A comprehensive framework for analysis of microRNA sequencing data in metastatic colorectal cancer.

Although microRNAs (miRNAs) contribute to all hallmarks of cancer, miRNA dysregulation in metastasis remains poorly understood. The aim of this work was to reliably identify miRNAs associated with metastatic progression of colorectal cancer (CRC) using novel and previously published next-generation sequencing (NGS) datasets generated from 268 samples of primary (pCRC) and metastatic CRC (mCRC; liver, lung and peritoneal metastases) and tumor adjacent tissues. Differential expression analysis was performed using a meticulous bioinformatics pipeline, including only bona fide miRNAs, and utilizing miRNA-tailored quality control and processing. Five miRNAs were identified as up-regulated at multiple metastatic sites Mir-210_3p, Mir-191_5p, Mir-8-P1b_3p [mir-141-3p], Mir-1307_5p and Mir-155_5p. Several have previously been implicated in metastasis through involvement in epithelial-to-mesenchymal transition and hypoxia, while other identified miRNAs represent novel findings. The use of a publicly available pipeline facilitates reproducibility and allows new datasets to be added as they become available. The set of miRNAs identified here provides a reliable starting-point for further research into the role of miRNAs in metastatic progression.

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases.

BACKGROUND: Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite-stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumor-infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T-cell infiltration in CLM using T-cell receptor (TCR) repertoire sequencing. Eighty-five resected CLMs from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T-cell fractions were calculated, repertoire clonality was analyzed based on Hill evenness curves, and TCR sequence convergence was assessed using network analysis. RESULTS: Increased T-cell fractions (10.6% vs. 6.3%) were detected in CLMs exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT-exposed tumors independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. CONCLUSIONS: TCR repertoire sequencing can be used to quantify T-cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T-cell clonal expansion in CLM in a clinical context.

Peptide vaccine targeting mutated GNAS: a potential novel treatment for pseudomyxoma peritonei.

BACKGROUND: Pseudomyxoma peritonei (PMP) is a rare, slow-growing abdominal cancer with no efficacious treatment options in non-resectable and recurrent cases. Otherwise, rare activating mutations in the GNAS oncogene are remarkably frequent in PMP and the mutated gene product, guanine nucleotide-binding protein α subunit (Gsα), is a potential tumor neoantigen, presenting an opportunity for targeting by a therapeutic cancer vaccine. METHODS: Tumor and blood samples were collected from 25 patients undergoing surgery for PMP (NCT02073500). GNAS mutation analysis was performed by next-generation targeted sequencing or digital droplet PCR. Responses to stimulation with Gsα mutated (point mutations R201H and R201C) 30 mer peptides were analyzed in peripheral blood T cells derived from patients with PMP and healthy donors. Fresh PMP tumor samples were analyzed by mass cytometry using a panel of 35 extracellular markers, and cellular subpopulations were clustered and visualized using the visual stochastic network embedding analysis tool. RESULTS: GNAS mutations were detected in 22/25 tumor samples (88%; R201H and R201C mutations detected in 16 and 6 cases, respectively). Strong T cell proliferation against Gsα mutated peptides was observed in 18/24 patients with PMP. Mass cytometry analysis of tumor revealed infiltration of CD3 +T cells in most samples, with variable CD4+:CD8 + ratios. A large proportion of T cells expressed immune checkpoint molecules, in particular programmed death receptor-1 and T cell immunoreceptor with Ig and ITIM, indicating that these T cells were antigen experienced. CONCLUSION: These findings point to the existence of a pre-existing immunity in patients with PMP towards mutated Gsα, which has been insufficient to control tumor growth, possibly because of inhibition of antitumor T cells by upregulation of immune checkpoint molecules. The results form a rationale for exploring peptide vaccination with Gsα peptides in combination with immune checkpoint inhibiton as a possible curative treatment for PMP and other GNAS mutated cancers.

Omics analyses in peritoneal metastasis-utility in the management of peritoneal metastases from colorectal cancer and pseudomyxoma peritonei: a narrative review.

High-throughput "-omics" analysis may provide a broader and deeper understanding of cancer biology to define prognostic and predictive biomarkers and identify novel therapy targets. In this review we provide an overview of studies where the peritoneal tumor component of peritoneal metastases from colorectal cancer (PM-CRC) and pseudomyxoma peritonei (PMP) were analyzed. Most of the available data was derived from DNA mutation analysis, but a brief review of findings from transcriptomic and protein expression analysis was also performed. Studies reporting genomic analysis of peritoneal tumor samples from 1,779 PM-CRC and 623 PMP cases were identified. The most frequently mutated genes in PM-CRC were KRAS, APC, SMAD4, BRAF, and PIK3CA, while in PMP KRAS, GNAS, FAT4, TGFBR1, TP53 and SMAD3/4 mutations were most commonly identified. Analyses were performed by single-gene analyses and to some extent targeted next-generation sequencing, and a very limited amount of broad explorative data exists. The investigated cohorts were typically small and heterogeneous with respect to the methods used and to the reporting of clinical data. This was even more apparent regarding transcriptomic and protein data, as the low number of cases examined and quality of clinical data would not support firm conclusions. Even for the most frequently mutated genes, the results varied greatly; for instance, KRAS mutations were reported at frequencies between 20-57% in PM-CRC and 38-100% in PMP. Such variation could be caused by random effects in small cohorts, heterogeneity in patient selection, or sensitivity of applied technology. Although a large number of samples have been subjected to analysis, cross-study comparisons are difficult to perform, and combined with small cohorts and varying quality and detail of clinical information, the observed variation precludes useful interpretation in a clinical context. Although omics data in theory could answer questions to aid management decisions in PM-CRC and PMP, the existing data does not presently support clinical implementation. With the necessary technologies being generally available, the main challenge will be to obtain sufficiently large, representative cohorts with adequate clinical data and standardized reporting of results. Importantly, studies where the focus is specifically on peritoneal disease are needed, where the study designs are aligned with clearly defined research questions to allow robust conclusions. Such studies are highly warranted if patients with PM-CRC and PMP are to derive benefit from recent advances in precision cancer medicine.

The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires.

Adaptive immune receptor repertoires (AIRR) are key targets for biomedical research as they record past and ongoing adaptive immune responses. The capacity of machine learning (ML) to identify complex discriminative sequence patterns renders it an ideal approach for AIRR-based diagnostic and therapeutic discovery. To date, widespread adoption of AIRR ML has been inhibited by a lack of reproducibility, transparency, and interoperability. immuneML (immuneml.uio.no) addresses these concerns by implementing each step of the AIRR ML process in an extensible, open-source software ecosystem that is based on fully specified and shareable workflows. To facilitate widespread user adoption, immuneML is available as a command-line tool and through an intuitive Galaxy web interface, and extensive documentation of workflows is provided. We demonstrate the broad applicability of immuneML by (i) reproducing a large-scale study on immune state prediction, (ii) developing, integrating, and applying a novel deep learning method for antigen specificity prediction, and (iii) showcasing streamlined interpretability-focused benchmarking of AIRR ML.

Experimental Treatment of Mucinous Peritoneal Metastases Using Patient-Derived Xenograft Models.

Mucinous peritoneal metastases (PM) generally respond poorly to systemic treatment, and there is a clear unmet need for new treatment strategies to improve survival and quality of life for patients with PM. In this work, the growth inhibitory effect of five drugs (oxaliplatin (OXA; 5 mg/kg), irinotecan (IRI; 60 mg/kg), cabazitaxel (CBZ; 15 or 30 mg/kg), regorafenib (REG; 10, 30 or 60 mg/kg), and capecitabine (CAP; 359 or 755 mg/kg) was investigated in three orthotopic patient-derived xenograft models that mimic mucinous PM. Drugs were administered intraperitoneally (i.p.) as monotherapy weekly for 4 weeks (OXA, IRI), as one single i.p. injection (CBZ), or orally (REG, CAP) daily 5 of 7 days per week for four weeks, and i.p. tumor growth and survival were monitored and compared between treatment groups. The i.p. administered drugs (OXA, IRI, CBZ) had the strongest growth inhibitory effect, with OXA being most efficacious, completely inhibiting tumor growth in the majority of the animals. CBZ and IRI also strongly inhibited tumor growth, but with more variation in efficacy between the models. A moderate reduction in tumor growth was observed in all models treated with REG, while CAP had little to no growth inhibitory effect. Targeted next-generation-sequencing has identified mutational profiles typically associated with PM (mutations in KRAS, GNAS, and BRAF oncogenes), supporting the representativeness of the models. The results presented in this work support the continued exploration of i.p. treatment protocols for PM, with OXA remaining and CBZ emerging as particularly interesting candidates for further studies.

Integrative genomic analysis of peritoneal malignant mesothelioma: understanding a case with extraordinary chemotherapy response.

Peritoneal malignant mesothelioma is a rare disease with a generally poor prognosis and poor response to chemotherapy. To improve survival there is a need for increased molecular understanding of the disease, including chemotherapy sensitivity and resistance. We here present an unusual case concerning a young woman with extensive peritoneal mesothelioma who had a remarkable response to palliative chemotherapy (platinum/pemetrexed). Tumor samples collected at surgery before and after treatment were analyzed on the genomic and transcriptional levels (exome sequencing, RNA-seq, and smallRNA-seq). Integrative analysis of single nucleotide and copy-number variants, mutational signatures, and gene expression was performed to provide a comprehensive picture of the disease. LATS1/2 were identified as the main mutational drivers together with homozygous loss of BAP1 and PBRM1, which also may have contributed to the extraordinary chemotherapy response. The presence of the S3 mutational signature is consistent with homologous recombination DNA repair defects due to BAP1 loss. Up-regulation of the PI3K/AKT/mTOR pathway after treatment, supported by deactivated PTEN through miRNA regulation, is associated with cancer progression and could explain chemotherapy resistance. The molecular profile suggests potential benefit from experimental targeting of PARP, EZH2, the PI3K/AKT/mTOR pathway and possibly also from immune checkpoint inhibition. In addition to providing the molecular background for this unusual case of peritoneal mesothelioma, the results show the potential value of integrative genomic analysis in precision medicine.

GSuite HyperBrowser: integrative analysis of dataset collections across the genome and epigenome.

Background: Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings: We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions: Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.

The rainfall plot: its motivation, characteristics and pitfalls.

BACKGROUND: A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. RESULTS: We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. CONCLUSIONS: This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

Hypoxia-induced alterations of G2 checkpoint regulators.

Hypoxia promotes an aggressive tumor phenotype with increased genomic instability, partially due to downregulation of DNA repair pathways. However, genome stability is also surveilled by cell cycle checkpoints. An important issue is therefore whether hypoxia also can influence the DNA damage-induced cell cycle checkpoints. Here, we show that hypoxia (24 h 0.2% O2) alters the expression of several G2 checkpoint regulators, as examined by microarray gene expression analysis and immunoblotting of U2OS cells. While some of the changes reflected hypoxia-induced inhibition of cell cycle progression, the levels of several G2 checkpoint regulators, in particular Cyclin B, were reduced in G2 phase cells after hypoxic exposure, as shown by flow cytometric barcoding analysis of individual cells. These effects were accompanied by decreased phosphorylation of a Cyclin dependent kinase (CDK) target in G2 phase cells after hypoxia, suggesting decreased CDK activity. Furthermore, cells pre-exposed to hypoxia showed increased G2 checkpoint arrest upon treatment with ionizing radiation. Similar results were found following other hypoxic conditions (∼0.03% O2 20 h and 0.2% O2 72 h). These results demonstrate that the DNA damage-induced G2 checkpoint can be altered as a consequence of hypoxia, and we propose that such alterations may influence the genome stability of hypoxic tumors.

PLK1-inhibition can cause radiosensitization or radioresistance dependent on the treatment schedule.

BACKGROUND AND PURPOSE: PLK1-inhibitors are emerging as new potential anticancer agents. It is therefore important to explore the combined effects of PLK1-inhibitors with conventional therapies. Based on the functional roles of PLK1 in both mitosis and the G2 checkpoint, we hypothesized that the treatment schedule might influence the combined effects of PLK1-inhibiton and radiation. MATERIALS AND METHODS: Human osteosarcoma U2OS and colorectal cancer HT29 and SW620 cells were treated with the PLK1-inhibitor BI2536 before or after X-ray irradiation (0-6 Gy). Clonogenic assays, flow cytometry, immunofluorescence and mCherry-53BP1 time-lapse imaging were used to assay cell survival, cell cycle progression and DNA damage repair. RESULTS: Treatment with the PLK1-inhibitor for 24h before radiation caused cells to accumulate in G2/M and resulted in increased radiosensitivity. In contrast, the cytotoxic effects of the two treatments were less-than-additive when cells were treated with the PLK1-inhibitor for 24h after radiation. This resistance was associated with a prolonged G2 checkpoint causing enhanced repair of the radiation-induced damage and decreased BI2536-mediated mitotic damage. CONCLUSIONS: PLK1-inhibitors need to be administrated several hours before radiation to achieve radiosensitization. If PLK1-inhibitors are given after radiation, cell killing is reduced due to the prolonged G2 checkpoint.

The amount of DNA damage needed to activate the radiation-induced G2 checkpoint varies between single cells.

BACKGROUND AND PURPOSE: The radiation-induced G2 checkpoint helps facilitate DNA repair before cell division. However, recent work has revealed that human cells often escape the G2 checkpoint with unrepaired DNA breaks. The purpose was to explore whether G2 checkpoint activation occurs according to a threshold level of DNA damage. MATERIALS AND METHODS: G2 checkpoint activation was assayed at 75-90 min and 24-48 h after X-ray irradiation of BJ diploid fibroblasts and U2OS osteosarcoma cells. Multiparameter flow cytometry with pacific blue barcoding, and flow cytometry-based sorting of phospho-H3 positive cells to microscope slides, were used to examine the DNA damage marker γ-H2AX in individual mitotic cells that had escaped the G2 checkpoint. RESULTS: For all radiation doses and times tested, the number of γ-H2AX foci varied between individual mitotic cells. At 75 min the median levels of γ-H2AX in mitotic cells increased with higher radiation doses. At 24-48 h, following a prolonged G2 checkpoint, cells were more resistant to checkpoint re-activation by a second dose of radiation. CONCLUSION: Our results suggest that different amounts of DNA damage are needed to activate the G2 checkpoint in individual cells. Such single cell variation in checkpoint activation may potentially contribute to radiation-induced genomic instability.

A genetic screen identifies BRCA2 and PALB2 as key regulators of G2 checkpoint maintenance.

To identify key connections between DNA-damage repair and checkpoint pathways, we performed RNA interference screens for regulators of the ionizing radiation-induced G2 checkpoint, and we identified the breast cancer gene BRCA2. The checkpoint was also abrogated following depletion of PALB2, an interaction partner of BRCA2. BRCA2 and PALB2 depletion led to premature checkpoint abrogation and earlier activation of the AURORA A-PLK1 checkpoint-recovery pathway. These results indicate that the breast cancer tumour suppressors and homologous recombination repair proteins BRCA2 and PALB2 are main regulators of G2 checkpoint maintenance following DNA-damage.