Cancer-specific association between Tau (MAPT) and cellular pathways, clinical outcome, and drug response

Tau (MAPT) is a microtubule-associated protein causing common neurodegenerative diseases or rare inherited frontotemporal lobar degenerations. Emerging evidence for non-canonical functions of Tau in DNA repair and P53 regulation suggests its involvement in cancer. To bring new evidence for a relevant role of Tau in cancer, we carried out an in-silico pan-cancer analysis of MAPT transcriptomic profile in over 10000 clinical samples from 32 cancer types and over 1300 pre-clinical samples from 28 cancer types provided by the TCGA and the DEPMAP datasets respectively. MAPT expression associated with key cancer hallmarks including inflammation, proliferation, and epithelial to mesenchymal transition, showing cancer-specific patterns. In some cancer types, MAPT functional networks were affected by P53 mutational status. We identified new associations of MAPT with clinical outcomes and drug response in a context-specific manner. Overall, our findings indicate that the MAPT gene is a potential major player in multiple types of cancer. Importantly, the impact of Tau on cancer seems to be heavily influenced by the specific cellular environment.


Figure S1 -
Figure S1 -(a)Correlation of MAPT gene expression with all expressed genes.Each histogram shows the correlation value distribution obtained for each cancer type.The number of genes with high positive/negative correlation (i.e.above 0.6 or below -0.6) is reported.(b) For the same analysis in (a), Benjamini-Hochberg adjusted p-values were computed and shown alongside correlation values in volcanoplots.An adjusted p-value threshold of 0.05 is indicated.(c) Association between MAPT average expression and the number of correlated genes per cancer type.The total number (left), the number of positively correlated genes (centre), and the number of negatively correlated genes (right) were evaluated.(d) All cancer types were clustered based on gene correlation with MAPT.The ConsensusClusterPlus algorithm was used.The plot shows changes in the 'area under the CDF curve' when increasing the number of clusters 'k', used as a parameter to select the optimal number of clusters, in this case 5. (e) Top 20 enriched Hallmark genesets in the comparison between MAPT KO and WT neuroblastoma cells.

Figure S2 -
Figure S2-Heatmap of 809 genes correlated with MAPT expression in at least one cancer type.Both genes and cancer types are ordered based on the hierarchical clustering of the correlation values.Fifty-two of the top 100 genes co-expressed with MAPT according to EnrichR (ARCHS 4 dataset) are overlapping with the 809 genes and are annotated in the heatmap.For each cancer type, the average MAPT expression and the number of genes correlated with MAPT are shown.Cancer types were grouped in 5 distinct clusters based on the correlation profiles using ConsensusClusterPlus and labels are indicated.

Figure S3 -
Figure S3-Selected PANTHER pathways in selected cancer types overlaid with the MAPT-gene correlation values for all evaluated genes.

Figure S4 -
Figure S4 -(a) Expression of MAPT in TP53 WT and TP53 MUT tumors.The analysis is stratified by cancer type.Differences are evaluated by a two-sided Student's t-test.(b) Expression of MAPT in tumors with WT P53 or with either a Truncating/HomDel mutation or an Inframe/Missense mutation in PT53.Differences were evaluated by a two-sided Student's t-test.

Figure S5 -
Figure S5 -Correlation with MAPT for all genes was computed separately for TP53 MUT and TP53 WT tumors.The delta correlation distribution (correlation in TP53 MUT -correlation in TP53 WT) is reported in the figure for each cancer type.The number of genes with an absolute delta above 0.6 is indicated.

Figure S6 -
Figure S6 -Heatmap of 514 genes with an absolute delta correlation above 0.6 in P53 WT vs P53 MUT tumors for at least one cancer type.The correlation analysis was performed only for 19 cancer types with at least 20 patients with P53 WT and 20 P53 MUT.MAPT correlation values are shown.For each group identified by the combination of cancer type and P53 status, the average MAPT expression and the number of genes correlated with MAPT are shown.

Figure S7 -
Figure S7 -Heatmap of 514 genes with an absolute delta correlation above 0.6 in P53 WT vs P53 MUT tumors for at least one cancer type.The correlation analysis was performed for 19 cancer types with at least 20 patients with P53 WT and 20 P53 MUT.

Figure S8 -Figure S9 -
Figure S8 -MAPT cancer-specific association with survival.Kaplan-Meier curves showing the association between MAPT (High/Low using the median as threshold) and survival in the overall population and stratifying according to P53 status.P-value obtained by log-rank test Figure S9 -Scatterplots for genes showing an absolute correlation >0.5 between the MAPT-gene correlation and MAPT hazard ratio across different cancer types.The 12 genes achieving an absolute MAPT-gene correlation >0.6 (as in Figure 1b) are shown.

Table S1
Percentage of TP53 mutations per cancer type.Mutation frequency is separated according to the 1 different mutation types (inframe/missense or truncating/homdel).