bims-dinmec 2025-07-06 papers

Issue of 2025–07–06
five papers selected by
Lorena Ancona, Humanitas Research

Sci Rep. 2025 Jul 01. 15(1): 22149

Diagnostic accuracy of urinary PENK methylation test for urothelial and other cancers: A prospective study.

Sangmin Lee, Bumjin Lim, Jungyo Suh, Bumsik Hong, In Gab Jeong.

The methylated PENK gene is known to be highly expressed in the urine of patients with bladder cancer. Recent large-scale multicenter studies have confirmed the robust diagnostic performance of urinary PENK methylation, reporting high sensitivity and specificity for bladder cancer detection. However, its association with other cancers remains unclear. This prospective study aimed to determine the diagnostic accuracy of the urinary PENK methylation test for urothelial carcinoma among patients with 13 different cancer types. Between August 2022 and April 2023, 183 patients were enrolled, including 17 with urothelial carcinoma (eight bladder cancer and nine upper tract urothelial carcinoma) and 166 with other cancers. The urinary PENK methylation test showed an overall sensitivity of 94.1% (87.5% for bladder cancer and 100% for UTUC) and a specificity of 95.8% when patients with non-urothelial cancers were used as the control group. Positive urinary PENK methylation test was obtained for two patients with cervical cancer (25.0%), 2 with colorectal cancer (10.5%), and one patient each with esophageal (4.8%), liver (5.0%), and kidney (5.3%) cancer. These findings confirm the high sensitivity and specificity of the urinary PENK methylation test for detecting urothelial carcinoma and support its potential as a non-invasive biomarker.

Keywords: DNA methylation; Hematuria; Tumor biomarkers; Urinary bladder neoplasms

DOI: https://doi.org/10.1038/s41598-025-07173-5

J Ovarian Res. 2025 Jul 02. 18(1): 140

Methylated ARHGAP40 DNA as a potential biomarker for early diagnosis in high-grade ovarian serous cancer.

Jiaxin Chai, Dongni Leng, Shuwei Guo, Rusong Zhang, Jiandong Wang, Yun Gu, Qiu Rao.

Ovarian cancer ranks as the eighth most common malignancy in women globally. Early detection remains a critical challenge for improving ovarian cancer diagnosis and treatment outcomes. Our prior study demonstrated that ARHGAP40 downregulation in basal cell carcinoma is attributed to CpG island hypermethylation. However, the expression and methylation status of ARHGAP40 in ovarian cancer remain unexplored. Here, we investigated ARHGAP40 protein expression in normal fallopian tubes, ovarian benign tumors, borderline tumors, low-grade serous carcinoma (LGSC) and high-grade serous carcinomas (HGSC). Methylation analysis of the ARHGAP40 was performed using bisulfite sequencing PCR (BSP). MethyLight assays were developed to detect methylated circulating tumor DNA (ctDNA) fragments of ARHGAP40. IHC results revealed absent or weak ARHGAP40 protein expression in 93.8% (30/32) of HGSC, 11.1% (2/18) of borderline tumors, and in 14.3% (1/7) of LGSC cases. ARHGAP40 protein expression was robust expressed in all normal fallopian tubes (15/15) and benign ovarian tumors (8/8). CpG island hypermethylation in the ARHGAP40 promoter showed a strong inverse correlation with protein expression (P < 0.001). Furthermore, methylated ctDNA for ARHGAP40 was detected in 80.0% (4/5) of HGSC patients' plasma, but not in benign tumor (0/3) and healthy controls (0/15). Our findings suggest that promoter hypermethylation may be a mechanism underlying ARHGAP40 silencing in HGSC. Detection of methylated ARHGAP40 ctDNA may serve as a noninvasive biomarker for early diagnosis and monitoring of HGSC. While our findings suggest the potential of methylated ARHGAP40 as an early diagnostic biomarker, the small sample size warrants validation in larger cohorts.

Keywords: ARHGAP40; CtDNA; Methylation, CfDNA; Ovarian cancer

DOI: https://doi.org/10.1186/s13048-025-01729-9

Sichuan Da Xue Xue Bao Yi Xue Ban. 2025 Mar 20. 56(2): 571-576

[Advances in Multi-omics Analysis of Cervical Cancer].

Jianhong Wang, Xue Xiao, Yuan Yao.

Cervical cancer (CC), a common malignant tumor afflicting women, poses serious threats to their health. Therefore, it is critical to develop a thorough understanding of the molecular mechanisms underlying the pathogenesis of CC, and to identify new therapeutic targets and methods for early diagnosis. The multi-omics research in tumors, involving proteomics, transcriptomics, genomics, microbiomics, and metabolomic, offers valuable insights. The multi-omics analysis of biological samples from patients with cervical intraepithelial neoplasia (CIN) and CC can help clarify the pathways involved in the pathogenesis and development of CC. Furthermore, multi-omics studies have identified a number of molecules associated with CC, including actin, lumican, family member with sequence similarity 83 (FAM83A), cadherin EGF-LAG seven-pass G-type receptor 3 (CELSR3), and 5,10-methylenetetrahydrofolate reductase (MTHFR), all of which show potential to be used as new biomarkers. These biomarkers will help make early diagnosis, improve the survival and prognosis of CC patients, and ultimately reduce CC incidence and mortality. This review synthesizes current advances in multi-omics research on cervical cancer.

Keywords: Biomarker; Cervical cancer; Early diagnosis; Multi-omics; Review

DOI: https://doi.org/10.12182/20250360403

Breast Cancer Res. 2025 Jul 01. 27(1): 120

A comparative study of four cell-free DNA assays for detecting circulating tumor DNA in early breast cancer.

Charlotta V Mulder, Elisabeth M Jongbloed, Marte C Liefaard, Stavros Makrodimitris, Daan M Hazelaar, Corine M Beaufort, Vanja de Weerd, Lennart Mulder, Carolien H M van Deurzen, Gabe S Sonke, Agnes Jager, Saskia M Wilting, John W M Martens, Maurice P H M Jansen, Esther H Lips.

Early prediction of the response to neoadjuvant chemotherapy (NAC) enables tailoring treatment strategies to the specific needs of individual breast cancer patients. Circulating tumor DNA (ctDNA) has shown to be a prognostic factor for response on NAC during treatment. However, at this point in time mostly tumor-informed ctDNA detection methods are used which are costly, have relatively long turnaround times and are subsequently potentially less feasible for widespread clinical application. In this study, we investigated four tumor-agnostic methods to determine their ability to accurately detect circulating tumor DNA (ctDNA) at baseline. These methods were the Oncomine Breast cell free DNA (cfDNA) NGS panel, the LINE-1 sequencing assay mFAST-SeqS, shallow whole genome sequencing and the genome-wide methylation profiling assay MeD-Seq. In total 40 patients with triple negative or luminal B breast cancer were included and cell free DNA (cfDNA) from plasma before the start of NAC was analyzed with the four assays. We detected ctDNA in 3/24 (12.5%) patients with Oncomine, 5/40 (12.5%) with mFast-SeqS, 3/40 (7.7%) with low pass shallow WGS and 23/40 with MeD-Seq (57.5%). When all methods were combined ctDNA was detected in 65% of patients. In conclusion, we demonstrated that tumor agnostic methods, in particular MeD-Seq, can detect ctDNA in a fraction of the patients with early breast cancer, but further optimization is needed to reach the potential currently demonstrated by tumor-informed methods.

Keywords: Circulating tumor DNA; Early breast cancer; Neoadjuvant treatment

DOI: https://doi.org/10.1186/s13058-025-02077-8

Res Sq. 2025 Jun 20. pii: rs.3.rs-6837659. [Epub ahead of print]

Multi-omics machine learning classifier and blood transcriptomic signature of Parkinson's disease.

Xianjun Dong, Ruifeng Hu, Ruoxuan Wang, Jie Yuan, Zechuan Lin, Elizabeth Hutchins, Barry Landin, Zhixiang Liao, Ganqiang Liu, Clemens Scherzer.

Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale, whole-blood total RNA and DNA sequencing data from the Accelerating Medicines Partnership in Parkinson's Disease (AMP PD) program to identify PD-associated RNAs, including both known genes and novel circular RNAs (circRNA) and enhancer RNAs (eRNAs). Initially, 874 known genes, 783 eRNAs, and 35 circRNAs were found differentially expressed in PD blood in the PPMI cohort (FDR < 0.05). Based on these findings, a novel multi-omics machine learning model was built to predict PD diagnosis with high performance (AUC = 0.89), which was superior to previous models. We further replicated this discovery in an independent PDBP/BioFIND cohort and confirmed 1,111 significant marker genes, including 491 known genes, 599 eRNAs, and 21 circRNAs. Functional enrichment analysis showed that the PD-associated genes are involved in neutrophil activation and degranulation, as well as the TNF-α signaling pathway. By comparing the PD-associated genes in blood with those in human brain dopamine neurons in our BRAINcode cohort, we found only 44 genes (9% of the known genes) showing significant changes with the same direction in both PD brain neurons and PD blood, among which are neuroinflammation-associated genes IKBIP, CXCR2, and NFKBIB. Our findings demonstrated consistently lower SNCA mRNA levels and the increased expression levels of VDR gene in the blood of early-stage PD patients. In summary, this study provides a generally useful computational framework for further biomarker development and early disease prediction. We also delineate a wide spectrum of the known and novel RNAs linked to PD that are detectable in circulating blood cells in a harmonized, large-scale dataset.

DOI: https://doi.org/10.21203/rs.3.rs-6837659/v1