Pilot clinical trial and phenotypic analysis in chemotherapy-pretreated, metastatic triple-negative breast cancer patients treated with oral TAK-228 and TAK-117 (PIKTOR) to increase DNA damage repair deficiency followed by cisplatin and nab paclitaxel.

BACKGROUND: A subset of triple-negative breast cancers (TNBCs) have homologous recombination deficiency with upregulation of compensatory DNA repair pathways. PIKTOR, a combination of TAK-228 (TORC1/2 inhibitor) and TAK-117 (PI3Kα inhibitor), is hypothesized to increase genomic instability and increase DNA damage repair (DDR) deficiency, leading to increased sensitivity to DNA-damaging chemotherapy and to immune checkpoint blockade inhibitors. METHODS: 10 metastatic TNBC patients received 4 mg TAK-228 and 200 mg TAK-117 (PIKTOR) orally each day for 3 days followed by 4 days off, weekly, until disease progression (PD), followed by intravenous cisplatin 75 mg/m2 plus nab paclitaxel 220 mg/m2 every 3 weeks for up to 6 cycles. Patients received subsequent treatment with pembrolizumab and/or chemotherapy. Primary endpoints were objective response rate with cisplatin/nab paclitaxel and safety. Biopsies of a metastatic lesion were collected prior to and at PD on PIKTOR. Whole exome and RNA-sequencing and reverse phase protein arrays (RPPA) were used to phenotype tumors pre- and post-PIKTOR for alterations in DDR, proliferation, and immune response. RESULTS: With cisplatin/nab paclitaxel (cis/nab pac) therapy post PIKTOR, 3 patients had clinical benefit (1 partial response (PR) and 2 stable disease (SD) ≥ 6 months) and continued to have durable benefit in progression-free survival with pembrolizumab post-cis/nab pac for 1.2, 2, and 3.6 years. Their post-PIKTOR metastatic tissue displayed decreased mismatch repair (MMR), increased tumor mutation burden, and significantly lower levels of 53BP1, DAG Lipase ß, GCN2, AKT Ser473, and PKCzeta Thr410/403 compared to pre-PIKTOR tumor tissue. CONCLUSIONS: Priming patients' chemotherapy-pretreated metastatic TNBC with PIKTOR led to very prolonged response/disease control with subsequent cis/nab pac, followed by pembrolizumab, in 3 of 10 treated patients. Our multi-omics approach revealed a higher number of genomic alterations, reductions in MMR, and alterations in immune and stress response pathways post-PIKTOR in patients who had durable responses. TRIAL REGISTRATION: This clinical trial was registered on June 21, 2017, at ClinicalTrials.gov using identifier NCT03193853.

Genomic landscapes of canine splenic angiosarcoma (hemangiosarcoma) contain extensive heterogeneity within and between patients.

Cancer genomic heterogeneity presents significant challenges for understanding oncogenic processes and for cancer's clinical management. Variation in driver mutation frequency between patients with the same tumor type as well as within an individual patients' cancer can shape the use of mutations as diagnostic, prognostic, and predictive biomarkers. We have characterized genomic heterogeneity between and within canine splenic hemangiosarcoma (HSA), a common naturally occurring cancer in pet dogs that is similar to human angiosarcoma (AS). HSA is a clinically, physiologically, and genomically complex canine cancer that may serve as a valuable model for understanding the origin and clinical impact of cancer heterogeneity. We conducted a prospective collection of 52 splenic masses from 43 dogs (27 HSA, 15 benign masses, and 1 stromal sarcoma) presenting for emergency care with hemoperitoneum secondary to a ruptured splenic mass. Multi-platform genomic analysis included matched tumor/normal targeted sequencing panel and exome sequencing. We found candidate somatic cancer driver mutations in 14/27 (52%) HSAs. Among recurrent candidate driver mutations, TP53 was most commonly mutated (30%) followed by PIK3CA (15%), AKT1 (11%), and CDKN2AIP (11%). We also identified significant intratumoral genomic heterogeneity, consistent with a branched evolution model, through multi-region exome sequencing of three distinct tumor regions from selected primary splenic tumors. These data provide new perspectives on the genomic landscape of this veterinary cancer and suggest a cross-species value for using HSA in pet dogs as a naturally occurring model of intratumoral heterogeneity.

Local production of lactate, ribose phosphate, and amino acids within human triple-negative breast cancer.

BACKGROUND: Upregulated glucose metabolism is a common feature of tumors. Glucose can be broken down by either glycolysis or the oxidative pentose phosphate pathway (oxPPP). The relative usage within tumors of these catabolic pathways remains unclear. Similarly, the extent to which tumors make biomass precursors from glucose, versus take them up from the circulation, is incompletely defined. METHODS: We explore human triple negative breast cancer (TNBC) metabolism by isotope tracing with [1,2-13C]glucose, a tracer that differentiates glycolytic versus oxPPP catabolism and reveals glucose-driven anabolism. Patients enrolled in clinical trial NCT03457779 and received IV infusion of [1,2-13C]glucose during core biopsy of their primary TNBC. Tumor samples were analyzed for metabolite labeling by liquid chromatography-mass spectrometry (LC-MS). Genomic and proteomic analyses were performed and related to observed metabolic fluxes. FINDINGS: TNBC ferments glucose to lactate, with glycolysis dominant over the oxPPP. Most ribose phosphate is nevertheless produced by oxPPP. Glucose also feeds amino acid synthesis, including of serine, glycine, aspartate, glutamate, proline and glutamine (but not asparagine). Downstream in glycolysis, tumor pyruvate and lactate labeling exceeds that found in serum, indicating that lactate exchange via monocarboxylic transporters is less prevalent in human TNBC compared with most normal tissues or non-small cell lung cancer. CONCLUSIONS: Glucose directly feeds ribose phosphate, amino acid synthesis, lactate, and the TCA cycle locally within human breast tumors.

Evaluating the effect of spaceflight on the host-pathogen interaction between human intestinal epithelial cells and Salmonella Typhimurium.

Spaceflight uniquely alters the physiology of both human cells and microbial pathogens, stimulating cellular and molecular changes directly relevant to infectious disease. However, the influence of this environment on host-pathogen interactions remains poorly understood. Here we report our results from the STL-IMMUNE study flown aboard Space Shuttle mission STS-131, which investigated multi-omic responses (transcriptomic, proteomic) of human intestinal epithelial cells to infection with Salmonella Typhimurium when both host and pathogen were simultaneously exposed to spaceflight. To our knowledge, this was the first in-flight infection and dual RNA-seq analysis using human cells.

Re-assigning the histologic identities of COV434 and TOV-112D ovarian cancer cell lines.

OBJECTIVE: The development of effective cancer treatments depends on the availability of cell lines that faithfully recapitulate the cancer in question. This study definitively re-assigns the histologic identities of two ovarian cancer cell lines, COV434 (originally described as a granulosa cell tumour) and TOV-112D (originally described as grade 3 endometrioid carcinoma), both of which were recently suggested to represent small cell carcinoma of the ovary, hypercalcemic type (SCCOHT), based on their shared gene expression profiles and sensitivity to EZH2 inhibitors. METHODS: For COV434 and TOV-112D, we re-reviewed the original pathology slides and obtained clinical follow-up on the patients, when available, and performed immunohistochemistry for SMARCA4, SMARCA2 and additional diagnostic markers on the original formalin-fixed, paraffin-embedded (FFPE) clinical material, when available. For COV434, we further performed whole exome sequencing and validated SMARCA4 mutations by Sanger sequencing. We studied the growth of the cell lines at baseline and upon re-expression of SMARCA4 in vitro for both cell lines and evaluated the serum calcium levels in vivo upon injection into immunodeficient mice for COV434 cells. RESULTS: The available morphological, immunohistochemical, genetic, and clinical features indicate COV434 is derived from SCCOHT, and TOV-112D is a dedifferentiated carcinoma. Transplantation of COV434 into mice leads to increased serum calcium level. Re-expression of SMARCA4 in either COV434 and TOV-112D cells suppressed their growth dramatically. CONCLUSIONS: COV434 represents a bona fide SCCOHT cell line. TOV-112D is a dedifferentiated ovarian carcinoma cell line.

Identification of Genetic Susceptibility Factors Associated with Canine Gastric Dilatation-Volvulus.

Canine gastric dilatation-volvulus (GDV) is a common life-threatening condition occurring primarily in large and giant breeds with a 3.9% to 36.7% lifetime risk. The genetic correlates of GDV have not previously been systematically explored. We undertook an inter-breed genome-wide association analysis (GWAS) of 253 dogs from ten breeds including 106 healthy dogs and 147 dogs with at least one GDV episode. SNP array genotyping followed by imputation was conducted on 241 samples to identify GDV-associated single-nucleotide polymorphisms (SNPs) and copy number variations (CNVs). A subset of 33 dogs (15 healthy dogs and 18 GDV patients from the three most represented breeds) was characterized by whole genome sequencing (WGS). After genome-wide Bonferroni correction, we identified a significant putatively protective intergenic SNP (rs851737064) across all breeds. The signal was most significant in Collies, German Shorthaired Pointers, and Great Danes. Subsequent focused analysis across these three breeds identified 12 significant additional putatively protective or deleterious SNPs. Notable significant SNPs included those occurring in genes involved in gastric tone and motility including VHL, NALCN, and PRKCZ. These data provide important new clues to canine GDV risk factors and facilitate generation of hypotheses regarding the genetic and molecular underpinnings this syndrome.

PD-1-Associated Gene Expression Signature of Neoadjuvant Trastuzumab-Treated Tumors Correlates with Patient Survival in HER2-Positive Breast Cancer.

The therapeutic HER2-targeting antibody trastuzumab has been shown to elicit tumor immune response in a subset of HER2-positive (HER2+) breast cancer. We performed genomic and immunohistochemical profiling of tumors from eight patients who have completed multiple rounds of neoadjuvant trastuzumabb to identify predictive biomarkers for trastuzumab-elicited tumor immune responses. Immunohistochemistry showed that all tumors had an activated tumor immune microenvironment positive for nuclear NF-κB/p65RelA, CD4, and CD8 T cell markers, but only four out of eight tumors were positive for the PD-1 immune checkpoint molecule, which is indicative of an exhausted immune environment. Exome sequencing showed no specific driver mutations correlating with PD-1 positivity. Hierarchical clustering of the RNA sequencing data revealed two distinct groups, of which Group 2 represented the PD-1 positive tumors. A gene expression signature that was derived from this clustering composed of 89 genes stratified HER2+ breast cancer patients in the TCGA dataset and it was named PD-1-Associated Gene Expression Signature in HER2+ Breast Cancer (PAGES-HBC). Patients with the Group 2 PAGES-HBC composition had significantly more favorable survival outcomes with mortality reduced by 83% (hazard ratio 0.17; 95% CI, 0.05 to 0.60; p = 0.011). Analysis of three longitudinal samples from a single patient showed that PAGES-HBC might be transiently induced by trastuzumab, independent of clonal tumor expansion over time. We conclude that PAGES-HBC could be further developed as a prognostic predictor of trastuzumab response in HER2+ breast cancer patients and be potentially used as an alternative biomarker for anti-PD-1 therapy trials.

Canine osteosarcoma genome sequencing identifies recurrent mutations in DMD and the histone methyltransferase gene SETD2.

Osteosarcoma (OS) is a rare, metastatic, human adolescent cancer that also occurs in pet dogs. To define the genomic underpinnings of canine OS, we performed multi-platform analysis of OS tumors from 59 dogs, including whole genome sequencing (n = 24) and whole exome sequencing (WES; n = 13) of primary tumors and matched normal tissue, WES (n = 10) of matched primary/metastatic/normal samples and RNA sequencing (n = 54) of primary tumors. We found that canine OS recapitulates features of human OS including low point mutation burden (median 1.98 per Mb) with a trend towards higher burden in metastases, high structural complexity, frequent TP53 (71%), PI3K pathway (37%), and MAPK pathway mutations (17%), and low expression of immune-associated genes. We also identified novel features of canine OS including putatively inactivating somatic SETD2 (42%) and DMD (50%) aberrations. These findings set the stage for understanding OS development in dogs and humans, and establish genomic contexts for future comparative analyses.

Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System.

In the event of a large-scale radiation exposure, accurate and quick assessment of radiation dose received would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to the limited availability of appropriate human samples, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate (NHP) models to build and test a biodosimetry algorithm for use in humans, we irradiated ex vivo peripheral blood samples from both humans and rhesus macaques with doses of 0, 2, 5, 6 and 7 Gy, and compared the gene expression profiles 24 h later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using NHP data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the NHP model. A "multi-gene" approach utilizing all gene values for cross-species conversion and applying the converted values on the NHP biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primates. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the NHP model.

Genome-wide profiling of human cap-independent translation-enhancing elements.

We report an in vitro selection strategy to identify RNA sequences that mediate cap-independent initiation of translation. This method entails mRNA display of trillions of genomic fragments, selection for initiation of translation and high-throughput deep sequencing. We identified >12,000 translation-enhancing elements (TEEs) in the human genome, generated a high-resolution map of human TEE-bearing regions (TBRs), and validated the function of a subset of sequences in vitro and in cultured cells.

Data mining of high density genomic variant data for prediction of Alzheimer's disease risk.

BACKGROUND: The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods. METHODS: Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step. RESULTS: The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with APOE and GAB2 SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included APOE and GAB2 SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling. CONCLUSIONS: With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.