PATHWORK DIAGNOSTICS TISSUE OF ORIGIN TEST

The Pathwork® Tissue of Origin Test identifies the potential origin of a tumor by analyzing its RNA expression pattern using a microarray and comparing it to a database of 15 known cancer types. This molecular diagnostic tool provides a 'Similarity Score' to aid clinicians, complementing traditional pathological assessments by leveraging distinct gene expression profiles characteristic of different tumor tissues.

The Pathwork® Tissue of Origin Test is a diagnostic kit that employs microarray technology to assist in identifying the origin of cancerous tumors. Its primary function is to quantify the degree of similarity between the RNA expression pattern obtained from a patient's fresh-frozen tumor specimen and a comprehensive database of RNA expression patterns derived from 15 common malignant tumor types, which collectively represent 60 distinct morphologies. The process begins with the extraction, amplification, and labeling of mRNA from the tumor biopsy. This processed mRNA is then hybridized to the Pathchip® microarray. Following hybridization, the microarray is scanned, and the resulting data file is securely transmitted to the Pathwork® System Software. This software performs data quality control and analytical computations, culminating in a Tissue of Origin Test Report that provides a 'Similarity Score' for each of the 15 tissues in the panel, accessible via a secure website for clinical interpretation. The test's performance was evaluated through non-clinical and clinical studies. Reproducibility studies across four sites yielded an overall site-to-site concordance of approximately 93%. Clinical validation involving 545 frozen specimens demonstrated a positive percent agreement of 89.4% and a negative percent agreement of 99.6% with available diagnoses across all 15 tissue types. Studies on interfering substances indicated no significant impact from common biopsy components like adipose tissue, fibrous tissue, or necrotic tissue (up to 20% of the specimen), although performance was noted to be somewhat lower for pancreas-related specimens, likely due to higher RNase levels. It is crucial to note that the test is intended for use by qualified clinicians as an adjunct to existing clinical and pathological information and is not designed to establish the origin of tumors undiagnosable by current standards (e.g., carcinoma of unknown primary), subclassify tumors, predict disease course or treatment efficacy, or distinguish between primary and metastatic tumors.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. How does the proprietary algorithm within the Pathwork® System Software calculate the 'Similarity Score,' and what are the specific gene markers or expression patterns it weighs most heavily for each of the 15 profiled tumor types?; What is the recommended clinical pathway or further diagnostic steps if a tumor sample yields ambiguous Similarity Scores across multiple tissue types or a low score for all profiled tissues?; Could you provide a breakdown of the positive and negative percent agreement for each of the 15 individual tumor types, especially for those known to be histologically complex or for pancreatic specimens where RNase impact was noted?; How frequently is the reference database of tumor RNA expression patterns updated to reflect new research, evolving cancer classifications, or to potentially expand the range of tumor types covered?; What were the specific criteria for selecting the 60 morphologies represented by the 15 cancer types in the database, and how does the test account for intra-tumor heterogeneity in RNA expression?