Regenerative medicine- Direct and indirect cell reprogramming

Regenerative medicine-Direct and indirect cell reprogramming
My last three blog posts commented on direct cell reprogramming. You may be wondering if there is a technology called indirect cell reprogramming. The answer is yes. It is formally called induced pluripotent stem cell (iPSC, cells that have the ability to become any cell in the body)-mediated reprogramming, and it was developed earlier than direct cell reprogramming. In this blog post, I give a brief introduction of the two technologies and the challenges faced by both technologies.

Both reprogramming technologies involve the conversion of one cell type into another, target, cell type, intended for therapeutic use. Usually, the conversion starts by using the most abundant cells in the body, such as human fibroblast cells, a type of cell found in connective tissue.

Indirect cell reprogramming
Indirect cell reprogramming is a technology that converts somatic cells to another type of cell via first transitioning through an intermediate state, induced pluripotent stem cells (iPSCs).¹ Therefore it is also called induced pluripotent stem cell (iPSC)-mediated reprogramming. The iPSCs have similar properties as embryonic stem cells in having unlimited differentiation capacity, while avoiding the ethical issues related to embryonic stem cells.² Moreover, as iPSCs are generated from patients, this eliminates the problem of tissue rejection following transplantation in patients. Once iPSCs are generated, the cells can then be directed for development and differentiation, to form desired cells.

Four main transcription factors (Oct3/4, Sox2, Klf4, c-Myc), called Yamanaka factors, that induce somatic cells into pluripotent states, were first identified by Japanese scientists, and the finding was published in 2006.¹ These transcription factors are highly expressed in embryonic stem cells, and are able to induce pluripotency in both mouse and human somatic cells.¹

Since the generation of the first induced pluripotent cells, some progress has been made to improve the quality of the iPSCs generated and the efficiency of the technology. Methods include:
1) replacing of c-Myc, which is oncogenic and may cause tumour formation, in many protocols of pluripotent cell induction;^3-6
2) using of viral delivery systems, such as an adenovirus, which does not integrate into the recipient’s DNA.^7,8 This choice of virus is because a retrovirus, which is used for delivery of the four factors in the original protocol, would integrate into host’s DNA and cause insertional mutagenesis, which increases the risk of tumorigenicity;
3) replacing the original Yamanaka factors by small molecules and chemical compounds. This could also avoid the use of retrovirus;⁹
4) expressing Yamanaka factors for a shorter time for induction. This saves the time required to generate, expand and differentiate pluripotent cells, and avoids the creation of teratomas, a rare type of tumor that can contain fully-developed tissues and organs.^10-12

Direct cell reprogramming
Direct cell reprogramming, also called transdifferentiation, is the conversion of a fully functional cell type into cell type of other lineage. The process bypasses a state of pluripotency. Transdifferentiation between some cell types can occur naturally in response to injury, and can be induced experimentally. I have made a brief introduction to transdifferentiation technology in a previous blog post.

A major limitation of direct cell reprogramming is the identification of reprogramming factors that promote conversion to a specific target cell type. The conventional strategy, which screens through a list of transcription factors that are important for the development of the target cells, is a time-consuming and laborious process. There are a few predictive software applications developed to facilitate the process. These include MOGRIFY¹³ and epiMOGRIFY¹⁴ which we mentioned in the last three blog posts, CellNet,^15,16 and the one developed by Massachusetts Institute of Technology (MIT).¹⁷

Challenges faced by the two technologies
As you can see from the general description of the two technologies, direct cell reprogramming is faster, cost-effective and more accessible than iPSC-based protocols. Direct cell reprogramming protocols do not use Yamanaka factors, which are licensed, to induce pluripotency. The technology does not involve ex vivo cell expansion and transplantation, as in iPSC-mediated reprogramming.

However, both technologies face the same problem of scalability, which could impede their therapeutic applications. For the direct cell conversion approach, most converted cells could either experience cell cycle arrest that limit the expansion of the cell populations, or they tend to revert back to what they were. This lowers the number of cells available for further use. Similarly, for the indirect cell reprogramming, forced differentiation of induced pluripotent stem cells to distinct lineages also leads to the problem of cell cycle arrest and inability to expand. Moreover, the efficiency of inducing mature cells into pluripotency is less than 4%, which is very low.¹⁸

Quality of induced pluripotent stem cells generated from the indirect cell reprogramming is also a concern. The iPSCs generated are highly tumorigenic.¹ This maybe due to the fact that the iPSCs are mostly derived from somatic cells of aged individuals. The risk that comes with this source of cells is the incidence of spontaneously occurring tumours, which commonly increases exponentially with aging. Concerns related to tumorigenicity and teratoma formation by these cells hamper their direct applicability.

Conclusion
Both direct and indirect cell reprogramming have been developed for more than a decade, and the technologies provide a feasible method to generate cells for biological studies, tissue engineering or transplantation. Diseases such as diabetes, heart failure, arthritis, and many more, which affect a high proportion of the world population, are hopefully to be treatable from the cell reprogramming technologies. Although no cell-based therapy has yet been officially approved in any country in the world, once the challenges mentioned above are overcome, the clinical application of this technology may not be far away.



References
1. K. Takahashi, and S. Yamanaka. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 2006, 126 (4): 663–76.
2. B. Lo, and L.Parham. Ethical issues in stem cell research. Endocrine Reviews, Volume 30, Issue 3, 1 May 2009, Pages 204–213.
3. J. Han, P. Yuan, H. Yang, et al. Tbx3 improves the germ-line competency of induced pluripotent stem cells. Nature, 2010;463:1096–100.
4. J. Chen, J. Liu, J. Yang, et al. BMPs functionally replace Klf4 and support efficient reprogramming of mouse fibroblasts by Oct4 alone. Cell Res., 2011;21:205–12.
5. H.Y. Li, Y. Chien, Y.J. Chen, et al. Reprogramming induced pluripotent stem cells in the absence of c-Myc for differentiation into hepatocyte-like cells. Biomaterials. 2011;32:5994–6005.
6. M. Maekawa, K. Yamaguchi, T. Nakamura, et al. Direct reprogramming of somatic cells is promoted by maternal transcription factor Glis1. Nature, 2011;474:225–9.
7. N, Fusaki, H. Ban, A. Nishiyama, et al. Efficient induction of transgene-free human pluripotent stem cells using a vector based on Sendai virus, an RNA virus that does not integrate into the host genome. Proc. Jpn. Acad. Ser.B., 2009;85:348–62.
8. W. Zhou, and C.R. Freed. Adenoviral gene delivery can reprogram human fibroblasts to induced pluripotent stem cells. Stem Cells, 2009;27(11): 2667–74.
9.X. Li, J. Xu, and H. Deng. Small molecule-induced cellular fate reprogramming: promising road leading to Rome. Curr. Opin. Genet. Dev., 2018, 52, 29–35.
10. L. Kurian, I. Sancho-Martinez, E. Nivet, et al. Conversion of human fibroblasts to angioblast-like progenitor cells. Nat. Methods, 2013; 10:77–83.
11. M. Thier, P. Wörsdörfer, Y.B. Lakes, et al. Direct conversion of fibroblasts into stably expandable neural stem cells. Cell Stem Cell. 2012; 10:473–479.
12. A. Ocampo, P. Reddy, P. Martinez-Redondo, et al. In vivo amelioration of age-associated hallmarks by partial reprogramming. Cell, 2016 December 15; 167(7): 1719–1733.e12.
13.O.J.L. Rackham, J. Firas, and H. Fang, et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, March 2016, Vol. 48, No. 3.
14. U.S. Kamaraj, J. Chen, K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 2020, 11, 509–522, November 18.
15. S.A. Morris, P. Cahan, H. Li, et al. Dissecting engineered cell types and enhancing cell fate conversion via CellNet. Cell, 2014, 158, 889–902.
16. P. Cahan, H.Li, S.A. Morris. et al. CellNet: network biology applied to stem cell engineering.Cell, 2014, 158, 903–915.
17. A.C. D’Alessio, Z.P. Fan, K.J. Wert, et al. A systematic approach to identify candidate transcription factors that control cell identity. Stem Cell Reports, 2015 Nov 10;5(5):763-775.
18. Rao MS, Malik N. Assessing iPSC reprogramming methods for their suitability in translational medicine. J Cell Biochem. 2012;113:3061–8.

Predictive bioinformatic platforms for direct cellular reprogramming-Mogrify Ltd (final part)

Predictive bioinformatic platforms for direct cellular reprogramming: Mogrify Ltd (final part)
Since its launch, Mogrify Ltd has started several projects on different therapeutic areas of regenerative medicine, which have made use of the prediction results from its computation platform Mogrify. In this blog post, I am going to present to you what I have found from the company’s website. (I am not sponsored by them, just looking.)

Application of the prediction from MOGRIFY
Through its wholly-owned subsidiary, Chondrogenix, Mogrify Ltd has stepped into the therapeutic area of musculoskeletal diseases such as osteoarthritis. The algorithm platform MOGRIFY identified a cocktail of transcription factors for the company, Chondrogenix, to convert, in a culture dish, different starting cell types from diseased patients, into functional chondrocytes that are capable of forming cartilage. Musculoskeletal diseases are usually caused by bone or cartilage defects. This technology paved the way for them to write an application request to the regulators to enhance the FDA-approved Autologous Chondrocyte Implantation (ACI) therapy, and to create additional reprogramming therapies using cells from donors (allogenic reprogramming therapy) or by direct cell conversion in living organisms (in vivo reprogramming therapy). Chondrogenix received two phases of funding from SBRI Healthcare for this project.^1,2

Mogrify Ltd is also using its computational platform to predict combinations of transcription factors to induce conversion of one cell type to another in order to produce proteins which are not produced sufficiently well by existing production systems. The resulting target cell types could provide researchers with improved access to important proteins found in human cell types that are difficult to obtain, and allow for more efficient antibody production methods for biologic drugs. This exploratory research is done with the collaboration of the MRC’s Laboratory of Molecular Biology (MRC-LMB) in Cambridge.³

In fact, Mogrify Ltd also collaborates with MRC-LMB to improve the MOGRIFY cell reprogramming platform itself. The enhanced version, MOGRIFY V2, incorporates data from next-generation sequencing and single-cell RNA sequencing into the algorithm to enhance the quality and accuracy of transcription factor predictions and cell conversion efficacy.⁴

Furthermore, Mogrify Ltd is also involved in allogeneic (using cells from a donor who is not the patient) T-cell immunotherapy for inflammatory and autoimmune diseases, by collaborating with Sangamo Therapeutics, a genomic medicine company in the US. Mogrify is responsible for the discovery and optimisation of the cell conversion technology from induced pluripotent stem cells (iPSCs) or embryonic stem cells (ESCs) to regulatory T cells (Tregs). Sangamo expects to then use its technology and therapeutic development capabilities to transform these Tregs cells into ready to use allogeneic therapy candidates for the treatment of inflammatory and autoimmune diseases. The resulting collaboration will hopefully accelerate the development of scalable and accessible CAR-Treg cell therapies so that the treatments can be delivered more rapidly, in a more cost-effective way to a larger patient population.⁵

Financial Support
Since its launch in February 2019, Mogrify Ltd has attracted investments from strategic corporate investors to strengthen its business. According to a press release of the company in May this year, Mogrify Ltd has raised a total of US$33 million from seed funding and two rounds of Series A financing. The investors include Ahren Innovation Capital, 24Haymarket, Dr. Darrin M. Disley, OBE (CEO of Mogrify Ltd), Parkwalk Advisors, Astellas Venture Management, Dr Jonathan Milner (co-founder of Abcam PLC), and the University of Bristol Enterprise Fund III.⁶

In March 2019, Mogrify Ltd was awarded $555,000 (£420,000) from Innovate UK, a UK innovation agency, on a data-driven cell conversions project to produce cell therapies with potential applications in wound healing and oncology immunotherapy.⁷

Moreover, Chondrogenix (the subsidiary of Mogrify Ltd) received two rounds of funding from SBRI Healthcare, an NHS England initiative, championed by the Academic Health Science Networks (AHSNs). These funds were awarded for the purpose of generating a safe, efficient and scalable source of cartilage cells for the treatment of cartilage defects, osteoarthritis and other musculoskeletal conditions.^1,2

Conclusion
From the above information, it is obvious that Mogrify Ltd has ambition to develop and scale up reprogramming of cells for many autologous and allogeneic cell therapies, as well as to create in vivo reprogramming therapies (direct cell conversion in living organisms).^1-3,5 The two software platforms developed by the company no doubt speed up the process of direct cellular reprogramming, by using algorithms based on the big data already available in public repositories instead of performing trial and error experimentally. With the financial support it has got so far, I have no doubt that the company, in the near future, can meet its target of producing stable reprogrammed cells at scale for some areas of cell therapies. However, the company needs to overcome some challenges when it comes to clinically applying its reprogrammed cells.

The hurdles include the safety issues regarding the components suggested by the software platforms for cell conversion. There is a possibility that some biological factors such as cMYC, when overexpressed, can cause tumour growth.^10,11 The method to deliver biological factors safely is also a concern. Engineered viruses constructed to deliver transcription factors may integrate into a DNA region of target cells and cause a tumour later. In addition, the recipient’s immunity against the reprogrammed cells also needs to be addressed. These challenges, though, are also faced by other biotech companies focusing on regenerative medicine.

Besides the above-mentioned issues, I am eager to see the reports on the experiments, which apply the prediction from MOGRIFY⁸ and epiMOGRIFY⁹, to be published soon. I am also expecting Mogrify Ltd will merge the two software platforms into a single platform with synergistic power.



References
1. Mogrify subsidiary Chondrogenix secures funding from SBRI Healthcare to advance regenerative cartilage therapy to the clinic. Mogrify Ltd press release, 1st April, 2019. https://mogrify.co.uk/mogrify-subsidiary-chondrogenix-secures-funding-from-sbri-healthcare-to-advance-regenerative-cartilage-therapy-to-the-clinic/
2. Mogrify awarded $1.1M additional funding from SBRI Healthcare. Mogrify Ltd press release, 28th January, 2020. https://mogrify.co.uk/mogrify-awarded-1-1m-additional-funding-from-sbri-healthcare/
3. Mogrify enters research collaboration with the MRC Laboratory of Molecular Biology. Mogrify Ltd press release, 11th January, 2021. https://mogrify.co.uk/mogrify-enters-research-collaboration-with-the-mrc-laboratory-of-molecular-biology/
4. Mogrify solidifies IP position surrounding core technology and expands platform algorithm to enhance cell conversion. Mogrify Ltd press release, 17th December, 2020. https://mogrify.co.uk/mogrify-solidifies-ip-position-surrounding-core-technology-and-expands-platform-algorithm-to-enhance-cell-conversion/
5. Mogrify and Sangamo announce collaboration and exclusive license agreement for Mogrify’s iPSC- and ESC-derived regulatory T cells. Mogrify Ltd press release, 21st April, 2020. https://mogrify.co.uk/mogrify-and-sangamo-announce-collaboration-and-exclusive-license-agreement-for-mogrifys-ipsc-and-esc-derived-regulatory-t-cells/
6. Mogrify completes Series A financing totalling $33 million USD. Mogrify Ltd press release, 4th May, 2021. https://mogrify.co.uk/mogrify-completes-series-a-financing-totaling-33-million-usd/
7. Mogrify awarded $555,000 USD (£420,000 GBP) Innovate UK funding to accelerate regenerative cell therapies. Mogrify Ltd press release, 18th March, 2019. https://mogrify.co.uk/mogrify-awarded-555000-usd-420000-gbp-innovate-uk-funding-to-accelerate-regenerative-cell-therapies/
8. O.J.L. Rackham, J. Firas, and H. Fang, et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, March 2016, Vol. 48, No. 3.
9. U.S. Kamaraj, J. Chen, and K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 2020, 11, 509–522, November 18.
10. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 2006;126:663–676.
11. Meyer N, Penn LZ. Reflecting on 25 years with MYC. Nat Rev Cancer. 2008;8:976–990

Predictive bioinformatic platforms for direct cellular reprogramming- Mogrify Ltd (cont'd)

Predictive bioinformatic platforms for direct cellular reprogramming: Mogrify Ltd (cont’d)
My previous blog post presented a brief understanding of recent progress in direct cellular reprogramming and the reason for the development of two software platforms by Mogrify Ltd. This blog post is about further details of the two platforms, MOGRIFY and epiMOGRIFY.

About MOGRIFY
MOGRIFY was first co-developed by two scientists, Julian Gough (Professor of Computer Science in the University of Bristol) and Owen Rackham (PhD student of Julian Gough in the University of Bristol), in 2011. They began the development of the platform by using the data from the FANTOM 5 consortium, an international consortium launched to provide gene expression data in virtually all cell types across the human body.¹ In 2014, they collaborated with Jose Polo from Monash University in Australia to test cell conversions in order to validate the prediction power of MOGRIFY. In 2015, based on the prediction results from MOGRIFY, the co-founders filed a patent application for the algorithm used by the computation platform, with over 30 direct cell conversions listed as example proof of what the algorithm can achieve.² The predictions and cell conversion results were then published in 2016.³

According to the paper, predictions from MOGRIFY have been applied on 173 human cell types and 134 tissues. In order to assess the predictive power of MOGRIFY, the performance of the algorithm was first compared against well-known, previously-published human cell conversions. MOGRIFY correctly predicted the transcription factors (enzyme proteins that bind to a particular DNA sequence and regulate the expression of genes) used in previously-published direct cell conversions from human fibroblasts (the most common type of cell found in connective tissue) into induced pluripotent stem cells,^4,5,6 and from B cells/ fibroblasts into macrophage-like cells.^7,8 In addition, MOGRIFY’s prediction list included four of the five transcription factors (or similar factors) used in the conversion of human dermal fibroblasts into cardiomyocytes (cells responsible for generating contractile force in the intact heart).⁹

The predictive capabilities of MOGRIFY® were also experimentally examined using human cells. Two cell conversions, human fibroblasts to keratinocyte cells (cell within the epidermis) and adult human keratinocyte cells to micro-vascular endothelial cells (cells isolated from small vessels within skin tissue), were performed using prediction results from MOGRIFY. By examining the morphological and molecular characterization of the reprogrammed cells, the conversions were found to be successful.³

The results showed that MOGRIFY provides a practical and efficient mechanism to facilitate the reprogramming of human cells.

However, since the publication of the results in 2016, no further reports of cell conversions using predictions from MOGRIFY, have been published, or at least I was not able to find any after extensive searches.

About EpiMOGRIFY
Once the cells are converted from other cell types, it is important to maintain the reprogrammed cells’ identity, as the converted cells tend to revert back to what they were before. Difficulty maintaining the differentiated cells makes a large-scale production of these differentiated cells hard to achieve. This can be a hurdle for the development of cell therapies.

EpiMOGRIFY was developed with the aim of identifying optimal culture conditions (with suggested small molecules and chemical compounds) required to maintain cell identity or induce cell conversion in chemically-defined media. The computation algorithm incorporated gene-regulatory information data and cell epigenetic landscapes for more than 100 human cells and tissues, from the ENCODE and Epigenome Roadmap consortia, to define culture conditions that can maintain the phenotype and function of the converted cell, or that can be used to induce cell conversion.¹⁰

The EpiMOGRIFY platform was co-developed by Duke-NUS Medical School (Professors Enrico Pettreto and Owen Rackham), Monash University (Professor Jose Polo) and Mogrify Ltd. Owen Rackham and Jose Polo were the co-developers of MOGRIFY.¹¹

Experiments validating the computational prediction in cell culture conditions for cell maintenance and differentiation have recently been published.¹² Using the suggestion factors predicted from EpiMOGRIFY, astrocytes (cells commonly found in the brain) and cardiomyocytes (cells that make up heart muscle) were able to grow as effectively, in terms of cell numbers and proliferation rate, as they are in the culture conditions that have long been used. Moreover, these cells appeared to better maintain their morphology, in terms of the biological structure and the presence of key markers for the cell types, when growing in the culture conditions with biological factors suggested from EpiMOGRIFY. These results provide a fundamental proof for EpiMOGRIFY’s predictive power to suggest culture conditions that are able to maintain a stable phenotype.¹²

Furthermore, using the cell conversion conditions predicted from EpiMOGRIFY, neural progenitors and embryonic stem cells were able to differentiate to astrocyte cells and cardiomyocyte cells, respectively. The differentiation efficiency was as good as that of existing differentiation protocols.¹² These results indicate that EpiMOGRIFY is highly accurate in identifying biological factors for cell conversion as well.

To be continued.

References
1. Our history. Mogrify Ltd website. https://mogrify.co.uk/about-us/
2. https://patents.google.com/patent/WO2017106932A1/en
3. O.J.L. Rackham, J. Firas, and H. Fang, et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, March 2016, Vol. 48, No. 3.
4. K. Takahashi, K. Tanabe, M. Ohnuki, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell, 2007, 131, 861–872.
5. J. Yu, M.A. Vodyanik, K. Smuga-Otto. et al. Induced pluripotent stem cell lines derived from human somatic cells. Science, 2007, 318, 1917–1920. 6. D. Huangfu, K. Osafune, R. Maehr, et al. Induction of pluripotent stem cells from primary human fibroblasts with only Oct4 and Sox2. Nat. Biotechnol., 2008, 26, 1269–1275.
7. H. Xie, M. Ye, R. Feng, & T. Graf. Stepwise reprogramming of B cells into macrophages. Cell, 2004, 117, 663–676.
8. F. Rapino, E.F. Robles, J.A. Richter-Larrea, et al. C/EBPα induces highly efficient macrophage transdifferentiation of B lymphoma and leukemia cell lines and impairs their tumorigenicity. Cell Reports, 2013, 3, 1153–1163.
9. J. D. Fu, N.R. Stone, L. Liu, et al. Direct reprogramming of human fibroblasts toward a cardiomyocyte-like state. Stem Cell Reports, 2013, 1, 235–247.
10. epiMOGRIFY PLATFORM. Systematically identify the epigenetically-predicted factors required to drive and maintain cell identity. Mogrify website. https://mogrify.co.uk/science/epimogrify/
11. Our history. Mogrify Ltd website. https://mogrify.co.uk/about-us/
12. U.S. Kamaraj, J. Chen, K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 11, 509–522, November 18, 2020.

Predictive bioinformatic platforms for direct cellular reprogramming- Mogrify Ltd

Predictive bioinformatic platforms for direct cellular reprogramming: Mogrify Ltd
Have you ever imagined one day we could have our liver, kidney or heart regenerated from our own skin cells, to replace our failed or damaged organs, without the need to wait for transplants from a suitable donor? Research studies in cellular reprogramming, targeting this prospect, have become a hot topic in recent decades. A new bioinformatic start-up, Mogrify Ltd, aiming to transform the development of cell therapies and to develop scalable off-the-shelf cell therapies, seems worth our attention.

Mogrify Ltd is situated in the Bio-Innovation Centre in Cambridge Science Park in the UK. According to the press release of the company on this March, the company has a headcount of over 60 scientific, operational, and commercial staff.¹ The main technology products of the company are two computation prediction platforms, MOGRIFY and EpiMOGRIFY, which are useful to facilitate the development of cell therapies.^2,3 The company was incorporated in 2016 and was launched in February 2019. However, the development of its first computational prediction platform, MOGRIFY version 1, was started in 8 years previously in 2011. The second platform, EpiMOGRIFY, was launched in 2020.⁴ Both platforms were validated and the results were published in peer reviewed journals.^5,6

Why did Mogrify Ltd develop the two computational prediction platforms? Why are the two platforms developed by Mogrify Ltd useful tools to facilitate the development of cell therapies? Let us briefly explore the development of direct cellular reprogramming, an important area in regenerative medicine.

Background of direct cellular reprogramming
As early as 1958, an experimental finding suggested that terminally-differentiated cells have a certain degree of plasticity and can be reprogrammed to alter cell fate.⁷ Nearly 30 years later, a single transcription factor (an enzyme protein that binds to a particular DNA sequence and regulates the expression of genes), MyoD, was shown to convert fibroblasts (the most common type of cell found in connective tissue) directly to myoblasts (embryonic progenitor cells that differentiate to form muscle cells).⁸ However, later findings suggested that a single factor is not sufficient to drive cellular reprogramming for most tissues. Since then, different combinations of key transcription factors and microRNAs, which are developmental regulators of the target cell lineage, have been identified to convert fibroblasts to various cell types with therapeutic purposes.^9,10,11

Traditionally, “minus-one” strategy is used to identify the combination of key transcription factors and microRNAs to convert mature cells to another mature cell type. In brief, scientists start with combinatorial screening using a pool of transcription factors and microRNAs, which are chosen according to the domain knowledge of the scientist on the biological networks controlling cell differentiation, to convert one cell type to another differentiated (mature, fully functional) cell type. Once the pool of the biological factors are experimentally proved to be efficient for the cell conversion, then a “minus-one” strategy is used to identify essential factors by removing one factor at a time from the pool, aiming at minimal combination required for cell conversion.

However, this method can be very time-consuming. Take for example an experiment which converted dermal or cardiac fibroblasts to induced cardiomyocyte (heart cells for contraction)-like cells: it was originally started with a pool of nearly 20 transcription factors and a similar number of miRNAs. “Minus-one” strategy was used to finally identify 3 key transcription factors for the cell conversion. You can imagine that it was a long, exhaustive task of trial and error.¹⁰ Moreover, the mechanism for direct reprogramming is cell type specific and still largely unknown for many cell types.

In addition, most of the converted cells cannot stay where they are after adding key biological factors for conversion. They either end up converted back to what they were, or rapidly exit the cell cycle and don’t proliferate. This is because cell fate is actually controlled by the epigenetic state, the regulation mechanism that happens on the DNA level, of each cell. Only the change in DNA level can bring permanent change in the fate of cells. Chemicals, microRNAs, and transcription factors with appropriate culture conditions which change the epigenetic state of cells could permanently change the cell fate. The addition of transcription factors and micro RNA which do not affect the change in DNA level can bring only a temporary conversion of the cells.

In general, traditional direct cell conversion method is not time efficient, and it is hard to produce stable, scalable converted cells for clinical applications. This presents a big challenge to the cell therapies which rely on converted cells using traditional direct cell conversion methods.

The two predictive computational platforms, MOGRIFY and epiMOGRIFY, were developed by Mogrify Ltd. to address the problems mentioned above. MOGRIFY® predicts transcription factors which promote any cell conversion from any source cell types.² EpiMOGRIFY identifies culture conditions with optimal combinations of transcription factors or growth factors required to maintain cell identity and epigenetically support the reprogramming of cells in chemically-defined media. These two platforms could help speed up the direct cell conversion process, and help to develop stable and scalable resulting cells that can meet clinical needs.

Data sources such as FANTOM5 and ENCODE, which were being incorporated to develop MOGRIFY® and epiMOGRIFY, have emerged thanks to the advances in developmental biology research and discovery, over the last two decades, of gene networks that drive cell fate.

To be continued.


References
1. Mogrify wins Hewitsons Award for Innovation in Business and Price Bailey Award for Business of the Year at CambridgeshireLive Business Excellence Awards 2020. Mogrify press release, 26 March, 2021. https://mogrify.co.uk/mogrify-wins-hewitsons-award-for-innovation-in-business-and-price-bailey-award-for-business-of-the-year-at-cambridgeshirelive-business-excellence-awards-2020/
2. MOGRIFY® PLATFORM. Systematically predict the transcriptomic switches required to produce any target cell type from any source cell type. Mogrify website. https://mogrify.co.uk/science/mogrify/
3. EpiMOGRIFY PLATFORM. Systematically identify the epigenetically-predicted factors required to drive and maintain cell identity. Mogrify website. https://mogrify.co.uk/science/epimogrify/
4. Our history. Mogrify Ltd website. https://mogrify.co.uk/about-us/
5. O.J.L. Rackham, J. Firas, and H. Fang, et al. A predictive computational framework for direct reprogramming between human cell types. Nature Genetics, March 2016, Vol. 48, No. 3.
6. U.S. Kamaraj, J. Chen, K. Katwadi, et al. EpiMogrify models H3K4me3 data to identify signaling molecules that improve cell fate control and maintenance. Cell Systems, 11, 509–522, November 18, 2020.
7. J.B. Gurdon, T.R. Elsdale, and M. Fischberg. Sexually mature individuals of Xenopus laevis from the transplantation of single somatic nuclei. Nature, 1958, 182, 64–65.
8. R.L. Davis, H. Weintraub, and A.B. Lassar. Expression of a single transfected cDNA converts fibroblasts to myoblasts. Cell, 1987, 51, 987–1000.
9. K. Batta, M. Florkowska, and V. Kouskoff, et al. Direct reprogramming of murine fibroblasts to hematopoietic progenitor cells. Cell Rep., 2014, 9:1871–1884.
10. M., Ieda, J.D. Fu, and P. Delgado-Olguin, et al. Direct reprogramming of fibroblasts into functional cardiomyocytes by defined factors. Cell, 2010, 142:375–386.
11. T. Vierbuchen, A. Ostermeier, and Z.P. Pang, et al. Direct conversion of fibroblasts to functional neurons by defined factors. Nature, 2010, 463:1035–1041.

A story of false data

A story of false data
In fiction, cancer research is about trying to find a cure for cancer. A single cure, that fixes everybody's cancer. While this certainly makes for good stories, and would indeed be wonderful if anyone ever managed to come up with it, most real-life cancer researchers settle for a lesser goal that is still an achievement: find drugs that will slow down (or, in some cases, remove) a particular type of cancer in a particular type of person. For example, they might come up with research that only works on nose cancer in Asians, and then only works some of the time. Nevertheless this can still add years of life to some people and is therefore worth checking.

In 2013-2014 I was involved in therapeutic aspects of cancer research, in further investigation of the interplay between the PRDM1 gene and the NF-κB protein that leads to different susceptibility rates of NK/T cell lymphoma (NKTCL) cancer patients towards chemotherapeutic agents. The research team of my supervisor had a leading study using a 26S proteasome inhibitor drug, bortezomib (Velcade), to act against NK/T cell lymphoma.¹ With the assumption that IL2 is an important factor in sustaining NK/T cell lymphoma, we investigated the combination treatment that can reduce bortezomib dosage by using either of the two fusion anti-IL2 receptor antibodies, basiliximab (Simulect®) and denileukin diftitox (ONTAK®). We found that IC50 (median inhibitory concentration) of NKTCL cells being treated by bortezomib can be decreased by ~53% to ~90% when combined with a low level of basiliximab. This was a promising result, but it still needed testing "in vivo" (in a live setting). As the lab I was in did not have enough live sample (and my supervisor was retiring and the grants were running out), we came up the idea of asking another lab (one in mainland China with whom we had long been in collaboration) to run the live tests for us.

I visited China, trained the people there to perform a couple of in vivo tests, and finished the job. Several months later I married and moved to the UK, and the lab in China kept informing us about the progress of their study by sending us results in pictures. Those results were coherent with the in vitro test results we had previously found in our lab. Maybe we really did have a new, more effective chemotherapy drug on our hands for people with that particular cancer type? I had to fly back to Hong Kong and check things out (we tried working remotely but the lab really wanted me there). Things seemed to be playing out like a film script, aeroplanes and all.

But sadly, our further analysis showed that the data from the China lab was very likely to be fake. I found two pictures sent at two different times, supposedly representing different samples, were actually identical. By reflecting and rotating one of the pictures later sent to me, I could not see any difference with the one that had been sent earlier. We decided not to publish it after all.

So, does our combination work? It has not been disproven. But science does not work on not disproving things, it works on positive proof. It might still be possible for other labs to re-check our combination, and we hope they will do so from our partial publications, but we were not able to show it ourselves. And we ended up being a little annoyed with that lab for faking their data (perhaps because they couldn't be bothered to run the real tests?) and causing all that excitement for nothing. But these things happen.

The quest to improve the lives of people with cancer continues, one small uncertain arduous step at a time.



References
1. L. Shen, W.Y. Au, T. Guo, et al. Proteasome inhibitor bortezomib-induced apoptosis in natural killer (NK)-cell leukemia and lymphoma: an in vitro and in vivo preclinical evaluation. Blood, 2007 Jul 1;110(1):469-70.