Identification of COL6A1 as the Key Gene Associated with Antivascular Endothelial Growth Factor Therapy in Glioblastoma Multiforme

A novel interplay between PRC2 and miR-3189 regulates epithelial-mesenchymal transition (EMT) via modulating COL6A2 in glioblastoma

Recent studies have shed light on disrupted collagen signaling in Gliomas, yet the regulatory landscape remains largely unexplored. This study enquired into the role of polycomb repressive complex-2 (PRC2)-mediated H3K27me3 modification, a key epigenetic factor in glioma. Using in-house data, we identified miRNAs downregulated in glioblastoma (GBM) with the potential to regulate Collagen VI family genes. Notably, miR-3189 emerged as a prime PRC2 target. Its expression was significantly downregulated in Indian GBM patients as well as other glioma cohorts. Mechanistic insights, involving Luciferase assays, mutagenesis, and Western blot analysis, confirmed direct targeting of Collagen VI member COL6A2 by miR-3189-3p. Functional assays demonstrated that miR-3189-3p restrained GBM malignancy by inhibiting proliferation, migration, and epithelial-mesenchymal transition (EMT). Conversely, COL6A2 overexpressed in GBM patients, countered miR-3189, and promoted the malignant phenotype. Gene set enrichment analysis highlighted EMT enrichment in GBM patients with elevated COL6A2 expression, carrying prognostic implications. This study uncovers intricate interactions between two epigenetic regulators-H3K27me3 and miR-3189-working synergistically to modulate Collagen VI gene; thus, influencing the malignancy of GBM. Targeting this H3K27me3|miR-3189-3p|COL6A2 axis presents a potential therapeutic avenue against GBM.

Identification and validation of COL6A1 as a novel target for tumor electric field therapy in glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is the most aggressive primary brain malignancy. Novel therapeutic modalities like tumor electric field therapy (TEFT) have shown promise, but underlying mechanisms remain unclear. The extracellular matrix (ECM) is implicated in GBM progression, warranting investigation into TEFT-ECM interplay.

METHODS

T98G cells were treated with TEFT (200 kHz, 2.2 V/m) for 72 h. Collagen type VI alpha 1 (COL6A1) was identified as hub gene via comprehensive bioinformatic analysis based on RNA sequencing (RNA-seq) and public glioma datasets. TEFT intervention models were established using T98G and Ln229 cell lines. Pre-TEFT and post-TEFT GBM tissues were collected for further validation. Focal adhesion pathway activity was assessed by western blot. Functional partners of COL6A1 were identified and validated by co-localization and survival analysis.

RESULTS

TEFT altered ECM-related gene expression in T98G cells, including the hub gene COL6A1. COL6A1 was upregulated in GBM and associated with poor prognosis. Muti-database GBM single-cell analysis revealed high-COL6A1 expression predominantly in malignant cell subpopulations. Differential expression and functional enrichment analyses suggested COL6A1 might be involved in ECM organization and focal adhesion. Western blot (WB), immunofluorescence (IF), and co-immunoprecipitation (Co-IP) experiments revealed that TEFT significantly inhibited expression of COL6A1, hindering its interaction with ITGA5, consequently suppressing the FAK/Paxillin/AKT pathway activity. These results suggested that TEFT might exert its antitumor effects by downregulating COL6A1 and thereby inhibiting the activity of the focal adhesion pathway.

CONCLUSION

TEFT could remodel the ECM of GBM cells by downregulating COL6A1 expression and inhibiting focal adhesion pathway. COL6A1 could interact with ITGA5 and activate the focal adhesion pathway, suggesting that it might be a potential therapeutic target mediating the antitumor effects of TEFT.

Digital profiling of cancer transcriptomes from histology images with grouped vision attention

Cancer is a heterogeneous disease that demands precise molecular profiling for better understanding and management. Recently, deep learning has demonstrated potentials for cost-efficient prediction of molecular alterations from histology images. While transformer-based deep learning architectures have enabled significant progress in non-medical domains, their application to histology images remains limited due to small dataset sizes coupled with the explosion of trainable parameters. Here, we develop SEQUOIA, a transformer model to predict cancer transcriptomes from whole-slide histology images. To enable the full potential of transformers, we first pre-train the model using data from 1,802 normal tissues. Then, we fine-tune and evaluate the model in 4,331 tumor samples across nine cancer types. The prediction performance is assessed at individual gene levels and pathway levels through Pearson correlation analysis and root mean square error. The generalization capacity is validated across two independent cohorts comprising 1,305 tumors. In predicting the expression levels of 25,749 genes, the highest performance is observed in cancers from breast, kidney and lung, where SEQUOIA accurately predicts the expression of 11,069, 10,086 and 8,759 genes, respectively. The accurately predicted genes are associated with the regulation of inflammatory response, cell cycles and metabolisms. While the model is trained at the tissue level, we showcase its potential in predicting spatial gene expression patterns using spatial transcriptomics datasets. Leveraging the prediction performance, we develop a digital gene expression signature that predicts the risk of recurrence in breast cancer. SEQUOIA deciphers clinically relevant gene expression patterns from histology images, opening avenues for improved cancer management and personalized therapies.

Proteome-Wide Profiling Using Sample Multiplexing of a Human Cell Line Treated with Cannabidiol (CBD) and Tetrahydrocannabinol (THC)

Cannabis has been used historically for both medicinal and recreational purposes, with the most notable cannabinoids being cannabidiol (CBD) and tetrahydrocannabinol (THC). Although their therapeutic effects have been well studied and their recreational use is highly debated, the underlying mechanisms of their biological effects remain poorly defined. In this study, we use isobaric tag-based sample multiplexed proteome profiling to investigate protein abundance differences in the human neuroblastoma SH-SY5Y cell line treated with CBD and THC. We identified significantly regulated proteins by each treatment and performed a pathway classification and associated protein-protein interaction analysis. Our findings suggest that these treatments may lead to mitochondrial dysfunction and induce endoplasmic reticulum stress. These data can potentially be interrogated further to investigate the potential role of CBD and THC in various biological and disease contexts, providing a foundation for future studies.

High expression of COL6A1 predicts poor prognosis and response to immunotherapy in bladder cancer

Extracellular matrix (ECM), as an important framework for tumor microenvironment, plays important roles in many critical processes, including tumor growth, invasion, immune suppression, and drug resistance. However, few biomarkers of ECM-related genes (ERGs) have been developed for prognosis prediction and clinical treatment of bladder cancer (BC) patients. Bioinformatics analysis and LC-MS/MS analysis were used to screen differentially expressed ERGs in BC. Multivariate Cox regression analysis and Lasso regression analysis were used to construct and validate an ERGs-based prognostic prediction model for BC. Immunohistochemistry was used to detect the protein expression of hub gene-COL6A1 in BC patients. Using bioinformatics analysis from The Cancer Genome Atlas (TCGA) database and proteomic analysis from our BC cohort, we constructed and validated an effective prognostic prediction model for BC patients based on four differentially expressed ERGs (MAP1B, FBN1, COL6A1, and MFAP5). Moreover, we identified human collagen VI-COL6A1 was a hub gene in this prognostic prediction model and found that COL6A1 was closely related to malignancy progression, prognosis, and response to PD-1 inhibitor immunotherapy in BC. Our findings highlight the satisfactory predictive value of ECM-related prognostic models in BC and suggested that COL6A1 may be a potential biomarker in predicting malignant progression, prognosis, and efficacy of immunotherapy in BC.

Correlation of Matrisome-Associatted Gene Expressions with LOX Family Members in Astrocytomas Stratified by IDH Mutation Status

Tumor cell infiltrative ability into surrounding brain tissue is a characteristic of diffusely infiltrative astrocytoma and is strongly associated with extracellular matrix (ECM) stiffness. Collagens are the most abundant ECM scaffolding proteins and contribute to matrix organization and stiffness. LOX family members, copper-dependent amine oxidases, participate in the collagen and elastin crosslinking that determine ECM tensile strength. Common IDH mutations in lower-grade gliomas (LGG) impact prognosis and have been associated with ECM stiffness. We analyzed the expression levels of LOX family members and matrisome-associated genes in astrocytoma stratified by malignancy grade and IDH mutation status. A progressive increase in expression of all five LOX family members according to malignancy grade was found. LOX, LOXL1, and LOXL3 expression correlated with matrisome gene expressions. LOXL1 correlations were detected in LGG with IDH mutation (IDH^mut), LOXL3 correlations in LGG with IDH wild type (IDH^wt) and strong LOX correlations in glioblastoma (GBM) were found. These increasing correlations may explain the increment of ECM stiffness and tumor aggressiveness from LGG-IDH^mut and LGG-IDH^wt through to GBM. The expression of the mechanosensitive transcription factor, β-catenin, also increased with malignancy grade and was correlated with LOXL1 and LOXL3 expression, suggesting involvement of this factor in the outside–in signaling pathway.

Tumor antigens and immune subtypes of glioblastoma: the fundamentals of mRNA vaccine and individualized immunotherapy development

PURPOSE

Glioblastoma (GBM) is the most common primary brain tumor in adults and is notorious for its lethality. Given its limited therapeutic measures and high heterogeneity, the development of new individualized therapies is important. mRNA vaccines have exhibited promising performance in a variety of solid tumors, those designed for glioblastoma (GBM) need further development. The aim of this study is to explore tumor antigens for the development of mRNA vaccines against GBM and to identify potential immune subtypes of GBM to identify the patients suitable for different immunotherapies.

METHODS

RNA-seq data and the clinical information of 143 GBM patients was extracted from the TCGA database; microarray data and the clinical information of 181 GBM patients was obtained from the REMBRANDT cohort. A GBM immunotherapy cohort of 17 patients was obtained from a previous literature. GEPIA2, cBioPortal, and TIMER2 were used to identify the potential tumor antigens. Immune subtypes and gene modules were identified using consensus clustering; immune landscape was constructed using graph-learning-based dimensionality reduction analysis.

RESULTS

Nine potential tumor antigens associated with poor prognosis and infiltration of antigen-presenting cells were identified in GBM: ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1. Four robust immune subtypes and seven functional gene modules were identified and validated in an independent cohort. Immune subtypes had different cellular and molecular characteristics, with IS1, an immune cold phenotype; IS2, an immune hot and immunosuppressive phenotype; IS3, a relatively immune cold phenotype, second only to IS1; IS4, having a moderate tumor immune microenvironment. Immune landscape revealed the immune distribution of the GBM patients. Additionally, the potential value of immune subtypes for individualized immunotherapy was demonstrated in a GBM immunotherapy cohort.

CONCLUSIONS

ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1 are the candidate tumor antigens for mRNA vaccine development in GBM, and IS1 GBM patients are best suited for mRNA vaccination, IS2 patients are best suited for immune checkpoint inhibitor. This study provides a theoretical framework for GBM mRNA vaccine development and individualized immunotherapy strategies.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s40537-022-00643-x.