16 juli 2025: Bron: Scientific Reports volume 15, Article number: 21173 (2025)

De Caris Assure® bloedtest van Caris Life Sciences meet en ontdekt nauwkeurig de aanwezigheid van kankercellen in het bloedplasma van verschillende vormen van kanker in alle stadia van stadium I t/m IV met een nauwkeurigheid van 83 tot 96 procent met een gevoeligheid en specificiteit van 100 procent. Ook de persoonlijke behandelingsmogelijkheden (personalised medicin) werden zeer nauwkeurig voorspelt.

Dat blijkt uit een studierapport gepubliceerd in Nature d.d. 1 juli 2025.

Hier het persbericht van Caris Life Sciences vertaalt met hulp van google translate:

Nieuwe studie toont de kracht en klinische bruikbaarheid aan van de Caris Assure® bloedgebaseerde assay voor vroege detectie van meerdere vormen van kanker, minimale restziekte en therapiekeuze.

Het Caris Assure®-platform is een baanbrekende, enkelvoudige assay die uitgebreide, zeer geavanceerde moleculaire profilering van meer dan 23.000 genen in DNA en RNA in bloedplasma combineert. Dit zet een nieuwe standaard voor op bloedgebaseerde testen en verbetert het management van de kankerzorg. Bovendien volgt Caris DNA in de "buffy coat", de laag gecentrifugeerd bloed tussen de rode bloedcellen en het plasma, die witte bloedcellen en bloedplaatjes bevat.
Caris Assure combineert Whole Exome Sequencing (WES) en Whole Transcriptome Sequencing (WTS) met geavanceerde machine learning (red: machine learning is een onderdeel dat aangestuurd wordt via AI = Kunstmatige Intelligentie) op één platform.
Caris Assure® wordt momenteel gebruikt voor therapiekeuze en maakt nauwkeurige vroege detectie en zeer gevoelige ziektemonitoring mogelijk.

"We hebben Caris Assure® ontworpen om meer te zijn dan een vloeibare biopsietest. Deze test maakt gebruik van geavanceerde sequencing- en computertechnologie om genetische informatie te verzamelen die beschikbaar is uit het volledige exoom en het volledige transcriptoom van het tumormateriaal dat in het bloed circuleert, en DNA van de witte bloedcellen van de patiënt", aldus David Spetzler, MS, PhD, MBA, directeur van Caris. "Dit stelt ons in staat om een zeer uitgebreid, individueel beeld te schetsen van de specifieke ziektetoestand van een patiënt. Dit is de eerste keer dat zoveel moleculaire informatie beschikbaar is via één enkele bloedtest, wat zorgt voor een grotere nauwkeurigheid en aanvullende inzichten die artsen kunnen helpen bij het nemen van beslissingen over kankerzorg."

Het Caris Assure® vloeibare biopsieplatform, aangestuurd door de Assure Blood-based Cancer Detection AI (ABCDai), is getraind met meer dan 376.000 volledige exoom- en volledige transcriptoomweefselprofielen en meer dan 7.000 gematchte bloed- en weefselmonsters.

  1. Naast de therapiekeuze valideert de studie de prestaties van Caris Assure® in: vroege ontdekking van meerdere kankersoorten (MCED): Bereikte een gevoeligheid van 83,1% tot 95,7% voor kankerstadia I-IV met een gevoeligheid en specificiteit van 99,6%.
  2. Voorspeller van het diagnostisch pad: Nauwkeurige identificatie van het diagnostisch pad voor MCED-positieve vormen van kanker met behulp van het ABCDai-GPS-model.
  3. MRD en recidiefmonitoring: Aangetoonde statistisch significante voorspellende waarde voor een recidief, met hazard ratio's van 33,4 (p < 0,005) voor MRD en 4,39 (p = 0,008) voor therapeutische monitoring.

Caris Assure® vereist geen voorafgaande weefselbiopsie. In plaats daarvan identificeert het AI-model tumorgerelateerde signalen op basis van patronen die zijn geleerd van honderdduizenden tumoren. Dit maakt een weefselonafhankelijke, zeer gevoelige benadering van kankerdetectie en -monitoring mogelijk.

Hoewel Caris Assure® momenteel commercieel beschikbaar is voor therapieselectie bij gevorderde kankers, legt deze studie de basis voor uitbreiding naar vroege detectie, MRD en therapeutische monitoring. Caris is actief bezig met het zoeken naar vergoedings- en regelgevingstrajecten om deze toepassingen op de markt te brengen.
"Dit is meer dan een validatiestudie; het is een blauwdruk voor de toekomst van kankerdiagnostiek", voegde David Spetzler eraan toe. "Ons doel is om een naadloos ecosysteem te creëren waar patiënten en clinici gedurende het hele kankertraject op één platform kunnen vertrouwen."

Het originele persbericht waarop bovenstaande vertaling is gemaakt is te lezen via deze link: 

Caris Life Sciences Announces New Study Demonstrating the Power and Clinical Utility of its Caris Assure® Blood-Based Assay for Multi-Cancer Early Detection, Minimal Residual Disease and Therapy Selection

Het volledige studierapport gepubliceert in Nature is gratis in te zien of te downloaden. Klik daarvoor op de titel van het abstract:

Validation of an AI-enabled exome/transcriptome liquid biopsy platform for early detection, MRD, disease monitoring, and therapy selection for solid tumors

Scientific Reports volume 15, Article number: 21173 (2025) Cite this article

Abstract

  • Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring of disease burden.
  • Caris Assure is a multifunctional blood-based assay that couples whole exome and whole transcriptome sequencing on plasma and leukocytes with advanced machine learning techniques to satisfy all three clinical testing needs on one platform.
  • Caris Assure for therapy selection was CLIA validated using 1,910 samples. 376,197 tissue profiles along with 7,061 paired blood and tissue profiles were used to engineer features for three machine learning models.
  • The MCED model was trained on 1,013 patients and validated on an independent set of 2,675 patients. The tissue of origin for MCED model was trained on 1,166 samples and validated using 5-fold cross validation.
  • The MRD & Monitoring model was trained on 3,439 patients and validated on two independent sets of 86 patients for MRD and 101 patients for monitoring.
  • For early detection, sensitivities for stages I-IV cancers (n = 284, 129, 90, 23 respectively) were 83.1%, 86.0%, 84.4%, and 95.7%, all at 99.6% specificity (n = 2149).
  • The diagnostic first-line procedure for tissue of origin was determined for 8 categories with a top-3 accuracy of 85% for stage I and II cancers.
  • Detection of driver mutations for therapy selection from blood collected within 30 days of matched tumor tissue, demonstrated high concordance (PPA of 93.8%, PPV of 96.8%) using CHIP subtraction.
  • For MRD and recurrence monitoring, the disease-free survival of patients whose cancers were predicted to have an event was significantly shorter than those predicted not to have an event using a tumor naïve approach (HR = 33.4, p < 0.005, HR = 4.39, p = 0.008, respectively).
  • The data presented here demonstrate a unified liquid biopsy platform that uses blood-based whole-exome and transcriptome sequencing coupled with artificial intelligence to address the important clinical needs in multi-cancer early detection, monitoring of MRD and recurrent cancers, and precision selection of molecularly targeted therapies.

Funding

This work was supported by Caris Life Sciences.

Author information

Author notes

  1. These authors jointly supervised this work: J. Abraham and V. Domenyuk.

Authors and Affiliations

  1. Caris Life Sciences, 350 W. Washington St, Irving, TX, 85281, USA

    J. Abraham, V. Domenyuk, N. Perdigones, S. Klimov, S. Antani, J. Xiu, D. A. Sacchetti, S. Stahl, R. Hahn-Lowry, A. Stark, J. Swensen, D. D. Halbert, M. Oberley, M. Radovich, G. W. Sledge & David B. Spetzler

  2. National Cancer Center Hospital East, Chiba, Japan

    T. Yoshino, Y. Nakamura & T. Fujisawa

  3. Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA

    E. I. Heath & A. F. Shields

  4. University of Minnesota, Minneapolis, MN, USA

    E. Lou

  5. Lombardi Comprehensive Cancer Center, Washington, D.C., DC, United States

    S. V. Liu & J. L. Marshall

  6. Brown University, Providence, RI, USA

    W. S. El-Deiry

  7. Oncology Network, Orlando, FL, US

    M. F. Dietrich

  8. Dana-Farber Cancer Institute and Ludwig Center, Harvard Medical School, Boston, MA, United States

    G. D. Demetri

  9. Arizona State University, Phoenix, AZ, USA

    A. Barker & G. Poste

Contributions

JA, VD, JX, RH, MO, MR, GS, and DS wrote the main manuscript text. SK and SA produced main figures. JS, VD, MPB, DS, SS, AS, DH, MO and DS developed the assay. TY, EH, EL, SL, JM, WE, AS, MD, YN, TF, GD, AB, JS, GP advised on study design, data interpretation, and clinical impact.

Corresponding author

Correspondence to David B. Spetzler.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics statement

Disclosure of Potential Conflicts of Interest: JA, VD, NP, SK, SA, JX, DAS, SS, RH, AS, JS, DDH, MO, MR, GWS and DS are employees of Caris Life Sciences. GP is a member of the board of directors of CLS. JLM, GDD, and AB serve on the scientific advisory board of Caris Life Sciences. All of the above have equity and/or equity options in Caris Life Sciences. EH, EL, SVL, and WSE have unpaid consultant/advisory board relationships with Caris Life Sciences. AFS serves on the consultant/advisory board, is on the speaker’s bureau, and has received travel funding from Caris Life Sciences.All the remaining authors declare no conflict of interestSVL reports advisory role for Abbvie, Amgen, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Catalyst, Daiichi Sankyo, Eisai, Elevation Oncology, Genentech/Roche, Gilead, Guardant Health, Janssen, Jazz Pharmaceuticals, Merck, Merus, Mirati, Novartis, Pfizer, Regeneron, Sanofi, Takeda, and Turning Point Therapeutics; research grant (to institution) from Abbvie, Alkermes, Elevation Oncology, Ellipses, Genentech, Gilead, Merck, Merus, Nuvalent, RAPT, and Turning Point Therapeutics; and serving on a Data Safety Monitoring Board for Candel Therapeutics.YN reports advisory role from Guardant Health Pte Ltd., Natera, Inc., Roche Ltd., Seagen, Inc., Premo Partners, Inc., Daiichi Sankyo Co., Ltd., Takeda Pharmaceutical Co., Ltd., Exact Sciences Corporation, Gilead Sciences, Inc.; speakers’ bureau from Guardant Health Pte Ltd., MSD K.K., Eisai Co., Ltd., Zeria Pharmaceutical Co., Ltd., Miyarisan Pharmaceutical Co., Ltd., Merck Biopharma Co., Ltd., CareNet, Inc., Hisamitsu Pharmaceutical Co., Inc., Taiho Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Chugai Pharmaceutical Co., Ltd., Becton, Dickinson and Company, Guardant Health Japan Corp; research funding from Seagen, Inc., Genomedia Inc., Guardant Health AMEA, Inc., Guardant Health, Inc., Tempus Labs, Inc., Roche Diagnostics K.K., Daiichi Sankyo Co., Ltd., Chugai Pharmaceutical Co., Ltd.TY research funding from Amgen K.K., Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Eisai Co., Ltd., FALCO biosystems Ltd., Genomedia Inc., Molecular Health GmbH, MSD K.K., Nippon Boehringer Ingelheim Co., Ltd., Ono Pharmaceutical Co., Ltd., Pfizer Japan Inc., Roche Diagnostics K.K., Sanofi K.K., Sysmex Corp. and Taiho Pharmaceutical Co., Ltd.; honoraria for lectures from Chugai Pharmaceutical Co., Ltd., MSD K.K., Ono Pharmaceutical Co., Ltd., Bayer Yakuhin, Ltd., Merck Biopharma Co., Ltd. and Takeda Pharmaceutical Co., Ltd.; Consulting fees from Sumitomo Corp.GDD has received institutional support for oncology research studies to Dana-Farber Cancer Institute from Adaptimmune, Bayer, Novartis, PharmaMar, and Daiichi-Sankyo; he is also is a co-founder and consulting scientific advisory board member with minor equity holding in IDRx; a consultant/SAB member with minor equity holding in Erasca Pharmaceuticals, RELAY Therapeutics, Bessor Pharmaceuticals, CellCarta, Ikena Oncology, Kojin Therapeutics, Aadi Biosciences, Acrivon Therapeutics, Blueprint Medicines, Tessellate Bio, and Boundless Bio; he is also a scientific consultant for EMD-Serono/Merck KGaA, WCG/Arsenal Capital, and Minghui Pharmaceuticals.

SVL reports advisory role for Abbvie, Amgen, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Catalyst, Daiichi Sankyo, Eisai, Elevation Oncology, Genentech/Roche, Gilead, Guardant Health, Janssen, Jazz Pharmaceuticals, Merck, Merus, Mirati, Novartis, Pfizer, Regeneron, Sanofi, Takeda, and Turning Point Therapeutics; research grant (to institution) from Abbvie, Alkermes, Elevation Oncology, Ellipses, Genentech, Gilead, Merck, Merus, Nuvalent, RAPT, and Turning Point Therapeutics; and serving on a Data Safety Monitoring Board for Candel Therapeutics.YN reports advisory role from Guardant Health Pte Ltd., Natera, Inc., Roche Ltd., Seagen, Inc., Premo Partners, Inc., Daiichi Sankyo Co., Ltd., Takeda Pharmaceutical Co., Ltd., Exact Sciences Corporation, Gilead Sciences, Inc.; speakers’ bureau from Guardant Health Pte Ltd., MSD K.K., Eisai Co., Ltd., Zeria Pharmaceutical Co., Ltd., Miyarisan Pharmaceutical Co., Ltd., Merck Biopharma Co., Ltd., CareNet, Inc., Hisamitsu Pharmaceutical Co., Inc., Taiho Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Chugai Pharmaceutical Co., Ltd., Becton, Dickinson and Company, Guardant Health Japan Corp; research funding from Seagen, Inc., Genomedia Inc., Guardant Health AMEA, Inc., Guardant Health, Inc., Tempus Labs, Inc., Roche Diagnostics K.K., Daiichi Sankyo Co., Ltd., Chugai Pharmaceutical Co., Ltd.

TY research funding from Amgen K.K., Chugai Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Eisai Co., Ltd., FALCO biosystems Ltd., Genomedia Inc., Molecular Health GmbH, MSD K.K., Nippon Boehringer Ingelheim Co., Ltd., Ono Pharmaceutical Co., Ltd., Pfizer Japan Inc., Roche Diagnostics K.K., Sanofi K.K., Sysmex Corp. and Taiho Pharmaceutical Co., Ltd.; honoraria for lectures from Chugai Pharmaceutical Co., Ltd., MSD K.K., Ono Pharmaceutical Co., Ltd., Bayer Yakuhin, Ltd., Merck Biopharma Co., Ltd. and Takeda Pharmaceutical Co., Ltd.; Consulting fees from Sumitomo Corp.

GDD has received institutional support for oncology research studies to Dana-Farber Cancer Institute from Adaptimmune, Bayer, Novartis, PharmaMar, and Daiichi-Sankyo; he is also is a co-founder and consulting scientific advisory board member with minor equity holding in IDRx; a consultant/SAB member with minor equity holding in Erasca Pharmaceuticals, RELAY Therapeutics, Bessor Pharmaceuticals, CellCarta, Ikena Oncology, Kojin Therapeutics, Aadi Biosciences, Acrivon Therapeutics, Blueprint Medicines, Tessellate Bio, and Boundless Bio; he is also a scientific consultant for EMD-Serono/Merck KGaA, WCG/Arsenal Capital, and Minghui Pharmaceuticals.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Supplementary Material 3

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abraham, J., Domenyuk, V., Perdigones, N. et al. Validation of an AI-enabled exome/transcriptome liquid biopsy platform for early detection, MRD, disease monitoring, and therapy selection for solid tumors. Sci Rep 15, 21173 (2025). https://doi.org/10.1038/s41598-025-08986-0

References

  1. Sanchez-Vega, F. et al. Oncogenic signaling pathways in the Cancer genome atlas. Cell 173 (2), 321–337e10. https://doi.org/10.1016/j.cell.2018.03.035 (2018).

    Article CAS PubMed PubMed Central Google Scholar 

  2. NCCN. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Non-Small Cell Lung Cancer Version 1.2024.

  3. Chakravarty, D. et al. Somatic genomic testing in patients with metastatic or advanced cancer: ASCO provisional clinical opinion. J. Clin. Oncol. Off J. Am. Soc. Clin. Oncol. 40 (11), 1231–1258. https://doi.org/10.1200/JCO.21.02767 (2022).

    Article CAS Google Scholar 

  4. Mosele, F. et al. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO precision medicine working group. Ann. Oncol. Off J. Eur. Soc. Med. Oncol. 31 (11), 1491–1505. https://doi.org/10.1016/j.annonc.2020.07.014 (2020).

    Article CAS Google Scholar 

  5. Le, D. T. et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 Blockade. Science 357 (6349), 409–413. https://doi.org/10.1126/science.aan6733 (2017).

    Article CAS PubMed PubMed Central Google Scholar 

  6. Abraham, J. et al. Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type. Transl Oncol. 14 (3), 101016. https://doi.org/10.1016/j.tranon.2021.101016 (2021).

    Article MathSciNet CAS PubMed PubMed Central Google Scholar 

  7. Wang, J. et al. Mutational analysis of microsatellite-stable Gastrointestinal cancer with high tumour mutational burden: a retrospective cohort study. Lancet Oncol. 24 (2), 151–161. https://doi.org/10.1016/S1470-2045(22)00783-5 (2023).

    Article PubMed PubMed Central Google Scholar 

  8. Rolfo, C. et al. Liquid biopsy for advanced NSCLC: A consensus statement from the international association for the study of lung Cancer. J. Thorac. Oncol. Off Publ Int. Assoc. Study Lung Cancer. 16 (10), 1647–1662. https://doi.org/10.1016/j.jtho.2021.06.017 (2021).

    Article CAS Google Scholar 

  9. Razavi, P. et al. High-intensity sequencing reveals the sources of plasma Circulating cell-free DNA variants. Nat. Med. 25 (12), 1928–1937. https://doi.org/10.1038/s41591-019-0652-7 (2019).

    Article CAS PubMed PubMed Central Google Scholar 

  10. Marshall, C. H., Gondek, L. P., Luo, J. & Antonarakis, E. S. Clonal hematopoiesis of indeterminate potential in patients with solid tumor malignancies. Cancer Res. 82 (22), 4107–4113. https://doi.org/10.1158/0008-5472.CAN-22-0985 (2022).

    Article CAS PubMed PubMed Central Google Scholar 

  11. Mittal, A. et al. Utility of ctdna in predicting relapse in solid tumors after curative therapy: a meta-analysis. JNCI Cancer Spectr. 7 (4), pkad040. https://doi.org/10.1093/jncics/pkad040 (2023).

    Article PubMed PubMed Central Google Scholar 

  12. Chaudhuri, A. A. et al. Early detection of molecular residual disease in localized lung Cancer by Circulating tumor DNA profiling. Cancer Discov. 7 (12), 1394–1403. https://doi.org/10.1158/2159-8290.CD-17-0716 (2017).

    Article CAS PubMed PubMed Central Google Scholar 

  13. Derman, B. A., Jakubowiak, A. J. & Thompson, M. A. Clinician survey regarding measurable residual disease-guided decision-making in multiple myeloma. Blood Cancer J. 12 (7), 108. https://doi.org/10.1038/s41408-022-00705-6 (2022).

    Article PubMed PubMed Central Google Scholar 

  14. Sahin, I. H. et al. Minimal residual Disease-Directed adjuvant therapy for patients with Early-Stage Colon cancer: CIRCULATE-US. Oncol. Williston Park N. 36 (10), 604–608. https://doi.org/10.46883/2022.25920976 (2022).

    Article Google Scholar 

  15. Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359 (6378), 926–930. https://doi.org/10.1126/science.aar3247 (2018).

    Article CAS PubMed PubMed Central Google Scholar 

  16. Liu, M. C. et al. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann. Oncol. Off J. Eur. Soc. Med. Oncol. 31 (6), 745–759. https://doi.org/10.1016/j.annonc.2020.02.011 (2020).

    Article CAS Google Scholar 

  17. Schrag, D. et al. Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study. Lancet Lond. Engl. 402 (10409), 1251–1260. https://doi.org/10.1016/S0140-6736(23)01700-2 (2023).

    Article Google Scholar 

  18. Snyder, M. W., Kircher, M., Hill, A. J., Daza, R. M. & Shendure, J. Cell-free DNA comprises an in vivo nucleosome footprint that informs its Tissues-Of-Origin. Cell 164 (1–2), 57–68. https://doi.org/10.1016/j.cell.2015.11.050 (2016).

    Article CAS PubMed PubMed Central Google Scholar 

  19. Chen, T., Guestrin, C. & XGBoost: A Scalable Tree Boosting System. Proc 22nd ACM SIGKDD Int Conf Knowl Discov Data Min.:785–794.

  20. Jiang, P. et al. Plasma DNA End-Motif profiling as a fragmentomic marker in cancer, pregnancy, and transplantation. Cancer Discov. 10 (5), 664–673. https://doi.org/10.1158/2159-8290.CD-19-0622 (2020).

    Article CAS PubMed Google Scholar 

  21. Wilcox, A. Indices of Qualitative Variation (No. ORNL-TM-1919).; (2019).

  22. Leighl, N. B. et al. Clinical utility of comprehensive cell-free DNA analysis to identify genomic biomarkers in patients with newly diagnosed metastatic Non-small cell lung Cancer. Clin. Cancer Res. Off J. Am. Assoc. Cancer Res. 25 (15), 4691–4700. https://doi.org/10.1158/1078-0432.CCR-19-0624 (2019).

    Article CAS Google Scholar 

  23. Aggarwal, C. et al. Clinical implications of Plasma-Based genotyping with the delivery of personalized therapy in metastatic Non-Small cell lung Cancer. JAMA Oncol. 5 (2), 173–180. https://doi.org/10.1001/jamaoncol.2018.4305 (2019).

    Article PubMed Google Scholar 

  24. Heitzer, E., Auinger, L., Speicher, M. R. & Cell-Free, D. N. A. Apoptosis: how dead cells inform about the living. Trends Mol. Med. 26 (5), 519–528. https://doi.org/10.1016/j.molmed.2020.01.012 (2020).

    Article CAS PubMed Google Scholar 

  25. Kustanovich, A., Schwartz, R., Peretz, T. & Grinshpun, A. Life and death of Circulating cell-free DNA. Cancer Biol. Ther. 20 (8), 1057–1067. https://doi.org/10.1080/15384047.2019.1598759 (2019).

    Article CAS PubMed PubMed Central Google Scholar 

  26. Jiang, C. & Pugh, B. F. Nucleosome positioning and gene regulation: advances through genomics. Nat. Rev. Genet. 10 (3), 161–172. https://doi.org/10.1038/nrg2522 (2009).

    Article CAS PubMed PubMed Central Google Scholar 

  27. Esfahani, M. S. et al. Inferring gene expression from cell-free DNA fragmentation profiles. Nat. Biotechnol. 40 (4), 585–597. https://doi.org/10.1038/s41587-022-01222-4 (2022).

    Article CAS PubMed PubMed Central Google Scholar 

  28. Ulz, P. et al. Inferring expressed genes by whole-genome sequencing of plasma DNA. Nat. Genet. 48 (10), 1273–1278. https://doi.org/10.1038/ng.3648 (2016).

    Article CAS PubMed Google Scholar 

  29. Valouev, A. et al. Determinants of nucleosome organization in primary human cells. Nature 474 (7352), 516–520. https://doi.org/10.1038/nature10002 (2011).

    Article CAS PubMed PubMed Central Google Scholar 

  30. Lo, Y. M. D. et al. Maternal plasma DNA sequencing reveals the genome-wide genetic and mutational profile of the fetus. Sci. Transl Med. 2 (61), 61ra91. https://doi.org/10.1126/scitranslmed.3001720 (2010).

    Article CAS PubMed Google Scholar 

  31. Lo, Y. M. D., Han, D. S. C., Jiang, P. & Chiu, R. W. K. Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies. Science 372 (6538), eaaw3616. https://doi.org/10.1126/science.aaw3616 (2021).

    Article CAS PubMed Google Scholar 

  32. Helzer, K. T. et al. Fragmentomic analysis of Circulating tumor DNA-targeted cancer panels. Ann. Oncol. Off J. Eur. Soc. Med. Oncol. 34 (9), 813–825. https://doi.org/10.1016/j.annonc.2023.06.001 (2023).

    Article CAS Google Scholar 

  33. Bowcock, A. DNA copy number changes as diagnostic tools for lung cancer. Thorax 69, 496–497 (2014).

  34. Oliveira, D. M. et al. Identification of copy number alterations in colon cancer from analysis of amplicon-based next generation sequencing data. Oncotarget 9 (29), 20409–20425. https://doi.org/10.18632/oncotarget.24912 (2018).

    Article PubMed PubMed Central Google Scholar 

  35. Debattista, J., Grech, L., Scerri, C. & Grech, G. Copy number variations as determinants of colorectal tumor progression in liquid biopsies. Int. J. Mol. Sci. 24 (2), 1738. https://doi.org/10.3390/ijms24021738 (2023).

    Article CAS PubMed PubMed Central Google Scholar 

  36. Shahrouzi, P., Forouz, F., Mathelier, A., Kristensen, V. N. & Duijf, P. H. G. Copy number alterations: a catastrophic orchestration of the breast cancer genome. Trends Mol. Med. 30 (8), 750–764. https://doi.org/10.1016/j.molmed.2024.04.017 (2024).

    Article CAS PubMed Google Scholar 

  37. Salachan, P. V., Ulhøi, B. P., Borre, M. & Sørensen, K. D. Association between copy number alterations estimated using low-pass whole genome sequencing of formalin-fixed paraffin-embedded prostate tumor tissue and cancer-specific clinical parameters. Sci. Rep. 13 (1), 22445. https://doi.org/10.1038/s41598-023-49811-w (2023).

    Article CAS PubMed PubMed Central Google Scholar 

  38. Sondka, Z. et al. The COSMIC Cancer gene census: describing genetic dysfunction across all human cancers. Nat. Rev. Cancer. 18 (11), 696–705. https://doi.org/10.1038/s41568-018-0060-1 (2018).

    Article CAS PubMed PubMed Central Google Scholar 

  39. Xu, D., Yin, S. & Shu, Y. NF2: an underestimated player in cancer metabolic reprogramming and tumor immunity. NPJ Precis Oncol. 8 (1), 133. https://doi.org/10.1038/s41698-024-00627-5 (2024).

    Article PubMed PubMed Central Google Scholar 

  40. Gu, Y. et al. CYLD regulates cell ferroptosis through hippo/yap signaling in prostate cancer progression. Cell. Death Dis. 15 (1), 79. https://doi.org/10.1038/s41419-024-06464-5 (2024).

    Article CAS PubMed PubMed Central Google Scholar 

  41. Clark, A. & Burleson, M. SPOP and cancer: a systematic review. Am. J. Cancer Res. 10 (3), 704–726 (2020).

    CAS PubMed PubMed Central Google Scholar 

  42. O’Neill, H. L., Cassidy, A. P., Harris, O. B. & Cassidy, J. W. BMP2/BMPR1A is linked to tumour progression in dedifferentiated liposarcomas. PeerJ. ;4:e1957. (2016). https://doi.org/10.7717/peerj.1957

  43. Reddy, B. A. et al. Nucleotide biosynthetic enzyme GMP synthase is a TRIM21-controlled relay of p53 stabilization. Mol. Cell. 53 (3), 458–470. https://doi.org/10.1016/j.molcel.2013.12.017 (2014).

    Article CAS PubMed Google Scholar 

  44. Shinmura, K. et al. POLQ overexpression is associated with an increased somatic mutation load and PLK4 overexpression in lung adenocarcinoma. Cancers 11 (5), 722. https://doi.org/10.3390/cancers11050722 (2019).

    Article CAS PubMed PubMed Central Google Scholar 

  45. Basu, A. et al. Expression of the stress response oncoprotein LEDGF/p75 in human cancer: a study of 21 tumor types. PloS One. 7 (1), e30132. https://doi.org/10.1371/journal.pone.0030132 (2012).

    Article CAS PubMed PubMed Central Google Scholar 

  46. Savoy, R. M. & Ghosh, P. M. The dual role of filamin A in cancer: can’t live with (too much of) it, can’t live without it. Endocr. Relat. Cancer. 20 (6), R341–356. https://doi.org/10.1530/ERC-13-0364 (2013).

    Article CAS PubMed PubMed Central Google Scholar 

  47. Fukuhara, S. et al. Functional role of DNA mismatch repair gene PMS2 in prostate cancer cells. Oncotarget 6 (18), 16341–16351. https://doi.org/10.18632/oncotarget.3854 (2015).

    Article PubMed PubMed Central Google Scholar 

  48. Liu, Z., Chen, S. S., Clarke, S., Veschi, V. & Thiele, C. J. Targeting MYCN in pediatric and adult cancers. Front. Oncol. 10, 623679. https://doi.org/10.3389/fonc.2020.623679 (2020).

    Article PubMed Google Scholar 

  49. Yuan, X., Larsson, C. & Xu, D. Mechanisms underlying the activation of TERT transcription and telomerase activity in human cancer: old actors and new players. Oncogene 38 (34), 6172–6183. https://doi.org/10.1038/s41388-019-0872-9 (2019).

    Article CAS PubMed PubMed Central Google Scholar 

  50. Nadauld, L. D. et al. The PATHFINDER study: assessment of the implementation of an investigational Multi-Cancer early detection test into clinical practice. Cancers 13 (14), 3501. https://doi.org/10.3390/cancers13143501 (2021).

    Article CAS PubMed PubMed Central Google Scholar 

  51. Klein, E. A. et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann. Oncol. Off J. Eur. Soc. Med. Oncol. 32 (9), 1167–1177. https://doi.org/10.1016/j.annonc.2021.05.806 (2021).

    Article CAS Google Scholar 

  52. Nakamura, Y. et al. Colorectal Cancer recurrence prediction using a Tissue-Free epigenomic minimal residual disease assay. Clin. Cancer Res. Off J. Am. Assoc. Cancer Res. 30 (19), 4377–4387. https://doi.org/10.1158/1078-0432.CCR-24-1651 (2024).

    Article CAS Google Scholar 

  53. Philipson, T. J., Durie, T., Cong, Z. & Fendrick, A. M. The aggregate value of cancer screenings in the united states: full potential value and value considering adherence. BMC Health Serv. Res. 23 (1), 829. https://doi.org/10.1186/s12913-023-09738-4 (2023).

    Article PubMed PubMed Central Google Scholar 

  54. Radovich, M. et al. Association of Circulating tumor DNA and Circulating tumor cells after neoadjuvant chemotherapy with disease recurrence in patients with Triple-Negative breast cancer: Preplanned secondary analysis of the BRE12-158 randomized clinical trial. JAMA Oncol. 6 (9), 1410–1415. https://doi.org/10.1001/jamaoncol.2020.2295 (2020).

    Article PubMed Google Scholar 

  55. Reinert, T. et al. Analysis of plasma Cell-Free DNA by ultradeep sequencing in patients with stages I to III colorectal Cancer. JAMA Oncol. 5 (8), 1124–1131. https://doi.org/10.1001/jamaoncol.2019.0528 (2019).

    Article PubMed PubMed Central Google Scholar 

  56. Christensen, E. et al. Early detection of metastatic relapse and monitoring of therapeutic efficacy by Ultra-Deep sequencing of plasma Cell-Free DNA in patients with urothelial bladder carcinoma. J. Clin. Oncol. Off J. Am. Soc. Clin. Oncol. 37 (18), 1547–1557. https://doi.org/10.1200/JCO.18.02052 (2019).

    Article CAS Google Scholar 

  57. Gale, D. et al. Residual ctdna after treatment predicts early relapse in patients with early-stage non-small cell lung cancer. Ann. Oncol. Off J. Eur. Soc. Med. Oncol. 33 (5), 500–510. https://doi.org/10.1016/j.annonc.2022.02.007 (2022).

    Article CAS Google Scholar 

  58. Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II Colon cancer. N Engl. J. Med. 386 (24), 2261–2272. https://doi.org/10.1056/NEJMoa2200075 (2022).

    Article CAS PubMed PubMed Central Google Scholar 

  59. Kotani, D. et al. Molecular residual disease and efficacy of adjuvant chemotherapy in patients with colorectal cancer. Nat. Med. 29 (1), 127–134. https://doi.org/10.1038/s41591-022-02115-4 (2023).

    Article CAS PubMed PubMed Central Google Scholar 

Download references

Caris Assure® bloedtest, specificiteit en gevoeligheid, bloedtest, preventie, minimale restziekte, personalised medicin, persoonlijke behandelingsmogelijkheden


Plaats een reactie ...

Reageer op "Caris Assure® bloedtest geeft uitstekende resultaten op zowel vroege ontdekking van meerdere vormen van kanker in alle stadia als van minimale restziekte plus daarvoor benodigde persoonlijke behandelingsmogelijkheden"


Gerelateerde artikelen
 

Gerelateerde artikelen

Caris Assure® bloedtest geeft >> ctDNA bloedtest vindt drie >> Bloedtest Oncoseek om vroegtijdig >> Bloedtest PanSeer kan met >> Bloedtest (MCED) spoort kanker >> Bloedtest via witte bloedcellen >> Bloedtest op in bloed circulerende >> Bloedtest geeft voor 96 procent >> Bloedtest, uitgevoerd op in >> Bloedtesten, een overzicht >>