tRF-29-79 regulates lung adenocarcinoma progression through mediating glutamine transporter SLC1A5.

In recent decades, considerable evidence has emerged indicating the involvement of tRNA-derived fragments (tRFs) in cancer progression through various mechanisms. However, the biological effects and mechanisms of tRFs in lung adenocarcinoma (LUAD) remain unclear. In this study, we screen out tRF-29-79, a 5'-tRF derived from tRNAGlyGCC, through profiling the tRF expressions in three pairs of LUAD tissues. We show that tRF-29-79 is downregulated in LUAD and downregulation of tRF-29-79 is associated with poorer prognosis. In vivo and in vitro assay reveal that tRF-29-79 inhibits proliferation, migration and invasion of LUAD cells. Mechanistically, we discovered that tRF-29-79 interacts with the RNA-binding protein PTBP1 and facilitates the transportation of PTBP1 from nucleus to cytoplasm, which regulates alternative splicing in the 3' untranslated region (UTR) of SLC1A5 pre-mRNA. Given that SLC1A5 is a core transporter of glutamine, we proved that tRF-29-79 mediate glutamine metabolism of LUAD through affecting the stability of SLC1A5 mRNA, thus exerts its anticancer function. In summary, our findings uncover the novel mechanism that tRF-29-79 participates in glutamine metabolism through interacting with PTBP1 and regulating alternative splicing in the 3' UTR of SLC1A5 pre-mRNA.

Noninvasive diagnosis of pulmonary nodules using a circulating tsRNA-based nomogram.

Evaluating the accuracy of pulmonary nodule diagnosis avoids repeated low-dose computed tomography (LDCT)/CT scans or invasive examination, yet remains a main clinical challenge. Screening for new diagnostic tools is urgent. Herein, we established a nomogram based on the diagnostic signature of five circulating tsRNAs and CT information to predict malignant pulmonary nodules. In total, 249 blood samples of patients with pulmonary nodules were selected from three different lung cancer centers. Five tsRNAs were identified in the discovery and training cohorts and the diagnostic signature was established by the randomForest algorithm (tRF-Ser-TGA-003, tRF-Val-CAC-005, tRF-Ala-AGC-060, tRF-Val-CAC-024, and tiRNA-Gln-TTG-001). A nomogram was developed by combining tsRNA signature and CT information. The high level of accuracy was identified in an internal validation cohort (n = 83, area under the receiver operating characteristic curve [AUC] = 0.930, sensitivity 100.0%, specificity 73.8%) and external validation cohort (n = 66, AUC = 0.943, sensitivity 100.0%, specificity 86.8%). Furthermore, the diagnostic ability of our model discriminating invasive malignant ones from noninvasive lesions was assessed. A robust performance was achieved in the diagnosis of invasive malignant lesions in both training and validation cohorts (discovery cohort: AUC = 0.850, sensitivity 86.0%, specificity 81.4%; internal validation cohort: AUC = 0.784, sensitivity 78.8%, specificity 78.1%; and external validation cohort: AUC = 0.837, sensitivity 85.7%, specificity 84.0%). This novel circulating tsRNA-based diagnostic model has potential significance in predicting malignant pulmonary nodules. Application of the model could improve the accuracy of pulmonary nodule diagnosis and optimize surgical plans.

Deep learning-based classification and spatial prognosis risk score on whole-slide images of lung adenocarcinoma.

AIMS: Classification of histological patterns in lung adenocarcinoma (LUAD) is critical for clinical decision-making, especially in the early stage. However, the inter- and intraobserver subjectivity of pathologists make the quantification of histological patterns varied and inconsistent. Moreover, the spatial information of histological patterns is not evident to the naked eye of pathologists. METHODS AND RESULTS: We establish the LUAD-subtype deep learning model (LSDLM) with optimal ResNet34 followed by a four-layer Neural Network classifier, based on 40 000 well-annotated path-level tiles. The LSDLM shows robust performance for the identification of histopathological subtypes on the whole-slide level, with an area under the curve (AUC) value of 0.93, 0.96 and 0.85 across one internal and two external validation data sets. The LSDLM is capable of accurately distinguishing different LUAD subtypes through confusion matrices, albeit with a bias for high-risk subtypes. It possesses mixed histology pattern recognition on a par with senior pathologists. Combining the LSDLM-based risk score with the spatial K score (K-RS) shows great capacity for stratifying patients. Furthermore, we found the corresponding gene-level signature (AI-SRSS) to be an independent risk factor correlated with prognosis. CONCLUSIONS: Leveraging state-of-the-art deep learning models, the LSDLM shows capacity to assist pathologists in classifying histological patterns and prognosis stratification of LUAD patients.

Clinical and prognostic implications of an immune-related risk model based on TP53 status in lung adenocarcinoma.

TP53 mutation is the most widespread mutation in lung adenocarcinoma (LUAD). Meanwhile, p53 (encoded by TP53) has recently been implicated in immune responses. However, it is still unknown whether TP53 mutation remodels the tumour microenvironment to influence tumour progression and prognosis in LUAD. In this study, we developed a 6-gene immune-related risk model (IRM) to predict the survival of patients with LUAD in The Cancer Genome Atlas (TCGA) cohort based on TP53 status, and the predictive ability was confirmed in 2 independent cohorts. TP53 mutation led to a decreased immune response in LUAD. Further analysis revealed that patients in the high-index group had observably lower relative infiltration of memory B cells and regulatory T cells and significantly higher relative infiltration of neutrophils and resting memory CD4+ T cells. Additionally, the IRM index positively correlated with the expression of critical immune checkpoint genes, including PDCD1 (encoding PD-1) and CD274 (encoding PD-L1), which was validated in the Nanjing cohort. Furthermore, as an independent prognostic factor, the IRM index was used to establish a nomogram for clinical application. In conclusion, this IRM may serve as a powerful prognostic tool to further optimize LUAD immunotherapy.

A novel gene expression signature-based on B-cell proportion to predict prognosis of patients with lung adenocarcinoma.

BACKGROUND: This study aimed to develop a reliable immune signature based on B-cell proportion to predict the prognosis and benefit of immunotherapy in LUAD. METHODS: The proportion of immune cells in the TCGA-LUAD dataset was estimated using MCP-counter. The Least Absolute Shrinkage and Selector Operation was used to identify a prognostic signature and validated in an independent cohort. We used quantitative reverse transcription-polymerase chain reaction (qRT-PCR) data and formalin-fixed paraffin-embedded (FFPE) specimens immunohistochemistry to illustrate the correlation between prognostic signature and leukocyte migration. RESULTS: We found that the relative abundance of B lineage positively correlated with overall survival. Then, we identified a 13-gene risk-score prognostic signature based on B lineage abundance in the testing cohort and validated it in a cohort from the GEO dataset. This model remained strongly predictive of prognoses across clinical subgroups. Further analysis revealed that patients with a low-risk score were characterized by B-cell activation and leukocyte migration, which was also confirmed in FFPE specimens by qRT-PCR and immunohistochemistry. Finally, this immune signature was an independent prognostic factor in the composite nomogram of clinical characteristics. CONCLUSIONS: In conclusion, the 13-gene immune signature based on B-cell proportion may serve as a powerful prognostic tool in LUAD.

Circular RNA circCRIM1 inhibits invasion and metastasis in lung adenocarcinoma through the microRNA (miR)-182/miR-93-leukemia inhibitory factor receptor pathway.

In recent years, circular RNAs (circRNAs) have been revealed to have important roles in carcinogenesis. Metastasis is the leading cause of lung adenocarcinoma (LUAC) death. However, the contributions of circRNA to the metastasis of LUAC remain largely unknown. Based on circBase data and our biobank tissues, we identified circCRIM1 (a circRNA derived from exons 2, 3 and 4 of the CRIM1 gene, hsa_circ_0002346) as having a significantly decreased expression in LUAC samples compared with matched normal control samples. Both in vivo and in vitro experiments revealed that circCRIM1 suppresses the invasion and metastasis of LUAC. In vitro precipitation of circRNAs, luciferase reporter assay, and biotin-coupled microRNA capture were carried out to investigate the Ago2-dependent interaction of circCRIM1 and microRNA (miR)-93/miR-182. Mechanistically, we found that circCRIM1 could promote the expression of leukemia inhibitory factor receptor, a well-known tumor suppressor, by sponging miR-93 and miR-182. In the clinical and pathological analyses, the downregulation of circCRIM1 in LUAC was significantly correlated with lymphatic metastasis and TNM stage, which served as an independent risk factor for the overall survival of patients with LUAC. Our study showed that circCRIM1 inhibits the invasion and metastasis of lung adenocarcinoma cancer cells, which makes it a potential therapeutic target.

Cell division cycle 20 overexpression predicts poor prognosis for patients with lung adenocarcinoma.

The cell division cycle 20, a key component of spindle assembly checkpoint, is an essential activator of the anaphase-promoting complex. Aberrant expression of cell division cycle 20 has been detected in various human cancers. However, its clinical significance has never been deeply investigated in non-small-cell lung cancer. By analyzing The Cancer Genome Atlas database and using some certain online databases, we validated overexpression of cell division cycle 20 in both messenger RNA and protein levels, explored its clinical significance, and evaluated the prognostic role of cell division cycle 20 in non-small-cell lung cancer. Cell division cycle 20 expression was significantly correlated with sex (p = 0.003), histological classification (p < 0.0001), and tumor size (p = 0.0116) in non-small-cell lung cancer patients. In lung adenocarcinoma patients, overexpression of cell division cycle 20 was significantly associated with bigger primary tumor size (p = 0.0023), higher MKI67 level (r = 0.7618, p < 0.0001), higher DNA ploidy level (p < 0.0001), and poor prognosis (hazard ratio = 2.39, confidence interval: 1.87-3.05, p < 0.0001). However, in lung squamous cell carcinoma patients, no significant association of cell division cycle 20 expression was observed with any clinical parameter or prognosis. Overexpression of cell division cycle 20 is associated with poor prognosis in lung adenocarcinoma patients, and its overexpression can also be used to identify high-risk groups. In conclusion, cell division cycle 20 might serve as a potential biomarker for lung adenocarcinoma patients.

Expression profile, clinical significance, and biological function of insulin-like growth factor 2 messenger RNA-binding proteins in non-small cell lung cancer.

Insulin-like growth factor 2 messenger RNA-binding proteins have been described to associate with malignant process in many cancers. However, the role of insulin-like growth factor 2 messenger RNA-binding protein family has not been thoroughly elucidated in non-small cell lung cancer. This study was to investigate the expression profile, clinical significance, and biological function of insulin-like growth factor 2 messenger RNA-binding proteins family in non-small cell lung cancer. The expression levels of IGF2BP1-IGF2BP3 in tumor and adjacent normal tissues were determined, and association with clinicopathological features and overall survival was investigated by analyzing The Cancer Genome Atlas lung cancer database. Proliferation, migration, invasion assays, and flow-cytometry analysis were used to investigate the biological function in vitro. Insulin-like growth factor 2 messenger RNA-binding protein expression levels were significantly increased in non-small cell lung cancer compared to adjacent normal lung tissues. Chi-square test indicated that IGF2BP1 and IGF2BP3 expressions correlated with some meaningful clinical characteristics in non-small cell lung cancer. Kaplan-Meier analysis showed that high-level expression of IGF2BP1 or IGF2BP3 predicted poor overall survival in lung adenocarcinoma patients. Multivariate regression analysis showed that high level of IGF2BP3 was an independent risk factor for poor prognosis in lung adenocarcinoma patients (hazard ratio = 1.616, p = 0.017). In vitro, knockdown of IGF2BP3 inhibited lung adenocarcinoma cell proliferation by inducing cell cycle arrest and apoptosis, and undermined abilities of migration and invasion, and overexpression of IGF2BP3 could promote malignant phenotypes in lung adenocarcinoma cells. Our study revealed that expression of insulin-like growth factor 2 messenger RNA-binding proteins was widely upregulated and correlated with some certain clinicopathological features in non-small cell lung cancer. Especially, in insulin-like growth factor 2 messenger RNA-binding protein family, IGF2BP3 might play the most important role in tumor aggressiveness and prognosis in lung adenocarcinoma, and IGF2BP3 might serve as a potential therapeutic target and a novel prognostic biomarker in lung adenocarcinoma patients.

Differentially expressed protein-coding genes and long noncoding RNA in early-stage lung cancer.

Due to the application of low-dose computed tomography screening, more and more early-stage lung cancers have been diagnosed. Thus, it is essential to characterize the gene expression profile of early-stage lung cancer to develop potential biomarkers for early diagnosis and therapeutic targets. Here, we analyzed microarray data of 181 early-stage lung cancer patients. By comparing gene expression between different tumor and lymph node metastasis stages, we identified various differentially expressed protein-coding genes and long noncoding RNA (lncRNA) in the comparisons of T2 vs. T2 and N1- vs. N0-stage lung cancer. Functional analyses revealed that these differentially expressed genes were enriched in various tumorigenesis or metastasis-related pathways. Survival analysis indicated that two protein-coding genes, C7 and SCN7A, were significantly associated survival of lung cancer. Notably, a novel lncRNA, LINC00313, was highly expressed in both T2- and N1-stage lung cancers. On the other hand, LINC00313 was also upregulated in lung cancer and metastasized lung cancer tissues, compared with adjacent lung tissues and primary lung cancer tissues. Additionally, higher expression level of LINC00313 indicated poor prognosis of lung cancer (hazard ratio = 0.658). Overall, we characterized the expression profiles of protein-coding genes and lncRNA in early-stage lung cancer and found that LINC00313 could be a biomarker for lung cancer.

Long noncoding RNA CCAT2 correlates with smoking in esophageal squamous cell carcinoma.

Esophageal cancer is one of the leading causes of cancer-related mortality, and most esophageal squamous cell carcinoma (ESCC) cases are located in Asian area. Recent studies about long noncoding RNAs (lncRNA) have offered a new perspective for cancer research and provided new approaches to understand the complex regulation network in cancer. Our group has reported that the novel lncRNA colon cancer-associated transcript 2 (CCAT2) has important biological function and could be a potential biomarkers in lung cancer. Here, we performed in silico analysis and characterized the expression profile of CCAT2 in a cohort of esophageal squamous cell carcinoma (ESCC) patients and cell lines. In silico analysis showed that no CpG island is found in the chromosome region of CCAT2, indicating that the expression of CCAT2 is possibly not regulated by DNA methylation. Compared with paired adjacent normal esophageal tissues, CCAT2 was significantly overexpressed in ESCC tissues with an average fold of 7.18. In ESCC cell lines, CCAT2 was mostly upregulated in KYSE410 cell (24.7-fold upregulation) when normalized to normal esophageal epithelium cell line (HEEC) and most CCAT2 transcripts were located in nucleus (> 95 %). Statistical analysis showed that CCAT2 expression level was significantly associated with smoking status (P = 0.036). Receiver operative curve and the area under curve were calculated to assess the diagnostic potential of CCAT2. Measured by area under curve (AUC), CCAT2 showed higher diagnostic performance than conventional serum biomarkers, like AFP, CA153, and NSE. In this study, we firstly characterized the expression profile of CCAT2 in ESCC and evaluated its potential diagnostic value as a biomarker.

A novel AluYb8 insertion-associated non-coding RNA, lncMUTYH, impairs mitochondrial function and dampens the M2-like polarization of macrophages.

An inverted AluYb8 insertion in the MUTYH intron 15 (AluYb8MUTYH variant) has been reported to be associated with reduced MUTYH1 expression and mitochondrial dysfunction with age. However, the underlying mechanism remains unknown. In this study, we identified a novel transcript associated with the AluYb8MUTYH variant, which revealed that this transcript is about 780 nucleotides in length with a poly-A tail, lacks protein-coding potential, referred to as lncMUTYH. The results from the reporter gene system confirmed that the lncMUTYH down-regulates MUTYH1 expression at the translational level. Site-directed mutagenesis on the 5'-terminal exon sequences of α-MUTYH and lncMUTYH constructs revealed that lncMUTYH can act as a trans-regulator that depends on the partial base pairing between its exonized AluYb8 sequence and the 5'UTR of α-MUTYH to impede MUTYH 1 expression. Furthermore, we have demonstrated a correlation between decreased mitochondrion-localized MUTYH1 caused by lncMUTYH and lowered levels of mitochondrial biological function indicators, such as mtDNA content, mitochondrial regulatory gene expression, oxygen consumption rate, ATP product, and mitochondrial respiratory capacity. Notably, we found that lncMUTYH inhibited the M2-like polarization of macrophages, and CD68/CD206-positive cell fractions were significantly lower in lncMUTYH ectopically expressing cells. The results confirmed that the AluYb8MUTYH-associated lncMUTYH, derived from an AluYb8 insertion mutation, acts as a trans-regulatory factor that inhibits the MUTYH1 protein expression, leading to a progressive mitochondrial dysfunction that may disrupt macrophage differentiation. In summary, lncMUTYH can contribute to AluYb8MUTYH-associated mitochondrial dysfunction with age and hamper the macrophage polarization process, potentially increasing the risk of developing age-related diseases.

A novel non-coding RNA was identified derived from the AluYb8 insertion in the MUTYH gene, namely lncMUTYH.LncMUTYH selectively decreased the MUTYH1 protein localized in mitochondrial, which is dependent on the sequence and orientation derived from AluYb8 insertion.Overexpression of lncMUTYH dampens the mitochondrial function and M2-like polarization of macrophages, partly due to the suppression of the MUTYH1 protein.

A pro-metastatic tRNA fragment drives aldolase A oligomerization to enhance aerobic glycolysis in lung adenocarcinoma.

Despite being the leading cause of lung cancer-related deaths, the underlying molecular mechanisms driving metastasis progression are still not fully understood. Transfer RNA-derived fragments (tRFs) have been implicated in various biological processes in cancer. However, the role of tRFs in lung adenocarcinoma (LUAD) remains unclear. Our study identified a tRF, tRF-Val-CAC-024, associated with the high-risk component of LUAD, through validation using 3 cohorts. Our findings demonstrated that tRF-Val-CAC-024 acts as an oncogene in LUAD. Mechanistically, tRF-Val-CAC-024 was revealed to bind to aldolase A (ALDOA) dependent on Q125/E224 and promote the oligomerization of ALDOA, resulting in increased enzyme activity and enhanced aerobic glycolysis in LUAD cells. Additionally, we provide preliminary evidence of its potential clinical value by investigating the therapeutic effects of tRF-Val-CAC-024 antagomir-loaded lipid nanoparticles (LNPs) in cell-line-derived xenograft models. These results could enhance our understanding of the regulatory mechanisms of tRFs in LUAD and provide a potential therapeutic target.

The recruitment of CD8+ T cells through YBX1 stabilization abrogates tumor intrinsic oncogenic role of MIR155HG in lung adenocarcinoma.

Previous studies revealed that MIR155HG possessed an oncogenic role in many types of tumors including lung adenocarcinoma (LUAD), along with higher expression in tumors. However, in our study, we observed a positive correlation between MIR155HG expression and overall survival across different cohorts. The transferred PBMC on the NCG mouse model abrogated the tumor intrinsic oncogenic role of MIR155HG in LUAD. Upregulation of MIR155HG positively correlated with CD8+ T cell infiltration both in vitro and in vivo, as well as LUAD tissues. Mechanistically, we revealed that MIR155HG increased the cytokine CCL5 expression at the transcriptional level, which depended on the interaction between MIR155HG and YBX1 protein, a novel transcription factor of CCL5, resulting in the more protein stability of YBX1 through dampening ubiquitination. Additionally, we also observed that MIR155 could increase PD-L1 expression to hamper the activity of recruited CD8+ T cells, which could be rescued through PD-L1 mAb addition. Finally, we uncovered that patients with high MIR155HG expression had a higher response rate to immunotherapy, and the combination of MIR155HG overexpression and PD-L1 mAb increased the efficacy of PD-L1 mAb. Together, our study provides a novel biomarker and potential combination treatment strategy for patients who received immunotherapy.

Deep learning-based detection and semi-quantitative model for spread through air spaces (STAS) in lung adenocarcinoma.

Tumor spread through air spaces (STAS) is a distinctive metastatic pattern affecting prognosis in lung adenocarcinoma (LUAD) patients. Several challenges are associated with STAS detection, including misdetection, low interobserver agreement, and lack of quantitative analysis. In this research, a total of 489 digital whole slide images (WSIs) were collected. The deep learning-based STAS detection model, named STASNet, was constructed to calculate semi-quantitative parameters associated with STAS density and distance. STASNet demonstrated an accuracy of 0.93 for STAS detection at the tiles level and had an AUC of 0.72-0.78 for determining the STAS status at the WSI level. Among the semi-quantitative parameters, T10S, combined with the spatial location information, significantly stratified stage I LUAD patients on disease-free survival. Additionally, STASNet was deployed into a real-time pathological diagnostic environment, which boosted the STAS detection rate and led to the identification of three easily misidentified types of occult STAS.

Ferritinophagy mediates adaptive resistance to EGFR tyrosine kinase inhibitors in non-small cell lung cancer.

Osimertinib (Osi) is a widely used epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI). However, the emergence of resistance is inevitable, partly due to the gradual evolution of adaptive resistant cells during initial treatment. Here, we find that Osi treatment rapidly triggers adaptive resistance in tumor cells. Metabolomics analysis reveals a significant enhancement of oxidative phosphorylation (OXPHOS) in Osi adaptive-resistant cells. Mechanically, Osi treatment induces an elevation of NCOA4, a key protein of ferritinophagy, which maintains the synthesis of iron-sulfur cluster (ISC) proteins of electron transport chain and OXPHOS. Additionally, active ISC protein synthesis in adaptive-resistant cells significantly increases the sensitivity to copper ions. Combining Osi with elesclomol, a copper ion ionophore, significantly increases the efficacy of Osi, with no additional toxicity. Altogether, this study reveals the mechanisms of NCOA4-mediated ferritinophagy in Osi adaptive resistance and introduces a promising new therapy of combining copper ionophores to improve its initial efficacy.

The Role of tRNA-Centered Translational Regulatory Mechanisms in Cancer.

Cancer is a leading cause of morbidity and mortality worldwide. While numerous factors have been identified as contributing to the development of malignancy, our understanding of the mechanisms involved remains limited. Early cancer detection and the development of effective treatments are therefore critical areas of research. One class of molecules that play a crucial role in the transmission of genetic information are transfer RNAs (tRNAs), which are the most abundant RNA molecules in the human transcriptome. Dysregulated synthesis of tRNAs directly results in translation disorders and diseases, including cancer. Moreover, various types of tRNA modifications and the enzymes responsible for these modifications have been implicated in tumor biology. Furthermore, alterations in tRNA modification can impact tRNA stability, and impaired stability can prompt the cleavage of tRNAs into smaller fragments known as tRNA fragments (tRFs). Initially believed to be random byproducts lacking any physiological function, tRFs have now been redefined as non-coding RNA molecules with distinct roles in regulating RNA stability, translation, target gene expression, and other biological processes. In this review, we present recent findings on translational regulatory models centered around tRNAs in tumors, providing a deeper understanding of tumorigenesis and suggesting new directions for cancer treatment.

High­risk pathological subtype associated FAM83A­AS1 promotes malignancy and glycolysis of lung adenocarcinoma via miR­202­3p/HK2 axis.

According to the diverse cellular morphology, lung adenocarcinoma (LUAD) was classified into five pathological subtypes, referred to as follows: High­risk group (micropapillary and solid), intermediate­risk group (acinar and papillary) and low­risk group (epidic). Nevertheless, little is known about the biological function of long non­coding RNA (lncRNA) in the molecular determination of LUAD histologic patterns. Screening the transcriptional expression data from TCGA­LUAD, the differentially expressed lncRNA across the divergent pathological subtypes were explored. Pan­cancer analysis revealed the characteristic of FAM83A­AS1, which was also confirmed in the LUAD tissues. The function of FAM83A­AS1 was uncovered through the in vitro assays. RNA immunoprecipitation and dual­luciferase reporter assays were performed to explore the molecular mechanisms of FAM83A­AS1. In the present study, it was identified that the expression of FAM83A­AS1 was increased from the low­risk group to the high, which was associated with a poorer prognosis and higher risk of recurrence. Pan­cancer analysis revealed that FAM83A­AS1 was positively correlated with high tumor mutational burden. Additionally, FAM83A­AS1 promoted cell migration, invasion and growth of LUAD cancer cells. Mechanistically, FAM83A­AS1 sponged miR­202­3p to regulate the expression of hexokinase II (HK2) in post­transcription, which facilitated the malignancy and glycolysis. The present study uncovered the biological roles of FAM83A­AS1/miR­202­3p/HK2 axis in regulating malignancy and glycolysis of LUAD, which provided novel avenues to addressing the determination of histologic patterns.

N6 -methyladenosine-modified circFUT8 competitively interacts with YTHDF2 and miR-186-5p to stabilize FUT8 mRNA to promote malignant progression in lung adenocarcinoma.

BACKGROUND: Lung cancer is the leading cause of cancer related to mortality worldwide, and the main pathological type is lung adenocarcinoma (LUAD). Circular RNAs (circRNAs) have been reported to be modified by N6 -methyladenosine (m6A), which is involved in the progression of diverse tumors. However, the crosstalk between circRNAs and m6A modification has not been well elucidated in LUAD. METHODS: MeRIP-seq and YTHDF2-RIP-seq datasets were explored to identify candidate circRNAs modified by YTHDF2. Dual-luciferase reporter assay, RIP, and rescue assays were performed to explore the relationship between circFUT8 and its parent mRNA of FUT8. In vitro and in vivo experiments were utilized to uncover the function of circFUT8. RESULTS: In this study, we identified a novel m6A-modified circFUT8, derived from exon 3 of FUT8, which was elevated in tumor tissues compared with adjacent noncancerous tissues. The m6A reader YTHDF2 recognized and destabilized circFUT8 in an m6A-dependent manner. YTHDF2 also combined with the line form of FUT8 (mFUT8), and circFUT8 competitively interacted with YTHDF2, blunting its binding to mFUT8, to stabilize the mRNA level of FUT8. Additionally, circFUT8 sponged miR-186-5p to elevate the expression of mFUT8. Finally, we revealed that circFUT8 promoted the malignant progression of LUAD dependent on the oncogenic function of FUT8. CONCLUSIONS: These findings identified a novel m6A-modified circFUT8 recognized and destabilized by YTHDF2, which competitively interacted with YTHDF2 and miR-186-5p to stabilize FUT8 mRNA to promote malignant progression in LUAD.

C-IGF1R encoded by cIGF1R acts as a molecular switch to restrict mitophagy of drug-tolerant persister tumour cells in non-small cell lung cancer.

The clinical efficacy of Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors (EGFR-TKIs) is limited by the emergence of drug resistance. We hypothesise that restoring dysregulated circular RNAs under initial treatment with EGFR-TKIs may enhance their effectiveness. Through high-throughput screening, we identify that combining circular RNA IGF1R (cIGF1R) with EGFR-TKIs significantly synergises to suppress tumour regrowth following drug withdrawal. Mechanistically, cIGF1R interacts with RNA helicase A (RHA) to depress insulin-like growth factor 1 receptor (IGF1R) mRNA splicing, negatively regulating the parent IGF1R signalling pathway. This regulation is similar to that of IGF1R inhibitor, which induces drug-tolerant persister (DTP) state with activated mitophagy. The cIGF1R also encodes a peptide C-IGF1R that reduces Parkin-mediated ubiquitination of voltage-dependent anion channel 1 (VDAC1) to restrict mitophagy, acting as a molecular switch that promotes the transition of DTP to apoptosis. Our study shows that combining cIGF1R with EGFR-TKIs efficiently reduces the emergence of DTP.

The super-enhancer-driven lncRNA LINC00880 acts as a scaffold between CDK1 and PRDX1 to sustain the malignance of lung adenocarcinoma.

Super-enhancers (SEs) are regulatory element clusters related to cell identity and disease. While the studies illustrating the function of SE-associated long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD) remains few. In our research, a SE-driven lncRNA, LINC00880, was identified, which showed higher expression in LUAD compared to normal tissues and indicated worse outcomes in stage I LUADs. We found that the transcription factor (TF) FOXP3 could simultaneously occupy the promoter and SE regions of LINC00880 to promote its transcription. The oncogenic function of LINC00880 was validated both in vitro and in vivo. Mechanically, LINC00880 binds to the protein CDK1 to increase its kinase activity, which rely on the phosphorylation state of pT161 in CDK1. LINC00880 also promotes the interaction between CDK1 and PRDX1. Moreover, LINC00880 interacts with PRDX1, which indicates that LINC00880 acts as a protein scaffold between CDK1 and PRDX1 to form a ternary complex, thereby resulting in the activation of PI3K/AKT to promote malignancy. Our results reveal that the SE-associated lncRNA LINC00880 regulates the CDK1/PRDX1 axis to sustain the malignancy of LUAD, providing a novel therapeutic target.