Construction of Metastasis-Specific Regulation Network in Ovarian Cancer Based on Prognostic Stemness-Related Signatures.

WE aimed to reveal the correlation between ovarian cancer (OV) metastasis and cancer stemness in OV. RNA-seq data and clinical information of 591 OV samples (551 without metastasis and 40 with metastasis) were obtained from TCGA. The edgeR method was used to determine differentially expressed genes (DEGs) and transcription factors (DETFs). Then, mRNA expression-based stemness index was calculated using one-class logistic regression (OCLR). Weighted gene co-expression network analysis (WGCNA) was used to define stemness-related genes (SRGs). Univariate and multivariate Cox proportional hazard regression were conducted to identify the prognostic SRGs (PSRGs). PSRGs, DETFs, and 50 hallmark pathways quantified by gene set variation analysis (GSVA) were integrated into Pearson co-expression analysis. Significant co-expression interactions were utilized to construct an OV metastasis-specific regulation network. Cell communication analysis was carried out based on single cell RNA sequencing data to explore the molecular regulation mechanism of OV. Eventually, assay for targeting accessible-chromatin with high throughout sequencing (ATAC), chromatin immunoprecipitation sequencing (ChIP-seq) validation, and multiple data sets were used to validate the expression levels and prognostic values of key stemness-related signatures. Moreover, connectivity map (CMap) was used to identify potential inhibitors of stemness-related signatures. Based on edgeR, WGCNA, and Cox proportional hazard regression, 22 PSRGs were defined to construct a prognostic prediction model for metastatic OV. In the metastasis-specific regulation network, key TF-PSRS interaction pair was NR4A1-EGR3 (correlation coefficient = 0.81, p < 0.05, positive), and key PSRG-hallmark pathway interaction pair was EGR3-TNFα signaling via NFκB (correlation coefficient = 0.44, p < 0.05, positive), which were validated in multi-omics databases. Thioridazine was postulated to be the most significant compound in treatment of OV metastasis. PSRGs played critical roles in OV metastasis. Specifically, EGR3 was the most significant PSRG, which was positively regulated by DETF NR4A1, inducing metastasis via TNFα signaling.

Postnatal eye size in mice is controlled by SREBP2-mediated transcriptional repression of Lrp2 and Bmp2.

Eye size is a key parameter of visual function, but the precise mechanisms of eye size control remain poorly understood. Here, we discovered that the lipogenic transcription factor sterol regulatory element-binding protein 2 (SREBP2) has an unanticipated function in the retinal pigment epithelium (RPE) to promote eye size in postnatal mice. SREBP2 transcriptionally represses low density lipoprotein receptor-related protein 2 (Lrp2), which has been shown to restrict eye overgrowth. Bone morphogenetic protein 2 (BMP2) is the downstream effector of Srebp2 and Lrp2, and Bmp2 is suppressed by SREBP2 transcriptionally but activated by Lrp2. During postnatal development, SREBP2 protein expression in the RPE decreases whereas that of Lrp2 and Bmp2 increases as the eye growth rate reduces. Bmp2 is the key determinant of eye size such that its level in mouse RPE inversely correlates with eye size. Notably, RPE-specific Bmp2 overexpression by adeno-associated virus effectively prevents the phenotypes caused by Lrp2 knock out. Together, our study shows that rapid postnatal eye size increase is governed by an RPE-derived signaling pathway, which consists of both positive and negative regulators of eye growth.

Mechanisms of Progression and Heterogeneity in Multiple Nodules of Lung Adenocarcinoma.

Lung cancer remains the leading cause of cancer-related death worldwide. Lung adenocarcinoma (LUAD) is thought to be caused by precursor lesions of atypical adenoma-like hyperplasia and may have extensive in situ growth before infiltration. To explore the relevant factors in heterogeneity and evolution of lung adenocarcinoma subtypes, the authors perform single-cell RNA sequencing (scRNA-seq) on tumor and normal tissue from five multiple nodules' LUAD patients and conduct a thorough gene expression profiling of cancer cells and cells in their microenvironment at single-cell level. This study gives a deep understanding of heterogeneity and evolution in early glandular neoplasia of the lung. This dataset leads to discovery of the changes in the immune microenvironment during the development of LUAD, and the development process from adenocarcinoma in situ (AIS) to invasive adenocarcinoma (IAC). This work sheds light on the direction of early tumor development and whether they are homologous.

mRNA Network: Solution for Tracking Chemotherapy Insensitivity in Small-Cell Lung Cancer.

Background: Small-cell lung cancer (SCLC) has poor prognosis and is prone to drug resistance. It is necessary to search for possible influencing factors for SCLC chemotherapy insensitivity. Therefore, we proposed an mRNA network to track the chemotherapy insensitivity in SCLC. Methods: Six samples of patients with SCLC were recruited for RNA sequencing. TopHat2 and Cufflinks were used to make differential analysis. Functional analysis was applied as well. Finally, multidimensional validation was applied for verifying the results we obtained by experiment. Results: This study was a trial of drug resistance in 6 SCLC patients after first-line chemotherapy. The top 10 downregulated genes differentially expressed in the chemo-insensitive group were SERPING1, DRD5, PARVG, PRAME, NKX1-1, MCTP2, PID1, PLEKHA4, SPP1, and SLN. Cell-cell signaling by Wnt (p=6.98E - 21) was the most significantly enriched GO term in biological process, while systemic lupus erythematosus (p=6.97E - 10), alcoholism (p=1.01E - 09), and transcriptional misregulation in cancer (p=0.00227988) were the top three ones of KEGG pathways. In multiple public databases, we also highlighted and verified the vital role of glycolysis/gluconeogenesis pathway and corresponding genes in chemo-insensitivity in SCLC. Conclusion: Our study confirmed some SCLC chemotherapy insensitivity-related genes, biological processes, and pathways, thus constructing the chemotherapy-insensitive network for SCLC.

A narrative review of tumor heterogeneity and challenges to tumor drug therapy.

OBJECTIVE: To accurately evaluate tumor heterogeneity, make multidimensional diagnosis according to the causes and phenotypes of tumor heterogeneity, and assist in the individualized treatment of tumors. BACKGROUND: Tumor heterogeneity is one of the most essential characteristics of malignant tumors. In tumor recurrence, development, and evolution, tumor heterogeneity can lead to the formation of different cell groups with other molecular characteristics. Tumor heterogeneity can be characterized by the uneven distribution of tumor cell subsets of other genes between and within the disease site (spatial heterogeneity) or the time change of cancer cell molecular composition (temporal heterogeneity). The discovery of tumor targeting drugs has dramatically promoted tumor therapy. However, the existence of heterogeneity seriously affects the effect of tumor treatment and the prognosis of patients. METHODS: The literature discussing tumor heterogeneity and its resistance to tumor therapy was broadly searched to analyze tumor heterogeneity as well as the challenges and solutions for gene detection and tumor drug therapy. CONCLUSIONS: Tumor heterogeneity is affected by many factors consist of internal cell factors and cell microenvironment. Tumor heterogeneity greatly hinders effective and individualized tumor treatment. Understanding the fickle of tumors in multiple dimensions and flexibly using a variety of detection methods to capture the changes of tumors can help to improve the design of diagnosis and treatment plans for cancer and benefit millions of patients.

Risk-score model to predict prognosis of malignant airway obstruction after interventional bronchoscopy.

BACKGROUND: Interventional bronchoscopy exhibits substantial effects for patients with malignant airway obstruction (MAO), while little information is available regarding the potential prognostic factors for these patients. METHODS: Between October 31, 2016, and July 31, 2019, a total of 150 patients undergoing interventional bronchoscopy and histologically-confirmed MAO were collected, in which 112 eligible participants formed the cohort for survival study. External validation cohort from another independent institution comprised 33 MAO patients with therapeutic bronchoscopy. The least absolute shrinkage and selection operator regression (LASSO) was applied to the model development dataset for selecting features correlated with MAO survival for inclusion in the Cox regression from which we elaborated the risk score system. A nomogram algorithm was also utilized. RESULTS: In our study, we observed a significant decline of stenosis rate after interventional bronchoscopy from 71.7%±2.1% to 36.6%±2.7% (P<0.001) and interventional bronchoscopy dilated airway effectively. Patients in our study undergoing interventional bronchoscopy had a median survival time of 614.000 days (95% CI: 269.876-958.124). Patients receiving distinct therapeutic methods of interventional bronchoscopy had different prognosis (P=0.022), and patients receiving treatment of electrocoagulation in combination with stenting and electrosurgical snare had worse survival than those receiving other options. Multivariate Cox analysis revealed that nonsmoking status, adenoid cystic carcinoma, and low preoperative stenosis length, as independent predictive factors for better overall survival (OS) of MAO patients. Then, the nomogram based on Cox regression and risk score system based on results from LASSO regression were elaborated respectively. Importantly, this risk score system was proved to have better performance than the nomogram and other single biomarkers such as traditional staging system (area under the curve 0.855 vs. 0.392-0.739). Survival curves showed that patients with the higher risk-score had poorer prognosis than those with lower risk-score (third quantile of OS: 126.000 days, 95% CI: 73.588-178.412 vs. 532.000 days, 95% CI: 0.000-1,110.372; P<0.001). CONCLUSIONS: Nonsmoking status, adenoid cystic carcinoma, and low preoperative stenosis length, were independent predictive factors for better OS of MAO patients. We proposed a nomogram and risk score system for survival prediction of MAO patients undergoing interventional bronchoscopy with good performance.

Collection on reports of molecules linked to epithelial-mesenchymal transition in the process of treating metastasizing cancer: a narrative review.

Epithelial-mesenchymal transition (EMT) is a morphological process in which epithelial cells transform into mesenchymal cells via a specific procedure. EMT plays an important role in the cancer invasion-metastasis cascade and the current treatment of metastatic cancer, influences the migration, polarity, and adhesion of tumor cells, promotes their migration, invasiveness, anti-apoptotic ability. It contributes to the changes of the tumor microenvironment and suppresses the sensitivity of tumor cells to chemotherapy, causing cancer metastasis and worse, hindering the control and therapy of it. This paper reviews the mechanisms, detection, and treatments of cancer metastasis that have been identified and applied to date, summarizes the EMT-related biological molecules, providing a reference for EMT-targeted research and therapy. As EMT is significant in the progress of tumor metastasis, it is meaningful for the therapy and control of metastatic cancer to understand the mechanism of EMT at the molecular level. We summarized the mechanisms, detection and therapeutic implications of EMT, listed the research progress of molecules like genes, miRNAs, signaling pathways in EMT. We also discussed the prospects of EMT-targeted treatment in cancer metastasis interventions and the challenges the treatment and researches are facing. The summary is conducive to the treatment and further research of EMT and metastatic cancer.

Tumor Mutation Burden and Differentially Mutated Genes Among Immune Phenotypes in Patients with Lung Adenocarcinoma.

INTRODUCTION: Nowadays, immune checkpoint blockades (ICBs) have been extensively applied in non-small cell lung cancer (NSCLC) treatment. However, the outcome of anti-program death-1/program death ligand-1 (anti-PD-1/PD-L1) therapy is not satisfying in EGFR-mutant lung adenocarcinoma (LUAD) patients and its exact mechanisms have not been fully understood. Since tumor mutation burden (TMB) and tumor immune phenotype had been thought as potential predictors for efficacy of ICBs, we further studied the TMB and immune phenotype in LUAD patients to explore potential mechanisms for poor efficacy of ICBs in EGFR positive mutated patients and to find possible factors that could impact the tumor immune phenotype which might uncover some new therapeutic strategies or combination therapies. METHODS: We enrolled 223 LUAD patients who underwent surgery in our hospital. We evaluated TMB through targeted panel sequencing. The tumor immune phenotype, which could be divided into non-inflamed, intermediate and inflamed, was determined through immunohistochemistry using formalin-fixed paraffin-embedded samples. Enumeration data were analyzed by Chi-square test or Fisher exact test and shown as number (proportion). Logistic regression model was employed for univariate and multivariate analysis of the association between TMB levels and clinical characteristics. RESULTS: The median TMB level was 4.0445 mutations/Mb. Multivariate analysis showed the TMB level was significantly associated with age (P=0.026), gender (P=0.041) and EGFR mutation status (P=0.015), and in EGFR-mutant patients we found a lower proportion of patients with mutated KRAS and BRCA2. Furthermore, we found patients with or without metastatic lesions would have different immune phenotype (P=0.007). And the mutational frequencies of ALK, CDKN2A, MAP2K1, IDH2 and PTEN were significantly different among three immune phenotypes. CONCLUSION: Low TMB level could be the reason for the poor efficacy of ICBs in patients having EGFR mutation. And mutational frequencies of KRAS and BRCA2 were lower in EGFR-mutant patients. Furthermore, ALK, CDKN2A, MAP2K1, IDH2 and PTEN might involve in the formation of immune phenotypes.

FOXP3-based immune risk model for recurrence prediction in small-cell lung cancer at stages I-III.

BACKGROUND: Immunotherapies may prolong the survival of patients with small-cell lung cancer (SCLC) to some extent. The role of forkhead box protein P3 (FOXP3) in tumor microenvironment (TME) remains controversial. We aimed to examine FOXP3-related expression characteristics and prognostic values and to develop a clinically relevant predictive system for SCLC. METHODS: We enrolled 102 patients with histologically confirmed SCLC at stages I-III. Through immunohistochemistry, we determined the expression pattern of FOXP3 and its association with other immune biomarkers. By machine learning and statistical analysis, we constructed effective immune risk score models. Furthermore, we examined FOXP3-related enrichment pathways and TME traits in distinct cohorts. RESULTS: In SCLC, FOXP3 level was significantly associated with status of programmed death-ligand 1 (PD-L1), programmed cell death protein 1 (PD-1), CD4, CD8, and CD3 (p=0.002, p=0.001, p=0.002, p=0.030, and p<0.001). High FOXP3 expression showed longer relapse-free survival (RFS) than the low-level group (41.200 months, 95% CI 26.937 to 55.463, vs 14.000 months, 95% CI 8.133 to 19.867; p=0.008). For tumor-infiltrating lymphocytes (TILs), subgroup analysis demonstrated FOXP3 and PD-1, PD-L1, lymphocyte activation gene-3, CD3, CD4, or CD8 double positive were significantly correlated with longer RFS. We further performed importance evaluation for immune biomarkers, constructed an immune risk score incorporating the top three important biomarkers, FOXP3, TIL PD-L1, and CD8, and found their independently prognostic role to predict SCLC relapse. Better predictive performance was achieved in this immune risk model compared with single-indicator-based or two-indicator-based prediction systems (area under the curve 0.715 vs 0.312-0.711). Then, relapse prediction system integrating clinical staging and immune risk score was established, which performed well in different cohorts. High FOXP3-related genes were enriched in several immune-related pathways, and the close relationships of interleukin-2, CD28, basic excision repair genes MUTYH, POLD1, POLD2, and oxidative phosphorylation related gene cytochrome c oxidase subunit 8A with FOXP3 expression were revealed. Moreover, we found low-immune risk score group had statistically higher activated CD4+ memory T cells (p=0.014) and plasma cells (p=0.049) than the high-risk group. The heterogeneity of tumor-infiltrating immune cells might represent a promising feature for risk prediction in SCLC. CONCLUSION: FOXP3 interacts closely with immune biomarkers on tumor-infiltrating cells in TME. This study highlighted the crucial prognostic value and promising clinical applications of FOXP3 in SCLC.

Research progress on the molecular mechanisms of hepatic metastasis in lung cancer: a narrative review.

The liver is one of the most common sites of metastatic spread of lung cancer, and the process of metastasis is regulated by many factors. A number of genes, including multiple tumor suppressor 1 (mts1), p120 catenin, and CT45A1, increase the possibility of hepatic metastasis in lung cancer, whereas Tip30/CC3, CUL5, and SOCS3 expression in lung tumors inhibit tumor metastasis. microRNAs (miRNAs), such as miRNA-126, miRNA-338, and miRNA-218, can affect the metastasis of lung cancer cells to the liver. The D114-Notch signaling pathway can inhibit liver metastasis in small cell lung cancer. Serum tumor markers cytokeratin 19 fragment antigen 21-1 and neuron-specific enolase (NSE) are closely related to the risk of hepatic metastasis in lung cancer. Based on previously published literature, we found that the metastasis and invasion of lung cancer to the liver are determined by molecular factors. Therefore, the selective identification and intervention of these erroneous signals can predict early lung cancer metastasis to the liver. In this review article, we describe the mechanisms and influencing factors (genes, signal pathways, chemicals, proteins, miRNAs) of hepatic metastasis in lung cancer. We hope to provide a summary of the evidence for the mechanisms by which related genes or proteins affect the malignancy of liver metastasis from lung cancer so that doctors and researchers can improve treatment options.

The landscape of immune checkpoints expression in non-small cell lung cancer: a narrative review.

With the increasing clinical potential of tumor immunotherapy, more and more clinical trials are undergoing with immune checkpoint inhibitors (ICIs). Immune checkpoints (ICs) have been identified as crucial regulators of the immune response and have improved ICIs-inhibitor therapeutic strategies. The most important ICs in lung cancer include programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), lymphocyte activation gene-3 (LAG-3), major histocompatibility complex class II (MHC II), T cell immunoglobulin and mucin-domain containing-3 (TIM-3), and Galectin-9 (GAL-9), OX-40, OX40L. However, the expression and prognostic value of these ICs are still controversial. Among them, high expression of PD-L1 on tumor cells (>50%) predicts a better therapeutic effect of anti-PD-1 monoclonal antibody compared to patients with low PD-L1 expression. However, only 20-30% of non-small cell lung cancer (NSCLC) patients seem to get benefit from immunotherapy. In order to improve the immunotherapy outcomes, more and more attention is paid to combination immunotherapy. Analyzing the co-expression of ICs can give us a more comprehensive basis for combination immunotherapy. This review article summarized our comprehensive expression of ICs based on our previous research, and analyzed their correlation with prognosis in NSCLC patients. We also provided suggestions for potentially personalized combination immunotherapy in NSCLC.

Single-Cell Sequencing, an Advanced Technology in Lung Cancer Research.

Single-cell sequencing (SCS) which has an unprecedentedly high resolution is an advanced technique for cancer research. Lung cancer still has a high mortality and morbidity. For further understanding the lung cancer, SCS is also been applied to lung cancer research to investigate its heterogeneity, metastasis, drug resistance, tumor microenvironment and many other issues. In this review, we summarized lung cancer research using SCS and their research achievements.

Aberrant methylation modifications reflect specific drug responses in small cell lung cancer.

In the study, Methylated DNA immunoprecipitation sequencing, RNA sequencing, and whole-exome sequencing were employed to clinical small cell lung cancer (SCLC) patients. Then, we verified the therapeutic predictive effects of differentially methylated genes (DMGs) in 62 SCLC cell lines. Of 4552 DMGs between chemo-sensitive and chemo-insensitive group, coding genes constituted the largest percentage (85.08%), followed by lncRNAs (10.52%) and miRNAs (3.56%). Both two groups demonstrated two methylation peaks near transcription start site and transcription end site. Two lncRNA-miRNA-mRNA networks suggested the extensive genome connection between chemotherapy efficacy-related non-coding RNAs (ncRNAs) and mRNAs. Combing miRNAs and lncRNAs could effectively predict chemotherapy response in SCLC. In addition, we also verified the predictive values of mutated genes in SCLC cell lines. This study was the first to evaluate multiple drugs efficacy-related ncRNAs and mRNAs which were modified by methylation in SCLC. DMGs identified in our research might serve as promising therapeutic targets to reverse drugs-insensitivity by complex lncRNA-miRNA-mRNA mechanisms in SCLC.

Current progress and mechanisms of bone metastasis in lung cancer: a narrative review.

Lung cancer is a kind of malignant tumor with rapid progression and poor prognosis. Distant metastasis has been the main cause of mortality among lung cancer patients. Bone is one of the most common sites. Among all lung cancer patients with bone metastasis, most of them are osteolytic metastasis. Some serious clinical consequences like bone pain, pathological fractures, spinal instability, spinal cord compression and hypercalcemia occur as well. Since the severity of bone metastasis in lung cancer, it is undoubtedly necessary to know how lung cancer spread to bone, how can we diagnose it and how can we treat it. Here, we reviewed the process, possible mechanisms, diagnosis methods and current treatment of bone metastasis in lung cancer. We divided the process of bone metastasis in lung cancer into three steps: tumor invasion, tumor cell migration and invasion in bone tissue. It may be influenced by genetic factors, microenvironment and other adhesion-related factors. Imaging examination, laboratory examination, and pathological examination are used to diagnose lung cancer metastasis to bone. Surgery, radiotherapy, targeted therapy, bisphosphonate, radiation therapy and chemotherapy are the common clinical treatment methods currently. We also found some problems remained to be solved. For example, drugs for skeletal related events mainly target on osteoclasts at present, which increase the ratio of patients in osteoporosis and fractures in the long term. In all, this review provides the direction for future research on bone metastasis in lung cancer.

Comparison between the first-line and second-line immunotherapy drugs in the progression-free survival and overall survival in advanced non-small cell lung cancer: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer but with a low early diagnosis rate. With immunotherapy becomes popular in lung cancer, single immunotherapy drug treatment as the first-line or second-line plays an important role. The meta-analysis compares different clinical effects of them by overall survival (OS) and progression-free survival (PFS) because it is important to detect the best time of immunotherapy for NSCLC patients. METHODS: Randomized controlled trials (RCTs) were selected by using the Cochrane Library, Embase, PubMed and Web of science. Pool the hazard ratio (HR) and use the PFS, OS as outcomes. RESULTS: Ten RCTs were included. The pooled results indicated that first-line and second-line single immunotherapy drug treatment seems to have a tiny difference in PFS, with HR 0.79, 95% confidence interval (CI): 0.51-1.21, I2 =89% in first-line single immunotherapy drug treatment and HR 0.74, 95% CI: 0.62-0.89, I2 =84% in second-line single immunotherapy drug treatment. When it comes to OS, first-line immunotherapy drug treatment still has better effects than the second-line. In first-line single immunotherapy drug treatment, HR 0.78, 95% CI: 0.55-1.11, I2 =83%, but in second-line, HR 0.70, 95% CI: 0.64-0.76, I2 =53%. CONCLUSIONS: First-line single drug immunotherapy had the tendency better than single immunotherapy drugs used in second-line treatment.

CD39: the potential target in small cell lung cancer.

BACKGROUND: It has been proven that the treatment window of small cell lung cancer (SCLC) is short, so it is vital to find other possible therapeutic targets. CD39 inhibits natural killer (NK) cells and promotes the occurrence and metastasis of tumors. There has been little research about the role of CD39 in SCLC, so we explored the correlation between CD39 and other surface antigens, and its association with survival in SCLC. METHODS: This study included 75 patients with SCLC from Shanghai Pulmonary Hospital. After paraffin embedding and sectioning, immunohistochemistry (IHC) was applied. Then we identify cutoff value for CD39 and other surface antigens based on the analysis of ROC curve in RFS by SPSS. All statistical analyses were based on SPSS and Graphpad Prism8. Chi-square test, Kendall's tau-b correlation analysis, Logistic regression analysis, Kaplan-Meier method, univariate and multivariate Cox regression analysis were conducted. In all analyses, P = 0.05 distinguished whether they had statistical significance. RESULTS: Of the 75 SCLC patients enrolled in this study, 61.33% positively expressed CD39. A correlation between CD39 and programmed cell death-ligand 1 (PD-L1) (P=0.007), CD3 (P<0.001), CD4 (P<0.001), CD8 (P<0.001), and forkhead box P3 (FOXP3) (P<0.001) on tumor-infiltrating lymphocytes (TILs) was identified by correlation analysis and logistic regression analysis. Based on Kaplan-Meier survival analysis, we found that CD39 affected relapse-free survival (RFS) [negative vs. positive, 95% confidence interval (CI): 0.2765-0.9862, P=0.0390]. SCLC patients with high-expressed CD39 and low-expressed PD-L1 had poor prognosis (P<0.001). Positive expression of CD39 and negative expression of CD3, CD4, CD8, and FOXP3 also indicated shorter RFS (P=0.0409). Univariate and multivariate Cox regression analysis was performed to confirm the factors that influenced RFS. CONCLUSIONS: CD39, programmed cell death-1 (PD-1), and PD-L1 expressed on TILs but not on tumor cells. CD39 has a significant association with PD-L1, CD3, CD4, CD8, and FOXP3 on TILs. The positive expression of CD39 predicts poor prognosis. SCLC patients with low expression of CD39 combined with high expression of PD-L1 or CD3, CD4, CD8, and FOXP3 have a more favorable prognosis.

Collagen Type III Alpha 1 chain regulated by GATA-Binding Protein 6 affects Type II IFN response and propanoate metabolism in the recurrence of lower grade glioma.

Some studies suggested the prognosis value of immune gene in lower grade glioma (LGG). Recurrence in LGG is a tough clinical problem for many LGG patients. Therefore, prognosis biomarker is required. Multivariate prognosis Cox model was constructed and then calculated the risk score. And differential expressed transcription factors (TFs) and differential expressed immune genes (DEIGs) were co-analysed. Besides, significant immune cells/pathways were identified by single sample gene set enrichment analysis (ssGSEA). Moreover, gene set variation analysis (GSVA) and univariate Cox regression were applied to filter prognostic signalling pathways. Additionally, significant DEIG and immune cells/pathways, and significant DEIG and pathways were co-analysed. Further, differential enriched pathways were identified by GSEA. In sum, a scientific hypothesis for recurrence LGG including TF, immune gene and immune cell/pathway was established. In our study, a total of 536 primary LGG samples, 2,498 immune genes and 318 TFs were acquired. Based on edgeR method, 2,164 DEGs, 2,498 DEIGs and 31 differentials expressed TFs were identified. A total of 106 DEIGs were integrated into multivariate prognostic model. Additionally, the AUC of the ROC curve was 0.860, and P value of Kaplan-Meier curve < 0.001. GATA6 (TF) and COL3A1 (DEIG) were selected (R = 0.900, P < 0.001, positive) as significant TF-immune gene links. Type II IFN response (P < 0.001) was the significant immune pathway. Propanoate metabolism (P < 0.001) was the significant KEGG pathway. We proposed that COL3A1 was positively regulated by GATA6, and by effecting type II IFN response and propanoate metabolism, COL3A1 involved in LGG recurrence.

Challenges and countermeasures of thoracic oncology in the epidemic of COVID-19.

Since December, 2019, a 2019 novel coronavirus disease (COVID-19) infected by the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) emerged in Wuhan, Hubei province, and the epidemic situation has continued to spread globally. The epidemic spread of COVID-19 has brought great challenges to the clinical practice of thoracic oncology. Outpatient clinics need to strengthen the differential diagnosis of initial symptoms, pulmonary ground-glass opacity (GGO), consolidation, interstitial and/or interlobular septal thickening, and crazy paving appearance. In the routine of oncology, the differential diagnosis of adverse events from COVID-19 is also significant, including radiation pneumonitis, checkpoint inhibitor pneumonitis (CIP), neutropenic fever, and so on. During the epidemic, indications of transbronchial biopsy (TBB) and CT-guided percutaneous thoracic biopsy are strictly controlled. For patients who are planning to undergo biopsy operation, screening to exclude the possibility of COVID-19 should be carried out. For confirmed or suspected patients, three-level protection should be performed during the operation. Disinfection and isolation measures should be strictly carried out during the operation. At last, more attention to the protection of cancer patients and give priority to the treatment of infected cancer patients.