The Experts below are selected from a list of 7377 Experts worldwide ranked by ideXlab platform
John M Timmerman - One of the best experts on this subject based on the ideXlab platform.
-
an hk2 antisense oligonucleotide induces Synthetic Lethality in hk1 hk2 multiple myeloma
Cancer Research, 2019Co-Authors: Shili Xu, Arthur Catapang, Nicholas A Bayley, Reiko E Yamada, Alex Vasuthasawat, Joshua Sasine, Tianyuan Zhou, Daniel Braas, Ryan K. Trinh, John M TimmermanAbstract:Although the majority of adult tissues express only hexokinase 1 (HK1) for glycolysis, most cancers express hexokinase 2 (HK2) and many coexpress HK1 and HK2. In contrast to HK1+HK2+ cancers, HK1−HK2+ cancer subsets are sensitive to cytostasis induced by HK2shRNA knockdown and are also sensitive to Synthetic Lethality in response to the combination of HK2shRNA knockdown, an oxidative phosphorylation (OXPHOS) inhibitor diphenyleneiodonium (DPI), and a fatty acid oxidation (FAO) inhibitor perhexiline (PER). The majority of human multiple myeloma cell lines are HK1−HK2+. Here we describe an antisense oligonucleotide (ASO) directed against human HK2 (HK2-ASO1), which suppressed HK2 expression in human multiple myeloma cell cultures and human multiple myeloma mouse xenograft models. The HK2-ASO1/DPI/PER triple-combination achieved Synthetic Lethality in multiple myeloma cells in culture and prevented HK1−HK2+ multiple myeloma tumor xenograft progression. DPI was replaceable by the FDA-approved OXPHOS inhibitor metformin (MET), both for Synthetic Lethality in culture and for inhibition of tumor xenograft progression. In addition, we used an ASO targeting murine HK2 (mHK2-ASO1) to validate the safety of mHK2-ASO1/MET/PER combination therapy in mice bearing murine multiple myeloma tumors. HK2-ASO1 is the first agent that shows selective HK2 inhibition and therapeutic efficacy in cell culture and in animal models, supporting clinical development of this Synthetically lethal combination as a therapy for HK1−HK2+ multiple myeloma. Significance: A first-in-class HK2 antisense oligonucleotide suppresses HK2 expression in cell culture and in in vivo, presenting an effective, tolerated combination therapy for preventing progression of HK1−HK2+ multiple myeloma tumors. Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/10/2748/F1.large.jpg.
-
an hk2 antisense oligonucleotide induces Synthetic Lethality in hk1 hk2 multiple myeloma
Cancer Research, 2019Co-Authors: Shili Xu, Arthur Catapang, Nicholas A Bayley, Reiko E Yamada, Alex Vasuthasawat, Joshua Sasine, Tianyuan Zhou, Daniel Braas, Ryan K. Trinh, John M TimmermanAbstract:Although the majority of adult tissues express only hexokinase 1 (HK1) for glycolysis, most cancers express hexokinase 2 (HK2) and many coexpress HK1 and HK2. In contrast to HK1+HK2+ cancers, HK1−HK2+ cancer subsets are sensitive to cytostasis induced by HK2shRNA knockdown and are also sensitive to Synthetic Lethality in response to the combination of HK2shRNA knockdown, an oxidative phosphorylation (OXPHOS) inhibitor diphenyleneiodonium (DPI), and a fatty acid oxidation (FAO) inhibitor perhexiline (PER). The majority of human multiple myeloma cell lines are HK1−HK2+. Here we describe an antisense oligonucleotide (ASO) directed against human HK2 (HK2-ASO1), which suppressed HK2 expression in human multiple myeloma cell cultures and human multiple myeloma mouse xenograft models. The HK2-ASO1/DPI/PER triple-combination achieved Synthetic Lethality in multiple myeloma cells in culture and prevented HK1−HK2+ multiple myeloma tumor xenograft progression. DPI was replaceable by the FDA-approved OXPHOS inhibitor metformin (MET), both for Synthetic Lethality in culture and for inhibition of tumor xenograft progression. In addition, we used an ASO targeting murine HK2 (mHK2-ASO1) to validate the safety of mHK2-ASO1/MET/PER combination therapy in mice bearing murine multiple myeloma tumors. HK2-ASO1 is the first agent that shows selective HK2 inhibition and therapeutic efficacy in cell culture and in animal models, supporting clinical development of this Synthetically lethal combination as a therapy for HK1−HK2+ multiple myeloma. Significance: A first-in-class HK2 antisense oligonucleotide suppresses HK2 expression in cell culture and in in vivo, presenting an effective, tolerated combination therapy for preventing progression of HK1−HK2+ multiple myeloma tumors. Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/10/2748/F1.large.jpg.
Joo Sang Lee - One of the best experts on this subject based on the ideXlab platform.
-
Synthetic Lethality-mediated precision oncology via the tumor transcriptome.
Cell, 2021Co-Authors: Joo Sang Lee, Nishanth Ulhas Nair, Gal Dinstag, Lesley Chapman, Youngmin Chung, Kun Wang, Sanju Sinha, Hongui Cha, Dasol Kim, Alexander V SchperbergAbstract:Precision oncology has made significant advances, mainly by targeting actionable mutations in cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun to explore the utility of tumor transcriptome to guide patient treatment. Here, we introduce SELECT (Synthetic Lethality and rescue-mediated precision oncology via the transcriptome), a precision oncology framework harnessing genetic interactions to predict patient response to cancer therapy from the tumor transcriptome. SELECT is tested on a broad collection of 35 published targeted and immunotherapy clinical trials from 10 different cancer types. It is predictive of patients' response in 80% of these clinical trials and in the recent multi-arm WINTHER trial. The predictive signatures and the code are made publicly available for academic use, laying a basis for future prospective clinical studies.
-
Synthetic Lethality across normal tissues is strongly associated with cancer risk onset and tumor suppressor specificity
Science Advances, 2021Co-Authors: Joo Sang Lee, Eytan Ruppin, Kuoyuan Cheng, Nishanth Ulhas NairAbstract:Various characteristics of cancers exhibit tissue specificity, including lifetime cancer risk, onset age, and cancer driver genes. Previously, the large variation in cancer risk across human tissues was found to strongly correlate with the number of stem cell divisions and abnormal DNA methylation levels. Here, we study the role of Synthetic Lethality in cancer risk. Analyzing normal tissue transcriptomics data in the Genotype-Tissue Expression project, we quantify the extent of co-inactivation of cancer Synthetic lethal (cSL) gene pairs and find that normal tissues with more down-regulated cSL gene pairs have lower and delayed cancer risk. Consistently, more cSL gene pairs become up-regulated in cells treated by carcinogens and throughout premalignant stages in vivo. We also show that the tissue specificity of numerous tumor suppressor genes is associated with the expression of their cSL partner genes across normal tissues. Overall, our findings support the possible role of Synthetic Lethality in tumorigenesis.
-
abstract 36 Synthetic Lethality across normal tissues is strongly associated with cancer risk onset and tumor suppressor specificity
Cancer Research, 2020Co-Authors: Nishanth Ulhas Nair, Joo Sang Lee, Kuoyuan Cheng, Eytan RuppinAbstract:The tissue-specificity of cancer and cancer risk is a fundamental open research question. Beyond advancing our understanding of carcinogenesis, elucidating the factors underlying cancer risk may also contribute to cancer prevention. Recent studies have shown that the variation in tissue cancer risk can be explained by the number of tissue stem cell divisions occurring during the lifetime and by abnormal levels of DNA methylation. While cancer risk is likely not determined by a single factor, no other factor has been reported since to account for this fundamental variation. Here we show that cancer Synthetic Lethality (SL) is another strong contributor of cancer risk in human tissues. SL is a well-known type of genetic interaction where cell death occurs under the combined inactivation of two paired SL genes but not either of them alone. Targeting SLs has been recognized as a highly valuable approach for cancer treatment. We hypothesized that since down-regulated cancer SL (cSL) gene pairs reduce the viability of cancer cells, they may impede the malignant transformation of normal cells, thus modulating cancer risk. Utilizing several recently published large-scale cancer SL networks, we systematically quantified the cancer SL load (defined as the fraction of down-regulated cancer SL gene pairs) in numerous normal and cancer tissues from the TCGA and GTEx datasets. Our key findings are: 1. The cSL loads are lower in cancers vs their matched normal tissues. Furthermore, we find that the cSL load decreases progressively as cancers develop from normal tissues through multiple stages of pre-malignant lesions. These results testify that high cSL load is detrimental to cancer cells, acting as a barrier to cancer development. That is, as normal cells undergo malignant transformation, they need to reactivate at least some of the down-regulated cSL genes for the emerging cancer cells to survive. 2. In accordance with these observations, we find that cSL load in normal tissues is strongly inversely correlated with their lifetime cancer risk. 3. We find that cSL load is the first identified predictor of cancer onset time across different normal tissues - higher cSL load in the younger population is associated with later onset of cancers in that tissue. 4. cSL are important contributors of the tissue/cancer-type specificity of numerous tumor suppressor genes (like BRCA1) - that is, the activity state of cSL partners of quite a few tumor suppressor genes predicts the specific tissues in which they are known to drive cancer. Taken together, these results show that Synthetic Lethality load in normal tissues is a novel important biological contributor of cancer risk in humans. While Synthetic Lethality has been attracting tremendous attention as a way to identify cancer vulnerabilities and target them, this is the first time that its role in mediating cancer development is uncovered. Citation Format: Nishanth Ulhas Nair, Kuoyuan Cheng, Joo Sang Lee, Eytan Ruppin. Synthetic Lethality across normal tissues is strongly associated with cancer risk, onset, and tumor suppressor specificity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 36.
-
Synthetic Lethality across normal tissues is strongly associated with cancer risk onset and tumor suppressor specificity
bioRxiv, 2020Co-Authors: Joo Sang Lee, Eytan Ruppin, Kuoyuan Cheng, Nishanth Ulhas NairAbstract:Abstract Various characteristics of cancers exhibit tissue-specificity, including lifetime cancer risk, onset age and cancer driver genes. Previously, the large variation in cancer risk across human tissues was found to strongly correlate with the number of stem cell divisions and abnormal DNA methylation levels occurring in them. Here we study the role of another potentially important factor, Synthetic Lethality, in cancer risk. Analyzing transcriptomics data in the GTEx compendium we quantify the extent of co-inactivation of cancer Synthetic lethal (cSL) gene pairs in normal tissues and find that normal tissues with more down-regulated cSL gene pairs have lower and delayed cancer risk. We also show that the tissue-specificity of numerous tumor suppressor genes is strongly associated with the expression of their cSL partner genes in the corresponding normal tissues. Overall, our findings uncover the role of Synthetic Lethality as a novel important factor involved in tumorigenesis.
-
beyond Synthetic Lethality charting the landscape of pairwise gene expression states associated with survival in cancer
Cell Reports, 2019Co-Authors: Assaf Magen, Avinash Das Sahu, Joo Sang Lee, Mahfuza Sharmin, Alexander LugoAbstract:The phenotypic effect of perturbing a gene's activity depends on the activity level of other genes, reflecting the notion that phenotypes are emergent properties of a network of functionally interacting genes. In the context of cancer, contemporary investigations have primarily focused on just one type of functional relationship between two genes-Synthetic Lethality (SL). Here, we define the more general concept of "survival-associated pairwise gene expression states" (SPAGEs) as gene pairs whose joint expression levels are associated with survival. We describe a data-driven approach called SPAGE-finder that when applied to The Cancer Genome Atlas (TCGA) data identified 71,946 SPAGEs spanning 12 distinct types, only a minority of which are SLs. The detected SPAGEs explain cancer driver genes' tissue specificity and differences in patients' response to drugs and stratify breast cancer tumors into refined subtypes. These results expand the scope of cancer SPAGEs and lay a conceptual basis for future studies of SPAGEs and their translational applications.
Shili Xu - One of the best experts on this subject based on the ideXlab platform.
-
an hk2 antisense oligonucleotide induces Synthetic Lethality in hk1 hk2 multiple myeloma
Cancer Research, 2019Co-Authors: Shili Xu, Arthur Catapang, Nicholas A Bayley, Reiko E Yamada, Alex Vasuthasawat, Joshua Sasine, Tianyuan Zhou, Daniel Braas, Ryan K. Trinh, John M TimmermanAbstract:Although the majority of adult tissues express only hexokinase 1 (HK1) for glycolysis, most cancers express hexokinase 2 (HK2) and many coexpress HK1 and HK2. In contrast to HK1+HK2+ cancers, HK1−HK2+ cancer subsets are sensitive to cytostasis induced by HK2shRNA knockdown and are also sensitive to Synthetic Lethality in response to the combination of HK2shRNA knockdown, an oxidative phosphorylation (OXPHOS) inhibitor diphenyleneiodonium (DPI), and a fatty acid oxidation (FAO) inhibitor perhexiline (PER). The majority of human multiple myeloma cell lines are HK1−HK2+. Here we describe an antisense oligonucleotide (ASO) directed against human HK2 (HK2-ASO1), which suppressed HK2 expression in human multiple myeloma cell cultures and human multiple myeloma mouse xenograft models. The HK2-ASO1/DPI/PER triple-combination achieved Synthetic Lethality in multiple myeloma cells in culture and prevented HK1−HK2+ multiple myeloma tumor xenograft progression. DPI was replaceable by the FDA-approved OXPHOS inhibitor metformin (MET), both for Synthetic Lethality in culture and for inhibition of tumor xenograft progression. In addition, we used an ASO targeting murine HK2 (mHK2-ASO1) to validate the safety of mHK2-ASO1/MET/PER combination therapy in mice bearing murine multiple myeloma tumors. HK2-ASO1 is the first agent that shows selective HK2 inhibition and therapeutic efficacy in cell culture and in animal models, supporting clinical development of this Synthetically lethal combination as a therapy for HK1−HK2+ multiple myeloma. Significance: A first-in-class HK2 antisense oligonucleotide suppresses HK2 expression in cell culture and in in vivo, presenting an effective, tolerated combination therapy for preventing progression of HK1−HK2+ multiple myeloma tumors. Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/10/2748/F1.large.jpg.
-
an hk2 antisense oligonucleotide induces Synthetic Lethality in hk1 hk2 multiple myeloma
Cancer Research, 2019Co-Authors: Shili Xu, Arthur Catapang, Nicholas A Bayley, Reiko E Yamada, Alex Vasuthasawat, Joshua Sasine, Tianyuan Zhou, Daniel Braas, Ryan K. Trinh, John M TimmermanAbstract:Although the majority of adult tissues express only hexokinase 1 (HK1) for glycolysis, most cancers express hexokinase 2 (HK2) and many coexpress HK1 and HK2. In contrast to HK1+HK2+ cancers, HK1−HK2+ cancer subsets are sensitive to cytostasis induced by HK2shRNA knockdown and are also sensitive to Synthetic Lethality in response to the combination of HK2shRNA knockdown, an oxidative phosphorylation (OXPHOS) inhibitor diphenyleneiodonium (DPI), and a fatty acid oxidation (FAO) inhibitor perhexiline (PER). The majority of human multiple myeloma cell lines are HK1−HK2+. Here we describe an antisense oligonucleotide (ASO) directed against human HK2 (HK2-ASO1), which suppressed HK2 expression in human multiple myeloma cell cultures and human multiple myeloma mouse xenograft models. The HK2-ASO1/DPI/PER triple-combination achieved Synthetic Lethality in multiple myeloma cells in culture and prevented HK1−HK2+ multiple myeloma tumor xenograft progression. DPI was replaceable by the FDA-approved OXPHOS inhibitor metformin (MET), both for Synthetic Lethality in culture and for inhibition of tumor xenograft progression. In addition, we used an ASO targeting murine HK2 (mHK2-ASO1) to validate the safety of mHK2-ASO1/MET/PER combination therapy in mice bearing murine multiple myeloma tumors. HK2-ASO1 is the first agent that shows selective HK2 inhibition and therapeutic efficacy in cell culture and in animal models, supporting clinical development of this Synthetically lethal combination as a therapy for HK1−HK2+ multiple myeloma. Significance: A first-in-class HK2 antisense oligonucleotide suppresses HK2 expression in cell culture and in in vivo, presenting an effective, tolerated combination therapy for preventing progression of HK1−HK2+ multiple myeloma tumors. Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/10/2748/F1.large.jpg.
William G Kaelin - One of the best experts on this subject based on the ideXlab platform.
-
abstract c124 hif independent Synthetic Lethality between cdk4 6 inhibition and vhl loss across species
Molecular Cancer Therapeutics, 2019Co-Authors: Hilary E Nicholson, Benjamin E Housden, Norbert Perrimon, William G KaelinAbstract:Inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene and its protein product, pVHL, occurs in ~90% of clear cell renal cell carcinoma (ccRCC) cases. pVHL is part of the ubiquitin ligase complex that targets the HIF2α transcription factor, an oncoprotein in ccRCC, for proteasomal degradation. Without functional pVHL, HIF2α accumulates and induces inappropriate transcription of angiogenic, invasive, and growth-promoting genes. Drugs inhibiting HIF2α or its downstream target VEGF are active against ccRCC, but both de novo and acquired resistance are common and no current therapies are curative. We hypothesized that loss of pVHL might create context-specific dependencies that could then be targeted therapeutically. To look for such Synthetic lethal targets, we generated human and Drosophila cell pairs that were isogenic for pVHL (or its Drosophila ortholog) and screened using RNAi and chemical compound libraries. The overlap of the hits from these screens identified a hyperdependence on CDK4/6 activity in pVHL-defective cells compared to their pVHL-proficient counterparts. In secondary assays we confirmed that pharmacologic inhibition of CDK4/6 by either Abemaciclib or Palbociclib preferentially reduced viability of VHL-/-cells as compared to VHL+/+cells across a variety of human ccRCC cell lines. Importantly, inhibition of VHL-/-ccRCC cells by Palbociclib was abrogated by expressing a Palbociclib-resistant CDK6 cDNA or by knockout of the canonical CDK4/6 target pRB. Sensitivity to Palbociclib could be reversed by expressing exogenous pVHL, but not a pVHL mutant lacking its known substrate docking site. HIF2aknockout in VHL-/-cells did not eliminate the effect of CDK4/6 inhibition, thus HIF2ais not necessary for the Synthetic lethal relationship between VHLand CDK4/6. Moreover, the combination of the HIF2ainhibitor PT2399 and the CDK4/6 inhibitor Palbociclib synergistically suppressed proliferation of VHL-/-ccRCC in vitro in HIF2a-sensitive cell lines. Both Palbociclib and Abemaciclib suppress VHL-/-ccRCC tumor growth in nude mice, including tumors that are PT2399-resistant. My future work will aim to identify the mechanism that underlies the Synthetic Lethality between VHLand CDK4/6 activity. Citation Format: Hilary Nicholson, Benjamin Housden, Norbert Perrimon, William G Kaelin. HIF-independent Synthetic Lethality between CDK4/6 inhibition and VHL loss across species [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr C124. doi:10.1158/1535-7163.TARG-19-C124
-
Synthetic Lethality a framework for the development of wiser cancer therapeutics
Genome Medicine, 2009Co-Authors: William G KaelinAbstract:The challenge in medical oncology has always been to identify compounds that will kill, or at least tame, cancer cells while leaving normal cells unscathed. Most chemotherapeutic agents in use today were selected primarily for their ability to kill rapidly dividing cancer cells grown in cell culture and in mice, with their selectivity determined empirically during subsequent animal and human testing. Unfortunately, most of the drugs developed in this way have relatively low therapeutic indices (low toxic dose relative to the therapeutic dose). Recent advances in genomics are leading to a more complete picture of the range of mutations, both driver and passenger, present in human cancers. Synthetic Lethality provides a conceptual framework for using this information to arrive at drugs that will preferentially kill cancer cells relative to normal cells. It also provides a possible way to tackle 'undruggable' targets. Two genes are Synthetically lethal if mutation of either gene alone is compatible with viability but simultaneous mutation of both genes leads to death. If one is a cancer-relevant gene, the task is to discover its Synthetic lethal interactors, because targeting these would theoretically kill cancer cells mutant in the cancer-relevant gene while sparing cells with a normal copy of that gene. All cancer drugs in use today, including conventional cytotoxic agents and newer 'targeted' agents, target molecules that are present in both normal cells and cancer cells. Their therapeutic indices almost certainly relate to Synthetic lethal interactions, even if those interactions are often poorly understood. Recent technical advances enable unbiased screens for Synthetic lethal interactors to be undertaken in human cancer cells. These approaches will hopefully facilitate the discovery of safer, more efficacious anticancer drugs that exploit vulnerabilities that are unique to cancer cells by virtue of the mutations they have accrued during tumor progression.
-
the concept of Synthetic Lethality in the context of anticancer therapy
Nature Reviews Cancer, 2005Co-Authors: William G KaelinAbstract:Two genes are Synthetic lethal if mutation of either alone is compatible with viability but mutation of both leads to death. So, targeting a gene that is Synthetic lethal to a cancer-relevant mutation should kill only cancer cells and spare normal cells. Synthetic Lethality therefore provides a conceptual framework for the development of cancer-specific cytotoxic agents. This paradigm has not been exploited in the past because there were no robust methods for systematically identifying Synthetic lethal genes. This is changing as a result of the increased availability of chemical and genetic tools for perturbing gene function in somatic cells.
Eytan Ruppin - One of the best experts on this subject based on the ideXlab platform.
-
Synthetic Lethality across normal tissues is strongly associated with cancer risk onset and tumor suppressor specificity
Science Advances, 2021Co-Authors: Joo Sang Lee, Eytan Ruppin, Kuoyuan Cheng, Nishanth Ulhas NairAbstract:Various characteristics of cancers exhibit tissue specificity, including lifetime cancer risk, onset age, and cancer driver genes. Previously, the large variation in cancer risk across human tissues was found to strongly correlate with the number of stem cell divisions and abnormal DNA methylation levels. Here, we study the role of Synthetic Lethality in cancer risk. Analyzing normal tissue transcriptomics data in the Genotype-Tissue Expression project, we quantify the extent of co-inactivation of cancer Synthetic lethal (cSL) gene pairs and find that normal tissues with more down-regulated cSL gene pairs have lower and delayed cancer risk. Consistently, more cSL gene pairs become up-regulated in cells treated by carcinogens and throughout premalignant stages in vivo. We also show that the tissue specificity of numerous tumor suppressor genes is associated with the expression of their cSL partner genes across normal tissues. Overall, our findings support the possible role of Synthetic Lethality in tumorigenesis.
-
abstract 36 Synthetic Lethality across normal tissues is strongly associated with cancer risk onset and tumor suppressor specificity
Cancer Research, 2020Co-Authors: Nishanth Ulhas Nair, Joo Sang Lee, Kuoyuan Cheng, Eytan RuppinAbstract:The tissue-specificity of cancer and cancer risk is a fundamental open research question. Beyond advancing our understanding of carcinogenesis, elucidating the factors underlying cancer risk may also contribute to cancer prevention. Recent studies have shown that the variation in tissue cancer risk can be explained by the number of tissue stem cell divisions occurring during the lifetime and by abnormal levels of DNA methylation. While cancer risk is likely not determined by a single factor, no other factor has been reported since to account for this fundamental variation. Here we show that cancer Synthetic Lethality (SL) is another strong contributor of cancer risk in human tissues. SL is a well-known type of genetic interaction where cell death occurs under the combined inactivation of two paired SL genes but not either of them alone. Targeting SLs has been recognized as a highly valuable approach for cancer treatment. We hypothesized that since down-regulated cancer SL (cSL) gene pairs reduce the viability of cancer cells, they may impede the malignant transformation of normal cells, thus modulating cancer risk. Utilizing several recently published large-scale cancer SL networks, we systematically quantified the cancer SL load (defined as the fraction of down-regulated cancer SL gene pairs) in numerous normal and cancer tissues from the TCGA and GTEx datasets. Our key findings are: 1. The cSL loads are lower in cancers vs their matched normal tissues. Furthermore, we find that the cSL load decreases progressively as cancers develop from normal tissues through multiple stages of pre-malignant lesions. These results testify that high cSL load is detrimental to cancer cells, acting as a barrier to cancer development. That is, as normal cells undergo malignant transformation, they need to reactivate at least some of the down-regulated cSL genes for the emerging cancer cells to survive. 2. In accordance with these observations, we find that cSL load in normal tissues is strongly inversely correlated with their lifetime cancer risk. 3. We find that cSL load is the first identified predictor of cancer onset time across different normal tissues - higher cSL load in the younger population is associated with later onset of cancers in that tissue. 4. cSL are important contributors of the tissue/cancer-type specificity of numerous tumor suppressor genes (like BRCA1) - that is, the activity state of cSL partners of quite a few tumor suppressor genes predicts the specific tissues in which they are known to drive cancer. Taken together, these results show that Synthetic Lethality load in normal tissues is a novel important biological contributor of cancer risk in humans. While Synthetic Lethality has been attracting tremendous attention as a way to identify cancer vulnerabilities and target them, this is the first time that its role in mediating cancer development is uncovered. Citation Format: Nishanth Ulhas Nair, Kuoyuan Cheng, Joo Sang Lee, Eytan Ruppin. Synthetic Lethality across normal tissues is strongly associated with cancer risk, onset, and tumor suppressor specificity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 36.
-
Synthetic Lethality across normal tissues is strongly associated with cancer risk onset and tumor suppressor specificity
bioRxiv, 2020Co-Authors: Joo Sang Lee, Eytan Ruppin, Kuoyuan Cheng, Nishanth Ulhas NairAbstract:Abstract Various characteristics of cancers exhibit tissue-specificity, including lifetime cancer risk, onset age and cancer driver genes. Previously, the large variation in cancer risk across human tissues was found to strongly correlate with the number of stem cell divisions and abnormal DNA methylation levels occurring in them. Here we study the role of another potentially important factor, Synthetic Lethality, in cancer risk. Analyzing transcriptomics data in the GTEx compendium we quantify the extent of co-inactivation of cancer Synthetic lethal (cSL) gene pairs in normal tissues and find that normal tissues with more down-regulated cSL gene pairs have lower and delayed cancer risk. We also show that the tissue-specificity of numerous tumor suppressor genes is strongly associated with the expression of their cSL partner genes in the corresponding normal tissues. Overall, our findings uncover the role of Synthetic Lethality as a novel important factor involved in tumorigenesis.
-
beyond Synthetic Lethality multiple gene interaction types play a key functional role in cancer
bioRxiv, 2018Co-Authors: Assaf Magen, Avinash Das Sahu, Joo Sang Lee, Mahfuza Sharmin, Alexander Lugo, Silvio J Gutkind, Eytan Ruppin, Sridhar HannenhalliAbstract:The phenotypic effect of perturbing a gene9s activity depends on the activity state of other genes, reflecting the fundamental notion that genotype to phenotype linkage is mediated by a network of functionally interacting genes. The vast majority of contemporary investigations have focused on just one type of genetic interactions (GI) - Synthetic Lethality (SL). However, there may be additional types of GIs whose systematic identification may markedly enrich the molecular and functional characterization of cancer. Here, based on a novel data-driven approach, we identify ~72K GIs of 11 new types, shared across cancers. These GIs are highly predictive of patient survival, stratify breast cancer tumors into refined subtypes, and explain differences in patients9 response to drugs and cancer driver genes9 tissue-specificity. These results markedly expand the scope of cancer GIs and lay a strong conceptual and computational basis for future studies of additional types of GIs and for their translational applications.
-
abstract pr09 harnessing Synthetic Lethality to predict clinical outcomes of cancer treatment
Molecular Cancer Therapeutics, 2017Co-Authors: Joo Sang Lee, Livnat Jerbyarnon, Avinash Das, Arnaud Amzallag, Dikla Atias, Cyril H Benes, Talia Golan, Eytan RuppinAbstract:Significance: The identification of Synthetic Lethal interactions (SLi) have long been considered a foundation for the advancement of cancer treatment. The rapidly accumulating large-scale patient data now provides a golden opportunity to infer SLi directly from patient samples. Here we present a new data-driven approach termed ISLE for identifying SLi, which is then shown to be predictive of clinical outcomes of cancer treatment in an unsupervised manner, for the first time. Methods: ISLE consists of four inference steps, analyzing tumor, cell line and gene evolutionary data: It first identifies putative SL gene pairs whose co-inactivation is underrepresented in tumors, testifying that they are selected against. Second, it further prioritizes candidate SL pairs whose co-inactivation is associated with better prognosis in patients, testifying that they may hamper tumor progression. Finally, it eliminates false positive SLi using gene essentiality screens (testifying to causal SLi relations) and prioritizing SLi paired genes with similar evolutionary phylogenetic profiles. Results: We applied ISLE to analyze the TCGA tumor collection and generated the first clinically-derived pan-cancer SL-network, composed of SLi common across many cancer types. We validated that these SLi match the known, experimentally identified SLi (AUC=0.87), and show that the SL-network is predictive of patient survival in an independent breast cancer dataset (METABRIC). Based on the predicted SLi, we predicted drug response in a wide variety of in vitro, mouse xenograft and patient data, altogether encompassing >700 single drugs and >5,000 drug combinations in >1,000 cell lines, 375 xenograft models and >5,000 patient samples. Importantly, these predictions were performed in an unsupervised manner, reducing the known risk of over-fitting the data commonly associated with supervised prediction methods. SL-derived predictions are based on computing an SL-score that estimates the efficacy of a given drug in a given tumor based on the latter9s omics data. The SL-score counts the number of inactive SL-partners of a given drug target(s) in the given tumor, reflecting the notion that a drug is likely to be more effective in tumors where many of its targets9 SL-partners are inactive. The predicted SL-scores show significant correlations (R > 0.4) with large-scale in vitro and in vivo drug response screens for the majority of drugs tested. Based on the conjecture that synergism between drugs may be mediated by underlying SLi between their targets, we additionally provide accurate predictions of drug synergism for both in vitro and in vivo drug combination screens (AUC~0.8). Most importantly, we demonstrate for the first time that an SL-network can successfully predict the treatment outcome in cancer patients in multiple large-scale patient datasets including the TCGA, where SLis successfully predict patients9 response for 75% of cancer drugs. Conclusions: ISLE is predictive of the patients9 response for the majority of current cancer drugs. Of paramount importance, the predictions of ISLE are based on SLi between (potentially) all genes in the cancer genome, thus prioritizing treatments for patients whose tumors do not bear specific actionable mutations in cancer driver genes, offering a novel approach to precision-based cancer therapy. The predictive performance of ISLE is likely to further improve with the expected rapid accumulation of additional cancer omics and clinical phenotypic data. Citation Format: Joo Sang Lee, Avinash Das, Livnat Jerby-Arnon, Dikla Atias, Arnaud Amzallag, Cyril H. Benes, Talia Golan, Eytan Ruppin. Harnessing Synthetic Lethality to predict clinical outcomes of cancer treatment [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr PR09.
