The latest medical research on Clinical Genetics

In newborns, elevated nucleated red blood cell (NRBC) levels can be associated with enhanced erythropoietic stress and might be predictive for adverse outcome. Also, the presence of NRBC in peripheral blood might lead to erroneous enumeration results of white blood cells in automated hematology analyzers. We aimed to assess the comparability of the Sysmex XN 1000 to manual slide reviews and correlation of NRBC with inflammation markers.

Specimens of 3397 children under 1 year were compared by automated and microscopic NRBC enumeration. Additionally, potential correlations between NRBC and age and inflammation markers were examined.

Overall, there was good correlation (r = 0.97) between automated (range: 0%-3883%) and microscopic enumeration (range: 0%-3694%) of NRBC with high comparability up to a NRBC value of 200% and an increase in the variation between the two methods with increasing NRBC numbers. When 94 samples with ≤ 200% NRBC and ≥ 30% divergence between methods were separately reanalyzed with respect to overlapping cell populations in their scattergrams, Sysmex would have generated unrecognized incorrect automated results in 47 samples, corresponding to 1.4% of total study samples. NRBC counts were negatively correlated to age, but not to inflammation markers.

Sysmex XN 1000 is highly precise in the enumeration of NRBC in children under 1 year up to counts of 200% and might replace time-intense manual counting in routine diagnostics. In the setting of neonatal and intensive care diagnostics, microscopic control and supervision of scattergrams are highly recommended for any automated NRBC enumeration processes.

Colon cancer is one of the most common digestive tract malignancies. Although immunotherapy has brought new hope to colon cancer patients, there is still a large proportion of patients who do not benefit from immunotherapy. Studies have shown that neutrophils can interact with immune cells and immune factors to affect the prognosis of patients.

We first determined the infiltration level of neutrophils in tumors using the CIBERSORT algorithm and identified key genes in the final risk model by Spearman correlation analysis and subsequent Cox analysis. The risk score of each patient was obtained by multiplying the Cox regression coefficient and the gene expression level, and patients were divided into two groups based on the median of risk score. Differences in overall survival (OS) and progression-free survival (PFS) were assessed by Kaplan-Meier survival analysis, and model accuracy was validated in independent dataset. Differences in immune infiltration and immunotherapy were evaluated by immunoassay. Finally, immunohistochemistry and western blotting were performed to verify the expression of the three genes in the colon normal and tumor tissues.

We established and validated a risk scoring model based on neutrophil-related genes in two independent datasets, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, with SLC11A1 and SLC2A3 as risk factors and MMP3 as a protective factor. A new nomogram was constructed and validated by combining clinical characteristics and the risk score model to better predict patients OS and PFS. Immune analysis showed that patients in the high-risk group had immune cell infiltration level, immune checkpoint level and tumor mutational burden, and were more likely to benefit from immunotherapy.

The low-risk group showed better OS and PFS than the high-risk group in the neutrophil-related gene-based risk model. Patients in the high-risk group presented higher immune infiltration levels and tumor mutational burden and thus may be more responsive to immunotherapy.