Cancer is one of the major healthcare challenges across the globe. Several anticancer drugs are available on the market but they either lack specificity or have poor safety, severe side effects, and suffer from resistance. So, there is a dire need to develop safer and target-specific anticancer drugs. More than 85% of all physiologically active pharmaceuticals are heterocycles or contain at least one heteroatom. Nitrogen heterocycles constituting the most common heterocyclic framework. In this study, we have compiled the FDA approved heterocyclic drugs with nitrogen atoms and their pharmacological properties. Moreover, we have reported nitrogen containing heterocycles, including pyrimidine, quinolone, carbazole, pyridine, imidazole, benzimidazole, triazole, β-lactam, indole, pyrazole, quinazoline, quinoxaline, isatin, pyrrolo-benzodiazepines, and pyridopyrimidines, which are used in the treatment of different types of cancer, concurrently covering the biochemical mechanisms of action and cellular targets. Carcinoma is the abnormal growth of normal cells that typically grow beyond their original boundaries, invade surrounding areas, spread to other organs, and result in metastasis, which is one of the main causes of cancer-related death, the second most common cause of deaths across the globe . Around In wealthy nations, cancer has become one of the leading causes of mortality. A DNA mutation can cause cancer to develop. The etiology of the gene can be either adopted or hereditary. Both genetic and epigenetic variables are involved. The co-carcinogenic responses, hormonal impacts, and many other epigenetic variables are tumor promoters. Conversion of protooncogene to oncogene and the inactivation of tumor-suppressing genes are the two genetic factors responsible for cancer. Cancer cells can divide quickly or slowly, as in the cases of plasma tumor cells and Burkitt’s lymphoma, respectively. In the cancer cell growth, proliferation is the crucial element, which is very quick compared to the regular cells. When cancerous cells proliferate out of control, alterations occur in the proteins and growth factors, telomerase expression, tumor-associated angiogenesis, and intracellular signaling pathways that regulate apoptosis and cell cycles . Sulfur Heterocyclic are substances where the ring carbon atom has been replaced by one of the other three elements, oxygen, nitrogen, or sulphur, in the parent scaffold. The existence of the modified atoms as well as the size of the scaffold in the compound affects its physical and chemical properties. Modifications to a molecule’s heterocyclic ring structure can alter its anti-inflammatory, antibacterial, anti-tumor, antiviral, and antifungal properties. In nature, nitrogen-containing heterocyclic compounds are widely distributed and serve as the basis for many different substances, including alkaloids, vitamins, hormones, dyes, antibiotics, herbicides, and pharmaceuticals ,10,11. TFor many years, nitrogen-containing heterocycles have attracted attention of scientists due to their structural variety and biological importance. The present study covers the most recent developments in nitrogen-containing heterocyclic compounds as potential cancer chemotherapeutics. With approximately 60% of unique small-molecules containing a nitrogen heterocyclic, a quick glance through FDA archives demonstrates the structural significance of nitrogen-based heterocycles in drug design. Due to the formation of hydrogen bonds between these heteroatoms and DNA, complexes containing heteroatoms are more stable. In reality, the strength of the binding between DNA and heterocyclic compounds corresponds with the anti-cancer impact ,14,15. Nhttps://www.ebi.ac.uk/chembl/, accessed on 22 November 2022), an open access biological database, and found 2,331,700 compounds on 467 targets. With the help of ChEMBL, we plotted a graph between the molecular weight of nitrogen containing heterocyclic compounds with log P values and color, which indicated the violation of rule of 5 (RO5). LogP values of the reported molecules were directly correlated with their molecular weight  respectively ,quinolones derivatives. One pot multicomponent condensation was carried out between malononitrile, 2,4-dihydroxy-1-methylquinoline, and substituted aromatic aldehydes to create a number of pyranoquinoline based structural analogues. The compounds were accessed for their cytotoxic and anti-inflammatory activity. Out of these, compound standard .19 have the IC50 values of 1.89, 1.43, and 4.21 µM against the cell lines HePG2, HCT-116, and MCF-7 respectively. The control drug colchicine with IC50 values of 7.4, 9.3, and 10.4 µM, respectively, and its effect on cell cycle distribution were evaluated. The outcomes showed that compound 19 had the ability to stop the cell cycle at the G2/M phase. A double-staining test with annexin V and PI was performed to investigate the apoptotic effect of the synthesized compounds. Compound 19 caused HepG-2 cells to apoptosis thirteen times more frequently than control cells carbazole derivative was significant against cancer cell lines. The most potent compound in this study was found to be compound 24 with the IC50 values 17 and 17 µM against the cancer cell lines HL60 N and HL60 MX2, respectively. Etoposide is used as a reference with IC50 values of 1.3 µM and 11.9 µM  pyrimidin-4(1H)-one and 2-cyano-N-(1-(pyridin-4-yl)ethylidene)-acetohydrazide with hydrazonoyl halides, 5-amino-N-(1-(pyridin-4-yl)ethylidene)-1H-pyrazole-4-carbohydrazides and 8-(pyridine-4-yl)pyridotriazolopyrimidin-5(1H)-ones were synthesized. The anti-cancer activity of the synthesized compounds was tested against the HEPG2 cell line. The most potent compound reported in this study was compound  0.74 µM . Fayed epoptosis . Nagendef 1.7 µM .35a with IC50 values of 0.22 µM (48 h) and 1.88 µM (72 h) and 35b with IC50 values of 0.11 µM (48 h) and 0.80 µM (72 h), were reported to present potent anti-cancer activity against the MCF-7 cell line. The most potent compound was compound 35b with the lowest IC50 value, while compared to the reference drugs, doxorubicin presented IC50 values of 1.93 µM (48 h) and 1.07 µM (72 h) and sorafenib with IC50 values of 4.50 µM (48 h) and 1.71 µM (72 h) respectively pyridin-4-ylium chloride. The synthesized complexes were tested for their cytotoxicity against HepG2 (human hepatocellular carcinoma), A549 (human lung adenocarcinoma), HCT 116 , and MCF-7 (human breast adenocarcinoma) cells. Compound ectively . El-Gohaorubicin .38, compared to reference drug Erlotinib with IC50 values of 0.13, 0.12, and 0.032 µM, against the cell lines A549, HepG2, and E.G.F.R. respectively. Compound 38 showed three hydrogen bonds and one -π cation interaction with a minimum binding energy of −54.6913 kcal/mol in the molecular docking studies with the catalytic pocket of protein imidazoquinoxaline derivatives and performed their anticancer evaluation. Compound 45 showed excellent anticancer activity at IC50 values of 14.62, 4.78, 1.55, and 1.04 μM against MDA-MB-231, MDA-MB-486, MCF-7, and MCF12A cell lines, respectively, whereas control cisplatin had IC50 values 3.26, 1.43, and 4.23 μM against MDA-MB-231, MDA-MB-486, and MCF-7 cell lines, respectively pyrimidines have been studied extensively as quinazoline analogs  Pyrido2. Kumar eectively .156 showed good activity with IC50 values of 1.63, 17.17, 29.73, 13.47, and 7.11 µM against MCF-7, SK-BR-3, A549, BT-474, and MDA-MB-231 cell lines which were comparable to standard gefitinib with IC50 values of 25.37, 4.92, 24.25, 0.53, and 37.82 µM, respectively  pyrimidine derivatives and tested their cytotoxic activity on five human cancer cell lines: BT-474, SK-BR-3, A549, MCF-7, and MDA-MB-231. Most of the prepared compounds showed potent anticancer activity. Compound ectively .157 was found to be the most effective of these derivatives since it had an IC50 value of 19 µg/mL against B16F10 cell line. Further, 5-Fluorouracil was used as a reference drug which showed IC50 value of 4.03, 9.82, 0.87 and 0.54 µg/mL against Colo205, B16F10, U937 and THP-1 cell lines respectively  pyrimidines and evaluated their cytotoxic activity against three human cancer cell lines HepG2, MCF-7, and HT29. Most of the synthesized derivatives showed potent anticancer activity. Many of the compounds showed good anticancer activity. Compounds 161 , 162 , and 163  presented comparable anticancer activity to that of doxorubicin with the LD50 value of 3, 4, and 40 µM  pyrimidine derivatives and tested their antiproliferative activity against MDA-MB-436 and T-47D cell lines. Many of the synthesized compounds showed potent anticancer activity. Among synthesized compounds, 165 displayed maximum anticancer activity towards MDA-MB-436 and T-47D with IC50 values of 10.52 and 3.02 µM. Ribociclib was used as positive control with IC50 values 24.35 and 4.81 µM, respectively pyrimidine based heterocyclic derivatives  are important and versatile molecules against the different forms of cancer. The spectrum of nitrogen-based molecules used in medicine is expanding every day and their numerous analogues offer a promising and significant route for the discovery of medications with a variety of biological applications.In vitro studies compiled herewith revealed that imidazole, pyridine, quinoxaline, β-lactam, quinazoline, and isatin majorly act against breast cancer (MCF-7), pyrimidine and pyrazole derivatives against liver cancer (HepG2), quinoline and triazole derivatives against cervical cancer (HeLa), carbazole, indole, and pyrrolo-benzodiazepines derivatives against lung cancer (A549), and bezimidazole and pyridopyrimidine against colorectal cancer (HCT-116).39a showed excellent anticancer activity on all tested cell lines, including MDA-MB-23, A549, and HeLa cell lines at IC50 values of 0.0031, 0.089, and 0.0038 µM, respectively. Further, Compounds 10, 13, 25a, 49, 59, 68, 86, 88, 104, 111, 122, 145, 151, and 164 also showed potent anticancer activity on MCF-7, HeLa, HepG2, EGFR, VEGFR-2, MCF-7, MCF-7 Colo-205, HepG2, MCF-7, MCF-7 BxPc3, THP-1, and PANC-1 at concentration of 0.23, 0.8, 0.012, 0.47, 0.02, 0.38, 0.017, 0.018, 0.028, 0.06, 0.01, 0.1, 0.49, and 0.02 µM to nM range respectively. Among these potent compounds, compounds 10, 68, 86, 111, and 122 showed excellent activity against the breast cancer (MCF-7 cell line).Particularly, pyridine derivative compound The compiled studies confirm the potential of nitrogen heterocyclic molecules in cancer treatment. The reported promising compounds from every scaffold present excellent activity against the different cell lines and kinase inhibitory assay which could be used in the structural based design of efficacious nitrogen-based anticancer drugs.


TP53. These cell lines and screening approach should prove useful for researchers studying a variety of cellular and biochemical phenomena.We describe the creation of an isogenic cell line panel representing common cancer pathways, with features optimized for high-throughput screening. More than 1,800 cell lines from three normal human cell lines were generated using CRISPR technologies. Surprisingly, most of these lines did not result in complete gene inactivation despite integration of sgRNA at the desired genomic site. A subset of the lines harbored biallelic disruptions of the targeted tumor suppressor gene, yielding a final panel of 100 well-characterized lines covering 19 frequently lost cancer pathways. This panel included genetic markers optimized for sequence-based ratiometric assays for drug-based screening assays. To illustrate the potential utility of this panel, we developed a high-throughput screen that identified Wee1 inhibitor MK-1775 as a selective growth inhibitor of cells with inactivation of   •Creation of an isogenic cell line panel representing the loss of 19 cancer pathways•TP53HTS confirmed MK-1775 as a selective inhibitor of cells with loss of •These cell lines are useful for studying a variety of cellular biochemical phenomena Biochemistry; Cancer; Biochemical analysis Recent advances in chemical synthesis techniques and robotics have led to an expansion in the availability of small molecule libraries . With thThe unprecedented progress in defining the cancer genome gave rise to hope for the development of new targeted cancer therapeutics. This hope was largely driven by early success of targeted therapies that inhibited the function of oncogenic driver mutations . HoweverEffective strategies for targeting loss of functions associated with tumor suppressor gene (TSG) mutations would substantially increase the number of therapeutically addressable pathways. Unfortunately, to date, only one FDA-approved therapy specifically exploits a TSG loss of function mutation . This thIn response to these issues, we created a human isogenic cell line panel targeting 19 critical genes inactivated in cancer. Each of these lines was engineered using CRISPR-based methods to disrupt a single tumor suppressor gene, and each contained a unique genetic barcode to permit multiplex screening. For each cell line, multiple orthogonal assays were used to validate successful gene disruption. Moreover, the panel was constructed from three distinct normal cell lines to ensure the generality of observed affects. And, finally, a sequence-based ratiometric assay was designed from this panel that incorporates numerous internal controls to maximize the reliability and sensitivity of the screening process.de novo, targeting either known mutation sites identified from the COSMIC database or early exons within the gene  and finally loss of wild-type transcript by transcriptome analysis. Western blot assays were performed on 95 cell line and protein loss was confirmed in 71 of them . For 102TP53 to the small molecule MDM2 inhibitor Nutlin-3a  and biologically significant  effect as described in the  MK-1775 .To model the power of the screen, we examined the distribution of counts across the entire screen, consisting of 43 RPE1 and 38 MCF10A cell lines and performed an in silico analysis where we reduced the level of each cell line reads by 50% or 90% in a given well . This anTP53-deficient cell lines from both RPE1 and MCF10a backgrounds within the primary screen when treated in the low micromolar ranges (TP53 mutant) and RFP (TP53 wild type)-labeled isogenic knockout cell lines .Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Kenneth Kinzler Ph.D (Biorepository@jhmi.edu.Cell lines generated in this experiments can be obtained by contacting the Johns Hopkins Genetic Resources Core Facility (GRCF) In vitro all cells were grown at 37°C with 5% CO2. Mycoplasma testing performed by The Genetic Resources Core Facility at Johns Hopkins University School of Medicine . Cells were not authenticated internally as they were sourced from a non-profit company (ATCC).RPE1, HEK293, MCF10a, and RPTec cells were purchased from The American Type Culture Collection . RPE1 cells (ATCC CRL-4000) are female in origin and were grown in RPMI 1640 Medium  supplemented with 10% fetal bovine serum . RPTec cells (ATCC CRL-4031) are male in origin and were grown in EPITHELIAL CELL MEDIUM-Complete Kit . HEK293 (ATCC CRL-1573) was grown in DMEM  supplemented with 10% FBS , MCF10a cells (ATCC CRL-10317) are female in origin and were grown in Bullet Kit MEBM Basal Medium 500 mL with cholera toxin (Sigma C8052-2MG) at 100 ng/mL and MEGM SingleQuots Kit Suppl. & Growth Factors  excluding gentomycin. MTAP is of particular interest and represented by multiple lines because it is frequently co-deleted with CDKN2A making it passenger mutation targetable for therapeutic benefit in human cancers  and amplified using primer pairs listed in Cells were lysed using RIPA buffer  with x1 protease inhibitor  and left on ice for 30 min. Samples were then centrifuged at max speed for 3 min in a QIAshredder  before being transferred to a new Eppendorf tube. Protein was quantified using a BCA assay .Westerns were performed by loading 30–50ug of total protein per well into 15 well polyacrylamide gels  and run for 30 min at 200 V. Gels were then transferred using manufacturer’s instructions (based on size) to nitrocellulose membrane using a Bio-Rad turbo transfer apparatus. Membranes were blocked for 1 h with 3% milk TBS-Tween before being incubated overnight in primary antibody (concentration dependent on antibody). Membranes were then washed 4 times for 5 min each with TBS-Tween. Secondary antibody was applied at 1:2500 . Membranes were imaged using Pierce™ ECL Western Blotting Substrate  following manufacturer’s instructions and imaged on a Bio-Rad Chemidoc . Antibody concentrations for IHC were specific for each protein being screened . GeneralFor RNA extraction, cells were pelleted, frozen in liquid nitrogen, and stored at −80°C until RNA extraction. RNA extraction using Qiagen AllPrep DNA/RNA Mini Kit  per manufacturer’s instruction with cell homogenization in RLT buffer via QIAshredder . RNA quality control using Agilent Tapestation 2200  and the Agilent RNA ScreenTape  and Agilent RNA ScreenTape Sample Buffer and Ladder  per manufacturer’s instruction. Library prep using Illumina RNA library prep kit  and sequenced on an Illumina HiSeq 4000 paired end using manufacturer’s instructions.Sequencing reads aligned to Hg38 using HISAT2 (version 2.0.5), assembly and quantification was performed using StringTie (version 1.3.3) and differential expression was performed using R package Ballgown (version 2.6.0) as described , 2016. ETP53 knockout cell lines were labeled with either a GFP or RFP plasmid . We then performed a co-culture of each knockout cell line with its respective parental line and treated with the compound of interest in a dose response curve. We imaged cells every 6 h for 4–6 days of treatment using Incucyte Zoom . Fluorescence was quantified using four locations in each treated sample by the IncuCyte Zoom 2016B software. Confluence assays were plated in 96-well plate format and imaged every 6 h for 4–6 days of treatment using Incucyte Zoom.Cell response assays were quantified using a sybr readout. Cells were rinsed 2× in phosphate buffered saline (PBS)  and lysed with 50 μL of 0.2% SDS  for 2 h at 37°C. 150 μL of Sybr Green I  solution (1:750 in water) was added and mixed 10× with a pipette. Fluorescence was read out with 485 nm excitation and emission measured at 530 nm on a BioTek microplate reader . DNA content of each sample analyzed relative to untreated samples.Z-scores calculated utilizing the ratio of target cell UID to total sequencing reads in a wellWe identified optimal plating of cells up to 7 distinct cell lines from the same background and 5,000 total cells per well of a 96-well plate maintained the best cell line representation and compound response. The library chosen was the FDA-approved & Passed Phase I Drug Library in 96 well format . We screened 81 total knockout cell lines across MCF10a and RPE1 cell line backgrounds and 19 critical cancer pathways at two doses: 1μM and 10 μM. Cells were plated in the morning and treated with the compound libraries in the evening of day 1. Plates were harvested on day 4 and molecular barcodes identifying each cell line were quantified by high-throughput sequencing.BARCODESTGTGGAAAGGACGAAACACC). Reverse primer includes Illumina primer sequence, well barcode, spacer, and a LentiV2 sequence (CAAGCAGAAGACGGCATACGAGATBARCODESNNCGGACTAGCCTTATTTTAACTTGC). This amplicon requires 96 reverse primers and 1 forward to amplify and uniquely identify each well in a 96-well plate  reads matching a single cell line in each staurosporin treated well to the cell lines respective UID reads from the untreated DMSO wells in the same screen plate. This was performed for each knockout line within each screen plate. To assess cell line representation and performance in each treated well, we calculated the z-score for each cell line’s fraction of reads within a single well to compare cell line abundance in drug treated wells and compared to the 95 other wells within the same plate. We assume the null hypothesis – for any given compound, it will not have a specific interaction with our gene of interest. Compounds in our screen with UIDs less than two-fold more unique molecular barcodes than the non-specific small molecule control within the same plate, staurosporine, were classified as non-specific cell killing. We did not consider compounds from these wells in our analysis.rd quartile, the lowest 25% of plates based on cell line representation within the plate. Based on this in silico calculated 3rd quartile z-score we classified cell lines as well powered, and used a cutoff of −1.5, or low powered, and used a cutoff of −1.0 to identify compounds of interest. Based on this classification, a maximum z-score threshold was set for each cell line either −1.5 for well powered or −1 for low powered. All compound-cell line z-scores below these thresholds were considered compounds of interest. For a compound to be considered a hit, the majority of cell lines in two cell line backgrounds would need to identify it as a compound of interest. Applying these criteria to DMSO wells showed that 0.11% of controls wells met the hit criteria.To determine the z-score threshold we looked at representation of each cell line in the DMSO treated control wells and down-sampled the sequencing of these well to 0 in increments of 10%, calculating the z-score at each increment to determine the power to see each cell line. This was determined for each plate in our screen and thresholds determined from the 3


The majority of high-risk neuroblastomas harbor telomerase activity, and telomerase-interacting compounds, such as 6-thio-2’-deoxyguanosine (6-thio-dG), have been found to impair the growth of telomerase-positive neuroblastoma cell lines. It has remained unclear, however, how such drugs can be combined with other compounds used in current treatment concepts for neuroblastoma patients.Growth-inhibitory effects of varying concentrations of 6-thio-dG in combination with etoposide, doxorubicin or ceritinib were determined in eight telomerase-positive neuroblastoma cell lines with distinct genetic backgrounds. Tumor growth inhibition of subcutaneous xenografts from three different cell lines was assessed upon treatment with 6-thio-dG, the competitive telomerase inhibitor imetelstat, etoposide, or combinations of these compounds.in vitro. Treatment of mouse xenografts with combinations of 6-thio-dG and etoposide significantly attenuated tumor growth and improved mouse survival over etoposide alone in two of three cell line models. Treatment of xenograft tumors by imetelstat monotherapy decreased telomerase activity by roughly 50% and significantly improved survival over control in all three models, whereas treatment with imetelstat plus etoposide led to enhanced survival over etoposide monotherapy in one model. Mechanistically, the synergistic effect was found to be due to both increased apoptosis and cell cycle arrest.Robust synergistic anti-tumor effects were observed for combinations of 6-thio-dG and etoposide or doxorubicin, but not for 6-thio-dG and ceritinib, in telomerase-positive neuroblastoma cell lines Our study indicates that telomerase is an actionable target in telomerase-positive neuroblastoma, and demonstrates that combination therapies including telomerase-interacting compounds may improve the efficacy of established cytotoxic drugs. Targeting telomerase may thus represent a therapeutic option in high-risk neuroblastoma patients.The online version contains supplementary material available at 10.1007/s13402-022-00702-8. TERT) gene through MYCN over-expression in MYCN-amplified tumors, or through genomic rearrangements of the TERT locus [TERT is upregulated by unknown mechanisms [ATRX gene [RAS pathway, such as the anaplastic lymphoma kinase (ALK) gene, and the p53 pathway have been found to contribute to neuroblastoma pathogenesis and to be associated with a poor clinical outcome, in particular in the presence of telomere maintenance mechanisms [Neuroblastoma is a pediatric solid tumor of the sympathetic nervous system. Clinical courses of neuroblastoma patients vary greatly, ranging from spontaneous regression to fatal progression despite intensive multimodal treatment . It has RT locus , 6. In achanisms . By contTRX gene , 4, 5, 7chanisms , 8, 9.TERT rearrangements, MYCN amplification or high TERT expression in the absence of these alterations, both in vitro and in vivo [de novo synthesized telomeres, which results in modified telomeres, leading to telomere dysfunction without substantial changes of telomere lengths [hTERC) and potently and competitively inhibits telomerase enzymatic activity [ALK inhibitors act synergistically on neuroblastoma growth in vitro and in vivo.Telomerase has been considered as a promising therapeutic target in cancer for many years, however, both the development of effective and specific telomerase inhibitors and incorporation of available telomerase inhibitors into clinical practice has remained challenging . It has  in vivo , 10–13. activity . Clinicaactivity , 16. Ime2 and temporarily stored in DMSO at -80 °C. CLB-GA, GI-MEN, BE(2)-C, IMR-32, TR-14, LS and SH-SY5Y were maintained in RPMI-GlutaMAX™ with 10% fetal calf serum (FCS), while SK-N-FI was maintained in DMEM supplemented with 10% FCS and 1% non-essential amino acids . TERT expression was determined by oligonucleotide microarray analysis  for all cell lines according to manufacturer’s guidelines.The NB cell-lines GI-MEN, CLB-GA, LS and IMR-32 were purchased from the German Collection of Microorganisms and Cell Cultures (DSMZ). The cell lines SK-N-FI, BE(2)-C, TR14 and SH-SY5Y were obtained from the American Tissue Culture Collection (ATCC). Cell lines were cultured at 37 °C and 5% CO6-thio-dG was purchased from BioVision , and imetelstat was kindly provided by Geron .TERT rearrangements , high TERT expression (SH-SY5Y) or MYCN amplification (BE(2)-C, IMR-32, Kelly, LS, TR-14) were determined after 96 h of substance incubation using CellTiter-Glo®. A semi-automated substance screening protocol was established on a Biomek 4000 Automated Workstation . Single or combined compounds in nine different concentrations and DMSO as control were added in triplicates 24 h after the cells were seeded in a 96-well plate at a density of 3000 cells/well. Cell viability was measured after 96 h of substance incubation using a CellTiter-Glo® (CTG) Luminescent Cell Viability Assay . In brief, 100 µl CTG-reagent was added to the wells and incubated for 30 min at room temperature. Signals were measured using a SpectraMax® i3x Multi-Mode microplate reader . Drug synergy was calculated according to the Chou-Talalay combination index method [Growth-inhibitory effects of varying concentrations of 6-thio-dG in combination with etoposide , doxorubicin  or ceritinib  on neuroblastoma cell lines with x method , 18.2 cell culture flasks and incubated for 48 h with varying drug concentrations after reaching medium density. Total protein was extracted using RIPA buffer  and protease inhibitors. Protein concentrations were quantified using the bicinchoninic acid bradford method. Protein lysates (50 μg) were separated using 10% SDS-PAGE4-12% Bis–Tris Gels and electrotransferred to polyvinylidene difluoride nitrocellulose membranes . The membranes were blocked in PBST 5% non-fat dry milk and TBST solution, incubated in TBST and gently shaken with primary antibodies diluted to vendor specifications at 4 °C overnight. Finally, the membranes were incubated with appropriate secondary antibodies and visualized using an enhanced chemiluminescence detection kit  or chemiluminescence detection kit . Antibodies directed against PCNA (rabbit), cleaved caspase-7 (rabbit), p21Waf1/Cip1 (rabbit), PARP (rabbit), anti-rabbit IgG HRP linked and β-Actin (rabbit) were purchased from Cell Signaling Technology , and against β-Actin (mouse) from Abcam (UK). An antibody directed against pCDK1 was purchased from Life Technologies  and a polyclonal goat anti-mouse Ig/HRP from Agilent .Neuroblastoma cells were seeded into 25 cm5 cells/ml. After two days the cells were treated with varying drug concentrations for 48 h. As a control, cells were treated with DMSO. Cells were harvested using accutase (Sigma-Aldrich). For cell cycle analysis cells and supernatants were harvested and washed twice with FACS buffer  and filtered through a 40 µm cell strainer . The pellet was subsequently resuspended in 500 µl PBS and permeabilized and fixed in ice-cold 70% ethanol overnight. After washing twice with PBS the cells were stained with PI after RNAse A was added. For apoptosis staining, cells and supernatants were harvested and washed twice with cell staining buffer . As positive control, cells were incubated at 70 °C for 5 min. Cells were resuspended in Annexin Binding Buffer, PI and Annexin-Alexa 488 following the manufacturer’s instructions , after which RNAse A was added. Cells were analyzed using a FACSCanto II instrument (BD Biosciences) and FlowJo software (BD Biosciences).Neuroblastoma cells were seeded in 60 mm cell culture dishes  at a density of 0.1 × 10Telomerase activity in cell lines and neuroblastoma xenografts was determined using a PCR-based telomeric repeat amplification protocol (TRAP) enzyme-linked immunosorbent assay (ELISA) kit  according to the manufacturer’s protocol. Briefly, the assay was performed in a 40 µl reaction mixture containing 20 mM Tris–HCl (pH 8.0), 1 mM dNTPs, and aliquots of proteins from T24 cell extracts (control), cell lines or tissue samples. Each mixture was incubated at 20 °C for 60 min. Telomerase activity was measured using SpectraMax at 450 nM. Tumors were excluded from the study when the extracted protein levels were too low for the TRAP assay, due to large areas of necrosis resulting in small residual tumor masses.DNA was isolated from tumor samples or cell lines using a Gentra Puregene Tissue Kit . Mean telomer restriction fragments (TRF) were determined using a Telo-TAGGG Telomere Length Assay kit  according to the manufacturer’s instructions. DNAs from Kelly and SK-N-FI neuroblastoma cell lines were used as controls. Signals were detected by using a BIORAD MP imaging System.6 to 1 × 107 neuroblastoma cells were resuspended in 200 µl Matrigel  and injected subcutaneously into the flank of immunodeficient athymic nude mice . Tumor volumes were measured in (LxWxD)/2 mm3 every two days by digital caliper, and animal weights were tracked daily. When tumors reached > 80 mm3 average volume, the mice were randomly divided into control and treatment groups . Intraperitoneal injections of imetelstat (30 mg/kg in aqua ad inj.), or vehicle alone were administered twice weekly. Etoposide (15 mg/kg) and/or 6-thio-dG (2.5 mg/kg), or control (DMSO 5%) were injected three times/week intraperitoneally. Mice were euthanized by cervical dislocation at a tumor volume > 1000 mm3. All animal experiments were performed according to German ethics guidelines and law (file number: 84–02.04.2016.A064 and 81–02.04.2017.A508) meeting the ARRIVE guidelines.To determine tumor growth inhibition by imetelstat, 6-thio-dG, etoposide, and drug combinations, 5 × 10Fresh frozen tumors were cut onto glass slides at 6 µm after which a terminal deoxynucleotidyl transferase mediated dUTP nick end labeling (TUNEL) assay was used to determine the rate of apoptotic cells. TUNEL assay was performed using an In Situ Cell Death Detection Kit, TMR red (Roche) according to the manufacturer’s instructions. Samples were mounted with VectaShield mounting media containing 4′,6-diamidino-2-phenylindole dihydrochloride (Vector Laboratories). Images were acquired using a Leica DM 5550B fluorescent light microscope system and full z-stacks were taken at 0.5 µm and projected using CytoVision® 7.6 software (Leica).p-value < 0.05 was considered significant. Statistical analyses were performed using the python packages pandas and scipy, while visualization was performed using matplotlib, seaborn and lifelines distributed through pypi.org under python version 3.8.10. Non-parametric variables between groups were compared using the Mann–Whitney-U test. Statistical significance of Kaplan Meier estimates were calculated using logrank test.The data obtained are presented as mean values ± standard deviation (SD). Comparisons of different groups for statistical significance were analyzed using a two-tailed, unpaired Student t test. A ALK inhibitor ceritinib), we assessed the effect of these compounds on cell viability individually and in combinations in eight neuroblastoma cell lines in vitro -C, SH-SY5Y, KELLY, GI-MEN, TR-14, IMR-32 and LS). All eight cell lines harbor telomerase activity, however, they differ in their genomic status of TERT, MYCN and ALK (Suppl. Table 50) was 2.65 µM for 6-thio-dG, which is similar to previously reported GI50 concentrations in telomerase-positive neuroblastoma cell lines [50 concentrations were 0.33 and 0.03 µM for etoposide and doxorubicin, respectively. Exposure to the ALK inhibitor ceritinib resulted in more pronounced growth inhibition in ALK-mutated than in ALK wild-type cell lines .To evaluate potential synergistic effects of the telomerase substrate nucleoside precursor 6-thio-dG with other compounds that are active in neuroblastoma . In particular, we did not observe substantially different synergistic effects in ALK-mutated  and in ALK wild-type  cell lines, with lowest CoIn*  in the ALK-mutated cell line CLB-GA, pointing towards antagonism in this case.To assess potential synergy of 6-thio-dG treatment in combination with cytotoxic drugs or ceritinib, we exposed all cell lines with increasing concentrations of combinations of these compounds, which had been selected to overlap with the therapeutic ranges according to the individual GInds Fig. . As expends Fig. . We thennds Fig. . Mean coTERT rearrangement (CLB-GA), MYCN amplification (BE(2)-C), or elevated TERT expression without such genomic alterations (SH-SY5Y). To assess which mechanisms may contribute to cell growth inhibition upon combination treatment, we first determined changes of cleaved caspase-7 as a marker of apoptosis, p21Waf1/Cip1 as a marker of cell cycle arrest, and PCNA as a marker of cellular proliferation by immunoblotting in cell lines SH-SY5Y, CLB-GA and BE(2)-C -C cells C treated with 6-thio-dG and etoposide using flow cytometry with annexin V/PI staining -C Fig. . We obsells Fig.  and a deation (BE-C), or ells Fig. . By conting Fig. , and an ation (BE-C), or eALK inhibition, leads to growth inhibition by inducing both cell cycle arrest and apoptosis.These data suggest that decreased cell viability caused by 6-thio-dG in combination with cytotoxic drugs is at least partly due to apoptosis, while this effect may vary after exposure to 6-thio-dG in combination with ceritinib. Together, our results indicate that combination treatment of 6-thio-dG plus genotoxic drugs, but not 6-thio-dG plus in vitro observations, we expected synergistic growth inhibitory effects in vivo for the combination of 6-thio-dG and genotoxic drugs. As we found comparable CoIn for both combination treatments (6-thio-dG/etoposide and 6-thio-dG/doxorubicin) in BE(2)-C and in SH-SY5Y, we opted to test a combination of 6-thio-dG (2 mg/kg) and etoposide (15 mg/kg) in mouse xenografts of these two cell lines. In addition, we selected CLB-GA, representing a cell line that bears a TERT rearrangement. We found that combination treatment was well tolerated, with no effects on mouse weight, appearance or behavior . Telomer length was not significantly altered in xenograft tumors after 28 days of treatment with 6-thio-dG and etoposide versus vehicle alone  and the MYCN-amplified cell line BE(2)-C (IC50 = 6.5 µM) at substantially lower concentrations than in SH-SY5Y cells that express high levels of TERT without such alterations -C and SH-SY5Y We next aimed to determine whether a combination of imetelstat and etoposide may act synergistically in neuroblastoma xenografts, analogous to 6-thio-dG. Similar to 6-thio-dG combination therapy, we noted that treatment with imetelstat in combination with etoposide was well tolerated by the animals . We found that treatment with this combination significantly improved mouse survival in all three models over treatment with control Fig. . SimilarALK inhibitor ceritinib, both in ALK-mutated and ALK-wildtype neuroblastoma cells.We here demonstrate that combinations of telomerase interacting compounds and cytotoxic drugs synergistically inhibit tumor growth in preclinical neuroblastoma models, thus offering a promising therapeutic approach for patients with telomerase-positive high-risk neuroblastoma. By contrast, we did not observe significant synergistic effects of 6-thio-dG in combination with the TERT occurs in the majority of high-risk neuroblastomas, and telomerase has thus been considered as a promising tractable target [in vitro and in vivo, but not that of ALT-positive tumors [TERT down-regulation in TERT-rearranged neuroblastoma cell lines [in vivo inhibitory efficiency of direct telomerase inhibitors may further increase their anticancer effects in telomerase-positive neuroblastoma.Induction of e target , 5, 6. We tumors . Therapye tumors . In linell lines . Similarll lines , leads tMYCN-amplified and p53-mutated cell line BE(2)-C to combination treatment in vitro was relatively poor, and that no synergistic effects were found in BE(2)-C xenografts. While the mechanistic understanding of this observation remains elusive, it has to be noted that this cell line had been generated from a chemotherapy refractory neuroblastoma [in vitro GI50 for etoposide in all tested cell lines, which was up to ten-fold higher than those in CLB-GA and SH-SY5Y cells 50) of individual compounds are given for each cell lineSupplementary file2 (JPG 1700 KB) Suppl. Fig. 1: Relative cell viability determined by CellTiter-Glo assay in neuroblastoma cell lines treated with various concentrations of 6-thio-dG, etoposide, doxorubicin, or ceritinib. Error bars indicate standard deviation. Half maximal inhibitory concentrations (GISupplementary file3 (PDF 426 KB) Suppl. Fig. 2: Western blot analysis of PARP, cleaved-PARP, and pCDK1 in cell-lines BE(2)-C, CLB-GA and SH-SY5Y after 48 hours of treatment with 6-thio-dG plus etoposide at the indicated concentrations or DMSO; ß-actin was used as loading controlSupplementary file4 (PDF 534 KB) Suppl. Fig. 3: Development of mouse weights (g) of the indicated treatment groups over time. Error bars indicate standard deviationin vitro, and after 4-week-treatment of xenograft tumorsSupplementary file5 (PDF 435 KB) Suppl. Fig. 4: Mean telomere lengths (kb) of SH-SY5Y cells as determined by telomere restriction fragment assay after treatment with control or 6-thio-dG and etoposide for 96 h Supplementary file6 (JPG 31 KB) Suppl. Fig. 5: (A) KaplanMeier estimates for survival of athymic nude mice bearing xenografts of human neuroblastoma cell line SK-N-FI treated with imetelstat versus vehicle alone. (B) Tumor growth of SK-N-FI xenografts as indicated in (A). P-values were calculated for the last day of measurementBelow is the link to the electronic supplementary material.


Colon cancer is the third most common cancer and second highest cause of cancer deaths worldwide. The aim of the study was to find new biomarkers for diagnosis, prognosis and therapeutic drug targets for this disease.Four low-grade and four high-grade human colon adenocarcinoma tumours with patient-matched normal colon tissues were analysed. Additionally, tissue-derived primary cell lines were established from each tumour tissue. The cell lines were validated using DNA sequencing to confirm that they are a suitable in vitro model for colon adenocarcinoma based on conserved gene mutations. Label-free quantitation proteomics was performed to compare the proteomes of colon adenocarcinoma samples to normal colon samples, and of colon adenocarcinoma tissues to tissue-derived cell lines to find significantly differentially abundant proteins. The functions enriched within the differentially expressed proteins were assessed using STRING. Proteomics data was validated by Western blotting.A total of 4767 proteins were identified across all tissues, and 4711 across primary tissue-derived cell lines. Of these, 3302 proteins were detected in both the tissues and the cell lines. On average, primary cell lines shared about 70% of proteins with their parent tissue, and they retained mutations to key colon adenocarcinoma-related genes and did not diverge far genetically from their parent tissues. Colon adenocarcinoma tissues displayed upregulation of RNA processing, steroid biosynthesis and detoxification, and downregulation of cytoskeletal organisation and loss of normal muscle function. Tissue-derived cell lines exhibited increased interferon-gamma signalling and aberrant ferroptosis. Overall, 318 proteins were significantly up-regulated and 362 proteins significantly down-regulated by comparisons of high-grade with low-grade tumours and low-grade tumour with normal colon tissues from both sample types.The differences exhibited between tissues and cell lines highlight the additional information that can be obtained from patient-derived primary cell lines. DNA sequencing and proteomics confirmed that these cell lines can be considered suitable in vitro models of the parent tumours. Various potential biomarkers for colon adenocarcinoma initiation and progression and drug targets were identified and discussed, including seven novel markers: ACSL4, ANK2, AMER3, EXOSC1, EXOSC6, GCLM, and TFRC.The online version contains supplementary material available at 10.1186/s12014-022-09364-y. Colorectal cancer (CRC) is the third most common cancer type, accounting for 10% of new cancer cases in 2020, and the second highest cause of cancer deaths [APC gene is considered the initiating event of CRC development [KRAS and deactivating mutations of TP53 and SMAD4 are also common in CRC, and their sequential accumulation contributes to the adenoma-carcinoma sequence of disease progression [Mutation of the elopment , 4. Actigression . This mogression .KRAS, NRAS and BRAF mutations and testing for mismatch repair (MMR) defects or microsatellite instability (MSI) [CRC is typically diagnosed late due to it being asymptomatic at earlier stages of disease progression. Diagnosis is typically made by colonoscopy to visualise polyps or tumours, or faecal occult blood tests to detect blood in the stool . Serum lty (MSI) . MSI staThere is a need for more reliable, non-invasive and specific biomarkers to enhance detection of early-stage CRC, and treatments that target the mechanisms enabling CRC progression. Recently, there has been a focus on employing proteomics to identify CRC biomarkers. Interrogation of liquid biopsies from patients –15 identIn this study, we analysed tumour tissue samples from 4 LGCA patients and 4 HGCA patients and their corresponding patient-matched normal colon (NC) tissue samples, and primary cell lines derived from the 8 CA tissue samples. Label-free quantitation (LFQ) proteomics was utilised to characterise the proteomes of the samples. The aims of this study were to characterise cell lines derived from colon tumour tissue in comparison with their tissues of origin, and to identify novel potential biomarkers and drug targets of CRC at tumour initiation and progression. The primary cell lines were validated using DNA sequencing and proteomics by comparison to their parental tissues. Differentially expressed proteins, measured by liquid chromatography tandem mass spectrometry (LC–MS/MS), were determined based on the confidence of protein identification and statistically significant changes in abundance between the patient-matched adjacent NC and LGCA and between LGCA and HGCA. The functional enrichments associated with these changes in the gene ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathways were analysed to evaluate the samples at the system level. The proteomes and functional implications were also compared between CA tissues and CA-derived primary cell lines.Formalin-fixed paraffin-embedded (FFPE) and snap-frozen tissue samples from 4 LGCA patients and 4 HGCA patients, with 8 patient-matched adjacent NC samples (4 from LGCA patients and 4 from HGCA patients), were provided by the Gillies McIndoe Research Institute Tissue Bank (GMRITB) for this study, which was approved by the Central Health and Disability Ethics Committee, Wellington, NZ Ref. 15/CEN/96) with written informed consent from all patients. The FFPE tissue samples were used for immunohistochemical (IHC) staining. The snap-frozen tissues were used for proteomics, with a total of 16 tissue samples analysed. Patient clinical data can be found in Additional File 5/CEN/96 Primary cell lines were derived from each of the CA tissues, giving 8 cell lines (4 from LGCA and 4 from HGCA) from different donors. Cell lines were provided by GMRITB at passage number 4–5 and were subcultured to a passage number not higher than 9 for experiments. Cells were cultured in Nunc™ EasYFlasks™ (ThermoFisher Scientific) using DMEM media  supplemented with 10% fetal calf serum , 5% mTeSR Complete , 1% penicillin–streptomycin  and 0.2% gentamicin/amphotericin B . Cells were passaged upon reaching 75–95% confluency using TrypLE Express Enzyme .IHC staining was performed as previously described  on 4 µm DNA was extracted from FFPE tissue samples and tissue-derived cells using the PureLink Genomic DNA Mini Kit . The TaqMan™ RNase P Detection Reagents Kit  was used, as per the manufacturer’s instructions, to determine whether DNA was of sufficient quality to be successfully and accurately sequenced. DNA sequencing was performed by ThermoFisher Scientific  using the Oncomine™ TML assay to assess the mutational signatures of key CA-related genes in the CA tissues and the CA tissue-derived primary cell lines. DNA sequencing data were analysed using the cloud-based Ion Reporter system. Single-nucleotide variants and their impacts and tumour mutational burden were compared between FFPE tissues and the CA tissue-matched primary cell lines.Tissues and cells were lysed in lysis buffer containing 30 mM Tris–HCl, pH 7.4; 7 M urea, 2 M thiourea, and 4% CHAPS plus 1% Halt™ Protease and Phosphatase inhibitor cocktail , with a 1 mL glass Dounce homogeniser  on ice. Samples were agitated for 45 min at 4 °C, then centrifuged at 17,000 g for 20 min at 4 °C. Protein concentration was measured by Bradford assay (Bio-Rad). The samples were stored at − 20 °C.Extracted proteins were precipitated using a Calbiochem ProteoExtract® Protein Precipitation Kit as per manufacturer’s instructions . The protein pellet was dissolved in a digestion buffer of 8 M urea and 100 mM Tris–HCl, pH 8.5. After a second Bradford assay, 20 µg of protein was taken from each sample and the volume brought to 25 µL using digestion buffer. Subsequently, the proteins were reduced, alkylated and digested as previously described , 30. TheProteomic analysis of the prepared samples was performed by LC–MS/MS using an UlitMate 3000 RSLCnano system and a high-resolution Orbitrap Fusion™ Lumos™ Tribrid™ mass spectrometer coupled via a Nanospray Flex ion source (ThermoFisher Scientific). All samples were run individually.Sample vials were placed in the autosampler of the HPLC unit for injection, maintained at 10 °C. Xcalibur™ software  was used to define the method and acquire LC–MS/MS data. Peptides were first loaded onto an Acclaim™ PepMap™ 100 C18, 5 μm 0.3 × 5 mm trap column  with 2% ACN and 0.05% trifluoroacetic acid at a loading pump flow rate of 8.0 µL/min, then separated on an Acclaim™ PepMap™ 100 C18, 2 µm, 100 A, 75 µm × 15 cm analytical column  with the Nano/Cap pump running at 0.3 µL/min with an organic solvent gradient constructed from buffer A (0.1% FA) and buffer B (0.1% FA in 80% ACN). The gradient was programmed as follows: 3% from 0 to 5 min, 30% from 5 to 70 min, 50% from 70 to 82 min, 95% from 82 to 88 min, and finally 3% from 88 to 99 min. Elution was based on reverse-phase liquid chromatography, whereby the more hydrophobic the peptide is the slower it will pass through the column. Also, larger peptides have longer retention times.The peptides eluted in solution were ionised by nanoelectrospray ionisation  with the 25 µM Ion Transfer capillary tube set to 275 °C and voltage set at 1.8 kV. MS scans were acquired in the Orbitrap (OT) with the following settings: detector type OT, resolution 120,000, scan range 375–1500 m/z, AGC target 5.0e3, Maximum Injection Time 50 ms, charge state 2–7, and data type Profile. Data-dependent MS/MS scans were acquired in Ion trap having the following settings: detector type IT, scan range mode Auto: m/z Normal, IT scan rate Rapid, AGC target 5.0e3, Maximum Injection Time 300 ms, and data type Centroid. For MS/MS, high-energy collision-induced dissociation (HCD) fragmentation was performed in the linear Quadrupole ion trap . The “Top 20” highest-intensity ions from each MS scan were selected for the subsequent MS/MS scans. Dynamic exclusion had the following settings: mass tolerance 10 ppm, exclusion duration 60 s. Each sample was run in triplicate for LC–MS/MS.Spectra were exported as .raw files and searched against SwissProt human protein sequence database  using the SequestHT search engine in Proteome Discoverer . Protein identification settings were as follows: peptide length range 6–144, allowing 2 missed trypsin cleavages, precursor mass tolerance 10 ppm, fragment mass tolerance 0.5 Da; cysteine carboxyamidomethylation static modification (+ 57.021); dynamic modifications included: oxidation (+ 15.995 Da) at M, carbamylation (+ 43.066 Da) at K, acetylation (+ 42.011 Da) at K, deamidation (+ 0.984 Da) at N and Q, peptide N-terminus modification of carbamylation (+ 43.066 Da). The files were searched against the protein sequence database and the decoy database (Percolator node) with a false discovery rate (FDR) of 0.01.LFQ was carried out using PD, which has been demonstrated to perform better in terms of quantifiable low abundance proteome coverage than other search engines . The .ra2 FC ≥ 1), and a p-value of 0.05 or smaller . These significantly differentially expressed proteins were subsequently analysed for functional enrichments using STRING database (string-db.org) [Proteins with a minimum of one unique high-confidence peptide assigned were considered as positive identifications. Protein quantitation grouped abundances were used to calculate the abundance ratio for any given comparison. A t-test was performed by built-in statistical tools in PD to determine the statistical significance for each comparison. The selection criteria for significantly differentially expressed proteins were set at a fold-change (FC) of 2 or greater (log-db.org) .Significantly up-regulated or down-regulated proteins determined by LFQ were imported into STRING (string-db.org)  to identProtein extraction and quantitation were performed as described above, except lysis buffer was Pierce™ RIPA buffer .Protein samples were diluted in 1 × Bolt LDS sample buffer , heated at 85 °C for 5 min and run on Bolt 4–12% Bis–Tris gels  with 20 µg of sample protein per lane, and 1–2 µL of Precision Plus Protein Kaleidoscope MW ladder  run in the first lane. Gels were run in Bolt MES SDS Running Buffer  for 50 min at 150 V, 3.00A and 300 W.Electrophoresed proteins were transferred to PVDF membranes using an iBlot 2 apparatus , briefly washed in water and blocked using iBind Flex FD solution  before exposure to primary and secondary antibodies in an iBind apparatus . Primary antibodies included: α-tubulin , CD44 , FN1 , and S100A9 . Secondary antibodies included: HRP-linked goat anti-rabbit , HRP-linked goat anti-rabbit , and Alexa Fluor® 488 donkey anti-mouse . Membranes were incubated in the iBind apparatus for 2.5 h or overnight. Following incubation, the membranes were briefly washed in water and developed using Clarity Western ECL Substrate . Imaging and densitometry were performed using a ChemiDoc MP Imaging System (Biorad) and ImageLab 6.0 software (Biorad), with the intensity values for the protein-of-interest normalised against α-tubulin and analysed using GraphPad Prism 8 .IHC staining demonstrated the branching crypts of LGCA tumours and the chaotic architecture of the HGCA tumours  and confirmed using the TaqMan™ RNase P Detection Reagents Kit  according to the manufacturer’s instructions, was isolated from 3 of the 4 LGCA and all 4 HGCA patient-derived tissue and cell line samples, and the DNA samples were analysed by DNA sequencing. The pre-defined Oncomine Tumor Mutation Load w3.2 analysis workflow was launched for each individual tissue and cell line sample, which calculated the tumour mutational burden (TMB) score for each sample, identified and annotated variants within 409 cancer-related genes, and assigned an impact level to each variant. Following this, paired analyses were performed to compare each tissue with its matched cell line.APC, TP53, KRAS, BRAF, PIK3CA and FBXW7 genes were identified by other studies as being relevant to CRC [MSH2, MSH6 and MLH1 genes are vital to DNA MMR and MSI, and mutations to these genes increase the risk of CRC development by approximately 80% [To confirm whether the mutations detected in the cells were the same as those in the tissues and thereby determine the similarity of the cell lines to their parent tissues, several CA-related genes were selected and the specific mutations within these genes were explored Table . The APCt to CRC , 23, 33.tely 80% .Table 1MAPC gene was the most commonly mutated, with the c.5034 G > A mutation present in the tissues and cell lines for all 7 samples. A total of 41 APC mutations were identified across all samples at 12 different sites  mutations were shared by the CA tissue samples and the matched CA-derived cell lines based on the analysis of these 9 genes  and/or coverage depth (< 300 reads), which were unique to 1 sample type  and/or unique to 1 patient, were considered to be read errors and were disregarded.A total of 4767 high-confidence proteins were identified across all tissue samples , and a total of 4711 high-confidence proteins were identified across cell lines . Of the proteins identified, 3302 proteins were shared by the pooled tissues and pooled cell lines, accounting for 69.3% and 70.1% of the proteins identified in the tissues and cell lines, respectively. This was also the case when comparing the proteomes of each primary cell line with its parent tumour tissue sample individually, with around 70% of proteins detected in one sample type also seen in the other. Complete lists of the proteins identified from tissue samples and from cell lines are available in Additional Files 5 and 6, and a list of all proteins shared by the tissues and cell lines can be found in Additional File The similarities of biological replicates for each condition were assessed for the tissues and cell lines. The 4 LGCA-derived cell lines shared 56.9% of identified proteins .The GO terms and KEGG and Reactome pathways enriched in the initiation (NC to LGCA) and progression (LGCA to HGCA) of tumours are summarised in Fig. Relative to NC tissues, the proteins overexpressed in LGCA tissues were enriched for preribosome activity, components of the RNA-degrading exosome complex and intracellular organelles Fig. A, indicaThe proteins with significant overexpression in HGCA tissues relative to LGCA tissues were enriched for immune system responses, detoxification and cell adhesion Fig. A. Among Proteins with significantly increased abundance in HGCA cells relative to LGCA cells were enriched for IFN-g and NF-kB signalling, cytokine-mediated signalling, ferroptosis and endocytosis Fig. A. Key feTo validate the LC–MS/MS results, western blotting (WB) was performed for representative selected proteins that had large differences in relative abundance with high statistical significance Fig. . DensitoFN1 was selected to validate the LC–MS/MS result in cell lines due to significant downregulation in HGCA cell lines relative to LGCA cell lines Table . DensitoCD44 was selected due to its significant upregulation in HGCA-derived cell lines relative to LGCA cell lines (abundance ratio HGCA / LGCA = 2.27) Table  and its S100A9 was selected because there was a sequential increase in abundance ratio for LGCA / NC (1.81), HGCA / LGCA 2.52) and HGCA / NC (4.86) in the tissue samples Table . This wa.52 and HIn order to assess the suitability of the tumour-derived primary cell lines as in vitro models of disease, DNA sequencing was performed to confirm that they carried over key mutations present in the parent tumour and did not diverge too far from the parent tissue by accumulating new mutations.APC gene are the most common mutations in CRC [MSH2 and MLH1, APC can be used as a predictive marker of CRC development [Inactivating mutations to the s in CRC , 4. Theys in CRC . Along welopment . Of the TP53 usually suffers from biallelic deactivation in CRC—one copy mutated and the other lost in a chromosomal deletion (17q), and this loss is associated with malignant transformation [TP53 [TP53 mutation also carried mutations in the MSH2, MSH6 and/or MLH1 genes, suggesting a hypermutated phenotype [MSH6 mutations in particular are prevalent in the hypermutated phenotype [henotype . MSH6 muhenotype , and theInterestingly, the LGCA tumours contained more mutations within these CRC-related genes than HGCA tumours; however, HGCA tumours had larger TMB scores -mediated signalling pathways in HGCA-derived cells relative to LGCA-derived cells Fig. .Ferroptosis is a recently recognised form of regulated cell death by iron-dependent lipid peroxidation that causes cellular membrane damage and the accumulation of reactive lipid hydroperoxides (known as lipid-ROS) to lethal levels . Long-chFerroptosis can be antagonised by neutralising lipid-ROS by coupling the oxidation reaction of glutathione . GlutamaCellular iron is another factor regulating ferroptosis via the Fenton reaction to produce lipid-ROS, and acts as a cofactor for lipoxygenases that catalyse lipid peroxidation . When inTP53 mutants where p53 is reduced or absent, DPP4 forms a complex with NOX1 to promote lipid peroxidation. TP53 is one of the most commonly mutated genes in CRC, and at least one mutation was detected in both the tissues and cell lines from 5 of the 7 samples  relative to NC tissues Fig. B. ConverInterestingly, the data for FN1 and for MCH class I components from the tissues and cell lines were inconsistent. FN1 is one of many ECM proteins with aberrant expression in cancer, where it is associated with angiogenesis, invasion via matrix metalloproteinase activation, self-renewal, proliferation, and resistance to therapy, and high expression correlates with poor survival , 50. OneSMC2 gene is a Wnt signalling target, and miRNA silencing of SMC2 reduces intestinal tumour cell proliferation [The Wnt signalling pathway is heavily implicated in cancer stem cell (CSC) function, and is considered the first pathway to be altered in CA development . APC memferation . DNA supferation . SMC2 diThe comparison of the proteomes of CA tissues with patient-matched tissue-derived primary cell lines provides unique insight. The cell lines, which are a purer population that retain the mutational signatures of the original tumour tissue, represents a unique and powerful method of analysing changes that are more relevant to the signalling within and between tumour cells without being overwhelmed by the large-scale changes occurring across the complexity of a tissue sample. For example, the HGCA cell lines revealed enrichment for IFN-g signalling and ferroptosis not seen in the comparison of NC, LGCA and HGCA tissues, which instead revealed less specific immune-related changes .Overall, this suggests that within the tissue there are many unique physiological and structural changes occurring that are important aspects of the loss of normal function and the response of the body to the tumour, and the primary cell lines supplemented these findings by revealing changes in proteins involved in immune interactions and ferroptosis that went undetected in the tissues.This study has identified various proteins of interest that warrant further research as potential CA biomarkers, as well as validating some that have previously been identified Table . Proteinhttps://www.proteinatlas.org/ENSG00000130234-ACE2/pathology). It is possible that ACE2 plays a role in CRC outside of the RAS, or that the outcomes of MasR signalling depend on their physiological context. The importance of ACE2 in CRC deserves further research.ACE2 is a component of the renin-angiotensin system (RAS) that catalyses the production of Mas receptor (MasR) ligands Ang1-9 and Ang1-7 . MasR siAnkyrins are adapter proteins that organise integral membrane proteins including cell junction proteins and cell adhesion molecules, ion channels and transporters by anchoring them to the spectrin-based membrane skeleton within the cell –67. ANK2The CA tissues displayed increased levels of preribosomal components  and RNA processing members . U3 small nucleolar RNA-associated protein 4 (CIRH1A/UTP4) strongly promotes CA cell proliferation and reduces apoptosis ; it was Calponin-1 (CNN1) regulates smooth muscle contraction by binding actin, calmodulin and tropomyosin , 71. Dow2+ and Zn2+ ions and plays an important role in inflammation caused by infection, autoimmunity or metabolic diseases [S100A8 (MRP8) and S100A9 (MRP14) are commonly found as a heterodimer called calprotectin that binds Cadiseases . Upreguldiseases . Accordidiseases , 23. SimFunctional assays, including miRNA silencing or CRISPR knock-outs, would clarify the roles of these potential CRC biomarkers.Proteomic analysis revealed that when compared to their NC controls, CA tissues displayed increases in preribosome function and RNA processing, and loss of normal muscle function. The alignment of DNA sequencing and LC–MS/MS data from both the CA tissues and CA-derived cell lines and with published data from other CRC proteogenomic studies suggests that patient-derived cell lines are a useful in vitro model for CA tumours, although they are not a complete reflection of the complex situation within CA tissues. The key differences between the two sample types included the global physiological changes such as to muscle structure and drug metabolism that were only seen in the tissue samples, and an increase in IFN-g and ferroptosis-related proteins in HGCA-derived cell lines. This study has highlighted a range of potential CRC protein biomarkers and drug targets including novel markers such as ferroptosis-related proteins ACSL4, TFRC and GCLM, membrane anchor protein ANK2, RNA exosome complex components EXOSC1 and EXOSC6, and Wnt effector AMER3. Furthermore, it has validated other CA-related proteins recently reported in the literature, including renin-angiotensin system component ACE2, membrane protein CNN1, and calprotectin components S100A8 and S100A9.Additional file 1. Patient demographics, pathology and biochemical characteristics.Additional file 2. Representative images of FFPE NC and CA tissues. (A) Normal colon, (B) LGCA tumour, (C) HGCA tumour. IHC staining for c-MYC was performed. Original magnification: 200x.Additional file 3. Mutations to CA-related genes in FFPE CA tissues and CA-derived primary cell lines.Additional file 4. Summary of TML assay results for CA tissues and CA-derived primary cell lines.Additional file 5. Lists of all proteins identified in NC and CA tissues and proteins with significantly differential abundance between tissue samples. Legend is available on Sheet 1. Abbreviations: LG = low-grade colon adenocarcinoma, HG = high-grade colon adenocarcinoma, NC = normal colon.Additional file 6. Lists of all proteins identified in CA tissue-derived primary cell lines and proteins with significantly differential abundance in HGCA cell lines relative to LGCA cell lines. Legend is available on Sheet 1. Abbreviations: LG = low-grade colon adenocarcinoma, HG = high-grade colon adenocarcinoma, NC = normal colon.Additional file 7. List of proteins found in both the tissue samples and the primary cell lines. Abbreviations: LG = low-grade colon adenocarcinoma, HG = high-grade colon adenocarcinoma, NC = normal colon.Additional file 8. Comparison of proteins identified in biological replicates for each condition. Abbreviations: LG = low-grade colon adenocarcinoma, HG = high-grade colon adenocarcinoma, NC = normal colon, Cells = Cell lines, T = Tumour tissue. The numbers in the graph titles denote the numbering of patients, with total number of proteins identified in each sample listed in brackets.Additional file 9. Analysis of proteins with significantly differential expression in LGCA tissues compared to NC tissues. A, Proteins with significantly increased abundance with a moderate confidence level (0.4), with GO terms or KEGG or Reactome pathways of interest coloured as follows: Red – sterol biosynthesis; Blue – cholesterol biosynthesis; Green – exosome (rnase complex); Yellow – preribosome. B, Proteins with significantly decreased abundance with a moderate confidence level (0.4), with GO terms or KEGG or Reactome pathways of interest coloured as follows: Red – regulation of cytoskeleton organization; Blue – cellular component assembly involved in morphogenesis; Light Green – muscle system process; Yellow – caveolar macromolecular signalling complex; Pink – cytoskeleton organization; Dark Green – myofibril assembly; Teal – actin-mediated cell contraction; Orange – plasma membrane organization; Purple – actomyosin structure organization; Brown – cellular component morphogenesis.Additional file 10. Analysis of proteins with significantly differential expression in HGCA tissues compared to LGCA tissues. A, Proteins with significantly increased abundance with a medium confidence level (0.4), with GO terms or KEGG or Reactome pathways of interest coloured as follows: Red – detoxification; Blue – cellular zinc ion homeostasis; Light Green – regulation of growth; Yellow – immune response; Pink – immune system process; Teal – neutrophil degranulation; Orange – positive regulation of cell growth; Purple – leukocyte mediated immunity; Brown – myeloid leukocyte activation. B, Proteins with significantly decreased abundance with a medium confidence level (0.4), with GO terms or KEGG or Reactome pathways of interest coloured as follows: Red – nitrogen metabolism; Blue – tyrosine metabolism; Yellow – drug metabolism cytochrome P450.Additional file 11. Analysis of proteins with significantly differential expression in HGCA cell lines compared to LGCA cell lines. A, Proteins with significantly increased abundance with a medium confidence level (0.4), with GO terms or KEGG or Reactome pathways of interest coloured as follows: Red – IFN-g-mediated signalling pathway; Blue – ferroptosis; Yellow – growth plate cartilage morphogenesis; Light Green – negative regulation of leukocyte mediated immunity; Pink – response to IFN-g; Teal – regulation of i-kappab kinase/nf-kappab signaling; Orange – cellular response to chemical stress; Dark Green – cytokine-mediated signaling pathway. B, Proteins with significantly decreased abundance with a medium confidence level (0.4), with GO terms or KEGG or Reactome pathways of interest coloured as follows: Red – MHC class I protein complex; Blue – filopodium membrane; Green – dystrophin-associated glycoprotein complex; Yellow – cell adhesion; Pink – cell junction; Orange – plasma membrane protein complex.Additional file 12. Western blotting for S100A9 protein extracted from CA tissue-derived primary cell lines. Fluorescent signals for S100A9  and the loading control α-tubulin . Means and standard deviations of normalised signal densities of S100A9 (B) against their corresponding α-tubulin bands. Comparison of abundance ratios for HGCA / LGCA as detected by LC–MS/MS and western blotting (WB) for S100A9. Tonsil tissue was used as a positive control. Abbreviations: LG = low-grade colon adenocarcinoma, HG = high-grade colon adenocarcinoma.


Differentially transcription factors (DETFs) were identified from differentially expressed genes (DEGs) in GSE62232 and transcription factors. Then, they were analyzed by regulatory networks, prognostic risk model, and overall survival analyses to identify the key DETF. Combined with the regulatory networks and binding site analysis, the target mRNA of key DETF was determined, and its prognostic value in HCC was evaluated by survival, clinical characteristics analyses, and experiments. Finally, the expressions and functions of the key DETF on the DEmRNAs were investigated in HCC cells. ASCL1 was identified as the key DETF, and SLC6A13 was predicted to be its target mRNA with the common binding site of CCAGCAACTGGCC, both downregulated in HCC. In survival analysis, high SLC6A13 was related to better HCC prognosis, and SLC6A13 was differentially expressed in HCC patients with clinical characteristics. Furthermore, cell experiments showed the mRNA expressions of ASCL1 and SLC6A13 were both reduced in HCC, and their overexpressions suppressed the growth, invasion, and migration of HCC cells. Besides, over-ASCL1 could upregulate SLC6A13 expression in HCC cells.  Through multiple bioinformatics analyses, ASCL1 and SLC6A13, and the key transcription factor ASCL1 suppresses HCC progression by targeting SLC6A13 mRNA. They are both potential treatment targets and prognostic biomarkers for HCC patients, which provides new clues for HCC research. This study identifies two suppressor genes in HCC progression,  Hepatocellular carcinoma (HCC) usually occurs in the liver, including primary and secondary liver cancer . Among tDTL, CDK1, CCNB1, and others in HCC, which might be related to its pathogenesis [Currently, researchers often use microarray technology to explore potential biomarkers of diseases to find better treatment targets . Zhou etogenesis . Throughogenesis . HoweverTCF4, RUNX1, HINFP, KDM2B, MAF, and JUN, are potential drivers of various tumors, and they regulate biological activities during tumorigenesis by targeting downstream target genes [FOX family can induce the pathogenesis of HCC by activating or inhibiting the expression of various tumor-related molecules [Transcription factors (TFs), such as et genes , 12. Curolecules . By bindolecules . AccordiAlthough studies in recent years have revealed potential targets that affect the occurrence and development of HCC, it is necessary to further analyze the potential key mechanisms affecting the prognosis and survival of HCC. Herein, we plan to combine TFs and microarray data to study the underlying mechanism and potential genes with clinical values in HCC, which further improves the clinical treatment and the prognostic effect for patients.P < 0.01, fold change (FC) > 2 as the standard for upregulation and FC < 0.5 for downregulation. The final results were displayed through the volcano maps. After that, based on the cluster profiler package of the R software, the enrichment of the upregulated and downregulated DEGs in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was analyzed, respectively. Under the premise of the threshold P < 0.05, the top 15 enrichment items were displayed.The GSE62232 microarray dataset was from the GEO database. The dataset had 10 nontumor liver tissues (control group) and 81 HCC tissues (case group), which were used as the basis for follow-up research. We screened the differentially expressed genes (DEGs) in 91 samples through the limma package of the R software, under the premise of TFs are able to connect with specific nucleotide sequences in an upstream gene as proteins, and these proteins can regulate the transcription of its downstream genes. This time, we determined the overlapping genes of DEGs and TFs as DETFs in GSE62232 and identified the potential mechanism in HCC. Then, the coexpressed networks for these DETFs were constructed.λ). 370 HCC tumor samples from The Cancer Genome Atlas (TCGA) database were evaluated by risk score and divided into 185 high-risk and 185 low-risk groups. The survival status in each sample and the expression levels of DETFs were also demonstrated. Then, the survival difference between different groups was compared based on the log-rank test Kaplan-Meier (KM) survival analysis; the hazard ratio (HR) was calculated. Next, the receiver operating characteristic (ROC) analysis was performed to judge the accuracy of the prediction model. Among them, the larger the Area Under Curve (AUC) value, the smaller the log-rank P value, indicating better prediction result.To investigate the impact of key TFs on the prognosis of HCC tumor samples, we constructed a prognostic model through LASSO regression to draw the relationship between partial likelihood deviation and log, Relapsed-Free Survival (RFS), and Disease-Specific Survival (DSS) and computed the relevant AUC values through ROC curve prediction.To study the relation between SLC6A13 in patients with different clinical parameters, including T, N, M, and G stages, histological subtypes, and TP53 mutation status.The normal and tumor tissues of HCC were downloaded from TCGA database, and Kruskal-Wallis one-way ANOVA was applied to analyze the levels of μ/ml of penicillin and 100 μg/ml of streptomycin (Gibco) were added to the medium and maintained in an environment containing 5% CO2 and 37°C. Subsequently, vectors for overexpressing ASCL1 and SLC6A13 were obtained from Gene-Pharma Co., Ltd. , with overnormal cells (NC) as a control. Lipofectamine 2000 was used to transfect over-ASCL1 and over-SLC6A13 into HCC cells.Human liver normal cells (L-02) and 3 HCC cell lines  were purchased from Shanghai Institutes for Biological Science, China, and then placed in Dulbecco's Modified Eagle Medium (DMEM) medium containing 10% fetal bovine serum (FBS). Next, 100 ASCL1 and SLC6A13 were detected by 2ΔΔCt–.Total RNA was extracted from cells based on Trizol reagent, followed by reverse transcription of RNA into complementary DNA (cDNA) using PrimeScript™ RT Master Mix . qRT-PCR was conducted by FastStart Universal SYBR-Green Master Mix, and the relative mRNA and protein levels of μl of Cell Counting Kit-8 (CCK-8) solution was dropped into each well plate and cultured at 37°C in a 5% CO2 environment for a period of time . After that, the optical density (OD) values of cells at 450 nm were detected by a microplate reader at different time periods.In the cell proliferation experiment, the transfected cells were first added to a 96-well plate, and 10 A certain amount of culture medium was added to the upper and lower chambers of the Transwell, the transfected cells were placed in the upper chamber, and the lower chamber was placed in RPMI-1640 medium containing 10% FBS. For cell migration experiments, no Matrigel was coated to the bottom, while invasion experiments were performed with Matrigel . The upper excess cells were removed by cotton swab, and the left cells were fixed with methanol for 10 minutes and stained with DAPI. Finally, the cell migration and invasion in different fields were observed by fluorescence microscopy.t-test. The acquired findings were statistically significant when P < 0.05 was used.All data was analyzed using SPSS v.16.0 software, with independent experiments presented as mean standard deviation (SD) and differences between groups examined using Student's DACH1, FOSB, FOS, ASCL1, EBF1, GTF2H2, and GTF2I  was lower than that of the low-risk group (GTF2H2 (log-rank P = 0.011) and DACH1 (log-rank P = 0.13) had a poorer OS probability, while those with high expressions of FOSB (log-rank P = 0.0024), ASCL1 (log-rank P = 0.0029), EBF1 (log-rank P = 0.048), and FOS (log-rank P = 0.23) had a better probability of OS. Thus, we concluded that the key DEDTF was ASCL1.According to the results in Figures ifferent . In the sk group . The ressk group . Based osk group . It was ASCL1 was downregulated in HCC tumors , the expression of EBF1 was inhibited in CCA, which was associated with long-term oxidative stress [GTF2H2 inhibits the proliferation of HCC cells and promotes its apoptosis, which is a potential inhibitor of hepatocarcinogenesis [GTF2H2 can also affect the growth of hepatoma cells Hep3B by mediating the AKT molecular signaling pathway [ASCL1 is underexpressed in small-cell lung cancer and ASCL1 deletion suppresses the neural crest stem cell-like state in SOX9+ small cell lung cancer [ASCL1 can combine with NKX2-1 and PROX1 complex to regulate NOTCH signaling, cell cycle, and other pathways involved in subtype-specific genes in small cell lung cancer [ASCL1 was identified as the key DETF related to HCC.Previously, these DETFs have been studied by researchers in the progression of HCC. of DACH1 , therebyr in HCC . EBF1 ace stress . Other sogenesis  and GTF2 pathway . The stug cancer . In addig cancer . The genASCL1, we speculated SLC6A13 as a key target gene by the regulatory network of ASCL1, which is one of the 6 members of the solute carrier family and involved in amino acid trans-plasma membrane import and monocarboxylic acid transport. Long et al. discovered novel biomarkers from blood during Alzheimer's disease, including SLC6A13, ECH1, and NHLRC2 [ASCL1 and SLC6A13 as CCAGCAACTGGCC. Subsequently, ASCL1 and SLC6A13 were found to be positively related by public database and functional experiments. These findings indicate that which SLC6A13 is a mRNA target of ASCL1 in HCC. In the survival and ROC analysis on SLC6A13, the high expression of SLC6A13 was associated with a better survival rate in HCC patients and had the certain predictive ability for the prognosis of HCC patients. Besides, we verified the expressions of SLC6A13 in HCC samples with different clinical parameters based on public databases and found that the expression of SLC6A13 gradually decreased with the HCC progression. All these results demonstrate the clinical application of SLC6A13 in HCC prognosis in the future.According to the regulatory network and previous studies of d NHLRC2 . Based oASCL1 and SLC6A13 had low expressions in HCC groups, and we then evaluated the effect of the key targets ASCL1 and SLC6A13 on the progression of HCC. The corresponding results showed that the upregulated expressions of ASCL1 and SLC6A13 in HCC cells could significantly inhibit the proliferation, migration, and invasion of HCC cells. In addition, over-ASCL1 could upregulate the expression of SLC6A13 in HCC cells. From the above research conclusions, we can conclude ASCL1 and SLC6A13 are the key tumor suppressor factors of HCC, and they might be the treatment targets in the progression of HCC.In cell experiments, both of ASCL1, and its downstream target SLC6A13 mRNA were identified, both lowly expressed in HCC tumor tissues and inhibiting the development of HCC in vitro. ASCL1 could suppress the progression of HCC by upregulating SLC6A13, and they are also promising treatment targets and prognostic biomarkers in HCC progression. However, there are still some limitations. For example, one of the limitations of the current study is that all the results are preliminary, and the further mechanism of the hub gene should be explored deeply. The further research is needed to be done in the future.In conclusion, we performed the enrichment analysis of DEGs on the GSE32232 dataset based on bioinformatics methods and obtained 6 DETF with predictive ability in HCC prognosis. Then, the key DETF,


Diplosphaera epiphytica, isolated from a lichen, and Edaphochlorella mirabilis, isolated from Tundra soil, assessed via growth and photosynthetic performance parameters. Metabolite profiling was conducted by GC–MS. A meta-analysis together with data from a terrestrial and an aquatic Chlorella vulgaris strain reflected elements of phylogenetic relationship, lifestyle, and relative desiccation tolerance of the four algal strains. For example, compatible solutes associated with desiccation tolerance were up-accumulated in D. epiphytica, but also sugars and sugar alcohols typically produced by lichen photobionts. The aquatic C. vulgaris, the most desiccation-sensitive strain, showed the greatest variation in metabolite accumulation after desiccation and rehydration, whereas the most desiccation-tolerant strain, D. epiphytica, showed the least, suggesting that it has a more efficient constitutive protection from desiccation and/or that desiccation disturbed the metabolic steady-state less than in the other three strains. The authors hope that this study will stimulate more research into desiccation tolerance mechanisms in these under-investigated microorganisms.Trebouxiophyceae are microalgae occupying even extreme environments such as polar regions or deserts, terrestrial or aquatic, and can occur free-living or as lichen photobionts. Yet, it is poorly understood how environmental factors shape their metabolism. Here, we report on responses to light and temperature, and metabolic adjustments to desiccation in  Chlorella vulgaris strains, one aquatic and one terrestrial, were investigated. In this study, the ecophysiological performance under different light and temperature conditions, and their ability to recover from desiccation of two phylogenetically well-characterized Trebouxiophycean green algae in the Prasiola-clade, Edaphochlorella mirabilis (SAG 38.88) isolated from Tundra soil, and Diplopshaera epiphytica (SAG 11.88) isolated from the lichen Pseudocyphellariacarpoloma [D. epiphtica and D. chodatii were recently reported [D. epiphtica, sorbitol and sucrose contents were used as chemotaxonomic markers [Diplopshaera spp. for biotechnological applications was investigated [D. chodatii, were used to study dispersal modes of the semi-aquatic lichen, Dermatocarpon luridum [Edaphochlorella spp., e.g., ecophysiological studies were conducted with arctic strains [Diplopshpaera and Edaphochlorella species exist, but hardly any information is available on changes in metabolism in response to environmental stress factors.Chlorophyte microalgae are receiving increasing attention due to their contribution to carbon and nitrogen cycling in soil crusts ,2 and asarpoloma ,6,7,8, warpoloma ,10,11 wiarpoloma  either farpoloma ,14,15. Ereported ,17,18. I markers , and thestigated . Further luridum . Compara strains ,22. In sApatococcus spp.) or cell colonies  [Klebsormidium spp.) may contribute to a protective matrix that retains water [Compared to aquatic species, aero-terrestrial algae are exposed to greater variations in temperature, higher irradiation, and a desiccating atmosphere. Mechanisms that protect aero-terrestrial chlorophytes from these environmental factors include photoprotectants and osmoprotectants ,24, and/xa spp.) . In addins water , whereassensu stricto, as the capability to survive drying at relative humidity below 65%, corresponding to a drop in absolute water contents to or below 0.1 g H2O g–1 dry mass and a water potential of ≤−100 MPa [Trebouxia sp. and Coccomyxa solorina-saccatae, the significance of polyols  for survival of desiccation was highlighted [Desiccation tolerance can be defined as the ability to revive from the air-dried state or, −100 MPa ,28,29). hlighted . Howeverhlighted ,32, and hlighted ,34,35. Ahlighted ,37).Tetradesmus spp., desiccation tolerance appears to be a common trait in temperate and desert soil crusts, but is missing in closely related aquatic species [Diploshaera chodatii was described as desiccation-tolerant, capable of recovering from desiccation at 10% relative humidity [Moreover, it remains an enigma why some phylogenetically closely related green algae vary strongly in their desiccation tolerance . For exa species . Differe species ,25,39. Dhumidity .C. vulgaris strains, one of which was desiccation-sensitive and the other capable of surviving desiccation at 84% relative humidity, in comparison with D. epiphytica and E. mirabilis. The central research aims were, first, to study the ecophysiological performance and primary metabolism of D. epiphytica and E. mirabilis in response to desiccation and rehydration; and second, to conduct a meta-analysis of the metabolite data gained together with those from both C. vulgaris strains [In the present paper, we made use of previously published data on the ecophysiology and the effects of desiccation and rehydration on differential metabolite accumulation in the above-mentioned Edaphochlorella mirabilis (SAG 38.88), Trebouxiophyceae incertae sedis, and Diplosphaera epiphytica, Stichococcaceae , both in the Prasiola clade [n = 20 cells) in D. epiphytica and E. mirabilis, respectively.The algal strains la clade ,8 were o−2 s−1 at 20 °C)/dark (8 h at 15 °C) cycle. Log-phase cultures were used in all experiments.Algae were cultivated in liquid Bolds Basal Medium plus vitamins (BBM + V)  under a D. epiphytica and E. mirabilis under different experimental light and temperature conditions to previously published data [−2 s−1, using the increase in chlorophyll a fluorescence over time as an indicator of biomass accumulation as previously described [To link the ecophysiological performance of hed data , the effescribed .a, analysed, and calculated as previously described [Photosynthetic oxygen production rates at temperatures from 5 °C to 50 °C were measured with a Fibox 3 oxygen optode  after , as prevescribed .−1, determined after freeze-drying  of algae, were wetted with 20 µL of BBM + V before placing them in a desiccation chamber above 100 mL of saturated KCl solution, resulting in a final relative air humidity (RH) of 84% inside the chamber at ambient temperature (22 ± 1 °C) and 20 µmol photons m−2 s−1. Cultures were exposed to 84% RH for 180 min, and then rehydrated by pipetting 20 µL of liquid BBM + V medium onto each filter and replacing the KCl solution with A. dest., resulting in 95% RH within the chamber.Algae were subjected to a desiccation and rehydration treatment exactly as previously described . BrieflyD. epiphytica and E. mirabilis, respectively; n = 5 filters per interval).To noninvasively monitor the algae’s response to desiccation and to assess their ability to recover from desiccation, the effective quantum yield Y(II) was measured using a pulse-amplitude-modulated (PAM) fluorimeter . Data were recorded at intervals during desiccation until no effective quantum yield Y(II) was detected, and during approximately 17 h of rehydration (1042 and 1044 min for n = 4 filters). For this, algae were 30 min dark-adapted on filters placed on agar plates and exposed to 16 PFDs from 0 to 1660 μmol photons m−2 s−1 (for 30 s each) as previously described [In addition, electron transport rates (ETRs) were measured before desiccation (controls) and at the end of the rehydration experiment (escribed .n = 3 filters each) were frozen in liquid nitrogen and freeze-dried. Freeze-dried material was ground with glass beads using a laboratory mill  at 30 Hz for 3 min before metabolite extraction.Algal cultures on filters prior to desiccation (controls) and at the end of the rehydration experiment . Metabolites were separated on a 30 m Rxi-5Sil MS column with a 10 m Integra-Guard pre-column (Restek) using a Trace 1300 gas chromatograph in splitless mode and detected by a TSQ8000 triple quadrupole mass spectrometer . A mix of alkanes was injected in the middle of the queue for external retention index calibration. Compound spectra were extracted from the raw data files using the “Automated Mass-spectral Deconvolution and Identification System” (AMDIS) and compared against a custom-built mass spectral library and commercial or publicly available databases, including the NIST, Golm, and Fiehn databases [Metabolite profiling was carried out using the slightly modified method of  as previribed in . Brieflyatabases ,46. PeakPrasiola calophylla for quantification [In addition, in untreated algae, proline contents were quantified spectrophotometrically , and sorfication .p < 0.05. Metabolites were reported as differentially accumulated between the strains when the false discovery rate , nonparametric tests  were applied instead. For each strain, metabolites were reported as differentially accumulated after desiccation and rehydration when the FDR-corrected Welch T-test p value was below 0.05.Statistical evaluation of the data was performed with R  using the ellipse, lsmeans , and ggpate (FDR )-correctD. epiphytica showed consistently lower growth rates than E. mirabilis. In response to increasing irradiation, both species showed maximum growth rates between 15 and 30 μmol photons m−2 s−1, and growth rates declined at higher PFDs. At 105 μmol photons m−2 s−1, growth rates were reduced by two-thirds compared to maximum values in D. epiphytica, but only by about 40% of maximum values in E. mirabilis (Growth rates were affected by both photon fluence density (PFD) A and temirabilis A. In resirabilis B.D. epiphytica did not change from 5 to 15 °C, and then increased significantly, with a plateau between 20 °C and 35 °C, before ceasing at 40 °C , accounting for 33% of the total variance. The two C. vulgaris strains were further separated from E. mirabilis separated along PC 2, accounting for 29% of the variance  and linoleic acid (C 18:2), were also differentially accumulated.Out of the four strains, D. epiphytica than in E. mirabilis , which are “functional liquid media” capable of dissolving chemicals of low water solubility [D. epiphytica support the finding that this alga is the most desiccation-tolerant of the four strains investigated, and produces sugars and sugar alcohols that are favoured carbon sources for lichenized fungi [PCA clearly separated profiles . Compare proline . Prolineectively , in agretrations ,17,18. Strations ,32, but trations ,32,58. Dariaceae . Sugars ariaceae ,60,61. Fariaceae ,63, and ariaceae . Comparelubility . This coed fungi ,67, makiEdaphochlorella mirabilis had low sucrose contents compared to the other three strains , and tolerance of osmotic and/or desiccation stress.Aigner et al.  previousbacteria . In highbacteria . The polbacteria ,84, was  species , includitabolism , comparemulation . HoweverSporobolus stapfianus and S. pyramidalis, showed that S. stapfianus is metabolically primed for desiccation by up-accumulating osmolytes and nitrogen source compounds, and down-accumulating compounds related to energy metabolism and growth, compared to S. pyramidalis [Selaginella lepidophylla retained higher amounts of sucrose, mono- and polysaccharides, and sugar alcohols such as sorbitol and xylitol than the desiccation-sensitive Selaginella moellendorffii [D. epiphytica, had the best capability of either maintaining or restoring its metabolic state upon rehydration, whereas the most desiccation-sensitive alga, the aquatic C. vulgaris strain, appeared to be out of equilibrium, assessed by its greater variation in metabolite accumulation after the desiccation-rehydration treatment . For examidalis . Furtherndorffii . Our prereatment . TherefoE. mirabilis and the terrestrial C. vulgaris strain, up-accumulated in D. epiphytica, and down-accumulated in the aquatic C. vulgaris (C. vulgaris strain also up-accumulated compatible solutes such as putrescine and xylitol, and trehalose-6-phosphate, which could reflect that it had received a signal to up-regulate mechanisms that protect from desiccation-induced injury. It will be interesting to conduct future experiments to see if repeated desiccation-rehydration cycles can induce hardening in the aquatic C. vulgaris strain. Furthermore, the two strains with intermediate desiccation tolerance, the terrestrial C. vulgaris strain and E. mirabilis, showed very similar patterns of differential accumulation, with few exceptions, including maltose. This disaccharide was down-accumulated in E. mirabilis and up-accumulated in the terrestrial C. vulgaris strain after treatment, indicative of starch degradation, similar to that reported for algal cells in the top layer of a Zygnema mat exposed to desiccation and irradiation, in which an increase in maltose was shown by metabolite profiling and starch degradation by transmission electron microscopy [E. mirabilis and the aquatic C. vulgaris strain and down-accumulated in the terrestrial C. vulgaris strain after desiccation and rehydration. Opposite accumulation patterns were also reported for some metabolites in the above-mentioned desiccation-tolerant and the desiccation-sensitive pairs of Sporobolus and Selaginella such as asparagine, aspartate, arginine, and glutamate [Of the individual differentially accumulated metabolites, sucrose was unaffected in vulgaris , suggestcroscopy . Howeverlutamate ,89.D. epiphytica, the abundance of other metabolites also reflects its suitability for symbiosis with a lichenized fungus [D. epiphytica, and the largest number in the least desiccation-tolerant strain, the aquatic C. vulgaris. This suggests that D. epiphytica had the best capability of either maintaining its primary metabolite composition required for metabolism prior to the treatment and/or re-adjusting its metabolism upon rehydration, in agreement with the full recovery of YII values of nondesiccated controls. By contrast, the metabolism of the aquatic C. vulgaris strain appeared to be more out of equilibrium, in agreement with the poor recovery of YII values of nondesiccated controls. Interestingly, the differential metabolite accumulation after the desiccation-rehydration experiment of the terrestrial C. vulgaris strain and E. mirabilis was in the middle of the two extremes, irrespective of their phylogenetic position in the Chlorellaceae and the Prasiola clade, respectively. Therefore, it appears that, at least for the four algal strains investigated here, the magnitude of differential metabolite accumulation after the desiccation-rehydration treatment reflects their degree of relative desiccation tolerance.The metabolite composition of the four algal strains investigated prior to the desiccation-rehydration experiment partly reflects their phylogenetic position, for example, sterol composition and prasiolin, whereas in d fungus , especiad fungus ,32. Furtd fungus ,30,31,32