Co-shared genomic alterations within tumors from patients with both myeloproliferative neoplasms and lymphoma.

Not available.

ADAM12-Generated Basigin Ectodomain Binds ß1 Integrin and Enhances the Expression of Cancer-Related Extracellular Matrix Proteins.

Desmoplasia is a common feature of aggressive cancers, driven by a complex interplay of protein production and degradation. Basigin is a type 1 integral membrane receptor secreted in exosomes or released by ectodomain shedding from the cell surface. Given that soluble basigin is increased in the circulation of patients with a poor cancer prognosis, we explored the putative role of the ADAM12-generated basigin ectodomain in cancer progression. We show that recombinant basigin ectodomain binds ß1 integrin and stimulates gelatin degradation and the migration of cancer cells in a matrix metalloproteinase (MMP)- and ß1-integrin-dependent manner. Subsequent in vitro and in vivo experiments demonstrated the altered expression of extracellular matrix proteins, including fibronectin and collagen type 5. Thus, we found increased deposits of collagen type 5 in the stroma of nude mice tumors of the human tumor cell line MCF7 expressing ADAM12-mimicking the desmoplastic response seen in human cancer. Our findings indicate a feedback loop between ADAM12 expression, basigin shedding, TGFß signaling, and extracellular matrix (ECM) remodeling, which could be a mechanism by which ADAM12-generated basigin ectodomain contributes to the regulation of desmoplasia, a key feature in human cancer progression.

Exploring the biology of ctDNA release in colorectal cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a promising tool for early cancer detection and minimal residual disease monitoring. However, the biology underlying ctDNA release and its variation across cancer types and histologies remains poorly understood. This study investigated the biology behind ctDNA shedding in colorectal cancer. METHODS: The study included a local cohort of 747 stage I-III colorectal cancer patients. All patients had ctDNA measurement prior to treatment and extensive clinical data. Primary tumor RNA sequencing and whole exome sequencing was performed in 95 and 652 patients respectively. Additionally, the study evaluated 89 non-small cell lung cancer patients from the TRACERx cohort, comprising primary tumor RNA sequencing and ctDNA measurement. RESULTS: We found tumor size and proliferative capacity to be key factors associated with ctDNA shedding in colorectal cancer. Furthermore, we found that the secretory and CMS3 colorectal cancer subtypes exhibited lower ctDNA shedding, while microsatellite instability (MSI) tumors had higher levels of ctDNA. Mutational analysis did not reveal any genes or pathways associated with ctDNA shedding in colorectal cancer. A comparison of transcriptomic profiles across multiple cancer types demonstrated that colorectal cancer and lung squamous cell carcinoma tumors shared a high-proliferative ctDNA shedding phenotype, while lung adenocarcinoma tumors displayed a distinct low-proliferative subgroup. Additionally, proliferation levels correlated with ctDNA detection sensitivity across multiple cancer types. CONCLUSION: These findings suggest that tumor size and proliferative capacity are drivers of ctDNA release in colorectal cancer and provide insights into the biology of ctDNA shedding on a pan-cancer level.

Gluco-metabolic response to exogenous oxytocin in totally pancreatectomized patients and healthy individuals.

Oxytocin has been proposed to possess glucose-stabilizing effects through the release of insulin and glucagon from the pancreas. Also, exogenous oxytocin has been shown to stimulate extrapancreatic glucagon secretion in depancreatized dogs. Here, we investigated the effect of exogenous oxytocin on circulating levels of pancreatic and gut-derived glucose-stabilizing hormones (insulin [measured as C-peptide], glucagon, glucagon-like peptide 1 [GLP-1], and glucose-dependent insulinotropic polypeptide). We studied nine pancreatectomized (PX) patients and nine healthy controls (CTRLs) (matched on age and body mass index) before, during, and after an intravenous infusion of 10 IU of oxytocin administered over 12 min. Oxytocin did not increase plasma glucagon levels, nor induce any changes in plasma glucose, C-peptide, or GIP in any of the groups. Oxytocin decreased plasma glucagon levels by 19 ± 10 % in CTRLs (from 2.0 ± 0.5 [mean ± SEM] to 1.3 ± 0.2 pmol/l, P = 0.0025) and increased GLP-1 by 42 ± 22 % in PX patients (from 9.0 ± 1.0-12.7 ± 1.0 pmol/l, P = 0.0003). Fasting plasma glucose levels were higher in PX patients compared with CTRLs (13.1 ± 1.1 vs. 5.1 ± 0.1 mmol/l, P < 0.0001). In conclusion, the present findings do not support pancreas-mediated glucose-stabilizing effects of acute oxytocin administration in humans and warrant further investigation of oxytocin's gluco-metabolic effects.

Exploring the molecular landscape of cancer of unknown primary: A comparative analysis with other metastatic cancers.

Cancer of unknown primary (CUP) tumors are biologically very heterogeneous, which complicates stratification of patients for treatment. Consequently, these patients face limited treatment options and a poor prognosis. With this study, we aim to expand on the current knowledge of CUP biology by analyzing two cohorts: a well-characterized cohort of 44 CUP patients, and 213 metastatic patients with known primary. These cohorts were treated at the same institution and characterized by identical molecular assessments. Through comparative analysis of genomic and transcriptomic data, we found that CUP tumors were characterized by high expression of immune-related genes and pathways compared to other metastatic tumors. Moreover, CUP tumors uniformly demonstrated high levels of tumor-infiltrating leukocytes and circulating T cells, indicating a strong immune response. Finally, the genetic landscape of CUP tumors resembled that of other metastatic cancers and demonstrated mutations in established cancer genes. In conclusion, CUP tumors possess a distinct immunophenotype that distinguishes them from other metastatic cancers. These results may suggest an immune response in CUP that facilitates metastatic tumor growth while limiting growth of the primary tumor.

Patients with autoimmune liver disease have glucose disturbances that mechanistically differ from steatotic liver disease.

Autoimmune liver diseases are associated with an increased risk of diabetes, yet the underlying mechanisms remain unknown. In this cross-sectional study, we investigated the glucose-regulatory disturbances in patients with autoimmune hepatitis (AIH, n = 19), primary biliary cholangitis (PBC, n = 15), and primary sclerosing cholangitis (PSC, n = 6). Healthy individuals (n = 24) and patients with metabolic dysfunction-associated steatotic liver disease (MASLD, n = 18) were included as controls. Blood samples were collected during a 120-min oral glucose tolerance test. We measured the concentrations of glucose, C-peptide, insulin, glucagon, and the two incretin hormones, glucose insulinotropic peptide (GIP) and glucagon-like peptide-1 (GLP-1). We calculated the homeostasis model assessment of insulin resistance (HOMA-IR), whole body insulin resistance (Matsuda index), insulin clearance, and insulinogenic index. All patient groups had increased fasting plasma glucose and impaired glucose responses compared with healthy controls. Beta-cell secretion was increased in AIH, PBC, and MASLD but not in PSC. Patients with AIH and MASLD had hyperglucagonemia and hepatic, as well as peripheral, insulin resistance and decreased insulin clearance, resulting in hyperinsulinemia. Patients with autoimmune liver disease had an increased GIP response, and those with AIH or PBC had an increased GLP-1 response. Our data demonstrate that the mechanism underlying glucose disturbances in patients with autoimmune liver disease differs from that underlying MASLD, including compensatory incretin responses in patients with autoimmune liver disease. Our results suggest that glucose disturbances are present at an early stage of the disease.NEW & NOTEWORTHY Patients with autoimmune liver disease but without overt diabetes display glucose disturbances early on in their disease course. We identified pathophysiological traits specific to these patients including altered incretin responses.

Foundation model for cancer imaging biomarkers.

Foundation models in deep learning are characterized by a single large-scale model trained on vast amounts of data serving as the foundation for various downstream tasks. Foundation models are generally trained using self-supervised learning and excel in reducing the demand for training samples in downstream applications. This is especially important in medicine, where large labelled datasets are often scarce. Here, we developed a foundation model for cancer imaging biomarker discovery by training a convolutional encoder through self-supervised learning using a comprehensive dataset of 11,467 radiographic lesions. The foundation model was evaluated in distinct and clinically relevant applications of cancer imaging-based biomarkers. We found that it facilitated better and more efficient learning of imaging biomarkers and yielded task-specific models that significantly outperformed conventional supervised and other state-of-the-art pretrained implementations on downstream tasks, especially when training dataset sizes were very limited. Furthermore, the foundation model was more stable to input variations and showed strong associations with underlying biology. Our results demonstrate the tremendous potential of foundation models in discovering new imaging biomarkers that may extend to other clinical use cases and can accelerate the widespread translation of imaging biomarkers into clinical settings.

Secretion of glucagon, GLP-1 and GIP may be affected by circadian rhythm in healthy males.

BACKGROUND: Glucagon is secreted from pancreatic alpha cells in response to low blood glucose and increases hepatic glucose production. Furthermore, glucagon enhances hepatic protein and lipid metabolism during a mixed meal. Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are secreted from gut endocrine cells during meals and control glucose homeostasis by potentiating insulin secretion and inhibiting food intake. Both glucose homeostasis and food intake have been reported to be affected by circadian rhythms and vice versa. In this study, we investigated whether the secretion of glucagon, GLP-1 and GIP was affected by circadian rhythms. METHODS: A total of 24 healthy men with regular sleep schedules were examined for 24 h at the hospital ward with 15 h of wakefulness and 9 h of sleep. Food intake was standardized, and blood samples were obtained every third hour. Plasma concentrations of glucagon, GLP-1 and GIP were measured, and data were analyzed by rhythmometric statistical methods. Available data on plasma glucose and plasma C-peptide were also included. RESULTS: Plasma concentrations of glucagon, GLP-1, GIP, C-peptide and glucose fluctuated with a diurnal 24-h rhythm, with the highest levels during the day and the lowest levels during the night: glucagon (p < 0.0001, peak time 18:26 h), GLP-1 (p < 0.0001, peak time 17:28 h), GIP (p < 0.0001, peak time 18:01 h), C-peptide (p < 0.0001, peak time 17.59 h), and glucose (p < 0.0001, peak time 23:26 h). As expected, we found significant correlations between plasma concentrations of C-peptide and GLP-1 and GIP but did not find correlations between glucose concentrations and concentrations of glucagon, GLP-1 and GIP. CONCLUSIONS: Our results demonstrate that under meal conditions that are similar to that of many free-living individuals, plasma concentrations of glucagon, GLP-1 and GIP were observed to be higher during daytime and evening than overnight. These findings underpin disturbed circadian rhythm as a potential risk factor for diabetes and obesity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06166368. Registered 12 December 2023.

CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction.

Intratumor heterogeneity provides the fuel for the evolution and selection of subclonal tumor cell populations. However, accurate inference of tumor subclonal architecture and reconstruction of tumor evolutionary histories from bulk DNA sequencing data remains challenging. Frequently, sequencing and alignment artifacts are not fully filtered out from cancer somatic mutations, and errors in the identification of copy number alterations or complex evolutionary events (e.g., mutation losses) affect the estimated cellular prevalence of mutations. Together, such errors propagate into the analysis of mutation clustering and phylogenetic reconstruction. In this Protocol, we present a new computational framework, CONIPHER (COrrecting Noise In PHylogenetic Evaluation and Reconstruction), that accurately infers subclonal structure and phylogenetic relationships from multisample tumor sequencing, accounting for both copy number alterations and mutation errors. CONIPHER has been used to reconstruct subclonal architecture and tumor phylogeny from multisample tumors with high-depth whole-exome sequencing from the TRACERx421 dataset, as well as matched primary-metastatic cases. CONIPHER outperforms similar methods on simulated datasets, and in particular scales to a large number of tumor samples and clones, while completing in under 1.5 h on average. CONIPHER enables automated phylogenetic analysis that can be effectively applied to large sequencing datasets generated with different technologies. CONIPHER can be run with a basic knowledge of bioinformatics and R and bash scripting languages.

Preanalytical impact on the accuracy of measurements of glucagon, GLP-1 and GIP in clinical trials.

BACKGROUND: Plasma concentrations of glucagon, GLP-1 and GIP are reported in numerous clinical trials as outcome measures but preanalytical guidelines are lacking. We addressed the impact of commonly used blood containers in metabolic research on measurements of glucagon, GLP-1 and GIP in humans. METHODS: Seventeen overweight individuals were subjected to an overnight fast followed by an intravenous infusion of amino acids to stimulate hormonal secretion. Blood was sampled into five containers: EDTA-coated tubes supplemented with DMSO (control), a neprilysin inhibitor, aprotinin (a kallikrein inhibitor) or a DPP-4 inhibitor, and P800 tubes. Plasma was kept on ice before and after centrifugation and stored at -80 Celsius until batch analysis using validated sandwich ELISAs or radioimmunoassays (RIA). RESULTS: Measures of fasting plasma glucagon did not depend on sampling containers, whether measured by ELISA or RIA. Amino acid-induced hyperglucagonemia was numerically higher when blood was collected into P800 tubes or tubes with aprotinin. The use of p800 tubes resulted in higher concentrations of GLP-1 by RIA compared to control tubes but not for measurements with sandwich ELISA. Plasma concentrations of GIP measured by ELISA were higher in control tubes and negatively affected by P800 and the addition of aprotinin. CONCLUSIONS: The choice of blood containers impacts on measurements of plasma concentrations of glucagon, GLP-1 and GIP, and based on this study, we recommend using EDTA-coated tubes without protease inhibitors or P800 tubes for measurements of glucagon, GLP-1 and GIP in clinical trials.

Neprilysin activity is increased in metabolic dysfunction-associated steatotic liver disease and normalizes after bariatric surgery or GLP-1 therapy.

Inhibitors of neprilysin improve glycemia in patients with heart failure and type 2 diabetes (T2D). The effect of weight loss by diet, surgery, or pharmacotherapy on neprilysin activity (NEPa) is unknown. We investigated circulating NEPa and neprilysin protein concentrations in obesity, T2D, metabolic dysfunction-associated steatotic liver disease (MASLD), and following bariatric surgery, or GLP-1-receptor-agonist therapy. NEPa, but not neprilysin protein, was enhanced in obesity, T2D, and MASLD. Notably, MASLD associated with NEPa independently of BMI and HbA1c. NEPa decreased after bariatric surgery with a concurrent increase in OGTT-stimulated GLP-1. Diet-induced weight loss did not affect NEPa, but individuals randomized to 52-week weight maintenance with liraglutide (1.2 mg/day) decreased NEPa, consistent with another study following 6-week liraglutide (3 mg/day). A 90-min GLP-1 infusion did not alter NEPa. Thus, MASLD may drive exaggerated NEPa, and lowered NEPa following bariatric surgery or liraglutide therapy may contribute to the reported improved cardiometabolic effects.

Suboptimal diagnostic accuracy of ultrasound and CT for compensated cirrhosis: Evidence from prospective cohort studies.

INTRODUCTION: Abdominal ultrasound (US) and CT are important tools for the initial evaluation of patients with liver disease. Our study aimed to determine the accuracy of these methods for diagnosing cirrhosis. METHODS: In all, 377 participants from 4 prospective cohort studies evaluating patients with various liver diseases were included. All patients were included between 2017 and 2022 and had undergone a liver biopsy as well as US and/or CT. Using the histological assessment as the gold standard, we calculated diagnostic accuracy for US and CT. Liver biopsies were evaluated by expert histopathologists and diagnostic scans by experienced radiologists. RESULTS: The mean age was 54 ± 14 years and 47% were female. Most patients had NAFLD (58.3%) or alcohol-associated liver disease (25.5%). The liver biopsy showed cirrhosis in 147 patients (39.0%). Eighty-three patients with cirrhosis had Child-Pugh A (56.4% of patients with cirrhosis) and 64 had Child-Pugh B/C (43.6%). Overall, the sensitivity for diagnosing cirrhosis by US was 0.71 (95% CI 0.62-0.79) and for CT 0.74 (95% CI 0.64-0.83). The specificity was high for US (0.94, 95% CI 0.90-0.97) and for CT (0.93, 95% CI 0.83-0.98). When evaluating patients with Child-Pugh A cirrhosis, sensitivity was only 0.62 (95% CI 0.49-0.74) for US and 0.60 (95% CI 0.43-0.75) for CT. For patients with Child-Pugh B/C, sensitivity was 0.83 (95% CI 0.70-0.92) for US and 0.87 (95% CI 0.74-0.95) for CT. When limiting our analysis to NAFLD (20% with cirrhosis), the sensitivity for US was 0.45 (95% CI 0.28-0.64) and specificity was 0.97 (95% CI 0.93-0.99). CONCLUSION: US and CT show moderate sensitivity and may potentially overlook compensated cirrhosis underlining the need for additional diagnostic testing.

Spatial transformation of multi-omics data unlocks novel insights into cancer biology.

The application of next-generation sequencing (NGS) has transformed cancer research. As costs have decreased, NGS has increasingly been applied to generate multiple layers of molecular data from the same samples, covering genomics, transcriptomics, and methylomics. Integrating these types of multi-omics data in a combined analysis is now becoming a common issue with no obvious solution, often handled on an ad hoc basis, with multi-omics data arriving in a tabular format and analyzed using computationally intensive statistical methods. These methods particularly ignore the spatial orientation of the genome and often apply stringent p-value corrections that likely result in the loss of true positive associations. Here, we present GENIUS (GEnome traNsformatIon and spatial representation of mUltiomicS data), a framework for integrating multi-omics data using deep learning models developed for advanced image analysis. The GENIUS framework is able to transform multi-omics data into images with genes displayed as spatially connected pixels and successfully extract relevant information with respect to the desired output. We demonstrate the utility of GENIUS by applying the framework to multi-omics datasets from the Cancer Genome Atlas. Our results are focused on predicting the development of metastatic cancer from primary tumors, and demonstrate how through model inference, we are able to extract the genes which are driving the model prediction and are likely associated with metastatic disease progression. We anticipate our framework to be a starting point and strong proof of concept for multi-omics data transformation and analysis without the need for statistical correction.

Foundation Models for Quantitative Biomarker Discovery in Cancer Imaging.

Foundation models represent a recent paradigm shift in deep learning, where a single large-scale model trained on vast amounts of data can serve as the foundation for various downstream tasks. Foundation models are generally trained using self-supervised learning and excel in reducing the demand for training samples in downstream applications. This is especially important in medicine, where large labeled datasets are often scarce. Here, we developed a foundation model for imaging biomarker discovery by training a convolutional encoder through self-supervised learning using a comprehensive dataset of 11,467 radiographic lesions. The foundation model was evaluated in distinct and clinically relevant applications of imaging-based biomarkers. We found that they facilitated better and more efficient learning of imaging biomarkers and yielded task-specific models that significantly outperformed their conventional supervised counterparts on downstream tasks. The performance gain was most prominent when training dataset sizes were very limited. Furthermore, foundation models were more stable to input and inter-reader variations and showed stronger associations with underlying biology. Our results demonstrate the tremendous potential of foundation models in discovering novel imaging biomarkers that may extend to other clinical use cases and can accelerate the widespread translation of imaging biomarkers into clinical settings.

Evolutionary characterization of lung adenocarcinoma morphology in TRACERx.

Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and 'tumor spread through air spaces' were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk.

Body composition and lung cancer-associated cachexia in TRACERx.

Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC.

Genomic-transcriptomic evolution in lung cancer and metastasis.

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic-transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary-metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.

Antibodies against endogenous retroviruses promote lung cancer immunotherapy.

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.

Carbonic anhydrases reduce the acidity of the tumor microenvironment, promote immune infiltration, decelerate tumor growth, and improve survival in ErbB2/HER2-enriched breast cancer.

BACKGROUND: Carbonic anhydrases catalyze CO2/HCO3- buffer reactions with implications for effective H+ mobility, pH dynamics, and cellular acid-base sensing. Yet, the integrated consequences of carbonic anhydrases for cancer and stromal cell functions, their interactions, and patient prognosis are not yet clear. METHODS: We combine (a) bioinformatic analyses of human proteomic data and bulk and single-cell transcriptomic data coupled to clinicopathologic and prognostic information; (b) ex vivo experimental studies of gene expression in breast tissue based on quantitative reverse transcription and polymerase chain reactions, intracellular and extracellular pH recordings based on fluorescence confocal microscopy, and immunohistochemical protein identification in human and murine breast cancer biopsies; and (c) in vivo tumor size measurements, pH-sensitive microelectrode recordings, and microdialysis-based metabolite analyses in mice with experimentally induced breast carcinomas. RESULTS: Carbonic anhydrases-particularly the extracellular isoforms CA4, CA6, CA9, CA12, and CA14-undergo potent expression changes during human and murine breast carcinogenesis. In patients with basal-like/triple-negative breast cancer, elevated expression of the extracellular carbonic anhydrases negatively predicts survival, whereas, surprisingly, the extracellular carbonic anhydrases positively predict patient survival in HER2/ErbB2-enriched breast cancer. Carbonic anhydrase inhibition attenuates cellular net acid extrusion and extracellular H+ elimination from diffusion-restricted to peripheral and well-perfused regions of human and murine breast cancer tissue. Supplied in vivo, the carbonic anhydrase inhibitor acetazolamide acidifies the microenvironment of ErbB2-induced murine breast carcinomas, limits tumor immune infiltration (CD3+ T cells, CD19+ B cells, F4/80+ macrophages), lowers inflammatory cytokine (Il1a, Il1b, Il6) and transcription factor (Nfkb1) expression, and accelerates tumor growth. Supporting the immunomodulatory influences of carbonic anhydrases, patient survival benefits associated with high extracellular carbonic anhydrase expression in HER2-enriched breast carcinomas depend on the tumor inflammatory profile. Acetazolamide lowers lactate levels in breast tissue and blood without influencing breast tumor perfusion, suggesting that carbonic anhydrase inhibition lowers fermentative glycolysis. CONCLUSIONS: We conclude that carbonic anhydrases (a) elevate pH in breast carcinomas by accelerating net H+ elimination from cancer cells and across the interstitial space and (b) raise immune infiltration and inflammation in ErbB2/HER2-driven breast carcinomas, restricting tumor growth and improving patient survival.

Postprandial dysfunction in fatty liver disease.

Fatty liver disease has mainly been characterized under fasting conditions. However, as the liver is essential for postprandial homeostasis, identifying postprandial disturbances may be important. Here, we investigated postprandial changes in markers of metabolic dysfunction between healthy individuals, obese individuals with non-alcoholic fatty liver disease (NAFLD) and patients with cirrhosis. We included individuals with biopsy-proven NAFLD (n = 9, mean age 50 years, mean BMI 35 kg/m2 , no/mild fibrosis), cirrhosis with hepatic steatosis (n = 10, age 62 years, BMI 32 kg/m2 , CHILD A/B) and healthy controls (n = 10, age 23, BMI 25 kg/m2 ), randomized 1:1 to fasting or standardized mixed meal test (postprandial). None of the patients randomized to mixed meal test had type 2 diabetes (T2D). Peripheral blood was collected for 120 min. After 60 min, a transjugular liver biopsy and liver vein blood was taken. Plasma levels of glucose, insulin, C-peptide, glucagon, and fibroblast growth factor 21 (FGF21) were measured. Postprandial peak glucose and C-peptide were significantly increased in NAFLD, and cirrhosis compared with healthy. Patients with NAFLD and cirrhosis had hyperglucagonemia as a potential sign of glucagon resistance. FGF21 was increased in NAFLD and cirrhosis independent of sampling from the liver vein versus peripheral blood. Glucagon levels were higher in the liver vein compared with peripheral blood. Patients with NAFLD and cirrhosis without T2D showed impaired glucose tolerance, hyperinsulinemia, and hyperglucagonemia after a meal compared to healthy individual. Postprandial characterization of patients with NAFLD may be important to capture their metabolic health.