Impact of residual tumor cells in the stem cell collection on multiple myeloma patients receiving autologous stem cell transplantation.
Jingyu XuWenqiang YanHuishou FanJiahui LiuLingna LiChenxing DuShuhui DengWeiwei SuiYan XuLugui QiuGang AnPublished in: Annals of hematology (2023)
Autologous stem cell transplantation (ASCT) is the standard therapy for patients with transplant-eligible multiple myeloma (TEMM). However, the ideal depth of response required before ASCT and the impact of residual tumor cells in the stem cell collection (SCC) on survival remains unclear. Here we collected data of 89 patients with TEMM undergoing ASCT and analyzed the minimal residual disease of SCC (cMRD) and bone marrow (BM) (mMRD) before transplantation. Before ASCT, 31.5% and 76.4% of patients achieved MRD negativity in BM and SCC, respectively. Tumor cells were less in SCC samples than that in BM samples. Neoplastic cells in SCC could be observed in patients with different responses after induction therapy, and there were no significant differences in the percentage and level of cMRD among these subgroups (P > 0.05). No correlation was found between the cMRD status and the response patients achieved after ASCT (P > 0.05). The median follow-up was 26.8 months. mMRD negativity before ASCT was associated with longer PFS (55.9 vs. 27.1 months; P = 0.009) but not OS (not reached vs. 58.9 months; P = 0.115). Patients with different cMRD statuses before ASCT experienced similar PFS (40.5 vs. 76.4 months for negativity vs. positivity; P = 0.685) and OS (not reached vs. 58.8 months for negativity vs. positivity; P = 0.889). These results suggested that detectable cMRD does not significantly predict the inferior post-ASCT response or shorter survival, and patients are eligible to undergo ASCT upon achieving partial response.
Keyphrases
- stem cell transplantation
- stem cells
- bone marrow
- end stage renal disease
- newly diagnosed
- ejection fraction
- multiple myeloma
- peritoneal dialysis
- mesenchymal stem cells
- signaling pathway
- oxidative stress
- patient reported outcomes
- induced apoptosis
- machine learning
- artificial intelligence
- optical coherence tomography