Microbes for lung cancer detection: feasibility and limitations.

As the second most common cancer in the world, the development of lung cancer is closely related to factors such as heredity, environmental exposure, and lung microenvironment, etc. Early screening and diagnosis of lung cancer can be helpful for the treatment of patients. Currently, CT screening and histopathologic biopsy are widely used in the clinical detection of lung cancer, but they have many disadvantages such as false positives and invasive operations. Microbes are another genome of the human body, which has recently been shown to be closely related to chronic inflammatory, metabolic processes in the host. At the same time, they are important players in cancer development, progression, treatment, and prognosis. The use of microbes for cancer therapy has been extensively studied, however, the diagnostic role of microbes is still unclear. This review aims to summarize recent research on using microbes for lung cancer detection and present the current shortcomings of microbes in collection and detection. Finally, it also looks ahead to the clinical benefits that may accrue to patients in the future about screening and early detection.

Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.

Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing "danger signals" to stimulate the body's immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.

Clinical research progress of ridaforolimus (AP23573, MK8668) over the past decade: a systemic review.

Rapamycin, an established mTOR inhibitor in clinical practice, is widely recognized for its therapeutic efficacy. Ridaforolimus, a non-prodrug rapalog, offers improved aqueous solubility, stability, and affinity compared to rapamycin. In recent years, there has been a surge in clinical trials involving ridaforolimus. We searched PubMed for ridaforolimus over the past decade and selected clinical trials of ridaforolimus to make a summary of the research progress of ridaforolimus in clinical trials. The majority of these trials explored the application of ridaforolimus in treating various tumors, including endometrial cancer, ovarian cancer, prostate cancer, breast cancer, renal cell carcinoma, and other solid tumors. These trials employed diverse drug combinations, incorporating agents such as ponatinib, bicalutamide, dalotuzumab, MK-2206, MK-0752, and taxanes. The outcomes of these trials unveiled the diverse potential applications of ridaforolimus in disease treatment. Our review encompassed analyses of signaling pathways, ridaforolimus as a single therapeutic agent, its compatibility in combination with other drugs, and an assessment of adverse events (AEs). We conclude by recommending further research to advance our understanding of ridaforolimus's clinical applications.

Deciphering the heterogeneity dominated by tumor-associated macrophages for survival prognostication and prediction of immunotherapy response in lung adenocarcinoma.

Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The "BayesPrism" and "Seurat" R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

OTUB1 Targets CHK1 for Deubiquitination and Stabilization to Facilitate Lung Cancer Progression and Radioresistance.

PURPOSE: Radioresistance of lung cancer poses a significant challenge when it comes to the treatment of advanced, recurrent, and metastatic cases. Ovarian tumor domain ubiquitin aldehyde binding 1 (OTUB1) is a key member of the deubiquitinase OTU superfamily. This protein is involved in various cellular functions, including cell proliferation, iron death, lipid metabolism, and cytokine secretion as well as immune response processes. However, its specific role and molecular mechanism in lung cancer radioresistance remain to be clarified. METHODS AND MATERIALS: The expression levels of OTUB1 in paired lung cancer tissues were determined by immunohistochemistry. In vitro and in vivo experiments were conducted to investigate the impact of OTUB1 on the growth and proliferation of lung cancer. Coimmunoprecipitation and Western blotting techniques were performed to examine the interaction between OTUB1 and CHK1. The DNA damage response was measured by comet tailing and immunofluorescence staining. KEGG pathways and Gene Ontology terms were analyzed based on RNA sequencing. RESULTS: Our findings reveal a high frequency of OTUB1 overexpression, which is associated with an unfavorable prognosis in patients with lung cancer. Through comprehensive investigations, we demonstrate that OTUB1 depletion impairs the process of DNA damage repair and overcomes radioresistance. In terms of the underlying mechanism, our study uncovers that OTUB1 deubiquitinates and stabilizes CHK1, which enhances CHK1 stability, thereby regulating DNA damage and repair. Additionally, we identify CHK1 as the primary downstream effector responsible for mediating the functional effects exerted by OTUB1 specifically in lung cancer. Importantly, OTUB1 has the potential to be a valuable marker for improving the efficacy of radiation therapy for lung adenocarcinoma. CONCLUSIONS: These findings unveil a novel role for OTUB1 in enhancing radioresistance by deubiquitination and stabilization of the expression of CHK1 in lung cancer and indicate that targeting OTUB1 holds great potential as an effective therapeutic approach for enhancing the efficacy of radiation therapy in lung cancer.

Design of target response wettability switchable core-shell-shell electrochemiluminescence nanoprobes for sensitive hyaluronidase detection.

Electrochemiluminescence nanoprobes with a core-shell-shell structure have been designed and applied for hyaluronidase detection. The nanoprobes can precipitate efficiently through target-regulation wettability for collection, and enrich near to the hydrophobic electrode surface through hydrophobic interaction to enhance the performance of the biosensor.

Progress in understanding and treating idiopathic pulmonary fibrosis: recent insights and emerging therapies.

Idiopathic pulmonary fibrosis (IPF) is a long-lasting, continuously advancing, and irrevocable interstitial lung disorder with an obscure origin and inadequately comprehended pathological mechanisms. Despite the intricate and uncharted causes and pathways of IPF, the scholarly consensus upholds that the transformation of fibroblasts into myofibroblasts-instigated by injury to the alveolar epithelial cells-and the disproportionate accumulation of extracellular matrix (ECM) components, such as collagen, are integral to IPF's progression. The introduction of two novel anti-fibrotic medications, pirfenidone and nintedanib, have exhibited efficacy in decelerating the ongoing degradation of lung function, lessening hospitalization risk, and postponing exacerbations among IPF patients. Nonetheless, these pharmacological interventions do not present a definitive solution to IPF, positioning lung transplantation as the solitary potential curative measure in contemporary medical practice. A host of innovative therapeutic strategies are presently under rigorous scrutiny. This comprehensive review encapsulates the recent advancements in IPF research, spanning from diagnosis and etiology to pathological mechanisms, and introduces a discussion on nascent therapeutic methodologies currently in the pipeline.

FIBP interacts with transcription factor STAT3 to induce EME1 expression and drive radioresistance in lung adenocarcinoma.

Cancer cells inevitably develop radioresistance during lung adenocarcinoma radiotherapy. However, the mechanisms are incompletely clarified. In this study, we show that FIBP protein expression in lung adenocarcinoma tissues is upregulated and associated with worse overall survival. Functionally, we find that depletion of FIBP inhibits lung adenocarcinoma progression and radioresistance in vitro and in vivo. Moreover, we uncover that FIBP interacts with STAT3 to enhance its transcriptional activity, thereby inducing the expression of the downstream target gene EME1. Importantly, we demonstrate that the biological effects of FIBP are partially dependent on EME1 in lung adenocarcinoma. Our work reveals that FIBP modulates the STAT3/EME1 axis to drive lung cancer progression and radioresistance, indicating that targeting FIBP may be a novel intervention strategy for lung adenocarcinoma radiotherapy.

Effect of dissolved organic nutrients on the bloom of Prorocentrum donghaiense in the East China Sea coastal waters.

Prorocentrum donghaiense blooms occur annually in the East China Sea coastal waters, degrading ecosystem functions and impeding economic development. Dissolved organic nitrogen and phosphorus (DON and DOP) are the main components in the marine nutrient pools and are closely related to harmful algal blooms. From April to June 2019, a survey was conducted along the East China Sea coast (Sansha and Lianjiang counties) to investigate the relationship between dissolved organic nutrients and P. donghaiense bloom. Our findings showed that dinoflagellates dominated the phytoplankton community, and dissolved organic nutrients were the major factors influencing community structure during the P. donghaiense bloom. Redundancy analysis indicated that P. donghaiense abundance was primarily affected by DON in the Sansha area while it was primarily affected by DON and DOP in the Lianjiang area. Correlation analysis also confirmed a strong positive correlation between dissolved organic nutrients and P. donghaiense abundance both in the Sansha and Lianjiang coastal areas (p < 0.001). Furthermore, a culture experiment was carried out during the bloom to further investigate the effect of dissolved organic nutrients on the phytoplankton community structure. After 10 days of culture, dinoflagellates' relative abundance decreased from 97.1% to 28.2% in the inorganic treatment, whereas dinoflagellates continued to dominate the phytoplankton community in the organic treatment (76.9%). As a result, we propose that dissolved organic nutrients are responsible for the P. donghaiense bloom outbreak and promote the phytoplankton community shift from diatoms to dinoflagellates.

Tetrodotoxin in Asian horseshoe crabs Carcinoscorpius rotundicauda and Tachypleus tridentatus across different life stages from northern Beibu Gulf, China.

Horseshoe crabs (HSCs) are a group of ancient chelicerates with great ecological and biomedical importance. Food poisonings caused by the consumption of Asian HSCs have significant impacts on public health and safety. This study measured tetrodotoxin (TTX) concentrations in two HSC species across various life stages in May 2020 from the northern Beibu Gulf, their most important spawning and nursery habitats in China. The average TTX contents in both Carcinoscorpius rotundicauda and Tachypleus tridentatus ranged 6.2-8.0 µg/kg and 3.8-8.4 µg/kg, respectively. While sampling location, growth and molt stages have little influence on TTX distribution in both species, significantly higher levels of TTX were detected in hemolymph, but lower in pooled tissues of early-instar juvenile T. tridentatus. These results provide a regional view of TTX occurrence and distribution in HSCs during their spawning season, which are critical for future studies to enhance understanding of TTX dynamics and formation in HSCs.

Transcriptomic data exploration of consensus genes and molecular mechanisms between chronic obstructive pulmonary disease and lung adenocarcinoma.

Most current research has focused on chronic obstructive pulmonary disease (COPD) and lung adenocarcinoma (LUAD) alone; however, it is important to understand the complex mechanism of COPD progression to LUAD. This study is the first to explore the unique and jointly molecular mechanisms in the pathogenesis of COPD and LUAD across several datasets based on a variety of analysis methods. We used weighted correlation network analysis to search hub genes in two datasets from public databases: GSE10072 and GSE76925. We explored the unique and jointly molecular mechanistic signatures of the two diseases in pathogenesis through enrichment analysis, immune infiltration analysis, and therapeutic targets analysis. Finally, the results were confirmed using real-time quantitative reverse transcription PCR. Fifteen hub genes were identified: GPI, EZH2, EFNA4, CFB, ENO1, SH3PXD2B, SELL, CORIN, MAD2L1, CENPF, TOP2A, ASPM, IGFBP2, CDKN2A, and ELF3. For the first time, SELL, CORIN, GPI, and EFNA4 were found to play a role in the etiology of COPD and LUAD. The LUAD genes identified were primarily involved in the cell cycle and DNA replication processes; COPD genes we found were related to ubiquitin-mediated proteolysis, ribosome, and T/B-cell receptor signaling pathways. The tumor microenvironment of LUAD pathogenesis was influenced by CD4 + T cells, type 1 regulatory T cells, and T helper 1 cells. T follicular helper cells, natural killer T cells, and B cells all impact the immunological inflammation in COPD. The results of drug targets analysis suggest that cisplatin and tretinoin, as well as bortezomib and metformin may be potential targeted therapy for patients with COPD combined LUAD. These signatures may be provided a new direction for developing early interventions and treatments to improve the prognosis of COPD and LUAD.

A New Species in Pseudophialophora From Wild Rice and Beneficial Potential.

Wild rice (Oryza granulata) is a natural resource pool containing abundant unknown endophytic fungi species. There are few reports on the endophytic fungi in wild rice. Here, one isolate recovered from wild rice roots was identified as a new species Pseudophialophora oryzae sp. nov based on the molecular phylogeny and morphological characteristics. Fluorescent protein-expressing P. oryzae was used to monitor the fungal colonization pattern. Hyphae invaded the epidermis to the inner cortex but not into the root stele. The inoculation of P. oryzae promoted the rice growth, with the growth parameters of chlorophyll content, shoot height, root length, fresh shoot weight, fresh root weight and dry weight increasing by 24.10, 35.32, 19.35, 90.00, 33.3, and 79.17%, respectively. P. oryzae induced up-regulation of nitrate transporter OsPTR9 and potassium transporter OsHAK16 by 7.28 ± 0.84 and 2.57 ± 0.80 folds, promoting nitrogen and potassium elements absorption. In addition, P. oryzae also conferred a systemic resistance against rice blast, showing a 72.65 and 75.63% control rate in sterile plates and potting conditions. This systemic resistance was mediated by the strongly up-regulated expression of resistance-related genes NAC, OsSAUR2, OsWRKY71, EL5, and PR1α. Since P. oryzae can promote rice growth, biomass and induce systemic disease resistance, it can be further developed as a new biogenic agent for agricultural production, providing a new approach for biocontrol of rice blast.

Integrated Analysis of MATH-Based Subtypes Reveals a Novel Screening Strategy for Early-Stage Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is a frequently diagnosed cancer type, and many patients have already reached an advanced stage when diagnosed. Thus, it is crucial to develop a novel and efficient approach to diagnose and classify lung adenocarcinoma at an early stage. In our study, we combined in silico analysis and machine learning to develop a new five-gene-based diagnosis strategy, which was further verified in independent cohorts and in vitro experiments. Considering the heterogeneity in cancer, we used the MATH (mutant-allele tumor heterogeneity) algorithm to divide patients with early-stage LUAD into two groups (C1 and C2). Specifically, patients in C2 had lower intratumor heterogeneity and higher abundance of immune cells (including B cell, CD4 T cell, CD8 T cell, macrophage, dendritic cell, and neutrophil). In addition, patients in C2 had a higher likelihood of immunotherapy response and overall survival advantage than patients in C1. Combined drug sensitivity analysis (CTRP/PRISM/CMap/GDSC) revealed that BI-2536 might serve as a new therapeutic compound for patients in C1. In order to realize the application value of our study, we constructed the classifier (to classify early-stage LUAD patients into C1 or C2 groups) with multiple machine learning and bioinformatic analyses. The 21-gene-based classification model showed high accuracy and strong generalization ability, and it was verified in four independent validation cohorts. In summary, our research provided a new strategy for clinicians to make a quick preliminary assisting diagnosis of early-stage LUAD and make patient classification at the intratumor heterogeneity level. All data, codes, and study processes have been deposited to Github and are available online.

Machine learning and bioinformatics analysis revealed classification and potential treatment strategy in stage 3-4 NSCLC patients.

BACKGROUND: Precision medicine has increased the accuracy of cancer diagnosis and treatment, especially in the era of cancer immunotherapy. Despite recent advances in cancer immunotherapy, the overall survival rate of advanced NSCLC patients remains low. A better classification in advanced NSCLC is important for developing more effective treatments. METHOD: The calculation of abundances of tumor-infiltrating immune cells (TIICs) was conducted using Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT), xCell (xCELL), Tumor IMmune Estimation Resource (TIMER), Estimate the Proportion of Immune and Cancer cells (EPIC), and Microenvironment Cell Populations-counter (MCP-counter). K-means clustering was used to classify patients, and four machine learning methods (SVM, Randomforest, Adaboost, Xgboost) were used to build the classifiers. Multi-omics datasets (including transcriptomics, DNA methylation, copy number alterations, miRNA profile) and ICI immunotherapy treatment cohorts were obtained from various databases. The drug sensitivity data were derived from PRISM and CTRP databases. RESULTS: In this study, patients with stage 3-4 NSCLC were divided into three clusters according to the abundance of TIICs, and we established classifiers to distinguish these clusters based on different machine learning algorithms (including SVM, RF, Xgboost, and Adaboost). Patients in cluster-2 were found to have a survival advantage and might have a favorable response to immunotherapy. We then constructed an immune-related Poor Prognosis Signature which could successfully predict the advanced NSCLC patient survival, and through epigenetic analysis, we found 3 key molecules (HSPA8, CREB1, RAP1A) which might serve as potential therapeutic targets in cluster-1. In the end, after screening of drug sensitivity data derived from CTRP and PRISM databases, we identified several compounds which might serve as medication for different clusters. CONCLUSIONS: Our study has not only depicted the landscape of different clusters of stage 3-4 NSCLC but presented a treatment strategy for patients with advanced NSCLC.

Application of Hyperspectral Imaging for Maturity and Soluble Solids Content Determination of Strawberry With Deep Learning Approaches.

Maturity degree and quality evaluation are important for strawberry harvest, trade, and consumption. Deep learning has been an efficient artificial intelligence tool for food and agro-products. Hyperspectral imaging coupled with deep learning was applied to determine the maturity degree and soluble solids content (SSC) of strawberries with four maturity degrees. Hyperspectral image of each strawberry was obtained and preprocessed, and the spectra were extracted from the images. One-dimension residual neural network (1D ResNet) and three-dimension (3D) ResNet were built using 1D spectra and 3D hyperspectral image as inputs for maturity degree evaluation. Good performances were obtained for maturity identification, with the classification accuracy over 84% for both 1D ResNet and 3D ResNet. The corresponding saliency maps showed that the pigments related wavelengths and image regions contributed more to the maturity identification. For SSC determination, 1D ResNet model was also built, with the determination of coefficient (R 2) over 0.55 of the training, validation, and testing sets. The saliency maps of 1D ResNet for the SSC determination were also explored. The overall results showed that deep learning could be used to identify strawberry maturity degree and determine SSC. More efforts were needed to explore the use of 3D deep learning methods for the SSC determination. The close results of 1D ResNet and 3D ResNet for classification indicated that more samples might be used to improve the performances of 3D ResNet. The results in this study would help to develop 1D and 3D deep learning models for fruit quality inspection and other researches using hyperspectral imaging, providing efficient analysis approaches of fruit quality inspection using hyperspectral imaging.

The Endophytic Fungus Piriformospora Indica-Assisted Alleviation of Cadmium in Tobacco.

Increasing evidence suggests that the endophytic fungus Piriformospora indica helps plants overcome various abiotic stresses, especially heavy metals. However, the mechanism of heavy metal tolerance has not yet been elucidated. Here, the role of P. indica in alleviating cadmium (Cd) toxicities in tobacco was investigated. It was found that P. indica improved Cd tolerance to tobacco, increasing Cd accumulation in roots but decreasing Cd accumulation in leaves. The colonization of P. indica altered the subcellular repartition of Cd, increasing the Cd proportion in cell walls while reducing the Cd proportion in membrane/organelle and soluble fractions. During Cd stress, P. indica significantly enhanced the peroxidase (POD) activity and glutathione (GSH) content in tobacco. The spatial distribution of GSH was further visualized by Raman spectroscopy, showing that GSH was distributed in the cortex of P. indica-inoculated roots while in the epidermis of the control roots. A LC-MS/MS-based label-free quantitative technique evaluated the differential proteomics of P. indica treatment vs. control plants under Cd stress. The expressions of peroxidase, glutathione synthase, and photosynthesis-related proteins were significantly upregulated. This study provided extensive evidence for how P. indica enhances Cd tolerance in tobacco at physiological, cytological, and protein levels.

An efficient genetic manipulation protocol for dark septate endophyte Falciphora oryzae.

OBJECTIVE: To investigate the protoplast preparation and transformation system of endophytic fungus Falciphora oryzae. RESULTS: F. oryzae strain obtained higher protoplast yield and effective transformation when treated with enzyme digestion solution containing 0.9 M KCl solution and 10 mg mL-1 glucanase at 30 °C with shaking at 80 rpm for 2-3 h. When the protoplasts were plated on a regenerations-agar medium containing 1 M sucrose, the re-growth rate of protoplasts was the highest. We successfully acquired green fluorescent protein-expressing transformants by transforming the pKD6-GFP vector into protoplasts. Further, the GFP expression in fungal hyphae possessed good stability and intensity during symbiosis in rice roots. CONCLUSIONS: This study provided a protoplast transformation system of F. oryzae, creating opportunities for future genetic research in other endophytic fungi.

Comprehensive Profiling Reveals Distinct Microenvironment and Metabolism Characterization of Lung Adenocarcinoma.

Lung adenocarcinoma has entered into an era of immunotherapy with the development of immune checkpoint inhibitors (ICIs). The identification of immune subtype is crucial to prolonging survival in patients. The tumor microenvironment (TME) and metabolism have a profound impact on prognosis and therapy. The majority of previous studies focused on only one aspect, while both of them are essential to the understanding of tumorigenesis and development. We hypothesized that lung adenocarcinoma can be stratified into immune subgroups with alterations in the TME infiltration. We aimed to explore the "TME-Metabolism-Risk" patterns in each subtypes and the mechanism behind. Glycolysis and cholesterol were selected for the analysis of metabolic states based on the first half of the study. Bioinformatic analysis was performed to investigate the transcriptomic and clinical data integrated by three lung adenocarcinoma cohorts (GSE30219, GSE31210, GSE37745, N = 415). The results were validated in an independent cohort (GSE50081, N = 127). In total, 415 lung adenocarcinoma samples were integrated and analyzed. Four major immune subtypes were indentified using bioinformatic analysis. Subtype NC1, characterized by a high level of glycolysis, with extremely low microenvironment cell infiltration. Subtype NC2, characterized by the "Silence" and "Cholesterol biosynthesis Predominant" metabolic states, with a middle degree infiltration of microenvironment cell. Subtype NC3, characterized by the lack of "Cholesterol biosynthesis Predominant" metabolic state, with abundant microenvironment cell infiltration. Subtype NC4, characterized by "Mixed" metabolic state, with a relatively low microenvironment cell infiltration. Least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were performed to calculate the risk of each sample, and we attempted to find out the potential immune escape mechanism in different subtypes. The result revealed that the lack of immune cells infiltration might contribute to the immune escape in subtypes NC1 and NC4. NC3 was characterized by the high expression of immune checkpoint molecules and fibroblasts. NC2 had defects in activation of innate immune cells. There existed an obviously survival advantage in subtype NC2. Gene set enrichment analysis (GSEA) and Gene Ontology analysis indicated that the PI3K-AKT-mTOR, TGF-ß, MYC-related pathways might be correlated with this phenomenon. In addition, some differentially expressed genes (DEGs) were indentified in subtype NC3, which might be potential targets for survival phenotype transformation.

Prognostic Value and Related Regulatory Networks of MRPL15 in Non-Small-Cell Lung Cancer.

BACKGROUND: Mitochondrial ribosomal protein L15 (MRPL15), a member of mitochondrial ribosomal proteins whose abnormal expression is related to tumorigenesis. However, the prognostic value and regulatory mechanisms of MRPL15 in non-small-cell lung cancer (NSCLC) remain unclear. METHODS: GEPIA, ONCOMINE, Gene Expression Omnibus (GEO), UALCAN, Kaplan-Meier plotter, PrognoScan, LinkedOmics and GeneMANIA database were utilized to explore the expression and prognostic value of MRPL15 in NSCLC. Additionally, immune infiltration patterns were evaluated via ESTIMATE algorithm and TISIDB database. Furthermore, the expression and prognostic value of MRPL15 in lung cancer were validated via immunohistochemistry (IHC) assays. RESULTS: In NSCLC, multiple cohorts including GEPIA, ONCOMINE and 8 GEO series (GSE8569, GSE101929, GSE33532, GSE27262, GSE21933, GSE19804, GSE19188, GSE18842) described that MRPL15 was up-regulated. Moreover, MRPL15 was notably linked to gender, clinical stage, lymph node status and the TP53 mutation status. And patients with high MRPL15 expression showed poor overall survival (OS), progression-free survival (PFS), disease-free survival (DFS) and relapse-free survival (RFS) in NSCLC. Then, functional network analysis suggested that MRPL15 participated in metabolism-related pathways, DNA replication and cell cycle signaling via pathways involving several kinases, miRNAs and transcription factors. Additionally, it was found that MRPL15 expression was negatively related to immune infiltration, including immune scores, stromal scores and several tumor-infiltrating lymphocytes (TILs). Furthermore, IHC results further confirmed the high MRPL15 expression and its prognostic potential in lung cancer. CONCLUSIONS: These findings demonstrate that high MRPL15 expression indicates poor prognosis in NSCLC and reveal potential regulatory networks as well as the negative relationship with immune infiltration. Thus, MRPL15 may be an attractive predictor and therapeutic strategy for NSCLC.

The Efficacy of First-Generation EGFR-TKI Combined With Brain Radiotherapy as the First-Line Treatment for Lung Adenocarcinoma Patients With Brain Metastases and EGFR Sensitive Mutations: A Retrospective study.

BACKGROUND: It was controversial that whether LUAD patients with brain metastases (BMs) and EGFR sensitive mutations should be conducted using brain radiotherapy when treated with first-generation EGFR-TKI. Herein, a retrospective study was designed to compare the efficacy of first-generation EGFR-TKI combined with brain radiotherapy and EGFR-TKI alone as first-line treatment for these LUAD patients. PATIENTS AND METHODS: We retrospectively analyzed the status of patients with advanced LUAD carrying EGFR sensitive mutations who received first-generation EGFR-TKI treatment in our center. iPFS was the first time of intracranial progression or death from the diagnosis of BMs, PFS was the time of progression of any site or death from the diagnosis of BMs, and OS was the time of confirmed BMs to death or the last follow-up time. Differences in characteristics between groups were compared using the Chi-square test. The Kaplan-Meier method was used to calculate the iPFS, PFS, and OS. Univariate analysis, multivariate analysis, and subgroup analysis were conducted by Cox regression model. RESULTS: There were 77 patients (77/134, 57.5%) in the TKI + RT group and 57 patients (57/134, 42.5%) in the TKI group. TKI + RT group had a significant higher intracranial ORR and DCR, and the combination therapy was independently significantly associated with a longer iPFS (18.9 vs. 10.5 months, P = 0.0009), systematic PFS (12.5 vs. 8.4 months, P = 0.0071) and OS (30.8 vs. 22.7 months, P = 0.0183). Females, non-smokers, and younger patients benefited more from the combination therapy. Subgroup analysis demonstrated that the combination therapy could improve the iPFS in patients with more than 3 BMs (P = 0.005); however, it couldn't improve the OS for these patients. CONCLUSION: Our study confirmed the effect of the combination of EGFR-TKI and brain radiotherapy as first-line treatment for LUAD patients with BMs and EGFR sensitive mutations.