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A randomized, non-comparative phase 2 study of neoadjuvant immune-checkpoint blockade in retroperitoneal dedifferentiated liposarcoma and extremity/truncal undifferentiated pleomorphic sarcoma

Nature Cancer volume 5, pages 625–641 (2024)Cite this article

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Abstract

Based on the demonstrated clinical activity of immune-checkpoint blockade (ICB) in advanced dedifferentiated liposarcoma (DDLPS) and undifferentiated pleomorphic sarcoma (UPS), we conducted a randomized, non-comparative phase 2 trial (NCT03307616) of neoadjuvant nivolumab or nivolumab/ipilimumab in patients with resectable retroperitoneal DDLPS (n = 17) and extremity/truncal UPS (+ concurrent nivolumab/radiation therapy; n = 10). The primary end point of pathologic response (percent hyalinization) was a median of 8.8% in DDLPS and 89% in UPS. Secondary end points were the changes in immune infiltrate, radiographic response, 12- and 24-month relapse-free survival and overall survival. Lower densities of regulatory T cells before treatment were associated with a major pathologic response (hyalinization > 30%). Tumor infiltration by B cells was increased following neoadjuvant treatment and was associated with overall survival in DDLPS. B cell infiltration was associated with higher densities of regulatory T cells before treatment, which was lost upon ICB treatment. Our data demonstrate that neoadjuvant ICB is associated with complex immune changes within the tumor microenvironment in DDLPS and UPS and that neoadjuvant ICB with concurrent radiotherapy has significant efficacy in UPS.

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Fig. 1: Trial schema of immune-checkpoint inhibition in retroperitoneal DDLPS and extremity/truncal UPS.
Fig. 2: Consolidated Standards of Reporting Trials flow diagram.
Fig. 3: Clinical responses to neoadjuvant nivolumab and ipilimumab/nivolumab in resectable retroperitoneal DDLPS and extremity/truncal UPS.
Fig. 4: Immune infiltration association with early relapse, survival and pathologic treatment response.
Fig. 5: Intratumor heterogeneity of immune cells at surgery.
Fig. 6: Intratumoral B cells and TLS association with other intratumoral immune cells and oncological outcomes.

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Data availability

The data supporting the findings of this study are available within the manuscript and its supplementary information files. RNA-seq data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession code GSE202361. All other relevant de-identified data related to the current study are available from the corresponding author (C.L.R.) upon reasonable request (including compelling scientific rationale and preliminary data requiring validation through use of this cohort; these preliminary data should be presented to the authors) and will require the researcher to sign a data access agreement with The University of Texas MD Anderson Cancer Center after approval. Individual patient identifiable clinical data (such as dates) are not publicly available due to concerns with identification of patients.

The hg19 human genome can be found at https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001405.13/.

Source data for all figures and extended data have been provided as Source Data files. Source data are provided with this paper.

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Acknowledgements

We thank the patients and their families for participating in this study. We thank all the members of our regulatory, clinical, data coordination and translational research teams in the Departments of Surgical Oncology and Sarcoma Medical Oncology at The University of Texas MD Anderson Cancer Center for their support on this trial. The clinical aspects of the study were funded by Bristol-Myers Squibb (drug and funding). Presequencing processing work was carried out by the Moon Shots Platform Cancer Genomics Laboratory, The University of Texas MD Anderson Cancer Center Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy. Sequencing and data generation was supported by a CA016672 (ATGC) grant from The University of Texas MD Anderson Cancer Center, Advanced Technology Genomics Core. This translational analysis was supported by the Rare Tumor Initiative, an MD Anderson Strategic Research Initiative Development Program Microbiome samples were processed by MD Anderson Cancer Center’s Program for Innovative Microbiome and Translational Research. Support for the study was also partially provided by the National Institutes of Health (NIH)/National Cancer Institute (NCI) P30 CA016672 Cancer Center Support Grant. J.A.W. is supported by the NIH (1 R01 CA219896-01A1), US–Israel Binational Science Foundation (201332), the Melanoma Research Alliance (4022024), American Association for Cancer Research Stand Up To Cancer (SU2C-AACR-IRG-19-17), Department of Defense (W81XWH-16-1-0121), MD Anderson Cancer Center Multidisciplinary Research Program Grant, Andrew Sabin Family Fellows Program and MD Anderson Cancer Center’s Melanoma Moon Shots Program. C.L.R. received support from NIH/NCI The Paul Calabresi K12 Career Development Award CA088084-16A1, The Society of Surgical Oncology Clinical Investigator Award and The American College of Surgeons Faculty Research Fellowship. E.F.N.H. received support from the LMS SPORE Career Enhancement Program, the QuadW foundation, Sarcoma Foundation of America, Fondation pour la Recherche Medicale and Fondation Nuovo-Soldati. E.Z.K. received grant support from the QuadW foundation, Sarcoma Foundation of America, Fondation pour la Recherche Medicale and the NCI Early Surgeon Scientist Program.

Author information

Author notes

  1. These authors contributed equally: Christina L. Roland, Elise F. Nassif Haddad, Emily Z. Keung.

Authors and Affiliations

  1. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Christina L. Roland, Elise F. Nassif Haddad, Emily Z. Keung, Manoj Chelvanambi, Kelly K. Hunt, Keila E. Torres, Barry W. Feig, Christopher P. Scally, Russell G. Witt, Raymond S. Traweek, Brandon Cope, Kate Callahan, Sa Nguyen, Sheila Duncan & Jennifer A. Wargo

  2. Centre Léon-Bérard, University Claude Bernard Lyon I, Lyon, France

    Elise F. Nassif Haddad & Jean-Yves Blay

  3. Department of Sarcoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Elise F. Nassif Haddad, Ravin Ratan, Dejka Araujo, M. Alexandra Zarzour, Shreyaskumar Patel, Robert Benjamin, Anthony P. Conley, J. Andrew Livingston, Vinod Ravi, Xiao Zhou & Neeta Somaiah

  4. Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Wei-Lien Wang, Alexander J. Lazar & Ignacio Wistuba

  5. Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Alexander J. Lazar, Elizabeth M. Burton, Keila E. Torres, Chia-Chin Wu, Mohammad M. Mohammad, Randy A. Chu, Jianhua Zhang, Ashish Damania, Pranoti Sahasrabhojane, Andrew Futreal, Nadim Ajami & Jennifer A. Wargo

  6. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Heather Lin

  7. Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Edwin R. Parra, Khalida Wani, Rossana Lazcano, Davis Ingram, Rohini Morey, Shadarra Crosby, Grace Mathew, Cibelle F. Lima & Ignacio Wistuba

  8. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    B. Ashleigh Guadagnolo & Andrew J. Bishop

  9. Department of Orthopedic Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Valerae O. Lewis, Justin E. Bird, Patrick P. Lin, Bryan S. Moon & Robert L. Satcher

  10. Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Hussein A. Tawbi & Taylor Tate

  11. Department of Musculoskeletal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Bilal Mujtaba

  12. Centre de Recherche des Cordeliers, Inserm, Université Paris-Cité, Equipe Labellisée Ligue Contre le Cancer, Paris, France

    Wolf Herman Fridman

  13. Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Kenna Shaw

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  1. Christina L. Roland
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  2. Elise F. Nassif Haddad
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Contributions

C.L.R., E.Z.K., H.A.T., E.M.B., J.A.W., B.A.G., A.J.B. and N.S. designed the study. C.L.R. and N.S. were the principal investigators. E.Z.K. was a co-principal investigator. H.Y.L. conducted the statistical design and analyses. C.L.R., N.S., E.Z.K., A.P.C., R.R., M.A.Z. and J.A.L. recruited patients. B.A.G., A.J.B., K.K.H., K.E.T., B.W.F., C.P.S., V.O.L., J.E.B., R.R., D.A.J., M.A.Z., S.P., R.B., A.P.C., J.A.L., V.R., P.P.L., B.S.M., T.T., K.C. and R.L.S. treated patients. E.Z.K., A.J.L., W.L.W., E.R.P., K.W., D.I. and E.F.N.H. collected and analyzed the translational data. W.L.W., A.J.L., E.R.P., K.W., R.L., D.I., R.M. and C.F.L. performed pathologic evaluation, IHC staining and interpretation, mIF staining and interpretation. B.M. interpreted the imaging evaluations. M.C., C.C.W., M.M.M., R.A.C., J.Z., A.D., P.S., S.C., G.M., S.D., K.S., I.W., A.F. and N.A. collected, handled and analyzed samples for genomic analyses. E.F.N.H., C.L.R., E.Z.K. and N.S. wrote the manuscript. E.F.N.H., E.Z.K., C.L.R., S.N., H.Y.L. and N.S. had access to the data. E.F.N.H., E.Z.K. and C.L.R. accessed and verified the data. M.C., R.G.W., R.S.T. and B.C. edited the figures and the manuscript. All authors contributed to editing the manuscript and gave final approval for the article.

Corresponding author

Correspondence to Christina L. Roland.

Ethics declarations

Competing interests

This study was supported by Bristol-Myers Squibb. A.J.L. has served on advisory boards and/or consulted for AbbVie, Adaptimmune, ArcherDX, AstraZeneca, Bayer, BMS, Deciphera Pharmaceuticals, Foghorn Therapeutics, Gothams, GSK, Guardant, Invitae, Illumina, Iterion Therapeutics, Merck, Novartis, Nucleai, Paige.AI, Pfizer, Roche/Genentech and Thermo Fisher. K.K.H. is on the medical advisory board for Armada Health and AstraZeneca and reports research funding to The MD Anderson Cancer Center from Cairn Surgical, Eli Lilly & Co. and Lumicell. D.A. receives research funding from Adaptimmune, GSK and Immatics. H.T. received grant or research support from BMS, Novartis, Merck, Genentech, GlaxoSmithKline, EMD Sereno, Eisai, Dragonfly Therapeutics, RAPT Therapeutics; and is a consultant for BMS, Genentech, Novartis, Merck, Boxer Capital, Karyopharm, Iovance, Eisai, Jazz Pharmaceuticals and Medicenna. R.G.W. is supported by the NIH T32 CA 009599 and The MD Anderson Cancer Center support grant P30 CA016672. J.Y.B. has received research support and honoraria from Roche, GlaxoSmithKline, BMS and MSD. W.H.F. is a consultant for Novartis, Adaptimmune, Anaveon, Catalym, OSE Immunotherapeutic, Oxford Biotherapeutics, Genenta and Parthenon. K.S. is a consultant for Guidepoint, GLG, BlueprintBiomedicines and Coleman and is on the editorial committee for a CSHP publication. I.W. has provided consulting or advisory roles for AstraZeneca/MedImmune, Bayer, Bristol-Myers Squibb, Genentech/Roche, GlaxoSmithKline, Guardant Health, HTG Molecular Diagnostics, Merck, MSD Oncology, OncoCyte, Jansen, Novartis, Flame and Pfizer; has received grants and personal fees from Genentech/Roche, Bristol-Myers Squibb, AstraZeneca/MedImmune, HTG Molecular, Merck and Guardant Health; has received personal fees from GlaxoSmithKline and Oncocyte, Daiichi Sankyo, Roche, AstraZeneca, Pfizer and Bayer; and has received research funding to his institution from 4D Molecular Therapeutics, Adaptimmune, Adaptive Biotechnologies, Akoya Biosciences, Amgen, Bayer, EMD Serono, Genentech, Guardant Health, HTG Molecular Diagnostics, Iovance Biotherapeutics, Johnson & Johnson, Karus Therapeutics, MedImmune, Merck, Novartis, OncoPlex Diagnostics, Pfizer, Takeda and Novartis. J.A.W. reports compensation for speaker’s bureau and honoraria from Imedex, Dava Oncology, Omniprex, Illumina, Gilead, PeerView, Physician Education Resource, MedImmune and Bristol-Myers Squibb; is on the advisory board as a consultant for Roche/Genentech, Novartis, AstraZeneca, GlaxoSmithKline, Bristol-Myers Squibb, Merck, Micronoma and Biothera Pharmaceuticals; and has stock options for Micronoma. N.S. is on the advisory board as a consultant for Deciphera, AADI Biosciences, Epizyme and Boehringer Ingelheim; receives research funding from Decipehra, Daiichi Sankyo, Karyopharm, AstraZeneca, Cogent Biosciences, Ascentage and GSK; and has an immediate family member with stock options from Pfizer and JNJ.

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Extended data

Extended Data Fig. 1 Maximum-Grade Treatment-Related Adverse Events.

Frequencies of maximum-grade treatment-related adverse events (TRAEs) in the whole cohort of patients in ascending shades of blue (nivolumab arms) and red (ipilimumab/nivolumab arms) for grades 1 to 3. There were no grade 4 or 5 TRAEs in this trial. All adverse events that were possibly or probably related to treatment are reported. All patients (n = 27) were included in this analysis.

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Extended Data Fig. 2 Pathologic response evaluation by hyalinization and correlation with other response criteria.

a, Patient-level pathological data showing percent hyalinization, percent viable tumor, and percent necrosis of surgical specimens in the ITT population (n = 27) in DDLPS (left panels) and UPS (right panels) patients. Patient 29 had clinical progression with lung metastasis treated by chemotherapy, followed by surgery off trial. b, Correlation between percent viable tumor and percent hyalinization at surgery. Two-sided p-value is Spearman rank-order correlation test. Gray zone is 95% CI. c, Correlation between overall change in tumor size from baseline at least 14 days after last dose assessed by RECIST1.1 and percent hyalinization at surgery. Dots are in ascending size of percent viable tumor at surgery. Two-sided p-value is Spearman rank-order correlation test. Gray zone is 95% CI. d, Table reporting pathologic response and early relapse in patients treated in arm B, according to the dose of ipilimumab received. P values are two-sided. e, Table reporting pathologic response and early relapse in patients treated in arm D, according to the dose of ipilimumab received. P values are two-sided.

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Extended Data Fig. 3 Survival outcomes and association with RECIST response, pathologic response, and resistance.

a, Kaplan-Meier curves of OS in DDLPS patients treated with nivolumab (n = 8) and ipilimumab/nivolumab (n = 9) from surgery (on-trial and off trial) to death. b, Kaplan-Meier curves of OS in UPS patients treated with nivolumab + RT (n = 6) and ipilimumab/nivolumab followed by nivolumab + RT (n = 4). c, Kaplan-Meier curves of RFS according to radiographic response (PD, SD, PR) as assessed by RECIST1.1 from baseline at least 14 days after last dose in DDLPS patients (left panel) and UPS patients (right panel). Two-sided p values indicate log-rank comparison. d, Kaplan-Meier curves of OS according to radiographic response (PD, SD, PR) as assessed by RECIST1.1 from baseline at least 14 days after last dose in DDLPS patients (left panels), and UPS patients (right panels). Two-sided p values indicate log-rank comparison. e, Kaplan-Meier curves of RFS according to dose of ipilimumab and nivolumab received in DDLPS patients (arm B; left panel) and UPS patients (arm D; right panel). Two-sided p values indicate log-rank comparison. f, Kaplan-Meier curves of OS according to dose of ipilimumab and nivolumab received in DDLPS patients (arm B; left panel) and UPS patients (arm D; right panel). Two-sided p values indicate log-rank comparison. g, Kaplan-Meier curves of RFS (left panel) and OS (right panel) according to disease status at initiation of treatment (primary versus recurrent) in DDLPS. Two-sided p values indicate log-rank comparison. h, Kaplan-Meier curves of RFS (left panel) and OS (right panel) according to focality at initiation of treatment in DDLPS patients. Two-sided p values indicate log-rank comparison.

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Extended Data Fig. 4 Association of tumor PD-L1 expression by IHC in malignant cells with oncological outcomes and immune infiltration.

a, Number of samples with positive (≥1%) and negative (<1%) PD-L1 IHC staining on malignant cells by clone 28-8 at each time point in DDLPS (left panel) and UPS (right panel) patients. b, Table displaying oncological efficacy end points in DDLPS and UPS patients with baseline PD-L1 positive and negative tumors. PD-L1 positive tumors were defined as those with ≥1% on expression on malignant cells by IHC with clone 28-8. Two-sided p values are Wilcoxon rank-sum tests and Fisher’s exact tests. c, d, Kaplan-Meier curves of probability of RFS from surgery to relapse or death according to positivity of PD-L1 staining on tumor cells at baseline, in (c) DDLPS and (d) UPS patients. P values indicate log-rank comparison of survival curves. e, Kaplan-Meier curves of probability of RFS from surgery to relapse or death according to positivity of PD-L1 staining on tumor cells at baseline, in DDLPS patients with primary tumors (left panel) or recurrent tumors (right panel) at initiation of treatment. Two-sided p values indicate log-rank comparison of survival curves. f, Kaplan-Meier curves of probability of RFS from surgery to relapse or death according to positivity of PD-L1 staining on tumor cells at baseline, in DDLPS patients with unifocal (left panel) or multifocal tumors (right panel) at initiation of treatment. Two-sided p values indicate log-rank comparison of survival curves.

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Extended Data Fig. 5 Association of immune cell densities with pathologic response.

a, Example of mIF images of T cells (CD3+), activated T cells (CD3 + Ki67+), CD8+ cells, activated cytotoxic T cells (CD3 + CD8 + Ki67+), PD-L1 positive cytotoxic T cells (CD3 + CD8 + PD-L1+), antigen-experienced T cells (CD3 + PD-1+), memory T cells (CD3 + CD45RO + CD8-), macrophages (CD68+), and PD-L1 positive macrophages (CD68 + PD-L1+). Scale shows 50 μm. b–d, Absolute densities (/mm2) of (b) tumor-associated macrophages (CD68+), (c) activated macrophages (CD68 + Ki67+), and PD-L1+ macrophages (CD68 + PD-L1+) in pathologic responders (≥30% hyalinization; blue dots and blue circles) and non-responders (red dots and red circles) at each time point (baseline, on-treatment, and surgery) in DDLPS (circles) and UPS (dots) patients. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Wilcoxon rank-sum test comparisons of densities of cells. e–g, Absolute densities (/mm2) of (b) tumor-associated macrophages (CD68+), (c) activated macrophages (CD68 + Ki67+), and PD-L1+ macrophages (CD68 + PD-L1+) in pathologic responders (≥30% hyalinization) and non-responders at each time point (baseline, on-treatment, and surgery) in DDLPS (top panels) and UPS (bottom panels) patients. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Wilcoxon rank-sum test comparisons of densities of cells.

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Extended Data Fig. 6 Intratumor infiltrating cytotoxic T cells and T-regulatory cells in subgroups of DDLPS.

a, Kaplan-Meier curves of RFS, according to baseline intratumoral relative density of cytotoxic T cells (CD3 + CD8+) in primary (left panel) and recurrent (right panel) DDLPS patients. Two-sided p values indicate log-rank comparison. b, Absolute densities (/mm2) of cytotoxic T cells (CD3 + CD8+) in primary and recurrent DDLPS at each time point. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Wilcoxon rank-sum test comparisons. c, Kaplan-Meier curves of RFS, according to baseline intratumoral relative density of cytotoxic T cells (CD3 + CD8+) in unifocal (left panel) and multifocal (right panel) DDLPS patients. Two-sided p values indicate log-rank comparison. d, Absolute densities (/mm2) of intratumoral cytotoxic T cells (CD3 + CD8+) in unifocal and multifocal DDLPS at each time point. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Wilcoxon rank-sum test comparisons. e, Kaplan-Meier curves of RFS, according to baseline intratumoral relative density of T-regs (CD3+FoxP3 + CD8-) in primary (left panel) and recurrent (right panel) DDLPS patients. Two-sided p values indicate log-rank comparison. f, Absolute densities (/mm2) of intratumoral T-regs (CD3+FoxP3 + CD8-) in primary and recurrent DDLPS at each time point. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Wilcoxon rank-sum test comparisons. g, Kaplan-Meier curves of RFS, according to baseline intratumoral relative density of T-regs (CD3+FoxP3 + CD8-) in unifocal (left panel) and multifocal (right panel) DDLPS patients. Two-sided p values indicate log-rank comparison of survival curves. h, Absolute densities (/mm2) of intratumoral T-regs (CD3+FoxP3 + CD8-) in unifocal and multifocal DDLPS at each time point. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Wilcoxon rank-sum test comparisons.

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Extended Data Fig. 7 Patterns of therapy-induced changes in intratumoral immune cells infiltration.

a, Absolute densities (/mm2) of intratumoral immune cells across treatment time points (baseline [BL], on-treatment [OT], and surgery [Surg]) in DDLPS and UPS patients. Dashed lines indicate paired samples. Colors indicate pathologic response. Two-sided p values are Kruskal–Wallis test for comparisons of immune densities across time points, adjusted for multiple comparison by FDR. b, c, Unsupervised hierarchical clustering of tumor specimens based on intratumoral immune densities of selected immune cell populations assessed by mIF at all time points in (b) DDLPS and (c) UPS patients. Absolute densities of immune cell populations have been scaled. Red shows higher densities of immune cells and blue indicates lower densities of immune cells. Annotations include early relapse status, presence of TLS features by IHC, and time point of tumor specimen collection.

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Extended Data Fig. 8 Association of intratumoral T-cell and macrophage densities with presence of intratumoral TLS and survival outcomes.

a, Absolute densities (/mm2) of intratumoral T cells and macrophages in samples displaying B cell aggregates with TLS features by CD20 and CD21 IHC (blue circles and blue dots) and samples without B cell and TLS features by IHC (red dots and red circles), at each time point (baseline, on-treatment, and surgery). Data are presented as minima from maxima, and solid line in the violin plot indicates median. Empty circles indicate DDLPS, solid dots indicate UPS. Two-sided p values are Wilcoxon rank-sum test comparisons of densities of cells between samples with or without TLS, adjusted for multiple comparison by FDR. b, Kaplan-Meier curves of probability of RFS (left panels) and OS from surgery to death (right panel) according to presence of B cell aggregates with TLS features by CD20 and CD21 IHC in tumor specimens of DDLPS patients at baseline. Two-sided p values indicate log-rank comparison of survival curves. c,d, Kaplan-Meier curves of probability of RFS (left panels) and overall survival from surgery to death (right panels) according to high (top quartile) or low (remaining quartiles) RNA-seq ssGSEA signature scores of TLS in baseline tumor specimens of (c) DDLPS and (d) UPS patients. Two-sided p values indicate log-rank comparison of survival curves.

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Extended Data Fig. 9 Intratumoral B cells and TLS subgroup analyses and intratumor heterogeneity.

a, Proportion of tumor specimens showing presence of B cell aggregates with TLS features assessed by CD20 and CD21 IHC at each time point in DDLPS patients with primary (top panels) and recurrent tumors (bottom panels). Samples which did not pass quality control for analysis by IHC are not represented. b, Proportion of tumor specimens showing presence of TLS features assessed by CD20 and CD21 IHC at each time point in DDLPS patients with unifocal (top panels) and multifocal tumors (bottom panels). Samples which did not pass quality control for analysis by IHC are not represented. c–f, Kaplan-Meier curves of OS according to presence of TLS features by CD20 and CD21 IHC in tumor specimens of DDLPS patients at surgery in (c) primary, (d) recurrent, (e) unifocal, and (f) multifocal tumors. Two-sided p values indicate log-rank comparison. g, Mean number of lymphoid aggregates by H&E per slide at surgery in patients with (blue dots and blue circles; n = 5) and without (red dots and red circles; n = 12) positive evaluation of TLS features by CD20/CD21 IHC. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Empty circles indicate DDLPS (n = 9), solid dots indicate UPS (n = 9). Two-sided p values are Wilcoxon rank-sum test comparisons of densities of cells between samples with or without TLS. h, Patient-level representation of the number of lymphoid aggregates by H&E per slide for each block of the surgical resection in patients with (blue dots; n = 5) and without (red dots; n = 12) positive evaluation of TLS features by CD20/CD21 IHC. Data are presented as minima from maxima, and solid line in the violin plot indicates median. Two-sided p values are Levene’s test for homogeneity of variance.

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Extended Data Table 1 Patient characteristics at baseline and clinical end points in DDLPS patients by disease status and focality
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Supplementary information

Supplementary Information

Supplementary Methods Tables 1 and 2.

Reporting Summary

Supplementary Data 1

CONSORT checklist.

Supplementary Data 1

Clinical trial protocol.

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Representative images of CT scans, MRIs and pathology evaluation of patients on trial before and after treatment.

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Representative images of CT scans, MRIs and pathology evaluation of patients on trial before and after treatment.

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Representative images of CT scans, MRIs and pathology evaluation of patients on trial before and after treatment.

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Representative images of CT scans, MRIs and pathology evaluation of patients on trial before and after treatment.

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Representative images of CT scans, MRIs and pathology evaluation of patients on trial before and after treatment.

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Roland, C.L., Nassif Haddad, E.F., Keung, E.Z. et al. A randomized, non-comparative phase 2 study of neoadjuvant immune-checkpoint blockade in retroperitoneal dedifferentiated liposarcoma and extremity/truncal undifferentiated pleomorphic sarcoma. Nat Cancer 5, 625–641 (2024). https://doi.org/10.1038/s43018-024-00726-z

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