hDirect-MAP: projection-free single-cell modeling of response to checkpoint immunotherapy.

There is a lack of robust generalizable predictive biomarkers of response to immune checkpoint blockade in multiple types of cancer. We develop hDirect-MAP, an algorithm that maps T cells into a shared high-dimensional (HD) expression space of diverse T cell functional signatures in which cells group by the common T cell phenotypes rather than dimensional reduced features or a distorted view of these features. Using projection-free single-cell modeling, hDirect-MAP first removed a large group of cells that did not contribute to response and then clearly distinguished T cells into response-specific subpopulations that were defined by critical T cell functional markers of strong differential expression patterns. We found that these grouped cells cannot be distinguished by dimensional-reduction algorithms but are blended by diluted expression patterns. Moreover, these identified response-specific T cell subpopulations enabled a generalizable prediction by their HD metrics. Tested using five single-cell RNA-seq or mass cytometry datasets from basal cell carcinoma, squamous cell carcinoma and melanoma, hDirect-MAP demonstrated common response-specific T cell phenotypes that defined a generalizable and accurate predictive biomarker.

Origin-independent analysis links SARS-CoV-2 local genomes with COVID-19 incidence and mortality.

There is an urgent public health need to better understand Severe Acute Respiratory Syndrome (SARS)-CoV-2/COVID-19, particularly how sequences of the viruses could lead to diverse incidence and mortality of COVID-19 in different countries. However, because of its unknown ancestors and hosts, elucidating the genetic variations of the novel coronavirus, SARS-CoV-2, has been difficult. Without needing to know ancestors, we identified an uneven distribution of local genome similarities among the viruses categorized by geographic regions, and it was strongly correlated with incidence and mortality. To ensure unbiased and origin-independent analyses, we used a pairwise comparison of local genome sequences of virus genomes by Basic Local Alignment Search Tool (BLAST). We found a strong statistical correlation between dominance of the SARS-CoV-2 in distributions of uneven similarities and the incidence and mortality of illness. Genomic annotation of the BLAST hits also showed that viruses from geographic regions with severe infections tended to have more dynamic genomic regions in the SARS-CoV-2 receptor-binding domain (RBD) and receptor-binding motif (RBM) of the spike protein (S protein). Dynamic domains in the S protein were also confirmed by a canyon region of mismatches coincident with RBM and RBD, without hits of alignments of 100% matching. Thus, our origin-independent analysis suggests that the dynamic and unstable SARS-CoV-2-RBD could be the main reason for diverse incidence and mortality of COVID-19 infection.

VOC-alarm: mutation-based prediction of SARS-CoV-2 variants of concern.

SUMMARY: Mutation is the key for a variant of concern (VOC) to overcome selective pressures, but this process is still unclear. Understanding the association of the mutational process with VOCs is an unmet need. Motivation: Here, we developed VOC-alarm, a method to predict VOCs and their caused COVID surges, using mutations of about 5.7 million SARS-CoV-2 complete sequences. We found that VOCs rely on lineage-level entropy value of mutation numbers to compete with other variants, suggestive of the importance of population-level mutations in the virus evolution. Thus, we hypothesized that VOCs are a result of a mutational process across the globe. Results: Analyzing the mutations from January 2020 to December 2021, we simulated the mutational process by estimating the pace of evolution, and thus divided the time period, January 2020-March 2022, into eight stages. We predicted Alpha, Delta, Delta Plus (AY.4.2) and Omicron (B.1.1.529) by their mutational entropy values in the Stages I, III, V and VII with accelerated paces, respectively. In late November 2021, VOC-alarm alerted that Omicron strongly competed with Delta and Delta plus to become a highly transmissible variant. Using simulated data, VOC-alarm also predicted that Omicron could lead to another COVID surge from January 2022 to March 2022. AVAILABILITY AND IMPLEMENTATION: Our software implementation is available at https://github.com/guangxujin/VOC-alarm. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PRESM: personalized reference editor for somatic mutation discovery in cancer genomics.

MOTIVATION: Accurate detection of somatic mutations is a crucial step toward understanding cancer. Various tools have been developed to detect somatic mutations from cancer genome sequencing data by mapping reads to a universal reference genome and inferring likelihoods from complex statistical models. However, read mapping is frequently obstructed by mismatches between germline and somatic mutations on a read and the reference genome. Previous attempts to develop personalized genome tools are not compatible with downstream statistical models for somatic mutation detection. RESULTS: We present PRESM, a tool that builds personalized reference genomes by integrating germline mutations into the reference genome. The aforementioned obstacle is circumvented by using a two-step germline substitution procedure, maintaining positional fidelity using an innovative workaround. Reads derived from tumor tissue can be positioned more accurately along a personalized reference than a universal reference due to the reduced genetic distance between the subject (tumor genome) and the target (the personalized genome). Application of PRESM's personalized genome reduced false-positive (FP) somatic mutation calls by as much as 55.5%, and facilitated the discovery of a novel somatic point mutation on a germline insertion in PDE1A, a phosphodiesterase associated with melanoma. Moreover, all improvements in calling accuracy were achieved without parameter optimization, as PRESM itself is parameter-free. Hence, similar increases in read mapping and decreases in the FP rate will persist when PRESM-built genomes are applied to any user-provided dataset. AVAILABILITY AND IMPLEMENTATION: The software is available at https://github.com/precisionomics/PRESM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prognostic Molecular Classification of Appendiceal Mucinous Neoplasms Treated with Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy.

BACKGROUND: Appendiceal mucinous neoplasm (AMN) with peritoneal metastasis is a rare but deadly disease with few prognostic or therapy-predictive biomarkers to guide treatment decisions. Here, we investigated the prognostic and biological attributes of gene expression-based AMN molecular subtypes. METHODS: AMN specimens (n = 138) derived from a population-based subseries of patients treated at our institution with cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) between 05/2000 and 05/2013 were analyzed for gene expression using a custom-designed NanoString 148-gene panel. Signed non-negative matrix factorization (sNMF) was used to define a gene signature capable of delineating robustly-classified AMN molecular subtypes. The sNMF class assignments were evaluated by topology learning, reverse-graph embedding and cross-cohort performance analysis. RESULTS: Three molecular subtypes of AMN were discerned by the expression patterns of 17 genes with roles in cancer progression or anti-tumor immunity. Tumor subtype assignments were confirmed by topology learning. AMN subtypes were termed immune-enriched (IE), oncogene-enriched (OE) and mixed (M) as evidenced by their gene expression patterns, and exhibited significantly different post-treatment survival outcomes. Genes with specialized immune functions, including markers of T-cells, natural killer cells, B-cells, and cytolytic activity showed increased expression in the low-risk IE subtype, while genes implicated in the promotion of cancer growth and progression were more highly expressed in the high-risk OE subtype. In multivariate analysis, the subtypes demonstrated independent prediction power for post-treatment survival. CONCLUSIONS: Our findings suggest a greater role for the immune system in AMN than previously recognized. AMN subtypes may have clinical utility for predicting CRS/HIPEC treatment outcomes.

Clinical Implications of Genetic Signatures in Appendiceal Cancer Patients with Incomplete Cytoreduction/HIPEC.

INTRODUCTION: Clinical decision-making is challenging in patients who undergo cytoreductive surgery/hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) when complete cytoreduction is not feasible. Nevertheless, some patients still benefit with long-term survival after incomplete CRS/HIPEC. There is currently no robust predictive tool that can assist clinical decision-making in this setting. METHODS: We quantified gene expression of 79 appendiceal mucinous neoplasms (AMN) from patients with incomplete CRS/HIPEC (R2 resection) using a custom NanoString gene panel. Using our previously defined, prognostic subtype classification algorithm based on signed nonnegative matrix factorization, we classified AMN cases into three molecular subtypes termed: immune enriched (IE), mixed (M), and oncogene enriched (OE). Kaplan-Meier and Cox proportional hazards analyses were used to associate subtypes and individual genes with overall survival (OS). RESULTS: Median overall survival (OS) was 7.7 years for IE, 3.6 years for M, and 1.4 years for OE. Compared with IE, OE was associated with significantly lower survival [hazard ratio (HR) 3.64, 95% confidence interval (CI) 1.63-8.13; p = 0.0017]. The differences were observed in both low-grade and high-grade tumors. While only two genes were identified to be associated with OS in low-grade tumors, multiple genes were identified to be associated with OS in high-grade tumors, particularly genes with functions in cell cycle/proliferation, mucin production, immune pathways, and cell adhesion/migration. CONCLUSION: Genetic signatures have prognostic value in patients with incomplete cytoreduction and provide valuable information to assist clinical and operative decision-making. Unraveling genetic alterations and involved pathways can direct efforts to design novel therapeutic modalities.

Safety and tolerability of the first-in-class agent CPI-613 in combination with modified FOLFIRINOX in patients with metastatic pancreatic cancer: a single-centre, open-label, dose-escalation, phase 1 trial.

BACKGROUND: Pancreatic cancer statistics are dismal, with a 5-year survival of less than 10%, and more than 50% of patients presenting with metastatic disease. Metabolic reprogramming is an emerging hallmark of pancreatic adenocarcinoma. CPI-613 is a novel anticancer agent that selectively targets the altered form of mitochondrial energy metabolism in tumour cells, causing changes in mitochondrial enzyme activities and redox status that lead to apoptosis, necrosis, and autophagy of tumour cells. We aimed to establish the maximum tolerated dose of CPI-613 when used in combination with modified FOLFIRINOX chemotherapy (comprising oxaliplatin, leucovorin, irinotecan, and fluorouracil) in patients with metastatic pancreatic cancer. METHODS: In this single-centre, open-label, dose-escalation phase 1 trial, we recruited adult patients (aged ≥18 years) with newly diagnosed metastatic pancreatic adenocarcinoma from the Comprehensive Cancer Center of Wake Forest Baptist Medical Center (Winston-Salem, NC, USA). Patients had good bone marrow, liver and kidney function, and good performance status (Eastern Cooperative Oncology Group [ECOG] performance status 0-1). We studied CPI-613 in combination with modified FOLFIRINOX (oxaliplatin at 65 mg/m2, leucovorin at 400 mg/m2, irinotecan at 140 mg/m2, and fluorouracil 400 mg/m2 bolus followed by 2400 mg/m2 over 46 h). We applied a two-stage dose-escalation scheme (single patient and traditional 3+3 design). In the single-patient stage, one patient was accrued per dose level. The starting dose of CPI-613 was 500 mg/m2 per day; the dose level was then escalated by doubling the previous dose if there were no adverse events worse than grade 2 within 4 weeks attributed as probably or definitely related to CPI-613. The traditional 3+3 dose-escalation stage was triggered if toxic effects attributed as probably or definitely related to CPI-613 were grade 2 or worse. The dose level for CPI-613 for the first cohort in the traditional dose-escalation stage was the same as that used in the last cohort of the single-patient dose-escalation stage. The primary objective was to establish the maximum tolerated dose of CPI-613 (as assessed by dose-limiting toxicities). This trial is registered with ClinicalTrials.gov, number NCT01835041, and is closed to recruitment. FINDINGS: Between April 22, 2013, and Jan 8, 2016, we enrolled 20 patients. The maximum tolerated dose of CPI-613 was 500 mg/m2. The median number of treatment cycles given at the maximum tolerated dose was 11 (IQR 4-19). Median follow-up of the 18 patients treated at the maximum tolerated dose was 378 days (IQR 250-602). Two patients enrolled at a higher dose of 1000 mg/m2, and both had a dose-limiting toxicity. Two unexpected serious adverse events occurred, both for the first patient enrolled. Expected serious adverse events were: thrombocytopenia, anaemia, and lymphopenia (all for patient number 2; anaemia and lymphopenia were dose-limiting toxicities); hyperglycaemia (in patient number 7); hypokalaemia, hypoalbuminaemia, and sepsis (patient number 11); and neutropenia (patient number 20). No deaths due to adverse events were reported. For the 18 patients given the maximum tolerated dose, the most common grade 3-4 non-haematological adverse events were hyperglycaemia (ten [55%] patients), hypokalaemia (six [33%]), peripheral sensory neuropathy (five [28%]), diarrhoea (five [28%]), and abdominal pain (four [22%]). The most common grade 3-4 haematological adverse events were neutropenia (five [28%] of 18 patients), lymphopenia (five [28%]), anaemia (four [22%], and thrombocytopenia in three [17%]). Sensory neuropathy (all grade 1-3) was recorded in 17 (94%) of the 18 patients and was managed with dose de-escalation or discontinuation per standard of care. No patients died while on active treatment; 11 study participants died, with cause of death as terminal pancreatic cancer. Of the 18 patients given the maximum tolerated dose, 11 (61%) achieved an objective (complete or partial) response. INTERPRETATION: A maximum tolerated dose of CPI-613 was established at 500 mg/m2 when used in combination with modified FOLFIRINOX in patients with metastatic pancreatic cancer. The findings of clinical activity will require validation in a phase 2 trial. FUNDING: Comprehensive Cancer Center of Wake Forest Baptist Medical Center.

Modeling the relationship of epigenetic modifications to transcription factor binding.

Transcription factors (TFs) and epigenetic modifications play crucial roles in the regulation of gene expression, and correlations between the two types of factors have been discovered. However, methods for quantitatively studying the correlations remain limited. Here, we present a computational approach to systematically investigating how epigenetic changes in chromatin architectures or DNA sequences relate to TF binding. We implemented statistical analyses to illustrate that epigenetic modifications are predictive of TF binding affinities, without the need of sequence information. Intriguingly, by considering genome locations relative to transcription start sites (TSSs) or enhancer midpoints, our analyses show that different locations display various relationship patterns. For instance, H3K4me3, H3k9ac and H3k27ac contribute more in the regions near TSSs, whereas H3K4me1 and H3k79me2 dominate in the regions far from TSSs. DNA methylation plays relatively important roles when close to TSSs than in other regions. In addition, the results show that epigenetic modification models for the predictions of TF binding affinities are cell line-specific. Taken together, our study elucidates highly coordinated, but location- and cell type-specific relationships between epigenetic modifications and binding affinities of TFs.

Chloroquine eliminates cancer stem cells through deregulation of Jak2 and DNMT1.

Triple negative breast cancer (TNBC) is known to contain a high percentage of CD44(+) /CD24(-/low) cancer stem cells (CSCs), corresponding with a poor prognosis despite systemic chemotherapy. Chloroquine (CQ), an antimalarial drug, is a lysotropic reagent which inhibits autophagy. CQ was identified as a potential CSC inhibitor through in silico gene expression signature analysis of the CD44(+) /CD24(-/low) CSC population. Autophagy plays a critical role in adaptation to stress conditions in cancer cells, and is related with drug resistance and CSC maintenance. Thus, the objectives of this study were to examine the potential enhanced efficacy arising from addition of CQ to standard chemotherapy (paclitaxel) in TNBC and to identify the mechanism by which CQ eliminates CSCs in TNBCs. Herein, we report that CQ sensitizes TNBC cells to paclitaxel through inhibition of autophagy and reduces the CD44(+) /CD24(-/low) CSC population in both preclinical and clinical settings. Also, we are the first to report a mechanism by which CQ regulates the CSCs in TNBC through inhibition of the Janus-activated kinase 2 (Jak2)-signal transducer and activator of transcription 3 signaling pathway by reducing the expression of Jak2 and DNA methyltransferase 1.

DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies.

SUMMARY: Systematic studies of drug repositioning require the integration of multi-level drug data, including basic chemical information (such as SMILES), drug targets, target-related signaling pathways, clinical trial information and Food and Drug Administration (FDA)-approval information, to predict new potential indications of existing drugs. Currently available databases, however, lack query support for multi-level drug information and thus are not designed to support drug repositioning studies. DrugMap Central (DMC), an online tool, is developed to help fill the gap. DMC enables the users to integrate, query, visualize, interrogate, and download multi-level data of known drugs or compounds quickly for drug repositioning studies all within one system. AVAILABILITY: DMC is accessible at http://r2d2drug.org/DMC.aspx. CONTACT: STWong@tmhs.org.

Chapter 17: bioimage informatics for systems pharmacology.

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies.

Clinical drug screening reveals clofazimine potentiates the efficacy while reducing the toxicity of anti-PD-1 and CTLA-4 immunotherapy.

Emerging as the most potent and durable combinational immunotherapy, dual anti-PD-1 and CTLA-4 immune checkpoint blockade (ICB) therapy notoriously increases grade 3-5 immune-related adverse events (irAEs) in patients. Accordingly, attempts to improve the antitumor potency of anti-PD-1+CTLA-4 ICB by including additional therapeutics have been largely discouraged due to concerns of further increasing fatal toxicity. Here, we screened ∼3,000 Food and Drug Administration (FDA)-approved drugs and identified clofazimine as a potential third agent to optimize anti-PD-1+CTLA-4 ICB. Remarkably, clofazimine outperforms ICB dose reduction or steroid treatment in reversing lethality of irAEs, but unlike the detrimental effect of steroids on antitumor efficacy, clofazimine potentiates curative responses in anti-PD-1+CTLA-4 ICB. Mechanistically, clofazimine promotes E2F1 activation in CD8+ T cells to overcome resistance and counteracts pathogenic Th17 cells to abolish irAEs. Collectively, clofazimine potentiates the antitumor efficacy of anti-PD-1+CTLA-4 ICB, curbs intractable irAEs, and may fill a desperate clinical need to improve patient survival.

Differential effects of low- and high-dose GW2974, a dual epidermal growth factor receptor and HER2 kinase inhibitor, on glioblastoma multiforme invasion.

Aberrant expression of epidermal growth factor receptor (EGFR; ErbB1) and HER2 (ErbB2) tyrosine kinases frequently occurs in glioblastoma multiforme (GBM) patients and is considered to be associated with tumor malignancy and poor patient prognosis. In the present study, a dual EGFR and HER2 inhibitor (GW2974) was evaluated for its effects in GBM in vitro and in vivo. Results showed that low-concentration GW2974 inhibited GBM cell invasion, whereas a high concentration of the same compound counteracted this effect. Similar results were observed in an intracranial GBM xenograft model, in which, although both doses of GW2974 slowed tumor growth, no improvement in survival was observed in mice treated with high-dose GW2974, presumably because of the augmentation of tumor invasion. By protein microarray and Western blot analyses, the p38 mitogen-activated protein kinase (MAPK) pathway was found to be activated in GBM cells under high-concentration GW2974. Additionally, blockage of the p38 MAPK pathway reproduced the inhibitory effect of low-concentration GW2974 on cell invasion. These data suggest that the p38 MAPK pathway might contribute to the differential regulation of cell invasion by GW2974. Taken together, our results indicate that GW2974 exerts different effects in GBM depending on drug dosage. This offers a new perspective on the role of GW2974 in tumor progression, providing a potential strategy for GBM treatment based on precise prescription.

The effect of mTOR inhibition alone or combined with MEK inhibitors on brain metastasis: an in vivo analysis in triple-negative breast cancer models.

mTOR inhibitor rapamycin and its analogs are lipophilic, demonstrate blood-brain barrier penetration, and have shown promising antitumor effects in several types of refractory tumors. We thus try to explore the therapeutic effects of mTOR inhibitors on brain metastasis models. We examined the effects of different dose of mTOR inhibitors (rapamycin, Temsirolimus-CCI-779) on cell invasion in two brain metastatic breast cancer cell lines (MDA-MB231-BR and CN34-BrM2). Antibody microarray and immunoblotting were applied to detect signaling pathways underlying the dose differential drug effects. The in vivo effects of single drug (CCI-779), and drug combination of CCI-779 with SL327 (a brain penetrant MEK inhibitor) to eliminate the unfavorable activation of MAPK pathway were evaluated in MDA-MB231-BR brain metastases xenograft mice. The two mTOR inhibitors, rapamycin and CCI-779, inhibited the invasion of brain metastatic cells only at a moderate concentration level, which was lost at higher concentrations secondary to activation of the MAPK signaling pathway. Pharmacological inhibition of ERK1/2 by PD98059 and SL327 restored the anti-invasion effects of mTOR inhibition in vitro. In vivo, a significant decrease was noted in the average number of micro and large metastatic lesions as well as the whole brain GFP expression in the CCI-779 1 mg/kg/day treated group compared with that in the vehicle group (P < 0.05). However, 10 mg/kg CCI-779 treatment did not show significant anti-metastasis effect on the animal model. High-dose CCI-779 eliciting the ERK MAPK activation in the brain metastatic lesion was corroborated. Combined with the brain penetrant MEK inhibitor SL327, high-dose CCI-779 significantly reduces the brain metastasis, and the combination treatment prohibited perivascular invasion of tumor cells and inhibits tumor angiogenesis in vivo. This study provides evidence on the potential value of CCI-779 as well as CCI-779 + SL327 in prohibiting breast cancer brain metastasis.

An enhanced Petri-net model to predict synergistic effects of pairwise drug combinations from gene microarray data.

MOTIVATION: Prediction of synergistic effects of drug combinations has traditionally been relied on phenotypic response data. However, such methods cannot be used to identify molecular signaling mechanisms of synergistic drug combinations. In this article, we propose an enhanced Petri-Net (EPN) model to recognize the synergistic effects of drug combinations from the molecular response profiles, i.e. drug-treated microarray data. METHODS: We addressed the downstream signaling network of the targets for the two individual drugs used in the pairwise combinations and applied EPN to the identified targeted signaling network. In EPN, drugs and signaling molecules are assigned to different types of places, while drug doses and molecular expressions are denoted by color tokens. The changes of molecular expressions caused by treatments of drugs are simulated by two actions of EPN: firing and blasting. Firing is to transit the drug and molecule tokens from one node or place to another, and blasting is to reduce the number of molecule tokens by drug tokens in a molecule node. The goal of EPN is to mediate the state characterized by control condition without any treatment to that of treatment and to depict the drug effects on molecules by the drug tokens. RESULTS: We applied EPN to our generated pairwise drug combination microarray data. The synergistic predictions using EPN are consistent with those predicted using phenotypic response data. The molecules responsible for the synergistic effects with their associated feedback loops display the mechanisms of synergism. AVAILABILITY: The software implemented in Python 2.7 programming language is available from request. CONTACT: stwong@tmhs.org.

Induction of tumor cell autosis by myxoma virus-infected CAR-T and TCR-T cells to overcome primary and acquired resistance.

Cytotoxicity of tumor-specific T cells requires tumor cell-to-T cell contact-dependent induction of classic tumor cell apoptosis and pyroptosis. However, this may not trigger sufficient primary responses of solid tumors to adoptive cell therapy or prevent tumor antigen escape-mediated acquired resistance. Here we test myxoma virus (MYXV)-infected tumor-specific T (TMYXV) cells expressing chimeric antigen receptor (CAR) or T cell receptor (TCR), which systemically deliver MYXV into solid tumors to overcome primary resistance. In addition to T cell-induced apoptosis and pyroptosis, tumor eradication by CAR/TCR-TMYXV cells is also attributed to tumor cell autosis induction, a special type of cell death. Mechanistically, T cell-derived interferon γ (IFNγ)-protein kinase B (AKT) signaling synergizes with MYXV-induced M-T5-SKP-1-VPS34 signaling to trigger robust tumor cell autosis. CAR/TCR-TMYXV-elicited autosis functions as a type of potent bystander killing to restrain antigen escape. We uncover an unexpected synergy between T cells and MYXV to bolster solid tumor cell autosis that reinforces tumor clearance.

Breast cancer extracellular vesicles-derived miR-1290 activates astrocytes in the brain metastatic microenvironment via the FOXA2→CNTF axis to promote progression of brain metastases.

Mechanisms underlying breast cancer brain metastasis (BCBM) are still unclear. In this study, we observed that extracellular vesicles (EVs) secreted from breast cancer cells with increased expression of tGLI1, a BCBM-promoting transcription factor, strongly activated astrocytes. EV-derived microRNA/miRNA microarray revealed tGLI1-positive breast cancer cells highly secreted miR-1290 and miR-1246 encapsulated in EVs. Genetic knockin/knockout studies established a direct link between tGLI1 and both miRNAs. Datamining and analysis of patient samples revealed that BCBM patients had more circulating EV-miRs-1290/1246 than those without metastasis. Ectopic expression of miR-1290 or miR-1246 strongly activated astrocytes whereas their inhibitors abrogated the effect. Conditioned media from miR-1290- or miR-1246-overexpressing astrocytes promoted mammospheres. Furthermore, miRs-1290/1246 suppressed expression of FOXA2 transcription repressor, leading to CNTF cytokine secretion and subsequent activation of astrocytes. Finally, we conducted a mouse study to demonstrate that astrocytes overexpressing miR-1290, but not miR-1246, enhanced intracranial colonization and growth of breast cancer cells. Collectively, our findings demonstrate, for the first time, that breast cancer EV-derived miR-1290 and miR-1246 activate astrocytes in the brain metastatic microenvironment and that EV-derived miR-1290 promotes progression of brain metastases through the novel EV-miR-1290→FOXA2→CNTF signaling axis.

NEDD4 degrades TUSC2 to promote glioblastoma progression.

Whether tumor suppressor candidate 2 (TUSC2) plays an important role in glioblastoma (GBM) progression is largely unknown. Whether TUSC2 undergoes polyubiquitination is unknown. Herein, we report that TUSC2 protein expression is reduced/lost in GBM compared to normal brain due to protein destabilization; TUSC2 mRNA is equally expressed in both tissues. NEDD4 E3 ubiquitin ligase polyubiquitinates TUSC2 at residue K71, and the TUSC2-K71R mutant is resistant to NEDD4-mediated proteasomal degradation. Analysis of GBM specimens showed NEDD4 protein is highly expressed in GBM and the level is inversely correlated with TUSC2 protein levels. Furthermore, TUSC2 restoration induces apoptosis and inhibits patient-derived glioma stem cells (PD-GSCs) in vitro and in vivo. Conversely, TUSC2-knockout promotes PD-GSCs in vitro and in vivo. RNA-Seq analysis and subsequent validations showed GBM cells with TUSC2-knockout expressed increased Bcl-xL and were more resistant to apoptosis induced by a Bcl-xL-specific BH3 mimetic. A TUSC2-knockout gene signature created from the RNA-seq data predicts poor patient survival. Together, these findings establish that NEDD4-mediated polyubiquitination is a novel mechanism for TUSC2 degradation in GBM and that TUSC2 loss promotes GBM progression in part through Bcl-xL upregulation.

Adoptive cell therapy with tumor-specific Th9 cells induces viral mimicry to eliminate antigen-loss-variant tumor cells.

Resistance can occur in patients receiving adoptive cell therapy (ACT) due to antigen-loss-variant (ALV) cancer cell outgrowth. Here we demonstrate that murine and human T helper (Th) 9 cells, but not Th1/Tc1 or Th17 cells, expressing tumor-specific T cell receptors (TCRs) or chimeric antigen receptors (CARs), eradicate advanced tumors that contain ALVs. This unprecedented antitumor capacity of Th9 cells is attributed to both enhanced direct tumor cell killing and bystander antitumor effects promoted by intratumor release of interferon (IFN) α/ß. Mechanistically, tumor-specific Th9 cells increase the intratumor accumulation of extracellular ATP (eATP; released from dying tumor cells), because of a unique feature of Th9 cells that lack the expression of ATP degrading ectoenzyme cluster of differentiation (CD) 39. Intratumor enrichment of eATP promotes the monocyte infiltration and stimulates their production of IFNα/ß by inducing eATP-endogenous retrovirus-Toll-like receptor 3 (TLR3)/mitochondrial antiviral signaling (MAVS) pathway activation. These results identify tumor-specific Th9 cells as a unique T cell subset endowed with the unprecedented capacity to eliminate ALVs for curative responses.

Elimination of acquired resistance to PD-1 blockade via the concurrent depletion of tumour cells and immunosuppressive cells.

Antigen release resulting from the death of tumour cells induced by chemotherapies and targeted therapies can augment the antitumour responses induced by immune checkpoint blockade (ICB). However, tumours responding to ICB therapies often become resistant to them. Here we show that the specific targeting of tumour cells promotes the growth of tumour-cell variants that are resistant to ICB, and that the acquired resistance can be overcome via the concurrent depletion of tumour cells and of major types of immunosuppressive cell via a monoclonal antibody binding the enzyme CD73, which we identified as highly expressed on tumour cells and on regulatory T cells, myeloid-derived suppressor cells and tumour-associated macrophages, but not on cytolytic T lymphocytes, natural killer cells and dendritic cells. In mice with murine tumours, the systemic administration of anti-PD1 antibodies and anti-CD73 antibodies conjugated to a near-infrared dye prevented near-infrared-irradiated tumours from acquiring resistance to ICB and resulted in the eradication of advanced tumours. The elimination of immunosuppressive cells may overcome acquired resistance to ICB across a range of tumour types and combination therapies.