Prognostic genome and transcriptome signatures in colorectal cancers.

Colorectal cancer is caused by a sequence of somatic genomic alterations affecting driver genes in core cancer pathways1. Here, to understand the functional and prognostic impact of cancer-causing somatic mutations, we analysed the whole genomes and transcriptomes of 1,063 primary colorectal cancers in a population-based cohort with long-term follow-up. From the 96 mutated driver genes, 9 were not previously implicated in colorectal cancer and 24 had not been linked to any cancer. Two distinct patterns of pathway co-mutations were observed, timing analyses identified nine early and three late driver gene mutations, and several signatures of colorectal-cancer-specific mutational processes were identified. Mutations in WNT, EGFR and TGFß pathway genes, the mitochondrial CYB gene and 3 regulatory elements along with 21 copy-number variations and the COSMIC SBS44 signature correlated with survival. Gene expression classification yielded five prognostic subtypes with distinct molecular features, in part explained by underlying genomic alterations. Microsatellite-instable tumours divided into two classes with different levels of hypoxia and infiltration of immune and stromal cells. To our knowledge, this study constitutes the largest integrated genome and transcriptome analysis of colorectal cancer, and interlinks mutations, gene expression and patient outcomes. The identification of prognostic mutations and expression subtypes can guide future efforts to individualize colorectal cancer therapy.

Discovery of a Therapeutic Agent for Glioblastoma Using a Systems Biology-Based Drug Repositioning Approach.

Glioblastoma (GBM), a highly malignant tumour of the central nervous system, presents with a dire prognosis and low survival rates. The heterogeneous and recurrent nature of GBM renders current treatments relatively ineffective. In our study, we utilized an integrative systems biology approach to uncover the molecular mechanisms driving GBM progression and identify viable therapeutic drug targets for developing more effective GBM treatment strategies. Our integrative analysis revealed an elevated expression of CHST2 in GBM tumours, designating it as an unfavourable prognostic gene in GBM, as supported by data from two independent GBM cohorts. Further, we pinpointed WZ-4002 as a potential drug candidate to modulate CHST2 through computational drug repositioning. WZ-4002 directly targeted EGFR (ERBB1) and ERBB2, affecting their dimerization and influencing the activity of adjacent genes, including CHST2. We validated our findings by treating U-138 MG cells with WZ-4002, observing a decrease in CHST2 protein levels and a reduction in cell viability. In summary, our research suggests that the WZ-4002 drug candidate may effectively modulate CHST2 and adjacent genes, offering a promising avenue for developing efficient treatment strategies for GBM patients.

Global compositional and functional states of the human gut microbiome in health and disease.

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses. Using interpreted machine learning classification models and statistical methods, we identified Fusobacterium nucleatum and Anaerostipes hadrus with the highest frequencies, enriched and depleted, respectively, across different disease cohorts. Distinct functional distributions were observed in the gut microbiomes of both westernized and nonwesternized populations. These compositional and functional analyses are presented in the open-access Human Gut Microbiome Atlas, allowing for the exploration of the richness, disease, and regional signatures of the gut microbiota across different cohorts.

Multiplexed mapping of the interactome of GPCRs with receptor activity-modifying proteins.

Receptor activity-modifying proteins (RAMPs) form complexes with G protein-coupled receptors (GPCRs) and may regulate their cellular trafficking and pharmacology. RAMP interactions have been identified for about 50 GPCRs, but only a few GPCR-RAMP complexes have been studied in detail. To elucidate a comprehensive GPCR-RAMP interactome, we created a library of 215 dual epitope-tagged (DuET) GPCRs representing all GPCR subfamilies and coexpressed each GPCR with each of the three RAMPs. Screening the GPCR-RAMP pairs with customized multiplexed suspension bead array (SBA) immunoassays, we identified 122 GPCRs that showed strong evidence for interaction with at least one RAMP. We screened for interactions in three cell lines and found 23 endogenously expressed GPCRs that formed complexes with RAMPs. Mapping the GPCR-RAMP interactome expands the current system-wide functional characterization of RAMP-interacting GPCRs to inform the design of selective therapeutics targeting GPCR-RAMP complexes.

Discovery of Cell-Permeable Allosteric Inhibitors of Liver Pyruvate Kinase: Design and Synthesis of Sulfone-Based Urolithins.

Metabolic dysfunction-associated fatty liver disease (MAFLD) presents a significant global health challenge, characterized by the accumulation of liver fat and impacting a considerable portion of the worldwide population. Despite its widespread occurrence, effective treatments for MAFLD are limited. The liver-specific isoform of pyruvate kinase (PKL) has been identified as a promising target for developing MAFLD therapies. Urolithin C, an allosteric inhibitor of PKL, has shown potential in preliminary studies. Expanding upon this groundwork, our study delved into delineating the structure-activity relationship of urolithin C via the synthesis of sulfone-based urolithin analogs. Our results highlight that incorporating a sulfone moiety leads to substantial PKL inhibition, with additional catechol moieties further enhancing this effect. Despite modest improvements in liver cell lines, there was a significant increase in inhibition observed in HepG2 cell lysates. Specifically, compounds 15d, 9d, 15e, 18a, 12d, and 15a displayed promising IC50 values ranging from 4.3 µM to 18.7 µM. Notably, compound 15e not only demonstrated a decrease in PKL activity and triacylglycerol (TAG) content but also showed efficient cellular uptake. These findings position compound 15e as a promising candidate for pharmacological MAFLD treatment, warranting further research and studies.

Characterization of reduced astrocyte creatine kinase levels in Alzheimer's disease.

The creatine-phosphocreatine cycle serves as a crucial temporary energy buffering system in the brain, regulated by brain creatine kinase (CKB), in maintaining Adenosine triphosphate (ATP) levels. Alzheimer's disease (AD) has been linked to increased CKB oxidation and loss of its regulatory function, although specific pathological processes and affected cell types remain unclear. In our study, cerebral cortex samples from individuals with AD, dementia with Lewy bodies (DLB), and age-matched controls were analyzed using antibody-based methods to quantify CKB levels and assess alterations associated with disease processes. Two independently validated antibodies exclusively labeled astrocytes in the human cerebral cortex. Combining immunofluorescence (IF) and mass spectrometry (MS), we explored CKB availability in AD and DLB cases. IF and Western blot analysis demonstrated a loss of CKB immunoreactivity correlated with increased plaque load, severity of tau pathology, and Lewy body pathology. However, transcriptomics data and targeted MS demonstrated unaltered total CKB levels, suggesting posttranslational modifications (PTMs) affecting antibody binding. This aligns with altered efficiency at proteolytic cleavage sites indicated in the targeted MS experiment. These findings highlight that the proper function of astrocytes, understudied in the brain compared with neurons, is highly affected by PTMs. Reduction in ATP levels within astrocytes can disrupt ATP-dependent processes, such as the glutamate-glutamine cycle. As CKB and the creatine-phosphocreatine cycle are important in securing constant ATP availability, PTMs in CKB, and astrocyte dysfunction may disturb homeostasis, driving excitotoxicity in the AD brain. CKB and its activity could be promising biomarkers for monitoring early-stage energy deficits in AD.

Design and synthesis of novel JNK inhibitors targeting liver pyruvate kinase for the treatment of non-alcoholic fatty liver disease and hepatocellular carcinoma.

Non-alcoholic fatty liver disease (NAFLD) comprises a broad range of liver disease including hepatocellular carcinoma (HCC) with is no FDA-approved drug. Liver pyruvate kinase (PKL) is a major regulator of metabolic flux and ATP generation in liver presenting a potential target for the treatment of NAFLD. Based on our recent finding of JNK-5A's effectiveness in inhibiting PKLR expression through a drug repositioning pipeline, this study aims to improve its efficacy further. We synthesized a series of JNK-5A analogues with targeted modifications, guided by molecular docking studies. These compounds were evaluated for their activities on PKL expression, cell viability, triacylglyceride (TAG) levels, and the expressions of steatosis-related proteins in the human HepG2 cell line. Subsequently, the efficacy of these compounds was assessed in reducing TAG level and toxicity. Compounds 40 (SET-151) and 41 (SET-152) proved to be the most efficient in reducing TAG levels (11.51 ± 0.90 % and 10.77 ± 0.67 %) and demonstrated lower toxicity (61.60 ± 5.00 % and 43.87 ± 1.42 %) in HepG2 cells. Additionally, all synthesized compounds were evaluated for their anti-cancer properties revealing that compound 74 (SET-171) exhibited the highest toxicity in cell viability with IC50 values of 8.82 µM and 2.97 µM in HepG2 and Huh7 cell lines, respectively. To summarize, compounds 40 (SET-151) and 41 (SET-152) show potential for treating NAFLD, while compound 74 (SET-171) holds potential for HCC therapy.

Fast and robust recombinant protein production utilizing episomal stable pools in WAVE bioreactors.

Protein reagents are essential resources for several stages of drug discovery projects from structural biology and assay development through lead optimization. Depending on the aim of the project different amounts of pure protein are required. Small-scale expressions are initially used to determine the reachable levels of production and quality before scaling up protein reagent supply. Commonly, amounts of several hundreds of milligrams to grams are needed for different experiments, including structural investigations and activity evaluations, which require rather large cultivation volumes. This implies that cultivation of large volumes of either transiently transfected cells or stable pools/stable cell lines is needed. Hence, a production process that is scalable, speeds up the development projects, and increases the robustness of protein reagent quality throughout scales. Here we present a protein production pipeline with high scalability. We show that our protocols for protein production in Chinese hamster ovary cells allow for a seamless and efficient scale-up with robust product quality and high performance. The flexible scale of the production process, as shown here, allows for shorter lead times in drug discovery projects where there is a reagent demand for a specific protein or a set of target proteins.

Arachidonic acid and docosahexaenoic acid levels correlate with the inflammation proteome in extremely preterm infants.

BACKGROUND & AIM: Clinical trials supplementing the long-chain polyunsaturated fatty acids (LCPUFAs) docosahexaenoic acid (DHA) and arachidonic acid (AA) to preterm infants have shown positive effects on inflammation-related morbidities, but the molecular mechanisms underlying these effects are not fully elucidated. This study aimed to determine associations between DHA, AA, and inflammation-related proteins during the neonatal period in extremely preterm infants. METHODS: A retrospective exploratory study of infants (n = 183) born below 28 weeks gestation from the Mega Donna Mega trial, a randomized multicenter trial designed to study the effect of DHA and AA on retinopathy of prematurity. Serial serum samples were collected after birth until postnatal day 100 (median 7 samples per infant) and analyzed for phospholipid fatty acids and proteins using targeted proteomics covering 538 proteins. Associations over time between LCPUFAs and proteins were explored using mixed effect modeling with splines, including an interaction term for time, and adjusted for gestational age, sex, and center. RESULTS: On postnatal day one, 55 proteins correlated with DHA levels and 10 proteins with AA levels. Five proteins were related to both fatty acids, all with a positive correlation. Over the first 100 days after birth, we identified 57 proteins to be associated with DHA and/or AA. Of these proteins, 41 (72%) related to inflammation. Thirty-eight proteins were associated with both fatty acids and the overall direction of association did not differ between DHA and AA, indicating that both LCPUFAs similarly contribute to up- and down-regulation of the preterm neonate inflammatory proteome. Primary examples of this were the inflammation-modulating cytokines IL-6 and CCL7, both being negatively related to levels of DHA and AA in the postnatal period. CONCLUSIONS: This study supports postnatal non-antagonistic and potentially synergistic effects of DHA and AA on the inflammation proteome in preterm infants, indicating that supplementation with both fatty acids may contribute to limiting the disease burden in this vulnerable population. CLINICAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT03201588).

Combined Metabolic Activators with Different NAD+ Precursors Improve Metabolic Functions in the Animal Models of Neurodegenerative Diseases.

BACKGROUND: Mitochondrial dysfunction and metabolic abnormalities are acknowledged as significant factors in the onset of neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). Our research has demonstrated that the use of combined metabolic activators (CMA) may alleviate metabolic dysfunctions and stimulate mitochondrial metabolism. Therefore, the use of CMA could potentially be an effective therapeutic strategy to slow down or halt the progression of PD and AD. CMAs include substances such as the glutathione precursors (L-serine and N-acetyl cysteine), the NAD+ precursor (nicotinamide riboside), and L-carnitine tartrate. METHODS: Here, we tested the effect of two different formulations, including CMA1 (nicotinamide riboside, L-serine, N-acetyl cysteine, L-carnitine tartrate), and CMA2 (nicotinamide, L-serine, N-acetyl cysteine, L-carnitine tartrate), as well as their individual components, on the animal models of AD and PD. We assessed the brain and liver tissues for pathological changes and immunohistochemical markers. Additionally, in the case of PD, we performed behavioral tests and measured responses to apomorphine-induced rotations. FINDINGS: Histological analysis showed that the administration of both CMA1 and CMA2 formulations led to improvements in hyperemia, degeneration, and necrosis in neurons for both AD and PD models. Moreover, the administration of CMA2 showed a superior effect compared to CMA1. This was further corroborated by immunohistochemical data, which indicated a reduction in immunoreactivity in the neurons. Additionally, notable metabolic enhancements in liver tissues were observed using both formulations. In PD rat models, the administration of both formulations positively influenced the behavioral functions of the animals. INTERPRETATION: Our findings suggest that the administration of both CMA1 and CMA2 markedly enhanced metabolic and behavioral outcomes, aligning with neuro-histological observations. These findings underscore the promise of CMA2 administration as an effective therapeutic strategy for enhancing metabolic parameters and cognitive function in AD and PD patients.

Transcriptome Analysis Reveals Distinct Patterns Between the Invasive and Noninvasive Pituitary Neuroendocrine Tumors.

Although most pituitary neuroendocrine tumors (PitNETs)/pituitary adenomas remain intrasellar, a significant proportion of tumors show parasellar invasive growth and 6% to 8% infiltrate the bone structures, thus affecting the prognosis. There is an unmet need to identify novel markers that can predict the parasellar growth of PitNETs. Furthermore, mechanisms that regulate bone invasiveness of PitNETs and factors related to tumor vascularization are largely unknown. We used genome-wide mRNA analysis in a cohort of 77 patients with PitNETs of different types to explore the differences in gene expression patterns between invasive and noninvasive tumors with respect to the parasellar growth and regarding the rare phenomenon of bone invasiveness. Additionally, we studied the genes correlated to the contrast enhancement quotient, a novel radiological parameter of tumor vascularization. Most of the genes differentially expressed related to the parasellar growth were genes involved in tumor invasiveness. Differentially expressed genes associated with bone invasiveness are involved in NF-κB pathway and antitumoral immune response. Lack of clear clustering regarding the parasellar and bone invasiveness may be explained by the influence of the cell lineage-related genes in this heterogeneous cohort of PitNETs. Our transcriptomics analysis revealed differences in the molecular fingerprints between invasive, including bone invasive, and noninvasive PitNETs, although without clear clustering. The contrast enhancement quotient emerged as a radiological parameter of tumor vascularization, correlating with several angiogenesis-related genes. Several of the top genes related to the PitNET invasiveness and vascularization have potential prognostic and therapeutic application requiring further research.

Sulfone-based human liver pyruvate kinase inhibitors - Design, synthesis and in vitro bioactivity.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent pathological condition characterised by the accumulation of fat in the liver. Almost one-third of the global population is affected by NAFLD, making it a significant health concern. However, despite its prevalence, there is currently no approved drug specifically designed for the treatment of NAFLD. To address this critical gap, researchers have been investigating potential targets for NAFLD drug development. One promising candidate is the liver isoform of pyruvate kinase (PKL). In recent studies, Urolithin C, an allosteric inhibitor of PKL, has emerged as a potential lead compound for therapeutic intervention. Building upon this knowledge, our team has conducted a comprehensive structure-activity relationship of Urolithin C. In this work, we have employed a scaffold-hopping approach, modifying the urolithin structure by replacing the urolithin carbonyl with a sulfone moiety. Our structure-activity relationship analysis has identified the sulfone group as particularly favourable for potent PKL inhibition. Additionally, we have found that the presence of catechol moieties on the two aromatic rings further improves the inhibitory activity. The most promising inhibitor from this new series displayed nanomolar inhibition, boasting an IC50 value of 0.07 µM. This level of potency rivals that of urolithin D and significantly surpasses the effectiveness of urolithin C by an order of magnitude. To better understand the molecular interactions underlying this inhibition, we obtained the crystal structure of one of the inhibitors complexed with PKL. This structural insight served as a valuable reference point, aiding us in the design of inhibitors.

Plasma proteomics for prediction of subclinical coronary artery calcifications in primary prevention.

BACKGROUND AND AIMS: Recent developments in high-throughput proteomic technologies enable the discovery of novel biomarkers of coronary atherosclerosis. The aims of this study were to test if plasma protein subsets could detect coronary artery calcifications (CAC) in asymptomatic individuals and if they add predictive value beyond traditional risk factors. METHODS: Using proximity extension assays, 1,342 plasma proteins were measured in 1,827 individuals from the Impaired Glucose Tolerance and Microbiota (IGTM) study and 883 individuals from the Swedish Cardiopulmonary BioImage Study (SCAPIS) aged 50-64 years without history of ischaemic heart disease and with CAC assessed by computed tomography. After data-driven feature selection, extreme gradient boosting machine learning models were trained on the IGTM cohort to predict the presence of CAC using combinations of proteins and traditional risk factors. The trained models were validated in SCAPIS. RESULTS: The best plasma protein subset (44 proteins) predicted CAC with an area under the curve (AUC) of 0.691 in the validation cohort. However, this was not better than prediction by traditional risk factors alone (AUC = 0.710, P = .17). Adding proteins to traditional risk factors did not improve the predictions (AUC = 0.705, P = .6). Most of these 44 proteins were highly correlated with traditional risk factors. CONCLUSIONS: A plasma protein subset that could predict the presence of subclinical CAC was identified but it did not outperform nor improve a model based on traditional risk factors. Thus, support for this targeted proteomics platform to predict subclinical CAC beyond traditional risk factors was not found.

Substance P, NPY, CCK and their receptors in five brain regions in major depressive disorder with transcriptomic analysis of locus coeruleus neurons.

Major depressive disorder (MDD) is a serious disease and a burden to patients, families and society. Rodent experiments and human studies suggest that several neuropeptide systems are involved in mood regulation. The aim of this study is two-fold: (i) to monitor, with qPCR, transcript levels of the substance P/tachykinin (TAC), NPY and CCK systems in bulk samples from control and suicide subjects, targeting five postmortem brain regions including locus coeruleus (LC); and (ii) to analyse expression of neuropeptide family transcripts in LC neurons of 'normal' postmortem brains by using laser capture microdissection with Smart-Seq2 RNA sequencing. qPCR revealed distinct regional expression patterns in male and female controls with higher levels for the TAC system in the dorsal raphe nucleus and LC, versus higher transcripts levels of the NPY and CCK systems in prefrontal cortex. In suicide patients, TAC, TAC receptors and a few NPY family transcript levels were increased mainly in prefrontal cortex and LC. The second study on 'normal' noradrenergic LC neurons revealed expression of transcripts for GAL, NPY, TAC1, CCK, and TACR1 and many other peptides (e.g. Cerebellin4 and CARTPT) and receptors (e.g. Adcyap1R1 and GPR173). These data and our previous results on suicide brains indicates that the tachykinin and galanin systems may be valid targets for developing antidepressant medicines. Moreover, the perturbation of neuropeptide systems in MDD patients, and the detection of further neuropeptide and receptor transcripts in LC, shed new light on signalling in noradrenergic LC neurons and on mechanisms possibly associated with mood disorders.

Open MoA: revealing the mechanism of action (MoA) based on network topology and hierarchy.

MOTIVATION: Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA). RESULTS: We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/XinmengLiao/Open_MoA.

Absolute Quantification of Pan-Cancer Plasma Proteomes Reveals Unique Signature in Multiple Myeloma.

Mass spectrometry based on data-independent acquisition (DIA) has developed into a powerful quantitative tool with a variety of implications, including precision medicine. Combined with stable isotope recombinant protein standards, this strategy provides confident protein identification and precise quantification on an absolute scale. Here, we describe a comprehensive targeted proteomics approach to profile a pan-cancer cohort consisting of 1800 blood plasma samples representing 15 different cancer types. We successfully performed an absolute quantification of 253 proteins in multiplex. The assay had low intra-assay variability with a coefficient of variation below 20% (CV = 17.2%) for a total of 1013 peptides quantified across almost two thousand injections. This study identified a potential biomarker panel of seven protein targets for the diagnosis of multiple myeloma patients using differential expression analysis and machine learning. The combination of markers, including the complement C1 complex, JCHAIN, and CD5L, resulted in a prediction model with an AUC of 0.96 for the identification of multiple myeloma patients across various cancer patients. All these proteins are known to interact with immunoglobulins.

Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation.

Cell lines are valuable resources as model for human biology and translational medicine. It is thus important to explore the concordance between the expression in various cell lines vis-à-vis human native and disease tissues. In this study, we investigate the expression of all human protein-coding genes in more than 1,000 human cell lines representing 27 cancer types by a genome-wide transcriptomics analysis. The cell line gene expression is compared with the corresponding profiles in various tissues, organs, single-cell types and cancers. Here, we present the expression for each cell line and give guidance for the most appropriate cell line for a given experimental study. In addition, we explore the cancer-related pathway and cytokine activity of the cell lines to aid human biology studies and drug development projects. All data are presented in an open access cell line section of the Human Protein Atlas to facilitate the exploration of all human protein-coding genes across these cell lines.