Melanoma of Unknown Primary With Metastasis to the Brain: A Case Report and Review of the Literature

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We present the case of a 72-year-old male found to have melanoma of unknown primary (MUP) in the lung with brain metastasis. The patient has a history of prostate cancer with radical proctectomy in 1999, hypertension with right-sided heart failure, and bilateral cataracts treated operatively. He presented to their home hospital after an unwitnessed fall, with a history of left-sided weakness. He was found to have a parietal lobe mass and two lung masses, where he was transferred to our hospital for a higher level of care. Biopsy of the lung lesion revealed melanoma, and the patient did not have any skin or mucosal foci present to indicate a primary source. We present this case in conjunction with a review of the literature. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, our review resulted in 31 MUP case reports. Data was extracted on epidemiology, clinical presentations, diagnostics, treatment, and outcomes. The mean age was 57.5 with a male-to-female ratio of 1:1.3. The greatest instances of MUP occurred in prior smokers and patients with comorbidities, accounting for 17.95% of cases each. Thirty-one percent of patients presented with a growing palpable mass, 21% with gastrointestinal symptoms, and 21% with B-symptoms. Biopsy was the diagnostic standard, and the majority of patients also underwent biomarker studies. Treatment varied widely, and many patients underwent multiple phases. Outcomes ranged from death within several months to a disease-free period of three years. Our paper highlights the complexity and nuances of diagnosing MUP and primary malignant melanoma of the lung (PMML) and calls for further investigations to improve diagnostic and therapeutic approaches for rare presentations of melanoma. Despite limitations in sample size and data heterogeneity, this study highlights the diverse presentation and disease course of MUP, necessitating further studies to optimize patient outcomes.

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