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Plasma Level of Circular RNA hsa_circ_0000190 Correlates with Tumor Progression and Poor Treatment Response in Advanced Lung Cancers

ABSTRACT: Plasma Level of Circular RNA hsa_circ_0000190 Correlates with Tumor Progression and Poor Treatment Response in Advanced Lung Cancers

PROVIDER: PRJNA639355 | ENA |

REPOSITORIES: ENA

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Project description:Background: Inter-patient prostate cancer (PrCa) heterogeneity results in highly variable patient outcomes. Multi-purpose biomarkers to dissect this heterogeneity are urgently required to improve treatment and accelerate drug development in PrCa. Circulating biomarkers are most practical for evaluating this disease. We pursued the analytical validation and clinical qualification of blood mRNA expression arrays. Methods: Whole blood samples were collected into PaxGeneTM tubes from PrCa patients: 31 good prognosis patients selected for active surveillance (AS) and 63 advanced castration resistant PrCa (CRPC) patients. RNA was extracted, amplified, biotinylated, and hybridised to Affymetrix U133plus2 microarrays and analysis of genome-wide expression profiles were analysed using Bayesian Latent Process Decomposition (LPD). Findings: LPD analysis of the mRNA expression data divided the evaluable patients (n=94) into 4 separate groups. LPD1 and LPD2 consisted almost entirely of CRPC patients (14/14; 17/18); LPD3 (15/31) and LDP4 (12/21) comprised both AS and CRPC. Ten patients were unclassifiable by LPD analysis. LPD1 CRPC patients had significantly poorer overall survival (median 10.7 months, CI-95% 4.2-17.2) than CRPC patients in LPD2 to 4 (median 26.5 months, CI-95% 18.1-34.9, p=0.00007). LPD 1 membership remained the strongest prognostic factor in a multivariate analysis (HR 5.0, CI-95% 2.1-11.9, p=0.0002). Gene signatures in the poor prognosis LPD group 1 were associated with increased CD71+ early erythroid cells and decreased B-cell and T-cell immune response. A 9-gene signature, that was validated by RT-PCR studies, classified patients as group LPD 1 with a very low misclassification rate (1.2%). Interpretation: Poor PrCa outcome can be predicted using gene expression signatures from whole blood and merits further evaluation in predictive and pharmacodynamic biomarker studies for novel anticancer drugs including immune therapies. 107 blood samples were collected in paxgene tubes from 94 prostate cancer patients (31 good prognosis & 63 advanced castration resistant PrCa). Replicates include 9 biological replicates and four technical replicates

Project description:Purpose: We aimed to investigate the distinct transcriptional landscape in the poor responders to concurrent chemoradiotherapy (CCRT) and to gain mechanistic insights on treatment resistance in cervical cancer. Methods: RNA sequencing was performed using archived pre-treatment tissue biopsies of patients with locally advanced cervical cancer treated with concurrent platinum-based CCRT. Transcriptome data of patients with no durable benefit (NDB; progression-free period < 3 years) and durable clinical benefit (DCB; progression-free period > 5 years) after were compared. NDB score was estimated for each patient using the differentially expressed genes between NDB and DCB patients. Three independent cohorts, including The Cancer Genome Atlas cervical cancer (TCGA-CESC) cohort, were utilized for validation of NDB score. Potential response to PD-1 blockade was estimated with Tumor Immune Dysfunction and Exclusion (TIDE) score and T-cell-inflamed gene expression profile (GEP). Results: Patients with NDB exhibited a distinct transcriptional profile compared to those with DCB such as higher signatures of extracellular matrix organization and epithelial-to-mesenchymal transition. The fraction of cancer-associated fibroblasts (CAFs) within the tumor was significantly higher in NDB than DCB patients. Higher NDB score was significantly associated with poor survival in the TCGA-CESC cohort (n = 274; P = 0.015), but only in patients that received curative aim radiotherapy (P = 0.002) and not in patients who received other treatments (P = 0.57). The transcriptomic characteristics of patients with NDB were recapitulated in patients with high NDB score in TCGA-CESC. Patients with high NDB score displayed significantly higher TIDE prediction score and lower T-cell-inflamed GEP score compared to patients with low NDB scores. Conclusion: Cervical cancer patients with poor treatment outcome following CCRT exhibited a distinct gene signature that was able to predict treatment outcomes. For poor responders, immune checkpoint inhibitors may be less effective and CAF-targeting treatments may be a promising approach.

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Plasma Level of Circular RNA hsa_circ_0000190 Correlates with Tumor Progression and Poor Treatment Response in Advanced Lung Cancers

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