovarian cancer a significant association between AB blood group and recurrence rates were found (p < 0.05). In case of the patient dependent GCs, a significant association between ovarian cancers and recurrence, fallopian tube cancers and adverse events and survival status, vaginal/vulval cancers and TNM stage and mixed GCs and tumor type (carcinoma) was observed (P < 0.05). Furthermore, multinomial analysis between various confounding factors and GCs revealed that the risk of Cervical, Endometrial and Ovarian cancers to be significant for Type B BG (P < 0.05).ConclusionOur study found that O + BG was the most prevalent among our population. Furthermore, there was a significant association between BG B and endometrial and serous histology in fallopian tube and between BG AB and ovarian malignancies, respectively. Additionally, multinomial analysis revealed higher risk of Cervical, Endometrial and Ovarian cancers for Type B BG (P < 0.05).

MRI Radiomics Analysis in the Diagnostic Differentiation of Malignant Soft Tissue Myxoid Sarcomas From Benign Soft Tissue Musculoskeletal Myxomas.

Differentiation of benign myxomas and malignant myxoid sarcomas can be difficult with an overlapping spectrum of morphologic MR findings. To assess the diagnostic utility of MRI radiomics in the differentiation of musculoskeletal myxomas and myxoid sarcomas. Retrospective. A total of 523 patients were included; histologically proven myxomas (N = 201) and myxoid sarcomas (N = 322), randomly divided (70:30) into training:test subsets. T1-weighted (T1W), T2-weighted fat-suppressed (fluid-sensitive), and T1-weighted post-contrast (T1W + C) sequences at 1.0 T, 1.5 T, or 3.0 T. Seven semantic (qualitative) tumor features were assessed in each case. Manual 3D tumor segmentations performed with radiomics features extracted from T1W, fluid-sensitive, and T1W + C acquisitions. Models were constructed based on radiomic features from individual sequences and from their combination, both with and without the addition of qualitative tumor features. Intraclass correlation evaluated in 60 cases segmented by three readers. Features with intraclass correlation <0.7 excluded from further analysis. Boruta feature selection and Random Forest modeling performed using the training-dataset, with resultant models used to assess class discrimination (myxoma vs. myxoid sarcoma) in the test dataset. Radiomics score defined as probability class = myxoma. Logistic regression modeling employed to estimate performance of the radiomics score. Area under the receiver operating characteristic curve (AUC) was used to assess diagnostic performance, and DeLong's test to assess performance between constructed models. A P-value <0.05 was considered significant. Four qualitative semantic features showed significant predictive power in class discrimination. Radiomic models demonstrated excellent differentiation of myxomas from myxoid sarcomas: AUC of 0.9271 (T1W), 0.9049 (fluid-sensitive), and 0.9179 (T1W + C). Incorporation of multiparametric data or semantic features did not significantly improve model performance (P ≥ 0.08) compared to radiomic models derived from any individual MRI sequence alone. MRI radiomics appears to be accurate in the differentiation of myxomas from myxoid sarcomas. Classification performance did not improve when incorporating qualitative features or multiparametric imaging data. Accurately distinguishing between benign soft tissue myxomas and malignant myxoid sarcomas is essential for guiding appropriate management but remains challenging with conventional MRI interpretation. This study utilized radiomics, a method that extracts quantitative mathematically derived features from images, to develop predictive models based on routine MRI examination. Analyzing over 500 cases, MRI radiomics demonstrated excellent diagnostic accuracy in differentiating between benign myxomas and malignant myxoid sarcomas, highlighting the potential of the technique, as a powerful non-invasive tool that could complement current diagnostic approaches, and enhance clinical decision-making in patients with soft tissue myxoid tumors of the musculoskeletal system. 3 TECHNICAL EFFICACY: Stage 2.

Single-cell profiling of SLC family transporters: uncovering the role of SLC7A1 in osteosarcoma

BackgroundOsteosarcoma is the most common malignant bone tumor in children and adolescents, characterized by high disability and mortality rates. Over the past three decades, therapeutic outcomes have plateaued, underscoring the critical need for innovative therapeutic targets. Solute carrier (SLC) family transporters have been implicated in the malignant progression of a variety of tumors, however, their specific role in osteosarcoma remains poorly understood.MethodsThe single-cell sequencing data from GSE152048 and GSE162454, along with RNA-seq from the TARGET and GSE21257 cohorts, were utilized for the analysis in this study. LASSO regression analysis was conducted to identify prognostic genes and construct an SLC-related prognostic signature. Survival analysis and ROC analysis evaluated the validity of the prognostic signature. The ESTIMATE and CIBERSORT Packages were utilized to assess the immune infiltration status. Pseudotime and CellChat analyses were performed to investigate the relationship between SLC7A1, malignant phenotypes, and the immune microenvironment. CCK8 assays, EdU staining, colony formation assays, Transwell assays, and co-culture systems were used to assess the effects of SLC7A1 on cell proliferation, metastasis, and macrophage polarization. Finally, virtual docking identified potential drugs targeting SLC7A1.ResultsSLCs displayed distinct expression patterns across various cell types within the osteosarcoma microenvironment, with myeloid cells exhibiting a preference for amino acid uptake. A prognostic model comprising nine genes was constructed via LASSO regression, with SLC7A1 showing the highest hazard ratio. Multiple analytical algorithms indicated that SLCs were associated with immune cell infiltration and immune checkpoint gene expression. Single-cell analysis indicated that SLC7A1 was predominantly expressed in osteosarcoma cells and correlated with various malignant tumor characteristics. SLC7A1 also regulate interactions between tumor cells and macrophages, as well as modulate macrophage function through multiple pathways. In vitro assays and survival analysis demonstrated that inhibition of SLC7A1 suppressed the malignant phenotype of osteosarcoma cells, with SLC7A1 expression correlating with poor prognosis. Co-culture models confirmed the involvement of SLC7A1 in macrophage polarization. Finally, virtual screening and CETSA identified Cepharanthine as potential inhibitors of SLC7A1.ConclusionSLC-related prognostic signatures can be utilized for the prognostic evaluation of osteosarcoma. Pharmacological inhibition of SLC7A1 may be a feasible therapeutic approach for osteosarcoma.

Contrast-enhanced ultrasound-based AI model for multi-classification of focal liver lesions.

Accurate multi-classification is the prerequisite for reasonable management of focal liver lesions (FLLs). Ultrasound is the common image examination, but lacks accuracy. Contrast enhanced ultrasound (CEUS) offers better performance, but highly relies on experience. Therefore, we aimed to develop a CEUS-based artificial intelligence (AI) model for FLL multi-classification and evaluate its performance in multicenter clinical tests. Since January 2017 to December 2023, CEUS videos, immunohistochemical biomarkers and clinical information of solid FLLs>1cm in adults were collected from 52 centers to build and test the model. It aimed to classify FLLs into six types: hepatocellular carcinoma, hepatic metastasis, intrahepatic cholangiocarcinoma, hepatic hemangioma, hepatic abscess and others. First, Module-Disease, Module-Biomarker and Module-Clinic were built in training set A and validation set. Then, three modules were aggregated as Model-DCB in training set B and internal test set. Model-DCB performance was compared with CEUS and MRI radiologists in three external test sets. In total 3725 FLLs from 52 centers were divided into training set A (n=2088), validation set (n=592), training set B (n=234), internal test set (n=110), external test set A (n=113), B (n=276) and C (n=312). In external test sets A, B and C, Model-DCB all achieved significantly better performance (Accuracy from 0.85 to 0.86) than junior CEUS-radiologists (0.59-0.73), and comparable to senior CEUS-radiologists (0.79-0.85) and senior MRI-radiologists (0.82-0.86). In multiple subgroup analyses on demographic characteristics, tumor characteristics and ultrasound devices, its accuracy ranged from 0.79 to 0.92. CEUS-based Model-DCB provides accurate multi-classification of FLLs. It holds promise to benefit a wide range of population, especially for patients in remote suburban areas who have difficulty accessing MRI. Ultrasound is the most common image examination for screening focal liver lesions (FLLs), but it lacks accuracy for multi-classification, which is the prerequisite for reasonable management. Contrast enhanced ultrasound (CEUS) offers better diagnostic performance, but highly relies on work experience of radiologists. We develop a CEUS-based model (Model-DCB) can assist junior CEUS radiologists to achieve comparable diagnostic ability to senior CEUS radiologists and senior MRI radiologists. The combination of ultrasound device, CEUS examination and Model-DCB enables even patients in remote areas to obtain excellent diagnostic performance through examination by junior radiologists. NCT04682886.

BCL-2 inhibitors in hematological malignancies: biomarkers that predict response and management strategies.

Apoptosis is an essential characteristic of cancer and its dysregular promotes tumor growth, clonal evolution, and treatment resistance. B-cell lymphoma-2 (BCL-2) protein family members are key to the intrinsic, mitochondrial apoptotic pathway. The inhibition of the BCL-2 family pro-survival proteins, which are frequently overexpressed in B-cell malignancies and pose a fundamental carcinogenic mechanism has been proposed as a promising therapeutic option, with venetoclax (ABT-199) being the first FDA-approved BCL-2 inhibitor. Unfortunately, although BCL-2 inhibition has shown remarkable results in a range of B-cell lymphoid cancers as well as acute myeloid leukemia (AML), the development of resistance significantly reduces response rates in specific tumor subtypes. In this article, we explain the role of BCL-2 family proteins in apoptosis and their mechanism of action that justifies their inhibition as a potential treatment target in B-cell malignancies, including chronic lymphocytic leukemia, multiple myeloma, B-cell lymphomas, but also AML. We further analyze the tumor characteristics that result in the development of intrinsic or inherited resistance to BCL-2 inhibitors. Finally, we focus on the biomarkers that can be used to predict responses to treatment in the name of personalized medicine, with the goal of exploring alternative strategies to overcome resistance.

A decade of AGO QS-Mamma – Adherence to the Recommendations of The AGO Breast Committee for Diagnosis and Treatment in EBC in Routine Therapy in Germany

Introduction: The cure for Early Breast Cancer (EBC) is increasing over the last decades due to the improvement of diagnosis and therapy. Individualization of cancer treatment in EBC requires constant optimization by implementing current guidelines. The AGO (working group gynecologic oncology) QS-Mamma initiative, a quality assurance program (QS) of the AGO Breast Committee, was introduced to provide insight in guideline adherence in real world practice in Germany. We evaluated 10 years of QS-Mamma data to identify gaps and trends implementing those guidelines. Methods: QS-Mamma is a retrospective sample survey providing a representative overview of the treatment landscape for the treatment of breast cancer in Germany. The last six cohorts were analyzed over a period of ten years. Across all cohorts, an average of 264 centers documented a total of n=4,577 patients with EBC. Results: Testing for BRCA mutations in triple-negative patients increased significantly. Breast conserving surgery has been standard of care since the start of data collection; choice of surgical procedure depends primarily on tumor size and nodal status according to the patient´s preference, if possible. Axillary intervention has shifted towards SLNE or targeted axillary procedures in patients with negative preoperative nodal staging. Neoadjuvant systemic therapy (NAST) in operable EBC is established. Anthracycline administration in the adjuvant setting decreases. We noted an uptake on using platinum-containing CTx in TNBC, corresponding to AGO recommendations. Dual HER2 blockade is established in HER2 positive EBC with increased risk of relapse. Changes in guidelines are reflected in real-world data. Conclusion: Guideline adherence in breast cancer care is high and new treatments and diagnostic options are implemented promptly. Finally, escalation and de-escalation of treatment is depending on individual tumor characteristics resulting in the individual risk of recurrence. Guidelines should be flanked by real-world evidence to ensure and survey their impact.