scholarly journals Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

2018 ◽  
Author(s):  
An-Shun Tai ◽  
Chien-Hua Peng ◽  
Shih-Chi Peng ◽  
Wen-Ping Hsieh
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Tumor Evolution ◽  
Depth Information ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Copy Number Aberrations

AbstractMultistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.

scholarly journals DeCiFering the Elusive Cancer Cell Fraction in Tumor Heterogeneity and Evolution

2021 ◽  
Author(s):  
Gryte Satas ◽  
Simone Zaccaria ◽  
Mohammed El-Kebir ◽  
Benjamin J. Raphael
Keyword(s):  
Phylogenetic Analysis ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Cell Fraction ◽  
Tumor Evolution ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Cancer Cell Fraction

AbstractMost tumors are heterogeneous mixtures of normal cells and cancer cells, with individual cancer cells distinguished by somatic mutations that accumulated during the evolution of the tumor. The fundamental quantity used to measure tumor heterogeneity from somatic single-nucleotide variants (SNVs) is the Cancer Cell Fraction (CCF), or proportion of cancer cells that contain the SNV. However, in tumors containing copy-number aberrations (CNAs) – e.g. most solid tumors – the estimation of CCFs from DNA sequencing data is challenging because a CNA may alter the mutation multiplicity, or number of copies of an SNV. Existing methods to estimate CCFs rely on the restrictive Constant Mutation Multiplicity (CMM) assumption that the mutation multiplicity is constant across all tumor cells containing the mutation. However, the CMM assumption is commonly violated in tumors containing CNAs, and thus CCFs computed under the CMM assumption may yield unrealistic conclusions about tumor heterogeneity and evolution. The CCF also has a second limitation for phylogenetic analysis: the CCF measures the presence of a mutation at the present time, but SNVs may be lost during the evolution of a tumor due to deletions of chromosomal segments. Thus, SNVs that co-occur on the same phylogenetic branch may have different CCFs.In this work, we address these limitations of the CCF in two ways. First, we show how to compute the CCF of an SNV under a less restrictive and more realistic assumption called the Single Split Copy Number (SSCN) assumption. Second, we introduce a novel statistic, the descendant cell fraction (DCF), that quantifies both the prevalence of an SNV and the past evolutionary history of SNVs under an evolutionary model that allows for mutation losses. That is, SNVs that co-occur on the same phylogenetic branch will have the same DCF. We implement these ideas in an algorithm named DeCiFer. DeCiFer computes the DCFs of SNVs from read counts and copy-number proportions and also infers clusters of mutations that are suitable for phylogenetic analysis. We show that DeCiFer clusters SNVs more accurately than existing methods on simulated data containing mutation losses. We apply DeCiFer to sequencing data from 49 metastatic prostate cancer samples and show that DeCiFer produces more parsimonious and reasonable reconstructions of tumor evolution compared to previous approaches. Thus, DeCiFer enables more accurate quantification of intra-tumor heterogeneity and improves downstream inference of tumor evolution.Code availabilitySoftware is available at https://github.com/raphael-group/decifer

scholarly journals Tumor Microenvironment and Immunotherapy Response in Head and Neck Cancer

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3377
Author(s):  
Panagiota Economopoulou ◽  
Ioannis Kotsantis ◽  
Amanda Psyrri
Keyword(s):  
Head And Neck Cancer ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Neck Cancer ◽  
Immune Escape ◽  
Treatment Resistance ◽  
Inflammatory Cells ◽  
Tumor Evolution ◽  
Complex Interactions ◽  
Cellular Components

The tumor microenvironment (TME) encompasses cellular and non-cellular components which play an important role in tumor evolution, invasion, and metastasis. A complicated interplay between tumor cells and adjacent TME cells, such as stromal cells, immune cells, inflammatory cells, and cytokines, leads to severe immunosuppression and the proliferation of cancer cells in several solid tumors. An immunosuppressive TME has a significant impact on treatment resistance and may guide response to immunotherapy. In head and neck cancer (HNC), immunotherapeutic drugs have been incorporated in everyday clinical practice. However, despite an exceptional rate of durable responses, only a low percentage of patients respond. In this review, we will focus on the complex interactions occurring in this dynamic system, the TME, which orchestrate key events that lead to tumor progression, immune escape, and resistance. Furthermore, we will summarize current clinical trials that depict the TME as a potential therapeutic target for improved patient selection.

scholarly journals Characterization of a head and neck cancer-derived cell line panel confirms the distinct TP53-proficient copy number-silent subclass

Oral Oncology ◽  
2019 ◽  
Vol 98 ◽  
pp. 53-61 ◽  
Author(s):  
Anne M. van Harten ◽  
Jos B. Poell ◽  
Marijke Buijze ◽  
Arjen Brink ◽  
Susanne I. Wells ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Cell Line ◽  
Neck Cancer ◽  
Copy Number ◽  
Cell Line Panel

Analysis of gene copy number changes in head and neck cancer

2018 ◽  
Vol 43 (4) ◽  
pp. 1004-1009 ◽  
Author(s):  
E. Baltaci ◽  
E. Karaman ◽  
N. Dalay ◽  
N. Buyru
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Copy Number ◽  
Gene Copy Number ◽  
Gene Copy ◽  
Copy Number Changes

Neoantigen-based vaccination as a practical measure for head and neck cancer treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e18528-e18528
Author(s):  
Xiao-bin Zheng ◽  
Chuan-ben Chen ◽  
Yu Chen ◽  
Shiguang Hao ◽  
Liu Jun ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Cancer Treatment ◽  
Head And Neck ◽  
Neck Cancer ◽  
Hla Typing ◽  
Sequencing Data ◽  
Coding Regions ◽  
Standard Procedures ◽  
Potential Vaccine ◽  
Practical Measure

e18528 Background: The view that neoantigens serve as potential vaccine targets has arisen in the last decade. Clinical and computational efforts have been done to increase the practicality of its application in real world. With these advances, we conducted a retrospective study on a Chinese population to explore the clinical feasibility of neoantigen-based vaccines for head and neck cancer treatment. Methods: Tumor and normal samples were profiled using a 1021-gene panel. Sequencing data were pre-analyzed according to our in-house standard procedures. Class I HLA typing was completed using OptiType v1.0. Curated somatic mutations in coding regions (SNVs and non-frameshift Indels with an allele frequency ≥ 5%) were collected and altered peptides produced by these mutations were analyzed using NetMHCpan v4.0. Peptides with an IC50 < 500 nM were considered potential binders, and especially, those with an IC50 < 50 nM were considered strong binders. An altered peptide was considered a neoantigen if IC50 altered is < IC50 wildtype. Results: We analyzed a total of 243 patients and detected 114 unique HLA alleles. By carrier percentage, the top three alleles are C*01:02 (44%), B*46:01 (36%), and A*11:01 (33%). In total, 743 mutations were deemed eligible for neoantigen prediction and 223 unique neoantigens were found. Of these neoantigens, 67 (carried by 21% of patients) were strong binders, among which 26 (carried by 9% patients) exhibited a great fold change (≥ 5 folds) of binding affinity. Moreover, the neoantigens in these patients are unique, as only two neoantigens were shared. A search for shared neoantigens revealed a combination of mutation PIK3CA p.E542K and HLA A*11:01, which was detected in 0.54% of all patients. Additionally, 43.6% (106/243) of patients were diagnosed with nasopharyngeal carcinoma, among whom 42% (44/106) possessed predicted neoantigens, including 15 patients with strong-binder neoantigens. Conclusions: (1) Neoantigen-based vaccination is a practical measure to treat patients with head and neck cancer, as indicated by the percentage of patients harboring strong-binder neoantigens. (2) Off-the-shelf neoantigen vaccines may not be practical, given the result that the most common combination of a neoantigen-producing mutation and the corresponding HLA was only found in 0.54% of all patients.

Mitochondrial DNA copy number is associated with diagnosis and prognosis of head and neck cancer

Biomarkers ◽  
2014 ◽  
Vol 19 (4) ◽  
pp. 269-274 ◽  
Author(s):  
Frank Cheau-Feng Lin ◽  
Ya-Chung Jeng ◽  
Tzu-Yun Huang ◽  
Ching-Shiang Chi ◽  
Ming-Chih Chou ◽  
...  
Keyword(s):  
Mitochondrial Dna ◽  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Copy Number ◽  
Dna Copy Number ◽  
Diagnosis And Prognosis ◽  
Mitochondrial Dna Copy Number

Influence of Sociodemographic Characteristics and Inflammation-Related Gene Variants on the Comfort Level of Caregivers of Patients With Head and Neck Cancer

2021 ◽  
pp. 089801012110467
Author(s):  
Daniel Paixão Pequeno ◽  
Elisângela Godoi Viaro ◽  
Juliana Carron ◽  
Diego Rodrigues Silva ◽  
Karla Cristina Gaspar ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Smoking Habit ◽  
Comfort Level ◽  
Sociodemographic Characteristics ◽  
Single Nucleotide Variants ◽  
Comfort Levels ◽  
The Relationship

Background: Sociodemographic characteristics and inflammatory cytokines, such as interleukin (IL)-1β, IL-1 cytokine receptor type 2 (IL1R2), IL-6, and triggering receptor expressed on myeloid cells like 2 (TREML2), may influence psychological disorders, including discomfort. Single-nucleotide variants (SNVs) determine individual differences for the modulation of cytokines and indicate that genetics may also influence the comfort levels. However, the relationship between sociodemographic characteristics, holistic comfort, and the roles played by IL1B rs16944, IL1R2 rs4141134, IL6 rs1800795, and TREML2 rs3747742 SNVs on the comfort levels of family caregivers (FCGs) of head and neck cancer (HNC) patients in palliative care (PC) is unknown. Thus, its investigation consisted in the aim of the present study. Methods: A questionnaire was applied to obtain sociodemographic information on 95 FCGs. The genotypes were identified using TaqMan assays. The Holistic Comfort Questionnaire for the Caregiver, which consists of 49 questions, was used to measure comfort levels. Differences between groups were assessed by the t test and linear regression. Results: Employed FCGs ( p  = .04), those youngest ( p  = .04), smokers ( p  = .04), and those with IL1R2 GA or AA genotypes ( p  = .03) presented lower comfort regarding the overall, environmental, sociocultural, and psychospiritual domains, respectively. Conclusions: Employment status, smoking habit, young age, and SNV IL1R2 rs4141134 could influence the comfort levels of FCGs of patients with HNC in PC.

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