Transcriptome Profiling of Archived Sectioned Formalin-Fixed Paraffin-Embedded (AS-FFPE) Tissue for Disease Classification

Kojima, Kensuke; April, Craig; Canasto-Chibuque, Claudia; Chen, Xintong; Deshmukh, Manjeet; Venkatesh, Anu; Tan, Poh Seng; Kobayashi, Masahiro; Kumada, Hiromitsu; Fan, Jie; Hoshida, Yujin

doi:10.1371/journal.pone.0086961

Cited by 42 publications

(33 citation statements)

References 32 publications

(39 reference statements)

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“…33 Recent development of assay platforms, which are capable of inexpensively analyzing archived FFPE tissues with minimal experimental variation, is a breakthrough that will facilitate clinical implementation of gene signature tests. 34–36 …”

Section: Discussionmentioning

confidence: 99%

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration

King

Canasto-Chibuque

Johnson

et al. 2014

Gut

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Objective The number of patients with hepatitis C virus (HCV)-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression. Design We developed a prognostic index, comprised of a 186-gene signature validated in our previous genome-wide profiling study, bilirubin (>1mg/dL), and platelet count (<100,000/mm3), in an Italian HCV cirrhosis cohort (training cohort, n=216, median follow-up 10 years). The gene signature test was implemented utilizing a digital transcript counting (nCounter) assay specifically developed for clinical use, and the prognostic index was evaluated using archived specimens from an independent cohort of HCV-related cirrhosis in the U.S. (validation cohort, n=145, median follow-up 8 years). Results In the training cohort, the prognostic index was associated with hepatic decompensation (HR=2.71, p=0.003), overall death (HR=6.00, p<0.001), hepatocellular carcinoma (HR=3.31, p=0.001), and progression of Child-Turcotte-Pugh class (HR=6.70, p<0.001). The patients in the validation cohort were stratified into high (16%), intermediate (42%), or low (42%) risk group by the prognostic index. The high-risk group had a significantly increased risk of hepatic decompensation (HR=7.36, p<0.001), overall death (HR=3.57, p=0.002), liver-related death (HR=6.49, p<0.001), and all liver-related adverse events (HR=4.98, p<0.001). Conclusion A genomic and clinical prognostic index readily available for clinical use was successfully validated, warranting further clinical evaluation for prognostic prediction, and clinical trial stratification and enrichment for preventive interventions.

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Section: Discussionmentioning

confidence: 99%

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration

King

Canasto-Chibuque

Johnson

et al. 2014

Gut

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“…FFPE tissues for transcriptomic analysis [15]. The assay is highly reproducible, as demonstrated by the high concordance when comparing gene expression profiles of matched fresh frozen and FFPE tissues.…”

Section: O R I G I N a L A R T I C L Ementioning

confidence: 98%

Potential role of effector memory T cells in chronic T cell-mediated kidney graft rejection

Curci

Sallustio

Serino

et al. 2016

Nephrol. Dial. Transplant.

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Background. Chronic T cell-mediated rejection (TCMR) in kidney graft is characterized by reduction of the vessel lumen with marked intimal thickening, fibrous hyperplasia of the small renal arteries and leukocyte infiltrates. The aim of this study was to find specific gene expression profiles in chronic TCMR kidney biopsies. Methods. RNA extracted from archival formalin-fixed, paraffinembedded renal biopsies was used for gene expression profiling. Our study included 14 patients with chronic TCMR and 10 with acute TCMR. Fifty-two cadaveric donors were used as controls. The results were validated in an independent set of kidney biopsies. Results. We identified 616 and 243 differentially expressed genes with a fold change ≥1.5 and a false discovery rate <0.05 in chronic and acute TCMR, respectively. Pathway analysis revealed upregulation of OX40 signalling. This pathway is involved in the generation of CD8 + effector memory T cells and the upregulation of killer cell lectin-like receptor G1 (KLRG-1), B lymphocyte-induced maturation protein 1 (BLIMP-1) and CD25, which characterize CD8 + effector memory T cells.

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“…To overcome these challenges, here we aimed to develop and validate clinically readily available surrogates of HCC molecular classification based on robust clinicopathological information, which enables clinical trial enrichment for molecular targeted anti‐HCC drugs. Furthermore, we implemented and evaluated a gene signature‐based HCC molecular classification assay in an FDA‐approved diagnostic platform applicable to clinical archived formalin‐fixed, paraffin‐embedded (FFPE) tissues . The assay may be used to retrospectively corroborate the clinicopathological indices‐based subclass prediction whenever funding and/or access to the assay facility become available in a real‐world clinical setting.…”

mentioning

confidence: 99%

Clinicopathological indices to predict hepatocellular carcinoma molecular classification

Tan

Nakagawa

Goossens

et al. 2015

Liver International

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101

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Background & Aims Hepatocellular carcinoma (HCC) is the second most lethal cancer due to lack of effective therapies. Although promising, HCC molecular classification, which enriches potential responders to specific therapies, has not yet been assessed in clinical trials of anti-HCC drugs. We aimed to overcome these challenges by developing clinicopathological surrogate indices of HCC molecular classification. Methods HCC classification defined in our previous transcriptome meta-analysis (S1, S2, and S3 subclasses) was implemented in an FDA-approved diagnostic platform (Elements assay, NanoString). Ninety-six HCC tumors (training set) were assayed to develop molecular subclass-predictive indices based on clinicopathological features, which were independently validated in 99 HCC tumors (validation set). Molecular deregulations associated with the histopathological features were determined by pathway analysis. Sample sizes for HCC clinical trials enriched with specific molecular subclasses were determined. Results HCC subclass-predictive indices were: steatohepatitic (SH)-HCC variant and immune cell infiltrate for S1 subclass, macrotrabecular/compact pattern, lack of pseudoglandular pattern, and high serum alpha-fetoprotein (>400 ng/mL) for S2 subclass, and microtrabecular pattern, lack of SH-HCC and clear cell variants, and lower histological grade for S3 subclass. Macrotrabecular/compact pattern, a predictor of S2 subclass, was associated with activation of therapeutically targetable oncogene YAP and stemness markers EPCAM/KRT19. BMP4 was associated with pseudoglandular pattern. Subclass-predictive indices-based patient enrichment reduced clinical trial sample sizes from 121, 184, and 53 to 30, 43, and 22 for S1, S2, and S3 subclass-targeting therapies, respectively. Conclusions HCC molecular subclasses can be enriched by clinicopathological indices tightly associated with deregulation of therapeutically targetable molecular pathways.

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Transcriptome Profiling of Archived Sectioned Formalin-Fixed Paraffin-Embedded (AS-FFPE) Tissue for Disease Classification

Cited by 42 publications

References 32 publications

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration

Potential role of effector memory T cells in chronic T cell-mediated kidney graft rejection

Clinicopathological indices to predict hepatocellular carcinoma molecular classification

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