Methylome profiling for melanoma detection

Skin Cancer & Regenerative Dermatology

Preventing skin cancer and healing scars.

Spatial transcriptomics of Basal Cell Carcinoma

Understanding Skin Cancer

Mapping the tumour microenvironment to stop cancer before it starts.

3D Fibroblast Spheroid Model for regenerative studies

Non-invasive Skin Cancer Detection

Combining AI and advanced imaging to detect skin cancer without a biopsy.

AI analysis of Optical Coherence Tomography scans

Minimising scars

Harnessing fibroblast subpopulations to improve scarring and restore skin function.

Senescence mapping in human skin

Preventing Skin Cancer

Using 3-dimensional cell culture models to test new treatments that prevent skin cancer.

About the Lab

The Lynch Lab is based in St John's Institute of Dermatology at King's College London, on the Guy's Campus. We are motivated by two of the key challenges in dermatological surgery: preventing skin cancer and minimising scarring. To understand how fibroblasts and keratinocytes interact, we combine single-cell genomics, spatial transcriptomics, non-invasive skin imaging, AI and 3-dimensional organotypic cell culture models.

Our Research

Our approach is translational: clinical problem → mechanistic insight → therapeutic strategy → IP → clinical trial or industry partnership.

Fluorescence image of 3D spheroid culture models of keratinocytes and fibroblasts, stained for POSTN and KRT17
3D spheroid culture models of keratinocytes and fibroblasts, stained for POSTN and KRT17.
Pillar 1

Skin cancer prevention and early detection

Skin cancer is the most common cancer in humans, and many patients face a lifelong cycle of new tumours. We ask:

  • Why do some mutant keratinocyte clones become dangerous?
  • Which fibroblast subtypes promote tumour progression?
  • Can we reprogramme the tumour microenvironment to reduce cancer risk?
  • How can we diagnose skin cancer early without cutting the skin?
  • Targets for preventing keratinocyte carcinomas3D culture models with single-cell and spatial datasets to find druggable pathways that reduce basal and squamous cell carcinoma.
  • Laser approaches to preventionCan fractional and vascular lasers reduce the incidence of basal cell and squamous cell carcinoma?
Publications (6)
  1. Choong RKJ, Brennan S, Gabriel J, Han WH, Yong SS, Kwan Z, Chew MF, Calonje J, Lynch MD, Barlow R. Basal cell carcinoma in skin of colour: a distinctive phenotype is emerging from studies in Asian patients. British Journal of Dermatology, 2026 (Accepted).
  2. Ganier C, Mazin P, Herrera-Oropeza G, Du-Harpur X, Blakeley M, Gabriel J, Predeus AV, Cakir B, Prete M, Harun N, Darrigrand JF, Haiser A, Wyles S, Shaw T, Teichmann SA, Haniffa M, Watt FM, Lynch MD. Multiscale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma. Proc Natl Acad Sci, 2024. PubMed 38165934
  3. Hughes S, Srenathan H, Lynch MD (Joint senior author), Leeman H. Multi-center experience from tertiary skin cancer units on the role of Sentinel Lymph Node Biopsy in patients with pT1b melanoma. Clin Exp Dermatol, 2024. PubMed 38112606
  4. Banila C, Green D, Katsanos D, Viana J, Osmaston A, Vasquez AM, Lynch MD, Kaveh S. A non-invasive method for whole-genome skin methylome profiling. British Journal of Dermatology, 2023. PubMed 37658851
  5. Wan B, Ganier C, Du-Harpur X, Harun N, Watt F, Patalay R, Lynch MD. Applications and future directions for Optical Coherence Tomography in Dermatology. British Journal of Dermatology, 2021. PubMed 32974943
  6. Lynch MD, Lynch CNS, Craythorne E, Liakath-Ali K, Mallipeddi R, Barker JN and Watt FM. Spatial constraints govern competition of mutant clones in human epidermis. Nature Communications, 2017. PubMed 29066762
Fibroblast spheroids stained for fibroblast subpopulation markers POSTN, APOD, SFRP2 and PTGDS, with DAPI
Fibroblast spheroids stained for subpopulation markers (POSTN, APOD, SFRP2, PTGDS) with DAPI.
Pillar 2

Regenerative dermatology and scarring

Scars follow trauma, surgery and inflammation such as acne. We want to understand how skin heals, and how to make it heal better:

  • What makes some wounds scar more severely than others?
  • How do fibroblast subpopulations contribute to fibrosis?
  • Why do some scars become hypertrophic or keloid?
  • Can cell-based or molecular therapies reduce scarring?
  • Fibroblast-based therapies (Fibrodyne)Building on our discovery of human fibroblast subpopulations to develop cell-based therapies for scars.
Publications (8)
  1. Du-Harpur X, Ganier C, Mazin P, Cheshire C, Gabriel J, Rashidghamat E, Luscombe NM, Lynch MD, Watt FM. Pathogenic Keratinocyte States and Fibroblast Niches Define the Tissue Microenvironment in Severe Hidradenitis Suppurativa. Journal of Investigative Dermatology, 2026 (Accepted). DOI: 10.1101/2025.11.11.682326
  2. Lynch MD, Wyles S. Regenerative Medicine: On the Vanguard of Dermatology. Dermatologic Surgery, 2024. PubMed 39480033
  3. Wyles S, Lynch MD. Introduction to special issue on Regenerative Medicine. Dermatologic Surgery, 2024. PubMed 39480032
  4. Ziebart R, Antezana L, Crum O, Lynch MD, Wyles S. Laser and Energy Treatments for Acne Scarring: A Review of Clinical Trials. Journal of Drugs and Dermatology, 2024. PubMed 39630683
  5. Ganier C, Rognoni E, Goss G, Lynch MD, Watt FM. Fibroblast heterogeneity in healthy and wounded skin. Cold Spring Harbour Perspectives in Biology, 2022. PubMed 35667795
  6. Philippeos C, Telerman S, Oules B, Pisco A, Shaw T, Elgueta R, Lombardi G, Driskell R, Soldin M, Lynch MD and Watt F. Spatial and single-cell transcriptional profiling identifies functionally distinct human dermal fibroblast subpopulations. Journal of Investigative Dermatology, 2018. PubMed 29391249
  7. Lynch MD, Watt FM. Fibroblast heterogeneity: Implications for human disease. Journal of Clinical Investigation, 2018. PubMed 29293096
  8. Lynch MD, Bashir S. Applications of Platelet-Rich-Plasma in Dermatology: A Critical Appraisal of the Literature. J Dermatol Treatment, 2016. PubMed 26466811
Grid of nine dermoscopic images of skin lesions, including melanomas, basal cell carcinomas, a squamous cell carcinoma, an actinic keratosis, naevi and a seborrhoeic keratosis
Dermoscopic images of biopsy-confirmed skin lesions used to test our models. Images: MILK10k, MILK study team, CC BY-NC.
Pillar 3

AI and computational models

We use AI to diagnose skin cancer and inflammatory skin conditions from clinical images and from non-invasive microscopy, such as dermoscopy and optical coherence tomography. We ask:

  • How accurate are AI models on the lesions that really worry clinicians, not just on curated test sets?
  • Where do they fail, and can they tell when they are unsure?
  • How do general-purpose large language models compare with models built for dermatology?
  • AI and optical coherence tomographyMachine learning on OCT images to tell BCC and cSCC from benign lesions without a biopsy.
  • Skin lesion classifier in the browserA fine-tuned Inception v3 that runs on the user's own device. Try it.
  • Frontier LLMs against a specialised modelGPT-6 Astra and Claude Fable 5.1 against a 10-year-old CNN on 200 biopsied lesions. Read the article.
Publications (8)
  1. Lynch MD. Beyond the algorithm: Ethical Challenges in AI-Driven Skin Cancer Diagnosis. British Journal of Dermatology, 2025. PubMed 39680502
  2. Sood A, Mansoor N, Memmi C, Lynch MD, Lynch JO. Generative Pretrained Transformer-4, an artificial intelligence text predictive model, has a high capability for passing novel written radiology exam questions. International Journal of Computer Assisted Radiology and Surgery, 2024. PubMed 38381363
  3. Shetty M, Ettlinger M, Lynch MD. GPT-4, an artificial intelligence large language model, exhibits high levels of accuracy on dermatology specialty certificate exam questions. medrxiv, 2023. Preprint
  4. Choy SP, Kim BJ, Paolino A, Tan WR, Lim S, Seo J, Tan SP, Francis L, Tsakok T, Simpson M, Barker J, Lynch MD, Corbett M, Smith C, Mahil S. Systematic review of deep learning image analyses for the diagnosis and monitoring of skin disease. npj Digital Medicine, 2023. PubMed 37758829
  5. Cunningham L, Ganier C, Ferguson F, White IR, Watt FM, McFadden J, Lynch MD. Gradient boosting approaches can outperform logistic regression for risk prediction in cutaneous allergy. Contact Dermatitis, 2022. PubMed 34812539
  6. Wan B, Ganier C, Du-Harpur X, Harun N, Watt F, Patalay R, Lynch MD. Applications and future directions for Optical Coherence Tomography in Dermatology. British Journal of Dermatology, 2021. PubMed 32974943
  7. Du-Harpur X, Arthurs C, Ganier C, Woolf RT, Laftah Z, Lakhan MK, Salam A, Wan B, Watt FM, Luscombe NM, Lynch MD. Clinically-relevant vulnerabilities of deep machine learning systems for skin cancer diagnosis. Journal of Investigative Dermatology, 2021. PubMed 32931808
  8. Du-Harpur X, Watt FM, Luscombe N, Lynch MD. What is AI? Applications of artificial intelligence to dermatology. British Journal of Dermatology, 2020. PubMed 31960407

Tools and Demos

Research software and write-ups you can try for yourself.

Commercial Partnerships & Translation

We translate our research from bench to bedside through commercial collaborations and spin-out companies.

Fibrodyne

Dr Lynch is a co-inventor on two patents covering the sorting and therapeutic use of human dermal fibroblast subpopulations. They form the core IP of Fibrodyne, a King's College London spin-out co-founded with Professor Fiona Watt, which secured £2M in seed investment to develop cell-based therapies for scars.

Epistat Therapeutics

Epistat Therapeutics is a King's College London spinout, founded on the lab's skin cancer prevention research, developing the first preventive medicines for squamous and basal cell skin cancer for high-risk patients.

Our Team

Dr Magnus Lynch
Principal Investigator

Dr Magnus Lynch MA DPhil MRCS FRCP

Honorary Reader, King’s College London - Consultant Dermatologist & Dermatological Surgeon, St John’s Institute of Dermatology

Dr Lynch is an Honorary Reader at King’s College London and a fellowship-trained Mohs surgeon and clinician-scientist whose work spans skin cancer prevention, non-invasive diagnostics, fibroblast biology, and regenerative dermatology.

Current Lab Members

Jeyrroy Gabriel
PhD Student

Jeyrroy Gabriel

Project: Jeyrroy uses fibroblast–keratinocyte spheroid co-cultures and spatial transcriptomics to identify pathways that drive tumour-associated phenotypes in BCC and cSCC, aiming to develop risk-reducing therapies.

Luis Escalante
Visiting Researcher

Luis Escalante

Luis is interested in understanding pathways that prevent the development of cutaneous squamous cell carcinoma (cSCC) and is currently applying for funding to pursue a research fellowship.

Previous Lab Members

Clarisse Ganier
Clarisse Ganier
Postdoctoral Researcher
Dr Bo Wan
Dr Bo Wan
PhD Student (completed 2024)
Nasrat Harun
Nasrat Harun
Research Assistant

Featured Publications

Selected highlights from the lab's work, with the full list below.

  1. Multiscale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma.
    Ganier C, Mazin P, Herrera-Oropeza G, Du-Harpur X, Blakeley M, Gabriel J, Predeus AV, Cakir B, Prete M, Harun N, Darrigrand JF, Haiser A, Wyles S, Shaw T, Teichmann SA, Haniffa M, Watt FM, Lynch MD. PNAS, 2024. PubMed 38165934

    A senior-author paper giving a multiscale spatial atlas of healthy skin and the basal cell carcinoma microenvironment, which directly informs the lab's cancer prevention work.

  2. Developmental cell programs are co-opted in inflammatory skin disease.
    Reynolds G, Vegh P, Fletcher J, … Lynch MD, … Teichmann S, Watt F, Haniffa M. Science, 2021. PubMed 33479125

    Part of the Human Cell Atlas: the cell types of healthy skin, eczema and psoriasis, a foundation for our work across anatomical sites and in skin cancer.

  3. Clinically-relevant vulnerabilities of deep machine learning systems for skin cancer diagnosis.
    Du-Harpur X, Arthurs C, Ganier C, Woolf RT, Laftah Z, Lakhan MK, Salam A, Wan B, Watt FM, Luscombe NM, Lynch MD. Journal of Investigative Dermatology, 2021. PubMed 32931808

    The first study to show that simple changes in colour balance and rotation can dramatically change the accuracy of deep learning models for skin cancer diagnosis.

  4. Spatial and single-cell transcriptional profiling identifies functionally distinct human dermal fibroblast subpopulations.
    Philippeos C, Telerman S, Oulès B, Pisco A, Shaw T, Elgueta R, Lombardi G, Driskell R, Soldin M, Lynch MD and Watt FM (joint senior author). Journal of Investigative Dermatology, 2018. PubMed 29391249

    A detailed census of fibroblast heterogeneity in human skin, identifying functionally distinct subpopulations.

  5. Spatial constraints govern competition of mutant clones in human epidermis.
    Lynch MD, Lynch CNS, Craythorne E, Liakath-Ali K, Mallipeddi R, Barker JN and Watt FM. Nature Communications, 2017. PubMed 29066762

    Sun-exposed, non-cancerous skin carries a high burden of expanded mutant clones, and spatial constraints govern how they compete.

View Full Publication List
  1. Choong RKJ, Brennan S, Gabriel J, Han WH, Yong SS, Kwan Z, Chew MF, Calonje J, Lynch MD, Barlow R. Basal cell carcinoma in skin of colour: a distinctive phenotype is emerging from studies in Asian patients. British Journal of Dermatology, 2026 (Accepted).
  2. Zakaria N, Griffiths A, Ganier C, Lynch MD, Messenger D, Bhogal R, Maret W. Age-related redistribution of zinc and copper within human skin. Journal of Trace Elements in Medicine and Biology, 2026. PubMed 41650808
  3. Du-Harpur X, Ganier C, Mazin P, Cheshire C, Gabriel J, Rashidghamat E, Luscombe NM, Lynch MD, Watt FM. Pathogenic Keratinocyte States and Fibroblast Niches Define the Tissue Microenvironment in Severe Hidradenitis Suppurativa. Journal of Investigative Dermatology, 2026 (Accepted). DOI: 10.1101/2025.11.11.682326
  4. Wyles SP, Yu GT, Ganier C, Tchkonia T, Lynch MD, Kuchel GA, Kirkland JL. SenSkin: a human skin-specific cellular senescence gene set. Geroscience, 2025. PubMed 39998731
  5. Kravvas G, Xie B, Ganier C, van den Munckhof H, van den Munckhof E, de Koning M, Gulin SJ, Freeman A, Haider A, Alnajjar H, Muneer A, Lynch MD, Millar M, Ahmed A, Bunker CB. A Direct Comparative Analysis of HPV DNA with Single-Molecule RNA and p16(INK4a) Protein Expression in Lichen Sclerosus: Implications for Diagnostics and Pathogenesis. JID Innovations, 2025. PubMed 40330849
  6. Lakhan M, Lynch MD. Skin pigmentation. Medicine, 2025. DOI: 10.1016/j.mpmed.2025.05.002
  7. Lynch MD. Beyond the algorithm: Ethical Challenges in AI-Driven Skin Cancer Diagnosis. British Journal of Dermatology, 2025. PubMed 39680502
  8. Yu GT, Ganier C, Allison DB, Tchkonia T, Khosla S, Kirkland JL, Lynch MD, Wyles S. Mapping epidermal and dermal cellular senescence in human skin aging. Aging Cell, 2025. PubMed 39370688
  9. Lynch MD, Wyles S. Regenerative Medicine: On the Vanguard of Dermatology. Dermatologic Surgery, 2024. PubMed 39480033
  10. Wyles S, Lynch MD. Introduction to special issue on Regenerative Medicine. Dermatologic Surgery, 2024. PubMed 39480032
  11. Ziebart R, Antezana L, Crum O, Lynch MD, Wyles S. Laser and Energy Treatments for Acne Scarring: A Review of Clinical Trials. Journal of Drugs and Dermatology, 2024. PubMed 39630683
  12. Sood A, Mansoor N, Memmi C, Lynch MD, Lynch JO. Generative Pretrained Transformer-4, an artificial intelligence text predictive model, has a high capability for passing novel written radiology exam questions. International Journal of Computer Assisted Radiology and Surgery, 2024. PubMed 38381363
  13. Ganier C, Mazin P, Herrera-Oropeza G, Du-Harpur X, Blakeley M, Gabriel J, Predeus AV, Cakir B, Prete M, Harun N, Darrigrand JF, Haiser A, Wyles S, Shaw T, Teichmann SA, Haniffa M, Watt FM, Lynch MD. Multiscale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma. Proc Natl Acad Sci, 2024. PubMed 38165934
  14. Hughes S, Srenathan H, Lynch MD (Joint senior author), Leeman H. Multi-center experience from tertiary skin cancer units on the role of Sentinel Lymph Node Biopsy in patients with pT1b melanoma. Clin Exp Dermatol, 2024. PubMed 38112606
  15. Shetty M, Ettlinger M, Lynch MD. GPT-4, an artificial intelligence large language model, exhibits high levels of accuracy on dermatology specialty certificate exam questions. medrxiv, 2023. Preprint
  16. Banila C, Green D, Katsanos D, Viana J, Osmaston A, Vasquez AM, Lynch MD, Kaveh S. A non-invasive method for whole-genome skin methylome profiling. British Journal of Dermatology, 2023. PubMed 37658851
  17. Choy SP, Kim BJ, Paolino A, Tan WR, Lim S, Seo J, Tan SP, Francis L, Tsakok T, Simpson M, Barker J, Lynch MD, Corbett M, Smith C, Mahil S. Systematic review of deep learning image analyses for the diagnosis and monitoring of skin disease. npj Digital Medicine, 2023. PubMed 37758829
  18. Ganier C, Rognoni E, Goss G, Lynch MD, Watt FM. Fibroblast heterogeneity in healthy and wounded skin. Cold Spring Harbour Perspectives in Biology, 2022. PubMed 35667795
  19. Kravvas G, Muneer A, Watchorn R, Castiglione F, Haider A, Freeman A, Hadway P, Alnajjar H, Lynch MD, Bunker C. Male genital lichen sclerosus, micro incontinence and occlusion: mapping the disease across the prepuce. Clinical and Experimental Dermatology, 2022. PubMed 35150005
  20. Cunningham L, Ganier C, Ferguson F, White IR, Watt FM, McFadden J, Lynch MD. Gradient boosting approaches can outperform logistic regression for risk prediction in cutaneous allergy. Contact Dermatitis, 2022. PubMed 34812539
  21. Ganier C, Harun N, Peplow I, Du-Harpur X, Arthurs C, Watt FM, Lynch MD. ACE2 expression is detectable in keratinocytes, cutaneous appendages and blood vessels by multiplex RNA in situ hybridization. Adv Skin Wound Care, 2022. PubMed 35085122
  22. Lakhan M, Lynch MD. Skin Pigmentation. Medicine, 2021. Preprint
  23. Reynolds G, Vegh P, Fletcher J,... Lynch MD,...Teichmann S, Watt F, Haniffa M. Developmental cell programs are co-opted in inflammatory skin disease. Science, 2021. PubMed 33479125
  24. Wan B, Ganier C, Du-Harpur X, Harun N, Watt F, Patalay R, Lynch MD. Applications and future directions for Optical Coherence Tomography in Dermatology. British Journal of Dermatology, 2021. PubMed 32974943
  25. Du-Harpur X, Arthurs C, Ganier C, Woolf RT, Laftah Z, Lakhan MK, Salam A, Wan B, Watt FM, Luscombe NM, Lynch MD. Clinically-relevant vulnerabilities of deep machine learning systems for skin cancer diagnosis. Journal of Investigative Dermatology, 2021. PubMed 32931808
  26. Du-Harpur X, Watt FM, Luscombe N, Lynch MD. What is AI? Applications of artificial intelligence to dermatology. British Journal of Dermatology, 2020. PubMed 31960407
  27. Teo Y, McFadden J, White I, Lynch MD and Banerjee P. Allergic Contact Dermatitis in Atopic Individuals: Results of a 30-year Retrospective Study. Contact Dermatitis, 2019. PubMed 31347185
  28. van de Lagemaat LN, Flenley M, Lynch MD, Garrick D, Tomlinson SR, Kranc KR, Vernimmen D. CpG binding protein (CFP1) occupies open chromatin regions of active genes, including enhancers and non-CpG islands. Epigenetics Chromatin, 2018. PubMed 30292235
  29. Philippeos C, Telerman S, Oules B, Pisco A, Shaw T, Elgueta R, Lombardi G, Driskell R, Soldin M, Lynch MD and Watt F. Spatial and single-cell transcriptional profiling identifies functionally distinct human dermal fibroblast subpopulations. Journal of Investigative Dermatology, 2018. PubMed 29391249
  30. Lynch MD, Watt FM. Fibroblast heterogeneity: Implications for human disease. Journal of Clinical Investigation, 2018. PubMed 29293096
  31. Lynch MD, Lynch CNS, Craythorne E, Liakath-Ali K, Mallipeddi R, Barker JN and Watt FM. Spatial constraints govern competition of mutant clones in human epidermis. Nature Communications, 2017. PubMed 29066762
  32. Lynch MD, McFadden JP, White JM, Banerjee P, White IR. Age-specific profiling of cutaneous allergy at high temporal resolution suggests age-related alterations in regulatory immune function. Journal of Allergy and Clinical Immunology, 2017. PubMed 28606588
  33. Lynch MD, White JM, McFadden JP, Wang Y, White IR, Banerjee P. A dynamic landscape of allergen associations in delayed-type cutaneous hypersensitivity. British Journal of Dermatology, 2017. PubMed 27285898
  34. Jeziorska DM, Murray RJS, De Gobbi M, Gaentzsch R, Garrick D, Ayyub H, Chen T, Li E, Telenius J, Lynch MD, Graham B, Smith AJH, Lund JN, Hughes JR, Higgs DR, Tufarelli C. DNA methylation of intragenic CpG islands depends on their transcriptional activity during differentiation and disease. Proc Natl Acad Sci, 2017. PubMed 28827334
  35. Alwan W, Lynch MD, McFadden J, White IR, Banerjee P. Patch testing in psoriasis patients: results of a 30-year retrospective cohort study. British Journal of Dermatology, 2018. PubMed 28617935
  36. Lynch MD, Ali F, Mallipeddi R. A pedunculated nasal nodule. British Medical Journal, 2017. PubMed 28254755
  37. Lynch MD, Bashir S. Applications of Platelet-Rich-Plasma in Dermatology: A Critical Appraisal of the Literature. J Dermatol Treatment, 2016. PubMed 26466811
  38. Lynch MD, Sears A, Cookson H, Lew T, Laftah Z, Orrin L, Zuckerman M, Creamer D, Higgins E. Disseminated Coxsackievirus A6 affecting children with atopic dermatitis. Clin Exp Dermatol, 2015. PubMed 25677678
  39. Lynch MD, Cliffe J, Morris-Jones R. Authors' reply to Cockayne and colleagues. BMJ, 2014. DOI: 10.1136/bmj.g4092
  40. Lynch MD, Cliffe J, Morris-Jones R. Management of cutaneous viral warts. BMJ, 2014. PubMed 24865780
  41. Hughes JR, Roberts N, McGowan S, Hay D, Giannoulatou E, Lynch MD, De Gobbi M, Taylor S, Gibbons R, Higgs DR. Analysis of hundreds of cis-regulatory landscapes at high resolution in a single, high-throughput experiment. Nat Genet, 2014. PubMed 24413732
  42. Lynch MD, Smith AJ, de Gobbi M, Flenley M, Hughes JR, Vernimmen D, Ayyub H, Sharpe JA, Sloane-Stanley JA, Sutherland L, Meek S, Burdon T, Gibbons RJ, Garrick D, Higgs DR. An interspecies analysis reveals a key role for unmethylated CpG dinucleotides in vertebrate Polycomb complex recruitment. EMBO Journal, 2012. PubMed 22056776
  43. Vernimmen D, Lynch MD, de Gobbi M, Garrick D, Sharpe JA, Sloane-Stanley JA, Smith AJ, Higgs DR. Polycomb Eviction as a New Distant Enhancer Function. Genes & Dev, 2011. PubMed 21828268
  44. Kowalczyk MS, Hughes JR, Garrick D, Lynch MD, Sharpe JA, Sloane-Stanley JA, McGowan SJ, De Gobbi M, Hosseini M, Vernimmen D, Brown JM, Gray NE, Collavin L, Gibbons RJ, Flint J, Taylor S, Buckle VJ, Milne TA, Wood WG, Higgs DR. Intragenic enhancers act as alternative promoters. Mol Cell, 2012. PubMed 22264824
  45. De Gobbi M, Garrick D, Lynch MD, Vernimmen D, Hughes JR, Goardon N, Luc S, Lower KM, Sloane-Stanley JA, Pina C, Soneji S, Renella R, Enver T, Taylor S, Jacobsen SEW, Vyas P, Gibbons RJ, Higgs DR. Generation of Bivalent Chromatin Domains During Cell Fate Decisions. Epigenetics and Chromatin, 2011. PubMed 21645363
  46. Garrick D, De Gobbi M, Lynch MD, Higgs DR. Switching genes on and off in haemopoiesis. Biochem Soc Trans, 2008. PubMed 18631127
  47. Lynch MD, Cariati M, Purushotham AD. Breast cancer, stem cells and prospects for therapy. Breast Cancer Res, 2006. PubMed 16834766
  48. Lynch MD, Jones AE, Marker A, Grant JW, Purushotham AD. Malignant eccrine poroma in breast cancer-related lymphoedema. Ann R Coll Surg Engl, 2004. PubMed 16749962
  49. Lynch MD. How does cellular senescence prevent cancer?. DNA Cell Biol, 2006. PubMed 16460230
  50. Lynch MD. The role of cellular senescence may be to prevent proliferation of neighboring cells within stem cell niches. Ann N Y Acad Sci, 2004. PubMed 15247012

Join Us

We welcome applications from PhD students, postdoctoral researchers, clinician-scientists, research assistants, computational biologists, and engineers.

We offer:

  • A collaborative, supportive and inclusive environment.
  • Opportunities to work on high-impact, clinically meaningful problems.
  • Access to world-class clinical and genomic facilities.
  • Projects that span fundamental biology to clinical translation.
View Current Projects

To enquire about positions, please send a CV and brief summary of your interests via the contact information below.