Evaluation of a deep-learning segmentation model for patients with colorectal cancer liver metastases (COALA) in the radiological workflow

OBJECTIVES

For patients with colorectal liver metastases (CRLM), total tumor volume (TTV) is prognostic. A deep-learning segmentation model for CRLM to assess TTV called COlorectal cAncer Liver metastases Assessment (COALA) has been developed. This study evaluated COALA's performance and practical utility in the radiological picture archiving and communication system (PACS). A secondary aim was to provide lessons for future researchers on the implementation of artificial intelligence (AI) models.

METHODS

Patients discussed between January and December 2023 in a multidisciplinary meeting for CRLM were included. In those patients, CRLM was automatically segmented in portal-venous phase CT scans by COALA and integrated with PACS. Eight expert abdominal radiologists completed a questionnaire addressing segmentation accuracy and PACS integration. They were also asked to write down general remarks.

RESULTS

In total, 57 patients were evaluated. Of those patients, 112 contrast-enhanced portal-venous phase CT scans were analyzed. Of eight radiologists, six (75%) evaluated the model as user-friendly in their radiological workflow. Areas of improvement of the COALA model were the segmentation of small lesions, heterogeneous lesions, and lesions at the border of the liver with involvement of the diaphragm or heart. Key lessons for implementation were a multidisciplinary approach, a robust method prior to model development and organizing evaluation sessions with end-users early in the development phase.

CONCLUSION

This study demonstrates that the deep-learning segmentation model for patients with CRLM (COALA) is user-friendly in the radiologist's PACS. Future researchers striving for implementation should have a multidisciplinary approach, propose a robust methodology and involve end-users prior to model development.

CRITICAL RELEVANCE STATEMENT

Many segmentation models are being developed, but none of those models are evaluated in the (radiological) workflow or clinically implemented. Our model is implemented in the radiological work system, providing valuable lessons for researchers to achieve clinical implementation.

KEY POINTS

Developed segmentation models should be implemented in the radiological workflow. Our implemented segmentation model provides valuable lessons for future researchers. If implemented in clinical practice, our model could allow for objective radiological evaluation.

Small intestinal neuroendocrine tumors lack early genomic drivers, acquire DNA repair defects and harbor hallmarks of low REST expression

The tumorigenesis of small intestinal neuroendocrine tumors (siNETs) is not understood and comprehensive genomic and transcriptomic data sets are limited. Therefore, we performed whole genome and transcriptome analysis of 39 well differentiated siNET samples. Our genomic data revealed a lack of recurrent driver mutations and demonstrated that multifocal siNETs from individual patients can arise genetically independently. We detected germline mutations in Fanconi anemia DNA repair pathway (FANC) genes, involved in homologous recombination (HR) DNA repair, in 9% of patients and found mutational signatures of defective HR DNA repair in late-stage tumor evolution. Furthermore, transcriptomic analysis revealed low expression of the transcriptional repressor REST. Summarizing, we identify a novel common transcriptomic signature of siNETs and demonstrate that genomic alterations alone do not explain initial tumor formation, while impaired DNA repair likely contributes to tumor evolution and represents a potential pharmaceutical target in a subset of patients.

High prevalence of hyperuricemia and its risk factors in a Chinese cohort of primary hyperparathyroidism patients

PURPOSE

Primary hyperparathyroidism (PHPT) is characterized by autonomous and excessive parathyroid hormone (PTH) secretion due to parathyroid gland lesions. Patients can be complicated with hyperuricemia (HUA), however, data about HUA in Chinese PHPT patients are lacking. This study aimed to explore the prevalence of HUA, factors influencing serum uric acid (SUA) level and the impacts of parathyroidectomy (PTX).

METHODS

328 inpatients diagnosed with PHPT were included in total. Clinical data were collected and compared between HUA and non-HUA group. Multivariate linear regression was used to explore the factors affecting preoperative SUA and its variation after PTX. The impacts of SUA on bone mineral density (BMD) under different models were also analyzed.

RESULTS

The prevalence of HUA in PHPT patients was nearly 32%. Compared with non-HUA group, HUA group had significantly higher serum calcium (Ca) (2.92 [2.75, 3.26] vs. 2.78 [2.62, 3.03] mmol/L, P < 0.001), while PTH increased without significance. Gender, body mass index, serum Ca, triglycerides and renal function were independently associated with SUA. SUA decreased after PTX (340.00 [291.50, 421.00] vs. 315.00 [270.50, 375.00] μmol/L, P = 0.018), with change of SUA significantly associating with changes in serum Ca and phosphate. Presurgical SUA was positively related with femoral neck, total hip and lumbar spine BMDs after adjusting for confounders.

CONCLUSION

A relatively high proportion of HUA was found in our study. Besides the common risk factors, hypercalcemia may contribute to the increased SUA in PHPT patients, which could be significantly improved by curative PTX. SUA might have a protective effect on bone loss in PHPT patients.

Exploration of Pathogenesis and Cutting-Edge Treatment Strategies of Sarcopenia: A Narrative Review

Sarcopenia a progressive and multifactorial musculoskeletal syndrome characterized by loss of muscle mass and function, poses a significant global health challenge, particularly in aging populations. Epidemiological studies reveal that sarcopenia affects approximately 5-10% of the general population, with prevalence rates escalating dramatically after age 60 to reach 10-27% in older adults. This age-associated increase contributes significantly to healthcare burdens by elevating risks of disability, frailty, and mortality. Despite its profound impact, current clinical approaches to sarcopenia remain limited. While resistance exercise and protein supplementation form the cornerstone of management, their efficacy is often constrained by poor long-term adherence and variable individual responses, highlighting the urgent need for more comprehensive and personalized treatment strategies. The pathogenesis of sarcopenia is complex and influenced by various factors, including aging, inflammation, nutritional deficits, physical inactivity, and mitochondrial dysfunction. However, the precise molecular mechanisms underlying this condition are still not fully understood. Recent research has made significant strides in elucidating the intricate mechanisms contributing to sarcopenia, revealing novel insights into its molecular and cellular underpinnings. Notably, emerging evidence points to the pivotal role of mitochondrial dysfunction, altered myokine profiles, and neuromuscular junction degeneration in sarcopenia progression. Additionally, breakthroughs in stem cell therapy, exosome-based treatments, and precision nutrition offer promising avenues for clinical intervention. This review aims to synthesize the latest advancements in sarcopenia research, focusing on the novel contributions to its pathogenesis and treatment strategies. We explore emerging trends such as the role of cellular senescence, epigenetic regulation, and targeted therapeutic interventions that could reshape future approaches to managing sarcopenia. By highlighting recent breakthroughs and cutting-edge research, we hope to advance the understanding of sarcopenia and foster the translation of these findings into effective clinical therapies.

Predictive value of combined DCE-MRI perfusion parameters and clinical features nomogram for microsatellite instability in colorectal cancer

OBJECTIVES

To develop a nomogram that combines dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameters, ADC values and clinical features to preoperatively identify microsatellite instability (MSI) in patients with colorectal cancer (CRC).

METHODS

This retrospective study included 63 CRC patients who underwent preoperative DCE-MRI and had immunohistochemistry results available. Two radiologists, in a double-blind manner, placed two circular regions of interests in the area with the highest perfusion intensity on the DCE-MRI perfusion map and the corresponding area on the ADC map. Perfusion parameters and ADC values were measured, and the average values from both radiologists were used for subsequent analysis. Univariate analysis was performed to identify independent risk factors for MSI. A nomogram was then constructed by combining the most significant clinical risk factors with DCE-MRI perfusion parameters. The model's performance was evaluated using receiver operating characteristic (ROC) curves. Calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC) were used to assess the nomogram's clinical utility and net benefit.

RESULTS

The nomogram prediction model, which combined PLT, LNM, Ktrans, Kep, iAUC, and ADC, demonstrated good predictive performance. The combined model had an AUC of 0.951 (95% CI: 0.903-0.998), an accuracy of 0.873, a sensitivity of 1.000, and a specificity of 0.818. Both the DCA and CIC demonstrated good clinical applicability and net benefit.

CONCLUSION

The nomogram method demonstrated good potential in the preoperative individualized identification of MSI status in CRC patients. This tool can assist clinicians in adopting appropriate treatment strategies and optimizing personalized stratification for CRC patients.

"Actual" peptide properties required for nanoparticle development in precision cancer therapeutic delivery

Functionalizing nanoparticles with peptides (3-30 amino acids) reduces premature clearance and increases colloidal stability and targeting capacity of cancer therapeutics. Glutamate/lysine-rich zwitterionic and hydrophilic/neutral peptides minimize reticuloendothelial digestion of nanomedicine through reducing particle hydrophobicity and depressing plasma anti-PEG immunoglobulin that disrupts the PEG-based particle stealth. Anionic peptides negate protein corona formation and subsequent particle aggregation in vivo enabling efficient nanoparticles biodistribution and drug targeting by facilitating their endothelial/extracellular matrix pore diffusion. Cationic and hydrophobic peptides display a strong affinity for anionic cancer cell membrane and mediate membrane porosification or receptor binding leading to particle uptake and endocytosis. The peptide ionic and hydrophobicity/hydrophilicity attributes collectively facilitate endosomal escape, and nuclear and mitochondria targeting of nanoparticles. Peptides are required to present with different physicochemical attributes from administration site, through blood and extracellular matrix, to cancer site of action. Charge/hydrophilicity-hydrophobicity switching and projection of receptor-specific domain of peptides are attainable through pH-pKa interplay and labile bond hydrolysis of "unwanted" domain to give rise to new functional domains in response to pH, thermal and enzymatic stimuli. Co-introducing all functional attributes on a single peptide is challenging. Use of peptide blends risks leaching during nanoparticles production. Peptides-nanoparticles conjugation risks peptide conformational alterations and loss of acidic/basic termini affecting their roles in nanoparticle stabilization, targeting, membrane permeabilization and subcellular delivery.

Artificial intelligence in neuro-oncology: methodological bases, practical applications and ethical and regulatory issues

Artificial Intelligence (AI) is transforming neuro-oncology by enhancing diagnosis, treatment planning, and prognosis prediction. AI-driven approaches-such as CNNs and deep learning-have improved the detection and classification of brain tumors through advanced imaging techniques and genomic analysis. Explainable AI methods mitigate the "black box" problem, promoting model transparency and clinical trust. Mechanistic models complement AI by integrating biological principles, enabling precise tumor growth predictions and treatment response assessments. AI applications also include the creation of digital twins for personalized therapy optimization, virtual clinical trials, and predictive modeling for estimation of tumor resection and pattern of recurrence. However, challenges such as data bias, ethical concerns, and regulatory compliance persist. The European Artificial Intelligence Act and the Health Data Space Regulation impose strict data protection and transparency requirements. This review explores AI's methodological foundations, clinical applications, and ethical challenges in neuro-oncology, emphasizing the need for interdisciplinary collaboration and regulatory adaptation.

Advancing Oncology Drug Development in the US: The Interplay between Innovations and Regulatory Science

The landscape of drug development has evolved with the adoption of new therapeutic modalities, cutting-edge technology platforms, emerging scientific insights, and modern patient-centric clinical trial designs. In this review, we investigate the interplay between innovation and regulatory science in cancer drug development in the United States. As new innovations emerge, regulatory science adapts to integrate new discoveries and technologies, ensuring alignment with established regulations and safety standards. This fuels additional innovations through data and evidence generation, potentially expediting the development of revolutionary treatments and advancing patient access to novel, promising therapies. Early and frequent engagement with regulators is vital for drug developers aiming to successfully apply innovative approaches.

The Role of EBV in the Pathogenesis of Diffuse Large B-Cell Lymphoma

There are multiple established risk factors for DLBCL; these risk factors share an underlying biology, which generally cause immune dysfunction, spanning immunosuppression to chronic inflammation. EBV is an established risk factor for DLBCL and approximately 10% of DLBCLs are EBV-positive. EBV is a ubiquitous infection, and it is thus among populations that are immunocompromised, by age or medically defined, where EBV-positive DLBCLs arise. In this chapter, we review the current classification, epidemiology, clinical, pathology, and molecular characteristics of EBV-positive DLBCL, and discuss the role of EBV in lymphoma tumorigenesis. We further discuss current and novel treatments aimed at the NFκB pathway and other targets.

Alternative splicing in human cells exposed to ionizing radiation: a comprehensive review of ex vivo and in vivo studies

PURPOSE

This study reviews how ionizing radiation (IR) induces alternative splicing (AS) in non-tumor and tumor cells under both ex vivo and in vivo irradiation conditions. The relevance and limitations of IR-induced AS in identifying potential biomarkers are highlighted for two main applications: biodosimetry and radiotherapy.

CONCLUSIONS

Radiation promotes alterations in AS, which may differentially affect the response in both tumor and non-tumor cells. This response can occur in genes that change their overall expression as well as in those that remain unaltered in response to IR. Although cis-regulators modulate AS, trans-regulators like splicing factors are more involved in the IR response. Variants of key genes involved in the DNA damage response (DDR) are regulated in non-tumor cells while they are often deregulated in tumor cells favoring radioresistance. Identifying IR-induced AS variants could enhance the sensitivity of biodosimeters for dose estimation and biomarkers for radiosensitivity, offering potential strategies to personalize radiotherapy and improve outcomes. New and advanced sequencing technologies will allow variant identification important for the field of radiobiological research.

Global DNA methylation differences involving germline structural variation impact gene expression in pediatric brain tumors

The extent of genetic variation and its influence on gene expression across multiple tissue and cellular contexts is still being characterized, with germline Structural Variants (SVs) being historically understudied. DNA methylation also represents a component of normal germline variation across individuals. Here, we combine germline SVs (by short-read sequencing) with tumor DNA methylation across 1292 pediatric brain tumor patients. For thousands of methylation probes for CpG Islands (CGIs) or enhancers, rare and common SV breakpoints upstream or downstream associate with differential methylation in tumors spanning various histologic types, a significant subset involving genes with SV-associated differential expression. Cancer predisposition genes involving SV-associated differential methylation and expression include MSH2, RSPA, and PALB2. SV breakpoints falling within CGIs or histone marks H3K36me3 or H3K9me3 associate with differential CGI methylation. Genes with SVs and CGI methylation associated with patient survival include POLD4. Our results capture a class of normal phenotypic variation having disease implications.

Parallel and convergent dynamics in the evolution of primary breast and lung adenocarcinomas

Cancer development requires an evolutionary transformation from mammalian cells fully regulated by and integrated into multicellular tissue to cancer cells  that, as single cell protists, are individually subject to Darwinian selection. Through genetic and epigenetic mechanisms of inheritance, the evolving cancer phenotype must acquire independence from host controls, downregulate differentiated functions that benefit the host but not individual cells, and generate phenotypic traits that increase fitness in the context of the selection forces within the local microenvironment. Here, we investigate this  evolutionary transition in breast (BRCA) and lung (LUAD, without EGFR, KRAS or BRAF driver mutations) adenocarcinomas using bulk mutation and expression data from the TCGA database. We define evolution selection for genes and molecular pathways based on 1) changes in gene expression compared to normal tissue, and 2) significantly larger or smaller observed mutation rates compared to those expected based on the gene size. We find BRCA and LUAD disable different genes and gene pathways associated with tissue-specific signaling and differentiated functions but promote common molecular pathways associated with cell cycle, cell-cell interactions, cytoskeleton, voltage gated ion channels, and microenvironmental niche construction. Thus, tissue-specific parallel evolution in early cancer development is followed by convergence to a common cancer phenotype.

Tumor diagnosis recharacterization enabled by comprehensive genomic profiling to guide precision medicine strategy

Comprehensive genomic profiling (CGP) via next-generation sequencing is standard clinical practice for advanced and metastatic cancers in the U.S. and can help identify clinically actionable alterations in patients who may benefit from targeted therapies. CGP can also complement clinicopathological findings and in certain cases, may lead to diagnostic recharacterization resulting in more precise therapeutic strategies. Here, we highlight examples where molecular findings resulted in tumor re-evaluation and subsequent recharacterization. Twenty-eight cases where CGP results were inconsistent with initial pathological diagnosis and clinical presentation were selected for secondary clinicopathological review to explore alternative diagnostic explanations more consistent with the genomic results. Genomic profiling identified clinically actionable and prognostic variants leading to more accurate therapeutic recommendations based on the updated diagnoses highlighting the value of CGP beyond biomarker detection for therapy selection and supporting its complementary use in diagnostic confirmation to unveil opportunities for precision medicine strategies.

CALB2 facilitates macrophage M2 polarization to promote the growth and metastasis of pancreatic adenocarcinoma

Tumor-associated macrophages mainly differentiate into M2 phenotypes, which secrete cytokines that reshape the tumor microenvironment and promote tumor progression. This study was to explore the mechanism of CALB2 in M2 polarization and pancreatic adenocarcinoma (PAAD). Clinical tissue samples of PAAD were collected, followed by detection of WTAP, FOSL1, and CALB2 expression. The correlation between WTAP and FOSL1 or between FOSL1 and CALB2 was analyzed. THP1 cells were induced into M0 macrophages, followed by plasmid transfection and induction of M2-type macrophages. After macrophages were co-cultured with PAAD cells, functional experiments were designed to evaluate PAAD cell malignant behaviors. A transplantation tumor model and a liver metastasis model were established to assess tumor growth and metastasis. High expression of WTAP, FOSL1, and CALB2 was found in PAAD tissues and M2-type macrophages. WTAP positively linked with FOSL1, so as FOSL1 and CALB2. Mechanistically, WTAP enhanced m6A modification of FOSL1 to promote its expression, and FOSL1 promoted CALB2 transcription. Knockdown of WTAP, FOSL1, or CALB2 in macrophages inhibited PAAD cell malignant behaviors, which could be reversed by CALB2 upregulation. WTAP knockdown restrained the growth and metastasis of PAAD in nude mice via the FOSL1/CALB2 axis. In conclusion, WTAP increased the m6A level of FOSL1, activated CALB2 transcription, and promoted M2 polarization of macrophages, thereby promoting the growth and metastasis of PAAD.

GEPIA3: Enhanced drug sensitivity and interaction network analysis for cancer research

The GEPIA series has provided robust and widely used tools for pan-cancer analysis of gene expression data. In the post-genomic era, a major challenge lies in deconvoluting complex regulatory relationship influenced by multiple factors and discovering gene-based precision therapeutics. Here we present GEPIA3, an advanced version of GEPIA that provides a comprehensive analysis of gene/protein interactions across various cancer types. This version facilitates the investigation of treatment sensitivity utilizing both real-world patient data and cell line screens for over 1000 therapeutic agents, as well as the integration of RNA alterations derived from the pan-cancer analysis of whole genomes project. GEPIA3 represents a significant enhancement of the original platform, enabling in-depth exploration of gene regulation and cancer phenotypes, thereby supporting the identification of novel biomarkers and therapeutic targets. GEPIA3 is publicly accessible at https://gepia3.bioinfoliu.com.

Pericardial Fat and Primary Tumor Radiomics for Predicting Occult N2 Disease and Survival in Clinical Stage I Non-Small Cell Lung Cancer: Multicenter Study With Biologic Correlation

Background: Occult N2 disease significantly affects clinical stage I non-small cell lung cancer (NSCLC) prognosis. Pericardial fat characteristics also have prognostic associations. Objective: To develop and test a model incorporating pericardial fat and tumor radiomic features on CT for detecting occult N2 disease in clinical stage I NSCLC, explore the model's prognostic role, and investigate its biologic basis through radiogenomics analyses. Methods: This retrospective study included patients who underwent clinical stage I NSCLC resection at three hospitals [center 1 (January 2016 to December 2022), stratified randomly by 6:2:2 ratio into training, tuning, and internal test sets; centers 2 and 3 (January 2019 to December 2023), serving as external test sets]. Pericardial fat and primary tumors were segmented on preoperative CT to extract radiomic features and generate tumor and fat rad-scores, respectively. Multivariable analysis was performed to create a hybrid model for predicting occult N2 disease at surgery. Performance was evaluated in external test sets. Associations with recurrence-free survival (RFS) and overall survival (OS) were evaluated using log-rank tests in the internal test set; follow-up data were unavailable in external test sets. Biologic mechanisms were explored through RNA and gene expression analysis in a separate set of patients with NSCLC obtained from a public radiogenomics database. Results: From the three centers, 1662 patients (mean age, 58.6 years; 663 men, 999 women) were included. Following multivariable analysis, the hybrid model included nodule density, fat rad-score, and tumor rad-score. The model had AUC, accuracy, sensitivity, and specificity for occult N2 disease of 0.921, 89.7%, 59.3%, and 93.1%, and 0.913, 91.8%, 56.2%, and 95.5% in external test sets 1 and 2, respectively. High-risk compared with low-risk patients, applying the model in the internal test set, showed worse RFS (p<.001) and OS (p<.001). In 122 patients in radiogenomics analysis, high-risk status was associated with activation of molecular pathways and increased activated dendritic cell and mast cell infiltration. Conclusion: A model incorporating tumor and pericardial fat radiomics showed good performance in predicting occult N2 disease as well as associations with survival and with RNA and gene expression. Clinical Impact: The model could help guide NSCLC management.

Associations of sarcopenia, sarcopenia components and sarcopenic obesity with cancer incidence: A prospective cohort study of 414,094 participants in UK Biobank

Sarcopenia is characterised by low grip strength, muscle quantity or quality, and physical performance. This study investigated the associations of sarcopenia and its components with cancer incidence. A prospective cohort study was conducted utilising data from the UK Biobank. Sarcopenia and its components were defined according to the European Working Group on Sarcopenia in Older People criteria (EWGSOP2 2019). Cox proportional hazard models adjusted for sociodemographic, lifestyle, and health-related factors were performed. Overall, 63,379 out of 414,094 study participants had an incident diagnosis of cancer during a median follow-up of 11.7 years. In total, 32,286 participants had probable sarcopenia and 934 confirmed/severe sarcopenia at recruitment. Combined probable, confirmed, and severe sarcopenia was associated with a higher risk of liver (hazard ratio [HR] = 1.65, 95% confidence interval [CI]: 1.17-2.33), haematological (HR = 1.22, 95% CI: 1.01-1.46), and colorectal cancer (HR = 1.21, 95% CI: 1.04-1.41) in males, but not in females. The components of sarcopenia were associated with a higher risk of several cancers, including low grip strength (with liver, haematological and colorectal cancer in males), low muscle mass index (oesophageal in females and oral cancer in males), and slow walking pace (liver and lung in males, lung and overall cancer in females). Compared to participants with non-sarcopenic obesity, those with sarcopenic obesity had a higher risk of colorectal cancer in males (HR = 1.31, 95% CI: 1.03-1.68). Our study suggests that sarcopenia, sarcopenia components, and sarcopenic obesity can be associated with risk for several cancers, mainly of the gastrointestinal tract and in males. Thus, early identification of sarcopenia components may benefit cancer prevention.

Genomic landscape of multiple myeloma and its precursor conditions

Reliable strategies to capture patients at risk of progression from precursor stages of multiple myeloma (MM) to overt disease are still missing. We assembled a comprehensive collection of MM genomic data comprising 1,030 patients (218 with precursor conditions) that we used to identify recurrent coding and non-coding candidate drivers as well as significant hotspots of structural variation. We used those drivers to define and validate a simple 'MM-like' score, which we could use to place patients' tumors on a gradual axis of progression toward active disease. Our MM precursor genomic map provides insights into the time of initiation and cell-of-origin of the disease, order of acquisition of genomic alterations and mutational processes found across the stages of transformation. Taken together, we highlight here the potential of genome sequencing to better inform risk assessment and monitoring of MM precursor conditions.

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

Joint association of frailty index and biological age with chronic obstructive pulmonary disease: a cohort study from CHARLS

Chronic Obstructive Pulmonary Disease (COPD) is associated with frailty and ageing, but there is insufficient evidence from existing longitudinal studies. This research explored the longitudinal association between frailty, ageing and COPD. We used the China Health and Retirement Longitudinal Study (CHARLS) data to perform a cohort study. The study population was non-COPD patients in wave 1 (2011), and the outcome was the occurrence of COPD at the end of follow-up (wave 4-wave 5). Frailty was assessed using the CHARLS modified frailty index (CMFI), and ageing was evaluated using the biological age (BA). We used multivariate logistic regression to examine the longitudinal associations between CMFI and BA with COPD. Fitted curves were used to analyze the dose-response relationship of CMFI and BA with COPD. A 3D surface diagram was used to analyze the association between BA and CMFI with COPD. In addition, subgroup and sensitivity analyses were performed. 6452 non-COPD patients were enrolled in the study, and after follow-up, 616 participants were diagnosed with COPD. Logistic regression and fitted curves showed a positive correlation between CMFI and BA and the development of COPD. The risk of COPD increased by 19% for every one standard deviation (SD) increase in BA and 32% for every one SD increase in CMFI. A 3D surface diagram shows a joint association between CMFI and BA with the COPD. Subgroup and sensitivity analysis results are stable. This study found a joint association between CMFI and BA with COPD, suggesting that CMFI and BA are risk factors for the development of COPD.

XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples

It is estimated that approximately 15% of cancers worldwide can be linked to viral infections. The viruses that can cause or increase the risk of cancer include human papillomavirus, hepatitis B and C viruses, Epstein-Barr virus, and human immunodeficiency virus, to name a few. The computational analysis of the massive amounts of tumor DNA data, whose collection is enabled by the advancements in sequencing technologies, has allowed studies of the potential association between cancers and viral pathogens. However, the high diversity of oncoviral families makes reliable detection of viral DNA difficult, and the training of machine learning models that enable such analysis computationally challenging. We introduce XVir, a data pipeline that deploys a transformer-based deep learning architecture to reliably identify viral DNA present in human tumors. XVir is trained on a mix of sequencing reads coming from viral and human genomes, resulting in a model capable of robust detection of potentially mutated viral DNA across a range of experimental settings. Results on semi-experimental data demonstrate that XVir is able to achieve high classification accuracy, generally outperforming state-of-the-art competing methods. In particular, it retains high accuracy even when faced with diverse viral populations while being significantly faster to train than other large deep learning-based classifiers.

Whole genome sequencing improves tissue-of-origin diagnosis and treatment options for cancer of unknown primary

Genomics can inform both tissue-of-origin (TOO) and precision treatments for patients with cancer of unknown primary (CUP). Here, we use whole genome and transcriptome sequencing (WGTS) for 72 patients and show diagnostic superiority of WGTS over panel testing (386-523 genes) in 71 paired cases. WGTS detects all reportable DNA features found by panel as well as additional mutations of diagnostic or therapeutic relevance in 76% of cases. Curated WGTS features and a CUP prediction algorithm (CUPPA) trained on WGTS data of known cancer types informs TOO in 71% of cases otherwise undiagnosed by clinicopathology review. WGTS informs treatments for 79% of patients, compared to 59% by panel testing. Finally, WGS of cell-free DNA (cfDNA) from patients with a high cfDNA tumour fraction (>7%), enables high-likelihood CUPPA predictions in 41% of cases. WGTS is therefore superior to panel testing, broadens treatment options, and is feasible using routine pathology samples and cfDNA.

Storage Time and DNA Quality Determine BRCA1/2 Sequencing Success in Prostate Cancer: A Multicentre Analysis with Therapeutic Implications

BACKGROUND

Approximately 25.0% of metastatic prostate cancer patients harbour DNA damage repair mutations, including BRCA1 and BRCA2, which are actionable targets for poly(ADP-ribose) polymerase (PARP) inhibitors. Accurate detection of BRCA1/2 mutations is critical for guiding targeted therapies, but crucial pre-analytical factors, such as tissue storage duration and DNA fragmentation, drastically affect the reliability of next-generation sequencing (NGS) using real-world diagnostic specimens.

METHODS

This multicentre study analysed 954 formalin-fixed paraffin-embedded tissue samples from 11 centres, including 559 biopsies and 395 surgical specimens. This study examined the impact of storage duration (<1 year, 1-2 years, and >2 years) and DNA parameters (concentration and fragmentation index) on NGS success rates. Logistic regression and Cox regression analyses were used to assess correlations between these factors and sequencing outcomes.

RESULTS

NGS success rates decreased significantly with longer storage, from 87.8% (<1 year) to 69.1% (>2 years). Samples with higher DNA concentrations and fragmentation indexes had higher success rates (p < 0.001). Surgical specimens had superior success rates (83.3%) compared with biopsies (72.8%) due to better DNA quality. The DNA degradation rate was more pronounced in older samples, underscoring the negative impact of extended storage.

CONCLUSIONS

Timely testing of BRCA1/2 mutations is critical for optimizing the identification of prostate cancer patients eligible for PARP inhibitors. Surgical specimens provide more reliable results than biopsies and minimizing the storage duration significantly enhances testing outcomes. Standardizing pre-analytical and laboratory procedures across centres is essential to ensure personalized treatments and improve patient outcomes.

Evaluating topography of mutational signatures with SigProfilerTopography

The mutations found in a cancer genome are shaped by diverse processes, each displaying a characteristic mutational signature that may be influenced by the genome's architecture. While prior analyses have evaluated the effect of topographical genomic features on mutational signatures, there has been no computational tool that can comprehensively examine this interplay. Here, we present SigProfilerTopography, a Python package that allows evaluating the effect of chromatin organization, histone modifications, transcription factor binding, DNA replication, and DNA transcription on the activities of different mutational processes. SigProfilerTopography elucidates the unique topographical characteristics of mutational signatures, unveiling their underlying biological and molecular mechanisms.

Germline testing for prostate cancer: current state and opportunities for enhanced access

Germline Testing (GT) for prostate cancer (PCA) is now central to PCA care and hereditary cancer assessment, with a rising role in PCA screening approaches. Guidelines have significantly expanded to include testing patients with metastatic PCA, advanced PCA or with high-risk features, and for males with or without PCA with a strong family cancer history to identify hereditary cancer syndromes for patients and their families. However, the expansion of GT has overwhelmed genetic counselling programs, necessitating the development and evaluation of alternate genetic delivery models. Furthermore, disparities in engagement in PCA GT are of major concern for impacting PCA-related and overall cancer-related outcomes for patients and their families. This review focuses on integrating PCA GT guidelines with implementation strategies and addressing PCA GT disparities to help inform current and future strategies to enhance the benefits of GT across populations.

RobusTAD: reference panel based annotation of nested topologically associating domains

Topologically associating domains (TADs) are fundamental units of 3D genomes and play essential roles in gene regulation. Hi-C data suggests a hierarchical organization of TADs. Accurately annotating nested TADs from Hi-C data remains challenging, both in terms of the precise identification of boundaries and the correct inference of hierarchies. While domain boundary is relatively well conserved across cells, few approaches have taken advantage of this fact. Here, we present RobusTAD to annotate TAD hierarchies. It incorporates additional Hi-C data to refine boundaries annotated from the study sample. RobusTAD outperforms existing tools at boundary and domain annotation across several benchmarking tasks.

Links between short-chain fatty acids and osteoarthritis from pathology to clinic via gut-joint axis

Short-chain fatty acids (SCFAs), the primary metabolites produced by the microbial fermentation of dietary fibers in the gut, have a key role in protecting gut health. Increasing evidence indicates SCFAs can exert effects on distant tissues and organs beyond the gut via blood circulation. Osteoarthritis (OA) is a chronic inflammatory joint disease that severely diminishes the physical function and quality of life. However, effective clinical treatments for OA remain elusive. Recent studies have shown that SCFAs can exert beneficial effects on damaged joints in OA. SCFAs can mitigate OA progression by preserving intestinal barrier function and maintaining the integrity of cartilage and subchondral bone, suggesting that they have substantial potential to be the adjunctive treatment strategy for OA. This review described the SCFAs in the human body and their cellular signaling mechanism, and summarized the multiple effects of SCFAs (especially butyrate, propionate, and acetate) on the prevention and treatment of OA by regulating the gut-joint axis, providing novel insights into their promising clinical applications.

Immune checkpoint inhibitor (ICI) therapy in central nervous system cancers: State-of-the-art and future outlook

Invasive central nervous system (CNS) cancers are an area where the development of breakthrough therapies is urgently needed. For instance, conditions such as glioblastoma multiforme (GBM) are associated with poor clinical prognosis, with the majority of trials offering no improvement to marginally enhanced survival. Unleashing the potential of targeting the immune system in CNS cancers has gained attention in recent years. Inhibition of immune checkpoints such as CTLA-4, PD-1/PD-L1, TIM-3, and LAG-3 has been attempted in recent trials. While potentially offering a notable edge over other immunotherapies, multi-organ adverse events have been found with the administration of immune checkpoint inhibitors (ICIs). The present review captures the state-of-the-art evidence on ICI treatments in different CNS cancers. Also, we discuss the value of combinational therapies involving ICIs as well as next-generation therapeutics such as bispecific antibodies targeting PD-1/LAG-3/TIM-3 and CRISPR-Cas9-edited PD-1-knock-out checkpoint-resistant CAR T-cells.

Associations between plant-based diets and cardiovascular disease, frailty, and cognitive dysfunction in middle and old age: a systematic review and meta-analysis of cohort studies

Background: Evidence suggests that plant-based diets are associated with multiple health outcomes. However, in previous pooled studies, the lack of a standardized definition of plant-based diet has led to conflicting evidence regarding its relationship with health outcomes in middle-aged and elderly people. Methods and findings: Searches were conducted on PubMed, Embase, Cochrane Library and Web of Science databases from inception until July 10, 2024. We included studies that examined the association between (1) the standardized healthy plant-based diet index (hPDI) and unhealthy plant-based diet index (uPDI) and (2) cardiovascular disease (CVD), cardiovascular mortality (CVD mortality), frailty, and cognitive dysfunction. Dose-response analysis was performed to assess the relationships between (1) hPDI and uPDI and (2) CVD and frailty. Statistical analyses were performed using an inverse variance random-effects model, and results are reported as risk ratio (RR) with 95% confidence interval (CI) by combining the most adjusted RR, odds ratio (OR) and hazard ratio (HR) under the rare outcome assumption. A total of 25 cohort studies were included. Higher hPDI scores were associated with lower risks of CVD (RR = 0.81, 95% CI 0.71-0.93), CVD mortality (RR = 0.83, 95% CI 0.75-0.90), coronary heart disease (CHD) (RR = 0.79, 95% CI 0.70-0.88), stroke (RR = 0.91, 95% CI 0.86-0.96), ischemic stroke (RR = 0.86, 95% CI 0.79-0.94), cognitive dysfunction (RR = 0.75, 95% CI 0.66-0.84) and frailty (RR = 0.72, 95% CI 0.60-0.86). By contrast, higher uPDI scores were associated with increased risks of CVD (RR = 1.16, 95% CI 1.09-1.24), CVD mortality (RR = 1.14, 95% CI 1.05-1.23), frailty (RR = 1.52, 95% CI 1.10-2.08) and cognitive dysfunction (RR = 1.24, 95% CI 1.11-1.38). Dose-response analyses showed that increasing adherence to hPDI was associated with reduced risks of CVD and frailty, whereas increasing intake of hPDI was linked to increased risk of CVD and frailty. Conclusions: Our study suggests that adherence to hPDI is associated with favourable health outcomes in middle-aged and elderly people, except for hemorrhagic stroke. These findings highlight the potential benefits of hPDI for promoting healthy ageing.

Consumption of fruit juice and risk of type 2 diabetes mellitus: A systematic review and meta-analysis of prospective cohort studies: Fruit Juice and Risk of Type 2 Diabetes

BACKGROUND

Previous observational studies on the association between the consumption of fruit juice and the risk of type 2 diabetes mellitus have reported inconsistent findings. We investigated the association using a meta-analysis of prospective cohort studies.

METHODS

Studies were identified through PubMed and EMBASE searches from inception to August 3, 2024. We calculated pooled relative risks (RRs) and 95% confidence intervals (CIs). The consumption of fruit juice was categorized into 100% fruit juice and non-100% fruit juice. The primary outcome was the incidence of type 2 diabetes mellitus.

RESULTS

Out of 1591 articles, 14 prospective cohort studies were included in the final analysis. In the meta-analysis of all studies, there was no significant association between the consumption of overall fruit juice and the risk of type 2 diabetes mellitus (RR, 1.06 [95% CI, 0.98-1.15], P = 0.170). In the subgroup meta-analysis by juice type, non-100% fruit juice was statistically significantly associated with an increased risk of type 2 diabetes mellitus (RR, 1.15 [95% CI, 1.03-1.28], P = 0.012), while there was no significant association between the consumption of 100% fruit juice and the risk of type 2 diabetes mellitus. An increased risk of type 2 diabetes mellitus by fruit juice was observed only in Asian populations (RR, 1.17 [95% CI 1.02-1.34], P = 0.023).

CONCLUSION

The consumption of non-100% fruit juice increased the risk of type 2 diabetes mellitus. Unlike whole fruit consumption, 100% fruit juice had no beneficial effect on the risk of type 2 diabetes mellitus.

New insights into tumor microenvironment and HPV integrations in cervical cancer pathogenesis revealed by single-cell transcriptome data

HPV infection is common among women and can result in serious illnesses. This research utilizes single-cell RNA-sequencing (scRNA-seq) to study the connection between cellular heterogeneity and HPV integrations in cervical histopathology. scRNA-seq was used to examine heterogeneity among normal patients and those in three disease stages: high-grade squamous intraepithelial lesions (HSIL), microinvasive carcinoma (MIC), and cervical squamous epithelium carcinoma cancer (CSCC) tissues. A method was developed to identify HPV integration events from scRNA-seq data. Our results indicated an increase in squamous epithelial cells and a decrease in columnar epithelial cells as the disease progressed from normal to CSCC. We discovered HPV genes that were differentially expressed across normal patients and those in the three disease stages. Notably, HPV integration events were more common in squamous epithelial cells at the single-cell level. The ratio of HPV-integrated cells increased as the disease progressed from normal tissue to CSCC, eventually stabilizing. Several genes, such as EGR1, S100A11, S100A8, KRT5, RPL34, ATP1B1, RPS4X and EEF2, were frequently integrated by HPV across patients. In contrast, genes like PAN3, BABAM2, SPEN, TCIM-SIRLNT, TEX41-PABPC1P2 and KCNV1-LINC01608 showed frequent integration events across cells. KRT5, ATP1B1, RPS4X, PAN3 and SPEN were novel recurrent HPV-integrated genes we observed at the patient or cell level in this study. Additionally, we found that HPV genes from various HPV types exhibited integration preferences in various samples and disease stages. This provides a valuable insight into the mechanism of HPV-induced cervical cancer from a single-cell standpoint, highlighting its clinical relevance.

Advances in understanding LINE-1 regulation and function in the human genome

LINE-1 (long interspersed nuclear element 1, L1) retrotransposons constitute ~17% of human DNA (~0.5 million genomic L1 copies) and exhibit context-dependent expression in different cell lines. Recent studies reveal that L1 is under multilayered control by diverse factors that either collaborate or compete with each other to ensure precise L1 activity. Remarkably, L1s have been co-opted as various transcription-dependent regulatory elements, such as promoters, enhancers, and topologically associating domain (TAD) boundaries, that regulate gene expression in zygotic genome activation, aging, cancer, and other disorders. This review highlights the regulation of L1 and its regulatory functions that influence disease and development.

Immune Checkpoint Inhibitors and Immunosuppressive Tumor Microenvironment: Current Challenges and Strategies to Overcome Resistance

Immune checkpoint inhibitors (ICIs) are shown to improve cancer treatment effectiveness by boosting the immune system of the patient. Nevertheless, the unique and highly suppressive TME poses a significant challenge, causing heterogeneity of response or resistance in a considerable number of patients. This review focuses on the evasive attributes of the TME. Immune evasion mechanism in TME include immunosuppressive cells, cytokine and chemokine signaling, metabolic alterations and overexpression of immune checkpoint molecules such as PD-1, CTLA-4, LAG-3, TIM-3, TIGIT, BTLA and their interactions within the TME. In addition, this review focuses on the overcoming resistance by targeting immunosuppressive cells, normalizing tumor blood vessels, blocking two or three checkpoints simultaneously, combining vaccines, oncolytic viruses and metabolic inhibitors with ICIs or other therapies. This review also focuses on the necessity of finding predictive markers for the stratification of patients and to check response of ICIs treatment. It remains to be made certain by new research and intelligent innovations how these discoveries of the TME and its interplay facilitate ICI treatment and change the face of cancer treatment.

Deciphering human endogenous retrovirus expression in colorectal cancers: exploratory analysis regarding prognostic value in liver metastases

BACKGROUND

Human Endogenous RetroVirus (HERV) expression in tumours reflects epigenetic dysregulation of cancer and an oncogenic factor through promoter/enhancer action on genes. While more than 50% of colorectal cancers develop liver metastases, HERV has not been studied in this context.

METHODS

We collected 400 RNA-seq samples from over 200 patients with primary and liver metastases, including public data and a novel set of 200 samples.

FINDINGS

We observed global stability of HERV expression between liver metastases and primary colorectal cancers, suggesting an early oncogenic footprint. We identified a list of 17 HERV loci for liver metastatic colorectal cancer (lmCRC) characterization; with tumour-specificity validated in single-cell metastatic colorectal cancer data and normal tissue bulk RNA-seq. Eleven loci produced HERV-derived peptides as per tandem mass spectrometry from primary colorectal cancer. Six loci were associated with the risk of relapse after lmCRC surgery. Four, HERVH_Xp22.32a, HERVH_20p11.23b, HERVH_13q33.3, HERVH_13q31.3, had adverse prognostic value (log-rank p-value 0.028, 0.0083, 9e-4, 0.05, respectively) while two, HERVH_Xp22.2c (log-rank p-value 0.032) and HERVH_8q21.3b (in multivariable models) were associated with better prognosis. Moreover, the markers showed a cumulative effect on survival when expressed. Some were associated with decreased cytotoxic immune cells and most of them correlated with cell cycle pathways.

INTERPRETATION

These findings provide insights into the lmCRC transcriptome landscape by suggesting prognostic markers and potential therapeutic targets.

FUNDING

This work was supported by funding from institutional grants from Inserm, EFS, University of Bourgogne Franche-Comté, national found "Agence Nationale de la Recherche - ANR-JCJC: Projet HERIC and ANR-22-CE45-0007", and "La ligue contre le cancer".

SEER-based evaluation of lymph node yield as a prognostic indicator of cancer-specific survival in nonmetastatic pancreatic ductal adenocarcinoma

BACKGROUND/OBJECTIVES

Although the American Joint Committee on Cancer (AJCC) 8th edition recommends harvesting at least 12 lymph nodes for optimal staging in pancreatic ductal adenocarcinoma (PDAC), the precise lymph node yield (LNY) needed for accurate prognostication in different treatment settings remains unclear. This study aimed to identify subgroup-specific LNY cutoffs and evaluate their prognostic significance in nonmetastatic PDAC.

METHODS

We analyzed 5609 patients with nonmetastatic PDAC from the Surveillance, Epidemiology, and End Results (SEER) database undergoing pancreatectomy. Patients were categorized by nodal status (N0 vs. N+) and receipt of neoadjuvant therapy (NAT) or upfront surgery (UPS). We used maximum selected rank statistics and a conditional inference tree approach to determine optimal LNY cutoffs for each subgroup. Kaplan-Meier curves and Cox proportional hazards models were employed to assess cancer-specific survival (CSS) and identify independent prognostic factors.

RESULTS

Distinct LNY thresholds were identified for N0 (>13) and N+ (>10) cohorts, with the highest cutoffs in N0-NAT subgroups (>27). Across all analyses, patients exceeding these LNY cutoffs demonstrated significantly prolonged CSS. The N0-NAT group with LNY >27 achieved the longest median survival (60 months), whereas N+ patients undergoing UPS with LNY ≤10 had the poorest outcomes (16 months). Multivariate Cox regressions consistently showed that higher LNY was an independent predictor of improved survival.

CONCLUSIONS

Higher LNY thresholds than the current AJCC standard of 12 appear beneficial for more accurate staging and improved survival in resected PDAC. Tailoring LNY goals based on nodal status and treatment modality may further refine prognostic stratification and guide more effective therapeutic strategies.

Loss of function of Atrx recapitulates phenotypes of alternative lengthening of telomeres in a primary mouse model of sarcoma

The development of a telomere maintenance mechanism is essential for immortalization in human cancer. While most cancers elongate their telomeres by expression of telomerase, 10-15% of human cancers utilize a pathway known as alternative lengthening of telomeres (ALT). ALT is commonly associated with loss-of-function mutations in ATRX. Here, we developed a genetically engineered primary mouse model of sarcoma in CAST/EiJ mice to investigate the extent to which telomerase deficiency and Atrx-inactivation lead to ALT induction. We observed increases in multiple ALT-associated phenotypic indicators in tumors with loss of function mutations of Atrx. Furthermore, we found that loss of Atrx leads to an increase in telomeric instability and telomere sister chromatid exchange. However, Atrx-deficient tumors did not show productive telomere length maintenance in the absence of telomerase. This primary mouse model of sarcoma could facilitate future investigations into the molecular features of ALT in vivo.

Artificial intelligence as a predictive tool for gastric cancer: Bridging innovation, clinical translation, and ethical considerations

With gastric cancer ranking among the most prevalent and deadly malignancies worldwide, early detection and individualized prognosis remain essential for improving patient outcomes. This letter discusses recent advancements in artificial intelligence (AI)-driven predictive tools for gastric cancer, emphasizing a computed tomography-based radiomic model that achieved a predictive accuracy of area under the curve of 0.893 for treatment response in advanced cases undergoing neoadjuvant immunochemotherapy. AI offers promising avenues for predictive accuracy and personalized treatment planning in gastric oncology. Additionally, this letter highlights the comparison of these AI tools with traditional methodologies, demonstrating their potential to streamline clinical workflows and address existing gaps in risk stratification and early detection. Furthermore, this letter addresses the ethical considerations and the need for robust clinical-AI collaboration to achieve reliable, transparent, and unbiased outcomes. Strengthening cross-disciplinary efforts will be vital for the responsible and effective deployment of AI in this critical area of oncology.

Macromolecular interactions dictate Polycomb-mediated epigenetic repression

The dynamic regulation of epigenetic states relies on complex macromolecular interactions. PRC2, the methyltransferase complex responsible for depositing H3K27me3, interacts with distinct accessory proteins to form the mutually exclusive subcomplexes PHF1-PRC2.1, MTF2-PRC2.1, PHF19-PRC2.1, and PRC2.2. The functions of these subcomplexes are unclear and thought to be highly redundant. Here we show that PRC2 subcomplexes have distinct roles in epigenetic repression of lineage-specific genes and stem cell differentiation. Using a human pluripotent stem cell model, we engineered a comprehensive set of separation-of-function mutants to dissect the roles of individual protein-protein and DNA-protein interactions. Our results show that PRC2.1 and PRC2.2 deposit H3K27me3 locus-specifically, resulting in opposing outcomes in cardiomyocyte differentiation. We find that MTF2 stimulates PRC2.1-mediated repression in stem cells and cardiac differentiation through its interaction with DNA and H3K36me3, while PHF19 antagonizes it. Furthermore, MTF2-PRC2.1 maintains normal cardiomyocyte function. Together, these results reveal the importance and specificity of individual macromolecular interactions in Polycomb-mediated epigenetic repression in human stem cells and differentiation.

Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification

Classifying cancer genetic variants based on clinical actionability is crucial yet challenging in precision oncology. Large language models (LLMs) offer potential solutions, but their performance remains underexplored. This study evaluates GPT-4o, Llama 3.1, and Qwen 2.5 in classifying genetic variants from the OncoKB and CIViC databases, as well as a real-world dataset derived from FoundationOne CDx reports. GPT-4o achieved the highest accuracy (0.7318) in distinguishing clinically relevant variants from variants of unknown clinical significance (VUS), outperforming Qwen 2.5 (0.5731) and Llama 3.1 (0.4976). LLMs demonstrated better concordance with expert annotations for variants with strong clinical evidence but exhibited greater inconsistencies for those with weaker evidence. All three models showed a tendency to assign variants to higher evidence levels, suggesting a propensity for overclassification. Prompt engineering significantly improved accuracy, while retrieval-augmented generation (RAG) further enhanced performance. Stability analysis across 100 iterations revealed greater consistency with the CIViC system than with OncoKB. These findings highlight the promise of LLMs in cancer genetic variant classification while underscoring the need for further optimization to improve accuracy, consistency, and clinical applicability.

A multi-tissue and -breed catalogue of chromatin conformations and their implications in gene regulation in pigs

BACKGROUND

Topologically associating domains (TADs) are functional units that organize chromosomes into 3D structures of interacting chromatin, and play a crucial role in regulating gene expression by constraining enhancer-promoter contacts. Evidence suggests that deletion of TAD boundaries can lead to aberrant expression of neighboring genes. In our study, we analyzed high-throughput chromatin conformation capture (Hi-C) datasets from publicly available sources, integrating 71 datasets across five tissues in six pig breeds.

RESULTS

Our comprehensive analysis revealed 65,843 TADs in pigs, and we found that TAD boundaries are enriched for expression Quantitative Trait Loci (eQTL), splicing Quantitative Trait Loci (sQTL), Loss-of-Function variants (LoFs), and other regulatory variants. Genes within conserved TADs are associated with fundamental biological functions, while those in dynamic TADs may have tissue-specific roles. Specifically, we observed differential expression of the NCOA2 gene within dynamic TADs. This gene is highly expressed in adipose tissue, where it plays a crucial role in regulating lipid metabolism and maintaining energy homeostasis. Additionally, differential expression of the BMPER gene within dynamic TADs is associated with its role in modulating the activities of bone morphogenetic proteins (BMPs)-critical growth factors involved in bone and cartilage development.

CONCLUSION

Our investigations have shed light on the pivotal roles of TADs in governing gene expression and even influencing traits. Our study has unveiled a holistic interplay between chromatin interactions and gene regulation across various tissues and pig breeds. Furthermore, we anticipate that incorporating markers, such as structural variants (SVs), and phenotypes will enhance our understanding of their intricate interactions.

Mucinous cystic neoplasms and simple mucinous cysts are two distinct precursors of pancreatic cancer: clinicopathological, genomic, and transcriptomic characterization

Mucinous cystic neoplasms (MCNs) of the pancreas are macroscopic precursors of pancreatic cancer. A similar cystic lesion but lacking the ovarian-type subepithelial stroma has been recently defined as a simple mucinous cyst (SMC); however, its nature remains unclear. This study aims to define the clinicopathological and molecular profiles of a cohort of MCNs and SMCs of the pancreas and their associated invasive carcinoma. Overall, 23 cases were identified, comprising 19 MCNs and 4 SMCs with co-occurring invasive carcinoma. A multiregional (two samples from each cystic lesion and one from the adenocarcinoma) DNA and RNA sequencing approach was used. The key findings can be summarized as follows: (1) Molecular association: In 22/23 cases (95.7%), the concomitant mucinous cyst and invasive carcinoma shared specific genomic alterations, establishing for the first time that SMC is a true precursor of pancreatic cancer. (2) Clinical behavior: carcinomas arising from SMC appeared to be more aggressive than those arising from MCN. (3) Mutational profile: both cyst types showed significant similarities to conventional pancreatic ductal adenocarcinoma (PDAC), with KRAS and TP53 the most commonly altered genes. (4) Intracystic heterogeneity: while most molecular alterations were present in both analyzed cystic areas, RNF43 showed the highest heterogeneity. (5) CDKN2A: its alterations were predominantly restricted to the invasive component, suggesting a role in driving the invasion in a subset of cases. CNKN2A may also serve as a potential biomarker for identifying high-risk cysts. (6) RNAseq: most cases showed a switch from the classical to the basal transcriptome subtype during the progression from cystic neoplasms to invasive cancers. These findings establish SMCs as new precursors of pancreatic cancer and provide critical insights into the tumorigenesis of MCNs, with potential immediate implications for tumor taxonomy and clinical management. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Genomic instability, DNA damage response and telomere homeostasis in pancreatic cancer

Pancreatic cancer (PC) is becoming one of the most serious health problems at present, but its causes and risk factors are still unclear. One of the drivers in pancreatic carcinogenesis is altered genomic (DNA) integrity with subsequent genomic instability in cancer cells. The latter comprises a) DNA damage response and DNA repair mechanisms, b) DNA replication and mitosis, c) epigenetic regulation, and d) telomere maintenance. In our review we addressed the above aspects in relation to the most abundant and severe form of PC, pancreatic ductal adenocarcinoma (PDAC). In summary, the interactions between the DNA damage response, telomere homeostasis and mitotic regulation are not comprehensively understood at present, including the epigenetic factors entering the trait of genomic stability maintenance. In addition, the complexity of telomere homeostasis in relation to PDAC risk, prognosis and prediction also warrants further investigations.

FADD Functions as an Oncogene in Chr11q13.3-Amplified Head and Neck Squamous Cell Carcinoma

Chromosomal 11q13.3 amplification is the most common gene copy-number variation event in head and neck squamous cell carcinoma (HNSCC) that corresponds with poor prognosis. Although cyclin D1, a G1/S phase cell-cycle regulatory protein at this locus, is considered as a key driver of malignant progression, further exploration is needed to develop more effective targets for cases with this amplification. Using CRISPR-based gene knockout screening of genes located in chr11q13.3, we found that loss of the gene encoding the Fas-associated death domain (FADD) protein, a well-recognized adapter to caspase-8 that induces cell apoptosis, significantly reduced cancer cell proliferation. FADD expression was elevated in chr11q13.3-amplified tumors and correlated with poor prognosis. RNA sequencing, mass spectrometry, and proteomics analyses revealed a direct relationship between FADD and the DNA helicase MCM5 in the S phase. FADD and cyclin D1 acted at different stages of the cell cycle to synergistically induce proliferation, and caspase-8 deficiency was required for the oncogenic activity of FADD. In a patient-derived xenograft model with chr11q13.3 amplification, combined administration of the DNA helicase complex inhibitor and CDK4/6 inhibitor effectively curtailed tumor growth. Overall, this study identified a nonclassic oncogenic role for FADD in mediating tumor progression in HNSCC and provided a feasible treatment option for patients with chr11q13.3 amplification. Significance: FADD promotes progression of tumors with chr11q13.3 amplification by binding to the DNA helicase complex, which can be targeted in combination with cyclin D1 as a viable therapeutic strategy for HNSCC patients.

Characteristics of sarcopenia in patients with rheumatoid arthritis at a central university hospital in Hanoi, Vietnam: a cross-sectional study

AIM

To determine the prevalence and factors associated with sarcopenia in rheumatoid arthritis (RA) patients at a central university hospital in Hanoi, Vietnam.

METHODS

Patients with RA aged ≥ 18 were enrolled in this cross-sectional study. Dual-energy X-ray absorptiometry was performed to measure appendicular skeletal muscle (ASM). Assessment of muscle function included hand grip strength (HGS) and gait speed (GS). Sarcopenia was defined according to Asian Working Group for Sarcopenia (AWGS) criteria 2019. RA disease activity was evaluated by disease activity score 28 CRP (DAS28-CRP). Medical history and previous medications including steroids, methotrexate, bDMARDs, clinical characteristics, and comorbidities were also documented. Multivariable adjusted regression was used to examine potential factors associated with sarcopenia in patients with RA.

RESULTS

A total of 156 patients with RA were recruited, out of which the prevalence of sarcopenia was 62.82%. Among the participants, 95.16% had a low appendicular lean mass index (ALMI), 91.67% had low hand grip strength, and 36.54% had slow gait speed. Active RA disease was significantly associated with a higher odd ratio of having sarcopenia, low muscle mass, and low hand grip strength. After adjusting for potential factors, male (aOR 6.66), RA disease activity level (aOR 3.07), and hypertension (aOR 4.06) were statistically independent factors associated with sarcopenia.

CONCLUSION

Effective RA management to achieve clinical remission is essential to mitigate sarcopenia risk. Further studies are essential to better understand sarcopenia and improve management in patients with RA. Key Points • Prevalence: Sarcopenia was present in 62.82% of patients with RA, especially in those with higher disease activity. • Risk Factors: Male gender, active disease, and hypertension were associated with sarcopenia. • Inflammation and disease activity: Active RA and elevated CRP levels were linked to reduced muscle mass and strength.

Dynamic clustering of genomics cohorts beyond race, ethnicity-and ancestry

BACKGROUND

Recent decades have witnessed a steady decrease in the use of race categories in genomic studies. While studies that still include race categories vary in goal and type, these categories already build on a history during which racial color lines have been enforced and adjusted in the service of social and political systems of power and disenfranchisement. For early modern classification systems, data collection was also considerably arbitrary and limited. Fixed, discrete classifications have limited the study of human genomic variation and disrupted widely spread genetic and phenotypic continuums across geographic scales. Relatedly, the use of broad and predefined classification schemes-e.g. continent-based-across traits can risk missing important trait-specific genomic signals.

METHODS

To address these issues, we introduce a dynamic approach to clustering human genomics cohorts based on genomic variation in trait-specific loci and without using a set of predefined categories. We tested the approach on whole-exome sequencing datasets in ten cancer types and partitioned them based on germline variants in cancer-relevant genes that could confer cancer type-specific disease predisposition.

RESULTS

Results demonstrate clustering patterns that transcend discrete continent-based categories across cancer types. Functional analysis based on cancer type-specific clusterings also captures the fundamental biological processes underlying cancer, differentiates between dynamic clusters on a functional level, and identifies novel potential drivers overlooked by a predefined continent-based clustering.

CONCLUSIONS

Through a trait-based lens, the dynamic clustering approach reveals genomic patterns that transcend predefined classification categories. We propose that coupled with diverse data collection, new clustering approaches have the potential to draw a more complete portrait of genomic variation and to address, in parallel, technical and social aspects of its study.

SMARCA4 Inhibits Breast Cancer Progression and Metastasis through RHOA Suppression

Triple-negative breast cancer (TNBC) is the most challenging subtype of the disease due to its aggressive nature and lack of targeted therapy options. To identify regulators of TNBC, we conducted a genome-wide CRISPR knockout screen in both three-dimensional (3D) tumor spheroid and two-dimensional cell culture models. The 3D spheroid model displayed unique potential in identifying putative tumor suppressors because of its closer mimicry of in vivo tumor growth conditions. Notably, the chromatin remodeling SWI/SNF complex emerged as a potent suppressor of tumor spheroid growth. Specifically, loss of the SWI/SNF ATPase subunit SMARCA4 promoted tumor spheroid growth with reduced compactness and enhanced primary tumor growth and metastasis across multiple TNBC models. SMARCA4 was required for the transcription of the Rho GTPase-activating factor ARHGAP29 by enhancing DNA accessibility through direct binding to its promoter. SMARCA4 loss resulted in reduced ARHGAP29 levels and hyperactive RHOA signaling, subsequently disrupting cell adhesion, facilitating the formation of a loose spheroid structure in vitro, and enhancing breast cancer growth and metastasis in vivo. These results establish SMARCA4 and SWI/SNF as tumor suppressors of TNBC through suppression of RHOA activity. Significance: CRISPR-knockout screen in 3D tumor spheroid revealed that SMARCA4, a SWI/SNF ATPase subunit, suppresses triple-negative breast cancer growth and metastasis by increasing ARHGAP29 transcription and inhibiting the RHOA signaling pathway.

Cardiac Amyloidosis in Older Adults With a Focus on Frailty: JACC: Advances Expert Consensus

Amyloidosis, which is caused by misfolded proteins that form amyloid fibrils, is predominantly diagnosed in older adults. Although previously considered a rare disease, increased awareness and noninvasive diagnostic methods have resulted in a rise in diagnoses. As a multisystem disease that affects multiple organ systems (cardiac, gastrointestinal, renal, and neurological), there is significant overlap with both geriatric conditions and common conditions in heart failure. Frailty is recognized as a distinct biological syndrome of declines across multiple physiological systems, which prevents maintenance of homeostasis and limits the ability to respond to stressors. Frailty was initially characterized as physical frailty alone; however, it is increasingly recognized that it is multidimensional with components including nutrition, cognitive, psychological, and social. Frailty in cardiovascular disease has become an important risk factor, indicator for disease severity, and can help guide decisions around intervention. In certain patients, frailty may be reversible. Given the lack of consensus definitions, tools, and implementation of frailty in both clinical and research settings in the field of amyloidosis, we convened a group of experts from cardiology, geriatric cardiology, geriatrics, hematology, and allied health to form this state-of-the-art review. There are many points of intersectionality between amyloidosis, aging, and frailty which herald a need for multidisciplinary care. This review document aims to provide guidance in how to understand and address frailty in older patients with a specific focus on cardiac amyloidosis.

Predictive factors for efficacy of oxaliplatin-based chemotherapy in advanced well-differentiated neuroendocrine tumors: an observational cohort study and meta-analysis

Background

Oxaliplatin-based chemotherapy (OX-CT) has shown promising antitumor activity in advanced well-differentiated neuroendocrine tumors (WD-NETs). However, no meta-analysis has been conducted to explore the factors associated with ORR and PFS of OX-CT, and data are still limited in Chinese cohort.

Methods

We performed a retrospective cohort study with advanced WD-NETs who received OX-CT. We also conducted a systematic review and performed a meta-analysis to explore factors associated with ORR and PFS.

Results

A total of 27 patients were included, with 21 receiving OX-CT as first line. Furthermore, 18 were of pancreas origin, and the median Ki-67 was 30%. The ORR and DCR were 29.6% and 81.5%, respectively. The median PFS was 9.3 months (95%CI: 4.6-14.0), and OS was not reached. A Ki-67 value >10% predicted higher ORR (36.4% vs. 0.0%, p = 0.28) and better PFS (10.0 vs. 2.1 months, p = 0.06). Patients with hepatic tumor burden ≤25% had a similar ORR (33.3% vs. 22.2%, p = 0.68), but with a trend of longer PFS (10.2 vs. 4.7 months, p = 0.21) than those >25%. Both ORR and PFS were independent of MGMT status. A total of 962 patients were included in the systemic review. The pooled ORR (28.2%, p = 0.84) and DCR (82.9%, p = 0.85) were comparable with this cohort. No difference was observed between GEMOX and FOLFOX/CAPOX in both ORR (23.9% vs. 29.6%, p = 0.19) and PFS (10.5 vs. 11.8 months, p = 0.69). Enhanced ORR was seen in pNETs than epNETs (36.8% vs. 16.7%, p < 0.001) and also in G3 NETs than G1-2 NETs (45.5% vs. 24.7%, p < 0.001). The pooled median PFS and OS were 10.8 months (95%CI: 8.8-12.8) and 30.4 months (95%CI: 24.8-35.9).

Conclusions

Oxaliplatin-based chemotherapy could be a good option for advanced WD-NETs with high Ki-67 index and pancreatic origin.

Tumor break load quantitates structural variant-associated genomic instability with biological and clinical relevance across cancers

While structural variants (SVs) are a clear sign of genomic instability, they have not been systematically quantified per patient since declining costs have only recently enabled large-scale profiling. Therefore, the biological and clinical impact of high numbers of SVs in patients is unknown. We introduce tumor break load (TBL), defined as the sum of unbalanced SVs, as a measure for SV-associated genomic instability. Using pan-cancer data from TCGA, PCAWG, and CCLE, we show that a high TBL is associated with significant changes in gene expression in 26/31 cancer types that consistently involve upregulation of DNA damage repair and downregulation of immune response pathways. Patients with a high TBL show a higher risk of recurrence and shorter median survival times for 5/15 cancer types. Our data demonstrate that TBL is a biologically and clinically relevant feature of genomic instability that may aid patient prognostication and treatment stratification. For the datasets analyzed in this study, TBL has been made available in cBioPortal.