Background: There was rare studies on prognosis of pulmonary venous CTC and early or advanced NSCLC patients. We want to investigate whether CTCs and the subtype of it can predict the prognosis of NSCLC patients. Patients and Methods: One hundred and fourteen patients with stage I-III NSCLC were included CanPatrol (TM) CTC analysis. PD-L1 expression level were detected in CTC of pulmonary vein. PD-L1, number of CTC in pulmonary, CTC's subtype, clinical characteristics, prognosis of patients were analyzed. Results: 110/114 (96.5%) patients could be found CTCs in pulmonary vein, 58/114 (50.9%) patients had CTC >= 15/ml in pulmonary vein, 53/110 patients (48.2%) were defined as having MCTC subtype and 56/110 patient were found have PD-L1 (+) CTC in pulmonary vein. Multivariate analyses showed that PVCTC, MCTC, and stage were independent factors of DFS (P < 0.05). No OS difference was found between number of CTC (P = 0.33) and other CTC factors (P > 0.05), only stage was independent factor of OS (P = 0.019). There were decreases of CTC number and MCTC number in EGFR mutant subgroup (P = 0.0009 and P = 0.007). There were increases of CTC (P = 0.0217), MCTC (P = 0.0041), and PD-L1 (+) CTC (P = 0.0002) number in KRAS mutant subgroup. There was increase of MCTC (P =0.0323) number in BRAF mutant. There were fewer CTCs in pulmonary vein for patients with EGFR mutant than in patients with full wild-type gene (P = 0.0346). There were more PD-L1 positive CTCs in pulmonary vein for patients with ALK rearrangement, KRAS mutant, BRAF mutant, or ROS1 mutant than in patients with full wild-type gene (P = 0.0610, P = 0.0003, P = 0.032, and P = 0.0237). There were more mesenchymal CTCs in pulmonary vein for patients with KRAS mutant and BRAF mutant than in patients with full wild-type gene (P = 0.073 and P = 0.0381). There were fewer mesenchymal CTCs in pulmonary vein for patients with EGFR mutant than in patients with full wild-type gene (P = 0.0898). Conclusions: The patients with high number of CTCs, MCTCs, or PD-L1 (+) CTCs in pulmonary vein experienced poor prognosis of DFS. There are obvious correlations between the CTC subtype of NSCLC and the gene subgroups of tumor tissue.
Study Objective: To compare the surgical and oncologic outcomes between open abdomen radical hysterectomy (ARH) and laparoscopic radical hysterectomy (LRH) for cervical cancer. Methods: Retrospective observational study with propensity score matching was used to ensure balanced groups for ARH and LRH. One-hundred-and-ninety-eight women with cervical cancer, 99 treated using ARH and 99 using LRH, between January 2012 and December 2014. Outcomes included disease-free survival (DFS), overall survival (OS), intra-operative factors, post-operator recovery, urinary retention, and adverse events. Moreover, the inverse probability of the treatment weighting (IPTW) method was also used. Main Results: Compared with ARH, LRH was associated with a lower volume of blood loss (P < 0.001) and transfusion rate (P < 0.001), with a broader resection of the parametrium (P < 0.001). Post-operatively, the time to first flatus was shorter for LRH than ARH (P < 0.001) but the rate of urinary retention was higher for LRH (22.2%) than ARH (8.1%; P = 0.009). DFS and OS were similar between groups. By IPTW, laparoscopy was also not associated with poorer survival in terms of DFS (HR 1.52, CI 0.799-2.891, P = 0.202) or OS (HR 0.942, HR 0.425-2.09, P = 0.883). Conclusion: Compared with ARH, LRH provided better intra-operative and post-operative outcomes, with no significant difference in oncologic outcomes and survival. Urinary retention remains a clinical issue to improve with LRH. The technology of LRH has been improved in China to address the inconsistent results of oncologic outcomes in previous studies. Whether these improvements could be effective needs to be investigated in the future.
Environmental exposure to certain compounds contribute to cell plasticity, tumor progression and even chemoresistance. 2,2 ',4,4 '-tetrabromo diphenyl ether (BDE-47), one of the most frequently detected polybrominated diphenyl ethers (PBDEs) in environmental and biological samples, is a known estrogen disruptor closely associated with the development of hormone-dependent cancers. However, the effect of BDE-47 on endometrial carcinoma (EC), an estrogen-dependent cancer, remains to be elucidated. Mechanisms of estrogen receptor alpha (ER alpha) and G-protein-coupled receptor-30 (GPR30) involved in BDE-47 carcinogenesis are yet to be identified. This study aims to investigate the effect of BDE-47 on the invasive phenotype of estrogen-dependent EC cells. BDE-47-treated cells, such as Ishikawa-BDE-47 and HEC-1B-BDE-47 cells, exhibited increased cell viability and enhanced metastatic ability. In vivo studies showed larger tumor volumes and more metastasis in mice injected with Ishikawa-BDE-47 cells compared with parental Ishikawa cells. MTT assay showed that BDE-47 exposure could attenuate sensitivity of EC cells to cisplatin or paclitaxel treatment in vitro. Western blotting revealed overexpression of ER alpha, GPR30, pEGFR (phosphorylated epidermal growth factor receptor), and pERK (phosphorylated extracellular-regulated protein kinase) in Ishikawa-BDE-47 and HEC-1B-BDE-47 cells. Knockdown of ER alpha or GPR30 by small interfering RNA reversed the stimulating effect of BDE-47 on cell growth, migration and invasion of EC cells. Additionally, treatment with pEGFR or pERK inhibitor impaired cell viability, migration and invasion in Ishikawa-BDE-47 and HEC-1B-BDE-47 cells. Overall, our results indicate that chronic BDE-47 exposure triggers phenotypic plasticity, promotes progression and even chemoresistance in EC cells, at least in part, via ER alpha/GPR30 and EGFR/ERK signaling pathways.
Background: Bladder urothelial cancer (BLCA) treatment using immune checkpoint inhibitors (IMCIs) can result in long-lasting clinical benefits. However, only a fraction of patients respond to such treatment. In this study, we aimed to identify the relationships between immune cell infiltration levels (ICILs) and IMCIs and identify markers for ICILs. Methods: ICILs were estimated based on single-sample gene set enrichment analysis. The response rates of different ICILs to IMCIs were calculated by combining the ICILs of molecular subtypes in BLCA with the response rates of different molecular subtypes of IMvigor 210 trials to a programmed cell death ligand-1 inhibitor. Weighted gene co-expression network analysis was used to identify modules of interest with ICILs. Functional enrichment analysis was performed to functionally annotate the modules. Screening of key genes and unsupervised clustering were used to identify candidate biomarkers. Tumor IMmune Estimation Resource was used to validate the relationships between the biomarkers and ICILs. Finally, we verified the expression of key genes in molecular subtypes of different response rates for IMCIs. Findings: The basal squamous subtype and luminal infiltrated subtype, which showed low response rates for IMCIs, had the highest levels of immune infiltration. The neuronal subtypes, which showed the highest response rates to IMCIs, had low ICILs. The modules of interest and key genes were determined based on topological overlap measurement, clustering results, and inclusion criteria. Modules highly correlated with ICILs were mainly enriched in immune responses and epithelial-mesenchymal transition. After screening the key genes in the modules, five candidate biomarkers (CD48, SEPT1, ACAP1, PPP1R16B, and IL16) were selected by unsupervised clustering. The key genes were inversely associated with tumor purity and were mostly expressed in the basal squamous subtype and luminal infiltrated subtypes. Interpretation: Patients with high ICILs may benefit the least from treatment with IMCIs. Five key genes could predict ICILs in BLCA, and their high expression suggested that the response rate to IMCIs may decrease.
Background: Von Hippel-Lindau (VHL) disease is an autosomal-dominant hereditary cancer syndrome. Currently, studies on tyrosine kinase inhibitor (TKI) therapy for VHL disease are scarce. In this study, we retrospectively evaluated the efficacy and safety of four TKIs in patients with VHL disease. Methods: Patients diagnosed with VHL disease who were receiving TKIs were recruited. Patients were treated with sunitinib (n = 12), sorafenib (n = 11), axitinib (n = 6), or pazopanib (n = 3). The therapeutic response was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Results: From July 2009 to September 2018, 32 patients with VHL disease were eligible and included in this study. The median duration of TKI therapy was 22 months (IQR 8.5-44.75), and the median follow-up period was 31.5 months (IQR 13.5-63.5). According to the RECIST, 9 (28%) of 32 patients showed a partial response, 15 (47%) achieved stable disease, and eight exhibited continued disease progression. A partial response was observed in 11 (31%) of 36 renal cell carcinomas, 4 (27%) of 15 pancreatic lesions, and 1 (20%) of five central nervous system (CNS) hemangioblastomas. The average tumor size decreased significantly for renal cell carcinomas (P = 0.0001), renal cysts (P = 0.027), and pancreatic lesions (P = 0.003) after TKI therapy. Common side effects included hand-foot skin reactions, diarrhea, alopecia, thrombocytopenia, and fatigue. Conclusions: Partial alleviation of VHL disease-related tumors can be achieved by TKI therapies in some patients, providing an alternative treatment strategy, and the side effects of TKIs are acceptable. Larger prospective studies are warranted to further evaluate the efficacy and safety of TKIs in patients with VHL disease.
Introduction: People with metastatic gastric cancer (GC) have a poor prognosis. The study aims to investigate the efficacy of multi-modality treatment for patients with metastatic GC. Methods: We retrospectively identified 267 patients with stage IV gastric cancer who were treated with systemic chemotherapy: 114 received multi-modality treatments, 153 received systematic chemotherapy alone. The survival of these two groups was compared by log rank test, the independent prognostic factors were investigated using univariate and multivariate analyses. Results: The median survival of metastatic GC patients who received multi-modality treatment was significantly longer than those who received systematic chemotherapy alone (18.4 vs. 11.4 months, P < 0.001). Multivariate analysis identified tumor histologic differentiation, CA19-9 level, previous curative resection, palliative gastrectomy, and metastasectomy as independent prognostic factors for overall survival. In the multimodality treatment group, patients who received palliative gastrectomy or metastasectomy had a longer survival than those who only received intraperitoneal chemotherapy or radiotherapy (21.6 vs. 15.2 months, P = 0.014). Conclusion: Multi-modality treatments offer a survival benefit for patients with metastatic GC. Future prospective studies are needed to confirm the result.
Background: Metastatic cervical cancer (mCEC) is the end stage of cervical cancer. This study aimed to establish and validate a nomogram to predict the overall survival (OS) of mCEC patients. Methods: We investigated the Surveillance, Epidemiology, and End Results (SEER) database for mCEC patients diagnosed between 2010 and 2014. Univariate and multivariable Cox analyses was performed to select the clinically important predictors of OS when developing the nomogram. The performance of nomogram was validated with Harrell's concordance index (C-index), calibration curves, receiver operating characteristic curve (ROC), and decision curve analysis (DCA). Results: One thousand two hundred and fifty-two mCEC patients were included and were divided into training (n = 880) and independent validation (n = 372) cohorts. Age, race, pathological type, histology grade, radiotherapy, and chemotherapy were independent predictors of OS and used to develop the nomogram for predicting 1- and 3-year OS. This nomogram had a C-index of 0.753 (95% confidence interval [CI]: 0.780-0.726) and 0.751 (95% CI: 0.794-0.708) in the training and the validation cohorts, respectively. Internal and external calibration curves indicated satisfactory agreement between nomogram prediction and actual survival, and DCA indicated its clinical usefulness. Furthermore, a risk stratification system was established that was able to accurately stratify mCEC patients into three risk subgroups with significantly different prognosis. Conclusions: We constructed the first nomogram and corresponding risk classification system to predict the OS of mCEC patients. These tools showed satisfactory accuracy, and clinical utility, and could aid in patient counseling and individualized clinical decision-making.
Background: The efficacy of an EGFR-targeted treatment strategy for non-small cell lung cancer (NSCLC) is reduced by drug resistance. IL-22 enhances tumor growth and induces chemotherapy resistance in human lung cancer cells. The present study elucidated the IL-22-induced mechanism underlying EGFR-tyrosine kinase inhibitor (TKI) resistance in NSCLC. Methods: The plasma and tissues of patients who received EGFR-TKIs were utilized to determine the association between IL-22 expression and gefitinib efficacy. The IL-22 effect on the EGFR/ERK/AKT pathways in NSCLC HCC827 and PC-9 cells was determined using the CCK-8 assay, western blot, and flow cytometric analysis. A PC-9 xenograft model of IL-22 exposure was established. Gefitinib was administered to mice in combination with IL-22 or vehicle. Results: We showed that IL-22 expression was higher in the EGFR-TKI-resistant group compared to EGFR-TKI-sensitive group. IL-22 expression was associated with EGFR-TKI efficacy in plasma. Additional treatment of IL-22 induced gefitinib resistance and reduced apoptosis in PC-9 and HCC827 cell lines. Furthermore, we showed that the effects of IL-22 attributed to p-ERK, p-EGFR, and p-AKT up-regulation. IL-22 neutralizing antibody completely abrogated the effects of IL-22 on apoptosis and AKT/EGFR/ERK signaling. Finally, we showed that IL-22 enhanced tumor growth and induced gefitinib resistance in the PC-9 xenograft model. Moreover, compared with gefitinib alone, the combination of IL-22 and gefitinib led to an increase in Ki67-positive staining and a reduction in TUNEL staining. Conclusions: Our findings indicate that IL-22 plays a role in tumor progression and EGFR-TKI resistance in NSCLC. Thus, IL-22 might serve as a novel biomarker to overcome resistance of EGFR-TKI.
Breast cancer is still the most common and leading cause of cancer-related deaths in women worldwide. Long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) have shown key regulator roles in various cancers. Previous reports have identified miR-125b as a critical tumor suppressor in breast cancer. However, the role of lncRNAs in breast cancer is far from well-characterized. In this study, we identified a novel lncRNA LINC01787, which specifically binds pre-miR-125b, inhibits the binding between DICER and pre-miR-125b, represses the processing of pre-miR-125b by DICER, and therefore induces pre-miR-125b accumulation and represses mature miR-125b generation. Functional assays showed that LINC01787 promotes breast cancer cell proliferation and migration and breast cancer xenograft growth in vivo, which is abolished by the mutation of pre-miR-125b binding sites on LINC01787 or overexpression of miR-125b. Furthermore, LINC01787 is up-regulated in breast cancer tissues and is associated with advanced stages and poor survival. The expression of LINC01787 is inversely associated with that of miR-125b in breast cancer tissues. In conclusion, our findings identified a novel up-regulated and oncogenic lncRNA LINC01787 in breast cancer, which binds pre-miR-125b and represses mature miR-125b generation. Our data suggests LINC01787 as a potential prognostic biomarker and therapeutic target for breast cancer.
Signal transducer and activator of transcription 3 (STAT3), a previously accepted tumor-promoting protein in various malignancies, plays a key role in the process of cancer glycolysis. However, the role and potential mechanism of STAT3 in aerobic glycolysis and progression of oral squamous cell carcinoma (OSCC) has not been explored. In the present study, we demonstrated that STAT3 knockdown remarkably inhibited migration, invasion, expressions of epithelial-mesenchymal transition (EMT) markers, and aerobic glycolysis of OSCC cells by up-regulation of FoxO1. Consistently, the expression of nuclear Tyr705-phosphorylated STAT3, an active form of STAT3, was significantly elevated in OSCC tissues compared with adjacent normal tissues, and increased nuclear staining of Tyr705-phosphorylated STAT3 was associated with metastasis and shorter overall survival. Moreover, FoxO1, which was also mainly expressed in OSCC specimens, decreased in poorly-differentiated tissues compared with the relatively well-differentiated ones, and inversely correlated with the expression of nuclear Tyr705-phosphorylated STAT3 from patients with OSCC. Hence, our findings collectively characterized the contributing role of STAT3/FoxO1 in invasion and aerobic glycolysis of OSCC cells, which may lead to the worse clinical outcome.
Background: The identification of prognostic markers for non-small-cell lung carcinoma (NSCLC) is needed for clinical practice. The metabolism-reprogramming marker ketohexokinase (KHK)-A and acetyl-CoA synthetase 2 (ACSS2) phosphorylation at S659 (ACSS2 pS659) play important roles in tumorigenesis and tumor development. However, the clinical significance of KHK-A and ACSS2 pS659 in NSCLC is largely unknown. Methods: The expression levels of KHK-A and ACSS2 pS659 were assessed by immunohistochemistry analyses of surgical specimens from 303 NSCLC patients. The prognostic values of KHK-A and ACSS2 pS659 were evaluated by Kaplan-Meier methods and Cox regression models. Results: The expression levels of KHK-A and ACSS2 pS659 were significantly higher in NSCLC tissues than those in adjacent non-tumor tissues (P < 0.0001). KHK-A or ACSS2 pS659 alone and the combination of KHK-A and ACSS2 pS659 were inversely correlated with overall survival in NSCLC patients (P < 0.001). The multivariate analysis indicated that KHK-A or ACSS2 pS659 and KHK-A/ACSS2 pS659 were independent prognostic biomarkers for NSCLC (P = 0.008 for KHK-A, P < 0.001 for ACSS2 pS659, and P < 0.001 for KHK-A/ACSS2 pS659). Furthermore, the combination of KHK-A and ACSS2 pS659 can be used as a prognostic indicator for all stages of NSCLC. Conclusions: KHK-A or ACSS2 pS659 alone and the combination of KHK-A and ACSS2 pS659 can be used as prognostic markers for NSCLC. Our findings highlight the important role of metabolic reprogramming in NSCLC progression.
As the first oral multi-target anti-tumor drug proved for the treatment of patients with advanced liver cancer in 2007, sorafenib has changed the landscape of advanced hepatocellular carcinoma (HCC) treatment. However, drug resistance largely hinders its clinical application. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), and long non-coding (lncRNAs), have recently been demonstrated playing critical roles in a variety of cancers including HCC, while the mechanisms of ncRNAs in HCC sorafenib resistance have not been extensively characterized yet. Herein, we summarize the mechanisms of recently reported ncRNAs involved in sorafenib resistance and discuss the potential strategies for their application in the battle against HCC.
Background: Relevant serum tumor markers have been indicated to be associated with peritoneal dissemination (PD) of gastric cancer (GC). Fibrinogen has been shown to play an important role in the systemic inflammatory response (SIR) and in tumor progression. However, the clinical significance of the fibrinogen-to-lymphocyte ratio (FLR) in GC with PD has not been studied. Methods: The clinical data of 391 patients with GC were collected, including 86 cases of PD. Then, 1:3 matching was performed by propensity score matching (PSM), and the clinical data of the matched 344 patients were analyzed by univariate and multivariate conditional logistic regression. Classification tree analysis was used to obtain the decision rules and a random forest algorithm to extract the important risk factors of PD in GC. A nomogram model for risk assessment of PD in GC was established by using the rms package of R software. Results: Univariate analysis showed that the factors related to PD in GC were: carbohydrate antigen (CA) 125 (P < 0.0001), CA19-9 (P < 0.0001), CA72-4 (P < 0.0001), FLR (P < 0.0001), neutrophil-to-lymphocyte ratio (NLR) (P < 0.0001), albumin-to- lymphocyte ratio (ALR) (P < 0.0001), platelet-to-lymphocyte ratio (PLR) (P = 0.013), and carcinoembryonic antigen (CEA) (P = 0.031). Conditional logistic regression found that CA125 (OR: 1.046; P < 0.0001), CA19-9 (OR: 1.002; P < 0.0001), and FLR (OR: 1.266; P = 0.024) were independent risk factors for GC with PD. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the decision rules for detecting PD of GC were 89.5, 77.4, 94.0, 82.8, and 91.8%, respectively. According to the important variables identified by the classification tree and random forest algorithm, the risk assessment model of PD in GC was established. The accuracy, sensitivity, and specificity of the model were 91, 89.5, and 79.5%, respectively. Conclusion: CA125 > 17.3 U/ml, CA19-9 > 27.315 U/ml, and FLR > 2.555 were the risk factors for GC with PD. The decision rules and nomogram model constructed by CA125, CA19-9, CA72-4, and FLR can correctly predict the risk of PD in GC.
Background: Despite an increasing understanding about tumor mutation burden (TMB) in cancer immunity and cancer immunotherapy, the comprehensive cognition between TMB and efficiency of immune checkpoint inhibitors (ICIs) is still lacking. A systematic review and meta-analysis was conducted to evaluate the predictive value of TMB on efficacy of ICIs. Methods: Systematic literature search was conducted on PubMed, EMBASE, Web of Science and Cochrane Library up to June 16, 2019. Pooled odds ratio (OR) of objective response rate (ORR), hazard ratio (HR) of progression-free survival (PFS) and overall survival (OS) were estimated by inverse variance weighted fixed-effects model (I-2 <= 50%) or DerSimonian-Laird random-effects model (I-2 > 50%). In addition, heterogeneity analysis, sensitivity analysis, publication bias and subgroup analysis were conducted. Moreover, fractional polynomial regression was conducted to investigate the dose-response relationship between TMB cutoffs and efficacy of ICIs. Furthermore, we assessed ORR by TMB and programmed cell death ligand 1 (PD-L1) expression after layering each other in studies which the two could be both acquired. Results: Three thousand six hundred fifty-seven records were retrieved through database searching, and 29 studies with 4,431 patients were finally included in the meta-analysis. TMB high group had significantly improved ORR (pooled OR 3.31, 95% CI 2.61, 4.19, P < 0.001), PFS (pooled HR 0.59, 95% CI 0.49, 0.71, P < 0.001) and OS (pooled HR 0.68, 95% CI 0.53, 0.89, P = 0.004). Sensitivity analyses illustrated the results were stable, and publication bias was identified in ORR. Subgroup analyses showed the predictive value of TMB was significant in non-small-cell lung cancer (except for the OS) and melanoma. In addition, heterogeneity was substantial in targeted next generation sequencing group but tiny in whole exome sequencing group. Furthermore, TMB and PD-L1 expression were capable to predict improved ORR of ICIs after stratification of each other, with tiny heterogeneity. Conclusions: High tumor mutation burden predicted improved efficacy of immune checkpoint inhibitors in cancers, and targeted next generation sequencing for estimating tumor mutation burden in clinic should be standardized to eliminate heterogeneity in the future. Moreover, tumor mutation burden and programmed cell death ligand 1 expression were independent factors on predicting efficacy of immune checkpoint inhibitors.
Purpose: The aim of this study was to test whether radiomics-based machine learning can enable the better differentiation between glioblastoma (GBM) and anaplastic oligodendroglioma (AO). Methods: This retrospective study involved 126 patients histologically diagnosed as GBM (n = 76) or AO (n = 50) in our institution from January 2015 to December 2018. A total number of 40 three-dimensional texture features were extracted from contrast-enhanced T1-weighted images using LIFEx package. Six diagnostic models were established with selection methods and classifiers. The optimal radiomics features were separately selected into three datasets with three feature selection methods [distance correlation, least absolute shrinkage and selection operator (LASSO), and gradient boosting decision tree (GBDT)]. Then datasets were separately adopted into linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Specificity, sensitivity, accuracy, and area under curve (AUC) of each model were calculated to evaluate their diagnostic performances. Results: The diagnostic performance of machine learning models was superior to human readers. Both classifiers showed promising ability in discrimination with AUC more than 0.900 when combined with suitable feature selection method. For LDA-based models, the AUC of models were 0.986, 0.994, and 0.970 in the testing group, respectively. For the SVM-based models, the AUC of models were 0.923, 0.817, and 0.500 in the testing group, respectively. The over-fitting model was GBDT + SVM, suggesting that this model was too volatile that unsuitable for classification. Conclusion: This study indicates radiomics-based machine learning has the potential to be utilized in clinically discriminating GBM from AO.