Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases.

Somatic mosaicism is defined as an occurrence of two or more populations of cells having genomic sequences differing at given loci in an individual who is derived from a single zygote. It is a characteristic of multicellular organisms that plays a crucial role in normal development and disease. To study the nature and extent of somatic mosaicism in autism spectrum disorder, bipolar disorder, focal cortical dysplasia, schizophrenia, and Tourette syndrome, a multi-institutional consortium called the Brain Somatic Mosaicism Network (BSMN) was formed through the National Institute of Mental Health (NIMH). In addition to genomic data of affected and neurotypical brains, the BSMN also developed and validated a best practices somatic single nucleotide variant calling workflow through the analysis of reference brain tissue. These resources, which include >400 terabytes of data from 1087 subjects, are now available to the research community via the NIMH Data Archive (NDA) and are described here.

Efficient reconstruction of cell lineage trees for cell ancestry and cancer.

Mosaic mutations can be used to track cell ancestries and reconstruct high-resolution lineage trees during cancer progression and during development, starting from the first cell divisions of the zygote. However, this approach requires sampling and analyzing the genomes of multiple cells, which can be redundant in lineage representation, limiting the scalability of the approach. We describe a strategy for cost- and time-efficient lineage reconstruction using clonal induced pluripotent stem cell lines from human skin fibroblasts. The approach leverages shallow sequencing coverage to assess the clonality of the lines, clusters redundant lines and sums their coverage to accurately discover mutations in the corresponding lineages. Only a fraction of lines needs to be sequenced to high coverage. We demonstrate the effectiveness of this approach for reconstructing lineage trees during development and in hematologic malignancies. We discuss and propose an optimal experimental design for reconstructing lineage trees.

Control-independent mosaic single nucleotide variant detection with DeepMosaic.

Mosaic variants (MVs) reflect mutagenic processes during embryonic development and environmental exposure, accumulate with aging and underlie diseases such as cancer and autism. The detection of noncancer MVs has been computationally challenging due to the sparse representation of nonclonally expanded MVs. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs and a convolutional neural network-based classification module for control-independent MV detection. DeepMosaic was trained on 180,000 simulated or experimentally assessed MVs, and was benchmarked on 619,740 simulated MVs and 530 independent biologically tested MVs from 16 genomes and 181 exomes. DeepMosaic achieved higher accuracy compared with existing methods on biological data, with a sensitivity of 0.78, specificity of 0.83 and positive predictive value of 0.96 on noncancer whole-genome sequencing data, as well as doubling the validation rate over previous best-practice methods on noncancer whole-exome sequencing data (0.43 versus 0.18). DeepMosaic represents an accurate MV classifier for noncancer samples that can be implemented as an alternative or complement to existing methods.

Comprehensive multi-omic profiling of somatic mutations in malformations of cortical development.

Malformations of cortical development (MCD) are neurological conditions involving focal disruptions of cortical architecture and cellular organization that arise during embryogenesis, largely from somatic mosaic mutations, and cause intractable epilepsy. Identifying the genetic causes of MCD has been a challenge, as mutations remain at low allelic fractions in brain tissue resected to treat condition-related epilepsy. Here we report a genetic landscape from 283 brain resections, identifying 69 mutated genes through intensive profiling of somatic mutations, combining whole-exome and targeted-amplicon sequencing with functional validation including in utero electroporation of mice and single-nucleus RNA sequencing. Genotype-phenotype correlation analysis elucidated specific MCD gene sets associated with distinct pathophysiological and clinical phenotypes. The unique single-cell level spatiotemporal expression patterns of mutated genes in control and patient brains indicate critical roles in excitatory neurogenic pools during brain development and in promoting neuronal hyperexcitability after birth.

A noncoding single-nucleotide polymorphism at 8q24 drives IDH1-mutant glioma formation.

Establishing causal links between inherited polymorphisms and cancer risk is challenging. Here, we focus on the single-nucleotide polymorphism rs55705857, which confers a sixfold greater risk of isocitrate dehydrogenase (IDH)-mutant low-grade glioma (LGG). We reveal that rs55705857 itself is the causal variant and is associated with molecular pathways that drive LGG. Mechanistically, we show that rs55705857 resides within a brain-specific enhancer, where the risk allele disrupts OCT2/4 binding, allowing increased interaction with the Myc promoter and increased Myc expression. Mutating the orthologous mouse rs55705857 locus accelerated tumor development in an Idh1R132H-driven LGG mouse model from 472 to 172 days and increased penetrance from 30% to 75%. Our work reveals mechanisms of the heritable predisposition to lethal glioma in ~40% of LGG patients.

Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Comprehensive identification of somatic nucleotide variants in human brain tissue.

BACKGROUND: Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. RESULTS: Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. CONCLUSIONS: This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

SCELLECTOR: ranking amplification bias in single cells using shallow sequencing.

BACKGROUND: The study of mosaic mutation is important since it has been linked to cancer and various disorders. Single cell sequencing has become a powerful tool to study the genome of individual cells for the detection of mosaic mutations. The amount of DNA in a single cell needs to be amplified before sequencing and multiple displacement amplification (MDA) is widely used owing to its low error rate and long fragment length of amplified DNA. However, the phi29 polymerase used in MDA is sensitive to template fragmentation and presence of sites with DNA damage that can lead to biases such as allelic imbalance, uneven coverage and over representation of C to T mutations. It is therefore important to select cells with uniform amplification to decrease false positives and increase sensitivity for mosaic mutation detection. RESULTS: We propose a method, Scellector (single cell selector), which uses haplotype information to detect amplification quality in shallow coverage sequencing data. We tested Scellector on single human neuronal cells, obtained in vitro and amplified by MDA. Qualities were estimated from shallow sequencing with coverage as low as 0.3× per cell and then confirmed using 30× deep coverage sequencing. The high concordance between shallow and high coverage data validated the method. CONCLUSION: Scellector can potentially be used to rank amplifications obtained from single cell platforms relying on a MDA-like amplification step, such as Chromium Single Cell profiling solution.

Complex mosaic structural variations in human fetal brains.

Somatic mosaicism, manifesting as single nucleotide variants (SNVs), mobile element insertions, and structural changes in the DNA, is a common phenomenon in human brain cells, with potential functional consequences. Using a clonal approach, we previously detected 200-400 mosaic SNVs per cell in three human fetal brains (15-21 wk postconception). However, structural variation in the human fetal brain has not yet been investigated. Here, we discover and validate four mosaic structural variants (SVs) in the same brains and resolve their precise breakpoints. The SVs were of kilobase scale and complex, consisting of deletion(s) and rearranged genomic fragments, which sometimes originated from different chromosomes. Sequences at the breakpoints of these rearrangements had microhomologies, suggesting their origin from replication errors. One SV was found in two clones, and we timed its origin to ∼14 wk postconception. No large scale mosaic copy number variants (CNVs) were detectable in normal fetal human brains, suggesting that previously reported megabase-scale CNVs in neurons arise at later stages of development. By reanalysis of public single nuclei data from adult brain neurons, we detected an extrachromosomal circular DNA event. Our study reveals the existence of mosaic SVs in the developing human brain, likely arising from cell proliferation during mid-neurogenesis. Although relatively rare compared to SNVs and present in ∼10% of neurons, SVs in developing human brain affect a comparable number of bases in the genome (∼6200 vs. ∼4000 bp), implying that they may have similar functional consequences.

Adult diffuse glioma GWAS by molecular subtype identifies variants in D2HGDH and FAM20C.

BACKGROUND: Twenty-five germline variants are associated with adult diffuse glioma, and some of these variants have been shown to be associated with particular subtypes of glioma. We hypothesized that additional germline variants could be identified if a genome-wide association study (GWAS) were performed by molecular subtype. METHODS: A total of 1320 glioma cases and 1889 controls were used in the discovery set and 799 glioma cases and 808 controls in the validation set. Glioma cases were classified into molecular subtypes based on combinations of isocitrate dehydrogenase (IDH) mutation, telomerase reverse transcriptase (TERT) promoter mutation, and 1p/19q codeletion. Logistic regression was applied to the discovery and validation sets to test for associations of variants with each of the subtypes. A meta-analysis was subsequently performed using a genome-wide P-value threshold of 5 × 10-8. RESULTS: Nine variants in or near D-2-hydroxyglutarate dehydrogenase (D2HGDH) on chromosome 2 were genome-wide significant in IDH-mutated glioma (most significant was rs5839764, meta P = 2.82 × 10-10). Further stratifying by 1p/19q codeletion status, one variant in D2HGDH was genome-wide significant in IDH-mutated non-codeleted glioma (rs1106639, meta P = 4.96 × 10-8). Further stratifying by TERT mutation, one variant near FAM20C (family with sequence similarity 20, member C) on chromosome 7 was genome-wide significant in gliomas that have IDH mutation, TERT mutation, and 1p/19q codeletion (rs111976262, meta P = 9.56 × 10-9). Thirty-six variants in or near GMEB2 on chromosome 20 near regulator of telomere elongation helicase 1 (RTEL1) were genome-wide significant in IDH wild-type glioma (most significant was rs4809313, meta P = 2.60 × 10-10). CONCLUSIONS: Performing a GWAS by molecular subtype identified 2 new regions and a candidate independent region near RTEL1, which were associated with specific glioma molecular subtypes.

Combining copy number, methylation markers, and mutations as a panel for endometrial cancer detection via intravaginal tampon collection.

OBJECTIVE: We aimed to assess whether endometrial cancer (EC) can be detected in shed DNA collected with vaginal tampon by analyzing copy number, methylation markers, and mutations. METHODS: Tampons were collected prior to hysterectomy from 38 EC patients and 28 women with benign indications. Extracted tampon DNA underwent the following: 1) low-coverage whole genome sequencing (LC-WGS) to assess copy number, 2) pyrosequencing to measure percent promotor methylation of HOXA9, RASSF1, and CDH13 and 3) next generation sequencing (NGS) to identify mutations in 19 genes associated with EC identified through The Cancer Genome Atlas. Sensitivity and specificity for each test and test combinations were calculated. RESULTS: Methylation analysis yielded the highest specificities but lowest sensitivities (37-40% sensitivity; 100% specificity for HOXA9, RASSF1 and HTR1B) while mutation analysis had improved sensitivity (50% sensitivity; 83% specificity). Only one "false positive" result for copy number variants was identified among women with benign surgical indications, which was based on detection of copy number changes, and associated with a leiomyosarcoma that was only recognized at hysterectomy. Considering any of the 3 biomarker classes as a positive, resulted in a sensitivity of 92% and specificity of 86%. Mutation analysis did not add sensitivity to the combination of analysis of copy number and methylation. CONCLUSIONS: This study demonstrates a proof-of-principle for non-invasive yet precise detection of endometrial cancer. We propose that with improved biomarker testing, it may be possible to develop a clinically useful test for detecting EC.

Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2.

HepG2 is one of the most widely used human cancer cell lines in biomedical research and one of the main cell lines of ENCODE. Although the functional genomic and epigenomic characteristics of HepG2 are extensively studied, its genome sequence has never been comprehensively analyzed and higher order genomic structural features are largely unknown. The high degree of aneuploidy in HepG2 renders traditional genome variant analysis methods challenging and partially ineffective. Correct and complete interpretation of the extensive functional genomics data from HepG2 requires an understanding of the cell line's genome sequence and genome structure. Using a variety of sequencing and analysis methods, we identified a wide spectrum of genome characteristics in HepG2: copy numbers of chromosomal segments at high resolution, SNVs and Indels (corrected for aneuploidy), regions with loss of heterozygosity, phased haplotypes extending to entire chromosome arms, retrotransposon insertions and structural variants (SVs) including complex and somatic genomic rearrangements. A large number of SVs were phased, sequence assembled and experimentally validated. We re-analyzed published HepG2 datasets for allele-specific expression and DNA methylation and assembled an allele-specific CRISPR/Cas9 targeting map. We demonstrate how deeper insights into genomic regulatory complexity are gained by adopting a genome-integrated framework.

Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562.

K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and indels (both corrected for CN in aneuploid regions), loss of heterozygosity, megabase-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs), including small and large-scale complex SVs and nonreference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene FHIT Taking aneuploidy into account, we reanalyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.

Molecular signatures of multiple myeloma progression through single cell RNA-Seq.

We used single cell RNA-Seq to examine molecular heterogeneity in multiple myeloma (MM) in 597 CD138 positive cells from bone marrow aspirates of 15 patients at different stages of disease progression. 790 genes were selected by coefficient of variation (CV) method and organized cells into four groups (L1-L4) using unsupervised clustering. Plasma cells from each patient clustered into at least two groups based on gene expression signature. The L1 group contained cells from all MGUS patients having the lowest expression of genes involved in the oxidative phosphorylation, Myc targets, and mTORC1 signaling pathways (p < 1.2 × 10-14). In contrast, the expression level of these pathway genes increased progressively and were the highest in L4 group containing only cells from MM patients with t(4;14) translocations. A 44 genes signature of consistently overexpressed genes among the four groups was associated with poorer overall survival in MM patients (APEX trial, p < 0.0001; HR, 1.83; 95% CI, 1.33-2.52), particularly those treated with bortezomib (p < 0.0001; HR, 2.00; 95% CI, 1.39-2.89). Our study, using single cell RNA-Seq, identified the most significantly affected molecular pathways during MM progression and provided a novel signature predictive of patient prognosis and treatment stratification.

Molecular characterization of colorectal adenomas with and without malignancy reveals distinguishing genome, transcriptome and methylome alterations.

The majority of colorectal cancer (CRC) arises from precursor lesions known as polyps. The molecular determinants that distinguish benign from malignant polyps remain unclear. To molecularly characterize polyps, we utilized Cancer Adjacent Polyp (CAP) and Cancer Free Polyp (CFP) patients. CAPs had tissues from the residual polyp of origin and contiguous cancer; CFPs had polyp tissues matched to CAPs based on polyp size, histology and dysplasia. To determine whether molecular features distinguish CAPs and CFPs, we conducted Whole Genome Sequencing, RNA-seq, and RRBS on over 90 tissues from 31 patients. CAPs had significantly more mutations, altered expression and hypermethylation compared to CFPs. APC was significantly mutated in both polyp groups, but mutations in TP53, FBXW7, PIK3CA, KIAA1804 and SMAD2 were exclusive to CAPs. We found significant expression changes between CAPs and CFPs in GREM1, IGF2, CTGF, and PLAU, and both expression and methylation alterations in FES and HES1. Integrative analyses revealed 124 genes with alterations in at least two platforms, and ERBB3 and E2F8 showed aberrations specific to CAPs across all platforms. These findings provide a resource of molecular distinctions between polyps with and without cancer, which have the potential to enhance the diagnosis, risk assessment and management of polyps.

Inferring modes of evolution from colorectal cancer with residual polyp of origin.

Besides the classical evolutionary model of colorectal cancer (CRC) defined by the stepwise accumulation of mutations in which normal epithelium transforms through an intermediary polyp stage to cancer, a few studies have proposed alternative modes of evolution (MOE): early eruptive subclonal expansion, branching of the subclones in parallel evolution, and neutral evolution. However, frequencies of MOEs and their connection to mutational characteristics of cancer remain elusive. In this study, we analyzed patterns of somatic single nucleotide variations (SNVs) and copy number aberrations (CNAs) in CRC with residual polyp of origin from 13 patients in order to determine this relationship. For each MOE we defined an expected pattern with characteristic features of allele frequency distributions for SNVs in cancers and their matching adenomas. From these distinct patterns, we then assigned an MOE to each CRC case and found that stepwise progression was the most common (70% of cases). We found that CRC with the same MOE may exhibit different mutational spectra, suggesting that different mutational mechanisms can result in the same MOE. Inversely, cancers with different MOEs can have the same mutational spectrum, suggesting that the same mutational mechanism can lead to different MOEs. The types of somatic substitutions, distribution of CNAs across genome, and mutated pathways did not correlate with MOEs. As this could be due to small sample size, these relations warrant further investigation. Our study paves the way to connect MOE with clinical and mutational characteristics not only in CRC but also to neoplastic transformation in other cancers.

Different mutational rates and mechanisms in human cells at pregastrulation and neurogenesis.

Somatic mosaicism in the human brain may alter function of individual neurons. We analyzed genomes of single cells from the forebrains of three human fetuses (15 to 21 weeks postconception) using clonal cell populations. We detected 200 to 400 single-nucleotide variations (SNVs) per cell. SNV patterns resembled those found in cancer cell genomes, indicating a role of background mutagenesis in cancer. SNVs with a frequency of >2% in brain were also present in the spleen, revealing a pregastrulation origin. We reconstructed cell lineages for the first five postzygotic cleavages and calculated a mutation rate of ~1.3 mutations per division per cell. Later in development, during neurogenesis, the mutation spectrum shifted toward oxidative damage, and the mutation rate increased. Both neurogenesis and early embryogenesis exhibit substantially more mutagenesis than adulthood.

Patient-reported (EORTC QLQ-CIPN20) versus physician-reported (CTCAE) quantification of oxaliplatin- and paclitaxel/carboplatin-induced peripheral neuropathy in NCCTG/Alliance clinical trials.

PURPOSE: Clinical practice guidelines on chemotherapy-induced peripheral neuropathy (CIPN) use the NCI Common Terminology Criteria for Adverse Events (CTCAE), while recent clinical trials employ a potentially superior measure, the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-CIPN twenty-item scale (QLQ-CIPN20), a patient-reported outcome (PRO). Practitioners and researchers lack guidance, regarding how QLQ-CIPN20 results relate to the traditional CTCAE during the serial assessment of patients undergoing chemotherapy. METHODS: Two large CIPN clinical trial datasets (538 patients) pairing QLQ-CIPN20 and CTCAE outcomes were analyzed using a multivariable linear mixed model with QLQ-CIPN20 score as the outcome variable, CTCAE grade as the main effect, and patient as random effect (accounting for internal correlation of serial measures). RESULTS: The association between QLQ-CIPN20 scores and CTCAE grades was strong (p < 0.0001), whereby patients with higher CTCAE grade had worse QLQ-CIPN20 scores. Some variation of QLQ-CIPN20 scores was observed based on drug, treatment, and cycle. While there was a marked difference in the mean QLQ-CIPN20 scores between CTCAE grades, the ranges of QLQ-CIPN20 scores within each CTCAE grade were large, leading to large overlap in CIPN20 scores across CTCAE grades. CONCLUSIONS: A strong positive association of QLQ-CIPN20 scores and CTCAE grade provides evidence of convergent validity as well as practical guidance, as to how to quantitatively interpret QLQ-CIPN20 scores at the study level in terms of the traditional CTCAE. The present results also highlight an important clinical caveat, specifically, that conversion of a specific QLQ-CIPN20 score to a specific CTCAE score may not be reliable at the level of an individual patient.

One thousand somatic SNVs per skin fibroblast cell set baseline of mosaic mutational load with patterns that suggest proliferative origin.

Few studies have been conducted to understand post-zygotic accumulation of mutations in cells of the healthy human body. We reprogrammed 32 skin fibroblast cells from families of donors into human induced pluripotent stem cell (hiPSC) lines. The clonal nature of hiPSC lines allows a high-resolution analysis of the genomes of the founder fibroblast cells without being confounded by the artifacts of single-cell whole-genome amplification. We estimate that on average a fibroblast cell in children has 1035 mostly benign mosaic SNVs. On average, 235 SNVs could be directly confirmed in the original fibroblast population by ultradeep sequencing, down to an allele frequency (AF) of 0.1%. More sensitive droplet digital PCR experiments confirmed more SNVs as mosaic with AF as low as 0.01%, suggesting that 1035 mosaic SNVs per fibroblast cell is the true average. Similar analyses in adults revealed no significant increase in the number of SNVs per cell, suggesting that a major fraction of mosaic SNVs in fibroblasts arises during development. Mosaic SNVs were distributed uniformly across the genome and were enriched in a mutational signature previously observed in cancers and in de novo variants and which, we hypothesize, is a hallmark of normal cell proliferation. Finally, AF distribution of mosaic SNVs had distinct narrow peaks, which could be a characteristic of clonal cell selection, clonal expansion, or both. These findings reveal a large degree of somatic mosaicism in healthy human tissues, link de novo and cancer mutations to somatic mosaicism, and couple somatic mosaicism with cell proliferation.

Colorectal Cancer with Residual Polyp of Origin: A Model of Malignant Transformation.

The majority of colorectal cancers (CRCs) arise from adenomatous polyps. In this study, we sought to present the underrecognized CRC with the residual polyp of origin (CRC RPO+) as an entity to be utilized as a model to study colorectal carcinogenesis. We identified all subjects with biopsy-proven CRC RPO+ that were evaluated over 10 years at Mayo Clinic, Rochester, MN, and compared their clinical and pathologic characteristics to CRC without remnant polyps (CRC RPO-). Overall survival and disease-free survival overlap with an equivalent hazard ratio between CRC RPO+ and RPO- cases when age, stage, and grade are adjusted. The somatic genomic profile obtained by whole genome sequencing and the gene expression profiles by RNA-seq for CRC RPO+ tumors were compared with that of age -and gender-matched CRC RPO- evaluated by The Cancer Genome Atlas. CRC RPO+ cases were more commonly found with lower-grade, earlier-stage disease than CRC RPO-. However, within the same disease stage and grade, their clinical course is very similar to that of CRC RPO-. The mutation frequencies of commonly mutated genes in CRC are similar between CRC RPO+ and RPO- cases. Likewise, gene expression patterns are indistinguishable between the RPO+ and RPO- cases. We have confirmed that CRC RPO+ is clinically and biologically similar to CRC RPO- and may be utilized as a model of the adenoma to carcinoma transition.