Single-cell resolution of longitudinal blood transcriptome profiles in rheumatoid arthritis, systemic lupus erythematosus and healthy control pregnancies.

OBJECTIVES: Comparative longitudinal analyses of cellular composition and peripheral blood gene expression in Rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and healthy pregnancies. METHODS: In total, 335 whole blood samples from 84 RA, SLE and healthy controls before pregnancy, at each trimester, 6 weeks, 6 months and 12 months post partum were analysed. We combined bulk and single cell RNA analyses for cell-type estimation, validated by flow cytometry, before combining this in a cell-type adjusted analysis for an improved resolution of unrecognised gene expression changes associated with RA and SLE pregnancies. RESULTS: Patients were well regulated throughout pregnancy, and few had pregnancy complications. In SLE, the interferon signature was augmented during pregnancy, and the pregnancy signature was continued post partum. An altered cell type composition strongly influences the profile. In the pregnancy signature, transcripts involved in galactosylation potentially altering the effector functions of autoantibodies became more evident. Several genes in the adjusted RA signature are expressed in mucosal associated invariant T cells. CONCLUSION: We found distinct RA, SLE and pregnancy signatures, and no expression patterns could be attributed to medication or disease activity. Our results support the need for close postpartum follow-up of patients with SLE. Gene expression patterns in RA were closer to healthy controls than to SLE, and primarily became evident after cell-type adjustment. Adjusting for cell abundance unravelled gene expression signatures less associated with variation in cell-composition and highlighted genes with expression profiles associated with changes in specialised cell populations.

Mismatch repair markers in preoperative and operative endometrial cancer samples; expression concordance and prognostic value.

BACKGROUND: The endometrial cancer mismatch repair (MMR) deficient subgroup is defined by loss of MSH6, MSH2, PMS2 or MLH1. We compare MMR status in paired preoperative and operative samples and investigate the prognostic impact of differential MMR protein expression levels. METHODS: Tumour lesions from 1058 endometrial cancer patients were immunohistochemically stained for MSH6, MSH2, PMS2 and MLH1. MMR protein expression was evaluated as loss or intact to determine MMR status, or by staining index to evaluate the prognostic potential of differential expression. Gene expression data from a local (n = 235) and the TCGA (n = 524) endometrial cancer cohorts was used for validation. RESULTS: We identified a substantial agreement in MMR status between paired curettage and hysterectomy samples. Individual high expression of all four MMR markers associated with non-endometrioid subtype, and high MSH6 or MSH2 strongly associated with several aggressive disease characteristics including high tumour grade and FIGO stage, and for MSH6, with lymph node metastasis. In multivariate Cox analysis, MSH6 remained an independent prognostic marker, also within the endometrioid low-grade subgroup (P < 0.001). CONCLUSION: We demonstrate that in addition to determine MMR status, MMR protein expression levels, particularly MSH6, may add prognostic information in endometrial cancer.

Single-cell profiling of low-stage endometrial cancers identifies low epithelial vimentin expression as a marker of recurrent disease.

BACKGROUND: Identification of aggressive low-stage endometrial cancers is challenging. So far, studies have failed to pinpoint robust features or biomarkers associated with risk of recurrence for these patients. METHODS: Imaging mass cytometry was used to examine single-cell expression of 23 proteins in 36 primary FIGO IB endometrial cancers, of which 17 recurred. Single-cell information was extracted for each tumor and unsupervised clustering was used to identify cellular phenotypes. Distinct phenotypes and cellular neighborhoods were compared in relation to recurrence. Cellular differences were validated in a separate gene expression dataset and the TCGA EC dataset. Vimentin protein expression was evaluated by IHC in pre-operative samples from 518 patients to validate its robustness as a prognostic marker. FINDINGS: The abundance of epithelial, immune or stromal cell types did not associate with recurrence. Clustering of patients based on tumor single cell marker expression revealed distinct patient clusters associated with outcome. A cell population neighboring CD8+ T cells, defined by vimentin, ER, and PR expressing epithelial cells, was more prevalent in non-recurrent tumors. Importantly, lower epithelial vimentin expression and lower gene expression of VIM associated with worse recurrence-free survival. Loss and low expression of vimentin was validated by IHC as a robust marker for recurrence in FIGO I stage disease and predicted poor prognosis also when including all patients and in endometrioid patients only. INTERPRETATION: This study reveals distinct characteristics in low-stage tumors and points to vimentin as a clinically relevant marker that may aid in identifying a here to unidentified subgroup of high-risk patients. FUNDING: A full list of funding that contributed to this study can be found in the Acknowledgements section.

High-dimensional immunotyping of tumors grown in obese and non-obese mice.

Obesity is a disease characterized by chronic low-grade systemic inflammation and has been causally linked to the development of 13 cancer types. Several studies have been undertaken to determine whether tumors evolving in obese environments adapt differential interactions with immune cells and whether this can be connected to disease outcome. Most of these studies have been limited to single-cell lines and tumor models and analysis of limited immune cell populations. Given the multicellular complexity of the immune system and its dysregulation in obesity, we applied high-dimensional suspension mass cytometry to investigate how obesity affects tumor immunity. We used a 36-marker immune-focused mass cytometry panel to interrogate the immune landscape of orthotopic syngeneic mouse models of pancreatic and breast cancer. Unanchored batch correction was implemented to enable simultaneous analysis of tumor cohorts to uncover the immunotypes of each cancer model and reveal remarkably model-specific immune regulation. In the E0771 breast cancer model, we demonstrate an important link to obesity with an increase in two T-cell-suppressive cell types and a decrease in CD8 T cells.

Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis.

Background: A major hurdle in translational endometrial cancer (EC) research is the lack of robust preclinical models that capture both inter- and intra-tumor heterogeneity. This has hampered the development of new treatment strategies for people with EC. Methods: EC organoids were derived from resected patient tumor tissue and expanded in a chemically defined medium. Established EC organoids were orthotopically implanted into female NSG mice. Patient tissue and corresponding models were characterized by morphological evaluation, biomarker and gene expression and by whole exome sequencing. A gene signature was defined and its prognostic value was assessed in multiple EC cohorts using Mantel-Cox (log-rank) test. Response to carboplatin and/or paclitaxel was measured in vitro and evaluated in vivo. Statistical difference between groups was calculated using paired t-test. Results: We report EC organoids established from EC patient tissue, and orthotopic organoid-based patient-derived xenograft models (O-PDXs). The EC organoids and O-PDX models mimic the tissue architecture, protein biomarker expression and genetic profile of the original tissue. Organoids show heterogenous sensitivity to conventional chemotherapy, and drug response is reproduced in vivo. The relevance of these models is further supported by the identification of an organoid-derived prognostic gene signature. This signature is validated as prognostic both in our local patient cohorts and in the TCGA endometrial cancer cohort. Conclusions: We establish robust model systems that capture both the diversity of endometrial tumors and intra-tumor heterogeneity. These models are highly relevant preclinical tools for the elucidation of the molecular pathogenesis of EC and identification of potential treatment strategies.

Erratum: Author Correction: Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis.

[This corrects the article DOI: 10.1038/s43856-021-00019-x.].