MANIFEST: Multiomic platform for cancer immunotherapy

Kok Haw Jonathan Lim; Zayd Tippu; Pippa G Corrie; Michael Hubank; James Larkin; Trevor D Lawley; Mark Stares; Grant D Stewart; Amy Strange; Stefan N Symeonides; Bernadett Szabados; Nicholas C Turner; Tom Waddell; Santiago Zelenay; Manuel Salto-Tellez; Caroline Dive; Samra Turajlic; MANIFEST consortium

doi:10.1158/2159-8290.CD-25-0099

MANIFEST: Multiomic platform for cancer immunotherapy

Kok Haw Jonathan Lim
, Zayd Tippu
, Pippa G Corrie
, Michael Hubank
, James Larkin
, Trevor D Lawley
, Mark Stares
, Grant D Stewart
, Amy Strange
, Stefan N Symeonides
, Bernadett Szabados
, Nicholas C Turner
, Tom Waddell
, Santiago Zelenay
, Manuel Salto-Tellez
, Caroline Dive
, Samra Turajlic^*
, MANIFEST consortium

^*Corresponding author for this work

Francis Crick Institute
Cambridge University Hospitals NHS Foundation Trust
The Royal Marsden NHS Foundation Trust
The Royal Marsden Nhs Foundation Trust (Applicatio
Wellcome Trust Sanger Institute
Edinburgh Cancer Research Centre
University of Cambridge
Queen Mary University of London
The Institute of Cancer Research (University of London)
The Christie Hospital NHS Foundation Trust

Research output: Contribution to journal › Editorial › peer-review

249 Downloads (Pure)

Abstract

Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

Original language	English
Pages (from-to)	878-883
Number of pages	6
Journal	Cancer discovery
Volume	15
Issue number	5
DOIs	https://doi.org/10.1158/2159-8290.CD-25-0099
Publication status	Published - 2 May 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Highlights, Institutes and Platforms

Lydia Becker Institute

Access to Document

10.1158/2159-8290.CD-25-0099

CD-25-0099R1_Merged_PDFAccepted author manuscript, 1.73 MBLicence: CC BY

Cite this

Lim, K. H. J., Tippu, Z., Corrie, P. G., Hubank, M., Larkin, J., Lawley, T. D., Stares, M., Stewart, G. D., Strange, A., Symeonides, S. N., Szabados, B., Turner, N. C., Waddell, T., Zelenay, S., Salto-Tellez, M., Dive, C., Turajlic, S., & MANIFEST consortium (2025). MANIFEST: Multiomic platform for cancer immunotherapy. Cancer discovery, 15(5), 878-883. https://doi.org/10.1158/2159-8290.CD-25-0099

@article{418e78c0221645c08ef45ea54f842cc4,

title = "MANIFEST: Multiomic platform for cancer immunotherapy",

abstract = "Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.",

author = "Lim, \{Kok Haw Jonathan\} and Zayd Tippu and Corrie, \{Pippa G\} and Michael Hubank and James Larkin and Lawley, \{Trevor D\} and Mark Stares and Stewart, \{Grant D\} and Amy Strange and Symeonides, \{Stefan N\} and Bernadett Szabados and Turner, \{Nicholas C\} and Tom Waddell and Santiago Zelenay and Manuel Salto-Tellez and Caroline Dive and Samra Turajlic and \{MANIFEST consortium\}",

note = "{\textcopyright}2025 American Association for Cancer Research.",

year = "2025",

month = may,

day = "2",

doi = "10.1158/2159-8290.CD-25-0099",

language = "English",

volume = "15",

pages = "878--883",

journal = "Cancer discovery",

issn = "2159-8274",

publisher = "American Association for Cancer Research",

number = "5",

}

Lim, KHJ, Tippu, Z, Corrie, PG, Hubank, M, Larkin, J, Lawley, TD, Stares, M, Stewart, GD, Strange, A, Symeonides, SN, Szabados, B, Turner, NC, Waddell, T, Zelenay, S, Salto-Tellez, M, Dive, C, Turajlic, S & MANIFEST consortium 2025, 'MANIFEST: Multiomic platform for cancer immunotherapy', Cancer discovery, vol. 15, no. 5, pp. 878-883. https://doi.org/10.1158/2159-8290.CD-25-0099

TY - JOUR

T1 - MANIFEST

T2 - Multiomic platform for cancer immunotherapy

AU - Lim, Kok Haw Jonathan

AU - Tippu, Zayd

AU - Corrie, Pippa G

AU - Hubank, Michael

AU - Larkin, James

AU - Lawley, Trevor D

AU - Stares, Mark

AU - Stewart, Grant D

AU - Strange, Amy

AU - Symeonides, Stefan N

AU - Szabados, Bernadett

AU - Turner, Nicholas C

AU - Waddell, Tom

AU - Zelenay, Santiago

AU - Salto-Tellez, Manuel

AU - Dive, Caroline

AU - Turajlic, Samra

AU - MANIFEST consortium

PY - 2025/5/2

Y1 - 2025/5/2

N2 - Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

AB - Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

U2 - 10.1158/2159-8290.CD-25-0099

DO - 10.1158/2159-8290.CD-25-0099

M3 - Editorial

C2 - 40313120

SN - 2159-8274

VL - 15

SP - 878

EP - 883

JO - Cancer discovery

JF - Cancer discovery

IS - 5

ER -

MANIFEST: Multiomic platform for cancer immunotherapy

Abstract

UN SDGs

Research Highlights, Institutes and Platforms

Access to Document

Other files and links

Fingerprint

Cite this