Likelihood Of Metastasis Research Articles

Photogallery. HIV infection and neoplastic skin diseases

Malignant neoplasms constitute a group of the most important secondary diseases that develop in people infected with the human immunodeficiency virus (HIV). The first neoplastic disease described in HIV-infected patients is Kaposi's sarcoma. In contrast to other types of Kaposi's sarcoma, its epidemic (AIDS-associated) type is more common in young and middle-aged HIV-positive individuals, especially among men who have same-sex sex. Epidemic Kaposi's sarcoma does not have a favourite localisation. However, there is a tendency to lesions of the scalp (face, ear flaps), upper extremities, anogenital area, oral mucosa. On the trunk, the pathological process spreads along the Langer lines. Skin rashes are represented by spotty, papular, nodular elements of red-brown or purple colour. The aggressive course is characteristic: rapid dissemination and generalisation of rashes. Plasmoblastic lymphoma is associated with immunodeficiency states and is rare. The tumour lesion is usually located in the oral cavity. Few cases of plasmoblastic lymphoma with skin and soft tissue involvement have been described in the literature. Squamous cell skin cancer in the context of HIV infection is a dangerous disease. In people living with HIV, it manifests at a significantly earlier age and is associated with a high risk of local recurrence. The extent of invasion and the likelihood of metastasis are influenced by HIV-associated immunodeficiency. In the vast majority of cases, risk factors and clinical manifestations of basal cell skin cancer do not differ from those in immunocompetent individuals. Basal cell carcinomas rarely metastasise. Nevertheless, metastatic forms lead to unfavourable outcome. Here is a photo gallery of cases of neoplastic skin lesions developed in HIV-positive patients.

Cerebellar Metastasis Manifesting as a Cyst with Mural Nodule(s): Differentiating It From Hemangioblastoma on MRI

A cyst with mural nodule(s) (CMN) is a rare imaging finding of cerebellar metastasis (CMET). It is a great challenge to differentiate it from cerebellar hemangioblastoma (CHB). In the present study, we explore the differences in the magnetic resonance imaging (MRI) characteristics of the 2 tumors. Patients with pathologically confirmed CMET or CHB at our hospital from July 2009 to September 2021 were enrolled in the present study. All the patients underwent conventional head MRI (before and after contrast administration) before surgery and had ≥1 lesion in the cerebellum that presented as CMN on MRI. The clinical and MRI features were compared between the 2 groups. A total of 33 patients (10 with CMET and 23 with CHB) met the study criteria. The CMET patients were significantly older than were the CHB patients (median age, 59.5 years vs. 37 years; P= 0.002). Compared with the CHB group, the CMET group showed significantly higher occurrence rates of multiple mural nodules (72.7% vs. 8.7%), lack of vascular flow voids (100% vs. 65.2%), isointense or hypointense mural nodules on fluid-attenuated inversion recovery imaging (100.0% vs. 22.7%), restricted diffusion of mural nodules (22.2% vs. 0.0%), mildly enhanced mural nodules (90.9% vs. 4.3%), and a ring-enhanced pattern of the cyst wall (100% vs. 8.7%; P < 0.05 for all). When CMN is detected in the cerebellum on MRI, older age, multiple mural nodules, absence of vascular flow voids, isointense or hypointense mural nodule on fluid-attenuated inversion recovery sequence, restricted diffusion of the mural nodule, mildly enhanced mural nodules, and a ring-enhanced pattern of the cyst wall are the clinical and imaging features that strongly indicate the likelihood of metastasis, rather than CHB.

Abstract 469: A multi-scale analysis and visualization platform for cancer data - deriving tumor microenvironment behavior from pathology and transcriptomics

Abstract Heterogeneity is a hallmark of cancer and perhaps one of the most important features associated with resistance to therapies and likelihood of recurrence and/or metastasis. Genomic instability contributes to genetic diversity, which leads to high levels of intratumoural heterogeneity. While genetic diversity is one contributor to phenotypic heterogeneity in tumors, the spatial variation in the tumor microenvironment (TME) also drives emergent phenotypic heterogeneity and intrinsic variation in resistance to drugs and the immune system. Ultimately, heterogeneity leads to higher likelihood of metastasis. Traditionally, pathology allowed for the assessment of heterogeneity. However, this was limited to gross assessment of the TME, through measurement of mitotic levels and severity of cancer invasion. We present SimBioSys PhenoScope, a multi-scale analysis and visualization platform that integrates cancer data across scales to extract cross modality trends that drive cancer invasion. As a demonstrated use case for the platform, we present a vignette of using the platform to analyze pathology slides at three scales. Three convolutional neural networks (CNN) are developed and validated. The outputs of these networks were combined with 2D simulations of the metabolic behavior and growth of cells within the TME. Two CNNs were developed and one implemented: one that identifies cells undergoing mitosis, one that segments individual cells and classifies their type, and one that segments five tissues from pathology slides. Additionally, transcriptional data was used to generate patient specific metabolic models. Each CNN was developed using training images and validated on the test images. The mitosis detection CNN was found to have an accuracy of 76.2% (precision=83%, recall=76%) in the test set. The classification CNN was found to have a Dice Similarity Coefficient (DSC) of 0.821 for segmenting cells and an F1 score for classifying cells ranging from 0.559 (F1i) to 0.756 (F1d). The segmentation CNN was found to have an accuracy of 78.1% with DSC ranging from 0.66 and 0.86 depending on tissue. The segmentations were input into a proprietary simulation framework along with patient-specific metabolic models to predict the spatial gradients of nutrients, and spatial organization of growth and metabolism. Simulations show multiple behaviors such as regions of high lactate production or consumption by cancer, and regions that differ by lactate production and alanine uptake in cancers. These behaviors were correlated with local cell mitoses and invasion of Tumor Infiltrating Lymphocytes. Tools to examine cancers across scales and within the TME are currently lacking. We demonstrate a proof-of-principle approach of combining data across scales in a fashion that allows for novel predictions of TME behavior. Citation Format: Joseph R. Peterson, Matthew Shin, Patricia Carrigan, Michael J. Hallock, Snehal Patel, The SimBioSys Team. A multi-scale analysis and visualization platform for cancer data - deriving tumor microenvironment behavior from pathology and transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 469.

Abstract A020: Multi-species regulatory analysis of osteosarcoma to reduce clinical trial failure rates

Abstract Osteosarcoma is a rare pediatric cancer characterized by poor prognosis and a high likelihood of metastasis, for which no systemic treatments have been successfully developed in the past 30 years [1]. The lack of effective biologically relevant osteosarcoma tumor models is a significant obstacle to the development of effective therapeutics [2]. Therefore, developing a framework that addresses this issue is essential in further advancing therapeutics studies. We postulate that a comparative genomics approach, evaluating whole-transcriptome osteosarcoma response in species closely related to humans, would highlight immune and other differences in each species that will better guide the design of human therapeutics. To investigate this, we compile RNA-seq data from studies of mice, human, and canine osteosarcoma [3], and perform an integrated analysis of disease in these three species. We build a tri-species multi-layer network of regulatory interactions in osteosarcomas to identify evolutionary links between osteosarcomas. Each layer of our network represents the interactions in one species, and the integrated network captures interactions preserved across species. We perform enrichment analysis on these networks and statistically evaluate differences between the topologies of the regulatory networks of these three species, investigating the functional impact of species-specific interactions and how each affects drug response. Additionally, we survey the literature to identify mutations in osteosarcomas from each species, and calculate diffusion scores for mutated genes in each layer of the network compared to genes mutated in osteosarcoma. As future work, we aim to utilize our comparative genomics approach and leverage the differences between interaction networks of related species to compute the likelihood of identifying early-stage therapeutic trials that will fail in later stages, thus avoiding costly experiments and guiding drug development. Citation Format: Tina Salehi Torabi, Soumya Gottipati, Tamer Kahveci, Kiley Graim. Multi-species regulatory analysis of osteosarcoma to reduce clinical trial failure rates [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A020.

Merkel cell carcinoma brain metastasis with radiological findings mimicking primary CNS lymphoma: illustrative case.

BACKGROUNDMerkel cell carcinoma (MCC) is a rare and aggressive neuroendocrine tumor with a high likelihood of distant metastasis. Approximately 30 cases of MCC brain metastasis have been reported. The authors report a case of MCC brain metastasis with imaging findings mimicking primary central nervous system lymphoma.OBSERVATIONSA 69-year-old asymptomatic White female with a past medical history of rheumatoid arthritis and MCC of the right cheek with no known regional or distant spread presented with a right frontal lobe lesion discovered incidentally on a surveillance scan. Brain magnetic resonance imaging revealed a vividly enhancing homogeneous lesion with restricted diffusion on diffusion-weighted imaging and corresponding apparent diffusion coefficient maps. Imaging characteristics suggested a highly cellular mass consistent with primary central nervous system lymphoma; however, given the likelihood of metastasis, resection was recommended. An intraoperative frozen section suggested lymphoma. However, further examination revealed positive cytokeratin 20 staining for a tumor, and a final diagnosis of MCC brain metastasis was made.LESSONSImaging characteristics of MCC brain metastasis can vary widely. A high level of suspicion should be maintained in a patient with a known history of MCC. Aggressive resection is recommended, regardless of appearance on scans or pathology of frozen sections, because MCC can mimic other intracranial pathologies.

Logistic Regression Model of Relationship between Breast Cancer Pathology Diagnosis with Metastasis

Management of breast cancer requires a diagnosis of breast cancer, including an accurate pathology diagnosis to direct the provision of appropriate treatment. Part of inseparable diagnosis of breast cancer itself is determining the presence of metastasis. This study aims to determine the relationship model of pathological diagnosis with the possibility of metastasis to other organs of the breast. Pathology diagnosis results include tumor position, topography, behavior, grade, and tumor status. This study used secondary data from the Hospital Information System (SIRS) of the hospital in Makassar, Indonesia. Data obtained from the results of pathology and clinical examinations of breast tumor as many as 204 patients were hospitalized during the year of 2018. Binary regression analysis modeling was performed to see the relationship between types of pathological diagnosis (laterality, topography, behavior, grade, tumor status) of breast cancer with the possibility of metastases to other organs. The results of the analysis found a significant relationship between the position and status of the tumor with the presence of metastasis. The results of the metastatic binary logistic regression model was L(Y) = 1.330 – 0.670lat1 – 0.779lat2 – 0.724status Chi-square analysis between metastasis with surgery and chemotherapy found the significant relationships between metastasis with surgery (X2 = 15.951; p value = 0.001) and metastasis with chemotherapy (X2 = 20,796; p value = 0.001). The results of this analysis indicate that the position and status of the tumor have a relationship with the likelihood of metastasis. In addition, this metastasis further determines the management of treatment whether surgery or chemotherapy or both.

Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay.

Cancer mortality is mostly related to metastasis. Metastasis is currently prognosed via histopathology, disease-statistics, or genetics; those are potentiallyinaccurate, not rapidly available and require known markers. We had developed a rapid (~ 2 h) mechanobiology-based approach to provide early prognosis of the clinical likelihood for metastasis. Specifically, invasive cell-subsets seeded on impenetrable, physiological-stiffness polyacrylamide gels forcefully indent the gels, while non-invasive/benign cells do not. The number of indenting cells and their attained depths, the mechanical invasiveness, accurately define the metastatic risk of tumors and cell-lines. Utilizing our experimental database, we compare the capacity of several machine learning models to predict the metastatic risk. Models underwent supervised training on individual experiments using classification from literature and commercial-sources for established cell-lines and clinical histopathology reports for tumor samples. We evaluated 2-class models, separating invasive/non-invasive (e.g. benign) samples, and obtained sensitivity and specificity of 0.92 and 1, respectively; this surpasses other works. We also introduce a novel approach, using 5-class models (i.e. normal, benign, cancer-metastatic-non/low/high) that provided average sensitivity and specificity of 0.69 and 0.91. Combining our rapid, mechanical invasiveness assay with machine learning classification can provide accurate and early prognosis of metastatic risk, to support choice of treatments and disease management.

Tumor volume is more reliable to predict nodal metastasis in non-small cell lung cancer of 3.0\u2009cm or less in the greatest tumor diameter

BackgroundIn this study, we sought to evaluate the correlation between TV, GTD, and lymph node metastases in NSCLC patients with tumors of GTD ≤ 3.0 cm.MethodsWe retrospectively analyzed the characteristics of clinicopathologic variables for lymph node involvement in 285 NSCLC patients with tumors of GTD ≤ 3.0 cm who accepted curative surgical resection. The TVs were semi-automatically measured by a software, and optimal cutoff points were obtained using the X-tile software. The relationship between GTD and TV were described using non-linear regression. The correlation between GTD, TV, and N stages was analyzed using the Pearson correlation coefficient. The one-way ANOVA was used to compare the GTD and TV of different lymph node stage groups.ResultsThe relationship between GTD and TV accorded with the exponential growth model: y = 0.113e1.455x (y = TV, x = GTD). TV for patients with node metastases (4.78 cm3) was significantly greater than those without metastases (3.57 cm3) (P < 0.001). However, there were no obvious GTD differences in cases with or without lymph node metastases (P = 0.054). We divided all cases into three TV groups using the two cutoff values (0.9 cm3 and 3.9 cm3), and there was an obvious difference in the lymphatic involvement rate between the groups (P < 0.001). The tendency to metastasize was greater with higher TV especially when the TV was > 0.9–14.2 cm3 (P = 0.010).ConclusionsFor NSCLC tumors with GTD ≤ 3.0 cm, TV is a more sensitive marker than GTD in predicting the positive lymph node metastases. The likelihood for metastasis increases with an increasing TV especially when GTD is > 2.0–3.0 cm.

Abstract IA18: The unnecessary epidemic: Skin cancer in Hispanics and what we need to do about it

Abstract Melanoma is a highly complex disease with multifaceted etiology, whose incidence is on the rise, over and above the impact of screening. Hispanics represent an underserved and understudied population when it comes to melanoma occurrence and outcome. Hispanics are diagnosed with melanoma at later stages than their non-Hispanic white (NHW) counterparts, leading to increased likelihood of metastasis and worse survival. Hispanics are the largest ethnic group in the United States and have rising rates of melanoma, and in particular, increases in tumors with the worst prognosis. While histologic type of melanoma varies by ethnicity (Hispanics tend to get more acral lentiginous melanomas, which tend to present at a later stage), histology does not explain the poorer experience of Hispanics: they are diagnosed with later-stage disease regardless of histology. In our recent analysis, while the risk of presenting with a late-stage melanoma was higher for Hispanics (OR:1.65 [95% CI:1.52-1.79]) than NHW, the overall risk of death from melanoma after accounting for stage at diagnosis was similar for Hispanics and NHW (HR: 0.99 [95% CI: 0.94-1.04]), implying that the overall poorer prognosis for Hispanics is due almost entirely to their later stage of disease at diagnosis, rather than response to treatment or other factors (e.g., ability to access treatment) once they are diagnosed. However, the key question remaining to be answered is why Hispanics are diagnosed at a later stage: without answering that question, we cannot begin to design, test, and implement effective interventions to reduce the melanoma burden in Hispanics. A later stage of diagnosis among Hispanics (compared to NHWs) could be due to a multitude of factors, all of which are modifiable: a lack of access to appropriate screening, lack of adherence to screening recommendations, lack of understanding of appropriate screening approaches in the primary care setting (among both patients and physicians), or a combination of these factors. Addressing the epidemic of melanoma among Hispanics is not limited to investigation of factors resulting in delayed diagnosis: we also lack an understanding of the primary drivers of Hispanics’ lower overall incidence of melanoma (roughly 7 times lower than non-Hispanic whites). Melanoma risk factors either have similar frequency in Hispanics and NHWs (e.g., many large nevi) or are less frequent in Hispanics but do not explain a high proportion of disease variation (e.g., red hair). Considering current knowledge of risk factor prevalence, melanoma incidence rates should actually be similar in Hispanics and non-Hispanic whites. Understanding the factors leading to the lower overall rate of melanoma in Hispanics could help inform prevention strategies for non-Hispanic whites—or determine new genetic pathways as yet undiscovered. While it is possible that Hispanics’ rates of melanoma are lower because they practice better sun-exposure behaviors, we have recently shown that Hispanic children, while frequently engaging in some sun-protective behaviors, also had a high rate of sunburn (59%). U.S.-acculturated Hispanic children reported less shade-seeking at school (P = .001). The surprisingly high rate of sunburn in Hispanic children suggests that the way in which they are practicing sun protection is not preventing sunburns and is an alarming early warning sign for future increases in melanoma rates among Hispanics. Sun safety interventions should be targeted toward Hispanic youth to provide them with practical methods of effective sun protection, in addition to education on the risks of high sun exposure. The contrast in melanoma experience between Hispanics and NHW implies that we already know how to reduce the occurrence of late-stage melanoma in Hispanics, and a better understanding of the differing rates of melanoma among Hispanics and NHW might actually provide insight into enhanced melanoma primary prevention in both groups. Citation Format: Myles Cockburn, Jennifer Unger, Kimberly Miller. The unnecessary epidemic: Skin cancer in Hispanics and what we need to do about it [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr IA18.

Interfacial Stability and the Onset of Metastasis

We examine whether onset of metastasis can be understood, in part, by considering the stability of the interface between a growing tumour and the surrounding tissue. Whilst the interface is stable, small projections and bulges from the surface of the tumour into surrounding tissue will tend to be flattened and reabsorbed. If, by contrast, the interface becomes unstable, small protrusions will tend to grow into surrounding tissue. Once protrusions are able to grow they can split off to form separate tumours. We derive an expression for the critical size of a protrusion from the surface of a primary tumour. Below that size it will tend to shrink, but above that size it will tend to grow and possibly separate from the tumour. We explore some consequences of this analysis for, e.g., likelihood of metastasis and sizes of escaping metastatic clusters. We show how closely-separated pinning sites may aid formation of metastatic clusters, and suggest how multiple metastatic clusters can emerge from the same section of pinned interface.

Clinical features of metastasis from superficial squamous cell carcinoma of the thoracic esophagus

BackgroundIt is important to understand the sites and the frequency of metastasis to perform less invasive treatments for superficial esophageal cancer, such as minimized or focused lymphadenectomy, endoscopic resection, and chemoradiotherapy. The distribution pattern and frequency of metastases from superficial esophageal cancer, however, have not been well elucidated. MethodsIn 342 patients with superficial esophageal squamous cell carcinoma who underwent esophagectomy, the sites and frequency of any metastasis, including lymph node metastasis at the time of esophagectomy, lymph node recurrence, and hematologic metastases were investigated. Factors associated with the likelihood of metastasis and prognosis were also examined. ResultsThe incidence of lymph node metastasis increased with tumor depth (m2 = 7%; m3 = 17%; sm1 = 29%; sm2 = 41%; and sm3 = 42%). Lymph node metastases were observed most frequently in upper mediastinal lymph nodes, such as upper paratracheal lymph nodes, and in perigastric lymph nodes, such as paracardial lymph nodes and the left gastric lymph nodes. Lymph node metastases were also observed across a broad range of lymph nodes, including cervical, mediastinal, and abdominal lymph node regions, irrespective of tumor location. The 5-year overall survival and disease-specific survival rates were 78% and 89%, respectively. Submucosal invasion and lymphatic invasion were identified as independent factors associated with metastasis. Lymphatic invasion was also identified as an independent factor associated with disease-specific survival. ConclusionThe present study shows that metastasis can occur in a wide range of lymph node stations even in superficial esophageal squamous cell carcinoma. Together with the finding that lymphatic invasion is an independent prognostic factor, this study may help determine the treatment strategy for superficial esophageal squamous cell carcinoma.

Abstract LB-275: Targeting poor-prognosis subtypes of prostate cancer by inhibition of DNA repair gene ribonucleotide reductase small subunit M2

Abstract Studies reveal defective DNA repair contribute to prostate cancer (PC) progression. We hypothesize that overexpression of DNA repair genes could also contribute to poorer outcomes in PC. The nucleotide metabolism enzyme ribonucleotide reductase (RNR) is essential for DNA synthesis and DNA repair by producing dNTPs. The small subunit M2 (RRM2), as the rate-limiting RNR subunit, is frequently up-regulated in cancers. Clinically, targeting of RRM2 with small molecules is being tested in multiple cancers, but there is little knowledge of RRM2 function in PC. The analysis of multiple PC clinical cohorts (total include 1602 cases) revealed that high RRM2 level was associated with poor clinical outcomes, including a higher likelihood of metastasis (p&amp;lt;0.001), biochemical recurrence (p&amp;lt;0.001), and lethality (p&amp;lt;0.0001). In PC cells, knockdown of RRM2 inhibited dNTP production and induced DNA damage, which led to significant cell growth inhibition, major S phase arrest, and apoptosis. Overexpression of RRM2 promoted epithelial-mesenchymal transition (EMT) by increasing the expression of multiple EMT markers. Furthermore, the small molecule RRM2 inhibitor (COH29) induced a similar phenotype as knocking down RRM2 in PC cells. RNA-Seq analysis in siRRM2 or COH29 treated PC cells provided a global assessment of RRM2-regulated transcriptome changes. GSEA analysis revealed that inhibition of RRM2 could activate biological processes including cell cycle checkpoint, DNA damage response, and apoptotic signaling. COH29 treatment could target genes highly enriched in PC. We further applied an RRM2-regulated gene signature (from RNA-Seq datasets) to TCGA and Taylor cohorts. Intriguingly, the RRM2 signature was highly correlated with metastasis and disease free survival (p&amp;lt;0.001). Furthermore, inhibition of RRM2 specifically targets poor prognostic luminal subtypes (PCS1 subtype; Lum B in PAM50 classifier) recently reported. Besides transcriptome changes, protein kinase arrays showed that AKT/mTOR and SFK-STAT signaling were repressed by inhibition of RRM2. These oncogenic signaling pathways are crucial for EMT program. Amplification of RRM2 is rare in PC and transcriptional activation of RRM2 may play a major role in overexpression of RRM2. H3K27ac ChIP-Seq from tissues revealed more activated RRM2 promoter in PC than in normal prostate. 13 potential RRM2-targeting transcription factors (TFs) were identified by integrating clinical cohorts and a TF database. They showed a positive correlation with RRM2 expression in PC cohorts. Among these TFs, FOXM1 was reported to be the master driver of the aggressive luminal subtype of PC. We revealed that FOXM1 expression was associated with clinical outcomes. The ChIP-PCR and luciferase reporter assays provided evidence of physical binding of FOXM1 to the RRM2 promoter in PC cells. Knockdown of FOXM1 significantly repressed RRM2 mRNA and protein levels. Altogether, FOXM1-regulated transcriptional activation contributes to overexpression of RRM2. Intriguingly, COH29 can also repress FOXM1 expression, which leads to transcription repression of RRM2. Altogether, our study elucidated the molecular mechanisms underlying RRM2 oncogenic functions and the transcriptional regulation of RRM2 in PC cells. We suggest that RRM2 can be a novel therapeutic target for PC treatment. Citation Format: Ying Z. Mazzu, Joshua Armenia, Goutam Chakraborty, Yuki Yoshikawa, Travis A. Gerke, Si Ana A. Coggins, Xintao Qiu, Mohammad Atiq, Konrad H. Stopsack, Gwo-Shu Mary Lee, Henry W. Long, Baek Kim, Matthew L. Freedman, Mark M. Pomerantz, Lorelei A. Mucci, Philip W. Kantoff. Targeting poor-prognosis subtypes of prostate cancer by inhibition of DNA repair gene ribonucleotide reductase small subunit M2 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-275.

Prognostic and therapeutic significance of ribonucleotide reductase small subunit M2 in prostate cancer.

240 Background: DNA-repair defects are common in advanced prostate cancer (PC) and high-risk localized tumors. Besides deficiency of DNA repair, overexpression of DNA repair genes could also contribute to poorer outcomes for PC patients. The nucleotide metabolism enzyme ribonucleotide reductase (RNR) plays the key role in DNA synthesis and repair. RRM2, the rate-limiting RNR subunit, is frequently up-regulated in cancer, and its overexpression leads to chemoresistance. Although targeting RRM2 by siRNA and small molecules has been applied in clinical trials in multiple cancers, limited knowledge of RRM2 function in PC delays potential clinical application of RRM2 inhibition. Methods: We leveraged publically available PC clinical cohorts to examine RRM2 levels and clinical outcomes. siRNAs was applied to knockdown of RRM2 in multiple PC cell lines. Cell growth, cell cycle and apoptosis were analyzed to determine siRRM2 or RRM2 inhibitor (COH29)-induced phenotypes. RNA-seq and protein array were performed to identify downstream targets of RRM2. Immunohistochemistry staining was applied to determine prevalence of RRM2 protein expression in PC tissues microarrays (TMAs). Results: In PC cohorts, increased RRM2 expression was associated with a higher likelihood of metastasis, poorer disease-free survival, and increased risk of development of lethal disease (N = 1200, PHS/HPFS cohorts). In PC cells, Inhibition of RRM2 induced remarkable cell growth inhibition, cell cycle arrest (at S phase) and apoptosis. DNA damage was observed in siRRM2/COH29-treated PC cells with increased activation of DNA damage markers. GSEA analysis of the RNA-seq dataset revealed multiple biological processes were affected by inhibition of RRM2, such as cell cycle, apoptosis, and DNA damage response. Intriguingly, MYC oncogenic signaling is the major downstream targets of RRM2. Furthermore, inhibition of RRM2 can block multiple oncogenic signaling including mTOR/AKT, SFK, and STAT signaling by repressing the key phospho-kinases in PC cells. Among 121 cases on the PC TMAs, 20% showed strong RRM2 protein expression. Conclusions: RRM2 may serve as a prognostic biomarker and novel therapeutic target in PC.

Abstract PD4-10: FGFR1 / ZNF217 copy numbers and outcome in patients with node positive, HR+/Her2- early breast cancer: A genomic analysis of PACS04 trial

Abstract Purpose: There is a need to identify which patients present a high risk of relapse after optimal adjuvant therapies, in order to better define which population of early breast cancer patients is eligible to new drugs. Previous studies have shown that gene copy numbers drive breast cancer progression. In the BIG1-98 trial, FGFR1 (8p11) and ZNF217 (20q13) amplifications were associated with poor outcome in patients with HR+/Her2- early breast cancers. In the present study, we aim to validate these findings using retrospective analysis of samples prospectively collected in a randomized trial (PACS04). Patients and methods: Tumor DNA was extracted from FFPE samples obtained from patients included in PACS04 trial. This trial compared FEC to ED75 in patients with node positive, early breast cancer and included 3000 patients between 2001 and 2004. The biomarker study focuses on HR+/Her2- breast cancer. 500 samples were collected and hybridization was performed on 390. DNA copy numbers were assessed on 900 genes using Oncoscan FFPE assay kit. Prognostic value of FGFR1 (8p11) and ZNF217 (20q13) copy numbers was assessed in a Cox model that included prognostic parameters. Prognostic value was assessed using CNA as continuous variable, and with a predefined cut-off (CN&amp;gt;=3). Metastases-free survival (MFS) was chosen as endpoint for this biomarker study. Results: Tumor copy numbers alterations were obtained in 390 patients with HR+/Her2-, node positive, early breast cancer. 31% of the patients presented more than 3 lymph node involved, and 25% a poorly differenciated tumor. The median tumor size was 20 mm. 120 (30%) and 112 (28%) patients presented FGFR1 and/or ZNF217 gene gain with a cut-off for amplification predefined at 3 copies. When assessed as continuous variable, FGFR1 (HR: 1.02, 95%CI:1.007-1.04, p=0.0045) and ZNF217 (HR: 1.011, 95%CI:1.003-1.01, p=0.006) copy numbers were associated with MFS. The 10 years MFS rates were 68% (95%CI: 59-78%) and 85% (95%CI: 81-91%) in patients with FGFR1-gained and FGFR1-normal tumors respectively (HR: 2.51, 95%CI:1.56-4.01, p=0.0001). The 10 years MFS rates were 72% (95%CI:65%-83%) and 83% (95%CI: 77-87%) in patients with ZNF217-gained and ZNF217-normal tumors (HR: 1.79, 95%CI:1.12-2.86, p=0.013). In a multivariate analysis, FGFR1-gain (HR: 2.45, 95%CI:1.42-4.22, p=0.0012) and ZNF217-gain (HR:1.78, 95%CI:1.00-3.17, p=0.049) were associated with a higher likelihood of metastases and/or death. The 10 MFS rate was 88% (95%CI: 83-94%) for patients who presented FGFR1- and ZNF217-normal tumor (n=191), and 71% (95%CI: 66-76%) in patients presenting FGFR1 and/or ZNF217 gene gain. Conclusion: Using samples prospectively collected in a randomized trial, this study validates the prognostic value of FGFR1- and ZNF217- copy numbers in patients who present HR+/Her2- early breast cancer. Exploratory analyses on copy number alterations, together with targeted sequencing are ongoing and will be presented. Citation Format: Andre F, Penault Llorca F, Carene D, Roche H, Delaloge S, Lacroix L, Scott V, Richon C, Lacroix-Ticrit M, Lemonnier J, Michiels S. FGFR1 / ZNF217 copy numbers and outcome in patients with node positive, HR+/Her2- early breast cancer: A genomic analysis of PACS04 trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD4-10.

Progranulin modulates cholangiocarcinoma cell proliferation, apoptosis, and motility via the PI3K/pAkt pathway.

Progranulin (PGRN) is a growth factor normally expressed in rapidly cycling epithelial cells for growth, differentiation, and motility. Several studies have shown the association of PGRN overexpression with the progression of numerous malignancies, including cholangiocarcinoma (CCA). However, the underlying mechanisms on how PGRN modulates CCA cell proliferation and motility is not clear. In this study, we investigated the prognostic significance of PGRN expression in human CCA tissue and the mechanisms of PGRN modulation of CCA cell proliferation and motility. We found that CCA tissues with high PGRN expression were correlated with poor prognosis and likelihood of metastasis. PGRN knockdown KKU-100 and KKU-213 cells demonstrated a reduced rate of proliferation and colony formation and decreased levels of phosphatidyl inositol-3-kinase (PI3K) and phosphorylated Akt (pAkt) proteins. Accumulation of cells at the G1 phase was observed and was accompanied by a reduction of cyclin D1 and CDK4 protein levels. Knockdown cells also induced apoptosis by increasing the Bax-to-Bcl-2 ratio. Increased cell apoptosis was confirmed by annexin V-FITC/PI staining. Moreover, suppression of PGRN reduced CCA cell migration and invasion in vitro. Investigating the biomarkers in epithelial–mesenchymal transition (EMT) revealed a decrease in the expression of vimentin, snail, and metalloproteinase-9. In conclusion, our findings imply that PGRN modulates cell proliferation by dysregulating the G1 phase, inhibiting apoptosis, and that it plays a role in the EMT affecting CCA cell motility, possibly via the PI3K/pAkt pathway.

Establishment and Characterization of New Canine and Feline Osteosarcoma Primary Cell Lines.

Osteosarcomas are the most abundant form of bone malignancies in multiple species. Canine osteosarcomas are considered a valuable model for human osteosarcomas because of their similar features. Feline osteosarcomas, on the other hand, are rarely studied but have interesting characteristics, such as a better survival prognosis than dogs or humans, and less likelihood of metastasis. To enable experimental approaches to study these differences we have established five new canine osteosarcoma cell lines out of three tumors, COS_1186h, COS_1186w, COS_1189, and COS_1220, one osteosarcoma-derived lung metastasis, COS_1033, and two new feline osteosarcoma cell lines, FOS_1077 and FOS_1140. Their osteogenic and neoplastic origin, as well as their potential to produce calcified structures, was determined by the markers osteocalcin, osteonectin, tissue unspecific alkaline phosphatase, p53, cytokeratin, vimentin, and alizarin red. The newly developed cell lines retained most of their markers in vitro but only spontaneously formed spheroids produced by COS_1189 showed calcification in vitro.

The way forward for big data analysis in ophthalmology and medicine

It was the best of times; it was the worst of times. It was the season of population medicine; it was the season of personalized medicine—or was it? Charles Dickens’ fictional depiction of late eighteenth century France walked a tense line that masterfully narrated the untenable socioeconomic disparity of its day. He described the forces that inevitably led to the French revolution. Today in the world of medicine we are on the verge of similar untenable tension. Unravelling of the human genome was indeed an epochal event that brought with it the promise of personalized medicine. Thirteen years later, this is a promise that is certainly yet to be fulfilled. We are unable to bear the massive weight of the unmet promise of personalized medicine. It is therefore little surprise that any glimmers of its potential realization get great attention and scrutiny. One such glimmer is the work of Dr. J. William Harbour and colleagues in which they have correlated gene expression profiles with prognosis in ocular melanoma (1). They classified (2) tumor gene expression profiles into two classes, those associated with a higher likelihood of metastasis and those associated with a lower likelihood of metastasis. Their clinically-relevant result is an example that rekindles hope that our massive investment in unravelling the human genome may yet yield a return. Our team at Quantum Lucid Research Laboratories consists of ophthalmologists, mathematicians, computer scientists, physicists, and engineers, and has a unique appreciation for how such work bridges ostensibly disparate worlds. Data from the human genome project is an example of big data. Other examples of big data include the troves of imaging and clinical laboratory data which we are accumulating in our health centers and other institutions. It is vital that such big data not lay dormant, but instead be translated into better means for diagnosing and treating disease.

Cancer: Organ-seeking vesicles.

An analysis reveals that cancer cells remotely prepare distant sites for tumour spread in an organ-specific manner, by deploying organ-seeking extracellular vesicles. See Article p.329 How do cancer cells choose the next organ to target? David Lyden and colleagues show that extracellular vesicles (exosomes) that originate from tumour cells can preferentially fuse with specific resident cells of the target organs — lung, liver and brain — to prepare the site of metastasis. At a molecular level, expression of distinct combinations of integrin proteins on exosomes seems to mediate their targeting to one of the three organs. By blocking these integrins, the authors could reduce the uptake of the associated exosomes by the target organs and so the likelihood of metastasis. Moreover, the exosomal integrins could be used to predict organ-specific metastasis in cancer patients.

The likelihood of metastases in equidae

The likelihood of metastases in equidae

Large-scale molecular characterization and analysis of gastric cancer.

The recent effort by The Cancer Genome Atlas (TCGA) Network has revealed that gastric cancer, which is a leading cause of cancer-related deaths worldwide with a 5-year survival rate less than 25%, is a much more heterogeneous disease than previously thought. And yet, conventional treatment approaches and clinical trials have assumed it is a single disease. Although it is well known that under the microscope, gastric cancer cells appear quite different, the current classification scheme recognizes two main categories of gastric cancer: diffuse and intestinal. By integrating large-scale measurements of DNA, RNA, and proteins from 295 primary gastric tumors, the TCGA project found that there are four major subtypes of gastric cancer. The fact that these subtypes appear quite distinct on the molecular level suggests not only that the molecular processes driving tumorigenesis can vary among patients but also that the treatments may have to be tailored based on the subtype of tumor a patient has. This molecular stratification of patients, enabled by large-scale molecular characterization, is a significant step towards personalized therapy. The data that are generated from tumors in the TCGA project are not only very large in terms of volume, but, perhaps even more importantly, highly heterogeneous. Six different molecular analysis technologies were used for the molecular characterization of gastric cancer. These technologies provided information on DNA mutations, amplifications or deletions of gene sequences, epigenetic modifications of DNA, and levels of mRNA, microRNA, and proteins. Additionally, coded clinical information on pathology, histology, tumor characteristics, and other relevant data on each patient was collected. The computational challenge is how to integrate all this information not only to see broad differences among tumors but also to identify strong statistical associations among all these molecular and clinical data. Such associations may provide clues to how molecular systems in cancer cells are disrupted in different subtypes of gastric cancer and what treatment strategies may be most effective. For example, one of the four subtypes is characterized by the presence of the Epstein-Barr virus (EBV). Patients having tumors of this subtype tend to also have mutations in the PIK3CA pathway, extreme DNA hypermethylation, and extra copies of PD-L1 and PD-L2 genes, which are suppressors of immune response. These findings suggest that inhibitors of the PI3-K pathway may be of potential use for this subtype of gastric cancer. Further, PD-L1/2 antagonists may help promote immune destruction of the tumor. Another example of a statistical association that may have clinical use is the finding that frequent mutations in a gene called RHOA occur predominantly in the subtype of gastric cancer termed “genomically stable,” which is characterized by the lack of high levels of aneuploidy and are predominantly diffuse-type tumors. These subtypes of tumors have a higher likelihood of metastasis and are more invasive. It is known that the gene product of RHOA interacts with other proteins to alter cellular shape and motility, which are important for tumor growth. This protein or pathway may be an important therapeutic target for the genomically stable subtype of gastric cancer. The large-scale statistical analysis of the data revealed numerous other prevalent associations among factors, such as age at diagnosis, anatomic region of the stomach where the tumor occurs, gender, mutation status of genes such as TP53, and other tumor or patient characteristics. Although identifying such relationships in heterogeneous cancer data is important for the initial discovery process, much work lies ahead to functionally characterize the molecular aberrations in cancer and to develop and test effective targeted therapies. The ever-increasing volume and complexity of molecular data from cancer, exemplified by the TCGA project, calls for more sophisticated analytical approaches that can detect multivariate relationships in heterogeneous data and map that information onto the existing body of knowledge of the structure of molecular networks that govern all cellular processes. Other large-scale molecular characterization projects, such as the ENCyclopedia Of DNA Elements (ENCODE) and the Genomics of Drug Sensitivity in Cancer, are producing highly complementary data that will allow scientists to paint a more complete picture of how molecular regulatory processes are disrupted in cancer cells and what drugs may be effective in targeting a cancer's weaknesses. This first large-scale molecular characterization and analysis of gastric cancer undertaken by the TCGA project takes us one step closer toward helping patients suffering from this deadly type of cancer.