Exome sequencing identified rare recurrent copy number variants and hereditary breast cancer susceptibility.

Copy number variants (CNVs) are a major source of genetic variation and can disrupt genes or affect gene dosage. They are known to be causal or underlie predisposition to various diseases. However, the role of CNVs in inherited breast cancer susceptibility has not been thoroughly investigated. To address this, we performed whole-exome sequencing based analysis of rare CNVs in 98 high-risk Northern Finnish breast cancer cases. After filtering, selected candidate alleles were validated and characterized with a combination of orthogonal methods, including PCR-based approaches, optical genome mapping and long-read sequencing. This revealed three recurrent alterations: a 31 kb deletion co-occurring with a retrotransposon insertion (delins) in RAD52, a 13.4 kb deletion in HSD17B14 and a 64 kb partial duplication of RAD51C. Notably, all these genes encode proteins involved in pathways previously identified as essential for breast cancer development. Variants were genotyped in geographically matched cases and controls (altogether 278 hereditary and 1983 unselected breast cancer cases, and 1229 controls). The RAD52 delins and HSD17B14 deletion both showed significant enrichment among cases with indications of hereditary disease susceptibility. RAD52 delins was identified in 7/278 cases (2.5%, P = 0.034, OR = 2.86, 95% CI = 1.10-7.45) and HSD17B14 deletion in 8/278 cases (2.9%, P = 0.014, OR = 3.28, 95% CI = 1.31-8.23), the frequency of both variants in the controls being 11/1229 (0.9%). This suggests a role for RAD52 and HSD17B14 in hereditary breast cancer susceptibility. The RAD51C duplication was very rare, identified only in 2/278 of hereditary cases and 2/1229 controls (P = 0.157, OR = 4.45, 95% CI = 0.62-31.70). The identification of recurrent CNVs in these genes, and especially the relatively high frequency of RAD52 and HSD17B14 alterations in the Finnish population, highlights the importance of studying CNVs alongside single nucleotide variants when searching for genetic factors underlying hereditary disease predisposition.

Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer.

Tumor necrosis has been reported to represent an independent prognostic factor in colorectal cancer, but its evaluation methods have not been described in sufficient detail to introduce tumor necrosis evaluation into clinical use. To study the potential of tumor necrosis as a prognostic indicator in colorectal cancer, criteria for 3 methods for its evaluation were defined: the average percentage method (tumor necrosis percentage of the whole tumor), the hotspot method (tumor necrosis percentage in a single hotspot), and the linear method (the diameter of the single largest necrotic focus). Cox regression models were used to calculate cancer-specific mortality hazard ratios (HRs) for tumor necrosis categories in 2 colorectal cancer cohorts with more than 1800 cases. For reproducibility assessment, 30 cases were evaluated by 9 investigators, and Spearman's rank correlation coefficients and Cohen's kappa coefficients were calculated. We found that all 3 methods predicted colorectal cancer-specific survival independent of other prognostic parameters, including disease stage, lymphovascular invasion, and tumor budding. The greatest multivariable HRs were observed for the average percentage method (cohort 1: HR for ≥ 40% vs. <3% 3.03, 95% CI, 1.93-4.78; cohort 2: HR for ≥ 40% vs. < 3% 2.97; 95% CI, 1.63-5.40). All 3 methods had high reproducibility, with the linear method showing the highest mean Spearman's correlation coefficient (0.91) and Cohen's kappa (0.70). In conclusion, detailed criteria for tumor necrosis evaluation were established. All 3 methods showed good reproducibility and predictive ability. The findings pave the way for the use of tumor necrosis as a prognostic factor in colorectal cancer.

Whole slide image registration via multi-stained feature matching.

In the recent decade, medical image registration and fusion process has emerged as an effective application to follow up diseases and decide the necessary therapies based on the conditions of patient. For many of the considerable diagnostic analyses, it is common practice to assess two or more different histological slides or images from one tissue sample. A specific area analysis of two image modalities requires an overlay of the images to distinguish positions in the sample that are organized at a similar coordinate in both images. In particular cases, there are two common challenges in digital pathology: first, dissimilar appearances of images resulting due to staining variances and artifacts; second, large image size. In this paper, we develop algorithm to overcome the fact that scanners from different manufacturers have variations in the images. We propose whole slide image registration algorithm where adaptive smoothing is employed to smooth the stained image. A modified scale-invariant feature transform is applied to extract common information and a joint distance helps to match keypoints correctly by eliminating position transformation error. Finally, the registered image is obtained by utilizing correct correspondences and the interpolation of color intensities. We validate our proposal using different images acquired from surgical resection samples of lung cancer (adenocarcinoma). Extensive feature matching with apparently increasing correct correspondences and registration performance on several images demonstrate the superiority of our method over state-of-the-art methods. Our method potentially improves the matching accuracy that might be beneficial for computer-aided diagnosis in biobank applications.

Putative anoikis resistant subpopulations are enriched in lymph node metastases and indicate adverse prognosis in colorectal carcinoma.

Anoikis refers to apoptosis induced by the loss of contact with the extracellular matrix. Anoikis resistance is essential for metastasis. We have recently shown that it is possible to quantitatively evaluate putative anoikis resistant (AR) subpopulations in colorectal carcinoma (CRC). Abundance of these multi-cell structures is an independent marker of adverse prognosis. Here, we have quantified putative AR subpopulations in lymph node (LN) metastases of CRC and evaluated their prognostic value and relationship with the characteristics of primary tumors. A case series included 137 unselected CRC patients, 54 with LN metastases. Areal densities (structures/mm2) of putative AR structures in primary tumors had been analyzed previously and now were determined from all nodal metastases (n = 183). Areal density of putative AR structures was higher in LN metastases than in primary tumors. Variation of the areal density within different LN metastases of a single patient was lower than between metastases of different patients. Abundance of putative AR structures in LN metastases was associated with shorter cancer specific survival (p = 0.013), and this association was independent of T and N stages. Abundance of putative AR structures in primary tumors and LN metastases had a cumulative adverse effect on prognosis. Enrichment of putative AR subpopulations in LN metastases suggest that in metastasis formation, there is a selection favoring cells capable of forming these structures. Higher intra-case constancy relative to inter-case variation suggests that such selection is stable in metastasis development. Our findings indirectly support the biological validity of our concept of putative AR structures.

Putative anoikis-resistant subpopulations in colorectal carcinoma: a marker of adverse prognosis.

Anoikis is a form of apoptosis induced when a cell loses contact with the extracellular matrix (ECM). Anoikis resistance is essential for metastasis formation, yet only detectable by in vitro experiments. We present a method for quantitation of putative anoikis-resistant (AR) subpopulations in colorectal carcinoma (CRC) and evaluate their prognostic significance. We studied 137 CRC cases and identified cell subpopulations with and without stromal or extracellular matrix (ECM) contact with hematoxylin-and-eosin-stained sections and immunohistochemistry for laminin and type IV collagen. Suprabasal cells of micropapillary structures and inner cells of cribriform and solid structures lacked both stromal contact and contact with ECM proteins. Apoptosis rate (M30) was lower in these subpopulations than in the other carcinoma cells, consistent with putative AR subpopulation. We determined the areal density of these subpopulations (number/mm2 tumor tissue), and their high areal density independently indicates low cancer-specific survival. In conclusion, we show evidence that subpopulations of carcinoma cells in micropapillary, cribriform, and solid structures are resistant to anoikis as shown by lack of ECM contact and low apoptosis rate. Abundance of these subpopulations is a new independent indicator of poor prognosis in CRC, consistent with the importance of anoikis resistance in the formation of metastasis.