Antibodies against CD47, which block tumor cell CD47 interactions with macrophage signal regulatory protein-α, have been shown to decrease tumor size in hematological and epithelial tumor models by interfering with the protection from phagocytosis by macrophages that intact CD47 bestows upon tumor cells. Leiomyosarcoma (LMS) is a tumor of smooth muscle that can express varying levels of colony-stimulating factor-1 (CSF1), the expression of which correlates with the numbers of tumor-associated macrophages (TAMs) that are found in these tumors. We have previously shown that the presence of TAMs in LMS is associated with poor clinical outcome and the overall effect of TAMs in LMS therefore appears to be protumorigenic. However, the use of inhibitory antibodies against CD47 offers an opportunity to turn TAMs against LMS cells by allowing the phagocytic behavior of resident macrophages to predominate. Here we show that interference with CD47 increases phagocytosis of two human LMS cell lines, LMS04 and LMS05, in vitro. In addition, treatment of mice bearing subcutaneous LMS04 and LMS05 tumors with a novel, humanized anti-CD47 antibody resulted in significant reductions in tumor size. Mice bearing LMS04 tumors develop large numbers of lymph node and lung metastases. In a unique model for neoadjuvant treatment, mice were treated with anti-CD47 antibody starting 1 wk before resection of established primary tumors and subsequently showed a striking decrease in the size and number of metastases. These data suggest that treatment with anti-CD47 antibodies not only reduces primary tumor size but can also be used to inhibit the development of, or to eliminate, metastatic disease.
Leiomyosarcoma (LMS) is a malignant, soft-tissue tumor for which few effective therapies exist. Previously, we showed that there are three molecular subtypes of LMS. Here, we analyzed genes differentially expressed in each of the three LMS subtypes as compared to benign leiomyomas and then used the Connectivity Map (cmap) to calculate enrichment scores for the 1309 cmap drugs in order to identify candidate molecules with the potential to induce a benign, leiomyoma-like phenotype in LMS cells. 11 drugs were selected and tested for their ability to inhibit the growth of three human LMS cell lines. We identified two drugs with in vitro efficacy against LMS, one of which had a strongly negative enrichment score (Cantharidin) and the other of which had a strongly positive enrichment score (MG-132). Given MG-132's strong inhibitory effect on LMS cell viability, we hypothesized that LMS cells may be sensitive to treatment with other proteasome inhibitors and demonstrated that bortezomib, a clinically-approved proteasome inhibitor not included in the original cmap screen, potently inhibited the viability of the LMS cell lines. These findings suggest that systematically linking LMS subtype-specific expression signatures with drug-associated expression profiles represents a promising approach for the identification of new drugs for LMS.
We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.
ProExC expression has been shown to perform similarly to p16 as an aid in the diagnosis of cervical dysplasia but has not been well characterized in head and neck squamous cell carcinomas (SCC). The purpose of this study is to determine whether ProExC performs similarly to p16 as a prognostic marker in oropharyngeal SCC and to evaluate the threshold of ProExC and p16 staining that correlates with survival. ProExC, p16, and human papillomavirus DNA in situ hybridization were performed on tissue microarray (TMA) cores and whole sections from 62 patients with oropharyngeal SCC. Sensitivity and specificity for high-risk HPV and correlation with overall survival (OS), cancer-specific survival (CSS), and time to distant metastasis (TDM) were calculated for ProExC and p16 at different thresholds. ProExC did not prove to be a robust marker. It showed strong correlation with OS at a 66% threshold on TMA cores, but correlation with OS was lost on whole sections. It also exhibited low sensitivity (53.7%) on TMA cores and low specificity on whole sections (65%). ProExC at a 33% threshold exhibited unacceptably low specificity and did not correlate with OS, CSS, or TDM. Sensitivity and specificity of p16 varied predictably with threshold: higher sensitivity and lower specificity with lower thresholds and vice versa for higher thresholds. p16 at a 50% threshold offers a balance between sensitivity and specificity, and correlates with OS, CSS, and TDM on whole sections; correlation with TDM is lost on TMA cores. These findings indicate that ProExC does not perform well enough to be used as a prognostic marker in oropharyngeal SCC. p16 should be used and scored as positive when at least half the tumor is strongly stained.
In recent decades, epidemiology, public health, and medical sciences have been increasingly compartmentalized into narrower disciplines. The authors recognize the value of integration of divergent scientific fields in order to create new methods, concepts, paradigms, and knowledge. Herein they describe the recent emergence of molecular pathological epidemiology (MPE), which represents an integration of population and molecular biologic science to gain insights into the etiologies, pathogenesis, evolution, and outcomes of complex multifactorial diseases. Most human diseases, including common cancers (such as breast, lung, prostate, and colorectal cancers, leukemia, and lymphoma) and other chronic diseases (such as diabetes mellitus, cardiovascular diseases, hypertension, autoimmune diseases, psychiatric diseases, and some infectious diseases), are caused by alterations in the genome, epigenome, transcriptome, proteome, metabolome, microbiome, and interactome of all of the above components. In this era of personalized medicine and personalized prevention, we need integrated science (such as MPE) which can decipher diseases at the molecular, genetic, cellular, and population levels simultaneously. The authors believe that convergence and integration of multiple disciplines should be commonplace in research and education. We need to be open-minded and flexible in designing integrated education curricula and training programs for future students, clinicians, practitioners, and investigators.
Soft-tissue sarcomas are a group of malignant tumours whose clinical management is complicated by morphological heterogeneity, inadequate molecular markers and limited therapeutic options. Receptor tyrosine kinases (RTKs) have been shown to play important roles in cancer, both as therapeutic targets and as prognostic biomarkers. An initial screen of gene expression data for 48 RTKs in 148 sarcomas showed that ROR2 was expressed in a subset of leiomyosarcoma (LMS), gastrointestinal stromal tumour (GIST) and desmoid-type fibromatosis (DTF). This was further confirmed by immunohistochemistry (IHC) on 573 tissue samples from 59 sarcoma tumour types. Here we provide evidence that ROR2 expression plays a role in the invasive abilities of LMS and GIST cells in vitro. We also show that knockdown of ROR2 significantly reduces tumour mass in vivo using a xenotransplantation model of LMS. Lastly, we show that ROR2 expression, as measured by IHC, predicts poor clinical outcome in patients with LMS and GIST, although it was not independent of other clinico-pathological features in a multivariate analysis, and that ROR2 expression is maintained between primary tumours and their metastases. Together, these results show that ROR2 is a useful prognostic indicator in the clinical management of these soft-tissue sarcomas and may represent a novel therapeutic target.
Current clinical judgment in bladder cancer (BC) relies primarily on pathological stage and grade. We investigated whether a molecular classification of tumor cell differentiation, based on a developmental biology approach, can provide additional prognostic information. Exploiting large preexisting gene-expression databases, we developed a biologically supervised computational model to predict markers that correspond with BC differentiation. To provide mechanistic insight, we assessed relative tumorigenicity and differentiation potential via xenotransplantation. We then correlated the prognostic utility of the identified markers to outcomes within gene expression and formalin-fixed paraffin-embedded (FFPE) tissue datasets. Our data indicate that BC can be subclassified into three subtypes, on the basis of their differentiation states: basal, intermediate, and differentiated, where only the most primitive tumor cell subpopulation within each subtype is capable of generating xenograft tumors and recapitulating downstream populations. We found that keratin 14 (KRT14) marks the most primitive differentiation state that precedes KRT5 and KRT20 expression. Furthermore, KRT14 expression is consistently associated with worse prognosis in both univariate and multivariate analyses. We identify here three distinct BC subtypes on the basis of their differentiation states, each harboring a unique tumor-initiating population.
BACKGROUND: Molecular characterization of tumors has been critical for identifying important genes in cancer biology and for improving tumor classification and diagnosis. Long non-coding RNAs, as a new, relatively unstudied class of transcripts, provide a rich opportunity to identify both functional drivers and cancer-type-specific biomarkers. However, despite the potential importance of long non-coding RNAs to the cancer field, no comprehensive survey of long non-coding RNA expression across various cancers has been reported.
RESULTS: We performed a sequencing-based transcriptional survey of both known long non-coding RNAs and novel intergenic transcripts across a panel of 64 archival tumor samples comprising 17 diagnostic subtypes of adenocarcinomas, squamous cell carcinomas and sarcomas. We identified hundreds of transcripts from among the known 1,065 long non-coding RNAs surveyed that showed variability in transcript levels between the tumor types and are therefore potential biomarker candidates. We discovered 1,071 novel intergenic transcribed regions and demonstrate that these show similar patterns of variability between tumor types. We found that many of these differentially expressed cancer transcripts are also expressed in normal tissues. One such novel transcript specifically expressed in breast tissue was further evaluated using RNA in situ hybridization on a panel of breast tumors. It was shown to correlate with low tumor grade and estrogen receptor expression, thereby representing a potentially important new breast cancer biomarker.
CONCLUSIONS: This study provides the first large survey of long non-coding RNA expression within a panel of solid cancers and also identifies a number of novel transcribed regions differentially expressed across distinct cancer types that represent candidate biomarkers for future research.