Melanoma Molecular Maps Projects

Padova

Prognostic factors

[1] Tumor thickness (T)
[2] Lymph node involvement (N)
[3] Distant metastasis (M)
[4] Ulceration
[5] Regression
[6] Mitotic rate
[7] Lymphovascular invasion
[8] Age
[9] Histological type
[10] Tumor infiltrating lymphocytes
[11] Molecular markers


Tumor thickness (T)

Together with nodal involvement and distant metastasis, tumor thickness is one of the most reliable prognostic predictors currently available (see TNM staging section) [1, 2].
Two grading systems have been classically employed: 1) the Breslow's system is based upon the measurement of the maximum absolute thickness of the melanoma from the granular layer of the epidermis to the deepest point of invasion into the dermis: this is the most widely accepted system to grade melanoma depth and is adopted by the TNM staging system (see TNM staging section); 2) the Clark's levels describe melanoma depth according to the invasion of the four skin layers.



Lymph node involvement (N)

Together with tumor thickness and distant metastasis, the status of regional lymph nodes is one of the most reliable prognostic predictors currently available (see TNM staging section) [1, 2].
In-transit metastatic disease is a typical occurrence of skin melanoma and is believed to represent the spread of malignant cells through the lymphatic vessels draining the primary tumor. As such, in-transit metastases are classified together with lymph node metastases in the TNM staging system (see TNM staging section).
The relatively recent introduction of the sentinel lymph node biopsy (SNB) has drastically changed the way to assess lymph node status (2). See Sentinel lymph node section for more details.


Distant metastasis (M)

Together with tumor thickness and lymph node involvement, the presence or absence of metastatic disease profoundly affects patients' survival (see TNM staging section) [1, 2].
The most frequently involved distant sites of metastasis are lungs, central nervous system (CNS), soft tissues (e.g. subcutis, extraregional lymph nodes), liver and bone. Of note, the prognosis of superficial distant metastases (e.g. skin, subcutis) is better than that of visceral metastatic disease (e.g. lung, CNS, liver, bone and so forth).


Ulceration

Ulceration, histologically defined as the absence of an intact layer of epidermis over any part of the tumor, is found in 20% to 60% of primary melanomas. It presence is strongly linked to tumor thickness, although melanomas of any depth can ulcerate.
As it independently predicts disease recurrence and worse overall survival, ulceration has been implemented in the TNM staging system (see TNM staging section) [1, 2].



Regression

Regression is characterized by the replacement of tumor cells with lymphocytic infiltrate associated with variable dermal fibrosis, vascular proliferation and melanin-containing macrophages [7]. Its prognostic significance is still controversial. It has been hypothesized that the unfavorable influence may be related to a permissive role played by regression in the development of a vertical phase; on the other hand, regression may lead to underestimate Breslow depth, which ultimately causes the understaging of patients.



Mitotic rate

Mitotic rate is usually expressed as the number of mitoses per squared millimeter. Although its prognostic value is not universally recognized, several recent studies have demonstrated that the mitotic rate is an independent prognostic factor in localized melanoma [3-5].



Lymphovascular invasion

As for other solid tumors, the infiltration of blood and lymphatic vessels by melanoma cells has been associated with worse prognosis [6].



Age

Although older patients present more frequently with thicker and ulcerated melanomas, many studies have reported age to be an independent prognostic factor. In a large study (more than 17,000 patients), each 10-year increase in age was associated with a decline in both 5- and 10-year survival rates [1].


Histological type

Melanoma histotype has been classically associated with prognosis, a progressively worse outcome being associated with lentigo maligna melanoma, superficial spreading melanoma, acral lentiginous melanoma and nodular melanoma, respectively. However, at multivariate analysis, the histological type is not usually retained as an independent variable when other prognostic factors (e.g. tumor thickness) are included.


Tumor infiltrating lymphocytes

The prognostic role of tumor infiltrating lymphocytes (TIL) in patients with melanoma has been analyzed in several studies that yielded conflicting results. This might be related to the different methods used in evaluating and quantifying this parameter.




Molecular markers

Despite the fact that the above mentioned clinicopathological factors are the most reliable prognosticators currently available, none of them or their combinations can accurately predict the clinical outcome on a single patient basis, as demonstrated by the relatively wide range of survival rates within each TNM stage (see TNM staging section).

Since the malignant phenotype is sustained by the complex molecular derangement of tumor cells, it is logical to expect that advancements in molecular oncology will provide clinicians with novel and more effective prognostic tools [8, 9].

Prognostic biomarkers are being sought mainly in the primary tumor by investigating the expression of molecules suggestive of cancer aggressiveness, which ultimately can be considered a surrogate marker of the risk for the patient of harboring minimal residual disease (MRD). As the molecular biology of melanoma is dissected, a growing number of molecular markers is being proposed. For some of them (e.g. Akt, MITF, PTEN, Bcl-2, NCOA3) a prognostic value has been claimed [10-14]. The discovery pace for novel prognosis indicators has been recently accelerated by the implementation of high-throughput technologies, such as gene microarray [15, 16]. However, the statistical independence of molecular markers from traditional clinicopathological factors (with particular regard to tumor thickness) has not been demonstrated in all series, which are often small and heterogeneous; moreover, results are rarely confirmed in different series.

The direct search for MRD is an emerging research field whose aim is to demonstrate the presence of microscopic melanoma residues not detectable by conventional imaging techniques or pathological examinations. Thus far, the only biomarker universally recognized as an useful prognostic factor is lactate-dehydrogenase (LDH): its plasma levels are in fact included in the TNM system for patients with distant metastatic disease (LDH is of no use for earlier disease stages) [1, 2]. Other single plasma proteins have been proposed (e.g. S100, melanoma inhibitory activity [MIA], TA90), but no consensus exists on their prognostic power [17, 18]. Examples of more recent developments in this field are the sentinel node ultrastaging by means of PCR based methods [19], the detection of circulating tumor cells or free DNA in the peripheral blood [20], and the serum protein profiling by means of proteomics technologies [21]. However, results are often controversial, and overall no conclusive evidence is yet available.

Besides molecular factors with strictly prognostic value, biomarkers predictive of response to therapy are another active and fundamental field of investigation to select patients who most benefit from a given anticancer agent, which ultimately would lead to increase the therapeutic index (i.e., the ratio between clinical benefit and toxicity) of available treatments [8, 22]. However, as regards melanoma, this research field is still in its infancy [9, 23].

Thus far, there is no critical mass of scientific evidence for any biomarker to be implemented in the routine clinical management of patients with melanoma. This observation urges investigators to systematically include the study of biological correlates while designing clinical trials [24, 25].


References

[1] Balch CM et al, Prognostic factors analysis of 17,600 melanoma patients: validation of the American Joint Committee on Cancer melanoma staging system. J Clin Oncol 2001, 19:3622-34

[2] Balch CM et al, An evidence-based staging system for cutaneous melanoma. CA Cancer J Clin 2004, 54:131-49

[3] Gimotty PA et al, Biologic and prognostic significance of dermal Ki67 expression, mitoses, and tumorigenicity in thin invasive cutaneous melanoma. J Clin Oncol 2005, 23:8048-56

[4] Nagore E et al, Prognostic factors in localized invasive cutaneous melanoma: high value of mitotic rate, vascular invasion and microscopic satellitosis. Melanoma Res 2005, 15:169-77

[5] Francken AB et al, The prognostic importance of tumor mitotic rate confirmed in 1317 patients with primary cutaneous melanoma and long follow-up. Ann Surg Oncol 2004, 11:426-33

[6] Kashani-Sabet M et al, Vascular involvement in the prognosis of primary cutaneous melanoma. Arch Dermatol 2001, 137:1169-73

[7] Kang S et al, Histologic regression in malignant melanoma: an interobserver concordance study. J Cutan Pathol 1993, 20:126-9

[8] Ludwig JA et al, Biomarkers in cancer staging, prognosis and treatment selection. Nat Rev Cancer 2005, 5:845-56

[9] Torabian S et al, Biomarkers for melanoma. Curr Opin Oncol 2005, 17:167-71

[10] Fecker LF et al, Loss of proapoptotic Bcl-2-related multidomain proteins in primary melanomas is associated with poor prognosis. J Invest Dermatol 2006, 126:1366-71

[11] Mikhail M et al, PTEN expression in melanoma: relationship with patient survival, Bcl-2 expression, and proliferation. Clin Cancer Res 2005, 11:5153-7

[12] Rangel J et al, Prognostic significance of nuclear receptor coactivator-3 overexpression in primary cutaneous melanoma. J Clin Oncol 2006, 24:4565-9

[13] Dai DL et al, Prognostic significance of activated Akt expression in melanoma: a clinicopathologic study of 292 cases. J Clin Oncol 2005, 23:1473-82

[14] Salti GI et al, Micropthalmia transcription factor: a new prognostic marker in intermediate-thickness cutaneous malignant melanoma. Cancer Res 2000, 60:5012-6

[15] Winnepenninckx V et al, Gene expression profiling of primary cutaneous melanoma and clinical outcome. J Natl Cancer Inst 2006, 98:472-82

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

[17] Kounalakis N et al, Tumor cell and circulating markers in melanoma: diagnosis, prognosis, and management. Curr Oncol Rep 2005, 7:377-82

[18] Brochez L et al, Serological markers for melanoma. Br J Dermatol 2000, 143:256-68

[19] Martinez SR et al, Molecular upstaging of sentinel lymph nodes in melanoma: where are we now? Surg Oncol Clin N Am 2006, 15:331-40

[20] Mocellin S et al, The prognostic value of circulating tumor cells in patients with melanoma: a systematic review and meta-analysis. Clin Cancer Res 2006, 12:4605-13

[21] Mian S et al, Serum proteomic fingerprinting discriminates between clinical stages and predicts disease progression in melanoma patients. J Clin Oncol 2005, 23:5088-93

[22] Longley DB et al, Molecular mechanisms of drug resistance. J Pathol 2005, 205:275-92

[23] Soengas MS et al, Apoptosis and melanoma chemoresistance. Oncogene 2003, 22:3138-51

[24] Sargent DJ et al, Clinical trial designs for predictive marker validation in cancer treatment trials. J Clin Oncol 2005, 23:2020-7

[25] Singer E, Personalized medicine prompts push to redesign clinical trials. Nat Med 2005, 11:462

Figure 1: Clark's levels for cutaneous melanoma. Level I corresponds to in situ melanoma.

Search the site


Risk Assessment Tools

TNM Staging System | Total Dermoscopy Score | Thin Melanoma Prognosis |


Melanoma News


NCBI's Disclaimer and Copyright notice