Translational Oncology 13 (2020) 100778 Contents lists available at ScienceDirect Translational Oncology journal homepage: www.elsevier.com/locate/tranon Comprehensive Characterization of the Mutational Landscape in Localized Anal Squamous Cell Carcinoma Lucía Trilla-Fuertes a, Ismael Ghanem b, Joan Maurel c, Laura G-Pastrián d,e, Marta Mendiola e,f, Cristina Peña d, Rocío López-Vacas g, Guillermo Prado-Vázquez a, Elena López-Camacho g, Andrea Zapater-Moros g, Victoria Heredia f,h, Miriam Cuatrecasas i, Pilar García-Alfonso j, Jaume Capdevila k, Carles Conill l, Rocío García-Carbonero m, Karen E. Heath n, Ricardo Ramos-Ruiz o, Carlos Llorens p, Ángel Campos-Barros n, ⁎ Angelo Gámez-Pozo g, Jaime Feliu b,f,q, , Juan Ángel Fresno Vara f,g, ⁎ a Biomedica Molecular Medicine SL, C/Faraday 7, 28049, Madrid, Spain b Medical Oncology Department, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain c Medical Oncology Department, Hospital Clinic of Barcelona, Translational Genomics and Targeted Therapeutics in Solid Tumors Group, IDIBAPS, University of Barcelona, Carrer de Villarroel 170, 08036, Barcelona, Spain d Pathology Department, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain e Molecular Pathology and Therapeutic Targets Group, Hospital Universitario La Paz-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain f Biomedical Research Networking Center on Oncology-CIBERONC, ISCIII, Av. Monforte de Lemos 5, 28029, Madrid, Spain g Molecular Oncology & Pathology Lab, Institute of Medical and Molecular Genetics-INGEMM, Hospital Universitario La Paz-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain h Translational Oncology Lab, Hospital Universitario La Paz-IdiPAZ, Paseo de la Castellana 261, 28046, Madrid, Spain i Pathology Department, Hospital Clínic Universitari de Barcelona, Carrer de Villarroel 170, 08036, Barcelona, Spain j Medical Oncology Department, Hospital General Universitario Gregorio Marañón, C/ Dr Esquerdo 46, 28007, Madrid, Spain k Medical Oncology Service, Vall Hebron University Hospital. Vall Hebron Institute of Oncology (VHIO), Passeig de la Vall d'Hebron, 119-129, 08035, Barcelona, Spain l Radiotherapy Oncology Department, Hospital Clínic Universitari de Barcelona, Carrer de Villarroel 170, 08036, Barcelona, Spain m Medical Oncology Department, Hospital Universitario 12 de Ocubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), UCM, CNIO, CIBERONC, Av. Córdoba s/n, 28041, Madrid, Spain n Institute of Medical and Molecular Genetics, IdiPAZ, Hospital Universitario La Paz /& CIBERER, Unit 753, ISCIII, Paseo de la Castellana 261, 28046, Madrid, Spain o Genomics Unit Cantoblanco, Parque Científico de Madrid, C/ Faraday 7, 28049, Madrid, Spain p Biotechvana SL, Parque Científico de Madrid, C/ Faraday 7, 28049, Madrid, Spain q Cátedra UAM-Amgen, Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain A R T I C L E I N F O A B S T R A C T Article history: Anal squamous cell carcinoma (ASCC) is a rare neoplasm. Chemoradiotherapy is the standard of care, with no thera- Received 25 November 2019 peutic advances achieved over the past three decades. Thus, a deeper molecular characterization of this disease is still Accepted 2 April 2020 necessary. We analyzed 46 paraffin-embedded tumor samples from patients diagnosed with primary ASCC by exome Available online xxxx sequencing. A bioinformatics approach focused in the identification of high-impact genetic variants, which may act as drivers of oncogenesis, was performed. The relation between genetics variants and prognosis was also studied. The list of high-impact genetic variants was unique for each patient. However, the pathways in which these genes are involved are well-known hallmarks of cancer, such as angiogenesis or immune pathways. Additionally, we determined that ge- netic variants in BRCA2, ZNF750, FAM208B, ZNF599, and ZC3H13 genes are related with poor disease-free survival in ASCC. This may help to stratify the patient's prognosis and open new avenues for potential therapeutic intervention. In conclusion, sequencing of ASCC clinical samples appears an encouraging tool for the molecular portrait of this disease. Introduction Since the 1970s, the standard treatment has consisted of a combination of 5-fluorouracil (5FU) with mitomycin C or cisplatin and radiotherapy Anal squamous cell carcinoma (ASCC) is a rare tumor. In 2019, an esti- [2,3]. Despite this treatment being very effective for early-stage tumors, mated 8300 new cases will occur in the United States, representing approx- the disease-free survival (DFS) rate in T3-T4 or N+ tumors ranges between imately 2.5% of all gastrointestinal cancers [1]. 40% and 70% [4,5]. Patients diagnosed with ASCC do not benefit from ⁎ Address all correspondence to: Jaime Feliu, Medical Oncology Department, Hospital Universitario La Paz, Paseo de la Castellana, 261, 28046, Madrid, Spain. or Juan Ángel Fresno Vara, Molecular Oncology & Pathology Lab, Hospital Universitario La Paz, Paseo de la Castellana, 261, 28046, Madrid, Spain. E-mail addresses: jaimefeliu@hotmail.com, (J. Feliu), juanangel.fresno@salud.madrid.org. (J.Á.F. Vara). http://dx.doi.org/10.1016/j.tranon.2020.100778 1936-5233/© 2020 The Authors. Published by Elsevier Inc. on behalf of Neoplasia Press, Inc. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 targeted therapy or immunotherapy. In addition, there is insufficient infor- Bioinformatics Exome Sequencing Data Processing mation on molecular prognostic or response prediction factors. With the improvements in high-throughput molecular techniques, it is The quality of the ES experiments was verified using FASTQC (http:// possible to study several variables instead of the classical gene-centered www.bioinformmatics.babraham.ac.uk/projects/fastqc). view. These technical advances allow for the study of multiple genetic alter- First, adaptors were removed using Cutadapt [13], and FASTQ files ations from clinical samples. Exome sequencing (ES) has contributed to the were filtered by quality using PrinSeq [14]; both tools are included in the identification of new disease-causing genes and is now being incorporated GPRO Suite (Biotechvana SL) [15]. Alignment of the sequences was into clinical practice [6]. Since the first work reporting ES [7], numerous achieved using the human genome h19 as the reference genome. The medical sequencing projects have faced the challenge of identifying molec- tools BWA [16], Samtools [17], and Picard Tools (http://picard. ular alterations related to rare diseases or cancers [8]. The Cancer Genome sourceforge.net) were used. Variant calling was performed using the Atlas is making huge strides in characterizing several tumor types by com- MuTect tool from the GATK4 package [18] combined with PicardTools, prehensive molecular techniques. However, ASCC is not included because first, to create a panel of normal samples and, second, for the variant calling this project is focused on more frequent tumors. [19]. The panel of normal samples was built using 11 samples from Iberian Previous studies have analyzed metastatic or primary ASCC tumors by exomes from 1000 genomes (http://www.ncbi.nlm.nih.gov/sra/), and it ES or even by gene panels in an attempt to describe the most frequent alter- was used to discard germline variants. ations in this disease. These studies established PIK3CA as a frequently mu- tated gene in ASCC [9–12]. However, the exact relationship between Prioritization of High-Impact Genetic Variants genetic variations, phenotype, and tumor evolution is currently unknown. In this study, we analyzed 46 ASCC formalin-fixed, paraffin-embedded With the aim of establishing the genetic variants that may act as drivers (FFPE) samples. On the one hand, we characterized the main genetic vari- of the disease, the VarSEQ software (Golden Helix) was used. Variant Call ants present in these tumors and the main biological processes in which Format files were filtered according to strict criteria: a reading depth of at these genes are involved, while on the other hand, we identified those least 15×, a gnomAD global frequency <1%, high impact (frameshift, genes in which the presence of a genetic variant is associated with DFS in splice variants, and stop-loss and stop-gain variants), and a detectable pres- ASCC. ence in at least 15% of the reads [20]. Materials and Methods Filtering of the Most Frequent Genetic Variants in Our Cohort Patients On the other hand, with the aim of establishing the most frequent high- and moderate-impact variants, genetic variants were further annotated Forty-six treatment-naive FFPE samples from patients diagnosed with using Variant Effect Predictor (VEP) [21] and the Varsome database localized ASCC were analyzed by ES. All tumor samples were reviewed (https://varsome.com/). Then, the information provided by VEP was by an experienced pathologist. All the samples contained at least 70% inva- used to filter the genetic variants. The filtering criteria were a frequency sive tumor cells. Informed consent was obtained for all patients, and the in the general population, according to the gnomAD database, of less than study was approved by the Hospital Universitario La Paz Research Ethics 1%; a high or moderate impact; and the presence of the variant in at least Committee. Patients were required to have a histologically confirmed diag- 10% of the patients in our cohort. nosis of ASCC; be 18 years of age or older; have an Eastern Cooperative On- cology Group performance status score from 0 to 2; have not received prior radiotherapy or chemotherapy for this malignancy; and present with no dis- Visual Validation of the High-Impact Genetic Variants tant metastasis. Demographic characteristics related to the tumor and the treatments were collected. The presence of human papillomavirus (HPV) The BAM files containing the prioritized variants were verified using infection was determined using CLART HPV2 (Genomica). Alamut Visual v2.11 (Interactive Biosoftware). DNA Isolation Pathway Annotation One 10-mm section from each FFPE sample was deparaffinized, and Pathway annotation of the genes containing the prioritized variants was DNA was extracted with GeneRead DNA FFPE Kit (Qiagen), following the done using PANTHER database (http://www.pantherdb.org/) and DAVID manufacturer's instructions. Once eluted, DNA was frozen at −80°C until webtool [22] selecting GO-BP as the category and Homo sapiens as the use. background. Library Preparation, Exome Capture, and Illumina Sequencing Genes Associated with Prognosis ES from 46 FFPE samples of ASCC was performed. Purified DNA was From the list of genes with high- or moderate-impact variants identified quantified by Picogreen, and mean size was determined by gel electropho- by VEP, those genes in which the presence of a genetic variant was associ- resis. Genomic DNA was fragmented by mechanical means (Bioruptor) to a ated with DFS were identified using BRB Array Tools developed by Dr. mean size of approximately 200 bp. Then, DNA samples were repaired, Richard Simon's team [23]. Genes associated with DFS were selected ac- phosphorylated, A-tailed, and ligated to specific adaptors, followed by cording to their P values by a Kaplan-Meier analysis. DFS was defined as PCR-mediated labeling with Illumina-specific sequences and sample- the time from primary tumor surgery until local and/or distant tumor re- specific barcodes (Kapa DNA library generation kit). lapse. For survival analyses, only the 41 patients treated with chemoradio- Exome capture was performed using the VCRome system (capture size therapy were included (Figure 1). of 37 Mb, Roche Nimblegen) under a multiplexing of eight samples per cap- ture reaction. Capture was strictly carried out following manufacturer's in- Statistical Analyses structions. After capture, libraries were purified, quantified, and titrated by real-time PCR before sequencing. Samples were then sequenced to an ap- Statistical analyses were performed using GraphPad Prism v6 and IBM proximate coverage of 4.5 Gb per sample in Illumina-NextSeq NS500 SPSS Statistics v20. All P values were two-tailed, and statistical significance (Illumina Inc.) using 150-cycle (2 × 75) high-output cartridges. was set as .05 or less. 2 L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 Figure 1. Workflow followed in this study. Results Three patients who were initially treated only with surgery and one patient treated with radiotherapy alone were excluded from the survival analyses Patient Cohort (Table 1). Forty-six FFPE samples of ASCC were analyzed by ES. Twenty-eight sam- Exome Sequencing Experiments ples were from patients included in the VITAL clinical trial (GEMCAD-09- 02, NCT01285778). These patients were treated with panitumumab, 5FU, The mean coverage obtained in ES experiments was >42.6×, with the and mitomycin C, concomitantly with radiotherapy. The remaining 18 pa- exception of one sample with a coverage of 3.57× that was excluded tients were retrospectively included from the clinical practice in Hospital from subsequent analyses. Once this sample was dismissed, the remaining Universitario La Paz and Hospital Clinic. Fourteen patients were treated samples presented a mapping efficiency of between 90% and 98% with with cisplatin-5FU or mitomycin C-5FU, concomitantly with radiotherapy. the exception of one sample (75.4%). The human exome has >195,000 ex- onic regions, out of which only 23,021 (11.21%) were not mapped in any sample. Table 1 Patient Clinical Characteristics Relevant Genes and Their Associated Genetic Variants Number of Patients Percentage (%) Number of patients 46 100% VarSEQ and Alamut were used to filter and visualize the variants that Age at diagnosis (median and range) 61 (41-86) may play a significant role in the development of ASCC. For this purpose, Age at diagnosis (mean) 61 we studied all genetic variants that caused a high impact in their respective Gender Male 23 50% gene. A total of 333 high-impact variants across 312 genes in the 45 pa- Female 23 50% tients were prioritized by the VarSEQ software. HPV The list of the implicated genes with high-impact variants is shown in 16 26 57% Supplementary Table 1. Other subtypes 8 17% Within the high-impact variants, the most frequent type of alteration Negative 6 13% Unknown 6 13% was the nonsense substitution which introduces a premature STOP codon HIV (Table 2). Positive 2 4% Negative 44 96% Lymph node status Table 2 N0 19 41% Description of the Type of High-Impact Alterations Detected by N positive 24 52% WES Analysis Unknown 3 7% Type of Alteration Frequency TNM stage I 3 7% Duplications 16 (4.8%) II 16 35% Insertions 32 (9.6%) III 27 58% Deletions 55 (16.4%) Treatment Nonsense substitutions 204 (62%) Chemoradiotherapy 14 30% Splice site substitutions 19 (6%) Chemoradiotherapy-panitumumab 28 61% Intronic deletions 2 (0.6%) Other 4 9% Intronic substitutions 2 (0.6%) 3 L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 Figure 2. List of high-impact genetic variants identified by VarSEQ in our cohort in more than one patient. The principal alterations identified by these analyses were different be- and moderate-impact genetic variants were analyzed. After filtering by tween patients; i.e., each patient presented a unique set of high-impact ge- VEP results, 382 genes were found to present at least one high- or netic variants. However, in some cases, the genes affected by these high- moderate-impact genetic variant in at least 10% of the patients in our co- impact alterations were common. The list of these genes is shown in Supple- hort (Supplementary Table 3). The functions associated with these 382 mentary Table 2 and Figure 2. genes were cytoskeleton, DNA repair, adhesion, and chromatin binding. PIK3CA was mutated in 40% of the patients, FBXW7 in 16%, FAT1 in Ontology Analysis of the High-Impact Genetic Variants Identified 18%, and ATM in 27% of the patients. The most frequent variants found in PIK3CA are rs104886003 (seven patients), classified as a variant of un- With the aim of identifying the pathways affected by the genetic alter- certain significance in Varsome, and rs121913273 (three patients), classi- ations, PANTHER and DAVID databases were used. The most frequently im- fied as likely pathogenic by the same database. plicated pathways were intracellular signal transduction (22% of the genes, 24% of the patients in the cohort), immune (20% of the genes, 15% of the patients), and apoptosis (17% of the genes, 15% of the patients) pathways, Genetic Variants Associated with Prognosis in ASCC although there were also relatively frequent alterations in genes implicated in angiogenesis (11% of the genes, 11% of the patients), metabolism (11% With the aim of determining the genes associated with relapse in ASCC, of the genes, 9% of the patients), chromatin modification (8% of the genes, a Kaplan-Meier analysis was performed. This analysis showed that, in this 11% of the patients), EGFR signaling (8% of the genes, 7% of the patients), cohort, the presence of a high- or moderate-impact genetic variant in or Wnt signaling pathways (8% of the genes, 11% of the patients) (Figure BRCA2, ZNF750, FAM208B, ZNF599, and ZC3H13 was associated with 3). poor disease-free survival (Figure 4). The genetic variants detected in these genes are summarized in Table 3. Presenting more than one genetic Characterization of the Most Frequently Mutated Genes in Our Cohort variant in any of these genes implied a worse DFS (P = .001) (Figure 5). Pa- tients without genetic variants or with only a single genetic variant in these With the aim of characterizing the most frequently mutated genes in genes did not reach the median DFS, and DFS percentages at 60 months ASCC, genetic variants were annotated using VEP, and genes with high- were 54% and 29%, respectively. The median DFS in those patients with Figure 3. Pathways in which genes presenting high-impact genetic variants are involved. 4 L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 Figure 4. Survival curves for those patients whose high- and moderate-impact genetic variants are associated with DFS. two or more genetic variant in these genes was 7 months, and DFS percent- Varsome databases. The rs121913273 variant has been described as likely age at 60 months was 86%. pathogenic in esophageal and squamous cell carcinoma of the head and neck and in uterine cervical neoplasms (VCV000376244.2). Our results Discussion are comparable with the percentage observed in previous studies trying to identify the predominant genetic variants in ASCC [9–12]. Cacheux ASCC is a relatively rare type of cancer, although its incidence has in- et al. established variants in PIK3CA as a frequent alteration (20.3%) in creased in recent years. The management of these patients consists of mito- this type of cancer [10]. Chung et al. studied 70 patients and described re- mycin C combined with 5FU chemotherapy and radiotherapy, but not all current alterations in 40 genes such as PIK3CA (40%), FBXW7 (13%), PTEN patients obtain a benefit from these treatments. For this reason, it is neces- (14%), and RICTOR (9%) [12]. Both studies included localized but also sary to delve deeper into the molecular characterization of this disease, metastatic ASCC. Morris et al. analyzed metastatic ASCC samples combin- with the objective of identifying biomarkers and new potential therapeutic ing ES and gene panels. They confirmed that PIK3CA is commonly mutated targets. In this study, a cohort of 46 ASCC patients was studied by ES, and a in ASCC (29%), and they used a xenograft model to test EGFR and PIK3CA list of genes with high-impact genetic variants that may be drivers of onco- inhibitors with a decrease in tumor growth [11]. In a later work, Cacheux genesis processes was identified. In addition, a characterization of the most et al. performed ES on 20 ASCC patients and described PIK3CA (25%), frequently mutated genes with high- and moderate-impact variants was FBXW7 (15%), and FAT1 (15%) as frequently mutated genes, and TRIP12 performed. Finally, five genes in which the presence of a genetic variant (15%), and chromatin remodeling as a pathway playing an important role was associated with DFS were identified. in ASCC [9]. In this study, 46 ASCC paraffin samples were analyzed by ES. The anal- In contrast to the gene panel-based analyses, the nondirected ES ap- ysis of FFPE samples using next-generation sequencing has been challeng- proach made it possible to propose a list of genetic variants which may ing due to the DNA fragmentation and the artificial alterations of the play an important role in the development of the disease and to identify sequence caused by the fixation process. However, paired comparisons be- five genes in which the presence of a genetic variant is associated with tween fresh-frozen tissue and FFPE samples showed that although DNA DFS. Moreover, this analysis replicated the identification of genetic variants damage in FFPE samples was evident, the results of fresh-frozen tissue in some genes previously described in ASCC, such as FBWX7, but also sug- and FFPE samples sequencing were comparable [24]. gested the involvement of novel genes, such as ZNF750. PIK3CA variants with a well-established functional effect were identi- In addition, we found that 16% of the patients presented a high- or fied in 40% of our cohort samples. This value is consistent with that re- moderate-impact variant in FBXW7, 18% in FAT1, and 27% in ATM. A re- ported in previous studies [11,12]. The most frequent PIK3CA variants markable finding was the presence of high-impact genetic variants of the were rs121913273 and rs104886003, both described in the COSMIC and FBXW7 gene in four patients. FBXW7 is a cell cycle key regulator, and its 5 L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 Table 3 Genetic Variants Associated with Disease-Free Survival in ASCC. Gene Chromosomal Location Number of Mutated Samples % Genetic Variants cDNA Level Protein Level BRCA2 chr13 8 18% chr13_32914858_G/T NM_000059.3:c.6366G > T p.(Met2122Ile) chr13_32936775_G/A NM_000059.3:c.7921G > A p.(Glu2641Lys) chr13_32972631_-/TAGAC NM_000059.3:c.9980_9981insTAGAC p.(Lys3327Asnfs*15) chr13_32900790_G/A NM_000059.3:c.631+ 40G > A Not predictable chr13_32936713_T/C NM_000059.3:c.7859 T > C p.(Val2620Ala) chr13_32914516_−/G NM_000059.3:c.6024dup p.(Gln2009Alafs*9) chr13_32968918_C/T NM_000059.3:c.9349C > T p.(His3117Tyr) chr13_32953641_A/G NM_000059.3:c.8942A > G p.(Glu2981Gly) ZNF750 chr17 4 9% chr17_80788075_C/T NM_024702.2:c.2115G > A p.(Ala705=) chr17_80789547_C/− NM_024702.2:c.784del p.(Ala262Leufs*104) chr17_80789802_C/A NM_024702.2:c.529G > T p.(Glu177*) chr17_80789503_G/C NM_024702.2:c.828C > G p.(Tyr276*) ZNF599 chr19 6 13% chr19_35249946_C/G NM_001007248.2:c.1760G > C p.(Arg587Thr) chr19_35250950_T/A NM_001007248.2:c.756A > T p.(Glu252Asp) chr19_35251215_C/T NM_001007248.2:c.491G > A p.(Gly164Asp) chr19_35250352_C/T NM_001007248.2:c.1354G > A p.(Glu452Lys) chr19_35260373_C/T NM_001007248.2:c.106G > A p.(Glu36Lys) chr19_35250567_G/T NM_001007248.2:c.1139C > A p.(Ser380*) ZC3H13 chr13 6 13% chr13_46616368_C/− NM_015070.4:c.270del p.(Asn91Thrfs*37) chr13_46539442_C/T NM_015070.4:c.4447G > A p.(Asp1483Asn) chr13_46542026_CGCG/− NM_015070.4:c.3931_3934del p.(Glu1314Glyfs*48) chr13_46563072_G/A NM_015070.4:c.1105C > T p.(Arg369Cys) chr13_46584507_G/A NM_015070.4:c.722C > T p.(Ser241Phe) chr13_46563125_C/T NM_015070.4:c.1052G > A p.(Arg351Gln) FAM208B chr10 6 13% chr10_5784388_T/C NM_001321783.1:c.2656 T > C p.(Leu886=) chr10_5781712_G/A NM_001321783.1:c.1579G > A p.(Val527Ile) chr10_5762722_G/C NM_001321783.1:c.31G > C p.(Glu11Gln) chr10_5782394_C/A NM_001321783.1:c.2261C > A p.(Ala754Glu) chr10_5789623_G/C NM_001321783.1:c.4239G > C p.(Glu1413Asp) chr10_5781667_G/C NM_001321783.1:c.1534G > C p.(Glu512Gln) function as a tumor suppressor is well known [25]. Genetic variants in this With the aim of determining the most frequent alterations in our cohort gene have been previously described in 15% of ASCC patients. FAT1, which and identifying variants related to the progression of the disease, less re- presented high-impact variants in two patients of our cohort, has also been strictive filtering criteria were used. This led us to the identification of described as a tumor suppressor gene involved in the Wnt pathway [26]. high- or moderate-impact genetic variants in 382 genes. These genes are FAT1 genetic variants have also been described in ASCC patients [9]. mainly involved in DNA repair, chromatin binding, cytoskeleton, and adhe- Strikingly, each patient presented a unique set of high-impact variants. sion processes. Chromatin remodeling was previously suggested as a pro- The most frequent alterations were nonsense stop-gain variants. However, cess with an important role in ASCC [9]. the pathway analysis showed that, despite the individual variant diversity Survival analyses identified five genes associated with DFS. ZNF750 between patients, the affected biological pathways were shared between was recently associated with prognosis in esophageal squamous cell carci- patients. This has already been seen in other tumors from The Cancer Ge- noma [29,30]. Variants of BRCA2 were also associated with esophageal nome Atlas studies [27]. Moreover, the implicated pathways are tradition- squamous cell carcinoma and head and neck squamous cell carcinoma, ally associated with tumor progression and cancer development such as both of which are related to HPV infection [31,32]. Moreover, BRCA muta- angiogenesis or metabolism pathways [28]. The presence of high-impact tions are associated with response to PPAR inhibitors in pancreatic, breast, variants in the EGFR pathway in 7% of patients or in immunological pro- and ovarian tumors [33–35]. Therefore, the prevalence of BRCA2 muta- cesses may be relevant when proposing new therapies such as EGFR- tions may have therapeutic implications. Other genes associated with DFS targeted therapy or immunotherapy. (FAM208B, ZNF599, and ZC3H13) had not been previously associated with cancer. The two analyses performed offer complementary insights. The most re- strictive filtering identified those genetic variants with a highly deleterious impact upon the resulting protein and proposed a list of variants that may be related to tumor development. In addition, based on the affected genes, the principal altered pathways involved were identified. In contrast, the alternative filtering pipeline yielded the most frequent variants in our cohort, some of them also associated with tumor progression and DFS. ES analysis allowed us to identify candidate genes potentially involved in the etiology of ASCC without the bias of previous knowledge. On the other hand, our study led to the identification of genes that presented ge- netic variants associated with DFS in ASCC. As far as we know, this is the first time that an analysis of these characteristics has been performed. An- other important point is the sample size. With ASCC being a rare tumor, it is difficult to gather a representative and homogeneous cohort. Our study Figure 5. Survival curves obtained after considering the presence of high- and analyzed 46 samples, the second largest cohort in ASCC from localized tu- moderate-impact genetic variants in BRCA2, FAM208B, ZNF750, ZNF599, and mors treated with chemoradiotherapy so far. ZC3H13 (0 genetic variant, n = 23 patients; 1 genetic variant, n = 11 patients; 2- This study has some limitations. A validation with an independent co- 5 genetic variants, n = 7 patients). hort, especially for the prognostic genetic variants, is still needed. Unlike 6 L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 the traditional genetic diseases, where an analysis pipeline is well research support from Pfizer and BMS, all beyond the scope of this work. established, in tumor sequencing data, it is still necessary to establish a con- The other authors declare no conflicts of interests. sensus analysis workflow. Authors' Contributions Conclusions All the authors have directly participated in the preparation of this man- To summarize, we analyzed 46 ASCC tumor samples by ES, an impor- uscript and have approved the final version submitted and declare no ethi- tant cohort taking into account that ASCC is a rare tumor. Our study iden- cal conflicts of interest. R. L.-V., M. M., E. L.-C., and V. H. contributed the tified a set of variants having a high impact upon the corresponding DNA extraction. M. M. and V. H. contributed the HPV determination. L. protein and proposed a list of candidate genes which may play an important G.-P., C. P., and M. C. contributed the pathological review of the samples. role in the etiology of ASCC. On the other hand, our study yielded a list of R. R.-R. and C. L. contributed the sequencing analyses. I. G., J. M., P. G.- genetic variants apparently associated with poor disease progression. In A., J. C., C. C., R. G.-C., and J. F. contributed the clinical data and the anal- conclusion, sequencing of ASCC clinical samples seems to be a promising yses related. L. T.-F., I. G., A. G.-P., G. P.-V., and A. Z.-M. contributed in the tool for the molecular characterization of this pathology, which may aid design of the study and the statistical and prognosis analyses. L. T.-F., A. G.- the clinician in the prognostic stratification of patients and open new ave- P., A. C.-B., and K. E. H. contributed to high-impact genetic variants analy- nues for drug development. sis. L. T.-F. drafted the manuscript. I. G., J. M., J. A. F. V., and J. F. conceived Supplementary data to this article can be found online at https://doi. of the study and participated in its design and interpretation. A. G.-P., J. M., org/10.1016/j.tranon.2020.100778. J. A. F. V., and J. F. reviewed the manuscript. J. F. and J. A. F. V. coordi- nated the study. All authors read and approved the final manuscript. Declarations References Ethics Approval and Consent to Participate [1] R.L. Siegel, K.D. Miller, A. Jemal, Cancer statistics, 2019, CA Cancer J. Clin. 69 (1) This study was approved by the Ethics Committee of Hospital (2019) 7–34, Epub 2019/01/08 https://doi.org/10.3322/caac.21551, PubMed Universitario La Paz (PI-1926). Informed consents were obtained for all pa- 30620402. [2] A. Benson, A. Venook, M. Al-Hawary, L. Cederquist, Y. Chen, K. Ciombor, et al., Anal tients included in this study. carcinoma, version 2.2018, NCCN clinical practice guidelines in oncology, J Natl Compr Canc Netw (2018) 852–871. Availability of Supporting Data [3] R. Glynne-Jones, P.J. Nilsson, C. Aschele, V. Goh, D. Peiffert, A. Cervantes, et al., Anal cancer: ESMO-ESSO-ESTRO clinical practice guidelines for diagnosis, treatment and follow-up, Eur. J. Surg. Oncol. 40 (10) (2014) 1165–1176, https://doi.org/10.1016/j. The exome sequencing data are available in SRA (https://www.ncbi. ejso.2014.07.030, PubMed 25239441. nlm.nih.gov/sra) under the name PRJNA573670. [4] L.L. Gunderson, K.A. Winter, J.A. Ajani, J.E. Pedersen, J. Moughan, A.B. Benson, et al., Long-term update of US GI intergroup RTOG 98-11 phase III trial for anal carcinoma: survival, relapse, and colostomy failure with concurrent chemoradiation involving fluo- Funding rouracil/mitomycin versus fluorouracil/cisplatin, J Clin Oncol 30 (35) (2012) 4344–4351, Epub 2012/11/13 https://doi.org/10.1200/JCO.2012.43.8085, PubMed This study was supported by Instituto de Salud Carlos III, Spanish Econ- 23150707 PubMed Central. PMCPMC3515768. [5] J.A. Ajani, K.A. Winter, L.L. Gunderson, J. Pedersen, A.B. Benson, C.R. Thomas, et al., Prog- omy and Competitiveness Ministry, Spain and co-funded by the FEDER pro- nostic factors derived from a prospective database dictate clinical biology of anal cancer: the gram “Una forma de hacer Europa” (PI15/01310), a Roche Farma funding, intergroup trial (RTOG 98-11), Cancer 116 (17) (2010) 4007–4013, https://doi.org/10. Amgen and a grant from Grupo Español Multidisciplinar en Cáncer 1002/cncr.25188, PubMed 20564111 PubMed Central. PMCPMC3831519. [6] M. Tetreault, E. Bareke, J. Nadaf, N. Alirezaie, J. Majewski, Whole-exome sequencing as Digestivo (GEMCAD1403). L. T.-F. is supported by the Spanish Economy a diagnostic tool: current challenges and future opportunities, Expert. Rev. Mol. Diagn. and Competitiveness Ministry (DI-15-07614). G. P.-V. and E. L.-C. are sup- 15 (6) (2015) 749–760, Epub 2015/05/09 https://doi.org/10.1586/14737159.2015. ported by the Consejería de Educación, Juventud y Deporte of Comunidad 1039516, PubMed 25959410. [7] S. Ng, E. Turner, P. Robertson, S. Flygare, A. Bigham, C. Lee, et al., Targeted capture and de Madrid (IND2017/BMD7783); A. Z.-M. is supported by a Jesús Antolín massively parallel sequencing of 12 human exomes, Nature 461 (7261) (2009) Garciarena fellowship from IdiPAZ. The funders played no role in the 272–276, Epub 2009 Aug 16 https://doi.org/10.1038/nature08250. study design, data collection and analysis, decision to publish or prepara- [8] B. Rabbani, M. Tekin, N. Mahdieh, The promise of whole-exome sequencing in medical genetics, J. Hum. Genet. 59 (1) (2014) 5–15, Epub 2013/11/07 https://doi.org/10. tion of the manuscript. 1038/jhg.2013.114, PubMed 24196381. [9] W. Cacheux, V. Dangles-Marie, E. Rouleau, J. Lazartigues, E. Girard, A. Briaux, et al., Exome Declaration of Interest sequencing reveals aberrant signalling pathways as hallmark of treatment-naive anal squa- mous cell carcinoma, Oncotarget 9 (1) (2018) 464–476, Epub 2017/12/08 10.18632/ oncotarget.23066, PubMed 29416628 PubMed Central. PMCPMC5787481. J. A. F. V. and A. G.-P. are shareholders in Biomedica Molecular Medi- [10] W. Cacheux, E. Rouleau, A. Briaux, P. Tsantoulis, P. Mariani, M. Richard-Molard, et al., cine SL. L. T.-F. and G. P.-V. are employees of Biomedica Molecular Medi- Mutational analysis of anal cancers demonstrates frequent PIK3CA mutations associated cine SL. J. C. has received scientific consulting fees (speaker and advisory with poor outcome after salvage abdominoperineal resection, Br J Cancer 114 (12) (2016) 1387–1394, Epub 2016/05/24 https://doi.org/10.1038/bjc.2016.144, PubMed roles) from Novartis, Pfizer, Ipsen, Exelixis, Bayer, Eisai, Advanced Acceler- 27219019 PubMed Central. PMCPMC4984471. ator Applications, Amgen, Sanofi, and Merck Serono and research support [11] V. Morris, X. Rao, C. Pickering, W.C. Foo, A. Rashid, K. Eterovic, et al., Comprehensive from Eisai, Novartis, Ipsen, Astrazeneca, Pfizer, and Advanced Accelerator genomic profiling of metastatic squamous cell carcinoma of the anal canal, Mol Cancer Res 15 (11) (2017) 1542–1550, Epub 2017/08/07 https://doi.org/10.1158/1541- Applications. I. G. has received fees and/or travel expenses from Roche, 7786.MCR-17-0060, PubMed 28784613 PubMed Central. PMCPMC5991496. Sanofi, Merck, Servier, Amgen, and Sirtflex, and consulting fees from [12] J.H. Chung, E. Sanford, A. Johnson, S.J. Klempner, A.B. Schrock, N.A. Palma, et al., Merck and Sanofi. J. F. has received honoraria for consulting and advisory Comprehensive genomic profiling of anal squamous cell carcinoma reveals distinct genomically defined classes, Ann. Oncol. 27 (7) (2016) 1336–1341, Epub 2016/04/ role in Amgen, Ipsen, Eissai, Merck, Roche, and Novartis; research funding 06 https://doi.org/10.1093/annonc/mdw152, PubMed 27052656. from Merck. and travel expenses from Amgen and Servier. J. M. reports [13] M. Martin, Cutadapt removes adapter sequences from high-throughput sequencing grants (clinical trial lead principal investigator) from Merck, Amgen, and reads, EMBnetjournal 17 (1) (2011) 10–12, https://doi.org/10.14806/ej.17.1.200. [14] R. Schmieder, R. Edwards, Quality control and preprocessing of metagenomic datasets, Servier and grants (project lead principal investigator) from NanoString, Bioinformatics 27 (6) (2011) 863–864. Incyte, and Biocartis and also reports personal fees from Sirtex, Pierre- [15] R. Futami, A. Muñoz-Pomer, J. Viu, R. Domínguez-Escribá, L. Covelli, G. Bernet, et al., Fabre, Shire, Astra-Zeneca, Bayer, Servier, Sanofi, and Roche, outside the GPRO The professional tool for annotation, management and functional analysis of scope of this work. R. G.-C. declares having provided consulting services omic databases, Biotechvana Bioinformatics: SOFT3. (2011). [16] H. Li, R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform, and/or received fees from AAA, Amgen, Bayer, Ipsen, Lilly, Merck, MSD, Bioinformatics 25 (14) (2009) 1754–1760, https://doi.org/10.1093/bioinformatics/ Novartis, PharmaMar, Pfizer, Roche, and Sanofi-Aventis and has received btp324 Epub 2009 May 18. 7 L. Trilla-Fuertes et al. Translational Oncology 13 (2020) 100778 [17] H. Li, B. Handsaker, B. Wysoker, T. Fennell, J. Ruan, N. Homer, et al., The Sequence activation, Nat Genet 45 (3) (2013) 253–261, Epub 2013/01/27 https://doi.org/10. Alignment/Map format and SAMtools, Bioinformatics 25 (2009) 2078–2079. 1038/ng.2538, PubMed 23354438 PubMed Central. PMCPMC3729040. [18] A. McKenna, M. Hanna, E. Banks, A. Sivachenko, K. Cibulskis, A. Kernytsky, et al., The [27] M.H. Bailey, C. Tokheim, E. Porta-Pardo, S. Sengupta, D. Bertrand, A. Weerasinghe, et al., Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA Comprehensive characterization of cancer driver genes and mutations, Cell 174 (4) sequencing data, Genome Res. 20 (9) (2010) 1297–1303, https://doi.org/10.1101/gr. (2018) 1034–1035, https://doi.org/10.1016/j.cell.2018.07.034, PubMed 30096302. 107524.110 Epub 2010 Jul 19. [28] D. Hanahan, R.A. Weinberg, Hallmarks of cancer: the next generation, Cell 144 (5) [19] K. Cibulskis, M. Lawrence, S. Carter, A. Sivachenco, D. Jaffe, C. Sougnez, et al., Sensitive (2011) 646–674, https://doi.org/10.1016/j.cell.2011.02.013, PubMed 21376230. detection of somatic point mutations in impure and heterogeneous cancer samples, Nat. [29] R. Otsuka, Y. Akutsu, H. Sakata, N. Hanari, K. Murakami, M. Kano, et al., ZNF750 ex- Biotechnol. 31 (3) (2013) 213–219, https://doi.org/10.1038/nbt.2514 Epub 2013 Feb pression is a potential prognostic biomarker in esophageal squamous cell carcinoma, 10. Oncology 94 (3) (2018) 142–148, Epub 2017/12/08 https://doi.org/10.1159/ [20] Jalali Sefid Dasthi M, J G. A practical guide to filtering and prioritizing genetic variants. 000484932, PubMed 29216641 PubMed Central. PMCPMC5969074. BioTechniques 2017;62(1):18–30. doi: https://doi.org/10.2144/000114492. [30] M. Hazawa, D.C. Lin, H. Handral, L. Xu, Y. Chen, Y.Y. Jiang, et al., ZNF750 is a lineage- [21] Cunningham F, Amode MR, Barrell D, Beal K, Billis K, Brent S, et al. Ensembl 2015. specific tumour suppressor in squamous cell carcinoma, Oncogene 36 (16) (2017) Nucleic Acids Res. 2015;43(Database issue):D662-9. Epub 2014/10/28. doi: https:// 2243–2254, Epub 2016/11/07 https://doi.org/10.1038/onc.2016.377, PubMed doi.org/10.1093/nar/gku1010. PubMed PMID: 25352552; PubMed Central PMCID: 27819679 PubMed Central. PMCPMC5415641. PMCPMC4383879. [31] M.R. Akbari, R. Malekzadeh, P. Lepage, D. Roquis, A.R. Sadjadi, K. Aghcheli, et al., Mu- [22] dW Huang, B.T. Sherman, R.A. Lempicki, Systematic and integrative analysis of large tations in Fanconi anemia genes and the risk of esophageal cancer, Hum. Genet. 129 (5) gene lists using DAVID bioinformatics resources, Nat. Protoc. 4 (1) (2009) 44–57, (2011) 573–582, Epub 2011/01/30 https://doi.org/10.1007/s00439-011-0951-7, https://doi.org/10.1038/nprot.2008.211, PubMed 19131956. PubMed 21279724. [23] R. Simon, Roadmap for developing and validating therapeutically relevant genomic [32] G.M. Low, D.S. Thylur, V. Yamamoto, U.K. Sinha, The effect of human papillomavirus classifiers, J. Clin. Oncol. 23 (29) (2005) 7332–7341, Epub 2005/09/06 https://doi. on DNA repair in head and neck squamous cell carcinoma, Oral Oncol. 61 (2016) org/10.1200/JCO.2005.02.8712, PubMed 16145063. 27–30, Epub 2016/08/18 https://doi.org/10.1016/j.oraloncology.2016.08.002, [24] E. Oh, Y.L. Choi, M.J. Kwon, R.N. Kim, Y.J. Kim, J.Y. Song, et al., Comparison of accuracy PubMed 27688101. of whole-exome sequencing with formalin-fixed paraffin-embedded and fresh frozen tis- [33] M. Munroe, J. Kolesar, Olaparib for the treatment of BRCA-mutated advanced ovarian sue samples, PLoS One 10 (12) (2015) e0144162, Epub 2015/12/07 https://doi.org/10. cancer, Am. J. Health Syst. Pharm. 73 (14) (2016) 1037–1041, https://doi.org/10. 1371/journal.pone.0144162 PubMed. 26641479. PubMed Central. PMCPMC4671711. 2146/ajhp150550, PubMed 27385701. [25] S. Takeishi, K.I. Nakayama, Role of Fbxw7 in the maintenance of normal stem cells [34] M. Robson, C. Goessl, S. Domchek, Olaparib for metastatic germline BRCA-mutated and cancer-initiating cells, Br J Cancer 111 (6) (2014) 1054–1059, Epub 2014/05/ breast cancer, N. Engl. J. Med. 377 (18) (2017) 1792–1793, https://doi.org/10.1056/ 22 https://doi.org/10.1038/bjc.2014.259, PubMed 24853181 PubMed Central. NEJMc1711644, PubMed 29091556. PMCPMC4453837. [35] T. Golan, P. Hammel, M. Reni, E. Van Cutsem, T. Macarulla, M.J. Hall, et al., Maintenance [26] L.G. Morris, A.M. Kaufman, Y. Gong, D. Ramaswami, L.A. Walsh, Ş. Turcan, et al., Re- olaparib for germline BRCA-mutated metastatic pancreatic cancer, N Engl J Med. (2019) current somatic mutation of FAT1 in multiple human cancers leads to aberrant Wnt https://doi.org/10.1056/NEJMoa1903387, Epub 2019/06/02. PubMed 31157963. 8