Melanoma Molecular Maps Projects

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Molecular biology



Over the past two decades, several preclinical advancements have been made in the field of melanoma molecular biology [1-15]. The study of familiar cases has led to the identification of putative melanoma susceptibility genes (e.g. p16, p14ARF, see Familial Melanoma section). However, familiar melanomas represent approximately 5-10% of all melanoma cases, and sporadic melanomas rarely show the same molecular derangements found in familiar cases. Therefore, other molecular derangements must be involved in the pathogenesis of most melanomas.

Although sunlight is believed to play a key role in melanomagenesis (see Sun Exposure paragraph in the Risk Factors section), the cascade of molecular events leading to sporadic melanoma development is just beginning to be dissected. In particular, thousands of reports have been published describing molecular mechanisms underlying melanoma development, progression and resistance to conventional therapies. A few classical examples of molecular pathways whose alterations have been linked to melanoma malignant behavior are the following: tyrosine kinase receptors (TKR) pathways (e.g. VEGFR, HER, TGFBR), Ras / Raf / MEK / ERK pathway, PI3K / Akt / PTEN / mTOR pathway, cell cycle regulation pathways (Rb / p53 / p16INKA / p14ARF / HDM2), epigenetic gene expression regulation (DNA methylation, histone acetylation and microRNA), programmed cell death (apoptosis) pathways (e.g. death receptor pathway: FAS, TRAILR, TNFR; mitochondrial pathway: Bcl2 family), common apoptosis effectors (e.g. caspases), protein chaperoning and degradation (HSP, proteasome).

Recently, the implementation on a large scale of novel biotechnologies such as high-throughput platforms (e.g. gene microarray, proteomics) and genomic tools (e.g. RNA interference) has further increased the discovery pace in the field of molecular oncology, including melanoma research [7, 16-20]. The huge amount of data presently available has required the development of dedicated statistical and mathematical models to analyze and integrate the information generated. Moreover, the myriad of interactions between single molecules, regulatory circuits, different pathways, normal and malignant cells is making the understanding of cancer biology so complicated that a new discipline called "systems biology" has been dedicated to the integration of all this information [21].

In a translational medicine perspective [22], these advancements should lead to the identification of highly accurate diagnostic (i.e. related the presence or absence of minimal residual disease), prognostic (i.e. related to patient survival) and predictive (tumor response to therapy) biomarkers as well as to the identification of molecular targets suitable for the development of cancer specific drugs. Ultimately, this approach should lead to the holy grail of molecular oncology, which is the clinical implementation of the personalized treatment of cancer (see Molecularly targeted therapy section).

The description of the role of each single molecular derangement in melanoma development, progression and resistance to conventional therapy is one of the main objectives of the MMMP website.

The following are some examples of the molecular pathways involved in melanoma biology and described in the Biomaps database (by clicking on the image, the reader will be redirected to the corresponding Biomap).

The full list of pathways described in the MMMP website is available at: MMMP Biomaps.



FIGURE 1: The AKT pathways (click on the snapshot to open the corresponding Biomap).




FIGURE 2: The apoptosis pathways (click on the snapshot to open the corresponding Biomap).




FIGURE 3: The ceramide pathways (click on the snapshot to open the corresponding Biomap).




FIGURE 4: The EGFR pathways (click on the snapshot to open the corresponding Biomap).




FIGURE 5: The FOXO pathways (click on the snapshot to open the corresponding Biomap).




FIGURE 6: The Hedgehog pathways (click on the snapshot to open the corresponding Biomap).





References

[1] Zaidi MR et al, From UVs to metastases: modeling melanoma initiation and progression in the mouse. J Invest Dermatol 2008, 128:2381-91

[2] Sekulic A et al, Malignant melanoma in the 21st century: the emerging molecular landscape. Mayo Clin Proc 2008, 83:825-46

[3] Lomas J et al, The genetics of malignant melanoma. Front Biosci 2008, 13:5071-93

[4] Pons M et al, Molecular biology of malignant melanoma. Adv Exp Med Biol 2008, 624:252-64

[5] Fecher LA et al, Toward a molecular classification of melanoma. J Clin Oncol 2007, 25:1606-20

[6] Gray-Schopfer V et al, Melanoma biology and new targeted therapy. Nature 2007, 445:851-7

[7] Hoek KS. DNA microarray analyses of melanoma gene expression: a decade in the mines. Pigment Cell Res 2007, 20:466-84

[8] Hayward NK, Genetics of melanoma predisposition. Oncogene 2003, 22:3053-62

[9] Chin L, The genetics of malignant melanoma: lessons from mouse and man. Nat Rev Cancer 2003, 3:559-70

[10] Houghton AN et al, Focus on melanoma. Cancer Cell 2002, 2:275-8

[11] Merlino G et al, Modeling gene-environment interactions in malignant melanoma. Trends Mol Med 2003, 9:102-8

[12] Miller AJ et al, Melanoma. NEJM 2006, 355:51-65

[13] Rivers JK, Is there more than one road to melanoma? Lancet 2004, 363:728-30

[14] Haluska FG et al, Genetic alterations in signaling pathways in melanoma. Clin Cancer Res 2006, 12:2301s-2307s

[15] Kabbarah O et al, Revealing the genomic heterogeneity of melanoma. Cancer Cell 2005, 8:439-41

[16] Bittner M et al, Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature 2000, 406:536-40

[17] Winnepenninckx V et al, Gene expression profiling of primary cutaneous melanoma and clinical outcome. JNCI 2006, 98:472-82

[18] Garraway LA et al, Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 2005, 436:117-22

[19] Bernard K et al, Functional proteomic analysis of melanoma progression. Cancer Res 2003, 63:6716-25

[20] Kim M et al, Comparative oncogenomics identifies NEDD9 as a melanoma metastasis gene. Cell 2006, 125:1269-81

[21] Hornberg JJ et al, Cancer: a systems biology disease. Biosystems 2006, 83:81-90

[22] Marincola FM, Translational medicine: a two-way road. J Transl Med 2003, 1:1

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