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Pfob A, Cai L, Schneeweiss A, Rauch G, Thomas B, Schaefgen B, Kuemmel S, Reimer T, Hahn M, Thill M, Blohmer JU, Hackmann J, Malter W, Bekes I, Friedrichs K, Wojcinski S, Joos S, Paepke S, Degenhardt T, Rom J, Rody A, van Mackelenbergh M, Banys-Paluchowski M, Große R, Reinisch M, Karsten MM, Sidey-Gibbons C, Wallwiener M, Golatta M, Heil J. Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept. Ann Surg Oncol 2024; 31:957-965. [PMID: 37947974 PMCID: PMC10761434 DOI: 10.1245/s10434-023-14551-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 10/23/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Breast cancer patients with residual disease after neoadjuvant systemic treatment (NAST) have a worse prognosis compared with those achieving a pathologic complete response (pCR). Earlier identification of these patients might allow timely, extended neoadjuvant treatment strategies. We explored the feasibility of a vacuum-assisted biopsy (VAB) after NAST to identify patients with residual disease (ypT+ or ypN+) prior to surgery. METHODS We used data from a multicenter trial, collected at 21 study sites (NCT02948764). The trial included women with cT1-3, cN0/+ breast cancer undergoing routine post-neoadjuvant imaging (ultrasound, MRI, mammography) and VAB prior to surgery. We compared the findings of VAB and routine imaging with the histopathologic evaluation of the surgical specimen. RESULTS Of 398 patients, 34 patients with missing ypN status and 127 patients with luminal tumors were excluded. Among the remaining 237 patients, tumor cells in the VAB indicated a surgical non-pCR in all patients (73/73, positive predictive value [PPV] 100%), whereas PPV of routine imaging after NAST was 56.0% (75/134). Sensitivity of the VAB was 72.3% (73/101), and 74.3% for sensitivity of imaging (75/101). CONCLUSION Residual cancer found in a VAB specimen after NAST always corresponds to non-pCR. Residual cancer assumed on routine imaging after NAST corresponds to actual residual cancer in about half of patients. Response assessment by VAB is not safe for the exclusion of residual cancer. Response assessment by biopsies after NAST may allow studying the new concept of extended neoadjuvant treatment for patients with residual disease in future trials.
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Affiliation(s)
- André Pfob
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.
- MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany.
| | - Lie Cai
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Andreas Schneeweiss
- National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany
| | - Geraldine Rauch
- Institute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Bettina Thomas
- Coordination Centre for Clinical Trials (KKS), University Heidelberg, Heidelberg, Germany
| | - Benedikt Schaefgen
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Sherko Kuemmel
- Breast Unit, Kliniken Essen-Mitte, Essen, Germany
- Department of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Toralf Reimer
- Department of Gynecology/Breast Unit, University Hospital Rostock, Rostock, Germany
| | - Markus Hahn
- Department of Gynecology/Breast Unit, University Hospital Tuebingen, Tübingen, Germany
| | - Marc Thill
- Department of Gynecology and Gynecological Oncology/Breast Unit, Agaplesion Markus Hospital Frankfurt, Frankfurt, Germany
| | - Jens-Uwe Blohmer
- Department of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - John Hackmann
- Department of Gynecology/Breast Unit, Marienhospital, Witten, Germany
| | - Wolfram Malter
- Department of Gynecology and Obstetrics, Medical Faculty, Breast Cancer Center, University of Cologne, Cologne, Germany
| | - Inga Bekes
- Department of Gynecology/Breast Unit, University Hospital Ulm, Ulm, Germany
| | - Kay Friedrichs
- Department of Gynecology/Breast Unit, Jerusalem Hospital Hamburg, Hamburg, Germany
| | - Sebastian Wojcinski
- Department of Gynecology and Obstetrics, Breast Cancer Center, Klinikum Bielefeld Mitte GmbH, Bielefeld, Germany
| | - Sylvie Joos
- Radiologische Allianz Hamburg, Hamburg, Germany
| | - Stefan Paepke
- Frauenklinik, Interdisziplinäres Brustzentrum des Klinikums rechts der Isar der Technischen Universität München, Munich, Germany
| | - Tom Degenhardt
- Department of Gynecology/Breast Unit, University Hospital Munich, Munich, Germany
| | - Joachim Rom
- Department of Gynecology/Breast Unit, Klinikum Frankfurt-Höchst, Frankfurt, Germany
| | - Achim Rody
- Department of Gynecology/Breast Unit, University Hospital Schleswig-Holstein, Lübeck, Germany
| | | | | | - Regina Große
- Department of Gynecology/Breast Unit, University Hospital Halle, Halle, Germany
| | | | - Maria Margarete Karsten
- Department of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - Chris Sidey-Gibbons
- MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Symptom Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Markus Wallwiener
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Michael Golatta
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
- Breast Unit, Klinikum Sankt Elisabeth, Heidelberg, Germany
| | - Joerg Heil
- Department of Obstetrics and Gynecology, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
- Breast Unit, Klinikum Sankt Elisabeth, Heidelberg, Germany
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Mondello A, Dal Bo M, Toffoli G, Polano M. Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges. Front Pharmacol 2024; 14:1260276. [PMID: 38264526 PMCID: PMC10803549 DOI: 10.3389/fphar.2023.1260276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/26/2023] [Indexed: 01/25/2024] Open
Abstract
Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover hidden patterns from complex NGS data and to solve various PGx problems. In this review, we provide a comprehensive overview of the NGS approaches that can be employed and the different PGx studies implicating the use of NGS data. We also provide an excursus of the ML algorithms that can exert a role as fundamental strategies in the PGx field to improve personalized medicine in cancer.
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Affiliation(s)
| | | | | | - Maurizio Polano
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO), Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Aviano, Italy
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