The effective and efficient management of cancer patients relies upon early diagnosis and/or the monitoring of treatment, something that is often difficult to achieve using standard tissue biopsy techniques. Biological fluids such as blood hold great possibilities as a source of non-invasive cancer biomarkers that can act as surrogate markers to biopsy-based sampling. The non-invasive nature of these “liquid biopsies” ultimately means that cancer detection may be earlier and that the ability to monitor disease progression and/or treatment response represents a paradigm shift in the treatment of cancer patients. Below, we review one of the most promising classes of circulating cancer biomarkers: microRNAs (miRNAs). In particular, we will consider their history, the controversy surrounding their origin and biology, and, most importantly, the hurdles that remain to be overcome if they are really to become part of future clinical practice.

The diagnosis of myelodysplastic syndromes (MDS) is based on morphological changes in the blood and bone marrow. The parameters NEUT-X and NEUT-Y of the Sysmex XE-2100 analyzer could help detect neutrophil dysplasia. A control group of 50 patients, along with 50 postpartum patients, 50 anemias, 50 leukopenias, 50 patients with microscopically visible hypergranulated neutrophils and 50 MDS patients were assessed. The NEUT-X and NEUT-Y values (mean +/- SD) for the control group were 1346 +/- 28.2 and 420 +/- 19.3, respectively, with the anemia and leukopenia groups giving similar values. The postpartum and hypergranulated neutrophils groups presented higher values (P < 0.05), whereas the values in the MDS group were 1286 +/- 72.8 and 385 +/- 50.9 (P < 0.05), respectively. There were no differences between the morphological MDS types. The NEUT-X and NEUT-Y values in MDS patients with optical hypogranulation were significantly lower than for MDS patients without optical hypogranulation. NEUT-X and NEUT-Y values lower than 1298 and 398, respectively, would have a specificity for detecting MDS of 94% and 91% and would detect 60% and 56% of cases, respectively, whereas they would detect 75% and 74%, respectively, of MDS cases with optical hypogranulation. NEUT-X and NEUT-Y parameters can be used to detect neutrophil dysplasia arising from MDS and chronic myelomonocytic leukemia.

XN analyzer has improved blast detection in oncohematologic patients. Operators cannot rely on the blast flag alone but have to consider other flags and hemogram data. In lymphoproliferative disorders, XN analyzer yields less samples with pseudobasophilia. Both analyzers must improve flagging for hairy cell leukemia.

The lymphocyte positional parameters provided by Sysmex XN analysers are useful to differentiate expansions of T-GLs from other LPD and to differentiate MNS cases from other diagnostic groups. In addition, these parameters are very useful for detecting changes in the lymphocytes that make it necessary to review blood smears in samples without morphological flagging.

Introduction We evaluated the value of hematopoietic progenitor cells (HPCs) counted in Sysmex XN analyzers to predict the mobilization and collection of CD34+ cells in apheresis for stem cell transplantation. Methods Eighty patients who underwent stem cell transplantation were enrolled (50 autologous and 30 allogeneic). In the autologous group, patients were considered poor mobilizers when the CD34+ count was <10 × 106/L or <20 × 106/L in patients with multiple myeloma who were going to undergo two transplants. ROC curves were generated, and HPC cutoffs were calculated. Results The correlation between the HPC and CD34+ cell counts was good. Two algorithms were proposed. In the first algorithm, samples collected the day before apheresis, negative and positive HPC cutoffs were selected to detect poor and good mobilization and, therefore, the need or not to administer plerixafor. In the second algorithm, samples collected pre‐apheresis, the negative HPC cutoff was an indication to delay apheresis; an HPC higher than the optimal cutoff was an indication to start apheresis. When the HPC values were between these cutoffs, there was an indication to count CD34+ cells for a better decision‐making. Finally, in samples collected pre‐apheresis, HPC counts could be used to predict patients who would have poor CD34+ cell collections. In the allogeneic group, all the donors mobilized well, and very few needed two apheresis procedures. Conclusions The HPC count is useful for decision‐making in the management of patients subjected to apheresis procedures to collect peripheral blood stem cells.