Spurious elevation of serum potassium concentration measured in samples with thrombocytosis

Background: Several factors that can lead to falsely elevated values of serum. Thrombocytosis is one of these factors, since breakage or activation of platelets during blood coagulation in vitro may lead to spurious release of potassium. The purpose of the study was to evaluate to which extent the platelet count may impact on potassium in both serum and plasma.Methods: The study population consisted of 42 subjects with platelets values comprised between 20 and 750×109/L. In each sample potassium was measured in both serum and plasma using potentiometric indirect method on the analyzer Modular P800 (Roche, Milan, Italy). Platelet count was performed with the hematological analyzer Advia 120 (Siemens, Milano, Italy).Results: Significant differences were found between potassium values in serum and in plasma. A significant correlation was also observed between serum potassium values and the platelet count in whole blood, but not with the age, sex, erythrocyte and leukocyte counts in whole blood. No similar correlation was noticed between plasma potassium and platelet count in whole blood. The frequency of hyperkalemia was also found to be higher in serum (20%) than in plasma (7%) in samples with a platelet count in whole blood >450×109/L.Conclusions: The results of this study show that platelets in the biological samples may impact on potassium measurement when exceeding 450×109/L. We henceforth suggest that potassium measurement in plasma may be more accurate than in serum, especially in subjects with thrombocytosis

Spurious elevation of serum potassium concentration measured in samples with thrombocytosis

Background: Several factors that can lead to falsely elevated values of serum. Thrombocytosis is one of these factors, since breakage or activation of platelets during blood coagulation in vitro may lead to spurious release of potassium. The purpose of the study was to evaluate to which extent the platelet count may impact on potassium in both serum and plasma.Methods: The study population consisted of 42 subjects with platelets values comprised between 20 and 750×109/L. In each sample potassium was measured in both serum and plasma using potentiometric indirect method on the analyzer Modular P800 (Roche, Milan, Italy). Platelet count was performed with the hematological analyzer Advia 120 (Siemens, Milano, Italy).Results: Significant differences were found between potassium values in serum and in plasma. A significant correlation was also observed between serum potassium values and the platelet count in whole blood, but not with the age, sex, erythrocyte and leukocyte counts in whole blood. No similar correlation was noticed between plasma potassium and platelet count in whole blood. The frequency of hyperkalemia was also found to be higher in serum (20%) than in plasma (7%) in samples with a platelet count in whole blood >450×109/L.Conclusions: The results of this study show that platelets in the biological samples may impact on potassium measurement when exceeding 450×109/L. We henceforth suggest that potassium measurement in plasma may be more accurate than in serum, especially in subjects with thrombocytosis

Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients

Abstract Recurring sequences of genomic alterations occurring across patients can highlight repeated evolutionary processes with significant implications for predicting cancer progression. Leveraging the ever-increasing availability of cancer omics data, here we unveil cancer’s evolutionary signatures tied to distinct disease outcomes, representing “favored trajectories” of acquisition of driver mutations detected in patients with similar prognosis. We present a framework named ASCETIC (Agony-baSed Cancer EvoluTion InferenCe) to extract such signatures from sequencing experiments generated by different technologies such as bulk and single-cell sequencing data. We apply ASCETIC to (i) single-cell data from 146 myeloid malignancy patients and bulk sequencing from 366 acute myeloid leukemia patients, (ii) multi-region sequencing from 100 early-stage lung cancer patients, (iii) exome/genome data from 10,000+ Pan-Cancer Atlas samples, and (iv) targeted sequencing from 25,000+ MSK-MET metastatic patients, revealing subtype-specific single-nucleotide variant signatures associated with distinct prognostic clusters. Validations on several datasets underscore the robustness and generalizability of the extracted signatures