**Molecular Taxonomy: Use of Transcriptional Profiles to Identify Different ALS Subtypes**

Giovanna Morello, Francesca Luisa Conforti, Antonio Gianmaria Spampinato and Sebastiano Cavallaro

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/62988

#### **Abstract**

Advances in diagnostic techniques and high-throughput biotechnologies provide a compelling opportunity to improve the diagnosis and treatment of diseases by developing a "New Taxonomy" that defines diseases on the basis of their underlying molecular and environmental factors rather than on traditional physical signs and symptoms. Oncology represents the first interesting example of how genomic medicine has changed the understanding of diseases and their therapy. However, much work remains to be completed on the molecular characterization and classification of complex and multifactorial diseases, including neurodegenerative disorders. Our research group has recently shown the genomic heterogeneity of sporadic amyotrophic lateral sclerosis (SALS), identifying two divergent subtypes associated with differentially expressed genes and pathways and providing several potential biomarkers and therapeutic targets. This chapter reviews the results emerged from our work, highlighting how molecular characterization of SALS patients may provide a framework for developing a more precise and accurate classification of diseases that could revolutionize the diagnosis, therapy, and clinical decisions of diseases, leading to more individualized treatments and improved outcomes for patients.

**Keywords:** ALS, expression profiling, genomics, molecular taxonomy, pathway anal‐ ysis, system biology

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **1. Introduction**

The current diagnosis and classification of diseases are primarily based on physical signs and symptoms that, despite providing valuable information about clinical course, are often not sufficient to fully characterize the complex and heterogeneous nature of many disorders.

The completion of the human genome sequencing together with advances in high-throughput genomic, proteomic, imaging, and other diagnostic techniques in the past decades has provided a framework for developing a new, more accurate, and refined "molecular taxono‐ my" of human diseases which implies the use of molecular data (i.e., gene expression, copy number variants, single nucleotide polymorphisms, and haplotype analysis) to classify patients into distinct subgroups with differing diagnostic, prognostic, or therapeutic implica‐ tions. This new disease classification has profound implications not only providing new insights into studying mechanisms and environmental causes underpinning diseases but also facilitating the development of a more precise diagnosis and individualized treatment for optimal therapeutic efficacy [1–3]. One seminal example of how molecular data may translate into clinical practice is represented by the "drug repositioning "approach. In fact, many drugs that were abandoned at clinical stages because of their low efficacy and/or toxicity in a specific subtype of patients may be re-evaluated for their potential therapeutic role with the consequent possibility to reduce both the time and costs associated with drug discovery and development [4].

Oncology offers multiple examples of how genomic medicine has changed disease under‐ standing and drove targeted therapeutic interventions. Numerous studies, in fact, have demonstrated the power and ability of gene expression profiling, and other molecular approaches, to classify and substratify patients with various types of cancer (e.g., glioblastoma, breast, and colon carcinoma) into selective clinically relevant subtypes characterized by similar clinicopathological features but different biological properties, prognostic biomarkers, and treatment options [5]. Based on these promising results, over the past years, this new molecular reclassification has been extended to other polygenic and multifactorial human disorders, including cardiovascular and rheumatic diseases and multiple sclerosis [6]. However, a lack of progress remains in the understanding of detailed molecular mechanisms of several neurological and neurodegenerative diseases mainly because of the limited access to human brain tissues. Thus, the patient-specific molecular diagnosis of many neurological disorders and the consequent translation of this into tailored clinical trials and specific treatments remain challenging tasks [7].

Recently, by using an unsupervised hierarchical clustering analysis on motor cortex samples of patients with sporadic amyotrophic lateral sclerosis (SALS), our research group has identified two greatly divergent subtypes, each associated with differentially expressed genes and biological pathways [8]. These experiments highlight, for the first time, the genomic heterogeneity of SALS, revealing new clues for defining molecular signatures for this disease that were not put in evidence by considering SALS as a single entity. Moreover, the altered pathways of biological molecules in SALS also provided a number of potential biomarkers and therapeutic targets that could be used for developing personalized diagnosis and treatment of amyotrophic lateral sclerosis (ALS) [9, 10].

In this chapter, we will first briefly review the current state of the art in the ALS classification system, showing how the recent advances in technology and genetic discoveries have revo‐ lutionized ALS research. Then, we will discuss our data, the experimental setup, and results, highlighting how the molecular characterization of SALS patients may provide a framework for developing a new taxonomy of the disease and establishing the foundation for personalized medicine in ALS.
