Zheng Bo, Yi Ke, Zhang Yajun, Pang Tongfang, Zhou Jieyi, He Jie, Lan Hongyan, Xian Hongming, Li Rong
Nuclear Radiation Injury Protection and Treatment Department, Navy Medical Center of PLA, Naval Medical University, Huaihai West Road No. 338, Shanghai, 200050, China.
Clin Exp Med. 2023 Nov;23(7):3833-3846. doi: 10.1007/s10238-023-01148-4. Epub 2023 Jul 29.
The genome backgrounds of multiple myeloma (MM) would affect the efficacy of specific treatment. However, the mutational and transcriptional landscapes in MM patients with differential response to first-line treatment remains unclear. We collected paired whole-exome sequencing (WES) and transcriptomic data of over 200 MM cases from MMRF-COMPASS project. R package, maftools was applied to analyze the somatic mutations and mutational signatures across MM samples. Differential expressed genes (DEG) was calculated using R package, DESeq2. The feature selection of the predictive model was determined by LASSO regression. In silico analysis revealed newly discovered recurrent mutated genes such as TTN, MUC16. TP53 mutation was observed more frequent in nonCR (complete remission) group with poor prognosis. DNA repair-associated mutational signatures were enriched in CR patients. Transcriptomic profiling showed that the activity of NF-kappa B and TGF-β pathways was suppressed in CR patients. A transcriptome-based response predictive model was constructed and showed promising predictive accuracy in MM patients receiving first-line treatment. Our study delineated distinctive mutational and transcriptional landscapes in MM patients with differential response to first-line treatment. Furthermore, we constructed a 20-gene predictive model which showed promising accuracy in predicting treatment response in newly diagnosed MM patients.
多发性骨髓瘤（MM）的基因组背景会影响特定治疗的疗效。然而，对一线治疗反应不同的MM患者的突变和转录图谱仍不清楚。我们从MMRF-COMPASS项目中收集了200多例MM病例的配对全外显子组测序（WES）和转录组数据。使用R包maftools分析MM样本中的体细胞突变和突变特征。使用R包DESeq2计算差异表达基因（DEG）。预测模型的特征选择通过LASSO回归确定。计算机分析揭示了新发现的复发性突变基因，如TTN、MUC16。在预后不良的非CR（完全缓解）组中观察到TP53突变更为频繁。与DNA修复相关的突变特征在CR患者中富集。转录组分析表明，CR患者中NF-κB和TGF-β信号通路的活性受到抑制。构建了一个基于转录组的反应预测模型，该模型在接受一线治疗的MM患者中显示出有前景的预测准确性。我们的研究描绘了对一线治疗反应不同的MM患者独特的突变和转录图谱。此外，我们构建了一个20基因预测模型，该模型在预测新诊断MM患者的治疗反应方面显示出有前景的准确性。
