Background AIDS is one of the most devastating diseases in human history. Decades of studies have revealed host factors required for HIV infection, indicating that HIV exploits host processes for its own purposes. HIV infection leads to AIDS as well as various comorbidities. The associations between HIV and human pathways and diseases may reveal non-obvious relationships between HIV and non-HIV-defining diseases. Principal Findings Human biological pathways were evaluated and statistically compared against the presence of HIV host factor related genes. All of the obtained scores comparing HIV targeted genes and biological pathways were ranked. Different rank results based on overlapping genes, recovered virus-host interactions, co-expressed genes, and common interactions in human protein-protein interaction networks were obtained. Correlations between rankings suggested that these measures yielded diverse rankings. Rank combination of these ranks led to a final ranking of HIV-associated pathways, which revealed that HIV is associated with immune cell-related pathways and several cancer-related pathways. The proposed method is also applicable to the evaluation of associations between other pathogens and human pathways and diseases. Conclusions Our results suggest that HIV infection shares common molecular mechanisms with certain signaling pathways and cancers. Interference in apoptosis pathways and the long-term suppression of immune system functions by HIV infection might contribute to tumorigenesis. Relationships between HIV infection and human pathways of disease may aid in the identification of common drug targets for viral infections and other diseases.
References
[1]
Brass AL, Dykxhoorn DM, Benita Y, Yan N, Engelman A, et al. (2008) Identification of host proteins required for HIV infection through a functional genomic screen. Science 319: 921–926.
[2]
Konig R, Zhou Y, Elleder D, Diamond TL, Bonamy GM, et al. (2008) Global analysis of host-pathogen interactions that regulate early-stage HIV-1 replication. Cell 135: 49–60.
[3]
Zhou H, Xu M, Huang Q, Gates AT, Zhang XD, et al. (2008) Genome-scale RNAi screen for host factors required for HIV replication. Cell Host Microbe 4: 495–504.
[4]
Pinney JW, Dickerson JE, Fu W, Sanders-Beer BE, Ptak RG, et al. (2009) HIV-host interactions: a map of viral perturbation of the host system. AIDS 23: 549–554.
[5]
Ziegler JL (1985) AIDS and oncogenesis. Front Radiat Ther Oncol 19: 99–104.
[6]
Kwan CK, Ernst JD (2011) HIV and tuberculosis: a deadly human syndemic. Clin Microbiol Rev 24: 351–376.
[7]
Thio CL (2009) Hepatitis B and human immunodeficiency virus coinfection. Hepatology 49: S138–145.
[8]
Heaton RK, Franklin DR, Ellis RJ, McCutchan JA, Letendre SL, et al. (2011) HIV-associated neurocognitive disorders before and during the era of combination antiretroviral therapy: differences in rates, nature, and predictors. J Neurovirol 17: 3–16.
[9]
de Chassey B, Navratil V, Tafforeau L, Hiet MS, Aublin-Gex A, et al. (2008) Hepatitis C virus infection protein network. Mol Syst Biol 4: 230.
[10]
Calderwood MA, Venkatesan K, Xing L, Chase MR, Vazquez A, et al. (2007) Epstein-Barr virus and virus human protein interaction maps. Proc Natl Acad Sci U S A 104: 7606–7611.
[11]
Konig R, Stertz S, Zhou Y, Inoue A, Hoffmann HH, et al. (2010) Human host factors required for influenza virus replication. Nature 463: 813–817.
[12]
Dyer MD, Neff C, Dufford M, Rivera CG, Shattuck D, et al. (2010) The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis. PLoS One 5: e12089.
[13]
Dyer MD, Murali TM, Sobral BW (2008) The landscape of human proteins interacting with viruses and other pathogens. PLoS Pathog 4: e32.
[14]
Navratil V, de Chassey B, Combe CR, Lotteau V (2011) When the human viral infectome and diseasome networks collide: towards a systems biology platform for the aetiology of human diseases. BMC Syst Biol 5: 13.
[15]
Dickerson JE, Pinney JW, Robertson DL (2010) The biological context of HIV-1 host interactions reveals subtle insights into a system hijack. BMC Syst Biol 4: 80.
[16]
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, et al. (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102: 15545–15550.
[17]
Yi M, Stephens RM (2008) SLEPR: a sample-level enrichment-based pathway ranking method – seeking biological themes through pathway-level consistency. PLoS One 3: e3288.
[18]
Aerts S, Lambrechts D, Maity S, Van Loo P, Coessens B, et al. (2006) Gene prioritization through genomic data fusion. Nat Biotechnol 24: 537–544.
[19]
Yang J-M, Chen Y-F, Shen T-W, Kristal BS, Hsu DF (2005) Consensus Scoring Criteria for Improving Enrichment in Virtual Screening. Journal of Chemical Information and Modeling 45: 1134–1146.
[20]
Hsu DF, Taksa I (2005) Comparing Rank and Score Combination Methods for Data Fusion in Information Retrieval. Inf Retr 8: 449–480.
[21]
Kao CY, Hsu DF, Chuang HY, Huang CYF, Chen KC (2004) To combine or not to combine. Bulletin of International Chinese Statistical Associations July 2004: 37–39.
[22]
Brown JN, Kohler JJ, Coberley CR, Sleasman JW, Goodenow MM (2008) HIV-1 activates macrophages independent of Toll-like receptors. PLoS One 3: e3664.
[23]
Hyrcza MD, Kovacs C, Loutfy M, Halpenny R, Heisler L, et al. (2007) Distinct transcriptional profiles in ex vivo CD4+ and CD8+ T cells are established early in human immunodeficiency virus type 1 infection and are characterized by a chronic interferon response as well as extensive transcriptional changes in CD8+ T cells. J Virol 81: 3477–3486.
[24]
Sutton L, Guenel P, Tanguy ML, Rio B, Dhedin N, et al. (2001) Acute myeloid leukaemia in human immunodeficiency virus-infected adults: epidemiology, treatment feasibility and outcome. Br J Haematol 112: 900–908.
[25]
Gale RP, Opelz G (2011) Commentary: does immune suppression increase risk of developing acute myeloid leukemia? Leukemia (Advanced online publication).
Engels EA, Brock MV, Chen J, Hooker CM, Gillison M, et al. (2006) Elevated incidence of lung cancer among HIV-infected individuals. J Clin Oncol 24: 1383–1388.
[28]
Kirk GD, Merlo C, O'Driscoll P, Mehta SH, Galai N, et al. (2007) HIV infection is associated with an increased risk for lung cancer, independent of smoking. Clin Infect Dis 45: 103–110.
[29]
Frisch M, Biggar RJ, Engels EA, Goedert JJ (2001) Association of cancer with AIDS-related immunosuppression in adults. JAMA 285: 1736–1745.
[30]
Bonnet F, Burty C, Lewden C, Costagliola D, May T, et al. (2009) Changes in Cancer Mortality among HIV-Infected Patients: The Mortalité 2005 Survey. Clinical Infectious Diseases 48: 633–639.
[31]
Serraino D, Dal Maso L, De Paoli A, Zucchetto A, Bruzzone S, et al. (2009) On changes in cancer mortality among HIV-infected patients: is there an excess risk of death from pancreatic cancer? Clin Infect Dis 49: 481–482.
[32]
Kim RJ, Wilson CG, Wabitsch M, Lazar MA, Steppan CM (2006) HIV Protease Inhibitor-Specific Alterations in Human Adipocyte Differentiation and Metabolism[ast]. Obesity 14: 994–1002.
[33]
Estrada V, Martínez-Larrad MT, González-Sánchez JL, de Villar NGP, Zabena C, et al. (2006) Lipodystrophy and metabolic syndrome in HIV-infected patients treated with antiretroviral therapy. Metabolism 55: 940–945.
[34]
Mallewa JE, Wilkins E, Vilar J, Mallewa M, Doran D, et al. (2008) HIV-associated lipodystrophy: a review of underlying mechanisms and therapeutic options. J Antimicrob Chemother 62: 648–660.
[35]
Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100: 57–70.
[36]
Collado M, Serrano M (2010) Senescence in tumours: evidence from mice and humans. Nat Rev Cancer 10: 51–57.
[37]
Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M (2012) KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 40: D109–114.
[38]
Chugh P, Fan S, Planelles V, Maggirwar SB, Dewhurst S, et al. (2007) Infection of human immunodeficiency virus and intracellular viral Tat protein exert a pro-survival effect in a human microglial cell line. J Mol Biol 366: 67–81.
[39]
Deregibus MC, Cantaluppi V, Doublier S, Brizzi MF, Deambrosis I, et al. (2002) HIV-1-Tat protein activates phosphatidylinositol 3-kinase/AKT-dependent survival pathways in Kaposi's sarcoma cells. J Biol Chem 277: 25195–25202.
[40]
Manfredi R, Calza L, Chiodo F (2004) A case-control study of HIV-associated pancreatic abnormalities during HAART era. Focus on emerging risk factors and specific management. Eur J Med Res 9: 537–544.
[41]
Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ, et al. (2008) Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321: 1801–1806.
[42]
Grulich AE, van Leeuwen MT, Falster MO, Vajdic CM (2007) Incidence of cancers in people with HIV/AIDS compared with immunosuppressed transplant recipients: a meta-analysis. The Lancet 370: 59–67.
[43]
Kang TW, Yevsa T, Woller N, Hoenicke L, Wuestefeld T, et al. (2011) Senescence surveillance of pre-malignant hepatocytes limits liver cancer development. Nature.
[44]
Serrano M (2011) Cancer: Final act of senescence. Nature 479: 481–482.
[45]
Chow WA, Jiang C, Guan M (2009) Anti-HIV drugs for cancer therapeutics: back to the future? Lancet Oncol 10: 61–71.
[46]
Brunner TB, Geiger M, Grabenbauer GG, Lang-Welzenbach M, Mantoni TS, et al. (2008) Phase I trial of the human immunodeficiency virus protease inhibitor nelfinavir and chemoradiation for locally advanced pancreatic cancer. J Clin Oncol 26: 2699–2706.
[47]
Xie L, Evangelidis T, Bourne PE (2011) Drug discovery using chemical systems biology: weak inhibition of multiple kinases may contribute to the anti-cancer effect of nelfinavir. PLoS Comput Biol 7: e1002037.
de la Fuente C, Maddukuri A, Kehn K, Baylor SY, Deng L, et al. (2003) Pharmacological cyclin-dependent kinase inhibitors as HIV-1 antiviral therapeutics. Curr HIV Res 1: 131–152.
[50]
Sadaie MR, Mayner R, Doniger J (2004) A novel approach to develop anti-HIV drugs: adapting non-nucleoside anticancer chemotherapeutics. Antiviral Res 61: 1–18.
[51]
Hsu DF, Chung Y-S, Kristal BS (2006) Combinatorial Fusion Analysis: Methods and Practices of Combining Multiple Scoring Systems. In: Hsu HH, editor. Advanced Data Mining Technologies in Bioinformatics. Idea Group Inc.
[52]
Hsu DF, Kristal BS, Schweikert C (2010) Rank-score characteristics (RSC) function and cognitive diversity. Proceedings of the 2010 international conference on Brain informatics. Toronto, ON, Canada: Springer-Verlag. pp. 42–54.
[53]
Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27: 431–432.
[54]
Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38: D355–360.
[55]
Carlson MR, Zhang B, Fang Z, Mischel PS, Horvath S, et al. (2006) Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks. BMC Genomics 7: 40.
[56]
D'haeseleer P, Liang S, Somogyi R (2000) Genetic network inference: from co-expression clustering to reverse engineering. Bioinformatics 16: 707–726.
[57]
Wu C, Orozco C, Boyer J, Leglise M, Goodale J, et al. (2009) BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome Biol 10: R130.
[58]
Marcotte EM, Pellegrini M, Ng H-L, Rice DW, Yeates TO, et al. (1999) Detecting Protein Function and Protein-Protein Interactions from Genome Sequences. Science 285: 751–753.
[59]
Vazquez A, Flammini A, Maritan A, Vespignani A (2003) Global protein function prediction from protein-protein interaction networks. Nat Biotech 21: 697–700.
