Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes.

Schizophrenia has been conceived as a disorder of brain connectivity, but it is unclear how this network phenotype is related to the underlying genetics. We used morphometric similarity analysis of MRI data as a marker of interareal cortical connectivity in three prior case-control studies of psychosis: in total, n = 185 cases and n = 227 controls. Psychosis was associated with globally reduced morphometric similarity in all three studies. There was also a replicable pattern of case-control differences in regional morphometric similarity, which was significantly reduced in patients in frontal and temporal cortical areas but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in morphometric similarity was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally overexpressed in cortical areas with reduced morphometric similarity were significantly up-regulated in three prior post mortem studies of schizophrenia. We propose that this combined analysis of neuroimaging and transcriptional data provides insight into how previously implicated genes and proteins as well as a number of unreported genes in their topological vicinity on the protein interaction network may drive structural brain network changes mediating the genetic risk of schizophrenia.This study was supported by grants from the European Commission (PSYSCAN - Translating neuroimaging findings from research into clinical practice; ID: 603196) and the NIHR Cambridge Biomedical Research Centre (Mental Health). SEM holds a Henslow Fellowship at Lucy Cavendish College, University of Cambridge, funded by the Cambridge Philosophical Society. PEV was supported by the Medical Research Council (MR/K020706/1) and an MQ fellowship (MQF17_24) and is a Fellow of the Alan Turing Institute funded under the EPSRC grant EP/N510129/1. KJW was funded by an Alan Turing Institute Research Fellowship under EPSRC Research grant TU/A/000017. ETB is supported by a NIHR Senior Investigator Award

EGFR amplification and outcome in a randomised phase III trial of chemotherapy alone or chemotherapy plus panitumumab for advanced gastro-oesophageal cancers.

Funder: FP7 People: Marie-Curie Actions; FundRef: http://dx.doi.org/10.13039/100011264; Grant(s): CIG 334261OBJECTIVE: Epidermal growth factor receptor (EGFR) inhibition may be effective in biomarker-selected populations of advanced gastro-oesophageal adenocarcinoma (aGEA) patients. Here, we tested the association between outcome and EGFR copy number (CN) in pretreatment tissue and plasma cell-free DNA (cfDNA) of patients enrolled in a randomised first-line phase III clinical trial of chemotherapy or chemotherapy plus the anti-EGFR monoclonal antibody panitumumab in aGEA (NCT00824785). DESIGN: EGFR CN by either fluorescence in situ hybridisation (n=114) or digital-droplet PCR in tissues (n=250) and plasma cfDNAs (n=354) was available for 474 (86%) patients in the intention-to-treat (ITT) population. Tissue and plasma low-pass whole-genome sequencing was used to screen for coamplifications in receptor tyrosine kinases. Interaction between chemotherapy and EGFR inhibitors was modelled in patient-derived organoids (PDOs) from aGEA patients. RESULTS: EGFR amplification in cfDNA correlated with poor survival in the ITT population and similar trends were observed when the analysis was conducted in tissue and plasma by treatment arm. EGFR inhibition in combination with chemotherapy did not correlate with improved survival, even in patients with significant EGFR CN gains. Addition of anti-EGFR inhibitors to the chemotherapy agent epirubicin in PDOs, resulted in a paradoxical increase in viability and accelerated progression through the cell cycle, associated with p21 and cyclin B1 downregulation and cyclin E1 upregulation, selectively in organoids from EGFR-amplified aGEA. CONCLUSION: EGFR CN can be accurately measured in tissue and liquid biopsies and may be used for the selection of aGEA patients. EGFR inhibitors may antagonise the antitumour effect of anthracyclines with important implications for the design of future combinatorial trials

Analysis and modelling of gastric cancer subtypes by the use of patient derived and murine organoids as well as a stomach specific mouse model.

Gastric cancer is the second leading cause of cancer related deaths and the fifth most common malignancy worldwide. The prognosis of gastric cancer is often poor. Frequently, the lack of clinical signs lead to a delayed diagnosis with three quarters of patients presenting with non-curable advanced disease. The only curative option is surgery, supported in recent years by perioperative chemotherapy. However, known molecular alterations represent possibilities for targeted therapies to improve overall survival. Nevertheless, biomarkers to predict therapy response are missing, resulting in several failed clinical trials for targeted drugs. Organoids are a recently developed three-dimensional culture system derived from different sources, i.e. adult tissue stem cells, embryonic stem cells (ESC) or induced pluripotent stem cells (iPSC). While in ESC or iPSC derived organoids a functional niche is present that maintains stem cells, this niche is missing in adult stem cell derived organoids and needs to be replaced by a definite medium containing the relevant growth factors. Organoids have the ability of proliferation, self-renewal and self-organization. They show a comparable functionality of the organs they are derived from. In sum, organoids are valuable tools to study diseases on a patient level. In this work, we focused on the characterization of gastric cancer by using human and mouse cancer organoids. Firstly, a human gastric cancer organoid biobank was established. The patient derived organoid lines were characterized concerning their molecular profile, treated with classical chemotherapeutics and mutation specific targeting was performed. The generated human cancer organoids showed a high similarity to the tissue they were derived from and allowed a detailed analysis of observed alterations for each individual patient. However, the high number of mutations effected targeted therapies and needed to be interpreted in the whole mutation spectrum of each specific organoid line. In order to establish organoids with defined mutations for in depth analysis of pathway interference, we decided to combine inducible alleles of frequently altered signaling pathways in gastric cancer in mice and derived organoids of the stomach. These organoid lines were further analyzed by their morphology, functionality and drug response. Successful interference with activated pathways demonstrated their potential usefulness as living biomarkers for therapy response testing. In order to analyze gastric cancer in vivo a stomach specific mouse model was established. Intensive literature and database research resulted in the identification of Annexin10 (Anxa10) as potential stomach specific gene which at the same time is expressed in all different cell types of the stomach epithelium. We therefore generated an inducible Cre recombinase mouse line under the Anxa10 promotor. The Anxa10 CreERT2 line showed only stomach specific recombination events and no restriction to a specific cell type. Nevertheless, activation of Cre resulted in a patchy recombination pattern throughout the whole gland and not a uniform recombination in all cells. Due to this patchy expression, the mouse line is an optimal tool for cancer models, where a complete transformation of an organ is not desired. On the other side it is not useful, if a complete knock-out of a certain floxed allele is needed. This new stomach specific mouse line was then used to model gastric cancer subtypes in vivo. Frequently altered pathways and hotspot mutations of each gastric cancer subtype were defined based on the TCGA database. Alterations were mainly found in the following pathways: RTK/RAS, PI3K/AKT, WNT, TGF β, cell adhesion and chromatin remodelling. We generated and analyzed three different mouse models: one for the chromosomal instability (CIN) subtype and two for the genomically stable (GS) subtype. The different models mimicked very closely the histology of known human gastric cancer subtypes. The intestinal CIN model with mutations in Kras, Smad4 and Tp53 developed tumors with glandular and tubular structures showing morphologies to human intestinal type gastric cancer. The first GS model with alterations in Kras, Cdh1 and Smad4 showed cancers with a diffuse tumor cell morphology with the presence of typical signet ring cells. The second GS model with Kras, Cdh1 and Apc alterations showed similarities to the adenomatous tooth like gastric cancer subtype. Taken together, this study demonstrates that gastric cancer organoids might serve as living biomarkers to predict therapy response and resistance in individual patients. Additionally, the generated gastric cancer mouse model is to our knowledge the first model initiating tumor formation exclusively in the stomach with similar characteristics as described for human gastric cancer. This mouse represents a prime tool for further gastric cancer research

CFTR Expression Analysis for Subtyping of Human Pancreatic Cancer Organoids

Background. Organoid cultures of human pancreatic ductal adenocarcinoma (PDAC) have become a promising tool for tumor subtyping and individualized chemosensitivity testing. PDACs have recently been grouped into different molecular subtypes with clinical impact based on cytokeratin-81 (KRT81) and hepatocyte nuclear factor 1A (HNF1A). However, a suitable antibody for HNF1A is currently unavailable. The present study is aimed at establishing subtyping in PDAC organoids using an alternative marker. Methods. A PDAC organoid biobank was generated from human primary tumor samples containing 22 lines. Immunofluorescence staining was established and done for 10 organoid lines for cystic fibrosis transmembrane conductance regulator (CFTR) and KRT81. Quantitative real-time PCR (qPCR) was performed for CFTR and HNF1A. A chemotherapeutic drug response analysis was done using gemcitabine, 5-FU, oxaliplatin, and irinotecan. Results. A biobank of patient-derived PDAC organoids was established. The efficiency was 71% (22/31) with 68% for surgical resections and 83% for fine needle aspirations. Organoids could be categorized into the established quasimesenchymal, exocrine-like, and classical subtypes based on KRT81 and CFTR immunoreactivity. CFTR protein expression was confirmed on the transcript level. CFTR and HNF1A transcript expression levels positively correlated (n=10; r=0.927; p=0.001). PDAC subtypes of the primary tumors and the corresponding organoid lines were identical for most of the cases analyzed (6/7). Treatment with chemotherapeutic drugs revealed tendencies but no significant differences regarding drug responses. Conclusions. Human PDAC organoids can be classified into known subtypes based on KRT81 and CFTR immunoreactivity. CFTR and HNF1A mRNA levels correlated well. Furthermore, subtype-specific immunoreactivity matched well between PDAC organoids and the respective primary tumor tissue. Subtyping of human PDACs using CFTR might constitute an alternative to HNF1A and should be further investigated

Sensitivity towards HDAC inhibition is associated with RTK/MAPK pathway activation in gastric cancer

Gastric cancer ranks the fifth most common and third leading cause of cancer-related deaths worldwide. Alterations in the RTK/MAPK, WNT, cell adhesion, TP53, TGF beta, NOTCH, and NF kappa B signaling pathways could be identified as main oncogenic drivers. A combination of altered pathways can be associated with molecular subtypes of gastric cancer. In order to generate model systems to study the impact of different pathway alterations in a defined genetic background, we generated three murine organoid models: a RAS-activated (Kras(G12D), Tp53(R172H)), a WNT-activated (Apc(fl/fl), Tp53(R172H)), and a diffuse (Cdh1(fl/fl), Apc(fl/fl)) model. These organoid models were morphologically and phenotypically diverse, differed in proteome expression signatures and possessed individual drug sensitivities. A differential vulnerability to RTK/MAPK pathway interference based on the different mitogenic drivers and according to the level of dependence on the pathway could be uncovered. Furthermore, an association between RTK/MAPK pathway activity and susceptibility to HDAC inhibition was observed. This finding was further validated in patient-derived organoids from gastric adenocarcinoma, thus identifying a novel treatment approach for RTK/MAPK pathway altered gastric cancer patients.11Nsciescopu

Sensitization of Patient-Derived Colorectal Cancer Organoids to Photon and Proton Radiation by Targeting DNA Damage Response Mechanisms

Pathological complete response (pCR) has been correlated with overall survival in several cancer entities including colorectal cancer. Novel total neoadjuvant treatment (TNT) in rectal cancer has achieved pathological complete response in one-third of the patients. To define better treatment options for nonresponding patients, we used patient-derived organoids (PDOs) as avatars of the patient’s tumor to apply both photon- and proton-based irradiation as well as single and combined chemo(radio)therapeutic treatments. While response to photon and proton therapy was similar, PDOs revealed heterogeneous responses to irradiation and different chemotherapeutic drugs. Radiotherapeutic response of the PDOs was significantly correlated with their ability to repair irradiation-induced DNA damage. The classical combination of 5-FU and irradiation could not sensitize radioresistant tumor cells. Ataxia-telangiectasia mutated (ATM) kinase was activated upon radiation, and by inhibition of this central sensor of DNA damage, radioresistant PDOs were resensitized. The study underlined the capability of PDOs to define nonresponders to irradiation and could delineate therapeutic approaches for radioresistant patients

Detecting drug resistance in pancreatic cancer organoids guides optimized chemotherapy treatment

Drug combination therapies for cancer treatment show high efficacy but often induce severe side effects, resulting in dose or cycle number reduction. We investigated the impact of neoadjuvant chemotherapy (neoCTx) adaptions on treatment outcome in 59 patients with pancreatic ductal adenocarcinoma (PDAC). Resections with tumor-free margins were significantly more frequent when full-dose neoCTx was applied. We determined if patient-derived organoids (PDOs) can be used to personalize poly-chemotherapy regimens by pharmacotyping of treatment-naïve and post-neoCTx PDAC PDOs. Five out of ten CTx-naïve PDO lines exhibited a differential response to either the FOLFIRINOX or the Gem/Pac regimen. NeoCTx PDOs showed a poor response to the neoadjuvant regimen that had been administered to the respective patient in 30% of cases. No significant difference in PDO response was noted when comparing modified treatments in which the least effective single drug was removed from the complete regimen.Drug testing of CTx-naïve PDAC PDOs and neoCTx PDOs may be useful to guide neoadjuvant and adjuvant regimen selection, respectively. Personalizing poly-chemotherapy regimens by omitting substances with low efficacy could potentially result in less severe side effects, thereby increasing the fraction of patients receiving a full course of neoadjuvant treatment

Additional file 1 of Stratifying esophago-gastric cancer treatment using a patient-derived organoid-based threshold

Additional file 1

A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013-2022), the first ten-year stage of the lifespan CCNP (2013-2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0-17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the "Chinese Data-sharing Warehouse for In-vivo Imaging Brain" in the Chinese Color Nest Project (CCNP) - Lifespan Brain-Mind Development Data Community (https://ccnp.scidb.cn) at the Science Data Bank