Cancers doi: 10.20517/jtgg.2025.109

Authors: Fanzhang Lei,Xiaolian Wu,Qinglin Liu,Tong Xie,Bofeng Zhu

Aim: Kinship analysis in trace amounts and degraded biological samples has consistently posed a challenge in forensic practice. With shorter amplicons and no stutter peak, Insertion/Deletion polymorphisms (InDels) significantly improve kinship analyses of deceased individuals and their potential living relatives. However, room for improvement remains in identifying 2nd-degree and more distant kinships. To address this issue, a kinship analysis workflow based on machine learning (ML) models was proposed.

Methods: Based on multiple kinship parameters including identity-by-state (IBS) scores, k coefficients, proportion identity-by-descent (IBD), and likelihood ratio (LR) values, this pilot study applied a recently validated InDel locus to preliminarily develop an ML workflow for forensic kinship multi-classification.

Results: In the binary classification of 2nd-degree relatives and unrelated pairs, the LR cutoff threshold workflow and the ML workflow achieved a similar accuracy of 0.9194. However, the ML method had a conclusiveness rate (CR) of 1.0, compared to 0.7066 for the LR workflow. In the multiclass task, the LR-based workflow had a macro F1 score of 0.6955/0.5212 and a CR of 0.7375/0.7046 for single and dual thresholds methods, respectively. However, the ML-based workflow showed that the optimal model - feature combination (XGBoost-IBD+LR) could classify all samples conclusively, with a macro F1 score of 0.9020.

Conclusion: In summary, the ML workflow enhanced the kinship analysis efficiency based on the InDel genotyping system by combining multiple parameters, aiming to provide a more flexible and efficient solution for large-scale database screening.

Cancers doi: 10.20517/jtgg.2025.141

Authors: Ali El-Far,Jingliang Cheng,Li Fu,Mufan Li,Xia Jiang,Alaa Elmetwalli,Alora Grace Linehan,Henry James Li,Xianghui Fu,Junjiang Fu

G-quadruplexes (G4s) are structurally unique, four-stranded nucleic acid formations composed of guanine-rich sequences stabilized by Hoogsteen hydrogen bonds. These highly stable secondary structures have emerged as vital regulatory elements in DNA and RNA metabolism, where they support genomic stability, telomere integrity, and transcriptional control. Their regulation depends on G4 helicases - specialized enzymes that unwind G4 structures using energy derived from nucleoside triphosphate hydrolysis to ensure proper cellular function. Among them, DEAH-box helicase 36 (DHX36) is a principally essential G4 helicase in human cells, capable of resolving G4s in DNA and RNA. Its activity is critical for preserving genomic integrity and regulating broader cellular processes, underscoring its potential impact on human health and disease. This review synthesizes computational and experimental approaches to discuss the interplay within the DHX36-N6-methyladenosine (m6A)-G4 axis and its role in RNA regulation and cancer genetics or epigenetics, where it post-transcriptionally controls the expression of chromatin-modifying enzymes and oncogenic transcripts. It examines the axis’s diverse activities, including roles in spermatogenesis, antiviral defense, and muscle development, and its regulatory effects in both normal physiological and diseased states. The computational identification of DHX36’s target G4 structures, combined with experimental methods, is crucial for advancing our understanding of its biological functions and disease mechanisms. This approach enhances the accuracy of target recognition and provides insights into the complex interactions within cellular processes that DHX36 may influence.

Cancers doi: 10.20517/jtgg.2025.146

Authors: Tehan Zhang,Yanbin Feng,Wei Wang,Wenzhao Wang,Liying Shan,Xiaoli Yang,Haijian Sun,Shiqing Feng

Receptor activator of nuclear factor-κB ligand (RANKL) is indispensable for osteoclast differentiation, activation, and bone resorption. While the relative contributions of membrane-bound RANKL (mRANKL) and soluble RANKL were historically debated, evidence from the past decade increasingly establishes mRANKL as the primary driver of osteoclastogenesis. However, a systematic literature synthesis integrating these diverse cellular sources and structural modalities remains lacking. It has also not been systematically defined which cellular sources of RANKL - arising from bone marrow mesenchymal lineage cells or hematopoietic lineage cells - play dominant roles in driving osteoclast activation. Clarifying these distinct forms and sources of RANKL will refine the conceptual framework of osteoclast regulation and provide a mechanistic basis for next-generation antiresorptive therapies that selectively target specific RANKL modalities to achieve more durable skeletal protection.

Cancers doi: 10.20517/jtgg.2025.112

Authors: Meiyun He,Litao Huang,Linying Ye,Mingjin Yang,Xiaofeng Zhang,Xin Liu,Chao Liu,Ling Chen

Aim: Illicit etomidate (ET) use in e-cigarettes has increased recently, but its effects on the oral microbiome remain unknown. This study investigates oral microbiota alterations in chronic ET users.

Methods: Saliva from 45 ET users and 44 controls underwent 16S ribosomal RNA (rRNA) sequencing. We compared microbial diversity, composition, predicted functions, and co-occurrence networks between groups, and developed 12 machine learning models to classify ET users based on microbial features.

Results: Chronic ET-containing e-cigarette use was strongly associated with significant oral microbial dysbiosis. Species richness and diversity were significantly lower in the ET group. ET users exhibited proliferation of taxa associated with oral diseases, including Actinomyces, Rothia, and Atopobium. PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2) predicted enhanced carbohydrate and amino acid metabolism in the ET group, while controls showed greater abundance of biotin and fatty acid metabolism pathways. Network analysis revealed reduced complexity and stability in the ET group. The ensemble model GLMBoost (generalized linear model boosting) + Random Forest achieved an area under the curve (AUC) of 1.00 and 100% accuracy on the test set. Seven key genera were identified as discriminative biomarkers: Prevotella_7, Rothia, Neisseria, Veillonella, Haemophilus, Actinomyces, and Fusobacterium.

Conclusion: Chronic use of ET-containing e-cigarettes is linked to altered homeostasis of the oral microbiota, providing a deeper understanding of how substance addiction impacts oral microbial ecology and highlights the potential of machine learning-derived microbial signatures as non-invasive tools for accurately distinguishing ET-containing e-cigarette users from non-users.

Cancers doi: 10.20517/jtgg.2025.95

Authors: Greg Crawford,Pervinder Sagoo,H. Bobby Gaspar

The use of autologous haematopoietic stem cell gene therapy is increasingly recognised as a promising treatment option for severe combined immunodeficiency diseases (SCID). This approach seeks to correct the underlying genetic cause of SCID conditions, potentially allowing a single treatment to restore a healthy immune system for the lifespan of the patient. To date, such gene therapy has relied on the use of gamma-retroviruses or lentiviruses to deliver genetic material to a patient’s haematopoietic stem cells before reinfusion. This approach has had notable successes in the clinic for conditions including X-linked severe combined immunodeficiency (SCID-X1), Artemis-SCID, and adenosine deaminase-SCID. However, significant hurdles have been met when using viral-mediated gene addition, primarily linked to the potential risk of insertional mutagenesis; however, for certain SCID forms, there are also limitations associated with the regulation and levels of gene expression achievable. This has driven the development of new gene editing technologies for the treatment of SCID conditions. CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated protein 9), base editing and prime editors are all actively under investigation, mainly in the preclinical stage to understand their potential applications. In this review, we explore gene editing approaches that are in development for the treatment of SCID. While initial results look promising, significant challenges need to be overcome before their clinical use. Such technologies represent an exciting new wave of treatment options for SCID patients.

Cancers doi: 10.20517/jtgg.2025.161

Authors: Yu Jiang,Lili Wu,Liya Du,Zhenyu Luo,Hao Zhao,Mei Lu,Yanhong Zhang

To elucidate the etiology of recurrent fetal brain developmental malformations accompanied by other structural ultrasound anomalies in a Chinese non-consanguineous couple, we performed a comprehensive evaluation of prenatal ultrasound phenotypes across their two consecutive pregnancies. Copy number variation sequencing and exome sequencing were applied to the amniotic fluid sample obtained from the affected pregnancy. One copy number variation and four candidate missense variants in three genes identified in the initial analysis were reassessed and reclassified according to current clinical and genetic evidence. Our results demonstrated that a maternal mosaic c.7G>A(p.Glu3Lys) variant in the tubulin alpha 1a (TUBA1A) gene was the underlying cause of the couple’s recurrent adverse pregnancy outcomes. These findings enrich the database of pathogenic TUBA1A variants, expand the spectrum of associated prenatal ultrasound phenotypes, and provide valuable insights into the underlying pathogenic mechanisms.