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At least 37 records · Page 2Linked to original sources
PubMed2025

Targeting RECQL4 in hepatocellular carcinoma: from prognosis to therapeutic potential.

OBJECTIVE: The aim of this study is to assess the clinical utility of RecQ Like Helicase 4 (RECQL4) as a prognostic marker in hepatocellular carcinoma (HCC) and investigate its associations with various biological processes, angiogenesis-related factors, immune cell infiltration, immune checkpoints, and drug sensitivity. METHODS: RECQL4 expression was analyzed across a range of cancer types utilizing data from the TCGA database. Disparities in RECQL4 expression levels between normal and malignant tissues were evaluated, alongside an analysis of progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) curves. Exploration of pertinent pathways, immune cell infiltration, single-cell RNA-seq data, and drug sensitivity was conducted employing The Cancer Genome Atlas (TCGA) and Tumor Immune Single-Cell Hub (TISCH) databases. Furthermore, validation of in-silico results was validated through qPCR, Western blotting, CCK-8 assay, EdU assay, clonogenic assay, wound-healing assay, and transwell assay. RESULTS: In HCC, RECQL4 was highly expressed and associated with poorer prognosis (p&#x2009;<&#x2009;0.05). It positively correlated with pathways related to MYC targets, DNA replication, PI3K/AKT/mTOR signaling, DNA repair mechanisms, and the G2/M checkpoint (R&#x2009;>&#x2009;0.24, p&#x2009;<&#x2009;0.001). RECQL4 also showed significant correlations with angiogenesis-related genes, including PTK2 (R&#x2009;>&#x2009;0.4, p&#x2009;<&#x2009;0.05), suggesting a potential role in angiogenesis regulation. Immune analysis indicated that RECQL4 was associated with immune cell types such as T helper 2 cells, NK CD56bright cells, and follicular helper T cells, suggesting a positive relationship with their infiltration. High RECQL4 expression was also linked to increased sensitivity to drugs including Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Cellular experiments showed that RECQL4 expression at the mRNA and protein levels were significantly higher in HCC cell lines Hep3B and Huh7 compared to the normal liver cell line MHA. Moreover, RECQL4 knockdown resulted in reduced proliferation and migration in HCC cell lines (p&#x2009;<&#x2009;0.05). CONCLUSIONS: RECQL4 shows promise as a biomarker for predicting recurrence and survival in HCC and may affect angiogenesis regulation. Its expression also appears to impact sensitivity to drugs such as Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Furthermore, silencing RECQL4 significantly inhibits HCC cell line proliferation and migration.

Humans↗
PubMed2025

Advances in tumor subclone formation and mechanisms of growth and invasion.

Tumor subclones refer to distinct cell populations within the same tumor that possess different genetic characteristics. They play a crucial role in understanding tumor heterogeneity, evolution, and therapeutic resistance. The formation of tumor subclones is driven by several key mechanisms, including the inherent genetic instability of tumor cells, which facilitates the accumulation of novel mutations; selective pressures from the tumor microenvironment and therapeutic interventions, which promote the expansion of certain subclones; and epigenetic modifications, such as DNA methylation and histone modifications, which alter gene expression patterns. Major methodologies for studying tumor subclones include single-cell sequencing, liquid biopsy, and spatial transcriptomics, which provide insights into clonal architecture and dynamic evolution. Beyond their direct involvement in tumor growth and invasion, subclones significantly contribute to tumor heterogeneity, immune evasion, and treatment resistance. Thus, an in-depth investigation of tumor subclones not only aids in guiding personalized precision therapy, overcoming drug resistance, and identifying novel therapeutic targets, but also enhances our ability to predict recurrence and metastasis risks while elucidating the mechanisms underlying tumor heterogeneity. The integration of artificial intelligence, big data analytics, and multi-omics technologies is expected to further advance research in tumor subclones, paving the way for novel strategies in cancer diagnosis and treatment. This review aims to provide a comprehensive overview of tumor subclone formation mechanisms, evolutionary models, analytical methods, and clinical implications, offering insights into precision oncology and future translational research.

Humans↗
PubMed2025

Identification of multicohort-based predictive signature for NMIBC recurrence reveals SDCBP as a novel oncogene in bladder cancer.

BACKGROUND: Despite surgical and intravesical chemotherapy interventions, non-muscle invasive bladder cancer (NMIBC) poses a high risk of recurrence, which significantly impacts patient survival. Traditional clinical characteristics alone are inadequate for accurately assessing the risk of NMIBC recurrence, necessitating the development of novel predictive tools. METHODS: We analyzed microarray data of NMIBC samples obtained from the ArrayExpress and GEO databases. LASSO regression was utilized to develop the predictive signature. We combined gene signature and clinicopathological factors to construct a clinical nomogram for estimating NMIBC recurrence in a local cohort. Finally. the biological functions and potential mechanisms of SDCBP in bladder cancer were investigated experimentally in vitro and in vivo. RESULTS: An 8-gene signature was developed, and its efficiency for predicting NMIBC recurrence was evaluated using Kaplan-Meier and time-dependent ROC curves in both training and validation datasets. Immunohistochemical testing revealed elevated levels of ACTN4 and SDCBP in recurrent NMIBC tissues. We integrated the two proteins with clinical factors to develop a nomogram model, which showed superior accuracy compared to individual parameters. Gene Set Variation Analysis and Gene Set Enrichment Analysis unveiled SDCBP exerted cancer-promoting biological processes, such as angiogenesis, EMT, metastasis and proliferation. Experimental procedures demonstrated that silencing SDCBP attenuated cell growth, glucose metabolism and extracellular acidification rate, accompanied by decreased expression of p-AKT, p-ERK1/2, LDHA and Vimentin. CONCLUSIONS: The established 8-gene signature holds promise as a tool for predicting NMIBC recurrence, while targeting SDCBP may represent a potential strategy for delaying disease relapse.

Urinary Bladder Neoplasms↗
PubMed2026

Oncotype DX: Clinical Utility, Evidence, and Future Trends in Personalized Breast Cancer Management.

The Oncotype DX assay has revolutionized the management of early-stage, hormone receptor-positive, HER2-negative breast cancer. Developed in 2004, it quantifies 21 genes to generate a recurrence score that predicts distant recurrence risk and guides adjuvant chemotherapy. Multiple studies have validated its reliability and clinical utility in enabling more precise risk stratification and individualized treatment planning, thereby minimizing unnecessary chemotherapy exposure and improving patient outcomes. Leading oncology organizations such as the American Society of Clinical Oncology and National Comprehensive Cancer Network have incorporated it into their clinical guidelines. Beyond its well-established role in adjuvant chemotherapy decision-making, Oncotype DX is increasingly being investigated in broader clinical contexts, including lymph node-positive breast cancer, neoadjuvant therapy, radiotherapy, and ductal carcinoma in&#xa0;situ. Ongoing research and technological advancements, such as artificial intelligence-based predictive models and novel biomarker identification, hold significant promise for further enhancing its predictive accuracy and expanding its applications. This review synthesizes current evidence supporting the clinical utility of Oncotype DX, discusses evolving applications, and highlights future directions for integrating this genomic tool into precision oncology practice.

Humans↗
PubMed2025

Computational Pathology for Accurate Prediction of Breast Cancer Recurrence: Development and Validation of a Deep Learning-Based Tool.

Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cancer patients. Current prognostic tools like Oncotype DX offer valuable genomic insights into hormone receptor-positive and human epidermal growth factor receptor-negative patients but are limited by cost and accessibility, particularly in underserved populations. In this study, we present Deep-Breast-Cancer-Recurrence (BCR)-Auto, a deep learning-based computational pathology approach that predicts breast cancer recurrence risk from routine hematoxylin and eosin-stained whole slide images. Our methodology was validated on 2 independent cohorts: The Cancer Genome Atlas Program breast cancer data set and an in-house data set from The Ohio State University. Deep-BCR-Auto demonstrated robust performance in stratifying patients into low- and high-recurrence risk categories. On The Cancer Genome Atlas Program breast cancer data set, the model achieved an area under the receiver operating characteristic curve of 0.827, significantly outperforming the existing weakly supervised models (P = .041). In the independent The Ohio State University data set, Deep-BCR-Auto maintained strong generalizability, achieving an area under the receiver operating characteristic curve of 0.832, along with 82.0% accuracy, 85.0% specificity, and 67.7% sensitivity. These findings highlight the potential of computational pathology as a cost-effective alternative for recurrence risk assessment, broadening access to personalized treatment strategies. This study underscores the clinical utility of integrating deep learning-based computational pathology into routine pathological assessment for breast cancer prognosis across diverse clinical settings.

Humans↗
PubMed2025

Serum, Cell-Free, HPV-Human DNA Junction Detection and HPV Typing for Predicting and Monitoring Cervical Cancer Recurrence.

Almost all cervical cancers are caused by human papillomaviruses (HPVs). In most cases, HPV DNA is integrated into the human genome. We found that tumor-specific, HPV-human DNA junctions are detectable in serum cell-free DNA of a fraction of cervical cancer patients at the time of initial treatment and/or at six months following treatment. Retrospective analysis revealed these junctions were more frequently detectable in women in whom the cancer later recurred. We also found that cervical cancers caused by HPV types outside of phylogenetic clade &#x3b1;9 had a higher recurrence frequency than those caused by &#x3b1;9 types in both our study and The Cancer Genome Atlas cervical cancer database, despite the higher prevalence of &#x3b1;9 types including HPV16 in cervical cancer. Thus, HPV-human DNA junction detection in serum cell-free DNA and HPV type determination in tumor tissue may help predict recurrence risk. Screening serum cell-free DNA for junctions may also offer an unambiguous, non-invasive means to monitor absence of recurrence following treatment.

DNA integration↗
PubMed2026

Serum, cell-free, HPV-human DNA junction detection and HPV typing for predicting and monitoring cervical cancer recurrence.

Almost all cervical cancers are caused by human papillomaviruses (HPVs). In most cases, HPV DNA is integrated into the human genome. We found that tumor-specific, HPV-human DNA junctions are detectable in serum cell-free DNA of a fraction of cervical cancer patients at the time of initial treatment and/or at 6 months following treatment. Retrospective analysis revealed these junctions were more frequently detectable in women in whom the cancer later recurred. We also found that cervical cancers caused by HPV types outside of phylogenetic clade &#x3b1;9 had a higher recurrence frequency than those caused by &#x3b1;9 types in both our study and The Cancer Genome Atlas cervical cancer database, despite the higher prevalence of&#x3b1;9 types, including HPV16, in cervical cancer. Thus, HPV-human DNA junction detection in serum cell-free DNA and HPV type determination in tumor tissue may help predict recurrence risk. Screening serum cell-free DNA for junctions may also offer an unambiguous non-invasive means to monitor absence of recurrence following treatment.

Humans↗
PubMed2026

Identifying gene expression signatures for risk stratification of postoperative adjuvant chemotherapy in colorectal cancer.

Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential for guiding the use of postoperative adjuvant chemotherapy (ACT). In this study, we identified novel prognostic gene expression biomarkers in patients with pStage II CRC and developed a new risk stratification framework for ACT decision-making. First, genome-wide biomarker discovery was conducted to identify prognostic gene expression biomarkers associated with recurrence risk in pStage II CRC. This analysis identified 10 differentially expressed genes as potential biomarkers for recurrence. The efficacy of these biomarkers was then tested using 188 clinical surgical specimens obtained from patients with pStage II CRC. A predictive panel was developed using qRT-PCR and used to assess 93 clinical specimens with an area under the curve (AUC) of 0.82, and its performance was further validated in an independent cohort (n&#x2009;=&#x2009;95). By incorporating key clinicopathological features, a Gene expression-based Prediction of Recurrence in pStage II CRC (GPRSC) signature was developed, which robustly predicted postoperative recurrence (AUC: 0.80). Finally, combining the GPRSC signature, microsatellite instability status, and conventional criteria, we developed a novel risk stratification system for postoperative ACT decision-making in pStage II CRC. Overall, we identified novel gene expression biomarkers and developed a prognostic signature that informs clinical decision-making regarding postoperative ACT in patients with pStage II CRC.

Humans↗
PubMed2026

Breast Cancer Recurrence Status Assessment in 5 Years Using Multimodal Integrated Learning: A Feasibility Study.

Despite advances in breast cancer detection and treatment, recurrence after curative therapy continues to impact long-term survival and quality of life. Therefore, early identification of high-risk patients is crucial to guide personalized treatment and follow-up strategies. Although genomic assays provide valuable prognostic insights, their high cost and limited accessibility hinder widespread adoption in clinical practice. Recent machine learning or deep learning approaches leveraging clinical, imaging, or multimodal data have shown promise but do not reflect real-world clinical scenarios. This study proposes a deep learning-based multimodal framework for predicting 5-year breast cancer recurrence using routinely collected clinical data. The framework consists of three main components. First, we adopted automated tumor segmentation with MedSAM to extract the tumor region from ultrasound images. The radiomics features are extracted from those tumor regions. Second, report features are extracted using a Med-Contrastive Pre-trained Transformers (MedCPT)-based approach incorporating predefined, clinically informed queries. Third, a multimodal integration model jointly processes image, radiomics, clinical features, and report features through modality-specific branches. The image branch employs the Ultrasound Foundation Model (USFM) as the backbone, while structured tabular data is processed using the FT-Transformer architecture. The features of all branches are fused using a mixture-of-experts (MoE)-based classifier, and the entire model is trained using a progressive fusion training strategy. Experimental results confirm the feasibility of using ultrasound images with tumor mask integration for recurrence prediction and demonstrate the additive value of integrating multiple data modalities through the proposed multimodal integration model. The final model for recurrence prediction achieved an AUC of 0.7540, accuracy of 74.61%, sensitivity of 70.41%, and specificity of 76.44%. This feasibility study's findings underscore the potential of the proposed multimodal deep learning framework to provide accessible, accurate, and generalizable recurrence risk prediction using routinely available clinical data, potentially supporting more informed treatment decisions and personalized post-treatment monitoring in real-world clinical practice.

Breast cancer recurrence↗
PubMed1979

Predictability of present outcome and future recurrence in acute pancreatitis.

Although acute pancreatitis is relatively common, factors useful in predicting immediate outcome or likelihood of recurrence have seldom been studied in greater detail. A ten-year experience with 389 patients hospitalized for 821 separate episodes of acute pancreatitis was reviewed. The overall mortality was 6.7%, being highest on the first admission and considerably greater for white males. Respiratory complications accounting for 27% of the fatalities were the most common causes of death. The incidence of considerable morbidity was 19.5%. Clinical diagnoses of "shock" and "respiratory distress" were associated with mortalities of 88% and 71%, respectively. The overall recurrence rate was 50.1%, with little variation regardless as to the number of previous bouts. Recurrence was more likely if the patient was black, male, older than 30 years of age, and had experienced a second episode of acute pancreatitis. Admission data aid considerably in identifying high-risk patients in whom major complications develop, who die during the present episode, or who have a future recurrent bout of acute pancreatitis.

Acute Disease↗
PubMed1979

Systolic time intervals before and after cardioversion of atrial fibrillation.

The effect of cardioversion of atrial fibrillation to normal sinus rhythm on systolic time intervals was evaluated in 18 patients. Variable results in the left ventricular ejection time index, the external isovolumic contraction time (EICT), and the ratio of the left ventricular ejection time over the EICT (LVET/EICT) and shortening of the preejection period (PEP) (P less than 0.01), the PEP index (PEPI) (P less than 0.005), and the ratio of PEP/LVET (P less than 0.001) occurred at five hours after cardioversion. Six (33 percent) of the 18 patients developed recurrent atrial fibrillation within one month after cardioversion, and the hearts of 12 (67 percent) of the 18 patients remained in sinus rhythm for one to ten months after cardioversion. Four of five patients in whom the EICT became worse at five hours after cardioversion and two of two patients in whom the PEPI became worse at five hours after cardioversion developed recurrent atrial fibrillation. The EICT and PEPI at five hours after cardioversion may be helpful in predicting subsequent recurrence of atrial fibrillation.

Aged↗
PubMed2024

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Meningioma↗
PubMed1976

Blastformation rate of peripheral blood lymphocytes before and after recurrence of cancer.

Following curative resection for gastrointestinal cancer, it has been demonstrated that the blastformation rate rises slightly 3-4 months before the recurrence of cancer and that, during the two months prior to recurrence, the blastformation rate of peripheral blood lymphocytes to PHA decreases rapidly. The blastformation rate, therefore, if monitored routinely postoperatively, should be a significant improvement in predicting any recurrence of the cancer.

Gastrointestinal Neoplasms↗
PubMed2026

Unveiling novel transcriptomic prognostic biomarkers for specific breast cancer subtypes and treatment regimens.

BACKGROUND: Breast cancer (BRCA) is the most common cancer in women worldwide, yet current gene expression panels offer limited insight into treatment responses across different subtypes and therapies. This study aimed to identify reliable biomarkers for predicting treatment outcomes in specific BRCA subtypes and treatment regimens. METHODS: This study analyzed transcriptomic data from The Cancer Genome Atlas to identify differentially expressed genes (DEGs) in patient groups treated with different combinations of hormone therapy (H), chemotherapy (C), radiotherapy (R), and targeted therapy (T). Non-negative matrix factorization clustering was performed to stratify patients into clusters representing different BRCA subtypes. Functional enrichment analysis was performed, and survival assessments were conducted using the METABRIC dataset. RESULTS: A total of 1,148 DEGs were identified across treatment regimens, with 75 common DEGs shared across multiple regimens. Among these, 12 candidate biomarkers were associated with luminal subtypes treated with H, including LRP1B, of which high expression predicted cancer recurrence. In triple-negative breast cancer (TNBC) treated with C, 76 candidate biomarkers were identified, including TTYH1 for recurrence and ANXA8L1 and MPZ for non-recurrence. Functional analyses identified intermediate filament organization and keratinization as pathways associated with specific candidate biomarkers of TNBC following C. Survival analysis using METABRIC strengthened the prognostic ability of LRP1B and TTYH1 to predict worse survival and ANXA8L1 and MPZ to predict prolonged survival, with four additional prognostic biomarkers. CONCLUSION: This study identified gene expression prognostic biomarkers for luminal and TNBC subtypes, thereby supporting personalized therapies. Further experimental validation is required to confirm these findings for clinical application. CLINICAL TRIAL REGISTRY: No.

Breast cancer↗
PubMed1979

The prognostic value of cell surface antigens in low grade, non-invasive, transitional cell carcinoma of the bladder.

Tumors in 23 patients who presented with a low grade, non-invasive transitional cell carcinoma of the bladder were studied for blood group antigens A, B or O on the cell surface. Of 14 patients without cell surface antigens initially 13 suffered an invasive tumor subsequently and 1 had diffuse carcinoma in situ. Of 9 patients with cell surface antigens initially 8 did not have an invasive recurrence during a 5 or more-year followup and 1 did. The presence or absence of blood group cell surface antigen on a low grade, non-invasive transitional cell carcinoma of the bladder would seem to have value in predicting future recurrence with muscle invasion.

ABO Blood-Group System↗
PubMed1977

Monitoring immunotherapy with Bacillus Calmette-Guérin by antibody titer.

Antibody titer to Bacillus Calmette-Guérin (BCG) was determined by complement fixation in 111 normal volunteers and 83 melanoma patients. In 43 of these melanoma patients, sequential determination of antibody titer was made and correlated with clinical course. Low titers of antibody to BCG were found frequently in normal volunteers and in melanoma patients prior to BCG immunotherapy. The typical response to BCG immunotherapy was a rapid rise of antibody titer to high levels. Six of 19 patients with recurrence had disappearance of antibody preceding clinical recurrence by up to 5 months. In 13 of 40 patients receiving BCG, serum antibody was a better indicator of the patient's response than measurement of delayed cutaneous hypersensitivity to purified protein derivative. These results suggest that measurement of the antibody response to BCG may be useful in developing an optimum mode of BCG immunotherapy as well as predicting clinical recurrence in patients with melanoma.

Antibodies, Bacterial↗
PubMed1978

Hypoplastic left heart in a patient with 45,X/46,XX/47,XXX mosaicism.

Recurrence risks for primary congenital heart lesions are well defined. An infant with hypoplastic left heart syndrome is observed to have a short neck with a full skin fold on the right side, unilateral single palmar crease, and whorls on all ten fingers. She was found to have the Ullrich-Turner syndrome with mosaicism 45,X/46,XX/47,XXX. We believe the cardiac malformation was secondary to her aneuploidy. This could have important implications for prediction of recurrence risks to the parents. Chromosomal tests may be indicated for infants were severe congenital cardiac lesions, based on subtle clinical findings.

Female↗