1
|
Gloster HM and Brodland DG: The
epidemiology of skin cancer. Dermatol Surg. 22:217–226.
1996.PubMed/NCBI View Article : Google Scholar
|
2
|
Becker JC, Kirkwood JM, Agarwala SS,
Dummer R, Schrama D and Hauschild A: Molecularly targeted therapy
for melanoma: Current reality and future options. Cancer.
107:2317–2327. 2006.PubMed/NCBI View Article : Google Scholar
|
3
|
Ferrone CR, Ben Porat L, Panageas KS,
Berwick M, Halpern AC, Patel A and Coit DG: Clinicopathological
features of and risk factors for multiple primary melanomas. JAMA.
294:1647–1654. 2005.PubMed/NCBI View Article : Google Scholar
|
4
|
Bevona C, Goggins W, Quinn T, Fullerton J
and Tsao H: Cutaneous melanomas associated with nevi. Arch
Dermatol. 139:1620–1624. 2003.PubMed/NCBI View Article : Google Scholar
|
5
|
Balch CM, Gershenwald JE, Soong SJ,
Thompson JF, Atkins MB, Byrd DR, Buzaid AC, Cochran AJ, Coit DG,
Ding S, et al: Final version of 2009 AJCC melanoma staging and
classification. J Clin Oncol. 27:6199–6206. 2009.PubMed/NCBI View Article : Google Scholar
|
6
|
Balch CM, Murad TM, Soong SJ, Ingalls AL,
Halpern NB and Maddox WA: A multifactorial analysis of melanoma:
Prognostic histopathological features comparing Clark's and
Breslow's staging methods. Ann Surg. 188:732–742. 1978.PubMed/NCBI View Article : Google Scholar
|
7
|
Hoon DS, Bostick P, Kuo C, Okamoto T, Wang
HJ, Elashoff R and Morton DL: Molecular markers in blood as
surrogate prognostic indicators of melanoma recurrence. Cancer Res.
60:2253–2257. 2000.PubMed/NCBI
|
8
|
Takata M and Saida T: Genetic alterations
in melanocytic tumors. J Dermatol Sci. 43:1–10. 2006.PubMed/NCBI View Article : Google Scholar
|
9
|
Ilie MA, Caruntu C, Lupu M, Lixandru D,
Georgescu SR, Bastian A, Constantin C, Neagu M, Zurac SA and Boda
D: Current and future applications of confocal laser scanning
microscopy imaging in skin oncology. Oncol Lett. 17:4102–4111.
2019.PubMed/NCBI View Article : Google Scholar
|
10
|
Ali Z, Yousaf N and Larkin J: Melanoma
epidemiology, biology and prognosis. EJC Suppl. 11:81–91.
2013.PubMed/NCBI View Article : Google Scholar
|
11
|
Demierre MF, Chung C, Miller DR and Geller
AC: Early detection of thick melanomas in the United States: Beware
of the nodular subtype. Arch Dermatol. 141:745–750. 2005.PubMed/NCBI View Article : Google Scholar
|
12
|
Urist MM and Karnell LH: The national
cancer data base. Report on melanoma. Cancer. 74:782–788.
1994.PubMed/NCBI View Article : Google Scholar
|
13
|
Weyers W, Euler M, Diaz-Cascajo C, Schill
WB and Bonczkowitz M: Classification of cutaneous malignant
melanoma: A reassessment of histopathologic criteria for the
distinction of different types. Cancer. 86:288–299. 1999.PubMed/NCBI View Article : Google Scholar
|
14
|
Jaeger J, Koczan D, Thiesen HJ, Ibrahim
SM, Gross G, Spang R and Kunz M: Gene expression signatures for
tumor progression, tumor subtype, and tumor thickness in
laser-microdissected melanoma tissues. Clin Cancer Res. 13:806–815.
2007.PubMed/NCBI View Article : Google Scholar
|
15
|
Arrington JH, Reed RJ, Ichinose H and
Krementz ET: Plantar lentiginous melanoma: A distinctive variant of
human cutaneous malignant melanoma. Am J Surg. Pathol. 1:131–143.
1977.PubMed/NCBI
|
16
|
Feibleman GE, Stoll H and Maize JC:
Melanomas of the palm, sole, and nailbed: A clinicopathologic
study. Cancer. 46:2492–2504. 1980.PubMed/NCBI View Article : Google Scholar
|
17
|
Kossard S, Commens C, Symons M and Doyle
J: Lentinginous dysplastic naevi in the elderly: A potential
precursor for malignant melanoma. Australas J Dermatol. 32:27–37.
1991.PubMed/NCBI View Article : Google Scholar
|
18
|
Mandita A, Timofte D, Balcangiu-Stroescu
AE, Balan DG, Raducu L, Tanasescu MD, Diaconescu AC, Dragos D,
Cosconel CI, Stoicescu SM, et al: Treatment of high blood pressure
in patients with chronic renal disease. Rev Chim. 70:993–995.
2019.
|
19
|
Banerjee SS and Harris M: Morphological
and immunophenotypic variations in malignant melanoma.
Histopathology. 36:387–402. 2000.PubMed/NCBI View Article : Google Scholar
|
20
|
Marenholz I, Heizmann CW and Fritz G: S100
proteins in mouse and man: From evolution to function and pathology
(including an update of the nomenclature). Biochem Biophys Res
Commun. 322:1111–1122. 2004.PubMed/NCBI View Article : Google Scholar
|
21
|
Sedaghat F and Notopoulos A: S100 protein
family and its application in clinical practice. Hippokratia.
12:198–204. 2008.PubMed/NCBI
|
22
|
Ravasi T, Hsu K, Goyette J, Schroder K,
Yang Z, Rahimi F, Miranda LP, Alewood PF, Hume DA and Geczy C:
Probing the S100 protein family through genomic and functional
analysis. Genomics. 84:10–22. 2004.PubMed/NCBI View Article : Google Scholar
|
23
|
El Halal Schuch L, Azevedo MM, Furian R,
Rigon P, Reiter KC, Crivelatti I, Riccardi F and Bica CG:
Evaluation of Kindlin-1 and Ki-67 immunohistochemical expression in
primary cutaneous malignant melanoma: A clinical series. Appl
Cancer Res. 39(10)2019.
|
24
|
Bengtsson E and Ranefall P: Image analysis
in digital pathology: Combining automated assessment of Ki67
staining quality with calculation of Ki67 cell proliferation index.
Cytometry A. 95:714–716. 2019.PubMed/NCBI View Article : Google Scholar
|
25
|
Menon SS, Guruvayoorappan C, Sakthivel KM
and Rasmi RR: Ki-67 protein as a tumour proliferation marker. Clin
Chim Acta. 491:39–45. 2019.PubMed/NCBI View Article : Google Scholar
|
26
|
Thompson JJ, Herlyn MF, Elder DE, Clark
WH, Steplewski Z and Koprowski H: Use of monoclonal antibodies in
detection of melanoma-associated antigens in intact human tumors.
Am J Pathol. 107:357–361. 1982.PubMed/NCBI
|
27
|
Sun J, Morton TH Jr and Gown AM: Antibody
HMB-45 identifies the cells of blue nevi. An immunohistochemical
study on paraffin sections. Am J Surg Pathol. 14:748–751.
1990.PubMed/NCBI View Article : Google Scholar
|
28
|
Kaufmann O, Koch S, Burghardt J, Audring H
and Dietel M: Tyrosinase, melan-A, and KBA62 as markers for the
immunohistochemical identification of metastatic amelanotic
melanomas on paraffin sections. Mod Pathol. 11:740–746.
1998.PubMed/NCBI
|
29
|
Boda D: Cellomics as integrative omics for
cancer. Curr Proteomics. 10:237–245. 2013.
|
30
|
Ancuceanu R, Dinu M, Neaga I, Laszlo FG
and Boda D: Development of QSAR machine learning-based models to
forecast the effect of substances on malignant melanoma cells.
Oncol Lett. 17:4188–4196. 2019.PubMed/NCBI View Article : Google Scholar
|