Complete genomic characterization in patients with cancer of unknown primary origin in routine diagnostics

L. J. Schipper, K. G. Samsom, P. Snaebjornsson, T. Battaglia, L. J.W. Bosch, F. Lalezari, P. Priestley, C. Shale, A. J. van den Broek, N. Jacobs, P. Roepman, J. J.M. van der Hoeven, N. Steeghs, M. A. Vollebergh, S. Marchetti, E. Cuppen, G. A. Meijer, E. E. Voest, K. Monkhorst*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Background: In ∼3%-5% of patients with metastatic disease, tumor origin remains unknown despite modern imaging techniques and extensive pathology work-up. With long diagnostic delays and limited and ineffective therapy options, the clinical outcome of patients with cancer of unknown primary (CUP) remains poor. Large-scale genome sequencing studies have revealed that tumor types can be predicted based on distinct patterns of somatic variants and other genomic characteristics. Moreover, actionable genomic events are present in almost half of CUP patients. This study investigated the clinical value of whole genome sequencing (WGS) in terms of primary tumor identification and detection of actionable events, in the routine diagnostic work-up of CUP patients. Patients and methods: A WGS-based tumor type ‘cancer of unknown primary prediction algorithm’ (CUPPA) was developed based on previously described principles and validated on a large pan-cancer WGS database of metastatic cancer patients (>4000 samples) and 254 independent patients, respectively. We assessed the clinical value of this prediction algorithm as part of routine WGS-based diagnostic work-up for 72 CUP patients. Results: CUPPA correctly predicted the primary tumor type in 78% of samples in the independent validation cohort (194/254 patients). High-confidence predictions (>95% precision) were obtained for 162/254 patients (64%). When integrated in the diagnostic work-up of CUP patients, CUPPA could identify a primary tumor type for 49/72 patients (68%). Most common diagnoses included non-small-cell lung (n = 7), gastroesophageal (n = 4), pancreatic (n = 4), and colorectal cancer (n = 3). Actionable events with matched therapy options in clinical trials were identified in 47% of patients. Conclusions: Genome-based tumor type prediction can predict cancer diagnoses with high accuracy when integrated in the routine diagnostic work-up of patients with metastatic cancer. With identification of the primary tumor type in the majority of patients and detection of actionable events, WGS is a valuable diagnostic tool for patients with CUP.

Original languageEnglish
Article number100611
JournalESMO Open
Issue number6
Publication statusPublished - Dec 2022

Bibliographical note

Funding Information:
This work was supported by ZonMw , the Netherlands Organization for Health Research and Development (Project Number 446002004) as part of the WIDE study, including an in-kind contribution of Hartwig Medical Foundation (no grant number) . The study protocol has been independently peer-reviewed by ZonMw. ZonMw had no role in the design nor the collection, analysis, and interpretation of the data, nor the writing of the manuscript.

Publisher Copyright:
© 2022 The Author(s)

Other keywords

  • cancer of unknown primary
  • diagnostic tool
  • tumor type prediction
  • whole genome sequencing


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