Leukocyte Count

We performed two in silico experiments to assess the detection limits of different deconvolution algorithms. In the first experiment (Supplementary Fig. 6), we used the same cell line GEPs described above to compare CIBERSORT and RLR with five other GEP deconvolution methods^{4 (link)–8 (link)}. We evaluated detection limit using Jurkat cells (spike-in concentrations of 0.5%, 1%, 2.5%, 5%, 7.5%, and 10%), whose reference GEP (median of three replicates in GSE11103) was added into randomly created background mixtures of the other three blood cell lines. Five mixtures were created for each spike-in concentration. Predicted Jurkat fractions were assessed in the presence of differential tumor content, which we simulated by adding HCT116 (described above) in ten even increments, from 0% to 90%. Of note, we also used the same marker or signature genes described for simulated tumors (above). In a second experiment (Supplementary Fig. 7a), we compared CIBERSORT with QP^{5 (link)}, LLSR^{4 (link)}, PERT^{6 (link)}, and RLR. We spiked naïve B cell GEPs from the leukocyte signature matrix into four random background mixtures of the remaining 21 leukocyte subsets in the signature matrix. The same background mixtures were used for each spike-in. We also tested the addition of unknown content by adding defined proportions (0 to 90%) of randomly permuted expression values from a naïve B cell reference transcriptome (median expression profile from samples used to build LM22, Supplementary Table 1). We then repeated this analysis for each of the remaining leukocyte subsets in LM22 (Supplementary Fig. 7b).

This study was a preplanned secondary analysis of a prospective registry of consecutive ED patients with severe sepsis with evidence of hypoperfusion treated with an institutional quantitative resuscitation protocol that is initiated in the ED at the time of recognition of sepsis (18 (link)). This study protocol was reviewed and approved by the institutional review board for the conduct of human research before enrollment of patients.
Subjects were enrolled from November 2005 through October 2007 in the ED at Carolinas Medical Center, an 800-bed teaching hospital with 120,000 ED patient visits per year. Explicit criteria for enrollment included 1) age >17 years; 2) suspected or confirmed infection; 3) two or more systemic inflammatory response syndrome criteria (19 (link)): heart rate >90 beats per minute, respiratory rate >20 breaths per minute, temperature >38°C or <36°C, white blood cell count >12,000 or <4000 cells/mm³ or >10% bands; and 4) systolic blood pressure <90 mm Hg or mean arterial pressure <65 mm Hg after a isotonic fluid bolus and anticipated need for ICU care, or a serum lactate concentration ≥4.0 mmol/L and anticipated need for ICU care. Exclusion criteria included 1) age <18 years; 2) need for immediate surgery; and 3) absolute contraindication for a chest central venous catheter.
Eligible subjects were identified by board-certified emergency physicians and were treated in the ED and medical ICU with an institution-approved quantitative resuscitation protocol that was previously described (20 (link)). All data elements required for calculation of the SOFA score at the time of ED recognition and resuscitation (T0) and 72 hours after ICU admission (T72), as well as hospital outcomes, were prospectively collected on standardized forms and entered into a database for later analysis. For T0 scores, only data available in the ED were used for calculation; and for T72 scores, data available within 12 hours of the 72-hour time point were used for calculation. To our knowledge, no physician in the ED had any independent knowledge of the SOFA score. For purposes of this study, we made one modification in the calculation of the respiratory component of the SOFA score (Table 1). We preferentially used the PaO₂ to FIO₂ ratio (PaO₂/FIO₂) when arterial blood gases were obtained. In cases where the PaO₂ was not available, we used the peripheral arterial oxygen saturation (SaO₂) to FIO₂ ratio (SaO₂/FIO₂). This substitution has been previously validated with high correlation (21 (link)). The definitions of SOFA score variables were otherwise identical to those reported in the original publication by Vincent et al (17 (link)).