Successful Clinical Sequencing by Molecular ......more widespread as a clinical tool for accurate di-agnosis and proper treatment in clinical oncology.4 However, the use of various

molecular

tumor

boards

Successful Clinical Sequencing by MolecularTumor Board in an Elderly Patient With RefractorySézary SyndromeYasuki Hijikata, MD, PhD1; Kazuaki Yokoyama, MD, PhD2; Nozomi Yokoyama, MT3; Yasuo Matsubara, MD, PhD1; Eigo Shimizu4;Makoto Nakashima, PhD5; Makoto Yamagishi, PhD5; Yasunori Ota, MD, PhD7; Lay Ahyoung Lim, MD, PhD1; Rui Yamaguchi, PhD4;Mika Ito6; Yukihisa Tanaka, MT7; Tamami Denda, MS7; Kenzaburo Tani, MD1; Hiroshi Yotsuyanagi, MD1; Seiya Imoto, PhD8;Satoru Miyano, PhD4; Kaoru Uchimaru, MD, PhD5; and Arinobu Tojo, MD, PhD2,8

INTRODUCTION

Sézary syndrome (SS), a rare, aggressive, leukemicvariant of cutaneous T-cell lymphoma (CTCL), com-prises the malignant clonal proliferation of T lym-phocytes, and is prone to skin involvement.1 Mostpatients with SS are elderly, with erythroderma presenton . 80% of the body. SS is rarely curable and hasa poor prognosis; the median survival of patients withstage IV SS is approximately 2 years.2 Recent SSgenomic profiling with next-generation sequencing(NGS) demonstrated impaired normal signaling, whichsuggests the possibility of new treatment targets.3

NGS-based genomic testing for cancer is becomingmore widespread as a clinical tool for accurate di-agnosis and proper treatment in clinical oncology.4

However, the use of various NGS techniques toguide cancer therapy has created challenges in an-alyzing large volumes of genomic data and reportingresults to patients and caregivers.5 To resolve this, weorganized a clinical sequencing team called the mo-lecular tumor board (MTB) at the Institute of MedicalScience, The University of Tokyo. Clinical sequencingis associated with several potential challenges inanalysis, interpretation, and drug development for rarecancers such as SS. Here, we report the use of clinicalsequencing to achieve a complete response in anelderly patient with SS refractory to standard treatment.

CASE REPORT

A 75-year-old male was diagnosed with SS (T4N3M0B1b;stage IVA2) in 2015. He had received varioustreatments in multiple hospitals, including pred-nisone, psoralen and ultraviolet A, extracorporealphotopheresis, bexarotene, romidepsin, total skinelectron beam therapy, brentuximab vedotin, in-terferon alfa-2b, methotrexate, and pembrolizumab,but skin lesions did not respond adequately. Severepneumonia also occurred duringmethotrexate therapyand was resolved by intensive care. The patient wasadmitted to our hospital in November 2016. Gener-alized erythroderma, clinical stage IIIA, was observed.He received mogalizumab, low-dose VP-16, and local

radiation therapy. Each resulted in temporal clinicalresponses, but with limited effects.

Our study protocol (No. 26-112-270402/28-17-0708;Appendix) was approved by our institutional reviewboard and was in accordance with the Declarationof Helsinki. After obtaining written informed consent,whole-exome sequencing (WES) and RNA sequencingwere performed on skin tumor biopsy samples onFebruary 1, 2017, for comparisons with normal tissue,followed by analysis by our hospital curators (AppendixFigs A1 and A2). Specifically, from WES, 77 codingvariants were identified (Appendix Table A1). Amongthese, the MTB inferred only one driver mutation inTP53 (c.560-1G.A, splicing mutation, AppendixTable A1) from which no actionable molecular targetswere identified. However, from RNA sequencing,actionable molecular targets were identified. Weregarded the following gene upregulations as directlytargetable: CCR4 (mogalizumab), LCK (dasatinib),CD274 as PD-L1 (PD-L1 inhibitors, pembrolizumab),CTLA4 (ipilimumab), IL2RA as CD25 (denileukin dif-titox), TNFRSF8 as CD30 (brentuximab vedotin), andnuclear factor-κB (NF-κB) signaling pathway (Table 1).Of note, we also inferred lenalidomide as a potentialtherapeutic option on the basis of the following tworeasons: The tumor was enriched in pathways that wereall indirectly targetable by lenalidomide (eg, KyotoEncyclopedia of Genes and Genomes [KEGG]-NF-κBsignaling [Appendix Fig A7], KEGG-cytokine-cytokinereceptor interaction [Appendix Fig A9], andKEGG-naturalkiller [NK]-cell–mediated cytotoxicity6 [Appendix Fig A8],and KEGG-tumor necrosis factor [TNF] signal-ing [Appendix Fig A10] on the basis of the KEGGDRUGDatabase,7 Therapeutic Target Database8), anddocumented efficacy of lenalidomide was reported inpatients with CTCL with overall response rates of28% in a phase II trial of monotherapy for refractorySS9 and a phase III trial of maintenance therapy.10

Mogalizumab, pembrolizumab, and brentuximabvedotin had already been used during the patient’sprotracted clinical course. Denileukin diftitox wasexcluded because the latest immunohistochemical

ASSOCIATEDCONTENT

Appendix

Author affiliationsand supportinformation (ifapplicable) appear atthe end of thisarticle.

Accepted onDecember 14, 2019and published atascopubs.org/journal/po on May 15, 2020:DOI https://doi.org/10.1200/PO.19.00254

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analysis of the patient’s lesions showed that they wereCD25−. The two remaining candidates were ipilimumaband lenalidomide. The patient was reluctant to receiveipilimumab because its mechanism of action is similar tothat of pembrolizumab. Therefore, we focused on lenali-domide as a therapeutic option.

To identify any potential predictive signatures of responseto lenalidomide therapy in this patient, we investigatedwhether there could be any overlapping lenalidomide-related gene signatures in our in-house, independentRNA sequencing data set (Appendix Figs A2-A5). Spe-cifically, we focused on available data from patients withadult T-cell leukemia/lymphoma (ATL), another mature/peripheral T-cell neoplasm in which lenalidomide dem-onstrated clinical efficacy with an overall response rate of42% in a phase II study (ATLL-002 [ClinicialTrials.govidentifier: NCT01724177]). Gene expression data fromtumors of two patients with ATL before lenalidomidetherapy were available for this purpose; one patient (uniquepatient number [UPN] 1) had an objective response tolenalidomide therapy, whereas the other patient (UPN2)was primarily refractory to lenalidomide (the patient char-acteristics are listed in Appendix Table A2). To identifymolecular signatures associated with lenalidomide re-sponse and to reduce bias derived from different dis-eases, such as ATL, we extracted differentially expressedgenes from the tumor of UPN1 (responsive ATL case)compared with expression levels in the tumor from UPN2(refractory ATL case). Overall, we found 1,250 and 1,197genes upregulated in CTCL and the current ATL case,respectively.

KEGG pathway enrichment on the basis of the DAVIDannotation tool revealed that 73 and 88 pathways wereenriched in CTCL and ATL, respectively (Appendix Fig A3;Appendix Table A3). Among common pathways (n = 52),we identified HTLV-1 and lenalidomide target signatures(Appendix Fig A3, A7-A10; Appendix Table A3). Gene setenrichment analysis (GSEA) of panels of curated gene setsrelated to lenalidomide confirmed the enrichment of asignature predictive of response to lenalidomide in both

CTCL and ATL. In contrast, neither signature of resistancewas enriched in CTCL and ATL (Table 2). On the basis ofthese predictive signatures and documented efficacy inpatients with CTCL,9,10 we chose lenalidomide.

Beginning on September 11, 2017, lenalidomide was orallyadministered at a daily dose of 25 mg for 21 days of a28-day cycle while the patient had clinical stage IIB disease(Fig 1A). After the first course of treatment, all skin tumorsdisappeared except for one on his sternal region (Fig 1B). Inaddition, a transient flare reaction (TFR) that presented aserythema around skin tumors was observed during the firstcourse (Fig 1C). Aspiration pneumonia developed at theend of the first course, and thus, the dosage of the secondcourse was reduced to 10 mg daily; it was subsequentlyincreased by 5 mg every cycle to a maximum of 20 mgdaily. We extended the interval course from 1 to 2 weeksaccording to the patient’s status. Although new lesionsdisappeared after three courses of treatment, a 9-cmsternal tumor remained, but it was smaller than its pre-vious size. It was later irradiated with 20 Gy in December2017. The fifth course of lenalidomide was completed onFebruary 3, 2017, and all tumors, including sternal lesions,disappeared completely (Fig 1D).

Upon immunohistochemical analysis of tumor specimensbefore and after lenalidomide treatment, a remarkablenumber of CD8+ cells and few CD25+ and Foxp3+ cells wereobserved in each skin tumor (Appendix Table A4; AppendixFig A6). Especially, the number of CD8+ cells after the firstcourse increased compared with that before the treatmentbut decreased in the treatment-resistant lesion after thethird course of lenalidomide.

DISCUSSION

To our knowledge, this report is the first of successfulclinical results in a patient with refractory SS treated withlenalidomide, which was selected on the basis of clinicalsequencing. Advances in clinical sequencing have enabledthe discovery of actionable alterations that yield clinicalbenefit.11 Patients with advanced-stage SS have an un-favorable prognosis and an unmet clinical need for effective

TABLE 1. Actionable Alterations With DrugUpregulated Gene Drug Reason of the Exclusion

CCR4 Mogalizumab Drug resistance

LCK Dasatinib Lack of clinical evidence

PDL1 PD-L1 inhibitor Drug resistance

CTLA4 Ipilimumab Lack of consent

CD25 Denileukin diftitox Lack of expression by immunohistochemistry

CD30 Brentuximab vedotin Drug resistance

Activated signaling pathway

NF-κB Lenalidomide MTB recommendation

NOTE. See also Table 2. Candidate genes and drugs selected by the MTB proposed the activated NF-κB pathway on the basis of gene set enrichmentanalysis results. The attending physician chose lenalidomide (off-label use) from this report.Abbreviations: MTB, molecular tumor board; NF-κB, nuclear factor-κB.

Clinical Sequencing in a Patient With Sézary Syndrome

JCO Precision Oncology 535


treatment. Overall survival has not been shown to benefitfrom aggressive intervention with cytotoxic agents becauseof serious treatment-associated toxicities, including pro-longed myelosuppression. An increased understanding ofthe pathogenesis of SS, with the identification of new tar-gets, has led to new therapeutic approaches with biologicagents to reduce treatment-related toxicities and improveoutcomes.1

The rationale for lenalidomide selection by the MTB wasbased on five factors. First, lenalidomide binds the cullin4-RING-E3 ubiquitin ligase cereblon complex and de-grades lymphoid transcription factors IKZF1 and IKZF3,leading to a decrease in NF-κB.12 Second, activated tumornecrosis factor signaling, known as a lenalidomide-targetpathway in the KEGG DRUG database, was detected in thetumor, which is also considered targetable by lenalidomideon the basis of our in-house data, UPN1. Third, a phase IItrial of lenalidomide monotherapy for advanced refractoryCTCL reported reliable and meaningful clinical benefits; inthat trial, lenalidomide-induced TFR was correlated with

good clinical response in patients with SS, which suggeststhat mechanisms that underlie this reaction might repre-sent specific anticancer immune responses.9 Indeed, in thecurrent patient, immune response to cancer was consid-ered to be induced by lenalidomide as shown by the ap-pearance of TFR (Fig 1C). Immunohistochemical stainingshowed that CD8+ cells in the tumor after the appearance ofTFR were increased after lenalidomide treatment. Fourth,lenalidomide exerts immunomodulatory effects, such asNK- and T-cell activation and the induction of T-helper1 cytokine production and cytotoxic activity; it also altersthe tumor microenvironment through its anti-angiogenic,antiproliferative, and pro-apoptotic properties.13 These char-acteristics provided the rationale for using this agent inour elderly patient with SS with susceptibility to infection.Actually, NK-cell–mediated cytotoxicity and cytokine-cytokine receptor interactions were enriched in the tu-mor before lenalidomide treatment. In addition, the fre-quencies of circulating NK cells and CD3+CD8+ T cellsincreased after the administration of lenalidomide compared

TABLE 2. Lenalidomide-Related Gene Sets and Annotations

Lenalidomide-Related Gene Sets and Annotations Current Patient

A Lenalidomide-Responsive Patient

With ATL

Gene SetGeneSize Signature Reference NES P FDR q NES P FDR q

HINATA_NFKB_IMMU_INF 17 Lenalidomide-responsive/target pathway

TTD8, KEGG DRUG/pathway7

1.88 .004 0.008 1.55 .027 0.013

TIAN_TNF_SIGNALING_VIA_NFKB 25 Lenalidomide-responsive/target pathway


1.67 .005 0.025 1.36 .029 0.046

KEGG_NF-kappa_B_signaling_pathway 102 Lenalidomide-responsive/target pathway


1.93 .000 0.005 1.38 .017 0.033

KEGG_CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION

249 Lenalidomide-responsive/target pathway


1.75 .000 0.005 1.58 .000 0.009

KEGG_NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY



1.73 .000 0.005 1.45 .003 0.018

KEGG_APOPTOSIS 86 Lenalidomide-responsive/target pathway

TTD, KEGG DRUG/pathway

1.44 .004 0.023 1.18 .118 0.114

Aue_CLL_lenalidomide_target_Th1immunity_TableS1


Aue17 1.93 .000 0.009 1.94 .000 0

Bhutani_myeloma_lenalidomide_target_genes_TableS2


Bhutani18 1.22 .035 0.104 1.60 .000 0.009

E2F3_UP.V1_UP 186 Lenalidomide resistance Neri19 1.23 .029 0.284 NE

KRAS.600.LUNG.BREAST_UP.V1_UP 271 Lenalidomide resistance Neri19 1.23 .320 0.220 1.42 0.062

KRAS.KIDNEY_UP.V1_UP 139 Lenalidomide resistance Neri19 NE NE

KRAS.LUNG_UP.V1_UP 136 Lenalidomide resistance Neri19 1.44 .005 0.206 1.00 .452 0.486

RAF_UP.V1_DN 183 Lenalidomide resistance Neri19 NE 1.12 .181 0.358

MEK_UP.V1_DN 182 Lenalidomide resistance Neri19 NE 1.03 .388 0.445

RPS14_DN.V1_DN 179 Lenalidomide resistance Neri19 1.12 .109 0.333 NE

AKT_UP_MTOR_DN.V1_DN 173 Lenalidomide resistance Neri19 NE 1.12 .217 0.334

STK33_DN 256 Lenalidomide resistance Neri19 NE 1.33 .004 0.103

Abbreviations: ATL, adult T-cell leukemia/lymphoma; FDR, false discovery rate; KEGG, Kyoto Encyclopedia of Genes and Genomes; NE, not enriched; NES,normalized enrichment score; TTD, Therapeutic Target Database.

Hijikata et al

536 © 2020 by American Society of Clinical Oncology


with those at first treatment (Appendix Fig A11). Incontrast, the frequency of effector regulatory T cells didnot increase (Appendix Fig A11). These findings weresimilar to those described in the immunohistochemistry(Appendix Fig A6). These immunologic changes mighthave induced anticancer effects9 and prevented severeinfection.14 Finally, the Japanese national health in-surance system has already approved lenalidomide for thetreatment of myelodysplastic syndrome, refractory/relapsemultiple myeloma, and ATL.

Lenalidomide did not adequately treat the patient’s bulkysternal mass. Acquired lenalidomide resistance is con-sidered to be caused by reduced levels of tumor cellcereblon protein because of epigenetic modifications ofthe cereblon promotor region, cereblon gene mutations or

chromosomal deletions, or acquired cereblon pathway mu-tations and detects in other components of the E3 ligasecomplex.15 Another possible reason is that the delivery oflenalidomide to the tumor was hindered by the abundantsurrounding interstitial tissue and the immunosuppressivetumor microenvironment.16

In the near future, clinical sequencing will support clinicaldecisions with regard to appropriate treatments for patientswith rare and refractory cancers. In addition, clinical se-quencing on the basis of a combination of several NGStechniques might be particularly useful in identifying ap-propriate treatment options. This case report is the first toour knowledge of the use of clinical sequencing to iden-tify a successful treatment strategy for a patient withrefractory SS.

AFFILIATIONS1Department of General Medicine, IMSUT Hospital, Institute of MedicalScience, The University of Tokyo, Tokyo, Japan2Department of Hematology/Oncology, IMSUT Hospital, Institute ofMedical Science, The University of Tokyo, Tokyo, Japan3Department of Applied Genomics, Research Hospital, Institute ofMedical Science, The University of Tokyo, Tokyo, Japan4Laboratory of DNA Information Analysis, Human Genome Center,Institute of Medical Science, The University of Tokyo, Tokyo, Japan5Laboratory of Tumor Cell Biology, Department of Computational Biologyand Medical Sciences, Graduate School of Frontier Sciences, TheUniversity of Tokyo, Tokyo, Japan6Division of Molecular Therapy, Advanced Clinical Research Center,Institute of Medical Science, The University of Tokyo, Tokyo, Japan

7Department of Diagnostic Pathology, IMSUT Hospital, Institute ofMedical Science, The University of Tokyo, Tokyo, Japan8Division of Health Medical Data Science, Health Intelligence Center,Institute of Medical Science, The University of Tokyo, Tokyo, Japan

CORRESPONDING AUTHORArinobu Tojo, MD, PhD, Institute of Medical Science, The University ofTokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan; e-mail:[email protected].

EQUAL CONTRIBUTIONY.H. and K.Y. contributed equally as co-first authors.K.Y. and A.T. contributed equally as senior authors.

A B

DC

FIG 1. Changes in the patient’s skin lesions during lenalidomide treatment. (A) The skin lesions on the trunk andarms before lenalidomide treatment. (B) After the first treatment course, almost all skin lesions except for that onthe patient’s sternal region disappeared. (C) Documented transient flare reaction presented as erythema aroundskin lesions. (D) All lesions, including the sternal lesion, disappeared after the fifth cycle.




mailto:[email protected]

SUPPORTSupported in part by the Center of Innovation Program of the JapanScience and Technology Agency and Ministry of Education, Culture,Sports, Science and Technology Innovative Area 15H05912.

AUTHOR CONTRIBUTIONSConception and design: Kazuaki Yokoyama, Arinobu TojoFinancial support: Kenzaburo Tani, Satoru MiyanoAdministrative support: Hiroshi YotsuyanagiProvision of study material or patients: Makoto Nakashima, Yasunori Ota,Kaoru UchimaruCollection and assembly of data: Yasuki Hijikata, Kazuaki Yokoyama,Makoto Yamagishi, Lay Ahyoung Lim, Kaoru UchimaruData analysis and interpretation: Yasuki Hijikata, Kazuaki Yokoyama,Nozomi Yokoyama, Yasuo Matsubara, Eigo Shimizu, Makoto Nakashima,Yasunori Ota, Rui Yamaguchi, Mika Ito, Yukihisa Tanaka, TamamiDenda, Kenzaburo Tani, Hiroshi Yotsuyanagi, Seiya Imoto, SatoruMiyanoManuscript writing: All authorsFinal approval of manuscript: All authorsAccountable for all aspects of the work: All authors

DATA AVAILABILITY STATEMENTBoth sequence data and materials described in this article are availableupon request to the corresponding author K.Y. ([email protected]), but the request must include a description of the researchproposal.

AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OFINTERESTThe following represents disclosure information provided by authors ofthis manuscript. All relationships are considered compensated unlessotherwise noted. Relationships are self-held unless noted. I = Immediate

Family Member, Inst = My Institution. Relationships may not relate to thesubject matter of this manuscript. For more information about ASCO’sconflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/po/author-center.Open Payments is a public database containing information reported bycompanies about payments made to US-licensed physicians (OpenPayments).

Rui YamaguchiHonoraria: Janssen Pharmaceuticals, Chugai Pharma

Kenzaburo TaniStock and Other Ownership Interests: Shinnihonseiyaku Co Ltd, PrecisionTherapeutics, Oncolys BioPharmaConsulting or Advisory Role: Precision TherapeuticsResearch Funding: Shinnihonseiyaku Co Ltd, Neopharma Japan,Takara Bio

Kaoru UchimaruHonoraria: CelgeneResearch Funding: Daiichi Sankyo, Celgene, NEC

Arinobu TojoHonoraria: Otsuka PharmaceuticalConsulting or Advisory Role: SysmexSpeakers’ Bureau: Novartis, Otsuka Pharmaceutical, Bristol-MyersSquibbResearch Funding: Chugai Pharma, Torii Pharmaceutical, KM Biologics

No other potential conflicts of interest were reported.

ACKNOWLEDGMENTWe thank all members of the study team as well as the patients and theirfamilies.

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ternational Society for Cutaneous Lymphomas/European Organisation for Research and Treatment of Cancer staging proposal. J Clin Oncol 28:4730-4739,2010

2. Wilcox RA: Cutaneous T-cell lymphoma: 2017 update on diagnosis, risk-stratification, and management. Am J Hematol 92:1085-1102, 2017

3. Wang L, Ni X, Covington KR, et al: Genomic profiling of Sézary syndrome identifies alterations of key T cell signaling and differentiation genes. Nat Genet47:1426-1434, 2015

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6. KEGG: Kyoto Encyclopedia of Genes and Genomes. http://www.kegg.jp or http://www.genome.jp/kegg

7. Kyoto Encyclopedia of Genes and Genomes: KEGG DRUG: Lenalidomide. https://www.kegg.jp/dbget-bin/www_bget?D04687+-us

8. Innovative Drug Research and Bioinformatics Group: Therapeutic Target Database. http://db.idrblab.net/ttd/data/drug/details/d0q5nx

9. Querfeld C, Rosen ST, Guitart J, et al: Results of an open-label multicenter phase 2 trial of lenalidomidemonotherapy in refractory mycosis fungoides and Sézarysyndrome. Blood 123:1159-1166, 2014

10. Bagot M, Hasan B, Whittaker S, et al: A phase III study of lenalidomide maintenance after debulking therapy in patients with advanced cutaneous T-celllymphoma - EORTC 21081 (NCT01098656): Results and lessons learned for future trial designs. Eur J Dermatol 27:286-294, 2017

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12. Kritharis A, Coyle M, Sharma J, et al: Lenalidomide in non-Hodgkin lymphoma: Biological perspectives and therapeutic opportunities. Blood 125:2471-2476,2015

13. Kotla V, Goel S, Nischal S, et al: Mechanism of action of lenalidomide in hematological malignancies. J Hematol Oncol 2:36, 2009

14. Lenartić M, Jelenčić V, Zafirova B, et al: NKG2D promotes B1a cell development and protection against bacterial infection. J Immunol 198:1531-1542, 2017

15. Franssen LE, Nijhof IS, Couto S, et al: Cereblon loss and up-regulation of c-Myc are associated with lenalidomide resistance in multiple myeloma patients.Haematologica 103:e368-e371, 2018

16. Sriraman SK, Aryasomayajula B, Torchilin VP: Barriers to drug delivery in solid tumors. Tissue Barriers 2:e29528, 2014

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18. Bhutani M, Zhang Q, Friend R, et al: Investigation of a gene signature to predict a gene signature to predict response to immunomodulatory derivatives forpatients with multiple myeloma: An exploratory, retrospective study using microarray datasets from prospective clinical trials. Lancet Haematol 4:e443-e451,2017

19. Neri P, Gratton K, Ren L, et al: RNA-sequencing of paired pre-treatment and relapse samples reveals differentially expressed genes associated withlenalidomide resistance in multiple myeloma. Blood 122:530, 2013

n n n




APPENDIX

Materials and Methods

Patients and samples. Our study protocol was approved by ourinstitutional research ethics committee and was in accordance with theDeclaration of Helsinki. Three patients were recruited for our study, allof whom provided written informed consent. The characteristics of tworeference patients with adult T-cell leukemia/lymphoma (ATL) arelisted in Table A2. The following samples were collected: (1) the tumor(cutaneous T-cell lymphoma [CTCL]), patient’s skin tumor samplebefore lenalidomide therapy, and control (CTCL), patient’s tumor-freenormal skin lesion, which had been histologically confirmed, and (2)the tumor (ATL), tumor-rich peripheral blood mononuclear cells(PBMNCs) before lenalidomide therapy in a patient with ATL(uniquepatient number 1 [UPN1]) for whom clinical partial response wasobserved under lenalidomide therapy, and control (ATL), tumor-richPBMNCs before lenalidomide therapy in another patient with ATL(UPN2) for whom no objective response had been observed withlenalidomide therapy.

Extraction of DNA and RNA. DNA was extracted using the GentraPuregene Blood Kit and the QIAamp Circulating Nucleic Acid Kit(QIAGEN, Hilden, Germany). DNA was quantified using the QubitdsDNA HS Assay Kit (Life Technologies, Carlsbad, CA). Total RNA wasextracted using the RNeasy Mini Kit (QIAGEN).

Whole-exome sequencing. To identify driver mutations, we per-formed whole-exome sequencing (WES). Libraries were prepared from200 ng of paired DNA (tumor/control) using SureSelectXT Human AllExon V5 (Agilent Technologies, Santa Clara, CA). WES was performedon the basis of 2× 100-base pair (bp) paired-end reads on the NextSeq500 platform with NextSeq 500/550 Kit v2 chemistry (Illumina, SanDiego, CA). All procedures were performed according to the manu-facturers’ protocols.

Somatic variant calling and subsequent primary filtering ofWES data. We used human genome build 19 as the referencesequence for our analysis. Primary processing of sequencing data wasperformed using our in-house software. Single nucleotide variantswere identified using Genomon2 (http://genomon.hgc.jp/exome/en/)with default parameters. All variant calls were annotated withANNOVAR (using an in-house annotation database resource). TheIntegrative Genomics Viewer (IGV) version 2.3.57 (https://software.broadinstitute.org/software/igv/download) was used to visualize andinspect the read alignments and variant calls. For our analysis, thedatabases used to annotate variants included the following: RefSeq(http://www.ncbi.nlm.nih.gov/RefSeq/), the 1000 Genomes Projectas of August 2015 (http://www.internationalgenome.org/data),dbSNP131 (http://www.ncbi.nlm.nih.gov/projects/SNP/), ToMMoversion 1 (https://ijgvd.megabank.tohoku.ac.jp/), the Human GeneticVariation Database as of October 2013 (http://www.hgvd.genome.med.kyoto-u.ac.jp/), ClinVar as of June 2015 (https://www.ncbi.nlm.nih.gov/clinvar/), the Human Gene Mutation Database Professional asof March 2015 (http://www.hgmd.cf.ac.uk/ac/index.php), the cBio-Portal for Cancer Genomics as of September 2015 (http://cbioportal.org), the TumorPortal as of September 2015 (http://www.tumorportal.org/), the Catalogue of Somatic Mutations in Cancer (COSMIC) version70 (http://cancer.sanger.ac.uk/cosmic), and the International CancerGenome Consortium Data Portal (https://dcc.icgc.org/). The compu-tational algorithms Sorting Intolerant From Tolerant (http://sift-dna.org)and PolyPhen-2 (http://genetics.bwh.harvard.edu/pph2/) were used topredict whether mutations were damaging. Synonymous or noncodingvariants were excluded, and single nucleotide polymorphisms (SNPs;minor allele frequency . 1%) reported to be present in either of theaforementioned SNP databases were automatically excluded, unlessthey were recurrently (three or more times) found in the COSMICdatabase. Copy number variation analysis was performed using CNVkitversion 0.8.2 software (E. Talevich, University of Southern California,San Francisco, San Francisco, CA), and the data were filtered on thebasis of the following parameters: log2 ≥ 0.6 or log2 ≤ −1 and read

depth . 10. Upon somatic mutation calling followed by a primaryfiltering step, the list of variants was stored in a variant calling file format(.vcf). Gene-level copy number alterations, as a log2 ratio of tumor tonormal, were also stored in text format (.log2).

Identification of putative driver mutations fromWES data. Weclassified variants into three tiers. We regarded tier 1 mutations asdefinitive driver mutations. Briefly, tier 1 included definitive drivermutations with abundant evidence in the literature and/or cancermutation databases with a variant frequency (VAF) of ≥ 5%. Tier2 included mutations with a little or no evidence in the literature and/ordatabases, namely, uncertain/unclassified significance, with VAF≥ 5%. Tier 3 included all remaining variants. The selection of mutationcriteria for tier 1 was as follows: all changes in the amino acid codingregions of annotated exons that were frequently (at least three times)reported in hematopoietic tumor samples in the COSMIC database(version 71) or all predictive, highly deleterious variants (in consensussplice site regions, frameshift mutations, any premature predictedtruncation mutation, or large in-frame insertions/deletions) in non-Hodgkin lymphoma or CTCL-associated genes, according to previousstudies (Ungewickell A, et al: Nat Genet 47:1056-1060, 2015; Choi J,et al: Nat Genet 47:1011-1019, 2015; Lohr JG, et al: Proc Natl AcadSci U S A 109:3879-3884, 2012). Curated tier 1-2 somatic mutationsare listed in Table A1.

RNA SequencingWe used the following RNA samples: the tumor (CTCL), patient’s skintumor sample before lenalidomide therapy; control (CTCL), and pa-tient’s tumor-free normal skin lesion; the tumor (ATL) and tumor-richPBMNCs in lenalidomide-responsive ATL (UPN1); and the control(ATL) and tumor-rich PBMNCs in lenalidomide-primary refractory ATL(UPN2). cDNA libraries for next-generation sequencing were con-structed from 100 ng of total RNA using TruSeq RNA Access LibraryPrep Kit (Illumina). Each paired end–indexed library was sequenced toa length of 75 nucleotides per pair (2 × 75 bp) using a NextSeq in-strument. Sequence reads were processed by our in-house Genomon-RNA/Genomon-expression pipeline (Shiraishi Y, et al: PLoS One 9:e114263, 2014; http://genomon.hgc.jp/rna/). IGV version 2.3.57 wasused to visualize the mapped sequence. For gene expression, frag-ments per kilobase of gene model per million mapped read (FPKM)values were calculated and used.

To investigate any changes in gene expression in a certain enrichedpathway involved in the clinical features of the current patient withCTCL, as well as the reference patients with ATL, we used the onlineDAVID tool version 6.8 (https://david.ncifcrf.gov/) and gene set en-richment analysis (GSEA) with FPKMmetrics at the gene level (tumor vcontrol). For DAVID-based pathway analysis, upregulated genes rel-ative to expression in the control (fold-change ≥ 2 and with a cutoffvalue of FPKM ≥ 10) were stored in comma-separated value format(.csv) and inputted into the web-based interface of DAVID. Theseoutputs were reviewed, and significantly enriched Kyoto Encyclopediaof Genes and Genomes (KEGG) pathways are listed in Table A3. Thefour significant lenalidomide-target pathways were also visualizedusing Pathview (https://pathview.uncc.edu/) and displayed in FiguresA7-A10. For GSEA, a stand-alone application was used (Broad In-stitute, Cambridge, MA; http://broadinstitute.org/gsea/index.jsp) withthe MSIGDB library version 7.1 as well as in-house–created gene setsthat were based on a false discovery rate threshold of q , 0.05.

ImmunohistochemistryFormalin-fixed paraffin embedded tissue sections of 3-μm thick-ness were deparaffinized in xylene and rehydrated in a series ofgraded alcohols and heated in an antigen retrieval solution at pH9.0 (Vector Laboratories, Burlingame, CA) for 10 minutes at 120°C.Endogenous peroxidase was blocked by incubation with 3% hy-drogen peroxidase for 5 minutes at room temperature. Next,sections were incubated with the following primary antibodies for30 minutes at 37°C: CD4 (clone EPR6855, dilution 1:250; Abcam,Cambridge, United Kingdom), CD8 (clone SP16, dilution 1:100;

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http://genomon.hgc.jp/exome/en/https://software.broadinstitute.org/software/igv/downloadhttps://software.broadinstitute.org/software/igv/downloadhttp://www.ncbi.nlm.nih.gov/RefSeq/http://www.internationalgenome.org/datahttp://www.ncbi.nlm.nih.gov/projects/SNP/https://ijgvd.megabank.tohoku.ac.jp/http://www.hgvd.genome.med.kyoto-u.ac.jp/http://www.hgvd.genome.med.kyoto-u.ac.jp/https://www.ncbi.nlm.nih.gov/clinvar/https://www.ncbi.nlm.nih.gov/clinvar/http://www.hgmd.cf.ac.uk/ac/index.phphttp://cbioportal.orghttp://cbioportal.orghttp://www.tumorportal.org/http://www.tumorportal.org/http://cancer.sanger.ac.uk/cosmichttps://dcc.icgc.org/http://sift-dna.orghttp://genetics.bwh.harvard.edu/pph2/http://genomon.hgc.jp/rna/https://david.ncifcrf.gov/https://pathview.uncc.edu/http://broadinstitute.org/gsea/index.jsp

Abcam), CD25 (clone 305, dilution 1:80; Leica Biosystems,Newcastle, United Kingdom), and Foxp3 (clone SP97, dilution 1:80; Abcam). After washing, sections were treated with secondaryantibody (EnVision+ Dual Link System-HRP; Dako, Glostrup,Denmark) for 30 minutes at 37°C. To visualize antigen-antibody

complex, EnVision+ DAB kit (Dako) was used, and then sectionswere counterstained in hematoxylin. Normal lymph node wasplaced on the same slide glass as a positive control, and negativecontrols were used in phosphate-buffered saline instead of theprimary antibodies.

Tumor DNAskin tumor

Control DNAnormal tumor

Somatic mutation call byGenomon pipeline

Copy number alterationcall by CNVkit pipeline

1. Variants

.vcf file

2. Copy number alterations

.log2 file

Annotation by ANNOVARwith in-house medicalinformatics pipeline

Curation of candidategenes

MTBActionable gene alteration

WES on NextSeq(Illumina)

FIG A1. Flowchart of whole-exome sequencing. MTB,molecular tumor board; vcf, variant calling file; WES, wholeexome sequencing.




Curation of candidate genes

Identification of lenalidomidetarget signature

Prediction of lenalidomideResponse in current patient

with CTCL

MTBActionable gene alteration

Tumor RNA-seqlenalidomide-responsive ATL (UPN1) PBMNC

Control RNA-seqlenalidomide-refractory ATL (UPN2) PBMNC

Tumor RNAskin tumor

Control RNAnormal tumor

Present CTCL case

RNA-seq on NextSeq(Illumina)

Transcript assembly/quantification (FPKM)by Genomon RNA

Differential gene expression Fold change ≥ 2 Tumor (or control) FPKM ≥10 .dge file

Exploring overlapping lenalidomide targetSignature in in-house RNA-seq data:A lenalidomide-responsive patient with ATL (Fig A3)

Functional–annotation/pathway analysis

GSEA DAVID

FIG A2. Flow of overall RNA sequencing. ATL, adult T-cell leukemia/lymphoma; CTCL, cutaneous T-cell lymphoma;.dge, digital gene expression; FPKM, fragments per kilobase of gene model per million mapped read; GSEA, gene setenrichment analysis; Len, lenalidomide; MTB, molecular tumor board; PBMNC, peripheral blood mononuclear cell;RNA-seq, RNA sequencing; UPN, unique patient number.

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RNA-seq: tumor v control

Differential gene expression,upregulated in tumor (v control):

1,250 genes (patient with CTCL) 1,197 genes (patient with ATL)

Pathway analysis by DAVID (KEGG pathway)

Curation of overlapping KEGG pathways

1. Lenalidomide target pathway in KEGG-DRUG/pathway

KEGG_NF-kappa_B_signaling_pathway

KEGG_CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION

KEGG_NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY

KEGG_APOPTOSIS

2. HTLV-1 signature

KEGG_HTLV-1 infection

Identification of HTLV-1 + lenalidomide target pathway Confirmation of lenalidomide target signature by GSEA analysis

Current patient with CTCL

73 52 88

Patient with ATL

FIG A3. Flow chart of overlapping lenalidomide (Len) target signaturediscovery. ATL, adult T-cell leukemia/lymphoma; CTCL, cutaneousT-cell lymphoma; GSEA, gene set enrichment analysis; KEGG, KyotoEncyclopedia of Genes and Genomes; RNA-seq, RNA sequencing.




Rank

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etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.00.10.20.30.40.5

0 5,000 10,000 15,000 20,000 25,000

Rank in Ordered Data Set

Enrichment plot: GEORG ETALJOURNALOFIMMUNOLOGYTABLES2_LENALIDOMIDE-CLL_ALL_DAY8TODAY0

Zero cross at 7660

‘TUMOR’ (positively correlated)

‘NORMAL’ (negatively correlated)

Enrichment plot: KEGG-NF-KAPPAB SIGNALING PATHWAY

Rank

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(Sig

nal2

Noi

se)

Enric

hmen

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–5.0–2.50.02.55.0

0.00.10.20.30.40.50.6

0 5,000 10,000 15,000 20,000 25,000


Zero cross at 7660



Enrichment plot:HINATA_NFKB_IMMU_INF

Rank

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etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.00.10.20.30.40.5

0.70.6

0.8

0 5,000

Zero cross at 7660

‘TUMOR’ positively correlated)


10,000 15,000 20,000 25,000


Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tsc

ore

–5.0–2.50.02.55.0

0.450.400.350.300.250.200.150.100.050.00

–0.05–0.10

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot: KEGG_APOPTOSIS

Zero cross at 7660



Zero cross at 7660



Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

–0.1–0.2

0.00.10.20.3

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:LANCETHEMATOLOGYTABLES2_ALL

Enrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores

Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.00.10.20.30.4

0.60.5

0.7

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:TIAN_TNF_SIGNALING_VIA_NFKB

Zero cross at 7660



Zero cross at 7660



Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1–0.2

0.10.20.30.40.5

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:KEGG_CYTOKINE_CYTOKINE_

RECEPTOR_INTERACTION

Zero cross at 7660

‘TUMOR’ positively correlated)

Enrichment plot:KEGG_NATURAL_KILLER_

CELL_MEDIATED_CYTOTOXICITY


Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1

0.10.20.30.40.5

0 5,000 10,000 15,000 20,000 25,000

Rank in Ordered Data SetEnrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores

Enrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores

FIG A4. Lenalidomide-target signature enriched in cutaneous T-cell lymphoma (CTCL) on the basis of gene set enrichment analysis (GSEA; related toTable 1). Enrichment plots and heat maps from GSEA in the patient. GSEA of the tumor disclosed significant enrichment of nuclear factor-κB (NF-κB)pathways, including that of a custom gene set, GEORG ETALJOURNALOFIMMUNOLOGYTABLES2_LENALIDOMIDE-CLL_ALL_DAY8TODAY0, on the basisof the report and Supplementary Table 2 by Aue et al17 as follows: NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY from the MSIGDB library,CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION from the MSIGDB library, TIAN_TNF_SIGNALING_VIA_NFKB and APOPTOSIS from the MSIGDBlibrary, and a custom gene set, LANCETHEMATOLOGYTABLES2_ALL, on the basis of the report and Supplementary Table 2 by Bhutani et al18. Red indicatesthat gene expression increased compared with that in control. Blue indicates that gene expression decreased compared with that in control. KEGG, KyotoEncyclopedia of Genes and Genomes.

Hijikata et al



Enrichment plot:KEGG_CYTOKINE_CYTOKINE_

RECEPTOR_INTERACTION

Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.00.10.20.30.4

0.60.5

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot: GEORG ETALJOURNALOFIMMUNOLOGYTABLES2_LENALIDO MIDE-CLL_ALL_DAY8TODAY0

Zero cross at 8016



Enrichment plot:LANCETHEMATOLOGYTABLES2_ALL

Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1

0.10.20.30.40.5

0 5,000 10,000 15,000 20,000 25,000


Zero cross at 8016



Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1

0.10.20.30.40.5

0 5,000

Zero cross at 8016



10,000 15,000 20,000 25,000


Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1

0.10.20.30.4

0.60.5

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:TIAN_TNF_SIGNALING_VIA_NFKB

Zero cross at 8016



Zero cross at 8016



Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.00–0.05–0.10

0.100.05

0.150.200.250.300.350.400.45

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:KEGG_APOPTOSIS

Enrichment profile Hits Ranking metric scores Enrichment profile Hits Ranking metric scores

Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.00.10.20.30.4

0.60.5

0.7

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:HINATA_NFKB_IMMU_INF

Zero cross at 8016



Zero cross at 8016



Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1

0.10.20.30.40.5

0 5,000 10,000 15,000 20,000 25,000


Enrichment plot:KEGG_NATURAL_KILLER_CELL_

MEDIATED_CYTOTOXICITY

Zero cross at 8016


Enrichment plot:KEGG-NF-KAPPA B SIGNALING PATHWAY


Rank

ed L

ist M

etric

(Sig

nal2

Noi

se)

Enric

hmen

tSc

ore

–5.0–2.50.02.55.0

0.0–0.1

0.10.20.30.40.5

0 5,000 10,000 15,000 20,000 25,000


FIG A5. Lenalidomide-target signature enriched in adult T-cell leukemia/lymphoma (ATL) on the basis of gene set enrichment analysis (GSEA; related toTable 1). Enrichment plots and heat maps from GSEA of ATL. In relation to Fig A4, GSEA of the tumor disclosed significant enrichment of nuclear factor-κB(NF-κB) pathways, including the gene sets of NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY, CYTOKINE_CYTOKINE_RECEPTOR_INTERACTION,TIAN_TNF_SIGNALING_VIA_NFKB, APOPTOSIS and custom gene sets on the basis of the report and Appendix Table A2 by Aue et al17 and Bhutani et al18.Red indicates that gene expression increased compared with that in the control. Blue indicates that gene expression decreased compared with that in thecontrol. KEGG, Kyoto Encyclopedia of Genes and Genomes.




B C

E F

A

D

IHG

FIG A6. Histologic and immunohistochemical analysis of tumor specimens before and after the lenalidomidetreatment. Hematoxylin and eosin staining and anti-CD8 and anti-Foxp3 antibody staining of tumor cells andlymphocytes (A, D, and G) before the lenalidomide treatment, (B, E, and H) in a tumor showing good response afterthe first course, and (C, F, and I) in a tumor showing a poor response after three courses of lenalidomide. (D and E) Aremarkable number of CD8+ cells are shown, whereas (G, H, and I) few Foxp3+ cells were observed in each tumor.The number of CD8+ cells after the first course of lenalidomide was increased compared with that (E) beforetreatment but was decreased in the poorly responding lesion (F) after the third course of lenalidomide.

Hijikata et al



TCRLck

Zap

SykBLNK

LAT PLC1

PLC2Btk

LynBCR

IL-1R

TNF-R1TNF

IL-1

Antigen

MHC/antigen

EDA-A1

EDA-A2

LBPLPS(G-)

MD-2

CD40L

RANKL

LTALTB

LIGHT

BAFF

EDA-A2 XEDAR

BAFF-R

LT-R

TRAF2

TRAF2TRAF3

TRAF6cIAF1/2

+u

TIRAP

TRAF6

TRAF6

TRAF6

TRAF2/5TRADD

CYLD

TAK1TAB

Btk

IB

(Y42)

IB

p50

p50

p65

p50

IB Degradation

NEMO

SUMOylation

DNA

Shuttling

DNA damage

PARP1

–1 0 1

–1 0 1

ATMNEMO

NEMOPIDDRIP1

c-IAP1/2

Bcl-XL

TRAF1/2

p100

IL8

IL-1 TNF-

IB

MIP-2

uPA

Survival

Survival

Activation ofnoncanonical pathway

Survival

Positive feedback

Negative feedback

Inflammation

Inflammation

Survival

Lymphoid tissuehoming

B-cell development,B-cell survival

Myelpoiesis andB-cell lymphopoiesis

Lymphocyte adhesion,T-cell costimulation

(H/R)

Bcl-XL(NGF)

Bcl-XL

A1/Bf1-1

(UV)

MIP-1

(TNF-)VCAM-1

A20

COX2

(TNF-, IL-1, LPS)

(Antigen, TNF-)

c-FLIP

Bcl-2 gadd45

A1/Bf1-1

XIAP

PIASyUbs9

(S32, S36)+p

p65

p65

CK2UV, HER2

Atypical pathways

Pervanadate,H/R,H2O2, EGF, CNTF, NGF

+p

+p

+p +p

NF-B

NF-B

NF-B

NF-B

p100RelB

p52DNA

DNA

DNA

Degradation

Degradation

BLC ELC

SLC

SDF-1

BAFF

ICAM

(LT/LIGHT)

(S/T (PEST))

IKKIKK

NEMO

CARMA

PKC

+p+pCa2+

Ca2+

DAG

DAG

IP3

IP3 PKC8

Bcl10ELKS

MALT1

Canonical pathway

RIG-I–like receptorsignaling pathway

Ubiquitin-mediatedproteolysis

Proteasome

BCRsignaling pathway

TCRsignaling pathway

Genotoxic agent

Calcium signalingpathway

cIAP1/2

Apoptosis

Auto-ubiquitination

Auto-ubiquitination

Toll-like receptorsignaling pathway

Osteoclastdifferentiation

Cytokine-cytokinereceptor interaction

Data on KEGG graphrendered by Pathview

+u

-u

+u

+p

+u

+u

+p

+p

RIP1

TRAF3

RIG-I

TRAF6

TRIM25

TRAF2/6

IRAK1/4

IRAK1/4

TRAF6TRAM

MyD88

MyD88

TRIFRIP1

TRAF6TRAF2

NIK

NIK

cIAP1/2

(S866, S870)

Partialdegradation

IKK

Noncanonical pathway

TRAF5

TRAF2

TRAF2TRAF3

TRAF3TRAF6

TRAF3

RANK

TLR4

CD14

CD40

Virus

XEDAR

EDAR EDARADD

TCRLck

Zap

SykBLNK

LAT PLC1

PLC2BtkLyn

BCR

IL-1R

TNF-R1TNF

IL-1

Antigen

MHC/antigen

EDA-A1

EDA-A2

LBPLPS(G-)

MD-2

CD40L

RANKL

LTALTB

LIGHT

BAFF

EDA-A2 XEDAR

BAFF-R

LT-R

TRAF2

TRAF2TRAF3

TRAF6cIAP1/2

+u

TIRAP

TRAF6

TRAF6

TRAF6

TRAF2/5TRADD

CYLD

TAK1TAB

Btk

IBa

(Y42)

IkB

p50

p50

p65

p50

IB Degradation

NEMO

SUMOylation

DNA

Shuttling

DNA damage

PARP1ATM

NEMO

NEMOPIDDRIP1

c-IAP1/2

Bcl-XL

TRAF1/2

p100

IL8

IL-1 TNF-

IB

MIP-2

uPASurvival

Survival

Activation ofnoncanonical pathway

Survival

Positive feedback

Negative feedback

Inflammation

Inflammation

Survival

Lymphoid tissuehoming

B-cell development,B-cell survival

Myelpoiesis andB-cell lymphopoiesis

Lymphocyte adhesion,T-cell costimulation

(H/R)

Bcl-XL(NGF)

Bcl-XL

A1/Bf1-1

(UV)

MIP-1

(TNF-)VCAM-1

A20

COX2

(TNF-, IL-1, LPS)

(Antigen, TNF-)

c-FLIP

Bcl-2 gadd45

A1/Bf1-1

XIAP

PIASyUbs9

(S32, S36)+p

p65

p65

CK2UV, HER2

Atypical pathways

Pervanadate,H/R,H2O2, EGF, CNTF, NGF

+p

+p

+p +p

NF-B

NF-B

NF-B

p100RelB

p52 DNA

DNA

DNA

Degradation

Degradation

BLC ELC

SLC

SDF-1

BAFF

ICAM

(LT/LIGHT)

(S/T (PEST))

IKKIKKNEMO

CARMA

PKC

+p+pCa2+

Ca2+

DAG

DAG

IP3

IP3 PKC8

Bcl10ELKS

MALT1

Canonical pathway

RIG-I–like receptorsignaling pathway


Proteasome

BCRsignaling pathway

TCRsignaling pathway

Genotoxic agent


cIAP1/2

Apoptosis

Auto-ubiquitination

Auto-ubiquitination

Toll-like receptorsignaling pathway

Osteoclastdifferentiation



-u

+u

+u

+p

+u

+u

+p

+p

RIP1

TRAF3

RIG-I

TRAF6

TRIM25

TRAF2/6

IRAK1/4

IRAK1/4

TRAF6TRAM

MyD88

MyD88

TRIFRIP1

TRAF6TRAF2

NIK

NIK

cIAP1/2

(S866, S870)

Partialdegradation

IKK

Noncanonical pathway

TRAF5

TRAF2

TRAF2TRAF3

TRAF3TRAF6

TRAF3

RANK

TLR4

CD14

CD40

Virus

XEDAR

EDAR EDARADD

NF-B Signaling Pathway

NF-B Signaling Pathway

A

B

FIG A7. Lenalidomide target pathway: nuclear factor-κB (NF-κB) signaling pathway. (A) Cutaneous T-cell lym-phoma. (B) Adult T-cell leukemia/lymphoma. Green gradient colors indicate downregulation of the gene, and redcolors indicate upregulation of the gene relative to the control sample. BCR, B-cell receptor; H/R, hypoxia/re-oxygenation; IL, interleukin; KEGG, Kyoto Encyclopedia of Genes and Genomes; LPS, lipopolysaccharide; MHC,major histocompatibility complex; TCR, T-cell receptor; TNF-α, tumor necrosis factor-α; UV, ultraviolet.




HumanTarget cell

(MHCclass I)

Normal cell

Stressed ortumor cell

Apoptosis

Infectedcell

?

DNA

CASP3 Perforin

TRAILR

CD48

IFNyR

FAS FASL

FASL


JAK-STATsignaling pathway

Cytotoxic granulesmovement and exocytosis

Perforin

Granzyme

TRAIL

IFNsR

2B4

NKG2D DAP-10

SAP

EAT-2

LAT

+p

+p

+p

+p

+p

+p

Ca2+

DAG

NK-cell activation

IP3 -p

-p

-p

+p

+p

+p

Fyn

Syk

ZAP70

Lck

DAP-12

ITGAL

CD94NKG2A/B

KIR2DL

KIR3DL2

KIR3DL1HLA-B

HLA-A3

HLA-G1

HLA-B46

HLA-C

HLA-E

ICAM1/2

MICA

MICB

ULPP1-3

HA

?

?

?

SHP-2

SHP-1

Activating receptors

ITGB2

KIR2DS

NKG2C/E

NKp44

NKp46

FcR1

CD3FcRIII

Antigen

AntibodyIgG

NKp30

CD94 SLP-76

LATPLC

PI3K

Shc Grb2

PLC

Fyn

Sos Ras Raf

ERK1/2

MULT1

Rae-1

H-60

?

m157Antigen

IgGAntibody

NKG2DL

Cytokine release

TNF-

GM-CSF

IFN-DNA

DNA

NFATCaN

PKC


NKR-P1C

NKp46

FcRIII

Ly49H

CD94NKG2C

Ly49D

ITGAL

NKG2A/BCD94


NK cellInhibitory receptors

Ly49I

Ly49G2

Ly49C

Ly49AH-2Db

(MHCclass I)

Target cell

H-2Dd

H-2Dk

H-2Kb

H-2Kd

Qa-1

ICAM1/2

Inhibitory receptors

ITGB2

(MCMV)

?

MEK1/2MAPK signalingpathway

PAK1

Vav

Pyk-2

Rac

3BP2

IFNs

Bid

Granzyme


HumanTarget cell

(MHCclass I)

Normal cell

Stressed ortumor cell

Apoptosis

Infectedcell

?

DNA

CASP3 Perforin

Perforin

TRAILR

CD48

IFNR

FAS FASL

FASL


JAK-STATsignaling pathway

Cytotoxic granulesmovement and exocytosis

Perforin

Granzyme

TRAIL

IFNsR

2B4

NKG2D DAP-10

SAP

EAT-2

LAT

+p

+p

+p

+p

+p

+p

Ca2+

DAG

NK-cell activation

IP3 -p

-p

-p

+p

+p

+p

Fyn

Syk

ZAP70

Lck

DAP-12

ITGAL

CD94NKG2A/B

KIR2DL

KIR3DL2

KIR3DL1HLA-B

HLA-A3

HLA-G1

HLA-B46

HLA-C

HLA-E

ICAM1/2

MICA

MICB

ULPP1-3

HA

?

?

?

SHP-2

SHP-1


ITGB2

KIR2DS

NKG2C/E

NKp44

NKp46

FcR1

CD3FcRIII

Antigen

Antibody

IgG

NKp30

CD94 SLP-76

LATPLC

PI3K

Shc Grb2

PLC

Fyn

Sos Ras Raf

ERK1/2

MULT1

Rae-1

H-60

?

m157Antigen

IgGAntibody

NKG2DL

Cytokine release

TNF-

GM-CSF

IFN-

TRAIL

TRAIL

DNA

DNA

NFATCaN

PKC


NKR-P1C

NKp46

FcRIII

Ly49H

CD94NKG2C

Ly49D

ITGAL

NKG2A/BCD94


NK cellInhibitory receptors

Ly49I

Ly49G2

Ly49C

Ly49AH-2Db

(MHCclass I)

Target cell

H-2Dd

H-2Dk

H-2Kb

H-2Kd

Qa-1

Inhibitory receptors

ITGB2

(MCMV)

?

MEK1/2MAPK signalingpathway

PAK1

Vav

Pyk-2

Rac

3BP2

IFNs

Bid

Granzyme


ICAM1/2

PI(3,4,5)P3

Perforin

PI(3,4,5)P3

NK-Cell–Mediated Cytotoxicity

NK-Cell–Mediated Cytotoxicity

–1 0 1

–1 0 1

A

B

FIG A8. Lenalidomide target pathway: natural killer (NK)-cell–mediated cytotoxicity. (A) Cutaneous T-cell lymphoma. (B)Adult T-cell leukemia/lymphoma. Green gradient colors indicate downregulation of the gene, and red colors indicateupregulation of the gene relative to the control sample. JAK-STAT, Janus kinase–signal transducers and activators oftranscription; KEGG, Kyoto Encyclopedia of genes and genomes; MAPK, mitogen-activated protein kinase; MCMV, murinecytomegalovirus; MHC, major histocompatibility complex.

Hijikata et al



CC subfamily

Chemokines

Cytokine-Cytokine Receptor Interaction

CXC subfamily

The class I helical cytokines

-Chain utilizing IL6/12-like Interferon family

IL1-like cytokines

IL17-like cytokinesThe class

II helical cytokinesIL10/28-like

Human/murine

Human

Prolactin family

IL4-like

C subfamily

CX3C subfamily

Nonclassified

NO signaltransduction

TNF family TGF- family

CCL1

CCL25

CCL19

CCL21

CCL3L1

CCL4CCL4L1

CCL4L2

CCL17

CCL22

CCL5

CCL3

CCL8

CCL9

CCL14

CCL16

CCL23

CCL15

CCL13

CCL6

CCL7

CCL2

CCL12

CCL11

CCL24

CCL27

CCL28

CCL18

CCL20



CCR6

CCR10

CCR3

CCR2

CCR11

CCR3

CCR1

CCR2

CCR11

CCR3

CCR5

CCR4

CCR7

CCR11

CCR9

CCR8 CXCL1

CXCL5

CXCL6

CXCL8

CXCL2

CXCL3

CXCL7

CXCL4

CXCL9

CXCL10

CXCL11

CXCL13

CXCL12

CXCL16

CXCL14

CXCR6

CXCR7

CXCR4

CXCR5

CXCR3

CXCR2

CXCR1

IL2RA

IL2

IL4

IL7

IL9

IL15

IL21

IL3

IL5

IL4

IL13

EPO

GH1

GH2

PRL

TPO

CSF3

LEPIL29

IL28BIL28A

IL26

IL22

IL24

IL20

IL19

IL10

OSM

OSM

LIF

CTF1

CNTF

CLCF1

IL31

IL27A

IL23A

IL12

IL11

IL6IL6R

IL6ST

IL11RA

IL12RB1

IL23RIL12RB1

IL27RA

IL31RA

IL6ST

OSMR

CNTFRLIFR

IL6ST

?LIFR

IL6ST

LIFRIL6ST

OSMRIL6ST

IL12RB2

IL6ST

IL10RAIL10RB

IL20RAIL20RB

IL22RA1IL20RB

IL22RA1IL10RB

IL20RAIL10RB

IL28RAIL10RB

CSF1

IL34

IL32

IL16

IL17E

IL17D

IL17C

IL17B

IL17F

IL17A

IL18

IL1F7

IL1F9

IL1F10

IL1F8

IL1F6

IL1F5

IL1RN

IL1R1

IL1R2

IL1RL2IL1RAP

IL18RAP

IL1RAP

IL17RC

IL17RB

IL17RE

IL17RAIL17RB

CD4

CSF1R

?

?

IL17RA

ST2

IL18R1

IL1RAPIL1B

IL1A

IFNG

IFNT1

IFNK

IFNW1

IFNB1

IFNATNF

LTA

LTB

LIGHT

FASLG

VEGI

TRAIL

?

EDA-A1

EDA-A2EDA

EDA

NGF

RANKL

TWEAK

CD70

CD30L

CD40LG

41BBL

OX-40L

GITRL

APRIL

BAFF

?

?

DCR3

FAS

HVEM

LTBR

TNFR2

TNFR1TGFB1

TGFB2

TGFB3

GDF15

GDF2

BMP10

BMP3

GDF10

GDF11

MSTN

INHBA

INHBBGDF1

GDF3

NODAL

GDF9

INHBE

AMH

AMHR2

AMHR2ACVR1

ACVR1B

ACVR2B

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVRL1BMPR2

ACVRL1

ACVRL1

TGFBR2

BMP2

BMP4

GDF5

GDF6

GDF7

BMP15

BMP5

BMP6

BMP7

BMP8

TGFBR2

TGFBR2TGFBR1

ACVR2A

?

TGFBR1

TGFBR1

ACVR1B

ACVR1B

ACVR1C

ACVR1CACVR2A

BMPR2

BMPR2BMPR1B

BMPR1B

BMPR1B

BMPR1A

BMPR1A

BMPR1A

BMPR2

BMPR2BMPR1B

BMPR1B

BMPR1B

BMPR1A

BMPR1A

BMPR1A

BMPR2

BMPR2

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVR1

ACVR1

ACVR1

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVR2A

ACVR2B

?

?

BMPR1A

INHBC

INHA

DR3

DR4

DR5

DCR1

DCR2

DR6

EDAR

XEDAR

NGFR

RANK

FN14

CD27

CD30

CD40

41BB

Ox40

GITR

BCMA

TACI

BAFFR

TROY

RELT

OPG

IFNAR1IFNAR2

IFNGR1IFNGR2

IL33

TSLP

CSF2

IL2RBIL2RG

IL2RBIL2RG

IL4R

IL7R

IL9R

IL15RA

IL2RG

IL2RG

IL2RG

IL2RB

IL21RIL2RG

IL7RTSLPR

CSF2RBIL3RA

CSF2RB

CSF2RB

IL4R

IL4R

IL4R

IL13RA1

IL13RA2

IL13RA1

IL13RA2

EPOR

GHR

PRLR

MPL

CSF3R

LEPR

CSF2RA

IL5RA

IL2RG

CXCL15

CXCL17

XCL1XCR1

?

?

?

CX3CR1

XCL2

CX3CL1

CXCL4L1

?

CCL26

CC subfamilyChemokines

Cytokine-Cytokine Receptor Interaction

CXC subfamilyThe class I helical cytokines

-Chain utilizing IL6/12-like Interferon family

IL1-like cytokines

IL17-like cytokines

The class II helical cytokinesIL10/28-like

Human/murine

Human

Prolactin family

IL4-like

C subfamily

CX3C subfamily

Nonclassified

NO signaltransduction

TNF family TGF- family–1 0 1

CCL1

CCL25

CCL19

CCL21

CCL3L1

CCL4CCL4L1

CCL4L2

CCL17

CCL22

CCL5

CCL3

CCL8

CCL9

CCL14

CCL16

CCL123

CCL15

CCL13

CCL6

CCL7

CCL2

CCL12

CCL11

CCL24

CCL27

CCL28

CCL18

CCL20 CCR6

CCR10

CCR3

CCR2

CCR11

CCR3

CCR1

CCR2

CCR11

CCR3

CCR5

CCR4

CCR7

CCR11

CCR9

CCR8 CXCL1

CXCL5CXCL6

CXCL8

CXCL2

CXCL3

CXCL7

CXCL4

CXCL9

CXCL10

CXCL11

CXCL13

CXCL12

CXCL16

CXCL14

CXCR6

CXCR7

CXCR4

CXCR5

CXCR3

CXCR2

CXCR1

IL2RA

IL2

IL4

IL7

IL9

IL15

IL21

IL3

IL5

IL4

IL13

EPO

GH1

GH2

PRL

TPO

CSF3

LEPIL29

IL28BIL28A

IL26

IL22

IL24

IL20

IL19

IL10

OSM

OSM

LIF

CTF1

CNTF

CLCF1

IL31

IL27A

IL23A

IL12

IL11

IL6 IL6RIL6ST

IL11RA

IL12RB1

IL23RIL12RB1

IL27RA

IL31RA

IL6ST

OSMR

CNTFRLIFR

IL6ST

?LIFR

IL6ST

LIFRIL6ST

OSMRIL6ST

IL12RB2

IL6ST

IL10RAIL10RB

IL20RAIL20RB

IL22RA1IL20RB

IL22RA1IL10RB

IL20RAIL10RB

IL28RAIL10RB

CSF1

IL34

IL32

IL16

IL17E

IL17D

IL17C

IL17B

IL17F

IL17A

IL18

IL1F7

IL1F9IL1F10

IL1F8

IL1F6

IL1F5

IL1RN

IL1R1

IL1R2

IL1RL2IL1RAP

IL18RAP

IL1RAP

IL17RC

IL17RB

IL17RE

IL17RAIL17RB

CD4

CSF1R

?

?

IL17RA

ST2

IL18R1

IL1RAPIL1B

IL1A

IFNG

IFNT1

IFNK

IFNW1

IFNB1

IFNATNF

LTA

LTB

LIGHT

FASLG

VEGI

TRAIL

?

EDA-A1

EDA-A2EDA

EDA

NGF

RANKL

TWEAK

CD70

CD30L

CD40LG

41BBL

OX-40L

GITRL

APRIL

BAFF

?

?

DCR3

FAS

HVEM

LTBR

TNFR2

TNFR1TGFB1

TGFB2

TGFB3

GDF15

GDF2

BMP10

BMP3

GDF10

GDF11

MSTN

INHBA

INHBBGDF1

GDF3

NODAL

GDF9

INHBE

AMH

AMHR2

AMHR2ACVR1

ACVR1B

ACVR2B

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVRL1BMPR2

ACVRL1

ACVRL1

TGFBR2

BMP2

BMP4

GDF5

GDF6

GDF7

BMP15

BMP5

BMP6

BMP7

BMP8

TGFBR2

TGFBR2TGFBR1

ACVR2A

?

TGFBR1

TGFBR1

ACVR1B

ACVR1B

ACVR1C

ACVR1CACVR2A

BMPR2

BMPR2BMPR1B

BMPR1B

BMPR1B

BMPR1A

BMPR1A

BMPR1A

BMPR2

BMPR2BMPR1B

BMPR1B

BMPR1B

BMPR1A

BMPR1A

BMPR1A

BMPR2

BMPR2

ACVR2B

ACVR2A

ACVR2A

ACVR2A

ACVR1

ACVR1

ACVR1

ACVR2B

ACVR2A

ACVR2B

ACVR2A

ACVR2A

ACVR2B

?

?

BMPR1A

INHBC

INHA

DR3

DR4

DR5

DCR1

DCR2

DR6

EDAR

XEDAR

NGFR

RANK

FN14

CD27

CD30

CD40

41BB

Ox40

GITR

BCMA

TACI

BAFFR

TROY

RELT

OPG

IFNAR1IFNAR2

IFNGR1IFNGR2

IL33

TSLP

CSF2

IL2RBIL2RG

IL2RBIL2RG

IL4R

IL7R

IL9R

IL15RA

IL2RG

IL2RG

IL2RG

IL2RB

IL21RIL2RG

IL7RTSLPR

CSF2RBIL3RA

CSF2RB

CSF2RB

IL4R

IL4R

IL4R

IL13RA1

IL13RA2

IL13RA1

IL13RA2

EPOR

GHR

PRLR

MPL

CSF3R

LEPR

CSF2RA

IL5RA

IL2RG

CXCL15

CXCL17

XCL1XCR1

?

?

?

CX3CR1

XCL2

CX3CL1

CXCL4L1

?

CCL26

–1 0 1

A

B

FIG A9. Lenalidomide target pathway: cytokine-cytokine receptor interaction. (A) Cutaneous T-cell lymphoma. (B) Adult T-cellleukemia/lymphoma. Green gradient colors indicate downregulation of the gene, and red colors indicate upregulation of thegene relative to the control sample. IFN, interferon; IL, interleukin; KEGG, Kyoto Encyclopedia of genes and genomes; TGF-β,transforming growth factor-β; TNF, tumor necrosis factor.




TNF Signaling Pathway


cIAP1/2

ASK1

TAB1/2/3TAK1

NIKNF-B

Tpl2

IKK

IKK NF-B

PGAM5LMLKL

PI3K

TRAF1

TNF/LTA

TNF

TRAF2TRAF3

NIK

cIAP1/2

AIP1

RIP

JNK

MKK3

IKKs

NF-B

IB

p38

c-Jun

IRF1

Apoptosis

DNAIFN

Cell survival

Degradation

Necroptosis

DNA

DNA

Akt+p

+p

+p

+p

-p

+p

+p

+p

+p

+p

+p

+p

+p

+u

+p +p

+p

+p

RIP3RIP1

Deubiquitination

Necrosome

(Limited expression)

PGAM5SDrp1

NF-Bsignaling pathway

IB ubiquitinationand degradation


PI3K-Aktsignaling pathway

MEK1

MKK3/6

MSK1/2

AP-1

c/EBP

CREB

ERK1/2

p38

JNK1/2

ITCH c-FLIP

CASP3Apoptosis

Apoptosis

–1 0 1

–1 0 1

Ccl20Ccl5Ccl2

Cxcl1

Cxcl5

Csf1

Fas

IL1b

Bcl3

Fos

Mmp14Mmp9Mmp3

Vegfc

Nod2

Icam1 Sele Vcam1

Edn1

PRRs

Cell adhesion

Ptgs2

Synthesis of inflammatory mediators

Vascular effects

Jun JunB

Ifi47

Transcription factors

Remodeling of extracellular matrix

Intracellular signaling (negative)

Intracellular signaling (positive)

Nfkbia Socs3

IL6 IL15 Lif Tnf

Traf1Tnfaip3

Csf2

IL18R1

Leukocyte activation

Surface receptors

Inflammatory cytokines

Cxcl2

Cxcl10 Cx3cl1

Cxcl3

Leukocyte recruitment

CASP7CASP10

CASP8

FADD

MKK4/7

MAPKsignaling pathway

cIAP1/2 degradation

IBIKK

TRAF2/5

RIP1TRADD

SODD

Jag1

TNF Signaling Pathway


cIAP1/2

ASK1

TAB1/2/3TAK1

NIKNF-B

Tpl2

IKK

IKK NF-B

PGAM5LDrp1

PI3K

TRAF1

TNF/LTA

TNF

TRAF2

TRAF3

NIK

cIAP1/2

AIP1

RIP

JNK

MKK3

IKKs

NF-B

IB

p38

c-Jun

IRF1

Apoptosis

DNAIFN

Cell survival

Degradation

Necroptosis

DNA

DNA

Akt+p

+p

+p

+p

-p

+p

+p

+p

+p

+p

+p

+p

+p

+u

+p +p

+p

+p

RIP3 MLKLRIP1

Deubiquitination

Necrosome

(Limited expression)

PGAM5S

NF-Bsignaling pathway

IB ubiquitinationand degradation


PI3K-Aktsignaling pathway

MEK1

MKK3/6

MSK1/2

AP-1

c/EBP

CREB

ERK1/2

p38

JNK1/2

ITCH c-FLIP

CASP3Apoptosis

ApoptosisCcl20Ccl5Ccl2

Cxcl1

Cxcl5

Csf1

Fas

IL1b

Bcl3

Fos

Mmp14Mmp9Mmp3

Vegfc

Nod2

Icam1 Sele Vcam1

Edn1

PRRs

Cell adhesion

Ptgs2

Synthesis of inflammatory mediators

Vascular effects

Jun JunB

Ifi47

Transcription factors

Remodeling of extracellular matrix

Intracellular signaling (negative)

Intracellular signaling (positive)

Nfkbia Socs3

IL6 IL15 Lif Tnf

Traf1Tnfaip3

Csf2

IL18R1

Leukocyte activation

Surface receptors

Inflammatory cytokines

Cxcl2

Cxcl10 Cx3cl1

Cxcl3

Leukocyte recruitment

CASP7CASP10

CASP8

FADD

MKK4/7

MAPKsignaling pathway

cIAP1/2 degradation

IBIKK

TRAF2/5

RIP1TRADD

SODD

Jag1

TNFR1

TNFR2

TNFR1

TNFR2

A

B

FIG A10. Lenalidomide target pathway: tumor necrosis factor (TNF) signaling pathway. (A) Cutaneous T-cell lymphoma. (B)Adult T-cell leukemia/lymphoma. Green gradient colors indicate downregulation of the gene, and red colors indicateupregulation of the gene relative to the control sample. KEGG, Kyoto Encyclopedia of genes and genomes; MAPK, mitogen-activated protein kinase; NF-κB, nuclear factor-κB; PRR, pattern recognition receptor.

Hijikata et al



B

7 Nov 2017 12 Jan 2018 7 Feb 2018

Perc

ent

CD3–CD16+CD56+/lym

CD3+CD8+

CD3+CD4+CD45RA–Foxp3+high

0

10

20

30

40

50

60

70

16 Oct 2017

A

SSC-W, FSC-W subset102 103 104 105

CD235a/PI

0

0

102 103 104 1050 102 103 104 1050

102 103 104 1050 102 103 104 1050

50K

100K

150K

200K

250KFS

C56.6

PI–CD235a–250K

SSC

0

0

105

104

103

102

0

105

104

103

102

0

105

104

103

102

0

105

104

103

102

0

105

104

103

102

CD14

73.3

CD3–CD19– cells CD16

CD56

90.6

CD14– cells CD3

CD19

44.3

50.9

4.75

CD3+ T cells CD8

CD4

30.4

63

CD4+ T cells (Foxp3)

CD45

RA0.746 0.0403

6.0780.4 12.7

Doublet free

CD3+ T cells

CD235a–PI– cells CD14– cells CD3–CD19– cells

CD4+ T cells

50K 100K 150K 200K

FIG A11. Immunophenotypes of peripheral blood mononuclear cells (PBMNCs) from the patient during lenalidomide treatment. PBMNCs were stainedfor CD3, CD4, CD8, CD14, CD16, CD19, CD45RA, CD235a/PI, and Foxp3. (A) Lymphocytes (lym) were identified based on light scatter characteristics(low forward and low side scatter) and negative for CD14 and CD235/PI. Natural killer (NK) cells were defined as CD3−CD16+CD56+ after gating for CD19−

lymphocytes. Effector regulatory T (Treg) cells were defined as CD4+CD45RA−Foxp3+high. (B) The frequencies of NK cells and ratio of CD3+CD8+ T cellsincreased after lenalidomide treatment, which was not accompanied by an increase in effector Treg cells. FSC-W, forward scatter pulse width; SSC-W,side scatter pulse width.




TABLEA1

.Cod

ingVa

riantsIden

tified

From

Who

le-ExomeSe

quen

cing

Tier

Grad

ing

(driv

er)

Chrom

Positio

nRe

fALT

Depth

(tumor)

Depth

(normal)

VAF

−Log

10

Pa

Gene

AminoAc

idCh

ange

COSM

IC70

IDSIFT

PolyPh

en-2

MutationTaster

117

7578

290

CT

9014

80.56

725

.1TP

53splicing

COSM

O41

3986

9—

—D

2(VUS)

1740

3121

26TC

TGGCAC

T14

813

40.07

43.0

KCNH4

p.P99

3fs

——

——

2(VUS)

1753

0074

53G

T89

630.07

91.4

TOM1L

1p.R24

7L—

DD

D

2(VUS)

418

7539

038

GT

164

133

0.10

44.4

FAT1

p.T2

901K

—T

PD

2(VUS)

1870

8042

1C

T12

398

0.12

23.8

LAMA1

p.A33

T—

TD

D

2(VUS)

312

6194

576

CG

4352

0.14

02.2

ZXDC

p.G45

R—

DB

N

2(VUS)

1772

8690

18G

A43

530.14

02.2

FDXR

p.R18

W—

DD

N

2(VUS)

1832

1506

5C

T57

520.14

02.2

MYO

M1

p.A53

T—

TD

D

2(VUS)

119

9519

97C

G49

840.14

33.2

MINOS1

p.Q11

2E—

——

—

2(VUS)

296

8011

04C

A97

790.14

43.5

ASTL

p.D77

Y—

DD

N

2(VUS)

1328

6113

93G

T12

511

30.14

45.2

FLT3

p.P41

3Q—

TD

D

2(VUS)

216

6854

673

GA

102

117

0.14

74.1

SCN1A

p.P14

51S

—D

DD

2(VUS)

1395

3638

07CGCGGCGGC

GGCGGCGGCGGCA

C60

670.15

03.1

SOX2

1p.15

9_16

6del

——

——

2(VUS)

412

1957

868

GA

9981

0.15

23.0

NDNF

p.R42

0X—

T—

D

2(VUS)

316

4732

921

CA

149

163

0.15

47.8

SIp.C13

30F

—T

PN

2(VUS)

1779

6619

73G

A17

316

10.16

28.5

HGS

p.R33

2QCOSM

3388

305

TD

D

2(VUS)

913

1252

77TT

T11

510

10.16

55.5

MPD

Zp.K15

82fs

——

——

2(VUS)

1739

5374

60G

T15

712

30.16

66.7

KRT3

4p.Q18

8K—

DB

N

2(VUS)

336

8734

72A

T12

113

40.17

47.2

TRAN

K1p.C24

90X

—T

—A

2(VUS)

995

2678

18AAATA

GA

134

137

0.17

97.8

ECM2

p.S4

86fs

——

——

2(VUS)

X15

5915

54GG

G53

430.18

92.7

ACE2

p.P49

2fs

——

——

2(VUS)

119

9520

61C

T63

740.19

04.3

MINOS1

p.S1

33F

——

——

2(VUS)

1689

6574

21C

T18

416

10.19

68.3

CPNE7

p.H45

0Y—

DD

D

2(VUS)

1870

5260

84G

A85

760.21

24.3

NET

O1

p.S1

49L

—T

DD

2(VUS)

353

5356

80A

T61

550.21

33.8

CACN

A1D

p.N13

9I—

DD

D

2(VUS)

178

4308

24C

A12

114

90.21

57.4

FUBP1

p.E1

89X

—T

—A

2(VUS)

123

7802

393

GT

7312

70.21

97.5

RYR

2p.R23

36I

—D

DD

2(VUS)

832

6568

5C

T18

213

80.22

09.1

CSMD1

p.E6

03K

—T

DD

2(VUS)

1193

5539

92CACAGCAGCG

C93

960.22

67.0

VSTM

5p.15

6_15

9del

——

——

2(VUS)

111

5840

44C

T48

610.22

94.2

PTCH

D2

p.T8

03M

—D

DD

2(VUS)

146

6509

54G

T55

480.25

54.2

TSPA

N1

p.V2

18L

—T

DD

2(VUS)

1286

7284

3AGATA

A12

013

20.25

811

.0CL

EC4D

p.D13

6fs

——

——

(Con

tinue

don

followingpa

ge)

Hijikata et al



TABLEA1

.Cod

ingVa

riantsIden

tified

From

Who

le-ExomeSe

quen

cing

(Con

tinue

d)Tier

Grad

ing

(driv

er)

Chrom

Positio

nRe

fALT

Depth

(tumor)

Depth

(normal)

VAF

−Log

10

Pa

Gene

AminoAc

idCh

ange

COSM

IC70

IDSIFT

PolyPh

en-2

MutationTaster

2(VUS)

2064

4532

CG

2534

0.28

02.9

SCRT2

p.G23

6A—

DD

D

2(VUS)

1915

8068

29G

A15

113

60.28

512

.0CY

P4F1

2p.R40

0Q—

DD

N

2(VUS)

1739

2217

48G

T12

212

80.28

712

.2KR

TAP2

-4p.T1

17N

—T

—N

2(VUS)

146

6509

55T

A52

420.28

84.1

TSPA

N1

p.V2

18E

—D

DD

2(VUS)

1720

1568

52G

T51

740.29

45.4

SPEC

C1p.S8

78I

COSM

1609

946

TD

D

2(VUS)

810

3287

953

CT

155

113

0.29

712

.4UBR5

p.G22

05R

—D

DD

2(VUS)

1480

2714

80C

A12

190

0.29

89.8

NRXN

3p.S9

44Y

——

DD

2(VUS)

2043

3535

25A

G41

320.31

73.5

WISP2

p.S1

42G

—T

PN

2(VUS)

X13

8633

26A

T11

286

0.32

110

.0F9

p.K18

8X—

T—

A

2(VUS)

729

6395

4G

T10

988

0.33

010

.5CA

RD11

p.S6

18Y

—D

DD

2(VUS)

313

5871

427

AG

9710

70.34

012

.1MSL

2p.L9

9P—

DB

D

2(VUS)

1953

5181

31A

G21

121

30.34

123

.4ER

VV-1

p.N26

3S—

——

—

2(VUS)

218

6609

095

CG

7010

10.34

310

.5FS

IP2

p.T2

34S

—D

—N

2(VUS)

2147

6274

32C

A42

720.35

76.2

LSS

p.E3

79D

—D

DD

2(VUS)

542

7970

23G

A53

630.37

77.8

CCDC1

52p.E1

75K

—T

PD

2(VUS)

773

0119

83G

T46

480.39

16.5

MLX

IPL

p.L3

78I

—T

DN

2(VUS)

1944

0966

99G

A51

290.39

24.6

IRGQ

p.P45

1S—

TD

N

2(VUS)

729

6395

5A

G11

488

0.40

413

.3CA

RD11

p.S6

18P

—D

DD

2(VUS)

1548

0552

95A

T71

116

0.40

812

.8SE

MA6

Dp.L2

47F

—D

DD

2(VUS)

1946

9156

85C

T15

615

60.41

019

.6CC

DC8

p.R12

8H—

DD

D

2(VUS)

1168

3694

16C

CC

9867

0.42

98.0

PPP6

R3

p.A76

0fs

——

——

2(VUS)

1256

4818

67C

A77

780.45

512

.8ER

BB3

p.Y2

65X

—T

—D

2(VUS)

1876

7552

35G

A83

830.45

813

.5SA

LL3

p.A10

82T

COSM

3388

512

TP

N

2(VUS)

739

0464

68G

A91

800.46

214

.0PO

U6F

2splicing

——

—N

2(VUS)

1232

1375

70GTG

TG

5147

0.47

18.3

KIAA

1551

p.12

28_

1228

del

——

——

2(VUS)

642

9930

08G

A72

Documents

Successful Clinical Sequencing by Molecular ......more widespread as a clinical tool for accurate di-agnosis and proper treatment in clinical oncology.4 However, the use of various