Humanizing the endocrine milieu of female mice for women’s health-related studies

Humanizing the endocrine milieu of female mice for women’s health-related studies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Humanizing the endocrine milieu of female mice for women’s health-related studies Céline Constantin, Daria Matvienko, csaba laszlo, Valentina Scabia, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4808879/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract To improve on the quality of preclinical studies and their clinical translatability, patient-derived xenograft (PDX) models are increasingly used because they reflect inter- and intra-patient heterogeneity as well as human-specific tumor cell characteristics. However, the endocrine milieu of human patients, which affects grafted tumor cells may differ from mice. This is a growing concern as evidence of sex-specific biology in cancer has accumulated and an increase in the incidence of endocrine-related cancers has been observed highlighting the need to correctly reflect the hormonal milieu in PDX models. Here, we address the need to better model different female endocrine milieus in xenograft studies. Using an improved Liquid Chromatography-Mass Spectrometry (LC-MS) protocol for concomitant analysis of four different ovarian steroids in low volume plasma samples, we show that female mice of NOD.Cg-Prkdc scid Il2rg tm1Wjl /SzJ (NSG) strain frequently used for xenografts have 17-β-estradiol (E2) and testosterone (T) levels comparable to widely used C57Bl6 strain but higher progesterone (P4) levels. While NSG E2 levels are comparable, T levels are lower and P4 levels higher compared to those observed in menopausal women. Following ovariectomy, T levels increase to those found in postmenopausal women. Subcutaneous implantation of E2 and combined E2 and P4 silicon pellets mimic ovarian hormone levels of premenopausal women in follicular and luteal phase of the menstrual cycle. Thus, straightforward procedures can effectively humanize the endocrine environment of experimental animals and improve physiologic relevance in women’s health-related research. Health sciences/Diseases/Cancer Biological sciences/Physiology Health sciences/Diseases Biological sciences/Cancer Biological sciences/Cancer/Gynaecological cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Research into women’s health depends on experimental models ranging from in vitro cell lines to complex genetically engineered mouse and xenograft models 1 – 4 . Notably, in oncology, the success rate of clinical translation has been low because the models used in preclinical research fail to adequately mimic the human disease 5 – 7 . To increase the translatability, PDXs are increasingly used because they capture intra- and inter-tumor heterogeneity better than the widely used cell lines or genetically engineered mouse models (GEMMs) 2 , 4 , 8 , 9 . Improved engraftment by injection into the milk ducts has recently been shown to be enabling for studying both normal breast epithelial cells as well as breast cancer cells 10 – 12 when in particular, estrogen receptor positive breast cancer was previously difficult to study 13 – 15 . Host mice are severely immunocompromised 16 allowing them to tolerate grafts of human origin but also presenting a major limitation of xenograft models. In recent years, numerous efforts to humanize the immune system of recipient mice have further improved the predictive value of xenograft studies 17 – 22 . Yet, another important factor, the hormonal milieu of the models used, is often overlooked. Ovarian hormones control numerous physiological functions and impinge on tumor development 23 – 25 . While this is well established for breast cancer and tumors of other reproductive organs, evidence has accumulated that this applies also to malignancies arising from non-reproductive organs 26 , 27 . For instance, bladder cancer has a higher incidence in men than in women and the role of androgen receptor signaling in its progression is actively explored 28 – 30 . Similarly, higher incidence rates in hepatocellular carcinoma in males depend on sex hormones, with estrogen receptor signaling suppressing, and androgen receptor signaling promoting hepatocarcinogenesis 31 , 32 . Likewise, E2 plays a role in thyroid cancer, which primarily affects women 33 – 35 . Furthermore, epidemiologic studies have revealed that early menarche along with late menopause and hormone replacement therapy increases the risk of various hormone-dependent tumors 36 – 40 . While most hormones are shared across mammals, there are differences among species with regards to reproductive biology. Female mice have 4-day reproductive cycles known as estrous cycles consisting of three phases proestrus, estrus and diestrus while the human menstrual cycles last from 25 to 30 days and is divided into follicular and luteal phase 41 . Humans are one of few mammalian species who experience menopause, a reproductive stage that is not observed in rodents. Additionally, there are differences in mouse and human sex steroid metabolism. In humans, the plasma protein, sex hormone binding globulin (SHBG), binds with high affinity to sex steroids and controls their availability by regulating their tissue distribution and metabolism 42 . Rodents do not express this protein and this affects how the sex hormones circulate and function. Similarly, in humans, but not rodents, the adrenal gland secretes substantial amounts of the sex steroid precursors, androstenedione and dehydroepiandrosterone (DHEA) 43 . Together, these differences result in species-specific plasma concentrations of sex steroids 44 . To gain physiologically relevant insights into female health, sex steroid profiles need to be adequately reflected in the experimental design 45 – 47 . Previously, it has been difficult to measure hormone levels in mice due to the high sample volume requirement. The low steroid hormone concentrations and the inability to measure more than one hormone at a time with immunoassays were additional challenges 48 , 49 . MS is the optimal technique for analyzing sex steroids in plasma samples because multiple substances can be measured simultaneously within each sample with high precision and accuracy 44 , 50 , 51 . With the present study, we address the need for more physiologic models in the study of hormone-sensitive diseases. We present a LC-MS assay to measure concomitantly E2, estrone (E1), P4 and T in small volumes of plasma as can be routinely obtained by tail vein sampling and measure these in female NSG mice, the most widely used immunocompromised mouse strain in PDX modelling. Finally, we propose simple approaches to mimic critical physiological stages in women’s lives to enable more physiologically relevant modelling of women’s health issues. Results LC-MS method to measure 17β-estradiol (E2), estrone (E1), progesterone (P4), and testosterone (T) To enable simultaneous measurements of four ovarian hormones in blood samples from small animals, we adapted a previously used LC-MS method for 100 µl of plasma 51 , 52 . To enhance the detection for the particularly low estrogens, we introduced a derivatization step with dansyl chloride to improve the ionization efficiency through reaction with phenolic hydroxyl group of estrogens 53 – 55 (Fig. 1 a) Sensitivity evaluation of the assay revealed that the lower limits of quantitation (LLOQ) for E2, E1, P4, and T were 4.1, 10.24, 160 and 50 pg/ml, respectively (Fig. 1 b). Thus, 100 µl of plasma as obtained through routine tail bleeding are sufficient to measure four major ovarian hormones facilitating routine profiling in small animal experiments. a Illustration of the optimized LC-MS method for simultaneous measurements of four ovarian hormones in plasma samples from humans and mice. Plasma samples are prepared using solid-phase extraction (SPE) for LC-MS analysis of progesterone (P4) and testosterone (T). The remaining samples are derivatized and analyzed by LC-MS for 17β-estradiol (E2) and estrone (E1). Generated with Biorender.com with modifications. b LLOQ for E2, E1, P4 and testosterone T, % Relative standard deviation (RSD), % bias at LLOQ and calibration ranges. Plasma levels of ovarian steroids in NOD.Cg- Prkdc scid Il2rg tm1Wjl /SzJ ( NSG ) mice NSG mice are widely used in biomedical research for xenograft experiments because of the broad extent of immune suppression. Yet there are no reference values of hormone plasma levels. We determined E2, E1, P4, and T plasma concentrations in adult virgin NSG females and compared them to those of C57/Bl6 mice we reported previously 52 as well as to values from other studies 44 , 56 – 60 . E2 plasma levels in NSG females with mean values of 11,21 pg/ml were comparable to C57/Bl6 females with mean value 12,41 pg/ml (Fig. 2 a, d). P4 levels tended to be higher and more variable in NSG mice with mean value of 4,90 ng/ml compared to C57/Bl6 mice in our dataset with mean 2,11 ng/ml. However, these levels were within the same range as the published reference values for C57/Bl6 mice 44 , 56 – 60 (Fig. 2 b, d). T levels were similar in both strains with mean 0,10 ng/ml in NSG and 0,12 ng/ml in C57/Bl6 mice (Fig. 2 c). Most E1 measurements were below the LLOQ in both strains (data not shown). Thus, NSG and C57/Bl6 females have comparable sex steroid profiles within the range from values measured by others in C57/Bl6 model 44 , 56 – 60 (Fig. 2 ). Plasma ovarian steroid levels in murine versus human samples To compare the ovarian hormone levels detected in NSG females to those observed in women, we measured the 4 ovarian steroids in plasma from 156 pre- and 23 post-menopausal women and recurred to published reference values 61 – 65 . Murine E2 levels (mean 11,21 pg/ml) were more than 10-fold lower than those observed in premenopausal women who had mean value 161 pg/ml but comparable to the levels detected in postmenopausal women with mean 12.80 pg/ml (Fig. 3 a, e). E1 was readily detected in the plasma of both pre- and post-menopausal women with mean values of 67,85 and 29,32 pg/ml respectively, while below LLOQ in mice (Fig. 3 b, e). Plasma P4 levels were higher in mice (mean 4,90 ng/ml) than in pre- and post-menopausal women with mean values 1,70 and 0,07 ng/ml respectively (Fig. 3 c, e). The mean P4 value observed in NSG mice was comparable to luteal phase levels in women, which range from approximately 5 to 20 ng/ml (Fig. 3 c, e). T was lower in mice (mean 0,10 ng/ml) than in pre- and postmenopausal women with means of 0,30 and 0,26 ng/ml (Fig. 3 d, e). The E2 and P4 concentrations measured in women from our cohort were in the same range as the reference values 61 – 65 . However, the range of E1 levels in postmenopausal women we measured was twice as wide as ranges reported by others 44 , 66 – 68 . Taken together, murine E2 levels are comparable to those found in postmenopausal women while murine P4 levels are closer to luteal phase values in humans. Hormone treatments of mice mimic pre- and post-menopausal steroid profiles To mimic the endocrine milieu of pre- and postmenopausal women, we used two strategies − subcutaneous implantation of slow-release hormone pellets with E2, P4, or E2 alongside with P4 and hormone ablation by ovariectomy 12 . Sixty days after the implantation of 0.3 mg E2-containing silicone pellets, E2 levels increased 46-fold with mean 529,30 pg/ml in comparison to intact mice (mean 11,21 pg/ml) (Fig. 4 a, e). Consistent with a fraction of the administered E2 being converted to E1, E1 levels increased 17-fold with mean 25,82 pg/ml (Fig. 4 b, e). P4 levels were decreased to mean 0,85 pg/ml consistent with exogenous E2 suppressing the estrous cycle-related peaks in P4 levels 69 . The 20 mg slow-release P4 pellets increased plasma P4 levels 2-fold with mean 15,75 ng/ml compared to intact mice (mean 4,90 ng/ml) and had no effect on other hormone levels (Fig. 4 c, e). In premenopausal women, E2 levels peak during the follicular phase, while the luteal phase is characterized by a lower peak in E2 levels and high P4 levels. To mimic human luteal phase hormone levels and overcome the inhibitory effect of E2 treatments on P4 secretion, we implanted mice with 0.3 mg E2 pellets alongside 20 mg P4 pellets and compared the resulting hormone levels to published data 61 , 63 , 65 . E2 levels were higher in treated mice with mean 426,30 pg/ml than in premenopausal women (mean 161 pg/ml) (Fig. 4 f) and had higher P4 with mean 19,39 ng/ml than premenopausal women (mean 1,70 ng/ml) (Fig. 4 h). It is important to note that we did not separate the plasma values from women of our dataset by phase of the menstrual cycle, which results in more heterogeneous hormone ranges. E1 and T remained lower in mice than in women (Fig. 4 g, i). Thus, E2- and E2 + P4-treated mice have E2 and P4 plasma levels comparable to those in women during follicular and luteal phase 61 , 63 , 65 , respectively. Intact mice have similar E2 (mean 11,21 pg/ml), but higher P4 levels (mean 4,90 ng/ml) than postmenopausal women (means E2: 12,80 pg/ml and P4: 0,07 ng/ml) (Fig. 3 a, c and Fig. 4 j, l). Therefore, we compared the steroid profile of ovariectomized mice with decreased E2 and E1 levels to postmenopausal women. Sixty days following ovariectomy, both E2 and E1 levels dropped below quantitation limit (Fig. 4 j, k). Plasma P4 levels in ovariectomized mice remained higher with mean value 1,74 ng/ml compared to postmenopausal patients, though these levels were closer to human settings than those observed in intact mice (Fig. 4 l). Ovariectomy elevated mouse plasma T concentrations to mean 0,33 ng/ml, thereby better matching levels of postmenopausal women (mean 0,27 ng/ml) (Fig. 4 m). Thus, postmenopausal E2 levels are similar to levels in intact NSG females, but T and P4 levels are better mimicked in ovariectomized mice. Discussion Mouse models are essential in preclinical and translational research, and improving their predictive power by better mimicking human physiology is a continuous effort. Here, we sought to improve the endocrine context of the murine models, with regard to ovarian steroid hormones, central to women’s health. We focused on the widely used NSG strain and propose a simple practical approach to mimic distinct endocrine milieus pertinent to women’s health. First, we optimized a LC-MS method 51,52 for the simultaneous measurement of E2, E1, P4, and T in 100 µl. This optimization is crucial for working with low volume mice blood samples and allows for repeat measurements via tail vein sampling vital for accurately monitoring hormone fluctuations over time. Our LC-MS method, while effective, has limitations; like higher LLOQs than other methods such as gas chromatography (GC)-MS 44 . This applies in particular to E1, where the values we measured remained below the quantitation limit in untreated mice and higher errors for low values may also explain the high variation we observed in postmenopausal women. Additionally, tandem LC–MS/MS with triple quadrupole type instruments provide a wide range from LLOQs with the minimal of 0.14 pg/ml for E1 and E2 70 providing potential for further improvement of the present method. Our findings demonstrate that intact NSG mice have plasma E2 concentrations similar to postmenopausal women suggest that at least with regard to E2 levels they provide an approximative endocrine milieu of postmenopausal women, whereas T and P4 levels were better reflected by ovariectomized mice. Interestingly, while T levels increase upon ovariectomy in NSG mice, they decrease in oophorectomized women 71 . This may be an NSG -specific phenomenon as reduced but still measurable T levels were observed in ovariectomized C57/BL6 mice and suggest that the adrenal glands could contribute to circulating T in female mice 44 . Further studies are needed to determine if the adrenal glands can compensate T production in the case of gonadectomy. Moreover, the day of the estrous cycle when the blood sample is collected may influence T hormone levels 72 . As NSG mice lack B and T cells, the estrous cycle stage could not be assessed by vaginal smear. To better match the hormone profile of women with murine models, we propose simple strategies. The approaches are low cost, the fabrication of slow-release hormone pellets is flexible and readily adjustable to different time windows requirements, moreover it can readily be extended to other steroids. The estrone levels were consistently lower in mice than humans, regardless of treatment. None of the strategies we tested allowed to match E1 levels in postmenopausal women without simultaneously increasing E2. To mimic the specific sex steroid levels in murine model this issue could be addressed by using E1 pellets can be added, as suggested by Qureshi et al. 73 . Additionally, since estrogens can inhibit the hypothalamic secretion of gonadotropin-releasing hormone 74,75 E1 pellets may also help suppress the cycle-related variation in circulating P4. As such, ovariectomized mice with estrone pellets might most accurately reflect the menopausal endocrine milieu. E2 and E2 in combination with P4 slow-released pellets allowed us to mimic the follicular and luteal phase levels of the two major ovarian hormones. Our results showed that E2 levels in treated mice were higher compared to premenopausal women which is likely due to the use of a single concentration of E2 pellet of 0.3 mg in our study. Adjusting the pellet dosage by titration could help to better approximate the E2 levels observed in premenopausal women, improving the translational relevance of our model. An important limitation of hormone-released pellet implantation is that hormone release decreases over time and fails to mimic natural cyclicity. Slow-release silicone-based implants are easy to prepare and are flexible, but they administer chronic instead of fluctuating doses of hormones. Drug delivery technology devices, such as ALZET® or iPRECIO®, are tools for more accurate and continuous delivery and more drug-release devices with varying release rates are currently under development 76–79 . Depending on the specific research question, scientists may choose to use hormone treatments to more accurately mimic patients' physiology. With the present approach flexible tools are at hand. Methods Animal experiments Animal experiments with NSG mice were performed in accordance with protocol (VD 1865.3, 1865.4, and 1865.5) approved by the Service de la Consommation et des Affaires Vétérinaires of Canton de Vaud. NOD.Cg-Prkdc scid Il2rg tm1Wjl /SzJ mice ( NSG ) were purchased from Jackson Laboratories and 10-20-week-old females were subcutaneously implanted with slow-release-hormone pellets and sacrificed 60 days later, blood was collected by heart puncture. Patient samples Human plasma samples were obtained from patients undergoing breast reduction surgery at the Centre Hôspitalier Universitaire Vaudois and Hirslanden Hospital. The study was approved by the Commission cantonale d’éthique de la recherche sur l’être humain ethics committee (VD183/10) and informed consent was obtained from all the participants. Patients on hormonal contraception or hormone replacement therapy and blood samples, in which a progestin was detectable by LC-MS (gestodene, levonorgestrel, etonogestrel, chlormadinone acetate, cyproteroneacetate, drospirenone, desacetyl norgestimate, medroxyprogesterone acetate, norethindrone, dienogest or nomegestrol acetate) were excluded 51 . Pellet preparation Pellets were prepared by mixing part A (MP3745/E81949) and B (MP3744/E8195) of the low viscosity silicon elastomer (MED-4011) with hormone powder as indicated below. The mix was incubated overnight at 37°C and cut as described 12 . Hormone Catalog number Hormone dose/pellet (mg) Silicon part A (mg) Silicon part B (µl) Hormone powder (mg) Pellet weight (mg) 17β-estradiol (E2) E2758 0,3 4700 500 250 7,8 Progesterone (P4) P0130-25G 20 3525 375 3525 49,5 Hormone measurements E2, E1, P4, and T plasma levels were measured by high resolution LC-MS (Q-Exactive Orbitrap, ThermoFisher Scientific) using targeted-SIM (tSIM) acquisition 51,52 with the following modifications. For sample preparation, 100 µl of plasma were mixed with 100 µl of internal standards in 5% (w/v) phosphoric acid, applied to a solid phase extraction plate (Oasis MCX µElution 96-well plate, Waters) and washed with 5% (w/v) ammonium hydroxide (NH 4 OH) and 20% (v/v) methanol and eluted with isopropyl alcohol. Eluates were evaporated under N 2 on a TurboVap 96 (Biotage, Uppsala, Sweden) and reconstituted in 100 µl 40% acetonitrile (ACN), corresponding to initial LC mobile phase conditions. To detect P4 and T, 20 µl of sample were injected onto a Zorbax Eclipse Plus C18 (2.1 × 50 mm 1.8 µ m) column (AgilentTechnologies, Santa Clara, California, United States) at a flow rate of 0,2 ml/min using a gradient of purified H 2 O and ACN, both containing 0,1% (v/v) formic acid. Solvent gradient was started at 40% ACN, held for 2 min, linearly increased to 70% ACN over 6 min, further increased to 100% ACN over 0,5 min, held at 100% ACN for 1 min, decreased to 40% ACN over 0,5 min and finally held at 40% ACN for re-equilibration until end of 12 min run. For the combined analysis of E2 and E1 with P4 and T, the same sample extracts were again evaporated under nitrogen and reconstituted in 50 µL sodium bicarbonate buffer (NaHCO 3 , 100 mM, pH adjusted to 10 with NaOH) and 50 µl dansyl chloride (2.0 mg/ml in acetone) were added per sample for derivatization. The plate was left at 65°C for 15 min in an incubator, cooled to 4°C and transferred to the LC autosampler. For E2 and E1 detection, 25 µl of sample were injected onto the same LC column at a flow rate of 0,2 ml/min using a gradient of purified H 2 O and ACN, both containing 0,1% (v/v) formic acid. The solvent gradient started at 70% ACN was held for 2 min, linearly increased to 85% ACN over 6 min, further increased to 100% ACN over 2 min, held at 100% ACN for 1 min, decreased to 70% ACN over 1 min and finally held at 70% ACN for re-equilibration until the end of the 15 min run. The mass spectrometer was a QExactive Orbitrap working in positive mode using previously reported parameters (Laszlo et al., 2019) for P4 and T and the following modifications for E2 and E1: resolution 70k, automatic gain control (AGC) target 1e6, MAX ion injection time 100 ms, isolation window 0.5 m/z, scan range 500-750 m/z. The tSIM method acquires the user-defined targeted masses in retention time dependent time segments. Data were processed with Thermo Xcalibur 4.0.27.10. The targeted SIM method contained an inclusion list with 10 ppm precision (Supplemental table 1). Mass extraction for analysis was carried out at 5 ppm. LLOQs were determined on triplicate samples serially diluted 1:2,5 over 8 dilutions. Statistical analysis Statistical analysis was performed using GraphPad Prism (version 10) (San Diego, California, USA, www.graphpad.com). Statistical tests are indicated in the figure legends. Significance was set as p < 0.05 and data are presented as mean ± standard deviation (SD). Declarations Competing interests The Authors declare no Competing Financial or Non-Financial Interests. Author Contribution Conceptualization: CC, SB and CB; methodology: CL, CC, SB; analysis and data visualization: CC, CL and DM; resources: CB, SB, P-AB; data generation: CC, CL, VS, LB; writing/original draft preparation: CC, DM, and CB; writing, review, and editing: CC, DM, SB, VS and CB; supervision: SB, CB. All authors have read and agreed to the published version of the manuscript. Acknowledgments This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme Marie Skłodowska-Curie (grant number 859860). CB has support from Breast Cancer Now as part of program funding to the Breast Cancer Now Toby Robins Research Centre. Data Availability Data is provided within the manuscript. References Sausville, E. A. & Burger, A. M. Contributions of human tumor xenografts to anticancer drug development. Cancer Research vol. 66 Preprint at https://doi.org/10.1158/0008-5472.CAN-05-3627 (2006). Day, C. P., Merlino, G. & Van Dyke, T. Preclinical Mouse Cancer Models: A Maze of Opportunities and Challenges. Cell vol. 163 Preprint at https://doi.org/10.1016/j.cell.2015.08.068 (2015). Holen, I., Speirs, V., Morrissey, B. & Blyth, K. In vivo models in breast cancer research: Progress, challenges and future directions. DMM Disease Models and Mechanisms vol. 10 Preprint at https://doi.org/10.1242/dmm.028274 (2017). Hidalgo, M. et al. Patient-derived Xenograft models: An emerging platform for translational cancer research. Cancer Discov 4 , (2014). Hait, W. N. Anticancer drug development: The grand challenges. Nature Reviews Drug Discovery vol. 9 Preprint at https://doi.org/10.1038/nrd3144 (2010). Johnson, J. I. et al. Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. Br J Cancer 84 , (2001). Prinz, F., Schlange, T. & Asadullah, K. Believe it or not: How much can we rely on published data on potential drug targets? Nature Reviews Drug Discovery vol. 10 Preprint at https://doi.org/10.1038/nrd3439-c1 (2011). Whittle, J. R., Lewis, M. T., Lindeman, G. J. & Visvader, J. E. Patient-derived xenograft models of breast cancer and their predictive power. Breast Cancer Research vol. 17 Preprint at https://doi.org/10.1186/s13058-015-0523-1 (2015). Yada, E., Wada, S., Yoshida, S. & Sasada, T. Use of patient-derived xenograft mouse models in cancer research and treatment. Future Science OA vol. 4 Preprint at https://doi.org/10.4155/fsoa-2017-0136 (2018). Shamseddin, M. et al. Contraceptive progestins with androgenic properties stimulate breast epithelial cell proliferation. EMBO Mol Med 13 , (2021). Sflomos, G. et al. A Preclinical Model for ERα-Positive Breast Cancer Points to the Epithelial Microenvironment as Determinant of Luminal Phenotype and Hormone Response. Cancer Cell 29 , 407–422 (2016). Duss, S. et al. An oestrogen-dependent model of breast cancer created by transformation of normal human mammary epithelial cells. Breast Cancer Research 9 , (2007). Scabia, V. et al. Estrogen receptor positive breast cancers have patient specific hormone sensitivities and rely on progesterone receptor. Nat Commun 13 , (2022). Fiche, M. et al. Intraductal patient-derived xenografts of estrogen receptor α-positive breast cancer recapitulate the histopathological spectrum and metastatic potential of human lesions. J Pathol 247 , 287–292 (2019). Sflomos, G. et al. Intraductal xenografts show lobular carcinoma cells rely on their own extracellular matrix and LOXL1. EMBO Mol Med 13 , (2021). Abdolahi, S. et al. Patient-derived xenograft (PDX) models, applications and challenges in cancer research. J Transl Med 20 , 206 (2022). Carpenter, R. S. et al. Human immune cells infiltrate the spinal cord and impair recovery after spinal cord injury in humanized mice. Sci Rep 9 , (2019). Zhao, Y. et al. Development of a new patient-derived xenograft humanised mouse model to study human-specific tumour microenvironment and immunotherapy. Gut vol. 67 Preprint at https://doi.org/10.1136/gutjnl-2017-315201 (2018). Scherer, S. D. et al. An immune-humanized patient-derived xenograft model of estrogen-independent, hormone receptor positive metastatic breast cancer. Breast Cancer Research 23 , (2021). Dobrolecki, L. E. et al. Patient-derived xenograft (PDX) models in basic and translational breast cancer research. Cancer and Metastasis Reviews 35 , 547–573 (2016). Kostlan, R. Joseph. et al. Clinically relevant humanized mouse models of metastatic prostate cancer facilitate therapeutic evaluation. Molecular Cancer Research (2024) doi:10.1158/1541-7786.mcr-23-0904. Yang, Y. et al. Humanized mouse models: A valuable platform for preclinical evaluation of human cancer. Biotechnology and Bioengineering vol. 121 Preprint at https://doi.org/10.1002/bit.28618 (2024). Henderson, B. E. & Feigelson, H. S. Hormonal carcinogenesis. Carcinogenesis vol. 21 Preprint at https://doi.org/10.1093/carcin/21.3.427 (2000). Brisken, C. Progesterone signalling in breast cancer: A neglected hormone coming into the limelight. Nature Reviews Cancer vol. 13 Preprint at https://doi.org/10.1038/nrc3518 (2013). Singh, R. R. & Kumar, R. Steroid hormone receptor signaling in tumorigenesis. Journal of Cellular Biochemistry vol. 96 Preprint at https://doi.org/10.1002/jcb.20566 (2005). Costa, A. R. et al. The Sex Bias of Cancer. Trends in Endocrinology and Metabolism vol. 31 Preprint at https://doi.org/10.1016/j.tem.2020.07.002 (2020). Manolagas, S. C. & Kousteni, S. Perspective: Nonreproductive sites of action of reproductive hormones. Endocrinology vol. 142 Preprint at https://doi.org/10.1210/endo.142.6.8221 (2001). Gil, D. et al. Dihydrotestosterone increases the risk of bladder cancer in men. Hum Cell 32 , (2019). Godoy, G., Gakis, G., Smith, C. L. & Fahmy, O. Effects of androgen and estrogen receptor signaling pathways on bladder cancer initiation and progression. Bladder Cancer vol. 2 Preprint at https://doi.org/10.3233/BLC-160052 (2016). Chen, J. et al. The androgen receptor in bladder cancer. Nature Reviews Urology vol. 20 Preprint at https://doi.org/10.1038/s41585-023-00761-y (2023). Li, Z., Tuteja, G., Schug, J. & Kaestner, K. H. Foxa1 and Foxa2 are essential for sexual dimorphism in liver cancer. Cell 148 , (2012). Zhang, L. et al. Sex steroid axes in determining male predominance in hepatocellular carcinoma. Cancer Letters vol. 555 Preprint at https://doi.org/10.1016/j.canlet.2022.216037 (2023). Liu, J., Xu, T., Ma, L. & Chang, W. Signal Pathway of Estrogen and Estrogen Receptor in the Development of Thyroid Cancer. Frontiers in Oncology vol. 11 Preprint at https://doi.org/10.3389/fonc.2021.593479 (2021). Derwahl, M. & Nicula, D. Estrogen and its role in thyroid cancer. Endocr Relat Cancer 21 , (2014). O’Grady, T. J. et al. Association of hormonal and reproductive factors with differentiated thyroid cancer risk in women: a pooled prospective cohort analysis. Int J Epidemiol 53 , (2024). Kelsey, J. L. & Horn-ross, P. L. Breast cancer: Magnitude of the problem and descriptive epidemiology. Epidemiol Rev 15 , (1993). Chang-Claude, J. et al. Age at menarche and menopause and breast cancer risk in the International BRCA1/2 Carrier Cohort Study. Cancer Epidemiology Biomarkers and Prevention 16 , (2007). Colditz, G. A., Rosner, B. A., Chen, W. Y., Holmes, M. D. & Hankinson, S. E. Risk Factors for Breast Cancer According to Estrogen and Progesterone Receptor Status. JNCI: Journal of the National Cancer Institute 96 , 218–228 (2004). Travis, R. C. & Key, T. J. Oestrogen exposure and breast cancer risk. Breast Cancer Research vol. 5 Preprint at https://doi.org/10.1186/bcr628 (2003). Villa, P. et al. Hormone Replacement Therapy in Post-Menopause Hormone-Dependent Gynecological Cancer Patients: A Narrative Review. Journal of Clinical Medicine vol. 13 Preprint at https://doi.org/10.3390/jcm13051443 (2024). Bull, J. R. et al. Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles. NPJ Digit Med 2 , (2019). Jänne, M., Deol, H. K., Power, S. G. A., Yee, S. P. & Hammond, G. L. Human sex hormone-binding globulin gene expression in transgenic mice. Molecular Endocrinology 12 , (1998). van Weerden, W. M., Bierings, H. G., Van Steenbrugge, G. J., De Jong, F. H. & Schröder, F. H. Adrenal glands of mouse and rat do not synthesize androgens. Life Sci 50 , (1992). Nilsson, M. E. et al. Measurement of a comprehensive sex steroid profile in rodent serum by high-sensitive gas chromatography-tandem mass spectrometry. Endocrinology (United States) 156 , (2015). Beery, A. K. & Zucker, I. Sex bias in neuroscience and biomedical research. Neuroscience and Biobehavioral Reviews vol. 35 Preprint at https://doi.org/10.1016/j.neubiorev.2010.07.002 (2011). Zheng, D. et al. Sexual dimorphism in the incidence of human cancers. BMC Cancer 19 , (2019). Clocchiatti, A., Cora, E., Zhang, Y. & Dotto, G. P. Sexual dimorphism in cancer. Nature Reviews Cancer vol. 16 330–339 Preprint at https://doi.org/10.1038/nrc.2016.30 (2016). Rosner, W., Hankinson, S. E., Sluss, P. M., Vesper, H. W. & Wierman, M. E. Challenges to the measurement of estradiol: An endocrine society position statement. Journal of Clinical Endocrinology and Metabolism 98 , (2013). Folkerd, E. J., Lønning, P. E. & Dowsett, M. Interpreting plasma estrogen levels in breast cancer: Caution needed. Journal of Clinical Oncology 32 , (2014). Karashima, S. & Osaka, I. Rapidity and Precision of Steroid Hormone Measurement. Journal of Clinical Medicine vol. 11 Preprint at https://doi.org/10.3390/jcm11040956 (2022). Laszlo, C. F. et al. A high resolution LC–MS targeted method for the concomitant analysis of 11 contraceptive progestins and 4 steroids. J Pharm Biomed Anal 175 , (2019). Cagnet, S. et al. Oestrogen receptor α AF-1 and AF-2 domains have cell population-specific functions in the mammary epithelium. Nat Commun 9 , (2018). Ke, Y., Bertin, J., Gonthier, R., Simard, J. N. & Labrie, F. A sensitive, simple and robust LC-MS/MS method for the simultaneous quantification of seven androgen- and estrogen-related steroids in postmenopausal serum. Journal of Steroid Biochemistry and Molecular Biology 144 , (2014). Nelson, R. E., Grebe, S. K., O’Kane, D. J. & Singh, R. J. Liquid Chromatography - Tandem Mass Spectrometry Assay for Simultaneous Measurement of Estradiol and Estrone in Human Plasma. Clin Chem 50 , (2004). Vitku, J. et al. Derivatized versus non-derivatized LC-MS/MS techniques for the analysis of estrogens and estrogen-like endocrine disruptors in human plasma. Ecotoxicol Environ Saf 260 , (2023). Wood, G. A., Fata, J. E., Watson, K. L. M. & Khokha, R. Circulating hormones and estrous stage predict cellular and stromal remodeling in murine uterus. Reproduction 133 , (2007). Toran-Allerand, C. D., Tinnikov, A. A., Singh, R. J. & Nethrapalli, I. S. 17 alpha-estradiol: A brain-active estrogen? Endocrinology vol. 146 Preprint at (2005). Sims, N. A. et al. Deletion of estrogen receptors reveals a regulatory role for estrogen receptors-β in bone remodeling in females but not in males. Bone 30 , (2002). Lindberg, M. K. et al. Estrogen receptor specificity in the regulation of the skeleton in female mice. Journal of Endocrinology 171 , (2001). Caldwell, A. S. L. et al. Characterization of reproductive, metabolic, and endocrine features of polycystic ovary syndrome in female hyperandrogenic mouse models. Endocrinology 155 , (2014). Kratz, A., Ferraro, M., Sluss, P. M. & Lewandrowski, K. B. Normal Reference Laboratory Values. New England Journal of Medicine 351 , (2004). Verdonk, S. J. E. et al. Estradiol reference intervals in women during the menstrual cycle, postmenopausal women and men using an LC-MS/MS method. Clinica Chimica Acta 495 , (2019). Stricker, R. et al. Establishment of detailed reference values for luteinizing hormone, follicle stimulating hormone, estradiol, and progesterone during different phases of the menstrual cycle on the Abbott ARCHITECT® analyzer. Clin Chem Lab Med 44 , (2006). de Wit, A. E. et al. Plasma androgens and the presence and course of depression in a large cohort of women. Transl Psychiatry 11 , (2021). Kyriakopoulou, L. et al. A sensitive and rapid mass spectrometric method for the simultaneous measurement of eight steroid hormones and CALIPER pediatric reference intervals. Clin Biochem 46 , (2013). Wooding, K. M. et al. Measurement of estradiol, estrone, and testosterone in postmenopausal human serum by isotope dilution liquid chromatography tandem mass spectrometry without derivatization. Steroids 96 , (2015). Faqehi, A. M. M. et al. Derivatization of estrogens enhances specificity and sensitivity of analysis of human plasma and serum by liquid chromatography tandem mass spectrometry. Talanta 151 , (2016). Li, X. & Franke, A. A. Improved profiling of estrogen metabolites by orbitrap LC/MS. Steroids (2015) doi:10.1016/j.steroids.2014.12.005. Kalra, S. P. & Kalra, P. S. Temporal interrelationships among circulating levels of estradiol, progesterone and LH during the rat estrous cycle: effects of exogenous progesterone. Endocrinology 95 , (1974). Denver, N., Khan, S., Homer, N. Z. M., MacLean, M. R. & Andrew, R. Current strategies for quantification of estrogens in clinical research. Journal of Steroid Biochemistry and Molecular Biology vol. 192 Preprint at https://doi.org/10.1016/j.jsbmb.2019.04.022 (2019). Shifren, J. L. et al. Transdermal Testosterone Treatment in Women with Impaired Sexual Function after Oophorectomy. New England Journal of Medicine 343 , (2000). Flores, A. et al. The acute effects of bilateral ovariectomy or adrenalectomy on progesterone, testosterone and estradiol serum levels depend on the surgical approach and the day of the estrous cycle when they are performed. Reproductive Biology and Endocrinology 6 , (2008). Qureshi, R. et al. The Major Pre- and Postmenopausal Estrogens Play Opposing Roles in Obesity-Driven Mammary Inflammation and Breast Cancer Development. Cell Metab 31 , (2020). Shaw, N. D. et al. Estrogen negative feedback on gonadotropin secretion: Evidence for a direct pituitary effect in women. Journal of Clinical Endocrinology and Metabolism 95 , (2010). Glidewell-Kenney, C. et al. Nonclassical estrogen receptor α signaling mediates negative feedback in the female mouse reproductive axis. Proc Natl Acad Sci U S A 104 , (2007). Knedla, A. et al. The therapeutic use of osmotic minipumps in the severe combined immunodeficiency (SCID) mouse model for rheumatoid arthritis. Ann Rheum Dis 68 , (2009). Tan, T., Watts, S. W. & Davis, R. P. Drug delivery: Enabling technology for drug discovery and development. iPRECIO® Micro Infusion Pump: programmable, refillable, and implantable. Front Pharmacol JUL , (2011). Itzhaki, E. et al. Tumor-Targeted Poly(ArgGlyAsp) Nanocapsules for Personalized Cancer Therapy – In Vivo Study. Adv Ther (Weinh) 6 , (2023). Moskovits, N. et al. Palbociclib in combination with sunitinib exerts a synergistic anti-cancer effect in patient-derived xenograft models of various human cancers types. Cancer Lett 536 , (2022). Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Sep, 2024 Reviews received at journal 07 Sep, 2024 Reviewers agreed at journal 23 Aug, 2024 Reviews received at journal 23 Aug, 2024 Reviewers agreed at journal 09 Aug, 2024 Reviewers invited by journal 09 Aug, 2024 Editor assigned by journal 08 Aug, 2024 Submission checks completed at journal 05 Aug, 2024 First submitted to journal 26 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4808879","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":346389049,"identity":"84587f99-e503-4438-a7ed-c5090afd5f4e","order_by":0,"name":"Céline Constantin","email":"","orcid":"","institution":"École Polytechnique Fédérale de Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Céline","middleName":"","lastName":"Constantin","suffix":""},{"id":346389050,"identity":"bc14f252-e708-43bf-a619-9dff72c3160b","order_by":1,"name":"Daria Matvienko","email":"","orcid":"","institution":"École Polytechnique Fédérale de Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Daria","middleName":"","lastName":"Matvienko","suffix":""},{"id":346389054,"identity":"403a071d-b751-4f59-8a7e-d07475f4fd07","order_by":2,"name":"csaba laszlo","email":"","orcid":"","institution":"École Polytechnique Fédérale de Lausanne","correspondingAuthor":false,"prefix":"","firstName":"csaba","middleName":"","lastName":"laszlo","suffix":""},{"id":346389055,"identity":"4fc68217-a837-4dfe-8699-b34bd8e09453","order_by":3,"name":"Valentina Scabia","email":"","orcid":"","institution":"École Polytechnique Fédérale de Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Valentina","middleName":"","lastName":"Scabia","suffix":""},{"id":346389056,"identity":"45195fdb-6317-41e0-8740-c1f26806befb","order_by":4,"name":"Laura Battista","email":"","orcid":"","institution":"École Polytechnique Fédérale de Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Battista","suffix":""},{"id":346389057,"identity":"a51aa518-96b4-49d4-9e84-d45085a39e61","order_by":5,"name":"Pierre-Alain Binz","email":"","orcid":"","institution":"University Hospital of Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Pierre-Alain","middleName":"","lastName":"Binz","suffix":""},{"id":346389058,"identity":"a57ebc66-f666-48f3-9b0d-ff75fe5d54e9","order_by":6,"name":"Stephen Bruce","email":"","orcid":"","institution":"University Hospital of Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"","lastName":"Bruce","suffix":""},{"id":346389059,"identity":"e39c4f7a-79f5-4ec0-8caf-aa27f89c3630","order_by":7,"name":"Cathrin Brisken","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie3PsWrCQBzH8d8h6BLImkOwr3AiKE59lYQMTtKODhkOAnGRuqa0D2HfIPCHTIGuGTI0BDI3eym9CGodLrabyH25W/7ch7sDTKbrrA+IdjHJJDACWJkASYfonZOJmog/EOwVWuLJS8Rev6fV6rHAbEhhE6+KxXYYqvNBoSVO5g/Gmagxf/Iivsvq5fMrKZLWWiLg97kUBJGxiJURLXf5Q5IwSXpiV0cSNuU3Le5zH93EOd0i+ZskV026iZNX05ZY8w2LeJzSOC7UX9xUT+ytV3P5RaOZNaiaTUB39kvIPj4DPTlk/bpYbfciOH/r/46bTCbT7fcDAZVcxy83SjIAAAAASUVORK5CYII=","orcid":"","institution":"École Polytechnique Fédérale de Lausanne","correspondingAuthor":true,"prefix":"","firstName":"Cathrin","middleName":"","lastName":"Brisken","suffix":""}],"badges":[],"createdAt":"2024-07-26 14:49:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4808879/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4808879/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64248372,"identity":"80bc11b0-e2c5-4573-b4b6-a40cff8d5711","added_by":"auto","created_at":"2024-09-10 20:48:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":442034,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorkflow of LC-MS based sample analysis and lower limits of detection (LLOQ).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea \u003c/strong\u003eIllustration of the optimized LC-MS method for simultaneous measurements of four ovarian hormones in plasma samples from humans and mice. Plasma samples are prepared using solid-phase extraction (SPE) for LC-MS analysis of progesterone (P4) and testosterone (T). The remaining samples are derivatized and analyzed by LC-MS for 17β-estradiol (E2) and estrone (E1). Generated with Biorender.com with modifications. \u003cstrong\u003eb \u003c/strong\u003eLLOQ for E2, E1, P4 and testosterone T, % Relative standard deviation (RSD), % bias at LLOQ and calibration ranges.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4808879/v1/7b153daf303d272ea457a331.png"},{"id":64248376,"identity":"aedd1f0b-588c-41c9-95f7-1f74f276d677","added_by":"auto","created_at":"2024-09-10 20:48:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":254403,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOvarian hormone levels in\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e NSG \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e C57/\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eBl6 adult 10-20-week-old females.\u003c/strong\u003e \u003cstrong\u003ea \u003c/strong\u003eE2 (pink points), \u003cstrong\u003eb\u003c/strong\u003e P4 (violet points) and \u003cstrong\u003ec\u003c/strong\u003e T (blue points) plasma levels in \u003cem\u003eNSG \u003c/em\u003ecompared to levels of previously reported by us \u003cem\u003eC57/Bl6 \u003c/em\u003emice (grey squares) plasma levels measured by LC-MS . Each dot represents an individual mouse, and bars represent the median hormone levels with error bars indicating the range (means ± SD). Black and dark grey triangles on grey background indicate previously reported upper and lower ranges for corresponding hormones in \u003cem\u003eC57/Bl6\u003c/em\u003e mice reported by others . Grid line indicates LLOQ. NSG n=227, \u003cem\u003eC57/Bl6 \u003c/em\u003en=34. Unpaired Student’s t-test (two-tailed p value). \u003cstrong\u003ed\u003c/strong\u003e Table showing median plasma concentrations and 2.5-97.5th percentiles range for 10 to 20-week-old females of \u003cem\u003eNSG \u003c/em\u003eand\u003cem\u003e C57/Bl6\u003c/em\u003e background.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4808879/v1/46ee4385612c3baf6f6f59aa.png"},{"id":64248959,"identity":"cee42fbc-9b0b-4b67-b94b-6c648cbf2628","added_by":"auto","created_at":"2024-09-10 20:56:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":368467,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEndogenous ovarian steroid levels in plasma of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNSG\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e females and pre- and postmenopausal women.\u003c/strong\u003e \u003cstrong\u003ea \u003c/strong\u003eE2 (pink), \u003cstrong\u003eb\u003c/strong\u003e estrone (E1) (orange), \u003cstrong\u003ec\u003c/strong\u003e P4 (violet) and \u003cstrong\u003ed\u003c/strong\u003e T (blue) plasma\u003cstrong\u003e \u003c/strong\u003elevels in 10 to 20-week-old \u003cem\u003eNSG\u003c/em\u003e female mice \u003cem\u003e(NSG)\u003c/em\u003e compared to samples from premenopausal (pre-M) and postmenopausal women (post-M) measured by LC-MS. Each dot represents an individual sample and bars represent means ± SD. Black and dark grey triangles on grey background indicate previously reported upper and lower ranges for pre- and postmenopausal women\u003csup\u003e \u003c/sup\u003e. Grid lines show LLOQs. NSG n=227, pre-M n=156, post-M n=23. Statistical significance was tested by one-way ANOVA (Dunnett's multiple comparisons test),* p \u0026lt; 0.05, ** p \u0026lt; 0.005, **** p \u0026lt; 0.0001. \u003cstrong\u003ee\u003c/strong\u003e Table showing\u003cu\u003e \u003c/u\u003emedian plasma concentrations and 2.5-97.5th percentiles range for pre- and postmenopausal women.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4808879/v1/87e4dfc5dd253f7b50147e25.png"},{"id":64248373,"identity":"8377e06d-c8dd-4786-9444-2f3e8ddc2042","added_by":"auto","created_at":"2024-09-10 20:48:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":697884,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSex steroid levels in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eNSG\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e females subjected to hormone treatments.\u003c/strong\u003e \u003cstrong\u003ea \u003c/strong\u003eE2 (pink), \u003cstrong\u003eb\u003c/strong\u003e E1 (orange), \u003cstrong\u003ec\u003c/strong\u003e P4 (violet) and \u003cstrong\u003ed\u003c/strong\u003e T (blue) plasma\u003cstrong\u003e \u003c/strong\u003elevels E2-, P4-, E2 + P4-treated and ovariectomized mice (OVX) after 60-day-treatment measured by LC-MS and compared to intact mice (CTRL, grey dots). \u003cstrong\u003ee\u003c/strong\u003e Table showing median plasma concentrations and 2.5-97.5th percentiles range for E2-, P4-, E2 + P4-treated and ovariectomized mice (OVX). \u003cstrong\u003ef \u003c/strong\u003eE2, \u003cstrong\u003eg\u003c/strong\u003e E1, \u003cstrong\u003eh\u003c/strong\u003e P4 and \u003cstrong\u003ei \u003c/strong\u003eT plasma\u003cstrong\u003e \u003c/strong\u003elevels in E2-, P4-, E2 + P4-treated for 60 days \u003cem\u003eNSG\u003c/em\u003e female mice compared to premenopausal women (pre-M, grey dots) data measured by LC-MS. \u003cstrong\u003ej \u003c/strong\u003eE2, \u003cstrong\u003ek\u003c/strong\u003e E1, \u003cstrong\u003el \u003c/strong\u003eP4 and \u003cstrong\u003em\u003c/strong\u003e T plasma\u003cstrong\u003e \u003c/strong\u003elevels\u003cstrong\u003e \u003c/strong\u003ein the plasma of untreated (CTRL, grey dots\u003cem\u003e)\u003c/em\u003e or ovariectomized \u003cem\u003e(\u003c/em\u003eOVX) \u003cem\u003eNSG\u003c/em\u003e females compared to postmenopausal women (post-M) measured by LC-MS. Bars on grey background indicate previously reported upper and lower ranges for pre- and post-menopausal women\u003csup\u003e \u003c/sup\u003e. Each dot represents an individual mouse and the bars represent the mean hormone levels with error bars indicating ± SD. Grid lines indicate the LLOQ. CTRL n=227, E2 n=42, P4 n=72, E2 + P4 n=44, OVX n=18, pre-M n=156, Statistical significance was tested by one-way ANOVA (Dunnett's multiple comparisons test),* p \u0026lt; 0.05, ** p \u0026lt; 0.005, **** p \u0026lt; 0.0001.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4808879/v1/856da6910107be9972e6ee4b.png"},{"id":64249353,"identity":"72c5dd2e-5ecc-4f8b-83c7-daf603f0bc2c","added_by":"auto","created_at":"2024-09-10 21:04:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2122436,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4808879/v1/d56c8ab7-242c-4924-b034-3b22758127d6.pdf"},{"id":64248374,"identity":"10743e0a-cf04-4f07-9050-33bfc7f800ab","added_by":"auto","created_at":"2024-09-10 20:48:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":758436,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4808879/v1/3c04e57af19e7eee6b11c25b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Humanizing the endocrine milieu of female mice for women’s health-related studies","fulltext":[{"header":"Introduction","content":"\u003cp\u003eResearch into women\u0026rsquo;s health depends on experimental models ranging from \u003cem\u003ein vitro\u003c/em\u003e cell lines to complex genetically engineered mouse and xenograft models \u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Notably, in oncology, the success rate of clinical translation has been low because the models used in preclinical research fail to adequately mimic the human disease \u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. To increase the translatability, PDXs are increasingly used because they capture intra- and inter-tumor heterogeneity better than the widely used cell lines or genetically engineered mouse models (GEMMs) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Improved engraftment by injection into the milk ducts has recently been shown to be enabling for studying both normal breast epithelial cells as well as breast cancer cells \u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e when in particular, estrogen receptor positive breast cancer was previously difficult to study \u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHost mice are severely immunocompromised \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e allowing them to tolerate grafts of human origin but also presenting a major limitation of xenograft models. In recent years, numerous efforts to humanize the immune system of recipient mice have further improved the predictive value of xenograft studies \u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Yet, another important factor, the hormonal milieu of the models used, is often overlooked.\u003c/p\u003e \u003cp\u003eOvarian hormones control numerous physiological functions and impinge on tumor development \u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. While this is well established for breast cancer and tumors of other reproductive organs, evidence has accumulated that this applies also to malignancies arising from non-reproductive organs \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. For instance, bladder cancer has a higher incidence in men than in women and the role of androgen receptor signaling in its progression is actively explored \u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Similarly, higher incidence rates in hepatocellular carcinoma in males depend on sex hormones, with estrogen receptor signaling suppressing, and androgen receptor signaling promoting hepatocarcinogenesis \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Likewise, E2 plays a role in thyroid cancer, which primarily affects women \u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Furthermore, epidemiologic studies have revealed that early menarche along with late menopause and hormone replacement therapy increases the risk of various hormone-dependent tumors \u003csup\u003e\u003cspan additionalcitationids=\"CR37 CR38 CR39\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile most hormones are shared across mammals, there are differences among species with regards to reproductive biology. Female mice have 4-day reproductive cycles known as estrous cycles consisting of three phases proestrus, estrus and diestrus while the human menstrual cycles last from 25 to 30 days and is divided into follicular and luteal phase \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Humans are one of few mammalian species who experience menopause, a reproductive stage that is not observed in rodents. Additionally, there are differences in mouse and human sex steroid metabolism. In humans, the plasma protein, sex hormone binding globulin (SHBG), binds with high affinity to sex steroids and controls their availability by regulating their tissue distribution and metabolism \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Rodents do not express this protein and this affects how the sex hormones circulate and function. Similarly, in humans, but not rodents, the adrenal gland secretes substantial amounts of the sex steroid precursors, androstenedione and dehydroepiandrosterone (DHEA) \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Together, these differences result in species-specific plasma concentrations of sex steroids \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo gain physiologically relevant insights into female health, sex steroid profiles need to be adequately reflected in the experimental design \u003csup\u003e\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Previously, it has been difficult to measure hormone levels in mice due to the high sample volume requirement. The low steroid hormone concentrations and the inability to measure more than one hormone at a time with immunoassays were additional challenges \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. MS is the optimal technique for analyzing sex steroids in plasma samples because multiple substances can be measured simultaneously within each sample with high precision and accuracy \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWith the present study, we address the need for more physiologic models in the study of hormone-sensitive diseases. We present a LC-MS assay to measure concomitantly E2, estrone (E1), P4 and T in small volumes of plasma as can be routinely obtained by tail vein sampling and measure these in female \u003cem\u003eNSG\u003c/em\u003e mice, the most widely used immunocompromised mouse strain in PDX modelling. Finally, we propose simple approaches to mimic critical physiological stages in women\u0026rsquo;s lives to enable more physiologically relevant modelling of women\u0026rsquo;s health issues.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLC-MS method to measure 17β-estradiol (E2), estrone (E1), progesterone (P4), and testosterone (T)\u003c/h2\u003e \u003cp\u003eTo enable simultaneous measurements of four ovarian hormones in blood samples from small animals, we adapted a previously used LC-MS method for 100 \u0026micro;l of plasma \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. To enhance the detection for the particularly low estrogens, we introduced a derivatization step with dansyl chloride to improve the ionization efficiency through reaction with phenolic hydroxyl group of estrogens \u003csup\u003e\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea) Sensitivity evaluation of the assay revealed that the lower limits of quantitation (LLOQ) for E2, E1, P4, and T were 4.1, 10.24, 160 and 50 pg/ml, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Thus, 100 \u0026micro;l of plasma as obtained through routine tail bleeding are sufficient to measure four major ovarian hormones facilitating routine profiling in small animal experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ea\u003c/b\u003e Illustration of the optimized LC-MS method for simultaneous measurements of four ovarian hormones in plasma samples from humans and mice. Plasma samples are prepared using solid-phase extraction (SPE) for LC-MS analysis of progesterone (P4) and testosterone (T). The remaining samples are derivatized and analyzed by LC-MS for 17β-estradiol (E2) and estrone (E1). Generated with Biorender.com with modifications. \u003cb\u003eb\u003c/b\u003e LLOQ for E2, E1, P4 and testosterone T, % Relative standard deviation (RSD), % bias at LLOQ and calibration ranges.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlasma levels of ovarian steroids in NOD.Cg-\u003c/b\u003e \u003cb\u003ePrkdc\u003c/b\u003e \u003csup\u003e \u003cb\u003escid\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eIl2rg\u003c/b\u003e\u003csup\u003e\u003cb\u003etm1Wjl\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/SzJ (\u003c/b\u003e\u003cb\u003eNSG\u003c/b\u003e\u003cb\u003e) mice\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eNSG\u003c/em\u003e mice are widely used in biomedical research for xenograft experiments because of the broad extent of immune suppression. Yet there are no reference values of hormone plasma levels. We determined E2, E1, P4, and T plasma concentrations in adult virgin \u003cem\u003eNSG\u003c/em\u003e females and compared them to those of \u003cem\u003eC57/Bl6\u003c/em\u003e mice we reported previously \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e as well as to values from other studies \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan additionalcitationids=\"CR57 CR58 CR59\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. E2 plasma levels in \u003cem\u003eNSG\u003c/em\u003e females with mean values of 11,21 pg/ml were comparable to \u003cem\u003eC57/Bl6\u003c/em\u003e females with mean value 12,41 pg/ml (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, d). P4 levels tended to be higher and more variable in \u003cem\u003eNSG\u003c/em\u003e mice with mean value of 4,90 ng/ml compared to \u003cem\u003eC57/Bl6\u003c/em\u003e mice in our dataset with mean 2,11 ng/ml. However, these levels were within the same range as the published reference values for \u003cem\u003eC57/Bl6\u003c/em\u003e mice \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan additionalcitationids=\"CR57 CR58 CR59\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, d). T levels were similar in both strains with mean 0,10 ng/ml in \u003cem\u003eNSG\u003c/em\u003e and 0,12 ng/ml in \u003cem\u003eC57/Bl6\u003c/em\u003e mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Most E1 measurements were below the LLOQ in both strains (data not shown). Thus, \u003cem\u003eNSG\u003c/em\u003e and \u003cem\u003eC57/Bl6\u003c/em\u003e females have comparable sex steroid profiles within the range from values measured by others in \u003cem\u003eC57/Bl6\u003c/em\u003e model \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan additionalcitationids=\"CR57 CR58 CR59\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePlasma ovarian steroid levels in murine versus human samples\u003c/h2\u003e \u003cp\u003eTo compare the ovarian hormone levels detected in \u003cem\u003eNSG\u003c/em\u003e females to those observed in women, we measured the 4 ovarian steroids in plasma from 156 pre- and 23 post-menopausal women and recurred to published reference values \u003csup\u003e\u003cspan additionalcitationids=\"CR62 CR63 CR64\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Murine E2 levels (mean 11,21 pg/ml) were more than 10-fold lower than those observed in premenopausal women who had mean value 161 pg/ml but comparable to the levels detected in postmenopausal women with mean 12.80 pg/ml (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, e). E1 was readily detected in the plasma of both pre- and post-menopausal women with mean values of 67,85 and 29,32 pg/ml respectively, while below LLOQ in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, e). Plasma P4 levels were higher in mice (mean 4,90 ng/ml) than in pre- and post-menopausal women with mean values 1,70 and 0,07 ng/ml respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, e). The mean P4 value observed in \u003cem\u003eNSG\u003c/em\u003e mice was comparable to luteal phase levels in women, which range from approximately 5 to 20 ng/ml (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, e). T was lower in mice (mean 0,10 ng/ml) than in pre- and postmenopausal women with means of 0,30 and 0,26 ng/ml (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, e). The E2 and P4 concentrations measured in women from our cohort were in the same range as the reference values \u003csup\u003e\u003cspan additionalcitationids=\"CR62 CR63 CR64\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. However, the range of E1 levels in postmenopausal women we measured was twice as wide as ranges reported by others \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Taken together, murine E2 levels are comparable to those found in postmenopausal women while murine P4 levels are closer to luteal phase values in humans.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eHormone treatments of mice mimic pre- and post-menopausal steroid profiles\u003c/h2\u003e \u003cp\u003eTo mimic the endocrine milieu of pre- and postmenopausal women, we used two strategies\u0026thinsp;\u0026minus;\u0026thinsp;subcutaneous implantation of slow-release hormone pellets with E2, P4, or E2 alongside with P4 and hormone ablation by ovariectomy \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSixty days after the implantation of 0.3 mg E2-containing silicone pellets, E2 levels increased 46-fold with mean 529,30 pg/ml in comparison to intact mice (mean 11,21 pg/ml) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, e). Consistent with a fraction of the administered E2 being converted to E1, E1 levels increased 17-fold with mean 25,82 pg/ml (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, e). P4 levels were decreased to mean 0,85 pg/ml consistent with exogenous E2 suppressing the estrous cycle-related peaks in P4 levels \u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. The 20 mg slow-release P4 pellets increased plasma P4 levels 2-fold with mean 15,75 ng/ml compared to intact mice (mean 4,90 ng/ml) and had no effect on other hormone levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, e). In premenopausal women, E2 levels peak during the follicular phase, while the luteal phase is characterized by a lower peak in E2 levels and high P4 levels. To mimic human luteal phase hormone levels and overcome the inhibitory effect of E2 treatments on P4 secretion, we implanted mice with 0.3 mg E2 pellets alongside 20 mg P4 pellets and compared the resulting hormone levels to published data \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. E2 levels were higher in treated mice with mean 426,30 pg/ml than in premenopausal women (mean 161 pg/ml) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef) and had higher P4 with mean 19,39 ng/ml than premenopausal women (mean 1,70 ng/ml) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eh). It is important to note that we did not separate the plasma values from women of our dataset by phase of the menstrual cycle, which results in more heterogeneous hormone ranges. E1 and T remained lower in mice than in women (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg, i). Thus, E2- and E2\u0026thinsp;+\u0026thinsp;P4-treated mice have E2 and P4 plasma levels comparable to those in women during follicular and luteal phase \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e, respectively.\u003c/p\u003e \u003cp\u003eIntact mice have similar E2 (mean 11,21 pg/ml), but higher P4 levels (mean 4,90 ng/ml) than postmenopausal women (means E2: 12,80 pg/ml and P4: 0,07 ng/ml) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, c and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ej, l). Therefore, we compared the steroid profile of ovariectomized mice with decreased E2 and E1 levels to postmenopausal women. Sixty days following ovariectomy, both E2 and E1 levels dropped below quantitation limit (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ej, k). Plasma P4 levels in ovariectomized mice remained higher with mean value 1,74 ng/ml compared to postmenopausal patients, though these levels were closer to human settings than those observed in intact mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003el). Ovariectomy elevated mouse plasma T concentrations to mean 0,33 ng/ml, thereby better matching levels of postmenopausal women (mean 0,27 ng/ml) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003em). Thus, postmenopausal E2 levels are similar to levels in intact \u003cem\u003eNSG\u003c/em\u003e females, but T and P4 levels are better mimicked in ovariectomized mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMouse models are essential in preclinical and translational research, and improving their predictive power by better mimicking human physiology is a continuous effort. Here, we sought to improve the endocrine context of the murine models, with regard to ovarian steroid hormones, central to women\u0026rsquo;s health. We focused on the widely used \u003cem\u003eNSG\u003c/em\u003e strain and propose a simple practical approach to mimic distinct endocrine milieus pertinent to women\u0026rsquo;s health. First, we optimized a LC-MS method \u003csup\u003e51,52\u003c/sup\u003e for the simultaneous measurement of E2, E1, P4, and T in 100 \u0026micro;l. This optimization is crucial for working with low volume mice blood samples and allows for repeat measurements via tail vein sampling vital for accurately monitoring hormone fluctuations over time. Our LC-MS method, while effective, has limitations; like higher LLOQs than other methods such as gas chromatography (GC)-MS \u003csup\u003e44\u003c/sup\u003e . This applies in particular to E1, where the values we measured remained below the quantitation limit in untreated mice and higher errors for low values may also explain the high variation we observed in postmenopausal women. Additionally, tandem LC\u0026ndash;MS/MS with triple quadrupole type instruments provide a wide range from LLOQs with the minimal of 0.14 pg/ml for E1 and E2 \u003csup\u003e70\u003c/sup\u003e providing potential for further improvement of the present method.\u003c/p\u003e\n\u003cp\u003eOur findings demonstrate that intact \u003cem\u003eNSG\u003c/em\u003e mice have plasma E2 concentrations similar to postmenopausal women suggest that at least with regard to E2 levels they provide an approximative endocrine milieu of postmenopausal women, whereas T and P4 levels were better reflected by ovariectomized mice. Interestingly, while T levels increase upon ovariectomy in \u003cem\u003eNSG\u003c/em\u003e mice, they decrease in oophorectomized women \u003csup\u003e71\u003c/sup\u003e. This may be an \u003cem\u003eNSG\u003c/em\u003e-specific phenomenon as reduced but still measurable T levels were observed in ovariectomized \u003cem\u003eC57/BL6\u003c/em\u003e mice and suggest that the adrenal glands could contribute to circulating T in female mice \u003csup\u003e44\u003c/sup\u003e.\u0026nbsp;Further studies are needed to determine if the adrenal glands can compensate T production in the case of gonadectomy. Moreover, the day of the estrous cycle when the blood sample is collected may influence T hormone levels \u003csup\u003e72\u003c/sup\u003e. As \u003cem\u003eNSG\u003c/em\u003e mice lack B and T cells, the estrous cycle stage could not be assessed by vaginal smear.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo better match the hormone profile of women with murine models, we propose simple strategies. The approaches are low cost, the fabrication of slow-release hormone pellets is flexible and readily adjustable to different time windows requirements, moreover it can readily be extended to other steroids.\u003c/p\u003e\n\u003cp\u003eThe estrone levels were consistently lower in mice than humans, regardless of treatment. None of the strategies we tested allowed to match E1 levels in postmenopausal women without simultaneously increasing E2. To mimic the specific sex steroid levels in murine model this issue could be addressed by using E1 pellets can be added, as suggested by Qureshi et al. \u003csup\u003e73\u003c/sup\u003e. Additionally, since estrogens can inhibit the hypothalamic secretion of gonadotropin-releasing hormone \u003csup\u003e74,75\u003c/sup\u003e E1 pellets may also help suppress the cycle-related variation in circulating P4. As such, ovariectomized mice with estrone pellets might most accurately reflect the menopausal endocrine milieu.\u003c/p\u003e\n\u003cp\u003eE2 and E2 in combination with P4 slow-released pellets allowed us to mimic the follicular and luteal phase levels of the two major ovarian hormones. Our results showed that E2 levels in treated mice were higher compared to premenopausal women which is likely due to the use of a single concentration of E2 pellet of 0.3 mg in our study. Adjusting the pellet dosage by titration could help to better approximate the E2 levels observed in premenopausal women, improving the translational relevance of our model. An important limitation of hormone-released pellet implantation is that hormone release decreases over time and fails to mimic natural cyclicity. Slow-release silicone-based implants are easy to prepare and are flexible, but they administer chronic instead of fluctuating doses of hormones. Drug delivery technology devices, such as ALZET\u0026reg; or iPRECIO\u0026reg;, are tools for more accurate and continuous delivery and more drug-release devices with varying release rates are currently under development \u003csup\u003e76\u0026ndash;79\u003c/sup\u003e. Depending on the specific research question, scientists may choose to use hormone treatments to more accurately mimic patients\u0026apos; physiology. With the present approach flexible tools are at hand.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAnimal experiments\u003c/p\u003e\n\u003cp\u003eAnimal experiments with \u003cem\u003eNSG\u003c/em\u003e mice were performed in accordance with protocol (VD 1865.3, 1865.4, and 1865.5) approved by the Service de la Consommation et des Affaires V\u0026eacute;t\u0026eacute;rinaires of Canton de Vaud. \u003cem\u003eNOD.Cg-Prkdc\u003csup\u003escid\u003c/sup\u003e Il2rg\u003csup\u003etm1Wjl\u003c/sup\u003e/SzJ\u003c/em\u003e mice (\u003cem\u003eNSG\u003c/em\u003e) were purchased from Jackson Laboratories and 10-20-week-old females were subcutaneously implanted with slow-release-hormone pellets and sacrificed 60 days later, blood was collected by heart puncture.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePatient samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHuman plasma samples were obtained from patients undergoing breast reduction surgery at the Centre H\u0026ocirc;spitalier Universitaire Vaudois and Hirslanden Hospital. The study was approved by the Commission cantonale d\u0026rsquo;\u0026eacute;thique de la recherche sur l\u0026rsquo;\u0026ecirc;tre humain ethics committee (VD183/10) and informed consent was obtained from all the participants. Patients on hormonal contraception or hormone replacement therapy and blood samples, in which a progestin was detectable by LC-MS (gestodene, levonorgestrel, etonogestrel, chlormadinone acetate, cyproteroneacetate, drospirenone, desacetyl norgestimate, medroxyprogesterone acetate, norethindrone, dienogest or nomegestrol acetate) were excluded \u003csup\u003e51\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePellet preparation\u003c/p\u003e\n\u003cp\u003ePellets were prepared by mixing part A (MP3745/E81949) and B (MP3744/E8195) of the low viscosity silicon elastomer (MED-4011) with hormone powder as indicated below. The mix was incubated overnight at 37\u0026deg;C and cut as described \u003csup\u003e12\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHormone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCatalog number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHormone dose/pellet\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSilicon part A\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSilicon part B\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026micro;l)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHormone powder\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(mg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePellet weight (mg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e17\u0026beta;-estradiol (E2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eE2758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7,8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eProgesterone (P4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP0130-25G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eHormone measurements\u003c/p\u003e\n\u003cp\u003eE2, E1, P4, and T plasma levels were measured by high resolution LC-MS (Q-Exactive Orbitrap, ThermoFisher Scientific) using targeted-SIM (tSIM) acquisition \u003csup\u003e51,52\u003c/sup\u003e with the following modifications. For sample preparation, 100 \u0026micro;l of plasma were mixed with 100 \u0026micro;l of internal standards in 5% (w/v) phosphoric acid, applied to a solid phase extraction plate (Oasis MCX \u0026micro;Elution 96-well plate, Waters) and washed with 5% (w/v) ammonium hydroxide (NH\u003csub\u003e4\u003c/sub\u003eOH) and 20% (v/v) methanol and eluted with isopropyl alcohol. Eluates were evaporated under N\u003csub\u003e2\u003c/sub\u003e on a TurboVap 96 (Biotage, Uppsala, Sweden) and reconstituted in 100 \u0026micro;l 40% acetonitrile (ACN), corresponding to initial LC mobile phase conditions. To detect P4 and T, 20 \u0026micro;l of sample were injected onto a Zorbax Eclipse Plus C18 (2.1 \u0026times; 50 mm 1.8 \u0026micro; m) column (AgilentTechnologies, Santa Clara, California, United States) at a flow rate of 0,2 ml/min using a gradient of purified H\u003csub\u003e2\u003c/sub\u003eO and ACN, both containing 0,1% (v/v) formic acid. Solvent gradient was started at 40% ACN, held for 2 min, linearly increased to 70% ACN over 6 min, further increased to 100% ACN over 0,5 min, held at 100% ACN for 1 min, decreased to 40% ACN over 0,5 min and finally held at 40% ACN for re-equilibration until end of 12 min run. For the combined\u0026nbsp;analysis of E2 and E1 with P4 and T, the same\u0026nbsp;sample extracts were again evaporated under nitrogen and reconstituted in 50 \u0026micro;L sodium bicarbonate buffer (NaHCO\u003csub\u003e3\u003c/sub\u003e, 100 mM, pH adjusted to 10 with NaOH) and 50 \u0026micro;l dansyl chloride (2.0 mg/ml in acetone) were added per sample for derivatization. The plate was left at 65\u0026deg;C for 15 min in an incubator, cooled to 4\u0026deg;C and transferred to the LC autosampler. For E2 and E1 detection, 25 \u0026micro;l of sample were injected onto the same LC column at a flow rate of 0,2 ml/min using a gradient of purified H\u003csub\u003e2\u003c/sub\u003eO and ACN, both containing 0,1% (v/v) formic acid. The solvent gradient started at 70% ACN was held for 2 min, linearly increased to 85% ACN over 6 min, further increased to 100% ACN over 2 min, held at 100% ACN for 1 min, decreased to 70% ACN over 1 min and finally held at 70% ACN for re-equilibration until the end of the 15 min run.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mass spectrometer was a QExactive Orbitrap working in positive mode using previously reported parameters (Laszlo et al., 2019) for P4 and T and the following modifications for E2 and E1: resolution 70k, automatic gain control (AGC) target 1e6, MAX ion injection time 100 ms, isolation window 0.5 m/z, scan range 500-750 m/z. The tSIM method acquires the user-defined targeted masses in retention time\u0026nbsp;dependent time segments. Data were processed with Thermo Xcalibur 4.0.27.10. The targeted SIM method contained an inclusion list with 10 ppm precision (Supplemental table 1). Mass extraction for analysis was carried out at 5 ppm. LLOQs were determined on triplicate samples serially diluted 1:2,5 over 8 dilutions.\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using GraphPad Prism (version 10) (San Diego, California, USA, www.graphpad.com). Statistical tests are indicated in the figure legends. Significance was set as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe Authors declare no Competing Financial or Non-Financial Interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: CC, SB and CB; methodology: CL, CC, SB; analysis and data visualization: CC, CL and DM; resources: CB, SB, P-AB; data generation: CC, CL, VS, LB; writing/original draft preparation: CC, DM, and CB; writing, review, and editing: CC, DM, SB, VS and CB; supervision: SB, CB. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work was supported by the European Union\u0026rsquo;s Horizon 2020 Research and Innovation Programme Marie Skłodowska-Curie (grant number 859860). CB has support from Breast Cancer Now as part of program funding to the Breast Cancer Now Toby Robins Research Centre.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSausville, E. A. \u0026amp; Burger, A. M. Contributions of human tumor xenografts to anticancer drug development. \u003cem\u003eCancer Research\u003c/em\u003e vol. 66 Preprint at https://doi.org/10.1158/0008-5472.CAN-05-3627 (2006).\u003c/li\u003e\n\u003cli\u003eDay, C. P., Merlino, G. \u0026amp; Van Dyke, T. Preclinical Mouse Cancer Models: A Maze of Opportunities and Challenges. \u003cem\u003eCell\u003c/em\u003e vol. 163 Preprint at https://doi.org/10.1016/j.cell.2015.08.068 (2015).\u003c/li\u003e\n\u003cli\u003eHolen, I., Speirs, V., Morrissey, B. \u0026amp; Blyth, K. In vivo models in breast cancer research: Progress, challenges and future directions. \u003cem\u003eDMM Disease Models and Mechanisms\u003c/em\u003e vol. 10 Preprint at https://doi.org/10.1242/dmm.028274 (2017).\u003c/li\u003e\n\u003cli\u003eHidalgo, M. \u003cem\u003eet al.\u003c/em\u003e Patient-derived Xenograft models: An emerging platform for translational cancer research. \u003cem\u003eCancer Discov\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eHait, W. N. Anticancer drug development: The grand challenges. \u003cem\u003eNature Reviews Drug Discovery\u003c/em\u003e vol. 9 Preprint at https://doi.org/10.1038/nrd3144 (2010).\u003c/li\u003e\n\u003cli\u003eJohnson, J. I. \u003cem\u003eet al.\u003c/em\u003e Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials. \u003cem\u003eBr J Cancer\u003c/em\u003e \u003cstrong\u003e84\u003c/strong\u003e, (2001).\u003c/li\u003e\n\u003cli\u003ePrinz, F., Schlange, T. \u0026amp; Asadullah, K. Believe it or not: How much can we rely on published data on potential drug targets? \u003cem\u003eNature Reviews Drug Discovery\u003c/em\u003e vol. 10 Preprint at https://doi.org/10.1038/nrd3439-c1 (2011).\u003c/li\u003e\n\u003cli\u003eWhittle, J. R., Lewis, M. T., Lindeman, G. J. \u0026amp; Visvader, J. E. Patient-derived xenograft models of breast cancer and their predictive power. \u003cem\u003eBreast Cancer Research\u003c/em\u003e vol. 17 Preprint at https://doi.org/10.1186/s13058-015-0523-1 (2015).\u003c/li\u003e\n\u003cli\u003eYada, E., Wada, S., Yoshida, S. \u0026amp; Sasada, T. Use of patient-derived xenograft mouse models in cancer research and treatment. \u003cem\u003eFuture Science OA\u003c/em\u003e vol. 4 Preprint at https://doi.org/10.4155/fsoa-2017-0136 (2018).\u003c/li\u003e\n\u003cli\u003eShamseddin, M. \u003cem\u003eet al.\u003c/em\u003e Contraceptive progestins with androgenic properties stimulate breast epithelial cell proliferation. \u003cem\u003eEMBO Mol Med\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003cli\u003eSflomos, G. \u003cem\u003eet al.\u003c/em\u003e A Preclinical Model for ER\u0026alpha;-Positive Breast Cancer Points to the Epithelial Microenvironment as Determinant of Luminal Phenotype and Hormone Response. \u003cem\u003eCancer Cell\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 407\u0026ndash;422 (2016).\u003c/li\u003e\n\u003cli\u003eDuss, S. \u003cem\u003eet al.\u003c/em\u003e An oestrogen-dependent model of breast cancer created by transformation of normal human mammary epithelial cells. \u003cem\u003eBreast Cancer Research\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, (2007).\u003c/li\u003e\n\u003cli\u003eScabia, V. \u003cem\u003eet al.\u003c/em\u003e Estrogen receptor positive breast cancers have patient specific hormone sensitivities and rely on progesterone receptor. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eFiche, M. \u003cem\u003eet al.\u003c/em\u003e Intraductal patient-derived xenografts of estrogen receptor \u0026alpha;-positive breast cancer recapitulate the histopathological spectrum and metastatic potential of human lesions. \u003cem\u003eJ Pathol\u003c/em\u003e \u003cstrong\u003e247\u003c/strong\u003e, 287\u0026ndash;292 (2019).\u003c/li\u003e\n\u003cli\u003eSflomos, G. \u003cem\u003eet al.\u003c/em\u003e Intraductal xenografts show lobular carcinoma cells rely on their own extracellular matrix and LOXL1. \u003cem\u003eEMBO Mol Med\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003cli\u003eAbdolahi, S. \u003cem\u003eet al.\u003c/em\u003e Patient-derived xenograft (PDX) models, applications and challenges in cancer research. \u003cem\u003eJ Transl Med\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 206 (2022).\u003c/li\u003e\n\u003cli\u003eCarpenter, R. S. \u003cem\u003eet al.\u003c/em\u003e Human immune cells infiltrate the spinal cord and impair recovery after spinal cord injury in humanized mice. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eZhao, Y. \u003cem\u003eet al.\u003c/em\u003e Development of a new patient-derived xenograft humanised mouse model to study human-specific tumour microenvironment and immunotherapy. \u003cem\u003eGut\u003c/em\u003e vol. 67 Preprint at https://doi.org/10.1136/gutjnl-2017-315201 (2018).\u003c/li\u003e\n\u003cli\u003eScherer, S. D. \u003cem\u003eet al.\u003c/em\u003e An immune-humanized patient-derived xenograft model of estrogen-independent, hormone receptor positive metastatic breast cancer. \u003cem\u003eBreast Cancer Research\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003cli\u003eDobrolecki, L. E. \u003cem\u003eet al.\u003c/em\u003e Patient-derived xenograft (PDX) models in basic and translational breast cancer research. \u003cem\u003eCancer and Metastasis Reviews\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 547\u0026ndash;573 (2016).\u003c/li\u003e\n\u003cli\u003eKostlan, R. Joseph. \u003cem\u003eet al.\u003c/em\u003e Clinically relevant humanized mouse models of metastatic prostate cancer facilitate therapeutic evaluation. \u003cem\u003eMolecular Cancer Research\u003c/em\u003e (2024) doi:10.1158/1541-7786.mcr-23-0904.\u003c/li\u003e\n\u003cli\u003eYang, Y. \u003cem\u003eet al.\u003c/em\u003e Humanized mouse models: A valuable platform for preclinical evaluation of human cancer. \u003cem\u003eBiotechnology and Bioengineering\u003c/em\u003e vol. 121 Preprint at https://doi.org/10.1002/bit.28618 (2024).\u003c/li\u003e\n\u003cli\u003eHenderson, B. E. \u0026amp; Feigelson, H. S. Hormonal carcinogenesis. \u003cem\u003eCarcinogenesis\u003c/em\u003e vol. 21 Preprint at https://doi.org/10.1093/carcin/21.3.427 (2000).\u003c/li\u003e\n\u003cli\u003eBrisken, C. Progesterone signalling in breast cancer: A neglected hormone coming into the limelight. \u003cem\u003eNature Reviews Cancer\u003c/em\u003e vol. 13 Preprint at https://doi.org/10.1038/nrc3518 (2013).\u003c/li\u003e\n\u003cli\u003eSingh, R. R. \u0026amp; Kumar, R. Steroid hormone receptor signaling in tumorigenesis. \u003cem\u003eJournal of Cellular Biochemistry\u003c/em\u003e vol. 96 Preprint at https://doi.org/10.1002/jcb.20566 (2005).\u003c/li\u003e\n\u003cli\u003eCosta, A. R. \u003cem\u003eet al.\u003c/em\u003e The Sex Bias of Cancer. \u003cem\u003eTrends in Endocrinology and Metabolism\u003c/em\u003e vol. 31 Preprint at https://doi.org/10.1016/j.tem.2020.07.002 (2020).\u003c/li\u003e\n\u003cli\u003eManolagas, S. C. \u0026amp; Kousteni, S. Perspective: Nonreproductive sites of action of reproductive hormones. \u003cem\u003eEndocrinology\u003c/em\u003e vol. 142 Preprint at https://doi.org/10.1210/endo.142.6.8221 (2001).\u003c/li\u003e\n\u003cli\u003eGil, D. \u003cem\u003eet al.\u003c/em\u003e Dihydrotestosterone increases the risk of bladder cancer in men. \u003cem\u003eHum Cell\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eGodoy, G., Gakis, G., Smith, C. L. \u0026amp; Fahmy, O. Effects of androgen and estrogen receptor signaling pathways on bladder cancer initiation and progression. \u003cem\u003eBladder Cancer\u003c/em\u003e vol. 2 Preprint at https://doi.org/10.3233/BLC-160052 (2016).\u003c/li\u003e\n\u003cli\u003eChen, J. \u003cem\u003eet al.\u003c/em\u003e The androgen receptor in bladder cancer. \u003cem\u003eNature Reviews Urology\u003c/em\u003e vol. 20 Preprint at https://doi.org/10.1038/s41585-023-00761-y (2023).\u003c/li\u003e\n\u003cli\u003eLi, Z., Tuteja, G., Schug, J. \u0026amp; Kaestner, K. H. Foxa1 and Foxa2 are essential for sexual dimorphism in liver cancer. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e148\u003c/strong\u003e, (2012).\u003c/li\u003e\n\u003cli\u003eZhang, L. \u003cem\u003eet al.\u003c/em\u003e Sex steroid axes in determining male predominance in hepatocellular carcinoma. \u003cem\u003eCancer Letters\u003c/em\u003e vol. 555 Preprint at https://doi.org/10.1016/j.canlet.2022.216037 (2023).\u003c/li\u003e\n\u003cli\u003eLiu, J., Xu, T., Ma, L. \u0026amp; Chang, W. Signal Pathway of Estrogen and Estrogen Receptor in the Development of Thyroid Cancer. \u003cem\u003eFrontiers in Oncology\u003c/em\u003e vol. 11 Preprint at https://doi.org/10.3389/fonc.2021.593479 (2021).\u003c/li\u003e\n\u003cli\u003eDerwahl, M. \u0026amp; Nicula, D. Estrogen and its role in thyroid cancer. \u003cem\u003eEndocr Relat Cancer\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Grady, T. J. \u003cem\u003eet al.\u003c/em\u003e Association of hormonal and reproductive factors with differentiated thyroid cancer risk in women: a pooled prospective cohort analysis. \u003cem\u003eInt J Epidemiol\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, (2024).\u003c/li\u003e\n\u003cli\u003eKelsey, J. L. \u0026amp; Horn-ross, P. L. Breast cancer: Magnitude of the problem and descriptive epidemiology. \u003cem\u003eEpidemiol Rev\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, (1993).\u003c/li\u003e\n\u003cli\u003eChang-Claude, J. \u003cem\u003eet al.\u003c/em\u003e Age at menarche and menopause and breast cancer risk in the International BRCA1/2 Carrier Cohort Study. \u003cem\u003eCancer Epidemiology Biomarkers and Prevention\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, (2007).\u003c/li\u003e\n\u003cli\u003eColditz, G. A., Rosner, B. A., Chen, W. Y., Holmes, M. D. \u0026amp; Hankinson, S. E. Risk Factors for Breast Cancer According to Estrogen and Progesterone Receptor Status. \u003cem\u003eJNCI: Journal of the National Cancer Institute\u003c/em\u003e \u003cstrong\u003e96\u003c/strong\u003e, 218\u0026ndash;228 (2004).\u003c/li\u003e\n\u003cli\u003eTravis, R. C. \u0026amp; Key, T. J. Oestrogen exposure and breast cancer risk. \u003cem\u003eBreast Cancer Research\u003c/em\u003e vol. 5 Preprint at https://doi.org/10.1186/bcr628 (2003).\u003c/li\u003e\n\u003cli\u003eVilla, P. \u003cem\u003eet al.\u003c/em\u003e Hormone Replacement Therapy in Post-Menopause Hormone-Dependent Gynecological Cancer Patients: A Narrative Review. \u003cem\u003eJournal of Clinical Medicine\u003c/em\u003e vol. 13 Preprint at https://doi.org/10.3390/jcm13051443 (2024).\u003c/li\u003e\n\u003cli\u003eBull, J. R. \u003cem\u003eet al.\u003c/em\u003e Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles. \u003cem\u003eNPJ Digit Med\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eJ\u0026auml;nne, M., Deol, H. K., Power, S. G. A., Yee, S. P. \u0026amp; Hammond, G. L. Human sex hormone-binding globulin gene expression in transgenic mice. \u003cem\u003eMolecular Endocrinology\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, (1998).\u003c/li\u003e\n\u003cli\u003evan Weerden, W. M., Bierings, H. G., Van Steenbrugge, G. J., De Jong, F. H. \u0026amp; Schr\u0026ouml;der, F. H. Adrenal glands of mouse and rat do not synthesize androgens. \u003cem\u003eLife Sci\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, (1992).\u003c/li\u003e\n\u003cli\u003eNilsson, M. E. \u003cem\u003eet al.\u003c/em\u003e Measurement of a comprehensive sex steroid profile in rodent serum by high-sensitive gas chromatography-tandem mass spectrometry. \u003cem\u003eEndocrinology (United States)\u003c/em\u003e \u003cstrong\u003e156\u003c/strong\u003e, (2015).\u003c/li\u003e\n\u003cli\u003eBeery, A. K. \u0026amp; Zucker, I. Sex bias in neuroscience and biomedical research. \u003cem\u003eNeuroscience and Biobehavioral Reviews\u003c/em\u003e vol. 35 Preprint at https://doi.org/10.1016/j.neubiorev.2010.07.002 (2011).\u003c/li\u003e\n\u003cli\u003eZheng, D. \u003cem\u003eet al.\u003c/em\u003e Sexual dimorphism in the incidence of human cancers. \u003cem\u003eBMC Cancer\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eClocchiatti, A., Cora, E., Zhang, Y. \u0026amp; Dotto, G. P. Sexual dimorphism in cancer. \u003cem\u003eNature Reviews Cancer\u003c/em\u003e vol. 16 330\u0026ndash;339 Preprint at https://doi.org/10.1038/nrc.2016.30 (2016).\u003c/li\u003e\n\u003cli\u003eRosner, W., Hankinson, S. E., Sluss, P. M., Vesper, H. W. \u0026amp; Wierman, M. E. Challenges to the measurement of estradiol: An endocrine society position statement. \u003cem\u003eJournal of Clinical Endocrinology and Metabolism\u003c/em\u003e \u003cstrong\u003e98\u003c/strong\u003e, (2013).\u003c/li\u003e\n\u003cli\u003eFolkerd, E. J., L\u0026oslash;nning, P. E. \u0026amp; Dowsett, M. Interpreting plasma estrogen levels in breast cancer: Caution needed. \u003cem\u003eJournal of Clinical Oncology\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eKarashima, S. \u0026amp; Osaka, I. Rapidity and Precision of Steroid Hormone Measurement. \u003cem\u003eJournal of Clinical Medicine\u003c/em\u003e vol. 11 Preprint at https://doi.org/10.3390/jcm11040956 (2022).\u003c/li\u003e\n\u003cli\u003eLaszlo, C. F. \u003cem\u003eet al.\u003c/em\u003e A high resolution LC\u0026ndash;MS targeted method for the concomitant analysis of 11 contraceptive progestins and 4 steroids. \u003cem\u003eJ Pharm Biomed Anal\u003c/em\u003e \u003cstrong\u003e175\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eCagnet, S. \u003cem\u003eet al.\u003c/em\u003e Oestrogen receptor \u0026alpha; AF-1 and AF-2 domains have cell population-specific functions in the mammary epithelium. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, (2018).\u003c/li\u003e\n\u003cli\u003eKe, Y., Bertin, J., Gonthier, R., Simard, J. N. \u0026amp; Labrie, F. A sensitive, simple and robust LC-MS/MS method for the simultaneous quantification of seven androgen- and estrogen-related steroids in postmenopausal serum. \u003cem\u003eJournal of Steroid Biochemistry and Molecular Biology\u003c/em\u003e \u003cstrong\u003e144\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eNelson, R. E., Grebe, S. K., O\u0026rsquo;Kane, D. J. \u0026amp; Singh, R. J. Liquid Chromatography - Tandem Mass Spectrometry Assay for Simultaneous Measurement of Estradiol and Estrone in Human Plasma. \u003cem\u003eClin Chem\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, (2004).\u003c/li\u003e\n\u003cli\u003eVitku, J. \u003cem\u003eet al.\u003c/em\u003e Derivatized versus non-derivatized LC-MS/MS techniques for the analysis of estrogens and estrogen-like endocrine disruptors in human plasma. \u003cem\u003eEcotoxicol Environ Saf\u003c/em\u003e \u003cstrong\u003e260\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eWood, G. A., Fata, J. E., Watson, K. L. M. \u0026amp; Khokha, R. Circulating hormones and estrous stage predict cellular and stromal remodeling in murine uterus. \u003cem\u003eReproduction\u003c/em\u003e \u003cstrong\u003e133\u003c/strong\u003e, (2007).\u003c/li\u003e\n\u003cli\u003eToran-Allerand, C. D., Tinnikov, A. A., Singh, R. J. \u0026amp; Nethrapalli, I. S. 17 alpha-estradiol: A brain-active estrogen? \u003cem\u003eEndocrinology\u003c/em\u003e vol. 146 Preprint at (2005).\u003c/li\u003e\n\u003cli\u003eSims, N. A. \u003cem\u003eet al.\u003c/em\u003e Deletion of estrogen receptors reveals a regulatory role for estrogen receptors-\u0026beta; in bone remodeling in females but not in males. \u003cem\u003eBone\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, (2002).\u003c/li\u003e\n\u003cli\u003eLindberg, M. K. \u003cem\u003eet al.\u003c/em\u003e Estrogen receptor specificity in the regulation of the skeleton in female mice. \u003cem\u003eJournal of Endocrinology\u003c/em\u003e \u003cstrong\u003e171\u003c/strong\u003e, (2001).\u003c/li\u003e\n\u003cli\u003eCaldwell, A. S. L. \u003cem\u003eet al.\u003c/em\u003e Characterization of reproductive, metabolic, and endocrine features of polycystic ovary syndrome in female hyperandrogenic mouse models. \u003cem\u003eEndocrinology\u003c/em\u003e \u003cstrong\u003e155\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eKratz, A., Ferraro, M., Sluss, P. M. \u0026amp; Lewandrowski, K. B. Normal Reference Laboratory Values. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e \u003cstrong\u003e351\u003c/strong\u003e, (2004).\u003c/li\u003e\n\u003cli\u003eVerdonk, S. J. E. \u003cem\u003eet al.\u003c/em\u003e Estradiol reference intervals in women during the menstrual cycle, postmenopausal women and men using an LC-MS/MS method. \u003cem\u003eClinica Chimica Acta\u003c/em\u003e \u003cstrong\u003e495\u003c/strong\u003e, (2019).\u003c/li\u003e\n\u003cli\u003eStricker, R. \u003cem\u003eet al.\u003c/em\u003e Establishment of detailed reference values for luteinizing hormone, follicle stimulating hormone, estradiol, and progesterone during different phases of the menstrual cycle on the Abbott ARCHITECT\u0026reg; analyzer. \u003cem\u003eClin Chem Lab Med\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, (2006).\u003c/li\u003e\n\u003cli\u003ede Wit, A. E. \u003cem\u003eet al.\u003c/em\u003e Plasma androgens and the presence and course of depression in a large cohort of women. \u003cem\u003eTransl Psychiatry\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003cli\u003eKyriakopoulou, L. \u003cem\u003eet al.\u003c/em\u003e A sensitive and rapid mass spectrometric method for the simultaneous measurement of eight steroid hormones and CALIPER pediatric reference intervals. \u003cem\u003eClin Biochem\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, (2013).\u003c/li\u003e\n\u003cli\u003eWooding, K. M. \u003cem\u003eet al.\u003c/em\u003e Measurement of estradiol, estrone, and testosterone in postmenopausal human serum by isotope dilution liquid chromatography tandem mass spectrometry without derivatization. \u003cem\u003eSteroids\u003c/em\u003e \u003cstrong\u003e96\u003c/strong\u003e, (2015).\u003c/li\u003e\n\u003cli\u003eFaqehi, A. M. M. \u003cem\u003eet al.\u003c/em\u003e Derivatization of estrogens enhances specificity and sensitivity of analysis of human plasma and serum by liquid chromatography tandem mass spectrometry. \u003cem\u003eTalanta\u003c/em\u003e \u003cstrong\u003e151\u003c/strong\u003e, (2016).\u003c/li\u003e\n\u003cli\u003eLi, X. \u0026amp; Franke, A. A. Improved profiling of estrogen metabolites by orbitrap LC/MS. \u003cem\u003eSteroids\u003c/em\u003e (2015) doi:10.1016/j.steroids.2014.12.005.\u003c/li\u003e\n\u003cli\u003eKalra, S. P. \u0026amp; Kalra, P. S. Temporal interrelationships among circulating levels of estradiol, progesterone and LH during the rat estrous cycle: effects of exogenous progesterone. \u003cem\u003eEndocrinology\u003c/em\u003e \u003cstrong\u003e95\u003c/strong\u003e, (1974).\u003c/li\u003e\n\u003cli\u003eDenver, N., Khan, S., Homer, N. Z. M., MacLean, M. R. \u0026amp; Andrew, R. Current strategies for quantification of estrogens in clinical research. \u003cem\u003eJournal of Steroid Biochemistry and Molecular Biology\u003c/em\u003e vol. 192 Preprint at https://doi.org/10.1016/j.jsbmb.2019.04.022 (2019).\u003c/li\u003e\n\u003cli\u003eShifren, J. L. \u003cem\u003eet al.\u003c/em\u003e Transdermal Testosterone Treatment in Women with Impaired Sexual Function after Oophorectomy. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e \u003cstrong\u003e343\u003c/strong\u003e, (2000).\u003c/li\u003e\n\u003cli\u003eFlores, A. \u003cem\u003eet al.\u003c/em\u003e The acute effects of bilateral ovariectomy or adrenalectomy on progesterone, testosterone and estradiol serum levels depend on the surgical approach and the day of the estrous cycle when they are performed. \u003cem\u003eReproductive Biology and Endocrinology\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, (2008).\u003c/li\u003e\n\u003cli\u003eQureshi, R. \u003cem\u003eet al.\u003c/em\u003e The Major Pre- and Postmenopausal Estrogens Play Opposing Roles in Obesity-Driven Mammary Inflammation and Breast Cancer Development. \u003cem\u003eCell Metab\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, (2020).\u003c/li\u003e\n\u003cli\u003eShaw, N. D. \u003cem\u003eet al.\u003c/em\u003e Estrogen negative feedback on gonadotropin secretion: Evidence for a direct pituitary effect in women. \u003cem\u003eJournal of Clinical Endocrinology and Metabolism\u003c/em\u003e \u003cstrong\u003e95\u003c/strong\u003e, (2010).\u003c/li\u003e\n\u003cli\u003eGlidewell-Kenney, C. \u003cem\u003eet al.\u003c/em\u003e Nonclassical estrogen receptor \u0026alpha; signaling mediates negative feedback in the female mouse reproductive axis. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e \u003cstrong\u003e104\u003c/strong\u003e, (2007).\u003c/li\u003e\n\u003cli\u003eKnedla, A. \u003cem\u003eet al.\u003c/em\u003e The therapeutic use of osmotic minipumps in the severe combined immunodeficiency (SCID) mouse model for rheumatoid arthritis. \u003cem\u003eAnn Rheum Dis\u003c/em\u003e \u003cstrong\u003e68\u003c/strong\u003e, (2009).\u003c/li\u003e\n\u003cli\u003eTan, T., Watts, S. W. \u0026amp; Davis, R. P. Drug delivery: Enabling technology for drug discovery and development. iPRECIO\u0026reg; Micro Infusion Pump: programmable, refillable, and implantable. \u003cem\u003eFront Pharmacol\u003c/em\u003e \u003cstrong\u003eJUL\u003c/strong\u003e, (2011).\u003c/li\u003e\n\u003cli\u003eItzhaki, E. \u003cem\u003eet al.\u003c/em\u003e Tumor-Targeted Poly(ArgGlyAsp) Nanocapsules for Personalized Cancer Therapy \u0026ndash; In Vivo Study. \u003cem\u003eAdv Ther (Weinh)\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eMoskovits, N. \u003cem\u003eet al.\u003c/em\u003e Palbociclib in combination with sunitinib exerts a synergistic anti-cancer effect in patient-derived xenograft models of various human cancers types. \u003cem\u003eCancer Lett\u003c/em\u003e \u003cstrong\u003e536\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Women's Health](https://www.nature.com/npjwomenshealth/)","snPcode":"44294","submissionUrl":"https://submission.springernature.com/new-submission/44294/3","title":"npj Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4808879/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4808879/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo improve on the quality of preclinical studies and their clinical translatability, patient-derived xenograft (PDX) models are increasingly used because they reflect inter- and intra-patient heterogeneity as well as human-specific tumor cell characteristics. However, the endocrine milieu of human patients, which affects grafted tumor cells may differ from mice. This is a growing concern as evidence of sex-specific biology in cancer has accumulated and an increase in the incidence of endocrine-related cancers has been observed highlighting the need to correctly reflect the hormonal milieu in PDX models. Here, we address the need to better model different female endocrine milieus in xenograft studies. Using an improved Liquid Chromatography-Mass Spectrometry (LC-MS) protocol for concomitant analysis of four different ovarian steroids in low volume plasma samples, we show that female mice of \u003cem\u003eNOD.Cg-Prkdc\u003c/em\u003e\u003csup\u003e\u003cem\u003escid\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eIl2rg\u003c/em\u003e\u003csup\u003e\u003cem\u003etm1Wjl\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/SzJ (NSG)\u003c/em\u003e strain frequently used for xenografts have 17-β-estradiol (E2) and testosterone (T) levels comparable to widely used \u003cem\u003eC57Bl6\u003c/em\u003e strain but higher progesterone (P4) levels. While \u003cem\u003eNSG\u003c/em\u003e E2 levels are comparable, T levels are lower and P4 levels higher compared to those observed in menopausal women. Following ovariectomy, T levels increase to those found in postmenopausal women. Subcutaneous implantation of E2 and combined E2 and P4 silicon pellets mimic ovarian hormone levels of premenopausal women in follicular and luteal phase of the menstrual cycle. Thus, straightforward procedures can effectively humanize the endocrine environment of experimental animals and improve physiologic relevance in women\u0026rsquo;s health-related research.\u003c/p\u003e","manuscriptTitle":"Humanizing the endocrine milieu of female mice for women’s health-related studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-10 20:48:38","doi":"10.21203/rs.3.rs-4808879/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-11T07:33:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-07T19:04:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88004566320455008419735897538852570757","date":"2024-08-23T17:39:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-23T16:09:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259620396799443369540235437104687110117","date":"2024-08-09T14:37:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-09T07:15:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-09T02:36:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-05T10:33:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Women's Health","date":"2024-07-26T14:45:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Women's Health](https://www.nature.com/npjwomenshealth/)","snPcode":"44294","submissionUrl":"https://submission.springernature.com/new-submission/44294/3","title":"npj Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e96d5da2-56c9-4a2b-8836-ffaa5b7b95d2","owner":[],"postedDate":"September 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":36729280,"name":"Health sciences/Diseases/Cancer"},{"id":36729281,"name":"Biological sciences/Physiology"},{"id":36729282,"name":"Health sciences/Diseases"},{"id":36729283,"name":"Biological sciences/Cancer"},{"id":36729284,"name":"Biological sciences/Cancer/Gynaecological cancer"}],"tags":[],"updatedAt":"2025-01-30T20:23:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-10 20:48:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4808879","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4808879","identity":"rs-4808879","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}