Insertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection.We have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines  and reciprocally. Next, we designed an Affymetrix® Axiom® array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35 bp to 129kbp. After Affymetrix® quality control, we successfully genotyped 86,648 polymorphic InDels  on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~ 3%), high call rate (~ 98%), and high reproducibility (> 95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels . This “proof of concept” tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50 K SNP arrays.We efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix® Axiom® array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale. Arabidopsis thaliana [In the past decade, there has been growing evidence that structural variations (SVs) are pervasive within plant genomes –9. Inserthaliana , potato thaliana , pigeon thaliana , and sorthaliana . These rthaliana , 19–25 .In maize, BAC sequence comparison first revealed that gene and transposable element content greatly vary between inbred lines , 27. WhoMethods based on SNP array experiments have been developed to detect CNVs and were shown to be more affordable and with higher throughput than CGH arrays –33 . DidWith the emergence of massive parallel sequencing, new methods have been developed to detect structural variations based on the alignment of resequencing reads onto a high quality reference genome sequence. Among these, three have been mainly used : (i) theThe “assembly” (AS) method is able to detect all types of SVs of any size, but is also the most cost and computation-intensive. It is the only method able to detect large insertions with precise breakpoint definition. However, the assembly of large and complex genomes such as maize remains very expensive and computationally intensive, despite recent progress in this area –21. TherTo design a comprehensive InDel genotyping array, we first discovered a set of InDels which would be representative of the maize temperate germplasm. We already had access to sequence data for the European flint line F2, and we benefited from a first set of 42,330 F2-specific sequences, larger than 150pb and totaling 16Mbp. This dataset was derived from the de novo assembly of an F2 paired-end that failed (at least for one read of the pair) to align onto the B73 AGPv2 sequence, and which were totally devoid of coverage by B73 reads . We did not use the “no map” approach for InDel discovery on PH207 and C103, because this approach did not give access to breakpoint resolution, did not allow the discovery of InDels without specific sequence, and was almost redundant with the assembly approach.We first aligned F2, PH207, and C103 sequences against the B73 reference genome sequence in order to detect deletions. Here, the term “deletion” does not reflect any underlying biological process of DNA excision but refers to a sequence of at least 100 bp present in the B73 genome at one locus and absent in another line at the same locus. Deletions were detected for the three lines simultaneously using the “genotyping” option of PInDel , generatNext, we generated a draft genome assembly for each of these lines, which was used as a template for alignment of B73 reads to detect insertions relative to the B73 reference genome , comprising 52,175 deletions and 89,150 insertions. These regions were then used for the design of genotyping probes.Large InDels can be efficiently genotyped with a SNP array using a combination of two types of probes: (i) “external” probes, which target breakpoints using the two flanking sequences of a given InDel (BP probes), and (ii) “internal” probes, which target presence/absence regions (PARs) within the internal sequence of InDels on polymorphic (OTV probes) or monomorphic sites (MONO probes). We define PARs as small portions of DNA sequence of at least 35 bp that were observed present or absent at the genome level, when comparing two individuals. They are thus suitable for the design of presence/absence genotyping probes. Ideally, each InDel should be called by two BP probes on either side and by multiple internal probes, regularly distributed along the internal sequence of the InDel Fig. a. Howevenot possible (18%), not recommended (33%), neutral (15%) and recommended (35%) by this automated pipeline (see Methods for details), leaving 33,430 InDels (51%) that could be targeted by at least one recommended probe.BP probes should behave like classical SNP probes where one allele corresponds to the presence and the other to the absence of the InDel. They are useful to explore the conservation of the localization of large insertion/deletion events across multiple individuals, even when no internal probe can be designed due to the absence of PARs. Among the 141,325 selected variants, 86,406 InDels  had breakpoints defined at base-pair resolution and were suitable for BP probe design. Four different breakpoint types were identified according to the presence of micro-homology and/or shorter non homologous sequence  in placeInternal probes, which should behave like “off-target” variants  where thnot possible (0.05%), not recommended (71%), neutral (14%) and recommended (16%), leaving 17,589 InDels (82%) which could be targeted by at least one recommended probe.For the design of OTV probes, we benefited from the availability of SNPs which had been previously identified from the alignment of resequencing data from a core collection of 25 temperate maize inbred lines against the B73-F2 maize pan-genome from . As a corecommended and allowed to target 62,875 InDels (79%).For the design of BP and OTV probes we could rely on Affymetrix® design pipeline to identify probes localized in PARs and thus suitable for the Affymetrix® Axiom® technology. For the design of MONO probes, we first had to identify such PARs within 141,325 InDels cumulating 133Mbp of sequence. We used sequence masking methods to exclude repeats based on similarity to known maize repeats or on occurrence of 17-mers found within the sequencing datasets we had for B73, F2, PH207, and C103 (see Methods). By doing so, we identified 122,972 PARs, representing a cumulated size of 27Mbp, corresponding to 20.3% of the initial size and allowing the possibility to design MONO probes for 79,987 InDels (56.5%). These PAR sequences were successfully used for the design of 25,735,797 MONO probes, among which 59% were scored as With this combined approach, we designed a total of 26,715,361 probes targeting 117,756 InDels, which represent a cumulated length of 250 Mbp including 27 Mbp of PARs  can only be targeted with either internal or external probes, but not both , and only one hit (for deletions), against the B73 reference genome sequence. We then considered their density with the objective to maximize the number of InDels that could be surveyed, as well as to have an even distribution of probes along targeted InDel sequences (see Methods). We then performed a second selection among not recommended OTV and MONO probes for 4,541 InDels that were still not targeted. After filtering some duplicated probes, we built a final array design containing 662,772 probes targeting 105,927 InDels that represent a cumulated length of 232 Mbp, including 25.9 Mbp of PARs.We used the Affymetrix® recommendations to select the 700,000 probes to be included in the final array, plus some other criteria depending on the probe type. Nevertheless, because of their added value, we decided to keep all BP probes as long as they had less than 3 hits on the B73 reference genome sequence. This first selection consumed 84,994 probes targeting 53,456 InDels, among which 70% could only be targeted by BP probes. Concerning OTV and MONO probes, we first selected The final array design allows genotyping InDels with various sizes, ranging from 37 bp to 129.7 kbp, with a median of 501 bp , 1311 inside a pseudo-gene and 2212 inside a transposable element. InDels and probe density varied across each chromosome  with the observed clustering of inbred lines based on fluorescence intensity and contrast of 445 inbred lines genotyped with the array. For BP probes, we expected at least two clusters corresponding to the individuals homozygous either for presence (“AA” or “BB”) or absence (“OO”). A third cluster could be observed when individuals were heterozygous individuals for presence/absence (“OA” or “OB” hemizygous) Fig. c. For OTWe observed also some unexpected clustering. For 57% of BP probes, we observed an additional off-target cluster  when the sequence was present suggesting the presence of single nucleotide polymorphisms at this position. Among these, we were able to distinguish two types of clustering Table . 4.7% ofFor 18% of OTV  with those from sequencing (GBS: Genotyping by Sequencing) for the 4 lines used for the discovery of InDels . Respectively, 97, 92, and 88% of the BP, OTV, and MONO probes had a genotyping result consistent with results obtained from BLAST alignments against our three draft genome assemblies and the B73 reference genome. We observed a strong asymmetry for concordance rates for internal probes (OTV and MONO) depending on whether the genotype has been called by sequencing as present or absent . This could be partially explained by the higher proportion of GBS present calls in F2 as compared to the three other lines since GBS present calls are more consistent with GBA than GBS absent calls. The median consistency rate of probes within InDels remained relatively high and stable, around 90%, independently of the number of probes per InDel  and 0 (absence) indicated that all probes displayed consistent genotyping for the corresponding inbred line  allelic frequency different from 0 or 1 (FreqDiff01), according to the number of probe interrogating that InDel Fig. . For InDi.e more complex rearrangement), rather than being genotyping errors. Additionally, 35% of InDels called by BP had their FW and REV probes classified differently (e.g. one as BP and the other as OTV). Altogether, these results suggest that some calling inconsistencies between probes within InDels could come from polymorphisms in the flanking sequence while some other could be due to local rearrangements in the genotyped lines as compared to the lines used for InDels discovery.Combining genotyping from multiple probes within InDels greatly improved reliability of InDel genotyping, since it allowed (i) to correct the individual genotyping errors due to polymorphisms within probe sequences, (ii) to reduce the missing data rate due to bad clustering or probes polymorphisms, and (iii) to remove probes displaying highly-divergent genotypes compared to other probes for the same InDel, due, for example, to a bad design of the probes. In order to evaluate the combining of genotypes of several probes on the accuracy of InDel genotyping, we simulated global genotyping error rates for InDels by assigning to each inbred line the most frequent allele, based on the average frequency over all probes from an InDel, with various genotyping error rates , except those for a couple of lines closely related to B73 and F2  the ‘accuracy’ of detecting InDels using whole genome assembly, with the detection of 89,150 insertions and 52,175 deletions from the comparison of three newly sequenced and assembled maize inbred line  genomes and the public maize B73 AGPv2 reference genome, (ii) and the ‘high-throughput’ genotyping utility provided by SNP arrays. This approach allowed us to genotype, for the first time, thousands of insertion/deletion variants, including PAVs, on a few hundred maize individuals. Genotyping cost per individual using the InDel array was at least 10–20 fold cheaper than any approach based on sequencing for a species with a genome as complex as maize, at a similar level of reliability . This genotyping cost did not include bioinformatics analysis. Calling SVs from a pan-genome of a species with a large and complex genome, such as maize, was time-consuming and required bioinformatics skills and large informatics facilities, which are costly and not available in all laboratories. In the contrary, the array could be analyzed rapidly on a laptop using a pipeline already implemented for analyzing SNPs and the Hom2OTV R script developed for analyzing MONO probes. Additionally, the array provided a wet-lab validation of the InDel discovery and allowed the removal of putative genotyping errors from sequencing (particularly for PAVs), due to incomplete or bad genome assembly, as we observed in our study. In the end, the probe content of the InDel array can be largely optimized, either to reduce the size of array (and therefore the cost), or to increase the number of SVs genotyped, without losing reliability  by filtering out under-performing probes, by strongly reducing the number of probes per InDel (2–3), and by removing false positive InDels. It would also be easy to design an array combining probes targeting InDels and more classical SNPs, outside of InDel sequences.With the use of breakpoint probes for both insertions and deletions, our approach overcomes some of the limitations of previous CGH or SNP array-based studies, which were only able to call deletions if a few successive probes had lower fluorescent intensity signals –33. UnteAlthough the use of BP probes is clearly the simplest way to genotype InDels using an SNP array, breakpoints are not always available (“no map” approach discovery) or “designable” with 35 bp probes, for instance, the cases where sequences of microhomology at breakpoint site were larger than 5 bp. In order to genotype the 52,471 InDels without breakpoints and explore the genetic diversity within InDels, we also designed 577,778 internal probes both on monomorphic and polymorphic sites in PARs for both insertions and deletions. To genotype PARs in InDel sequences using SNPs, we took advantage of the already available Affymetrix® algorithms to call Off-Target Variants (OTVs), which can detect variation of fluorescent intensity signals for a single probe  the genotypes obtained by array and by sequencing were highly consistent for BP probes (97%) and in a lesser extent with OTV and MONO probes , due to the fact that the genome assembly of sequenced lines were incomplete or incorrect, resulting in high error rates for absent calls using GBS; (ii) the average probe genotyping error rate was estimated at 3% ; (iii) the InDel genotyping errors could be greatly reduced by combining the genotypes of different probes within the InDels (0.02% for 5 probes); (iv) the genotyping results were highly reproducible between DNA replicates of F1 hybrids  and between inbred lines (94.8 to 99.4%); and (v) the call rate for individuals was very high (96 to 99%) and can be increased by combining the genotypes of the probes within the InDels .Our approach is promising as a method to genotype structural variations in maize, as well as other species with complex genomes. We obtained high metrics, comparable to classical SNP arrays, based on Affymetrix® Axiom® Technologies, even though InDels are more complex to genotype. First, call rates are high and quite similar to those obtained for SNP with the 600 K SNP Affymetrix® array (98% against 98.1% in ). NevertWe identified some inconsistencies between genotyping by array (GBA) and genotyping by sequencing (GBS) obtained by aligning probes against our genomes Table . These iWe also found that 20,574 InDels were monomorphic and present across all lines, suggesting they represented false positives from regions not assembled in our draft genomes. To reduce this false positive rate, we strongly advise to not only align B73 reads onto each draft genome assembly but to also align reads from each sequenced genome on each other and against itself. This would have several benefits: (i) it would allow to discover even more and higher-quality InDels, as each putative deletion discovered in one sample could potentially benefit from supporting reads from another sample; (ii) this would simplify the identification of InDels common to more than one genotype; and (iii) it would help to identify and eliminate false positive deletions by the alignment of each sample on its own draft assembly.Nevertheless, the use of incomplete draft genomes does not explain all discrepancies between genotypes obtained by sequencing and by array. First, these discrepancies could also be due to incorrect clustering and assignment of a genotype call (array errors). This was exemplified by some MONO probes classified as SNPs, although the clustering pattern looks like a MONO cluster with a large difference of fluorescence intensity between two clusters  was slightly higher than observed by sequencing a small set of diverse lines , 65. It 1 bp was These potential clustering errors, as well as the incorrect design of some probes, can explain some inconsistent genotypes for presence/absence between probes for the same InDel. Comparison of genotyping across different probes within InDels could help to identify and remove probes displaying highly discordant genotypes, due to errors originating from poor clustering or from poor design. Interestingly, some InDels showed reproducible inconsistent genotypes for presence/absence across their probes in several inbred lines  and C103 (Lancaster). For the F2 inbred line, see [http://www.novocraft.com) (default parameters). Samtools [http://broadinstitute.github.io/picard) version 1.48. PInDel [For the deletion discovery step, F2, PH207, and C103 paired-end reads were aligned against B73 AGPv2 genome sequence using novoalign version 3.01.01  was used to mask redundant regions by similarity using an iterative approach. First, “ALLPATHs-LG assembly” F2 insertions were masked with “ABySS assembly” F2 insertions (at least 95% of identity) to generate a non-redundant set of F2 insertions. Then C103 insertions were masked with F2 insertions (at 90% of identity), PH207 insertions were masked with C103 and F2 insertions (90%), and finally F2 no map specific sequences were masked with PH207, C103, and F2 insertions (90%).The multiple references and approaches used during the InDel discovery step led to a set of InDels with various levels of redundancy. Some “intra-tool” redundancy was found . These “ambiguous” calls were systematically identified using the Bedtools suite version 2.16.1  and elimTo identify presence/absence regions (PARs) within InDel sequences suitable for the design of “off-target” probes, we used the genometools Tallymer utility  version Breakpoints could be targeted by probes Fig. a providein-silico analysis to predict their microarray performance. A p-convert value, which arises from a random forest model intended to predict the probability that the SNP will convert on the array, was determined for all probes. The model considers factors including probe sequence, binding energies, and the expected degree of non-specific binding and hybridization to multiple genomic regions. This degree of non-specific binding is estimated calculating 16-mer hit counts, which is the number of times all 16 bp sequences in the 30 bp flanking region from either side of the SNP have a matched sequence in the genome. These scores were generated both for forward and reverse probes. A probeset is recommended if p-convert> = 0.6 and there are no expected polymorphisms in the flanking region. A probeset is neutral if p-convert> = 0.4, the number of expected polymorphisms in the flanking region is less than 3, and the polymorphisms are further than 21 bp of the variant of interest. Probesets not falling into these two categories are scored as not recommended. Probesets that cannot be designed are scored as not possible.All potential probes were evaluated in an Concerning OTV and MONO probes, we applied three successive filtering steps. First, we selected only probes classified as recommended and neutral based on their scoring, with no more than one hit on the B73 reference genome for deletion probes, and no hit at all for insertion probes. After this step, 204,213 OTV probes and 18,884,827 MONO probes remained. Secondly, only probes with more than 70% in PARs were kept. An additional filtering step was implemented specifically for MONO probes to optimize probe distribution along the targeted PARs. For this step, PARs were split in 75 bp windows using windowmaker (Bedtools) and the MONO probe with the highest p-convert value was selected for each window. If there were InDels with less than 4 MONO probes selected using 75 bp windows, these probes were eliminated and a second iteration was attempted, using 50 bp windows, followed by a last iteration with 25 bp windows. This generated 616,286 probes including BP and OTV probes targeting 108,24 InDels (90% of InDel selected for design). We completed the design by rescuing 6219 OTV and 53,441 MONO probes from InDels or PARs not targeted by any probes, bringing the total number of probes selected to 675,946 to target 109,292 InDel.At the last step, duplicated probeset were removed based on their sequence by Affymetrix® during the chip design procedure, leaving 662,772 probeset  corresponding to 1,404,570 different probes to be tiled on the array.For genotyping, 480 different DNA samples were extracted from leaves following a NaBisulfite method modified from , 76. TheEach type of probe had a dedicated algorithm , except for an empirically determined, more stringent heterozygous variance filter (AB.varY.Z.cut = 2.6). Example of clusters from each classification were visualized using the Ps_Visualization function , MonoHighResolution (MHR), and OTV).Algorithms used to convert BP and OTV were similar, as BP and OTV probes behaved like classical SNPs. For initial genotype calling, a priori (generic) cluster positions were used, since no information about expected positions was available. A first analysis was performed according to Affymetrix® recommendations. Secondly, the level of inbreeding was taking into account for a posteriori cluster definition, because of the high amount of inbred lines in the panel. This parameter took values from 0 for fully heterozygous to 16 for completely homozygous samples. For OTV and BP algorithms, an inbred penalty of 4  was applied to try to re-labelled probes that fall into categories: CallRateBelowThreshold (CRBT), HomHomResolution (HHR), NoMinorHom (NMH), Other and UnexpectedHeterozygosity, after the first cluster analysis  to re-labelled probes displaying higher-than-expected levels of heterozygosity. Finally, the new function called Hom2OTV was implemented to classified probes exhibiting two homozygous clusters, with primarily an intensity difference. This function determined if the intensity difference represents one homozygous cluster (InDel presence) and one OTV cluster (InDel absence), as we expected. There are no parameters in this function. The lower intensity homozygous cluster is recalled as OTV.BP and OTV probes that exhibited only two clusters (AA or BB and OTV) should fall into the monomorphic classification and be considered as not recommended. A new MONO algorithm was developed Fig. , becauseWe compared the genotyping for 479,027 probes from the InDel array (Genotyping By Array: GBA) with the genotyping from sequencing (Genotyping By Sequencing: GBS) of 4 inbred lines used to discover the InDels: B73, F2, PH207, and C103. Genotyping by sequencing was built from the alignment of probe sequences on the reference genome B73 and the de novo assembly of 3 inbred lines  with Blast software. Sequences were considered present in lines when the probes were aligned with less than 5% of mismatch or otherwise considered absent.Genotyping consistency for B73, F2, PH207, and C103 was calculated between GBS and GBA according to genotype calls “present” or “absent”, produced by GBS Table . For thii.e the proportion of lines where the average frequency across all probes is 0 or 1. We also calculated frequency of inbred lines that have a least one probe with an inconsistent genotype (FreqDiff01), i.e the proportion of lines where the average frequency across all probes is not 0 or 1. To evaluate the effect of the probe numbers on the frequency of lines inconsistent within InDels, we analyzed the variation of frequency of lines not fully consistent (FreqDiff01) with relation to the number of probes within the InDels, by estimating median and average FreqDiff01 for each probe count  that originated from different seed sources  the clustering observed were consistent with expectation (Table We estimated two kinship matrices between 362 lines using “identity by descent” estimators (IBD) based on 57,824 InDels and on 28,143 prefixed Panzea SNPs from the Illumina 50 K  Probes recommended for genotyping, B) Probes not recommended for genotyping. Table S3. Classification by the Affymetrix® pipeline of 163,278 OTV probes based on cluster number, separation, variance, and call rate. A) Probes recommended for genotyping B) Probes not recommended probes for genotyping. Table S4. Classification by the Affymetrix® pipeline of 414,500 MONO probes, based on cluster number, separation, variance, and call rate. A) Probes recommended for genotyping B) Probes not recommended for genotyping. Table S5. Effect of probe number within InDels on average percentage of missing data, of genotypes absent and genotypes not fully concordant. Table S6. Simulation of genotyping error rates for 362 lines and 10,000 InDels called by various numbers of probes with a probe genotyping error rate ranging from 1 to 10%. Table S7. Comparison of reproducibility between 5 DNA replicates of hybrid F1 according to probes type and observed clustering. Table S8. Mendelian inheritance of 12 hybrids F1 derived from 9 different parental inbred lines for 46,382 BP probes passing Affymetrix quality control and polymorphic. Table S9. Comparison of the reproducibility of InDels and SNP genotyping between 13 maize varieties replicated on 50 K Illumina SNP and Affymetrix® Axiom® InDel arrays.Additional file 2: Figure S1. Description of two approaches used to discover InDels using resequencing data of DNA. Figure S2. Number and complementarity of A) deletions and B) insertions regarding B73 reference genome discovered between F2, PH207 and C103 inbred lines and B73. Figure S3. Schematic representation of four different breakpoint types identified by PINDEL at InDel breakpoints according to the presence of micro-homology sequence or not in place of the deleted sequence. Figure S4. Distribution of probe number per InDel for 105,927 InDels genotyped with the array. Figure S5. Relationship between probes number genotyping the InDel and A) the InDel length B) cumulated length of specific sequence (PARs) within InDel. Figure S6. Variation of probes and InDels density across the 10 maize chromosomes. Figure S7. Three dedicated Affymetrix pipelines used for calling InDel polymorphisms from the fluorescent intensity variation of BP probes (A), OTV probes (B) and MONO probes (C). Figure S8. Example of clustering based on probes fluorescence (intensity in y-axis and contrast in x-axis), for 14 different classifications of probes assigned by the Affymetrix® algorithm. Figure S9. Example of clustering for 6 randomly probes in different classifications. Figure S10. Variation of the distribution of the average consistency rate (%) of InDels between expected and observed genotyping of probes according to number of probes within the InDel. Figure S11. Haplotype of two InDels genotyped with multiple probes (in column) for 362 individuals (in rows). Figure S12. Effect of average frequency of absence across 362 lines on consistencies between probes genotyping within InDels. Figure S13. Comparison of kinship between 362 inbred lines estimated with 57,824 InDels and with 28,143 SNPs from the 50 K Illumina genotyping array. Figure S14. Principal coordinate analysis on the genetic distance between 360 inbred lines from an association panel (B73 and F2 were excluded) estimated by A) 57,824 InDels and B) 28,143 SNPs.


The cytotoxic effects were dose dependent for all tested tumour and non-tumour cell lines. Under in vivo conditions, three application routes of phenylboronic acid were studied: intra-peritoneal (i.p.), intra-tumour (i.t.) and per-oral. After tumour transplantation in syngeneic mice, phenylboronic acid was shown to slow the growth of both tumour cell lines (4T1 and SCCVII) compared with the control. The inhibitory effects were pronounced during the application of phenylboronic acid. For both tested tumour cell lines, the most prominent antitumour effect was obtained by intraperitoneal administration, followed significantly by oral administration.The cytotoxic activity of phenylboroxine acid was evaluated  However, conventional therapeutics are not sufficiently selective for tumourigenic cells. Damage to normal tissues could be significantly reduced if a potential therapeutic compound selectively impacts tumour cells while avoiding normal, healthy cellsin vitro and in vivo antitumour effects of PBA against mouse mammary adenocarcinoma 4T1 and squamous carcinoma SCCVII cells. In vivo experiments were performed on mice using three modes of administration: intra-peritoneal, intra-tumour and per-oral.These aforementioned studies have indicated the promising direction of studying the effects of PBA inhibition properties on other types of cancer cell lines. Therefore, as part of our project, “Research on antitumour properties of different derivatives of boronic acid”, we decided to investigate in vivo and in vitro. Cells were grown in RPMI 1640 medium  supplemented with 10% foetal calf serum , in a humidified 5% CO2, 37 °C atmosphere.PBA solutions  were prepared by dissolution in phosphate buffer . Mouse mammary adenocarcinoma 4T1 cell line was purchased from American Type Culture Collection  and mouse squamous cell carcinoma SCCVII cell line was obtained from BC Cancer Research Centre . Both SCCVII and 4T1 murine tumour cells are widely accepted animal models for the investigation of these types of tumours in humans: SCCVII for human head and neck tumoursad libitum. The animals were kept under conventional conditions: 12/12 h light/dark rhythms, 22 °C temperature and 55% humidity. Animals were treated according to the Animal Welfare Regulations. Each experimental group consisted of seven animals. Mouse tumour models of mammary adenocarcinoma 4T1 and squamous cell carcinoma SCCVII were established by injecting 5 × 105 tumour cells subcutaneously into the right thighs of syngeneic mice.The mice used in the study were obtained from Ruđer Boškovic Institute’s breeding colony. Two mouse strains, BALB/c syngeneic with 4T1 cells and C3H/H syngeneic with SCCVII cells, were used. The animals were ∼3-months-old and weighed 20–23 g. They were provided standard diet  and tap water All experimental procedures were performed in accordance with the current guidelines for the care of laboratory animals (including the use of the 3Rs procedures). The experiments were terminated before the mean tumour diameter exceeded 15 mm as recommended in the 2010 guidelines for the welfare and use of Animals in cancer research4 tumour cells/250 μl medium were added to each well. After 24 h, when the cells reached confluence, old cultured media were replaced with fresh media. The tested compound PBA was added to the cultures to final concentrations of 0.1, 1.0 and 10.0 mg/ml . Control cells were incubated in RPMI medium without the tested substance. The cells were incubated for an additional 24 h. Cytotoxicity tests with crystal violet were performed to measure cell growth inhibition rates. Briefly, cells were fixed by the addition of a 3% solution of formalin for 15 min, washed with deionised water and dried in air. Afterwards, cells were stained with 0.1% crystal violet for 20 min, then extensively washed with deionised water and left to dry overnight. The dye was extracted from the cells using a 10% solution of acetic acid. Then, absorbance was measured using a microplate reader. The absorbance at 590 nm is proportional to the number of surviving cells. Each experiment was performed in quadruplicate. Inhibition of cell growth relative to controls was calculated according to the formula: inhibition of cell growth I% = (C − T)/C × 100, where T denotes the mean absorbance of treated cells and C indicates the mean absorbance of untreated (control) cells. The LC50 concentrations were estimated using probit analysis,For evaluation of cell viability and cytotoxic effects of PBA on cultured cells, a crystal violet staining assays was used3. For both experiments (cell lines 4T1 and SCCVII), mice were randomly divided into four groups (seven mice per group). Three application routes of PBA were studied: intra-peritoneal (i.p.), intra-tumour (i.t.) and per-oral. Briefly, 300 μl saline with a PBA dose of 100 mg/kg of mice (average body weight of 20–23 g) were administered once a day for nine consecutive days starting from Day 10. The total received dose was 900 mg/kg of mice for each mode of administration. Control mice received the same volumes of saline without PBA. The dosage regimen applied in this study was well-tolerated by the animals with no signs of overtoxicity, i.e. the animals were generally in good condition and did not show significant weight loss. Available literature has also suggested low toxicity of boron-containing acids, including PBA. Thus, in mice, a high LD50 dose of 900 mg/kg for acute toxicity was determined50 dose.The treatment was started on Day 9 after transplantation, when tumour volumes reached ∼250–300 mmpost hoc test of multiple comparisons. p ≤ .05 was considered significant.Tumour growth was observed by measuring three orthogonal tumour diameters  with a calliper. Tumour volume was calculated by the formula V = ABCπ/6. The inhibition of tumour growth was calculated by the formula: TGI (%) = (C−T)/C × 100, where C is the mean tumour volume of the control (untreated) group, and T is the mean tumour volume of the treated groups. Significant differences in tumour volumes between the groups were determined by one-way analysis of variance (ANOVA) and Tukey’s 50 values were estimated to be 4.5 and 7.5 mg/ml for the SCCVII and 4T1 cells and 6.0 and 7.5 mg/ml for the L929 and V79 cells, respectively.The cytotoxic activities of PBA at different concentrations 0.1, 1.0 and 10 mg/ml  were evaluated on mouse mammary adenocarcinoma 4T1 and squamous cell carcinoma SCCVII cell lines  and on hin vivo was assessed on the same tumour models as the in vitro experiments. Preliminary experiments showed that the intra-peritoneal application of 50 mg/kg of PBA in a single dose was well-tolerated by all mice. The same results were achieved when PBA was applied as a single 50 mg/kg intra-tumoural dose. When PBA was administered per-orally in five consecutive days in five doses of 50 mg/kg, PBA was also well-tolerated by all mice. The effects of intra-peritoneal (i.p.), intra-tumour (i.t.) and per-oral (p.o.) applications of PBA on the growth of squamous cell carcinoma SCCVII is presented in Antitumour activity 3, which represents a 57% tumour growth inhibition and 7 days tumour growth delay.PBA significantly reduced the growth of adenocarcinoma 4T1 in all three modes of administration . The intin vitro and in vivo by three modes of administration, i.e. intra-peritoneal, intra-tumour and per-oral. As presented in the previous section, at PBA concentrations <1 mg/ml (8.2 mM), no inhibitions in tumour 4T1 cells in vitro were observed. Similar results were observed with non-tumour cells V79 and L929, whereas in tumour SCCVII cells, partial growth inhibition was seen. Significant growth inhibition LC50 values were estimated at 4.5–7.5 mg/ml demonstrating no significant differences in inhibition between tumour cells and non-tumour cells.This is the first report showing that PBA can inhibit the growth of mouse mammary adenocarcinoma 4T1 and mouse squamous cell carcinoma SCCVII. The data presented indicated that PBA is capable of inhibiting growth in the selected cell lines in vitro and in vivo remains unknown. The sialic acid is known to be over-expressed on the cell surface of tumour cells and the increasing expression of sialic acid was previously shown on 4T1 cellsApoptosis is one of the most potent defences against cancer. This process eliminates potentially deleterious mutated cellsi = 1.96 × 10−4 M compared with Ki = 1.0 × 10−2 M of benzyl alcohol, which lacks the boronic acid motif. Evidence suggested that the inhibition activity was due solely to the boronic acid. Slight changes in pH can result in the release of the inhibitor from the active site, enabling the use of boronic acids as biological probes and in therapeuticsin vitro and in vivo PBA antitumour activities using the same tumour cell lines. In vivo experiments were performed intra-peritoneally, intra-tumourally and per-orally. With respect to the mode of administration, the results observed were generally similar for both tumour models, i.e. the most pronounced effect was obtained by intraperitoneal administration followed by oral and intratumoural administrations. The remarkable inhibition of tumour growth after oral administration suggested that PBA is not metabolised after oral administration or that its metabolites have similar antitumour effects. These metabolites, such as arylboronic acids and their esters, could have selectively reacted with H2O2 and metabolised the formation of boronate intermediates that rapidly hydrolyse to release phenols, borate esters, and boric acids2O2 to release active anticancer drugs (effectors) with selective toxicity towards cancer cells,2O2 found in cancer cellsPreviously, PBA had been suggested to act as proteasome inhibitors. The boronic acid motif acts as a transition state analogue, forming hydrogen and covalent bonds in the enzyme active site. For example, the inhibition constants of chymotrypsin at pH 7 for simple PBA were found to be K2[B3O3F4OH], have been suggested for use in the prevention and/or treatment of benign or malignant changes in epidermal tissuein vitro and in vivo growth of 4T1 mammary adenocarcinoma, B16F10 melanoma and squamous cell carcinoma SCCVII cells. In previous studies, boronic acid derivative K2[B3O3F4OH] was hypothesised to reduce catalase2O2 to produce beneficial effects in tumour tissues alone. Considering these results, the same mode of action for PBA could be suggested but would require further study.Recently, halogenated boroxines, e.g. KAs outlined by Baker et al.


Complex coacervation is an emerging liquid/liquid phase separation (LLPS) phenomenon that behaves as a membrane-less organelle in living cells. Yet while one of the critical factors for complex coacervation is temperature, little analysis and research has been devoted to the temperature effect on complex coacervation. Here, we performed a complex coacervation of cationic protamine and multivalent anions (citrate and tripolyphosphate (TPP)). Both mixtures  underwent coacervation in an aqueous solution, while a mixture of protamine and sodium chloride did not. Interestingly, the complex coacervation of protamine and multivalent anions showed upper critical solution temperature (UCST) behavior, and the coacervation of protamine and multivalent anions was reversible with solution temperature changes. The large asymmetry in molecular weight between positively charged protamine (~4 kDa) and the multivalent anions (<0.4 kDa) and strong electrostatic interactions between positively charged guanidine residues in protamine and multivalent anions were likely to contribute to UCST behavior in this coacervation system. Coacervation is a liquid/liquid phase separation (LLPS) phenomenon in aqueous solution caused by the complexation of dissolved polymers in the aqueous solution due to a variety of attractive forces ,2,3,4. WWhen coacervation is driven by electrostatic attraction in water, the process is called “complex coacervation” . ComplexThe formation of complex coacervates is controlled by the pH and ionic strength of the solution, the type of polyelectrolyte, the concentration of the polymers, the molecular weight and conformation of the polymers, the mixing ratio between two oppositely charged polymers, and the temperature. Among the aforementioned conditions, the effect of temperature on the formation of complex coacervates has not yet been systematically studied.Contrary to the fact that conventional theories of complex coacervates based on Flory–Huggins theory ,18, suchProtamine sulfate salt from salmon (p4020), sodium citrate tribasic dehydrate (S4641), sodium tripolyphosphate (7758-29-4)and Sigmacote (SL2) were purchased from Sigma . FITC (5(6)-SFX (6-(Fluorescein-5-(and-6)-Carboxamido) Hexanoic Acid, Succinimidyl Ester), F2181) and particles with a size of 0.2 μm (FluoSpheres) from Thermo Fisher Scientific  and 2% PFPE (Perfluorinated polyethers) –PEG (Polyethyleneglycol) –PFPE (Perfluorinated polyethers) triblock copolymer surfactant (E2K0660) from RAN Biotechnologies, Inc. , were obtained. Circular dichroism (CD) spectropolarimeter , Confocal microscopy , Optical microscopy , Zetasizer , MATLAB software  and UV-Vis spectrometer  were used.Cp) (0.1 to 1.6% (w/v)), and pH, coacervation of the protamine and multivalent ions was quantified by turbidity at room temperature. The solution pH values of the protamine/citrate system and protamine/TPP system were ~8.0 and ~4.5, respectively, where both multivalent ions lost three protons. The protamine and multivalent ions were dissolved in water to 1% (w/v) as stock solution and filtered with a 0.45-μm filter. The pH of sodium citrate stock (1% w/v) was titrated to ~8.0, and the pH of sodium tripolyphosphate was adjusted to ~4.5 by adding 10 mM HCl. Each stock solution was diluted to make different total polyelectrolyte concentrations (Cp) and ratios between protamine and multivalent ions. Relative turbidity measurements were performed by UV–VIS spectrometer  at 600 nm, at which the absorbance interference from protamine was negligible. The relative turbidity was defined as -ln (T/T0), where T and T0 are the light transmittance with and without polyelectrolytes, respectively [By varying the ratio between protamine and multivalent ions (0 to 1), total polyelectrolyte concentration (ectively . Each exCp was fixed at 1% (w/v).Temperature-dependent turbidity measurements were performed with a circular dichroism (CD) spectropolarimeter  with a temperature controller. The absorbance of the coacervates was obtained at 600 nm with a temperature change rate of 1 °C /min, and the chamber was purged with nitrogen gas. Each temperature cycling experiment was performed from 25 to 60 °C. The weight ratio between protamine and multivalent ions was fixed at a ratio of 6:4, and w/v) was prepared freshly. To determine the viscosity, microrheology was performed by embedding fluorescent probe particles  into the dense phase of the complex coacervate. The particle-dispersed dense phase was introduced into a flow cell, which was a channel that was formed in a sandwiched coverslip–parafilm–coverslip configuration using end-cut pipette tips and subsequently sealed with epoxy [n = 189) in the dense phase was tracked using confocal microscopy  for 50 s with 10-ms intervals at 20 °C. The averaged mean squared displacement (MSD) of the particles was calculated using MATLAB software  and fit to the form MSD(τ) ~4Dprobeατ, where α is the diffusive exponent, to estimate the diffusion coefficient Dprobe. The viscosity η of the dense phase was calculated using the Stokes–Einstein equation, Dprobe = BTk/6πηr, where Bk is the Boltzmann constant, T = 293 K is temperature, and r = 100 nm is the probe radius.The viscosity of the protamine/citrate coacervate was measured by microrheology. The dense phase of the protamine/citrate complex coacervate at a ratio of 6:4 in 1% (th epoxy . The mobTM NovecTM 7500 Engineered Fluid) and the aqueous phases was stabilized with PFPE-PEG-PFPE triblock copolymer surfactant . Coalescence events were recorded with confocal microscopy (Visitech) with 4-ms intervals at 488 nm excitation and decay timescales τ. Changes in the dimensionless parameter L) and width (W) of a droplet during relaxation, were measured at late stages when all coalescing droplets looked convex. We then used a formula for the relaxation kinetics of a deformed liquid droplet [r) of the liquid droplet from the Equation (1) [The interfacial tension of the protamine/citrate coacervate was measured by observing coalescence events of two droplets over time. A solution containing droplets of an FITC (Fluorescein isothiocyanate)-tagged protamine/citrate coacervate phase was prepared and flowed into a coverslip-sandwiched fluid chamber with a flat oil/water interface  to minim droplet ,(1)τ≅19tion (1) .Protamine (~4 kDa) from salmon sperm was selected as a positively charged polyelectrolyte, and sodium citrate (189 Da) or sodium tripolyphosphate  was selected as a multivalent anion . ProtamiTc) for protamine/citrate and protamine/TPP was ~33 and ~45 °C, respectively. At higher temperatures, mixing entropy dominated and favored a macroscopic homogeneous mixture.However, while one of the critical factors for complex coacervation is temperature, little analysis and research has been devoted to the temperature effect on complex coacervation. The temperature dependence of the protamine/multivalent ion system was determined at a protamine/multivalent ion ratio of 6:4. Upon heating, the turbid mixture of protamine and multivalent ions changed to a transparent solution . Cp was defined as the weight sum of protamine and multivalent ions in the solution. The results of relative turbidity measurements for mixtures of protamine/multivalent ions with different Cp values are presented in Cp in the system increased from 0.1% (w/v) to 1.6% (w/v), the relative turbidity increased in both systems. The protamine/TPP system had a higher relative turbidity when Cp was ~0.2% (w/v), implying that the bonding between positively charged guanidine in protamine and negatively charged phosphate in TPP was stronger than the bonding between positively charged guanidine in protamine and negatively charged carboxyl groups in citrate.Coacervation can be affected by the total polyelectrolyte concentration , ~4.8 (pKa2), and ~6.4 (pKa3) at 25 °C; while TPP is a pentabasic acid with five pKa values of ~1.0 (pKa1), ~2.2 (pKa2), ~2.30 (pKa3), ~6.50 (pKa4), and ~9.24 (pKa5); and guanidine groups in arginine have a pKa value of ~12.5. Therefore, the protamine/citrate system had maximum turbidity at pH ~8.0. In the case of TPP, the maximum turbidity was observed at pH ~4.5, where the surface charges of the complex coacervates dropped to zero. Since TPP is a pentabasic acid, the turbidity of the protamine/TPP complex decreased as the pH changed from 4.5 to 12 due to deprotonation in TPP.The surface charge and the relative turbidity were measured in a pH range from ~2 to ~12. Both coacervate systems reached maximum turbidity when the surface charge determined by the Zetasizer converged to zero . With a MSD> 2/s from <MSD> = 4probeταD, and the viscosity of the coacervate phase calculated from the Stokes–Einstein equation was 0.0659 Pa·s when T = 293 K and r = 100 nm were used. We then used the measured viscosity value to extract the interfacial tension of the coacervate phase by monitoring coalescence events between two droplets, as coalescences are driven by minimizing the interfacial area and are resisted by the viscosity of the liquid phase. For each of 11 droplet coalescence events, the timescales of the deformed droplets being relaxed into spheres were extracted as described in the “Materials and Methods” section  is crosslinked by multivalent anions (<0.4 kDa) to form a network structure, the network structure in this system is similar to that of a solid-like hydrogel. In this case, the origin of the phase transition is enthalpic. The cross-linking due to electrostatic attraction weakens with increasing temperature, and the system shows UCST behavior .Interestingly, the complex coacervate found in this study was formed from strong electrical interactions, as are hydrogels, but underwent liquid–liquid phase separation, similar to conventional complex coacervates. The complex coacervate did not undergo phase separation with monovalent salts , but it Tc than citrate.In addition to temperature, phase separation depends on the valence of the multivalent anion, its concentration, pH, and hydration effects. When the valence of the multivalent anion is high, phase separation is induced even at lower concentrations, as observed in the pH control experiment, because the charge bridging becomes stronger with a higher valence of multivalent anions. However, if the pH is too high, the condensation effect of the anion is reduced, and the phase separation disappears. Another notable point is that TPP induces a phase transition at lower salt concentrations and has a higher critical solution temperature than citrate. The difference between citrate and TPP is likely to originate from the hydration effect. TPP may have a more fragile hydration shell than citrate, which can mediate a stronger electrostatic bridge . The valIn this report, the complex coacervation of positively charged protamine and multivalent anions (citrate and TPP) was studied. Unlike conventional complex coacervates made of two oppositely charged polyelectrolytes with similar molecular weights showing LCST behavior, a complex coacervate of protamine and multivalent anions showed upper critical solution temperature (UCST) behavior, which was reversible with temperature cycling. Due to the large molecular weight asymmetry in between positively charged polyelectrolytes (~4 kDa) and multivalent anions (<0.4 kDa), multivalent anions seemed to behave as crosslinkers of relatively long positively charged polymers. The electrostatic origin crosslinking was not strong enough to make a gel phase: Instead, it formed a dense liquid phase, leaving dilute supernatant outside. Therefore, this enthalpic origin phase transition showed UCST behavior.


The aim of this study is to profile the cytokines and immune cells of body fluid from metastatic gastric cancer (mGC), and evaluate the potential role as a prognostic factor and the feasibility as a predictive biomarker or monitoring source for immune checkpoint inhibitor.Body fluid including ascites and pleural fluid were obtained from 55 mGC patients and 24 matched blood. VEGF-A, IL-10, and TGF-β1 were measured and immune cells were profiled by fluorescence assisted cell sorting (FACS).VEGF-A and IL-10 were significantly higher in body fluid than in plasma of mGC. Proportion of T lymphocytes with CD69 or PD-1, memory T cell marked with CD45RO, and number of Foxp3+ T regulatory cells (Tregs) were significantly higher in body fluid than those in blood of mGC. Proportion of CD8 T lymphocyte with memory marker (CD45RO) and activation marker (HLA-DR), CD3 T lymphocyte with PD-1, and number of FoxP3+ Tregs were identified as independent prognostic factors. When patients were classified by molecular subgroups of primary tumor, VEGF-A was significantly higher in genomically stable (GS)-like group than that in chromosomal instability (CIN)-like group while PD-L1 positive tumor cells (%) showed opposite results. Monitoring immune dynamics using body fluid was also feasible. Early activated T cell marked with CD25 was significantly increased in chemotherapy treated group.By analyzing cytokines and proportion of immune cells in body fluid, prognosis of patients with mGC can be predicted. Immune monitoring using body fluid may provide more effective treatment for patients with mGC.The online version of this article (10.1186/s40425-019-0708-8) contains supplementary material, which is available to authorized users. Collective clinical evidence suggests that ICI is more effective for inflamed tumors [Gastric cancer ranks the fourth among the most common cancers worldwide and the third in mortality rate . It is td tumors .However, not all patients with inflamed tumors respond to ICI. T cell receptor (TCR)-peptide-major histocompatibility complex (pMHC) binding is the central event in the activation of T cell. Activation antigens on T cell include CD25, CD26, CD38, CD54, CD69, and HLA-DR , 12. ActAbout 30–40% of mGC patients have malignant ascites associated with peritoneal carcinomatosis , 16. AscBetween December 2014 and April 2016 at Yonsei Cancer Center, Seoul, Korea, body fluid including ascites and pleural fluid were obtained in a prospective, nonselective fashion from 55 mGC patients via paracentesis or catheter drainage. Twenty-four matched blood samples were also taken before or at the time of body fluid acquisition. Cancer cells from body fluid were confirmed by pathologist using cell block. Eleven non-cancerous ascites and 4 matched blood samples were obtained from patients with Child-Pugh B/C liver cirrhosis. Blood samples from 15 healthy volunteers were used as controls. Clinical data including age and sex were collected for all study subjects. The following clinico-pathologic information was obtained by reviewing electronic medical records (EMR) of gastric cancer (GC) patients: disease presentation (recurrent or metastatic), type of surgery, differentiation, Lauren classification, HER2 status, type of body fluid, acquisition timing of body fluid, and survival time. This study was approved by the Institutional Review Board of Severance Hospital (No. 4–2014-0638).VEGF-A, IL-10, and TGF-β1 which are known immune suppressive cytokines were selected for measurement to evaluate their clinical roles and associations with immune cells. Plasma was isolated from collected 10 ml peripheral blood in EDTA tube using Ficoll-Paque™ PLUS  gradient centrifugation and stored at − 80 °C until assay. Body fluid was incubated in 10 X RBC lysis buffer  to remove RBC and centrifuged . The supernatant was separated, aliquoted, and stored at − 80 °C until analysis. Plasma and body fluid supernatant were used to measure levels of circulating VEGF-A, IL-10, and TGF-β1 using a commercially available enzyme-linked immunosorbent assay (ELISA) kit  following the manufacturer’s protocols. Samples were measured in duplicates and mean value was presented as final concentration. ELISA plates were read on a Sunrise absorbance microplate reader .Peripheral blood mononuclear cells (PBMCs) were isolated from 10 ml peripheral blood collected into EDTA tube using Ficoll-Paque™ PLUS  gradient centrifugation. Tumor associated lymphocytes (TALs) from 100 to 500 mL malignant fluid were isolated using the following protocol. Briefly, the fluid was incubated with 10 X RBC lysis buffer  to remove RBC and centrifuged in 50 ml tubes at 1500 rpm for 5 min. After two washes with PBS , isolated cells were suspended in 1 ml of Cellbanker-2  and stored at − 80 °C until analysis.Flow cytometry was performed using FACS LSR2 . Data were analyzed using FlowJo software . Fluorescence-conjugated monoclonal antibodies were purchased from the following sources: Human LAG-3 Alexa Fluor® 488-conjugated Antibody ; PE/Cy7 anti-CD3, FITC anti-CD4, PE anti-CD8, FITC anti-CD45RO, FITC anti-HLA-DR, APC anti-CD25, APC/Cy7 anti-CD69, APC anti-human CD279 (PD-1), APC/Cy7 anti-human CD366 (Tim-3), and PE anti-FoxP3 . Furthermore, cells were stained with PE anti-human CD274  to identify proportion of PD-L1 positive tumor cells in body fluid.For Treg cell staining, cells were stained with various antibodies except FoxP3 antibody for which cells were fixed and permeabilized with eBioscience™ FoxP3 Fixation/Permeabilization solution . FoxP3 antibodies were administered after permeabilization for intracellular staining of Tregs. FACS analyses were performed for cells isolated from malignant fluid and peripheral blood. First, levels of CD4+ and CD25+ T cells in cells isolated from these two sources  were measured. Next, we quantified the percentage of cells that were positive for FoxP3 in the CD4 + CD25+ T cell population.Gastric cancer panel practically used in our institution has 10 markers, including Epstein-Barr virus encoded small RNAs (EBER) in-situ hybridization, mismatch repair proteins , receptor tyrosine kinases , PTEN, and p53 protein expression by IHC using formalin-fixed, paraffin-embedded (FFPE) tissue blocks from paired primary stomach cancer. Detailed methods of in situ hybridization (ISH) and IHC staining have been described in our previous study . Patientp-value of less than 0.05 was considered statistically significant. PASW Statistics 18.0  was used for all statistical analyses.Differences in cytokine and immune profiles among blood and body fluid samples were compared using the Mann-Whitney U test. Pearson’s correlation coefficient was calculated to determine relationships among variables. A value of higher than 0.7 means highly positive correlation . ContinuBaseline characteristics of enrolled patients are shown in Table P = 0.013 and P = 0.001, respectively). VEGF-A and IL-10 levels in mGC body fluid were significantly higher than those in mGC plasma and non-cancerous body fluid   of mGC. Proportion of memory T cell marked with CD45RO  and activated T lymphocytes  were significantly higher in body fluid than those in peripheral blood of mGC . In contrast, VEGF-A and number of FoxP3+ Tregs showed significant negative correlation  . However, patients with high levels of at least two cytokines showed significantly shorter OS than patients with zero or one cytokine at high level  showed poor survival outcome with borderline tendency ((Table ).Survival analysis was also conducted using immune cell profiles. Results are shown in Fig. Table .Table 2P = 0.003). No significant difference was observed in immune cell profile, although percentage of PD-L1 positive tumor cells showed a higher tendency in CIN-like group than that in GS-like group   Fig. a-b.Fig.P = 0.017 and P = 0.035, respectively, Fig. P = 0.084; CD8CD45, P = 0.157). In addition, body fluid of patients treated with chemotherapy had higher VEGF-A levels than chemotherapy naïve patients , suggesting that chemotherapy might induce immune suppressive environment.Cytokine and immune cell profile from body fluid were compared between chemotherapy naïve and previously treated groups. Proportion of early activated T cells (CD3CD25 and CD4CD25) in previously chemotherapy treated patients was higher level than that in chemotherapy naive patients , myeloid-derived suppressor cells (MDSCs), and regulatory T cells . VEGF-A,Immune cell profiling of body fluid in mGC was also conducted and compared to that of plasma. Proportion of memory T cell with CD45RO and early activated T cell with CD69 was higher in malignant body fluid than that in plasma. This phenomenon was observed in other studies on ovarian cancer . It mighAs a prognostic factor, higher proportions of CD8CD45RO, CD8HLA-DR, and CD3PD1 were independent poor prognostic factors. CD45RO and HLA-DR are generally regarded as activation markers while PD1 is a well-known suppressive marker , 32. TheMolecular subtype was classified into MSI, EBV, CIN-like, and GS-like group based on immunohistochemistry results, not genomics. Differences in cytokine and immune profiling were clustered by each group. VEGF-A level showed significant difference between CIN-like and GS-like group. VEGF-A level was higher in the GS-like group. However, other factors did not show statistically significant differences between these two groups. CIN-like group showed increased tendency of proportion of PD-L1 positive cancer cells than that in GS-like group. According to these differences, anti-VEGF therapy might give GS-like group more benefit while PD1 or PD-L1 inhibitor can be applied to CIN-like group. However, further mechanisms and clinical studies are needed to establish precision medicine based on body fluid monitoring.The benefit of immune monitoring has already been studied and several approaches including tissue biopsy and blood sampling are ongoing , 34, 35.This study has some limitations. Firstly, a small number of patients were analyzed. Therefore, it is hard to have enough statistical power. Results of this study should be validated through more studies with larger sample size. Second, we only checked a limited number of cytokines and immune cell markers. This should be overcome by multiplex technology including cytometry by time of flight (CyTOF). In addition, we did not perform comparison between body fluid and tumor tissues due to invasiveness of tumor biopsy and poor performance of most patients. However, this study also has several advantages. Healthy volunteer and non-cancerous patients with ascites were included as controls to find the distinct meaning of immune profiling from malignant body fluid. In most studies, characterization and prognostic role of malignant body fluid were reported in ovarian cancer. Study of mGC body fluid was limited. We comprehensively characterized cytokines and immune profile of body fluid and evaluated the possibility of using body fluid as a monitoring source for predicting prognosis and marking therapeutic decision. In addition, we checked the proportion of PD-L1 positive tumor cells in body fluid. However, further studies with serial sampling of body fluid acquisition and immune profiling of paired primary tumor tissue are needed to verify our results.Additional file 1:Cytokine level of plasma and body fluid in healthy volunteers, non-cancerous and gastric cancer patients. (DOCX 16 kb)Additional file 2:Immune cell profiling of peripheral blood and body fluid in metastatic gastric cancer patients. (DOCX 20 kb)Additional file 3:Univariate analysis of body fluids immune cell subset for overall survival. (DOCX 20 kb)Additional file 4:Correlation of cytokine levels between plasma and body fluid. (PPTX 80 kb)Additional file 5:Correlation of different cytokines in body fluid. (PPTX 81 kb)Additional file 6:Correlation between FoxP3+ T regulatory cells (Tregs) and immune cells with suppressive markers. (PPTX 147 kb)Additional file 7:Correlation between VEGF-A and proportion of immune cells in the body fluid. (PPTX 190 kb)


This data article presents 36 raw and unprocessed video files which were obtained during hydraulic fracture experiments in two-dimensionally confined gelatin plates. Initiation and propagation of bi-wing fractures were recorded at 50 frames per second with the resolution of 1920 × 1080 pixels. The gelatin stiffness, the fluid viscosity, and the flow rate were controlled. With these data, the fracture geometry, such as length, width, and propagation velocity were discussed in the research article “Characteristics of steady-state propagation of hydraulic fractures in ductile elastic and two-dimensionally confined plate media” Ham and Kwon et al., 2019. The movies are formatted in MP4 format with the frame size of 1920 × 1080 pixels. Conditions for each HF experiment are indicated by the filename: S for the gelatin stiffness, Q for the fluid injection rate, and CP for the fluid viscosity. The videos were recorded from the onset of fluid injection. The bi-wing hydraulic fractures were generated and propagated, and then the experiment was terminated when the fluid injection stopped.123456789101112131415161718192021222324252627282930313233343536The following are the supplementary data related to this article:2Ham and Kwon (2019)Gelatin samples were prepared in the acrylic mold, of which the size was 200 × 200 × 5 mm (length × width × thickness), by pouring gelatin solutions and then cured at 4 °C for 20 hours. Thereafter, the copper tube was placed at the center of the plate, and was then connected to the transfer vessel. This gelatin sample was placed under a LED lamp for recording using a high-speed camera . Bi-wing type of two hydraulic fractures were generated by injecting the fracture fluid dyed with blue ink through the penetrated borehole. The time-lapsed images of hydraulic fracture initiation and propagation were acquired using the high-speed camera facing up the gelatin sample recorded at 50 frames per second with the resolution of 1920 × 1080 pixels. A total of 36 cases were tested with four levels of gelatin stiffness, three classes of fracturing fluid viscosity , and four different flow rates . The gelatin stiffness was controlled with the water prior to gelatin concentration: 3.84, 7.41, and 12.28, 13.79 wt% for S0, S1, S2, and S3. Each of the HF experiments is labeled using the symbols representing each test condition: S0, S1, S2, and S3 for gelatin stiffness levels, CP1, CP10, and CP100 for the fracturing fluid viscosity, and Q5, Q10, Q20, and Q40 for the injection flow rate. For example, S0Q5CP1 which is VideoS01_S0Q5CP1 file is the result of the experiment under the conditions of S0 stiffness of gelatin, 5 mL/min of the flow rate, and 1 cp of the fluid viscosity. The detailed experiment procedure and analysis were presented in


To assess the long‐term stability of the anchored radiofrequency transponders and compare displacement rates with other commercially available lung fiducial markers. We also sought to describe late toxicity attributable to fiducial implantation or migration.SBRT database and matching 2:1 based on the lobe containing tumor and proximity to the bronchial tree. Assessment of migration was performed by rigidly registering the most recent follow‐up CT scan to the simulation scan, and assessing whether the relative geometry of the fiducial markers had changed by more than 5 mm. Toxicity outcomes of interest were hemoptysis and pneumothorax.The transponder cohort was comprised of 17 patients at our institution who enrolled in a multisite prospective clinical trial and underwent bronchoscopic implantation of three anchored transponders into small (2–2.5 mm) airways. We generated a comparison cohort of 34 patients by selecting patients from our institutional lung CT, all fiducial markers were within 5 mm of their position at CT simulation in 11 (65%) patients in the transponder group as compared to 23 (68%) in the comparison group (P = 0.28). One case of hemoptysis was identified in the transponder cohort, and bronchoscopy confirmed bleeding from recurrent tumor; no cases of hemoptysis were noted in the comparison cohort. No case of pneumothorax was noted in either group.The median follow‐up of patients in the transponder cohort was 25.3 months and the median follow‐up in the comparison cohort was 21.7 months. When assessing the most recent No significant difference in the rates of fiducial marker retention and migration were noted when comparing patients who had anchored transponders placed into small airways and a 2:1 matched cohort of patients who had other commercially available lung fiducial markers placed. In both groups, no late or chronic toxicity appeared to be related to the implanted fiducial markers. Since SBRT requires delivery of ablative radiation doses with steep dose gradients, accounting for target motion is critical. Early lung SBRT techniques required large internal target volume (ITV) expansions in order to account for target motion throughout the respiratory cycle.® System  has been suggested as a potential solution.To mitigate the concern that movement of the gating marker and tumor may be discordant, real time radiographic tracking of implanted fiducial markers can be combined with respiratory gating. The use of triggered planar imaging to assess fiducial marker position improves the accuracy of treatment delivery,The Calypso System consists of electromagnetic transponders paired with a detector array. The Calypso System has been validated for providing real‐time tumor tracking within a variety of solid tissues.22.AThe transponder cohort consisted of all patients at our institution who underwent placement of anchored transponders into small airways as part of a prospective clinical trial NCT01396551); no patients who underwent transponder placement were excluded. A comparison cohort was constructed by first reviewing the records of all patients who underwent lung SBRT at our institution between 2010 and 2016. For each transponder case, two matched patient cases were selected who had undergone placement of other types of radiopaque lung fiducial markers. Matching criteria were lung lobe and proximity to the proximal bronchial tree  near the tumor. In the comparison cohort, 2–3 radiopaque fiducial markers were placed near the tumor either via bronchoscopy or via CT‐guided transthoracic needle. In all cases an immediate chest radiograph was performed to confirm retention of the fiducial markers.4‐Dimension CT simulation for SBRT planning was typically performed within 2 weeks of fiducial marker placement. In most cases, peripheral tumors were prescribed a dose of 54 Gy in 3 fractions and central tumors were prescribed a dose of 48–52.5 Gy in 4–5 fractions. One patient received fractionated therapy (60 Gy in 30 fractions) due to mediastinal adenopathy that was identified at the time of simulation. Following treatment, a baseline chest CT was performed within 3 months and repeated every 6 months coinciding with clinical toxicity assessment. Additional thoracic imaging and bronchoscopy were performed only if clinically indicated.2.CThe simulation CT scan was considered as the reference image for baseline fiducial location. On the 4‐dimensional simulation CT data set, the implanted markers were manually segmented on the earliest phase of the respiratory cycle for which treatment was planned (corresponding to when the treatment gate opens) using Varian Eclipse software and a uniform 5 mm spherical expansion structure around each marker was generated  was located within an area of fibrosis or normal appearing lung parenchyma. In each case, whether marker displacement was most likely due to evolving postradiation fibrosis Fig.  or to mi2.Dχ2 test. An unconditional test of frequencies was chosen because of the large number of potential pairings between patients in the transponder and comparison cohorts.All statistical analyses were performed using SPSS Statistics 24 . Differences in frequencies between the two patient cohorts were assessed using the 33.AA description of baseline patient and treatment characteristics is given in Table 3.BP = 0.28). Of the six patients with marker displacement within the transponder group, five instances appeared to be related to radiation fibrosis around one or more transponders. Of the 11 patients with fiducial displacement within the comparison group, four instances of fiducial displacement appeared to be related to progressive radiation fibrosis.The median follow‐up of patients in the transponder cohort was 25.3 months and the median follow‐up in the comparison cohort was 21.7 months. Across both groups, no fiducial marker noted at the time of CT simulation was unaccounted for at the most recent CT. When assessing the most recent CT, all markers were within 5 mm of the position on the CT simulation scan in 11 (65%) patients in the transponder group as compared to 23 (68%) in the comparison group  research funding from Varian Medical Systems.


Varicella zoster virus (VZV) encephalitis is an infectious inflammatory disease of brain that can cause irreversible mental damage without timely treatment. In fact, many viruses can cause encephalitis, and the viral loads in cerebrospinal fluid (CSF) in the early stage of the disease are usually too low to be detected. Here we report a case of VZV encephalitis diagnosed by advanced fragment analysis (AFA), which could potentially to contribute to early diagnosis of VZV central nervous system (CNS) infections with a small volume of CSF samples.A 10-year-old boy was admitted to the hospital with obvious neurological symptoms of headache, dizziness and vomiting for one day. Physical examination showed left facial paralysis. Complete blood count (CBC) test only showed an unspecific inflammation, and the culture of cerebrospinal fluid and microscopic staining examination were all negative. AFA was performed to screen the common 18 encephalitis related pathogens in CSF. Obvious VZV DNA fragments were observed by capillary electrophoresis at 160 nt, suggesting the existence of VZV CNS infection in children. The results were consistence with real-time quantitative PCR and concomitant symptoms in the acute stage of the disease.We report a case of acute VZV encephalitis in a child without obvious skin manifestations, which was rapidly diagnosed by AFA. Overall, we would recommend the use of AFA analysis as the rapid screening system for the identification and differentiation of encephalitis pathogens in children. Encephalitis is a kind of inflammatory disease of brain that is caused especially by infection with bacterial, virus and fungi –3. CliniVaricella-zoster virus (VZV) is an important α-herpesvirus which can lifelong remain latent in trigeminal and dorsal root ganglia, and therefore might lead various neurologic diseases such as meningitis, encephalitis, myelitis, meningoencephalitis, cranial neuropathy, and peripheral neuropathy , 11. In Common diagnostic methods of VZV include general medical tests and more accurate pathogen tests , 18. As At present with the development of molecular diagnostic technology, the application of molecular techniques such as advanced fragment analysis (AFA) could be a useful method of identifying and confirming the existence of VZV infection in clinical specimens, especially in the CSF. Here, we report on an indigenous case of encephalitis in a 10-year-old male child with a recessive VZV infection, which rapidly diagnosed by AFA method.A 10-year-old boy  in Sichuan province was admitted to the hospital with neurological symptoms of headache, dizziness and vomiting for one day. Physical examination showed left facial paralysis and no rash. His temperature is 36.5 °C, breath is 21 times per minute, pulse is 109 beats per minute, and the blood pressure is 103/72 mmHg. Additionally, he had no previous history of infection for these days.6/L nucleated cells and 13× 106/L erythrocytes. Among the nucleated cells, lymphocytes and monocytes account for 98 and 2% respectively. These results indicated the presence of infectious encephalitis. However, the ink staining, gram staining and acid fast staining of CSF were all negative. Besides the bacteria culture of CSF for 5 days was negative as well. Therefore, the child was suspected to have acute viral encephalitis.According to the general medical tests, we found the percentage of neutrophil in peripheral blood increased to a number of 85.2% (reference range 23.6–75%), which suggests the presence of inflammation. In addition, we punctured cerebrospinal fluid for accurate examination. The CSF biochemical examination showed that the protein (136.8 mg/L), glucose (3.85 mmol/L), chloride (127 mmol/L) and lactate dehydrogenase (12 U/L) were all in the reference range. The cerebrospinal fluid cytology (CSFC) tests showed that the CSF was colorless and transparent, containing 25 × 10The pathogenesis of acute viral encephalitis involves a variety of viruses. Due to the small volume of CSF in children, the diagnosis of encephalitis related pathogens in CSF is very difficult, especially when the clinical symptoms are not obvious. In this case, we firstly test the IgM and IgG antibodies of herpes simplex virus (HSV), because HSV is the main virus that causes viral encephalitis , 20. TheCryptococcus neoformans (CN), neisseria meningitidis (NM), Streptococcus pneumoniae (SP), epstein-barr virus (EBV), varicella-zoster virus (VZV), cytomegalovirus (HCMV), tuberculosis (TB), herpes simplex virus-1 (HSV-1), herpes simplex virus-2 (HSV-2), mycoplasma pneumoniae (MP), Escherichia coli (E.Coli), Listeria monocytogenes (LM), group B streptococcal (GBS), mumps virus (MuV), human herpes virus-6 (HHV-6), Haemophilus influenzae (HI) and acinetobacter baumannii (A.B)  is a molecular technique, which provides an alternative method for high-throughput multiplexed quantitative pathogens related gene expression. AFA integrates multiplex PCR and capillary electrophoresis to offer a simple and effective way to analyze dozens of specific genes in a single tube . In this< 40). Consistent with the previous results, VZV DNA was detected in both CSF and serum  is a kind of molecular biological diagnostic technology, which combined multiplex polymerase chain reaction (PCR) with capillary electrophoresis (CE) together. Usually, the experimental process consists of three parts. Firstly, we extract total nucleic acid of pathogenic microorganisms including both DNA and RNA from samples. Secondly, we amplified the specific region of nucleic acid in pathogenic microorganisms by multiple PCR. Therefore we can obtain several amplification products with dedicated fragment sizes . In this study, we have 18 pairs of specific primers in the reaction fluid, which indicates that we can use the single experiment to screen for 18 common encephalitis related pathogenic microorganisms simultaneously. Last, we separate the fragments with capillary electrophoresis, and each fragment of a specific size represents a specific bacterial or virus infection of interest.As a new type of molecular technique, the key feature of fragment analysis is that multiple microbial infections can be detected at one time using a small volume of sample (300 μl) within approximately 4 h. While in terms of the traditional testing technique, 3–5 ml CSF was needed in pathogenic microorganisms culturing test for more than 2 weeks. Furthermore, thanks to the using of multiple PCR, the amount of nucleic acid which needed in the experiment is far more less than that in traditional PCR technology. On this occasion, the fragment analysis can be also applied to samples with low abundant or low nucleic acid concentration, including cerebrospinal fluid (CSF), feces, and pharynx swabs and so on. This greatly enriched the type of specimens that we can test, and enabled the early diagnosis of a small number of pathogenic microbial infections.In a word, the application of AFA in screening for encephalitis related pathogens in child has many advantages. The whole experiment process is fast, the operation is simple, the sensitivity is high, the species of testing pathogenic microorganism is abundant, and the amount of sample needed is less. All these characteristics make AFA technique to be one of the excellent laboratory methods for detecting bacterial and viral encephalitis in child. Overall, we would recommend the use of AFA analysis as the rapid screening system for the identification and differentiation of encephalitis pathogens in child.