Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

Gutman, David; Cobb, Jake; Somanna, Dhananjaya; Park, Jinah; Wang, Fusheng; Kurç, Tahsin; Saltz, Joel; Brat, Daniel J.; Cooper, Lee

doi:10.1136/amiajnl-2012-001469

Cited by 170 publications

(111 citation statements)

References 22 publications

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“…To determine the involvement this epigenetic mechanism of silencing for FENDRR and FOXF1, firstly we analyzed the in silico results from The Cancer Genome Atlas database [17] using the Wanderer web tool [18]. The methylation status of the promoter CpG islands of FENDRR and FOXF1 was significantly different in tumor versus normal tissue.…”

Section: Methylation Status Of Fendrr and Foxf1mentioning

confidence: 99%

The value of lncRNAFENDRRandFOXF1as a prognostic factor for survival of lung adenocarcinoma

et al. 2017

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It is increasingly evident that non-coding RNAs play a significant role in tumour development. However, we still have a limited knowledge of the clinical significance of long non-coding RNAs (lncRNAs) in lung cancer. The FENDRR is a long coding RNA (also named FOXF1-AS1) located in the vicinity of the protein-coding gene FOXF1 at 16q24.1 chromosomal region. The present study aimed to define the clinic pathological significance of the long-non-coding RNA FENDRR in lung adenocarcinomas. FENDRR expression measured by quantitative PCR was found significantly downregulated (p<0.001) in lung adenocarcinoma samples in comparison with their normal adjacent tissues (n=70). RNA in situ hybridization (RNA-FISH) corroborated independently the down-regulation of FENDRR. Interestingly, the expression of FENDRR correlated positively (p<0.001) with the expression of its protein-coding neighbor gene FOXF1. Additionally, FOXF1 expression was also found downregulated in adenocarcinomas compared to normal samples (p<0.001) and its expression was significantly correlated with overall survival alone (p=0.003) or in combination with FENDRR expression (p=0.01). In conclusion, our data support that FENDRR and FOXF1 expression is decreased in lung adenocarcinoma and should be considered as new potential diagnostic/prognosis biomarkers.

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Section: Methylation Status Of Fendrr and Foxf1mentioning

confidence: 99%

The value of lncRNAFENDRRandFOXF1as a prognostic factor for survival of lung adenocarcinoma

et al. 2017

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“…Furthermore, few studies have highlighted the importance of combining comprehensive histopathological image features with –omics data [3]. Existing integrative imaging and genomic studies focus primarily on radiology [4, 5] or imaging meta-data [6].…”

Section: Introductionmentioning

confidence: 99%

Integration of multi-modal biomedical data to predict cancer grade and patient survival

Phan

Hoffman

Kothari

et al. 2016

2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

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The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

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“…WSI can be simply used during comparison with multiple stains side by side; if multiple sections stained using multiple stains have to be compared, one can use “match and zoom” tool in Adobe Photoshop to compare the exact areas in the section. If any researcher wants to identify and count specific type of cell(s), this can be done using the entire section rather than the conventional method of counting the cells in “per high power fields.” Several recent studies of The Cancer Genome Atlas data have illustrated important relationships between morphology observed in whole slide images, outcome, and genetic events [13]. Numerous studies using WSI relating to Identification of mitosis [14–16] are already published.…”

Section: Discussionmentioning

confidence: 99%

Image Montaging for Creating a Virtual Pathology Slide: An Innovative and Economical Tool to Obtain a Whole Slide Image

Banavar

Chippagiri

Pandurangappa

et al. 2016

Analytical Cellular Pathology

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Background. Microscopes are omnipresent throughout the field of biological research. With microscopes one can see in detail what is going on at the cellular level in tissues. Though it is a ubiquitous tool, the limitation is that with high magnification there is a small field of view. It is often advantageous to see an entire sample at high magnification. Over the years technological advancements in optics have helped to provide solutions to this limitation of microscopes by creating the so-called dedicated “slide scanners” which can provide a “whole slide digital image.” These scanners can provide seamless, large-field-of-view, high resolution image of entire tissue section. The only disadvantage of such complete slide imaging system is its outrageous cost, thereby hindering their practical use by most laboratories, especially in developing and low resource countries. Methods. In a quest for their substitute, we tried commonly used image editing software Adobe Photoshop along with a basic image capturing device attached to a trinocular microscope to create a digital pathology slide. Results. The seamless image created using Adobe Photoshop maintained its diagnostic quality. Conclusion. With time and effort photomicrographs obtained from a basic camera-microscope set up can be combined and merged in Adobe Photoshop to create a whole slide digital image of practically usable quality at a negligible cost.

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Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

Abstract: With the increasing availability of whole-slide scanners, analysis of digitized pathology images will become increasingly important in linking morphologic observations with genomic and clinical endpoints.

Cited by 170 publications

References 22 publications

The value of lncRNAFENDRRandFOXF1as a prognostic factor for survival of lung adenocarcinoma

The value of lncRNAFENDRRandFOXF1as a prognostic factor for survival of lung adenocarcinoma

Integration of multi-modal biomedical data to predict cancer grade and patient survival

Image Montaging for Creating a Virtual Pathology Slide: An Innovative and Economical Tool to Obtain a Whole Slide Image

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