All 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


    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

  • Genomic, Transcriptional, and Immunological Validation of Distinct Molecular Subtypes of Classic Hodgkin Lymphoma through Tissue-Based and Noninvasive Methods Alig, S. K., Esfahani, M., Garofalo, A., Li, M., Rossi, C., Flerlage, T., Flerlage, J. E., Adams, R., Binkley, M. S., Shukla, N., Jin, M., Olsen, M., Telenius, A., Mutter, J. A., Schroers-Martin, J., Sworder, B. J., Rai, S., King, D., Schultz, A., Bogeholz, J., Su, S., Kathuria, K. R., Liu, C., Kang, X., Langfitt, D. M., Pobre-Piza, K., Tian, F., Strohband, M. J., Spina, V., Tousseyn, T., Buedts, L., Fornecker, L., Castellino, S. M., Advani, R. H., Rossi, D., Lynch, R. C., Ghesquieres, H., Casasnovas, O., Kurtz, D. M., Marks, L. J., Link, M. P., Andre, M., Vandenberghe, P., Steidl, C., Diehn, M., Alizadeh, A. A. AMER SOC HEMATOLOGY. 2023
  • PlantRegMap: charting functional regulatory maps in plants NUCLEIC ACIDS RESEARCH Tian, F., Yang, D., Meng, Y., Jin, J., Gao, G. 2020; 48 (D1): D1104-D1113


    With the goal of charting plant transcriptional regulatory maps (i.e. transcription factors (TFs), cis-elements and interactions between them), we have upgraded the TF-centred database PlantTFDB ( to a plant regulatory data and analysis platform PlantRegMap ( over the past three years. In this version, we updated the annotations for the previously collected TFs and set up a new section, 'extended TF repertoires' (TFext), to allow users prompt access to the TF repertoires of newly sequenced species. In addition to our regular TF updates, we are dedicated to updating the data on cis-elements and functional interactions between TFs and cis-elements. We established genome-wide conservation landscapes for 63 representative plants and then developed an algorithm, FunTFBS, to screen for functional regulatory elements and interactions by coupling the base-varied binding affinities of TFs with the evolutionary footprints on their binding sites. Using the FunTFBS algorithm and the conservation landscapes, we further identified over 20 million functional TF binding sites (TFBSs) and two million functional interactions for 21 346 TFs, charting the functional regulatory maps of these 63 plants. These resources are publicly available at PlantRegMap ( and a cloud-based mirror (, providing the plant research community with valuable resources for decoding plant transcriptional regulatory systems.

    View details for DOI 10.1093/nar/gkz1020

    View details for Web of Science ID 000525956700141

    View details for PubMedID 31701126

    View details for PubMedCentralID PMC7145545

  • Painting a specific chromosome with CRISPR/Cas9 for live-cell imaging CELL RESEARCH Zhou, Y., Wang, P., Tian, F., Gao, G., Huang, L., Wei, W., Xie, X. 2017; 27 (2): 298-301

    View details for DOI 10.1038/cr.2017.9

    View details for Web of Science ID 000394187900011

    View details for PubMedID 28084328

    View details for PubMedCentralID PMC5339855

  • PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants NUCLEIC ACIDS RESEARCH Jin, J., Tian, F., Yang, D., Meng, Y., Kong, L., Luo, J., Gao, G. 2017; 45 (D1): D1040-D1045


    With the goal of providing a comprehensive, high-quality resource for both plant transcription factors (TFs) and their regulatory interactions with target genes, we upgraded plant TF database PlantTFDB to version 4.0 ( In the new version, we identified 320 370 TFs from 165 species, presenting a more comprehensive genomic TF repertoires of green plants. Besides updating the pre-existing abundant functional and evolutionary annotation for identified TFs, we generated three new types of annotation which provide more directly clues to investigate functional mechanisms underlying: (i) a set of high-quality, non-redundant TF binding motifs derived from experiments; (ii) multiple types of regulatory elements identified from high-throughput sequencing data; (iii) regulatory interactions curated from literature and inferred by combining TF binding motifs and regulatory elements. In addition, we upgraded previous TF prediction server, and set up four novel tools for regulation prediction and functional enrichment analyses. Finally, we set up a novel companion portal PlantRegMap ( for users to access the regulation resource and analysis tools conveniently.

    View details for DOI 10.1093/nar/gkw982

    View details for Web of Science ID 000396575500143

    View details for PubMedID 27924042

    View details for PubMedCentralID PMC5210657