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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Identification of CXCL13/CXCR5 axis's crucial and complex effect in human lung adenocarcinoma.

Immune escape and low response to immunotherapy are crucial challenges in present lung cancer treatment. In this study, we constructed a new immune-related classifier based on CXCL13/CXCR5, an important tumor microenvironment component and strongly related with the formation of tertiary lymphoid structures (TLSs) in tumor microenvironment. With the classifier, we divided patients into two main clusters and each cluster was further divided into subcluster (A1, A2, B1, B2, B3). In the later analysis, we noticed that patients in subcluster B3 had a distinct advantage over patients in A1 in survival time and immune infiltration, suggesting a more favorable response to immunotherapy. Moreover, we demonstrated the genetic and epigenetic regulation related to the subclusters and recovered four key differentially expressed genes (ERBB4, GRIN2A, IL2RA, CCND2). With several experiments, we verified the unique role of CCND2 in tumor metastasis and T cell apoptosis. Overexpressing CCND2 could significantly impair cancer cell abilities of migration and invasion and downregulate PD-1/PD-L1 signaling, which may be the cause of T cell apoptosis reduction. In the end, we constructed a regression risk model that could successfully predict ICI response. To sum up, our study established new stratification models that can successfully predict patient survival and response to ICI. And using integrative analysis of multi-omics data, four key DEGs were noticed, and CCND2, one of the four genes, was identified as a potential treatment target because of its effect in tumor metastasis and T cell apoptosis.

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.

Exploration of the immune cell infiltration-related gene signature in the prognosis of melanoma.

Melanoma is a life-threatening form of skin cancer with an elevated risk of metastasis and high mortality rates. The prognosis and clinical outcomes of cancer immunotherapy in melanoma patients are influenced by immune cell infiltration in the tumor microenvironment (TME) and the expression of genetic factors. Despite reports suggesting that immune-classification may have a better prediction of prognosis compared to the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) TNM-classification, the definition of Immunoscore in melanoma is becoming a difficult challenge. In this study, we established and verified a 7-gene prognostic signature. Melanoma patients from the Cancer Genome Atlas (TCGA) were separated into a low-risk group and a high-risk group using the median risk score. Receiver operating characteristic (ROC) analysis for overall survival (OS) showed that the area under the curve (AUC) was 0.701 for 1 year, 0.726 for 3 years, and 0.745 for 5 years, respectively. Moreover, a nomogram was constructed as a practical prognostic tool, and the AUC was 0.829 for 3 years, and 0.803 for 5 years, respectively. Furthermore, we validated the above results in two datasets from the Gene Expression Omnibus (GEO) database and the relationship between 7-gene prognostic signature and immune infiltration estimated.

IQGAP3 interacts with Rad17 to recruit the Mre11-Rad50-Nbs1 complex and contributes to radioresistance in lung cancer.

IQ motif containing GTPase-activating protein 3 (IQGAP3) has been implicated in diverse cellular processes, including neuronal morphogenesis, cell proliferation and motility, and epithelial-mesenchymal transition. However, its role in cancer radioresistance is completely unknown. Here, we report that IQGAP3 is overproduced in lung cancer patients and correlates with poor clinical outcomes. Functionally, we demonstrate that depletion of IQGAP3 impairs oncogenesis and overcomes radioresistance in lung cancer in vitro and in vivo. Mechanistically, we uncover that IQGAP3 interacts with Rad17 and controls its expression to activate the ATM/Chk2 and ATR/Chk1 signaling pathways by recruiting the Mre11-Rad50-Nbs1 (MRN) complex in response to DNA damage. Moreover, Rad17 is identified as the major downstream effector that mediates the functions of IQGAP3 in lung cancer. Clinically, IQGAP3 overexpression positively correlates with Rad17 upregulation in human lung cancer tissues. Collectively, these data support key role for IQGAP3 in promoting lung cancer radioresistance by interacting with Rad17 and suggest that targeting IQGAP3 may be an attractive strategy for lung cancer radiotherapy.

Targeting NEK2 impairs oncogenesis and radioresistance via inhibiting the Wnt1/ß-catenin signaling pathway in cervical cancer.

BACKGROUND: NEK2, a serine/threonine kinase involved in mitosis, has been found to function in chromosome instability, tumor progression and metastasis, but its role in cervical cancer radioresistance remains unknown. METHODS: We detected the protein levels of NEK2 in cervical carcinoma tissues and paired paracarcinoma tissues by immunohistochemistry. The roles of NEK2 in oncogenesis were examined using cell growth and colony formation assays, EdU assay, apoptosis assay as well as in vivo mouse model. γ-H2AX and Rad51 foci formation, neutral comet assay and clonogenic cell survival assay were applied to determine the radiosensitivity of cervical cancer cells. RNA-seq was performed to identify the downstream effector of NEK2. The gene expression levels were measured by Real-time PCR. RESULTS: We report that NEK2 protein level is overexpressed and correlated with the tumor stage and lymph node metastasis in cervical cancer tissues. Furthermore, we provided evidence that depletion of NEK2 impairs oncogenesis and enhances radiosensitivity in cervical cancer. Using RNA sequencing, we identify Wnt1 as a key downstream effector of NEK2. Knockdown of NEK2 downregulates the mRNA and protein levels of Wnt1, thereby inhibiting the activation of the Wnt/ß-catenin signaling pathway. More importantly, the observed consequences induced by NEK2 depletion in cervical cancer cells can be partially rescued by Wnt1 overexpression. CONCLUSIONS: Our results demonstrate that NEK2 activates the Wnt/ß-catenin signaling pathway via Wnt1 to drive oncogenesis and radioresistance in cervical cancer, indicating that NEK2 may be a promising target for the radiosensitization of cervical cancer.

Identification of Clonal Neoantigens Derived From Driver Mutations in an EGFR-Mutated Lung Cancer Patient Benefitting From Anti-PD-1.

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have been recommended as the first-line therapy for non-small cell lung cancer (NSCLC) patients harboring EGFR mutations. However, acquired resistance to EGFR-TKIs is inevitable. Although immune checkpoint blockades (ICBs) targeting the programmed cell death 1 (PD-1)/PD-ligand (L)1 axis have achieved clinical success for many cancer types, the clinical efficacy of anti-PD-1/PD-L1 blockades in EGFR mutated NSCLC patients has been demonstrated to be lower than those without EGFR mutations. Here, we reported an advanced NSCLC patient with EGFR driver mutations benefitting from anti-PD-1 blockade therapy after acquiring resistance to EGFR-TKI. We characterized the mutational landscape of the patient with next-generation sequencing (NGS) and successfully identified specific T-cell responses to clonal neoantigens encoded by EGFR exon 19 deletion, TP53 A116T and DENND6B R398Q mutations. Our findings support the potential application of immune checkpoint blockades in NSCLC patients with acquired resistance to EGFR-TKIs in the context of specific clonal neoantigens with high immunogenicity. Personalized immunomodulatory therapy targeting these neoantigens should be explored for better clinical outcomes in EGFR mutated NSCLC patients.

The Superior Ability of Human BDCA3+ (CD141+) Dendritic Cells (DCs) to Cross-Present Antigens Derived From Necrotic Lung Cancer Cells.

Dendritic cells (DCs) play a key role in initiating and regulating the immune responses to pathogens, self-antigens, and cancers. Human blood DCs comprise a family of different subsets: plasmacytoid DCs (pDCs) and CD16+, CD1c/BDCA1+, and BDCA3+ (CD141+) myeloid DCs and possess different phenotypes and functional characteristics. Lung cancer is the most common cancer, with the highest morbidity and mortality in the world. However, which DC subset plays a leading role in the lung cancer immune responses is unclear. We reanalyzed C-type lectin domain family 9 member A (CLEC9A) and CD141 (THBD) gene expression profiles from the Cancer Genome Atlas (TCGA) database and performed the Kaplan-Meier survival analysis of overall survival for several cancers according to their expression levels. Next, we investigated the capacities of five human blood DC subsets to stimulate T cell proliferation and capture, process and (cross-) present tumor antigen. Human BDCA3+ (CD141+) DCs have a superior capacity to stimulate allogeneic CD4+T cells proliferation and induce superior Th1 response compared with other DC subsets. Interestingly, toll-like receptor (TLR) agonists have little effect on DCs to induce the proliferation of naïve CD4+ T cells, but contribute to their differentiation. Importantly, BDCA3+ (CD141+) DCs possess the most potent ability to cross-present human tumor antigen after their uptake of necrotic lung cancer cells despite their lower antigen uptake. These findings suggest that human BDCA3+ (CD141+) DCs are critical mediators of cytotoxic T lymphocyte responses against EGFR-positive lung cancer. Therefore, our findings may provide theoretical basis for the development of DC-based antitumor vaccines.