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. 2019 Jan 2;11(473):eaao5253.
doi: 10.1126/scitranslmed.aao5253.

Sex differences in GBM revealed by analysis of patient imaging, transcriptome, and survival data

Wei Yang  1 , Nicole M Warrington  2 , Sara J Taylor  2 , Paula Whitmire  3 , Eduardo Carrasco  3 , Kyle W Singleton  3 , Ningying Wu  4   5 , Justin D Lathia  6 , Michael E Berens  7 , Albert H Kim  8   9 , Jill S Barnholtz-Sloan  10 , Kristin R Swanson  3   5 , Jingqin Luo  11   12 , Joshua B Rubin  13   9
Affiliations

Sex differences in GBM revealed by analysis of patient imaging, transcriptome, and survival data

Wei Yang et al. Sci Transl Med. .

Abstract

Sex differences in the incidence and outcome of human disease are broadly recognized but, in most cases, not sufficiently understood to enable sex-specific approaches to treatment. Glioblastoma (GBM), the most common malignant brain tumor, provides a case in point. Despite well-established differences in incidence and emerging indications of differences in outcome, there are few insights that distinguish male and female GBM at the molecular level or allow specific targeting of these biological differences. Here, using a quantitative imaging-based measure of response, we found that standard therapy is more effective in female compared with male patients with GBM. We then applied a computational algorithm to linked GBM transcriptome and outcome data and identified sex-specific molecular subtypes of GBM in which cell cycle and integrin signaling are the critical determinants of survival for male and female patients, respectively. The clinical relevance of cell cycle and integrin signaling pathway signatures was further established through correlations between gene expression and in vitro chemotherapy sensitivity in a panel of male and female patient-derived GBM cell lines. Together, these results suggest that greater precision in GBM molecular subtyping can be achieved through sex-specific analyses and that improved outcomes for all patients might be accomplished by tailoring treatment to sex differences in molecular mechanisms.

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Figures

Figure 1:
Figure 1:. Sex differences in MRI-based metrics of therapeutic responses and their correlation with survival.
(A) Tumor growth velocities calculated from serial MR images exhibit progressive decline for female but not male patients treated with temozolomide (TMZ) in 63 GBM patients. (B) Velocity of tumor growth (low velocity = green line, high velocity = purple line) over the first temozolomide imaging interval (1–3, 28 day cycles of TMZ) stratifies female survival (log-rank, p=0.00817), but not male survival (p=0.263). (C) Histograms of pretreatment D and rho values in all available MRI cases (independent 53 and 318 GBM case series) for male (n=227) and female (n=144) patients. (D) Pretreatment D significantly stratifies survival among females (n=144, log-rank, p=0.0071), and not among males (n=227, p=0.61). (E) High pretreatment rho is associated with worse survival outcomes for both females (n=144, logrank, p=0.032) and males (n= 227, p=0.0037).
Figure 2:
Figure 2:. Heatmaps of joint and sex-specific expression components of TCGA GBM transcriptome data revealed by JIVE.
The heatmaps visualize each expression component. Each row represents a gene and each column a patient sample. For each patient, there are two color codes presented above the heatmap. These identify their assignment to sex-specific clusters and to TCGA molecular subtypes (gray indicates unassigned samples). Samples were ordered by sex-specific clusters. The original female (A) and male (B) expression data were decomposed into the shared expression component common to both sexes (“Joint”) and the expression component individual to each sex (“Female-specific” and “Male-specific”) and residuals as indicated. The female-relevant heatmaps (A) show 283 signature genes that define the five female-specific clusters, and the male-relevant heatmaps (B) show 293 signature genes that define the five male-specific clusters. (C) Venn diagram of male and female signature genes indicates that 116 genes are in common.
Figure 3:
Figure 3:. Sex-specific survival effects of IDH mutation.
(A) Overall survival benefit of fc3 and mc5 is demonstrated in the combined TCGA, GSE13041, GSE16011, and REMBRANDT datasets. See table S3 for p-values and hazard ratios. (B) Overall survival for IDH1 wildtype cases indicate that both fc3 and mc5 exert effects on survival in the absence of IDH1 mutation. (C) Overall survival in IDH1-mutant cases indicates that male-specific clusters are still associated with an effect on survival. The numbers of female IDH1-mutant cases not assigned to fc3 are n= 3, 2, 3, 6 in fc1, 2, 4 and 5 respectively, using TCGA and GSE16011 samples in combination (see table S7). (D) IDH1 mutation confers a similar survival benefit in males and females with GBM. (E) The survival benefit of fc3 is independent of IDH1 status. In contrast, IDH1 status exerts a significant effect on survival in mc5 cases. p = 4.3e-4 for the comparison between mc5 cases with and without IDH1 mutation. Overall log rank test p value is shown comparing across all the groups presented in each panel (table S8 shows the p-values and hazard ratios for all pairwise comparisons).
Figure 4:
Figure 4:. Disease-free survival of sex-specific clusters in TCGA GBM dataset and overall survival of sex-specific clusters in three independent datasets combined.
(A) Disease-free survival (DFS) in TCGA-derived female clusters (1–5). (B) DFS in TCGA-derived male clusters (1–5). (C) DFS in TCGA-derived female clusters (1–5) in which IDH1-mutant cases are plotted as an independent cluster. (D) DFS in TCGA-derived male clusters (1–5) in which IDH1-mutant cases are plotted as an independent cluster. Independent samples combining GSE13041, GSE16011, and REMBRANDT datasets were assigned to sex-specific clusters, and the superiority of overall survival of fc3 (E) and mc5 (F) was validated in the independent samples. Overall log rank test p value is shown comparing across all the groups presented in each panel (see tables S3 and S4 for the p-values and hazard ratios for all pairwise comparisons).
Figure 5:
Figure 5:. Analysis of genes and pathways that mediate better survival.
(A) In the combined dataset, the survival of females assigned to female cluster 3 (median survival 1172 days) was compared to the survival of males assigned to male cluster 5 (median survival 620 days). (B-D) Genes that distinguished female cluster 3 and male cluster 5 from other female and male clusters, respectively, were compared (see table S2). Pathways in all analyses were prioritized by the combination of the numbers of genes from the pathway involved and the corrected p-value for the relevance of the pathway. (B) Calcium/calmodulin signaling was the most significantly involved shared pathway between female cluster 3 and male cluster 5 (adjusted p < 0.001). (C) The integrin signaling pathway was the most significant female-specific pathway (adjusted p-value < 0.001, table S9). Genes that were up- and down- regulated in fc3 compared to the other female clusters are in red and blue boxes, respectively. (D) Cell cycle regulation was the most significant male-specific pathway (adjusted p-value < 0.001, table S9). Genes that were up- and down- regulated in mc5 compared to the other male clusters are in red and blue boxes, respectively. See table S2 for complete gene lists and statistics for each analysis.
Figure 6:
Figure 6:. Male Cluster 5-defining genes and overall survival in the merged TCGA, GSE16011, and GSE13041 dataset.
(A) Density plots for sex-specific expression of male (in blue) and female (in red) GBM specimens of three male cluster 5 defining genes (BIRC5, KIF20A, CCNB2). The overlay in male and female plots indicates near identical expression in the populations. (B) Expression of each gene by sex and sex-specific clusters is presented as boxplots. (C) High and low expression groups for each gene were defined relative to the level of expression that distinguished male cluster 5 from the other male clusters (see Supplemental Material—overall sex-specific survival effects). The survival effects of differences in expression were determined for males and females. Each gene exerted a greater effect on survival in males compared to females. P-values from Cox regression model are labeled in red for comparisons between survival curves of female GBM patients with low vs. high expression of each and labeled in blue for the same survival analysis of male GBM patients. The p-value labeled in green refers to the interaction of sex and low/high expression of a gene in Cox regression models. Parallel analyses of the female cluster 3-defining genes and the other male cluster 5-defining genes are presented in fig. S9 and fig S10, respectively.
Figure 7:
Figure 7:. Expression of cluster-defining genes and response to common chemotherapeutics in vitro.
(A) Absolute IC 50 values for temozolomide, etoposide, lomustine, and vincristine for 5 male and 4 female patient-derived glioblastoma cell lines were calculated from six-point dose response curves for each cell line. Boxplots of IC50 across cell lines by sex are presented (horizontal bar indicates median). Median male and female IC50 values were not significantly different based on two sample t-test. Spearman correlation coefficients of IC50 values for each drug with expression of mc5.17 genes (B), fc3.9 genes (C), or random gene sets are shown in male and female cell lines. For mc5.17 and fc3.9 genes, box plots represent the distribution of the 17 or 9 cluster-defining genes, respectively, and for random gene sets, the box plots represent the distribution of the Olkin-averaged Spearman correlation coefficient [54] of 17 or 9 randomly selected genes per random gene set for 1000 random gene sets. Asterisks represent p<0.01 compared to random gene sets for each sex. (D) Quantification of the percent of phospho-histone H3 (pHH3) positive nuclei in male GBM cells implanted in male (black bars) or female (white bars) nude mice. Tumor-bearing mice were treated with vehicle (DMSO), temozolomide (21 mg/kg/day x 5 days), or etoposide (20 mg/kg/every other day x 3 doses), and pHH3 positivity was determined in a blinded fashion.
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