Liquid-liquid phase separation-related genes associated with prognosis, tumor microenvironment characteristics, and tumor cell features in bladder cancer.

OBJECTIVE: This study aimed to explore the Liquid-liquid phase separation (LLPS)-related genes associated with the prognosis of bladder cancer (BCa) and assess the potential application of LLPS-related prognostic signature for predicting prognosis in BCa patients. METHODS: Clinical information and transcriptome data of BCa patients were extracted from the Cancer Genome Atlas-BLCA (TCGA-BLCA) database and the GSE13507 database. Furthermore, 108 BCa patients who received treatment at our institution were subjected to a retrospective analysis. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an LLPS-related prognostic signature for BCa. The CCK8, wound healing and Transwell assays were performed. RESULTS: Based on 62 differentially expressed LLPS-related genes (DELRGs), three DELRGs were screened by LASSO analysis including kallikrein-related peptidase 5 (KLK5), monoacylglycerol O-acyltransferase 2 (MOGAT2) and S100 calcium-binding protein A7 (S100A7). Based on three DELRGs, a novel LLPS-related prognostic signature was constructed for individualized prognosis assessment. Kaplan-Meier curve analyses showed that LLPS-related prognostic signature was significantly correlated with overall survival (OS) of BCa. ROC analyses demonstrated the LLPS-related prognostic signature performed well in predicting the prognosis of BCa patients in the training group (the area under the curve (AUC) = 0.733), which was externally verified in the validation cohort 1 (AUC = 0.794) and validation cohort 2 (AUC = 0.766). Further experiments demonstrated that inhibiting KLK5 could affect the proliferation, migration, and invasion of BCa cells. CONCLUSIONS: In this study, a novel LLPS-related prognostic signature was successfully developed and validated, demonstrating strong performance in predicting the prognosis of BCa patients.

Construction of M2 macrophage-related gene signature for predicting prognosis and revealing different immunotherapy response in bladder cancer patients.

BACKGROUND: Bladder cancer development is closely associated with the dynamic interaction and communication between M2 macrophages and tumor cells. However, specific biomarkers for targeting M2 macrophages in immunotherapy remain limited and require further investigation. METHODS: In this study, we identified key co-expressed genes in M2 macrophages and developed gene signatures to predict prognosis and immunotherapy response in patients. Public database provided the bioinformatics data used in the analysis. We created and verified an M2 macrophage-related gene signature in these datasets using Lasso-Cox analysis. RESULTS: The predictive value and immunological functions of our risk model were examined in bladder cancer patients, and 158 genes were found to be significantly positively correlated with M2 macrophages. Moreover, we identified two molecular subgroups of bladder cancer with markedly different immunological profiles and clinical prognoses. The five key risk genes identified in this model were validated, including CALU, ECM1, LRP1, CYTL1, and CCDC102B, demonstrating the model can accurately predict prognosis and identify unique responses to immunotherapy in patients with bladder cancer. CONCLUSIONS: In summary, we constructed and validated a five-gene signature related to M2 macrophages, which shows strong potential for forecasting bladder cancer prognosis and immunotherapy response.

Spatio-Temporal Variations of Volatile Metabolites as an Eco-Physiological Response of a Native Species in the Tropical Forest.

This study evaluates the essential oil (EO) composition of Piper rivinoides Kunth, a shrub native to the Brazilian tropical rainforest, across different plant parts and developmental phases. The aim was to explore the chemical diversity of EO and its reflection in the plant's ecological interactions and adaptations. Plant organs (roots, stems, branches, and leaves) at different developmental phases were subjected to hydrodistillation followed by chemical analysis using Gas Chromatography-Mass Spectrometry (GC-MS) and Gas Chromatography-Flame Ionization Detector (GC-FID). The results revealed a relevant variation in EO yield and composition among different plant parts and developmental phases. Leaves showed the highest yield and chemical diversity, with α-pinene and ß-pinene as major constituents, while roots and stems were characterized by a predominance of arylpropanoids, particularly apiol. The chemical diversity in leaves increased with plant maturity, indicating a dynamic adaptation to environmental interactions. The study underscores the importance of considering the ontogeny of plant parts in understanding the ecological roles and potential applications of P. rivinoides in medicine and agriculture. The findings contribute to the overall knowledge of Piperaceae chemodiversity and ecological adaptations, offering insights into the plant's interaction with its environment and its potential uses based on chemical composition.

Unveiling morphophysiological and metabolic adaptive strategies of the CAM epiphytic bromeliad Acanthostachys pitcairnioides to drought.

Ongoing climate changes are expected to intensify drought periods in tropical regions, directly impacting epiphytic bromeliads that depend on intermittent water availability. This study aimed to elucidate if Acanthostachys pitcairnioides, an epiphytic bromeliad of Atlantic Forest, tolerates extended drought periods and the potential strategies involved in its tolerance and recovery capacity. We suppressed irrigation for 42 days, rehydrated plants for four days, and evaluated leaf water status, and photochemical, metabolic, and anatomical changes. During the initial 28 days of drought, translocation of water from hydrenchyma to chlorenchyma, higher chlorophyll content, and accumulation of abscisic and salicylic acid and antioxidants contributed to maintaining the cell turgor and functionality of photosynthetic apparatus. At 42 days, a significant reduction in leaf water content to 45.5% was accompanied by a 2.5-fold increase in non-photochemical quenching and enhanced levels of carotenoids, anthocyanins, osmoregulators (proline, myo-inositol, and trehalose), and phytohormones (abscisic acid and jasmonates). After rewatering, water storage in the hydrenchyma and almost all pigments, hormones, and metabolites were restored to pre-stress conditions. Leaf succulence, carbohydrate and organic acid accumulation, and carbon isotope data (δ13C-14.5‰) provide evidence of induction of CAM metabolism by water limitation in A. pitcairnioides. Our findings indicate the prevalence of water accumulation strategy during the first half of the drought stress. At the end of the drought period, the complete depletion of water from the hydrenchyma favored the osmotic adjustment. Considering this set of tolerance strategies and the rapid recovery after rehydration, A. pitcairnioides can successfully withstand environments with restricted water availability.

Low-cost clamp for the measurement of vegetation spectral signatures.

Spectral signatures allow the characterization of a surface from the reflected or emitted energy along the electromagnetic spectrum. This type of measurement has several potential applications in precision agriculture. However, capturing the spectral signatures of plants requires specialized instruments, either in the field or the laboratory. The cost of these instruments is high, so their incorporation in crop monitoring tasks is not massive, given the low investment in agricultural technology. This paper presents a low-cost clamp to capture spectral leaf signatures in the laboratory and the field. The clamp can be 3D printed using PLA (polylactic acid); it allows the connection of 2 optical fibers: one for a spectrometer and one for a light source. It is designed for ease of use and holds a leave firmly without causing damage, allowing data to be collected with less disturbance. The article compares signatures captured directly using a fiber and the proposed clamp; noise reduction across the spectrum is achieved with the clamp.

A mutational signature and ARID1A mutation associated with outcome in hepatocellular carcinoma.

OBJECTIVE: The prognosis of hepatocellular carcinoma (HCC) is poor and there is no stable and reliable molecular biomarker for evaluation. This study attempted to find reliable prognostic markers from tumor mutational profiles. METHODS: A total of 362 HCC samples with whole-exome sequencing were collected as discovery datasets, and 200 samples with targeted sequencing were used for validation of the relevant results. All HCC samples were obtained from previously published studies. Bayesian non-negative matrix factorization was used to extract mutational signatures, and multivariate Cox regression models were utilized to identify the prognostic role of mutational factors. Gene set enrichment analysis was employed to discover potential signaling pathways associated with specific mutational groups. RESULTS: In the HCC discovery dataset, a total of four mutational signatures (i.e., signatures 4, 6, 16, and 22) were extracted, of which signature 16 characterized by T>C mutations was observed to be associated with favorable HCC prognosis, and this correlation was also found in the validation dataset. Further analysis showed that patients with ARID1A mutations exhibited inferior survival outcomes in both discovery and validation datasets. Mechanistic exploration revealed that the presence of signature 16 was associated with better immune infiltration and tumor immunogenicity, while patients with ARID1A mutations were away from these favorable immunological features. CONCLUSION: By integrating somatic mutation data and clinical information of HCC, this study identified that signature 16 and ARID1A mutations were associated with better and worse outcomes respectively, providing a basis for prognosis prediction and clinical treatment strategies of HCC.

Machine Learning Gene Signature to Metastatic ccRCC Based on ceRNA Network.

Clear-cell renal-cell carcinoma (ccRCC) is a silent-development pathology with a high rate of metastasis in patients. The activity of coding genes in metastatic progression is well known. New studies evaluate the association with non-coding genes, such as competitive endogenous RNA (ceRNA). This study aims to build a ceRNA network and a gene signature for ccRCC associated with metastatic development and analyze their biological functions. Using data from The Cancer Genome Atlas (TCGA), we constructed the ceRNA network with differentially expressed genes, assembled nine preliminary gene signatures from eight feature selection techniques, and evaluated the classification metrics to choose a final signature. After that, we performed a genomic analysis, a risk analysis, and a functional annotation analysis. We present an 11-gene signature: SNHG15, AF117829.1, hsa-miR-130a-3p, hsa-mir-381-3p, BTBD11, INSR, HECW2, RFLNB, PTTG1, HMMR, and RASD1. It was possible to assess the generalization of the signature using an external dataset from the International Cancer Genome Consortium (ICGC-RECA), which showed an Area Under the Curve of 81.5%. The genomic analysis identified the signature participants on chromosomes with highly mutated regions. The hsa-miR-130a-3p, AF117829.1, hsa-miR-381-3p, and PTTG1 were significantly related to the patient's survival and metastatic development. Additionally, functional annotation resulted in relevant pathways for tumor development and cell cycle control, such as RNA polymerase II transcription regulation and cell control. The gene signature analysis within the ceRNA network, with literature evidence, suggests that the lncRNAs act as "sponges" upon the microRNAs (miRNAs). Therefore, this gene signature presents coding and non-coding genes and could act as potential biomarkers for a better understanding of ccRCC.

Identification of a gene expression signature associated with brain metastasis in colorectal cancer.

PURPOSE: Brain metastasis (BM) in colorectal cancer (CRC) is a rare event with poor prognosis. Apart from (K)RAS status and lung and bone metastasis no biomarkers exist to identify patients at risk. This study aimed to identify a gene expression signature associated with colorectal BM. METHODS: Three patient groups were formed: 1. CRC with brain metastasis (BRA), 2. exclusive liver metastasis (HEP) and, 3. non-metastatic disease (M0). RNA was extracted from primary tumors and mRNA expression was measured using a NanoString Panel (770 genes). Expression was confirmed by qPCR in a validation cohort. Statistical analyses including multivariate logistic regression followed by receiver operating characteristic (ROC) analysis were performed. RESULTS: EMILIN3, MTA1, SV2B, TMPRSS6, ACVR1C, NFAT5 and SMC3 were differentially expressed in BRA and HEP/M0 groups. In the validation cohort, differential NFAT5, ACVR1C and SMC3 expressions were confirmed. BRA patients showed highest NFAT5 levels compared to HEP/M0 groups (global p = 0.02). High ACVR1C expression was observed more frequently in the BRA group (42.9%) than in HEP (0%) and M0 (7.1%) groups (global p = 0.01). High SMC3 expressions were only detectable in the BRA group (global p = 0.003). Only patients with BM showed a combined high expression of NFAT5, ACVR1C or SMC3 as well as of all three genes. ROC analysis revealed a good prediction of brain metastasis by the three genes (area under the curve (AUC) = 0.78). CONCLUSIONS: The NFAT5, ACVR1C and SMC3 gene expression signature is associated with colorectal BM. Future studies should further investigate the importance of this biomarker signature.

Copy number signatures and CCNE1 amplification reveal the involvement of replication stress in high-grade endometrial tumors oncogenesis.

PURPOSE: Managing high-grade endometrial cancer in Martinique poses significant challenges. The diversity of copy number alterations in high-grade endometrial tumors, often associated with a TP53 mutation, is a key factor complicating treatment. Due to the high incidence of high-grade tumors with poor prognosis, our study aimed to characterize the molecular signature of these tumors within a cohort of 25 high-grade endometrial cases. METHODS: We conducted a comprehensive pangenomic analysis to categorize the copy number alterations involved in these tumors. Whole-Exome Sequencing (WES) and Homologous Recombination (HR) analysis were performed. The alterations obtained from the WES were classified into various signatures using the Copy Number Signatures tool available in COSMIC. RESULTS: We identified several signatures that correlated with tumor stage and disctinct prognoses. These signatures all seem to be linked to replication stress, with CCNE1 amplification identified as the primary driver of oncogenesis in over 70% of tumors analyzed. CONCLUSION: The identification of CCNE1 amplification, which is currently being explored as a therapeutic target in clinical trials, suggests new treatment strategies for high-grade endometrial cancer. This finding holds particular significance for Martinique, where access to care is challenging.

C1q and HBHA-specific IL-13 levels as surrogate plasma biomarkers for monitoring tuberculosis treatment efficacy: a cross-sectional cohort study in Paraguay.

Introduction: New diagnostic tools are needed to rapidly assess the efficacy of pulmonary tuberculosis (PTB) treatment. The aim of this study was to evaluate several immune biomarkers in an observational and cross-sectional cohort study conducted in Paraguay. Methods: Thirty-two patients with clinically and microbiologically confirmed PTB were evaluated before starting treatment (T0), after 2 months of treatment (T1) and at the end of treatment (T2). At each timepoint plasma levels of IFN-y, 17 pro- and anti-inflammatory cytokines/chemokines and complement factors C1q, C3 and C4 were assessed in unstimulated and Mtb-specific stimulated whole blood samples using QuantiFERON-TB gold plus and recombinant Mycobacterium smegmatis heparin binding hemagglutinin (rmsHBHA) as stimulation antigen. Complete blood counts and liver enzyme assays were also evaluated and correlated with biomarker levels in plasma. Results: In unstimulated plasma, C1q (P<0.001), C4 (P<0.001), hemoglobin (P<0.001), lymphocyte proportion (P<0.001) and absolute white blood cell count (P=0.01) were significantly higher in PTB patients at baseline than in cured patients. C1q and C4 levels were found to be related to Mycobacterium tuberculosis load in sputum. Finally, a combinatorial analysis identified a plasma host signature comprising the detection of C1q and IL-13 levels in response to rmsHBHA as a tool differentiating PTB patients from cured TB profiles, with an AUC of 0.92 (sensitivity 94% and specificity 79%). Conclusion: This observational study provides new insights on host immune responses throughout anti-TB treatment and emphasizes the role of host C1q and HBHA-specific IL-13 response as surrogate plasma biomarkers for monitoring TB treatment efficacy.

Identification of runs of homozygosity (ROHs) in Curraleiro Pé-Duro and Pantaneiro cattle breeds.

This study aimed to identify and characterize runs of homozygosis (ROHs), genes involved in production characteristics and adaptation to tropical systems and to estimate the inbreeding coefficient of Curraleiro Pé-Duro (CPD) and Pantaneiro (PANT), two brazilian locally adapted cattle breeds. The results demonstrated that 79.25% and 54.29% of ROH segments were bigger than 8 Mb in CPD and PANT, respectively, indicating recent inbred matings in the studied population. Six homozygosis islands were identified simultaneously in both breeds, where 175 QTLs and 1072 genes previously described as associated with production traits are located. The inbreeding coefficient (FROH) estimated based on ROHs (FROH) showed that inbreeding is low (2 to 4%), which is different from expected for small populations such as locally adapted ones.

Immunological signatures unveiled by integrative systems vaccinology characterization of dengue vaccination trials and natural infection.

Introduction: Dengue virus infection is a global health problem lacking specific therapy, requiring an improved understanding of DENV immunity and vaccine responses. Considering the recent emerging of new dengue vaccines, here we performed an integrative systems vaccinology characterization of molecular signatures triggered by the natural DENV infection (NDI) and attenuated dengue virus infection models (DVTs). Methods and results: We analyzed 955 samples of transcriptomic datasets of patients with NDI and attenuated dengue virus infection trials (DVT1, DVT2, and DVT3) using a systems vaccinology approach. Differential expression analysis identified 237 common differentially expressed genes (DEGs) between DVTs and NDI. Among them, 28 and 60 DEGs were up or downregulated by dengue vaccination during DVT2 and DVT3, respectively, with 20 DEGs intersecting across all three DVTs. Enriched biological processes of these genes included type I/II interferon signaling, cytokine regulation, apoptosis, and T-cell differentiation. Principal component analysis based on 20 common DEGs (overlapping between DVTs and our NDI validation dataset) distinguished dengue patients by disease severity, particularly in the late acute phase. Machine learning analysis ranked the ten most critical predictors of disease severity in NDI, crucial for the anti-viral immune response. Conclusion: This work provides insights into the NDI and vaccine-induced overlapping immune response and suggests molecular markers (e.g., IFIT5, ISG15, and HERC5) for anti-dengue-specific therapies and effective vaccination development.

Integrated analysis reveals an aspartate metabolism-related gene signature for predicting the overall survival in patients with hepatocellular carcinoma.

BACKGROUND: Deregulating cellular metabolism is one of the prominent hallmarks of malignancy, with a critical role in tumor survival and growth. However, the role of reprogramming aspartate metabolism in hepatocellular carcinoma (HCC) are largely unknown. METHODS: The multi-omics data of HCC patients were downloaded from public databases. Univariate and multivariate stepwise Cox regression were used to establish an aspartate metabolism-related gene signature (AMGS) in HCC. The Kaplan-Meier and receiver operating characteristic curve analyses were performed to evaluate the predictive ability for overall survival (OS) in HCC patients. Gene set enrichment analysis and immune infiltration analysis were operated to determine the potential mechanisms underlying the AMGS. Single-cell RNA sequencing (scRNA-seq) data of liver cancer stem cells were visualized by t-SNE algorithm. In vivo and in vitro experiments were implemented to investigate the biological function of CAD in HCC. In addition, a nomogram based on the AMGS and clinicopathologic characteristics was constructed by univariate and multivariate Cox regression analyses. RESULTS: Patients in the high-AMGS subgroup exerted advanced tumor status and poor prognosis. Mechanistically, the high-AMGS subgroup patients had significantly enhanced proliferation and stemness-related pathways, increased infiltration of regulatory T cells and upregulated expression levels of suppressive immune checkpoints in the tumor immune microenvironment. Notably, scRNA-seq data revealed CAD, one of the aspartate metabolism-related gene, is significantly upregulated in liver cancer stem cells. Silencing CAD inhibited proliferative capacity and stemness properties of HCC cells in vitro and in vivo. Finally, a novel nomogram based on the AMGS showed an accurate prediction in HCC patients. CONCLUSIONS: The AMGS represents a promising prognostic value for HCC patients, providing a perspective for finding novel biomarkers and therapeutic targets for HCC.

Development of fatty acid metabolism score based on gene signature for predicting prognosis and immunotherapy response in colon cancer.

PURPOSE: Metabolic reprogramming is a novel hallmark and therapeutic target of cancer. Our study aimed to establish fatty acid metabolism-associated scores based on gene signature and investigated its effects on immunotherapy in colon cancer. METHODS: Gene expression and clinical information were collected from Gene Expression Omnibus (GEO) database to identify a gene signature by non-negative matrix factorization (NMF) clustering and Cox regression analysis. Subsequently, we constructed the fatty acid metabolism score (FA-score) model by principal component analysis (PCA) and explored its relativity of prognosis and the response to immunotherapy in colon cancer. Finally, the Cancer Genome Atlas (TCGA) database was introduced and in vitro study was performed for verification. RESULTS: The FA-score-high group had a higher level of fatty acid metabolism and was associated with worse patient overall survival. Significantly, FA-score correlated closely with the biomarkers of immunotherapy, and the FA-score-high group had a poorer therapeutic efficacy of immune checkpoint blockade. In vitro experiments demonstrated that ACSL5 may be a critical metabolic regulatory target. CONCLUSIONS: Our study provided a comprehensive analysis of the heterogeneity of fatty acid metabolism in colon cancer. We highlighted the potential clinical utility of fatty acid metabolism-related genes to be biomarkers of colon cancer prognosis and targets to improve the effect of immunotherapy.

Identification of immune-related signature with prognosis in children with stage 4 and 4S neuroblastoma.

OBJECTIVE: Spontaneous regression of tumors is an attractive phenomenon that most commonly occurs in stage 4S neuroblastoma (NB). However, the mechanism underlying this phenomenon remains unclear. METHODS: Datasets correlated with NB were downloaded from online public databases, the differentially expressed genes (DEGs) between stage 4 and 4S associated with immunity were identified, and functional enrichment analysis was utilized to explore the potential functions and signaling pathways of these DEGs. In addition, based on these DEGs, a prognostic signature was constructed and validated, and differences in immune cell infiltration were analyzed. RESULTS: A total of 13 DEGs were finally identified, and functional enrichment analysis revealed that these DEGs were primarily enriched in the positive regulation of neuron differentiation and TGF-ß signaling pathway. The signature successfully stratifies patients into two risk score groups and performs well in judging prognosis and predicting overall survival time. In addition, the prognostic value of the risk score calculated by the signature was independent of clinical factors. The results of immune cell infiltration showed that patients with a high infiltration of resting CD4 + memory T cells had a better prognosis, while plasma cells had a worse prognosis. CONCLUSION: The results of the functional enrichment analysis of these identified DEGs suggested that these DEGs may be related to spontaneous regression of NB. In addition, the prognostic signature has the potential to create new risk stratification in patients with NB.

Anoikis patterns via machine learning strategy and experimental verification exhibit distinct prognostic and immune landscapes in melanoma.

BACKGROUND: Anoikis is a cell death programmed to eliminate dysfunctional or damaged cells induced by detachment from the extracellular matrix. Utilizing an anoikis-based risk stratification is anticipated to understand melanoma's prognostic and immune landscapes comprehensively. METHODS: Differential expression genes (DEGs) were analyzed between melanoma and normal skin tissues in The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data sets. Next, least absolute shrinkage and selection operator, support vector machine-recursive feature elimination algorithm, and univariate and multivariate Cox analyses on the 308 DEGs were performed to build the prognostic signature in the TCGA-melanoma data set. Finally, the signature was validated in GSE65904 and GSE22155 data sets. NOTCH3, PIK3R2, and SOD2 were validated in our clinical samples by immunohistochemistry. RESULTS: The prognostic model for melanoma patients was developed utilizing ten hub anoikis-related genes. The overall survival (OS) of patients in the high-risk subgroup, which was classified by the optimal cutoff value, was remarkably shorter in the TCGA-melanoma, GSE65904, and GSE22155 data sets. Low-risk patients exhibited low immune cell infiltration and high expression of immunophenoscores and immune checkpoints. They also demonstrated increased sensitivity to various drugs, including dasatinib and dabrafenib. NOTCH3, PIK3R2, and SOD2 were notably associated with OS by univariate Cox analysis in the GSE65904 data set. The clinical melanoma samples showed remarkably higher protein expressions of NOTCH3 (P = 0.003) and PIK3R2 (P = 0.009) than the para-melanoma samples, while the SOD2 protein expression remained unchanged. CONCLUSIONS: In this study, we successfully established a prognostic anoikis-connected signature using machine learning. This model may aid in evaluating patient prognosis, clinical characteristics, and immune treatment modalities for melanoma.

Unraveling clinical outcomes of long-term cART treatment in HIV-1 patients with or without the Brazilian GWGR motif in the V3 loop

ABSTRACT The presence of genetic mutations in HIV poses a significant challenge, potentially leading to antiretroviral resistance and hampering therapeutic development. The Brazilian population has presented variations in the HIV envelope V3 loop gene, especially the GWGR motif. This motif has been linked to reduced transmission potential and slower CD4+ T cell decline. This study aimed to assess clinical outcomes in patients with HIV-1 infected with strains containing the GWGR motif compared with those without it during long-term cART. A cohort of 295 patients with HIV was examined for the GWGR motif presence in the V3 loop. A total of 58 samples showed the GWGR signature, while 237 had other signatures. Multifactorial analyses showed no significant differences in demographic characteristics, CD4+ cell count, AIDS progression, or mortality between GWGR carriers and others. However, the mean interval between the first positive HIV test and the initial AIDS-defining event was more than two times longer for women carrying the GWGR signature (p = 0.0231). We emphasize the positive impact of cART on HIV/AIDS treatment, including viral suppression, CD4+ cell preservation, and immune function maintenance. Although no significant differences were found during cART, residual outcomes reflecting adherence challenges were observed between diagnosis and the first AIDS-defining event. The previously described outcomes, highlighting statistically significant differences between individuals carrying the GPGR motif compared with those with the Brazilian GWGR motif, may be directly linked to the natural progression of infection before advancements in cART. Presently, these physicochemical aspects may no longer hold the same relevance.

Relating mutational signature exposures to clinical data in cancers via signeR 2.0.

BACKGROUND: Cancer is a collection of diseases caused by the deregulation of cell processes, which is triggered by somatic mutations. The search for patterns in somatic mutations, known as mutational signatures, is a growing field of study that has already become a useful tool in oncology. Several algorithms have been proposed to perform one or both the following two tasks: (1) de novo estimation of signatures and their exposures, (2) estimation of the exposures of each one of a set of pre-defined signatures. RESULTS: Our group developed signeR, a Bayesian approach to both of these tasks. Here we present a new version of the software, signeR 2.0, which extends the possibilities of previous analyses to explore the relation of signature exposures to other data of clinical relevance. signeR 2.0 includes a user-friendly interface developed using the R-Shiny framework and improvements in performance. This version allows the analysis of submitted data or public TCGA data, which is embedded in the package for easy access. CONCLUSION: signeR 2.0 is a valuable tool to generate and explore exposure data, both from de novo or fitting analyses and is an open-source R package available through the Bioconductor project at ( https://doi.org/10.18129/B9.bioc.signeR ).

Ephexin3/ARHGEF5 Together with Cell Migration Signaling Partners within the Tumor Microenvironment Define Prognostic Transcriptional Signatures in Multiple Cancer Types.

Cancer cell migration involves a repertoire of signaling proteins that lead cytoskeleton reorganization as a critical step in metastatic dissemination. RhoGEFs are multidomain effectors that integrate signaling inputs to activate the molecular switches that orchestrate actin cytoskeleton reorganization. Ephexins, a group of five RhoGEFs, play oncogenic roles in invasive and metastatic cancer, leading to a mechanistic hypothesis about their function as signaling nodes assembling functional complexes that guide cancer cell migration. To identify clinically significant Ephexin signaling partners, we applied three systematic data mining strategies, based on the screening of essential Ephexins in multiple cancer cell lines and the identification of coexpressed signaling partners in the TCGA cancer patient datasets. Based on the domain architecture of encoded proteins and gene ontology criteria, we selected Ephexin signaling partners with a role in cytoskeletal reorganization and cell migration. We focused on Ephexin3/ARHGEF5, identified as an essential gene in multiple cancer cell types. Based on significant coexpression data and coessentiality, the signaling repertoire that accompanies Ephexin3 corresponded to three groups: pan-cancer, cancer-specific and coessential. To further select the Ephexin3 signaling partners likely to be relevant in clinical settings, we first identified those whose high expression was statistical linked to shorter patient survival. The resulting Ephexin3 transcriptional signatures represent significant accumulated risk, predictive of shorter survival, in 17 cancer types, including PAAD, LUAD, LGG, OSC, AML, KIRC, THYM, BLCA, LIHC and UCEC. The signaling landscape that accompanies Ephexin3 in various cancer types included the tyrosine kinase receptor MET and the tyrosine phosphatase receptor PTPRF, the serine/threonine kinases MARK2 and PAK6, the Rho GTPases RHOD, RHOF and RAC1, and the cytoskeletal regulator DIAHP1. Our findings set the basis to further explore the role of Ephexin3/ARHGEF5 as an essential effector and signaling hub in cancer cell migration.

Identification of tumor-agnostic biomarkers for predicting prostate cancer progression and biochemical recurrence.

The diverse clinical outcomes of prostate cancer have led to the development of gene signature assays predicting disease progression. Improved prostate cancer progression biomarkers are needed as current RNA biomarker tests have varying success for intermediate prostate cancer. Interest grows in universal gene signatures for invasive carcinoma progression. Early breast and prostate cancers share characteristics, including hormone dependence and BRCA1/2 mutations. Given the similarities in the pathobiology of breast and prostate cancer, we utilized the NanoString BC360 panel, comprising the validated PAM50 classifier and pathway-specific signatures associated with general tumor progression as well as breast cancer-specific classifiers. This retrospective cohort of primary prostate cancers (n=53) was stratified according to biochemical recurrence (BCR) status and the CAPRA-S to identify genes related to high-risk disease. Two public cohort (TCGA-PRAD and GSE54460) were used to validate the results. Expression profiling of our cohort uncovered associations between PIP and INHBA with BCR and high CAPRA-S score, as well as associations between VCAN, SFRP2, and THBS4 and BCR. Despite low levels of the ESR1 gene compared to AR, we found strong expression of the ER signaling signature, suggesting that BCR may be driven by ER-mediated pathways. Kaplan-Meier and univariate Cox proportional hazards regression analysis indicated the expression of ESR1, PGR, VCAN, and SFRP2 could predict the occurrence of relapse events. This is in keeping with the pathways represented by these genes which contribute to angiogenesis and the epithelial-mesenchymal transition. It is likely that VCAN works by activating the stroma and remodeling the tumor microenvironment. Additionally, SFRP2 overexpression has been associated with increased tumor size and reduced survival rates in breast cancer and among prostate cancer patients who experienced BCR. ESR1 influences disease progression by activating stroma, stimulating stem/progenitor prostate cancer, and inducing TGF-ß. Estrogen signaling may therefore serve as a surrogate to AR signaling during progression and in hormone-refractory disease, particularly in prostate cancer patients with stromal-rich tumors. Collectively, the use of agnostic biomarkers developed for breast cancer stratification has facilitated a precise clinical classification of patients undergoing radical prostatectomy and highlighted the therapeutic potential of targeting estrogen signaling in prostate cancer.