Antagonistic Inflammatory Phenotypes Dictate Tumor Fate and Response to Immune Checkpoint Blockade.

Inflammation can support or restrain cancer progression and the response to therapy. Here, we searched for primary regulators of cancer-inhibitory inflammation through deep profiling of inflammatory tumor microenvironments (TMEs) linked to immune-dependent control in mice. We found that early intratumoral accumulation of interferon gamma (IFN-γ)-producing natural killer (NK) cells induced a profound remodeling of the TME and unleashed cytotoxic T cell (CTL)-mediated tumor eradication. Mechanistically, tumor-derived prostaglandin E2 (PGE2) acted selectively on EP2 and EP4 receptors on NK cells, hampered the TME switch, and enabled immune evasion. Analysis of patient datasets across human cancers revealed distinct inflammatory TME phenotypes resembling those associated with cancer immune control versus escape in mice. This allowed us to generate a gene-expression signature that integrated opposing inflammatory factors and predicted patient survival and response to immune checkpoint blockade. Our findings identify features of the tumor inflammatory milieu associated with immune control of cancer and establish a strategy to predict immunotherapy outcomes.

Hypoxia Is Associated with Increased Immune Infiltrates and Both Anti-Tumour and Immune Suppressive Signalling in Muscle-Invasive Bladder Cancer.

Hypoxia and a suppressive tumour microenvironment (TME) are both independent negative prognostic factors for muscle-invasive bladder cancer (MIBC) that contribute to treatment resistance. Hypoxia has been shown to induce an immune suppressive TME by recruiting myeloid cells that inhibit anti-tumour T cell responses. Recent transcriptomic analyses show hypoxia increases suppressive and anti-tumour immune signalling and infiltrates in bladder cancer. This study sought to investigate the relationship between hypoxia-inducible factor (HIF)-1 and -2, hypoxia, and immune signalling and infiltrates in MIBC. ChIP-seq was performed to identify HIF1α, HIF2α, and HIF1ß binding in the genome of the MIBC cell line T24 cultured in 1% and 0.1% oxygen for 24 h. Microarray data from four MIBC cell lines (T24, J82, UMUC3, and HT1376) cultured under 1%, 0.2%, and 0.1% oxygen for 24 h were used. Differences in the immune contexture between high- and low-hypoxia tumours were investigated using in silico analyses of two bladder cancer cohorts (BCON and TCGA) filtered to only include MIBC cases. GO and GSEA were used with the R packages "limma" and "fgsea". Immune deconvolution was performed using ImSig and TIMER algorithms. RStudio was used for all analyses. Under hypoxia, HIF1α and HIF2α bound to ~11.5-13.5% and ~4.5-7.5% of immune-related genes, respectively (1-0.1% O2). HIF1α and HIF2α both bound to genes associated with T cell activation and differentiation signalling pathways. HIF1α and HIF2α had distinct roles in immune-related signalling. HIF1 was associated with interferon production specifically, whilst HIF2 was associated with generic cytokine signalling as well as humoral and toll-like receptor immune responses. Neutrophil and myeloid cell signalling was enriched under hypoxia, alongside hallmark pathways associated with Tregs and macrophages. High-hypoxia MIBC tumours had increased expression of both suppressive and anti-tumour immune gene signatures and were associated with increased immune infiltrates. Overall, hypoxia is associated with increased inflammation for both suppressive and anti-tumour-related immune signalling and immune infiltrates, as seen in vitro and in situ using MIBC patient tumours.

ProbFold: a probabilistic method for integration of probing data in RNA secondary structure prediction.

MOTIVATION: Recently, new RNA secondary structure probing techniques have been developed, including Next Generation Sequencing based methods capable of probing transcriptome-wide. These techniques hold great promise for improving structure prediction accuracy. However, each new data type comes with its own signal properties and biases, which may even be experiment specific. There is therefore a growing need for RNA structure prediction methods that can be automatically trained on new data types and readily extended to integrate and fully exploit multiple types of data. RESULTS: Here, we develop and explore a modular probabilistic approach for integrating probing data in RNA structure prediction. It can be automatically trained given a set of known structures with probing data. The approach is demonstrated on SHAPE datasets, where we evaluate and selectively model specific correlations. The approach often makes superior use of the probing data signal compared to other methods. We illustrate the use of ProbFold on multiple data types using both simulations and a small set of structures with both SHAPE, DMS and CMCT data. Technically, the approach combines stochastic context-free grammars (SCFGs) with probabilistic graphical models. This approach allows rapid adaptation and integration of new probing data types. AVAILABILITY AND IMPLEMENTATION: ProbFold is implemented in C ++. Models are specified using simple textual formats. Data reformatting is done using separate C ++ programs. Source code, statically compiled binaries for x86 Linux machines, C ++ programs, example datasets and a tutorial is available from http://moma.ki.au.dk/prj/probfold/ CONTACT: : jakob.skou@clin.au.dk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dealing With Variable Drug Exposure Due to Variable Hepatic Metabolism: A Proof-of-Concept Application of Liquid Biopsy in Renal Impairment.

Precision dosing strategies require accounting for between-patient variability in pharmacokinetics (PK), affecting drug exposure, and in pharmacodynamics (PD), affecting response achieved at the same drug concentration at the site of action. Although liquid biopsy for assessing different levels of molecular drug targets has yet to be established, individual characterization of drug elimination pathways using liquid biopsy has recently been demonstrated. The feasibility of applying this approach in conjunction with modeling tools to guide individual dosing remains unexplored. In this study, we aimed to individualize physiologically-based pharmacokinetic (PBPK) models based on liquid biopsy measurements in plasma from 25 donors with different grades of renal function who were previously administered oral midazolam as part of a microdose cocktail. Virtual twin models were constructed based on demographics, renal function, and hepatic expression of relevant pharmacokinetic pathways projected from liquid biopsy output. Simulated exposure (AUC) to midazolam was in agreement with observed data (AFE = 1.38, AAFE = 1.78). Simulated AUC variability with three dosing approaches indicated higher variability with uniform dosing (14-fold) and stratified dosing (13-fold) compared with individualized dosing informed by liquid biopsy (fivefold). Further, exosome screening revealed mRNA expression of 532 targets relevant to drug metabolism and disposition (169 enzymes and 361 transporters). Data related to these targets can be used to further individualize PBPK models for pathways relevant to PK of other drugs. This study provides additional verification of liquid biopsy-informed PBPK modeling approaches, necessary to advance strategies that seek to achieve precise dosing from the start of treatment.

Long non-coding RNA HIF1A-As2 and MYC form a double-positive feedback loop to promote cell proliferation and metastasis in KRAS-driven non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide. KRAS is the main oncogenic driver in lung cancer that can be activated by gene mutation or amplification, but whether long non-coding RNAs (lncRNAs) regulate its activation remains unknown. Through gain and loss of function approaches, we identified that lncRNA HIF1A-As2, a KRAS-induced lncRNA, is required for cell proliferation, epithelial-mesenchymal transition (EMT) and tumor propagation in non-small cell lung cancer (NSCLC) in vitro and in vivo. Integrative analysis of HIF1A-As2 transcriptomic profiling reveals that HIF1A-As2 modulates gene expression in trans, particularly regulating transcriptional factor genes including MYC. Mechanistically, HIF1A-As2 epigenetically activates MYC by recruiting DHX9 on MYC promoter, consequently stimulating the transcription of MYC and its target genes. In addition, KRAS promotes HIF1A-As2 expression via the induction of MYC, suggesting HIF1A-As2 and MYC form a double-regulatory loop to strengthen cell proliferation and tumor metastasis in lung cancer. Inhibition of HIF1A-As2 by LNA GapmeR antisense oligonucleotides (ASO) significantly improves sensitization to 10058-F4 (a MYC-specific inhibitor) and cisplatin treatment in PDX and KRASLSLG12D-driven lung tumors, respectively.

Tumour infiltrating B cells discriminate checkpoint blockade-induced responses.

BACKGROUND: Immune cell-driven anti-cancer activity is paramount for effective responses to checkpoint inhibitors (ICB). However, the contribution of the different immune cell subsets in the circulation and within the tumour is poorly understood. MATERIALS AND METHODS: To elucidate the role of the different cell subsets in anti-tumour responses elicited by ICB, we performed single-cell analysis of the transcriptome and surface proteome of paired pre- and early on-treatment metastatic melanoma tumour biopsies and matched peripheral blood mononuclear cell samples. We next compared the survival of metastatic melanoma patients treated with ICB according to the abundance of pre-treatment tumour-infiltrating B cell clonotypes. RESULTS: We identified cell clusters associated with disease control or progression, defined differential expression of biological pathways likely involved in the immune awakening against the tumour and examined how cell-cell communication patterns between the tumour cell subsets change during treatment. Furthermore, we discovered that B cells (immunoglobulin expression and abundance of B cell clonotypes) discriminate the clinical response after ICB and propose that B cells likely contribute to anti-tumour immunity by antigen presentation through major histocompatibility complex molecules. Finally, we demonstrated that the abundance of tumour-infiltrating B cell clonotypes at baseline identifies two distinct risk groups, a finding that we confirmed in an independent cohort. CONCLUSIONS: Our exploratory translational study provides new insights on the mechanistic role of B cells in anti-melanoma immunity during treatment with ICB. Additionally, we support pre-treatment B cell tumour infiltration as a promising prognostic biomarker to be further validated as a tool for clinical risk stratification.

AMPKα loss promotes KRAS-mediated lung tumorigenesis.

AMP-activated protein kinase (AMPK) is a critical sensor of energy status that coordinates cell growth with energy balance. In non-small cell lung cancer (NSCLC) the role of AMPKα is controversial and its contribution to lung carcinogenesis is not well-defined. Furthermore, it remains largely unknown whether long non-coding RNAs (lncRNAs) are involved in the regulation of AMPK-mediated pathways. Here, we found that loss of AMPKα in combination with activation of mutant KRASG12D increased lung tumour burden and reduced survival in KrasLSLG12D/+/AMPKαfl/fl mice. In agreement, functional in vitro studies revealed that AMPKα silencing increased growth and migration of NSCLC cells. In addition, we identified an AMPKα-modulated lncRNA, KIMAT1 (ENSG00000228709), which in turn regulates AMPKα activation by stabilizing the lactate dehydrogenase B (LDHB). Collectively, our study indicates that AMPKα loss promotes KRAS-mediated lung tumorigenesis and proposes a novel KRAS/KIMAT1/LDHB/AMPKα axis that could be exploited for therapeutic purposes.

CKAP2L Promotes Non-Small Cell Lung Cancer Progression through Regulation of Transcription Elongation.

Chromosomal instability (CIN) is a driver of clonal diversification and intratumor heterogeneity, providing genetic diversity that contributes to tumor progression. It is estimated that approximately 80% of solid cancers, including non-small cell lung cancer (NSCLC), exhibit features of CIN, which affects tumor growth and response to therapy. However, the molecular mechanisms connecting CIN to tumor progression are still poorly understood. Through an RNAi screen performed on genes involved in CIN and overexpressed in human lung adenocarcinoma samples, we identified the cytoskeleton-associated protein 2-like (CKAP2L) as a potential oncogene that promotes lung cancer proliferation and growth in vitro and in vivo. Mechanistically, CKAP2L directly interacted with RNA Pol II and regulated transcription elongation of key genes involved in spindle assembly checkpoint, chromosome segregation, cell cycle, and E2F signaling. Furthermore, depletion of CKAP2L increased the sensitivity of NSCLC cells to alvocidib, a pan-CDK inhibitor, leading to a significant reduction of cell proliferation and an increase in cell death. Altogether, these findings shed light on the molecular mechanisms through which CKAP2L, a protein involved in CIN, promotes cancer progression and suggest that its inhibition represents a novel therapeutic strategy in NSCLC. SIGNIFICANCE: These findings demonstrate the oncogenic function of CKAP2L through regulation of transcription elongation and suggest that targeting CKAP2L could enhance therapeutic response in patients with NSCLC.

A KRAS-responsive long non-coding RNA controls microRNA processing.

Wild-type KRAS (KRASWT) amplification has been shown to be a secondary means of KRAS activation in cancer and associated with poor survival. Nevertheless, the precise role of KRASWT overexpression in lung cancer progression is largely unexplored. Here, we identify and characterize a KRAS-responsive lncRNA, KIMAT1 (ENSG00000228709) and show that it correlates with KRAS levels both in cell lines and in lung cancer specimens. Mechanistically, KIMAT1 is a MYC target and drives lung tumorigenesis by promoting the processing of oncogenic microRNAs (miRNAs) through DHX9 and NPM1 stabilization while halting the biogenesis of miRNAs with tumor suppressor function via MYC-dependent silencing of p21, a component of the Microprocessor Complex. KIMAT1 knockdown suppresses not only KRAS expression but also KRAS downstream signaling, thereby arresting lung cancer growth in vitro and in vivo. Taken together, this study uncovers a role for KIMAT1 in maintaining a positive feedback loop that sustains KRAS signaling during lung cancer progression and provides a proof of principle that interfering with KIMAT1 could be a strategy to hamper KRAS-induced tumorigenesis.

Profiling of Circulating Free DNA Using Targeted and Genome-wide Sequencing in Patients with SCLC.

INTRODUCTION: SCLC accounts for approximately 250,000 deaths worldwide each year. Acquisition of adequate tumor biopsy samples is challenging, and liquid biopsies present an alternative option for patient stratification and response monitoring. METHODS: We applied whole genome next-generation sequencing to circulating free DNA (cfDNA) from 39 patients with limited-stage (LS) SCLC and 30 patients with extensive-stage SCLC to establish genome-wide copy number aberrations and also performed targeted mutation analysis of 110 SCLC associated genes. Quantitative metrics were calculated for copy number aberrations, including percent genome amplified (PGA [the percentage of genomic regions amplified]), Z-score (a measure of standard deviation), and Moran's I (a measure of spatial autocorrelation). In addition CellSearch, an epitope-dependent enrichment platform, was used to enumerate circulating tumor cells (CTCs) from a parallel blood sample. RESULTS: Genome-wide and targeted cfDNA sequencing data identified tumor-related changes in 94% of patients with LS SCLC and 100% of patients with extensive-stage SCLC. Parallel analysis of CTCs based on at least 1 CTC/7.5 mL of blood increased tumor detection frequencies to 95% for LS SCLC. Both CTC counts and cfDNA readouts correlated with disease stage and overall survival. CONCLUSIONS: We demonstrate that a simple cfDNA genome-wide copy number approach provides an effective means of monitoring patients through treatment and show that targeted cfDNA sequencing identifies potential therapeutic targets in more than 50% of patients. We are now incorporating this approach into additional studies and trials of targeted therapies.