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Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer (NanoString)

ABSTRACT: We assess three major subtype classification schemas in the context of results from two clinical trials and by meta-analysis of publicly available expression data to assess statistical criteria of subtype robustness and overall clinical relevance. We then developed a Single Sample Classifier (SSC) using penalized logistic regression based on the most robust and replicable schema. We demonstrate that a tumor-intrinsic two subtype schema is most robust, replicable, and clinically relevant. We developed purity independent subtyping of tumors (PurIST), a SSC with robust and highly replicable performance on a wide range of platforms and sample types. We show that PurIST subtypes have meaningful associations with patient prognosis and have significant implications for treatment response to FOLIFIRNOX. Keywords: Expression profiling by array

ORGANISM(S): Homo sapiens

PROVIDER: GSE131051 | GEO | 2020/02/21

REPOSITORIES: GEO

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Purity Independent Subtyping of Tumors (PurIST), a clinically robust single-sample classifier for tumor subtyping in pancreatic cancer (RNA-Seq)

Project description:Purpose: Molecular subtyping for pancreatic cancer has made substantial progress in recent years, facilitating the optimization of existing therapeutic approaches to improve clinical outcomes in pancreatic cancer. With advances in treatment combinations and choices, it is becoming increasingly important to determine ways to place patients on the best therapies upfront. Although various molecular subtyping systems for pancreatic cancer have been proposed, consensus regarding proposed subtypes, as well as their relative clinical utility, remains largely unknown and presents a natural barrier to wider clinical adoption. Methods: We assess three major subtype classification schemas in the context of results from two clinical trials and by meta-analysis of publicly available expression data to assess statistical criteria of subtype robustness and overall clinical relevance. We then developed a single-sample classifier (SSC) using penalized logistic regression based on the most robust and replicable schema. Results: We demonstrate that a tumor-intrinsic two-subtype schema is most robust, replicable, and clinically relevant. We developed Purity Independent Subtyping of Tumors (PurIST), a SSC with robust and highly replicable performance on a wide range of platforms and sample types. We show that PurIST subtypes have meaningful associations with patient prognosis and have significant implications for treatment response to FOLIFIRNOX. Conclusions: The flexibility and utility of PurIST on low-input samples such as tumor biopsies allows it to be used at the time of diagnosis to facilitate the choice of effective therapies for patients with pancreatic ductal adenocarcinoma and should be considered in the context of future clinical trials.

2019-12-10 | GSE131050 | GEO

Purity Independent Subtyping of Tumors (PurIST), a clinically robust single-sample classifier for tumor subtyping in pancreatic cancer

Project description:Purity Independent Subtyping of Tumors (PurIST), a clinically robust single-sample classifier for tumor subtyping in pancreatic cancer

| PRJNA542386 | ENA

Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer

Project description:Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer

| PRJNA607898 | ENA

Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer (NanoString)

Project description:Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer (NanoString)

| PRJNA542387 | ENA

Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer (NanoString)

Project description:Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer (NanoString)

| PRJNA607901 | ENA

Purity Independent Subtyping of Tumors (PurIST), a clinically robust single-sample classifier for tumor subtyping in pancreatic cancer (RNA-Seq)

Project description:Purity Independent Subtyping of Tumors (PurIST), a clinically robust single-sample classifier for tumor subtyping in pancreatic cancer (RNA-Seq)

| PRJNA542388 | ENA

Purity Independent Subtyping of Tumors (PurIST), A Clinically Robust, Single-sample Classifier for Tumor Subtyping in Pancreatic Cancer.

Project description:PurposeMolecular subtyping for pancreatic cancer has made substantial progress in recent years, facilitating the optimization of existing therapeutic approaches to improve clinical outcomes in pancreatic cancer. With advances in treatment combinations and choices, it is becoming increasingly important to determine ways to place patients on the best therapies upfront. Although various molecular subtyping systems for pancreatic cancer have been proposed, consensus regarding proposed subtypes, as well as their relative clinical utility, remains largely unknown and presents a natural barrier to wider clinical adoption.Experimental designWe assess three major subtype classification schemas in the context of results from two clinical trials and by meta-analysis of publicly available expression data to assess statistical criteria of subtype robustness and overall clinical relevance. We then developed a single-sample classifier (SSC) using penalized logistic regression based on the most robust and replicable schema.ResultsWe demonstrate that a tumor-intrinsic two-subtype schema is most robust, replicable, and clinically relevant. We developed Purity Independent Subtyping of Tumors (PurIST), a SSC with robust and highly replicable performance on a wide range of platforms and sample types. We show that PurIST subtypes have meaningful associations with patient prognosis and have significant implications for treatment response to FOLIFIRNOX.ConclusionsThe flexibility and utility of PurIST on low-input samples such as tumor biopsies allows it to be used at the time of diagnosis to facilitate the choice of effective therapies for patients with pancreatic ductal adenocarcinoma and should be considered in the context of future clinical trials.

| S-EPMC6942634 | biostudies-literature

Cerebrospinal fluid cell-free DNA methylomes subtyping pediatric medulloblastoma

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Purity Independent Subtyping of Tumors (PurIST), a clinically robust single sample classifier for tumor subtyping in pancreatic cancer

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-02-21 | GSE131049 | GEO

Spatially preserved multi-region transcriptomic subtyping and biomarkers of outcome with chemoimmunotherapy in extensive-stage small cell lung cancer [IMfirst_DSP cohort]

Project description:Transcriptomic subtyping holds promise for personalized therapy in extensive stage small cell lung cancer (ES-SCLC). In this study, we aimed to assess intratumoral transcriptomic subtype diversity and to identify biomarkers associated with long-term chemoimmunotherapy benefit in human ES-SCLC. Our work highlights that high intratumoral heterogeneity, lack of consistent association with outcome, and unclear subtype-specific target expression are major challenges for SCLC subtype-based precision oncology. Pre-existing IFNϒ-driven immunity and mitochondrial metabolism seem key correlates of long-term efficacy for chemoimmunotherapy in ES-SCLC.

2024-04-09 | GSE261348 | GEO

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