Prognostic Model Based on Tumor Immune Cell Infiltration Score May Predict Prognosis in Multiple Myeloma

Immune function has been found to play a significant role in multiple myeloma.

A recent analysis published in Scientific Reports suggests that when split into multiple groups, patients with multiple myeloma (MM) differed significantly in immune risk, survival, and tumor environments.

MM is defined as the presence of clonal malignant plasma cells in the bone marrow. Its symptoms may include bone pain, anemia, recurrent infections, hypercalcemia, and renal failure. Immune function has been found to play a significant role in MM, and a detailed analysis of the relationship between the immune system genes and cancer outcomes may indicate a new method to predict outcomes and treatment course for patients with MM, the study authors wrote.

The tumor microenvironment is vital in various processes in the body, including tumorigenesis, cancer progression, and metastasis. Immune signatures have been verified for use in diagnosis and prognosis prediction. The study authors used single-sample Gene Set Enrichment Analysis to evaluate tumor immune cell infiltration score (TIICs) and verified their prognostic significance in both training and validation cohorts. The information was subsequently used to build a prognostic model.

“To date, there has been no investigation of the role of the TIICs in the prognosis of MM,” the study authors wrote. “A straightforward and robust model based on immune function in MM would thus be extremely useful.”

In total, 1281 samples were collected for further evaluation of the immune enrichment scores of 28 immune cells, which showed that Th17 cells contributed most significantly to survival. After using the median TIICs to divide the samples into 2 groups, the study showed that the high-TIICs group was associated with favorable outcomes in both the training and validation sets.

Additionally, the team created a prognostic model to predict the 6-, 8-, and 10-year survival outcomes. The analysis revealed that immune score and tumor purity were higher in the high-TIICs group, whereas the matrix score was lower in this group. There were 42 differentially expressed genes identified between the groups. Patients in the low-TIICs group had lower levels of tumor purity, which was associated with lower survival.

The new prognostic model based on immune cell infiltration signifies the potential for TIICs in predicting prognosis and as targets for treatment, according to the researchers. They concluded that the immune cell risk signature may symbolize the MM tumor environment, which allows the prediction of patient prognosis and suggests new directions for MM treatment.

There were some limitations to the study, such as in clinical information. The study authors were not able to compare the prognostic model with multiple clinical characteristics. Further, they were also not able to pinpoint clinical differences, such as stage and risk stratification, between the groups. Lastly, survival was only measured over 1 to 3 years, so the prediction model of the nomogram could only be developed for 4 to 5 years.

“In conclusion, patients were classified into two groups based on TIICs, and the groups were shown to differ significantly in terms of immune risk, survival, and tumor environments. Thus, the identified immune cell risk signature may represent the MM tumor environment, allowing the prediction of patient prognosis and suggesting new directions for MM treatment,” the study authors wrote.

REFERENCE

Chen, C., Li, Y., Miao, P. et al. Tumor immune cell infiltration score based model predicts prognosis in multiple myeloma. Sci Rep 12, 17082 (2022). https://doi.org/10.1038/s41598-022-21763-7