A role for SETD2 loss in tumorigenesis through DNA methylation dysregulation

SETD2-dependent H3 Lysine-36 trimethylation (H3K36me3) has been recently linked to the deposition of de-novo DNA methylation. SETD2 is frequently mutated in cancer, however, the functional impact of SETD2 loss and depletion on DNA methylation across cancer types and tumorigenesis is currently unknown. Here, we perform a pan-cancer analysis and show that both SETD2 mutation and reduced expression are associated with DNA methylation dysregulation across 21 out of the 24 cancer types tested. In renal cancer, these DNA methylation changes are associated with altered gene expression of oncogenes, tumour suppressors, and genes involved in neoplasm invasiveness, including TP53, FOXO1, and CDK4. This suggests a new role for SETD2 loss in tumorigenesis and cancer aggressiveness through DNA methylation dysregulation. Moreover, using a robust machine learning methodology, we develop and validate a 3-CpG methylation signature which is sufficient to predict SETD2 mutation status with high accuracy and correlates with patient prognosis.</p

Profile of genetic mutations and aberrant methylation.

<p>(A) Mutation status of RAS pathway genes and secondary genes (<i>SETBP1</i> and <i>JAK3</i>) identified as gene targets. Aberrant methylation scores (AMS) in a cohort of 92 patients with juvenile myelomonocytic leukemia are summarized. A rhombus denotes a patient with Noonan syndrome-associated myeloproliferative disorder. (B) Mutations in <i>SETBP1</i> and <i>JAK3</i> were associated with a higher AMS. The mean AMS of patients with <i>SETBP1</i> and/or <i>JAK3</i> mutations was higher than that of patients without secondary mutations (p = 0.03).</p

Summary of DNA methylation in candidate genes.

<p>(A) The dot plot represents the frequencies of methylated CpG sites for each candidate gene in the 92 patients with juvenile myelomonocytic leukemia. Aberrant hypermethylation was defined as >3 standard deviations above the mean methylation level of the healthy control population. The threshold values of each gene are shown as red broken lines. (B) Kaplan–Meier plots of the patient groups, defined by aberrant methylation of the indicated genes, are shown for <i>BMP4</i>, <i>CALCA</i>, <i>CDKN2A</i>, <i>CDKN2B</i>, <i>H19</i>, and <i>RARB</i>.</p

Patient characteristics.

<p>Patient characteristics.</p

Multivariate model for transplantation-free and overall survival.

<p>Multivariate model for transplantation-free and overall survival.</p

Hypermethylation status and clinical outcome in patients with juvenile myelomonocytic leukemia (JMML).

<p>(A) Kaplan–Meier curves represent the probability of transplantation-free survival (TFS) in the 92 patients with JMML. TFS was defined as the probability of being alive and transplantation free. Both death and transplantation were considered events. The probability of 5-year TFS in the aberrant methylation score (AMS) 0 cohort (solid line) was significantly higher than that in the AMS 1–2 (long dashed line) and AMS 3–4 cohorts (dashed line), p < 0.001. (B) Kaplan–Meier curves represent the probability of overall survival (OS) in the 92 patients with JMML. Death was considered an event. The probability of OS in both the AMS 0 (solid line) and 1–2 cohorts (long dashed line) was significantly higher than that in the AMS 3–4 cohort (dashed line), p < 0.001.</p

Detection of the G17V RHOA Mutation in Angioimmunoblastic T-Cell Lymphoma and Related Lymphomas Using Quantitative Allele-Specific PCR

<div><p>Angioimmunoblastic T-cell lymphoma (AITL) and peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) are subtypes of T-cell lymphoma. Due to low tumor cell content and substantial reactive cell infiltration, these lymphomas are sometimes mistaken for other types of lymphomas or even non-neoplastic diseases. In addition, a significant proportion of PTCL-NOS cases reportedly exhibit features of AITL (AITL-like PTCL-NOS). Thus disagreement is common in distinguishing between AITL and PTCL-NOS. Using whole-exome and subsequent targeted sequencing, we recently identified G17V <i>RHOA</i> mutations in 60–70% of AITL and AITL-like PTCL-NOS cases but not in other hematologic cancers, including other T-cell malignancies. Here, we establish a sensitive detection method for the G17V <i>RHOA</i> mutation using a quantitative allele-specific polymerase chain reaction (qAS-PCR) assay. Mutated allele frequencies deduced from this approach were highly correlated with those determined by deep sequencing. This method could serve as a novel diagnostic tool for 60–70% of AITL and AITL-like PTCL-NOS.</p></div

Correlation between qAS-PCR and MiSeq.

<p>*¹N, number; *²RCC, rank correlation coefficient; *³PPV, positive predictive value; *⁴NPV, negative predictive value, *⁵WGA, whole-genome amplification. *⁶FFPE, formalin-fixed/paraffin-embedded.</p><p>Correlation between qAS-PCR and MiSeq.</p

Analysis of genomic DNA samples.

<p>*¹amp, amplified; *²not-amp, not-amplified.</p><p>Analysis of genomic DNA samples.</p

Standard curve showing linearity of quantitative allele-specific PCR.

<p>A standard curve was generated by serial dilution of WT or G17V cDNA that had been subcloned into pBluescript. A. Serial dilution of pBS/mutRHOA. Black dots correspond to 1.0×10⁻⁹∼1.0 unit of mutant plasmid (duplicate samples). The titration slope is −3.550 and R² is 0.996. B. pBS/mutRHOA was mixed with pBS/wtRHOA at 100%, 10%, 1.0%, 0.1%, 0.01% and 0%. Mix concentrations were adjusted to 1.0 ng/well and diluted 1∶10 4 times for quantitative PCR analysis with allele-specific mutant primers. Horizonal axis indicates the amount of DNA per well. Vertical axis indicates unit for each sample. Black dot, MUT 100%; open dot, MUT 10%; square, MUT 1%; open square, MUT 0.1%; diamond, MUT 0.01%; triangle, MUT 0% (WT 100%) C. Serial dilution of pBS/wtRHOA. Black dots correspond to 1.0×10⁻⁶∼1.0 unit of WT cDNA (duplicate samples). The titration slope is −4.256, and R² is 0.998. D. pBS/wtRHOA was mixed with pBS/mutRHOA at 100%, 10%, 1.0%, 0.1%, 0.1% and 0%. Mix concentrations were adjusted to 1.0 ng/well and diluted 1∶10 4 times for quantitative PCR analysis with WT allele-specific primers. Black dot, WT 100%; open dot, WT 10%; square, WT 1%; open square, WT 0.1%; triangle, WT 0% (MUT 100%).</p