Systematic analysis of IL-6 as a predictive biomarker and desensitizer of immunotherapy responses in patients with non-small cell lung cancer.

BACKGROUND: Cytokines have been reported to alter the response to immune checkpoint inhibitors (ICIs) in patients with the tumor in accordance with their plasma concentrations. Here, we aimed to identify the key cytokines which influenced the responses and stimulated resistance to ICIs and tried to improve immunological response and develop novel clinical treatments in non-small cell lung cancer (NSCLC). METHODS: The promising predictive cytokines were analyzed via the multi-analyte flow assay. Next, we explored the correlation baseline level of plasma cytokines and clinical outcomes in 45 NSCLC patients treated with ICIs. The mechanism of the potential candidate cytokine in predicting response and inducing resistance to ICIs was then investigated. RESULTS: We found NSCLC with a low baseline concentration of IL-6 in plasma specimens or tumor tissues could derive more benefit from ICIs based on the patient cohort. Further analyses revealed that a favorable relationship between PD-L1 and IL-6 expression was seen in NSCLC specimens. Results in vitro showed that PD-L1 expression in the tumor was enhanced by IL-6 via the JAK1/Stat3 pathway, which induced immune evasion. Notably, an adverse correlation was found between IL-6 levels and CD8+ T cells. And a positive association between IL-6 levels and myeloid-derived suppressor cells, M2 macrophages and regulator T cells was also seen in tumor samples, which may result in an inferior response to ICIs. Results of murine models of NSCLC suggested that the dual blockade of IL-6 and PD-L1 attenuated tumor growth. Further analyses detected that the inhibitor of IL-6 stimulated the infiltration of CD8+ T cells and yielded the inflammatory phenotype. CONCLUSIONS: This study elucidated the role of baseline IL-6 levels in predicting the responses and promoting resistance to immunotherapy in patients with NSCLC. Our results indicated that the treatment targeting IL-6 may be beneficial for ICIs in NSCLC.

Tumor microenvironment characterization identifies two lung adenocarcinoma subtypes with specific immune and metabolic state.

The tumor microenvironment (TME) is a vital component of tumor tissue. Increasing evidence suggests their significance in predicting outcomes and guiding therapies. However, no studies have reported a systematic analysis of the clinicopathologic significance of TME in lung adenocarcinoma (LUAD). Here, we inferred tumor stromal cells in 1184 LUAD patients using computational algorithms based on bulk tumor expression data, and evaluated the clinicopathologic significance of stromal cells. We found LUAD patients showed heterogeneous abundance in stromal cells. Infiltration of stromal cells was influenced by clinicopathologic features, such as age, gender, smoking, and TNM stage. By clustering stromal cells, we identified 2 clinically and molecularly distinct LUAD subtypes with immune active and immune repressed features. The immune active subtype is characterized by repressed metabolism and repressed proliferation of tumor cells, while the immune repressed subtype is characterized by active metabolism and active proliferation of tumor cells. Differentially expressed gene analysis of the two LUAD subtypes identified an immune activation signature. To diagnose TME subtypes practically, we constructed a TME score using principal component analysis based on the immune activation signature. The TME score predicted TME subtypes effectively in 3 independent datasets with areas under the receiver operating characteristic curves of 0.960, 0.812, and 0.819, respectively. In conclusion, we proposed 2 clinically and molecularly distinct LUAD subtypes based on tumor microenvironment that could be valuable in predicting clinical outcome and guiding immunotherapy.

Survival-associated alternative splicing signatures in esophageal carcinoma.

Alternative splicing (AS), a major mechanism for the enhancement of transcriptome and proteome diversity, has been widely demonstrated to be involved in the full spectrum of oncogenic processes. High-throughput sequencing technology and the rapid accumulation of clinical data sets have provided an opportunity to systemically analyze the association between messenger RNA AS variants and patient clinical outcomes. Here, we compared differentially spliced AS transcripts between esophageal carcinoma (ESCA) and non-tumor tissues, profiled genome-wide survival-associated AS events in 87 patients with esophageal adenocarcinoma (EAC) and 79 patients with esophageal squamous cell carcinoma (ESCC) using The Cancer Genome Atlas (TCGA) RNA-seq data set, and constructed predictive models as well as splicing regulation networks by integrated bioinformatic analysis. A total of 2326 AS events in 1738 genes and 1812 AS events in 1360 genes were determined to be significantly associated with overall survival (OS) of patients in the EAC and ESCC cohorts, respectively, including some essential participants in the oncogenic process. The predictive model of each splice type performed reasonably well in distinguishing good and poor outcomes of patients with esophageal cancer, and values for the area under curve reached 0.942 and 0.815 in the EAC exon skip predictive model and the ESCC alternate acceptor site predictive model, respectively. The splicing regulation networks revealed an interesting correlation between survival-associated splicing factors and prognostic AS genes. In summary, we created prognostic models for patients with esophageal cancer based on AS signatures and constructed novel splicing correlation networks.

Translational value of IDH1 and DNA methylation biomarkers in diagnosing lung cancers: a novel diagnostic panel of stage and histology-specificity.

BACKGROUND: Lung cancer is the leading cause of cancer-related death worldwide, and the timely and serial assessment of low-dose computed tomography (LDCT) in high-risk populations remains a challenge. Furthermore, testing a single biomarker for the diagnosis of lung cancers is of relatively low effectiveness. Thus, a stronger diagnostic combination of blood biomarkers is needed to improve the diagnosis of non-small cell lung cancer (NSCLC). METHODS: The blood levels of individual biomarkers [IDH1, DNA methylation of short stature homeobox 2 gene (SHOX2), and prostaglandin E receptor 4 gene (PTGER4)] were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. In total, 221 candidates were enrolled and randomly assigned into two groups for the training and validation of a diagnostic panel. Additionally, a subgroup analysis was performed in the whole cohort. RESULTS: A newly combined 3-marker diagnostic model for lung cancers was established and validated with area under the receiver operating characteristic (ROC) curve (AUC) values ranging from 0.835 to 0.905 in independent groups showing significantly stronger diagnostic value compared with a single tested biomarker. The sensitivity of the diagnostic model was as high as 86.1% and 80.0% in the training and validation sets, respectively. Although no apparent differences were found between the 3-marker and 2-marker models, the high clinical T-stage and histological type specificity of IDH1 and two other methylated DNA biomarkers were demonstrated in the subgroup analysis. CONCLUSIONS: The combination of single biomarkers with high stage-specificity and histological type specificity (SHOX2 and PTGER4 DNA methylation and IDH1) showed better diagnostic performance in the detection of lung cancers compared with single marker assessment. A greater clinical utility of the panel may be developed by adding demographic/epidemiologic characteristics.

Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators.

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

Corrigendum: Clinical Significance and Immunometabolism Landscapes of a Novel Recurrence-Associated Lipid Metabolism Signature In Early-Stage Lung Adenocarcinoma: A Comprehensive Analysis.

[This corrects the article DOI: 10.3389/fimmu.2022.783495.].

Clinical Significance and Immunometabolism Landscapes of a Novel Recurrence-Associated Lipid Metabolism Signature In Early-Stage Lung Adenocarcinoma: A Comprehensive Analysis.

Background: The early-stage lung adenocarcinoma (LUAD) incidence has increased with heightened public awareness and lung cancer screening implementation. Lipid metabolism abnormalities are associated with lung cancer initiation and progression. However, the comprehensive features and clinical significance of the immunometabolism landscape and lipid metabolism-related genes (LMRGs) in cancer recurrence for early-stage LUAD remain obscure. Methods: LMRGs were extracted from Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Samples from The Cancer Genome Atlas (TCGA) were used as training cohort, and samples from four Gene Expression Omnibus (GEO) datasets were used as validation cohorts. The LUAD recurrence-associated LMRG molecular pattern and signature was constructed through unsupervised consensus clustering, time-dependent receiver operating characteristic (ROC), and least absolute shrinkage and selection operator (LASSO) analyses. Kaplan-Meier, ROC, and multivariate Cox regression analyses and prognostic meta-analysis were used to test the suitability and stability of the signature. We used Gene Ontology (GO), KEGG pathway, immune cell infiltration, chemotherapy response analyses, gene set variation analysis (GSVA), and GSEA to explore molecular mechanisms and immune landscapes related to the signature and the potential of the signature to predict immunotherapy or chemotherapy response. Results: First, two LMRG molecular patterns were established, which showed diverse prognoses and immune infiltration statuses. Then, a 12-gene signature was identified, and a risk model was built. The signature remained an independent prognostic parameter in multivariate Cox regression and prognostic meta-analysis. In addition, this signature stratified patients into high- and low-risk groups with significantly different recurrence rates and was well validated in different clinical subgroups and several independent validation cohorts. The results of GO and KEGG analyses and GSEA showed that there were differences in multiple lipid metabolism, immune response, and drug metabolism pathways between the high- and low-risk groups. Further analyses revealed that the signature-based risk model was related to distinct immune cell proportions, immune checkpoint parameters, and immunotherapy and chemotherapy response, consistent with the GO, KEGG, and GSEA results. Conclusions: This is the first lipid metabolism-based signature for predicting recurrence, and it could provide vital guidance to achieve optimized antitumor for immunotherapy or chemotherapy for early-stage LUAD.

KRAS-G12D mutation drives immune suppression and the primary resistance of anti-PD-1/PD-L1 immunotherapy in non-small cell lung cancer.

BACKGROUND: Although immune checkpoint inhibitors (ICIs) against programmed cell death protein 1 (PD-1) and its ligand PD-L1 have demonstrated potency towards treating patients with non-small cell lung carcinoma (NSCLC), the potential association between Kirsten rat sarcoma viral oncogene homolog (KRAS) oncogene substitutions and the efficacy of ICIs remains unclear. In this study, we aimed to find point mutations in the KRAS gene resistant to ICIs and elucidate resistance mechanism. METHODS: The association between KRAS variant status and the efficacy of ICIs was explored with a clinical cohort (n = 74), and confirmed with a mouse model. In addition, the tumor immune microenvironment (TIME) of KRAS-mutant NSCLC, such as CD8+ tumor-infiltrating lymphocytes (TILs) and PD-L1 level, was investigated. Cell lines expressing classic KRAS substitutions were used to explore signaling pathway activation involved in the formation of TIME. Furthermore, interventions that improved TIME were developed to increase responsiveness to ICIs. RESULTS: We observed the inferior efficacy of ICIs in KRAS-G12D-mutant NSCLC. Based upon transcriptome data and immunostaining results from KRAS-mutant NSCLC, KRAS-G12D point mutation negatively correlated with PD-L1 level and secretion of chemokines CXCL10/CXCL11 that led to a decrease in CD8+ TILs, which in turn yielded an immunosuppressive TIME. The analysis of cell lines overexpressing classic KRAS substitutions further revealed that KRAS-G12D mutation suppressed PD-L1 level via the P70S6K/PI3K/AKT axis and reduced CXCL10/CXCL11 levels by down-regulating high mobility group protein A2 (HMGA2) level. Notably, paclitaxel, a chemotherapeutic agent, upregulated HMGA2 level, and in turn, stimulated the secretion of CXCL10/CXCL11. Moreover, PD-L1 blockade combined with paclitaxel significantly suppressed tumor growth compared with PD-L1 inhibitor monotherapy in a mouse model with KRAS-G12D-mutant lung adenocarcinoma. Further analyses revealed that the combined treatment significantly enhanced the recruitment of CD8+ TILs via the up-regulation of CXCL10/CXCL11 levels. Results of clinical study also revealed the superior efficacy of chemo-immunotherapy in patients with KRAS-G12D-mutant NSCLC compared with ICI monotherapy. CONCLUSIONS: Our study elucidated the molecular mechanism by which KRAS-G12D mutation drives immunosuppression and enhances resistance of ICIs in NSCLC. Importantly, our findings demonstrate that ICIs in combination with chemotherapy may be more effective in patients with KRAS-G12D-mutant NSCLC.

Development and external validation of a composite immune-clinical prognostic model associated with EGFR mutation in East-Asian patients with lung adenocarcinoma.

BACKGROUND: EGFR mutation is a common oncogene driver in East Asians with lung adenocarcinoma (LUAD), conferring a favorable prognosis with effective targeted therapy. However, the EGFR mutation is a weak predictor of long-term survival. Therefore, a powerful predictive tool is urgently needed to estimate disease prognosis and patient survival for East-Asian patients with LUAD. METHODS: In this first systematic analysis of the relationships among EGFR mutation, immunophenotype, and prognosis in LUAD samples from East-Asian patients, we constructed a prognostic signature consisting of EGFR-associated immune-related gene pairs (EIGPs). The predictive performance for overall survival (OS) and the clinical significance of this signature were then comprehensively investigated. RESULTS: Based on transcriptome data analysis of a training set, we proposed the EIGP index (EIGPI), represented by five EIGPs, which was significantly associated with the OS of East-Asian patients with LUAD. It was also well validated in a test set. Furthermore, the prognostic performance of the EIGPI was further verified using protein levels in an additional independent set. Stratification analysis and multivariate Cox regression analysis revealed that the EIGPI was an independent prognostic factor. When combined with stage, the composite immune-clinical prognostic model index (ICPMI) showed improved prognostic accuracy in all datasets. CONCLUSION: This study was the first to systematically investigate the relationships among EGFR mutation, immunophenotype, and prognosis in East Asians with LUAD and develop a composite clinical and immune model associated with EGFR mutation. This model may be a reliable and promising prognostic tool and help further personalize patient management.

Avoiding Absolute Quantification Trap: A Novel Predictive Signature of Clinical Benefit to Anti-PD-1 Immunotherapy in Non-Small Cell Lung Cancer.

Immunotherapy has been focused on by many oncologists and researchers. While, due to technical biases of absolute quantification, few traditional biomarkers for anti-PD-1 immunotherapy have been applied in regular clinical practice of non-small cell lung cancer (NSCLC). Therefore, there is an urgent and unmet need for a feasible tool-immune to data source bias-for identifying patients who might benefit from ICIs in clinical practice. Using the strategy based on the relative ranking of gene expression levels, we herein proposed the novel BRGP index (BRGPI): four BRGPs significantly related with progression-free survival of NSCLC patients treated with anti-PD-1 immunotherapy in the multicohort analysis. Moreover, stratification and multivariate Cox regression analyses demonstrated that BRGPI was an independent prognostic factor. Notably, compared to PD-L1, BRGPI exerted the best predictive ability. Further analysis showed that the patients in the BRGPI-low and PD-L1-high subgroup derived more clinical benefits from anti-PD-1 immunotherapy. In conclusion, the prospect of applying the BRGPI to real clinical practice is promising owing to its powerful and reliable predictive value.

A novel recurrence-associated metabolic prognostic model for risk stratification and therapeutic response prediction in patients with stage I lung adenocarcinoma.

OBJECTIVE: The proportion of patients with stage I lung adenocarcinoma (LUAD) has dramatically increased with the prevalence of low-dose computed tomography use for screening. Up to 30% of patients with stage I LUAD experience recurrence within 5 years after curative surgery. A robust risk stratification tool is urgently needed to identify patients who might benefit from adjuvant treatment. METHODS: In this first investigation of the relationship between metabolic reprogramming and recurrence in stage I LUAD, we developed a recurrence-associated metabolic signature (RAMS). This RAMS was based on metabolism-associated genes to predict cancer relapse and overall prognoses of patients with stage I LUAD. The clinical significance and immune landscapes of the signature were comprehensively analyzed. RESULTS: Based on a gene expression profile from the GSE31210 database, functional enrichment analysis revealed a significant difference in metabolic reprogramming that distinguished patients with stage I LUAD with relapse from those without relapse. We then identified a metabolic signature (i.e., RAMS) represented by 2 genes (ACADM and RPS8) significantly related to recurrence-free survival and overall survival times of patients with stage I LUAD using transcriptome data analysis of a training set. The training set was well validated in a test set. The discriminatory power of the 2 gene metabolic signature was further validated using protein values in an additional independent cohort. The results indicated a clear association between a high risk score and a very poor patient prognosis. Stratification analysis and multivariate Cox regression analysis showed that the RAMS was an independent prognostic factor. We also found that the risk score was positively correlated with inflammatory response, the antigen-presenting process, and the expression levels of many immunosuppressive checkpoint molecules (e.g., PD-L1, PD-L2, B7-H3, galectin-9, and FGL-1). These results suggested that high risk patients had immune response suppression. Further analysis revealed that anti-PD-1/PD-L1 immunotherapy did not have significant benefits for high risk patients. However, the patients could respond better to chemotherapy. CONCLUSIONS: This study is the first to highlight the relationship between metabolic reprogramming and recurrence in stage I LUAD, and is the first to also develop a clinically feasible signature. This signature may be a powerful prognostic tool and help further optimize the cancer therapy paradigm.

TGF-ß-induced PLEK2 promotes metastasis and chemoresistance in oesophageal squamous cell carcinoma by regulating LCN2.

Oesophageal squamous cell carcinoma (ESCC) has a relatively unfavourable prognosis due to metastasis and chemoresistance. Our previous research established a comprehensive ESCC database (GSE53625). After analysing data from TCGA database and GSE53625, we found that PLEK2 predicted poor prognosis in ESCC. Moreover, PLEK2 expression was also related to the overall survival of ESCC patients undergoing chemotherapy. Repression of PLEK2 decreased the proliferation, migration, invasion and chemoresistance of ESCC cells in vitro and decreased tumorigenicity and distant metastasis in vivo. Mechanistically, luciferase reporter assay and chromatin immunoprecipitation assay suggested that TGF-ß stimulated the process that Smad2/3 binds to the promoter sequences of PLEK2 and induced its expression. RNA-seq suggested LCN2 might a key molecular regulated by PLEK2. LCN2 overexpression in PLEK2 knockdown ESCC cells reversed the effects of decreased migration and invasion. In addition, TGF-ß induced the expression of LCN2, but the effect disappeared when PLEK2 was knockdown. Moreover, AKT was phosphorylated in all regulatory processes. This study detected the major role of PLEK2 in driving metastasis and chemoresistance in ESCC by regulating LCN2, which indicates the potential use of PLEK2 as a biomarker to predict prognosis and as a therapeutic target for ESCC.

Exosomal miR-375-3p breaks vascular barrier and promotes small cell lung cancer metastasis by targeting claudin-1.

BACKGROUND: High incidence of metastasis is the main cause of death for small cell lung cancer (SCLC), with its underlying molecular mechanisms remain unclear. Exosomal miRNAs are important regulators in metastatic processes of various tumors, but their specific role in SCLC metastasis is unknown. METHODS: Small RNA sequencing followed by qRT-PCR verification was used to screen the potential exosomal miRNAs that might mediate SCLC metastasis. SCLC-cell-secreted exosomes were labeled followed by incubating with vascular endothelial cells to evaluate exosome-mediated communication between SCLC cells and vascular endothelial cells. In vitro permeability assay and transendothelial migration assay were applied to investigate the function of exosomal miRNA on vascular endothelial cells. In vivo permeability assay and mouse lung colonization assay were used to verify the effects of exosomal miRNA on vascular barriers and SCLC metastasis in vivo. Proteomics technology, dual-luciferase reporter system together with rescue assays were conducted to excavate the downstream pathways of miRNA. RESULTS: Compared with 57 healthy volunteers and 46 non-small cell lung cancer patients, we identified that the level of exosomal miR-375-3p in 126 SCLC patients was obviously higher and was positively correlated with patient TNM stages. In vitro functional experiments found that SCLC-cell-secreted exosomal miR-375-3p could increase the permeability of vascular endothelial cells and facilitate the transendothelial migration of SCLC cells. In vivo, miR-375-3p-enriched exosomes also destroyed the barrier structure of lung, liver and brain tissues of mice, leaded to an increased blood vessel permeability and finally promoted SCLC metastasis. Mechanistically, SCLC-cell-secreted exosomal miR-375-3p was transferred to vascular endothelial cells. The internalized miR-375-3p broke the tight junction of vascular endothelial cells by directedly binding to the 3'UTR of tight junction protein claudin-1 and negatively regulating its expression. Overexpressing claudin-1 in vascular endothelial cells could rescue the broken vascular barriers induced by miR-375-3p. CONCLUSIONS: Our findings underline the crucial roles of exosomal miRNA-375-3p in regulating vascular endothelial barrier integrity and SCLC metastasis. miRNA-375-3p has a great potential to be a novel biomarker monitoring metastasis and guiding clinical therapeutics of SCLC patients.

The average copy number variation (CNVA) of chromosome fragments is a potential surrogate for tumor mutational burden in predicting responses to immunotherapy in non-small-cell lung cancer.

OBJECTIVES: The tumor mutational burden (TMB) is closely related to immunotherapy outcome. However, the cost of TMB detection is extremely high, which limits its use in clinical practice. A new indicator of genomic instability, the average copy number variation (CNVA), calculates the changes of 0.5-Mb chromosomal fragments and requires extremely low sequencing depth. METHODS: In this study, 50 samples (23 of which were from patients who received immunotherapy) were subjected to low-depth (10X) chromosome sequencing on the MGI platform. CNVA was calculated by the formula avg (abs (copy number-2)). In addition, CNVA and TMB were compared with regard to their ability to predict immune infiltration in 509 patients from TCGA. RESULTS: The high-CNVA group had higher expression levels of PD-L1, CD39 and CD19 and a higher degree of infiltration of CD8+ T cells and CD3 + T cells. Among the 23 patients treated with immunotherapy, the average CNVA value of the stable disease/partial response group was higher than that of the progressive disease group (P < 0.05). Whole-genome sequencing data of 509 patients from TCGA and RT-PCR results of 22 frozen specimens showed that CNVA is more effective than TMB in indicating infiltration of CD8+ T cells and expression of PD-L1, and CNVA also showed a specific positive correlation with TMB (r = 0.2728, P < 0.0001). CONCLUSIONS: Copy number variation can be a good indicator of immune infiltration and immunotherapy efficacy, and with its low cost, it is expected to become a substitute for TMB.

S100A7 as a potential diagnostic and prognostic biomarker of esophageal squamous cell carcinoma promotes M2 macrophage infiltration and angiogenesis.

Dysregulated expression of S100A7 is found in several cancers and plays an important role in tumor progression; however, its carcinogenic role in esophageal squamous carcinoma (ESCC) is still poorly understood. Here, we identified that the levels of S100A7 were remarkably upregulated in 341 tumor tissues (P < .001) and 274 serum samples (P < .001) of ESCC patients compared with normal control. It was an independent prognostic factor (P = .026). Furthermore, a new diagnostic model for ESCC based on serum S100A7, SCC, and crfra21-1 was established with area under curve (AUC) up to 0.863 (95% CI: 0.802-0.925). Mechanically, we found upregulated S100A7 could promote cell migration and proliferation through intracellular binding to JAB1 and paracrine interaction with RAGE receptors and then activates the downstream signaling pathways. In addition, exocrine S100A7 could promote M2 macrophage infiltration and polarization by up-regulating M2 macrophage associated proteins, and tumor angiogenesis by enhancing the activation of p-ErK and p-FAK pathways. Further animal experiments confirmed the role of S100A7 in promoting M2 macrophage infiltration and angiogenesis in ESCC. In conclusion, these findings highlighted the potential diagnostic and prognostic value of S100A7 in patients with ESCC. Meanwhile, our results reveal that S100A7 promotes tumor progression by activating oncogenic pathways and remodeling tumor microenvironment, which paving the way for the progress of S100A7 as a therapeutic target for cancer treatment.

Desmoglein-2 modulates tumor progression and osimertinib drug resistance through the EGFR/Src/PAK1 pathway in lung adenocarcinoma.

Desmoglein-2 (DSG2), a member of the cadherin superfamily, has been implicated in cell-cell adhesion and tumorigenesis. Here, we demonstrate that high DSG2 expression in both lung adenocarcinoma (LUAD) cell lines and tissues is associated with poor prognosis in LUAD patients. Notably, DSG2 overexpression promoted cell proliferation and migration, and increased resistance to the EGFR tyrosine kinase inhibitor osimertinib, whereas DSG2 silencing could reverse these results. Moreover, direct interaction between DSG2 and EGFR in the cell membrane stimulated EGFR signaling to promote tumorigenesis, and loss of DSG2 resulted in EGFR translocation into the cytoplasm. In addition, DSG2 was required for EGFR binding to Src; consequently, DSG2 silencing inhibited tumor cell malignancy via suppression of the EGFR-Src-Rac1-PAK1 signaling pathway. Consistent with these findings, a nude mouse xenograft model using H1975 cells demonstrated that DSG2 promoted LUAD cell growth in vivo and increased osimertinib resistance. Collectively, these observations are the first to elucidate a unique role for DSG2 in the development and progression of lung adenocarcinoma via EGFR signaling.

Molecular heterogeneity of anti-PD-1/PD-L1 immunotherapy efficacy is correlated with tumor immune microenvironment in East Asian patients with non-small cell lung cancer.

Objective: The aim of this study was to investigate how the tumor immune microenvironment differs regarding tumor genomics, as well as its impact on prognoses and responses to immunotherapy in East Asian patients with non-small cell lung cancer (NSCLC). Methods: We performed an integrated analysis using publicly available data to identify associations between anti-programmed death 1 (PD-1)/ programmed death-ligand 1 (PD-L1) immunotherapy efficacy and classic driver oncogene mutations in East Asian NSCLC patients. Four pooled and clinical cohort analyses were used to correlate driver oncogene mutation status and tumor microenvironment based on PD-L1 and CD8+ tumor-infiltrating lymphocytes (TILs). Immune infiltrating patterns were also established for genomic NSCLC subgroups using the CIBERSORT algorithm. Results: Based on East Asian NSCLC patients, TIDE analyses revealed that for anti-PD-1/PD-L1 immunotherapy, epidermal growth factor receptor (EGFR)-mutant and anaplastic lymphoma kinase (ALK)-rearranged tumors yielded inferior responses; however, although Kirsten rat sarcoma viral oncogene homolog (KRAS)-mutant tumors responded better, the difference was not statistically significant (EGFR: P = 0.037; ALK: P < 0.001; KRAS: P = 0.701). Pooled and clinical cohort analyses demonstrated tumor immune microenvironment heterogeneities correlated with oncogenic patterns. The results showed remarkably higher PD-L1- and TIL-positive KRAS-mutant tumors, suggesting KRAS mutations may drive an inflammatory phenotype with adaptive immune resistance. However, the EGFR-mutant or ALK-rearranged groups showed a remarkably higher proportion of PD-L1-/TIL-tumors, suggesting an uninflamed phenotype with immunological ignorance. Notably, similar to triple wild-type NSCLC tumors, EGFR L858R-mutant tumors positively correlated with an inflammatory phenotype, suggesting responsiveness to anti-PD-1/PD-L1 immunotherapy (P < 0.05). Furthermore, the CIBERSORT algorithm results revealed that EGFR-mutant and ALK-rearranged tumors were characterized by an enriched resting memory CD4+ T cell population (P < 0.001), as well as a lack of CD8+ T cells (P < 0.01), and activated memory CD4+ T cells (P = 0.001). Conclusions: Our study highlighted the complex relationships between immune heterogeneity and immunotherapeutic responses in East Asian NSCLC patients regarding oncogenic dependence.

The superior efficacy of anti-PD-1/PD-L1 immunotherapy in KRAS-mutant non-small cell lung cancer that correlates with an inflammatory phenotype and increased immunogenicity.

Immune checkpoint inhibitors against PD-1/PD-L1 yield improved survival rates of KRAS-mutant NSCLC patients, who conferred a poor prognosis without effective targeted therapy until now. Yet, the underlying association between KRAS mutations and immune responses remains unclear. We performed an integrated analysis of the data from publicly available repositories and from clinical center cohorts to explore the association between KRAS mutation status and tumor immunity-associated features, including PD-L1 expression, CD8+ tumor-infiltrating lymphocytes (TILs) and tumor mutational burden (TMB). Our results revealed that KRAS mutations are correlated with an inflammatory tumor microenvironment and tumor immunogenicity, resulting in superior patient response to PD-1/PD-L1 inhibitors. Meanwhile, three-pool analysis further confirmed that KRAS-mutant NSCLC patients show remarkable clinical benefit from anti-PD-1/PD-L1 immunotherapy. In addition, a KRAS-mutant lung adenocarcinoma mouse model was established to estimate the relative efficacy of anti-PD-L1 monoclonal antibody monotherapy or combination treatment with docetaxel versus docetaxel alone. Most surprisingly, we found that PD-L1 blockade combined with docetaxel did not promote an anti-tumor response. These findings uncover that PD-1/PD-L1 blockade monotherapy may be the optimal therapeutic schedule in NSCLC patients harboring KRAS mutations.

The membrane-bound and soluble form of melanotransferrin function independently in the diagnosis and targeted therapy of lung cancer.

Melanotransferrin (MFI2) is a newly identified tumor-associated protein, which consists of two forms of proteins, membrane-bound (mMFI2) and secretory (sMFI2). However, little is known about the expression pattern and their relevance in lung cancer. Here, we found that both two forms of MFI2 are highly expressed in lung cancer. The expression of MFI2 in lung cancer was detected by using the public database and qRT-PCR. Overexpression and knockdown cell lines and recombinant sMFI2 protein were used to study the function of mMFI2 and sMFI2. RNA-seq, protein chip, ChIP assay, Immunoprecipitation, ELISA, and immunofluorescence were used to study the molecular biological mechanism of mMFI2 and sMFI2. We found that mMFI2 promoted the expression of EMT's common marker N-cadherin by downregulating the transcription factor KLI4, which in turn promoted tumor metastasis; sMFI2 could promote the metastasis of autologous tumor cells in an autocrine manner but the mechanism is different from that of mMFI2. In addition, sMFI2 was proved could inhibit the migration of vascular endothelial cells and subsequently enhance angiogenic responses in a paracrine manner. We propose that the expressions and functions of the two forms of MFI2 in lung cancer are relatively independent. Specifically, mMFI2 was a potential lung cancer therapeutic target, while sMFI2 was highly enriched in advanced lung cancer, and could be used as a tumor staging index.