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Mohammad Shahrokh Esfahani

Publications

  • Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling. Nature Alig, S. K., Esfahani, M. S., Garofalo, A., Li, M. Y., Rossi, C., Flerlage, T., Flerlage, J. E., Adams, R., Binkley, M. S., Shukla, N., Jin, M. C., Olsen, M., Telenius, A., Mutter, J. A., Schroers-Martin, J. G., Sworder, B. J., Rai, S., King, D. A., Schultz, A., Bögeholz, J., Su, S., Kathuria, K. R., Liu, C. L., Kang, X., Strohband, M. J., Langfitt, D., Pobre-Piza, K. F., Surman, S., Tian, F., Spina, V., Tousseyn, T., Buedts, L., Hoppe, R., Natkunam, Y., Fornecker, L. M., Castellino, S. M., Advani, R., Rossi, D., Lynch, R., Ghesquières, H., Casasnovas, O., Kurtz, D. M., Marks, L. J., Link, M. P., André, M., Vandenberghe, P., Steidl, C., Diehn, M., Alizadeh, A. A. 2023

    Abstract

    The scarcity of malignant Hodgkin and Reed-Sternberg (HRS) cells hamper tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). Liquid biopsies, in contrast, show promise for molecular profiling of cHL due to relatively high circulating tumor DNA (ctDNA) levels1-4. Here, we show that the plasma representation of mutations exceeds the bulk tumor representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumors, we demonstrate HRS ctDNA shedding to be shaped by DNASE1L3, whose increased tumor microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R-mutations that are dependent on IL13 signaling and therapeutically targetable with IL4R blocking antibodies. Finally, using PhasED-Seq5 we demonstrate the clinical value of pre- and on-treatment ctDNA levels for longitudinally refining cHL risk prediction, and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL as well as capturing molecularly distinct subtypes with diagnostic, prognostic, and therapeutic potential.

    View details for DOI 10.1038/s41586-023-06903-x

    View details for PubMedID 38081297

  • 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

  • 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

  • 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

  • Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction. Cell Kurtz, D. M., Esfahani, M. S., Scherer, F., Soo, J., Jin, M. C., Liu, C. L., Newman, A. M., Duhrsen, U., Huttmann, A., Casasnovas, O., Westin, J. R., Ritgen, M., Bottcher, S., Langerak, A. W., Roschewski, M., Wilson, W. H., Gaidano, G., Rossi, D., Bahlo, J., Hallek, M., Tibshirani, R., Diehn, M., Alizadeh, A. A. 2019

    Abstract

    Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision thatdynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.

    View details for DOI 10.1016/j.cell.2019.06.011

    View details for PubMedID 31280963

  • Functional significance of U2AF1 S34F mutations in lung adenocarcinomas. Nature communications Esfahani, M. S., Lee, L. J., Jeon, Y. J., Flynn, R. A., Stehr, H. n., Hui, A. B., Ishisoko, N. n., Kildebeck, E. n., Newman, A. M., Bratman, S. V., Porteus, M. H., Chang, H. Y., Alizadeh, A. A., Diehn, M. n. 2019; 10 (1): 5712

    Abstract

    The functional role of U2AF1 mutations in lung adenocarcinomas (LUADs) remains incompletely understood. Here, we report a significant co-occurrence of U2AF1 S34F mutations with ROS1 translocations in LUADs. To characterize this interaction, we profiled effects of S34F on the transcriptome-wide distribution of RNA binding and alternative splicing in cells harboring the ROS1 translocation. Compared to its wild-type counterpart, U2AF1 S34F preferentially binds and modulates splicing of introns containing CAG trinucleotides at their 3' splice junctions. The presence of S34F caused a shift in cross-linking at 3' splice sites, which was significantly associated with alternative splicing of skipped exons. U2AF1 S34F induced expression of genes involved in the epithelial-mesenchymal transition (EMT) and increased tumor cell invasion. Finally, S34F increased splicing of the long over the short SLC34A2-ROS1 isoform, which was also associated with enhanced invasiveness. Taken together, our results suggest a mechanistic interaction between mutant U2AF1 and ROS1 in LUAD.

    View details for DOI 10.1038/s41467-019-13392-y

    View details for PubMedID 31836708

  • Effect of separate sampling on classification accuracy. Bioinformatics Shahrokh Esfahani, M., Dougherty, E. R. 2014; 30 (2): 242-250

    Abstract

    Measurements are commonly taken from two phenotypes to build a classifier, where the number of data points from each class is predetermined, not random. In this 'separate sampling' scenario, the data cannot be used to estimate the class prior probabilities. Moreover, predetermined class sizes can severely degrade classifier performance, even for large samples.We employ simulations using both synthetic and real data to show the detrimental effect of separate sampling on a variety of classification rules. We establish propositions related to the effect on the expected classifier error owing to a sampling ratio different from the population class ratio. From these we derive a sample-based minimax sampling ratio and provide an algorithm for approximating it from the data. We also extend to arbitrary distributions the classical population-based Anderson linear discriminant analysis minimax sampling ratio derived from the discriminant form of the Bayes classifier.All the codes for synthetic data and real data examples are written in MATLAB. A function called mmratio, whose output is an approximation of the minimax sampling ratio of a given dataset, is also written in MATLAB. All the codes are available at: http://gsp.tamu.edu/Publications/supplementary/shahrokh13b.

    View details for DOI 10.1093/bioinformatics/btt662

    View details for PubMedID 24257187

  • Integrating ctDNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer. Cancer discovery Moding, E. J., Shahrokh Esfahani, M., Jin, C., Hui, A. B., Nabet, B. Y., Liu, Y., Chabon, J. J., Binkley, M. S., Kurtz, D. M., Hamilton, E. G., Chaudhuri, A. A., Liu, C. L., Li, Z., Bonilla, R. F., Jiang, A. L., Lau, B. C., Lopez, P., He, J., Qiao, Y., Xu, T., Yao, L., Gandhi, S., Liao, Z., Das, M., Ramchandran, K. J., Padda, S. K., Neal, J. W., Wakelee, H. A., Gensheimer, M. F., Loo, B. W., Li, R., Lin, S. H., Alizadeh, A. A., Diehn, M. 2025: OF1-OF21

    Abstract

    This study demonstrates that combining tumor features, radiomics, and ctDNA analysis improves outcome prediction in NSCLC treated with CRT therapy. Our integrated model could enable personalized and response-adapted therapies to reduce toxicity and improve outcomes in patients.

    View details for DOI 10.1158/2159-8290.CD-24-1704

    View details for PubMedID 40299851

  • Inferred Gene Expression By Cell-Free DNA Profiling Allows Noninvasive Lymphoma Classification Mutter, J. A., Esfahani, M., Schroers-Martin, J., Alig, S. K., Hamilton, M. P., Sworder, B. J., Tessoulin, B., Boegeholz, J., Flerlage, T., Flerlage, J. E., Binkley, M. S., Sugio, T., Rossi, C., Olsen, M., Liu, C., Le Gouill, S., Kurtz, D. M., Diehn, M., Alizadeh, A. A. AMER SOC HEMATOLOGY. 2023

    View details for DOI 10.1182/blood-2023-186853

    View details for Web of Science ID 001159306701002

  • Determinants of resistance to engineered T cell therapies targeting CD19 in large B cell lymphomas. Cancer cell Sworder, B. J., Kurtz, D. M., Alig, S. K., Frank, M. J., Shukla, N., Garofalo, A., Macaulay, C. W., Shahrokh Esfahani, M., Olsen, M. N., Hamilton, J., Hosoya, H., Hamilton, M., Spiegel, J. Y., Baird, J. H., Sugio, T., Carleton, M., Craig, A. F., Younes, S. F., Sahaf, B., Sheybani, N. D., Schroers-Martin, J. G., Liu, C. L., Oak, J. S., Jin, M. C., Beygi, S., Hüttmann, A., Hanoun, C., Dührsen, U., Westin, J. R., Khodadoust, M. S., Natkunam, Y., Majzner, R. G., Mackall, C. L., Diehn, M., Miklos, D. B., Alizadeh, A. A. 2022

    Abstract

    Most relapsed/refractory large B cell lymphoma (r/rLBCL) patients receiving anti-CD19 chimeric antigen receptor (CAR19) T cells relapse. To characterize determinants of resistance, we profiled over 700 longitudinal specimens from two independent cohorts (n = 65 and n = 73) of r/rLBCL patients treated with axicabtagene ciloleucel. A method for simultaneous profiling of circulating tumor DNA (ctDNA), cell-free CAR19 (cfCAR19) retroviral fragments, and cell-free T cell receptor rearrangements (cfTCR) enabled integration of tumor and both engineered and non-engineered T cell effector-mediated factors for assessing treatment failure and predicting outcomes. Alterations in multiple classes of genes are associated with resistance, including B cell identity (PAX5 and IRF8), immune checkpoints (CD274), and those affecting the microenvironment (TMEM30A). Somatic tumor alterations affect CAR19 therapy at multiple levels, including CAR19 T cell expansion, persistence, and tumor microenvironment. Further, CAR19 T cells play a reciprocal role in shaping tumor genotype and phenotype. We envision these findings will facilitate improved chimeric antigen receptor (CAR) T cells and personalized therapeutic approaches.

    View details for DOI 10.1016/j.ccell.2022.12.005

    View details for PubMedID 36584673