Our focus is on translation of a novel microscopy approach, femtosecond pump-probe microscopy, which
our preliminary data shows can determine which (nominally) early-stage primary melanomas are instead
metastatic cancer. This is important because the current clinical “gold standard” of staging (histopathology and
sentinel lymph node biopsy (SLNB)) can assign early (non-metastatic) stages to tumors which are in reality
metastatic cancers, which delays treatment and costs lives. In fact, more people die from melanoma after initial
Stage I tumor diagnosis than after diagnosis of any higher grade. Today adjuvant therapies have made great
strides (on late-stage tumors) but all FDA-approved therapies are restricted to metastatic (stage III or IV)
melanomas because significant treatment-related adverse events are common. We believe adjuvant therapies
could be more effective, and less toxic, if applied to supposedly early stage tumors which have already generated
undetected metastases. Such “early adjuvant therapy” could have great benefits for disease control, reduced
toxicity, and reduced health costs, but this requires a good marker for deciding which early-stage patients should
go into such therapy, and existing markers have limited value. Our preliminary results show that we can identify
such patients with pump-probe microscopy. The ultimate goal is routine identification of incorrectly classified
early-stage lesions, at least from stages IIB/C and preferably from earlier stages as well, so the patient can be
treated to interrupt disease progression.
Specific Aim 1 focuses on optimizing multi-parameter pump-probe imaging to concentrate the clinically
relevant contrast. The apparatus redesign features modulation schemes that keep the applied power constant
while retaining complete control over pulse polarization and delays, plus detection schemes with angular
resolution. Demonstrations start with melanin in model systems and melanoma cells and move on to biopsies,
characterizing directional and polarization components of the pump-probe decay to maximize signal correlation
with chemical or cellular melanin degradation. Specific Aim 2 focuses on maximizing diagnostic utility using
patient biopsies from the Duke Biorepository to retrospectively diagnose metastatic melanoma and test the
performance of the improved clinically relevant contrast. This work is closely connected to pathology, as we view
the technology as complementing existing diagnostic protocols. Based on our very encouraging preliminary
results, machine learning algorithms will pay a large role in our assessment of diagnostic utility. We expect to
demonstrate that for at least Stage IIB/IIC tumors (7000 cases a year) pump-probe imaging can reliably segment
this population and identify the patients who almost certainly need treatment beyond excision.