Role of Tfh17 cells in patients with multiple myeloma

Clinical significance of T helper cell subsets in the peripheral blood and bone marrow of patients with multiple myeloma

Background

T helper (Th) cell subsets primarily assist B cells in differentiating into plasma cells in the germinal center. The mechanism of malignant transformation of plasma cells is an important target for the clinical treatment of MM; however, the mechanism remains unclear.

Methods

We collected the peripheral blood (PB) and bone marrow (BM) samples of 33 patients with MM. In addition, the PB was also collected from 25 normal healthy controls (HCs). We analyzed the percentages of Th cell subsets in the PB and BM samples of patients with MM.

Results

Tfh/CD4+ were positively correlated with the proportion of myeloma cells in the BM and PB samples (r = 0.592, P = 0.002 and r = 0.510, P = 0.010 respectively), and showed a strong correlation between the BM and PB samples (r = 0.6559, P = 0.0095). In the PB samples, the percentages of Th2/CD4+ and Tfh2/Tfh cells were significantly lower in patients with MM than in HCs (P = 0.00013 and P = 0.0004, respectively), whereas the percentage of Th17/CD4+ and Tfh17/Tfh was significantly higher in newly diagnosed patients with MM than in HCs (P = 0.0037 and P = 0.03, respectively), and all these cells showed a good predictive value for MM (area under the curve [AUC] 0.781, = 0.792, = 0.837, and 0.723 respectively). In the PB samples, all subsets of PD-1+ICOS- Tfh showed a noticeable downward trend in MM from newly diagnosed to non-remission and remission groups. In contrast, all subsets of PD-1-ICOS+ Tfh increased gradually.

Conclusion

Th cell subsets play an important role in the occurrence and development of MM and may provide a fundamental basis for identifying new immunotherapy targets and prognosis.

An inflammatory response-related gene signature can predict the prognosis and impact the immune infiltration of multiple myeloma

Multiple myeloma (MM) is a highly heterogeneous and incurable disease. Inflammation plays a vital role in cancer genesis and progression. However, the relationship between inflammatory response-related genes (IRRGs) and the prognosis of MM patients remains unknown. We constructed a IRRGs prognosis model by least absolute shrinkage and selection operator regression analysis. Moreover, clinical multivariate regression was performed to identify clinical implications. Gene set enrichment analysis was implemented to conduct its biological properties. CIBERSORT deconvolution algorithm was utilized to calculate the immune cell infiltration in different risk groups. The flow cytometry was utilized to perform protein expression of prognostic gene. A Six-IRRGs (VCAM1, RGS1, KIT, CD81, BLNK, and BIRC3) prognostic risk model was successfully constructed and validated. The risk model was an independent predictor for overall survival. Enrichment analysis revealed autophagy and PI3K-Akt signaling pathways were enriched in the high-risk group. Furthermore, we found CD81 widely impacted on the infiltration of immune cells, especially on monocytes and macrophages2. At last, the role of CD81 in MM was confirmed to be an adverse prognostic factor in clinical. Our study explores the potential application value of IRRGs in MM. These findings may provide new insights into the treatment for MM patients.