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A high-throughput RNAi screen for detection of immune-checkpoint molecules that mediate tumor resistance to cytotoxic T lymphocytes.

Khandelwal N, Breinig M, Speck T, Michels T, Kreutzer C, Sorrentino A, Sharma AK, Umansky L, Conrad H, Poschke I, Offringa R, König R, Bernhard H, Machlenkin A, Boutros M, Beckhove P - EMBO Mol Med (2015)

Bottom Line: Tumor-immune resistance is mediated by cell surface ligands that engage immune-inhibitory receptors on T cells.These ligands represent potent targets for therapeutic inhibition.So far, only few immune-suppressive ligands have been identified.

View Article: PubMed Central - PubMed

Affiliation: Division of Translational Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany n.khandelwal@dkfz.de p.beckhove@dkfz.de.

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Related in: MedlinePlus

Heat map representation of potential positive and negative immune modulators identified from the RNAi screensDifferential scores were used to identify positive immune modulators (yellow) the knockdown of which enhance CTL-mediated cell killing and negative immune modulators (blue) the knockdown of which reduce CTL-mediated cell killing. Differential scores prior to filtering are shown for all genes tested in the 3 different screens (see Materials and Methods). Selected representative clusters of high-confidence hits are displayed herein.
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fig03: Heat map representation of potential positive and negative immune modulators identified from the RNAi screensDifferential scores were used to identify positive immune modulators (yellow) the knockdown of which enhance CTL-mediated cell killing and negative immune modulators (blue) the knockdown of which reduce CTL-mediated cell killing. Differential scores prior to filtering are shown for all genes tested in the 3 different screens (see Materials and Methods). Selected representative clusters of high-confidence hits are displayed herein.

Mentions: The reproducibility between the replicates within the individual screens was high for both the toxicity set and the viability set and is represented for screen 2 in Fig2B (Pearson rank correlation coefficient: 0.73 and 0.94, respectively). An overview of results for each gene from the individual screens is depicted in Fig2C–E. Luciferase-targeting siRNA (FLuc) expectedly abrogated the luciferase signal under both conditions and served as an internal control for the luciferase-based readout. As anticipated, control siRNAs targeting genes indispensable for cell survival (UBC, PLK-1) induced prominent cell killing (without CTLs; x-axis; Fig2C–E). In contrast, negative control siRNAs did not affect the luciferase signal. Thus, UBC and PLK-1 on one hand and negative control siRNA1 and siRNA2 on the other hand defined a range among which candidate genes were ranked according to their impact on CTL-mediated tumor lysis. Silencing of genes with reported immune-regulatory function, namely PD-L1, CEACAM-6, and galectin-3 (GAL-3), strongly reduced luciferase activity only in the cytotoxicity setup, whereby PD-L1 showed a higher impact on tumor lysis (Blank et al, 2004; Peng et al, 2008; Witzens-Harig et al, 2013). These therefore served as immune-modulatory reference genes throughout the screens. Next, unsupervised hierarchical clustering of the differential score between toxicity and viability values for all genes across the different screens was used to identify candidate immune modulators (Fig3). Clustering analysis revealed heterogeneity in the immune-modulatory properties of certain genes when compared across the 3 screens, which was expected given the intentional assorted biological setup used for the 3 different screens, including CTL source and tumor cell modification for luciferase expression. Therefore, only those robust immune-regulatory genes that modified anti-tumor-immune response irrespective of the T cell source or tumor modification were shortlisted for further filtering based on CTG assay to exclude hits that revealed viability effects. Rigorous filtering resulted in the identification of high-confidence hits of immune suppressors as well as immune activators associated with breast cancer.


A high-throughput RNAi screen for detection of immune-checkpoint molecules that mediate tumor resistance to cytotoxic T lymphocytes.

Khandelwal N, Breinig M, Speck T, Michels T, Kreutzer C, Sorrentino A, Sharma AK, Umansky L, Conrad H, Poschke I, Offringa R, König R, Bernhard H, Machlenkin A, Boutros M, Beckhove P - EMBO Mol Med (2015)

Heat map representation of potential positive and negative immune modulators identified from the RNAi screensDifferential scores were used to identify positive immune modulators (yellow) the knockdown of which enhance CTL-mediated cell killing and negative immune modulators (blue) the knockdown of which reduce CTL-mediated cell killing. Differential scores prior to filtering are shown for all genes tested in the 3 different screens (see Materials and Methods). Selected representative clusters of high-confidence hits are displayed herein.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4403046&req=5

fig03: Heat map representation of potential positive and negative immune modulators identified from the RNAi screensDifferential scores were used to identify positive immune modulators (yellow) the knockdown of which enhance CTL-mediated cell killing and negative immune modulators (blue) the knockdown of which reduce CTL-mediated cell killing. Differential scores prior to filtering are shown for all genes tested in the 3 different screens (see Materials and Methods). Selected representative clusters of high-confidence hits are displayed herein.
Mentions: The reproducibility between the replicates within the individual screens was high for both the toxicity set and the viability set and is represented for screen 2 in Fig2B (Pearson rank correlation coefficient: 0.73 and 0.94, respectively). An overview of results for each gene from the individual screens is depicted in Fig2C–E. Luciferase-targeting siRNA (FLuc) expectedly abrogated the luciferase signal under both conditions and served as an internal control for the luciferase-based readout. As anticipated, control siRNAs targeting genes indispensable for cell survival (UBC, PLK-1) induced prominent cell killing (without CTLs; x-axis; Fig2C–E). In contrast, negative control siRNAs did not affect the luciferase signal. Thus, UBC and PLK-1 on one hand and negative control siRNA1 and siRNA2 on the other hand defined a range among which candidate genes were ranked according to their impact on CTL-mediated tumor lysis. Silencing of genes with reported immune-regulatory function, namely PD-L1, CEACAM-6, and galectin-3 (GAL-3), strongly reduced luciferase activity only in the cytotoxicity setup, whereby PD-L1 showed a higher impact on tumor lysis (Blank et al, 2004; Peng et al, 2008; Witzens-Harig et al, 2013). These therefore served as immune-modulatory reference genes throughout the screens. Next, unsupervised hierarchical clustering of the differential score between toxicity and viability values for all genes across the different screens was used to identify candidate immune modulators (Fig3). Clustering analysis revealed heterogeneity in the immune-modulatory properties of certain genes when compared across the 3 screens, which was expected given the intentional assorted biological setup used for the 3 different screens, including CTL source and tumor cell modification for luciferase expression. Therefore, only those robust immune-regulatory genes that modified anti-tumor-immune response irrespective of the T cell source or tumor modification were shortlisted for further filtering based on CTG assay to exclude hits that revealed viability effects. Rigorous filtering resulted in the identification of high-confidence hits of immune suppressors as well as immune activators associated with breast cancer.

Bottom Line: Tumor-immune resistance is mediated by cell surface ligands that engage immune-inhibitory receptors on T cells.These ligands represent potent targets for therapeutic inhibition.So far, only few immune-suppressive ligands have been identified.

View Article: PubMed Central - PubMed

Affiliation: Division of Translational Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany n.khandelwal@dkfz.de p.beckhove@dkfz.de.

Show MeSH
Related in: MedlinePlus