Functional and spatial proteomics profiling reveals intra- and intercellular signaling crosstalk in colorectal cancer.

Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology-a strategy that is based on perturbing primary tumor cells from cancer patients-could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.

Driver mutations in GNAQ and GNA11 genes as potential targets for precision immunotherapy in uveal melanoma patients.

Uveal melanoma (UM) is the most common ocular malignancy in adults. Nearly 95% of UM patients carry the mutually exclusive mutations in the homologous genes GNAQ (amino acid change Q209L/Q209P) and GNA11 (aminoacid change Q209L). UM is located in an immunosuppressed organ and does not suffer immunoediting. Therefore, we hypothesize that driver mutations in GNAQ/11 genes could be recognized by the immune system. Genomic and transcriptomic data from primary uveal tumors were collected from the TCGA-UM dataset (n = 80) and used to assess the immunogenic potential for GNAQ/GNA11 Q209L/Q209P mutations using a variety of tools and HLA type information. All prediction tools showed stronger GNAQ/11 Q209L binding to HLA than GNAQ/11 Q209P. The immunogenicity analysis revealed that Q209L is likely to be presented by more than 73% of individuals in 1000 G databases whereas Q209P is only predicted to be presented in 24% of individuals. GNAQ/11 Q209L showed a higher likelihood to be presented by HLA-I molecules than almost all driver mutations analyzed. Finally, samples carrying Q209L had a higher immune-reactive phenotype. Regarding cancer risk, seven HLA genotypes with low Q209L affinity show higher frequency in uveal melanoma patients than in the general population. However, no clear association was found between any HLA genotype and survival. Results suggest a high potential immunogenicity of the GNAQ/11 Q209L variant that could allow the generation of novel therapeutic tools to treat UM like neoantigen vaccinations.

Colorectal Cancer Organoid-Stroma Biobank Allows Subtype-Specific Assessment of Individualized Therapy Responses.

In colorectal cancers, the tumor microenvironment plays a key role in prognosis and therapy efficacy. Patient-derived tumor organoids (PDTO) show enormous potential for preclinical testing; however, cultured tumor cells lose important characteristics, including the consensus molecular subtypes (CMS). To better reflect the cellular heterogeneity, we established the colorectal cancer organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAF) from 30 patients. Context-specific phenotyping showed that xenotransplantation or coculture with CAFs improves the transcriptomic fidelity and instructs subtype-specific stromal gene expression. Furthermore, functional profiling in coculture exposed CMS4-specific therapeutic resistance to gefitinib and SN-38 and prognostic expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as a common target. Our results demonstrate that colorectal cancer phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for a faithful representation of molecular subtypes and therapy responses ex vivo. SIGNIFICANCE: Systematic characterization of the organoid-stroma biobank provides a resource for context dependency in colorectal cancer. We demonstrate a colorectal cancer subtype memory of PDTOs that is independent of specific driver mutations. Our data underscore the importance of functional profiling in cocultures for improved preclinical testing and identification of stromal resistance mechanisms. This article is featured in Selected Articles from This Issue, p. 2109.

High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is characterized by molecular heterogeneity with diverse immune cell infiltration patterns, which has been linked to therapy sensitivity and resistance. However, full understanding of how immune cell phenotypes vary across different patient subgroups is lacking. Here, we dissect the NSCLC tumor microenvironment at high resolution by integrating 1,283,972 single cells from 556 samples and 318 patients across 29 datasets, including our dataset capturing cells with low mRNA content. We stratify patients into immune-deserted, B cell, T cell, and myeloid cell subtypes. Using bulk samples with genomic and clinical information, we identify cellular components associated with tumor histology and genotypes. We then focus on the analysis of tissue-resident neutrophils (TRNs) and uncover distinct subpopulations that acquire new functional properties in the tissue microenvironment, providing evidence for the plasticity of TRNs. Finally, we show that a TRN-derived gene signature is associated with anti-programmed cell death ligand 1 (PD-L1) treatment failure.

6-Thioguanosine Monophosphate Prodrugs Display Enhanced Performance against Thiopurine-Resistant Leukemia and Breast Cancer Cells.

Thiopurines are in widespread clinical use for the treatment of immunological disorders and certain cancers. However, treatment failure due to resistance or adverse drug reactions are common, asking for new therapeutic strategies. We investigated the potential of 6-thioguanosine monophosphate (6sGMP) prodrugs to overcome resistance to 6-thioguanine. We successfully developed synthetic routes toward diverse 6sGMP prodrugs, tested their proliferation inhibitory potential in different cell lines, and examined their mode of action. Our results show that 4-acetyloxybenzyl- and cycloSaligenyl-derivatized 6sGMP prodrugs are effective antiproliferative compounds in cells that are resistant to thiopurines. We find that resistance is related to the expression of salvage pathway enzyme HGPRT. Using TUC-seq DUAL, we demonstrate the intracellular conversion of 6sGMP prodrugs into bioactive 6sGTPs. Thus, our study offers a promising strategy for thiopurine therapy by using 6sGMP prodrugs, and it suggests TUC-seq DUAL as a simple and fast method to measure the success of thiopurine therapy.

MIO: microRNA target analysis system for immuno-oncology.

SUMMARY: MicroRNAs have been shown to be able to modulate the tumor microenvironment and the immune response and hence could be interesting biomarkers and therapeutic targets in immuno-oncology; however, dedicated analysis tools are missing. Here, we present a user-friendly web platform MIO and a Python toolkit miopy integrating various methods for visualization and analysis of provided or custom bulk microRNA and gene expression data. We include regularized regression and survival analysis and provide information of 40 microRNA target prediction tools as well as a collection of curated immune related gene and microRNA signatures and processed TCGA data including estimations of infiltrated immune cells and the immunophenoscore. The integration of several machine learning methods enables the selection of prognostic and predictive microRNAs and gene interaction network biomarkers. AVAILABILITY AND IMPLEMENTATION: https://mio.icbi.at, https://github.com/icbi-lab/mio and https://github.com/icbi-lab/miopy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comprehensive Analysis of R-Spondin Fusions and RNF43 Mutations Implicate Novel Therapeutic Options in Colorectal Cancer.

PURPOSE: Gene fusions involving R-spondin (RSPOfp) and RNF43 mutations have been shown to drive Wnt-dependent tumor initiation in colorectal cancer. Herein, we aimed to characterize the molecular features of RSPOfp/RNF43 mutated (mut) compared with wild-type (WT) colorectal cancers to gain insights into potential rationales for therapeutic strategies. EXPERIMENTAL DESIGN: A discovery cohort was classified for RSPOfp/RNF43 status using DNA/RNA sequencing and IHC. An independent cohort was used to validate our findings. RESULTS: The discovery cohort consisted of 7,245 colorectal cancer samples. RSPOfp and RNF43 mutations were detected in 1.3% (n = 94) and 6.1% (n = 443) of cases. We found 5 RSPO fusion events that had not previously been reported (e.g., IFNGR1-RSPO3). RNF43-mut tumors were associated with right-sided primary tumors. No RSPOfp tumors had RNF43 mutations. In comparison with WT colorectal cancers, RSPOfp tumors were characterized by a higher frequency of BRAF, BMPR1A, and SMAD4 mutations. APC mutations were observed in only a minority of RSPOfp-positive compared with WT cases (4.4% vs. 81.4%). Regarding RNF43 mutations, a higher rate of KMT2D and BRAF mutations were detectable compared with WT samples. Although RNF43 mutations were associated with a microsatellite instability (MSI-H)/mismatch repair deficiency (dMMR) phenotype (64.3%), and a tumor mutation burden ≥10 mt/Mb (65.8%), RSPOfp was not associated with MSI-H/dMMR. The validation cohort replicated our genetic findings. CONCLUSIONS: This is the largest series of RSPOfp/RNF43-mut colorectal cancers reported to date. Comprehensive molecular analyses asserted the unique molecular landscape associated with RSPO/RNF43 and suggested potential alternative strategies to overcome the low clinical impact of Wnt-targeted agents and immunotherapy.

nextNEOpi: a comprehensive pipeline for computational neoantigen prediction.

SUMMARY: Somatic mutations and gene fusions can produce immunogenic neoantigens mediating anticancer immune responses. However, their computational prediction from sequencing data requires complex computational workflows to identify tumor-specific aberrations, derive the resulting peptides, infer patients' Human Leukocyte Antigen types and predict neoepitopes binding to them, together with a set of features underlying their immunogenicity. Here, we present nextNEOpi (nextflow NEOantigen prediction pipeline) a comprehensive and fully automated bioinformatic pipeline to predict tumor neoantigens from raw DNA and RNA sequencing data. In addition, nextNEOpi quantifies neoepitope- and patient-specific features associated with tumor immunogenicity and response to immunotherapy. AVAILABILITY AND IMPLEMENTATION: nextNEOpi source code and documentation are available at https://github.com/icbi-lab/nextNEOpi. CONTACT: dietmar.rieder@i-med.ac.at or francesca.finotello@uibk.ac.at. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Deconvoluting tumor-infiltrating immune cells from RNA-seq data using quanTIseq.

Tumor-infiltrating immune cells comprise various cells of the innate and the adaptive immune system, which influence tumor growth and response to immunotherapy by exerting anti- and protumorigenic functions. Therefore, the quantification of tumor immune infiltrates is of paramount importance for cancer immunology and immunotherapy. We recently developed quanTIseq, a computational pipeline for the quantification of immune-cell fractions from bulk RNA sequencing (RNA-seq) data from blood or tumor samples. In this chapter, we show the capabilities of quanTIseq by analyzing two publicly available data sets. In the first example, we demonstrate how quanTIseq can be used to quantify circulating immune cells from preprocessed RNA-seq data and how to validate the results using matched flow cytometry data. In the second example, we analyze raw RNA-seq data from bulk tumor samples of melanoma patients collected before and on-treatment with kinase inhibitors to show how quanTIseq can be used to reveal the immunological effects of targeted and conventional drugs.

Tumour-infiltrating lymphocytes (TILs) and BRCA-like status in stage III breast cancer patients randomised to adjuvant intensified platinum-based chemotherapy versus conventional chemotherapy.

BACKGROUND: The prognostic value of tumour-infiltrating lymphocytes (TILs) differs by breast cancer (BC) subtype. The aim of this study was to evaluate TILs in stage III BC in the context of BRCA1/2-like phenotypes and association with outcome and benefit of intensified platinum-based chemotherapy. PATIENTS AND METHODS: Patients participated in a randomised controlled trial of adjuvant intensified platinum-based chemotherapy versus conventional anthracycline-based chemotherapy carried out between 1993 and 1999 in stage III BC. Stromal TILs were scored according to International guidelines in these human epidermal growth factor receptor 2 (HER2)-negative tumours. BRCA-profiles were determined using Comparative Genomic Hybridization. RESULTS: TIL levels were evaluated in 248 BCs. High TILs were associated with Triple Negative BC (TNBC). BRCA-like tumours harboured higher TILs compared to non-BRCA-like tumours (median TILs of 20% versus 10%, p < 0.01). TIL levels in BRCA1-like tumours were higher compared to BRCA2-like tumours (median TILs of 20% versus 10%, p < 0.001). These correlations remained significant within the oestrogen (ER)-positive subgroup, however not within the TNBC subgroup. In this stage III BC cohort, high TIL level was associated with favourable outcome (TILs per 10% increment, recurrence-free survival (RFS): multivariate hazard ratio (HR) 0.82, 95% confidence interval (CI) 0.71-0.94, p = 0.01; overall survival (OS): multivariate HR 0.80, 95% CI 0.68-0.94, p = 0.01). There was no significant interaction between TILs and benefit of intensified platinum-based chemotherapy. CONCLUSION: In this high-risk breast cancer cohort, high TILs were associated with TNBC and BRCA1-like status. Within the ER-positive subgroup, TIL levels were higher in BRCA1-like compared to BRCA2-like tumours. When adjusted for clinical characteristics, TILs were significantly associated with a more favourable outcome in stage III BC patients.

Thioguanosine Conversion Enables mRNA-Lifetime Evaluation by RNA Sequencing Using Double Metabolic Labeling (TUC-seq DUAL).

Temporal information about cellular RNA populations is essential to understand the functional roles of RNA. We have developed the hydrazine/NH4 Cl/OsO4 -based conversion of 6-thioguanosine (6sG) into A', where A' constitutes a 6-hydrazino purine derivative. A' retains the Watson-Crick base-pair mode and is efficiently decoded as adenosine in primer extension assays and in RNA sequencing. Because 6sG is applicable to metabolic labeling of freshly synthesized RNA and because the conversion chemistry is fully compatible with the conversion of the frequently used metabolic label 4-thiouridine (4sU) into C, the combination of both modified nucleosides in dual-labeling setups enables high accuracy measurements of RNA decay. This approach, termed TUC-seq DUAL, uses the two modified nucleosides in subsequent pulses and their simultaneous detection, enabling mRNA-lifetime evaluation with unprecedented precision.

NeoFuse: predicting fusion neoantigens from RNA sequencing data.

SUMMARY: Gene fusions can generate immunogenic neoantigens that mediate anticancer immune responses. However, their computational prediction from RNA sequencing (RNA-seq) data requires deep bioinformatics expertise to assembly a computational workflow covering the prediction of: fusion transcripts, their translated proteins and peptides, Human Leukocyte Antigen (HLA) types, and peptide-HLA binding affinity. Here, we present NeoFuse, a computational pipeline for the prediction of fusion neoantigens from tumor RNA-seq data. NeoFuse can be applied to cancer patients' RNA-seq data to identify fusion neoantigens that might expand the repertoire of suitable targets for immunotherapy. AVAILABILITY AND IMPLEMENTATION: NeoFuse source code and documentation are available under GPLv3 license at https://icbi.i-med.ac.at/NeoFuse/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Next-generation computational tools for interrogating cancer immunity.

The remarkable success of cancer therapies with immune checkpoint blockers is revolutionizing oncology and has sparked intensive basic and translational research into the mechanisms of cancer-immune cell interactions. In parallel, numerous novel cutting-edge technologies for comprehensive molecular and cellular characterization of cancer immunity have been developed, including single-cell sequencing, mass cytometry and multiplexed spatial cellular phenotyping. In order to process, analyse and visualize multidimensional data sets generated by these technologies, computational methods and software tools are required. Here, we review computational tools for interrogating cancer immunity, discuss advantages and limitations of the various methods and provide guidelines to assist in method selection.

Guadecitabine Plus Ipilimumab in Unresectable Melanoma: The NIBIT-M4 Clinical Trial.

PURPOSE: The immunomodulatory activity of DNA hypomethylating agents (DHAs) suggests they may improve the effectiveness of cancer immunotherapies. The phase Ib NIBIT-M4 trial tested this hypothesis using the next-generation DHA guadecitabine combined with ipilimumab. PATIENTS AND METHODS: Patients with unresectable stage III/IV melanoma received escalating doses of guadecitabine 30, 45, or 60 mg/m2/day subcutaneously on days 1 to 5 every 3 weeks, and ipilimumab 3 mg/kg intravenously on day 1 every 3 weeks, starting 1 week after guadecitabine, for four cycles. Primary endpoints were safety, tolerability, and MTD of treatment; secondary were immune-related (ir) disease control rate (DCR) and objective response rate (ORR); and exploratory were changes in methylome, transcriptome, and immune contextures in sequential tumor biopsies, and pharmacokinetics. RESULTS: Nineteen patients were treated; 84% had grade 3/4 adverse events, and neither dose-limiting toxicities per protocol nor overlapping toxicities were observed. Ir-DCR and ir-ORR were 42% and 26%, respectively. Median CpG site methylation of tumor samples (n = 8) at week 4 (74.5%) and week 12 (75.5%) was significantly (P < 0.05) lower than at baseline (80.3%), with a median of 2,454 (week 4) and 4,131 (week 12) differentially expressed genes. Among the 136 pathways significantly (P < 0.05; Z score >2 or ←2) modulated by treatment, the most frequently activated were immune-related. Tumor immune contexture analysis (n = 11) demonstrated upregulation of HLA class I on melanoma cells, an increase in CD8+, PD-1+ T cells and in CD20+ B cells in posttreatment tumor cores. CONCLUSIONS: Treatment of guadecitabine combined with ipilimumab is safe and tolerable in advanced melanoma and has promising immunomodulatory and antitumor activity.

Correction to: Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data.

It was highlighted that the original article [1] contained a typesetting mistake in the name of Noel Filipe da Cunha Carvalho de Miranda. This was incorrectly captured as Noel Filipe da Cunha Carvahlo de Miranda. It was also highlighted that in Fig. 3C the left panels Y-axis were cropped and in Fig. 5C, CD8 bar was cropped. This Correction article shows the correct Figs. 3 and 5. The original article has been updated.

Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data.

We introduce quanTIseq, a method to quantify the fractions of ten immune cell types from bulk RNA-sequencing data. quanTIseq was extensively validated in blood and tumor samples using simulated, flow cytometry, and immunohistochemistry data.quanTIseq analysis of 8000 tumor samples revealed that cytotoxic T cell infiltration is more strongly associated with the activation of the CXCR3/CXCL9 axis than with mutational load and that deconvolution-based cell scores have prognostic value in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture and to reveal immune-cell types that underlie differential patients' responses to checkpoint blockers.Availability: quanTIseq is available at http://icbi.at/quantiseq .

A Variant of a Killer Cell Immunoglobulin-like Receptor Is Associated with Resistance to PD-1 Blockade in Lung Cancer.

PURPOSE: PD-(L)1-blocking antibodies have clinical activity in metastatic non-small cell lung cancer (NSCLC) and mediate durable tumor remissions. However, the majority of patients are resistant to PD-(L)1 blockade. Understanding mechanisms of primary resistance may allow prediction of clinical response and identification of new targetable pathways. EXPERIMENTAL DESIGN: Peripheral blood mononuclear cells were collected from 35 patients with NSCLC receiving nivolumab monotherapy. Cellular changes, cytokine levels, gene expression, and polymorphisms were compared between responders and nonresponders to treatment. Findings were confirmed in additional cohorts of patients with NSCLC receiving immune checkpoint blockade. RESULTS: We identified a genetic variant of a killer cell immunoglobulin-like receptor (KIR) KIR3DS1 that is associated with primary resistance to PD-1 blockade in patients with NSCLC. This association could be confirmed in independent cohorts of patients with NSCLC. In a multivariate analysis of the pooled cohort of 135 patients, the progression-free survival was significantly associated with presence of the KIR3DS1 allele (HR, 1.72; 95% confidence interval, 1.10-2.68; P = 0.017). No relationship was seen in cohorts of patients with NSCLC who did not receive immunotherapy. Cellular assays from patients before and during PD-1 blockade showed that resistance may be due to NK-cell dysfunction. CONCLUSIONS: We identified an association of the KIR3DS1 allelic variant with response to PD-1-targeted immunotherapy in patients with NSCLC. This finding links NK cells with response to PD-1 therapy. Although the findings are interesting, a larger analysis in a randomized trial will be needed to confirm KIRs as predictive markers for response to PD-1-targeted immunotherapy.

Adoptive T Cell Therapy: New Avenues Leading to Safe Targets and Powerful Allies.

Adoptive transfer of TCR-engineered T cells is a potent therapy, able to induce clinical responses in different human malignancies. Nevertheless, treatment toxicities may occur and, in particular for solid tumors, responses may be variable and often not durable. To address these challenges, it is imperative to carefully select target antigens and to immunologically interrogate the corresponding tumors when designing optimal T cell therapies. Here, we review recent advances, covering both omics- and laboratory tools that can enable the selection of optimal T cell epitopes and TCRs as well as the identification of dominant immune evasive mechanisms within tumor tissues. Furthermore, we discuss how these techniques may aid in a rational design of effective combinatorial adoptive T cell therapies.

Nuclear receptor NR2F6 inhibition potentiates responses to PD-L1/PD-1 cancer immune checkpoint blockade.

Analyzing mouse tumor models in vivo, human T cells ex vivo, and human lung cancer samples, we provide direct evidence that NR2F6 acts as an immune checkpoint. Genetic ablation of Nr2f6, particularly in combination with established cancer immune checkpoint blockade, efficiently delays tumor progression and improves survival in experimental mouse models. The target genes deregulated in intratumoral T lymphocytes upon genetic ablation of Nr2f6 alone or together with PD-L1 blockade reveal multiple advantageous transcriptional alterations. Acute Nr2f6 silencing in both mouse and human T cells induces hyper-responsiveness that establishes a non-redundant T-cell-inhibitory function of NR2F6. NR2F6 protein expression in T-cell-infiltrating human NSCLC is upregulated in 54% of the cases (n = 303) and significantly correlates with PD-1 and CTLA-4 expression. Our data define NR2F6 as an intracellular immune checkpoint that suppresses adaptive anti-cancer immune responses and set the stage for clinical validation of targeting NR2F6 for next-generation immuno-oncological regimens.