<i>LRP1B</i> mutations are associated with favorable outcomes to immune checkpoint inhibitors across multiple cancer types.



Low-density lipoprotein receptor-related protein 1b (encoded by LRP1B) is a putative tumor suppressor, and preliminary evidence suggests LRP1B-mutated cancers may have improved outcomes with immune checkpoint inhibitors (ICI).


We conducted a multicenter, retrospective pan-cancer analysis of patients with LRP1B alterations treated with ICI at Duke University, Johns Hopkins University (JHU) and University of Michigan (UM). The primary objective was to assess the association between overall response rate (ORR) to ICI and pathogenic or likely pathogenic (P/LP) LRP1B alterations compared with LRP1B variants of unknown significance (VUS). Secondary outcomes were the associations with progression-free survival (PFS) and overall survival (OS) by LRP1B status.


We identified 101 patients (44 Duke, 35 JHU, 22 UM) with LRP1B alterations who were treated with ICI. The most common tumor types by alteration (P/LP vs VUS%) were lung (36% vs 49%), prostate (9% vs 7%), sarcoma (5% vs 7%), melanoma (9% vs 0%) and breast cancer (3% vs 7%). The ORR for patients with LRP1B P/LP versus VUS alterations was 54% and 13%, respectively (OR 7.5, 95% CI 2.9 to 22.3, p=0.0009). P/LP LRP1B alterations were associated with longer PFS (HR 0.42, 95% CI 0.26 to 0.68, p=0.0003) and OS (HR 0.62, 95% CI 0.39 to 1.01, p=0.053). These results remained consistent when excluding patients harboring microsatellite instability (MSI) and controlling for tumor mutational burden (TMB).


This multicenter study shows significantly better outcomes with ICI therapy in patients harboring P/LP versus VUS LRP1B alterations, independently of TMB/MSI status. Further mechanistic and prospective validation studies are warranted.





Published Version (Please cite this version)


Publication Info

Brown, Landon C, Matthew D Tucker, Ramy Sedhom, Eric B Schwartz, Jason Zhu, Chester Kao, Matthew K Labriola, Rajan T Gupta, et al. (2021). LRP1B mutations are associated with favorable outcomes to immune checkpoint inhibitors across multiple cancer types. Journal for immunotherapy of cancer, 9(3). pp. e001792–e001792. 10.1136/jitc-2020-001792 Retrieved from https://hdl.handle.net/10161/22508.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.



Matthew Kyle Labriola

Assistant Professor of Medicine

Rajan Tilak Gupta

Professor of Radiology

Abdominal Imaging; Multiparametric MR imaging of prostate cancer; MR imaging of the hepatobiliary system; Applications of dual energy CT in the abdomen and pelvis


Daniele Marin

Associate Professor of Radiology

Liver Imaging
Dual Energy CT
CT Protocol Optimization
Dose Reduction Strategies for Abdominal CT Applications


Yuan Wu

Associate Professor in Biostatistics & Bioinformatics

Survival analysis, Sequential clinical trial design, Machine learning, Causal inference, Non/Semi-parametric method, Statistical computing


Tian Zhang

Adjunct Associate Professor in the Department of Medicine

Michael Roger Harrison

Associate Professor of Medicine

Daniel James George

Eleanor Easley Distinguished Professor in the School of Medicine

Andrew John Armstrong

Professor of Medicine

I am a clinical and translational investigator focused on precision therapies and biomarkers in advanced prostate and other GU cancers.  I oversee a large research team of clinical and lab based investigators focused on improving patient outcomes, preventing metastatic disease, and understanding the biology of aggressive prostate cancer.  Some key themes:
1. Predictors of sensitivity and clinical efficacy of therapies in advanced prostate cancer
2. Novel designs of clinical trials and pharmacodynamic/translational studies in prostate, kidney, bladder cancer
3. Pre-operative models for drug development of novel agents in human testing in prostate cancer
4. Novel therapies and drug development for prostate, renal, bladder, and testicular cancer
5. Design of rational combination therapies in men with metastatic hormone-refractory prostate cancer
6. Developing prognostic and predictive models for progression and survival in metastatic prostate cancer
7. Examining surrogate markers of mortality in metastatic prostate cancer
8. Clear cell and non-clear cell renal cell carcinoma: natural history, sensitivity to novel agents including mTOR and VEGF inhibition

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