Tumour growth rate improves tumour assessment and first-line systemic treatment decision-making for immunotherapy in patients with liver metastatic uveal melanoma

Pretreatment Tumor Growth Rate and Radiological Response as Predictive Markers of Pathological Response and Survival in Patients with Resectable Lung Cancer Treated by Neoadjuvant Treatment

INTRODUCTION

Predictive biomarkers associated with pathological response, progression precluding surgery, and/or recurrence after surgery are needed for patients with resectable non-small cell lung carcinoma (NSCLC) treated by neoadjuvant treatment. We evaluated the clinical impact of the pretreatment tumor growth rate (TGR0) and radiological response for patients with resectable NSCLC treated with neoadjuvant therapies.

METHODS

Consecutive patients with resectable stage IB (≥4 cm) to IIIA NSCLC treated by neoadjuvant platinum-doublet chemotherapy with or without nivolumab at our tertiary center were retrospectively analyzed. TGR0 and RECIST objective responses were determined. Multivariable analyses identified independent predictors of event-free survival (EFS), overall survival (OS), and major pathological response (MPR).

RESULTS

Between November 2017 and December 2022, 32 patients (mean [SD] age, 63.8 [8.0] years) were included. At a median follow-up of 54.8 months (95% CI, 42.3-60.4 months), eleven patients (34%) experienced progression or recurrence, and twelve deaths (38%) were recorded. The TGR0 cutoff of 30%/month remained the only independent factor associated with EFS (HR = 0.04; 95% CI, 0.01-0.3; p = 0.003) and OS (HR = 0.2; 95% CI, 0.03-0.7; p = 0.01). The TGR0 cut-off had a mean time-dependent AUC of 0.83 (95% CI, 0.64-0.95) and 0.80 (95% CI, 0.62-0.97) for predicting EFS and OS, respectively. Fifteen of 26 resection cases (58%) showed MPR including nine with pathological complete responses (35%). Only the objective response of the primary tumor was associated with MPR (OR = 27.5; 95% CI, 2.6-289.1; p = 0.006).

CONCLUSIONS

Assessment of TGR0 can identify patients who should benefit from neoadjuvant treatment. A tumor objective response might be a predictor of MPR after neoadjuvant treatment, which will help to adapt surgical management.

Evolving Management of Stage IV Melanoma

Significant advancements have been made in the treatment of advanced melanoma with the use of immune checkpoint inhibitors, novel immunotherapies, and BRAF/MEK-targeted therapies with numerous frontline treatment options. However, there remains suboptimal evidence to guide treatment decisions in many patients. These include patients with newly diagnosed disease, immune checkpoint inhibitor (ICI)-resistant/ICI-refractory disease, CNS metastases, history of autoimmune disease, and/or immune-related adverse events (irAEs). Uveal melanoma (UM) is a rare melanoma associated with a poor prognosis in the metastatic setting. Systemic treatments, including checkpoint inhibitors, failed to demonstrate any survival benefit. Tebentafusp, a bispecific molecule, is the first treatment to improve overall survival (OS) in patients with HLA A*02:01-positive metastatic UM.

Tumor Growth Rate as a Predictive Marker for Recurrence and Survival After Liver Resection in Patients with Liver Metastases of Uveal Melanoma

BACKGROUND

Surgical management of liver metastases of uveal melanoma (LMUM) is associated with the best survival rates, especially for patients with a low tumor burden in the liver. The aim was to determine whether the tumor growth rate (TGR₀) before liver resection helps predict survival in patients with resectable LMUM.

METHODS

This retrospective study included 99 patients with LMUM treated with liver resection between November 2007 and November 2020. TGR₀ was expressed as the percentage change in tumor volume over 1 month according to two pretreatment imaging scans. Multivariate Cox analyses identified independent predictors of disease-free survival (DFS) and overall survival (OS).

RESULTS

DFS and OS had a statistically significant positive linear relationship (Spearman correlation r = 0.68, p < 0.001). A disease-free interval (DFI) > 24 months and a TGR₀ ≤ 50%/month were independent factors associated with better DFS and OS. The 2-component model including TGR₀ and DFI had a mean time-dependent area under the curve (AUC) of 0.81 (95% CI, 0.75-0.86) and 0.77 (95% CI, 0.67-0.87), respectively, for predicting DFS and OS. DFI with TGR₀ defined three kinetic risk groups that had distinct DFS and OS outcomes (p < 0.001). Cytogenetic alterations at baseline were partially predictive factors of the kinetic risk score based on TGR₀ and DFI.

DISCUSSION

The assessment of TGR₀ improves prognostic stratification by identifying patients at high risk of recurrence and poor survival after liver resection. TGR₀ and DFI, reflecting tumor aggressivity, have the potential to be important markers for systemic adjuvant decisions.