Degenerative cervical myelopathy is a common cause of spinal cord injury,with longer symptom duration and higher myelopathy severity indicating a worse prognosis.While numerous studies have investigated serological bi...Degenerative cervical myelopathy is a common cause of spinal cord injury,with longer symptom duration and higher myelopathy severity indicating a worse prognosis.While numerous studies have investigated serological biomarkers for acute spinal cord injury,few studies have explored such biomarkers for diagnosing degenerative cervical myelopathy.This study involved 30 patients with degenerative cervical myelopathy(51.3±7.3 years old,12 women and 18 men),seven healthy controls(25.7±1.7 years old,one woman and six men),and nine patients with cervical spondylotic radiculopathy(51.9±8.6 years old,three women and six men).Analysis of blood samples from the three groups showed clear differences in transcriptomic characteristics.Enrichment analysis identified 128 differentially expressed genes that were enriched in patients with neurological disabilities.Using least absolute shrinkage and selection operator analysis,we constructed a five-gene model(TBCD,TPM2,PNKD,EIF4G2,and AP5Z1)to diagnose degenerative cervical myelopathy with an accuracy of 93.5%.One-gene models(TCAP and SDHA)identified mild and severe degenerative cervical myelopathy with accuracies of 83.3%and 76.7%,respectively.Signatures of two immune cell types(memory B cells and memory-activated CD4^(+)T cells)predicted levels of lesions in degenerative cervical myelopathy with 80%accuracy.Our results suggest that peripheral blood RNA biomarkers could be used to predict lesion severity in degenerative cervical myelopathy.展开更多
In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer （PCa） to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses ...In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer （PCa） to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses （e.g., progression and mortality） differ even among individuals with similar clinical and pathological characteristics. Existing risk classifiers （TMN grading system, Gleason score, etc.） are not accurately enough to represent the biological features of PCa. Using new genomic technologies, novel biomarkers and classifiers have been developed and shown to add value to clinical or pathological risk factors for predicting aggressive disease. Among them, RNA testing （gene expression analysis） is useful because it can not only reflect genetic variations but also reflect epigenetic regulations. Commercially available RNA profiling tests （Oncotype Dx, Prolaris, and Decipher） have demonstrated strong abilities to discriminate PCa with poor prognosis from less aggressive diseases. For instance, these RNA profiling tests can predict disease progression in active surveillance patients or early recurrence after radical treatments. These tests may offer more dependable methods for PCa prognosis prediction to make more accurate and personal medical decisions.展开更多
Body fluid identification through messenger RNA(mRNA)has been proposed as a useful supplement to presumptive and confirmatory tests by previous laboratory studies;however,its application in routine clinical forensic e...Body fluid identification through messenger RNA(mRNA)has been proposed as a useful supplement to presumptive and confirmatory tests by previous laboratory studies;however,its application in routine clinical forensic examination was rare.We report a case of sexual assault in which body fluid identification by mRNA profiling was used.Vaginal secretions mRNA markers(MUC4,HBD1,and CYP2B7P1)were used to test the sample,being obtained positive results.This case demonstrates that mRNA profiling of body fluids could be applied to routine case examinations as an aid,acting as a scientific collaborative evidence to strengthen the medicolegal opinion.展开更多
Background： Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profilin...Background： Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transeriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data. Results： We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy. Conclusions： To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.展开更多
基金supported by Hunan Provincial Key Research and Development Program,No.2021SK2002(to BW)the Natural Science Foundation of Hunan Province of China(General Program),No.2021JJ30938(to YL)。
文摘Degenerative cervical myelopathy is a common cause of spinal cord injury,with longer symptom duration and higher myelopathy severity indicating a worse prognosis.While numerous studies have investigated serological biomarkers for acute spinal cord injury,few studies have explored such biomarkers for diagnosing degenerative cervical myelopathy.This study involved 30 patients with degenerative cervical myelopathy(51.3±7.3 years old,12 women and 18 men),seven healthy controls(25.7±1.7 years old,one woman and six men),and nine patients with cervical spondylotic radiculopathy(51.9±8.6 years old,three women and six men).Analysis of blood samples from the three groups showed clear differences in transcriptomic characteristics.Enrichment analysis identified 128 differentially expressed genes that were enriched in patients with neurological disabilities.Using least absolute shrinkage and selection operator analysis,we constructed a five-gene model(TBCD,TPM2,PNKD,EIF4G2,and AP5Z1)to diagnose degenerative cervical myelopathy with an accuracy of 93.5%.One-gene models(TCAP and SDHA)identified mild and severe degenerative cervical myelopathy with accuracies of 83.3%and 76.7%,respectively.Signatures of two immune cell types(memory B cells and memory-activated CD4^(+)T cells)predicted levels of lesions in degenerative cervical myelopathy with 80%accuracy.Our results suggest that peripheral blood RNA biomarkers could be used to predict lesion severity in degenerative cervical myelopathy.
基金The work was supported by the National Natural Science Foundation of China （Grant No. 81402339）.
文摘In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer （PCa） to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses （e.g., progression and mortality） differ even among individuals with similar clinical and pathological characteristics. Existing risk classifiers （TMN grading system, Gleason score, etc.） are not accurately enough to represent the biological features of PCa. Using new genomic technologies, novel biomarkers and classifiers have been developed and shown to add value to clinical or pathological risk factors for predicting aggressive disease. Among them, RNA testing （gene expression analysis） is useful because it can not only reflect genetic variations but also reflect epigenetic regulations. Commercially available RNA profiling tests （Oncotype Dx, Prolaris, and Decipher） have demonstrated strong abilities to discriminate PCa with poor prognosis from less aggressive diseases. For instance, these RNA profiling tests can predict disease progression in active surveillance patients or early recurrence after radical treatments. These tests may offer more dependable methods for PCa prognosis prediction to make more accurate and personal medical decisions.
文摘Body fluid identification through messenger RNA(mRNA)has been proposed as a useful supplement to presumptive and confirmatory tests by previous laboratory studies;however,its application in routine clinical forensic examination was rare.We report a case of sexual assault in which body fluid identification by mRNA profiling was used.Vaginal secretions mRNA markers(MUC4,HBD1,and CYP2B7P1)were used to test the sample,being obtained positive results.This case demonstrates that mRNA profiling of body fluids could be applied to routine case examinations as an aid,acting as a scientific collaborative evidence to strengthen the medicolegal opinion.
文摘Background： Structure profiling experiments provide single-nucleotide information on RNA structure. Recent advances in chemistry combined with application of high-throughput sequencing have enabled structure profiling at transeriptome scale and in living cells, creating unprecedented opportunities for RNA biology. Propelled by these experimental advances, massive data with ever-increasing diversity and complexity have been generated, which give rise to new challenges in interpreting and analyzing these data. Results： We review current practices in analysis of structure profiling data with emphasis on comparative and integrative analysis as well as highlight emerging questions. Comparative analysis has revealed structural patterns across transcriptomes and has become an integral component of recent profiling studies. Additionally, profiling data can be integrated into traditional structure prediction algorithms to improve prediction accuracy. Conclusions： To keep pace with experimental developments, methods to facilitate, enhance and refine such analyses are needed. Parallel advances in analysis methodology will complement profiling technologies and help them reach their full potential.
