Explore the vast range of titles available.

Brain metastases are the most common tumor of the brain with a dismal prognosis. A fraction of patients with brain metastasis benefit from treatment with immune checkpoint inhibitors (ICI) and the degree and phenotype of the immune cell infiltration has been used to predict response to ICI. However, the anatomical location of brain lesions limits access to tumor material to characterize the immune phenotype. Here, we characterize immune cells present in brain lesions and matched cerebrospinal fluid (CSF) using single-cell RNA sequencing combined with T cell receptor genotyping. Tumor immune infiltration and specifically CD8 + T cell infiltration can be discerned through the analysis of the CSF. Consistently, identical T cell receptor clonotypes are detected in brain lesions and CSF, confirming cell exchange between these compartments. The analysis of immune cells of the CSF can provide a non-invasive alternative to predict the response to ICI, as well as identify the T cell receptor clonotypes present in brain metastasis. The use of CSF for diagnosis of metastatic brain tumors could be of clinical and patient benefit. Here the authors undertake a single-cell RNA analysis of CSF and brain to determine whether the phenotype in the CSF is reflective of the phenotype in the tumor.

Colorectal cancers comprise a complex mixture of malignant cells, nontransformed cells, and microorganisms. Fusobacterium nucleatum is among the most prevalent bacterial species in colorectal cancer tissues. Here we show that colonization of human colorectal cancers with Fusobacterium and its associated microbiome—including Bacteroides, Selenomonas, and Prevotella species—is maintained in distal metastases, demonstrating microbiome stability between paired primary and metastatic tumors. In situ hybridization analysis revealed that Fusobacterium is predominantly associated with cancer cells in the metastatic lesions. Mouse xenografts of human primary colorectal adenocarcinomas were found to retain viable Fusobacterium and its associated microbiome through successive passages. Treatment of mice bearing a colon cancer xenograft with the antibiotic metronidazole reduced Fusobacterium load, cancer cell proliferation, and overall tumor growth. These observations argue for further investigation of antimicrobial interventions as a potential treatment for patients with Fusobacterium-associated colorectal cancer.

BackgroundThe efficacy of immune checkpoint inhibitors (ICIs) depends on the tumor immune microenvironment (TIME), with a preference for a T cell-inflamed TIME. However, challenges in tissue-based assessments via biopsies have triggered the exploration of non-invasive alternatives, such as radiomics, to comprehensively evaluate TIME across diverse cancers. To address these challenges, we develop an ICI response signature by integrating radiomics with T cell-inflamed gene-expression profiles.MethodsWe conducted a pan-cancer investigation into the utility of radiomics for TIME assessment, including 1360 tumors from 428 patients. Leveraging contrast-enhanced CT images, we characterized TIME through RNA gene expression analysis, using the T cell-inflamed gene expression signature. Subsequently, a pan-cancer CT-radiomic signature predicting inflamed TIME (CT-TIME) was developed and externally validated. Machine learning was employed to select robust radiomic features and predict inflamed TIME. The study also integrated independent cohorts with longitudinal CT images, baseline biopsies, and comprehensive immunohistochemistry panel evaluation to assess the pan-cancer biological associations, spatiotemporal landscape and clinical utility of the CT-TIME.ResultsThe CT-TIME signature, comprising four radiomic features linked to a T-cell inflamed microenvironment, demonstrated robust performance with AUCs (95% CI) of 0.85 (0.73 to 0.96) (training) and 0.78 (0.65 to 0.92) (external validation). CT-TIME scores exhibited positive correlations with CD3, CD8, and CD163 expression. Intrapatient analysis revealed considerable heterogeneity in TIME between tumors, which could not be assessed using biopsies. Evaluation of aggregated per-patient CT-TIME scores highlighted its promising clinical utility for dynamically assessing the immune microenvironment and predicting immunotherapy response across diverse scenarios in advanced cancer. Despite demonstrating progression disease at the first follow-up, patients within the inflamed status group, identified by CT-TIME, exhibited significantly prolonged progression-free survival (PFS), with some surpassing 5 months, suggesting a potential phenomenon of pseudoprogression. Cox models using aggregated CT-TIME scores from baseline images revealed a statistically significant reduction in the risk of PFS in the pan-cancer cohort (HR 0.62, 95% CI 0.44 to 0.88, p=0.007), and Kaplan-Meier analysis further confirmed substantial differences in PFS between patients with inflamed and uninflamed status (log-rank test p=0.009).ConclusionsThe signature holds promise for impacting clinical decision-making, pan-cancer patient stratification, and treatment outcomes in immune checkpoint therapies.

Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most widely available clinical material to study colorectal cancer (CRC). However, the accuracy and clinical validity of FFPE microbiome profiling in CRC is uncertain. Here, we compared the microbial composition of 10 paired fresh-frozen (FF) and FFPE CRC tissues using 16S rRNA sequencing and RNA-ISH. Both sample types showed different microbial diversity and composition. FF samples were enriched in archaea and representative CRC-associated bacteria, such as Firmicutes, Bacteroidetes and Fusobacteria. Conversely, FFPE samples were mainly enriched in typical contaminants, such as Sphingomonadales and Rhodobacterales. RNA-ISH in FFPE tissues confirmed the presence of CRC-associated bacteria, such as Fusobacterium and Bacteroides, as well as Propionibacterium allowing discrimination between tumor-associated and contaminant taxa. An internal quality index showed that the degree of similarity within sample pairs inversely correlated with the dominance of contaminant taxa. Given the importance of FFPE specimens for larger studies in human cancer genomics, our findings may provide useful indications on potential confounding factors to consider for accurate and reproducible metagenomics analyses.

Diffusion Magnetic Resonance Imaging (dMRI) simulations in geometries mimicking the microscopic complexity of human tissues enable the development of innovative biomarkers with unprecedented fidelity to histology. Simulation-informed dMRI has traditionally focussed on brain imaging, and it has neglected other applications, as for example body cancer imaging, where new non-invasive biomarkers are still sought. This article fills this gap by introducing a Monte Carlo diffusion simulation framework informed by histology, for enhanced body dMR microstructural imaging: the Histo- μ Sim approach. We generate dictionaries of synthetic dMRI signals with coupled tissue properties from virtual cancer environments, reconstructed from hematoxylin-eosin stains of human liver biopsies. These enable the data-driven estimation of properties such as the intrinsic extra-cellular diffusivity, cell size or cell membrane permeability. We compare Histo- μ Sim to metrics from well-established analytical multi-compartment models in silico, on fixed mouse tissues scanned ex vivo (kidneys, spleens, and breast tumours) and in cancer patients in vivo. Results suggest that Histo- μ Sim is feasible in clinical settings, and that it delivers metrics that more accurately reflect histology as compared to analytical models. In conclusion, Histo- μ Sim offers histologically-meaningful tissue descriptors that may increase the specificity of dMRI towards cancer, and thus play a crucial role in precision oncology. A histology-informed, diffusion Magnetic Resonance Imaging simulation framework improves the non-invasive assessment of cancer biology in solid tumours in vivo

Background Innovative diffusion Magnetic Resonance Imaging (MRI) models enable the non-invasive measurement of cancer biological properties in vivo. However, while cancers frequently spread to the liver, models tailored for liver application and easy to deploy in the clinic are still sought. We fill this gap by delivering a practical, clinically-viable framework for liver tumour diffusion imaging, informing its design through histology. Methods: We compare MRI and histological data from mice and cancer patients, namely: MRI and hemaotxylin-eosin (HE) stains from N = 7 fixed mouse livers; MRI of N = 38 patients suffering from liver solid tumours, N = 18 of whom with HE biopsies. We study five diffusion models, ranking them according to a total MRI-histology correlation score. Afterwards, we test metrics from the top-ranking model on our cohort, assessing their sensitivity to cell proliferation (Ki-67 staining, N = 10), evaluating their association with tumour volume (N = 140 tumours), and comparing them across primary cancer types. Results: We select a dMRI signal model of restricted intra-cellular diffusion with negligible extra-cellular contributions, which maximises radiological-histological correlations (total score: 0.625). The model provides cell size and density estimates that i) correlate with histology (e.g., for cell size: r = 0.44, p = 0.029), ii) are associated to Ki-67 cell proliferation (for MRI cell density: r = 0.80, p = 0.006) and tumour volume (r = 0.40, p < 10 –5 for tumour volume regression), and iii) that distinguish melanoma (N = 8) from colorectal cancer (N = 13) (p = 0.011 for intra-cellular fraction). Conclusions: Our biologically meaningful approach may complement standard-of-care radiology, and become a new tool for enhanced cancer characterisation in precision oncology. Plain language summary Magnetic Resonance Imaging (MRI) is an imaging tool used frequently to detect and monitor malignant tumours. Notably, the latest MRI technology enables physicians to measure not only the size of a tumour, but even properties related to the cells it contains. This information, like number or size of cells can help oncologists to choose the best treatment. Obtaining this information using this imaging tool in tumors that have spread to the liver, remained challenging. Here we present an MRI method developed specifically to capture the biology of liver tumour cells. We base it on mathematical models that use information gathered from microscopy images – known as histology, where individual cells are visible – to guide the analysis of the scan. We show that the method quantifies tumour cell size and density from a simple, clinically feasible MRI scan and propose this technique for oncological applications. Grussu et al. use co-localised MRI and histology data to design a practical MRI technique for cell size and density measurement in liver tumours in vivo. The method provides non-invasive proxies of histological properties that are associated to cell proliferation, that explain tumour volume and that distinguish liver tumour types.

To predict outcome to combination bevacizumab (BVZ) therapy, we employed cell-free DNA (cfDNA) to determine chromosomal instability (CIN), nucleosome footprints (NF) and methylation profiles in metastatic colorectal cancer (mCRC) patients. Low-coverage whole-genome sequencing (LC-WGS) was performed on matched tumor and plasma samples, collected from 74 mCRC patients from the AC-ANGIOPREDICT Phase II trial (NCT01822444), and analysed for CIN and NFs. A validation cohort of plasma samples from the University Medical Center Mannheim (UMM) was similarly profiled. 61 AC-ANGIOPREDICT plasma samples collected before and following BVZ treatment were selected for targeted methylation sequencing. Using cfDNA CIN profiles, AC-ANGIOPREDICT samples were subtyped with 92.3% accuracy into low and high CIN clusters, with good concordance observed between matched plasma and tumor. Improved survival was observed in CIN-high patients. Plasma-based CIN clustering was validated in the UMM cohort. Methylation profiling identified differences in CIN-low vs. CIN high (AUC = 0.87). Moreover, significant methylation score decreases following BVZ was associated with improved outcome (p = 0.013). Analysis of CIN, NFs and methylation profiles from cfDNA in plasma samples facilitates stratification into CIN clusters which inform patient response to treatment.

The effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the pathophysiology of the placenta and its impact on pregnancy outcome has not yet been fully elucidated. Here, we present a comprehensive clinical, morphological, and molecular analysis of placental tissues from pregnant women with and without SARS-CoV-2 infection. SARS-CoV-2 could be detected in half of placental tissues from SARS-CoV-2-positive women. The presence of the virus was not associated with any distinctive pathological, maternal, or neonatal outcome features. SARS-CoV-2 tissue load was low in all but one patient who exhibited severe placental damage leading to neonatal neurological manifestations. The placental transcriptional response induced by high viral load of SARS-CoV-2 showed an immunopathology phenotype similar to autopsy lung tissues from patients with severe coronavirus disease 2019. This finding contrasted with the lack of inflammatory response in placental tissues from SARS-CoV-2-positive women with low viral tissue load and from SARS-CoV-2-negative women. Importantly, no evidence of vertical transmission of SARS-CoV-2 was found in any newborns, suggesting that the placenta may be an effective maternal-neonatal barrier against the virus even in the presence of severe infection. Our observations suggest that severe placental damage induced by the virus may be detrimental for the neonate independently of vertical transmission.

Patient-derived organoids (PDOs) recapitulate tumor architecture, contain cancer stem cells and have predictive value supporting personalized medicine. Here we describe a large-scale functional screen of dual-targeting bispecific antibodies (bAbs) on a heterogeneous colorectal cancer PDO biobank and paired healthy colonic mucosa samples. More than 500 therapeutic bAbs generated against Wingless-related integration site (WNT) and receptor tyrosine kinase (RTK) targets were functionally evaluated by high-content imaging to capture the complexity of PDO responses. Our drug discovery strategy resulted in the generation of MCLA-158, a bAb that specifically triggers epidermal growth factor receptor degradation in leucine-rich repeat-containing G-protein-coupled receptor 5-positive (LGR5+) cancer stem cells but shows minimal toxicity toward healthy LGR5+ colon stem cells. MCLA-158 exhibits therapeutic properties such as growth inhibition of KRAS-mutant colorectal cancers, blockade of metastasis initiation and suppression of tumor outgrowth in preclinical models for several epithelial cancer types.

Genome‐wide association studies have described several genes as genetic susceptibility loci for Alzheimer's disease (AD). Among them, CD2AP encodes CD2‐associated protein, a scaffold protein implicated in dynamic actin remodeling and membrane trafficking during endocytosis and cytokinesis. Although a clear link between CD2AP defects and glomerular pathology has been described, little is known about the function of CD2AP in the brain. The aim of this study was to analyze the distribution of CD2AP in the AD brain and its potential associations with tau aggregation and β‐amyloid (Aβ) deposition. First, we performed immunohistochemical analysis of CD2AP expression in brain tissue from AD patients and controls (N = 60). Our results showed granular CD2AP immunoreactivity in the human brain endothelium in all samples. In AD cases, no CD2AP was found to be associated with Aβ deposits in vessels or parenchymal plaques. CD2AP neuronal inclusions similar to neurofibrillary tangles (NFT) and neuropil thread‐like deposits were found only in AD samples. Moreover, immunofluorescence analysis revealed that CD2AP colocalized with pTau. Regarding CD2AP neuronal distribution, a hierarchical progression from the entorhinal to the temporal and occipital cortex was detected. We found that CD2AP immunodetection in neurons was strongly and positively associated with Braak neurofibrillary stage, independent of age and other pathological hallmarks. To further investigate the association between pTau and CD2AP, we included samples from cases of primary tauopathies (corticobasal degeneration [CBD], progressive supranuclear palsy [PSP], and Pick's disease [PiD]) in our study. Among these cases, CD2AP positivity was only found in PiD samples as neurofibrillary tangle‐like and Pick body‐like deposits, whereas no neuronal CD2AP deposits were detected in PSP or CBD samples, which suggested an association of CD2AP neuronal expression with 3R‐Tau‐diseases. In conclusion, our findings open a new road to investigate the complex cellular mechanism underlying the tangle conformation and tau pathology in the brain.