The peripheral blood lymphocyte-to-monocyte ratio (LMR) has been associated with prognosis in many malignancies including metastatic melanoma. However, it has not been studied in patients treated with immune checkpoint inhibitors. In this study, we analyzed the baseline LMR with progression-free survival (PFS) and overall survival (OS) in metastatic melanoma patients treated with pembrolizumab. A total of 133 patients with metastatic melanoma treated with pembrolizumab were included in this retrospective study. LMR was calculated from pretherapy peripheral blood counts and the optimal cutoff value was determined by a receiver operator characteristic curve. PFS and OS were evaluated using the Kaplan-Meier method and multivariate Cox proportional hazard modeling. Patients with an LMR of at least 1.7 showed improved PFS (hazard ratio=0.55; 95% confidence interval: 0.34-0.92; P=0.024) and OS (hazard ratio=0.29; 95% confidence interval: 0.15-0.59; P=0.0007). The baseline LMR is associated with PFS and OS in metastatic melanoma patients treated with pembrolizumab, and could represent a convenient and cost-effective prognostic biomarker. Validation of these findings in an independent cohort is needed.
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http://dx.doi.org/10.1097/CMR.0000000000000404 | DOI Listing |
Bull Cancer
January 2025
Palliative Care Unit, ULR 2694 METRICS, CHU de Lille, Université de Lille, 59000 Lille, France.
Introduction: Immune checkpoint inhibition has revolutionized the management of metastatic melanoma, including in the final stages of disease progression: because it is well tolerated, some teams do not discontinue it in hopes of slowing disease progression. The risks are that treatment may be continued unnecessarily, causing side effects, and reduce access to specialist palliative care, in addition to increasing the cost of treatment.
Method: We explored the experiences of 10 patients in a university hospital with metastatic melanoma under continued immune checkpoint inhibitors combined with specialist palliative care.
J Immunother Cancer
January 2025
Surgery Branch, National Cancer Institute, Bethesda, Maryland, USA
Background: The use of tumor-infiltrating T lymphocytes (TIL) that recognize cancer neoantigens has led to lasting remissions in metastatic melanoma and certain cases of metastatic epithelial cancer. For the treatment of the latter, selecting cells for therapy typically involves laborious screening of TIL for recognition of autologous tumor-specific mutations, detected through next-generation sequencing of freshly resected metastatic tumors. Our study explored the feasibility of using archived formalin-fixed, paraffin-embedded (FFPE) primary tumor samples for cancer neoantigen discovery, to potentially expedite this process and reduce the need for resections normally required for tumor sequencing.
View Article and Find Full Text PDFFuture Oncol
January 2025
Department of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL, USA.
Patients diagnosed with metastatic basal cell carcinoma (BCC) have a poor prognosis. The current standard of care for adults with locally advanced or metastatic BCC who are not candidates for surgery or radiation therapy is treatment with hedgehog pathway inhibitors (HHIs). For patients who progress while on this therapy, further treatment options are limited.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Department of Medical Oncology, Hospital de la Santa Creu I Sant Pau, 08025 Barcelona, Spain.
Background: Anti-PD-1-based immunotherapy has improved outcomes in stage IIB to IV resected melanoma patients in clinical trials. However, little is known about real-world outcomes, prognostic factors and patterns of relapse.
Methods: This is a retrospective multicenter observational study including patients with resected melanoma treated with subsequent anti-PD-1-based adjuvant immunotherapy.
Cancers (Basel)
January 2025
Department of Biomedical Sciences and Engineering, National Central University, Taoyuan 320, Taiwan.
Background: Skin cancer is the most common cancer worldwide, with melanoma being the deadliest type, though it accounts for less than 5% of cases. Traditional skin cancer detection methods are effective but are often costly and time-consuming. Recent advances in artificial intelligence have improved skin cancer diagnosis by helping dermatologists identify suspicious lesions.
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