Background As technologies for genome-wide gene-expression analysis continue to develop, the databases storing the resulting data have grown accordingly. The Gene Expression Omnibus (GEO) has grown to over 250,000 data series across more than 25,000 omics platforms. Likewise, ArrayExpress is comprised of over 70,000 transcriptome and methylome datasets. Conducting meta-analyses of data from these databases can be challenging, typically requiring extensive manual grouping of samples to identify experimental groups for comparison. Results Here we present sampleclusteR, a lightweight R package which automates the clustering of gene-expression study samples based on their metadata. To demonstrate the utility of the approach to large scale analysis of GEO data series, 275 GEO data series were analysed using the package. sampleclusteR was able to correctly cluster 4694 of the 5081 samples across the 275 data sets in an unsupervised manner. In addition, 250 datasets from ArrayExpress were analysed by the package with 8547 of the 9154 samples being automatically clustered into correct groups. We show how sampleclusteR can be used to automate analysis of gene-expression datasets by conducting a meta-analysis of multiple GEO data series related to the Wnt signaling pathway. sampleclusteR correctly assigned all samples to the correct experimental groups and identified sets of differentially expressed genes for downstream analysis. Conclusions sampleclusteR enables large-scale analysis of data from GEO or ArrayExpress by automating the clustering of both GEO and ArrayExpress metadata tables using text mining of their associated metadata. ### Competing Interest Statement The authors have declared no competing interest.

L1TD1 is a pluripotency factor required for embryonic stem cell self-renewal; its expression has also been detected in solid tumors, including embryonal tumors of the central nervous system (CNS). Previously, we showed that L1TD1 expression correlates with metastasis formation and shorter overall survival of medulloblastoma patients. Here, we used affinity purification coupled to mass spectrometry to map the L1TD1 interactome, and global proteomics to assess proteins differentially regulated by L1TD1 expression in patient-derived embryonal CNS tumor cell lines. We identified novel L1TD1 interactors and differentially expressed proteins related to cell proliferation, death and motility. Finally, we demonstrated that L1TD1-overexpressing tumor cells have distinct cell morphology with enhanced filopodial formation, higher cell motility, greater proliferation capability, and reduced sensitivity to cisplatin treatment.

Brain tumours disproportionately affect children and are the largest cause of paediatric cancer-related death. Novel therapies that engage the immune system, such as oncolytic viruses (OVs), hold great promise and are desperately needed. Zika virus (ZIKV) infects and destroys aggressive cells from multiple paediatric central nervous system (CNS) tumours. Despite this, the molecular mechanisms underpinning this response are largely unknown. We comprehensively investigate the transcriptomic response of paediatric medulloblastoma and atypical teratoid rhabdoid tumour (ATRT) cells to ZIKV infection. We observe conserved TNF signalling and cytokine signalling-related signatures and show that the TNF-alpha signalling pathway is implicated in oncolysis by reducing the viability of ZIKV-infected brain tumour cells. Our findings highlight TNF-alpha as a potential prognostic marker for oncolytic ZIKV (oZIKV) therapy. Complementing our analysis with a 49-plex ELISA, we demonstrate that ZIKV infection induces a clinically relevant and diverse pro-inflammatory brain tumour cell secretome, including TNF-alpha. We assess publicly available scRNA-Seq data to model how ZIKV-induced secretome paracrine and endocrine signalling may orchestrate the anti-tumoural immune response during oZIKV infection of brain tumours. Our findings significantly contribute to understanding the molecular mechanisms governing oZIKV infection and will help pave the way towards oZIKV therapy.

Despite decades of research, survival from brain cancer has scarcely improved and is drastically lower than that of other cancers. Novel therapies, such as immunotherapy, hold great promise for treating brain tumours and are desperately needed. Zika virus (ZIKV) infects and kills aggressive cancer cells with stem-like properties (CSCs) from both paediatric and adult brain tumours. Whilst T cell recruitment into ZIKV-infected brain tumours is becoming well documented, the specific mechanisms through which they are activated are poorly understood. We address this by employing a combined global proteome and immunopeptidome mass spectrometry approach to describe, for the first time, human leukocyte antigen (HLA) presentation of ZIKV peptides on the surface of infected brain tumour cells. We first show that antigen processing and presentation by HLA class I (HLA-I) is the top enriched immune response pathway in the global proteome of aggressive paediatric USP7-ATRT brain tumour cells following ZIKV infection. We identify USP7-ATRT cells as a desirable immunopeptidome model as they express the globally common HLA-A allotype (A*02:01). We predict the majority of our 19 identified ZIKV peptides to strongly bind and be presented by HLA-A*02:01. We observe a trend between immunopeptide presentation and cellular ZIKV protein abundance, with nearly half of the peptides arising from the most abundant viral protein; non-structural protein 3 (NS3). We show the ZIKV NS3 helicase domain to be a particularly rich source of peptides. Finally, we verify that the 19 ZIKV peptides identified here are not predicted to mimic peptides of the human proteome. The ZIKV peptides we identify here are novel targets for immunotherapy, and our findings provide potential insight into the efficacious cytotoxic T cell response that oncolytic ZIKV virotherapy can induce against brain tumours.

Ubiquitin-specific protease 7 (USP7) is implicated in many cancers including colorectal cancer in which it regulates cellular pathways such as Wnt signaling and the P53-MDM2 pathway. With the discovery of small-molecule inhibitors, USP7 has also become a promising target for cancer therapy and therefore systematically identifying USP7 deubiquitinase interaction partners and substrates has become an important goal. In this study, we selected a colorectal cancer cell model that is highly dependent on USP7 and in which USP7 knockdown significantly inhibited colorectal cancer cell viability, colony formation, and cell-cell adhesion. We then used inducible knockdown of USP7 followed by LC-MS/MS to quantify USP7-dependent proteins. We identified the Ajuba LIM domain protein as an interacting partner of USP7 through co-IP, its substantially reduced protein levels in response to USP7 knockdown, and its sensitivity to the specific USP7 inhibitor FT671. The Ajuba protein has been shown to have oncogenic functions in colorectal and other tumors, including regulation of cell-cell adhesion. We show that both knockdown of USP7 or Ajuba results in a substantial reduction of cell-cell adhesion, with concomitant effects on other proteins associated with adherens junctions. Our findings underlie the role of USP7 in colorectal cancer through its protein interaction networks and show that the Ajuba protein is a component of USP7 protein networks present in colorectal cancer.

The factors that determine fibrosis progression or normal tissue repair are largely unknown. We previously demonstrated that autophagy inhibition-mediated epithelial–mesenchymal transition (EMT) in human alveolar epithelial type II (ATII) cells augments local myofibroblast differentiation in pulmonary fibrosis by paracrine signaling. Here, we report that liver kinase B1 (LKB1) inactivation in ATII cells inhibits autophagy and induces EMT as a consequence. In IPF lungs, this is caused by the down-regulation of CAB39L, a key subunit within the LKB1 complex. 3D co-cultures of ATII cells and MRC5 lung fibroblasts coupled with RNA sequencing (RNA-seq) confirmed that paracrine signaling between LKB1-depleted ATII cells and fibroblasts augmented myofibroblast differentiation. Together, these data suggest that reduced autophagy caused by LKB1 inhibition can induce EMT in ATII cells and contribute to fibrosis via aberrant epithelial–fibroblast crosstalk.

Motivation Protein language models (PLMs), which borrowed ideas for modelling and inference from natural language processing, have demonstrated the ability to extract meaningful representations in an unsupervised way. This led to significant performance improvement in several downstream tasks. Clustering amino acids based on their physical-chemical properties to achieve reduced alphabets has been of interest in past research, but their application to PLMs or folding models is unexplored.Results Here, we investigate the efficacy of PLMs trained on reduced amino acid alphabets in capturing evolutionary information, and we explore how the loss of protein sequence information impacts learned representations and downstream task performance. Our empirical work shows that PLMs trained on the full alphabet and a large number of sequences capture fine details that are lost in alphabet reduction methods. We further show the ability of a structure prediction model(ESMFold) to fold CASP14 protein sequences translated using a reduced alphabet. For 10 proteins out of the 50 targets, reduced alphabets improve structural predictions with LDDT-C alpha differences of up to 19%.Availability and implementation Trained models and code are available at github.com/Ieremie/reduced-alph-PLM.

BACKGROUND:Despite the extensive study of MYCN-amplified neuroblastomas, there is a significant unmet clinical need in MYCN non-amplified cases. In particular, the extent of heterogeneity within the MYCN non-amplified population is unknown. METHODS:A total of 1566 samples from 16 datasets were identified in Gene Expression Omnibus (GEO) and ArrayExpress. Characterisation of the subtypes was analysed by ConsensusClusterPlus. Independent predictors for subgrouping were constructed from the single sample predictor based on the multiclassPairs package. Findings were verified using immunohistochemistry and CIBERSORTx analysis. RESULTS:We demonstrate that MYCN non-amplified neuroblastomas are heterogeneous and can be classified into 3 subgroups based on their transcriptional signatures. Within these groups, subgroup_2 has the worst prognosis and this group shows a 'MYCN' signature that is potentially induced by the overexpression of Aurora Kinase A (AURKA); whilst subgroup_3 is characterised by an 'inflamed' gene signature. The clinical implications of this subtype classification are significant, as each subtype demonstrates a unique prognosis and vulnerability to investigational therapies. A total of 420 genes were identified as independent subgroup predictors with average balanced accuracy of 0.93 and 0.84 for train and test datasets, respectively. CONCLUSION:We propose that transcriptional subtyping may enhance precision prognosis and therapy stratification for patients with MYCN non-amplified neuroblastomas.

BACKGROUND:Influenza is a common illness for its high rates of morbidity and transmission. The implementation of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic to manage its dissemination could affect the transmission of influenza. METHODS:A retrospective analysis, between 2018 and 2023, was conducted to examine the incidence of influenza virus types A and B among patients in sentinel cities located in North or South China as well as in Wuhan City. For validations, data on the total count of influenza patients from 2018 to 2023 were collected at the Central Hospital of Wuhan, which is not included in the sentinel hospital network. Time series methods were utilized to examine seasonal patterns and to forecast future influenza trends. RESULTS:Northern and southern cities in China had earlier outbreaks during the NPIs period by about 8 weeks compared to the 2018-2019. The implementation of NPIs significantly reduced the influenza-like illness (ILI) rate and infection durations. Influenza B Victoria and H3N2 were the first circulating strains detected after the relaxation of NPIs, followed by H1N1 across mainland China. The SARIMA model predicted synchronized H1N1 outbreak cycles in North and South China, with H3N2 expected to occur in the summer in southern cities and in the winter in northern cities over the next 3 years. The ILI burden is expected to rise in both North and South China over the next 3 years, with higher ILI% levels in southern cities throughout the year, especially in winter, and in northern cities mainly during winter. In Wuhan City and the Central Hospital of Wuhan, influenza levels are projected to peak in the winter of 2024, with 2 smaller peaks expected during the summer of 2023. CONCLUSIONS:In this study, we report the impact of NPIs on future influenza trends in mainland China. We recommend that local governments encourage vaccination during the transition period between summer and winter to mitigate economic losses and mortality associated with influenza.

Background Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) can access the nervous system and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma. Methods Here, we perform extensive data mining, integration and re-analysis of ZIKV infection datasets to highlight molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We collate infection data of multiple neuroblastoma cell lines by different ZIKV strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection. Results Through data mining of published literature, we observed most paediatric neuroblastoma cell lines to be highly susceptible to ZIKV infection and propose the PRVABC59 ZIKV strain to be the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV non-structural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon. Conclusions Our work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials.

Background Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) can access the nervous system and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma. Methods Here, we perform extensive data mining, integration and re-analysis of ZIKV infection datasets to highlight molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We collate infection data of multiple neuroblastoma cell lines by different ZIKV strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection. Results Through data mining of published literature, we observed most paediatric neuroblastoma cell lines to be highly susceptible to ZIKV infection and propose the PRVABC59 ZIKV strain to be the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV non-structural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon. Conclusions Our work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials.

Phosphatase and tensin homolog (PTEN) is a tumor suppressor gene and has a role in inhibiting the oncogenic AKT signaling pathway by dephosphorylating phosphatidylinositol 3,4,5-triphosphate (PIP3) into phosphatidylinositol 4,5-bisphosphate (PIP2). The function of PTEN is regulated by different mechanisms and inactive PTEN results in aggressive tumor phenotype and tumorigenesis. Identifying targeted therapies for inactive tumor suppressor genes such as PTEN has been challenging as it is difficult to restore the tumor suppressor functions. Therefore, focusing on the downstream signaling pathways to discover a targeted therapy for inactive tumor suppressor genes has highlighted the importance of synthetic lethality studies. This review focused on the potential synthetic lethality genes discovered in PTEN-inactive cancer types. These discovered genes could be potential targeted therapies for PTEN-inactive cancer types and may improve the treatment response rates for aggressive types of cancer.

Background Limonium Sinense (Girard) Kuntze (L. sinense) has been widely used for the treatment of anaemia, bleeding, cancer, and other disorders in Chinese folk medicine. The aim of this study is to predict the therapeutic effects of L. sinense and investigate the potential mechanisms using integrated network pharmacology methods and in vitro cellular experiments.Methods The active ingredients of L. sinense were collected from published literature, and the potential targets related to L. sinense were obtained from public databases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and DisGeNET enrichment analyses were performed to explore the underlying mechanisms. Molecular docking, cellular experiments, RNA-sequencing (RNA-seq) and Gene Expression Omnibus (GEO) datasets were employed to further evaluate the findings.Results A total of 15 active ingredients of L. sinense and their corresponding 389 targets were obtained. KEGG enrichment analysis revealed that the biological effects of L. sinense were primarily associated with "Pathways in cancer". DisGeNET enrichment analysis highlighted the potential role of L. sinense in the treatment of breast cancer. Apigenin within L. sinense showed promising potential against cancer. Cellular experiments demonstrated that the L. sinense ethanol extract (LSE) exhibited a significant growth inhibitory effect on multiple breast cancer cell lines in both 2D and 3D cultures. RNA-seq analysis revealed a potential impact of LSE on breast cancer. Additionally, analysis of GEO datasets verified the significant enrichment of breast cancer and several cancer-related pathways upon treatment with Apigenin in human breast cancer cells.Conclusion This study predicts the biological activities of L. sinense and demonstrates the inhibitory effect of LSE on breast cancer cells, highlighting the potential application of L. sinense in cancer treatment.

Supplementary proteomics data

Supplementary Figures 1-7. Supplementary Figure 1.Cell-cycle profiles of HEK293T cells following treatment with Wnt3a. Supplementary Figure 2. Protein lysate samples used in the immunoprecipitation or immunoblots analyses were treated with Nuclease. Supplementary Figure 3. Dnmt1 (native antibody) immuno-precipitates β-catenin in parent HCT116 cells. Supplementary Figure 4. DNMT1 protein is stabilized by treatment with Wnt3a in HCT116 but not in CTNNB1KO-HCT116 cells. Supplementary Figure 5. Degradation profiles for β-catenin and Dnmt1 in HCT116, DNMT1KO-HCT116 or CTNNB1KO-HCT116 cells following cycloheximide treatment. Supplementary Figure 6. Abundance of β-catenin and Dnmt1 in DNMT1KO-HCT116 (A) or CTNNB1KO-HCT116 (B) cells treated with MG-132 proteasome inhibitor. Supplementary Figure 7. RT-PCR analysis of H19 expression in HCT116 and CTNNB1KO-HCT116 cells shows increase H19 transcript levels in the KO cells.

Abstract BACKGROUND Malignant paediatric nervous system tumours, such as medulloblastoma, ATRT and high-risk neuroblastoma commonly harbour tumour cells with stem-like features which are highly tumorigenic and resistant to conventional therapies. These tumours can exhibit high lethality and may result in severe sequelae that significantly affect paediatric patients' quality of life. Oncolytic virotherapy exploits viruses that preferentially infect and destroy tumour cells. These viruses present a unique advantage in targeting highly heterogeneous cancers as they possess a secondary mechanism of action, through which they induce an anti-tumoral immune response. The Zika virus (ZIKV) is capable of infecting and destroying aggressive human paediatric brain tumour and neuroblastoma cells in vitro. ZIKV effectively reduces brain tumour size in mice (xenograft model) and canines (naturally occurring) and can induce an immune response against canine brain tumours. METHODS Employing global expression omics profiling of ZIKV infection and mapping of viral protein-host protein interactions, we aim to elucidate the mechanisms which underpin ZIKVs therapeutic properties, both at the molecular and cellular pathway levels. RESULTS Through extensive transcriptome profiling of ZIKV-infected paediatric brain tumour, neuroblastoma and NPCs, we have identified a variety of pathways which are involved in the ZIKV oncolytic response in the tumour cells and its neuro-dysregulation of NPCs. Despite both brain tumour and neuroblastoma cells undergoing ZIKV-induced oncolysis, we observed there to be a heterogeneous response within these different tumour cells at the molecular level to lead to oncolysis. Additionally, the infected tumour cells demonstrate elevated immune system profiles which alludes to the immune response that ZIKV may raise within the patient’s body against the paediatric tumour. Analysing our findings alongside the neuro-dysregulation we observe in our ZIKV-infected NPCs is allowing us to build a safety profile for employing a ZIKV-based therapy, whilst contributing to the growing knowledge of Congenital ZIKV Syndrome.

Extracellular matrix (ECM) stiffening with downstream activation of mechanosensitive pathways is strongly implicated in fibrosis. We previously reported that altered collagen nanoarchitecture is a key determinant of pathogenetic ECM structure-function in human fibrosis (Jones et al., 2018). Here, through human tissue, bioinformatic and ex vivo studies we provide evidence that hypoxia-inducible factor (HIF) pathway activation is a critical pathway for this process regardless of the oxygen status (pseudohypoxia). Whilst TGFβ increased the rate of fibrillar collagen synthesis, HIF pathway activation was required to dysregulate post-translational modification of fibrillar collagen, promoting pyridinoline cross-linking, altering collagen nanostructure, and increasing tissue stiffness. In vitro, knockdown of Factor Inhibiting HIF (FIH), which modulates HIF activity, or oxidative stress caused pseudohypoxic HIF activation in the normal fibroblasts. By contrast, endogenous FIH activity was reduced in fibroblasts from patients with lung fibrosis in association with significantly increased normoxic HIF pathway activation. In human lung fibrosis tissue, HIF-mediated signalling was increased at sites of active fibrogenesis whilst subpopulations of human lung fibrosis mesenchymal cells had increases in both HIF and oxidative stress scores. Our data demonstrate that oxidative stress can drive pseudohypoxic HIF pathway activation which is a critical regulator of pathogenetic collagen structure-function in fibrosis.

We previously reported that oxidative stress drives pseudohypoxic hypoxia-inducible factor (HIF) pathway activation to promote pathogenetic collagen structure-function in human lung fibrosis (Brereton et al., 2022). Here, through bioinformatic studies we investigate HIF pathway activation status in patients with idiopathic pulmonary fibrosis (IPF) and whether this has prognostic significance. Applying a well-established HIF gene expression signature, we classified publicly available datasets into HIF score-high and score-low groups across multiple tissue compartments. The HIF scores in lung tissue, bronchoalveolar lavage (BAL) and peripheral blood mononuclear cells (PBMC) were increased in IPF patients and significantly correlated with an oxidative stress signature consistent with pseudohypoxic HIF pathway activation. A high HIF score in BAL and in PBMC was a strong independent predictor of mortality in multivariate analysis. Thus, a validated HIF gene signature predicts survival across tissue compartments in IPF and merits prospective study as a non-invasive biomarker of lung fibrosis progression.