Technical differences between sequencing and microarray platforms impact transcriptomic subtyping of colorectal cancer

Eilertsen, Ina A.; Moosavi, Seyed H.; Strømme, Jonas Meier; Nesbakken, Arild; Johannessen, Bjarne; Sveen, Anita

doi:10.1016/j.canlet.2019.10.040

Cited by 18 publications

(15 citation statements)

References 49 publications

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“…Sample preparation, including ribosomal RNA depletion using the Ribo-Zero Gold rRNA removal kit and sequence library generation with the TruSeq Stranded Total RNA Library Prep Gold kit (Illumina), was done at the Oslo University Hospital Genomics Core Facility. Bioinformatic processing of raw sequencing reads was done as previously described [ 24 ], including adapter trimming with Trimmomatic version 0.38, alignment to the human reference genome GRCh38 using STAR, read sorting by SAMtools, and quantification of reads mapping to protein-coding genes using the HTSeq-count tool (version 0.10.0). The median number of uniquely mapped trimmed RNA sequencing read pairs across the 126 primary tumor samples was 30.2 × 10 6 (10–90th percentile 24.7 × 10 6 –50.2 × 10 6 ).…”

Section: Methodsmentioning

confidence: 99%

The expressed mutational landscape of microsatellite stable colorectal cancers

et al. 2021

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Background Colorectal cancer is the 2nd leading cause of cancer-related deaths with few patients benefiting from biomarker-guided therapy. Mutation expression is essential for accurate interpretation of mutations as biomarkers, but surprisingly, little has been done to analyze somatic cancer mutations on the expression level. We report a large-scale analysis of allele-specific mutation expression. Methods Whole-exome and total RNA sequencing was performed on 137 samples from 121 microsatellite stable colorectal cancers, including multiregional samples of primary and metastatic tumors from 4 patients. Data were integrated with allele-specific resolution. Results were validated in an independent set of 241 colon cancers. Therapeutic associations were explored by pharmacogenomic profiling of 15 cell lines or patient-derived organoids. Results The median proportion of expressed mutations per tumor was 34%. Cancer-critical mutations had the highest expression frequency (gene-wise mean of 58%), independent of frequent allelic imbalance. Systematic deviation from the general pattern of expression levels according to allelic frequencies was detected, including preferential expression of mutated alleles dependent on the mutation type and target gene. Translational relevance was suggested by correlations of KRAS/NRAS or TP53 mutation expression levels with downstream oncogenic signatures (p < 0.03), overall survival among patients with stage II and III cancer (KRAS/NRAS: hazard ratio 6.1, p = 0.0070), and targeted drug sensitivity. The latter was demonstrated for EGFR and MDM2 inhibition in pre-clinical models. Conclusions Only a subset of mutations in microsatellite stable colorectal cancers were expressed, and the “expressed mutation dose” may provide an opportunity for more fine-tuned biomarker interpretations.

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Section: Methodsmentioning

confidence: 99%

The expressed mutational landscape of microsatellite stable colorectal cancers

et al. 2021

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“…Gene expression profiles from 477 patients treated surgically for their primary CRC and/or liver metastases at Oslo University Hospital, Norway, between 2009 and 2019 were analyzed (Table 1). The original sample set consisted of 298 metastatic samples, 24 patient-matched non-malignant liver samples, and 317 primary tumor samples (from 315 patients 25,35,36 ). Three metastasis samples with a low tumor cell content were discarded, based on an upper threshold for the "liver background" (described below) estimated in normal liver samples as reference (≤10th percentile).…”

Section: Gene Expression Datamentioning

confidence: 99%

Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer

et al. 2021

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Gene expression-based subtypes of colorectal cancer have clinical relevance, but the representativeness of primary tumors and the consensus molecular subtypes (CMS) for metastatic cancers is not well known. We investigated the metastatic heterogeneity of CMS. The best approach to subtype translation was delineated by comparisons of transcriptomic profiles from 317 primary tumors and 295 liver metastases, including multi-metastatic samples from 45 patients and 14 primary-metastasis sets. Associations were validated in an external data set (n = 618). Projection of metastases onto principal components of primary tumors showed that metastases were depleted of CMS1-immune/CMS3-metabolic signals, enriched for CMS4-mesenchymal/stromal signals, and heavily influenced by the microenvironment. The tailored CMS classifier (available in an updated version of the R package CMScaller) therefore implemented an approach to regress out the liver tissue background. The majority of classified metastases were either CMS2 or CMS4. Nonetheless, subtype switching and inter-metastatic CMS heterogeneity were frequent and increased with sampling intensity. Poor-prognostic value of CMS1/3 metastases was consistent in the context of intra-patient tumor heterogeneity.

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“…Raw RNA sequencing reads were processed in a bioinformatics pipeline implemented with Snakemake (v.6.6.1) and using Python (v.3.9.5), Java (v.11.0.2) and PyYAML (v.5.4.1). The pipeline has previously been described and included adapter trimming with Trimmomatic (v.0.38), read alignment to the human reference genome GRCh38.p13 (v.41) using STAR (v.2.7.6a) with 2-pass mapping and the feature annotation le gencode.v41.annotation.gtf, quanti cation of reads mapping to protein-coding genes using the HTseq-count tool (v.2.0.2), and normalization of gene expression levels by estimation of transcripts per million (TPM) for non-overlapping exonic gene lengths 45 . The TPM values were log2transformed after adding a pseudocount of 1.…”

Section: Gene Expression Pro Ling and Data Processingmentioning

confidence: 99%

Multiregional transcriptomics identifies congruent consensus molecular subtypes with prognostic value beyond tumor heterogeneity in colorectal cancer.

Sveen,

Langerud,

Eilertsen

et al. 2023

Preprint

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Intra-tumor heterogeneity compromises the clinical value of transcriptomic classifications of colorectal cancer. We investigated the prognostic effect of transcriptomic heterogeneity and the potential for a classification less vulnerable to heterogeneity in a single-hospital series of 1,093 primary and metastatic tumor samples from 692 patients, including 2–4 multiregional samples from 98 primary tumors and primary-metastasis sets from 35 patients. Intra-tumor heterogeneity of the consensus molecular subtypes (CMS) was frequent (40%) and associated with poor patient survival independently of tumor microenvironment markers. Multiregional transcriptomics uncovered cancer cell-intrinsic and low-heterogeneity signals that recapitulated the two intrinsic subtypes (iCMS2/iCMS3) proposed by single-cell sequencing. Further subclassification resulted in four congruent CMSs defining good-prognostic and poor-prognostic subtypes. Congruent CMS explained a larger proportion of variation in patient survival than intra-tumor CMS heterogeneity. Evidence of plasticity was found by discordant phenotypes of matched primary and metastatic tumors (28%), even according to the two-state intrinsic classification. In conclusion, multiregional sampling reconciled the prognostic power of tumor classifications from single-cell and bulk transcriptomics in the context of intra-tumor heterogeneity, and phenotypic plasticity challenges the reconciliation of primary and metastatic subtypes.

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Technical differences between sequencing and microarray platforms impact transcriptomic subtyping of colorectal cancer

Cited by 18 publications

References 49 publications

The expressed mutational landscape of microsatellite stable colorectal cancers

The expressed mutational landscape of microsatellite stable colorectal cancers

Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer

Multiregional transcriptomics identifies congruent consensus molecular subtypes with prognostic value beyond tumor heterogeneity in colorectal cancer.

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