Citations 2
Design and quality control of large-scale two-sample Mendelian randomization studies
Haycock, Philip , Borges, Maria Carolina , Burrows, Kimberley , Harrison, Sean , Burgess, Stephen , Chang, Xuling , Khankari, Nikhil K. , Tsilidis, Kostas K, Gaunt, Tom R. , Hemani, Gibran , Zheng, Jie , Truong, Thérèse , Law, Matthew H. , Mariosa, Daniela , Hung, Rayjean J, Smith, George Davey , Relton, Caroline L. , Martin, Richard M. , Peters, Ulrike , Rice, Terri, Gallinger, Steve, Cornish, Alex J. , Vijayakrishnan, Jayaram , Wrensch, Margaret , Korat, Andres V Ardisson , Wheeler, Bill, Nilsson, Björn , Smith, Caren E. , Riadi, David, Claus, Elizabeth B. , Hosnijeh, Ng, Irene Oi‐Lin , Passow, Jeanette E, Han, Jiali , Schildkraut, Joellen M. , Wiemels, Joseph L. , Yang, Keming , Wu, Lang , Boutron, Marie-Christine, Iles, Mark M. , Stanulla, Martin , Gaudet, Mia M., Lenha, Mobuchon, Camp, Nicki J, Sham, Pak C. , Brennan, Paul , Jenkins, Robert B. , Diskin, Sharon J. , Berndt, Sonja I. , Tsavachidis, Spiridon, Channock, Stephen J., Galesloot, Tessel E. , Haycock, Philip , Harrison, Sean , Chang, Xuling , Zheng, Jie , Law, Matthew H , Birmann, Brenda M , Mariosa, Daniela , Zheng, Wei , Davey Smith, George , Borges, Maria C , Martin, Richard M , Iles, Mark M , Truong, Therese , Lemaître, Rozenn N. , Westra, Jason , Tsilidis, Kostas K, O’Mara, Tracy A. , Spurdle, Amanda B. , Slager, Susan L. , Birmann, Brenda M. , Hosnijeh, Fatemeh Saberi , Amos, Christopher I. , Hung, Rayjean J, Zheng, Wei , Gunter, Marc J. , Tintle, Nathan , Cheng, Iona C. , Jenkins, Mark A. , Sud, Amit , Johansson, Mattias , Norman, Aaron D. , Klein, Alison P. , Clay‐Gilmour, Alyssa , Franke, André , Heng, Chew‐Kiat , Song, Ci , Ellinghaus, Eva , Ostroumova, Evgenia , Vathaire, Florent de , Cugliari, Giovanni , Matullo, Giuseppe , Cerhan, James R. , Passow, Jeanette E. Eckel, Foo, Jia Nee , Liu, Jianjun , Barnholtz‐Sloan, Jill S. , Maris, John M. , Hemminki, Kari , Kiemeney, Lambertus A. , Ámundadóttir, Laufey T. , Stern, Marc‐Henri , Purdue, Mark P. , Bondy, Melissa L. , Guénel, Pascal , Taylor, Philip R. , Gharahkhani, Puya , Ostrom, Quinn T. , Stolzenberg‐Solomon, Rachael Z. , Dorajoo, Rajkumar , Houlston, Richard S. , Enroth, Stefan , Harrison, Tabitha A. , Gyllensten, Ulf B , Vijai, Joseph , Shi, Yufang , Yang, Wenjian , Lin, Yi , Van Den Eeden, Stephen K
International Journal of Epidemiology | February 11, 2023 | Volume: 52 | Issue: 5 | Pages: 1498-1521
Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).
Abstract 1003: Targeting liver-tumor initiating cells via hampering the lipogenesis pathways through stearoyl - CoA desaturase
Fai, Kin, Lo, Jessica, Copland, John A. , Lau, Eunice Yuen-Ting , Ng, Irene Oi‐Lin , Lee, Terence K.
Cancer Research | July 26, 2016 | Volume: 76 | Issue: 14_Supplement | Pages: 1003-1003
Abstract Hepatocellular carcinoma is one of the most lethal cancers in the world. Most of the patients are diagnosed at advanced stage, and they receive sorafenib as their treatment modality. However, sorafenib can only extend patients’ survival to a median of 3-4 months. Hence, there is an urgent need to identify a new therapeutic target for treatment of this disease. Increasing evidence showed that tumor-initiating cells (T-ICs) are intrinsically resistant to conventional treatments. Identification of the signalling pathways that maintain the functions of T-ICs provides potential targets for treatment of HCC. For this purpose, we cultured serial passages of hepatospheres combined with chemotherapeutic regimens as a strategy to enrich liver T-IC population. Using cDNA microarray, we found upregulation of several key enzymes in lipogenesis in enriched T-IC population, among which Stearoyl CoA desaturase-1 (SCD1), the enzyme involved in the conversion of saturated into monounsaturated fatty acids, was the most significant. In HCC clinical samples, 62% (36/58) was found to be overexpressed (> 2-fold) when compared with non-tumor counterparts and patients with SCD1 overexpression had shorter disease free survival. Using overexpression and knockdown approaches, SCD1 was found to regulate the traits of T-ICs, including tumorigenicity, self-renewal, drug resistance and expression of liver T-IC markers. SCD1 was found critical in survival of T-ICs, as enriched T-IC population are more sensitive to the inhibition of SCD1 compared to adherent lineages. Interestingly, SCD1 was found to be upregulated in sorafenib-resistant HCC cells. Pharmacological inhibition of SCD1 by A939572 not only suppressed self-renewal ability but also consistently enhanced the sensitivity towards sorafenib. Using a patient-derived xenograft model, we found that a new inhibitor against SCD1 demonstrated significant growth suppressive effect. By comparing the genetic profiles between SCD1 knockdown cells and control cells by RNA sequencing analysis, we found that upregulation of ER stress signature genes may be the potential downstream targets of SCD1 to maintain the properties of T-ICs. In conclusion, we demonstrated the crucial role of SCD1 in maintenance of liver T-ICs, and targeting SCD1 in combination with sorafenib might be a novel therapeutic regimen against HCC. Citation Format: Kin Fai Ma, Jessica Lo, Eunice Yuen-Ting Lau, John A. Copland, Irene Oi-Lin Ng, Terence Kin-Wah Lee. Targeting liver-tumor initiating cells via hampering the lipogenesis pathways through stearoyl - CoA desaturase. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1003.