Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer

<div><p>Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitry has been identified as a major cause of acquired resistance. We developed a computational framework using a Bayesian statistical approach to model signal rewiring in acquired resistance. We used the <i>p</i>₁-model to infer potential aberrant gene-pairs with differential posterior probabilities of appearing in resistant-vs-parental networks. Results were obtained using matched gene expression profiles under resistant and parental conditions. Using two lapatinib-treated ErbB2-positive breast cancer cell-lines: SKBR3 and BT474, our method identified similar dysregulated signaling pathways including EGFR-related pathways as well as other receptor-related pathways, many of which were reported previously as compensatory pathways of EGFR-inhibition via signaling cross-talk. A manual literature survey provided strong evidence that aberrant signaling activities in dysregulated pathways are closely related to acquired resistance in EGFR tyrosine kinase inhibitors. Our approach predicted literature-supported dysregulated pathways complementary to both node-centric (SPIA, DAVID, and GATHER) and edge-centric (ESEA and PAGI) methods. Moreover, by proposing a novel pattern of aberrant signaling called V-structures, we observed that genes were dysregulated in resistant-vs-sensitive conditions when they were involved in the switch of dependencies from <i>targeted</i> to <i>bypass</i> signaling events. A literature survey of some important V-structures suggested they play a role in breast cancer metastasis and/or acquired resistance to EGFR-TKIs, where the mRNA changes of <i>TGFBR</i>2, <i>LEF</i>1 and <i>TP</i>53 in resistant-vs-sensitive conditions were related to the dependency switch from <i>targeted</i> to <i>bypass</i> signaling links. Our results suggest many signaling pathway structures are compromised in acquired resistance, and V-structures of aberrant signaling within/among those pathways may provide further insights into the bypass mechanism of targeted inhibition.</p></div

Performance comparison between the current model and our previous model [10] in terms of detecting perturbed signaling in acquired resistance.

<p>Percentages of signaling pathways detected as perturbed in acquired resistance by our <i>current</i> and <i>old models</i> in all KEGG, Reactome and WikiPathway databases: (A) in SKBR3, and (B) in BT474 cell-lines. For both the cell-lines, the performances using KEGG and Reactome pathways are comparable in both approaches, whereas our current model outperforms the old model for pathways from WikiPathway database.</p

Comparing the posterior probabilities of putative aberrant gene-pairs with corresponding PCC (Pearson Correlation Coefficient) values that were defined among genes prior to the Bayesian analyses, (A) for SKBR3 and (B) BT474 cell-lines.

<p>The first figures in (A) and (B) show the sorted posterior probability values of the putative aberrant gene-pairs in descending order, and the second figures of (A) and (B) show the scatter plot of their corresponding PCC values. Note that for both the graphs in (A) and (B) the rank of ordered aberrant pairs is shown in X-axis, and the posterior probabilities and PCC values of <i>red</i> gene-pairs are shown in Positive Y-axis and those of <i>green</i> pairs are shown in Negative Y-axis, correspondingly. A trendline (red or yellow trendlines for the SKBR3 and BT474 cell-lines, respectively) is drawn for each of the scatter plots (in (A) and (B)) by using a moving average with a <i>window size</i> set to 25. For both SKBR3 and BT474, these trendlines clearly show the similarity of the signal contained in the PCC values (defined prior to Bayesian analyses) and the pattern of changes in <i>a posteriori</i> values (resulting from Bayesian analyses), and demonstrates the robustness of Bayesian statistical modeling for selecting putative aberrant gene-pairs involved in acquired resistance.</p

Detection of perturbed pathways with SPIA method.

<p>(A) Two-way evidence plot for all 45 KEGG pathways for BT474 cell-line is drawn. Here, pathways are represented with dots and the pathways with red dots and blue dots correspond to perturbed pathways with FDR-corrected and Bonferroni-corrected global <i>p</i>-value, <i>pG</i> < 0.05, respectively. (B) Next, the perturbation plot for FoxO signaling pathway (KEGG pathway ID = 04068) was also observed, since it contains the lowest perturbation <i>p</i>-value among all, <i>pPERT</i> = 0.053. In this plot, perturbation of all genes in the FoxO signaling pathway are shown as a function of their initial log2 fold-change (lower-left panel), where each dot indicates a gene in the pathway, and non-differentially expressed genes are assigned 0 as their log2 fold-change value. The null distribution and the observed net accumulated perturbation (red line) are shown in the lower-right panel. (C) Network view of FoxO signaling pathway for BT474 cell-line, where nodes are the constituent genes and the edges are known links collected from literature [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173331#pone.0173331.ref034" target="_blank">34</a>]. Here, <i>green</i> and <i>red</i> edges are the aberrant gene-pairs found by our method. (D) The heatmap of the genes’ expression in aberrant gene-pairs found by our method in FoxO signaling network for BT474 cell-line.</p

Summary of predicted dysregulated signaling pathways from KEGG, Reactome and WikiPathway databases that plays a role as compensatory pathway of EGFR/HER2 inhibition in acquired resistance in both SKBR3 and BT474 cell-lines.

<p>Summary of predicted dysregulated signaling pathways from KEGG, Reactome and WikiPathway databases that plays a role as compensatory pathway of EGFR/HER2 inhibition in acquired resistance in both SKBR3 and BT474 cell-lines.</p

Comparative identification of pathway dysregulation in all 45 KEGG signaling pathways in resistant-vs-parental conditions in both SKBR3 and BT474 cell-lines.

<p>‘S’ for SKBR3 cell-line, and ‘B’ for BT474 cell-line.</p

The role of literature-supported Type-II and Type-III V-structures (<i>VSs</i>) in explaining gene dysregulation in acquired resistance.

<p>(A) Network views of Type-II <i>VSs</i> along with their pathway annotations in SKBR3 and BT474 cell-lines. (B) Network views of Type-III <i>VSs</i> in SKBR3 and BT474 cell-lines. Note that <i>VSs</i> shown here are only those for which the crossing-genes were found as up- or down-regulated in PT-vs-PB conditions, but oppositely regulated in both RB-vs-PB and RT-vs-PB conditions. Nodes are genes, and the edges are known signaling links [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0173331#pone.0173331.ref034" target="_blank">34</a>] that were also found as aberrant gene-pairs identified by our framework. Note that the width of edges is proportional to the posterior probability of corresponding pairs. Furthermore, for three <i>VSs</i> shown in (A) and (B) (right panels), mRNA changes for their constituent genes were found in the literature, implicating their role in breast cancer metastasis and/or in developing acquired resistance in EGFR-TKIs. (C) Above three <i>VSs</i> with their corresponding posterior probabilities, odds, and literature references of gene-pair associations for each of the <i>red</i> and <i>green</i> pairs. Statistical significance tests were done using t-tests and one-way ANOVA with multiple corrections (Sidak method). All the mRNA values were normalized by corresponding PB expression values in all three replicates. Significance was indicated by * (<i>p</i>-<i>value</i> < 0.05), ** (<i>p</i>-<i>value</i> < 0.005), and so on.</p

Schematic diagram of our proposed framework to identify and analyse aberrant signaling pathways in acquired resistance.

<p>(A) Gene expression datasets of breast cancer cell-lines for both parental and resistant conditions. (B) Two gene-gene relationship networks (GGR) were built from gene expression datasets of breast cancer cell-lines in Parental and resistant conditions. (C) & (D) A fully Bayesian approach was applied for detecting putative aberrant gene-pairs involved in acquired resistance. (E) Using the putative aberrant gene-pairs and a literature-curated signaling network, a statistical test was conducted to identify dysregulated pathways in acquired resistance. (F) Applying the known aberrant signaling links (from literature), we identify and explain the role of a proposed novel structure of aberrant pairs: V-structure (<i>VS</i>) in breast cancer metastasis and/or in developing acquired resistance to EGFR-TKIs.</p

Motifs identified by MEME.

<p>Sequence LOGOs for four of the motifs identified by MEME in the 15-class model for the <i>D. melanogaster</i> versus <i>D. simulans</i> 3′ UTR alignment: A) a polyA motif identified in Class 1, B) a CAG repeat motif identified in Class 9, C) a CA repeat motif identified in Class 12, D) a TCC repeat motif identified in Class 9.</p

Intergenic regions (IGR) selected for 5’RACE experiments^a and name and position of the two putative<i>Wolbachia</i> small non-coding RNAs we identified.

<p>^aNote that we did not demonstrate sRNA-like intergenic-specific transcription for most of these regions</p><p>^bIGR ID as designed in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118595#pone.0118595.s001" target="_blank">S1 Data</a></p><p>^cDetermined by 5’RACE</p><p>^dDetermined by RT-PCR with downstream CDS</p><p>^eAlso predicted by the bioinformatic approach.</p><p>Intergenic regions (IGR) selected for 5’RACE experiments^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118595#t004fn001" target="_blank">a</a>} and name and position of the two putative<i>Wolbachia</i> small non-coding RNAs we identified.</p