Frequent CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression.

We analyzed genomic data from the prostate cancer of African- and European American men to identify differences contributing to racial disparity of outcome. We also performed FISH-based studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CHD1-deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis. Subclonal deletion of CHD1 was nearly three times as frequent in prostate tumors of African American than in European American men and it associates with rapid disease progression. CHD1 deletion was not associated with HR deficiency associated mutational signatures or HR deficiency as detected by RAD51 foci formation. This was consistent with the moderate increase of olaparib and talazoparib sensitivity with several CHD1 deficient cell lines showing talazoparib sensitivity in the clinically relevant concentration range. CHD1 loss may contribute to worse disease outcome in African American men.

A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer.

The Gleason score is an important predictor of prognosis in prostate cancer. However, its subjective nature can result in over- or under-grading. Our objective was to train an artificial intelligence (AI)-based algorithm to grade prostate cancer in specimens from patients who underwent radical prostatectomy (RP) and to assess the correlation of AI-estimated proportions of different Gleason patterns with biochemical recurrence-free survival (RFS), metastasis-free survival (MFS), and overall survival (OS). Training and validation of algorithms for cancer detection and grading were completed with three large datasets containing a total of 580 whole-mount prostate slides from 191 RP patients at two centers and 6218 annotated needle biopsy slides from the publicly available Prostate Cancer Grading Assessment dataset. A cancer detection model was trained using MobileNetV3 on 0.5 mm × 0.5 mm cancer areas (tiles) captured at 10× magnification. For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. This strategy resulted in improved model generalizability in the test set compared with three different control experiments when evaluated on both needle biopsy slides and whole-mount prostate slides from different centers. In an additional test cohort of RP patients who were clinically followed over 30 years, quantitative Gleason pattern AI estimates achieved concordance indexes of 0.69, 0.72, and 0.64 for predicting RFS, MFS, and OS times, outperforming the control experiments and International Society of Urological Pathology system (ISUP) grading by pathologists. Finally, unsupervised clustering of test RP patient specimens into low-, medium-, and high-risk groups based on AI-estimated proportions of each Gleason pattern resulted in significantly improved RFS and MFS stratification compared with ISUP grading. In summary, deep learning-based quantitative Gleason scoring using a selective CutMix training strategy may improve prognostication after prostate cancer surgery.

Quality Assurance Model for Breast Cancer Prognostication Using the Modified Magee Equations.

CONTEXT.­: The Oncotype DX recurrence score (RS) is a widely used test that provides prognostic information on the likelihood of disease recurrence and predictive information on the benefit of chemotherapy in early-stage, hormone receptor-positive breast cancer. Despite its widespread use, quality assurance of the RS does not receive the same level of scrutiny as other tests, such as human epidermal growth factor receptor 2 (HER2) immunohistochemistry. OBJECTIVE.­: To use modified Magee equations to calculate Magee score (MS) as a quality check of RS. DESIGN.­: The MS is an easily accessible prognostic model that uses histopathologic and immunohistochemical criteria. We identified cases where the RS and MS differed by 10 points or more or were in different risk categories. These instances were considered significant discordances. MS was presented along with RS at multidisciplinary tumor boards and all discrepancies were discussed to determine clinical significance and appropriate next steps. RESULTS.­: Twenty-five of 155 cases (16.1%) had discrepancies between RS and MS. Of these 25 cases, 3 (12%) had problems with either the RS or the histopathologic interpretation. Among the cases with concordant RS and MS, no RS or interpretive problems were identified. CONCLUSIONS.­: Use of the MS as a quality control check for the RS can help ensure appropriate treatment decisions in breast cancer patients. Pathologists can play a key role in ensuring the quality of molecular-based prognostic scores by using histopathologic models to ensure accurate risk stratification and improve clinical outcomes.

Current laboratory testing practices for mismatch repair deficiency and microsatellite instability testing: A survey-based review of current laboratory practices.

OBJECTIVES: To describe mismatch repair (MMR) and microsatellite instability (MSI) testing practices in laboratories using the College of American Pathologists (CAP) MSI/MMR proficiency testing programs prior to the 2022 publication of the MSI/MMR practice guidelines copublished by CAP and the Association of Molecular Pathology (AMP). METHODS: Data from supplemental questionnaires provided with the 2020-B MSI/MMR programs to 542 laboratories across different practice settings were reviewed. Questionnaires contained 21 questions regarding the type of testing performed, specimen/tumor types used for testing, and clinical practices for checkpoint blockade therapy. RESULTS: Domestic laboratories test for MSI/MMR more often than international laboratories (P = .04) and academic hospitals/medical centers test more frequently than nonhospital sites/clinics (P = .03). The most commonly used testing modality is immunohistochemistry, followed by polymerase chain reaction, then next-generation sequencing. Most laboratories (72.6%; 347/478) reported awareness of the use of immune checkpoint inhibitor therapy for patients with high MSI or MMR-deficient results. CONCLUSIONS: The results demonstrate the state of MMR and MSI testing in laboratories prior to the publication of the CAP/AMP best practice guidelines, highlighting differences between various laboratory types. The findings indicate the importance of consensus guidelines and provide a baseline for comparison after their implementation.

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

CONTEXT.­: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based models share some features of conventional laboratory testing methods. Accreditation requirements that specifically address clinical laboratories' use of ML remain in the early stages of development. OBJECTIVE.­: To identify relevant CAP accreditation requirements that may be applied to the clinical adoption of ML-based molecular oncology assays, and to provide examples of current and emerging ML applications in molecular oncology testing. DESIGN.­: CAP accreditation checklists related to molecular pathology and general laboratory practices (Molecular Pathology, All Common and Laboratory General) were reviewed. Examples of checklist requirements that are generally applicable to validation, revalidation, quality management, infrastructure, and analytical procedures of ML-based molecular oncology assays were summarized. Instances of ML use in molecular oncology testing were assessed from literature review. RESULTS.­: Components of the general CAP accreditation framework that exist for traditional molecular oncology assay validation and maintenance are also relevant for implementing ML-based tests in a clinical laboratory. Current and emerging applications of ML in molecular oncology testing include DNA methylation profiling for central nervous system tumor classification, variant calling, microsatellite instability testing, mutational signature analysis, and variant prediction from histopathology images. CONCLUSIONS.­: Currently, much of the ML activity in molecular oncology is within early clinical implementation. Despite specific considerations that apply to the adoption of ML-based methods, existing CAP requirements can serve as general guidelines for the clinical implementation of ML-based assays in molecular oncology testing.

Laboratory Considerations for Releasing Next-Generation Sequencing Data to Patients.

CONTEXT.­: Title 45, section 164.524 of the Code of Federal Regulations states that health care systems must provide patient health records upon that patient's request. For complex testing, such as next-generation sequencing (NGS), this raises questions related to what data should be released and the laboratory considerations regarding the release of this data. OBJECTIVE.­: To describe the laboratory implications of releasing different NGS data files and the limitations for the clinical use of different NGS data files. DESIGN.­: The College of American Pathologists workgroup, composed of laboratorians with expertise regarding NGS testing, reviewed pertinent literature, including title 45, section 164.524, and the Health and Human Services "Guidance on Individuals' Right to Access Health Information." RESULT.­: From an accreditation standpoint, validation of NGS includes both the wet bench and data processing (bioinformatics) portions, and appropriately validated laboratory testing is required to ensure quality patient results. NGS testing generates intermediate data files that have not completed the fully validated process but are often kept by the laboratory. These files may be requested by patients, but most patients will not be aware of the test validation process and the limitations of data that have not gone through a fully validated process. CONCLUSIONS.­: Laboratories should encourage patients to receive their health data and to help individuals understand the content, uses, and limitations of laboratory data they have requested or received. NGS data used in a nonvalidated manner should not be used for clinical purposes without confirmation by a clinically validated method.

SPOT/Dx Pilot Reanalysis and College of American Pathologists Proficiency Testing for KRAS and NRAS Demonstrate Excellent Laboratory Performance.

CONTEXT.­: The Sustainable Predictive Oncology Therapeutics and Diagnostics quality assurance pilot study (SPOT/Dx pilot) on molecular oncology next-generation sequencing (NGS) reportedly demonstrated performance limitations of NGS laboratory-developed tests, including discrepancies with a US Food and Drug Administration-approved companion diagnostic. The SPOT/Dx pilot methods differ from those used in proficiency testing (PT) programs. OBJECTIVE.­: To reanalyze SPOT/Dx pilot data using PT program methods and compare to PT program data.Also see p. 136. DESIGN.­: The College of American Pathologists (CAP) Molecular Oncology Committee reanalyzed SPOT/Dx pilot data applying PT program methods, adjusting for confounding conditions, and compared them to CAP NGS PT program performance (2019-2022). RESULTS.­: Overall detection rates of KRAS and NRAS single-nucleotide variants (SNVs) and multinucleotide variants (MNVs) by SPOT/Dx pilot laboratories were 96.8% (716 of 740) and 81.1% (129 of 159), respectively. In CAP PT programs, the overall detection rates for the same SNVs and MNVs were 97.2% (2671 of 2748) and 91.8% (1853 of 2019), respectively. In 2022, the overall detection rate for 5 KRAS and NRAS MNVs in CAP PT programs was 97.3% (1161 of 1193). CONCLUSIONS.­: CAP PT program data demonstrate that laboratories consistently have high detection rates for KRAS and NRAS variants. The SPOT/Dx pilot has multiple design and analytic differences with established PT programs. Reanalyzed pilot data that adjust for confounding conditions demonstrate that laboratories proficiently detect SNVs and less successfully detect rare to never-observed MNVs. The SPOT/Dx pilot results are not generalizable to all molecular oncology testing and should not be used to market products or change policy affecting all molecular oncology testing.

RNA Sequencing for Solid Tumor Fusion Gene Detection: Proficiency Testing Practice and Performance Comparison.

CONTEXT.­: Next-generation sequencing-based approaches using RNA have increasingly been used by clinical laboratories for the detection of fusion genes, intragenic rearrangements, and exon-skipping events. Correspondingly, the College of American Pathologists (CAP) has advanced RNA sequencing proficiency testing (PT) to ensure optimal performance of these assays. OBJECTIVE.­: To report on laboratory performance and practices of RNA sequencing for the detection of fusion genes, intragenic rearrangements, and exon-skipping events using CAP PT data from 8 mailings (2018-A through 2021-B). DESIGN.­: CAP PT RNA sequencing program results from 153 laboratories across 24 proficiency test specimens, interrogating 22 distinct engineered fusion transcripts, were analyzed for correct identification of the fusion event, associated performance variables, and laboratory practices. RESULTS.­: Overall, the 4-year program detection rate (sensitivity) was 95.5% (1486 of 1556 results). False-negative rates were 3.6% (53 of 1463) and 18.3% (17 of 93) for fusion gene and intragenic rearrangement/exon-skipping events, respectively. Only 19 false-positive results were reported among the 8 PT mailings, and most were likely the result of preanalytical or postanalytical errors. There were no practice characteristics (eg, instrumentation, sequencing method) significantly associated with the fusion detection results. CONCLUSIONS.­: These data reveal a high overall sensitivity and specificity for fusion gene detection by participating laboratories using clinical RNA sequencing. Performance was comparable across all laboratories, regardless of methodology. The fraction of false-negative results for intragenic rearrangement/exon-skipping events was greater than that for the chimeric fusion genes. False-negative results could not be attributed to any specific practice characteristics.

Clinical Testing for Tumor Cell-Free DNA: College of American Pathologists Proficiency Programs Reveal Practice Trends.

CONTEXT.­: Clinical testing for tumor cell-free DNA (cfDNA) has evolved rapidly, but no practice guidelines exist. OBJECTIVE.­: To summarize cfDNA laboratory practices based on self-reporting and assess preanalytical, analytical, and postanalytical trends that may influence the quality, accuracy, and consistency of cfDNA testing. DESIGN.­: Data were derived from the College of American Pathologists cfDNA proficiency testing program submitted by 101 participating laboratories from 2018 to 2019. RESULTS.­: Most laboratories performing clinical circulating tumor DNA testing are commercial/nonhospital (71.2%; 72 of 101) and international (77.2%; 78 of 101) laboratories. Commercial laboratories had higher monthly test volumes than hospital-based laboratories (median, 36 versus 7-8) and tended to have larger gene panels (median, 50 versus 11 genes) when panel-based testing was offered. The main clinical indications include therapy selection and treatment/disease monitoring. Plasma is the most commonly accepted specimen, which is predominantly collected in cell-stabilizing tubes. Equal proportions of laboratories use next-generation sequencing (NGS) and non-NGS methods to assess key genes, including EGFR, BRAF, KRAS, NRAS, and IDH1. Most laboratories reported a lower limit of detection (LLOD) of 0.5%, variant allele frequency or less, which did not differ by method, NGS or non-NGS, except for EGFR. Sixty-five percent (17 of 26) of laboratories using the US Food and Drug Administration (FDA)-approved non-NGS EGFR assay report analytical sensitivities higher than 0.5%, as compared to 15% (16 of 104) of laboratories using an alternative NGS or non-NGS method. There is also a wider range in LLODs obtained for the FDA-approved EGFR assay than nonapproved assays. CONCLUSIONS.­: These results highlight emerging practice trends and serve as a foundation to initiate future practice recommendations.