Skip to main content
Chinese Journal of Hematology logoLink to Chinese Journal of Hematology
. 2025 Nov;46(11):1076–1080. [Article in Chinese] doi: 10.3760/cma.j.cn121090-20250305-00117

基因突变在多发性骨髓瘤预后及治疗中的价值

Value of gene mutation in the prognosis and treatment of multiple myeloma

Lili Cheng 1, Junling Zhuang 1,
Editor: 律 琦1
PMCID: PMC12708951  PMID: 41407470

Abstract

Multiple myeloma(MM)is a highly het1076erogeneous hematologic malignancy driven by complex genetic and molecular abnormalities. Driver gene mutations, particularly in the RAS/MAPK, DNA damage repair, and NF-κB pathways, are central to MM pathogenesis, progression, and prognosis. Existing risk stratification systems based on cytogenetics and clinical features remain limited in predictive accuracy. Emerging genomic prognostic models and targeted therapies offer new precision treatment strategies. Integrating gene mutation analysis into prognostic frameworks may improve outcome prediction and guide therapy. This review summarizes current advances on gene mutations in MM, their prognostic implications, and potential therapeutic targets.


多发性骨髓瘤(multiple myeloma, MM)是发病率位居第二的血液系统恶性肿瘤,由意义未明单克隆丙种球蛋白病(monoclonal gammopathy of undetermined significance, MGUS)和冒烟型多发性骨髓瘤(smoldering multiple myeloma, SMM)进展而来。MM的生物学和临床特征具有高度异质性[1],随着新药和治疗策略不断进步,在过去20年间,MM患者的总生存(OS)期已从3~5年延长至8~10年,但MM仍不可治愈,部分高危患者OS期不足3年。因此,精准的危险分层体系对评估MM的预后至关重要。

国际分期系统(ISS)首次提出时仅包含β2微球蛋白和血白蛋白两个指标[2],后续进行过两次修订,增加了高危细胞遗传学异常(HRCA)、乳酸脱氢酶(LDH),并对高危因素进行加权[3][4]。尽管HRCA被认为是影响MM患者预后的主要因素,骨髓瘤预后评分系统(MPSS)中还纳入了临床指标如血小板计数等[5],但MM的发病机制和遗传学异常极其复杂,尤其在新药、新治疗、新检测手段不断涌现的时代,上述危险分层体系难以准确预测患者的生存,需要建立新模型或引入新的预后因素。基因突变在MM发生发展的各个阶段都发挥了重要作用,然而这些突变的预后意义却一直存在争议。本文对基因突变在MM中的研究现状进行综述,并分析其在疾病预后和潜在治疗靶点中的意义。

一、驱动基因突变对疾病演变的影响

肿瘤发生的重要原因之一是基因突变,这些突变因能驱动肿瘤发生而被称为“驱动基因”,它们赋予了体细胞相对于邻近细胞的某些选择优势[6]。2018年发表的一项1 273例新诊断MM(newly diagnosed multiple myeloma, NDMM)的大样本研究中,研究者使用4种方法共发现63个驱动基因,其中84.1%的患者至少包含1种驱动突变,且随着驱动基因突变数量增加,无进展生存(PFS)期和OS期逐渐缩短[7]。驱动基因突变主要发生在RAS/MAPK通路(KRAS、NRAS、BRAF,占56%)、DNA损伤修复通路(TP53、ATM、ATR、BRCA2,占22%)以及NF-κB信号通路(TRAF2、TRAF3、CYLD、NFKB2,占22%)[8]。MM中最常见的驱动基因为RAS突变,分为KRAS(56%)和NRAS(44%)突变[7],与实体瘤存在差异。这些驱动基因突变常见的发生位点大多也存在差异。其中NRAS突变最常见的位点在Q61密码子上,而KRAS突变最常见位点在G12、G13和Q61密码子上[9]。不同驱动基因间存在一定相关性,如KRAS和NRAS突变互斥,但与BRAF突变却无此关联[8],[10][11]。研究MM的驱动基因对于了解肿瘤的生物学特性非常重要,并有助于开发靶向药物。

MM的发生和发展包含多个步骤,由主要和次要遗传事件共同促成[12]。主要事件指染色体异常,发生在B细胞发育早期,是发生MM的启动因素。次要事件通常更为复杂,包括拷贝数异常、MYC易位及驱动基因突变等[1],[13]。虽然染色体异常和驱动基因突变在MM中发生的先后顺序不同,但两者之间存在显著关联,如FGFR3、PRKD2和ACTG1仅在t(4;14)中发生显著突变;CCND1、IRF4、LTB和HUWE1仅在t(11;14)中发生显著突变;MAF仅在t(14;16)中发生显著突变;PRDM1仅在超二倍体中发生显著突变[7]

驱动基因的突变在MGUS和SMM进展为MM的过程中也发挥了重要作用。2020年的一项SMM基因组特征的研究结果显示,多数NDMM中发现的驱动基因突变在SMM阶段已经出现,并且是疾病进展的独立危险因素。SMM患者如果出现MAPK通路和DNA修复相关基因突变,则进展为MM的风险更高,出现APOBEC相关突变则进展速度更快[14][15]。Bustoros等[14]依据这些研究结果提出了第1个基于基因组异常的SMM进展预后评分,包含3个独立风险因素,分别为MAPK信号通路基因突变(KRAS、BRAF、NRAS和PTPN11)、DNA修复异常及MYC易位或拷贝数变异。后来又有研究者在前述研究的基础上对MGUS患者的基因组特征进行分析,发现与SMM结果相似,根据特定的基因组事件可以有效区分两种前体疾病是否稳定[16]。另外,驱动基因突变数量也会影响疾病转化或进展,如突变数量多的SMM患者中位OS期较短,与NDMM的结果相似[7],[17]。KRAS突变在MGUS中很少检测到,但在SMM和MM中很常见,这提示KRAS突变可能与疾病转化有关[17][18]。综上,驱动基因突变是MGUS和SMM进展的重要因素,为探究靶向阻断肿瘤进展过程的研究提供了重要基础。

驱动基因突变还与治疗耐药性相关。有研究报道,在难治复发MM(RRMM)中检测到EXZH2、MAML3、TDG、PIGO、NBPF15等10个既往未报道过的潜在驱动基因以及其他新突变,一些基线时已存在的突变在复发时明显增多[19][20]。表明新增突变或原有突变可能与耐药或复发有关。一些罕见的驱动基因,如CRBN、IKZF1或IKZF3突变可预测对免疫调节剂的耐药性[21],XBP1突变可预测对硼替佐米的耐药性[7]

二、基因突变在MM中的预后意义

MM属于惰性肿瘤,从克隆性浆细胞发生、肿瘤负荷增多至产生终末器官损伤常需要数年甚至十余年[22]。因此,很多在癌前病变时发生的基因突变会一直延续到需要治疗的MM阶段,并在疾病进展、病灶迁移、耐药等方面继续发挥作用。

虽然MM中能检出的基因突变很多,但多数预后意义并不确定,只有少数突变与预后不良存在显著相关性。其中,最为明确的是TP53突变[23]。在NDMM中,TP53异常分为以下三类:发生17p−的单等位基因缺失(占8%)、单等位基因突变(占6%)和双等位基因失活(占4%)。其中17p−是多种MM分期标准中已确定的高风险特征之一。TP53突变在MM早期进展中发挥了重要作用[24]。国内最新的高危MM(HRMM)专家共识将初治和复发时新出现TP53突变纳入HRMM诊断标准[25]。但因其作用机制复杂,暂无靶向TP53的药物应用于临床[26]

RAS突变是NDMM中突变频率最高的基因,在RRMM中的突变频率更高[27],突变发生在非典型密码子如A146、K117和Q22更为常见[28]。在实体瘤中,RAS突变与不良预后明确相关,但在MM中尚无定论。多数研究发现,其与更短的PFS期和OS期相关[28],并促使髓外病变发生,导致疾病更为难治[29]。但也有研究认为,RAS突变并不影响MM的整体预后,其中最主要的两种类型是KRAS和NRAS[9],[30]。BRAF也是RAS突变的一种,比例稍低于KRAS和NRAS[7]。此外,最常见的突变还包括FAM46C和DIS3,在MM中发生比例仅次于RAS突变[7]。多个研究显示,FAM46C和DIS3也与肿瘤发生发展密切相关(表1)。

表1. 多发性骨髓瘤中常见的基因突变.

突变基因 信号通路 突变频率[7] 与肿瘤发生发展的相关性
KRAS RAS/MAPK 22% 结论不一,多数呈负相关[9],[29][32]
NRAS RAS/MAPK 18% 结论不一,多数呈负相关[9],[29][32]
DIS3 RNA代谢[33] 10% 呈负相关[34][35]
FAM46C PI3K-Akt[36] 10% 呈负相关[36][38]
BRAF RAS/MAPK 8% 结论不一,多数呈负相关[9],[29][32]
TP53 DNA修复 6% 呈负相关[23]

除上述较为常见的驱动基因突变外,IGLL5被发现与血液系统恶性肿瘤发生增加有关[39]。该基因与MM疾病进展有关,在NDMM中的突变频率为16%~18%,且与各种RAS突变存在互斥[24],[40]。IGLL5是MM早期进展的独立危险因素,与一年后进展患者相比,一年内进展患者的突变发生率较高(20%对14%)[24]

应用较为广泛的MM预后系统以ISS及两次修订的标准为代表[2][4],还包括结合基因组学建立的IRMMa模型及预测早期复发的S-ERMM模型等[41][42],但鲜有将基因突变纳入预后分层的标准。近年的研究发现,部分MM患者基线时没有任何已知的高风险遗传因素,但在早期(12~18个月)就发生疾病进展,且预后极差,称为功能性高危(functional high-risk, FHR)MM[42]。二代测序结果显示,KIAA1549L、LUZP2和BMPR1B等基因突变会特异发生在FHR MM患者中,影响IL-6/JAK/STAT3通路的突变也明显增多,说明现有危险分层系统未识别出高危患者可能是未知基因突变所致[43]。目前的危险度分层体系不能精准预测MM患者的预后,基于MM发病机制的复杂性,可能需要纳入更全面的预后因素如基因突变,建立适应更复杂情况的预测模型才能不断提高预后判断的准确性。

三、基因突变与靶向治疗

尽管IRMMa预测模型的预后因素包含基因突变[43],但目前根据基因突变指导MM治疗的研究仍十分有限。RAS/MAPK通路上重要的基因突变可以通过影响细胞增殖、存活和分化在MM中发挥关键作用,因此成为靶向治疗研究的主要信号通路之一[43][44]。AZD4785是一种高效、选择性靶向KRAS的反义寡核苷酸,能与KRAS的3′端非翻译区结合,靶向所有KRAS突变亚型,特异性沉默KRAS并在体内和体外显著抑制肿瘤细胞生长[27],具有良好的治疗潜力。CH5126766/VS-6766是一种新型MEK-pan-RAF抑制剂,通过间歇性给药方式,在携带RAS-RAF-MEK通路突变的MM患者中表现出良好且持久的缓解及良好的耐受性[45]。另一项基础研究发现,GCK抑制剂TL4-12可诱导RAS突变的MM细胞出现细胞周期停滞并促进细胞凋亡,联合来那度胺治疗时可以发挥协同作用[46]表2)。

表2. 靶向基因突变治疗多发性骨髓瘤(MM)的药物总结.

药物名称 靶向突变 药物类型 作用效果
AZD4785[27] KRAS 反义寡核苷酸 体内和体外抑制MM肿瘤细胞生长
CH5126766/VS-6766[45] KRAS MEK-pan-RAF抑制剂 客观反应率为27%
TL4-12[46] RAS(NRAS、KRAS、BRAF) GCK抑制剂 促进细胞周期停滞和细胞凋亡,降低对免疫调节剂的耐药性
恩考芬尼联合比美替尼[47] BRAFV600E BRAF/MEK抑制剂 中位PFS期5.6个月,24个月OS率55%
达拉非尼联合曲美替尼[48] BRAFV600E BRAF/MEK抑制剂 中位DOR 11.1个月,中位PFS期6.3个月,中位OS期33.9个月

 PFS:无进展生存;OS:总生存;DOR:缓解持续时间

RAS/MAPK通路的另一个常用的靶向药物为BRAF抑制剂。一项多中心Ⅱ期试验评估BRAF/MEK抑制剂恩考芬尼和比美替尼联合应用于BRAFV600E突变RRMM患者的疗效。结果显示,总体有效率为83.3%,中位PFS期为5.6个月,24个月OS率为55%,这是首个证明联合BRAF/MEK抑制剂对BRAFV600E突变RRMM患者有效的前瞻性临床试验[47]。Ⅱ期ROAR试验评估了达拉非尼(BRAF激酶抑制剂)联合曲美替尼(MEK抑制剂)对BRAFV600E突变RRMM患者的疗效和安全性,结果显示,总体有效率为50%,中位缓解持续时间为11.1个月,中位PFS期为6.3个月,中位OS期为33.9个月[48]表2)。靶向分子及信号通路的治疗可以在有效杀死肿瘤细胞的同时保护健康细胞,最大限度地减少不良反应,可作为有特定基因突变患者的治疗选择。但靶向治疗也存在一定的局限性,如多数中心并未开展二代测序,且有些突变的发生率低。另一个局限在于,靶向基因突变的治疗并未考虑RNA和蛋白质水平的变化,而很多药物主要作用于蛋白质,因此治疗结果可能并不稳定[49]

MM的发病机制和疾病异质性显著,目前的预后分层体系仍不能精准预测临床结局。随着对MM的认识逐渐深入,治疗策略不断突破,危险分层体系也在不断完善。尽管临床指标和细胞遗传学异常是主要危险因素,未来对基因突变的分析仍有很大空间,突变异常可能成为预后模型的有力补充,从而更好地预测疾病转归。

Funding Statement

基金项目:中国医学科学院医学与健康科技创新工程项目(2024-I2M-C&T-B-017)

References

  • 1.Malard F, Neri P, Bahlis NJ, et al. Multiple myeloma[J] Nat Rev Dis Primers. 2024;10(1):45. doi: 10.1038/s41572-024-00529-7. [DOI] [PubMed] [Google Scholar]
  • 2.Greipp PR, San Miguel J, Durie BG, et al. International staging system for multiple myeloma[J] J Clin Oncol. 2005;23(15):3412–3420. doi: 10.1200/JCO.2005.04.242. [DOI] [PubMed] [Google Scholar]
  • 3.Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised International Staging System for Multiple Myeloma: A Report From International Myeloma Working Group[J] J Clin Oncol. 2015;33(26):2863–2869. doi: 10.1200/JCO.2015.61.2267. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.D'Agostino M, Cairns DA, Lahuerta JJ, et al. 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] J Clin Oncol. 2022;40(29):3406–3418. doi: 10.1200/JCO.21.02614. [DOI] [PubMed] [Google Scholar]
  • 5.Mao X, Yan W, Mery D, et al. Development and validation of an individualized and weighted Myeloma Prognostic Score System (MPSS) in patients with newly diagnosed multiple myeloma[J] Am J Hematol. 2024;99(4):523–533. doi: 10.1002/ajh.27207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Martínez-Jiménez F, Muiños F, Sentís I, et al. A compendium of mutational cancer driver genes[J] Nat Rev Cancer. 2020;20(10):555–572. doi: 10.1038/s41568-020-0290-x. [DOI] [PubMed] [Google Scholar]
  • 7.Walker BA, Mavrommatis K, Wardell CP, et al. Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma[J] Blood. 2018;132(6):587–597. doi: 10.1182/blood-2018-03-840132. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Bolli N, Biancon G, Moarii M, et al. Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups[J] Leukemia. 2018;32(12):2604–2616. doi: 10.1038/s41375-018-0037-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Lin YT, Way GP, Barwick BG, et al. Integrated phosphoproteomics and transcriptional classifiers reveal hidden RAS signaling dynamics in multiple myeloma[J] Blood Adv. 2019;3(21):3214–3227. doi: 10.1182/bloodadvances.2019000303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Maura F, Bolli N, Angelopoulos N, et al. Genomic landscape and chronological reconstruction of driver events in multiple myeloma[J] Nat Commun. 2019;10(1):3835. doi: 10.1038/s41467-019-11680-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Melchor L, Brioli A, Wardell CP, et al. Single-cell genetic analysis reveals the composition of initiating clones and phylogenetic patterns of branching and parallel evolution in myeloma[J] Leukemia. 2014;28(8):1705–1715. doi: 10.1038/leu.2014.13. [DOI] [PubMed] [Google Scholar]
  • 12.Corre J, Munshi N, Avet-Loiseau H. Genetics of multiple myeloma: another heterogeneity level?[J] Blood. 2015;125(12):1870–1876. doi: 10.1182/blood-2014-10-567370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Manier S, Salem KZ, Park J, et al. Genomic complexity of multiple myeloma and its clinical implications[J] Nat Rev Clin Oncol. 2017;14(2):100–113. doi: 10.1038/nrclinonc.2016.122. [DOI] [PubMed] [Google Scholar]
  • 14.Bustoros M, Sklavenitis-Pistofidis R, Park J, et al. Genomic profiling of smoldering multiple myeloma identifies patients at a high risk of disease progression[J] J Clin Oncol. 2020;38(21):2380–2389. doi: 10.1200/JCO.20.00437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Bolli N, Maura F, Minvielle S, et al. Genomic patterns of progression in smoldering multiple myeloma[J] Nat Commun. 2018;9(1):3363. doi: 10.1038/s41467-018-05058-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Oben B, Froyen G, Maclachlan KH, et al. Whole-genome sequencing reveals progressive versus stable myeloma precursor conditions as two distinct entities[J] Nat Commun. 2021;12(1):1861. doi: 10.1038/s41467-021-22140-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Boyle EM, Deshpande S, Tytarenko R, et al. The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma[J] Nat Commun. 2021;12(1):293. doi: 10.1038/s41467-020-20524-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Rasmussen T, Kuehl M, Lodahl M, et al. Possible roles for activating RAS mutations in the MGUS to MM transition and in the intramedullary to extramedullary transition in some plasma cell tumors[J] Blood. 2005;105(1):317–323. doi: 10.1182/blood-2004-03-0833. [DOI] [PubMed] [Google Scholar]
  • 19.Ansari-Pour N, Samur M, Flynt E, et al. Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma[J] Blood. 2023;141(6):620–633. doi: 10.1182/blood.2022017010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Corre J, Cleynen A, Robiou du Pont S, et al. Multiple myeloma clonal evolution in homogeneously treated patients[J] Leukemia. 2018;32(12):2636–2647. doi: 10.1038/s41375-018-0153-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Egan JB, Kortuem KM, Kurdoglu A, et al. Extramedullary myeloma whole genome sequencing reveals novel mutations in Cereblon, proteasome subunit G2 and the glucocorticoid receptor in multi drug resistant disease[J] Br J Haematol. 2013;161(5):748–751. doi: 10.1111/bjh.12291. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Rajkumar SV, Dimopoulos MA, Palumbo A, et al. International Myeloma Working Group updated criteria for the diagnosis of multiple myeloma[J] Lancet Oncol. 2014;15(12):e538–548. doi: 10.1016/S1470-2045(14)70442-5. [DOI] [PubMed] [Google Scholar]
  • 23.Robiou du Pont S, Cleynen A, Fontan C, et al. Genomics of multiple myeloma[J] J Clin Oncol. 2017;35(9):963–967. doi: 10.1200/JCO.2016.70.6705. [DOI] [PubMed] [Google Scholar]
  • 24.D'Agostino M, Zaccaria GM, Ziccheddu B, et al. Early relapse risk in patients with newly diagnosed multiple myeloma characterized by next-generation sequencing[J] Clin Cancer Res. 2020;26(18):4832–4841. doi: 10.1158/1078-0432.CCR-20-0951. [DOI] [PubMed] [Google Scholar]
  • 25.Hagen P, Zhang J, Barton K. High-risk disease in newly diagnosed multiple myeloma: beyond the R-ISS and IMWG definitions[J] Blood Cancer J. 2022;12(5):83. doi: 10.1038/s41408-022-00679-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Flynt E, Bisht K, Sridharan V, et al. Prognosis, biology, and targeting of TP53 dysregulation in multiple myeloma[J] Cells. 2020;9(2):287. doi: 10.3390/cells9020287. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Sacco A, Federico C, Todoerti K, et al. Specific targeting of the KRAS mutational landscape in myeloma as a tool to unveil the elicited antitumor activity[J] Blood. 2021;138(18):1705–1720. doi: 10.1182/blood.2020010572. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Vo JN, Wu YM, Mishler J, et al. The genetic heterogeneity and drug resistance mechanisms of relapsed refractory multiple myeloma[J] Nat Commun. 2022;13(1):3750. doi: 10.1038/s41467-022-31430-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Nakamoto-Matsubara R, Nardi V, Horick N, et al. Integration of clinical outcomes and molecular features in extramedullary disease in multiple myeloma[J] Blood Cancer J. 2024;14(1):224. doi: 10.1038/s41408-024-01190-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Xu J, Haigis KM, Firestone AJ, et al. Dominant role of oncogene dosage and absence of tumor suppressor activity in Nras-driven hematopoietic transformation[J] Cancer Discov. 2013;3(9):993–1001. doi: 10.1158/2159-8290.CD-13-0096. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Perroud C, Thurian D, Andres M, et al. Effect of MAPK activation via mutations in NRAS, KRAS and BRAF on clinical outcome in newly diagnosed multiple myeloma[J] Hematol Oncol. 2023;41(5):912–921. doi: 10.1002/hon.3208. [DOI] [PubMed] [Google Scholar]
  • 32.Schavgoulidze A, Corre J, Samur MK, et al. RAS/RAF landscape in monoclonal plasma cell conditions[J] Blood. 2024;144(2):201–205. doi: 10.1182/blood.2023022295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Todoerti K, Ronchetti D, Favasuli V, et al. DIS3 mutations in multiple myeloma impact the transcriptional signature and clinical outcome[J] Haematologica. 2022;107(4):921–932. doi: 10.3324/haematol.2021.278342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Ohguchi Y, Ohguchi H. DIS3: The Enigmatic Gene in Multiple Myeloma[J] Int J Mol Sci. 2023;24(4):4079. doi: 10.3390/ijms24044079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Favasuli VK, Ronchetti D, Silvestris I, et al. DIS3 depletion in multiple myeloma causes extensive perturbation in cell cycle progression and centrosome amplification[J] Haematologica. 2024;109(1):231–244. doi: 10.3324/haematol.2023.283274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Kanasugi J, Hanamura I, Ota A, et al. Biallelic loss of FAM46C triggers tumor growth with concomitant activation of Akt signaling in multiple myeloma cells[J] Cancer Sci. 2020;111(5):1663–1675. doi: 10.1111/cas.14386. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Zhang W, Wu C, Geng S, et al. FAM46C-mediated tumor heterogeneity predicts extramedullary metastasis and poorer survival in multiple myeloma[J] Aging (Albany NY) 2023;15(9):3644–3677. doi: 10.18632/aging.204697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Resnati M, Pennacchio S, Viviani L, et al. TENT5C/FAM46C modulation in vivo reveals a trade-off between antibody secretion and tumor growth in multiple myeloma[J] Haematologica. 2024;109(6):1966–1972. doi: 10.3324/haematol.2023.284299. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Bernstein N, Spencer Chapman M, Nyamondo K, et al. Analysis of somatic mutations in whole blood from 200,618 individuals identifies pervasive positive selection and novel drivers of clonal hematopoiesis[J] Nat Genet. 2024;56(6):1147–1155. doi: 10.1038/s41588-024-01755-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.White BS, Lanc I, O'Neal J, et al. A multiple myeloma-specific capture sequencing platform discovers novel translocations and frequent, risk-associated point mutations in IGLL5[J] Blood Cancer J. 2018;8(3):35. doi: 10.1038/s41408-018-0062-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Maura F, Rajanna AR, Ziccheddu B, et al. Genomic classification and individualized prognosis in multiple myeloma[J] J Clin Oncol. 2024;42(11):1229–1240. doi: 10.1200/JCO.23.01277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Zaccaria GM, Bertamini L, Petrucci MT, et al. Development and validation of a simplified score to predict early relapse in newly diagnosed multiple myeloma in a pooled dataset of 2,190 patients[J] Clin Cancer Res. 2021;27(13):3695–3703. doi: 10.1158/1078-0432.CCR-21-0134. [DOI] [PubMed] [Google Scholar]
  • 43.Soekojo CY, Chung TH, Furqan MS, et al. Genomic characterization of functional high-risk multiple myeloma patients[J] Blood Cancer J. 2022;12(1):24. doi: 10.1038/s41408-021-00576-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Lu Q, Yang D, Li H, et al. Multiple myeloma: signaling pathways and targeted therapy[J] Mol Biomed. 2024;5(1):25. doi: 10.1186/s43556-024-00188-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Guo C, Chénard-Poirier M, Roda D, et al. Intermittent schedules of the oral RAF-MEK inhibitor CH5126766/VS-6766 in patients with RAS/RAF-mutant solid tumours and multiple myeloma: a single-centre, open-label, phase 1 dose-escalation and basket dose-expansion study[J] Lancet Oncol. 2020;21(11):1478–1488. doi: 10.1016/S1470-2045(20)30464-2. [DOI] [PubMed] [Google Scholar]
  • 46.Li S, Fu J, Yang J, et al. Targeting the GCK pathway: a novel and selective therapeutic strategy against RAS-mutated multiple myeloma[J] Blood. 2021;137(13):1754–1764. doi: 10.1182/blood.2020006334. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Giesen N, Chatterjee M, Scheid C, et al. A phase 2 clinical trial of combined BRAF/MEK inhibition for BRAFV600E-mutated multiple myeloma[J] Blood. 2023;141(14):1685–1690. doi: 10.1182/blood.2022017789. [DOI] [PubMed] [Google Scholar]
  • 48.Subbiah V, Kreitman RJ, Wainberg ZA, et al. Dabrafenib plus trametinib in BRAFV600E-mutated rare cancers: the phase 2 ROAR trial[J] Nat Med. 2023;29(5):1103–1112. doi: 10.1038/s41591-023-02321-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Pawlyn C, Davies FE. Toward personalized treatment in multiple myeloma based on molecular characteristics[J] Blood. 2019;133(7):660–675. doi: 10.1182/blood-2018-09-825331. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Chinese Journal of Hematology are provided here courtesy of Editorial Office of Chinese Journal of Hematology

RESOURCES