Sjoerd G. Elias
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Sjoerd G. Elias has a total of 325 co-authors. Here are the top co-authors by number of shared publications:
- Adrienne H. Brouwers
Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
18 shared publications - Anne Isabelle Juliette Arens
Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
15 shared publications - Astrid A. M. van der Veldt
Department of Medical Oncology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands
15 shared publications - Bertha Eisses
Department of Medical Oncology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
15 shared publications - Carla Marie Louise van Herpen
Department of Medical Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
15 shared publications - Catharina Willemien Menke-Van der Houven van Oordt
Amsterdam UMC, Amsterdam, The Netherlands
15 shared publications
Latest Publications
- Open Access
- 10 February 2026
- Published by Springer Nature in Nature Communications
- Vol. 17 (1) , 1499
Author Correction: Whole-body CD8+ T-cell PET imaging in patients with large B-cell lymphoma before and during CD19-directed CAR T-cell therapy: a phase 2 study
- 10 February 2026
- Published by Springer Nature in Nature Communications
- Vol. 17 (1) , 1499
Open AccessAuthor Correction: Whole-body CD8+ T-cell PET imaging in patients with large B-cell lymphoma before and during CD19-directed CAR T-cell therapy: a phase 2 study
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Table 1 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Baseline characteristics of the study population, with key demographic, clinical, and molecular details from regular diagnostic sequencing.
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessTable 1 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Baseline characteristics of the study population, with key demographic, clinical, and molecular details from regular diagnostic sequencing.
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Figure 3 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Genomic landscape of 36 tumors and/or PDOs derived from patients with mCRC. Top, microsatellite stability, tumor mutational load, tumor mutational burden, and whether the sequencing was performed on the PDOs or the tumor of origin; bottom, somatic driver mutations. MS, microsatellite status; MSI, microsatellite instability; MSS, microsatellite stability; Seq, sequencing; TML, tumor mutational load.
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessFigure 3 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Genomic landscape of 36 tumors and/or PDOs derived from patients with mCRC. Top, microsatellite stability, tumor mutational load, tumor mutational burden, and whether the sequencing was performed on the PDOs or the tumor of origin; bottom, somatic driver mutations. MS, microsatellite status; MSI, microsatellite instability; MSS, microsatellite stability; Seq, sequencing; TML, tumor mutational load.
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Supplementary Data 1 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Tables S1-S6 and Figures S1–S8
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Data 1 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Tables S1-S6 and Figures S1–S8
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Figure 2 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Clinical variables related to PDO establishment success: CEA, LDH, mutational status, sex, primary tumor sidedness, prior chemotherapeutic treatment, metastatic site of the biopsy, WGS success, and aggregated biopsy color (brown, pink, red, and white). CEA, carcinoembryonic antigen; mut, mutant.
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessFigure 2 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Clinical variables related to PDO establishment success: CEA, LDH, mutational status, sex, primary tumor sidedness, prior chemotherapeutic treatment, metastatic site of the biopsy, WGS success, and aggregated biopsy color (brown, pink, red, and white). CEA, carcinoembryonic antigen; mut, mutant.
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Figure 5 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
A, Heatmap of the drug sensitivity per PDO for different types of systemic treatment. The columns show the normalized GRAUC (left) and AUC (right), respectively. Potential other treatment options for intermediate or high 5-FU and oxaliplatin–resistant PDOs, as well as intermediate or high 5-FU and oxaliplatin–sensitive but 5-FU and irinotecan–resistant PDOs, are shown in black bars. PDOs that were not screened are shown in gray. B, Sensitivity (GRAUC) to doublet and triplet chemotherapy showing increased sensitivity with the addition of irinotecan. C, Sensitivity (normalized GRAUC) to panitumumab for PDOs categorized according to the tumor’s mutational status and primary tumor sidedness (RAS-mutant, BRAF-mutant, and/or right-sided; RAS/BRAF-WT and left-sided. Boxplots show the minimum, median, maximum, upper and lower quartiles, and individual data points. iri, irinotecan; oxa, oxaliplatin; TT, trifluridine/tipiracil.
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessFigure 5 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
A, Heatmap of the drug sensitivity per PDO for different types of systemic treatment. The columns show the normalized GRAUC (left) and AUC (right), respectively. Potential other treatment options for intermediate or high 5-FU and oxaliplatin–resistant PDOs, as well as intermediate or high 5-FU and oxaliplatin–sensitive but 5-FU and irinotecan–resistant PDOs, are shown in black bars. PDOs that were not screened are shown in gray. B, Sensitivity (GRAUC) to doublet and triplet chemotherapy showing increased sensitivity with the addition of irinotecan. C, Sensitivity (normalized GRAUC) to panitumumab for PDOs categorized according to the tumor’s mutational status and primary tumor sidedness (RAS-mutant, BRAF-mutant, and/or right-sided; RAS/BRAF-WT and left-sided. Boxplots show the minimum, median, maximum, upper and lower quartiles, and individual data points. iri, irinotecan; oxa, oxaliplatin; TT, trifluridine/tipiracil.
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Figure 4 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Correlations between patient response (best RECIST response, size change of all target lesions, and the biopsied lesion) and PDO response (normalized GRAUC per treatment in A–C and AUC in D–F). ROC curves showing the performance of the PDO classification based on GRAUC. The curve plots the true-positive rate (sensitivity) against the false-positive rate (1 − specificity). The AUC indicates the model’s ability to distinguish between responders and nonresponders to 5-FU and oxaliplatin, defined by size change of all target lesions (G) and the biopsied lesion (H). Kaplan–Meier PFS (I) and OS (J) curves of patients stratified by PDO sensitivity to 5-FU and oxaliplatin, based on normalized GRAUC (cutoff = 0.63). Censored events are indicated by vertical bars on the corresponding curve. The table underneath each plot denotes the numbers at risk. Log-rank test–based P value is shown. SN-38, active metabolite of irinotecan.
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessFigure 4 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Correlations between patient response (best RECIST response, size change of all target lesions, and the biopsied lesion) and PDO response (normalized GRAUC per treatment in A–C and AUC in D–F). ROC curves showing the performance of the PDO classification based on GRAUC. The curve plots the true-positive rate (sensitivity) against the false-positive rate (1 − specificity). The AUC indicates the model’s ability to distinguish between responders and nonresponders to 5-FU and oxaliplatin, defined by size change of all target lesions (G) and the biopsied lesion (H). Kaplan–Meier PFS (I) and OS (J) curves of patients stratified by PDO sensitivity to 5-FU and oxaliplatin, based on normalized GRAUC (cutoff = 0.63). Censored events are indicated by vertical bars on the corresponding curve. The table underneath each plot denotes the numbers at risk. Log-rank test–based P value is shown. SN-38, active metabolite of irinotecan.
- Open Access
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Figure 1 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Schematic overview of the study. Patients underwent a biopsy of a metastasis for PDO culture and WGS, before starting a new line of systemic treatment. Predictors of successful PDO establishment were identified: male sex, increased LDH, biopsy in academic hospitals, optimized culture conditions, and experience. A total of 42 PDOs were screened for standard-of-care treatments, and the patient received standard systemic treatment. PDO response was correlated with patient response, and the association between PDO response and survival was assessed. (Created in BioRender. Roodhart, J. [2025] https://BioRender.com/by1f1uq.)
- 1 December 2025
- Published by American Association for Cancer Research (AACR)
Open AccessFigure 1 from Patient-Derived Organoids Predict Treatment Response in Metastatic Colorectal Cancer
Schematic overview of the study. Patients underwent a biopsy of a metastasis for PDO culture and WGS, before starting a new line of systemic treatment. Predictors of successful PDO establishment were identified: male sex, increased LDH, biopsy in academic hospitals, optimized culture conditions, and experience. A total of 42 PDOs were screened for standard-of-care treatments, and the patient received standard systemic treatment. PDO response was correlated with patient response, and the association between PDO response and survival was assessed. (Created in BioRender. Roodhart, J. [2025] https://BioRender.com/by1f1uq.)
- Open Access
- 25 November 2025
- Published by American Association for Cancer Research (AACR)
Supplementary Figure S3 from [89Zr]Zr-DFO-girentuximab and [18F]FDG PET/CT to Predict Watchful Waiting Duration in Patients with Metastatic Clear-cell Renal Cell Carcinoma
Flow-chart patients according to RECIST-defined PD. *All patients had clinical disease progression; no CT-imaging was performed before initiation of systemic treatment ** In total 7 patients choose best supportive care. Three other patients underwent radiotherapy or surgery of all target lesions.
- 25 November 2025
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Figure S3 from [89Zr]Zr-DFO-girentuximab and [18F]FDG PET/CT to Predict Watchful Waiting Duration in Patients with Metastatic Clear-cell Renal Cell Carcinoma
Flow-chart patients according to RECIST-defined PD. *All patients had clinical disease progression; no CT-imaging was performed before initiation of systemic treatment ** In total 7 patients choose best supportive care. Three other patients underwent radiotherapy or surgery of all target lesions.