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UCLA School of Dentistry, MD Anderson Cancer Center, Fred Hutchinson Cancer Research Center
SSU01 Interim ReportStudy Architecture
2
Samples Available
Current Status Goal
- 133 samples passed QC- ~80 remaining to be assayed
210 Classified Samples- Passed QC- Excluded from Screen
Failures
SSU01 Interim Analysis Workflow
• Test biomarker panel for Sjogren Syndrome– 4 autoantibodies using Lifetech
protoplex panel (no standard curve)
– 3 autoantibodies using in-house developed assay and EMD millipore assay (with standard curve)
• Performance of triplicate tests on 210 blinded Sjogren syndrome patient samples
Key Objectives
• Sensitivity and specificity data on blinded samples
Key end products
Objectives and End Products Desired
4
SSU01 INTERIM ANALYSISKey Parties Involved
UCLA
• Project Lead– David Wong [email protected]
• Clinical Coordinator– David Akin [email protected]
• Scientists– Stergios Katsiougiannis [email protected]– Shigeo Ishikawa [email protected]– Michael Tu [email protected]’
MDA• Biostatistics
– Ziding Feng [email protected]
FH
• Information Exchange– Litwin, Paul E [email protected]– Tim M Monahan [email protected]
UCLA
MDA
FH
SSU01 Interim Analysis Workflow
5
- UCLA finalizes raw data format
UCLA ProtocolDev.
UCLA Finalizes data formats
UCLA Test Run
UCLA – MDA blinding
Process Samples
- UCLA sends MDA complete list of samples
- MDA randomizes blinded samples for testing
- Scheme sent to UCLA and FH
- UCLA will process samples according to protocol. - Raw files and
compiled files sent to FH.
Biostatistics
- FH processes data and sends to MDA
- UCLA finalizes assay development and protocol used for study.
Preparation Interim Analysis
Preparation and Interim Phases
- Data sent to FH in “test run”
6
Workflow and Dependencies (If the processes are dependent they are the same color)
Task
• QC of remaining samples (Stergios)
• 3-Plex Assay (Stergios)– Finalization of Protocol for 3-Plex Panel – Finalizing data format– Mock-run of 3-plex using in-house saliva
samples on 78 different saliva samples
• 4-Plex Assay (Stergios)– UCLA performs initial optimization– Finalizing data format for 4-Plex
• Mock Run/ Data handshake with FH
• Data for randomization – Dave Akin sends list of barcodes for samples to
Ziding Feng– Ziding Feng randomizes and sends randomized
wells/plates to UCLA. Barcodes 1-78 will be randomized across plates 1-3, 79-156 across plates 4-6,and 157-210 across plates 7-9
• Validation and analysis– Stergios performs protocol on samples– Michael Tu compiles data file for FH, transmits
compiled data and raws to FH– FH sends data to MDA– MDA Analysis and compilation of results
4-10 11-17 18-24 25-31
January
1-7 8-14 15-21 22-28
Februrary
1-7 8-14 15-21 22-28
March
SSU01 Interim Analysis Workflow
7
Data Formats and LabelingFH send sample list and patient records to MDA for randomization (XLSX file)
- QC failures should be excluded- Screen failures should be excluded
8
1 2 3 4 5 6
Experimental WorkflowDays of Experiment Work
Read
Read
Read
Read
Read
4 Plex Panel
3 Plex Panel
123
123
456
789
456
Read
789
9
Data Formats and LabelingMDA to UCLA XLSX file with barcode IDs and randomization (2 files total, one for 3plex and one for 4plex)Example of the 3plex format:
• Triplicates• 1 replicate/ plate• 78 samples/plate• 9 plates total
3plex (a-enolase, cathespin D, B2M)
1,2,3
4,5,6
7,8,9
10
Data Formats and LabelingMDA to UCLA XLSX file with barcode IDs and randomization (2 files total, one for 3plex and one for 4plex)Example of the 4plex format:
• Triplicates• 1 replicate/ plate• 78 samples/plate• 9 plates total
4plex (SSA, SSB, Histones, Transglutaminase
1,2,3
4,5,6
7,8,9
11
Data Formats and LabelingUCLA Experimental DataMagpix generated CSV (18 files total, 9 for the 3plex and 9 for the 4plex)
Example for 3plex output
12
Data Formats and LabelingUCLA Experimental DataMagpix generated CSV (18 files total, 9 for the 3plex and 9 for the 4plex)
Example for 4plex output
13
Data Formats and LabelingRaw Output to Compiled File for UCLA to send to FHOne XLSX file with all the results compiled together (18 files total)
UCLA will compile the raw output data
14
Data Formats and LabelingConventions for Naming Files
Title Step in Process Data Files and Naming Convention Links to file
UCLA -> FH XLSX file with list of QC failed samples (1 file total)
FH (to correlate QC’ed sample+Screen Failures to patient records) -> MDA
XLSX file with barcode ID (1 file total)
MDA (randomized list) -> FH -> UCLA
XLSX file with barcode IDS and randomization (2 files total, one for 3 plex and one for 4plex)
3plex well layout link
4plex well layout link
UCLA Experimental Data
Magpix generated CSV (18 files total, 9 for the 3plex and 9 for the 4plex)
Naming convention: [3 or 4 Plex]_[Plate_number]Example: 3Plex_Plate1, 4Plex_Plate8
3plex raw
4plex raw
UCLA (compiled data) -> FH (associates with patients) - > MDA (Analysis)
One XLSX file with all the results compiled together (54 file total) Compiled data
Standard Curve 3plexStandard Curve 4plex
Associates Patient ID’s with patient
data (unblinding)
Summary Overview of Workflow
15
UCLAFH MDA
ArrangesPlates
In Random order
UCLA Receives
Design and Performs
Experiments
3-Plex Layout,4-Plex Layout
Experiment performed over 4 days
Performs QC of Samples and informs FH of
failed QC samples
18 Raw Data CSV files
9 File holding 4plex QC (XLS)
18 File Holding Patient Marker Levels (XLS)
9 File holding 3plex QC and Standards (XLS)
UCLA Compiles Data
Analyzes Data
Correlates sample ID’s
to patient records and
removes screen failures
Clinical Collection of Samples
16
1. Six Clinical Tests2. Up to 10 weeks
1. Rheumatologist2. Opthalmologist3. Oral Medicine
3. Expenses4. Diagnosis ~6.5 years5. B-cell lymphoma
S
Saliva Biomarker Test
Literature References
21
Hu, S, Gao, K, Pollard, R, Arellano-Garcia, M, Zhou, H, Zhang, L, Elashoff, D, Kallenberg, C G, Vissink, A, and Wong, D T Preclinical validation of salivary biomarkers for primary Sjogren's syndrome. Arthritis Care Res (Hoboken), 2010; 62: 1633-1638. PMCID: 2995446.
1) Three salivary protein markers b2M, cathepsin D and a-enolase yielded an ROC of 0.99 in distinguishing pSS from non-pSS subjects
Hu, S, Vissink, A, Arellano, M, Roozendaal, C, Zhou, H, Kallenberg, C G, and Wong, D T Identification of autoantibody biomarkers for primary Sjögren's syndrome using protein microarrays. Proteomics, 2011; 11: 1499-1507. PMCID: NIHMSID # 323544.
2) Four Salivary autoantibody biomarkers, anti-transglutaminase, anti-histone, anti-SSA and anti-SSB yielded an ROC of 0.99 in distinguishing pSS from non-SS subjects
22
ReferencesLiterature