Timing and location dictate monocyte fate and their transition to tumor-associated macrophages.

Tumor-associated macrophages (TAMs) are a heterogeneous population of cells whose phenotypes and functions are shaped by factors that are incompletely understood. Herein, we asked when and where TAMs arise from blood monocytes and how they evolve during tumor development. We initiated pancreatic ductal adenocarcinoma (PDAC) in inducible monocyte fate-mapping mice and combined single-cell transcriptomics and high-dimensional flow cytometry to profile the monocyte-to-TAM transition. We revealed that monocytes differentiate first into a transient intermediate population of TAMs that generates two longer-lived lineages of terminally differentiated TAMs with distinct gene expression profiles, phenotypes, and intratumoral localization. Transcriptome datasets and tumor samples from patients with PDAC evidenced parallel TAM populations in humans and their prognostic associations. These insights will support the design of new therapeutic strategies targeting TAMs in PDAC.

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data.

Motivation: Spatial transcriptomics enables the analysis of cell crosstalk in healthy and diseased organs by capturing the transcriptomic profiles of millions of cells within their spatial contexts. However, spatial transcriptomics approaches also raise new computational challenges for the multidimensional data analysis associated with spatial coordinates. Results: In this context, we introduce a novel analytical framework called CellsFromSpace based on independent component analysis (ICA), which allows users to analyze various commercially available technologies without relying on a single-cell reference dataset. The ICA approach deployed in CellsFromSpace decomposes spatial transcriptomics data into interpretable components associated with distinct cell types or activities. ICA also enables noise or artifact reduction and subset analysis of cell types of interest through component selection. We demonstrate the flexibility and performance of CellsFromSpace using real-world samples to demonstrate ICA's ability to successfully identify spatially distributed cells as well as rare diffuse cells, and quantitatively deconvolute datasets from the Visium, Slide-seq, MERSCOPE, and CosMX technologies. Comparative analysis with a current alternative reference-free deconvolution tool also highlights CellsFromSpace's speed, scalability and accuracy in processing complex, even multisample datasets. CellsFromSpace also offers a user-friendly graphical interface enabling non-bioinformaticians to annotate and interpret components based on spatial distribution and contributor genes, and perform full downstream analysis. Availability and implementation: CellsFromSpace (CFS) is distributed as an R package available from github at https://github.com/gustaveroussy/CFS along with tutorials, examples, and detailed documentation.

B cells and the coordination of immune checkpoint inhibitor response in patients with solid tumors.

Immunotherapy profoundly changed the landscape of cancer therapy by providing long-lasting responses in subsets of patients and is now the standard of care in several solid tumor types. However, immunotherapy activity beyond conventional immune checkpoint inhibition is plateauing, and biomarkers are overall lacking to guide treatment selection. Most studies have focused on T cell engagement and response, but there is a growing evidence that B cells may be key players in the establishment of an organized immune response, notably through tertiary lymphoid structures. Mechanisms of B cell response include antibody-dependent cellular cytotoxicity and phagocytosis, promotion of CD4+ and CD8+ T cell activation, maintenance of antitumor immune memory. In several solid tumor types, higher levels of B cells, specific B cell subpopulations, or the presence of tertiary lymphoid structures have been associated with improved outcomes on immune checkpoint inhibitors. The fate of B cell subpopulations may be widely influenced by the cytokine milieu, with versatile roles for B-specific cytokines B cell activating factor and B cell attracting chemokine-1/CXCL13, and a master regulatory role for IL-10. Roles of B cell-specific immune checkpoints such as TIM-1 are emerging and could represent potential therapeutic targets. Overall, the expanding field of B cells in solid tumors of holds promise for the improvement of current immunotherapy strategies and patient selection.

Uterine adenosarcoma: Clinical significance of histological classification and SNP array analysis.

Mullerian adenosarcoma is a rare malignant biphasic tumor. The mesenchymal component may be low or high grade, with or without sarcomatous overgrowth (SO). Little is known about the molecular heterogeneity of these tumors. In this study, we aim to reclassify a large retrospective monocentric cohort of uterine adenosarcomas according to tumor grade and SO, to evaluate the clinical significance of pathological classification and to correlate with copy-number variations inferred from single nucleotide polymorphism array. Of the 67 uterine adenosarcomas, 18 (26.9%) were low grade without SO, 7 (10.4%) low grade with SO, 8 (11.9%) high grade without SO and 34 (50.7%) high grade with SO. SO, necrosis and RMS were more frequent in high grade than low grade adenosarcomas (p < 0.001). Low-rank test showed that recurrence-free survival was significantly shortened in high grade than low grade adenosarcomas (p = 0.035) and SO was associated with shortened overall and recurrence-free survival (p = 0.038 and p = 0.009, respectively). High-grade tumors displayed complex genomic profiles with multiple segmental losses including TP53, ATM and PTEN genes. The median genomic index was significantly higher in high grade than low grade tumors (27 [3-60] vs 5,3 [0-16], p < 0.0001) and was significantly higher in presence of SO in low grade tumors (12,8 [10-16] vs 2,6 [0-10], p = 0.0006). We propose to report sarcomatous overgrowth with the tumor grade for prognostication in adenosarcoma and representative sampling is crucial for evaluation of these histological criteria.

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).

Molecular profiling of biliary tract cancers reveals distinct genomic landscapes between circulating and tissue tumor DNA.

Biliary tract cancers (BTCs) are heterogeneous malignancies with dismal prognosis due to tumor aggressiveness and poor response to limited current therapeutic options. Tumor exome profiling has allowed to successfully establish targeted therapeutic strategies in the clinical management of cholangiocarcinoma (CCA). Still, whether liquid biopsy profiling could inform on BTC biology and patient management is unknown. In order to test this and generate novel insight into BTC biology, we analyzed the molecular landscape of 128 CCA patients, using a 394-gene NGS panel (Foundation Medicine). Among them, 32 patients had matched circulating tumor (ct) DNA and tumor DNA samples, where both samples were profiled. In both tumor and liquid biopsies, we identified an increased frequency of alterations in genes involved in genome integrity or chromatin remodeling, including ARID1A (15%), PBRM1 (9%), and BAP1 (14%), which were validated using an in-house-developed immunohistochemistry panel. ctDNA and tumor DNA showed variable concordance, with a significant correlation in the total number of detected variants, but some heterogeneity in the detection of actionable mutations. FGFR2 mutations were more frequently identified in liquid biopsies, whereas KRAS alterations were mostly found in tumors. All IDH1 mutations detected in tumor DNA were also identified in liquid biopsies. These findings provide novel insights in the concordance between the tumor and liquid biopsies genomic landscape in a large cohort of patients with BTC and highlight the complementarity of both analyses when guiding therapeutic prescription.

Patterns of Treatment Failure After Selective Rearranged During Transfection (RET) Inhibitors in Patients With Metastatic Medullary Thyroid Carcinoma.

PURPOSE: Medullary thyroid cancer (MTC) harbors frequent mutations in RET oncogene. Selective RET inhibitors (RETi) have emerged as effective treatments. However, resistance almost invariably occurs. METHODS: MTC patients who were initiated on RETi between 2018 and 2022 were included. Baseline characteristics, RET mutational status, RETi response, available tumor tissue and molecular profiles sampled pre- and post-RETi were analyzed. RESULTS: Among 46 MTC patients on RETi during the study period, 26 patients had discontinued at data cut-off because of progression (n = 16), death (n = 4), and toxicity (n = 6). The most frequent RET mutations at baseline were p.M918T (n = 29), and p.C634X (n = 6). Pre- and post-RETi molecular profiles were available in 14 patients. There was no primary resistance on pre-RETi samples. Post-RETi profiles revealed a bypass mechanism of resistance in 75% of the cases including RAS genes mutations (50%), FGFR2 and ALK fusions and and MYC p.P44L. RET solvent from and hinge region mutations was the only resistance mechanisms in 25% of the cases. Tumor samples from initial thyroidectomy, pre- and post-RETi, from six patients, showed an increase of the mean Ki 67-index of 7%, 17% and 40% respectively (P = 0.037) and a more aggressive poorly differentiated histology in three patients. DISCUSSION: Bypass resistance may be the most frequent mechanism of progression under RETi. A more aggressive histology may arise following RETi and warrants further investigation.

Divergent HLA variations and heterogeneous expression but recurrent HLA loss-of- heterozygosity and common HLA-B and TAP transcriptional silencing across advanced pediatric solid cancers.

The human leukocyte antigen (HLA) system is a major factor controlling cancer immunosurveillance and response to immunotherapy, yet its status in pediatric cancers remains fragmentary. We determined high-confidence HLA genotypes in 576 children, adolescents and young adults with recurrent/refractory solid tumors from the MOSCATO-01 and MAPPYACTS trials, using normal and tumor whole exome and RNA sequencing data and benchmarked algorithms. There was no evidence for narrowed HLA allelic diversity but discordant homozygosity and allele frequencies across tumor types and subtypes, such as in embryonal and alveolar rhabdomyosarcoma, neuroblastoma MYCN and 11q subtypes, and high-grade glioma, and several alleles may represent protective or susceptibility factors to specific pediatric solid cancers. There was a paucity of somatic mutations in HLA and antigen processing and presentation (APP) genes in most tumors, except in cases with mismatch repair deficiency or genetic instability. The prevalence of loss-of-heterozygosity (LOH) ranged from 5.9 to 7.7% in HLA class I and 8.0 to 16.7% in HLA class II genes, but was widely increased in osteosarcoma and glioblastoma (~15-25%), and for DRB1-DQA1-DQB1 in Ewing sarcoma (~23-28%) and low-grade glioma (~33-50%). HLA class I and HLA-DR antigen expression was assessed in 194 tumors and 44 patient-derived xenografts (PDXs) by immunochemistry, and class I and APP transcript levels quantified in PDXs by RT-qPCR. We confirmed that HLA class I antigen expression is heterogeneous in advanced pediatric solid tumors, with class I loss commonly associated with the transcriptional downregulation of HLA-B and transporter associated with antigen processing (TAP) genes, whereas class II antigen expression is scarce on tumor cells and occurs on immune infiltrating cells. Patients with tumors expressing sufficient HLA class I and TAP levels such as some glioma, osteosarcoma, Ewing sarcoma and non-rhabdomyosarcoma soft-tissue sarcoma cases may more likely benefit from T cell-based approaches, whereas strategies to upregulate HLA expression, to expand the immunopeptidome, and to target TAP-independent epitopes or possibly LOH might provide novel therapeutic opportunities in others. The consequences of HLA class II expression by immune cells remain to be established. Immunogenetic profiling should be implemented in routine to inform immunotherapy trials for precision medicine of pediatric cancers.