Long noncoding RNAs (lncRNAs) are emerging as critical regulators of tumor initiation and progression through transcriptional and posttranscriptional mechanisms. UPK1A antisense RNA 1 (UPK1A-AS1), a cancer-associated lncRNA, has been reported to participate in oncogenic processes; however, its overall landscape across human malignancies and its biological role in therapy resistance remain poorly understood. Given the increasing importance of identifying functional lncRNAs with prognostic and therapeutic potential, this study presents a comprehensive multiomics characterization of UPK1A-AS1 and its experimental validation in hepatocellular carcinoma (HCC). We integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression Project (GTEx), the cancer immunology data engine (CIDE), and the cBioPortal for cancer genomics (cBioPortal) to systematically assess its expression pattern, genomic alterations, clinical significance, and immunological associations. Our analyses revealed that UPK1A-AS1 is significantly upregulated in multiple tumor types, with copy-number amplification as the predominant genomic alteration driving its overexpression. Elevated UPK1A-AS1 expression was correlated with advanced disease stage, poor differentiation, immune exclusion, and unfavorable prognosis, supporting its potential as a cancer type-dependent biomarker. In parallel, functional studies demonstrated that hypoxia transcriptionally induces UPK1A-AS1 in HCC, where it promotes sorafenib resistance by suppressing apoptosis. Silencing UPK1A-AS1 restored apoptotic and enhanced sorafenib efficacy both in vitro and in vivo. Collectively, our findings suggest that UPK1A-AS1 is a hypoxia-inducible oncogenic lncRNA that plays dual roles in cancer, with cancer type-dependent associations with progression and immune modulation across malignancies and mechanistically mediating hypoxia-associated drug resistance in HCC.
INTRODUCTION:There is no specific therapy for triple-negative breast cancer (TNBC), and the recurrence rate is high. Cancer stem cells (CSCs) play an important role in cancer chemoresistance and metastasis, but there is no consensus marker in this type of cancer. The aim of this study was to identify CSC biomarkers in the plasma secretome of TNBC patients. METHODS:CD44+/CD24- CSCs were isolated from MDA-MB-436 and MDA-MB-231 (ATCC) lines by magnetic immunoselection. The extracellular vesicles (EVs) of CSCs were isolated by size exclusion chromatography (SEC) of conditioned medium (CM) without fetal bovine serum (FBS) and blood plasma from TNBC and healthy women. Tetraspanins CD9 and CD81 identified the EVs, while electron microscopy determined the morphology and tunable resistive pulse sensing (TRPS) established particle size. Luminex technology was used to determine the presence of L1 cell adhesion molecule (L1CAM), carbonic anhydrase IX (CA9), mesothelin, midkine, hepsin, kallikrein-6 (KLK6), transglutaminase 2 (TGM2), aldehyde dehydrogenase 1a1 (ALDH1A1), epithelial cell adhesion molecule (EpCAM), and differentiation cluster 44 (CD44). RESULTS:Particles of 0-200 nm in size were more frequent in CSC-MDA-MB-436, while particles of 201-500 nm were more frequent in CSC-MDA-MB-231. In blood plasma, the particle size was 150-250 nm in TNBC patients and 150-300 nm in healthy individuals. Particle concentrations were 1.3 × 1010 in CSCs of the MDA-MB-231 (CSC-MDA-MB-231) cell line and 3.8 × 107 in the MDA-MB-231 cell line (L-MDA-MB-231). The concentration of CSCs in MDA-MB-436 was 2.7 × 108 compared to 9.4 × 107 in L-MDA-MB-436. Midkine and CA9 were present in the EVs of both CSC lines and in the plasma of women with TNBC but absent in the blood plasma of healthy women. Midkine showed better statistical discrimination. CONCLUSIONS:The size and concentration of EVs are heterogeneous. Midkine and CA9 are produced by CSCs in women with TNBC and may be possible biomarkers of these cells in this tumour type.
BACKGROUND:Whole-slide imaging (WSI) has shifted pathology toward digital workflows, creating the foundation for applying artificial intelligence (AI) to diagnostic tasks. This review summarises validated AI applications in diagnostic pathology, with an emphasis on clinical performance, regulatory developments and the practical barriers that affect implementation. METHODS:A structured search of PubMed, Scopus and Google Scholar identified English-language, peer-reviewed studies from January 2020 to May 2025. Eligible studies applied AI to diagnostic, grading or prognostic tasks in human tissue, used a pathologist-confirmed reference standard and included external or multi-centre validation. RESULTS:More than 150,000 digital slides were represented across the included studies. Reported performance metrics demonstrated strong diagnostic accuracy across several validated applications. Large meta-analyses and externally validated studies reported sensitivity values exceeding 96% and specificity above 93% for selected cancer-detection tasks, while other studies demonstrated high agreement for Gleason grading (QWK up to 0.862) and biomarker quantification (Ki-67 ICC 0.98). CONCLUSION:AI has the capacity to strengthen diagnostic pathology by improving consistency, measurement and efficiency. Moving from experimental use to routine reporting will require broad validation across centres, enhanced model transparency, strong quality-assurance systems and close cooperation between developers and pathologists.
BACKGROUND:Human papillomavirus (HPV) infection is a major contributor to cervical cancer (CC), yet the molecular mechanisms driving HPV-associated immune evasion remain largely undefined. METHODS:Bulk RNA-seq (The Cancer Genome Atlas [TCGA]-CESC) and single-cell RNA-seq datasets (GSE171894, GSE197461) were analyzed to elucidate transcriptional and immune landscape differences between HPV-positive and HPV-negative cervical tumors. Differentially expressed genes (DEGs) were identified using DESeq2. Functional enrichment analyses were conducted through gene set enrichment analysis (GSEA), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) methodologies. Immune evasion feature genes were selected employing LASSO, Random Forest, and SVM-RFE techniques. Regulatory networks for transcription factors and miRNAs were constructed. Immune infiltration was evaluated using CIBERSORT and ssGSEA. Validation of key signature genes was performed in CC cell lines (HeLa, SiHa, C33A, and W12) via real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot. The functional roles of IFNGR1 were examined through siRNA-mediated knockdown, complemented by CCK-8, colony formation, Transwell migration/invasion, and flow cytometry apoptosis assays. RESULTS:A total of 6266 DEGs effectively differentiated HPV-positive from HPV-negative tumors. HPV-positive tumors exhibited enrichment in viral infection and immune response pathways, while HPV-negative tumors demonstrated activation of oncogenic signaling. Machine learning algorithms identified IFNGR1, TRADD, and PSMB9 as immune evasion feature genes associated with HPV. Regulatory network analysis emphasized IRF1/IRF2 and several miRNAs as critical modulators. Immune infiltration analysis indicated increased infiltration of Dendritic and Plasma cells in HPV-positive tumors, correlating with TRADD expression. Kaplan-Meier analysis further showed a trend toward worse overall survival among HPV-positive patients with high IFNGR1 expression (hazard ratio [HR] = 1.78, 95% confidence interval [CI]: 0.86-3.68; log-rank p = 0.113). Notably, IFNGR1 was significantly upregulated in HPV-positive CC cell lines at both mRNA and protein levels. IFNGR1 knockdown markedly inhibited proliferation, colony formation, migration, and invasion, while enhancing apoptosis in HeLa and SiHa cells, thereby confirming its essential role in the progression of HPV-associated CC. CONCLUSION:This study identified IFNGR1 as a key immune evasion-related gene in HPV-positive CC, elucidating its regulatory network and functional contributions, while positioning it as a potential therapeutic target for HPV-associated tumors.
BACKGROUND:Heterotopic ossification (HO) represents a highly active research field in pathological bone formation. Despite substantial advancements, a comprehensive understanding of its underlying mechanisms and clinical trajectory remains incomplete. MATERIALS AND METHODS:A bibliometric and machine-learning latent Dirichlet allocation (LDA) analysis was performed using data retrieved from the Web of Science Core Collection database. RESULTS:A total of 4722 publications related to HO were identified. The most prolific countries included the USA, CHINA, GERMANY, the UK, JAPAN, SOUTH KOREA, ITALY, TURKEY, FRANCE, and CANADA . GERMANY demonstrated the highest citation strength, followed by CHINA . Aside from "heterotopic ossification," other frequently occurring author keywords included "fibrodysplasia ossificans progressive," "complications" and "total hip arthroplasty." In keywords plus, besides HO, replacement, bone-formation, and arthroplasty were the most frequently occurring terms. Institutional network analysis with subject-specific clustering indicated that Shanghai Jiao Tong University was significantly enriched in radiology, nuclear medicine and medical imaging, while Wilderness Spine Serv specialized in surgical management. A developmental timeline plot of a network of most contributing authors also was visualized, along with the most influential references. Meanwhile, citation analysis indicated that Kaplan FS and Shore EM were the top-cited authors. By LDA analysis, a total of 16 key topics were identified in this field with distinct period-proportion visualization. One of the topics, cell bone express differentiation and formation has clearly dominated the last 10 years. CONCLUSION:This study constitutes the most extensive text processing analysis of HO to date, offering valuable insights and directions for future development.
INTRODUCTION:Colposcopy plays a central role in the evaluation of cervical intraepithelial lesions; however, its diagnostic performance varies widely. While high sensitivity is desirable, low specificity may lead to unnecessary excisional procedures. This study aimed to evaluate the diagnostic performance of colposcopy and its potential contribution to overtreatment in a tertiary referral center. METHODS:This retrospective single-center study included 150 patients who underwent LEEP between April 2023 and September 2024. Colposcopic impressions were compared with LEEP histopathological outcomes. Sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratios were calculated. A subgroup analysis was performed for HPV16-positive patients. RESULTS:Colposcopy demonstrated high sensitivity (93.9%, 95% CI: 87.3-97.4) but low specificity (31.4%, 95% CI: 20.2-45.0), with an overall accuracy of 72.7% (95% CI: 65.0-79.2). The PPV and NPV were 72.6% (95% CI: 64.2-79.7) and 72.7% (95% CI: 51.9-86.9), respectively. The positive and negative likelihood ratios were 1.37 and 0.19. Notably, 35 patients (23.3%) were false positives. In HPV16-positive patients, sensitivity was 80.8% (95% CI: 71.7-87.5), specificity was 33.3% (95% CI: 21.9-47.1), and accuracy was 64.7% (95% CI: 56.7-72.0). CONCLUSION:Although colposcopy is highly sensitive, its low specificity may result in substantial overtreatment, particularly in tertiary referral settings.
Colorectal cancer (CRC) remains a formidable global health challenge, characterized by uncontrolled cell proliferation and significant socioeconomic burden. Projections anticipate a substantial increase in new cases, straining healthcare systems worldwide. CRC, the most common histological subtype, originates from gland cells lining the colon and rectum, often preceded by benign polyps. Its development is complex, influenced by sporadic, familial, and inherited factors. Sporadic cases, accounting for 70%-80%, are linked to genetic mutations and epigenetic alterations, with lifestyle factors like physical inactivity, diet, obesity, smoking, and alcohol consumption playing significant roles. Familial cases (25%) suggest shared environmental influences, while inherited conditions (5%) like familial adenomatous polyposis (FAP) and Lynch syndrome involve germline mutation with high lifetime CRC risk. The molecular pathogenesis of CRC involves genomic instability, notably chromosomal instability (CIN), microsatellite instability (MSI), and the CpG island methylator phenotype (CIMP). Mitochondria, beyond ATP production, critically influence cellular processes. The mitochondrial metabolic theory (MMT) proposes impaired oxidative phosphorylation (OxPhos) drives genomic instability. While the Warburg effect is recognized, many tumors retain functional oxidative metabolism, often relying heavily on OxPhos. Key genetic mutations like KRAS and BRAF significantly impact CRC, influencing mitochondrial metabolism and tumor progression, and are associated with different prognostic outcomes. Emerging therapeutic strategies target metabolic vulnerabilities to overcome chemoresistance. Inhibition of mitochondrial genes and key enzymes, along with modulating calcium homeostasis, shows promise. Preclinical research highlights sorghum extracts as potential therapeutic agents. High-phenolic sorghum bran extracts demonstrate anticancer action by suppressing proliferation, inducing apoptosis, and inhibiting migration and invasion. These effects involve targeting specific cancer pathways and influencing proteins like those in the Ras-ERK pathway, β-catenin, cMyc, cyclin D1, and surviving. Specific sorghum compounds like anthocyanidins, luteolin, and quercetin exhibit cytotoxicity against CRC cells, including those with KRAS and BRAF mutations. Further research is crucial to translate these preclinical findings into clinical applications, understand bioavailability, and account for individual differences in gut microbiota.
BACKGROUND:Intratumor heterogeneity (ITH) plays an important role in patients' clinical outcomes. The prognostic impact of ITH and its influencing factors is unclear in papillary thyroid carcinoma (PTC), which deserves further investigation. METHODS:The Mutation Annotation Format (MAF) and clinical features were collected from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) cohort. We first assessed the influence of ITH on the prognosis of patients. We used the Mutant Allele Tumor Heterogeneity score to evaluate and represent ITH. Then we explored the potential factors associated with ITH. Finally, we predicted possible pathways involved in ITH. RESULTS:Among 4 prognostic outcomes, higher ITH was mainly related to poor disease-free interval (DFI) (HR = 2.64, p = 0.01), and ITH had potential value for predicting DFI. Further, we identified BRAF mutation and thyroid differentiation score (TDS) as key factors independently influencing ITH (all p < 0.05), especially TDS, which had a favorable ability and obtained good net benefit in predicting ITH. TDS maintained a stable negative effect on ITH. In contrast, BRAF mutation positively correlated with ITH in univariable regression (β = 0.196). Through performing sensitivity, regression, subgroup, interaction effect, and mediation analyses, we identified that TDS played a suppression effect in the impact of BRAF mutation on ITH. Finally, we revealed that the propionate metabolism pathway was most strongly associated with ITH. CONCLUSIONS:ITH is associated with DFI in patients with PTC and deserves more attention. TDS and BRAF mutation are the key influencing factors of ITH, but TDS exerts a suppression effect on the impact of BRAF mutation on ITH.
BackgroundDiffuse large B-cell lymphoma (DLBCL) is a malignant neoplasm characterized by intermediate to high aggressiveness and heterogeneity. Chemokines and their receptors are involved in various antitumor and protumor immune processes in vivo and influence patient prognosis and treatment response. Therefore, investigating the potential associations between chemotactic cytokine-related genes (CCRGs) and prognosis, as well as the immune microenvironment in DLBCL holds significant importance.MethodsDifferentially expressed and prognosis-related CCRGs in DLBCL were extracted from the GEO database. A prognostic risk model was constructed using Lasso-Cox regression analysis, followed by internal and external cohort validation to assess the model's predictive independence. This risk model was then applied to immunological analysis, enrichment analysis, and drug prediction analysis. Single-cell sequencing was employed to investigate the correlation between genes in the prognostic model and immune cell types.ResultsWe identified 23 prognosis-related CCRGs and revealed two CCRG-associated subtypes exhibiting distinct immune processes. Subsequently, a six-gene prognostic model was established using LASSO-Cox regression analysis. Univariate and multivariate prognostic analyses demonstrated that the risk model serves as an independent prognostic factor, and both the CCRG prognostic model and signature genes showed a significant correlation with the tumor immune microenvironment (TIME).ConclusionThe CCRG risk model proposed in this study can accurately and stably predict the prognosis of DLBCL patients and is closely associated with the TIME, providing new targets and theoretical support for DLBCL patients.
BACKGROUND:Long non-coding RNA PAR5 (lncRNA-PAR5) is downregulated in glioma and has been confirmed to inhibit glioma progression; however, the specific regulatory mechanism underlying its downregulation remains unclear. OBJECTIVE:This study aimed to investigate the key molecular mechanism by which PAR5 inhibits glioma progression, with a focus on the regulatory role of m6A modification. METHODS:Potential m6A modification sites in the PAR5 sequence were predicted using the SRAMP online tool. The expression profiles of m6A regulatory genes in glioblastoma were analyzed via the GEPIA database. RNA pull-down, RIP-qPCR, and MeRIP-qPCR were employed to validate the specific binding of YTHDF3 to PAR5 and its effect on the m6A modification level of PAR5. The expression of PAR5 and YTHDF3 was modulated by cell transfection, and cell proliferation, invasion, and migration were assessed using CCK-8, Transwell, and wound healing assays, respectively. Further in vivo functional validation was performed using a subcutaneous xenograft tumor model in nude mice. RESULTS:lncRNA-PAR5 significantly inhibited the proliferation, invasion, and migration of glioma cells. Bioinformatics analysis and experimental validation revealed that the m6A reader protein YTHDF3 is highly expressed in glioma, specifically recognizes and binds to PAR5, and promotes PAR5 degradation by enhancing its m6A modification level, thereby negatively regulating PAR5 expression. Functional experiments demonstrated that YTHDF3 plays a pro‑oncogenic role, while knockdown of YTHDF3 suppressed malignant phenotypes of glioma, an effect that could be partially reversed by simultaneous knockdown of PAR5. In vivo experiments further confirmed that YTHDF3 knockdown inhibits tumor growth by upregulating PAR5. CONCLUSION:YTHDF3 promotes glioma cell proliferation, invasion, and migration by inhibiting PAR5 expression through enhancing its m6A modification. This study reveals the critical role of the YTHDF3/PAR5 axis in glioma progression and provides a potential novel target for glioma‑targeted therapy.
BACKGROUND:Not enough is known about how ophiopogonin D (OP-D) works and the molecular mechanisms involved in nonalcoholic steatohepatitis (NASH). This study aimed to investigate the antifibrosis effect and underlying mechanism of OP-D in NAFLD. METHODS:The rats were fed a high-fat diet (HFD) to simulate NAFLD. After OP-D treatment or not, the rat serum lipid levels and inflammatory and ferroptosis-related factors were detected. Online databases and network pharmacology were used to collect the targets of OP-D against NASH. The effect of OP-D on AKT1, STAT3, ferroptotic markers, and fibrotic markers was determined using western blot or PCR assays. RESULTS:OP-D inhibited abnormal liver function, fibrotic markers (α-SMA/Col1α1), and ferroptosis-related factor (GPX4) in NASH rats. Network pharmacology proposed AKT1 and STAT3 as targets for OP-D against NASH. OP-D reduced the p-AKT and p-STAT3 in liver tissues. OP-D reduced the levels of AKT1, STAT3, and HIF-1α in model hepatic stellate cells. AKT1 and STAT3 overexpression reversed the antifibrosis and ferroptosis-induced effects of OP-D in model hepatic stellate cells. CONCLUSION:OP-D may alleviate fibrosis in NASH by regulating ferroptosis via the AKT1/STAT3/HIF-1α axis.
Naegleria fowleri, the brain-eating ameba, causes primary amebic meningoencephalitis (PAM), a fatal infectious disease that affects the central nervous system (CNS). We aimed to evaluate the functions and potential drugs targeting PAM using text mining and bioinformatics analyses. PAM-associated genes were identified using a disease database and mined from literature. To identify candidate drugs targeting PAM, 218 genes were analyzed using PanDrugs, drug Manually Annotated Targets and Drugs Online Resource (MATADOR), and the drug Comparative Toxicogenomics Database (CTD) by text mining. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional analyses were performed to examine the mechanism of action of PAM. The GO functions of genes involved in PAM identified by text mining were leukocyte differentiation and the regulation of cytokine production. Disease-related PAM analyses indicated association with Zellweger syndrome, peroxisomal disease, periodontitis, and leishmaniasis. KEGG enrichment included pathways related to inflammatory bowel disease, malaria, interleukin (IL)-17 signaling pathway, Yersinia infection, Chagas disease, amebiasis, rheumatoid arthritis, pathogenic Escherichia coli infection, lipids, atherosclerosis, and peroxisomes. In addition, arsenic trioxide, bortezomib, dasatinib, bosutinib, bevacizumab, paclitaxel, midostaurin, tamoxifen, copanlisib, and pazopanib were identified as potential drugs targeting PAM using PanDrugs software. Our analyses revealed that text mining-related PAM genes were enriched in several pathways, such as peroxisomes and protein localization. We suggest that PAM is linked to other diseases, such as Zellweger's syndrome, leishmaniasis, and periodontitis, and provide potential drugs for effective treatment.
BACKGROUND:Hepatocellular carcinoma (HCC) is a global malignant tumor type. Pyrroline-5-carboxylate reductase 1 (PYCR1) is a metabolic enzyme that exhibits pro-tumor properties in cancer progression. However, the exact molecular mechanism of PYCR1 in HCC progression is still unclear. METHODS:CCK8, EdU, and Transwell assays were used to measure the proliferation, migration, and invasion of HCC cells, respectively. Immunostaining and flow cytometry were used to detect cellular autophagy and apoptosis. RESULTS:The downregulation of PYCR1 can inhibit the survival, proliferation, migration, and invasion of HCC cells. At the same time, downregulation of PYCR1 induces autophagy and subsequently activates cell apoptosis. Therefore, we pretreated HCC cells with mTOR activators or inhibitors to inhibit or promote autophagy, leading to an inhibition or an increase in apoptosis. Simultaneously, the PI3K activators or inhibitors to activate or inhibit the PI3K/AKT/mTOR pathway also lead to inhibition or activation of autophagy and apoptosis. CONCLUSION:The downregulation of PYCR1 induces autophagy-dependent apoptosis in HCC cells by inhibiting the PI3K/AKT/mTOR pathway, revealing a novel mechanistic link in HCC pathophysiology.
Gliosarcoma (GS) is a rare and aggressive variant of glioblastoma multiforme (GBM), characterized by a biphasic histopathological pattern featuring both glial and mesenchymal components. Accounting for 2% of all GBM cases, this brain tumor is known for its poor prognosis, rapid progression, and resistance to conventional treatments. Despite advances in molecular profiling and multimodal treatment strategies, GS remains a therapeutic challenge due to their highly invasive nature and limited response to standard regimens. The purpose of this study was to characterize the neuroradiological, surgical, clinicopathological, and radiotherapeutic profiles of a cohort of patients affected by GS, including two recurrences of disease.
