Pancreatic surgery

Prognostic value of early changes in CT-measured body composition in patients receiving chemotherapy for unresectable pancreatic cancer

OBJECTIVES

Skeletal muscle mass is a prognostic factor in pancreatic ductal adenocarcinoma (PDAC). However, it remains unclear whether changes in body composition provide an incremental prognostic value to established risk factors, especially the Response Evaluation Criteria in Solid Tumors version 1.1 (RECISTv1.1). The aim of this study was to determine the prognostic value of CT-quantified body composition changes in patients with unresectable PDAC starting chemotherapy.

METHODS

We retrospectively evaluated 105 patients with unresectable (locally advanced or metastatic) PDAC treated with FOLFIRINOX (n = 64) or gemcitabine-based (n = 41) first-line chemotherapy within a multicenter prospective trial. Changes (Δ) in skeletal muscle index (SMI), subcutaneous (SATI), and visceral adipose tissue index (VATI) between pre-chemotherapy and first follow-up CT were assessed. Cox regression models and covariate-adjusted survival curves were used to identify predictors of overall survival (OS).

RESULTS

At multivariable analysis, adjusting for RECISTv1.1-response at first follow-up, ΔSMI was prognostic for OS with a hazard ratio (HR) of 1.2 (95% CI: 1.08-1.33, p = 0.001). No significant association with OS was observed for ΔSATI (HR: 1, 95% CI: 0.97-1.04, p = 0.88) and ΔVATI (HR: 1.01, 95% CI: 0.99-1.04, p = 0.33). At an optimal cutoff of 2.8 cm²/m² per 30 days, the median survival of patients with high versus low ΔSMI was 143 versus 233 days (p < 0.001).

CONCLUSIONS

Patients with a lower rate of skeletal muscle loss at first follow-up demonstrated improved survival for unresectable PDAC, regardless of their RECISTv1.1-category. Assessing ΔSMI at the first follow-up CT may be useful for prognostication, in addition to routine radiological assessment.

KEY POINTS

• In patients with unresectable pancreatic ductal adenocarcinoma, change of skeletal muscle index (ΔSMI) in the early phase of chemotherapy is prognostic for overall survival, even after adjusting for Response Evaluation Criteria in Solid Tumors version 1.1 (RECISTv1.1) assessment at first follow-up. • Changes in adipose tissue compartments at first follow-up demonstrated no significant association with overall survival. • Integrating ΔSMI into routine radiological assessment may improve prognostic stratification and impact treatment decision-making at the first follow-up.

CT-Based Radiomics Analysis to Predict Malignancy in Patients with Intraductal Papillary Mucinous Neoplasm (IPMN) of the Pancreas

To assess the performance of CT-based radiomics analysis in differentiating benign from malignant intraductal papillary mucinous neoplasms of the pancreas (IPMN), preoperative scans of 408 resected patients with IPMN were retrospectively analyzed. IPMNs were classified as benign (low-grade dysplasia, n = 181), or malignant (high grade, n = 128, and invasive, n = 99). Clinicobiological data were reported. Patients were divided into a training cohort (TC) of 296 patients and an external validation cohort (EVC) of 112 patients. After semi-automatic tumor segmentation, PyRadiomics was used to extract radiomics features. A multivariate model was developed using a logistic regression approach. In the training cohort, 85/107 radiomics features were significantly different between patients with benign and malignant IPMNs. Unsupervised clustering analysis revealed four distinct clusters of patients with similar radiomics features patterns with malignancy as the most significant association. The multivariate model differentiated benign from malignant tumors in TC with an area under the ROC curve (AUC) of 0.84, sensitivity (Se) of 0.82, specificity (Spe) of 0.74, and in EVC with an AUC of 0.71, Se of 0.69, Spe of 0.57. This large study confirms the high diagnostic performance of preoperative CT-based radiomics analysis to differentiate between benign from malignant IPMNs.

Radiomics Improves Cancer Screening and Early Detection

Imaging is a key technology in the early detection of cancers, including X-ray mammography, low-dose CT for lung cancer, or optical imaging for skin, esophageal, or colorectal cancers. Historically, imaging information in early detection schema was assessed qualitatively. However, the last decade has seen increased development of computerized tools that convert images into quantitative mineable data (radiomics), and their subsequent analyses with artificial intelligence (AI). These tools are improving diagnostic accuracy of early lesions to define risk and classify malignant/aggressive from benign/indolent disease. The first section of this review will briefly describe the various imaging modalities and their use as primary or secondary screens in an early detection pipeline. The second section will describe specific use cases to illustrate the breadth of imaging modalities as well as the benefits of quantitative image analytics. These will include optical (skin cancer), X-ray CT (pancreatic and lung cancer), X-ray mammography (breast cancer), multiparametric MRI (breast and prostate cancer), PET (pancreatic cancer), and ultrasound elastography (liver cancer). Finally, we will discuss the inexorable improvements in radiomics to build more robust classifier models and the significant limitations to this development, including access to well-annotated databases, and biological descriptors of the imaged feature data.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Carboxypeptidase E-∆N Promotes Proliferation and Invasion of Pancreatic Cancer Cells via Upregulation of CXCR2 Gene Expression

Pancreatic cancer is one of the leading causes of cancer-related mortality worldwide. The molecular basis for the pathogenesis of this disease remains elusive. In this study, we have investigated the role of wild-type Carboxypeptidase E (CPE-WT) and a 40 kDa N-terminal truncated isoform, CPE-ΔN in promoting proliferation and invasion of Panc-1 cells, a pancreatic cancer cell line. Both CPE-WT and CPE-ΔN were expressed in Panc-1 and BXPC-3 pancreatic cancer cells. Immunocytochemical studies revealed that in CPE transfected Panc-1 cells, CPE-ΔN was found primarily in the nucleus, whereas CPE-WT was present exclusively in the cytoplasm as puncta, characteristic of secretory vesicles. Endogenous CPE-WT was secreted into the media. Overexpression of CPE-ΔN in Panc-1 cells resulted in enhancement of proliferation and invasion of these cells, as determined by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) cell proliferation assay and Matrigel invasion assay, respectively. In contrast, the expression of CPE-WT protein at comparable levels to CPE-ΔN in Panc-1 cells resulted in promotion of proliferation but not invasion. Importantly, there was an upregulation of the expression of CXCR2 mRNA and protein in Panc-1 cells overexpressing CPE-ΔN, and these cells exhibited significant increase in proliferation in a CXCR2-dependent manner. Thus, CPE-ΔN may play an important role in promoting pancreatic cancer growth and malignancy through upregulating the expression of the metastasis-related gene, CXCR2.

Computer-Aided Diagnosis of Pancreas Serous Cystic Neoplasms: A Radiomics Method on Preoperative MDCT Images

OBJECTIVE

Our aim was to propose a preoperative computer-aided diagnosis scheme to differentiate pancreatic serous cystic neoplasms from other pancreatic cystic neoplasms, providing supportive opinions for clinicians and avoiding overtreatment.

MATERIALS AND METHODS

In this retrospective study, 260 patients with pancreatic cystic neoplasm were included. Each patient underwent a multidetector row computed tomography scan and pancreatic resection. In all, 200 patients constituted a cross-validation cohort, and 60 patients formed an independent validation cohort. Demographic information, clinical information, and multidetector row computed tomography images were obtained from Picture Archiving and Communication Systems. The peripheral margin of each neoplasm was manually outlined by experienced radiologists. A radiomics system containing 24 guideline-based features and 385 radiomics high-throughput features was designed. After the feature extraction, least absolute shrinkage selection operator regression was used to select the most important features. A support vector machine classifier with 5-fold cross-validation was applied to build the diagnostic model. The independent validation cohort was used to validate the performance.

RESULTS

Only 31 of 102 serous cystic neoplasm cases in this study were recognized correctly by clinicians before the surgery. Twenty-two features were selected from the radiomics system after 100 bootstrapping repetitions of the least absolute shrinkage selection operator regression. The diagnostic scheme performed accurately and robustly, showing the area under the receiver operating characteristic curve = 0.767, sensitivity = 0.686, and specificity = 0.709. In the independent validation cohort, we acquired similar results with receiver operating characteristic curve = 0.837, sensitivity = 0.667, and specificity = 0.818.

CONCLUSION

The proposed radiomics-based computer-aided diagnosis scheme could increase preoperative diagnostic accuracy and assist clinicians in making accurate management decisions.

Combining radiomic features with a miRNA classifier may improve prediction of malignant pathology for pancreatic intraductal papillary mucinous neoplasms

Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cancer precursors incidentally discovered by cross-sectional imaging. Consensus guidelines for IPMN management rely on standard radiologic features to predict pathology, but they lack accuracy. Using a retrospective cohort of 38 surgically-resected, pathologically-confirmed IPMNs (20 benign; 18 malignant) with preoperative computed tomography (CT) images and matched plasma-based ‘miRNA genomic classifier (MGC)’ data, we determined whether quantitative ‘radiomic’ CT features (+/- the MGC) can more accurately predict IPMN pathology than standard radiologic features ‘high-risk’ or ‘worrisome’ for malignancy. Logistic regression, principal component analyses, and cross-validation were used to examine associations. Sensitivity, specificity, positive and negative predictive value (PPV, NPV) were estimated. The MGC, ‘high-risk,’ and ‘worrisome’ radiologic features had area under the receiver operating characteristic curve (AUC) values of 0.83, 0.84, and 0.54, respectively. Fourteen radiomic features differentiated malignant from benign IPMNs (p<0.05) and collectively had an AUC=0.77. Combining radiomic features with the MGC revealed an AUC=0.92 and superior sensitivity (83%), specificity (89%), PPV (88%), and NPV (85%) than other models. Evaluation of uncertainty by 10-fold cross-validation retained an AUC>0.80 (0.87 (95% CI:0.84-0.89)). This proof-of-concept study suggests a noninvasive radiogenomic approach may more accurately predict IPMN pathology than ‘worrisome’ radiologic features considered in consensus guidelines.

Mesenchymal Stromal Cells for Antineoplastic Drug Loading and Delivery

Mesenchymal stromal cells are a population of undifferentiated multipotent adult cells possessing extensive self-renewal properties and the potential to differentiate into a variety of mesenchymal lineage cells. They express broad anti-inflammatory and immunomodulatory activity on the immune system and after transplantation can interact with the surrounding microenvironment, promoting tissue healing and regeneration. For this reason, mesenchymal stromal cells have been widely used in regenerative medicine, both in preclinical and clinical settings. Another clinical application of mesenchymal stromal cells is the targeted delivery of chemotherapeutic agents to neoplastic cells, maximizing the cytotoxic activity against cancer cells and minimizing collateral damage to non-neoplastic tissues. Mesenchymal stem cells are home to the stroma of several primary and metastatic neoplasms and hence can be used as vectors for targeted delivery of antineoplastic drugs to the tumour microenvironment, thereby reducing systemic toxicity and maximizing antitumour effects. Paclitaxel and gemcitabine are the chemotherapeutic drugs best loaded by mesenchymal stromal cells and delivered to neoplastic cells, whereas other agents, like pemetrexed, are not internalized by mesenchymal stromal cells and therefore are not suitable for advanced antineoplastic therapy. This review focuses on the state of the art of advanced antineoplastic cell therapy and its future perspectives, emphasizing in vitro and in vivo preclinical results and future clinical applications.

Linc-ing Circulating Long Non-coding RNAs to the Diagnosis and Malignant Prediction of Intraductal Papillary Mucinous Neoplasms of the Pancreas

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease that lacks effective biomarkers for early detection. We hypothesized that circulating long non-coding RNAs (lncRNAs) may act as diagnostic markers of incidentally-detected cystic PDAC precursors known as intraductal papillary mucinous neoplasms (IPMNs) and predictors of their pathology/histological classification. Using NanoString nCounter® technology, we measured the abundance of 28 candidate lncRNAs in pre-operative plasma from a cohort of pathologically-confirmed IPMN cases of various grades of severity and non-diseased controls. Results showed that two lncRNAs (GAS5 and SRA) aided in differentiating IPMNs from controls. An 8-lncRNA signature (including ADARB2-AS1, ANRIL, GLIS3-AS1, LINC00472, MEG3, PANDA, PVT1, and UCA1) had greater accuracy than standard clinical and radiologic features in distinguishing 'aggressive/malignant' IPMNs that warrant surgical removal from 'indolent/benign' IPMNs that can be observed. When the 8-lncRNA signature was combined with plasma miRNA data and quantitative 'radiomic' imaging features, the accuracy of predicting IPMN pathological classification improved. Our findings provide novel information on the ability to detect lncRNAs in plasma from patients with IPMNs and suggest that an lncRNA-based blood test may have utility as a diagnostic adjunct for identifying IPMNs and their pathology, especially when incorporated with biomarkers such as miRNAs, quantitative imaging features, and clinical data.

A pilot study of radiologic measures of abdominal adiposity: weighty contributors to early pancreatic carcinogenesis worth evaluating?

Objective:

Intra-abdominal fat is a risk factor for pancreatic cancer (PC), but little is known about its contribution to PC precursors known as intraductal papillary mucinous neoplasms (IPMNs). Our goal was to evaluate quantitative radiologic measures of abdominal/visceral obesity as possible diagnostic markers of IPMN severity/pathology.

Methods:

In a cohort of 34 surgically-resected, pathologically-confirmed IPMNs (17 benign; 17 malignant) with preoperative abdominal computed tomography (CT) images, we calculated body mass index (BMI) and four radiologic measures of obesity: total abdominal fat (TAF) area, visceral fat area (VFA), subcutaneous fat area (SFA), and visceral to subcutaneous fat ratio (V/S). Measures were compared between groups using Wilcoxon two-sample exact tests and other metrics.

Results:

Mean BMI for individuals with malignant IPMNs (28.9 kg/m²) was higher than mean BMI for those with benign IPMNs (25.8 kg/m²) (P=0.045). Mean VFA was higher for patients with malignant IPMNs (199.3 cm²) compared to benign IPMNs (120.4 cm²),P=0.092. V/S was significantly higher (P=0.013) for patients with malignant versus benign IPMNs (1.25vs. 0.69 cm²), especially among females. The accuracy, sensitivity, specificity, and positive and negative predictive value of V/S in predicting malignant IPMN pathology were 74%, 71%, 76%, 75%, and 72%, respectively.

Conclusions:

Preliminary findings suggest measures of visceral fat from routine medical images may help predict IPMN pathology, acting as potential noninvasive diagnostic adjuncts for management and targets for intervention that may be more biologically-relevant than BMI. Further investigation of gender-specific associations in larger, prospective IPMN cohorts is warranted to validate and expand upon these observations.

Gemcitabine-releasing mesenchymal stromal cells inhibit in vitro proliferation of human pancreatic carcinoma cells

BACKGROUND AIMS

Pancreatic cancer (pCa) is a tumor characterized by a fibrotic state and associated with a poor prognosis. The observation that mesenchymal stromal cells (MSCs) migrate toward inflammatory micro-environments and engraft into tumor stroma after systemic administration suggested new therapeutic approaches with the use of engineered MSCs to deliver and produce anti-cancer molecules directly within the tumor. Previously, we demonstrated that without any genetic modifications, MSCs are able to deliver anti-cancer drugs. MSCs loaded with paclitaxel by exposure to high concentrations release the drug both in vitro and in vivo, inhibiting tumor proliferation. On the basis of these observations, we evaluated the ability of MSCs (from bone marrow and pancreas) to uptake and release gemcitabine (GCB), a drug widely used in pCa treatment.

METHODS

MSCs were primed by 24-h exposure to 2000 ng/mL of GCB. The anti-tumor potential of primed MSCs was then investigated by in vitro anti-proliferation assays with the use of CFPAC-1, a pancreatic tumor cell line sensitive to GCB. The uptake/release ability was confirmed by means of high-performance liquid chromatography analysis. A cell-cycle study and secretome evaluation were also conducted to better understand the characteristics of primed MSCs.

RESULTS

GCB-releasing MSCs inhibit the growth of a human pCa cell line in vitro.

CONCLUSIONS

The use of MSCs as a "trojan horse" can open the way to a new pCa therapeutic approach; GCB-loaded MSCs that integrate into the tumor mass could deliver much higher concentrations of the drug in situ than can be achieved by intravenous injection.

Metastases of pancreatic adenocarcinoma: A systematic review of literature and a new functional concept

INTRODUCTION

Pancreatic cancer, especially Pancreatic Adenocarcinoma, is still associated with a high mortality and morbidity for affected patients notwithstanding considerable progresses in diagnosis and both surgical pharmacological therapy. Despite metastases from colorectal, gastric and neuroendocrine primary tumor and their treatment are widely reported, the literature has been rarely investigated the impact of localization and numbers of pancreatic metastases. This study performed a systematic analysis of the most recent scientific literature on the natural history of Pancreatic Adenocarcinoma focusing attention on the role that the "M" parameter has on a possible prognostic stratification of these patients.

MATERIAL AND METHODS

PubMed and Science Direct databases were searched for relevant articles on these issue.

RESULTS

Initial database searches yielded 7231 studies from PubMed and 29101 from Science Direct. We evaluated 1031 eligible full text articles.

CONCLUSIONS

An updated insight into the world of Pancreatic Tumors might help physicians in better evaluating mechanisms of metastases, patients selection and survival and in programming appropriate interventions to modify the worst outcomes of advanced disease.

A genome-wide investigation of microRNA expression identifies biologically-meaningful microRNAs that distinguish between high-risk and low-risk intraductal papillary mucinous neoplasms of the pancreas

BACKGROUND

Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic ductal adenocarcinoma (PDAC) precursors. Differentiating between high-risk IPMNs that warrant surgical resection and low-risk IPMNs that can be monitored is a significant clinical problem, and we sought to discover a panel of mi(cro)RNAs that accurately classify IPMN risk status.

METHODOLOGY/PRINCIPAL FINDINGS

In a discovery phase, genome-wide miRNA expression profiling was performed on 28 surgically-resected, pathologically-confirmed IPMNs (19 high-risk, 9 low-risk) using Taqman MicroRNA Arrays. A validation phase was performed in 21 independent IPMNs (13 high-risk, 8 low-risk). We also explored associations between miRNA expression level and various clinical and pathological factors and examined genes and pathways regulated by the identified miRNAs by integrating data from bioinformatic analyses and microarray analysis of miRNA gene targets. Six miRNAs (miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-130a) were down-regulated in high-risk versus low-risk IPMNs and distinguished between groups (P<10-3, area underneath the curve (AUC) = 87%). The same trend was observed in the validation phase (AUC = 74%). Low miR-99b expression was associated with main pancreatic duct involvement (P = 0.021), and serum albumin levels were positively correlated with miR-99a (r = 0.52, P = 0.004) and miR-100 expression (r = 0.49, P = 0.008). Literature, validated miRNA:target gene interactions, and pathway enrichment analysis supported the candidate miRNAs as tumor suppressors and regulators of PDAC development. Microarray analysis revealed that oncogenic targets of miR-130a (ATG2B, MEOX2), miR-342-3p (DNMT1), and miR-126 (IRS-1) were up-regulated in high- versus low-risk IPMNs (P<0.10).

CONCLUSIONS

This pilot study highlights miRNAs that may aid in preoperative risk stratification of IPMNs and provides novel insights into miRNA-mediated progression to pancreatic malignancy. The miRNAs identified here and in other recent investigations warrant evaluation in biofluids in a well-powered prospective cohort of individuals newly-diagnosed with IPMNs and other pancreatic cysts and those at increased genetic risk for these lesions.

CXCR2: a target for pancreatic cancer treatment?

INTRODUCTION

Pancreatic cancer, a leading cause of cancer deaths worldwide, is very aggressive and has minimally effective treatment options. For those who have no surgical options, medical treatments are limited. The chemokine receptor CXCR2 has become the subject of much interest recently because of multiple studies indicating its involvement in cancer and inflammatory conditions. Research now indicates that CXCR2 and its ligands are intimately involved in tumor regulation and growth and that inhibition of its function shows promising results in multiple cancer types, including pancreatic cancer.

AREAS COVERED

In this study, the authors review basic molecular and structural details of CXCR2, as well as the known functions of CXCR2 and several of its ligands in inflammation and cancer biology with specific attention to pancreatic cancer. Then the future possibilities and questions remaining for pharmacological intervention against CXCR2 in pancreatic cancer are explored.

EXPERT OPINION

Many current inhibitory strategies already exist for targeting CXCR2 in vitro as well as in vivo. Clinically speaking, CXCR2 is an exciting potential target for pancreatic cancer; however, CXCR2 is functionally important for multiple processes and therapeutic options would benefit from further work toward understanding of these roles as well as structural and target specificity.