Multiple cancer types demonstrate abnormal expression of repetitive RNA sequences as a form of epigenetic instability. There is growing interest in understanding the role of repetitive RNAs in cancer ...pathogenesis and immunogenicity and in their potential role as diagnostic or therapeutic biomarkers. In this issue of the JCI, Porter and colleagues report on satellite RNA in a subset of ovarian cancers. The authors found that high expression of human satellite (HSAT) repeats--but not other families of repeats--was associated with an immunosuppressive phenotype in ovarian cancer cell lines and tumor samples. Further induction of HSAT RNA levels in vitro, surprisingly, leads to innate immune activation, suggesting a potential therapeutic strategy. This work highlights the expanding role of repetitive RNAs in tumor biology and the need to better define specific classes of repetitive elements expressed in cancer--as well as their role in tumorigenesis, tumor immunity, and the host response to cancer.
Epithelial ovarian cancer is a highly heterogeneous disease characterized by multiple histological subtypes. Molecular diversity has been shown to occur within specific histological subtypes of ...epithelial ovarian cancer, between different tumors of an individual patient, as well as within individual tumors. Recent advances in the molecular characterization of epithelial ovarian cancer tumors have provided the basis for a simplified classification scheme in which these cancers are classified as either type I or type II tumors, and these two categories have implications regarding disease pathogenesis and prognosis. Molecular analyses, primarily based on next-generation sequencing, otherwise known as high-throughput sequencing, are allowing for further refinement of ovarian cancer classification, facilitating the elucidation of the site(s) of precursor lesions of high-grade serous ovarian cancer, and providing insight into the processes of clonal selection and evolution that may be associated with development of chemoresistance. Potential therapeutic targets have been identified from recent molecular profiling studies of these tumors, and the effectiveness and safety of a number of specific targeted therapies have been evaluated or are currently being studied for the treatment of women with this disease.
With the increasing ability to routinely and rapidly digitize whole slide images with slide scanners, there has been interest in developing computerized image analysis algorithms for automated ...detection of disease extent from digital pathology images. The manual identification of presence and extent of breast cancer by a pathologist is critical for patient management for tumor staging and assessing treatment response. However, this process is tedious and subject to inter- and intra-reader variability. For computerized methods to be useful as decision support tools, they need to be resilient to data acquired from different sources, different staining and cutting protocols and different scanners. The objective of this study was to evaluate the accuracy and robustness of a deep learning-based method to automatically identify the extent of invasive tumor on digitized images. Here, we present a new method that employs a convolutional neural network for detecting presence of invasive tumor on whole slide images. Our approach involves training the classifier on nearly 400 exemplars from multiple different sites, and scanners, and then independently validating on almost 200 cases from The Cancer Genome Atlas. Our approach yielded a Dice coefficient of 75.86%, a positive predictive value of 71.62% and a negative predictive value of 96.77% in terms of pixel-by-pixel evaluation compared to manually annotated regions of invasive ductal carcinoma.
Early-stage estrogen receptor-positive (ER+) breast cancer (BCa) is the most common type of BCa in the United States. One critical question with these tumors is identifying which patients will ...receive added benefit from adjuvant chemotherapy. Nuclear pleomorphism (variance in nuclear shape and morphology) is an important constituent of breast grading schemes, and in ER+ cases, the grade is highly correlated with disease outcome. This study aimed to investigate whether quantitative computer-extracted image features of nuclear shape and orientation on digitized images of hematoxylin-stained and eosin-stained tissue of lymph node-negative (LN−), ER+ BCa could help stratify patients into discrete (<10 years short-term vs. >10 years long-term survival) outcome groups independent of standard clinical and pathological parameters. We considered a tissue microarray (TMA) cohort of 276 ER+, LN− patients comprising 150 patients with long-term and 126 patients with short-term overall survival, wherein 177 randomly chosen cases formed the modeling set, and 99 remaining cases the test set. Segmentation of individual nuclei was performed using multiresolution watershed; subsequently, 615 features relating to nuclear shape/texture and orientation disorder were extracted from each TMA spot. The Wilcoxon's rank-sum test identified the 15 most prognostic quantitative histomorphometric features within the modeling set. These features were then subsequently combined via a linear discriminant analysis classifier and evaluated on the test set to assign a probability of long-term vs. short-term disease-specific survival. In univariate survival analysis, patients identified by the image classifier as high risk had significantly poorer survival outcome: hazard ratio (95% confident interval) = 2.91(1.23–6.92), p = 0.02786. Multivariate analysis controlling for T-stage, histology grade, and nuclear grade showed the classifier to be independently predictive of poorer survival: hazard ratio (95% confident interval) = 3.17(0.33–30.46), p = 0.01039. Our results suggest that quantitative histomorphometric features of nuclear shape and orientation are strongly and independently predictive of patient survival in ER+, LN− BCa.
This study investigated whether quantitative computer-extracted images of tissue of lymph node (LN)-, estrogen receptor (ER)+ breast cancer could help stratify patients into discrete outcome groups. The results suggest that quantitative histomorphometric features of nuclear shape and orientation are strongly and independently predictive of patient survival in ER+, LN- breast cancer.
Precise detection of invasive cancer on whole-slide images (WSI) is a critical first step in digital pathology tasks of diagnosis and grading. Convolutional neural network (CNN) is the most popular ...representation learning method for computer vision tasks, which have been successfully applied in digital pathology, including tumor and mitosis detection. However, CNNs are typically only tenable with relatively small image sizes (200 × 200 pixels). Only recently, Fully convolutional networks (FCN) are able to deal with larger image sizes (500 × 500 pixels) for semantic segmentation. Hence, the direct application of CNNs to WSI is not computationally feasible because for a WSI, a CNN would require billions or trillions of parameters. To alleviate this issue, this paper presents a novel method, High-throughput Adaptive Sampling for whole-slide Histopathology Image analysis (HASHI), which involves: i) a new efficient adaptive sampling method based on probability gradient and quasi-Monte Carlo sampling, and, ii) a powerful representation learning classifier based on CNNs. We applied HASHI to automated detection of invasive breast cancer on WSI. HASHI was trained and validated using three different data cohorts involving near 500 cases and then independently tested on 195 studies from The Cancer Genome Atlas. The results show that (1) the adaptive sampling method is an effective strategy to deal with WSI without compromising prediction accuracy by obtaining comparative results of a dense sampling (∼6 million of samples in 24 hours) with far fewer samples (∼2,000 samples in 1 minute), and (2) on an independent test dataset, HASHI is effective and robust to data from multiple sites, scanners, and platforms, achieving an average Dice coefficient of 76%.
Evidence suggests that the catabolic process of macroautophagy (autophagy hereafter) can either suppress or promote cancer. The essential autophagy gene ATG6/BECN1 encoding the Beclin1 protein has ...been implicated as a haploinsufficient tumor suppressor in breast, ovarian, and prostate cancers. The proximity of BECN1 to the known breast and ovarian tumor suppressor breast cancer 1, early onset, BRCA1, on chromosome 17q21, has made this determination equivocal. Here, the mutational status of BECN1 was assessed in human tumor sequencing data from The Cancer Genome Atlas (TCGA) and other databases. Large deletions encompassing both BRCA1 and BECN1, and deletions of only BRCA1 but not BECN1, were found in breast and ovarian cancers, consistent with BRCA1 loss being a primary driver mutation in these cancers. Furthermore, there was no evidence for BECN1 mutation or loss in any other cancer, casting doubt on whether BECN1 is a tumor suppressor in most human cancers.
Contrary to previous reports, BECN1 is not significantly mutated in human cancer and not a tumor-suppressor gene, as originally thought. VISUAL OVERVIEW: http://mcr.aacrjournals.org/content/early/2014/04/01/1541-7786.MCR-13-0614/F1.large.jpg.
Immune checkpoint blockade leads to unprecedented responses in many cancer types. An alternative method of unleashing anti-tumor immune response is to target immunosuppressive metabolic pathways like ...the indoleamine 2,3-dioxygenase (IDO) pathway. Despite promising results in Phase I/II clinical trials, an IDO-1 inhibitor did not show clinical benefit in a Phase III clinical trial. Since, a treatment can be quite effective in a specific subset without being effective in the whole cancer type, it is important to identify the subsets of cancers that may benefit from IDO-1 inhibitors. In this study, we looked for the genomic and immunologic correlates of IDO pathway expression in cancer using the Cancer Genome Atlas (TCGA) dataset. Strong CD8
T-cell infiltration, high mutation burden, and expression of exogenous viruses Epstein-Barr virus (EBV), Human papilloma virus (HPV), and Hepatitis C virus (HCV) or endogenous retrovirus (
) were associated with over-expression of
in most cancer types,
in many cancer types, and
in a few cancer types. High mutation burden in ER+ HER2- breast cancer, and
expression in ER- HER2- and HER2+ breast, colon, and endometrial cancers were associated with over-expression of all three genes. These results may have important implications for guiding development clinical trials of IDO-1 inhibitors.
Antibodies that target the immune checkpoint receptor programmed cell death protein 1 (PD-1) have resulted in prolonged and beneficial responses toward a variety of human cancers. However, anti-PD-1 ...therapy in some patients provides no benefit and/or results in adverse side effects. The factors that determine whether patients will be drug sensitive or resistant are not fully understood; therefore, genomic assessment of exceptional responders can provide important insight into patient response. Here, we identified a patient with endometrial cancer who had an exceptional response to the anti-PD-1 antibody pembrolizumab. Clinical grade targeted genomic profiling of a pretreatment tumor sample from this individual identified a mutation in DNA polymerase epsilon (POLE) that associated with an ultramutator phenotype. Analysis of The Cancer Genome Atlas (TCGA) revealed that the presence of POLE mutation associates with high mutational burden and elevated expression of several immune checkpoint genes. Together, these data suggest that cancers harboring POLE mutations are good candidates for immune checkpoint inhibitor therapy.
Targeted therapies such as Cyclin Dependent Kinase 4 and 6 (CDK 4/6) inhibitors have improved the prognosis of metastatic hormone receptor (HR) positive breast cancer by combating the resistance seen ...with traditional endocrine therapy. The three approved agents currently in the market are palbociclib, ribociclib and abemaciclib. Besides the overall similarities associated with CDK4/6 inhibition, there are differences between the three approved agents that may explain the differences noted in unique clinical scenarios- monotherapy, patients with brain metastases or use in the adjuvant setting. This review article will explore the preclinical and pharmacological differences between the three agents and help understand the benefits seen with these agents in certain subgroups of patients with metastatic HR positive breast cancer.
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