Endometriosis (EMS) is a chronic gynecological condition affecting 6-10% of reproductive-age women. These lesions, albeit of benign nature, present cancer-like features, and may progress to epithelial ovarian cancer (EOC) through a multistep process. The coexistence of EMS and EOC in the presence of transitional lesions (TL) - i.e. atypical EMS/borderline lesions - is termed as endometriosis-correlated ovarian cancer (ECOC). Given the regulatory role of miRNAs in gene expression and biological pathways, we aimed to identify miRNAs that may drive or modulate the malignant transformation of ovarian EMS. Global miRNA profiling was evaluated on 81 samples (EMS, TL and ECOC) from 44 patients. Principal component analysis and unsupervised clustering revealed two distinct clusters formed by ECOC and ovarian EMS samples, whereas TL were dispersed among the other two. Differential expression analysis (DEA) of TL vs. ovarian EMS, revealed 30 significantly upregulated miRNAs. Comparison of ECOC vs. TL samples yielded 118 significantly upregulated and 77 downregulated miRNAs. Finally, DEA of ECOC vs. ovarian EMS lesions yielded 200 upregulated and 128 downregulated miRNAs. Evaluation of miRNAs commonly deregulated between the three groups showed 14 shared upregulated miRNAs (miR-429, miR-425-5p, miR-200c-3p, miR-200c-5p, miR-200b-3p, miR-200a-3p, miR-183-5p, miR-182-5p, miR-141-5p, miR-141-3p, miR-96-5p, miR-93-5p, miR-10a-5p, miR-10a-3p) with a progressive increase in expression levels, from ovarian EMS to TL and ultimately to ECOC. The identified miRNA expression profiles associated with the progression from ovarian EMS, TL and ECOC provide valuable insights into the molecular progression from benign to malignant lesions and could represent potential biomarkers for the early detection of ECOC.

SEPT9 methylation has been closely linked to breast cancer, yet its role in differentiating disease stages remains unclear. In particular, Few studies previously have examined differences in SEPT9 methylation between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC), or among DCIS lesions of varying nuclear grades. This study investigated SEPT9 methylation across 105 breast cancer cases, classified into pure DCIS, DCIS with invasive components (DCIS-INV), IDC alone, and metastatic breast cancer (MBC). Methylation levels were measured using real-time PCR, and in vitro experiments were conducted using MCF-7 and T47D cell lines treated with decitabine to explore the relationship between methylation and microtubule stability. SEPT9 methylation was significantly elevated in cancer cells compared to normal breast epithelium, with positivity rates of 90.6% in DCIS-INV, 77.8% in IDC, and 79.2% in MBC, versus only 18.2% in pure DCIS. SEPT9 methylation was negtive in low-grade DCIS and positive in 28.6% of intermediate- to high-grade cases. Positive methylation was significantly associated with high Ki-67 expression and lymph node metastasis (P < 0.05), but showed no correlation with age, menopausal status, tumor size, or hormone receptor status. Additionally, decitabine treatment induced a reduction in SEPT9 methylation levels, which affects microtubule stability, suggesting a potential mechanistic link to tumor invasion. These findings indicate that SEPT9 methylation is a promising biomarker for distinguishing invasive breast cancer from DCIS and for identifying high-risk DCIS lesions with greater potential for progression.

Papillary thyroid carcinoma (PTC) is a malignancy with an ambiguous etiology. The competitive endogenous RNA (ceRNA) hypothesis provides a framework for clarifying the molecular mechanisms that drive carcinogenesis. In this study, we constructed a novel ceRNA network to identify reliable diagnostic and prognostic indicators applicable across all stages of PTC. Transcriptome analysis was performed to identify stage-specific hub genes using the MCC, IVI, and MCODE algorithms. A novel five-layer ceRNA network and its associated regulatory network (DE-TF) were constructed. Receiver operating characteristic curves were used to evaluate the diagnostic performance of elements within both networks. A risk assessment model was developed by identifying key genes from the ceRNA and DE-TF components through univariable Cox regression and LASSO regression analyses. RNA-seq findings were validated by RT-qPCR. The correlations between gene expression levels and blood calcium levels were examined. The ceRNA and DE-TF networks contained 33 and 21 components, respectively. Logistic regression analysis identified PKMYT1, E2F1, NFATC1, STAT6, E2F3, LINC02910, GAS5, and TK1 as reliable diagnostic markers for PTC, achieving an AUC of 96.9%. Among these, PKMYT1 and GAS5 were stage-specific markers, showing significant upregulation in highly aggressive PTC tumors compared to less aggressive ones. Both genes demonstrated strong diagnostic value in differentiating high- from low-aggressive tumors, with AUCs of 0.81 and 0.87, respectively. circMET, which was overexpressed in both low- and high-aggressive tumors, showed diagnostic potential in distinguishing low-aggressive tumors from normal adjacent tissues (AUC = 0.81). GAS5 expression demonstrated an association with blood calcium levels. The SERN prognostic model, including STAT6, E2F1, RMI2, and NR4A1, illustrates the importance of these four genes as reliable prognostic markers for overall survival in PTC. Three components of the ceRNA network-PKMYT1, GAS5, and circMET-were significantly associated with PTC aggressiveness. PKMYT1 and GAS5 demonstrated strong diagnostic value in distinguishing high-aggressive from low-aggressive tumors, while circMET showed notable diagnostic efficacy in differentiating low-aggressive PTC tumors from adjacent normal tissues. Furthermore, GAS5 expression levels were correlated with blood calcium levels.

Precision oncology relies on predictive biomarkers for selecting targeted cancer therapies. Network-based properties of proteins, together with structural features such as intrinsic disorder, are likely to shape their potential as biomarkers. We therefore designed a hypothesis-generating framework that integrates network motifs and protein disorder to explore their contribution to predictive biomarker discovery. This encouraged us to develop MarkerPredict by using literature evidence-based positive and negative training sets of 880 target-interacting protein pairs total with Random Forest and XGBoost machine learning models on three signalling networks. MarkerPredict classified 3670 target-neighbour pairs with 32 different models achieving a 0.7-0.96 LOOCV accuracy. We defined a Biomarker Probability Score (BPS) as a normalised summative rank of the models. The scores identified 2084 potential predictive biomarkers to targeted cancer therapeutics, 426 was classified as a biomarker by all 4 calculations. We detailed the biomarker potential of LCK and ERK1. This study encourages further validation of the high-ranked predictive biomarkers. The development of the MarkerPredict tool (which is available on GitHub) for predictive biomarker identification may have a significant impact on clinical decision-making in oncology.

The contribution of rare pathogenic/likely pathogenic (P/LP) germline variants to pediatric central nervous system (CNS) tumor development remains understudied. Here, we characterize the prevalence and biological significance of germline P/LP variants in cancer predisposition genes across 830 CNS tumor patients from the Pediatric Brain Tumor Atlas (PBTA). We identify germline P/LP variants in 23.3% (193/830) of patients and the majority (137/193) lack clinical reporting of genetic tumor syndromes. Among P/LP carriers, 34.6% have putative somatic second hits or loss of function tumor alterations. Finally, we link pathogenic germline variation with somatic events and patient survival to highlight the impact of germline variation on tumorigenesis and patient outcomes.

Changes in the immune microenvironment are frequent in cancers occurring in adult patients, yet our understanding of the pediatric cancer immune microenvironment and its clinical relevance is limited. We investigate the immune microenvironment in pediatric T cell acute lymphoblastic leukemia (T-ALL), using single-cell CITE-seq and immune repertoire analyses. We identify a T-ALL subgroup characterized by a remodeled immune microenvironment, which is associated with adverse clinical outcome in minimal residual disease low patients. This adverse immune landscape is dominated by the presence of a population of non-malignant CD4-CD8-TCRαβ T cells that interact with CXCL16 expressing non-classical monocytes. Leukemia cell intrinsic transcriptional rewiring in these patients is associated with activation of Rap1 signaling. Inhibiting Rap1 signaling results in increased sensitivity to the BCL2/BCL-XL inhibitor navitoclax. Our study provides insights into the immune microenvironment of pediatric hematologic malignancies, forming the basis for identifying potential (immuno) therapeutic targets and risk stratification for treatment.

Lysine lactylation is a post-translational modification induced by lactate discovered in recent years. Abnormal lysine lactylation contributes to the occurrence and progression of various tumors. However, the mediators and downstream targets of lysine lactylation remain unclear. Here, we report that HAT1 serves as a potential lactyltransferase that can promote homologous recombination and lead to radioresistance by regulating lactylation of RPA1. Lactylation of RPA1 facilitates its binding to single-stranded DNA and MRE11-RAD50-NBS1 (MRN) complexes and promotes homologous recombination. HAT1 knockout inhibits DNA repair in lung adenocarcinoma cells, thereby increasing radiotherapy sensitivity. Interestingly, we also found that K15 auto-lactylation of HAT1 can modulate its lactyltransferase activity. In conclusion, our research reveals that HAT1-regulated RPA1 lactylation plays an important role in homologous recombination and radioresistance, suggesting that HAT1 may become a potential therapeutic target for reversing the radioresistance caused by lactate accumulation in cancer cells.

Many non-small cell lung cancer (NSCLC) patients remain unresponsive to the current standard of care, which includes chemotherapy and immune checkpoint inhibitors, like anti-PD-1/PD-L1 antibodies. While interleukin (IL)-1β is known to promote lung cancer growth in humans and mice, we show here that IL-1β administration or overexpression overcomes resistance to classical chemo-immunotherapy (cisplatin/pemetrexed/anti-PD-1) in mouse lung cancer models. The antitumor effects of IL-1β rely on cancer cell-derived CXCL10 which mediates CD8 T cell recruitment at the tumor site. In lung cancer cells, Thioredoxin Interacting Protein (TXNIP) induces mitochondrial DNA (mtDNA) release in the cytosol, activating Absence in Melanoma 2 (AIM2) inflammasome, which subsequently triggers IL-1β and CXCL10 secretion, thereby reversing chemo-immunotherapy resistance. The clinical relevance of our findings is supported by the transcriptomic analysis of patient tumors, showing that high expression of IL1B, IL1R1, AIM2 and/or TXNIP is associated with better response to immunotherapy in NSCLC patients. Additionally, drug screening identifies MEK and MDM2 inhibitors as inducers of TXNIP expression capable of reversing resistance to chemo-immunotherapy. This study highlights a positive role of IL-1β in lung cancer treatment and suggests that enhancing IL-1β production at the tumor site can overcome resistance to chemo-immunotherapy.

Ubiquitin carboxyl-terminal hydrolase L3 (UCHL3) is a deubiquitinating enzyme involved in various cancers, yet its role in gastric cancer (GC) requires further exploration. This study primarily investigates the expression, function, and mechanisms of UCHL3 in GC. Clinical samples and bioinformatics analysis indicated that UCHL3 is overexpressed in GC tissues compared to adjacent normal tissues, with higher expression levels correlating with worse prognosis. Functional assays demonstrated that UCHL3 promotes GC cell proliferation, invasion, and migration, accelerates cell cycle progression, and induces epithelial-mesenchymal transition (EMT). In vivo studies using a cell line-derived xenograft (CDX) model confirmed that UCHL3 enhances GC proliferation, and its therapeutic potential was validated in patient-derived xenografts (PDX). Mechanistically, transcriptomic analysis and validation experiments identified the AKT/CCND1 signaling pathway as a key mediator of UCHL3-driven GC progression. Co-immunoprecipitation (Co-IP) and liquid chromatography-mass spectrometry identified potential UCHL3-binding proteins, notably the AKT activator ENO1. Molecular docking simulations, Co-IP, and GST-pull down assays further confirmed the interaction, mapping the binding regions between UCHL3 (AA 179-230) and ENO1 (AA 140-434). Cycloheximide (CHX) and in vivo ubiquitination assays demonstrated that UCHL3 deubiquitinates and stabilizes ENO1, thus extending its half-life, while UCHL3 inhibition produced the opposite effect. A C95A point mutation significantly impaired UCHL3's deubiquitination function on ENO1. Further studies revealed UCHL3 removes K48-linked polyubiquitin chains from ENO1 at lysine 92, activating the AKT/CCND1 signaling pathway. In addition, the small-molecule inhibitor TCID, specific for UCHL3, inhibited this deubiquitination, counteracting pro-tumorigenic effects. In vitro and in vivo experiments demonstrated that TCID increased the sensitivity of GC cells to CDK4/6 inhibitors palbociclib. These findings suggest that UCHL3 contributes to GC progression and represents a promising therapeutic target for GC treatment.

Stress-induced alternative processing of mRNA is emerging as an essential mechanism to drive almost every hallmark of cancer. Through a genome-wide screening based on an abnormal transcriptional readthrough event favoring the malignant progression of ovarian carcinoma (OC), we identified novel mRNA processing regulators including RRN3, an essential factor for the transcriptional initiation of rRNA. The long-read RNA sequencing and PAR-CLIP analyses revealed that RRN3 was involved in the usage of alternative polyadenylation (APA) sites, resulting in the altered stability of autophagy-related mRNAs. More interestingly, we discovered that nutrient-deprivation-induced phosphorylation of RRN3 at serine 199 was sufficient to divert RRN3 out of the nucleolus to the nuclear plasma, where RRN3 regulated the APA of autophagy mRNAs, such as OPTN, to enhance their stability and eventually promoted autophagy. Further in vivo experiments showed that nutrient-stress-triggered switch of RRN3 from rRNA transcription to APA regulation was essential for the growth and dissemination of OC in mice.

Blood coagulation and cancer are intricately related. Hypercoagulation associated with cancer leads to aberrant thrombin generation, which contributes to thrombosis. Thrombin also activates anticoagulant protein C and the activated protein C (aPC), in addition to regulating the coagulation pathway, it also elicits cell signaling by binding to endothelial cell protein C receptor (EPCR) and activating protease-activated receptor 1 (PAR1)-mediated cell signaling. Earlier studies showed that aPC promotes lung adenocarcinoma survival and metastasis. However, the underlying mechanism remains largely unknown. Our present study provides mechanistic insight into how aPC promotes lung adenocarcinoma survival, metastasis, and drug resistance. Our study shows that aPC, through EPCR-PAR1-driven activation of RhoA-ROCKII-JNK1/2-MLC2 signaling, triggers extracellular vesicle (EV) release from lung adenocarcinoma cells. aPC-EVs, via the transfer of microRNA (miR)-200a, promote proliferation, migration, and invasion of normal lung epithelial cells. They also confer resistance to lung cancer against chemotherapeutic agents. Inhibition of miR-200a functions through the incorporation of anti-miR-200a abrogates aPC-EVs-mediated tumorigenic effects. Furthermore, loading miR-200a mimic into control EVs showed similar phenotypic responses to that of aPC-EVs. miR-200a is shown to target SOX17 in the recipient cells, leading to tumorigenesis. miR-200a upregulation and SOX17 downregulation are consistently observed in lung cancer tissues in the UALCAN portal database of clinical specimens. Consistent with these findings, our in vivo studies in BALB/c nude mice showed that aPC-EVs from lung cancer cells promote tumor growth, metastasis, and drug resistance through miR-200a transfer. Targeting EV biogenesis, EV's miR-200a, and/or EV uptake mechanisms may offer novel therapeutic strategies in limiting lung tumorigenesis, thereby increasing patients' survival.

Type-II topoisomerases resolve topological stress in DNA through double-strand breaks. While topoisomerases are chemotherapy targets linked to therapy-related genotoxicity, TOP2B is uniquely positioned to influence mutagenesis through its activity in non-dividing cells and sensitivity to topoisomerase poisons. To investigate this, we generated DNA-binding maps of TOP2B, CTCF, and RAD21 in human cancer samples and analyzed these for driver mutations and mutational processes across 6500 whole cancer genomes. TOP2B-CTCF-RAD21 and TOP2B-RAD21 sites are enriched in somatic mutations and structural variants, particularly at sites with evolutionary conservation, high transcription and long-range chromatin interactions. TOP2B binds driver genes such as TP53, MYC, FOXA1, and VHL, and many frequently mutated non-coding regions. We show that one non-coding TOP2B-bound element at the non-coding RNA gene RMRP drives tumor initiation and growth in vivo. Our study highlights TOP2B as a safeguard of genome integrity and a marker of mutational processes and hotspots in cancer, underscoring implications for cancer genomics research.

In this issue of Cell Chemical Biology, Zhang et al.1 report the identification of a high-affinity EMBOW-derived inhibitor of WDR5, Ac7, which demonstrates in-cell target engagement and in vivo antileukemic efficacy. The microprotein-inspired inhibitor potently blocks the WDR5-MLL1 interaction, suppressing H3K4 methylation and transcription of target genes in mixed lineage leukemia (MLL)-rearranged leukemia.

Mitochondrial DNA (mtDNA) mutations are emerging as important molecular features of tumorigenesis. Liquid biopsies, involving analysis of cell-free mtDNA, enable early cancer detection but suffer from low sensitivity due to scarce analytes. Here, we developed a CRISPR/Cas12a-mediated urinary biomarker, termed CasUber, for in vivo monitoring of tumor progression and metastasis. Our results demonstrate that CasUber can deliver a CRISPR detection system into tumor cell mitochondria, leverage the single-nucleotide variant recognition ability and trans-cleavage activity of Cas12a to convert tumor-specific mtDNA mutations into renal-clearable fluorescent biomarkers, and exocytosed along with the natural efflux pathway of damaged mtDNA. As a result, CasUber enables discrimination of ultrasmall tumor lesions (~1 cubic millimeter) and detection of lung tumor nodules earlier than bioluminescence imaging in a blood-lung metastasis model. This renal clearable nanosensor allows in situ recognition of specific gene mutation to generate amplified signals, overcoming the limitation of low mtDNA abundance and enabling noninvasive and ultrasensitive monitoring of tumor progression and metastasis via a simple urine test.

Prostate cancer is one of the most common malignant tumors among men worldwide, and surgery remains its mainstay of treatment. It is unclear how prostate cancer develops and what the most effective drug targets are for treating prostate cancer. Therefore, we sought to identify the genes responsible for prostate cancer. By integrating multidimensional and high-throughput data, proteome wide association studies (PWAS), transcriptome wide association studies (TWAS), single-cell sequencing, functional enrichment, Mendelian randomization (MR), and Bayesian co-localization analyses were used to screen for candidate genes that may contribute to prostate cancer and associate with clinical results of prostate cancer. Our comprehensive analysis showed that protein abundance of eight genes was associated with prostate cancer, four of which were validated at the transcriptome level. These 8 candidate genes (MSMB, PLG, CHMP2B, ATF6B, EGF, TAPBP, GAS1 and MMP7) were validated. After combining single-cell sequencing, Mendelian randomization, and Bayesian co-localization analyses, we identified 1 gene (TAPBP) that is strongly associated with prostate cancer.

Schistosoma haematobium is a parasitic worm that infects over 110 million people worldwide, laying eggs that migrate into host urinary and reproductive tracts. While S. haematobium is a known carcinogen in the urinary bladder, its role in cervical cancer remains unclear and molecular effects of parasite eggs in genital tissue are largely unknown. Our objective was to characterize cervical transcriptional profiles in women with or without active S. haematobium infection and after anti-schistosome treatment.

Von Hippel-Lindau (VHL) disease is a rare inherited tumor syndrome characterized by the development of multiple neoplasms. The broad variability in clinical manifestations makes this entity susceptible to being overlooked during clinicpathological diagnosis. A female patient in her late 20s presented with multiple adrenal masses during a routine health check-up, with associated dizziness and palpitations lasting 1 month. Laboratory studies revealed plasma-free normetanephrine level of 2894.9 pg/ml. Abdominal contrast-enhanced computed tomography showed multiple lesions consisting of bilateral adrenal masses and retroperitoneal nodules. Postoperative pathological examination demonstrated the diagnosis of bilateral adrenal pheochromocytomas, retroperitoneal paraganglioma, and pancreatic neuroendocrine tumor. Molecular genetic testing detected a pathogenic germline mutation in the VHL gene (c.499C > T: p.R167 W). Subsequent brain magnetic resonance imaging revealed a hypervascular cerebellar nodule. Genetic and clinical findings confirmed a definitive diagnosis of VHL syndrome type 2B. The diverse manifestations of VHL syndrome often cause diagnostic delays. Analyzing this case alongside the literature highlights the need to suspect VHL in young patients with multiple tumors, for whom genetic testing is crucial for definitive diagnosis. While a single case cannot capture the full disease spectrum, it provides valuable clinical insight.

Multi-omics strategies, integrating genomics, transcriptomics, proteomics, and metabolomics, have revolutionized biomarker discovery and enabled novel applications in personalized oncology. Despite rapid technological developments, a comprehensive synthesis addressing integration strategies, analytical workflows, and translational applications has been lacking. This review presents a comprehensive framework of multi-omics integration, encompassing workflows, analytical techniques, and computational tools for both horizontal and vertical integration strategies, with particular emphasis on machine learning and deep learning approaches for data interpretation. Recent applications of multi-omics have yielded promising biomarker panels at the single-molecule, multi-molecule, and cross-omics levels, supporting cancer diagnosis, prognosis, and therapeutic decision-making. However, major challenges persist, particularly in data heterogeneity, reproducibility, and the clinical validation of biomarkers across diverse patient populations. This review also highlights cutting-edge advances in single-cell multi-omics and spatial multi-omics technologies, which are expanding the scope of biomarker discovery and deepening our understanding of tumor heterogeneity. Finally, we discuss the integral role of multi-omics in personalized oncology, with a particular focus on predicting drug responses and optimizing individualized treatment strategies, supported by real-world clinical practice cases. By bridging technological innovations with translational applications, this review aims to provide a valuable resource for researchers and clinicians, offering insights into both current methodologies and future directions for implementing multi-omics data in biomarker discovery and personalized cancer care.

Myasthenia gravis (MG) is an autoimmune disease caused by dysfunction at the neuromuscular junction. Current studies on MG are increasingly focusing on the involvement of B cell immunophenotypes in the development of the disease. Nonetheless, the specific correlation between B cells and MG still needs to be fully clarified. From published GWAS studies, we gathered summary results on B cell immunophenotypes and MG. We performed a Two-sample Mendelian randomization (MR) analysis to investigate the potential causal relationship between B cells and MG. The primary estimation was done by using IVW and the Wald ratio. To assess pleiotropy and heterogeneity, a range of tests were utilized, including the Cochran Q test, MR-Egger intercept analysis, and the MR-PRESSO test. Next, we explored the potential for a reverse connection between B cells and MG using reverse MR analysis. Subsequently, in order to control for any potential confounding variables among the B cells, we carried out a multivariable MR analysis. Finally, we conducted co-localization analysis to examine the correlation between B cells and MG. Additionally, we repeated the above analysis process for two different MG subtypes. A total of 15 B cells were found to be significantly associated with MG, 7 B cells showed significant association with Early-onset MG, and 13 B cells showed significant association with Late-onset MG, as identified by MR analysis. We verified the reliability of the results by examining heterogeneity or pleiotropy. The Reverse MR analysis showed that there is bidirectional causality between 4 B cells and Early-onset MG, as well as between 2 B cells and Late-onset MG. To prevent confusion among B cells, we utilized multivariable MR analysis and identified that only 7 B cell immunophenotypes had independent effects on MG, while 4 B cell immunophenotypes had independent effects on Late-onset MG. None of the B cells had independent effects on Early-onset MG. Through colocalization analysis, it was found that two B-cell variants (rs75787009, rs354026) were associated with MG, along with two variants (rs138791329, rs11882257) were linked to Late-onset MG. Our results indicate a connection between B cells and the risk of MG, underscoring the possibility of using B-cell depletion therapy as a treatment option for MG patients based on genetic factors. Nevertheless, further research is needed to explore the specific mechanisms involved in this association.

Pancreatic cancer remains one of the deadliest malignancies due to its high metastatic potential and resistance to treatment. Transcription factors driving epithelial-to-mesenchymal transition (EMT) are critical in promoting invasion and metastasis, yet their full repertoire remains poorly understood. Here, we identify Basonuclin 2 (BNC2), a zinc-finger transcription factor, as a novel regulator of pancreatic cancer progression. Through integrative transcriptomic analyses, we demonstrate that BNC2 is significantly upregulated in pancreatic cancer and correlates with advanced tumor grade, stage, and poor prognosis. Functional assays reveal that BNC2 promotes EMT and cancer cell invasion by transcriptionally activating collagen type III alpha 1 (COL3A1), a key extracellular matrix component. Knockdown of BNC2 suppresses EMT, reduces invasiveness, and downregulates COL3A1, whereas COL3A1 overexpression rescues these effects, establishing the BNC2-COL3A1 axis as a critical driver of tumor progression. These findings highlight BNC2 as a potential biomarker and therapeutic target in pancreatic cancer, offering new insights into the molecular mechanisms underlying this aggressive disease.