Identification of the GTPase IMAP family as an immune-related prognostic biomarker in the breast cancer tumor microenvironment

Identification and validation of GIMAP family genes as immune-related prognostic biomarkers in lung adenocarcinoma

Background

The GIMAP family genes play a key role in immune function. Increasing evidence suggests that GIMAP genes were implicated in the tumorigenesis of lung adenocarcinoma (LUAD). This study aimed to investigate the clinical significance of GIMAP family genes in LUAD.

Methods

In this study, we explored the expression, mutation, prognostic value of GIMAP family genes and the correlation with immune microenvironment in LUAD. We further investigated the relationship between GIMAP family genes expression and immunotherapy response in GEO LUAD and melanoma cohorts.

Results

Among the GIMAP family genes, the expression levels of GIMAP1, GIMAP2, GIMAP4, GIMAP5, GIMAP6, GIMAP7, and GIMAP8 were significantly lower in LUAD tumor tissues than normal tissues. Most GIMAP genes were closely related to age, tumor grade and T stage, but not significantly related to sex, N stage and M stage. In the overall population, patients with high expression of GIMAP family genes had a significant longer overall survival (OS). GO and KEGG enrichment analysis showed that GIMAP family genes were highly enriched in immune-related biological process. The expression of GIMAP family genes was positively correlated with immune cell infiltration and immune checkpoint molecules. Furthermore, high expression of GIMAP family genes were correlated with therapeutic response to immunotherapy in LUAD and melanoma patients.

Conclusion

In this study, we identified that GIMAP family genes were significantly associated with immune cell infiltration and immune checkpoint molecules. They potentially play a critical role in anti-tumor immunity and serve as immunotherapy biomarkers.

Transcriptome analysis of host anti-Aeromonas hydrophila infection revealed the pathogenicity of A. hydrophila to American eels (Anguilla rostrata)

Aeromonas hydrophila is a commonly pathogenic bacterium in cultivated eels, but its pathogenicity to American eel (Anguilla rostrata) and the molecular mechanism of host anti-A. hydrophila infection remains uncertain. In this study, LD50 of A. hydrophila to American eels was determined and bacterial load in the liver and kidney of eels was assessed post 2.56 doses of LD50 of A. hydrophila infection. The results showed that the LD50 of A. hydrophila to American eels was determined to be 3.9 × 105 cfu/g body weight (7.8 × 106 cfu/fish), and the bacterial load peaked at 36 h post the infection (hpi) in the liver. Then, the histopathology was highlighted by congestion in splenic blood vessels, atrophied glomeruli, and necrotic hepatocytes. Additionally, the results of qRT-PCR revealed that 18 host immune-related genes showed significantly up or downregulated post-infection compare to that of pre-infection. Finally, results of the RNA-seq revealed 10 hub DEGs and 7 encoded proteins play essential role to the anti-A. hydrophila infection in American eels. Pathogenicity of A. hydrophila to American eels and RNA-seq of host anti-A. hydrophila infection were firstly reported in this study, shedding new light on our understanding of the A. hydrophila pathogenesis and the host immune response to the A. hydrophila infection strategies in gene transcript.

Transcriptome Analysis of Host Anti-Vibrio harveyi Infection Revealed the Pathogenicity of V. harveyi to American Eel (Anguilla rostrata)

Vibrio harveyi, a recently discovered pathogenic bacterium isolated from American eels (Anguilla rostrata), poses uncertainties regarding its pathogenesis in American eel and the molecular mechanisms underlying host defense against V. harveyi infection. This study aimed to determine the LD50 of V. harveyi in American eel and assess the bacterial load in the liver, spleen, and kidney post-infection with the LD50 dose. The results showed that the LD50 of V. harveyi via intraperitoneal injection in American eels over a 14d period was determined to be 1.24 × 103 cfu/g body weight (6.2 × 104 cfu/fish). The peak bacterial load occurred at 36 h post-infection (hpi) in all three organs examined. Histopathology analysis revealed hepatic vein congestion and thrombi, tubular vacuolar degeneration, and splenic bleeding. Moreover, quantitative reverse transcription polymerase chain reaction (qRT-PCR) results indicated significant up or downregulation of 18 host immune- or anti-infection-related genes post 12 to 60 hpi following the infection. Additionally, RNA sequencing (RNA-seq) unveiled 7 hub differentially expressed genes (DEGs) and 11 encoded proteins play crucial roles in the anti-V. harveyi response in American eels. This study firstly represents the comprehensive report on the pathogenicity of V. harveyi to American eels and RNA-seq of host's response to V. harveyi infection. These findings provide valuable insights into V. harveyi pathogenesis and the strategies employed by the host's immune system at the transcriptomic level to combat V. harveyi infection.

GIMAP7 inhibits epithelial-mesenchymal transition and glycolysis in lung adenocarcinoma cells via regulating the Smo/AMPK signaling pathway

BACKGROUND

GTPase immunity-associated protein 7 (GIMAP7) has been previously recognized as a prognostic marker in pan-cancer. Our objective was to explore the function of GIMAP7 in the progression of lung adenocarcinoma (LUAD).

METHODS

GIMAP7 was overexpressed by transfection with GIMAP7 plasmid, and knocked down using siRNAs. The biological functions of GIMAP7 were examined by employing CCK-8, EdU, colony formation, flow cytometry, wound healing, and transwell assays. The effects of GIMAP7 on the extracellular acidification rate (ECAR), oxygen consumption rate (OCR), lactate production, and glucose uptake were evaluated. In addition, the related mRNA and protein expression was detected employing immunohistochemical, western blot, and qRT-PCR. A xenograft tumor model was established in nude mice to evaluate the effects of GIMAP7 on tumor growth.

RESULTS

GIMAP7 was lowly expressed in LUAD tissues and cells. GIMAP7 inhibited the proliferation, mobility, EMT, glycolysis, but promoted apoptosis in LUAD cells. Moreover, we also confirmed that GIMAP7 suppressed Smo/AMPK signaling in LUAD cells. By adding the Smo agonist SAG and AMPK agonist GSK621, the results of rescue experiments further verified that GIMAP7 played a role in LUAD inhibition through inhibition of the Smo/AMPK signaling pathway. Furthermore, the role of GIMAP7 in inhibiting tumor growth was verified in vivo.

CONCLUSIONS

These results demonstrate that GIMAP7 could inhibit cell proliferation, mobility and glycolysis, but accelerate apoptosis via repressing the Smo/AMPK signaling pathway in LUAD.

GIMAP7 induces oxidative stress and apoptosis of ovarian granulosa cells in polycystic ovary syndrome by inhibiting sonic hedgehog signalling pathway

Polycystic ovary syndrome (PCOS) is a gynaecological endocrine disease. The objective of the present study was to investigate the role of GTPase immunity-associated protein (GIMAP) 7 in PCOS. A PCOS rat model was established using dehydroepiandrosterone injection. The data showed that GIMAP7 was mainly located in granulosa cells and was abundantly expressed in the ovarian granulosa cells of PCOS rats. GIMAP7 silencing decreased blood glucose levels, HOMA-IR scores, and number of cystic follicles. In addition, GIMAP7 silencing corrected erratic oestrous cycles, inhibited apoptosis and reduced c-caspase-3 protein expression in the ovarian tissues of PCOS rats. GIMAP7 silencing reduced malondialdehyde (MDA) but increased glutathione (GSH) and superoxide dismutase (SOD) levels in the serum and ovarian tissues of PCOS rats. The effects of GIMAP7 were further investigated in human ovarian granulosa KGN cells. GIMAP7 silencing increased the viability, promoted proliferation, and increased the percentage of S-phase KGN cells. The apoptosis rate was significantly decreased by GIMAP7 silencing. GIMAP7 also inhibited oxidative stress in KGN cells, resulting in decreased levels of reactive oxygen species (ROS) and MDA and increased levels of GSH and SOD. Notably, GIMAP7 inhibited the sonic hedgehog (SHH) signalling pathway, and GIMAP7 silencing increased the expression of the SHH signalling pathway downstream genes SHH, SMO, and Gli1. Inhibition of the SHH signalling pathway using cyclopamine reduced the effect of GIMAP7 silencing on KGN cells. This study proved that GIMAP7 promotes oxidative stress and apoptosis in ovarian granulosa cells in PCOS by inhibiting the SHH signalling pathway.

Identification and Validation of Immune-Related Long Non-Coding RNA Signature for Predicting Immunotherapeutic Response and Prognosis in NSCLC Patients Treated With Immunotherapy

Background

Numerous studies have reported that long non-coding RNAs (lncRNAs) play important roles in immune-related pathways in cancer. However, immune-related lncRNAs and their roles in predicting immunotherapeutic response and prognosis of non-small cell lung cancer (NSCLC) patients treated with immunotherapy remain largely unexplored.

Methods

Transcriptomic data from NSCLC patients were used to identify novel lncRNAs by a custom pipeline. ImmuCellAI was utilized to calculate the infiltration score of immune cells. The marker genes of immunotherapeutic response-related (ITR)-immune cells were used to identify immune-related (IR)-lncRNAs. A co-expression network was constructed to determine their functions. LASSO and multivariate Cox analyses were performed on the training set to construct an immunotherapeutic response and immune-related (ITIR)-lncRNA signature for predicting the immunotherapeutic response and prognosis of NSCLC. Four independent datasets involving NSCLC and melanoma patients were used to validate the ITIR-lncRNA signature.

Results

In total, 7,693 novel lncRNAs were identified for NSCLC. By comparing responders with non-responders, 154 ITR-lncRNAs were identified. Based on the correlation between the marker genes of ITR-immune cells and lncRNAs, 39 ITIR-lncRNAs were identified. A co-expression network was constructed and the potential functions of 38 ITIR-lncRNAs were annotated, most of which were related to immune/inflammatory-related pathways. Single-cell RNA-seq analysis was performed to confirm the functional prediction results of an ITIR-lncRNA, LINC01272. Four-ITIR-lncRNA signature was identified and verified for predicting the immunotherapeutic response and prognosis of NSCLC. Compared with non-responders, responders had a lower risk score in both NSCLC datasets (P<0.05). NSCLC patients in the high-risk group had significantly shorter PFS/OS time than those in the low-risk group in the training and testing sets (P<0.05). The AUC value was 1 of responsiveness in the training set. In melanoma validation datasets, patients in the high-risk group also had significantly shorter OS/PFS time than those in the low-risk group (P<0.05). The ITIR-lncRNA signature was an independent prognostic factor (P<0.001).

Conclusion

Thousands of novel lncRNAs in NSCLC were identified and characterized. In total, 39 ITIR-lncRNAs were identified, 38 of which were functionally annotated. Four ITIR-lncRNAs were identified as a novel ITIR-lncRNA signature for predicting the immunotherapeutic response and prognosis in NSCLC patients treated with immunotherapy.

Identification of Biomarkers Associated With CD4+ T-Cell Infiltration With Gene Coexpression Network in Dermatomyositis

Background

Dermatomyositis is an autoimmune disease characterized by damage to the skin and muscles. CD4⁺ T cells are of crucial importance in the occurrence and development of dermatomyositis (DM). However, there are few bioinformatics studies on potential pathogenic genes and immune cell infiltration of DM. Therefore, this study intended to explore CD4⁺ T-cell infiltration–associated key genes in DM and construct a new model to predict the level of CD4⁺ T-cell infiltration in DM.

Methods

GSE46239, GSE142807, GSE1551, and GSE193276 datasets were downloaded. The WGCNA and CIBERSORT algorithms were performed to identify the most correlated gene module with CD4⁺ T cells. Matascape was used for GO enrichment and KEGG pathway analysis of the key gene module. LASSO regression analysis was used to identify the key genes and construct the prediction model. The correlation between the key genes and CD4⁺ T-cell infiltration was investigated. GSEA was performed to research the underlying signaling pathways of the key genes. The key gene-correlated transcription factors were identified through the RcisTarget and Gene-motif rankings databases. The miRcode and DIANA-LncBase databases were used to build the lncRNA-miRNA-mRNA network.

Results

In the brown module, 5 key genes (chromosome 1 open reading frame 106 (C1orf106), component of oligomeric Golgi complex 8 (COG8), envoplakin (EVPL), GTPases of immunity-associated protein family member 6 (GIMAP6), and interferon-alpha inducible protein 6 (IFI6)) highly associated with CD4⁺ T-cell infiltration were identified. The prediction model was constructed and showed better predictive performance in the training set, and this satisfactory model performance was validated in another skin biopsy dataset and a muscle biopsy dataset. The expression levels of the key genes promoted the CD4⁺ T-cell infiltration. GSEA results revealed that the key genes were remarkably enriched in many immunity-associated pathways, such as JAK/STAT signaling pathway. The cisbp_M2205, transcription factor-binding site, was enriched in C1orf106, EVPL, and IF16. Finally, 3,835 lncRNAs and 52 miRNAs significantly correlated with key genes were used to build a ceRNA network.

Conclusion

The C1orf106, COG8, EVPL, GIMAP6, and IFI6 genes are associated with CD4⁺ T-cell infiltration. The prediction model constructed based on the 5 key genes may better predict the level of CD4⁺ T-cell infiltration in damaged muscle and lesional skin of DM. These key genes could be recognized as potential biomarkers and immunotherapeutic targets of DM.