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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.

Background The majority of individuals with acute myeloid leukemia (AML) respond to initial chemotherapy and achieve a complete remission, yet only a minority experience long-term survival because a large proportion of patients eventually relapse with therapy-resistant disease. Relapse therefore represents a central problem in the treatment of AML. Despite this, and in contrast to the extensive knowledge about the molecular events underlying the process of leukemogenesis, information about the mechanisms leading to therapy resistance and relapse is still limited. Purpose and content of review Recently, a number of studies have aimed to fill this gap and provided valuable information about the clonal composition and evolution of leukemic cell populations during the course of disease, and about genetic, epigenetic, and gene expression changes associated with relapse. In this review, these studies are summarized and discussed, and the data reported in them are compiled in order to provide a resource for the identification of molecular aberrations recurrently acquired at, and thus potentially contributing to, disease recurrence and the associated therapy resistance. This survey indeed uncovered genetic aberrations with known associations with therapy resistance that were newly gained at relapse in a subset of patients. Furthermore, the expression of a number of protein coding and microRNA genes was reported to change between diagnosis and relapse in a statistically significant manner. Conclusions Together, these findings foster the expectation that future studies on larger and more homogeneous patient cohorts will uncover pathways that are robustly associated with relapse, thus representing potential targets for rationally designed therapies that may improve the treatment of patients with relapsed AML, or even facilitate the prevention of relapse in the first place.

The cancer immunoediting hypothesis postulates a dual role of the immune system: protecting the host by eliminating tumor cells, and shaping the tumor by editing its genome. Here, we elucidate the impact of evolutionary and immune-related forces on editing the tumor in a mouse model for hypermutated and microsatellite-instable colorectal cancer. Analyses of wild-type and immunodeficient RAG1 knockout mice transplanted with MC38 cells reveal that upregulation of checkpoint molecules and infiltration by Tregs are the major tumor escape mechanisms. Our results show that the effects of immunoediting are weak and that neutral accumulation of mutations dominates. Targeting the PD-1/PD-L1 pathway using immune checkpoint blocker effectively potentiates immunoediting. The immunoediting effects are less pronounced in the CT26 cell line, a non-hypermutated/microsatellite-instable model. Our study demonstrates that neutral evolution is another force that contributes to sculpting the tumor and that checkpoint blockade effectively enforces T-cell-dependent immunoselective pressure. The cancer immunoediting hypothesis assumes the immune system sculpts the cancer genome. Here the authors show, in a mouse model, that neutral evolution outweighs the effects of immunoselection and that immune checkpoint blockade potentiates the immunoediting, switching the system to non-neutral evolution.

While large-scale cancer genomic projects are comprehensively characterizing the mutational spectrum of various cancers, so far little attention has been devoted to either define the antigenicity of these mutations or to characterize the immune responses they elicit. Here we present a strategy to characterize the immunophenotypes and the antigen-ome of human colorectal cancer. We apply our strategy to a large colorectal cancer cohort (n = 598) and show that subpopulations of tumor-infiltrating lymphocytes are associated with distinct molecular phenotypes. The characterization of the antigenome shows that a large number of cancer-germline antigens are expressed in all patients. In contrast, neo-antigens are rarely shared between patients, indicating that cancer vaccination requires individualized strategy. Analysis of the genetic basis of the tumors reveals distinct tumor escape mechanisms for the patient subgroups. Hypermutated tumors are depleted of immunosuppressive cells and show upregulation of immunoinhibitory molecules. Non-hypermutated tumors are enriched with immunosuppressive cells, and the expression of immunoinhibitors and MHC molecules is downregulated. Reconstruction of the interaction network of tumor-infiltrating lymphocytes and immunomodulatory molecules followed by a validation with 11 independent cohorts (n = 1,945) identifies BCMA as a novel druggable target. Finally, linear regression modeling identifies major determinants of tumor immunogenicity, which include well-characterized modulators as well as a novel candidate, CCR8, which is then tested in an orthologous immunodeficient mouse model. The immunophenotypes of the tumors and the cancer antigenome remain widely unexplored, and our findings represent a step toward the development of personalized cancer immunotherapies.

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 .

Mechanical interaction between cells – specifically distortion of tensional homeostasis-emerged as an important aspect of breast cancer genesis and progression. We investigated the biophysical characteristics of mechanosensitive ion channels (MSCs) in the malignant MCF-7 breast cancer cell line. MSCs turned out to be the most abundant ion channel species and could be activated by negative pressure at the outer side of the cell membrane in a saturable manner. Assessing single channel conductance (G Λ ) for different monovalent cations revealed an increase in the succession: Li + < Na + < K + ≈Rb + ≈ Cs + . Divalent cations permeated also with the order: Ca 2+ < Ba 2+ . Comparison of biophysical properties enabled us to identify MSCs in MCF-7 as ion channels formed by the Piezo1 protein. Using patch clamp technique no functional MSCs were observed in the benign MCF-10A mammary epithelial cell line. Blocking of MSCs by GsMTx-4 resulted in decreased motility of MCF-7, but not of MCF-10A cells, underscoring a possible role of Piezo1 in invasion and metastatic propagation. The role of Piezo1 in biology and progression of breast cancer is further substantiated by markedly reduced overall survival in patients with increased Piezo1 mRNA levels in the primary tumor.

Background Reverse transcription quantitative PCR (RT-qPCR) with intercalating dyes is one of the main techniques to assess gene expression levels used in basic and applied research as well as in diagnostics. However, primer design for RT-qPCR can be complex due to the high demands on primer quality. Primers are best placed on exon junctions, should avoid polymorphic regions, be specific to the target transcripts and also prevent genomic amplification accurately, among others. Current software tools manage to meet all the necessary criteria only insufficiently. Here, we present ExonSurfer, a novel, user-friendly web-tool for qPCR primer design. Results ExonSurfer combines the different steps of the primer design process, encompassing target selection, specificity and self-complementarity assessment, and the avoidance of issues arising from polymorphisms. Amplification of potentially contaminating genomic DNA is avoided by designing primers on exon-exon junctions, moreover, a genomic alignment is performed to filter the primers accordingly and inform the user of any predicted interaction. In order to test the whole performance of the application, we designed primer pairs for 26 targets and checked both primer efficiency, amplicon melting temperature and length and confirmed the targeted amplicon by Sanger sequencing. Most of the tested primers accurately and selectively amplified the corresponding targets. Conclusion ExonSurfer offers a comprehensive end-to-end primer design, guaranteeing transcript-specific amplification. The user interface is intuitive, providing essential specificity and amplicon details. The tool can also be used by command line and the source code is available. Overall, we expect ExonSurfer to facilitate RT-qPCR set-up for researchers in many fields.

Molecular mechanisms underlying sexual dimorphism in mammals, fetal sex influences on intrauterine development, and the sex-biased susceptibility for selected diseases in adulthood are novel areas of current research. As importantly, two decades of multifaceted research has established that susceptibility to many adult disorders originates in utero, commonly secondary to the effects of placental dysfunction. We hypothesized that fetal sex influences gene expression and produces functional differences in human placentas. We thus extended previous studies on sexual dimorphism in mammals, which used RNA isolated from whole tissues, to investigate the effects of sex on four cell-phenotypes within a single key tissue, human placental villi. The cells studied included cytotrophoblasts, syncytiotrophoblast, arterial and venous endothelial cells. The cells were isolated from placentas of male or female fetuses and subjected to microarray analysis. We found that fetal sex differentially affected gene expression in a cell-phenotype dependent manner among all four cell-phenotypes. The markedly enriched pathways in males were identified to be signaling pathways for graft-versus-host disease as well as the immune and inflammatory systems that parallel the reported poorer outcome of male fetuses. Our study is the first to compare global gene expression by microarray analysis in purified, characterized, somatic cells from a single human tissue, i.e. placental villi. Importantly, our findings demonstrate that there are cell-phenotype specific, and tissue-specific, sex-biased responses in the human placenta, suggesting fetal sex should be considered as an independent variable in gene expression analysis of human placental villi.

The efficacy of immunotherapies in high-grade serous ovarian cancer (HGSOC) is limited, but clinical trials investigating the potential of combination immunotherapy including poly-ADP-ribose polymerase inhibitors (PARPis) are ongoing. Homologous recombination repair deficiency or BRCAness and the composition of the tumor microenvironment appear to play a critical role in determining the therapeutic response. We conducted comprehensive immunogenomic analyses of HGSOC using data from several patient cohorts. Machine learning methods were used to develop a classification model for BRCAness from gene expression data. Integrated analysis of bulk and single-cell RNA sequencing data was used to delineate the tumor immune microenvironment and was validated by immunohistochemistry. The impact of PARPi and BRCA1 mutations on the activation of immune-related pathways was studied using ovarian cancer cell lines, RNA sequencing, and immunofluorescence analysis. We identified a 24-gene signature that predicts BRCAness. Comprehensive immunogenomic analyses across patient cohorts identified samples with BRCAness and high immune infiltration. Further characterization of these samples revealed increased infiltration of immunosuppressive cells, including tumor-associated macrophages expressing , , and , as specified by single-cell RNA sequencing data and gene expression analysis of samples from patients receiving combination therapy with PARPi and anti-PD-1. Our findings show also that genomic instability and PARPi activated the cGAS-STING signaling pathway and the downstream innate immune response in a similar manner to HGSOC patients with BRCAness status. Finally, we have developed a web application (https://ovrseq.icbi.at) and an associated R package OvRSeq, which allow for comprehensive characterization of ovarian cancer patient samples and assessment of a vulnerability score that enables stratification of patients to predict response to the combination immunotherapy. Genomic instability in HGSOC affects the tumor immune environment, and TAMs play a crucial role in modulating the immune response. Based on various datasets, we have developed a diagnostic application that uses RNA sequencing data not only to comprehensively characterize HGSOC but also to predict vulnerability and response to combination immunotherapy.

Liver resection (LR) is the primary treatment for hepatic tumors, yet posthepatectomy liver failure (PHLF) remains a significant concern. While the precise etiology of PHLF remains elusive, dysregulated inflammatory processes are pivotal. Therefore, we explored the theragnostic potential of extracellular high-mobility-group-box protein 1 (HMGB1), a key damage-associated molecular pattern (DAMP) released by hepatocytes, in liver recovery post LR in patients and animal models. Plasma from 96 LR patients and liver tissues from a subset of 24 LR patients were analyzed for HMGB1 levels, and associations with PHLF and liver injury markers were assessed. In a murine LR model, the HMGB1 inhibitor glycyrrhizin, was administered to assess its impact on liver regeneration. Furthermore, plasma levels of keratin-18 (K18) and cleaved cytokeratin-18 (ccK18) were quantified to assess suitability as predictive biomarkers for PHLF. Patients experiencing PHLF exhibited elevated levels of intrahepatic and circulating HMGB1, correlating with markers of liver injury. In a murine LR model, inhibition of HMGB1 improved liver function, reduced steatosis, enhanced regeneration and decreased hepatic cell death. Elevated levels of hepatic cell death markers K18 and ccK18 were detected in patients with PHLF and correlations with levels of circulating HMGB1 was observed. Our study underscores the therapeutic and predictive potential of HMGB1 in PHLF mitigation. Elevated HMGB1, K18, and ccK18 levels correlate with patient outcomes, highlighting their predictive significance. Targeting HMGB1 enhances liver regeneration in murine LR models, emphasizing its role in potential intervention and prediction strategies for liver surgery.