Patients with histologically confirmed diagnosis of unresectable locally advanced or metastatic RCC who were treated with a first line immunotherapy-based combination treatment at Pisa oncology centre between June 2019 and June 2023 were retrospectively selected. All enrolled patients were treated according to current guidelines of European Society of Medical Oncology (ESMO) [1]. Archival formalin-fixed, paraffin-embedded (FFPE) samples of primary tumor or metastatic site obtained at diagnosis were retrieved from the pathology department.

The main inclusion criteria were: histological diagnosis of RCC; presence of advanced or metastatic (synchronous or metachronous) disease; the availability of sufficient histological material to perform an adequate IHC evaluation of TME; at least one cycle of a first-line combination treatment (including dual immune checkpoint blockade or ICI in combination with a TKI); at least one disease assessment to evaluate response to first-line therapy. In case of metachronous metastatic disease, histological material from a maximum of 3 months before the diagnosis of metastatic stage was required to be included. Patients without clear cell component were also included. A dedicated pathologist assessed the adequacy of material from FFPE tumor blocks.

For each patient, pathological data (stage at diagnosis, histology of RCC, nucleolar grading, presence of sarcomatoid features) and clinical data (previous nephrectomy, performance status, IMDC risk score, sites of metastasis) have been collected. In addition, data related to first-line immunotherapy-based treatment (type of combination therapy, best overall response and objective response rate-ORR, progression-free survival-PFS, overall survival-OS) have been recorded.

All information regarding human material was managed using anonymous codes and all samples were handled in compliance with the Declaration of Helsinki.

A pathological assessment was performed on 5 µm sections from tumor samples, evaluating immunohistochemical expression of selected markers representative of tumor cell (TC) and immune cell (IC) population; a quantitative analysis of the expression of each marker has been reported. The number of positive cells was determined by scoring a minimum of 10 high-power fields (magnification, 40×) and counting the number of immunoreactive cells out of the total epithelial cells analyzed in each field of view.

Object counting was performed using the automatic image analysis tool of the NIS Elements BR digital analysis system (NIS Elements BR, Basic Research, Vers. 5.20 Nikon Europe B.V., Stroombaan 14, Amstelveen, Netherlands) which allows the operator to create, through thresholds based on intensity values, binary levels able to recognize the different elements to be calculated. After having selected the high-power field on the optic microscope, the “auto-measurement” tool of the software calculated the number of objects in the area following the set-up values. The automated system detected the similar objects on the image and highlighted them by colour. The results were exported as an excel file containing a table that shows parameters such as the total area (e.g. 43,334,01 μm2 for each high-power field), the surface fraction and the number of detected objects for each evaluated field. Moreover, NIS-Elements BR calculated the basic statistics (e.g. mean value). Having carried out the quantitative analysis using the described software has made the evaluation operator-independent, generating a reliable and reproducible methodology.

The qualitative detection of PD-L1 (CD274) was assessed using Ventana PD-L1 (SP263) assay; the expression of PD-L1 in both TCs and tumor-infiltrating ICs was determined and was reported using combined positive score (CPS).

Immunophenotypic study of TME included assessment of expression of CD8+ and CD4+ T cell infiltration and the relative ratio. Macrophage population was assessed through IHC determination of CD163, a scavenger receptor that is highly expressed in TAMs with M2-like phenotype; this subgroup of macrophages is involved in downregulation of T cell function [15]. In addition, expression of CD80, generally considered a typical marker of activated macrophages with M1 features (with antitumor activity and involved in restoring an immune responsive microenvironment), was evaluated [16].

Descriptive statistics were provided as frequency (rate) for categorical data and as median value and ranges for continuous variables. The chi-square test (or the Fisher’s exact test, when appropriate) was used to compare categorical data, while the Student’s t test and the Mann–Whitney test (or the Kruskal–Wallis test) were performed to compare means and medians of continuous data, respectively.

Survival times were calculated using the Kaplan–Meier method; Cox regression analysis was performed to find difference in clinical outcome. Statistical significance was defined as p < 0.05.

ORR was defined as the percentage of patients who achieve a response, which could either be complete response or partial response according to RECIST, version 1.1. PFS was defined as the time from the beginning of first-line therapy to the development of disease progression or death for any cause, whereas OS was calculated as the time from the beginning of first-line therapy to death for any cause or last follow-up.

Selected TME markers were evaluated according to the median value and interquartile range (IQR); the receiver operating curves (ROCs) method was performed to find reliable cut-off value for each marker. In case a reliable value could not be determined via ROCs, an arbitrary value (coinciding with the median value) was chosen for each marker and was used to calculate PFS and OS, comparing as two different groups.

Statistical analyses were performed using IBM® SPSS® Statistics version 26.0 (IBM Corp., Armonk, NY, USA).