Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images. METHODS AND FINDINGS: We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I-IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a "deep stroma score," which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27-3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I-IV CRC patients from the "Darmkrebs: Chancen der Verhütung durch Screening" (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14-2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5-3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34-2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows. CONCLUSIONS: In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images

The CD95 Receptor: Apoptosis Revisited

CD95 is the quintessential death receptor and, when it is bound by ligand, cells undergo apoptosis. Recent evidence suggests, however, that CD95 mediates not only apoptosis but also diverse nonapoptotic functions depending on the tissue and the conditions

Patterns of antibody responses to nonviral cancer antigens in head and neck squamous cell carcinoma patients differ by human papillomavirus status

There have been hints that nonviral cancer antigens are differentially expressed in human papillomavirus (HPV)-positive and HPV-negative head and neck squamous cell carcinoma (HNSCC). Antibody responses (AR) to cancer antigens may be used to indirectly determine cancer antigen expression in the tumor using a noninvasive and tissue-saving liquid biopsy. Here, we set out to characterize AR to a panel of nonviral cancer antigens in HPV-positive and HPV-negative HNSCC patients. A fluorescent microbead multiplex serology to 29 cancer antigens (16 cancer-testis antigens, 5 cancer-retina antigens and 8 oncogenes) and 29 HPV-antigens was performed in 382 HNSCC patients from five independent cohorts (153 HPV-positive and 209 HPV-negative). AR to any of the cancer antigens were found in 272/382 patients (72%). The ten most frequent AR were CT47, cTAGE5a, c-myc, LAGE-1, MAGE-A1, -A3, -A4, NY-ESO-1, SpanX-a1 and p53. AR to MAGE-A3, MAGE-A9 and p53 were found at significantly different prevalences by HPV status. An analysis of AR mean fluorescent intensity values uncovered remarkably different AR clusters by HPV status. To identify optimal antigen selections covering a maximum of patients with ≤10 AR, multiobjective optimization revealed distinct antigen selections by HPV status. We identified that AR to nonviral antigens differ by HPV status indicating differential antigen expression. Multiplex serology may be used to characterize antigen expression using serum or plasma as a tissue-sparing liquid biopsy. Cancer antigen panels should address the distinct antigen repertoire of HPV-positive and HPV-negative HNSCC

Lack of association between gene polymorphisms of Angiotensin converting enzyme, Nod-like receptor 1, Toll-like receptor 4, FAS/FASL and the presence of Helicobacter pylori-induced premalignant gastric lesions and gastric cancer in Caucasians

<p>Abstract</p> <p>Background</p> <p>Several polymorphisms of genes involved in the immunological recognition of <it>Helicobacter pylori </it>and regulating apoptosis and proliferation have been linked to gastric carcinogenesis, however reported data are partially conflicting. The aim of our study was to evaluate potential associations between the presence of gastric cancer (GC) and high risk atrophic gastritis (HRAG) and polymorphisms of genes encoding <it>Angiotensin converting enzyme </it>(<it>ACE</it>), <it>Nod-like receptor 1 </it>(<it>NOD1</it>), <it>Toll-like receptor 4 </it>(<it>TLR4</it>) and <it>FAS/FASL</it>.</p> <p>Methods</p> <p>Gene polymorphisms were analyzed in 574 subjects (GC: n = 114; HRAG: n = 222, controls: n = 238) of Caucasian origin. <it>ACE I/D </it>(rs4646994), <it>NOD1 796G>A </it>(rs5743336), <it>TLR4 3725G>C </it>(rs11536889), <it>FAS 1377G>A </it>(rs2234767), <it>FAS 670A>G </it>(rs1800682) and <it>FASL 844T>C </it>(rs763110) were genotyped by different PCR approaches and restriction fragment length polymorphism analysis.</p> <p>Results</p> <p>Frequencies of genotypes in our study are similar to the data reported on subjects of Caucasian ethnicity. There was a tendency for <it>NOD1 796G/G </it>genotype to be associated with increased risk of HRAG (62.4% <it>vs</it>. 54.5% in controls, <it>p </it>= 0.082). <it>FAS 670G/G </it>genotype was more frequent in HRAG when compared to controls, 23.9% and 17.2% respectively, however it failed to reach significance level (<it>p </it>= 0.077). We did not find any significant associations for all polymorphisms in relation to GC or HRAG. <it>NOD1 796G>A </it>and <it>TLR4 3725G>C </it>gene polymorphisms were also not associated with <it>Helicobacter pylori </it>infection.</p> <p>Conclusions</p> <p><it>ACE, NOD1, TRL4 </it>and <it>FAS/FASL </it>gene polymorphisms are not linked with gastric carcinogenesis in Caucasians, and therefore they should not be considered as potential biomarkers for identifying individuals with higher risk for GC.</p

AVEN (apoptosis, caspase activation inhibitor)

Review on AVEN, with data on DNA/RNA, on the protein encoded and where the gene is implicated

FUBP1 (far upstream element (FUSE) binding protein 1)

Review on FUBP1 (far upstream element (FUSE) binding protein 1), with data on DNA, on the protein encoded, and where the gene is implicated