Roles and inhibitors of FAK in cancer: current advances and future directions.

Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase that exhibits high expression in various tumors and is associated with a poor prognosis. FAK activation promotes tumor growth, invasion, metastasis, and angiogenesis via both kinase-dependent and kinase-independent pathways. Moreover, FAK is crucial for sustaining the tumor microenvironment. The inhibition of FAK impedes tumorigenesis, metastasis, and drug resistance in cancer. Therefore, developing targeted inhibitors against FAK presents a promising therapeutic strategy. To date, numerous FAK inhibitors, including IN10018, defactinib, GSK2256098, conteltinib, and APG-2449, have been developed, which have demonstrated positive anti-tumor effects in preclinical studies and are undergoing clinical trials for several types of tumors. Moreover, many novel FAK inhibitors are currently in preclinical studies to advance targeted therapy for tumors with aberrantly activated FAK. The benefits of FAK degraders, especially in terms of their scaffold function, are increasingly evident, holding promising potential for future clinical exploration and breakthroughs. This review aims to clarify FAK's role in cancer, offering a comprehensive overview of the current status and future prospects of FAK-targeted therapy and combination approaches. The goal is to provide valuable insights for advancing anti-cancer treatment strategies.

A new prognostic model of esophageal squamous cell carcinoma based on Cloud-least squares support vector machine.

Background: In view of the low accuracy of the prognosis model of esophageal squamous cell carcinoma (ESCC), this study aimed to optimize the least squares support vector machine (LSSVM) algorithm to determine the uncertain prognostic factors using a Cloud model, and consequently, to establish a new high-precision prognosis model of ESCC. Methods: We studied 4,771 ESCC patients(training samples) from the Surveillance, Epidemiology, and End Results (SEER) database and 635 ESCC patients(validation samples) from the Henan Provincial Center for Disease Control and Prevention (HCDC) database, with the same exclusion criteria and inclusion criteria for both databases, and obtained permission to obtain a research data file in the SEER database from the National Cancer Institute. The independent risk factors were analyzed using the log-rank method, survival curves, univariate and multivariate Cox analysis. Finally, the independent prognostic factors were used to construct the nomogram, random forest and Cloud-LSSVM prognostic models were utilized for validation. Results: The overall median survival time of the SEER database was 14 months (HCDC samples was 46 months), the mean survival time was 26.5 months (HCDC samples was 36.8 months), and the 3-year survival rate was 65.8%. This is because most of the patients with Henan samples are early ESCC, and most of the Seer patients are T3 and T4 people. The multivariate Cox analysis showed that age at diagnosis (P<0.001), sex (P=0.001), race (P=0.002), differentiation grade (P<0.001), pathologic T category (P<0.001), and pathologic M category (P<0.001) were the factors affecting the prognosis of ESCC patients. The SEER data and HCDC database results showed that the accuracy of the Cloud-LSSVM (C-index =0.71, 0.689) model is higher than the differentiation grade (C-index =0.548, 0.506), random forest (C-index =0.649, 0.498), and nomogram (C-index =0.659, 0.563). This new model can realize the unity of the randomness and fuzziness of the Cloud model and utilize the powerful learning and non-linear mapping abilities of LSSVM. Conclusions: Due to the difference of clans between training samples and test samples, the accuracy of prediction is generally not high, but the accuracy of Cloud-LSSVM model is much higher than other models. The new model provides a clear prognostic superiority over the random forest, nomogram, and other models.

High glucose-increased miR-200c contributes to cellular senescence and DNA damage in neural stem cells.

BACKGROUND: Maternal diabetes increases the risk for neural tube defects (NTDs). It is unclear if miRNAs, senescence, and DNA damage are involved in this process. In this study, we used neural stem cells as an in vitro proxy of embryonic neuroepithelium to investigate whether high glucose triggers neural stem cell senescence and DNA damage by upregulating miR-200c, which may be responsible for NTDs. METHODS: C17.2 neural stem cells were cultured with normal glucose (5 mM) or high glucose (≥16.7 mM) at different doses and time points for detecting miR-200c levels, markers of senescence and DNA damage. Neural stem cells were exposed to antioxidant SOD1 mimetic Tempol and high glucose for 48 h to test roles of oxidative stress on the miR-200c, senescence, and DNA damage levels. An miR-200c mimic and an inhibitor were transfected into neural stem cells to increase or decrease miR-200c activities. RESULTS: High glucose upregulated miR-200c in neural stem cells. A time course study of the effect of high glucose revealed that miR-200c initially increased at 12 h and reached its zenith at 18 h. Tempol reduced miR-200c levels caused by high glucose. High glucose induced markers of senescence and DNA damage in neural stem cells. Tempol abolished high glucose-induced markers of senescence and DNA damage. The miR-200c inhibitor suppressed high glucose-induced markers of senescence and DNA damage. Treatment with miR-200c mimic imitates high glucose-induced markers of senescence and DNA damage. CONCLUSIONS: We show that high glucose increases miR-200c, which contributes to cellular senescence and DNA damage in neural stem cells and provides a potential pathway for maternal diabetes-induced neural tube defects.

Clinicopathological characteristics and postoperative prognosis of patients with nuclear pedigree of esophageal squamous cell carcinoma.

The aim of this work is to analyze the clinicopathological characteristics and prognostic factors of patients with nuclear pedigree of esophageal cancer. The clinicopathological data and follow-up information of 3,260 patients from different nuclear pedigree of esophageal cancer who underwent radical resection of esophageal cancer were collected, and the clinicopathological characteristics and prognostic factors of the patients were analyzed. The male to female ratio of 3,260 patients with esophageal cancer was 1.7:1. The diagnosis age was ranged from 32 to 85 (60.2 ± 8.1) years old. About 53.8% of the patients were ≥ 60 years old; About 88.8% of the patients came from the high incidence area of esophageal cancer; About 82.5% of the tumors were located in the middle and lower segments of esophagus; Poor, moderate and well differentiation accounted for 26.6%, 61.9% and 11.5% respectively; The surgical margin accounted for 94.3%; 47.6% of the tumors were shorter than 4 cm in length; Clinicopathological TNM stage (0+I) accounted for 15.2%, and stage II, III and IV accounted for 54.5%, 29.9% and 0.4%, respectively. Cox analysis showed that male, diagnosed age ≥ 60 years, tumor located in neck and upper esophageal segments, poor differentiation, tumor length ≥ 4 cm, and advanced TNM were independent risk factors for the prognosis of patients in nuclear pedigree with esophageal cancer. Gender, diagnosis age, tumor location, degree of differentiation, tumor length and TNM stage are the influencing factors for the prognosis of patients with nuclear pedigree of esophageal cancer, which will provide important data for the future study of esophageal cancer family aggregation.

Porphyromonas gingivalis predicts local recurrence after endoscopic submucosal dissection of early esophageal squamous cell carcinoma or precancerous lesion.

BACKGROUND: Porphyromonas gingivalis plays an oncogenic role in development and progression of esophageal squamous cell carcinoma (ESCC). However, the impact of P. gingivalis on local recurrence of early ESCC or precancerous lesion after ESD treatment remains unknown. The present study aimed to evaluate the impact of P. gingivalis on local recurrence after ESD treatment of early ESCC or high-grade dysplasia (HGD). METHODS: The amount of P. gingivalis was assessed by immunohistochemistry in 205 patients with early ESCC or HGD. Univariate and multivariate Cox regression analyses were performed to determine the effect of P. gingivalis on local recurrence. Propensity score matching analysis was performed to reduce the imbalance of baseline characteristics. A nomogram integrating significant prognostic factors was built for local recurrence prediction. RESULTS: The amount of P. gingivalis increased significantly in neoplasms that invaded up to muscularis mucosa and submucosa compared with lesions confined to epithelium or lamina propria. Overabundance of P. gingivalis was positively associated with invasion depth, post-ESD stricture and local recurrence. Univariate and multivariate Cox regression analyses revealed that P. gingivalis, longitudinal length of lesion and lymphovascular invasion were independent predictors for post-ESD recurrence. A nomogram comprising P. gingivalis, lymphovascular involvement, and lesion length performed well for prediction of post-ESD local recurrence with the concordance indices of 0.72 (95%CI, 0.62 to 0.80), 0.72 (95%CI, 0.63 to 0.80), and 0.74 (95%CI, 0.65 to 0.83) in the validation cohort, the entire cohort, and the subcohort after PSM, respectively. CONCLUSION: P. gingivalis overabundance is a risk factor and a potential predictor for local recurrence of early ESCC or HGD after ESD treatment. Thus, clearance of P. gingivalis represents an attractive strategy for prognosis improvement and for prevention of ESCC.

N-linked glycoproteomic profiling in esophageal squamous cell carcinoma.

BACKGROUND: Mass spectrometry-based proteomics and glycomics reveal post-translational modifications providing significant biological insights beyond the scope of genomic sequencing. AIM: To characterize the N-linked glycoproteomic profile in esophageal squamous cell carcinoma (ESCC) via two complementary approaches. METHODS: Using tandem multilectin affinity chromatography for enrichment of N-linked glycoproteins, we performed N-linked glycoproteomic profiling in ESCC tissues by two-dimensional gel electrophoresis (2-DE)-based and isobaric tags for relative and absolute quantification (iTRAQ) labeling-based mass spectrometry quantitation in parallel, followed by validation of candidate glycoprotein biomarkers by Western blot. RESULTS: 2-DE-based and iTRAQ labeling-based quantitation identified 24 and 402 differentially expressed N-linked glycoproteins, respectively, with 15 in common, demonstrating the outperformance of iTRAQ labeling-based quantitation over 2-DE and complementarity of these two approaches. Proteomaps showed the distinct compositions of functional categories between proteins and glycoproteins with differential expression associated with ESCC. Western blot analysis validated the up-regulation of total procathepsin D and high-mannose procathepsin D, and the down-regulation of total haptoglobin, high-mannose clusterin, and GlcNAc/sialic acid-containing fraction of 14-3-3ζ in ESCC tissues. The serum levels of glycosylated fractions of clusterin, proline-arginine-rich end leucine-rich repeat protein, and haptoglobin in patients with ESCC were remarkably higher than those in healthy controls. CONCLUSION: Our study provides insights into the aberrant N-linked glycoproteome associated with ESCC, which will be a valuable resource for future investigations.

Transthoracic, thoracoabdominal, and transabdominal surgical approaches for gastric cardia adenocarcinomas: a survival evaluation based on a cohort of 7103 patients.

BACKGROUND: This study compared the survival outcomes of different surgical approaches to determine the optimal approach for gastric cardia adenocarcinoma (GCA) and aimed to standardize the surgical treatment guidelines for GCA. METHODS: A total of 7103 patients with GCA were enrolled from our previously established gastric cardia and esophageal carcinoma databases. In our database, when the epicenter of the tumor was at or within 2 cm distally from the esophagogastric junction, the adenocarcinoma was considered to originate from the cardia and was considered a Siewert type 2 cancer. The main criteria for the enrolled patients included treatment with radical surgery, no radio- or chemotherapy before the operation, and detailed clinicopathological information. Follow-up was mainly performed by telephone or through home interviews. According to the medical records, the surgical approaches included transthoracic, thoracoabdominal, and transabdominal approaches. Kaplan-Meier and Cox proportional hazards regression models were applied to correlate the surgical approach with survival in patients with GCA. RESULTS: There were marked differences in age and tumor stage among the patients who underwent the three surgical approaches (P < 0.001). Univariate analysis showed that survival was related to sex, age, tumor stage, and N stage (P < 0.001 for all). Cox regression model analysis revealed that thoracoabdominal approach (P < 0.001) and transabdominal approach (P < 0.001) were significant risk factors for poor survival. GCA patients treated with the transthoracic approach had the best survival (5-year survival rate of 53.7%), and survival varied among the different surgical approaches for different tumor stages. CONCLUSION: Thoracoabdominal approach and transabdominal approach were shown to be poor prognostic factors. Patients with (locally advanced) GCA may benefit from the transthoracic approach. Further prospective randomized clinical trials are necessary.

A Prognostic Model Based on mRNA Expression Analysis of Esophageal Squamous Cell Carcinoma.

Background: The aim of this study was to identify prognostic markers for esophageal squamous cell carcinoma (ESCC) and build an effective prognostic nomogram for ESCC. Methods: A total of 365 patients with ESCC from three medical centers were divided into four cohorts. In the discovery phase of the study, we analyzed transcriptional data from 179 cancer tissue samples and identified nine marker genes using edgeR and rbsurv packages. In the training phase, penalized Cox regression was used to select the best marker genes and clinical characteristics in the 179 samples. In the verification phase, these marker genes and clinical characteristics were verified by internal validation cohort (n = 58) and two external cohorts (n = 81, n = 105). Results: We constructed and verified a nomogram model based on multiple clinicopathologic characteristics and gene expression of a patient cohort undergoing esophagectomy and adjuvant radiochemotherapy. The predictive accuracy for 4-year overall survival (OS) indicated by the C-index was 0.75 (95% CI, 0.72-0.78), which was statistically significantly higher than that of the American Joint Committee on Cancer (AJCC) seventh edition (0.65). Furthermore, we found two marker genes (TM9SF1, PDZK1IP) directly related to the OS of esophageal cancer. Conclusion: The nomogram presented in this study can accurately and impersonally predict the prognosis of ESCC patients after partial resection of the esophagus. More research is required to determine whether it can be applied to other patient populations. Moreover, we found two marker genes directly related to the prognosis of ESCC, which will provide a basis for future research.

Serum Metabolomic Profiling Reveals Biomarkers for Early Detection and Prognosis of Esophageal Squamous Cell Carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most common aggressive malignancies worldwide, particularly in northern China. The absence of specific early symptoms and biomarkers leads to late-stage diagnosis, while early diagnosis and risk stratification are crucial for improving overall prognosis. We performed UPLC-MS/MS on 450 ESCC patients and 588 controls consisting of a discovery group and two validation groups to identify biomarkers for early detection and prognosis. Bioinformatics and clinical statistical methods were used for profiling metabolites and evaluating potential biomarkers. A total of 105 differential metabolites were identified as reliable biomarker candidates for ESCC with the same tendency in three cohorts, mainly including amino acids and fatty acyls. A predictive model of 15 metabolites [all-trans-13,14-dihydroretinol, (±)-myristylcarnitine, (2S,3S)-3-methylphenylalanine, 3-(pyrazol-1-yl)-L-alanine, carnitine C10:1, carnitine C10:1 isomer1, carnitine C14-OH, carnitine C16:2-OH, carnitine C9:1, formononetin, hyodeoxycholic acid, indole-3-carboxylic acid, PysoPE 20:3, PysoPE 20:3(2n isomer1), and resolvin E1] was developed by logistic regression after LASSO and random forest analysis. This model held high predictive accuracies on distinguishing ESCC from controls in the discovery and validation groups (accuracies > 89%). In addition, the levels of four downregulated metabolites [hyodeoxycholic acid, (2S,3S)-3-methylphenylalanine, carnitine C9:1, and indole-3-carboxylic acid] were significantly higher in early cancer than advanced cancer. Furthermore, three independent prognostic markers were identified by multivariate Cox regression analyses with and without clinical indicators: a high level of MG(20:4)isomer and low levels of 9,12-octadecadienoic acid and L-isoleucine correlated with an unfavorable prognosis; the risk score based on these three metabolites was able to stratify patients into low or high risk. Moreover, pathway analysis indicated that retinol metabolism and linoleic acid metabolism were prominent perturbed pathways in ESCC. In conclusion, metabolic profiling revealed that perturbed amino acids and lipid metabolism were crucial metabolic signatures of ESCC. Both panels of diagnostic and prognostic markers showed excellent predictive performances. Targeting retinol and linoleic acid metabolism pathways may be new promising mechanism-based therapeutic approaches. Thus, this study would provide novel insights for the early detection and risk stratification for the clinical management of ESCC and potentially improve the outcomes of ESCC.

A one-step platform for screening high-efficient and minimal off-target CRISPR/Cas13 crRNAs to eradicate SARS-CoV-2 virus for treatment of COVID-19 patients.

Coronavirus disease 2019 (COVID-19) is a new respiratory illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and now spreads globally. Currently, therapeutics and effective treatment options remain scarce and there is no proven drug to treat COVID-19. Targeting the positive-sense RNA genome and viral mRNAs of SARS-CoV-2 to simultaneously degrade viral genome templates for replication and viral mRNAs for essential gene expression would be a strategy to completely realize virus elimination. Type VI CRISPR enzymes Cas13 have recently been identified as programmable RNA-guided, RNA-targeting Cas proteins with nuclease activity that allows for RNA cleavage and degradation. The precise viral RNA detection and antiviral application of the CRISPR/Cas13 system depend on high-efficient and minimal off-target crRNAs. Although a computer-based algorithm has been applied for the design of crRNAs targeting SRAS-CoV-2, the experimental screening system to identify optimal crRNA is not available. We develop a one-step experimental screening system to identify high-efficient crRNAs with minimal off-target effects for CRISPR/Cas13-based SARS-CoV-2 elimination. This platform provides the foundation for CRISPR/Cas13-based diagnostics and therapeutics for COVID-19. This platform is versatile and could also be applied for crRNAs screening for other RNA viruses.

Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.

BACKGROUND: A plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that have hitherto been reported are challenged with low reproducibility due to high molecular heterogeneity of ESCC. The purpose of this study was to identify the optimal biomarkers for ESCC using machine learning algorithms. METHODS: Biomarkers related to clinical survival, recurrence or therapeutic response of patients with ESCC were determined through literature database searching. Forty-eight biomarkers linked to recurrence or prognosis of ESCC were used to construct a molecular interaction network based on NetBox and then to identify the functional modules. Publicably available mRNA transcriptome data of ESCC downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets included GSE53625 and TCGA-ESCC. Five machine learning algorithms, including logical regression (LR), support vector machine (SVM), artificial neural network (ANN), random forest (RF) and XGBoost, were used to develop classifiers for prognostic classification for feature selection. The area under ROC curve (AUC) was used to evaluate the performance of the prognostic classifiers. The importances of identified molecules were ranked by their occurrence frequencies in the prognostic classifiers. Kaplan-Meier survival analysis and log-rank test were performed to determine the statistical significance of overall survival. RESULTS: A total of 48 clinically proven molecules associated with ESCC progression were used to construct a molecular interaction network with 3 functional modules comprising 17 component molecules. The 131,071 prognostic classifiers using these 17 molecules were built for each machine learning algorithm. Using the occurrence frequencies in the prognostic classifiers with AUCs greater than the mean value of all 131,071 AUCs to rank importances of these 17 molecules, stratifin encoded by SFN was identified as the optimal prognostic biomarker for ESCC, whose performance was further validated in another 2 independent cohorts. CONCLUSION: The occurrence frequencies across various feature selection approaches reflect the degree of clinical importance and stratifin is an optimal prognostic biomarker for ESCC.

CRISPR/Cas9-mediated gene editing on Sox2ot promoter leads to its truncated expression and does not influence neural tube closure and embryonic development in mice.

Sox2 overlapping transcript (Sox2ot) is a long non-coding RNA (lncRNA), which harbors one of the major regulators of pluripotency, the Sox2 gene, in its intronic region. Sox2ot is primarily expressed in the developing neuroepithelium. However, its role in neural tube closure and embryonic development remains unclear. To investigate if Sox2ot is required for neural tube closure and embryonic development, Sox2ot promoter was deleted by CRISPR-Cas9 genome editing technology to prevent Sox2ot gene expression in mice. We designed 9 guide RNAs to specifically target the Sox2ot promoter and 3 gRNAs induced gene editing on the promoter of the Sox2ot gene in cells transfected with Cas9 mRNA and gRNAs. Then, these gRNAs and Cas9 mRNA were injected into mouse zygotes and implanted into pseudopregnant mice. A Sox2ot promoter-deleted mouse line was identified with complete deletion of promoter as well as deletion of exon 1 and exon 2. Sox2ot transcript was truncated with a lack of exon 1 and exon 2 in Sox2ot promoter-deleted mice. Furthermore, neural tube closure and embryonic development were checked at E9.5, E10.5, E14.5, E17.5 and after-birth (P2) and we did not find any failure of neural tube closure and aberrant embryonic development in Sox2ot promoter-deleted mice. Thus, our study demonstrated that CRISPR-Cas9 gene editing in Sox2ot promoter leads to its truncated expression and does not influence neural tube closure and embryonic development.

Long Noncoding RNA SOX2-OT: Regulations, Functions, and Roles on Mental Illnesses, Cancers, and Diabetic Complications.

SRY-box transcription factor 2 (SOX2) overlapping transcript (SOX2-OT) is an evolutionarily conserved long noncoding RNA. Its intronic region contains the SOX2 gene, the major regulator of the pluripotency of embryonic stem cells. The human SOX2-OT gene comprises multiple exons and has multiple transcription start sites and generates hundreds of transcripts. Transcription factors (IRF4, AR, and SOX3), transcriptional inhibitors (NSPc1, MTA3, and YY1), and miRNAs (miR-211 and miR-375) have been demonstrated to control certain SOX2-OT transcript level at the transcriptional or posttranscriptional levels. Accumulated evidence indicates its crucial roles in the regulation of the SOX2 gene, miRNAs, and transcriptional process. Restricted expression of SOX2-OT transcripts in the brain results in the association between SOX2-OT single nucleotide polymorphisms and mental illnesses such as schizophrenia and anorexia nervosa. SOX2-OT is notably elevated in tumor tissues, and a high level of SOX2-OT is well correlated with poor clinical outcomes in cancer patients, leading to the establishment of its role as an oncogene and a prognostic or diagnostic biomarker for cancers. The emerging evidence supports that SOX2-OT mediates diabetic complications. In summary, SOX2-OT has diversified functions and could be a therapeutic target for various diseases.

Porphyromonas gingivalis promotes progression of esophageal squamous cell cancer via TGFß-dependent Smad/YAP/TAZ signaling.

Microbial dysbiosis in the upper digestive tract is linked to an increased risk of esophageal squamous cell carcinoma (ESCC). Overabundance of Porphyromonas gingivalis is associated with shorter survival of ESCC patients. We investigated the molecular mechanisms driving aggressive progression of ESCC by P. gingivalis. Intracellular invasion of P. gingivalis potentiated proliferation, migration, invasion, and metastasis abilities of ESCC cells via transforming growth factor-ß (TGFß)-dependent Drosophila mothers against decapentaplegic homologs (Smads)/Yes-associated protein (YAP)/Transcriptional coactivator with PDZ-binding motif (TAZ) activation. Smads/YAP/TAZ/TEA domain transcription factor1 (TEAD1) complex formation was essential to initiate downstream target gene expression, inducing an epithelial-mesenchymal transition (EMT) and stemness features. Furthermore, P. gingivalis augmented secretion and bioactivity of TGFß through glycoprotein A repetitions predominant (GARP) up-regulation. Accordingly, disruption of either the GARP/TGFß axis or its activated Smads/YAP/TAZ complex abrogated the tumor-promoting role of P. gingivalis. P. gingivalis signature genes based on its activated effector molecules can efficiently distinguish ESCC patients into low- and high-risk groups. Targeting P. gingivalis or its activated effectors may provide novel insights into clinical management of ESCC.

NEAT1_2-SFPQ axis mediates cisplatin resistance in liver cancer cells in vitro.

BACKGROUND: Liver cancer is a type of malignant tumor with high morbidity and mortality in People's Republic of China. Its occurrence and development involve the variation and expression changes of multiple genes, and the pathogenesis and related regulatory networks are complex. PURPOSE: In the present research, we investigate the involvement of NEAT1_2 and SFPQ in cisplatin resistance in liver cancer. The effects of LncRNA NEAT1 and SFPQ expression on the chemotherapeutic resistance of liver cancer cells were analyzed. METHODS: The expression level of NEAT1_2 and SFPQ mRNA in tissue specimens or cell lines were examined by RT-qPCR and western blotting. CCK-8 assay was performed to evaluate cell viability. Cell proliferation was performed using the EdU cell proliferation assay. RESULTS: Our data showed that increase NEAT1_2 and SFPQ expressions in liver cancer specimens were associated with the development of cisplatin resistance; high SFPQ expression level impaired patients' survival from liver cancer. Gain-and loss-of function assay using NEAT1_2 knock-in and knock-out cells constructed using CRISPER/Cas9 system revealed that NEAT1_2 is essential for liver cancer cell survival and mediates cisplatin resistance in liver cancer cells at least partially through SFPQ. Artificial change in NEAT1_2 expression level didn't significantly influence SFPQ transcription or translation level. CONCLUSION: Our data revealed NEAT1_2-SFPQ axis as a novel cisplatin resistance mechanism in liver cancer cells in vitro.

Cell-free DNA in blood and urine as a diagnostic tool for bladder cancer: a meta-analysis.

OBJECTIVE: To assess the diagnostic performance of cell-free DNA assays in the detection of bladder cancer. PATIENTS AND METHODS: The quality of the studies included in this meta-analysis was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Statistical analyses were performed using the software RevMan 5.3 and Stata 14.0. We assessed the pooled sensitivity and specificity, positive/negative likelihood ratios (PLRs/NLRs), diagnostic odds ratios (DORs), and corresponding 95% confidence intervals (95% CIs). Summary receiver operating characteristic curve (ROC curve) and area under the curve (AUC) were used to summarize the overall test performance. Heterogeneity and publication bias were also examined. RESULTS: Eleven studies included 802 bladder cancer patients and 668 controls met the eligibility criteria. The overall diagnostic accuracy was measured as follows: sensitivity 0.71 (95% CI = 0.64-0.77), specificity 0.78 (95% CI = 0.70-0.85), PLR 3.3 (95% CI = 2.4-54.5), NLR 0.37 (95% CI = 0.30-0.46), DOR 9 (95% CI = 6-14), and AUC 0.80 (95% CI = 0.77-0.83). Subgroup analysis suggested that ethnicity significantly accounted for the heterogeneity of specificity. The Deeks' funnel plot asymmetry test (P = 0.97) suggested no potential publication bias. CONCLUSIONS: Cell-free DNA has a high diagnostic value in bladder cancer.

A highly integrated precision nanomedicine strategy to target esophageal squamous cell cancer molecularly and physically.

The prognosis of esophageal squamous cell carcinoma is poor. We hereby presented a highly integrated and clinically relevant precision nanomedicine strategy to target ESCC molecularly and physically for significant improvement of the treatment efficacy. We firstly identified PI3K overexpression in patient samples and its relation to poor patient survival. With our highly versatile tumor-targeted drug delivery platform (DCM), we were able to load a potent but toxic docetaxel (DTX) and a PI3K inhibitor (AZD8186) with favorable physical properties. The combination of the DTX-DCM and AZD8186-DCM showed a highly efficacious and synergistic anti-tumor effect and decreased hematotoxicity. A pro-apoptotic protein, Bax was significantly upregulated in ESCC cells treated with combination therapy compared to that with monotherapy. This study utilized a highly integrated precision nano-medicine strategy that combines the identification of cancer molecular target from human patients, precision drug delivery and effective combination therapy for the development of better ESCC treatment.

Nanoformulated paclitaxel and AZD9291 synergistically eradicate non-small-cell lung cancers in vivo.

AIM: This study aims to develop new nanoformulations of EGFR T790M targeted inhibitor AZD9291 and paclitaxel (PTX) for combination therapy of lung cancer. MATERIALS & METHODS: We prepared and characterized PTX- and AZD9291-loaded disulfide cross-linking micelles (DCMs), and evaluate their combination effect and toxicity in vitro and in lung cancer-bearing mice. RESULTS: Drug-loaded DCMs were relatively small in size, and possessed glutathione-responsive drug release. The combination of PTX-DCMs and AZD92921-DCMs exhibited strong synergistic effects in both cell line and in vivo without additional toxicity. Molecular studies demonstrated the synergistic modification in both IKB-α/NF-κB/Bcl-2 and EGFR/Akt pathways. CONCLUSION: The combination of DCM-loaded AZD9291 and PTX could potentially offer more effective and less toxicity treatment options for lung cancer patients.

Preoperative serum immunoglobulin G and A antibodies to Porphyromonas gingivalis are potential serum biomarkers for the diagnosis and prognosis of esophageal squamous cell carcinoma.

BACKGROUND: The key-stone-pathogen, Porphyromonas gingivalis associates not only with periodontal diseases but with a variety of other chronic diseases such as cancer. We previously reported an association between the presence of Porphyromonas gingivalis in esophageal squamous cell carcinoma (ESCC) and its progression. We now report the diagnostic and prognostic potential of serum immunoglobulin G and A antibodies (IgG/A) against Porphyromonas gingivalis for ESCC. METHODS: An enzyme-linked immunosorbent assay (ELISA) was used to determine the serum levels of Porphyromonas gingivalis IgG and IgA in 96 cases with ESCC, 50 cases with esophagitis and 80 healthy controls. RESULTS: The median serum levels of IgG and IgA for P. gingivalis were significantly higher in ESCC patients than non-ESCC controls. P. gingivalis IgG and IgA in serum demonstrated sensitivities/specificities of 29.17%/96.90% and 52.10%/70.81%, respectively, and combination of IgG and IgA produced a sensitivity/specificity of 68.75%/68.46%. The diagnostic performance of serum P. gingivalis IgA for early ESCC was superior to that of IgG (54.54% vs. 20.45%). Furthermore, high serum levels of P. gingivalis IgG or IgA were associated with worse prognosis of ESCC patients, in particular for patients with stage 0-IIor negative lymphnode metastasis, and ESCC patients with high levels of both IgG and IgA had the worst prognosis. Multivariate analysis revealed that lymph node status, IgG and IgA were independent prognostic factors. CONCLUSIONS: The IgG and IgA for P. gingivalis are potential serum biomarkers for ESCC and combination of IgG and IgA improves the diagnostic and prognostic performance. Furthermore, serum P. gingivalis IgG and IgA can detect early stage ESCC.

Macrophage migration inhibitory factor promotes tumor aggressiveness of esophageal squamous cell carcinoma via activation of Akt and inactivation of GSK3ß.

The pleiotropic pro-inflammatory cytokine, macrophage migration inhibitory factor (MIF), represents an important link between chronic inflammation and tumorigenesis. Although accumulating evidence demonstrates that MIF overexpression is implicated in the development and progression of multiple cancers, including esophageal squamous cell carcinoma (ESCC), the molecular mechanisms underlying its tumor-promoting roles in ESCC remain unclear. In the present study, we observed that MIF is overexpressed in ESCC and correlated significantly with lymph node metastasis, advanced clinical stage, and poor survival of ESCC. MIF knockdown attenuated the proliferation, migration, and invasion of ESCC cells in vitro and in vivo. Moreover, blockage of MIF expression decreased the activation of the Akt, MEK/ERK, and NF-κB pathways and enhanced sensitivity to apoptosis. Meanwhile, repression of MIF expression resulted in activation of glycogen synthase kinase 3 beta (GSK3ß) and subsequent decrease of active ß-catenin, as well as its downstream targets including cyclin D1, matrix metalloproteinase (MMP)-7, c-myc, and c-Jun. Collectively, our results provided mechanistic insights into the tumor-promoting role of MIF in ESCC, and suggested that MIF represents a potential therapeutic target for treatment of ESCC.