Inhibition of the Spectraplakin Protein Microtubule Actin Crosslinking Factor 1 Sensitizes Glioblastomas to Radiation

Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways

BACKGROUND

Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data.

METHOD

We propose a Quantum Neural Networks architecture to discover genetic biomarkers for input activation pathways. The Maximum Relevance-Minimum Redundancy criteria score biomarker candidate sets. Our proposed model is economical since the neural solution can be delivered on constrained hardware.

RESULTS

We demonstrate the proof of concept on four activation pathways associated with CTLA4, including (1) CTLA4-activation stand-alone, (2) CTLA4-CD8A-CD8B co-activation, (3) CTLA4-CD2 co-activation, and (4) CTLA4-CD2-CD48-CD53-CD58-CD84 co-activation.

CONCLUSION

The model indicates new genetic biomarkers associated with the mutational activation of CLTA4-associated pathways, including 20 genes: CLIC4, CPE, ETS2, FAM107A, GPR116, HYOU1, LCN2, MACF1, MT1G, NAPA, NDUFS5, PAK1, PFN1, PGAP3, PPM1G, PSMD8, RNF213, SLC25A3, UBA1, and WLS. We open source the implementation at: https://github.com/namnguyen0510/Biomarker-Discovery-with-Quantum-Neural-Networks .

Surfaceome Proteomic of Glioblastoma Revealed Potential Targets for Immunotherapy

Glioblastoma (GBM) is the most common and devastating malignant brain tumor in adults. The mortality rate is very high despite different treatments. New therapeutic targets are therefore highly needed. Cell-surface proteins represent attractive targets due to their accessibility, their involvement in essential signaling pathways, and their dysregulated expression in cancer. Moreover, they are potential targets for CAR-based immunotherapy or mRNA vaccine strategies. In this context, we investigated the GBM-associated surfaceome by comparing it to astrocytes cell line surfaceome to identify new specific targets for GBM. For this purpose, biotinylation of cell surface proteins has been carried out in GBM and astrocytes cell lines. Biotinylated proteins were purified on streptavidin beads and analyzed by shotgun proteomics. Cell surface proteins were identified with Cell Surface Proteins Atlas (CSPA) and Gene Ontology enrichment. Among all the surface proteins identified in the different cell lines we have confirmed the expression of 66 of these in patient’s glioblastoma using spatial proteomic guided by MALDI-mass spectrometry. Moreover, 87 surface proteins overexpressed or exclusive in GBM cell lines have been identified. Among these, we found 11 specific potential targets for GBM including 5 mutated proteins such as RELL1, CYBA, EGFR, and MHC I proteins. Matching with drugs and clinical trials databases revealed that 7 proteins were druggable and under evaluation, 3 proteins have no known drug interaction yet and none of them are the mutated form of the identified proteins. Taken together, we discovered potential targets for immune therapy strategies in GBM.

Expression and Clinical Significance of Microtubule-Actin Cross-Linking Factor 1 in Serous Ovarian Cancer

BACKGROUND

Ovarian Cancer (OC) remains the first leading cause of gynecologic malignancy. The survival rate from Serous Ovarian Cancer (SOC) is very low, and the present prognostic predictors of SOC are not very sensitive or specific.

OBJECTIVE

The present study aimed to investigate Microtubule-Actin Cross-Linking Factor 1 (MACF1) expression in SOC tissues (including paraffin-embedded and fresh tissues) and to assess its expression and significant value in patients with SOC.

METHODS

A total of 18 fresh SOC tissues and their paired paratumor tissues were performed with reverse-transcription quantitative PCR analysis to detect MACF1 mRNA expression. Moreover, 175 paraffin-embedded SOC tissues and 41 paratumor tissues were assessed for MACF1 expression using immunohistochemistry.

RESULTS

The mRNA and protein expression of MACF1, both were higher in cancer tissues than that in paratumor tissues, and the high expression of MACF1 was associated with shorter Recurrence Free Survival (RFS) and Overall Survival (OS) in patients with SOC. Furthermore, multivariate regression analysis showed that high MACF1 expression was an independent poor survival predictor of patients with SOC.

CONCLUSION

MACF1 is upregulated in SOC, and it may be used as a useful prognostic biomarker in SOC.

Strength Through Unity: The Power of the Mega-Scaffold MACF1

The tight coordination of diverse cytoskeleton elements is required to support several dynamic cellular processes involved in development and tissue homeostasis. The spectraplakin-family of proteins are composed of multiple domains that provide versatility to connect different components of the cytoskeleton, including the actin microfilaments, microtubules and intermediates filaments. Spectraplakins act as orchestrators of precise cytoskeletal dynamic events. In this review, we focus on the prototypical spectraplakin MACF1, a protein scaffold of more than 700 kDa that coordinates the crosstalk between actin microfilaments and microtubules to support cell-cell connections, cell polarity, vesicular transport, proliferation, and cell migration. We will review over two decades of research aimed at understanding the molecular, physiological and pathological roles of MACF1, with a focus on its roles in developmental and cancer. A deeper understanding of MACF1 is currently limited by technical challenges associated to the study of such a large protein and we discuss ideas to advance the field.

Identification of key genes in lung adenocarcinoma based on a competing endogenous RNA network

Lung adenocarcinoma (LUAD) is the most commonly diagnosed type of lung cancer and exhibits a high morbidity. The present study aimed to investigate the long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) mechanisms in LUAD. The receptor activity modifying protein 2-antisense RNA 1 (RAMP2-AS1) was identified using GSE113852 and GSE130779 datasets downloaded from the Gene Expression Omnibus database, and the downregulation of RAMP2-AS1 was the most significant in LUAD. In addition, microRNA (miR)-296-5p was identified to bind to RAMP2-AS1 via bioinformatics analysis. Subsequently, CD44, cyclin D3 (CCND3), neurocalcin δ (NCALD), microtubule actin crosslinking factor 1 (MACF1) and potassium channel tetramerization domain containing 15 were obtained by intersecting the predicted target genes of miR-296-5p and 368 differentially expressed mRNAs in LUAD. According to the Gene Expression Profiling Interactive Analysis and UALCAN databases, these five mRNAs were downregulated in LUAD, and their expression levels were positively correlated with those of RAMP2-AS1. CD44, CCND3, NCALD and MACF1 were selected as key mRNAs in LUAD based on prognostic analyses. Furthermore, functional enrichment analyses were performed and an interaction network was constructed to reveal the functions of the RAMP2-AS1-associated ceRNA in LUAD. The results indicated that the functions were mainly enriched in generic transcription pathways, cyclin D-associated events in G₁ and epithelial stromal transformation. Reverse transcription-quantitative PCR assays revealed that RAMP2-AS1, CD44, CCND3, NCALD and MACF1 expression was lower in tumor tissues than in normal tissues, while miR-296-5p expression was higher in tumor tissues compared with in normal tissues. The association between RAMP2-AS1 and MACF1 was further confirmed using in vitro experiments. Overall, the present results indicated that RAMP2-AS1, miR-296-5p, CD44, CCND3, NCALD and MACF1 may be involved in LUAD progression and may therefore serve as potential biomarkers and provide a theoretical basis for the study of the pathogenesis of LUAD.