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

Cinzia Di Pietro, Marco Ragusa, Davide Barbagallo, Laura R. Duro, Maria R. Guglielmino, Alessandra Majorana, Rosario Angelica, Marina Scalia, Luisa Statello, Loredana Salito, Luisa Tomasello, Salvo Pernagallo, Salvo Valenti, Vito D'Agostino, Patrizio Triberio, Igor Tandurella, Giuseppe A. Palumbo, Piera La Cava, Viviana Cafiso, Taschia BertuccioMaria Santagati, Giovanni Li Destri, Salvatore Lanzafame, Francesco Di Raimondo, Stefania Stefani, Bud Mishra, Michele Purrello

Research output: Contribution to journalArticle

Abstract

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. Conclusion. 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.

Original languageEnglish
Article number20
JournalBMC Medical Genomics
Volume2
DOIs
Publication statusPublished - 2009

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Genetic Association Studies
Systems Analysis
Neuroblastoma
Neoplasms
Pharmacology
Apoptosis
Molecular Medicine
Biological Phenomena
Cell Physiological Phenomena
Regenerative Medicine
Gene Targeting
Neoplasm Genes
Pharmacogenetics
Clinical Medicine
Proteome
Genomics
Computational Biology
Transcriptome
Proteomics
Uterus

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics

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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. / Di Pietro, Cinzia; Ragusa, Marco; Barbagallo, Davide; Duro, Laura R.; Guglielmino, Maria R.; Majorana, Alessandra; Angelica, Rosario; Scalia, Marina; Statello, Luisa; Salito, Loredana; Tomasello, Luisa; Pernagallo, Salvo; Valenti, Salvo; D'Agostino, Vito; Triberio, Patrizio; Tandurella, Igor; Palumbo, Giuseppe A.; La Cava, Piera; Cafiso, Viviana; Bertuccio, Taschia; Santagati, Maria; Li Destri, Giovanni; Lanzafame, Salvatore; Di Raimondo, Francesco; Stefani, Stefania; Mishra, Bud; Purrello, Michele.

In: BMC Medical Genomics, Vol. 2, 20, 2009.

Research output: Contribution to journalArticle

Di Pietro, C, Ragusa, M, Barbagallo, D, Duro, LR, Guglielmino, MR, Majorana, A, Angelica, R, Scalia, M, Statello, L, Salito, L, Tomasello, L, Pernagallo, S, Valenti, S, D'Agostino, V, Triberio, P, Tandurella, I, Palumbo, GA, La Cava, P, Cafiso, V, Bertuccio, T, Santagati, M, Li Destri, G, Lanzafame, S, Di Raimondo, F, Stefani, S, Mishra, B & Purrello, M 2009, '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', BMC Medical Genomics, vol. 2, 20. https://doi.org/10.1186/1755-8794-2-20
Di Pietro, Cinzia ; Ragusa, Marco ; Barbagallo, Davide ; Duro, Laura R. ; Guglielmino, Maria R. ; Majorana, Alessandra ; Angelica, Rosario ; Scalia, Marina ; Statello, Luisa ; Salito, Loredana ; Tomasello, Luisa ; Pernagallo, Salvo ; Valenti, Salvo ; D'Agostino, Vito ; Triberio, Patrizio ; Tandurella, Igor ; Palumbo, Giuseppe A. ; La Cava, Piera ; Cafiso, Viviana ; Bertuccio, Taschia ; Santagati, Maria ; Li Destri, Giovanni ; Lanzafame, Salvatore ; Di Raimondo, Francesco ; Stefani, Stefania ; Mishra, Bud ; Purrello, Michele. / 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. In: BMC Medical Genomics. 2009 ; Vol. 2.
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abstract = "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. Conclusion. 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.",
author = "{Di Pietro}, Cinzia and Marco Ragusa and Davide Barbagallo and Duro, {Laura R.} and Guglielmino, {Maria R.} and Alessandra Majorana and Rosario Angelica and Marina Scalia and Luisa Statello and Loredana Salito and Luisa Tomasello and Salvo Pernagallo and Salvo Valenti and Vito D'Agostino and Patrizio Triberio and Igor Tandurella and Palumbo, {Giuseppe A.} and {La Cava}, Piera and Viviana Cafiso and Taschia Bertuccio and Maria Santagati and {Li Destri}, Giovanni and Salvatore Lanzafame and {Di Raimondo}, Francesco and Stefania Stefani and Bud Mishra and Michele Purrello",
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T1 - The apoptotic machinery as a biological complex system

T2 - Analysis of its omics and evolution, identification of candidate genes for fourteen major types of cancer, and experimental validation in CML and neuroblastoma

AU - Di Pietro, Cinzia

AU - Ragusa, Marco

AU - Barbagallo, Davide

AU - Duro, Laura R.

AU - Guglielmino, Maria R.

AU - Majorana, Alessandra

AU - Angelica, Rosario

AU - Scalia, Marina

AU - Statello, Luisa

AU - Salito, Loredana

AU - Tomasello, Luisa

AU - Pernagallo, Salvo

AU - Valenti, Salvo

AU - D'Agostino, Vito

AU - Triberio, Patrizio

AU - Tandurella, Igor

AU - Palumbo, Giuseppe A.

AU - La Cava, Piera

AU - Cafiso, Viviana

AU - Bertuccio, Taschia

AU - Santagati, Maria

AU - Li Destri, Giovanni

AU - Lanzafame, Salvatore

AU - Di Raimondo, Francesco

AU - Stefani, Stefania

AU - Mishra, Bud

AU - Purrello, Michele

PY - 2009

Y1 - 2009

N2 - 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. Conclusion. 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.

AB - 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. Conclusion. 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.

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