Human Mutation最新文献

Polycystic ovary syndrome is a common clinical condition often linked to insulin resistance (IR) and primarily affects women at reproductive age. Previous research has indicated a close association between mitochondrial tRNA (mt-tRNA) mutations and this syndrome; however, the range of mt-tRNA mutations in PCOS-IR remains largely unclear. In this study, we examined mt-tRNA mutations in 302 Han Chinese women with PCOS-IR and 589 control subjects, identifying a novel m.7544C>T mutation potentially related to this syndrome. At the molecular level, the m.7544C>T mutation occurs at a highly conserved nucleotide within the anticodon stem of mt-tRNA^Asp, disrupting the 30C-40G base-pairing. Using cybrids cells derived from two individuals carrying this mutation and two controls without it, we observed that the m.7544C>T decreased the steady-state levels of tRNA^Asp, altered mitochondrial RNA transcripts, impaired the activities of respiratory chain enzymes and oxygen consumption rates (OCRs), compromised mitochondrial functions, and increased oxidative stress. Overall, our findings strongly suggest that the m.7544C>T mutation contributes to the development of PCOS-IR, offering new insights into the pathophysiology of PCOS-IR driven by tRNA mutation–induced mitochondrial dysfunction and oxidative stress.

S. Zhao, X. Lin, Y. Huang, et al., “Prognostic Value of Ubiquitination-Related Genes in Ovarian Cancer and Their Correlation With Tumor Immunity,” Human Mutation 2025 (2025): 8369299, https://doi.org/10.1155/humu/8369299.

In the article titled “Prognostic Value of Ubiquitination-Related Genes in Ovarian Cancer and Their Correlation With Tumor Immunity,” there were errors in all the affiliations. The corrected affiliation list appears below:

Shu Zhao,^1,2,3,4 Xiaojing Lin,^1,3 Yuying Huang,² Zhongmin Kang,⁵ Huali Luo,² Qizhu Zhang,^1,3 Qinshan Li,^1,2,3 and Mengxing Li⁵

¹Department of Obstetrics and Gynecology, Institute of Precision Medicine of Guizhou Province, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China

²Department of Clinical Biochemistry, School of Medical Laboratory Science, Guizhou Medical University, Guiyang, Guizhou, China

³Clinical Medical College, Guizhou Medical University, Guiyang, Guizhou, China

⁴Department of Obstetrics, Guizhou Provincial People’s Hospital, Guiyang, Guizhou, China

⁵Department of Hematology, Guizhou Province Institute of Hematology, Guizhou Province Laboratory of Hematopoietic Stem Cell Transplantation Centre, Affiliated Hospital of Guizhou Medical University Guiyang, Guizhou, China

We apologize for this error.

RyR1-related disorders, arising from variants in the RYR1 gene encoding the skeletal muscle ryanodine receptor, encompass a wide range of dominant and recessive phenotypes. The extensive length of RyR1 and diverse mechanisms underlying disease variants pose significant challenges for clinical interpretation, exacerbated by the limited performance and biases of current variant effect predictors (VEPs). This study evaluates the efficacy of 70 VEPs for distinguishing pathogenic RyR1 missense variants from putatively benign variants derived from population databases. Existing VEPs show variable performance. Those trained on known clinical labels show greater classification performance, but this is likely inflated by data circularity. In contrast, VEPs using methodologies that avoid or minimise training bias show limited performance, likely reflecting difficulty in identifying gain-of-function variants. Leveraging protein structural information, we introduce Spatial Proximity to Disease Variants (SPDV), a novel metric based solely on three-dimensional clustering of pathogenic mutations. We determine ACMG/AMP PP3/BP4 classification thresholds for our method and top-performing VEPs, allowing us to assign PP3/BP4 evidence levels to all RyR1 missense variants of uncertain significance. Thus, we suggest that our protein structure–based approach represents an orthogonal strategy over existing computational tools for aiding in the diagnosis of RyR1-related diseases.

While hypoxia-driven nucleolar stress (NS) has been recognized as a critical modulator of the immunosuppressive tumor microenvironment in clear cell renal cell carcinoma (ccRCC), its mechanistic contribution to disease progression remains poorly defined. To address this gap, we systematically mapped NS-associated molecular landscapes through integrated spatial transcriptomics and single-cell RNA sequencing of ccRCC specimens. Our analysis stratified tumors into two distinct NS subtypes, revealing that high-NS tumors exhibit aggressive clinical behavior, elevated expression of immunosuppressive checkpoints, and significantly reduced survival. At single-cell resolution, high-NS malignant cells displayed enhanced proliferative activity, glycolytic metabolic reprograming, and marked chromosomal instability. Mechanistic investigations demonstrated that hypoxia-induced ETS1 activation orchestrates NS via the MYC/NPM1/DDX17 signaling axis, directly promoting tumor proliferation and metabolic adaptation in preclinical models. Spatial multiomics further uncovered coordinated niche formation between high-NS cells and OLR1⁺ macrophages, with ligand–receptor profiling identifying the EDN1–EDNRA–OLR1 axis as a central mediator of this immunosuppressive crosstalk. Functional validation in syngeneic mouse models confirmed that ETS1 overexpression accelerates tumor growth while enriching OLR1⁺ macrophages with immunosuppressive phenotypes. Clinically, high OLR1⁺ macrophage infiltration correlated with shorter survival across independent cohorts. These findings establish a hypoxia–ETS1–NS–macrophage axis as a key mechanism sustaining ccRCC progression and highlight actionable targets for disrupting protumorigenic immune niches through modulation of the NS pathway.

Background: Vimentin (VIM), a cytoskeletal protein implicated in tumor progression, has been associated with poor prognosis in B cell lymphomas. Alternative polyadenylation (APA), a posttranscriptional mechanism that modulates mRNA isoforms via 3 ^′UTR length changes, is frequently dysregulated in cancer. The interaction between VIM and APA in B cell lymphoma remains poorly understood.

Methods: We performed RNA-seq, APA analysis (DaPars), and proteomic profiling in wild-type and VIM-knockout (VIM-KO) B cell lymphoma cells (A20 and M12). Functional assays including CCK-8, EdU, Western blot, and ARVCF overexpression were used to explore the regulatory axis involving APA and mTOR signaling.

Results: VIM deletion in B cell lymphoma cells triggered widespread transcriptome remodeling, inducing 4089 APA shortening events that preferentially targeted prosurvival pathways, for example, mTORC1, G2-M checkpoint. Strikingly, RRAGA—a critical mTOR activator—underwent 3 ^′UTR shortening, concomitant with ARVCF downregulation in proteomic profiles. Functional rescue experiments demonstrated ARVCF’s dual role in maintaining RRAGA 3 ^′UTR length and suppressing mTOR-EIF4G1 signaling, ultimately inhibiting lymphoma proliferation.

Conclusion: This study reveals a novel VIM–ARVCF–RRAGA–mTOR axis in B cell lymphoma, linking cytoskeletal disruption to APA-mediated oncogenic signaling. VIM loss drives APA shortening and mTOR activation via ARVCF downregulation, promoting lymphoma progression. These findings offer mechanistic insight and potential targets for therapeutic intervention.

Colon adenocarcinoma (COAD) is a particularly aggressive cancer type, frequently identified at a later stage. Thus, it is crucial to enhance our understanding of the fundamental mechanisms that govern COAD cellular behavior and to perform extensive research into the biological foundations underlying its development, progression, invasion, and metastasis. We initially discovered NOL3 as a significant gene influencing COAD metastasis through the application of the weighted gene coexpression network analysis algorithm using the TCGA-COAD dataset. This was succeeded by an assessment of NOL3’s expression levels and prognostic significance. Moreover, we investigated the biological roles of NOL3 utilizing transcriptomic data. Our results demonstrate significant associations between NOL3 and immune infiltration in COAD, as well as sensitivity to chemotherapy. Furthermore, we utilized the tumor immune dysfunction and exclusion (TIDE) algorithm to evaluate how various cohorts responded to immune checkpoint therapies. Ultimately, the influence of NOL3 on the metastasis of COAD cells was confirmed through in vitro experiments. Our results indicate that NOL3 can promote COAD metastasis, and its underlying mechanism may be associated with DNA methylation. In summary, NOL3 has been identified by us as a key biomarker for COAD metastasis.

Colorectal cancer (CRC) ranks among the most common malignant tumors worldwide, with the metabolism of fatty acids being crucial for its development and progression. Altered fatty acid metabolism is a well-established metabolic characteristic of malignant tumors, including CRC. A complex and reciprocal relationship exists between fatty acid metabolism and CRC. On one side, the emergence and advancement of CRC can trigger a reprogramming of fatty acid metabolism. To fulfill the requirements of rapid cell division and survival, cancer cells increase both the synthesis and uptake of fatty acids while also suppressing their oxidation. Conversely, modifications in fatty acid metabolism can affect CRC, as abnormal fatty acid byproducts may activate signaling pathways that foster tumor cell proliferation, thus enhancing tumor progression. Understanding the interplay between fatty acid metabolism and the early stages and advancement of CRC, in conjunction with its relationship with the tumor microenvironment, is a vital area for future investigation. This article reviews the most recent discoveries concerning the impact of fatty acid metabolism on CRC progression, with the objective of supplying a solid theoretical framework and innovative perspectives for additional research and treatment of this condition.

Abdominal aortic aneurysm (AAA) is a serious vascular condition that significantly endangers the lives of patients. Although there have been improvements in early detection and treatment methods, considerable challenges persist regarding the timely identification and evaluation of risk associated with this disease. Therefore, there is an immediate requirement for novel biomarkers that can enhance the early diagnosis and risk evaluation of AAA, thus allowing for more accurate and individualized medical interventions. In this study, we identified key diagnostic markers for AAA using various machine learning algorithms, and we explored the functions of these genes in AAA through gene enrichment analysis. A diagnostic model for AAA was constructed based on multiple machine learning algorithms, with the random forest algorithm highlighting the central role of ARHGAP9. In vitro experiments confirmed the influence of ARHGAP9 on vascular smooth muscle cells (VSMCs). Our findings indicate that the key genes identified are associated with the immune microenvironment and metabolism in AAA samples. The validated diagnostic model exhibited excellent predictive performance. Knockdown of ARHGAP9 significantly inhibited the proliferative capacity of VSMCs. In conclusion, our results suggest that ARHGAP9 may serve as a diagnostic and therapeutic marker for AAA.