Periodic Reporting for period 1 - METLINK (METLINK: Identification of links between cancer cell growth and metabolism genes.)
Reporting period: 2018-10-01 to 2020-12-31
Recent advancements in genetic technologies reveal the possibility to ask new and previously inaccessible questions. The word metabolism, coming from the Greek Μεταβολισμός or “metabolismos” (translated means change) has already been known since the thirteenth century to indicate any transformation that the human body would encounter. Later on, the first organic molecules were discovered, but only with the 20th century and Hans Krebs and other notable biochemists, the field exploded and led to the assembly of what is known to us as the metabolic map. One of the drawbacks of these studies that could not be assessed with the available technologies at the time, resided in the lack of large part of the knowledge necessary to reveal the higher links that are present between cellular growth processes or signaling pathways and enzymatic reactions that were leading to the production of metabolites. Furthermore, still nowadays most of the Pubmed entries for metabolic enzymes are about the kinetic analysis of the reactions that they catalyze in their purified form, thus abstracted from their cellular environment. Synthetic lethality (SL) is a genetic phenomenon originally observed in Drosophila melanogaster by Bridges in 1922 and the term later coined by Dobzhansky in 1946, to describe complementary lethal systems in wild-type population of Drosophila pseudoobscura. It refers to cases in which the combination of two genes inactivation or mutations, which singularly are non-lethal, yields to lethality . This effect can be derived from the loss-of-function of two genes that act in parallel in redundant pathways, or belong to the same essential pathway or act in two distant pathways that are needed to react to a specific cellular perturbation. Questioning synthetic lethality is thus an elegant approach to study and link cellular growth processes dependent on genes and pathways in a systematic way. It promises to identify new therapeutic targets in different disease setting where either metabolism or growth defects are observed. Furthermore, cancer, which is due to an uncontrolled proliferation, has been shown to be surrounded by a different microenvironment, both immunological and at the nutrient levels. Regarding the presence of different nutrients, we already know that this is a quite distinctive feature of cancer, and indeed we use it in diagnostics when we measure glucose uptake in PET scans.
So far, synthetic lethality has offered its first approved drug (PARP inhibitors) for ovarian cancer mutated for BRCA genes. This therapeutic approach arrived to the clinic with an unprecedented speed. It is therefore the objective of this project to seek new genes within metabolic conditions, which are synthetic lethal to human cancer mutations. In this way new therapies could be designed against those targets and brought to the clinic faster than with single agents.
So far, synthetic lethality has offered its first approved drug (PARP inhibitors) for ovarian cancer mutated for BRCA genes. This therapeutic approach arrived to the clinic with an unprecedented speed. It is therefore the objective of this project to seek new genes within metabolic conditions, which are synthetic lethal to human cancer mutations. In this way new therapies could be designed against those targets and brought to the clinic faster than with single agents.
The project started with the design and production of a combinatorial CRISPR library. The genes were selected among genes being part of predicted synthetic lethalities or validated ones as positive controls. Given the non-automatable nature of combinatorial CRISPR screenings and the relatively new field, I selected 30 genes, controls included, for every side of the combination totaling 900 combinations (30*30). Given the fact that CRISPR guides are not yet perfect in their targeting ability, some redundancy and controls were needed. So, I designed 3 guides per gene, and this would total 8100 combinations (90*90). In order to make the production of the library affordable for an academic laboratory, we adapted the protocol originally published by the Doench laboratory for cloning in the so called Papi vector (https://www.nature.com/articles/nbt.4048(opens in new window)) available on Addgene. This took large part of the fellowship itself. I ordered sample oligonucleotides to optimize and establish the conditions of the cloning and later on, I ordered the entire oligonucleotides library necessary to prepare the combinatorial library. It was a learning by doing process which resulted in a combinatorial CRISPR library validated and ready to use, once its content was verified by deep sequencing. Later on, I choose to screen the library in a cell line previously used for similar purposes by Doench himself. It is a a kidney line immortalized by large T antigen, which inactivates TP53: HA1E which were obtained as a gift from the Weinberg laboratory. Another variant was added to the experiment: different metabolic conditions created with media supplemented or depleted of various non-essential components for a total of 23 different media. The screening was performed over a 21 days window. Afterwards genomic DNA was extracted from surviving cells and analyzed by NGS. The data are being analyzed with the help of a bioinformatician from CNIO which had to develop analysis tools.
Large part of the fellowship was dedicated to build the combinatorial CRISPR library and to prepare this screening. The screening was over by beginning of November 2019. By the beginning of January 2020, protocols to prepare the library for sequencing were established, but unfortunately a change in sequencing machine in the facility and a wrong advice on the primers to use for library preparation, extended the sequencing time to 3 months deviating from the planned 2 weeks. The sequencing data arrived at the beginning of March 2020, when non-essential activities were blocked in the laboratory in Madrid. At that time, we were ready to start the analysis which took a long time due to the complex set of data generated. Therefore, I suspended the fellowship (July-September) to let the analysis advance and came back to the project in October when it was still ongoing. In this time, I wrote a manuscript which is at the moment being reviewed by Plos Genetics. Anticipating the difficulty in finding other economic support for my research, as no extensions were provided to the grants and a long term prospect was not available for me in the laboratory, I decided to search for a research job in industry and requested an early termination of the fellowship to end of October 2020.
Large part of the fellowship was dedicated to build the combinatorial CRISPR library and to prepare this screening. The screening was over by beginning of November 2019. By the beginning of January 2020, protocols to prepare the library for sequencing were established, but unfortunately a change in sequencing machine in the facility and a wrong advice on the primers to use for library preparation, extended the sequencing time to 3 months deviating from the planned 2 weeks. The sequencing data arrived at the beginning of March 2020, when non-essential activities were blocked in the laboratory in Madrid. At that time, we were ready to start the analysis which took a long time due to the complex set of data generated. Therefore, I suspended the fellowship (July-September) to let the analysis advance and came back to the project in October when it was still ongoing. In this time, I wrote a manuscript which is at the moment being reviewed by Plos Genetics. Anticipating the difficulty in finding other economic support for my research, as no extensions were provided to the grants and a long term prospect was not available for me in the laboratory, I decided to search for a research job in industry and requested an early termination of the fellowship to end of October 2020.
The project devised a new method of cloning combinatorial CRISPR libraries in the Papi vector system, making the investigation of synthetic lethality approximately 50 folds cheaper than with previously published methods. These data are currently being peer reviewed. At the end of the analysis, which unfortunately is still ongoing, the final results of the screenings could suggest new cancer synthetic lethalities to be further investigated in order to provide new cancer targets and therefore new treatment avenues.