All Publications


  • Targeting TRIP13 in favorable histology Wilms tumor with nuclear export inhibitors synergizes with doxorubicin COMMUNICATIONS BIOLOGY Mittal, K., Cooper, G. W., Lee, B. P., Su, Y., Skinner, K. T., Shim, J., Jonus, H. C., Kim, W., Doshi, M., Almanza, D., Kynnap, B. D., Christie, A. L., Yang, X., Cowley, G. S., Leeper, B. A., Morton, C. L., Dwivedi, B., Lawrence, T., Rupji, M., Keskula, P., Meyer, S., Clinton, C. M., Bhasin, M., Crompton, B. D., Tseng, Y., Boehm, J. S., Ligon, K. L., Root, D. E., Murphy, A. J., Weinstock, D. M., Gokhale, P. C., Spangle, J. M., Rivera, M. N., Mullen, E. A., Stegmaier, K., Goldsmith, K. C., Hahn, W. C., Hong, A. L. 2024; 7 (1): 426

    Abstract

    Wilms tumor (WT) is the most common renal malignancy of childhood. Despite improvements in the overall survival, relapse occurs in ~15% of patients with favorable histology WT (FHWT). Half of these patients will succumb to their disease. Identifying novel targeted therapies remains challenging in part due to the lack of faithful preclinical in vitro models. Here we establish twelve patient-derived WT cell lines and demonstrate that these models faithfully recapitulate WT biology using genomic and transcriptomic techniques. We then perform loss-of-function screens to identify the nuclear export gene, XPO1, as a vulnerability. We find that the FDA approved XPO1 inhibitor, KPT-330, suppresses TRIP13 expression, which is required for survival. We further identify synergy between KPT-330 and doxorubicin, a chemotherapy used in high-risk FHWT. Taken together, we identify XPO1 inhibition with KPT-330 as a potential therapeutic option to treat FHWTs and in combination with doxorubicin, leads to durable remissions in vivo.

    View details for DOI 10.1038/s42003-024-06140-6

    View details for Web of Science ID 001198699900005

    View details for PubMedID 38589567

    View details for PubMedCentralID PMC11001930

  • Investigating gene expression profiles associated with clinical radiation resistance in KEAP1/NFE2L2 wildtype lung cancer. Binkley, M. S., Jeon, Y., Nesselbush, M., Moding, E. J., Nabet, B., Almanza, D., Yoo, C., Kurtz, D. M., Owen, S., Backhus, L. M., Berry, M. F., Shrager, J. B., Ramchandran, K. J., Padda, S. K., Das, M., Neal, J. W., Wakelee, H. A., Alizadeh, A. A., Loo, B. W., Diehn, M. AMER ASSOC CANCER RESEARCH. 2021
  • KEAP1/NFE2L2 mutations to predict local recurrence after radiotherapy but not surgery in localized non-small cell lung cancer. Binkley, M. S., Jeon, Y., Nesselbush, M., Moding, E. J., Nabet, B., Almanza, D. S., Yoo, C., Kurtz, D., Owen, S., Backhus, L., Berry, M. F., Shrager, J. B., Ramchandran, K., Padda, S., Das, M., Neal, J. W., Wakelee, H. A., Alizadeh, A. A., Loo, B. W., Diehn, M. AMER SOC CLINICAL ONCOLOGY. 2020
  • Integrating genomic features for non-invasive early lung cancer detection. Nature Chabon, J. J., Hamilton, E. G., Kurtz, D. M., Esfahani, M. S., Moding, E. J., Stehr, H., Schroers-Martin, J., Nabet, B. Y., Chen, B., Chaudhuri, A. A., Liu, C. L., Hui, A. B., Jin, M. C., Azad, T. D., Almanza, D., Jeon, Y. J., Nesselbush, M. C., Co Ting Keh, L., Bonilla, R. F., Yoo, C. H., Ko, R. B., Chen, E. L., Merriott, D. J., Massion, P. P., Mansfield, A. S., Jen, J., Ren, H. Z., Lin, S. H., Costantino, C. L., Burr, R., Tibshirani, R., Gambhir, S. S., Berry, G. J., Jensen, K. C., West, R. B., Neal, J. W., Wakelee, H. A., Loo, B. W., Kunder, C. A., Leung, A. N., Lui, N. S., Berry, M. F., Shrager, J. B., Nair, V. S., Haber, D. A., Sequist, L. V., Alizadeh, A. A., Diehn, M. 2020; 580 (7802): 245-251

    Abstract

    Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

    View details for DOI 10.1038/s41586-020-2140-0

    View details for PubMedID 32269342

  • Integrating genomic features for non-invasive early lung cancer detection NATURE Chabon, J. J., Hamilton, E. G., Kurtz, D. M., Esfahani, M. S., Moding, E. J., Stehr, H., Schroers-Martin, J., Nabet, B. Y., Chen, B., Chaudhuri, A. A., Liu, C., Hui, A. B., Jin, M. C., Azad, T. D., Almanza, D., Jeon, Y., Nesselbush, M. C., Keh, L., Bonilla, R. F., Yoo, C. H., Ko, R. B., Chen, E. L., Merriott, D. J., Massion, P. P., Mansfield, A. S., Jen, J., Ren, H. Z., Lin, S. H., Costantino, C. L., Burr, R., Tibshirani, R., Gambhir, S. S., Berry, G. J., Jensen, K. C., West, R. B., Neal, J. W., Wakelee, H. A., Loo, B. W., Kunder, C. A., Leung, A. N., Lui, N. S., Berry, M. F., Shrager, J. B., Nair, V. S., Haber, D. A., Sequist, L. V., Alizadeh, A. A., Diehn, M. 2020
  • Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition. Cell Nabet, B. Y., Esfahani, M. S., Moding, E. J., Hamilton, E. G., Chabon, J. J., Rizvi, H. n., Steen, C. B., Chaudhuri, A. A., Liu, C. L., Hui, A. B., Almanza, D. n., Stehr, H. n., Gojenola, L. n., Bonilla, R. F., Jin, M. C., Jeon, Y. J., Tseng, D. n., Liu, C. n., Merghoub, T. n., Neal, J. W., Wakelee, H. A., Padda, S. K., Ramchandran, K. J., Das, M. n., Plodkowski, A. J., Yoo, C. n., Chen, E. L., Ko, R. B., Newman, A. M., Hellmann, M. D., Alizadeh, A. A., Diehn, M. n. 2020

    Abstract

    Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

    View details for DOI 10.1016/j.cell.2020.09.001

    View details for PubMedID 33007267

  • KEAP1/NFE2L2 mutations predict lung cancer radiation resistance that can be targeted by glutaminase inhibition. Cancer discovery Binkley, M. S., Jeon, Y. J., Nesselbush, M. n., Moding, E. J., Nabet, B. Y., Almanza, D. n., Kunder, C. n., Stehr, H. n., Yoo, C. H., Rhee, S. n., Xiang, M. n., Chabon, J. J., Hamilton, E. n., Kurtz, D. M., Gojenola, L. n., Owen, S. G., Ko, R. B., Shin, J. H., Maxim, P. G., Lui, N. S., Backhus, L. M., Berry, M. F., Shrager, J. B., Ramchandran, K. J., Padda, S. K., Das, M. n., Neal, J. W., Wakelee, H. A., Alizadeh, A. A., Loo, B. W., Diehn, M. n. 2020

    Abstract

    Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that KEAP1 and NFE2L2 mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in KEAP1/NFE2L2 mutation tumors, indicating they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate KEAP1/NFE2L2 mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes KEAP1 mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for KEAP1/NFE2L2 mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations.

    View details for DOI 10.1158/2159-8290.CD-20-0282

    View details for PubMedID 33071215

  • Circulating tumor DNA analysis to assess risk of progression after long-term response to PD-(L)1 blockade in NSCLC. Clinical cancer research : an official journal of the American Association for Cancer Research Hellmann, M. D., Nabet, B. Y., Rizvi, H. n., Chaudhuri, A. A., Wells, D. K., Dunphy, M. P., Chabon, J. J., Liu, C. L., Hui, A. B., Arbour, K. C., Luo, J. n., Preeshagul, I. R., Moding, E. J., Almanza, D. n., Bonilla, R. F., Sauter, J. L., Choi, H. n., Tenet, M. n., Abu-Akeel, M. n., Plodkowski, A. J., Perez-Johnston, R. n., Yoo, C. H., Ko, R. B., Stehr, H. n., Gojenola, L. n., Wakelee, H. A., Padda, S. K., Neal, J. W., Chaft, J. E., Kris, M. G., Rudin, C. M., Merghoub, T. n., Li, B. T., Alizadeh, A. A., Diehn, M. n. 2020

    Abstract

    Treatment with PD-(L)1 blockade can produce remarkably durable responses in non-small cell lung cancer (NSCLC) patients. However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression.In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (PFS≥12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq). Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing (n=18) or by targeted sequencing (n=6).31 NSCLC patients with long-term benefit to PD-(L)1 blockade were identified and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; by contrast, all four patients with detectable ctDNA eventually progressed (Fisher's p<0.0001; PPV 1 [95% CI 0.51-1]; NPV 0.93 [95% CI 0.80-0.99]).ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.

    View details for DOI 10.1158/1078-0432.CCR-19-3418

    View details for PubMedID 32046999