Co-evolution of vaginal microbiome and cervical cancer.

BACKGROUND: Exploration of adaptive evolutionary changes at the genetic level in vaginal microbial communities during different stages of cervical cancer remains limited. This study aimed to elucidate the mutational profile of the vaginal microbiota throughout the progression of cervical disease and subsequently establish diagnostic models. METHODS: This study utilized a metagenomic dataset consisting of 151 subjects classified into four categories: invasive cervical cancer (CC) (n = 42), cervical intraepithelial neoplasia (CIN) (n = 43), HPV-infected (HPVi) patients without cervical lesions (n = 34), and healthy controls (n = 32). The analysis focused on changes in microbiome abundance and extracted information on genetic variation. Consequently, comprehensive multimodal microbial signatures associated with CC, encompassing taxonomic alterations, mutation signatures, and enriched metabolic functional pathways, were identified. Diagnostic models for predicting CC were established considering gene characteristics based on single nucleotide variants (SNVs). RESULTS: In this study, we screened and analyzed the abundances of 18 key microbial strains during CC progression. Additionally, 71,6358 non-redundant mutations were identified, predominantly consisting of SNVs that were further annotated into 25,773 genes. Altered abundances of SNVs and mutation types were observed across the four groups. Specifically, there were 9847 SNVs in the HPV-infected group and 14,892 in the CC group. Furthermore, two distinct mutation signatures corresponding to the benign and malignant groups were identified. The enriched metabolic pathways showed limited similarity with only two overlapping pathways among the four groups. HPVi patients exhibited active nucleotide biosynthesis, whereas patients with CC demonstrated a significantly higher abundance of signaling and cellular-associated protein families. In contrast, healthy controls showed a distinct enrichment in sugar metabolism. Moreover, biomarkers based on microbial SNV abundance displayed stronger diagnostic capability (cc.AUC = 0.87) than the species-level biomarkers (cc.AUC = 0.78). Ultimately, the integration of multimodal biomarkers demonstrated optimal performance for accurately identifying different cervical statuses (cc.AUC = 0.86), with an acceptable performance (AUC = 0.79) in the external testing set. CONCLUSIONS: The vaginal microbiome exhibits specific SNV evolution in conjunction with the progression of CC, and serves as a specific biomarker for distinguishing between different statuses of cervical disease.

Genomic analyses of a new baculovirus isolated from the wheat armyworm, Mythimna sequax (Franclemont) (Lepidoptera: Noctuidae).

We report the genomic analysis of a novel alphabaculovirus, Mythimna sequax nucleopolyhedrovirus isolate CNPSo-98 (MyseNPV-CNPSo-98), obtained from cadavers of the winter crop pest, Mythimna sequax Franclemont (Lepidoptera: Noctuidae). The insects were collected from rice fields in Southern Brazil in the 1980's and belongs to the 'EMBRAPA-Soja' Virus Collection. High-throughput sequencing reads of DNA from MyseNPV occlusion bodies and assembly of the data yielded an AT-rich circular genome contig of 148,403 bp in length with 163 annotated opening reading frames (ORFs) and four homologous regions (hrs). Phylogenetic inference based on baculovirus core protein sequence alignments indicated that MyseNPV-CNPSo-98 is a member of Alphabaculovirus genus that clustered with other group II noctuid-infecting baculoviruses, including viruses isolated from Helicoverpa armigera and Mamestra spp. The genomes of the clade share strict collinearity and high pairwise nucleotide identity, with a common set of 149 genes, evolving under negative selection, except a bro gene. Branch lengths and Kimura-2-parameter pairwise nucleotide distances indicated that MyseNPV-CNPSo-98 represents a distinct lineage that may not be classified in any of the currently listed species in the genus.

A Predictive Noninvasive Single-Nucleotide Variation-Based Biomarker Signature for Resectable Pancreatic Cancer: Protocol for a Prospective Validation Study.

BACKGROUND: Single-nucleotide variations (SNVs; formerly SNPs) are inherited genetic variants that can be easily determined in routine clinical practice using a simple blood or saliva test. SNVs have potential to serve as noninvasive biomarkers for predicting cancer-specific patient outcomes after resection of pancreatic ductal adenocarcinoma (PDAC). Two recent analyses led to the identification and validation of three SNVs in the CD44 and CHI3L2 genes (rs187115, rs353630, and rs684559), which can be used as predictive biomarkers to help select patients most likely to benefit from pancreatic resection. These variants were associated with an over 2-fold increased risk for tumor-related death in three independent PDAC study cohorts from Europe and the United States, including The Cancer Genome Atlas cohorts (reaching a P value of 1×10-8). However, these analyses were limited by the inherent biases of a retrospective study design, such as selection and publication biases, thereby limiting the clinical use of these promising biomarkers in guiding PDAC therapy. OBJECTIVE: To overcome the limitations of previous retrospectively designed studies and translate the findings into clinical practice, we aim to validate the association of the identified SNVs with survival in a controlled setting using a prospective cohort of patients with PDAC following pancreatic resection. METHODS: All patients with PDAC who will undergo pancreatic resection at three participating hospitals in Switzerland and fulfill the inclusion criteria will be included in the study consecutively. The SNV genotypes will be determined using standard genotyping techniques from patient blood samples. For each genotyped locus, log-rank and Cox multivariate regression tests will be performed, accounting for the relevant covariates American Joint Committee on Cancer stage and resection status. Clinical follow-up data will be collected for at least 3 years. Sample size calculation resulted in a required sample of 150 patients to sufficiently power the analysis. RESULTS: The follow-up data collection started in August 2019 and the estimated end of data collection will be in May 2027. The study is still recruiting participants and 142 patients have been recruited as of November 2023. The DNA extraction and genotyping of the SNVs will be performed after inclusion of the last patient. Since no SNV genotypes have been determined, no data analysis has been performed to date. The results are expected to be published in 2027. CONCLUSIONS: This is the first prospective study of the CD44 and CHI3L2 SNV-based biomarker signature in PDAC. A prospective validation of this signature would enable its clinical use as a noninvasive predictive biomarker of survival after pancreatic resection that is readily available at the time of diagnosis and can assist in guiding PDAC therapy. The results of this study may help to individualize treatment decisions and potentially improve patient outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54042.

Developmental dyslexia susceptibility genes DNAAF4, DCDC2, and NRSN1 are associated with brain function in fluently reading adolescents and young adults.

Reading skills and developmental dyslexia, characterized by difficulties in developing reading skills, have been associated with brain anomalies within the language network. Genetic factors contribute to developmental dyslexia risk, but the mechanisms by which these genes influence reading skills remain unclear. In this preregistered study (https://osf.io/7sehx), we explored if developmental dyslexia susceptibility genes DNAAF4, DCDC2, NRSN1, and KIAA0319 are associated with brain function in fluently reading adolescents and young adults. Functional MRI and task performance data were collected during tasks involving written and spoken sentence processing, and DNA sequence variants of developmental dyslexia susceptibility genes previously associated with brain structure anomalies were genotyped. The results revealed that variation in DNAAF4, DCDC2, and NRSN1 is associated with brain activity in key language regions: the left inferior frontal gyrus, middle temporal gyrus, and intraparietal sulcus. Furthermore, NRSN1 was associated with task performance, but KIAA0319 did not yield any significant associations. Our findings suggest that individuals with a genetic predisposition to developmental dyslexia may partly employ compensatory neural and behavioral mechanisms to maintain typical task performance. Our study highlights the relevance of these developmental dyslexia susceptibility genes in language-related brain function, even in individuals without developmental dyslexia, providing valuable insights into the genetic factors influencing language processing.

Effects of genetic variation on the structure of RNA and protein.

Changes in the structure of RNA and protein, have an important impact on biological functions and are even important determinants of disease pathogenesis and treatment. Some genetic variations, including copy number variation, single nucleotide variation, and so on, can lead to changes in biological function and increased susceptibility to certain diseases by changing the structure of RNA or protein. With the development of structural biology and sequencing technology, a large amount of RNA and protein structure data and genetic variation data resources has emerged to be used to explain biological processes. Here, we reviewed the effects of genetic variation on the structure of RNAs and proteins, and investigated their impact on several diseases. An online resource (http://www.onethird-lab.com/gems/) to support convenient retrieval of common tools is also built. Finally, the challenges and future development of the effects of genetic variation on RNA and protein were discussed.

Ultra-Fast Single-Nucleotide-Variation Detection Enabled by Argonaute-Mediated Transistor Platform.

"Test-and-go" single-nucleotide variation (SNV) detection within several minutes remains challenging, especially in low-abundance samples, since existing methods face a trade-off between sensitivity and testing speed. Sensitive detection usually relies on complex and time-consuming nucleic acid amplification or sequencing. Here, a graphene field-effect transistor (GFET) platform mediated by Argonaute protein that enables rapid, sensitive, and specific SNV detection is developed. The Argonaute protein provides a nanoscale binding channel to preorganize the DNA probe, accelerating target binding and rapidly recognizing SNVs with single-nucleotide resolution in unamplified tumor-associated microRNA, circulating tumor DNA, virus RNA, and reverse transcribed cDNA when a mismatch occurs in the seed region. An integrated microchip simultaneously detects multiple SNVs in agreement with sequencing results within 5 min, achieving the fastest SNV detection in a "test-and-go" manner without the requirement of nucleic acid extraction, reverse transcription, and amplification.

Whole genome sequencing reveals candidate genes involving in PAS resistance in M. Tuberculosis isolated from patients in Thailand.

Para-amino salicylic acid (PAS) was first reported by Lehmann in 1946 and used for tuberculosis treatment. However, due to its adverse effects, it is now used only as a second line anti-tuberculosis drug for treatment of multidrug resistant or extensively drug resistant M. tuberculosis. The structure of PAS is similar to para-amino benzoic acid (pABA), an intermediate metabolite in the folate synthesis pathway. The study has identified mutations in genes in folate pathway and their intergenic regions for their possibilities in responsible for PAS resistance. Genomic DNA from 120 PAS-resistant and 49 PAS-sensitive M. tuberculosis isolated from tuberculosis patients in Thailand were studied by whole genome sequencing. Twelve genes in the folate synthesis pathway were investigated for variants associated with PAS resistance. Fifty-one SNVs were found in nine genes and their intergenic regions (pabC, pabB, folC, ribD, thyX, dfrA, thyA, folK, folP). Functional correlation test confirmed mutations in RibD, ThyX, and ThyA are responsible for PAS resistance. Detection of mutation in thyA, folC, intergenic regions of thyX, ribD, and double deletion of thyA dfrA are proposed for determination of PAS resistant M. tuberculosis.

Reclassifying variations of unknown significance in diseases affecting Saudi Arabia's population reveal new associations.

Introduction: Physicians face diagnostic dilemmas upon reports indicating disease variants of unknown significance (VUS). The most puzzling cases are patients with rare diseases, where finding another matched genotype and phenotype to associate their results is challenging. This study aims to prove the value of updating patient files with new classifications, potentially leading to better assessment and prevention. Methodology: We recruited retrospective phenotypic and genotypic data from King Saud Medical City, Riyadh, Kingdom of Saudi Arabia. Between September 2020 and December 2021, 1,080 patients' genetic profiles were tested in a College of American Pathologists accredited laboratory. We excluded all confirmed pathogenic variants, likely pathogenic variants and copy number variations. Finally, we further reclassified 194 VUS using different local and global databases, employing in silico prediction to justify the phenotype-genotype association. Results: Of the 194 VUS, 90 remained VUS, and the other 104 were reclassified as follows: 16 pathogenic, 49 likely pathogenic, nine benign, and 30 likely benign. Moreover, most of these variants had never been observed in other local or international databases. Conclusion: Reclassifying the VUS adds value to understanding the causality of the phenotype if it has been reported in another family or population. The healthcare system should establish guidelines for re-evaluating VUS, and upgrading VUS should reflect on individual/family risks and management strategies.

Cross-cohort single-nucleotide-variant profiling of gut microbiota suggests a novel gut-health assessment approach.

IMPORTANCE: Most studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

Transmission Dynamics of Imported Vaccine-Origin PRRSV-2 within and between Commercial Swine Integrations in Hungary.

This study reports on the molecular epidemiology of Ingelvac-PRRS-MLV-associated cases in Hungary for the period 2020-2021. Field epidemiology investigations led the experts to conclude that imported pigs, which were shipped through transit stations in Denmark, introduced the vaccine virus. The movement of fatteners and the neglect of disease control measures contributed to the spread of the virus to PRRS-free pig holdings in the vicinity. Deep sequencing was performed to genetically characterize the genes coding for the virion antigens (i.e., ORF2 through ORF7). The study isolates exhibited a range of 0.1 to 1.8% nucleotide sequence divergence from the Ingelvac PRRS MLV and identified numerous polymorphic sites (up to 57 sites) along the amplified 3.2 kilo base pair genomic region. Our findings confirm that some PRRSV-2 vaccine strains can accumulate very high number of point mutations within a short period in immunologically naive pig herds.

Whole-Exome Sequencing Reveals Mutational Signature of Hypertrophic Cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is an extremely insidious and lethal disease caused by genetic variation. It has been studied for nearly 70 years since its discovery, but its cause of the disease remains a mystery. This study is aimed to explore the genetic pathogenesis of HCM in order to provide new insight for the diagnosis and treatment of HCM. Methods: Patients with HCM at 4 hospitals from January 1, 2020, to December 31, 2021, were collected. Peripheral blood of these patients was collected for whole exome sequencing. Moreover, data on the HCM transcriptome were analyzed in the GEO database. Results: Totally, 14 patients were enrolled, and 6 single-nucleotide variation (SNV) mutant genes represented by MUC12 were observed. Most of the gene mutations in HCM patients were synonymous and non-synonymous, and the types of base mutations were mainly C > T and G > A. Copy number variants (CNVs) predominantly occurred on chromosome 1 in HCM patients. Furthermore, we found that the only ATP2A2 gene was differentially expressed in 3 groups of transcriptome data in GEO database, and the presence of ATP2A2 mutation in 10 samples was observed in this study. Conclusion: In summary, 7 mutated genes represented by MUC12 and ATP2A2 were found in this study, which may provide novel insights into the pathogenic mechanism of HCM.

Chromosome instability region analysis and identification of the driver genes of the epithelial ovarian cancer cell lines A2780 and SKOV3.

Epithelial ovarian cancer (EOC) is one of the most prevalent gynaecological cancers worldwide. The molecular mechanisms of serous ovarian cancer (SOC) remain unclear and not well understood. SOC cases are primarily diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to obtain a better understanding of precise molecular mechanisms and to identify the chromosome instability region and key driver genes in the carcinogenesis and progression of SOC. Whole-exome sequencing was performed on the normal ovarian cell line IOSE80 and the EOC cell lines SKOV3 and A2780. The single-nucleotide variation burden, distribution, frequency and signature followed the known ovarian mutation profiles, without chromosomal bias. Recurrently mutated ovarian cancer driver genes, including LRP1B, KMT2A, ARID1A, KMT2C and ATRX were also found in two cell lines. The genome distribution of copy number alterations was found by copy number variation (CNV) analysis, including amplification of 17q12 and 4p16.1 and deletion of 10q23.33. The CNVs of MED1, GRB7 and MIEN1 located at 17q12 were found to be correlated with the overall survival of SOC patients (MED1: p = 0.028, GRB7: p = 0.0048, MIEN1: p = 0.0051), and the expression of the three driver genes in the ovarian cell line IOSE80 and EOC cell lines SKOV3 and A2780 was confirmed by western blot and cell immunohistochemistry.

Microbial Communities in Gynecological Cancers and Their Association with Tumor Somatic Variation.

There are strong correlations between the microbiome and human disease, including cancer. However, very little is known about potential mechanisms associated with malignant transformation in microbiome-associated gynecological cancer, except for HPV-induced cervical cancer. Our hypothesis is that differences in bacterial communities in upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. We first assessed differences in the taxonomic composition of microbial communities and genomic variation between gynecologic cancers and normal samples. Then, we performed a correlation analysis to assess whether differences in microbial communities selected for specific single nucleotide variation (SNV) between normal and gynecological cancers. We validated these results in independent datasets. This is a retrospective nested case-control study that used clinical and genomic information to perform all analyses. Our present study confirms a changing landscape in microbial communities as we progress into the upper genital tract, with more diversity in lower levels of the tract. Some of the different genomic variations between cancer and controls strongly correlated with the changing microbial communities. Pathway analyses including these correlated genes may help understand the basis for how changing bacterial landscapes may lead to these cancers. However, one of the most important implications of our findings is the possibility of cancer prevention in women at risk by detecting altered bacterial communities in the upper genital tract epithelium.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples.

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenge was overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE2.0, powered by multi-step parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE2.0 speeds up 50 times than MuSE1.0 and 8-80 times than other popular callers. Our benchmark study suggests combining MuSE2.0 and the recently expedited Strelka2 can achieve high efficiency and accuracy in analyzing large cancer genomic datasets.

Enhancing genomic mutation data storage optimization based on the compression of asymmetry of sparsity.

Background: With the rapid development of high-throughput sequencing technology and the explosive growth of genomic data, storing, transmitting and processing massive amounts of data has become a new challenge. How to achieve fast lossless compression and decompression according to the characteristics of the data to speed up data transmission and processing requires research on relevant compression algorithms. Methods: In this paper, a compression algorithm for sparse asymmetric gene mutations (CA_SAGM) based on the characteristics of sparse genomic mutation data was proposed. The data was first sorted on a row-first basis so that neighboring non-zero elements were as close as possible to each other. The data were then renumbered using the reverse Cuthill-Mckee sorting technique. Finally the data were compressed into sparse row format (CSR) and stored. We had analyzed and compared the results of the CA_SAGM, coordinate format (COO) and compressed sparse column format (CSC) algorithms for sparse asymmetric genomic data. Nine types of single-nucleotide variation (SNV) data and six types of copy number variation (CNV) data from the TCGA database were used as the subjects of this study. Compression and decompression time, compression and decompression rate, compression memory and compression ratio were used as evaluation metrics. The correlation between each metric and the basic characteristics of the original data was further investigated. Results: The experimental results showed that the COO method had the shortest compression time, the fastest compression rate and the largest compression ratio, and had the best compression performance. CSC compression performance was the worst, and CA_SAGM compression performance was between the two. When decompressing the data, CA_SAGM performed the best, with the shortest decompression time and the fastest decompression rate. COO decompression performance was the worst. With increasing sparsity, the COO, CSC and CA_SAGM algorithms all exhibited longer compression and decompression times, lower compression and decompression rates, larger compression memory and lower compression ratios. When the sparsity was large, the compression memory and compression ratio of the three algorithms showed no difference characteristics, but the rest of the indexes were still different. Conclusion: CA_SAGM was an efficient compression algorithm that combines compression and decompression performance for sparse genomic mutation data.

Traceability of SARS-CoV-2 transmission through quasispecies analysis.

During COVID-19 pandemic, consensus genomic sequences were used for rapidly monitor the spread of the virus worldwide. However, less attention was paid to intrahost genetic diversity. In fact, in the infected host, SARS-CoV-2 consists in an ensemble of replicating and closely related viral variants so-called quasispecies. Here we show that intrahost single nucleotide variants (iSNVs) represent a target for contact tracing analysis. Our data indicate that in the acute phase of infection, in highly likely transmission links, the number of viral particles transmitted from one host to another (bottleneck size) is large enough to propagate iSNVs among individuals. Furthermore, we demonstrate that, during SARS-CoV-2 outbreaks when the consensus sequences are identical, it is possible to reconstruct the transmission chains by genomic investigations of iSNVs. Specifically, we found that it is possible to identify transmission chains by limiting the analysis of iSNVs to only three well-conserved genes, namely nsp2, ORF3, and ORF7.

Age at menarche and polycystic ovary syndrome: A Mendelian randomization study.

OBJECTIVE: The authors aimed to use a large two-sample Mendelian randomization (MR) study to reveal the causality between age at menarche (AAM) and polycystic ovary syndrome (PCOS) incidence. METHODS: The authors collected summary statistics from the hitherto largest genome-wide association studies conducted in AAM and PCOS in the same ancestry. MR with inverse variance weighting was conducted as the main analysis method, while weighted median and MR-Egger regression were used for comprehensive analysis. As for pleiotropy detection, inverse variance weighting, MR-Egger regression, Mendelian Randomization Pleiotropy Residual Sum and Outlier, as well as leave-one-out analysis were used to detect pleiotropy. Risk factor analysis was conducted to investigate the underlying mechanisms linking AAM to PCOS. RESULTS: Each standard deviation increment in AAM was associated with a significantly lower incidence of PCOS (odds ratio, 0.86 [95% confidence interval, 0.75-0.98]). After adjustment in horizontal pleiotropy by eliminating four outliers, this pathogenic association was still statistically detected. All pleiotropy indexes were without statistical differences, which suggested the conclusions were robust. It showed the causal association between later AAM and lower body mass index, lower fasting insulin level and insulin resistance. CONCLUSION: Our MR analysis verified that a slightly later onset age (15 to 18 years) at menarche could reduce the risk of PCOS. A more comprehensive investigation in a prospective setting is strongly advised.

Viral intra-host evolutionary dynamics revealed via serial passage of Japanese encephalitis virus in vitro.

Analyses of viral inter- and intra-host mutations could better guide the prevention and control of infectious diseases. For a long time, studies on viral evolution have focused on viral inter-host variations. Next-generation sequencing has accelerated the investigations of viral intra-host diversity. However, the theoretical basis and dynamic characteristics of viral intra-host mutations remain unknown. Here, using serial passages of the SA14-14-2 vaccine strain of Japanese encephalitis virus (JEV) as the in vitro model, the distribution characteristics of 1,788 detected intra-host single-nucleotide variations (iSNVs) and their mutated frequencies from 477 deep-sequenced samples were analyzed. Our results revealed that in adaptive (baby hamster kidney (BHK)) cells, JEV is under a nearly neutral selection pressure, and both non-synonymous and synonymous mutations represent an S-shaped growth trend over time. A higher positive selection pressure was observed in the nonadaptive (C6/36) cells, and logarithmic growth in non-synonymous iSNVs and linear growth in synonymous iSNVs were observed over time. Moreover, the mutation rates of the NS4B protein and the untranslated region (UTR) of the JEV are significantly different between BHK and C6/36 cells, suggesting that viral selection pressure is regulated by different cellular environments. In addition, no significant difference was detected in the distribution of mutated frequencies of iSNVs between BHK and C6/36 cells.

Prevalence, variation, and transmission patterns of human respiratory syncytial virus from pediatric patients in Hubei, China during 2020-2021.

Human respiratory syncytial virus (RSV) is a severe threat to children and a main cause of acute lower respiratory tract infections. Nevertheless, the intra-host evolution and inter-regional diffusion of RSV are little known. In this study, we performed a systematic surveillance in hospitalized children in Hubei during 2020-2021, in which 106 RSV-positive samples were detected both clinically and by metagenomic next generation sequencing (mNGS). RSV-A and RSV-B groups co-circulated during surveillance with RSV-B being predominant. About 46 high-quality genomes were used for further analyses. A total of 163 intra-host nucleotide variation (iSNV) sites distributed in 34 samples were detected, and glycoprotein (G) gene was the most enriched gene for iSNVs, with non-synonymous substitutions more than synonymous substitutions. Evolutionary dynamic analysis showed that the evolutionary rates of G and NS2 genes were higher, and the population size of RSV groups changed over time. We also found evidences of inter-regional diffusion from Europe and Oceania to Hubei for RSV-A and RSV-B, respectively. This study highlighted the intra-host and inter-host evolution of RSV, and provided some evidences for understanding the evolution of RSV.

Distinct genomic features between osteosarcomas firstly metastasing to bone and to lung.

Background: Osteosarcoma initially metastasing to bone only shows distinct biological features compared to osteosarcoma that firstly metastasizes to the lung, which suggests us underlying different genomic pathogenetic mechanism. Methods: We analyzed whole-exome sequencing (WES) data for 38 osteosarcoma with paired samples in different relapse patterns. We also sought to redefine disease subclassifications for osteosarcoma based on genetic alterations and correlate these genetic profiles with clinical treatment courses to elucidate potential evolving cladograms. Results: We investigated WES of 12/38 patients with high-grade osteosarcoma (31.6%) with initial bone metastasis (group A) and 26/38 (68.4%) with initial pulmonary metastasis (group B), of whom 15/38 (39.5%) had paired samples of primary lesions and metastatic lesions. We found that osteosarcoma in group A mainly carries single-nucleotide variations displaying higher tumor mutation burden and neoantigen load and more tertiary lymphoid structures, while those in group B mainly exhibits structural variants. High conservation of reported genetic sequencing over time in their evolving cladograms. Conclusions: Osteosarcoma with mainly single-nucleotide variations other than structural variants might exhibit biological behavior predisposing toward bone metastases as well as better immunogenicity in tumor microenvironment.