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Archive for the ‘Pancreatic adenocarcinoma classifier’ Category


Single-cell RNA-seq helps in finding intra-tumoral heterogeneity in pancreatic cancer

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Pancreatic cancer is a significant cause of cancer mortality; therefore, the development of early diagnostic strategies and effective treatment is essential. Improvements in imaging technology, as well as use of biomarkers are changing the way that pancreas cancer is diagnosed and staged. Although progress in treatment for pancreas cancer has been incremental, development of combination therapies involving both chemotherapeutic and biologic agents is ongoing.

 

Cancer is an evolutionary disease, containing the hallmarks of an asexually reproducing unicellular organism subject to evolutionary paradigms. Pancreatic ductal adenocarcinoma (PDAC) is a particularly robust example of this phenomenon. Genomic features indicate that pancreatic cancer cells are selected for fitness advantages when encountering the geographic and resource-depleted constraints of the microenvironment. Phenotypic adaptations to these pressures help disseminated cells to survive in secondary sites, a major clinical problem for patients with this disease.

 

The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology.

 

PDAC is the most common type of pancreatic cancer featured with high intra-tumoral heterogeneity and poor prognosis. In the present study to comprehensively delineate the PDAC intra-tumoral heterogeneity and the underlying mechanism for PDAC progression, single-cell RNA-seq (scRNA-seq) was employed to acquire the transcriptomic atlas of 57,530 individual pancreatic cells from primary PDAC tumors and control pancreases. The diverse malignant and stromal cell types, including two ductal subtypes with abnormal and malignant gene expression profiles respectively, were identified in PDAC.

 

The researchers found that the heterogenous malignant subtype was composed of several subpopulations with differential proliferative and migratory potentials. Cell trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. Furthermore, it was found a subset of ductal cells with unique proliferative features were associated with an inactivation state in tumor-infiltrating T cells, providing novel markers for the prediction of antitumor immune response. Together, the findings provided a valuable resource for deciphering the intra-tumoral heterogeneity in PDAC and uncover a connection between tumor intrinsic transcriptional state and T cell activation, suggesting potential biomarkers for anticancer treatment such as targeted therapy and immunotherapy.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/31273297

 

https://www.ncbi.nlm.nih.gov/pubmed/21491194

 

https://www.ncbi.nlm.nih.gov/pubmed/27444064

 

https://www.ncbi.nlm.nih.gov/pubmed/28983043

 

https://www.ncbi.nlm.nih.gov/pubmed/24976721

 

https://www.ncbi.nlm.nih.gov/pubmed/27693023

 

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Hypertriglyceridemia: Evaluation and Treatment Guideline

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Severe and very severe hypertriglyceridemia increase the risk for pancreatitis, whereas mild or moderate hypertriglyceridemia may be a risk factor for cardiovascular disease. Individuals found to have any elevation of fasting triglycerides should be evaluated for secondary causes of hyperlipidemia including endocrine conditions and medications. Patients with primary hypertriglyceridemia must be assessed for other cardiovascular risk factors, such as central obesity, hypertension, abnormalities of glucose metabolism, and liver dysfunction. The aim of this study was to develop clinical practice guidelines on hypertriglyceridemia.

The diagnosis of hypertriglyceridemia should be based on fasting levels, that mild and moderate hypertriglyceridemia (triglycerides of 150–999 mg/dl) be diagnosed to aid in the evaluation of cardiovascular risk, and that severe and very severe hypertriglyceridemia (triglycerides of >1000 mg/dl) be considered a risk for pancreatitis. The patients with hypertriglyceridemia must be evaluated for secondary causes of hyperlipidemia and that subjects with primary hypertriglyceridemia be evaluated for family history of dyslipidemia and cardiovascular disease.

The treatment goal in patients with moderate hypertriglyceridemia should be a non-high-density lipoprotein cholesterol level in agreement with National Cholesterol Education Program Adult Treatment Panel guidelines. The initial treatment should be lifestyle therapy; a combination of diet modification, physical activity and drug therapy may also be considered. In patients with severe or very severe hypertriglyceridemia, a fibrate can be used as a first-line agent for reduction of triglycerides in patients at risk for triglyceride-induced pancreatitis.

Three drug classes (fibrates, niacin, n-3 fatty acids) alone or in combination with statins may be considered as treatment options in patients with moderate to severe triglyceride levels. Statins are not be used as monotherapy for severe or very severe hypertriglyceridemia. However, statins may be useful for the treatment of moderate hypertriglyceridemia when indicated to modify cardiovascular risk.

 

References:

 

https://www.medpagetoday.com/clinical-connection/cardio-endo/77242?xid=NL_CardioEndoConnection_2019-01-21

https://www.ncbi.nlm.nih.gov/pubmed/19307519

https://www.ncbi.nlm.nih.gov/pubmed/23009776

https://www.ncbi.nlm.nih.gov/pubmed/6827992

https://www.ncbi.nlm.nih.gov/pubmed/22463676

https://www.ncbi.nlm.nih.gov/pubmed/17635890

 

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A novel 5-gene pancreatic adenocarcinoma classifier: Meta-analysis of transcriptome data – Clinical Genomics Research @BIDMC

Curator: Tilda Barliya, PhD

Analysis of  Bhasin et al paper and Literature search

Table 1: 5-genes classifiers as biomarkers for PDAC:

Gene symbol Gene name Subcellular localization
ECT2 Epithelial cell transforming sequence 2 oncogene Nucleus, cytoplasm
AHNAK2 AHNAKE nucleoprotein 2 Plasma membrane, cytoplasm
POSTN Periostin, osteoblast specific factor Extracellular space
TMPRSS4 Transmembrane protease, serine 4 Plasma membrane

 

SERPINB5 Serpin peptidase inhibitor, clade B (ovalbumin) member 5 Extracellular space


Introduction
:

  • Bhasin et al, conducted a beautiful study using a powerful meta-analysis from different sources to identify the “important/classifier” genes associated with Pancreatic Cancer (PDAC).
  • The authors identified 5 genes that were considered as good classifiers (table 1).
  • It is important to note that the meta-analysis was performed on tissue and microdissection samples.
  • In their summary, the authors aim to validate these genes in blood/urine samples.
  • While these genes might be over expressed in tissue samples it may not be true to their existence in blood and careful examination and validation is required.
  • Liquid biopsies are emerging as the go-to use tools for disease detection, mostly aimed for early diagnosis.
  • Liquid biopsies are non-invasive biopsies of blood, urine (potentially saliva) and their “exotic” components, i.e miRNA, exosomes etc.
  • Since Liquid biopsies are non-invasive, they are painless and patients are more complied.
  • It is important to note that there is a gap between the expression of a gene or a protein in tissue section and their expression in the blood and may not necessarily correlate.
  • It will be very interesting to follow their research and future outcomes.

Additional References:

  • TMPRSS4: an emerging potential therapeutic target in cancer.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4453593/

  • The tumour trail left in blood

http://www.nature.com/nature/journal/v532/n7598/full/532269a.html

Aashir Awan, PhD, wrote on 12/28/2016

I was wondering if these same 5 genes were upregulated in the pancreatic ductal adenocarcinoma cell lines that are available out there.  In doing cell biology work, there is always a dilemma whether cancer cell lines correctly re-capitulate in vivo tumors or not.  Personally, I prefer primary cell lines to do analysis but this finding can be used to test primary vs cell line.  In addition, I’ve attached the gene network for Ect2.  If you look carefully, the two big proteins that jump out are RACGAP1 and KIF23.  I think in designing therapies, combinatorial targets can yield the best outcomes.  Drugs directed towards two or more targets would seem ideal in my opinion.

ect2

Gene Network for Ect2

Original Research
Oncotarget. 2016 Apr 26;7(17):23263-81. doi: 10.18632/oncotarget.8139.

Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier.

Abstract

PURPOSE:

Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification.

EXPERIMENTAL DESIGN:

Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells.

RESULTS:

A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar performance (sensitivity = 94%, specificity = 89.6%) in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC = 0.83), other cancers (AUC = 0.89), and non-tumor from PDAC precursors (AUC = 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1-Cre;LSL-KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non-tumor pancreas or pancreatitis. Notably, knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion.

CONCLUSIONS:

This study identified and validated a highly accurate 5-gene PDAC classifier for discriminating PDAC and early precursor lesions from non-malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell-based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets.

KEYWORDS:

bioinformatics; biomarkers; meta-analysis; pancreatic cancer; transcriptome

PMID:
26993610
PMCID:
PMC5029625
DOI:
10.18632/oncotarget.8139

SOURCE

Oncotarget, Vol. 7, No. 17 – Referred as PDF, above

 

BIDMC Researchers Discover Early Indicators of Pancreatic Cancer

LibermannBhasin_PancreasCancerStudy

Markers may help doctors detect pancreatic cancer before it becomes deadly

In photo: First author Manoj Bhasin, PhD, and co-senior author Towia Libermann, PhD, Co-Director and Director of BIDMC’s Genomics, Proteomics, Bioinformatics and Systems Biology Center.

SOURCE

http://www.bidmc.org/News/PRLandingPage/2016/March/Libermann-Pancreatic-Cancer-Research-2016.aspx

BOSTON – Pancreatic cancer, the fourth leading cause of cancer death in the United States, is often diagnosed at a late stage, when curative treatment is no longer possible. A team led by investigators at Beth Israel Deaconess Medical Center (BIDMC) has now identified and validated an accurate 5-gene classifier for discriminating early pancreatic cancer from non-malignant tissue. Described online in the journal Oncotarget, the finding is a promising advance in the fight against this typically fatal disease.

“Pancreatic cancer is a devastating disease with a death rate close to the incidence rate,” said co-senior author Towia Libermann, PhD, Director of the Genomics, Proteomics, Bioinformatics and Systems Biology Center at BIDMC and Associate Professor of Medicine at Harvard Medical School (HMS). “Because more than 90 percent of pancreatic cancer cases are diagnosed at the metastatic stage, when there are only limited therapeutic options, earlier diagnosis is anticipated to have a major impact on extending life expectancy for patients. There has been a lack of reliable markers, early indicators and risk factors associated with pancreatic cancer, but this new way of differentiating between healthy and malignant tissue offers hope for earlier diagnosis and treatment.”

The investigators used a number of publicly available gene expression datasets for pancreatic cancer and developed a strategy to reanalyze these datasets together, applying rigorous statistical criteria to compare different datasets from different laboratories and different platforms with each other. The team then selected a subset of data for developing a panel for differentiating between pancreatic cancer and healthy pancreas tissue and thereafter applied this “Pancreatic Cancer Predictor” to the remaining datasets for independent validation to confirm the accuracy of the markers.

After demonstrating and independently validating that a 5-gene pancreatic cancer predictor discriminated between cancerous and healthy tissue, the researchers applied the predictor to datasets that also included benign lesions of the pancreas, including pancreatitis and early stage cancer. The predictor accurately differentiated pancreatic cancer, benign pancreatic lesions, early stage pancreatic cancer and healthy tissue. The predictor achieved on average 95 percent sensitivity and 89 percent specificity in discriminating pancreatic cancer from non-tumor samples in four training sets and similar performance (94 percent sensitivity, 90 percent specificity) in five independent validation datasets.

“Using innovative data normalization and gene selection approaches, we combined the statistical power of multiple genomic studies and masked their variability and batch effects to identify robust early diagnostic biomarkers of pancreatic cancer,” said first author Manoj Bhasin, PhD, Co-Director of BIDMC’s Genomics, Proteomics, Bioinformatics and Systems Biology Center and Assistant Professor of Medicine at HMS.

“The identification and initial validation of a highly accurate 5-gene pancreatic cancer biomarker panel that can discriminate late and early stages of pancreatic cancer from normal pancreas and benign pancreatic lesions could facilitate early diagnosis of pancreatic cancer,” said co-senior author Roya Khosravi-Far, PhD, Associate Professor of Pathology at BIDMC. “Our findings may open a window of opportunity for earlier diagnosis and, consequently, earlier intervention and more effective treatment of this deadly cancer, leading to higher survival rates.”

The first diagnostic application of the panel may be for analyses of fine needle biopsies routinely used for diagnosing pancreatic cancer and for determining the malignant potential of mostly benign pancreatic cysts that can sometimes be precursors of pancreatic cancer. In addition to providing a new tool for diagnoses, the research may also lead to new insights into how pancreatic cancer arises.

“Because these five genes are ‘turned on’ so early in the development of pancreatic cancer, they may play roles as drivers of this disease and may be exciting targets for therapies,” said Libermann. Most of the five genes—named TMPRSS4, AHNAK2, POSTN, ECT2 and SERPINB5—have been linked to migration, invasion, adhesion, and metastasis of pancreatic or other cancers.

The scientists next plan to evaluate the precise roles of the five genes and to validate the accuracy of their diagnostic assay in a prospective clinical study. “Moving forward, we will explore the potential to convert this tissue-based diagnostic into a noninvasive blood or urine test,” Libermann said.

“To further enhance the diagnostic power of this biomarker, we plan to expand it by including non-coding RNAs, proteins, metabolites and mutations associated with pancreatic cancer. This will result in development of the first of its kind biomarker that gauges pancreatic cancer alterations from multiple genomic angles for making highly accurate diagnoses,” added Bhasin. Such an inexpensive and simple test could help transform the landscape of pancreatic cancer and help prevent many of the estimated 330,000 deaths that it causes worldwide each year.

Study coauthors include BIDMC investigators Kenneth Ndebele, Octavian Bucur, Eric Yee, Jessica Plati, Andrea Bullock, Xuesong Gu, Eduardo Castan, Peng Zhang, Robert Najarian, Maria Muraru and Rebecca Miksad, and the University of Nebraska-Lincoln’s Hasan H. Otu. The work was supported by the National Institutes of Health, National Cancer Institute and Ben and Rose Cole Charitable Pria Foundation.

SOURCE

http://www.bidmc.org/News/PRLandingPage/2016/March/Libermann-Pancreatic-Cancer-Research-2016.aspx

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