Glioblastoma multiforme is a malignant primary brain tumor with a poor prognosis and high rates of chemo-radiotherapy failure, mainly due to a small cell fraction with stem-like properties (GSCs). The mechanisms underlying GSC response to radiation need to be elucidated to enhance sensitivity to treatments and to develop new therapeutic strategies. In a previous study, two GSC lines, named line #1 and line #83, responded differently to carbon ions and photon beams, with the differences likely attributable to their own different metabolic fingerprint rather than to radiation type. Data from the literature showed the capability of RHPS4, a G-quadruplex stabilizing ligand, to sensitize the glioblastoma radioresistant U251MG cells to X-rays. The combined metabolic effect of ligand #190, a new RHPS4-derivative showing reduced cardiotoxicity, and a photon beam has been monitored by magnetic resonance (MR) spectroscopy for the two GSC lines, #1 and #83, to reveal whether a synergistic response occurs. MR spectra from both lines were affected by single and combined treatments, but the variations of the analysed metabolites were statistically significant mainly in line #1, without synergistic effects due to combination. The multivariate analysis of ten metabolites shows a separation between control and treated samples in line #1 regardless of treatment type, while separation was not detected in line #83. Glioblastoma (GBM) is the most lethal primary brain tumor and is associated with a median overall survival of 14 months. It inevitably recurs, even after surgical resection followed by intensive chemo-radiation therapy ,3,4. To 8).In a previous paper , it has To gain greater insight into the synergistic effects of radiation and G4-ligands, we performed a metabolomic analysis with MR spectroscopy (MRS) to study changes occurring after GSC treatment with one of the RHPS4 analogues, namely, Ligand #190, and photon beam irradiation. Improved knowledge of the metabolism of brain tumors after chemo-radiotherapeutic treatment may contribute to the discovery of new diagnostic or prognostic biomarkers. In particular, metabolic reprogramming is a hallmark of GSCs  used to GSC lines #1 and #83 have been selected from a panel of patient-derived GSCs on the basis of their biological, metabolic, and genetic characteristics ,32,33,34The synergistic effect of radiation and ligand #190 has been tested through MRS experiments at different times after ligand treatment and photon irradiation at 20 Gy; three different treatment conditions  were compared with the controls. Cell survival in these different conditions was also evaluated.8, namely, ligand #190, was prepared according to the synthetic protocols outlined in 2–6 to improve the global yields of the single steps, as described in the The target compound 8, we performed a primary ammine acylation of 6 and subsequent methylation of 7, following a known protocol not already reported in the literature, on our substrate. In brief, 2-amino-4-nitroaniline is first subjected to a nucleophilic substitution conducted in methanol treated with 9-chloroacridine 1 over 30 min. The mixture was refluxed for 90 min, cooled, and the product was precipitated with diethyl ether. Product 3 was obtained after a nitrosation of 2 with NaNO2 in HCl, and it was subsequently thermalized in Triglyme, reaching compound 4. The methylation of 4 with NaH and dimethyl sulfate yielded 8-methyl-2-nitroquinoacridine 5, which was then reduced to the corresponding amine 6 with stannous chloride in concentrated hydrochloric acid, after which the mixture was stirred at room temperature for 5 days. Then, to obtain the final product, we performed an acylation of 6 with the cyclopropanecarbonyl chloride, gaining the amide 7, which was then heated with an excess of methyl iodide for 4 days at 150 °C in a pressure tube to obtain 8 (ligand #190) with a high yield  was observed late after the different treatments in the spectra of line #1, while this signal intensity showed a fluctuant behaviour in spectra of line #83.Mobile lipid (ML) signals at 1.28 ppm and 0.89 ppm from the spectra of both cell lines are affected by the treatments, even if to differing extents. An increase of 2D A peak intensity  signal is clearly observable in line #1 cell spectra while it is slightly above the detection threshold in cell #83 spectra B,B’. TreThe signals of GSH, Gln, and Glu were influenced in line #1 and line #83 after treatments, though to a different extent . InteresFinally, an unsupervised hierarchical analysis was performed with a metabolomics approach for both lines for the 10 metabolic parameters from 2D spectra Line #83 was only slightly affected by irradiation, as previously observed in Palma et al. . Ligand (ii)Line #1 cells showed a slowdown in growth after the combined treatments with radiation and ligand #190. Cell growth was mainly slowed down by the action of the ligand, while the combined treatment gave only a moderate synergistic effect;(iii)MRS experiments on the two cell lines showed significant effects on several metabolites, mainly on lipid signals.Metabolomics may help in clarifying stem cell fate and reprogramming function ,44. In tLipid metabolism is abnormally regulated in gliomas compared to normal cells. GBM tumors accumulate more fatty acids than the surrounding normal brain ,47. ThesFrom the MR spectra of the two cell lines, we observed that the mobile lipid content of control samples present in cytoplasmic droplets is quite different from the cell lines and is also differently influenced by treatments, i.e., radiation . In factMetabolic alterations have long been regarded as a hallmark of cancer cells; however, contradictory results have been reported for GSCs, suggesting metabolic plasticity, especially concerning mitochondria and energetic metabolism . Recent Glutamine (Gln)-high GSCs metabolize more glutamine to sustain mitochondrial respiration, and the reduction of glutamine can weaken their ability to enhance cell proliferation and self-renewal. Our study on genetic and metabolic profiles distinguished two clusters of GSCs, GSf-like and GSr-like ,34. CellIt is known that GBM tissue shows a higher glutamine level than the surrounding normal brain and that the ability to metabolize glutamine is critical for GBM proliferation and survival . In cellGlu is often synthesized from glutamine by the enzyme glutaminase or from oxidative deamination. Its synthesis and degradation are part of the glutamate/glutamine cycle. Due to its role as a neurotransmitter, Glu is constantly released from neurons and its uptake by astrocytes at the neuronal synapse is essential for maintaining normal brain function ,66. AfteMolecular changes in the GSH antioxidant system and remolding in GSH homeostasis have been implicated in tumor initiation, progression, and treatment response because of both protective and pathogenic roles of GSH. Although in healthy cells it is crucial for the removal and detoxification of carcinogens, elevated GSH levels in tumor cells are associated with tumor progression and increased resistance to chemotherapeutic drugs. Recently, several novel therapies have been developed to target the GSH antioxidant system in tumors .GSH deficiency or a change in the GSH/GSSG ratio increases the vulnerability of cells to oxidative stress, inflammation, and tumor progression. However, elevated GSH levels increase antioxidant capacity and resistance to oxidative stress, as is evident in many tumors . It has As for GSH, signal intensities in spectra from line #83 are not affected by treatments, thus suggesting that GSH is not a key metabolite in protecting cells from treatment; other mechanisms have to be invoked probably due to the high heterogeneity of line #83 and cell lines belonging to the mesenchymal cluster. In addition, GSH levels in line #83 are low and do not seem to be relevant for cell protection.  On the cMyo-I is one of the most abundant metabolites in the human brain, and is located mainly in glial cells and functions as an osmolyte. Myo-I concentration is high in many brain disorders, including Alzheimer’s disease and in a variety of pathological conditions that involve astrocytic proliferation ,71. The As far as NAA is concerned, the literature reports that NAA levels decreased in GBM compared to normal brains and that NAA is a marker of the neuronal phenotype. Different levels of NAA were observed in GSCs associated with different metabolic and genomic signatures ,44. In mAn unsupervised statistical analysis of 10 metabolites , made with a metabolomic approach, showed different groupings for the two cell lines. In line #1, controls are grouped in a different cluster compared to their treated counterparts , while for line #83 cells, no cluster separation was observed.In conclusion, in both cell lines a possible synergistic interaction of combined treatments seems to be excluded. From the metabolic point of view only for a few metabolites was a synergistic effect between ligand treatment and radiation observed, but the complete statistical analysis does not confirm this synergy. These results confirm that the mesenchymal phenotype is more resistant to radiation and treatment with ligand #190 than the proneural phenotype. Specifically tailored therapies should be developed which take into account the high heterogeneity of GSCs as the use of combined treatments, such as those proposed in this paper, seem to fail. On the other hand, single treatment with G-quadruplex stabilizing ligand seems to induce alterations at the metabolic level in the two GSC lines, mainly in the proneural phenotype.® BEH C18 column . The following method was used: flow 1.4 mL/min, isocratic gradient over 2 min 95% of H2O + 0.1% TFA (5% CH3CN), gradually to 40% aqueous solvent over 6 min, then isocratic flow for 4 min (λ = 256 nm). UPLC-MS data were recorded using a surveyor UPLC system  equipped with a BEH Acquity UPLC column (1.7 μm) 2.1 × 50 mm, and an LCQ ADV MAX ion-trap mass spectrometer, with an ESI ion source. Chromatographic purification was conducted using ISOLERA-One, a Biotae Flash Purification system. Recordings of 1H-NMR spectra were made with a Bruker Avance 300 MHz  calibrated to the internal standard TMS or the residual solvent peak. All the products were characterized by ESI-MS and 1H-NMR. The synthetic procedure needed to obtain RHPS4 derivative is reported in detail in the All solvents and reagents were purchased from TCI and Sigma-Aldrich and used without further purification. HPLC analyses were performed using an Agilent system SERIES 1260  with an XBridgeGSCs were obtained from adult GBM patients (WHO grade IV) who had undergone complete or partial surgical resection at the Institute of Neurosurgery, Catholic University School of Medicine, Rome, Italy. Informed consent was obtained from the patients before surgery. The tumor tissues were mechanically dissociated and single-cell suspension cultured in a serum-free medium supplemented with epidermal growth factor and basic fibroblast growth factor, as previously described . The in 4 cells/mL. After 16 h, #190 was added to the cells. ATP levels were measured at different time points as a surrogate of cell viability using CellTiter-Glo™  according to the manufacturer’s instructions. The mean of the raw luminescence values from triplicate wells treated with vehicle alone (mLC) was used as a reference to interpolate percentage viability from wells treated with drugs (VD), using the following formula: VD = (LD/mLC) × 100 [For ligand #190 dose-response experiments, GSCs were mechanically dissociated and plated in 96-well plates at a density of 2 × 10C) × 100 .Maximal inhibitory concentration (IC50) and 25% inhibitory concentration (IC25) values were determined by a non-linear regression curve through the plotted experimental data and represent compound concentrations able to reduce cell proliferation by 50% and 25%, respectively.2 flasks at a density of 10 × 104 cells/mL in 50 mL total volume. Cells were the treated with 0.7 µM (line #1) and 0.75 µM (line #83) ligand #190 concentration (IC 25 for each line) for 48, 72, 96, and 120 h.For MRS and cell viability experiments, GSCs were seeded in T175 cm137Cs) gamma ray source  operating at a dose rate of 0.8 Gy/min (Istituto Superiore Sanità facility). A single radiation dose of 20 Gy was used, comparable to total doses delivered during radiation therapy in a fractionated regimen and to a single high dose used in special therapeutic modalities, such as intraoperative radiotherapy and stereotactic radiosurgery [For combined treatments see , cells wosurgery .2O and 2mM Sodium 3-(trimethylsilyl)propionate-2,2,3,3-d4 (TMSP) as a frequency standard. A 20 μL aliquot of the suspension was transferred into a 1 mm MR tube and centrifuged to obtain a packed cell volume, as previously described [Cells were washed in phospate buffered saline (PBS)  without calcium and magnesium at pH 7.4 and centrifuged at 162 rcf for 3 min. The pellet was resuspended in PBS with 20% Described . All MRS1H MRS experiments were run on a digital Bruker Avance spectrometer  at 400.14 MHz equipped with a 1mm microprobe. Both one-dimensional (1D) and two-dimensional correlation spectroscopy (2D COSY) experiments were performed, at T = 298 K.1H MRS spectra of GSCs and culture media were acquired with a 90° RF pulse, the number of scans (ns) was equal to 1000  for cell spectra. 2D COSY spectra were acquired with a 90°-t1–90°-t2 pulse sequence and ns = 32 for cell or ns = 128 for culture media samples. Spectra were acquired as a matrix of 512 × 128 data points in time domain.1D MRS parameters were obtained in at least three independent experiments and data expressed as mean ± standard deviation (SD) values. WINNMR software  was used to perform 1D signal deconvolution and 2D cross peak integration, as reported in . A macrot-test were performed utilizing Past 4.03 Software, version 2020 [Unsupervised agglomerative hierarchical clustering, principal component analysis and Student’s ion 2020 .


Metabolic and personalized interventions in cancer treatment require a better understanding of the relationship between the induction of cell death and metabolism. Consequently, we treated three primary liver cancer cell lines with two anthracyclins (doxorubicin and idarubin) and studied the changes in the lipidome. We found that both anthracyclins in the three cell lines increased the levels of polyunsaturated fatty acids (PUFAs) and alkylacylglycerophosphoethanolamines (etherPEs) with PUFAs. As PUFAs and alkylacylglycerophospholipids with PUFAs are fundamental in lipid peroxidation during ferroptotic cell death, our results suggest supplementation with PUFAs and/or etherPEs with PUFAs as a potential general adjuvant of anthracyclins. In contrast, neither the markers of de novo lipogenesis nor cholesterol lipids presented the same trend in all cell lines and treatments. In agreement with previous research, this suggests that modulation of the metabolism of cholesterol could be considered a specific adjuvant of anthracyclins depending on the type of tumor and the individual. Finally, in agreement with previous research, we found a relationship across the different cell types between: (i) the change in endoplasmic reticulum (ER) stress, and (ii) the imbalance between PUFAs and cholesterol and saturated lipids. In the light of previous research, this imbalance partially explains the sensitivity to anthracyclins of the different cells. In conclusion, our results suggest that the modulation of different lipid metabolic pathways may be considered for generalized and personalized metabochemotherapies. All cancers are characterized by an inherent metabolic reprograming that promotes tumorigenesis by facilitating and enabling proliferation, metastasis, and resistance to therapies ,2. ThereClinicians have used anthracyclins, such as doxorubicin (DOX) and idarubicin (IDA), as chemotherapeutic agents for more than five decades. Anthracyclins intercalate into the nucleus and mitochondrial DNA and subsequently inhibit the synthesis of proteins and affect the redox state of the cell. Anthracyclins also act on the mitochondrial electron transport and convert oxygen into reactive oxygen species that may cause mitochondrial dysfunction, change the redox state, and induce lipid peroxidation . HoweverCurrently, there are few studies about the effect of DOX on the lipidome of cancer cells and even less on the effect of other anthracyclins. In addition, different studies have reported that lipidic modulation affects ER stress, cell death, and cardiotoxicity induced by anthracyclins ,13,14. C® HB-8065™, SNU 449 ATCC® CRL-2234™, and Huh7 from Dilruba Ahmed, Karolinska Institute, Stockholm, Sweden) were cultured at 37 °C with 5% CO2 and 95% humidity within a CO2 incubator. HepG2 and Huh7 were cultured in GlutaMAX™ supplemented, high glucose DMEM  supplemented with 1% antibiotic antimycotic solution  and 10% fetal bovine serum (FBS)  (cell culture media + FBS: CCMFed). SNU449 was cultured in GlutaMAX™ supplemented, RPMI  medium supplemented with 1% antibiotic antimycotic solution and 10% FBS (cell culture media + FBS: CCMFed). Standard culture medium without supplemented FBS was used during starvation (CCMSM). Misidentification of all cell lines was checked at the Register of Misidentified Cell Lines . In. In33]. Here, we show that anthracyclins elicit the upregulation of PUFAs and etherPEs with PUFAs in different primary liver cancer cells. By using DOX and IDA in three different cell lines, we present new evidence that this is a general effect of anthracyclins on the metabolism of cancer cells. We also present evidence that the regulation of cholesterol lipids and de novo lipogenesis by anthracyclins is cell type-dependent for three different cell lines of primary liver cancer. As etherPEs with PUFAs are involved in programmed cell death by ferroptosis  and statLXRs and SREBPs control the expression of the enzymes responsible for the de novo lipogenesis of fatty acids, glycerolipids, and cholesterol . The incConsidering our results and previous research together, we conclude that the up- or downregulation of the LXR/SREBP-mediated de novo lipogenesis of fatty acids, glycerolipids, and cholesterol was not a general effect of anthracyclins. Nevertheless, as we saw different regulations for three different lines of the same type of cancer, it could depend on the cell type, tumor, or even individual genotypes and phenotypes.The synthesis of etherGLs is initiated in the peroxisome and completed in the ER, where the activity of alcohol reductase FAR1 is the limiting step  40,41,4,441,42. The levels of free PUFAs could be increased by three different factors: (i) the increase in their synthesis by elongation and desaturation of essential linoleic and linolenic acids ; (ii) thWe conclude that the observation of the ensemble of free PUFAs and glycerolipids with PUFAs suggests the upregulation of the elongation and desaturation of linoleic and linolenic acids as responsible for the increase in free PUFAs and etherPEs with PUFAs .Regarding cell death by anthracyclins, PUFAs and etherGLs with PUFAs have been associated with lipid peroxidation and ferroptosis ,50,51,52In the context of lipid peroxidation and ferroptosis, first, our analysis about the regulation of PUFAs indicates that their increase was due to the upregulation of elongation and desaturation . In thisSecond, we found a general increase in etherPEs with PUFAs. It is known that: (i) glycerophospholipids of ethanolamine with PUFAs are necessary for ferroptosis ; and  of cell death.In conclusion, the behavior of the lipidome in the three cell lines suggests that: (i) PUFAs or PUFA-containing lipids may potentiate the effect of anthracyclins in a general way, and (ii) statins may potentiate or attenuate the effect of anthracyclins in a cancer/patient-specific way. Further research in animal models and patients is warranted to establish the possibility of transferring these observations from bench to bedside.


Breast cancers characterized by expression of estrogen receptor-alpha  represent approximately 70% of all new cases and comprise the largest molecular subtype of this disease. Despite this high prevalence, the number of adequate experimental models of ER+ breast cancer is relatively limited. Nonetheless, these models have proved very useful in advancing understanding of how cells respond to and resist endocrine therapies, and how the ER acts as a transcription factor to regulate cell fate signaling. We discuss the primary experimental models of ER+ breast cancer including 2D and 3D cultures of established cell lines, cell line- and patient-derived xenografts, and chemically induced rodent models, with a consideration of their respective general strengths and limitations. What can and cannot be learned easily from these models is also discussed, and some observations on how these models may be used more effectively are provided. Overall, despite their limitations, the panel of models currently available has enabled major advances in the field, and these models remain central to the ability to study mechanisms of therapy action and resistance and for hypothesis testing that would otherwise be intractable or unethical in human subjects. Of the estimated > 280,000 breast cancer cases newly diagnosed in the United States annually, approximately 70% will express estrogen receptor alpha . For ER+ breast cancer patients, the recurrence risk after five years of adjuvant endocrine therapy currently ranges from ~40% (T2 N4-9 at diagnosis) to 10% (T1 N0),4. Many tumors that respond to an endocrine and/or cytotoxic therapy later recur as metastatic disease. Recurrent ER+ breast cancer is rarely cured. Interventions that interfere with ER activation have been available for over 120 years. Unfortunately, the inability of endocrine therapies to cure all ER+ breast cancers has also been a barrier to progress since the 1890s. Human breast cancer cells growing in vitro and as xenografts, chemically induced mammary tumors, and other animal models have been central to advancing our understanding of the endocrine responsiveness of ER+ breast cancer and to the development of drugs that are now in widespread use as standard of clinical care. In this review, we discuss several of the key issues associated with the use of these models in breast cancer research.Breast cancer is the most prevalent cancer and the second leading cause of cancer deaths after lung cancer in women, followed later by adrenalectomy and hypophysectomy. The first systemic intervention for ER+ breast cancer was high-dose estrogen administration, with cytotoxic chemotherapy beginning later. Unfortunately, ER+ breast cancers often exhibit a lower response rate to cytotoxic chemotherapy than other breast cancer subtypes,7. The first antiestrogen  was introduced in the early 1970s. TAM remains widely used in premenopausal women but has been supplanted by aromatase inhibitors as the first-line endocrine therapy for postmenopausal women. Differences in progression-free and disease-free survival currently favor the use of the aromatase inhibitors over TAM, as well as in the patterns of side effects, and they can help to direct an optimal therapy to individual patients. However, there is no compelling evidence of any major or widespread difference in overall survival rates between TAM, a partial ER agonist, and the aromatase inhibitors that block estradiol production,10.Early endocrine interventions for breast cancer patients included oophorectomy,11-13. Unfortunately, the optimal dosing of fulvestrant was not used in the initial clinical trials; 500 mg (not 250 mg) is now the standard dosing. Despite evidence of superiority over an aromatase inhibitor for overall survival,15, fulvestrant (500 mg) remains largely relegated to second-line therapy for postmenopausal patients. Fulvestrant requires injection as a depot that can be painful, whereas TAM and the aromatase inhibitors are given orally. It remains to be seen whether this pattern of use will persist long into the future, or whether aromatase inhibitors will be replaced by orally active ER antagonists, several of which are actively receiving clinical evaluation.The first advance beyond TAM in the context of an improvement in overall survival obtained from targeting ER was reported for the ER antagonist fulvestrant , which showed increased progression-free and overall survival activity and comparable quality of life benefit when compared with an aromatase inhibitor,17. While many CDK4/6 inhibitors are under investigation, only ribociclib  and abemaciclib (Verzenio®) in combination with an endocrine therapy have thus far shown any further increase in overall survival beyond that seen with single-agent endocrine therapy-20. The efficacy of histone deacetylase inhibitors (HDAC) in combination with endocrine therapy is also being investigated in at least 14 ongoing clinical trials, although these regimens also have shown only modest improvements in clinical benefit. Despite these advances and the notable improvements in disease-free and progression-free survival for patients with ER+ breast cancer, many patients experience distant recurrence that is eventually fatal. Clearly, there is much room for improvement. Among the most pressing issues is acquiring a greater understanding of endocrine resistance, whether de novo (some ER+ tumors never respond to an endocrine intervention) or acquired resistance (many ER+ breast cancers recur decades after an apparently successful treatment). Experimental models, both in vitro and in vivo, are likely to remain central tools in experimental approaches to acquiring this new knowledge.Most recently, combinations of an endocrine therapy (aromatase inhibitor or fulvestrant) with a CDK4/6 inhibitor have shown a significant improvement in clinical benefit relative to single agent endocrine therapy-24. All such models have limitations. The paraphrased aphorism that “All models are wrong but some models are useful”, attributed to the British statistician George E.P. Box (1919-2013), is not restricted to statistical models and is clearly also applicable to experimental models of ER+ breast cancer, as we explore in this review. The determination of which model(s) is sufficiently “useful” and which model(s) is not, along with how best these models can be used, is not necessarily trivial. Making an accurate determination is largely, but not exclusively, an issue of understanding the characteristics of the experimental model well enough to know if it is capable of allowing the investigator to test their hypothesis in a meaningful and objectively interpretable manner when used with an appropriate experimental design. Thus, the choice of model must be guided by its ability to address the question(s) at hand, rather than forcing a question upon an inadequate or inappropriate experimental model. An otherwise appropriately designed experiment forced upon a poor experimental model can produce data that may meet the expectations of the investigator yet could be misleading. Some features of this choice may be reasonably clear - testing a new antiestrogen in ER− models would be a poor choice. However, the converse assumption that testing a new endocrine intervention in any ER+ model is correct may depend on the presence or absence of ESR1 mutations (which can affect response to aromatase inhibitors), ESR2 (which can affect activity of ESR1), inherent sensitivity of the cell line selected to established antiestrogens, or other phenotypic or molecular characteristics. In this overly simple example, knowing which model(s) not to use is somewhat easier than knowing the best model(s) in which to test a new antiestrogen.Mechanism-based cancer research requires laboratory models of the human diseasein vitro and in vivo models available have generated many powerful insights. Not least among those contributions is research that supported the repurposing of the failed contraceptive TAM into one of the most successful anticancer agents for any cancer, the first molecularly targeted antineoplastic agent and the first United States FDA-approved cancer chemopreventive drug-29. Indeed, the cytotoxic, endocrine, and immunologic agents that are now used as standard of clinical care for breast cancer patients each showed safety and activity in cell culture and/or animal models at some point in their preclinical development. In this regard, the biological properties of the models appear to have been adequate to the task of early drug evaluation, despite any other cellular, genetic, and/or molecular differences among these models and apparently otherwise comparable human breast tumors.Good experimental models of ER+, endocrine-responsive breast cancer are relatively few, despite being derived from the most prevalent breast cancer subtype. Nonetheless, for many studies, whether for initial drug screening, molecular modeling, or biomarker discovery, the In vitro studies are perhaps most commonly used when there are technical or ethical reasons that the studies cannot be done in either animals or humans. For example, drug screening or mechanistic studies that may require gene knockdown, knockout, or cDNA overexpression are often best done first in vitro. Such studies can allow for multiple genetic modifications and determine their effects on responsiveness to drugs, molecular signaling, or other experimental endpoints with relative technical ease, high throughput, and low cost. The costs in time and resources to generate multiple animal models with a comparable panel of genetic modifications, and multiple drug or treatment scheduling studies, can be prohibitive. Nonetheless, preclinical animal studies are often still necessary, e.g., to support advancing a candidate drug to a first-in-human analysis. Such in vivo studies are generally left until sufficient data from appropriate in vitro experiments are available to constrain the scope and guide the design of any necessary in vivo experimentation. Importantly, this approach is also ethically sound because it can greatly limit the number of vertebrate animals required to test a more directed hypothesis.,31. For example, cellular and molecular heterogeneity are rarely synonymous. In most cell populations, some cells will be in G0 while others in G1, S, G2, or the M phase of the cell cycle, with features of their respective transcriptomes, proteomes, and metabolomes expressed differentially. If treated with a cell cycle-dependent drug, some cells will appear sensitive and some resistant. These observations provide simple examples of molecular and drug response heterogeneity in a cell population that otherwise appears to exhibit cellular homogeneity. An often-overlooked advantage of cell culture models, at least for testing some hypotheses, is their relative cellular homogeneity when compared with the mixed cell populations seen in some patient-derived xenograft (PDX) models. Relative homogeneity can reduce noise in some experimental designs or readouts. However, the type of heterogeneity can be an important factorin vitro that may (or may not) be known to affect a relevant experimental outcome; (3) apparently poor correlations of specific genetic or other features with those evident in tissue samples from patients; (4) species differences ; or (5) lack of an appropriate tumor microenvironment or supporting structure for cell lines growing in 2D culture in vitro and to a lesser degree cell lines growing in 3D culture or as xenografts. The extent to which any or all of these limitations are correct, relevant, or applicable to any given study is usually hypothesis specific. We address several of these issues, in part, elsewhere in this review. Here, we briefly comment on one of the more important concerns - the rate of false positives associated with drug screening using in vitro and in vivo models.Perhaps the most common problems leveled at tumor cell lines and animal models include: (1) the high prevalence of false positives with respect to identifying agents that are effective in preclinical studies but later show limited activity in phase II or III clinical trials; (2) long-term adaptations to growth in vitro and in vivo experimental models are used as the first line of exploration. This use reflects, among several considerations, the low cost and high throughput when used, for example, for in vitro drug discovery studies. The false positive and false negative rates of current preclinical drug screening strategies are connected because, as one rate increases, the other rate will usually decrease. For hypothesis testing, investigators seek an appropriate balance in the false positive and false negative rates. For very early drug screening, a reasonable position to take is that a high false positive rate (which identifies as active some drugs that are inactive) is more acceptable than a high false negative rate (which identifies as inactive some drugs that are active). Where the most appropriate balance between false positive and false negative outcomes lies, or how this balance should be determined, is context specific and may be affected by factors unrelated to the hypothesis, such as cost, time, availability of resources, or other constraints. Later in drug development, where an agent is finally being tested in human subjects, the costs  often dictate a balance where the likelihood of a false discovery (whether positive or negative) is as low as possible.In most cases, in vitro models and xenografts may predict poorly for subsequent clinical activity. However, given the long and multistep process of drug development, which can exceed ten years, laying the failure of an agent in phase II or III clinical trials squarely at the feet of the experimental cell lines and animal models used in the earliest stages of this process may not be entirely warranted. It is not that more and better preclinical models and tools are not needed, as they most certainly are and especially for ER+ breast cancer. Rather, focusing in this area may detract from a more objective analysis to identify flaws in every step in the process that could have a major impact on the overall process. A notably challenging issue is why many drugs that meet the requirements for successful indication of safety and efficacy in phase I and II clinical trials fail to show comparable activity in phase III trials,32. New approaches in clinical study design, such as the use of phase 0 designs, window of opportunity trials for biomarker discovery, and/or a more effective use of data from regional/global populations, continue to emerge. These and other advances may yet change the standard workflows for screening and developing some agents and eventually improve the success rate for new drugs completing phase III clinical trials.There are many reasons -50. A key consideration is an objective and informed assessment of the limitations in these models and the application of appropriate experimental designs to hypotheses that can be tested adequately within these limitations. For example, relatively few ER+ models overexpress endogenous aromatase, thus transfection with the aromatase cDNA is more widely used to create cell line models for testing drugs for aromatase inhibition-51. Cell lines used in 2D/3D culture and as xenografts in immune-deficient rodents enable studies that are intractable in more complex models. For example, many studies in human subjects have both technical and ethical limitations. Studies in humans essentially use patients or subjects as the model, for example, patients enrolled in a clinical trial are used to predict outcomes for the population at large. Patient selection is analogous, at least in principle, to the choice of a cell line or animal model with respect to designing an experiment to test a specific hypothesis. Detailed mechanistic studies can also be difficult when there is a need to deliver a specific genetic or molecular perturbation to the cancer cell components of a PDX model tumor, and to do so with broadly comparable efficiency in all appropriate cells in the xenograft. Cell lines have limitations but have been widely proven to be appropriate models for multiple aspects of breast cancer researchin vitro and in vivo, and metastasize routinely and to the most clinically relevant sites when injected as standard mammary fat pad inoculations in the most widely used immune-compromised mouse strains. Hence, there are few parental models from which to derive isogenic models of endocrine resistance. Here, we use the commonly understood definition of isogenic as it relates to cell line variants, that is, cells known to be derived from a common parental population. This definition does not require that cells be extensively sequenced to show that they have identical  genomes, which would be largely irrelevant in many cancer cell models that can acquire multiple new genetic changes quickly relative to most normal cells. Indeed, genome instability is one of the accepted hallmarks of cancer,53. As noted below, measuring a few well-defined short tandem repeats (STR) is usually adequate to establish the genetic lineage of a cell line variant as being isogenic as the term is commonly understood.Relatively few human breast cancer cell lines or PDX models express a fully endocrine sensitive phenotype in that they are ER+ and/or PR+, sensitive to all endocrine therapies currently used as standard of care in the clinic, grow both For testing some hypotheses, the lack of a large, well-characterized series of appropriate ER+ models  is a limitation in the field. Since choices are limited, how well any current ER+ breast cancer model(s) reflects the most relevant aspect(s) of the human disease to the hypothesis being tested remains an important consideration.While it has become popular in some areas to criticize established cell lines as having limited clinical relevance, such criticism often lacks an objective assessment of precisely for which characteristics of the human disease cell lines are adequate models and for which they are clearly inadequate. An inherent assumption in several such comparisons is that a single cell line, or even a panel of similar cell lines, should be a “good” reflection of what is a highly heterogeneous tumor (intratumor variability) and a highly heterogeneous disease (intertumor variability within and among currently defined molecular subtypes). Hence, a cell line may be expected to reflect some general properties shared among all tumors in the subtype of the human disease that it is believed to represent. Whether this is a reasonable assumption as such comparisons have sometimes been constructed, often in the context of genomic or transcriptomic features, may be questionable. For example, what are the most appropriate general properties, how and why were these selected, and are these properties relevant to most hypotheses that could be tested in any given cell line? Not surprisingly, cellular heterogeneous PDX models can show a “better” correlation with more features of the human disease, but whether the use of PDX models can lead to fundamentally new insights that were not already known from established cell line models remains to be determined, as is discussed elsewhere in this review.in vitro, may be present only in a small or undefined subgroup of patients, artifactual and not present in any samples from breast cancer patients, and/or relevant or irrelevant to the hypothesis being tested.One limitation in these general approaches or comparisons of experimental models to the human disease is that one question that is rarely asked effectively is: how well does any random patient sample (or model derived therefrom) also reflect the same characteristic(s) of the patient population from which the sample was drawn? This is essentially asking how good is any human sample as a model of the human disease. Hence, it is often not well established whether any deviation an individual cell line exhibits from a predetermined feature(s) of a heterogeneous patient population with which it is compared is within the range present across a larger population or other broadly similar populations of breast cancers. Some features of a cell line, perhaps gained (or lost) as a consequence of prolonged culture ,43-45,47.Some predetermined features would (or likely should) not be present in an established cell line. For example, dynamic molecular features that are essentially a reflection of changing immune cell infiltration or the presence of stromal cells that are absent in established cell line cultures will not be represented in the cell line transcriptomes. Nonetheless, at some level, it is clear that data from established cell lines maintained in 2D cell culture can exhibit significant similarities to patient samples when matched to the appropriate breast cancer subtypein vitro models, has also been raised as a limitation of established cell line models growing in vitro in 2D. As with many other issues raised in this review, care should be taken in the context of such concerns. If the goal of the study is to explore the extrinsic effects of the tumor microenvironment, then these models will have significant limitations. However, for many experimental endpoints, the extrinsic signals from the microenvironment are received, interpreted, and executed by the intrinsic machinery of the cancer cell, whether these signals are initiated by drugs, growth factors, cytokines, or other molecules derived extrinsically. Moreover, many of the most important functions of cells, such as progressing through the cell cycle, obtaining energy from glucose, or executing apoptosis, are highly conserved - not simply between normal and cancer cells of the same species and tissue but often widely across tissues and species.The absence of a 3D culture matrix in 2D cultures, as well as of a complex extracellular tumor microenvironment in 2D or 3D . Consequently, if the external (extrinsic) signals are selected, such as a drug or growth factor exposure that affects proliferation or cell survival (sensed and executed by intrinsic functions), much can be learned correctly regarding the intrinsic features that the exposure modifies from the use of 2D and 3D cultures of established cell lines. Indeed, if a human breast cancer cell line or xenograft is considered a poor model for the reasons often advanced, as noted above, the questions then arise as to what can we hope to learn about human biology from studies in fish, flies, worms, or yeast and why have we already learned so much from the study of such organisms,56.The conservation of cellular and molecular features across different species is often referred to as evolutionary parsimony, and it can explain why studying processes in quite simple species including yeast, worms, or flies can greatly advance our understanding of what happens within human cellsFor many studies, the applicability of the experimental model(s) to the clinical disease is tested indirectly. For example, a biomarker or other molecular target is identified in experimental models and the strength of a correlation between the biomarker or target and a clinically meaningful event is determined in one or more patient populations. A positive outcome - a clear and compelling correlation being found - may be interpreted that both the experimental model and the predictions associated with the molecule were “correct” (assuming that neither could have arisen by chance). A negative outcome - no correlation being found - is more difficult to interpret. For example, a lack of correlation could be because the molecule was “wrong”  and/or because the experimental model was “wrong” (the model could never be able to identify a “correct” candidate in the context of the hypothesis being tested).Mycoplasma species and cross-contamination with other cell lines. Mycoplasma is a genus of bacteria that lacks a cell wall and is often considered the simplest form of bacteria. Unfortunately, many members of this genus are resistant to common antibiotics and can be difficult to eradicate from infected cultures. Moreover, unlike contamination with other bacteria and fungi, which often turn cell culture media turbid, cell line cultures can be infected with Mycoplasma and show no immediately obvious signs of this infection. Cross-contamination from other infected cell lines is common and cultures can also be infected by researchers, since Mycoplasma are common in the human respiratory tract. Hence, infection can be prevalent; over 70% of cultures have been reported as being infected in some studies. The consequences of Mycoplasma infection can be far reaching, from altering responsiveness to steroid hormones and gene expression profiles to affecting tumorigenicity of xenografts in immune-deficient hosts. Hence, results from in vitro studies with infected cells are often unreliable and/or misleading. Unlike respiratory tract Mycoplasma, the breast microbiota interacts with breast cancer cells and may therefore impact the effectiveness of endocrine therapies,60, an underexplored research area.Two common challenges to executing reproducible cell line studies are linked to quality control issues, specifically infection with Mycoplasma infections is often difficult, the most effective strategies are: (1) to obtain and work only with cultures known to be free of contamination; (2) routine testing of cell line stock and other cultures in the laboratory; (3) to practice effective aseptic technique during all manipulations that require retaining viable cells in culture; and (4) returning to validated cell culture stocks within a reasonably short period of time  to replicate experiments. Hence, cells should be obtained from reliable sources and tested as soon as they are brought into the laboratory, with frozen stocks created only from definitively Mycoplasma-free cultures. Fortunately, there are several excellent and cost-effective tools and services available to test for Mycoplasma contamination.Since eradication of Mycoplasma infection, such contamination may not be immediately obvious. The presence of other cell lines in a cancer cell culture is reflective of the presence of multiple cell types in the tumor microenvironment and may not be visible under the microscope, particularly if the cross-contamination is from another cell line of the same or a closely related cell of origin. In addition, similar to Mycoplasma infection, the basic growth or other characteristics of the culture may not initially appear altered, although a clear morphological change in cells is often a sign of gross cross-contamination. Data from cross-contaminated cell lines can also be unreliable and/or misleading. While the problem of cell line cross-contamination is also prevalent, there are simple methods to detect the presence of even relatively few foreign cells within a culture. For many years, the standard approach was to compare the cell line karyotype against that of the original cell line or other cultures. Reporting the karyotype of new cell lines or variants of existing lines, such as drug-resistant variants derived from a sensitive parental population, was common practice.Cross-contamination by other cell lines is also highly problematic. As with  and is the current best practice for ensuring the authenticity of cell lines and the absence of cross contamination with other cells. For example, in our hands, we analyzed 16 loci in the human genome through coamplification and multicolor detection of 15 STRs and amelogenin (gender identification) and established a genetic profile for MCF-7 cells and our MCF-7 derived cell lines  and from other sources,63. Fortunately, the four basic practices noted above to reduce the risk of Mycoplasma infection also reduce the risk of cell line cross-contamination. Regular authentication solves one other common and related problem, knowing that the cell line being used is not an entirely different cell line.More recently, measuring short tandem repeat (STR) patterns has proved to exhibit both high sensitivity and high specificityll lines  with a r,65. For example, 3D matrices can be prepared from ER+, human breast cancer-associated fibroblasts, or normal breast tissue (often obtained from reduction mammoplasties). During tumor progression, stromal fibroblasts can become reprogrammed to produce an extracellular matrix altered in both physical organization and physical composition. Changes include abundant collagen I, fibronectin, desmin, smooth muscle alpha-actin, TGF-β, a specific stromal isoform of the actin binding protein palladin, and other proteins that enhance tumor growth. Studies on cell invasion often use a 3D matrix to measure the ability of cells to traverse from one side of a collagen or other matrix to the other in a Boyden chamber, Transwell, or similar apparatus.Experimental design is too complicated to cover all possible issues here. However, a few generic observations may be helpful to some readers. Most cell culture studies are done with cells growing on a 2D plastic surface, an approach that has proven useful for many types of studies for several decades. For some studies, a 3D culture matrix can offer a more physiologically relevant experimental context. However, bioavailability can be different in vitro, where the concentration of serum may affect the concentration of drug available to act. Using appropriate statistical analyses to estimate IC50 and IC80 values from dose-response data can be useful and may adjust for inherent response differences among isogenic cell lines. Recently, a growth rate inhibition endpoint has been proposed that may be less sensitive to differences in the rates of cell division among cell lines used for drug sensitivity studies. Careful selections of the most appropriate cytotoxicity assay and a series of other technical and analytical parameters,70 are critical considerations. For example, cell density can affect the rate of cell proliferation. Seeding at different cell densities can be used as a simple means to alter the proliferation rate. However, for screening agents that may affect the cell population growth rate and/or cell cycle distribution, controlling for cell density - and thus also for the proliferative capacity of the population - is a key consideration. Many cytotoxic drugs are sensitive to the cell population growth rate and/or the proportion of actively cycling cells and can exhibit different dose-response relationships when cell populations are seeded at different densities and/or growing at different rates.For many drug testing studies, using a pharmacologically based dose-response method is important, as is careful consideration of several features of experimental designThe selection of cell culture media can also affect outcomes and can be particularly important for some metabolism studies. For example, the concentration of glucose in many cell culture medium formulations is much higher than that found in normal human serum. Historically, these high concentrations were used as a matter of convenience because cancer cell lines often metabolize glucose at a high rate and can expend the glucose available so quickly that daily medium replenishment may be required. Since glucose and other key nutrients including glutamine and pyruvate are often initially present in excess in cell culture media formulations, this can affect the apparent responsiveness to agents that affect these features of cellular metabolism. Often, metabolism studies measure changes in the kinetics of substrate-product reactions governed by mass action and so may be affected when a key substrate or product is present in significant excess.For many studies, investigators choose ER− cell lines as negative controls for ER+ cells. While often a reasonable choice, there are many cellular and molecular differences between ER− models and ER+ models than cannot be explained only by the presence or absence of functional ER. Hence, care is needed when interpreting differences between ER+ and ER− models. Additional controls that are often advisable or preferable include comparing the effects of an intervention, or a change in molecular signaling, in the presence and absence of 17β-estradiol in both estrogen responsive and unresponsive isogenic ER+ variants. Showing the ability of an effect to be blocked by an appropriate antiestrogen (often a SERD rather than a SERM) in such models and experimental designs or the loss of an effect with genetic knockdown of ER can be informative. The latter approach can be challenging because some ER+ models, whether estrogen-dependent or -independent, may not tolerate loss of ER expression for a prolonged time, at least in our hands.,72. These models exhibit phenotypes, genomes, methylomes, and transcriptomes that simulate many key features of ER+ human breast tumors,43-48,73.Breast cancer is a heterogeneous group of diseases, which is broadly classified in the clinic into three major subtypes based on the expression or absence of estrogen receptor (ERα), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). Among the three subtypes, the most prevalent subtype represents 70%-80% breast cancers, which is characterized by the expression of ERα and its general dependence on estrogen for proliferation. There are several models available to study the complexity of ER+ breast cancer. Since the 1970s, breast cancer cell lines have been used to replicate and investigate key clinical and molecular features of ERα-expressing breast cancers. The three most common and widely used ER+ cell lines in the field include MCF-7, T47D, and ZR-75-1in vitro, was isolated from the pleural effusion of a Caucasian woman with metastatic breast cancer. MCF-7 cells express functional ERα. Since then, the MCF-7 cell line and its numerous variants have become standard and faithful laboratory models for many in vitro and in vivo preclinical studies. Many ERα+ breast cancer patients do not respond to or become resistant to targeted therapeutic drugs such as antiestrogens and aromatase inhibitors. In an effort to identify alterations associated with this resistance, many laboratories developed MCF-7 variants that resemble clinical characteristics of endocrine responsiveness , by selecting the cells from MCF-7-derived tumors in ovariectomized, athymic mice that did not receive any estrogenic supplementation. These cells were further inoculated in ovariectomized, athymic mice to form tumors in the absence of estrogen. The cells from this tumor were reestablished in vitro as MCF-7/LCC1 cells that showed a significantly reduced lag time in the appearance of tumors in athymic, ovariectomized mice as compared to MCF-7/MIII. Another cell line, MCF-7/LCC9, was developed in vitro by propagating MCF-7/LCC1 cells in increasing concentrations of fulvestrant, a steroidal antiestrogen anthracene (DMBA) induces mammary tumors in some rat strains, especially in Sprague-Dawley rats. While DMBA is not found in the human environment, similar PAHs are associated with breast cancer risk in humans,140, but the animals require priming (pre-treatment) with a progestin. Progestin can be given as either a single intraperitoneal injection of medroxyprogesterone acetate (MPA) or an implant that releases MPA throughout the study. MPA is given when mice are six weeks of age, with DMBA subsequently administered at a dose of 1 mg via oral gavage in weeks 7-10. About 20 weeks from the first DMBA dose, 100% of the mice exhibit at least one mammary tumor. This regimen initiates mammary tumors in C57BL/6, Balb/c, FVB, and DBA/2 mice. While other tumor types are rarely seen, some mice (< 10%) may develop tumors in lungs, digestive tract, skin, lymphoid tissue, or ovaries. The mammary tumors are mostly ER+ and both HER2 and vimentin negative,142. MPA/DMBA-initiated mouse mammary tumors are malignant and mostly resemble human luminal B breast cancers. In our hands, mammary tumors initiated by MPA/DMBA in mice do not respond to tamoxifen. Buque et al. recently reported that tamoxifen delayed the development of mammary tumors in MPA-primed, DMBA-initiated C57BL/6 mice. However, this limits the MPA/DMBA mouse model to studying factors linked to tamoxifen-induced primary prevention of mammary tumors; the model may not be well suited to studies of those factors that drive acquired resistance. Thus, the rat remains the best of the DMBA-induced rodent models in which to investigate antiestrogen resistance and local mammary tumor recurrence after an initial endocrine treatment response.DMBA can also be used to induce ER+ mammary tumors in miceC57BL/6 mouse have been used as allografts for luminal B disease given their expression of ESR2 (ERβ), although these cells also have been classified as basal-like,145. Since the stability and/or functionality of ER expression in EO771 tumors is inconsistently reported and basal-like tumors arise from allografted cells, EO771 has yet to be proven as a reliable and robustly responsive model in which to study ER+ breast cancers. In our hands, EO771 tumors were ESR1 negative and did not respond to physiological doses of TAM in vitro or in vivo (unpublished data). However, EO771 cells were highly responsive to the isoflavone genistein, a compound that activates both ESR1 and ESR2. These results are consistent with ESR2 being reported to be expressed in EO771 cells and activation of ESR2 inhibiting breast cancer cell growth. Other ER+ mouse mammary tumor cell lines have also been described, such as 67NR, but whether the resulting allografted tumors are responsive to antiestrogens has not been fully established. EO771 mouse mammary tumor cells originated from a spontaneous ER+ mammary tumor in a in vivo models for testing some hypotheses. However, the general lack of a series of genetically manipulated rodent models that exhibit a consistent and reproducible ER+ and endocrine therapy responsive phenotype remains a limitation, particularly given the high prevalence of this phenotype in patients. In addition to 3D growth of established cell lines, the generation of organoids from normal and neoplastic tissue from human subjects also offers novel opportunities to study key hypotheses in a more physiologically relevant context than simple 2D culture. Such organoids can be maintained and expanded in vitro and can be transfected with nucleic acids, enabling several lines of mechanism-based inquiry. Patient-derived organoids can naturally exhibit some cellular heterogeneity. One limitation is the ability to retain the mixed cellular organization and overall population phenotype over prolonged periods and multiple passages. When this limitation is reduced or eliminated, there is great potential for patient-derived organoids to become more widely available and more widely used. Another approach is to co-culture relatively homogeneous cultures such as cancer cells with different phenotypes, whether from established breast cancer cell lines or primary cultures, or co-cultured with cancer associated fibroblasts,148. While likely less heterogeneous than PDX models and patient-derived organoid cultures, the greater homogeneity can be useful in identifying mechanistically relevant interactions among specific, predefined cell types with less noise in the data than seen with systems where cellular heterogeneity is greater.While there are adequate models for some breast cancer subtypes, the field remains somewhat constrained by the lack of a large and diverse panel of ER+ models, particularly for the luminal A phenotype but also for the luminal B phenotype. The advent of PDX models and intraductal inoculation as a site for cell line xenografts have improved the utility of The use of established cell lines and animal models will likely remain for the foreseeable future, particularly for those studies that are technically intractable or ethically impossible in human subjects. Hence, the need for new models that can, together, capture all of the key features of the disease will also remain. The ability of experimental models of ER+ breast cancer to lead to more major discoveries in the field will continue to require a careful choice of the most appropriate model(s) and a careful design of the experiments in which the model(s) is used.


GLUT1 is a membrane associated carrier protein that functions in the physiologic transport of glucose across cell membranes. Multiple studies have shown an increased GLUT1 expression in various tumor types and a role in cancer prognosis. The aim of this study was to determine whether cutaneous sebaceous lesions have a differential expression of GLUT1 by immunohistochemistry (IHC). GLUT1 IHC was performed on excision specimens of ten cases of sebaceous carcinoma, nine of sebaceoma, ten of sebaceous adenoma, and ten of sebaceous hyperplasia. Intense, diffuse cytoplasmic staining was observed in sebaceous carcinoma. The pattern of GLUT1 staining in sebaceomas and sebaceous adenomas consisted of a gradient of intense cytoplasmic staining in the basaloid cells with a decreased intensity to membranous staining only and absent staining in mature sebaceous cells. In lesions of sebaceous hyperplasia, GLUT1 staining outlined the basal layer of each gland; cytoplasmic staining was minimal to absent. Increased cytoplasmic staining of GLUT1 may correlate with cellular metabolic and proliferative activity. GLUT1 has potential utility in differentiating sebaceous lesions. Sebaceous gland hyperplasia is commonly encountered in skin biopsy specimens while sebaceous neoplasms are relatively rare. An accurate diagnosis is imperative for treatment and follow-up, and in determining which patients should be tested for mismatch repair (MMR) deficiency, seen in Muir Torre syndrome . This syGlucose, an essential source of energy for rapidly proliferating cells, is transported through highly regulated membrane-associated proteins of the GLUT family . The GLUThe laboratory information system of the surgical pathology department of the University of Rochester Medical Center (URMC) was queried to identify cases of sebaceous hyperplasia, sebaceous adenoma, sebaceoma, and sebaceous carcinoma diagnosed from 1 January 2010 to 1 January 2020. The slides were retrieved and reviewed to verify the diagnoses and cases with sufficient tissue for additional immunohistochemical (IHC) studies were selected from each category to include ten cases each of sebaceous hyperplasia, sebaceous adenoma, and sebaceous carcinoma; only nine cases of sebaceoma were available. The patient age, gender, and tumor site were noted. In addition, the mismatch repair (MMR) protein status was reviewed in cases where immunohistochemical studies for loss of these proteins were previously conducted in the URMC laboratory. The antibody clones used for MMR evaluation were: MLH1 (M1), MSH2 (G219-1129), MSH6 (SP93), and PMS2 (A16-4).The tissue blocks for the selected cases were retrieved and slides cut for IHC staining with a monoclonal GLUT1 antibody (SPM498). The antibody is validated and currently in use for clinical cases. The results of GLUT1 IHC were evaluated using standard light microscopy.Thirty-nine sebaceous lesions were assessed. The average patient age was 66 years (range 40 to 89), 69% were male, and most lesions arose on the face or head and neck see . SebaceoGLUT1 IHC staining was distinct between the various diagnostic categories. Sebaceous carcinomas displayed intense cytoplasmic and membranous staining that was diffuse throughout the basaloid cells see . SebaceoResults for mismatch repair deficiency were available for 21 of the 39 cases. Testing had been assessed using IHC staining for proteins MLH1, PMS2, MSH2, and MSH6. Cases with the loss of at least one of these proteins were considered deficient. In sebaceous carcinomas, testing was conducted in 9/10 cases and there was a deficiency in 8/10 cases with the loss of MSH2 and/or MSH6 seen in 6/10 cases. Testing was not performed on the majority of sebaceoma cases but one case was deficient and two sebaceous adenoma cases were also deficient; protein losses were identified for MSH2 and/or MSH6 in these lesions. No cases of sebaceous hyperplasia had undergone IHC testing for MMR deficiency see . The patSebaceous adenomas, sebaceomas, and sebaceous carcinomas are neoplasms with variable proportions of immature and proliferating sebocytes. In contrast, sebaceous hyperplasia is a benign process with normal maturation in which sebocyte turnover is slowed and glands appear more numerous and crowded . Factor Testing for MMR deficiency by IHC in sebaceous neoplasms is common practice and an important step in the diagnosis of Muir-Torre syndrome ,20. As eSebaceous neoplasms and sebaceous hyperplasia display distinctive patterns of GLUT1 staining by immunohistochemistry. The patterns seen may correlate with cell immaturity and higher metabolic requirements for glucose in proliferating cells. Although GLUT1 is a membrane protein, the strong cytoplasmic staining seen in neoplastic cells demonstrates the presence of the protein in high quantities beyond the membrane, within the cytoplasm. Increased cytoplasmic staining of GLUT1 may correlate with cellular metabolic and proliferative activity in poorly differentiated, immature sebocytes. Additional immunohistochemical studies with a GLUT1 antibody will be helpful in elucidating the role of this glucose transporter in sebaceous cutaneous lesions and may aid in an accurate diagnosis. Research is currently underway to determine the utility of GLUT1 inhibitors for targeted treatment of various malignancies with multiple clinical trials in progress . In the