A Pilot Study Evaluating Serum MMP7 as a Preoperative Prognostic Marker for Pancreatic Ductal Adenocarcinoma Patients

New nomogram for predicting lymph node positivity in pancreatic head cancer

Background

Pancreatic cancer is one of the most malignant cancers worldwide, and it mostly occurs in the head of the pancreas. Existing laparoscopic pancreaticoduodenectomy (LPD) surgical techniques have has undergone a learning curve, a wide variety of approaches for the treatment of pancreatic cancer have been proposed, and the operation has matured. At present, pancreatic head cancer has been gradually changing from "surgeons' evaluation of anatomical resection" to "biologically inappropriate resection". In this study, the risk of lymph node metastasis in pancreatic head cancer was predicted using common preoperative clinical indicators.

Methods

The preoperative clinical data of 191 patients with pancreatic head cancer who received LPD in the First Affiliated Hospital of Jilin University from May 2016 to December 2021 were obtained. A univariate regression analysis study was conducted, and the indicators with a significance level of P<0.05 were included in the univariate logistic regression analysis into multivariate. Lastly, a nomogram was built based on age, tumor size, leucocyte,albumin(ALB), and lymphocytes/monocytes(LMR). The model with the highest resolution was selected by obtaining the area under a curve. The clinical net benefit of the prediction model was examined using decision curve analyses.Risk stratification was performed by combining preoperative CT scan with existing models.

Results

Multivariate logistic regression analysis found age, tumor size, WBC, ALB, and LMR as five independent factors. A nomogram model was constructed based on the above indicators. The model was calibrated by validating the calibration curve within 1000 bootstrap resamples. The ROC curve achieved an AUC of 0.745(confidence interval of 95%: 0.673-0.816), thus indicating that the model had excellent discriminative skills. DCA suggested that the predictive model achieved a high net benefit in the nearly entire threshold probability range.

Conclusions

This study has been the first to investigate a nomogram for preoperative prediction of lymphatic metastasis in pancreatic head cancer. The result suggests that age, ALB, tumor size, WBC, and LMR are independent risk factors for lymph node metastasis in pancreatic head cancer. This study may provide a novel perspective for the selection of appropriate continuous treatment regimens, the increase of the survival rate of patients with pancreatic head cancer, and the selection of appropriate neoadjuvant therapy patients.

A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we used the Immuno-oncology panel and the Target 96 Oncology III panel to simultaneously detect the levels of 92 cancer-related proteins in serum, using a proximity extension assay. By applying this methodology, we identified 20 proteins, associated with the outcome at binary logistic regression, with a p-value below 0.01 for the first panel and 24 proteins with a p-value below 0.02 for the second one. The final multivariate logistic regression model, combining proteins from the two panels, generated a model with a sensitivity of 97.67% and a specificity of 83.72%. These results support the use of the proposed algorithm after a validation phase.

Preoperative Prediction of Lymph Node Metastasis of Pancreatic Ductal Adenocarcinoma Based on a Radiomics Nomogram of Dual-Parametric MRI Imaging

Purpose

This study aims to uncover and validate an MRI-based radiomics nomogram for detecting lymph node metastasis (LNM) in pancreatic ductal adenocarcinoma (PDAC) patients prior to surgery.

Materials and Methods

We retrospectively collected 141 patients with pathologically confirmed PDAC who underwent preoperative T2-weighted imaging (T2WI) and portal venous phase (PVP) contrast-enhanced T1-weighted imaging (T1WI) scans between January 2017 and December 2021. The patients were randomly divided into training (n = 98) and validation (n = 43) cohorts at a ratio of 7:3. For each sequence, 1037 radiomics features were extracted and analyzed. After applying the gradient-boosting decision tree (GBDT), the key MRI radiomics features were selected. Three radiomics scores (rad-score 1 for PVP, rad-score 2 for T2WI, and rad-score 3 for T2WI combined with PVP) were calculated. Rad-score 3 and clinical independent risk factors were combined to construct a nomogram for the prediction of LNM of PDAC by multivariable logistic regression analysis. The predictive performances of the rad-scores and the nomogram were assessed by the area under the operating characteristic curve (AUC), and the clinical utility of the radiomics nomogram was assessed by decision curve analysis (DCA).

Results

Six radiomics features of T2WI, eight radiomics features of PVP and ten radiomics features of T2WI combined with PVP were found to be associated with LNM. Multivariate logistic regression analysis showed that rad-score 3 and MRI-reported LN status were independent predictors. In the training and validation cohorts, the AUCs of rad-score 1, rad-score 2 and rad-score 3 were 0.769 and 0.751, 0.807 and 0.784, and 0.834 and 0.807, respectively. The predictive value of rad-score 3 was similar to that of rad-score 1 and rad-score 2 in both the training and validation cohorts (P &gt; 0.05). The radiomics nomogram constructed by rad-score 3 and MRI-reported LN status showed encouraging clinical benefit, with an AUC of 0.845 for the training cohort and 0.816 for the validation cohort.

Conclusions

The radiomics nomogram derived from the rad-score based on MRI features and MRI-reported lymph status showed outstanding performance for the preoperative prediction of LNM of PDAC.

Association of Matrix Metalloproteinase 7 Expression With Pathologic Response After Neoadjuvant Treatment in Patients With Resected Pancreatic Ductal Adenocarcinoma

Importance

The use of neoadjuvant therapy (NAT) in resectable pancreatic ductal adenocarcinoma (PDAC) remains controversial. A favorable pathologic response (complete or marked tumor regression) to NAT is associated with better outcomes in patients with resected PDAC. The role of NAT for early systemic control compared with immediate surgical resection for PDAC is under investigation. In the era of precision medicine, biomarkers for patient selection and prediction of therapy response are crucial.

Objective

To evaluate the use of assessment for protein expression on fine-needle aspiration (FNA) biopsy specimens in predicting pathologic response to NAT in treatment-naive patients.

Design, Setting, and Participants

This was a single-institution prognostic study from a high-volume center for pancreatic cancer. All specimens were obtained between January 1, 2009, and December 31, 2018, with a median (SE) follow-up of 20.2 (1.4) months. Analysis of the data was performed from October 1, 2019, to April 30, 2021. Targeted RNA sequencing of frozen FNA biopsy specimens from a discovery cohort of 23 patients was performed to identify genes with aberrant expression that was associated with patients' pathologic response to NAT. Immunohistochemical staining was performed on an additional 80 FNA biopsy specimens to assess expression of matrix metalloproteinase 7 (MMP-7) and its association with pathologic response. Receiver operating characteristic curves for prediction of favorable pathologic response were determined.

Results

In the discovery cohort (12 [52.1%] male; 3 [13.0%] Black and 20 [86.9%] White), RNA sequencing showed that lower MMP-7 expression was associated with favorable pathologic response (College of American Pathologists system scores of 0 [complete response] and 1 [marked response]). In the validation cohort (40 [50.0%] female; 9 [11.3%] Black and 71 [88.7%] White), patients with negative MMP-7 expression were significantly more likely to have a favorable pathologic response (odds ratio, 21.25; 95% CI, 6.19-72.95; P = .001). Receiver operating characteristic curves for prediction of favorable pathologic response from multivariable Cox proportional hazards regression modeling showed that MMP-7 expression increased the area under the curve from 0.726 to 0.906 (P < .001) even after stratifying by resectability status. The positive predictive value and negative predictive value of MMP-7 protein expression on FNA biopsy specimens in predicting unfavorable pathologic response (scores of 2 [partial response] or 3 [poor or no response]) were 88.2% and 73.9%, respectively.

Conclusions and Relevance

Assessment of MMP-7 expression on FNA biopsy specimens at the time of diagnosis may help identify patients who would benefit the most from NAT.

MMP-7 marks severe pancreatic cancer and alters tumor cell signaling by proteolytic release of ectodomains

Pancreatic cancer incurs the worst survival rate of the major cancers. High levels of the protease matrix metalloproteinase-7 (MMP-7) in circulation correlate with poor prognosis and limited survival of patients. MMP-7 is required for a key path of pancreatic tumorigenesis in mice and is present throughout tumor progression. Enhancements to chemotherapies are needed for increasing the number of pancreatic tumors that can be removed and for preventing relapses after surgery. With these ends in mind, selective inhibition of MMP-7 may be worth investigation. An anti-MMP-7 monoclonal antibody was recently shown to increase the susceptibility of several pancreatic cancer cell lines to chemotherapeutics, increase their apoptosis, and decrease their migration. MMP-7 activities are most apparent at the surfaces of innate immune, epithelial, and tumor cells. Proteolytic shedding of multiple protein ectodomains by MMP-7 from such cell surfaces influence apoptosis, proliferation, migration, and invasion. These activities warrant targeting of MMP-7 selectively in pancreatic cancer and other tumors of mucosal epithelia. Competitive and non-competitive modes of MMP-7 inhibition are discussed.

Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma

PURPOSE

Diagnosis of lymph node metastasis (LNM) is critical for patients with pancreatic ductal adenocarcinoma (PDAC). We aimed to build deep learning radiomics (DLR) models of dual-energy computed tomography (DECT) to classify LNM status of PDAC and to stratify the overall survival before treatment.

METHODS

From August 2016 to October 2020, 148 PDAC patients underwent regional lymph node dissection and scanned preoperatively DECT were enrolled. The virtual monoenergetic image at 40 keV was reconstructed from 100 and 150 keV of DECT. By setting January 1, 2021, as the cut-off date, 113 patients were assigned into the primary set, and 35 were in the test set. DLR models using VMI 40 keV, 100 keV, 150 keV, and 100 + 150 keV images were developed and compared. The best model was integrated with key clinical features selected by multivariate Cox regression analysis to achieve the most accurate prediction.

RESULTS

DLR based on 100 + 150 keV DECT yields the best performance in predicting LNM status with the AUC of 0.87 (95% confidence interval [CI]: 0.85-0.89) in the test cohort. After integrating key clinical features (CT-reported T stage, LN status, glutamyl transpeptadase, and glucose), the AUC was improved to 0.92 (95% CI: 0.91-0.94). Patients at high risk of LNM portended significantly worse overall survival than those at low risk after surgery (P = 0.012).

CONCLUSIONS

The DLR model showed outstanding performance for predicting LNM in PADC and hold promise of improving clinical decision-making.

Conformation-Specific Inhibitory Anti-MMP-7 Monoclonal Antibody Sensitizes Pancreatic Ductal Adenocarcinoma Cells to Chemotherapeutic Cell Kill

Matrix metalloproteases (MMPs) undergo post-translational modifications including pro-domain shedding. The activated forms of these enzymes are effective drug targets, but generating potent biological inhibitors against them remains challenging. We report the generation of anti-MMP-7 inhibitory monoclonal antibody (GSM-192), using an alternating immunization strategy with an active site mimicry antigen and the activated enzyme. Our protocol yielded highly selective anti-MMP-7 monoclonal antibody, which specifically inhibits MMP-7's enzyme activity with high affinity (IC₅₀ = 132 ± 10 nM). The atomic model of the MMP-7-GSM-192 Fab complex exhibited antibody binding to unique epitopes at the rim of the enzyme active site, sterically preventing entry of substrates into the catalytic cleft. In human PDAC biopsies, tissue staining with GSM-192 showed characteristic spatial distribution of activated MMP-7. Treatment with GSM-192 in vitro induced apoptosis via stabilization of cell surface Fas ligand and retarded cell migration. Co-treatment with GSM-192 and chemotherapeutics, gemcitabine and oxaliplatin elicited a synergistic effect. Our data illustrate the advantage of precisely targeting catalytic MMP-7 mediated disease specific activity.

Roles of matrix metalloproteinase-7 (MMP-7) in cancer

Matrix metalloproteinase-7 (MMP-7) is a small proteolytic enzyme that secretes zinc and calcium endopeptidases. It can degrade a variety of extracellular matrix substrates and other substrates and plays important regulatory roles in many human pathophysiological processes. Since its discovery, MMP-7 has been recognized as a regulatory protein in wound healing, bone growth, and remodeling. Later, MMP-7 was reported to regulate the occurrence and development of cancers and mediate the proliferation, differentiation, metastasis, and invasion of several types of cancer cells via various mechanisms. Thus, matrix metalloproteinase-7 may be a promising tumor biomarker and therapeutic target. The expression of MMP-7 correlates with the clinical characteristics of cancer patients, and its expression profile is a new diagnostic and prognostic biomarker for a variety of human diseases. Hence, manipulating the expression or function of MMP-7 may be a potential treatment strategy for different diseases including cancers. This review summarizes the role played by MMP-7 in carcinogenesis of several human cancers, underlying mechanisms, and its clinical significance of the occurrence and development of cancers.

A MicroRNA Signature Identifies Pancreatic Ductal Adenocarcinoma Patients at Risk for Lymph Node Metastases

BACKGROUND & AIMS

Pancreatic ductal adenocarcinomas (PDACs) frequently metastasize to the lymph nodes; strategies are needed to identify patients at highest risk for lymph node metastases. We performed genome-wide expression profile analyses of PDAC specimens, collected during surgery or endoscopic ultrasound-guided fine-need aspiration (EUS-FNA), to identify a microRNA (miRNA) signature associated with metastasis to lymph nodes.

METHODS

For biomarker discovery, we analyzed miRNA expression profiles of primary pancreatic tumors from 3 public data sets (The Cancer Genome Atlas, GSE24279, and GSE32688). We then analyzed 157 PDAC specimens (83 from patients with lymph node metastases and 74 without) from Japan, collected from 2001 through 2017, for the training cohort and 107 PDAC specimens (63 from patients with lymph node metastases and 44 without) from a different medical center in Japan, from 2002 through 2016, for the validation cohort. We also analyzed samples collected by EUS-FNA before surgery from 47 patients (22 patients with lymph node metastases and 25 without; 17 for the training cohort and 30 from the validation cohort) and 62 specimens before any treatment from patients who received neoadjuvant chemotherapy (9 patients with lymph node metastasis and 53 without) for additional validation. Multivariate logistic regression analyses were used to evaluate the statistical differences in miRNA expression between patients with vs without metastases.

RESULTS

We identified an miRNA expression pattern associated with diagnosis of PDAC metastasis to lymph nodes. Using logistic regression analysis, we optimized and trained a 6-miRNA risk prediction model for the training cohort; this model discriminated patients with vs without lymph node metastases with an area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.77-0.89). In the validation cohort, the model identified patients with vs without lymph node metastases with an AUC of 0.73 (95% CI, 0.64-0.81). In EUS-FNA biopsy samples, the model identified patients with vs without lymph node metastases with an AUC of 0.78 (95% CI, 0.63-0.89). The miRNA expression pattern was an independent predictor of PDAC metastasis to lymph nodes in the validation cohort (odds ratio, 17.05; 95% CI, 2.43-119.57) and in the EUS-FNA cohort (95% CI, 0.65-0.87).

CONCLUSIONS

Using data and tumor samples from 3 independent cohorts, we identified an miRNA signature that identifies patients at risk for PDAC metastasis to lymph nodes. The signature has similar levels of accuracy in the analysis of resected tumor specimens and EUS-FNA biopsy specimens. This model might be used to select treatment and management strategies for patients with PDAC.

Matrix Metalloproteases in Pancreatic Ductal Adenocarcinoma: Key Drivers of Disease Progression?

Pancreatic cancer is a dismal disorder that is histologically characterized by a dense fibrotic stroma around the tumor cells. As the extracellular matrix comprises the bulk of the stroma, matrix degrading proteases may play an important role in pancreatic cancer. It has been suggested that matrix metalloproteases are key drivers of both tumor growth and metastasis during pancreatic cancer progression. Based upon this notion, changes in matrix metalloprotease expression levels are often considered surrogate markers for pancreatic cancer progression and/or treatment response. Indeed, reduced matrix metalloprotease levels upon treatment (either pharmacological or due to genetic ablation) are considered as proof of the anti-tumorigenic potential of the mediator under study. In the current review, we aim to establish whether matrix metalloproteases indeed drive pancreatic cancer progression and whether decreased matrix metalloprotease levels in experimental settings are therefore indicative of treatment response. After a systematic review of the studies focusing on matrix metalloproteases in pancreatic cancer, we conclude that the available literature is not as convincing as expected and that, although individual matrix metalloproteases may contribute to pancreatic cancer growth and metastasis, this does not support the generalized notion that matrix metalloproteases drive pancreatic ductal adenocarcinoma progression.

Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: a pilot study

BACKGROUND

We developed a computational model integrating clinical data and imaging features extracted from contrast-enhanced computed tomography (CECT) images, to predict lymph node (LN) metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

This retrospective study included 159 patients with PDAC (118 in the primary cohort and 41 in the validation cohort) who underwent preoperative contrast-enhanced computed tomography examination between 2012 and 2015. All patients underwent surgery and lymph node status was determined. A total of 2041 radiomics features were extracted from venous phase images in the primary cohort, and optimal features were extracted to construct a radiomics signature. A combined prediction model was built by incorporating the radiomics signature and clinical characteristics selected by using multivariable logistic regression. Clinical prediction models were generated and used to evaluate both cohorts.

RESULTS

Fifteen features were selected for constructing the radiomics signature based on the primary cohort. The combined prediction model for identifying preoperative lymph node metastasis reached a better discrimination power than the clinical prediction model, with an area under the curve of 0.944 vs. 0.666 in the primary cohort, and 0.912 vs. 0.713 in the validation cohort.

CONCLUSIONS

This pilot study demonstrated that a noninvasive radiomics signature extracted from contrast-enhanced computed tomography imaging can be conveniently used for preoperative prediction of lymph node metastasis in patients with PDAC.

Novel potential biomarkers for pancreatic cancer - A systematic review

BACKGROUND

It is estimated that in developed countries the incidence rate of pancreatic cancer (PC) will continue to rise and by 2020 will be the second most fatal cancer. The mortality of PC patients closely parallels the incidence rate, as this malignancy remains asymptomatic until it reaches an advanced stage of disease. Thus, novel biochemical markers that improve the management of PC patients are necessary. The aim of the work that follows is to investigate whether selected inflammatory mediators might be used in the diagnosis of PC, with the aim of improving the prognosis for PC patients.

METHODS

We performed a thorough search for literature pertaining to our investigation via the MEDLINE/PubMed database.

RESULTS

It has been proved that certain inflammatory mediators might be involved in tumor progression, such as growth, proliferation, migration and angiogenesis of tumor cells. In the present review, we summarized and referred to a number of original papers concerning the clinical significance of selected cytokines and specific inflammatory proteins such as C-reactive protein, as well as of various matrix metalloproteinases and their tissue inhibitors, as potential biomarkers for PC in comparison to well-established tumor markers for this malignancy.

CONCLUSION

Presented proteins might be potential biomarkers in the diagnosis and progression of PC.

Circular RNA hsa_circRNA_0007334 is Predicted to Promote MMP7 and COL1A1 Expression by Functioning as a miRNA Sponge in Pancreatic Ductal Adenocarcinoma

Pancreatic cancer remains one of the leading causes of cancer-related deaths worldwide. Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic tumor. Many circular RNAs (circRNAs) have proven to play vital roles in the physiological and pathological processes of tumorigenesis; however, their biogenesis in PDAC remains unclear. In this study, the expression profiles of circRNAs from 10 PDAC tissues and their paired adjacent nontumor tissues were analyzed through RNA sequencing analysis. An enrichment analysis was employed to predict the functions of the differentially expressed circRNAs. Sequence alignment information and mRNA microarray projects were used to predict the RNA regulatory network. The knockdown of circRNAs by small interfering RNAs followed by wound healing and western blot assays was used to confirm their functions in a PDAC cell line. A total of 278 circRNAs were identified as differentially expressed in PDAC tissue. Of these, we found that hsa_circRNA_0007334 was significantly upregulated and may serve as a competing endogenous RNA to regulate matrix metallopeptidase 7 (MMP7) and collagen type I alpha 1 chain (COL1A1) by the competitive adsorption of hsa-miR-144-3p and hsa-miR-577 to enhance the expression and functions of MMP7 and COL1A1 in PDAC. In vitro experiments confirmed these results. The present study is the first to propose two regulatory pathways in PDAC: hsa_circRNA_0007334–hsa-miR-144-3p–MMP7 and hsa_circRNA_0007334–hsa-miR-577–COL1A1.

DKK1 inhibits breast cancer cell migration and invasion through suppression of β-catenin/MMP7 signaling pathway

Background

DKK1 has been reported to act as a tumor suppressor in breast cancer. However, the mechanism of DKK1 inhibits breast cancer migration and invasion was still unclear.

Methods

Western blot and real time PCR was used to detect the expression of DKK1, β-catenin and MMP7 in breast cancer cells. Wound scratch assay and transwell assay was employed to examine migration and invasion of breast cancer cell.

Results

DKK1 overexpression dramatically inhibits breast cancer cell migration and invasion. Knockdown of DKK1 promotes migration and invasion of breast cancer cells. DKK1 suppressed breast cancer cell migration and invasion through suppression of β-catenin and MMP7 expression. XAV-939, an inhibitor of β-catenin accumulation could reverse DKK1 silencing-induced MMP7 expression in breast cancer cells. Meanwhile, XAV-939 also could reverse the increase in the cell number invaded through Matrigel when DKK1 was knockdown. Furthermore, depletion of MMP7 also could reverse DKK1 knockdown-induced increase in the cell number invaded through Matrigel.

Conclusions

DKK1 inhibits migration and invasion of breast cancer cell through suppression of β-catenin/MMP7 pathway, our findings offered a potential alternative for breast cancer prevention and treatment.

The effects of systemic inflammatory response on prognosis of pancreatic ductal adenocarcinoma

Backgrounds/Aims

The aim of this study was to investigate the prognostic significance of neutrophyil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), CRP and CA19-9 in patients were diagnosed with pancreatic ductal adenocarcinoma (PDAC) to better verify pre-operative risk stratification and management.

Methods

This retrospective study included data from 133 consecutive patients with PDAC, who were treated between 2013 and 2015. PDAC diagnosis was made by cytology or assumed by radiological assessment or surgical resection samples. All clinico-pathological data were retrieved from medical records at our institution. The laboratory data were obtained before any treatment modality. Dates of death were obtained from the central registry.

Results

There was a statistically significant relation between radiological staging and CA19-9 and survival (p=0.001, p=0.005) and there are significant differences in CA19-9 level between stage I and III, I and IV, II and III, and II and IV. Both CRP and CA19-9 levels were statistically significantly higher in patients with radiological lymph node metastasis than patients with N0 disease (p=0.037, p=0.026). NLR and CA19-9 levels were also higher in metastatic disease (p=0.032, p=0.007). According to Spearman's correlation analysis, we found in all patients that there was a negative correlation between the survival time and CRP and neutrophil count (p=0.019, p=0.011).

Conclusions

Preoperative CRP, CA19-9 and NLR are simple, repeatable, inexpensive and well available marker, can give information on lymph node and solid organ metastasis and survival, give clues to prognosis and be useful in clinical staging of patients with PDAC.

Identification of hub genes with diagnostic values in pancreatic cancer by bioinformatics analyses and supervised learning methods

Background

Pancreatic cancer is one of the most lethal tumors with poor prognosis, and lacks of effective biomarkers in diagnosis and treatment. The aim of this investigation was to identify hub genes in pancreatic cancer, which would serve as potential biomarkers for cancer diagnosis and therapy in the future.

Methods

Combination of two expression profiles of GSE16515 and GSE22780 from Gene Expression Omnibus (GEO) database was served as training set. Differentially expressed genes (DEGs) with top 25% variance followed by protein-protein interaction (PPI) network were performed to find candidate genes. Then, hub genes were further screened by survival and cox analyses in The Cancer Genome Atlas (TCGA) database. Finally, hub genes were validated in GSE15471 dataset from GEO by supervised learning methods k-nearest neighbor (kNN) and random forest algorithms.

Results

After quality control and batch effect elimination of training set, 181 DEGs bearing top 25% variance were identified as candidate genes. Then, two hub genes, MMP7 and ITGA2, correlating with diagnosis and prognosis of pancreatic cancer were screened as hub genes according to above-mentioned bioinformatics methods. Finally, hub genes were demonstrated to successfully differ tumor samples from normal tissues with predictive accuracies reached to 93.59 and 81.31% by using kNN and random forest algorithms, respectively.

Conclusions

All the hub genes were associated with the regulation of tumor microenvironment, which implicated in tumor proliferation, progression, migration, and metastasis. Our results provide a novel prospect for diagnosis and treatment of pancreatic cancer, which may have a further application in clinical.

Electronic supplementary material

The online version of this article (10.1186/s12957-018-1519-y) contains supplementary material, which is available to authorized users.

Can physician gestalt predict survival in patients with resectable pancreatic adenocarcinoma?

PURPOSE

Clinician gestalt may hold unexplored information that can be capitalized upon to improve existing nomograms. The study objective was to evaluate physician ability to predict 2-year overall survival (OS) in resected pancreatic ductal adenocarcinoma (PDAC) patients based on pre-operative clinical characteristics and routine CT imaging.

METHODS

Ten surgeons and two radiologists were provided with a clinical vignette (including age, gender, presenting symptoms, and pre-operative CA19-9 when available) and pre-operative CT scan for 20 resected PDAC patients and asked to predict the probability of each patient reaching 2-year OS. Receiver operating characteristic curves were used to assess agreement and to compare performance with an established institutional nomogram.

RESULTS

Ten surgeons and 2 radiologists participated in this study. The area under the curve (AUC) for all physicians was 0.707 (95% CI 0.642-0.772). Attending physicians with > 5 years experience performed better than physicians with < 5 years of clinical experience since completion of post-graduate training (AUC = 0.710, 95% CI [0.536-0.884] compared to AUC = 0.662, 95% CI [0.398-0.927]). Radiologists performed better than surgeons (AUC = 0.875, 95% CI [0.765-0.985] compared to AUC = 0.656, 95% CI [0.580-0.732]). All but one physician outperformed the clinical nomogram (AUC = 0.604).

CONCLUSIONS

This pilot study demonstrated significant promise in the quantification of physician gestalt. While PDAC remains a difficult disease to prognosticate, physicians, particularly those with more clinical experience and radiologic expertise, are able to perform with higher accuracy than existing nomograms in predicting 2-year survival.

Extracellular matrix proteins and carcinoembryonic antigen-related cell adhesion molecules characterize pancreatic duct fluid exosomes in patients with pancreatic cancer

BACKGROUND

Exosomes are nanovesicles that have been shown to mediate carcinogenesis in pancreatic ductal adenocarcinoma (PDAC). Given the direct communication of pancreatic duct fluid with the tumor and its relative accessibility, we aimed to determine the feasibility of isolating and characterizing exosomes from pancreatic duct fluid.

METHODS

Pancreatic duct fluid was collected from 26 patients with PDAC (n = 13), intraductal papillary mucinous neoplasm (IPMN) (n = 8) and other benign pancreatic diseases (n = 5) at resection. Exosomes were isolated by serial ultracentrifugation, proteins were identified by mass spectrometry, and their expression was evaluated by immunohistochemistry.

RESULTS

Exosomes were isolated from all specimens with a mean concentration of 5.9 ± 1 × 10⁸ particles/mL and most frequent size of 138 ± 9 nm. Among the top 35 proteins that were significantly associated with PDAC, multiple carcinoembryonic antigen-related cell adhesion molecules (CEACAMs) and extracellular matrix (ECM) proteins were identified. Interestingly, CEACAM 1/5 expression by immunohistochemistry was seen only on tumor epithelia whereas tenascin C positivity was restricted to stroma, suggesting that both tumor and stromal cells contributed to exosomes.

CONCLUSION

This is the first study showing that exosome isolation is feasible from pancreatic duct fluid, and that exosomal proteins may be utilized to diagnose patients with PDAC.

Preoperative neutrophil-to-lymphocyte ratio and tumor-related factors to predict lymph node metastasis in patients with pancreatic ductal adenocarcinoma (PDAC)

As a poor prognosis indicator in patients with pancreatic ductal adenocarcinoma (PDCA), lymph node (LN) metastasis is of great importance in treatment. Present study was performed to evaluate the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR) and possible clinical parameters on the LN metastasis in PDCA patients. A total of 159 operable patients with PDCA were enrolled in our study. The clinical utility of NLR and other clinical parameters was evaluated by receiver operating characteristic (ROC) curves. Overall survival analysis indicated that LN metastasis is an independent prognostic factor. The logistic analysis was used to determine the independent parameters associated with LN metastasis. Ideal cutoff values for predicting LN metastasis are 2.12 for NLR and 130.96 for PLR according to the ROC curve. Multivariate analyses indicate that NLR (HR 2.588; 95% CI 1.246-5.376; P = 0.011), CA125 (HR 6.348; 95% CI 2.056-19.594; P = 0.001) and CA19-9 (HR 2.738; 95% CI 1.151-6.515; P = 0.023) are associated significantly with LN metastasis independently. Preoperative NLR, CA125 and CA19-9 are useful biomarkers for the prediction of LN metastasis in PDCA patients.

3D-spheroids: What can they tell us about pancreatic ductal adenocarcinoma cell phenotype?

We aimed at analyzing the effect of the 3D-arrangement on the expression of some genes and proteins which play a key role in pancreatic adenocarcinoma (PDAC) progression in HPAF-II, HPAC and PL45 PDAC cells cultured in either 2D-monolayers or 3D-spheroids. Cytokeratins 7, 8, 18, 19 were differently expressed in 3D-spheroids compared to 2D-monolayers. Syndecan 1 was upregulated in HPAF-II and PL45 3D-spheroids, and downregulated in HPAC. Heparanase mRNA levels were almost unchanged in HPAF-II, and increased in HPAC and PL45 3D-spheroids. Hyaluronan synthase (HAS) 2 and 3 mRNA increased in all 3D-spheroids compared to 2D-monolayers. CD44 and CD44s were expressed to a lower extent in HPAF-II and HPAC 3D-spheroids. By contrast, the CD44s/v3 and the CD44s/v6 ratio increased in HPAC and PL45 3D-spheroids, compared to 2D-monolayers. The expression of MMP-7 was strongly upregulated in 3D-spheroids. STAT3 was similarly expressed 3D-spheroids or 2D-monolayers, while pSTAT3 was almost undetectable in 2D-monolayers and strongly upregulated in 3D-spheroids. These results suggest that 3D-spheroids represent a cell culture model that allows the characterization of PDAC cell phenotype, adding new information that contributes to a better understanding of the biology and behavior of PDAC cells.