title: The potential of optical proteomic technologies to individualize prognosis and guide rational treatment for cancer patients.
abstract: Genomics and proteomics will improve outcome prediction in cancer and have great potential to help in the discovery of unknown mechanisms of metastasis, ripe for therapeutic exploitation. Current methods of prognosis estimation rely on clinical data, anatomical staging and histopathological features. It is hoped that translational genomic and proteomic research will discriminate more accurately than is possible at present between patients with a good prognosis and those who carry a high risk of recurrence. Rational treatments, targeted to the specific molecular pathways of an individual's high-risk tumor, are at the core of tailored therapy. The aim of targeted oncology is to select the right patient for the right drug at precisely the right point in their cancer journey. Optical proteomics uses advanced optical imaging technologies to quantify the activity states of and associations between signaling proteins by measuring energy transfer between fluorophores attached to specific proteins. Förster resonance energy transfer (FRET) and fluorescence lifetime imaging microscopy (FLIM) assays are suitable for use in cell line models of cancer, fresh human tissues and formalin-fixed paraffin-embedded tissue (FFPE). In animal models, dynamic deep tissue FLIM/FRET imaging of cancer cells in vivo is now also feasible. Analysis of protein expression and post-translational modifications such as phosphorylation and ubiquitination can be performed in cell lines and are remarkably efficiently in cancer tissue samples using tissue microarrays (TMAs). FRET assays can be performed to quantify protein-protein interactions within FFPE tissue, far beyond the spatial resolution conventionally associated with light or confocal laser microscopy. Multivariate optical parameters can be correlated with disease relapse for individual patients. FRET-FLIM assays allow rapid screening of target modifiers using high content drug screens. Specific protein-protein interactions conferring a poor prognosis identified by high content tissue screening will be perturbed with targeted therapeutics. Future targeted drugs will be identified using high content/throughput drug screens that are based on multivariate proteomic assays. Response to therapy at a molecular level can be monitored using these assays while the patient receives treatment: utilizing re-biopsy tumor tissue samples in the neoadjuvant setting or by examining surrogate tissues. These technologies will prove to be both prognostic of risk for individuals when applied to tumor tissue at first diagnosis and predictive of response to specifically selected targeted anticancer drugs. Advanced optical assays have great potential to be translated into real-life benefit for cancer patients.
authors.affiliation: Richard Dimbleby Department of Cancer Research, Randall Division & Division of Cancer Studies, Kings College London, 2nd Floor, New Hunt House, Guy's Medical School Campus, London, SE1 1UL, UK.
authors.forename: Muireann T
authors.initials: MT
authors.lastname: Kelleher
authors.forename: Gilbert
authors.initials: G
authors.lastname: Fruhwirth
authors.forename: Gargi
authors.initials: G
authors.lastname: Patel
authors.forename: Enyinnaya
authors.initials: E
authors.lastname: Ofo
authors.forename: Frederic
authors.initials: F
authors.lastname: Festy
authors.forename: Paul R
authors.initials: PR
authors.lastname: Barber
authors.forename: Simon M
authors.initials: SM
authors.lastname: Ameer-Beg
authors.forename: Borivoj
authors.initials: B
authors.lastname: Vojnovic
authors.forename: Cheryl
authors.initials: C
authors.lastname: Gillett
authors.forename: Anthony
authors.initials: A
authors.lastname: Coolen
authors.forename: György
authors.initials: G
authors.lastname: Kéri
authors.forename: Paul A
authors.initials: PA
authors.lastname: Ellis
authors.forename: Tony
authors.initials: T
authors.lastname: Ng
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D006801:Humans; D009369:Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000628:therapy*; D057285:Precision Medicine; D011379:Prognosis; D040901:Proteomics
chemical_list: D014408:Biomarkers, Tumor