Human endogenous retroviruses (HERV) form a substantial part of the human genome, but mostly remain transcriptionally silent under strict epigenetic regulation, yet can potentially be reactivated by malignant transformation or epigenetic therapies. Here, we evaluate the potential for T cell recognition of HERV elements in myeloid malignancies by mapping transcribed HERV genes and generating a library of 1169 potential antigenic HERV-derived peptides predicted for presentation by 4 HLA class I molecules. Using DNA barcode-labeled MHC-I multimers, we find CD8+ T cell populations recognizing 29 HERV-derived peptides representing 18 different HERV loci, of which HERVH-5, HERVW-1, and HERVE-3 have more profound responses; such HERV-specific T cells are present in 17 of the 34 patients, but less frequently in healthy donors. Transcriptomic analyses reveal enhanced transcription of the HERVs in patients; meanwhile DNA-demethylating therapy causes a small and heterogeneous enhancement in HERV transcription without altering T cell recognition. Our study thus uncovers T cell recognition of HERVs in myeloid malignancies, thereby implicating HERVs as potential targets for immunotherapeutic therapies.

Formalin-fixed paraffin-embedded tissue, the most common tissue specimen stored in clinical practice, presents challenges in the analysis due to formalin-induced artifacts. Here, we present Strand Orientation Bias Detector (SOBDetector), a flexible computational platform compatible with all the common somatic SNV-calling pipelines, designed to assess the probability whether a given detected mutation is an artifact. The underlying predictor mechanism is based on the posterior distribution of a Bayesian logistic regression model trained on The Cancer Genome Atlas whole exomes. SOBDetector is a freely available cross-platform program, implemented in Java 1.8.

Mutation-derived neoantigens are important targets for T cell-mediated reactivity toward tumors and, due to their unique tumor expression, an attractive target for immunotherapy. Neoepitope-specific T cells have been detected across a number of solid cancers with high mutational burden tumors, but neoepitopes have been mostly selected from single nucleotide variations (SNVs), and little focus has been given to neoepitopes derived from in-frame and frameshift indels, which might be equally important and potentially highly immunogenic. Clear cell renal cell carcinomas (ccRCCs) are medium-range mutational burden tumors with a high pan-cancer proportion of frameshift mutations. In this study, the mutational landscape of tumors from six RCC patients was analyzed by whole-exome sequencing (WES) of DNA from tumor fragments (TFs), autologous tumor cell lines (TCLs), and tumor-infiltrating lymphocytes (TILs, germline reference). Neopeptides were predicted using MuPeXI, and patient-specific peptide-MHC (pMHC) libraries were created for all neopeptides with a rank score < 2 for binding to the patient's HLAs. T cell recognition toward neoepitopes in TILs was evaluated using the high-throughput technology of DNA barcode-labeled pMHC multimers. The patient-specific libraries consisted of, on average, 258 putative neopeptides (range, 103-397, n = 6). In four patients, WES was performed on two different sources (TF and TCL), whereas in two patients, WES was performed only on TF. Most of the peptides were predicted from both sources. However, a fraction was predicted from one source only. Among the total predicted neopeptides, 16% were derived from frameshift indels. T cell recognition of 52 neoepitopes was detected across all patients (range, 4-18, n = 6) and spanning two to five HLA restrictions per patient. On average, 21% of the recognized neoepitopes were derived from frameshift indels (range, 0-43%, n = 6). Thus, frameshift indels are equally Hansen et al. Neoepitopes in ccRCC represented in the pool of immunogenic neoepitopes as SNV-derived neoepitopes. This suggests the importance of a broad neopeptide prediction strategy covering multiple sources of tumor material, and including different genetic alterations. This study, for the first time, describes the T cell recognition of frameshift-derived neoepitopes in RCC and determines their immunogenic profile.

BackgroundHuman milk oligosaccharides (HMOs) have important biological functions for a healthy development in early life.ObjectiveThis study aimed to investigate gut maturation effects of an infant formula containing five HMOs (2′-fucosyllactose, 2′,3-di-fucosyllactose, lacto-N-tetraose, 3′-sialyllactose, and 6′-sialyllactose).MethodsIn a multicenter study, healthy infants (7–21 days old) were randomly assigned to a standard cow’s milk-based infant formula (control group, CG); the same formula with 1.5 g/L HMOs (test group 1, TG1); or with 2.5 g/L HMOs (test group 2, TG2). A human milk-fed group (HMG) was enrolled as a reference. Fecal samples collected at baseline (n∼150/formula group; HMG n = 60), age 3 (n∼140/formula group; HMG n = 65) and 6 (n∼115/formula group; HMG n = 60) months were analyzed for microbiome (shotgun metagenomics), metabolism, and biomarkers.ResultsAt both post-baseline visits, weighted UniFrac analysis indicated different microbiota compositions in the two test groups (TGs) compared to CG (P &lt; 0.01) with coordinates closer to that of HMG. The relative abundance of Bifidobacterium longum subsp. infantis (B. infantis) was higher in TGs vs. CG (P &lt; 0.05; except at 6 months: TG2 vs. CG P = 0.083). Bifidobacterium abundance was higher by ∼45% in TGs vs. CG at 6-month approaching HMG. At both post-baseline visits, toxigenic Clostridioides difficile abundance was 75–85% lower in TGs vs. CG (P &lt; 0.05) and comparable with HMG. Fecal pH was significantly lower in TGs vs. CG, and the overall organic acid profile was different in TGs vs. CG, approaching HMG. At 3 months, TGs (vs. CG) had higher secretory immunoglobulin A (sIgA) and lower alpha-1-antitrypsin (P &lt; 0.05). At 6 months, sIgA in TG2 vs. CG remained higher (P &lt; 0.05), and calprotectin was lower in TG1 (P &lt; 0.05) vs. CG.ConclusionInfant formula with a specific blend of five HMOs supports the development of the intestinal immune system and gut barrier function and shifts the gut microbiome closer to that of breastfed infants with higher bifidobacteria, particularly B. infantis, and lower toxigenic Clostridioides difficile.Clinical Trial Registration[https://clinicaltrials.gov/ct2/show/], identifier [NCT03722550].

Human milk oligosaccharides (HMOs) are structurally diverse oligosaccharides present in breast milk, supporting the development of the gut microbiota and immune system. Previously, 2-HMO (2'fucosyllactose, lacto-N-neotetraose) compared to control formula feeding was associated with reduced risk of lower respiratory tract infections (LRTIs), in part linked to lower acetate and higher bifidobacteria proportions. Here, our objective was to gain further insight into additional molecular pathways linking the 2-HMO formula feeding and LRTI mitigation. From the same trial, we measured the microbiota composition and 743 known biochemical species in infant stool at 3 months of age using shotgun metagenomic sequencing and untargeted mass spectrometry metabolomics. We used multivariate analysis to identify biochemicals associated to 2-HMO formula feeding and LRTI and integrated those findings with the microbiota compositional data. Three molecular pathways stood out: increased gamma-glutamylation and N-acetylation of amino acids and decreased inflammatory signaling lipids. Integration of stool metagenomic data revealed some Bifidobacterium and Bacteroides species to be implicated. These findings deepen our understanding of the infant gut/microbiome co-metabolism in early life and provide evidence for how such metabolic changes may influence immune competence at distant mucosal sites such as the airways.

The observed risk reduction of acute respiratory infections (ARIs) among infants of secretor mothers during the predominant breastfeeding period is consistent with the hypothesis that fucosylated oligosaccharides in human milk contribute to protection against respiratory infections. Respiratory pathogens were only weak modulators of risk, and the nasopharyngeal microbiome did not influence ARI risk, suggesting that the associated protective effects of human milk oligosaccharides (HMOs) are not conveyed via changes in the nasopharyngeal microbiome.

Gene expression profiling has yielded important insights about tumor biology that may improve treatment decisions in patients. However, it is difficult to collect a specimen of pure tumor cells, and thus microarray measurements usually reflect the contribution of tumor cells as well as stromal and other normal cells. We applied unsupervised matrix factorization methods to gene expression data to derive several sets of co-expressed genes, or signatures, that together comprise a set of independent descriptors of breast tumors. Some of these signatures correspond to specific cell types (adipocytes, lymphocytes, fibroblasts), while others reflect well-known tumor-intrinsic expression programs (ER, ERBB2, proliferation). We confirmed the specificity of the signatures using expression data from purified normal cells and tumor cell lines, microdissected tumors, and bulk tumors with corresponding histological cellularity estimates. In several data sets, cell-type signatures were highly variable and anticorrelated with tumor-intrinsic signatures, confirming that variation in normal cell content is a potential source of measurement bias.Overall, these results provide an intuitive framework for the interpetation of tumor expression profiles and may lead to an improved understanding of the physiological mechanisms involved in tumor development. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1166.

Cisplatin-based chemotherapy promotes DNA inter- and intra-strand cross-links and is effective treatment in multiple cancer types, yet it is rarely used for first-line therapy of breast cancer. Cisplatin is an effective cytotoxic in BRCA1 mutant cancer cell lines and in breast and ovarian cancers with BRCA1 mutations, prompting speculation that defective DNA double-strand break repair is associated with cisplatin sensitivity. Furthermore, tumors with BRCA1 mutation are presumed to be defective in various aspects of DNA repair and also display increased levels of chromosomal instability. Thus, we hypothesized that the total number of chromosomal breakpoints in a specific tumor may reflect defective DNA repair and/or chromosomal instability, and may therefore be used as a predictor of cisplatin sensitivity. Supporting this relationship, we identified a correlation (r = 0.8, P = 0.08) between the total number of chromosomal breakpoints, estimated by the number of genomic regions showing allelic imbalance, and cisplatin sensitivity in five triple negative breast cancer cell lines. To validate this relationship in a clinical setting we compared the total number of chromosomal breakpoints to therapy response in a cisplatin treated breast cancer cohort. A total of 28 women with stage II or III ER-/PR-/HER2- breast cancer were treated with cisplatin in the neo-adjuvant setting followed by surgery and standard adjuvant chemotherapy. A core biopsy was obtained before treatment commenced, tumor cells were enriched by needle microdissection, and DNA was extracted for genotyping. As only limited amounts of DNA were available, we used a Molecular Inversion Probe assay (in collaboration with Affymetrix), which allowed us to genotype 42,000 SNPs with only 40 ng of starting DNA. We then estimated the total number of putative genomic breakpoints in 21 samples containing at least 75% tumor cells. We compared this summary genomic measure to the response rate as quantitated by the Miller-Payne score determined on the pathological specimen obtained at surgery. This genomic measure showed a remarkably accurate separation of patients by degree of response, correctly classifying 20 out of 21 patients (P &lt; 0.001).These results suggest that the total number of DNA breakpoints may be an accurate biomarker of breast cancers which may be sensitive to cisplatin treatment. The molecular explanations for these findings await further work. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 111.