Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer.

To uncover the intricate, chemotherapy-induced spatiotemporal remodeling of the tumor microenvironment, we conducted integrative spatial and molecular characterization of 97 high-grade serous ovarian cancer (HGSC) samples collected before and after chemotherapy. Using single-cell and spatial analyses, we identify increasingly versatile immune cell states, which form spatiotemporally dynamic microcommunities at the tumor-stroma interface. We demonstrate that chemotherapy triggers spatial redistribution and exhaustion of CD8+ T cells due to prolonged antigen presentation by macrophages, both within interconnected myeloid networks termed "Myelonets" and at the tumor stroma interface. Single-cell and spatial transcriptomics identifies prominent TIGIT-NECTIN2 ligand-receptor interactions induced by chemotherapy. Using a functional patient-derived immuno-oncology platform, we show that CD8+T-cell activity can be boosted by combining immune checkpoint blockade with chemotherapy. Our discovery of chemotherapy-induced myeloid-driven spatial T-cell exhaustion paves the way for novel immunotherapeutic strategies to unleash CD8+ T-cell-mediated anti-tumor immunity in HGSC.

Locus-specific LINE-1 expression in clinical ovarian cancer specimens at the single-cell level.

Long interspersed nuclear elements (LINE-1s/L1s) are a group of retrotransposons that can copy themselves within a genome. In humans, it is the most successful transposon in nucleotide content. L1 expression is generally mild in normal human tissues, but the activity has been shown to increase significantly in many cancers. Few studies have examined L1 expression at single-cell resolution, thus it is undetermined whether L1 reactivation occurs solely in malignant cells within tumors. One of the cancer types with frequent L1 activity is high-grade serous ovarian carcinoma (HGSOC). Here, we identified locus-specific L1 expression with 3' single-cell RNA sequencing in pre- and post-chemotherapy HGSOC sample pairs from 11 patients, and in fallopian tube samples from five healthy women. Although L1 expression quantification with the chosen technique was challenging due to the repetitive nature of the element, we found evidence of L1 expression primarily in cancer cells, but also in other cell types, e.g. cancer-associated fibroblasts. The expression levels were similar in samples taken before and after neoadjuvant chemotherapy, indicating that L1 transcriptional activity was unaffected by clinical platinum-taxane treatment. Furthermore, L1 activity was negatively associated with the expression of MYC target genes, a finding that supports earlier literature of MYC being an L1 suppressor.

A platform for efficient establishment and drug-response profiling of high-grade serous ovarian cancer organoids.

The broad research use of organoids from high-grade serous ovarian cancer (HGSC) has been hampered by low culture success rates and limited availability of fresh tumor material. Here, we describe a method for generation and long-term expansion of HGSC organoids with efficacy markedly improved over previous reports (53% vs. 23%-38%). We established organoids from cryopreserved material, demonstrating the feasibility of using viably biobanked tissue for HGSC organoid derivation. Genomic, histologic, and single-cell transcriptomic analyses revealed that organoids recapitulated genetic and phenotypic features of original tumors. Organoid drug responses correlated with clinical treatment outcomes, although in a culture conditions-dependent manner and only in organoids maintained in human plasma-like medium (HPLM). Organoids from consenting patients are available to the research community through a public biobank and organoid genomic data are explorable through an interactive online tool. Taken together, this resource facilitates the application of HGSC organoids in basic and translational ovarian cancer research.

Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer.

Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing. The stress-associated state exists before chemotherapy, is subclonally enriched during the treatment, and associates with poor progression-free survival. Co-occurrence with an inflammatory cancer-associated fibroblast subtype in tumors implies that chemotherapy is associated with stress response in both cancer cells and stroma, driving a paracrine feed-forward loop. In summary, we have found a resistant state that integrates stromal signaling and subclonal evolution and offers targets to overcome chemotherapy resistance.

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer.

Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.

miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data.

Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC.

PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples.

MOTIVATION: A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples. RESULTS: To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell-type-specific whole-transcriptome profiles adapted to each individual sample. Our results indicate that the PRISM-derived composition-free transcriptomic profiles and signatures derived from them predict the patient response better than the composite raw bulk data. We validated our findings in independent ovarian cancer and melanoma cohorts, and verified that PRISM accurately estimates the composition and cell-type-specific expression through whole-genome sequencing and RNA in situ hybridization experiments. AVAILABILITYAND IMPLEMENTATION: https://bitbucket.org/anthakki/prism. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Circulating Tumor Biomarkers in Meningiomas Reveal a Signature of Equilibrium Between Tumor Growth and Immune Modulation.

Meningiomas are primary central nervous system (CNS) tumors that originate from the arachnoid cells of the meninges. Recurrence occurs in higher grade meningiomas and a small subset of Grade I meningiomas with benign histology. Currently, there are no established circulating tumor markers which can be used for diagnostic and prognostic purposes in a non-invasive way for meningiomas. Here, we aimed to identify potential biomarkers of meningioma in patient sera. For this purpose, we collected preoperative (n = 30) serum samples from the meningioma patients classified as Grade I (n = 23), Grade II (n = 4), or Grade III (n = 3). We used a high-throughput, multiplex immunoassay cancer panel comprising of 92 cancer-related protein biomarkers to explore the serum protein profiles of meningioma patients. We detected 14 differentially expressed proteins in the sera of the Grade I meningioma patients in comparison to the age- and gender-matched control subjects (n = 12). Compared to the control group, Grade I meningioma patients showed increased serum levels of amphiregulin (AREG), CCL24, CD69, prolactin, EGF, HB-EGF, caspase-3, and decreased levels of VEGFD, TGF-α, E-Selectin, BAFF, IL-12, CCL9, and GH. For validation studies, we utilized an independent set of meningioma tumor tissue samples (Grade I, n = 20; Grade II, n = 10; Grade III, n = 6), and found that the expressions of amphiregulin and Caspase3 are significantly increased in all grades of meningiomas either at the transcriptional or protein level, respectively. In contrast, the gene expression of VEGF-D was significantly lower in Grade I meningioma tissue samples. Taken together, our study identifies a meningioma-specific protein signature in blood circulation of meningioma patients and highlights the importance of equilibrium between tumor-promoting factors and anti-tumor immunity.

Extracellular Vesicles as Carriers of Suicide mRNA and/or Protein in Cancer Therapy.

Gene therapy involves the introduction of genes (termed transgenes) into cells to compensate for a deficiency or to make a beneficial protein. Gene therapy can used as a form of cancer treatment. A particularly attractive paradigm in this regard involves the selective introduction of transgenes into cancer cells that converts inactive prodrugs into active chemotherapeutic agents, thereby triggering the death of cancer cells. Since prodrugs are inactive, they tend not to cause significant side-effects and are well-tolerated by patients relative to conventional chemotherapy. Several viral and nonviral vectors have been used as delivery tools for suicide gene therapy. Extracellular vesicles (EVs) are now recognized as a promising class of nonviral delivery vectors. Here, we describe a method in which a suicide fusion gene construct is loaded into EVs derived from a non-tumorigenic cell line. Delivery of these modified EVs to glioblastoma cell lines and spheroids decreases glioblastoma cell viability, induces apoptotic cell death, and inhibits tumor growth in vivo.

A Functional Homologous Recombination Assay Predicts Primary Chemotherapy Response and Long-Term Survival in Ovarian Cancer Patients.

Purpose: Homologous recombination deficiency (HRD) correlates with platinum sensitivity in patients with ovarian cancer, which clinically is the most useful predictor of sensitivity to PARPi. To date, there are no reliable diagnostic tools to anticipate response to platinum-based chemotherapy, thus we aimed to develop an ex vivo functional HRD detection test that could predict both platinum-sensitivity and patient eligibility to targeted drug treatments.Experimental Design: We obtained a functional HR score by quantifying homologous recombination (HR) repair after ionizing radiation-induced DNA damage in primary ovarian cancer samples (n = 32). Samples clustered in 3 categories: HR-deficient, HR-low, and HR-proficient. We analyzed the HR score association with platinum sensitivity and treatment response, platinum-free interval (PFI) and overall survival (OS), and compared it with other clinical parameters. In parallel, we performed DNA-sequencing of HR genes to assess if functional HRD can be predicted by currently offered genetic screening.Results: Low HR scores predicted primary platinum sensitivity with high statistical significance (P = 0.0103), associated with longer PFI (HR-deficient vs. HR-proficient: 531 vs. 53 days), and significantly correlated with improved OS (HR score <35 vs. ≥35, hazard ratio = 0.08, P = 0.0116). At the genomic level, we identified a few unclear mutations in HR genes and the mutational signature associated with HRD, but, overall, genetic screening failed to predict functional HRD.Conclusions: We developed an ex vivo assay that detects tumor functional HRD and an HR score able to predict platinum sensitivity, which holds the clinically relevant potential to become the routine companion diagnostic in the management of patients with ovarian cancer. Clin Cancer Res; 24(18); 4482-93. ©2018 AACR.

Overexpression of minichromosome maintenance protein 10 in medulloblastoma and its clinical implications.

BACKGROUND: Overexpression of minichromosome maintenance (MCM) proteins 2, 3, and 7 is associated with migration and invasion in medulloblastoma (MB). However, expression profiling of all prereplication complex (pre-RC) has not been addressed in MBs. PROCEDURE: We performed mRNA expression profiling of a large set of pre-RC elements in cell lines and tumor tissues of MB. RNAi technology was employed for functional studies in MB cell lines. RESULTS: Our data showed that most of the pre-RC components are significantly overexpressed in MB. Among all pre-RC mRNAs, MCM10 showed the highest level of expression (∼500- to 1,000-fold) in MB cell lines and tissues compared to the levels detected in cerebellum. In addition, RNAi silencing of MCM10 caused reduced cell proliferation and cell viability in MB cells. CONCLUSIONS: Taken together, our study reveals that the pre-RC is dysregulated in MB. In addition, MCM10, a member of this complex, is significantly overexpressed in MB and is required for tumor cell proliferation.

Role of the microRNA-29 family in fibrotic skin diseases.

Fibrotic skin diseases are characterized by the accumulation of collagen. The hallmarks of fibrotic skin diseases are unbalanced fibroblast proliferation and differentiation, extracellular matrix production and transforming growth factor-ß signalling. Numerous studies have investigated the possibility that microRNAs (miRNAs or miRs) are involved in the pathogenesis of certain fibrotic diseases, including skin, heart, lung and liver diseases. miRNAs are a class of small non-coding RNAs, which modify gene expression by binding to target messenger RNA (mRNA) and blocking the translation or inducing the degradation of target mRNA. The biological relevance of miRNAs has been investigated in physiological and pathological conditions, and there is increasing evidence that the miR-29 family is associated with fibrotic diseases. The aim of the present review is to provide an up-to-date summary of current knowledge on the latest developments associated with the miR-29 family and fibrotic skin diseases.

Cell division cycle 7-kinase inhibitor PHA-767491 hydrochloride suppresses glioblastoma growth and invasiveness.

BACKGROUND: Genomic instability is a hallmark of cancer cells, and this cellular phenomenon can emerge as a result of replicative stress. It is possible to take advantage of replicative stress, and enhance it in a targeted way to fight cancer cells. One of such strategies involves targeting the cell division cycle 7-related protein kinase (CDC7), a protein with key roles in regulation of initiation of DNA replication. CDC7 overexpression is present in different cancers, and small molecule inhibitors of the CDC7 have well-documented anti-tumor effects. Here, we aimed to test the potential of CDC7 inhibition as a new strategy for glioblastoma treatment. METHODS: PHA-767491 hydrochloride was used as the CDC7 inhibitor. Two glioblastoma cell lines (U87-MG and U251-MG) and a control cell line (3T3) were used to characterize the effects of CDC7 inhibition. The effect of CDC7 inhibition on cell viability, cell proliferation, apoptosis, migration, and invasion were analyzed. In addition, real-time PCR arrays were used to identify the differentially expressed genes in response to CDC7 inhibition. RESULTS: Our results showed that CDC7 inhibition reduces glioblastoma cell viability, suppresses cell proliferation, and triggers apoptosis in glioblastoma cell lines. In addition, we determined that CDC7 inhibition also suppresses glioblastoma cell migration and invasion. To identify molecular targets of CDC7 inhibition, we used real-time PCR arrays, which showed dysregulation of several mRNAs and miRNAs. CONCLUSIONS: Taken together, our findings suggest that CDC7 inhibition is a promising strategy for treatment of glioblastoma.

Extracellular Vesicles as Novel Delivery Tools for Cancer Treatment.

Extracellular vesicles (EVs) are different types of membrane-derived vesicles that originate from the endosomal pathway or the plasma membrane. These vesicles are used as "carriers" in intercellular communication, and are responsible for the transfer of biological cargo (lipids, proteins, RNA species, and DNA) between different cells. Despite the shortcomings in our knowledge of EV biology, attempts to employ EVs as natural delivery tools for therapeutic purposes have been partly successful in different settings. In this review, we highlight this unique potential of EVs, and discuss previous examples and future scenarios.

Genetically engineered microvesicles carrying suicide mRNA/protein inhibit schwannoma tumor growth.

Microvesicles (MVs) play an important role in intercellular communication by carrying mRNAs, microRNAs (miRNAs), non-coding RNAs, proteins, and DNA from cell to cell. To our knowledge, this is the first report of delivery of a therapeutic mRNA/protein via MVs for treatment of cancer. We first generated genetically engineered MVs by expressing high levels of the suicide gene mRNA and protein-cytosine deaminase (CD) fused to uracil phosphoribosyltransferase (UPRT) in MV donor cells. MVs were isolated from these cells and used to treat pre-established nerve sheath tumors (schwannomas) in an orthotopic mouse model. We demonstrated that MV-mediated delivery of CD-UPRT mRNA/protein by direct injection into schwannomas led to regression of these tumors upon systemic treatment with the prodrug (5-fluorocytosine (5-FC)), which is converted within tumor cells to 5-fluorouracil (5-FU)-an anticancer agent. Taken together, these studies suggest that MVs can serve as novel cell-derived "liposomes" to effectively deliver therapeutic mRNA/proteins to treatment of diseases.

miR-1289 and "Zipcode"-like Sequence Enrich mRNAs in Microvesicles.

Despite intensive studies, the molecular mechanisms by which the genetic materials are uploaded into microvesicles (MVs) are still unknown. This is the first study describing a zipcode-like 25 nucleotide (nt) sequence in the 3'-untranslated region (3'UTR) of mRNAs, with variants of this sequence present in many mRNAs enriched in MVs, as compared to their glioblastoma cells of origin. When this sequence was incorporated into the 3'UTR of a reporter message and expressed in a different cell type, it led to enrichment of the reporter mRNA in MVs. Critical features of this sequence are both a CUGCC core presented on a stem-loop structure and a miRNA-binding site, with increased levels of the corresponding miRNA in cells further increasing levels of mRNAs in MVs.

miRNA signature of schwannomas: possible role(s) of "tumor suppressor" miRNAs in benign tumors.

miRNAs have been recently implicated as drivers in several carcinogenic processes, where they can act either as oncogenes or as tumor suppressors. Schwannomas arise from Schwann cells, the myelinating cells of the peripheral nervous system. These benign tumors typically result from loss of the neurofibromatosis type 2 (NF2) tumor suppressor gene. We have recently carried out high-throughput miRNA expression profiling of human vestibular schwannomas using an array representing 407 known miRNAs in order to explore the role of miRNAs in the tumorigenesis of schwannomas. We found that miR-7 functions as a "tumor suppressor" by targeting proteins in three major oncogenic pathways - EGFR, Pak1, and Ack1. Interestingly, in this study, we also observed that several previously described potential tumor suppressor miRNAs that are down-regulated in malignant tumors were up-regulated in schwannomas. Here we discuss the possibility that "tumor suppressor" miRNAs may play a role in the transition stage(s) of cancer from benign to malignant forms.