- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06140992
PaCIFiC-CUP Classifies Cancer of Unknown Primary
April 22, 2026 updated by: Xiao-Peng Tian, Sun Yat-sen University
PaCIFiC-CUP:Pan-Cancer Integrated Fingerprinting Classifier for Identifying the Origin of Cancer of Unknown Primary: A Multi-Center Prospective Cohort Study
This study aims to initially utilize machine learning on pan-cancer DNA methylation data from public databases to construct a DNA methylation classification model (PaCIFiC-CUP, pan-cancer integrated fingerprinting classifier of CUP) for diagnosing various types of cancer, particularly the primary site of cancer of unknown primary.
The goal is to achieve diagnosis of cancer pathology type by analyzing the DNA methylation patterns of cancer specimens, thereby guiding subsequent precision treatment for cancer.
Study Overview
Status
Recruiting
Conditions
Study Type
Observational
Enrollment (Estimated)
120
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Yiyang Zhang
- Phone Number: +8615652797092
- Email: zhangyy@sysucc.org.cn
Study Locations
-
-
Guangdong
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Guangzhou, Guangdong, China, 510060
- Recruiting
- Sun Yat-sen University Cancer Center
-
Contact:
- Yiyang Zhang
- Phone Number: +8615652797092
- Email: zhangyy@sysucc.org.cn
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Sampling Method
Non-Probability Sample
Study Population
The study population consists of patients diagnosed with CUP who meet the inclusion and exclusion criteria.
Description
Inclusion Criteria:
- The patient specimens were obtained from the Sun Yat-sen University Cancer Center and affiliated cooperating centers, with written consent from the patients authorizing the use of the specimens for research purposes.
- Following standard assessments (medical history, physical examination, complete blood count, biochemistry, computed tomography scans of the neck, chest, abdomen, and pelvis, targeted evaluations of all symptomatic areas, pathology, and immunohistochemistry), the diagnosis was determined as a primary site unknown tumor (including adenocarcinoma, squamous cell carcinoma, undifferentiated carcinoma, neuroendocrine carcinoma, sarcoma, etc).
- The diagnosis was confirmed at the participating institution and the patient had received systemic therapy.
- Complete clinical, pathological, and follow-up data for the patients can be obtained.
- ECOG performance status score: 0-2 points.
Exclusion Criteria:
- Pregnant or lactating female patients.
- Tumor tissue sample size is too small (tumor tissue accounts for <70% in the biopsy or slice tissue).
- Organ transplant or history of non-autologous (allogeneic) bone marrow or stem cell transplantation.
- History of previous tumors, with the current condition being a recurrent tumor.
- Hematological malignancies (excluding lymphoma).
- Other diseases that may severely impact patient survival, such as severe cardiovascular or cerebrovascular diseases, sepsis, severe trauma or burns, etc.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
|---|
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Site-Specific Therapy Group
These patients with cancer of unknown primary received site-specific therapy that matched the particular site predicted by the DNA methylation classifier.
|
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Empirical Therapy Group
These patients with cancer of unknown primary received empirical therapy that didn't match the particular site predicted by the DNA methylation classifier.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Overall Survival
Time Frame: From date of diagnosis until the date of death from any cause, assessed up to 24 months
|
Overall survival refers to the length of time that a person lives after being diagnosed with cancer of unknown primary, without regard to any specific cause of death.
|
From date of diagnosis until the date of death from any cause, assessed up to 24 months
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Progression-Free Survival
Time Frame: From date of diagnosis until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 24 months
|
Progression-Free Survival refers to the length of time during which a patient with cancer of unknown primary remains alive without any signs or symptoms of disease progression
|
From date of diagnosis until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 24 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Kramer A, Bochtler T, Pauli C, Baciarello G, Delorme S, Hemminki K, Mileshkin L, Moch H, Oien K, Olivier T, Patrikidou A, Wasan H, Zarkavelis G, Pentheroudakis G, Fizazi K; ESMO Guidelines Committee. Electronic address: clinicalguidelines@esmo.org. Cancer of unknown primary: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol. 2023 Mar;34(3):228-246. doi: 10.1016/j.annonc.2022.11.013. Epub 2022 Dec 20. No abstract available.
- Paziewska A, Dabrowska M, Goryca K, Antoniewicz A, Dobruch J, Mikula M, Jarosz D, Zapala L, Borowka A, Ostrowski J. DNA methylation status is more reliable than gene expression at detecting cancer in prostate biopsy. Br J Cancer. 2014 Aug 12;111(4):781-9. doi: 10.1038/bjc.2014.337. Epub 2014 Jun 17.
- Wehmas LC, Hester SD, Wood CE. Direct formalin fixation induces widespread transcriptomic effects in archival tissue samples. Sci Rep. 2020 Sep 2;10(1):14497. doi: 10.1038/s41598-020-71521-w.
- Capper D, Jones DTW, Sill M, Hovestadt V, Schrimpf D, Sturm D, Koelsche C, Sahm F, Chavez L, Reuss DE, Kratz A, Wefers AK, Huang K, Pajtler KW, Schweizer L, Stichel D, Olar A, Engel NW, Lindenberg K, Harter PN, Braczynski AK, Plate KH, Dohmen H, Garvalov BK, Coras R, Holsken A, Hewer E, Bewerunge-Hudler M, Schick M, Fischer R, Beschorner R, Schittenhelm J, Staszewski O, Wani K, Varlet P, Pages M, Temming P, Lohmann D, Selt F, Witt H, Milde T, Witt O, Aronica E, Giangaspero F, Rushing E, Scheurlen W, Geisenberger C, Rodriguez FJ, Becker A, Preusser M, Haberler C, Bjerkvig R, Cryan J, Farrell M, Deckert M, Hench J, Frank S, Serrano J, Kannan K, Tsirigos A, Bruck W, Hofer S, Brehmer S, Seiz-Rosenhagen M, Hanggi D, Hans V, Rozsnoki S, Hansford JR, Kohlhof P, Kristensen BW, Lechner M, Lopes B, Mawrin C, Ketter R, Kulozik A, Khatib Z, Heppner F, Koch A, Jouvet A, Keohane C, Muhleisen H, Mueller W, Pohl U, Prinz M, Benner A, Zapatka M, Gottardo NG, Driever PH, Kramm CM, Muller HL, Rutkowski S, von Hoff K, Fruhwald MC, Gnekow A, Fleischhack G, Tippelt S, Calaminus G, Monoranu CM, Perry A, Jones C, Jacques TS, Radlwimmer B, Gessi M, Pietsch T, Schramm J, Schackert G, Westphal M, Reifenberger G, Wesseling P, Weller M, Collins VP, Blumcke I, Bendszus M, Debus J, Huang A, Jabado N, Northcott PA, Paulus W, Gajjar A, Robinson GW, Taylor MD, Jaunmuktane Z, Ryzhova M, Platten M, Unterberg A, Wick W, Karajannis MA, Mittelbronn M, Acker T, Hartmann C, Aldape K, Schuller U, Buslei R, Lichter P, Kool M, Herold-Mende C, Ellison DW, Hasselblatt M, Snuderl M, Brandner S, Korshunov A, von Deimling A, Pfister SM. DNA methylation-based classification of central nervous system tumours. Nature. 2018 Mar 22;555(7697):469-474. doi: 10.1038/nature26000. Epub 2018 Mar 14.
- Koelsche C, Schrimpf D, Stichel D, Sill M, Sahm F, Reuss DE, Blattner M, Worst B, Heilig CE, Beck K, Horak P, Kreutzfeldt S, Paff E, Stark S, Johann P, Selt F, Ecker J, Sturm D, Pajtler KW, Reinhardt A, Wefers AK, Sievers P, Ebrahimi A, Suwala A, Fernandez-Klett F, Casalini B, Korshunov A, Hovestadt V, Kommoss FKF, Kriegsmann M, Schick M, Bewerunge-Hudler M, Milde T, Witt O, Kulozik AE, Kool M, Romero-Perez L, Grunewald TGP, Kirchner T, Wick W, Platten M, Unterberg A, Uhl M, Abdollahi A, Debus J, Lehner B, Thomas C, Hasselblatt M, Paulus W, Hartmann C, Staszewski O, Prinz M, Hench J, Frank S, Versleijen-Jonkers YMH, Weidema ME, Mentzel T, Griewank K, de Alava E, Martin JD, Gastearena MAI, Chang KT, Low SYY, Cuevas-Bourdier A, Mittelbronn M, Mynarek M, Rutkowski S, Schuller U, Mautner VF, Schittenhelm J, Serrano J, Snuderl M, Buttner R, Klingebiel T, Buslei R, Gessler M, Wesseling P, Dinjens WNM, Brandner S, Jaunmuktane Z, Lyskjaer I, Schirmacher P, Stenzinger A, Brors B, Glimm H, Heining C, Tirado OM, Sainz-Jaspeado M, Mora J, Alonso J, Del Muro XG, Moran S, Esteller M, Benhamida JK, Ladanyi M, Wardelmann E, Antonescu C, Flanagan A, Dirksen U, Hohenberger P, Baumhoer D, Hartmann W, Vokuhl C, Flucke U, Petersen I, Mechtersheimer G, Capper D, Jones DTW, Frohling S, Pfister SM, von Deimling A. Sarcoma classification by DNA methylation profiling. Nat Commun. 2021 Jan 21;12(1):498. doi: 10.1038/s41467-020-20603-4.
- Hovestadt V, Remke M, Kool M, Pietsch T, Northcott PA, Fischer R, Cavalli FM, Ramaswamy V, Zapatka M, Reifenberger G, Rutkowski S, Schick M, Bewerunge-Hudler M, Korshunov A, Lichter P, Taylor MD, Pfister SM, Jones DT. Robust molecular subgrouping and copy-number profiling of medulloblastoma from small amounts of archival tumour material using high-density DNA methylation arrays. Acta Neuropathol. 2013 Jun;125(6):913-6. doi: 10.1007/s00401-013-1126-5. Epub 2013 May 14. No abstract available.
- Pajtler KW, Witt H, Sill M, Jones DT, Hovestadt V, Kratochwil F, Wani K, Tatevossian R, Punchihewa C, Johann P, Reimand J, Warnatz HJ, Ryzhova M, Mack S, Ramaswamy V, Capper D, Schweizer L, Sieber L, Wittmann A, Huang Z, van Sluis P, Volckmann R, Koster J, Versteeg R, Fults D, Toledano H, Avigad S, Hoffman LM, Donson AM, Foreman N, Hewer E, Zitterbart K, Gilbert M, Armstrong TS, Gupta N, Allen JC, Karajannis MA, Zagzag D, Hasselblatt M, Kulozik AE, Witt O, Collins VP, von Hoff K, Rutkowski S, Pietsch T, Bader G, Yaspo ML, von Deimling A, Lichter P, Taylor MD, Gilbertson R, Ellison DW, Aldape K, Korshunov A, Kool M, Pfister SM. Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups. Cancer Cell. 2015 May 11;27(5):728-43. doi: 10.1016/j.ccell.2015.04.002.
- Sturm D, Orr BA, Toprak UH, Hovestadt V, Jones DTW, Capper D, Sill M, Buchhalter I, Northcott PA, Leis I, Ryzhova M, Koelsche C, Pfaff E, Allen SJ, Balasubramanian G, Worst BC, Pajtler KW, Brabetz S, Johann PD, Sahm F, Reimand J, Mackay A, Carvalho DM, Remke M, Phillips JJ, Perry A, Cowdrey C, Drissi R, Fouladi M, Giangaspero F, Lastowska M, Grajkowska W, Scheurlen W, Pietsch T, Hagel C, Gojo J, Lotsch D, Berger W, Slavc I, Haberler C, Jouvet A, Holm S, Hofer S, Prinz M, Keohane C, Fried I, Mawrin C, Scheie D, Mobley BC, Schniederjan MJ, Santi M, Buccoliero AM, Dahiya S, Kramm CM, von Bueren AO, von Hoff K, Rutkowski S, Herold-Mende C, Fruhwald MC, Milde T, Hasselblatt M, Wesseling P, Rossler J, Schuller U, Ebinger M, Schittenhelm J, Frank S, Grobholz R, Vajtai I, Hans V, Schneppenheim R, Zitterbart K, Collins VP, Aronica E, Varlet P, Puget S, Dufour C, Grill J, Figarella-Branger D, Wolter M, Schuhmann MU, Shalaby T, Grotzer M, van Meter T, Monoranu CM, Felsberg J, Reifenberger G, Snuderl M, Forrester LA, Koster J, Versteeg R, Volckmann R, van Sluis P, Wolf S, Mikkelsen T, Gajjar A, Aldape K, Moore AS, Taylor MD, Jones C, Jabado N, Karajannis MA, Eils R, Schlesner M, Lichter P, von Deimling A, Pfister SM, Ellison DW, Korshunov A, Kool M. New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs. Cell. 2016 Feb 25;164(5):1060-1072. doi: 10.1016/j.cell.2016.01.015.
- Pisanic TR 2nd, Wang Y, Sun H, Considine M, Li L, Wang TH, Wang TL, Shih IM. Methylomic Landscapes of Ovarian Cancer Precursor Lesions. Clin Cancer Res. 2020 Dec 1;26(23):6310-6320. doi: 10.1158/1078-0432.CCR-20-0270. Epub 2020 Aug 17.
- Muller D, Gyorffy B. DNA methylation-based diagnostic, prognostic, and predictive biomarkers in colorectal cancer. Biochim Biophys Acta Rev Cancer. 2022 May;1877(3):188722. doi: 10.1016/j.bbcan.2022.188722. Epub 2022 Mar 17.
- Liu MC, Oxnard GR, Klein EA, Swanton C, Seiden MV; CCGA Consortium. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020 Jun;31(6):745-759. doi: 10.1016/j.annonc.2020.02.011. Epub 2020 Mar 30.
- Nunes SP, Moreira-Barbosa C, Salta S, Palma de Sousa S, Pousa I, Oliveira J, Soares M, Rego L, Dias T, Rodrigues J, Antunes L, Henrique R, Jeronimo C. Cell-Free DNA Methylation of Selected Genes Allows for Early Detection of the Major Cancers in Women. Cancers (Basel). 2018 Sep 26;10(10):357. doi: 10.3390/cancers10100357.
- Moran S, Martinez-Cardus A, Sayols S, Musulen E, Balana C, Estival-Gonzalez A, Moutinho C, Heyn H, Diaz-Lagares A, de Moura MC, Stella GM, Comoglio PM, Ruiz-Miro M, Matias-Guiu X, Pazo-Cid R, Anton A, Lopez-Lopez R, Soler G, Longo F, Guerra I, Fernandez S, Assenov Y, Plass C, Morales R, Carles J, Bowtell D, Mileshkin L, Sia D, Tothill R, Tabernero J, Llovet JM, Esteller M. Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis. Lancet Oncol. 2016 Oct;17(10):1386-1395. doi: 10.1016/S1470-2045(16)30297-2. Epub 2016 Aug 27.
- Zhang Z, Lu Y, Vosoughi S, Levy JJ, Christensen BC, Salas LA. HiTAIC: hierarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation. NAR Cancer. 2023 Apr 19;5(2):zcad017. doi: 10.1093/narcan/zcad017. eCollection 2023 Jun.
- Greco FA, Lennington WJ, Spigel DR, Hainsworth JD. Molecular profiling diagnosis in unknown primary cancer: accuracy and ability to complement standard pathology. J Natl Cancer Inst. 2013 Jun 5;105(11):782-90. doi: 10.1093/jnci/djt099. Epub 2013 May 2.
- Maros ME, Capper D, Jones DTW, Hovestadt V, von Deimling A, Pfister SM, Benner A, Zucknick M, Sill M. Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data. Nat Protoc. 2020 Feb;15(2):479-512. doi: 10.1038/s41596-019-0251-6. Epub 2020 Jan 13.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
July 1, 2023
Primary Completion (Estimated)
December 31, 2026
Study Completion (Estimated)
December 31, 2026
Study Registration Dates
First Submitted
November 14, 2023
First Submitted That Met QC Criteria
November 20, 2023
First Posted (Actual)
November 21, 2023
Study Record Updates
Last Update Posted (Actual)
April 23, 2026
Last Update Submitted That Met QC Criteria
April 22, 2026
Last Verified
April 1, 2026
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- PaCIFiC-CUP
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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