Why is pancreatic cancer so deadly? The pathologist's view

Clinical Relevance of Cancerization of Ducts in Resected Pancreatic Ductal Adenocarcinoma

OBJECTIVES

Although prevalent in 50%-90% of pancreatic ductal adenocarcinomas, the clinical relevance of "cancerization of ducts" (COD) remains unknown.

METHODS

Pathologists retrospectively reviewed slides classifying prevalence of COD. Histopathological parameters, location of first recurrence, recurrence-free survival (RFS), and overall survival (OS) were collected from the institutional pancreatectomy registry.

RESULTS

Among 311 pancreatic ductal adenocarcinomas, COD was present in 216 (69.5%) and more prevalent in the cohort that underwent upfront surgery (75.3% vs 63.1%, P = 0.019). Furthermore, COD was associated with female gender (P = 0.040), advanced T stage (P = 0.007), perineural invasion (P = 0.014), lymphovascular invasion (P = 0.025), and R1 margin (P = 0.009), but not N stage (P = 0.401) or tumor differentiation (P = 0.717). In multivariable regression, COD was associated with less liver recurrence (odds ratio, 0.44; P < 0.005). This association was driven by the cohort of patients who had received preoperative treatment (odds ratio, 0.18; P < 0.001). COD was not predictive for RFS or OS.

CONCLUSIONS

Cancerization of ducts was not associated with RFS or OS. Currently underrecognized, standardized implementation into histopathological reports may have merit, and further mechanistic scientific experiments need to illuminate its clinical and biologic impact.

Prognostic significance of collagen signatures in pancreatic ductal adenocarcinoma obtained from second-harmonic generation imaging

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) ranks among the deadliest types of cancer, and it will be meaningful to search for new biomarkers with prognostic value to help clinicians tailor therapeutic strategies.

METHODS

Here we tried to use an advanced optical imaging technique, multiphoton microscopy (MPM) combining second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) imaging, for the label-free detection of PDAC tissues from a cohort of 149 patients. An automated image processing method was used to extract collagen features from SHG images and the Kaplan-Meier survival analysis and Cox proportional hazards regression were used to assess the prognostic value of collagen signatures.

RESULTS

SHG images clearly show the different characteristics of collagen fibers in tumor microenvironment. We gained eight collagen morphological features, and a Feature-score was derived for each patient by the combination of these features using ridge regression. Statistical analyses reveal that Feature-score is an independent factor, and can predict the overall survival of PDAC patients as well as provide well risk stratification.

CONCLUSIONS

SHG imaging technique can potentially be a tool for the accurate diagnosis of PDAC, and this optical biomarker (Feature-score) may help clinicians make more approximate treatment decisions.

The radiomorphological appearance of the invasive margin in pancreatic cancer is associated with tumor budding

PURPOSE

Pancreatic cancer (PDAC) is characterized by infiltrative, spiculated tumor growth into the surrounding non-neoplastic tissue. Clinically, its diagnosis is often established by magnetic resonance imaging (MRI). At the invasive margin, tumor buds can be detected by histology, an established marker associated with poor prognosis in different types of tumors.

METHODS

We analyzed PDAC by determining the degree of tumor spiculation on T2-weighted MRI using a 3-tier grading system. The grade of spiculation was correlated with the density of tumor buds quantified in histological sections of the respective surgical specimen according to the guidelines of the International Tumor Budding Consensus Conference (n = 28 patients).

RESULTS

64% of tumors revealed intermediate to high spiculation on MRI. In over 90% of cases, tumor buds were detected. We observed a significant positive rank correlation between the grade of radiological tumor spiculation and the histopathological number of tumor buds (rs = 0.745, p < 0.001). The number of tumor buds was not significantly associated with tumor stage, presence of lymph node metastases, or histopathological grading (p ≥ 0.352).

CONCLUSION

Our study identifies a readily available radiological marker for non-invasive estimation of tumor budding, as a correlate for infiltrative tumor growth. This finding could help to identify PDAC patients who might benefit from more extensive peripancreatic soft tissue resection during surgery or stratify patients for personalized therapy concepts.

Comparative molecular profiling of pancreatic ductal adenocarcinoma of the head versus body and tail

Pancreatic ductal adenocarcinoma (PDAC) of the head (H) and body/tail (B/T) differ in embryonic origin, cell composition, blood supply, lymphatic and venous drainage, and innervation. We aimed to compare the molecular and tumor immune microenvironment (TIME) profiles of PDAC of the H vs. B/T. A total of 3499 PDAC samples were analyzed via next-generation sequencing (NGS) of RNA (whole transcriptome, NovaSeq), DNA (NextSeq, 592 genes or NovaSeq, whole exome sequencing), and immunohistochemistry (Caris Life Sciences, Phoenix, AZ). Significance was determined as p values adjusted for multiple corrections (q) of <0.05. Anatomic subsites of PDAC tumors were grouped by primary tumor sites into H (N = 2058) or B/T (N = 1384). There were significantly more metastatic tumors profiled from B/T vs. H (57% vs. 44%, p < 0.001). KRAS mutations (93.8% vs. 90.2%), genomic loss of heterozygosity (12.7% vs. 9.1%), and several copy number alterations (FGF3, FGF4, FGF19, CCND1, ZNF703, FLT4, MUTYH, TNFRS14) trended higher in B/T when compared to H (p < 0.05 but q > 0.05). Expression analysis of immuno-oncology (IO)-related genes showed significantly higher expression of CTLA4 and PDCD1 in H (q < 0.05, fold change 1.2 and 1.3) and IDO1 and PDCD1LG2 expression trended higher in B/T (p < 0.05, fold change 0.95). To our knowledge, this is one of the largest cohorts of PDAC tumors subjected to broad molecular profiling. Differences in IO-related gene expression and TIME cell distribution suggest that response to IO therapies may differ in PDAC arising from H vs. B/T. Subtle differences in the genomic profiles of H vs. B/T tumors were observed.

Development of Clinical Radiomics-Based Models to Predict Survival Outcome in Pancreatic Ductal Adenocarcinoma: A Multicenter Retrospective Study

PURPOSE

This multicenter retrospective study aims to identify reliable clinical and radiomic features to build machine learning models that predict progression-free survival (PFS) and overall survival (OS) in pancreatic ductal adenocarcinoma (PDAC) patients.

METHODS

Between 2010 and 2020 pre-treatment contrast-enhanced CT scans of 287 pathology-confirmed PDAC patients from two sites of the Hopital Universitaire de Bruxelles (HUB) and from 47 hospitals within the HUB network were retrospectively analysed. Demographic, clinical, and survival data were also collected. Gross tumour volume (GTV) and non-tumoral pancreas (RPV) were semi-manually segmented and radiomics features were extracted. Patients from two HUB sites comprised the training dataset, while those from the remaining 47 hospitals of the HUB network constituted the testing dataset. A three-step method was used for feature selection. Based on the GradientBoostingSurvivalAnalysis classifier, different machine learning models were trained and tested to predict OS and PFS. Model performances were assessed using the C-index and Kaplan-Meier curves. SHAP analysis was applied to allow for post hoc interpretability.

RESULTS

A total of 107 radiomics features were extracted from each of the GTV and RPV. Fourteen subgroups of features were selected: clinical, GTV, RPV, clinical & GTV, clinical & GTV & RPV, GTV-volume and RPV-volume both for OS and PFS. Subsequently, 14 Gradient Boosting Survival Analysis models were trained and tested. In the testing dataset, the clinical & GTV model demonstrated the highest performance for OS (C-index: 0.72) among all other models, while for PFS, the clinical model exhibited a superior performance (C-index: 0.70).

CONCLUSIONS

An integrated approach, combining clinical and radiomics features, excels in predicting OS, whereas clinical features demonstrate strong performance in PFS prediction.

Development of a radiomics-based model to predict occult liver metastases of pancreatic ductal adenocarcinoma: a multicenter study

BACKGROUND

Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to predict occult liver metastases and assess its prognostic capacity for survival.

MATERIALS AND METHODS

Patients who underwent surgical resection and were pathologically proven with PDAC were recruited retrospectively from five tertiary hospitals between January 2015 and December 2020. Radiomics features were extracted from tumors, and the radiomics-based model was developed in the training cohort using LASSO-logistic regression. The model's performance was assessed in the internal and external validation cohorts using the area under the receiver operating curve (AUC). Subsequently, the association of the model's risk stratification with progression-free survival (PFS) and overall survival (OS) was then statistically examined using Cox regression analysis and the log-rank test.

RESULTS

A total of 438 patients [mean (SD) age, 62.0 (10.0) years; 255 (58.2%) male] were divided into the training cohort ( n =235), internal validation cohort ( n =100), and external validation cohort ( n =103). The radiomics-based model yielded an AUC of 0.73 (95% CI: 0.66-0.80), 0.72 (95% CI: 0.62-0.80), and 0.71 (95% CI: 0.61-0.80) in the training, internal validation, and external validation cohorts, respectively, which were higher than the preoperative clinical model. The model's risk stratification was an independent predictor of PFS (all P <0.05) and OS (all P <0.05). Furthermore, patients in the high-risk group stratified by the model consistently had a significantly shorter PFS and OS at each TNM stage (all P <0.05).

CONCLUSION

The proposed radiomics-based model provided a promising tool to predict occult liver metastases and had a great significance in prognosis.

Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility

Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.

A primer on artificial intelligence in pancreatic imaging

Artificial Intelligence (AI) is set to transform medical imaging by leveraging the vast data contained in medical images. Deep learning and radiomics are the two main AI methods currently being applied within radiology. Deep learning uses a layered set of self-correcting algorithms to develop a mathematical model that best fits the data. Radiomics converts imaging data into mineable features such as signal intensity, shape, texture, and higher-order features. Both methods have the potential to improve disease detection, characterization, and prognostication. This article reviews the current status of artificial intelligence in pancreatic imaging and critically appraises the quality of existing evidence using the radiomics quality score.

Pancreaticoduodenectomy with preoperative total embolization of the hepatic arteries (PD-HAE)-a novel treatment with sacrifice of the hepatic arterial blood supply without the need for arterial reconstruction

PURPOSE

Tumors with involvement of common hepatic and gastroduodenal arteries (CHA and GDA) or GDA and the proper hepatic artery (PHA) are traditionally considered nonresectable. We have devised a new procedure that includes pancreaticoduodenectomy with preoperative hepatic artery embolization (PD-HAE) to facilitate an R0 resection of tumors involving the hepatic arteries without vascular anastomoses and complete sacrifice of normal hepatic arterial blood supply.

METHODS

To allow resection of the hepatic arteries, preoperative embolization of the PHA was performed to induce an increased collateral arterial blood flow from the periphery of the liver, far from the hepatic hilum 10-14 days prior to the operation. Between May 1, 2017 and December 31, 2019, eight patients with ductal adenocarcinoma were operated with the PD-HAE procedure.

RESULTS

The embolizations were uneventful apart from a transient marginal elevation of alanine aminotransferase in three patients. All patients had N disease with perineural invasion of tumor cells around the adventitia of the artery and severe perivascular inflammation. An R0 resection (> 1.0 mm to all resection margins) was obtained in six patients (75%). Mean hospital stay was 12 days. Median survival was 23 months (95% CI: 19.5-26.5 months). Six patients (75%) are still alive 11 to 36 months after the operation. There was perioperative fatality, and morbidity was comparable to standard pancreaticoduodenectomy.

CONCLUSION

PD-HAE is a safe procedure and may provide the opportunity for curative resection in otherwise unresectable patients. However, larger studies are needed to evaluate this procedure.

Proteomics-Driven Biomarkers in Pancreatic Cancer

Pancreatic cancer is a devastating disease that has a grim prognosis, highlighting the need for improved screening, diagnosis, and treatment strategies. Currently, the sole biomarker for pancreatic ductal adenocarcinoma (PDAC) authorized by the U.S. Food and Drug Administration is CA 19-9, which proves to be the most beneficial in tracking treatment response rather than in early detection. In recent years, proteomics has emerged as a powerful tool for advancing our understanding of pancreatic cancer biology and identifying potential biomarkers and therapeutic targets. This review aims to offer a comprehensive survey of proteomics' current status in pancreatic cancer research, specifically accentuating its applications and its potential to drastically enhance screening, diagnosis, and treatment response. With respect to screening and diagnostic precision, proteomics carries the capacity to augment the sensitivity and specificity of extant screening and diagnostic methodologies. Nonetheless, more research is imperative for validating potential biomarkers and establishing standard procedures for sample preparation and data analysis. Furthermore, proteomics presents opportunities for unveiling new biomarkers and therapeutic targets, as well as fostering the development of personalized treatment strategies based on protein expression patterns associated with treatment response. In conclusion, proteomics holds great promise for advancing our understanding of pancreatic cancer biology and improving patient outcomes. It is essential to maintain momentum in investment and innovation in this arena to unearth more groundbreaking discoveries and transmute them into practical diagnostic and therapeutic strategies in the clinical context.

Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection

BACKGROUND

Pancreatic ductal carcinoma patients have a really poor prognosis given its difficult early detection and the lack of early symptoms. Digital pathology is routinely used by pathologists to diagnose the disease. However, visually inspecting the tissue is a time-consuming task, which slows down the diagnostic procedure. With the advances occurred in the area of artificial intelligence, specifically with deep learning models, and the growing availability of public histology data, clinical decision support systems are being created. However, the generalization capabilities of these systems are not always tested, nor the integration of publicly available datasets for pancreatic ductal carcinoma detection (PDAC).

METHODS

In this work, we explored the performace of two weakly-supervised deep learning models using the two more widely available datasets with pancreatic ductal carcinoma histology images, The Cancer Genome Atlas Project (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). In order to have sufficient training data, the TCGA dataset was integrated with the Genotype-Tissue Expression (GTEx) project dataset, which contains healthy pancreatic samples.

RESULTS

We showed how the model trained on CPTAC generalizes better than the one trained on the integrated dataset, obtaining an inter-dataset accuracy of 90.62% ± 2.32 and an outer-dataset accuracy of 92.17% when evaluated on TCGA + GTEx. Furthermore, we tested the performance on another dataset formed by tissue micro-arrays, obtaining an accuracy of 98.59%. We showed how the features learned in an integrated dataset do not differentiate between the classes, but between the datasets, noticing that a stronger normalization might be needed when creating clinical decision support systems with datasets obtained from different sources. To mitigate this effect, we proposed to train on the three available datasets, improving the detection performance and generalization capabilities of a model trained only on TCGA + GTEx and achieving a similar performance to the model trained only on CPTAC.

CONCLUSIONS

The integration of datasets where both classes are present can mitigate the batch effect present when integrating datasets, improving the classification performance, and accurately detecting PDAC across different datasets.

The role of molecular testing in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDA) is highly aggressive and has few treatment options. To personalize therapy, it is critical to delineate molecular subtypes and understand inter- and intra-tumoral heterogeneity. Germline testing for hereditary genetic abnormalities is recommended for all patients with PDA and somatic molecular testing is recommended for all patients with locally advanced or metastatic disease. KRAS mutations are present in 90% of PDA, while 10% are KRAS wild type and are potentially targetable with epidermal growth factor receptor blockade. KRASG12C inhibitors have shown activity in G12C-mutated cancers, and novel G12D and pan-RAS inhibitors are in clinical trials. DNA damage repair abnormalities, germline or somatic, occur in 5-10% of patients and are likely to benefit from DNA damaging agents and maintenance therapy with poly-ADP ribose polymerase inhibitors. Fewer than 1% of PDA harbor microsatellite instability high status and are susceptible to immune checkpoint blockade. Albeit very rare, occurring in <1% of patients with KRAS wild-type PDAs, BRAF V600E mutations, RET and NTRK fusions are targetable with cancer agnostic Food and Drug Administration-approved therapies. Genetic, epigenetic, and tumor microenvironment targets continue to be identified at an unprecedented pace, enabling PDA patients to be matched to targeted and immune therapeutics, including antibody-drug conjugates, and genetically engineered chimeric antigen receptor or T-cell receptor - T-cell therapies. In this review, we highlight clinically relevant molecular alterations and focus on targeted strategies that can improve patient outcomes through precision medicine.

Three-dimensional analysis of human pancreatic cancer specimens by phase-contrast based X-ray tomography - the next dimension of diagnosis

BACKGROUND

The worldwide increase of pancreatic ductal adenocarcinoma (PDAC), which still has one of the lowest survival rates, requires novel imaging tools to improve early detection and to refine diagnosis. Therefore, the aim of this study was to assess the feasibility of propagation-based phase-contrast X-ray computed tomography of already paraffin-embedded and unlabeled human pancreatic tumor tissue to achieve a detailed three-dimensional (3D) view of the tumor sample in its entirety.

METHODS

Punch biopsies of areas of particular interest were taken from paraffin blocks after initial histological analysis of hematoxylin and eosin stained tumor sections. To cover the entire 3.5 mm diameter of the punch biopsy, nine individual tomograms with overlapping regions were acquired in a synchrotron parallel beam configuration and stitched together after data reconstruction. Due to the intrinsic contrast based on electron density differences of tissue components and a voxel size of 1.3 μm achieved PDAC and its precursors were clearly identified.

RESULTS

Characteristic tissue structures for PDAC and its precursors, such as dilated pancreatic ducts, altered ductal epithelium, diffuse immune cell infiltrations, increased occurrence of tumor stroma and perineural invasion were clearly identified. Certain structures of interest were visualized in three dimensions throughout the tissue punch. Pancreatic duct ectasia of different caliber and atypical shape as well as perineural infiltration could be contiguously traced by viewing serial tomographic slices and by applying semi-automatic segmentation. Histological validation of corresponding sections confirmed the former identified PDAC features.

CONCLUSION

In conclusion, virtual 3D histology via phase-contrast X-ray tomography visualizes diagnostically relevant tissue structures of PDAC in their entirety, preserving tissue integrity in label-free, paraffin embedded tissue biopsies. In the future, this will not only enable a more comprehensive diagnosis but also a possible identification of new 3D imaging tumor markers.

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Phytoradiotherapy to enhance cancer treatment outcomes with cannabidiol, bitter melon juice, and plant hemoglobin

Despite technological advances in radiation therapy for cancer treatment, many patient populations still experience mediocre survival percentages, local control, and quality of life. Additionally, much of the world lacks access to expensive, modern treatment options. The need for innovative, cost-effective solutions that can improve patient treatment outcomes is essential. Phytomedicines have been shown to induce apoptotic tumor cell death, diminish tumor progression, reduce cancer incidence, alleviate harmful hypoxic conditions, and more. While an ample amount of research is available that characterizes many phytomedicines as having anti-cancer properties that increase tumor cell killing/control and mitigate the harmful side effects of radiation damage, little work has been done to investigate the synergistic effect of phytoradiotherapy: combining radiation treatment with phytomedicines. In this study, a protocol for testing the radiosensitizing effects of phytomedicines was validated and used to investigate the well-known plant based medicine cannabidiol (CBD) and the lesser-known medicinal fruit Bitter Melon. Additionally, based on its high concentration of plant hemoglobin which has been shown to abate hypoxia, the African-indigenous Justicia plant was tested in pancreatic adenocarcinoma mouse models. The studies reveal that these phytomedicines can effectively enhance tumor cell killing, minimize tumor growth, and prolong mice survival. There is certainly the need for additional research in this regard, however, phytoradiotherapy: the use of phytomedicines to enhance radiation therapy treatment outcomes, continues to show potential as a promising, innovative way to improve cancer care.

Fluid-sensitive migration mechanisms predict association between metastasis and high interstitial fluid pressure in pancreatic cancer

A remarkable feature in pancreatic cancer is the propensity to metastasize early, even for small, early stage cancers. We use a computer-based pancreatic model to simulate tumor progression behavior where fluid-sensitive migration mechanisms are accounted for as a plausible driver for metastasis. The model has been trained to comply with in vitro results to determine input parameters that characterize the migration mechanisms. To mimic previously studied preclinical xenografts we run the computer model informed with an ensemble of stochastic-generated realizations of unknown parameters related to tumor microenvironment only constrained such that pathological realistic values for interstitial fluid pressure (IFP) are obtained. The in silico model suggests the occurrence of a steady production of small clusters of cancer cells that detach from the primary tumor and form isolated islands and thereby creates a natural prerequisite for a strong invasion into the lymph nodes and venous system. The model predicts that this behavior is associated with high interstitial fluid pressure (IFP), consistent with published experimental findings. The continuum-based model is the first to explain published results for preclinical models which have reported associations between high IFP and high metastatic propensity and thereby serves to shed light on possible mechanisms behind the clinical aggressiveness of pancreatic cancer.

Cell Dissemination in Pancreatic Cancer

Pancreatic cancer is a disease notorious for its high frequency of recurrence and low survival rate. Surgery is the most effective treatment for localized pancreatic cancer, but most cancer recurs after surgery, and patients die within ten years of diagnosis. The question persists: what makes pancreatic cancer recur and metastasize with such a high frequency? Herein, we review evidence that subclinical dormant pancreatic cancer cells disseminate before developing metastatic or recurring cancer. We then discuss several routes by which pancreatic cancer migrates and the mechanisms by which pancreatic cancer cells adapt. Lastly, we discuss unanswered questions in pancreatic cancer cell migration and our perspectives.

CODA: quantitative 3D reconstruction of large tissues at cellular resolution

A central challenge in biology is obtaining high-content, high-resolution information while analyzing tissue samples at volumes relevant to disease progression. We address this here with CODA, a method to reconstruct exceptionally large (up to multicentimeter cubed) tissues at subcellular resolution using serially sectioned hematoxylin and eosin-stained tissue sections. Here we demonstrate CODA's ability to reconstruct three-dimensional (3D) distinct microanatomical structures in pancreas, skin, lung and liver tissues. CODA allows creation of readily quantifiable tissue volumes amenable to biological research. As a testbed, we assess the microanatomy of the human pancreas during tumorigenesis within the branching pancreatic ductal system, labeling ten distinct structures to examine heterogeneity and structural transformation during neoplastic progression. We show that pancreatic precancerous lesions develop into distinct 3D morphological phenotypes and that pancreatic cancer tends to spread far from the bulk tumor along collagen fibers that are highly aligned to the 3D curves of ductal, lobular, vascular and neural structures. Thus, CODA establishes a means to transform broadly the structural study of human diseases through exploration of exhaustively labeled 3D microarchitecture.

Neoplastic cell enrichment of tumor tissues using coring and laser microdissection for proteomic and genomic analyses of pancreatic ductal adenocarcinoma

BACKGROUND

The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses.

METHODS

Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations.

RESULTS

The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity.

CONCLUSIONS

In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Neoantigens and their clinical applications in human gastrointestinal cancers

Background

Tumor-specific neoantigens are ideal targets for cancer immunotherapy. As research findings have proved, neoantigen-specific T cell activity is immunotherapy’s most important determinant.

Main text

There is sufficient evidence showing the role of neoantigens in clinically successful immunotherapy, providing a justification for targeting. Because of the significance of the pre-existing anti-tumor immune response for the immune checkpoint inhibitor, it is believed that personalized neoantigen-based therapy may be an imperative approach for cancer therapy. Thus, intensive attention is given to strategies targeting neoantigens for the significant impact with other immunotherapies, such as the immune checkpoint inhibitor. Today, several algorithms are designed and optimized based on Next-Generation Sequencing and public databases, including dbPepNeo, TANTIGEN 2.0, Cancer Antigenic Peptide Database, NEPdb, and CEDAR databases for predicting neoantigens in silico that stimulates the development of T cell therapies, cancer vaccine, and other ongoing immunotherapy approaches.

Conclusions

In this review, we deliberated the current developments in understanding and recognition of the immunogenicity of newly found gastrointestinal neoantigens as well as their functions in immunotherapies and cancer detection. We also described how neoantigens are being developed and how they might be used in the treatment of GI malignancies.

The Development of a Prediction Model Based on Random Survival Forest for the Postoperative Prognosis of Pancreatic Cancer: A SEER-Based Study

Simple Summary

Surgery is the main treatment to cure pancreatic cancer (PC). However, the 5-year survival rate of surgical resection is only 10–20%. The aim of our study was to develop a prediction model with the novel machine learning algorithm random survival forest (RSF) and to offer easy-to-use prediction tools, including risk stratification and individual prognosis. The study would benefit patients and physicians in postoperative management and facilitate personalized medicine.

Abstract

Accurate prediction for the prognosis of patients with pancreatic cancer (PC) is a emerge task nowadays. We aimed to develop survival models for postoperative PC patients, based on a novel algorithm, random survival forest (RSF), traditional Cox regression and neural networks (Deepsurv), using the Surveillance, Epidemiology, and End Results Program (SEER) database. A total of 3988 patients were included in this study. Eight clinicopathological features were selected using least absolute shrinkage and selection operator (LASSO) regression analysis and were utilized to develop the RSF model. The model was evaluated based on three dimensions: discrimination, calibration, and clinical benefit. It found that the RSF model predicted the cancer-specific survival (CSS) of the postoperative PC patients with a c-index of 0.723, which was higher than the models built by Cox regression (0.670) and Deepsurv (0.700). The Brier scores at 1, 3, and 5 years (0.188, 0.177, and 0.131) of the RSF model demonstrated the model’s favorable calibration and the decision curve analysis illustrated the model’s value of clinical implement. Moreover, the roles of the key variables were visualized in the Shapley Additive Explanations plotting. Lastly, the prediction model demonstrates value in risk stratification and individual prognosis. In this study, a high-performance prediction model for PC postoperative prognosis was developed, based on RSF The model presented significant strengths in the risk stratification and individual prognosis prediction.

Pancreatic ductal adenocarcinoma with a predominant large duct pattern has better recurrence-free survival than conventional pancreatic ductal adenocarcinoma: a comprehensive histopathological, immunohistochemical, and mutational study

Large duct pattern of pancreatic ductal adenocarcinomas (PDACs) comprises occasional large cancer glands (>0.5 mm in size), along with conventional smaller cancer glands. They histologically mimic intraductal papillary mucinous neoplasms. However, the clinicopathologic significance of PDACs with predominant large duct pattern (PLDP) has not been systematically evaluated. A total of 41 cases of PDACs with PLDP, which were defined as irregularly-shaped cancer glands >0.5 mm in size occupied >50% of tumor volume, were enrolled and their clinicopathological, immunohistochemical, and targeted exome-wise mutational characteristics were compared with 298 conventional PDACs. PDACs with PLDP had cancers with larger tumor sizes (P = 0.025), which were more frequently well to moderately differentiation (P < 0.001), with less lymphovascular invasion (P = 0.013) and had a higher T category (P = 0.023) than conventional PDACs. Immunohistochemically, PDACs with PLDP showed similar abnormal p53 (61%) and SMAD4 (59%) expression patterns as conventional PDACs. In addition, PDACs with PLDP showed diffuse MUC1 (88%), MUC5AC (100%), MUC6 (66%), and focal MUC2 (20%) expressions. More frequent ROS1 mutations were observed in PDACs with PLDP. PDAC patients with PLDP had a better overall and recurrence-free survival (OS and RFS; median, 42 and 34 months) than that of patients with conventional PDACs (34 and 16 months) as per univariate (P = 0.037 and P = 0.001) and multivariate (P = 0.031 and P = 0.034) analyses. PDACs with PLDP showed mutational patterns similar to those of conventional PDACs. They had unique histologic features and longer OS and RFS compared to those of conventional PDACs. Therefore, PDACs with PLDP could be considered a histologic subtype of PDACs.

The Effect of 1,2,4-Triazole-3-thiol Derivatives Bearing Hydrazone Moiety on Cancer Cell Migration and Growth of Melanoma, Breast, and Pancreatic Cancer Spheroids

4-Phenyl-3-[2-(phenylamino)ethyl]-1H-1,2,4-triazole-5(4H)-thione was used as a starting compound for the synthesis of the corresponding 1,2,4-triazol-3-ylthioacetohydrazide, which reacts with isatins and various aldehydes bearing aromatic and heterocyclic moieties provided target hydrazones. Their cytotoxicity was tested by the MTT assay against human melanoma IGR39, human triple-negative breast cancer (MDA-MB-231), and pancreatic carcinoma (Panc-1) cell lines. The selectivity of compounds towards cancer cells was also studied. In general, the synthesized compounds were more cytotoxic against the melanoma cell line. N′-(2-oxoindolin-3-ylidene)-2-((4-phenyl-5-(2-(phenylamino)ethyl)-4H-1,2,4-triazol-3-yl)thio)acetohydrazide, N′-((1H-pyrrol-2-yl)methylene)-2-((4-phenyl-5-(2-(phenylamino)ethyl)-4H-1,2,4-triazol-3-yl)thio)acetohydrazide and N′-(2-hydroxy-5-nitrobenzylidene)-2-((4-phenyl-5-(2-(phenylamino)ethyl)-4H-1,2,4-triazol-3-yl)thio)acetohydrazide were identified as the most active among all synthesized compounds in 3D cell cultures. N′-(4-(dimethylamino)benzylidene)-2-((4-phenyl-5-(2-(phenylamino)ethyl)-4H-1,2,4-triazol-3-yl)thio)acetohydrazide inhibited all cancer cell migration, was characterized as relatively more selective towards cancer cells, and could be further tested as an antimetastatic candidate.

Clinical applications of mass spectrometry-based proteomics in cancer: where are we?

Tumor tissue processing methodologies in combination with data-independent acquisition mass spectrometry (DIA-MS) have emerged that can comprehensively analyze the proteome of multiple tumor samples accurately and reproducibly. Increasing recognition and adoption of these technologies has resulted in a tranche of studies providing novel insights into cancer classification systems, functional tumor biology, cancer biomarkers, treatment response and drug targets. Despite this, with some limited exceptions, MS-based proteomics has not yet been implemented in routine cancer clinical practice. Here, we summarize the use of DIA-MS in studies that may pave the way for future clinical cancer applications, and highlight the role of alternative MS technologies and multi-omic strategies. We discuss limitations and challenges of studies in this field to date and propose steps for integrating proteomic data into the cancer clinic. This article is protected by copyright. All rights reserved.

Pancreatic cancer cells spectral library by DIA-MS and the phenotype analysis of gemcitabine sensitivity

Data-independent acquisition (DIA)-mass spectrometry (MS)-based proteome strategies are increasingly used for detecting and validating protein biomarkers and therapeutic targets. Here, based on an in-depth proteome analysis of seven pancreatic cancer cell lines, we built a pancreas-specific mass spectrum library containing 10633 protein groups and 184551 peptides. The proteome difference among the seven pancreatic cancer cells was significant, especially for the divergent expression of proteins related to epithelial-mesenchymal transition (EMT). The spectra library was applied to explore the proteome difference of PANC-1 and BxPC-3 cells upon gemcitabine (GEM) treatment, and potential GEM targets were identified. The cytotoxicity test and GEM target analysis found that HPAC, CFPAC-1, and BxPC-3 were sensitive to GEM treatment, whereas PANC-1 and AsPC-1 were resistant. Finally, we found EMT was significant for CFPAC-1, AsPC-1, and PANC-1 cells, whereas BxPC-3 and HPAC cells showed more typical epithelial features. This library provides a valuable resource for in-depth proteomic analysis on pancreatic cancer cell lines, meeting the urgent demands for cell line-dependent protein differences and targeted drug analysis.

Measurement(s)	protein expression profiling
Technology Type(s)	Mass Spectrometry

A Substance P (SP)/Neurokinin-1 Receptor Axis Promotes Perineural Invasion of Pancreatic Cancer and Is Affected by lncRNA LOC389641

Perineural invasion (PNI) is considered to be a main reason for the poor prognosis of pancreatic cancer. In the present study, we analyzed the roles of substance P (SP)/neurokinin-1 receptor (NK-1R) and lncRNA LOC389641 in pancreatic cancer PNI. Pancreatic cancer cell lines BxPC-3 and MIAPaCa-2 were cocultured with SH-SY5Y cells and then stimulated with SP to simulate the in vivo influence of ganglia on pancreatic cancer. The BxPC-3 and MIAPaCa-2 cells were transfected with a neurokinin-1 receptor (NK-1R) overexpression vector, NK-1R silencing vector, LOC389641 overexpression vector, or LOC389641 silencing vector, respectively. The proliferative abilities of BxPC-3 and MIAPaCa-2 cells were assessed using the cell counting kit-8 and 5-ethynyl-2'-deoxyuridine (EdU) assays. Wound-healing and Transwell assays were performed to determine the migration and invasion abilities of the cells. When SP was added to the coculture system, it positively regulated cancer cell proliferation, migration, and PNI and significantly activated the NK-1R/Akt/NF-κB signaling pathway. Incubation with 100 nmol/L SP for 24 h was selected as the optimal condition for treatment. The activated NK-1R positively regulated the proliferation, migration, and invasion of pancreatic cancer cells. However, the levels of lncRNA LOC389641 and tumor necrosis factor receptor SF10A (TNFRSF10A) mRNA in BxPC-3 and MIAPaCa-2 cells were not affected by SP treatment. Overexpression or silencing of LOC389641 changed the effect of SP stimulation on pancreatic cancer PNI. When taken together, these results revealed that SP/NK-1R and LOC389641 promoted the progression of pancreatic cancer PNI. Moreover, we found that pancreatic cancer PNI promoted by the SP/NK-1R axis could be blocked by the TNFRSF10A/NF-κB pathway mediated by LOC389641.

The Impact of the COVID-19 Pandemic on Multidisciplinary Clinics: A High-Volume Pancreatic Cancer Center Experience

The unprecedented impact of the Sars-CoV-2 pandemic (COVID-19) has strained the healthcare system worldwide. The impact is even more profound on diseases requiring timely complex multidisciplinary care such as pancreatic cancer. Multidisciplinary care teams have been affected significantly in multiple ways as healthcare teams collectively acclimate to significant space limitations and shortages of personnel and supplies. As a result, many patients are now receiving suboptimal remote imaging for diagnosis, staging, and surgical planning for pancreatic cancer. In addition, the lack of face-to-face interactions between the physician and patient and between multidisciplinary teams has challenged patient safety, research investigations, and house staff education. In this study, we discuss how the COVID-19 pandemic has transformed our high-volume pancreatic multidisciplinary clinic, the unique challenges faced, as well as the potential benefits that have arisen out of this situation. We also reflect on its implications for the future during and beyond the pandemic as we anticipate a hybrid model that includes a component of virtual multidisciplinary clinics as a means to provide accessible world-class healthcare for patients who require complex oncologic management.

Circulating Fatty Objects and Their Preferential Presence in Pancreatic Cancer Patient Blood Samples

Human cancers are often complicated with increased incidences of blood vessel occlusion, which are mostly insensitive to anticoagulation therapy. We searched for causal factors of cancer-associated embolism. A total of 2,017 blood samples was examined for visible abnormalities. Examined were peripheral blood samples from cancer patients who were about to undergo surgical treatment for genitourinary, breast, gastrointestinal or abdominal tumors. Samples from ambulatory patients being treated for recurrent or castration-resistant prostate cancers were included in the study. The lipid-rich nature was studied with lipophilic stains and lipid panel analysis, while surface membrane was assessed with specific staining and antibody detection. We identified a new entity, lipid droplet-like objects or circulating fatty objects (CFOs), visible in the blood samples of many cancer patients, with the potential of causing embolism. CFOs were defined as lipid-rich objects with a membrane, capable of gaining in volume through interaction with peripheral blood mononuclear cells in ex vivo culture. Blood samples from pancreatic cancer patients were found to have the highest CFO incidence and largest CFO numbers. Most noticeably, CFOs from many pancreatic cancer samples presented as large clusters entangled in insoluble fiber networks, suggestive of intravascular clotting. This study identifies CFO as an abnormal entity in cancer patient blood, and a contributory factor to intravascular embolism during cancer development and progression.

Novel systemic treatment approaches for metastatic pancreatic cancer

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) has a 5-year overall survival rate of 10 %, emphasizing the need for more effective therapies, especially in metastatic disease. The immunosuppressive tumor microenvironment, poor vascularization, and dense tumor stroma typical for PDAC are hurdles that need to be overcome by novel drugs. Investigations are moving towards more targeted treatments including immunotherapy and cell-based approaches.

AREAS COVERED

This article reviews emerging drugs in clinical development for metastatic PDAC, focusing on cellular therapies and novel treatments targeting metabolism, tumor stroma, oncogenic pathways and immunosuppression. With immunotherapy and CAR T cell therapy on the rise in hematological malignancies, the transfer to solid tumors remains intriguing. Multiple exciting clinical trials investigating innovative therapeutic strategies for PDAC are currently ongoing and reviewed herein. ClinicalTrials.gov, conference abstracts and PubMed were searched in August 2021 and assessed for information on ongoing and published clinical studies.

EXPERT OPINION

With many challenges to overcome, the optimal therapy for patients with metastatic PDAC is likely to consist of a combination of different agents. We are slowly moving from entity-dependent approaches to ones more focused on molecular and pathological features. Increasingly personalized treatment plans tailored to each patient may be the future of PDAC therapy.

Deconstructing Pancreatic Cancer Using Next Generation-Omic Technologies-From Discovery to Knowledge-Guided Platforms for Better Patient Management

Comprehensive molecular landscaping studies reveal a potentially brighter future for pancreatic ductal adenocarcinoma (PDAC) patients. Blood-borne biomarkers obtained from minimally invasive "liquid biopsies" are now being trialled for early disease detection and to track responses to therapy. Integrated genomic and transcriptomic studies using resectable tumour material have defined intrinsic patient subtypes and actionable genomic segments that promise a shift towards genome-guided patient management. Multimodal mapping of PDAC using spatially resolved single cell transcriptomics and imaging techniques has identified new potentially therapeutically actionable cellular targets and is providing new insights into PDAC tumour heterogeneity. Despite these rapid advances, defining biomarkers for patient selection remain limited. This review examines the current PDAC cancer biomarker ecosystem (identified in tumour and blood) and explores how advances in single cell sequencing and spatially resolved imaging modalities are being used to uncover new targets for therapeutic intervention and are transforming our understanding of this difficult to treat disease.

Accurate Nodal Staging in Pancreatic Cancer in the Era of Neoadjuvant Therapy

BACKGROUND

Nodal disease is prognostic in pancreatic ductal adenocarcinoma (PDAC); however, optimal number of examined lymph nodes (ELNs) required to accurately stage nodal disease in the current era of neoadjuvant therapy remains unknown. The aim of the study was to evaluate the optimal number of ELNs in patients with neoadjuvantly treated PDAC.

METHODS

A retrospective study was performed on patients with PDAC undergoing resection following neoadjuvant treatment between 2011 and 2018. Clinicopathological data were extracted and analyzed.

RESULTS

Of 546 patients included, 232 (42.5%) had lymph node metastases. The median recurrence free survival (RFS) was 10.6 months (95% confidence interval: 9.7-11.7) and nodal disease was independently associated with shorter RFS (9.1 vs 11.9 months; p < 0.001). A cutoff of 22 ELNs was identified that stratified patients by RFS. Patients with N1 and N2 disease had similar median RFS (9.1 vs 8.9 months; p = 0.410). On multivariable analysis, ELN of ≥ 22 was found to be significantly associated with longer RFS among patients with N0 disease (14.2 vs. 10.9 months, p = 0.046). However, ELN has no impact on RFS for patients with N1/N2 disease (9.5 vs. 8.4 months, p = 0.190). Adjuvant therapy was associated with RFS only in patients with residual nodal disease.

CONCLUSIONS

Lymph node metastases remain prognostic in PDAC patients after neoadjuvant treatment. Among N0 patients, a cutoff of 22 ELN was associated with improved RFS and resulted in optimal nodal staging.

The role of coeliac axis resection in resected ductal adenocarcinoma of the distal pancreas: A result of tumour topography or a prognostic factor?

BACKGROUND

Whether coeliac axis resection (CAR) results from tumour topography or a prognostic factor for distal pancreatic ductal adenocarcinoma (PDAC) remains unclear. We aimed to compare the clinicopathological data between distal pancreatectomy with en bloc CAR (DP-CAR) and distal pancreatectomy plus splenectomy (DP-S) and analyse the prognostic factors.

METHODS

We retrospectively analysed clinicopathological data from 102 patients who underwent distal pancreatectomy for PDAC and the factors affecting disease-free survival (DFS) and overall survival (OS). Of these patients, 45 and 57 underwent DP-CAR and DP-S, respectively.

RESULTS

DP-CAR was associated with more operative challenges than DP-S: more portomesenteric vein resections (48.9% vs. 14.0%), longer operations (320 vs. 242 min), and greater estimated blood loss (EBL) (600 vs. 200 ml). DP-CAR had larger tumours (5 vs. 4 cm), more perineural invasion (91.1% vs. 73.7%), and more microscopically positive surgical margins (20% vs. 3.5%), compared to DP-S. The major complication was clinically relevant postoperative pancreatic fistula (20.6%). The median DFS was 15.8 months and the median OS was 20.1 months. CAR was not associated with DFS or OS. EBL>700 ml, lymphovascular invasion (LVI), and adjuvant chemotherapy independently affected DFS and OS.

CONCLUSION

DP-CAR was associated with larger tumours and more surgical challenges but not with poorer DFS and OS than DP-S. CAR was more likely to result from tumour topography rather than from an adverse prognostic factor for resected distal PDAC. EBL>700 ml, LVI, and adjuvant chemotherapy were independent factors affecting the survival of patients with distal PDAC who underwent surgical resection.

LINC00941 promotes glycolysis in pancreatic cancer by modulating the Hippo pathway

Pancreatic ductal adenocarcinoma (PDAC) is one of most lethal cancers and is projected to be the second leading cause of cancer deaths in the United States by 2030. The lack of effective treatment and increased incidence in PDAC encourage a deeper knowledge of PDAC progression. By analyzing a long noncoding RNA (lncRNA) dataset, we found that increased LINC00941 expression led to poor outcomes in PDAC patients. Furthermore, in vitro and in vivo experiments revealed that LINC00941 promoted PDAC cancer cell growth by enhancing aerobic glycolysis. Mechanistically, LINC00941 was found to interact with mammalian STE20-like protein kinase 1 (MST1), which facilitated the protein phosphatase 2A (PP2A)-mediated dephosphorylation of MST1, resulting in Hippo pathway activation and consequently, enhanced glycolysis in PDAC. These results suggest that LINC00941 plays a key role in regulating PDAC tumorigenesis, potentially highlighting novel avenues for PDAC therapy.

Treatment optimization of locally advanced and metastatic pancreatic cancer (Review)

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant tumor types, being the sixth leading cause of mortality worldwide and the fourth in Europe. Globally, it has a mortality/incidence ratio of 98%, and the 5‑year survival rate in Europe is only 3%. Although risk factors, such as obesity, diabetes mellitus, smoking, alcohol consumption and genetic factors, have been identified, the causes of PDAC remain elusive. Additionally, the only curative treatment for PDAC is surgery with negative margins. However, upon diagnosis, ~30% of the patients already present with locally advanced disease. In these cases, a multidisciplinary approach is required to improve disease‑related symptoms and prolong patient survival. In the present article, a comprehensive review of PDAC epidemiology, physiology and treatment is provided. Moreover, guidelines on patient treatment are suggested. Among the different available therapeutic options for the treatment of advanced PDAC, results are modest, most likely due to the complexity of the disease, and so the prognostic remains poor. Molecular approaches based on multi‑omics research are promising and will contribute to groundbreaking personalized medicine. Thus, economic investment that promotes research of pancreatic cancer will be critical to the development of more efficient diagnostic and treatment strategies.

Eukaryotic initiation factor 2 signaling behind neural invasion linked with lymphatic and vascular invasion in pancreatic cancer

Perineural invasion (PNI) is a typical poor prognostic factor in pancreatic ductal adenocarcinoma (PDAC). The mechanisms linking PNI to poor prognosis remain unclear. This study aimed to clarify what changes occurred alongside PNI in PDAC. A 128-patient cohort undergoing surgery for early-stage PDAC was evaluated. Subdivided into two groups, according to pathological state, a pancreatic nerve invasion (ne) score of less than three (from none to moderate invasion) was designated as the low-grade ne group. The high-grade (marked invasion) ne group (74 cases, 57.8%) showed a higher incidence of lymphatic metastasis (P = 0.002), a higher incidence of early recurrence (P = 0.004), decreased RFS (P < 0.001), and decreased DSS (P < 0.001). The severity of lymphatic (r = 0.440, P = 0.042) and venous (r = 0.610, P = 0.002) invasions was positively correlated with the ne score. Tumors having abundant stroma often displayed severe ne. Proteomics identified eukaryotic initiation factor 2 (EIF2) signaling as the most significantly enriched pathway in high-grade ne PDAC. Additionally, EIF2 signaling-related ribosome proteins decreased according to severity. Results showed that PNI is linked with lymphatic and vascular invasion in early-stage PDAC. Furthermore, the dysregulation of proteostasis and ribosome biogenesis can yield a difference in PNI severity.

Proteogenomic characterization of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

NEAT1/miR-101-dependent Up-regulation of DNA-PKcs Enhances Malignant Behaviors of Pancreatic Ductal Adenocarcinoma Cells

Background: Although we previously revealed that DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is overexpressed in pancreatic ductal adenocarcinoma (PDAC) and important for gemcitabine resistance, the role of DNA-PKcs in the progression and metastasis of PDAC remain unclear. To date, the upstream signaling events stimulating DNA-PKcs overexpression in PDAC are still not well characterized.

Methods: Expression of DNA-PKcs was measured by western blot. The levels of miRNA-101 and lncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) were detected by real-time PCR. Cell viability was determined by CCK-8. Cell migration and cell invasion were measured by transwell assay. The regulatory relationship between NEAT1 and miR-101 was determined by a luciferase assay.

Results: DNA-PKcs expression was significantly elevated in human PDAC tissues and cells. DNA-PKcs overexpression was correlated with TNM stage and lymph node metastasis. Higher expression of DNA-PKcs was closely correlated with patients of worse overall survival (OS). DNA-PKcs knockdown suppresses malignant behaviors of PDAC cells. Further study showed that miRNA-101 level was decreased in PDAC tissues and cells, which could be responsible for DNA-PKcs overexpression and DNA-PKcs mediated oncogenic actions in PDAC cells. Moreover, NEAT1 functions as an oncogene influencing cell proliferation, migration and invasion in part by serving as a competing endogenous RNA (ceRNAs) modulating miR-101 expression, leading to up-regulation of DNA-PKcs.

Conclusion: These findings suggest that NEAT1/miR-101-dependent up-regulation of DNA-PKcs promotes the malignant behaviors of PDAC cells. The NEAT1/miR-101/DNA-PKcs axis may serve as a viable prognostic marker and therapeutic target for PDAC.

Prognostic Significance of Microvascular Invasion in Pancreatic Ductal Adenocarcinoma: A Systematic Review and Meta-Analysis

BACKGROUND The incidence, pathogenesis, and prognostic effect of microvascular invasion on pancreatic ductal adenocarcinoma (PDAC) remain controversial. This study aimed to summarize the incidence, pathogenesis, role in clinical management, recurrence, and prognostic significance of microvascular invasion in PDAC. MATERIAL AND METHODS A literature review and meta-analysis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Systematic literature searches were conducted using PubMed and Google Scholar up to February 2021. RESULTS Seventeen studies were included in the meta-analysis. The incidence of microvascular invasion was 49.0% (95% confidence interval [CI], 43.8-54.5%) among PDAC patients who underwent surgery. The weighted multivariate Cox proportional hazards model hazard ratio for disease-free survival of 8 studies was 1.78 (95% CI 1.53-2.08, P<0.001), and there was no statistically significant difference between the subgroups (P=0.477). The hazard ratio for overall survival of 14 studies was 1.49 (95% CI 1.27-1.74, P<0.001), and there was no statistically significant difference between the subgroups (P=0.676). CONCLUSIONS Microvascular invasion occurred in nearly half of PDAC patients after surgery and was closely related to disease-free and overall survival. Understanding the role of microvascular invasion in PDAC will help provide more personalized and effective preoperative or postoperative strategies to achieve better survival outcomes.

A Novel miRNA-mRNA Axis Involves in Regulating Transcriptional Disorders in Pancreatic Adenocarcinoma

Background

Currently, there is still a lack of understanding about the mechanism and therapeutic targets of pancreatic adenocarcinoma (PAAD). The potential of miRNA-mRNA networks for the identification of regulatory mechanisms involved in PAAD development remains unexplored.

Methods

We compared differentially expressed miRNAs (DEMIs) and differentially expressed genes (DEGs) in PAAD and normal tissues from the Gene Expression Omnibus (GEO) database. Transcription factors (TFs) were obtained from FunRich. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs and DEMIs were implemented using Database for Annotation, Visualization and Integrated Discovery (DAVID). Then, key miRNAs and targeted mRNAs were identified by assessment of their expression and prognosis in UALCAN and Kaplan-Meier plotters. In the last step, the candidate miRNA-mRNA selected was confirmed by real-time quantitative polymerase chain reaction (qRT-PCR).

Results

We distinguished 62 significant DEMIs, 1314 upregulated DEGs, and 1110 downregulated DEGs. The top 10 TFs were identified. In total, there were 160 hub genes obtained by intersecting the set of 2224 predicted targets with the set of significant DEGs. And we selected 8 key miRNAs. Furthermore, low expression of miR-455-3p in PAAD tissue was closely connected with poor prognosis, and only 5 target mRNAs were predicted to be increased in PAAD tissue with poor prognosis. Therefore, a novel miRNA-hub gene regulatory network in PAAD was constructed. Finally, in vitro experiments indicated that miR-455-3p expression was decreased in PAAD sample. HOXC4, DLG4, DYNLL1 and FBXO45 were validated by qRT-PCR as highly probable targets of miR-455-3p.

Conclusion

A novel miRNA-mRNA axis has been discovered that may be involved in the regulation of transcriptional disorders and affected the survival of PAAD patients, which would provide a novel strategy for the treatment of PAAD.

The germline/somatic DNA damage repair gene mutations modulate the therapeutic response in Chinese patients with advanced pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a fatal disease with molecular heterogeneity, inducing differences in biological behavior, and therapeutic strategy. NGS profiles of pathogenic alterations in the Chinese PDAC population are limited. We conducted a retrospective study to investigate the predictive role of DNA damage repair (DDR) mutations in precision medicine.

METHODS

The NGS profiles were performed on resected tissues from 195 Chinese PDAC patients. Baseline clinical or genetic characteristics and survival status were collected. The Kaplan-Meier survival analyses were performed by the R version 3.6.1.

RESULTS

The main driver genes were KRAS, TP53, CDKN2A, and SMAD4. Advanced patients with KRAS mutation showed a worse OS than KRAS wild-type (p = 0.048). DDR pathogenic deficiency was identified in 30 (15.38%) of overall patients, mainly involving BRCA2 (n = 9, 4.62%), ATM (n = 8, 4.10%) and RAD50 genes (n = 3, 1.54%). No significance of OS between patients with or without DDR mutations (p = 0.88). But DDR mutation was an independent prognostic factor for survival analysis of advanced PDAC patients (p = 0.032). For DDR mutant patients, treatment with platinum-based chemotherapy (p = 0.0096) or olaparib (p = 0.018) respectively improved the overall survival. No statistical difference between tumor mutation burden (TMB) and DDR mutations was identified. Treatment of PD-1 blockades did not bring significantly improved OS to DDR-mutated patients than the naive DDR group (p = 0.14).

CONCLUSIONS

In this retrospective study, we showed the role of germline and somatic DDR mutation in predicting the efficacy of olaparib and platinum-based chemotherapy in Chinese patients. However, the value of DDR mutation in the prediction of hypermutation status and the sensitivity to the PD-1 blockade needed further investigation.

Ovarian Metastasis from Pancreatic Ductal Adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a high propensity for systemic dissemination. Ovarian metastases are rare and poorly described.

METHODS

We identified PDAC cases with ovarian metastasis from a prospectively maintained registry. We reported on the association between outcomes and clinicopathologic factors. Recurrence-free (RFS) and overall survival (OS) were calculated using Kaplan-Meier analysis.

RESULTS

Twelve patients with PDAC and synchronous or metachronous ovarian metastases were identified. Nine patients (75%) underwent pancreatectomy for localized PDAC and developed metachronous ovarian recurrence. The median OS for all patients was 25.4 (IQR:15.4-82.9) months. For the nine patients with metachronous ovarian metastasis, the median RFS and OS were 14.2 (IQR:7.2-58.3) and 44.6 (IQR:18.6-82.9) months, respectively. Nodal disease, poor grade, vascular invasion in the pancreatic primary, and bilateral ovarian disease tended to confer worse outcomes.

CONCLUSION

Patients with resected PDAC and ovarian recurrence tend to have a comparable disease course to more common patterns of recurrence. Primaries with nodal disease, poorer grade, vascular invasion, and bilateral ovarian disease were indicative of more aggressive disease biology. The ideal management remains largely unknown, and future collaborative efforts should optimize therapeutic strategies.

Desmoplastic Crosstalk in Pancreatic Ductal Adenocarcinoma Is Reflected by Different Responses of Panc-1, MIAPaCa-2, PaTu-8902, and CAPAN-2 Cell Lines to Cancer-associated/Normal Fibroblasts

BACKGROUND/AIM

Pancreatic ductal adenocarcinoma (PDAC) still represents one of the most aggressive cancers. Understanding of the epithelial-mesenchymal crosstalk as a crucial part of the tumor microenvironment should pave the way for therapies to improve patient survival rates. Well-established cell lines present a useful and reproducible model to study PDAC biology. However, the tumor-stromal interactions between cancer cells and cancer-associated fibroblasts (CAFs) are still poorly understood.

MATERIALS AND METHODS

We studied interactions between four PDAC cell lines (Panc-1, CAPAN-2, MIAPaCa-2, and PaTu-8902) and conditioned media derived from primary cultures of normal fibroblasts/PDAC-derived CAFs (PANFs).

RESULTS

When the tested PDAC cell lines were stimulated by PANF-derived conditioned media, the most aggressive behavior was acquired by the Panc-1 cell line (increased number and size of colonies, remaining expression of vimentin and keratin 8 as well as increase of epithelial-to-mesenchymal polarization markers), whereas PaTu-8902 cells were rather inhibited. Of note, administration of the conditioned media to MIAPaCa-2 cells resulted in an inverse effect on the size and number of colonies, whereas CAPAN-2 cells were rather stimulated. To explain the heterogeneous pattern of the observed PDAC crosstalk at the in vitro level, we further compared the phenotype of primary cultures of cells derived from ascitic fluid with that of the tested PDAC cell lines, analyzed tumor samples of PDAC patients, and performed gene expression profiling of PANFs. Immuno-cyto/histo-chemical analysis found specific phenotype differences within the group of examined patients and tested PDAC cell lines, whereas the genomic approach in PANFs found the key molecules (IL6, IL8, MFGE8 and periostin) that may contribute to the cancer aggressive behavior.

CONCLUSION

The desmoplastic patient-specific regulation of cancer cells by CAFs (also demonstrated by the heterogeneous response of PDAC cell lines to fibroblasts) precludes simple targeting and development of an effective treatment strategy and rather requires establishment of an individualized tumor-specific treatment protocol.

Defining a minimum number of examined lymph nodes improves the prognostic value of lymphadenectomy in pancreas ductal adenocarcinoma

BACKGROUND

Lymph node (LN) metastasis is associated with decreased survival following resection for pancreatic ductal adenocarcinoma (PDAC). In N0 disease, increasing total evaluated LN (ELN) correlates with improved outcomes suggesting patients may be understaged when LNs are undersampled. We aim to assess the optimal number of examined lymph nodes (ELN) following pancreatectomy.

METHODS

Data from 1837 patients undergoing surgery were prospectively collected. The binomial probability law was utilized to analyze the minimum number of examined LNs (minELN) and accurately characterize each histopathologic stage. LN ratio (LNR) was compared to American Joint Committee on Cancer (AJCC) guidelines.

RESULTS

As ELN total increased, the likelihood of finding node positive disease increased. An evaluation based upon the binomial probability law suggested an optimal minELN of 12 for accurate AJCC N staging. As the number of ELNs increased, the discriminatory capacity of alternative strategies to characterize LN disease exceeded that offered by AJCC N stage.

CONCLUSION

This is the first study dedicated to optimizing histopathologic staging in PDAC using models of minELN informed by the binomial probability law. This study highlights two separate cutoffs for ELNs depending upon prognostic goal and validates that 12 LNs are adequate to determine AJCC N stage for the majority of patients.

[The ambiguous role of the inflammatory micromilieu in solid tumors]

BACKGROUND

Besides host defense against infections, the main function of the immune system is to eliminate tumor cells. Therefore, nearly, all solid tumors have a heterogeneous fibro-inflammatory microenvironment, which consists of myofibroblastic cells, extracellular matrix components, and infiltrates from various types of immune cell. In particular, pancreatic ductal adenocarcinoma is a prototype of a tumor with a pronounced inflammatory microenvironment, in which the majority of the tumor mass consists of nonneoplastic stromal and immune cells. Our own data and data from the literature indicate a protective role of tumor-infiltrating T cells for the host. On the other hand, we were able to show that a defined T cell subpopulation paradoxically promotes the progression of the tumor. Our investigations now focus on these cells, known as "Th17," in the tumor microenvironment.

OBJECTIVES

To elucidate the mechanisms of the infiltrated immune cells and their mediators in the tumor microenvironment.

MATERIALS AND METHODS

Human pancreatic cancer tissue was used for (immune) histological staining and morphometric analysis and the results were correlated with clinical parameters and with diffusion-weighted magnetic resonance imaging images. The molecular mechanisms were analyzed in cell culture approaches using human tumor cells and human immune cells. With molecular biological methods and functional assays cell growth, invasion and colony formation were assessed. The in vivo correlation of the results and functional interventions were tested in murine and avian (xenograft) models.

RESULTS AND CONCLUSION

Tumor-infiltrating immune cells of type Th17 and their mediators promoted the progression of the tumor depending on density, activation status, and cytokine profile. On molecular level, we identified a Th17-mediated increase of tumor cell migration and invasion, an increased neoangiogenesis, as well as a reorganization of the tumor stroma and microarchitecture. The data show that the progression of pancreatic cancer, depends on the status of activation and the cytokine profile of the infiltrated T cells.

The genetics of ductal adenocarcinoma of the pancreas in the year 2020: dramatic progress, but far to go

The publication of the "Pan-Cancer Atlas" by the Pan-Cancer Analysis of Whole Genomes Consortium, a partnership formed by The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), provides a wonderful opportunity to reflect on where we stand in our understanding of the genetics of pancreatic cancer, as well as on the opportunities to translate this understanding to patient care. From germline variants that predispose to the development of pancreatic cancer, to somatic mutations that are therapeutically targetable, genetics is now providing hope, where there once was no hope, for those diagnosed with pancreatic cancer.

Desmin and CD31 immunolabeling for detecting venous invasion of the pancreatobiliary tract cancers

Although venous invasion (VI) is a poor prognostic factor for patients with pancreatobiliary tract cancers, its histopathologic characteristics have not been well described. We evaluated the patterns of VI and the added benefit provided by CD31, desmin, and dual CD31‒desmin immunolabeling for identification of VI. We included 120 surgically resected pancreatobiliary tract cancer cases—59 cases as a test set with known VI and 61 cases as a validation set without information of VI. VI was classified into three patterns: intraepithelial neoplasia-like (IN-like), conventional, and destructive. Hematoxylin and eosin (H&E) staining and CD31, desmin, and dual CD31‒desmin immunolabeling were performed. Foci number and patterns of VI were compared with the test and validation sets. More foci of VI were detected by single CD31 (P = 0.022) than H&E staining in the test set. CD31 immunolabeling detected more foci of the conventional pattern of VI, and desmin immunolabeling detected more foci of the destructive pattern (all, P < 0.001). Dual CD31‒desmin immunolabeling identified more foci of VI (P = 0.012) and specifically detected more foci of IN-like (P = 0.045) and destructive patterns (P < 0.001) than H&E staining in the validation set. However, dual CD31‒desmin immunolabeling was not helpful for detecting the conventional pattern of VI in the validation set. Patients with VI detected by dual CD31‒desmin immunolabeling had shorter disease-free survival (P <0.001) than those without VI. VI detected by dual CD31‒desmin immunolabeling was a worse prognostic indicator (P = 0.009). More foci of VI could be detected with additional single CD31 or dual CD31‒desmin immunolabeling. The precise evaluation of VI with dual CD31‒desmin immunolabeling can provide additional prognostic information for patients with surgically resected pancreatobiliary tract cancers.