Biology subjects

Schedin, P. J.

Publications and source records attributed to Schedin, P. J..

3 recordsLinked to original sources

bioRxiv2021

Pregnancy and weaning regulate human maternal liver size and function

BACKGROUNDDuring pregnancy, the rodent liver undergoes hepatocyte proliferation and increases in size, followed by weaning-induced involution via hepatocyte cell death and stromal remodeling, creating a pro-metastatic niche. These data suggest a mechanism for increased liver metastasis in postpartum breast cancer patients. OBJECTIVESInvestigate if the human liver changes in size and function during pregnancy and weaning. METHODSAbdominal imaging was obtained in healthy women at early and late pregnancy, and post-wean. During pregnancy time points, endogenous glucose production was measured and fasting blood taken to measure bile acids. RESULTSIndependent of weight gain, most womens livers increased in size with pregnancy, returning to baseline post-wean. Putative roles for bile acids in liver growth were observed in pregnant women and rodents. CONCLUSIONSThe human liver is regulated by reproductive state with growth during pregnancy and volume loss post-wean. These findings may have broad implications for sex-specific liver diseases and cancer.

physiology↗

bioRxiv2020

Phenotype-guided subpopulation identification from single-cell sequencing data

Single-cell sequencing yields novel discoveries by distinguishing cell types, states and lineages within the context of heterogeneous tissues. However, interpreting complex single-cell data from highly heterogeneous cell populations remains challenging. Currently, most existing single-cell data analyses focus on cell type clusters defined by unsupervised clustering methods, which cannot directly link cell clusters with specific biological and clinical phenotypes. Here we present Scissor, a novel approach that utilizes disease phenotypes to identify cell subpopulations from single-cell data that most highly correlate with a given phenotype. This "phenotype-to-cell within a single step" strategy enables the utilization of a large amount of clinical information that has been collected for bulk assays to identify the most highly phenotype-associated cell subpopulations. When applied to a lung cancer single-cell RNA-seq (scRNA-seq) dataset, Scissor identified a subset of cells exhibiting high hypoxia activities, which predicted worse survival outcomes in lung cancer patients. Furthermore, in a melanoma scRNA-seq dataset, Scissor discerned a T cell subpopulation with low PDCD1/CTLA4 and high TCF7 expressions, which is associated with a favorable immunotherapy response. Thus, Scissor provides a novel framework to identify the biologically and clinically relevant cell subpopulations from single-cell assays by leveraging the wealth of phenotypes and bulk-omics datasets.

bioinformatics↗

bioRxiv2020

S-nitrosylated and non-nitrosylated COX2 has differential expression and distinct subcellular localization in normal and breast cancer tissue

Immunohistochemical staining in breast cancer shows both gain and loss of COX2 expression with disease risk and progression. We investigated four common COX2 antibody clones and found high specificity for purified human COX2 for three clones; however, recognition of COX2 in cell lysates was clone dependent. Biochemical characterization revealed two distinct forms of COX2, with SP21 recognizing an S-nitrosylated form and CX229 and CX294 appearing to recognize the same non-nitrosylated COX2 antigen. We found S-nitrosylated and non-nitrosylated COX2 occupy different subcellular locations in normal and breast cancer tissue, implicating distinct synthetic/trafficking pathways and function. Dual stains of ~2000 breast cancer cases show early onset breast cancer has increased expression of both forms of COX2 compared to postmenopausal cases. Our results highlight the strengths of using multiple, highly characterized antibody clones for COX2 immunohistochemical studies and raise the prospect that S-nitrosylation of COX2 may play a role in breast cancer biology.

cancer biology↗