The efficacy of chemotherapy is limited by intratumoral senescent cells expressing PD-L2

Chemotherapy often generates intratumoral senescent cancer cells that strongly modify the tumor microenvironment, favoring immunosuppression and tumor growth. We discovered, through an unbiased proteomics screen, that the immune checkpoint inhibitor programmed cell death 1 ligand 2 (PD-L2) is highly upregulated upon induction of senescence in different types of cancer cells. PD-L2 is not required for cells to undergo senescence, but it is critical for senescent cells to evade the immune system and persist intratumorally. Indeed, after chemotherapy, PD-L2-deficient senescent cancer cells are rapidly eliminated and tumors do not produce the senescence-associated chemokines CXCL1 and CXCL2. Accordingly, PD-L2-deficient pancreatic tumors fail to recruit myeloid-derived suppressor cells and undergo regression driven by CD8 T cells after chemotherapy. Finally, antibody-mediated blockade of PD-L2 strongly synergizes with chemotherapy causing remission of mammary tumors in mice. The combination of chemotherapy with anti-PD-L2 provides a therapeutic strategy that exploits vulnerabilities arising from therapy-induced senescence. © 2024, The Author(s)

A Differentiation-Based Phylogeny of Cancer Subtypes

Histopathological classification of human tumors relies in part on the degree of differentiation of the tumor sample. To date, there is no objective systematic method to categorize tumor subtypes by maturation. In this paper, we introduce a novel computational algorithm to rank tumor subtypes according to the dissimilarity of their gene expression from that of stem cells and fully differentiated tissue, and thereby construct a phylogenetic tree of cancer. We validate our methodology with expression data of leukemia, breast cancer and liposarcoma subtypes and then apply it to a broader group of sarcomas. This ranking of tumor subtypes resulting from the application of our methodology allows the identification of genes correlated with differentiation and may help to identify novel therapeutic targets. Our algorithm represents the first phylogeny-based tool to analyze the differentiation status of human tumors

GEMC1 is a critical regulator of multiciliated cell differentiation.

The generation of multiciliated cells (MCCs) is required for the proper function of many tissues, including the respiratory tract, brain, and germline. Defects in MCC development have been demonstrated to cause a subclass of mucociliary clearance disorders termed reduced generation of multiple motile cilia (RGMC). To date, only two genes, Multicilin (MCIDAS) and cyclin O (CCNO) have been identified in this disorder in humans.We thank the Ministerio de Economía y Competitividad (MINECO) for funding to TS (BFU2012-39521) and MAV (SAF2012-38140; Fondo de Investigación Sanitaria (RD12/0042/0014); FEDER Funds); G.G.-G. is supported by ISCIII (PI13/00864); V.C. is funded by the Associazione Italiana per Ricerca sul Cancro (AIRC), the European Research Council (ERC) consolidator grant (614541), the Association for International Cancer Research (AICR) (13-0026), the Giovanni Armenise Award to V.C., the Epigen Progetto Bandiera (4.7) and the Fondazione Telethon (GGP13071); G.P. was supported by AIRC Borsa: Fondazione Giovanna Ciani Rif. 16444; S.S.B. was supported by a fellowship from Fundació La Caixa; P.A.K. was supported by an Early Postdoc Mobility Fellowship from the Swiss National Science Foundation; and B.T. was supported by a Severo Ochoa FPI Fellowship (MINECO). IRB Barcelona is a Severo Ochoa Award of Excellence Recipient (MINECO)

Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors

Patient-derived organoids (PDOs) recapitulate tumor architecture, contain cancer stem cells and have predictive value supporting personalized medicine. Here we describe a large-scale functional screen of dual-targeting bispecific antibodies (bAbs) on a heterogeneous colorectal cancer PDO biobank and paired healthy colonic mucosa samples. More than 500 therapeutic bAbs generated against Wingless-related integration site (WNT) and receptor tyrosine kinase (RTK) targets were functionally evaluated by high-content imaging to capture the complexity of PDO responses. Our drug discovery strategy resulted in the generation of MCLA-158, a bAb that specifically triggers epidermal growth factor receptor degradation in leucine-rich repeat-containing G-protein-coupled receptor 5-positive (LGR5+) cancer stem cells but shows minimal toxicity toward healthy LGR5+ colon stem cells. MCLA-158 exhibits therapeutic properties such as growth inhibition of KRAS-mutant colorectal cancers, blockade of metastasis initiation and suppression of tumor outgrowth in preclinical models for several epithelial cancer types.© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc

12 Grand Challenges in Single-Cell Data Science

Laehnemann D, Köster J, Szczurek E, et al. 12 Grand Challenges in Single-Cell Data Science. PeerJ. 2019.The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.</jats:p

Eleven grand challenges in single-cell data science

The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands—or even millions—of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.Medicine, Faculty ofScience, Faculty ofOther UBCNon UBCPathology and Laboratory Medicine, Department ofStatistics, Department ofReviewedFacult

TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis

Most patients with colorectal cancer die as a result of the disease spreading to other organs. However, no prevalent mutations have been associated with metastatic colorectal cancers1,2. Instead, particular features of the tumour microenvironment, such as lack of T-cell infiltration3, low type 1 T-helper cell (TH1) activity and reduced immune cytotoxicity2 or increased TGFβ levels4 predict adverse outcomes in patients with colorectal cancer. Here we analyse the interplay between genetic alterations and the tumour microenvironment by crossing mice bearing conditional alleles of four main colorectal cancer mutations in intestinal stem cells. Quadruple-mutant mice developed metastatic intestinal tumours that display key hallmarks of human microsatellite-stable colorectal cancers, including low mutational burden5, T-cell exclusion3 and TGFβ-activated stroma4,6,7. Inhibition of the PD-1–PD-L1 immune checkpoint provoked a limited response in this model system. By contrast, inhibition of TGFβ unleashed a potent and enduring cytotoxic T-cell response against tumour cells that prevented metastasis. In mice with progressive liver metastatic disease, blockade of TGFβ signalling rendered tumours susceptible to anti-PD-1–PD-L1 therapy. Our data show that increased TGFβ in the tumour microenvironment represents a primary mechanism of immune evasion that promotes T-cell exclusion and blocks acquisition of the TH1-effector phenotype. Immunotherapies directed against TGFβ signalling may therefore have broad applications in treating patients with advanced colorectal cancer

Stromal gene expression defines poor-prognosis subtypes in colorectal cancer

Recent molecular classifications of colorectal cancer (CRC) based on global gene expression profiles have defined subtypes displaying resistance to therapy and poor prognosis. Upon evaluation of these classification systems, we discovered that their predictive power arises from genes expressed by stromal cells rather than epithelial tumor cells. Bioinformatic and immunohistochemical analyses identify stromal markers that associate robustly with disease relapse across the various classifications. Functional studies indicate that cancer-associated fibroblasts (CAFs) increase the frequency of tumor-initiating cells, an effect that is dramatically enhanced by transforming growth factor (TGF)-β signaling. Likewise, we find that all poor-prognosis CRC subtypes share a gene program induced by TGF-β in tumor stromal cells. Using patient-derived tumor organoids and xenografts, we show that the use of TGF-β signaling inhibitors to block the cross-talk between cancer cells and the microenvironment halts disease progressio