The clinical and economic implications of specimen provenance complications in diagnostic prostate biopsies

Molecular Auditing: An Evaluation of Unsuspected Tissue Specimen Misidentification

CONTEXT.—

Specimen misidentification is the most significant error in laboratory medicine, potentially accounting for hundreds of millions of dollars in extra health care expenses and significant morbidity in patient populations in the United States alone. New technology allows the unequivocal documentation of specimen misidentification or contamination; however, the value of this technology currently depends on suspicion of the specimen integrity by a pathologist or other health care worker.

OBJECTIVE.—

To test the hypothesis that there is a detectable incidence of unsuspected tissue specimen misidentification among cases submitted for routine surgical pathology examination.

DESIGN.—

To test this hypothesis, we selected specimen pairs that were obtained at different times and/or different hospitals from the same patient, and compared their genotypes using standardized microsatellite markers used commonly for forensic human DNA comparison in order to identify unsuspected mismatches between the specimen pairs as a trial of "molecular auditing." We preferentially selected gastrointestinal, prostate, and skin biopsies because we estimated that these types of specimens had the greatest potential for misidentification.

RESULTS.—

Of 972 specimen pairs, 1 showed an unexpected discordant genotype profile, indicating that 1 of the 2 specimens was misidentified. To date, we are unable to identify the etiology of the discordance.

CONCLUSIONS.—

These results demonstrate that, indeed, there is a low level of unsuspected tissue specimen misidentification, even in an environment with careful adherence to stringent quality assurance practices. This study demonstrates that molecular auditing of random, routine biopsy specimens can identify occult misidentified specimens, and may function as a useful quality indicator.

Genomic DNA Methylation-Derived Algorithm Enables Accurate Detection of Malignant Prostate Tissues

Introduction

The current methodology involving diagnosis of prostate cancer (PCa) relies on the pathology examination of prostate needle biopsies, a method with high false negative rates partly due to temporospatial, molecular, and morphological heterogeneity of prostate adenocarcinoma. It is postulated that molecular markers have a potential to assign diagnosis to a considerable portion of undetected prostate tumors. This study examines the genome-wide DNA methylation changes in PCa in search of genomic markers for the development of a diagnostic algorithm for PCa screening.

Methods

Archival PCa and normal tissues were assessed using genomic DNA methylation arrays. Differentially methylated sites and regions (DMRs) were used for functional assessment, gene-set enrichment and protein interaction analyses, and examination of transcription factor-binding patterns. Raw signal intensity data were used for identification of recurrent copy number variations (CNVs). Non-redundant fully differentiating cytosine-phosphate-guanine sites (CpGs), which did not overlap CNV segments, were used in an L1 regularized logistic regression model (LASSO) to train a classification algorithm. Validation of this algorithm was performed using a large external cohort of benign and tumor prostate arrays.

Results

Approximately 6,000 probes and 600 genomic regions showed significant DNA methylation changes, primarily involving hypermethylation. Gene-set enrichment and protein interaction analyses found an overrepresentation of genes related to cell communications, neurogenesis, and proliferation. Motif enrichment analysis demonstrated enrichment of tumor suppressor-binding sites nearby DMRs. Several of these regions were also found to contain copy number amplifications. Using four non-redundant fully differentiating CpGs, we trained a classification model with 100% accuracy in discriminating tumors from benign samples. Validation of this algorithm using an external cohort of 234 tumors and 92 benign samples yielded 96% sensitivity and 98% specificity. The model was found to be highly sensitive to detect metastatic lesions in bone, lymph node, and soft tissue, while being specific enough to differentiate the benign hyperplasia of prostate from tumor.

Conclusion

A considerable component of PCa DNA methylation profile represent driver events potentially established/maintained by disruption of tumor suppressor activity. As few as four CpGs from this profile can be used for screening of PCa.

Specimen Provenance Testing Identifies Contamination That Affects Molecular Prognostic Assay Results in Prostate Cancer Biopsy Specimens

OBJECTIVE

To determine if tissue contamination in histologic specimens can significantly affect the results of prognostic molecular markers that are routinely used as confirmatory tests to safely assign appropriate candidates to prostate cancer active surveillance protocols.

MATERIALS AND METHODS

This study evaluates 2134 cases from a single, large urology practice that were successfully tested for DNA specimen provenance verification using short tandem repeat analysis for the presence of a significant level of contaminating DNA. After removal of the contamination, 5 of the samples were retested, and the results of the molecular diagnostic test were compared.

RESULTS

Forty-nine of the 2134 cases (2.3%) sent for DNA provenance analysis were found to possess significant levels of contamination. Of these 49 cases, 7 were resent for a repeat molecular diagnostic test after being decontaminated. Five of these prostate cancer specimens had sufficient tissue and RNA to give a more accurate cell cycle progression (CCP) score. The average absolute change in these patients' CCP scores was 0.48, with a minimum of 0.1-unit and a maximum of 1.0-unit difference. These changes in CCP scores are significant enough to cause meaningful alterations in a patient's calculated 10-year mortality rate, as defined by their combined risk score.

CONCLUSION

DNA contamination in unstained tissue sections sent for prognostic prostate cancer molecular diagnostic testing occurs in 2.3% of the cases, and can be of a magnitude that affects the results and subsequent clinical decision of appropriateness for active surveillance.

Pathology-related cases in the Norwegian System of Patient Injury Compensation in the period 2010-2015

BACKGROUND

The Norwegian System of Patient Injury Compensation (NPE) processes compensation claims from patients who complain about malpractice in the health services. A wrong diagnosis in pathology may cause serious injury to the patient, but the incidence of compensation claims is unknown, because pathology is not specified as a separate category in NPE’s statistics. Knowledge about errors is required to assess quality-enhancing measures. We have therefore searched through the NPE records to identify cases whose background stems from errors committed in pathology departments and laboratories.

MATERIAL AND METHOD

We have searched through the NPE records for cases related to pathology for the years 2010 – 2015.

RESULTS

During this period the NPE processed a total of 26 600 cases, of which 93 were related to pathology. The compensation claim was upheld in 66 cases, resulting in total compensation payments amounting to NOK 63 million. False-negative results in the form of undetected diagnoses were the most frequent grounds for compensation claims (63 cases), with an undetected malignant melanoma (n = 23) or atypia in cell samples from the cervix uteri (n = 16) as the major groups. Sixteen cases involved non-diagnostic issues such as mix-up of samples (n = 8), contamination of samples (n = 4) or delayed responses (n = 4).

INTERPRETATION

The number of compensation claims caused by errors in pathology diagnostics is low in relative terms. The errors may, however, be of a serious nature, especially if malignant conditions are overlooked or samples mixed up.

Application of a Clinical Whole-Transcriptome Assay for Staging and Prognosis of Prostate Cancer Diagnosed in Needle Core Biopsy Specimens

Molecular and genomic analysis of microscopic quantities of tumor from formalin-fixed, paraffin-embedded biopsy specimens has many unique challenges. Herein, we evaluated the feasibility of obtaining transcriptome-wide RNA expression to measure prognostic classifiers in diagnostic prostate needle core biopsy specimens. One-hundred fifty-eight samples from diagnostic needle core biopsy specimens (BX) and radical prostatectomies (RPs) were collected from 33 patients at three hospitals; each patient provided up to six tumor and benign samples. Genome-wide transcriptomic profiles were generated using Affymetrix Human Exon arrays for comparison of gene expression alterations and prognostic signatures between the BX and RP samples. A sufficient amount of RNA (>100 ng) was obtained from all RP specimens (n = 77) and from 72 of 81 of BX specimens. Of transcriptomic features detected in RP, 95% were detectable in BX tissues and demonstrated a high correlation (r = 0.96). Likewise, an expression signature pattern validated on RPs (Decipher prognostic test) showed correlation between BX and RP (r = 0.70). Of matched BX and RP pairs, 25% showed discordant molecular subtypes. Genome-wide exon arrays yielded data of comparable quality from biopsy and RP tissues. The high concordance of tumor-associated gene expression changes between BX and RP samples provides evidence for the adequate performance of the assay platform with samples from prostate needle biopsy specimens with limited tumor volume.