bioRxiv Science⌕ Search

Biology subjects

Hassan, S.

Publications and source records attributed to Hassan, S..

38 records · Page 3Linked to original sources

Intermittent hormonal therapy shows similar outcome than SOC in ER+ breast cancer preclinical model.

Clinical breast cancers in which at least 10% of cells express the estrogen receptor are labeled as \"ER positive.\" First line therapy for these patients is typically continuous administration of anti-estrogen drugs at maximum tolerated dose (MTD) until progression. In the vast majority of patients, resistance to hormone therapy evolves in the breast cancer cells within 2 years leading to treatment failure and tumor progression. In prior studies, we have demonstrated continuous application of MTD chemotherapy results in evolutionary dynamics (termed \"competitive release\") that accelerates proliferation of treatment-resistance populations. In contrast, evolution-informed application of treatment reduces drug administration to maintain substantial populations of therapy-sensitive cells to reduce proliferation of resistant phenotypes. Prior pre-clinical and clinical studies have shown this strategy can delay or prevent proliferation of resistant cells and prolong time to progression (TTP). We hypothesize that similar dynamics may be observed in hormonal therapy of ER+ breast cancers. Here we address two important dynamics. First, we consider a clinical scenario in which symptoms are sufficiently severe or life-threatening to require rapid and substantial tumor reduction. Can this be achieved while retaining evolutionary dynamics to subsequently delay proliferation of resistance? A second, related question is defining the cost of resistance to anti-estrogen therapy. Here, we investigated the evolutionary dynamics of resistance to anti-estrogen therapy using ER+ MCF-7 orthotropic xenografts treated with both continuous Tamoxifen as well as cycles in which estrogen stimulation is combined with estrogen suppression. As expected, continuous administration of anti-estrogen drugs successfully suppressed tumor growth. However we found that brief interruptions in drug administration permitted equal tumor control while administering up to 50% less drug and maintaining cell phenotypes that retained high levels of ER expression and lower levels of MDR1 expression. In follow-on experiments combining hormonal and chemo-therapies; we obtained similar tumor control to hormonal therapy alone but with more necrosis and significantly lower ER expression in the surviving population.

cancer biology↗

Genetics of human plasma lipidome: Understanding lipid metabolism and its link to diseases beyond traditional lipids

AimGenetic investigation of human plasma lipidome to get insights into lipid-related disorders beyond traditional lipid measures.\n\nMethods and ResultsWe performed a genome-wide association study (GWAS) of 141 lipid species (n=2,181 individuals), followed by phenome-wide scans (PheWAS) with 44 clinical endpoints related to cardiometabolic, psychiatric and gastrointestinal disorders (n=456,941 individuals). SNP-based heritability for lipid species ranged from 0.10-0.54. Lipids with long-chain polyunsaturated fatty acids showed higher heritability and genetic sharing, suggesting considerable genetic regulation at acyl chains levels. We identified 35 genomic regions associated with at least one lipid species (P<5x10-8), revealing 37 new SNP-lipid species pair associations e.g. new association between ABCG5/8 and CE(20:2;0). PheWAS of lipid-species-associated loci suggested new associations of BLK with obesity, FADS2 with thrombophlebitis, and BLK and SPTLC3 with gallbladder disease (false discovery rate <0.05). The association patterns of lipid-species-associated loci supplied clues to their probable roles in lipid metabolism e.g. suggestive role of SYNGR1, MIR100HG, and PTPRN2 in desaturation and/or elongation of fatty acids. At known lipid loci (FADS2, APOA5 and LPL), genetic associations provided detailed insights to their roles in lipid biology and diseases. We also show that traditional lipid measures may fail to capture lipids such as lysophospatidylcholines (LPCs) and phosphatidylcholines (PCs) that are potential disease risk factors, but are not included in routine screens. The full genome-wide association statistics are available on the web-based database (http://35.205.141.92).\n\nConclusionOur study reveals genetic regulation of plasma lipidome and highlights the potential of lipidomic profiling in disease gene mapping.

genetics↗