WGA in Platinum-refractory HNSCC Underwent Nivolumab

April 24, 2019 updated by: Chang Gung Memorial Hospital

Using Whole-Genome Analysis on Cancer Tissue of Patients With Platinum-refractory Head and Neck Squamous Cell Carcinoma Who Underwent Nivolumab to Precisely Predict Responders: An Observational Biomarker Study

To choose a subgroup who could clearly benefit from Nivolumab, we are proposing a prospective observational study. Whole-genome study (WGS) analysis will be performed on archived cancer tissues from patients who were (1) cisplatin-refractory and subsequently (2) received Nivolumab (at least 4 doses) and (3) had completed imaging response evaluation at 3-4 month after Nivolumab. The estimated sample size was designed to be 80, including 20 responders and 60 non-responders (1:3 design) after Nivolumab alone at a dosage of 2-3mg/kg every 2 weeks (+/- 7 days could be allowed), given the minimal requirement of statistical significance. The specific bio-signature(s) found in this prospective observational study could possibly greatly contribute to precision immuno-oncology medicine, especially Nivolumab.

Study Overview

Status

Unknown

Conditions

Detailed Description

1-1 PD-1 pathway as a novel and effective pathway in cancer treatment The programmed death 1 (PD-1) receptor, which is expressed on activated T cells, is engaged by ligands PD-L1 and PD-L2, which are expressed by tumor cells and infiltrating immune cells 1. Tumor PD-L1 expression is commonly seen in a broad spectrum of cancers, and the interaction between PD-1 and PD-L1, PD-L2 ligands inhibits T-cell activation and promotes tumor immune escape (i.e., the mechanism by which tumor cells escape recognition and elimination by the immune system) 2, 3. Immune checkpoint inhibitors (ICI) developed on the basis of the above mechanism have shown their success with good treatment efficacy in patients with melanoma4-8, lung cancer3, 7, 9-21, and renal cell carcinoma12, 22-24 to date. Owing to the mechanism of targeting probably very common pathways of cancer (PD-1 pathway), ICIs seems to be equally effective in a wide range of cancers with a similar response rate of 20-30% 25, which indicates a common immune defect on PD-1 pathway exists amongst the various type of cancer.

1-2 Subpopulation selection could possibly contribute better efficacy Recently, two PD1 inhibitors, Nivolumab and Pembrolizumab, showed their different results in large-scale clinical trials 11, 14. Subpopulation selection strategies in these 2 trials have been widely considered as one of the major reasons. A precise selection of patients with the best response is critically warranted and a truly unmet need, given PD-L1 cannot clearly stratify patients who will benefit most from Nivolumab.

1-3 No available biomarkers to predict severe irAEs is an unmet need Another problem is that all ICIs have occasionally severe and sometimes life-threatening immune-related adverse events (irAEs). At present, no good biomarker is available to predict such irAEs. It is imperative to identify the biomarkers that can predict the risk of severe irAEs 25.

1-4 NGS technology could probably provide solutions to the above 2 problems Next-generation sequencing (NGS) technology has been introduced in recent years (Fig. 1), and allows the analysis of genomes, including those representing disease states 26, 27. Generally speaking, there are three NGS approaches to improve diagnostics for cancer gene mutations: (1) targeted enrichment of a set of genes (gene panel), (2) whole-exome sequencing (WES), and (3) whole-genome sequencing (WGS) 28. When comparing the three options, it is clear that-theoretically-WGS is the superior approach as it will produce the most complete data set on an individual's genome (Table 1)28. A recent study 29 concluded that WGS offers significant advantages of (a) more coverage of the exome, (b) detection of intronic variants, and (c) calling of all structural variants, including single exon deletions; however, the costs and testing time limited the routine use of WGS. In brief, WGS for cancer patients before treatment could most possibly help to select patients with specific signature(s) to receive specific treatment in a manner of precision medicine 30-37.

1-5 Host immunity (inherent, host) and Cancer (somatic, acquired) interaction could only be seen in whole genome analysis By means of WGS, we could approach the question of how to identify the responders from Nivolumab in the direction of "cancer part (somatic)" conventionally. In another way, we could also approach this question by "host part", which is also the advantages of WGS testing.

In WGS analysis, we could use genome-wide association studies (GWAS) analysis to compare common genetic variants in large numbers of affected cases to those in unaffected controls to determine whether an association with disease exists 38, 39. GWAS have been made possible by the identification of millions of single nucleotide polymorphisms (SNPs) across the human genome and the realization that a subset of these SNPs can capture ("tag") common genetic variation via linkage disequilibrium 40. By SNP analysis in WGS, we proposed to find genotypic characteristics to predict which patients could more possibly respond to Nivolumab.

In further hypothesis, we could analyze the upstream and downstream of the B cell signaling pathway in addition to T cell pathway. Currently, almost all studies addressed the T functional analysis when investigating PD-1-PD-L1 inhibitors. We hypothesize that B cell or even Natural killer's pathway could play some roles to T cell activation to help us to predict the response of immunotherapy.

1-6 Current evidence of NGS for stratification before ICIs Currently, there are only very few data available carrying out a design using the WGS method. In 2016, Kimura et al. 25 from the U.S.A used targeted panel NGS to prove a strong T cell response and further suggested to exclude of patients with subclinical autoimmune disease is very important for treatment with immune checkpoint inhibitors 25. Yaghmour et al. (2016) also used a panel NGS (Foundation One panel) and found that the use of immune checkpoint blockade in tumors with higher mutational load was associated with improved OS. They further suggested that the evaluation of tumor genomes may be predictive of immunotherapy benefit 41. Voss et al. (2016) presented their preliminary data using WES and RNA-Seq in patients with RCC in ASCO. They found that somatic mutations, particularly those causing tumor neoantigens, and the counterbalance between molecular immune compartments may be determinants of treatment benefit from Nivolumab and warrant future study 42. Another team (de Velasco et al.) also found that both DNA- and RNA-level data may be relevant for explaining clinical benefit from nivolumab in mRCC. In contrast with results from other tumor types, responders to nivolumab did not have more mutated tumors, though immune-related gene expression may be related to response 43. However, their sample sizes of study, retrospective in nature, study scale, and NGS methods are all relatively small.

Fig. 1. Recent advances of genetic analysis.44

Fig 2. The differences between several methods of NGS analysis. 45

1-7 The purpose of the study and brief design To choose a subgroup who could clearly benefit from Nivolumab, we are proposing a prospective observational study. Whole-genome study (WGS) analysis will be performed on archived cancer tissues from patients who were (1) cisplatin-refractory and subsequently (2) received Nivolumab (at least 4 doses) and (3) had completed imaging response evaluation at 3-4 month after Nivolumab. The estimated sample size was designed to be 80, including 20 responders and 60 non-responders (1:3 design) after Nivolumab alone at a dosage of 2-3mg/kg every 2 weeks (+/- 7 days could be allowed), given the minimal requirement of statistical significance. The specific bio-signature(s) found in this prospective observational study could possibly greatly contribute to precision immuno-oncology medicine, especially Nivolumab.

Study Type

Observational

Enrollment (Anticipated)

80

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

      • Taoyuan, Taiwan, 333
        • Recruiting
        • Chang Gung Memorial Hospital
        • Principal Investigator:
          • Chia-Hsun Hsieh, M.D., M.S
        • Sub-Investigator:
          • Min-Hsien Wu, PhD.
        • Sub-Investigator:
          • Hung-Ming Wang, M.D.
        • Sub-Investigator:
          • Siang-Fu Huang, M.D.,PhD.
        • Sub-Investigator:
          • Yonɡ-Chanɡ Lin, M.D.

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Retrospectively analyze WGS information from cancer tissues from HNSCC patients have used Nivolumab

Description

Inclusion Criteria:

  • Age above 20 years old

Exclusion Criteria:

  • Age below 20 years old

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
HNSCC patients have used Nivolumab
Retrospectively analyze WGS information from cancer tissues from HNSCC patients have used Nivolumab
Using Whole-Genome Analysis on Cancer Tissue of Patients with Platinum-refractory Head and Neck Squamous cell carcinoma Who Underwent Nivolumab to Precisely Predict Responders: An Observational Biomarker Study

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Prediction rate of Nivolumab Response
Time Frame: 2-4 months
Prediction rate of Nivolumab Response
2-4 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Adverse effects (types and grading) of Nivolumab
Time Frame: 2-4 months
Adverse effects (types and grading) of Nivolumab
2-4 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Study Chair: Tsang-Tang Hsieh, M.D., Chang Gung Memorial Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

April 1, 2018

Primary Completion (Anticipated)

March 31, 2021

Study Completion (Anticipated)

March 31, 2022

Study Registration Dates

First Submitted

April 15, 2019

First Submitted That Met QC Criteria

April 15, 2019

First Posted (Actual)

April 17, 2019

Study Record Updates

Last Update Posted (Actual)

April 25, 2019

Last Update Submitted That Met QC Criteria

April 24, 2019

Last Verified

July 1, 2018

More Information

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on HNSCC

Clinical Trials on HNSCC patients have used Nivolumab

3
Subscribe