Background:
A better understanding of prognostic factors and biomarkers that predict response
to treatment is required in order to further improve survival rates in patients with melanoma.
Predictive Biomarkers:
The most important histopathological factors prognostic of worse outcomes in
melanoma are sentinel lymph node involvement, increased tumor thickness, ulceration and higher mitotic
rate. Poorer survival may also be related to several clinical factors, including male gender, older
age, axial location of the melanoma, elevated serum levels of lactate dehydrogenase and S100B.
Predictive Biomarkers:
Several biomarkers have been investigated as being predictive of response to
melanoma therapies. For anti-Programmed Death-1(PD-1)/Programmed Death-Ligand 1 (PD-L1)
checkpoint inhibitors, PD-L1 tumor expression was initially proposed to have a predictive role in response
to anti-PD-1/PD-L1 treatment. However, patients without PD-L1 expression also have a survival
benefit with anti-PD-1/PD-L1 therapy, meaning it cannot be used alone to select patients for
treatment, in order to affirm that it could be considered a correlative, but not a predictive marker. A
range of other factors have shown an association with treatment outcomes and offer potential as predictive
biomarkers for immunotherapy, including immune infiltration, chemokine signatures, and tumor
mutational load. However, none of these have been clinically validated as a factor for patient selection.
For combined targeted therapy (BRAF and MEK inhibition), lactate dehydrogenase level and tumor
burden seem to have a role in patient outcomes.
Conclusions:
With increasing knowledge, the understanding of melanoma stage-specific prognostic
features should further improve. Moreover, ongoing trials should provide increasing evidence on the
best use of biomarkers to help select the most appropriate patients for tailored treatment with immunotherapies
and targeted therapies.
Parosteal Osteosarcoma: Radiologic and Prognostic Features
