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.

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.

Inclusion Criteria:

• Age above 20 years old

Exclusion Criteria:

• Age below 20 years old

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