The metabolic features of normal pancreas and pancreatic adenocarcinoma: preliminary result of in vivo proton magnetic resonance spectroscopy at 3.0 T. J Comput Assist Tomogr. 2011;35:539-543. [PMID: 21926845 DOI: 10.1097/rct.0b013e318227a545]

Alterations in genes involved in glycolysis and hypoxia affect the prognosis of pancreatic cancer

Purpose

To construct a prognostic model for pancreatic cancer based on glycolytic and hypoxic metabolic subtypes. To analyze the biological characteristics of these subtypes and explore potential therapeutic options.

Methods

We obtained mRNA, simple nucleotide variation (SNP), and clinical data for pancreatic cancer from The Cancer Genome Atlas (TCGA). Patients were classified into four metabolic subtypes. We focused on glycolysis and hypoxia subtypes. Single-sample gene set enrichment analysis (ssGSEA) assessed immune cell infiltration. We evaluated the effects of immunotherapy and chemotherapy on these subtypes. Cox regression and random survival forest algorithms were used to build a prognostic model. Validation was performed using data from the International Cancer Genome Consortium (ICGC) and ArrayExpress database.

Results

We identified four subtypes. Kaplan-Meier survival analysis showed the glycolytic subtype had the longest survival, while the hypoxic subtype had the shortest. The glycolytic subtype exhibited higher immune cell infiltration. Immunotherapy and chemotherapy appeared more beneficial for the glycolytic subtype. KRAS mutations were more frequent in the hypoxic subtype. Our prognostic model indicated a worse prognosis for high-risk groups, validated by external data.

Conclusion

The glycolytic metabolic subtype of pancreatic cancer is associated with longer survival and better response to chemotherapy and immunotherapy compared to the hypoxic subtype.

Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer

Pancreatic cancer (PC) is burdened with a low 5-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using ultra-high-performance liquid chromatography with a high-resolution mass spectrometer (UHPLC-HRMS) to identify and validate metabolite biomarkers from paired tissue samples of PC patients. Results showed that the metabolic reprogramming of PC mainly featured enhanced amino acid metabolism and inhibited sphingolipid metabolism, which satisfied the energy and biomass requirements for tumorigenesis and progression. The altered metabolism results were confirmed by the significantly changed gene expressions in PC tissues from an online database. A metabolites biomarker panel (six metabolites) was identified for the differential diagnosis between PC tumors and normal pancreatic tissues. The panel biomarker distinguished tumors from normal pancreatic tissues in the discovery group with an area under the curve (AUC) of 1.0 (95%CI, 1.000−1.000). The biomarker panel cutoff was 0.776. In the validation group, an AUC of 0.9000 (95%CI = 0.782–1.000) using the same cutoff, successfully validated the biomarker signature. Moreover, this metabolites panel biomarker had a great capability to predict the overall survival (OS) of PC. Taken together, this metabolomics method identifies and validates metabolite biomarkers that can diagnose the onsite progression and prognosis of PC precisely and sensitively in a clinical setting. It may also help clinicians choose proper therapeutic interventions for different PC patients and improve the survival of PC patients.

Tumor Microenvironment Features and Chemoresistance in Pancreatic Ductal Adenocarcinoma: Insights into Targeting Physicochemical Barriers and Metabolism as Therapeutic Approaches

Currently, the median overall survival of PDAC patients rarely exceeds 1 year and has an overall 5-year survival rate of about 9%. These numbers are anticipated to worsen in the future due to the lack of understanding of the factors involved in its strong chemoresistance. Chemotherapy remains the only treatment option for most PDAC patients; however, the available therapeutic strategies are insufficient. The factors involved in chemoresistance include the development of a desmoplastic stroma which reprograms cellular metabolism, and both contribute to an impaired response to therapy. PDAC stroma is composed of immune cells, endothelial cells, and cancer-associated fibroblasts embedded in a prominent, dense extracellular matrix associated with areas of hypoxia and acidic extracellular pH. While multiple gene mutations are involved in PDAC initiation, this desmoplastic stroma plays an important role in driving progression, metastasis, and chemoresistance. Elucidating the mechanisms underlying PDAC resistance are a prerequisite for designing novel approaches to increase patient survival. In this review, we provide an overview of the stromal features and how they contribute to the chemoresistance in PDAC treatment. By highlighting new paradigms in the role of the stromal compartment in PDAC therapy, we hope to stimulate new concepts aimed at improving patient outcomes.

The Intricate Metabolism of Pancreatic Cancers

Currently, approximately 95% of pancreatic cancers are pancreatic ductal adenocarcinomas (PDAC), which are the most aggressive form and the fourth leading cause of cancer death with extremely poor prognosis [1]. Poor prognosis is primarily attributed to the late diagnosis of the disease when patients are no longer candidates for surgical resection [2]. Cancer cells are dependent on the oncogenes that allow them to proliferate limitlessly. Thus, targeting the expression of known oncogenes in pancreatic cancer has been shown to lead to more effective treatment [3]. This chapter discusses the complexity of metabolic features in pancreatic cancers. In order to comprehend the heterogeneous nature of cancer metabolism fully, we need to take into account the close relationship between cancer metabolism and genetics. Gene expression varies tremendously, not only among different types of cancers but also within the same type of cancer among different patients. Cancer metabolism heterogeneity is often prompted and perpetuated not only by mutations in oncogenes and tumor-suppressor genes but also by the innate diversity of the tumor microenvironment. Much effort has been focused on elucidating the genetic alterations that correlate with disease progression and treatment response [4, 5]. However, the precise mechanisms by which tumor metabolism contributes to cancer growth, survival, mobility, and aggressiveness represent a functional readout of tumor progression (Fig. 1).

Seven Glycolysis-Related Genes Predict the Prognosis of Patients With Pancreatic Cancer

Objectives

To identify the key glycolysis-related genes (GRGs) in the occurrence and development of pancreatic ductal carcinoma (PDAC), and to construct a glycolysis-related gene model for predicting the prognosis of PDAC patients.

Methodology

Pancreatic ductal carcinoma (PDAC) data and that of normal individuals were downloaded from the TCGA database and Genotype-Tissue Expression database, respectively. GSEA analysis of glycolysis-related pathways was then performed on PDAC data to identify significantly enriched GRGs. The genes were combined with other patient’s clinical information and used to construct a glycolysis-related gene model using cox regression analysis. The model was further evaluated using data from the validation group. Mutations in the model genes were subsequently identified using the cBioPortal. In the same line, the expression levels of glycolysis related model genes in PDAC were analyzed and verified using immunohistochemical images. Model prediction for PDAC patients with different clinical characteristics was then done and the relationship between gene expression level, clinical stage and prognosis further discussed. Finally, a nomogram map of the predictive model was constructed to evaluate the prognosis of patients with PDAC.

Results

GSEA results of the training set revealed that genes in the training set were significantly related to glycolysis pathway and iconic glycolysis pathway. There were 108 differentially expressed GRGs. Among them, 29 GRGs were closely related to prognosis based on clinical survival time. Risk regression analysis further revealed that there were seven significantly expressed glycolysis related genes. The genes were subsequently used to construct a predictive model. The model had an AUC value of more than 0.85. It was also significantly correlated with survival time. Further expression analysis revealed that CDK1, DSC2, ERO1A, MET, PYGL, and SLC35A3 were highly expressed in PDAC and CHST12 was highly expressed in normal pancreatic tissues. These results were confirmed using immunohistochemistry images of normal and diseases cells. The model could effectively evaluate the prognosis of PDAC patients with different clinical characteristics.

Conclusion

The constructed glycolysis-related gene model effectively predicts the occurrence and development of PDAC. As such, it can be used as a prognostic marker to diagnose patients with PDAC.

Water and Collagen Content Are High in Pancreatic Cancer: Implications for Quantitative Metabolic Imaging

In magnetic resonance metabolic imaging, signal from the water content is frequently used for normalization to derive quantitative or semi-quantitative values of metabolites in vivo or ex vivo tumors and tissues. Ex vivo high-resolution metabolic characterization of tumors with magnetic resonance spectroscopy (MRS) provides valuable information that can be used to drive the development of noninvasive MRS biomarkers and to identify metabolic therapeutic targets. Variability in the water content between tumor and normal tissue can result in over or underestimation of metabolite concentrations when assuming a constant water content. Assuming a constant water content can lead to masking of differences between malignant and normal tissues both in vivo and ex vivo. There is a critical need to develop biomarkers to detect pancreatic cancer and to develop novel treatments. Our purpose here was to determine the differences in water content between pancreatic tumors and normal pancreatic tissue as well as other organs to accurately quantify metabolic differences when using the water signal for normalization. Our data identify the importance of factoring the differences in water content between tumors and organs. High-resolution proton spectra of tumors and pancreatic tissue extracts normalized to the water signal, assuming similar water content, did not reflect the significantly increased total choline observed in tumors in vivo without factoring the differences in water content. We identified significant differences in the collagen 1 content between Panc1 and BxPC3 pancreatic tumors and the pancreas that can contribute to the differences in water content that were observed.

MiR-135 suppresses glycolysis and promotes pancreatic cancer cell adaptation to metabolic stress by targeting phosphofructokinase-1

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers. It thrives in a nutrient-poor environment; however, the mechanisms by which PDAC cells undergo metabolic reprogramming to adapt to metabolic stress are still poorly understood. Here, we show that microRNA-135 is significantly increased in PDAC patient samples compared to adjacent normal tissue. Mechanistically, miR-135 accumulates specifically in response to glutamine deprivation and requires ROS-dependent activation of mutant p53, which directly promotes miR-135 expression. Functionally, we found miR-135 targets phosphofructokinase-1 (PFK1) and inhibits aerobic glycolysis, thereby promoting the utilization of glucose to support the tricarboxylic acid (TCA) cycle. Consistently, miR-135 silencing sensitizes PDAC cells to glutamine deprivation and represses tumor growth in vivo. Together, these results identify a mechanism used by PDAC cells to survive the nutrient-poor tumor microenvironment, and also provide insight regarding the role of mutant p53 and miRNA in pancreatic cancer cell adaptation to metabolic stresses.

Identification of key regulators of pancreatic ductal adenocarcinoma using bioinformatics analysis of microarray data

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer, and its etiology remains largely unknown. This study aimed to screen a panel of key genes and to identify their potential impact on the molecular pathways associated with the development of PDAC. Four gene expression profiles, GSE28735, GSE15471, GSE102238, and GSE43795, were downloaded from the Gene Expression Omnibus (GEO) database. The intersection of the differentially expressed genes (DEGs) in each dataset was obtained using Venn analysis. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis were subsequently carried out. To screen for hub genes, a protein-protein interaction (PPI) network was constructed.The intersection of the DEGs revealed 7 upregulated and 9 downregulated genes. Upon relaxation of the selection criteria, 58 upregulated and 32 downregulated DEGs were identified. The top 5 biological processes identified by GO analysis involved peptide cross-linking, extracellular matrix (ECM) disassembly, regulation of the fibroblast growth factor receptor signaling pathway, mesoderm morphogenesis, and lipid digestion. The results of KEGG analysis revealed that the DEGs were significantly enriched in pathways involved in protein digestion and absorption, ECM-receptor interaction, pancreatic secretion, and fat digestion and absorption. The top ten hub genes were identified based on the PPI network.In conclusion, the identified hub genes may contribute to the elucidation of the underlying molecular mechanisms of PDAC and serve as promising candidates that can be utilized for the early diagnosis and prognostic prediction of PDAC. However, further experimental validation is required to confirm these results.

Functional imaging in pancreatic disease

In addition to the classical morphological evaluation of pancreatic disease, the constant technological advances in imaging techniques based fundamentally on computed tomography and magnetic resonance imaging have enabled the quantitative functional and molecular evaluation of this organ. In many cases, this imaging-based information results in substantial changes to patient management and can be a fundamental tool for the development of biomarkers. The aim of this article is to review the role of emerging functional and molecular techniques based on computed tomography and magnetic resonance imaging in the evaluation of pancreatic disease.

The plasticity of pancreatic cancer metabolism in tumor progression and therapeutic resistance

Pancreatic ductal adenocarcinoma (PDA) is an aggressive cancer that is highly refractory to the current standards of care. The difficulty in treating this disease is due to a number of different factors, including altered metabolism. In PDA, the metabolic rewiring favors anabolic reactions which supply the cancer cell with necessary cellular building blocks for unconstrained growth. Furthermore, PDA cells display high levels of basal autophagy and macropinocytosis. KRAS is the driving oncogene in PDA and many of the metabolic changes are downstream of its activation. Together, these unique pathways for nutrient utilization and acquisition result in metabolic plasticity enabling cells to rapidly adapt to nutrient and oxygen fluctuations. This remarkable adaptability has been implicated as a cause of the intense therapeutic resistance. In this review, we discuss metabolic pathways in PDA tumors and highlight how they contribute to the pathogenesis and treatment of the disease.

Proton magnetic resonance spectroscopy in oncology: the fingerprints of cancer?

Abnormal metabolism is a key tumor hallmark. Proton magnetic resonance spectroscopy (1H-MRS) allows measurement of metabolite concentration that can be utilized to characterize tumor metabolic changes. 1H-MRS measurements of specific metabolites have been implemented in the clinic. This article performs a systematic review of image acquisition and interpretation of 1H-MRS for cancer evaluation, evaluates its strengths and limitations, and correlates metabolite peaks at 1H-MRS with diagnostic and prognostic parameters of cancer in different tumor types.

Employing Metabolism to Improve the Diagnosis and Treatment of Pancreatic Cancer

Pancreatic ductal adenocarcinoma is on pace to become the second leading cause of cancer-related death. The high mortality rate results from a lack of methods for early detection and the inability to successfully treat patients once diagnosed. Pancreatic cancer cells have extensively reprogrammed metabolism, which is driven by oncogene-mediated cell-autonomous pathways, the unique physiology of the tumor microenvironment, and interactions with non-cancer cells. In this review, we discuss how recent efforts delineating rewired metabolic networks in pancreatic cancer have revealed new in-roads to develop detection and treatment strategies for this dreadful disease.

Energy sources identify metabolic phenotypes in pancreatic cancer

Metabolic reprogramming is one of the emerging hallmarks of cancers. As a highly malignant tumor, pancreatic ductal adenocarcinoma (PDA) is not only a metabolic disease but also a heterogeneous disease. Heterogeneity induces PDA dependence on distinct nutritive substrates, thereby inducing different metabolic phenotypes. We stratified PDA into four phenotypes with distinct types of energy metabolism, including a Warburg phenotype, a reverse Warburg phenotype, a glutaminolysis phenotype, and a lipid-dependent phenotype. The four phenotypes possess distinct metabolic features and reprogram their metabolic pathways to adapt to stress. The metabolic type present in PDA should prompt differential imaging and serologic metabolite detection for diagnosis and prognosis. The targeting of an individual metabolic phenotype with corresponding metabolic inhibitors is considered a promising therapeutic approach and, in combination with chemotherapy, is expected to be a novel strategy for PDA treatment.

Clinical Imaging of Tumor Metabolism with ¹H Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is a noninvasive functional technique to evaluate the biochemical behavior of human tissues. This property has been widely used in assessment and therapy monitoring of brain tumors. MRS studies can be implemented outside the brain, with successful and promising results in the evaluation of prostate and breast cancer, although still with limited reproducibility. As a result of technical improvements, malignancies of the musculoskeletal system and abdominopelvic organs can benefit from the molecular information that MRS provides. The technical challenges and main applications in oncology of (1)H MRS in a clinical setting are the focus of this review.

Combining in Vitro Diagnostics with in Vivo Imaging for Earlier Detection of Pancreatic Ductal Adenocarcinoma: Challenges and Solutions

Pancreatic ductal adenocarcinoma (PDAC) is the fourth-leading cause of cancer-related death in the United States and is associated with a dismal prognosis, particularly when diagnosed at an advanced stage. Overall survival is significantly improved if PDAC is detected at an early stage prior to the onset of symptoms. At present, there is no suitable screening strategy for the general population. Available diagnostic serum markers are not sensitive or specific enough, and clinically available imaging modalities are inadequate for visualizing early-stage lesions. In this article, the role of currently available blood biomarkers and imaging tests for the early detection of PDAC will be reviewed. Also, the emerging biomarkers and molecularly targeted imaging agents being developed to improve the specificity of current imaging modalities for PDAC will be discussed. A strategy incorporating blood biomarkers and molecularly targeted imaging agents could lead to improved screening and earlier detection of PDAC in the future. (©) RSNA, 2015.

Pancreatic Cancer Metabolism: Breaking It Down to Build It Back Up

How do cancer cells escape tightly controlled regulatory circuits that link their proliferation to extracellular nutrient cues? An emerging theme in cancer biology is the hijacking of normal stress response mechanisms to enable growth even when nutrients are limiting. Pancreatic ductal adenocarcinoma (PDA) is the quintessential aggressive malignancy that thrives in nutrient-poor, hypoxic environments. PDAs overcome these limitations through appropriation of unorthodox strategies for fuel source acquisition and utilization. In addition, the interplay between evolving PDA and whole-body metabolism contributes to disease pathogenesis. Deciphering how these pathways function and integrate with one another can reveal novel angles of therapeutic attack.

SIGNIFICANCE

Alterations in tumor cell and systemic metabolism are central to the biology of pancreatic cancer. Further investigation of these processes will provide important insights into how these tumors develop and grow, and suggest new approaches for its detection, prevention, and treatment.

Metabolic imaging of pancreatic ductal adenocarcinoma detects altered choline metabolism

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal disease that develops relatively symptom-free and is therefore advanced at the time of diagnosis. The absence of early symptoms and effective treatments has created a critical need for identifying and developing new noninvasive biomarkers and therapeutic targets.

EXPERIMENTAL DESIGN

We investigated the metabolism of a panel of PDAC cell lines in culture and noninvasively in vivo with (1)H magnetic resonance spectroscopic imaging (MRSI) to identify noninvasive biomarkers and uncover potential metabolic targets.

RESULTS

We observed elevated choline-containing compounds in the PDAC cell lines and tumors. These elevated choline-containing compounds were easily detected by increased total choline (tCho) in vivo, in spectroscopic images obtained from tumors. Principal component analysis of the spectral data identified additional differences in metabolites between immortalized human pancreatic cells and neoplastic PDAC cells. Molecular characterization revealed overexpression of choline kinase (Chk)-α, choline transporter 1 (CHT1), and choline transporter-like protein 1 (CTL1) in the PDAC cell lines and tumors.

CONCLUSIONS

Collectively, these data identify new metabolic characteristics of PDAC and reveal potential metabolic targets. Total choline detected with (1)H MRSI may provide an intrinsic, imaging probe-independent biomarker to complement existing techniques in detecting PDAC. The expression of Chk-α, CHT1, and CTL1 may provide additional molecular markers in aspirated cytological samples.

HR-MAS MRS of the pancreas reveals reduced lipid and elevated lactate and taurine associated with early pancreatic cancer

The prognosis for patients with pancreatic cancer is extremely poor, as evidenced by the disease's five-year survival rate of ~5%. New approaches are therefore urgently needed to improve detection, treatment, and monitoring of pancreatic cancer. MRS-detectable metabolic changes provide useful biomarkers for tumor detection and response-monitoring in other cancers. The goal of this study was to identify MRS-detectable biomarkers of pancreatic cancer that could enhance currently available imaging approaches. We used (1) H high-resolution magic angle spinning MRS to probe metabolite levels in pancreatic tissue samples from mouse models and patients. In mice, the levels of lipids dropped significantly in pancreata with lipopolysaccharide-induced inflammation, in pancreata with pre-cancerous metaplasia (4 week old p48-Cre;LSL-Kras(G12D) mice), and in pancreata with pancreatic intraepithelial neoplasia, which precedes invasive pancreatic cancer (8 week old p48-Cre LSL-Kras(G12D) mice), to 26 ± 19% (p = 0.03), 19 ± 16% (p = 0.04), and 26 ± 10% (p = 0.05) of controls, respectively. Lactate and taurine remained unchanged in inflammation and in pre-cancerous metaplasia but increased significantly in pancreatic intraepithelial neoplasia to 266 ± 61% (p = 0.0001) and 999 ± 174% (p < 0.00001) of controls, respectively. Importantly, analysis of patient biopsies was consistent with the mouse findings. Lipids dropped in pancreatitis and in invasive cancer biopsies to 29 ± 15% (p = 0.01) and 26 ± 38% (p = 0.02) of normal tissue. In addition, lactate and taurine levels remained unchanged in inflammation but rose in tumor samples to 244 ± 155% (p = 0.02) and 188 ± 67% (p = 0.02), respectively, compared with normal tissue. Based on these findings, we propose that a drop in lipid levels could serve to inform on pancreatitis and cancer-associated inflammation, whereas elevated lactate and taurine could serve to identify the presence of pancreatic intraepithelial neoplasia and invasive tumor. Our findings may help enhance current imaging methods to improve early pancreatic cancer detection and monitoring.

The complex landscape of pancreatic cancer metabolism

Pancreatic ductal adenocarcinomas (PDA) are extremely aggressive cancers and currently available therapies are only minimally effective in treating this disease. Tackling this devastating cancer has been a major challenge to the scientific and medical communities, in part due to its intense therapeutic resistance. One of the aspects of this tumor that contributes to its aggressive behavior is its altered cellular metabolism. Indeed, PDA cells seem to possess the ability to adapt their metabolism to the particular environment to which they are exposed, including utilizing diverse fuel sources depending on their availability. Moreover, PDA tumors are efficient at recycling various metabolic substrates through activation of different salvage pathways such as autophagy and macropinocytosis. Together, these diverse metabolic adaptations allow PDA cells to survive and thrive in harsh environments that may lack nutrients and oxygen. Not surprisingly, given its central role in the pathogenesis of this tumor, oncogenic Kras plays a critical role in much of the metabolic reprogramming seen in PDA. In this review, we discuss the metabolic landscape of PDA tumors, including the molecular underpinnings of the key regulatory nodes, and describe how such pathways can be exploited for future diagnostic and therapeutic approaches.

Morphological and functional evaluation of chronic pancreatitis with magnetic resonance imaging

Magnetic resonance imaging (MRI) techniques for assessment of morphology and function of the pancreas have been improved dramatically the recent years and MRI is very often used in diagnosing and follow-up of chronic pancreatitis (CP) patients. Standard MRI including fat-suppressed T1-weighted and T2-weighted imaging techniques reveal decreased signal and glandular atrophy of the pancreas in CP. In contrast-enhanced MRI of the pancreas in CP the pancreatic signal is usually reduced and delayed due to decreased perfusion as a result of chronic inflammation and fibrosis. Thus, morphological changes of the ductal system can be assessed by magnetic resonance cholangiopancreatography (MRCP). Furthermore, secretin-stimulated MRCP is a valuable technique to evaluate side branch pathology and the exocrine function of the pancreas and diffusion weighted imaging can be used to quantify both parenchymal fibrotic changes and the exocrine function of the pancreas. These standard and advanced MRI techniques are supplementary techniques to reveal morphological and functional changes of the pancreas in CP. Recently, spectroscopy has been used for assessment of metabolite concentrations in-vivo in different tissues and may have the potential to offer better tissue characterization of the pancreas. Hence, the purpose of the present review is to provide an update on standard and advanced MRI techniques of the pancreas in CP.

Advances in magnetic resonance molecular and functional imaging to diagnose pancreatic cancer

Pancreatic cancer has a high mortality rate, which is generally related to the initial diagnosis coming at late stage disease combined with a lack of effective diagnostic techniques. Over the past few years, molecular-functional imaging, which can be defined as the in vivo characterization and measurement of biologic processes at the molecular and gene levels, has developed rapidly and allows diagnosing pancreatic cancer more early and specifically. Magnetic resonance (MR) imaging is widely used for molecular imaging because of the high spatial resolution. This paper reviews recent advances in MR molecular and functional imaging to diagnose pancreatic cancer.