Genome-wide colocalization of RNA-DNA interactions and fusion RNA pairs.

Fusion transcripts are used as biomarkers in companion diagnoses. Although more than 15,000 fusion RNAs have been identified from diverse cancer types, few common features have been reported. Here, we compared 16,410 fusion transcripts detected in cancer (from a published cohort of 9,966 tumor samples of 33 cancer types) with genome-wide RNA-DNA interactions mapped in two normal, noncancerous cell types [using iMARGI, an enhanced version of the mapping of RNA-genome interactions (MARGI) assay]. Among the top 10 most significant RNA-DNA interactions in normal cells, 5 colocalized with the gene pairs that formed fusion RNAs in cancer. Furthermore, throughout the genome, the frequency of a gene pair to exhibit RNA-DNA interactions is positively correlated with the probability of this gene pair to present documented fusion transcripts in cancer. To test whether RNA-DNA interactions in normal cells are predictive of fusion RNAs, we analyzed these in a validation cohort of 96 lung cancer samples using RNA sequencing (RNA-seq). Thirty-seven of 42 fusion transcripts in the validation cohort were found to exhibit RNA-DNA interactions in normal cells. Finally, by combining RNA-seq, single-molecule RNA FISH, and DNA FISH, we detected a cancer sample with EML4-ALK fusion RNA without forming the EML4-ALK fusion gene. Collectively, these data suggest an RNA-poise model, where spatial proximity of RNA and DNA could poise for the creation of fusion transcripts.

RNA, Action through Interactions.

As transcription of the human genome is quite pervasive, it is possible that many novel functions of the noncoding genome have yet to be identified. Often the noncoding genome's functions are carried out by their RNA transcripts, which may rely on their structures and/or extensive interactions with other molecules. Recent technology developments are transforming the fields of RNA biology from studying one RNA at a time to transcriptome-wide mapping of structures and interactions. Here, we highlight the recent advances in transcriptome-wide RNA interaction analysis. These technologies revealed surprising versatility of RNA to participate in diverse molecular systems. For example, tens of thousands of RNA-RNA interactions have been revealed in cultured cells as well as in mouse brain, including interactions between transposon-produced transcripts and mRNAs. In addition, most transcription start sites in the human genome are associated with noncoding RNA transcribed from other genomic loci. These recent discoveries expanded our understanding of RNAs' roles in chromatin organization, gene regulation, and intracellular signaling.

[Treatment effect analysis of the standard regimen and the optimized regimen for retreatment pulmonary tuberculosis complicated with diabetes].

OBJECTIVE: To analyze the therapeutic effects of the standard regimen and the optimized regimen in retreatment pulmonary tuberculosis complicated with diabetes mellitus (DM). METHODS: In a multi-center cohort study, patients with smear positive retreatment pulmonary tuberculosis (TB) with DM and those without DM [excluding multi-drug resistance (MDR), extensively drug-resistant (XDR) and non-tuberculosis Mycobacterium pulmonary disease(NTM)] were enrolled. There were a total of 178 cases, including 60 smear positive retreatment TB patients with DM and 118 without DM, who were randomly divided into 4 groups: Optimized group 1 [individualized treatment in 30 DM cases, 29 males, age (48 ± 11)], retreatment group 1 [standard retreatment regimen in 30 DM cases, 28 males, age(48 ± 10)], Optimized group 2[individual regimen in 57 non-DM cases, 37 males, age (41 ± 14)], and retreatment group 2 [standard retreatment regimen in 61 non-DM cases, 49 males, age (43 ± 13)]. Patients in the optimized group were treated with optimized individualized regimen based on DST result, with 3-4 sensitive drugs in the regimen, while those in the retreatment group were treated with national standard retreatment regimen. The therapeutic effect of different groups were recorded and the related factors of treatment outcome were analyzed with Chi-square test and multi-factor analysis. RESULTS: The treatment success rates of the optimized group 1 and the retreatment group 1 were 83.3%(25/30) and 60.0%(18/30), respectively, and the difference was statistically significant (χ(2)=4.02, P=0.045<0.05). The treatment failure rate of the optimized group 1 (6.7%, 2/30) and the retreatment group 1(30.0%, 9/30) was statistically different (χ(2)=5.46, P=0.02<0.05). The outcome difference between the optimized group 2 and the retreatment group 2 showed no statistical significance. Multi-factor analysis showed that treatment regimen, DM, gender and drug resistance were the significant factors related with treatment outcome. The probability of treatment success using the individualized treatment regimen was 2.7 times higher than that using the standard regimen (P=0.025). The risk of treatment failure of the drug resistance cases was 2.8 times higher than that of the drug sensitive cases (P=0.038). The probability of treatment success in DM cases was 0.4 times that in non-DM cases (P<0.05). CONCLUSION: The outcome of the optimized regimen group was better than that of the standard regimen group, and retreatment TB patients complicated with DM faced a higher risk of treatment failure, which should receive more attention.

Effect of a modified regimen on drug-sensitive retreated pulmonary tuberculosis: A multicenter study in China.

Background and objective: Retreatment pulmonary tuberculosis (PTB) still accounts for a large proportion of tuberculosis, and the treatment outcome is unfavorable. The recurrence of retreatment PTB based on long-term follow-up has not been well demonstrated. This study aimed to evaluate effect of a modified regimen on drug-sensitive retreated pulmonary tuberculosis. Methods: This multicenter cohort study was conducted in 29 hospitals from 23 regions of China from July 1, 2009, to December 31, 2020. Patients were divided into two treatment regimen groups including experimental group [modified regimen (4H-Rt2-E-Z-S(Lfx)/4H-Rt2-E)]and control group [standard regimen (2H-R-E-Z-S/6H-R-E or 3H-R-E-Z/6H-R-E)]. The patients enrolled were followed up of 56 months after successful treatment. We compared the treatment success rate, treatment failure rate, adverse reaction rate, and recurrence rate between two regimens. Multivariate Cox regression model was used to identify the potential risk factors for recurrence after successful treatment with proportional hazards assumptions tested for all variables. Results: A total of 381 patients with retreatment PTB were enrolled, including 244 (64.0%) in the experimental group and 137 (36.0%) in the control group. Overall, the treatment success rate was significant higher in the experimental group than control group (84.0 vs. 74.5%, P = 0.024); no difference was observed in adverse reactions between the two groups (25.8 vs. 21.2%, P > 0.05). A total of 307 patients completed the 56 months of follow-up, including 205 with the modified regimen and 102 with the standard regimen. Among these, 10 cases (3.3%) relapsed, including 3 in the experimental group and 7 in the control group (1.5% vs 6.9%, P = 0.035). Reduced risks of recurrence were observed in patients treated with the modified regimen compared with the standard regimen, and the adjusted hazard ratio was 0.19 (0.04-0.77). Conclusion: The modified retreatment regimen had more favorable treatment effects, including higher treatment success rate and lower recurrence rate in patients with retreated drug-sensitive PTB.

[Comparison of clinical manifestations between Mycobacterium avium-intracellulare complex and Mycobacterium abscessus pulmonary diseases].

OBJECTIVE: To compare the clinical manifestations of nontuberculous mycobacterial (NTM) pulmonary diseases caused by Mycobacterium avium-intracellulare complex (MAC) and Mycobacterium abscessus. METHODS: The clinical manifestations of 18 patients with MAC and 9 patients with Mycobacterium abscessus pulmonary diseases diagnosed from 2010 to 2011 were reviewed. RESULTS: There were no significant differences in the gender, age, body mass index, predisposed diseases, symptoms and positive sputum acid-fast bacillus between MAC and Mycobacterium abscessus groups. Upper lobe cavities were more frequently observed in the MAC group (13/18), whereas nodular bronchiectatic changes were more frequent in the Mycobacterium abscessus group (3/9). Compared with MAC pulmonary diseases, several imaging characteristics were more common in the Mycobacterium abscessus group, including bilateral micro nodules (Mycobacterium abscessus group 8/9 vs MAC group 7/18), tree-in-bud sign (Mycobacterium abscessus group 7/9 vs MAC group 6/18) and multiple bronchiectasis (Mycobacterium abscessus group 8/9 vs MAC group 5/18). CONCLUSIONS: There was considerable overlap in clinical characteristics of MAC and Mycobacterium abscessus pulmonary diseases. However, bilateral micro nodules, tree-in-bud sign and multiple bronchiectasis were more frequently seen in Mycobacterium abscessus than in MAC pulmonary diseases, while upper lobe cavities were more frequently seen in MAC than in Mycobacterium abscessus pulmonary diseases.

Value of serum cytokine biomarkers TNF-α, IL-4, sIL-2R and IFN-γ for use in monitoring bacterial load and anti-tuberculosis treatment progress.

Tuberculosis (TB) patient serum cytokine levels may be predictive of anti-tuberculosis treatment progress. Here, serum levels of cytokines TNF-α, IL-4, sIL-2R and IFN-γ were measured then correlated to clinical TB manifestations, bacterial burden, chest imaging findings and clinical course. Study subjects included 67 newly diagnosed pulmonary TB (PTB) patients with active disease admitted to Beijing Chest Hospital for anti-TB chemotherapeutic treatment. Blood was drawn at 0 months (pre-treatment), 1-2 months (at any time between 1 and 2 month) and after 6 months completion of treatment and serum TNF-α, IL-4, sIL-2R and IFN-γ levels were measured in duplicate using enzyme-linked immunosorbent assays (ELISAs). Correlation analysis was conducted to evaluate sensitivity and specificity of cytokine levels as predictors of disease activity and treatment progress. The results indicated that the pre-treatment serum TNF-α level of the smear-negative group was lower than that of the smear 1+ group, while serum TNF-α after 6 months completion of treatment and IFN-γ levels at 1-2 months and after 6 months completion of treatment were significantly lower, respectively, than at 0 months (before treatment) (P < 0.05). Using a cut-off value of 845 pg/ml, serum TNF-α level was predictive of treatment progress, with a sensitivity of 51%, specificity of 60% and AUC of 0.594 (P = 0.013). Meanwhile, using a cut-off value of 393 pg/ml, serum IFN-γ provided superior monitoring efficacy, with a sensitivity of 60%, specificity of 64% and AUC of 0.651 (P = 0.017). In conclusion, both serum TNF-α and IFN-γ levels might be useful biomarkers for monitoring treatment progress.

RNAs as Proximity-Labeling Media for Identifying Nuclear Speckle Positions Relative to the Genome.

It remains challenging to identify all parts of the nuclear genome that are in proximity to nuclear speckles, due to physical separation between the nuclear speckle cores and chromatin. We hypothesized that noncoding RNAs including small nuclear RNA (snRNAs) and Malat1, which accumulate at the periphery of nuclear speckles (nsaRNA [nuclear speckle-associated RNA]), may extend to sufficient proximity to the genome. Leveraging a transcriptome-genome interaction assay (mapping of RNA-genome interactions [MARGI]), we identified clusters of nsaRNA-interacting genomic sequences (nsaPeaks). Posttranscriptional pre-mRNAs, which also accumulate to nuclear speckles, exhibited proximity to nsaPeaks but rarely to other genomic regions. Our combined DNA fluorescence in situ hybridization and immunofluorescence analysis in 182 single cells revealed a 3-fold increase in odds for nuclear speckles to localize near an nsaPeak than its neighboring genomic sequence. These data suggest a model that nsaRNAs are located in sufficient proximity to the nuclear genome and leave identifiable genomic footprints, thus revealing the parts of genome proximal to nuclear speckles.

[A preliminary study on the definition of resistant breakpoints of ofloxacin and levofloxacin for Mycobacterium tuberculosis].

OBJECTIVE: To test the MIC of ofloxacin and levofloxacin (MIC(F) and MIC(V)) in 101 strains of Mycobacterium tuberculosis (M. tb) isolated from patients with active tuberculosis and to analyze the relation between MIC and past history of fluoroquinolones (FQs) administration. And according to the analysis of the therapeutic effect of the regimen including FQs, we want to define the resistant breakpoints of OFLX and LVFX clinically. METHOD: All isolates from sputa or pus obtained from in-patients in our hospital from Jan 1999 to Sept 2000 were tested for MIC and susceptibility. 47 patients with pulmonary tuberculosis received regimens including FQs were observed consecutively. Chi-square test was applied for the statistical analysis. RESULT: (1) The MIC(V) of 96% clinical isolates tested were 2 times lower than MIC(F). (2) The MIC(F) < 8 microg/ml and MIC(V) < 4 microg/ml were found among 91% and 92% patients without previous FQs administration, while only the MIC(F) > or = 8 microg/ml and MIC(V) > or = 4 microg/ml were found among 54% and 57% for the patients with FQs administration history. (3) If MIC(F) > or = 8 microg/ml and MIC(V) > or = 4 microg/ml were defined as the clinical resistant breakpoints, in susceptible group, the sputum negative conversion rates were 54%, 75% and 82% respectively after receiving the regimens including FQs in 3, 6, and 12 months, while 16%, 32%, and 42% respectively in resistant group, (P < 0.01). Also, there were significant differences between these two groups for chest X-ray improvements after 12 months' treatment, (P < 0.01). There were significant differences for sputum conversion rates and chest X-ray improvement between MIC(V) < 4 microg/ml and MIC(V) > or = 4 microg/ml groups (P < 0.01). CONCLUSIONS: According to the evaluation for the therapeutic effects of regimens including FQs, it is suggested that MIC(F) > or = 8 microg/ml and MIC(V) > or = 4 microg/ml be defined as resistant breakpoints clinically. The emergence of resistance to FQs in patients with tuberculosis can influence the therapeutic effects.