Prostaglandins

Each brain area was processed separately and all tissues from a specific brain area were processed together, although the order of processing was randomized, as previously described [10 ]. The samples were removed from the −80°C freezer. After being shocked with liquid nitrogen, they were weighed and placed in centrifuge tubes on ice. Furthermore, 40 : 1 volumes of methanol were added to each tube followed by 10 μL of 1 uM d4-AEA. d4-AEA was added to act as an internal standard to determine the recovery of the compounds of interest. The tubes were then covered with parafilm and left on ice and in darkness for approximately 2 hours. Remaining on ice, the samples were then homogenized using a polytron for approximately 1 minute on each sample. The samples were then centrifuged at 19,000 ×g at 24°C for 20 minutes. The supernatants were then collected and placed in polypropylene tubes (15 or 50 mL), and HPLC-grade water was added making the final supernatant/water solution 25% organic. To isolate the compounds of interest, partial purification of the 25% solution was performed on a Preppy apparatus (Sigma-Aldrich) assembled with 500 mg C18 solid-phase extraction columns (Agilent Technologies, Santa Clara, CA). The columns were conditioned with 5 mL of HPLC-grade methanol immediately followed by 2.5 mL of HPLC-grade water. The supernatant/water solution was then loaded onto the C18 column and then washed with 2.5 mL of HPLC-grade water followed by 1.5 mL of 40% methanol. The prostaglandins were then collected with a 1.5 mL elution of 70% methanol, NAGly with a 1.5 mL elution of 85% methanol, and the ethanolamides with a 1.5 mL elution of 100% methanol. All were collected in individual autosampler vials and then stored in a −20°C freezer until mass spectrometer analysis.

BioVision (Waltham, MA, USA) provided the ELISA kits for assessing IL-6 (interleukin 6; K4145-100) and TNF-α (tumor necrosis factor, ab285327) with sensitivity values of 1 and 5 pg/mL, respectively [20 (link)]. The levels of glycosaminoglycans (GAGs; ab289842) in SYF were detected using commercial colorimetric kits provided by BioVision (Waltham, MA, USA) according to the method outlined in [21 (link)]. The serum levels of C-reactive protein (CRP), osteocalcin, (matrix metalloproteinases) MMP-1, and cathepsin K were estimated using a specialized sandwich ELISA kit (RayBiotech, USA) according to the manufacturer’s instructions. Prostaglandin (PGE2) and interleukin-1β (IL-1β) were measured in rat serum using a quantitative competitive ELISA kit (Cusabio, Wuhan, China) according to the manufacturer’s guidelines.

Two different statistical tests were used to determine if the stratification procedures generated four different tumor phenotypes, as shown in Figure 2A and Figure 5A.
Firstly, the median enzyme/receptor transcript levels in the four ‘PG’ or ‘Bile’ groups were tested against the expected global population using chi-squared tests to answer the research question: Are the transcript medians of the four groups different from the population from which they were taken?
Secondly, the distribution of the enzyme/receptor transcript levels within each of the prostaglandin or bile synthesizing groups was compared with their distribution within the respective ‘Low PG’ or ‘Low Bile’ group using t-tests to answer the research question: Is the distribution of the transcript levels in the PG-positive or Bile-positive groups different from the respective ‘Low PG’ or ‘Low Bile’ groups?
Each patient tumor was identified as belonging to one of the three canonical GMP subtypes (classical, mesenchymal, or proneural) independently using the algorithms described on the Gliovis platform. Then, utilizing the contingency tables, chi-squared tests were performed to analyze the relationships between the distribution of these three canonical classifications within each of the four stratified ‘PG’ or ‘Bile’ groups and the global population distribution (Figure 2B and Figure 5B).
The distribution of cell-type proxies and individual gene transcripts were tested for statistical significance for each of the stratified prostaglandin or bile-synthesizing groups relative to their respective ‘Low PG’ or ‘Low Bile’ groups using t-tests to identify the statistical differences between normalized transcript levels in the phenotypes vs. the ‘Low PG’ or ‘Low Bile’ groups (Figure 3B, Figure 4, Figure 6B and Figure 7).
Kaplan–Meier survival curves were analyzed using the log-rank test, with statistical significance calculated from the chi-squared value compared to the ‘Low PG’ subgroups (Figure 4A) and the ‘Low Bile’ subgroups (Figure 6A).
In Tables S1–S5, the overlap between the stratified prostaglandin and bile tumors is compared with previously identified tumor subtypes; the tumors were stratified with respect to Treg infiltration and HIF markers or were based on tumor sex-steroid generation [1 (link)]. Chi-squared tests were also used to analyze the statistically significant overlap between the groups.
Excel was used to perform the chi-squared tests, the t-tests, and the Kaplan–Meier log-rank tests.
For the cross-correlation analysis, shown in Figures S1–S7 and S10, the Gliovis platform was used to calculate Pearson’s correlation between the transcript pairs as indicated by the numeral and the superscripted stars (*); statistical significance is indicated when p < 0.05 *, p < 0.01 **, and p < 0.001 ***.