A Low-cost Multiplex Biomarker Assay Stratifies Colorectal Cancer Patient Samples into Clinically-relevant Subtypes
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ABSTRACT:
PROVIDER: PRJNA395057 | ENA |
REPOSITORIES: ENA
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Project description:Objective: In order to personalize standard therapies based on molecular profiles, we previously classified colorectal cancers (CRCs) into five distinct subtypes (CRCAssigner) and later into four consensus molecular subtypes (CMS) with different prognoses and treatment responses. For clinical application, here we developed an inexpensive multiplex biomarker-based assay.Objective: In order to personalise standard therapies based on molecular profiles, we previously classified colorectal cancers (CRCs) into five distinct subtypes (CRCAssigner) and later into four consensus molecular subtypes (CMS) with different prognoses and treatment responses. For clinical application, here we developed a low-cost multiplex biomarker assay. Design: Three cohorts of untreated fresh frozen CRC samples (n = 57) predominantly from primary tumours and profiled by microarray/RNA-Seq were analysed. A reduced 38-gene panel (CRCAssigner-38) was selected from the published 786-gene CRCAssigner signature (CRCAssigner-786) using an in-house gene selection approach. A customised NanoString Technologies nCounter platform-based assay (NanoCRCAssigner) was developed for comparison with different classifiers (CMS subtypes), platforms (microarrays and RNA-Seq), and gene sets (CRCAssigner-38 and CRCAssigner-786). An additional cohort of fresh-frozen paraffin embedded (FFPE) samples (n = 24) was subtyped using NanoCRCAssigner as a proof-of-concept. Results: NanoCRCAssigner classified fresh frozen samples (n = 48; except those showing a mixture of subtypes) into all five CRCAssigner subtypes with overall high concordance across platforms (>87%) and with CMS subtypes (81%) irrespective of variable tumour cellularity. The association of subtypes with their known molecular (microsatellite-instable and stemness), mutational (KRAS/BRAF), and clinical characteristics (including overall survival) further demonstrated assay validity. To reduce costs, we switched from the standard protocol to a low-cost protocol with a high Pearson correlation co-efficient (0.9) between protocols. Technical replicates were highly correlated (0.98). FFPE samples were also successfully classified and showed high reproducibility (0.96).
2019-03-04 | GSE101481 | GEO
Project description:Objective: In order to personalise standard therapies based on molecular profiles, we previously classified colorectal cancers (CRCs) into five distinct subtypes (CRCAssigner) and later into four consensus molecular subtypes (CMS) with different prognoses and treatment responses. For clinical application, here we developed a low-cost multiplex biomarker assay. Design: Three cohorts of primary (except one liver metastases) untreated and fresh frozen CRC samples (n=57) profiled by microarray and RNA-Seq were analyzed. A reduced 38-gene panel (CRCAssigner-38) was selected from the 786-gene CRCAssigner signature (CRCAssigner-786) using an in-house class prediction approach. A customised NanoString Technologies’ nCounter platform-based assay (NanoCRCAssigner) was developed for comparison with different classifiers (CMS subtypes), platforms (microarrays and RNA-Seq), and gene sets (CRCAssigner-38 and CRCAssigner-786). Results: NanoCRCAssigner classified samples (n=48; except those showing a mixture of subtypes) into all five CRCAssigner subtypes with overall high concordance across platforms (>87%) and with CMS subtypes (81%) irrespective of variable tumour cellularity. The association of subtypes with their known molecular (microsatellite-instable and stemness), mutational (KRAS/BRAF), and clinical characteristics (including overall survival) further demonstrated assay validity. To reduce costs, we switched from standard protocol to a low-cost protocol with a high Pearson correlation co-efficient (0.9) between protocols. Technical replicates were highly correlated (0.98).
2019-03-04 | GSE101588 | GEO
Project description:Objective: In order to personalise standard therapies based on molecular profiles, we previously classified colorectal cancers (CRCs) into five distinct subtypes (CRCAssigner) and later into four consensus molecular subtypes (CMS) with different prognoses and treatment responses. For clinical application, here we developed a low-cost multiplex biomarker assay. Design: Three cohorts of primary (except one liver metastases) untreated and fresh frozen CRC samples (n=57) profiled by microarray and RNA-Seq were analyzed. A reduced 38-gene panel (CRCAssigner-38) was selected from the 786-gene CRCAssigner signature (CRCAssigner-786) using an in-house class prediction approach. A customised NanoString Technologies’ nCounter platform-based assay (NanoCRCAssigner) was developed for comparison with different classifiers (CMS subtypes), platforms (microarrays and RNA-Seq), and gene sets (CRCAssigner-38 and CRCAssigner-786). Results: NanoCRCAssigner classified samples (n=48; except those showing a mixture of subtypes) into all five CRCAssigner subtypes with overall high concordance across platforms (>87%) and with CMS subtypes (81%) irrespective of variable tumour cellularity. The association of subtypes with their known molecular (microsatellite-instable and stemness), mutational (KRAS/BRAF), and clinical characteristics (including overall survival) further demonstrated assay validity. To reduce costs, we switched from standard protocol to a low-cost protocol with a high Pearson correlation co-efficient (0.9) between protocols. Technical replicates were highly correlated (0.98).
2019-03-04 | GSE101472 | GEO
Project description:Objective: In order to personalize standard therapies based on molecular profiles, we previously classified colorectal cancers (CRCs) into five distinct subtypes (CRCAssigner) and later into four consensus molecular subtypes (CMS) with different prognoses and treatment responses. For clinical application, here we developed an inexpensive multiplex biomarker-based assay. Design: Three cohorts of untreated fresh frozen CRC samples (n = 57) predominantly from primary tumours and profiled by microarray/RNA-Seq were analysed. A reduced 38-gene panel (CRCAssigner-38) was selected from the published 786-gene CRCAssigner signature (CRCAssigner-786) using an in-house gene selection approach. A customised NanoString Technologies nCounter platform-based assay (NanoCRCAssigner) was developed for comparison with different classifiers (CMS subtypes), platforms (microarrays and RNA-Seq), and gene sets (CRCAssigner-38 and CRCAssigner-786). An additional cohort of fresh-frozen paraffin embedded (FFPE) samples (n = 24) was subtyped using NanoCRCAssigner as a proof-of-concept. Results: NanoCRCAssigner classified fresh frozen samples (n = 48; except those showing a mixture of subtypes) into all five CRCAssigner subtypes with overall high concordance across platforms (>87%) and with CMS subtypes (81%) irrespective of variable tumour cellularity. The association of subtypes with their known molecular (microsatellite-instable and stemness), mutational (KRAS/BRAF), and clinical characteristics (including overall survival) further demonstrated assay validity. To reduce costs, we switched from the standard protocol to a low-cost protocol with a high Pearson correlation co-efficient (0.9) between protocols. Technical replicates were highly correlated (0.98). FFPE samples were also successfully classified and showed high reproducibility (0.96).
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