Conditional transcriptional relationships may serve as cancer prognostic markers

Background While most differential coexpression (DC) methods are bound to quantify a single correlation value for a gene pair across multiple samples, a newly devised approach under the name Correlation by Individual Level Product (CILP) revolutionarily projects the summary correlation value to individual product correlation values for separate samples. CILP greatly widened DC analysis opportunities by allowing integration of non-compromised statistical methods. Methods Here, we performed a study to verify our hypothesis that conditional relationships, i.e., gene pairs of remarkable differential coexpression, may be sought as quantitative prognostic markers for human cancers. Alongside the seeking of prognostic gene links in a pan-cancer setting, we also examined whether a trend of global expression correlation loss appeared in a wide panel of cancer types and revisited the controversial subject of mutual relationship between the DE approach and the DC approach. Results By integrating CILP with classical univariate survival analysis, we identified up to 244 conditional gene links as potential prognostic markers in five cancer types. In particular, five prognostic gene links for kidney renal papillary cell carcinoma tended to condense around cancer gene ESPL1, and the transcriptional synchrony between ESPL1 and PTTG1 tended to be elevated in patients of adverse prognosis. In addition, we extended the observation of global trend of correlation loss in more than ten cancer types and empirically proved DC analysis results were independent of gene differential expression in five cancer types. Conclusions Combining the power of CILP and the classical survival analysis, we successfully fetched conditional transcriptional relationships that conferred prognosis power for five cancer types. Despite a general trend of global correlation loss in tumor transcriptomes, most of these prognosis conditional links demonstrated stronger expression correlation in tumors, and their stronger coexpression was associated with poor survival.

Global Proteomic Profiling Identifies Novel Prognostic Factors in Undifferentiated Leukemia Blasts from Patients with NPM1 Mutations: A Previously Unreported Approach to Biomarker Discovery from the Fred Hutch and SWOG

AML blasts harbor multiple genomic, epigenomic, and transcriptomic abnormalities. Proteins are responsible for much of the functional biology derived from these transforming events, yet few studies have examined the global proteome in specimens from AML patients. To gain insight into the biology and prognostic biomarkers for AML, we examined the genome, transcriptome and proteome in highly enriched less differentiated, viable leukemic blasts (VLBs) from previously untreated patients with NPM1 mutated (NPM1+) AML. We focused on NPM1+ AML because 1) NPM1 mutations are the most common genomic abnormality used for risk stratifying AML patients; 2) clinical outcomes for NPM1+ patients vary substantially; and 3) restricting studies to VLBs from patients with NPM1+ AMLreduces the molecular diversity and confounding interactions that may impede identification of biological and clinically relevant biomarkers. Cryopreserved specimens from patients with NPM1+ AML were obtained from the SWOG Leukemia and Fred Hutch/University of Washington Hematopoietic Disease Repositories (N=178). All patients were treated with dose intensive induction and consolidation with curative intent. VLBs were isolated from specimens using fluorescence-activated cell sorting (FACS). Fragment analysis was used to identify FLT3-ITDs, while other genomic mutations were identified using targeted next generation sequencing (NGS). RNA sequencing (RNAseq) was used to quantify transcript expression, while protein expression was quantified using tandem mass tag labelling followed by liquid chromatograph with tandem mass spectrometry (TMT-LC-MS/MS). Prognostic significance of biomarkers was examined by univariate and multivariate analyses, with the later adjusting for both age and ELN2017 risk. Adequate analyte from VLBs were available for RNAseq and TMT-LC-MS/MS studies in 131 and 71 patients, respectively. Proteomic profiling identified 6712 expressed proteins. Multivariable analyses adjusting for age and ELN2017 risk identified 211, 218, and 313 proteins were significantly associated with CR, EFS, and OS, respectively, of which 116 and 174 had a HR ≥ 2 or ≤ 0.5 for EFS and OS (Fig 1A). Analyses showed an overall modest correlation between RNA and protein expression for the 6297 genes present in both RNA and protein datasets (Fig 1B, R =0.27). A total of 163 of the 174 proteomic candidates for OS had RNAseq data, but RNA expression was not significantly correlated with OS for most of these genes (Fig 1C). Similarly, the expression correlation between RNA and protein was not improved by restricting the analyses to these 163 genes (Fig 1D, R =0.28). We also compared protein expression between the NPM1+ VLBs and CD34 progenitors from healthy donors (NLCD34=5), which identified 747 proteins with significant expression differences between the two cell populations (FDR ≤ 0.1). Seventy-three of the 747 proteins displayed > 3-fold increased expression in NPM1+ VLBs, some of which activate targetable pathways (HOMER->WNT/CTNNB1) and/or amenable to adoptive immunotherapies (e.g., CT45). Additional analyses identified 401 proteins with significantly increased expression in VLBs harboring a high FLT3-ITD allelic ratio (NPM1+/FLT3-ITD-H), a less favorable population of patients. In these less favorable patients, many of the same proteins remained overexpressed (e.g., CT45 with 7.85-fold increased expression, FDR=0.009), but other targetable proteins also emerged. For example, PKCD had a 3.41-fold increased expression (FDR=0.001) in the NPM1+/FLT3-ITD-H VLBs, and targetable inhibitors against this protein (e.g., Parsaclisib) are already in clinical trials for other cancers. This study examines for the first time the global proteome in a large number of VLBs from patients with AML. As with recent publications examining other cancers, the overall expression correlation between RNA and protein was modest, at best, and most of the informative prognostic proteins for OS were not significant in the transcriptome. In addition, the results show the potential to identify novel proteomic targets in subpopulations of AML patients, which may not be otherwise discovered using other means. Thus, the results demonstrate the need to include proteomic profiling in future multi-omics studies seeking to discover novel prognostic biomarkers and therapeutic targets. Figure 1 Figure 1. Disclosures Erba: AbbVie Inc; Agios Pharmaceuticals Inc; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Incyte Corporation; Jazz Pharmaceuticals Inc; Novartis: Speakers Bureau; AbbVie Inc: Other: Independent review committee; AbbVie Inc; Agios Pharmaceuticals Inc; ALX Oncology; Amgen Inc; Daiichi Sankyo Inc; FORMA Therapeutics; Forty Seven Inc; Gilead Sciences Inc; GlycoMimetics Inc; ImmunoGen Inc; Jazz Pharmaceuticals Inc; MacroGenics Inc; Novartis; PTC Therapeutics: Research Funding; AbbVie Inc; Agios Pharmaceuticals Inc; Astellas; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Daiichi Sankyo Inc; Genentech, a member of the Roche Group; GlycoMimetics Inc; Incyte Corporation; Jazz Pharmaceuticals Inc; Kura Oncology; Nov: Other: Advisory Committee. Moseley: BioSight Ltd: Consultancy. Radich: Novartis: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees.

Low GNG12 Expression Predicts Adverse Outcomes: A Potential Therapeutic Target for Osteosarcoma

BackgroundG protein subunit gamma 12 (GNG12) is observed in some types of cancer, but its role in osteosarcoma is unknown. This study hypothesized that GNG12 may be a potential biomarker and therapeutic target. We aimed to identify an association between GNG12 and osteosarcoma based on the Gene Expression Omnibus and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) databases.MethodsOsteosarcoma samples in GSE42352 and TARGET database were selected as the test cohorts. As the external validation cohort, 78 osteosarcoma specimens from The Second Affiliated Hospital of Nanchang University were collected. Patients with osteosarcoma were divided into high and low GNG12 mRNA-expression groups; differentially expressed genes were identified as GNG12-related genes. The biological function of GNG12 was annotated using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and immune infiltration analysis. Gene expression correlation analysis and competing endogenous RNA regulatory network construction were used to determine potential biological regulatory relationships of GNG12. Overall survival, Kaplan–Meier analysis, and log-rank tests were calculated to determine GNG12 reliability in predicting survival prognosis.ResultsGNG12 expression decreased in osteosarcoma samples. GNG12 was a highly effective biomarker for osteosarcoma [area under the receiver operating characteristic (ROC) curve (AUC) = 0.920], and the results of our Kaplan–Meier analysis indicated that overall survival and progression-free survival differed significantly between low and high GNG-expression group (p < 0.05). Functional analyses indicated that GNG12 may promote osteosarcoma through regulating the endoplasmic reticulum. Expression correlation analysis and competing endogenous RNA network construction showed that HOTTIP/miR-27a-3p may regulate GNG12 expression. Furthermore, the subunit suppresses adaptive immunity via inhibiting M1 and M2 macrophage infiltration. GNG12 was inhibited in metastatic osteosarcoma compared with non-metastatic osteosarcoma, and its expression predicted survival of patients (1, 3, and 5-year AUCs were 0.961, 0.826, and 0.808, respectively).ConclusionThis study identified GNG12 as a potential biomarker for osteosarcoma prognosis, highlighting its potential as an immunotherapy target.

Genome-wide analysis of MYB transcription factors of Vaccinium corymbosum and their positive responses to drought stress

Background Blueberry (Vaccinium corymbosum L.) is an important species with a high content of flavonoids in fruits. As a perennial shrub, blueberry is characterized by shallow-rooted property and susceptible to drought stress. MYB transcription factor was reported to be widely involved in plant response to abiotic stresses, however, the role of MYB family in blueberry responding to drought stress remains elusive. Results In this study, we conducted a comprehensive analysis of VcMYBs in blueberry based on the genome data under drought stress, including phylogenetic relationship, identification of differentially expressed genes (DEGs), expression profiling, conserved motifs, expression correlation and protein-protein interaction prediction, etc. The results showed that 229 non-redundant MYB sequences were identified in the blueberry genome, and divided into 23 subgroups. A total of 102 MYB DEGs with a significant response to drought stress were identified, of which 72 in leaves and 69 in roots, and 8 differential expression genes with a > 20-fold change in the level of expression. 17 DEGs had a higher expression correlation with other MYB members. The interaction partners of the key VcMYB proteins were predicted by STRING analysis and in combination with physiological and morphological observation. 10 key VcMYB genes such as VcMYB8, VcMYB102 and VcMYB228 were predicted to be probably involved in reactive oxygen species (ROS) pathway, and 7 key VcMYB genes (VcMYB41, VcMYB88 and VcMYB100, etc..) probably participated in leaf regulation under drought treatment. Conclusions Our studies provide a new understanding of the regulation mechanism of VcMYB family in blueberry response to drought stress, and lay fundamental support for future studies on blueberry grown in regions with limited water supply for this crop.

Gene Expression Correlation Analysis Reveals MYC-NAC Regulatory Network in Cotton Pigment Gland Development

Plant NAC (NAM, ATAF1/2, and CUC2) family is involved in various development processes including Programmed Cell Death (PCD) associated development. However, the relationship between NAC family and PCD-associated cotton pigment gland development is largely unknown. In this study, we identified 150, 153 and 299 NAC genes in newly updated genome sequences of G. arboreum, G. raimondii and G. hirsutum, respectively. All NAC genes were divided into 8 groups by the phylogenetic analysis and most of them were conserved during cotton evolution. Using the vital regulator of gland formation GhMYC2-like as bait, expression correlation analysis screened out 6 NAC genes which were low-expressed in glandless cotton and high-expressed in glanded cotton. These 6 NAC genes acted downstream of GhMYC2-like and were induced by MeJA. Silencing CGF1(Cotton Gland Formation1), another MYC-coding gene, caused almost glandless phenotype and down-regulated expression of GhMYC2-like and the 6 NAC genes, indicating a MYC-NAC regulatory network in gland development. In addition, predicted regulatory mechanism showed that the 6 NAC genes were possibly regulated by light, various phytohormones and transcription factors as well as miRNAs. The interaction network and DNA binding sites of the 6 NAC transcription factors were also predicted. These results laid the foundation for further study of gland-related genes and gland development regulatory network.

Expression correlation attenuates within and between key signaling pathways in chronic kidney disease

Background Compared to the conventional differential expression approach, differential coexpression analysis represents a different yet complementary perspective into diseased transcriptomes. In particular, global loss of transcriptome correlation was previously observed in aging mice, and a most recent study found genetic and environmental perturbations on human subjects tended to cause universal attenuation of transcriptome coherence. While methodological progresses surrounding differential coexpression have helped with research on several human diseases, there has not been an investigation of coexpression disruptions in chronic kidney disease (CKD) yet. Methods RNA-seq was performed on total RNAs of kidney tissue samples from 140 CKD patients. A combination of differential coexpression methods were employed to analyze the transcriptome transition in CKD from the early, mild phase to the late, severe kidney damage phase. Results We discovered a global expression correlation attenuation in CKD progression, with pathway Regulation of nuclear SMAD2/3 signaling demonstrating the most remarkable intra-pathway correlation rewiring. Moreover, the pathway Signaling events mediated by focal adhesion kinase displayed significantly weakened crosstalk with seven pathways, including Regulation of nuclear SMAD2/3 signaling. Well-known relevant genes, such as ACTN4, were characterized with widespread correlation disassociation with partners from a wide array of signaling pathways. Conclusions Altogether, our analysis reported a global expression correlation attenuation within and between key signaling pathways in chronic kidney disease, and presented a list of vanishing hub genes and disrupted correlations within and between key signaling pathways, illuminating on the pathophysiological mechanisms of CKD progression.