Gene profiling in active dermatitis lesions strengthens the diagnosis of allergic contact dermatitis

BACKGROUND

Distinguishing between allergic and nonallergic forms of Contact Dermatitis (CD) is challenging and requires investigations based on patch-testing. Early detection of allergy biomarkers in active CD lesions could refine and simplify the management of CD patients.

OBJECTIVE

To characterize the molecular signatures of active CD lesions.

METHODS

We studied the expression of 12 allergy biomarkers by qRT-PCR in active lesions of 38 CD patients. Allergic CD (ACD) was diagnosed based on patch test (PT) results and exposure assessment. Molecular signatures of active lesions, as well as positive PT reactions, were compared with those of reference chemical allergens and irritants.

RESULTS

Nineteen of the 38 CD patients reacted positively upon patch-testing and exposure assessment confirmed ACD diagnosis for 17 of them. Gene profiling of active CD lesions revealed 2 distinct molecular patterns: patients harboring signatures similar to reference allergens (n = 23) or irritants (n = 15). Among the 23 patients with an "allergy signature," we found the 17 patients with confirmed ACD, while no culprit allergen was identified for the 6 other patients. Interestingly, the 15 patients without biomarker induction had negative PT, suggesting that they developed nonallergic CD reactions.

CONCLUSION

Molecular signatures from active skin lesions may help to stratify CD patients and predict those suffering from ACD.

Free Radical-Associated Gene Signature Predicts Survival in Sepsis Patients

Sepsis continues to overwhelm hospital systems with its high mortality rate and prevalence. A strategy to reduce the strain of sepsis on hospital systems is to develop a diagnostic/prognostic measure that identifies patients who are more susceptible to septic death. Current biomarkers fail to achieve this outcome, as they only have moderate diagnostic power and limited prognostic capabilities. Sepsis disrupts a multitude of pathways in many different organ systems, making the identification of a single powerful biomarker difficult to achieve. However, a common feature of many of these perturbed pathways is the increased generation of reactive oxygen species (ROS), which can alter gene expression, changes in which may precede the clinical manifestation of severe sepsis. Therefore, the aim of this study was to evaluate whether ROS-related circulating molecular signature can be used as a tool to predict sepsis survival. Here we created a ROS-related gene signature and used two Gene Expression Omnibus datasets from whole blood samples of septic patients to generate a 37-gene molecular signature that can predict survival of sepsis patients. Our results indicate that peripheral blood gene expression data can be used to predict the survival of sepsis patients by assessing the gene expression pattern of free radical-associated -related genes in patients, warranting further exploration.

Proteogenomic characterization of primary colorectal cancer and metastatic progression identifies proteome-based subtypes and signatures

Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we performed multiomics analyses of primary CRC and liver metastases. Genomic alterations, such as structural variants or copy number alterations, were enriched in oncogenes and tumor suppressor genes and increased in metastases. Unsupervised mass spectrometry-based proteomics of 135 primary and 123 metastatic CRCs uncovered distinct proteomic subtypes, three each for primary and metastatic CRCs, respectively. Integrated analyses revealed that hypoxia, stemness, and immune signatures characterize these 6 subtypes. Hypoxic CRC harbors high epithelial-to-mesenchymal transition features and metabolic adaptation. CRC with a stemness signature shows high oncogenic pathway activation and alternative telomere lengthening (ALT) phenotype, especially in metastatic lesions. Tumor microenvironment analysis shows immune evasion via modulation of major histocompatibility complex (MHC) class I/II and antigen processing pathways. This study characterizes both primary and metastatic CRCs and provides a large proteogenomics dataset of metastatic progression.

The Epigenetic Regulation of Quiescent in Stem Cells

This review article discusses the epigenetic regulation of quiescent stem cells. Quiescent stem cells are a rare population of stem cells that remain in a state of cell cycle arrest until activated to proliferate and differentiate. The molecular signature of quiescent stem cells is characterized by unique epigenetic modifications, including histone modifications and deoxyribonucleic acid (DNA) methylation. These modifications play critical roles in regulating stem cell behavior, including maintenance of quiescence, proliferation, and differentiation. The article specifically focuses on the role of histone modifications and DNA methylation in quiescent stem cells, and how these modifications can be dynamically regulated by environmental cues. The future perspectives of quiescent stem cell research are also discussed, including their potential for tissue repair and regeneration, their role in aging and age-related diseases, and their implications for cancer research. Overall, this review provides a comprehensive overview of the epigenetic regulation of quiescent stem cells and highlights the potential of this research for the development of new therapies in regenerative medicine, aging research, and cancer biology.

Dynamic Molecular Investigation of the Solid-Electrolyte Interphase of an Anode-Free Lithium Metal Battery Using In Situ Liquid SIMS and Cryo-TEM

We use in situ liquid secondary ion mass spectroscopy, cryogenic transmission electron microscopy, and density functional theory calculation to delineate the molecular process in the formation of the solid-electrolyte interphase (SEI) layer under the dynamic operating conditions. We discover that the onset potential for SEI layer formation and the thickness of the SEI show dependence on the solvation shell structure. On a Cu film anode, the SEI is noticed to start to form at around 2.0 V (nominal cell voltage) with a final thickness of about 40-50 nm in the 1.0 M LiPF6/EC-DMC electrolyte, while for the case of 1.0 M LiFSI/DME, the SEI starts to form at around 1.5 V with a final thickness of about 20 nm. Our observations clearly indicate the inner and outer SEI layer formation and dissipation upon charging and discharging, implying a continued evolution of electrolyte structure with extended cycling.

ReProMSig: an integrative platform for development and application of reproducible multivariable models for cancer prognosis supporting guideline-based transparent reporting

Adequate reporting is essential for evaluating the performance and clinical utility of a prognostic prediction model. Previous studies indicated a prevalence of incomplete or suboptimal reporting in translational and clinical studies involving development of multivariable prediction models for prognosis, which limited the potential applications of these models. While reporting templates introduced by the established guidelines provide an invaluable framework for reporting prognostic studies uniformly, there is a widespread lack of qualified adherence, which may be due to miscellaneous challenges in manual reporting of extensive model details, especially in the era of precision medicine. Here, we present ReProMSig (Reproducible Prognosis Molecular Signature), a web-based integrative platform providing the analysis framework for development, validation and application of a multivariable prediction model for cancer prognosis, using clinicopathological features and/or molecular profiles. ReProMSig platform supports transparent reporting by presenting both methodology details and analysis results in a strictly structured reporting file, following the guideline checklist with minimal manual input needed. The generated reporting file can be published together with a developed prediction model, to allow thorough interrogation and external validation, as well as online application for prospective cases. We demonstrated the utilities of ReProMSig by development of prognostic molecular signatures for stage II and III colorectal cancer respectively, in comparison with a published signature reproduced by ReProMSig. Together, ReProMSig provides an integrated framework for development, evaluation and application of prognostic/predictive biomarkers for cancer in a more transparent and reproducible way, which would be a useful resource for health care professionals and biomedical researchers.

Identification of the HNSC88 Molecular Signature for Predicting Subtypes of Head and Neck Cancer

Head and neck squamous cell carcinoma (HNSC) exhibits genetic heterogeneity in etiologies, tumor sites, and biological processes, which significantly impact therapeutic strategies and prognosis. While the influence of human papillomavirus on clinical outcomes is established, the molecular subtypes determining additional treatment options for HNSC remain unclear and inconsistent. This study aims to identify distinct HNSC molecular subtypes to enhance diagnosis and prognosis accuracy. In this study, we collected three HNSC microarrays (n = 306) from the Gene Expression Omnibus (GEO), and HNSC RNA-Seq data (n = 566) from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes (DEGs) and validate our results. Two scoring methods, representative score (RS) and perturbative score (PS), were developed for DEGs to summarize their possible activation functions and influence in tumorigenesis. Based on the RS and PS scoring, we selected candidate genes to cluster TCGA samples for the identification of molecular subtypes in HNSC. We have identified 289 up-regulated DEGs and selected 88 genes (called HNSC88) using the RS and PS scoring methods. Based on HNSC88 and TCGA samples, we determined three HNSC subtypes, including one HPV-associated subtype, and two HPV-negative subtypes. One of the HPV-negative subtypes showed a relationship to smoking behavior, while the other exhibited high expression in tumor immune response. The Kaplan-Meier method was used to compare overall survival among the three subtypes. The HPV-associated subtype showed a better prognosis compared to the other two HPV-negative subtypes (log rank, p = 0.0092 and 0.0001; hazard ratio, 1.36 and 1.39). Additionally, within the HPV-negative group, the smoking-related subgroup exhibited worse prognosis compared to the subgroup with high expression in immune response (log rank, p = 0.039; hazard ratio, 1.53). The HNSC88 not only enables the identification of HPV-associated subtypes, but also proposes two potential HPV-negative subtypes with distinct prognoses and molecular signatures. This study provides valuable strategies for summarizing the roles and influences of genes in tumorigenesis for identifying molecular signatures and subtypes of HNSC.

A Diagnostic Gene-Expression Signature in Fibroblasts of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disease with limited treatment options. Diagnosis can be difficult due to the heterogeneity and non-specific nature of the initial symptoms, resulting in delays that compromise prompt access to effective therapeutic strategies. Transcriptome profiling of patient-derived peripheral cells represents a valuable benchmark in overcoming such challenges, providing the opportunity to identify molecular diagnostic signatures. In this study, we characterized transcriptome changes in skin fibroblasts of sporadic ALS patients (sALS) and controls and evaluated their utility as a molecular classifier for ALS diagnosis. Our analysis identified 277 differentially expressed transcripts predominantly involved in transcriptional regulation, synaptic transmission, and the inflammatory response. A support vector machine classifier based on this 277-gene signature was developed to discriminate patients with sALS from controls, showing significant predictive power in both the discovery dataset and in six independent publicly available gene expression datasets obtained from different sALS tissue/cell samples. Taken together, our findings support the utility of transcriptional signatures in peripheral cells as valuable biomarkers for the diagnosis of ALS.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

Molecular signatures of post-traumatic stress disorder in war-zone-exposed veteran and active-duty soldiers

Post-traumatic stress disorder (PTSD) is a multisystem syndrome. Integration of systems-level multi-modal datasets can provide a molecular understanding of PTSD. Proteomic, metabolomic, and epigenomic assays are conducted on blood samples of two cohorts of well-characterized PTSD cases and controls: 340 veterans and 180 active-duty soldiers. All participants had been deployed to Iraq and/or Afghanistan and exposed to military-service-related criterion A trauma. Molecular signatures are identified from a discovery cohort of 218 veterans (109/109 PTSD+/-). Identified molecular signatures are tested in 122 separate veterans (62/60 PTSD+/-) and in 180 active-duty soldiers (PTSD+/-). Molecular profiles are computationally integrated with upstream regulators (genetic/methylation/microRNAs) and functional units (mRNAs/proteins/metabolites). Reproducible molecular features of PTSD are identified, including activated inflammation, oxidative stress, metabolic dysregulation, and impaired angiogenesis. These processes may play a role in psychiatric and physical comorbidities, including impaired repair/wound healing mechanisms and cardiovascular, metabolic, and psychiatric diseases.

A novel strategy for precise prognosis management and treatment option in colon adenocarcinoma with TP53 mutations

Background

TP53 is one of the most frequent mutated genes in colon cancer. Although colon cancer with TP53 mutations has a high risk of metastasis and worse prognosis generally, it showed high heterogeneity clinically.

Methods

A total of 1,412 colon adenocarcinoma (COAD) samples were obtained from two RNA-seq cohorts and three microarray cohorts, including the TCGA-COAD (N = 408), the CPTAC-COAD (N = 106), GSE39582 (N = 541), GSE17536 (N = 171) and GSE41258 (N = 186). The LASSO-Cox method was used to establish the prognostic signature based on the expression data. The patients were divided into high-risk and low-risk groups based on the median risk score. The efficiency of the prognostic signature was validated in various cohorts, including TP53-mutant and TP53 wild-type. The exploration of potential therapeutic targets and agents was performed by using the expression data of TP53-mutant COAD cell lines obtained from the CCLE database and the corresponding drug sensitivity data obtained from the GDSC database.

Results

A 16-gene prognostic signature was established in TP53-mutant COAD. The high-risk group had significantly inferior survival time compared to the low-risk group in all TP53-mutant datasets, while the prognostic signature failed to classify the prognosis of COAD with TP53 wild-type properly. Besides, the risk score was the independent poor factor for the prognosis in TP53-mutant COAD and the nomogram based on the risk score was also shown good predictive efficiency in TP53-mutant COAD. Moreover, we identified SGPP1, RHOQ, and PDGFRB as potential targets for TP53-mutant COAD, and illuminated that the high-risk patients might benefit from IGFR-3801, Staurosporine, and Sabutoclax.

Conclusion

A novel prognostic signature with great efficiency was established especially for COAD patients with TP53 mutations. Besides, we identified novel therapeutic targets and potential sensitive agents for TP53-mutant COAD with high risk. Our findings provided not only a new strategy for prognosis management but also new clues for drug application and precision treatment in COAD with TP53 mutations.

A prediction model identifying glycolysis signature as therapeutic target for psoriasis

Background

The hyperproliferation featured with upregulated glycolysis is a hallmark of psoriasis. However, molecular difference of keratinocyte glycolysis amongst varied pathologic states in psoriasis remain elusive.

Objectives

To characterize glycolysis status of psoriatic skin and assess the potential of glycolysis score for therapeutic decision.

Methods

We analyzed 345414 cells collected from different cohorts of single-cell RNA seq database. A new method, Scissor, was used to integrate the phenotypes in GSE11903 to guide single-cell data analysis, allowing identification of responder subpopulations. AUCell algorithm was performed to evaluate the glycolysis status of single cell. Glycolysis signature was used for further ordering in trajectory analysis. The signature model was built with logistic regression analysis and validated using external datasets.

Results

Keratinocytes (KCs) expressing SLC2A1 and LDH1 were identified as a novel glycolysis-related subpopulation. Scissor⁺ cells and Scissor^- cells were defined as response and non-response phenotypes. In Scissor⁺ SLC2A1⁺ LDH1⁺ KCs, ATP synthesis pathway was activated, especially, the glycolysis pathway being intriguing. Based on the glycolysis signature, keratinocyte differentiation was decomposed into a three-phase trajectory of normal, non-lesional, and lesional psoriatic cells. The area under the curve (AUC) and Brier score (BS) were used to estimate the performance of the glycolysis signature in distinguishing response and non-response samples in GSE69967 (AUC =0.786, BS =17.7) and GSE85034 (AUC=0.849, BS=11.1). Furthermore, Decision Curve Analysis suggested that the glycolysis score was clinically practicable.

Conclusion

We demonstrated a novel glycolysis-related subpopulation of KCs, identified 12-glycolysis signature, and validated its promising predictive efficacy of treatment effectiveness.

A Novel Molecular Signature of Cancer-Associated Fibroblasts Predicts Prognosis and Immunotherapy Response in Pancreatic Cancer

Cancer-associated fibroblasts (CAFs), a prominent population of stromal cells, play a crucial role in tumor progression, prognosis, and treatment response. However, the relationship among CAF-based molecular signatures, clinical outcomes, and tumor microenvironment infiltration remains largely elusive in pancreatic cancer (PC). Here, we collected multicenter PC data and performed integrated analysis to investigate the role of CAF-related genes (CRGs) in PC. Firstly, we demonstrated that α-SMA⁺ CAFs were the most prominent stromal components and correlated with the poor survival rates of PC patients in our tissue microarrays. Then, we discriminated two diverse molecular subtypes (CAF clusters A and B) and revealed the significant differences in the tumor immune microenvironment (TME), four reported CAF subpopulations, clinical characteristics, and prognosis in PC samples. Furthermore, we analyzed their association with the immunotherapy response of PC patients. Lastly, a CRG score was constructed to predict prognosis, immunotherapy responses, and chemosensitivity in pancreatic cancer patients. In summary, these findings provide insights into further research targeting CAFs and their TME, and they pave a new road for the prognosis evaluation and individualized treatment of PC patients.

Patient outcomes improve when a molecular signature test guides treatment decision-making in rheumatoid arthritis

BACKGROUND

The molecular signature response classifier (MSRC) predicts tumor necrosis factor-ɑ inhibitor (TNFi) non-response in rheumatoid arthritis. This study evaluates decision-making, validity, and utility of MSRC testing.

METHODS

This comparative cohort study compared an MSRC-tested arm (N = 627) from the Study to Accelerate Information of Molecular Signatures (AIMS) with an external control arm (N = 2721) from US electronic health records. Propensity score matching was applied to balance baseline characteristics. Patients initiated a biologic/targeted synthetic disease-modifying antirheumatic drug, or continued TNFi therapy. Odds ratios (ORs) for six-month response were calculated based on clinical disease activity index (CDAI) scores for low disease activity/remission (CDAI-LDA/REM), remission (CDAI-REM), and minimally important differences (CDAI-MID) .

RESULTS

In MSRC-tested patients, 59% had a non-response signature and 70% received MSRC-aligned therapy . In TNFi-treated patients, the MSRC had an 88% PPV and 54% sensitivity. MSRC-guided patients were significantly (p < 0.0001) more likely to respond to b/tsDMARDs than those treated according to standard care (CDAI-LDA/REM: 36.0% vs 21.9%, OR 2.01[1.55-2.60]; CDAI-REM: 10.4% vs 3.6%, OR 3.14 [1.94-5.08]; CDAI-MID: 49.5% vs 32.8%, OR 2.01[1.58-2.55]).

CONCLUSION

MSRC clinical validity supports high clinical utility: guided treatment selection resulted in significantly superior outcomes relative to standard care; nearly three times more patients reached CDAI remission.

Prognostic of recurrence and survival in poorly differentiated thyroid cancer

The prognosis of poorly differentiated thyroid carcinomas (PDTC) defined by the Turin criteria is variable. The aim of this study on 51 PDTC patients was to determine clinical, histological and molecular prognostic factors associated with recurrence in patients with localized disease at initial treatment and with overall survival in patients with distant metastases. Of 40 patients for whom next-generation sequencing (NGS) by ThyroSeq v3 was able to be performed on historical samples, we identified high-risk molecular signature (TERT, TP53 mutations) in 24 (60%) cases, intermediate risk signature in 9 (22.5%) cases and low-risk signature in 7 (17.5%) cases. Potentially actionable mutations were identified in 10% of cases. After a median follow-up of 57.5 months, recurrence occurred in 11 (39%) of the 28 patients with localized disease. The American Thyroid Association (ATA) high risk of relapse, high mitotic count, high molecular risk signature and CD163 expression were associated with recurrence (P = 0.009, 0.01, 0.049, 0.03 respectively). After a median follow-up of 49.5 months, thyroid cancer-related death occurred in 53% of the patients with distant metastases. There was no significant prognostic factor associated with death in univariate analysis. However, none of the patients with intermediate ATA risk of recurrence and none of the patients with low-risk molecular signature died from the disease. In addition, high molecular-risk signature was associated with the presence of synchronous or metachronous distant metastasis (P = 0.007) and with poor overall survival (P = 0.01). In conclusion, ATA risk of relapse and high mitotic count was associated with higher rate of recurrence in localized PDTC. High molecular-risk signature was associated with the presence of distant metastasis and poor overall survival. Further studies are needed to determine if molecular testing adds to ATA risk stratification or response to therapy in predicting outcomes.

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma.

Network-based response module comprised of gene expression biomarkers predicts response to infliximab at treatment initiation in ulcerative colitis

This cross-cohort study aimed to (1) determine a network-based molecular signature that predicts the likelihood of inadequate response to the tumor necrosis factor-ɑ inhibitor (TNFi) therapy, infliximab, in ulcerative colitis (UC) patients, and (2) address biomarker irreproducibility across different cohort studies. Whole-transcriptome microarray data were derived from biopsies of affected colon tissue from 2 cohorts of infliximab-treated UC patients (training N = 24 and validation N = 22). Response was defined as endoscopic and histologic healing at 4-6 weeks and 8 weeks, respectively. From the training cohort, genes with RNA expression that significantly correlated with clinical response outcomes were mapped onto the Human Interactome network map of protein-protein interactions to identify a largest connected component (LCC) of proteins indicative of infliximab response status in UC. Expression levels of transcripts within the LCC were fed into a probabilistic neural network model to generate a classifier that predicts inadequate response to infliximab. A classifier predictive of inadequate response to infliximab was generated and tested in a cross-cohort, blinded fashion; the AUC was 0.83 and inadequate response was predicted with a 100% positive predictive value and 64% sensitivity. Genes separately identified from the 2 cohorts that correlated with response to infliximab appeared distinct but mapped onto the same network region of the Human Interactome, reflecting a common underlying biology of response among UC patients. Cross-cohort validation of a classifier predictive of infliximab response status in UC patients indicates that a molecular signature of non-response to TNFi therapies is present in patients' baseline gene expression data. The goal is to develop a diagnostic test that predicts which patients will have an inadequate response to targeted therapies and define new targets and pathways for therapeutic development.

The elusive transcriptional memory trace

Memory is the brain faculty to store and remember information. It is a sequential process in which four different phases can be distinguished: encoding or learning, consolidation, storage and reactivation. Since the discovery of the first Drosophila gene essential for memory formation in 1976, our knowledge of its mechanisms has progressed greatly. The current view considers the existence of engrams, ensembles of neuronal populations whose activity is temporally coordinated and represents the minimal correlate of experience in brain circuits. In order to form and maintain the engram, protein synthesis and, probably, specific transcriptional program(s) is required. The immediate early gene response during learning process has been extensively studied. However, a detailed description of the transcriptional response for later memory phases was technically challenging. Recent advances in transcriptomics have allowed us to tackle this biological problem. This review summarizes recent findings in this field, and discusses whether or not it is possible to identify a transcriptional trace for memory.

Improvement in clinical disease activity index when treatment selection is informed by the tumor necrosis factor-ɑ inhibitor molecular signature response classifier: analysis from the study to accelerate information of molecular signatures in rheumatoid arthritis

BACKGROUND

A blood-based molecular signature response classifier (MSRC) predicts non-response to tumor necrosis factor-ɑ inhibitors (TNFi) in rheumatoid arthritis (RA).

RESEARCH DESIGN AND METHODS

This is an interim analysis of data collected in the Study to Accelerate Information of Molecular Signatures (AIMS) in RA from patients who received the MSRC test between September 2020 and November 2021. Absolute changes in clinical disease activity index (CDAI) scores from baseline were evaluated at 12 weeks (n = 470) and 24 weeks (n = 274).

RESULTS

Predicted TNFi non-responders who received a biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) with an alternative mechanism of action (altMOA) experienced up to 1.8-fold greater improvements in CDAI scores than those treated with a TNFi (12 weeks: 12.2 vs 8.0; p-value = 0.083; 24 weeks: 14.2 vs 7.8 p-value = 0.009). In patients with a molecular signature of non-response to TNFi in high disease activity at baseline, this corresponded to 43.2% relative improvement in achieving a lower CDAI disease activity level when likely TNFi non-responders were treated with a non-TNFi therapy (38.9% vs 55.7%). Commensurate improvements in efficiency of spend are expected when TNFi are avoided in favor of altMOA.

CONCLUSIONS

RA treatment selection informed by MSRC test results improves clinical outcomes in real-world care and offers improvements in efficiency of healthcare spending.

Molecular and Functional Signatures Associated with CAR T Cell Exhaustion and Impaired Clinical Response in Patients with B Cell Malignancies

Despite the high rates of complete remission following chimeric antigen receptor (CAR) T cell therapy, its full capacity is currently limited by the generation of dysfunctional CAR T cells. Senescent or exhausted CAR T cells possess poor targeting and effector functions, as well as impaired cell proliferation and persistence in vivo. Strategies to detect, prevent or reverse T cell exhaustion are therefore required in order to enhance the effectiveness of CAR T immunotherapy. Here we report that CD19 CAR T cells from non-responding patients with B cell malignancies show enrichment of CD8⁺ cells with exhausted/senescent phenotype and display a distinct transcriptional signature with dysregulation of genes associated with terminal exhaustion. Furthermore, CAR T cells from non-responding patients exhibit reduced proliferative capacity and decreased IL-2 production in vitro, indicating functional impairment. Overall, our work reveals potential mediators of resistance, paving the way to studies that will enhance the efficacy and durability of CAR T therapy in B cell malignancies.

A Novel Ferroptosis-Based Molecular Signature Associated with Biochemical Recurrence-Free Survival and Tumor Immune Microenvironment of Prostate Cancer

Objective: To identify ferroptosis-related molecular clusters, and to develop and validate a ferroptosis-based molecular signature for predicting biochemical recurrence-free survival (BCRFS) and tumor immune microenvironment of prostate cancer (PCa). Materials and Methods: The clinical data and transcriptome data of PCa were downloaded from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained from FerrDb database. We performed consensus clustering analysis to identify ferroptosis-related molecular subtypes for PCa. Univariate and multivariate Cox regression analysis were used to establish a ferroptosis-based signature for predicting BCRFS. Internal verification, external verification and subgroup survival analysis were then successfully performed. Results: There was a total of 40 differentially expressed FRGs in PCa. We then identified three ferroptosis-related molecular clusters of PCa, which have significantly different immune infiltrating cells, tumor immune microenvironment and PD-L1 expression level. More importantly, a novel ferroptosis-based signature for predicting BCRFS of PCa based on four FRGs (including ASNS, GPT2, NFE2L2, RRM2) was developed. Internal and external verifications were then successfully performed. Patients with high-risk score were associated with significant poor BCRFS compared with those with low-risk score in training cohort, testing cohort and validating cohort, respectively. The area under time-dependent Receiver Operating Characteristic (ROC) curve were 0.755, 0.705 and 0.726 in training cohort, testing cohort and validating cohort, respectively, indicating the great performance of this signature. Independent prognostic analysis indicated that this signature was an independent predictor for BCRFS of PCa. Subgroup analysis revealed that this signature was particularly suitable for younger or stage T III-IV or stage N0 or cluster 1-2 PCa patients. Patients with high-risk score have significantly different tumor immune microenvironment in comparison with those with low-risk score. The results of qRT-PCR successfully verified the mRNA expression levels of ASNS, GPT2, RRM2 and NFE2L2 in DU-145 and RWPE-1 cells while the results of IHC staining exactly verified the relative protein expression levels of ASNS, GPT2, RRM2 and NFE2L2 between PCa and BPH tissues. Conclusions: This study successfully identified three ferroptosis-related molecular clusters. Besides, we developed and validated a novel ferroptosis-based molecular signature, which performed well in predicting BCRFS and tumor immune microenvironment of PCa.

The role of selected molecular factors in ovarian cancer metastasis

The main reason for treatment failure in ovarian cancer is chemoresistance and the presence of metastasis. Ascites, whichallows the physical movement of cancer cells, the lymphovascular pathway, and several molecular factors and signalling axes, are involved in metastasis. Ascites, with the involvement of cytokines and chemokines, MAPK/STAT1 and NOTCH as well as CXCL12/CXCR4 signaling pathways and circulating anoikis induces cancer dissemination, in particular to the peritoneum and omentum. The spread of lymphatic and bloodstream cancer cells is a multi-stage process. Tumour infiltration of the stroma and lymphovascular space (LVSI) produces biologically active cancer-associated fibroblasts and macrophages (CAFs, TAMs) that secrete numerous cytokines, chemokines and growth factors, inhibit NK function, induce epithelial-mesenchymal transition (EMT), resulting in an increase of the metastatic potential of cancer cells and the formation of cancer stem cells (CSCs). Overexpression of some genes, and microRNAs, in LVSI-(LMGS) associated with metastasis has been identified. The role of extracellular vesicles (EVs) transporting metastasis-associated factors has been described as has the role of cancer stem cells (CSCs) in chemotherapy resistance and metastasis. Sirtuins, enzymes involved in metastasis formation, have also been detected. Certain types of microRNAs (miR-509-3p, microRNA-506-3p) and melatonin have been shown to inhibit metastasis.

Clinical utility of therapy selection informed by predicted nonresponse to tumor necrosis factor-ɑ inhibitors: an analysis from the Study to Accelerate Information of Molecular Signatures (AIMS) in rheumatoid arthritis

BACKGROUND

The molecular signature response classifier (MSRC) is a blood-based precision medicine test that predicts nonresponders to tumor necrosis factor-ɑ inhibitors (TNFi) in rheumatoid arthritis (RA) so that patients with a molecular signature of non-response to TNFi can be directed to a treatment with an alternative mechanism of action.

RESEARCH DESIGN AND METHODS

This study evaluated decision choice and treatment outcomes resulting from MSRC-informed treatment selection within a real-world cohort.

RESULTS

Therapy selection by providers was informed by MSRC results for 73.5% (277/377) of patients. When MSRC results were not incorporated into decision-making, 62.0% (62/100) of providers reported deviating from test recommendations due to insurance-related restrictions. The 24-week ACR50 responses in patients prescribed a therapy in alignment with MSRC results were 39.6%. Patients with a molecular signature of non-response had significantly improved responses to non-TNFi therapies compared with TNFi therapies (ACR50 34.8% vs 10.3%, p-value = 0.05). This indicates that predicted non-responders to TNFi therapies are not nonresponders to other classes of RA targeted therapy. Significant changes were also observed for CDAI, ACR20, ACR70, and for responses at 12 weeks.

CONCLUSIONS

Adoption of the MSRC into patient care could fundamentally shift treatment paradigms in RA, resulting in substantial improvements in real-world treatment outcomes.

Molecular Signature and Immune Landscape of HCV-Associated Hepatocellular Carcinoma (HCC): Differences and Similarities with HBV-HCC

Introduction

HCC is the third leading cause of cancer-related death worldwide, with chronic viral hepatitis accounting for more than 70% of the cases. Therapeutic options are limited and ineffective. The increasing use of immune-based therapies in solid tumors highlights the need to expand our knowledge on the immunologic microenvironment of HCC.

Methods

Access to liver samples from 20 well-characterized patients with HCC associated with HCV (n = 9) or HBV (n = 11) gave us the opportunity to study the immunologic landscape in these tumors. For each patient, RNA-sequencing was performed on the tumor and surrounding nontumorous tissue.

Results

We found that both HCV- and HBV-HCC are associated with a predominance of downregulated genes (74% and 67%, respectively). Analysis of the immune landscape using a curated gene list showed 216 of 2481 (9%) immune genes in HCV-HCC and 164 of 2560 (6%) in HBV-HCC. However, only 8 immune genes (4%) were upregulated in HCV-HCC and 27 (16.5%) in HBV-HCC. HCV-HCC was characterized by an enrichment of downregulated genes related to T-cell activation and oxidative stress. The dramatic downregulation of immune genes related to T-cell activation in HCV-HCC prompted us to perform an extensive immunohistochemistry analysis on paraffin-embedded liver specimen. Interestingly, we found a significant reduction of immune-cell infiltration (CD3, CD8 and CD20 positive cells) within the tumor. Moreover, we observed that HCV-HCC is characterized by an enrichment of M2-like CD68-positive cells. These data are consistent with the dramatic downregulation of immune-cell infiltration seen in HCV-HCC. Conversely, HBV-HCC was characterized by upregulation of genes related to monocyte/macrophage activation and cell cycle control, and downregulation of genes involved in various cell metabolisms.

Conclusion

This study demonstrates a distinctive molecular signature and immune landscape in HCC of different viral etiology, which could provide new insights into pathogenesis and lead to the development of novel immune-based therapies.

Angiogenic factors could help us to define patients obtaining complete response with undetectable minimal residual disease in untreated CLL patients treated by FCR: results from the CLL2010FMP, a FILO study

Angiogenesis is in a constant balance between pro and anti-angiogenic factors. Neoangiogenesis, implicated in metastatic spreading is characterized in solid cancers, but fairly new in chronic lymphocytic leukemia (CLL). We hypothesize that secretion of angiogenic factors could be correlated to the pathogenesis of CLL, and therefore predict the outcome of patients. We investigated concentrations of 22 cytokines and chemokines in 137 non-del 17p B-CLL patients, treated with a fludarabine-cyclophosphamide-rituximab (FCR)-based regimen. We constructed a biomarker index defining different risk groups based on lymphocyte count, the intensity of CD20 antigen on CD19⁺ cells, Ang-2, and PDGF-BB plasma concentrations at diagnosis. Four groups were defined, exhibiting specific molecular signatures and correlated with progression-free survival of patients. Our results suggest that we can determine at diagnosis of non-del 17p B-CLL patients, those with a very high probability of progression-free survival, independently of IGVH mutational status and residual disease at the end of treatment.

Global mapping of cancers: The Cancer Genome Atlas and beyond

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.

Intraductal Papillary Mucinous Neoplasms of the Pancreas: A Review of Their Genetic Characteristics and Mouse Models

Simple Summary

Pancreatic cancer is one of the deadliest cancers with the lowest survival rate. Little progress has been achieved in prolonging the survival for patients with pancreatic adenocarcinoma. Hence, special attention should be paid to pre-cancerous lesions, for instance, an intraductal papillary mucinous neoplasm (IPMN). Here, we reviewed its genetic characteristics and the mouse models involving mutations in specific pathways, and updated our current perception of how this lesion develops into a precursor of invasive cancer.

Abstract

The intraductal papillary mucinous neoplasm (IPMN) is attracting research attention because of its increasing incidence and proven potential to progress into invasive pancreatic ductal adenocarcinoma (PDAC). In this review, we summarized the key signaling pathways or protein complexes (GPCR, TGF, SWI/SNF, WNT, and PI3K) that appear to be involved in IPMN pathogenesis. In addition, we collected information regarding all the genetic mouse models that mimic the human IPMN phenotype with specific immunohistochemistry techniques. The mouse models enable us to gain insight into the complex mechanism of the origin of IPMN, revealing that it can be developed from both acinar cells and duct cells according to different models. Furthermore, recent genomic studies describe the potential mechanism by which heterogeneous IPMN gives rise to malignant carcinoma through sequential, branch-off, or de novo approaches. The most intractable problem is that the risk of malignancy persists to some extent even if the primary IPMN is excised with a perfect margin, calling for the re-evaluation and improvement of diagnostic, pre-emptive, and therapeutic measures.

Characterization of Biomarkers in Colorectal Cancer Liver Metastases as a Prognostic Tool

BACKGROUND

Unfortunately, the majority of patients with colorectal cancer liver metastases (CRCLM) experience disease recurrence following hepatic surgery. The key challenge is therefore optimal patient selection, which currently relies on anatomical and clinical parameters. Exploring a potential molecular signature may be predictive for seeing a clinical benefit from CRCLM resection.

METHODS

Consecutive patients who underwent CRCLM resection at our medical center between 2006 and 2016 were divided into cohorts of "good prognosis" (GP) or "poor prognosis" (PP) based on the time interval between their resection and disease recurrence. Proteomic analysis was performed on the surgical specimen and correlation analysis was carried out with demographics and clinical outcomes.

RESULTS

Proteomic analysis revealed 99 differentially expressed proteins of which a third were associated with extracellular matrix (ECM) pathways as the matrix metalloproteinases (MMPs). Multivariate analysis yielded a statistically differential proteomic pattern between the cohort regardless of perioperative treatment.

CONCLUSION

Our results indicate a different proteomic landscape in the cohort of patients who had a clinical benefit from CRCLM resection which appears to be correlated with ECM pathways. Further prospective studies are needed to define the role of ECM pathways in prognostics and patient selection for surgical procedures for CRCLM.

A Claudin-Based Molecular Signature Identifies High-Risk, Chemoresistant Colorectal Cancer Patients

Identifying molecular characteristics that are associated with aggressive cancer phenotypes through gene expression profiling can help predict treatment responses and clinical outcomes. Claudins are deregulated in colorectal cancer (CRC). In CRC, increased claudin-1 expression results in epithelial-to-mesenchymal transition and metastasis, while claudin-7 functions as a tumor suppressor. In this study, we have developed a molecular signature based on claudin-1 and claudin-7 associated with poor patient survival and chemoresistance. This signature was validated using an integrated approach including publicly available datasets and CRC samples from patients who either responded or did not respond to standard-of-care treatment, CRC cell lines, and patient-derived rectal and colon tumoroids. Transcriptomic analysis from a patient dataset initially yielded 23 genes that were differentially expressed along with higher claudin-1 and decreased claudin-7. From this analysis, we selected a claudins-associated molecular signature including PIK3CA, SLC6A6, TMEM43, and ASAP-1 based on their importance in CRC. The upregulation of these genes and their protein products was validated using multiple CRC patient datasets, in vitro chemoresistant cell lines, and patient-derived tumoroid models. Additionally, blocking these genes improved 5-FU sensitivity in chemoresistant CRC cells. Our findings propose a new claudin-based molecular signature that associates with poor prognosis as well as characteristics of treatment-resistant CRC including chemoresistance, metastasis, and relapse.

Identification of Distinct Molecular Subtypes of Endometrioid Adenocarcinoma

Endometrial carcinoma (EC) is one of the most common gynecological cancers worldwide. Endometrioid adenocarcinoma (EAC) is the major form of EC, accounting for 75–80% of cases. Currently, there is no molecular classification system for EAC, so there are no corresponding targeted treatments. In this study, we identified two distinct molecular subtypes of EAC with different gene expression patterns and clinicopathologic characteristics. Subtype I EAC cases, accounting for the majority of cases (56%), were associated with an earlier stage, a more well-differentiated grade, a lower tumor invasion rate, and a more favorable prognosis, and the median tumor necrosis percent (15%) was also significantly higher in subtype I EAC. In contrast, subtype II EAC represents high-grade EAC, with a higher tumor invasion rate and tumor weight. The up-regulated genes in subtype I EAC were associated with the immune response, defense response, cell motion, and cell motility pathway, whereas the up-regulated genes in subtype II EAC were associated with the cell cycle, DNA replication, and RNA processing pathways. Additionally, we identified three potential subtype-specific biomarkers, comprising MDM2 (MDM2 proto-oncogene) for subtype I, and MSH2 (mutS homolog 2) and MSH6 (mutS homolog 6) for subtype II.

Role of molecular signature to differentiate second primary lung cancer from metastasis in a patient with squamous cell carcinoma of oral cavity

Background

Lung is the most common site of distant metastasis for patients with head and neck squamous cell carcinoma (HNSCC). However, differentiating second primary lung cancers from metastasis may be difficult for p16 negative HNSCC.

Case

We describe a case of oral cavity squamous cell carcinoma (SCC) who was found to have lung nodule and hilar lymphadenopathy (LAD) after surgery and radiation therapy. Hilar node was consistent with SCC however, it was difficult to differentiate second primary lung cancer and metastasis from oral cavity SCC.

Next‐generation sequencing was done for the primary oral cavity and the hilar node. Both samples had the same type of TP53 mutation and variants of unknown significance suggesting metastatic HNSCC. He was treated with a chemotherapy regimen for metastatic HNSCC.

Conclusion

Molecular studies can help to differentiate metastasis from second primary lung cancers for p16 negative HNSCC.

Correlation of NUCB2/Nesfatin-1 with Cytokine Levels in Primary Open-Angle Glaucoma

Purpose

Nesfatin-1 is produced in various tissues of the body including the hypothalamus. Neuroprotective properties of the neuropeptide hormone Nesfatin-1 were recently described. The aim of the study was to analyze the molecule Nesfatin-1 as a possible biomarker in POAG with neuroprotective properties pointing out the retinal-hypothalamic axis as target site in POAG and to obtain a molecular signature of cytokines in POAG as neuroinflammatory processes are a key factor of glaucoma development.

Methods

In this study, n=35 patients with moderate and advanced POAG (mean age 65.0y, IOP 13.9±3.0mmHg) and n=35 healthy controls (mean age 51.6y, IOP 14.3±2.7mmHg) were included. Clinical parameters including IOP, cup to disc ratio (CDR), glaucoma medication and retinal nerve fiber layer thickness (RNFL) were recorded. Plasma was collected for NUCB2/nesfatin-1 measurement using a Nesfatin-1 ELISA and for detection of 13 inflammatory cytokines using a multiplex bead-based immunoassay (MagPix). Multiple linear regression analysis was performed to adjust for confounding factors.

Results

Sex-independent or sex-dependent variables showed no significant differences in the Nesfatin-1 level (p>0.05). As a trend, an increase in NUCB2/nesfatin-1 in male glaucoma patients was found. Increased concentrations of 11 cytokines (GM-CSF, Interferon-γ, Interleukin-1β, IL-2, 4, 5, 6, 7, 10, 12 and TNF-α) were detected in POAG. The female glaucoma patients demonstrated elevated cytokine concentrations compared to male patients. NUCB2/nesfatin-1 showed a significant correlation to IL-2 and IL-13 levels in POAG. Stepwise multiple regression analysis showed no difference in NUCB2/nesfatin-1 level between POAG and healthy controls after adjusting for sex and age (all p>0.05).

Conclusion

As a trend, male POAG patients showed increased plasma NUCB2/nesfatin-1 levels. We further found inflammation as contributing factor to the pathogenesis of glaucoma, with a greater inflammatory response in women.

Developing novel drug candidates and repurposed drugs for prostate cancer based on molecular profiles

Prostate cancer (PCa) carries a growing burden on society. Lack of curative treatment and poor prognosis among patients with advanced PCa implies an urgent need for novel and improved drug identification. This is hampered by the disease's high molecular heterogeneity and complex molecular pathophysiology, resulting in drugs being efficient in few patients and cancer developing resistance to treatment. De novo drug discovery has proven to be complex and challenging. Along with technological advancements (mainly linked to -omics approaches) that allow for comprehensive characterization of the molecular changes underlying disease, and considering respective developments in bioinformatics, computational drug repurposing has emerged as a promising approach to shorten the way from discovery to clinical application and address the disease molecular complexity. With this article, we aimed at reviewing recent studies in which drugs/ compounds for PCa were defined through the investigation of molecular profiling (-omics) data and application of drug repurposing strategies. A brief overview of the technical requirements and associated challenges with the latter are also provided. For that purpose, a literature search was conducted using the PubMed database. Numerous drugs/ compounds have been proposed as potential PCa therapeutics, mostly based on the investigation of genomics and transcriptomics data. In most cases, further assessment in disease models is required. Since ultimately proteins are targeted by drugs, expanding on the use of proteomics profiling data (alone or in combination with other -omics) is expected to advance further defining new/repurposed drugs for PCa.

Panel biomarkers associated with cancer invasion and prognostic prediction for head-neck cancer

Aim: Cell invasion leading to metastasis is a major cause of treatment failure in head-neck cancers (HNCs). Identifying prognostic molecules associated with invasiveness is imperative for clinical applications. Materials & methods: A systemic approach was used to globally survey invasion-related genes, including transcriptomic profiling, pathway analysis, data mining and prognostic assessment using TCGA-HNSC dataset. Results: Six functional pathways and six hub molecules (LAMA3, LAMC2, THBS1, IGF1R, PDGFB and TGFβ1) were identified that significantly contributed to cell invasion, leading to poor survival in HNC patients. Combinations of multiple biomarkers substantially increased the probability of accurately predicting prognosis. Conclusion: Our six defined invasion-related molecules may be used as a panel signature in precision medicine for prognostic indicators or molecular therapeutic targets for HNC.

Prognostic Significance of BIRC5/Survivin in Breast Cancer: Results from Three Independent Cohorts

Simple Summary

Survivin, coded by the BIRC5 gene, is the cell death preventing protein, which is important for cell division in normal and cancer cells. It is intensively studied as a cancer biomarker and target for antitumor therapy. In this study we asked if we could get clinically helpful information on how active BIRC5 is in breast cancer patients? We studied the BIRC5 protein level in tumor samples for breast cancer patients from a West Swedish cohort and its mRNA level in two different public gene expression databases. Survival analysis demonstrated that a higher BIRC5 protein or mRNA level was associated with poor survival in all cohorts and for different cancer subtypes. We show that BIRC5 is a promising independent cancer survival marker.

Abstract

Breast cancer (BC) histological and molecular classifications significantly improved the treatment strategy and prognosis. Inhibitor of apoptosis BIRC5/survivin is often overexpressed in cancers, however, indications of its importance in BC are inconsistent. We integrate BIRC5 protein and mRNA measures with clinical associates and long-term outcome in three independent cohorts Protein levels of BIRC5 were measured in primary lysates of 845 patients of the West Swedish BC cohort (VGR-BC) and linked to 5- and 27-years survival. The results were externally validated in transcriptomic data from METABRIC and SCAN-B cohorts. Survival analysis showed that high levels of BIRC5 were consistently associated with a poor probability of 5-year overall survival. High BIRC5 in VGR-BC contributed negatively to the disease-specific survival at 5 and 27 years. Subsets with different status by ER (estrogen receptor) expression and presence of nodal metastasis supported independent association of high BIRC5 with poor prognosis in all cohorts. In METABRIC and SCAN-B cohorts, high levels of BIRC5 mRNA were associated with the basal-like and luminal B molecular BC subtypes and with increasing histologic grade. BIRC5 is a sensitive survival marker that acts independent of ER and nodal status, and its levels need to be considered when making treatment decisions.

Comprehensive and Computable Molecular Diagnostic Panel (C2Dx) From Small Volume Specimens for Precision Oncology: Molecular Subtyping of Non-Small Cell Lung Cancer From Fine Needle Aspirates

The Comprehensive, Computable NanoString Diagnostic gene panel (C2Dx) is a promising solution to address the need for a molecular pathological research and diagnostic tool for precision oncology utilizing small volume tumor specimens. We translate subtyping-related gene expression patterns of Non-Small Cell Lung Cancer (NSCLC) derived from public transcriptomic data which establish a highly robust and accurate subtyping system. The C2Dx demonstrates supreme performance on the NanoString platform using microgram-level FNA samples and has excellent portability to frozen tissues and RNA-Seq transcriptomic data. This workflow shows great potential for research and the clinical practice of cancer molecular diagnosis.

A Narrative Review of Genetic Alterations in Primary Thyroid Epithelial Cancer

Thyroid carcinoma is the most frequent endocrine neoplasia. Different types of thyroid carcinoma are described: well-differentiated papillary thyroid carcinoma (PTC), poorly differentiated thyroid carcinoma (PDTC), follicular thyroid carcinoma (FTC), anaplastic thyroid carcinoma (ATC), and medullary thyroid carcinoma (MTC). MTC is inherited as an autosomal dominant trait in 25% of cases. The genetic landscape of thyroid carcinoma has been largely deciphered. In PTC, genetic alterations have been found in about 95% of tumors: BRAF mutations and RET rearrangements are the main genetic alterations. BRAF and RAS mutations have been confirmed to play an important role also in PDTC and ATC, together with TP53 mutations that are fundamental in tumor progression. It has also been clearly demonstrated that telomerase reverse transcriptase (TERT) promoter mutations and TP53 mutations are present with a high-frequency in more advanced tumors, frequently associated with other mutations, and their presence, especially if simultaneous, is a signature of aggressiveness. In MTC, next-generation sequencing confirmed that mutations in the RET gene are the most common molecular events followed by H-RAS and K-RAS mutations. The comprehensive knowledge of the genetic events responsible for thyroid tumorigenesis is important to better predict the biological behavior and better plan the therapeutic strategy for specific treatment of the malignancy based on its molecular profile.

MicroRNA and protein-coding gene expression analysis in idiopathic pulmonary fibrosis yields novel biomarker signatures associated to survival

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive interstitial lung disease of unknown etiology that poses significant challenges in early diagnosis and prediction of progression. Analyses of microRNA and gene expression in IPF have yielded potentially predictive information. However, the relationship between microRNA/gene expression and quantitative phenotypic value in IPF remains controversial, as is the added value of this approach to current molecular signatures in IPF. To identify biomarkers predictive of survival in IPF via a microRNA-driven strategy. We profiled microRNA and protein-coding gene expression in peripheral blood mononuclear cells from 70 IPF subjects in a discovery cohort. We linked the microRNA/gene expression level with the quantitative phenotypic variation in IPF, including diffusing capacity of the lung for carbon monoxide and the forced vital capacity percent predicted. In silico analyses of expression profiles and quantitative phenotypic data allowed the generation of 2 sets of IPF molecular signatures (unique for microRNAs and protein-coding genes) that predict IPF survival. Each signature performed well in a validation cohort comprised of IPF patients aggregated from distinct patient populations recruited from different sites. Resampling test suggests that the protein-coding gene based signature is comparable and potentially superior to published IPF prognostic gene signatures. In conclusion, these results highlight the utility of microRNA-driven peripheral blood molecular signatures as valuable and novel biomarkers associated to individuals at high survival risk and for potentially facilitating individualized therapies in this enigmatic disorder.

A new 7-gene survival score assay for pancreatic cancer patient prognosis prediction

Gene expression features that are valuable for pancreatic ductal adenocarcinoma (PDAC) prognosis are still largely unknown. We aimed to explore pivotal molecular signatures for PDAC progression and establish an efficient survival score to predict PDAC prognosis. Overall, 163 overlapping genes were identified from three statistical methods, including differentially expressed genes (DEGs), coexpression network analysis (WGCNA), and target genes for miRNAs that were significantly related to PDAC patients' overall survival (OS). Then, according to the optimal value of the cross-validation curve (lambda = 0.031), 7 non-zero coefficients (ARNTL2, DSG3, PTPRR, ANLN, S100A14, ANKRD22, and TSPAN7) were selected to establish a prognostic prediction model of PDAC patients. We further confirmed the expression level of 7 genes using RT-PCR, western blot, and immunohistochemistry staining in PDAC patients' tissues. Our results showed that the ROC curve of the 7-mRNA model indicated good predictive ability for 1- and 2-year OS in three datasets (TCGA: 0.71, 0.69; ICGC: 0.8, 0.74; GEO batch: 0.61, 0.7, respectively). The hazard ratio (HR) of the low-risk group had a similar significant result (TCGA: HR = 0.3723; ICGC: HR = 0.2813; GEO batch: HR = 0.4999; all P < 0.001). Furthermore, Log-rank test results in three cohorts showed that the 7-mRNA assay excellently predicted the prognosis and metastasis, especially in TNM stage I&II subgroups of PDAC. In conclusion, the strong validation of our 7-mRNA signature indicates the promising effectiveness of its clinical application, especially in patients with TNM stages I&II.

Longitudinal Multi-Parametric Liquid Biopsy Approach Identifies Unique Features of Circulating Tumor Cell, Extracellular Vesicle, and Cell-Free DNA Characterization for Disease Monitoring in Metastatic Breast Cancer Patients

Dynamics of mRNA from circulating tumor cells (CTCs), mRNA from extracellular vesicles (EVs), and cell-free DNA (cfDNA) were assessed to examine the relevance of a longitudinal multi-parametric liquid biopsy strategy. Eighteen milliliters of blood was drawn from 27 hormone receptor-positive and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC) patients at disease progression and at two subsequent radiologic staging time points. CTC mRNA and EV mRNA were analyzed using multi-marker qPCR, and cfDNA was analyzed using targeted next-generation sequencing (NGS). The presence of ERBB2 or ERBB3 overexpression signals in CTCs significantly correlated with disease progression (87% specificity, 36% sensitivity, p-value = 0.023), and the presence of either ERBB3 signals in CTCs or EVs or cfDNA variants in ERBB3 also showed a significant association with progressive MBC. Fluctuations during treatment were detected in the EV fraction with the appearance of hitherto undetected ERCC1 signals correlating with progressive disease (97% specificity, 18% sensitivity, p-value = 0.030). Allele frequency development of ESR1 and PIK3CA variants detected at subsequent staging time points could be used as a predictor for therapy success and, importantly, might help guide therapy decisions. The three analytes, each with their own unique features for disease monitoring, were shown to be complementary, underlining the usefulness of the longitudinal multi-parametric liquid biopsy approach.

Molecular Mechanisms of Renal Progenitor Regulation: How Many Pieces in the Puzzle?

Kidneys of mice, rats and humans possess progenitors that maintain daily homeostasis and take part in endogenous regenerative processes following injury, owing to their capacity to proliferate and differentiate. In the glomerular and tubular compartments of the nephron, consistent studies demonstrated that well-characterized, distinct populations of progenitor cells, localized in the parietal epithelium of Bowman capsule and scattered in the proximal and distal tubules, could generate segment-specific cells in physiological conditions and following tissue injury. However, defective or abnormal regenerative responses of these progenitors can contribute to pathologic conditions. The molecular characteristics of renal progenitors have been extensively studied, revealing that numerous classical and evolutionarily conserved pathways, such as Notch or Wnt/β-catenin, play a major role in cell regulation. Others, such as retinoic acid, renin-angiotensin-aldosterone system, TLR2 (Toll-like receptor 2) and leptin, are also important in this process. In this review, we summarize the plethora of molecular mechanisms directing renal progenitor responses during homeostasis and following kidney injury. Finally, we will explore how single-cell RNA sequencing could bring the characterization of renal progenitors to the next level, while knowing their molecular signature is gaining relevance in the clinic.

Qualitative Transcriptional Signature for the Pathological Diagnosis of Pancreatic Cancer

It is currently difficult for pathologists to diagnose pancreatic cancer (PC) using biopsy specimens because samples may have been from an incorrect site or contain an insufficient amount of tissue. Thus, there is a need to develop a platform-independent molecular classifier that accurately distinguishes benign pancreatic lesions from PC. Here, we developed a robust qualitative messenger RNA signature based on within-sample relative expression orderings (REOs) of genes to discriminate both PC tissues and cancer-adjacent normal tissues from non-PC pancreatitis and healthy pancreatic tissues. A signature comprising 12 gene pairs and 17 genes was built in the training datasets and validated in microarray and RNA-sequencing datasets from biopsy samples and surgically resected samples. Analysis of 1,007 PC tissues and 257 non-tumor samples from nine databases indicated that the geometric mean of sensitivity and specificity was 96.7%, and the area under receiver operating characteristic curve was 0.978 (95% confidence interval, 0.947–0.994). For 20 specimens obtained from endoscopic biopsy, the signature had a diagnostic accuracy of 100%. The REO-based signature described here can aid in the molecular diagnosis of PC and may facilitate objective differentiation between benign and malignant pancreatic lesions.

Systems Biology Approach Identifies Prognostic Signatures of Poor Overall Survival and Guides the Prioritization of Novel BET-CHK1 Combination Therapy for Osteosarcoma

Osteosarcoma (OS) patients exhibit poor overall survival, partly due to copy number variations (CNVs) resulting in dysregulated gene expression and therapeutic resistance. To identify actionable prognostic signatures of poor overall survival, we employed a systems biology approach using public databases to integrate CNVs, gene expression, and survival outcomes in pediatric, adolescent, and young adult OS patients. Chromosome 8 was a hotspot for poor prognostic signatures. The MYC-RAD21 copy number gain (8q24) correlated with increased gene expression and poor overall survival in 90% of the patients (n = 85). MYC and RAD21 play a role in replication-stress, which is a therapeutically actionable network. We prioritized replication-stress regulators, bromodomain and extra-terminal proteins (BETs), and CHK1, in order to test the hypothesis that the inhibition of BET + CHK1 in MYC-RAD21+ pediatric OS models would be efficacious and safe. We demonstrate that MYC-RAD21+ pediatric OS cell lines were sensitive to the inhibition of BET (BETi) and CHK1 (CHK1i) at clinically achievable concentrations. While the potentiation of CHK1i-mediated effects by BETi was BET-BRD4-dependent, MYC expression was BET-BRD4-independent. In MYC-RAD21+ pediatric OS xenografts, BETi + CHK1i significantly decreased tumor growth, increased survival, and was well tolerated. Therefore, targeting replication stress is a promising strategy to pursue as a therapeutic option for this devastating disease.

FGF2-induced PI3K/Akt signaling evokes greater proliferation and adipogenic differentiation of human adipose stem cells from breast than from abdomen or thigh

In this study, human adipose stem cells were isolated from subcutaneous fat in the thigh (htASCs), abdomen (haASCs) and breast (hbASCs). Flow cytometry was used to detect cell surface markers, and an enzyme-linked immunosorbent assay was used to detect paracrine activity. Paracrine gene expression in the three cell types was examined using real-time qPCR, and adipogenic ability was assessed using Oil Red O staining. RNA from third-passage haASCs and hbASCs was sequenced. The results showed that the differentiation potential marker markers CD49d and CD54 were similar across hbASCs from 10 subjects. The hbASCs showed higher colony forming ability and expression of fibroblast growth factor-2, tissue inhibitor of metalloproteinase-1 and stromal cell derived factor-1 than htASCs and haASCs. Stimulating hbASCs with FGF2 promoted adipogenic differentiation, while treating the cells with the PI3K inhibitor LY294002 inhibited differentiation. These results suggest that the PI3K/Akt signaling pathway can promote proliferation and adipogenic differentiation of adipose stem cells, and that activation of this pathway by FGF2 may explain why hbASCs show greater proliferation and adipogenic differentiation than haASCs and htASCs.

A digital mRNA expression signature to classify challenging Spitzoid melanocytic neoplasms

Spitzoid neoplasms are a challenging group of cutaneous melanocytic proliferations. They are characterized by epithelioid and/or spindle-shaped melanocytes and classified as benign Spitz nevi (SN), atypical Spitz tumors (AST), or malignant Spitz tumors (MST). The intermediate AST category represents a diagnostically challenging group since on purely histopathological grounds, their benign or malignant character remains unpredictable. This results in uncertainties in patient treatment and prognosis. The molecular properties of Spitzoid lesions, especially their transcriptomic landscape, remain poorly understood, and genomic alterations in melanoma-associated oncogenes are typically absent. The aim of this study was to characterize their transcriptome with digital mRNA expression profiling. Formalin-fixed paraffin-embedded samples (including 27 SN, 10 AST, and 14 MST) were analyzed using the NanoString nCounter PanCancer Pathways Panel. The number of significantly differentially expressed genes in SN vs. MST, SN vs. AST, and AST vs. MST was 68, 167, and 18, respectively. Gene set enrichment analysis revealed upregulation of pathways related to epithelial-mesenchymal transition and immunomodulatory-, angiogenesis-, hormonal-, and myogenesis-associated processes in AST and MST. A molecular signature of SN vs. MST was discovered based on the top-ranked most informative genes: NRAS, NF1, BMP2, EIF2B4, IFNA17, and FZD9. The AST samples showed intermediate levels of the identified signature. This implies that the gene signature can potentially be used to distinguish high-grade from low-grade AST with a larger study cohort in the future. This combined histopathological and transcriptomic methodology is promising for prospective diagnostics of Spitzoid neoplasms and patient management in dermatological oncology.

An Overview of Candidate Therapeutic Target Genes in Ovarian Cancer

Ovarian cancer (OC) shows the highest mortality rate among gynecological malignancies and, because of the absence of specific symptoms, it is frequently diagnosed at an advanced stage, mainly due to the lack of specific and early biomarkers, such as those based on cancer molecular signature identification. Indeed, although significant progress has been made toward improving the clinical outcome of other cancers, rates of mortality for OC are essentially unchanged since 1980, suggesting the need of new approaches to identify and characterize the molecular mechanisms underlying pathogenesis and progression of these malignancies. In addition, due to the low response rate and the high frequency of resistance to current treatments, emerging therapeutic strategies against OC focus on targeting single factors and pathways specifically involved in tumor growth and metastasis. To date, loss-of-function screenings are extensively applied to identify key drug targets in cancer, seeking for more effective, disease-tailored treatments to overcome lack of response or resistance to current therapies. We review here the information relative to essential genes and functional pathways recently discovered in OC, often strictly interconnected with each other and representing promising biomarkers and molecular targets to treat these malignancies.

Clinical impact of the lung tissue transcriptome in a teenager with multifocal invasive mucinous adenocarcinoma-a case report

The transcriptional profiling of cancer and normal tissues harboring cancer can be a clinical and discovery tool, especially for the study of rare tumors. Invasive mucinous adenocarcinoma (IMA) is a rare lung cancer histotype, which mostly affects the elderly and commonly has a poor prognosis. We investigated the exceptional case of a teenager, exposed to passive smoke and chemical carcinogens, who developed a multifocal IMA with bilateral involvement. The malignancy was asymptomatic and was diagnosed occasionally during hospitalization for acute abdominal pain due to adnexitis. The young patient underwent video-assisted thoracoscopic surgery and lung samples were analysed by RNA-Sequencing. The transcriptome of patient’s normal and neoplastic lung tissues was compared with matched healthy controls and IMA signature cases, using Gene Set Enrichment Analyses, Gene Ontology and Genotype Tissue Expression database. Compared to healthy controls, the patient’s lung tissue lacked the expression of lymphocyte and humoral-mediated immune response genes, whereas genes driving the response to stimulus, chemical and organic substances, primarily, CXCL8, ACKR1, RAB7B, HOXC9, HOXD9, KLF5 and NKX2-8 were overexpressed. Genes driving extracellular structure organization, cell adhesion, cell movement, metabolic and apoptotic processes were down-modulated in patient’s lung tissue. When compared to IMA signature cases, the patient’s IMA revealed a prevalent expression of genes regulating the response to stimulus, myeloid and neutrophil activation and immune system processes, primarily CD1a and CXCL13/BCA1, whereas stemness genes and proto-oncogenes, such as SOX4, HES1, IER3 and SERPINH1 were downmodulated. These transcriptional signature associated with a favorable clinical course, since the patient was healthy five years after initial diagnosis. The transcriptome of the normal tissues bearing tumor provides meaningful information on the gene pathways driving tumor histogenesis, with a prospective impact on early diagnosis. Unlike the tumor histotype-related transcriptional signature, the individual patient’s signature enables tailored treatment and accurate prognosis.

ZEBrA: Zebra finch Expression Brain Atlas-A resource for comparative molecular neuroanatomy and brain evolution studies

An in-depth understanding of the genetics and evolution of brain function and behavior requires a detailed mapping of gene expression in functional brain circuits across major vertebrate clades. Here we present the Zebra finch Expression Brain Atlas (ZEBrA; www.zebrafinchatlas.org, RRID: SCR_012988), a web-based resource that maps the expression of genes linked to a broad range of functions onto the brain of zebra finches. ZEBrA is a first of its kind gene expression brain atlas for a bird species and a first for any sauropsid. ZEBrA's >3,200 high-resolution digital images of in situ hybridized sections for ~650 genes (as of June 2019) are presented in alignment with an annotated histological atlas and can be browsed down to cellular resolution. An extensive relational database connects expression patterns to information about gene function, mouse expression patterns and phenotypes, and gene involvement in human diseases and communication disorders. By enabling brain-wide gene expression assessments in a bird, ZEBrA provides important substrates for comparative neuroanatomy and molecular brain evolution studies. ZEBrA also provides unique opportunities for linking genetic pathways to vocal learning and motor control circuits, as well as for novel insights into the molecular basis of sex steroids actions, brain dimorphisms, reproductive and social behaviors, sleep function, and adult neurogenesis, among many fundamental themes.

Qualitative transcriptional signature for predicting pathological response of colorectal cancer to FOLFOX therapy

FOLFOX (5‐fluorouracil, leucovorin and oxaliplatin) is one of the main chemotherapy regimens for colorectal cancer (CRC), but only half of CRC patients respond to this regimen. Using gene expression profiles of 96 metastatic CRC patients treated with FOLFOX, we first selected gene pairs whose within‐sample relative expression orderings (REO) were significantly associated with the response to FOLFOX using the exact binomial test. Then, from these gene pairs, we applied an optimization procedure to obtain a subset that achieved the largest F‐score in predicting pathological response of CRC to FOLFOX. The REO‐based qualitative transcriptional signature, consisting of five gene pairs, was developed in the training dataset consisting of 96 samples with an F‐score of 0.90. In an independent test dataset consisting of 25 samples with the response information, an F‐score of 0.82 was obtained. In three other independent survival datasets, the predicted responders showed significantly better progression‐free survival than the predicted non‐responders. In addition, the signature showed a better predictive performance than two published FOLFOX signatures across different datasets and is more suitable for CRC patients treated with FOLFOX than 5‐fluorouracil‐based signatures. In conclusion, the REO‐based qualitative transcriptional signature can accurately identify metastatic CRC patients who may benefit from the FOLFOX regimen.