Journal

Clinical and Experimental Medicine

Papers (14)

The association between hepatic viral infections and cancers: a cross-sectional study in the Taiwan adult population

Abstract Background Hepatitis B (HBV) and hepatitis C (HCV) viruses are diseases of global public health concern and are associated with liver cancer. Recent studies have revealed associations between hepatic viral infections and extrahepatic cancers. This study aimed to explore the associations between hepatitis B and C viruses and cancer at baseline in the Taiwan Biobank database while controlling for a wide range of confounding variables. Methods In a cross-sectional study of adults aged > 20 years, we compared the distribution of demographic factors, lifestyle, and comorbidities between viral and nonviral hepatic groups using the chi-square test. Univariate and multivariate logistic regressions were performed to observe the associations between hepatitis B and C viral infections and cancers by estimating the odds ratio (OR) and 95% confidence interval (CI). Multivariate regression analysis was adjusted for sociodemographic factors, lifestyle, and comorbidities. Results From the database, 2955 participants were identified as having HCV infection, 15,305 as having HBV infection, and 140,108 as the nonviral group. HBV infection was associated with an increased likelihood of liver cancer (adjusted OR (aOR) = 6.60, 95% CI = 3.21–13.57, P < 0.001) and ovarian cancer (aOR = 4.63, 95% CI = 1.98–10.83, P = 0.001). HCV infection was observed to increase the likelihood of liver cancer (aOR = 4.90, 95% CI = 1.37–17.53, P = 0.015), ovarian cancer (aOR = 8.50, 95% CI = 1.78–40.69, P = 0.007), and kidney cancer (aOR = 12.89, 95% CI = 2.41–69.01, P = 0.003). Conclusion Our findings suggest that hepatic viral infections are associated with intra- and extrahepatic cancers. However, being cross-sectional, causal inferences cannot be made. A recall-by-genotype study is recommended to further investigate the causality of these associations.

lncRNAs as prognostic markers and therapeutic targets in cuproptosis-mediated cancer

AbstractLong non-coding RNAs (lncRNAs) have emerged as crucial regulators in various cellular processes, including cancer progression and stress response. Recent studies have demonstrated that copper accumulation induces a unique form of cell death known as cuproptosis, with lncRNAs playing a key role in regulating cuproptosis-associated pathways. These lncRNAs may trigger cell-specific responses to copper stress, presenting new opportunities as prognostic markers and therapeutic targets. This paper delves into the role of lncRNAs in cuproptosis-mediated cancer, underscoring their potential as biomarkers and targets for innovative therapeutic strategies. A thorough review of scientific literature was conducted, utilizing databases such as PubMed, Google Scholar, and ScienceDirect, with search terms like 'lncRNAs,' 'cuproptosis,' and 'cancer.' Studies were selected based on their relevance to lncRNA regulation of cuproptosis pathways and their implications for cancer prognosis and treatment. The review highlights the significant contribution of lncRNAs in regulating cuproptosis-related genes and pathways, impacting copper metabolism, mitochondrial stress responses, and apoptotic signaling. Specific lncRNAs are potential prognostic markers in breast, lung, liver, ovarian, pancreatic, and gastric cancers. The objective of this article is to explore the role of lncRNAs as potential prognostic markers and therapeutic targets in cancers mediated by cuproptosis.

METTL3 stabilizes DDX17 mRNA via IGF2BP2-mediated m6A modification to suppress endometrial cancer progression

Endometrial cancer (EC), a type of uterine cancer, is witnessing a global increase in incidence. Despite advancement in diagnosis and treatment, metastatic or recurrent EC often exhibits a poor prognosis, necessitating novel therapeutic strategies. DEAD-box helicase 17 (DDX17) is implicated in several cancers. Our study aimed to uncover the biological function and molecular mechanism of DDX17 in EC. EC and matched adjacent normal tissues from 80 patients were analyzed; DDX17 mRNA/protein expression was quantified via RT-qPCR and immunoblotting in clinical specimens and cell lines (HEC-1A, HEC-1B, Ishikawa), with functional assays (proliferation/migration/invasion) performed following DDX17 overexpression in vitro, while xenograft modeling in BALB/c nude mice enabled in vivo validation through immunofluorescence and immunohistochemical staining; mechanistic studies employed RNA immunoprecipitation (RIP-PCR), m6A-specific RNA immunoprecipitation (MeRIP-PCR), and protein interaction analyses. DDX17 was significantly downregulated in EC tissues/cells, correlating with poor prognosis in clinical cohorts. Overexpression of DDX17 suppressed tumorigenesis both in vitro and in vivo through PI3K/AKT pathway inactivation. METTL3-mediated m6A modification stabilized DDX17 mRNA, with IGF2BP2 specifically recognizing m6A-modified transcripts. Critically, METTL3 ablation reversed DDX17 stabilization and abolished its tumor-suppressive effects, while PI3K inhibition (LY294002) phenocopied METTL3 restoration in rescuing DDX17 deficiency-induced oncogenicity. METTL3-mediated m6A modification stabilizes DDX17 to suppress EC cell proliferation, migration, and invasion through an IGF2BP2-dependent mechanism by inactivating the PI3K/AKT pathway.

Deleterious and ethnic-related BRCA1/2 mutations in tissue and blood of Egyptian colorectal cancer patients and its correlation with human papillomavirus

AbstractThis study aimed to identify BRCA1/2 mutational patterns in the tissue and blood of Egyptian colorectal cancer (CRC) patients and to study the possible correlation of this mutational pattern with Human papillomavirus (HPV) infection. Eighty-two colonoscopic biopsies and forty-six blood samples were collected from Egyptian CRC patients, as well as blood samples of age and sex-matched healthy controls (n = 43) were enrolled. The libraries were performed using Qiaseq Human BRCA1 and BRCA2 targeted DNA panel and sequenced via Ion proton sequencer. Also, the CRC tissues were subjected to conventional PCR targeting the HPV Late 1 (L1) region. Our analysis revealed that the BRCA-DNA damage pathway had been altered in more than 65% of the CRC patients. Comparing tissue and blood samples from CRC patients, 25 somatic mutations were found exclusively in tissue, while 41 germline mutations were found exclusively in blood. Additionally, we identified 23 shared BRCA1/2 pathogenic (PVs) mutations in both blood and tissue samples, with a significantly higher frequency in blood samples compared to tissue samples. The most affected exon in BRCA1 was exon 10, while the most affected exons in BRCA2 were 11, 14, 18, 24, and 27 exons. Notably, we revealed an ethnic-related cluster of polymorphism variants in our population closely related to South Asian and African ethnicities. Novel PVs were identified and submitted to the ClinVar database. HPV was found in 23.8% of the CRC tissues, and 54% of HPV-positive cases had somatic BRCA1/2 PVs. The results of this research point to a possible connection between infection with HPV and BRCA1/2 mutations in the occurrence of colorectal cancer in the Egyptian population, which has a mixed ethnic background. Our data also indicate that liquid biopsy (blood samples) may be more representative than tissue samples for detecting BRCA1/2 mutations. These findings may have implications for cancer screening and the development of personalized, targeted therapies, such as PARP inhibitors, which can effectively target BRCA1/2 mutations.

Long non-coding RNA LOXL1-AS1: a potential biomarker and therapeutic target in human malignant tumors

AbstractLong non-coding RNAs (lncRNAs) are transcripts that contain more than 200 nucleotides. Despite their inability to code proteins, multiple studies have identified their important role in human cancer through different mechanisms. LncRNA lysyl oxidase like 1 antisense RNA 1 (LOXL1-AS1), a newly discovered lncRNA located on human chromosome 15q24.1, has recently been shown to be involved in the occurrence and progression of various malignancies, such as colorectal cancer, gastric cancer, hepatocellular carcinoma, prostate cancer, non-small cell lung cancer, ovarian cancer, cervical cancer, breast cancer, glioma, thymic carcinoma, pancreatic carcinoma. LOXL1-AS1 acts as competitive endogenous RNA (ceRNA) and via sponging various miRNAs, including miR-374b-5p, miR-21, miR-423-5p, miR-589-5p, miR-28-5p, miR-324-3p, miR-708-5p, miR-143-3p, miR-18b-5p, miR-761, miR-525-5p, miR-541-3p, miR-let-7a-5p, miR-3128, miR-3614-5p, miR-377-3p and miR-1224-5p to promote tumor cell proliferation, invasion, migration, apoptosis, cell cycle, and epithelial–mesenchymal transformation (EMT). In addition, LOXL1-AS1 is involved in the regulation of P13K/AKT and MAPK signaling pathways. This article reviews the current understanding of the biological function and clinical significance of LOXL1-AS1 in human cancers. These findings suggest that LOXL1-AS1 may be both a reliable biomarker and a potential therapeutic target for cancers.

Binary classification of gynecological cancers based on ATR-FTIR spectroscopy and machine learning using urine samples

Abstract Making an early diagnosis of cancer still in the early stages, when completely asymptomatic, is the challenge modern medicine has been setting for several decades. In gynecology, no effective screening has yet been found and approved for endometrial and ovarian cancer. Mammography is an effective screening method for Breast Cancer, as well as Pap Test for Cervical Cancer, but they are underused in third world countries because of their expensive and specific instrumentation. Previous studies showed how “machine learning analysis methods” of the spectral information obtained from dried urine samples could provide good accuracy in differentiation between healthy and ovarian or endometrial cancer. In this study, we also apply ATR-FTIR spectrometry’s practical, fast, and relatively inexpensive principles to liquid urine analysis from 309 patients undergoing surgical treatment for benign or malignant diseases (endometrium, breast, cervix, vulvar and ovarian cancer). The data obtained from those liquid samples were then analyzed to train a machine learning model to classify healthy VS cancer patients. We obtained an accuracy of > 91%, and we also identified discriminant wavelengths (2093, 1774 cm −1 ). These frequencies are close to already reported ones in other studies, indicating a possible association with tumor presence and/or progression.

Publisher

Springer Science and Business Media LLC

ISSN

1591-9528