Urine cell flow cytometry analysis of PD-L1 expression and DNA content for bladder cancer.

466 Background: Bladder cancer is the fifth most common cancer in the United States. PD-1/PD-L1, a pathway used by cancer cells to evade immune response, correlates with bladder cancer severity and has emerged as a target in bladder cancer treatment. Chromosomal instability is also a prominent feature associated with the development of bladder cancer. A method to unbiasedly analyze PD-L1 expression and DNA content in cells from urine samples will help us better understand bladder cancer. Methods: To evaluate the PD-L1 expression and DNA content, we developed a 4-color flow assay. Cells in urine samples were pelleted, fixed/permeabilized (in incellMAX, IncellDx Inc.) and stained with antibodies against pan-cytokeratin (CK), CD45, PD-L1 and a cell cycle dye. The stained samples were analyzed by a flow cytometer alongside stained control cells. Results: Fifty bladder cancer patient and 15 normal donor urine samples were collected and tested with this assay. We could distinguish epithelial cells (pan-CK+) and white blood cells (WBCs, CD45+) in urine samples and obtain PD-L1 expression and DNA content information simultaneously from these cell populations. The patient samples showed a significantly higher percentage of WBCs with substantial PD-L1 expression. The percentage of PD-L1 positive epithelial cells was not distinguishable between normal donor and patient samples. However, increased post G1 epithelial cells ( > 5%) were observed in a majority of bladder cancer patients, with around 25% of samples showing a DNA index above 1.05. In addition, a comparison of urine collection fixatives showed that incellMAX-fixed samples had the best single cell recovery and DNA content measurement, as shown by lower cell cycle dye staining variability (lower rCV). Statistically significant differences were found between cancer patients and normal samples. Conclusions: We developed a flow cytometry-based method to investigate PD-L1 and DNA content simultaneously in cells from urine samples. Comparing urine samples from bladder cancer patients and normal yielded statistically significant differences that could provide valuable information for bladder cancer patient management.

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Developing a new urine cell flow cytometry analysis of PD-L1 expression and DNA content for diagnosis of bladder cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.8_suppl.60 ◽

2019 ◽

Vol 37 (8_suppl) ◽

pp. 60-60

Author(s):

Shaheen Riadh Alanee ◽

Mustafa Deebajah ◽

Pin-I Chen ◽

Alice (Xiaoyang) Wang ◽

Bruce Kendrick Patterson

Keyword(s):

Flow Cytometry ◽

Bladder Cancer ◽

Epithelial Cells ◽

Cancer Patients ◽

Dna Content ◽

The United States ◽

Urine Samples ◽

Normal Donor ◽

Urine Testing ◽

In Cells

60 Background: Bladder cancer is the fifth most common cancer in the United States. PD-1/PD-L1, a pathway used by cancer cells to evade immune response, correlates with bladder cancer severity and has emerged as a target in bladder cancer treatment. Chromosomal instability is also a prominent feature associated with the development of bladder cancer. A method for unbiased analysis of PD-L1 expression and DNA content in cells from urine samples promises to be a new test for diagnosis of bladder cancer. Methods: To evaluate the PD-L1 expression and DNA content, we developed a 4-color flow assay. Cells in voided urine samples were pelleted, fixed in incellMAX (IncellDx Inc.) and stained with antibodies against pan-cytokeratin (CK), CD45, PD-L1 and a cell cycle dye. The stained samples were analyzed by a flow cytometer alongside stained control cells. Results: Fifty bladder cancer patient and 15 normal donor urine samples were collected and tested with this assay. We could distinguish epithelial cells (pan-CK+) and white blood cells (WBCs, CD45+) in urine samples and obtain PD-L1 expression and DNA content information simultaneously from these cell populations. The patient samples showed a significantly higher percentage of WBCs with substantial PD-L1 expression (P < 0.001). The percentage of PD-L1 positive epithelial cells was not distinguishable between normal donor and patient samples. However increased post G1 epithelial cells ( > 5%) were observed in a majority of bladder cancer patients, with around 25% of samples showing a DNA index above 1.05. Conclusions: We developed a flow cytometry-based method to investigate PD-L1 and DNA content simultaneously in cells from urine samples that could provide us with a new method to accurately identify bladder cancer patients through urine testing.

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Uranium concentration variation dependency on gender correlated with age of bladder cancer patient

International Journal of Research in Pharmaceutical Sciences ◽

10.26452/ijrps.v10i3.1363 ◽

2019 ◽

Vol 10 (3) ◽

pp. 1730-1734

Author(s):

Aseel S. Mahmood ◽

Omar Sh. Shafeq ◽

Mohamed S. Shafiq

Keyword(s):

Bladder Cancer ◽

Cancer Patient ◽

Cancer Patients ◽

Uranium Concentration ◽

Bladder Cancer Patient ◽

Age Group ◽

Average Period ◽

Age And Gender ◽

Males And Females ◽

And Gender

Human health was and still the most important problem and objective of all most researches. Finding out what causes in the decadence of healthiness of Iraqi population is our tendency in the present work, Uranium causing cancer that is affected by a correlation between age and gender of bladder cancer patients is studied in the present work. Mean of Uranium concentration (Uc) decreased with increasing age for all age group without dependency on gender. While, there is a wide dispersion in Mean Uc excretion between males and females, due to the effect of correlated gender with age, where female Mean Uc is maximum at age 50-69 year (2.355 µg/L), and it's higher than male Mean Uc (2.022 µg/L) in this age stage because of menopause, also average period of illness and the percentage of patients are affected by correlated gender with age. So that factor of gender correlation with age affects in the calculation of background levels and radiation exposure and causing bladder cancer incidence.

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82 Single-cell RNA sequencing and CITE-Seq analysis of bladder cancer patient urine with matched tumor and peripheral blood suggests urine as a window into the tumor immune microenvironment

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.082 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A90-A90

Author(s):

Michelle Tran ◽

Adam Farkas ◽

Kristin Beaumont ◽

Timothy O’Donnell ◽

Reza Mehrazin ◽

...

Keyword(s):

Bladder Cancer ◽

Cancer Patient ◽

Single Cell ◽

Cancer Patients ◽

Immune Cells ◽

Peripheral Blood ◽

Single Cells ◽

Bladder Cancer Patient ◽

Immune Microenvironment ◽

Tumor Immune Microenvironment

BackgroundFDA-approved immunotherapies for early and advanced stage bladder cancer have response rates of 15–65% in bladder cancer, suggesting that tumor-associated resistance mechanisms undermine their efficacy. Accordingly, there is an unmet need to identify accessible biomarkers that predict response. Urine, which is in direct contact with urothelial tumors, represents an easily accessible patient material that may reflect cellular and/or genetic signatures related to immune resistance. It has been demonstrated that urine from bladder cancer patients contains not only tumor cells, which are routinely assessed by clinical urinalyses, but also immune cells that previous studies suggest may reflect the tumor microenvironment (TME).1 However, the concordance between cells in the urine and those in bladder tumors is unknown., Here, we characterized patient urine in an unbiased fashion by performing the first single-cell RNA sequencing (scRNAseq) and Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) on matched bladder cancer patient urine, tumor, and peripheral blood.MethodsMatched tumor tissue, urine, and peripheral blood were collected from bladder cancer patients (n=7) during surgery; either trans-urethral resection of bladder tumor or cystectomy. All three tissues were processed to single-cell suspensions and sequenced using the 10X Genomics platform (scRNAseq: 17 samples, CITE-seq: 3 samples). These sequencing approaches permitted quantification of both transcriptomic and surface protein expression of 54,469 cells total.2 3 Analysis was performed using Seurat, Enrichr, and Monocle packages and platforms.4 5 6Results scRNAseq of urine from bladder cancer patients revealed several immune populations including CD4+ and CD8+ T cells, Treg cells, NK cells, B cells, neutrophils, dendritic cells, monocytes, and macrophages in addition to non-hematopoietic lineages including bladder epithelial cells, neuronal cells, prostate epithelial cells, fibroblasts, myofibroblasts, and endothelial cells. The composition and transcriptional profiles of urine immune cells were more similar to TME immune cells than to peripheral blood immune cells. Urine immune cells expressed gene signatures associated with hypoxia, anergy, pro-inflammation, and glucose deprivation that were more similar to tumor immune cells than those in the peripheral blood.ConclusionsOur work represents the first scRNAseq and CITEseq profiling of cancer patient urine. Our study suggests several viable immune cells shed in bladder cancer patient urine that look more transcriptionally and phenotypically similar to the TME than peripheral blood cells. This important finding has several implications for future research and clinical applications as urine can be sampled non-invasively in scenarios when tumor resection may not be feasible.ReferencesWong YNS, Joshi K, Khetrapal P, et al. Urine-derived lymphocytes as a non-invasive measure of the bladder tumor immune microenvironment. Journal of Experimental Medicine. 2018; 215:2748–59.Zheng GXY, Terry JM, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells. Nature Communications 2017; 8.Stoeckius M, Hafemeister C, Stephenson W, et al. Simultaneous epitope and transcriptome measurement in single cells. Nature Methods 2017;14, 865–68.Butler A, Hoffman P, Smibert, P, et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nature Biotechnology 2018; 36: 411–20.Xie Z, Bailey A, Kuleshov MV, et al. Gene set knowledge discovery with Enrichr. Current Protocols 2021.Trapnell C, Cacchiarelli D, Grimsby J, et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nature Biotechnology 2014; 32: 381–6.Ethics ApprovalThe study was approved by Mount Sinai Institution’s Ethics Board, approval number 10–1180. Participants gave informed consent before taking part in the study.

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