Acute myeloid leukaemia (AML) cells interact and modulate components of their surrounding microenvironment into their own benefit. Stromal cells have been shown to support AML survival and progression through various mechanisms. Nonetheless, whether AML cells could establish beneficial metabolic interactions with stromal cells is underexplored. By using a combination of human AML cell lines and AML patient samples together with mouse stromal cells and a MLL-AF9 mouse model, here we identify a novel metabolic crosstalk between AML and stromal cells where AML cells prompt stromal cells to secrete acetate for their own consumption to feed the tricarboxylic acid cycle (TCA) and lipid biosynthesis. By performing transcriptome analysis and tracer-based metabolic NMR analysis, we observe that stromal cells present a higher rate of glycolysis when co-cultured with AML cells. We also find that acetate in stromal cells is derived from pyruvate via chemical conversion under the influence of reactive oxygen species (ROS) following ROS transfer from AML to stromal cells via gap junctions. Overall, we present a unique metabolic communication between AML and stromal cells and propose two different molecular targets, ACSS2 and gap junctions, that could potentially be exploited for adjuvant therapy. Acute myeloid leukaemia (AML) is a heterogeneous multiclonal disease characterised by a rapid proliferation of aberrant immature myeloid cells that accumulate in the bone marrow, and eventually in the blood and other organs, severely impairing normal haematopoiesis. AML cells show a highly adaptive metabolism that allows them to efficiently use a variety of nutrients to obtain energy and generate biomass  support AML progression by increasing the bioenergetic capacity of AML cells and providing them with glutathione (GSH)-mediated antioxidant defence to balance the excess ROS  data, our results demonstrate that stromal cell metabolism is rewired in co-culture resulting in higher glycolysis and pyruvate decarboxylation, leading to acetate secretion. Our results also show that AML cells are able to transfer ROS to stromal cells by direct interaction through gap junctions and that these ROS can be used by stromal cells to generate and secrete acetate, which is utilised by AML cells to feed the TCA cycle and to generate lipids. Targeting ROS transfer via modulation of gap junctions to suppress acetate provision by stromal cells or targeting acetate usage could serve as an adjuvant therapy to eradicate AML.1H-NMR and compared at different time points. The most striking difference found in co-culture compared to cells cultured separately was an increased secretion of acetate, which was common for the three cell lines used  representing different AML subtypes , and M2, respectively) were cultured separately and in co-culture with MS-5, a stromal mouse cell line capable of maintaining haematopoiesis . The metnes used . MoreoveWe further examined the levels of other common extracellular metabolites, including glucose, lactate, glutamate and glutamine. As shown in The metabolic differences found in co-culture, could be due to altered proliferation under these conditions. To determine whether this was the case, a CFSE-based proliferation assay was performed in which AML cellsbut not stromal cells were stained and their growth compared when cultured separately vs in co-culture. Over 48 hr, none of the human AML cell lines tested presented differences in their proliferation rates , thus coNext, we aimed to determine whether cell-to-cell contact could play a role in the increased acetate secretion found in co-culture. For this we co-cultured AML and stromal cells separated by a permeable membrane, allowing cells to share the extracellular medium but impeding cell-to-cell contact. Co-culturing cells using a permeable membrane blocked the increase in acetate secretion observed under direct contact conditions . In factTo examine whether increased acetate secretion is specific for the interaction of AML cells with stromal cells, we co-cultured the human AML cell lines with the cervical human cancer cell line HeLa and compared the levels of acetate of each cell type cultured alone. We found that there was no acetate secretion in co-culture, also not by HeLa and AML cells cultured alone , suggestConsidering that our previous data seemed to indicate that MS-5 cells were responsible for acetate secretion when co-cultured with human AML cell lines, we decided to investigate how the levels of extracellular acetate would vary after separating cells from co-culture. The three human AML cell lines were co-cultured for 24 hr with the MS-5 mouse stromal cells prior to separation and subsequent culture in the same spent media. Extracellular acetate levels in previously co-cultured MS-5 cells followed a similar trend as before separation, suggesting that the MS-5 cells most likely are responsible for the increased acetate secretion found in co-culture . Moreove+ population of four primary AML patient samples, and of three independent healthy donors  of mice transplanted either with mouse MLL-AF9controls .Following the finding that stromal cells might be responsible for acetate secretion in co-culture, we next examined whether AML cells could metabolise the secreted acetate. We first sought to define the concentration of secreted acetate in the extracellular medium in co-culture. For this, we compared a sample of extracellular medium from a co-culture of SKM-1 and MS-5 cells after 24 hr to a calibration curve , which a13C]acetate to assess whether SKM-1 or MS-5 cells can utilise acetate  was used. Overall, this data suggests that acetate in co-culture could be utilised by SKM-1 cells but not by MS-5 cells.We then employed a tracer-based approach using acetate to the spent extracellular medium and cultured cells for 30 min and 8 hr before analysing the intracellular metabolites in each cell type   .Overall, these results indicated that AML cells could uptake and utilise the acetate secreted by stromal cells in co-culture as a substrate to feed into the TCA cycle and for lipid biosynthesis.13C]acetate label incorporation we observed that the ACSS2i reduced the incorporation of acetate to the TCA metabolites by approximately 60% after 24 hr of treatment . Our data showed that the AML cells studied displayed different degrees of sensitivity to AraC, with HL-60 cells being more sensitive and Kasumi-1 more resistant . Interesreatment , indicatAfter establishing that stromal cells are responsible for acetate secretion  and thatFollowing clustering of differentially expressed genes, gene set enrichment analysis (GSEA) was performed  revealinSlc2a1 and Slc2a4) and glucose breakdown to pyruvate  were upregulated, including the gene encoding for the 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (Pfkfb3), a well-known activator of glycolysis.A closer examination of the genes involved in the glycolysis pathway revealed a major upregulation of several glycolysis-related genes in MS-5 cells in co-culture . Most ofMpc1, Mpc2) and several pyruvate dehydrogenase (PDH) complex-related genes , involved in the conversion of pyruvate to acetyl-CoA, remained largely unaltered or were slightly downregulated by co-culture. Additionally, the pyruvate dehydrogenase kinases , which inhibit the activity of the PDH complex, were found to be upregulated by co-culture , to lactate by lactate dehydrogenase (Ldha), and to alanine via alanine transaminase (Gpt). Only Ldha was found to be moderately upregulated in co-culture. However, we did not observe a substantial increase in lactate production experimentally in co-culture. Altogether, transcriptomic data suggests that MS-5 cells in co-culture present a major upregulation of glycolysis and downregulation of the PDH complex.In contrast, individual examination of genes related to pyruvate metabolism revealed that the genes related to pyruvate conversion to acetyl-CoA were downregulated . Pyruvat-culture . Interes13C]glucose tracing on AML and MS-5 cells cultured alone and in co-culture and analysed the label incorporation in glycolysis-related extracellular metabolites  was used as a ROS scavenger. Extracellular acetate levels were measured by -culture . This ex-culture . Additio-culture . The dec-culture , indicat2DCFDA fluorescent dye. Our data showed that ROS levels in the three human AML cell lines used were significantly decreased in co-culture, whilst in the stromal cells ROS levels were significantly increased in two of the three co-cultures , a well-known gap junction inhibitor . We firs1H-NMR after 24 hr. We found that inhibition of gap junctions by CBX treatment resulted in a decrease in acetate levels when mouse stromal cells were co-cultured with human AML cell lines compared to untreated co-cultures, indicating that indeed acetate secretion is dependent on the formation of gap junctions between AML and stromal cells   , or withe (TBHP) . In contOnce confirmed that acetate secretion is dependent of direct contact through gap junctions and ROS, we then sought to get further insight in the order of events and determine whether gap junctions are upregulated first, leading to increase ROS intake and metabolic re-wiring or whether the acetate production and gap junction formation were due to increased ROS. To discern between these two possibilities, we labelled MS-5 mouse stromal cells with calcein-AM, cultured them with unlabelled human AML cells in the presence of catalase and analysed the fluorescence of AML cells after three hours. We found that, for the three human AML cell lines tested, the calcein-AM transfer was reduced between 50 and 70% compared to cells co-cultured without the ROS scavenger , indicatOverall, our results indicate that ROS is required for the upregulation of gap junctions facilitating in this way its transfer to stromal cells for acetate production and that inhibition of gap junctions affects acetate secretion by stromal cells .AML cells are known to interact and remodel niche cells through various mechanisms, including the secretion of soluble factors, cytokines or metabolites, resulting in a better support of AML cells at the expense of normal haematopoiesis. Yet, metabolic crosstalk studies between AML and stromal cells remain scarce. Here, we have identified a novel metabolic communication between AML and stromal cells mediated by acetate. Our in vivo data shows high acetate levels in the bone marrow extracellular fluid of AML but not in healthy control mice, indicative of a potential role for acetate in AML development. Our in vitro data suggests that AML cells can modulate stromal cells into secreting acetate in co-culture, by rewiring stromal cell metabolism, and can then utilise acetate to feed their own TCA cycle and for lipid biosynthesis. Mechanistically, our data revealed that acetate secretion involves not only a higher glycolytic rate in stromal cells but is also a likely consequence of the non enzymatic ROS-mediated conversion of pyruvate to acetate., which was supported by the fact that MS-5 cells grown in thiamine-free media were still capable to produce acetate. Furthermore, our data indicates that AML cells can diminish their ROS levels by establishing gap junctions with stromal cells facilitating ROS transfer to stromal cells.Studying the interactions between cancer cells and their microenvironment in terms of metabolism has become an exciting new field of cancer research. Our data indicates that AML cells can influence the metabolism of stromal cells causing increased acetate secretion, which was not observed in healthy counterparts.13C-labelled acetate to co-cultured AML cells and showing label incorporation in several TCA cycle metabolites and in lipid metabolism exclusively in AML cells, strongly supports this hypothesis. Interestingly, acetate has been reported as an alternative fuel for cancer cells  stromal cells cultured alone secreted acetate, whilst AML cell lines and primary AML cells did not; (ii) after separating stromal cells from co-culture with AML cell lines, stromal cells continued to secrete acetate at a similar rate to that observed in co-culture; and, (iii) glycolysis was upregulated in stromal cells in co-culture, and glucose was found to be the precursor of the secreted acetate in co-culture. Thus, although some alternative metabolic rewiring in AML cells dependent on the direct contact with stromal cells cannot be discarded, our data strongly suggests stromal cells secreting acetate as the main pathway. Although we cannot provide an absolute proof that AML cells consume the acetate specifically secreted by stromal cells, our data adding er cells , especiaer cells , but it er cells . Our worer cells  and otheer cells , this is13C]glucose, demonstrated that more label gets incorporated into acetate in stromal cells in co-culture compared to either AML or stromal cells cultured alone. Enrichment of hypoxia genes and elevated Pdk expression have been reported to be related to higher glycolytic activity , the mouse stromal cell line (MS-5) and the human cervical cancer cell line (HeLa) were cultured in RPMI 1640 media supplemented with 15% (v/v) FBS, 2 mmol/L L-glutamine and 100 U/ml Penicillin/Streptomycin . Co-cultures were plated in a 4:1 AML-stromal ratio, and 750,000 cells/ml density of AML cells over confluent stromal cells. Prior to cell extraction for NMR, RNA collection or protein extraction, a suspension of 10 million AML cells was collected, the stromal layer was washed with PBS and was subject to mild trypsinisation with 1:5 dilution of 0.25% Trypsin 1 mM EDTA (Thermofisher) to remove attached residual leukaemic cells before completely detaching stromal cells with 0.25% Trypsin-EDTA. Micoplasma test using MycoAlert (Lonza) was performed every three months in all cell lines.AML and PBMC primary specimens’ procedures were obtained in accordance with the Declaration of Helsinki at the University Medical Center Groningen, approved by the UMCG Medical Ethical Committee or at the University Hospital Birmingham NHS Foundation Trust, approved by the West Midlands – Solihull Research Ethics Committee (10 /H1206//58).Additional information about the primary AML samples used in this study can be found in 4 (Sigma-Aldrich) and heparin (5 Units/mL) (Ziekenhuis Apotheek Midden-Brabant) and incubated on 37 °C for 15 min. For AML1 and PBMC1, cells were sorted after thawing by fluorescence-activated cell sorting (FACS) for the CD34 +CD38- population using 10 μL of anti-CD34 APC , 10 μL of anti-CD38 FITC  and 10 μL of DAPI  per 10 million cells. Cells were sorted using a Sony SH800S (Sony) sorter. For AML2 and PBMC2, cells were thawed and the CD34 +population was sorted by magnetic-activated cell sorting (MACS) using 10 μL of anti-CD34 microbeads  per million of expected CD34 cells following manufacturer’s protocol.For AML1-2 and PBMC1-2, samples were thawed and resuspended in newborn calf serum (NCS) supplemented with DNase I (20 Units/mL) (Roche), 4 mM MgSO+ cells from PBMC1 and PBMC2 the medium was supplemented with 100 ng/ml of human SCF , 100 ng/ml of NPlate , 100 ng/ml of FLT3 ligand (Amgen) and 20 ng/ml of IL-3. Samples of medium were collected at 0 and 48 hr.AML1-2, PBMC1-2, and MS-5 cells were cultured alone and in co-culture in a 4:1 AML/PBMC-stromal ratio and 500,000 cells/mL density in α-MEM (Gibco) with 12.5% (v/v) FCS (Sigma-Aldrich), 1% (v/v) Pen/Strep (Thermo Fisher Scientific), 12.5% (v/v) Horse serum (Invitrogen), 0.4% (v/v) β-mercaptoethanol (Merck Sharp & Dohme BV) and 0.1% hydrocortisone . For AML1 and AML2, the medium was supplemented with 0.02 μg/mL of IL-3 (Sandoz), 0.02 μg/mL NPlate (Amgen), and 0.02 μg/mL of G-CSF (Amgen). CD34AML3 - 7 and PBMC3 were thawed and kept in culture for 16–24 hr in Stem Span H3000 media (STEMCELL Technologies) supplemented with 50 μg/ml ascorbic acid (Sigma-Aldrich), 50 ng/ml human SCF , 10 ng/ml human IL-3 , 2 units/ml human-erythropoietin , 40 ng/ml insulin-like growth factor 1 (IGF-1) , 1 μM dexamethasone , and 100 μg/ml primocin . CD34 +cKit + cells from AML and healthy controls were purified using magnetic microbeads (130-046-702 (CD34) and 130-091-332 (CD117), Miltenyi Biotec). Cells were cultured in the supplemented Stem Span media for 24 hr prior to co-culture setting. Co-cultures were plated with a 4:1 leukaemic to stromal cells ratio and a 300,000 cells/ml density in supplemented Stem Span medium. Samples of leukaemic/healthy cells and MS-5 cells alone were also cultured in supplemented Stem Span media as controls. Samples of medium were collected at 0 and 48 hr.6 bone marrow (BM) nucleated cells isolated as previously described  were lethally irradiated with 9 Gy (2 doses of 4.5 Gy separated by 3 hr) using an X-RAY source (Rad Source’s RS 2000). Mice were transplanted by intravenous injection 4 hr after with 2x10escribed  from leuescribed . Male trRecipients were euthanized 6 months after the transplant, bone marrow from femur and tibia was flushed with a syringe in 150 µL of cold PBS and centrifuged at 15,000 g for 10 min at 4 °C. The supernatant made of bone marrow extracellular fluid (BMEF) was kept for analysis of acetate level.+ or WT BM nucleated cells into C57BL6/J female recipients. Mice were daily injected intraperitoneally with 500 µmol/kg of ROS enhancer tert-Butyl hydroxyperoxide (TBHP) or PBS as described previously .Treatments started 6 weeks after transplantation of MLL-AF9eviously . A groupeviously . AnimalsSample size was calculated according to standard deviations from the means of parameters in groups under study, 5% significance level, power of 90%, and two-tailed T test. Standardised effect size  = (Mean1-Mean2)/SD is expected to be higher than 2.2. Randomization: Mice were randomized to treatment groups. Mice of the same sex and age were used to control for covariates. No blinding was performed due to regulations at the Animal Facilities of the UiT – The Arctic University of Norway and the University of Oslo. Animals that showed symptoms of unrelated disease were excluded of the study (1 mouse). Criteria applied for mouse termination before the established end point were in accordance with the Norwegian Food and Safety Authority. Outliers were not removed. ARRIVE guidelines were followed.Experiments were conducted with the ethical approval of the Norwegian Food and Safety Authority. Animals were housed under specific opportunistic and pathogen free environment at the Section of Comparative Medicine at the University of Oslo, Norway, and the Unit of Comparative Medicine at UiT - the Arctic University of Norway.The CellTrace carboxyfluorescein succinimidyl ester (CFSE) Cell Proliferation Kit  was used to assess proliferation of AML cells following the manufacturer’s protocol. AML cells were stained and their fluorescence was assessed before dividing the bulk of cells into culturing them alone or with MS-5 cells for 48 hr. Small aliquots of cells after 24 and 48 hr were analysed by flow cytometry. Flow cytometry analysis was carried out in a CyAn ADP flow cytometer (Beckman Coulter). Data analysis was performed using the FlowJo software package (BD).Cellular ROS was measured by incubating cells with 100 µM 2′,7′-Dichlorofluorescin diacetate (DCFH-DA)  in Hank’s Balanced Salt Solution (HBSS) (Thermo Fisher Scientific) at 37 °C for 30 min protected from light. Cells were then harvested and stained with 5 μg/μL anti-human CD33 eFluor 450  for 30 min at 4 °C before flow cytometry analysis as previously described.Thiamine-free medium  was prepared as per manufacturer instructions and supplemented with 10% dialised FBS.MS-5 cells were cultured in thiamine-free medium or control RPMI medium for 4 days prior to the experiment. Cells were then seeded with fresh thiamine-free or control RPMI medium and incubated for 24 hr. Samples of medium were collected at 0 and 24 hr and kept at –80 °C.2O2 (Merck) complete cell culture medium, 5 mM N-acetylcysteine (NAC)  complete cell culture medium or control medium. Samples of medium were collected at 0 and 24 hr and kept at –80 °C.SKM-1, Kasumi-1, HL-60 and MS-5 cells cultured alone and in co-culture were incubated for 24 hr in 50 μM H+ and Calcein-AM+ cells or as the geometric mean of FITC channel.Functional gap junction presence was evaluated using the fluorescent dye Calcein-AM green  adapting a previously established protocol . MS-5 ceCarbenoxolone (CBX) disodium salt  was prepared fresh at 200 μM in cell culture medium. Catalase  was prepared fresh at 10 mg/ml in PBS and filtered sterilized. Cells were resuspended in the CBX medium or media containing catalase at 100 μg/ml or 500 μg/ml and cultured alone or in co-culture for 24 hr prior to ROS, Calcein-AM dye transfer experiments or medium collection.13C]Glucose  was added to RPMI 1640 medium without glucose  to a final concentration of 2 g/L (as in the complete cell culture medium) and was supplemented as usual with 15% (v/v) FBS, 2 mmol/L L-glutamine and 100 U/mL Pen/Strep. The medium was prepared fresh and was filtered with a 0.2 μm syringe filter (Sartorius) before each experiment.[U-13C]acetate  was added to complete cell culture medium and the medium was filtered with a 0.2 μm syringe filter before each experiment. Cells were incubated for the time indicated in each experiment before separation of cells and/or metabolite extraction. Unlabelled samples were prepared as a control for 2D-NMR experiments and to measure acetate consumption by adding unlabelled sodium acetate trihydrate  to complete cell culture medium before metabolite extraction or collection of medium samples.4 mM sodium  and the all-1H spectra and the difference 1H[13C] spectrum was obtained by aligning on chemical shift. Metabolites were selected in the 1H[13C] spectrum and integrated in all the spectra . Label incorporations (13C percentages) were calculated by dividing the signal areas obtained in the 1H[13C] spectrum by the ones obtained in the all-1H spectrum.For 1H-13C-HSQC experiments, spectra were acquired using a modified version of Bruker’s hsqcgphprsp pulse program, with additional gradient pulses during the INEPT echo periods and using soft 180° pulses for 13C. For the 1H dimension, the spectral width was 13.018 ppm with 2048 complex points as described by 13C dimension, the spectral width was 160 ppm with 2048 complex points. Two scans were acquired per spectrum and with an interscan delay of 1.5 s. Non-uniform sampling (NUS) with a 25% sampling schedule  with a tolerance of 0.01 and default values for the other parameters) was used with 4096 increments yielding 8192 complex points after processing. The total experimental time was 4 hr. Spectra were processed and phased with NMRPipe . MetaboLab was used to reference the chemical shift using the signal for the methyl group of L-lactic acid, at 1.31/22.9 ppm in the 1H and 13C dimensions, respectively. Identification of metabolites in 2D spectra was carried out using the MetaboLab software which includes a chemical shift library for ca. 200 metabolites. Intensities were obtained from signals in the spectra and were corrected for differences in cell numbers contributing to the sample as follows: A 1H-NMR spectrum was acquired for each sample and the total metabolite area of this spectrum after removal of the water and TMSP reference signal was calculated in MetaboLab. The intensities in the 2D spectra were then divided by the total metabolite area of the corresponding 1H-NMR spectrum. To obtain the % of 13C in a metabolite, the normalized intensity of a certain carbon in the labelled sample was divided by the normalized intensity of the same carbon in the unlabelled sample and was multiplied by the natural abundance of 13C (1.1%).For 13C-label incorporation in lipids, 1D 1H spectra  were acquired on a Bruker 600MHz spectrometer equipped with a 5 mm triple resonance pulse field gradient (PFG) room temperature probe at 300 K. The data was collected with a spectral width of 12 ppm, the number of data points was 32,768 and interscan delay was 4 s. The 1H carrier was set at 7.26 ppm corresponding to CDCl3. The spectra were processed and analyzed using Bruker Topspin. A 0.3 Hz exponential apodization function was applied to FIDs followed by zero-filling to 131,072 data points prior to Fourier transformation. The chemical shift was calibrated by referencing the TMSP signal to 0 ppm and spectra were manually phase corrected. The baseline was corrected by applying a spline baseline correction.To determine the MS-5 cells were cultured alone or in co-culture with SKM-1 cells for 24 hr. Cells were separated and washed with PBS prior to RNA extraction with TRIzol (Gibco) according to the manufacturer’s protocol. RNA was purified with RNeasy Plus Micro kit. Samples were sent to Theragenetex to be sequenced with Novaseq 150 bp PE with 40 M reads.Hk2 (NM_013820), Pdhx (NM_175094), Pdk1 (NM_172665), and Pdk2  were carried out using the SYBRGreen Master mix (Thermo Fisher Scientific) and qRT-PCR of B2m  was performed using TaqMan PCR Master Mix (Thermo Fisher Scientific). Reactions were performed in a Stratagene Mx3000P and were run in triplicate. Relative gene expression was calculated following the 2-ΔΔCt method relative to the expression of B2m.Samples of RNA from SKM-1 and MS-5 co-cultures were collected and extracted using Trizol (Invitrogen) following manufacturer’s protocol. cDNA was synthesized using the M-MLV reverse transcriptase (Promega) according to manufacturer’s instructions. For gene expression analysis, qRT-PCR of https://www.theragenetex.net). cDNA libraries were prepared with the TruSeq Stranded mRNA Sample Prep Kit (Illumina) and RNA sequencing was performed in a HiSeq2500 platform (Illumina). Quality control metrics were obtained with FastQC 0.11.7 software (Babraham Bioinformatics). To quantify transcript abundances using the Kallisto 0.43.0 software (Patcher Lab), read counts were aligned to the GRCm38 mouse reference genome cDNA index (Ensembl rel.67). Gene-level differential expression analysis was carried out with the R statistical package Sleuth 0.30.0 comparing the expression of cells cultured alone vs co-culture. Differentially expressed genes were calculated using the Wald statistical test, correcting for multiple testing with the Benjamin-Hochberg method. The false discovery rate (FDR) threshold was set at 1% . Ensembl gene transcripts were annotated to Entrez IDs and official gene symbols with the R statistical package BioMart 2.40.3. To normalise for sequencing depth and gene length, transcripts per million (TPM) expression values were calculated. Gene Set Enrichment Analysis (GSEA) was performed with the R statistical package fgsea 1.10.0. The collection of hallmark gene sets from the Molecular Signature Database was used for the GSEA, setting the FDR threshold at 5%. Data was deposited in GEO (GSE163478).RNA samples of MS-5 cells cultured alone and in co-culture with SKM-1 cells extracted using Trizol were purified using the Rneasy Plus Micro kit (Qiagen) according to manufacturer’s protocol. Transcriptome analysis was performed by Theragen Etex Co., LTD. .scRNA-seq data generated by  This article will be of interest to those working in the fields of hematopoiesis, leukemia and cancer microenvironment. The work describes a novel phenomenon whereby the direct interaction of acute myeloid leukemia (AML) cell lines and bone marrow stromal cell lines results in increased production of extracellular acetate in stromal cells, which can then be metabolised by the AML cells. Overall, the data are very thought-provoking but future work some of which is technically challenging, will be necessary for a full appreciation of the biological relevance of this interaction. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Utpal Banerjee as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Mick Milson (Reviewer #2).Thank you for submitting your article "Crosstalk between AML and stromal cells triggers acetate secretion through the metabolic rewiring of stromal cells" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.eLife, our "no scoop policy" will protect your work if another similar paper appears in press during your revision.The suggested revisions are fairly extensive, and due to the current situation with the pandemic, if you will need more time than the usual 2 month time limit for revisions, please let our editorial office know and we will be flexible in adjusting to a reasonable time scale. There is only one major revision allowed, so please take your time (within reason), and attend to all the points raised. At Essential revisions:1) The conclusion that acetate is used as biofuel by AML cells is not supported by the data at least in the co-culture. Please strengthen this conclusion based on the following comments, and specific comments from Reviewer 2 and 3. The intracellular labelling in Figure 2E does not show a significant increase in any of the TCA cycle intermediates labelling in the SKM-1 cells compared to MS-5 and S3B does not show the MS-5 levels at all. The big increase in acetyl-carnitine without corresponding increase in TCA cycle intermediates makes one wonder if there is a blockage in oxidation of this product.2) It is important to show that the acetate used by AML cells is produced by MS5 cells. Is it possible to demonstrate not just AML cells uptake of acetate but the full pathway of U-C13 entering MS5 cells and subsequently AML cells? It should be possible to use data from the experiment with U-C13 glucose labelling, to show intracellular labelling in MS-5 and AML cells. These data will be very useful to 1. Confirm glycolysis is upregulated in MS-5 cells in co-culture, 2. Acetate is coming from the labelled pyruvate in MS-5 cells. These data should be presented to support the claims that at the moment is mostly indirect re MS-5 upregulating glycolysis and producing acetate via pyruvate through a non-enzymatic reaction. Please consider specific points from Reviewer 2 and 3 linked to this.3) The biological relevance of the presented findings needs strengthening, especially given that the AML cells do not grow more on MS5 cells than in single culture. Are the findings linked to AML growth, or perhaps chemoresistance or leukaemia propagation? Please note points from Reviewer 1 and 3 when addressing this.4) the link between gap junctions, ROS transfer and induction of acetate production needs strengthening. See Reviewr 2 point: the experiments are overall convincing including re the role of gap junctions. What is missing is direct proof that inhibiting gap junction would reduce acetate production in the co-culture and this is something that needs done to support the statement that it is the ROS transfer via gap junction that is leading to acetate production. And Reviewer 1: is the metabolic rewiring and overexpression of gap junctions a consequence of increased ROS? Or are gap junctions upregulated first, leading to increased ROS intake and metabolic re-wiring?5)While further extensive in vivo experiments may be beyond the scope of this work and would require considerably longer than 3 months to complete, is there any evidence from already published transcriptomic datasets that stroma cells in vivo upregulate the same genes/pathways? Is it possible to identify the specific cell type responsible for the mechanism presented here?6) Please clarify the rational behind the choice of AML cell lines and human healthy control samples used.Further points:7) Please consider specific points from each reviewer in your response letter.Reviewer #1 (Recommendations for the authors):1) Is the metabolic rewiring and overexpression of gap junctions a consequence of increased ROS? Or are gap junctions upregulated first, leading to increased ROS intake and metabolic re-wiring?2) Is there evidence from in vivo studies that stroma cells upregulate the same genes/pathways? Is it possible to identify the specific cell type responsible for the mechanism presented here? If a specific cell type appears to be important with this, it would be exciting to see an effect following specific targeting of that cell type, although this may be beyond the scope of the presented work.3) Is the mechanism presented here supporting AML growth prior or also following chemotherapy administration?Reviewer #2 (Recommendations for the authors):The manuscript by Vilaplana-Lopera et al., highlights a novel interesting metabolic cross-talk between the stroma and AML cells through production of acetate. The main conclusion of the paper, ie that acetate production is increased in co-culture most likely because of stroma production and is taken up by AML cells, is supported by the data. Some of the other conclusions re the utilisation of acetate in AML cells and the exact mechanism leading to acetate production might require further experimental work to be fully supported. The authors make an effort to validate their findings in primary AML cells model and in vivo although the mechanistic insight is mostly done in AML cell lines grown on a MS-5 stromal layer. As a result whether the described interaction is also present in other stroma/AML combination remains to be demonstrated. However I think this is not necessary for this paper.Technically the paper appears rigorous although I would not be able to comment on the technical aspects of the NMR analysis and I would hope some of the other reviewers can comment on that.Specific comments:Figure 1 – overall I find the data here convincing. My main criticism is that the author appear to support the notion that acetate comes from MS-5 cells only while it cannot be excluded that AML cells might be reprogrammed by the stroma to a certain extent to produce acetate as in 1D for SKM1 and HL60 there is a slight increase in acetate following interruption of the coculture. See below on how to strengthen this conclusion or otherwise reword the discussion.Figure 2 – what do the author mean by physiological conditions? How is the acetate concentration of 0.25mM considered physiological and are they implying that their co-culture system is not physiological? Also the conclusion that acetate is used as biofuel by AML cells is not supported by the data at least in the coculture. The intracellular labelling in Figure 2E does not show a significant increase in any of the TCA cycle intermediates labelling in the SKM-1 cells compared to MS-5 and S3B does not show the MS-5 levels at all. Infact the big increase in acetyl-carnitine without corresponding increase in TCA cycle intermediates makes one wonder if there is a blockage in oxidation of this product.One way to address that would be to measure ATP in AML cells or oxygen consumption following co-culture. Alternative fates for acetate, i.e. lipid biosynthesis, might otherwise need to be explored.Figure 3 – Upregulation of glycolysis in MS-5 in coculture is indirectly demonstrated from transcriptomic data. There is no direct proof of it and infact based on the patterns of glucose and lactate levels in coculture shown in S1, the authors themselves had concluded that "the overall increase in glycolysis in co-culture was just a result of culturing both cell types together". As the authors have done U-C13 glucose labelling , they might have data for intracellular labelling in MS-5 and AML cells. These data will be very useful to 1. Confirm glycolysis is upregulated in MS-5 cells in co-culture, 2. Acetate is coming from the labelled pyruvate in MS-5 cells. These data should be presented to support the claims that at the moment is mostly indirect re MS-5 upregulating glycolysis and producing acetate via pyruvate through a non-enzymatic reaction.Figure 4 – Regarding production of acetate. Overall the data are supportive but do not provide conclusive evidence that acetate production is via non-enzymatic reaction. The authors could inhibit pyruvate carrier to see if that has an effect on acetate production (prediction would be not).The intracellular labelling from U-C13 glucose proposed above would be very helpful to clarify this too. I cannot fully interpret their thiamine depletion experiment as it appears to have been done not in co-culture system so I am not sure how much it does support that no production of acetate via enzymatic happens in the co-culture system.Finally treatment with HDAC might help ensure that indeed the acetate is mostly coming via production through glycolysis although this is supported by their labelling and might not be a key experiment.With regards to the role of ROS, the experiments are overall convincing including re the role of gap junctions. What is missing is direct proof that inhibiting gap junction would reduce acetate production in the co-culture and this is something that needs done to support the statement that it is the ROS transfer via gap junction that is leading to acetate production.Discussion – the authors state that acetate is used to feed TCA cycle to generate energy. This is not supported by the data as labelling of TCA cycle is unclear from co-culture and ATP production or oxygen consumption not shown. Acetate fate can be complex including in lipid biosynthesis or to support TCA cycle intermediates for biosynthesis of other macromolecules (cataplerosis). As such the authors should be careful about drawing conclusions which are not supported by their data and provide further evidence to their claims or change discussion (see above).Also the conclusion “Mechanistically, our data revealed that acetate secretion involves not only a higher glycolytic rate but also the non-enzymatic ROS-mediated conversion of pyruvate to acetate, as cells grown in thiamine-free media were still capable to produce acetate” needs further experimental support although their data suggest this is likely true. The experiment suggested above to support this statement would also further support the conclusion that acetate comes mostly from the stroma.The conclusion "We showed that AML cells are capable of modulating the metabolism of stromal cells by transferring ROS via gap junctions resulting in an increased secretion of acetate and its subsequent accumulation in the extracellular medium" is not fully supported as it is not shown that inhibiting gap junction reduces acetate.Also "Furthermore, we found that AML cells consume the secreted acetate and use it as an energy source, by fluxing it into the TCA cycle" needs to be reconsidered as per above.Reviewer #3 (Recommendations for the authors):In general, I found the data in the manuscript to be novel, interesting and thought provoking. However, I would like to suggest some experiments that would help to solidify the claims that are made in the manuscript as well as potentially increase the impact of the work.1) While the acetate secretion by stromal cells and uptake by AML cells is a very interesting finding, I'm sure that many readers would join me in asking: what is the biological relevance of this? Is it simply a metabolic quirk or does it convey some advantage to the AML cells? Can the authors find any aspect of altered biology in the AML cells that may be relevant to disease progression, therapy resistance, relapse etc? Is it possible to block/inhibit AML import of acetate or stromal cell secretion of acetate in order to assess the impact of this phenomenon? Can alterations in culture conditions or treatment with AML therapy relevant drugs demonstrate a dependency/advantage conferred by stromal derived acetate? If so, this would significantly boost the impact of the work and demonstrate the importance of the mechanism.2) It may seem to be nit-picking, but I noted that it has not been directly shown that AML cells can metabolise the acetate that is produced by stromal cells upon co-culture. The metabolic tracing experiments have been performed using labelled acetate that has been added to the culture medium. Since this is a central claim of the manuscript, I think it is important to show this, if at all possible. Can the stromal cells be grown in media that will label the carbon molecules in acetate prior to co-culture, as opposed to adding acetate directly to the culture medium?3) Although the authors show no effect of AML cell growth upon co-culture, they do not assess whether the growth of stromal cells is altered. This would have important implications for the interpretation of any alteration in metabolism of these cells.4) I would strongly encourage the authors to use an additional method to rescue ROS production rather than NAC, which is problematic in this experimental setting since it can directly feed into the metabolic pathways that are being studied. As well as considering the use of other chemicals that are considered to act as antioxidants, I would also encourage the authors to explore overexpression of ROS detoxifying enzymes such as superoxide dismutase and catalase. By taking the latter approach, one could specifically detoxify ROS in either AML cells or stromal cells, which would help to strengthen the proposed transfer mechanism. Genetic ablation/knockdown of the same enzymes could also be used as an elegant way to strengthen the ROS transfer concept.5) Relating to 4), I was very surprised that the authors referenced the prior work documenting transfer of mitochondria between stromal cells and HSCs via gap junctions, but did not address whether this was of any mechanistic relevance to their own observations. Since mitochondria are thought to be the major source of intracellular ROS, this would seem to be a clear alternative possible mechanism which would yield similar experimental outcomes to those observed by the authors.6) The authors should make sure that the primary patient AML co-culture experiments have been conducted using identical culture conditions. It is problematic for the reader to assess the experimental outcome if culture conditions have been inconsistently altered across different test and control samples. I appreciate that such patient samples are not easy to acquire or work with, but the authors should repeat these experiments if necessary.7) Related to 6), could the authors clearly state what the primary hematopoietic control cells that they use in the control experiments are? In the figure, it seems to suggest that peripheral blood mononuclear cells were used, but in the methods, it seems to suggest that CD34+ cells are used, which seems inconsistent with the description of PBMNCs. If the authors used CD34+ cells from AML patients, then I would suggest that CD34+ cells from the bone marrow of normal donors is probably the best control for this experiment.My final comment is beyond the scope of the current manuscript, but I would also encourage the authors to pursue this line of investigation further using the murine MLL-AF9 model that they perform a preliminary characterization with in this manuscript. This would afford the possibility of using a wide range of genetic models to interrogate mechanism in vivo, as well as a being an attractive model to explore biological relevance in the context of disease evolution and therapy. Essential revisions:1) The conclusion that acetate is used as biofuel by AML cells is not supported by the data at least in the co-culture. Please strengthen this conclusion based on the following comments, and specific comments from Reviewer 2 and 3. The intracellular labelling in Figure 2E does not show a significant increase in any of the TCA cycle intermediates labelling in the SKM-1 cells compared to MS-5 and S3B does not show the MS-5 levels at all. The big increase in acetyl-carnitine without corresponding increase in TCA cycle intermediates makes one wonder if there is a blockage in oxidation of this product.13C] acetate to the coculture before harvesting and separating AML and MS-5 cells 30 minutes after acetate addition. The new data clearly shows labelling in TCA intermediates: citrate, glutamate, oxoglutarate, malate, proline and succinate in SKM-1 and Kasumi-1 cells whilst labelled citrate, glutamate and succinate are the main metabolites found in HL-60 cells. In contrast, no labelled metabolites were found in the stromal cells. We have included this data in Figure 2C and Figure 2-Supplement Figure 2B-C (left panels). In this respect the result is the same as for MS-5 and SKM-1 grown in isolation.We have taken into consideration the reviewers’ comments and performed intracellular labelling by adding  acetate for 8 and 48 hours. Our data revealed that at 8h, no label incorporation could be detected in the non-polar or lipid fraction . In contrast, at 48h, the 1H spectrum shows 13C-coupled 1H-signals at 0.75-0.80 ppm arising from 13C incorporation  in lipid CH3 groups . While NMR cannot determine the chain length of the lipids, integration of the signals yields the overall label incorporation in any lipid CH3 groups, indicating that acetate is being used for lipid biosynthesis.We have also explored other possible products of acetate by analysing the intracellular non-polar fraction of AML cells after labelling with glucose prior to co-culture with AML cells. However, after removing the spent medium containing labelled acetate (and the remaining labelled glucose before co-culturing cells), the amount of label left in MS-5 cells is not sufficient to accumulate in the medium and be taken up by AML cells. Moreover, as new non-labelled glucose is added in the form of fresh medium when starting the co-culture, any acetate newly generated from glucose is unlabelled, hence decreasing even more the percentage of labelled acetate. This is consistent with the view described above that MS-5 cells actually do not store acetate, but rather secrete it into the medium, and part of it is subsequently taken up by AML cells. Without a sufficient amount of labelled acetate present in the medium it is impossible to detect labelling in AML cells by NMR (and possibly by any other technique).Nevertheless, we have attempted to label MS-5 cells with [U-13C]glucose and have found that labelling in acetate, alanine and lactate is higher in co-culture . This is more clear when %13C are represented as ratios.We have performed 2D HSQCs spectra on intracellular polar metabolites in MS-5 cells cultured alone vs in co-culture labelled with [1,2-Interestingly, we do not observe pyruvate intracellularly in MS-5 cells and therefore cannot assess label incorporation, probably owing to fast turn-over into acetate.However, we believe that the build-up of acetate in the medium and the general increase in label incorporation in acetate and other metabolites derived from this pathway supports our claims on the upregulation of glycolysis in MS-5 cells in coculture and MS-5 cells as the major source for acetate. This data has been incorporated in Figure 3E.3) The biological relevance of the presented findings needs strengthening, especially given that the AML cells do not grow more on MS5 cells than in single culture. Are the findings linked to AML growth, or perhaps chemoresistance or leukaemia propagation? Please note points from Reviewer 1 and 3 when addressing this.To understand the biological relevance of our findings we have performed survival assays when cells are treated with the chemotherapeutic drug cytarabine (AraC) and with the ACSS2 inhibitor (ACSS2i) alone or in combination, in medium without glucose in the presence of 4mM acetate or in normal media media (containing glucose but not acetate). This experiment was not performed in coculture as we reasoned it would be clearer to use just the cancer cells, to avoid the possibility of other metabolites provided by MS-5 having an effect on cell survival.Our data shows that the AraC treatment affects cell survival in a cell line-dependent manner, with HL-60 being the more sensitive to this drug then Kasumi-1 and SKM-1. Interestingly and supporting the importance of acetate in cell metabolism, the survival of the cells treated with ACSS2i is greatly compromised and the combination of AraC and ACSS2i showed very consistently sensitisation of all the AML cell lines studied to AraC. We also performed these experiments in medium supplemented with a high concentration of acetate (4mM) and found a partial recovery of this sensitisation. We believe that these results highlight the importance of acetate for AML cells and reveal a potential role of acetate in AML chemoresistance. This data can be found in the new Figure 2E and explained in the text in lines 199-220.Additionally, we have performed in vivo experiments in which mice were transplanted with leukaemic cells and injected with a ROS inducer (TBHP) alone or in combination with the gap junction inhibitor CBX. TBHP injection accelerated the development of leukaemia, promoting an increase in the total monocyte count in peripheral blood and reducing the lifespan of TBHP- versus vehicle-treated leukaemic mice. Moreover, our data showed that administration of the gap junction inhibitor partially counteracts the effect of TBPH in both monocyte counts and survival. This data can be found in the new Figure 5G and 5H and explained in the text in lines 357-367. These in vivo results support a biological relevance in leukaemia progression for our observations in vitro involving ROS transfer through gap junctions between AML and stromal cells.4) the link between gap junctions, ROS transfer and induction of acetate production needs strengthening. See Reviewr 2 point: the experiments are overall convincing including re the role of gap junctions. What is missing is direct proof that inhibiting gap junction would reduce acetate production in the co-culture and this is something that needs done to support the statement that it is the ROS transfer via gap junction that is leading to acetate production.As suggested by the reviewer and provide with a direct proof that inhibiting gap junctions reduces acetate production, we have performed co-cultures with CBX to inhibit the gap junctions and measured acetate extracellular levels by NMR. Our results show that gap junction inhibition reduces acetate production in co-cultures in the three cell lines. The results can be found in new Figure 5F and explained in the text in lines 349-356.And Reviewer 1: is the metabolic rewiring and overexpression of gap junctions a consequence of increased ROS? Or are gap junctions upregulated first, leading to increased ROS intake and metabolic re-wiring?This is an interesting point that we have addressed by performing experiments using a ROS-scavenging enzyme  as suggested by reviewer 3. First, we performed a dose curve and observed that a decrease in ROS levels could be seen at concentrations above 100ug/ml. We chose 500ug/ml of catalase to perform further experiments. We pre-treated the AML cells with catalase for 24h and assessed gap junction formation by following the calcein-AM transfer protocol as before. Our results showed that catalase treatment reduces calcein-AM transfer in co-culture and, thus, the ability of forming gap junctions . This result together with new NMR data showing that in the presence of GAP junction inhibitor (CBX) the production of acetate is reduced  provides clarification on the order of events, which we believe occurs as follows: high ROS in AML cells induces gap junction formation as a mechanism of ROS transfer to stromal cells causing the metabolic rewiring .5) While further extensive in vivo experiments may be beyond the scope of this work and would require considerably longer than 3 months to complete, is there any evidence from already published transcriptomic datasets that stroma cells in vivo upregulate the same genes/pathways? Is it possible to identify the specific cell type responsible for the mechanism presented here?As suggested by the reviewer we have made use of published data sets in particular the single cell RNA seq data published in Cell by the group of David Scadden  in which they analysed the transcriptome of bone marrow stroma in homeostasis versus leukaemia . These data sets show three specific clusters  present in leukaemic stroma, which have upregulated the glycolysis and hypoxia pathways. The proportion of osteoprogenitor cluster (cluster 7) was shown to increase in the stroma of leukaemic mice, and cells in this cluster shared the same hallmark gene sets that MS-5 in co-culture: TNFalpha, Hypoxia, allograft rejection, glycolysis, IFNγ, K-ras, complement, epithelial to mesenchymal transition, IL2-STAT5 etc .This information has been included in the discussion, in lines 429-435.6) Please clarify the rational behind the choice of AML cell lines and human healthy control samples used.We made use of three different AML cell lines during this work to cover a range of AML and not looking at a specific subtype. The subtypes chosen would reflect M2 immature AML (HL-60), MS-5 mature AML (SKM-1) and AML with the common translocation AML1-ETO (Kasumi-1). As requested by the reviewer we have included this information in line 88.Human healthy control samples were CD34+ cells from the peripheral blood. This information has been included in the Materials and methods section, line 508 and 517.Reviewer #1 (Recommendations for the authors):1) Is the metabolic rewiring and overexpression of gap junctions a consequence of increased ROS? Or are gap junctions upregulated first, leading to increased ROS intake and metabolic re-wiring?Please, see answer to point 4 in “essentials”.2) Is there evidence from in vivo studies that stroma cells upregulate the same genes/pathways? Is it possible to identify the specific cell type responsible for the mechanism presented here? If a specific cell type appears to be important with this, it would be exciting to see an effect following specific targeting of that cell type, although this may be beyond the scope of the presented work.Please, see answer to point 5 in “essentials”.3) Is the mechanism presented here supporting AML growth prior or also following chemotherapy administration?Please, see answer to point 3 in “essentials”.Reviewer #2 (Recommendations for the authors):The manuscript by Vilaplana-Lopera et al., highlights a novel interesting metabolic cross-talk between the stroma and AML cells through production of acetate. The main conclusion of the paper, ie that acetate production is increased in co-culture most likely because of stroma production and is taken up by AML cells, is supported by the data. Some of the other conclusions re the utilisation of acetate in AML cells and the exact mechanism leading to acetate production might require further experimental work to be fully supported. The authors make an effort to validate their findings in primary AML cells model and in vivo although the mechanistic insight is mostly done in AML cell lines grown on a MS-5 stromal layer. As a result whether the described interaction is also present in other stroma/AML combination remains to be demonstrated. However I think this is not necessary for this paper.Technically the paper appears rigorous although I would not be able to comment on the technical aspects of the NMR analysis and I would hope some of the other reviewers can comment on that.Specific comments:Figure 1 – overall I find the data here convincing. My main criticism is that the author appear to support the notion that acetate comes from MS-5 cells only while it cannot be excluded that AML cells might be reprogrammed by the stroma to a certain extent to produce acetate as in 1D for SKM1 and HL60 there is a slight increase in acetate following interruption of the coculture. See below on how to strengthen this conclusion or otherwise reword the discussionAs suggested by the reviewer, the discussion has been reworded to contemplate the possibility of AML metabolism being rewired. This can be found in line 410-412.Figure 2 – what do the author mean by physiological conditions? How is the acetate concentration of 0.25mM considered physiological and are they implying that their co-culture system is not physiological?et al., Nature comms 2016; reference number 26).By physiological conditions we mean normal levels in plasma, we have changed the word in the text to make it clearer (line 166 and 168). A reference supporting that normal acetate levels in human plasma are 0.25mM has also been included .The intracellular labelling from U-C13 glucose proposed above would be very helpful to clarify this too. I cannot fully interpret their thiamine depletion experiment as it appears to have been done not in co-culture system so I am not sure how much it does support that no production of acetate via enzymatic happens in the co-culture system.The reaction doesn’t take place in the mitochondria, so we don’t think that the inhibition of the pyruvate carrier would affect acetate production .The experiment with thiamine free media aimed to support our previous publication showing that it is possible to produce acetate by a non-enzymatic reaction in the presence of ROS (adding H2O2). Our previous publication described this reaction in a cell-free system. We felt that we needed to prove that this reaction occurs in a cellular system. If the reviewer thinks that our results are confusing we would be happy to remove them.Finally treatment with HDAC might help ensure that indeed the acetate is mostly coming via production through glycolysis although this is supported by their labelling and might not be a key experiment.We thank the reviewer for this suggestion. As the reviewer acknowledged, our labelling experiments already supports that acetate is produced through glycolysis and thus we decided to focus our efforts on answering the essential questions highlighted by the editor.With regards to the role of ROS, the experiments are overall convincing including re the role of gap junctions. What is missing is direct proof that inhibiting gap junction would reduce acetate production in the co-culture and this is something that needs done to support the statement that it is the ROS transfer via gap junction that is leading to acetate production.Please, see answer to point 4 in “essentials”.Discussion – the authors state that acetate is used to feed TCA cycle to generate energy. This is not supported by the data as labelling of TCA cycle is unclear from co-culture and ATP production or oxygen consumption not shown. Acetate fate can be complex including in lipid biosynthesis or to support TCA cycle intermediates for biosynthesis of other macromolecules (cataplerosis). As such the authors should be careful about drawing conclusions which are not supported by their data and provide further evidence to their claims or change discussion (see above).We thank the reviewer for this comment. We have removed the conclusion of using the TCA cycle to generate energy as suggested by the reviewer. (Line 394)Also the conclusion “Mechanistically, our data revealed that acetate secretion involves not only a higher glycolytic rate but also the non-enzymatic ROS-mediated conversion of pyruvate to acetate, as cells grown in thiamine-free media were still capable to produce acetate” needs further experimental support although their data suggest this is likely true. The experiment suggested above to support this statement would also further support the conclusion that acetate comes mostly from the stroma.As explained above, this experiment was performed to support our work in a cell-free system. Additionally, our labelling experiments and RNA-seq experiments do not show an upregulation of the enzyme that converts acetate from pyruvate. We have changed this conclusion to tone down the message and write “quite likely” instead of “revealed”:“Mechanistically, our data revealed that acetate secretion involves not only a higher glycolytic rate but also very probably the non-enzymatic ROS-mediated conversion of pyruvate to acetate, as cells grown in thiamine-free media were still capable to produce acetate and expression of keto acid dehydrogenase was not upregulated”. (Line 395).The conclusion “We showed that AML cells are capable of modulating the metabolism of stromal cells by transferring ROS via gap junctions resulting in an increased secretion of acetate and its subsequent accumulation in the extracellular medium” is not fully supported as it is not shown that inhibiting gap junction reduces acetate.We have maintained this conclusion based on the new data presented in Figure 5F, in which we show a reduction in acetate extracellular levels when cells are grown in coculture in the presence of the gap junction inhibitor (CBX).Also “Furthermore, we found that AML cells consume the secreted acetate and use it as an energy source, by fluxing it into the TCA cycle” needs to be reconsidered as per above.As above, we have also removed “use as energy source”. Line 459Reviewer #3 (Recommendations for the authors):In general, I found the data in the manuscript to be novel, interesting and thought provoking. However, I would like to suggest some experiments that would help to solidify the claims that are made in the manuscript as well as potentially increase the impact of the work.1) While the acetate secretion by stromal cells and uptake by AML cells is a very interesting finding, I’m sure that many readers would join me in asking: what is the biological relevance of this? Is it simply a metabolic quirk or does it convey some advantage to the AML cells? Can the authors find any aspect of altered biology in the AML cells that may be relevant to disease progression, therapy resistance, relapse etc? Is it possible to block/inhibit AML import of acetate or stromal cell secretion of acetate in order to assess the impact of this phenomenon? Can alterations in culture conditions or treatment with AML therapy relevant drugs demonstrate a dependency/advantage conferred by stromal derived acetate? If so, this would significantly boost the impact of the work and demonstrate the importance of the mechanism.Please, see answer to point 4 in “essentials”.2) It may seem to be nit-picking, but I noted that it has not been directly shown that AML cells can metabolise the acetate that is produced by stromal cells upon co-culture. The metabolic tracing experiments have been performed using labelled acetate that has been added to the culture medium. Since this is a central claim of the manuscript, I think it is important to show this, if at all possible. Can the stromal cells be grown in media that will label the carbon molecules in acetate prior to co-culture, as opposed to adding acetate directly to the culture medium?Please, see answer to point 2 in “essentials”.3) Although the authors show no effect of AML cell growth upon co-culture, they do not assess whether the growth of stromal cells is altered. This would have important implications for the interpretation of any alteration in metabolism of these cells.We understand the concerns of the reviewer. Stromal growth could not be altered as stromal cells are grown until confluency prior to the experiment.4) I would strongly encourage the authors to use an additional method to rescue ROS production rather than NAC, which is problematic in this experimental setting since it can directly feed into the metabolic pathways that are being studied. As well as considering the use of other chemicals that are considered to act as antioxidants, I would also encourage the authors to explore overexpression of ROS detoxifying enzymes such as superoxide dismutase and catalase. By taking the latter approach, one could specifically detoxify ROS in either AML cells or stromal cells, which would help to strengthen the proposed transfer mechanism. Genetic ablation/knockdown of the same enzymes could also be used as an elegant way to strengthen the ROS transfer concept.We agree with the reviewer that experiments with genetic ablation/knockdown of catalase or superoxide dismutase would be a very good way to strengthen our results. Still, given the amount of time that we required for performing the essential experiments, these experiments have not been pursued.As suggested by the reviewer, we have performed additional experiments using the ROS-scavenging enzyme catalase. Treating cocultures with catalase affected acetate production by MS-5 .Additionally, based on the suggestion of using catalase to strengthen the proposed mechanism, we have performed experiments to determine the order of events (ROS/gap junction) and found a reduction in gap junction formation measured by calcein transfer when co-cultures are treated with catalase . Please, see answer to point 4 in “essentials”.5) Relating to 4), I was very surprised that the authors referenced the prior work documenting transfer of mitochondria between stromal cells and HSCs via gap junctions, but did not address whether this was of any mechanistic relevance to their own observations. Since mitochondria are thought to be the major source of intracellular ROS, this would seem to be a clear alternative possible mechanism which would yield similar experimental outcomes to those observed by the authors.et al., Cell Metabolism,2020 reference 14). Although the work from Forte et al., did not explore the mechanism of mitochondria transfer, previous work by others have linked the mitochondrial transfer to the formation of tunnelling nanotubes (TNT) . To our knowledge, mitochondria transfer between AML and stromal cells has never been linked directly to gap junctions Although transference of mitochondria through gap junction may indeed occur, our work aims to highlight a novel mechanism of ROS transfer (ROS/Gap/metabolic rewiring) that the AML cells use beyond mitochondria transfer.As mentioned by the reviewer, we were aware and cited the work of others revealing the importance of mitochondria and activation of glutathione-related antioxidant pathways in AML as a way of detox from ROS excess due to chemotherapy (Forte 6) The authors should make sure that the primary patient AML co-culture experiments have been conducted using identical culture conditions. It is problematic for the reader to assess the experimental outcome if culture conditions have been inconsistently altered across different test and control samples. I appreciate that such patient samples are not easy to acquire or work with, but the authors should repeat these experiments if necessary.We understand the concern of the reviewer. This was mainly due to the different growth conditions that were established in the two labs, JJ Schruinga’s lab where the first author of the paper spent a placement and our lab in the University of Birmingham. Still, I would think that the fact that by using two different culture conditions primary AML behave in the same way regarding acetate would be seen as a strength rather than a weakness, as it validates our observations in two different settings. Moreover, data is relative to MS-5 cells cultured in the exact conditions as the matching AML co-cultures.7) Related to 6), could the authors clearly state what the primary hematopoietic control cells that they use in the control experiments are? In the figure, it seems to suggest that peripheral blood mononuclear cells were used, but in the methods, it seems to suggest that CD34+ cells are used, which seems inconsistent with the description of PBMNCs. If the authors used CD34+ cells from AML patients, then I would suggest that CD34+ cells from the bone marrow of normal donors is probably the best control for this experiment.We used CD34+ cells from peripheral blood. We have changed PBMC in the figure legend by “healthy” .My final comment is beyond the scope of the current manuscript, but I would also encourage the authors to pursue this line of investigation further using the murine MLL-AF9 model that they perform a preliminary characterization with in this manuscript. This would afford the possibility of using a wide range of genetic models to interrogate mechanism in vivo, as well as a being an attractive model to explore biological relevance in the context of disease evolution and therapy.We thank the reviewer for his comment; indeed this is something that we would like to pursue further.


Dupilumab is the first monoclonal antibody therapy to be approved in Canada for the treatment of Chronic Rhinosinusitis with Nasal Polyps (CRSwNP). The goal of the study was to assess its effectiveness and efficacy in a real-world setting. This study aims to assess how clinical outcomes of biologic therapy in real-world application (effectiveness) correspond to outcomes in clinical trials (efficacy) and to look into factors that might explain an efficacy-effectiveness gap.A retrospective study evaluating disease specific sinonasal outcomes routinely collected for clinical care. This study included patients who were evaluated for coverage of dupilumab at a tertiary care rhinology clinic for the treatment of CRSwNP in the first year since dupilumab was approved in Canada for this indication. Sinonasal outcomes were be evaluated by collecting data on the Sino-Nasal Outcome Test (SNOT)-22 questionnaire.Eighty-five patients were considered for dupilumab therapy during the study period, 49% patients were able to attain coverage for the requested therapy. The mean SNOT-22 score at baseline was 60.56 (SD 21.63). After 16 weeks of treatment the mean SNOT-22 score decreased by 37 points to 23.36; at 28 weeks the mean SNOT-22 was 23.47. After 1 year, the mean SNOT-22 score was 14.37.Patients treated with dupilumab for CRSwNP at out tertiary rhinology clinic showed substantial clinical symptom improvement that is similar to that observed in prior randomised clinical trials. No serious adverse effects related to dupilumab were reported in this cohort. Long-term follow-up is needed to inform effectiveness analyses beyond the 1 year clinical trial duration. Chronic rhinosinusitis with polyps (CRSwNP) is a common idiopathic heterogeneous inflammatory disease of the nose and paranasal sinuses that is commonly characterized by the clinical symptoms of nasal obstruction, rhinorrhea and olfactory loss. The diagnosis of CRSwNP is dependent upon the presence of major symptoms for at least eight consecutive weeks with confirmatory findings on either computed tomography (CT) scan or nasal endoscopy . The sevCRSwNP has been classified as a type 2 inflammatory disease in North America and Europe . As suchGiven the inexperience of clinicians managing patients with CRSwNP, the Canadian Rhinology Working Group produced a white paper providing guidance to treating physicians, both in Canada and internationally, when considering monoclonal antibody therapy for patients with CRSwNP . DespiteA single center electronic medical record (EMR) practice audit of access to dupilumab therapy and disease-specific quality of life outcomes for patients with CRSwNP considered for dupilumab treatment was conducted. All identified patients had applied for dupilumab coverage through the FREEDOM program . The result of this application was reviewed for each patient. Data on diagnosis, application status, and patient characteristics were obtained. The electronic medical record contains, among others, information on individual prescriptions with dupilumab dosage, date of first administration and administration duration as well as adverse events. Data was collected and managed in an excel spreadsheet .Patients with CRSwNP who had undergone prior sinus surgery  and had been managed with topical steroid therapy with or without systemic steroid were considered for dupilumab therapy between August 18, 2020 and Sep 15, 2021. Characteristics that were recorded for included patients were age (at visit for dupilumab application), gender, number of prior surgeries, time since last surgery, presence of asthma, NSAID sensitivity, aeroallergen sensitivity, start date of dupilumab therapy and number of doses of dupilumab up until the date of data cut off as well as adverse events.The Sinonasal Outcome Test- 22 (SNOT-22) is a validated and reliable tool for assessing symptoms of chronic rhinosinusitis with polyps; its minimal clinically important difference (MCID) is 8.9 points [We present a descriptive analysis of patient characteristics and the changes in SNOT-22 scores collected during the period of time of this chart review.All methods were carried out in accordance with relevant guidelines and regulations. The study was approved by the research ethics board, (IRB #Pro00057336). The study was performed in accordance with the ethical standards of the 1964 Helsinki declaration and its later amendments or comparable ethical standards.A total of 85 patients were considered for dupilumab therapy during the study period. Forty-three patients started therapy; ten patients are awaiting the decision from their insurer during the study period. We present the baseline data for the 53 patients who have started therapy or are awaiting a decision Table . In thisA total of 85 patients requested insurance coverage for dupilumab therapy between Aug 18, 2020 and Sep 15, 2021. Of these, 42 (49%) patients were able to attain coverage for the requested therapy; one patient was denied coverage but started therapy by paying out of pocket. The reasons for noncoverage of patients by their insurers are listed in Table All patients who initiated dupilumab therapy opted to receive therapy by self-injection at home rather than receiving treatment in the rhinology clinic. The cohort had a mean baseline SNOT-22 score of 60.56 SD 21.63). After 16 weeks of treatment the mean SNOT-22 score decreased by 37 points to 23.36; this improvement was maintained at 28 weeks with a mean SNOT-22 of 23.47 , after 16 and 28 weeks of treatment, the mean score for this item was 1.8 (SD 1.7) and 1.65 (SD 1.53) respectively.Baseline SNOT-22 scores grouped by domains showed that the rhinologic symptoms domain (maximum score = 30) had the highest score mean 20.4 SD 5.8) followed by the sleep dysfunction domain (mean 15.6 SD 6.7) and the extra-nasal rhinologic symptoms domain (mean 8.7 SD 3.2). Table  SD 5.8 fAt each follow-up appointment patients were screened for the following potential adverse events: changes in their asthma control, arthralgia, ocular changes , local reactions at the injection site, dermatologic changes, nasopharyngitis). Each patient was also offered the opportunity to inform their clinician of any new symptoms they may be experiencing since the initiation of dupilumab therapy. One patient reported a single incident of transient skin erythema at the injection site lasting up to 2 h. A second patient reported experiencing dry eyes but the patient has a history of thyroid eye disease which can also be associated with dry eyes. No therapy was sought for this symptom. A third patient reported bilateral joint pain specifically in the knees and ankles that started 3 months after the start of dupilumab therapy. At this time dupilumab was stopped and the patient was referred to a rheumatology specialist. A full rheumatologic panel was done and was negative. Patient resumed dupilumab therapy after 4 months but reduced the frequency of injection to once a month instead of every two weeks. At this time the patient noticed a slight return of joint pain and stiffness but no swelling. A fourth patient reported ongoing cough that required prednisone as determined and prescribed by their family physician. Lastly, one patient reported having been hospitalized for 4 days due to an episode of asthma exacerbation while on dupilumab therapy.We present our experience using dupilumab for the treatment of CRSwNP in the first year since it was approved in Canada for this indication. Improvement in the SNOT-22 scores seen in our cohort after 28 weeks  of therapy exceeded the minimal clinically important difference of 8.9 points. These changes were also seen in the efficacy of dupilumab in clinical trials  [In the last 12 months at our centre, 85 patients applied for insurance coverage for dupilumab therapy, 42 patients 49%) received coverage and started therapy; one additional patient was denied coverage but started therapy by paying out of pocket. The main reason given by the insurers was that they were not considering coverage for the CRSwNP indication at the time of application. To date, the Canadian Agency for Drugs and Technologies in Health (CADTH) has provided a reimbursement recommendation for dupilumab for the atopic dermatitis and asthma indications % receive, howeverThis study sought to identify evidence, from a single center tertiary care rhinology practice, of an efficacy-effectiveness gap between clinical trial results with dupilumab in comparison to real world experience. Baseline mean SNOT-22 score of the practice cohort  exceeded the MCID when compared to the baseline data of the dupilumab trial groups . However, the 24-week SNOT-22 scores  from the treatment group in the SINUS-52 clinical trial were not different than similar time SNOT-22 scores of this clinical cohort (23.36 SD 15.97). This suggests that there does not appear to be an efficacy-effectiveness gap when considering symptom improvement as reported by patients using the SNOT-22 questionnaire. We were unable to evaluate other outcomes included in the SINUS- 24 and SINUS 52 studies such as polyp score, olfactory function using objective measures and Lund-Mackay CT scores, however, the SNOT-22 is a well validated instrument that is able to discern treatment effects and is representative of patient CRS-related quality of life. Further, the SNOT-22, a subjective patient reported outcome measure (PROM), has been identified as a key CRS outcome for research and currently the most notable when considering patient preference and value judgements for treatment options , 12. As The Canadian Rhinology Working Group recommends that biologic therapies for chronic rhinosinusitis be considered only for patients who have failed medical therapy and have undergone sufficient sinus surgery or for patients who cannot undergo sinus surgery and have failed medical therapy . HoweverLong-term follow-up data is needed in order to determine if the higher yearly cost of dupilumab therapy is offset by the need for multiple surgeries, disease complications, the costs and any adverse effects of systemic and topical corticosteroids as well as the impact on the quality of life for patients who have poorly controlled CRSwNP. Underappreciated, is the effect of CRSwNP on the olfactory ability of patients, with those affected having levels of impact ranging from impairment, to disability and potential handicap . In partAs with any new therapy, but specifically with the advent of biologic therapy for CRS, clinicians will rightfully be seeking to evaluate an efficacy-effectiveness difference between the trial results and clinical practice. The current study, although small, provides a first look for this difference. No efficacy-effectiveness gap is evident from the current results. Further study is required to evaluate the long-term implications of monoclonal antibody therapy use in patients with poorly controlled CRS despite adequate surgical and medical therapy.


Hif-1a, Aldoa, and Pgk1 expression, suggesting upregulated glycolysis, whereas MTD NAC causes a significant reduction in the expression of the aforementioned genes and of Vegf, leading to vascular remodeling in MTD-treated tumors. Taken together, this study demonstrates the ability of combined optical and molecular methodologies to provide a holistic picture of tumor response to therapy in CRC in a minimally invasive manner.Metronomic chemotherapy (MET) has been developed to address the shortcomings of maximum-tolerated chemotherapy (MTD) in regard to toxicity and development of resistance mechanisms in the tumor. In colorectal cancer (CRC), MET is a promising novel strategy to treat locally advanced malignancies when used as neoadjuvant chemotherapy (NAC). However, so far there are no preclinical studies to assess the impact of MET NAC in CRC to assess the benefits and challenges of this approach. Here, we used a primary model of CRC (via azoxymethane) to analyze longitudinal changes in angiogenesis in primary tumors under MET and MTD NAC using a combination of diffuse reflectance spectroscopy and mRNA expression (via qPCR). Our results show that MET and MTD NAC lead to increased mean tissue oxygen saturation  and oxyhemoglobin (15% and 10%) between weeks 2 and 5 of NAC, and that such increases are caused by distinct molecular signatures in the angiogenic program. Specifically, we find that in the MET group there is a sustained increase in  Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the US In biomedical research, there is an active area of interest in novel treatment strategies that can be used to treat locally advanced disease in CRC. In this regard, an increasing body of evidence has shown that neoadjuvant chemotherapy  is able to reduce tumor size, facilitate resection, and improve completion rates in CRC Although the goal of MTD NAC is to reduce tumor burden as much as possible, its associated toxicity makes necessary the delivery of therapy in a cyclic manner. For example, the FOLFOX regimen  is delivered in cycles that last two weeks; only the first 48 h are of active infusion, followed by 12 days of rest During the last decade, the biological effect of chemotherapeutic drugs at doses below the MTD threshold started to be explored. The term “metronomic chemotherapy” was coined to describe chemotherapy that involves the use of lower but active doses of chemotherapeutic drugs without prolonged rest periods in between Various studies have explored the use of MET in recurring and late-stage malignancies such as colon, glioma, breast, and ovarian cancer where it has been shown to improve survival More specifically, although it is assumed that the main effect of MET is its ability to disrupt the angiogenic program of tumors by impairing blood vessel development, it is not known how this effect varies between different types of malignancies. In particular, it is possible that the anti-angiogenic effect of MET is heavily dependent of the anatomic location of the tumor, as it is known from preclinical studies that the tumor milieu plays a critical role in the response to treatment In this study, we hypothesized that the differences in dosing and frequency of administration between MTD and MET NAC would cause distinct changes in the angiogenic program of primary colorectal tumors that could be analyzed to better understand the opportunities and pitfalls of MET NAC when used on CRC. To this end, we used a dual approach to examine ‘high level’ and ‘low level’ changes in angiogenesis. Firstly, we used endoscopic diffuse reflectance spectroscopy (DRS), an optical technique that enables quantification of physiological metrics of perfusion in tissue such as oxygen saturation  involved in the classical hypoxia-inducible factor 1 (HIF-1A) and vascular endothelial growth factor (VEGF) angiogenic axis to examine molecular (‘low level’) changes that could provide the rationale for the observed changes in perfusion obtained via DRS. In addition, gene expression data were used to gain insight in the metabolic alterations that therapy progression causes in the tumor for both MET and MTD NAC. Our study addresses the need to connect ‘high level’ reporters of perfusion of DRS with molecular changes via qPCR to better understand the challenges and opportunities of MTD and MET NAC strategies in CRC.All procedures were approved by the University of Arkansas Institutional Animal Care and Use Committee under protocol 21024. An azoxymethane (AOM) model of CRC was used where nine-week-old female A/J mice  received AOM injections  at a dose of 10 mg/kg once a week for six weeks At 16 weeks after the last AOM injection the size of tumors was periodically assessed using a veterinary colonoscopy system  as we have previously described During colonoscopies, tumor size was scored relative to the circumference of the colon using a modified version of the tumor scoring system of Becker et al. Chemotherapy was based on 5-FU , which was first solubilized in dimethyl sulfoxide  to a concentration of 50 mg/mL. This solution was then diluted in sterile saline to concentrations of 3.0 mg/mL (for the MTD group) and of 1.2 mg/mL (for the MET group), stored at -20ther day A. DosingThe next day of the first 5-FU  injection, mice underwent a colonoscopy as previously described and DRS spectra were acquired as we have reported elsewhere Spectra were post-processed to obtain perfusion values from tissue , and total mRNA extraction was performed using the RNAeasy Micro Kit  following manufacturer recommendations. Quality of the extracted mRNA was determined using a spectrophotometer , using samples whose 260/280 absorbance ratio ranged between 1.8–2.0 Vegf and Hif-1a as they are known to be the main drivers of vascular development in tumors. Additionally, Dek and Stat3 were used as they influence Vegf expression in an Hif-1a independent manner Hif-a we used RaptorFrom all the potential pro-angiogenic targets we chose Gapdh) as the housekeeping gene The Luna Universal qPCR Master Mix  was used for qPCR employing 2 µL of cDNA sample and 18 µL mix of master mix  per well in 96-well plates , which were sealed using transparent film . All qPCR experiments were performed in a CFX96 Real Time PCR system (Bio-Rad) and were run in triplicate. Changes in the relative mRNA expression of all genes were quantified using Pfaffl’s method After the 6th (last) endoscopy for DRS and biopsy acquisition, mice were euthanized and colons were excised and cleaned using phosphate-buffered saline solution.Tumors were identified by comparing their anatomical location with the available imaging data in each case. Samples were stored in 10% neutral-buffered formalin for 24 h, rinsed in saline, and later professionally embedded in paraffin and prepared by IHC World . Samples were sectioned in the sagittal plane to a thickness of 5 µm prior to immunoperoxidase staining for Nestin-1 , a marker that is used to detect vessels in AOM-induced tumors Tumor sections were imaged in an upright Nikon widefield microscope using a 10x objective (0.30 NA), and a gain of 1. Between 1–3 non-overlapping regions of interest (ROI) were obtained per sample, and in each ROI areas for segmentation were labeled as Nestin-positive (brown), background, or tissue (blue). The segmentation of each ROI was performed using the Trainable WEKA Segmentation from Fiji Statistical analyses were performed in R (4.1.1) A subset of tumors from each group was randomly selected to determine the trend in scores from each group . In other words, the scores for the same tumors were followed up over time, and the individual trends for each tumor were plotted, and the proportion of tumor scores within each group was quantified each week. If missing observations existed for a tumor, those were not included in the overall count used to quantify the final proportion. .For the longitudinal data  an assessment of the trends in the response over time showed that they did not follow a linear pattern , 4. Therp-values were considered below 0.05.For the imaging data, a Kruskal Wallis test was performed for the MVD values between groups to determine any statistically significant differences. Significant The size of tumors was endoscopically determined using the imaging data obtained during each colonoscopy . The analysis of imaging data revealed that in the MTD group changes in tumor size and appearance were endoscopically visible, including tumor regression in some cases A, whereaUsing the endoscopically-acquired spectroscopy data we longitudinally quantified values of perfusion in all groups. For fold changes in ectively A. For Hbectively B. Total ectively C. The trectively D with meTo determine if significant differences between the different groups existed, we performed pairwise comparisons to estimate the difference between the fitted smooths (via GAMs) for each DRS-derived perfusion value across the different groups. The rationale in this case is that when the difference between the fitted smooths is computed, a simultaneous confidence interval (s-CI) can be constructed around the difference, and the regions where the s-CI does not cover zero can be considered statistically significant periods of change. To improve visualization, we added a ribbon to highlight those periods where statistically significant differences existed. Significant differences existed in genation E, whereagenation F. For Hb 3 and 4 G. For tH 3 and 4 H, I.Vegf showed a decrease over time in the CG and MET groups and an increase over time was observed in the MTD group, the MTD-treated tumors showed a 50% reduction in the expression of Vegf at week 1. Over the course of the study, the expression of Vegf in the MTD-treated group remained below the levels observed in the other groups  were obtained for each group in each case . Althougr groups A.Hif-1a, a decrease in expression was observed in the CG group between weeks 1–4 followed by an increase between weeks 4–6; a increase between weeks 1–4 followed by a decrease between weeks 4–6 was observed in the MET group; and a 50% reduction at week 1 was observed in the MTD group, followed by an increase over the six-week period , and MET-MTD (weeks 1–6) groups (In the case of  3 and 4 E. In the 3 and 4 F. Additi) groups G, H.Hif-1a and Aldoa, but in this case significant differences existed between all groups. The expression of this gene was significantly lower in the MET group compared to the CG group between weeks 3-4 . There was a significant difference between the CG-MTD and MET-MTD groups in MVD (.9×10−7) D.Fig. 6IAlthough MTD NAC in CRC aims to maximize the number of cancerous cells to be killed, this ultimate goal is limited by the rest periods it requires which lead to tumor re-growth and resistance In this regard, one way that tumor response to therapy  has been extensively studied in the past involves the use of DRS as a low-cost, non-destructive approach that quantifies changes in perfusion parameters  would be able to provide a more comprehensive picture of the effect of MET and MTD NAC regimens in tumor angiogenesis in CRC. Our results suggest that while MET and MTD NAC elicit similar responses in perfusion, they cause distinct molecular responses in tumors under 5-FU chemotherapy. Considering the current interest in MET, our study points to the importance of the use of multimodal approaches that can provide insight on the different mechanisms that the angiogenic program of tumors undergo during therapy.Specifically, because in the classical angiogenesis pathway the main driver of vascular development is From our imaging data , only the MTD group showed endoscopically visible tumor regression, whereas such changes were not observed in the MET and CG groups A. FurtheHowever, it has to be noted that endoscopic quantification of tumor size using categorical scores from imaging data cannot provide a direct assessment of tumor size such as traditional tumor volume measurements in subcutaneous murine models. Endoscopic quantification of tumor size is challenging due to the inherent variability in the obtained imaging data due to the anatomical location of the malignancies, and because of this the focus our work here was centered on analyzing tumor sizes but rather evaluating how physiological (via DRS-derived markers of perfusion), and molecular values (via mRNA expression) could be used to evaluate the efficacy and limitations of MET NAC.Our DRS results show that NAC (either MTD or MET) causes a similar effect in the trends of ond half A, B. The 3 and 5 G, the saThe significant increase in Vegf across all groups. Our analysis shows that both MET and MTD NAC are able to decrease the relative expression of Vegf when compared to the levels of untreated tumors, but such reduction is only significant for the MTD group through the first 4 weeks of treatment when compared to the MET and CG groups  leads to significant blood vessel reduction/remodeling in the tumor when compared to the MET and CG groups  Pgk1 (phosphoglycerate kinase 1), which is one of the two ATP-generating enzymes in glycolysis Hif-1a, Aldoa, and Pgk1 has a similar trend , and from week 2 until week 6 (Pgk1)  instead of limiting tumor growth.Interestingly, 6 (Pgk1) F, K. ThiStat3 and Dek, which are known to regulate VEGF in a HIF-1a independent manner Hif-1a we analyzed Raptor, as it encodes the RAPTOR protein which in turn regulates HIF-1a in an oxygen-independent manner Because angiogenesis is a complex process that does not rely exclusively on hypoxia to occur, we also analyzed three genes that regulate VEGF and HIF-1a by independent mechanisms. In the case of VEGF, we analyzed Raptor, the trend in expression in the MET group remains relatively flat and similar in magnitude to that of the CG group, but the MTD group shows decreased expression at week 1 (Raptor expression between the CG and MTD groups (at week 6), and the MET-MTD groups (beginning of week 1 until the end of the study) Stat3 and Dek across all treatment groups, indicating that both genes do not play a major role in regulating Vegf expression in primary colorectal tumors .For  (≈ 50%) G. MoreovIn the past, DRS has been used to quantify tumor response to therapy in vivo as there is potential in the use of the information generated by these technologies to determine their correlation with molecular markers of treatment response in CRC. In this way, DRS can be used to better to better understand the effects of therapy with regard to tumor resistance. Additionally, there is a need to obtain longitudinal information from tumors at the molecular level  as such methods can provide powerful insight on the periods of increased cellular activity or changes in metabolism that can be exploited by novel therapeutic drugs and treatment strategies.On the other hand, the endosocopic application of DRS and the acquisition of colorectal tumor biopsies (where the placement of the instruments is done in an indirect manner) presents multiple challenges which can lead to artifacts in the collected signal due to pressure or probe misplacement Vegf expression when compared to tumors treated with MET NAC; such reduction leads to the remodeling of blood vessels, therefore causing decrease in MVD, which is quantifiable at the end of therapy. In MET-treated tumors the increase in oxygen saturation is caused by an increase in perfusion, and because Aldoa and Pgk1 have increased expression, glycolysis appears to be upregulated in the MET group. Our study also demonstrates that when used in tandem, optical and molecular techniques can provide a comprehensive picture in the effects of novel treatment strategies. Our long term goal is to incorporate RNA-seq and optical techniques  to holistically examine tumor biology and identify opportunities and challenges for novel therapeutic approaches in colorectal cancer. Future work will incorporate the use of technologies (such as MRI) that allow primary tumor burden quantification, and the use of male mice to address potential sex-specific effects of chemotherapy.In summary, in this study we used a combination of diffuse reflectance spectroscopy and mRNA expression (via qPCR) to longitudinally assess changes in the angiogenic program of primary colorectal tumors under MTD and MET NAC regimens. In our model, MET and MTD NAC cause an increase in oxygen saturation in tumors that is quantifiable via DRS and becomes significant between the third and fourth week of treatment. When paired with the trends in mRNA expression, additional context can be provided to the observed changes in oxygenation. In the MTD group the increase in saturation is driven by reduced oxygen demand and is coupled with a significant reduction in