Prognostic model based on B cell marker genes for NSCLC patients under neoadjuvant immunotherapy by integrated analysis of single-cell and bulk RNA-sequencing data

BACKGROUND

Neoadjuvant immunotherapy has evolved as an effective option to treat non-small cell lung cancer (NSCLC). B cells play essential roles in the immune system as well as cancer progression. However, the repertoire of B cells and its association with clinical outcomes remains unclear in NSCLC patients receiving neoadjuvant immunotherapy.

METHODS

Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data for LUAD samples were accessed from the TCGA and GEO databases. LUAD-related B cell marker genes were confirmed based on comprehensive analysis of scRNA-seq data. We then constructed the B cell marker gene signature (BCMGS) and validated it. In addition, we evaluated the association of BCGMS with tumor immune microenvironment (TIME) characteristics. Furthermore, we validated the efficacy of BCGMS in a cohort of NSCLC patients receiving neoadjuvant immunotherapy.

RESULTS

A BCMGS was constructed based on the TCGA cohort and further validated in three independent GSE cohorts. In addition, the BCMGS was proven to be significantly associated with TIME characteristics. Moreover, a relatively higher risk score indicated poor clinical outcomes and a worse immune response among NSCLC patients receiving neoadjuvant immunotherapy.

CONCLUSIONS

We constructed an 18-gene prognostic signature derived from B cell marker genes based on scRNA-seq data, which had the potential to predict the prognosis and immune response of NSCLC patients receiving neoadjuvant immunotherapy.

Machine learning-based radiomics to distinguish pulmonary nodules between lung adenocarcinoma and tuberculosis

BACKGROUND

Radiomics is increasingly utilized to distinguish pulmonary nodules between lung adenocarcinoma (LUAD) and tuberculosis (TB). However, it remains unclear whether different segmentation criteria, such as the inclusion or exclusion of the cavity region within nodules, affect the results.

METHODS

A total of 525 patients from two medical centers were retrospectively enrolled. The radiomics features were extracted according to two regions of interest (ROI) segmentation criteria. Multiple logistic regression models were trained to predict the pathology: (1) The clinical model relied on clinical-radiological semantic features; (2) The radiomics models (radiomics+ and radiomics-) utilized radiomics features from different ROIs (including or excluding cavities); (3) the composite models (composite+ and composite-) incorporated both above.

RESULTS

In the testing set, the radiomics+/- models and the composite+/- models still possessed efficient prediction performance (AUC ≥ 0.94), while the AUC of the clinical model was 0.881. In the validation set, the AUC of the clinical model was only 0.717, while that of the radiomics+/- models and the composite+/- models ranged from 0.801 to 0.825. The prediction performance of all the radiomics+/- and composite+/- models were significantly superior to that of the clinical model (p < 0.05). Whether the ROI segmentation included or excluded the cavity had no significant effect on these models (radiomics+ vs. radiomics-, composite+ model vs. composite-) (p > 0.05).

CONCLUSIONS

The present study established a machine learning-based radiomics strategy for differentiating LUAD from TB lesions. The ROI segmentation including or excluding the cavity region may exert no significant effect on the predictive ability.

Peripheral blood inflammatory biomarkers dynamics reflect treatment response and predict prognosis in non-small cell lung cancer patients with neoadjuvant immunotherapy

Neoadjuvant immunotherapy has significantly changed the therapeutic approach for treating patients with surgically resectable non-small cell lung cancer (NSCLC). Here, peripheral blood inflammation-based biomarkers as well as previously less focused eosinophil fraction, modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) were systematically included to comprehensively analyze their potential in predicting neoadjuvant immunotherapy efficacy and prognosis. We enrolled 189 patients (94 in training and 95 in validation cohorts) with stage I-III B surgically resectable NSCLC treated with neoadjuvant immunotherapy from the National Cancer Center of China. Baseline and post-treatment eosinophils fraction, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), PNI, mGPS, and their changes were calculated and analyzed for correlation with neoadjuvant immunotherapy efficacy and prognosis. In patients in the major pathological response (MPR) group, the post-treatment eosinophil fraction was significantly high, and NLR, PLR, SII, and MLR were significantly lower compared to the non-MPR group in both the training and validation cohorts. The receiver operating characteristic curve showed that post-treatment, eosinophil fraction and SII and their changing were two of the most important factors. Univariate and multivariate logistic regression analyses showed that post-treatment eosinophil fraction, SII, mGPS, and ΔSII could independently predict MPR in patients treated with neoadjuvant immunotherapy. Survival analysis showed a significant correlation between high post-treatment NLR, PLR, SII, mGPS, and their changes in ΔNLR and ΔSII elevation with poor overall survival and event-free survival of patients. Our results suggest that inflammatory biomarkers could predict the patient's response to neoadjuvant immunotherapy and prognosis.

Single-cell RNA sequencing analysis reveals transcriptional heterogeneity of multiple primary lung cancer

INTRODUCTION

With the advancements in early diagnosis, more and more patients with multiple primary lung cancer (MPLC) have been identified. However, the progression of MPLC involves complex changes in cell composition and metabolic function, which remains largely controversial.

OBJECTIVE

Our study aims to comprehensively reveal the cellular characteristics and inter-cellular connections of MPLC.

METHODS

We performed scRNA-seq from 23 samples of six MPLC patients, combined with bulk whole-exome sequencing. We performed trajectory analysis to investigate the transition of different cell types during the development of MPLC.

RESULTS

A total of 1 67 397 cells were sequenced derived from tumour and adjacent tissues of MPLC patients, and tumour, normal, immune and stromal cells were identified. Two states of epithelial cells were identified, which were associated with immune response and cell death, respectively. Furthermore, both CD8+ naïve and memory T cells participated in the differentiation of CD8+ T cells. The terminal states of CD8+ T cells were exhausted T cells and cytotoxic T cells, which positively regulated cell death and were implicated in the regulation of cytokine production, respectively. Two main subpopulations of B cells with distinct functions were identified, which participate in the regulation of the immune response and antigen presentation, respectively. In addition, we found a specific type of endothelial cells that were abundant in tumour samples, with an increasing trend from normal to tumour samples.

CONCLUSIONS

Our study showed the comprehensive landscape of different cells of MPLC, which might reveal the key cellular mechanisms and, therefore, may provide new insights into the early diagnosis and treatment of MPLC.

Plasma extracellular vesicle long RNAs predict response to neoadjuvant immunotherapy and survival in patients with non-small cell lung cancer

Neoadjuvant immunotherapy has brought new hope for patients with non-small cell lung cancer (NSCLC). However, limited by the lack of clinically feasible markers, it is still difficult to select NSCLC patients who respond well and to predict patients' clinical outcomes before the treatment. Before the treatment, we isolated plasma extracellular vesicles (EVs) from three cohorts (discovery, training and validation) of 78 NSCLC patients treated with neoadjuvant immunotherapy. To identify differentially-expressed EV long RNAs (exLRs), we employed RNA-seq in the discovery cohort. And we subsequently used qRT-PCR to establish and validate the predictive signature in the other two cohorts. We have identified 8 candidate exLRs from 27 top-ranked exLRs differentially expressed between responders and non-responders, and tested their expression with qRT-PCR in the training cohort. We finally identified H3C2 (P = 0.029), MALAT1 (P = 0.043) and RPS3 (P = 0.0086) significantly expressed in responders for establishing the predictive signature. Integrated with PD-L1 expression, our signature performed well in predicting immunotherapeutic responses in the training (AUC=0.892) and validation cohorts (AUC=0.747). Furthermore, our signature was proven to be a predictor for favorable prognosis of patients treated with neoadjuvant immunotherapy, which demonstrates the feasibility of our signature in clinical practices (P = 0.048). Our results demonstrate that the exLR-based signature could accurately predict responses to neoadjuvant immunotherapy and prognosis in NSCLC patients.

Multimodal analysis of cell-free DNA whole-methylome sequencing for cancer detection and localization

Multimodal epigenetic characterization of cell-free DNA (cfDNA) could improve the performance of blood-based early cancer detection. However, integrative profiling of cfDNA methylome and fragmentome has been technologically challenging. Here, we adapt an enzyme-mediated methylation sequencing method for comprehensive analysis of genome-wide cfDNA methylation, fragmentation, and copy number alteration (CNA) characteristics for enhanced cancer detection. We apply this method to plasma samples of 497 healthy controls and 780 patients of seven cancer types and develop an ensemble classifier by incorporating methylation, fragmentation, and CNA features. In the test cohort, our approach achieves an area under the curve value of 0.966 for overall cancer detection. Detection sensitivity for early-stage patients achieves 73% at 99% specificity. Finally, we demonstrate the feasibility to accurately localize the origin of cancer signals with combined methylation and fragmentation profiling of tissue-specific accessible chromatin regions. Overall, this proof-of-concept study provides a technical platform to utilize multimodal cfDNA features for improved cancer detection.

Utility of 18F-FDG uptake in predicting major pathological response to neoadjuvant immunotherapy in patients with resectable non‑small cell lung cancer

PURPOSE

The aim of present study was to investigate the efficiency of ¹⁸F-FDG uptake in predicting major pathological response (MPR) in resectable non-small cell lung cancer (NSCLC) patients with neoadjuvant immunotherapy.

METHODS

A total of 104 patients with stage I-IIIB NSCLC were retrospectively derived from National Cancer Center of China, of which 36 cases received immune checkpoint inhibitors (ICIs) monotherapy (I-M) and 68 cases with ICI combination therapy (I-C). ¹⁸F-FDG PET-CT scans were performed at baseline and after neoadjuvant therapy (NAT). Receiver-operating characteristic (ROC) curve analyses were conducted and area under ROC curve (AUC) was calculated for biomarkers including maximum standardized uptake value (SUVmax), inflammatory biomarkers, tumor mutation burden (TMB), PD-L1 tumor proportion score (TPS) and iRECIST.

RESULTS

Fifty-four resected NSCLC tumors achieved MPR (51.9%, 54/104). In both neoadjuvant I-M and I-C cohorts, post-NAT SUVmax and the percentage changes of SUVmax (ΔSUVmax%) were significantly lower in the patients with MPR versus non-MPR (p < 0.01), and were also negatively correlated with the degree of pathological regression (p < 0.01). The AUC of ΔSUVmax% for predicting MPR was respectively 1.00 (95% CI: 1.00-1.00) in neoadjuvant I-M cohort and 0.94 (95% CI: 0.86-1.00) in I-C cohort. Baseline SUVmax had a statistical prediction value for MPR only in I-M cohort, with an AUC up to 0.76 at the threshold of 17.0. ΔSUVmax% showed an obvious advantage in MPR prediction over inflammatory biomarkers, TMB, PD-L1 TPS and iRECIST.

CONCLUSION

¹⁸F-FDG uptake can predict MPR in NSCLC patients with neoadjuvant immunotherapy.

Single-cell RNA-sequencing data reveals the genetic source of extracellular vesicles in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is invasive cancer and the complex mechanisms underlying carcinogenesis remain unclear. Extracellular vesicles (EVs), secreted by most cell types, serve as a critical factor in tumorigenesis via intercellular communications. Our study aims to investigate the cellular origin of EVs in ESCC, and unveil the unknown molecular and cellular mechanisms underlying cell-cell communications. Six ESCC patients were enrolled and single-cell RNA sequencing (scRNA-seq) analyses were conducted to screen different cell subpopulations. The genetic origin of EVs was tracked using the supernatant from different cellular extracts. Nanoparticle tracking analysis (NTA), western blot analysis, and transmission electron microscopy (TEM) were performed for validation. Using scRNA-seq analysis, eleven cell subpopulations were identified in ESCC. Differences in gene expression in EVs between malignant and non-malignant esophageal tissues were found. Our findings demonstrated that epithelial cells releasing EVs were the most prevalent in malignant tissues, while endothelial cells and fibroblasts releasing EVs were predominant in non-malignant tissues. Furthermore, the high levels of gene expression in EVs released from these cells were correlated significantly with a worse prognosis. Our findings revealed the genetic origin of EVs in malignant and non-malignant esophageal tissues and provided a comprehensive overview of the associated cell-cell interactions in ESCC.

Comprehensive analysis of the immunological implication and prognostic value of CXCR4 in non-small cell lung cancer

CXCR4 (C-X-C chemokine receptor type 4) is the most commonly expressed of all chemokine receptors in malignant tumors. However, studies on CXCR4 in non-small cell lung cancer (NSCLC) tumor immune microenvironment, including those determining its immune efficacy and prognostic potential, are still scarce. Therefore, in this study, we determined the ability of CXCR4 to predict immunotherapy response and prognosis in NSCLC using immunohistochemical staining and RT-PCR, respectively, in two independent cohorts from the National Cancer Center of China. We analyzed transcriptome sequencing data and clinical information from multiple public databases to assess immune cell infiltration in NSCLC and constructed immune risk prognostic signatures based on CXCR4-related immunomodulators. We found that immune cell infiltration is significant differences in NSCLC tissues and is moderately correlated with CXCR4 expression. High CXCR4 expression was significantly associated with poor prognosis in NSCLC patients and a higher response rate to immunotherapy. The ROC curve showed that CXCR4 expression exhibited excellent performance in predicting the efficacy of immunotherapy in NSCLC. We identified 30 CXCR4-related immunomodulators in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) and constructed immune prognostic signatures based on CXCR4-related immunomodulators and CXCR4-related mutant genes. The signature-based prognostic risk score showed good performance in predicting patient prognosis in both LUAD and LUSC; high risk scores were significantly associated with poor prognosis (P < 0.0001) and was established as an independent prognostic factor by multivariate Cox regression. We postulate that CXCR4 is a potential predictive marker of immunotherapy efficacy in NSCLC and should be used in clinical settings. Moreover, the constructed signatures may be valuable in predicting patient prognosis in NSCLC.

Association between radiotherapy and risk of second primary malignancies in patients with resectable lung cancer: a population-based study

BACKGROUND

The most common form of treatment for non-metastatic lung cancer is surgery-based combination therapy, which may also include adjuvant radiotherapy or chemotherapy. Second primary malignancies (SPMs) are uncommon but significant radiation side effects in patients with resectable lung cancer, and SPMs have not been adequately investigated. Our study aims to assess the correlations of radiotherapy with the development of SPMs in patients with resectable lung cancer.

METHODS

We screened for any primary malignancy that occurred more than five years after the diagnosis of resectable lung cancer. Based on the large cohort of the Surveillance, Epidemiology and End Results database, radiotherapy-correlated risks were estimated using the Poisson regression analysis and the cumulative incidence of SPMs was calculated using Fine-Gray competing risk regression analysis.

RESULTS

Among the 62,435 patients with non-metastatic lung cancer undergoing surgery, a total of 11,341 (18.16%) patients have received radiotherapy. Our findings indicated that radiotherapy was substantially related to a high risk of main second solid malignancies (RR = 1.21; 95%CI, 1.08 to 1.35) and a negligible risk of main second hematologic malignancies (RR = 1.08; 95%CI, 0.84 to 1.37). With the greatest number of patients, the risk of acquiring a second primary gastrointestinal cancer was the highest overall (RR = 1.77; 95 percent CI, 1.44 to 2.15). The cumulative incidence and standardized incidence ratios of SPMs revealed similar findings. Furthermore, the young and the elderly may be more vulnerable, and the highest risk of acquiring most SPMs was seen more than ten years after lung cancer diagnosis. Additionally, more attention should be paid to the second primary gastrointestinal cancer in young individuals with resectable lung cancer.

CONCLUSION

After receiving radiotherapy, an increased risk of developing second primary solid and gastrointestinal cancers was observed for patients with resectable lung cancer. The prevention of SPMs associated with radiotherapy requires further attention.

Integrating microarray-based spatial transcriptomics and single-cell RNA-sequencing reveals tissue architecture in esophageal squamous cell carcinoma

Background

The tumor microenvironment (TME) serves as an important factor in tumorigenesis and metastasis. Although distinct cell subsets can be identified via single-cell RNA sequencing (scRNA-seq), the spatial composition of cells within the TME is difficult to characterise.

Methods

Tissue samples were collected from three patients with esophageal squamous cell carcinoma (ESCC), and scRNA-seq was performed to identify distinct cell subsets. In addition, a microarray-based spatial transcriptomics (ST) method was used to characterise the spatial landscape of expression data via an array of spots. Using multimodal intersection analysis (MIA) to integrate scRNA-seq and ST, the exact cellular components of the tumor and stromal regions were annotated.

Findings

The subpopulations of seven stromal cells were identified within the TME of ESCC, and the architecture of scRNA-seq-determined subsets was mapped in cancer and stromal regions. The distribution of various stromal cells and their subpopulations was heterogeneous. Compared with immune cells, non-immune stromal cells were significantly enriched in the TME. Most subsets of epithelial cells were enriched in the cancer regions, whereas inflammatory cancer-associated fibroblasts were correlated with the stromal regions. Furthermore, TME features were different between metastatic and non-metastatic samples and between the primary and metastatic sites of the metastatic sample.

Interpretation

This study revealed the spatial landscape of various cell subsets within the TME and the potential cross-talk among diverse cells, which provides novel insights into cancer intervention.

Funding

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

TIGIT/CD47 dual high expression predicts prognosis and is associated with immunotherapy response in lung squamous cell carcinoma

Background

Recent studies indicated that T cell immunoreceptor with immunoglobulin and ITIM domains (TIGIT) and cluster of differentiation 47 (CD47) have emerged as new potential immunotherapy targets. However, the roles of TIGIT and CD47 in lung squamous cell carcinoma (LUSC) have not been fully illustrated.

Methods

The specimens and clinicopathological information from 190 LUSC patients who underwent surgeries in our center were retrospectively collected. Immunohistochemical staining for TIGIT and CD47 was conducted. Transcriptional and clinical data of 479 LUSC were downloaded from The Cancer Genome Atlas (TCGA).

Results

In the TCGA LUSC cohort, 142 (29.6%) cases were TIGIT/CD47 dual high expression at RNA level. The expression levels of TIGIT and CD47 were significantly correlated (p < 0.001). The proportions of patients with high TIGIT expression (p = 0.001) and high TIGIT/CD47 dual high expression (p = 0.049) were both higher in female cases. Advanced TNM stage (p = 0.006) and TIGIT/CD47 dual high expression (p = 0.047) were independent prognostic factors for LUSC. In the 190 LUSC cohort of our center, 75 (39.5%) cases were TIGIT/CD47 dual high expression at protein level. Cross‐table analysis showed a correlation between TIGIT and CD47 expression. Older age (p = 0.001), advanced TNM stage (p < 0.001) and TIGIT/CD47 dual high expression (p = 0.046) were independent prognostic factors in our cohort.

Conclusion

We found that TIGIT and CD47 dual high expression was associated with poor prognosis in LUSC. We speculated that patients with dual high expression of CD47/TIGIT might be suitable for new target immunotherapy in the future.

Plasma extracellular vesicle long RNA profiling identifies a diagnostic signature for stage I lung adenocarcinoma

Background

Methods

Results

Conclusions

Identification of prognostic genes and tumor-infiltrating immune cells in the tumor microenvironment of esophageal squamous cell carcinoma and esophageal adenocarcinoma

BACKGROUND

Esophageal cancer (EC) is a highly aggressive malignancy that is classified as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Infiltrating stromal/immune cells, a major component of the tumor immune microenvironment (TIME), have prognostic significance in various cancers.

METHODS

In this study we investigated genes and immune factors in the tumor microenvironment (TME) of ESCC and EAC that can serve as prognostic biomarkers. Stromal and immune scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) algorithm based on gene expression profiles of patient-derived tumor tissues in The Cancer Genome Atlas database. The correlation between ESTIMATE scores and survival rates in EC were analyzed. A comparison of high and low stromal/immune score groups revealed multiple differentially expressed genes (DEGs) as candidate prognostic genes; their role in immune-related biological processes was evaluated by functional and protein-protein interaction (PPI) network analyses, and the genes were validated using Gene Expression Omnibus datasets. Additionally, 22 tumor-infiltrating immune cell (TIIC) subsets were analyzed using the CIBERSORT algorithm.

RESULTS

Median stromal score was higher whereas immune score was lower in ESCC than in EAC (both P<0.01). Stromal score was lower in female as compared to male ESCC patients (P<0.05), and was significantly correlated with T stage (P<0.05). In EAC, median immune score was higher in female as compared to male patients (P<0.05) and was correlated with tumor-node-metastasis stage (P<0.05). The identified DEGs were mainly involved in lymphocyte (especially T-lymphocyte) activation and carbohydrate binding. Moreover, the levels of infiltrating resting-stage dendritic cells, CD8+ T cells, naïve B cells, activated mast cells, and resting memory CD4+ T cells were significantly correlated with EC prognosis (P<0.05).

CONCLUSIONS

The immune microenvironment of ESCC and EAC are quite different. We have found genes with prognostic value in multiple tumor databases.

Severe hypoglycemia and finger clubbing in a patient with a BRCA1 mutation in a solitary fibrous tumor: a case report

Solitary fibrous tumors (SFTs) are rare tumors that stem from mesenchymal cells of submesothelial tissues belonging to the pleura. They can occur in many places such as the spinal canal, intracranial, neck, kidney, liver, pelvis, limbs and other places, most commonly in the chest and abdomen. Pleural SFTs are one of the most common types, and are common in middle-aged people. Pleural SFTs can have an insidious expression, such that the illness can progress for years before diagnosis. SFTs can induce paraneoplastic syndromes, such as reactive hypoglycemia [Doege-Potter syndrome (DPS)] or hypertrophic osteoarthropathy [Pierre-Marie-Bamberger syndrome (PMBS)]. In this article, we report a case study of a 51-year-old man with pleural SFTs. Preoperative imaging examinations, including chest X-ray, computed tomography (CT), and magnetic resonance imaging (MRI), showed a huge mass in the right thoracic cavity, compressing surrounding tissues and organs and may invade other tissues. In addition, he suffers from severe hypoglycemia and finger clubbing, and has successfully undergone a complete resection, and now attends regular follow-up appointments. The paraneoplastic syndromes have resolved, and no recurrence has been found. Importantly, we used next-generation sequencing (NGS) to explore the molecular characteristics of the patient’s pathological tissue at the DNA level and mRNA level, and found that breast cancer gene 1 (BRAC1) mutations may be an important pathogenic factor.

Comprehensive Analysis of PD-L1 Expression, Immune Infiltrates, and m6A RNA Methylation Regulators in Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancer types and represents a threat to global public health. N6-Methyladenosine (m6A) methylation plays a key role in the occurrence and development of many tumors, but there are still few studies investigating ESCC. This study attempts to construct a prognostic signature of ESCC based on m6A RNA methylation regulators and to explore the potential association of these regulators with the tumor immune microenvironment (TIME).

Methods

The transcriptome sequencing data and clinical information of 20 m6A RNA methylation regulators in 453 patients with ESCC (The Cancer Genome Atlas [TCGA] cohort, n = 95; Gene Expression Omnibus [GEO] cohort, n = 358) were obtained. The differing expression levels of m6A regulators between ESCC and normal tissue were evaluated. Based on the expression of these regulators, consensus clustering was performed to investigate different ESCC clusters. PD-L1 expression, immune score, immune cell infiltration and potential mechanisms among different clusters were examined. LASSO Cox regression analysis was utilized to obtain a prognostic signature based on m6A RNA methylation modulators. The relationship between the risk score based on the prognostic signature and the TIME of ESCC patients was studied in detail.

Results

Six m6A regulators (METTL3, WTAP, IGF2BP3, YTHDF1, HNRNPA2B1 and HNRNPC) were observed to be significantly highly expressed in ESCC tissues. Two molecular subtypes (clusters 1/2) were determined by consensus clustering of 20 m6A modulators. The expression level of PD-L1 in ESCC tissues increased significantly and was significantly negatively correlated with the expression levels of YTHDF2, METL14 and KIAA1429. The immune score, CD8 T cells, resting mast cells, and regulatory T cells (Tregs) in cluster 2 were significantly increased. Gene set enrichment analysis (GSEA) shows that this cluster involves multiple hallmark pathways. We constructed a five-gene prognostic signature based on m6A RNA methylation, and the risk score based on the prognostic signature was determined to be an independent prognostic indicator of ESCC. More importantly, the prognostic value of the prognostic signature was verified using another independent cohort. m6A regulators are related to TIME, and their copy-number alterations will dynamically affect the number of tumor-infiltrating immune cells.

Conclusion

Our study established a strong prognostic signature based on m6A RNA methylation regulators; this signature was able to accurately predict the prognosis of ESCC patients. The m6A methylation regulator may be a key mediator of PD-L1 expression and immune cell infiltration and may strongly affect the TIME of ESCC.

Elevated Heterogeneous Nuclear Ribonucleoprotein C Expression Correlates With Poor Prognosis in Patients With Surgically Resected Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD), as the most common histological subtype of lung cancer, is a high-grade malignancy and a leading cause of cancer-related death globally. Identification of biomarkers with prognostic value is of great significance for the diagnosis and treatment of LUAD. Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an RNA-binding protein “reader” of N6-methyladenosine (m⁶A) methylation, and is related to the progression of various cancers; however, its role in LUAD is unclear. The aims of this study aims were to study the expression and prognostic value of HNRNPC in LUAD.

Methods

The Oncomine database and gene expression profiling interactive analysis (GEPIA) were used for preliminary exploration of HNRNPC expression and prognostic value in LUAD. LUAD cases from The Cancer Genome Atlas (TCGA) (n = 416) and the Kaplan-Meier plotter database (n = 720) were extracted to study the differential expression and prognostic value of HNRNPC. HNRNPC expression in the National Cancer Center of China (NCC) cohort was analyzed by immunohistochemical staining, and the relationship between HNRNPC expression and survival rate evaluated using the Kaplan-Meier method and log-rank test. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. Several pathways that were significantly enriched in the HNRNPC high expression group were identified by Gene Set Enrichment Analysis (GSEA).

Results

Five data sets from the Oncomine and GEPIA databases all supported that HNRNPC expression is significantly higher in LUAD than in normal lung tissue. In TCGA cohort, HNRNPC was highly expressed in LUAD tissues and significantly related to age, sex, smoking history, ethnicity, lymph node metastasis, and TNM staging (P < 0.001). High HNRNPC expression was significantly correlated with poor prognosis in the three cohorts (NCC, TCGA, and K-M plotter) (P < 0.05). Multivariate Cox regression analysis showed that HNRNPC expression was an independent prognostic factor in both TCGA and NCC cohorts (P < 0.05). Further, 10 significantly enriched pathways were identified from TCGA data and 118 lung cancer cell lines in CCLE, respectively.

Conclusions

High HNRNPC expression is significantly related to poor overall survival in patients with LUAD, suggesting that HNRNPC may be a cancer-promoting factor and a potential prognostic biomarker in LUAD.

Prognostic Impact of IGF2BP3 Expression in Patients with Surgically Resected Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) acts as the representative histological subtype regarding lung cancer, and its mortality and morbidity remain high. Therefore, more therapeutic targets are needed. Insulin-like growth factor 2 messenger RNA-binding proteins (IGF2BPs), a class of RNA-binding proteins, including IGF2BP1, IGF2BP2, and IGF2BP3, are considered to be the "reader" of N6-methyladenosine (m6A) methylation and remarkably affects cancer occurrence and development. Studies have shown that IGF2BP3 has prognostic potential in multiple public databases compared with other members of the IGF2BPs family. This research aims to use the expression data of IGF2BP3 in multiple cohorts to explore the expression as well as prognostic significance of IGF2BP3 in LUAD. Based on the six datasets from the Oncomine database, LUAD tissue presented obviously higher IGF2BP3 expression relative to normal tissue. In the three cohorts of The Cancer Genome Atlas (TCGA), Gene expression profiling interactive analysis, and Gene Expression Omnibus, IGF2BP3 was abnormally highly expressed in LUAD, and it could lead to a weaker prognosis (p < 0.05). The cohort from National Cancer Center of China (NCC) verified the prognostic value of IGF2BP3, and the high IGF2BP3 expression could be remarkably related to gender, tumor length, differentiation, and T stage (p < 0.05). Cox regression analysis of TCGA and NCC cohorts consistently showed that IGF2BP3 expression could serve for independently predicting the prognosis of LUAD patients (p < 0.05). Ten hallmark pathways with significant enrichment were identified. IGF2BP3 is abnormally highly expressed in LUAD tissue, and can lead to worse overall survival. In summary, IGF2BP3 may be an oncogene and potential prognostic biomarker of LUAD.

Crystal structures of 1-aminocyclopropane-1-carboxylate (ACC) synthase in complex with aminoethoxyvinylglycine and pyridoxal-5'-phosphate provide new insight into catalytic mechanisms

The structures of tomato 1-aminocyclopropane-1-carboxylate synthase (ACS) in complex with either cofactor pyridoxal-5'-phosphate (PLP) or both PLP and inhibitor aminoethoxyvinylglycine have been determined by x-ray crystallography. The structures showed good conservation of the catalytic residues, suggesting a similar catalytic mechanism for ACS and other PLP-dependent enzymes. However, the proximity of Tyr152 to the C-gamma-S bond of model substrate S-adenosylmethionine implies its critical role in the catalysis. The concerted accomplishment of catalysis by cofactor PLP and a protein residue, as proposed on the basis of the ACS structures in this paper, may represent a general scheme for the diversity of PLP-dependent catalyses. PLP-dependent enzymes have been categorized into four types of folds. A structural comparison revealed that a core fragment of ACS in fold type I is superimposable over tryptophan synthase beta subunit in fold type II and mouse ornithine decarboxylase in fold type III, thus suggesting a divergent evolution of PLP-dependent enzymes.

Structure of NaeI-DNA complex reveals dual-mode DNA recognition and complete dimer rearrangement

NaeI, a novel DNA endonuclease, shows topoisomerase and recombinase activities when a Lys residue is substituted for Leu 43. The NaeI-DNA structure demonstrates that each of the two domains of NaeI recognizes one molecule of DNA duplex. DNA recognition induces dramatic rearrangements: narrowing the binding site of the Topo domain 16 A to grip DNA, widening that of the Endo domain 8 A to encircle and bend DNA 45 degrees for cleavage, and completely rebuilding the homodimer interface. The NaeI-DNA structure presents the first example of novel recognition of two copies of one DNA sequence by two different amino acid sequences and two different structural motifs in one polypeptide.

Uptake and distribution of rare earth elements in rice seeds cultured in fertilizer solution of rare earth elements

The uptake behavior of rare earth elements (REEs) under pot conditions using deionized water and a REE fertilizer solution as the culture media as well as the distribution of REEs in rice proteins were studied. The uptake of REEs in rice seeds increased dramatically after a lag period of approximately three days. Roots can accumulate a much higher content of REEs than germs and the resting seeds. The REE content in each water-soluble (albumin) and salt-soluble (globulin) component of the rice seeds accounted for 5-8% and 4-6% of the total REEs, respectively. However, there are less than 1.5% of the total REEs were found in the alcohol-soluble (prolamin) and acetic acid-soluble (glutelin) components. The high performance liquid chromatography (HPLC) in the gel permeation and the reserved-phase were used to monitor changes in the molecular weight distribution changes of the soluble proteins of rice seeds during germination after having been cultured in the same solution for seven days. No changes occurred in the prolamin, while a slight change occurred in the albumin, globulin and glutelin. Fractionation of the albumin of rice seeds cultured in a REE fertilizer solution on the Sephadex G-100 column indicated that REEs, especially Ce, La, Pr and Nd, were associated mainly with biological compounds of a molecular weight between 10,000 and 12,000.

Isolation and characterization of rare earth element-binding protein in roots of maize

Rare earth element-binding protein was isolated from maize, which was grown under greenhouse conditions and characterized in terms of molecular weight, amino acid composition, and ultraviolet absorption. The molecular weight of the maize protein was determined to be 183,000, with two distinct subunits of approximately molecular weights of 22,000 and 69,000, respectively. The protein is particularly rich in asparagine/aspartic acid, glutamine/glutamic acid, glycine, alanine, and leucine and contains 8.0% of covalently bound carbohydrate. The ultraviolet absorption of the protein is low at 280 nm and no change in the adsorption was observed with a change in pH. Compared to the unique features of the metallothioneins with a molecular weight of approximately 10,000, a high cysteine content of 30%, high absorption at 254 nm and a low absorption at 280 nm, and absorption change with pH, the REE-binding protein is unlikely to be plant metallothionein in nature. It was found that an almost twofold greater concentration was found for most of the REEs in the protein isolated from the maize with REE fertilizer use than that without REE fertilizer. This study suggests that the REE-binding protein is a glycoprotein and REEs can be firmly bound with the protein of maize roots.

Crystal structure of NaeI-an evolutionary bridge between DNA endonuclease and topoisomerase

NAE:I is transformed from DNA endonuclease to DNA topoisomerase and recombinase by a single amino acid substitution. The crystal structure of NAE:I was solved at 2.3 A resolution and shows that NAE:I is a dimeric molecule with two domains per monomer. Each domain contains one potential DNA recognition motif corresponding to either endonuclease or topoisomerase activity. The N-terminal domain core folds like the other type II restriction endonucleases as well as lambda-exonuclease and the DNA repair enzymes MutH and Vsr, implying a common evolutionary origin and catalytic mechanism. The C-terminal domain contains a catabolite activator protein (CAP) motif present in many DNA-binding proteins, including the type IA and type II topoisomerases. Thus, the NAE:I structure implies that DNA processing enzymes evolved from a few common ancestors. NAE:I may be an evolutionary bridge between endonuclease and DNA processing enzymes.