Age-dependent reference intervals in children for the disialoganglioside, GD2, a circulating tumor biomarker for the childhood cancer, neuroblastoma.

BACKGROUND: The disialoganglioside GD2 is a circulating tumor biomarker for the childhood cancer, neuroblastoma. This study establishes reference intervals for GD2 concentration in children within the age range where neuroblastoma commonly occurs. METHODS: Leftover plasma samples taken for routine clinical laboratory tests from children without cancer were collected and assayed for the 18-carbon fatty acid chain length lipoform of GD2 using a validated high-pressure liquid chromatography tandem mass spectrometry method with a lower limit of quantification of 3 nM. Samples were stratified into 5 age cohorts (0-6 months, 6-12 months, 12-36 months, 3-10 years and > 10 years). Non-parametric statistical methods were used to define the upper bound of the reference interval for each age cohort. RESULTS: GD2 was measurable in 90% of samples from children < 10 years of age and GD2 concentration was age-dependent, peaking at 9 months followed by a gradual decline. GD2 was below the lower limit of quantification in 55% of samples in the > 10 years cohort. Upper bounds of reference intervals were 15.5 nM in 0-6 month cohort, 35.1 nM in 6-12 month cohort, 24.9 nM in 12-36 month cohort, 18.4 in 3-10 year cohort and 10.4 nM in > 10 year cohort. CONCLUSIONS: Age-dependent reference intervals were defined for circulating GD2 in children. GD2 concentration was highest in the 6-12 month age cohort, which is below the age of most children with high-risk neuroblastoma. The peak GD2 concentration at 9 months may reflect neurodevelopmental events in the brain.

Long noncoding RNAs to predict postoperative recurrence in bladder cancer and to develop a new molecular classification system.

BACKGROUND: Reliable molecular markers are much needed for early prediction of recurrence in muscle-invasive bladder cancer (MIBC) patients. We aimed to build a long-noncoding RNA (lncRNA) signature to improve recurrence prediction and lncRNA-based molecular classification of MIBC. METHODS: LncRNAs of 320 MIBC patients from the Cancer Genome Atlas (TCGA) database were analyzed, and a nomogram was established. A molecular classification system was created, and immunotherapy and chemotherapy response predictions, immune score analysis, immune infiltration analysis, and mutational data analysis were conducted. Survival analysis validation was also performed. RESULTS: An eight-lncRNA signature classifed the patients into high- and low-risk subgroups, and these groups had significantly different (disease-free survival) DFS. The ability of the eight-lncRNA signature to make an accurate prognosis was tested using a validation dataset from our samples. The nomogram achieved a C-index of 0.719 (95% CI, 0.674-0.764). Time-dependent receiver operating characteristic curve (ROC) analysis indicated the superior prognostic accuracy of nomograms for DFS prediction (0.76, 95% CI, 0.697-0.807). Further, the four clusters (median DFS = 11.8, 15.3, 17.9, and 18.9 months, respectively) showed a high frequency of TTN (cluster 1), fibroblast growth factor receptor-3 (cluster 2), TP53 (cluster 3), and TP53 mutations (cluster 4), respectively. They were enriched with M2 macrophages (cluster 1), CD8+ T cells (cluster 2), M0 macrophages (cluster 3), and M0 macrophages (cluster 4), respectively. Clusters 2 and 3 demonstrated potential sensitivity to immunotherapy and insensitivity to chemotherapy, whereas cluster 4 showed potential insensitivity to immunotherapy and sensitivity to chemotherapy. CONCLUSIONS: The eight-lncRNA signature risk model may be a reliable prognostic signature for MIBC, which provides new insights into prediction of recurrence of MIBC. The model may help clinical decision and eventually benefit patients.

THE ROLE OF THE APPARENT DIFFUSION COEFFICIENT OF THE BIPARAMETRIC MRI AS AN IMAGING MARKER OF PROSTATE CANCER. / ROL' VYMIRIuVANOGO KOEFITsIIeNTA DYFUZIÏ BIPARAMETRYChNOÏ MRT IaK PROMENEVOGO MARKERA RAKU PEREDMIKhUROVOÏ ZALOZY.

Prostate cancer (PCa) is the most common malignancy in men. The role of the apparent diffusion coefficient (ADC)of biparametric MRI (biMRI) which is a study without the use of dynamic contrast enhancement (DCE), in detectionof PCa is still not comprehensively investigated. OBJECTIVE: The goal of the study was to assess the role of ADC of biMRI as an imaging marker of clinically significant PCaMaterials and methods. The study involved 78 men suspected of having PCa. All patients underwent a comprehensive clinical examination, which included multiparametric MRI of the prostate, a component of which was biMRI. TheMRI data was evaluated according to the PIRADS system version 2.1. RESULTS: The distribution of patients according to the PIRADS system was as follows: 1 point - 9 (11.54 %)patients, 2 points - 12 (15.38 %) patients, 3 points - 25 (32.05 %) patients, 4 points - 19 (24.36 %) patients and5 points - 13 (16.67 %) patients. In a subgroup of patients with 5 points, clinically significant PCa was detected in 100 % of cases. In the subgroup of patients with tumors of 4 points clinically significant PCa was diagnosed in 16of 19 (84.21 %) cases, and in 3 (15.79 %) patients - clinically insignificant tumor. In the subgroup of patients with3 points, clinically significant PCa was diagnosed in 11 of 25 (44.0 %) cases, in 8 (32.0 %) patients - clinicallyinsignificant tumor and in 6 (24.0 %) patients - benign prostatic hyperplasia. PCa with a score of 7 on the Gleasonscale showed significantly lower mean values of ADC of the diffusion weighted MRI images compared to tumors witha score of < 7 on the Gleason scale: (0.86 ± 0.07) x 103 mm2/s vs (1.08 ± 0.04) x 103 mm2/s (р < 0.05). CONCLUSIONS: The obtained results testify to the high informativeness of biMRI in the diagnosis of prostate cancer.The use of ADC allowed to differentiate clinically significant and insignificant variants of the tumor, as well asbenign changes in prostate tissues and can be considered as a potential imaging marker of PCa.

Using Comorbidity Pattern Analysis to Detect Reliable Methylated Genes in Colorectal Cancer Verified by Stool DNA Test.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide in 2020. Colonoscopy and the fecal immunochemical test (FIT) are commonly used as CRC screening tests, but both types of tests possess different limitations. Recently, liquid biopsy-based DNA methylation test has become a powerful tool for cancer screening, and the detection of abnormal DNA methylation in stool specimens is considered as an effective approach for CRC screening. The aim of this study was to develop a novel approach in biomarker selection based on integrating primary biomarkers from genome-wide methylation profiles and secondary biomarkers from CRC comorbidity analytics. A total of 125 differential methylated probes (DMPs) were identified as primary biomarkers from 352 genome-wide methylation profiles. Among them, 51 biomarkers, including 48 hypermethylated DMPs and 3 hypomethylated DMPs, were considered as suitable DMP candidates for CRC screening tests. After comparing with commercial kits, three genes (ADHFE1, SDC2, and PPP2R5C) were selected as candidate epigenetic biomarkers for CRC screening tests. Methylation levels of these three biomarkers were significantly higher for patients with CRC than normal subjects. The sensitivity and specificity of integrating methylated ADHFE1, SDC2, and PPP2R5C for CRC detection achieved 84.6% and 92.3%, respectively. Through an integrated approach using genome-wide DNA methylation profiles and electronic medical records, we could design a biomarker panel that allows for early and accurate noninvasive detection of CRC using stool samples.

The subtype-specific molecular function of SPDEF in breast cancer and insights into prognostic significance.

Breast cancer (BC) is a molecular diverse disease which becomes the most common malignancy among women worldwide. There are four BC subtypes (Luminal A, Luminal B, HER2-enriched and Basal-like) robustly established following gene expression pattern-based characterization, behave significant differences in terms of their incidence, risk factors, prognosis and therapeutic sensitivity. Thus, there is an urgent need to provide mechanism research, treatment strategies and/or prognosis evaluation based on the patient stratification of BC subtypes. The prostate-derived ETS factor SPDEF was first identified as an activator of prostate specific antigen, and then, the involvements in many aspects of BC have been proposed. However, the subtype-specific molecular function of SPDEF in BC and insights into prognostic significance have not been clearly elucidated. This study demonstrated for the first time that SPDEF may play a diversity role in the expression levels, clinicopathologic importance, biological function and prognostic evaluation in BC via bioinformatics and experimental evidence, which mainly depends on different BC subtyping. In summary, our findings would help to better understand the possible mechanisms of various BC subtypes and to find possible candidate genes for prognostic and therapeutic usage.

Validation of the functions and prognostic values of synapse-associated proteins in lower-grade glioma.

Synapse and synapse-associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. In the present study, we integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from GEO, TCGA and CGGA database. The prognosis associated SAPs in key modules of PPI (protein-protein interaction networks) was regarded as hub SAPs. Western blot, quantitative reverse transcription PCR (qRT-PCR) and immunochemistry results from HPA database were used to verify the expression of hub SAPs. There were 68 up-regulated SAPs and 44 down-regulated SAPs in LGG tissue compared with normal brain tissue. Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed that four SAPs, GRIK2, GABRD, GRID2 and ARC were correlate with the prognosis of LGG patients. Interestingly, we found that GABRD were up-regulated in LGG patients with seizures, indicating that SAPs may link to the pathogenesis of seizures in glioma patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs.

Diagnostic Accuracy with Total Adenosine Deaminase as a Biomarker for Discriminating Pleural Transudates and Exudates in a Population-Based Cohort Study.

BACKGROUND: An initial step in the evaluation of patients with pleural effusion syndrome (PES) is to determine whether the pleural fluid is a transudate or an exudate. OBJECTIVES: To investigate total adenosine deaminase (ADA) as a biomarker to classify pleural transudates and exudates. METHODS: An assay of total ADA in pleural fluids (P-ADA) was observed using a commercial kit in a population-based cohort study. RESULTS: 157 pleural fluid samples were collected from untreated individuals with PES due to several causes. The cause most prevalent in transudate samples (21%, n = 33/157) was congestive heart failure (79%, 26/33) and that among exudate samples (71%, n = 124/157) was tuberculosis (28.0%, 44/124). There was no significant difference in the proportion of either sex between the transudate and exudate groups. The median values of P-ADA were significantly different (P < 0.0001) between both total exudates (18.4 U/L; IQR, 9.85-41.4) and exudates without pleural tuberculosis (11.0 U/L; IQR, 7.25-19.75) and transudates (6.85; IQR, 2.67-11.26). For exudates, the AUC was 0.820 (95% CI, 0.751-0.877; P < 0.001), with excellent discrimination. The optimum cut-off point in the ROC curve was determined as the level that provided the maximum positive likelihood ratio (PLR; 14.64; 95% CI, 2.11-101.9) and was22.0 U/L. For transudates, the AUC was 0.8245 (95% CI, 0.7470-0.9020; P < 0.0001). Internal validation of the AUC after 1000 resamples was evaluated with a tolerance minor than 2%. The clinical utility was equal to 92% (95% CI, 0.84 to 0.96, P < 0.05). CONCLUSIONS: P-ADA is a useful biomarker for distinguishing pleural exudates from transudates.

Prognostic Value of Pretreated Blood Inflammatory Markers in Patients with Bone Sarcoma: A Meta-Analysis.

METHOD: We conducted a detailed literature search in Medline and Embase databases and collected relevant publications written in English before April 2020. Overall survival (OS) and disease-free survival (DFS) were the primary and secondary outcomes, respectively. Basic features of patients, hazard ratios (HRs), and 95% confidence intervals (CI) were retrieved to assess the correlation between pretreated blood inflammatory markers and patients with bone sarcoma. This meta-analysis used Stata 12.0. RESULTS: A total of 10 studies containing 1845 cases were included for analysis. Nine of them evaluated the neutrophil lymphocyte ratio (NLR), 7 the platelet lymphocyte ratio (PLR), and 4 the lymphocyte monocyte ratio (LMR). Pooled results revealed that higher pretreatment NLR was associated with poorer OS (HR = 1.76, 95% CI: 1.29-2.41, and P < 0.001) and DFS (HR = 1.77, 95% CI: 1.09-2.88, and P = 0.021). In contrast, a lower LMR was related to worse OS (HR = 0.73, 95% CI: 0.57-0.92, and P = 0.009), but not DFS (HR = 0.68, 95% CI: 0.41-1.11, and P > 0.05). Combined results did not show a significant predictive effect of PLR on the clinical outcomes of patients with bone sarcoma (OS : HR = 1.32, 95% CI: 0.99-1.75, and P > 0.05; DFS: HR = 1.12, 95% CI: 0.87-1.44, P > 0.05). CONCLUSION: NLR and LMR might be promising predictive biomarkers for patients with bone sarcoma and could be used to stratify patients and provide personalized therapeutic strategies.

The Value of a Seven-Autoantibody Panel Combined with the Mayo Model in the Differential Diagnosis of Pulmonary Nodules.

BACKGROUND: Identifying malignant pulmonary nodules and detecting early-stage lung cancer (LC) could reduce mortality. This study investigated the clinical value of a seven-autoantibody (7-AAB) panel in combination with the Mayo model for the early detection of LC and distinguishing benign from malignant pulmonary nodules (MPNs). METHODS: The concentrations of the elements of a 7-AAB panel were quantitated by enzyme-linked immunosorbent assay (ELISA) in 806 participants. The probability of MPNs was calculated using the Mayo predictive model. The performances of the 7-AAB panel and the Mayo model were analyzed by receiver operating characteristic (ROC) analyses, and the difference between groups was evaluated by chi-square tests (χ 2). RESULTS: The combined area under the ROC curve (AUC) for all 7 AABs was higher than that of a single one. The sensitivities of the 7-AAB panel were 67.5% in the stage I-II LC patients and 60.3% in the stage III-IV patients, with a specificity of 89.6% for the healthy controls and 83.1% for benign lung disease patients. The detection rate of the 7-AAB panel in the early-stage LC patients was higher than that of traditional tumor markers. The AUC of the 7-AAB panel in combination with the Mayo model was higher than that of the 7-AAB panel alone or the Mayo model alone in distinguishing MPN from benign nodules. For early-stage MPN, the sensitivity and specificity of the combination were 93.5% and 58.0%, respectively. For advanced-stage MPN, the sensitivity and specificity of the combination were 91.4% and 72.8%, respectively. The combination of the 7-AAB panel with the Mayo model significantly improved the detection rate of MPN, but the positive predictive value (PPV) and the specificity were not improved when compared with either the 7-AAB panel alone or the Mayo model alone. CONCLUSION: Our study confirmed the clinical value of the 7-AAB panel for the early detection of lung cancer and in combination with the Mayo model could be used to distinguish benign from malignant pulmonary nodules.

Clinicopathological Features and Prognostic Value of KRAS/NRAS/BRAF Mutations in Colorectal Cancer Patients of Central China.

The incidence of colorectal cancer (CRC) is increasing in China, with high mortality. Here, we aimed to evaluate the latest clinicopathological features and prognostic value of the KRAS/NRAS/BRAF mutation status in CRC patients in Central China. The clinical data of 1549 CRC patients with stage I-IV disease diagnosed at Union Hospital, Tongji Medical College of Huazhong University of Science and Technology from 2015 to 2017 were collected and analyzed retrospectively. KRAS/NRAS/BRAF mutations were detected by real-time quantitative polymerase chain reaction (q-PCR) in 410 CRC patients, with mutation frequencies of KRAS, NRAS and BRAF of 47.56%, 2.93% and 4.15%, respectively. The gene mutation status and clinicopathological characteristics of 410 patients with CRC who underwent qPCR were analyzed. The KRAS and BRAF gene mutations were related to the pathological differentiation and number of metastatic lymph nodes. The BRAF gene mutation was also associated with cancer thrombosis in blood vessels. Cox regression analysis showed that there was no statistically significant difference in the overall survival (OS) between patients with KRAS, NRAS mutants and wild-type CRC patients, while the BRAF gene mutation was negatively correlated with the OS rate of CRC patients. It is suggested that the BRAF gene mutation may be an independent risk factor for the prognosis of CRC.

Identification of Circulating Serum miRNAs as Novel Biomarkers in Pancreatic Cancer Using a Penalized Algorithm.

Pancreatic cancer (PC) is difficult to detect in the early stages; thus, identifying specific and sensitive biomarkers for PC diagnosis is crucial, especially in the case of early-stage tumors. Circulating microRNAs are promising non-invasive biomarkers. Therefore, we aimed to identify non-invasive miRNA biomarkers and build a model for PC diagnosis. For the training model, blood serum samples from 63 PC patients and 63 control subjects were used. We selected 39 miRNA markers using a smoothly clipped absolute deviation-based penalized support vector machine and built a PC diagnosis model. From the double cross-validation, the average test AUC was 0.98. We validated the diagnosis model using independent samples from 25 PC patients and 81 patients with intrahepatic cholangiocarcinoma (ICC) and compared the results with those obtained from the diagnosis using carbohydrate antigen 19-9. For the markers miR-155-5p, miR-4284, miR-346, miR-7145-5p, miR-5100, miR-661, miR-22-3p, miR-4486, let-7b-5p, and miR-4703-5p, we conducted quantitative reverse transcription PCR using samples from 17 independent PC patients, 8 ICC patients, and 8 healthy individuals. Differential expression was observed in samples from PC patients. The diagnosis model based on the identified markers showed high sensitivity and specificity for PC detection and is potentially useful for early PC diagnosis.

High-dimensional variable selection for ordinal outcomes with error control.

Many high-throughput genomic applications involve a large set of potential covariates and a response which is frequently measured on an ordinal scale, and it is crucial to identify which variables are truly associated with the response. Effectively controlling the false discovery rate (FDR) without sacrificing power has been a major challenge in variable selection research. This study reviews two existing variable selection frameworks, model-X knockoffs and a modified version of reference distribution variable selection (RDVS), both of which utilize artificial variables as benchmarks for decision making. Model-X knockoffs constructs a 'knockoff' variable for each covariate to mimic the covariance structure, while RDVS generates only one null variable and forms a reference distribution by performing multiple runs of model fitting. Herein, we describe how different importance measures for ordinal responses can be constructed that fit into these two selection frameworks, using either penalized regression or machine learning techniques. We compared these measures in terms of the FDR and power using simulated data. Moreover, we applied these two frameworks to high-throughput methylation data for identifying features associated with the progression from normal liver tissue to hepatocellular carcinoma to further compare and contrast their performances.

Prospective Evaluation of the NETest as a Liquid Biopsy for Gastroenteropancreatic and Bronchopulmonary Neuroendocrine Tumors: An ENETS Center of Excellence Experience.

BACKGROUND: There is a substantial unmet clinical need for an accurate and effective blood biomarker for neuroendocrine neoplasms (NEN). We therefore evaluated, under real-world conditions in an ENETS Center of Excellence (CoE), the clinical utility of the NETest as a liquid biopsy and compared its utility with chromogranin A (CgA) measurement. METHODS: The cohorts were: gastroenteropancreatic NEN (GEP-NEN; n = 253), bronchopulmonary NEN (BPNEN; n = 64), thymic NEN (n = 1), colon cancer (n = 37), non-small-cell lung cancer (NSCLC; n = 63), benign lung disease (n = 59), and controls (n = 86). In the GEPNEN group, 164 (65%) had image-positive disease (IPD, n = 135) or were image-negative but resection-margin/biopsy-positive (n = 29), and were graded as G1 (n = 106), G2 (n = 49), G3 (n = 7), or no data (n = 2). The remainder (n = 71) had no evidence of disease (NED). In the BPNEN group, 43/64 (67%) had IPD. Histology revealed typical carcinoids (TC, n = 14), atypical carcinoids (AC, n = 14), small-cell lung cancer (SCLC, n = 11), and large-cell neuroendocrine carcinoma (LCNEC, n = 4). Disease status (stable or progressive) was evaluated according to RECIST v1.1. Blood sampling involved NETest (n = 563) and NETest/CgA analysis matched samples (n = 178). NETest was performed by PCR (on a scale of 0-100), with a score ≥20 reflecting a disease-positive status and >40 reflecting progressive disease. CgA positivity was determined by ELISA. Samples were deidentified and measurements blinded. The Kruskal-Wallis, Mann-Whitney U, and McNemar tests, and the area under the curve (AUC) of the receiver-operating characteristics (ROC) were used in the statistical analysis. RESULTS: In the GEPNEN group, NETest was significantly higher (34.4 ± 1.8, p < 0.0001) in disease-positive patients than in patients with NED (10.5 ± 1, p < 0.0001), colon cancer patients (18 ± 4, p < 0.0004), and controls (7 ± 0.5, p < 0.0001). Sensitivity for detecting disease compared to controls was 89% and specificity was 94%. NETest levels were increased in G2 vs. G1 (39 ± 3 vs. 32 ± 2, p = 0.02) and correlated with stage (localized: 26 ± 2 vs. regional/distant: 40 ± 3, p = 0.0002) and progression (55 ± 5 vs. 34 ± 2 in stable disease, p = 0.0005). In the BPNEN group, diagnostic sensitivity was 100% and levels were significantly higher in patients with bronchopulmonary carcinoids (BPC; 30 ± 1.3) who had IPD than in controls (7 ± 0.5, p < 0.0001), patients with NED (24.1 ± 1.3, p < 0.005), and NSCLC patients (17 ± 3, p = 0.0001). NETest levels were higher in patients with poorly differentiated BPNEN (LCNEC + SCLC; 59 ± 7) than in those with BPC (30 ± 1.3, p = 0.0005) or progressive disease (57.8 ± 7), compared to those with stable disease (29.4 ± 1, p < 0.0001). The AUC for differentiating disease from controls was 0.87 in the GEPNEN group and 0.99 in BPC patients (p < 0.0001). Matched CgA analysis was performed in 178 patients. In the GEPNEN group (n = 135), NETest was significantly more accurate for detecting disease (99%) than CgA positivity (53%; McNemar test χ2 = 87, p < 0.0001). In the BPNEN group (n = 43), NETest was significantly more accurate for disease detection (100%) than CgA positivity (26%; McNemar's test χ2 = 30, p < 0.0001). CONCLUSIONS: The NETest is an accurate diagnostic for GEPNEN and BPNEN. It exhibits tumor biology correlation with grading, staging, and progression. CgA as a biomarker is significantly less accurate than NETest. The NETest has substantial clinical utility that can facilitate patient management.

Prognostic significance of the MDM2/HMGA2 ratio and histological tumor grade in dedifferentiated liposarcoma.

Dedifferentiated liposarcoma (DDLPS) is a relatively common soft tissue sarcoma that results from the progression of well-differentiated liposarcoma (WDLPS). This study aimed to investigate the progression process and to clarify the pathological and genetic factors related to poor prognosis in DDLPS. In 32 DDLPS cases and five WDLPS cases, genetic factors were analyzed by custom comparative genomic hybridization (CGH) array, which was designed to densely cover gene regions known to be frequently amplified in WD/DDLPS. The analyses comparing primary and metastatic lesions and those comparing histologically different areas in the same tumor revealed intra-tumoral genetic heterogeneity and progression. According to a prognostic analysis comparing the good-prognosis and the poor-prognosis groups, we selected MDM2 and HMGA2 as candidate genes associated with poor and good prognosis, respectively. The ratios of the amplification or gain levels of MDM2 and HMGA2 expressed in log ratios (log[MDM2/HMGA2] = log[MDM2]-log[HMGA2]) were significantly associated with prognosis. An amplification or gain level of MDM2 that was more than twice that of HMGA2 (MDM2/HMGA2 > 2, log[MDM2/HMGA2] > 1) was strongly related to poor OS (P < .001) and poor distant metastasis-free survival (DMFS) (P < .001). In the pathological analysis of 44 cases of DDLPS, histological tumor grade, cellular atypia, and MDM2 immunoreactivity were related to overall survival (OS), while HMGA2 immunoreactivity tended to be associated with OS. Cellular atypia was also associated with DMFS. In conclusion, histological grade and MDM2 expression were determined to be prognostically important, and the MDM2/HMGA2 amplification or gain ratio was found to have significant prognostic value by the custom CGH array analysis.

Prognostic Threshold for Circulating Tumor Cells in Patients With Pancreatic and Midgut Neuroendocrine Tumors.

BACKGROUND: Circulating tumor cells (CTCs) are detectable in patients with neuroendocrine tumors (NETs) and are accurate prognostic markers although the optimum threshold has not been defined. OBJECTIVE: This work aims to define optimal prognostic CTC thresholds in PanNET and midgut NETs. PATIENTS AND METHODS: CellSearch was used to enumerate CTCs in 199 patients with metastatic pancreatic (PanNET) (90) or midgut NETs (109). Patients were followed for progression-free survival (PFS) and overall survival (OS) for a minimum of 3 years or until death. RESULTS: The area under the receiver operating characteristic curve (AUROC) for progression at 12 months in PanNETs and midgut NETs identified the optimal CTC threshold as 1 or greater and 2 or greater, respectively. In multivariate logistic regression analysis, these thresholds were predictive for 12-month progression with an odds ratio (OR) of 6.69 (P < .01) for PanNETs and 5.88 (P < .003) for midgut NETs. The same thresholds were found to be optimal for predicting death at 36 months, with an OR of 2.87 (P < .03) and 5.09 (P < .005) for PanNETs and midgut NETs, respectively. In multivariate Cox hazard regression analysis for PFS in PanNETs, 1 or greater CTC had a hazard ratio (HR) of 2.6 (P < .01), whereas 2 or greater CTCs had an HR of 2.25 (P < .01) in midgut NETs. In multivariate analysis OS in PanNETs, 1 or greater CTCs had an HR of 3.16 (P < .01) and in midgut NETs, 2 or greater CTCs had an HR of 1.73 (P < .06). CONCLUSIONS: The optimal CTC threshold to predict PFS and OS in metastatic PanNETs and midgut NETs is 1 and 2, respectively. These thresholds can be used to stratify patients in clinical practice and clinical trials.

Development and validation of a novel survival model for head and neck squamous cell carcinoma based on autophagy-related genes.

BACKGROUND: In view of the critical role of autophagy-related genes (ARGs) in the pathogenesis of various diseases including cancer, this study aims to identify and evaluate the potential value of ARGs in head and neck squamous cell carcinoma (HNSCC). METHODS: RNA sequencing and clinical data in The Cancer Genome Atlas (TCGA) were analyzed by univariate Cox regression analysis and Lasso Cox regression analysis model established a novel 13- autophagy related prognostic genes, which were used to build a prognostic risk model. A multivariate Cox proportional regression model and the survival analysis were used to evaluate the prognostic risk model. Moreover, the efficiency of prognostic risk model was tested by receiver operating characteristic (ROC) curve analysis based on data from TCGA database and Gene Expression Omnibus (GEO). Besides, the other independent datasets from Human Protein Atlas dataset (HPA) also applied. RESULTS: 13 ARGs (GABARAPL1, ITGA3, USP10, ST13, MAPK9, PRKN, FADD, IKBKB, ITPR1, TP73, MAP2K7, CDKN2A, and EEF2K) with prognostic value were identified in HNSCC patients. Subsequently, a prognostic risk model was established based on 13 ARGs, and significantly stratified HNSCC patients into high- and low-risk groups in terms of overall survival (OS) (HR = 0.379，95% CI: 0.289-0.495, p < 0.0001). The multivariate Cox analysis revealed that this model was an independent prognostic factor (HR = 1.506, 95% CI = 1.330-1.706, P < 0.001). The areas under the ROC curves (AUC) were significant for both the TCGA and GEO, with AUC of 0.685 and 0.928 respectively. Functional annotation revealed that model significantly enriched in many critical pathways correlated with tumorigenesis, including the p53 pathway, IL2 STAT5 signaling, TGF beta signaling, PI3K Ak mTOR signaling by gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). In addition, we developed a nomogram shown some clinical net could be used as a reference for clinical decision-making. CONCLUSIONS: Collectively, we developed and validated a novel robust 13-gene signatures for HNSCC prognosis prediction. The 13 ARGs could serve as an independent and reliable prognostic biomarkers and therapeutic targets for the HNSCC patients.

The serological responses to acute exercise in humans reduce cancer cell growth in vitro: A systematic review and meta-analysis.

We systematically reviewed and meta-analyzed the effects of acute exercise-conditioned serum on cancer cell growth in vitro. Five literature databases were systematically searched for studies that measured cancer cell growth after exposure to human sera obtained before and immediately after an acute bout of exercise. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were pooled using a three-level random-effects model. Meta-regressions were also performed with participant age and disease status, exercise type, cell line TP53 status, and serum incubation time entered as covariates. Seven studies met the inclusion criteria encompassing a total of 21 effect estimates and 98 participants. Exercise-conditioned serum significantly reduced cancer cell growth compared with preexercise serum (SMD = -1.23, 95% CI: -1.96 to -0.50; p = .002; I2  = 75.1%). The weighted mean reduction as a percentage of preexercise values was 8.6%. The overall treatment effect and magnitude of heterogeneity were not statistically influenced by any covariate. There were concerns regarding the risk of bias within individual studies and Egger's test of the intercept showed evidence of small study effects (ß = -3.6, p = .004). These findings provide in vitro evidence that the transient serological responses to acute exercises reduce cancer cell growth, although many questions remain regarding the underlying mechanistic pathways and potential effect modifiers. To strengthen this evidence-base, future studies should seek to reduce the risk of bias by using more rigorous experimental designs, and consider using 3D cell culture models to better replicate in vivo tumor conditions. PROSPERO registration: CRD42020161333.

Prognostic value of the common tumour-infiltrating lymphocyte subtypes for patients with non-small cell lung cancer: A meta-analysis.

BACKGROUND: Many previous studies have revealed that tumour-infiltrating lymphocytes (TILs) are significantly associated with prognosis in various tumours. However, this finding remains controversial in non-small cell lung cancer (NSCLC). We performed this meta-analysis systematically to evaluate the prognostic value of TILs in NSCLC. METHODS: The references were collected by searching the PubMed, EMBASE and Web of Science databases. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were summarized using random or fixed effects models to evaluate the association between TILs and NSCLC survival outcomes. RESULTS: A total of 45 interrelated studies were eligible that included 11,448 patients. Pooled analysis showed that a high density of TILs indicated a better overall survival (HR = 0.80, 0.70-0.89) and progression-free survival (HR = 0.73, 0.61-0.85) for patients with NSCLC; a high density of CD3+ TILs in the tumour nest indicated a better overall survival (HR = 0.84, 0.69-0.99) and disease-specific survival (HR = 0.57, 0.34-0.80); a high density of CD4+ TILs in the tumor nest indicated a favourable overall survival (HR = 0.86, 0.76-0.96); a high density of CD8+ TILs indicated a favourable overall survival (HR = 0.995, 0.99-1.0), progression-free survival (HR = 0.52, 0.34-0.71), disease-free survival (HR = 0.64, 0.43-0.85), relapse/recurrence-free survival (HR = 0.42, 0.18-0.67) and disease-specific survival (HR = 0.56, 0.35-0.78); and a high density of CD20+ TILs in the tumour nest indicated a favourable overall survival (HR = 0.65, 0.36-0.94). However, a high density of Foxp3+ TILs in the tumour stroma indicated a worse relapse/recurrence-free survival (HR = 1.90, 1.05-2.76) in NSCLC. CONCLUSIONS: Our meta-analysis confirmed that high densities of TILs, CD3+TILs, CD4+TILs, CD8+TILs and CD20+TILs in the tumour nest are favourable prognostic biomarkers for patients with NSCLC, and Foxp3+TILs in the tumour stroma are a poor prognostic biomarker.

Current Status of Circulating Tumor DNA Liquid Biopsy in Pancreatic Cancer.

Pancreatic cancer is a challenging disease with a low 5-year survival rate. There are areas for improvement in the tools used for screening, diagnosis, prognosis, treatment selection, and assessing treatment response. Liquid biopsy, particularly cell free DNA liquid biopsy, has shown promise as an adjunct to our standard care for pancreatic cancer patients, but has not yet been universally adopted into regular use by clinicians. In this publication, we aim to review cfDNA liquid biopsy in pancreatic cancer with an emphasis on current techniques, clinical utility, and areas of active investigation. We feel that researchers and clinicians alike should be familiar with this exciting modality as it gains increasing importance in the care of cancer patients.