Validation of a transcriptome-based assay for classifying cancers of unknown primary origin

Abstract

Cancers assume a variety of distinct histologies and may originate from a myriad of sites including solid organs, hematopoietic cells, and connective tissue. Clinical decision making based on consensus guidelines such as NCCN is often predicated on a specific histologic and anatomic diagnosis, supported by clinical features and pathologist interpretation of morphology and immunohistochemical (IHC) staining patterns. However, in patients with nonspecific morphologic and IHC findings—in addition to ambiguous clinical presentations such as recurrence versus new primary—a definitive diagnosis may not be possible, resulting in the patient being categorized as having a cancer of unknown primary (CUP). Therapeutic options and clinical outcomes are poor for CUP patients, with a median survival of 8-11 months. Here we describe and validate the Tempus Tumor Origin (Tempus TO) assay, an RNA-seq-based machine learning classifier capable of discriminating between 68 clinically relevant cancer subtypes. We show that the Tempus TO model is 91% accurate when assessed on retrospectively and prospectively held out cohorts of containing 9,210 samples with known diagnoses. When evaluated on a cohort of CUPs, the model recapitulated established associations between genomic alterations and cancer subtype. Combining diagnostic prediction tests (e.g., Tempus TO) with sequencing-based variant reporting (e.g., Tempus xT) may expand therapeutic options for patients with cancers of unknown primary or uncertain histology.

Utility of RNA Expression to Determine the Tissue of Origin of Malignancies with an Inconclusive Histopathology

“…The origin testing platform used in the cases above utilizes a machine learning RNA-based molecular cancer classifier to identify the most likely cancer type from multiple possible cancer types with an accuracy of over 90% [18]. A retrospective study analyzed 289 patients with CUP diagnosis and revealed that cholangiocarcinoma, lung adenocarcinoma, and pancreatic adenocarcinoma were the most common cancer types, as predicted by the origin testing algorithm, and this led to an alteration in therapeutic decision-making in over 80% of the patients [19].…”

Real-world data validation of the PurIST pancreatic ductal adenocarcinoma gene expression classifier and its prognostic implications

“…The assay also evaluates transcriptomic alterations from whole-transcriptome RNA sequencing data, including variations in gene expression, altered splicing, and fusions. Sample preparation, DNA sequencing, and RNA sequencing were conducted as described (Leibowitz et al 2022; Michuda et al 2022).…”

Assessing the utility of molecular diagnostic classification for cancers of unknown primary

“…The Tempus TO test is a CAP/CLIA validated molecular diagnostic classifier that uses whole‐exome capture RNA‐seq data as input to provide diagnostic predictions from 68 possible subtypes. The model was trained on 43,726 tumor samples of known origin and has an overall accuracy of 91% based on an independent validation cohort consisting of 9210 tumor samples 11 . For individual patient records, results are reported with one or more predicted diagnoses including the probability that the sample belongs to the given label.…”

“…[8][9][10] The Tempus Tumor Origin (TO) test uses RNA expression data to select from 68 possible histological subtypes and showed a 91% classification accuracy when applied to an independent validation set of samples with known primary. 11 A limited number of studies have evaluated the clinical utility of tissue-of-origin diagnosis via molecular diagnostic classifier in the setting of CUP owing to methodological challenges with studying this population. 12 Several randomized studies have found no significant difference in CUP patient outcomes according to whether they received tissue-specific or empiric therapies, 13,14 while another showed that patients receiving tissue-specific therapies have improved outcomes.…”

“…Numerous assays that rely on either genomic profiling, microRNA expression, DNA methylation, transcriptome expression, or some combination of these data sources have been developed to aid in diagnosing the tissue of origin for CUP patients 8–10 . The Tempus Tumor Origin (TO) test uses RNA expression data to select from 68 possible histological subtypes and showed a 91% classification accuracy when applied to an independent validation set of samples with known primary 11 …”