Non-invasive prenatal testing (NIPT) based on fetal free DNA is a non-invasive technique to screen for common fetal aneuploidies by analyzing cell-free fetal DNA (cffDNA) in the peripheral blood of pregnant women. This technique has opened a new era of prenatal screening for its high safety and reliability. In recent years, it has been shown that NIPT can not only screen for fetal aneuploidies, but may also reveal maternal genomic abnormalities. The incidental detection of maternal tumors has aroused widespread concern in the clinical settings. The aim of this review is to systematically summarize the research progress of NIPT technique in incidental detection of maternal tumors, and to discuss its clinical significance, technical challenges, and future development direction. It has been found that multiple chromosome aneuploidies (MCAs) in NIPT detection is one of the important biomarkers suggesting occult maternal malignant tumors. In this paper, the relevant progress of NIPT technique in the incidental discovery of maternal tumors were reviewed in order to provide a reference for individualized and standardized application of NIPT technique in maternal health monitoring.
Humans ; Female ; Pregnancy ; Cell-Free Nucleic Acids/blood* ; Prenatal Diagnosis/methods* ; Incidental Findings ; Neoplasms/genetics* ; Noninvasive Prenatal Testing/methods* ; Aneuploidy ; Fetus/metabolism*

Lung cancer is a leading cause of cancer-related deaths worldwide, with its high mortality rate primarily attributed to delayed diagnosis. Radiomics, by extracting abundant quantitative features from medical images, offers novel possibilities for early diagnosis and precise treatment of lung cancer. This article reviewed the latest advancements in radiomics for lung cancer management, particularly its integration with artificial intelligence (AI) to optimize diagnostic processes and personalize treatment strategies. Despite existing challenges, such as non-standardized image acquisition parameters and limitations in model reproducibility, the incorporation of AI significantly enhanced the precision and efficiency of image analysis, thereby improving the prediction of disease progression and the formulation of treatment plans. We emphasized the critical importance of standardizing image acquisition parameters and discussed the role of AI in advancing the clinical application of radiomics, alongside future research directions.
Humans ; Lung Neoplasms/diagnosis* ; Artificial Intelligence ; Early Detection of Cancer/methods* ; Precision Medicine ; Image Processing, Computer-Assisted/methods* ; Tomography, X-Ray Computed ; Radiomics

Thyroid nodules are a common endocrine disorder, and their early detection and accurate diagnosis are crucial for the prevention of thyroid cancer. However, the highly heterogeneous morphology and boundaries of thyroid nodules pose significant challenges to their precise identification and classification. Traditional diagnostic approaches rely heavily on physicians' experience, which increases the risk of misdiagnosis and missed diagnoses. With the rapid advancement of computer-aided diagnosis (CAD) technologies, applying deep learning algorithms to the analysis of thyroid nodule ultrasound images has shown great potential. This paper reviews the latest research progress on deep learning-based CAD methods for thyroid nodules, with a focus on their applications in image preprocessing, segmentation and classification. The advantages and limitations of current techniques are analyzed, and potential future directions are discussed. This review aims to highlight the potential of deep learning in thyroid nodule diagnosis and to provide a foundation for selecting feasible pathways for future clinical applications.
Humans ; Thyroid Nodule/diagnostic imaging* ; Deep Learning ; Ultrasonography/methods* ; Diagnosis, Computer-Assisted/methods* ; Algorithms ; Thyroid Neoplasms/diagnostic imaging* ; Image Processing, Computer-Assisted/methods*

Objective To investigate the clinical relevance and diagnostic or prognostic value of ST3β-galactoside α-2, 3-sialyltransferase 1 (ST3GAL1) in glioma and to confirm its role in promoting malignant phenotypes. Methods Using data from The Cancer Genome Atlas (TCGA) database, we analyzed the correlation between ST3GAL1 expression levels in glioma and clinical parameters to evaluate its diagnostic and prognostic value. The impact of ST3GAL1 on malignant phenotypes of glioma cells-including proliferation, cell cycle progression, apoptosis, and invasion was further validated through ST3GAL1 knockdown experiments. Results The expression level of ST3GAL1 was significantly higher in glioma tissues compared to healthy brain tissues and showed a strong correlation with clinical characteristics of glioma patients. Survival analysis and receiver operating characteristic (ROC) curve demonstrated that ST3GAL1 could serve as a potential diagnostic and prognostic biomarker for glioma. Knockdown of ST3GAL1 suppressed proliferation, invasion, and migration capabilities of glioma cell lines, and induced G1-phase cell cycle arrest. Conclusion ST3GAL1 promotes malignant phenotypes in glioma and plays a critical role in its malignant progression, suggesting its potential as a biomarker for glioma diagnosis and prognosis.
Humans ; Sialyltransferases/metabolism* ; Glioma/diagnosis* ; Cell Proliferation/genetics* ; Cell Line, Tumor ; Brain Neoplasms/enzymology* ; beta-Galactoside alpha-2,3-Sialyltransferase ; Disease Progression ; Prognosis ; Cell Movement/genetics* ; Apoptosis/genetics* ; Male ; Female ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/metabolism* ; Middle Aged

The early diagnosis and precise treatment of esophageal squamous cell carcinoma (ESCC) hold significant clinical value in improving patient survival rate. Current diagnostic methods for early-stage ESCC primarily rely on invasive procedures and endoscopy, which can cause discomfort and financial burden for patients. Therefore, non-invasive biomarkers with high sensitivity and specificity present a more suitable alternative for early tumor diagnosis. Tumor associated autoantibodies (TAAb), identified as potential biomarkers, have considerable clinical implications for the early diagnosis, treatment monitoring, and prognosis assessment of ESCC. Here in we aim to summarize recent research on ESCC-related autoantibodies, including their background, types and development, analyze the potential of those autoantibodies in clinical diagnosis, treatment monitoring, and prognosis assessment, and also discuss the limitations of existing research and future directions. The goal is to provide a theoretical foundation for the early diagnosis and personalized treatment of ESCC.
Humans ; Autoantibodies/immunology* ; Esophageal Neoplasms/therapy* ; Esophageal Squamous Cell Carcinoma/immunology* ; Biomarkers, Tumor/immunology* ; Prognosis ; Carcinoma, Squamous Cell/diagnosis* ; Animals

Objective TXN is a thioredoxin (TXN) that participates in many redox reactions and plays a crucial role in various signaling pathways. However, the role of TXN in many cancers is still unclear. The objective of this study is to investigate and visualize the diagnostic, prognostic, and immunological implications of TXN expression across various cancer types. Methods The clinical data were downloaded from the cancer genome mapping project(TCGA) database to analyze the expression level of TXN in pan cancer, and the expression level was preliminarily verified by human protein mapping (HPA)(https://www.proteinatlas.org/)database. The ESTIMATE algorithm and CIBERSORT algorithm were applied to calculate the correlation between TXN expression and immune cell infiltration. The correlation between TXN and microsatellite instability (MSI) and tumor mutation burden (TMB) was analyzed using Spearman method. Gene Set Enrichment Analysis (GSEA) is used for gene biology functional analysis and sensitivity analysis of genes to pan cancer therapeutic drugs. Results TXN is highly expressed in most malignant tumors. The high expression of TXN is associated with overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression free interval (PFI) in various cancers. Moreover, TXN expression is associated with TMB, MSI, tumor microenvironment, chemotherapy sensitivity and so on. Conclusion TXN may become a potential prognostic biomarker in pan cancer, providing strong theoretical basis for future tumor diagnosis and prognosis judgment. The retinoic acid-inducible gene-I (RIG-I)-like receptor signaling pathway, Toll-like receptor (TLR) signaling pathway, and nucleotide binding oligomerization domain (NOD)-like receptor signaling pathway may be crucial pathways through which TXN influences tumor immunity.
Humans ; Prognosis ; Neoplasms/diagnosis* ; Thioredoxins/metabolism* ; Microsatellite Instability ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Mutation ; Tumor Microenvironment

The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4-12 ng ml -1 (>4 ng ml -1 and ≤12 ng ml -1 , which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4-12 ng ml -1 or PI-RADS 3 lesions.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Propensity Score ; Retrospective Studies ; Middle Aged ; Aged ; Image-Guided Biopsy/methods* ; Prostate-Specific Antigen/blood* ; Prostate/diagnostic imaging*

OBJECTIVES: To systematically review the methodological quality and measurement properties of childhood cancer-related fatigue assessment tools based on the consensus-based standards for the selection of health measurement instruments (COSMIN) guidelines, providing a basis for clinical practitioners to select appropriate assessment tools. METHODS: The databases searched included China National Knowledge Infrastructure, Wanfang Data, China Biomedical Literature, Weipu, PubMed, CINAHL, Embase, and Web of Science for studies published up to January 2024. Children under 12 years old and their primary caregivers were enrolled as subjects. Articles were screened based on inclusion criteria, and the key information regarding the assessment tools was extracted. The risk of bias checklist from the COSMIN guidelines and the quality standard rating scale were employed to evaluate measurement properties and formulate final recommendations. RESULTS: A total of 18 articles were included, covering 7 fatigue measurement tools, consisting of 4 specific tools and 3 generic tools tools. Methodological differences were observed in measurement properties across these scales. The Chinese Version of the Pediatric Patient-Reported Outcomes Measurement Information System (C-Ped-PROMIS) was rated as grade A recommendation due to its adequate content validity and internal consistency, while the remaining six scales were rated as grade B recommendation since their content validity was assessed as "insufficient" based on moderate-level evidence or higher. CONCLUSIONS The C-Ped-PROMIS scale demonstrates good reliability, validity, and cross-cultural validity as the preferred tool for measuring childhood cancer-related fatigue. The scale can serve as an auxiliary tool, and future research should focus on the applicability of various tools to enhance the effectiveness of interventions for assessing childhood cancer-related fatigue.
Humans ; Neoplasms/complications* ; Fatigue/diagnosis* ; Child

OBJECTIVES: To identify potential plasma lipidomic biomarkers that distinguish non-metastatic medulloblastoma (nmMB) from metastatic medulloblastoma (mMB) in children. METHODS: In this prospective study, 17 children with mMB and 20 matched children with nmMB were enrolled. Plasma samples were analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Lipid metabolites were evaluated for their associations and diagnostic performance. RESULTS: Orthogonal partial least squares discriminant analysis based on lipid profiles clearly separated nmMB from mMB, and 14 differential lipids were identified, including DG(18:2/20:4/0:0) and SM(d18:1/20:0). Receiver operating characteristic analysis showed nine metabolites with area under the curve greater than 0.7. Differential lipids were enriched in sphingolipid, glycerophospholipid, and arachidonic acid metabolism, suggesting an association with the metastatic phenotype. CONCLUSIONS Plasma lipidomics provides a new approach to identify mMB, and the identified lipid metabolites may support early diagnosis and treatment, prognostic assessment, and selection of therapeutic targets for metastatic medulloblastoma.
Humans ; Medulloblastoma/diagnosis* ; Lipidomics ; Child ; Male ; Female ; Child, Preschool ; Cerebellar Neoplasms/blood* ; Biomarkers, Tumor/blood* ; Neoplasm Metastasis ; Prospective Studies ; Adolescent ; Lipids/blood*

OBJECTIVES: To develop a risk prediction model for the transformation of chronic atrophic gastritis to high-grade intraepithelial neoplasia (HGIN) based on traditional Chinese medicine (TCM) syndrome patterns. METHODS: Clinical data of 201 chronic atrophic gastritis patients who visited the Second People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine and Dong'erhuan Branch between January 2022 and March 2023 were retrospectively analyzed, including 32 patients with HGIN (HGIN group) and 169 patients with moderate and severe chronic atrophic gastritis (non-HGIN group). The information of demographic characteristics, dietary habits, lifestyle factors, social and psychosocial factors, family history of tumors, medical history and comorbidities, long-term medication, endoscopic findings, histopathological examination results, as well as TCM syndrome types were collected. Potential HGIN risk factors were screened using LASSO regression, and the significant risk factors for establishing an HGIN risk prediction model were identified using logistic regression analysis. The final model was visually presented using a nomogram, and its diagnostic performance was evaluated through receiver operating characteristic curve analysis. RESULTS: Spleen-stomach Qi deficiency was the most common TCM syndrome in both HGIN and non-HGIN groups. LASSO-logistic regression model analysis showed that heavy alcohol consumption (X1), syndrome of static blood in stomach collaterals (X2), low-grade intraepithelial neoplasia (X3), high-salt diet (X4), and age (X5) were independent risk factors related to the occurrence of HGIN, and the predictive model was ln［P/(1－P)］=2.159X1+2.230X2+1.664X3+2.070X4+0.122X5- 11.096. The model demonstrated good discriminative ability, calibration, and goodness-of-fit, with area under the curve values of 0.940 and 0.891 in the training and validation sets, respectively. CONCLUSIONS The TCM syndrome of static blood in stomach collaterals shows correlation with the transformation from chronic atrophic gastritis to HGIN. The HGIN prediction model based on TCM syndrome patterns developed in the study demonstrates potential value in clinical application.
Humans ; Gastritis, Atrophic/diagnosis* ; Medicine, Chinese Traditional ; Retrospective Studies ; Female ; Male ; Middle Aged ; Stomach Neoplasms/diagnosis* ; Adult ; Risk Factors ; Carcinoma in Situ/diagnosis* ; Aged ; Nomograms ; Chronic Disease ; Logistic Models