Abstract

Immune checkpoint inhibitors have revolutionized treatment and outcome of melanoma and many other solid malignancies including non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC). Unfortunately, only a minority of patients have a long-term benefit, while the remaining demonstrate primary or acquired resistance. Recently, it has been demonstrated that the prevalence of programmed death-ligand 1 (PD-L1) and tumor-infiltrating lymphocytes (TILs) varies based on the anatomical site of metastases. In particular, liver seems to have more immunosuppressive microenvironment while both the presence of lymph nodal disease and lung metastases seem to have the highest prevalence of PD-L1 and TILs. The aim of the present study is to investigate the possible role of site of metastases as a predictive factor for response or resistance to immunotherapy in several types of cancer. In this multicenter retrospective study, we enrolled patients with metastatic NSCLC, melanoma, RCC, urothelial, merkel carcinoma, and colon cancer who received immunotherapy from April 2015 to August 2019. Major clinicopathological parameters were retrieved and correlated with patients’ survival outcomes in order to assess their prognostic value and build a useful tool to assist in the decision-making process. A total of 291 patients were included in this study. One hundred eighty-seven (64%) patients were male and 104 (36%) female. The tumor histology was squamous NSCLC in 56 (19%) patients, non-squamous NSCLC in 99 (34%) patients, melanoma in 101 (35%) patients, RCC in 28 (10%) patients, and other tumors in the remaining 7 (2%) patients. The number of metastatic sites was 1 in 103 patients (35%), 2 in 104 patients (36%) and 3 in 84 patients (29%). Out of 183 valuable patients, the entity of response was complete response (CR), partial response (PR), stable disease (SD), and progression disease (PD) in 15, 53, 31, and 79 patients, respectively. Using an univariate analysis (UVA), tumor burden (p = 0.0004), the presence of liver (p = 0.0009), bone (p = 0.0016), brain metastases (p < 0.0001), the other metastatic sites (p = 0.0375), the number of metastatic sites (p = 0.0039), the histology (p = 0.0034), the upfront use of immunotherapy (p = 0.0032), and Eastern Cooperative Oncology Group (ECOG) Perfomance status (PS) ≥ 1 (p < 0.0001) were significantly associated with poor overall survival (OS). Using a multivariate analysis (MVA) the presence of liver (p = 0.0105) and brain (p = 0.0026) metastases, the NSCLC diagnosis (p < 0.0001) and the ECOG PS (p < 0.0001) resulted as significant prognostic factors of survival. Regarding the progression free survival (PFS), using a UVA of the tumor burden (p = 0.0004), bone (p = 0.0098) and brain (p = 0.0038) metastases, the presence of other metastatic sites (p = 0.0063), the number of metastatic sites (p = 0.0007), the histology (p = 0.0007), the use of immunotherapy as first line (p = 0.0031), and the ECOG PS ≥ 1 (p ≤ 0.0001) were associated with a lower PFS rate. Using an MVA, the presence of brain (p = 0.0088) and liver metastases (p = 0.024) and the ECOG PS (p < 0.0001) resulted as predictors of poor PFS. Our study suggests that the site of metastases could have a role as prognostic and predictive factor in patients treated with immunotherapy. Indeed, regardless of the histology, the presence of liver and brain metastases was associated with a shorter PFS and OS, but these results must be confirmed in further studies. In this context, a deep characterization of microenvironment could be crucial to prepare patients through novel strategies with combination or sequential immunotherapy in order to improve treatment response.

Highlights

  • Two hundred ninety-one metastatic patients treated with immune checkpoint inhibitors (ICIs) were enrolled in this study

  • We evaluated OS between different cancer histologies, highlighting a worse prognosis in patients affected by both squamous and non-squamous non-small cell lung cancer (NSCLC) compared to other cancers (Figure 1e,f, p < 0.001 and p = 0.0044 respectively)

  • In order to translate these data into clinical practice, we have developed two nomograms for OS and Progression-free survival (PFS), that are based on available and inexpensive clinical factors that have showed a good performance in predicting individual PFS and OS probability among cancer patients treated with immunotherapy

Read more

Summary

Introduction

The advent of immunotherapy represents a revolutionary event for the treatment of cancer especially for melanoma, advanced non-small-cell lung cancer (NSCLC), renal cell carcinoma (RCC), breast cancer, head and neck, and urothelial cancer both in metastatic and adjuvant settings.The immune checkpoint inhibitors (ICIs) currently used in clinical practise include the antibody anti-cytotoxic T lymphocyte antigen-4 (CTLA-4 inhibitor) ipilimumab, anti-programmed death 1(anti PD-1) (nivolumab and pembrolizumab) and anti-programmed death-ligand 1 (anti PD-L1)(atezolizumab, avelumab, and durvalumab) were used as monotherapies as well as in combination with other anticancer drugs [1,2,3,4,5].These agents have a favorable toxicity profile than chemotherapy or targeted therapies offering the promise of durable clinical benefit, albeit only for a minority of patients [6,7,8,9,10].Today, the real goal is the selection of the ideal patient who can receive immunotherapy through the identification of specific biomarkers. (atezolizumab, avelumab, and durvalumab) were used as monotherapies as well as in combination with other anticancer drugs [1,2,3,4,5] These agents have a favorable toxicity profile than chemotherapy or targeted therapies offering the promise of durable clinical benefit, albeit only for a minority of patients [6,7,8,9,10]. Programmed death-ligand 1 (PD-L1) expression has been studied in lung cancer, bladder cancer, RCC and breast cancer in order to define its putative prognostic and predictive value even though several limitations have been highlighted [11,12,13,14]. To date the PD-L1 expression is available in clinical practice only for the choice of treatment of NSCLC [15,16,17,18,19,20] and breast cancer patients [21,22,23,24]

Objectives
Methods
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call