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Prostate cancer is the second most common malignancy in men worldwide and consists of a mixture of tumor and non-tumor cell types. To characterize the prostate cancer tumor microenvironment, we perform single-cell RNA-sequencing on prostate biopsies, prostatectomy specimens, and patient-derived organoids from localized prostate cancer patients. We uncover heterogeneous cellular states in prostate epithelial cells marked by high androgen signaling states that are enriched in prostate cancer and identify a population of tumor-associated club cells that may be associated with prostate carcinogenesis. ERG -negative tumor cells, compared to ERG -positive cells, demonstrate shared heterogeneity with surrounding luminal epithelial cells and appear to give rise to common tumor microenvironment responses. Finally, we show that prostate epithelial organoids harbor tumor-associated epithelial cell states and are enriched with distinct cell types and states from their parent tissues. Our results provide diagnostically relevant insights and advance our understanding of the cellular states associated with prostate carcinogenesis. The changes that prostate cancer (PCa) induces in its microenvironment are not fully understood. Here the authors use single-cell RNA-seq and organoids to characterise how the microenvironment responds to PCa, and also identify tumour-associated epithelial cell states and club cells.

Pediatric hepatoblastoma is the most common primary liver cancer in infants and children. Studies of hepatoblastoma that focus exclusively on tumor cells demonstrate sparse somatic mutations and a common cell of origin, the hepatoblast, across patients. In contrast to the homogeneity these studies would suggest, hepatoblastoma tumors have a high degree of heterogeneity that can portend poor prognosis. In this study, we use single-cell transcriptomic techniques to analyze resected human pediatric hepatoblastoma specimens, and identify five hepatoblastoma tumor signatures that may account for the tumor heterogeneity observed in this disease. Notably, patient-derived hepatoblastoma spheroid cultures predict differential responses to treatment based on the transcriptomic signature of each tumor, suggesting a path forward for precision oncology for these tumors. In this work, we define hepatoblastoma tumor heterogeneity with single-cell resolution and demonstrate that patient-derived spheroids can be used to evaluate responses to chemotherapy. The mechanisms of tumor heterogeneity in pediatric hepatoblastoma remain poorly characterized. Here, the authors perform single cell RNA sequencing and identify 5 signatures with distinct responses to chemotherapy using patient-derived hepatoblastoma spheroid cultures.

In cancer, telomere maintenance is critical for the development of replicative immortality. Using genome sequences from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer Project, we calculated telomere content across 1299 cancer cell lines. We find that telomerase reverse transcriptase ( TERT ) expression correlates with telomere content in lung, central nervous system, and leukemia cell lines. Using CRISPR/Cas9 screening data, we show that lower telomeric content is associated with dependency of CST telomere maintenance genes. Increased dependencies of shelterin members are associated with wild-type TP53 status. Investigating the epigenetic regulation of TERT , we find widespread allele-specific expression in promoter-wildtype contexts. TERT promoter-mutant cell lines exhibit hypomethylation at PRC2-repressed regions, suggesting a cooperative global epigenetic state in the reactivation of telomerase. By incorporating telomere content with genomic features across comprehensively characterized cell lines, we provide further insights into the role of telomere regulation in cancer immortality.

Benign prostatic hyperplasia (BPH) is characterized by excessive cell proliferation and inflammation and affects most aging men. The development of new therapies for BPH requires a deeper understanding of the underlying pathophysiology and cellular components of BPH. Single-cell RNA-sequencing was performed on prostate tissue from 15 patients undergoing holmium laser enucleation of the prostate for treatment of BPH. Clustering and differential expression analysis on aligned single-cell RNA-seq data was performed to annotate all cell types. 16,234 cells were analyzed and specific stromal, epithelial, and immune subgroups were found to be strongly associated with inflammation. A rare luminal subgroup was identified and pseudotime analysis indicated this luminal subgroup might give rise to other luminal cells. Using a gene set derived from epithelial stem cells, we found that this luminal subgroup had a significantly higher stem cell signature score than all other epithelial subgroups, suggesting this subgroup is a luminal precursor state. Ligand-receptor interactions between stromal, epithelial, and immune cells were explored with CellPhoneDB. Significant interactions involving MIF, a pro-inflammatory cytokine that promotes epithelial cell growth and inflammatory response in the prostate, were identified between the progenitor-like luminal subgroup and both fibroblasts and macrophages. Our single-cell profiling of BPH provides a roadmap for investigating inflammation-linked cell subgroups and highlights a progenitor-like luminal subgroup interacting with other cell groups via MIF that may contribute to the inflammation and cell proliferation phenotype associated with BPH.

Background Significant racial disparities in prostate cancer incidence and mortality have been reported between African American Men (AAM), who are at increased risk for prostate cancer, and European American Men (EAM). In most of the studies carried out on prostate cancer, this population is underrepresented. With the advancement of genome‐wide association studies, several genetic predictor models of prostate cancer risk have been elaborated, as well as numerous studies that identify both germline and somatic mutations with clinical utility. Recent Findings Despite significant advances, the AAM population continues to be underrepresented in genomic studies, which can limit generalizability and potentially widen disparities. Here we outline racial disparities in currently available genomic applications that are used to estimate the risk of individuals developing prostate cancer and to identify personalized oncology treatment strategies. While the incidence and mortality of prostate cancer are different between AAM and EAM, samples from AAM remain to be unrepresented in different studies. Conclusion This disparity impacts the available genomic data on prostate cancer. As a result, the disparity can limit the predictive utility of the genomic applications and may lead to the widening of the existing disparities. More studies with substantially higher recruitment and engagement of African American patients are necessary to overcome this disparity.

Systemic iron balance is regulated by hepcidin, a peptide hormone secreted by the liver. By decreasing cell surface expression of the iron exporter ferroportin, hepcidin decreases iron absorption from the intestine and iron release from reticuloendothelial stores. Hepcidin excess has been implicated in the pathogenesis of anemia of chronic disease, while hepcidin deficiency has a key role in the pathogenesis of the iron overload disorder hemochromatosis. We have recently shown that hemojuvelin is a coreceptor for bone morphogenetic protein (BMP) signaling and that BMP signaling positively regulates hepcidin expression in liver cells in vitro. Here we show that BMP-2 administration increases hepcidin expression and decreases serum iron levels in vivo. We also show that soluble hemojuvelin (HJV.Fc) selectively inhibits BMP induction of hepcidin expression in vitro and that administration of HJV.Fc decreases hepcidin expression, increases ferroportin expression, mobilizes splenic iron stores, and increases serum iron levels in vivo. These data support a role for modulators of the BMP signaling pathway in treating diseases of iron overload and anemia of chronic disease.

Histologic variant (HV) subtypes of bladder cancer are clinically aggressive tumors that are more resistant to standard therapy compared to conventional urothelial carcinoma (UC). Little is known about the transcriptional programs that account for their biological differences. Here we show using single cell analysis that HVs harbor a tumor cell state characterized by expression of MUC16 (CA125), MUC4 , and KRT24 . This cell state is enriched in metastases, predicted to be highly resistant to chemotherapy, and linked with poor survival. We also find enriched expression of TM4SF1 , a transmembrane protein, in HV tumor cells. Chimeric antigen receptor (CAR) T cells engineered against TM4SF1 protein demonstrated in vitro and in vivo activity against bladder cancer cell lines in a TM4SF1 expression-dependent manner, highlighting its potential as a therapeutic target. Single cell analysis of histologic variant bladder tumors detects a shared CA125+ tumor cell state associated with aggressive clinical features and reveals enriched expression of TM4SF1, a membrane protein that can be targeted with CAR T cells.

Background Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors. Methods We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence. Results We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity. Conclusions CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods We conducted a retrospective cohort study using the University of California Health COVID Research Dataset, which includes electronic health data of patients tested for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) at 17 California medical centers. We identified adults tested for SARS‐CoV‐2 from 2/1/2020–12/31/2020 and selected a cohort of patients with cancer. We obtained demographic, clinical, cancer type, and antineoplastic therapy data. The primary outcome was hospitalization within 30d after the first positive SARS‐CoV‐2 test. Secondary outcomes were SARS‐CoV‐2 positivity and severe COVID‐19 (intensive care, mechanical ventilation, or death within 30d after the first positive test). We used multivariable logistic regression to identify cancer‐related factors associated with outcomes. Results We identified 409,462 patients undergoing SARS‐CoV‐2 testing. Of 49,918 patients with cancer, 1781 (3.6%) tested positive. Patients with cancer were less likely to test positive (RR 0.70, 95% CI: 0.67–0.74, p < 0.001). Among the 1781 SARS‐CoV‐2‐positive patients with cancer, BCR/ABL‐negative myeloproliferative neoplasms (RR 2.15, 95% CI: 1.25–3.41, p = 0.007), venetoclax (RR 2.96, 95% CI: 1.14–5.66, p = 0.028), and methotrexate (RR 2.72, 95% CI: 1.10–5.19, p = 0.032) were associated with greater hospitalization risk. Cancer and therapy types were not associated with severe COVID‐19. Conclusions In this large, diverse cohort, cancer was associated with a decreased risk of SARS‐CoV‐2 positivity. Patients with BCR/ABL‐negative myeloproliferative neoplasm or receiving methotrexate or venetoclax may be at increased risk of hospitalization following SARS‐CoV‐2 infection. Mechanistic and comparative studies are needed to validate findings. In a large dataset of patients who underwent SARS‐CoV‐2 testing across 17 California medical centers, we conducted multivariable analyses to evaluate cancer‐related risk factors for poor COVID‐19 outcomes. We found that patients with cancer had a lower risk of SARS‐CoV‐2 positivity than those without cancer. BCR/ABL‐negative myeloproliferative neoplasms, venetoclax use, and methotrexate use were associated with an increased risk of hospitalization after a COVID‐19 diagnosis.

Human prostate cancer can result from chromosomal rearrangements that lead to aberrant ETS gene expression. The mechanisms that lead to fusion-independent ETS factor upregulation and prostate oncogenesis remain relatively unknown. Here, we show that two neighboring transcription factors, Capicua ( CIC ) and ETS2 repressor factor ( ERF ), which are co-deleted in human prostate tumors can drive prostate oncogenesis. Concurrent CIC and ERF loss commonly occur through focal genomic deletions at chromosome 19q13.2. Mechanistically, CIC and ERF co-bind the proximal regulatory element and mutually repress the ETS transcription factor, ETV1 . Targeting ETV1 in CIC and ERF -deficient prostate cancer limits tumor growth. Thus, we have uncovered a fusion-independent mode of ETS transcriptional activation defined by concurrent loss of CIC and ERF .