Construction of relatedness matrices in autopolyploid populations using low-depth high-throughput sequencing data.

KEY MESSAGE: An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

RBFOX2 deregulation promotes pancreatic cancer progression and metastasis through alternative splicing.

RNA splicing is an important biological process associated with cancer initiation and progression. However, the contribution of alternative splicing to pancreatic cancer (PDAC) development is not well understood. Here, we identify an enrichment of RNA binding proteins (RBPs) involved in splicing regulation linked to PDAC progression from a forward genetic screen using Sleeping Beauty insertional mutagenesis in a mouse model of pancreatic cancer. We demonstrate downregulation of RBFOX2, an RBP of the FOX family, promotes pancreatic cancer progression and liver metastasis. Specifically, we show RBFOX2 regulates exon splicing events in transcripts encoding proteins involved in cytoskeletal remodeling programs. These exons are differentially spliced in PDAC patients, with enhanced exon skipping in the classical subtype for several RBFOX2 targets. RBFOX2 mediated splicing of ABI1, encoding the Abelson-interactor 1 adapter protein, controls the abundance and localization of ABI1 protein isoforms in pancreatic cancer cells and promotes the relocalization of ABI1 from the cytoplasm to the periphery of migrating cells. Using splice-switching antisense oligonucleotides (AONs) we demonstrate the ABI1 ∆Ex9 isoform enhances cell migration. Together, our data identify a role for RBFOX2 in promoting PDAC progression through alternative splicing regulation.

Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis.

BACKGROUND: Genome-wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale. METHODS: WGS data from 560 breast cancer patients was used for in silico library simulations to evaluate the accuracy of an FDA approved cancer gene panel as well as restriction enzyme associated DNA sequencing (RADseq) libraries for TMB estimation and mutation signature analysis. We also transfected a mouse mammary cell line with APOBEC enzymes and sequenced resulting clones to evaluate the efficacy of RADseq in an experimental setting. RESULTS: RADseq had improved accuracy of TMB estimation and derivation of mutation profiles when compared to the FDA approved cancer panel. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate TMB estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. The utility of RADseq in an experimental setting was also demonstrated, based on characterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line. CONCLUSION: In conclusion, our work demonstrates that RADseq has the potential to be used as a cost-effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers.

Aotearoa genomic data repository: An ahuru mowai for taonga species sequencing data.

The Aotearoa Genomic Data Repository (AGDR) is an initiative to provide a secure within-nation option for the storage, management and sharing of non-human genomic data generated from biological and environmental samples originating in Aotearoa New Zealand. This resource has been developed to follow the principles of Maori Data Sovereignty, and to enable the right of kaitiakitanga (guardianship), so that iwi, hapu and whanau (tribes, kinship groups and families) can effectively exercise their responsibilities as guardians over biological entities that they regard as taonga (precious or treasured). While the repository is designed to facilitate the sharing of data-making it findable by researchers and interoperable with data held in other genomic repositories-the decision-making process regarding who can access the data is entirely in the hands of those holding kaitiakitanga over each data set. No data are made available to the requesting researcher until the request has been approved, and the conditions for access (which can vary by data set) have been agreed to. Here we describe the development of the AGDR, from both a cultural perspective, and a technical one, and outline the processes that underpin its operation.

Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads.

Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications.

Impact of Clinical Data Veracity on Cancer Genomic Research.

Genomic analysis of tumors is transforming our understanding of cancer. However, although a great deal of attention is paid to the accuracy of the cancer genomic data itself, less attention has been paid to the accuracy of the associated clinical information that renders the genomic data useful for research. In this brief communication, we suggest that omissions and errors in clinical annotations have a major impact on the interpretation of cancer genomic data. We describe our discovery of annotation omissions and errors when reviewing an already carefully annotated colorectal cancer gene expression dataset from our laboratory. The potential importance of clinical annotation omissions and errors was then explored using simulation analyses with an independent genomic dataset. We suggest that the completeness and veracity of clinical annotations accompanying cancer genomic data require renewed focus by the oncology research community, when planning new collections and when interpreting existing cancer genomic data.

E-Cadherin-Deficient Cells Are Sensitive to the Multikinase Inhibitor Dasatinib.

The CDH1 gene, encoding the cell adhesion protein E-cadherin, is one of the most frequently mutated genes in gastric cancer and inactivating germline CDH1 mutations are responsible for the cancer syndrome hereditary diffuse gastric cancer (HDGC). CDH1-deficient gastric cancers exhibit high AKT serine/threonine kinase 3 (AKT3) expression, but specific drugs against this AKT isoform are not available. We therefore used two publicly available datasets to identify AKT3-associated genes which could be used to indirectly target AKT3. Reactome analysis identified an enrichment of extracellular matrix remodelling genes in AKT3-high gastric cancers. Of the 51 genes that were significantly correlated with AKT3 (but not AKT1), discoidin domain receptor tyrosine kinase 2 (DDR2) showed the strongest positive association. Treatment of isogenic human cells and mouse gastric and mammary organoids with dasatinib, a small molecule inhibitor of multiple kinases including SRC, BCR-ABL and DDR2, preferentially slowed the growth and induced apoptosis of E-cadherin-deficient cells. Dasatinib treatment also preferentially slowed the growth of gastric and mammary organoids harbouring both Cdh1 and Tp53 mutations. In organoid models, dasatinib treatment was associated with decreased phosphorylation of total AKT, with a stronger effect seen in Cdh1-deficient organoids. Treatment with combinations of dasatinib and an inhibitor of AKT, MK2206, enhanced the effect of dasatinib in breast MCF10A cells. In conclusion, targeting the DDR2-SRC-AKT3 axis with dasatinib represents a promising approach for the chemoprevention and chemotherapy of gastric and breast cancers lacking E-cadherin.

Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software.

BACKGROUND: Computational biology provides software tools for testing and making inferences about biological data. In the face of increasing volumes of data, heuristic methods that trade software speed for accuracy may be employed. We have studied these trade-offs using the results of a large number of independent software benchmarks, and evaluated whether external factors, including speed, author reputation, journal impact, recency and developer efforts, are indicative of accurate software. RESULTS: We find that software speed, author reputation, journal impact, number of citations and age are unreliable predictors of software accuracy. This is unfortunate because these are frequently cited reasons for selecting software tools. However, GitHub-derived statistics and high version numbers show that accurate bioinformatic software tools are generally the product of many improvements over time. We also find an excess of slow and inaccurate bioinformatic software tools, and this is consistent across many sub-disciplines. There are few tools that are middle-of-road in terms of accuracy and speed trade-offs. CONCLUSIONS: Our findings indicate that accurate bioinformatic software is primarily the product of long-term commitments to software development. In addition, we hypothesise that bioinformatics software suffers from publication bias. Software that is intermediate in terms of both speed and accuracy may be difficult to publish-possibly due to author, editor and reviewer practises. This leaves an unfortunate hole in the literature, as ideal tools may fall into this gap. High accuracy tools are not always useful if they are slow, while high speed is not useful if the results are also inaccurate.

Insights into H2O2-induced signaling in Jurkat cells from analysis of gene expression.

Hydrogen peroxide (H2O2) is a ubiquitous oxidant produced in a regulated manner by various enzymes in mammalian cells. H2O2 reversibly oxidizes thiol groups of cysteine residues to mediate intracellular signaling. While examples of H2O2-dependent signaling have been reported, the exact molecular mechanism(s) of signaling and the pathways affected are not well understood. Here, the transcriptomic response of Jurkat T cells to H2O2 was investigated to determine global effects on gene expression. With a low H2O2 concentration (10 µM) that did not induce an oxidative stress response or cell death, extensive changes in gene expression occurred after 4 h (6803 differentially expressed genes). Of the genes with a greater then 2-fold change in expression, 85% were upregulated suggesting that in a physiological setting H2O2 predominantly activates gene expression. Pathway analysis identified gene expression signatures associated with FOXO and NTRK signaling. These signatures were associated with an overlapping set of transcriptional regulators. Overall, our results provide a snapshot of gene expression changes in response to H2O2, which, along with further studies, will lead to new insights into the specific pathways that are activated in response to endogenous production of H2O2, and the molecular mechanisms of H2O2 signaling.

Bulk and Single-Cell Profiling of Breast Tumors Identifies TREM-1 as a Dominant Immune Suppressive Marker Associated With Poor Outcomes.

BACKGROUND: Triggering receptor expressed on myeloid cells (TREM)-1 is a key mediator of innate immunity previously associated with the severity of inflammatory disorders, and more recently, the inferior survival of lung and liver cancer patients. Here, we investigated the prognostic impact and immunological correlates of TREM1 expression in breast tumors. METHODS: Breast tumor microarray and RNAseq expression profiles (n=4,364 tumors) were analyzed for associations between gene expression, tumor immune subtypes, distant metastasis-free survival (DMFS) and clinical response to neoadjuvant chemotherapy (NAC). Single-cell (sc)RNAseq was performed using the 10X Genomics platform. Statistical associations were assessed by logistic regression, Cox regression, Kaplan-Meier analysis, Spearman correlation, Student's t-test and Chi-square test. RESULTS: In pre-treatment biopsies, TREM1 and known TREM-1 inducible cytokines (IL1B, IL8) were discovered by a statistical ranking procedure as top genes for which high expression was associated with reduced response to NAC, but only in the context of immunologically "hot" tumors otherwise associated with a high NAC response rate. In surgical specimens, TREM1 expression varied among tumor molecular subtypes, with highest expression in the more aggressive subtypes (Basal-like, HER2-E). High TREM1 significantly and reproducibly associated with inferior distant metastasis-free survival (DMFS), independent of conventional prognostic markers. Notably, the association between high TREM1 and inferior DMFS was most prominent in the subset of immunogenic tumors that exhibited the immunologically hot phenotype and otherwise associated with superior DMFS. Further observations from bulk and single-cell RNAseq analyses indicated that TREM1 expression was significantly enriched in polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and M2-like macrophages, and correlated with downstream transcriptional targets of TREM-1 (IL8, IL-1B, IL6, MCP-1, SPP1, IL1RN, INHBA) which have been previously associated with pro-tumorigenic and immunosuppressive functions. CONCLUSIONS: Together, these findings indicate that increased TREM1 expression is prognostic of inferior breast cancer outcomes and may contribute to myeloid-mediated breast cancer progression and immune suppression.

Single-Cell RNA-Seq Reveals Heterogeneous lncRNA Expression in Xenografted Triple-Negative Breast Cancer Cells.

Breast cancer is the most commonly diagnosed cancer in the world, with triple-negative breast cancer (TNBC) making up 12% of these diagnoses. TNBC tumours are highly heterogeneous in both inter-tumour and intra-tumour gene expression profiles, where they form subclonal populations of varying levels of aggressiveness. These aspects make it difficult to study and treat TNBC, requiring further research into tumour heterogeneity as well as potential therapeutic targets and biomarkers. Recently, it was discovered that the majority of the transcribed genome comprises non-coding RNAs, in particular long non-coding RNAs (lncRNAs). LncRNAs are transcripts of >200 nucleotides in length that do not encode a protein. They have been characterised as regulatory molecules and their expression can be associated with a malignant phenotype. We set out to explore TNBC tumour heterogeneity in vivo at a single cell level to investigate whether lncRNA expression varies across different cells within the tumour, even if cells are coming from the same cell line, and whether lncRNA expression is sufficient to define cellular subpopulations. We applied single-cell expression profiling due to its ability to capture expression signals of lncRNAs expressed in small subpopulations of cells. Overall, we observed most lncRNAs to be expressed at low, but detectable levels in TNBC xenografts, with a median of 25 lncRNAs detected per cell. LncRNA expression alone was insufficient to define a subpopulation of cells, and lncRNAs showed highly heterogeneous expression patterns, including ubiquitous expression, subpopulation-specific expression, and a hybrid pattern of lncRNAs expressed in several, but not all subpopulations. These findings reinforce that transcriptionally defined tumour cell subpopulations can be identified in cell-line derived xenografts, and uses single-cell RNA-seq (scRNA-seq) to detect and characterise lncRNA expression across these subpopulations in xenografted tumours. Future studies will aim to investigate the spatial distribution of lncRNAs within xenografts and patient tissues, and study the potential of subclone-specific lncRNAs as new therapeutic targets and/or biomarkers.

Transposon mutagenesis identifies cooperating genetic drivers during keratinocyte transformation and cutaneous squamous cell carcinoma progression.

The systematic identification of genetic events driving cellular transformation and tumor progression in the absence of a highly recurrent oncogenic driver mutation is a challenge in cutaneous oncology. In cutaneous squamous cell carcinoma (cuSCC), the high UV-induced mutational burden poses a hurdle to achieve a complete molecular landscape of this disease. Here, we utilized the Sleeping Beauty transposon mutagenesis system to statistically define drivers of keratinocyte transformation and cuSCC progression in vivo in the absence of UV-IR, and identified both known tumor suppressor genes and novel oncogenic drivers of cuSCC. Functional analysis confirms an oncogenic role for the ZMIZ genes, and tumor suppressive roles for KMT2C, CREBBP and NCOA2, in the initiation or progression of human cuSCC. Taken together, our in vivo screen demonstrates an extremely heterogeneous genetic landscape of cuSCC initiation and progression, which can be harnessed to better understand skin oncogenic etiology and prioritize therapeutic candidates.

Increased gene expression variability in BRCA1-associated and basal-like breast tumours.

PURPOSE: Inherited variants in the cancer susceptibility genes, BRCA1 and BRCA2 account for up to 5% of breast cancers. Multiple gene expression studies have analysed gene expression patterns that maybe associated with BRCA12 pathogenic variant status; however, results from these studies lack consensus. These studies have focused on the differences in population means to identified genes associated with BRCA1/2-carriers with little consideration for gene expression variability, which is also under genetic control and is a feature of cellular function. METHODS: We measured differential gene expression variability in three of the largest familial breast cancer datasets and a 2116 breast cancer meta-cohort. Additionally, we used RNA in situ hybridisation to confirm expression variability of EN1 in an independent cohort of more than 500 breast tumours. RESULTS: BRCA1-associated breast tumours exhibited a 22.8% (95% CI 22.3-23.2) increase in transcriptome-wide gene expression variability compared to BRCAx tumours. Additionally, 40 genes were associated with BRCA1-related breast cancers that had ChIP-seq data suggestive of enriched EZH2 binding. Of these, two genes (EN1 and IGF2BP3) were significantly variable in both BRCA1-associated and basal-like breast tumours. RNA in situ analysis of EN1 supported a significant (p = 6.3 × 10-04) increase in expression variability in BRCA1-associated breast tumours. CONCLUSION: Our novel results describe a state of increased gene expression variability in BRCA1-related and basal-like breast tumours. Furthermore, genes with increased variability may be driven by changes in DNA occupancy of epigenetic effectors. The variation in gene expression is replicable and led to the identification of novel associations between genes and disease phenotypes.

Variable expression quantitative trait loci analysis of breast cancer risk variants.

Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations (p < 5 × 10-8) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes (CYP11B1, CYP17A1 HSD3B2 and STAR) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO, suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.

E-Cadherin-Deficient Epithelial Cells Are Sensitive to HDAC Inhibitors.

Inactivating germline mutations in the CDH1 gene (encoding the E-cadherin protein) are the genetic hallmark of hereditary diffuse gastric cancer (HDGC), and somatic CDH1 mutations are an early event in the development of sporadic diffuse gastric cancer (DGC) and lobular breast cancer (LBC). In this study, histone deacetylase (HDAC) inhibitors were tested for their ability to preferentially inhibit the growth of human cell lines (MCF10A and NCI-N87) and murine organoids lacking CDH1 expression. CDH1-/- breast and gastric cells were more sensitive to the pan-HDAC inhibitors entinostat, pracinostat, mocetinostat and vorinostat than wild-type cells, with an elevated growth inhibition that was, in part, attributable to increased apoptosis. CDH1-null cells were also sensitive to more class-specific HDAC inhibitors, but compared to the pan-inhibitors, these effects were less robust to genetic background. Increased sensitivity to entinostat was also observed in gastric organoids with both Cdh1 and Tp53 deletions. However, the deletion of Tp53 largely abrogated the sensitivity of the Cdh1-null organoids to pracinostat and mocetinostat. Finally, entinostat enhanced Cdh1 expression in heterozygous Cdh1+/- murine organoids. In conclusion, entinostat is a promising drug for the chemoprevention and/or treatment of HDGC and may also be beneficial for the treatment of sporadic CDH1-deficient cancers.

Noninvasive Assessment of Epidermal Genomic Markers of UV Exposure in Skin.

The measurement of UV-induced DNA damage as a dosimeter of exposure and predictor of skin cancer risk has been proposed by multiple groups. Although UV-induced mutations and adducts are present in normal-appearing UV-exposed epidermis, sampling normal nonlesional skin requires noninvasive methods to extract epidermal DNA for analysis. Here, we demonstrate the feasibility of such an approach, termed surfactant-based tissue acquisition for molecular profiling. Sampling in patients was performed using a felt-tip pen soaked in a mixture of surfactants (Brij-30/N-decyl-N,N-dimethyl-3-ammonio-1-propanesulfonate). In mice, we show that the epidermis can be selectively removed without scarring, with complete healing within 2 weeks. We exposed hairless mice to low-dose UV radiation over a period of 3 months and serially sampled them through up to 2 months following the cessation of UV exposure, observing a progressive increase in a UV signature mutational burden. To test whether surfactant-based tissue acquisition for molecular profiling could be applied to human patients, samples were collected from sun-exposed and sun-protected areas, which were then subjected to high-depth targeted exome sequencing. Extensive UV-driven mosaicism and substantially increased mutational loads in sun-exposed versus sun-protected areas were observed, suggesting that genomic measures, as an integrated readout of DNA damage, repair, and clonal expansion, may be informative markers of UV exposure.

Circulating tumor DNA is a sensitive marker for routine monitoring of treatment response in advanced colorectal cancer.

Accurate assessment of chemotherapy response provides the means to terminate ineffective treatment, trial alternative drug regimens or schedules and reduce dose to minimize toxicity. Here, we have compared circulating tumor DNA (ctDNA) with carcinoembryonic antigen (CEA) for the cycle by cycle assessment of chemotherapy response in 30 patients with metastatic colorectal cancer. CtDNA (quantified using individualized digital droplet PCR (ddPCR) assays) and CEA levels were determined immediately prior to each chemotherapy cycle over time periods ranging from 42-548 days (average of 10 time points/patient). Twenty-nine/thirty (97%) patients had detectable ctDNA compared with 83% whose tumors were CEA-positive (>5 ng/ml) during the monitoring course. Over the course of treatment, 20 disease progression events were detected by computed tomography; ctDNA predicted significantly more of these events than CEA (16 (80%) versus 6 (30%), respectively; P-value = 0.004). When progression was detected by both ctDNA and CEA, the rise in ctDNA occurred significantly earlier than CEA (P-value = 0.046). Partial responses to chemotherapy were also detected more frequently by ctDNA, although this was not significant (P-value = 0.07). In addition, another 28 colorectal cancer patients who underwent potentially curative surgery and showed no evidence of residual disease were monitored with ctDNA for up to 2 years. Clinical relapse was observed in 6/28 (21%) patients. Four out of 6 of these patients showed a significant increase in ctDNA at or prior to relapse. Overall, ctDNA analyses were able to be performed in a clinically relevant timeline and were a more sensitive and responsive measure of tumor burden than CEA.

Distinctive Subpopulations of Stromal Cells Are Present in Human Lymph Nodes Infiltrated with Melanoma.

Metastasis of human tumors to lymph nodes (LN) is a universally negative prognostic factor. LN stromal cells (SC) play a crucial role in enabling T-cell responses, and because tumor metastases modulate their structure and function, this interaction may suppress immune responses to tumor antigens. The SC subpopulations that respond to infiltration of malignant cells into human LNs have not been defined. Here, we identify distinctive subpopulations of CD90+ SCs present in melanoma-infiltrated LNs and compare them with their counterparts in normal LNs. The first population (CD90+ podoplanin+ CD105+ CD146+ CD271+ VCAM-1+ ICAM-1+ α-SMA+) corresponds to fibroblastic reticular cells that express various T-cell modulating cytokines, chemokines, and adhesion molecules. The second (CD90+ CD34+ CD105+ CD271+) represents a novel population of CD34+ SCs embedded in collagenous structures, such as the capsule and trabeculae, that predominantly produce extracellular matrix. We also demonstrated that these two SC subpopulations are distinct from two subsets of human LN pericytes, CD90+ CD146+ CD36+ NG2- pericytes in the walls of high endothelial venules and other small vessels, and CD90+ CD146+ NG2+ CD36- pericytes in the walls of larger vessels. Distinguishing between these CD90+ SC subpopulations in human LNs allows for further study of their respective impact on T-cell responses to tumor antigens and clinical outcomes.

A Predictor of Early Disease Recurrence in Patients With Breast Cancer Using a Cell-free RNA and Protein Liquid Biopsy.

INTRODUCTION: Circulating biomarkers have been increasingly used in the clinical management of breast cancer. The present study evaluated whether RNAs and a protein present in the plasma of patients with breast cancer might have utility as prognostic biomarkers complementary to existing clinical tests. PATIENTS AND METHODS: We performed microarray profiling of small noncoding RNAs in plasma samples from 30 patients with breast cancer and 10 control individuals. Two small noncoding RNAs, including microRNA (miR)-923, were selected and quantified in plasma samples from an evaluation cohort of 253 patients with breast cancer, using droplet digital polymerase chain reaction. We also measured cancer antigen (CA) 15-3 protein levels in these samples. Cox regression survival analysis was used to determine which markers were associated with patient prognosis. RESULTS: As independent markers of prognosis, the plasma levels of miR-923 and CA 15-3 at the time of surgery for breast cancer were significantly associated with prognosis, irrespective of treatment (Cox proportional hazards, P = 3.9 × 10-3 and 1.9 × 10-9, respectively). After building a multivariable model with standard clinical and pathological features, the addition of miR-923 and CA 15-3 information into the model resulted in a significantly better predictor of disease recurrence in patients, irrespective of treatment, compared with the use of clinicopathological data alone (area under the curve at 3 years, 0.858 vs. 0.770 with clinicopathological markers only; P = .017). CONCLUSION: We propose that the plasma levels of miR-923 and CA 15-3, combined with standard clinicopathological predictors, could be used as a preoperative, noninvasive estimate of patient prognosis to identify which women might need more aggressive treatment or closer surveillance after surgery for breast cancer.

Allosteric AKT Inhibitors Target Synthetic Lethal Vulnerabilities in E-Cadherin-Deficient Cells.

The CDH1 gene, encoding the cell adhesion protein E-cadherin, is one of the most frequently mutated genes in gastric cancer and inactivating germline CDH1 mutations are responsible for hereditary diffuse gastric cancer syndrome (HDGC). Using cell viability assays, we identified that breast (MCF10A) and gastric (NCI-N87) cells lacking CDH1 expression are more sensitive to allosteric AKT inhibitors than their CDH1-expressing isogenic counterparts. Apoptosis priming and total apoptosis assays in the isogenic MCF10A cells confirmed the enhanced sensitivity of E-cadherin-null cells to the AKT inhibitors. In addition, two of these inhibitors, ARQ-092 and MK2206, preferentially targeted mouse-derived gastric Cdh1-/- organoids for growth arrest. AKT protein expression and activation (as measured by phosphorylation of serine 473) were differentially regulated in E-cadherin-null MCF10A and NCI-N87 cells, with downregulation in the normal breast cells, but upregulation in the gastric cancer cells. Bioinformatic analysis of the TCGA STAD dataset revealed that AKT3, but not AKT1 or AKT2, is upregulated in the majority of E-cadherin-deficient gastric cancers. In conclusion, allosteric AKT inhibitors represent a promising class of drugs for chemoprevention and chemotherapy of cancers with E-cadherin loss.