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ACMG technical standards and guidelines: microarray analysis for chromosome abnormalities in neoplastic disorders (2013) (view source)
Revision as of 16:59, 27 July 2016
, 16:59, 27 July 2016→Quality Control
== Quality Control ==
== Quality Control ==
'''Identification'''
For each microarray, the slide ID, sample sex, control sex (when appropriate), and sample-tracking control (for multiplex microarrays) should be verified. Discrepancies in the documentation from the physical sample should be investigated and resolved before processing.
For each microarray, the slide ID, sample sex, control sex (when appropriate), and sample-tracking control (for multiplex microarrays) should be verified. Discrepancies in the documentation from the physical sample should be investigated and resolved before processing.
'''Sample requirements'''
The laboratory should establish parameters for the minimum DNA quality and quantity requirements for each sample type used for clinical testing. The laboratory should demonstrate proficiency in sample preparation, DNA extraction, and DNA purification for each sample type. Fresh or frozen tumor tissue is preferable to fixed tumor tissue for quality. FFPE tumor samples should be evaluated by a surgical pathologist to assess the quality and quantity of tumor in the sample used for microarray analysis. A minimum of 25% tumor is recommended to prevent masking of clonal changes by normal tissue DNA.
The laboratory should establish parameters for the minimum DNA quality and quantity requirements for each sample type used for clinical testing. The laboratory should demonstrate proficiency in sample preparation, DNA extraction, and DNA purification for each sample type. Fresh or frozen tumor tissue is preferable to fixed tumor tissue for quality. FFPE tumor samples should be evaluated by a surgical pathologist to assess the quality and quantity of tumor in the sample used for microarray analysis. A minimum of 25% tumor is recommended to prevent masking of clonal changes by normal tissue DNA.
'''DNA extraction, purification, measurement, and amplification with different sample types'''
DNA extraction methods should ensure the highest-quality DNA possible from the sample type(s) tested by the laboratory. Samples from neoplastic disorders present unique challenges for generating high-quality, tumor-specific DNA. Written protocols should be available in the laboratory procedure manual and/or quality management program for optimizing DNA extraction and labeling, DNA quantification (e.g., fluorometer, spectrophotometer), DNA quality and concentration (e.g., examination by gel electrophoresis), DNA fragmentation (e.g., via sonication or digestion), fluorescent labeling (e.g., examination by gel electrophoresis, visual inspection, ultraviolet/visible spectroscopy), and amplification (e.g., significant increase in product). For any labeling method, acceptable ranges should be determined for proper dye incorporation. Protocols for optimization, e.g., reextraction, repurification, tumor cell enrichment for hematological samples (cell sorting or concentration), and/or microdissection for paraffin-embedded tumor, should be available as appropriate. Laboratories should be aware that fixatives other than formalin may influence DNA quality and that decalcification of bony tumors may adversely affect DNA quality.
DNA extraction methods should ensure the highest-quality DNA possible from the sample type(s) tested by the laboratory. Samples from neoplastic disorders present unique challenges for generating high-quality, tumor-specific DNA. Written protocols should be available in the laboratory procedure manual and/or quality management program for optimizing DNA extraction and labeling, DNA quantification (e.g., fluorometer, spectrophotometer), DNA quality and concentration (e.g., examination by gel electrophoresis), DNA fragmentation (e.g., via sonication or digestion), fluorescent labeling (e.g., examination by gel electrophoresis, visual inspection, ultraviolet/visible spectroscopy), and amplification (e.g., significant increase in product). For any labeling method, acceptable ranges should be determined for proper dye incorporation. Protocols for optimization, e.g., reextraction, repurification, tumor cell enrichment for hematological samples (cell sorting or concentration), and/or microdissection for paraffin-embedded tumor, should be available as appropriate. Laboratories should be aware that fixatives other than formalin may influence DNA quality and that decalcification of bony tumors may adversely affect DNA quality.
'''Suboptimal samples'''
The laboratory should establish sample adequacy requirements. Samples that do not meet the laboratory requirements should be rejected with a repeat sample requested from the referring physician.
The laboratory should establish sample adequacy requirements. Samples that do not meet the laboratory requirements should be rejected with a repeat sample requested from the referring physician.
When a repeat sample is not available, whole-genome amplification may be a reasonable alternative if the laboratory has expertise with the method and if potential biases inherent in the technique are detailed in the report. Laboratory policies and protocols should describe when and how whole-genome amplification is performed.
When a repeat sample is not available, whole-genome amplification may be a reasonable alternative if the laboratory has expertise with the method and if potential biases inherent in the technique are detailed in the report. Laboratory policies and protocols should describe when and how whole-genome amplification is performed.
'''Equipment calibration, maintenance, and QC'''
Equipment, instrumentation, and methodologies employed during the validation and use of microarray platforms should be calibrated, receive regular maintenance, and be monitored for QC. Quality metrics should be established for each step of the assay.
Equipment, instrumentation, and methodologies employed during the validation and use of microarray platforms should be calibrated, receive regular maintenance, and be monitored for QC. Quality metrics should be established for each step of the assay.
'''QC metrics'''
Every microarray platform has defined quality metric values, e.g., adequate dye incorporation and/or amplification, fluorescence intensities variance, signal-to-background-noise ratio, and SD or error. Standard cutoff values and acceptable limits should be established for these metrics to ensure that the generated results are reliable and sufficiently precise to be used for a clinical assessment. Quality metrics should be monitored for DNA labeling, hybridization efficiency, data generation and analysis, and other platform-specific parameters. QC metrics should be incorporated into the laboratory quality assurance and quality improvement programs to monitor analytical variables.
Every microarray platform has defined quality metric values, e.g., adequate dye incorporation and/or amplification, fluorescence intensities variance, signal-to-background-noise ratio, and SD or error. Standard cutoff values and acceptable limits should be established for these metrics to ensure that the generated results are reliable and sufficiently precise to be used for a clinical assessment. Quality metrics should be monitored for DNA labeling, hybridization efficiency, data generation and analysis, and other platform-specific parameters. QC metrics should be incorporated into the laboratory quality assurance and quality improvement programs to monitor analytical variables.
'''Microarray content'''
It is not feasible for a laboratory to validate the identity and copy-number responsiveness of every probe on a microarray. The laboratory should obtain documentation from the microarray manufacturer that the probes on each microarray are the intended sequence, located appropriately by the software, empirically selected for appropriate copy-number responsiveness and/or SNP allele specificity, and stable for these assessments from lot to lot.
It is not feasible for a laboratory to validate the identity and copy-number responsiveness of every probe on a microarray. The laboratory should obtain documentation from the microarray manufacturer that the probes on each microarray are the intended sequence, located appropriately by the software, empirically selected for appropriate copy-number responsiveness and/or SNP allele specificity, and stable for these assessments from lot to lot.
'''Data quality'''
Detection of genomic aberrations is dependent on the size of the DNA targets, the probe density, the probe performance, and the distance between the sequences naturally located on the chromosome. The quality of the data will affect the ability to detect genomic aberrations; thus, the laboratory needs to understand the within-array metrics provided by the analysis software and how each metric reflects the quality of the data. One metric that provides a measurement of noise or random variance unrelated to genomic location in the data is the derivative log ratio. The derivative log ratio is the difference between the log ratio values of consecutive probes (derivative log ratio spread), i.e., the spread of the derivative log ratio values after outlier rejection. For SNP arrays, quality may be assessed using data from such parameters as call rates and variability (spread) of allele frequency.
Detection of genomic aberrations is dependent on the size of the DNA targets, the probe density, the probe performance, and the distance between the sequences naturally located on the chromosome. The quality of the data will affect the ability to detect genomic aberrations; thus, the laboratory needs to understand the within-array metrics provided by the analysis software and how each metric reflects the quality of the data. One metric that provides a measurement of noise or random variance unrelated to genomic location in the data is the derivative log ratio. The derivative log ratio is the difference between the log ratio values of consecutive probes (derivative log ratio spread), i.e., the spread of the derivative log ratio values after outlier rejection. For SNP arrays, quality may be assessed using data from such parameters as call rates and variability (spread) of allele frequency.
Laboratories should ensure that the software manufacturer provides documentation and safeguards such that data are processed and summarized in a consistent manner for every clinical analysis. Most analysis software provides a hierarchy of users with customizable permissions, which enables the laboratory to prevent modification of analysis settings so that all specimens are analyzed consistently. Any changes to data processing should be validated and documented.
Laboratories should ensure that the software manufacturer provides documentation and safeguards such that data are processed and summarized in a consistent manner for every clinical analysis. Most analysis software provides a hierarchy of users with customizable permissions, which enables the laboratory to prevent modification of analysis settings so that all specimens are analyzed consistently. Any changes to data processing should be validated and documented.
'''Verification of new lots of microarrays and/or reagents'''
Verification should ensure that new lots of microarray slides and/or reagents perform in the same manner as the previous lot. The manufacturer should supply documentation of the QC comparison between lots of microarray slides, e.g., oligo synthesis verification, accuracy of SNP calls, or other defined control parameters. A new lot of microarray slides should be tested to ensure equivalency by testing, either before or concurrently with new patient specimens, preferably using a patient specimen with an abnormal result that has been tested on a previous lot. Manufacturers may include a normal control and request that it be run. New lots of reagents, e.g., new labeling kits and consumables, should have documented equivalency between runs. This may be accomplished by documenting that the QC metrics meet certain set parameters for the new lot of reagents.
Verification should ensure that new lots of microarray slides and/or reagents perform in the same manner as the previous lot. The manufacturer should supply documentation of the QC comparison between lots of microarray slides, e.g., oligo synthesis verification, accuracy of SNP calls, or other defined control parameters. A new lot of microarray slides should be tested to ensure equivalency by testing, either before or concurrently with new patient specimens, preferably using a patient specimen with an abnormal result that has been tested on a previous lot. Manufacturers may include a normal control and request that it be run. New lots of reagents, e.g., new labeling kits and consumables, should have documented equivalency between runs. This may be accomplished by documenting that the QC metrics meet certain set parameters for the new lot of reagents.