# The Role of BCL-2 Expression in Patients with Myelodysplastic Neoplasms

## TL;DR

This study shows that lower BCL-2 protein levels in bone marrow biopsies of MDS patients are linked to better survival outcomes.

## Contribution

The study identifies BCL-2 as a potential complementary biomarker for improving MDS prognosis and treatment decisions.

## Key findings

- Patients with BCL-2 expression below 10 had better survival outcomes than those with expression ≥ 10.
- Lack of detectable BCL-2 expression was significantly associated with better survival (p = 0.0084).
- Higher BCL-2 expression correlated with high and very high cytogenetic risk according to IPSS-R.

## Abstract

Myelodysplastic neoplasms (MDS) represent a heterogeneous group of neoplastic bone marrow disorders. A crucial component in regulating bone marrow cell apoptosis is the B-cell CLL/lymphoma 2 (BCL-2) protein. This retrospective study aimed to assess BCL-2 expression by immunohistochemistry in trephine biopsy specimens from 76 patients diagnosed with MDS. The obtained retrospective results were correlated with clinical parameters, including age, sex, MDS subtype, IPSS, IPSS-R, bone marrow blast percentage, Ogata score, response to treatment, blood morphology parameters, and overall survival (OS). The median follow-up duration was 16 months. During the observation period, 58 patients died (median OS of this group: 14.6 months), and 25 patients experienced progression to acute myeloid leukemia. The median BCL-2 expression assessed using the Histoscore (H-score) was 10. Patients with BCL-2 expression below 10 had better survival outcomes than those with expression ≥ 10. Furthermore, patients without detectable BCL-2 expression had significantly better survival compared to those with detectable BCL-2 expression (p = 0.0084). Higher BCL-2 expression was significantly associated with high and very high cytogenetic risk, as defined by IPSS-R. BCL-2 immunohistochemistry should be viewed as a complementary biomarker that, when integrated with IPSS-R and mutational data, could refine therapeutic algorithms.