Development of Novel Models of Aggressive Variants of Castration-resistant Prostate Cancer.

BACKGROUND: Genomic studies have identified new subsets of aggressive prostate cancer (PCa) with poor prognosis (eg, neuroendocrine prostate cancer [NEPC], PCa with DNA damage response [DDR] alterations, or PCa resistant to androgen receptor pathway inhibitors [ARPIs]). Development of novel therapies relies on the availability of relevant preclinical models. OBJECTIVE: To develop new preclinical models (patient-derived xenograft [PDX], PDX-derived organoid [PDXO], and patient-derived organoid [PDO]) representative of the most aggressive variants of PCa and to develop a new drug evaluation strategy. DESIGN, SETTING, AND PARTICIPANTS: NEPC (n = 5), DDR (n = 7), and microsatellite instability (MSI)-high (n = 1) PDXs were established from 51 patients with metastatic PCa; PDXOs (n = 16) and PDOs (n = 6) were developed to perform drug screening. Histopathology and treatment response were characterized. Molecular profiling was performed by whole-exome sequencing (WES; n = 13), RNA sequencing (RNA-seq; n = 13), and single-cell RNA-seq (n = 14). WES and RNA-seq data from patient tumors were compared with the models. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Relationships with outcome were analyzed using the multivariable chi-square test and the tumor growth inhibition test. RESULTS AND LIMITATIONS: Our PDXs captured both common and rare molecular phenotypes and their molecular drivers, including alterations of BRCA2, CDK12, MSI-high status, and NEPC. RNA-seq profiling demonstrated broad representation of PCa subtypes. Single-cell RNA-seq indicates that PDXs reproduce cellular and molecular intratumor heterogeneity. WES of matched patient tumors showed preservation of most genetic driver alterations. PDXOs and PDOs preserve drug sensitivity of the matched tissue and can be used to determine drug sensitivity. CONCLUSIONS: Our models reproduce the phenotypic and genomic features of both common and aggressive PCa variants and capture their molecular heterogeneity. Successfully developed aggressive-variant PCa preclinical models provide an important tool for predicting tumor response to anticancer therapy and studying resistance mechanisms. PATIENT SUMMARY: In this report, we looked at the outcomes of preclinical models from patients with metastatic prostate cancer enrolled in the MATCH-R trial (NCT02517892).

Immune checkpoints are predominantly co-expressed by clonally expanded CD4+FoxP3+ intratumoral T-cells in primary human cancers.

BACKGROUND: In addition to anti-PD(L)1, anti-CTLA-4 and anti-LAG-3, novel immune checkpoint proteins (ICP)-targeted antibodies have recently failed to demonstrate significant efficacy in clinical trials. In these trials, patients were enrolled without screening for drug target expression. Although these novel ICP-targeted antibodies were expected to stimulate anti-tumor CD8 + T-cells, the rationale for their target expression in human tumors relied on pre-clinical IHC stainings and transcriptomic data, which are poorly sensitive and specific techniques for assessing membrane protein expression on immune cell subsets. Our aim was to describe ICP expression on intratumoral T-cells from primary solid tumors to better design upcoming neoadjuvant cancer immunotherapy trials. METHODS: We prospectively performed multiparameter flow cytometry and single-cell RNA sequencing (scRNA-Seq) paired with TCR sequencing on freshly resected human primary tumors of various histological types to precisely determine ICP expression levels within T-cell subsets. RESULTS: Within a given tumor type, we found high inter-individual variability for tumor infiltrating CD45 + cells and for T-cells subsets. The proportions of CD8+ T-cells (~ 40%), CD4+ FoxP3- T-cells (~ 40%) and CD4+ FoxP3+ T-cells (~ 10%) were consistent across patients and indications. Intriguingly, both stimulatory (CD25, CD28, 4-1BB, ICOS, OX40) and inhibitory (PD-1, CTLA-4, PD-L1, CD39 and TIGIT) checkpoint proteins were predominantly co-expressed by intratumoral CD4+FoxP3+ T-cells. ScRNA-Seq paired with TCR sequencing revealed that T-cells with high clonality and high ICP expressions comprised over 80% of FoxP3+ cells among CD4+ T-cells. Unsupervised clustering of flow cytometry and scRNAseq data identified subsets of CD8+ T-cells and of CD4+ FoxP3- T-cells expressing certain checkpoints, though these expressions were generally lower than in CD4+ FoxP3+ T-cell subsets, both in terms of proportions among total T-cells and ICP expression levels. CONCLUSIONS: Tumor histology alone does not reveal the complete picture of the tumor immune contexture. In clinical trials, assumptions regarding target expression should rely on more sensitive and specific techniques than conventional IHC or transcriptomics. Flow cytometry and scRNAseq accurately characterize ICP expression within immune cell subsets. Much like in hematology, flow cytometry can better describe the immune contexture of solid tumors, offering the opportunity to guide patient treatment according to drug target expression rather than tumor histological type.

Stepwise GATA1 and SMC3 mutations alter megakaryocyte differentiation in a Down syndrome leukemia model.

Acute megakaryoblastic leukemia of Down syndrome (DS-AMKL) is a model of clonal evolution from a preleukemic transient myeloproliferative disorder requiring both a trisomy 21 (T21) and a GATA1s mutation to a leukemia driven by additional driver mutations. We modeled the megakaryocyte differentiation defect through stepwise gene editing of GATA1s, SMC3+/-, and MPLW515K, providing 20 different T21 or disomy 21 (D21) induced pluripotent stem cell (iPSC) clones. GATA1s profoundly reshaped iPSC-derived hematopoietic architecture with gradual myeloid-to-megakaryocyte shift and megakaryocyte differentiation alteration upon addition of SMC3 and MPL mutations. Transcriptional, chromatin accessibility, and GATA1-binding data showed alteration of essential megakaryocyte differentiation genes, including NFE2 downregulation that was associated with loss of GATA1s binding and functionally involved in megakaryocyte differentiation blockage. T21 enhanced the proliferative phenotype, reproducing the cellular and molecular abnormalities of DS-AMKL. Our study provides an array of human cell-based models revealing individual contributions of different mutations to DS-AMKL differentiation blockage, a major determinant of leukemic progression.

Macrophage migration inhibitory factor is overproduced through EGR1 in TET2low resting monocytes.

Somatic mutation in TET2 gene is one of the most common clonal genetic events detected in age-related clonal hematopoiesis as well as in chronic myelomonocytic leukemia (CMML). In addition to being a pre-malignant state, TET2 mutated clones are associated with an increased risk of death from cardiovascular disease, which could involve cytokine/chemokine overproduction by monocytic cells. Here, we show in mice and in human cells that, in the absence of any inflammatory challenge, TET2 downregulation promotes the production of MIF (macrophage migration inhibitory factor), a pivotal mediator of atherosclerotic lesion formation. In healthy monocytes, TET2 is recruited to MIF promoter and interacts with the transcription factor EGR1 and histone deacetylases. Disruption of these interactions as a consequence of TET2-decreased expression favors EGR1-driven transcription of MIF gene and its secretion. MIF favors monocytic differentiation of myeloid progenitors. These results designate MIF as a chronically overproduced chemokine and a potential therapeutic target in patients with clonal TET2 downregulation in myeloid cells.

The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma.

The identity of cancer cells is defined by the interplay between genetic, epigenetic transcriptional and post-transcriptional variation. A lot of this variation is present in RNA-seq data and can be captured at once using reference-free, k-mer analysis. An important issue with k-mer analysis, however, is the difficulty of distinguishing signal from noise. Here, we use two independent lung adenocarcinoma datasets to identify all reproducible events at the k-mer level, in a tumor versus normal setting. We find reproducible events in many different locations (introns, intergenic, repeats) and forms (spliced, polyadenylated, chimeric etc.). We systematically analyze events that are ignored in conventional transcriptomics and assess their value as biomarkers and for tumor classification, survival prediction, neoantigen prediction and correlation with the immune microenvironment. We find that unannotated lincRNAs, novel splice variants, endogenous HERV, Line1 and Alu repeats and bacterial RNAs each contribute to different, important aspects of tumor identity. We argue that differential RNA-seq analysis of tumor/normal sample collections would benefit from this type k-mer analysis to cast a wider net on important cancer-related events. The code is available at https://github.com/Transipedia/dekupl-lung-cancer-inter-cohort.

Cancer Induces a Stress Ileopathy Depending on ß-Adrenergic Receptors and Promoting Dysbiosis that Contributes to Carcinogenesis.

Gut dysbiosis has been associated with intestinal and extraintestinal malignancies, but whether and how carcinogenesis drives compositional shifts of the microbiome to its own benefit remains an open conundrum. Here, we show that malignant processes can cause ileal mucosa atrophy, with villous microvascular constriction associated with dominance of sympathetic over cholinergic signaling. The rapid onset of tumorigenesis induced a burst of REG3γ release by ileal cells, and transient epithelial barrier permeability that culminated in overt and long-lasting dysbiosis dominated by Gram-positive Clostridium species. Pharmacologic blockade of ß-adrenergic receptors or genetic deficiency in Adrb2 gene, vancomycin, or cohousing of tumor bearers with tumor-free littermates prevented cancer-induced ileopathy, eventually slowing tumor growth kinetics. Patients with cancer harbor distinct hallmarks of this stress ileopathy dominated by Clostridium species. Hence, stress ileopathy is a corollary disease of extraintestinal malignancies requiring specific therapies. SIGNIFICANCE: Whether gut dysbiosis promotes tumorigenesis and how it controls tumor progression remain open questions. We show that 50% of transplantable extraintestinal malignancies triggered a ß-adrenergic receptor-dependent ileal mucosa atrophy, associated with increased gut permeability, sustained Clostridium spp.-related dysbiosis, and cancer growth. Vancomycin or propranolol prevented cancer-associated stress ileopathy. This article is highlighted in the In This Issue feature, p. 873.

Applications of single-cell and bulk RNA sequencing in onco-immunology.

The rising interest for precise characterization of the tumour immune contexture has recently brought forward the high potential of RNA sequencing (RNA-seq) in identifying molecular mechanisms engaged in the response to immunotherapy. In this review, we provide an overview of the major principles of single-cell and conventional (bulk) RNA-seq applied to onco-immunology. We describe standard preprocessing and statistical analyses of data obtained from such techniques and highlight some computational challenges relative to the sequencing of individual cells. We notably provide examples of gene expression analyses such as differential expression analysis, dimensionality reduction, clustering and enrichment analysis. Additionally, we used public data sets to exemplify how deconvolution algorithms can identify and quantify multiple immune subpopulations from either bulk or single-cell RNA-seq. We give examples of machine and deep learning models used to predict patient outcomes and treatment effect from high-dimensional data. Finally, we balance the strengths and weaknesses of single-cell and bulk RNA-seq regarding their applications in the clinic.