Intramuscular myxoma (IM) is a benign tumor that harbors GNAS missense variants. Distinguishing IM from low-grade myxofibrosarcoma (LGMFS) is challenging due to similarities in imaging and histological features. While molecular analysis aids differentiation, the low number of tumor cells available for DNA extraction necessitates highly accurate detection methods for variant identification. The aim of this study was to delineate molecular characteristics using next-generation sequencing (NGS) and to propose an optimal screening method in a clinical setting to differentiate IM from LGMFS.

Ovarian cancer exhibits high molecular heterogeneity and metastatic potential, contributing to its status as a leading cause of gynecologic cancer mortality. Cell polarity is essential in tumorigenesis, yet the role of Crumbs family proteins (CRBs), key regulators of apical-basal polarity, in epithelial ovarian cancer (EOC) remains unclear. In this study, we analysed CRB expression profiles using TCGA and GEO datasets, and validated our findings through immunohistochemical staining of ovarian tumour tissue microarrays. Among CRBs, CRB2 was significantly overexpressed in EOC tissues and correlated with poor patient prognosis. Functional assays revealed that CRB2 enhances ovarian cancer cell proliferation, migration, and invasion, while suppressing apoptosis. Immunofluorescence staining of planar cell polarity markers demonstrated that CRB2 induces polarity alterations in EOC cells. Furthermore, Western blot analysis suggested that CRB2 may activate the Wnt/planar cell polarity (PCP) signalling pathway, contributing to tumour progression. These findings identify CRB2 as a key modulator of cell polarity and a potential driver of EOC aggressiveness. CRB2 may serve as a novel prognostic biomarker and therapeutic target for epithelial ovarian cancer.

Pituitary adenomas (PAs) are common intracranial tumours, and invasiveness in nonfunctioning invasive pituitary adenomas (NIPAs) predicts poor prognosis. The molecular mechanisms driving this phenotype remain unclear. This study explored the role of nuclear receptor subfamily 3 group C member 1 (NR3C1) in NIPA invasiveness and its regulation of Wnt signalling. mRNA expression profiles of 32 PA samples were generated by RNA-seq, and proteomic data from 19 samples were obtained by mass spectrometry. Immune-related differentially expressed genes (DEGs) were retrieved from GeneCards. Weighted gene coexpression network analysis identified modules and hub genes linked to invasiveness, while machine learning methods (support vector machine, LASSO, random forest) prioritised key genes. Gene set enrichment analysis (GSEA) assessed pathways associated with candidate gene expression. NR3C1 expression and function were validated by immunohistochemistry, Western blotting and invasion assays. Integration of transcriptomic, proteomic and immune-related datasets yielded 11 overlapping genes, with NR3C1 emerging as the top candidate. NR3C1 was significantly upregulated in NIPAs and demonstrated good discriminatory power by ROC analysis. GSEA associated high NR3C1 expression with Wnt pathway activation. Functional experiments confirmed that NR3C1 overexpression enhances the invasive capacity of PA cells. NR3C1 promotes the invasive phenotype of NIPAs by activating Wnt signalling. These findings suggest NR3C1 as a potential biomarker and therapeutic target for invasive pituitary adenomas.

Circulating tumor DNA (ctDNA) analysis has emerged as a pivotal minimally invasive tool for early detection, monitoring, and treatment stratification in cancer patients. However, the accuracy and reliability of ctDNA assays are profoundly influenced by preanalytical variables. This review discusses the impact of biological features (circadian rhythm, age, and sex), lifestyle factors (diet, smoking, and physical activity), as well as technical aspects such as hemolysis, leukocyte lysis, and delayed plasma separation on ctDNA integrity and concentration. Fluctuations in ctDNA levels driven by these factors highlight the need for clear guidelines regarding precollection timing, dietary restrictions, and sample processing. Furthermore, the adoption of harmonized protocols is essential to reduce variability and improve reproducibility across clinical and research settings.

Chondrosarcoma (CS) has a prognosis largely influenced by tumor grade. Although IDH mutations have been reported in CS, impact on patient`s survival remains controversial. This study aims to assess prognostic relevance of IDH mutations on disease-specific survival (DSS), metastasis-free survival (MFS), and local recurrence-free survival (RFS), in a large cohort of CS patients.

Ferroptosis, the most common programmed cell death process, and immune checkpoints play increasingly prominent roles in glioma. However, the effects of ferroptosis on immune checkpoints on glioma remain unclear. The intracellular ROS levels of ferroptotic glioma cells were observed via fluorescence microscopy. The extracellular Acetyl-HMGB1 content of ferroptotic glioma cells was detected via an ELISA kit. Transwell chambers (8.0 μm) were used to detect the invasion ability of ferroptotic glioma cells. The ability of ferroptotic glioma cells to proliferate was detected via the CCK-8 reagent. The apoptosis of ferroptotic glioma cells was detected via an Annexin V-FITC apoptosis kit. The transcriptional levels of four immune checkpoints (CD80, CD155, HMGB1, and galectin-9) in ferroptotic glioma cells were detected via RT-PCR. Ferroptosis in glioma cells promotes the release of acetyl-HMGB1 and autophagy is involved in this process. Inhibiting extracellular acetyl-HMGB1 while inducing ferroptosis promoted the invasion and proliferation of glioma cells and inhibited apoptosis. Ferroptosis downregulated the transcription of CD155 and galectin-9 in glioma cells, but inhibition of extracellular acetyl-HMGB1 reversed the effect of ferroptosis on the downregulation of galectin-9 transcription. In conclusion, ferroptosis downregulates galectin-9 transcription via extracellular acetyl-HMGB1, thereby inhibiting the biological behavior of glioma cells.

Tumor heterogeneity in breast cancer is well recognized, but research has largely focused on primary tumors, while metastatic lesions, particularly brain metastases (BM), remain understudied. With the rising incidence of BM in metastatic breast cancer (MBC) and their poor prognosis, a deeper understanding of the molecular mechanisms driving BM formation, progression, and immune evasion is crucial for developing better therapeutic strategies. We performed an integrated analysis of BM and matched primary breast tumors using immunohistochemistry, in-situ hybridization, tumor-infiltrating lymphocyte (TIL) quantification, and bulk RNA sequencing. Tumor receptor status, gene expression profiles, immune cell composition, and pathway alterations were analyzed in ten patients with paired samples. Changes in receptor status were observed between primary tumors and BM, including alterations in estrogen receptor and HER2 expression. RNA sequencing revealed differentially expressed genes and pathways, with an apparent downregulation of immune-related genes in BM. Immune profiling suggested a shift in the tumor microenvironment, with BM showing lower B- and CD8 + T-cell infiltration and a relative increase in M2 macrophages and follicular helper T-cells. While these findings are descriptive and limited by sample size, they point towards a potentially more immunosuppressive milieu in BM that may contribute to immune evasion and reduced responsiveness to checkpoint inhibitor therapy. Our study highlights molecular and immunological differences between primary breast tumors and BM. The altered immune landscape in BM, characterized by diminished TIL infiltration and an increase in immunosuppressive cells, warrants further investigation in larger, more homogeneous cohorts.

MRVI1 is a multifaceted gene whose functions in cancer vary across tissue types, acting either as a tumor-promoting or tumor-suppressive factor. In colorectal cancer, MRVI1 functions downstream of p53, and its loss enhances malignant phenotypes; however, the effects of MRVI1 overexpression have remained unclear. In this study, we established HCT116 colorectal cancer cells stably overexpressing MRVI1 to examine its functional impact. Western blot analysis confirmed robust expression of the V5-TurboID-MRVI1 fusion protein in the established cell line. Cell proliferation assays showed that MRVI1 overexpression markedly reduced cell growth compared with control cells under standard culture conditions. Trypan blue staining demonstrated that MRVI1 overexpression did not increase cell death, indicating that the reduction in cell number reflects a cytostatic rather than cytotoxic effect. These findings provide direct evidence that MRVI1 suppresses the proliferation of colorectal cancer cells when overexpressed. Combined with previous reports demonstrating that MRVI1 knockdown promotes proliferation and invasive behavior in colorectal cancer cells, our results support the view that MRVI1 contributes to p53-associated growth control in this tumor lineage. These observations further reinforce the concept that MRVI1 is a context-dependent, multifaceted cancer-associated gene.

Cancer progression is governed by a dynamic interplay between genetic alterations and epigenetic modifications, which shape tumor adaptation, immune evasion, and therapy resistance. Among these modifications, epigenetic regulation of autophagy, a cellular process critical for maintaining homeostasis, has emerged as a key player in cancer biology. While autophagy suppresses tumor initiation by eliminating damaged organelles and reducing oxidative stress, tumors can hijack this process to sustain survival under metabolic stress and promote resistance to chemotherapy, radiotherapy, and immunotherapy. This review explores the intricate crosstalk between DNA methylation, histone modifications, and non-coding RNAs in controlling autophagy-related genes and their dual role in cancer progression. We also highlight the therapeutic potential of targeting epigenetic modulators (HDAC and DNMT inhibitors) and autophagy regulators to overcome multidrug resistance. Understanding the epigenetic-autophagy axis provides novel insights into cancer treatment, emphasizing the need for personalized approaches that balance autophagic activity to enhance therapy efficacy and improve patient outcomes. This emerging field presents a promising frontier for epigenetic-driven precision medicine in oncology.

The epigenetic landscape of cancer reveals how microRNAs (miRNAs) regulate gene expression through epigenetic mechanisms, alongside advancements in miRNA-based biosensor technology for early detection. Epigenetics, which studies heritable gene function changes without altering DNA sequences, has transformed our understanding of cancer by highlighting the complex interaction between genetics and environment. Key mechanisms such as DNA methylation, histone modification, and chromatin remodelling shape gene expression and cellular identity, with dysregulation in these processes often marking cancer development. Within this framework, miRNAs act as crucial epigenetic regulators, influencing gene expression post-transcriptionally and functioning as either oncogenes (oncomiRs) or tumour suppressors. miRNAs interact with epigenetic modifiers like histone deacetylases (HDACs) and DNA methyltransferases (DNMTs), creating regulatory networks that affect cancer cell behaviours such as proliferation, differentiation, and apoptosis. To apply these molecular insights, the chapter reviews innovations in miRNA-targeting biosensors. Electrochemical and photoelectrochemical biosensors, enhanced with nanotechnology, are designed to detect miRNAs at ultra-low concentrations in biological fluids, addressing limitations of conventional cancer diagnostics. These biosensors offer high sensitivity, specificity, and point-of-care potential, with benefits such as rapid response, cost-efficiency, and miniaturization. Case studies showcase miRNA-based biosensors targeting cancer-related miRNAs, underscoring their promise in early cancer detection and monitoring. By bridging epigenetics, miRNA regulation, and biosensor technology, these emerging diagnostic tools offer new possibilities for improving cancer diagnosis and patient outcomes.

The dysregulation at the epigenetic level, such as DNA methylation, histone modifications, and changes in noncoding RNA, plays an important role in many serious human pathologies, including cancers. Epigenetics modulates the expression of tumor-related genes without any changes in the DNA sequences, thus understanding the epigenetic profile is a promising way to clarify the underlying mechanism of cancers as well as other diseases. Specific techniques like chromatin immunoprecipitation followed by sequencing (ChIP-seq), whole-genome bisulfite sequencing (WGBS), or mass spectrometry (MS) were developed to obtain epigenetic data. This leads to the need for robust tools to analyze and interpret these high-throughput data. With the development of bioinformatics tools, several complex interactions between DNA methylation and chromatin modification were clarified to help researchers control gene expression. Moreover, data science, and information technology, especially machine learning and deep learning, have revolutionized the study of epigenetics in cancer, providing powerful tools to integrate both genetic and epigenetic data, as well as clinical/para-clinical characteristics to enhance the accuracy of cancer diagnosis and treatment strategies. In this study, we will provide an overview of epigenetics' role in cancer, and more importantly, an update on the application of bioinformatics and data science in the epigenetic field for cancers. Integrating epigenetic data with other data like omics and clinical data with the help of bioinformatics and data science is an emerging direction for deciphering the epigenetic landscape of cancer and identifying potential therapeutic targets.

One of the three most common cancers in the world today is breast cancer. In recent years, molecular biology studies have highlighted the role of gene mutations. Epigenetic modifications have also been studied and have been shown to be one of the main contributors to the development and progression of breast cancer. Targeting these epigenetic regulatory mechanisms is considered a potential therapeutic strategy with the goal of inhibiting tumor progression and restoring normal gene activity. Epigenetic research has shed light on the important role of epigenetics in various aspects of breast cancer development, the underlying mechanisms of breast cancer, and its potential applications in improving diagnosis, prognosis, and treatment. These findings highlight the transformative potential of epigenetics in advancing the understanding and management of breast cancer. From there, it opens opportunities to detect breast cancer early even in a non-invasive way.

Ovarian cancer is a highly heterogeneous and lethal gynecological malignancy, with its progression tightly regulated by both genetic and epigenetic mechanisms. Among the epigenetic regulators, histone modifications-including acetylation, methylation, phosphorylation, ubiquitination, and SUMOylation-have emerged as pivotal modulators of chromatin architecture and gene transcription. These post-translational modifications, governed by specific histone-modifying enzymes, shape the transcriptional landscape of tumor cells and influence key oncogenic processes such as cellular proliferation, invasion, stemness, DNA repair, and chemotherapy resistance. Dysregulation of enzymes such as histone acetyltransferases (HATs), deacetylases (HDACs), methyltransferases (HMTs), demethylases (HDMs), ubiquitin ligases, and SUMO ligases has been implicated in the pathogenesis of ovarian cancer and is associated with adverse clinical outcomes. Importantly, these modifications are reversible, rendering them tractable therapeutic targets. This review provides a comprehensive synthesis of the major classes of histone modifications and their biological functions in ovarian cancer, highlights recent insights into the interplay between different modifications (crosstalk), and evaluates ongoing therapeutic strategies that aim to reverse epigenetic dysregulation. By elucidating the complex epigenetic landscape, this review supports the development of next-generation diagnostic, prognostic, and therapeutic approaches in ovarian cancer.

Malignant melanoma is the most aggressive and lethal type of skin cancer associated with increased mortality rates. Moreover, beyond the genetic background, the altered epigenetic landscape (e.g., abnormal patterns of DNA methylation, aberrant histone modifications and de-regulated expression levels of ncRNAs) further contributes to the pathophysiology of the disease. In addition, despite the improvement of current anti-melanoma strategies and the development of new therapeutic approaches, the 5-year survival among melanoma patients is still high, mainly due to acquired-drug resistance. On the other hand, phytochemicals have been associated with various health-promoting properties through pleiotropic mechanisms including acting as potent epigenetic regulators restoring back a normal phenotype in various experimental cancer models. In this review article, we discuss the general characteristics of malignant melanoma and current therapeutic approaches while we report the epigenetic basis of the disease along with the main compounds capable of restoring a normal epigenetic landscape. Finally, we describe the role of various phytochemicals in targeting the epigenome of malignant melanoma thereby potentially acting as an alternative therapeutic approach.

Spontaneous pneumothorax (SP) is defined by the presence of air in the pleural space arising from neither trauma nor iatrogenic causes. It can develop secondary to various etiologies. The familial clustering observed in some patients with SP supports the view that genetic factors play a role in the pathogenesis of SP. Several recognizable pneumothorax-associated genetic syndromes exist, including Birt-Hogg-Dubé syndrome (BHD), tuberous sclerosis complex-associated lymphangioleiomyomatosis (TSC-LAM), Marfan syndrome (MFS), cystic fibrosis (CF), alpha-1 antitrypsin deficiency (AATD), vascular Ehlers-Danlos syndrome (vEDS), Loeys-Dietz syndrome (LDS), and a few others. Recognition of these syndromes underlying SP facilitates optimal management and counseling regarding prognosis and potential comorbidities. In this review, we systematically summarize several genetic syndromes associated with pneumothorax, in which SP may manifest either as an initial presenting symptom or as a potential complication that adversely affects the prognosis.

Tertiary lymphoid structures (TLS) are organized lymphoid aggregates that form outside lymph nodes within the tumor microenvironment. They are linked to better prognosis and stronger antitumor immune responses. However, the key molecular factors that control TLS maturation in non-small cell lung cancer (NSCLC) are still not clear, and their prognostic value is not fully defined. We analyzed TLS-related genes to identify markers linked to prognosis. We used consensus clustering to define molecular subtypes with different survival outcomes. We then built a TLS risk score signature (TLSRS) using LASSO-Cox regression and tested it in independent meta-GEO cohorts. We also examined the association between DKK1 expression and TLS maturation by multiplex immunofluorescence in a clinical cohort. TLSRS separated patients into high- and low-risk groups in the training cohort (n = 503, P < 0.0001) and in the validation cohorts (n = 681, P < 0.0001). The time-dependent AUC values were 0.762, 0.710, and 0.708 at 1, 3, and 5 years. Multivariable analysis showed that TLSRS was an independent prognostic factor in all cohorts. Patients with low TLSRS showed higher immune cell infiltration and higher CCL19 expression, and they also showed stronger immune-related activity across cohorts. In an independent in-house cohort (n = 119), higher DKK1 expression was linked to worse overall survival. DKK1 expression was negatively correlated with the TLS maturity ratio, but it was not correlated with the number of TLS. We developed a prognostic TLSRS that captures key features of the immune microenvironment in NSCLC. We also found that DKK1 may act as a negative regulator of TLS maturation. These results help explain TLS biology and suggest that DKK1 could be a therapeutic target to improve antitumor immunity in NSCLC.

Structural variants (SVs) are increasingly recognized as important contributors to oncogenesis through their effects on 3D genome folding. Recent advances in whole-genome sequencing have enabled large-scale profiling of SVs across diverse tumors, yet experimental characterization of their individual impact on genome folding remains infeasible. Here, we leveraged a convolutional neural network, Akita, to predict disruptions in genome folding caused by somatic SVs identified in 61 tumor types from the Children's Brain Tumor Network dataset. Our analysis reveals significant variability in SV-induced disruptions across tumor types, with the most disruptive SVs coming from lymphomas and sarcomas, metastatic tumors, and germline cell tumors. Dimensionality reduction of disruption scores identified five recurrently disrupted regions enriched for high-impact SVs across multiple tumors. Some of these regions are highly disrupted despite not being highly mutated, and harbor tumor-associated genes and transcriptional regulators. To further interpret the functional relevance of high-scoring SVs, we integrated epigenetic data and developed a modified Activity-by-Contact scoring approach to prioritize SVs with disrupted genome contacts at active enhancers. This method highlighted highly disruptive SVs near key oncogenes, as well as novel candidate loci potentially implicated in tumorigenesis. These findings highlight the utility of machine learning for identifying novel SVs, loci, and genetic mechanisms contributing to pediatric cancers. This framework provides a foundation for future studies linking SV-driven regulatory changes to cancer pathogenesis.

Lung cancer, being the top cause of global cancer-related mortality, calls for effective treatments. RN7SK (7SK) is a long non-coding RNA (lncRNA) that plays a significant role in the regulation of gene transcription and thereby controls essential cellular activities. Limited evidence supports the anticancer potential of 7SK, and its suppressive effects have not been tested against lung cancer. This study explored the anticancer effects of RN7SK (7SK), a long non-coding RNA known to regulate gene transcription, through exosome-mediated delivery in lung cancer cells. Treatment with exosome-loaded 7SK (Exo-7SK) significantly elevated 7SK levels in non-small-cell lung cancer cells and suppressed key cancer traits. Exo-7SK reduced cell viability and proliferation, promoted apoptosis, and inhibited migration and invasion by shifting gene expression away from epithelial-mesenchymal transition. It also impaired spheroid formation and reduced spheroid dispersion and viability in 3D microfluidic cultures. In conclusion, our findings highlight the cancer-suppressive potential of exosome-mediated 7SK delivery against lung cancer, demonstrating significant efficacy in both 2D and 3D culture models. These observations warrant further confirmation in future studies employing advanced designs and clinically relevant models.

Liquid biopsies offer a promising, noninvasive approach for monitoring and predicting responses to immunotherapy across multiple solid tumors. For the most part these are circulating tumor DNA (ctDNA) based assays. Here, we discuss the biological basis, clinical evidence, and potential applications of different types of ctDNA assays in tracking tumor dynamics, distinguishing pseudoprogression, and assessing minimal residual disease. We explore the current limitations, assay variability, and future directions, including integration with other biomarkers and real-world clinical trials aimed at validating ctDNA as a routine tool in precision immuno-oncology.

In biomedical studies, testing for differences in covariance may offer scientific insights, especially when differences are driven by complex joint behavior between features. However, when differences in joint behavior are weakly dispersed across many dimensions and arise from differences in low-rank structures within the data, as is often the case in genomics and neuroimaging, existing two-sample covariance testing methods may suffer from power loss. The Ky-Fan(k) norm, defined by the sum of the top k singular values, is a simple and intuitive matrix norm able to capture signals caused by differences in low-rank structures between matrices, but its statistical properties in hypothesis testing have not been studied well. In this paper, we investigate the behavior of the Ky-Fan(k) norm in two-sample covariance testing. Ultimately, we propose a novel methodology, rank-adaptive covariance testing (RACT), which is able to leverage differences in low-rank structures found in the covariance matrices of two groups in order to maximize power. RACT uses permutation for statistical inference, ensuring an exact Type I error control. We validate RACT in simulation studies and evaluate its performance when testing for differences in gene expression networks between two types of lung cancer, as well as testing for covariance heterogeneity in diffusion tensor imaging data taken on two different scanner types.