Integrative Bioinformatics Links HNF1B with Clear Cell Carcinoma and Tumor-Associated Thrombosis

<div><p>Clear cell carcinoma (CCC) is a histologically distinct carcinoma subtype that arises in several organ systems and is marked by cytoplasmic clearing, attributed to abundant intracellular glycogen. Previously, transcription factor hepatocyte nuclear factor 1-beta (HNF1B) was identified as a biomarker of ovarian CCC. Here, we set out to explore more broadly the relation between HNF1B and carcinomas with clear cell histology. HNF1B expression, evaluated by immunohistochemistry, was significantly associated with clear cell histology across diverse gynecologic and renal carcinomas (<i>P</i><0.001), as was hypomethylation of the <i>HNF1B</i> promoter (<i>P</i><0.001). From microarray analysis, an empirically-derived HNF1B signature was significantly enriched for computationally-predicted targets (with HNF1 binding sites) (<i>P</i><0.03), as well as genes associated with glycogen metabolism, including glucose-6-phophatase, and strikingly the blood clotting cascade, including fibrinogen, prothrombin and factor XIII. Enrichment of the clotting cascade was also evident in microarray data from ovarian CCC <i>versus</i> other histotypes (<i>P</i><0.01), and HNF1B-associated prothrombin expression was verified by immunohistochemistry (<i>P</i> = 0.015). Finally, among gynecologic carcinomas with cytoplasmic clearing, HNF1B immunostaining was linked to a 3.0-fold increased risk of clinically-significant venous thrombosis (<i>P</i> = 0.043), and with a 2.3-fold increased risk (<i>P</i> = 0.011) in a combined gynecologic and renal carcinoma cohort. Our results define HNF1B as a broad marker of clear cell phenotype, and support a mechanistic link to glycogen accumulation and thrombosis, possibly reflecting (for gynecologic CCC) derivation from secretory endometrium. Our findings also implicate a novel mechanism of tumor-associated thrombosis (a major cause of cancer mortality), based on the direct production of clotting factors by cancer cells.</p></div

Nuclear HNF1B expression is associated with cytoplasmic clearing across multiple tumor types.

<p>Representative H&E (10×objective, and magnified inset) and positive HNF1B immunostains are shown for (<b>A</b>) ovarian CCC, (<b>B</b>) renal CCC, and (<b>C</b>) mixed endometrioid/clear cell ovarian carcinoma. In the ovarian carcinoma with mixed histology (C), the upper row of panels depicts a region of the tumor with clear cell histology (HNF1B-positive); the middle row of panels (insets) depicts a different region of the same tumor with endometrioid histology and clear cell features (note papillary pattern, highlighted by green box) (also HNF1B-positive); and the bottom row (insets) depicts yet another region of the same tumor with endometrioid histology but without clear cell features (and with correspondingly weaker HNF1B-immunostaining). Note that this patient experienced a tumor-associated thromboembolic event (see main text). (<b>D</b>) Graphical display of proportion of HNF1B positive cases (shaded red) among different carcinoma types with or without cytoplasmic clearing. Gynecologic carcinomas include those from the endometrium, cervix and ovary. Other neoplasms represent diverse anatomic sites (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074562#pone.0074562.s001" target="_blank">Table S1</a>). <i>P</i>-values (two-sided Fisher’s exact test) for pairwise comparisons are indicated.</p

HNF1B-positive gynecologic malignancies are associated with cytoplasmic prothrombin expression, and increased clotting factor transcript levels.

<p>(<b>A</b>) Representative prothrombin immunostains (10×objective, and magnified inset) are shown for HNF1B-negative, prothrombin-negative mixed-histology endometrial carcinoma (<i>left</i>); and HNF1B-positive, prothrombin-positive (moderate cytoplasmic staining) mixed endometrioid/clear cell ovarian carcinoma (<i>right</i>; same case as depicted in Fig. 1C). (<b>B</b>) Q-RT-PCR analysis demonstrates increased clotting factor transcript levels in ovarian CCC (n = 6) compared to ovarian serous carcinoma (n = 7). Transcript levels are normalized to GAPDH, then set relative to a single serous carcinoma “reference” sample, and reported as log2 values. For graphs shown, undetected transcript levels (green diamonds) are arbitrarily set to smallest detectable levels. Red bars indicate average levels; <i>P</i>-values (non-parametric Mann-Whitney U-test) are shown.</p

HNF1B transcriptional targets and clotting cascade are enriched in ovarian CCC.

<p>(<b>A</b>) GSEA analysis shows enrichment of putative HNF1 targets (“leading edge” from Fig. 3) among genes selectively expressed in ovarian carcinoma with clear cell <i>vs</i>. other histotype <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074562#pone.0074562-Hendrix1" target="_blank">[25]</a>. (<b>B</b>) The leading edge enriched genes determined here (n = 25) are significantly over-represented among select functional gene sets (nominal <i>P</i> values<0.01); the top 10 gene sets are shown. Columns on the left depict relative log₂ gene expression levels (red/blue scale indicated) among normal ovary and ovarian carcinomas of different histotype. Columns on the right indicate membership (gray fill) among the top 10 most significant gene sets, which include liver-specific genes, and the clotting cascade (represented by five different gene sets). (<b>C</b>) Clotting factor genes (<i>FGA</i>, <i>FGB</i>, <i>F2</i>, and <i>F13B</i>) are more highly expressed in laser-microdissected ovarian CCC <i>vs</i>. normal ovarian surface epithelium (dataset from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074562#pone.0074562-Stany1" target="_blank">[26]</a>). Heatmap depicts all microarray probes for the respective genes; corresponding <i>P</i>-values (two-sided Student’s t-test) are indicated.</p

Tumor HNF1B expression is associated with venous thrombosis.

1<p>Two-sided Fisher’s exact test.</p

Breakpoint Analysis of Transcriptional and Genomic Profiles Uncovers Novel Gene Fusions Spanning Multiple Human Cancer Types

<div><p>Gene fusions, like <i>BCR/ABL1</i> in chronic myelogenous leukemia, have long been recognized in hematologic and mesenchymal malignancies. The recent finding of gene fusions in prostate and lung cancers has motivated the search for pathogenic gene fusions in other malignancies. Here, we developed a “breakpoint analysis” pipeline to discover candidate gene fusions by tell-tale transcript level or genomic DNA copy number transitions occurring within genes. Mining data from 974 diverse cancer samples, we identified 198 candidate fusions involving annotated cancer genes. From these, we validated and further characterized novel gene fusions involving <i>ROS1</i> tyrosine kinase in angiosarcoma (<i>CEP85L/ROS1</i>), <i>SLC1A2</i> glutamate transporter in colon cancer (<i>APIP/SLC1A2</i>), <i>RAF1</i> kinase in pancreatic cancer (<i>ATG7/RAF1</i>) and anaplastic astrocytoma (<i>BCL6/RAF1</i>), <i>EWSR1</i> in melanoma (<i>EWSR1/CREM</i>), <i>CDK6</i> kinase in T-cell acute lymphoblastic leukemia (<i>FAM133B/CDK6</i>), and <i>CLTC</i> in breast cancer (<i>CLTC/VMP1</i>). Notably, while these fusions involved known cancer genes, all occurred with novel fusion partners and in previously unreported cancer types. Moreover, several constituted druggable targets (including kinases), with therapeutic implications for their respective malignancies. Lastly, breakpoint analysis identified new cell line models for known rearrangements, including <i>EGFRvIII</i> and <i>FIP1L1/PDGFRA</i>. Taken together, we provide a robust approach for gene fusion discovery, and our results highlight a more widespread role of fusion genes in cancer pathogenesis.</p></div

Discovery and characterization of <i>EWSR1/CREM</i> in melanoma.

<p>(<i>A</i>) Array CGH heatmap displaying intragenic <i>EWSR1</i> breakpoints identified in the SH-4 and CHL-1 melanoma cell lines. (<i>B</i>) Paired-end RNA-seq identification of <i>EWSR1/CREM</i> in CHL-1. Paired-end reads supporting the rearrangement are depicted along with the predicted gene fusion structure. CREM contributes a basic leucine zipper motif (ZIP), while EWSR1 contributes the EWS Activation Domain (EAD). (<i>C</i>) RT-PCR verification of <i>EWSR1/CREM</i> in CHL-1. (<i>D</i>) Quantitative RT-PCR using primers flanking the gene fusion junction verifies <i>EWSR1/CREM</i> knockdown following transfection of an siRNA pool targeting the 3′ end of <i>CREM</i>. (<i>E</i>, <i>F</i>, <i>G</i>) Transfection of CHL-1 with <i>CREM</i>-targeting siRNA pool results in (<i>E</i>) decreased cell proliferation, (<i>F</i>) decreased invasion, and (<i>G</i>) a higher fraction of senescent cells, compared to non-targeting control (NTC). **<i>P</i><0.01 (two-sided Student's t-test).</p

Breakpoint analysis for discovering novel cancer gene rearrangements.

<p>Schematic depiction of the approach and workflow, demonstrated by example of the rediscovery of a known gene fusion, <i>SET/NUP214</i>, in the T-ALL cell line LOUCY. Various publicly-available and in-house exon microarray and high-density CGH/SNP array experiments were analyzed. RNA breakpoint analysis (RBA) identifies significant transitions in exon expression level, which may reflect elevated expression of exons distal (3′ partner) or proximal (5′ partner) to a gene fusion junction. To identify such transitions a “walking” Student's t-test was applied, comparing expression levels of proximal and distal exons. Candidate rearrangements were subsequently filtered for those disrupting genes of the Cancer Gene Census, with directional orientation (i.e. being the 5′ or 3′ partner) consistent with known rearrangements of that gene. RBA candidates were further filtered using a Bonferroni correction to adjust for multiple t-tests. DNA breakpoint analysis (DBA) screens for intragenic DNA copy number transitions, which may reflect unbalanced chromosomal rearrangements leading to the formation of gene fusions. The fused lasso method (FDR 1%) followed by a copy number smoothing algorithm was applied to identify CNAs. Copy number transitions were filtered for those disrupting any annotated gene and then further filtered for those disrupting genes of the Cancer Gene Census. We included only candidate breakpoints where the directional orientation of the copy number transition was consistent with known rearrangements of that gene. Several candidates were then validated using molecular and cytogenetic approaches. The average numbers of candidate rearrangements per cancer sample are depicted along the left and right panels at various stages of the workflow.</p

DBA discovery of recurrent rearrangements of <i>CLTC</i> and <i>VMP1</i> across diverse cancer types.

<p>(<i>A</i>) Heatmap depicting focal deletions between <i>CLTC</i> and <i>VMP1</i> in the breast cancer cell lines BT-549 and HCC1954. (<i>B</i>) Discovery of the recurrent <i>CLTC/VMP1</i> rearrangement in BT-549 (<i>left</i> panel) and HCC1954 (<i>right</i> panel) by paired-end RNA-seq. (<i>C</i>) RT-PCR verification of <i>CLTC/VMP1</i> fusion in BT-549 and HCC1954. (<i>D</i>) Heatmap depicting focal deletions disrupting <i>CLTC</i>, <i>PTRH2</i> and/or <i>VMP1</i> in various cancer types (see legend). (<i>E</i>) A renal cell carcinoma line, RXF393, was also profiled by exon microarray where an expression breakpoint was evident within <i>CLTC</i>. ***<i>P<10⁻⁹</i> (Student's t-test).</p

Validated gene fusions and rearrangements.

a<p>Gene fusions initially nominated by breakpoint analysis and subsequently validated by paired-end RNA-seq (or 5′ RACE for <i>CEP85L/ROS1</i>) and RT-PCR.</p>b<p><i>ABL1</i> and <i>EGFR</i> locus rearrangements were previously reported in the respective cell lines <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003464#pgen.1003464-Heisterkamp1" target="_blank">[96]</a>–<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003464#pgen.1003464-Hunts1" target="_blank">[98]</a>; however associated fusion transcripts were not identified.</p