Profiles of gene expression & diagnosis/prognosis of cancer. MCs in Advanced Genetics Ainoa Planas Riverola

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1 Profiles of gene expression & diagnosis/prognosis of cancer MCs in Advanced Genetics Ainoa Planas Riverola

2 Gene expression profiles Gene expression profiling Used in molecular biology, it measures the expression of thousands of genes simultaneously. Sample Sample Preparation RNA extraction Profiling and Quantification Gene expression profile

3 Gene expression profiles In cancer this techniques are useful to classify and diagnose tumors. Cancer cells can be differentiated from normal cells by his transcriptoma, it also can predict if a tumor is more or less agressive (prognosis), depending on the gene expression of its cells. Oncogenes Tumor suppressors

4 Gene expression profiles Techniques used: DNA Microarray technologies Serial analysis of gene expression (SAGE) RNA-Sequencing Real-Time RT-PCR

5 Microarrays First tool used to measure RNA levels, the most used for gene expression profiling. Labeled cdna from a sample is hybridized to complementary probe sequences on the chip, and strongly associated complexes are identified optically. There are different subtypes cdna microarray microrna microarray Oligonucleotide microarray

6 SAGE Experimental technique designed to gain a direct and quantitative measure of gene expression. Based on the isolation of unique sequence tags from individual mrnas and concatenation of tags serially into long DNA molecules for a lump-sum sequencing. Quantitative and simultaneous analysis of a large number of transcripts in any particular cells or tissues, without prior knowledge of the genes. Yamamoto, M. et al., 2001

7 RNA-Seq Uses the capabilities of next-generation sequencing to reveal a snapshot of RNA presence and quantity from a genome at a given moment in time Detect a single molecule, it is very sensitive and has a high reproducibility. It is expensive and the analysis of the data is more difficult. Wang, Z. et al., 2009

8 Real-Time RT-PCR Steady-state levels of mrna are quantitated by reverse transcription of the RNA to cdna followed by quantitative PCR (qpcr) on the cdna. The amount of each specific target is determined by measuring the increase in fluorescence signal from DNA-binding dyes or probes during successive rounds of enzyme-mediated amplification. Expression levels can be measured relative to other genes (relative quantification) or against a standard (absolute quantification).

9 mirnas expression profiling mirnas are small non-coding regions of nt, they play an important role in all biological pathways by safeguarding key biological processes as cell proliferation, differentiation and apoptosis. Deregulation of the mirnas has severe consequences in the expression patterns of a lot of mrnas mirna expression in cancer Microarray data has shown that aberrant mirna expression is a rule in almost all tumor tissues.

10 mirnas for cancer diagnose mirna profiling in cancer cells compared with those in normal cells in the same tissue shown significantly differences. Lu, J. et al. (2005)

11 mirnas for cancer diagnose A combination of upregulated mir-155 and downregulated mir-141 is found in a 97% overall correct classification of malignant and non-malignant tissues. In breast cancer there is an upregulation of mir-21, mir- 155, mir-191 and mir-196a, and there is an downregulation of mir-125b, mir-221. In plasma of colorectal cancer there is a high expression of mir-92, this permits to differentiate this disease from gastric cancer and normal patients.

12 mirnas for cancer prognosis Downregulation of mir-451 is associated with worse prognosis. Overexpression of this mirna in gastric cancer reduces cell proliferation and increases sensitivity to radioteraphy. Low expression of mir-34a in chronic lymphocytic leukemia is a marker for poor prognosis, this low expression is associated with p53 inactivation and apoptosis resistance. Lin-28 is a highly specific embryonic stem cell marker, epithelial ovarian cancer patients with high expressions of lin-28 s homologues have shorter survivall.

13 Conclusions Dectects and diagnoses cancers in all kind of tissues Classifies and prognoses different kinds of tumors Genetic expression profiling Good biomarker Helps to chose an adequated therapy for every patient Can be the answer for reducing the high mortality of cancer

14 References Yamamoto, M. et al. (2001). Use of serial analysis of gene expression (SAGE) technology. Journal of Immunological Methods, 250;1 2 Wang, Z. et al. (2009). RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet, 10(1):57-63 Reddy, BK. (2015). MicroRNA (mirna) in cancer). Cancer Cell International, 15:38 Lun, J. et al. (2005). MicroRNA expression profiles classify human cancers. Nature, 435. Cho, W. (2010). MicroRNAs: Potential biomarkers for cancer diagnosis, prognosis and targets for therapy. The International Journal of Biochemistry & Cell Biology, 42 Bio-Rad. (2015). What is Gene Expression Analysis? Online at: