Genetic Testing for Hereditary Cancer
By Dr. Zubair Khalid, DVM, MS, PhD ·
Quick Answer
- Variant classification in clinical laboratories follows the ACMG/AMP framework, which assigns pathogenicity based on weighted evidence categories instead of a single test result.
- The practical next step for lab professionals is to establish a structured variant assessment workflow that documents each evidence type and its classification strength.
- A key limitation is that the ACMG/AMP system requires professional judgment, and automated tools cannot replace the final interpretation by a qualified molecular specialist.
Understanding Variant Classification in Hereditary Cancer Testing
Hereditary cancer genetic testing identifies sequence changes in genes associated with increased cancer risk. The clinical value of a test result depends on how the laboratory classifies the detected variant. A variant classified as pathogenic may guide surgical decisions, surveillance protocols, and family member testing. A variant classified as benign may reassure a patient and avoid unnecessary medical intervention. The classification process is therefore a critical quality control point in the laboratory workflow.
The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published a joint recommendation in 2015 that established a standardized framework for sequence variant interpretation. This framework assigns each variant to one of five categories: pathogenic, likely pathogenic, uncertain significance, likely benign, or benign. The system uses a combination of evidence types, each weighted according to its strength, to arrive at a final classification.
For a molecular biologist working in a clinical laboratory, understanding the structure of these guidelines is essential for producing accurate reports. The classification process requires the integration of population data, computational predictions, functional assays, segregation data, and clinical observations. Each piece of evidence contributes to a scoring system that determines the final category.
The Five-Tier Classification System
The ACMG/AMP framework organizes variants into five categories. Each category has a distinct clinical meaning and triggers different patient management actions.
| Classification | Clinical Meaning | Typical Laboratory Action |
|---|---|---|
| Pathogenic | Variant is disease-causing | Report as positive, recommend clinical management |
| Likely Pathogenic | Variant is probably disease-causing | Report as positive, recommend clinical management |
| Uncertain | Evidence is insufficient or conflicting | Report as VUS, do not use for clinical decisions |
| Likely Benign | Variant is probably not disease-causing | Report as negative, no clinical action |
| Benign | Variant is not disease-causing | Report as negative, no clinical action |
The distinction between pathogenic and likely pathogenic is important. A pathogenic classification indicates that the evidence is strong enough to support clinical action. A likely pathogenic classification indicates that the evidence is strong but not definitive. In practice, many laboratories treat likely pathogenic variants as actionable for surveillance purposes, but the clinical confidence is lower.
The uncertain category is the most challenging for laboratory professionals. A variant of uncertain significance (VUS) cannot be used for clinical decision-making. The laboratory report must clearly state that the variant is not actionable and that further testing may be needed. The patient and the ordering clinician must understand that a VUS is not a positive result.
Evidence Categories and Their Weights
The ACMG framework uses a set of evidence codes, each with a designated strength. The codes are organized into two groups: those that support pathogenicity and those that support benign classification. Each code has a weight of very strong, strong, moderate, or supporting.
Population Data
Population databases such as gnomAD provide allele frequency information for variants in large, diverse populations. A variant that is common in the general population is unlikely to be pathogenic for a rare hereditary cancer syndrome. The absence of a variant from population databases may support pathogenicity, but this evidence is weak because the database may not include all relevant populations.
The laboratory must consider the allele frequency threshold for the specific gene and disease. A variant that is present at a frequency higher than the expected disease prevalence is unlikely to be a high-penetrance pathogenic variant. The laboratory must also consider the ethnicity of the patient and the composition of the population database.
Computational and Predictive Data
Computational tools predict the effect of a variant on protein function. These tools include sequence conservation analysis, protein structure prediction, and splice site prediction algorithms. The ACMG framework assigns a supporting strength to computational evidence. The evidence is not sufficient on its own to classify a variant as pathogenic.
The laboratory must use multiple computational tools and compare their results. A variant that is predicted to be damaging by several different algorithms is more likely to be pathogenic than a variant that is predicted to be damaging by only one. The laboratory must also consider the limitations of each tool. Some tools are trained on specific types of variants and may not perform well on others.
Functional Studies
Functional studies provide direct evidence of the effect of a variant on protein function. These studies may include assays that measure protein activity, protein stability, or protein-protein interactions. The ACMG framework assigns a strong or moderate strength to functional evidence, depending on the quality of the study.
The laboratory must evaluate the quality of the functional study. A well-designed study that uses a relevant cell line and a validated assay provides stronger evidence than a study that uses a non-relevant model system. The laboratory must also consider whether the functional study was performed in a clinical laboratory or in a research laboratory. Research laboratory results may be less reliable.
Segregation Data
Segregation data comes from family studies that examine whether the variant co-segregates with the disease in affected family members. The ACMG framework assigns a moderate strength to segregation evidence. The strength of the evidence depends on the number of affected family members and the pattern of inheritance.
The laboratory must have access to family history information to use segregation data. The laboratory may need to request additional family information from the ordering clinician. The laboratory must also consider the possibility of phenocopies, which are individuals who have the disease but do not carry the variant.
Clinical and Allelic Data
Clinical data includes the patient's personal and family history of cancer. The laboratory must evaluate whether the patient's phenotype is consistent with the gene being tested. The laboratory must also consider the presence of other variants in the same gene or in other genes.
The ACMG framework assigns a strong strength to the evidence that the variant is present in a gene that is known to cause the disease. The framework also assigns a strong strength to the evidence that the variant is absent in a healthy control population. The laboratory must be careful to use the correct control population.
The Scoring System
The ACMG framework uses a scoring system to combine the evidence codes. The laboratory assigns each evidence code to the variant and then combines the codes to determine the final classification. The scoring system is not a simple addition of points. The framework provides specific rules for combining the evidence.
The framework provides that a variant is classified as pathogenic if it meets one of the following criteria: one very strong evidence code, two strong evidence codes, one strong and three moderate evidence codes, or one strong and two moderate and two supporting evidence codes. The framework provides similar rules for the other categories.
The laboratory must document the evidence codes that were used for each variant. The documentation must include the specific evidence code, the strength of the evidence, and the rationale for the classification. The documentation must be included in the laboratory report or in the laboratory's internal records.
Common Pitfalls in Variant Classification
The classification of a variant is a complex process that requires careful attention to detail. The following are common pitfalls that laboratory professionals may encounter.
Overreliance on Computational Predictions
Computational predictions are a useful tool, but they are not definitive. A variant that is predicted to be damaging by multiple algorithms may still be benign. The laboratory must not classify a variant as pathogenic based on computational predictions alone. The laboratory must also consider the limitations of the computational tools.
Misinterpreting Population Data
Population data is a useful tool, but it must be interpreted carefully. A variant that is present in a population database at a low frequency may still be pathogenic. The laboratory must consider the specific population and the disease prevalence. The laboratory must also consider the possibility that the variant is a founder mutation.
Ignoring the Clinical Context
The clinical context is essential for variant classification. A variant that is classified as pathogenic in one gene may be benign in another gene. The laboratory must consider the patient's phenotype and family history. The laboratory must also consider the possibility that the patient has a variant in a different gene.
Failing to Document the Evidence
The laboratory must document the evidence codes that were used for each variant. The documentation must be clear and complete. The laboratory must also document the rationale for the classification. The documentation is essential for the laboratory's quality control and for the review of the classification.
The Role of the Molecular Biologist
The molecular biologist plays a central role in the variant classification process. The molecular biologist is responsible for the technical aspects of the testing, including the selection of the assay, the analysis of the data, and the interpretation of the results. The molecular biologist must also be able to communicate the results to the ordering clinician and to the patient.
The molecular biologist must have a strong foundation in molecular biology, including the principles of DNA replication, transcription, and translation. The molecular biologist must also have a strong foundation in genetics, including the principles of inheritance and the structure of the human genome. The molecular biologist must also have a strong foundation in bioinformatics, including the ability to use computational tools for the analysis of the data.
The molecular biologist must also have a strong foundation in the clinical aspects of hereditary cancer. The molecular biologist must understand the clinical presentation of the disease, the genetic basis of the disease, and the clinical management of the patient. The molecular biologist must also be able to communicate with the ordering clinician and with the patient.
The molecular biologist must also be able to work in a team environment. The molecular biologist may work with genetic counselors, pathologists, and other laboratory professionals. The molecular biologist must be able to communicate the results of the analysis to the team and to the patient.
Laboratory Workflow for Variant Classification
The laboratory workflow for variant classification is a multi-step process that requires careful attention to detail. The following is a typical workflow for a clinical laboratory.
Step 1: Variant Detection
The first step is the detection of the variant. The laboratory uses a variety of methods to detect variants, including Sanger sequencing, next-generation sequencing, and multiplex ligation-dependent probe amplification. The laboratory must validate the method and ensure that the method is appropriate for the gene and the variant.
Step 2: Variant Annotation
The second step is the annotation of the variant. The laboratory must identify the gene, the transcript, and the protein change. The laboratory must also identify the variant's location in the gene and the effect of the variant on the protein. The laboratory must use a standard annotation system, such as the Human Genome Variation Society (HGVS) nomenclature.
Step 3: Evidence Collection
The third step is the collection of the evidence. The laboratory must collect the population data, the computational predictions, the functional data, the segregation data, and the clinical data. The laboratory must also collect the data from the literature and from the databases.
Step 4: Evidence Evaluation
The fourth step is the evaluation of the evidence. The laboratory must evaluate the quality of the evidence and the strength of the evidence. The laboratory must also consider the limitations of the evidence.
Step 5: Classification
The fifth step is the classification of the variant. The laboratory must use the ACMG/AMP framework to classify the variant. The laboratory must document the evidence codes and the rationale for the classification.
Step 6: Reporting
The sixth step is the reporting of the variant. The laboratory must prepare a report that includes the classification of the variant, the evidence codes, and the clinical interpretation. The report must be clear and complete.
Step 7: Review
The seventh step is the review of the classification. The laboratory must review the classification and the report. The laboratory must also review the classification of the variant in the context of the other variants in the gene.
Records and Measurements
The laboratory must maintain records of the variant classification process. The records must include the evidence codes, the rationale for the classification, and the final classification. The records must be maintained in a secure and accessible format.
The laboratory must also measure the performance of the variant classification process. The laboratory must track the number of variants that are classified as pathogenic, likely pathogenic, uncertain, likely benign, and benign. The laboratory must also track the number of variants that are reclassified.
The laboratory must also measure the turnaround time for the variant classification. The laboratory must track the time from the receipt of the sample to the release of the report. The laboratory must also track the time from the detection of the variant to the classification of the variant.
Common Failure Patterns
The following are common failure patterns in the variant classification process.
Failure to Use the ACMG/AMP Guidelines
The laboratory may fail to use the ACMG/AMP guidelines. The laboratory may use a different classification system or may not use a classification system at all. The laboratory must use the ACMG/AMP guidelines to ensure the consistency and the accuracy of the classification.
Failure to Document the Evidence
The laboratory may fail to document the evidence codes and the rationale for the classification. The laboratory must document the evidence codes and the rationale for the classification. The documentation is essential for the quality control and for the review of the report.
Failure to Consider the Clinical Context
The laboratory may fail to consider the clinical context of the variant. The laboratory must consider the patient's phenotype and family history. The laboratory must also consider the possibility that the patient has a variant in a different gene.
Failure to Use the Appropriate Databases
The laboratory may fail to use the appropriate databases. The laboratory must use the appropriate databases for the population data, the computational predictions, and the functional data. The laboratory must also use the appropriate databases for the clinical data.
Limitations of the ACMG/AMP Framework
The ACMG/AMP framework is a useful tool, but it has limitations. The framework is not a substitute for professional judgment. The laboratory must use the framework as a guide, but the laboratory must also use the clinical judgment.
The framework is also not a substitute for the clinical context. The laboratory must consider the clinical context of the variant. The laboratory must also consider the possibility of the variant in a different gene.
The framework is also not a substitute for the functional data. The laboratory must consider the functional data. The laboratory must also consider the possibility that the functional data is not available.
The framework is also not a substitute for the segregation data. The laboratory must consider the segregation data. The laboratory must also consider the possibility that the segregation data is not available.
Professional Escalation Criteria
The laboratory must have a process for the escalation of the variant classification. The laboratory must escalate the classification to a senior laboratory professional if the classification is uncertain or if the classification is not clear.
The laboratory must also escalate the classification to a clinical professional if the classification is not clear. The laboratory must also escalate the classification to a clinical professional if the classification is not clear.
The laboratory must also escalate the classification to a clinical professional if the classification is not clear. The laboratory must also escalate the classification to a clinical professional if the classification is not clear.
Career Context for Molecular Biologists
The work of a molecular biologist in a clinical laboratory is a specialized career path. The U.S. Bureau of Labor Statistics provides information on the occupation of biological technicians and medical scientists. The O*NET OnLine provides information on the tasks, skills, and work context for these occupations.
The National Institutes of Health provides information on the training and the professional development for the research careers. The American Society for Microbiology provides information on the career development for the microbiology professionals. The National Science Foundation provides information on the careers in the federal research organizations.
The molecular biologist must have a strong foundation in the molecular biology, the genetics, and the bioinformatics. The molecular biologist must also have a strong foundation in the clinical aspects of the disease. The molecular biologist must also have a strong foundation in the communication and the teamwork.
Frequently Asked Questions
What is the ACMG/AMP classification system?
The ACMG/AMP classification system is a standardized framework for the interpretation of the genetic variants. The system assigns each variant to one of five categories: pathogenic, likely pathogenic, uncertain, likely benign, or benign. The system uses a combination of evidence categories, each weighted by its strength, to arrive at a final classification.
How does a laboratory classify a variant as pathogenic?
A laboratory classifies a variant as pathogenic by using the ACMG/AMP framework. The laboratory collects the evidence, evaluates the evidence, and uses the scoring system to determine the classification. The laboratory must document the evidence codes and the rationale for the classification.
What is a variant of uncertain significance?
A variant of uncertain significance is a variant that cannot be classified as pathogenic or benign. The laboratory reports the variant as uncertain and does not recommend clinical action. The patient may need additional testing or family studies to clarify the classification.
What is the role of the molecular biologist in variant classification?
The molecular biologist is responsible for the technical analysis of the variant, including the detection, the annotation, and the interpretation. The molecular biologist must also be able to communicate the clinical interpretation to the ordering clinician and to the patient.
What are the common pitfalls in variant classification?
The common pitfalls include the overreliance on computational predictions, the misinterpretation of the population data, the failure to consider the clinical context, and the failure to document the evidence.
What is the difference between a pathogenic and a likely pathogenic variant?
A pathogenic variant is a variant that is disease-associated. A likely pathogenic variant is a variant that is probably disease-associated. The clinical action is the same for both, but the confidence is lower for the likely pathogenic variant.
How does a laboratory use the population data?
The laboratory uses the population data to determine the allele frequency of the variant. A variant that is present in the general population at a high frequency is unlikely to be pathogenic. The laboratory must also consider the specific population and the disease.
What is the role of the functional data in variant classification?
The functional data provides evidence of the effect of the variant on the protein function. The laboratory uses the functional data to support the classification. The functional data is not sufficient on its own to classify a variant as pathogenic.
Using the Evidence
| Source | Best use in this topic | Important limitation |
|---|---|---|
| Occupational Outlook Handbook | official guidance | Check the linked page for current local requirements |
| O*NET OnLine | official guidance | Check the linked page for current local requirements |
| Office of Intramural Training and Education | official guidance | Check the linked page for current local requirements |
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References and Further Reading
- Occupational Outlook Handbook. U.S. Bureau of Labor Statistics.
- O*NET OnLine. U.S. Department of Labor.
- Office of Intramural Training and Education. National Institutes of Health.
- Careers at NSF. U.S. National Science Foundation.
- Career Services. American Society for Microbiology.
- AAVMC Career Resources. Association of American Veterinary Medical Colleges.
- NCBI Literature Resources. National Center for Biotechnology Information.
- PubMed. National Library of Medicine.
This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.