The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

Factors associated with radiological misstaging of pancreatic ductal adenocarcinoma: A retrospective observational study

PURPOSE

Accurate staging of disease is vital in determining appropriate care for patients with pancreatic ductal adenocarcinoma (PDAC). It has been shown that the quality of scans and the experience of a radiologist can impact computed tomography (CT) based assessment of disease. The aim of the current study was to evaluate the impact of the rereading of outside hospital (OH) CT by an expert radiologist and a repeat pancreatic protocol CT (PPCT) on staging of disease.

METHODS

Patients evaluated at the our institute's pancreatic multidisciplinary clinic (2006 to 2014) with OH scan and repeat PPCT performed within 30 days were included. In-house radiologists staged disease using OH scans and repeat PPCT, and factors associated with misstaging were determined.

RESULTS

The study included 100 patients, with a median time between OH scan and PPCT of 19 days (IQR: 13-23 days.) Stage migration was mostly accounted for by upstaging of disease (58.8 % to 83.3 %) in all comparison groups. When OH scans were rereviewed, 21.5 % of the misstaging was due to missed metastases, however, when rereads were compared to the PPCT, occult metastases accounted for the majority of misstaged patients (62.5 %). Potential factors associated with misstaging were primarily related to imaging technique.

CONCLUSION

A repeat PPCT results in increased detection of metastatic disease that rereviews of OH scans may otherwise miss. Accessible insurance coverage for repeat PPCT imaging even within 30 days of an OH scan could help optimize delivery of care and alleviate burdens associated with misstaging.

Meta-analysis of adjuvant chemotherapy versus no adjuvant chemotherapy for resected stage I pancreatic cancer

BACKGROUND

To evaluate comparative outcomes of pancreatic cancer resection with or without adjuvant chemotherapy in patients with stage I pancreatic cancer.

METHODS

A systematic search of MEDLINE, CENTRAL, and Web of Science and bibliographic reference lists were conducted. All comparative studies reporting outcomes of pancreatic cancer resection for stage I cancer with or without adjuvant chemotherapy were included, and their risk of bias was assessed using the Risk Of Bias In Non-randomized Studies-of Interventions tool. Survival outcomes were analyzed using the hazard ratio and odds ratio for the time-to-event and dichotomous outcomes, respectively.

RESULTS

We included 6 comparative studies reporting a total of 6,874 patients with resected stage 1 pancreatic cancer, of whom 3,951 patients had no adjuvant chemotherapy, and the remaining 2,923 patients received adjuvant chemotherapy. The use of adjuvant chemotherapy was associated with significantly higher overall survival (hazard ratio 0.71, 95% confidence interval 0.62-0.82, P < .00001) and 2-year survival (65.1% vs 57.4%, odds ratio 1.99; 95% confidence interval 1.01-1.41, P = .04) compared to no use of adjuvant chemotherapy. However, there was no statistically significant difference in 1-year (86.8% vs 78.4%, odds ratio 1.60; 95% confidence interval 0.72-3.57, P = .25), 3-year (46.0% vs 44.0%, odds ratio 1.07; 95% confidence interval 0.90-1.29, P = .43), or 5-year survival (24.8% vs 23.3%, odds ratio 1.03; 95% confidence interval 0.80-1.33, P = .81) between the 2 groups.

CONCLUSION

Meta-analysis of best available evidence (level 2a with low to moderate certainty) demonstrates that adjuvant chemotherapy may confer survival benefits for stage I pancreatic cancer when compared to the use of surgery alone. Randomized control trials are required to escalate the level of evidence and confirm these findings with consideration of contemporary chemotherapy agents and regimens.

IGFBP2 promotes proliferation and cell migration through STAT3 signaling in Sonic hedgehog medulloblastoma

Medulloblastoma (MB) is the most common pediatric brain malignancy and is divided into four molecularly distinct subgroups: WNT, Sonic Hedgehog (SHHp53mut and SHHp53wt), Group 3, and Group 4. Previous reports suggest that SHH MB features a unique tumor microenvironment compared with other MB groups. To better understand how SHH MB tumor cells interact with and potentially modify their microenvironment, we performed cytokine array analysis of culture media from freshly isolated MB patient tumor cells, spontaneous SHH MB mouse tumor cells and mouse and human MB cell lines. We found that the SHH MB cells produced elevated levels of IGFBP2 compared to non-SHH MBs. We confirmed these results using ELISA, western blotting, and immunofluorescence staining. IGFBP2 is a pleiotropic member of the IGFBP super-family with secreted and intracellular functions that can modulate tumor cell proliferation, metastasis, and drug resistance, but has been understudied in medulloblastoma. We found that IGFBP2 is required for SHH MB cell proliferation, colony formation, and cell migration, through promoting STAT3 activation and upregulation of epithelial to mesenchymal transition markers; indeed, ectopic STAT3 expression fully compensated for IGFBP2 knockdown in wound healing assays. Taken together, our findings reveal novel roles for IGFBP2 in SHH medulloblastoma growth and metastasis, which is associated with very poor prognosis, and they indicate an IGFBP2-STAT3 axis that could represent a novel therapeutic target in medulloblastoma.

The association between CD3+ and CD8+tumor-infiltrating lymphocytes (TILs) and prognosis in patients with pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PDAC), with more than 250,000 deaths each year, is the eighth leading cause of death worldwide, with a five-year survival of less than 5% and a median recurrence time between 5 and 23 months. The association between PDAC and CD3⁺/CD8⁺ tumor-infiltrating lymphocytes (TILs) and the extent of tumor spread and clinical outcomes has been recently shown. This study aimed to determine and compare the density of TILs and their association with disease prognosis in patients with PDAC.

MATERIALS AND METHODS

In this study, we collected PDAC tissues and corresponding adjacent normal tissues from 64 patients with TIL-positive PDAC. The immunohistochemistry method was used for the detection of the expression levels of CD3⁺ and CD8⁺ TILs in PDAC tissues. Also, the completed follow-up history was evaluated for at least five years.

RESULTS

The frequency of intratumoral and peritumoral TILs was 20 (31.2%) and 44 (68.8%), respectively. The mean density of CD3⁺ TILs and CD8⁺ TILs was 67.73%±20.17% and 69.45%±17.82%, respectively. The density of CD3⁺ TILs and CD8⁺ TILs was not associated with overall survival nor metastasis-free survival of the patients and tumor grade. However, the density of TILs was significantly lower in those patients who experienced tumor recurrence than those without this recurrence.

CONCLUSION

TILs density was high in patients with PDAC. The density of both CD3⁺ and CD8⁺ TILs was significantly lower in patients who experienced tumor recurrence. Thus, this study suggests that tracking and determining the density of CD3⁺ and CD8⁺ TILs might be effective in predicting PDAC recurrence.

Bile Acids: Physiological Activity and Perspectives of Using in Clinical and Laboratory Diagnostics

Bile acids play a significant role in the digestion of nutrients. In addition, bile acids perform a signaling function through their blood-circulating fraction. They regulate the activity of nuclear and membrane receptors, located in many tissues. The gut microbiota is an important factor influencing the effects of bile acids via enzymatic modification. Depending on the rate of healthy and pathogenic microbiota, a number of bile acids may support lipid and glucose homeostasis as well as shift to more toxic compounds participating in many pathological conditions. Thus, bile acids can be possible biomarkers of human pathology. However, the chemical structure of bile acids is similar and their analysis requires sensitive and specific methods of analysis. In this review, we provide information on the chemical structure and the biosynthesis of bile acids, their regulation, and their physiological role. In addition, the review describes the involvement of bile acids in various diseases of the digestive system, the approaches and challenges in the analysis of bile acids, and the prospects of their use in omics technologies.

Risk prediction of pancreatic cancer using AI analysis of pancreatic subregions in computed tomography images

Early detection of Pancreatic Ductal Adenocarcinoma (PDAC) is complicated as PDAC remains asymptomatic until cancer advances to late stages when treatment is mostly ineffective. Stratifying the risk of developing PDAC can improve early detection as subsequent screening of high-risk individuals through specialized surveillance systems reduces the chance of misdiagnosis at the initial stage of cancer. Risk stratification is however challenging as PDAC lacks specific predictive biomarkers. Studies reported that the pancreas undergoes local morphological changes in response to underlying biological evolution associated with PDAC development. Accurate identification of these changes can help stratify the risk of PDAC. In this retrospective study, an extensive radiomic analysis of the precancerous pancreatic subregions was performed using abdominal Computed Tomography (CT) scans. The analysis was performed using 324 pancreatic subregions identified in 108 contrast-enhanced abdominal CT scans with equal proportion from healthy control, pre-diagnostic, and diagnostic groups. In a pairwise feature analysis, several textural features were found potentially predictive of PDAC. A machine learning classifier was then trained to perform risk prediction of PDAC by automatically classifying the CT scans into healthy control (low-risk) and pre-diagnostic (high-risk) classes and specifying the subregion(s) likely to develop a tumor. The proposed model was trained on CT scans from multiple phases. Whereas using 42 CT scans from the venous phase, model validation was performed which resulted in ~89.3% classification accuracy on average, with sensitivity and specificity reaching 86% and 93%, respectively, for predicting the development of PDAC (i.e., high-risk). To our knowledge, this is the first model that unveiled microlevel precancerous changes across pancreatic subregions and quantified the risk of developing PDAC. The model demonstrated improved prediction by 3.3% in comparison to the state-of-the-art method that considers the global (whole pancreas) features for PDAC prediction.

Galectins Are Central Mediators of Immune Escape in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and is highly immune tolerant. Although there is immune cell infiltration in PDAC tissues, most of the immune cells do not function properly and, therefore, the prognosis of PDAC is very poor. Galectins are carbohydrate-binding proteins that are intimately involved in the proliferation and metastasis of tumor cells and, in particular, play a crucial role in the immune evasion of tumor cells. Galectins induce abnormal functions and reduce numbers of tumor-associated macrophages (TAM), natural killer cells (NK), T cells and B cells. It further promotes fibrosis of tissues surrounding PDAC, enhances local cellular metabolism, and ultimately constructs tumor immune privileged areas to induce immune evasion behavior of tumor cells. Here, we summarize the respective mechanisms of action played by different Galectins in the process of immune escape from PDAC, focusing on the mechanism of action of Galectin-1. Galectins cause imbalance between tumor immunity and anti-tumor immunity by coordinating the function and number of immune cells, which leads to the development and progression of PDAC.

Predicting pancreatic ductal adenocarcinoma using artificial intelligence analysis of pre-diagnostic computed tomography images

BACKGROUND

Early stage diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is challenging due to the lack of specific diagnostic biomarkers. However, stratifying individuals at high risk of PDAC, followed by monitoring their health conditions on regular basis, has the potential to allow diagnosis at early stages.

OBJECTIVE

To stratify high risk individuals for PDAC by identifying predictive features in pre-diagnostic abdominal Computed Tomography (CT) scans.

METHODS

A set of CT features, potentially predictive of PDAC, was identified in the analysis of 4000 raw radiomic parameters extracted from pancreases in pre-diagnostic scans. The naïve Bayes classifier was then developed for automatic classification of CT scans of the pancreas with high risk for PDAC. A set of 108 retrospective CT scans (36 scans from each healthy control, pre-diagnostic, and diagnostic group) from 72 subjects was used for the study. Model development was performed on 66 multiphase CT scans, whereas external validation was performed on 42 venous-phase CT scans.

RESULTS

The system achieved an average classification accuracy of 86% on the external dataset.

CONCLUSIONS

Radiomic analysis of abdominal CT scans can unveil, quantify, and interpret micro-level changes in the pre-diagnostic pancreas and can efficiently assist in the stratification of high risk individuals for PDAC.

Data parsing in mass spectrometry imaging using R Studio and Cardinal: A tutorial

Mass spectrometry imaging (MSI) has emerged as a rapidly expanding field in the MS community. The analysis of large spectral data is further complicated by the added spatial dimension of MSI. A plethora of resources exist for expert users to begin parsing MSI data in R, but there is a critical lack of guidance for absolute beginners. This tutorial is designed to serve as a one-stop guide to start using R with MSI data and describe the possibilities that data science can bring to MSI analysis.

Reciprocal interplay between asporin and decorin: Implications in gastric cancer prognosis

Effective patient prognosis necessitates identification of novel tumor promoting drivers of gastric cancer (GC) which contribute to worsened conditions by analysing TCGA-gastric adenocarcinoma dataset. Small leucine-rich proteoglycans, asporin (ASPN) and decorin (DCN), play overlapping roles in development and diseases; however, the mechanisms underlying their interplay remain elusive. Here, we investigated the complex interplay of asporin, decorin and their interaction with TGFβ in GC tumor and corresponding normal tissues. The mRNA levels, protein expressions and cellular localizations of ASPN and DCN were analyzed using real-time PCR, western blot and immunohistochemistry, respectively. The protein-protein interaction was predicted by in-silico interaction analysis and validated by co-immunoprecipitation assay. The correlations between ASPN and EMT proteins, VEGF and collagen were achieved using western blot analysis. A significant increase in expression of ASPN in tumor tissue vs. normal tissue was observed in both TCGA and our patient cohort. DCN, an effective inhibitor of the TGFβ pathway, was negatively correlated with stages of GC. Co-immunoprecipitation demonstrated that DCN binds with TGFβ, in normal gastric epithelium, whereas in GC, ASPN preferentially binds TGFβ. Possible activation of the canonical TGFβ pathway by phosphorylation of SMAD2 in tumor tissues suggests its role as an intracellular tumor promoter. Furthermore, tissues expressing ASPN showed unregulated EMT signalling. Our study uncovers ASPN as a GC-promoting gene and DCN as tumor suppressor, suggesting that ASPN can act as a prognostic marker in GC. For the first time, we describe the physical interaction of TGFβ with ASPN in GC and DCN with TGFβ in GC and normal gastric epithelium respectively. This study suggests that prevention of ASPN-TGFβ interaction or overexpression of DCN could serve as promising therapeutic strategies for GC patients.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

IGFBP2 promotes tumor progression by inducing alternative polarization of macrophages in pancreatic ductal adenocarcinoma through the STAT3 pathway

Tumor-associated macrophages (TAMs) represent the M2-like phenotype with potent immunosuppressive activity, and play a pro-tumor role in pancreatic ductal adenocarcinoma (PDAC) biology. In this study, we investigated the role of the insulin-like growth factor binding protein 2 (IGFBP2) as a determinant of TAM polarity. Clinical data revealed that the levels of IGFBP2 correlated with M2 TAMs accumulation and disease progression in human PDAC. In vivo mouse model experiments showed that IGFBP2 promoted an immunosuppressive microenvironment and tumor growth in a macrophage dependent manner. Bioinformatics analysis of PDAC transcriptomes revealed a significant association between IGFBP2 expression and M2 macrophage polarization and signal transducer and activator of transcription 3 (STAT3) activation. Mechanistic investigations demonstrated that IGFBP2 augmented the expression and secretion of IL-10 through STAT3 activation in PDAC cells, which induced TAM polarization toward an M2 phenotype. IGFBP2-polarized M2 macrophages significantly increased Tregs infiltration and impaired antitumor T-cell immunity in a mouse model. Thus, our investigations have illuminated the IGFBP2 signaling pathway that contributes to the macrophage-based immunosuppressive microenvironment in PDAC, suggesting that blocking the IGFBP2 axis constitutes a potential treatment strategy to reset TAM polarization toward an antitumor state in PDAC.

Integrin and autocrine IGF2 pathways control fasting insulin secretion in β-cells

Elevated levels of fasting insulin release and insufficient glucose-stimulated insulin secretion (GSIS) are hallmarks of diabetes. Studies have established cross-talk between integrin signaling and insulin activity, but more details of how integrin-dependent signaling impacts the pathophysiology of diabetes are needed. Here, we dissected integrin-dependent signaling pathways involved in the regulation of insulin secretion in β-cells and studied their link to the still debated autocrine regulation of insulin secretion by insulin/insulin-like growth factor (IGF) 2-AKT signaling. We observed for the first time a cooperation between different AKT isoforms and focal adhesion kinase (FAK)-dependent adhesion signaling, which either controlled GSIS or prevented insulin secretion under fasting conditions. Indeed, β-cells form integrin-containing adhesions, which provide anchorage to the pancreatic extracellular matrix and are the origin of intracellular signaling via FAK and paxillin. Under low-glucose conditions, β-cells adopt a starved adhesion phenotype consisting of actin stress fibers and large peripheral focal adhesion. In contrast, glucose stimulation induces cell spreading, actin remodeling, and point-like adhesions that contain phospho-FAK and phosphopaxillin, located in small protrusions. Rat primary β-cells and mouse insulinomas showed an adhesion remodeling during GSIS resulting from autocrine insulin/IGF2 and AKT1 signaling. However, under starving conditions, the maintenance of stress fibers and the large adhesion phenotype required autocrine IGF2-IGF1 receptor signaling mediated by AKT2 and elevated FAK-kinase activity and ROCK-RhoA levels but low levels of paxillin phosphorylation. This starved adhesion phenotype prevented excessive insulin granule release to maintain low insulin secretion during fasting. Thus, deregulation of the IGF2 and adhesion-mediated signaling may explain dysfunctions observed in diabetes.

[Laboratory diagnostics in medicine]

The development of clinical laboratory diagnostics is in line with the evidence-based medicine, which requires that clinical decisions have to be based on diagnostic methods with proven informativity. This creates a request for the scientific validity of the use of laboratory researches and application of probabilistic interpretation tools corresponding to the tasks. The concept of indefiniteness (analytical, biological and clinical) is at the heart of interpretation of laboratory results. The inclusion of laboratory research in clinical guidelines, the choice and appointment of this research to the patient should not be made from the position of ideas about increasing or decreasing the laboratory index in the disease, but on the basis of its scientifically proven characteristics as a laboratory biomarker sensitivity, specificity, predictive value, as well as the relationship with certain clinical events, outcomes, risks. These characteristics are probabilistic and can be defined.

Identification of dissociation factors in pancreatic Cancer using a mass spectrometry-based proteomic approach

Backgroud

Pancreatic cancer is a highly malignant tumor of the digestive system. This secretome of pancreatic cancer is key to its progression and metastasis. But different methods of protein extraction affect the final results. In other words, the real secretion of proteins in cancer cells has been changed. Based on mass spectrometry, we analyze the secretome from the serum-containing and serum-free medium, using different protein pretreatment methods. This study aims to identify dissociation factors in pancreatic cancer.

Methods

In this study, pancreatic cancer cells were cultured in serum-containing or serum-free medium, and the corresponding supernatants were extracted as samples. Subsequently, the above samples were separated by size exclusion chromatography (SEC), and peptide segments were identified by LC-MS/MS. The final results were identified via the hamster secreted protein database and a public database.

Results

Although the number of identified proteins in the serum-free medium group was high, the real secretion of proteins in pancreatic cancer cells was changed. There were six significant secreted proteins in the serum-containing medium group. Survival analysis via the TCGA database suggested that patients with higher expression levels of YWHAG showed a worse overall survival rate than those with lower YWHAG expression.

Conclusions

Our study demonstrated the results in the serum-containing medium group were more similar to the real secretome of pancreatic cancer cells. YWHAG could be used as a prognostic indicator for pancreatic cancer.

Alpha-1-acid glycoprotein 1 is upregulated in pancreatic ductal adenocarcinoma and confers a poor prognosis

Pancreatic cancer is an aggressive malignancy that carries a high mortality rate. A major contributor to the poor outcome is the lack of effective molecular markers. The purpose of this study was to develop protein markers for improved prognostication and noninvasive diagnosis. A mass spectrometry (MS)-based discovery approach was applied to pancreatic cancer tissues and healthy pancreas. In the verification phase, extracellular proteins with differential expression were further quantified in targeted mode using parallel reaction monitoring (PRM). Next, a tissue microarray (TMA) cohort including 140 pancreatic cancer resection specimens was constructed, in order to validate protein expression status and investigate potential prognostic implications. The levels of protein candidates were finally assessed in a prospective series of 110 serum samples in an accredited clinical laboratory using the automated Cobas system. Protein sequencing with nanoliquid chromatography tandem MS (nano-LC-MS/MS) and targeted PRM identified alpha-1-acid glycoprotein 1 (AGP1) as an upregulated protein in pancreatic cancer tissue. Using TMA and immunohistochemistry, AGP1 expression was significantly associated with shorter overall survival (HR = 2.22; 95% CI 1.30-3.79, P =  0.004). Multivariable analysis confirmed the results (HR = 1.87; 95% CI 1.08-3.24, P  =  0.026). Circulating levels of AGP1 yielded an area under the curve (AUC) of 0.837 for the discrimination of resectable pancreatic cancer from healthy controls. Combining AGP1 with CA 19-9 enhanced the diagnostic performance, with an AUC of 0.963. This study suggests that AGP1 is a novel prognostic biomarker in pancreatic cancer tissue. Serum AGP1 levels may be useful as part of a biomarker panel for early detection of pancreatic cancer but further studies are needed.

Quantitative proteomics identifies brain acid soluble protein 1 (BASP1) as a prognostic biomarker candidate in pancreatic cancer tissue

BACKGROUND

Pancreatic cancer is a heterogenous disease with a poor prognosis. This study aimed to discover and validate prognostic tissue biomarkers in pancreatic cancer using a mass spectrometry (MS) based proteomics approach.

METHODS

Global protein sequencing of fresh frozen pancreatic cancer and healthy pancreas tissue samples was conducted by MS to discover potential protein biomarkers. Selected candidate proteins were further verified by targeted proteomics using parallel reaction monitoring (PRM). The expression of biomarker candidates was validated by immunohistochemistry in a large tissue microarray (TMA) cohort of 141 patients with resectable pancreatic cancer. Kaplan-Meier and Cox proportional hazard modelling was used to investigate the prognostic utility of candidate protein markers.

FINDINGS

In the initial MS-discovery phase, 165 proteins were identified as potential biomarkers. In the subsequent MS-verification phase, a panel of 45 candidate proteins was verified by the development of a PRM assay. Brain acid soluble protein 1 (BASP1) was identified as a new biomarker candidate for pancreatic cancer possessing largely unknown biological and clinical functions and was selected for further analysis. Importantly, bioinformatic analysis indicated that BASP1 interacts with Wilms tumour protein (WT1) in pancreatic cancer. TMA-based immunohistochemistry analysis showed that BASP1 was an independent predictor of prolonged survival (HR 0.468, 95% CI 0.257-0.852, p = .013) and predicted favourable response to adjuvant chemotherapy, whereas WT1 indicated a worsened survival (HR 1.636, 95% CI 1.083-2.473, p = .019) and resistance to chemotherapy. Interaction analysis showed that patients with negative BASP1 and high WT1 expression had the poorest outcome (HR 3.536, 95% CI 1.336-9.362, p = .011).

INTERPRETATION

We here describe an MS-based proteomics platform for developing biomarkers for pancreatic cancer. Bioinformatic analysis and clinical data from our study suggest that BASP1 and its putative interaction partner WT1 can be used as biomarkers for predicting outcomes in pancreatic cancer patients.

Proteomic and genomic profiling of pancreatic cancer

Pancreatic cancer remains the most fatal human tumor type. The aggressive tumor biology coupled with the lack of early detection strategies and effective treatment are major reasons for the poor survival rate. Collaborative research efforts have been devoted to understand pancreatic cancer at the molecular level. Large-scale genomic studies have generated important insights into the genetic drivers of pancreatic cancer. In the post-genomic era, protein sequencing of tumor tissue, cell lines, pancreatic juice, and blood from patients with pancreatic cancer has provided a fundament for the development of new diagnostic and prognostic biomarkers. The integration of mass spectrometry and genomic sequencing strategies may help characterize protein identities and post-translational modifications that relate to a specific mutation. Consequently, proteomic and genomic techniques have become a compulsory requirement in modern medicine and health care. These types of proteogenomic studies may usher in a new era of precision diagnostics and treatment in patients with pancreatic cancer.

Cytoplasmic Asporin promotes cell migration by regulating TGF-β/Smad2/3 pathway and indicates a poor prognosis in colorectal cancer

Previous studies revealed that Asporin (ASPN) is a potential mediator in the development of various types of cancer as a secreted stroma protein, but the function of ASPN inside the cancer cells remains largely unknown. Here, we demonstrated a higher expression level of ASPN in colorectal cancer (CRC) than matched normal tissues, and 25% (2/8) CRC showed copy number variation (CNV) gain/amplification in ASPN gene. Both higher ASPN expression levels and ASPN CNV gain/amplification indicated a worse prognosis in CRC patients. ASPN can promote proliferation, migration, and invasion of CRC cells, and inhibit apoptosis by activating Akt/Erk and TGF-β/Smad2/3 signalings. Further investigations revealed that ASPN interacts with Smad2/3, facilitates its translocation into nucleus, and up-regulates the expression of Epithelial-mesenchymal transition (EMT) related genes. Rescue assays confirmed that TGF-β signaling is essential for the effects of ASPN on promoting CRC cell migration and invasion. In conclusion, ASPN promotes the migration and invasion of CRC cells via TGF-β/Smad2/3 pathway and could serve as a potential prognostic biomarker in CRC patients.

Prognostic Impact of Tumor-Infiltrating Lymphocytes and Neutrophils on Survival of Patients with Upfront Resection of Pancreatic Cancer

In patients with pancreatic ductal adenocarcinoma (PDAC), the tumor microenvironment consists of cellular and stromal components that influence prognosis. Hence, tumor-infiltrating lymphocytes (TILs) may predict prognosis more precisely than conventional staging systems. Studies on the impact of TILs are heterogeneous and further research is needed. Therefore, this study aims to point out the importance of peritumoral TILs, tumor-infiltrating neutrophils (TINs), and immune subtype classification in PDAC. Material from 57 patients was analyzed with immunohistochemistry performed for CD3, CD8, CD20, CD66b, α-sma, and collagen. Hot spots with peritumoral TILs and TINs were quantified according to the QTiS algorithm and the distance of TILs hot spots to the tumor front was measured. Results were correlated with overall (OS) and progression-free survival (PFS). High densities of peritumoral hot spots with CD3⁺, CD8⁺, and CD20⁺ TILs correlated significantly with improved OS and PFS. Combined immune cell subtypes predicted improved OS and PFS. High infiltration of CD3⁺ TILs predicted progression after 12 months. The location of TILs' hot spots and their distance to the tumor front did not correlate with patient survival. Peritumoral TILs and the composition of the stroma predict OS and PFS in PDAC.

Biomarkers of translational medicine

The development of new medicines is one of the priority areas of translational medicine. A significant role for biomarkers (BM) that assess the safety and efficacy of new drugs. The right choice of BM reduces the time and costs necessary for the development of drugs and transfer them to the clinic. The review is devoted to the analysis of modern scientific literature on the role of previously known and newly discovered BM in translational research. Translational BM (TBM) established during preclinical studies and are applicable at all stages of the study. TBM should have a high sensitivity and specificity, be easily measured in real time in an easily accessible biological fluids, to evaluate the same process in different species of animals (including humans), make it possible to compare the results of clinical trials with preclinical. The main role of the TBM toxicity to predict, identify and monitor the toxicity of drugs at all stages of their study. The international consortium (Predictive Safety Testing Consortium, PSTC) whose main task is the qualification of new TBM toxicity and the search for new, more advanced than existing methods for testing markers, was established. Under PSTC formed 6 working groups, each of which coordinates research for the study and selection of TBM toxicity caused by the administration of drugs in the liver, kidney, heart and blood vessels, skeletal muscle, testes. The first qualified consortium markers were 7 contained in the urine markers for preclinical studies on rats with the goal of establishing early lesions in the kidney induced by drugs. Only a small number of BM used in the study of new drugs, can be translational.

Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis

Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC.

Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein–protein interaction network and Cox proportional hazards model analyses.

Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals.

Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC.

The emerging role of galectins in high-fatality cancers

Although we witnessed considerable progress in the prevention and treatment of cancer during the past few decades, a number of cancers remain difficult to treat. The main reasons for this are a lack of effective biomarkers necessary for an early detection and inefficient treatments for cancer that are diagnosed at late stages of the disease. Because of their alarmin-like properties and their protumorigenic role during cancer progression, members of the galectin family are uniquely positioned to provide information that could be used for the exploration of possible avenues for the treatment of high fatality cancer (HFC). A rapid overview of studies that examined the expressions and functions of galectins in cancer cells reveals that they play a central role in at least three major features that characterize HFCs: (1) induction of systemic and local immunosuppression, (2) chemoresistance of cancer cells, and (3) increased invasive behavior. Defining the galectinome in HFCs will also lead to a better understanding of tumor heterogeneity while providing critical information that could improve the accuracy of biomarker panels for a more personalized treatment of HFCs. In this review, we discuss the relevance of the galectinome in HFC and its possible contribution to providing potential solutions.

Asporin enhances colorectal cancer metastasis through activating the EGFR/src/cortactin signaling pathway

Asporin has been implicated as an oncogene in various types of human cancers; however, the roles of asporin in the development and progression of colorectal cancer (CRC) have not yet been determined. With clinical samples, we found that asporin was highly expressed in CRC tissues compared to adjacent normal tissues and the asporin expression levels were significantly associated with lymph node metastasis status and TNM stage of the patients. Through knockdown of asporin in CRC cell lines RKO and SW620 or overexpression of asporin in cell lines HT-29 and LoVo, we found that asporin could enhance wound healing, migration and invasion abilities of the CRC cells. Further more, with the human umbilical vein endothelial cells (HUVECs) tube formation assays and the xenograft model, we found that asporin promoted the tumor growth through stimulating the VEGF signaling pathway. The portal vein injection models suggested that asporin overexpression stimulated the liver metastasis of HT29 cell line, while asporin knockdown inhibited the liver metastasis of RKO cell line. In addition, asporin was found to augment the phosphorylation of EGFR/src/cortactin signaling pathway, which might be contributed to the biological functions of asporin in CRC metastasis. These results suggested that asporin promoted the tumor growth and metastasis of CRC, and it could be a potential therapeutic target for CRC patients in future.

Proteomic analyses identify prognostic biomarkers for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Here we show that shotgun and targeted protein sequencing can be used to identify potential prognostic biomarkers in formalin-fixed paraffin-embedded specimens from 9 patients with PDAC with “short” survival (<12 months) and 10 patients with “long” survival (>45 months) undergoing surgical resection. A total of 24 and 147 proteins were significantly upregulated [fold change ≥2 or ≤0.5 and P<0.05; or different detection frequencies (≥5 samples)] in patients with “short” survival (including GLUT1) and “long” survival (including C9orf64, FAM96A, CDH1 and CDH17), respectively. STRING analysis of these proteins indicated a tight protein-protein interaction network centered on TP53. Ingenuity pathway analysis linked proteins representing “activated stroma factors” and “basal tumor factors” to poor prognosis of PDAC. It also highlighted TCF1 and CTNNB1 as possible upstream regulators. Further parallel reaction monitoring verified that seven proteins were upregulated in patients with “short” survival (MMP9, CLIC3, MMP8, PRTN3, P4HA2, THBS1 and FN1), while 18 proteins were upregulated in patients with “long” survival, including EPCAM, LGALS4, VIL1, CLCA1 and TPPP3. Thus, we verified 25 protein biomarker candidates for PDAC prognosis at the tissue level. Furthermore, an activated stroma status and protein-protein interactions with TP53 might be linked to poor prognosis of PDAC.

Chemical composition and the potential for proteomic transformation in cancer, hypoxia, and hyperosmotic stress

The changes of protein expression that are monitored in proteomic experiments are a type of biological transformation that also involves changes in chemical composition. Accompanying the myriad molecular-level interactions that underlie any proteomic transformation, there is an overall thermodynamic potential that is sensitive to microenvironmental conditions, including local oxidation and hydration potential. Here, up- and down-expressed proteins identified in 71 comparative proteomics studies were analyzed using the average oxidation state of carbon (Z_C) and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O), calculated using elemental abundances and stoichiometric reactions to form proteins from basis species. Experimental lowering of oxygen availability (hypoxia) or water activity (hyperosmotic stress) generally results in decreased Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of up-expressed compared to down-expressed proteins. This correspondence of chemical composition with experimental conditions provides evidence for attraction of the proteomes to a low-energy state. An opposite compositional change, toward higher average oxidation or hydration state, is found for proteomic transformations in colorectal and pancreatic cancer, and in two experiments for adipose-derived stem cells. Calculations of chemical affinity were used to estimate the thermodynamic potentials for proteomic transformations as a function of fugacity of O₂ and activity of H₂O, which serve as scales of oxidation and hydration potential. Diagrams summarizing the relative potential for formation of up- and down-expressed proteins have predicted equipotential lines that cluster around particular values of oxygen fugacity and water activity for similar datasets. The changes in chemical composition of proteomes are likely linked with reactions among other cellular molecules. A redox balance calculation indicates that an increase in the lipid to protein ratio in cancer cells by 20% over hypoxic cells would generate a large enough electron sink for oxidation of the cancer proteomes. The datasets and computer code used here are made available in a new R package, canprot.

A Network Pharmacology Approach to Explore the Pharmacological Mechanism of Xiaoyao Powder on Anovulatory Infertility

Aim. To explore the pharmacological mechanism of Xiaoyao powder (XYP) on anovulatory infertility by a network pharmacology approach. Method. Collect XYP's active compounds by traditional Chinese medicine (TCM) databases, and input them into PharmMapper to get their targets. Then note these targets by Kyoto Encyclopedia of Genes and Genomes (KEGG) and filter out targets that can be noted by human signal pathway. Get the information of modern pharmacology of active compounds and recipe's traditional effects through databases. Acquire infertility targets by Therapeutic Target Database (TTD). Collect the interactions of all the targets and other human proteins via String and INACT. Put all the targets into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to do GO enrichment analysis. Finally, draw the network by Cytoscape by the information above. Result. Six network pictures and two GO enrichment analysis pictures are visualized. Conclusion. According to this network pharmacology approach some signal pathways of XYP acting on infertility are found for the first time. Some biological processes can also be identified as XYP's effects on anovulatory infertility. We believe that evaluating the efficacy of TCM recipes and uncovering the pharmacological mechanism on a systematic level will be a significant method for future studies.

Cancer heterogeneity determined by functional proteomics

Current manuscript gives a synopsis of tumor heterogeneity related to patient samples analyzed by proteomics, protein expression analysis and imaging mass spectrometry. First, we discuss the pathophysiologocal background of cancer biology as a multifactorial and challenging diseases. Disease pathology forms the basis for protein target selection. Therefore, histopathological diagnostics and grading of tumors is highlighted. Pathology is the cornerstone of state-of-the-art diagnostics of tumors today both by establishing dignity and - when needed - describing molecular properties of the cancers. Drug development by the pharmaceutical industry utilizes proteomics studies to pinpoint the most relevant targets. Molecular studies profiling affinity-interactions of the protein(s) with targeted small drug molecules to reach efficacy and optimal patient safety are today requested by the FDA and other agencies for new drug development. An understading of basic mechanisms, controlling drug action and drug binding is central, as a new era of personalized medicine becomes an important milestone solution for the healthcare sector as well as the Pharma and Biotech industry. Development of further diagnostic, prognostic and predictive tests will aid current and future treatment of cancer patients. In the paper we present current status of Proteomics that we believe requires attention in order to collectively advance forward in the fight against cancer, addressing the burning opportunities and challenges.

Available technologies and clinical applications of targeted chemotherapy in pancreatic cancer

The incidence of pancreatic cancer, the fourth leading cause of cancer death in United States, is increasing worldwide. Even though the cure rate has doubled in 40 years, it is abysmally poor at 6-7%. As surgical resection remains the only curative treatment and less than 20% of the newly diagnosed cancers are resectable, the major burden of disease management lies in early diagnosis, good prognostication, and proper neo-adjuvant and/or adjuvant therapy. With advancing technologies and their ease of availability, researchers have better tools to understand pancreatic cancer. In the post-genetic era, proteomic, phosphoproteomic, metabolomic, and more have brought us to a multi-omics era. These newer avenues bring promises of better screening modalities, less invasive diagnostics and monitoring, subtyping of pancreatic cancer, and fine tuning the treatment modalities not only to the right stage of tumor but also to the right tumor biology. As the multitudes of technologies are generating extensive amounts of incongruous data, they are giving clinicians a lot of non-actionable information. In this paper, we wish to encompass the newer technologies, sub-classifications, and future treatment modalities in personalized care of patients with pancreatic cancer.

Mining the Human Proteome: Biomarker Discovery for Human Cancer and Metastases

As our knowledge of the mechanisms underlying cancer development and progression has increased, so too have more effective, less toxic, and targeted therapies begun to reach the clinic. However, the full impact of these clinical advances and the practical success of the emerging field of precision medicine are dependent on the discovery and validation of sensitive and accurate biomarkers that can enable appropriate and rigorous sample type and patient selection, reliable longitudinal monitoring of therapeutic efficacy, and even risk assessment and early detection. Within the context of this review, we examine state-of-the-art approaches to the discovery and validation of noninvasive cancer biomarkers, with a specific emphasis on those that are protein or protein-associated ones. We also review sample selection strategies, currently utilized proteomic approaches for both discovery and validation requirements, and data analysis standards. Finally, we provide examples of these elements of biomarker discovery and validation from our own biomarker research.

Fibulin-5 Blocks Microenvironmental ROS in Pancreatic Cancer

Elevated oxidative stress is an aberration seen in many solid tumors, and exploiting this biochemical difference has the potential to enhance the efficacy of anticancer agents. Homeostasis of reactive oxygen species (ROS) is important for normal cell function, but excessive production of ROS can result in cellular toxicity, and therefore ROS levels must be balanced finely. Here, we highlight the relationship between the extracellular matrix and ROS production by reporting a novel function of the matricellular protein Fibulin-5 (Fbln5). We used genetically engineered mouse models of pancreatic ductal adenocarcinoma (PDAC) and found that mutation of the integrin-binding domain of Fbln5 led to decreased tumor growth, increased survival, and enhanced chemoresponse to standard PDAC therapies. Through mechanistic investigations, we found that improved survival was due to increased levels of oxidative stress in Fbln5-mutant tumors. Furthermore, loss of the Fbln5-integrin interaction augmented fibronectin signaling, driving integrin-induced ROS production in a 5-lipooxygenase-dependent manner. These data indicate that Fbln5 promotes PDAC progression by functioning as a molecular rheostat that modulates cell-ECM interactions to reduce ROS production, and thus tip the balance in favor of tumor cell survival and treatment-refractory disease.

Update on the management of pancreatic cancer: Surgery is not enough

Pancreatic ductal adenocarcinoma (PDAC) represents the fourth cause of death in cancer and has a 5-year survival of < 5%. Only about 15% of the patients present with a resectable PDAC with potential to undergo “curative” surgery. After surgery, local and systemic recurrence, is though very common. The median survival of resected patients with adjuvant chemotherapy after surgery is only 20-23 mo. This underscores the significant need to improve PDAC management strategies. Increased survival rate is dependent on new breakthroughs in our understanding of not at least tumor biology. The aim of this review is to update and comment on recent knowledge concerning PDAC biology and new diagnostics and treatment modalities. One fundamental approach to improve survival rates is by earlier and improved diagnosis of the disease. In recent years, novel blood-based biomarkers have emerged based on genetic, epigenetic and protein changes in PDAC with very promising results. For biomarkers to enter clinical practice they need to have been developed using adequate control groups and provide high sensitivity and specificity and by this identify patients at risk already in a pre-symptomatic stage. Another way to improve outcomes, is by employing neoadjuvant treatments thereby increasing the number of resectable cases. Novel systemic treatment regimes like FOLFIRINOX and nab-paclitaxel have demonstrated improvements in prolonging survival in advanced cases, but long-term survival is still scarce. The future improved understanding of PDAC biology will inevitably render new treatment options directed against both the cancer cells and the surrounding microenvironment.

Asporin participates in gastric cancer cell growth and migration by influencing EGF receptor signaling

Asporin (ASPN), a novel member of the small leucine-rich proteoglycan (SLRP) family, serves as a key component of the tumor stroma and has been reported to be abnormally expressed in certain types of tumors. Specifically, the proteoglycan was proven to activate the coordinated invasion of scirrhous gastric cancer and cancer-associated fibroblasts. However, the role of ASPN in cancer cell growth and metastasis has not yet been addressed. In the present study, we aimed to evaluate the tumoricidal benefits of ASPN on tumorigenesis and progression of gastric cancer. Firstly, it was demonstrated that ASPN was overexpressed in gastric carcinoma tissues when compared to the corresponding non‑cancerous tissues, and it had varied levels of expression in gastric cancer epithelial cell lines. Additionally, we assessed the effects of transient siRNA‑mediated ASPN knockdown on gastric cancer cells. ASPN silencing inhibited proliferation and suppressed the migration of immortalized neoplastic epithelial cells. Furthermore, at the molecular level, we found that downregulation of ASPN blocked the anti-apoptotic molecule Bcl-2, increased the expression of pro-apoptotic molecule Bad, reduced the expression of migration-related proteins CD44 and matrix metalloproteinase (MMP)-2, and abrogated the activation of the phosphorylation status of ERK and epidermal growth factor (EGF) and its receptor (EGFR). Collectively, our findings indicate that ASPN is upregulated and plays an oncogenic role in gastric cancer progression and metastasis by influencing the EGFR signaling pathway.

IGF-Binding Protein 2 - Oncogene or Tumor Suppressor?

The role of insulin-like growth factor binding protein 2 (IGFBP2) in cancer is unclear. In general, IGFBP2 is considered to be oncogenic and its expression is often observed to be elevated in cancer. However, there are a number of conflicting reports in vitro and in vivo where IGFBP2 acts in a tumor suppressor manner. In this mini-review, we discuss the factors influencing the variation in IGFBP2 expression in cancer and our interpretation of these findings.

Clinical initiatives linking Japanese and Swedish healthcare resources on cancer studies utilizing Biobank Repositories

The Tokyo Medical University Hospital in Japan and the Lund University hospital in Sweden have recently initiated a research program with the objective to impact on patient treatment by clinical disease stage characterization (phenotyping), utilizing proteomics sequencing platforms. By sharing clinical experiences, patient treatment principles, and biobank strategies, our respective clinical teams in Japan and Sweden will aid in the development of predictive and drug related protein biomarkers.

Data from joint lung cancer studies are presented where protein expression from Neuro- Endocrine lung cancer (LCNEC) phenotype patients can be separated from Small cell- (SCLC) and Large Cell lung cancer (LCC) patients by deep sequencing and spectral counting analysis. LCNEC, a subtype of large cell carcinoma (LCC), is characterized by neuroendocrine differentiation that small cell lung carcinoma (SCLC) shares. Pre-therapeutic histological distinction between LCNEC and SCLC has so far been problematic, leading to adverse clinical outcome. An establishment of protein targets characteristic of LCNEC is quite helpful for decision of optimal therapeutic strategy by diagnosing individual patients. Proteoform annotation and clinical biobanking is part of the HUPO initiative (http://www.hupo.org) within chromosome 10 and chromosome 19 consortia.

N-methylnicotinamide and nicotinamide N-methyltransferase are associated with microRNA-1291-altered pancreatic carcinoma cell metabolome and suppressed tumorigenesis

The cell metabolome comprises abundant information that may be predictive of cell functions in response to epigenetic or genetic changes at different stages of cell proliferation and metastasis. An unbiased ultra-performance liquid chromatography-mass spectrometry-based metabolomics study revealed a significantly altered metabolome for human pancreatic carcinoma PANC-1 cells with gain-of-function non-coding microRNA-1291 (miR-1291), which led to a lower migration and invasion capacity as well as suppressed tumorigenesis in a xenograft tumor mouse model. A number of metabolites, including N-methylnicotinamide, involved in nicotinamide metabolism, and l-carnitine, isobutyryl-carnitine and isovaleryl-carnitine, involved in fatty acid metabolism, were elevated in miR-1291-expressing PANC-1. Notably, N-methylnicotinamide was elevated to the greatest extent, and this was associated with a sharp increase in nicotinamide N-methyltransferase (NNMT) mRNA level in miR-1291-expressing PANC-1 cells. In addition, expression of NNMT mRNA was inversely correlated with pancreatic tumor size in the xenograft mouse model. These results indicate that miR-1291-altered PANC-1 cell function is associated with the increase in N-methylnicotinamide level and NNMT expression, and in turn NNMT may be indicative of the extent of pancreatic carcinogenesis.

Protein deep sequencing applied to biobank samples from patients with pancreatic cancer

PURPOSE

Pancreatic cancer is commonly detected at advanced stages when the tumor is no longer amenable to surgical resection. Therefore, finding biomarkers for early stage disease is urgent. Here, we show that high-definition mass spectrometry (HDMS(E)) can be used to identify serum protein alterations associated with early stage pancreatic cancer.

METHODS

We analyzed serum samples from patients with resectable pancreatic cancer, benign pancreatic disease, and healthy controls. The SYNAPT G2-Si platform was used in a data-independent manner coupled with ion mobility. The dilution of the samples with yeast alcohol dehydrogenase tryptic digest of known concentration allowed the estimated amounts of each identified protein to be calculated (Silva et al. in Anal Chem 77:2187-2200, 2005; Silva et al. in Mol Cell Proteomics 5:144-156, 2006). A global protein expression comparison of the three study groups was made using label-free quantification and bioinformatic analyses.

RESULTS

Two-way unsupervised hierarchical clustering revealed 134 proteins that successfully classified pancreatic cancer patients from the controls, and identified 40 proteins that showed a significant up-regulation in the pancreatic cancer group. This discrimination reliability was further confirmed by principal component analysis. The differentially expressed candidates were aligned with protein network analyses and linked to biological pathways related to pancreatic tumorigenesis. Pancreatic disease link associations could be made for BAZ2A, CDK13, DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by pathway network linkages to p53, the most frequently altered tumor suppressor in pancreatic cancer.

CONCLUSION

These pancreatic cancer study candidates may provide new avenues of research for a noninvasive blood-based diagnosis for pancreatic tumor stratification.