Personalized neoantigen-based T cell therapy triggers cytotoxic lymphocytes expressing polyclonal TCR against metastatic ovarian cancer.

Neoantigen-reactive cytotoxic T lymphocytes play a vital role in precise cancer cell elimination. In this study, we demonstrate the effectiveness of personalized neoantigen-based T cell therapy in inducing tumor regression in two patients suffering from heavily-burdened metastatic ovarian cancer. Our approach involved the development of a robust pipeline for ex vivo expansion of neoantigen-reactive T lymphocytes. Neoantigen peptides were designed and synthesized based on the somatic mutations of the tumors and their predicted HLA binding affinities. These peptides were then presented to T lymphocytes through co-culture with neoantigen-loaded dendritic cells for ex vivo expansion. Subsequent to cell therapy, both patients exhibited significant reductions in tumor marker levels and experienced substantial tumor regression. One patient achieved repeated cancer regression through infusions of T cell products generated from newly identified neoantigens. Transcriptomic analyses revealed a remarkable increase in neoantigen-reactive cytotoxic lymphocytes in the peripheral blood of the patients following cell therapy. These cytotoxic T lymphocytes expressed polyclonal T cell receptors (TCR) against neoantigens, along with abundant cytotoxic proteins and pro-inflammatory cytokines. The efficacy of neoantigen targeting was significantly associated with the immunogenicity and TCR polyclonality. Notably, the neoantigen-specific TCR clonotypes persisted in the peripheral blood after cell therapy. Our findings indicate that personalized neoantigen-based T cell therapy triggers cytotoxic lymphocytes expressing polyclonal TCR against ovarian cancer, suggesting its promising potential in cancer immunotherapy.

Whole genome sequencing identifies genetic variants associated with co-trimoxazole hypersensitivity in Asians.

BACKGROUND: Co-trimoxazole, a sulfonamide antibiotic, is used to treat a variety of infections worldwide, and it remains a common first-line medicine for prophylaxis against Pneumocystis jiroveci pneumonia. However, it can cause severe cutaneous adverse reaction (SCAR), including Stevens-Johnson syndrome, toxic epidermal necrolysis, and drug reaction with eosinophilia and systemic symptoms. The pathomechanism of co-trimoxazole-induced SCAR remains unclear. OBJECTIVE: We aimed to investigate the genetic predisposition of co-trimoxazole-induced SCAR. METHODS: We conducted a multicountry case-control association study that included 151 patients with of co-trimoxazole-induced SCAR and 4631 population controls from Taiwan, Thailand, and Malaysia, as well as 138 tolerant controls from Taiwan. Whole-genome sequencing was performed for the patients and population controls from Taiwan; it further validated the results from Thailand and Malaysia. RESULTS: The whole-genome sequencing study (43 case patients vs 507 controls) discovered that the single-nucleotide polymorphism rs41554616, which is located between the HLA-B and MICA loci, had the strongest association with co-trimoxazole-induced SCAR (P = 8.2 × 10-9; odds ratio [OR] = 7.7). There were weak associations of variants in co-trimoxazole-related metabolizing enzymes (CYP2D6, GSTP1, GCLC, N-acetyltransferase [NAT2], and CYP2C8). A replication study using HLA genotyping revealed that HLA-B∗13:01 was strongly associated with co-trimoxazole-induced SCAR (the combined sample comprised 91 case patients vs 2545 controls [P = 7.2 × 10-21; OR = 8.7]). A strong HLA association was also observed in the case patients from Thailand (P = 3.2 × 10-5; OR = 3.6) and Malaysia (P = .002; OR = 12.8), respectively. A meta-analysis and phenotype stratification study further indicated a strong association between HLA-B∗13:01 and co-trimoxazole-induced drug reaction with eosinophilia and systemic symptoms (P = 4.2 × 10-23; OR = 40.1). CONCLUSION: This study identified HLA-B∗13:01 as an important genetic factor associated with co-trimoxazole-induced SCAR in Asians.

Detecting Lesional Granulysin Levels for Rapid Diagnosis of Cytotoxic T lymphocyte-Mediated Bullous Skin Disorders.

BACKGROUND: Bullous skin disorders are induced by different pathomechanisms and several are emergent, including Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN). Rapid diagnostic methods for SJS/TEN or cytotoxic T-lymphocyte (CTL)-mediated bullous disorders are crucial for early treatment. Granulysin, primarily expressed by CTLs, is a specific cytotoxic protein responsible for SJS/TEN and similar skin reactions. OBJECTIVE: To assess granulysin levels in blister fluids to differentiate SJS/TEN and similar CTL-mediated bullous reactions from other autoimmune bullous disorders. METHODS: Using ELISA, we measured granulysin in blister fluids from patients with bullous skin disorders, including SJS/TEN, erythema multiforme major, bullous fixed-drug eruption, bullous lupus erythematosus, paraneoplastic pemphigus, pemphigus vulgaris, bullous pemphigoid, purpura fulminans-related bullae, and hand-foot syndrome/hand-foot-skin reactions. We compared serum and blister granulysin levels in patients with SJS/TEN presenting varying severity, monitoring serial granulysin levels from acute to late stages. RESULTS: Overall, 144 patients presenting with bullous skin disorders were enrolled. Blister granulysin levels (mean ± SD) in CTL-mediated disorders, including TEN (n = 28; 3938.7 ± 3475.7), SJS-TEN overlapping (n = 22; 1440.4 ± 1179.6), SJS (n = 14; 542.0 ± 503.2), erythema multiforme major (n = 7; 766.3 ± 1073.7), generalized bullous fixed-drug eruption (n = 10; 720.4 ± 858.3), and localized bullous fixed-drug eruption (n = 16; 69.0 ± 56.4), were significantly higher than in non-CTL-mediated bullous disorders (P < .0001), including bullous lupus erythematosus (n = 3; 22.7 ± 20.1), paraneoplastic pemphigus (n = 3; 20.3 ± 8.6), pemphigus vulgaris (n = 3; 4.4 ± 2.8), bullous pemphigoid (n = 18; 4.0 ± 2.7), purpura fulminans (n = 4; 5.9 ± 5.5), and hand-foot syndrome/hand-foot-skin reactions (n = 6; 4.6 ± 3.5). Blister granulysin levels correlated with clinical severity of SJS/TEN (P < .0001). CONCLUSIONS: Determination of blister granulysin levels is a noninvasive and useful tool for rapid differential diagnosis of SJS/TEN and other similar CTL-mediated bullous skin disorders for treatment selection.

Genomic Analysis of Mycobacterium tuberculosis Isolates and Construction of a Beijing Lineage Reference Genome.

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, kills over 1 million people worldwide annually. Development of drug resistance (DR) in the pathogen is a major challenge for TB control. We conducted whole-genome analysis of seven Taiwan M. tuberculosis isolates: One drug susceptible (DS) and five DR Beijing lineage isolates and one DR Euro-American lineage isolate. Developing a new method for DR mutation identification and applying it to the next-generation sequencing (NGS) data from the 6 Beijing lineage isolates, we identified 13 known and 6 candidate DR mutations and provided experimental support for 4 of them. We assembled the genomes of one DS and two DR Beijing lineage isolates and the Euro-American lineage isolate using NGS data. Moreover, using both PacBio and NGS sequencing data, we obtained a high-quality assembly of an extensive DR Beijing lineage isolate. Comparative analysis of these five newly assembled genomes and two published complete genomes revealed a large number of genetic changes, including gene gains and losses, indels and translocations, suggesting rapid evolution of M. tuberculosis. We found the MazEF toxin-antitoxin system in all the seven isolates studied and several interesting mutations in MazEF proteins. Finally, we used the four assembled Beijing lineage genomes to construct a high-quality Beijing lineage reference genome that is DS and contains all the genes in the four genomes. It contains 212 genes not found in the standard reference H37Rv, which is Euro-American. It is therefore a better reference than H37Rv for the Beijing lineage, the predominant lineage in Asia.

Effect of a computer-aided diagnosis system on radiologists' performance in grading gliomas with MRI.

The effects of a computer-aided diagnosis (CAD) system based on quantitative intensity features with magnetic resonance (MR) imaging (MRI) were evaluated by examining radiologists' performance in grading gliomas. The acquired MRI database included 71 lower-grade gliomas and 34 glioblastomas. Quantitative image features were extracted from the tumor area and combined in a CAD system to generate a prediction model. The effect of the CAD system was evaluated in a two-stage procedure. First, a radiologist performed a conventional reading. A sequential second reading was determined with a malignancy estimation by the CAD system. Each MR image was regularly read by one radiologist out of a group of three radiologists. The CAD system achieved an accuracy of 87% (91/105), a sensitivity of 79% (27/34), a specificity of 90% (64/71), and an area under the receiver operating characteristic curve (Az) of 0.89. In the evaluation, the radiologists' Az values significantly improved from 0.81, 0.87, and 0.84 to 0.90, 0.90, and 0.88 with p = 0.0011, 0.0076, and 0.0167, respectively. Based on the MR image features, the proposed CAD system not only performed well in distinguishing glioblastomas from lower-grade gliomas but also provided suggestions about glioma grading to reinforce radiologists' confidence rating.

ViralmiR: a support-vector-machine-based method for predicting viral microRNA precursors.

BACKGROUND: microRNAs (miRNAs) play a vital role in development, oncogenesis, and apoptosis by binding to mRNAs to regulate the posttranscriptional level of coding genes in mammals, plants, and insects. Recent studies have demonstrated that the expression of viral miRNAs is associated with the ability of the virus to infect a host. Identifying potential viral miRNAs from experimental sequence data is valuable for deciphering virus-host interactions. Thus far, a specific predictive model for viral miRNA identification has yet to be developed. METHODS AND RESULTS: Here, we present ViralmiR for identifying viral miRNA precursors on the basis of sequencing and structural information. We collected 263 experimentally validated miRNA precursors (pre-miRNAs) from 26 virus species and generated sequencing fragments from virus and human genomes as the negative dataset. Support vector machine and random forest models were established using 54 features from RNA sequences and secondary structural information. The results show that ViralmiR achieved a balanced accuracy higher than 83%, which is superior to that of previously developed tools for identifying pre-miRNAs. CONCLUSIONS: The easy-to-use ViralmiR web interface has been provided as a helpful resource for researchers to use in analyzing and deciphering virus-host interactions. The web interface of ViralmiR can be accessed at http://csb.cse.yzu.edu.tw/viralmir/.

Genomic and transcriptomic analyses of the medicinal fungus Antrodia cinnamomea for its metabolite biosynthesis and sexual development.

Antrodia cinnamomea, a polyporus mushroom of Taiwan, has long been used as a remedy for cancer, hypertension, and hangover, with an annual market of over $100 million (US) in Taiwan. We obtained a 32.15-Mb genome draft containing 9,254 genes. Genome ontology enrichment and pathway analyses shed light on sexual development and the biosynthesis of sesquiterpenoids, triterpenoids, ergostanes, antroquinonol, and antrocamphin. We identified genes differentially expressed between mycelium and fruiting body and 242 proteins in the mevalonate pathway, terpenoid pathways, cytochrome P450s, and polyketide synthases, which may contribute to the production of medicinal secondary metabolites. Genes of secondary metabolite biosynthetic pathways showed expression enrichment for tissue-specific compounds, including 14-α-demethylase (CYP51F1) in fruiting body for converting lanostane to ergostane triterpenoids, coenzymes Q (COQ) for antroquinonol biosynthesis in mycelium, and polyketide synthase for antrocamphin biosynthesis in fruiting body. Our data will be useful for developing a strategy to increase the production of useful metabolites.

dbSNO: a database of cysteine S-nitrosylation.

UNLABELLED: S-nitrosylation (SNO), a selective and reversible protein post-translational modification that involves the covalent attachment of nitric oxide (NO) to the sulfur atom of cysteine, critically regulates protein activity, localization and stability. Due to its importance in regulating protein functions and cell signaling, a mass spectrometry-based proteomics method rapidly evolved to increase the dataset of experimentally determined SNO sites. However, there is currently no database dedicated to the integration of all experimentally verified S-nitrosylation sites with their structural or functional information. Thus, the dbSNO database is created to integrate all available datasets and to provide their structural analysis. Up to April 15, 2012, the dbSNO has manually accumulated >3000 experimentally verified S-nitrosylated peptides from 219 research articles using a text mining approach. To solve the heterogeneity among the data collected from different sources, the sequence identity of these reported S-nitrosylated peptides are mapped to the UniProtKB protein entries. To delineate the structural correlation and consensus motif of these SNO sites, the dbSNO database also provides structural and functional analyses, including the motifs of substrate sites, solvent accessibility, protein secondary and tertiary structures, protein domains and gene ontology. AVAILABILITY: The dbSNO is now freely accessible via http://dbSNO.mbc.nctu.edu.tw. The database content is regularly updated upon collecting new data obtained from continuously surveying research articles.

Evaluation of the diagnostic performance of infrared imaging of the breast: a preliminary study.

BACKGROUND: The study was conducted to investigate the diagnostic performance of infrared (IR) imaging of the breast using an interpretive model derived from a scoring system. METHODS: The study was approved by the Institutional Review Board of our hospital. A total of 276 women (mean age = 50.8 years, SD 11.8) with suspicious findings on mammograms or ultrasound received IR imaging of the breast before excisional biopsy. The interpreting radiologists scored the lesions using a scoring system that combines five IR signs. The ROC (receiver operating characteristic) curve and AUC (area under the ROC curve) were analyzed by the univariate logistic regression model for each IR sign and an age-adjusted multivariate logistic regression model including 5 IR signs. The cut-off values and corresponding sensitivity, specificity, Youden's Index (Index = sensitivity+specificity-1), positive predictive value (PPV), negative predictive value (NPV) were estimated from the age-adjusted multivariate model. The most optimal cut-off value was determined by the one with highest Youden's Index. RESULTS: For the univariate model, the AUC of the ROC curve from five IR signs ranged from 0.557 to 0.701, and the AUC of the ROC from the age-adjusted multivariate model was 0.828. From the ROC derived from the multivariate model, the sensitivity of the most optimal cut-off value would be 72.4% with the corresponding specificity 76.6% (Youden's Index = 0.49), PPV 81.3% and NPV 66.4%. CONCLUSIONS: We established an interpretive age-adjusted multivariate model for IR imaging of the breast. The cut-off values and the corresponding sensitivity and specificity can be inferred from the model in a subpopulation for diagnostic purpose. TRIAL REGISTRATION: NCT00166998.

Use of Bayesian modeling to estimate the sensitivity of stereotactic directional vacuum-assisted breast biopsy when the gold standard is incomplete.

RATIONALE AND OBJECTIVES: This study is conducted to estimate the sensitivity of stereotactic directional vacuum-assisted breast biopsy (ST DVAB) using Bayesian modeling and to predict how many more cancers can be inferred from those lesions without surgical correlation. MATERIALS AND METHODS: We retrospectively reviewed the 103 lesions from 84 women who underwent ST DVAB. The study was approved by the Institutional Review Board of our hospital. We estimated the sensitivity and prevalence of the study population for ST DVAB by two types of approaches: for the type I approach, the gold standards were surgical correlation or postbiopsy mammographic follow-up. For the type II approach using Bayesian modeling by a beta-binomial model, the only gold standard was surgical correlation and the predicted number of cancerous lesions in those patients without surgical correlation was estimated. RESULTS: For the type I approach, the sensitivity was 92.3%, and the prevalence 12.6%. For the type II approach, the mean sensitivity of ST DVAB was 89%, and the mean prevalence was 15%. We predicted that an average of 1.7 cancerous lesions occurred among those lesions without surgical correlation by the Bayesian estimation. CONCLUSIONS: The mean sensitivity of ST DVAB using the Bayesian (type II) approach was lower than that using the type I approach, because we regarded the surgery as the only gold standard in Bayesian modeling and the nonoperated lesions were thought to be with unknown true disease status. The Bayesian approach is thus more appropriate to use than the type I approach when the gold standard is incomplete.