KREX-Technology-Overview.Pdf

Misfolded proteins are washed away

Only correctly folded proteins are immobilised

1. Company 2. Technology 3. Case Studies 4. Study Design

Cambridge roots Protein folding Autoantibodies Samples Main collaborators Protein function Diagnostics Study design Team Performance Response prediction Business case

2020 2021 2008

Acquired by multi-billion dollar, life-science focused, Swedish firm

Cambridge spin-out

Boston R&D facility 2016

Protein production and high-throughput assay facility in Asia

9 out of top 10 Pharma globally 10 academic institutions 6 academic institutions >50 projects

M e m b e r o f C a n c e r , I n f l a mma t i on & I m m u n i t y , a n d N e u r o s c i e n c e S t e e r i n g C o m m i t t e e s 27 academic institutions

>200 projects

Industrial advisory board member

Type 1 Type 2 Type 3 Core Tech Patents Sero-diagnostics Drug ADR-Response

14 Granted 3 Filed 1 Filed 1 Filed 20+ Unfiled 16 Unfiled 2 Unfiled

. Group 1 - Preparing protein arrays with . Aging . Sjogren’s . Anti TNF marker tag to immobilise proteins . Oral Cancer . Zika . Anti IL . Group 2 - Protein Variant Arrays . NSCLC . Melanoma . Anti CTLA-4 . Group 3 - BCCP tag . Type II Diabetes . Malaria . Anti PDL1 . Group 4 - Cytosolic Accessory Proteins . Parkinson’s . Gastric Cancer . Other drugs . Group 5 - Drug discovery . Alzheimer’s . Crohn’s . Prostate Cancer . RA . Lupus . Breast Cancer

> BCCP: compact, inert, folding marker > Biotin is attached ONLY to correctly folded proteins > Misfolded proteins misfold BCCP > BCCP loses its biotinylation activity > Only correctly folded proteins are attached

> No conventional purification: Simultaneous purification and immobilisation PROTEINS > KREX proteins retain folded structure and function in the behave as if aqueous environment they are in > Streptavidin tetramers covalently bound to hydrogel free solution - - COO layer COO - COO > Single attachment point ensures - - COO COO consistent orientation of proteins > Proteins are immobilised onto proprietary streptavidin-coated HYDROGEL > Proteins are projected 50 Angstroms from the glass surface

PTM & complex protein Bacterial protein Peptide DNA

Viral protein

QC of KREX protein arrays demonstrates performance required for downstream assays 9

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Spot diameter ~25nm 202+/-33 streptavidin units per mm2 Dual wavelength scan of an on-array c-Myc Distance between streptavidin units assay: Red = Cy5-biotin BSA controls (red); 52.9+/-3.1 nm Green = C-terminally c-myc-tagged antigens 40,000 binding units / 200mm2 spot

Western blot analysis Anti-c-myc assay Streptavidin density

Very high specificity High signal:noise ratio and clearly interpretable hits

. Obviates conventional blood draw and cold chain As little as . Collect samples during 1µl flare-ups of serum or plasma . Leverages sensitivity of sample KREX platform

Highly reproducible Exceptional sensitivity Duplicate samples exhibit exceptional performance Limit of detection is 10pg/ml range and consistency Single digit µl levels of sample can be used (Pearson correlation >0.97) Five orders of magnitude dynamic range

> Kinases auto-phosphorylate and Kinase inhibition assays correlate with published data > DNA binding proteins bind DNA – p53 mutant proteins exhibit differential binding of labelled oligo > Indirect functional assays

Kinases autophosphorylate P53 mutants bind labelled Autoimmune disease hits in the presence of ATP DNA oligo with different Kd values correlate with published data

H E T E R O D I M E R S T R I M E R S ON- A R R A Y P T M s F U N C T I O N A L A S S A Y S

The detection of the 58 kDa Western blot analyses of expressed Quantifying the effect of post-translational On-chip phosphorylation of p53 by hexahistidine-tagged -subunit (lower HA variants protein. Two samples modifications on autoantibody casein kinase II (CKII) boxes in red) and a band at ~90 kDa (denatured and non-denatured recognition: neoantigens in colorectal (upper boxes in red) underβ semi-native proteins) of each HA variant were run cancer. Protein arrays were incubated in assay conditions of all TCR proteins provides side-by-side on SDS-PAGE gels. buffer containing ATP in the presence evidence for heterodimer complex Arginine deimidation to citrullene on chip and absence of CKII formation during protein expression in using peptide arginine deimidase 4. Results: Specific phosphorylation of insect cell. S392 was detected using residue specific antiphosphoserine primary Only the -subunit was detected at ~58 antibody with detection by secondary kDa under denaturing/reducing antibody-peroxidase conjugate and conditions.β chemiluminescence.

Mutations with “X” denote truncations due to introduction of premature stop codons and therefore lack S392

Reproducibility of quadruplicates CV% below 4% Breast cancer autoantibody biomarkers

High-throughput Quantification of Simultaneous screening of Multi-antigen, autoantibody profiling autoantibodies to 200+ 100+ wild-type and multi-domain COVID-19 against 1600+ proteins clinically relevant CT antigens mutant p53 antibody test

Using Orvar, the totality of all possible autoantigens and neoantigens representing a given disease and its sub-types can be identified

The total number of antigens if you add all possible variants of human proteins, splice variants of those human proteins and neoantigens is in the millions

Use KREX to clone, express and attach every single autoantigen or antigen on to a Sengenics protein array

Tissue from Colorectal Cancer (CRC) individuals (cancer and adjacent normal tissue) were characterised on Orvar:

Plasma samples from CRC and healthy individuals were screened against existing KREX proteins KREX proteins

Positive on both platforms: Wild-type antigens

13.7% Positive on Orvar only: Neoantigens 9.8% 54.9% New autoantigens 21.6%

Homologue autoantigens to KREX proteins which may contain overlapping surface epitopes reactive to the bound autoantibodies

GO enrichment analysis: Results indicate % of antigens with high significance (adjusted p-values < 0.01)

Continuous Dis-continuous Folding independent Folding dependent Non-conformational Conformational epitope

1. *Barlow, D. J., Edwards, M. S., & Thornton, J. M. (1986). Continuous and discontinuous protein antigenic determinants. Nature, 322(6081), 747–748; 2. *Van Regenmortel, M. H. V. (2006, May). Immunoinformatics may lead to a reappraisal of the nature of B cell epitopes and of the feasibility of synthetic peptide vaccines. Journal of Molecular Recognition, 19(3), 183–187.

C A N C E R A U T O I M M U N E N E U R O

C A N C E R A U T O I M M U N E

Early diagnosis of diseases using Predict response and ADRs autoantibodies for cancer and autoimmune drugs using autoantibodies

Diagnosis and screening of infectious diseases M I C R O B E S

Microarray Scanner

1. Add sample – 1 to 10μl (Serum, Plasma, CSF, Lung lavage, Tissue homogenate)

2. Autoantibodies in sample bind quantitatively to proteins on array

3. Scan to Quantify Autoantibody signal by adding anti-IgG secondary antibody

Autoantigens from tissue source

aAb from patient serum

1. Use ORVAR to identify the auto-proteome of interest using patient tissue source and serum

2. Use KREX to clone, express and attach every single autoantigen on to a Sengenics protein array

3. High-throughput quantification of autoantibodies for intra-disease stratification

> Stage I/II Melanoma patients (n=124) vs controls (n=121) profiled on Sengenics Immunome arrays

“The test, billed as a world first, is designed to make it easier to spot the skin cancer before it becomes fatal, according to researchers.” - BBC, 18 July 2018

139 biomarkers based on cut-off of positive score >5. A panel 10 biomarkers was selected based on a Biomarkers appear primarily related to general VEGFb, p53, MITF, KIT and MLANA have previously been random forest and classification tree analysis, resulted a cancer pathways, including apoptosis, associated with cancer and Melanoma combined sensitivity 84% and specificity 79% and an AUC of pathways associated with the immune 0.828. Biomarkers Panel : ZBTB7B, PRKCH, TP53, PCTK1, response and cell cycle, p53 signaling and the PQBP1, UBE2V1, IRF4, MAPK8_tv2, MSN and TPM1 MAPK signalling pathway, the main pathway associated with melanomagenesis Zaenker, Pauline et al. 2018

Confidential © 2008–2021 Sengenics Corporation Pte Ltd Case Study Stratification of Melanoma patients to Pembro using autoantibodies 23 250000 CTAG2 24A 200000 NY-ESO-1 24B 150000 > Study Design: 24C 100000 > Metastatic melanoma, BRAF mutant patients, treated 24D Average RFU 50000 with either Pembrolizumab (anti-PD-1)

0 24E

FES TYR

> Patient sera collected at different points of treatment PBK

LIP1

SILV

OIP5

TPTE

AKT1

CDK7

GDF3

ITGB1

SYCP1

SSX2A

PRKCZ

SPO11

SPAG9

CSAG2

DPPA4

CTAG2

BAGE4

DDX53

GAGE5

GAGE1

ROPN1

CALM1

MAPK3

NANOG

COL6A1 SPANXC

(baseline, post-treatment 1, 2 etc.) CDC25A

MAGEB6

MAGEA5

p53S46A

NY-CO-45

CXorf48.1

5T4/TPBG

MAGEA11

XAGE3av1

p53K382R p53Q136x > Sera screened on the KREX arrays for the MAGEA4v2 25000 p53 S15A quantification of autoantibodies towards CT antigens p53 S46A 20000 > Figures show autoantibody profiles across 3 p53 K382R 15000 p53p53 C141Y L344P patients treated with Pembro whom were reported P53 T18A

to have; 10000 47A Average RFU 5000 47B > complete response (top) 0

> disease progression (middle)

FES

TYR

PBK

LIP1

SILV

OIP5

TPTE

AKT1

CDK7

GDF3

ITGB1

SYCP1

SSX2A

PRKCZ

SPO11

SPAG9

CSAG2

DPPA4

CTAG2

BAGE4

DDX53

GAGE5

GAGE1

ROPN1

CALM1

MAPK3

NANOG

COL6A1 SPANXC

> initially stable and then disease progression CDC25A

MAGEB6

MAGEA5

p53S46A

NY-CO-45

CXorf48.1

5T4/TPBG

MAGEA11

XAGE3av1

p53K382R p53Q136x (bottom) MAGEA4v2 300000 DDX53 > Differences in autoantibody signatures observed 250000 MAGEB6 suggest the platform’s potential in providing a 200000 MAGEB1 CTAG2 NY-ESO-1 practical route to patient stratification prior to 150000 51A 100000 treatment 51C

50000 Average RFU

0 51D

FES

TYR

PBK

LIP1

SILV

OIP5

TPTE

AKT1

CDK7

GDF3

ITGB1

SYCP1

SSX2A

PRKCZ

SPO11

SPAG9

CSAG2

DPPA4

CTAG2

BAGE4

DDX53

GAGE5

GAGE1

ROPN1

CALM1

MAPK3

NANOG

COL6A1

SPANXC

CDC25A

MAGEB6

MAGEA5

p53S46A

NY-CO-45

CXorf48.1

5T4/TPBG

MAGEA11

XAGE3av1

p53K382R

p53Q136x MAGEA4v2

> Two independent studies both identified well-known SLE autoantigens TROVE2 (Ro60) and SSB (La) showing the most significant difference between SLE and healthy cohorts. (Study 1: 86 SLE patients vs 90 matched healthy individuals Study 2: 10 SLE patients vs 10 healthy individuals) > These studies also identified previously reported SLE autoantigens such as PRM1 (U.S. Patent Application No. 14/418,700). The array also validated other previously reported SLE autoantigens PSME3 (also known as Ki) (M. Matsushita, 2004)

Volcano plot summarising the results from a comparison analysis of 86 SLE Comparison analysis of 10 SLE patients VS 10 matched healthy samples run on the patients VS 90 matched healthy samples run on the Sengenics Immunome Sengenics Immunome array in Study 2 array in Study 1

Lewis, M. J., et. al. 2018

> Autoantibody profiles stratify SLE patients significantly based on disease trajectories – potential therapeutic targets based on severity > Identified autoantigens cluster into functional groups, hinting at differing underlying pathogenic mechanisms and possibly at differing treatments for the SLE subgroups > 13 of the novel antigens directly implicated in SLE pathogenesis

Unsupervised clustering of the autoantibody repertoire revealed Two key themes emerged: cluster 2 autoantigens centred around four distinct SLE clusters (1a, 1b, 2, 3) in discovery and validation SMAD2 and SMAD5 were linked to TGF-b/Wnt/BMP signalling; cohort. These clusters represent distinct molecular subtype of SLE cluster 3 autoantigens were implicated in TLR/NF-kB signalling, and different response to treatment apoptosis regulation, and B and T lymphocyte development.

Lewis, M. J., et. al. 2018

Red = subgroup 1a Purple = subgroup B-cell-directed therapies? 1b (e.g. Rituximab) Green = subgroup 2 Blue = subgroup 3

Non-B-cell-directed therapies? (e.g. cyclophosphamide)

Lewis, M. J., et. al. 2018

Immunogenicity and Effectiveness in RA Good responders

Anti-drug antibody (ADAb) positive vs negative patients at baseline and at week 24 of adalimumab therapy > Results: > Panel of top 8 biomarkers identified: autoantibodies Heat map showing clear against TROVE2, SSB, NDE1, ZHX2, SH3GL1, CARD9, distinction between poor PTON20, and KLHL12 and good (purple box) > Combined discriminatory power with: responders to adalimumab > Sensitivity = 77% therapy > Specificity = 81%

Panel: 8 biomarkers Mean sensitivity: 0.774 Mean specificity: 0.806 Mean distribution plot from Mean accuracy: 0.790 random forest analysis showing a panel consisting of 8 biomarkers resulting in the most stable performance Anti-TROVE2 had the highest individual discriminating ability, and may serve as a novel predictor of adalimumab immunogenicity. Plasma autoantibody levels against TROVE2 correlated positively with ADAb titres and negatively with drug levels Chen, P. K. et. al., 2021 Patent no. 10202011473Y

Pilot study Validation Custom Clinical Matched samples Training and Signature ID FDA process Time points Validation set +Orvar proteins Regulatory

6 weeks 8 weeks 12 weeks

2500

2000

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0 Samples Proteins

Percentage of Sample Size Estimation and Power Calculation for Various Diseases Category Type of Disease Power (%) Biomarkers 2% 1% 800 90.00% 153 250

n 700 Rheumatoid Arthritis 95.00% 189 309 tio

a 99.00% 267 437

m 600 Autoimmune

ti 90.00% 128 221

s e Sjogren’s syndrome 95.00% 149 256

500 ize

s 99.00% 191 329

e l 400 90.00% 91 116

Gastric Cancer 95.00% 113 143 amp

s 300

f 99.00% 159 203

o Cancer r r

e 200 90.00% 57 90

b Non-small-cell lung

m 95.00% 66 104

u 100 Statistical carcinoma (NSCLC)

N 99.00% 85 134 Power 90.00% 160 182 0 Metabolic Type 2 Diabetes (T2D) 95.00% 186 211 0.9 0.95 0.99 0.9 0.95 0.99 0.9 0.95 0.99 0.9 0.95 0.99 0.9 0.95 0.99 0.9 0.95 0.99 Disorder NSCLC Gastric Cancer T2D Sjogren Rheumatoid Parkinson 99.00% 239 271 Syndrome Athritis 90.00% 357 427 Neurological Parkinson 95.00% 442 528 Percentage of Biomarkers 2% 1% 99.00% 624 746

Autoantibodies Targeting TLR and SMAD Pathways Define New Subgroups in Systemic Lupus Erythematosus Lewis, Myles J. et al. 2018

Identification of Novel Native Autoantigens in Rheumatoid Arthritis Poulsen, Thomas B. G. et al. 2020 A U T O I M M U N E Detection of Putative Autoantibodies in Systemic Lupus Erythematous using a Novel Native-conformation Protein Microarray Platform Mak, Anselm. et al. 2020

Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA Chen, Der-Yuan et al. 2021

Functional Protein Microarrays for Parallel Characterisation of P53 Mutants Boutell, Jonathan M. et al. 2004

Seromic Analysis of Antibody Responses in Non-Small Cell Lung Cancer Patients and Healthy Donors Using Conformational Protein Arrays Gnjatic, Sacha et al. 2009

Protein Function Microarrays: Design, Use and Bioinformatic Analysis in Cancer Biomarker Discovery and Quantitation Duarte, Jessica et al. 2013

Serologic Autoantibodies as Diagnostic Cancer Biomarkers — A Review Zaenker, Pauline et al. 2013

C A N C E R Development Of A Novel, Quantitative Protein Microarray Platform for the Multiplexed Serological Analysis of Autoantibodies to Cancer-Testis Antigens Beeton-Kempen, Natasha et al. 2014

Novel Potential Serological Prostate Cancer Biomarkers Using CT100+ Cancer Antigen Microarray Platform in a Multi-Cultural South African Cohort Adeola, Henry A et al. 2016

Autoantibodies May Predict Immune-Related Toxicity: Results from a Phase I Study of Intralesional Bacillus Calmette–Guérin followed by Ipilimumab in Patients with Advanced Metastatic Melanoma Da Gama Duarte, Jessica et al. 2018

A Diagnostic Autoantibody Signature for Primary Cutaneous Melanoma Zaenker, Pauline et al. 2018

B cells and Antibody Production in Melanoma Da Gama Duarte, Jessica et al. 2018

Augmentation of Autoantibodies by Helicobacter pylori in Parkinson’s Disease Patients May Be Linked to Greater Severity N E U R O Suwarnalata, Gunasekaran et al. 2016

Autoantibody Profile of Patients Infected with Knowlesi Malaria Liew, Jonathan et al. 2015

Identifying Protein Biomarkers in Predicting Disease Severity of Dengue Virus Infection Using Immune-Related Protein Microarray Soe, Hui Jen et al. 2018 M I C R O B I A L COVID-19 Antibody Testing: From Hype to Immunological Reality Blackburn, Jonathan M et al. 2020

Quantitative, Epitope-specific, Serological Screening of COVID-19 Patients Using a Novel Multiplexed Array-based Immunoassay Platform Blackburn, Jonathan M et al. 2020

A Novel Method to Identify Autoantibodies against Putative Target Proteins in Serum from beta-Thalassemia Major: A Pilot Study Sumera, Afshan et. al. 2020 O T H E R Potential Novel Proteomic Biomarkers for Diagnosis of Vertebral Osteomyelitis Identified using an Immunomics Protein Array Technique Chen, Chang-Hua et al. 2020

Protein Function Microarrays for Customised Systems-Oriented Proteome Analysis Blackburn, Jonathan M, and Shoko, Aubrey 2011

Advances in the Development of Human Protein Microarrays Duarte, Jessica G, and Blackburn, Jonathan M 2017 T E C H N O L O G Y Autoantibody-Based Diagnostic Biomarkers: Technological Approaches to Discovery and Validation Aziz, Farhanah et al. 2018

Applications of Functional Protein Arrays for Detection and Development of Autoantibody-based Diagnostics and Therapeutics Aziz, Farhanah et al. 2018

Use KREX protein arrays to discover high-accuracy autoantibody signatures

Diagnose cancers/autoimmune diseases earlier Predict irAEs at baseline for IO and autoimmune drugs

High PPV/NPV drug response prediction Intra-disease stratification

How to use SEROMAX

1. Wipe alcohol swab across your fingertip 3. Prick finger by pushing lancet firmly down 5. Gently drip blood onto all 4 circles of the 2. Twist off the cap from the lancet with your other hand blood card 4. Press finger lightly towards the puncture 6. Insert blood card into the biohazard bag site to obtain blood before posting the box back to your service provider

. Sample collection kit which only requires a pin-prick amount of blood for quantifying antibodies or autoantibodies . Obviates conventional blood draw and cold chain . Leverages sensitivity of KREX platform . Enables sample collection during flare-up events