Monica Nesselbush

All Publications

• An ultrasensitive method for detection of cell-free RNA. Nature Nesselbush, M. C., Luca, B. A., Jeon, Y. J., Jabara, I., Meador, C. B., Garofalo, A., Binkley, M. S., Hui, A. B., van 't Erve, I., Xu, N., Shi, W. Y., Liu, K. J., Sugio, T., Kastelowitz, N., Hamilton, E. G., Liu, C. L., Olsen, M., Bonilla, R. F., Wang, Y. P., Jiang, A., Lau, B., Eichholz, J., Banwait, M., Schroers-Martin, J., Boegeholz, J., King, D. A., Luikart, H., Esfahani, M. S., Mehrmohamadi, M., Stehr, H., Raclin, T., Tibshirani, R., Khush, K., Srinivas, S., Yu, H., Rogers, A. J., Nair, V. S., Isbell, J. M., Li, B. T., Piotrowska, Z., Sequist, L. V., Hata, A. N., Neal, J. W., Wakelee, H. A., Gentles, A. J., Alizadeh, A. A., Diehn, M. 2025

  Abstract

  Sensitive methods for detection of cell-free RNA (cfRNA) could facilitate non-invasive gene expression profiling and monitoring of diseases1-6. Here we describe RARE-seq (random priming and affinity capture of cfRNA fragments for enrichment analysis by sequencing), a method optimized for cfRNA analysis. We demonstrate that platelet contamination can substantially confound cfRNA analyses and develop an approach to overcome it. In analytical validations, we find RARE-seq to be approximately 50-fold more sensitive for detecting tumour-derived cfRNA than whole-transcriptome RNA sequencing (RNA-seq), with a limit of detection of 0.05%. To explore clinical utility, we profiled 437 plasma samples from 369 individuals with cancer or non-malignant conditions and controls. Detection of non-small-cell lung cancer expression signatures in cfRNA increased with stage (6 out of 20 (30%) in stage I; 5 out of 8 (63%) in stage II; 10 out of 15 (67%) in stage III; 80 out of 96 (83% sensitivity) in stage IV at 95% specificity) and RARE-seq was more sensitive than tumour-naive circulating tumour DNA (ctDNA) analysis. In patients with EGFR-mutant non-small-cell lung cancer who developed resistance to tyrosine kinase inhibitors, we detected both histological transformation and mutation-based resistance mechanisms. Finally, we demonstrate the potential utility of RARE-seq for determination of tissue of origin, assessing benign pulmonary conditions and tracking response to mRNA vaccines. These results highlight the potential value of ultrasensitive cfRNA analysis and provide proof of concept for diverse clinical applications.

  View details for DOI 10.1038/s41586-025-08834-1

  View details for PubMedID 40240612

  View details for PubMedCentralID 8060291

• A phase 2 study of amivantamab plus lazertinib in patients with <i>EGFR</i>-mutant lung cancer and active central nervous system disease Yu, H., Chen, M. F., Hui, A. B., Choudhury, N. J., Lee, J., Zheng, J., Ahn, L., Pupo, A., Nesselbush, M., Jabara, I., Heller, G., Arbour, K. C., Santini, F., Offin, M., Chaft, J. E., Young, R. J., Riely, G. J., Kris, M. G., Diehn, M., Boire, A. LIPPINCOTT WILLIAMS & WILKINS. 2024

  View details for Web of Science ID 001275557402015

• ULTRASENSITIVE URINARY LIQUID BIOPSY ANALYSIS FOR BCG RESPONSE ASSESSMENT IN HIGH-RISK NON-MUSCLE INVASIVE BLADDER CANCER Shi, W. Y., Liu, K. J., Esfahani, M. S., Schroers-Martin, J. G., Nesselbush, M., Chen, S. B., Alig, S. K., Mullane, P., Mach, K. E., Trabanino, L., Lee, T. J., Yoo, I., Vinh La, Rodriguez, G., Kornberg, Z., Shkolyar, E., Gill, H., Thong, A., Shah, J. B., Prado, K., Skinner, E. C., Alizadeh, A. A., Liao, J. C., Diehn, M. LIPPINCOTT WILLIAMS & WILKINS. 2024: E1169

  View details for Web of Science ID 001263885304019

• An Integrated Multimodal Framework for Noninvasive TCL Disease Detection and Monitoring Sugio, T., Shukla, N., Khodadoust, M. S., Nesselbush, M., Kato, K., Alig, S. K., Boegeholz, J., Schroers-Martin, J., Esfahani, M., Mutter, J. A., Garofalo, A., Jun, S., Hamilton, M. P., Rossi, C., Olsen, M., Liu, C., Akashi, K., Diehn, M., Alizadeh, A. A. AMER SOC HEMATOLOGY. 2023

  View details for DOI 10.1182/blood-2023-180492

  View details for Web of Science ID 001159306706091

• Inferring gene expression from cell-free DNA fragmentation profiles. Nature biotechnology Esfahani, M. S., Hamilton, E. G., Mehrmohamadi, M., Nabet, B. Y., Alig, S. K., King, D. A., Steen, C. B., Macaulay, C. W., Schultz, A., Nesselbush, M. C., Soo, J., Schroers-Martin, J. G., Chen, B., Binkley, M. S., Stehr, H., Chabon, J. J., Sworder, B. J., Hui, A. B., Frank, M. J., Moding, E. J., Liu, C. L., Newman, A. M., Isbell, J. M., Rudin, C. M., Li, B. T., Kurtz, D. M., Diehn, M., Alizadeh, A. A. 2022

  Abstract

  Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

  View details for DOI 10.1038/s41587-022-01222-4

  View details for PubMedID 35361996

• 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

  View details for Web of Science ID 000641160600087

• 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

  View details for Web of Science ID 000560368303348

• 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

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

  View details for Web of Science ID 000521531000011

• 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