MayMolecular basis of targeted therapy in T/NK- cell lymphoma/leukemia: A comprehensive genomic and immunohistochemical analysis of a panel of 33 cell linesRufino Mondejar 1 2Cristina Pe rez 1 2Arantza Onaindia 0 2Nerea Martinez 1 2Julia Gonza lez- Rinco n 2Helena Pisonero 1 2Jose Pedro Vaque 1 2Laura Cereceda 1 2Miguel Santibañez 2Margarita Sa nchez-Beato 2Miguel Angel Piris 0 1 20 Pathology Department, Hospital Universitario Marqu eÂs de Valdecilla , Santander , Spain , 3 Lymphoma Research Group (Medical Oncology Service) Oncohematology Area, Instituto InvestigacioÂn Sanitaria Puerta de Hierro-Majadahonda (IDIPHIM) , Madrid , Spain , 4 Instituto de Biomedicina y BiotecnologÂõa de Cantabria , IBBTEC (CSIC , Universidad de Cantabria), Departamento de BiologÂõa Molecular, Universidad de Cantabria , Santander , Spain , 5 Universidad de Cantabria-IDIVAL , Santander , Spain1 Cancer Genomics Laboratory, Instituto de Investigaci oÂn Marqu eÂs de Valdecilla, IDIVAL , Santander , Spain2 Editor: Renato Franco, Seconda Universita degli Studi di Napoli , ITALYT and NK-cell lymphoma is a collection of aggressive disorders with unfavorable outcome, in which targeted treatments are still at a preliminary phase. To gain deeper insights into the deregulated mechanisms promoting this disease, we searched a panel of 31 representative T-cell and 2 NK-cell lymphoma/leukemia cell lines for predictive markers of response to targeted therapy. To this end, targeted sequencing was performed alongside the expression of specific biomarkers corresponding to potentially activated survival pathways. The study identified TP53, NOTCH1 and DNMT3A as the most frequently mutated genes. We also found common alterations in JAK/STAT and epigenetic pathways. Immunohistochemical analysis showed nuclear accumulation of MYC (in 85% of the cases), NFKB (62%), p-STAT (44%) and p-MAPK (30%). This panel of cell lines captures the complexity of T/NK-cell lymphoproliferative processes samples, with the partial exception of AITL cases. Integrated mutational and immunohistochemical analysis shows that mutational changes cannot fully explain the activation of key survival pathways and the resulting phenotypes. The combined integration of mutational/expression changes forms a useful tool with which new compounds may be assayed.IntroductionT and NK-cell leukemia/lymphoma is a collection of aggressive disorders with unfavorableoutcome accounting for 10±15% of non-Hodgkin lymphomas. The most recent WHOAES-FEDER to MSB (Plan Estatal I+D+I 2013-2016:PI14/00221), and the AsociacioÂn Española Contrael CaÂncer (AECC to MAP). CP is a recipient of aSara Borrel postdoctoral contract from ISCIII(CD13/00088). RM is a recipient of a Rio Hortegaspecialised healthcare post-training contract(ISCIII, CM15/00186). JG-R is a recipient of aniPFIS predoctoral fellowship (IFI14/00003) fromISCIII-MINECO-AES-FEDER (Plan Estatal I+D+I2013-2016). MSB was supported by a MiguelServet contract (CP11/00018) from theISCIIIMINECO-AES-FEDER (Plan Nacional I+D+I20082011), and currently holds a Miguel Servet IIcontract (CPII16/00024), supported byISCIIIMINECO-AES-FEDER (Plan Estatal I+D+I20132016) and FundacioÂn de InvestigacioÂn BiomeÂdicaPuerta de Hierro. JPV was supported by a RamoÂn yCajal research program (RYC-2013-14097). http://www.rticc.org/, http://www.isciii.es/. The fundershad no role in study design, data collection andanalysis, decision to publish, or preparation of themanuscript.Competing interests: The authors have declaredthat no competing interests exist.Classification established 23 subtypes grouped by clinical presentation [1]. T-cell lymphomas(TCLs) are the most common group, and within this subgroup the major subtypes areperipheral TCL (PTCL), not otherwise specified (PTCL-NOS), angioimmunoblastic T cell lymphoma(AITL), anaplastic lymphoma kinase (ALK)-positive anaplastic large cell lymphoma (ALCL)and ALK-negative ALCL. Among these, PTCL-NOS is the most widespread subtypeworldwide and typically represents a variant that does not meet the criteria for other subtypes [2].On the other hand, T-cell acute lymphoblastic leukemia (T-ALL), a T-cell neoplasm oflymphoblasts, accounts for about 15% and 25% of acute lymphoblastic leukemia (ALL) cases inpediatric and adult cohorts, respectively.Nowadays, PTCL diagnosis requires the integration of information about clinical status,morphology, immunohistochemistry, flow cytometry, cytogenetics and molecular biology[3,4]. The treatment approach of PTCL has customarily been based on the knowledgeaccumulated from diffuse large B cell lymphoma treatment. The standard first-line therapy stillconsists of cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) or a CHOP-likeregimen, although the outcome is poor, with frequent relapses and low 5-year overall survivaland failure-free survival [5,6]. Routine introduction of targeted therapy for PTCL and otherTCL types still requires the identification of solid predictor biomarkers that relate clinical andphenotypic variability to existing therapeutic options.Thus, it is possible that, having molecularly characterized the individual TCL cases, wecould identify potential candidates for targeted therapy. In this study, we integrated targeteddeep sequencing with immunohistochemical analysis in a large cohort of 33 well-characterizedT/NK-cell lymphoma/leukemia cell lines. This has provided insights into the specificmolecular mechanisms underlying the pathogenesis of TCL and into the potential implications forfuture diagnosis and targeted therapy of TCL patients.Material and methodsCell lines33 T/NK-cell lymphoma/leukemia cell lines were obtained from various sources (S1 Table).These included T-ALL (n = 20), ALCL (n = 5), CTCL (cutaneous T-cell lymphoma, n = 3),ATLL (adult T-cell lymphoblastic leukemia, n = 2), NK lymphoma subtypes (n = 2), andTlarge granular lymphoma (T-LGL, n = 1) PTCL subtypes. Cell lines were cultured under basalconditions following the manufacturer's instructions. All cell lines were purchased orauthenticated before use and were tested for mycoplasma (MycoAlert™ mycoplasma detection kit;Lonza, Basel, Switzerland).Targeted amplicon-based enrichment and sequencing16 genes were selected for sequencing. This set consisted of genes that are known potentiallyto play a role in tumorigenesis [7±20] (S2 Table). The gene panel was designed by IlluminaDesign Studio and comprised 547 amplicons, each of 170±190 bp. Libraries were preparedusing the Illumina TruSeq Custom Amplicon Kit v1.5 and sequenced on a MiSeq sequencer(Illumina, San Diego, CA), following the manufacturer's instructions. Variants were calledusing MiSeq Reporter and RUbioSeq [21], employing the default settings, and were visuallyinspected on IGV (www.broadinstitute.org/igv/). Variants were annotated with Variant EffectPredictor (GRCh37, http://grch37.ensembl.org/Tools/VEP). Known SNPs with an allelicfrequency greater than 1% in public databases (dbSNP138, 1000 Genomes Project, ExomeSequencing Project, Exome Aggregation Consortium) were filtered out. In order to avoidfalse-positive calls, we performed duplicates with separate library preparation and sequencingin independent runs. Only variants called by both runs were considered.2 / 14Tissue microarrays and immunostainingTissue microarrays (TMAs) were designed as described previously [22]using two 0.6-mmtissue cores per case, taken from formalin-fixed, paraffin-embedded archival tumor blocks. Allimmunostaining was done following standardized protocols. The panel of antibodies waschosen on the basis of their biological and clinical relevance in clinical classification andpathogenesis of TCL as well as with respect to their pharmacological implications (S3 Table). Newantibodies were titrated with four or five dilutions (with an at least 2-fold difference betweeneach) on the whole-mount tissue sections, according to the manufacturer's recommendation.Each TMA was analyzed by at least two independent pathologists, who considered either thecytoplasmic or membranous staining intensity, or the percentage of positive nuclei. Specificthresholds are described in the S3 Table.Statistical analysisUnsupervised hierarchical clustering with an average linkage algorithm was performed usingGene-E software v3.0.206 (www.broadinstitute.org/cancer/software/GENE-E). TheMannWhitney U or Kruskal-Wallis tests were used to determine group differences. The chi-squareor Fisher exact test was used as appropriate to determine associations between the presence orabsence of markers. Statistical analyses were carried out using SPSS for Windows version 15(Chicago, IL).Other resources and repositoriesWe consulted repositories with genomic data of TCL cell lines in order to ensure a broadlandscape. Specifically, we unified genomic data from the CCLE (Cancer Cell Line Encyclopedia,http://www.broadinstitute.org/ccle), the COSMIC Cell Lines Project (http://cancer.sanger.ac.uk/cell_lines) [23], EGAS00001000268 [24] from the European Genome-Phenome Archive(https://www.ebi.ac.uk/ega/), and data from four exomes produced by our group in HH,HUT-78, MJ and Myla cell lines (S4 Table). Sequencing data have been deposited in theSequence Read Archive (SRA) under accession reference SUB2029552.ResultsVariants identified by target enrichment and deep sequencing33 T/NK-cell lymphoma/leukemia cell lines were subjected to target amplicon-basedenrichment and sequencing of the 16 selected genes (see details in S2 Table). On average, 91% of theamplicons in the panel studied had a depth of >100X, with 73% exceeding 500X. Afterconservative filtering, we validated 102 variants (S5 Table) in 15 genes from 30/33 samples (91%),including missense (74), frameshift (11), nonsense (8), splicing (7), and 3Â/5Â- UTR (2)variants (S5 Table and Fig 1). A mean of 3.1 SNVs per cell line (range: 0±11) was observed. We didnot detect any SNVs in CCR4, CD28 or IDH2.TP53, NOTCH1 and DNMT3A were altered in 72.7%, 42.4% and 18.2% of the cell lines,respectively. TP53 harbored a large number of mutations, most of which were missense (21/33)and truncating mutations (7/33) (Figs 1 and 2A). Residues 248 and 273 were recurrentlymutated, which produced different alterations at the nucleotide level. The P12-Ichikawa cellline carried a double-heterozygous mutation in the same nucleotide (c.743G>A/C; p.Arg248Gln/p.Arg248Pro) and seven cell lines had two or more TP53 variants.NOTCH1 mainly harbored missense and truncating mutations (26 and 5 of 32 SNVs,respectively). We found more than one variant of NOTCH1 per TCL cell line in six cell lines,with up to eight variants in MOLT4. NOTCH1 SNVs were distributed throughout the whole3 / 14gene. We found only truncating mutations in the PEST domain; these are known to lead toaberrantly prolonged signaling in the nucleus in this domain [25].We detected 17 SNVs associated with the JAK/STAT pathway. JAK3 and JAK1 harboredseven and five variants, five and four of them being missense mutations, respectively. Threeand two variants were found in STAT5B and STAT3, respectively. Interestingly, Jurkatharbored the three STAT5B and the one STAT3 variants.With respect to epigenetic-related genes, DNMT3A was the most frequently mutated genewith high diversity: we found seven variants, four of which were missense, two were truncatingvariants and one was located in the 5ÂUTR region. TET2 had three missense variants and onetruncating variant, whereas IDH2 harbored no SNVs.We found little variation in the other genes. We detected the same mutation (p.V385M) inHPB-ALL and MHH-TALL-2 in the TNFRSF1B gene. Two mutations were detected in PLCG1(both in the DND-41 cell line), DDX3X and RHOA and one was found in SYK (S5 Table).Variants identified by subtypeAmong the cell lines, the T-ALL subtype carried the greatest frequency of SNVs (85/102, 4.25SNVs per cell line). ATLL and CTCL both harbored 4/102 variants (2 and 1.33 SNVs per cellline, respectively) (Fig 1). We detected four and two variants (one SNV per cell line) in theALCL and NK subtypes. TP53 and NOTCH1 mutations co-occurred in the T-ALL (11/20)and T-LGL cell lines (1/1), but not in any other subtype. NK cell lines featured solely TP53mutations. Mutations in genes involved in the JAK/STAT pathway were most frequentlyFig 1. Mutational landscape of TCL cell lines. The results of targeted deep sequencing of 16 genes in 20T-ALL (black), 5 ALCL (dark grey), 3 CTCL (medium grey), 2 NK (light grey), 2 ATLL (diagonal lines) and oneT-LGL (dots) cell lines. Mutated genes (rows) are arranged in decreasing order of mutation frequency. Celllines (columns) are arranged from left to right on the basis of their mutational frequency following generanking. HTLV-1-positive cell lines (green) and translocation t(2;5)(p23;q35) (ALK +, dark blue) are showed.4 / 14mutated in T-ALL. In this respect, four JAK1 mutations, six JAK3 mutations, and all STAT3and STAT5B mutations occurred in T-ALL cell lines. Only one mutation in the JAK1 and inJAK3 genes was detected in CTCL, which co-occurred in HUT-78. Similarly, the epigeneticgenes DNMT3A and TET2, most of which were related to T-ALL, were found to be altered inthese subtypes. Furthermore, DNMT3A was mutated in one ALCL and ATLL case each. Twonovel PLCG1 mutations were found in a single case of T-ALL (p.Q152H and p.D1199N).Expression of immunomarkersIn order to identify a number of potentially deregulated disease actionable mechanisms, weused a set of 26 immunomarkers chosen not only on the basis of their biological and clinicalrelevance to clinical classification and pathogenesis of TCL, but also for their pharmacologicalimplications (S3 Table). Hence, as shown in Fig 3, the NFKB pathway was activated in roughlyhalf of the cell lines, both the canonical (p50/p65) and the non-canonical (p52/RelB), asindicated by the nuclear expression of the NFKB subunits. Nuclear NFAT was found in eight cases(24.2%), ERK and STATs proteins were activated in 30% and in 21±33% of cell lines,respectively, with STAT3 being the most frequent (Fig 3). The CD30 surface marker was expressedin 60.6% of cases, while CD10 and CD56 were detected in only 21.2% and 6.1%, respectively.Tumor suppressors p53 and RB were detected in 57.6% and 81.8% of cell lines, respectively.Notch1 was found in the nucleus (the active form) in five cases (15.2%) and its downstreamtarget MYC was detected in 84.8%. GATA-3, ROR-gamma and TIA-1 showed positiveexpression in 15, 14 and 9 cell lines (45.5%, 42.4% and 27.2%), respectively (Fig 3).Unsupervised hierarchical clustering analysis of tissue microarray immunostainingIn order to classify our cases by specific immunohistochemical biomarkers, and to identifytheir potential association with pathogenesis, an unsupervised hierarchical clustering analysisFig 2. Mapping of variants in a TCL gene panel. Schematic of the alterations encoded by SNVs in TP53, NOTCH1, DNMT3A, JAK1,JAK3, STAT3 and STAT5B. Type of variation and disease are represented by color and shape, respectively. TAD: transactivationdomain; PRD: proline-rich domain; TD: tetramerization domain; C-term: C-terminal domain; HD: heterodimerization domain; TM:transmembrane domain; RAM: Rbp-associated molecule domain; ANK: ankyrin domain; PEST: proline (P), glutamic acid (E), serine(S), threonine (T) degradation domain; ZNF: zinc-finger domain; Mtase: methyltransferase domain.5 / 14Fig 3. Unsupervised hierarchical clustering analysis with 26 immunomarkers. Each row represents asingle cell line; each column represents a single immunomarker. Blue (score 0); white, weak immunostaining(score 1); light red (score 2); red, strong immunoreactivity (score 3); grey, missing data.(average linkage method) of the TMAs was undertaken. This produced a dendrogram with sixwell-defined clusters (Fig 3).Most of the groups were defined by specific biomarkers. All groups clearly showed positiveMYC and TCRBF1 expression, with the possible exception of group 6, which had limitedTCRBF1 expression. Group 1 had differential positive PD1 expression alongside activatedMAPK-ERK, GATA-3 and ROR-gamma-T. In group 2, the cluster featured broad RB staining(12/14) and heterogeneous expression of TP53, MAPK-ERK, NFAT and CD30. Group 3showed the strongest activation of both canonical and non-canonical NFKB pathways, withpositive expression of CD30 and NFAT in three of five cases. Group 4 showed characteristicconstitutive activation of STAT 1, 3 and 5, with positive CD30 expression in all cases, alongwith the heterogeneous activation of the NFKB pathway in three of the four of cell lines.Group 5, formed exclusively of ALCL-ALK+ cell lines, was defined by strongly positive ALK,BCL6, CD30 Granzyme B and TIA-1 expression, together with STAT 3 activation. Group 6,comprised the two NK cell lines included in the study. They showed a typical NK signaturepositive for the expression of CD56, Granzyme B and TIA-1. This small group also showedactivation of STAT 3 and 5. It is worth noting that under these circumstances, CTCL cell lineswere dispersed into different groups.6 / 14Immunohistochemistry (IHC) scores were dichotomized to enable associations betweenmarkers to be determined (IHC score >1 = positive; IHC score 1 = negative) in all cell lines(S7 Table). Overall, the presence of canonical and of non-canonical NFKB pathway markerswas significantly associated (p<0.05). Furthermore, the NFKB pathway was directly associatedwith NFAT (p65 RelA), CD30 (c-Rel) and GATA-3 (RelB), but inversely associated withRORgamma, p53 and RB (canonical NFKB), and MAPK-ERK (c-Rel). We found a positiveassociation of the presence of ALK, Granzyme B, TIA-1 and BCL-6 with the activation of STAT 3(p<0.05).Relation between IHC expression and mutational statusWe analyzed the relation between mutational status and expression of specificimmunomarkers. We subdivided TP53 status into wild type, and missense and truncating mutation group.The expression of p53 was strongly associated with the presence of missense mutationscompared with wild type and truncating mutations (p<0.001), (S1 Fig). However, we did not findany differences between NOTCH1 status and Notch1 (S1 Fig) or MYC expression. In the caseof MYC, 28/33 cell lines showed positive MYC expression, so we can conclude that MYCexpression is not dependent on NOTCH1 mutational status. Likewise, it is important to notethat JAK mutations were not associated with the expression of their downstream targets. Onlythree of ten (30%) cell lines with mutated JAK showed STAT activation, as defined by nuclearstaining. By contrast, ten out of 23 (43.5%) cell lines with JAK wild type showed STATactivation (S2 Fig).DiscussionOur growing knowledge about the molecular basis of T- and NK-cell lymphoma is leading to abetter understanding of their pathogenesis and is helping refine the subclassification of TCL.Nevertheless, despite this progress, targeted therapy is still in a preliminary phase. The resultspresented here can help identify the more commonly deregulated mechanisms drivingtumorigenesis in TCL, and provide a useful tool for analyzing the interaction between gene mutationsand the activation of key survival pathways.However, the panel of TCL cell lines tested has some limitations inherent to the difficulty ofgenerating cell lines derived from particular T-cell lymphoma subtypes, notably AITL andPTCL-NOS. The panel is more representative for T-ALL, ATLL, CTCL, ALCL-ALK+ and NKsubtypes. Despite these limitations, our results show that most T-cell lymphoma subtypesshare mutations and activation of some essential pathways, such as JAK-STAT, NFKB, NFAT,chromatin regulation and others.In this study we have examined 16 genes related to TCL pathogenesis [7±20], selectedbecause of the presence of somatic mutations identified in previous studies, or due to theirimportance in TCL biology. We have identified 102 variants. A review of the data available inpublic repositories validated 64 of these SNVs (S6 Table) and identified 4 SNVs that were notpicked up by our algorithm. On the other hand, 27 SNVs found in public repositories were notdetected by our amplicon-based enrichment method. This discrepancy highlights howdifferent methods may yield different results.TP53 was the mutated gene in our cell lines (72.7%). Truncating and missense mutationswere correlated with low and high levels of p53 expression, respectively. The NOTCH1 genewas also frequently mutated, with five truncating mutations located in the PEST domain. Onlythe MOLT-4 cell line showed a high level of expression of Notch1; it was not expressed in theother cell lines (DND-41, HPB-ALL, KE-37 and PF-382). Whereas KE-37 cell line harboredonly one mutation in the PEST domain, the DND-41, HPB-ALL, MOLT-4 and PF-382 cell7 / 14lines were also found to be mutated in the HD domain. The MOLT-4 cell line harbored eightmutations in NOTCH1, localized in different domains from the PEST and HD domain. It hasbeen reported that truncating mutations in the PEST domain lead to aberrantly prolongedsignaling in the nucleus, but are only functional in the presence of Notch ligands [25]. Mutationsin the HD domain, which comprises exons 26 and 27, destabilize the interaction between theN- and C-terminal HD subunits, resulting in increased signaling through eitherligand-independent or ligand-hypersensitive activation of Notch1, or in the displacement of theprocessing site for ADAM cleavage, allowing for constitutive ligand-independent metalloproteaseprocessing [25]. Mutations in other domains need to be functionally elucidated. Therefore,understanding the complexity and consequences of Notch activation is critical for definingoptimal therapeutic strategies targeting the Notch pathway.Mutations in the JAK/STAT pathway have been reported in PTCL patients [11,12,20]. Wefound 17 different mutations in 12 cell lines, which enabled us to detect mutations in JAK1and JAK3 genes in 27.3% of the cell lines analyzed. HUT-78 showed mutations in JAK1 andJAK3 pseudokinase domains [20] and MOLT-14 in JAK1 the pseudokinase domain.Mutations in these domains have been widely reported and are usually associated with increaseddownstream signaling in some hematological malignancies as well as in solid tumors. Thus, ithas been shown that JAK pseudokinases are autoinhibitory domains that keep the kinasedomain inactive until receptor dimerization stimulates transition to an active state.Nonetheless, these three cell lines showed no activation of STAT proteins. This lack of agenotypephenotype correlation between mutations in the pseudokinase domain and STAT expression(S1 Fig) can be explained by the basal conditions (e.g., without cytokines) in which the cellswere cultured [26]. Mutations in the JAK1 kinase domain were found in three cases(HPBALL, MHH-TALL-2 and MOTN-1 cell lines). It is important to note that the HPB-ALL andMHH-TALL-2 cell lines shared the same mutation (p.Q966V), but STAT was activated onlyin the MHH-TALL-2 cell line. The molecular significance of these mutations is not easy tointerpret, since they could act in a receptor-dependent or independent manner with respect toactivation. Therefore, although JAK inhibitors (JAKis) constitute a new therapeutic option forthe treatment of PTCL patients [20,26], further studies are needed to elucidate the relationbetween mutations and the activation of the JAK/STAT pathway as well as the mechanisms ofJAKi resistance.Mutations of epigenetic regulators are so common in PTCL that they constitute one of thelargest groups of mutation, including those affecting the splicing machinery, signalingpathways and transcription factors [2]. Mutations in DNMT3A and TET2 were found in 18.2% and9.1% of our panel of cell lines, respectively. DNMT3A encodes a protein that catalyzesmethylation and demethylation of DNA, depending on the microenvironment conditions [27]. Thespecific relevance of DNMT3A mutations to the cancer phenotype has not been explored,except for p.R882 mutations, which predict poor prognosis in acute myeloid leukemia [28,29].TET family proteins are known to play critical roles in DNA demethylation by converting5-mC to 5-hydroxymethylcytosine (5-hmC) in α-KG-dependent and a Fe (II)-dependentmanner [30]. Mutations that disrupt the catalytic domain or lead to a truncated TET2 havebeen linked to the development of hematological malignancies [31]. In fact, several leukemiaand lymphoma disorders have a TET2 that is mutated at notably high frequencies (chronicmyelomonocytic leukemia: 35±50%; AITL: 50±80%; PTCL-NOS: 40±50%) [32±37]. Someepigenetic drugs, such as vorinostat, belinostat and romidepsin, have been positioned as a secondline for TCL treatment, and have produced improved response rates.This study found two mutations in PLCG1 (encoding p.Gln152His and p.Asp1199Asn),both of which were present in a T-ALL cell line, DND-41. Recently, two hot-spot PLCG1mutations (encoding p.Ser345Phe and p.Ser520Phe) that enhance PLCγ activity have been8 / 14reported in T-cell lymphoma [19,38]. PLCG1 encodes phospholipase Cγ1 (PLCγ1), a keyregulator of proximal TCR signaling [38]. Interestingly, NFAT expression was positive in the cellsharboring PLCG1 mutations, suggesting that these mutations may promote deregulatedactivation of downstream PLCγ1 signaling. This activation may support the idea that specifictargeting of PLC downstream signaling, like tacrolimus, which acts as a calcineurin inhibitor, couldbe a therapeutic option for the treatment of patients with mutations in PLCG1.Two RHOA mutations were detected, both of them in T-ALL. Several research groupshave found frequent RHOA mutations, specifically the p.G17V mutation, in AITL and PTCLpatients [37,39]. Interestingly this p.G17V mutation appears to act similarly towell-characterized dominant negative mutations of RHOA, rather than as an activating mutation. Althoughnone of the mutations found in our study corresponds to the p.G17V variant, it is importantto note that both cells lines in our study that harbor RHOA mutations showed robust MYCexpression. In this context, it has been reported that there is cross-regulation between MYCand RhoA activation [40].From a therapeutic perspective, our results highlight important disease mechanisms thathave the potential to serve as targets for therapy. In this regard, the immunohistochemicalanalysis identified an activated NFKB pathway in about 62% of TCL cell lines (Fig 3). Recently,Odqvist and colleagues reported worse overall survival in PTCL patients associated withnuclear expression of classical or alternative NFKB components, implying thatNFKB-inducing kinase (NIK) silencing could be an effective target for abrogating the NIK-dependentNFKB activation [41]. The number of NIK inhibitors currently known is limited. A preclinicalstudy with ALK-negative ALCL patient cells [42] and CTCL cell lines [43] reported thepotential for the effective use of bortezomib, but a phase II study in refractory ATLL patients wascancelled because single-agent activity did not produce significant improvements in patients[44]. NIK and IKK inhibitors may be promising agents in T-cell lymphomas with an activatedNFKB pathway, but further studies and clinical trials are needed to evaluate the real potentialof these agents in single and combined usage.The second most frequently activated pathway in cell lines was JAK/STAT (42.4%), makingthe blockade of this pathway a promising means of treating TCL patients. Ruxolitinib has beendemonstrated to inhibit CTCL cell line proliferation at micromolar concentrations [20] andclinical trials are now ongoing (www.clinicaltrials.gov; accessed September 2016) in T-celllymphomas and other hematological malignancies. Tofacitinib has been shown to inhibitJAK3 in CTCL [45] but other JAK inhibitors such as momelotinib, baricitinib or filgotinibhave not been tested in TCL. Although few preclinical and clinical data are available, STAT3inhibitors, which seem to have a low toxicity profile [46], are other emerging targets.Unsupervised hierarchical clustering identified six groups on the basis of their expressionprofile. We can propose a targeted therapy that takes into account the mutational backgroundof each group (S2 Fig). Group 1 had a differentially positive PD1 expression and activatedMAPK-ERK. Given this, anti-PD1 and ERK inhibitors could constitute an effective therapyfor this group. A recent phase I study noted a response rate of 17% with nivolumab treatment[47]. Group 2, mainly composed of T-ALL cell lines, was complex because of theheterogeneous expression of immunomarkers, so different approaches should be adopted to treat suchpatients. Group 3 exhibited the strongest activation of both canonical and non-canonicalNFKB pathways, with strong expression of CD30, so drugs reducing NFKB activation andanti-CD30 may be good options for therapy. Interestingly, Group 4 showed activation ofSTAT 1, 3 and 5, with positive expression of CD30 in all cases. Anti-CD30 and JAKi therapycould be a treatment option for this group. Group 5, comprising the ALCL-ALK+ cell lines,was strongly positive for ALK, BCL6, CD30 and STAT3, so the treatment options couldinclude the use of anti-CD30 antibody and ALK and JAK inhibitors. In fact, brentuximab9 / 14vedotin, an anti-CD30 antibody, has recently been approved to treat ALCL patients [48]. Onthe other hand, the ALK inhibitor alectinib was tested in the ALCL-ALK+ cell lineKARPAS299 [49], in which it showed potent efficacy in a KARPAS-299 mouse xenograft. Group 6comprised only the two NK cell lines included in the study. As recently reported [50], JAKi couldbe a new option for treating this lymphoma subtype.In conclusion, the study identifies commonly deregulated pathways and genes in TCL,including JAK/STAT, NOTCH, NFKB and chromatin conformation. Activation of thesepathways is somehow the consequence of somatic mutation and other causes. Our findings mayhelp in the development of preclinical models for the evaluation of new targeted drugs.Supporting informationS1 Table. Cell lines used in the study.(XLSX)S2 Table. List of genes sequenced by amplicon-based methodology in cell lines.(XLSX)S3 Table. Antibodies used in immunohistochemical analysis.(XLSX)S4 Table. Public data consulted to validate our 16-gene panel.(XLSX)S5 Table. List of variants found in our panel of cell lines.(XLSX)S6 Table. List of variants found in public data.(XLSX)S7 Table. Association between immunomarkers. Probabilities of chi-square or Fisher exacttests for tests of association between pairs of the 26 immunomarkers used. Green and orangeindicate positive and negative associations, respectively.(XLSX)S1 Fig. Genotype-phenotype associations. a) Mutational status of TP53 was defined asNonsense/Frameshift (n = 10, blue), wild type (WT, n = 9, white) and missense (n = 15, red).Mutational status of NOTCH1 was defined as wild type (n = 20, White) and mutated (n = 14, red).Mutational status of JAK was defined to be JAK1 and/or JAK3 wild type (n = 23, white) ormutated (n = 11, red). The immunomarkers p53, NOTCH1 and STATs, are indicated in coloras in Fig 3. STATs was defined as the mean of p-STAT1, p-STAT3 and p-STAT5. b) Mean ofimmunomarkers with respect to mutational status. Error bars indicate the SEM (standarderror of mean).(TIF)S2 Fig. Mutational landscape of TCL cell lines grouped by unsupervised hierarchicalclustering.(TIF)AcknowledgmentsWe thank the Bioinformatics Unit of the CNIO for its support with bioinformatic analysis. Weespecially thank Jose Revert from the Instituto FormacioÂn e InvestigacioÂn HospitalUniversitario MarqueÂs de Valdecilla (IDIVAL), and the staff of the Biobank and the Pathology Service10 / 14at the Hospital Universitario MarqueÂs de Valdecilla for their exceptional work in samplecollection and organization.Author ContributionsConceptualization: MAP JPV NM MSB.Data curation: RM CP AO JGR.Formal analysis: RM CP MS.Investigation: RM CP AO JGR.Project administration: MAP.Resources: HP LC.Validation: RM CP.Writing ± original draft: RM CP MAP JPV.Writing ± review & editing: RM CP MAP JPV.11 / 1412 / 1413 / 141. Vose J , Armitage J , Weisenburger D , International TCLP ( 2008 ) International peripheral T-cell and natural killer/T-cell lymphoma study: pathology findings and clinical outcomes . J Clin Oncol 26 : 4124 ± 4130 . https://doi.org/10.1200/JCO. 2008 . 16 .4558 PMID: 186260052. Bene MC , Castoldi G , Knapp W , Ludwig WD , Matutes E , Orfao A , et al. 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MayMolecular basis of targeted therapy in T/NK- cell lymphoma/leukemia: A comprehensive genomic and immunohistochemical analysis of a panel of 33 cell linesRufino Mondejar 1 2Cristina Pe rez 1 2Arantza Onaindia 0 2Nerea Martinez 1 2Julia Gonza lez- Rinco n 2Helena Pisonero 1 2Jose Pedro Vaque 1 2Laura Cereceda 1 2Miguel Santibañez 2Margarita Sa nchez-Beato 2Miguel Angel Piris 0 1 20 Pathology Department, Hospital Universitario Marqu eÂs de Valdecilla , Santander , Spain , 3 Lymphoma Research Group (Medical Oncology Service) Oncohematology Area, Instituto InvestigacioÂn Sanitaria Puerta de Hierro-Majadahonda (IDIPHIM) , Madrid , Spain , 4 Instituto de Biomedicina y BiotecnologÂõa de Cantabria , IBBTEC (CSIC , Universidad de Cantabria), Departamento de BiologÂõa Molecular, Universidad de Cantabria , Santander , Spain , 5 Universidad de Cantabria-IDIVAL , Santander , Spain1 Cancer Genomics Laboratory, Instituto de Investigaci oÂn Marqu eÂs de Valdecilla, IDIVAL , Santander , Spain2 Editor: Renato Franco, Seconda Universita degli Studi di Napoli , ITALYT and NK-cell lymphoma is a collection of aggressive disorders with unfavorable outcome, in which targeted treatments are still at a preliminary phase. To gain deeper insights into the deregulated mechanisms promoting this disease, we searched a panel of 31 representative T-cell and 2 NK-cell lymphoma/leukemia cell lines for predictive markers of response to targeted therapy. To this end, targeted sequencing was performed alongside the expression of specific biomarkers corresponding to potentially activated survival pathways. The study identified TP53, NOTCH1 and DNMT3A as the most frequently mutated genes. We also found common alterations in JAK/STAT and epigenetic pathways. Immunohistochemical analysis showed nuclear accumulation of MYC (in 85% of the cases), NFKB (62%), p-STAT (44%) and p-MAPK (30%). This panel of cell lines captures the complexity of T/NK-cell lymphoproliferative processes samples, with the partial exception of AITL cases. Integrated mutational and immunohistochemical analysis shows that mutational changes cannot fully explain the activation of key survival pathways and the resulting phenotypes. The combined integration of mutational/expression changes forms a useful tool with which new compounds may be assayed.IntroductionT and NK-cell leukemia/lymphoma is a collection of aggressive disorders with unfavorableoutcome accounting for 10±15% of non-Hodgkin lymphomas. The most recent WHOAES-FEDER to MSB (Plan Estatal I+D+I 2013-2016:PI14/00221), and the AsociacioÂn Española Contrael CaÂncer (AECC to MAP). CP is a recipient of aSara Borrel postdoctoral contract from ISCIII(CD13/00088). RM is a recipient of a Rio Hortegaspecialised healthcare post-training contract(ISCIII, CM15/00186). JG-R is a recipient of aniPFIS predoctoral fellowship (IFI14/00003) fromISCIII-MINECO-AES-FEDER (Plan Estatal I+D+I2013-2016). MSB was supported by a MiguelServet contract (CP11/00018) from theISCIIIMINECO-AES-FEDER (Plan Nacional I+D+I20082011), and currently holds a Miguel Servet IIcontract (CPII16/00024), supported byISCIIIMINECO-AES-FEDER (Plan Estatal I+D+I20132016) and FundacioÂn de InvestigacioÂn BiomeÂdicaPuerta de Hierro. JPV was supported by a RamoÂn yCajal research program (RYC-2013-14097). http://www.rticc.org/, http://www.isciii.es/. The fundershad no role in study design, data collection andanalysis, decision to publish, or preparation of themanuscript.Competing interests: The authors have declaredthat no competing interests exist.Classification established 23 subtypes grouped by clinical presentation [1]. T-cell lymphomas(TCLs) are the most common group, and within this subgroup the major subtypes areperipheral TCL (PTCL), not otherwise specified (PTCL-NOS), angioimmunoblastic T cell lymphoma(AITL), anaplastic lymphoma kinase (ALK)-positive anaplastic large cell lymphoma (ALCL)and ALK-negative ALCL. Among these, PTCL-NOS is the most widespread subtypeworldwide and typically represents a variant that does not meet the criteria for other subtypes [2].On the other hand, T-cell acute lymphoblastic leukemia (T-ALL), a T-cell neoplasm oflymphoblasts, accounts for about 15% and 25% of acute lymphoblastic leukemia (ALL) cases inpediatric and adult cohorts, respectively.Nowadays, PTCL diagnosis requires the integration of information about clinical status,morphology, immunohistochemistry, flow cytometry, cytogenetics and molecular biology[3,4]. The treatment approach of PTCL has customarily been based on the knowledgeaccumulated from diffuse large B cell lymphoma treatment. The standard first-line therapy stillconsists of cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) or a CHOP-likeregimen, although the outcome is poor, with frequent relapses and low 5-year overall survivaland failure-free survival [5,6]. Routine introduction of targeted therapy for PTCL and otherTCL types still requires the identification of solid predictor biomarkers that relate clinical andphenotypic variability to existing therapeutic options.Thus, it is possible that, having molecularly characterized the individual TCL cases, wecould identify potential candidates for targeted therapy. In this study, we integrated targeteddeep sequencing with immunohistochemical analysis in a large cohort of 33 well-characterizedT/NK-cell lymphoma/leukemia cell lines. This has provided insights into the specificmolecular mechanisms underlying the pathogenesis of TCL and into the potential implications forfuture diagnosis and targeted therapy of TCL patients.Material and methodsCell lines33 T/NK-cell lymphoma/leukemia cell lines were obtained from various sources (S1 Table).These included T-ALL (n = 20), ALCL (n = 5), CTCL (cutaneous T-cell lymphoma, n = 3),ATLL (adult T-cell lymphoblastic leukemia, n = 2), NK lymphoma subtypes (n = 2), andTlarge granular lymphoma (T-LGL, n = 1) PTCL subtypes. Cell lines were cultured under basalconditions following the manufacturer's instructions. All cell lines were purchased orauthenticated before use and were tested for mycoplasma (MycoAlert™ mycoplasma detection kit;Lonza, Basel, Switzerland).Targeted amplicon-based enrichment and sequencing16 genes were selected for sequencing. This set consisted of genes that are known potentiallyto play a role in tumorigenesis [7±20] (S2 Table). The gene panel was designed by IlluminaDesign Studio and comprised 547 amplicons, each of 170±190 bp. Libraries were preparedusing the Illumina TruSeq Custom Amplicon Kit v1.5 and sequenced on a MiSeq sequencer(Illumina, San Diego, CA), following the manufacturer's instructions. Variants were calledusing MiSeq Reporter and RUbioSeq [21], employing the default settings, and were visuallyinspected on IGV (www.broadinstitute.org/igv/). Variants were annotated with Variant EffectPredictor (GRCh37, http://grch37.ensembl.org/Tools/VEP). Known SNPs with an allelicfrequency greater than 1% in public databases (dbSNP138, 1000 Genomes Project, ExomeSequencing Project, Exome Aggregation Consortium) were filtered out. In order to avoidfalse-positive calls, we performed duplicates with separate library preparation and sequencingin independent runs. Only variants called by both runs were considered.2 / 14Tissue microarrays and immunostainingTissue microarrays (TMAs) were designed as described previously [22]using two 0.6-mmtissue cores per case, taken from formalin-fixed, paraffin-embedded archival tumor blocks. Allimmunostaining was done following standardized protocols. The panel of antibodies waschosen on the basis of their biological and clinical relevance in clinical classification andpathogenesis of TCL as well as with respect to their pharmacological implications (S3 Table). Newantibodies were titrated with four or five dilutions (with an at least 2-fold difference betweeneach) on the whole-mount tissue sections, according to the manufacturer's recommendation.Each TMA was analyzed by at least two independent pathologists, who considered either thecytoplasmic or membranous staining intensity, or the percentage of positive nuclei. Specificthresholds are described in the S3 Table.Statistical analysisUnsupervised hierarchical clustering with an average linkage algorithm was performed usingGene-E software v3.0.206 (www.broadinstitute.org/cancer/software/GENE-E). TheMannWhitney U or Kruskal-Wallis tests were used to determine group differences. The chi-squareor Fisher exact test was used as appropriate to determine associations between the presence orabsence of markers. Statistical analyses were carried out using SPSS for Windows version 15(Chicago, IL).Other resources and repositoriesWe consulted repositories with genomic data of TCL cell lines in order to ensure a broadlandscape. Specifically, we unified genomic data from the CCLE (Cancer Cell Line Encyclopedia,http://www.broadinstitute.org/ccle), the COSMIC Cell Lines Project (http://cancer.sanger.ac.uk/cell_lines) [23], EGAS00001000268 [24] from the European Genome-Phenome Archive(https://www.ebi.ac.uk/ega/), and data from four exomes produced by our group in HH,HUT-78, MJ and Myla cell lines (S4 Table). Sequencing data have been deposited in theSequence Read Archive (SRA) under accession reference SUB2029552.ResultsVariants identified by target enrichment and deep sequencing33 T/NK-cell lymphoma/leukemia cell lines were subjected to target amplicon-basedenrichment and sequencing of the 16 selected genes (see details in S2 Table). On average, 91% of theamplicons in the panel studied had a depth of >100X, with 73% exceeding 500X. Afterconservative filtering, we validated 102 variants (S5 Table) in 15 genes from 30/33 samples (91%),including missense (74), frameshift (11), nonsense (8), splicing (7), and 3Â/5Â- UTR (2)variants (S5 Table and Fig 1). A mean of 3.1 SNVs per cell line (range: 0±11) was observed. We didnot detect any SNVs in CCR4, CD28 or IDH2.TP53, NOTCH1 and DNMT3A were altered in 72.7%, 42.4% and 18.2% of the cell lines,respectively. TP53 harbored a large number of mutations, most of which were missense (21/33)and truncating mutations (7/33) (Figs 1 and 2A). Residues 248 and 273 were recurrentlymutated, which produced different alterations at the nucleotide level. The P12-Ichikawa cellline carried a double-heterozygous mutation in the same nucleotide (c.743G>A/C; p.Arg248Gln/p.Arg248Pro) and seven cell lines had two or more TP53 variants.NOTCH1 mainly harbored missense and truncating mutations (26 and 5 of 32 SNVs,respectively). We found more than one variant of NOTCH1 per TCL cell line in six cell lines,with up to eight variants in MOLT4. NOTCH1 SNVs were distributed throughout the whole3 / 14gene. We found only truncating mutations in the PEST domain; these are known to lead toaberrantly prolonged signaling in the nucleus in this domain [25].We detected 17 SNVs associated with the JAK/STAT pathway. JAK3 and JAK1 harboredseven and five variants, five and four of them being missense mutations, respectively. Threeand two variants were found in STAT5B and STAT3, respectively. Interestingly, Jurkatharbored the three STAT5B and the one STAT3 variants.With respect to epigenetic-related genes, DNMT3A was the most frequently mutated genewith high diversity: we found seven variants, four of which were missense, two were truncatingvariants and one was located in the 5ÂUTR region. TET2 had three missense variants and onetruncating variant, whereas IDH2 harbored no SNVs.We found little variation in the other genes. We detected the same mutation (p.V385M) inHPB-ALL and MHH-TALL-2 in the TNFRSF1B gene. Two mutations were detected in PLCG1(both in the DND-41 cell line), DDX3X and RHOA and one was found in SYK (S5 Table).Variants identified by subtypeAmong the cell lines, the T-ALL subtype carried the greatest frequency of SNVs (85/102, 4.25SNVs per cell line). ATLL and CTCL both harbored 4/102 variants (2 and 1.33 SNVs per cellline, respectively) (Fig 1). We detected four and two variants (one SNV per cell line) in theALCL and NK subtypes. TP53 and NOTCH1 mutations co-occurred in the T-ALL (11/20)and T-LGL cell lines (1/1), but not in any other subtype. NK cell lines featured solely TP53mutations. Mutations in genes involved in the JAK/STAT pathway were most frequentlyFig 1. Mutational landscape of TCL cell lines. The results of targeted deep sequencing of 16 genes in 20T-ALL (black), 5 ALCL (dark grey), 3 CTCL (medium grey), 2 NK (light grey), 2 ATLL (diagonal lines) and oneT-LGL (dots) cell lines. Mutated genes (rows) are arranged in decreasing order of mutation frequency. Celllines (columns) are arranged from left to right on the basis of their mutational frequency following generanking. HTLV-1-positive cell lines (green) and translocation t(2;5)(p23;q35) (ALK +, dark blue) are showed.4 / 14mutated in T-ALL. In this respect, four JAK1 mutations, six JAK3 mutations, and all STAT3and STAT5B mutations occurred in T-ALL cell lines. Only one mutation in the JAK1 and inJAK3 genes was detected in CTCL, which co-occurred in HUT-78. Similarly, the epigeneticgenes DNMT3A and TET2, most of which were related to T-ALL, were found to be altered inthese subtypes. Furthermore, DNMT3A was mutated in one ALCL and ATLL case each. Twonovel PLCG1 mutations were found in a single case of T-ALL (p.Q152H and p.D1199N).Expression of immunomarkersIn order to identify a number of potentially deregulated disease actionable mechanisms, weused a set of 26 immunomarkers chosen not only on the basis of their biological and clinicalrelevance to clinical classification and pathogenesis of TCL, but also for their pharmacologicalimplications (S3 Table). Hence, as shown in Fig 3, the NFKB pathway was activated in roughlyhalf of the cell lines, both the canonical (p50/p65) and the non-canonical (p52/RelB), asindicated by the nuclear expression of the NFKB subunits. Nuclear NFAT was found in eight cases(24.2%), ERK and STATs proteins were activated in 30% and in 21±33% of cell lines,respectively, with STAT3 being the most frequent (Fig 3). The CD30 surface marker was expressedin 60.6% of cases, while CD10 and CD56 were detected in only 21.2% and 6.1%, respectively.Tumor suppressors p53 and RB were detected in 57.6% and 81.8% of cell lines, respectively.Notch1 was found in the nucleus (the active form) in five cases (15.2%) and its downstreamtarget MYC was detected in 84.8%. GATA-3, ROR-gamma and TIA-1 showed positiveexpression in 15, 14 and 9 cell lines (45.5%, 42.4% and 27.2%), respectively (Fig 3).Unsupervised hierarchical clustering analysis of tissue microarray immunostainingIn order to classify our cases by specific immunohistochemical biomarkers, and to identifytheir potential association with pathogenesis, an unsupervised hierarchical clustering analysisFig 2. Mapping of variants in a TCL gene panel. Schematic of the alterations encoded by SNVs in TP53, NOTCH1, DNMT3A, JAK1,JAK3, STAT3 and STAT5B. Type of variation and disease are represented by color and shape, respectively. TAD: transactivationdomain; PRD: proline-rich domain; TD: tetramerization domain; C-term: C-terminal domain; HD: heterodimerization domain; TM:transmembrane domain; RAM: Rbp-associated molecule domain; ANK: ankyrin domain; PEST: proline (P), glutamic acid (E), serine(S), threonine (T) degradation domain; ZNF: zinc-finger domain; Mtase: methyltransferase domain.5 / 14Fig 3. Unsupervised hierarchical clustering analysis with 26 immunomarkers. Each row represents asingle cell line; each column represents a single immunomarker. Blue (score 0); white, weak immunostaining(score 1); light red (score 2); red, strong immunoreactivity (score 3); grey, missing data.(average linkage method) of the TMAs was undertaken. This produced a dendrogram with sixwell-defined clusters (Fig 3).Most of the groups were defined by specific biomarkers. All groups clearly showed positiveMYC and TCRBF1 expression, with the possible exception of group 6, which had limitedTCRBF1 expression. Group 1 had differential positive PD1 expression alongside activatedMAPK-ERK, GATA-3 and ROR-gamma-T. In group 2, the cluster featured broad RB staining(12/14) and heterogeneous expression of TP53, MAPK-ERK, NFAT and CD30. Group 3showed the strongest activation of both canonical and non-canonical NFKB pathways, withpositive expression of CD30 and NFAT in three of five cases. Group 4 showed characteristicconstitutive activation of STAT 1, 3 and 5, with positive CD30 expression in all cases, alongwith the heterogeneous activation of the NFKB pathway in three of the four of cell lines.Group 5, formed exclusively of ALCL-ALK+ cell lines, was defined by strongly positive ALK,BCL6, CD30 Granzyme B and TIA-1 expression, together with STAT 3 activation. Group 6,comprised the two NK cell lines included in the study. They showed a typical NK signaturepositive for the expression of CD56, Granzyme B and TIA-1. This small group also showedactivation of STAT 3 and 5. It is worth noting that under these circumstances, CTCL cell lineswere dispersed into different groups.6 / 14Immunohistochemistry (IHC) scores were dichotomized to enable associations betweenmarkers to be determined (IHC score >1 = positive; IHC score 1 = negative) in all cell lines(S7 Table). Overall, the presence of canonical and of non-canonical NFKB pathway markerswas significantly associated (p<0.05). Furthermore, the NFKB pathway was directly associatedwith NFAT (p65 RelA), CD30 (c-Rel) and GATA-3 (RelB), but inversely associated withRORgamma, p53 and RB (canonical NFKB), and MAPK-ERK (c-Rel). We found a positiveassociation of the presence of ALK, Granzyme B, TIA-1 and BCL-6 with the activation of STAT 3(p<0.05).Relation between IHC expression and mutational statusWe analyzed the relation between mutational status and expression of specificimmunomarkers. We subdivided TP53 status into wild type, and missense and truncating mutation group.The expression of p53 was strongly associated with the presence of missense mutationscompared with wild type and truncating mutations (p<0.001), (S1 Fig). However, we did not findany differences between NOTCH1 status and Notch1 (S1 Fig) or MYC expression. In the caseof MYC, 28/33 cell lines showed positive MYC expression, so we can conclude that MYCexpression is not dependent on NOTCH1 mutational status. Likewise, it is important to notethat JAK mutations were not associated with the expression of their downstream targets. Onlythree of ten (30%) cell lines with mutated JAK showed STAT activation, as defined by nuclearstaining. By contrast, ten out of 23 (43.5%) cell lines with JAK wild type showed STATactivation (S2 Fig).DiscussionOur growing knowledge about the molecular basis of T- and NK-cell lymphoma is leading to abetter understanding of their pathogenesis and is helping refine the subclassification of TCL.Nevertheless, despite this progress, targeted therapy is still in a preliminary phase. The resultspresented here can help identify the more commonly deregulated mechanisms drivingtumorigenesis in TCL, and provide a useful tool for analyzing the interaction between gene mutationsand the activation of key survival pathways.However, the panel of TCL cell lines tested has some limitations inherent to the difficulty ofgenerating cell lines derived from particular T-cell lymphoma subtypes, notably AITL andPTCL-NOS. The panel is more representative for T-ALL, ATLL, CTCL, ALCL-ALK+ and NKsubtypes. Despite these limitations, our results show that most T-cell lymphoma subtypesshare mutations and activation of some essential pathways, such as JAK-STAT, NFKB, NFAT,chromatin regulation and others.In this study we have examined 16 genes related to TCL pathogenesis [7±20], selectedbecause of the presence of somatic mutations identified in previous studies, or due to theirimportance in TCL biology. We have identified 102 variants. A review of the data available inpublic repositories validated 64 of these SNVs (S6 Table) and identified 4 SNVs that were notpicked up by our algorithm. On the other hand, 27 SNVs found in public repositories were notdetected by our amplicon-based enrichment method. This discrepancy highlights howdifferent methods may yield different results.TP53 was the mutated gene in our cell lines (72.7%). Truncating and missense mutationswere correlated with low and high levels of p53 expression, respectively. The NOTCH1 genewas also frequently mutated, with five truncating mutations located in the PEST domain. Onlythe MOLT-4 cell line showed a high level of expression of Notch1; it was not expressed in theother cell lines (DND-41, HPB-ALL, KE-37 and PF-382). Whereas KE-37 cell line harboredonly one mutation in the PEST domain, the DND-41, HPB-ALL, MOLT-4 and PF-382 cell7 / 14lines were also found to be mutated in the HD domain. The MOLT-4 cell line harbored eightmutations in NOTCH1, localized in different domains from the PEST and HD domain. It hasbeen reported that truncating mutations in the PEST domain lead to aberrantly prolongedsignaling in the nucleus, but are only functional in the presence of Notch ligands [25]. Mutationsin the HD domain, which comprises exons 26 and 27, destabilize the interaction between theN- and C-terminal HD subunits, resulting in increased signaling through eitherligand-independent or ligand-hypersensitive activation of Notch1, or in the displacement of theprocessing site for ADAM cleavage, allowing for constitutive ligand-independent metalloproteaseprocessing [25]. Mutations in other domains need to be functionally elucidated. Therefore,understanding the complexity and consequences of Notch activation is critical for definingoptimal therapeutic strategies targeting the Notch pathway.Mutations in the JAK/STAT pathway have been reported in PTCL patients [11,12,20]. Wefound 17 different mutations in 12 cell lines, which enabled us to detect mutations in JAK1and JAK3 genes in 27.3% of the cell lines analyzed. HUT-78 showed mutations in JAK1 andJAK3 pseudokinase domains [20] and MOLT-14 in JAK1 the pseudokinase domain.Mutations in these domains have been widely reported and are usually associated with increaseddownstream signaling in some hematological malignancies as well as in solid tumors. Thus, ithas been shown that JAK pseudokinases are autoinhibitory domains that keep the kinasedomain inactive until receptor dimerization stimulates transition to an active state.Nonetheless, these three cell lines showed no activation of STAT proteins. This lack of agenotypephenotype correlation between mutations in the pseudokinase domain and STAT expression(S1 Fig) can be explained by the basal conditions (e.g., without cytokines) in which the cellswere cultured [26]. Mutations in the JAK1 kinase domain were found in three cases(HPBALL, MHH-TALL-2 and MOTN-1 cell lines). It is important to note that the HPB-ALL andMHH-TALL-2 cell lines shared the same mutation (p.Q966V), but STAT was activated onlyin the MHH-TALL-2 cell line. The molecular significance of these mutations is not easy tointerpret, since they could act in a receptor-dependent or independent manner with respect toactivation. Therefore, although JAK inhibitors (JAKis) constitute a new therapeutic option forthe treatment of PTCL patients [20,26], further studies are needed to elucidate the relationbetween mutations and the activation of the JAK/STAT pathway as well as the mechanisms ofJAKi resistance.Mutations of epigenetic regulators are so common in PTCL that they constitute one of thelargest groups of mutation, including those affecting the splicing machinery, signalingpathways and transcription factors [2]. Mutations in DNMT3A and TET2 were found in 18.2% and9.1% of our panel of cell lines, respectively. DNMT3A encodes a protein that catalyzesmethylation and demethylation of DNA, depending on the microenvironment conditions [27]. Thespecific relevance of DNMT3A mutations to the cancer phenotype has not been explored,except for p.R882 mutations, which predict poor prognosis in acute myeloid leukemia [28,29].TET family proteins are known to play critical roles in DNA demethylation by converting5-mC to 5-hydroxymethylcytosine (5-hmC) in α-KG-dependent and a Fe (II)-dependentmanner [30]. Mutations that disrupt the catalytic domain or lead to a truncated TET2 havebeen linked to the development of hematological malignancies [31]. In fact, several leukemiaand lymphoma disorders have a TET2 that is mutated at notably high frequencies (chronicmyelomonocytic leukemia: 35±50%; AITL: 50±80%; PTCL-NOS: 40±50%) [32±37]. Someepigenetic drugs, such as vorinostat, belinostat and romidepsin, have been positioned as a secondline for TCL treatment, and have produced improved response rates.This study found two mutations in PLCG1 (encoding p.Gln152His and p.Asp1199Asn),both of which were present in a T-ALL cell line, DND-41. Recently, two hot-spot PLCG1mutations (encoding p.Ser345Phe and p.Ser520Phe) that enhance PLCγ activity have been8 / 14reported in T-cell lymphoma [19,38]. PLCG1 encodes phospholipase Cγ1 (PLCγ1), a keyregulator of proximal TCR signaling [38]. Interestingly, NFAT expression was positive in the cellsharboring PLCG1 mutations, suggesting that these mutations may promote deregulatedactivation of downstream PLCγ1 signaling. This activation may support the idea that specifictargeting of PLC downstream signaling, like tacrolimus, which acts as a calcineurin inhibitor, couldbe a therapeutic option for the treatment of patients with mutations in PLCG1.Two RHOA mutations were detected, both of them in T-ALL. Several research groupshave found frequent RHOA mutations, specifically the p.G17V mutation, in AITL and PTCLpatients [37,39]. Interestingly this p.G17V mutation appears to act similarly towell-characterized dominant negative mutations of RHOA, rather than as an activating mutation. Althoughnone of the mutations found in our study corresponds to the p.G17V variant, it is importantto note that both cells lines in our study that harbor RHOA mutations showed robust MYCexpression. In this context, it has been reported that there is cross-regulation between MYCand RhoA activation [40].From a therapeutic perspective, our results highlight important disease mechanisms thathave the potential to serve as targets for therapy. In this regard, the immunohistochemicalanalysis identified an activated NFKB pathway in about 62% of TCL cell lines (Fig 3). Recently,Odqvist and colleagues reported worse overall survival in PTCL patients associated withnuclear expression of classical or alternative NFKB components, implying thatNFKB-inducing kinase (NIK) silencing could be an effective target for abrogating the NIK-dependentNFKB activation [41]. The number of NIK inhibitors currently known is limited. A preclinicalstudy with ALK-negative ALCL patient cells [42] and CTCL cell lines [43] reported thepotential for the effective use of bortezomib, but a phase II study in refractory ATLL patients wascancelled because single-agent activity did not produce significant improvements in patients[44]. NIK and IKK inhibitors may be promising agents in T-cell lymphomas with an activatedNFKB pathway, but further studies and clinical trials are needed to evaluate the real potentialof these agents in single and combined usage.The second most frequently activated pathway in cell lines was JAK/STAT (42.4%), makingthe blockade of this pathway a promising means of treating TCL patients. Ruxolitinib has beendemonstrated to inhibit CTCL cell line proliferation at micromolar concentrations [20] andclinical trials are now ongoing (www.clinicaltrials.gov; accessed September 2016) in T-celllymphomas and other hematological malignancies. Tofacitinib has been shown to inhibitJAK3 in CTCL [45] but other JAK inhibitors such as momelotinib, baricitinib or filgotinibhave not been tested in TCL. Although few preclinical and clinical data are available, STAT3inhibitors, which seem to have a low toxicity profile [46], are other emerging targets.Unsupervised hierarchical clustering identified six groups on the basis of their expressionprofile. We can propose a targeted therapy that takes into account the mutational backgroundof each group (S2 Fig). Group 1 had a differentially positive PD1 expression and activatedMAPK-ERK. Given this, anti-PD1 and ERK inhibitors could constitute an effective therapyfor this group. A recent phase I study noted a response rate of 17% with nivolumab treatment[47]. Group 2, mainly composed of T-ALL cell lines, was complex because of theheterogeneous expression of immunomarkers, so different approaches should be adopted to treat suchpatients. Group 3 exhibited the strongest activation of both canonical and non-canonicalNFKB pathways, with strong expression of CD30, so drugs reducing NFKB activation andanti-CD30 may be good options for therapy. Interestingly, Group 4 showed activation ofSTAT 1, 3 and 5, with positive expression of CD30 in all cases. Anti-CD30 and JAKi therapycould be a treatment option for this group. Group 5, comprising the ALCL-ALK+ cell lines,was strongly positive for ALK, BCL6, CD30 and STAT3, so the treatment options couldinclude the use of anti-CD30 antibody and ALK and JAK inhibitors. In fact, brentuximab9 / 14vedotin, an anti-CD30 antibody, has recently been approved to treat ALCL patients [48]. Onthe other hand, the ALK inhibitor alectinib was tested in the ALCL-ALK+ cell lineKARPAS299 [49], in which it showed potent efficacy in a KARPAS-299 mouse xenograft. Group 6comprised only the two NK cell lines included in the study. As recently reported [50], JAKi couldbe a new option for treating this lymphoma subtype.In conclusion, the study identifies commonly deregulated pathways and genes in TCL,including JAK/STAT, NOTCH, NFKB and chromatin conformation. Activation of thesepathways is somehow the consequence of somatic mutation and other causes. Our findings mayhelp in the development of preclinical models for the evaluation of new targeted drugs.Supporting informationS1 Table. Cell lines used in the study.(XLSX)S2 Table. List of genes sequenced by amplicon-based methodology in cell lines.(XLSX)S3 Table. Antibodies used in immunohistochemical analysis.(XLSX)S4 Table. Public data consulted to validate our 16-gene panel.(XLSX)S5 Table. List of variants found in our panel of cell lines.(XLSX)S6 Table. List of variants found in public data.(XLSX)S7 Table. Association between immunomarkers. Probabilities of chi-square or Fisher exacttests for tests of association between pairs of the 26 immunomarkers used. Green and orangeindicate positive and negative associations, respectively.(XLSX)S1 Fig. Genotype-phenotype associations. a) Mutational status of TP53 was defined asNonsense/Frameshift (n = 10, blue), wild type (WT, n = 9, white) and missense (n = 15, red).Mutational status of NOTCH1 was defined as wild type (n = 20, White) and mutated (n = 14, red).Mutational status of JAK was defined to be JAK1 and/or JAK3 wild type (n = 23, white) ormutated (n = 11, red). The immunomarkers p53, NOTCH1 and STATs, are indicated in coloras in Fig 3. STATs was defined as the mean of p-STAT1, p-STAT3 and p-STAT5. b) Mean ofimmunomarkers with respect to mutational status. Error bars indicate the SEM (standarderror of mean).(TIF)S2 Fig. Mutational landscape of TCL cell lines grouped by unsupervised hierarchicalclustering.(TIF)AcknowledgmentsWe thank the Bioinformatics Unit of the CNIO for its support with bioinformatic analysis. 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