Deconvolution of clinical variance in CAR-T cell pharmacology and response.

Chimeric antigen receptor T cell (CAR-T) expansion and persistence vary widely among patients and predict both efficacy and toxicity. However, the mechanisms underlying clinical outcomes and patient variability are poorly defined. In this study, we developed a mathematical description of T cell responses wherein transitions among memory, effector and exhausted T cell states are coordinately regulated by tumor antigen engagement.

Identification and stratification of systemic lupus erythematosus patients into two transcriptionally distinct clusters based on IFN-I signature.

Objective: Despite the significant advancement in the understanding of the pathophysiology of systemic lupus erythematosus (SLE) variable clinical response to newer therapies remain a major concern, especially for patients with lupus nephritis and neuropsychiatric systemic lupus erythematosus (NPSLE). We performed this study with an objective to comprehensively characterize Indian SLE patients with renal and neuropsychiatric manifestation with respect to their gene signature, cytokine profile and immune cell phenotypes.

Methods: We characterized 68 Indian SLE subjects with diverse clinical profiles and disease activity and tried to identify differentially expressed genes and enriched pathways.

Transporter Activity Changes in Nonalcoholic Steatohepatitis: Assessment with Plasma Coproporphyrin I and III.

Expression and functional changes in the organic anion transporting polypeptide (OATP)-multidrug resistance-associated protein (MRP) axis of transporters are well reported in patients with nonalcoholic steatohepatitis (NASH). These changes can impact plasma and tissue disposition of endo- and exogenous compounds. The transporter alterations are often assessed by administration of a xenobiotic or by transporter proteomic analysis from liver biopsies.

Considerations for Optimization of High-Throughput Sequencing Bioinformatics Pipelines for Virus Detection.

High-throughput sequencing (HTS) has demonstrated capabilities for broad virus detection based upon discovery of known and novel viruses in a variety of samples, including clinical, environmental, and biological. An important goal for HTS applications in biologics is to establish parameter settings that can afford adequate sensitivity at an acceptable computational cost (computation time, computer memory, storage, expense or/and efficiency), at critical steps in the bioinformatics pipeline, including initial data quality assessment, trimming/cleaning, and assembly (to reduce data volume and increase likelihood of appropriate sequence identification). Additionally, the quality and reliability of the results depend on the availability of a complete and curated viral database for obtaining accurate results; selection of sequence alignment programs and their configuration, that retains specificity for broad virus detection with reduced false-positive signals; removal of host sequences without loss of endogenous viral sequences of interest; and use of a meaningful reporting format, which can retain critical information of the analysis for presentation of readily interpretable data and actionable results.

A Multicenter Study To Evaluate the Performance of High-Throughput Sequencing for Virus Detection.

The capability of high-throughput sequencing (HTS) for detection of known and unknown viruses makes it a powerful tool for broad microbial investigations, such as evaluation of novel cell substrates that may be used for the development of new biological products. However, like any new assay, regulatory applications of HTS need method standardization. Therefore, our three laboratories initiated a study to evaluate performance of HTS for potential detection of viral adventitious agents by spiking model viruses in different cellular matrices to mimic putative materials for manufacturing of biologics.

Systems approach for the selection of micro-RNAs as therapeutic biomarkers of anti-EGFR monoclonal antibody treatment in colorectal cancer.

miRNA plays an important role in tumourgenesis by regulating expression of oncogenes and tumour suppressors. Thus affects cell proliferation and differentiation, apoptosis, invasion and angiogenesis. miRNAs are potential biomarkers for diagnosis, prognosis and therapies of different forms of cancer.

Molecular biomarkers in clinical development: what could we learn from the clinical trial registry?

Aim: Objective of this research is to assess whether the trend of stratified medicine widely discussed in scientific literature is translated into real clinical trials registered in ClinicalTrials.gov .

Methods: By semi-automatic screening of over 150,000 trials, we filtered trials with stratified biomarker to analyze their therapeutic focus, major drivers and elucidated the impact of stratified biomarker programs on trial duration and completion.

Challenges and opportunities for oncology biomarker discovery.

Recent success of companion diagnostics along with the increasing regulatory pressure for better identification of the target population has created an unprecedented incentive for drug discovery companies to invest in novel strategies for biomarker discovery. In parallel with the rapid advancement and clinical adoption of high-throughput technologies, a number of knowledge management and systems biology approaches have been developed to analyze an ever increasing collection of OMICs data. This review discusses current biomarker discovery technologies highlighting challenges and opportunities of knowledge capturing and presenting a perspective of the future integrative modeling approaches as an emerging trend in biomarker prediction.