BackgroundAn immune active cancer phenotype typified by a T helper 1 (Th-1) immune response has been associated with increased responsiveness to immunotherapy and favorable prognosis in some but not all cancer types. The reason of this differential prognostic connotation remains unknown.MethodsTo explore the contextual prognostic value of cancer immune phenotypes, we applied a multimodal pan-cancer analysis among 31 different histologies (9282 patients), encompassing immune and oncogenic transcriptomic analysis, mutational and neoantigen load and copy number variations.ResultsWe demonstrated that the favorable prognostic connotation conferred by the presence of a Th-1 immune response was abolished in tumors displaying specific tumor-cell intrinsic attributes such as high transforming growth factor-beta (TGF-β) signaling and low proliferation capacity. This observation was independent of mutation rate. We validated this observation in the context of immune checkpoint inhibition. WNT-βcatenin, barrier molecules, Notch, hedgehog, mismatch repair, telomerase activity and AMPK signaling were the pathways most coherently associated with an immune silent phenotype together with mutations of driver genes includingIDH1/2, FOXA2, HDAC3, PSIP1, MAP3K1, KRAS, NRAS, EGFR, FGFR3, WNT5AandIRF7.ConclusionsThis is the first systematic study demonstrating that the prognostic and predictive role of a bona fide favorable intratumoral immune response is dependent on the disposition of specific oncogenic pathways. This information could be used to refine stratification algorithms and prioritize hierarchically relevant targets for combination therapies.

More than one million prostate biopsies are performed in the United States every year. A failure to find cancer is not definitive in a significant percentage of patients due to the presence of equivocal structures or continuing clinical suspicion. We have identified gene expression changes in stroma that can detect tumor nearby. We compared gene expression profiles of 13 biopsies containing stroma near tumor and 15 biopsies from volunteers without prostate cancer. About 3,800 significant expression changes were found and thereafter filtered using independent expression profiles to eliminate possible age-related genes and genes expressed at detectable levels in tumor cells. A stroma-specific classifier for nearby tumor was constructed on the basis of 114 candidate genes and tested on 364 independent samples including 243 tumor-bearing samples and 121 nontumor samples (normal biopsies, normal autopsies, remote stroma, as well as stroma within a few millimeters of tumor). The classifier predicted the tumor status of patients using tumor-free samples with an average accuracy of 97% (sensitivity ¼ 98% and specificity ¼ 88%) whereas classifiers trained with sets of 100 randomly generated genes had no diagnostic value. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorizing the presence of tumor in patients when a prostate sample is derived from near the tumor but does not contain any recognizable tumor. Cancer Res; 71(7); 2476-87. Ó2011 AACR.

Epigenetic transcriptional regulation plays an important role in the life cycle of human papillomaviruses (HPVs) and the carcinogenic progression of anogenital HPV associated lesions. We performed a study designed to assess the methylation status of the HPV-18 genome, specifically of the late L1 gene, the adjacent long control region (LCR), and part of the E6 oncogene in cervical specimens with a range of pathological diagnoses. In asymptomatic infections and infections with precancerous (precursor) lesions, HPV-18 DNA was mostly unmethylated, with the exception of four samples where hypermethylation of L1 was detected. In contrast, L1 sequences were strongly methylated in all cervical carcinomas, while the LCR and E6 remained unmethylated. HeLa cells, derived from a cervical adenocarcinoma, contain chromosomally integrated HPV-18 genomes. We found that L1 is hypermethylated in these cells, while the LCR and E6 are unmethylated. Treatment of HeLa cells with the methylation inhibitor 5-Aza-2'-deoxycytidine (5-Aza-CdR) led to the expected reduction of L1 methylation. After removal of 5-Aza-CdR, L1 methylation resumed and exceeded pretreatment levels. Unexpectedly, the LCR and E6 also became methylated under these conditions, albeit at lower levels than L1. We hypothesize that L1 is preferentially methylated after integration of the HPV genome into the cellular DNA, possibly since linearization prohibits its normal transcription, while the enhancer and promoter may be protected from methylation by transcription factors. Since our data suggest that HPV-18 L1 methylation can only be detected in carcinomas, except in some few precancerous lesions and asymptomatic infections, L1 methylation may constitute a powerful molecular marker for detecting this important step of neoplastic progression.

Anti-cancer immunotherapy is encountering its own checkpoint. Responses are dramatic and long lasting but occur in a subset of tumors and are largely dependent upon the pre-existing immune contexture of individual cancers. Available data suggest that three landscapes best define the cancer microenvironment: immune-active, immune-deserted and immune-excluded. This trichotomy is observable across most solid tumors (although the frequency of each landscape varies depending on tumor tissue of origin) and is associated with cancer prognosis and response to checkpoint inhibitor therapy (CIT). Various gene signatures (e.g. Immunological Constant of Rejection - ICR and Tumor Inflammation Signature - TIS) that delineate these landscapes have been described by different groups. In an effort to explain the mechanisms of cancer immune responsiveness or resistance to CIT, several models have been proposed that are loosely associated with the three landscapes. Here, we propose a strategy to integrate compelling data from various paradigms into a “Theory of Everything”. Founded upon this unified theory, we also propose the creation of a task force led by the Society for Immunotherapy of Cancer (SITC) aimed at systematically addressing salient questions relevant to cancer immune responsiveness and immune evasion. This multidisciplinary effort will encompass aspects of genetics, tumor cell biology, and immunology that are pertinent to the understanding of this multifaceted problem.Electronic supplementary materialThe online version of this article (10.1186/s40425-018-0355-5) contains supplementary material, which is available to authorized users.

The L1 gene of human papillomavirus-18 (HPV-18) is consistently hypermethylated in cervical carcinomas, but frequently hypo- or unmethylated in exfoliated cells from asymptomatic patients. In precancerous lesions, L1 is sporadically hypermethylated, correlating with the severity of the neoplasia. In order to explore the potential of using L1 methylation as a workable biomarker for carcinogenic progression of HPV-18 infections in routinely taken samples, our aim was to develop methylation-detection techniques that were sensitive and rapid without being overly complex technically. Therein, we developed a methylation-specific PCR (MSP) through the design of primer sets that specifically amplify either methylated or unmethylated HPV-18 L1 DNA within bisulfite-modified sample DNA. Amplification of unmethylated and in vitro methylated HPV-18 DNA by MSP resulted in 2500 copies of either of the two L1 DNA species being detected, a satisfactory sensitivity considering that bisulfite treatment leads to the fragmentation of about 99% of sample DNA. The primers proved specific and did not generate false positive results at concentrations exceeding the lowest limit of detection by a factor of 400. DNA from carcinomas yielded PCR signals only with the methylation-specific primers, and not with primers specific for unmethylated L1 genes. The inverse result was obtained with DNA from precursor lesions that contained only hypomethylated DNA. High-grade precursor lesions and carcinomas that contained hyper- as well as hypomethylated L1 DNA yielded PCR signals with both primers. By developing a fluorescence based real-time PCR, we quantitatively analyzed samples with in vitro methylated and unmethylated L1 DNA, and could distinguish clinical samples with hyper- and hypomethylated DNA or mixtures of both DNAs. The methylation-specific and real-time PCR techniques permitted efficient HPV-18 L1 methylation analyses and open the door for larger-scale clinical studies where the utility of methylation status to predict the progression of HPV-18 infection and HPV-18 associated lesions is assessed.

Mutations in the Drosophila variable nurse cells (vnc) gene result in female sterility and oogenesis defects, including egg chambers with too many or too few nurse cells. We show that vnc corresponds to Arrest Defective1 (Ard1) and encodes the catalytic subunit of NatA, the major N-terminal acetyl-transferase complex. While N-terminal acetylation is one of the most prevalent covalent protein modifications in eukaryotes, analysis of its role in development has been challenging since mutants that compromise NatA activity have not been described in any multicellular animal. Our data show that reduced ARD1 levels result in pleiotropic oogenesis defects including abnormal cyst encapsulation, desynchronized cystocyte division, disrupted nurse cell chromosome dispersion, and abnormal chorion patterning, consistent with the wide range of predicted NatA substrates. Furthermore, we find that loss of Ard1 affects cell survival/ proliferation and is lethal for the animal, providing the first demonstration that this modification is essential in higher eukaryotes. Developmental Dynamics 239:2813-2827,

Over 1 million prostate biopsies are performed in the U.S. every year. A failure to find cancer is not definitive in a significant percentage of patients due to the presence of equivocal structures or continuing clinical suspicion. We have identified gene expression changes in stroma that can detect tumor nearby. We compared gene expression profiles of 13 biopsies containing stroma near tumor and 15 biopsies from volunteers without prostate cancer. More than a thousand significant expression changes were found and thereafter filtered using large numbers of other expression profiles to eliminate possible age-related genes and genes expressed at detectable levels in tumor cells. A stroma-specific classifier was constructed based on 114 candidate genes and tested on 364 independent samples, including 243 tumor-bearing samples and 121 non-tumor samples (normal biopsies, normal autopsies, remote stroma, as well as stroma within a few millimeters of tumor). The classifier predicted the tumor status of patients using tumor-free samples with an average accuracy of 97.2% (sensitivity = 97.9% and specificity = 88.0%) whereas classifiers trained with sets of 100 randomly generated genes had no diagnostic value. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorizing the presence of tumor in patients when a prostate sample is derived from near the tumor but does not contain any recognizable tumor.

Background The balance between immune-stimulatory and immune-suppressive mechanisms in the tumour microenvironment is associated with tumour rejection and can predict the efficacy of immune checkpoint-inhibition therapies. Methods We consider the observed differences between the transcriptional programmes associated with cancer types where the levels of immune infiltration predict a favourable prognosis versus those in which the immune infiltration predicts an unfavourable prognosis and defined a score named Mediators of Immune Response Against Cancer in soLid microEnvironments (MIRACLE). MIRACLE deconvolves T cell infiltration, from inhibitory mechanisms, such as TGFβ, EMT and PI3Kγ signatures. Results Our score outperforms current state-of-the-art immune signatures as a predictive marker of survival in TCGA (n = 9305, HR: 0.043, p value: 6.7 × 10−36). In a validation cohort (n = 7623), MIRACLE predicts better survival compared to other immune metrics (HR: 0.1985, p value: 2.73 × 10−38). MIRACLE also predicts response to checkpoint-inhibitor therapies (n = 333). The tumour-intrinsic factors inversely associated with the reported score such as EGFR, PRKAR1A and MAP3K1 are frequently associated with immune-suppressive phenotypes. Conclusions The association of cancer outcome with the level of infiltrating immune cells is mediated by the balance of activatory and suppressive factors. MIRACLE accounts for this balance and predicts favourable cancer outcomes.