Somatic DNA copy number variations (CNVs) are prevalent in cancer and can drive cancer progression, albeit with often uncharacterized roles in altering cell signaling states. Here, we integrate genomic and proteomic data for 5,598 tumor samples to identify CNVs leading to aberrant signal transduction. The resulting associations recapitulate known kinase-substrate relationships, and further network analysis prioritizes likely causal genes. Of the 303 significant associations we identify from the pan-tumor analysis, 43% are replicated in cancer cell lines, including 44 robust gene-phosphosite associations identified across multiple tumor types. Several predicted regulators of hippo signaling are experimentally validated. Using RNAi, CRISPR, and drug screening data, we find evidence of kinase addiction in cancer cell lines, identifying inhibitors for targeting of kinase-dependent cell lines. We propose copy number status of genes as a useful predictor of differential impact of kinase inhibition, a strategy that may be of use in the future for anticancer therapies.  •Alterations in copy number and in signaling pathways are robustly associated in cancer•Differences in essentiality of phosphoproteins show evidence of kinase addiction•Copy number markers of dysregulated signaling suggest treatment stratification options Memon et al. show that copy number alterations can be used as molecular fingerprints to predict the activity of signaling pathways in cancer. Kinase dependencies of cancer cells can be exploited for targeted anticancer therapy. Kinases are druggable proteins that are key targets for cancer treatment, because they are highly prone to acquiring somatic mutations and acting as oncogenes . SeveralLarge-scale phosphorylation measurements of tumor samples have relied primarily on reverse-phase protein arrays (RPPAs) that consists of (phospho)protein antibody microarrays used to estimate protein abundances in a high-throughput manner. The TCGA (The Cancer Genome Atlas) RPPA platform, TCPA (The Cancer Proteome Atlas), currently has estimates for around 150 proteins and 50 phosphoproteins for nearly 10,000 tumor samples (33 tumor types) . The phoFrom the integration of large-scale pan-cancer genomic, transcriptomic, and RPPA phosphoproteomic datasets, we identified genes likely to drive changes in kinase signaling. These associations were found to be enriched in known kinase-substrate relationships and were then systematically filtered to select reliable associations that also replicated by analyzing cancer cell line data. Several predicted regulators of hippo signaling  were experimentally tested, and a top-ranked predicted regulator (ARHGEF17) of hippo signaling (YAP) was further studied through (phospho)proteomic analysis. In parallel, we found evidence of kinase addiction in cancer cell lines and identified inhibitors for targeting of kinase-dependent cell lines. This work suggests that copy number status of genes may be indicative of kinase activity differences and predictive of sensitivity to kinase inhibition. In the long term, this strategy can be used to stratify patients for targeted therapy based on the copy number status of regulators.We have developed a computational method to identify genes driving changes in phosphorylation signaling in patient-derived cancer samples A. A geneBefore filtering for spurious associations because of coamplification, we tested whether the CNV-phosphosite associations can recapitulate prior knowledge on kinase-substrate relationships. For this, we analyzed 118 known kinase-substrate relationships curated in the PhosphositePlus  databaseGiven that copy number alterations affect multiple genes within altered regions, many previously defined associations are likely to be spurious passenger associations. We then sought to identify the most likely causal gene controlling the downstream kinase signaling change for each region. First, we selected CNV-associated genes whose expression was also associated with the phosphosite activities (FDR < 5%). We then selected the top-ranked associated genes within each chromosome region based on a combined rank from 3 measurements: (1) the CNV, (2) the gene expression association effect size, and (3) the gene-phosphoprotein distance in a functional interaction network . We exemWe obtained 303 associations between causal genes and regulated phosphosites in the pan-tumor dataset . All 303Several recurrent protein missense genetic variants are known to cause changes in kinase signaling . From 1,in vitro culturing. To assess the overall predictive power of levels of individual phosphosites, we trained models of phosphosite levels as a linear combination of expression profiles of the predicted causal genes  with publicly available copy number , expressal genes . For 8 oal genes A. For thal genes A.Figure A stringent set of 44 causal gene-phosphosite pairs were defined that were replicated in at least 20% of tumor types (4/18) and replicated independently in two cancer cell line datasets B. Among Having shown that copy number alterations lead to kinase signaling changes, we next sought to find cases in which such signaling differences create potential genetic vulnerabilities. Previous studies have proposed that cancer cells have a tendency to become dependent on the activity of proteins such as kinases  and are We next investigated drug response datasets to interrogate the relationship between phosphosite levels and drugs. We correlated phosphosite levels as measured by 37 phospho-Ab with sensitivity profiles of 265 drugs in 746 cancer cell lines from Genomics of Drug Sensitivity in Cancer (GDSC) database , in whicOur results indicate that copy number changes in genes can be indicative of changes in phosphosite levels and that cancer cells can become dependent on activity as measured by these phosphosites. Therefore, copy number changes correlated with kinase activity should also be predictive of kinase susceptibility. Indeed, we found several examples in which the CNVs predictive of phosphosite level differences correlated with the impact of downregulation, knockout, or inhibition of the corresponding protein. For instance, ERBB2 and EPN3 CNVs were predictive of EGFR pS1068 phosphosite levels and correlated with sensitivity to loss of the EGFR gene and sensitivity to EGFR inhibitors, including afatinib and gefitinib A and 4B.As an additional example, we looked more in detail at the CNV-phosphosite association for YAP pS127, identifying 12 genes as potential regulators, 5 of which were replicated in cancer cell lines A. We ranWe experimentally tested the effect of loss of ARHGEF17 and PLA2G16 genes on YAP pS127 phosphosite levels. We selected cell lines with different baseline levels of YAP phosphorylation and confirmed that YAP pS127 levels were low in MCF7 and MDA-MB-361 cells and high in MDA-MB-468 and T47D cells, consistent with the measurements in the MCLP RPPA phosphoproteomics dataset from the cancer cell line cohort . EffectiTo further dissect the regulatory role of ARHGEF17 in hippo signaling, we performed proteomics and phosphoproteomics of MDA-MB-468 and T47D cells treated with shRNA targeting ARHGEF17, along with their matched controls. Differential phosphosite analysis data showed significant changes in 3,182 and 259 phosphosites after ARHGEF17 knockdown (5% FDR) in MDA-MB-468 and T47D cells, respectively . These iAltogether, these analyses suggest that ARHGEF17, EAF1, PFKM, and PLA2G16 copy number changes can be linked with changes in YAP signaling. Across the tumor samples, increased expression of ARHGEF17 is associated with increased YAP activity and increased sensitivity to loss of the YAP gene and interestingly is linked with decreased sensitivity to methotrexate J. This eWe propose here a genetic association approach to identify genes whose expression changes can drive differences in kinase signaling. Such regulators are unlikely to be direct, because they are found through genetic association for differences in steady-state phosphorylation levels. We use copy number variation instead of recurrent missense mutations, given that they form a critical mass of genomic aberrations encountered in multiple tumor types and compared with point mutations, the impact of copy number changes on an individual gene is easier to interpret. For most genes, their copy number profiles tend to be well correlated with gene expression data . AlthougWe selected for further analysis several putative regulators of YAP phosphorylation, including ARHGEF17 that we followed up through (phospho)proteomics studies. ARHGEF17 is a Rho guanosine triphosphatase (GTPase) with a functional role in the maintenance of actin cytoskeleton organization and focal adhesion . In the The current study relied on antibody measurement of phosphorylation and protein abundance levels of proteins with reliable antibodies and previous evidence of a role in cancer. This approach has great coverage, allowing us to identify associations from ∼5,600 samples and thus providing reliable significant associations among key signaling changes in cancer. However, our analysis is focused on a restricted set of signaling pathways, and inevitably, we are unable to identify regulators of less studied pathways. More recently, mass spectrometry has started to be used to profile tumor samples on a large scale for an increasing number of samples . AlthougCancer cells often become dependent on changes in the genes that led to the cancer development, a phenomenon dubbed oncogene addiction. When a signaling pathway is observed to be hyperactive in a tumor, relative to healthy tissue, it is often assumed that such activation is a driving event and a requirement for cell viability. Therefore, cellular dependency on kinase activity has been exploited in many targeted therapies . We testpbeltrao@ebi.ac.uk).Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Pedro Beltrao (Plasmids generated in this study are available upon request or can be purchased from the named supplier or contact listed as supplying the reagent.PXD021031 (The accession number for the mass spectrometry (phospho-)proteomics reported in this paper is ProteomeXchange Consortium PRIDE: XD021031 .The human breast cancer cell lines - MDA-MB-468 , MDA-MB-361 , T47D , MCF7  and the cervical cancer HeLa cells  were all maintained at 37°C with 5% CO2. All cells were grown in DMEM with 10% FBS. For serum starvation, cells were incubated in DMEM without other supplements for 24 h. All cell lines were authenticated using STR profiling method at the CRUK core facility.http://sherwood.cshl.edu:8080/sherwood/) and cloned into the expression vector pZIP-SSFV-Ultra-Puro_ZsGreen . ShRNA plasmids together with pMDL, pCMV-Rev, and pVSV-G were used to produce virus in 293FT cells. Resulting viruses were used to infect and generate stable cell lines for both MDA-MB-468 and T47D using puromycin selection.ShRNA hairpins were designed using (ARHGEF17_shRNA1 (TGCTGTTGACAGTGAGCGCCAGGAGGTTATTCAGAGCATATAGTGAAGCCACAGATGTATATGCTCTGAATAACCTCCTGATGCCTACTGCCTCGGA)ARHGEF17_shRNA2 (TGCTGTTGACAGTGAGCGACATCACCAAGATGGTATCTGATAGTGAAGCCACAGATGTATCAGATACCATCTTGGTGATGGTGCCTACTGCCTCGGA)PLA2G16_shRNA1 (TGCTGTTGACAGTGAGCGCTGGAGTCATGTTCTCAAGAAATAGTGAAGCCACAGATGTATTTCTTGAGAACATGACTCCAATGCCTACTGCCTCGGA)PLA2G16_shRNA2 (TGCTGTTGACAGTGAGCGCGAACTGCGAGCACTTTGTGAATAGTGAAGCCACAGATGTATTCACAAAGTGCTCGCAGTTCTTGCCTACTGCCTCGGA)HeLa cells were plated on glass cover slides in a 24 well plate at 1e5 cells/plate in DMEM-12 media with 10% FBS. 24 h later cells were transfected with the following plasmids using Lipofectamine 2000 (Thermo Fisher) in accordance with the manufacturer’s instructions; GFP-LATS2 , GFP-ARHGEF17 , Flag-tagged-EAF1 or -PFKM (purchased from GensScript). 24 h post transfection cells were fixed in 4% formaldehyde for 20 m, washed with T-PBS (0.1% Tween/PBS), and permeabilised with 0.1% Triton X-100 for 15 m. After blocking for 1h , fixed cells were incubated with primary antibody to FLAG (F1804/ThermoFisher) and YAP  in blocking buffer for 1h. Following extensive washing with T-BPS slides were incubated with Alexa conjugated antibodies for FLAG and YAP detection and then mounted with Prolong Antifade mounting. Images were captured in a Leica SP5 confocal microscope and processed using Fiji software.For GFP-TEM4/GFP-LATS2 overexpression studies, cells were seeded at low density (50% confluency), in contrast to EAF1/PFKM overexpression studies were cells were seeded at high density (100% confluency). Both transfected and shRNA KD cells were lysed in 50 mM Tris-Cl, pH 7.6; 150 mM NaCl, 1% NP-40 supplemented with Protease inhibitors . Cells lysates were centrifuged for 10 min at 4oC to remove insoluble debris. Lysates were separated using 4%–20% Gradient gels  and immunoblotted using standard protocol. Primary antibodies used were YAP , p-YAP (S127) and GAPDH . Blots were probed with mouse or rabbit specific IRDye 800 (LiCOR) and acquired, and quantified, using Odyssey Classic. Total RNA was isolated and purified from cells using miRNeasy Mini Kit (QIAGEN). cDNA was synthesized using the High Capacity RNA-to-cDNA kit (ABI) according to manufacturer’s instructions. qRT-PCR was performed using Fast SYBR Green Master Mix (ABI) on the QuantStudio 12K Flex Real-Time PCR System (ABI). Relative expression levels were defined using the DDCt method and normalizing to 36B4/RPLP0.(AGGCCATCGTGAAGAAGGAA & CAAAGTGCTCGCAGTTCTCA), primer pair 2 (AGGAGGTGCTCTACAAGCTG & CTCCATAGCGCAGCTCATTC). ARHGEF17: primer pair 1 (GAGAAGTTGAGCCCATGCTG & GTAGGGCCCTTTCAGACTGT), primer pair 2 (GCGGAAGTCCCTGTCAAATC & ACCCTCAGCTCTGAAAGGTC). 36B4/RPLP0: primer pair (GTGTTCGACAATGGCAGCAT & GACACCCTCCAGGAAGCGA)PLA2G16: primer pair 1 Adherent cells were grown to complete confluence prior to harvesting and harvested by scraping on ice in 1X PBS containing protease inhibitors . Cell pellets were dissolved as described previously  and protNormalized copy number (log2) datasets  and RNaseq expression datasets  for 31 different tumor types generated as part of TCGA  consortihttps://depmap.org/portal/achilles/). These datasets were generated by Project Achilles to catalog gene essentiality across cancer cell lines. The RNAi screen (Ach 2.20.2) has high coverage targeting 17,098 genes in 501 cell lines. Out of these, 406 cell lines had DepMap-RPPA data and 166 cell lines had available MCLP-RPPA data  and tumor type as covariates. A separate covariate model was run for each phosphosite.Cy) with expression-based measurements (Ey) in the model.Two models were compared using a likelihood ratio test to identify the effect of a given CNV on phosphosite levels after taking into account the matched protein abundance and tumor specificity. In order to identify associations between gene expression and phosphosite levels, the same approach was repeated after replacing the copy number measurements  effect size of CNV∼Phosphosite levels, ii) effect size of Expression∼Phosphosite levels and iii) the network based score. Short-listed genes for a phosphosite were ordered by their highest average combined rank, calculated using Borda method in R. Genes were iteratively picked with priority given to the highest ranked gene over other genes with strongly correlated copy number profile (r > 0.5), which made them more likely to belong to the same genomic segment.Significant associations identified in tumor samples were also tested in 890 cancer cell lines with RPPA and expression data in DepMap database and 319 cancer cell lines with Expression and RPPA datasets. To evaluate the quality of our associations from the pan-tumor analysis, we predicted the phosphosite levels from expression data in cancer cell lines using models trained using TCGA, MCLP and DepMap data and correlated with the ‘true’ phosphosite activities measured independently in MCLP or DepMap databases.50 values) generated from drug treatment of cancer cell lines were associated with levels of individual phosphosites across these cancer cell lines with the protein abundance of the phosphosite as a covariate in the linear model. The p-values of these drug∼gene associations were adjusted for multiple comparisons and used as a measure of significance.Similar to genetic associations performed between gene copy number and phosphosite levels, associations were also performed between drug screens and phosphosite levels across cancer cell lines using a linear model approach. Briefly, drug response data  providing quantification for 34,716 unique phosphosites in T47D cell line. Similarly, there were 40,754 phosphopeptides  providing quantification for 34,223 unique phosphosites in MDA-MB-468 cell line. The data were quantile normalized for each cell line separately. Differential phosphoproteome analysis between siARHGEF17 and matched siRNA control samples was performed separately for T47D cell line and MDA-MB-468 cell line using the lmFit and the eBayes functions in the limma  package All statistical tests were performed in R. The two-tailed paired t test was applied to analyze differences between control and the positive (or negative) regulators in the knockdown and overexpression experiments. Data are shown as mean + SEM relative to control experiment.


Drosophila stable cell lines has become invaluable for complementing in vivo experiments and as tools for genetic screens. Recent advances utilizing attP/PhiC31 integrase system has permitted the creation of Drosophila cells in which recombination mediated cassette exchange (RMCE) can be utilized to generate stably integrated transgenic cell lines that contain a single copy of the transgene at the desired locus. Current techniques, besides being laborious and introducing extraneous elements, are limited to a handful of cell lines of embryonic origin. Nonetheless, with well over 100 Drosophila cell lines available, including an ever-increasing number CRISPR/Cas9 modified cell lines, a more universal methodology is needed to generate a stably integrated transgenic line from any one of the available Drosophila melanogaster cell lines. Here, we describe a toolkit and procedure that combines CRISPR/Cas9 and theaaa PhiC31 integrase system. We have generated and isolated single cell clones containing an Actin5C::dsRed cassette flanked by attP sites into the genome of Kc167 and S2R+ cell lines that mimic the in vivo attP sites located at 25C6 and 99F8 of the Drosophila genome. Furthermore, we tested the functionality of the attP docking sites utilizing two independent GFP expressing constructs flanked by attB sites that permit RMCE and therefore the insertion of any DNA of interest. Lastly, to demonstrate the universality of our methodology and existing constructs, we have successfully integrated the Actin5C::dsRed cassette flanked by attP sites into two different CNS cell lines, ML-DmBG2-c2 and ML-DmBG3-c2. Overall, the reagents and methodology reported here permit the efficient generation of stable transgenic cassettes with minimal change in the cellular genomes in existing D. melanogaster cell lines.The generation of  Drosophila biology, both in vivo and in vitro tissue culture cells. Over time, the techniques utilized have been modified and refined to increase the efficiency of generating stable transgenic lines  as a dual plasmid system or with dual expression cassettes in a single vector or using a multicistronic vector  in Both the approaches described above have their advantages. With the Ras-attP lines, constitutive GAL4 expression can be leveraged for transgenic expression and the genomes of the Ras-attP lines are not as complex as the other established lines  and CNS (ML-DmBG2-c2 and ML-DmBG3-c2) lines. Eventually, the attP insertion cassette will be expanded to include more of the existing Drosophila cell line collection. Furthermore, all the reagents generated are available to the Drosophila research community to either independently create attP containing cell lines or utilize the created attP lines reported here for RMCE to insert desired transgene of interest.Subsequently, CRISPR-Cas9 based approaches have revolutionized genome editing  on in vivo attP sites demonstrated to produce transformants and having high viability. Upon finalizing the target loci, guide RNA (gRNA) candidates were determined using the tool at http://tools.flycrispr.molbio.wisc.edu/targetFinder/, last accessed 05/19/2019 . For the site at 99F8, a single gRNA was cloned into the pU6-3-gRNA vector  as described  was custom synthesized by Synbio Technologies Inc., NJ. Donor template for the 99F8 exchange cassette was assembled into a pBluescript  vector backbone using Gibson Assembly to create pBS-99F8-5’HR-attP≫Act5C::GFP≪attP-3’HR (DGRC Cat# 1544) vector. The replacement donor was cloned into BsgI digested pBS with the 5’ and 3’ homology arms, which were 0.96 and 1.14 kb, respectively, flanking the attP≫Act::dsRed≪attP insert amplified from pUC57-25C6-5′HR-attP≫Act5C::dsRed≪attP-3′HR. Sequencing confirmed the correct assembly of pBS-99F8-5’HR-attP≫Act5C::GFP≪attP-3’HR vector. The vectors for RMCE, pUC57-attB≫MCS-Act5C::EGFP≪attB (DGRC Cat# 1545) and pUC57-attB≫MCS-MT::EGFP≪attB (DGRC Cat# 1546) were custom gene synthesized by Synbio Technologies Inc., NJ.Drosophila S2R+ , S2 DGRC  cells were grown in M3 media (Sigma) containing Bactopetone, yeast extract and supplemented with 10% fetal bovine serum (M3+BPYE + 10%FBS). Embryonic Kc167  cells were grown in CCM3 (GE Life Sciences) medium. Larval central nervous system derived cell lines ML-DmBG2-c2  and ML-DmBG3-c2  were grown in M3+BPYE + 10%FBS supplemented with 10 µg/ml insulin.Detailed cell culture protocols have been described previously . Briefly6/ml) cells plated in a well of a 6-well dish were transfected with 300 ng of Act::Cas9 (Addgene #62209) and the respective gRNA and repair templates for the 25C6 (75 ng pU6-3-25C6-gRNA1 (DGRC Cat# 1547), 75 ng pU6-3-25C6-gRNA2 (DGRC Cat# 1548) and 150 ng pUC57-25C6-5′HR-attP≫Act5C::dsRed≪attP-3′HR) and 99F8 (150 ng pU6-3-99F8-gRNA (DGRC Cat# 1549) and 150 ng pBS-99F8-5’HR-attP≫Act5C::GFP≪attP-3’HR) loci using Effectene Transfection reagent (QIAGEN) as per the manufacturer’s recommendation. Transfected cells were cultured for 10–20 days to amplify the cultures to two 100 mm dishes before bulk or single cell sorting the cells.For the CRISPR-Cas9 transfections, 2 ml (1.5 × 106/ml) cells plated in a well of a 6-well dish were transfected with 300 ng of either pUC57 attB≫MCS-Act5C::EGFP≪attB or pUC57 attB≫MCS-MT::EGFP≪attB and 200 ng Act::phiC31 integrase (DGRC Cat # 1368), using Effectene Transfection reagent (QIAGEN) as per the manufacturer’s recommendation. Transfected cells were cultured for 10–20 days to amplify the cultures to two 10 cm dishes before bulk sorting the cells.For RMCE transfections, 2 ml  isolation. The harvested cells were centrifuged and washed once with phosphate-buffered saline (PBS). Genomic DNA was extracted from the PBS washed pellet using the Zymo Quick-DNA™ MiniprepPlusKit (D4068/4069). PCR reactions were performed to diagnose and confirm CRISPR-Cas9 mediated homologous recombination , allowed to attach for 1–2 hours, fixed with 4% paraformaldehyde in PBS, pH 7.0, washed and immunostained with rabbit Anti-dsRed  and/or mouse Anti-EGFP (DHSB 12A6) antibodies and the respective Alexa dye-coupled secondary antibodies (Jackson ImmunoResearch) reconstituted in 5% Normal Goat Serum, 0.1% Triton in PBS. Cells were then mounted on DAPI containing mounting media (Vectashield H-1200) prior to imaging on a Leica SP8 confocal microscope.https://doi.org/10.25387/g3.14551074.All data necessary for confirming the conclusions in this paper are included in this article and in supplementary figures and tables. All cell lines and plasmids are available from the DGRC. Supplementary material is available at figshare: D. melanogaster lines had the highest survival rates of transformants listed in the Rainbow Transgenics website. Amongst the lines that were positive for transgenic transformants, the insertion at 99F8 on 3 R had the highest survival rate . Despite the low percentages of the GFP- and double-positive fractions, it was feasible to expand these fractions to an extent that cassette exchange at the 99F8 locus  could be confirmed and sequence verified.Constitutive overexpression of certain transgenes in cell culture could potentially be toxic leading to cell death. This can be circumvented by the use of an inducible metallothionein (MT) promoter (It is evident from the data presented that the inserted attP site(s) in the S2R+-attP-99F8 Clone 141 line are functional. Taken together, it is most likely that this line has at least 2–3 attP insertions at the 99F8 locus given the number of copies of the 3rd chromosome in S2R+ cells . To generate the attP insertion at the 25C6 locus using CRISPR-Cas9 strategy, cells were transfected with two gRNAs accompanied by the repair construct containing the attP≫Act::dsRed≪attP cassette flanked with the homology arms. Cells positive for dsRed were enriched by fluorescence cell sorting at least 10–20 days after the initial transfection before sorting to derive SCCs. The integration of the donor repair cassette was assessed by PCR amplification across the integration locus from outside the homology arms . A successful insertion yielded a 5.7 kb amplicon while a 2.6 kb amplicon was observed if the 25C6 genomic locus remained unmodified. A nonhomozygous modification of the locus would be expected to yield both bands, while a homozygous genomic modification would only yield a single 5.7 kb amplicon (Band 1) . We further used primer pairs that amplified from within the insert to outside the homology arms  to verify the clones and also sequence for the presence of the attP sites . This PCR diagnosis indicated that we obtained a homozygous S2-DGRC clone containing the attP cassette at the 25C6 locus .D. melanogaster cell lines, we introduced attP sites at 25C6 and 99F8 in other cell lines. We documented the homozygote ML-DmBG2-c2-attP-25C6-Clone 8  and ML-DmBG3-c2-attP-25C6-Clone 74 , Kc167-attP-25C6-Clone 35  and the heterozygote Kc167-attP-99F8-Clone 71 , and ML-DmBG3-c2-attP-99F8 28 . We summarize the various efficiencies of the genomic modification process and single cell cloning with different cell lines in In order to investigate the applicability of this technique to other D. melanogaster cell lines. All the reagents generated in this study will be accessible to researchers from the Drosophila Genomics Resource Center to create their own cell lines, as well as a cost-recovery service to aid with deriving clonal populations post-RMCE. Overall, these cell lines and plasmid collection created will aid researchers to further harness D. melanogaster cell culture to address broader research questions.In summary, we have been able to insert RMCE docking cassettes containing flanking inverted attP sites in two different genomic loci in both embryonic and larval CNS derived cell lines. Successful cassette exchange was demonstrated in the generated S2 and Kc167 attP lines. Moreover, the methodology presented here not only permits the introduction of attP sites at loci 25C6 and 99F8 in any cell line but also with a few minor modifications of the reagents generated in this study, an attP site could be inserted in any desired locus. Interestingly, our results demonstrate that the insertion of an attP site in every copy of the genome and RMCE conversion is variable. Nonetheless, this “heterozygosity” would enable researchers to generate a multitude of clones that could have multiple transgenes within the same clonal line or express varying doses of the transgene with the option to choose the directionality of the exchanged cassette. Given the numerous polyclonal variants that are observed in the bulk-sorted post-RMCE population, we strongly recommend deriving a single cell population. Our approach also permits the comparisons of transgenic expression from the same locus across various biological and physiologically diverse


Cyclin-dependent kinases are involved in the regulation of cancer-initiating processes like cell cycle progression, transcription, and DNA repair. In hematological neoplasms, these enzymes are often overexpressed, resulting in increased cell proliferation and cancer progression. Early (pre-)clinical data using cyclin-dependent kinase inhibitors are promising but identifying the right drug for each subgroup and patient is challenging. Certain chromosomal abnormalities and signaling molecule activities are considered as potential biomarkers. We therefore summarized relevant studies investigating cyclin-dependent kinase inhibitors in hematological malignancies and further discuss molecular mechanisms of resistance and other open questions.Genetically altered stem or progenitor cells feature gross chromosomal abnormalities, inducing modified ability of self-renewal and abnormal hematopoiesis. Cyclin-dependent kinases (CDK) regulate cell cycle progression, transcription, DNA repair and are aberrantly expressed in hematopoietic malignancies. Incorporation of CDK inhibitors (CDKIs) into the existing therapeutic regimens therefore constitutes a promising strategy. However, the complex molecular heterogeneity and different clinical presentation is challenging for selecting the right target and defining the ideal combination to mediate long-term disease control. Preclinical and early clinical data suggest that specific CDKIs have activity in selected patients, dependent on the existing rearrangements and mutations, potentially acting as biomarkers. Indeed, CDK6, expressed in hematopoietic cells, is a direct target of MLL fusion proteins often observed in acute leukemia and thus contributes to leukemogenesis. The high frequency of aberrancies in the retinoblastoma pathway additionally warrants application of CDKIs in hematopoietic neoplasms. In this review, we describe the preclinical and clinical advances recently made in the use of CDKIs. These include the FDA-approved CDK4/6 inhibitors, traditional and novel pan-CDKIs, as well as dual kinase inhibitors. We additionally provide an overview on molecular mechanisms of response vs. resistance and discuss open questions. Despite the clinical implementation of novel treatments like kinase inhibitors, hypomethylating agents or pathway modulators during the last decades, several hematological malignancies still face a poor prognosis. Relapsed or refractory courses are particularly difficult to manage, often exhibiting multiple drug resistances and intimidating survival rates ,2,3,4. TCell cycle regulation is a key mechanism to prevent malignant cell proliferation and uncontrolled cell division. Aleem and Arceci reviewed the roles of CDKs in controlling cell cycle and development of hematological malignancies in detail . Here, wINK4A, the most frequently deleted locus in human cancer. Translocations of the MLL gene locus are common in acute myeloid leukemia (AML) and account for most infant ALL cases. CDK6 is a direct target of MLL fusion proteins and thus activated. Finally, CDK6 can be activated by FLT3-ITD-mediated down-regulation of cyclins D2 and D3. Besides CDK6, other CDKs are also involved in leukemogenesis. For example, the AML driver mutation FLT3-ITD is an activator of CDK1. Further, mutations and deletions of the cyclin C and CDK19 locus on 6q21 result in altered Notch1 regulation especially in T-ALL . Be. Be40]. ML cells .T315I mutated CML, via reducing proliferation and inducing G1 arrest. This is of importance because tyrosine kinase inhibitor resistance is frequently observed in this CML subtype, leading to challenging clinical problems [Although there is a clear connection between BCR-ABL1 fusion and cell cycle regulation, only very limited data is available for the evaluation of CDKIs in chronic myeloid leukemia (CML). Rangatia and Bonnet have shown that lack of BCR-ABL1 leads to G1 phase arrest and a decrease in cyclin D1. Physiological CDKIs p21 and p27 subsequently exhibited increased gene expression . Schneewproblems . In ALL,problems ,44. Incrproblems ,46. In mproblems ,47.FOXO3A can additionally control p27 gene expression. However, it was not influenced in palbociclib-resistant cells; ruling out the possibility of FOXO3A directly induced p27 downregulation. Palbociclib-sensitive cell lines exhibited a similar drop in p27 gene expression, while protein abundance remained stable. Hence, the p27-downregulating effect is rather due to posttranslational modification than reduced p27 gene expression  is another CDK4/6 inhibitor that demonstrated significant anti-proliferative and apoptosis-inducing effects in AML and B-ALL cell lines and primary samples, probably mediated via G1 arrest and senescence . A recenNOTCH1-mutant and wildtype T-ALL and found both subtypes sensitive to the inhibitor. The combination with glucocorticoid dexamethasone and mTOR inhibitor everolimus acted synergistically in vitro and in vivo. In contrast, antagonistic effects were observed with several drugs used in T-ALL standard chemotherapy including methotrexate, mercaptopurine, asparaginase, or doxorubicin [Pikman et al. investigated ribociclib in orubicin .CD25 and RUNX1 expression upon CDK6 inhibition and that CD25 ablation results in T-ALL leukemogenesis. They further showed that CD25 mediates the therapeutic response to ribociclib, suggesting CD25 deletion as a potential mechanism of resistance to CDK6 inhibitors as well as predictive marker for ribociclib response  has been more widely evaluated in lymphoma. Here, inhibited proliferation and induced apoptosis was reported in germinal center-derived B-cell lymphoma cell lines, but not in activated B-cell like diffuse large B-cell lymphoma cell lines . In a clMLL-rearranged AML cell lines and xenografts [Further preclinical studies found abemaciclib effective in nografts  as well nografts . Nakatannografts . Moleculnografts .The novel CDK4/6 inhibitor lerociclib (G1T38) was capable of decreasing Rb phosphorylation and induced G1 cell cycle arrest in leukemia and lymphoma cell lines in vitro. Of note, lerociclib demonstrated a superior efficacy compared to palbociclib and did not induce severe neutropenia in an estrogen receptor positive breast cancer dog animal model, which is a common side effect of CDK4/6 inhibitors. Using mouse xenograft models, the authors further demonstrated that lerociclib accumulated within the tumor but not in plasma, implying less severe effects on myeloid progenitor cells compared to palbociclib therapy. Indeed, plasma concentrations after palbociclib treatment were significantly higher than the concentration needed to inhibit cell proliferation in several cell lines. In contrast, after lerociclib treatment, plasma concentrations dropped faster. The authors thus claim that palbociclib-induced neutropenia is a product of CDK4/6 inhibition in the bone marrow, preventing proliferation of healthy bone marrow cells .CDK4/6 inhibitors including the novel promising molecule lerociclib are without doubt the most intensively researched group of CDKIs in both, solid and hematological malignancies. While palbociclib, ribociclib, and abemaciclib already obtained FDA approval for breast cancer, current preclinical and clinical studies for leukemia and lymphoma also focus on inhibitors targeting other CDKs.MLL in acute leukemias, are also part of the super elongation complex, thus mis-localizing CDK9 to HOX gene promoters and inducing abnormal CDK9 expression, cell growth, and proliferation [CDKs 7, 8, and 9 are novel emerging targets in preclinical research. Indeed, recent data reveal anti-leukemic activity upon inhibition of these transcriptional regulators. CDK9 is a global transcriptional regulator and part of the super elongation complex controlling RNA polymerase II phosphorylation and elongation. AFF family members, which are frequently fused to feration . Anotherferation .So far, AZD4573 is the only selective CDK9 inhibitor invested clinically in hematological malignancies. A preclinical study on different hematological neoplasms proved significant induction of apoptosis via MCL-1 suppression in vitro and in vivo . The samMCL1 gene expression after CDK9 inhibition while fludarabine had the opposite effect. Combined application of CDKI-73 and fludarabine downregulated RNA polymerase II mediated genes MCL1, XIAP, CCND1, and CCND2. Of note, synergistic effects were also observed under CD40L-expressing pro-survival co-culture conditions with initial fludarabine resistance [The non-selective CDK9 inhibitor CDKI-73 proved anti-proliferative and pro-apoptotic capacity in chronic lymphoblastic leukemia (CLL) , diffusesistance . In diffsistance . The samsistance . Many mosistance ,69,70,71CDK8 regulates transcription as part of the mediator complex or by phosphorylation of transcription factors . In primRUNX1/ETO rearranged cell line [First CDK7 inhibitors are also arising and are being tested in AML cell lines. The CDK7/12/13 inhibitor THZ1 showed anti-proliferative effects and induced apoptosis in a ell line . A preclell line .SY-1365, which is under clinical investigation for solid tumors, decreased MCL-1 protein levels and induced transcriptional changes mainly of oncogenic transcription factor genes and members of cell cycle and DNA damage repair related pathways. Of note, this inhibitor was more effective in cells with low BCL-XL expression. When combined with BCL-2 inhibitor venetoclax, antitumor effects were synergistically increased in vitro and in vivo . FinallyCollectively, CDK7/8/9 inhibitors hold promise for being implemented in trials because of their unique ability to modify transcriptional processes and regulate apoptosis. Other approaches featuring down-regulation of these kinases are less specific, resulting in a broader spectrum of mechanistic actions to be dealt with.Flavopiridol  is a first generation pan CDK inhibitor, targeting CDKs 1, 2, 4, 6, 7, and 9. It induces cell cycle arrest in ALL and AML cell lines as well as leukemia and lymphoma animal models ,80. PrecClinical efficacy was observed in hematological neoplasms including CLL and AML, especially in AML as part of the FLAM regimen (flavopiridol followed by cytarabine and mitoxanthrone) ,84. ClinSeveral mechanisms of resistance have been described for flavopiridol . MahoneyMLL rearrangement, primary patient cells, and in vivo models [Dinaciclib (SCH727965) is now widely evaluated in hematological malignancies. By inhibiting CDKs 1, 2, 5, and 9, dinaciclib reduces cell viability, induces apoptosis and cell cycle arrest in ALL and AML cell lines, also with o models ,90,91,92In CLL, dinaciclib downregulates MCL-1 gene and protein expression and potently induces apoptosis in patient-derived cells . InteresIn mantle cell lymphoma, Höring et al. pursued a combined MCL-1 inhibiting and NOXA stabilizing approach using dinaciclib and fatty acid synthase inhibitor orlistat. They observed synergistically-induced NOXA-dependent apoptosis in mantle cell lymphoma cell lines and primary samples along with tumor growth inhibition in vivo . In advaFurther preclinical evaluation detected increased doxorubicin response rates in myeloma cell lines after low dose dinaciclib treatment, boosting growth inhibition and promoting senescence . InteresFurther pan CDK inhibitors are now also tested in the clinical setting. Besides the CDKs targeted by dinaciclib , AT7519M also inhibits CDK4, still inducing apoptosis in vitro and in vivo and reducing proliferation in myeloma and CLL ,104. TwoMCL-1 and c-Myc downregulation was only reached in an intermittent drug administration schedule that should be considered in clinical practice [Voruciclib (P1446A), a CDK1/2/4/5/6/8/9 inhibitor, was evaluated in a phase I study recruiting follicular lymphoma, mantle cell lymphoma, marginal zone lymphoma, small lymphocytic lymphoma, CLL, diffuse large B-cell lymphoma, and AML patients after demonstrating significant potential in preclinical studies ,107. Compractice .The CDK1/4/9 inhibitor P276-00 showed promising in vitro and in vivo results in AML , myelomaINK4C as a potential tumor suppressor gene in Hodgkin lymphoma [INK4A expression has been observed in Reed–Sternberg cells of Hodgkin lymphoma cases [Roniciclib (BAY1000394) targets the same CDKs as flavopiridol  and achieved SD in three out of seven patients with lymphoid neoplasms . Of notelymphoma . Finallyma cases .Due to its variety in mechanistic pathways, pan CDK inhibition offers a broad range of possibilities to target virtually every hematological subtype. Most progress has been made for dinaciclib, which is already investigated in clinical trials; however, results are ambiguous. Chemical modifications or combinatorial schedules might be beneficial to increase the therapeutic outcome.Developing resistance to CDKI monotherapy is frequently seen in both preclinical and clinical studies. Hence, novel approaches are being evaluated, including dual kinase inhibitors. In the AML setting, most inhibitors target one or more CDKs and FLT3. AMG925 and FN-1501 inhibit FLT3 in combination with CDK4 and CDK2/4/6, respectively. Both drugs significantly induced apoptosis and anti-leukemic effects as well as ERK/AKT/Rb dephosphorylation in vitro and in vivo ,118.TG02, a pan CDK and FLT3 inhibitor, further targets JAK2. This inhibition promoted G1 arrest, apoptosis, and tumor regression in AML cell lines, in vivo models, and primary samples ,120,121.Additionally in myeloma, pan CDK/JAK/Src/AMPK/GSK3β inhibitor RGB-286638 achieved cytotoxicity in vitro and prolonged animal survival . BesidesStructural similarity of CDK ATP binding sites is a major challenge in the design and development of selective inhibitors. Proteolysis-targeting chimeras (PROTACs) are a novel approach of CDK elimination. These synthetic molecules comprise a ligand for the protein of interest, for example, CDK6, and another ligand which recruits E3 ligases. E3 ligases then induce ubiquitination and proteasomal degradation of the target structure. In a recent study of De Dominici et al. investigating BCR-ABL1-positive ALL, PROTAC YX-2-107 was designed to bind CDK4/6, reducing CDK6 enzymatic activity and inducing degradation in vitro. Further, S phase transition was suppressed and Rb and FOXM1 dephosphorylation was observed. In vivo, PROTAC YX-2-107 achieved a comparable or better reduced leukemia burden in PDX mice compared to palbociclib . AnotherNovel and innovative strategies like dual kinase inhibition or PROTAC design are important steps towards an improved targeted therapy. Further preclinical studies in syngeneic and xenograft models are needed to identify candidates with a high likelihood of proving beneficial in a clinical setting.A major challenge for receiving long-term disease free-survival in hematological diseases is successful targeting of the malignant niche in the bone marrow. The latter is a complex microenvironment in which hematopoietic stem cells interact with multiple non-hematopoietic cell types. Just like normal stem cells, leukemia stem cells, hosted in the stem cell niche, undergo self-renewal, can efflux drugs, and have a quiescent cell cycle status, which makes them difficult to target. Especially CDK6 plays a critical role in hematopoietic stem cell differentiation . A compaIschemia-like conditions are the driving force of leukemia stem cell refractoriness to classical drugs as well as targeted agents, such as imatinib mesylate . Though The field of hematological neoplasms is very heterogeneous with each entity featuring individual characteristics and challenges. However, most of them are still difficult to treat, indicated by high relapse rates, intimidating prognoses, and lack of durable curative therapies. CDKs and their regulating cyclins are of major importance for the tumorigenic potential of developing leukemia or lymphoma cells and frequently dysregulated in those malignancies. Modulation of CDK expression and activity thus represents a promising strategy to target aberrant cell cycle progression and proliferation in hematological tumor cells.The results of extensive preclinical evaluations are promising, with several clinical studies currently testing CDKIs in most hematological malignancies. CDK4/6Is palbociclib, abemaciclib, and ribociclib are already FDA-approved for solid neoplasms, raising hopes for a subsequent clinical implementation in hematological malignancies in the near future. Interestingly, clinical trials have mainly been finished for lymphoma  and CLL patients while data on acute leukemias are lagging behind. Published results indicate that combined therapy with other small molecule inhibitors like ibrutinib or bortezomib as well as inhibitors of anti-apoptotic proteins may have the capacity to circumvent CDKI resistance development. Importantly, most clinical studies so far have been conducted in heavily pretreated relapsed/refractory patient cohorts, highlighting the potential of CDK targeting for hematological malignancy management. Another open question that must be addressed in future studies is why inhibitors of the same class result in highly variable response rates in the same entity. This underlines the importance of further investigation on biomarkers, resistance mechanisms, and exact modes of action.This is an exciting period potentially improving the therapeutic outcome of leukemia and lymphoma patients; however, there are still unanswered questions and several issues to be addressed. Clinical data on acute leukemias are still missing while results in other entities are ambiguous or obtained from rather small cohorts. Appropriate combination partners need to be identified, ideal application sequences and dosages are to be evaluated, and biomarkers are necessary to offer a useful and potent CDKI-based therapy for the special needs of every molecular subgroup in a variety of hematological entities.


In many human cancers, the rate of cell growth depends crucially on the size of the tumor cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations from three patient-derived brain tumor cell lines grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy. A common feature of tumor growth is the production, by the cancer cells themselves, of hormones known as growth factors that increase the rate of cell division. This type of signalling makes the growth rate of the tumor depend on the population size in a non-linear manner, and the growth rate might become low or negative for small population sizes. This is known as the Allee effect which has been studied extensively in ecology. We have developed a computational model that can explain the Allee effect in terms of growth factor signalling, and show by mathematical analysis of the model that the magnitude of the Allee effect depends on the ratio of cell death to proliferation, as well as the properties of the growth factor. In addition we show that the model is consistent with experimental observations from three different cell lines derived from the brain tumor glioblastoma. Our findings indicate that the Allee effect can be exploited in order to improve the treatment of glioblastoma patients. Cancer growth is increasingly understood as an ecosystem, in which the different cellular components not only grow, but also interact. Such cellular interactions were originally proposed by Laird  and the One such nonlinear growth behavior, with strong empirical support, is the Allee effect. A central idea in ecological population dynamics, the Allee effect denotes a per-capita growth rate that is reduced at low population densities . There iin vitro conditions in the lab at limiting densities . We. WeAIC=2el error . We thusA > μ implying a weak Allee effect, whereas for U3123MG we have μ > A which corresponds to a strong Allee effect. These differences can also been seen in When comparing the optimal parameters for the cell lines we note that for U3013MG and U3289MG we have We have proposed a mathematical model to explain the Allee effect, a phenomenon observed in many experimental datasets of cancer cell population dynamics. Our model, which posits that autocrine secreted growth factors increase the rate of cell division, yields population dynamics that can exhibit a weak or strong Allee effect depending on the relationships between the model parameters. Fitting the model to a dataset of three patient-derived glioma cell lines showed that a parameter setting with an Allee effect provided the best fit.α and EGF [Due to the large heterogeneity between patient-derived cell lines coupled to the experimental difficulties of measuring growth factor production and decay, we chose an approach where we used the IB-model as a means of showing that an Allee effects is possible. This observation was confirmed by our experimental data, but parametrizations of individual experiments remain difficult. Additional experiments to measure, e.g. the rate of growth factor production and its precise impact on cell division would be needed, as these two parameters are not identifiable in the ODE model. The situation is further complicated by the fact that several distinct growth factors have been identified as autocrine signals in glioblastoma, e.g. TGF- and EGF .In recent years many studies have focused on the Allee effect in cancer, either in an effort to understand its origin or to investigate how the effect can be therapeutically exploited . For exaemergence of Allee effects based on a feasible bio-physical mechanism such as secretion and uptake of growth-stimulating molecules. Thus, our integrative framework here complements these results by directly showing that autocrine signalling induced, and density-dependent feedback, can have detrimental effects on the per-capita growth rate of the cell population. We showed that this type of interaction is plausible to generate an Alee effect, integrating an analytical framework with agent based modeling and novel experimental results.Neither of the above mentioned results were directly linked to production and consumption of secreted factors. Böttger et al.  approachβ, EGF) and is beyond the scope of this paper.We provide a mechanistic explanation for a density-dependent proliferation rate in terms of local growth factor concentration. Mathematical analysis of the individual-based model allowed for the derivation of an ODE-model whose coefficients depend on the IB-model parameters. Our ODE-model was fitted to experimental data, and we found that a model which included an Allee effect best explained the empirical observations, in accordance with a previously observed weak Allee effect in breast cancer cell populations . These aAnother way of testing the hypothesis put forth is to investigate the impact of local cell density on the rate of cell division on the cell lines considered in this study. Given microscopy time-lapse data it should possible to estimate the impact of neighbouring cells on the rate of division. An inferred rate of division as an increasing function of the number of neighbouring cells would lend strong support to a localised interaction (e.g. a diffusing GF) as the potential origin of the Allee effect.In light of cancer therapy, a strong Allee effect would be more beneficial for the ability to control a tumor, since the strong effect leads to population extinction at critically low population densities. Such conditions are typically present after therapeutic interventions (e.g. surgery and radiotherapy). If the population dynamics could be tipped towards a strong Allee effect during therapy, similar to an extinction threshold , one couIn conclusion, our findings provide a general model for the population dynamics of cancer cells driven by autocrine signaling. We provide a possible mechanistic explanation for the ubiquitous Allee effect. Further, our findings warrant more research into the therapeutic benefits of altering the effects of autocrine signaling to understand and achieve tumor control.S1 Supplementary MethodsFig A: The confluence plotted against the cell count for a single well across all time points. Fig B: The mean squared displacement as a function of time averaged across all cells in a single well. The dashed line shows the best fit for a line with intercept y = 0. The slope of the line equals 4D, where D is the diffusion coefficient of the cells.(PDF)Click here for additional data file.


CDKN2A variants are associated with an increased risk of pancreatic ductal adenocarcinoma (PDAC). CDKN2A variants of uncertain significance (VUSs) are reported in up to 4.3% of patients with PDAC and result in significant uncertainty for patients and their family members as an unknown fraction are functionally deleterious, and therefore, likely pathogenic. Functional characterization of CDKN2A VUSs is needed to reclassify variants and inform clinical management. Twenty-nine germline CDKN2A VUSs previously reported in patients with PDAC or in ClinVar were evaluated using a validated in vitro cell proliferation assay. Twelve of the 29 CDKN2A VUSs were functionally deleterious (11 VUSs) or potentially functionally deleterious (1 VUS) and were reclassified as likely pathogenic variants. Thus, over 40% of CDKN2A VUSs identified in patients with PDAC are functionally deleterious and likely pathogenic. When incorporating VUSs found to be functionally deleterious, and reclassified as likely pathogenic, the prevalence of pathogenic/likely pathogenic CDKN2A in patients with PDAC reported in the published literature is increased to up to 4.1% of patients, depending on family history. Therefore, CDKN2A VUSs may play a significant, unappreciated role in risk of pancreatic cancer. These findings have significant implications for the counselling and care of patients and their relatives.Pathogenic germline  ATM, BRCA1, BRCA2, CDKN2A, CPA1, CPB1, MLH1, MSH2, MSH6, PALB2, PMS2, PRSS1, and STK11, has the potential to reduce mortality through detection of early, potentially curable, PDAC and its precursor lesions  during a median follow-up 53 months  is a lethal cancer with a median survival of less than 6 months and a 5-year survival rate of only 10% . Surveil lesions . The Int lesions . Similar3 months . Importa3 months . Further3 months . Consequ3 months .CDKN2A gene encodes two proteins, p16INK4a and p14ARF. p16INK4a inhibits CDK4 activity, is a regulator of cell cycle progression, and a tumor suppressor gene (CDKN2A that affect p16INK4a (hereafter referred to CDKN2A variants) can be classified as either pathogenic, benign, or variants of uncertain significance (VUSs) based on American College of Medical Genetics (ACMG) guidelines  p16INK4a, but do not inhibit cell proliferation, indicating that additional functions not assessed in vitro CDK4 binding are important for cellular function  was not detectable in PANC-1 cells by western blot  is a human PDAC cell line with a homozygous deletion of CDKN2A . Consistern blot . Stable ern blot . Convers control .CDKN2A VUSs, we next determined cell proliferation values for an additional six known pathogenic and six known benign variants in our assay. Known pathogenic and benign variants are likely functionally deleterious and functionally neutral, respectively, in our assay and were used as benchmarks for interpretation of CDKN2A VUSs. The mean cell proliferation value for all pathogenic variants assayed was 0.90 (range: 0.84–1.03), while the mean cell proliferation value for all benign variants assayed was 0.26 (range: 0.14–0.48)  . Importa14–0.48) .CDKN2A VUSs. These VUSs were selected because they were either reported in previously published studies in patients with PDAC and/or were reported in ClinVar  using two additional PDAC cell lines with homozygous deletions of CDKN2A: MIA PaCa-2  and AsPC-1   . Westernell line . Importaell line . In MIA ell line . In AsPCell line . Importaell line . When coell line .As reintroduction of CDKN2A into cancer cells lacking CDKN2A delays cell cycle progression, we determined the percent of variant-expressing PANC-1 cells in G1, G2/M, and S phases of the cell cycle . The perCDKN2A VUSs assayed had previously reported functional data available  of the 17 CDKN2A VUSs identified in a study of 638 patients with familial pancreatic cancer  in patients with familial pancreatic cancer, 0.9% (95% CI: 0.5–1.8%) in patients with PDAC positive family history of PDAC , and 0.1% (95% CI: 0.02–0.3%) in PDAC patients unselected for family history. When incorporating functionally deleterious VUSs we have reclassified as likely pathogenic variants with known pathogenic variants in CDKN2A, the cumulative prevalence of pathogenic and likely pathogenic CDKN2A variants in these studies increased from 2.5% to 4.1% (95% CI: 2.8–5.9%) in patients with familial pancreatic cancer, from 1.7% to 2.7% (95% CI: 1.9–3.9%) in patients with PDAC who had a positive for a family history of the disease , and from 0.7% to 1.0% (95% CI: 0.6–1.7%) in PDAC patients unselected for family history.As we assayed all CDKN2A VUSs are identified in up to 4.3% patients with PDAC and are the cause of significant clinical uncertainty. Individuals with a CDKN2A VUS are not currently eligible for surveillance unless they meet other family history criteria. We used a cell proliferation assay to functionally characterize germline CDKN2A VUSs identified in patients with PDAC and/or reported in ClinVar and provide evidence to reclassify variants into clinically actionable strata.Germline CDKN2A variants previously classified as VUS were functionally deleterious in our assay and could be reclassified as likely pathogenic variants . When considering CDKN2A VUS identified in patients with PDAC, our results suggest that the prevalence of CDKN2A VUSs that are functionally deleterious is up to 1.6% in patients with PDAC, depending on family history. It should be noted, however, that we characterized only missense CDKN2A VUS in our assay. Functional characterization of other types of CDKN2A VUS, such as synonymous variants, in-frame indels, and non-coding variants, would refine these estimates.We found that over 40% of CDKN2A VUSs that are functionally deleterious in patients with PDAC reported in previously published literature. Overlap of patient cohorts between these studies may affect estimates of prevalence. Regardless, we can conclude that functionally deleterious CDKN2A VUSs are likely to play a significant and previously unappreciated role in risk of PDAC, particularly for patients with a family history of the disease. Studies to define age-specific penetrance estimates for individuals with a pathogenic germline CDKN2A variant, including functionally deleterious variants previously classified as VUSs, are necessary and will inform genetic counselling, surveillance, and early detection efforts.Furthermore, we determined the prevalence of germline VUS functional characterizations were generally consistent when using PANC-1, MIA PaCA-2, and AsPC-1 cells in our cell proliferation assay. Specifically, no variant found to be functionally deleterious or potentially functionally deleterious when assayed with one cell line, had a functionally neutral or potentially functionally neutral classification when assayed with another cell line. Furthermore, PDAC cell lines had different genetic alterations and degrees of ploidy  indicatiCDKN2A variants classified as pathogenic, functionally deleterious, or potentially functionally deleterious do not control progression through the cell cycle.Consistent with our functional classifications, we found that benchmark pathogenic variants and VUSs classified as functionally deleterious or potentially functionally deleterious had a significantly lower percent of cells in G1 phase and a significantly higher percent of cells in G2/M phase of the cell cycle compared to either benchmark benign variants or VUSs classified as functionally benign or potentially functionally benign. These data suggest that expression of CDKN2A VUSs with previously published data. In general, our assay results were consistent with previous reports. However, assay results for two VUSs, p.Gly67Arg and p.Glu69Gly, were inconsistent with previously reported partial reduction in CDK4 binding. There are several explanations for these observations. First, our assay is of broad cellular function, specifically cell proliferation, and therefore, may encompass functions other than CDK4 binding. Second, it is possible that overexpression of CDKN2A variants with partial loss-of-function may be obscured in our assay by non-physiological levels of expression. Future studies to correlate CDK4 binding with pathogenicity and to develop of functional assays that utilize endogenous promoters and enhancers would provide further clarity.We were also able to compare our assay results for five CDKN2A VUSs identified in patients with PDAC or reported in ClinVar using a validated functional assay. We found that over 40% of CDKN2A VUS assayed were, in fact, functionally deleterious and as a result can be reclassified as likely pathogenic using ACMG guidelines. This finding may have significant implications for the management of patients with PDAC, and their relatives found to have a CDKN2A VUS.In conclusion, we functionally characterized and reclassified 29 PANC-1 , MIA PaCa-2 , and AsPC-1 , and the human embryonic kidney cell line 293T  were purchased from American Type Culture Collection . PANC-1, MIA PaCa-2, and 293T cells were maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum. AsPC-1 cells were maintained in RPMI-1640 supplemented with 10% fetal bovine serum. Cell line authentication and mycoplasma testing of PDAC cell lines was performed using GenePrint 10 System  and a PCR-based MycoDtect kit , respectively, by the Genetics Resource Core Facility of The Johns Hopkins University School of Medicine, Baltimore, MD.INK4A at a 1:1000 dilution . Western blotting data and images presented are representative of at least three independent experiments.Western blots were performed as previously described with the following modifications : (1) antCDKN2A and CDKN2A-L78Hfs*41 cDNAs were subcloned into the pLJM1-Empty from pHAGE-CDKN2A and pHAGE-CDKN2A-L78Hfs*41, respectively, using the Q5 High-Fidelity PCR kit  as previously described  and Sanger sequencing . Restriction enzyme, EcoRI-HF digest was performed with CutSmart Buffer  at 37°C for 15 min. Expression constructs for each assayed CDKN2A variant were produced from the pLJM1-CDKN2A using the Q5 Site-Directed Mutagenesis kit . Primers used to generate each CDKN2A variant expression plasmids are given in CDKN2A VUS was confirmed using Sanger sequencing . The manufacturer’s protocol was followed unless otherwise specified.pHAGE-CDKN2A  and pHAGE-CDKN2A-L78Hfs*41  created by Gordon Mills & Kenneth Scott , and pLJescribed . PrimersCDKN2A cDNA (WT or variant) and the lentiviral packaging vectors, psPAX2  and pCMV-VSV-G , created by Didier Trono and Bob Weinberg, respectively  or selected variants were generated by lentiviral transduction. Briefly, 1 × 105 cells were cultured in media supplemented with 10 µg/ml polybrene and transduced with 10 TUs/ml lentivirus particles. Cells were then centrifuged at 1200× g for 1 hr. After 48 hr of culture at 37°C and 5% CO2, transduced cells were selected by culture in media containing 3 µg/ml puromycin for PANC-1 cells and 1 µg/ml puromycin for MIA PaCa-2 and AsPC-1 cells for 7 days.PANC-1, MIA PaCa-2, and AsPC-1 cells stably expressing WT CDKN2A  and cell numbers were counted using a TC20 Automated Cell Counter  on day 7 for MIAPaCa-2 cells, and day 14 for PANC-1 and AsPC-1 cells. Cell numbers were normalized to empty vector transduced cells to give a relative cell proliferation value. Assays to determine the functional effect of CDKN2A variants were repeated in triplicate. Mean cell proliferation value and standard deviation (s.d.) were calculated.1 × 10CDKN2A VUSs were functionally characterized into four categories: (1) deleterious, (2) potentially deleterious, (3) potentially neutral, and (4) neutral, based on the results of the cell proliferation assay using previously described methodology  and the FxCycle Violet Ready Flow Reagent  according to the manufacturer’s protocols. Flow cytometry was performed on Cytek Aurora Flow Cytometry System  and the data analyzed to determine the percentage of cells in each phase of the cell cycle using the FlowJo software .CDKN2A variants were calculated using the modified Wald Method. A p-value less than 0.05 considered statistically significant.Statistical analyses were performed using JMP v.11  and Prism v.6 . Comparison of means used the Student’s t test. CIs for the prevalence of functionally deleterious  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Decision letter after peer review:eLife. Your article has been reviewed by 2 reviewers, one of whom is member of our Board of Reviewing Editors and the evaluation has been overseen by Wafik El-Deiry as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for resubmitting your work entitled "Functional CDKN2A assay identifies frequent deleterious alleles misclassified as variants of unknown significance" for further consideration by The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:Reviewer #1:The investigators postulated that some variants of uncertain significance (VUS) of CDKN2A have been misclassified, and that some proportion may be in fact be deleterious and possibly pathogenic in carcinogenesis of pancreatic ductal adenocarcinoma (PDAC). in vitro analysis of cell proliferation of 29 known VUSs was performed, and the authors report that >40% of these variants are functionally deleterious.CDKN2A encodes a tumor suppressor as well as an important regulator of progression through the cell cycle. It has been extensively studied in epithelial carcinomas, including pancreatic ductal adenocarcinomas (PDAC). The concept that a significant number of previously reported variants of this gene may not be as benign has important implications for understanding etiology and downstream molecular effects and tumoral progression of this cancer, especially in the albeit relatively small number of patients who harbor germline variants that may be important in driving pancreatic cancer development. The study is well-written and leverages an established and validated in vitro cell proliferation assay from this lab.1. The information redesignating 40% of the VUS as functionally deleterious and possibly pathogenic is applied to external datasets. Did the investigators gain access to the raw data from the authors of the cited published works, or were the reassignments based on available information that was published? It would be important to access and confirm the raw data.2. Application to an internal dataset of tumor samples would affirm the conclusions made from the in vitro validation steps.3. The use of only a single PDAC cell line is a limitation that tempers the conclusions of the study .The in vitro analysis should be performed on at least three cell lines to control for other differences between cell lines. This work would strengthen the argument, as the premise of the study is to extend the finding to in vivo/human PDAC, with implications that the reassigned germline VUSs are more pathogenic in humans than previously thought.Reviewer #2:The study provides evidence of functionality of mutations present in pancreatic cancer, a dismal condition predicted be the second cause of cancer death by 2030. Specifically, the authors showed that mutations in CDKN2A associated with increased risk of developing pancreatic cancer have lost the ability to control cell growth.The authors have functionally characterized CDKN2A mutations present in familial pancreatic cancer cases. The methodology used is for the most adequate to address the main goal of the study. Some of the deficiencies/weaknesses are associated with limitations of the pancreatic cancer model/methodologies and lack of side by side comparison with other known factors associated with increased risk of the disease as well as clinical correlations of these mutations.To fully support the authors conclusions, the authors should1) The Panc1 results should be repeated in two additional lines to avoid any cell line bias effect.2) The cell growth analysis should be confirmed using a cell cycle analysis to define if the mutants lack the ability to control G1 progression.3) The study should include side-by-side comparison with other know p16 mutations from familial cases. Reviewer #1:The investigators postulated that some variants of uncertain significance (VUS) of CDKN2A have been misclassified, and that some proportion may be in fact be deleterious and possibly pathogenic in carcinogenesis of pancreatic ductal adenocarcinoma (PDAC). in vitro analysis of cell proliferation of 29 known VUSs was performed, and the authors report that >40% of these variants are functionally deleterious.CDKN2A encodes a tumor suppressor as well as an important regulator of progression through the cell cycle. It has been extensively studied in epithelial carcinomas, including pancreatic ductal adenocarcinomas (PDAC). The concept that a significant number of previously reported variants of this gene may not be as benign has important implications for understanding etiology and downstream molecular effects and tumoral progression of this cancer, especially in the albeit relatively small number of patients who harbor germline variants that may be important in driving pancreatic cancer development. The study is well-written and leverages an established and validated in vitro cell proliferation assay from this lab.1. The information redesignating 40% of the VUS as functionally deleterious and possibly pathogenic is applied to external datasets. Did the investigators gain access to the raw data from the authors of the cited published works, or were the reassignments based on available information that was published? It would be important to access and confirm the raw data.We are happy to clarify. Several authors of this manuscript were also authors of the cited published works used to identify VUS for assay. These authors were extensively involved in the analysis and interpretation of these variant data. The cited studies included research next-generation sequencing (whole genome and gene-panel), Sanger sequencing, and CLIA approved clinical genetic testing that have high-confidence for single base substitution calls. As such, we are confident in the VUS calls used in this manuscript.2. Application to an internal dataset of tumor samples would affirm the conclusions made from the in vitro validation steps.CDKN2A loss-of-heterozygosity with retention of the deleterious variant (supporting evidence) or somatic loss of the deleterious variant (refuting evidence). However, even without tumor samples, we present additional experimental evidence to support our functional characterizations (see below).We thank the reviewer for their suggestion. We agree that analysis of tumor samples might provide additional evidence to validate functional characterizations. Unfortunately, only ~10% of patients with pancreatic ductal adenocarcinoma undergo resection and have tissue available for correlative studies. We were unable to identify any tumor tissue for patients with functionally deleterious or potentially functionally deleterious VUS where additional studies would be informative, for example, somatic 3. The use of only a single PDAC cell line is a limitation that tempers the conclusions of the study .The in vitro analysis should be performed on at least three cell lines to control for other differences between cell lines. This work would strengthen the argument, as the premise of the study is to extend the finding to in vivo/human PDAC, with implications that the reassigned germline VUSs are more pathogenic in humans than previously thought.CDKN2A variants  in two additional cell lines (MIA PaCa-2 and AsPC-1). Reassuringly, no VUS with a functionally deleterious or potentially functionally deleterious classification in one cell line had a functionally neutral or potentially functionally neutral classification in the other cell lines tested. Furthermore, cell cycle analysis to determine the distribution of cells in each stage of the cell cycle provides support for our functional classifications. These additional data indicate that our functional classifications are robust to cell lines specific effects included ploidy and genetic background.We are happy to provide the additional experimental data requested by the reviewer. We have now assayed selected Reviewer #2:The study provides evidence of functionality of mutations present in pancreatic cancer, a dismal condition predicted be the second cause of cancer death by 2030. Specifically, the authors showed that mutations in CDK2A associated with increased risk of developing pancreatic cancer have lost the ability to control cell growth.The authors have functionally characterized CDK2A mutations present in familial pancreatic cancer cases. The methodology used is for the most adequate to address the main goal of the study. Some of the deficiencies/weaknesses are associated with limitations of the pancreatic cancer model/methodologies and lack of side by side comparison with other known factors associated with increased risk of the disease as well as clinical correlations of these mutations.To fully support the authors conclusions, the authors should1) The Panc1 results should be repeated in two additional lines to avoid any cell line bias effect.CDKN2A variants  in two additional cell lines (MIA PaCa-2 and AsPC-1). Reassuringly, no VUS with a functionally deleterious or potentially functionally deleterious classification in one cell line had a functionally neutral or potentially functionally neutral classification in the other cell lines tested.We are happy to provide the additional experimental data requested by the reviewer. We have now assayed selected 2) The cell growth analysis should be confirmed using a cell cycle analysis to define if the mutants lack the ability to control G1 progression.We thank the reviewer for this suggestion. We have completed cell cycle analysis to determine the distribution of cells in each stage of the cell cycle for each assayed variant in PANC-1 cells. These data provide clear support for our functional classifications and indicate that expression of pathogenic or functionally deleterious variants do not inhibit cell cycle progression. Specifically, pathogenic and functionally deleterious variants had a lower percentage of cells in G1 phase and a higher percentage of cells in G2/M phase compared to benign and functionally neutral variants.3) The study should include side-by-side comparison with other know p16 mutations from familial cases.We are grateful for the opportunity to clarify. The majority of pathogenic germline variants tested in our assay were either identified in patients with familial pancreatic cancer (5 of 9 variants) or in patients with pancreatic adenocarcinoma (2 of 9). Furthermore, these variants were classified as pathogenic using American College of Medical Genetics variant interpretation guidelines. As such, our assay has broad applicability to patients with pancreatic cancer.


Obesity, a physiological situation where different proinflammatory cytokines and hormones are secreted, is a major risk factor for breast cancer. Mitochondrial functionality exhibits a relevant role in the tumorigenic potential of a cancer cell. In the present study, it has been examined the influence of an obesity-related inflammation ELIT treatment , which aims to stimulate the hormonal conditions of a postmenopausal obese woman on the mitochondrial functionality and invasiveness of MCF7 and T47D breast cancer cell lines, which display a different ratio of both estrogen receptor isoforms, ERα and ERβ. The results showed a decrease in mitochondrial functionality, with an increase in oxidative stress and invasiveness and motility, in the MCF7 cell line (high ERα/ERβ ratio) compared to a maintained status in the T47D cell line (low ERα/ERβ ratio) after ELIT treatment. In addition, breast cancer biopsies were analyzed, showing that breast tumors of obese patients present a high positive correlation between IL-6 receptor and ERβ and have an increased expression of cytokines, antioxidant enzymes, and mitochondrial biogenesis and dynamics genes. Altogether, giving special importance to ERβ in the pathology of obese patients with breast cancer is necessary, approaching to personalized medicine. Cancer, a pathology characterized by the excessive proliferation of tumor cells, is the second cause of death in the world, responsible for approximately 9.6 million deaths in 2018. In addition, breast cancer is a disease causing more than half a million deaths annually, projecting an increase in its incidence to a total of 3.2 million new cases per year in 2050 [Obesity is a chronic metabolic disease characterized by excess fat accumulation in the body, and its prevalence has increased markedly in the last two decades in the most developed countries . In obesThe cellular effects of estrogens are mediated by their binding to estrogen receptors (ER) alpha (ERα), beta(ERβ), and GPER. Although ERα and ERβ show homology in the DNA and ligand-binding domains, their activity and affinity for 17β-estradiol are different, with ERα having a higher affinity for it. In addition, the expression pattern of the receptors also varies according to the cell type ,9,10. ERAnother adipokine synthesized and secreted by adipocytes is leptin, whose circulating levels are directly correlated with the individual’s BMI . Leptin It is worth noting that obesity is considered an inducing factor of inflammation, where adipose tissue takes on the role of producer of cytokines and inflammatory proteins. However, the biochemical role between inflammation and cancer-inducing cellular modifications has not yet been elucidated . In thisThe expression of inflammatory cytokines, such as interleukin-6 (IL6) and Tumor necrosis factor alpha (TNFα), have been related to an increase in invasiveness and a poor prognosis in breast cancer . IL6 is Mitochondria is a cellular organelle that is highly influenced in response to estrogens, and it is the main source of reactive oxygen species (ROS), playing an important role in tumor processes, as well as in proliferation and apoptosis ,21,22. TMitochondrial function depends on mitochondria morphology, changes in shape, number, and location, which can translate into important functional modifications. Thus, mitochondrial biogenesis is the combination of both proliferation  and differentiation  processes , while mMitochondrial structure and function can be regulated by the activation of ERα and ERβ receptors by binding of 17β-estradiol ,26. RegaDysfunctional mitochondria play a relevant role in cancer and in the epithelial-to-mesenchymal transition (EMT) program in breast cancer . As a coThe aim of the present work was to study mitochondrial functionality and invasiveness, analyzing mitochondrial biogenesis and dynamics processes, as well as oxidative stress and inflammatory status and motility, in cell lines with different estrogen receptors ratio, exposed to a treatment consisting of 17β-estradiol, leptin, IL-6, and TNFα simulating circulating hormonal conditions in a postmenopausal obese woman ,32,33 LiSpecific reagents 17β-estradiol, leptin, interleukin-6, and TNF-α were purchased from Sigma-Aldrich . Dulbecco’s modified Eagle’s medium without phenol red was purchased from GIBCO , Fetal Bovine Serum, and antibiotics solution (penicillin and streptomycin) from Biological Industries . Routine chemicals were supplied by Sigma-Aldrich , Panreac , and Bio-Rad Laboratories .2. To avoid phenol red estrogenic effect, cells were seeded in 6-well or 96-well plates in phenol red-free DMEM containing 10% FBS and 1% antibiotics 24 h prior to treatment. Cells were treated, at 70–80% confluence, with vehicle (0.1% DMSO) or ELIT treatment  for 24 or 48 h.MCF7 and T47D breast cancer cell lines were purchased from American Type Culture Collection ATCC  and maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% Foetal bovine serum (FBS) and 1% antibiotics (penicillin and streptomycin) at 37 °C with 5% CO4 cells/well for MCF7 and 3.2 × 104 cells/well for T47D cell line) and treated with ELIT for 48 h. Hydrogen peroxide production was determined by Amplex® Red Hydrogen Peroxide/Peroxidase Assay Kit, following the manufacturer’s protocol, as described previously [® Red reagent, following the manufacturer’s protocol, as described previously [Cells were seeded in 96-well plates  and treated with ELIT for 48 h. Cells were stained with 250 nM of Nonyl Acridine Orange (NAO) to measure cardiolipin content as previously described [Cells were seeded in 96-well plates  in 6-well plates and treated with ELIT for 24 h. Total RNA from cultured cells or breast cancer human biopsies (25 mg) was isolated using TRI Reagent , following the manufacturer’s protocol, and then quantified using a BioSpec-nano spectrophotometer  set at 260 nm and 280 nm, getting 260/280 nm ratio. Samples were retrotranscribed to cDNA, and PCR reactions were carried out as previously reported [Cells were seeded . Membranes were blocked in 5% non-fat powdered milk in TBS with 0.05% Tween for 1 h. Antisera against OXPHOS complexes , SOD-1 , SOD-2 , CAT , GRd , 4-HNE , COXIV , PGC1α , and GAPDH  were used as primary antibodies. Protein bands were visualized as described previously by [After 48 h of ELIT treatment, cells were harvested as described previously by Torrens-Mas . Proteinously by .For 4-hydroxy-2-nonenal (4-HNE) adducts analysis, as lipid oxidative damage marker, 20 μg of total protein from cell lysate, processed as previously described by Pons et al. .6 cells/well for T47D cell line and 8.5 × 105 cells/well for MCF7 cell line. Wound healing assay was performed as previously described by Torrens-Mas et al. [Cells were seeded in six-well plates at a density of 1 × 10s et al. . The are5 cells/well for MCF7 and 5 × 105 cells/well for T47D. After 24 h, cells were treated with ELIT treatment for 24 h. Then, cells were incubated with MitoTracker™ Green 0.5 µM  for 1 h and LysoTracker™ Red 0.5 µM  for 20 min, both at 37 °C in the dark. For DNA staining, cells were incubated with 1/200 dilution of 1 μg/mL Hoechst 33342  for 5 min at 37 °C in the dark.Cells were seeded on a glass coverslip inside 6-well plates at a density of 2 × 10The fluorescence was monitored with a Leica TCS-SPE Confocal Microscope, using 63× immersion oil (147 N.A.) objective lens. Fluorescence excitation/emission was 490/516 nm for MitoTracker Green, 577/590 for LysoTracker Red, and 350/455 nm for Hoechst 33342.Mitochondrial Roundness was analyzed in ImageJ software with Mito-Morphology Macro designed by Ruben K. Dagda at the University of Pittsburgh (2010). This macro is currently maintained and supported by grants NIH/NINDS R01NS105783-01 grant and by NIH/NIGMS R25 1R25-OD023795-01.3 cells/well for MCF7 and 9.600 cells/well for T47D into XFe96 well cell culture plates and incubated overnight to allow attachment at 37 °C in 5% CO2. After 24 h, cells were incubated with vehicle or ELIT treatment. After 48 h of incubation, cells were maintained in 200 μL/well of XF assay media at 37 °C, in a non-CO2 incubator for 1 h. During the incubation time, mitochondrial complex inhibitors  were preloaded for OCR measurements, in XF assay media into the injection ports in the XFe96 sensor cartridge.Real-time oxygen consumption rates (OCRs) were determined for MCF7 and T47D cells using the Seahorse Extracellular Flux (XFe96) analyzer . Cells were seeded at a density of 4.8 × 102).Human breast cancer biopsies were obtained from 33 women, ages between 45–90 years. Samples of these patients were obtained from the Biological Specimen Bank of Son Llàtzer Hospital and as specified by and with the necessary permission granted from the Balearic Island Bioethics Committee. Tumor samples were collected immediately after tumor removal and were frozen in isopentane for analysis as described by Sastre-Serra et al. . Writtent-test with statistical significance was set at p < 0.05 (*). The statistical differences in human samples were analyzed using Pearson’s correlation with statistical significance was set at p < 0.01 (**) and p < 0.05 (*).The statistical analyses were performed with the Statistical Programme for the Social Sciences software for Windows . Data are presented as mean ± standard error of the mean (SEM). The statistical differences in cell lines between vehicle- and ELIT-treated cells were analyzed using a Student’s IL6, IL6R, CXCL8, PTGS2, TNF, and STAT3) showed a statistically significant increase in both MCF7 and T47D cell lines after 24 h of ELIT (17β-estradiol (10 nM), leptin (100 ng/mL), interleukin-6 (50 ng/mL), and TNFα (10 ng/mL)) treatment. In contrast, PPARG anti-inflammatory gene had decreased expression in the MCF7 cell line, and TGFB anti-inflammatory gene showed a statistically significant increase in the T47D cell line.To confirm the obesity-related inflammation treatment effectivity, mRNA expression of main inflammatory genes was determined. As shown in 2O2 production increased in both cell lines (+100% in MCF7 and +34% in T47D cells). However, cardiolipin content, as an indicator of mitochondrial inner membrane quantity, decreased in MCF7 treated cells. Moreover, as shown in As shown in SOD2  showed a high increase in both cell lines; in addition, a decrease in SOD1 (copper/zinc superoxide dismutase) was observed. However, ELIT-treated MCF7 cells showed a general decrease in catalase (CAT) and glutathione reductase (GSR). Nevertheless, in the T47D cell line, ELIT treatment increased GSR and nuclear factor erythroid 2-related factor 2 (NFE2L2) expression, as shown in The mRNA expression of antioxidant enzymes was analyzed  in both Main antioxidant protein expression levels were determined  after 48ESRRA) and Twinkle (TWNK) were found in ELIT-treated cells versus non-treated cells. Moreover, uncoupling proteins 2 and 5  mRNA expression was analyzed, and a decrease in UCP2 expression in both cell lines was accompanied by a decrease in uncoupling protein 5 expression in the MCF7 cell line.Mitochondrial biogenesis genes were also checked, as shown in Mitochondrial biogenesis master regulator PPARGC1A protein levels increased after ELIT treatment in the MCF7 cell line. However, to check the effect of ELIT treatment on the mitochondrial respiratory chain (OXPHOS), protein levels of these OXPHOS complexes were analyzed. As seen in To further investigate mitochondrial function, the oxygen consumption rate (OCR) was determined. As shown in MFN1, MFN2, OMA1, OPA1 showed decreased levels in the MCF7 cell line, whereas, in the T47D cell line, ELIT treatment increased expression of MFN1, MFN2, and OMA1. Fission-related mitochondrial genes presented a different pattern expression between cell lines, with a statistically significant increase in FIS1 mRNA expression in the T47D cell line after ELIT treatment.As shown in On the one hand, mitochondrial networking was modified after 24 h-ELIT treatment in both MCF7 and T47D cell lines. However, as shown in CDH1) expression was decreased in MCF7 cells after 24 h ELIT treatment, but Matrix Metalloproteinase 9 (MMP9) expression increased three times with respect to vehicle-treated cells. In contrast, CDH1 expression increased in the T47D cell line after treatment. In addition to these results, a wound-healing assay was performed. As shown in As shown in ESR1) mRNA expression was decreased in both cell lines after 24 h-ELIT treatment. However, estrogen receptor beta (ESR2) and GPER (GPER1) mRNA expression only shown a decrease in the MCF7 cell line, maintaining its expression in the T47D cell line.To observe the effects of obesity-related inflammation treatment over estrogen receptors alpha (ERα), beta (ERβ), and GPER in MCF7 and T47D breast cancer cell lines, mRNA expression was analyzed. As shown in CXCR8, CXCL8, TNF, SLC25A14, NRF1, NFE2L2, PPARGC1A, and FIS1 were significantly and positively correlated with IL6R expression in the nw group. CXCR8, TNF, SLC25A14, NRF1, NFE2L2, and PPARGC1A were significantly and positively correlated with IL6R expression in the ow group. CXCR8, CXCL8, TNF, PTGS2, ESR2, GPX1, SOD1, SLC25A14, NRF1, NFE2L2, PPARGC1A, SIRT1, FIS1, and OMA1 were significantly and positively correlated with IL6R expression in the ow group.ESR1 and ESR2 gene expression correlations are shown in IL6, CXCL8, SOD1, and SSBP1 were significantly and negatively correlated with ESR1 expression; instead, SIRT3 was significantly and positively correlated. On the other hand, IL6R, CXCR8, GPX1, SLC25A14, NRF1, PPARGC1A, SIRT1, and OMA1 were significantly and positively correlated with ESR2 expression.Moreover, In this study, the effects of obesity related-inflammation on mitochondrial functionality in breast cancer cell lines and breast tumors, focusing on estrogen receptors ratio, were analyzed. Moreover, invasiveness in this situation was also analyzed. We demonstrated that ERβ, in an inflammatory and obesity condition, maintains mitochondrial functionality and avoids invasiveness in breast cancer cell lines. Moreover, we found a strong correlation between interleukin-6 receptor gene expression and inflammation, mitochondrial functionality, and oxidative stress markers, as well as with estrogen receptor beta, in breast cancer human samples in different BMI situations. Obesity stimulates the adipose tissues to release inflammatory mediators such as tumor necrosis factor α and interleukin 6, predisposing them to a proinflammatory state and oxidative stress ,39. ThesPrevious studies in our group and other research groups have shown the independent effects of 17β-estradiol or leptin on oxidative stress and mitochondrial biogenesis and dynamics ,42,43,442O2 and superoxide anion, as similarly described by some authors [In this study, MCF7 and T47D cell lines have been treated with an ELIT inflammatory cocktail with the aim of generates an inflammation situation (IL6 and TNFα) in the presence of Leptin and 17β-estradiol levels, simulating the physiological condition of postmenopausal obese women. In this way, an increase in reactive oxygen species has been observed in both cell lines; however, in the T47D cell line, a lower increase in the production of hydrogen peroxide and levels of superoxide anion was observed. These data make more sense when studying the oxidative damage present in both cell lines, where a significant increase was only observed in the MCF7 cell line. On the other hand, it seems that the T47D treated cell line does not present differences compared to the control group, despite presenting higher levels of H authors ,45,46.NFE2L2, a transcription factor that controls mainly antioxidant enzymes expression, and glutathione reductase, which recycles glutathione, was also increased, avoiding a high increase in free radical levels in low ERα/ERβ ratio T47D cell line. In addition, it should be noted that those tumors with a high correlation between IL6R and ESR2 gene expression presented an increase in antioxidant enzymes, thus could palliate levels of free radicals, which can ultimately diminish oxidative damage.Oxidative stress is generated in breast cancer, and in many other pathologies, in two main ways. The first one, as observed in the high ERα/ERβ ratio MCF7 cell line after ELIt treatment, is a decrease in the expression of the antioxidant enzymes. It was observed that all antioxidant enzymes had decreased their gene or protein expression in the MCF7 cell line, except the SOD2 enzyme that had increased expression in both MCF7 and T47D cell lines. It has been described that SOD2 plays a role as a free radical detector, increasing gene and/or protein expression in order to alleviate oxidative damage [The other pathway that increases oxidative stress is the poor maintenance of a functional mitochondrial pool . To achiESRRA) and Twinkle (TWNK). ESRRA belongs to a superfamily of nuclear receptors independent of estrogen activation. Its expression is induced and activated by PGC1α, and the two factors together are capable of binding to response elements and promoting the initiation and elongation of the transcription of metabolic and mitochondrial target genes [However, the T47D cell line, with high levels of ERβ, had mitochondrial dynamics elevated, maintaining a more functional pool of mitochondria. In the case of mitochondrial biogenesis, it should be noted that there are two genes that presented a very significant elevation, estrogen-related receptor alpha (et genes . Twinkleet genes . In factet genes . Taking into account that patients with tumors with low ERα/ERβ ratios have a worse response to chemical agents oxidative damage inductors , we obseIn addition to mitochondrial biogenesis and dynamics, our study reveals an oxygen consumption rate decreased in the MCF7 cell line that supports all the results commented above. It is worth noting that ELIT treatment decreases basal respiration, maximal respiratory capacity, ATP-linked respiration as much as proton leak in the MCF7 cell line. Proton leak decrease is in concordance with low uncoupling proteins mRNA expression levels found in the MCF7 cell line after ELIT treatment. UCPs, which promote proton leak across the inner mitochondrial membrane, have emerged as essential regulators of mitochondrial membrane potential, respiratory activity, and ROS generation . As seenOxidative stress, inflammation, and poor mitochondrial network observed in MCF7 cell lines after ELIT treatment leads to a worse situation, and some authors have described a relationship between this situation and metastasis . Our resAs mentioned above, the MCF7 cell line has a higher ERα/ERβ ratio, and the T47D cell line has a lower ratio. ELIT-treatment decreases estrogen receptor alpha mRNA expression in both MCF7 and T47D cell lines, as shown in results. However, estrogen receptor beta mRNA expression only decreases in the MCF7 cell line but not in the T47D cell line. This fact supports that all the results showed in our study could be through estrogen receptor beta T47D cell lines maintenance, giving to this receptor subtype the protective role that previously some studies have been described ,39. The presence of estrogen receptor beta allows maintaining a more functional mitochondrial pool, with active mitochondrial biogenesis and dynamics, which means less production of reactive oxygen species and better mitochondrial metabolism in an obesity-related inflammation condition. In addition, antioxidant enzymes are active, preventing oxidative damage and, at least in part, invasiveness.This study could be important to remark the importance of estrogen receptor beta and mitochondria as an important organelle in the development and prognosis of breast cancer in obese patients. Likewise, more studies are necessary in order to clarify the estrogen receptor beta mechanism in breast cancer and establish it as a clinical biomarker, as is the estrogen receptor alpha.