Understanding tumor heterogeneity with gene expression analysis

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Strategies to counter tumor heterogeneity are high on the wish list of oncologists and cancer researchers. Within a single tumor, cells can differ in size, proliferation rate and ability to metastasize. Most significantly for physicians and patients, they can also differ in their sensitivity to chemotherapy. How can we best understand and investigate this aspect of tumor biology?

Tumor heterogeneity is defined as the genetic and functional differences between cells within or among tumor cell populations (1). Interest in tumor heterogeneity began in the 1950s, when histologists looked at cells from mouse ascite tumor samples and for the first time saw that the chromosome number was not the same in every cell (2). Those observations were made with microscopes. Every tumor displays a certain degree of heterogeneity, with molecular and genetic variations. There are two types: intertumor heterogeneity and intratumor heterogeneity. Intertumor heterogeneity means genetic and phenotypic variation between tumors of different tissue and cell types and between individuals with the same tumor type. Intratumor heterogeneity, by contrast, is variation within the primary tumor and its metastases. The fundamental basis for intratumor heterogeneity is the molecular variability of the tissue microenvironment and the neoplastic cells within a single tumor.

The idea that cancer is primarily driven by a smaller population of stem cells has important implications. For instance, if an anti-cancer therapy was to succeed at shrinking the tumor, but had not killed the cancer stem cells, the tumor would soon grow back. Another important implication is that cancer stem cells that had not been destroyed could act as a reservoir, causing a relapse after therapy had eliminated all observable signs of a cancer.

How can we study the expression of different mRNAs in a given tumor sample and compare them across multiple conditions? Gene expression analysis is one of the powerful technologies at our disposal, which has enabled cancer research to discover disease-specific biomarker signatures. These studies have provided a progressively deeper understanding of this complex human disease. In particular, the discovery of microRNAs (miRNAs) and long noncoding RNAs that directly regulate gene expression has provided researchers with an excellent means to truly understand gene expression in tumor cells.

At QIAGEN, RT2 Profiler and RT2 lncRNA PCR Arrays are highly reliable and sensitive technologies for analyzing focused panels of genes to discover their roles in signal transduction, biological processes or disease pathways. They use a straightforward workflow based on qRT-PCR (see the figure below). Each PCR array contains a list of pathway-focused genes along with 5 housekeeping (reference) genes. In addition, they contain a panel of patented controls to monitor genomic DNA contamination, cDNA synthesis and real-time PCR efficiency.

Unlock the secrets of the transcriptome

RT2 workflow
RT2 PCR Array workflow

 

However, gene expression analysis is not without its own challenges. The most common issue lies with the quality of the primer assays, including parameters like specificity and amplification efficiency. RT² Profiler PCR Arrays enable quick, reliable gene expression analysis of 170+ pathways using laboratory-verified qPCR assays, allowing researchers to spend less time at the bench and more time interpreting results. The arrays are pathway-focused panels with integrated, patented controls to ensure a successful experiment every time. Additionally, complimentary online tools are provided for quick and easy data analysis.

Download the RT2 Profiler PCR Array product profile.

We would be happy to help address any other challenges you may face in studying tumor heterogeneity by gene expression analysis – let us know in the comments!

References

  1. 1. Heppner, G.H. (1984) Tumor heterogeneity. Cancer Res. 44, 2259. Link
  2. 2. Levan, A. and Hauschka, T.S. (1953) Endomitotic reduplication mechanisms in ascites tumors of the mouse. J. Natl. Cancer Inst. 14, 1. Link
  3. 3. Marusyk, A., Almendro, V. and Polyak, K. (2012) Intratumor heterogeneity: a looking glass for cancer? Nat. Rev. Cancer 12, 323. Link

 

 

 

Vishwadeepak Tripathi

Vishwadeepak Tripathi, PhD is a Global Market Manager at QIAGEN. He received his PhD in biochemistry at the Faculty of Medicine from Ruhr-University Bochum, Germany. Dr. Tripathi studied the role of chaperones and co-chaperones in protein folding and quality control and authored a number of scientific publications. He was also at RIKEN Institute in Japan where he studied the pathogenesis of Huntington's disease in cellular and mice models. He is currently interested in biomarker research, NGS and neurodegeneration.

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