Plasma cell development-based prediction of prognosis and treatment response in individual multiple myeloma
Sitao Jiang
,
Yuan Yang
,
Man Yao
,
Ayaz Ali Samo
,
Pengli Xiao
,
Qinglan Cao
,
Jiuyi Li
,
Huijuan Wang
,
Wenming Chen
,
Xuzhang Lu
,
Yin Wu
,
Xiaolong Fan
1. Department of Biology, Key Laboratory of Cell Proliferation and Regulation Biology, Ministry of Education, School of Life Sciences, Beijing Normal University, Beijing 100875, China
2. Department of Physiology, University of Sindh, Jamshoro 76080, Pakistan
3. College of Life Sciences, Sichuan Normal University, Chengdu 610101, China
4. Department of Hematology, Chaoyang Hospital, Capital Medical University, Beijing 100020, China
5. Department of Hematology, Changzhou No. 2 People’s Hospital, The Affiliated Hospital of Nanjing Medical University, Changzhou 213100, China
xfan@bnu.edu.cn
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History+
Received
Accepted
Published Online
2025-06-18
2025-09-17
2025-11-18
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(6854KB)
Abstract
We hypothesized that gene networks converged between plasma cell development and multiple myeloma (MM) pathogenesis may better explain the clinical heterogeneity in individual MM patients. Here, we transformed the reciprocal expression pattern between a gene module centered on the expression of MCL1 and another gene module represented by the expression of TLR10 from individual MM transcriptomes into a myeloma classification score (MCS). MCS enabled prognostication in 1738 patients with newly diagnosed MM (NDMM) and 319 patients with relapsed/refractory MM (RRMM) from our own observational cohort, from MMRF, and from five prospective trials. MCS also enabled the discrimination between progressive and stable disease states in the longitudinal samples from 85 patients in MMRF and the PETHEMA/GEM2012MENOS65 trial. MCS further enabled prediction of the responses to bortezomib-based treatment in 425 patients enrolled in the HOVON-65/GMMG-HD4 and APEX (039) trials, and the response to carfilzomib-based treatment in 86 transplantation-eligible patients from MMRF. MCS-defined risk groups harbored distinct targetable pathways, including unfolded protein response, replication stress, genomic instability and interferon responses. However, MCS-based individualized prediction of prognosis and treatment response was independent of the hitherto available prognostic models. Thus, MCS represents an alternative biomarker for risk stratification and prediction of treatment response in individual MM patients.
D’Agostino M, Cairns DA, Lahuerta JJ, Wester R, Bertsch U, Waage A, Zamagni E, Mateos MV, Dall’Olio D, van de Donk NWCJ, Jackson G, Rocchi S, Salwender H, Bladé Creixenti J, van der Holt B, Castellani G, Bonello F, Capra A, Mai EK, Dürig J, Gay F, Zweegman S, Cavo M, Kaiser MF, Goldschmidt H, Hernández Rivas JM, Larocca A, Cook G, San-Miguel JF, Boccadoro M, Sonneveld P. Second Revision of the international staging system (R2-ISS) for overall survival in multiple myeloma: a European Myeloma Network (EMN) report within the HARMONY project. J Clin Oncol2022; 40(29): 3406–3418
[2]
Palumbo A, Avet-Loiseau H, Oliva S, Lokhorst HM, Goldschmidt H, Rosinol L, Richardson P, Caltagirone S, Lahuerta JJ, Facon T, Bringhen S, Gay F, Attal M, Passera R, Spencer A, Offidani M, Kumar S, Musto P, Lonial S, Petrucci MT, Orlowski RZ, Zamagni E, Morgan G, Dimopoulos MA, Durie BGM, Anderson KC, Sonneveld P, San Miguel J, Cavo M, Rajkumar SV, Moreau P. Revised international staging system for multiple myeloma: a report from International Myeloma Working Group. J Clin Oncol2015; 33(26): 2863–2869
[3]
Pawlyn C, Davies FE. Toward personalized treatment in multiple myeloma based on molecular characteristics. Blood2019; 133(7): 660–675
[4]
Caro J, Al Hadidi S, Usmani S, Yee AJ, Raje N, Davies FE. How to treat high-risk myeloma at diagnosis and relapse. Am Soc Clin Oncol Educ Book2021; 41(41): 291–309
[5]
Usmani SZ, Rodriguez-Otero P, Bhutani M, Mateos MV, Miguel JS. Defining and treating high-risk multiple myeloma. Leukemia2015; 29(11): 2119–2125
[6]
Kuiper R, Broyl A, de Knegt Y, van Vliet MH, van Beers EH, van der Holt B, el Jarari L, Mulligan G, Gregory W, Morgan G, Goldschmidt H, Lokhorst HM, van Duin M, Sonneveld P. A gene expression signature for high-risk multiple myeloma. Leukemia2012; 26(11): 2406–2413
[7]
Perrot A, Lauwers-Cances V, Tournay E, Hulin C, Chretien ML, Royer B, Dib M, Decaux O, Jaccard A, Belhadj K, Brechignac S, Fontan J, Voillat L, Demarquette H, Collet P, Rodon P, Sohn C, Lifermann F, Orsini-Piocelle F, Richez V, Mohty M, Macro M, Minvielle S, Moreau P, Leleu X, Facon T, Attal M, Avet-Loiseau H, Corre J. Development and validation of a cytogenetic prognostic index predicting survival in multiple myeloma. J Clin Oncol2019; 37(19): 1657–1665
[8]
Kumar SK, Dispenzieri A, Lacy MQ, Gertz MA, Buadi FK, Pandey S, Kapoor P, Dingli D, Hayman SR, Leung N, Lust J, McCurdy A, Russell SJ, Zeldenrust SR, Kyle RA, Rajkumar SV. Continued improvement in survival in multiple myeloma: changes in early mortality and outcomes in older patients. Leukemia2014; 28(5): 1122–1128
Ubels J, Sonneveld P, van Vliet MH, de Ridder J. Gene networks constructed through simulated treatment learning can predict proteasome inhibitor benefit in multiple myeloma. Clin Cancer Res2020; 26(22): 5952–5961
[11]
Mulligan G, Mitsiades C, Bryant B, Zhan F, Chng WJ, Roels S, Koenig E, Fergus A, Huang Y, Richardson P, Trepicchio WL, Broyl A, Sonneveld P, Shaughnessy JD Jr, Leif Bergsagel P, Schenkein D, Esseltine DL, Boral A, Anderson KC. Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib. Blood2007; 109(8): 3177–3188
[12]
Richardson PG, Xie W, Mitsiades C, Chanan-Khan AA, Lonial S, Hassoun H, Avigan DE, Oaklander AL, Kuter DJ, Wen PY, Kesari S, Briemberg HR, Schlossman RL, Munshi NC, Heffner LT, Doss D, Esseltine DL, Weller E, Anderson KC, Amato AA. Single-agent bortezomib in previously untreated multiple myeloma: efficacy, characterization of peripheral neuropathy, and molecular correlations with response and neuropathy. J Clin Oncol2009; 27(21): 3518–3525
[13]
Mehta J. Total therapy 2 in treatment of multiple myeloma: questions about gene expression profiling and treatment-related mortality. J Clin Oncol2011; 29(5): e124
[14]
Barlogie B, Tricot G, Anaissie E, Shaughnessy J, Rasmussen E, van Rhee F, Fassas A, Zangari M, Hollmig K, Pineda-Roman M, Lee C, Talamo G, Thertulien R, Kiwan E, Krishna S, Fox M, Crowley J. Thalidomide and hematopoietic-cell transplantation for multiple myeloma. N Engl J Med2006; 354(10): 1021–1030
[15]
Bergsagel PL, Kuehl WM, Zhan F, Sawyer J, Barlogie B, Shaughnessy J Jr. Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma. Blood2005; 106(1): 296–303
[16]
Zhan F, Huang Y, Colla S, Stewart JP, Hanamura I, Gupta S, Epstein J, Yaccoby S, Sawyer J, Burington B, Anaissie E, Hollmig K, Pineda-Roman M, Tricot G, van Rhee F, Walker R, Zangari M, Crowley J, Barlogie B, Shaughnessy JD Jr. The molecular classification of multiple myeloma. Blood2006; 108(6): 2020–2028
[17]
Broyl A, Hose D, Lokhorst H, de Knegt Y, Peeters J, Jauch A, Bertsch U, Buijs A, Stevens-Kroef M, Beverloo HB, Vellenga E, Zweegman S, Kersten MJ, van der Holt B, el Jarari L, Mulligan G, Goldschmidt H, van Duin M, Sonneveld P. Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients. Blood2010; 116(14): 2543–2553
[18]
Skerget S, Penaherrera D, Chari A, Jagannath S, Siegel DS, Vij R, Orloff G, Jakubowiak A, Niesvizky R, Liles D, Berdeja J, Levy M, Wolf J, Usmani SZ, Rifkin R, Meehan K, Benson D, Zonder J, Ascensao J, Gasparetto C, Hernández M, Trudel S, Dakhil S, Bahlis N, Paganini JV, Rios P, Sampol A, Mannem S, Silbermann R, Lunning M, Chu M, Milner C, Harroff A, Graham M, Shao S, Dodlapati J, de Larrea CF, Klein L, Kuzma C, Fonseca R, Azaceta G, Granell M, Martinez-Chamorro C, Balaraman R, Silva C, Chinea A, Costello C, Kambhampati S, Lewis DQ, Grossbard M, Yost K, Robles R, Sebag M, Harris W, Ngaiza J, Bar M, Shieh M, Min F, Onitilo A, Volterra F, Wachsman W, Yalamachili M, Abella E, Anderson L, Bargay J, Hassoun H, Hsu G, Kaya H, Menter A, Patel D, Richards D, Solomon W, Anderson R, Chandra S, Conde M, Girnius S, Matkiwsky M, Krsnik I, Kumar S, Oriol A, Rodríguez P, Roy V, Srinivas S, Steis R, Christofferson AW, Nasser S, Aldrich JL, Legendre C, Benard B, Miller C, Turner B, Kurdoglu A, Washington M, Yellapantula V, Adkins JR, Cuyugan L, Boateng M, Helland A, Kyman S, McDonald J, Reiman R, Stephenson K, Tassone E, Blanski A, Livermore B, Kirchhoff M, Rohrer DC, D’Agostino M, Gambella M, Collison K, Stumph J, Kidd P, Donnelly A, Zaugg B, Toone M, McBride K, DeRome M, Rogers J, Craig D, Liang WS, Gutierrez NC, Jewell SD, Carpten J, Anderson KC, Cho HJ, Auclair D, Lonial S, Keats JJ. Comprehensive molecular profiling of multiple myeloma identifies refined copy number and expression subtypes. Nat Genet2024; 56(9): 1878–1889
[19]
Shaughnessy JD Jr, Zhan F, Burington BE, Huang Y, Colla S, Hanamura I, Stewart JP, Kordsmeier B, Randolph C, Williams DR, Xiao Y, Xu H, Epstein J, Anaissie E, Krishna SG, Cottler-Fox M, Hollmig K, Mohiuddin A, Pineda-Roman M, Tricot G, van Rhee F, Sawyer J, Alsayed Y, Walker R, Zangari M, Crowley J, Barlogie B. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood2007; 109(6): 2276–2284
[20]
Bhutani M, Zhang Q, Friend R, Voorhees PM, Druhan LJ, Barlogie B, Sonneveld P, Morgan GJ, Symanowski JT, Avalos BR, Copelan EA, Usmani SZ. Investigation of a gene signature to predict response to immunomodulatory derivatives for patients with multiple myeloma: an exploratory, retrospective study using microarray datasets from prospective clinical trials. Lancet Haematol2017; 4(9): e443–e451
[21]
Shaughnessy JD Jr, Qu P, Usmani S, Heuck CJ, Zhang Q, Zhou Y, Tian E, Hanamura I, van Rhee F, Anaissie E, Epstein J, Nair B, Stephens O, Williams R, Waheed S, Alsayed Y, Crowley J, Barlogie B. Pharmacogenomics of bortezomib test-dosing identifies hyperexpression of proteasome genes, especially PSMD4, as novel high-risk feature in myeloma treated with Total Therapy 3. Blood2011; 118(13): 3512–3524
[22]
Chapman MA, Sive J, Ambrose J, Roddie C, Counsell N, Lach A, Abbasian M, Popat R, Cavenagh JD, Oakervee H, Streetly MJ, Schey S, Koh M, Willis F, Virchis AE, Crowe J, Quinn MF, Cook G, Crawley CR, Pratt G, Cook M, Braganza N, Adedayo T, Smith P, Clifton-Hadley L, Owen RG, Sonneveld P, Keats JJ, Herrero J, Yong K. RNA-seq of newly diagnosed patients in the PADIMAC study leads to a bortezomib/lenalidomide decision signature. Blood2018; 132(20): 2154–2165
[23]
Maura F, Rajanna AR, Ziccheddu B, Poos AM, Derkach A, Maclachlan K, Durante M, Diamond B, Papadimitriou M, Davies F, Boyle EM, Walker B, Hultcrantz M, Silva A, Hampton O, Teer JK, Siegel EM, Bolli N, Jackson GH, Kaiser M, Pawlyn C, Cook G, Kazandjian D, Stein C, Chesi M, Bergsagel L, Mai EK, Goldschmidt H, Weisel KC, Fenk R, Raab MS, Van Rhee F, Usmani S, Shain KH, Weinhold N, Morgan G, Landgren O. Genomic classification and individualized prognosis in multiple myeloma. J Clin Oncol2024; 42(11): 1229–1240
[24]
Maley CC, Aktipis A, Graham TA, Sottoriva A, Boddy AM, Janiszewska M, Silva AS, Gerlinger M, Yuan Y, Pienta KJ, Anderson KS, Gatenby R, Swanton C, Posada D, Wu CI, Schiffman JD, Hwang ES, Polyak K, Anderson ARA, Brown JS, Greaves M, Shibata D. Classifying the evolutionary and ecological features of neoplasms. Nat Rev Cancer2017; 17(10): 605–619
[25]
Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabasi AL. The human disease network. Proc Natl Acad Sci USA2007; 104(21): 8685–8690
[26]
Klein U, Dalla-Favera R. Germinal centres: role in B-cell physiology and malignancy. Nat Rev Immunol2008; 8(1): 22–33
[27]
De Silva NS, Klein U. Dynamics of B cells in germinal centres. Nat Rev Immunol2015; 15(3): 137–148
[28]
Samo AA, Li J, Zhou M, Sun Y, Yang Y, Zhang Y, Li J, van Duin M, Lu X, Fan X. MCL1 gene co-expression module stratifies multiple myeloma and predicts response to proteasome inhibitor-based therapy. Genes Chromosomes Cancer2018; 57(8): 420–429
[29]
Peperzak V, Vikstrom I, Walker J, Glaser SP, LePage M, Coquery CM, Erickson LD, Fairfax K, Mackay F, Strasser A, Nutt SL, Tarlinton DM. Mcl-1 is essential for the survival of plasma cells. Nat Immunol2013; 14(3): 290–297
[30]
Gupta VA, Matulis SM, Conage-Pough JE, Nooka AK, Kaufman JL, Lonial S, Boise LH. Bone marrow microenvironment-derived signals induce Mcl-1 dependence in multiple myeloma. Blood2017; 129(14): 1969–1979
[31]
Nair B, van Rhee F, Shaughnessy JD Jr, Anaissie E, Szymonifka J, Hoering A, Alsayed Y, Waheed S, Crowley J, Barlogie B. Superior results of Total Therapy 3 (2003–33) in gene expression profiling-defined low-risk multiple myeloma confirmed in subsequent trial 2006–66 with VRD maintenance. Blood2010; 115(21): 4168–4173
[32]
Sonneveld P, Schmidt-Wolf IG, van der Holt B, El Jarari L, Bertsch U, Salwender H, Zweegman S, Vellenga E, Broyl A, Blau IW, Weisel KC, Wittebol S, Bos GMJ, Stevens-Kroef M, Scheid C, Pfreundschuh M, Hose D, Jauch A, van der Velde H, Raymakers R, Schaafsma MR, Kersten MJ, van Marwijk-Kooy M, Duehrsen U, Lindemann W, Wijermans PW, Lokhorst HM, Goldschmidt HM. Bortezomib induction and maintenance treatment in patients with newly diagnosed multiple myeloma: results of the randomized phase III HOVON-65/GMMG-HD4 trial. J Clin Oncol2012; 30(24): 2946–2955
[33]
Heuck CJ, Qu P, van Rhee F, Waheed S, Usmani SZ, Epstein J, Zhang Q, Edmondson R, Hoering A, Crowley J, Barlogie B. Five gene probes carry most of the discriminatory power of the 70-gene risk model in multiple myeloma. Leukemia2014; 28(12): 2410–2413
[34]
Goicoechea I, Puig N, Cedena MT, Burgos L, Cordon L, Vidriales MB, Flores-Montero J, Gutierrez NC, Calasanz MJ, Ramos MLM, Lara-Astiaso D, Vilas-Zornoza A, Alignani D, Rodriguez I, Sarvide S, Alameda D, Garcés JJ, Rodriguez S, Fresquet V, Celay J, Garcia-Sanz R, Martinez-Lopez J, Oriol A, Rios R, Martin-Sanchez J, Martinez-Martinez R, Sarra J, Hernandez MT, de la Rubia J, Krsnik I, Moraleda JM, Palomera L, Bargay J, Martinez-Climent JA, Orfao A, Rosiñol L, Mateos MV, Lahuerta JJ, Blade J, San Miguel J, Paiva B. Deep MRD profiling defines outcome and unveils different modes of treatment resistance in standard- and high-risk myeloma. Blood2021; 137(1): 49–60
[35]
Danziger SA, McConnell M, Gockley J, Young MH, Rosenthal A, Schmitz F, Reiss DJ, Farmer P, Alapat DV, Singh A, Ashby C, Bauer M, Ren Y, Smith K, Couto SS, van Rhee F, Davies F, Zangari M, Petty N, Orlowski RZ, Dhodapkar MV, Copeland WB, Fox B, Hoering A, Fitch A, Newhall K, Barlogie B, Trotter MWB, Hershberg RM, Walker BA, Dervan AP, Ratushny AV, Morgan GJ. Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials. PLoS Med2020; 17(11): e1003323
[36]
Zhang Y, Li J, Yi K, Feng J, Cong Z, Wang Z, Wei Y, Wu F, Cheng W, Samo AA, Salomoni P, Yang Q, Huang Y, Kang C, Jiang T, Fan X. Elevated signature of a gene module coexpressed with CDC20 marks genomic instability in glioma. Proc Natl Acad Sci USA2019; 116(14): 6975–6984
[37]
Cristescu R, Mogg R, Ayers M, Albright A, Murphy E, Yearley J, Sher X, Liu XQ, Lu H, Nebozhyn M, Zhang C, Lunceford JK, Joe A, Cheng J, Webber AL, Ibrahim N, Plimack ER, Ott PA, Seiwert TY, Ribas A, McClanahan TK, Tomassini JE, Loboda A, Kaufman D. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science2018; 362(6411): eaar3593
[38]
Ayers M, Lunceford J, Nebozhyn M, Murphy E, Loboda A, Kaufman DR, Albright A, Cheng JD, Kang SP, Shankaran V, Piha-Paul SA, Yearley J, Seiwert TY, Ribas A, McClanahan TK. IFN-gamma-related mRNA profile predicts clinical response to PD-1 blockade. J Clin Invest2017; 127(8): 2930–2940
[39]
Facon T, Lee JH, Moreau P, Niesvizky R, Dimopoulos M, Hajek R, Pour L, Jurczyszyn A, Qiu L, Klippel Z, Zahlten-Kumeli A, Osman M, Paiva B, San-Miguel J. Carfilzomib or bortezomib with melphalan-prednisone for transplant-ineligible patients with newly diagnosed multiple myeloma. Blood2019; 133(18): 1953–1963
[40]
Kumar SK, Jacobus SJ, Cohen AD, Weiss M, Callander N, Singh AK, Parker TL, Menter A, Yang X, Parsons B, Kumar P, Kapoor P, Rosenberg A, Zonder JA, Faber E Jr, Lonial S, Anderson KC, Richardson PG, Orlowski RZ, Wagner LI, Rajkumar SV. Carfilzomib or bortezomib in combination with lenalidomide and dexamethasone for patients with newly diagnosed multiple myeloma without intention for immediate autologous stem-cell transplantation (ENDURANCE): a multicentre, open-label, phase 3, randomised, controlled trial. Lancet Oncol2020; 21(10): 1317–1330
[41]
Walker BA, Mavrommatis K, Wardell CP, Ashby TC, Bauer M, Davies FE, Rosenthal A, Wang H, Qu P, Hoering A, Samur M, Towfic F, Ortiz M, Flynt E, Yu Z, Yang Z, Rozelle D, Obenauer J, Trotter M, Auclair D, Keats J, Bolli N, Fulciniti M, Szalat R, Moreau P, Durie B, Stewart AK, Goldschmidt H, Raab MS, Einsele H, Sonneveld P, San Miguel J, Lonial S, Jackson GH, Anderson KC, Avet-Loiseau H, Munshi N, Thakurta A, Morgan GJ. Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma. Blood2018; 132(6): 587–597
[42]
Walker BA, Mavrommatis K, Wardell CP, Ashby TC, Bauer M, Davies F, Rosenthal A, Wang H, Qu P, Hoering A, Samur M, Towfic F, Ortiz M, Flynt E, Yu Z, Yang Z, Rozelle D, Obenauer J, Trotter M, Auclair D, Keats J, Bolli N, Fulciniti M, Szalat R, Moreau P, Durie B, Stewart AK, Goldschmidt H, Raab MS, Einsele H, Sonneveld P, San Miguel J, Lonial S, Jackson GH, Anderson KC, Avet-Loiseau H, Munshi N, Thakurta A, Morgan G. A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis. Leukemia2019; 33(1): 159–170
[43]
Ubels J, Sonneveld P, van Beers EH, Broijl A, van Vliet MH, de Ridder J. Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects. Nat Commun2018; 9(1): 2943
[44]
Decaux O, Lode L, Magrangeas F, Charbonnel C, Gouraud W, Jezequel P, Attal M, Harousseau JL, Moreau P, Bataille R, Campion L, Avet-Loiseau H, Minvielle S. Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myelome. J Clin Oncol2008; 26(29): 4798–4805
[45]
Cowan AJ, Allen C, Barac A, Basaleem H, Bensenor I, Curado MP, Foreman K, Gupta R, Harvey J, Hosgood HD, Jakovljevic M, Khader Y, Linn S, Lad D, Mantovani L, Nong VM, Mokdad A, Naghavi M, Postma M, Roshandel G, Shackelford K, Sisay M, Nguyen CT, Tran TT, Xuan BT, Ukwaja KN, Vollset SE, Weiderpass E, Libby EN, Fitzmaurice C. Global burden of multiple myeloma: a systematic analysis for the Global Burden of Disease Study 2016. JAMA Oncol2018; 4(9): 1221–1227
[46]
Sistigu A, Yamazaki T, Vacchelli E, Chaba K, Enot DP, Adam J, Vitale I, Goubar A, Baracco EE, Remédios C, Fend L, Hannani D, Aymeric L, Ma Y, Niso-Santano M, Kepp O, Schultze JL, Tüting T, Belardelli F, Bracci L, La Sorsa V, Ziccheddu G, Sestili P, Urbani F, Delorenzi M, Lacroix-Triki M, Quidville V, Conforti R, Spano JP, Pusztai L, Poirier-Colame V, Delaloge S, Penault-Llorca F, Ladoire S, Arnould L, Cyrta J, Dessoliers MC, Eggermont A, Bianchi ME, Pittet M, Engblom C, Pfirschke C, Préville X, Uzè G, Schreiber RD, Chow MT, Smyth MJ, Proietti E, André F, Kroemer G, Zitvogel L. Cancer cell-autonomous contribution of type I interferon signaling to the efficacy of chemotherapy. Nat Med2014; 20(11): 1301–1309
[47]
He Y, Wang L, Wei T, Xiao YT, Sheng H, Su H, Hollern DP, Zhang X, Ma J, Wen S, Xie H, Yan Y, Pan Y, Hou X, Tang X, Suman VJ, Carter JM, Weinshilboum R, Wang L, Kalari KR, Weroha SJ, Bryce AH, Boughey JC, Dong H, Perou CM, Ye D, Goetz MP, Ren S, Huang H. FOXA1 overexpression suppresses interferon signaling and immune response in cancer. J Clin Invest2021; 131(14): e147025
[48]
von Locquenghien M, Rozalen C, Celia-Terrassa T. Interferons in cancer immunoediting: sculpting metastasis and immunotherapy response. J Clin Invest2021; 131(1): e143296
[49]
Borden EC. Interferons alpha and beta in cancer: therapeutic opportunities from new insights. Nat Rev Drug Discov2019; 18(3): 219–234
[50]
Sun Y, Zhang W, Chen D, Lv Y, Zheng J, Lilljebjorn H, Ran L, Bao Z, Soneson C, Sjögren HO, Salford LG, Ji J, French PJ, Fioretos T, Jiang T, Fan X. A glioma classification scheme based on coexpression modules of EGFR and PDGFRA. Proc Natl Acad Sci USA2014; 111(9): 3538–3543
[51]
Wei Y, Li G, Feng J, Wu F, Zhao Z, Bao Z, Zhang W, Su X, Li J, Qi X, Duan Z, Zhang Y, Vega SF, Jakola AS, Sun Y, Carén H, Jiang T, Fan X. Stalled oligodendrocyte differentiation in IDH-mutant gliomas. Genome Med2023; 15(1): 24
[52]
Yang Y, Jiang S, Du H, Tang J, Xiao P, Wu Y, Li J, Feng J, Wei Y, Samo AA, Lu X, Fan X. Distinct pathway activities are associated with prognosis and response to bortezomib-containing treatment in MCL1-M based molecular subtypes of multiple myeloma. Ann Hematol2024; 103(12): 5495–5510