Insertion/deletion polymorphism is a promising genetic marker in the forensic genetic fields, especially in the forensic application of degraded sample at crime scene. In this research, a novel five-dye multiplex amplification panel containing 43 highly polymorphic Insertion/deletion (InDel) loci and one Amelogenin gene locus is designed and constructed in-house for the individual identification in East Asian populations. The amplicon sizes of 43 InDel loci are less than 200 bp, which help to ensure that full allele profiles can be obtained from degraded DNA sample. A series of optimizations and developmental validations including optimization of PCR conditions, detection efficiency of the degraded and casework samples, sensitivity, reproducibility, precision, tolerance for inhibitors, species specificity and DNA mixtures are performed according to the Scientific Working Group on DNA Analysis Methods (SWGDAM) guideline. The results of the internal validation demonstrated that this novel InDel panel was a reliable, sensitive and accurate system with good tolerances to different inhibitors, and performed the considerable detection efficiency for the degraded or mixed samples, which could be used in the forensic applications. Human identification (HID) is one of dominating tasks in the forensic genetic field. Polymerase chain reaction-short tandem repeat (PCR-STR) analyses on capillary electrophoresis platform, which have been regarded as the “gold standard” for HID for more than 20 years , are notInDel is also a kind of length polymorphism that can be analyzed in the polymerase chain reaction – capillary electrophoresis (PCR-CE) platform. InDel loci distribute widely in the human genome. And millions of InDel loci have been identified since they were first discovered in 2006 . InDel g® DIPplex kit  that comprises of autosomal thirty InDel loci and an Amelogenin locus, is now commonly used for forensic HID in different populations  used in forensic genetics were in the range of 100 to 450 bp . InDel gIn the present research, a novel multiplex amplification panel containing one Amelogenin gene locus and 43 highly polymorphic InDel loci is self-developed for the human individual identification in East Asian populations. The amplicon sizes of 43 InDel loci are less than 200 bp, which helps to ensure that full allele profiles can be obtained from degraded DNA sample.Before a novel panel can be applied to the routine laboratory workflow, it is essential to evaluate its performance. In this research, a series of developmental validations were performed to validate the system performance of this novel panel according to the validation guideline of SWGDAM .This research was conducted in accordance with the ethical principle for medical research involving human subjects recommended by the World Medical Association Declaration of Helsinki. Our research was permitted and overseen by the ethics committee of Xi’an Jiaotong University, Health Science Center . Peripheral venous blood samples from 533 unrelated healthy Hui individuals living in northwest region of China were collected. Before the volunteer recruitment, we had plastered the posters which proclaimed our research purpose and basic requirement for the volunteers under the permission and assistance of local directors. We also set up an information desk in different residential communities to publicize our research and attract more people to participate in our research. People who noticed our posters and were willing to learn more about our research came to our sampling sites and proceed the following processes. All volunteers were asked to finish the questionnaire about their health states and then signed the written informed consents before the blood sample collections. All participants declared that they were Chinese Hui people whose families have lived in northwest regions of China for at least three generations. Every participant volunteered for this study and they could withdraw from our study. All data were kept strictly confidential and analyzed anonymously. Professional nurses helped us collect peripheral venous blood. Human tissue collected from autopsies with the consents of their family members and animal organs were used as input DNA in the tests of species specificity, tissues/organs concordances and degraded samples. Animal samples were acquired from experimental animal center of Xi’an Jiaotong University. Execution of experimental animals also followed the animal ethics guideline.1 according to the revised criteria as follows: (1) Candidate InDel loci should be biallelic variations which located on the non-coding regions of autosomes; (2) The allelic frequencies of candidate InDel loci in reference population data sets should be between 0.4 and 0.6; (3) The insertion/deletion sequence length for each allele should be between 2 and 30 bp; (4) Pairwise InDel loci should comply to linkage equilibrium; (5) All candidate InDel loci should show no significant deviations from Hardy–Weinberg equilibrium in reference data sets.Population data of 43 InDel loci from Han Chinese in Beijing (CHB), Southern Han Chinese (CHS), Chinese Dai in Xishuangbanna (CDX), Kinh in Ho Chi Minh City, Vietnam (KHV), and Japanese in Tokyo (JPT) acquired from 1000 Genomes Project Phase 3 (Ensembl release 86) were used as reference population data set . Accordi2. InDel primers were labeled by four different fluorescent dyes , respectively. Org500  was labeled orange and used as internal size standard. InDel primers were synthesized by Microread Genetics, Beijing, China. Allelic ladders of 43 InDel loci this novel panel were constructed by the method of genetic engineering, which followed the method of the published research  under the following conditions: 5 min of initial denaturation at 95°C, followed by 35 cycles of 45 s for 94°C, 60 s for 56°C, and 60 s for 72°C, and then the final extension at 60°C for 60 min. ABI 3500xL Genetic Analyzer  was used to separate the PCR products with POP-4 . Before the electrophoresis, each loading sample containing 8.5 μl of Hi-Di formamide, 1 μl of PCR product  and 0.5 μl of Size Standard Org500 were prepared together. The alleles were genotyped using the GeneMapper ID-X software v1.5 . Control DNA 9947A and 9948, and deionized water were used as positive DNA and negative control, respectively.We established a variety of tests to find out the optimal PCR reaction components and thermal cycling parameters. For each test, 1 μl of control DNA 9948 was used as input DNA. The amounts of Master mixtures and Primer mixtures, annealing temperatures and cycle numbers were adjusted respectively (the tested parameter varied while other parameters were in accordance with the PCR conditions mentioned above). For the tests of different reaction volumes, each experimental volume was enlarged or reduced proportionally based on the 20 μl volume. The tests were performed at the following conditions:Master mixtures: 9, 10, 11, 12, 13, 14, and 15 μl.Primer mixtures: 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, and 0.7 μl.Annealing temperatures: 54, 55, 56, 57, 58, and 59°C.Cycle numbers: 30, 31, 32, 33, 34, 35, and 36.PCR volumes: 5, 10, 15, 20, and 25 μl.A series of tests were performed to evaluate the efficiencies of this InDel panel for the detection of degraded samples. 10 ng of positive control DNA 9948 was digested by DNase I (1U) at 37°C for 0.5, 1, 1.5, 2, 2.5, 3, and 4 min, respectively. Artificial degraded samples were amplified by the novel 43-InDel panel and then the PCR products were genotyped by the CE platform. In addition to the artificially degraded samples, exfoliated cells acquired from fingernails, razor blade, toothbrush, and hair follicle were also analyzed by this InDel panel and Microreader 21ID STR kit , and then the ratios of detected alleles were calculated.® company . To ensure whether consistent genotyping results were acquired when DNA samples of different organs or tissues of the same person were amplified, tissues/organs concordance studies were performed by amplifying the different DNA samples extracted from lung, liver, bone, muscle, thyroid gland, hair follicle, brain, spleen, kidney, heart, blood, pancreas, and fingernail of the same individual.Control DNA 9948 was amplified by the novel 43-InDel panel, and then the purified PCR products were sequenced by the Sanger method to evaluate the genotyping accuracies of amplified fragments. Sanger sequencing was completed by Sangon BiotechA range of amounts of positive control DNA 9948  were made to evaluate the sensitivity of this InDel panel. Each input DNA was genotyped three times. A series of concentration gradients of hematin  and humic acid  were used to evaluate the anti-interference capability of this 43-InDel panel. 1 μl of inhibitors with different concentrations were added to the PCR system, respectively. The amount of positive control DNA 9948 was held constant at 1 ng in different assessments. Nine non-human DNA samples including duck, canine, pig, cattle, sheep, SD rat, Kunming mouse, horse, and pigeon were used to assess the species specificity of this panel. 1 ng of non-human DNA was amplified using 43-InDel panel according to the standard PCR conditions.Ten human blood samples were selected to evaluate the reproducibility of all the 43 InDel loci in this InDel panel. Each test sample was amplified for ten times based on this 43-InDel panel, and then the consistency of each genotyping result was compared. In another reproducibility study, two sets of positive control DNA 9948 were amplified by this panel and detected in two different laboratories independent each other . In the mixture studies, mixed DNA were prepared in which positive control DNA 9947A and 9948  were mixed with different ratios of 19:1, 9:1, 6:1, 4:1, 2:1, 1:1, 1:2, 1:4, 1:6, 1:9, and 1:19 (9947A: 9948).FST) values between Chinese Hui and the reference groups were calculated using Genepop v4 software. Multidimensional scaling (MDS) was conducted based on pairwise FST values using R 3.4.4 software.An online tool–STRAF  was usedAccording to the criteria for InDel selection, we finally chose 43 autosomal InDel loci to construct a multiplex amplification panel. The Amelogenin gene locus was added to the panel to identify the gender. The general information of 43 InDel loci was shown in These 43 InDel loci and one Amelogenin gene locus were divided into four groups according to the actual demand of the multiplex amplification. Primers of these InDel loci were labeled by fluorescent dyes with four different colors: the primers of rs142159306, rs142281120, rs146880183, rs3036240, rs3092307, rs33990282, rs35700881, rs3830564, rs5852131, rs6144473, and rs79287422 loci were labeled by the 6-FAM fluorescent dye (blue); the primers of rs10533337, rs10537321, rs10541072, rs10589141, rs201844336, rs3993057, rs4019986, rs5825145, and rs67941259 loci were marked with the HEX fluorescent dye (green); the primers of rs10544053, rs10555133, rs10573809, rs10584875, rs10588341, rs142392113, rs144537609, rs147682692, rs16646, rs3043804, rs3830885, rs5821525, and rs5892949 were marked by the ROX fluorescent dye (red); and the primers of rs10540867, rs10555434, rs140025863, rs142623177, rs35974596, rs55714089, rs5822909, rs5882232, rs63064161, rs63136060 loci and Amelogenin gene locus were labeled with the TAMRA fluorescent dye (yellow). The final concentrations of each primer ranged from 0.018 to 0.06 μM. Besides, the different fragments containing in the internal standard were labeled using Org500 (orange).2 and buffer. The different amounts of the Master mixtures may influence the PCR efficiency. In this validation experiment, amplification efficiencies were tested with a series of amounts of Master mixtures, and the InDel profiles were shown in Master mixtures – Master mixtures contained essential ingredients for the PCR reaction such as dNTPs, Taq DNA Polymerase, MgClPrimer mixtures – Primer mixtures composed of the forward and reverse primers of 43 InDel loci and the Amelogenin gene locus. An appropriate amount  of all the primers contributed to the high specificity and efficiency of multiplex PCR, so it was essential to study the optimal amount of the Primer mixtures in a novel panel during the process of panel construction. As shown in Annealing temperatures – Annealing temperature is one of the important factors that affect PCR efficiency and product purity. Too high or low annealing temperature can lead to the increase of non-specific PCR products, resulting in lower PCR amplification efficiency . In thisCycle numbers –In this study, 1 ng of template DNA was amplified at 30–36 cycles. In general, corresponding increases in allelic peak heights were observed with the increase of cycle numbers from 30 to 36 cycles. However, imbalance of peak heights was more obvious when the cycle numbers increased. In the routine practice, the cycle number of PCR was associate with the amount of template DNA and expected PCR product. A less cycle number may result in an insufficient amount of PCR product while PCR with too many cycle numbers produced abundant products, which may result in “fluorescent penetrant” phenomenon in the process of capillary electrophoresis. In this research, we chose 35 cycles as recommendatory cycle number when the template DNA was 1 ng.Total volume of PCR – In the PCR volume experiment, 1 ng of control DNA 9948 was used as the template DNA. No amplification failure, allele dropout, or peak height imbalance were observed in the different reaction volumes of 5, 10, 15, 20, and 25 μl, respectively, which indicated that this panel was suitable for the different changes of reaction volumes. However, the small reaction volume was not recommended because it might result in small amounts of PCR product due to evaporation or nonstandard experimental process. So, we suggested the total reaction volume was at least 15 μl, an optimal reaction volume was recommended as 20 μl.In the forensic caseworks, biological samples from criminal scenes usually showed the different degrees of degradation because they were exposed to adverse environments such as light, heat, humidity or microorganism. It was important to develop a panel with high efficiency for the detection of degraded sample, which was also the purpose of the present research. Artificial degraded samples and casework samples were used to evaluate the efficiencies of this panel for detecting degraded samples. In To assess the InDel genotyping accuracy of amplified fragments, alleles of all InDel loci detected in control DNA 9948 were sequenced by the Sanger method. The InDel profiles acquired from the CE platform were consistent with the corresponding results of Sanger sequence, which showed that InDel profiles produced by this panel were accurate. In forensic caseworks, though blood sample was the most common biological material, other biological samples such as hair follicle or bone tissue were often examined as well so that it’s essential to evaluate the suitability of this panel for the detection of different tissues or organs. In the concordance study, genomic DNA templates extracted from 13 different organs or tissues from the same individual were amplified by 43-InDel panel, and then we compared the InDel profiles of different organs/tissues. As shown in For forensic practitioners, it was not easy to acquire sufficient amounts of biological samples from crime scenes so that it’s essential for a panel to have the capacity for the detection of tiny DNA amount. The sensitivity study of this novel InDel panel was conducted by a range of DNA inputs from 15.625 pg to 5 ng. As shown in In addition to the quality and quantity of the input DNA, the tolerance for the inhibitors also influenced the efficiencies of PCR amplification. In the stability study, the control DNA mixed with two different inhibitors were amplified and genotyped by this panel. Humic acid is a kind of component in soil, which may exist in the samples that are buried in soil. Researchers believed that humic acid may bind to DNA templates and result in low amount of available template, which could inhibit the PCR . As showTo ensure that this novel panel showed no cross-reactivity between human and other species, BLAST tool was used to evaluate the species specificity of each primer sequence when we designed the InDel primers. In addition, nine non-human DNA samples were also used to evaluate the species specificity of this panel. The results showed that no peak was detected in these non-human DNA samples, which demonstrated this novel InDel panel performed no cross-reactivity between human and other species.We performed two kinds of reproducibility tests to evaluate the reliability and accuracy of this panel. In the first test, consistent genotyping profiles were obtained for each sample and no allele was off the ladder bin. In the reproducibility evaluation by two different laboratories, coincident profiles were acquired for the same sample, which indicated that this novel panel performed the considerable reproducibility and could acquire reliable profiles in different laboratories.It was necessary for a novel panel to have the ability for the genotyping of mixture DNA. In the mixture study shown in , variousp = 0.05/43 = 0.0012). The insertion allelic frequencies of these 43 InDel loci in Chinese Hui group ranged from 0.3799 (rs55714089) to 0.5891 (rs144537609), with an average value of 0.4815. The He values ranged from 0.4716 (rs55714089) to 0.5005 (rs3993057 and rs10589141), with an average value of 0.4943, which indicated these 43 InDel loci had high genetic polymorphisms in Chinese Hui group. The mean values of MP, PD, PIC, PE, Ho, and He were 0.3802, 0.6198, 0.3719, 0.1852, 0.4965, and 0.4943 respectively. The combined PD and PE values were 0.999999999999999999147246 and 0.999852151, respectively, which indicated that these 43 InDel loci could be used for forensic individual identifications in Chinese Hui group.Allelic frequencies of the novel 43 InDel loci in Hui and reference groups were shown in We investigated the genetic relationships between Chinese Hui and reference groups based on these 43 InDel loci. A heatmap was conducted on the basis of the insertion allelic frequencies of 43 InDel loci to visualize the genetic diversities of these loci, and the result was shown in FST values using R software, and the result was shown in A MDS plot was conducted based on pairwise –15 to 10–13 in European different groups . The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by Ethics Committee of Xi’an Jiaotong University, Health Science Center and Southern Medical University .BZ designed this multiple amplification system and was responsible for all the processes of this research. RJ and WC constructed and validated this multiple amplification system, analyzed the data, and wrote this manuscript. YF and XJ selected these 43 InDel loci. HW and YG assisted the experiments and data analyses. BZ, CC, QL, and XZ revised this manuscript. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


TP53 is the most frequently altered gene in osteosarcoma. Among other genes mutated in more than 10% of OS cases, c-Myc plays a role in OS development and promotes cell invasion by activating MEK–ERK pathways. Several genomic studies showed frequent alterations in the RB gene in pediatric OS patients. Osteosarcoma driver mutations have been reported in NOTCH1, FOS, NF2, WIF1, BRCA2, APC, PTCH1 and PRKAR1A genes. Some miRNAs such as miR-21, -34a, -143, -148a, -195a, -199a-3p and -382 regulate the pathogenic activity of MAPK and PI3K/Akt-signaling pathways in osteosarcoma. CD133+ osteosarcoma cells have been shown to exhibit stem-like gene expression and can be tumor-initiating cells and play a role in metastasis and development of drug resistance. Although currently osteosarcoma treatment is based on adriamycin chemoregimens and surgery, there are several potential targeted therapies in development. First of all, activity and safety of cabozantinib in osteosarcoma were studied, as well as sorafenib and pazopanib. Finally, novel bifunctional molecules, of potential imaging and osteosarcoma targeting applications may be used in the future.Osteosarcoma (OS) is the most frequent primary bone cancer in children and adolescents and the third most frequent in adults. Many inherited germline mutations are responsible for syndromes that predispose to osteosarcomas including Li Fraumeni syndrome, retinoblastoma syndrome, Werner syndrome, Bloom syndrome or Diamond–Blackfan anemia.  Primary bone cancers are a group of rare neoplasms responsible for 3–5% of pediatric cancers and nearly 0.2% of all malignant neoplasms . AccordiThe incidence of OS is characterized by irregular geographic pattern. Low OS prevalence is noted in selected Latin American populations as well as Asian  populations . OS is mOS is a primary malignant neoplasm of the skeleton, affecting mostly the long bones, where sarcoma cells form immature bone or osteoid tissue. It can be divided into subtypes depending on the tumor’s features and predominant stromal differentiation . Depending on the histological appearance, three categories can be distinguished—high-grade, which includes most the subtypes, intermediate-grade and low-grade, including periosteal and parosteal . ConventOS treatment requires a multidisciplinary approach and since the introduction of multimodal chemotherapy to the treatment regimen, the probability of disease-free survival for high-grade OS increased from 10–20% for surgery as the only treatment to more than 60% for multimodal chemotherapy (Chth). The current curative radical treatment combines surgery with multimodal preoperative and postoperative Chth using three or four cytotoxic agents  . HoweverIn the light of developing targeted therapies and increasing the survival rate of other cancers, OS still stands where it was decades ago. Recent interest in understanding the pathophysiology and genetics of osteosarcoma resulted in several genomic studies using whole-genome sequencing (WGS) and/or whole-exome sequencing (WES). The genome analysis led to the identification of genetic heterogeneity, numerous chromosomal abnormalities, mutations and the most down- and upregulated genes, including candidate driver genes ,18,19. AA number of inherited germline mutations are responsible for syndromes that predispose to some neoplasms, including osteosarcomas. There are eight currently known syndromes in which osteosarcoma occurs at an increased frequency—Li–Fraumeni, retinoblastoma, Rothmund–Thomson, RAPADILINO, Werner, Bloom and Diamond–Blackfan anemia .TP53 gene are inherited in an autosomal dominant fashion and responsible for about 70% of the cases of this syndrome. LFS is associated with soft tissue sarcomas, premenopausal breast cancer, brain tumors and many other cancers [TP53 mutation, the symptoms are similar. There are a few clinical classification schemes: Classic LFS [TP53 gene constitute from 14% to 56%. In the group of patients with a germline mutation in TP53, bone tumors were found in 0.7% [TP53 gene may were also reported [CHK2 gene [TP53 gene that is more common in LFS/LFL families from Southeastern Brazil [Li–Fraumeni syndrome (LFS) was described by Frederick Li and Joseph F. Fraumeni Jr. in 1969. The cases involved children that developed rhabdomyosarcoma and had elevated frequency of various types of cancers and leukemias in first- and second-degree relatives . Germlin cancers ,23. In Lssic LFS , Li–Fraussic LFS  and critssic LFS . Osteosassic LFS ,27,28,29 in 0.7% . Thirty-reported . Some LiHK2 gene ,33,34. Gn Brazil ,36.RB1 gene is childhood retinoblastomas; however, in later life there is an increased risk of various neoplasms, especially OS. There are over 180 mutations causing retinoblastoma. The frequency of retinoblastoma is 1 in 18,000 live births [RB1 mutations are also frequently occurring in OS patients, in a range of between 30% to 75% [RB gene caused osteosarcomas as the first detected tumor, without the previous occurrence of retinoblastoma.The primary symptom of germline mutations  in the e births . The exae births . Specifie births . Somatic% to 75% . Recentl% to 75%  where a Syndromes with an increased osteosarcoma risk are caused by germline mutations in genes encoding DNA helicases of the RecQ family. These germline mutations are recessive, and the syndromes they cause are very rare. These are Rothmund–Thomson type II, RAPALIDINO, Werner and Bloom syndromes .Rothmund–Thomson type II (RTS II) and RAPALIDINO syndromes. These two syndromes are both caused by mutations in the RECQL4 gene—that possess single-stranded DNA annealing activity and functions in DNA repair. Analysis of 33 RTS cases revealed an association between RECQL4 gene truncation (but not nonsense or missense point mutations) and osteosarcoma development [elopment .RTS II patients have among others poikiloderma, sparse hair, short stature and cataracts. About 30% of them develop osteosarcomas at age from less than 10 years to 14 years ,41. The RAPALIDINO syndrome  is very rare. The disease is found mainly in Finland, and there are very few cases, but 2/15 cases developed osteosarcoma .Werner syndrome. This disease, which is a progeria syndrome, is caused by mutations in the WRN gene, encoding a RECQ helicase. In contrast to most other osteosarcoma presentations in syndromes, the tumors develop not in children but in patients between the ages of 35 and 57 years. The prevalence of this disease is much higher in Japan  than in the rest of the world . Osteosarcomas are not really frequent, they constituted 7% of tumors in Werner syndrome patients, and the others were soft tissue sarcomas, meningiomas, thyroid cancers, melanomas and myeloid disorders [isorders .Bloom syndrome. This syndrome, first described in 1995 [BLM (RECQL3). It mainly causes carcinomas, leukemias and lymphomas, but the frequency of osteosarcoma is much higher than in the general population [ in 1995 , is relapulation . Bloom spulation .Diamond–Blackfan anemia. This syndrome, in contrast to the previous ones, is due not to a mutation in a tumor suppressor gene or a DNA helicase but is classified as a ribosomopathy—a disease due to a mutation in a gene encoding a ribosomal protein. The condition has varied presentation and only for 50% of cases, the genetic causes are known. The first one to be identified was a mutation in the gene encoding ribosomal protein S19; subsequently mutations in eight other genes encoding ribosomal proteins were discovered. Thirty-three osteosarcomas have been described in 608 cases, which indicates that the syndrome increases osteosarcoma risk [oma risk . In anotoma risk .TP53 is the most frequently altered gene in cancers, also in sporadic OS cases. Mutations in this gene were observed in approximately half of all tumors [TP53 gene) regulates the cycle of cell growth, DNA replication and cell division. When DNA is damaged by ionizing radiation, activation of p53 occurs. Growth signals from oncogenes activate p53. Chemotherapeutic drugs, UV light or protein–kinase inhibitors drive to inhibition of its degradation and increase of its concentration in a cell. p53 protein binds to DNA sequences and activates expression of particular genes. They are involved in cellular processes, like cell-cycle inhibition, apoptosis, genetic stability and vessel formation. These crucial processes are unsettled in cancer cells, and they may result in inactivation of p53 directly by mutation or by inactivation of proteins that interact with p53. Moreover, posttranslational modifications have an impact on structure, stability and function of p53. Inhibiting this regulation by mutations may also drive to tumor development [l tumors ,51. The elopment .TP53 gene are missense mutations and are localized in the DNA binding domain. In osteosarcoma, mutations of TP53 were found with a frequency of about 20% [TP53 gene locus with marked alterations found in osteosarcoma patients derived samples . Mutations in p53 may result in loss of it function or gain-of-function-mutated p53. An example gain-of-function mutation is R175H (dominant negative) that is generally common in broad spectrum of cancers. It was also present in osteosarcoma patients derived samples. In vitro studies suggest that this mutation promotes centrosome amplification connected with disturbing mitosis, cytokinesis and increase of chromosome segregation errors (aneuploidy). Expression of p53 R175H mutant results in reduced occurrence of apoptosis [In several cancers, most mutations in the poptosis ,55 Exprepoptosis . Increaspoptosis TP53 gene, structural variations are frequent in pediatric osteosarcoma. Structural variations (SVs) were mostly translocations with breakpoints within the first intron  and somatic nucleotide variants (SNVs) were found in 74% of osteosarcomas . In the t intron  in whichP53 gene ,59,60,61Mutations in introns  were characterized as splice site changes. Deletion of 31 bp fragment was observed in intron VI to exon 7 and resulted a frameshift effect .There were several interesting rodent animal models with a mutation in TP53 that develop osteosarcoma. In a mouse model with mutation p.R172H (p.R175H in humans) spectrum of tumors that were developed are predominantly osteosarcomas ,65. The RB gene in pediatric OS patients, mostly regarding structural variations and fewer point mutations [RB mutations occur in 70% of sporadic OS cases. The most common alteration is loss of heterozygosity (LOH) at 13q presenting in 60–70% of all cases [RB gene is considered a poor prognostic factor in OS patients [RB alterations include structural rearrangements presenting in 30% of all the cases and point mutations observed in only 10% of cases [INK4 gene deletions and loss of p16 expression [TP53 gene of these cells play a decisive role in proliferation, compromising the maturation, negatively regulating their differentiation and interfering with cellular processes such as ontogenesis [Several genomic studies showed frequent alterations in the utations . RB mutall cases . LOH in of cases . Other cof cases . Approxipression . Walkleypression  showed togenesis .TP53, RB1, CDKN2A, PTEN) are deletion, loss of heterozygosity and mutations. Amplifications of related oncogenes  occur as well [CDK4, MDM2, SAS and other potential oncogenes is present in 10% of osteosarcomas and is associated with ring chromosomes in parosteal OS [CDK4 is highly expressed in OS and its elevated expression correlates with the metastatic potential and is associated with poor outcome, it is considered to be a factor correlating with chemotherapy response. Additionally, CDK4 expression makes tumors more prone to targeted therapy. Inhibition of CDK4 decreases cell proliferation and migration along with arresting the cell cycle and inducing apoptosis in human OS cell lines [During sarcoma genesis, the loss of CDK inhibitors is a common event. Frequent alterations in CDK-related tumor suppressor genes . MYC family genes amplifications are more common in PDS-related OS than primary osteosarcoma . c-Myc pMyc expression in OS tumors correlates with the formation of metastasis and poor prognosis. Using osteosarcoma cell lines U2OS, 143B Chen et al.  showed tTGFB gene) in the pathogenesis of carcinomas depends on the stage of the disease. In premalignant tumors, it can act as a tumor suppressor by increasing the expression of cyclin-dependent kinase inhibitors (mainly p21Cip1 and p15lnk4b) and/or reducing expression of regulator gene c-Myc and proliferative factor cyclin-D. On the other hand, in later stages of the disease, TGF-β plays the role of a tumor promoter, being able to stimulate growth and metastatic progression [It is commonly accepted that the role of transforming growth factor-β , which results in variable gene copy numbers. This type of cancer is distinguished by the amount of gene amplification. It may be due to the fact that these are amplifications generated by chromothripsis. Another phenomenon observed in osteosarcoma, called kataegis, is connected with the arisal of hypermutated regions.TP53 gene [Circulating DNA released from cancer cells carries much important information about changes in its structure such as deletion, insertion or translocation. This information can be easily detected in the blood of patients with osteosarcoma. Attempts to collect such a fluid biopsy and its evaluation were performed for the assessment of mutations in the P53 gene .TP53 or RB gene. Based on the data from the genome analysis, we can distinguish other genes in which changes were observed and which are listed in Recently, much data have been obtained from whole genome sequencing, whole exome sequencing and whole-transcriptome sequencing for OS samples ,18,58,85BTNL9, MMP14, ABCA10, ACACB, COL11A1 and PKM2, but the study was performed on samples derived from 18 patients, so the obtained results should be verified in a larger cohort [In some tumors (approximately 14%) of adult patients, IGF1 receptor amplification was observed . The stur cohort .TP53, NOTCH1, MYC, FOS, NF2, WIF1, BRCA2, APC, PTCH1 and PRKAR1A. However, the potential to induce osteosarcoma in each of the above genes is different. Animal experiments showed that mutations in a pair of genes: WIF1 and BRCA2 resulted in a negligible effect of tumor formation, in contrast to a mutation in a pair of TP53 and NOTCH genes [Attempts are made with the help of functional tests to determine the occurrence of mutations and the order that is necessary for the initiation and development of the disease. Genes whose alteration may lead to cancerous process are summarized in CH genes ,88,89,90RB1, TWIST, PTEN and JUN [Synergistic genes  are those whose independent dysfunction cannot start the cancerous process. Tumor initiation and growth may occur when a synergistic driver coexists with a primary driver, also a synergistic driver could be a germline mutation, then the first driver could be damaged by a somatic mutation. The group of synergistic genes in OS includes  and JUN .Another group that could be potential biomarkers of osteosarcoma are alterations in mRNA or protein expression levels. The candidate biomarker may be cathepsin D. Overexpression of this protein was observed in osteosarcoma tumor samples and samples from lung metastases . Low expCDK4, MDM2, COPS3), gains  or disruption  of driver oncogenes and is localized in chromosomes 5,6,12,13,14,17 [Chromothripsis is a type of genetic abnormality which consists of fragmentation of the chromosomal region and setting it in a new configuration see . It resu13,14,17 ,86.TP53 or ATRX genes, the most frequently mutated genes in OS [The kataegis is a result of elevated mutation prevalence over regions in chromosomes see . In ostees in OS ,99.in vivo study using these cell lines showed a decrease in tumor growth and pulmonary metastases as a result of miR-34a overexpression [Small RNAs have the potential to become prognostic biomarkers of OS  are characterized by the potential to self-renew, high tumorigenicity in nude mice and the ability to efficiently reconstitute all tumor subpopulations as well as the primary tumor phenotype ,121,122.OCT3/4, NANOG and SOX2; TICs are capable of initiating sarcomagenesis ,126. TheOCT3/4 and NANOG), sphere formation and side population properties [+-derived spheres form large tumors in vivo [TICs have been primarily identified in OS over the last 10 years in cell lines, as well as in tissues obtained from tumor surgery. Although the cell biology of OS is still under investigation and needs further research, basic information has been confirmed by different sarcoma study groups. CD133+ cells have been shown to be present in two human primary cultures of OS cells and exhibit stem-like gene expression . Moreover, the CD133+CD44+ cell subpopulation is even more aggressive in terms of sphere formation, migration and invasiveness as well as characterized by high tumorigenicity. High expression of these tumor initiating cell markers has also been reported in clinical samples. Other suggested TIC markers are CD248 , CD117(c-KIT) and CXCR4  markers and retain pluripotent properties in vitro  and sevend CXCR4 . NeverthAdditional markers should also be present on TICs as according to the International Society for Cellular Therapy (ISCT) mesenchymal stem cells (MSCs) should be positive for CD73, CD90 and CD105, but negative for CD34, CD45, CD11b or CD14, CD19 or CD79α and HLA-DR. The transcription factors Oct-4, Sox2 and Nanog are capable of inducing the expression of each other and are essential for maintaining the self-renewing undifferentiated state of cells ,137,138.+ M2 abundance [In OS, as in other tumors, multiple cell–cell interactions between the OS malignant cell and tumor stromal cells are important in tumor development and progression. OS tumor niche is built of OS cells, bone cells , stromal cells , vascular cells , immune cells  and extracellular matrix (ECM) with cytoskeletal proteins and calcifications. Multiple cytokines, growth factors, chemokines as well as their receptors have been reported as significant for OS cells’ proliferation. In autocrine and paracrine mode these molecules stimulate cell division and differentiation of cells including not only OS cells, but also MSCs, osteoblasts and endothelial cells . In OS ibundance . Finallybundance .TP53 gene and activation of the Notch pathway in OS cells. Other studied factors include the CXCR4/CXCL12 pathway, overexpression of ezrin and MET, induction of Src-family tyrosine kinase (SFK) [OS is characterized by its early metastatic potential. At the time of diagnosis, 20% of OS patients have already developed metastases, out of which 90% are lung metastases. The 5-year survival rate of patients with distant metastases drops to only 15–30% . The mecse (SFK) ,162,163.SERPINE2, FHOD3, PAX3, DLX4, FOXQ1, LOX, PCBD1, EHF), whereas 31 genes were downregulated .Many studies screen metastatic and nonmetastatic groups or cell lines for differentially expressed genes (DEGs), revealing heterogeneity between cells with high and low metastatic potential. Muff et al.  analyzedIGFBP5, IGFBP6, WISP3, and MYL2) may play important role in the OS metastatic process. In the study conducted by Li et al. [ALOX5AP, CD74 and FCGR2A—were suggested to be the candidate genes with prognostic value. Interestingly, their expression was higher in the lung and lymph node tissues than, cancer tissues. This indicates that these candidate genes are probably expressed in the microenvironment of the tumor.Results by Tian et al.  using wei et al. , 24 downMost cases of OS are primarily diagnosed by medical imaging due to pain or as an incidental finding. The diagnosis is most often initiated by a classical X-ray check-up and later confirmed by an X-ray CT scan. CT enables an assessment of local tumor size and distant metastases, but soft tissue invasion is less clearly visualized. Therefore, MRI may provide additional information on local tissue infiltration, including locations of arteries or veins and tumor infiltration, intraosseous size of the tumor and size of the soft tissue component, neurovascular structural infiltration and allow to detect metastases. Finally, MRI is also used in patients with contraindications to I-based contrast agents. Dynamic MRI is reliable for evaluating changes in tumor vascularity and to provide additional information on the tumor response to primary chemotherapy. The clinical value of diffusion MRI is currently under evaluation .Several types of new promising approaches are currently in development for imaging of osteosarcomas. First of all, various positron emission tomography (PET) tracers have been proposed in addition to a standard technique based on (18F) fluorodeoxyglucose. One is (18F) sodium fluoride that visualizes calcium metabolic activity and is currently used for detecting bone metastasis . A recenAnother recent approach is based on hyperpolarized MRI tracers. Sensitivity enhancement achieved by hyperpolarization of nuclei of a metabolic tracer offers the possibility of using noninvasive magnetic resonance spectroscopy (MRS) and MRI to measure fluxes through individual enzyme-catalyzed reactions. In sarcoma animal models it was observed that quantitative reduction in lactate production after administration of hyperpolarized pyruvate as monitored by hyperpolarized MRI followed the tumor size changes and was useful for monitoring of therapy in this setting . AnotherFinally, several antibody-based molecular probes are in development, e.g., detecting CXCR4-  or CD105Understanding the molecular mechanisms of osteosarcoma formation and development provides information that allows us to set new targets for the molecular therapy of this type of cancer. Proteomic analyses as well as NGS sequencing that allow the comparison of the proteome and genome in sarcoma cells with normal cells enable the initial selection of potential targets for anticancer therapy . Only a The frequently altered protein p53 is a potential target in osteosarcoma therapy. Despite the many compounds tested in preclinical tests, there are no drugs that restore the function of mutated p53  though aCabozantinib is a vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitor (TKI) that also possesses specific MET receptor inhibitory activity. Its antitumor activity has been shown in experiments on cell lines as well as in vitro models. Besides direct inhibition of osteosarcoma cell growth and viability due to inhibition of ERK and Akt-signaling pathways, cabozantinib can affect the tumor microenvironment by reducing the production of receptor activator of nuclear factor-kB ligand (RANKL) by osteoblasts. This leads to the amelioration of growth-stimulating interactions between osteoblasts and osteosarcoma cells ,177.2 once daily. The study has reached its primary endpoint with 12% of patients with an objective response at six months  and 33% of patients nonprogressing after six months. Overall, 17% of patients had partial responses and 62% stable disease. Median PFS was 6.7 months and median OS 10.6 months. PFS rate at four months was 71% which is much better than 30%, considered as a threshold for promising therapies in osteosarcoma worth further investigations. Interestingly, 65% of patients who underwent metabolic assessment with 18F–FDG PET–CT had a partial metabolic response after the first cycle of cabozantinib what can be considered as a potential biomarker of cabozantinib efficacy in osteosarcoma. The metabolic response was associated with better PFS—patients with response had mPFS of 7.2 months, while patients with stable or progressive metabolic disease had mPFS of 4.5 and 1.8 months, respectively. Cabozantinib was generally well-tolerated. The most common grade 3 and 4 toxicities were hypophosphatemia (7%), AST increase (7%), palmar–plantar syndrome (4%), pneumothorax (9%) and neutropenia (9%) [The activity and safety of cabozantinib in osteosarcoma have been studied in a multicenter, single-arm phase II CABONE trial . The stunia (9%) . The stunia (9%) . AnotherPazopanib is a TKI with a high affinity to VEGFR, as well as activity against PDGFR, KIT and FGFR. Based on the PALETTE trial, pazopanib has been approved for second-line treatment of nonadipocytic soft tissue sarcomas after the failure of standard chemotherapy. Comparing to placebo, it has improved mPFS from 1.6 to 4.6 months.  Data on Sorafenib is a TKi that targets VEGFR, PDGFR, and KIT. In preclinical studies, it has shown some efficacy against osteosarcoma ,188 and Sorafenib has been also tested in combination with mTOR inhibitor, everolimus, in a non-randomized phase 2 trial . PatientTP53, RB, RECQ, WRN or BLM genes are also reported among osteosarcoma patients. In fact, analysis of these genes and syndromes may help understanding the molecular basis for developing this type of sarcoma. In fact, also somatic mutations in osteosarcomas occur in TP53, RB, CDK, TGFB genes. Osteosarcoma cells also carry numerous loss of heterozygosity (LOH) events, which results in variable gene copy numbers in osteosarcoma cells, in particular a high number of gene amplification. These amplifications are expected to occur by chromothripsis. The introduction of NGS and proteomic techniques allowed a better understanding of molecular alteration in OS and is expected to induce the development of new therapies.Osteosarcoma occurrence is high in adolescence and also in adults older than 65 years. Although osteosarcoma occurs mostly in patients without germline mutations, hereditary syndromes associated with mutations in the An important aspect of sarcomagenesis is the contribution of tumor initiating cells. TICs have been identified in OS in cell lines, as well as in tissues obtained from tumor surgery. These cells express various molecular markers, of which CD133 seems to be one of the most important. Other crucial membrane markers are CD44 and CXCR4. Basic information has been established by different sarcoma study groups, but the contribution of TICs to sarcomagenesis and their pathophysiology definitely needs further investigation. This should lead to TIC-targeted therapies in OS treatment.Current osteosarcoma treatment is based on adriamycin chemoregimens and surgery. Several potential targeted therapies in OS are in development. The most advanced trials concern cabozantinib, sorafenib and pazopanib. Nevertheless, these data are only preliminary and new randomized trials are needed for registration and implementation into routine clinical practice. In fact, novel drugs against osteosarcoma are expected and highly needed. It seems that molecular abnormalities currently explored in the field could be used as potential drug targets, including the deregulation of the p53 pathway as well as stem-cell related signaling. Finally, novel bifunctional molecules, of potential imaging and osteosarcoma targeting applications may be used in the future. New molecular imaging methods that are currently developed in vitro and in animal models of osteosarcomas may contribute not only to a better understanding of the pathogenetic mechanisms of this disease, but also to the monitoring of experimental therapies. In particular, approaches that combine therapy and diagnostics  and multimodal molecular imaging could be particularly important in the future. However, to date, only a few studies have exploited targeted imaging or the theranostic approach in OS or animal models of OS.


Diet quality is critical for postpartum type 2 diabetes mellitus (T2DM) progression among women with a history of gestational diabetes mellitus (GDM). The Chinese Healthy Eating Index (CHEI) is a dietary index developed according to the latest Chinese Dietary Guidelines (CDG-2016). Our study aimed to assess the diet quality of women with previous GDM in rural areas of Hunan Province by applying the CHEI. Women with previous GDM in two counties of Hunan were enrolled. Their food intake data, which were used to calculate their CHEI scores, were collected by a 24-h dietary recall. The association of CHEI with sociodemographic and anthropometric variables was evaluated via linear regression models. 404 women were included in the final analysis. The mean score of the total CHEI was 54.9 (SD 7.9). The components of whole grains and mixed beans, seeds and nuts, tubers, dairy, and poultry scored extremely low. Ethnic minority groups and women younger than 30 years had lower CHEI scores. Our study observed an unsatisfactory diet quality among women with previous GDM in rural areas of Hunan Province. Future dietary education focusing on the CDG is needed to improve their diet quality and help in T2DM prevention among this population, especially young and ethnic minority women. Women with previous gestational diabetes mellitus (GDM) have a sevenfold higher risk of type 2 diabetes mellitus (T2DM) progression ,2. To poDiet indices are comprehensive tools used to quantify the diet quality and predict the health outcomes of women with previous GDM ,11. In tThe Chinese Healthy Eating Index (CHEI) was developed in 2017  Table 1Table 1 bChina has witnessed a tremendous increase in the prevalence of T2DM—from 0.67% in 1980 to 10.4% in 2013 . Nearly This study is a baseline survey on the dietary practice of women with a history of GDM. This work is part of a randomized clinical trial ChiCTR1800015023) that aims to examine the effect of intensive lifestyle modifications on physiological health outcomes  for women with previous GDM in rural areas 00015023 , we calcWe chose two study sites located in the eastern and western areas of Hunan Province to represent the different socioeconomic status, lifestyles and ethnic groups in rural regions of Hunan. They are General Hospital of Youxian County and Maternal and Children’s Hospital of Yongding County. Adult women who were previously diagnosed with GDM through their medical records in these sites were introduced to our study by trained nurses. They decided whether to join our study by personal discretion, and those who agreed to participate were required to sign an informed consent form. Women who met any of the following criteria were excluded: diagnosed with T2DM before pregnancy or after delivery, pregnant or lactating, had physical or cognitive disability, or used concomitant drugs that influenced glucose metabolism or weight.All participants were instructed to fill out self-report questionnaires asking for sociodemographic information  and medical history .2 indicates obesity, and 24–27.9 shows overweightness [Anthropometric parameters (body weight and height) were measured and recorded by trained investigators who were graduate students of public health and nurses. Body mass index (BMI) was calculated by dividing the weight (in kilograms) by height (in meters squared). According to Chinese guidelines, BMI ≥28 kg/mightness .The dietary intake of each participant was collected via a 24-h dietary recall administered by trained investigators. Before interviews, the participants were required to take pictures of all the foods (including beverages) consumed in three consecutive days (two workdays and one weekend day). During the interviews, the participants showed the pictures and recalled their food quantities to investigators who filled out forms of 24-h dietary recalls.The nutrient content of the food was estimated using the NutriStar software  based on the 2018 Chinese Food Composition Table, which contains 1506 unique Chinese foods [The Chinese Healthy Eating Index (CHEI) was applied to evaluate dietary quality. Total CHEI score was the sum of scores of 17 components. Investigators assigned 0–5 or 0–10 points to the participants at each component based on their food intake (standard portion/day). For 12 adequacy components , point 0 was assigned for no intake, the maximum point was given where the intake met the recommendation, and the other scores were allotted proportionately. As to the five moderation components , the points were reversed (10–0 or 5–0). Women with complete adherence to the intake recommendation would receive 5 or 10 points. For those who consumed excessively, the more they consumed, the fewer point they received. The full score of CHEI is 100, indicating optimal diet quality that has great consistency with the dietary guidelines. 2 value, which indicated model fitness. To identify the sociodemographic/anthropometric factors of CHEI, we applied linear regression models and included age, ethnicity, education level, occupation status, family income, measures to control GDM, and number of children as potential influential factors. Factors with no significant association with the CHEI score in univariate regression analysis were excluded, and the remaining factors were further included in a multivariate model. Statistical analysis was conducted via SPSS (version 24), p value < 0.05 was considered statistically significant.Continuous variables were described by mean (SD) or median . Categorical variables were summarized with counts and percentages. The Kolmogorov–Smirnov (K–S) test was used to assess whether the total CHEI score and component scores had a normal distribution. If a normal distribution was confirmed, the scores would be described by the mean; otherwise, they would be described by the median. The patients were categorized by terciles of the total CHEI score . To compare the food and nutritional intake among these three groups, we applied one-way ANOVA or the Kruskal–Wallis (K–W) test. ANOVA would be used under circumstances with a homogeneous variance, and the K–W test would be used for heterogeneous variances. The energy and nutritional intake was categorized as insufficient, adequate and excessive by comparing it with CDG-2016’s recommendation, where insufficient intake was defined as less than 90% of EER/RNI or the lower cutoff of AMDR and excessive intake was defined as more than 110% of EER/RNI or the higher cutoff of AMDR. Multiple linear regression (stepwise method) was applied to analyze the association between the CHEI score and dietary nutrients intake. In this analysis, the dependent variable was the CHEI score, and the independent variables were energy, protein, fat, carbohydrate, dietary fiber, iron, zinc, copper, magnesium, selenium, calcium, sodium, phosphorus, iodine, vitamin A, thiamine, riboflavin, vitamin C, vitamin E, saturated fatty acid, monounsaturated fatty acid, polyunsaturated fatty acid, niacin, and cholesterol. The models were deemed significant if ANOVA sig. < 0.05. Among the significant models, we chose the one with the highest RA total of 461 women were enrolled in this study, and 57 were excluded from the final analysis due to the current diagnosis of T2DM or incomplete dietary information. The characteristics of the 404 remaining women are shown in p = 0.200). None of the component scores had a normal distribution. The total CHEI scores ranged from 33.6 to 78.2, with a mean value of 54.9 (SD 7.9). The median value of the component scores is in The total CHEI scores among the 404 participants had a normal distribution . The regression formula was as follows:1, intake of vitamin E; X2, intake of calcium; X3, intake of riboflavin; X4, intake of sodium; X5, intake of saturated fat; X6, intake of zinc; **, residue.The association between the total CHEI score and dietary nutrients was examined by a multiple linear regression test that implied vitamin E, calcium, riboflavin, sodium, saturated fatty acid, and zinc associated with the CHEI score significantly  . The association of CHEI with age and ethnicity was significant in the multivariate model  .As the first study assessing the dietary quality of Chinese women with previous GDM, our study revealed an alarming gap between the optimal and actual dietary quality. Generally, the intake of whole grains and mixed beans, tubers, dairy, fruits, and seeds and nuts was extremely low, whereas red meat and sodium were overconsumed. The average total score of CHEI was only 54.9. Although CHEI does not have cut-off points corresponding to good or poor diet quality, we may refer to the categorization of HEI, namely good, requiring improvement or poor  . Among tn = 257) of the participants ate more than 420 g of white rice every day. Excessive consumption of white rice is related to an increased risk of T2DM. Nanri and Villegas observed a significant increase in T2DM risk in women who consumed more than 300 g/day or 420 g/day of white rice [Chinese diet is characterized by a cereal-based pattern. White rice, commonly made of refined grain, is the daily food for most of the participants (98.0%) in our study. The average intake of white rice was 325.5 g/day; 53.6%  of them reported eating at least five kinds of fruits or vegetables, similar to the results of Kaiser, B. [n = 23,416) revealed that higher level of total carotenoids and vitamin C in plasma are associated with 25% and 18% lower risk of T2DM, respectively [Less than one-fifth of the participants met the CDG’s recommendation for vegetables and fruits, reflecting a very low consumption of these foods. Only 20.7% (iser, B. . A higheiser, B. ,45,46. Aiser, B. ,48,49, siser, B. ,44,45. Eiser, B. ,51,52. Rectively . For manSeveral nutrients, namely vitamin E, calcium, riboflavin, sodium, saturated fatty acid, and zinc, contributed to the CHEI score significantly. Most of these nutrients were consumed improperly. The issue of fat consumption was concerning. In our study, the fat %TE echoed the results in other surveys demonstrating “high-fat” as a character of Chinese dietary patterns in recent years ,54. MoreNearly half of the participants were from minority ethnic groups, and these women presented poorer diet quality than the Han participants. Previous studies show that children in rural and ethnic minority areas in central and western China have lower dietary diversity scores than those of their peers in other areas ,63. InveThis work has several limitations. We collected information relevant to food intake by 24-h dietary recalls. To aid in the food recall, we introduced visual reminders and study nurses, but we could not eliminate memory bias or misreporting. Moreover, this study was conducted in only one province, the participants were geographically concentrated and homogeneous. Thus, the result of our study might not be generalizable to other regions. Finally, although there is emerging evidence of an association between CHEI and metabolic syndrome ,73, we cWe observed an unsatisfactory diet quality among women with previous GDM in rural areas of Hunan Province, as manifested by extreme deficiencies in whole grains and mixed beans, seeds and nuts, tubers, dairy, and poultry, as well as an overconsumption of red meat and sodium. Nutritional intake was generally inappropriate. Ethnic minority groups and women younger than 30 years were more likely to obtain lower CHEI scores. To improve the diet quality and prevent T2DM among women with previous GDM, further dietary education should focus on the latest Chinese dietary guidelines. In rural areas, nutritional knowledge training for primary health workers is crucial, since they are the principal executors of health interventions. Mobile-health interventions, such as Applications providing online dietician consultations and personalized menus, can be integrated into educational schemes to improve health care delivery.


Understanding employees’ feelings at work plays a significant role in developing practical and effective organizational and human resource management policies and practices. Furthermore, work-related emotions may have a considerable effect on workers’ health and wellbeing and affect work effectiveness and work performance. The objectives of the current study were to investigate the relationships among four work-related (WOR) affective feelings (WORAF) and to validate the WORAF questionnaire in a Turkish sample. A survey was performed including four constructs: (1) WOR feelings of happiness, (2) WOR feelings of anxiety, (3) WOR feelings of anger, and (4) WOR feelings of dejection. A total of 322 workers from various companies in Turkey completed a paper-based survey. A research model was developed, and its main components were estimated with partial least squares structural equation modeling (PLS-SEM). The results revealed that dejection and anger at work play a critical role in experienced anxiety in occupational settings. Similarly, dejection, anger, and anxiety at work play a crucial role in perceived happiness at work.  Understanding the roles of employees’ feelings is critical to effective human resource management in contemporary organizations, because most individuals in the population spend more than 50% of their lives at work . A wide Contemporary research has shown that descriptions such as “positive” or “negative” emotions can be replaced by emotion-related terms when they apply to real-life circumstances or situations  . LindebaAlthough emotions or feelings have been studied across numerous epistemology systems, including neuroscience, social psychology, cognitive science, and philosophy, the mechanisms of human affective perception remain poorly understood. Little research has been conducted on the specific roles of feelings, particularly the critical connections of positive and negative emotions in organizations. A substantial research gap exists concerning the relationship between positive and negative feelings at work. Recently, Jaworek et al.  developeConsensus is currently lacking as to what constitutes a feeling, how feelings can be evaluated, or how the effects can be applied in workplaces through the analysis of feelings . ResearcSocial and sociocultural theories posit that feeling as a personal phenomenon clearly lacks the importance of complex social and cultural backgrounds and the internal, communicative role of emotions . FeelingResearchers have examined feelings from psychological and sociological perspectives in the field of organization and organizational research. In this field, the principles of emotional intelligence and feelings at work have been addressed. Emotional intelligence refers to the degree to which one can manage one’s emotions and correctly direct one’s own thoughts and acts ,19. ThisIn general, feeling at work requires workers to control or maintain their emotional behavior, in terms of the substance, frequency, severity, and length of emotions . TherefoVarious definitions have been proposed to explain the concept of happiness at work. For example, Fisher  has statIn view of the above discussion, the relationships among happiness, dejection, anger, and anxiety were explored on the basis of the following seven hypotheses :Hypotheses 1 (H1).There exists a significant negative relationship between dejection and happiness.Hypotheses 2 (H2).There exists a significant negative relationship between anger and happiness.Hypotheses 3 (H3).There exists a significant negative relationship between anxiety and happiness.Hypotheses 4 (H4).There exists a significant positive relationship between dejection and anxiety.Hypotheses 5 (H5).There exists a significant positive relationship between anger and anxiety.Hypotheses 6 (H6).Anxiety mediates the relationship between dejection and happiness.Hypotheses 7 (H7).Anxiety mediates the relationship between anger and happiness.In this cross-sectional study, Turkish employees in different occupations participated in a survey on emotions in the workplace. A cover letter was sent with an invitation to participate in the survey, and an informed consent form was required for participation. The Institutional Review Board of Gazi University, Ankara, Turkey, accepted the survey questionnaire and the experimental protocol (#91610558-604.01.02). The original questionnaire was published in a prior study and validated in a large group of Polish employees in different occupations [The questionnaire was divided into two sections. The first part asked respondents to provide demographic information, such as gender, age, education, occupation, working hours, and work experience. The second part included questions with answers calculated on a four-point Likert scale ranging from (1)  never, to (4)  always. To address missed and unanswered details, the surveys of participants who did not complete all the survey statements were omitted and not included in the final dataset. With the information described above in the questionnaire, the initial set of variables used for model development is described in A total of 575 workers were invited to participate in the research. Of these, 322 respondents (173 (53.7%) male workers and 149 (46.3%) female workers) provided valid surveys, thus resulting in a response rate of 56%. Participants worked in a variety of industries and organizations in Turkey. In the survey, the main occupational groups were as follows: 146 engineers (45.3%), 70 (21.7%) managers, 64 (19.9%) office workers, and 42 (13.1%) people reporting associations with other professions. The age ranged from 19 to 59 years. The age distribution included 56 (17.4%) respondents under 25, 98 (30.4%) between 25 and 30, 136 (42.3%) between 31 and 40, and 32 (9.9%) over 40 years of age. Regarding work experience, 127 (39.4%) of the respondents had worked less than 5 years, 92 (28.6%) had worked between 5 and 10 years, 81 (25.2%) had worked between 11 and 20 years, and 22 (6.8%) had worked more than 20 years . With reDescriptive statistics and frequency analysis of demographic information were performed in IBM SPSS (v.25), and other statistical analyses were conducted in SmartPLS (v.3.3.2) software ,31. Multp ≤ 0.01 level. There was a positive correlation between anxiety and dejection and also between anxiety and anger. In addition, there was a negative relationship between happiness and anxiety and also between happiness and dejection. Multicollinearity was described as a high correlation among two or more constructs [We calculated the means and standard deviations for all research variables as the first step of model testing. A correlation analysis was also performed to determine the relationship between any two variables used in model development . All modnstructs  and was nstructs , all VIFThe validation of the measurement model was performed through assessment of relationships between the constructs and their respective measurement elements with confirmatory factor analysis (CFA). The initial model consisted of several individual items with low indicator loadings . An initTo determine the reliability, validity, and path coefficients of our model, we conducted SmartPLS  analysis. The Cronbach alpha and composite reliability were used for reliability analysis, as suggested by Fornell and Larcker’s  and CronDiscriminant validity, as demonstrated in p-values (p) were obtained to determine whether the hypotheses were appropriate. p-value > 0.05); thus, H1 was rejected;Dejection at work was not statistically significantly associated with happiness at work , thus supporting H2;Anger at work negatively influenced happiness at work , thus supporting H3;Anxiety at work had a significant negative relationship with happiness at work , thus supporting H4;Dejection at work had a significant positive relationship with anxiety at work , thus supporting H5;Anger at work positively influenced anxiety at work , thus supporting H6;Anxiety at work mediated the relationship between dejection and happiness , thus supporting H7.Anxiety at work mediated the relationship between anger and happiness  to measure the validity of path coefficients by using PLS-SEM and to calculate t-test values. After the validation of the measurement model, path coefficients (β), t-values (t), and 2 of the model to assess the amount of change in the dependent constructs caused by the independent variables. We also hypothesized that the set of variables included in the experiment plays a key role in feelings at work. From the findings of the research and bootstrapping results, we inferred that dejection and anger at work play a key role in anxiety at work. Changes in dejection and anger at work were found to affect anxiety, with R2 = 0.607. That is, anxiety was affected by dejection and anger at work, with a contribution of 60.7%. Likewise, dejection, anger, and anxiety at work were found to play a crucial role in happiness, with R2 = 0.270 (We also calculated the R = 0.270 .As anger at work increases, happiness at work decreases.As anxiety at work increases, happiness at work decreases.As dejection at work increases, so does anxiety at work.As anger at work increases, so does anxiety at work.Anxiety at work mediates the relationship between dejection and happiness at work.Anxiety at work mediates the relationship between anger and happiness at work.The findings of the study demonstrate the patterns illustrated in The theoretical findings and outcomes of our study are supported by empirical experiments performed with a dimensional approach, thus suggesting that three of the observed work-based feelings are closely linked ,40,41.Overall, the current results are encouraging and enable further studies to be performed by using the measuring instrument applied herein. The WORAF included only the affective states selected in this study. Further studies examining different forms of work-related emotions, including remorse, embarrassment, envy, optimism, ambition, sympathy, and even love, should also be performed, as proposed by other researchers . BecauseThe findings of several studies ,44,45 inAn essential part of emotional regulation requires understanding the relationships among four work-related affective feelings investigated in the current study. Organizations can use such knowledge to manage emotions at work and mitigate their potential adverse effects by developing effective strategies for success, including higher leadership effectiveness, prevention of employee burnout, and increased job performance.This research’s primary objectives were to validate the WORAF questionnaire in a sample of employees in Turkey and assess the relationships among four work-related emotions: happiness, anxiety, anger, and dejection. A cross-sectional quantitative methodology with a correlational design was used for this purpose. The study results revealed that dejection and anger at work play a critical role in expressing anxiety at work. Changes in dejection and anger at work were found to affect anxiety. Similarly, dejection, anger, and anxiety at work were found to be related to the level of happiness. It is concluded that the WORAF scale can improve the understanding of individuals’ emotional functioning in work environments.It should be noted that all the study participants were Turkish, so that these findings cannot be generalized to include other nationalities. Therefore, additional WORAF-scale-based investigations using working communities other than Turkish workers are strongly recommended. Further studies on affective feelings at work should be based on both situational and permanent dimensions and should aim to incorporate interventions within and between individuals. The WORAF scale could also be used to develop similar instruments to assess other affective states concerning particular conditions at work. Finally, gender differences in emotion management in the workplace should also be examined.


Response to the treatment and prognosis, especially of NS, depend on precise diagnosis with a necessity for discovery of new biomarkers. We aimed to perform comprehensive in silico analysis at the DNA, RNA, and protein levels of six prospective  and six known TGCT biomarkers  and assess its congruence with histopathological analysis in all forms of TGCTs. Cancer Hallmarks Analytics Tool, the Search Tool for the Retrieval of Interacting Genes/Proteins database, and UALCAN, an interactive web resource for analyzing cancer OMICS data, were used. In 108 TGCT and 48 tumor-free testicular samples, the immunoreactivity score (IRS) was calculated. SE showed higher frequency in DNA alteration, while DNA methylation was significantly higher for all prospective biomarkers in NS. In GCNIS, we assessed the clinical positivity of RASSF1 and PRSS21 in 52% and 62% of samples, respectively, in contrast to low or nil positivity in healthy seminiferous tubules, TGTCs as a group, SE, NS, or all NS components. Although present in approximately 80% of healthy seminiferous tubules (HT) and GCNIS, HOXA9 was diagnostically positive in 64% of TGCTs, while it was positive in 82% of NS versus 29% of SE. Results at the DNA, mRNA, and protein levels on putative and already known biomarkers were included in the suggested panels that may prove to be important for better diagnostics of various forms of TGCTs.Testicular germ cell tumors (TGCTs) are ever more affecting the young male population. Germ cell neoplasia  Testicular germ cell tumors (TGCTs) represent the most common malignancy among males between 15-45 years of age in Caucasian populations , accordiin situ) [TGCTs are a very heterogeneous group of neoplasms divided into seminomas (SE) and nonseminomas (NS). Pure SE are the most frequent and account for about 55% of all TGCTs in patients with a median age of 35. NS accounts for about 45% of all diagnosed TGCTs in patients with a median age of 25 . A TGCT in situ)  which arin situ) .SE always consists of undifferentiated cells and arises as a pure form . NS consDespite histological heterogeneity, most TGCTs have the same genetic hallmark and additional genetic material on chromosome 12p . Its bioAside from genetic anomalies, epigenetic changes seem to play an important role in the development of TGCTs . Indeed,Immunohistochemical analysis is the main molecular tool used in diagnostics of TGCT, especially to differentiate the components of TGCT . As ChovOCT4, c-KIT, NANOG, SOX2, SOX17, and SALL4) and six as prominent biomarkers . Most of the already known TGCT biomarkers, OCT4, NANOG, SOX2, SOX17 [SALL4 [KIT along with KITLG is expressed in PGCs, and their interaction plays a crucial role in the migration process [RASSF1 and MGMT were concentrated on epigenetic alterations [RASSF1 was not investigated yet, while MGMT expression was reported in TGCT. The methylation patterns of HOXA9 and CFC1 were already investigated as potential TGCT markers [Based on the critical review of the literature, 12 TGCT-related genes were chosen for this study, six of which are already used in histopathological diagnostics of TGCTs  and in the healthy tissue has a crucial role in hematopoiesis. Overexpression of HOXA9 is associated with poor prognosis of acute myeloid leukemia (AML) [CFC1 is important during embryonal development. Expression of CFC1 in adult tissue is associated with various cancers, e.g., pancreatic cancer, colon cancer, and gall bladder cancer [PRSS21 in tumors is still unknown, but it is hypothesized to be a tumor suppressor [PRSS21 protein expression in TGCT has not yet been done, although its DNA methylation and gene expression status in SE and NS are extensively investigated [MAGEC2 belongs to the MAGE family which codes for cancer-testis antigen. They are located on the X chromosome and involved in normal tissue development as well as in tumorigenesis of various tumors [MAGEC2 expression is restricted to male germ cells and is not found in adult somatic cells. The protein expression of MAGEC2 in adult testicular tissue was reported as a novel sensitive marker for SE almost 10 years ago [ia (AML) . CFC1 isr cancer . The funppressor . To our stigated . MAGEC2 s tumors , 39. MAGears ago , while iPrecise diagnosis of TGCT is of great importance. Diverse histology and morphology of each individual TGCT component present in the patient which is often in the form of a MGCT require different treatments and management of the TGCT components  which main silico analysis at the DNA and RNA levels of, above-described, six prospective  and six recognized TGCT biomarkers . We further assessed the congruence of in silico results with histopathological analysis in all forms of TGCTs and healthy tissue. The findings of this study could elucidate on which molecular level and between which tissue types TGCT-related genes are discriminative.Therefore, in this study, we have investigated the molecular profile of selected genes in all relevant tissue types, i.e., healthy testicular seminiferous tubule tissue (HT), GCNIS, TGCT, SE, and NS, as well as NS components. We performed comprehensive To identify functional interactions between selected genes, their coexpression, gene enrichment and functional analysis, the Search Tool for the Retrieval of Interacting Genes/Proteins database , and Cytoscape 3.7.2 were used . The STRCancer Hallmarks Analytics Tool (CHAT) was used to determine the most evident cancer-related process for each selected gene. Based on the determined cancer-related process, selected genes were assigned to the specific hallmark of cancer according to the hallmarks of cancer (HoC) taxonomy of Baker et al. .The study was conducted according to the Declaration of Helsinki. The Ethics Committee of School of Medicine University of Zagreb, Sestre Milosrdnice University Hospital Center, and University Hospital Centre Zagreb approved the collection and manipulation of all tissue samples.In total, 108 GCNIS-related TGCT samples and nine tumor-free testicular samples were retrieved from the Tumor Registry at Sestre Milosrdnice University Hospital Center and University Hospital Centre Zagreb from a 20-year period (1999-2018). Tumor samples were routinely processed in the pathohistological laboratory and stored in the form of paraffin blocks, which were further analyzed. Three pathologists performed pathologic examination of routine hematoxylin-eosin–stained sections on each case. Cases were reevaluated, and histological subtypes of TGCT tumors were described . The extent of the heterogeneous component was assessed as a percentage of the tumor, and a joint committee resolved all doubts.Out of 108 TGCT archive samples, 52 were SE and 56 were NS . Seminiferous tubules with preserved spermatogenesis from TGCT samples (ST TGCT) and tumor-free testes (ST TF) were used as the joined control group (HT) , since nμ and deparaffinized. Antigen retrieval was performed with Tris-EDTA (pH 9) or citrate buffer (pH 6). Subsequently, sections were incubated with 10% BSA for 20 minutes. Then, sections were incubated with 12 primary antibodies . The signal was visualized with chromogen DAB . Slides were counterstained with hematoxylin, imbedded, and analyzed under Olympus Bx53. Appropriate positive and negative controls were used in staining.Samples were cut at 4 in situ, and tumor tissue. Staining signal (brown in color) was noted as nuclear, cytoplasmic, or membranous in tumor cells (TC), depending on the expected protein location. Staining percentage was scored from 0 to 5: 0 (negative TC), 1 (>1-≤10% positive TC), 2 (>10%-≤25% positive TC), 3 (>25%-≤50% positive TC), 4 (>50%-≤75% positive TC), and 5 (>75% positive TC). Intensity of staining was assessed (none-low-medium-high). Semiquantification of protein expression was expressed by the immunoreactivity score (IRS) which was calculated by multiplying staining percentage (0-5) and intensity of staining (0-3) creating a range of 0-15. Statistical analysis of protein expression was performed by GraphPad Prism software . Results were considered statistically significant when p < 0.05.Three pathologists performed morphometric analysis of the investigated genes for protein expression. A joint committee resolved all disagreements. Expression of proteins was analyzed in components of seminiferous tubules with apparent spermatogenesis, germ cell neoplasia To calculate diagnostic positivity, a cut-off value of IRS 4 was used, with IRS scores 0-3 being declared negative and scores 4+ being declared positive (at a minimum more than 10% positive cells with medium intensity staining), and the percentage of positive samples was calculated per component and gene of interest.vs. tumor tissue, and 165 samples were present in the GTEx study and 154 in the TCGA study. Welch's t-test was used to detect statistically significant differences between the two.For a comparative analysis of gene expression between healthy testis tissue and TGCT, data from the UCSC RNA-seq Compendium was used, where TCGA and GTEx samples are reanalyzed  by the same RNA-seq pipeline. Because all samples are processed using a uniform bioinformatic pipeline, a batch effect due to different computational processing is eliminated. UCSC XENA software was used , 46. Genvs. NS comparative analysis of gene expression was done using UALCAN, a comprehensive, user-friendly, and interactive web resource for analyzing cancer OMICS data [https://gdc.cancer.gov/). Sample gene expression data was matched to the TGCT histological type of 133 TGCT patients. Promoter DNA methylation data was matched to the TGCT histological type. DNA methylation was represented as β values, which range from 0 (nonmethylated) to 1 (fully methylated) and are calculated by the ratio of methylated and unmethylated probe signal intensities. Student's t-test with considered unequal variance was used to detect statistically significant differences between groups.SE ICS data . Level 3t-test with considered unequal variance was used to detect statistically significant differences between groups.UALCAN was used to compare promoter DNA methylation levels between SE and NS. Promoter DNA methylation data were obtained from the TGCT GDC of 133 TGCT patients. Promoter DNA methylation data was matched to the TGCT histological type. Student's From The Cancer Genome Atlas project, 149 TGCT samples were analyzed for alterations in the 12 target genes as well as alterations in the 12p chromosome using cBioPortal for cancer genomics . NonsynoCFC1, PRSS21, and MAGEC2 not being connected to it , SOX2, and NANOG activating genes related to proliferation; for UniProt keywords: disease, transcription regulation, and developmental protein; and for GO processes: regulation of cellular processes, cell differentiation, spermatogenesis, signal transduction, and positive regulation of gene expression . Text mining analysis of the selected genes showed their primary involvement in six pathways of cancer hallmarks: genome instability and mutations , inducing angiogenesis (PRSS21 and SOX17), replicative immortality (HOXA9 and OCT4), invasion and metastasis (NANOG and MAGEC2), sustaining proliferative signaling (SOX2), and resisting cell death (RASSF1)  .HOXA9, SOX2, KIT, MGMT, SALL4, SOX17, PRSS21, and NANOG) across 28% of the TGCT samples, with KIT alterations alone making up 15% and NANOG constituting an additional 7%  and assess the percentage of various DNA alteration types for genes of interest. Then, we compared protein expression and its diagnostic positivity for genes of interest, not only in the SE and NS groups but also in all possible components of NS that have different prognostic values.KIT makes up 30% of alterations in SE and 4% in NS samples and NANOG 7% in SE and 7% in NS samples. DNA alterations for other genes were scarce. Among them, MGMT showed deep deletions, while SOX2, SOX17, NANOG, and HOXA9 showed amplifications. There were no data on DNA alterations for SALL4 and PRSS21 . SE has shown higher expression than NS in RASSF1, KIT, SOX17, and MAGEC2, while NS has shown higher expression than SE in HOXA9, SOX2, and CFC1B (SOX17-c-KIT (p < 0.001) and POU5F1-SOX2 (p < 0.002), which confirms the distinct SE and EC profiles, with SE having SOX17-c-KIT and EC having POU5F1-SOX2 coexpression.Gene expression has shown no difference in expression between SE and NS in five of the 12 selected genes (nd CFC1B . Gene coHOXA9 and SOX2) was found more in samples of NS than in those of SE: 82% for HOXA9 in NS versus 29% in SE and 17% for SOX2 in NS versus 0% in SE. On the contrary, diagnostic positivity for another six genes was found more in SE samples than in NS samples: 68% for OCT4 in SE versus 29% in NS, 98% for SALL4 in SE versus 65% in NS, 79% for KIT in SE versus 0% in NS, 46% for SOX17 in SE versus 1% in NS, 85% for NANOG in SE versus 23% in NS, and 15% for MAGEC2 in SE versus 0% in NS  in SE than in NS was out of line with DNA methylation being also lower in SE and higher in NS. Considering SOX2, expression was lower in SE than in NS, but DNA methylation levels were similar, while for SOX17, expression was higher in SE and DNA methylation levels were also similar. For PRSS21, no differences in expression were found, although DNA methylation level was higher in NS. Considering OCT4, MGMT, and NANOG, the mRNA level was similar in SE and NS, although protein expression and DNA methylation were higher and lower, respectively, in SE and vice versa in NS. Protein expression and DNA methylation levels of SALL4 in SE were higher than those in NS, but mRNA levels were similar in SE and NS. CFC1 DNA methylation level and mRNA expression in SE were lower than those in NS, but protein expression was similar.Coherence in DNA methylation levels, mRNA expression, and protein expression was found only for on in NS . For HOXOCT4, SOX2, and NANOG. EC and YST both have had increased protein expression of SALL4, while all four components have had a high level of protein expression in HOXA9. CH has shown increased protein expression in PRSS21   .From the analyzed DNA alterations, the gain on the 12p chromosome was incorporated in the TGCT panel due to its confirmed overwhelming presence in TGCT samples .HOXA9, RASSF1, MGMT, CFC1B, PRSS21, and MAGEC2) (DNA methylation markers were chosen because they expressed the sharp distinction between methylation in NS and demethylation in SE ( MAGEC2) .vs. TGCT and SE vs. NS) were selected. Therefore, mRNA biomarkers that may be classified for the TGCT group are OCT4 (POUF1), SALL4, NANOG; for SE, SOX17, c-KIT, and MAGEC2; and for NS, SOX2 , mRNA level, and protein level. Taking all into account, we organized our results in four panels. The panel specific for the GCNIS that has a highly treatable proposed origin of TGCTs might prove to be of utility for much needed early diagnostics [Association of gnostics . The nexgnostics  , and no protein marker is specific enough for the detection of GCNIS cells by noninvasive methods such as immunocytochemistry in body fluids [RASSF1A and PRSS21 (testisin) protein expression, in comparison to both healthy seminiferous tubules and TGCT as a group; however, they have not made the 70% diagnostic positivity cut-off for the inclusion in the diagnostic panel. We also confirmed similar differences in protein expression for the already known GCNIS biomarkers: OCT4, SOX17, c-KIT, and NANOG. The biomarker SALL4, although highly expressed in GCNIS, showed no significant difference in expression in TGCT as a group and therefore was not included in our panel as highly discriminative for GCNIS in comparison to HT and the TGCT group. The combination of expressed genes HOXA9 and c-KIT on the protein level was selected for the GCNIS panel due to their high diagnostic positivity. Indeed, the combination of HOXA9 and c-KIT easily discriminates GCNIS from TGCTs.So far, early clinical GCNIS diagnostics are done only y fluids , 48. Ourin silico research confirmed an almost ubiquitous gain of the short arm of chromosome 12 in TGCTs that prompted us to include it in the TGCT panel. It is noteworthy that such gain was described only in GCNIS proximal to TGCTs and was absent from distant GCNIS [NANOG is located on the 12p chromosome but its alteration frequency in TGCT was rather low or not detected. We confirmed the highest alteration frequency for c-KIT, located on chromosome 4p, while other genes of our interest had a noninvasive rather low frequency of alterations or no alterations. Therefore, DNA alterations of those genes do not seem to be the drivers of TGCTs but are probably only passenger mutations that are estimated to occur in 99.9% of mutations found in cancer [Our nt GCNIS . Among tn cancer .OCT4, NANOG, and SALL4 displayed great discriminative potential in comparison to those in HT, which is in accordance with their involvement in malignant transformation of the cells [OCT4 and NANOG (stemness or pluripotency genes) in cancer hallmarks mainly enable the tumor replicative immortality and invasion that are crucial for tumor survival and growth [SALL4 is known for its essential role in maintaining the pluripotent state and self-renewal properties of embryonic stem cells (ESCs) [SALL4 in an adult testis is primarily associated with genome instability and mutations during tumor progression (invasion and metastasis) which may be important to explain DNA alterations found in TGCTs  . Unexpecin TGCTs . Decreasor genes  in TGCT.In silico-obtained results on DNA methylation of genes of our interest showed that the promoter of almost every gene was hypermethylated in NS and hypomethylated in SE, which is in congruence with the previously reported results on hypermethylation of the NS genome in comparison to the hypomethylation of the SE genome [PRSS21, CFC1, MAGEC2, MGMT, HOXA9, and RASSF1, which discriminated SE from NS, were included in our panels. Importantly, DNA methylation of HOXA9, CFC1, RASSF1, and MGMT has taken together displayed high accuracy in distinguishing SE from NS [MAGEC2, a previously reported sensitive protein SE biomarker [E genome . Therefo from NS . MAGEC2,iomarker  that hasSALL4 promoter, which was hypomethylated in NS and hypermethylated in SE, but at the mRNA level, no difference was found, implying other types of regulation of SALL4 gene expression.The only exception among the genes of our interest was the HOXA9 was upregulated in contrast to its downregulation in other three genes [We may conclude that the difference in the DNA methylation pattern of a significant number of genes that we described should be discriminative enough for diagnostics of SE versus NS similar to that recently proposed for lung adenocarcinoma where the methylation in ee genes . Importaee genes , 58 haveee genes .SOX2, KIT, SOX17, and MAGEC2 genes on the mRNA level also differs significantly between SE and NS. Increased mRNA expression of SOX2 in NS is in accordance with the theory that NS arises from blocked PGC by retaining an early embryonic marker profile among highly differentiated NS components [c-KIT and SOX17 in SE make them promising biomarkers on the mRNA level, especially because they are used in routine diagnostics of TGCT by immunohistochemistry [Expression of mponents . Our reshemistry . This suHOXA9 is significantly more expressed in NS in comparison with SE with clinical positivity in 82% of NS samples in contrast to 29% in SE. However, HOXA9 expression was not correlated with an assessed highly discriminative potential on the DNA methylation level, suggesting that there is more to the regulation of gene expression than just DNA methylation at work [vs. NS development, having in mind that it is primarily included in replicative immortality cancer hallmarks. We confirmed that protein expression of KIT is discriminative enough to be used even individually for SE diagnosis, while SOX17 and SOX2 could be used in differentiating SE from NS alongside OCT4 as previously proposed [MAGEC2, which was described as a biomarker for SE [At both protein and RNA levels, we found out that  at work . This diproposed . MAGEC2,r for SE , in our in silico and merged with our data of gene expression on a protein level. In fact, to our knowledge, no database presents data on an individual NS component, but rather for the whole NS group as a single entity, regardless of different biological and clinical features of EC, TE, YST, and CH. This standard of data representation obscures the differences within the NS group that could be further exploited in developing discriminatory biomarkers between them.For each single NS component panel, we used only our IHC data because of the lack of data on a single NS component that could be analyzed OCT4 and NANOG as biomarkers for EC [SOX2 was noticed in EC as well, although it was below our IRS cut-off level. However, we may confirm its use in combination with OCT4 and NANOG, already in the clinical practice [SALL4 protein is a good marker for YST in conjunction with the lack of OCT4, NANOG, and SOX2 protein expression [Our results confirm s for EC  because practice . Accordipression .Although teratoma is composed of differentiated cells or tissues, it has malignant potential as a part of the NS group and is very rare in its pure form. In addition, in our protein expression panel, there is no unique marker characteristic for this component, which is expected due to the heterogeneity of teratoma components. It seems that microRNAs of the miR-371-373 cluster do not discriminate teratomas and a professional histopathological analysis is still required for the assessment of mature (MT) and immature teratomas (IT) as a pure TGCT form or as an NS component with other histological germ cell subtypes  or with a somatic malignant component  as exemplified by the research of Terenziani et al. .HOXA9 while all the other markers were negative [CH is the rarest and most aggressive form of the NS group, whether it occurs in pure or MGCT form. It gives hematogenous metastases very early in tumor progression with a testicular mass being small or even “burned-out.” In our panel, the CH component showed positive expression of negative .MAGEC2, PRSS21, and CFC1 being unconnected to it implies that there are more related genes in the network, some of which could be potential biomarkers.Using a combination of standard clinical biomarkers and promising new TGCT biomarkers, we propose a diagnostic flowchart that distinguishes healthy tissue, GCNIS, TGCT, and TGCT individual components from each other, at least at one molecular level of the central dogma axis, and our panels, therefore, represent a proposal for “multianalyte tests that could be used to detect early cancers in a highly sensitive manner” . Among t