Comment in Cell Rep Med. 2023 Jan 17;4(1):100908.

Comment on Cancer Cell. 2023 Jan 9;41(1):70-87.e14.

Comment in Cancer Cell. 2023 Jan 9;41(1):15-40.

Comment on Cancer Cell. 2022 Aug 8;40(8):865-878.e6.

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.

Comment on Cancer Cell. 2023 Jan 9;41(1):124-138.e6.

Comment in Cancer Cell. 2023 Jan 9;41(1):12-14.

Lung squamous cell carcinoma (LUSC) represents a major subtype of lung cancer with limited treatment options. KMT2D is one of the most frequently mutated genes in LUSC (>20%), and yet its role in LUSC oncogenesis remains unknown. Here, we identify KMT2D as a key regulator of LUSC tumorigenesis wherein Kmt2d deletion transforms lung basal cell organoids to LUSC. Kmt2d loss increases activation of receptor tyrosine kinases (RTKs), EGFR and ERBB2, partly through reprogramming the chromatin landscape to repress the expression of protein tyrosine phosphatases. These events provoke a robust elevation in the oncogenic RTK-RAS signaling. Combining SHP2 inhibitor SHP099 and pan-ERBB inhibitor afatinib inhibits lung tumor growth in Kmt2d-deficient LUSC murine models and in patient-derived xenografts (PDXs) harboring KMT2D mutations. Our study identifies KMT2D as a pivotal epigenetic modulator for LUSC oncogenesis and suggests that KMT2D loss renders LUSC therapeutically vulnerable to RTK-RAS inhibition.

Comment on Cancer Cell. 2023 Jan 9;41(1):58-69.

Disparities in cancer care disproportionately impact minority groups, members of which face challenges in accessing high-quality cancer care, remain underrepresented in clinical trials, and experience significant financial toxicity and discrimination during their cancer journey. Diversifying our workforce, improving access to trials, and allocating research funding for equitable initiatives should be prioritized.

Therapy resistance is a major challenge in the treatment of cancer. Here, we performed CRISPR-Cas9 screens across a broad range of therapies used in acute myeloid leukemia to identify genomic determinants of drug response. Our screens uncover a selective dependency on RNA splicing factors whose loss preferentially enhances response to the BCL2 inhibitor venetoclax. Loss of the splicing factor RBM10 augments response to venetoclax in leukemia yet is completely dispensable for normal hematopoiesis. Combined RBM10 and BCL2 inhibition leads to mis-splicing and inactivation of the inhibitor of apoptosis XIAP and downregulation of BCL2A1, an anti-apoptotic protein implicated in venetoclax resistance. Inhibition of splicing kinase families CLKs (CDC-like kinases) and DYRKs (dual-specificity tyrosine-regulated kinases) leads to aberrant splicing of key splicing and apoptotic factors that synergize with venetoclax, and overcomes resistance to BCL2 inhibition. Our findings underscore the importance of splicing in modulating response to therapies and provide a strategy to improve venetoclax-based treatments.

Author information: (1)Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA. (2)Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21213, USA. (3)Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: saravana@med.umich.edu. (4)Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA. (5)Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. (6)International Institute for Molecular Oncology, 60-203 Poznań, Poland; Postgraduate School of Molecular Medicine, Medical University of Warsaw, 02-091 Warsaw, Poland. (7)Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA. (8)Van Andel Research Institute, Grand Rapids, MI 49503, USA. (9)Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA. (10)Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA. (11)Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. (12)McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63130, USA; Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA. (13)Department of Biomedical Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA. (14)Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21213, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. (15)Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA. (16)Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA; Division of Medical Oncology, Department of Medicine, Washington University School of Medicine, 660 S. Euclid Avenue, St. Louis, MO 63110, USA. (17)Departments of Pathology and Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. (18)Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA. (19)Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA. (20)Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA. (21)Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA; Department of Cell Biology and Physiology, Washington University in St. Louis, St. Louis, MO 63130, USA. (22)Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA. (23)Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. (24)Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA. (25)International Institute for Molecular Oncology, 60-203 Poznań, Poland; Heliodor Swiecicki Clinical Hospital in Poznań, ul. Przybyszewskiego 49, 60-355 Poznań, Poland; Poznań University of Medical Sciences, 61-701 Poznań, Poland. (26)Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, USA. (27)Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21213, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. (28)Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: chris.ricketts@nih.gov. (29)Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21213, USA; Department of Chemical and Biomolecular Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21218, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: huizhang@jhu.edu. (30)Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63130, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, USA. Electronic address: lding@wustl.edu.

Comment on Cancer Cell. 2023 Jan 9;41(1):106-123.e10.

Comment in Cancer Cell. 2023 Jan 9;41(1):9-11.

Comment in Cancer Cell. 2023 Jan 9;41(1):7-9.

Integrated molecular analysis of human cancer has yielded molecular classification for precise management of cancer patients. Here, we analyzed the whole genomic, epigenomic, transcriptomic, and proteomic data of 155 esophageal squamous cell carcinomas (ESCCs). Multi-omics analysis led to the classification of ESCCs into four subtypes: cell cycle pathway activation, NRF2 oncogenic activation, immune suppression (IS), and immune modulation (IM). IS and IM cases were highly immune infiltrated but differed in the type and distribution of immune cells. IM cases showed better response to immune checkpoint blockade therapy than other subtypes in a clinical trial. We further developed a classifier with 28 features to identify the IM subtype, which predicted anti-PD-1 therapy response with 85.7% sensitivity and 90% specificity. These results emphasize the clinical value of unbiased molecular classification based on multi-omics data and have the potential to further improve the understanding and treatment of ESCC.

T cells are at the center of cancer immunology because of their ability to recognize mutations in tumor cells and directly mediate cancer cell killing. Immunotherapies to rejuvenate exhausted T cell responses have transformed the clinical management of several malignancies. In parallel, the development of novel multidimensional analysis platforms, such as single-cell RNA sequencing and high-dimensional flow cytometry, has yielded unprecedented insights into immune cell biology. This convergence has revealed substantial heterogeneity of tumor-infiltrating immune cells in single tumors, across tumor types, and among individuals with cancer. Here we discuss the opportunities and challenges of studying the complex tumor microenvironment with -omics technologies that generate vast amounts of data, highlighting the opportunities and limitations of these technologies with a particular focus on interpreting high-dimensional studies of CD8+ T cells in the tumor microenvironment.