Gene expression-based biomarkers designating glioblastomas resistant to multiple treatment strategies

A Proteomic Investigation to Discover Candidate Proteins Involved in Novel Mechanisms of 5-Fluorouracil Resistance in Colorectal Cancer

One of the main obstacles to therapeutic success in colorectal cancer (CRC) is the development of acquired resistance to treatment with drugs such as 5-fluorouracil (5-FU). Whilst some resistance mechanisms are well known, it is clear from the stasis in therapy success rate that much is still unknown. Here, a proteomics approach is taken towards identification of candidate proteins using 5-FU-resistant sublines of human CRC cell lines generated in house. Using a multiplexed stable isotope labelling with amino acids in cell culture (SILAC) strategy, 5-FU-resistant and equivalently passaged sensitive cell lines were compared to parent cell lines by growing in Heavy medium with 2D liquid chromatography and Orbitrap Fusion™ Tribrid™ Mass Spectrometry analysis. Among 3003 commonly quantified proteins, six (CD44, APP, NAGLU, CORO7, AGR2, PLSCR1) were found up-regulated, and six (VPS45, RBMS2, RIOK1, RAP1GDS1, POLR3D, CD55) down-regulated. A total of 11 of the 12 proteins have a known association with drug resistance mechanisms or role in CRC oncogenesis. Validation through immunodetection techniques confirmed high expression of CD44 and CD63, two known drug resistance mediators with elevated proteomics expression results. The information revealed by the sensitivity of this method warrants it as an important tool for elaborating the complexity of acquired drug resistance in CRC.

Global analysis of iron metabolism-related genes identifies potential mechanisms of gliomagenesis and reveals novel targets

AIMS

This study aimed to investigate key regulators of aberrant iron metabolism in gliomas, and evaluate their effect on biological functions and clinical translational relevance.

METHODS

We used transcriptomic data from multiple cross-platform glioma cohorts to identify key iron metabolism-related genes (IMRGs) based on a series of bioinformatic and machine learning methods. The associations between IMRGs and prognosis, mesenchymal phenotype, and genomic alterations were analyzed in silico. The performance of the IMRGs-based signature in predicting temozolomide (TMZ) treatment sensitivity was evaluated. In vitro and in vivo experiments were used to explore the biological functions of these key IMRGs.

RESULTS

HMOX1, LTF, and STEAP3 were identified as the most essential IMRGs in gliomas. The expression levels of these genes were strongly related to clinicopathological and molecular features. The robust IMRG-based gene signature could be used for prognosis prediction. These genes facilitate mesenchymal transformation, driver gene mutations, and oncogenic alterations in gliomas. The gene signature was also associated with TMZ resistance. HMOX1, LTF, and STEAP3 knockdown in glioma cells significantly reduced cell proliferation, colony formation, migration, and malignant invasion.

CONCLUSION

The study presented a comprehensive view of key regulators underpinning iron metabolism in gliomas and provided new insights into novel therapeutic approaches.

Interferon-γ inducible protein 30 promotes the epithelial-mesenchymal transition-like phenotype and chemoresistance by activating EGFR/AKT/GSK3β/β-catenin pathway in glioma

AIMS

Previous studies have indicated that IFI30 plays a protective role in human cancers. However, its potential roles in regulating glioma development are not fully understood.

METHODS

Public datasets, immunohistochemistry, and western blotting (WB) were used to evaluate the expression of IFI30 in glioma. The potential functions and mechanisms of IFI30 were examined by public dataset analysis; quantitative real-time PCR; WB; limiting dilution analysis; xenograft tumor assays; CCK-8, colony formation, wound healing, and transwell assays; and immunofluorescence microscopy and flow cytometry.

RESULTS

IFI30 was significantly upregulated in glioma tissues and cell lines compared with corresponding controls, and the expression level of IFI30 was positively associated with tumor grade. Functionally, both in vivo and in vitro evidence showed that IFI30 regulated the migration and invasion of glioma cells. Mechanistically, we found that IFI30 dramatically promoted the epithelial-mesenchymal transition (EMT)-like process by activating the EGFR/AKT/GSK3β/β-catenin pathway. In addition, IFI30 regulated the chemoresistance of glioma cells to temozolomide directly via the expression of the transcription factor Slug, a key regulator of the EMT-like process.

CONCLUSION

The present study suggests that IFI30 is a regulator of the EMT-like phenotype and acts not only as a prognostic marker but also as a potential therapeutic target for temozolomide-resistant glioma.

Identification and characterization of putative biomarkers and therapeutic axis in Glioblastoma multiforme microenvironment

Non-cellular secretory components, including chemokines, cytokines, and growth factors in the tumor microenvironment, are often dysregulated, impacting tumorigenesis in Glioblastoma multiforme (GBM) microenvironment, where the prognostic significance of the current treatment remains unsatisfactory. Recent studies have demonstrated the potential of post-translational modifications (PTM) and their respective enzymes, such as acetylation and ubiquitination in GBM etiology through modulating signaling events. However, the relationship between non-cellular secretory components and post-translational modifications will create a research void in GBM therapeutics. Therefore, we aim to bridge the gap between non-cellular secretory components and PTM modifications through machine learning and computational biology approaches. Herein, we highlighted the importance of BMP1, CTSB, LOX, LOXL1, PLOD1, MMP9, SERPINE1, and SERPING1 in GBM etiology. Further, we demonstrated the positive relationship between the E2 conjugating enzymes (Ube2E1, Ube2H, Ube2J2, Ube2C, Ube2J2, and Ube2S), E3 ligases (VHL and GNB2L1) and substrate (HIF1A). Additionally, we reported the novel HAT1-induced acetylation sites of Ube2S (K211) and Ube2H (K8, K52). Structural and functional characterization of Ube2S (8) and Ube2H (1) have identified their association with protein kinases. Lastly, our results found a putative therapeutic axis HAT1-Ube2S(K211)-GNB2L1-HIF1A and potential predictive biomarkers (CTSB, HAT1, Ube2H, VHL, and GNB2L1) that play a critical role in GBM pathogenesis.

Cystathionine gamma-lyase (CTH) inhibition attenuates glioblastoma formation

PURPOSE

Glioblastoma (GBM) is the most common type of adult brain tumor with extremely poor survival. Cystathionine-gamma lyase (CTH) is one of the main Hydrogen Sulfide (H₂S) producing enzymes and its expression contributes to tumorigenesis and angiogenesis but its role in glioblastoma development remains poorly understood.

METHODS

and Principal Results: An established allogenic immunocompetent in vivo GBM model was used in C57BL/6J WT and CTH KO mice where the tumor volume and tumor microvessel density were blindly measured by stereological analysis. Tumor macrophage and stemness markers were measured by blinded immunohistochemistry. Mouse and human GBM cell lines were used for cell-based analyses. In human gliomas, the CTH expression was analyzed by bioinformatic analysis on different databases. In vivo, the genetic ablation of CTH in the host led to a significant reduction of the tumor volume and the protumorigenic and stemness transcription factor sex determining region Y-box 2 (SOX2). The tumor microvessel density (indicative of angiogenesis) and the expression levels of peritumoral macrophages showed no significant changes between the two genotypes. Bioinformatic analysis in human glioma tumors revealed that higher CTH expression is positively correlated to SOX2 expression and associated with worse overall survival in all grades of gliomas. Patients not responding to temozolomide have also higher CTH expression. In mouse or human GBM cells, pharmacological inhibition (PAG) or CTH knockdown (siRNA) attenuates GBM cell proliferation, migration and stem cell formation frequency.

MAJOR CONCLUSIONS

Inhibition of CTH could be a new promising target against glioblastoma formation.

Identification of MDM2 as a prognostic and immunotherapeutic biomarker in a comprehensive pan-cancer analysis: A promising target for breast cancer, bladder cancer and ovarian cancer immunotherapy

BACKGROUND

The murine double minute 2 (MDM2) gene is a crucial factor in the development and progression of various cancer types. Multiple rigorous scientific studies have consistently shown its involvement in tumorigenesis and cancer progression in a wide range of cancer types. However, a comprehensive analysis of the role of MDM2 in human cancer has yet to be conducted.

METHODS

We used various databases, including TIMER2.0, TCGA, GTEx and STRING, to analyze MDM2 expression and its correlation with clinical outcomes, interacting genes and immune cell infiltration. We also investigated the association of MDM2 with immune checkpoints and performed gene enrichment analysis using DAVID tools.

RESULTS

The pan-cancer MDM2 analysis found that MDM2 expression and mutation status were observably different in 25 types of cancer tissue compared with healthy tissues, and prognosis analysis showed that there was a significant correlation between MDM2 expression and patient prognosis. Furthermore, correlation analysis showed that MDM2 expression was correlated with tumor mutational burden, microsatellite instability and drug sensitivity in certain cancer types. We found that there was an association between MDM2 expression and immune cell infiltration across cancer types, and MDM2 inhibitors might enhance the effect of immunotherapy on breast cancer, bladder cancer and ovarian cancer.

CONCLUSIONS

The first systematic pan-cancer analysis of MDM2 was conducted, and it demonstrated that MDM2 was a reliable prognostic biomarker and was closely related to cancer immunity, providing a potential immunotherapeutic target for breast cancer, bladder cancer and ovarian cancer.

Identification of dual-purpose therapeutic targets implicated in aging and glioblastoma multiforme using PandaOmics - an AI-enabled biological target discovery platform

Glioblastoma Multiforme (GBM) is the most aggressive and most common primary malignant brain tumor. The age of GBM patients is considered as one of the disease's negative prognostic factors and the mean age of diagnosis is 62 years. A promising approach to preventing both GBM and aging is to identify new potential therapeutic targets that are associated with both conditions as concurrent drivers. In this work, we present a multi-angled approach of identifying targets, which takes into account not only the disease-related genes but also the ones important in aging. For this purpose, we developed three strategies of target identification using the results of correlation analysis augmented with survival data, differences in expression levels and previously published information of aging-related genes. Several studies have recently validated the robustness and applicability of AI-driven computational methods for target identification in both cancer and aging-related diseases. Therefore, we leveraged the AI predictive power of the PandaOmics TargetID engine in order to rank the resulting target hypotheses and prioritize the most promising therapeutic gene targets. We propose cyclic nucleotide gated channel subunit alpha 3 (CNGA3), glutamate dehydrogenase 1 (GLUD1) and sirtuin 1 (SIRT1) as potential novel dual-purpose therapeutic targets to treat aging and GBM.

Transcriptional Profiling of a Patient-Matched Cohort of Glioblastoma (IDH-Wildtype) for Therapeutic Target and Repurposing Drug Identification

Glioblastoma (GBM) is the most prevalent and aggressive adult brain tumor. Despite multi-modal therapies, GBM recurs, and patients have poor survival (~14 months). Resistance to therapy may originate from a subpopulation of tumor cells identified as glioma-stem cells (GSC), and new treatments are urgently needed to target these. The biology underpinning GBM recurrence was investigated using whole transcriptome profiling of patient-matched initial and recurrent GBM (recGBM). Differential expression analysis identified 147 significant probes. In total, 24 genes were validated using expression data from four public cohorts and the literature. Functional analyses revealed that transcriptional changes to recGBM were dominated by angiogenesis and immune-related processes. The role of MHC class II proteins in antigen presentation and the differentiation, proliferation, and infiltration of immune cells was enriched. These results suggest recGBM would benefit from immunotherapies. The altered gene signature was further analyzed in a connectivity mapping analysis with QUADrATiC software to identify FDA-approved repurposing drugs. Top-ranking target compounds that may be effective against GSC and GBM recurrence were rosiglitazone, nizatidine, pantoprazole, and tolmetin. Our translational bioinformatics pipeline provides an approach to identify target compounds for repurposing that may add clinical benefit in addition to standard therapies against resistant cancers such as GBM.

The addition of arginine deiminase potentiates Mithramycin A-induced cell death in patient-derived glioblastoma cells via ATF4 and cytochrome C

BACKGROUND

Arginine auxotrophy constitutes a shortcoming for ~ 30% of glioblastoma multiforme (GBM). Indeed, arginine-depleting therapy using arginine deiminase from Streptococcus pyogenes (SpyADI) has proven activity against GBM in preclinical studies. The good safety profile of SpyADI renders this agent an ideal combination partner for cytostatic therapy.

METHODS

In this study, we combined the antineoplastic antibiotic Mithramycin A (MitA) with SpyADI to boost single-agent activity and analyzed underlying response mechanisms in-depth.

RESULTS

MitA monotherapy induced a time- and dose-dependent cytotoxicity in eight patient-derived GBM cell lines and had a radiosensitizing effect in all but one cell line. Combination treatment boosted the effects of the monotherapy in 2D- and 3D models. The simultaneous approach was superior to the sequential application and significantly impaired colony formation after repetitive treatment. MitA monotherapy significantly inhibited GBM invasiveness. However, this effect was not enhanced in the combination. Functional analysis identified SpyADI-triggered senescence induction accompanied by increased mitochondrial membrane polarization upon mono- and combination therapy. In HROG63, induction of lysosomes was seen after both monotherapies, indicative of autophagy. These cells seemed swollen and had a more pronounced cortically formed cytoskeleton. Also, cytochrome C and endoplasmatic reticulum-stress-associated proteins ATF4 and Calnexin were enhanced in the combination, contributing to apoptosis. Notably, no significant increases in glioma-stemness marker were seen.

CONCLUSIONS

Therapeutic utilization of a metabolic defect in GBM along with cytostatic therapy provides a novel combination approach. Whether this SpyADI/MitA regimen will provide a safe alternative to combat GBM, will have to be addressed in subsequent (pre-)clinical trials.

Aporphine and isoquinoline derivatives block glioblastoma cell stemness and enhance temozolomide cytotoxicity

Glioblastoma (GBM) is the most aggressive and common primary malignant brain tumor with limited available therapeutic approaches. Despite improvements in therapeutic options for GBM patients, efforts to develop new successful strategies remain as major unmet medical needs. Based on the cytotoxic properties of aporphine compounds, we evaluated the biological effect of 12 compounds obtained through total synthesis of ( ±)-apomorphine hydrochloride (APO) against GBM cells. The compounds 2,2,2-trifluoro-1-(1-methylene-3,4-dihydroisoquinolin-2(1H)-yl)ethenone (A5) and ( ±)-1-(10,11-dimethoxy-6a,7-dihydro-4H-dibenzo[de,g]quinolin-6(5H)-yl)ethenone (C1) reduced the viability of GBM cells, with 50% inhibitory concentration ranging from 18 to 48 μM in patient-derived GBM cultures. Our data show that APO, A5 or C1 modulate the expression of DNA damage and apoptotic markers, impair 3D-gliomasphere growth and reduce the expression of stemness markers. Potential activity and protein targets of A5, C1 or APO were predicted in silico based on PASS and SEA software. Dopamine receptors (DRD1 and 5), CYP2B6, CYP2C9 and ABCB1, whose transcripts were differentially expressed in the GBM cells, were among the potential A5 or C1 target proteins. Docking analyses (HQSAR and 3D-QSAR) were performed to characterize possible interactions of ABCB1 and CYP2C9 with the compounds. Notably, A5 or C1 treatment, but not temozolomide (TMZ), reduced significantly the levels of extracellular ATP, suggesting ABCB1 negative regulation, which was correlated with stronger cytotoxicity induced by the combination of TMZ with A5 or C1 on GBM cells. Hence, our data reveal a potential therapeutic application of A5 and C1 as cytotoxic agents against GBM cells and predicted molecular networks that can be further exploited to characterize the pharmacological effects of these isoquinoline-containing substances.

A pan-cancer-bioinformatic-based literature review of TRPM7 in cancers

TRPM7, a divalent cation-selective channel with kinase domains, has been widely reported to potentially affect cancers. In this study, we conducted multiple bioinformatic analyses based on open databases and reviewed articles that provided evidence for the effects of TRPM7 on cancers. The purposes of this paper are 1) to provide a pan-cancer overview of TRPM7 in cancers; 2) to summarize evidence of TRPM7 effects on cancers; 3) to identify potential future studies of TRPM7 in cancer. Bioinformatics analysis revealed that no cancer-related TRPM7 mutation was found. TRPM7 is aberrantly expressed in most cancer types but the cancer-noncancer expression pattern varies across cancer types. TRPM7 was not associated with survival, TMB, or cancer stemness in most cancer types. TRPM7 affected drug sensitivity and tumor immunity in some cancer types. The in vitro evidence, preclinical in vivo evidence, and clinical evidence for TRPM7 effects on cancers as well as TRPM7 kinase substrate and TRPM7-targeting drugs associated with cancers were summarized to facilitate comparison. We matched the bioinformatics evidence to literature evidence, thereby unveiling potential avenues for future investigation of TRPM7 in cancers. We believe that this paper will help orient research toward important and relevant aspects of the role of TRPM7 in cancers.

Identify the immune characteristics and immunotherapy value of CD93 in the pan-cancer based on the public data sets

CD93 is a transmembrane receptor that is mainly expressed on endothelial cells. A recent study found that upregulated CD93 in tumor vessels is essential for tumor angiogenesis in several cancers. However, the underlying mechanisms are largely unexplored. Our present research systematically analyzed the characteristics of CD93 in tumor immunotherapy among 33 cancers. CD93 levels and co-expression of CD93 on cancer and stromal cells were detected using public databases and multiple immunofluorescence staining. The Kaplan-Meier (KM) analysis identified the predictive role of CD93 in these cancer types. The survival differences between CD93 mutants and WT, CNV groups, and methylation were also investigated. The immune landscape of CD93 in the tumor microenvironment was analyzed using the SangerBox, TIMER 2.0, and single-cell sequencing. The immunotherapy value of CD93 was predicted through public databases. CD93 mRNA and protein levels differed significantly between cancer samples and adjacent control tissues in multiply cancer types. CD93 mRNA expression associated with patient prognosis in many cancers. The correlation of CD93 levels with mutational status of other gene in these cancers was also analyzed. CD93 levels significantly positively related to three scores (immune, stromal, and extimate), immune infiltrates, immune checkpoints, and neoantigen expression.. Additionally, single-cell sequencing revealed that CD93 is predominantly co-expressed on tumor and stromal cells, such as endothelial cells, cancer-associated fibroblasts (CAFs), neutrophils, T cells, macrophages, M1 and M2 macrophages. Several immune-related signaling pathways were enriched based on CD93 expression, including immune cells activation and migration, focal adhesion, leukocyte transendothelial migration, oxidative phosphorylation, and complement. Multiple immunofluorescence staining displayed the relationship between CD93 expression and CD8, CD68, and CD163 in these cancers. Finally, the treatment response of CD93 in many immunotherapy cohorts and sensitive small molecules was predicted from the public datasets. CD93 expression is closely associated with clinical prognosis and immune infiltrates in a variety of tumors. Targeting CD93-related signaling pathways in the tumor microenvironment may be a novel therapeutic strategy for tumor immunotherapy.

NSMCE2, a novel super-enhancer-regulated gene, is linked to poor prognosis and therapy resistance in breast cancer

BACKGROUND

Despite today's advances in the treatment of cancer, breast cancer-related mortality remains high, in part due to the lack of effective targeted therapies against breast tumor types that do not respond to standard treatments. Therefore, identifying additional breast cancer molecular targets is urgently needed. Super-enhancers are large regions of open chromatin involved in the overactivation of oncogenes. Thus, inhibition of super-enhancers has become a focus in clinical trials for its therapeutic potential. Here, we aimed to identify novel super-enhancer dysregulated genes highly associated with breast cancer patients' poor prognosis and negative response to treatment.

METHODS

Using existing datasets containing super-enhancer-associated genes identified in breast tumors and public databases comprising genomic and clinical information for breast cancer patients, we investigated whether highly expressed super-enhancer-associated genes correlate to breast cancer patients' poor prognosis and to patients' poor response to therapy. Our computational findings were experimentally confirmed in breast cancer cells by pharmacological SE disruption and gene silencing techniques.

RESULTS

We bioinformatically identified two novel super-enhancer-associated genes - NSMCE2 and MAL2 - highly upregulated in breast tumors, for which high RNA levels significantly and specifically correlate with breast cancer patients' poor prognosis. Through in-vitro pharmacological super-enhancer disruption assays, we confirmed that super-enhancers upregulate NSMCE2 and MAL2 transcriptionally, and, through bioinformatics, we found that high levels of NSMCE2 strongly associate with patients' poor response to chemotherapy, especially for patients diagnosed with aggressive triple negative and HER2 positive tumor types. Finally, we showed that decreasing NSMCE2 gene expression increases breast cancer cells' sensitivity to chemotherapy treatment.

CONCLUSIONS

Our results indicate that moderating the transcript levels of NSMCE2 could improve patients' response to standard chemotherapy consequently improving disease outcome. Our approach offers a new avenue to identify a signature of tumor specific genes that are not frequently mutated but dysregulated by super-enhancers. As a result, this strategy can lead to the discovery of potential and novel pharmacological targets for improving targeted therapy and the treatment of breast cancer.

A unified platform enabling biomarker ranking and validation for 1,562 drugs using transcriptomic data of 1,250 cancer cell lines

Intro

In vitro cell line models provide a valuable resource to investigate compounds useful in the systemic chemotherapy of cancer. However, the due to the dispersal of the data into several different databases, the utilization of these resources is limited. Here, our aim was to establish a platform enabling the validation of chemoresistance-associated genes and the ranking of available cell line models.

Methods

We processed four independent databases, DepMap, GDSC1, GDSC2, and CTRP. The gene expression data was quantile normalized and HUGO gene names were assigned to have unambiguous identification of the genes. Resistance values were exported for all agents. The correlation between gene expression and therapy resistance is computed using ROC test.

Results

We combined four datasets with chemosensitivity data of 1562 agents and transcriptome-level gene expression of 1250 cancer cell lines. We have set up an online tool utilizing this database to correlate available cell line sensitivity data and treatment response in a uniform analysis pipeline (www.rocplot.com/cells). We employed the established pipeline to by rank genes related to resistance against afatinib and lapatinib, two inhibitors of the tyrosine-kinase domain of ERBB2.

Discussion

The computational tool is useful 1) to correlate gene expression with resistance, 2) to identify and rank resistant and sensitive cell lines, and 3) to rank resistance associated genes, cancer hallmarks, and gene ontology pathways. The platform will be an invaluable support to speed up cancer research by validating gene-resistance correlations and by selecting the best cell line models for new experiments.

Prostanoid Signaling in Cancers: Expression and Regulation Patterns of Enzymes and Receptors

Cancer-associated disturbance of prostanoid signaling provides an aberrant accumulation of prostanoids. This signaling consists of 19 target genes, encoding metabolic enzymes and G-protein-coupled receptors, and prostanoids (prostacyclin, thromboxane, and prostaglandins E2, F2α, D2, H2). The study addresses the systems biology analysis of target genes in 24 solid tumors using a data mining pipeline. We analyzed differential expression patterns of genes and proteins, promoter methylation status as well as tissue-specific master regulators and microRNAs. Tumor types were clustered into several groups according to gene expression patterns. Target genes were characterized as low mutated in tumors, with the exception of melanoma. We found at least six ubiquitin ligases and eight protein kinases that post-translationally modified the most connected proteins PTGES3 and PTGIS. Models of regulation of PTGIS and PTGIR gene expression in lung and uterine cancers were suggested. For the first time, we found associations between the patient’s overall survival rates with nine multigene transcriptomics signatures in eight tumors. Expression patterns of each of the six target genes have predictive value with respect to cytostatic therapy response. One of the consequences of the study is an assumption of prostanoid-dependent (or independent) tumor phenotypes. Thus, pharmacologic targeting the prostanoid signaling could be a probable additional anticancer strategy.

Chaperone-Mediated Autophagy Controls Proteomic and Transcriptomic Pathways to Maintain Glioma Stem Cell Activity

Chaperone-mediated autophagy (CMA) is a homeostatic process essential for the lysosomal degradation of a selected subset of the proteome. CMA activity directly depends on the levels of LAMP2A, a critical receptor for CMA substrate proteins at the lysosomal membrane. In glioblastoma (GBM), the most common and aggressive brain cancer in adulthood, high levels of LAMP2A in the tumor and tumor-associated pericytes have been linked to temozolomide resistance and tumor progression. However, the role of LAMP2A, and hence CMA, in any cancer stem cell type or in glioblastoma stem cells (GSC) remains unknown. In this work, we show that LAMP2A expression is enriched in patient-derived GSCs, and its depletion diminishes GSC-mediated tumorigenic activities. Conversely, overexpression of LAMP2A facilitates the acquisition of GSC properties. Proteomic and transcriptomic analysis of LAMP2A-depleted GSCs revealed reduced extracellular matrix interaction effectors in both analyses. Moreover, pathways related to mitochondrial metabolism and the immune system were differentially deregulated at the proteome level. Furthermore, clinical samples of GBM tissue presented overexpression of LAMP2, which correlated with advanced glioma grade and poor overall survival. In conclusion, we identified a novel role of CMA in directly regulating GSCs activity via multiple pathways at the proteome and transcriptome levels.

SIGNIFICANCE

A receptor of chaperone-mediated autophagy regulates glioblastoma stem cells and may serve as a potential biomarker for advanced tumor grade and poor survival in this disease.

Aberrant mitochondrial homeostasis at the crossroad of musculoskeletal ageing and non-small cell lung cancer

Cancer cachexia is accompanied by muscle atrophy, sharing multiple common catabolic pathways with sarcopenia, including mitochondrial dysfunction. This study investigated gene expression from skeletal muscle tissues of older healthy adults, who are at risk of age-related sarcopenia, to identify potential gene biomarkers whose dysregulated expression and protein interference were involved in non-small cell lung cancer (NSCLC). Screening of the literature resulted in 14 microarray datasets (GSE25941, GSE28392, GSE28422, GSE47881, GSE47969, GSE59880 in musculoskeletal ageing; GSE118370, GSE33532, GSE19804, GSE18842, GSE27262, GSE19188, GSE31210, GSE40791 in NSCLC). Differentially expressed genes (DEGs) were used to construct protein-protein interaction networks and retrieve clustering gene modules. Overlapping module DEGs were ranked based on 11 topological algorithms and were correlated with prognosis, tissue expression, and tumour purity in NSCLC. The analysis revealed that the dysregulated expression of the mammalian mitochondrial ribosomal proteins, Mitochondrial Ribosomal Protein S26 (MRPS26), Mitochondrial Ribosomal Protein S17 (MRPS17), Mitochondrial Ribosomal Protein L18 (MRPL18) and Mitochondrial Ribosomal Protein L51 (MRPL51) were linked to reduced survival and tumour purity in NSCLC while tissue expression of the same genes followed an opposite direction in healthy older adults. These results support a potential link between the mitochondrial ribosomal microenvironment in ageing muscle and NSCLC. Further studies comparing changes in sarcopenia and NSCLC associated cachexia are warranted.

An integrated network analysis approach to identify potential key genes, transcription factors, and microRNAs regulating human hematopoietic stem cell aging

Hematopoietic stem cells (HSCs) undergo functional deterioration with increasing age that causes loss of their self-renewal and regenerative potential. Despite various efforts, significant success in identifying molecular regulators of HSC aging has not been achieved, one prime reason being the non-availability of appropriate human HSC samples. To demonstrate the scope of integrating and re-analyzing the HSC transcriptomics data available, we used existing tools and databases to structure a sequential data analysis pipeline to predict potential candidate genes, transcription factors, and microRNAs simultaneously. This sequential approach comprises (i) collecting matched young and aged mice HSC sample datasets, (ii) identifying differentially expressed genes, (iii) identifying human homologs of differentially expressed genes, (iv) inferring gene co-expression network modules, and (v) inferring the microRNA-transcription factor-gene regulatory network. Systems-level analyses of HSC interaction networks provided various insights based on which several candidates were predicted. For example, 16 HSC aging-related candidate genes were predicted (e.g., CD38, BRCA1, AGTR1, GSTM1, etc.) from GCN analysis. Following this, the shortest path distance-based analyses of the regulatory network predicted several novel candidate miRNAs and TFs. Among these, miR-124-3p was a common regulator in candidate gene modules, while TFs MYC and SP1 were identified to regulate various candidate genes. Based on the regulatory interactions among candidate genes, TFs, and miRNAs, a potential regulation model of biological processes in each of the candidate modules was predicted, which provided systems-level insights into the molecular complexity of each module to regulate HSC aging.

CTR-DB, an omnibus for patient-derived gene expression signatures correlated with cancer drug response

To date, only some cancer patients can benefit from chemotherapy and targeted therapy. Drug resistance continues to be a major and challenging problem facing current cancer research. Rapidly accumulated patient-derived clinical transcriptomic data with cancer drug response bring opportunities for exploring molecular determinants of drug response, but meanwhile pose challenges for data management, integration, and reuse. Here we present the Cancer Treatment Response gene signature DataBase (CTR-DB, http://ctrdb.ncpsb.org.cn/), a unique database for basic and clinical researchers to access, integrate, and reuse clinical transcriptomes with cancer drug response. CTR-DB has collected and uniformly reprocessed 83 patient-derived pre-treatment transcriptomic source datasets with manually curated cancer drug response information, involving 28 histological cancer types, 123 drugs, and 5139 patient samples. These data are browsable, searchable, and downloadable. Moreover, CTR-DB supports single-dataset exploration (including differential gene expression, receiver operating characteristic curve, functional enrichment, sensitizing drug search, and tumor microenvironment analyses), and multiple-dataset combination and comparison, as well as biomarker validation function, which provide insights into the drug resistance mechanism, predictive biomarker discovery and validation, drug combination, and resistance mechanism heterogeneity.