Tumor-infiltrating leukocytes can either limit cancer growth or facilitate its spread. Diagnostic strategies that comprehensively assess the functional complexity of tumor immune infiltrates could ...have wide-reaching clinical value. In previous work we identified distinct immune gene signatures in breast tumors that reflect the relative abundance of infiltrating immune cells and exhibited significant associations with patient outcomes. Here we hypothesized that immune gene signatures agnostic to tumor type can be identified by de novo discovery of gene clusters enriched for immunological functions and possessing internal correlation structure conserved across solid tumors from different anatomic sites.
We assembled microarray expression datasets encompassing 5,295 tumors of the breast, colon, lung, ovarian and prostate. Unsupervised clustering methods were used to determine number and composition of gene clusters within each dataset. Immune-enriched gene clusters (signatures) identified by gene ontology enrichment were analyzed for internal correlation structure and conservation across tumors then compared against expression profiles of: 1) flow-sorted leukocytes from peripheral blood and 2) >300 cancer cell lines from solid and hematologic cancers. Cox regression analysis was used to identify signatures with significant associations with clinical outcome.
We identified nine distinct immune-enriched gene signatures conserved across all five tumor types. The signatures differentiated specific leukocyte lineages with moderate discernment overall, and naturally organized into six discrete groups indicative of admixed lineages. Moreover, seven of the signatures exhibit minimal and uncorrelated expression in cancer cell lines, suggesting that these signatures derive predominantly from infiltrating immune cells. All nine immune signatures achieved statistically significant associations with patient prognosis (p<0.05) in one or more tumor types with greatest significance observed in breast and skin cancers. Several signatures indicative of myeloid lineages exhibited poor outcome associations that were most apparent in brain and colon cancers.
These findings suggest that tumor infiltrating immune cells can be differentiated by immune-specific gene expression patterns that quantify the relative abundance of multiple immune infiltrates across a range of solid tumor types. That these markers of immune involvement are significantly associated with patient prognosis in diverse cancers suggests their clinical utility as pan-cancer markers of tumor behavior and immune responsiveness.
Mounting evidence supports a role for the immune system in breast cancer outcomes. The ability to distinguish highly immunogenic tumors susceptible to anti-tumor immunity from weakly immunogenic or ...inherently immune-resistant tumors would guide development of therapeutic strategies in breast cancer. Genomic, transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohorts were used to examine statistical associations between tumor mutational burden (TMB) and the survival of patients whose tumors were assigned to previously-described prognostic immune subclasses reflecting favorable, weak or poor immune-infiltrate dispositions (FID, WID or PID, respectively). Tumor immune subclasses were associated with survival in patients with high TMB (TMB-Hi, P < 0.001) but not in those with low TMB (TMB-Lo, P = 0.44). This statistical relationship was confirmed in the METABRIC cohort (TMB-Hi, P = 0.047; TMB-Lo, P = 0.39), and also found to hold true in the more-indolent Luminal A tumor subtype (TMB-Hi, P = 0.011; TMB-Lo, P = 0.91). In TMB-Hi tumors, the FID subclass was associated with prolonged survival independent of tumor stage, molecular subtype, age and treatment. Copy number analysis revealed the reproducible, preferential amplification of chromosome 1q immune-regulatory genes in the PID immune subclass. These findings demonstrate a previously unappreciated role for TMB as a determinant of immune-mediated survival of breast cancer patients and identify candidate immune-regulatory mechanisms associated with immunologically cold tumors. Immune subtyping of breast cancers may offer opportunities for therapeutic stratification.
We present a finely binned tomographic weak lensing analysis of the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) mitigating contamination to the signal from the presence of intrinsic ...galaxy alignments via the simultaneous fit of a cosmological model and an intrinsic alignment model. CFHTLenS spans 154 square degrees in five optical bands, with accurate shear and photometric redshifts for a galaxy sample with a median redshift of z
m = 0.70. We estimate the 21 sets of cosmic shear correlation functions associated with six redshift bins, each spanning the angular range of 1.5 < θ < 35 arcmin. We combine this CFHTLenS data with auxiliary cosmological probes: the cosmic microwave background with data from WMAP7, baryon acoustic oscillations with data from Baryon Oscillation Spectroscopic Survey and a prior on the Hubble constant from the Hubble Space Telescope distance ladder. This leads to constraints on the normalization of the matter power spectrum σ8 = 0.799 ± 0.015 and the matter density parameter Ωm = 0.271 ± 0.010 for a flat Λ cold dark matter (ΛCDM) cosmology. For a flat wCDM cosmology, we constrain the dark energy equation-of-state parameter w = −1.02 ± 0.09. We also provide constraints for curved ΛCDM and wCDM cosmologies. We find the intrinsic alignment contamination to be galaxy-type dependent with a significant intrinsic alignment signal found for early-type galaxies, in contrast to the late-type galaxy sample for which the intrinsic alignment signal is found to be consistent with zero.
Highlights • The Th-1 cancer phenotype is characterized by responsiveness to immunotherapy. • This phenotype is accompanied by activation of counter-regulatory mechanisms. • Tumor genetic program ...modulates the development of the Th-1 cancer phenotype. • Oncogenic pathways can be targeted to enhance the efficacy of cancer immunotherapy.
Context. The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope. It aims to image 1500 square degrees in four filters ...(ugri). The core science driver is mapping the large-scale matter distribution in the Universe, using weak lensing shear and photometric redshift measurements. Further science cases include galaxy evolution, Milky Way structure, detection of high-redshift clusters, and finding rare sources such as strong lenses and quasars. Aims. Here we present the third public data release and several associated data products, adding further area, homogenized photometric calibration, photometric redshifts and weak lensing shear measurements to the first two releases. Methods. A dedicated pipeline embedded in the Astro-WISE information system is used for the production of the main release. Modifications with respect to earlier releases are described in detail. Photometric redshifts have been derived using both Bayesian template fitting, and machine-learning techniques. For the weak lensing measurements, optimized procedures based on the THELI data reduction and lensfit shear measurement packages are used. Results. In this third data release an additional 292 new survey tiles (≈300 deg2) stacked ugri images are made available, accompanied by weight maps, masks, and source lists. The multi-band catalogue, including homogenized photometry and photometric redshifts, covers the combined DR1, DR2 and DR3 footprint of 440 survey tiles (44 deg2). Limiting magnitudes are typically 24.3, 25.1, 24.9, 23.8 (5σ in a 2′′ aperture) in ugri, respectively, and the typical r-band PSF size is less than 0.7′′. The photometric homogenization scheme ensures accurate colours and an absolute calibration stable to ≈2% for gri and ≈3% in u. Separately released for the combined area of all KiDS releases to date are a weak lensing shear catalogue and photometric redshifts based on two different machine-learning techniques.
Immunotherapy with checkpoint inhibitors is improving the outcomes of several cancers. However, only a subset of patients respond. Therefore, predictive biomarkers are critically needed to guide ...treatment decisions and develop approaches to the treatment of therapeutic resistance.
We compared bioenergetics of circulating immune cells and metabolomic profiles of plasma obtained at baseline from patients with melanoma treated with anti-PD-1 therapy. We also performed single-cell RNA sequencing (scRNAseq) to correlate transcriptional changes associated with metabolic changes observed in peripheral blood mononuclear cells (PBMC) and patient plasma.
Pretreatment PBMC from responders had a higher reserve respiratory capacity and higher basal glycolytic activity compared with nonresponders. Metabolomic analysis revealed that responder and nonresponder patient samples cluster differently, suggesting differences in metabolic signatures at baseline. Differential levels of specific lipid, amino acid, and glycolytic pathway metabolites were observed by response. Further, scRNAseq analysis revealed upregulation of T-cell genes regulating glycolysis. Our analysis showed that SLC2A14 (Glut-14; a glucose transporter) was the most significant gene upregulated in responder patients' T-cell population. Flow cytometry analysis confirmed significantly elevated cell surface expression of the Glut-14 in CD3+, CD8+, and CD4+ circulating populations in responder patients. Moreover, LDHC was also upregulated in the responder population.
Our results suggest a glycolytic signature characterizes checkpoint inhibitor responders; consistently, both ECAR and lactate-to-pyruvate ratio were significantly associated with overall survival. Together, these findings support the use of blood bioenergetics and metabolomics as predictive biomarkers of patient response to immune checkpoint inhibitor therapy.
Liver cancers, including hepatocellular carcinomas (HCCs), cholangiocarcinomas (CCs), and fibrolamellar HCCs (FL‐HCCs) are among the most common cancers worldwide and are associated with a poor ...prognosis. Investigations of genes important in liver cancers have focused on Sal‐like protein 4 (SALL4), a member of a family of zinc finger transcription factors. It is a regulator of embryogenesis, organogenesis, pluripotency, can elicit reprogramming of somatic cells, and is a marker of stem cells. We found it expressed in normal murine hepatoblasts, normal human hepatic stem cells, hepatoblasts and biliary tree stem cells, but not in mature parenchymal cells of liver or biliary tree. It was strongly expressed in surgical specimens of human HCCs, CCs, a combined hepatocellular and cholangiocarcinoma, a FL‐HCC, and in derivative, transplantable tumor lines in immune‐compromised hosts. Bioinformatics analyses indicated that elevated expression of SALL4 in tumors is associated with poor survival of HCC patients. Experimental manipulation of SALL4′s expression results in changes in proliferation versus differentiation in human HCC cell lines in vitro and in vivo in immune‐compromised hosts. Virus‐mediated gene transfer of SALL4 was used for gain‐ and loss‐of‐function analyses in the cell lines. Significant growth inhibition in vitro and in vivo, accompanied by an increase in differentiation occurred with down‐regulation of SALL4. Overexpression of SALL4 resulted in increased cell proliferation in vitro, correlating with an increase in expression of cytokeratin19 (CK19), epithelial cell adhesion molecules (EpCAM), and adenosine triphosphate (ATP)‐binding cassette‐G2 (ABCG2). Conclusion: SALL4′s expression is an indicator of stem cells, a prognostic marker in liver cancers, correlates with cell and tumor growth, with resistance to 5‐FU, and its suppression results in differentiation and slowed tumor growth. SALL4 is a novel therapeutic target for liver cancers. (HEPATOLOGY 2013)
Changes in iron regulation characterize the malignant state. However, the pathways that effect these changes and their specific impact on prognosis remain poorly understood. We capitalized on ...publicly available microarray datasets comprising 674 breast cancer cases to systematically investigate how expression of genes related to iron metabolism is linked to breast cancer prognosis. Of 61 genes involved in iron regulation, 49% were statistically significantly associated with distant metastasis-free survival. Cases were divided into test and training cohorts, and the supervised principal component method was used to stratify cases into risk groups. Optimal risk stratification was achieved with a model comprising 16 genes, which we term the iron regulatory gene signature (IRGS). Multivariable analysis revealed that the IRGS contributes information not captured by conventional prognostic indicators (HR = 1.61; 95% confidence interval: 1.16-2.24; P = 0.004). The IRGS successfully stratified homogeneously treated patients, including ER+ patients treated with tamoxifen monotherapy, both with (P = 0.006) and without (P = 0.03) lymph node metastases. To test whether multiple pathways were embedded within the IRGS, we evaluated the performance of two gene dyads with known roles in iron biology in ER+ patients treated with tamoxifen monotherapy (n = 371). For both dyads, gene combinations that minimized intracellular iron content anti-import: TFRC(Low)/HFE(High); or pro-export: SLC40A1 (ferroportin)(High)/HAMP(Low) were associated with favorable prognosis (P < 0.005). Although the clinical utility of the IRGS will require further evaluation, its ability to both identify high-risk patients within traditionally low-risk groups and low-risk patients within high-risk groups has the potential to affect therapeutic decision making.
We present cosmological constraints from 2D weak gravitational lensing by the large-scale structure in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) which spans 154 deg2 in five ...optical bands. Using accurate photometric redshifts and measured shapes for 4.2 million galaxies between redshifts of 0.2 and 1.3, we compute the 2D cosmic shear correlation function over angular scales ranging between 0.8 and 350 arcmin. Using non-linear models of the dark-matter power spectrum, we constrain cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. The best constraints from lensing alone are obtained for the small-scale density-fluctuations amplitude σ8 scaled with the total matter density Ωm. For a flat Λcold dark matter (ΛCDM) model we obtain σ8(Ωm/0.27)0.6 = 0.79 ± 0.03.
We combine the CFHTLenS data with 7-year Wilkinson Microwave Anisotropy Probe (WMAP7), baryonic acoustic oscillations (BAO): SDSS-III (BOSS) and a Hubble Space Telescope
distance-ladder prior on the Hubble constant to get joint constraints. For a flat ΛCDM model, we find Ωm = 0.283 ± 0.010 and σ8 = 0.813 ± 0.014. In the case of a curved wCDM universe, we obtain Ωm = 0.27 ± 0.03, σ8 = 0.83 ± 0.04, w
0 = −1.10 ± 0.15 and ΩK = 0.006+ 0.006
− 0.004.
We calculate the Bayesian evidence to compare flat and curved ΛCDM and dark-energy CDM models. From the combination of all four probes, we find models with curvature to be at moderately disfavoured with respect to the flat case. A simple dark-energy model is indistinguishable from ΛCDM. Our results therefore do not necessitate any deviations from the standard cosmological model.
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