Additional file 3: of Serum long noncoding RNA HOTAIR as a novel diagnostic and prognostic biomarker in glioblastoma multiforme

Figure S2. A longitudinal study on a single GBM patient was carried out in order to monitor the changes in serum HOTAIR expression over time. 3 different time points were included in this study: pre-op (the blood was drawn right before the surgery started), post-op (at least 24 h after surgery) and during the 2 week follow-up (F/U) with the neurosurgeon. We show that the level of HOTAIR decreases after surgery and at the follow-up visit. (PDF 430 kb

Additional file 1: of Serum long noncoding RNA HOTAIR as a novel diagnostic and prognostic biomarker in glioblastoma multiforme

Supplementary materials and methods. (DOCX 109 kb

Additional file 2: of Serum long noncoding RNA HOTAIR as a novel diagnostic and prognostic biomarker in glioblastoma multiforme

Figure S1. HOTAIR expression detected in our biomarker assay is derived mostly from circulating RNA, not DNA. 3 GBM serum samples were selected at random and the relative HOTAIR expression in GBM serum with and without reverse transcription (RT)-PCR was determined. The HOTAIR RNA was reverse-transcribed into HOTAIR cDNA and qPCR was performed. The circulating HOTAIR DNA in the serum was detected by qPCR without RT. The considerable difference between HOTAIR expression with and without RT demonstrates that the HOTAIR we are detecting in our qRT-PCR reactions is derived from RNA and not DNA. (PDF 1003 kb

Additional file 1: of Intra-patient and inter-patient comparisons of DNA damage response biomarkers in Nasopharynx Cancer (NPC): analysis of NCC0901 randomised controlled trial of induction chemotherapy in locally advanced NPC

Supplementary Methods. Selection of “best cases and controls” for subset analysis correlating assay readouts with severe late xerostomia. Table S1. Intraclass correlation coefficient (ICC) for additional sensitivity analysis of FLICA measurements. The single measurement and average of 3 measurements columns reports the ICC when either one or three tests were performed, respectively. Table S2. Summary of inter-patient heterogeneity in apoptotic and DNA damage responses. Table S3. Clinical and dosimetric characteristics of the 17 patients included in the sub-group exploratory analysis correlating assay readouts with severe late xerostomia using a “best case-control” design. Figure S1. Gating of (A) general lymphocyte population and (B) CD4+ or CD8+ lymphocyte sub-populations for FLICA apoptosis analysis by flow cytometry. Figure S2. Bland-Altman plots for (A) FLICA assay, and (B) γH2AX for the general lymphocyte population, as well as plots for FLICA assays of the (C) CD4+ and (D) CD8+ T lymphocyte subset populations. From Bland-Altman plots, outliers were identified and excluded from subsequent sensitivity analyses. Figure S3. Correlation between background %FLICA and %FLICA post-8 Gy for the (A) CD4 and (B) CD8 T-lymphocyte subsets. Solid lines were generated by linear regression; R values were generated by Spearman correlation test. Figure S4. Apoptotic responses post-8Gy in the CD4 and CD8 T-lymphocyte subsets were correlated for the same patient. Solid lines were generated by linear regression; R values were generated by Spearman correlation test. Figure S5. Sub-group exploratory analysis comparing residual γH2AX 4 Gy 24 h foci count between best cases (N = 9) and controls (N = 8). (PDF 5363 kb