Gene Expression Chromosomal Correlations in Tumors of Mesodermal Origin: The Case of Rhabdomyosarcoma and Acute Lymphoblastic Leukemia

Authors: Viktoria Papadimitriou; George I. Lambrou
DIN
IJOER-MAR-2017-33
Abstract

since the advent of high throughput methodologies, like microarrays, the load of genomic data has increased geometrically and along with that the need for computational methods which will interpret these data. In the present work we have studied the common gene expression patterns between two tumor cell types of mesodermal origin. In particular, we have attempted to find causal relations between gene expression levels with respect to chromosomal location. We have found that several genes manifested significant relations, using regression analysis and as such they could pose interesting targets for further investigations. This type of analysis can lead to the understanding of the common mechanisms that transform physiological cells to malignant, as well as it reveals a new holistic way to understand the dynamics of tumor onset as well as the mechanistic of oncogenic drivers. Such approaches could prove to be useful in the prediction of genomic targets that could be further studied in order to unravel the mechanics of tumor ontogenesis.

Keywords
Acute Lymphoblastic Leukemia Chromosomal correlations Mesoderm Microarrays Rhabdomyosarcoma.
Introduction

Acute lymphoblastic leukemia (ALL) and rhabdomyosarcoma (RMS) are two type of tumors, which originate from the embryonic mesoderm. ALL is the most frequent malignancy, which appears during childhood. Acute leukemia originates from the undifferentiated lymphoblast, which does not develop into the mature lymphoid cell, giving rise to a tumor. RMS is a rare cancer in childhood. This represents 5-8% of all tumors in childhood, but the sarcomas of head and neck are 12% of all neoplasias in childhood. RMS originates from myoblast or cells that will form the skeletal muscle. These are different from the smooth cells. RMS can be created at any part of the body, which has skeletal muscle but frequently appears in the head and neck. The embryonal form of RMS is most common at birth, which consists of spindle cells and botryoid form with better prognosis, but the alveolar form mainly appears in childhood and adolescence. ALL and RMS consist of cells that are undifferentiated, immortal and with the potential to divide infinitely. Myoblasts originate from the dorsal (paraxial) mesoderm, while blood cells derive from the lateral mesoderm that gives rise to the splachnic mesoderm and this to the hemangioblastic tissue. ALL and many alveolar RMS in childhood present chromosomal translocations, like the PAX3- FKHR, that is an indicator of poor prognosis and associated with metastasis [1].

During embryogenesis, blood cells originate from two sites. From the ventral mesoderm near the yolk sac, which gives rise to the intra-embryonic hematopoietic precursors, but the hematopoietic cells that last throughout the entire life time of an organism are derived from the mesodermal area surrounding the aorta. This differentiation is regulated with a network of various genes, which leads to two similar cell types with others functions and roles in the body. There are several factors that affect gene regulation, which means that aberrations in the regulatory network would lead to tumor cells.

Further on, it has been previously reported that correlation in gene expression and in particular, chromosomal correlation implies common gene regulation [1, 2]. Yet, it is also known that correlation does not imply causality. In that sense, it is of great importance if we would be able to infer gene regulatory mechanisms from chromosomal expression levels.

Conclusion

The present approach attempted to find common regulatory mechanisms in gene expression patterns of two cell types. In particular, we have attempted to discover possible causal relations in gene expression patterns. We have found evidence that such correlations could exist and it is probable that certain genes could be of great significance in tumor ontogenesis. Such approaches could prove to be useful in the prediction of genomic targets that could be further studied in order to unravel the mechanics of tumor ontogenesis.

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