Gimap5 Inhibits Lung Cancer Growth by Interacting With M6PR

A comprehensive multi-omics study reveals potential prognostic and diagnostic biomarkers for colorectal cancer

BACKGROUND AND OBJECTIVE

Colorectal cancer (CRC) is a complex disease with diverse genetic alterations and causes 10 % of cancer-related deaths worldwide. Understanding its molecular mechanisms is essential for identifying potential biomarkers and therapeutic targets for its effective management.

METHODS

We integrated copy number alterations (CNA) and mutation data via their differentially expressed genes termed as candidate genes (CGs) computed using bioinformatics approaches. Then, using the CGs, we perform Weighted correlation network analysis (WGCNA) and utilise several hazard models such as Univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO) Cox and multivariate Cox to identify the key genes involved in CRC progression. We used different machine-learning models to demonstrate the discriminative power of selected hub genes among normal and CRC (early and late-stage) samples.

RESULTS

The integration of CNA with mRNA expression identified over 3000 CGs, including CRC-specific driver genes like MYC and APC. In addition, pathway analysis revealed that the CGs are mainly enriched in endocytosis, cell cycle, wnt signalling and mTOR signalling pathways. Hazard models identified four key genes, CASP2, HCN4, LRRC69 and SRD5A1, that were significantly associated with CRC progression and predicted the 1-year, 3-years, and 5-years survival times. WGCNA identified seven hub genes: DSCC1, ETV4, KIAA1549, NOP56, RRS1, TEAD4 and ANKRD13B, which exhibited strong predictive performance in distinguishing normal from CRC (early and late-stage) samples.

CONCLUSIONS

Integrating regulatory information with gene expression improved early versus late-stage prediction. The identified potential prognostic and diagnostic biomarkers in this study may guide us in developing effective therapeutic strategies for CRC management.

MRPL13 is a metastatic and prognostic marker of breast cancer: A silico analysis accompanied with experimental validation

BACKGROUND

Although progress has been made in accurate diagnosis and targeted treatments, breast cancer (BC) patients with metastasis still present a grim prognosis. With the continuous emergence and development of new personalized and precision medicine targeting specific tumor biomarkers, there is an urgent need to find new metastatic and prognostic biomarkers for BC patients.

METHODS

We were dedicated to identifying genes linked to metastasis and prognosis in breast cancer through a combination of in silico analysis and experimental validation.

RESULTS

A total of 25 overlap differentially expressed genes were identified. Ten hub genes (namely MRPL13, CTR9, TCEB1, RPLP0, TIMM8B, METTL1, GOLT1B, PLK2, PARL and MANBA) were identified and confirmed. MRPL13, TCEB1 and GOLT1B were shown to be associated with the worse overall survival (OS) and were optionally chosen for further verification by western blot. Only MRPL13 was found associated with cell invasion, and the expression of MRPL13 in metastatic BC was significantly higher than in primary BC.

CONCLUSION

We proposed MRPL13 could be a potential novel biomarker for the metastasis and prognosis of breast cancer.

Cancer energy reprogramming and the immune responses

Cancer as an uncontrolled growth of cells due to existing mutation in host cells that may proliferate, induce angiogenesis and sometimes metastasize due to the favorable tumor microenvironment (TME). Since it kills more than any disease, biomedical science does not relent in studying the exact pathogenesis. It was believed to be a problem that lies in the nucleus of the host cells; however, recent oncology findings are shifting attention to the mitochondria as an adjuvant to cancer pathogenesis. The changes in the gene are strongly related to cellular metabolism and metabolic reprogramming. It is now understood that reprogramming the TME will have a direct effect on the immune cells' metabolism. Although there are a number of studies on immune cells' response towards tumor energy reprogramming and cancer progression, there is still no existence with the updated collation of these immune cells' response to distinct energy reprogramming in cancer studies. To this end, this mini review shed some light on cancer energy reprogramming mechanisms and enzyme degradation pathways, the cancer pathogenicity activity series involved with reduced lactate production, the specific immune cell responses due to the energy reprogramming. This study highlighted some prospects and future experiments in harnessing the host immune response towards the altered energy metabolism due to cancer.

A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Most patients are diagnosed at an advanced stage, therefore it is crucial to identify novel prognostic biomarkers for LUAD. As important regulatory cells, inducible regulatory T cells (iTregs) play a vital role in immune suppression and are important for the maintenance of immune homeostasis. This study explored the prognostic value and therapeutic effects of iTreg-related genes in LUAD. Data for LUAD patients, including immune infiltration data, RNA sequencing data, and clinical features, were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Single-cell Hub 2 databases. Immune-related subgroups with different infiltration patterns and iTreg-related genes were identified through univariate and multivariate Cox regression analyses and weighted correlation network analysis. Functional enrichment analyses were performed to explore the underlying mechanisms of iTreg-related genes. A prognostic risk signature was constructed using Cox regression analysis with the least absolute shrinkage and selection operator penalty. The ESTIMATE algorithm was applied to determine the immune status of LUAD patients. We applied the constructed signature to predict chemosensitivity and performed single-cell RNA sequencing analysis. The infiltration of iTregs was identified as an independent factor for predicting patient outcomes. We constructed a prognostic signature based on seven iTreg-related genes (GIMAP5, SLA, MS4A7, ZNF366, POU2AF1, MRPL12, and COL5A1), which was applied to subdivide patients into high- and low-risk subgroups. Our results revealed that patients in the iTreg-related low-risk subgroup had a better prognosis and possibly greater sensitivity to traditional chemotherapy. Our study provides a novel iTreg-related signature to elucidate the mechanisms underlying LUAD prognosis and promote individualized chemotherapy treatment.

Cation-independent mannose 6-phosphate receptor: From roles and functions to targeted therapies

The cation-independent mannose 6-phosphate receptor (CI-M6PR) is a ubiquitous transmembrane receptor whose main intracellular role is to direct enzymes carrying mannose 6-phosphate moieties to lysosomal compartments. Recently, the small membrane-bound portion of this receptor has appeared to be implicated in numerous pathophysiological processes. This review presents an overview of the main ligand partners and the roles of CI-M6PR in lysosomal storage diseases, neurology, immunology and cancer fields. Moreover, this membrane receptor has already been noted for its strong potential in therapeutic applications thanks to its cellular internalization activity and its ability to address pathogenic factors to lysosomes for degradation. A number of therapeutic delivery approaches using CI-M6PR, in particular with enzymes, antibodies or nanoparticles, are currently being proposed.

Gimap5 promoted RSV degradation through interaction with M6PR

Respiratory syncytial virus (RSV) is one of the main pathogens of viral pneumonia and bronchiolitis in infants and young children and life-threatening diseases among infants and young children. GTPases of the immune-associated protein family (GIMAP) are new family members of immune-associated GTPases. In recent years, much attention has been paid to the function of the GIMAP family in coping with infection and stress. Gimap5 is a member of the GIMAP family, which may be correlated with anti-infectious immunity. RT-qPCR, Western blot, and indirect immunofluorescence (IFA) were used to detect the expression of Gimap5, M6PR and IGF1R(the major RSV receptor). Transmission electron microscopy (TEM) was used to detect the degradation of RSV in Gimap5-overexpressed or -silent cell lines. Computer virtual screening was used to screen small molecule compounds targeting Gimap5 and the anti-RSV effects were explored through in vivo and in vitro experiments. GIMAP5 and M6PR were significantly downregulated after RSV infection. Gimap5 accelerated RSV degradation in lysosomes by interacting with M6PR, and further prevented RSV invasion by downregulating the expression of RSV surface receptor IGF1R. Three small molecule compounds targeting Gimap5 were confirmed to be the agonists of Gimap5. The three compounds effectively inhibited RSV infection and RSV-induced complications. Gimap5 promotes the degradation of RSV and its receptor through interacting with M6PR. Gimap5 agonists can effectively reduce RSV infection and RSV-induced complication in vivo and in vitro, which provides a new choice for the treatment of RSV.

An in silico comparative transcriptome analysis identifying hub lncRNAs and mRNAs in brain metastatic small cell lung cancer (SCLC)

Small cell lung cancer (SCLC) is a particularly lethal subtype of lung cancer. Metastatic lung tumours lead to most deaths from lung cancer. Predicting and preventing tumour metastasis is crucially essential for patient survivability. Hence, in the current study, we focused on a comprehensive analysis of lung cancer patients' differentially expressed genes (DEGs) on brain metastasis cell lines. DEGs are analysed through KEGG and GO databases for the most critical biological processes and pathways for enriched DEGs. Additionally, we performed protein-protein interaction (PPI), GeneMANIA, and Kaplan-Meier survival analyses on our DEGs. This article focused on mRNA and lncRNA DEGs for LC patients with brain metastasis and underlying molecular mechanisms. The expression data was gathered from the Gene Expression Omnibus database (GSE161968). We demonstrate that 30 distinct genes are up-expressed in brain metastatic SCLC patients, and 31 genes are down-expressed. All our analyses show that these genes are involved in metastatic SCLC. PPI analysis revealed two hub genes (CAT and APP). The results of this article present three lncRNAs, Including XLOC_l2_000941, LOC100507481, and XLOC_l2_007062, also notable mRNAs, have a close relation with brain metastasis in lung cancer and may have a role in the epithelial-mesenchymal transition (EMT) in tumour cells.

Abnormal Gene Expression Regulation Mechanism of Myeloid Cell Nuclear Differentiation Antigen in Lung Adenocarcinoma

Lung adenocarcinoma (LA) is the main pathological type of lung cancer with a very low 5-year survival rate. In the present study, after downloading the mRNA, miRNA, and DNA methylation sequencing data from TCGA, combined with the downloaded clinical data, comparative analysis, prognostic analysis, GO and KEGG analysis, GSEA analysis, methylation analysis, transcriptional regulation and post-transcriptional regulation were performed. We found that both methylation and gene expression of MNDA in LA were down-regulated, while high expression of MNDA was associated with good overall survival in LA. To probe the mechanism, further analysis showed that SPI1 was the main transcription factor of MNDA, but it was also down-regulated in LA. At the same time, the expression of eight target miRNAs of MNDA was significantly up-regulated, and the expression of hsa-miR-33a-5p and hsa-miR-33b-5p were verified to directly target MNDA. In conclusion, the abnormal expression of MNDA in LA is the result of the combined effects of transcriptional and post-transcriptional regulation.

Deep Proteomic Analysis on Biobanked Paraffine-Archived Melanoma with Prognostic/Predictive Biomarker Read-Out

The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort's heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient's response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments.