A single-cell atlas of the developing Drosophila ovary identifies follicle stem cell progenitors.

Addressing the complexity of organogenesis at a system-wide level requires a complete understanding of adult cell types, their origin, and precursor relationships. The Drosophila ovary has been a model to study how coordinated stem cell units, germline, and somatic follicle stem cells maintain and renew an organ. However, lack of cell type-specific tools have limited our ability to study the origin of individual cell types and stem cell units. Here, we used a single-cell RNA sequencing approach to uncover all known cell types of the developing ovary, reveal transcriptional signatures, and identify cell type-specific markers for lineage tracing. Our study identifies a novel cell type corresponding to the elusive follicle stem cell precursors and predicts subtypes of known cell types. Altogether, we reveal a previously unanticipated complexity of the developing ovary and provide a comprehensive resource for the systematic analysis of ovary morphogenesis.

Optimizing in silico drug discovery: simulation of connected differential expression signatures and applications to benchmarking.

BACKGROUND: We present a novel simulation method for generating connected differential expression signatures. Traditional methods have struggled with the lack of reliable benchmarking data and biases in drug-disease pair labeling, limiting the rigorous benchmarking of connectivity-based approaches. OBJECTIVE: Our aim is to develop a simulation method based on a statistical framework that allows for adjustable levels of parametrization, especially the connectivity, to generate a pair of interconnected differential signatures. This could help to address the issue of benchmarking data availability for connectivity-based drug repurposing approaches. METHODS: We first detailed the simulation process and how it reflected real biological variability and the interconnectedness of gene expression signatures. Then, we generated several datasets to enable the evaluation of different existing algorithms that compare differential expression signatures, providing insights into their performance and limitations. RESULTS: Our findings demonstrate the ability of our simulation to produce realistic data, as evidenced by correlation analyses and the log2 fold-change distribution of deregulated genes. Benchmarking reveals that methods like extreme cosine similarity and Pearson correlation outperform others in identifying connected signatures. CONCLUSION: Overall, our method provides a reliable tool for simulating differential expression signatures. The data simulated by our tool encompass a wide spectrum of possibilities to challenge and evaluate existing methods to estimate connectivity scores. This may represent a critical gap in connectivity-based drug repurposing research because reliable benchmarking data are essential for assessing and advancing in the development of new algorithms. The simulation tool is available as a R package (General Public License (GPL) license) at https://github.com/cgonzalez-gomez/cosimu.

Decoding Connectivity Map-based drug repurposing for oncotherapy.

The rising global burden of cancer has driven considerable efforts into the research and development of effective anti-cancer agents. Fortunately, with impressive advances in transcriptome profiling technology, the Connectivity Map (CMap) database has emerged as a promising and powerful drug repurposing approach. It provides an important platform for systematically discovering of the associations among genes, small-molecule compounds and diseases, and elucidating the mechanism of action of drug, contributing toward efficient anti-cancer pharmacotherapy. Moreover, CMap-based computational drug repurposing is gaining attention because of its potential to overcome the bottleneck constraints faced by traditional drug discovery in terms of cost, time and risk. Herein, we provide a comprehensive review of the applications of drug repurposing for anti-cancer drug discovery and summarize approaches for computational drug repurposing. We focus on the principle of the CMap database and novel CMap-based software/algorithms as well as their progress achieved for drug repurposing in the field of oncotherapy. This article is expected to illuminate the emerging potential of CMap in discovering effective anti-cancer drugs, thereby promoting efficient healthcare for cancer patients.

Association of early menarche with breast tumor molecular features and recurrence.

BACKGROUND: Early menarche is an established risk factor for breast cancer but its molecular contribution to tumor biology and prognosis remains unclear. METHODS: We profiled transcriptome-wide gene expression in breast tumors (N = 846) and tumor-adjacent normal tissues (N = 666) from women in the Nurses' Health Studies (NHS) to investigate whether early menarche (age < 12) is associated with tumor molecular and prognostic features in women with breast cancer. Multivariable linear regression and pathway analyses using competitive gene set enrichment analysis were conducted in both tumor and adjacent-normal tissue and externally validated in TCGA (N = 116). Subgroup analyses stratified on ER-status based on the tumor were also performed. PAM50 signatures were used for tumor molecular subtyping and to generate proliferation and risk of recurrence scores. We created a gene expression score using LASSO regression to capture early menarche based on 28 genes from FDR-significant pathways in breast tumor tissue in NHS and tested its association with 10-year disease-free survival in both NHS (N = 836) and METABRIC (N = 952). RESULTS: Early menarche was significantly associated with 369 individual genes in adjacent-normal tissues implicated in extracellular matrix, cell adhesion, and invasion (FDR ≤ 0.1). Early menarche was associated with upregulation of cancer hallmark pathways (18 significant pathways in tumor, 23 in tumor-adjacent normal, FDR ≤ 0.1) related to proliferation (e.g. Myc, PI3K/AKT/mTOR, cell cycle), oxidative stress (e.g. oxidative phosphorylation, unfolded protein response), and inflammation (e.g. pro-inflammatory cytokines IFN α and IFN γ ). Replication in TCGA confirmed these trends. Early menarche was associated with significantly higher PAM50 proliferation scores (ß = 0.082 [0.02-0.14]), odds of aggressive molecular tumor subtypes (basal-like, OR = 1.84 [1.18-2.85] and HER2-enriched, OR = 2.32 [1.46-3.69]), and PAM50 risk of recurrence score (ß = 4.81 [1.71-7.92]). Our NHS-derived early menarche gene expression signature was significantly associated with worse 10-year disease-free survival in METABRIC (N = 952, HR = 1.58 [1.10-2.25]). CONCLUSIONS: Early menarche is associated with more aggressive molecular tumor characteristics and its gene expression signature within tumors is associated with worse 10-year disease-free survival among women with breast cancer. As the age of onset of menarche continues to decline, understanding its relationship to breast tumor characteristics and prognosis may lead to novel secondary prevention strategies.

Gene expression signature predicts radiation sensitivity in cell lines using the integral of dose-response curve.

BACKGROUND: Although substantial efforts have been made to build molecular biomarkers to predict radiation sensitivity, the ability to accurately stratify the patients is still limited. In this study, we aim to leverage large-scale radiogenomics datasets to build genomic predictors of radiation response using the integral of the radiation dose-response curve. METHODS: Two radiogenomics datasets consisting of 511 and 60 cancer cell lines were utilized to develop genomic predictors of radiation sensitivity. The intrinsic radiation sensitivity, defined as the integral of the dose-response curve (AUC) was used as the radioresponse variable. The biological determinants driving AUC and SF2 were compared using pathway analysis. To build the predictive model, the largest and smallest datasets consisting of 511 and 60 cancer cell lines were used as the discovery and validation cohorts, respectively, with AUC as the response variable. RESULTS: Utilizing a compendium of three pathway databases, we illustrated that integral of the radiobiological model provides a more comprehensive characterization of molecular processes underpinning radioresponse compared to SF2. Furthermore, more pathways were found to be unique to AUC than SF2-30, 288 and 38 in KEGG, REACTOME and WIKIPATHWAYS, respectively. Also, the leading-edge genes driving the biological pathways using AUC were unique and different compared to SF2. With regards to radiation sensitivity gene signature, we obtained a concordance index of 0.65 and 0.61 on the discovery and validation cohorts, respectively. CONCLUSION: We developed an integrated framework that quantifies the impact of physical radiation dose and the biological effect of radiation therapy in interventional pre-clinical model systems. With the availability of more data in the future, the clinical potential of this signature can be assessed, which will eventually provide a framework to integrate genomics into biologically-driven precision radiation oncology.

A Tracheal Aspirate-derived Airway Basal Cell Model Reveals a Proinflammatory Epithelial Defect in Congenital Diaphragmatic Hernia.

Rationale: Congenital diaphragmatic hernia (CDH) is characterized by incomplete closure of the diaphragm and lung hypoplasia. The pathophysiology of lung defects in CDH is poorly understood. Objectives: To establish a translational model of human airway epithelium in CDH for pathogenic investigation and therapeutic testing. Methods: We developed a robust methodology of epithelial progenitor derivation from tracheal aspirates of newborns. Basal stem cells (BSCs) from patients with CDH and preterm and term non-CDH control subjects were derived and analyzed by bulk RNA sequencing, assay for transposase accessible chromatin with sequencing, and air-liquid interface differentiation. Lung sections from fetal human CDH samples and the nitrofen rat model of CDH were subjected to histological assessment of epithelial defects. Therapeutics to restore epithelial differentiation were evaluated in human epithelial cell culture and the nitrofen rat model of CDH. Measurements and Main Results: Transcriptomic and epigenetic profiling of CDH and control BSCs reveals a proinflammatory signature that is manifested by hyperactive nuclear factor kappa B and independent of severity and hernia size. In addition, CDH BSCs exhibit defective epithelial differentiation in vitro that recapitulates epithelial phenotypes found in fetal human CDH lung samples and fetal tracheas of the nitrofen rat model of CDH. Furthermore, blockade of nuclear factor kappa B hyperactivity normalizes epithelial differentiation phenotypes of human CDH BSCs in vitro and in nitrofen rat tracheas in vivo. Conclusions: Our findings have identified an underlying proinflammatory signature and BSC differentiation defects as a potential therapeutic target for airway epithelial defects in CDH.

Development and validation of a 23-gene expression signature for molecular subtyping of medulloblastoma in a long-term Chinese cohort.

PURPOSE: Medulloblastoma is the most common childhood malignant brain tumor and is a leading cause of cancer-related death in children. Recent transcriptional studies have shown that medulloblastomas comprise at least four molecular subgroups, each with distinct demographics, genetics, and clinical outcomes. Medulloblastoma subtyping has become critical for subgroup-specific therapies. The use of gene expression assays to determine the molecular subgroup of clinical specimens is a long-awaited application of molecular biology for this pediatric cancer. METHODS: In the current study, we established a medulloblastoma transcriptome database of 460 samples retrieved from three published datasets (GSE21140, GSE37382, and GSE37418). With this database, we identified a 23-gene signature that is significantly associated with the medulloblastoma subgroups and achieved a classification accuracy of 95.2%. RESULTS: The 23-gene signature was further validated in a long-term cohort of 142 Chinese medulloblastoma patients. The 23-gene signature classified 21 patients as WNT (15%), 41 as SHH (29%), 16 as Group 3 (11%), and 64 as Group 4 (45%). For patients of WNT, SHH, Group 3, and Group 4, 5-year overall-survival rate reached 80%, 62%, 27%, and 47%, respectively (p < 0.0001), meanwhile 5-year progression-free survival reached 80%, 52%, 27%, and 45%, respectively (p < 0.0001). Besides, SHH/TP53-mutant tumors were associated with worse prognosis compared with SHH/TP53 wild-type tumors and other subgroups. We demonstrated that subgroup assignments by the 23-gene signature and Northcott's NanoString assay were highly comparable with a concordance rate of 96.4%. CONCLUSIONS: In conclusion, we present a novel gene signature that is capable of accurately and reliably assigning FFPE medulloblastoma samples to their molecular subgroup, which may serve as an auxiliary tool for medulloblastoma subtyping in the clinic. Future incorporation of this gene signature into prospective clinical trials is warranted to further evaluate its clinical.

Pair bonding and disruption impact lung transcriptome in monogamous Peromyscus californicus.

Social interactions affect physiological and pathological processes, yet their direct impact in peripheral tissues remains elusive. Recently we showed that disruption of pair bonds in monogamous Peromyscus californicus promotes lung tumorigenesis, pointing to a direct effect of bonding status in the periphery (Naderi et al., 2021). Here we show that lung transcriptomes of tumor-free Peromyscus are altered in a manner that depends on pair bonding and superseding the impact of genetic relevance between siblings. Pathways affected involve response to hypoxia and heart development. These effects are consistent with the profile of the serum proteome of bonded and bond-disrupted Peromyscus and were extended to lung cancer cells cultured in vitro, with sera from animals that differ in bonding experiences. In this setting, the species' origin of serum (deer mouse vs FBS) is the most potent discriminator of RNA expression profiles, followed by bonding status. By analyzing the transcriptomes of lung cancer cells exposed to deer mouse sera, an expression signature was developed that discriminates cells according to the history of social interactions and possesses prognostic significance when applied to primary human lung cancers. The results suggest that present and past social experiences modulate the expression profile of peripheral tissues such as the lungs, in a manner that impacts physiological processes and may affect disease outcomes. Furthermore, they show that besides the direct effects of the hormones that regulate bonding behavior, physiological changes influencing oxygen metabolism may contribute to the adverse effects of bond disruption.

Expression signature and prognostic value of CREC gene family in human colorectal cancer.

Colorectal cancer (CRC) is one of the malignant tumors with the highest morbidity and mortality and poor prognosis. The mammalian gene family of Cab45/reticulocalbin/ERC-45/calumenin (CREC) consists of RCN1, RCN2, RCN3, SDF4 and CALU. Although CREC family members have been associated with CRC, the expression pattern, prognostic value, and the role of CREC family in CRC remain unclear. In this study, the expression, survival and biological functions of CREC family in CRC were determined via bioinformatic datasets analysis and experimental verification on clinical CRC specimen. Bioinformatic analysis showed that the expression levels of most CREC family genes were higher in CRC tissues than in normal colorectal tissues. The qPCR and western blot results also revealed that the transcriptional and protein levels of CREC family were elevated in CRC tissues compared with adjacent tissues. Besides, CREC family was significantly correlated with advanced tumor stage and poor prognosis of CRC patients. The expression levels of CREC family had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, macrophages, neutrophils, and dendritic cells in the microenvironment of CRC. Functional networks enrichment analysis indicated that the genes of CREC family were essential factors for CRC metastasis. Collectively, these findings suggest that CREC family might be potential targets for the treatment of CRC and candidate prognostic markers for CRC patients.

Use of a gene expression signature to identify trimetazidine for repurposing to treat bipolar depression.

OBJECTIVES: The aim of this study was to repurpose a drug for the treatment of bipolar depression. METHODS: A gene expression signature representing the overall transcriptomic effects of a cocktail of drugs widely prescribed to treat bipolar disorder was generated using human neuronal-like (NT2-N) cells. A compound library of 960 approved, off-patent drugs were then screened to identify those drugs that affect transcription most similar to the effects of the bipolar depression drug cocktail. For mechanistic studies, peripheral blood mononuclear cells were obtained from a healthy subject and reprogrammed into induced pluripotent stem cells, which were then differentiated into co-cultured neurons and astrocytes. Efficacy studies were conducted in two animal models of depressive-like behaviours (Flinders Sensitive Line rats and social isolation with chronic restraint stress rats). RESULTS: The screen identified trimetazidine as a potential drug for repurposing. Trimetazidine alters metabolic processes to increase ATP production, which is thought to be deficient in bipolar depression. We showed that trimetazidine increased mitochondrial respiration in cultured human neuronal-like cells. Transcriptomic analysis in induced pluripotent stem cell-derived neuron/astrocyte co-cultures suggested additional mechanisms of action via the focal adhesion and MAPK signalling pathways. In two different rodent models of depressive-like behaviours, trimetazidine exhibited antidepressant-like activity with reduced anhedonia and reduced immobility in the forced swim test. CONCLUSION: Collectively our data support the repurposing of trimetazidine for the treatment of bipolar depression.

Gene expression profiling of nasal inflammation induced by diesel particles using an in vivo system.

Korean diesel particulate matter 20 (KDP20) is a pollutant comprising a complex mixture of carbon and chemical irritants. Although particulate matter and nasal inflammation are strongly associated, the underlying molecular mechanism based on systematic transcriptome analysis remains unknown. In this study, genome-wide gene expression profiles of mouse nasal tissues were determined following exposure to KDP20 for 5 and 10 days and compared with those of the control (n = 4/group). We identified 758 significant differentially expressed genes (DEGs) and classified them as 5-day-specific, 10-day-specific, and common among groups based on their expression patterns. The terms "regulation of alpha-beta T cell differentiation," "macrophage differentiation," and "cell adhesion mediated by integrin" were significantly enriched in each group. Receiver operating characteristic analysis revealed six genes as potential predictive biomarkers. The differential expression of these six genes was validated using quantitative RT-PCR (n = 3/group). Furthermore, a possible mechanism for nasal inflammation was suggested through the binding analysis between metal ions and genes. The genes identified in this study may play important roles in regulating the mechanism of nasal inflammation induced by diesel particles, especially immune cell regulation, and may function as markers for diesel particle-induced nasal inflammation.

Bioinformatic Analysis of Key Regulatory Genes in Adult Asthma and Prediction of Potential Drug Candidates.

Asthma is a common chronic disease that is characterized by respiratory symptoms including cough, wheeze, shortness of breath, and chest tightness. The underlying mechanisms of this disease are not fully elucidated, so more research is needed to identify better therapeutic compounds and biomarkers to improve disease outcomes. In this present study, we used bioinformatics to analyze the gene expression of adult asthma in publicly available microarray datasets to identify putative therapeutic molecules for this disease. We first compared gene expression in healthy volunteers and adult asthma patients to obtain differentially expressed genes (DEGs) for further analysis. A final gene expression signature of 49 genes, including 34 upregulated and 15 downregulated genes, was obtained. Protein-protein interaction and hub analyses showed that 10 genes, including POSTN, CPA3, CCL26, SERPINB2, CLCA1, TPSAB1, TPSB2, MUC5B, BPIFA1, and CST1, may be hub genes. Then, the L1000CDS2 search engine was used for drug repurposing studies. The top approved drug candidate predicted to reverse the asthma gene signature was lovastatin. Clustergram results showed that lovastatin may perturb MUC5B expression. Moreover, molecular docking, molecular dynamics simulation, and computational alanine scanning results supported the notion that lovastatin may interact with MUC5B via key residues such as Thr80, Thr91, Leu93, and Gln105. In summary, by analyzing gene expression signatures, hub genes, and therapeutic perturbation, we show that lovastatin is an approved drug candidate that may have potential for treating adult asthma.

A Nine-Gene Expression Signature Distinguished a Patient with Chronic Lymphocytic Leukemia Who Underwent Prolonged Periodic Fasting.

Background and Objectives: This study aimed to investigate the causes of continuous deep fluctuations in the absolute lymphocyte count (ALC) in an untreated patient with Chronic Lymphocytic Leukemia (CLL), who has had a favorable prognosis since the time of diagnosis. Up until now, the patient has voluntarily chosen to adopt a predominantly vegetarian and fruitarian diet, along with prolonged periods of total fasting (ranging from 4 to 39 days) each year. Materials and Methods: For this purpose, we decided to analyze the whole transcriptome profiling of peripheral blood (PB) CD19+ cells from the patient (#1) at different time-points vs. the same cells of five other untreated CLL patients who followed a varied diet. Consequently, the CLL patients were categorized as follows: the 1st group comprised patient #1 at 20 different time-points (16 time-points during nutrition and 4 time-points during fasting), whereas the 2nd group included only one time point for each of the patients (#2, #3, #4, #5, and #6) as they followed a varied diet. We performed microarray experiments using a powerful tool, the Affymetrix Human Clariom™ D Pico Assay, to generate high-fidelity biomarker signatures. Statistical analysis was employed to identify differentially expressed genes and to perform sample clustering. Results: The lymphocytosis trend in patient #1 showed recurring fluctuations since the time of diagnosis. Interestingly, we observed that approximately 4-6 weeks after the conclusion of fasting periods, the absolute lymphocyte count was reduced by about half. The gene expression profiling analysis revealed that nine genes were statistically differently expressed between the 1st group and the 2nd group. Specifically, IGLC3, RPS26, CHPT1, and PCDH9 were under expressed in the 1st group compared to the 2nd group of CLL patients. Conversely, IGHV3-43, IGKV3D-20, PLEKHA1, CYBB, and GABRB2 were over-expressed in the 1st group when compared to the 2nd group of CLL patients. Furthermore, clustering analysis validated that all the samples from patient #1 clustered together, showing clear separation from the samples of the other CLL patients. Conclusions: This study unveiled a small gene expression signature consisting of nine genes that distinguished an untreated CLL patient who followed prolonged periods of total fasting, maintaining a gradual growth trend of lymphocytosis, compared to five untreated CLL patients with a varied diet. Future investigations focusing on patient #1 could potentially shed light on the role of prolonged periodic fasting and the implication of this specific gene signature in sustaining the lymphocytosis trend and the favorable course of the disease.

Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses' health study.

BACKGROUND: Breast tumor immune infiltration is clearly associated with improved treatment response and outcomes in breast cancer. However, modifiable patient factors associated with breast cancer immune infiltrates are poorly understood. The Nurses' Health Study (NHS) offers a unique cohort to study immune gene expression in tumor and adjacent normal breast tissue, immune cell-specific immunohistochemistry (IHC), and patient exposures. We evaluated the association of body mass index (BMI) change since age 18, physical activity, and the empirical dietary inflammatory pattern (EDIP) score, all implicated in systemic inflammation, with immune cell-specific expression scores. METHODS: This population-based, prospective observational study evaluated 882 NHS and NHSII participants diagnosed with invasive breast cancer with detailed exposure and gene expression data. Of these, 262 women (training cohort) had breast tumor IHC for four classic immune cell markers (CD8, CD4, CD20, and CD163). Four immune cell-specific scores were derived via lasso regression using 105 published immune expression signatures' association with IHC. In the remaining 620 patient evaluation cohort, we evaluated association of each immune cell-specific score as outcomes, with BMI change since age 18, physical activity, and EDIP score as predictors, using multivariable-adjusted linear regression. RESULTS: Among women with paired expression/IHC data from breast tumor tissue, we identified robust correlation between novel immune cell-specific expression scores and IHC. BMI change since age 18 was positively associated with CD4+ (ß = 0.16; p = 0.009), and CD163 novel immune scores (ß = 0.14; p = 0.04) in multivariable analyses. In other words, for each 10 unit (kg/m2) increase in BMI, the percentage of cells positive for CD4 and CD163 increased 1.6% and 1.4%, respectively. Neither physical activity nor EDIP was significantly associated with any immune cell-specific expression score in multivariable analyses. CONCLUSIONS: BMI change since age 18 was positively associated with novel CD4+ and CD163+ cell scores in breast cancer, supporting further study of the effect of modifiable factors like weight gain on the immune microenvironment.

The early-stage triple-negative breast cancer landscape derives a novel prognostic signature and therapeutic target.

PURPOSE: Triple-negative breast cancer (TNBC) is a highly heterogeneous disease. Patients with early-stage TNBCs have distinct likelihood of distant recurrence. This study aimed to develop a prognostic signature of early-stage TNBC patients to improve risk stratification. METHODS: Using RNA-sequencing data, we analyzed 189 pathologically confirmed pT1-2N0M0 TNBC patients and identified 21 mRNAs that were highly expressed in tumor and related to relapse-free survival. All-subset regression program was used for constructing a 7-mRNA signature in the training set (n = 159); the accuracy and prognostic value were then validated using an independent validation set (n = 158). RESULTS: Here, we profiled the transcriptome data from 189 early-stage TNBC patients along with 50 paired normal tissues. Early-stage TNBCs mainly consisted of basal-like immune-suppressed subtype and had higher homologous recombination deficiency scores. We developed a prognostic signature including seven mRNAs (ACAN, KRT5, TMEM101, LCA5, RPP40, LAGE3, CDKL2). In both the training (n = 159) and validation set (n = 158), this signature could identify patients with relatively high recurrence risks and served as an independent prognostic factor. Time-dependent receiver operating curve showed that the signature had better prognostic value than traditional clinicopathological features in both sets. Functionally, we showed that TMEM101 promoted cell proliferation and migration in vitro, which represented a potential therapeutic target. CONCLUSIONS: Our 7-mRNA signature could accurately predict recurrence risks of early-stage TNBCs. This model may facilitate personalized therapy decision-making for early-stage TNBCs individuals.

Identification of a novel HOOK3-FGFR1 fusion gene involved in activation of the NF-kappaB pathway.

BACKGROUND: Rearrangements involving the fibroblast growth factor receptor 1 (FGFR1) gene result in 8p11 myeloproliferative syndrome (EMS), which is a rare and aggressive hematological malignancy that is often initially diagnosed as myelodysplastic syndrome (MDS). Clinical outcomes are typically poor due to relative resistance to tyrosine kinase inhibitors (TKIs) and rapid transformation to acute leukemia. Deciphering the transcriptomic signature of FGFR1 fusions may open new treatment strategies for FGFR1 rearrangement patients. METHODS: DNA sequencing (DNA-seq) was performed for 20 MDS patients and whole exome sequencing (WES) was performed for one HOOK3-FGFR1 fusion positive patient. RNA sequencing (RNA-seq) was performed for 20 MDS patients and 8 healthy donors. Fusion genes were detected using the STAR-Fusion tool. Fluorescence in situ hybridization (FISH), quantitative real-time PCR (qRT-PCR), and Sanger sequencing were used to confirm the HOOK3-FGFR1 fusion gene. The phosphorylation antibody array was performed to validate the activation of nuclear factor-kappaB (NF-kappaB) signaling. RESULTS: We identified frequently recurrent mutations of ASXL1 and U2AF1 in the MDS cohort, which is consistent with previous reports. We also identified a novel in-frame HOOK3-FGFR1 fusion gene in one MDS case with abnormal monoclonal B-cell lymphocytosis and ring chromosome 8. FISH analysis detected the FGFR1 break-apart signal in myeloid blasts only. qRT-PCR and Sanger sequencing confirmed the HOOK3-FGFR1 fusion transcript with breakpoints located at the 11th exon of HOOK3 and 10th exon of FGFR1, and Western blot detected the chimeric HOOK3-FGFR1 fusion protein that is presumed to retain the entire tyrosine kinase domain of FGFR1. The transcriptional feature of HOOK3-FGFR1 fusion was characterized by the significant enrichment of the NF-kappaB pathway by comparing the expression profiling of FGFR1 fusion positive MDS with 8 healthy donors and FGFR1 fusion negative MDS patients. Further validation by phosphorylation antibody array also showed NF-kappaB activation, as evidenced by increased phosphorylation of p65 (Ser 536) and of IKBalpha (Ser 32). CONCLUSIONS: The HOOK3-FGFR1 fusion gene may contribute to the pathogenesis of MDS and activate the NF-kappaB pathway. These findings highlight a potential novel approach for combination therapy for FGFR1 rearrangement patients.

Values of OAS gene family in the expression signature, immune cell infiltration and prognosis of human bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is one of the most common genitourinary malignancies in the world, but its pathogenic genes have not been fully identified and the treatment outcomes are still unsatisfactory. Although the members of 2', 5'-oligoadenylate synthetase (OAS) gene family are known involved in some tumorous biological processes, the roles of the OAS gene family in BLCA are still undetermined. METHODS: By combining vast bioinformatic datasets analyses of BLCA and the experimental verification on clinical BLCA specimen, we identified the expressions and biological functions of OAS gene family members in BLCA with comparison to normal bladder tissues. RESULTS: The expression levels of OAS gene family members were higher in BLCA than in normal bladder tissues. The expression levels of most OAS genes had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells in the microenvironment of BLCA. In addition, high expressions of OAS1, OAS2, OAS3, and OASL predicted better overall survival in BLCA patients. CONCLUSIONS: The highly expressed OAS genes in BLCA can reflect immune cells infiltration in the tumor microenvironment and predict the better overall survival of BLCA, and thus may be considered as a signature of BLCA. The study provides new insights into the diagnosis, treatment, and prognosis of BLCA.

An integrative gene expression signature analysis identifies CMS4 KRAS-mutated colorectal cancers sensitive to combined MEK and SRC targeted therapy.

BACKGROUND: Over half of colorectal cancers (CRCs) are hard-wired to RAS/RAF/MEK/ERK pathway oncogenic signaling. However, the promise of targeted therapeutic inhibitors, has been tempered by disappointing clinical activity, likely due to complex resistance mechanisms that are not well understood. This study aims to investigate MEK inhibitor-associated resistance signaling and identify subpopulation(s) of CRC patients who may be sensitive to biomarker-driven drug combination(s). METHODS: We classified 2250 primary and metastatic human CRC tumors by consensus molecular subtypes (CMS). For each tumor, we generated multiple gene expression signature scores measuring MEK pathway activation, MEKi "bypass" resistance, SRC activation, dasatinib sensitivity, EMT, PC1, Hu-Lgr5-ISC, Hu-EphB2-ISC, Hu-Late TA, Hu-Proliferation, and WNT activity. We carried out correlation, survival and other bioinformatic analyses. Validation analyses were performed in two independent publicly available CRC tumor datasets (n = 585 and n = 677) and a CRC cell line dataset (n = 154). RESULTS: Here we report a central role of SRC in mediating "bypass"-resistance to MEK inhibition (MEKi), primarily in cancer stem cells (CSCs). Our integrated and comprehensive gene expression signature analyses in 2250 CRC tumors reveal that MEKi-resistance is strikingly-correlated with SRC activation (Spearman P < 10-320), which is similarly associated with EMT (epithelial to mesenchymal transition), regional metastasis and disease recurrence with poor prognosis. Deeper analysis shows that both MEKi-resistance and SRC activation are preferentially associated with a mesenchymal CSC phenotype. This association is validated in additional independent CRC tumor and cell lines datasets. The CMS classification analysis demonstrates the strikingly-distinct associations of CMS1-4 subtypes with the MEKi-resistance and SRC activation. Importantly, MEKi + SRCi sensitivities are predicted to occur predominantly in the KRAS mutant, mesenchymal CSC-like CMS4 CRCs. CONCLUSIONS: Large human tumor gene expression datasets representing CRC heterogeneity can provide deep biological insights heretofore not possible with cell line models, suggesting novel repurposed drug combinations. We identified SRC as a common targetable node--an Achilles' heel--in MEKi-targeted therapy-associated resistance in mesenchymal stem-like CRCs, which may help development of a biomarker-driven drug combination (MEKi + SRCi) to treat problematic subpopulations of CRC.

Association between cancer stem cell gene expression signatures and prognosis in head and neck squamous cell carcinoma.

BACKGROUND: Various cancer stem cell (CSC) biomarkers and the genes encoding them in head and neck squamous cell carcinoma (HNSCC) have been identified and evaluated. However, the validity of these factors in the prognosis of HNSCC has been questioned and remains unclear. In this study, we examined the clinical significance of CSC biomarker genes in HNSCC, using five publicly available HNSCC cohorts. METHODS: To predict the prognosis of patients with HNSCC, we developed and validated the expression signatures of CSC biomarker genes whose mRNA expression levels correlated with at least one of the four CSC genes (CD44, MET, ALDH1A1, and BMI1). RESULTS: Patients in The Cancer Genome Atlas (TCGA) HNSCC cohort were classified into CSC gene expression-associated high-risk (CSC-HR; n = 285) and CSC gene expression-associated low-risk (CSC-LR; n = 281) subgroups. The 5-year overall survival and recurrence-free survival rates were significantly lower in the CSC-HR subgroup than in the CSC-LR subgroup (p = 0.04 and 0.02, respectively). The clinical significance of the CSC gene expression signature was validated using four independent cohorts. Analysis using Cox proportional hazards models showed that the CSC gene expression signature was an independent prognostic factor of non-oropharyngeal HNSCC which mostly indicates HPV (-) status. Furthermore, the CSC gene expression signature was associated with the prognosis of HNSCC patients who received radiotherapy. CONCLUSION: The CSC gene expression signature is associated with the prognosis of HNSCC and may help in personalized treatments for patients with HNSCC, especially in cases with HPV (-) status who were classified in more detail.

Molecular Pathogenesis of Colorectal Cancer: Impact of Oncogenic Targets Regulated by Tumor Suppressive miR-139-3p.

We recently determined the RNA sequencing-based microRNA (miRNA) expression signature of colorectal cancer (CRC). Analysis of the signature showed that the expression of both strands of pre-miR-139 (miR-139-5p, the guide strand, and miR-139-3p, the passenger strand) was significantly reduced in CRC tissues. Transient transfection assays revealed that expression of miR-139-3p blocked cancer cell malignant transformation (e.g., cell proliferation, migration, and invasion). Notably, expression of miR-139-3p markedly blocked RAC-alpha serine/threonine-protein kinase (AKT) phosphorylation in CRC cells. A combination of in silico database and gene expression analyses of miR-139-3p-transfected cells revealed 29 putative targets regulated by miR-139-3p in CRC cells. RNA immunoprecipitation analysis using an Argonaute2 (AGO2) antibody revealed that KRT80 was efficiently incorporated into the RNA-induced silencing complex. Aberrant expression of Keratin 80 (KRT80) was detected in CRC clinical specimens by immunostaining. A knockdown assay using small interfering RNA (siRNA) targeting KRT80 showed that reducing KRT80 expression suppressed the malignant transformation (cancer cell migration and invasion) of CRC cells. Importantly, inhibiting KRT80 expression reduced AKT phosphorylation in CRC cells. Moreover, hexokinase-2 (HK2) expression was reduced in cells transfected with the KRT80 siRNAs or miR-139-3p. The involvement of miRNA passenger strands (e.g., miR-139-3p) in CRC cells is a new concept in miRNA studies. Our tumor-suppressive miRNA-based approach helps elucidate the molecular pathogenesis of CRC.