A lncRNA RP1-85F18.6 was reported to affect cell growth by regulating the cell cycle. Here we tested whether it affects the proliferation of osteoblast cells by regulating the cell cycle. We determined the expression of RP1-85F18.6 in two osteoblast cell lines hFOB and HOB by qPCR. Then we knocked down or overexpressed RP1-85F18.6 in hFOB and tested the alteration of viability, cell cycle, and cell cycle regulatory proteins. Results showed that both hFOB and HOB expressed RP1-85F18.6. The knockdown of RP1-85F18.6 decreased the viability of hFOB, while the overexpression of it increased the viability. Higher expression of RP1-85F18.6 results in higher cell viability. The knockdown of RP1-85F18.6 caused an increase in the S phase cells and a decrease in the G2/M phase cells. The overexpression of RP1-85F18.6 caused a decrease in the S phase cells and an increase in the G2/M phase cells. The knockdown of RP1-85F18.6 decreased cyclin A, cdk1, E2F, cyclin B, p53, and p21, whereas the overexpression of RP1-85F18.6 increased cyclin A, cdk1, E2F, cyclin B, p53, and p21. This study demonstrated that RP1-85F18.6 is expressed in osteoblast cell lines hFOB and HOB. RP1-85F18.6 affects the proliferation of osteoblasts by regulating the cell cycle. Annually, about 9,000,000 fracture cases are caused by osteoporosis worldwide . ApproxiLong non-coding RNAs (lncRNAs) are RNA transcripts with lengths over 200 nucleotides but are not translated into proteins . Much asA newly identified lncRNA, RP1-85F18.6, which is located on human chromosome 22 . Here we22.1® CCL-227) and human osteoblast cell line hFOB 1.19 (ATCC® CRL-11372™) were purchased from ATCC . The primary human osteoblast (HOB) cell line was purchased from PromoCell . SW620 was cultured in Dulbecco’s modified Eagle’s medium containing 10% fetal bovine serum, and the other two cell lines were cultured in Osteoblast Growth Medium C-27001  in a humidified atmosphere of 5% CO2 at 37°C.Human colon cancer cell line SW620 [SW-620] , and the sequences are as follows: GAPDH forward, 5′-GAAGGTGAAGGTCGGAGTC-3′; GAPDH reverse, 5′-GAAGATGGTGATGGGATTTC-3′. LncRNA RP1-85F18.6 forward, 5′-GGCTCTTTGCTCACATCG-3′; reverse, 5′-AAGGAAACCACAGGCTCA-3′.2.4® 2000 , which was described previously [The knockdown and overexpression of RP1-85F18.6 were achieved by the transfection of the siRNA or expression vector. The cells were transfected using Lipofectamineeviously .RP1-85F18.6 knockdown: lncRNA RP1-85F18.6 small interfering (si)RNA and negative control (NC) siRNA were purchased from Guangzhou RiboBio Company . The sequences were as follows: lncRNA RP1-85F18.6 siRNA, 5′-GACTCCGCCGTGAACCCTTCA-3′. A scramble siRNA (siN05815122147) was used as the NC siRNA. The transfection concentration of siRNA was 60 nM.® 2000. The transfection concentration of the plasmid was 2 µg/mL.RP1-85F18.6 overexpression: the entire sequence of human lncRNA RP1-85F18.6 was amplified from hFOB cell lines using PCR and cloned into the pcDNA3.1 vector. The NC empty vector, which was purchased from Shanghai GeneChem Co., Ltd , and the lncRNA RP1-85F18.6 plasmid were transfected into hFOB using Lipofectamine2.56/mL. Then, the cells were fixed with 100% ethanol and incubated for 3 h at 4°C. Then, the suspended cells were washed with PBS twice and added with PI staining solution . Then, the cells were incubated at 37°C for 15 min for staining. A BD FACSCalibur was used to acquire cell cycle data. FlowJo Version 10 was used for the cell cycle analysis.The cell cycle was analyzed using flow cytometry with propidium iodide (PI) staining, which was described previously . Briefly2.6® analysis software version 4.3.0. . The experiment was repeated more than three times.Protein expression was determined by a western blotting assay, which was described previously . ProteinThe primary antibodies used in the experiment are as follows: anti-cyclin A antibody (sc-271682), anti-cdk1 antibody (ab18), anti-E2F antibody (ab179445), anti-cyclin B antibody (ab72), anti-p53 antibody (ab26), anti-p21 antibody (ab109520), cyclin D1 antibody (#2922), anti-Cdk2 antibody (ab32147), anti-cyclin E1 antibody (ab33911), and anti-Cdk2 antibody (ab32147). The secondary antibodies were all purchased from Sigma-Aldrich (USA).2.7T-test or one-way ANOVA and Dunnett’s post hoc tests were used to compare the significant difference between the control and experimental groups (p  <  0.05). GraphPad Prism (version 6) was used to plot the figures and calculate statistics.All the experiments were repeated three times. 33.1Here we tested the expression of lncRNA RP1-85F18.6 in two osteoblast cell lines hFOB and HOB by a PCR assay. Colon cancer cell line SW620, which was reported to have RP1-85F18.6 expression, was used as the positive control . Results3.2To further explore the role of RP1-85F18.6 in osteoblasts, we selected one of the osteoblast cell lines hFOB, which has a higher expression of RP1-85F18.6, to conduct the subsequent study. We knocked down or overexpressed RP1-85F18.6 in hFOB and confirmed the expression by a PCR assay. Results showed that compared to blank control (control), the expressions of RP1-85F18.6 in NC for silencing RNA (NC siRNA) and NC for overexpression (NC overexpress) were not significantly different, while the expression in RP1-85F18.6 knockdown cells (si-RP1-85F18.6) was significantly decreased, and the expression in RP1-85F18.6 overexpressing cells (over-RP1-85F18.6) was significantly increased. This indicated that both the knockdown and overexpression were successful .3.3To test whether RP1-85F18.6 affects cell proliferation, we compared the viability of knocked-down cells, overexpressing cells, and wild-type osteoblasts using an MTT assay. MTT assay has been widely used in cell proliferation study . Results3.4To further explore the effect of RP1-85F18.6 on cell growth of osteoblasts, we analyzed the cell cycle of hFOB cells using a flow cytometry assay with PI staining. Results showed that compared to the control, the cell cycles of NC siRNA and NC overexpress were not significantly different, indicating that the transfection had no effect on the cell cycle. The knockdown of RP1-85F18.6 had no effect on the G0/G1 phase cells but caused a significant increase in the S phase cells and a decrease in the G2/M phase cells. On the other hand, the overexpression of RP1-85F18.6 also had no significant effect on the G0/G1 phase cells but caused a decrease in the S phase cells and an increase in the G2/M phase cells. This indicated that the expression of RP1-85F18.6 affected osteoblast cells in the S and G2/M phase . Therefo3.5p > 0.05). The knockdown of RP1-85F18.6 decreased the expression of cyclin B, p53, and p21 , whereas the overexpression of RP1-85F18.6 increased the expression of cyclin B, p53, and p21   . Moreove < 0.01) . Therefo < 0.01) .4This study tried to reveal the role of a newly discovered lncRNA RP1-85F18.6 in the proliferation of osteoblasts. We confirmed that RP1-85F18.6 was expressed in both adult (HOB) and fetus (hFOB) derived osteoblast cell lines. These two cell lines are different in their capability of proliferation and differentiation, but it is unknown whether this is associated with their difference in RP1-85F18.6 expression levels. In this study, we focused only on one of these cell lines, hFOB. The reason for selecting hFOB is that hFOB has higher expression of RP1-85F18.6, and it is a stable cell line for transfection . PreviouRP1-85F18.6 was reported to increase colon cancer cell growth , and we E2F is a protein that can activate genes required for DNA synthesis and S phase progression. The cyclin A and cdk1, downstream targets of E2F, are responsible for S phase regulation . In thisBesides, the p53/21 pathway is responsible for the negative regulation of cyclin B and cdk1, regulating activities of the G2 phase in cancer cells . The accFurthermore, cyclin D and cyclin E are the regulators for cell activities in the G1 phase . Our resIn summary, this study demonstrated that lncRNA RP1-85F18.6 plays a role in the proliferation of osteoblasts by affecting their cell cycle by regulating several cell cycle proteins. We suggested that RP1-85F18.6 is an upstream target of cell cycle-related proteins, but whether its regulation is direct or indirect is still unclear and requires more exploration. Additionally, lncRNA H19 was reported to promote osteoblast differentiation ,21. Furt


D-galactosamine. While LPS and TNF induced significant activation of apoptotic caspase 3/7, lipid tissue peroxidation and serum ALT accumulation in mice without entolimod treatment, these indicators of toxicity were reduced by entolimod pretreatment to the levels of untreated control mice. Entolimod was effective when injected 0.5–48 hours prior to, but not when injected simultaneously or after LPS or TNF. Using chimeric mice with hematopoiesis differing in its TLR5 status from the rest of tissues, we showed that this protective activity was dependent on TLR5 expression by non-hematopoietic cells. Gene expression analysis identified multiple genes upregulated by entolimod in the liver and cultured hepatocytes as possible mediators of its protective activity. Entolimod did not interfere with the antitumor activity of TNF in mouse hepatocellular and colorectal tumor models. These results support further development of TLR5 agonists to increase tissue resistance to cytotoxic cytokines, reduce the risk of septic shock and enable safe systemic application of TNF as an anticancer therapy.Tumor necrosis factor alpha (TNF) is capable of inducing regression of solid tumors. However, TNF released in response to Toll-like receptor 4 (TLR4) activation by bacterial lipopolysaccharide (LPS) is the key mediator of cytokine storm and septic shock that can cause severe tissue damage limiting anticancer applications of this cytokine. In our previous studies, we demonstrated that activation of another Toll-like receptor, TLR5, could protect from tissue damage caused by a variety of stresses including radiation, chemotherapy, Fas-activating antibody and ischemia-reperfusion. In this study, we tested whether entolimod could counteract TNF-induced toxicity in mouse models. We found that entolimod pretreatment effectively protects livers and lungs from LPS- and TNF-induced toxicity and prevents mortality caused by combining either of these agents with the sensitizer,  During infection, stimulation of Toll-like receptor 4 (TLR4) by lipopolysaccharide (LPS) from the outer membrane of gram-negative bacteria induces hematopoietic cells, particularly macrophages, to express a variety of pro-inflammatory cytokines . LPS actTumor necrosis factor alpha (TNF) plays a critical role in endotoxic (LPS-induced) shock, initiating the inflammatory reaction of the innate immune system by stimulating release of pre-formed TNF as a positive autocrine feedback signal to activate NF-κB and produce additional TNF as well as other cytokines such as GM-CSF and IL-8 . TNF canin vitro and in vivo studies has established that TNF exerts potent cytostatic and cytotoxic effects on tumors. These effects are strongly dependent on tumor type; colorectal, lung and breast cancers are among those displaying the highest sensitivity to TNF [TNF is also a key mediator of toxicity in tumors. TNF was first identified due to its ability to induce hemorrhagic necrosis of solid tumors and a large body of data from preclinical y to TNF –15. In ay to TNF , 17. Howy to TNF . Becausey to TNF , 18, 19.y to TNF , 21. UnfIn contrast to the potentially harmful outcome of TLR4 activation, stimulation of TLR5 by its ligand, the bacterial flagellin protein, leads to activation of NF-κB-dependent transcription and subsequent induction of multiple factors promoting cell growth, tissue regeneration and cell survival. Entolimod (CBLB502) is a pharmacologically optimized recombinant derivative of flagellin with reduced immunogenicity that was designed as a powerful and specific agonist of TLR5 . EntolimAn important consideration for potential use of entolimod to protect normal tissues during anticancer treatment with TNF is whether TLR5 stimulation would also protect tumors. Notably, our prior studies in multiple mouse models with total body irradiation , local rIn this work, we used mouse models to (i) test whether TLR5 stimulation by entolimod can mitigate LPS and TNF toxicity in normal tissues and, if so, identify the cellular and molecular mechanisms underlying this activity, and (ii) determine whether TLR5 stimulation affects the antitumor activity of TNF in mouse hepatocellular carcinoma (HCC) and colorectal cancer (CRC) models. Our results show that entolimod significantly reduces LPS and TNF toxicity in mice and that this activity is dependent on TLR5 expression by non-hematopoietic cells. In addition, we identified a number of genes encoding tissue protective factors that were upregulated by entolimod treatment in the liver and cultured hepatocytes suggesting that they may be involved in TLR5-mediated protection against LPS and TNF toxicity. Importantly, administration of entolimod did not reduce the antitumor efficacy of TNF in the CT26 model. Moreover, in HCC (BNL and Hepa 1–6) tumor models, we showed that entolimod prevented mouse mortality caused by TNF combined with D-galactosamine  sensitization but did not diminish tumor growth suppression. Overall, our results suggest that TLR5 agonist-based therapy can be used to increase tissue resistance to cytotoxic cytokines, reduce the risk of septic tissue distribution, and enable safe application of TNF for cancer treatment.tm1Aki) were a generous gift of Dr. Shizuo Akira  and BALB/c-Tg(IκBα-luc)Xen reporter mice were originally purchased from Xenogen ; both of these mouse strains were bred at RPCCC. All mice were maintained at 21°C with a 12-h light cycle in a pathogen-free environment with automatic reverse osmosis watering ports and standard chow. To create chimeric mice, TLR5-KO mice were irradiated with 9 Gy using a 137Cs Mark I-30 irradiator (J.L. Shepherd and Associates) and injected intravenously 3 h later with bone marrow cells (5×106 cells in 200 μL PBS) freshly isolated from wild type C57BL/6 donor mice. Control mice were irradiated and injected with either wild type or TLR5-KO bone marrow cells of the same genotype as the recipient mice. Two months after bone marrow transplantation, the mice were used to test entolimod’s protective activity in an LPS-induced septic shock model.NIH Swiss , BALB/c and C57BL/6  mice (8–12 weeks old) were used. Immunodeficient C.B.17 SCID mice were obtained from a colony maintained in the Department of Laboratory Animal Resources (DLAR) of Roswell Park Comprehensive Cancer Center . TLR5 deficient (TLR5-KO) mice  when indicators of severe morbidity  developed. Euthanized mice were considered non-survivors.All animal experiments were approved by the Institutional Animal Care and Use Committee (IACUC) of RPCCC, complied with all university, state and federal regulations and met the standards of the “Guide for the Care and Use of Laboratory Animals”. Experimental procedures were carried out by trained research specialists at RPCCC under the supervision of DLAR veterinary staff. In the septic shock model, organ failure and mortality usually occur within 6–8 h after injection of LPS or TNF with D-galactosamine. To avoid treatment- or tumor-related pain or death as an endpoint, animals were closely monitored after treatment with LPS and TNF for signs of discomfort, pain and distress hourly for eight hours, then twice a day for two days, then daily until the end of the experiment. This allowed us to avoid prolonged animal distress and humanely euthanize mice as required by IACUC guidelines  and D-galactosamine was purchased from Cayman Chemical . Recombinant human TNF-alpha (referred to herein as TNF) was purchased from Peprotech . Purified anti-Ly6G (α-Ly6G) and appropriate isotype control antibodies were purchased from BioXcell .Entolimod   was obtaIκBα-luc)Xen mice as described previously [−7 M dexamethasone, and 1x insulin-transferrin-selenite [2.Murine colorectal undifferentiated carcinoma CT26 cells from American Type Culture Collection  were cultured in RPMI containing 10% fetal bovine serum (FBS) with standard supplements and 1% penicillin/streptomycin. Murine hepatocellular carcinoma (HCC) BNL-1ME A.7R.1 (BNL) and Hepa 1–6 cells from ATCC were cultured in DMEM supplemented with 10% FBS and 1% penicillin/streptomycin. Primary mouse hepatocytes were isolated from livers of BALB/c-Tg(eviously  and cultselenite . Cells wMouse hepatocytes containing a luciferase reporter construct controlled by an IκB-dependent promoter were used to assess NF-κB activation by entolimod and TNF as described previously . To measIn vitro cytotoxicity assays were performed using primary mouse hepatocytes and the BNL and Hepa 1–6 tumor cell lines. Cells were seeded in 96-well plates (1x104/well) and treated the next day with entolimod (100 ng/ml) for 2 h. Then, the media was removed and the cells were treated (4 wells/treatment) for 24 h with the indicated doses of TNF diluted in medium containing D-GalN (2 mg/ml). Control cells (no TNF) were incubated in medium containing 2 mg/ml D-GalN. After 24 h incubation, the plates were gently washed with PBS to remove dead cells and debris. The remaining adherent cells were then stained with methylene blue and absorbance at 595 nm was measured using a plate reader . Percent cell survival was determined by comparing the mean absorbance value for treated wells to that for the untreated control wells .To assess the effect of entolimod on LPS and TNF toxicity, LPS (160 μg/200 μl per mouse) and TNF (2 μg/200 μl per mouse) in PBS were injected i.p. Entolimod (1 μg/100 μl per mouse) was injected s.c. 30 min before TNF or LPS. Blood was collected 5 h after LPS/TNF injection from the saphenous vein from live animals or from the heart from sacrificed mice to prepare serum for measurement of ALT concentrations. At 24 h after LPS/TNF injection, mice were euthanized, and livers and lungs were collected to assess caspase-3/7 activity and lipid peroxidation. Two independent experiments were performed with 3–5 mice per treatment group.In the septic shock model, TLR5-mediated protective activity was determined in mice treated with entolimod  1 h before LPS  or TNF  with D-GalN (16 mg/200 μl per mouse). To determine the time dependence of entolimod’s protective activity, C57BL/6 mice were injected s.c. with entolimod 0.5, 1, 6, 24, 48 and 72 h before, simultaneously (<1 min apart) or 0.5 h after injection of LPS/D-GalN (10 mice/group) or TNF/D-GalN (6–10 mice/group). Mouse survival was recorded 48 h after treatment with observation continuing for 2 weeks, at which point mice were sacrificed.Neutrophil depletion was accomplished by i.p. administration of 100 μg of α-Ly6G or an isotype-matched control antibody 24 h and 1 h before entolimod treatment followed by LPS/D-GalN or TNF/D-GalN injection (5 mice/group). To confirm the efficacy of neutrophil depletion, complete (CBC) and differential blood cell counts were measured in blood samples collected immediately prior to administration of entolimod using a Hemavet 950 Hematology System .Liver and lung samples were homogenized in lysis buffer . Caspase activity was measured by incubating homogenates  with a 50 μM solution of fluorogenic substrate acetyl-Asp(OMe)-Glu(OMe)-Val-Asp(OMe)-aminomethylcoumarin (Ac-DEVD-amc) . The data is expressed as the fold increase in fluorescence after 4 h incubation relative to fluorescence measured at the time of substrate addition .Lipid peroxidation levels were measured in homogenized liver and lung tissue samples by assessing thiobarbituric acid reactive substance (TBARS) levels normalized to total protein concentration using a TBARS Assay Kit according to the manufacturer's protocol .Alanine aminotransferase (ALT) concentrations in mouse blood serum were determined using a commercially available enzyme assay  according to the manufacturer’s protocol.TNF concentrations were determined in mouse blood serum samples from untreated control mice and in samples collected 3 and 5 h after treatment with entolimod alone  or 2 and 4 h after injection of LPS  with or without entolimod  1 h pretreatment (4 mice/group). TNF concentrations were determined using an ELISA kit  according to the manufacturer’s protocol.Lung tissue sections were prepared from NIH Swiss mice injected with TNF  with and without entolimod  30 min pretreatment and from control mice injected with PBS. Lung tissue was collected from 3 mice in each treatment group 24 h after drug administration and from untreated control mice. Sections were stained with hematoxylin-eosin (H&E) and evaluated for pathomorphological changes using a Zeiss Axio Imager A1 microscope equipped with an Axiocam MRc digital camera.Liver samples were collected from 3 untreated control mice, 3 mice treated for 7 h with entolimod alone (1 μg/mouse), and 4 mice in each group treated with TNF (1 μg/mouse)/D-GalN (16 mg/mouse) for 6 hours with or without entolimod (1 μg/mouse) 1 h pretreatment. Sterile Evans Blue (EB) solution in PBS  was injected into the tail vein 2 h before mouse sacrifice, which was done by cervical dislocation to prevent interference with vascular permeability as described in . The col5 cells/injection), Hepa 1–6 (5x105 cells/injection) and BNL (2x106 cells/injection) cells in 100 μl of PBS were injected into the flanks of BALB/c, C57BL/6 and SCID mice, respectively, to induce subcutaneous tumor growth. When tumors reached ~5 mm in diameter, mice were randomized into 4 groups and injected s.c. with entolimod  or PBS  followed by i.p. injection of TNF  or PBS  one hour later. In the BNL and Hepa 1–6 models, additional mice received TNF (0.5 μg/mouse)/D-GalN injection with or without entolimod  1 h pretreatment. Untreated mice and mice injected with D-GalN and PBS served as controls. Tumors were measured in two dimensions, length (L) and width (W), with a digital caliper every 2–4 days. Tumor volume (V) was calculated as: V = W2 x L/2.CT26 , total RNA was prepared from liver tissue samples of C57BL/6 and NIH Swiss mice 30 minutes after treatment with entolimod (5 μg/mouse), LPS (20 μg/mouse) or PBS (untreated control) and from untreated primary hepatocytes or primary hepatocytes treated with entolimod (100 ng/ml) for 30 min. The RNA samples were hybridized following manufacturer’s protocols to Illumina MGEW6 microarrays containing probes for 30,000 genes . The data was quantile normalized with background subtraction.Two-tailed paired and unpaired Student’s t-test and Log Rank criterion were used for data analysis in this study. The data were evaluated for normality showing that in all cases they fit the normal distribution allowing use of the parametric t-test for data analysis. Minimum sample sizes for all experiments were determined with the significance level alpha set at 0.05 and beta set at 0.20 to realize a study power of 80%.We and others have demonstrated the capacity of TLR5 agonists to protect tissues against a variety of stresses, including protection of the liver from FAS signaling-mediated hepatotoxicity, via activation of several major tissue protective signaling pathways in liver hepatocytes . The oveSince TNF is a key mediator of LPS toxicity , we testSince treatment with recombinant TNF has been found to induce pulmonary toxicity , we examTo determine entolimod’s capacity to reduce or eliminate hepatotoxicity under conditions of hepatocyte sensitization, we utilized a murine model of septic shock induced by either LPS or TNF combined with D-GalN. D-GalN is a hepatotoxic agent that inhibits RNA and protein synthesis exclusively in hepatocytes by reducing their content of adenine and uracil nucleotides and uridine triphosphate (UTP). Treatment with sub-toxic doses of D-GalN sensitizes hepatocytes to LPS and TNF toxicity , resultiResults obtained with TNF treatment in combination with D-GalN sensitization were similar to those for LPS/D-GalN treatment. Injection of recombinant TNF (1 μg/mouse) combined with D-GalN (16 mg/mouse) proved 100% lethal, with mice dying 12–24 h after TNF/D-GalN administration . In contThe acute organ failure and mortality caused by high levels of TNF are due to TNF’s induction of microvascular endothelial injury . To testSepsis and hemorrhagic shock result from accumulation of monocytes and activated neutrophils in various organs where they produce large amounts of cytotoxic cytokines , reactive oxygen species, and reactive nitrogen species which cause organ damage and, ultimately, death . The keyWe previously demonstrated that hepatocytes are the only liver-resident cells that respond directly to TLR5 stimulation with NF-κB activation while LPS activates NF-κB in liver stromal cells prior to engaging hepatocytes via a secondary response . To deteComparing treatment with entolimod and LPS, we previously showed that entolimod treatment resulted in stronger activation of the NF-κB, STAT3, Nrf2 and AP-1 signaling pathways in mouse livers 1h after injection . In addiin vitro for 30 min.In this study, we sought to identify the molecular mechanisms that contribute to entolimod’s protective activity against LPS and TNF toxicity by analyzing the gene expression changes induced in the mouse liver by entolimod treatment. Because hepatocytes are the first cells in the liver to respond to TLR5 agonist treatment (see above), we assume that most gene expression changes observed in the liver at early time points after entolimod treatment reflect transcriptional activity in hepatocytes. However, it is possible that some of the observed molecular response is associated with the influx and activation of immunocytes in the liver responding to secreted chemotactic factors such as CXCL1 which is highly expressed in entolimod-treated mice and acts as a neutrophil chemotactic factor . We alsoCXCL1 (KC) and CXCL2 and the interferon-inducible cytokines CXCL10 (IP10) and CXCL9  were upregulated by entolimod stronger than by LPS , IL-1α and IL-1β were more profoundly induced by LPS than entolimod  is a chemokine known to act as a powerful chemoattractant for neutrophils and hematopoietic stem cells and to be involved in multiple immune responses, wound healing and angiogenesis [GDF-15), a member of the transforming growth factor beta (TGF-β) superfamily with anti-inflammatory function, was also more strongly upregulated in livers of entolimod-treated mice than LPS-treated mice and was also upregulated in entolimod-treated hepatocytes. This cytokine attenuates TNF, IL-6 and IL-1β expression in serum and liver tissue and prevents LPS-induced liver injury [When hybridized with total RNA from liver samples of entolimod-treated C57BL/6 mice, 4,418 of the 30,000 genes included on the MGEW6 microarrays satisfied the established minimum expression level (>100); among these, 94 transcripts were induced at least two-fold compared to untreated mice in entolimod-treated mice and 157 in LPS-treated mice. Among 75 annotated genes upregulated at least 2-fold in entolimod-treated samples vs untreated controls, there were 40 genes upregulated by both entolimod and LPS and 35 upregulated uniquely by entolimod. Several of the annotated genes induced by both entolimod and LPS are related to the NF-κB, AP-1 and IFN signaling pathways, and while meeting the cut-off for induction by both treatments, showed significantly different levels of expression following entolimod versus LPS treatment. For example, the NF-кB-inducible cytokines n by LPS . On the ntolimod . All of atocytes . Among togenesis , 45. Gror injury .NFKBID, NFKBIZ and NFKBIA), pro-survival early stress response genes , anti-apoptotic genes , tissue regeneration-stimulating genes (SOCS3 and DUSP1) and anti-oxidant genes (RCAN1 and MT-ND2) found to be strongly induced by entolimod [There were also a number of NF-κB inhibitory genes , against TNF toxicity, we first tested the responsiveness of normal mouse hepatocytes and the BNL and Hepa 1–6 HCC tumor cell lines to entolimod tivation . In conttivation . The foltivation . Entolimtivation ; howevertivation . This dain vivo was found to successfully protect normal liver and lung tissues from TNF toxicity (see above), we investigated whether tumors growing in mice would be similarly protected. This was done by testing the antitumor effect of TNF administered alone or in combination with entolimod in mice bearing subcutaneous BNL, Hepa 1–6 or CT26 tumors. Mice were treated with TNF, entolimod or their combination when tumors reached ~5 mm in diameter (designated Study Day 0). Tumors were then measured by digital caliper every 2–4 days until euthanasia was required based on IACUC guidelines due to tumors reaching the maximum allowable size or developing necrotic lesions and bleeding. In BNL and Hepa 1–6 tumor-bearing mice, treatment with TNF (1 μg/mouse), entolimod (1 μg/mouse) or their combination had no observable effect on tumor growth in either HCC mouse model when compared to untreated control groups  Survival of BALB/c mice after injection of the indicated doses of LPS and D-GalN (16 mg/mouse). Mice were monitored for 2 weeks following treatment. All mortality occurred within 24 h after treatment (6 mice/group). (B) Survival (>48 h) of BALB/c mice after LPS (10 ng/mouse) and D-GalN (16 mg/mouse) treatment with a single dose of entolimod (1 μg/mouse) injected s.c. 30 min and 1 h before, simultaneously with (<1 min apart), or 1 h after LPS (5 mice/group). (C) Efficiency of neutrophil depletion in mice injected twice (24 h apart) with α-Ly6G antibody or an isotype-matched control rat IgG antibody. Neutrophil numbers were determined by complete and differential blood cell count (CBC) analysis of blood samples collected 1 h after the second antibody injection (3 mice/group).(TIF)Click here for additional data file.S2 FigMice were treated on day 0. Tumors were measured on the indicated days after treatment. Relative tumor volume on each day of measurement was calculated as a ratio to the tumor volume on the day of treatment (Day 0). Mean ±SEM is shown for the number of tumors per group indicated in parentheses (2 tumors per mouse). Control groups received entolimod alone or PBS (untreated).(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file. 4 Nov 2019PONE-D-19-26443Title - TLR5 agonist entolimod reduces the adverse toxicity of TNF while preserving its antitumor effectsPLOS ONEDear Dr. Burdelya,Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.We received positive feedback on your manuscript from both experts. 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Specifically, we ask that you state the product number and any lot numbers provided when the compound was purchased from Cleveland BioLabs.4.  Thank you for stating the following in the Competing Interests section:I have read the journal's policy and the authors of this manuscript have the following competing interests: Andrei Gudkov is a consultant and shareholder of Cleveland BioLabs, Inc., the biotech company that provided EntolimodTM for this work. This did not alter authors’ adherence to PLOS ONE policies. Other authors declare no competing interests.We note that you received funding from a commercial source: Cleveland BioLabs, Inc.relevant declarations relating to employment, consultancy, patents, products in development, marketed products, etc.Please provide an amended Competing Interests Statement that explicitly states this commercial funder, along with any other http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.Within this Competing Interests Statement, please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” . The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Significant work by Haderski et al suggesting the antitumor role of TNF. Below are the points which should be addressed before it's suitable for publication.1.It's been shown by several groups that LPS activates NRF2 antioxidant pathways. Authors should discuss their perspective on the above mentioned topic on basis of this current study.2. Authors must add a graphical abstract as a figure and discuss this to the text. It will help readers to get take-home message easily.3.Fig 1 ang Fig 2 resolution is very low. Every lebel is very hazy and hard to read. Authors should work on that.Reviewer #2: In the study, 'TLR5 agonist entolimid reduces the adverse toxicity of TNF while preserving its antitumor effects,' the authors have successfully demonstrated that combining entolimid with TNF treatment significantly reduces related toxicity while maintaining its efficacy as an anti-cancer agent. This study was performed rigorously, and bears merit. Some minor revisions have been recommended as follows:1) The authors use the term TNF, however, there are two members- TNF-alpha and TNF-beta. Please specify the correct member.2) Abstract: Please describe actual results. Mention what was increased and decreased, by what treatment, and by how many fold/was it significant?3) Introduction: Differentiate between a normal immune response triggered by bacteria which results in release of cytokines versus sepsis. Elaborate on 'cytokine storm'.4) Introduction: Give a bit more detail about the mechanism of action of TNF. How does TLR4 and NFKB fit in (provide more details)?5) Introduction: Page 5 Line 88: The authors say TLR5 has narrow tissue distribution. So, if TLR4 is more widespread, how then, does TLR5 neutralize the toxic effects of TLR4 effectively? Is the effect tissue specific and restricted, or is it systemic which would make more sense?6) Introduction: Page 5, Line 93: How does entolimid preferentially protect only normal tissues? What is the mechanism? Anything previously published?7) Introduction: Page 6, Line 110: Elaborate on how D-galactosamine administration sensitizes cells to TNF?8) Materials and methods: Mention how the gene expression profiling was done exactly here.9) Materials and methods: Please clarify how many mice were in each treatment group exactly?10) Statistical analysis: Student's t test was performed in some animal studies. If distribution was skewed, a non parametric test should be applied, not t test.11) Statistical analysis: Was power analysis performed to determine sample size?12) Figures: Images need to be of higher quality, as some of the labels are blurred.13) Figure 2F: There should be an Entolimid/TNF/D-GalN only control.14) Please separate the results section and figure legends sections completely.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  15 Dec 2019Editorial Comments:http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf1. When submitting your revision, we need you to address these additional requirements. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at We have checked the revised manuscript for full compliance with the style requirements of PLOS ONE.2. At this time, we request that you please report additional details in your Methods section regarding animal care, as per our editorial guidelines: (1) Please state the number of mice used in the study We have added information on the number of mice used for each experiment to the figure legends.(2) Please provide details of animal welfare Details regarding animal maintenance and welfare have been added to the Materials and Methods section. (3) Please describe any steps taken to minimize animal suffering and distress, such as by administering anesthesia, during intraperitoneal and subcutaneous injectionsSteps taken to minimize animal suffering and distress are included in the Ethics Statement . These included close monitoring of mice after treatment with LPS and TNF for signs of discomfort, pain and distress . Mice were euthanized as soon as signs of morbidity developed. In accordance with the IACUC-approved protocol, no anesthesia was used during intraperitoneal and subcutaneous injections of drugs or tumor cells.(4) Please include the method of euthanasia The method of euthanasia used in this study was CO2 asphyxiation followed by cervical dislocation, per IACUC guidelines. This information has been added to the revised manuscript in the Ethics Statement .(5) Please state specifically in your Methods section that no mice died before meeting the criteria for euthanasiaAs described in the Ethics Statement , we aimed to avoid treatment- or tumor-related pain or death as an endpoint by closely monitoring animals for signs of discomfort, pain and distress hourly for 8 hours after treatment, then twice a day for 2 days, then daily until end of experiments. This allowed us to euthanize animals, as required by IACUC guidelines, when indicators of severe morbidity such as weight loss, large or necrotized tumors, ruffled fur developed. 3. At this time, we ask that you please report some additional details regarding the Entolimod used in this study. Specifically, we ask that you state the product number and any lot numbers provided when the compound was purchased from Cleveland BioLabs.Requested details regarding the entolimod (CBLB502) lot used in the study have been added to the Methods section.4. Thank you for stating the following in the Competing Interests section:I have read the journal's policy and the authors of this manuscript have the following competing interests: Andrei Gudkov is a consultant and shareholder of Cleveland BioLabs, Inc., the biotech company that provided EntolimodTM for this work. This did not alter authors’ adherence to PLOS ONE policies. Other authors declare no competing interests.We note that you received funding from a commercial source: Cleveland BioLabs, Inc.Please provide an amended Competing Interests Statement that explicitly states this commercial funder, along with any other relevant declarations relating to employment, consultancy, patents, products in development, marketed products, etc.http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.Within this Competing Interests Statement, please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” , the company that developed and holds the rights to entolimod, was limited to receiving entolimod for this study. I, Lyudmila Burdelya, did not receive any monetary funding for this study from CBLI or any other commercial source, nor was I employed or paid by CBLI during the time period when the study was conducted. The fact that I am a co-inventor of entolimod as listed on several filed patent applications does not alter my adherence to PLOS ONE policies on sharing data and materials. Andrei Gudkov is also a co-inventor of entolimod and is a consultant and shareholder of CBLI; this does not alter the author’s adherence to PLOS ONE policies on sharing data and materials. Other authors declare no competing interests.”  Reviewer #1: Significant work by Haderski et al suggesting the antitumor role of TNF. Below are the points which should be addressed before it's suitable for publication.1. It's been shown by several groups that LPS activates NRF2 antioxidant pathways. Authors should discuss their perspective on the above-mentioned topic on basis of this current study.In the Introduction of the revised manuscript, we have added more information on LPS-induced inflammatory and pro-survival pathways, including the Nrf2 pathway (lines 100-102). However, because the goal of our study was to assess the ability of entolimod to mitigate tissue damaging effects of LPS and TNF, our work and the manuscript text is focused on the deleterious aspects of LPS responsible for excessive inflammation and septic shock syndrome. 2. Authors must add a graphical abstract as a figure and discuss this to the text. It will help readers to get take-home message easily.We appreciate this suggestion and have provided a schematic illustration of the mechanisms involved in entolimod-mediated protection of the liver from LPS and TNF toxicity as Figure 5. This figure is referred to in the Discussion section (lines 561-564).3. Fig. 1 ang Fig. 2 resolution is very low. Every label is very hazy and hard to read. Authors should work on that. The revised manuscript includes higher quality figures.Reviewer #2: In the study, 'TLR5 agonist entolimod reduces the adverse toxicity of TNF while preserving its antitumor effects,' the authors have successfully demonstrated that combining entolimod with TNF treatment significantly reduces related toxicity while maintaining its efficacy as an anti-cancer agent. This study was performed rigorously and bears merit. Some minor revisions have been recommended as follows:1) The authors use the term TNF, however, there are two members- TNF-alpha and TNF-beta. Please specify the correct member.https://en.wikipedia.org/wiki/Tumor_necrosis_factor_alpha). The fact that we used TNF-alpha abbreviated as TNF is described now in the Abstract, Introduction, and Materials and Methods sections of the revised manuscript . We used only TNF-alpha in this study, which is commonly abbreviated as TNF (2) Abstract: Please describe actual results. Mention what was increased and decreased, by what treatment, and by how many fold/was it significant?The abstract has been revised to more clearly describe specific results of the study in addition to the overall conclusions.3) Introduction: Differentiate between a normal immune response triggered by bacteria which results in release of cytokines versus sepsis. Elaborate on 'cytokine storm'.We have revised the Introduction section to more clearly describe and define the conditions of normal immune responses to bacteria, cytokine storm and septic shock (line 55).4) Introduction: Give a bit more detail about the mechanism of action of TNF. How does TLR4 and NFKB fit in (provide more details)?We have revised the Introduction section of the manuscript to include more detail regarding what is known about the mechanisms of action responsible for the toxicities of LPS and TNF.5) Introduction: Page 5 Line 88: The authors say TLR5 has narrow tissue distribution. So, if TLR4 is more widespread, how then, does TLR5 neutralize the toxic effects of TLR4 effectively? Is the effect tissue specific and restricted, or is it systemic which would make more sense?We have modified the text (line 96) to more clearly present our statement (different from TLR4 rather than narrow). We also explain that entolimod (i) has direct local protective effects in the liver due to TLR5-NF�B signaling in hepatocytes, and (ii) protects distant organs (including TLR5 non-expressing organs) through secretion of cytoprotective factors. 6) Introduction: Page 5, Line 93: How does entolimod preferentially protect only normal tissues? What is the mechanism? Anything previously published?Our previous studies have shown that entolimod does not protect tumors from various stress-induced therapies . Our current explanation is that the entolimod’s protective effects towards normal cells are mediated via NF-�B-mediated activation of pro-survival factors. Since tumors commonly have constitutively active NF-�B, they cannot benefit, in terms of survival under conditions of stress, from NF-�B-activating mechanisms such as TLR5 activation. This is discussed in the text of the manuscript  Introduction: Page 6, Line 110: Elaborate on how D-galactosamine administration sensitizes cells to TNF?We have added a description of (and references for) how D-galactosamine affects hepatocytes and sensitizes them to LPS- and TNF-induced toxicity in the Results section of the revised manuscript (lines 329-332).8) Materials and methods: Mention how the gene expression profiling was done exactly here.The methodological details of our gene expression profiling experiment are provided in the Results section of the manuscript (line 433 and below).9) Materials and methods: Please clarify how many mice were in each treatment group exactly?We have added sample size numbers for both in vivo and in vitro experiments .10) Statistical analysis: Student's t test was performed in some animal studies. If distribution was skewed, a non-parametric test should be applied, not t test.Data were evaluated using the multiple distribution tests available in GraphPad Prism software to determine whether the data followed the normal distribution. In each instance, the data were found to fit the normal distribution, thus allowing use of the parametric t-test for data analysis.11) Statistical analysis: Was power analysis performed to determine sample size?Minimum sample sizes for all experiments were determined using a significance level alpha (probability of a Type I error) value of 0.05 and a beta (probability of a Type II error) value of 0.20. The study power (probability of detecting a true positive) was then 80%. The calculations used are customary based on normal distributions. Ref: Rosner B. Fundamentals of Biostatistics. 8th ed. Cengage Learning, Inc. 2015. Animal protocols were reviewed by RPCCC’s biostatistician as part of IACUC protocol review and approval process.12) Figures: Images need to be of higher quality, as some of the labels are blurred.We have included higher quality figures in the revised manuscript.13) Figure 2F: There should be an Entolimod/TNF/D-GalN only control.The relevant controls without antibody treatment to deplete neutrophils are presented in Figures 2A  and 2D  of the revised manuscript.14) Please separate the results section and figure legends sections completely.The figure legends are inserted into the Results section and separated from the text according to PLOS One instructions.Additional changes:In Figure 3, panels B, C, D have been changed to bar graphs  since the data were obtained from individual treatment groups which are more accurately represented by independent bars than connected lines.AttachmentResponse to Reviewers.pdfSubmitted filename: Click here for additional data file. 6 Jan 2020TLR5 agonist entolimod reduces the adverse toxicity of TNF while preserving its antitumor effectsPONE-D-19-26443R1Dear Dr. Burdelya,We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.Within one week, you will receive an e-mail containing information on the amendments required prior to publication. 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Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact With kind regards,Partha Mukhopadhyay, Ph.D.Section EditorPLOS ONEAdditional Editor Comments :Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressed**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Significant work. All concerns have been addressed and modified the manuscript by incorporating the changes. Manuscript is ready for acceptance in plosone.**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article (If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.Reviewer #1: Yes: Suman Mukhopadhyay 22 Jan 2020PONE-D-19-26443R1 TLR5 agonist entolimod reduces the adverse toxicity of TNF while preserving its antitumor effects Dear Dr. Burdelya:I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. 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The prevalence of Type 2 diabetes mellitus (T2DM) is escalating globally. Patients suffer from multiple complications including the development of chronic wounds that can lead to amputation. These wounds are characterised by an inflammatory environment including elevated tumour necrosis factor alpha (TNF-α). Dermal fibroblasts (DF) are critical for effective wound healing, so we sought to establish whether there were any differences in DF cultured from T2DM donors or those without diabetes (ND-DF). ND- and T2DM-DF when cultured similarly in vitro secreted comparable concentrations of TNF-α. Functionally, pre-treatment with TNF-α reduced the proliferation of ND-DF and transiently altered ND-DF morphology; however, T2DM-DF were resistant to these TNF-α induced changes. In contrast, TNF-α inhibited ND- and T2DM-DF migration and matrix metalloprotease expression to the same degree, although T2DM-DF expressed significantly higher levels of tissue inhibitor of metalloproteases (TIMP)-2. Finally, TNF-α significantly increased the secretion of pro-inflammatory cytokines  in ND-DF, whilst this effect in T2DM-DF was blunted, presumably due to the tendency to higher baseline pro-inflammatory cytokine expression observed in this cell type. Collectively, these data demonstrate that T2DM-DF exhibit a selective loss of responsiveness to TNF-α, particularly regarding proliferative and secretory functions. This highlights important phenotypic changes in T2DM-DF that may explain the susceptibility to chronic wounds in these patients. Typically, cutaneous wound healing follows three sequential, overlapping phases; an inflammatory phase, a proliferative phase and a remodelling phase2. The inflammatory phase takes place early in the sequence, lasting only a few days, followed by progression to tissue regeneration and re-epithelialisation, granulation tissue formation, angiogenesis and tissue remodelling3.Patients with type 2 diabetes mellitus (T2DM) suffer from impaired wound healing with persistent inflammation, micro- and macro-circulatory dysfunction, hypoxia, and impaired neuropeptide signalling. This can result in a chronic, non-healing, diabetic foot ulcer, with significant risk of foot, or lower limb amputation4. During the inflammatory phase DF also secrete an array of cytokines, chemokines and growth factors that synchronise the migration of immune cells to the wound bed and control their retention and survival in damaged tissue6. Hence, DF have a potential role in regulating the switch from acute inflammatory responses to chronic persistent inflammation7.Dermal fibroblasts (DF) play a pivotal role during cutaneous wound healing; they proliferate and migrate into the wound bed to produce extracellular matrix (ECM) proteins that are essential for the generation of the granulation tissue and in providing a scaffold for the migration of inflammatory cells9. These wounds are characterised by a prolonged inflammatory phase, altered production of pro- and anti-inflammatory cytokines and impaired angiogenesis. DF exhibit diminished ECM synthesis and a decrease in their migratory and proliferative capacity. In addition, the migration and proliferation of keratinocytes is also decreased, which compromises the restoration of the epidermal barrier11.Chronic, non-healing wounds associated with diabetes exhibit an interruption in the normal healing process14. Therefore, the effects of TNF-α during the wound healing process are both time and concentration-dependent and TNF-α can initiate various effects on the DF. Lower concentrations of TNF-α promote remodelling/healing of injured tissue by stimulating inflammatory macrophages that secrete growth factors required to stimulate DF proliferation15. However, high concentrations of TNF-α for extended periods actually induce DF apoptosis with a deleterious effect on wound healing16. TNF-α inhibits their differentiation into myofibroblasts, which are important in the physical contraction of the wound17. High levels of TNF-α also inhibit synthesis of key ECM proteins such as fibronectin and type I collagen. Therefore, excessive and extensive exposure may contribute to chronic non-healing wounds prevalent in T2DM. Circulating plasma levels of TNF-α are typically around 10 pg/ml18 but in diabetic patients can be almost tenfold higher19 and circulating TNF-α concentrations positively correlate with diabetes duration20. In healthy skin tissue, concentrations of TNF-α are highly variable but typically in the order of 1.5 ng/ml21. However, TNF-α levels are three times higher in wound fluid from non-healing venous leg ulcers compared to healing ulcers22, and wounds of diabetic mice have higher levels of TNF-α compared to their normoglycaemic littermates23. Altogether, this implicates TNF-α in impaired wound healing in T2DM.The pro-inflammatory cytokine tumour necrosis factor alpha (TNF-α) plays a key role in controlling the inflammatory process during wound healing. However, continual, elevated levels of TNF-α can extend the inflammatory phase, which correlates with chronic, non-healing wounds, where there is no resolution of inflammation26. In normal human skin, MMP expression is low and is controlled by tissue inhibitors of MMPs (TIMPs). However, during wound repair MMP secretion is stimulated by pro-inflammatory cytokines, which also down-regulate TIMP synthesis28. MMP secretion is required for wound repair because they have a key role in the degradation and remodelling of the ECM, in addition to facilitating the migration of keratinocytes and fibroblasts. However, failure to control their expression due to persistent, chronic inflammation, can lead to disproportionate proteolytic activity and excessive ECM degradation, resulting in an impaired healing response28. DF within these wounds are unable to proliferate and/or migrate since their functional receptors that respond to cytokines and growth factors have been down-regulated29.TNF-α also stimulates the secretion of proteolytic enzymes such as matrix metalloproteases (MMPs), specifically MMP-1,-2,-3,-9 and -13; elevated levels of which have been associated with chronic wounds30. Since DF have a central role in regulating acute and chronic inflammation, fibrosis, and the resolution of inflammation, they may act as a gatekeeper of the inflammatory response in human skin during wound healing.While the role of DF in ECM assembly has long been recognised, additional roles during cutaneous wound healing are starting to emerge. Although inflammatory cells are the main source of TNF-α, it is also secreted by other by cells including DFIn this study we sought to clarify whether there were phenotypic differences in primary DF cultures from the skin of donors with T2DM (T2DM-DF) and no diagnosis of diabetes (ND-DF), which may impact on their responses in a wound healing environment. Furthermore, their responses to TNF-α, which is prevalent in chronic wounds, was also assessed. While the basal secretion of TNF-α levels by T2DM-DF and ND-DF was similar, we discovered that T2DM-DF were resistant to the anti-proliferative, pro-quiescent and pro-inflammatory effects of TNF-α. By contrast, the anti-migratory stimulus of TNF-α was retained. Understanding the disparity in the function of T2DM-DF may help to identify markers for new therapeutic targets to improve the treatment of chronic, non-healing wounds and diabetic foot ulcers.P = 0.8426, two-way ANOVA). As expected, in both populations there was significantly more TNF-α present in the conditioned medium (CM) following TNF-α treatment , but this increase was the same regardless of diabetes status . The higher concentration of 25 ng/ml TNF-α also significantly inhibited ND-DF proliferation but this was blunted and only significant at day 14 . TNF-α concentration had no impact on senescence in either ND-DF or T2DM-DF . At day 7, senescence scores for all DF were slightly elevated from day 3 levels but again there was no significant difference between ND-DF and T2DM-DF , and TNF-α had no impact under any conditions . Senescence-associated β-galacotosidase analysis at day 14 was not performed, as the cells had grown too confluent for individual cells to be visualised.We measured senescence-associated β-galacotosidase to investigate whether the reduced cell number in TNF-α-treated ND-DF primary cell cultures was due to induction of senescence. Three days after withdrawal of TNF-α, there was no significant difference between the senescence rates of ND-DF and T2DM-DF . However, there was no change in circularity suggesting that the cells were simply becoming smaller in size rather than more spindle shaped. In contrast, TNF-α had no impact on T2DM-DF morphology , however this was skewed by one T2DM-DF population with an exceptionally high expression level . TNF-α induced CCL2 expression in ND-DF by 32-fold over basal unstimulated levels  and was significantly induced by TNF-α in ND-DF only, by 27-fold , while TNF-α had no modulatory effect in either . Whilst TNF-α induced a significant 2.6-fold increase in SERPINE1 mRNA in ND-DF, there was no effect of TNF-α in T2DM-DF  to mimic this transiency. While TNF-α had no direct effect on cell number at day 3, prior exposure significantly inhibited ND-DF proliferation , DF also secrete pro-inflammatory cytokines, so we sought to identify differences between ND-DF and T2DM-DF in their secretion of other pro-inflammatory cytokines, and if these were modulated by TNF-α Fig. a-e. A nuF-α Fig. a concurs48. Likewise, CXCL1 promotes neutrophil infiltration. In the present study, expression of CCL2 and CXCL1 was highly variable in T2DM-DF with neither modulated by TNF-α, while in contrast TNF-α increased expression of both CCL2 and CXCL1 in ND-DF  containing penicillin/streptomycin (100U/ml/100 μg/ml) and amphotericin B (250 μl/ml), and digesting overnight at 4C in 0.1% dispase in PBS. The epidermis was removed and pieces of dermis washed in growth media (Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% foetal bovine serum (FBS) l-glutamine (10 mM) and penicillin, streptomycin and amphotericin B , before transferring to a T75 tissue culture flask containing fresh media and incubating at 37 °C in 5% CO2 to allow DF explant, which took 5–10 days. Once confluent cells were serially passaged at a ratio of 1:3. Patients without diabetes (ND) demographics were 100% female, age range 36–67 years. Patients with diabetes (T2DM) were 50% female, age range 52–66 years. All experiments were performed on cells at passage 3–6.DF were isolated from human skin provided by Ethical Tissue, University of Bradford. The use of human skin for this project was granted by the Yorkshire & the Humber—Leeds East Ethics Committee (reference numbers 17/YH/0086 and 07/H1306/98 + 5) and all donors gave informed consent. All methods were performed in accordance to the relevant guidelines and regulations. DF were isolated using an explant technique as previously describedDF were quiesced for 24 h and then treated with TNF-α (0–2.5 ng/ml) in DMEM + 10% FBS for 24 h. Conditioned medium was collected and the concentration of TNF-α quantified using a Human TNF-α Quantikine ELISA (R&D Systems) according to manufacturer’s instructions.Basal DF proliferation rates were assessed by cell counting. DF were plated in triplicate at a density of 20,000 cells per well in 24-well plates. Cells were quiesced in DMEM containing 0% serum (SF medium) for 24 h and then treated with DMEM + 10% FBS for up to 7 days. Viable and non-viable cells were counted using trypan blue and a haemocytometer, and media replenished, on days 0, 3, 5 and 7.To assess the impact of TNF-α on proliferation, DF were seeded in 96-well plates in quadruplicate at a density of 2,000 cells per well, quiesced in SF DMEM for 24 h and then treated with TNF-α (0–250 ng/ml) in DMEM + 10% FBS for 72 h. Medium was removed and replaced with DMEM + 10% FBS only for up to 14 days, and replenished every 3 days. DF proliferation was quantified using the CyQUANT fluorescence-based assay according to manufacturers’ instructions (Invitrogen). Fluorescence was measured at excitation 508 nm and emission 527 nm. Cell number was interpolated from a standard curve of 1–5000 cells at days 3, 7 and 14.60.DF were seeded in 6-well plates at a density of 7000 cells per well and treated as described for the proliferation assay. At days 3, 7 and 14, cells were fixed, and senescence approximated using the senescence-associated β-galactosidase kit  according to manufacturers’ instructions. After staining, 5 random fields of view (× 100 magnification) were captured from each treatment well for each patient, and a senescence score calculated from the ratio of positively stained senescent cells (blue) and the total number of cells present in the field as previously described58.Morphological characteristics of the cells were captured from the images generated from the senescence staining. Fifty random cells per patient per treatment were traced using Image J, and the spread cell area and circularity quantified61. DF were incubated in DMEM + 10% FBS with 0–25 ng/ml TNF-α for 24 h. Images were captured at × 40 magnification at 0 and 24 h. The migration distance between the wound edges was measured at 6 identical points in triplicate wells and the average taken. For TNF-α experiments, data is expressed as the percentage inhibition of migration compared to control (0 ng/ml) wells.Confluent DF were quiesced in SF medium for 24 h. A 0.8 mm wide linear scratch was made in triplicate monolayers and dislodged cells removed by washing in PBSCCL2, CXCL1, GAPDH, MIF, MMP2, MMP9, TIMP1, TIMP2, and SERPINE1 was measured in triplicate using specific TaqMan assays and expressed as a proportion of GAPDH using the formula 2−ΔCt.Following 24 h imaging of the migration assays, total RNA was extracted from DF using RNeasy mini kit (Qiagen) and reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems) according to manufacturers’ instructions. Gene expression of 2, 0.05% Brij, pH7.4) for 18 h (MMP-2 activity) or 24 h (MMP-9). Gels were stained with 0.1% Coomassie blue for 20 min and gelatinase activity visualised as clear bands of lysis on a dark background. MMP-2 and MMP-9 were measured using densitometry (Image J) and normalised to control (0 ng/ml) values62. Conditioned media from ND-DF treated with 100 nM phorbol 12-myristate 13-acetate (PMA) for 24 h was used as a marker for MMP-2 and MMP-9.Confluent DF were quiesced in SF medium for 24 h and treated with 2.5–25 ng/ml TNF-α for 48 h. Conditioned medium was collected, centrifuged at 600 g for 6 min to remove cell debris and snap frozen until needed for zymographical analysis. Conditioned medium was diluted (1:40) with non-reducing sample buffer and electrophoresed in an 10% SDS-gel containing 1.5 mg/ml gelatin for 110 min at 120 V. SDS was removed by washing in 2.5% Triton X-100 solution for 1 h and the gels placed in incubation buffer . Following completion, integrated density of the dots was calculated. Briefly, the mean densitometry of duplicate dots was measured using Image J. The reciprocal was calculated which was then corrected for the value of the background densitometry. Then, the integrated density of each pair of cytokines was expressed as a proportion of the integrated density of the reference spots that were included on all membranes. Expression was stratified into low (< 0.1 A.U.), medium (0.1–2 A.U.) or high (> 2 A.U.).Conditioned medium collected from the migration assays was used to evaluate a number of inflammatory cytokines using the Human Cytokine Array Panel A (R&D Biosystems) as per manufacturers’ instructions. The conditioned medium was centrifuged to remove any cellular debris and 1 ml was diluted with 0.5 ml of assay buffer (see n refers to the number of patient donors used in each experiment. All data was analysed using two-way ANOVA with Sidak post-hoc test. Alpha = 0.05 and P < 0.05 was considered statistically significant.Data are presented as mean ± standard error. Normalised data was transformed using the formula Y = log[Y]. Supplementary Information.


Nowadays, bioprinting is rapidly evolving and hydrogels are a key component for its success. In this sense, synthesis of hydrogels, as well as bioprinting process, and cross-linking of bioinks represent different challenges for the scientific community. A set of unified criteria and a common framework are missing, so multidisciplinary research teams might not efficiently share the advances and limitations of bioprinting. Although multiple combinations of materials and proportions have been used for several applications, it is still unclear the relationship between good printability of hydrogels and better medical/clinical behavior of bioprinted structures. For this reason, a PRISMA methodology was conducted in this review. Thus, 1,774 papers were retrieved from PUBMED, WOS, and SCOPUS databases. After selection, 118 papers were analyzed to extract information about materials, hydrogel synthesis, bioprinting process, and tests performed on bioprinted structures. The aim of this systematic review is to analyze materials used and their influence on the bioprinting parameters that ultimately generate tridimensional structures. Furthermore, a comparison of mechanical and cellular behavior of those bioprinted structures is presented. Finally, some conclusions and recommendations are exposed to improve reproducibility and facilitate a fair comparison of results. Biofabrication can be defined as a multidisciplinary research field with a combination of principles, protocols, and fabrication techniques from engineering, electronics, material science, cell biology, and biomedicine Silva, . BioprinSynthesis, bioprinting, and cross-linking of bioinks have a great impact on the generation of biological structures and especially on its mechanical and cellular behavior. Therefore, bioink is one of the most critical components of 3D bioprinting and it is intimately related to the bioprinting technique and the selected cells  process must control surface tension and viscosity of bioinks to get a proper droplet ejection  and extrusion-based bioprinting process (both bioprinting parameters and cross-linking methods) on post-printing results of the bioprinted structures  .A systematic review was conducted in accordance with PRISMA (P) guidelines. This review included original peer-reviewed studies based on the following criteria: (1) publication in an English-language journal; (2) papers related to extrusion-based bioprinting; (3) only original peer-reviewed papers were included, so editorials, proceedings, communications, letters, and reviews were excluded; (4) all papers based on complex tissue generation, organ generation or drug testing were excluded.The search engines used to identify studies were PUBMED, WOS, and SCOPUS. The following search items were used for the literature search: (Bioprinting AND Hydrogel). Search was performed on April 15th, 2019. No restriction was set on publication date. No meta-analyses were performed due to the heterogeneity of studies.general datacompiles authors, title, publication year, and journal; (2) materialcategorizes different materials by their importance and/or functionalities, including concentration and viscosity; (3) printing settingsgathers cartridge temperature, bed temperature, printing pressure, and printing speed; (4) cross-linking methodssummarizes cross-linking process depending on its type and characteristics, and finally (5) validation testsregisters types of cellular viability and mechanical tests. Specifically, main materials were classified as synthetic or natural, material name, cell-laden or post-printing cell addition, and according to its type of cross-linking . Furthermore, structural material was subdivided on material name and cross-linking type. Finally, sacrificial material was defined by material name, cross-linking type, and removal process. Papers were individually assigned to eight independent reviewers to be read in detail to extract available data.Before reviewing papers, several categories for data extraction were defined. A form was created and divided into different categories: (1) In all, 1,774 abstracts were found using the search string (Bioprinting AND Hydrogel) in three databases . Nine hundred and eleven papers were screened after removing duplicated, 783 of them excluded according to selection criteria, and 128 revised in full text. From those, 118 were finally considered for the review analysis .Additionally, material, journals of chemical/material-centered issues; (2) cellular, journals focused on the cellular/histological/biochemical topic; (3) engineering, journals focused on the technical and/or mechanical issues, and (4) multidisciplinary, journals that allow multiple topics. Additionally, the four combined subcategories are: (1) engineering/material, (2) cellular/material, (3) engineering/cellular, and (4) engineering/material/cellular.In this section, a classification of journals has been made to analyze what type of publications deal with our topics. Four main categories and other four subcategories from JCR or SJR were used to group journals. The main categories are: (1) Material contains the highest number of journals with 17 (29 papers). “Applied Materials & Interfaces” and “Biomaterials Science & Engineering” are the two most common journals in this category with 6 and 4 papers, respectively. All combinations of the material category reach 33 journals (86 papers). The remaining categories contain fewer journals. Cellular and engineering categories includ only four and seven journals (5 and 8 papers), respectively. “Scientific Reports” and “Plos One” are two journals associated to multidisciplinary category with 8 and 3 papers, respectively. “Journal of nanotechnology in Engineering and Medicine” is the only journal associated to the engineering/material/cellular category with one paper. Finally, the material/engineering subcategory is by far the most common with 12 journals (50 papers). In this subcategory, most papers are published by “Biofabrication” (23 papers) and “Acta Biomateralia” (8 papers).Natural and synthetic polymers can be considered as a broad cataloging of materials to synthesize hydrogels. In this sense, natural polymers are defined as bio-derived materials present in nature that can be extracted using physical or chemical methods . On the other hand, those human-made polymers are named synthetic and are usually classified into plastics, elastomers, and synthetic fibers  that are not considered as different material in this review. Specifically, the most common materials was alginate appearing in 58 papers followed by gelatin (26), GelMA (25), hyaluronic acid (16), and polyethylene glycol (PEG) with its chemical modifications (16).Although complex tissues and organs generation are out of the scope of this review, we consider interesting to include some information about those papers that define its biological purpose (61 out of 118). Most of them have a low frequency or a generic soft tissue use, but cartilage (22 papers) and vascular (9) usually use alginate (12 and 6 papers) and GelMA (9 and 2 papers), respectively.In this review, the 10 most used materials were selected for a detailed analysis. Alginate is the most used material in bioprinting appearing in a total of 58 papers. It is used with the other selected materials in pairs in 28 papers, with more than two selected materials in 10 papers, alone in 10 papers and with other chemical modifications in other 10 papers. Some of these interesting chemical modifications that improve its characteristics are: oxidized alginate   and with other combinations (7) mainly due to its poor rheological properties. Maybe for this reason, it is used alone in just two papers  and its derived materials are quite used being the fourth material in the list with 16 papers. It is an anionic, non-sulfated glycosaminoglycan that is present in connective and neural tissues as well as it is one of the major components of the skin. For this reason, HA is mostly used in skin tissue engineering. It appears alone in five papers  to solubility properties (short chains). It is usually modified replacing some hydroxyl groups with methoxy groups forming methylcellulose. Specifically, cellulose is used alone in three papers  and its derivatives PEG diacrylated (PEGDA) and PEG methacrylated (PEGMA) are used in the included studies in 6, 8, and 2 papers, respectively. PEG is a synthetic material formed by polymerization of ethylene oxide, highly valuable for its hydrophilicity that facilitates exchange of cell's nutrients and waste. Despite the fact that PEG is used alone in one paper with norbornene groups   and 10% w/v (4 papers), or 15% w/v (2 papers) other common values. It is noted that gelatin provides good thermoresponsive properties to hydrogel, but its concentration is highly dependent on the bioink application.Finally, there are a total of 43 concentrations of GelMA in 21 papers distributed from 1% up to 20% w/v, being the most usual 10% w/v (12 papers). This concentration is followed by 5% w/v (5 papers) and 1, 6, and 20% w/v (3 papers each). Overal, the most used concentrations are 2–4, 5, and 10% w/v for alginate, gelatin, and GelMA, respectively.This parameter can be considered an important factor for hydrogel printability. As it is known, viscosity indicates fluidity and for this reason it is very important for hydrogel extrusion. So, the more the viscous, the more the inner pressure of hydrogel during the extrusion process and increased cell damage. Pepelanova et al.  proposesHe et al.  performsPr  needed to properly produce bioprinted structures. In this sense, only a specific range of values are adequate for bioprinting and its selection is a key factor to obtain viable bioprinted structures. However, these values are highly dependent on the hydrogel composition, so they should be carefully selected in each case. An important feature of hydrogel is printability that was no analyzed in this review because it is rarely used  together with those materials that can be used with this temperature, such as alginate, gelatin, agarose, or GelMA (13 papers) . In this review, there are 6 papers that use room temperature for their cartridge temperature  do not inform about printing pressure used during their experiments or use the indistinct term −4 and 4.7·105 kPa, but the most used range is from 5·10−4 to 400 kPa (103 entries).Some authors use several pressures in their studies, so 127 different printing pressures were obtained. Almost all pressures in the range of 400–1,000 kPa are used with alginate . However, printing pressure is no longer a critical parameter of bioprinting using post-printing cell addition. In cell laden bioprinting the pressure ranges are in accordance to cellular viability, where the data obtained corroborate this affirmation. In all papers in which there are values of printing pressure and viability, 75.3% of pressure values have a viability over 80%.Finally, Aljohani et al.  use 0.5 Printing speed (X-Y movement) is important because it is directly related with the total bioprinting time. Aditionally, extrusion-based controls the hydrogel flow (filament width) using mainly printing speed and printing pressure. So, printing speed appears in 65 papers with 87 different velocities that vary from 0.2 to 150 mm/s. By taking a closer look, 91% of values are in the range of 1–30 mm/s where 57% of speeds are below 10 mm/s. In fact, the most used speed is 10 mm/s (13 entries) , chemical (controlled by the addition of reacting agents), or physical . In this sense, hydrogel composition determines the cross-linking type to use. It is a critical part in bioprinting process and surprisingly almost all authors define perfectly the materials and their protocols. Only Duarte Campos et al. ; Ahn et Thermal cross-linking is commonly used in gelatin or agarose hydrogels (16 papers). From those 16 papers, six of them perform cross-linking at 37°C  with CaCl2 solution (46 papers), and detailed concentrations can be seen in 2+) solutions are used in two papers . In general, solution with Cao et al.  uses CaSi et al. , and Kuni et al.  use NaClnd Kelly  uses CaCd et al.  uses 10 d et al.  uses a 3d et al.  performsFinally, physical cross-linking is usually performed with the exposure of the bioprinted structures to UV light. In this sense, GelMA is the most used material with this kind of cross-linking, but all materials modified with methacrylated groups can be photo-crosslinked, such as HAMA, AlgMA or PEGMA. Among all papers (41) with this kind of cross-linking, only two of them do not use UV: AnilKumar et al.  that useCurrently, cellular viability is one of the most common features to assess bioprinted structures that must be used on patients or drug testing. Here, post-printing analysis are focused on cellular and mechanical tests, but several biological measures appear during this review: gene expression (25 papers) that is usually related to cellular differentiation, and cell morphology (51 papers) that controls qualitatively cell shape or clustering. On the one hand, the most of gene expression studies used osteogenic- and chondrogenic-related markers such as cartilage formation genes (12 papers): ACAN (aggrecan), COL1, COL2, COL10 , or SOX-9. On the other hand, 37 papers conclude that there no morphological differences after bioprinting in comparison to a 2D culture and 19 papers clarify that the increasing of the stiffness, due to the increasing of the viscosity and concentration of the material or modifications of crosslinking parameters, tend cells to adopt a round shape losing its functionality  or propidium iodide (23 papers) as an orange-red and red stain for dead cells, respectively see . Additio18F-2-Fluor-2-deoxy-D-glucose ([18F]-FDG) tracer to check cell activity in volumetric geometries.According to metabolic tests, authors measure the metabolic activity with CCK-8 (Cell Counting Kit-8) in 3 papers and MTT -2,5-diphenyltetrazolium bromide) in other 3 papers. CCK-8 is a colorimetric assay where intracellular dehydrogenase activity produces the soluble substrate orange formazan, while MTT is transformed in a purple insoluble salt by living cells. Also, PET (Positron Emission Tomography) measurement was made by Polley et al.  with the0-day, 37 papers for 1-day, 25 papers for 3-days, 35 papers for 7-days, and 24 papers for 21-days. However, some papers' time points did not fit in our five groups, and they have been grouped in the closet category as follows: 0-day and 1-day groups fit perfectly but in 3-, 7-, and 21-day are counted from 2 to 4, 5 to 11 and 12 to 28 days, respectively. In this sense, 0-, 1-, and 7-days groups are the most used by authors, although only few of them use all groups in their studies , 1-, 3-, 7-, and 21-days. However, data heterogeneity does not allow a statistical inference. It is important to note that comparison among studies could be relatively unfair due to many different conditions, such as: variations in bioprinted structures , different cell lines survival characteristics (fibroblast vs. HUVECs), different measure periods , or different assay kits. 0-day. Maybe, a detailed analysis of viability by materials or cell lines could be significant, reducing the variability. For this reason, the three most used materials  and two of their combinations  have been selected in 0-day mean viability over 83%. This could indicate that cellular viability just after printing, has been partly sorted out. After that, 1-day viability decreases in most cases, being more accused in the alginate-GelMA combination (58.50% from 83.05%) with the most important exception of gelatin that increases (94.90% from 74.60%). Maybe, this decreasing trend could be due to nutritional or environmental conditions of cells during this first stage. In this sense, during these first hours after the bioprinting process, cells must adapt to a new environment which in some cases, stops their growth while other provoke their death. After this stressing period, 3-days group usually increases its cell viability, showing an adaptation to the new material in which they are embedded. Moreover, similar trend is found in 7-days group. Finally, after 21-days every material behaves in its own way, in GelMA and alginate/gelatin cellular viability continue its increase, while in alginate, gelatin and alginate/GelMA decrease. On the contrary, gelatin startes with a very high viability at 0- and 1-day, but after 3-days decreases, reaching its minimal 21-days later. It is noticeable that GelMA shows the best cellular viability, despite the fact that it is supposed to have the worst one even though it is synthetic  diminishes importance of mean viability (82.70%) obtained at Cell line depends mostly on the kind of tissue that wants to be replicated, but previous experience of authors can be a decisive too. In general, multipotent cells  are selected due to their differentiation potential. A total of 46 different cell lines are used in these papers. It is important to note that many papers are only qualifying cell viability using a fuzzy scale, such as good, regular or bad survival and other measures not related to viability, such as cell distribution.Additionally, NIH3T3 is used in 15 papers where some analyze percentage of cell viability (7)  use L929, a mouse fibroblast cell line: quantitative analysis (7)  , ADMSCs (86.07 ± 11.6%), and BMSCs (85.08 ± 4.95%) obtain similar viabilities. On the other hand, L-929 cells demonstrate a viability of 89.26 ± 7.42%, revealing to be the most resistant cells, in terms of viability, in all the included studies. This result is predictable, taking into consideration that L-929 cells derive from an immortalized cell line  compressive stress, (2) Young or elastic modulus, (3) compression modulus, (4) yield stress, and (5) ultimate tensile strength (UTS). To obtain these mechanical properties, tests are done to multiple different materials, where alginate (51% of papers), GelMA (27%), and gelatin (15%) are the most common.Compressive stress is defined as the stress on materials that leads to a smaller volume (14 papers). Kim et al.  is the oThree authors study compressive stress of different materials. On the one hand, Daly et al.  obtain 45 kPa, most of the values are in the range 0–100 kPa with 23 papers, followed by 100–400 kPa (10 papers), and above 400 kPa (3 papers). Alginate is the most studied material (16 papers). Several kinds of are present: Wei et al.  and strain  in a material in the linear elasticity regime of a uniaxial deformation. Approximately half of papers (35) study this property and some of them comment the expected result for a specific tissue, e.g., 4 MPa for cartilage tissue  is the maximum stress that a material can withstand while being stretched or pulled before breaking. This property appears in 12 papers and nine of them use alginate in their hydrogel. In this case, when alginate is used (mixed or not with another component) UTS values are within 40–500 kPa range with concentrations of 2–5%w/v.Finally, yield stress is little studied (3 papers) and most of them provide graphical results. Bandyopadhyay et al.  obtain a2+ for alginate/gelatin blend after measuring different time point and analyze it compressive modulus, noting that with higher time of exposition modulus increases. Also, Kang et al.  and the printing pressure at 100–200 kPa (reducing cell stress). Obviously, the addition of cells after hydrogel bioprinting minimize the importance of these parameters.Finally, MSCs are the cell line most used in combination with hydrogels. In general, good viability results are obtained with all cell lines. Regarding mechanical tests, the Young modulus is widely used in bioprinting, although there is no consensus on the most important mechanical property of each bioprinted structure.In our opinion, those missed bioprinting parameters are usually related to a poor reproducibility. Moreover, inappropriate evaluation tests may cause an unfair comparison of results. For this reason, some guidelines and recommendations are detailed below. Additionally, in order to facilitate reading and understanding for future papers, the International Systems of Units (SI) must be used.Concentration of materials and protocols to prepare hydrogels should be fully detailed and could be complemented with its viscosity. Although cartridge temperature and printing pressure are two essential parameters needed to set the bioprinter, bed temperature and printing speed will increase the reproducibility of the study. A quantitative measure of printability or the hydrogel printability window will facilitate its practical use. Additionally, in the cross-linking step, concentration for chemical-based cross-linking, temperature for thermal-based cross-linking, light wavelength/power for physical-based cross-linking must be defined. Furthermore, the exposition time must be defined for all three cross-linking types. On the other hand, cellular tests must include the identification of cell line and assay-kit information with quantifications at different time points . And finally, those studies whose bioprinted structures have a specific clinical application must perform mechanical tests to mimic the tissue/organ properties .Hence, we strongly recommend defining the following parameters in all studies. In summary, due to time and space restrictions, this review could not analyze all the information available in the selected papers. Thus, future works could focus on comparing results of commercial vs. homemade bioprinters , analyzing other rheological properties , printability vs. precision, or degradation speed for different hydrogels.EM performed literature search, screening, data extraction, preparation of graphics, tables, and manuscript. JG-B contributed to screening, data extraction, preparation of graphics, tables, and manuscript. JP contributed to screening, data extraction, and preparation of manuscript. EL, JC, AM-G, MD, JC-A, and DT contributed to screening, data extraction, and revision work to the manuscript. FS-M performed revision work to the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.