m6A-binding protein IGF2BP1 promotes the malignant phenotypes of lung adenocarcinoma

The m6A reader IGF2BP1 contributes to the activation of hepatic stellate cells through facilitating TUBB4B mRNA stabilization

The m6A reader insulin-like growth factor-2 mRNA-binding protein 1 (IGF2BP1) is involved in multiple pathophysiological processes through enhanced expression of the proteins encoded by their target mRNAs. However, the functional role of IGF2BP1-mediated m6A in liver fibrosis remains elusive. Here, we report that IGF2BP1 is highly expressed in activated hepatic stellate cells (HSCs), the major driver of fibrogenesis, and TUBB4B is identified as a potential target of IGF2BP1 by re-analysis of the RNA-seq, RIP-seq, and m6A-seq data. The relevant findings were subsequently demonstrated by a series of molecular and cellular evidences. The knockdown of IGF2BP1 or TUBB4B and pharmacological inhibition of TUBB4B by mebendazole treatments significantly suppress the proliferation, migration, and activation of HSCs. Mechanistically, IGF2BP1 upregulates TUBB4B expression through stabilizing TUBB4B in an m6A-dependent manner, and TUBB4B induces liver fibrosis by activating the FAK signaling pathway. Collectively, our results indicate that targeting IGF2BP1/TUBB4B/FAK axis in HSCs could be a promising therapeutic approach for liver fibrosis.

A novel subtype based on driver methylation-transcription in lung adenocarcinoma

AIMS

To identify driver methylation genes and a novel subtype of lung adenocarcinoma (LUAD) by multi-omics and elucidate its molecular features and clinical significance.

METHODS

We collected LUAD patients from public databases, and identified driver methylation genes (DMGs) by MethSig and MethylMix algrothms. And novel driver methylation multi-omics subtypes were identified by similarity network fusion (SNF). Furthermore, the prognosis, tumor microenvironment (TME), molecular features and therapy efficiency among subtypes were comprehensively evaluated.

RESULTS

147 overlapped driver methylation were identified and validated. By integrating the mRNA expression and methylation of DMGs using SNF, four distinct patterns, termed as S1-S4, were characterized by differences in prognosis, biological features, and TME. The S2 subtype showed unfavorable prognosis. By comparing the characteristics of the DMGs subtypes with the traditional subtypes, S3 was concentrated in proximal-inflammatory (PI) subtype, and S4 was consisted of terminal respiratory unit (TRU) subtype and PI subtype. By analyzing TME and epithelial mesenchymal transition (EMT) features, increased immune infiltration and higher expression of immune checkpoint genes were found in S3 and S4. While S4 showed higher EMT score and expression of EMT associated genes, indicating S4 may not be as immunosensitive as the S3. Additionally, S3 had lower TIDE and higher IPS score, indicating its increased sensitivity to immunotherapy.

CONCLUSION

The driver methylation-related subtypes of LUAD demonstrate prognostic predictive ability that could help inform treatment response and provide complementary information to the existing subtypes.

Implications of GCLC in prognosis and immunity of lung adenocarcinoma and multi-omics regulation mechanisms

BACKGROUND

Ferroptosis is an iron-dependent type of regulated cell death, and has been implicated in lung adenocarcinoma (LUAD). Evidence has proved the key role of glutamate-cysteine ligase catalytic subunit (GCLC) in ferroptosis, but its role in LUAD remains unclear. Herein, we explored the implications of GCLC and relevant genes in LUAD prognosis and immunity as well as underlying molecular mechanisms.

METHODS

This work gathered mRNA, miRNA, DNA methylation, somatic mutation and copy-number variation data from TCGA-LUAD. WGCNA was utilized for selecting GCLC-relevant genes, and a GCLC-relevant prognostic signature was built by uni- and multivariate-cox regression analyses. Immune compositions were estimated via CIBERSORT, and two immunotherapy cohorts of solid tumors were analyzed. Multi-omics regulatory mechanisms were finally assessed.

RESULTS

Our results showed that GCLC was overexpressed in LUAD, and potentially resulted in undesirable survival. A prognostic model was generated, which owned accurate and independent performance in prognostication. GCLC, and relevant genes were notably connected with immune compositions and immune checkpoints. High GCLC expression was linked with better responses to anti-PD-L1 and anti-CTLA-4 treatment. Their possible DNA methylation sites were inferred, e.g., hypomethylation in cg19740353 might contribute to GCLC up-regulation. Frequent genetic mutations also affected their expression. Upstream transcription factors (E2F1/3/4, etc.), post-transcriptional regulation of miRNAs (hsa-mir-30c-1, etc.), lncRNAs (C8orf34-AS1, etc.), and IGF2BP1-mediated m6A modification were identified. It was also found NOP58-mediated SUMOylation post-translational modification.

CONCLUSIONS

Together, we show that GCLC and relevant genes exert crucial roles in LUAD prognosis and immunity, and their expression can be controlled by complex multi-omics mechanisms.

Implications of different cell death patterns for prognosis and immunity in lung adenocarcinoma

In recent years, lung adenocarcinoma (LUAD) has become a focus of attention due to its low response to treatment, poor prognosis, and lack of reliable indicators to predict the progression or therapeutic effect of LUAD. Different cell death patterns play a crucial role in tumor development and are promising for predicting LUAD prognosis. From the TCGA and GEO databases, we obtained bulk transcriptomes, single-cell transcriptomes, and clinical information. Genes in 15 types of cell death were analyzed for cell death index (CDI) signature establishment. The CDI signature using necroptosis + immunologic cell death-related genes was established in the TCGA cohort with the 1-, 2-, 3-, 4- and 5-year AUC values were 0.772, 0.736, 0.723, 0.795, and 0.743, respectively. The prognosis was significantly better in the low CDI group than in the high CDI group. We also investigated the relationship between the CDI signature and clinical variables, published prognosis biomarkers, immune cell infiltration, functional enrichment pathways, and immunity biomarkers. In vitro assay showed that HNRNPF and FGF2 promoted lung cancer cell proliferation and migration and were also involved in cell death. Therefore, as a robust prognosis biomarker, CDI signatures can screen for patients who might benefit from immunotherapy and improve diagnostic accuracy and LUAD patient outcomes.