A Novel Multivariate Index for Pancreatic Cancer Detection Based On the Plasma Free Amino Acid Profile

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

Quantitative Metabolomics and Lipoprotein Analysis of PDAC Patients Suggests Serum Marker Categories for Pancreatic Function, Pancreatectomy, Cancer Metabolism, and Systemic Disturbances

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose in the early stages and lacks reliable biomarkers. The scope of this project was to establish quantitative nuclear magnetic resonance (NMR) spectroscopy to comprehensively study blood serum alterations in PDAC patients. Serum samples from 34 PDAC patients obtained before and after pancreatectomy as well as 83 age- and sex-matched control samples from healthy donors were analyzed with in vitro diagnostics research (IVDr) proton NMR spectroscopy at 600 MHz. Uni- and multivariate statistics were applied to identify significant biofluid alterations. We identified 29 significantly changed metabolites and 98 lipoproteins when comparing serum from healthy controls with those of PDAC patients. The most prominent features were assigned to (i) markers of pancreatic function (e.g., glucose and blood triglycerides), (ii) markers related to surgery (e.g., ketone bodies and blood cholesterols), (iii) PDAC-associated markers (e.g., amino acids and creatine), and (iv) markers for systemic disturbances in PDAC (e.g., gut metabolites DMG, TMAO, DMSO2, and liver lipoproteins). Quantitative serum NMR spectroscopy is suited as a diagnostic tool to investigate PDAC. Remarkably, 2-hydroxybutyrate (2-HB) as a previously suggested marker for insulin resistance was found in extraordinarily high levels only after pancreatectomy, suggesting this metabolite is the strongest marker for pancreatic loss of function.

Upregulation of BRCA1 and 2 protein expression is associated with dysregulation in amino acids profiles in breast cancer

BACKGROUND

The prevalence of breast cancer (BC) is high among cancers in Egypt, ranking it the most common cause of cancer mortality in women. BRCA1 and BRCA2 tumor suppressors proteins have a specific relationship with BC. Plasma free amino acids levels (PFAAs) have been reported to exhibit altered profiles among cancer patients. Thus, the present study aims to examine the alteration of the PFAAs profiles and investigate their association with BRCA1 and 2 circulating levels in Egyptian females diagnosed with BC and in females with family history of BC to establish potential early detection strategies for BC.

METHODS AND RESULTS

This study included 26 BC patients, 22 females with family history of BC (relatives) in addition to 38 healthy females as control group. Quantitative measurement of PFAAs was determined by the ion exchange separation method through high performance liquid chromatography. BRCA1 and BRCA2 concentrations were determined using ELISA. Our results showed PFAAs profiles in BC patients and in females with BC family history with significant upregulation in mean plasma levels of Alanine, Phenylalanine, Glutamate and Cysteine and downregulation of Taurine, Threonine, Serine, Glycine, Valine, Methionine and Histidine levels compared to controls. Also, a significant positive correlation was observed between plasma BRCA1 and Valine levels while a significant negative correlation was observed between BRCA2 and Lysine plasma levels.

CONCLUSION

PFAAs profile can potentially be used in early screening for BC patients and for susceptible females.

Greater plasma essential amino acids and lower 3-methylhistidine with higher protein intake during endurance training: a randomised control trial

Endurance exercise alters amino acid (AA) metabolism that necessitates greater AA intake in the post exercise recovery period to support recovery. Thus, daily AA ingestion during a period of endurance training may affect the metabolically active plasma free AA pool, which is otherwise maintained during periods of inadequate protein intake by the breakdown of skeletal muscle proteins. Nine endurance-trained males completed a 4-day running protocol (20 km, 5 km, 10 km and 20 km on days 1-4, respectively) on three occasions with a controlled diet providing different protein intakes [0.94(LOW), 1.20(MOD) or 1.83gprotein kgbody mass-1 day-1 (HIGH)]. Urine collected over 24 h on day-4 and plasma collected after an overnight fast on day-5 were analyzed for free AA (plasma) and 3-methylhistidine (3MH; plasma and urine), a marker of myofibrillar protein breakdown. There was an effect of protein intake (HIGH > MOD/LOW; P < 0.05) on fasted plasma essential AA, branched chain AA and 3MH but no effect on 24-h urinary 3-MH excretion. Consuming a previously determined optimal daily protein intake of 1.83 g kg-1 day-1 during endurance training maintains fasted plasma free AA and may attenuate myofibrillar protein catabolism, although this latter effect was not detected in 24-h urinary excretion. The maintenance of the metabolically active free plasma AA pool may support greater recovery from exercise and contribute to the previously determined greater whole-body net protein balance in this athletic population. TRN: NCT02801344 (June 15, 2016).

Sodium pyruvate improves the plasma amino acid profile in rats with L-arginine-induced acute pancreatitis

Plasma amino acid levels are altered upon many pathological conditions including acute pancreatitis. It is unclear whether amino acids can be used as specific biomarker of acute pancreatitis severity or recovery. Development of acute pancreatitis is associated with mitochondrial dysfunction and decreased cytosolic ATP level. Sodium pyruvate is considered as a potential treatment of pancreatitis due to its ability to sustain mitochondrial oxidative and ATP-productive capacity in vitro. This study investigated the effect of sodium pyruvate on pancreatic morphology and plasma amino acid levels in rats with acute pancreatitis. Acute pancreatitis in rats was induced by administration of L-arginine (5 g/kg) Experimental treatment group received sodium pyruvate (1 g/kg) for 4 days. On day 8 of the experiment, animals were killed, blood was collected and plasma amino acid concentration was determined with high-performance liquid chromatography. Histological examination showed large areas of fibrosis in the pancreas of animals treated with L-arginine irrespectively of sodium pyruvate administration. Sodium pyruvate improved the plasma amino acid levels. Rats with acute pancreatitis had significantly lower levels of most essential and non-essential amino acids and increased glutamate and aspartate in plasma. Administration of sodium pyruvate completely or partially restored the levels of methionine, phenylalanine, tryptophan, leucine, isoleucine, aspartate, asparagine and ornithine levels, while increasing glutamine and serine to levels significantly higher than control. Plasma lysine, alanine, arginine and taurine remained unaffected in all experimental groups. Sodium pyruvate may be considered for use as a maintenance therapy in acute pancreatitis.

Histidine Enhances the Anticancer Effect of Gemcitabine against Pancreatic Cancer via Disruption of Amino Acid Homeostasis and Oxidant-Antioxidant Balance

Due to the severe toxicity posed by chemotherapeutic drugs, adjuvant nutritional intervention has gained increased attention in the treatment of pancreatic cancer (PC). Amino acid (AA) metabolism is aberrantly regulated in PC and circulating histidine (His) levels are low in PC patients. We hypothesized that His uptake and/or metabolism is dysregulated in PC and that combining His with gemcitabine (Gem), a drug used in the treatment of PC, will enhance the anti-cancer effects of Gem. We performed in vitro and in vivo studies to determine the anticancer effect of the combination of His and Gem against lethal PC. We demonstrate that circulating His levels are low in both human subjects and genetically engineered mice exhibiting pancreatic tumors. Interestingly, the expression of histidine ammonia lyase, an enzyme involved in His catabolism, is higher in PC compared to normal subjects. His + Gem exerts a more potent cytotoxic effect in PC cells compared to individual treatments. His treatment results in a profound increase in His accumulation, accompanied by a depletion of a number of AAs, promoting cancer cell survival and/or glutathione (GSH) synthesis. His but not Gem increases hydrogen peroxide and depletes cellular GSH. Supplementation with GSH protects cells against His + Gem-induced cytotoxicity. Further, our in vivo studies demonstrate that His + Gem potently reduced tumor mass and improved mouse survival. Taken together, our data suggest that PC cells exhibit an aberrant His uptake/accumulation which, in turn, leads to oxidative stress and depletion of AA pool, thereby enhancing the anticancer effect of Gem.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Biomarkers for pancreatic cancer based on tissue and serum metabolomics analysis in a multicenter study

BACKGROUND

Early detection of pancreatic ductal adenocarcinoma (PDAC) may improve the prognosis of patients. This study was to identify metabolic features of PDAC and to discover early detection biomarkers for PDAC by tissue and serum metabolomics analysis.

METHODS

We conducted nontargeted metabolomics analysis in tissue samples of 51 PDAC tumors, 40 noncancerous pancreatic tissues (NT), and 14 benign pancreatic neoplasms (BP) as well as serum samples from 80 patients with PDAC, 36 with BP, and 48 healthy controls (Ctr). The candidate metabolites identified from the initial analysis were further quantified using targeted analysis in serum samples of an independent cohort of 22 early stage PDAC, 27 BP, and 27 Ctr subjects. Unconditional binary logistic regression analysis was used to construct the optimal model for PDAC diagnosis.

RESULTS

Upregulated levels of fatty acids and lipids and downregulated amino acids were observed in tissue and serum samples of PDAC patients. Proline, creatine, and palmitic acid were identified as a panel of potential biomarkers to distinguish PDAC from BP and Ctr (odds ratio = 2.17, [95% confidence interval 1.34-3.53]). The three markers showed area under the receiver-operating characteristic curves (AUCs) of 0.854 and 0.865, respectively, for the comparison of PDAC versus Ctr and PDAC versus BP. The AUCs were 0.830 and 0.852 in the validation set and were improved to 0.949 and 0.909 when serum carbohydrate antigen 19-9 (CA19-9) was added to the model.

CONCLUSION

The novel metabolite biomarker panel identified in this study exhibited promising performance in distinguishing PDAC from BP or Ctr, especially in combination with CA19-9.

Untargeted metabolomics characterization of the resectable pancreatic ductal adenocarcinoma

Background

Diagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to the lack of specific symptoms and screening methods. Only less than 10% of PDAC patients are candidates for surgery at the time of diagnosis. Thus, there is a great global unmet need for valuable biomarkers that could improve the opportunity to detect PDAC at the resectable stage. This study aimed to develop a potential biomarker model for the detection of resectable PDAC by tissue and serum metabolomics.

Methods

Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS) was performed for metabolome quantification in 98 serum samples (49 PDAC patients and 49 healthy controls (HCs)) and 20 pairs of matched pancreatic cancer tissues (PCTs) and adjacent noncancerous tissues (ANTs) from PDAC patients. Univariate and multivariate analyses were used to profile the differential metabolites between PDAC and HC.

Results

A total of 12 differential metabolites were present in both serum and tissue samples of PDAC. Among them, a total of eight differential metabolites showed the same expressional levels, including four upregulated and four downregulated metabolites. Finally, a panel of three metabolites including 16-hydroxypalmitic acid, phenylalanine, and norleucine was constructed by logistic regression analysis. Notably, the panel was capable of distinguishing resectable PDAC from HC with an AUC value of 0.942. Additionally, a multimarker model based on the 3-metabolites-based panel and CA19-9 showed a better performance than the metabolites panel or CA19-9 alone (AUC: 0.968 vs. 0.942, 0.850).

Conclusions

Taken together, the resectable early-stage PDAC has unique metabolic features in serum and tissue samples. The defined panel of three metabolites has the potential value for early screening of PDAC at the resectable stage.

Focal pancreatic parenchyma atrophy is a harbinger of pancreatic cancer and a clue to the intraductal spreading subtype

BACKGROUND/OBJECTIVES

Radiological evidence of focal pancreatic parenchymal atrophy (FPPA) may presage early pancreatic ductal adenocarcinoma (PDAC) development. We aimed to clarify the incidence of FPPA and the clinicopathological features of PDAC with FPPA before diagnosis.

METHODS

Data on endoscopic ultrasound-guided fine-needle biopsies and surgical samples from 170 patients with pancreatic cancer histologically diagnosed between 2014 and 2019 were extracted from the pathology database of Komagome Hospital and Juntendo University hospital and retrospectively evaluated together with 51 patients without PDAC.

RESULTS

FPPA was identified in 47/170 (28%) patients before PDAC diagnosis and in 2/51 (4%) patients in the control group (P < 0.01). The median duration from FPPA detection to diagnosis was 35 (interquartile range [IQR]:16-63) months. In 24/47 (51%) patients with FPPA, the atrophic area resolved. The lesion was in the head and body/tail in 7/40 and 67/56 of the patients with (n = 47) and without FPPA (n = 123), respectively (P < 0.001). Histopathologically confirmed non-invasive lesions in the main pancreatic duct and a positive surgical margin in the resected specimens occurred in 53% vs. 21% (P = 0.078) and 29% vs. 3% (P = 0.001) of the groups, respectively. The PDAC patients with FPPA accompanied by a malignant pancreatic resection margin had high-grade pancreatic intraepithelial neoplasia.

CONCLUSIONS

FPPA occurred in 28% of the PDAC group at 35 months prediagnosis. The FPPA area resolved before PDAC onset. Benchmarking previous images of the pancreas with the focus on FPPA may enable prediction of PDAC. PDAC with FPPA involves widespread high-grade pancreatic intraepithelial neoplasia requiring a wide surgical margin for surgical excision.

Association between serum arginine levels and cancer risk: A community-based nested case-control study

OBJECTIVE

The effect of arginine on tumors appears to be bidirectional. The association of serum arginine with the risk of incident cancer remains uncovered at present. We aimed to investigate the prospective relationship of baseline serum arginine concentrations with the risk of incident cancer in hypertensive participants.

MATERIALS AND METHODS

A nested, case-control study with 1,389 incident cancer cases and 1,389 matched controls was conducted using data from the China H-Type Hypertension Registry Study (CHHRS). Conditional logistic regression analyses were performed to evaluate the association between serum arginine and the risk of the overall, digestive system, non-digestive system, and site-specific cancer.

RESULTS

Compared with matched controls, cancer patients had higher levels of arginine (21.41 μg/mL vs. 20.88 μg/mL, p < 0.05). When serum arginine concentrations were assessed as quartiles, compared with participants in the lowest arginine quartile, participants in the highest arginine quartile had a 32% (OR = 1.32, 95% CI: 1.03 to 1.71), and 68% (OR = 1.68, 95% CI: 1.09 to 2.59) increased risk of overall and digestive system cancer, respectively, in the adjusted models. In the site-specific analysis, each standard deviation (SD) increment of serum arginine was independently and positively associated with the risk of colorectal cancer (OR = 1.35, 95% CI: 1.01 to 1.82) in the adjusted analysis.

CONCLUSION

We found that hypertensive individuals with higher serum arginine levels exhibited a higher risk of overall, digestive system, and colorectal cancer.

Associations of AminoIndex Cancer Screening (Breast) Grade with Clinical and Laboratory Variables

BACKGROUND

Altered metabolism in the blood of cancer patients is closely related to changes in amino acids. Amino acids play an important physiological role as essential metabolites and regulators of metabolism. AminoIndex Cancer Screening (AICS) uses multivariate analysis of plasma-free amino acid profiles to screen for seven cancer types, including breast cancer.

METHODS

To determine the clinical utility of AICS (breast), we retrospectively analyzed associations of AICS (breast) score with clinical and laboratory variables in 390 patients who underwent AICS (breast) testing. The mean age of participants was 50.7 years (range: 26-87 years) and all were female.

RESULTS

The AICS (breast) grade was A, B, and C for 250 (64.1%), 90 (23.1%), and 50 (12.8%) participants, respectively. AICS (breast) was significantly correlated with AICS (gastric) (r = 0.487, p < 0.0001) and AICS (lung) (r = 0.523, p < 0.0001). Multivariate linear regression analysis showed no significant difference of AICS (breast) grade with age, body mass index, estimated glomerular filtration rate, dyslipidemia, or blood pressure. However, neutrophil-to-lymphocyte ratio significantly differed in relation to AICS (breast) grade (cut-off value, 1.7; p = 0.030), although only data from 72 patients were analyzed.

CONCLUSION

To our knowledge, this is the first study to report associations of AICS (breast) grade with clinical variables.

Meta-Analysis Reveals Both the Promises and the Challenges of Clinical Metabolomics

Clinical metabolomics is a rapidly expanding field focused on identifying molecular biomarkers to aid in the efficient diagnosis and treatment of human diseases. Variations in study design, metabolomics methodologies, and investigator protocols raise serious concerns about the accuracy and reproducibility of these potential biomarkers. The explosive growth of the field has led to the recent availability of numerous replicate clinical studies, which permits an evaluation of the consistency of biomarkers identified across multiple metabolomics projects. Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related death and has the lowest five-year survival rate primarily due to the lack of an early diagnosis and the limited treatment options. Accordingly, PDAC has been a popular target of clinical metabolomics studies. We compiled 24 PDAC metabolomics studies from the scientific literature for a detailed meta-analysis. A consistent identification across these multiple studies allowed for the validation of potential clinical biomarkers of PDAC while also highlighting variations in study protocols that may explain poor reproducibility. Our meta-analysis identified 10 metabolites that may serve as PDAC biomarkers and warrant further investigation. However, 87% of the 655 metabolites identified as potential biomarkers were identified in single studies. Differences in cohort size and demographics, p-value choice, fold-change significance, sample type, handling and storage, data collection, and analysis were all factors that likely contributed to this apparently large false positive rate. Our meta-analysis demonstrated the need for consistent experimental design and normalized practices to accurately leverage clinical metabolomics data for reliable and reproducible biomarker discovery.

Integration of metabolites from meta-analysis with transcriptome reveals enhanced SPHK1 in PDAC with a background of pancreatitis

BACKGROUND

Pathophysiology of transformation of inflammatory lesions in chronic pancreatitis (CP) to pancreatic ductal adenocarcinoma (PDAC) is not clear.

METHODS

We conducted a systematic review, meta-analysis of circulating metabolites, integrated this data with transcriptome analysis of human pancreatic tissues and validated using immunohistochemistry. Our aim was to establish biomarker signatures for early malignant transformation in patients with underlying CP and identify therapeutic targets.

RESULTS

Analysis of 19 studies revealed AUC of 0.86 (95% CI 0.81-0.91, P < 0.0001) for all the altered metabolites (n = 88). Among them, lipids showed higher differentiating efficacy between PDAC and CP; P-value (< 0.0001). Pathway enrichment analysis identified sphingomyelin metabolism (impact value-0.29, FDR of 0.45) and TCA cycle (impact value-0.18, FDR of 0.06) to be prominent pathways in differentiating PDAC from CP. Mapping circulating metabolites to corresponding genes revealed 517 altered genes. Integration of these genes with transcriptome data of CP and PDAC with a background of CP (PDAC-CP) identified three upregulated genes; PIGC, PPIB, PKM and three downregulated genes; AZGP1, EGLN1, GNMT. Comparison of CP to PDAC-CP and PDAC-CP to PDAC identified upregulation of SPHK1, a known oncogene.

CONCLUSIONS

Our analysis suggests plausible role for SPHK1 in development of pancreatic adenocarcinoma in long standing CP patients. SPHK1 could be further explored as diagnostic and potential therapeutic target.

Advances in biomarkers and techniques for pancreatic cancer diagnosis

Pancreatic cancer is the most lethal type of malignancy and is characterized by high invasiveness without severe symptoms. It is difficult to detect PC at an early stage because of the low diagnostic accuracy of existing routine methods, such as abdominal ultrasound, CT, MRI, and endoscopic ultrasound (EUS). Therefore, it is of value to develop new diagnostic techniques for early detection with high accuracy. In this review, we aim to highlight research progress on novel biomarkers, artificial intelligence, and nanomaterial applications on the diagnostic accuracy of pancreatic cancer.

Pancreatic cancer: branched-chain amino acids as putative key metabolic regulators?

Branched-chain amino acids (BCAA) are essential amino acids utilized in anabolic and catabolic metabolism. While extensively studied in obesity and diabetes, recent evidence suggests an important role for BCAA metabolism in cancer. Elevated plasma levels of BCAA are associated with an increased risk of developing pancreatic cancer, namely pancreatic ductal adenocarcinoma (PDAC), a tumor with one of the highest 1-year mortality rates. The dreadful prognosis for PDAC patients could be attributable also to the early and frequent development of cancer cachexia, a fatal host metabolic reprogramming leading to muscle and adipose wasting. We propose that BCAA dysmetabolism is a unifying component of several pathological conditions, i.e., obesity, insulin resistance, and PDAC. These conditions are mutually dependent since PDAC ranks among cancers tightly associated with obesity and insulin resistance. It is also well-established that PDAC itself can trigger insulin resistance and new-onset diabetes. However, the exact link between BCAA metabolism, development of PDAC, and tissue wasting is still unclear. Although tissue-specific intracellular and systemic metabolism of BCAA is being intensively studied, unresolved questions related to PDAC and cancer cachexia remain, namely, whether elevated circulating BCAA contribute to PDAC etiology, what is the biological background of BCAA elevation, and what is the role of adipose tissue relative to BCAA metabolism during cancer cachexia. To cover those issues, we provide our view on BCAA metabolism at the intracellular, tissue, and whole-body level, with special emphasis on different metabolic links to BCAA intermediates and the role of insulin in substrate handling.

Evaluation of 64Cu-Labeled New Anti-EGFR Antibody NCAB001 with Intraperitoneal Injection for Early PET Diagnosis of Pancreatic Cancer in Orthotopic Tumor-Xenografted Mice and Nonhuman Primates

Objectives: To improve the prognosis of pancreatic cancer, new imaging methods to identify tumor lesions at a size of <1 cm are urgently needed. To approach this clinical issue, we developed a new method to detect small tumor lesions in the pancreas (≥3 mm) by positron emission tomography (PET) using an intraperitoneally (ip)-administered ⁶⁴Cu-labeled new anti-epidermal growth factor receptor (EGFR) antibody (encoded as NCAB001), called ⁶⁴Cu-NCAB001 ipPET. Methods: NCAB001 was manufactured under cGMP conditions and labeled with ⁶⁴Cu. The radiochemical and biological properties of ⁶⁴Cu-NCAB001 were evaluated. Tumor uptake of an ip-administered ⁶⁴Cu-NCAB001 in mice with orthotopic pancreatic tumor xPA1-DC xenografts was also evaluated. Pharmacokinetics and radiation dosimetry were examined using PET images acquired after the ip administration of ⁶⁴Cu-NCAB001 into cynomolgus monkeys with pharmacologic safety monitoring. Results: Radio-chromatography, cell-binding assays, and biodistribution of ⁶⁴Cu-NCAB001 in mice were identical to those of our previous data with clinically available cetuximab. Small tumor lesions in the pancreas (≥3 mm) of mice could be identified by ⁶⁴Cu-NCAB001 ipPET. The ip administration of ⁶⁴Cu-NCAB001 into monkeys was safely conducted using ultrasound imaging. PET images in monkeys showed that ip-administered ⁶⁴Cu-NCAB001 was distributed throughout the intraperitoneal cavity for up to 6 h and cleared thereafter. Most of the radioactivity was distributed in the liver and the large intestine. The radioactivity around the pancreas became negligible 24 h after administration. The estimated human effective dose was 0.0174 mSv/MBq. Conclusion: Our data support the initiation of clinical trials of ⁶⁴Cu-NCAB001 ipPET to transfer this promising tool for the early diagnosis of pancreatic cancers.

A merged method for targeted analysis of amino acids and derivatives using parallel reaction monitoring combined with untargeted profiling by HILIC-Q-Orbitrap HRMS

With continuously increased scan rate and sensitivity, high resolution mass spectrometry (HRMS) allows for both reliable targeted analysis (e.g., parallel reaction monitoring, PRM) and a global overview for discovery-based untargeted profiling (e.g., data dependent acquisition, DDA) to be performed. Based on previous study on PRM for large scale targeted metabolomics quantification, we developed an innovative method merged targeted and untargeted approaches in a single run. In our workflow, the scheduled PRM for targeted analysis of amino acids and derivatives combined with the full scan was acquired in every sample injection by hydrophilic interaction liquid chromatography tandem quadrupole-Orbitrap high resolution mass spectrometry (HILIC-Q-Orbitrap HRMS). The identification of metabolic features from full scan was further performed with DDA methodology on grouped quality control (QC) samples and matched with available database. Specifically, 20 amino acids and 40 derivatives were selected for targeted analysis with optimal chromatographic separation and PRM parameters. All isomers within the selected metabolites were totally separated in the robust HILIC condition. 36 of selected metabolites were well-detected and showed a good linearity and reproducibility in NIST SRM 1950 plasma. Moreover, the absolute quantification performance of targeted PRM method was systematically validated using 10 amino acids with the corresponding stable isotope-labeled internal standards (SIL-IS). Finally, the newly developed method was successfully applied to analysis of the plasma samples from patients of pancreatic benign tumor and pancreatic cancer. The significant reduction of circulating amino acids in patients with pancreatic malignancy was confirmed by targeted PRM method and other amino acids modifications as well as polar metabolites were identified with untargeted profiling. Therefore, we have established a workflow that combines specifically and reliably targeted PRM method as well as broad-coverage untargeted profiling, which provides an innovative strategy for basic and clinical metabolomics study.

Early Detection of Pancreatic Cancer in Type 2 Diabetes Mellitus Patients Based on 1H NMR Metabolomics

The association of pancreatic cancer with type 2 diabetes mellitus was investigated by ¹H NMR metabolomic analysis of blood plasma. Concentration data of 58 metabolites enabled discrimination of pancreatic cancer (PC) patients from healthy controls (HC) and long-term type 2 diabetes mellitus (T2DM) patients. A panel of eight metabolites was proposed and successfully tested for group discrimination. Furthermore, a prediction model for the identification of at-risk individuals for future development of pancreatic cancer was built and tested on recent-onset diabetes mellitus (RODM) patients. Six of 59 RODM samples were assessed as PC with an accuracy of more than 80%. The health condition of these individuals was re-examined, and in four cases, a correlation to the prediction was found. The current health condition can be retrospectively attributed to misdiagnosed pancreatogenic diabetes or to early-stage pancreatic cancer.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review

Introduction

Detecting upper gastrointestinal (GI) cancers in primary care is challenging, as cancer symptoms are common, often non-specific, and most patients presenting with these symptoms will not have cancer. Substantial investment has been made to develop biomarkers for cancer detection, but few have reached routine clinical practice. We aimed to identify novel biomarkers for upper GI cancers which have been sufficiently validated to be ready for evaluation in low-prevalence populations.

Methods

We systematically searched MEDLINE, Embase, Emcare, and Web of Science for studies published in English from January 2000 to October 2019 (PROSPERO registration CRD42020165005). Reference lists of included studies were assessed. Studies had to report on second measures of diagnostic performance (beyond discovery phase) for biomarkers (single or in panels) used to detect pancreatic, oesophageal, gastric, and biliary tract cancers. We included all designs and excluded studies with less than 50 cases/controls. Data were extracted on types of biomarkers, populations and outcomes. Heterogeneity prevented pooling of outcomes.

Results

We identified 149 eligible studies, involving 22,264 cancer cases and 49,474 controls. A total of 431 biomarkers were identified (183 microRNAs and other RNAs, 79 autoantibodies and other immunological markers, 119 other proteins, 36 metabolic markers, 6 circulating tumour DNA and 8 other). Over half (n = 231) were reported in pancreatic cancer studies. Only 35 biomarkers had been investigated in at least two studies, with reported outcomes for that individual marker for the same tumour type. Apolipoproteins (apoAII-AT and apoAII-ATQ), and pepsinogens (PGI and PGII) were the most promising biomarkers for pancreatic and gastric cancer, respectively.

Conclusion

Most novel biomarkers for the early detection of upper GI cancers are still at an early stage of matureness. Further evidence is needed on biomarker performance in low-prevalence populations, in addition to implementation and health economic studies, before extensive adoption into clinical practice can be recommended.

Electronic Supplementary Material

The online version of this article (10.1007/s12325-020-01571-z) contains supplementary material, which is available to authorized users.

Metabolomics Identifies Biomarker Signatures to Differentiate Pancreatic Cancer from Type 2 Diabetes Mellitus in Early Diagnosis

METHODS

Plasma metabolic profiles in 26 PC patients, 27 DM patients, and 23 healthy volunteers were examined using an ultraperformance liquid chromatography coupled with tandem mass spectrometry platform. Differential metabolite ions were then identified using the principal component analysis (PCA) model and the orthogonal partial least-squares discrimination analysis (OPLS-DA) model. The diagnosis performance of metabolite biomarkers was validated by logistic regression models.

RESULTS

We established a PCA model (R2X = 23.5%, Q2 = 8.21%) and an OPLS-DA model (R2X = 70.0%, R2Y = 84.9%, Q2 = 69.7%). LysoPC (16 : 0), catelaidic acid, cerebronic acid, nonadecanetriol, and asparaginyl-histidine were found to identify PC, with a sensitivity of 89% and a specificity of 91%. Besides, lysoPC (16 : 0), lysoPC (16 : 1), lysoPC (22 : 6), and lysoPC (20 : 3) were found to differentiate PC from DM, with higher accuracy (68% versus 55%) and higher AUC values (72% versus 63%) than those of CA19-9. The diagnostic performance of metabolite biomarkers was finally validated by logistic regression models.

CONCLUSION

We succeeded in screening differential metabolite ions among PC and DM patients and healthy individuals, thus providing a preliminary basis for screening the biomarkers for the early diagnosis of PC.

Use of plasma-free amino acids as biomarkers for detecting and predicting disease risk

This paper reviews developments regarding the use of plasma-free amino acid (PFAA) profiles as biomarkers for detecting and predicting disease risk. This work was initiated and first published in 2006 and was subsequently developed by Ajinomoto Co., Inc. After commercialization in 2011, PFAA-based tests were adopted in over 1500 clinics and hospitals in Japan, and numerous clinician-led studies have been performed to validate these tests. Evidence is accumulating that PFAA profiles can be used for diabetes prediction and evaluation of frailty; in particular, decreased plasma essential amino acids could contribute to the pathophysiology of severe frailty. Integration of PFAA evaluation as a biomarker and effective essential amino acid supplementation, which improves physical and mental functions in the elderly, could facilitate the development of precision nutrition, including personalized solutions. This present review provides the background for the technology as well as more recent clinical findings, and offers future possibilities regarding the implementation of precision nutrition.

Preoperative AminoIndex Cancer Screening (AICS) abnormalities predict postoperative recurrence in patients undergoing curative resection for non-small cell lung cancer

BACKGROUND

AminoIndex™ Cancer Screening (AICS (lung)) was developed as a screening test for lung cancer using a multivariate analysis of plasma-free amino acid (PFAA) profiles. According to the developed index composed of PFAA, the probability of lung cancer was categorized into AICS (lung) ranks A, B, and C in order of increasing risk. The aim of the present study was to investigate the relationship between the preoperative AICS (lung) rank and surgical outcomes in patients who underwent curative resection for non-small cell lung cancer (NSCLC).

METHODS

Preoperative blood samples were collected from 297 patients who underwent curative resection for NSCLC between 2006 and 2015. PFAA concentrations were measured. The relationship between the preoperative AICS (lung) rank and clinicopathological factors was examined. The effects of the preoperative AICS (lung) rank on postoperative outcomes were also analyzed.

RESULTS

The AICS (lung) rank was A in 93 patients (31.3%), B in 82 (27.6%), and C in 122 (41.1%). The AICS (lung) rank did not correlate with any clinicopathological factors, except for age. Based on follow-up data (median follow-up period of 6 years), postoperative recurrence was observed in 22 rank A patients (23.7%), 15 rank B (18.3%) and 49 rank C (40.2%). In the univariate analysis, preoperative AICS (lung) rank C was a worse factor of recurrence-free survival (p = 0.0002). The multivariate analysis identified preoperative AICS (lung) rank C (HR: 2.17, p = 0.0005) as a significant predictor of postoperative recurrence, particularly in patients with early-stage disease or adenocarcinoma.

CONCLUSION

Preoperative AICS (lung) rank C is a high-risk predictor of postoperative recurrence in patients undergoing curative resection for NSCLC.

Early Diagnosis of Pancreatic Cancer: The Key for Survival

Pancreatic cancer (PC) is one of the most aggressive forms of cancer. Negative prognosis is mainly due to the late diagnosis in advanced stages, when the disease is already therapeutically overcome. Studies in recent years have focused on identifying biomarkers that could play a role in early diagnosis, leading to the improvement of morbidity and mortality. Currently, the only biomarker widely used in the diagnosis of PC is carbohydrate antigen 19-9 (CA19.9), which has, however, more of a prognostic role in the follow-up of postoperative recurrence than a diagnostic role. Other biomarkers, recently identified as the methylation status of ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1) and BNC1 (zinc finger protein basonuclin-1) in cell-free deoxyribonucleic acid (DNA), may play a role in the early detection of PC. This review focuses on the diagnosis of PC in its early stages.

Screening Strategy of Pancreatic Cancer in Patients with Diabetes Mellitus

The incidence of pancreatic cancer (PCa) is increasing worldwide and has become one of the leading causes of cancer-related death. Screening for high risk populations is fundamental to overcome this intractable malignancy. Diabetes mellitus (DM) is classically known as a risk factor for PCa. Recently the reverse causality is in the spotlight, that is to say, DM is considered to be a manifestation of PCa. Numbers of epidemiological studies clarified that new-onset DM (≤2-year duration) was predominant in PCa patients and the relative risk for PCa inversely correlated with duration of DM. Among patients with new-onset DM, elder onset, weight loss, and rapid exacerbation of glycemic control were reported to be promising risk factors and signs, and the model was developed by combining these factors. Several pilot studies disclosed the possible utility of biomarkers to discriminate PCa-associated DM from type 2 DM. However, there is no reliable biomarkers to be used in the practice. We previously reported the application of a multivariate index for PCa based on the profile of plasma free amino acids (PFAAs) among diabetic patients. We are further investigating on the PFAA profile of PCa-associated DM, and it can be useful for developing the novel biomarker in the near future.

A web-based automated machine learning platform to analyze liquid biopsy data

Liquid biopsy (LB) technologies continue to improve in sensitivity, specificity, and multiplexing and can measure an ever growing library of disease biomarkers. However, clinical interpretation of the increasingly large sets of data these technologies generate remains a challenge. Machine learning is a popular approach to discover and detect signatures of disease. However, limited machine learning expertise in the LB field has kept the discipline from fully leveraging these tools and risks improper analyses and irreproducible results. In this paper, we develop a web-based automated machine learning tool tailored specifically for LB, where machine learning models can be built without the user's input. We also incorporate a differential privacy algorithm, designed to limit the effects of overfitting that can arise from users iteratively developing a panel with feedback from our platform. We validate our approach by performing a meta-analysis on 11 published LB datasets, and found that we had similar or better performance compared to those reported in the literature. Moreover, we show that our platform's performance improved when incorporating information from prior LB datasets, suggesting that this approach can continue to improve with increased access to LB data. Finally, we show that by using our platform the results achieved in the literature can be matched using 40% of the number of subjects in the training set, potentially reducing study cost and time. This self-improving and overfitting-resistant automatic machine learning platform provides a new standard that can be used to validate machine learning works in the LB field.

LC-MS/MS and SWATH based serum metabolomics enables biomarker discovery in pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is the fourth leading cause of cancer death because of its subtle clinical symptoms in the early stage. To discover particular serum metabolites as potential biomarkers to differentiate pancreatic carcinoma from benign disease (BD) is on urgent demand.

METHOD

To comprehensively analyze serum metabolites obtained from 14 patients with PC, 10 patients with BD and 10 healthy individuals (normal control, NC), we separated the metabolites using both reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC). The data were acquired on a high-resolution quadrupole time-of-flight mass spectrometer operated in negative (ESI-) and positive (ESI+) ionization modes, respectively. Differential metabolites were selected by univariate (Student's t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Sequential window acquisition of all theoretical spectra (SWATH) analysis was further utilized to validate the metabolites found in discovery stage. The receiver operator characteristics (ROC) curve analysis was performed to evaluate predictive clinical usefulness of 8 metabolites.

RESULTS

A total of 8 metabolites including taurocholic acid, glycochenodexycholic acid, glycocholic acid, L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine were identified and relatively quantified as differential metabolites for discriminating PC, BD and NC. The 8 metabolites and their combination discriminated PC from BD and NC with well-performed area under the curve (AUC) values, sensitivity and specificity.

CONCLUSION

Bile acids (especially taurocholic acid) performed to be potential biomarkers in PC diagnosis. Other amino acids (such as L-glutamine, glutamic acid, L-phenylalanine, L-tryptophan, and L-arginine) in serum samples from PC patients might provide a sensitive, blood-borne diagnostic signature for the presence of PC or its precursor lesions.

Immuno-OpenPET: a novel approach for early diagnosis and image-guided surgery for small resectable pancreatic cancer

Pancreatic cancer (PC) has a poor prognosis owing to difficulties in the diagnosis of resectable PC at early stages. Several clinical studies have indicated that the detection and surgery of small resectable PC (<1 cm) can significantly improve survival; however, imaging diagnosis and accurate resection of small PC remain challenging. Here, we report the feasibility of "immuno-OpenPET" as a novel approach enabling not only early diagnosis but also image-guided surgery, using a small (<1 cm) resectable PC orthotopic xenograft mouse model. For immuno-OpenPET, we utilized our original OpenPET system, which enables high-resolution positron emission tomography (PET) imaging with depth-of-interaction detectors, as well as real-time image-guided surgery, by arranging the detectors to create an open space for surgery and accelerating the image reconstruction process by graphics processing units. For immuno-OpenPET, ⁶⁴Cu-labeled anti-epidermal growth factor receptor antibody cetuximab was intraperitoneally administered into mice. It clearly identified PC tumors ≥3 mm. In contrast, neither OpenPET with intravenous-administered ⁶⁴Cu-cetuximab nor intraperitoneal/intravenous-administered ¹⁸F-FDG (a traditional PET probe) could detect PC in this model. Immuno-OpenPET-guided surgery accurately resected small PC in mice and achieved significantly prolonged survival. This technology could provide a novel diagnostic and therapeutic strategy for small resectable PC to improve patient survival.

Metabolomics Analysis of Laparoscopic Surgery Combined with Wuda Granule to Promote Rapid Recovery of Patients with Colorectal Cancer Using UPLC/Q-TOF-MS/MS

Surgery is the primary curative treatment for patients with nonmetastasized colorectal cancer (CRC). Rate of complications, morbidity, mortality, and overall survival of patients with CRC are factors associated with speed of recovery following surgery. Wuda granule (WD) is a traditional Chinese medicine (TCM) prescription used to promote rapid recovery after surgery. However, the specific mechanism of action of WD has not been characterized. Our study included 60 patients with clear histopathological evidence of colon or rectal cancer who underwent CRC laparoscopic surgery and 30 healthy individuals. Serum biochemistry and clinical evaluation of gastrointestinal function showed that WD could improve the nutritional status and gastrointestinal function and reduce the level of inflammation of patients with CRC following laparoscopic surgery. In addition, we used UPLC/Q-TOF-MS/MS-based metabolomics analysis to determine the mechanism of WD-related rapid recovery following laparoscopic surgery in patients with CRC. Twenty metabolites associated with arachidonic acid, alanine, aspartate and glutamate, α-linolenic acid, pyruvate, histidine, and glycerophospholipids were identified. The results suggested that the therapeutic mechanism of laparoscopic surgery combined with WD may be related to regulation of nutritional status, inflammation, immune function, energy, and gastrointestinal function in patients with CRC. This study also highlighted the ability of TCM compounds to interact with multiple targets to induce synergistic effects. This study may result in further studies of WD as a therapeutic agent to promote recovery following surgical resection of CRC tumors.

Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics

Altered metabolism is one of the key hallmarks of cancer. The development of sensitive, reproducible and robust bioanalytical tools such as Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry techniques offers numerous opportunities for cancer metabolism research, and provides additional and exciting avenues in cancer diagnosis, prognosis and for the development of more effective and personalized treatments. In this chapter, we introduce the current state of the art of metabolomics and metabolic phenotyping approaches in cancer research and clinical diagnostics.

Efficacy of prolonged elemental diet therapy after pancreaticoduodenectomy for pancreatic ductal adenocarcinoma: A pilot prospective randomized trial (UMIN000004108)

BACKGROUNDS AND AIMS

This randomized clinical trial examined efficacy of prolonged elemental diet (ED) therapy after pancreatoduodenectomy (PD) for pancreatic ductal adenocarcinoma (PDAC), which often causes postoperative malnutrition leading to worsened short- and long-term outcomes.

METHODS

Thirty-nine patients with PDAC receiving PD was randomly assigned to prolonged ED group (PEDG) and control group (CG). Fat-free ED (Elental®, EA Pharma CO., Ltd., Tokyo, Japan) via tube jejunostomy was initiated on postoperative day 1 and increased to maintain with 600 kcal/day in addition to oral intake. ED was discontinued if sufficient oral intake was achieved in CG but continued during 3 postoperative months in PEDG. Primary outcome was complication necessitating readmission. Secondary outcomes were nutritional parameters, relative dose intensity (RDI) in cases of adjuvant chemotherapy, and survival outcomes.

RESULTS

Twenty patients were assigned to CG and 19 to PEDG. Cumulative post-discharge readmission rate was significantly lower in PEDG than in CG (PEDG vs CG; 12.6% vs 43.7% at 12-post-discharge-month; p = 0.018). Total calorie and ED-derived protein intakes were significantly larger in PEDG than in CG up to 3-postoperative-month but thereafter similar among groups. Lymphocyte counts were significantly increased and neutrophil-to-lymphocyte-ratio (NLR) was significantly reduced in PEDG than in CG at 2-, 3-, and 6-postoperative-month. However, other outcome measures did not differ among groups.

CONCLUSION

This trial failed to show survival benefit of prolonged ED therapy but demonstrated its favorable effect on increased lymphocyte counts, reduced NLR, and prevention of complications necessitating readmission, those which may lead to survival benefit with some modifications.

Postoperative serum metabolites of patients on a low carbohydrate ketogenic diet after pancreatectomy for pancreatobiliary cancer: a nontargeted metabolomics pilot study

A ketogenic diet is a potential adjuvant cancer therapy that limits glucose availability to tumours while fuelling normal tissues with ketone bodies. We examined the effect of a low carbohydrate ketogenic diet (LCKD) (80% kcal from fat, ketogenic ratio 1.75:1, w/w) compared to a general hospital diet (GD) on serum metabolic profiles in patients (n = 18, ≥ 19 years old) who underwent pancreatectomy for pancreatobiliary cancer. Serum samples collected preoperatively (week 0) and after the dietary intervention (week 2) were analysed with a nontargeted metabolomics approach using liquid chromatography-tandem mass spectrometry. Serum β-hydroxybutyrate and total ketone levels significantly increased after 2 weeks of LCKD compared to GD (p < 0.05). Principal component analysis score plots and orthogonal partial least squares discriminant analysis also showed significant differences between groups at week 2, with strong validation. In all, 240 metabolites differed between LCKD and GD. Pathways including glycerophospholipid and sphingolipid metabolisms were significantly enriched in the LCKD samples. LCKD decreased C22:1-ceramide levels, which are reported to be high in pancreatic cancer, while increasing lysophosphatidylcholine (18:2), uric acid, citrulline, and inosine levels, which are generally low in pancreatic cancer. Postoperative LCKD might beneficially modulate pancreatic cancer-related metabolites in patients with pancreatobiliary cancer.

A multicentre clinical validation of AminoIndex Cancer Screening (AICS)

AminoIndex Cancer Screening (AICS) is a novel cancer screening test based on plasma free amino acid (PFAA) levels. This system categorises subjects as rank A, B, or C in order of increasing probability of each cancer incidence. The current study aimed to validate the potential of AICS for cancer detection. AICS values were determined from the PFAA levels in subjects examined at Chiba Cancer Center Cohort, Mitsui Memorial Hospital, and Saihaku Hospital, and the cancer incidence was investigated. The sensitivities of rank C for cancer diagnosis within 1 year after AICS examination were 83.3% (10/12) for gastric, 50.0% (2/4) for lung, 46.2% (6/13) for colorectal, 50.0% (8/16) for prostate, 43.8% (7/16) for breast, and 50.0% (1/2) for uterine/ovarian cancer. The total cancer detection rate via AICS was 0.33% (34/10,245). The sensitivities during the maximum follow-up period of 6.2 years were 51.7% (15/29) for gastric, 18.2% (2/11) for lung, 28.6% (8/28) for colorectal, 36.4% (8/22) for prostate, 29.0% (9/31) for breast, and 33.3% (2/6) for uterine/ovarian cancers. In conclusion, AICS is a more useful method for evaluating the probability of cancer incidence than for predicting onset, suggesting that annual AICS should be recommended to detect any malignancy.

Tissue amino acid profiles are characteristic of tumor type, malignant phenotype, and tumor progression in pancreatic tumors

Tissue amino acid profiles depend on the cell types and extracellular components that constitute the tissue, and their functions and activities. We aimed to characterize the tissue amino acid profiles in several types of pancreatic tumors and lesions. We examined tissue amino acid profiles in 311 patients with pancreatic tumors or lesions. We used newly developed LC-MS/MS methods to obtain the profiles, which were compared with clinicopathological data. Each tumor or lesion presented a characteristic tissue amino acid profile. Certain amino acids were markedly altered during the multistep pancreatic carcinogenesis and pancreatic ductal adenocarcinoma (PDAC) progression. A tissue amino acid index (TAAI) was developed based on the amino acids that were notably changed during both carcinogenesis and cancer progression. Univariate and multivariate survival analyses revealed that PDAC patients with a high TAAI exhibited a significantly shorter survival rate, and these findings were validated using a second cohort. We suggest that tissue amino acid profiles are characteristic for normal tissue type, tumor histological type, and pathological lesion, and are representative of the cancer grade or progression stage in multistep carcinogenesis and of malignant characteristics. The TAAI could serve as an independent prognosticator for patients with PDAC.

Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics

Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance-based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall-Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

Plasma-free amino acid profiles in dogs with hepatocellular carcinoma

BACKGROUND

Metabolomic analysis using blood samples has been suggested to be useful for the early detection of cancer. Among metabolites, plasma-free amino acid (PFAA) profiles are potential diagnostic biomarkers for several diseases including cancer. However, the relationship between PFAA concentrations and liver tumors in dogs remains unknown.

OBJECTIVE

To determine the characteristics of PFAA profiles of dogs with hepatocellular carcinoma (HCC) and correlated clinical features.

ANIMALS

Thirty-four client-owned dogs diagnosed with HCC (n = 26) and benign liver diseases (n = 8) and 11 age-matched healthy dogs.

METHODS

Prospective study using heparinized blood samples from fasted dogs. Plasma was deproteinized, and the concentrations of 21 amino acids were measured using an automated high-performance liquid chromatography amino acid analyzer.

RESULTS

Plasma glutamic acid concentrations were significantly different among groups (P < .0024 after Bonferroni correction). Compared to healthy dogs, dogs with HCC and benign liver diseases had significantly higher concentrations of glutamic acid by post hoc analysis. However, no significant difference in the PFAA profiles of HCC and benign liver diseases were detected. In addition, preoperative and postoperative PFAA profiles of dogs with HCC were not significantly different.

CONCLUSIONS AND CLINICAL IMPORTANCE

Increased glutamic acid concentrations might play a role in the development or be a consequence of liver tumor formation. However, PFAA profiles of HCC could not be differentiated from those of benign lesions. In addition, glutamic acid concentrations did not change after surgical resection. These results indicate that PFAA profiles may not be useful biomarkers for detecting HCC in dogs.

Diagnostic yield of the plasma free amino acid index for pancreatic cancer in patients with diabetes mellitus

OBJECTIVES

A multivariate index calculated using plasma free amino acids (PFAA index) was reported as a diagnostic biomarker for pancreatic cancer (PaC). Although diabetes mellitus (DM) is expected to be an early diagnostic indicator of PaC, identifying the high-risk individuals among patients with DM is warranted. We evaluated the diagnostic yield of the PFAA index for PaC in patients with DM.

METHODS

We compared the diagnostic yield of the PFAA index between individuals with and those without DM. Cases and controls were recruited prospectively, and controls were matched to cases at a 1:1 ratio for age, sex, and DM status.

RESULTS

A total of 180 case-control pairs were included in the analysis. The prevalence of DM was 53.3%. The sensitivity of the PFAA index was 66.7% in cases with DM and 56.0% in those without DM (P = 0.14), and the specificity was 92.7% in controls with DM and 94.0% in those without DM (P = 0.95).

CONCLUSIONS

This matched case-control study revealed a comparable diagnostic yield of the PFAA index for PaC in individuals with and those without DM. The PFAA index can be used as a biomarker for further diagnostic imaging in selected patients with DM.

Prognostic Significance of Serum Free Amino Acids in Head and Neck Cancers

Despite distinctive advances in the field of head and neck squamous cell cancer (HNSCC) biomarker discovery, the spectrum of clinically useful prognostic serum biomarkers is limited. As metabolic activities in highly proliferative transformed cells are fundamentally different from those in non-transformed cells, specific shifts in concentration of different metabolites may serve as diagnostic or prognostic markers. Blood amino acids have been identified as promising biomarkers in different cancers before, but little is known about this field in HNSCC. Blood amino acid profiles of 140 HNSCC patients were examined using high-performance liquid chromatography. Cox proportional hazards regression model was used to assess the prognostic value of amino acid concentrations in serum. Colony forming assay was used to identify the effect of amino acids that were significant in Cox proportional hazards regression models on colony forming ability of FaDu and Detroit 562 cell lines. In the multivariable Cox regression model for overall survival (OS), palliative treatment was associated with an unfavourable prognosis while high serum levels of methionine have had a positive prognostic impact. In the relapse-free survival (RFS) multivariable model, methionine was similarly identified as a positive prognostic factor, along with tumor localization in the oropharynx. Oral cavity localization and primary radio(chemo)therapy treatment strategy have been linked to poorer RFS. 1mM serine was shown to support the forming of colonies in both tested HNSCC cell lines. Effect of methionine was exactly the opposite.

A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women

To examine the association between metabolic deregulation and pancreatic cancer, we conducted a two-stage case-control targeted metabolomics study using prediagnostic sera collected one year before diagnosis in the Women's Health Initiative study. We used the LC/MS to quantitate 470 metabolites in 30 matched case/control pairs. From 180 detectable metabolites, we selected 14 metabolites to be validated in additional 18 matched case/control pairs. We used the paired t test to compare the concentrations of each metabolite between cases and controls and used the log fold change (FC) to indicate the magnitude of difference. FDR adjusted q-value < 0.25 was indicated statistically significant. Logistic regression model and ROC curve analysis were used to evaluate the clinical utility of the metabolites. Among 30 case/control pairs, 1-methyl-l-tryptophan (L-1MT) was significantly lower in the cases than in the controls (log₂ FC = -0.35; q-value = 0.03). The area under the ROC curve was 0.83 in the discrimination analysis based on the levels of L-1MT, acadesine, and aspartic acid. None of the metabolites was validated in additional independent 18 case/control pairs. No significant association was found between the examined metabolites and undiagnosed pancreatic cancer.

Methods for Absolute Quantification of Human Plasma Free Amino Acids by High-Performance Liquid Chromatography/Electrospray Ionization Mass Spectrometry Using Precolumn Derivatization

Plasma free amino acid (PFAA) concentrations in humans are affected by various diseases. However, the variations caused are not dramatic, so a high accurate and precise method for analyzing PFAAs is required. The PFAA analysis protocol described in this chapter covers blood sampling, sample pretreatment, amino acid derivatization, and LC-MS analysis. Each procedure is important for accurate and precise quantification.In the protocol, a human blood sample is collected using an EDTA-2Na or 2K vacuum collection tube and then immediately cooled in water mixed with crushed ice. The sample is then centrifuged on cooling to allow a plasma sample to be removed. A stable-isotope-labeled internal standard solution is added to the plasma, and then the plasma is deproteinized with acetonitrile. The amino acids in the plasma are then derivatized using 3-aminopyridyl-N-hydroxysuccinimidyl carbamate (APDS) reagent which is designed for LC-MS analysis. The derivatized amino acids are separated by reverse-phase HPLC and detected by electrospray ionization mass spectrometry. Using this method, 21 amino acids in human plasma can be analyzed with a 12 min cycle. The accuracy and precision are both better than the required criteria given by the US Food and Drug Administration in guidance of Bioanalytical Method Validation.

Increased Levels of Branched-Chain Amino Acid Associated With Increased Risk of Pancreatic Cancer in a Prospective Case-Control Study of a Large Cohort

BACKGROUND & AIMS

A marker is needed to identify individuals at risk for pancreatic cancer. Increases in branched-chain amino acids (BCAAs) have been associated with pancreatic cancer. We performed a prospective case-control study to study the association between plasma BCAA levels and risk of pancreatic cancer in a large cohort.

METHODS

We conducted a nested case-control study selected from 30,239 eligible participants 40-69 years old within the Japan Public Health Center-based prospective study. Over 16.4 years, 170 newly diagnosed pancreatic cancer cases were identified. Each case was matched to 2 controls by age, gender, geographic area, and fasting time at blood collection. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for pancreatic cancer were calculated using conditional logistic regression models with adjustment for potential confounding factors.

RESULTS

Increased plasma BCAA levels at baseline were associated with an increased risk of pancreatic cancer. Compared with the lowest quartile of BCAA levels, the OR in the highest quartile was 2.43 (95% CI 1.21-4.90), and the OR per 1 SD increase in BCAA levels was 1.32 (95% CI 1.05-1.67). The association was especially strong for cases with blood samples collected at least 10 years before cancer diagnosis (OR per SD 1.60, 95% CI 1.10-2.32) compared with those detected less than 10 years before diagnosis (OR per SD 1.16, 95% CI 0.86-1.57).

CONCLUSIONS

In an analysis of data from the Japan Public Health Center-based prospective study, we found an association between increased plasma BCAA level and increased risk of pancreatic cancer-particularly when the increase in BCAAs was observed at least 10 years before diagnosis. These findings add to the growing body of evidence for the association between BCAA levels and pancreatic cancer risk.

Normalization of abnormal plasma amino acid profile-based indexes in patients with gynecological malignant tumors after curative treatment

BACKGROUND

We developed a novel plasma amino acid profile-based index (API) to detect ovarian, uterine, cervical, and endometrial cancers. In this study, we aimed to evaluate whether abnormal API values could be normalized after curative treatment in patients with gynecological malignant tumors.

METHODS

Patients with gynecological cancer with abnormal API values were included in this study. Pre-operative absolute API values were compared with those after curative treatment. The normalization rates of API values in patients negative for the expression of three well-known tumor markers (SCC, CA125, and CA19-9) were also evaluated. In addition, related amino acid profiles in healthy controls and patients under pre- and post-treatment conditions were analyzed.

RESULTS

Among 94 patients with abnormal pre-operative API values, the median API value was decreased from 9.52 to 2.17 after treatment (normalization rate: 88.3%). The decreased ranges were similar in patients with adenocarcinoma (6.28; 95% confidence interval [CI]: 5.43-6.95) and squamous carcinoma (7.44; 95% CI: 3.04-8.46). In 93.5% (43/46) of patients negative for tumor markers prior to operation, API values were normalized after the successful treatment. In addition, some pre-operative abnormal amino acid profiles, including Ile, Trp, and His, were reversibly normalized after treatment.

CONCLUSION

The API is a promising tumor marker in gynecological malignancies for the diagnosis of remission, particularly in patients negative for general tumor markers. Further studies are needed to explore the mechanisms related to the normalization of abnormal amino acid profiles.

Post-operative AICS status in completely resected lung cancer patients with pre-operative AICS abnormalities: predictive significance of disease recurrence

The AminoIndex^TM Cancer Screening (AICS) system, a plasma-free amino acid (PFAA)-based multivariate discrimination index, is a blood screening test for lung cancer based on the comparison of PFAA concentrations between patients with lung cancer and healthy controls. Pre- and post-operative AICS values were compared among 72 patients who underwent curative resection for lung cancer. Post-operative changes in PFAA concentrations were also evaluated. AICS values were classified as rank A (0.0–4.9), B (5.0–7.9), or C (8.0–10.0). Rank B–C patients were evaluated for outcomes and post-operative changes in their AICS values. Twenty-three of the 44 pre-operative rank B–C patients experienced post-operative reductions in AICS rank. Only one patient experienced cancer recurrence. Post-operative changes in PFAA concentrations were associated with the risk of post-operative cancer recurrence (p = 0.001). Multivariate analysis revealed that the absence of a post-operative reduction in AICS rank independently predicted cancer recurrence (hazard ratio: 14.28; p = 0.012). The majority of patients had high pre-operative AICS values and exhibited a reduction in AICS rank after curative resection. However, the absence of a post-operative reduction in AICS rank was associated with cancer recurrence, suggesting that AICS rank may be a sensitive marker of post-operative recurrence.

A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer

INTRODUCTION

Metabolomics is an emerging approach for early detection of cancer. Along with the development of metabolomics, high-throughput technologies and statistical learning, the integration of multiple biomarkers has significantly improved clinical diagnosis and management for patients.

OBJECTIVES

In this study, we conducted a systematic review to examine recent advancements in the oncometabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer.

METHODS

PubMed, Scopus, and Web of Science were searched for relevant studies published before September 2017. We examined the study designs, the metabolomics approaches, and the reporting methodological quality following PRISMA statement. RESULTS AND CONCLUSION: The included 25 studies primarily focused on the identification rather than the validation of predictive capacity of potential biomarkers. The sample size ranged from 10 to 8760. External validation of the biomarker panels was observed in nine studies. The diagnostic area under the curve ranged from 0.68 to 1.00 (sensitivity: 0.43-1.00, specificity: 0.73-1.00). The effects of patients' bio-parameters on metabolome alterations in a context-dependent manner have not been thoroughly elucidated. The most reported candidates were glutamic acid and histidine in seven studies, and glutamine and isoleucine in five studies, leading to the predominant enrichment of amino acid-related pathways. Notably, 46 metabolites were estimated in at least two studies. Specific challenges and potential pitfalls to provide better insights into future research directions were thoroughly discussed. Our investigation suggests that metabolomics is a robust approach that will improve the diagnostic assessment of pancreatic cancer. Further studies are warranted to validate their validity in multi-clinical settings.

Targeting tryptophan availability to tumors: the answer to immune escape?

Tumoral immune escape is an obstacle to successful cancer therapy. Tryptophan (Trp) metabolites along the kynurenine pathway induce immunosuppression involving apoptosis of effector immune cells, which tumors use to escape an immune response. Production of these metabolites is initiated by indoleamine 2,3-dioxygenase (IDO1). IDO1 inhibitors, however, do not always overcome the immune escape and another enzyme expressed in tumors, Trp 2,3-dioxygenase (TDO2), has been suggested as the reason. However, without Trp, tumors cannot achieve an immune escape through either enzyme. Trp is therefore key to immune escape. In this perspective paper, Trp availability to tumors will be considered and strategies limiting it proposed. One major determinant of Trp availability is the large increase in plasma free (non-albumin-bound) Trp in cancer patients, caused by the low albumin and the high non-esterified fatty acid (NEFA) concentrations in plasma. Albumin infusions, antilipolytic therapy or both could be used, if indicated, as adjuncts to immunotherapy and other therapies. Inhibition of amino acid uptake by tumors is another strategy and α-methyl-DL-tryptophan or other potential inhibitors could fulfill this role. Glucocorticoid receptor antagonists may have a role in preventing glucocorticoid induction of TDO in host liver and tumors expressing it and in undermining the permissive effect of glucocorticoids on IDO1 induction by cytokines. Nicotinamide may be a promising TDO2 inhibitor lacking disadvantages of current inhibitors. Establishing the Trp disposition status of cancer patients and in various tumor types may provide the information necessary to formulate tailored therapeutic approaches to cancer immunotherapy that can also undermine tumoral immune escape.

A review of validated biomarkers obtained through metabolomics

INTRODUCTION

Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.

Amino acid kinetics and the response to nutrition in patients with cancer

PURPOSE

Amino acids are involved in many physiological processes in the body and serve as building blocks of proteins which are the main component of muscle mass. Often patients with cancer experience muscle wasting, which is associated with poor outcomes. The purpose of this paper is to discuss amino acid kinetics in cancer, review the evidence on the response to nutrition in patients with cancer, and to give recommendations on the appropriate level of amino acid or protein intake in cancer. Current evidence shows that amino acid kinetics in patients with cancer are disturbed, as reflected by increased and decreased levels of plasma amino acids, an increased whole body turnover of protein and muscle protein breakdown. A few studies show beneficial effects of acute and short-term supplementation of high protein meals or essential amino acid mixtures on muscle protein synthesis.

CONCLUSIONS

Cancer is associated with disturbances in amino acid kinetics. A high protein intake or supplementation of amino acids may improve muscle protein synthesis. Future research needs to identify the optimal level and amino acid mixtures for patients with cancer, in particular for those who are malnourished.

Free amino acid profiling of gastric juice as a method for discovering potential biomarkers of early gastric cancer

Background: Prior studies showed that aromatic amino acids (AAAs) could be used as potential gastric juice biomarkers in screening gastric cancer (GC). To identify new biomarkers for early diagnosis of GC, the characteristics of gastric juice free amino acid (GJFAA) profiling was determined. Method: First, gastric juice was collected from 130 consecutive patients who underwent gastroscopy. They were divided into GC group (n = 47) and non-neoplastic gastric disease (NGD) group (n = 83) according to the pathological diagnosis. The concentrations of 34 GJFAAs were examined by amino acid analyzer. Multivariate and univariate analyses were used for comparing the alterations of GJFAA profiles between the two groups. Then candidate differential GJFAAs were verified by LC-MS/MS in another set of patients, which included 32 GC patients and 38 NGD patients. The diagnostic performance of GJFAAs was evaluated by ROC curve. Results: Significant alterations in GJFAA profiles were observed in GC patients compared to NGD patients in the training set. A total of 14 amino acids were screened as differential GJFAAs. Leucine, threonine and serine were the most frequently altered. Combined AUC of the three non-AAAs [0.869 (95% CI, 0.805-0.934)] was superior to the combined three AAAs [0.841 (95% CI, 0.773-0.908)]. In addition, a combined AUC comprisingthe six ones was further improved to 0.871 (95% CI, 0.809-0.933) in the diagnosis of GC. A similar variation trend and diagnostic value were observed in the validation set. Conclusion: This study indicates the potential of GJFAA profiling as a promising approach for the early detection and screening of GC.

Metabolome analysis for pancreatic cancer risk in nested case-control study: Japan Public Health Center-based prospective Study

Discovery of a high-risk group for pancreatic cancer is important for prevention of pancreatic cancer. The present study was conducted as a nested case-control study including 170 pancreatic cancer cases and 340 matched controls of our population-based cohort study involving 30 239 subjects who answered a baseline questionnaire and supplied blood samples. Twelve targeted metabolites were quantitatively analyzed by gas chromatography/tandem mass spectrometry. Odds ratios (OR) and their corresponding 95% confidence intervals (CI) were calculated using conditional logistic regression models. Statistically significant P-value was defined as P < .05. Increasing 1,5-anhydro-d-glucitol (1,5-AG) levels were associated with a decreasing trend in pancreatic cancer risk (OR of quartile 4 [Q4], 0.50; 95% CI, 0.27-0.93; P = .02). Increasing methionine levels were also associated with an increasing trend of pancreatic cancer risk (OR of Q4, 1.79; 95% CI, 0.94-3.40: P = .03). Additional adjustment for potential confounders attenuated the observed associations of 1,5-AG and methionine (P for trend = .06 and .07, respectively). Comparing subjects diagnosed in the first 0-6 years, higher levels of 1,5-AG, asparagine, tyrosine and uric acid showed a decreasing trend for pancreatic cancer risk (P for trend = .04, .04, .04 and .02, respectively), even after adjustment for potential confounders. We found that the 12 target metabolites were not associated with pancreatic cancer risk. However, metabolic changes in the subjects diagnosed in the first 0-6 years showed a similar tendency to our previous reports. These results might suggest that these metabolites are useful for early detection but not for prediction of pancreatic cancer.