The apoptotic machinery as a biological complex system: analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma.
BACKGROUND
Apoptosis is a critical biological phenomenon, executed under the guidance of the Apoptotic Machinery (AM), which allows the physiologic elimination of terminally differentiated, senescent or diseased cells. Because of its relevance to BioMedicine, we have sought to obtain a detailed characterization of AM Omics in Homo sapiens, namely its Genomics and Evolution, Transcriptomics, Proteomics, Interactomics, Oncogenomics, and Pharmacogenomics.


METHODS
This project exploited the methodology commonly used in Computational Biology (i.e., mining of many omics databases of the web) as well as the High Throughput biomolecular analytical techniques.


RESULTS
In Homo sapiens AM is comprised of 342 protein-encoding genes (possessing either anti- or pro-apoptotic activity, or a regulatory function) and 110 MIR-encoding genes targeting them: some have a critical role within the system (core AM nodes), others perform tissue-, pathway-, or disease-specific functions (peripheral AM nodes). By overlapping the cancer type-specific AM mutation map in the fourteen most frequent cancers in western societies (breast, colon, kidney, leukaemia, liver, lung, neuroblastoma, ovary, pancreas, prostate, skin, stomach, thyroid, and uterus) to their transcriptome, proteome and interactome in the same tumour type, we have identified the most prominent AM molecular alterations within each class. The comparison of the fourteen mutated AM networks (both protein- as MIR-based) has allowed us to pinpoint the hubs with a general and critical role in tumour development and, conversely, in cell physiology: in particular, we found that some of these had already been used as targets for pharmacological anticancer therapy. For a better understanding of the relationship between AM molecular alterations and pharmacological induction of apoptosis in cancer, we examined the expression of AM genes in K562 and SH-SY5Y after anticancer treatment.


CONCLUSIONS
We believe that our data on the Apoptotic Machinery will lead to the identification of new cancer genes and to the discovery of new biomarkers, which could then be used to profile cancers for diagnostic purposes and to pinpoint new targets for pharmacological therapy. This approach could pave the way for future studies and applications in molecular and clinical Medicine with important perspectives both for Oncology as for Regenerative Medicine.
Di Pietro
Cinzia
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Dipartimento di Scienze BioMediche, Sezione di Biologia Generale, Biologia Cellulare, Genetica Molecolare G Sichel, Unità di Biologia Genomica e dei Sistemi Complessi, Genetica, Bioinformatica, Università di Catania, 95123 Catania, Italy. dipietro@unict.it
Ragusa
Marco
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Barbagallo
Davide
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Duro
Laura R
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Guglielmino
Maria R
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Majorana
Alessandra
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Angelica
Rosario
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Scalia
Marina
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Statello
Luisa
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Salito
Loredana
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Tomasello
Luisa
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Pernagallo
Salvo
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Valenti
Salvo
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D'Agostino
Vito
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Triberio
Patrizio
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Tandurella
Igor
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Palumbo
Giuseppe A
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La Cava
Piera
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Cafiso
Viviana
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Bertuccio
Taschia
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Santagati
Maria
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Li Destri
Giovanni
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Lanzafame
Salvatore
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Di Raimondo
Francesco
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Stefani
Stefania
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Mishra
Bud
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Purrello
Michele
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