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--- worked_example_perturbation_effect [2021/01/11 14:00] – krian
+++ worked_example_perturbation_effect [2024/02/27 13:31] (current) – [References] krian
@@ Line 1: / Line 1: @@
-====== Worked example : Perturbation effect ======
+====== Worked example: Perturbation effect ======
-===== PDAC study =====
-In this example, we will use a sample of Pancreatic ductal adenocarcinoma (PDAC) from the repository TCGA -The Cancer Genome Atlas-. In order to simulate the effect of such treatment mentioned in several previous studies [ [[https://pubmed.ncbi.nlm.nih.gov/30975481/ | Blasco MT et al. Complete Regression of Advanced Pancreatic Ductal Adenocarcinomas upon Combined Inhibition of EGFR and C-RAF.]] ], we will use the erlotinib drug and apply a  knock-out of [[https://www.genome.jp/dbget-bin/www_bget?hsa:5894|RAF1]].
+In silico simulations of the functional effects that drug-induced perturbations would have in the cell are extremely valuable to predict putative therapeutic impacts of drugs or combinations of them. They are also useful to evaluate response inconsistencies and to search for resistance mechanisms. To demonstrate the value of this tool, this example will be focused on the functional impact that the combined inhibition of //EGFR// and //c-RAF// (//RAF1//) would have on pancreatic tumors. To do so, we simulated the effect of Erlotinib (a known and widely used anti-EGFR drug) in combination with the knockdown of the //RAF1// gene. This combination has been described to achieve a complete regression of pancreatic cancer in ductal adenocarcinoma derived xenografts induced by //KRAS// mutation [1].
-This simulation is carried out by changing the expression level of the genes of interest, in this case are : [[https://www.genome.jp/dbget-bin/www_bget?hsa:1956|EGFR]] and [[https://www.genome.jp/dbget-bin/www_bget?hsa:5894|RAF1]], recalculating the resulting signaling profile in the simulated condition and comparing it to the original profile.
+The drug effect is simulated by multiplying the expression value by the activity factor provided in the settings. To simulate a knockdown, the activity of the target gene is multiplied by the provided knock-down factor. In this example, the effect of Erlotinib reduces //EGFR// activity to a 10%, while the //RAF1// knock-down reduces its activity to a 1%.
-Similarly, the effect of inhibitory or agonistic drugs can be simulated by decreasing or increasing the expression level of the target gene. This module of analysis brings the functionality of the [[https://academic.oup.com/nar/article/44/W1/W212/2499353|PathAct]] algorithm to the HiPathia application.
-The erlotinib drug is an EGFR inhibitor, that why in this example we will notice that the application of erlotinib drug decreases the expression level of each node that has EGFR in its gene list.
-{{ ::perturbationexample.png?nolink | http://hipathia.babelomics.org/}}
+==== Step by step ====
-For reproducing this example you can click //Perturbation effect example// under the help button or you can launch a new study by following these steps:
+To reproduce this example, click the //Perturbation effect example// under the //help// button.
-  * Log in Hipathia using login button on the top right corner, the login panel will appear. you can also login using an anonymous user. Please visit [[logging_in|Logging in]] in to further information on this step.
+{{ ::perturbationexample.png?nolink&300 | http://hipathia.babelomics.org/}}
+ You can also launch a new study by following these steps:
+  * Log into Hipathia. Click the login button on the top right corner to open the login panel. You can also log in using an anonymous user. Please visit [[logging_in|Logging in]] for further information on this step.
 {{ :loginhipathia.png |}}
-  * By clicking the Perturbation effect tool in the menu, the empty form will appear.
+  * Click the //Perturbation effect// tool in the menu to open the empty form.
+  * Click the //Run example// button. Alternatively, here si where you could also upload your own gene expression file.
 {{ :formeexampleperturbationeffect.png |}}
-  * Press the run example button, A study will appear on the My studies panel and will be processed.
+  * A study will appear on the //My studies// panel and will be processed.
 {{ :run_example.png |}}
-  * Once finished, click on it to open the view window.
+  * Once finished (//Done//), click the study name to open the view window.
 {{ :finishedexampleperturbationeffect.png |}}
-  * The view window will appear.
+  * The view window will open.
 {{ :perturbationeffectexample1.png |}}
-  * If you select the genes with a thick red border (as shown in the following image) you will notice that one of its genes is one of our chosen genes targets, and also you can see in this example that the Erlotinib drug (antagonist) has changed the expression value of EGFR to 0 (inhibitory effect). You can either click on a gene on the pathway viewer and change its value.
-{{ :perturbationeffectexamplechangevalue1.png |}}
-In the //add genes// panel you can see all targeted genes and their expression levels after such treatment simulation.
-In the //Search genes// box ,of the //Add genes// panel, you can add more genes and another genes.
-{{ :searchgene.png |}}
-  *  You can modify the expression level of the genes listed in the Add genes panel and remove them from the list by pressing the **X** button to their right. The expression level of the removed genes will return to their original value.
+/*change screenshot ???*/
-Gene perturbations can be studied one at a time or simultaneously in combinations. In this way, it is possible to check for the potential effect of drug combinations over the activity of signaling pathways in the Pancreatic ductal adenocarcinoma sample.
-For this example we fix the following expression values:
-     * EGFR (by Erlotinib drug)
-     * RAF1 (KO)
-{{ :addgenesexample.png |}}
-===== Resutls and discussion =====
-{{ :loadingperturbationeffectstudy.png |}}
+You will notice that the nodes with a thick red outline (as shown in the screenshot below) contain at least one of the knocked-down genes, and those with a thick green outline contain some gene affected by a drug applied.
-Perturbation effect tool infers the effect of the knock-out or over-expression of a set of genes on the signaling pathways activity by comparing the signaling values of the pathways in the uploaded sample and the signaling values resulting from the modification of the expression values in the current sample by the selected values.
+  * Gene perturbations can be studied individually or in combination. This makes it possible to check for potential effects of drug combinations over the activity of signaling pathways.
-Each time the //Update// button on the //Gene list// panel is pressed, **a comparison is performed** with the modifications present in the Gene list and the Additional drug targets.
+  * To remove an effect, simply click the "X" to its right and the expression levels of the affected genes will return to their original value after clicking the //Update// button.
-Pathways with signaling differences are depicted in bold characters in the //Pathway list// panel "Categories panel". The **up and down arrows** indicate that there exist up- and down-regulated circuits in the corresponding pathways, respectively. When the up arrow is red or the down arrow is blue, the differences are significant. An absolute fold change greater than 2 is considered significant. Therefore, an absolute log fold change greater than log(2)= 0.6931472 is considered significant.
+  * The //Clear// button removes all perturbations being applied to the signaling landscape of the sample. To restore the perturbations applied in this example:
+      * Search "RAF1" in the //add gene// box and add it. Write 0.01 as the knock-down factor.
+      * Search "erlotinib" in the //add drug// box and tick the box to its right.
+/* {{ :searchgene.png |}} */
+  * Remember to click **Update** to apply all changes.
+/* {{ :addgenesexample.png |}} */
+===== Results and interpretation =====
+/* {{ :loadingperturbationeffectstudy.png |}} */
+The Perturbation effect tool reproduces the effect of the knock-down or over-expression of a set of genes by comparing the signaling profile of the pathways in the uploaded sample and the signaling values resulting from the modification of the expression values in the current sample by the selected values.
+Each time the //Update// button on the //Gene list// panel is pressed, a comparison is performed with the modifications present in the Gene list and the Additional drug targets.
+Pathways with signaling differences are presented in bold characters in the //Pathway list// panel "Categories panel". The **up and down arrows** indicate that there exist up and down-regulated circuits in the corresponding pathways, respectively. When the up arrow is red or the down arrow is blue, the differences are significant. An absolute fold change greater than 2 is considered significant. Therefore, an absolute log fold change greater than log(2)= 0.6931472 is considered significant.
 {{ :results_pathway.png |}}
-Circuits with signaling differences are depicted in bold characters in the //Circuit list// panel. The up and down arrows indicate that the circuit is up- or down-regulated, respectively. When the up arrow is red or the down arrow is blue, the differences are significant.
+Circuits with signaling differences are presented in bold characters in the //Circuit list// panel. The up and down arrows indicate that the circuit is up or down-regulated, respectively. When the up arrow is red or the down arrow is blue, the differences are significant.
 {{ :results_circuit.png |}}
-Results can be also visualized in the //Pathway viewer// in a graphical way. Each time a pathway is selected in the //Pathway List// it is displayed in the //Pathway viewer//. The edges of the circuits with a difference in their activation are depicted in different colors.
+Results can be also visualized graphically in the //Pathway viewer//. Each time a pathway is selected in the //Pathway List// it is displayed in the //Pathway viewer//. The edges of the circuits with a difference in their activation are depicted in different colors.
   * **Light greyish red**: The circuit is up-regulated, but not significantly.
   * **Light greyish blue**: The circuit is down-regulated, but not significantly.
@@ Line 57: / Line 66: @@
 {{ :edge_colors.png |}}
-The results can be exhaustively examined and downloaded from the **report generated** by pressing the //Show report// button. A new window with the report of the results for the current comparison is displayed. This report includes two fields:
+The results can be exhaustively examined and downloaded from the generated **report** by clicking the //Show report// button. A new window with the results report for the current comparison will be displayed. This report includes two fields:
   * **Input**: Lists the genes whose expression has been modified in the current comparison, and the new expression value.
-  * **Path impact**: Lists the names of the pathways, ordered by the absolute value of their fold change (also log(Fold_Change)). An absolute fold change greater than 2 is considered significant. Therefore, an absolute log fold change greater than log(2)= 0.6931472 is significant.
+  * **Circuit impact**: Lists the names of the signaling circuits (pathway:effector node), ordered by the absolute value of their fold change (also measured as the logaritmic transformation of Fold_Change). An absolute fold change greater than 2 is considered significant. Therefore, an absolute log fold change greater than 0.6931472 is significant.
 {{ :reportofperturbationeffect.png |}}
-In order to close this window and return to the tool page, you can press the close button on the right upper side of the window or the Close button at the bottom of the panel. the report panel is movable.
+To close this window and return to the tool page, you can press the close button on the right upper side of the window or the Close button at the bottom of the panel. /*The report panel is movable. */
+===== Discussion =====
+The combination of the inhibitions has a clear impact on cell mechanisms related to the Hallmarks of Cancer, such as proliferation, apoptosis, and cell adhesion and motility. Among the pathways dysregulated by the perturbations, we highlight the Ras signaling pathway (hsa04014), proteoglycans in cancer (hsa05205), ErbB signaling pathway (hsa04012), and PI3K/Akt signaling pathway (hsa04151). The dysregulation deregulation of these signaling pathways have been described in pancreatic cancer [2] and the in silico inhibition globally reduces the activity and the functions triggered by these, indeed some targets within them are being used to treat pancreatic tumors (such as //EGFR//, //KRAS//, //TGFB//, //NFKB//, //MEK1//).
+Focusing on the //Ras signaling pathway// (hsa04014), three circuits appear as inhibited by the knock-down of c-Raf:
+  * The ELK-1 circuit, which is generally activated in pancreatic cancer [3].
+  * The ETS-1 circuit. The ETS Proto-Oncogene family (//ETS//) has been linked to pancreatic cancer progression and, specifically, //ETS-1// has been described as potential target reducing angiogenesis and progression in pancreatic cancer [4, 5].
+  * The PLA2G4B circuit. //PLA2G4B// is highly expressed in the pancreas and this gene has been described to modulate the sensitivity of pancreatic cancer cells to chemoradiation treatment [6].
+Among the most represented effector genes affected by the knock-down simulation, we want to highlight the roles of //PLA2G4B//, //MAPK1//, //CDKN1A//, //ELK1//, //PRKCA//, and //CAMK2A// in processes such as signal transduction, calcium metabolism, and cell cycle regulation. These mechanisms have been highly related to cell proliferation and cancer progression, therefore inactivating the circuits that trigger these effectors would result in a potential reduction in cancer progression, which is consistent with the results observed in //Blasco et al.// [1].
+==== References ====
+[1]    M. T. Blasco et al., “Complete Regression of Advanced Pancreatic Ductal Adenocarcinomas upon Combined Inhibition of EGFR and C-RAF,” Cancer Cell, vol. 35, no. 4, pp. 573-587.e6, Apr. 2019, doi: 10.1016/j.ccell.2019.03.002.
+[2]    R. V. Iozzo and R. D. Sanderson, “Proteoglycans in cancer biology, tumour microenvironment and angiogenesis,” J. Cell. Mol. Med., vol. 15, no. 5, pp. 1013–1031, May 2011, doi: 10.1111/j.1582-4934.2010.01236.x.
+[3]    A. Arlt, H. Schäfer, and H. Kalthoff, “The ‘N-factors’ in pancreatic cancer: functional relevance of NF-κB, NFAT and Nrf2 in pancreatic cancer,” Oncogenesis, vol. 1, no. 11, Art. no. 11, Nov. 2012, doi: 10.1038/oncsis.2012.35.
+[4]    L. P. Lefter et al., “Transcriptional silencing of ETS-1 efficiently suppresses angiogenesis of pancreatic cancer,” Cancer Gene Ther., vol. 16, no. 2, Art. no. 2, Feb. 2009, doi: 10.1038/cgt.2008.65.
+[5]    S. Kobberup, P. Nyeng, K. Juhl, J. Hutton, and J. Jensen, “ETS-family genes in pancreatic development,” Dev. Dyn. Off. Publ. Am. Assoc. Anat., vol. 236, no. 11, pp. 3100–3110, Nov. 2007, doi: 10.1002/dvdy.21292.
+[6]    D. Wei et al., “Inhibition of protein phosphatase 2A radiosensitizes pancreatic cancers by modulating CDC25C/CDK1 and homologous recombination repair,” Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res., vol. 19, no. 16, pp. 4422–4432, Aug. 2013, doi: 10.1158/1078-0432.CCR-13-0788.
-  /* Visualize the results. For further information in the interpretation of the results, see [[Perturbation effect results|Perturbation effect results]].*/
+/* Visualize the results. For further information in the interpretation of the results, see [[Perturbation effect results|Perturbation effect results]].*/