Combination of preoperative CEA and CA19-9 improves prediction outcomes in patients with resectable pancreatic adenocarcinoma: results from a large follow-up cohort

The EFNA4 gene is a potential prognostic biomarker in pancreatic cancer: a bioinformatics analysis

Background

Pancreatic cancer is a highly aggressive malignancy with poor prognosis, and there is an urgent need to understand its molecular mechanisms for early diagnosis and treatment. Despite surgical resection being the only effective treatment, most patients are diagnosed at an advanced stage, missing the optimal window for therapy. Identifying novel biomarkers is crucial for prognostic assessment, treatment planning, and early intervention. Ephrin A4 (EFNA4), a member of the receptor tyrosine kinase family, is involved in vascular and epithelial development via regulation of cell migration and rejection. However, the role of EFNA4 in pancreatic cancer has not been reported. Therefore, our study aimed to clarify the role of EFNA4 in pancreatic cancer through bioinformatics analysis and vitro experiments.

Methods

The expression of EFNA4 and its potential value as a diagnostic and prognostic biomarker in pancreatic cancer was analyzed using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) database. According to the expression level of EFNA4, patients were divided into high expression group and low expression group, and the correlation between overall survival (OS) and disease-free survival (DFS) with different expression levels of EFNA4 and clinical parameters were analyzed. Subsequently, reverse-transcription quantitative polymerase chain reaction (RT-qPCR) was performed to detect EFNA4 expression. The proliferation, invasion, and cloning ability of the cells were detected via Cell Counting Kit 8 (CCK8), Transwell, and plate cloning assays, respectively.

Results

EFNA4 is highly expressed in pancreatic cancer, and upregulation of EFNA4 is associated with poor prognosis. In this study, EFNA4 expression was correlated with T stage and TNM (tumor-node-metastasis) stage of pancreatic cancer, and the median survival time and progression-free survival (PFS) were worse in those with high EFNA4 expression (394 days) than in those with low expression (525 days) [hazard ratio (HR): 1.47, 95% confidence interval (CI): 1.00-2.16, P=0.047]. In addition, EFNA4 was also found to be involved in the regulation of signal pathways such as cell adhesion, cyclic AMP, insulin secretion, pancreatic secretion, and protein digestion and absorption. In vitro experiments demonstrated that EFNA4 knockdown significantly inhibited the proliferation, cloning ability, and invasiveness of the PANC-1 and SW1990 pancreatic cancer cell lines.

Conclusions

The abnormal expression of EFNA4 in pancreatic cancer is associated with poor prognosis. Knockout of EFNA4 gene could significantly inhibit the proliferation and invasion of pancreatic cancer cells. Therefore, EFNA4 may be one of the molecular targets for poor prognosis of patients with pancreatic cancer.

Identification of fibroblast-related genes based on single-cell and machine learning to predict the prognosis and endocrine metabolism of pancreatic cancer

Background

Single-cell sequencing technology has become an indispensable tool in tumor mechanism and heterogeneity studies. Pancreatic adenocarcinoma (PAAD) lacks early specific symptoms, and comprehensive bioinformatics analysis for PAAD contributes to the developmental mechanisms.

Methods

We performed dimensionality reduction analysis on the single-cell sequencing data GSE165399 of PAAD to obtain the specific cell clusters. We then obtained cell cluster-associated gene modules by weighted co-expression network analysis and identified tumorigenesis-associated cell clusters and gene modules in PAAD by trajectory analysis. Tumor-associated genes of PAAD were intersected with cell cluster marker genes and within the signature module to obtain genes associated with PAAD occurrence to construct a prognostic risk assessment tool by the COX model. The performance of the model was assessed by the Kaplan-Meier (K-M) curve and the receiver operating characteristic (ROC) curve. The score of endocrine pathways was assessed by ssGSEA analysis.

Results

The PAAD single-cell dataset GSE165399 was filtered and downscaled, and finally, 17 cell subgroups were filtered and 17 cell clusters were labeled. WGCNA analysis revealed that the brown module was most associated with tumorigenesis. Among them, the brown module was significantly associated with C11 and C14 cell clusters. C11 and C14 cell clusters belonged to fibroblast and circulating fetal cells, respectively, and trajectory analysis showed low heterogeneity for fibroblast and extremely high heterogeneity for circulating fetal cells. Next, through differential analysis, we found that genes within the C11 cluster were highly associated with tumorigenesis. Finally, we constructed the RiskScore system, and K-M curves and ROC curves revealed that RiskScore possessed objective clinical prognostic potential and demonstrated consistent robustness in multiple datasets. The low-risk group presented a higher endocrine metabolism and lower immune infiltrate state.

Conclusion

We identified prognostic models consisting of APOL1, BHLHE40, CLMP, GNG12, LOX, LY6E, MYL12B, RND3, SOX4, and RiskScore showed promising clinical value. RiskScore possibly carries a credible clinical prognostic potential for PAAD.

Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients

BACKGROUND

Pancreatic cancer (PC) is a malignancy with a poor prognosis and high mortality. Surgical resection is the only "curative" treatment. However, only a minority of patients with PC can obtain surgery. Improving the overall survival (OS) rate of patients with PC is still a major challenge. Molecular biomarkers are a significant approach for diagnostic and predictive use in PCs. Several prediction models have been developed for patients newly diagnosed with PC that is operable or patients with advanced and metastatic PC; however, these models require further validation. Therefore, precise biomarkers are urgently required to increase the efficiency of predicting a disease-free survival (DFS), OS, and sensitivity to immunotherapy in PC patients and to improve the prognosis of PC.

METHODS

In the present study, we first evaluated the highly and selectively expressed targets in PC, using the GeoMxTM Digital Spatial Profiler (DSP) and then, we analyzed the roles of these targets in PCs using TCGA database.

RESULTS

LAMB3, FN1, KRT17, KRT19, and ANXA1 were defined as the top five upregulated targets in PC compared with paracancer. The TCGA database results confirmed the expression pattern of LAMB3, FN1, KRT17, KRT19, and ANXA1 in PCs. Significantly, LAMB3, FN1, KRT19, and ANXA1 but not KRT17 can be considered as biomarkers for survival analysis, univariate and multivariate Cox proportional hazards model, and risk model analysis. Furthermore, in combination, LAMB3, FN1, KRT19, and ANXA1 predict the DFS and, in combination, LAMB3, KRT19, and ANXA1 predict the OS. Immunotherapy is significant for PCs that are inoperable. The immune checkpoint blockade (ICB) analysis indicated that higher expressions of FN1 or ANXA1 are correlated with lower ICB response. In contrast, there are no significant differences in the ICB response between high and low expression of LAMB3 and KRT19.

CONCLUSIONS

In conclusion, LAMB3, FN1, KRT19, and ANXA1 are good predictors of PC prognosis. Furthermore, FN1 and ANXA1 can be predictors of immunotherapy in PCs.

Prognostic Role of Carbohydrate Antigen 19 to 9 in Predicting Survival of Patients With Pancreatic Cancer: A Meta-Analysis

This study evaluates the prognostic role of carbohydrate antigen 19 to 9 (CA19-9) in predicting survival of pancreatic cancer patients. Literature search was conducted in electronic databases (Google Scholar, Ovid, PubMed, and Science Direct) and study selection was based on precise eligibility criteria. Random-effects meta-analyses were performed to achieve overall estimates of median survival and hazard ratios (HRs) of survival with cutoff defined lower and higher CA19-9 levels before and after surgery or chemotherapy (CT)/radiotherapy (RT) and the changes in CA19-9 levels after any treatment. A total of 41 studies (6519 patients; 42% females; age 63.3 years [95% confidence interval [CI]: 62.2, 64.4]) were included. A pooled HR of 1.79 with a narrow 95% CI (1.58, 2.01) showed that higher CA19-9 levels or less decrease in CA19-9 levels after treatment predicted shorter survival. Median survival in patients with lower and higher preoperative CA19-9 levels was 23.2 months [95% CI: 17.2, 29.2] and 14.0 months [95% CI: 10.9, 17.2], respectively, whereas median survival with lower and higher postoperative CA19-9 levels was 25.0 months [95% CI: 21.9, 28.0] and 13.0 months [95% CI: 10.9, 15.0] respectively. Median survival with lower and higher pre-CT/RT CA19-9 levels was 11.9 months [95% CI: 10.2, 13.6] and 7.7 months [95% CI: 6.2, 9.2], respectively, whereas median survival with lower and higher post-CT/RT CA19-9 levels was 15.1 months [95% CI: 13.2, 17.0] and 10.7 months [95% CI: 7.3, 14.0] respectively. A decrease in CA19-9 levels after treatment was also associated with longer survival. Thus, both pretreatment and posttreatment CA19-9 levels or their changes after treatment have good prognostic value in determining the survival of pancreatic cancer patients.

Pancreatic Ductal Adenocarcinoma: The Dawn of the Era of Nuclear Medicine?

Pancreatic ductal adenocarcinoma (PDAC), accounting for 90-95% of all pancreatic tumors, is a highly devastating disease associated with poor prognosis. The lack of accurate diagnostic tests and failure of conventional therapies contribute to this pejorative issue. Over the last decade, the advent of theranostics in nuclear medicine has opened great opportunities for the diagnosis and treatment of several solid tumors. Several radiotracers dedicated to PDAC imaging or internal vectorized radiotherapy have been developed and some of them are currently under clinical consideration. The functional information provided by Positron Emission Tomography (PET) or Single Photon Emission Computed Tomography (SPECT) could indeed provide an additive diagnostic value and thus help in the selection of patients for targeted therapies. Moreover, the therapeutic potential of β-- and α-emitter-radiolabeled agents could also overcome the resistance to conventional therapies. This review summarizes the current knowledge concerning the recent developments in the nuclear medicine field for the management of PDAC patients.

Essential updates 2019/2020: Multimodal treatment of localized pancreatic adenocarcinoma: Current topics and updates in survival outcomes and prognostic factors

Overall survival of patients with localized pancreatic ductal adenocarcinoma (PDAC) is extremely poor. Therefore, the establishment of multimodal treatment strategies is indispensable for PDAC patients because surgical treatment alone could not contribute to the improvement of survival. In this review article, we focus on the current topics and advancement of the treatments for localized PDAC including resectable, borderline resectable, and locally advanced PDAC in accordance with the articles mainly published from 2019 to 2020. Reviewing the articles, the recent progress of multimodal treatments notably improves the prognosis of patients with localized PDAC. For resectable PDAC, neoadjuvant chemo or chemoradiation therapy, rather than upfront surgery, plays a key role, especially in patients with a large tumor, poor performance status, high tumor marker levels, peripancreatic lymph nodes metastasis, or neural invasion suspected on preoperative imaging. For borderline resectable PDAC, neoadjuvant treatments followed by surgery is a desirable approach, and maintenance of immunonutritional status during the treatments are also important. For locally advanced disease, conversion surgery has a central role in improving a survival outcome; however, its indication should be standardized.

Identification of Preoperative Risk Factors for Poor Survival in Patients with Resectable Pancreatic Cancer Treated with Upfront Surgery

INTRODUCTION

The aim of this study was to identify preoperative risk factors for poor survival in patients with resectable pancreatic ductal adenocarcinoma (PDAC) treated with upfront surgery.

METHODS

Medical records of 268 patients with resectable PDAC defined by resectability status who underwent upfront surgery were reviewed retrospectively. Multivariate analyses were performed to identify preoperative risk factors for recurrence-free survival (RFS) and overall survival (OS). Moreover, a binary logistic regression model was built to determine preoperative independent risk factors of 2- and 3-year recurrence and survival.

RESULTS

Multivariate analyses identified CA19-9 (≥100 U/mL, p < 0.001) as an independent risk factor for poor RFS, and worse performance status (1 or 2, p = 0.03), platelet:lymphocyte ratio (<150, p = 0.04), and preoperative CA19-9 (≥100 U/mL, p < 0.001) as independent risk factors for poor OS. Moreover, preoperative CA19-9 (≥100 U/mL) was the only independent risk factor identified for 2- and 3-year recurrence and survival.

DISCUSSION/CONCLUSION

Preoperative CA19-9 (≥100 U/mL) was the most reliable preoperative predictive factor for poor survival in resectable PDAC treated with upfront surgery. These findings warrant further clinical trials investigating efficacy of neoadjuvant therapy targeting the subset of patients with resectable PDAC who have elevated preoperative CA19-9, namely, those with high risk of poor prognosis.

Prognostic Value of the Preoperative Tumor Marker Index in Resected Pancreatic Ductal Adenocarcinoma: A Retrospective Single-Institution Study

BACKGROUND

The prediction of prognostic outcomes can provide the most suitable strategy for patients with pancreatic ductal adenocarcinoma (PDAC). This study aimed to evaluate the clinical value of the preoperative tumor marker index (pre-TI) in predicting prognostic outcomes after resection for PDAC.

METHODS

For 183 patients who underwent pancreatic resection of PDAC, adjusted carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), pancreatic cancer-associated antigen-2 (DUpan-2), and s-pancreas-1 antigen (SPan-1) were retrospectively evaluated, and the positive number of these markers was scored as the pre-TI.

RESULTS

A high pre-TI (≥ 2) was significantly associated with a larger tumor and lymph node metastases, and the patients with a high pre-TI had worse prognostic outcomes in terms of both relapse-free survival (RFS) (P < 0.0001, log-rank) and overall survival (OS) (P < 0.0001, Λlog-rank) than the patients with a low pre-TI. The pre-TI was one of the independent factors of a poor prognosis for RFS (hazard ratio [HR], 2.36; P < 0.0001) and OS (HR, 2.27; P < 0.0001). In addition, even for the patients with normal adjusted CA19-9 values (n = 74, 40.4%), those with the high pre-TI had a significantly poorer prognosis than those with a low pre-TI (RFS: P = 0.002, log-rank; OS: P = 0.031, log-rank).

CONCLUSIONS

The pre-TI could be a potent predictive marker of prognostic outcomes for patients with resections for PDAC. Patients with a high pre-TI may need additional strategies to improve their prognosis.

Prognostic Nutritional Index After Chemoradiotherapy Was the Strongest Prognostic Predictor Among Biological and Conditional Factors in Localized Pancreatic Ductal Adenocarcinoma Patients

Background: In many malignancies, including pancreatic ductal adenocarcinoma (PDAC), host-related inflammatory/immunonutritional markers, such as the prognostic nutritional index (PNI), modified Glasgow prognostic score (mGPS), and C-reactive protein (CRP)/albumin ratio are reported to be prognostic factors. However, the prognostic influence of these factors before and after chemoradiotherapy (CRT) has not been studied in PDAC patients. Methods: Of 261 consecutive PDAC patients who were scheduled for CRT with gemcitabine or S1 plus gemcitabine between February 2005 and December 2015, participants in this study were 176 who completed CRT and had full data available on inflammatory/immunonutritional markers as well as on anatomical and biological factors for the investigation of prognostic/predictive factors. Results: In multivariate analysis, the significant prognostic factors were RECIST classification, cT category, performance status, post-CRT carcinoembryonic antigen, post-CRT C-reactive protein/albumin ratio, post-CRT mGPS, and post-CRT PNI. Post-CRT PNI (cut-off value, 39) was the strongest host-related prognostic factor according to the p-value. In the patients who underwent resection after CRT, median survival time (MST) was significantly shorter in the 12 patients with low PNI (<39) than in the 97 with high PNI (≥39), at 15.5 months versus 27.2 months, respectively (p = 0.0016). In the patients who did not undergo resection, MST was only 8.9 months in those with low PNI and 12.3 months in those with high PNI (p < 0.0001), and thus was similar to that of the resected patients with low PNI. Conclusions: Post-CRT PNI was the strongest prognostic/predictive indicator among the independent biological and conditional prognostic factors in PDAC patients who underwent CRT.

Prognostic Value of CT Radiomic Features in Resectable Pancreatic Ductal Adenocarcinoma

In this work, we assess the reproducibility and prognostic value of CT-derived radiomic features for resectable pancreatic ductal adenocarcinoma (PDAC). Two radiologists contoured tumour regions on pre-operative CT of two cohorts from two institutions undergoing curative-intent surgical resection for PDAC. The first (n = 30) and second cohorts (n = 68) were used for training and validation of proposed prognostic model for overall survival (OS), respectively. Radiomic features were extracted using PyRadiomics library and those with weak inter-reader reproducibility were excluded. Through Cox regression models, significant features were identified in the training cohort and retested in the validation cohort. Significant features were then fused via Cox regression to build a single radiomic signature in the training cohort, which was validated across readers in the validation cohort. Two radiomic features derived from Sum Entropy and Cluster Tendency features were both robust to inter-reader reproducibility and prognostic of OS across cohorts and readers. The radiomic signature showed prognostic value for OS in the validation cohort with hazard ratios of 1.56 (P = 0.005) and 1.35 (P = 0.022), for the first and second reader, respectively. CT-based radiomic features were shown to be prognostic in patients with resectable PDAC. These features may help stratify patients for neoadjuvant or alternative therapies.

Enrichment of short mutant cell-free DNA fragments enhanced detection of pancreatic cancer

Background

Analysis of cell-free DNA (cfDNA) is promising for broad applications in clinical settings, but with significant bias towards late-stage cancers. Although recent studies have discussed the diverse and degraded nature of cfDNA molecules, little is known about its impact on the practice of cfDNA analysis.

Methods

We developed single-strand library preparation and hybrid-capture-based cfDNA sequencing (SLHC-seq) to analysis degraded cfDNA fragments. Next we used SLHC-seq to perform cfDNA profiling in 112 pancreatic cancer patients, and the results were compared with 13 previous reports. Extensive analysis was performed in terms of cfDNA fragments to explore the reasons for higher detection rate of KRAS mutations in the circulation of pancreatic cancers.

Findings

By applying the new approach, we achieved higher efficiency in analysis of mutations than previously reported using other detection assays. 791 cancer-specific mutations were detected in plasma of 88% patients with KRAS hotspots detected in 70% of all patients. Only 8 mutations were detected in 28 healthy controls without any known oncogenic or truncating alleles. cfDNA profiling by SLHC-seq was largely consistent with results of tissue-based sequencing. SLHC-seq rescued short or damaged cfDNA fragments along to increase the sensitivity and accuracy of circulating-tumour DNA detection.

Interpretation

We found that the small mutant fragments are prevalent in early-stage patients, which provides strong evidence for fragment size-based detection of pancreatic cancer. The new pipeline enhanced our understanding of cfDNA biology and provide new insights for liquid biopsy.

Selecting chemotherapy for pancreatic cancer: Far away or so close?

Pancreatic cancer is a lethal disease with a very poor prognosis. In contrast to treatments for many other tumor types, cytotoxic agents are still the first-line drugs for pancreatic cancer in both the palliative and adjuvant settings. Some progress has been made in recent years, but most large phase 3 studies have not shown significant improvements in survival. Because the available drugs and regimens are limited in both type and effect, the selection of chemotherapy based on clinicopathologic characteristics may be consequential for pancreatic cancer. In the present report, we focused on 7 landmark clinical trials for pancreatic cancer. We observed that FOLFIRINOX (oxaliplatin, irinotecan, fluorouracil, and leucovorin) and NG (nab-paclitaxel and gemcitabine), 2 first-line regimens, exerted opposite effects on metastatic pancreatic cancer patients with different baseline carbohydrate antigen 19-9 (CA19-9) levels. This suggested that not only the performance status but possibly also CA19-9 levels should be considered when making a therapeutic choice for patients with advanced pancreatic cancer. Moreover, we found that patients with a diagnosis of pancreatic cancer who have undergone a surgical resection with a negative margin (R0) may benefit more from fluorouracil and/or oral prodrugs of fluorouracil-based adjuvant therapy than from gemcitabine. Conversely, gemcitabine or gemcitabine-based regimens may be more effective for patients with a positive resection margin (R1). Based on these findings, we propose flowcharts for selecting chemotherapy for both advanced and resected pancreatic cancer. Furthermore, we present possible mechanisms and interpretations underlying the selection of chemotherapy for pancreatic cancer and propose the tumor burden as a key variable in this process. Regardless of the possible bias and exact treatment selection process, this study offers an opportunity to improve patient outcomes by using agents currently used in the therapy of pancreatic cancer. Although these conclusions are based on indirect evidence, we provide insights and possibilities to drive the selection of chemotherapy for pancreatic cancer.

Translational molecular imaging in exocrine pancreatic cancer

Effective treatment for pancreatic cancer remains challenging, particularly the treatment of pancreatic ductal adenocarcinoma (PDAC), which makes up more than 95% of all pancreatic cancers. Late diagnosis and failure of chemotherapy and radiotherapy are all too common, and many patients die soon after diagnosis. Here, we make the case for the increased use of molecular imaging in PDAC preclinical research and in patient management.

Serum Marker Score Based on Prognostic Nutrition Index, Carcinoembryonic Antigen, and Carbohydrate Antigen 19-9 Is Associated With Recurrence for Patients Undergoing Surgery for Pancreatic Ductal Adenocarcinoma

OBJECTIVES

The prognostic value of the prognostic nutrition index (PNI) in pancreatic ductal adenocarcinoma (PDAC) is still controversial. This study aimed to assess the correlation between PNI and the outcome for PDAC patients and to generate a new score from PNI and serum markers.

METHODS

This study investigated 151 patients who underwent pancreatic resection for PDAC between April 2002 and June 2012. Disease-free survival (DFS), overall survival, and clinicopathological parameters were analyzed according to the PNI value.

RESULTS

The low PNI patients had poorer 5-year DFS rate than high-PNI patients (10.7% and 34.8%, respectively). Multivariate analyses revealed that independent risk factors for poor DFS were high carcinoembryonic antigen (hazard ratio [HR], 1.53; P = 0.038), high carbohydrate antigen 19-9 (HR, 1.67; P = 0.017), positive lymph node metastasis (HR, 1.98; P = 0.017), R1 or 2 resection (HR, 3.50; P < 0.001), and low PNI (HR, 0.37 [high/low]; P = 0.029]. Scoring based on the formula -0.49 × (PNI) + 0.41 × (carcinoembryonic antigen) + 0.67 × (carbohydrate antigen 19-9) was significantly associated with poor DFS (P < 0.001) and overall survival (P = 0.0019).

CONCLUSIONS

Low PNI and serum marker score are significantly associated with poor DFS.

Identification of Prognostic Biomarkers by Combined mRNA and miRNA Expression Microarray Analysis in Pancreatic Cancer

Pancreatic cancer is the fourth leading cause for cancer-related death, and early diagnosis is one key to improve the survival rate of this disease. Molecular biomarkers are an important method for diagnostic use in pancreatic cancer. We used data from three mRNA microarray datasets and a microRNA dataset (GSE16515, GSE15471, GSE28735, and GSE41372) to identify potential key genes. Differentially expressed genes (DEGs) and microRNAs (DEMs) were identified. Functional, pathway enrichment, and protein-protein interaction analyses were performed on common DEGs across all datasets. The target genes of the DEMs were identified. DEMs targets that were also DEGs were further scrutinized using overall survival analysis. A total of 236 DEGs and 21 DEMs were identified. There were a total of four DEGs (ECT2, NR5A2, NRP2, and TGFBI), which were also predicted target genes of DEMs. Overall survival analysis showed that high expression levels of three of these genes (ECT2, NRP2, and TGFBI) were associated with poor overall survival for pancreatic cancer patients. The basic expression of DEGs in pancreas stood lower level in various organ tissues. The expression of ECT2 and NRP2 was higher in different pancreatic cancer cell lines than normal pancreas cell line. Knockout of ECT2 by Crispr Cas9 gene editing system decreased proliferation and migration ability in pancreatic cancer cell line MiaPaCa2. In conclusion, we think that data mining method can do well in biomarker screening, and ECT2 and NRP2 can play as potential biomarker or therapy target by Crispr Cas9 in pancreatic cancer.

Lactic dehydrogenase to albumin ratio in prediction of unresectable pancreatic cancer with intervention chemotherapy

AIM

To validate the prognostic value of lactic dehydrogenase to albumin ratio (LAR) in patients with unresectable pancreatic cancer treated by intervention chemotherapy.

MATERIALS & METHODS

There were 139 patients retrospectively analyzed in this study. The survival was depicted with Kaplan-Meier curves and calculated by log-rank test. We used Cox proportional hazards regression model with univariate and multivariate analyses, and integrated all independent risk factors to establish the nomogram.

RESULTS

Patient with higher LAR group had poorer overall survival (OS). The Tumor, Node, Metastasis stage, carcinoembryonic antigen and LAR have been shown to be independent prognostic indicators for OS. The nomogram indicated superior predictive accuracy for OS.

CONCLUSION

The preoperative LAR can be a prognostic indicator for unresectable pancreatic cancer patients with interventional therapy.

Modeling the relationship between baseline lactate dehydrogenase and prognosis in patients with extensive-disease small cell lung cancer: a retrospective cohort study

Background

Elevated pretreatment lactate dehydrogenase (LDH) has been reported to be associated with poor survival in small cell lung cancer (SCLC). The present study aimed to investigate the continuous relationship between baseline LDH level and survival in patients with extensive-disease SCLC (ED-SCLC).

Methods

Data were retrospectively collected from Shanghai Health Information Network. Patients primarily diagnosed as ED-SCLC from April 2011 to August 2014 were eligible for our study. Patients' survival status was checked in March 2016. A multivariate Cox proportional hazard model was used to detect the association between baseline serum LDH and overall survival. The corresponding continuous relationship was analyzed by using natural spline functions in the Cox model.

Results

A total of 132 eligible ED-SCLC patients were analyzed. Elevated LDH at baseline was associated with poor survival (HR =1.92; 95% CI, 1.29-2.86). An increment of LDH would still raise the risk of death even in abnormal range. Among patients with elevated LDH, those who had relatively higher LDH levels (>370 U/L) would have a poorer prognosis than those with moderately elevated LDH levels (245-370 U/L; median survival time, 114 vs. 274 days; P value of log rank test, 0.007).

Conclusions

LDH is a significant prognostic biomarker for ED-SCLC patients. The interpretation of continuous relationship between LDH and patients' survival can provide more accurate information for clinical practice.

The role of miRNAs in the diagnosis, chemoresistance, and prognosis of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains a very challenging malignancy with late presentation, metastatic potential, chemoresistance, and poor prognosis. Therefore, there is an urgent need for novel diagnostic and prognostic biomarkers. miRNAs are small noncoding RNAs that regulate the expression of multitude number of genes. Aberrant expression of miRNAs has been linked to the development of various malignancies, including PDAC. A series of miRNAs have been defined as holding promise for early diagnostics, as indicators of therapy resistance, and even as markers for prognosis in PDAC patients. In this review, we summarize the current knowledge on the role of miRNAs in diagnosis, chemoresistance, and prognosis in PDAC patients.