Myelodysplastic Syndromes with Bone Marrow Fibrosis: An Update

Guo

et al. 2022

Cancers

The prognostic significance of bone marrow fibrosis (MF) grade in patients with myelodysplastic syndrome (MDS) is still debated and the molecular changes remain unclear. In our large cohort, a normal reticulum was found in 211 (25.9%) patients, whereas MF1, MF2 and MF3 were detected in 478 (58.7%), 90 (11.1%) and 35 (4.3%) patients at initial diagnosis, respectively. Patients with MF often correlated with some poor prognostic characteristics, including older age, anemia, unfavorable karyotype, higher BM blast and a higher IPSS-R category. For the entire cohort, the median OS was not reached, 30, 16 and 15 months for patients with MF 0, 1, 2 and 3, respectively. After adjusting for IPSS-R, the hazard ratio for mortality was 1.56 (95% CI, 1.18–2.06) for patients with MF1, 2.29 (95% CI, 1.61–3.27) for patients with MF2 and 2.75 (95% CI, 1.69–4.49) for patients with MF3 compared with those with MF0. The mutational landscape of 370 patients showed that TP53, U2AF1 and KMT2D mutations were more frequent in patients with MF2-3. In addition, of the 408 patients with MF0-1, 62 patients (15.1%) progressed to MF2-3 during the follow-up interval. The clinical features, mutation landscape and prognosis of patients with progressed fibrosis were similar to those of patients with MF2-3 at diagnosis. We concluded that BM fibrosis (MF1, 2 and 3) was an adverse prognosis feature in primary MDS and correlated with TP53 mutations both at the time of initial diagnosis and during the course of the disease. Therefore, BM fibrosis should be included in the revised prognostic scoring system and carefully considered in treatment selection.

Section: Discussionmentioning

confidence: 99%

Bone Marrow Fibrosis at Diagnosis and during the Course of Disease Is Associated with TP53 Mutations and Adverse Prognosis in Primary Myelodysplastic Syndrome

Guo

et al. 2022

Cancers

“…Bone marrow fibrosis was seen in a variety of malignancies (e.g., multiple myeloma and myelodysplastic syndrome) and non‐malignancies (e.g., chronic autoimmune diseases, infections, and exposure to radiation or toxins). [ 31 , 32 ] It was likely that both malignant and non‐malignant diseases activate fibrosis‐driving cells by common downstream mechanisms. [ 33 ] Dry tap refers failure to obtain bone marrow on attempted marrow aspiration.…”

Section: Discussionmentioning

confidence: 99%

The diagnostic role of complete MICM-P in metastatic carcinoma of bone marrow (MCBM) presented with atypical symptoms: A 7-year retrospective study of 45 cases in a single center

Wang

Tong

et al. 2022

Medicine

Metastatic carcinoma of bone marrow (MCBM) tends to present with atypical symptoms and can be easily misdiagnosed or miss diagnosed. This study was conducted to investigate the clinical-pathological and hematological characteristics of MCBM patients in order to develop strategies for early detection, staging, treatment selection and prognosis predicting. We retrospectively analyzed 45 patients with MCBM diagnosed by bone marrow biopsy in our hospital during the past 7 years. The clinical symptoms, hemogram and myelogram features, Hematoxylin and eosin staining and immunohistochemistry staining of bone marrow biopsies, location of primary carcinoma and corresponding treatment of the 45 MCBM patients were analyzed in this study. In total, 35 (77.9%) of all patients presented pains including bone pain (73.3%) as the main manifestation, and 37 (82.2%) patients had anemia. Metastatic cancer cells were found in only 22 patients (48.9%) upon bone marrow smear examination, but in all 45 patients by bone marrow biopsy. The bone marrow of 18 (40.0%) patients was dry extraction. Distribution of metastatic carcinoma was diffuse in 20 (44.4%) patients and multi-focal in 25 (55.6%) patients, complicated with myelofibrosis in 34 (75.6%) patients. For bone marrow biopsy immunohistochemistry, 97.8% of the patients were CD45-negative, while 75.6% of the patients were Cytokeratin-positive. There were 30 patients (66.7%) identified with primary malignancies. The overall survival (OS) of 1 year for MCBM patients was 6.7%. There was a trend that patients with cancer of known primary obtained better prognosis according to the survival curve, but the finding was not statistically significant with Log-rank P = .160. Complete MICM-P plays a significant role in early diagnosis of MCBM. Bone marrow biopsy combined with immunohistochemistry is an underappreciated method for the diagnosis of MCBM, which should be taken as part of regular tests as well as bone marrow smear. Understanding the clinicalpathological and hematological characteristics of MCBM and conducting bone marrow biopsy in time are of great significance for early detection and treatment selection.Abbreviations: CUP = cancer of unknown primary, IHC = immunohistochemistry, MCBM = metastatic carcinoma of bone marrow, MICM-P = morphology immunology cytogenetics molecular biology-pathology, OS = overall survival.

“…Evaluation of BM biopsy sections helps with the assessment of stromal fibers (collagen types I/III, reticulin) representing marrow fibrosis [ 35 ]. About 10–20% of MDS patients show marrow fibrosis at presentation [ 36 , 37 , 38 ].…”

Section: Mds Prognostic Scoring Systemsmentioning

confidence: 99%

Personalized Risk Schemes and Machine Learning to Empower Genomic Prognostication Models in Myelodysplastic Syndromes

Awada

Gurnari

Durmaz

et al. 2022

IJMS

Myelodysplastic syndromes (MDS) are characterized by variable clinical manifestations and outcomes. Several prognostic systems relying on clinical factors and cytogenetic abnormalities have been developed to help stratify MDS patients into different risk categories of distinct prognoses and therapeutic implications. The current abundance of molecular information poses the challenges of precisely defining patients’ molecular profiles and their incorporation in clinically established diagnostic and prognostic schemes. Perhaps the prognostic power of the current systems can be boosted by incorporating molecular features. Machine learning (ML) algorithms can be helpful in developing more precise prognostication models that integrate complex genomic interactions at a higher dimensional level. These techniques can potentially generate automated diagnostic and prognostic models and assist in advancing personalized therapies. This review highlights the current prognostication models used in MDS while shedding light on the latest achievements in ML-based research.