Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death worldwide. Most patients with advanced HCC acquire sorafenib resistance. Drug resistance reflects the heterogeneity of tumors and is the main cause of tumor recurrence and death.We identified and validated sorafenib resistance related-genes (SRGs) as prognostic biomarkers for HCC. We obtained SRGs from the Gene Expression Omnibus and selected four key SRGs using the least absolute shrinkage and selection operator, random forest, and Support Vector Machine-Recursive feature elimination machine learning algorithms. Samples from the The Cancer Genome Atlas (TCGA)-HCC were segregated into two groups by consensus clustering. Following difference analysis, 19 SRGs were obtained through univariate Cox regression analysis, and a sorafenib resistance model was constructed for risk stratification and prognosis prediction. In multivariate Cox regression analysis, the risk score was an independent predictor of overall survival (OS). Patients classified as high-risk were more sensitive to other chemotherapy drugs and showed a higher expression of the common immune checkpoints. Additionally, the expression of drug-resistance genes was verified in the International Cancer Genome Consortium cohort. A nomogram model with a risk score was established, and its prediction performance was verified by calibration chart analysis of the TCGA-HCC cohort. We conclude that there is a significant correlation between sorafenib resistance and the tumor immune microenvironment in HCC. The risk score could be used to identify a reliable prognostic biomarker to optimize the therapeutic benefits of chemotherapy and immunotherapy, which can be helpful in the clinical decision-making for HCC patients.

In this Viewpoint we discuss how experimental medicine applied in the setting of clinical trials can address unmet need in the prototypic autoimmune disease systemic lupus erythematosus (SLE) to improve outcomes for patients.

Autistic spectrum disorder (ASD) is a complicated developmental disease characterized by persistent difficulties in social interaction, speech and nonverbal communication, and restricted/ repetitive activities. Our goal is to deliver a step ahead awareness on neurodevelopment in ASD through early behavioral screenings, genetic testing, and detection of various environmental triggers. This would significantly reduce the tally of people with autistic characteristics. As of now, much work is to be done in understanding and treating ASD. Firstly, awareness campaigns must be organized and maintained so that ASD children can be identified and treated feasibly. Secondly, prenatal and prepregnancy environmental risk awareness, including advice against consanguineous marriages, information on optimum mother nutrition, and minimizing pollutants exposure, can be focused. Finally, the extension of genetic screening along with early postnatal monitoring of newborn feeding, nutrition, and eye contact will help in early therapy. People with ASD have strict dietary habits, but they are also more prone to gastrointestinal problems, including diarrhoea, constipation, and sometimes irritable bowel syndrome. Despite significant studies on the symptoms and possible causes of ASD, GI dysfunction is becoming a hot issue of discussion. Dietary strategies can partially help to alleviate both GI and behavioural issues due to the link between gut-microbiota and brain activity. Dietary treatments may be less expensive, easier to administer and have fewer adverse effects than pharmacological interventions. Hence, there is an increasing interest in autistic children\'s customized diets and supplements. Future studies should look at whether these diets are applicable to diverse people and whether they are practical in various circumstances (areas with fewer resources, lower socioeconomic areas, countries with different dietary restrictions, etc.). The dietary phytochemicals, including curcumin, resveratrol, naringenin, and sulforaphane, have a substantial role as neurotherapeutic agents. These agents can act as an antioxidant, immunomodulator, gut microbiota modulator and Nrf2 activator to provide benefits to ASD patients. Hence an urgent need is to create brain-targeted delivery methods for these dietary phytochemicals and to investigate their therapeutic value in ASD.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD). Its etiology is unclear. Much evidence suggests that the death of abnormal intestinal epithelial cells (IECs) leads to intestinal barrier disruption, and the subsequent inflammatory response plays a vital role in UC. Pyroptosis is a form of programmed inflammatory cell death, and the role of pyroptosis in UC etiology remains to be explored. This study identified 10 hub genes in pyroptosis by gene expression profiles obtained from the GSE87466 dataset. Meanwhile, the biomarkers were screened based on gene significance (GS) and module membership (MM) through the Weighted Gene Co-Expression Network Analysis (WGCNA). The following analysis indicated that hub genes were closely associated with the UC progression and therapeutic drug response. The single-cell RNA (scRNA) sequencing data from UC patients within the GSE162335 dataset indicated that macrophages were most related to pyroptosis. Finally, the expression of hub genes and response to the therapeutic drug [5-aminosalicylic acid (5-ASA)] were verified in dextran sulfate sodium (DSS)-induced colitis mice. Our study identified IL1B as the critical pyroptosis-related biomarker in UC. The crosstalk between macrophage pyroptosis and IEC pyroptosis may play an essential role in UC, deserving further exploration.

There is an urgent need for analgesics with improved efficacy, especially in neuropathic and other chronic pain conditions. Unfortunately, in recent decades, many candidate analgesics have failed in clinical phase II or III trials despite promising preclinical results. Translational assessment tools to verify engagement of pharmacological targets and actions on compartments of the nociceptive system are missing in both rodents and humans. Through the Innovative Medicines Initiative of the European Union and EFPIA, a consortium of researchers from academia and the pharmaceutical industry was established to identify and validate a set of functional biomarkers to assess drug-induced effects on nociceptive processing at peripheral, spinal and supraspinal levels using electrophysiological and functional neuroimaging techniques. Here, we report the results of a systematic literature search for pharmacological probes that allow for validation of these biomarkers. Of 26 candidate substances, only 7 met the inclusion criteria: evidence for nociceptive system modulation, tolerability, availability in oral form for human use and absence of active metabolites. Based on pharmacokinetic characteristics, three were selected for a set of crossover studies in rodents and healthy humans. All currently available probes act on more than one compartment of the nociceptive system. Once validated, biomarkers of nociceptive signal processing, combined with a pharmacometric modelling, will enable a more rational approach to selecting dose ranges and verifying target engagement. Combined with advances in classification of chronic pain conditions, these biomarkers are expected to accelerate analgesic drug development.

Dimethyl fumarate (DMF) is an immunomodulatory treatment for multiple sclerosis (MS). Despite its wide clinical use, the mechanisms underlying clinical response are not understood. This study aimed to reveal immune markers of therapeutic response to DMF treatment in MS. For this purpose, we prospectively collected peripheral blood mononuclear cells (PBMCs) from a highly characterized cohort of 44 individuals with MS before and at 12 and 48 wk of DMF treatment. Single cells were profiled using high-dimensional mass cytometry. To capture the heterogeneity of different immune subsets, we adopted a bioinformatic multipanel approach that allowed cell population-cluster assignment of more than 50 different parameters, including lineage and activation markers as well as chemokine receptors and cytokines. Data were further analyzed in a semiunbiased fashion implementing a supervised representation learning approach to capture subtle longitudinal immune changes characteristic for therapy response. With this approach, we identified a population of memory T helper cells expressing high levels of neuroinflammatory cytokines (granulocyte-macrophage colony-stimulating factor [GM-CSF], interferon γ [IFNγ]) as well as CXCR3, whose abundance correlated with treatment response. Using spectral flow cytometry, we confirmed these findings in a second cohort of patients. Serum neurofilament light-chain levels confirmed the correlation of this immune cell signature with axonal damage. The identified cell population is expanded in peripheral blood under natalizumab treatment, substantiating a specific role in treatment response. We propose that depletion of GM-CSF-, IFNγ-, and CXCR3-expressing T helper cells is the main mechanism of action of DMF and allows monitoring of treatment response.

To accelerate the translation of cancer nanomedicine, we used an integrated genomic approach to improve our understanding of the cellular processes that govern nanoparticle trafficking. We developed a massively parallel screen that leverages barcoded, pooled cancer cell lines annotated with multiomic data to investigate cell association patterns across a nanoparticle library spanning a range of formulations with clinical potential. We identified both materials properties and cell-intrinsic features that mediate nanoparticle-cell association. Using machine learning algorithms, we constructed genomic nanoparticle trafficking networks and identified nanoparticle-specific biomarkers. We validated one such biomarker: gene expression of SLC46A3, which inversely predicts lipid-based nanoparticle uptake in vitro and in vivo. Our work establishes the power of integrated screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations.

To explore biomarkers of Pien Tze Huang that ameliorated the symptoms of hepatic fibrosis.
Two groups of carbon tetrachloride-induced hepatic fibrosis (HF) mice model were constructed in our study: one group received PZH treatment and another group received no treatment. We performed this study to investigate the role of PZH in the regulation process of hepatic fibrosis.
We identified 31 down-regulated and 39 up-regulated miRNAs using small RNA-seq analysis. Combining RNA-Seq data analysis, our study revealed 7 significant target genes (Sp4, Slc2a6, Tln2, Hmga2, Ank3, Pax9, Fgf9). The results of real-time quantitative polymerase chain reaction analysis suggested that the expression level of 6 genes (Sp4, Tln2, Hmga2, Ank3, Pax9, Fgf9) were down-regulated compared to control group. On the other hand, the expression level of Slc2a6 appeared to be up-regulated. The protein mass spectrometry showed that PZH group had lower protein expression of Tln2 compared to control group.
We identified 7 genes that were significantly related to PZH response in HF mice using multiple conjoint analysis methods. These genes could participate in underlying regulation mechanism of hepatic fibrosis during PZH treatment.

Paclitaxel (PTX) is one of the most potent and commonly used chemotherapies for breast and pancreatic cancer. Several ongoing clinical trials are investigating means of enhancing delivery of PTX across the blood-brain barrier for glioblastomas. Despite the widespread use of PTX for breast cancer, and the initiative to repurpose this drug for gliomas, there are no predictive biomarkers to inform which patients will likely benefit from this therapy.
To identify predictive biomarkers for susceptibility to PTX, we performed a genome-wide CRISPR knockout (KO) screen using human glioma cells. The genes whose KO was most enriched in the CRISPR screen underwent further selection based on their correlation with survival in the breast cancer patient cohorts treated with PTX and not in patients treated with other chemotherapies, a finding that was validated on a second independent patient cohort using progression-free survival.
Combination of CRISPR screen results with outcomes from patients with taxane-treated breast cancer led to the discovery of endoplasmic reticulum (ER) protein SSR3 as a putative predictive biomarker for PTX. SSR3 protein levels showed positive correlation with susceptibility to PTX in breast cancer cells, glioma cells, and in multiple intracranial glioma xenografts models. KO of SSR3 turned the cells resistant to PTX while its overexpression sensitized the cells to PTX. Mechanistically, SSR3 confers susceptibility to PTX through regulation of phosphorylation of ER stress sensor IRE1α.
Our hypothesis generating study showed SSR3 as a putative biomarker for susceptibility to PTX, warranting its prospective clinical validation.

OBJECTIVE: The antisense oligonucleotide nusinersen (Spinraza) regulates splicing of the survival motor neuron 2 (SMN2) messenger RNA to increase SMN protein expression. Nusinersen has improved ventilator-free survival and motor function outcomes in infantile onset forms of spinal muscular atrophy (SMA), treated early in the course of the disease. However, the response in later onset forms of SMA is highly variable and dependent on symptom severity and disease duration at treatment initiation. Therefore, we aimed to identify novel noninvasive biomarkers that could predict the response to nusinersen in type II and III SMA patients.
METHODS: Thirty-four SMA patients were included. We applied next generation sequencing to identify microRNAs in the cerebrospinal fluid (CSF) as candidate biomarkers predicting response to nusinersen. Hammersmith Functional Motor Scale Expanded (HFMSE) was conducted at baseline and 6 months after initiation of nusinersen therapy to assess motor function. Patients changing by ≥3 or ≤0 points in the HFMSE total score were considered to be responders or nonresponders, respectively.
RESULTS: Lower baseline levels of two muscle microRNAs (miR-206 and miR-133a-3p), alone or in combination, predicted the clinical response to nusinersen after 6 months of therapy. Moreover, miR-206 levels were inversely correlated with the HFMSE score.
CONCLUSIONS: Lower miR-206 and miR-133a-3p in the CSF predict more robust clinical response to nusinersen treatment in later onset SMA patients. These novel findings have high clinical relevance for identifying early treatment response to nusinersen in later onset SMA patients and call for testing the ability of miRNAs to predict more sustained long-term benefit.