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RNA sequencing reveals PNN as a predictive biomarker of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

ABSTRACT: RNA sequencing reveals PNN as a predictive biomarker of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

PROVIDER: PRJNA504394 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR8169670.fastq.gz	Fastqsanger.gz
	SRR8169680.fastq.gz	Fastqsanger.gz
	SRR8169661.fastq.gz	Fastqsanger.gz
	SRR8169671.fastq.gz	Fastqsanger.gz
	SRR8169681.fastq.gz	Fastqsanger.gz

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RNA sequencing reveals PNN as a predictive biomarker of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy

Project description:Five-year overall survival of stage III colorectal cancer (CRC) patients treated with standard adjuvant chemotherapy (ACHT) is highly variable. Genomic biomarkers and/or transcriptomic profiles identified lack of adequate validation. Aim of our study was to identify and validate molecular biomarkers predictive of ACHT response in stage III CRC patients by a transcriptomic approach. From a series of CRC patients who received ACHT, two stage III extreme cohorts (unfavorable vs. favorable prognosis) were selected. RNA sequencing was performed from fresh frozen explants. Tumors were characterized for somatic mutations. Validation was performed in stage III CRC patients extracted from two GEO datasets. According to disease free survival (DFS), 108 differentially expressed genes (104/4 up/downregulated in the unfavorable prognosis group) were identified. Among 104 upregulated genes, 42 belonged to olfactory signaling pathways, 62 were classified as pseudogenes (n = 17), uncharacterized noncoding RNA (n = 10), immune response genes (n = 4), microRNA (n = 1), cancer-related genes (n = 14) and cancer-unrelated genes (n = 16). Three out of four down-regulated genes were cancer-related. Mutational status (i.e., RAS, BRAF, PIK3CA) did not differ among the cohorts. In the validation cohort, multivariate analysis showed high PNN and KCNQ1OT1 expression predictive of shorter DFS in ACHT treated patients (p = 0.018 and p = 0.014, respectively); no difference was observed in untreated patients. This is the first study that identifies by a transcriptomic approach and validates PNN and KCNQ1OT1 as molecular biomarkers predictive of chemotherapy response in stage III CRC patients. After a further validation in an independent cohort, PNN and KCNQ1OT1 evaluation could be proposed to prospectively identify stage III CRC patients benefiting from ACHT.

2020-05-03 | GSE122246 | GEO

CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients

Project description:CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients

2021-06-01 | GSE154540 | GEO

Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes

Project description:This SuperSeries is composed of the following subset Series: GSE35711: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [CF_S1S3_5Auto_20CF_10HC] GSE35712: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [H1N1_S5_5Pre_5D0] GSE35716: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [Pneu_S3S24_10Pneu_4HC] GSE35725: Transcriptional Signatures as a Disease-Specific and Predictive Inflammatory Biomarker for Type 1 Diabetes [T1D_114] Refer to individual Series

2012-09-01 | E-GEOD-35713 | biostudies-arrayexpress

Prognostic and Predictive Gene Signature for Adjuvant Chemotherapy in Resected Non-Small Cell Lung Cancer

Project description:Background: The JBR.10 trial demonstrated significant survival benefit from adjuvant cisplatin/vinorelbine (ACT) in stage IB-II NSCLC (HR 0.69, p=0.04), but stage IB patients did not derive significant benefit (HR: 0.94, p= 0.79). We hypothesized that expression profiling could identify stage-independent subgroups of patients who might benefit from adjuvant chemotherapy. Methods: Gene expression profiling was conducted on mRNA isolated from frozen JBR.10 tumor samples (either from patients under observation [OBS], or treated with ACT). The minimum gene set that selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified and this gene signature was used to classify patients into high and low risk for death after surgery, and predict ACT effect. The prognostic gene signature was additionally tested on ACT patients and publicly available microarray datasets. Results: A 15-gene signature separated OBS patients into equal high and low risk subgroups with significantly different prognoses (HR 15.02, 95% CI 5.12-44.04, p=0.0001). The signature was prognostic in both stage IB and II. It was also predictive of improved survival following ACT treatment in high-risk patients (HR 0.33, 95% CI 0.17-0.63, p=0.0005), but not in low risk patients (HR 3.67, 95% CI 1.22-11.06, p=0.0133; interaction p=0.0001). The prognostic effect of the signature was validated in two independent gene expression datasets of 169 stage I-II adenocarcinoma and 106 squamous cell carcinoma patients. Conclusions: This microarray-based 15-gene prognostic expression signature is stage and histology independent and may select early stage NSCLC patients who are most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine. Keywords: Expression profiling by microarray; prognosis prediction 90 samples

2010-09-09 | E-GEOD-14814 | biostudies-arrayexpress

Prognostic and Predictive Gene Signature for Adjuvant Chemotherapy in Resected Non-Small-Cell Lung Cancer

Project description:Purpose: The JBR.10 trial demonstrated benefit from adjuvant cisplatin/vinorelbine (ACT) in early-stage non-small-cell lung cancer (NSCLC). We hypothesized that expression profiling may identify stage-independent subgroups who might benefit from ACT. Patients and Methods: Gene expression profiling was conducted on mRNA from 133 frozen JBR.10 tumor samples (62 observation [OBS], 71 ACT). The minimum gene set that was selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified. The prognostic value of this gene signature was tested in four independent published microarray data sets and by quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR). Results: A 15-gene signature separated OBS patients into high-risk and low-risk subgroups with significantly different survival (hazard ratio [HR], 15.02; 95% CI, 5.12 to 44.04; P .001; stage I HR, 13.31; P .001; stage II HR, 13.47; P .001). The prognostic effect was verified in the same 62 OBS patients where gene expression was assessed by qPCR. Furthermore, it was validated consistently in four separate microarray data sets (total 356 stage IB to II patients without adjuvant treatment) and additional JBR.10 OBS patients by qPCR (n 19). The signature was also predictive of improved survival after ACT in JBR.10 high-risk patients (HR, 0.33; 95% CI, 0.17 to 0.63; P .0005), but not in low-risk patients (HR, 3.67; 95% CI, 1.22 to 11.06; P = .0133; interaction P .001). Significant interaction between risk groups and ACT was verified by qPCR. Conclusion: This 15-gene expression signature is an independent prognostic marker in early-stage, completely resected NSCLC, and to our knowledge, is the first signature that has demonstrated the potential to select patients with stage IB to II NSCLC most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine.

2010-09-09 | GSE14814 | GEO

CDK4 overexpression is a predictive biomarker for resistance to conventional chemotherapy in osteosarcoma patients

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CircRNA as Predictive Biomarker of Penumbra in Acute Ischemic Stroke

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CXCL13 is a predictive biomarker in idiopathic multicentric Castleman disease

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Benefit of adjuvant chemotherapy on recurrence free survival per consensus molecular subtype in stage III colon cancer

Project description:In this study, we evaluated the added value of CMS in predicting both prognosis and benefit of adjuvant chemotherapy in stage III CC patients.

2024-07-10 | GSE250057 | GEO

Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome

Project description:<h4><strong>INTRODUCTION: </strong>Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to new patients.</h4><h4><strong>OBJECTIVES: </strong>In this study, we accurately quantitate a subset of compounds in patient serum that were found predictive of severity and outcome.</h4><h4><strong>METHODS: </strong>A targeted LC-MS method was used in 46 control and 95 acute COVID-19 patient samples to quantitate the selected metabolites. These compounds included tryptophan and its degradation products kynurenine and kynurenic acid (reflective of immune response), butyrylcarnitine and its isomer (reflective of energy metabolism) and finally 3’,4’-didehydro-3’-deoxycytidine, a deoxycytidine analogue, (reflective of host viral defence response). We subsequently examine changes in those markers by disease severity and outcome relative to those of control patients’ levels.</h4><h4><strong>RESULTS & CONCLUSION: </strong>Finally, we demonstrate the added value of the kynurenic acid / tryptophan ratio for severity and outcome prediction and highlight the viral detection potential of ddhC.</h4>

2024-04-23 | MTBLS7429 | MetaboLights

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