116 research outputs found
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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 VerhĂĽtung 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
Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH) in association with an adenocarcinoma: a case report
<p>Abstract</p> <p>Introduction</p> <p>Diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH) is a rare disorder and information on this disease is limited, especially with regard to its management and prognosis. It has become generally accepted that DIPNECH is a precursor lesion to pulmonary carcinoid tumors.</p> <p>Case presentation</p> <p>Here we report on a 60-year-old female patient with DIPNECH and an associated pulmonary adenocarcinoma.</p> <p>Conclusion</p> <p>This case contributes to a better understanding of the disorder and its associated pathologies.</p
Histopathological growth patterns of colorectal liver metastasis exhibit little heterogeneity and can be determined with a high diagnostic accuracy
Colorectal liver metastases (CRLM) exhibit distinct histopathological growth patterns (HGPs) that are indicative of prognosis following surgical treatment. This study aims to assess the reliability and replicability of this histological biomarker. Within and between metastasis HGP concordance was analysed in patients who underwent surgery for CRLM. An independent cohort was used for external validation. Within metastasis concordance was assessed in CRLM with ≥ 2 tissue blocks. Similarly, concordance amongst multiple metastases was determined in patients with ≥ 2 resected CRLM. Diagnostic accuracy [expressed in area under the curve (AUC)] was compared by number of blocks and number of metastases scored. Interobserver agreement (Cohen’s k) compared to the gold standard was determined for a pathologist and a PhD candidate witho
Smoking is Associated with Hypermethylation of the APC 1A Promoter in Colorectal Cancer: the ColoCare Study
Smoking tobacco is a known risk factor for the development of colorectal cancer, and for mortality associated with the disease. While smoking has been reported to be associated with changes in DNA methylation in blood and in lung tumour tissues, there has been scant investigation of how epigenetic factors may be implicated in the increased risk of developing colorectal cancer. To identify epigenetic changes associated with smoking behaviours, we performed epigenome-wide analysis of DNA methylation in colorectal tumours from 36 never smokers, 47 former smokers and 13 active smokers, and adjacent mucosa from 49 never smokers, 64 former smokers and 18 active smokers. Our analyses identified 15 CpG sites within the APC 1A promoter that were significantly hypermethylated and 14 CpG loci within the NFATC1 gene body that were significantly hypomethylated (pLIS<1x10-5) in tumours of active smokers. The APC 1A promoter was hypermethylated in 7 of 36 tumours from never smokers (19%), 12 of 47 tumours from former smokers (26%), and 8 of 13 tumours from active smokers (62%). Promoter hypermethylation was positively associated with duration of smoking (Spearman rank correlation, =0.26, p=0.03) and was confined to tumours, with hypermethylation never observed in adjacent mucosa. Further analysis of adjacent mucosa revealed significant hypomethylation of four loci associated with the TNXB gene in tissue from active smokers. Our findings provide exploratory evidence for hypermethylation of the key tumour suppressor gene APC being implicated in smoking-associated colorectal carcinogenesis. Further work is required to establish the validity of our observations in independent cohorts
External validation of molecular subtype classifications of colorectal cancer based on microsatellite instability, CIMP, BRAF and KRAS
Background: Competing molecular classification systems have been proposed to complement the TNM staging system for a better prediction of survival in colorectal cancer (CRC). However, validation studies are so far lacking. The aim of this study was to validate and extend previously published molecular classifications of CRC in a large independent cohort of CRC patients.
Methods: CRC patients were recruited into a population-based cohort study (DACHS). Molecular subtypes were categorized based on three previously published classifications. Cox-proportional hazard models, based on the same set of patients and using the same confounders as reported by the original studies, were used to determine overall, cancer-specific, or relapse-free survival for each subtype. Hazard ratios and confidence intervals, as well as Kaplan-Meier plots were compared to those reported by the original studies.
Results: We observed similar patterns of worse survival for the microsatellite stable (MSS)/BRAF-mutated and MSS/KRAS-mutated subtypes in our validation analyses, which were included in two of the validated classifications. Of the two MSI subtypes, one defined by additional presence of CIMP-high and BRAF-mutation and the other by tumors negative for CIMP, BRAF and KRAS-mutations, we could not confirm associations with better prognosis as suggested by one of the classifications. For two of the published classifications, we were able to provide results for additional subgroups not included in the original studies (men, other disease stages, other locations).
Conclusions: External validation of three previously proposed classifications confirmed findings of worse survival for CRC patients with MSS subtypes and BRAF or KRAS mutations. Regarding MSI subtypes, other patient characteristics such as stage of the tumor, may influence the potential survival benefit. Further integration of methylation, genetic, and immunological information is needed to develop and validate a comprehensive classification that will have relevance for use in clinical practice
Loss of aquaporin-4 expression and putative function in non-small cell lung cancer
<p>Abstract</p> <p>Background</p> <p>Aquaporins (AQPs) have been recognized to promote tumor progression, invasion, and metastasis and are therefore recognized as promising targets for novel anti-cancer therapies. Potentially relevant AQPs in distinct cancer entities can be determined by a comprehensive expression analysis of the 13 human AQPs.</p> <p>Methods</p> <p>We analyzed the presence of all AQP transcripts in 576 different normal lung and non-small cell lung cancer (NSCLC) samples using microarray data and validated our findings by qRT-PCR and immunohistochemistry.</p> <p>Results</p> <p>Variable expression of several AQPs (AQP1, -3, -4, and -5) was found in NSCLC and normal lung tissues. Furthermore, we identified remarkable differences between NSCLC subtypes in regard to AQP1, -3 and -4 expression. Higher transcript and protein levels of AQP4 in well-differentiated lung adenocarcinomas suggested an association with a more favourable prognosis. Beyond water transport, data mining of co-expressed genes indicated an involvement of AQP4 in cell-cell signalling, cellular movement and lipid metabolism, and underlined the association of AQP4 to important physiological functions in benign lung tissue.</p> <p>Conclusions</p> <p>Our findings accentuate the need to identify functional differences and redundancies of active AQPs in normal and tumor cells in order to assess their value as promising drug targets.</p
A prognostic CpG score derived from epigenome-wide profiling of tumor tissue was independently associated with colorectal cancer survival
Background: Results of previous studies on the association of the CpG island methylator phenotype (CIMP) with colorectal cancer (CRC) prognosis were inconsistent and mostly based on different CIMP definitions. The current study aimed to comprehensively investigate the associations between DNA methylation on genes previously used to define CIMP status with CRC survival.
Results: Patients with CRC followed up for a median of 5.2 years were divided into a study cohort (n = 568) and a validation cohort (n = 308). DNA methylation was measured in tumor tissue using the Illumina Infinium HumanMethylation450 BeadChip and restricted to 43 genes used to define CIMP status in previous studies. Cox proportional hazard regression models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) of survival after CRC, including adjustment for tumor stage, microsatellite instability, and BRAF mutation status. In the study cohort, ten CpG sites were identified to be associated with CRC survival. Seven of these ten CpG sites were also associated with CRC survival in the validation cohort and were used to construct a prognostic score. CRC patients with a prognostic score of the lowest methylation level showed poorer disease-specific survival compared with patients with the highest methylation level in both the study cohort and the validation cohort (HR = 3.11 and 95% CI = 1.97–4.91, and HR = 3.06 and 95% CI = 1.71–5.45, respectively).
Conclusions: A CpG panel consisting of seven CpG sites was found to be strongly associated with CRC survival, independent from important clinical factors and mutations associated with CIMP. Further studies are required to confirm these findings
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