Integration of Baseline Metabolic Parameters and Mutational Profiles Predicts Long-Term Response to First-Line Therapy in DLBCL Patients: A Post Hoc Analysis of the SAKK38/07 Study

Sofia Genta; Guido Ghilardi; Luciano Cascione; Darius Juskevicius; Alexandar Tzankov; Sämi Schär; Lisa Milan; Maria Cristina Pirosa; Fabiana Esposito; Teresa Ruberto; Luca Giovanella; Stefanie Hayoz; Christoph Mamot; Stefan Dirnhofer; Emanuele Zucca; Luca Ceriani

doi:10.3390/cancers14041018

Integration of Baseline Metabolic Parameters and Mutational Profiles Predicts Long-Term Response to First-Line Therapy in DLBCL Patients: A Post Hoc Analysis of the SAKK38/07 Study

Cancers (Basel). 2022 Feb 17;14(4):1018. doi: 10.3390/cancers14041018.

Authors

Sofia Genta¹, Guido Ghilardi², Luciano Cascione^{3

4}, Darius Juskevicius⁵, Alexandar Tzankov⁵, Sämi Schär⁶, Lisa Milan⁷, Maria Cristina Pirosa^{1

2}, Fabiana Esposito¹, Teresa Ruberto⁷, Luca Giovanella^{7

8}, Stefanie Hayoz⁶, Christoph Mamot⁹, Stefan Dirnhofer⁵, Emanuele Zucca^{1

3

10}, Luca Ceriani^{3

7}

Affiliations

¹ Clinic of Medical Oncology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland.
² Clinic of Hematology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland.
³ Institute of Oncology Research, Faculty of Biomedical Sciences, Università della Svizzera Italiana, 6500 Bellinzona, Switzerland.
⁴ Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.
⁵ Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
⁶ Swiss Group for Clinical Cancer Research (SAKK) Coordinating Center, 3008 Bern, Switzerland.
⁷ Clinic of Nuclear Medicine and PET/CT Center, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland.
⁸ Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, 8006 Zurich, Switzerland.
⁹ Division of Oncology, Cantonal Hospital Aarau, 5001 Aarau, Switzerland.
¹⁰ Department of Medical Oncology, Bern University Hospital, University of Bern, 3008 Bern, Switzerland.

Abstract

Accurate estimation of the progression risk after first-line therapy represents an unmet clinical need in diffuse large B-cell lymphoma (DLBCL). Baseline (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) parameters, together with genetic analysis of lymphoma cells, could refine the prediction of treatment failure. We evaluated the combined impact of mutation profiling and baseline PET/CT functional parameters on the outcome of DLBCL patients treated with the R-CHOP14 regimen in the SAKK38/07 clinical trial (NCT00544219). The concomitant presence of mutated SOCS1 with wild-type CREBBP and EP300 defined a group of patients with a favorable prognosis and 2-year progression-free survival (PFS) of 100%. Using an unsupervised recursive partitioning approach, we generated a classification-tree algorithm that predicts treatment outcomes. Patients with elevated metabolic tumor volume (MTV) and high metabolic heterogeneity (MH) (15%) had the highest risk of relapse. Patients with low MTV and favorable mutational profile (9%) had the lowest risk, while the remaining patients constituted the intermediate-risk group (76%). The resulting model stratified patients among three groups with 2-year PFS of 100%, 82%, and 42%, respectively (p < 0.001).

Keywords: DLBCL; PET/CT; lymphoma; mutational profile; prognostic index.