ABSTRACT 234 diagnostic formalin-fixed paraffin-embedded (FFPE) blocks from homogeneously treated patients with locally advanced head and neck squamous cell carcinoma (HNSCC) within a

multicentre phase III clinical trial were characterised. The mutational spectrum was examined by next generation sequencing in the 26 most frequent oncogenic drivers in cancer and correlated

with treatment response and survival. Human papillomavirus (HPV) status was measured by p16INK4a immunohistochemistry in oropharyngeal tumours. Clinicopathological features and response to

treatment were measured and compared with the sequencing results. The results indicated _TP53_ as the most mutated gene in locally advanced HNSCC. HPV-positive oropharyngeal tumours were

HNSCC. Survival analysis showed that non-mutated HNSCC tumours associated with better prognosis and lack of mutations can be identified as an important biomarker in HNSCC. Frequent

alterations in PI3K pathway in HPV-positive HNSCC could define a promising pathway for pharmacological intervention in this group of tumours. SIMILAR CONTENT BEING VIEWED BY OTHERS TEMPORAL

EVOLUTION AND INTER-PATIENT HETEROGENEITY IN PRIMARY AND RECURRENT HEAD AND NECK SQUAMOUS CELL CARCINOMA Article Open access 29 August 2024 HALLMARKS OF A GENOMICALLY DISTINCT SUBCLASS OF

HEAD AND NECK CANCER Article Open access 20 October 2024 COMPUTATIONAL ANALYSIS OF TP53 MUTATIONAL LANDSCAPE UNVEILS KEY PROGNOSTIC SIGNATURES AND DISTINCT PATHOBIOLOGICAL PATHWAYS IN HEAD

AND NECK SQUAMOUS CELL CANCER Article Open access 20 July 2020 INTRODUCTION Head and neck squamous cell carcinoma (HNSCC) is the sixth most common neoplasia in the developed world1. It

constitutes a heterogeneous disease of tumours of the upper aerodigestive tract with different pathogenic origins and clinical prognosis. Tobacco smoking and alcohol consumption are still

the most classical risk factors2 followed by viral infection3,4. Most HNSCC are diagnosed as locally advanced disease (stage III or IV) and therefore multidisciplinary treatment strategies

include surgery, radiotherapy (RT), chemotherapy (CT) and targeted therapy. However, treatment with chemoradiotherapy (CTRT) has become the standard of care after the publication of a large

pool analysis5. With the aim of improving the clinical benefit, the addition of cetuximab, an IgG1 chimeric monoclonal antibody against epidermal growth factor receptor (EGFR), concomitant

with RT was explored, resulting in longer progression-free survival (PFS) and overall survival (OS) compared to RT alone, although a direct comparison with CTRT has not been evaluated yet6.

The role of induction chemotherapy has remained a subject of controversy. The combination of docetaxel-cisplatin and 5-fluorouracil (TPF) has emerged as the most active regimen in locally

advanced disease, showing better results than PF, although it did not show a convincing survival benefit in induction regimens compared with historical data of treatment with concomitant

chemoradiotherapy alone7,8,9. Induction chemotherapy to improve organ preservation and survival may be an alternative to CTRT. The addition of cetuximab to radiation therapy in patients with

laryngeal cancer stage III and IVA that respond to TPF could improve functional laryngeal preservation10, although randomized phase III trials did not find that induction chemotherapy

provided benefit in time-to-treatment failure or OS11,12,13,14. On the other hand, a randomized phase II–III study suggested that adding TPF induction chemotherapy to CTRT resulted in a

higher rate of radiological complete response compared with concurrent CTRT alone, improving PFS and OS by induction TPF15. The fact that patient populations in these trials were very

heterogeneous, questions induction chemotherapy’s benefit thus, subgroups that will have a benefit from it need to be identified. Next-generation sequencing (NGS) has helped to identify

genetic alterations that could be used as a molecular vulnerability for therapeutic discovery and target optimization. In addition, they could have a prognosis utility as biomarkers of

response in different tumour types including head and neck squamous cell carcinomas16,17. For instance, the analysis of _The Cancer Genome Atlas_ (TCGA) described the molecular landscape of

HPV-positive and HPV-negative HNSCC as having molecular alterations not reported before18. Since the first description of the recurrently mutated genes in HNSCC19, additional studies have

included other genes such as _TP53, NOTCH1, PIK3CA, CDKN2A, CCDN1, HRAS, FAT1, FBXW7_ and _FGFR3,_ among others20,21. For this reason, targeted sequencing has become a flexible tool to study

those genes previously reported as mutated in HNSCC21. To contribute to the understanding of how somatic mutations influence the outcome of HNSCC treatment, we have studied a panel of 26

genes (Table S1) by next-generation sequencing in a homogenously treated locally advanced HNSCC Spanish cohort. In this study we report some mutations linked with detrimental outcome and

their presence in relation to HPV presence. RESULTS COHORT CHARACTERISTICS 234 FFPE blocks with diagnostic biopsies from HNSCC patients within a multicentre phase III clinical trial were

incorporated in this study (Fig. S1). Clinical demographic factors such as age, gender, disease site and tumour stage are consistent between the whole cohort within the clinical trial and

the subsequent random selection due to FFPE block availability in this study. Overall, most were from men (89.7%), with pharyngeal carcinoma (65.4%) and diagnosed in tumour stage IV-A

(71.4%) with an average of 57 years old (Table 1). Clinicopathologic features by locations are shown in Table 1. Considering only oropharyngeal tumours (see “Methods” section), 13 samples

(17.1%) were HPV-positive based on p16 immunohistochemistry (IHC). According to its grade, HPV-positive samples were statistically associated with poorly differentiated (p = 0.016) and

_TP53_ wild-type (p = 0.009) tumours (Table 2). Targeted panel sequencing in HNSCC FFPE blocks identified 162 samples (69.23%) with previously described pathogenic mutations whereas 46

(19.66%) did not carry any mutation and 26 (11.11%) showed variants of uncertain clinical significance (VUS). 194 pathogenic mutations and 72 VUS were found in the sequencing of the 234 FFPE

blocks. All samples were sequenced > 5000 × (7074 ± 10,516). Globally, the most mutated gene was _TP53_ (61.1%) followed by _PIK3CA_ (10.3%), _FBXW7_ (1.7%), _PTEN_ (1.3%) and _CKIT_ and

_CTNNB1_ (both with 0.43%) (Fig. 1). 144 out of 162 (88.89%) mutated tumours had _TP53_ mutations either alone or with others. Most of the pathogenic variants were missense (55.67%),

followed by stop-gained (18.04%), frameshift (14.95%), splice-donor (8.76%) and in-frame deletions (2.58%) (Table S2). ASSOCIATION OF MUTATIONS WITH CLINICAL VARIABLES General comparison of

the mutational status and tumour characteristics such as location, grade and histology, did not show any significant difference (p > 0.05) (Table 3). However, considering variants of

uncertain significance, women were associated with a lower percentage of mutation than men in our cohort (p = 0.002) (Table 3). MUTATIONAL PROFILE AND HPV PRESENCE IN OROPHARYNGEAL TUMOURS

HPV mutational profile in oropharyngeal tumours is shown in Fig. 2. HPV-positive samples presented slightly more pathogenic mutations than HPV-negative (76.2% versus 69.2%, p = 0.762) (Table

2). Despite the fact that _TP53_ was the most frequently mutated gene in both groups, these mutations were more recurrent in HPV-negative tumours (71.4% in HPV-negative and 30.8% in

HPV-positive), difference statistically significant (p = 0.009). Conversely, the second most mutated gene, _PIK3CA,_ although more represented in HPV-positive tumours (9.5% in HPV-negative

versus 23.1% in HPV-positive), did not show any statistically significant difference (p = 0.178). While HPV-negative tumours did not present pathogenic mutations in other genes, _PTEN_ was

the third most commonly mutated in HPV-positive tumours (15.4%), followed by _FBXW7_ (7.7%). MUTATIONAL STATUS AND RESPONSE TO TREATMENT After induction chemotherapy, 188 (80.34%) patients

were similarly randomized: 95 (50.53%) to conventional treatment and 93 (49.47%) to the experimental arm. Preliminary data indicated that the two regimens showed similar survival, response

rates, toxicity and locoregional control22. For that reason, both arms were evaluated within the same group as final response (or response after randomization). Evaluation of the two

time-point responses according to the mutational profile did not show any statistical difference (Table 4). There was, however, a tendency between mutated tumours and complete response at

the end of the treatment taking VUS into consideration, p = 0.096 (Table S3). Considering only HPV profile in oropharyngeal tumours, there were no differences between HPV-positive and

HPV-negative individuals either after induction chemotherapy (p = 0.396) or randomization (p = 0.914) (Table 5). Finally, an exploratory analysis was performed using the two most mutated

genes in the study: _TP53_ and _PIK3CA_ (Table S4). Analysing patients with mutations in those genes alone or within other genes and the clinical response, indicated that none of the _TP53_

subgroups were associated in any of the clinical trial treatment timepoints (p > 0.05). By contrast, considering only _PIK3CA_ mutations, a statistically positive association was found in

the complete response group after induction chemotherapy (p = 0.024). However, this finding was not corroborated in final response group (p = 0.235) (Table S4) what could suggest that this

could be a false positive result taken into consideration multiple testing and sample size bias. Poeta’s23 and Neskey’s24 classification in patients harbouring _TP53_ mutations in relation

with clinical response before and after randomization did not show any statistically significant association (p > 0.05, Table S5). HPV, MUTATIONAL STATUS AND CLINICAL OUTCOME HPV-positive

oropharyngeal tumours showed higher OS compared with HPV-negative (p = 0.044). This tendency was also shown in PFS, however, without statistically significant results (p = 0.148, HR = 0.498

(0.194–1.280)) (Fig. 3A,B). Moreover, OS was correlated with the mutational status. Patients without mutations in the selected genes had a better OS than patients with mutated tumours (p = 

0.011, HR = 1.672 (1.123–2.491)) (Fig. 3C). This difference was also observed in PFS without statistically significant results (p = 0.135, HR = 1.349 (0.911–1.999)) (Fig. 3D). A correlation

with the number of mutations also showed that tumours with one mutation had lower OS (p = 0.038, HR = 1.544 (1.025–2.327)) than non-mutated patients, with the exception of PFS (p = 0.259, HR

 = 1.264 (0.842–1.898)) (Fig. 3E,F). Equally, tumours with more than one mutation showed lower OS (p = 0.001, HR = 2.524 (1.441–4.422)) and PFS (p = 0.036, HR = 1.824 (1.039–3.203)) than

non-mutated samples. Conversely, the differences between tumours with one or more mutations were not statistically significant (p > 0.05). Finally, we compared _TP53_ mutations based on

Poeta’s23 and Neskey’s24 stratification models with OS and PFS (Fig. S2). No association was observed between low-risk/high risk mutations or non-disruptive/disruptive mutations and survival

in these patients (Fig. S2). DISCUSSION As most of the head and neck cancers are diagnosed at a locally advanced stage the identification of biomarkers of response is a main goal to

optimize treatment and reduce side effects. In recent years, induction chemotherapy has been shown to produce a benefit in organ preservation without a clear improvement in survival. In

addition, this approach led to a high toxicity, particularly when concurrent radiotherapy was given with high doses of cisplatin. At present, very few predictive biomarkers of response have

been described. For this reason, we proposed a study of the mutational status in 26 of the most common altered genes in cancer with next-generation sequencing in a homogeneously treated

representative Spanish cohort of HNSCC from the phase III clinical trial TTCC-2007-0122. The epidemiology characteristics of the HNSCC patients included in our study were similar to other

series reported from the same region: the ratio between sexes is 9:1 in detriment of men, and most of the patients were diagnosed at stage IV25. p16 IHC, a surrogate of HPV infection in

oropharyngeal tumours, showed that HPV was present in 17.1% of samples, a lower percentage than previously reported in Europe26 but with similar location to other Southern European countries

in oropharynx27. Globally, the most mutated gene in our series was _TP53_ (61.1%). We observed a statistically significant lower percentage of mutated _TP53_ in HPV-positive oropharyngeal

tumours (71.4%) than in HPV-negative (30.8%) as has been previously reported in HNSCC28,29. These results could be explained if _TP53_ sequestration by the viral oncoprotein E6 prevents

gaining mutations in this gene under selective pressure of30,31. Comparing to other series, there was a higher percentage of _TP53_ mutations in HPV-positive tumours29. This fact could be

explained by the coexistence of viral infection and other aetiological factors such as tobacco smoking and alcohol consumption during tumourigenesis32; these data were not collected in this

study. TCGA data described 85% of _TP53_ mutation in HPV-negative tumours and only 3% in HPV-positive ones18. However, the sample population was very different with a high predominance of

oral cavity tumours (62%) and mainly heavy smokers. _PI3K/AKT/mTOR_ has been reported as the most mutated pathway in HNSCC (13% to 56%), regardless of the HPV status18. _PIK3CA_ gene, that

encodes the catalytic subunit of the family, has been reported with an average mutational rate of 10.53% in HNSCC33, similar to the 10.25% found in this cohort, and with a higher frequency

in laryngeal tumours34. Mutations in this gene have also been related to HPV-positive tumours4. Our results corroborate this fact, being _PIK3CA_ more frequently mutated in HPV-positive

tumours (23.1% versus 9.5% in HPV-negative oropharyngeal tumours), similar to previously described data35. We did not, however, see an increased percentage in laryngeal carcinoma. 73% of the

mutations in _PIK3CA_ are commonly located in 3 hotspots (E542K, E545K and H1047R/L)36, result also found in 76% of _PIK3CA_ mutated samples in our study, emphasising the accuracy of using

the targeted panel in HNSCC. Mutations in _FBXW7_: an E3 ubiquitin ligase member of the F-box protein family, have been previously observed in HNSCC19. This tumour suppressor gene targets

_NOTCH1_, being an important protein in cell proliferation control. Previous studies found _FBXW7_ mutated in 5% of HNSCC37,38 and a higher percentage of mutations was previously considered

as a prevalent event in HPV-positive tumours39. Our cohort confirmed these results in _FBXW7_ with a similar percentage only found in HPV-positive tumours (7.7%). _PTEN_ was the third most

mutated gene in 15.4% of the HPV-positive oropharyngeal tumours while not mutations were found in HPV-negative ones. Contrary to our results, TCGA study showed _PTEN_ mutated in 12% of

HPV-negative tumours and 6% of HPV-positive18. Apart from _PTEN_, there were other genes which mutated at a lower percentage in our series, such as _CKIT_ or _CTNNB1_ (both mutated at less

than 1% and only in non-oropharyngeal HPV-negative tumours)_,_ have been reported in HNSCC in varied percentages30,38,40. Together with _PIK3CA_, our result enhances the hypothesis of higher

prevalence of PI3K pathway activated mutations in HPV-positive tumours41. Overall, excluding _TP53_ mutations, recurrent alterations in _PIK3CA, PTEN_ and _FBXW7_ genes, all belonging to

the _PI3K/AKT/mTOR_ pathway, could define a potential new target for pharmacological intervention in HNSCC, as it has been suggested in other publications42. In terms of survival,

HPV-positive oropharyngeal tumours were associated with better prognosis, showing an increased OS and PFS compared to HPV-negative tumours as it was previously defined26,43,44,45,46,47.

Secondly, the presence of mutation in the targeted genes was associated with inferior outcome demonstrated by the presence of detrimental OS. These results could be an indirect measure of

tumour aggressiveness, as has been reported in other series43,47. Moreover, the fact that carriers of tumours with more than one mutation have lower OS than those with non-mutated tumours

reinforces this concept. Lastly, there was a lack of association between mutational status and response after treatment. This can indicate that, excluding genetic-driven druggable targets,

HNSCC mutational profile is not related to any clinical response but is a matter of mutational burden as is shown in the survival analyses. Similarly, there was no association between _TP53_

mutations stratified by Poeta’s23 and Neskey’s models24 and response to treatment or survival. These classification systems can serve as an important tool in individualizing and improving

treatment for high TP53 mutated tumours, as it was previously identified in a subset of high-risk patients with a decreased response to platinum-based therapies48. Nevertheless, these

classification models did not have any implication on outcome in our cohort. Overall, our data strongly support and expand previously published studies exploring the presence and prognosis

of mutations in this population. We have characterized the mutational profile of HPV-positive/HPV-negative oropharyngeal HNSCC in a representative cohort of patients. In this context apart

from _TP53_ mutations, frequent alterations in _PIK3CA, PTEN_ and _FBXW7_ genes, define possible pathways for pharmacological intervention. Finally, survival analysis showed that mutational

status in the tumour could define patient prognosis, and may potentially be used as biomarkers to stratify patients for more intensive treatment. However, larger studies should be performed

to confirm these results aiming at stratifying patients to different therapeutic interventions. METHODS SAMPLES 234 FFPE blocks with diagnostic biopsies from HNSCC patients were included in

this study. A consort diagram reporting the dropout is shown in Fig. S1. All samples belong to the clinical trial TTCC-2007-01 entitled: “Open label randomized, multi-centre phase III trial

of TPF plus concomitant treatment with cisplatin and radiotherapy versus concomitant cetuximab and radiotherapy in locally advanced, unresectable head and neck cancer”, ClinicalTrials.gov

identifier: NCT0071639122. TTCC-2007-01 TRIAL DESIGN AND DATA COLLECTION It was a non-inferiority, randomized and controlled study with a parallel assignment intervention model and an

endpoint of safety/efficacy, carried out between 2008 and 2013. The follow-up of the clinical trial finished in November 2016. According to protocol, written informed consent was obtained

from living subjects and the protocol was approved by the University Hospital of Salamanca and the ethical committees of each hospital in accordance with the 1964 Helsinki declaration and

its later amendments. Eligible patients: histologically or cytologically confirmed, previously untreated unresectable locally advanced (Stage III–IV) tumours (from oral cavity, oropharynx,

larynx, hypopharynx), ECOG performance status 0–1. Unresectable disease was determined by Northern California Oncology Group in measurable disease. Treatment: docetaxel, cisplatin,

5-fluorouracil (TPF)-based induction chemotherapy (T 75 mg/m2 d1, P 75 mg/m2 d1, F 750 mg/m2 CI d 1–5 q 21 d + G-CSF & ciprofloxacin, by 3 cycles; then, if objective response achieved,

they were randomized to: conventional radiotherapy (RT) up to 70 Gy + P 100 mg/m2 d 1–22–43 vs conventional RT up to 70 Gy + cetuximab 400/250 mg/m2 weekly until the completion of RT, and

they were stratified by primary tumour site. Surgery after RT (neck dissection) was allowed. The primary endpoint was non-inferiority of cetuximab-radiotherapy versus cisplatin-radiotherapy

in terms of overall survival. Response rate, loco-regional control and toxicity in both arms were considered secondary objectives. Preliminary data of this trial did not show any difference

in terms of survival or response rates, toxicity and loco-regional control as secondary end points in the two regimens22. Clinical data were compiled in a case report form by medical

oncologists involved in the clinical trial. All data were treated with the security measures established in compliance with the Protection of Personal Data Organic Law 15/1999, 13th

December, and safe-keeping at the University Hospital of Salamanca in its specific server. DNA EXTRACTION Percentage of tumour cells was measured in haematoxylin–eosin tissue sections by

central pathologist. Between four and ten 10 µm FFPE sections from diagnosis blocks were treated with deparaffinization solution (Qiagen, Hilden, Germany) and DNA extraction was done using

QIAamp DNA FFPE Tissue kit (Qiagen, Hilden, Germany). DNA QUALITY EVALUATION AND TARGETED NGS Following TruSight Tumor 26 Reference Guide (Illumina, San Diego, USA), DNA quality was measured

by qPCR. Comparing FFPE-gDNA amplification potential with a reference non-FFPE gDNA (QCT), delta Cq value was used to predict the dilution required for each sample. TruSight Tumor 26 panel

includes a set of 174 amplicons in complete exons of 26 cancer-associated genes (Table S1). This panel was selected due to its exceptional success rate using minimal DNA input even from FFPE

samples where genetic material is often degraded. Following steps of hybridization with the oligo pool, removing unbound oligos and extension and ligation with bound oligos, an

amplification of the libraries were performed. PCR products were checked on a 4% TBE agarose gel and finally the libraries were cleaned up by AMPure XP magnetic beads (Beckman Coulter, Brea,

CA, USA). PCR products were quantified using Qubit Fluorometer (Invitrogen, Carlsbad, CA, USA) and libraries were normalized at 4 nM in a final pool. Sequencing was performed in a NextSeq

500 System (Illumina, San Diego, USA). Data were transformed in BaseSpace platform and the VCF file format were read in the Variant Studio Software (Illumina, San Diego, USA). Following

Illumina recommendations, somatic variants over 5% of frequency, with yields at least 1000 × cumulative coverage between the 2 strands and considered from the software of PASS filter were

reported. Those variants of uncertain significance were considered pathogenic if at least two in silico prediction tools (SIFT and PolyPhen) classified them as deleterious/probably

damaging49, and they were defined as likely pathogenic in the Catalogue Of Somatic Mutations in Cancer (COSMIC; https://cancer.sanger.ac.uk/cosmic) or the National Center for Biotechnology

Information (NCBI; https://www.ncbi.nlm.nih.gov/clinvar) databases. ASSESSMENT OF HPV STATUS In the original study protocol, the assessment of HPV status was carried out by p16

immunohistochemistry (IHC), a surrogate marker for HPV infection50 as the gold-standard technique. FFPE sections were deparaffinized and exposed to 10 mM citrate buffer antigen retrieval at

92 °C for 30 min and then they were stained using a p16INK4a mouse monoclonal antibody (Cell Marque, Rocklin, CA, USA). Percentage of p16 staining was measured and only those tumours > 

70% nuclear and cytoplasmic p16+ were considered positive. 33 samples were considered HPV-positive following this methodology: 13 oropharyngeal, 4 hypopharyngeal, 2 laryngeal and 9 oral

cavity tumours. However, after the publication of the guidelines from the college of American pathologists, p16 IHC is only recommended in oropharyngeal tumours but other locations, where

DNA/RNA viral determination should be performed as a confirmatory test51. Since there was not more DNA from all the samples after the library preparation, only oropharyngeal tumours with 

> 70% p16 positive staining were considered HPV-positive. STATISTICAL ANALYSES Statistical analysis compared categorical parameters and mutational status by the Chi-square or Fisher’s

exact tests; while in continuous nonparametric variables, the Mann–Whitney U or Kruskal–Wallis H tests were used. p-values were calculated excluding missing values and they were considered

statistically significant when p < 0.05. Significant variables were included in the logistic regression analysis and size effects were indicated by odds ratio (OR) with their 95%

confidence interval (95% CI). Mutational status was classified as presence or absence of mutations, number of mutations (none, one or more than one) and the status of _TP53_ and _PIK3CA_

(mutant or wild-type). Response was divided in two groups of treatment: after induction chemotherapy and after chemo/cetuximab plus radiotherapy (final response) due to the similar outcome

in both arms22. Response was classified in both groups as complete response versus partial response/stabilization. No progressions were shown in the cohort. Survival analysis was done

according to the overall survival (OS) and progression-free survival (PFS) by Kaplan–Meier plots and log-rank test p-values were calculated in all the curves. Median was indicated in those

plots in which it was achieved. Hazard-ratio was calculated to measure the risk of the event with its 95% confidence interval (95% CI) by Cox regression. Median follow-up in OS was 32.23 

months while in PFS it was 15.31 months. Due to high prevalence in _TP53_ mutations, we applied Poeta’s and Neskey’s classifications stratifying the mutations according to its change and

functional effect, allowing a better comprehensive understanding on their relevance in clinical outcome. Following Poeta’s classification23, _TP53_ mutations were divided in two categories:

disruptive and non-disruptive according to their functional effects on the p53 protein. Additionally, according to Neskey’s model24, also named as Evolutionary Action score of _TP53_-coding

variants (EAp53), missense mutations were stratified into high-risk and low-risk through an _in-silico_ scoring (https://mammoth.bcm.tmc.edu/EAp53/). Then, comparative analysis was performed

in response to treatment, OS and PFS. All these tests were conducted using SPSS software version 21.0 (SPSS Inc., Chicago) and GraphPad Prism software version 6.0 (GraphPad Software Inc.,

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Pathologists. _Arch. Pathol. Lab. Med._ 142, 559–597 (2018). Article  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS Authors would like to thank the individuals who consented

to participate in this study and their relatives, and all their colleagues from the Spanish Group of Treatment of Head and Neck Cancer (TTCC) who have participated in this study and are not

included in the list of authors. We would also like to thank the pathologist technician María del Carmen Rodríguez for its implication in the study, Dr Eva Maria Sánchez Tapia and Dr Elena

Bueno-Martínez for technical support; and Roger Townsend for English editing. FUNDING This research was funded by the health research program of the “Instituto de Salud Carlos III”

(PI14/00071) co financed with FEDER founds and for the Health Regional Management of the Junta de Castilla y León (GRS1385/A/16). J. Fernández-Mateos was partially supported by a predoctoral

research grant from the Consejería de Educación—Junta de Castilla y León and the European Social Fund to CC-B (EDU/1084/2012). AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Medical Oncology

Service, University Hospital of Salamanca-IBSAL, 37007, Salamanca, Spain Javier Fernández-Mateos, Raquel Seijas-Tamayo, Juan Carlos Adansa Klain, Edel del Barco & Juan Jesús

Cruz-Hernández * Biomedical Research Institute of Salamanca (IBSAL), SACYL-University of Salamanca-CSIC, 37007, Salamanca, Spain Javier Fernández-Mateos, Raquel Seijas-Tamayo, Juan Carlos

Adansa Klain, Edel del Barco, Rogelio González-Sarmiento & Juan Jesús Cruz-Hernández * Molecular Medicine Unit-IBSAL, Department of Medicine, University of Salamanca, 37007, Salamanca,

Spain Javier Fernández-Mateos, Jéssica Pérez-García, Rogelio González-Sarmiento & Juan Jesús Cruz-Hernández * Institute of Molecular and Cellular Biology of Cancer (IBMCC), University of

Salamanca-CSIC, 37007, Salamanca, Spain Javier Fernández-Mateos, Jéssica Pérez-García, Rogelio González-Sarmiento & Juan Jesús Cruz-Hernández * Medical Oncology Department, Institut

Català d’Oncologia, L’Hospitalet de Llobregat, Universitat de Barcelona, IDIBELL, 08908, Barcelona, Spain Ricard Mesía, Miren Taberna & Silvia Vazquez * Medical Oncology Service,

Institut Català d’Oncologia, 17007, Gerona, Spain Jordi Rubió-Casadevall * Medical Oncology Service, Hospital Universitario de Burgos, 09006, Burgos, Spain Carlos García-Girón * Medical

Oncology Service, Hospital Universitario 12 de Octubre, 28041, Madrid, Spain Lara Iglesias * Medical Oncology Service, Hospital Universitario Lucus Augusti, 27003, Lugo, Spain Alberto Carral

Maseda * Pathologist Service, University Hospital of Salamanca, 37007, Salamanca, Spain María Asunción Gómez * Hospital Clínico San Carlos, IdISSC, CIBERONC, 28040, Madrid, Spain Alberto

Ocana * Centro Regional de Investigaciones Biomédicas, Universidad de Castilla La Mancha, 13071, Albacete, Spain Alberto Ocana Authors * Javier Fernández-Mateos View author publications You

can also search for this author inPubMed Google Scholar * Jéssica Pérez-García View author publications You can also search for this author inPubMed Google Scholar * Raquel Seijas-Tamayo

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search for this author inPubMed Google Scholar * Juan Carlos Adansa Klain View author publications You can also search for this author inPubMed Google Scholar * Miren Taberna View author

publications You can also search for this author inPubMed Google Scholar * Silvia Vazquez View author publications You can also search for this author inPubMed Google Scholar * María

Asunción Gómez View author publications You can also search for this author inPubMed Google Scholar * Edel del Barco View author publications You can also search for this author inPubMed 

Google Scholar * Alberto Ocana View author publications You can also search for this author inPubMed Google Scholar * Rogelio González-Sarmiento View author publications You can also search

for this author inPubMed Google Scholar * Juan Jesús Cruz-Hernández View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS All authors have read

and agree to the published version of the manuscript. Conceptualization, R.S.T., R.G.S. and J.J.C.H.; methodology, J.F.M. and J.P.G.; validation, J.F.M. and J.P.G.; formal analysis, J.F.M.

and A.O.; investigation, J.F.M., J.P.G., R.S.T, R.M., J.R.C., C.G.G., L.I., A.C.M., J.C.A.K., M.T., S.V., M.A.G. and E.D.B. ;resources, J.F.M., J.P.G, R.S.T, R.M., J.R.C., C.G.G., L.I.,

A.C.M., J.C.A.K., M.T., S.V., M.A.G., E.D.B., J.J.C.H. and R.G.S.; data curation, J.F.M., J.P.G. and R.S.T.; writing—original draft preparation, J.F.M., A.O., R.G.S. and J.J.C.H.;

writing—review and editing, all authors; visualization, J.F.M., A.O., R.G.S. and J.J.C.H.; supervision, R.G.S. and J.J.C.H.; project administration, .G.S. and J.J.C.H.; funding acquisition,

.G.S. and J.J.C.H. CORRESPONDING AUTHORS Correspondence to Rogelio González-Sarmiento or Juan Jesús Cruz-Hernández. ETHICS DECLARATIONS COMPETING INTERESTS J.J.C.H. declares conflict of

interest in advisory role: Merck, MSD, BMS, Novartis and conferences with fee: Merck, BMS, MSD, Roche, Astra Zeneca, Novartis. However, the funders had no role in the design of the study; in

the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. The rest of the authors declare no competing interest.

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mutations predict outcome in a cohort of head and neck squamous cell carcinoma (HNSCC) patients within a clinical trial. _Sci Rep_ 10, 16634 (2020).

https://doi.org/10.1038/s41598-020-72927-2 Download citation * Received: 05 April 2020 * Accepted: 13 August 2020 * Published: 06 October 2020 * DOI:

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