Identification of an Immune Single Cell Transcriptomic Profile of Responder and Non-responder Hepatocellular Carcinoma Patients Treated With Immune-checkpoint Inhibitors

Fondazione IRCCS Policlinico San Matteo di Pavia20 enrolled

Overview

The study aims to analyze blood samples from patients with advanced hepatocellular carcinoma who are receiving systemic treatment with immunotherapy. The objective is to determine whether treatment exposure leads to changes in the transcriptomic patterns of peripheral blood mononuclear cells (PBMCs), if these changes are associated with treatment response, and whether certain pre-treatment transcriptomic signatures can predict response to treatment. As an exploratory objective, PBMCs derived from patients exposed to immune checkpoint inhibitors will be co-cultured with their paired tumor cells in organoid cultures. This aims to assess whether these preclinical 3D models correlate with clinical outcomes.

The primary pivotal objective of the study is to analyse the single cell transcriptome of peripheral blood mononuclear cells (PBMCs) in patients with HCC treated with immunotherapy to define if treatment exposure determines transcriptomic pattern changes and if some of these changes are associated with treatment response. The secondary objective of the study is to investigate if some pre-treatment transcriptome signature of PBMCs is predictive of response and long-lasting response to treatment. As an exploratory objective, the study investigators will analyse the interaction between patients' peripheral immune cells previously exposed to immune check-point inhibitors and their paired tumour cells in the organoid cultures.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Advanced HCC Treated by Systemic Immunotherapy

Eligibility

Sex: ALLMin age: 18 YearsMax age: 90 Years

Medical Language ↔ Plain English

Inclusion Criteria: 1. diagnosis of advanced HCC treated with atezolizumab plus bevacizumab or tremelimumab single dose plus durvalumab (STRIDE regimen) as first-line treament 2. age ≥18 and \<90 years at time of signing informed consent 3. Signed Informed Consent Form Exclusion Criteria: 1. Life expectancy of \<12 months due to concomitant diseases 2. Active or history of autoimmune disease or immune deficiency on inflammatory chronic diseases 3. Ongoing drug abuse 4. History of malignancy other than HCC within 3 years prior to study entry with the following exception: 1. Completely resected malignancies with a negligible risk of metastasis or death (e.g., 5-year OS rate 90%) and without evidence of recurrence for \> 3 years prior to study entry 2. adequately treated non-melanoma skin carcinoma or lentigo maligna without evidence of metastases. 3. adequately treated carcinoma in situ of the cervix without evidence of recurrence 4. localised prostate cancer 5. adequately treated non invasive or in situ urothelial cancers 5. evidence or history of positive HIV test 6. inability to comply with the study protocol, in the investigator's judgment

Outcomes

Primary Outcomes

Analysis of the single cell profiling of peripheral blood mononuclear cells in patients with HCC treated with immunotherapy pre-therapy (T0) and the 3 months post-therapy (T3) to define if a difference between the two time points exists.

The single cell profiling of peripheral blood mononuclear cells in patients with HCC treated with immunotherapy will be analised at two type points: before starting therapy(T0), and the 3 months post-therapy (T3). The difference of single cell profiling of the two paired time-points will be analysed.

Time frame: From enrollment untill 3 months after treatment start, (up to 120 days from study inclusion)

Secondary Outcomes

Correlation between transcriptome signature at baseline and treatment outcomes.

To define if there is a correlation between baseline transcriptome signatures and treatment outcomes (duration of response, median progression-free survival, median overall survival)

Time frame: From enrollment to the time of best response to treatment, up to 24 months from enrollement

Correlation between baseline gene clusters and treatment responses

To identify baseline gene clusters that correlats with higher respose rates

Time frame: From enrollment to the time of best response, up to 24 months from enrollment