Dissortativity and duplications in Oral cancer

More than 300,000 new cases worldwide are being diagnosed with oral cancer annually. Complexity of oral cancer renders designing drug targets very difficult. We analyse proteinprotein interaction network for the normal and oral cancer tissue and detect crucial changes in the structural properties of the networks in terms of the interactions of the hub proteins and the degree-degree correlations. Further analysis of the spectra of both the networks, while exhibiting universal statistical behavior, manifest distinction in terms of the zero degeneracy, providing insight to the complexity of the underlying system. Oral cancer refers to a subgroup of head and neck malignancies that develop at the lips, tongue, salivary glands, gingiva, floor of the mouth, oropharynx, buccal surfaces and other intra-oral locations according to the international classification of diseases [1]. More than 300,000 new cases worldwide are being diagnosed with Oral squamous cell carcinoma (OSCC) annually [2]. WHO estimates it particularly to be the eighth most common cancer worldwide [3] and it is of significant public health importance to developing countries such as in Indian subcontinent where it ranks among the top three types of cancer and accounts for over 30% of all cancers [4–6]. Despite the growing propensity for oral cancer, majority of the research works have focused only on breast cancer [7], colon cancer [8] and lymphomas [9, 10]. Hence, the identification of genetic changes specific to oral cancer is very crucial because it provides an opportunity to use this information for the development of drugs to treat this disease [11]. Availability of huge amount of proteomic data [12] and information on the highly interlinked internal organization of the cell metabolism, signal transduction, transport etc. [13], provides us a scope to identify and understand, the principles that govern the behaviour of cells. We analyse the proteomic data using the network theory framework [14, 15] which is holistic approach that enables us to capture the intrinsic properties of the underlying system in a cost-effective and time-efficient manner. Previous attempts to understand various diseases under the network theory reveal that various types of cancers are interlinked through some pathways which are altered in different diseases [16]. This study explores the networks of the normal oral tissue and its diseasome, by characterizing their structural and spectral properties. This approach yields a comprehensive picture of the patterns and principles governing oral cancer which otherwise would not be apparent from the study of individual proteins [17]. We find significant variations between the structural and spectral properties of the Normal and Cancer network. The change in the degree-degree correlation provides quantitative information about the consequences of altered cell behaviour from the normal to cancer state. Further, the node duplication presents a clue to the abrupt transformation of the normal cells to the cancer cells which can be further used to predict potential therapeutics.