The OsGAPC1-OsSGL module negatively regulates salt tolerance by mediating abscisic acid biosynthesis in rice.

Plants frequently encounter adverse conditions and stress during their lives. Abscisic acid (ABA) plays a crucial role in response to salt stress, and dynamic regulation of ABA levels is essential for plant growth and stress resistance. In this study, we identified a transcription factor, OsSGL (Oryza sativa Stress tolerance and Grain Length), which acts as a negative regulator in salt stress, controlling ABA synthesis. OsSGL-overexpressing and mutant materials exhibited sensitivity and tolerance to salt stress, respectively. Notably, under salt treatment, several ABA-related genes, including the ABA synthesis enzyme OsNCED3 and the ABA response gene OsRAB21, were bound by OsSGL, leading to the inhibition of their transcription. Additionally, we found that a key enzyme involved in glycolysis, OsGAPC1, interacted with OsSGL and enhanced the inhibitory effect of OsSGL on OsNCED3. Upon salt stress, OsGAPC1 underwent acetylation and then translocated from the nucleus to the cytoplasm, partially alleviating the inhibitory effect of OsSGL on OsNCED3. Identification of the OsGAPC1-OsSGL module revealed a negative regulatory mechanism involved in the response of rice to salt stress. This discovery provides insight into the dynamic regulation of ABA synthesis in plants under salt stress conditions, highlighting the delicate balance between stress resistance and growth regulation.

Single-pixel imaging based on self-supervised conditional mask classifier-free guidance.

Reconstructing high-quality images at a low measurement rate is a pivotal objective of Single-Pixel Imaging (SPI). Currently, deep learning methods achieve this by optimizing the loss between the target image and the original image, thereby constraining the potential of low measurement values. We employ conditional probability to ameliorate this, introducing the classifier-free guidance model (CFG) for enhanced reconstruction. We propose a self-supervised conditional masked classifier-free guidance (SCM-CFG) for single-pixel reconstruction. At a 10% measurement rate, SCM-CFG efficiently completed the training task, achieving an average peak signal-to-noise ratio (PSNR) of 26.17 dB on the MNIST dataset. This surpasses other methods of photon imaging and computational ghost imaging. It demonstrates remarkable generalization performance. Moreover, thanks to the outstanding design of the conditional mask in this paper, it can significantly enhance the accuracy of reconstructed images through overlay. SCM-CFG achieved a notable improvement of an average of 7.3 dB in overlay processing, in contrast to only a 1 dB improvement in computational ghost imaging. Subsequent physical experiments validated the effectiveness of SCM-CFG.

Multicenter phase II study of moderate low-dose radiotherapy in indolent non-Hodgkin lymphoma: CLCG-iNHL-01 protocol.

Background: Radiotherapy is an effective treatment for indolent non-Hodgkin lymphoma (iNHL); however, the optimal radiotherapy dose remains to be determined. We hypothesize that a suitable dose may exist between 4 and 24 Gy. Methods: This prospective multicenter phase II trial intends to recruit 73 sites of iNHL patients, who will receive involved-site radiotherapy of 12 Gy in four fractions. The primary objective is the 6-month clinical complete response rate. Tumor tissue, blood and conjunctival specimens will be collected to identify potential predictive biomarkers. Discussion: The CLCG-iNHL-01 trial will evaluate the efficacy and toxicity of 12 Gy in patients with iNHL and provide information on a novel hypofractionation regimen of low-dose radiotherapy. Clinical Trial Registration: NCT05543070 (ClinicalTrials.gov).

Adaptive Dual Aggregation Network with Normalizing Flows for Low-Light Image Enhancement.

Low-light image enhancement (LLIE) aims to improve the visual quality of images taken under complex low-light conditions. Recent works focus on carefully designing Retinex-based methods or end-to-end networks based on deep learning for LLIE. However, these works usually utilize pixel-level error functions to optimize models and have difficulty effectively modeling the real visual errors between the enhanced images and the normally exposed images. In this paper, we propose an adaptive dual aggregation network with normalizing flows (ADANF) for LLIE. First, an adaptive dual aggregation encoder is built to fully explore the global properties and local details of the low-light images for extracting illumination-robust features. Next, a reversible normalizing flow decoder is utilized to model real visual errors between enhanced and normally exposed images by mapping images into underlying data distributions. Finally, to further improve the quality of the enhanced images, a gated multi-scale information transmitting module is leveraged to introduce the multi-scale information from the adaptive dual aggregation encoder into the normalizing flow decoder. Extensive experiments on paired and unpaired datasets have verified the effectiveness of the proposed ADANF.

Radiotherapy Improves Survival of Patients With Lymphovascular Invasion in pT1b Esophageal Squamous Cell Cancer After Endoscopic Submucosal Dissection.

INTRODUCTION: Adjuvant radiotherapy is recommended for pT1b esophageal squamous cell cancer (ESCC) after endoscopic submucosal dissection (ESD). However, it is unclear whether additional radiotherapy can improve patient survival. This study aimed to evaluate the efficacy of adjuvant radiotherapy after ESD for pT1b ESCC. METHODS: This was a multicenter, cross-sectional study involving 11 hospitals in China. Between January 2010 and December 2019, patients with T1bN0M0 ESCC treated with or without adjuvant radiotherapy after ESD were included. Survival between groups was compared. RESULTS: Overall, 774 patients were screened, and 161 patients were included. Forty-seven patients (29.2%) received adjuvant radiotherapy after ESD (RT group) and 114 (70.8%) underwent ESD alone (non-RT group). There were no significant differences in overall survival (OS) and disease-free survival (DFS) between the RT and non-RT groups. Lymphovascular invasion (LVI) was the only prognostic factor. In the LVI+ group, adjuvant radiotherapy significantly improved survival (5-year OS: 91.7% vs 59.5%, P = 0.050; 5-year DFS: 92.9% vs 42.6%, P = 0.010). In the LVI- group, adjuvant radiotherapy did not improve survival (5-year OS: 83.5% vs 93.9%, P = 0.148; 5-year DFS: 84.2% vs 84.7%, P = 0.907). The standardized mortality ratios were 1.52 (95% confidence interval 0.04-8.45) in the LVI+ group with radiotherapy and 0.55 (95% confidence interval 0.15-1.42) in the LVI- group without radiotherapy. DISCUSSION: Adjuvant radiotherapy could improve survival in pT1b ESCC with LVI+ other than LVI- after ESD. Selective adjuvant radiotherapy based on LVI status achieved survival rates similar to those of the general population.

Evidence of cure for extranodal nasal-type natural killer/T-cell lymphoma with current treatment: an analysis of the CLCG database.

Survival from extranodal nasal-type NK/T-cell lymphoma (ENKTCL) has substantially improved over the last decade. However, there is little consensus as to whether a population of patients with ENKTCL can be considered "cured" of the disease. We aimed to evaluate the statistical "cure" of ENKTCL in the modern treatment era. This retrospective multicentric study reviewed the clinical data of 1,955 patients with ENKTCL treated with non-anthracycline-based chemotherapy and/or radiotherapy in the China Lymphoma Collaborative Group multicenter database between 2008 and 2016. A non-mixture cure model with incorporation of background mortality was fitted to estimate cure fractions, median survival times and cure time points. The relative survival curves attained plateau for the entire cohort and most subsets, indicating that the notion of cure was robust. The overall cure fraction was 71.9%. The median survival was 1.1 years in uncured patients. The cure time was 4.5 years, indicating that beyond this time, mortality in ENKTCL patients was statistically equivalent to that in the general population. Cure probability was associated with B symptoms, stage, performance status, lactate dehydrogenase, primary tumor invasion, and primary upper aerodigestive tract site. Elderly patients (>60 years) had a similar cure fraction to that of younger patients. The 5-year overall survival rate correlated well with the cure fraction across risk-stratified groups. Thus, statistical cure is possible in ENKTCL patients receiving current treatment strategies. Overall probability of cure is favorable, though it is affected by the presence of risk factors. These findings have a high potential impact on clinical practice and patients' perspective.

Outcome and risk prediction of early progression in patients with extranodal natural killer/T cell lymphoma from the CLCG study.

Recently, progression-free survival at 24 months (PFS24) was defined as clinically relevant for patients with extranodal NK/T cell lymphoma. Herein, the clinical data from two independent random cohorts (696 patients each in the primary and validation datasets) were used to develop and validate a risk index for PFS24 (PFS24-RI), and evaluate its ability to predict early progression. Patients achieving PFS24 had a 5-year overall survival (OS) of 95.8%, whereas OS was only 21.2% in those failing PFS24 (P<0.001). PFS24 was an important predictor of subsequent OS, independent of risk stratification. The proportion of patients achieving PFS24 and 5-year OS rates correlated linearly among risk-stratified groups. Based on multivariate analysis of the primary dataset, the PFS24-RI included five risk factors: stage II or III/IV, elevated lactate dehydrogenase, Eastern Cooperative Oncology Group score ≥2, primary tumor invasion, and extra-upper aerodigestive tract. PFS24-RI stratified the patients into low-risk (0), intermediate-risk (1-2), high-risk (≥3) groups with different prognoses. Harrell's C-index of PFS24-RI for PFS24 prediction was 0.667 in the validation dataset, indicating a good discriminative ability. PFS24-RI calibration indicated that the actual observed and predicted probability of failing PFS24 agreed well. PFS24-RI provided the probability of achieving PFS24 at an individual patient level.

Prognostic ability of lung immune prognostic index in limited-stage small cell lung cancer.

BACKGROUND: Lung immune prognostic index (LIPI) is a prognostic marker of extensive-stage small cell lung cancer (ES-SCLC) patients received immunotherapy or chemotherapy. However, its ability in limited-stage SCLC (LS-SCLC) should be evaluated extensively. METHODS: We retrospectively enrolled 497 patients diagnosed as LS-SCLC between 2015 and 2018, and clinical data included pretreatment lactate dehydrogenase (LDH), white blood cell count, and absolute neutrophil count levels were collected. According to the LIPI scores, the patients were stratified into low-risk (0 points) and high-risk (1-2 points). The correlations between LIPI and overall survival (OS) or progression-free survival (PFS) were analyzed by the Cox regression. Additionally, the propensity score matching (PSM) and inverse probability of treatment weight (IPTW) methods were used to reduce the selection and confounding bias. A nomogram was constructed using on multivariable Cox model. RESULTS: Two hundred fifty and 247 patients were in the LIPI high-risk group and low-risk group, and their median OS was 14.67 months (95% CI: 12.30-16.85) and 20.53 months (95% CI: 17.67-23.39), respectively. In the statistical analysis, High-risk LIPI was significantly against worse OS (HR = 1.377, 95%CI:1.114-1.702) and poor PFS (HR = 1.338, 95%CI:1.1-1.626), and the result was similar after matching and compensating with the PSM or IPTW method. A novel nomogram based on LIPI has a decent level of predictive power. CONCLUSION: LIPI stratification was a significant factor against OS or PFS of LS-SCLC patients.

Sample-Specific Perturbation of Gene Interactions Identifies Pancreatic Cancer Subtypes.

Pancreatic cancer is a highly fatal disease and an increasing common cause of cancer mortality. Mounting evidence now indicates that molecular heterogeneity in pancreatic cancer significantly impacts its clinical features. However, the dynamic nature of gene expression pattern makes it difficult to rely solely on gene expression alterations to estimate disease status. By contrast, biological networks tend to be more stable over time under different situations. In this study, we used a gene interaction network from a new point of view to explore the subtypes of pancreatic cancer based on individual-specific edge perturbations calculated by relative gene expression value. Our study shows that pancreatic cancer patients from the TCGA database could be separated into four subtypes based on gene interaction perturbations at the individual level. The new network-based subtypes of pancreatic cancer exhibited substantial heterogeneity in many aspects, including prognosis, phenotypic traits, genetic mutations, the abundance of infiltrating immune cell, and predictive therapeutic efficacy (chemosensitivity and immunotherapy efficacy). The new network-based subtypes were closely related to previous reported molecular subtypes of pancreatic cancer. This work helps us to better understand the heterogeneity and mechanisms of pancreatic cancer from a network perspective.

[Construction of a nomogram model for predicting 2-year survival rate of small cell lung cancer based on more comprehensive variables].

Objective: To construct a novel prognostic nomogram model based on more comprehensive variables for patients with small-cell lung cancer (SCLC). Methods: The data of 722 patients with SCLC confirmed by pathology in Affiliated Cancer Hospital of Shanxi Medical University from January 2015 to December 2018 were retrospectively analyzed [including 592 males and 130 females, aged from 23 to 82(61±9) years]. A random seed count of 133 was used to divide those patients into training set (n=422) and validation set (n=300). Kaplan-Meier was used for survival curves analysis and univariate Log-rank test was used for evaluating the influence of clinical variables on the prognosis of sclc, variables with P<0.05 in univariate analysis were included in a multivariate Cox regression model. The nomogram was constructed based on the variables which P<0.05 in multivariate analysis. Receiver operating characteristic (ROC) curve, calibration by Integrated Brier score (IBS) and clinical net benefit by decision curve analysis (DCA) were used to evaluate model discriminative power, prediction error value, and clinical net benefit, and compared with the American Joint Committee on Cancer 8th TNM. Results: Male, abnormal monocyte (MON) counts, abnormal neuron specific enolase (NSE), abnormal cytokeratin 19 fragment (Cyfra211), M1a stage, M1b stage, M1c stage, radiotherapy (RT), chemotherapy ≥4 cycles and prophylactic cranial irradiation (PCI) were prognostic factors for SCLC[HR(95%CI)=1.39(1.00-1.92), 1.29(1.02-1.63), 1.41(1.11-1.80), 2.02(1.48-2.76), 1.09(0.77-1.55), 1.44(0.94-2.22), 2.01(1.49-2.71), 0.75(0.57-0.98), 0.40(0.31-0.51)and 0.42(0.26-0.68), respectively, all P<0.05]. The area under ROC curve (AUC) of the nomogram in training set and validation set were 0.814(95%CI: 0.765-0.862)and 0.787 (95%CI: 0.725-0.849), which were higher than TNM [0.616(95%CI: 0.558-0.674) and 0.648(95%CI: 0.581-0.715)].The calibration curve showed a good correlation between the nomogram prediction and actual observation for the 2-year overall survival (OS). IBS indicted a lower prediction error rate (training set: 0.132 vs 0.169; validation set: 0.138 vs 0.169). DCA showed a wider threshold range than TNM (training set: 0.01-0.96 vs 0.01-0.85, validation set: 0.01-0.94 vs 0.01-0.86) and a greater improvement of the clinical net benefit (in training set the nomogram had a greater clinical benefit than TNM in the range of 0.19-0.96, and remained in validation set in the range of 0.19-0.94). Conclusion: The established nomogram model for predicting 2-year OS in patients with SCLC based on 8 variables, including gender, MON, NSE, Cyfra211, M stage, RT, CT cycles and PCI can be used for an more accurately prognosis prediction and reference for therapeutic regimen selection.

RNA-binding protein RPS3 contributes to hepatocarcinogenesis by post-transcriptionally up-regulating SIRT1.

Although several studies indicate that RNA-binding proteins (RBPs) contribute to key steps in a variety of physiological processes and cancer, the detailed biological functions and mechanisms remain to be determined. By performing bioinformatics analysis using well-established hepatocellular carcinoma (HCC) datasets, we identified a set of HCC progression-associated RBPs (HPARBPs) and found that the global expression of HPARBPs was significantly correlated with patient prognosis. Among the 42 HPARBPs, human ribosomal protein S3 (RPS3) was one of the most abundant genes whose role remains uncharacterized in HCC. Gain- and loss-of-function analyses demonstrated that RPS3 promoted HCC tumorigenesis both in vitro and in vivo. Mechanistically, we revealed that silent information regulator 1 (SIRT1) was a critical target of RPS3 and was essential for sustaining the RPS3-induced malignant phenotypes of HCC cells. RPS3 stabilized SIRT1 mRNA by binding to AUUUA motifs in the 3448-3530 region of the 3' untranslated region (UTR) of SIRT1 mRNA. In addition, we found that (5-formylfuran-2-yl) methyl 4-hydroxy-2-methylenebutanoate (FMHM) inhibited HCC progression by repressing the RPS3/SIRT1 pathway. Our study unveils a novel extra-ribosomal role of RPS3 in facilitating hepatocarcinogenesis via the post-transcriptional regulation of SIRT1 expression and proposes that the RPS3/SIRT1 pathway serves as a potential therapeutic target in HCC.

Risk-based, response-adapted therapy for early-stage extranodal nasal-type NK/T-cell lymphoma in the modern chemotherapy era: A China Lymphoma Collaborative Group study.

We aimed to determine the survival benefits of chemotherapy (CT) added to radiotherapy (RT) in different risk groups of patients with early-stage extranodal nasal-type NK/T-cell lymphoma (ENKTCL), and to investigate the risk of postponing RT based on induction CT responses. A total of 1360 patients who received RT with or without new-regimen CT from 20 institutions were retrospectively reviewed. The patients had received RT alone, RT followed by CT (RT + CT), or CT followed by RT (CT + RT). The patients were stratified into different risk groups using the nomogram-revised risk index (NRI). A comparative study was performed using propensity score-matched (PSM) analysis. Adding new-regimen CT to RT (vs RT alone) significantly improved overall survival (OS, 73.2% vs 60.9%, P < .001) and progression-free survival (PFS, 63.5% vs 54.2%, P < .001) for intermediate-risk/high-risk patients, but not for low-risk patients. For intermediate-risk/high-risk patients, RT + CT and CT + RT resulted in non-significantly different OS (77.7% vs 72.4%; P = .290) and PFS (67.1% vs 63.1%; P = .592). For patients with complete response (CR) after induction CT, initiation of RT within or beyond three cycles of CT resulted in similar OS (78.2% vs 81.7%, P = .915) and PFS (68.2% vs 69.9%, P = .519). For patients without CR, early RT resulted in better PFS (63.4% vs 47.6%, P = .019) than late RT. Risk-based, response-adapted therapy involving early RT combined with CT is a viable, effective strategy for intermediate-risk/high-risk early-stage patients with ENKTCL in the modern treatment era.

High-performance concealment of defective pixel clusters in infrared imagers.

Defective pixel concealment is a necessary procedure in infrared image processing and is widely used. However, current approaches are mainly focused on the concealment of isolated pixels and small defective pixel clusters. Consequently, these approaches cannot meet the requirements when applied to infrared detectors with large defective pixel clusters. In this paper, we present a novel and comprehensive approach to processing the image data acquired from infrared imagers with large and small defective pixel clusters. Our approach consists of preprocessing, coarse concealment, high dynamic range enhancement, and fine concealment by generative adversarial networks. Experiments using mid-wave infrared and long-wave infrared images demonstrated that the proposed approach achieves better results than the best conventional approach, known as transforming image completion, with the peak signal-to-noise ratio and structural similarity metrics improved by 2.7063 dB (16.3%) and 0.1951 dB (34.1%), respectively.

Real-time infrared image detail enhancement based on fast guided image filter and plateau equalization.

Image detail enhancement is critical to the performance of infrared imaging systems because the original images generally suffer from low contrast and a low signal-to-noise ratio. Although conventional decomposition-based methods have advantages in enhancing image details, they also have clear disadvantages, which include intensive computations, over-enhanced noise, and gradient reversal artifacts. In this paper, we propose to accelerate enhancement processing by using a fast guided filter and plateau equalization. Our method consists of image decomposition, base and detail layers processing, and projection of the enhanced image to an 8-bit dynamic range. Experimental results demonstrated that our proposed method achieves a good balance among detail enhancement performance, noise and gradient reversal artifacts suppression, and computational cost, with a frame rate around 30 fps for 640×512 infrared images.

Prognostic role of the systemic immune-inflammation index in brain metastases from lung adenocarcinoma with different EGFR mutations.

The prognostic value of the systemic immune-inflammation index (SII) has been shown in various types of cancers. We aimed to evaluate the predictive values in brain metastases from lung adenocarcinoma with status of EGFR mutations. We, retrospectively, examined 310 patients with brain metastases from lung adenocarcinoma with status of EGFR mutations. SII was calculated using P * N/L, where P, N, and L, respectively refer to peripheral blood lymphocyte, neutrophil, and platelet counts. The cut-off value of SII was assessed by area under the curve (AUC). The log-rank test and Cox proportional hazard model were used to confirm the impact of SII and other variables on survival. The SII value ≤ 1218.81 was associated with prolonged survival in patients with brain metastases from lung adenocarcinoma in both variable and multivariable analysis In patients with EGFR mutations, the SII had statistical effect on OS only in invariable test. While, for patients with wild-type EGFR, SII achieved statistically significant differences both in variable and multivariable analyses. SII is an independent prognostic factor in brain metastases from lung adenocarcinoma. SII may have varying prognostic effects on patients with and without EGFR mutations and is a promising variable for the future prognostic systems.

A Fast Calibration and Compensation Method for Magnetometers in Strap-Down Spinning Projectiles.

Attitude measurement is an essential technology in projectile trajectory correction. Magnetometers have been used for projectile attitude measurement systems as they are small in size, lightweight, and low cost. However, magnetometers are seriously disturbed by the artillery magnetic field during launch. Moreover, the error parameters of the magnetometers, which are calibrated in advance, usually change after extended storage. The changed parameters have negative effects on attitude estimation of the projectile. To improve the accuracy of attitude estimation, the magnetometers should be calibrated again before launch or during flight. This paper presents a fast calibration method specific for a spinning projectile. At the launch site, the tri-axial magnetometer is calibrated, the parameters of magnetometer are quickly obtained by optimal ellipsoid fitting based on a least squares criterion. Then, the calibration parameters are used to compensate for magnetometer outputs during flight. The numerical simulation results show that the proposed calibration method can effectively determine zero bias, scale factors, and alignment angle errors. Finally, a semi-physical experimental system was designed to further verify the performance of the calibration method. The results show that pitch angle error reduces from 3.52° to 0.58° after calibration. The roll angle error is reduced from 2.59° to 0.65°. Simulations and experimental results indicate that the accuracy of magnetometer in strap-down spinning projectile has been greatly enhanced, and the attitude estimation errors are reduced after calibration.

Risk-adapted therapy for early-stage extranodal nasal-type NK/T-cell lymphoma: analysis from a multicenter study.

The optimal combination and sequence of radiotherapy (RT) and chemotherapy (CT) for extranodal nasal-type natural killer/T-cell lymphoma (NKTCL) are not well-defined. The aim of this study was to create a risk-adapted therapeutic strategy for early-stage NKTCL. A total of 1273 early-stage patients from 10 institutions were reviewed. Patients received CT alone (n = 170), RT alone (n = 253), RT followed by CT (n = 209), or CT followed by RT (n = 641). A comprehensive comparative study was performed using multivariable and propensity score-matched analyses. Early-stage NKTCL was classified as low risk or high risk based on 5 independent prognostic factors (stage, age, performance status, lactate dehydrogenase, primary tumor invasion). RT alone and RT with or without CT were more effective than CT alone (5-year overall survival [OS], 69.6% and 67.7% vs 33.9%, P < .001). For low-risk patients, RT alone achieved a favorable OS (88.8%); incorporation of induction or consolidation CT did not provide additional benefit (86.9% and 86.3%). For high-risk patients, RT followed by CT resulted in superior OS (72.2%) compared with induction CT and RT (58.3%, P = .004) or RT alone (59.6%, P = .017). After adjustment, similar significant differences in OS were still observed between treatment groups. New CT regimens provided limited benefit in early-stage NKTCL. Risk-adapted therapy involving RT alone for low-risk patients and RT consolidated by CT for high-risk patients is a viable, effective strategy for early-stage NKTCL.

The overexpression and prognostic role of DCAF13 in hepatocellular carcinoma.

DDB1 and CUL4 associated factor 13 (DCAF13) is a protein coding gene located on chromosome 8q22.3, which is a hotspot amplified in various cancers. DCAF13 has been reported to be frequently amplified in breast cancer patients. However, the genetic alteration and potential role of DCAF13 in other cancers, including hepatocellular carcinoma, have not been investigated yet. In this study, we found that DCAF13 was amplified in 14.7% of the cases and its expression was upregulated (p < 0.001) in hepatocellular carcinoma samples in The Cancer Genome Atlas dataset. Increased expression of DCAF13 was also noticed in 40 paired hepatocellular carcinoma and adjacent non-tumor tissues both at messenger RNA and protein levels (p = 0.0002 and 0.0016, respectively). A positive relationship was observed between augmented DCAF13 levels and poorer tumor grade (p = 0.005), and we also found that hepatocellular carcinoma patients with increased DCAF13 expression in their tumors had significantly poorer survival compared with those with decreased DCAF13 expression (median survival time: 45.73 and 70.53 months, respectively). Multivariate Cox regression analysis showed that DCAF13 was an independent prognostic predictor of survival in hepatocellular carcinoma patients. Gene ontology and Kyoto Encyclopedia of Genes and genomes analysis indicated the potential role of DCAF13 as a crucial cell cycle regulator. Collectively, our findings revealed that the overexpression of DCAF13 in hepatocellular carcinoma was significantly associated with poor survival and may participate in the regulation of cell cycle progression.

Assessment of prognostic scores of brain metastases from lung adenocarcinoma with EGFR mutations.

The aim of this study was to analyze prognostic factors and evaluate the value of four prognostic scores including RPA, DS-GPA BS-BM, GGS for the EGFR mutant BM patients from lung adenocarcinoma treated with EGFR-TKI. Data of NSCLC were retrospectively reviewed from August 2010 to June 2015 using the medical database of Shanxi Provincial Cancer Hospital. Patients with BM from lung adenocarcinoma with mutant EGFR treated by EGFR-TKI or a combination of EGFR-TKI and WBRT were included. Potential prognostic factors were statistically examined. The C-index of each prognostic score was calculated. A total of 1063 BM patients with lung adenocarcinoma that had been identified with EGFR mutations were reviewed. A total of 104 patients that had been diagnosed with BM were confirmed to have mutant EGFR in primary tumors. These patients received treatment with EGFR-TKI or EGFR-TKI with WBRT to BM. The potential predictive factors in multivariable analysis included KPS (70 vs.70-80 vs. 90-100) and number of brain metastatic lesions. In the log-rank test, the indexes of RPA, DS-GPA BS-BM, and GGS were all significant predictors of OS. The C-indexes of each prognostic score were 0.79, 0.76, 0.77, and 0.74 in DS-GPA, RPA, GGS, and BS-BM, respectively. The indexes of RPA, DS-GPA BS-BM, GGS were applicable for asessing survival stratification in brain metastases from lung adenocarcinoma with presented EGFR mutations in our independent population. The DS-GPA appears to be the best predictive value. However, all four of the indexes could not evaluate the exact independent prognostic factors in multivariable analysis. A prognostic index specific for this group of patients was needed for targeted lung cancer therapy.

Over-Expression of Alpha-Enolase as a Prognostic Biomarker in Patients with Pancreatic Cancer.

Background: Alpha-enolase is an important glycolytic enzyme, and its aberrant expression has been associated with multiple tumor progression. However, few studies investigated the expression of alpha-enolase and its clinical significance in pancreatic cancer (PC). Objectives: To evaluate alpha-enolase level in PC tissues by immunohistochemical (IHC) analysis, and investigate the association of alpha-enolase expression with clinicopathologic features. Methods: The alpha-enolase levels in pancreatic cancer tissues were analyzed by using the Oncomine database. The expression of alpha-enolase, Ki67 and p53 in pancreatic cancer and adjacent normal tissues were evaluated by IHC using the corresponding primary antibodies on the commercial tissue arrays. We also examined their association with clinicopathologic parameters, and explored their prognostic value in PC. Results: We identified an elevation of alpha-enolase mRNA level in pancreatic cancer independent datasets from Oncomine. IHC analysis showed that alpha-enolase protein levels were elevated in 47% (n=100) PC tissue samples, but there was weak or no staining in the normal tissues. Statistical analysis revealed that high levels of alpha-enolase were significantly associated with Stage and Lymph node metastasis. Correlation analysis indicated that over-expression of alpha-enolase was positively associated with Ki67 expression and inversely correlated with p53 expression. Furthermore, membranous expression of alpha-enolase was also observed in 29.8% (14/47) total alpha-enolase positive samples, and was significantly associated with Lymph node metastasis. Kaplan-Meier survival analysis demonstrated that high total alpha-enolase expression was significantly associated with unfavorable survival, while membranous alpha-enolase expression was significantly associated with better survival of PC patients. Multivariate Cox analysis demonstrated that total alpha-enolase expression was an independent prognostic factor for PC patients. Conclusions: Our results suggested that alpha-enolase level was significantly elevated in pancreatic cancer tissues, which was closely associated with PC progression. It might be a candidate target for targeted pancreatic cancer treatments.