Evaluation of drug-targetable genes by defining modes of abnormality in gene expression

Comparison of Glioblastoma Cell Culture Platforms Based on Transcriptional Similarity with Paired Tissue

No standardized in vitro cell culture models for glioblastoma (GBM) have yet been established, excluding the traditional two-dimensional culture. GBM tumorspheres (TSs) have been highlighted as a good model platform for testing drug effects and characterizing specific features of GBM, but a detailed evaluation of their suitability and comparative performance is lacking. Here, we isolated GBM TSs and extracellular matrices (ECM) from tissues obtained from newly diagnosed IDH1 wild-type GBM patients and cultured GBM TSs on five different culture platforms: (1) ordinary TS culture liquid media (LM), (2) collagen-based three-dimensional (3D) matrix, (3) patient typical ECM-based 3D matrix, (4) patient tumor ECM-based 3D matrix, and (5) mouse brain. For evaluation, we obtained transcriptome data from all cultured GBM TSs using microarrays. The LM platform exhibited the most similar transcriptional program to paired tissues based on GBM genes, stemness- and invasiveness-related genes, transcription factor activity, and canonical signaling pathways. GBM TSs can be cultured via an easy-to-handle and cost- and time-efficient LM platform while preserving the transcriptional program of the originating tissues without supplementing the ECM or embedding it into the mouse brain. In addition to applications in basic cancer research, GBM TSs cultured in LM may also serve as patient avatars in drug screening and pre-clinical evaluation of targeted therapy and as standardized and clinically relevant models for precision medicine.

Classification of IDH wild-type glioblastoma tumorspheres into low- and high-invasion groups based on their transcriptional program

BACKGROUND

Glioblastoma (GBM), one of the most lethal tumors, exhibits a highly infiltrative phenotype. Here, we identified transcription factors (TFs) that collectively modulate invasion-related genes in GBM.

METHODS

The invasiveness of tumorspheres (TSs) were quantified using collagen-based 3D invasion assays. TF activities were quantified by enrichment analysis using GBM transcriptome, and confirmed by cell-magnified analysis of proteome imaging. Invasion-associated TFs were knocked down using siRNA or shRNA, and TSs were orthotopically implanted into mice.

RESULTS

After classifying 23 patient-derived GBM TSs into low- and high-invasion groups, we identified active TFs in each group-PCBP1 for low invasion, and STAT3 and SRF for high invasion. Knockdown of these TFs reversed the phenotype and invasion-associated-marker expression of GBM TSs. Notably, MRI revealed consistent patterns of invasiveness between TSs and the originating tumors, with an association between high invasiveness and poor prognosis. Compared to controls, mice implanted with STAT3- or SRF-downregulated GBM TSs showed reduced normal tissue infiltration and tumor growth, and prolonged survival, indicating a therapeutic response.

CONCLUSIONS

Our integrative transcriptome analysis revealed three invasion-associated TFs in GBM. Based on the relationship among the transcriptional program, invasive phenotype, and prognosis, we suggest these TFs as potential targets for GBM therapy.

Single-cell RNA sequencing reveals a pro-metastatic subpopulation and the driver transcription factor NFE2L1 in ovarian cancer cells

BACKGROUND

Although cytoreductive surgery followed by adjuvant chemotherapy is effective as a standard treatment for early-stage ovarian cancer, the majority of ovarian cancer cases are diagnosed at the advanced stages with dissemination to the peritoneal cavity, leading to a poor prognosis. Therefore, it is crucial to understand the cellular and molecular mechanisms underlying metastasis and identify novel therapeutic targets.

OBJECTIVE

In this study, we aimed to elucidate the mechanisms underlying gene expression alterations during the acquisition of metastatic potential and characterize the metastatic subpopulations within ovarian cancer cells.

METHODS

We conducted single-cell RNA sequencing of two human ovarian cancer cell lines: SKOV-3 and SKOV-3-13, a highly metastatic subclone of SKOV-3. Suppression of NFE2L1 expression was performed through siRNA-mediated knockdown and CRISPR-Cas9-mediated knockout.

RESULTS

Clustering and pseudotime trajectory analysis revealed pro-metastatic subpopulation within these cells. Furthermore, gene set enrichment analysis and prognosis analysis indicated that NFE2L1 could be a key transcription factor in the acquisition of metastasis potential. Inhibition of NFE2L1 significantly reduced migration and viability of both cells. In addition, NFE2L1 knockout cells exhibited significantly reduced tumor growth in a mouse xenograft model, recapitulating in silico and in vitro results.

CONCLUSION

The results presented in this study deepen our understanding of the molecular pathogenesis of ovarian cancer metastasis with the ultimate goal of developing treatments targeting pro-metastatic subclones prior to metastasis.

Machine learning multi-omics analysis reveals cancer driver dysregulation in pan-cancer cell lines compared to primary tumors

Cancer cell lines have been widely used for decades to study biological processes driving cancer development, and to identify biomarkers of response to therapeutic agents. Advances in genomic sequencing have made possible large-scale genomic characterizations of collections of cancer cell lines and primary tumors, such as the Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA). These studies allow for the first time a comprehensive evaluation of the comparability of cancer cell lines and primary tumors on the genomic and proteomic level. Here we employ bulk mRNA and micro-RNA sequencing data from thousands of samples in CCLE and TCGA, and proteomic data from partner studies in the MD Anderson Cell Line Project (MCLP) and The Cancer Proteome Atlas (TCPA), to characterize the extent to which cancer cell lines recapitulate tumors. We identify dysregulation of a long non-coding RNA and microRNA regulatory network in cancer cell lines, associated with differential expression between cell lines and primary tumors in four key cancer driver pathways: KRAS signaling, NFKB signaling, IL2/STAT5 signaling and TP53 signaling. Our results emphasize the necessity for careful interpretation of cancer cell line experiments, particularly with respect to therapeutic treatments targeting these important cancer pathways.

Regulation of bioenergetics through dual inhibition of aldehyde dehydrogenase and mitochondrial complex I suppresses glioblastoma tumorspheres

Background

Targeted approaches for treating glioblastoma (GBM) attempted to date have consistently failed, highlighting the imperative for treatment strategies that operate on different mechanistic principles. Bioenergetics deprivation has emerged as an effective therapeutic approach for various tumors. We have previously found that cancer cells preferentially utilize cytosolic NADH supplied by aldehyde dehydrogenase (ALDH) for ATP production through oxidative phosphorylation (OxPhos). This study is aimed at examining therapeutic responses and underlying mechanisms of dual inhibition of ALDH and OxPhos against GBM.

Methods

For inhibition of ALDH and OxPhos, the corresponding inhibitors, gossypol and phenformin were used. Biological functions, including ATP levels, stemness, invasiveness, and viability, were evaluated in GBM tumorspheres (TSs). Gene expression profiles were analyzed using microarray data. In vivo anticancer efficacy was examined in a mouse orthotopic xenograft model.

Results

Combined treatment of GBM TSs with gossypol and phenformin significantly reduced ATP levels, stemness, invasiveness, and cell viability. Consistently, this therapy substantially decreased expression of genes associated with stemness, mesenchymal transition, and invasion in GBM TSs. Supplementation of ATP using malate abrogated these effects, whereas knockdown of ALDH1L1 mimicked them, suggesting that disruption of ALDH-mediated ATP production is a key mechanism of this therapeutic combination. In vivo efficacy confirmed remarkable therapeutic responses to combined treatment with gossypol and phenformin.

Conclusion

Our findings suggest that dual inhibition of tumor bioenergetics is a novel and effective strategy for the treatment of GBM.

Prognostic Value of mRNA Expression of MAP4K Family in Acute Myeloid Leukemia

BACKGROUND

Despite diverse functions in diseases, the prognostic potential of the family of mitogen-activated protein kinase kinase kinase kinase genes in acute myeloid leukemia remains unknown.

METHODS

The messenger RNA expression of the MAP4K family members in 151 patients with acute myeloid leukemia was extracted from the OncoLnc database. Data for gender, age, cytogenetic, leukocyte count, CD34, FAB classification, RUNX1, and TP53 were provided by the University of California-Santa Cruz Xena platform. Kaplan-Meier analysis and Cox regression model provided an estimate of the hazard ratio with 95% confidence intervals for overall survival.

RESULTS

Analysis demonstrated favorable overall survival in patients with acute myeloid leukemia attributing to high expression of MAP4K3, MAP4K4, and MAP4K5 and low expression of MAP4K1 (adjusted P = .005, P = .022, P = .002, and P = .024; adjusted hazard ratio = 0.490, 95% confidence interval = 0.297-0.809, hazard ratio = 0.598, 95% confidence interval = 0.385-0.928, hazard ratio = 0.490, 95% confidence interval = 0.310-0.776, and hazard ratio = 0.615, 95% confidence interval = 0.403-0.938, respectively). Combining the high-expressing MAP4K3, MAP4K4, and MAP4K5 with the low-expressing MAP4K1 in a joint effect analysis predicted a favorable prognosis of overall survival in acute myeloid leukemia.

CONCLUSION

High expression of MAP4K3, MAP4K4, and MAP4K5 combined with low expression of MAP4K1 can serve as a sensitive tool to predict favorable overall survival in patients with acute myeloid leukemia.

Astragalus polysaccharide combined with 10-hydroxycamptothecin inhibits metastasis in non-small cell lung carcinoma cell lines via the MAP4K3/mTOR signaling pathway

Non‑small cell lung carcinoma (NSCLC) is a life‑threatening malignancy. The level of the cell growth regulator mitogen‑activated protein kinase kinase kinase kinase 3 (MAP4K3) has been shown to be correlated with a high risk of NSCLC recurrence and poor recurrence‑free survival rate. The present study examined the effects of Astragalus polysaccharide (APS) and 10‑hydroxycamptothecin (HCPT), which are associated with marked suppression and dephosphorylation of the MAP4K3/mammalian target of rapamycin (mTOR) signaling pathway, in the H1299 NSCLC cell line. APS and HCPT decreased H1299 cell viability, induced apoptosis and altered the cell cycle stages, as evaluated using an 3‑(4,5‑dimethylthiazol‑2‑yl)‑2,5‑diphenyltetrazolium bromide assay and flow cytometric analysis. Furthermore, APS increased the expression of apoptosis‑associated genes B‑cell lymphoma 2 (Bcl‑2) and Bcl‑2‑associated X protein (BAX), of proteases cysteine‑aspartic acid protease (caspase)‑3 and ‑9, and of cytochrome c. HCPT promoted autophagy in H1299 cells, with concomitant suppression of the expression of MAP4K3 and downregulation of mTOR signaling. Notably, combination treatment with the two agents reduced the migration and invasion of H1299 cells compared with the single treatments. It was also demonstrated that the overexpression of MAP4K3 promoted the migration and invasion of H1299 cells, and that the kinase activity was essential to this. These findings suggested that MAP4K3 may be an attractive target for the treatment of NSCLC.

A Computational Method for Classifying Different Human Tissues with Quantitatively Tissue-Specific Expressed Genes

Tissue-specific gene expression has long been recognized as a crucial key for understanding tissue development and function. Efforts have been made in the past decade to identify tissue-specific expression profiles, such as the Human Proteome Atlas and FANTOM5. However, these studies mainly focused on "qualitatively tissue-specific expressed genes" which are highly enriched in one or a group of tissues but paid less attention to "quantitatively tissue-specific expressed genes", which are expressed in all or most tissues but with differential expression levels. In this study, we applied machine learning algorithms to build a computational method for identifying "quantitatively tissue-specific expressed genes" capable of distinguishing 25 human tissues from their expression patterns. Our results uncovered the expression of 432 genes as optimal features for tissue classification, which were obtained with a Matthews Correlation Coefficient (MCC) of more than 0.99 yielded by a support vector machine (SVM). This constructed model was superior to the SVM model using tissue enriched genes and yielded MCC of 0.985 on an independent test dataset, indicating its good generalization ability. These 432 genes were proven to be widely expressed in multiple tissues and a literature review of the top 23 genes found that most of them support their discriminating powers. As a complement to previous studies, our discovery of these quantitatively tissue-specific genes provides insights into the detailed understanding of tissue development and function.

Potential prognostic biomarkers identified by DNA methylation profiling analysis for patients with lung adenocarcinoma

Lung adenocarcinoma is frequently occurring type of lung cancer with high metastatic risk. We performed a DNA methylation profiling analysis to identify possible prognostic markers involved in lung adenocarcinoma. DNA methylation profiling data (GSE66386) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially methylated genes were identified using a limma package. GO enrichment analysis was performed to identify vital functions related to differential gene methylation, and pathway analysis was performed to assess the associations between different proteins with regard to regulation of cell function and metabolism. The screening results showed a total of 112,662 differentially methylated genes in lung adenocarcinoma patients compared with those of the normal controls. These CpGs were involved in 16,705 genes. The skeletal system development (P=9.46E-27) and embryonic organ morphogenesis (P=8.67E-24) were found to be involved in lung adenocarcinoma. The cancer (P=3.64E-07), Rap1 signaling (P=9.21E-05) and calcium signaling (P=9.21E-05) pathways constituted the important pathways associated with lung adenocarcinoma. In conclusion, methylated PTPRF, HOXD3, HOXD13 and CACNA1A are potential markers and may be utilized for the diagnosis and therapy of lung adenocarcinoma.

Germinal-center kinase-like kinase co-crystal structure reveals a swapped activation loop and C-terminal extension

Germinal-center kinase-like kinase (GLK, Map4k3), a GCK-I family kinase, plays multiple roles in regulating apoptosis, amino acid sensing, and immune signaling. We describe here the crystal structure of an activation loop mutant of GLK kinase domain bound to an inhibitor. The structure reveals a weakly associated, activation-loop swapped dimer with more than 20 amino acids of ordered density at the carboxy-terminus. This C-terminal PEST region binds intermolecularly to the hydrophobic groove of the N-terminal domain of a neighboring molecule. Although the GLK activation loop mutant crystallized demonstrates reduced kinase activity, its structure demonstrates all the hallmarks of an "active" kinase, including the salt bridge between the C-helix glutamate and the catalytic lysine. Our compound displacement data suggests that the effect of the Ser170Ala mutation in reducing kinase activity is likely due to its effect in reducing substrate peptide binding affinity rather than reducing ATP binding or ATP turnover. This report details the first structure of GLK; comparison of its activation loop sequence and P-loop structure to that of Map4k4 suggests ideas for designing inhibitors that can distinguish between these family members to achieve selective pharmacological inhibitors.