Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Editorial Policies
    • Subscribers
    • Advertisers
    • Editorial Board
    • Special Issues
  • Journal Metrics
  • Other Publications
    • In Vivo
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
    • 2008 Nobel Laureates
  • About Us
    • General Policy
    • Contact
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Genomics & Proteomics

User menu

  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Anticancer Research
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Genomics & Proteomics
  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Anticancer Research

Advanced Search

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Editorial Policies
    • Subscribers
    • Advertisers
    • Editorial Board
    • Special Issues
  • Journal Metrics
  • Other Publications
    • In Vivo
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
    • 2008 Nobel Laureates
  • About Us
    • General Policy
    • Contact
  • Visit us on Facebook
  • Follow us on Linkedin
Research ArticleClinical Studies
Open Access

Immunological and Genetic Characterization of Patients With Head and Neck Cancer who Developed Recurrence

KAZUAKI YASUI, RYOTA KONDOU, HARUO MIYATA, AKIRA IIZUKA, TADASHI ASHIZAWA, TAKESHI NAGASHIMA, KEIICHI OHSHIMA, KENICHI URAKAMI, KOJI MURAMATSU, TAKASHI SUGINO, KEN YAMAGUCHI, HIROFUMI OGAWA, TSUYOSHI ONOE, HIDEYUKI HARADA, HIROFUMI ASAKURA, SHIGEYUKI MURAYAMA, TETSUO NISHIMURA, SEIYA GOTO, SHINICHI OKADA, TAKASHI MUKAIGAWA, SATOSHI HAMAUCHI, TOMOYA YOKOTA, YUSUKE ONOZAWA and YASUTO AKIYAMA
Anticancer Research September 2022, 42 (9) 4417-4428; DOI: https://doi.org/10.21873/anticanres.15942
KAZUAKI YASUI
1Immunotherapy Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
RYOTA KONDOU
1Immunotherapy Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
HARUO MIYATA
1Immunotherapy Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
AKIRA IIZUKA
1Immunotherapy Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TADASHI ASHIZAWA
1Immunotherapy Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TAKESHI NAGASHIMA
3Cancer Diagnostic Research Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
4SRL Inc., Tokyo, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
KEIICHI OHSHIMA
5Medical Genetics Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
KENICHI URAKAMI
3Cancer Diagnostic Research Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
KOJI MURAMATSU
6Division of Pathology, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TAKASHI SUGINO
6Division of Pathology, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
KEN YAMAGUCHI
7Office of the President, Shizuoka Cancer Center, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
HIROFUMI OGAWA
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TSUYOSHI ONOE
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
HIDEYUKI HARADA
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
HIROFUMI ASAKURA
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SHIGEYUKI MURAYAMA
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TETSUO NISHIMURA
2Radiation and Proton Therapy Center, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SEIYA GOTO
8Division of Head and Neck Surgery, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SHINICHI OKADA
8Division of Head and Neck Surgery, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TAKASHI MUKAIGAWA
8Division of Head and Neck Surgery, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SATOSHI HAMAUCHI
9Division of Gastrointestinal Oncology, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
TOMOYA YOKOTA
9Division of Gastrointestinal Oncology, Shizuoka Cancer Center Hospital, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
YUSUKE ONOZAWA
10Division of Clinical Oncology, Shizuoka Cancer Center Hospital, Shizuoka, Japan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
YASUTO AKIYAMA
1Immunotherapy Division, Shizuoka Cancer Center Research Institute, Shizuoka, Japan;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: y.akiyama{at}scchr.jp
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Background/Aim: The recurrence rate of head and neck squamous cell carcinoma (HNSCC) remains high; thus the control of recurrence is a clinical problem to be challenged. To clarify the precise mechanism, specific immunological biomarkers responsible for recurrence were investigated. Patients and Methods: The expression levels of immune response-associated and Shizuoka Cancer Center 820 cancer-associated genes, and genetic mutations from whole-exome sequencing were compared between HNSCC patients who developed recurrence (n=8) and HNSCC patients who did not develop recurrence (n=19) using a volcano plot analysis. Cytokine and epithelial-mesenchymal transition marker genes were analyzed using quantitative PCR. Tumor-infiltrating lymphocytes, immune checkpoint molecules, and human papilloma virus status were investigated using immunohistochemistry (IHC). Results: Twenty-seven evaluable patients with HNSCCs received radiation therapy after surgery. Recurrence was identified in 8 patients. TP53 mutations tended to be higher in patients who developed recurrence than in those who did not develop recurrence (75% vs. 31.6%). Gene expression profiling showed the down-regulation of T cell activation genes (ICOS, CD69 and CD83) and the upregulation of the ERBB4, EGFR, VEGF, HIF1A, TGFB1, TWIST1, IL-8, and PAX7 genes, which suggested the activation of the TP53 mutation-TGF-β1-PAX7 pathway and epithelial-mesenchymal transition. Additionally, IHC indicated a tendency toward a reduction in T cell accumulation and an increase in M2-type macrophage infiltration in tumors that recurred. Conclusion: A TP53 mutation-mediated immune-suppressive state in the tumor microenvironment and TGF-β1-PAX7-mediated EMT might contribute to the promotion of recurrence in patients with HNSCC after postoperative radiotherapy.

Key Words:
  • Tumor microenvironment (TME)
  • epithelial-mesenchymal transition
  • tumor-infiltrating lymphocytes
  • human papillomavirus
  • TP53 mutation-TGF-β1-PAX7 pathway

Head and neck squamous cell carcinoma (HNSCC) is a common type of cancer; however, a reduction in the rate of its recurrence remains challenging; the 5-year survival rate of patients with HNSCCs is reported to be only 50-60% (1, 2). The recurrence rate is high, approximately 30%, which indicates not only high mortality and difficulty in treatment, but also the genetic complexity affecting cancer progression (3). These observations might suggest that the aspect shifted from a single cancer cell to a complex cancer tissue, namely, the tumor microenvironment (TME) (4).

The TME comprises stromal (cancer-associated) fibroblasts, immune cells (T cells, macrophages etc.) and other supporting cells. Recently, along with recent advances in next-generation sequencing (NGS)-based single-cell RNA sequencing technology, immune landscape studies have been performed according to genetic classification of tumor-infiltrating lymphocytes (TILs), enabling the evaluation of the immunological status in the TME (5-7). These studies have elucidated the importance of mutations in the tumor-suppressor gene TP53 and human papillomavirus (HPV)-positive status in the clinical prognosis of patients with HNSCCs (8, 9).

TP53 mutations are the most frequently identified mutations in non-HPV HNSCCs, and its frequency in HNSCCs is approximately 50%. Additionally, a higher rate of TP53 mutations was recognized in recurrent HNSCCs after chemoradiotherapy (CRT) compared to patients with HNSCC who did not recur (10-12). Meanwhile, an HPV-positive status has been demonstrated to be a good prognostic factor in patients with HNSCC (9, 13). Importantly, oncogenic HPV16 and other factors have recently been described as apparent etiologies for oropharyngeal cancer in young non-smoking patients (14). According to these observations, HPV status and smoking history define three groups with distinct survival outcomes: low risk (HPV-positive and <10 pack-years), intermediate risk (HPV-positive and >10 pack-years), and high risk (HPV-negative) (15).

In the present study, we focused on patients with HNSCCs who subsequently developed recurrence after postoperative radiotherapy, who showed a high frequency of TP53 mutation and an HPV-negative status and were categorized as the high-risk group. Eventually, we characterized genetic and immunological features using gene expression profiling (GEP) and whole exome sequencing (WES) analysis of these patients to identify novel prognostic biomarkers.

Patients and Methods

Patient registration. Shizuoka Cancer Center (SCC) has been conducting the comprehensive human genome analysis Project HOPE (High-tech Omics-based Patient Evaluation) using WES and GEP (16, 17). Informed consent was obtained from all registered cancer patients. The study was approved by the Institutional Review Board of Shizuoka Cancer Center, Japan (Authorization Number: 25–33). All experimental protocols using clinical samples were carried out in accordance with the Helsinki Declaration and the Ethical Guidelines for Human Genome and Genetic Analysis Research. Thirty patients with HNSCC were registered in Project HOPE from 2014 to 2015 and received radiotherapy after surgical resection. Three patients were not evaluable due to insufficient tumor cell content in formalin-fixed, paraffin-embedded (FFPE) samples and were not included in the analysis. The median follow-up time for overall survival was 47.8 months (range, 7.5-63.1 months).

DNA microarray-based GEP and WES using next-generation sequencing and Sanger sequencing. The method used to perform GEP and WES analyses was described previously (17). Briefly, in GFP analysis, the ratio of the expression levels in the tumor tissue versus the normal tissue was calculated from the normalized values. In WES analysis, the variants called by the variant caller were filtered and those mutations that were identified in tumor samples only were identified as somatic mutations.

Determinations of tumor mutation burden (TMB) and copy number variation (CNV) number. Tumor mutation burden (TMB) represents the number of somatic mutations per megabase and the methods for determining of TMB and copy number variation (CNV) number were described previously (18).

Immune response-associated genes and SCC820 panel gene expression profiling. The lists of genes in the 204 immune response-associated gene panel and the SCC820 cancer-associated panel were shown previously (17, 19). Briefly, the expression levels of 204 immune response-associated genes and the SCC820 cancer-associated genes of HNSCCs were compared between patients who developed recurrence and patients who did not develop recurrence with a volcano plot analysis. The expression-altered (more than 2-fold) genes among the 204 immune response-associated genes and the SCC820 cancer-associated gene panel were identified.

Real-time PCR analysis. Real-time PCR analysis of the apoptosis-related, cytokine and EMT-associated genes was performed using the QuantStudio 12K Flex Real Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA) as described previously (20). Additionally, in the cancer metabolomic study, real-time PCR using primers targeting glycolytic enzyme genes, such as HK2, PDK1, PFKM, PGM1, and PKM, was performed. Total RNA was isolated from formalin-fixed paraffin-embedded (FFPE) head and neck cancer specimens using the High Pure RNA Paraffin Kit (Roche Diagnostics, Indianapolis, IN, USA).

Immunohistochemistry. For the tumor-infiltrating immune cells, antibodies against CD4 and CD8 (Thermo Fisher Scientific), FoxP3 (Abcam, Cambridge, UK), CD204 (Transgenic, Kobe, Japan), TGF-β1 (R and D Systems, Minneapolis, MN, USA), cytokeratin (AE1 and AE3, Nichirei Bio., Tokyo, Japan), IL-8 (Abcam), Granzyme B (Dako, Glostrup, Denmark), PD-L1 (Abcam) and PAX7 (Novus Biologicals, Centennial, CO, USA) were purchased and used for immunohistochemistry and immunofluorescence analyses. For the evaluation of HPV infection, an anti-human p16ink4a mouse monoclonal antibody (clone E6H4; Roche Diagnostics, Basel, Switzerland) was purchased. Positive staining of more than 70% of the area was diagnosed as positive according to Schache et al.’s report (21). To measure TIL numbers, 10 areas of tumor at a high magnification (×200) in each section stained with various antibodies were used and analyzed by two highly experienced pathologists.

For immunofluorescence staining, TGF-β1, cytokeratin, PAX7, IL-8 and CD204 staining was conducted using the Opal 4-color IHC kit (Perkin-Elmer, Waltham, MA, USA) and evaluated on a fluorescent Zeiss imager Z1 microscope (Carl Zeiss, Oberkochen, Germany).

T cell receptor gene repertoire analysis in head and neck tumors using human TCRα and TCRβ profiling kit. Total RNAs were isolated from 27 head and neck squamous tumors and applied to Switching Mechanisms at 5′ End of RNA Template (SMARTer™) human TCRα and TCRβ profiling kit (Clontech Laboratories, Mountain View, CA, USA) as described previously (22). TCR repertoire analysis was performed using MiTCR, software for T cell receptor sequencing data analysis (23).

Statistical analysis. The genes from the immune response-associated gene panel and SCC820 cancer-associated gene panel that were upregulated in patients who developed recurrence compared to patients who did not develop recurrence were identified using the volcano plot method. The statistical significance of the difference in the proportion of variables between recurrent patients and non-recurrent patients was calculated using an unpaired two-tailed t-test. Values with p<0.05 were considered significant. Data analysis was performed using GeneSpring GX software version 13.1.1 (Agilent Technologies, Santa Clara, CA, USA). For survival analysis, the association of PAX7 gene expression, driver mutations, TP53 mutation, disease recurrence and HPV status with overall survival was analyzed using Excel 2016. Specifically, PAX7 gene expression and the clinical data of HNSCC patients were downloaded from TCGA database. The overall survival was analyzed using the Kaplan–Meier method and the statistical significance of each parameter was evaluated using the log-rank test and a generalized Wilcoxon test.

Results

Clinical characteristics of HNSCC patients. The characteristics of 27 evaluable HNSCC patients are shown in Table I. There were 20 male and 7 female patients, and the mean age was 61 years (range, 26-83 years). The site of the primary tumor was the oral cavity in 12 patients, the hypopharynx in 6 patients, the oropharynx in 7 patients, and the larynx in 2 patients. According to the tumor-node-metastasis (TNM) 7th classification, one patient had stage II disease, two patients had stage III disease, and 24 patients had stage IV disease. Among 27 patients with HNSCC, eight patients developed recurrence (local and distal recurrence in 5 patients, distal recurrence only in 3 patients). HPV statuses were positive in seven patients. Radiotherapy or chemoradiotherapy was performed postoperatively. Concurrent chemoradiotherapy was administered to patients with high-risk features such as positive surgical margin or extranodal extension, and with good performance status. Chemotherapy regimens included weekly cisplatin (CDDP) at 40 mg/m2, triweekly CDDP at 80-100 mg/m2, or CDDP at 70 mg/m2 and 5-fluorouracil at 700 mg/m2. The median radiation dose was 60 Gy (range, 40-70 Gy).

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table I.

Characteristics of patients with head and neck squamous cell carcinoma.

Characterization of genetic features using WES and GEP analysis. The features of genetic mutations were compared between patients who developed recurrence and patients who did not develop recurrence (Table II). The total number of single-nucleotide variants (SNVs) was not different between the groups. Regarding driver mutations suggested by Vogelstein, the frequency of TP53 mutation was significantly higher in patients who developed recurrence than in patients who did not develop recurrence. However, the frequencies of other mutations were not different. In contrast, patients with HPV-positive tumors developed no recurrence and had no driver mutations, including TP53 mutations (Table II).

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table II.

Effect of driver mutation frequency and HPV status on the recurrence of head and neck cancer.

Expression profiling of immune response-associated and SCC820 panel genes in recurrent HNSCC. Volcano plot analysis showed one up-regulated and 10 down-regulated genes from the immune response-associated panel of genes (Figure 1A, Table III), and 18 up-regulated and five downregulated genes from the SCC820 cancer-associated panel of genes (Figure 1B, Table IV) in patients who developed recurrence. Briefly, T cell and dendritic cell-activating genes (CCL5, ICOS, CD69, and CD83) and the cyclin-dependent kinase inhibitor (CDKN)2A and CDKN2B genes were downregulated, while cancer-associated genes, such as PAX7, MAGEA1, TLX1 and ERBB4, were up-regulated in patients who developed recurrence.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Comparison of gene expression between the recurrence group and the no recurrence group after postoperative radiotherapy. (A) Immune response-associated genes and (B) cancer-associated SCC820 genes. Up-regulated or down-regulated genes with changes greater than 2-fold were identified using volcano plots with the Benjamini-Hochberg correction. The horizontal gray line represents a p-value of 0.05. The vertical gray lines show 2- and 0.5-fold changes in gene expression. The black and white squares represent the down-regulated and up-regulated genes, respectively.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table III.

Expression-altered genes of immune response-associated gene in recurrent head and neck cancer patients.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table IV.

Expression-altered genes of SCC820 cancer-associated genes in recurrent head and neck cancer patients.

Apoptosis and EMT marker gene expression measured using quantitative PCR. Quantitative PCR demonstrated that the expression of EMT-associated genes (COL1A2, HIF1A, IL-8, SNAIL2, TWIST1, TGFB1, and TGFB3) and glycolytic enzyme genes (HK2 and PDK1) was up-regulated in patients who developed recurrence (Figure 2). In contrast, the expression of CDKN2A was down-regulated. Other cancer signaling pathway genes (EGFR, VEGF, and CCND1) were also up-regulated. Based on the gene expression profiling data from the volcano plot analysis and quantitative PCR data, a scheme of differentially expressed genes in patients who developed recurrence was created and is shown in Figure 3; this schematic indicates specific mechanisms or pathways that might be associated with head and neck cancer metastasis and progression after postoperative radiotherapy.

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Apoptosis-related, cytokine and EMT-associated gene expression profiling using real-time PCR. Total RNA was isolated from formalin-fixed paraffin-embedded (FFPE) head and neck cancer specimens, and real-time PCR was performed using the QuantStudio 12K Flex Real Time PCR System. The open column shows nonrecurrent cases; the closed column shows recurrent cases. Each column represents the mean value of triplicate experiments.

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

Schematic of differentially expressed genes that could be associated with cancer metastasis in patients who developed recurrence. The up-regulated (EGFR, ERBB4, VEGF, TGFB1, PAX7, IL-8, SNAIL2, TWIST1, COL1A2, CLEC12B, etc.) and down-regulated genes (CDKN2A, CDKN2B, CD69, ICOS, CD83, etc.) might be associated with cancer metastasis, as determined from the gene profiling of immune response-associated and SCC820 panel genes, and real time PCR.

Association of PAX7-positive tumor cells with IL-8-producing tumor-associated macrophages using immunofluorescence staining. Immuno-fluorescence staining showed that TGF-β1 might be positive in tumor cells with PAX-7 expression and IL-8 was positively stained in CD204+ tumor-associated macrophages (Figure 4).

Figure 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 4.

Tumor cell and macrophage characterization using immunofluorescence staining (IFS). (A) IFS for cytokeratin (blue), TGF-β1 (green) and PAX7 (red) proteins and (B) IFS for cytokeratin (blue), IL-8 (green) and CD204 (red) using the Opal 4-color kit. The tumor sections were derived from the recurrent group (No. 21). The arrows in panel A show TGF-beta1+PAX7+ cancer cells and the arrows in panel B show CD204+IL-8+ macrophages. Magnification: ×400.

Tumor-infiltrating immune cell characterization and HPV status determination in HNSCCs using IHC. The number of CD8+ T cells and granzyme B+ cells tended to decrease in patients who subsequently developed recurrence (Figure 5). Specifically, the granzyme B+ cell number was significantly smaller in patients who developed recurrence than in those who did not. Additionally, CD204+ macrophage infiltration tended to be higher in patients who subsequently developed recurrence than in those who did not; however, it was not a significant difference (Figure 5B). In contrast, none of the patients with HPV-positive tumors developed recurrence, and they had a significantly greater number of infiltrating CD8+ T cells than patients with HPV-negative tumors.

Figure 5.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 5.

Tumor-infiltrating immune cell characterization using immunohistochemical (IHC) staining. (A) IHC staining against CD8, Granzyme B, Foxp3 and CD204 in the no recurrence group (No. 25) and the recurrence group (No. 17). Magnification; ×400. (B) Comparison of TIL numbers between the groups that developed or did not develop recurrence. Ten areas from the tumor section were stained with various antibodies and analyzed at high magnification (×200) using image analysis software. Positive cell counts per field were compared between the recurrence group and the no recurrence group. Each value shows the mean±SD. **p<0.01, *p<0.05, statistically significant.

Association of PAX7 gene expression or other parameters with cancer prognosis. PAX7 is a transcription factor and plays critical roles during fetal development and cancer growth. Interestingly, PAX7 is known to form a fusion gene with the FKHR gene in rhabdomyosarcomas associated with TP53 mutation (24). Therefore, we investigated the prognostic potential of PAX7 gene expression. Using survival data from TCGA database, the PAX7-high group showed a worse prognosis than the PAX7-low group (Figure 6A). Meanwhile, among our 27 HNSCC patients, the association of driver mutations, TP53 mutation, recurrence and HPV status with overall survival was analyzed. Patients who developed recurrence and who had driver gene-mutations showed worse prognosis than those who did not develop recurrence and who did not have driver gene mutations, and those who had TP53-mutations tended to have shorter survival times than patients without mutations. Meanwhile patients with HPV-positive tumors showed no recurrence, had no driver mutations, and exhibited a tendency toward better prognosis (Figure 6B).

Figure 6.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 6.

The effect of PAX7 gene expression and other parameters on the overall survival of patients with head and neck cancer. (A) PAX7 gene expression and clinical data of TCGA tumor samples downloaded from the UCSC Cancer Browser. Patients with head and neck cancer registered in the TCGA study were divided into high PAX7 expression (blue line) and low PAX7 expression (red line) groups by the median value. (B) The association of driver mutations, TP53 mutations, recurrence and HPV status with overall survival was analyzed. Recurrence (+) eight cases vs. recurrence (−) 19 cases, driver mutation (+) 15 cases vs. driver mutation (−) 12 cases, TP53 mutation (+) 12 cases vs. TP53 mutation (−) 15 cases, and HPV (+) seven cases vs. HPV (−) 20 cases. The prognostic significance of each parameter was evaluated using a Kaplan–Meier plot (log-rank test or generalized Wilcoxon test). **p<0.01, *p<0.05, statistically significant.

T cell receptor gene repertoire analysis in head and neck tumors. TCR repertoire profiling data did not show any association with the recurrence of HNSCC (Table V). However, HPV-positive cases exhibited a tendency toward higher number of total repertoires or higher DE50 (diversity evenness score) values compared to HPV-negative or recurrent HNSCC cases.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table V.

Association of TCRα and TCRβ repertoire profiling with tumor recurrence and HPV-status.

Discussion

Postoperative radiotherapy for locally advanced HNSCC with pathological high-risk features is a standard treatment strategy (25), but recurrence at an early follow-up time is still a clinical problem and achieving long-term local control and preventing early metastasis is a crucial issue.

The TME comprises stromal (cancer-associated) fibroblasts, immune cells (T cells, macrophages, etc.) and other supporting cells. Recently, advances in NGS-based clinical sequencing have widely extended the research targets from cancer cells to the entire TME. Genetic and immunological characterization studies of the TME based on NGS technology have demonstrated that tumors can be classified into several immune-types ranging from immune-suppressive to highly immunogenic, and some of them have been reported to be closely associated with the prognosis of cancer patients (7, 26, 27). Our group also reported that 1,734 tumors could be classified into 4 immune types based on PD-L1 and CD8B gene expression levels and that tumors with EGFR mutations showed immune-suppressive features (27). Regarding the TME status in HNSCC, many studies have demonstrated that specific genetic changes, such as TP53 mutation, contribute to the dysregulation of TME cells and cancer-associated fibroblasts (CAFs), the overproduction of cytokines and EMT, resulting in cancer invasion and metastasis (28, 29).

In the present study, we similarly demonstrated that patients who developed recurrence had a higher frequency of TP53 mutations than patients who did not develop recurrence, and down-regulation of the CDKN2 gene and the TP53 mutation/TGF-β/PAX7 pathway contributed to EMT induction (Figure 3). Additionally, patients who had TP53 mutations and subsequently developed recurrence exhibited cancer-related ERBB (EGFR) and VEGF pathway activation, and an immune-suppressive TME, which was achieved through a reduction in TIL number and function. Loss of function TP53 mutations are commonly identified in patients with advanced HNSCC and are closely associated with poor prognosis in patients with HNSCC (30, 31). Interestingly, loss of function TP53 mutation play an important role in cancer cell metabolism, where they can activate the glycolytic pathway and block the TriCarboxylic Acid cycle (Warburg effect) (32, 33). Our real-time PCR study showed the up-regulation of glycolytic enzyme gene (HK2 and PDK1) expression in patients who developed recurrence (Figure 2B), which may be mediated by the up-regulation of HIF1A gene expression, which contributes to radioresistance (34). Additionally, another metabolic factor which might be involved in the survival of HNSCC patients, the adenosine monophosphate deaminase 3 (AMPD3) gene, was reported to be significantly downregulated in head and neck cancer tissues (35).

The PAX7 gene is reported to be commonly up-regulated as is TGF-β1 in radiation-treated muscle tissues (36) and to affect the TP53 pathway by way of fusion gene construction (24). Importantly, PAX7 gene up-regulation in patients with TP53 mutations who subsequently developed recurrence has been suggested to be the first sign of recurrence, and high expression levels of PAX7 mRNA in HNSCC could be a possible poor prognostic marker according to TCGA dataset analysis (Figure 6A).

Moreover, HPV-infection status is another important clinical factor because HPV-positive HNSCCs have a better prognosis than HPV-negative HNSCCs (13). Chen et al. demonstrated, using immune-related gene expression profiling based on TCGA genome data, that the active immune signature group was associated with good prognosis and high HPV infection in head and neck cancers (37). In our study, seven patients with HPV-positive tumors did not develop recurrence and had no driver mutations or increased CD8+ TIL numbers. In contrast, patients who developed recurrence were characterized by HPV-negative tumors and a history of smoking. In summary, patients with HNSCCs who developed recurrence tended to have a higher frequency of driver and TP53 mutations, negative-HPV status, EMT induction and an immune-suppressive state, including a decrease in T cells and an increase in M2-type tumor-associated macrophages (TAMs) in the TME, than patients who did not develop recurrence.

Additionally, TCR profiling analysis using next generation sequencing (NGS) did not show any association with HNSCC recurrence. However, HPV-positive cases exhibited a tendency toward high number of total repertoires and high DE50 score (Table V), which might contribute to no recurrence and good prognosis in HPV-positive HNSCC patients.

In the future, to improve the survival of patients with locally advanced HNSCCs by achieving long-term local control and preventing metastases, novel therapeutic approaches that enable the reversal of TME conditions to antitumorigenic should include the following: 1) immune-checkpoint blockade (e.g., combinations of anti-PD-1/PD-L1 and anti-CTLA4 antibodies), 2) agents targeting M2-type TAMs or TGF-beta signaling pathway (38), and 3) strategies aimed at restoring the metabolic skew with metformin (39). A clinical trial using metformin was reported by Amin et al.; metformin treatment decreased intratumoral FOXP3+ T cell numbers and increased stromal CD8+ T cell numbers in patients with head and neck cancer (40). Hopefully, novel promising regimens following RT will be developed in upcoming clinical trials aiming to overcome EMT and immune-suppression and achieve long-term disease control.

There are several limitations in the present study. Bulk tumor samples collected at the time of tumor resection were used for GEP and WES analyses, which limited the investigation of intratumoral heterogeneity. Moreover, this study was conducted in a single institution with a limited number of patients; thus, selection bias is a significant concern in the present study. Nevertheless, patients with high PAX7 gene expression exhibited poorer prognosis in TCGA dataset than those with low PAX7 expression. To validate our findings, we need prospective observational studies of the correlation between PAX7 gene expression and HNSCC treatment response and tumor recurrence.

In the present study, patients with HNSCCs who developed recurrence were genetically and immunologically characterized and compared to patients who did not develop recurrence. The present study demonstrated that PAX7 gene expression might serve as a prognostic marker in HNSCCs.

Acknowledgements

The Authors thank the staff of the Shizuoka Cancer Center Hospital for assistance in sample preparation and the members of the Shizuoka Cancer Center Research Institute for discussions. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Footnotes

  • Authors’ Contributions

    KY and YA participated in the design of the study and drafting of the manuscript and were responsible for completing the study. HM, AI and TA performed immunological in vitro experiments. TN, KO and KU performed genetic analysis using NGS and gene microarray. RK was responsible for the statistical analysis. KM and TS contributed to the preparation of pathological specimens. HO, TO, HH, HA, SM, TN, SG, SO, TM, SH and TY participated in collecting clinical samples and clinical data. YO and KY reviewed the manuscript. All Authors read and approved the final draft.

  • Conflicts of Interest

    The Authors declare that they have no conflicts of interest in relation to this study.

  • Received June 1, 2022.
  • Revision received July 5, 2022.
  • Accepted July 6, 2022.
  • Copyright © 2022 The Author(s). Published by the International Institute of Anticancer Research.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Kamangar F,
    2. Dores GM and
    3. Anderson WF
    : Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol 24(14): 2137-2150, 2006. PMID: 16682732. DOI: 10.1200/JCO.2005.05.2308
    OpenUrlAbstract/FREE Full Text
  2. ↵
    1. Marur S and
    2. Forastiere AA
    : Head and neck cancer: changing epidemiology, diagnosis, and treatment. Mayo Clin Proc 83(4): 489-501, 2008. PMID: 18380996. DOI: 10.4065/83.4.489
    OpenUrlCrossRefPubMed
  3. ↵
    1. Leemans CR,
    2. Tiwari R,
    3. Nauta JJ,
    4. van der Waal I and
    5. Snow GB
    : Recurrence at the primary site in head and neck cancer and the significance of neck lymph node metastases as a prognostic factor. Cancer 73(1): 187-190, 1994. PMID: 8275423. DOI: 10.1002/1097-0142(19940101)73:1<187::aid-cncr2820730132>3.0.co;2-j
    OpenUrlCrossRefPubMed
  4. ↵
    1. Zhang J,
    2. Zhong X,
    3. Jiang H,
    4. Jiang H,
    5. Xie T,
    6. Tian Y,
    7. Li R,
    8. Wang B,
    9. Zhang J and
    10. Yuan Y
    : Comprehensive characterization of the tumor microenvironment for assessing immunotherapy outcome in patients with head and neck squamous cell carcinoma. Aging (Albany NY) 12(22): 22509-22526, 2020. PMID: 33216727. DOI: 10.18632/aging.103460
    OpenUrlCrossRefPubMed
  5. ↵
    1. Bagaev A,
    2. Kotlov N,
    3. Nomie K,
    4. Svekolkin V,
    5. Gafurov A,
    6. Isaeva O,
    7. Osokin N,
    8. Kozlov I,
    9. Frenkel F,
    10. Gancharova O,
    11. Almog N,
    12. Tsiper M,
    13. Ataullakhanov R and
    14. Fowler N
    : Conserved pan-cancer microenvironment subtypes predict response to immunotherapy. Cancer Cell 39(6): 845-865.e7, 2021. PMID: 34019806. DOI: 10.1016/j.ccell.2021.04.014
    OpenUrlCrossRefPubMed
    1. Wu T,
    2. Tang C,
    3. Tao R,
    4. Yong X,
    5. Jiang Q and
    6. Feng C
    : PD-L1-mediated immunosuppression in oral squamous cell carcinoma: Relationship with macrophage infiltration and epithelial to mesenchymal transition markers. Front Immunol 12: 693881, 2021. PMID: 34552581. DOI: 10.3389/fimmu.2021.693881
    OpenUrlCrossRefPubMed
  6. ↵
    1. Thorsson V,
    2. Gibbs DL,
    3. Brown SD,
    4. Wolf D,
    5. Bortone DS,
    6. Ou Yang TH,
    7. Porta-Pardo E,
    8. Gao GF,
    9. Plaisier CL,
    10. Eddy JA,
    11. Ziv E,
    12. Culhane AC,
    13. Paull EO,
    14. Sivakumar IKA,
    15. Gentles AJ,
    16. Malhotra R,
    17. Farshidfar F,
    18. Colaprico A,
    19. Parker JS,
    20. Mose LE,
    21. Vo NS,
    22. Liu J,
    23. Liu Y,
    24. Rader J,
    25. Dhankani V,
    26. Reynolds SM,
    27. Bowlby R,
    28. Califano A,
    29. Cherniack AD,
    30. Anastassiou D,
    31. Bedognetti D,
    32. Mokrab Y,
    33. Newman AM,
    34. Rao A,
    35. Chen K,
    36. Krasnitz A,
    37. Hu H,
    38. Malta TM,
    39. Noushmehr H,
    40. Pedamallu CS,
    41. Bullman S,
    42. Ojesina AI,
    43. Lamb A,
    44. Zhou W,
    45. Shen H,
    46. Choueiri TK,
    47. Weinstein JN,
    48. Guinney J,
    49. Saltz J,
    50. Holt RA,
    51. Rabkin CS, Cancer Genome Atlas Research Network,
    52. Lazar AJ,
    53. Serody JS,
    54. Demicco EG,
    55. Disis ML,
    56. Vincent BG and
    57. Shmulevich I
    : The immune landscape of cancer. Immunity 48(4): 812-830.e14, 2018. PMID: 29628290. DOI: 10.1016/j.immuni.2018.03.023
    OpenUrlCrossRefPubMed
  7. ↵
    1. Curry JM,
    2. Sprandio J,
    3. Cognetti D,
    4. Luginbuhl A,
    5. Bar-ad V,
    6. Pribitkin E and
    7. Tuluc M
    : Tumor microenvironment in head and neck squamous cell carcinoma. Semin Oncol 41(2): 217-234, 2014. PMID: 24787294. DOI: 10.1053/j.seminoncol.2014.03.003
    OpenUrlCrossRefPubMed
  8. ↵
    1. Ang KK,
    2. Harris J,
    3. Wheeler R,
    4. Weber R,
    5. Rosenthal DI,
    6. Nguyen-Tân PF,
    7. Westra WH,
    8. Chung CH,
    9. Jordan RC,
    10. Lu C,
    11. Kim H,
    12. Axelrod R,
    13. Silverman CC,
    14. Redmond KP and
    15. Gillison ML
    : Human papillomavirus and survival of patients with oropharyngeal cancer. N Engl J Med 363(1): 24-35, 2010. PMID: 20530316. DOI: 10.1056/NEJMoa0912217
    OpenUrlCrossRefPubMed
  9. ↵
    1. Alsner J,
    2. Sørensen SB and
    3. Overgaard J
    : TP53 mutation is related to poor prognosis after radiotherapy, but not surgery, in squamous cell carcinoma of the head and neck. Radiother Oncol 59(2): 179-185, 2001. PMID: 11325447. DOI: 10.1016/s0167-8140(01)00301-2
    OpenUrlCrossRefPubMed
    1. Heaton CM,
    2. Durr ML,
    3. Tetsu O,
    4. van Zante A and
    5. Wang SJ
    : TP53 and CDKN2a mutations in never-smoker oral tongue squamous cell carcinoma. Laryngoscope 124(7): E267-E273, 2014. PMID: 24431303. DOI: 10.1002/lary.24595
    OpenUrlCrossRefPubMed
  10. ↵
    1. van Ginkel JH,
    2. de Leng WW,
    3. de Bree R,
    4. van Es RJ and
    5. Willems SM
    : Targeted sequencing reveals TP53 as a potential diagnostic biomarker in the post-treatment surveillance of head and neck cancer. Oncotarget 7(38): 61575-61586, 2016. PMID: 27528217. DOI: 10.18632/oncotarget.11196
    OpenUrlCrossRefPubMed
  11. ↵
    1. Mehanna H,
    2. Beech T,
    3. Nicholson T,
    4. El-Hariry I,
    5. McConkey C,
    6. Paleri V and
    7. Roberts S
    : Prevalence of human papillomavirus in oropharyngeal and nonoropharyngeal head and neck cancer – systematic review and meta-analysis of trends by time and region. Head Neck 35(5): 747-755, 2013. PMID: 22267298. DOI: 10.1002/hed.22015
    OpenUrlCrossRefPubMed
  12. ↵
    1. Marur S,
    2. D’Souza G,
    3. Westra WH and
    4. Forastiere AA
    : HPV-associated head and neck cancer: a virus-related cancer epidemic. Lancet Oncol 11(8): 781-789, 2010. PMID: 20451455. DOI: 10.1016/S1470-2045(10)70017-6
    OpenUrlCrossRefPubMed
  13. ↵
    1. Mehanna H,
    2. Robinson M,
    3. Hartley A,
    4. Kong A,
    5. Foran B,
    6. Fulton-Lieuw T,
    7. Dalby M,
    8. Mistry P,
    9. Sen M,
    10. O’Toole L,
    11. Al Booz H,
    12. Dyker K,
    13. Moleron R,
    14. Whitaker S,
    15. Brennan S,
    16. Cook A,
    17. Griffin M,
    18. Aynsley E,
    19. Rolles M,
    20. De Winton E,
    21. Chan A,
    22. Srinivasan D,
    23. Nixon I,
    24. Grumett J,
    25. Leemans CR,
    26. Buter J,
    27. Henderson J,
    28. Harrington K,
    29. McConkey C,
    30. Gray A,
    31. Dunn J and De-ESCALaTE HPV Trial Group
    : Radiotherapy plus cisplatin or cetuximab in low-risk human papillomavirus-positive oropharyngeal cancer (De-ESCALaTE HPV): an open-label randomised controlled phase 3 trial. Lancet 393(10166): 51-60, 2019. PMID: 30449623. DOI: 10.1016/S0140-6736(18)32752-1
    OpenUrlCrossRefPubMed
  14. ↵
    1. Yamaguchi K,
    2. Urakami K,
    3. Nagashima T,
    4. Shimoda Y,
    5. Ohnami S,
    6. Ohnami S,
    7. Ohshima K,
    8. Mochizuki T,
    9. Hatakeyama K,
    10. Serizawa M,
    11. Akiyama Y,
    12. Maruyama K,
    13. Katagiri H,
    14. Ishida Y,
    15. Takahashi K,
    16. Nishimura S,
    17. Terashima M,
    18. Kawamura T,
    19. Kinugasa Y,
    20. Yamakawa Y,
    21. Onitsuka T,
    22. Ohde Y,
    23. Sugino T,
    24. Ito I,
    25. Matsubayashi H,
    26. Horiuchi Y,
    27. Mizuguchi M,
    28. Yamazaki M,
    29. Inoue K,
    30. Wakamatsu K,
    31. Sugiyama M,
    32. Uesaka K and
    33. Kusuhara M
    : Prevalence of low-penetrant germline TP53 D49H mutation in Japanese cancer patients. Biomed Res 37(4): 259-264, 2016. PMID: 27545002. DOI: 10.2220/biomedres.37.259
    OpenUrlCrossRefPubMed
  15. ↵
    1. Ohshima K,
    2. Hatakeyama K,
    3. Nagashima T,
    4. Watanabe Y,
    5. Kanto K,
    6. Doi Y,
    7. Ide T,
    8. Shimoda Y,
    9. Tanabe T,
    10. Ohnami S,
    11. Ohnami S,
    12. Serizawa M,
    13. Maruyama K,
    14. Akiyama Y,
    15. Urakami K,
    16. Kusuhara M,
    17. Mochizuki T and
    18. Yamaguchi K
    : Integrated analysis of gene expression and copy number identified potential cancer driver genes with amplification-dependent overexpression in 1,454 solid tumors. Sci Rep 7(1): 641, 2017. PMID: 28377632. DOI: 10.1038/s41598-017-00219-3
    OpenUrlCrossRefPubMed
  16. ↵
    1. Hatakeyama K,
    2. Nagashima T,
    3. Urakami K,
    4. Ohshima K,
    5. Serizawa M,
    6. Ohnami S,
    7. Shimoda Y,
    8. Ohnami S,
    9. Maruyama K,
    10. Naruoka A,
    11. Akiyama Y,
    12. Kusuhara M,
    13. Mochizuki T and
    14. Yamaguchi K
    : Tumor mutational burden analysis of 2,000 Japanese cancer genomes using whole exome and targeted gene panel sequencing. Biomed Res 39(3): 159-167, 2018. PMID: 29899191. DOI: 10.2220/biomedres.39.159
    OpenUrlCrossRefPubMed
  17. ↵
    1. Akiyama Y,
    2. Kiyohara Y,
    3. Yoshikawa S,
    4. Otsuka M,
    5. Kondou R,
    6. Nonomura C,
    7. Miyata H,
    8. Iizuka A,
    9. Ashizawa T,
    10. Ohshima K,
    11. Urakami K,
    12. Nagashima T,
    13. Kusuhara M,
    14. Sugino T and
    15. Yamaguchi K
    : Immune response-associated gene profiling in Japanese melanoma patients using multi-omics analysis. Oncol Rep 39(3): 1125-1131, 2018. PMID: 29286146. DOI: 10.3892/or.2017.6173
    OpenUrlCrossRefPubMed
  18. ↵
    1. Ashizawa T,
    2. Iizuka A,
    3. Nonomura C,
    4. Kondou R,
    5. Maeda C,
    6. Miyata H,
    7. Sugino T,
    8. Mitsuya K,
    9. Hayashi N,
    10. Nakasu Y,
    11. Maruyama K,
    12. Yamaguchi K,
    13. Katano I,
    14. Ito M and
    15. Akiyama Y
    : Antitumor effect of programmed death-1 (PD-1) blockade in humanized the NOG-MHC double knockout mouse. Clin Cancer Res 23(1): 149-158, 2017. PMID: 27458246. DOI: 10.1158/1078-0432.CCR-16-0122
    OpenUrlAbstract/FREE Full Text
  19. ↵
    1. Schache AG,
    2. Liloglou T,
    3. Risk JM,
    4. Filia A,
    5. Jones TM,
    6. Sheard J,
    7. Woolgar JA,
    8. Helliwell TR,
    9. Triantafyllou A,
    10. Robinson M,
    11. Sloan P,
    12. Harvey-Woodworth C,
    13. Sisson D and
    14. Shaw RJ
    : Evaluation of human papilloma virus diagnostic testing in oropharyngeal squamous cell carcinoma: sensitivity, specificity, and prognostic discrimination. Clin Cancer Res 17(19): 6262-6271, 2011. PMID: 21969383. DOI: 10.1158/1078-0432.CCR-11-0388
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Nonomura C,
    2. Otsuka M,
    3. Kondou R,
    4. Iizuka A,
    5. Miyata H,
    6. Ashizawa T,
    7. Sakura N,
    8. Yoshikawa S,
    9. Kiyohara Y,
    10. Ohshima K,
    11. Urakami K,
    12. Nagashima T,
    13. Ohnami S,
    14. Kusuhara M,
    15. Mitsuya K,
    16. Hayashi N,
    17. Nakasu Y,
    18. Mochizuki T,
    19. Yamaguchi K and
    20. Akiyama Y
    : Identification of a neoantigen epitope in a melanoma patient with good response to anti-PD-1 antibody therapy. Immunol Lett 208: 52-59, 2019. PMID: 30880120. DOI: 10.1016/j.imlet.2019.02.004
    OpenUrlCrossRefPubMed
  21. ↵
    1. Bolotin DA,
    2. Poslavsky S,
    3. Mitrophanov I,
    4. Shugay M,
    5. Mamedov IZ,
    6. Putintseva EV and
    7. Chudakov DM
    : MiXCR: software for comprehensive adaptive immunity profiling. Nat Methods 12(5): 380-381, 2015. PMID: 25924071. DOI: 10.1038/nmeth.3364
    OpenUrlCrossRefPubMed
  22. ↵
    1. Xia SJ,
    2. Pressey JG and
    3. Barr FG
    : Molecular pathogenesis of rhabdomyosarcoma. Cancer Biol Ther 1(2): 97-104, 2002. PMID: 12170781. DOI: 10.4161/cbt.51
    OpenUrlCrossRefPubMed
  23. ↵
    1. Magrini SM,
    2. Buglione M,
    3. Corvò R,
    4. Pirtoli L,
    5. Paiar F,
    6. Ponticelli P,
    7. Petrucci A,
    8. Bacigalupo A,
    9. Crociani M,
    10. Lastrucci L,
    11. Vecchio S,
    12. Bonomo P,
    13. Pasinetti N,
    14. Triggiani L,
    15. Cavagnini R,
    16. Costa L,
    17. Tonoli S,
    18. Maddalo M and
    19. Grisanti S
    : Cetuximab and radiotherapy versus cisplatin and radiotherapy for locally advanced head and neck cancer: a randomized Phase II trial. J Clin Oncol 34(5): 427-435, 2016. PMID: 26644536. DOI: 10.1200/JCO.2015.63.1671
    OpenUrlAbstract/FREE Full Text
  24. ↵
    1. Ock CY,
    2. Keam B,
    3. Kim S,
    4. Lee JS,
    5. Kim M,
    6. Kim TM,
    7. Jeon YK,
    8. Kim DW,
    9. Chung DH and
    10. Heo DS
    : Pan-Cancer immunogenomic perspective on the tumor microenvironment based on PD-L1 and CD8 T-cell infiltration. Clin Cancer Res 22(9): 2261-2270, 2016. PMID: 26819449. DOI: 10.1158/1078-0432.CCR-15-2834
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Kondou R,
    2. Iizuka A,
    3. Nonomura C,
    4. Miyata H,
    5. Ashizawa T,
    6. Nagashima T,
    7. Ohshima K,
    8. Urakami K,
    9. Kusuhara M,
    10. Yamaguchi K and
    11. Akiyama Y
    : Classification of tumor microenvironment immune types based on immune response-associated gene expression. Int J Oncol 54(1): 219-228, 2019. PMID: 30387832. DOI: 10.3892/ijo.2018.4617
    OpenUrlCrossRefPubMed
  26. ↵
    1. Coradini D,
    2. Fornili M,
    3. Ambrogi F,
    4. Boracchi P and
    5. Biganzoli E
    : TP53 mutation, epithelial-mesenchymal transition, and stemlike features in breast cancer subtypes. J Biomed Biotechnol 2012: 254085, 2012. PMID: 22899882. DOI: 10.1155/2012/254085
    OpenUrlCrossRefPubMed
  27. ↵
    1. Ohashi S,
    2. Natsuizaka M,
    3. Wong GS,
    4. Michaylira CZ,
    5. Grugan KD,
    6. Stairs DB,
    7. Kalabis J,
    8. Vega ME,
    9. Kalman RA,
    10. Nakagawa M,
    11. Klein-Szanto AJ,
    12. Herlyn M,
    13. Diehl JA,
    14. Rustgi AK and
    15. Nakagawa H
    : Epidermal growth factor receptor and mutant p53 expand an esophageal cellular subpopulation capable of epithelial-to-mesenchymal transition through ZEB transcription factors. Cancer Res 70(10): 4174-4184, 2010. PMID: 20424117. DOI: 10.1158/0008-5472.CAN-09-4614
    OpenUrlAbstract/FREE Full Text
  28. ↵
    1. Skinner HD,
    2. Sandulache VC,
    3. Ow TJ,
    4. Meyn RE,
    5. Yordy JS,
    6. Beadle BM,
    7. Fitzgerald AL,
    8. Giri U,
    9. Ang KK and
    10. Myers JN
    : TP53 disruptive mutations lead to head and neck cancer treatment failure through inhibition of radiation-induced senescence. Clin Cancer Res 18(1): 290-300, 2012. PMID: 22090360. DOI: 10.1158/1078-0432.CCR-11-2260
    OpenUrlAbstract/FREE Full Text
  29. ↵
    1. Huang X,
    2. Pateromichelakis S,
    3. Hills A,
    4. Sherriff M,
    5. Lyons A,
    6. Langdon J,
    7. Odell E,
    8. Morgan P,
    9. Harrison J and
    10. Partridge M
    : p53 mutations in deep tissues are more strongly associated with recurrence than mutation-positive mucosal margins. Clin Cancer Res 13(20): 6099-6106, 2007. PMID: 17947474. DOI: 10.1158/1078-0432.CCR-07-1369
    OpenUrlAbstract/FREE Full Text
  30. ↵
    1. Cairns RA,
    2. Harris IS and
    3. Mak TW
    : Regulation of cancer cell metabolism. Nat Rev Cancer 11(2): 85-95, 2011. PMID: 21258394. DOI: 10.1038/nrc2981
    OpenUrlCrossRefPubMed
  31. ↵
    1. Vousden KH and
    2. Ryan KM
    : p53 and metabolism. Nat Rev Cancer 9(10): 691-700, 2009. PMID: 19759539. DOI: 10.1038/nrc2715
    OpenUrlCrossRefPubMed
  32. ↵
    1. Harada H
    : Hypoxia-inducible factor 1-mediated characteristic features of cancer cells for tumor radioresistance. J Radiat Res 57(Suppl 1): i99-i105, 2016. PMID: 26983985. DOI: 10.1093/jrr/rrw012
    OpenUrlCrossRefPubMed
  33. ↵
    1. Hsu CM,
    2. Chang SF,
    3. Tsai YT,
    4. Tsai MS,
    5. Chang GH,
    6. Chen HC,
    7. Huang PC,
    8. Ko CA,
    9. Wu CY,
    10. Lin SF and
    11. Yang MY
    : Downregulation of AMPD3 is associated with poor survival in head and neck squamous cell carcinoma. In Vivo 36(2): 704-712, 2022. PMID: 35241525. DOI: 10.21873/invivo.12756
    OpenUrlAbstract/FREE Full Text
  34. ↵
    1. Zhou Y,
    2. Sheng X,
    3. Deng F,
    4. Wang H,
    5. Shen L,
    6. Zeng Y,
    7. Ni Q,
    8. Zhan S and
    9. Zhou X
    : Radiation-induced muscle fibrosis rat model: establishment and valuation. Radiat Oncol 13(1): 160, 2018. PMID: 30157899. DOI: 10.1186/s13014-018-1104-0
    OpenUrlCrossRefPubMed
  35. ↵
    1. Chen YP,
    2. Wang YQ,
    3. Lv JW,
    4. Li YQ,
    5. Chua MLK,
    6. Le QT,
    7. Lee N,
    8. Colevas AD,
    9. Seiwert T,
    10. Hayes DN,
    11. Riaz N,
    12. Vermorken JB,
    13. O’Sullivan B,
    14. He QM,
    15. Yang XJ,
    16. Tang LL,
    17. Mao YP,
    18. Sun Y,
    19. Liu N and
    20. Ma J
    : Identification and validation of novel microenvironment-based immune molecular subgroups of head and neck squamous cell carcinoma: implications for immunotherapy. Ann Oncol 30(1): 68-75, 2019. PMID: 30407504. DOI: 10.1093/annonc/mdy470
    OpenUrlCrossRefPubMed
  36. ↵
    1. Lind H,
    2. Gameiro SR,
    3. Jochems C,
    4. Donahue RN,
    5. Strauss J,
    6. Gulley JL,
    7. Palena C and
    8. Schlom J
    : Dual targeting of TGF-β and PD-L1 via a bifunctional anti-PD-L1/TGF-βRII agent: status of preclinical and clinical advances. J Immunother Cancer 8(1): e000433, 2020. PMID: 32079617. DOI: 10.1136/jitc-2019-000433
    OpenUrlAbstract/FREE Full Text
  37. ↵
    1. Kubo T,
    2. Ninomiya T,
    3. Hotta K,
    4. Kozuki T,
    5. Toyooka S,
    6. Okada H,
    7. Fujiwara T,
    8. Udono H and
    9. Kiura K
    : Study protocol: Phase-Ib trial of nivolumab combined with metformin for refractory/recurrent solid tumors. Clin Lung Cancer 19(6): e861-e864, 2018. PMID: 30172698. DOI: 10.1016/j.cllc.2018.07.010
    OpenUrlCrossRefPubMed
  38. ↵
    1. Amin D,
    2. Richa T,
    3. Mollaee M,
    4. Zhan T,
    5. Tassone P,
    6. Johnson J,
    7. Luginbuhl A,
    8. Cognetti D,
    9. Martinez-Outschoorn U,
    10. Stapp R,
    11. Solomides C,
    12. Rodeck U and
    13. Curry J
    : Metformin effects on FOXP3+ and CD8+ T cell infiltrates of head and neck squamous cell carcinoma. Laryngoscope 130(9): E490-E498, 2020. PMID: 31593308. DOI: 10.1002/lary.28336
    OpenUrlCrossRefPubMed
PreviousNext
Back to top

In this issue

Anticancer Research: 42 (9)
Anticancer Research
Vol. 42, Issue 9
September 2022
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Back Matter (PDF)
  • Ed Board (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Anticancer Research.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Immunological and Genetic Characterization of Patients With Head and Neck Cancer who Developed Recurrence
(Your Name) has sent you a message from Anticancer Research
(Your Name) thought you would like to see the Anticancer Research web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
2 + 6 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Immunological and Genetic Characterization of Patients With Head and Neck Cancer who Developed Recurrence
KAZUAKI YASUI, RYOTA KONDOU, HARUO MIYATA, AKIRA IIZUKA, TADASHI ASHIZAWA, TAKESHI NAGASHIMA, KEIICHI OHSHIMA, KENICHI URAKAMI, KOJI MURAMATSU, TAKASHI SUGINO, KEN YAMAGUCHI, HIROFUMI OGAWA, TSUYOSHI ONOE, HIDEYUKI HARADA, HIROFUMI ASAKURA, SHIGEYUKI MURAYAMA, TETSUO NISHIMURA, SEIYA GOTO, SHINICHI OKADA, TAKASHI MUKAIGAWA, SATOSHI HAMAUCHI, TOMOYA YOKOTA, YUSUKE ONOZAWA, YASUTO AKIYAMA
Anticancer Research Sep 2022, 42 (9) 4417-4428; DOI: 10.21873/anticanres.15942

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Reprints and Permissions
Share
Immunological and Genetic Characterization of Patients With Head and Neck Cancer who Developed Recurrence
KAZUAKI YASUI, RYOTA KONDOU, HARUO MIYATA, AKIRA IIZUKA, TADASHI ASHIZAWA, TAKESHI NAGASHIMA, KEIICHI OHSHIMA, KENICHI URAKAMI, KOJI MURAMATSU, TAKASHI SUGINO, KEN YAMAGUCHI, HIROFUMI OGAWA, TSUYOSHI ONOE, HIDEYUKI HARADA, HIROFUMI ASAKURA, SHIGEYUKI MURAYAMA, TETSUO NISHIMURA, SEIYA GOTO, SHINICHI OKADA, TAKASHI MUKAIGAWA, SATOSHI HAMAUCHI, TOMOYA YOKOTA, YUSUKE ONOZAWA, YASUTO AKIYAMA
Anticancer Research Sep 2022, 42 (9) 4417-4428; DOI: 10.21873/anticanres.15942
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Patients and Methods
    • Results
    • Discussion
    • Acknowledgements
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

Cited By...

  • Genetic and Immunological Characterization of Brain Metastases from Solid Cancers
  • Impact of Mutations in Subunit Genes of the Mammalian SWI/SNF Complex on Immunological Tumor Microenvironment
  • Localization of EGFR Mutations in Non-small-cell Lung Cancer Tissues Using Mutation-specific PNA-DNA Probes
  • Google Scholar

More in this TOC Section

  • Preoperative Cachexia Index Predicts Overall Survival Following Curative Resection for Remnant Gastric Cancer
  • Effect of Increased Image Matrix on Lung Nodule Volumetry in Chest CT: A Phantom Study
  • Prognostic Impact of the Geriatric Nutritional Risk Index in Elderly Patients With Colorectal Cancer
Show more Clinical Studies

Keywords

  • Tumor microenvironment (TME)
  • epithelial-mesenchymal transition
  • Tumor-infiltrating lymphocytes
  • human papillomavirus
  • TP53 mutation-TGF-β1-PAX7 pathway
Anticancer Research

© 2026 Anticancer Research

Powered by HighWire