ITIH5 mediates epigenetic reprogramming of breast cancer cells

Extracellular matrix (ECM) is known to maintain epithelial integrity. In carcinogenesis ECM degradation triggers metastasis by controlling migration and differentiation including cancer stem cell (CSC) characteristics. The ECM-modulator inter- α-trypsin inhibitor heavy chain family member five (ITIH5) was recently identified as tumor suppressor potentially involved in impairing breast cancer progression but molecular mechanisms underlying its function are still elusive

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34–7.3; HR = 2.24 and 95% CI = 1.28–3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11–4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution

Conversations under a Tung Tree

<p>Secreted frizzled related protein 3 (SFRP3) contains a cysteine-rich domain (CRD) that shares homology with Frizzled CRD and regulates WNT signaling. Independent studies showed epigenetic silencing of <i>SFRP3</i> in melanoma and hepatocellular carcinoma. Moreover, a tumor suppressive function of SFRP3 was shown in androgen-independent prostate and gastric cancer cells. The current study is the first to investigate <i>SFRP3</i> expression and its potential clinical impact on non-small cell lung carcinoma (NSCLC). WNT signaling components present on NSCLC subtypes were preliminary elucidated by expression data of The Cancer Genome Atlas (TCGA). We identified a distinct expression signature of relevant WNT signaling components that differ between adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Of interest, canonical WNT signaling is predominant in LUAD samples and non-canonical WNT signaling is predominant in LUSC. In line, high SFRP3 expression resulted in beneficial clinical outcome for LUAD but not for LUSC patients. Furthermore, <i>SFRP3</i> mRNA expression was significantly decreased in NSCLC tissue compared to normal lung samples. TCGA data verified the reduction of <i>SFRP3</i> in LUAD and LUSC patients. Moreover, DNA hypermethylation of <i>SFRP3</i> was evaluated in the TCGA methylation dataset resulting in epigenetic inactivation of <i>SFRP3</i> expression in LUAD, but not in LUSC, and was validated by pyrosequencing of our NSCLC tissue cohort and <i>in vitro</i> demethylation experiments. Immunohistochemistry confirmed SFRP3 protein downregulation in primary NSCLC and indicated abundant expression in normal lung tissue. Two adenocarcinoma gain-of-function models were used to analyze the functional impact of SFRP3 on cell proliferation and regulation of <i>CyclinD1</i> expression <i>in vitro</i>. Our results indicate that <i>SFRP3</i> acts as a novel putative tumor suppressor gene in adenocarcinoma of the lung possibly regulating canonical WNT signaling.</p

03 - ATAC-seq differential peak analysis

   03-CNA_adjustment.pdf: Association between CNA and the observed ATAC-seq signals. (A) As expected, association between CNA and the coefficients of the negative-binomial regression with edgeR was found. Black line indicates CNA profile determined by WGS. (B) This relationship was generally explained by the expected effect of CNA under a given ploidy and purity. The black crosses show the average signal of sides with a given rounded CN and the black line the expected relationship. (C) A consistent variability of the signal at different CN states was observed.  03-significant_peaks.pdf: Identified SCAAs after adjustment for CNAs. A subset of highly recurrent SCAAs are labelled in the figure. Significantly differential SCAAs are show in red. 03-effect_of_CNA_adjustment.pdf: Number of significant SCAA before and after adjustment of the test for the expected effects of CNA alterations.</p

02 - SNVs

02-SNVs.pdf: Single nucleotide variant profiles. We called point mutations and Indels in each sample and identified clusters of mutations found at the same frequency in the same samples. Values in Cancer Cell Fraction (CCF) are represented.</p

04-RNA-seq

04-RNA_ATAC_assocation.pdf: Gene expression differences for all the recurrent peaks that correlated with gene expression.  04-eQTL.pdf: Some of the eQTL somatic variants from a related analysis (Househam, Heide et al.) were associated with changes in chromatin accessibility at the locus. Here we show the significant examples of this phenomenon for each patient, with the SNV phylogenetic tree (left) versus changes in chromatin accessibility (right).</p

01 - Inference Notes

Supplementary note of the EPICC ABC-SMC inference.</p

02 - Inference Result Booklet

Supplementary booklet with EPICC inference results.</p