Microenvironment Cell Populations Research Articles

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases. While numerous methods can quantify immune or stromal cells in human tissue samples from transcriptomic data, few are available for mouse studies. We introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that accurately quantify 16 immune and stromal murine cell populations. We validated mMCP-counter with flow cytometry data and showed that mMCP-counter outperforms existing methods. We showed that mMCP-counter scores are predictive of response to immune checkpoint blockade in cancer mouse models and identify early immune impacts of Alzheimer’s disease.

Abstract 927: Deep proteomic profiling of CD4+ and CD8+ T cell-depleted tumor models in PD-1 treatment

Abstract Background Immunotherapies targeting the PD-1/PD-L1 axis have been shown to be effective in only around 20% of cancer patients and the mechanism of action (MOA) underlying the differences between responders and non-responders remains poorly understood. It is therefore critical to understand the roles of different lineages of immune cells play mediating PD-1 response, while gaining an overall understanding of the interplay between tumor microenvironment (TME) and immune cell populations. To address this, tumor-bearing syngeneic mice were treated with an anti-PD-1 antibody in combination with targeted CD4+ or CD8+ T cell depletion. Tumor tissues were subsequently investigated with an unbiased proteomics workflow based on data-independent acquisition (DIA) mass spectrometry to provide insights into TME in different treatment contexts. Methods T cell subpopulations were depleted in two subcutaneous murine syngeneic models (MC38, and Hepa 1-6) followed by anti-PD-1 treatment (10mg/kg). The depletion of CD4+ and CD8+ T cells were accomplished with anti-CD4 (GK1.5) and anti-CD8 (2.43). The effectiveness of each depletion was assessed by tumor growth, followed by flow cytometry analysis of tumor infiltrating lymphocytes. FFPE tumor tissue samples, taken at the end of study (17-20 days), were digested using standard procedures and analyzed using 4h gradients on a C18 column coupled to a Thermo Scientific Q Exactive HF-X mass spectrometer. Data were extracted using Spectronaut™ (Biognosys) with a sample specific library. Results Consistent with expectation, depletion of CD8+ T cells significantly attenuated the antitumor effects of anti-PD-1 treatment in both tumor models, confirming the crucial roles of CD8+ T cells in tumor cell killing and inhibition of growth. However, depletion of CD4+ T cells showed opposing effects in the two models tested with a significant enhancement of anti-PD-1 efficacy in MC38 tumors and a reduction of anti-PD-1 efficacy in Hepa1-6 tumors. These effects were further studied by a deep proteome analysis (>9'000 proteins quantified. Statistical analysis showed large differences on proteome level between the two models (>3,000 proteins differentially expressed). We observed a strong upregulation of IFNγ inducible proteins upon anti-PD-1 therapy in the MC38 model, which is boosted upon CD4+ depletion, while many IFNγ pathway related markers were downregulated in the combo group of anti-PD-1 and anti-CD4 in Hepa 1-6. The data of the proteome analysis will be correlated to additional data from RNAseq analysis. Conclusions This study shows an unequivocal role of CD8+ T cells in anti-PD-1 induced tumor growth inhibition whereas the role of CD4+ T cells depends on the specific tumor type and TME. In our study we demonstrate how a deep proteome analysis improves the understanding of the interdependency of immune cells and the TME. Citation Format: Jan Muntel, Ying Jin, Haochen Yu, Nicholas Dupuis, Yongli Shan, Annie X. An, Wubin Qian, Davy Ouyang, Kristina Beeler, Roland Bruderer. Deep proteomic profiling of CD4+ and CD8+ T cell-depleted tumor models in PD-1 treatment [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 927.

ScCancer: a package for automated processing of single-cell RNA-seq data in cancer.

Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis and treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer cell heterogeneities and microenvironments at single-cell transcriptomic level. Here, we develop an R package named scCancer, which focuses on processing and analyzing scRNA-seq data for cancer research. Except basic data processing steps, this package takes several special considerations for cancer-specific features. Firstly, the package introduced comprehensive quality control metrics. Secondly, it used a data-driven machine learning algorithm to accurately identify major cancer microenvironment cell populations. Thirdly, it estimated a malignancy score to classify malignant (cancerous) and non-malignant cells. Then, it analyzed intra-tumor heterogeneities by key cellular phenotypes (such as cell cycle and stemness), gene signatures and cell-cell interactions. Besides, it provided multi-sample data integration analysis with different batch-effect correction strategies. Finally, user-friendly graphic reports were generated for all the analyses. By testing on 56 samples with 433405 cells in total, we demonstrated its good performance. The package is available at: http://lifeome.net/software/sccancer/.

Comprehensive analysis of CTLA-4 in the tumor immune microenvironment of 33 cancer types

Immunotherapy has recently become a powerful weapon against cancer. Cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) was the first immune checkpoint used for immunotherapy. However, CTLA-4-related mechanisms in various cancers have not been comprehensively investigated. This aim of this study was an in-depth investigation of CTLA-4 in the tumor microenvironment and its relationship with other immunomodulators, immune-related pathways and survival outcomes of 33 cancer types.Overall 9,743 tumor samples and 710 normal samples of 33 cancer types from The Cancer Genome Atlas (TCGA) database were included. CTLA-4 expression level was compared between tumor and normal tissues in 22 cancer types. The microenvironment cell populations (MCP)-counter method was used to analyze the correlation between CTLA-4 and immune cell infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to investigate its relationship with immune pathways. Survival analysis was conducted using the Kaplan-Meier method with log-rank test.CTLA-4 expression was found to be increased in some types of cancer and decreased in other cancer types (P < 0.05). When comparing between different tumor tissues, CTLA-4 was lowest in uveal melanoma (UVM). MCP analysis demonstrated that CTLA-4 had a strong correlation with T cells in almost all cancer types and that CTLA-4 showed a positive correlation with most immune cells in UVM. Immune pathway analysis found that CTLA-4 is involved in a variety of immune pathways. Survival analysis revealed that CTLA-4 can predict patients’ survival outcomes. This comprehensive analysis of CTLA-4 will promote anti-CTLA-4 therapy and personalized combined immunotherapy.

Bioinformatics profiling integrating a three immune-related long non-coding RNA signature as a prognostic model for clear cell renal cell carcinoma

BackgroundRenal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in urogenital system, and the clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma. Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IRlncRs analysis based on abundant ccRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field.MethodsBased on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immune-related genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines.ResultsA total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRlncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient.ConclusionOur results demonstrate some sIRlncRs with remark clinical relevance show the latent monitoring and prognosis values for ccRCC patients and may provide new insight in immunological researches and treatment strategies of ccRCC patients.

Genetic lesions in MYC and STAT3 drive oncogenic transcription factor overexpression in plasmablastic lymphoma.

The mutational profile of plasmablastic lymphoma has not been described. We performed a targeted, exonic next-generation sequencing analysis of 30 plasmablastic lymphoma cases with a Bcell lymphoma-dedicated panel and fluorescence in situ hybridization for the detection of MYC rearrangements. Complete phenotyping of the neoplastic and microenvironmental cell populations was also performed. We identified an enrichment in recurrent genetic events in MYC (69% with MYC translocation or amplification and three cases with missense point mutations), PRDM1/Blimp1 and STAT3 mutations. These gene mutations were more frequent in Epstein-Barr virus (EBV)-positive disease. Other genetic events included mutations in BRAF, EP300, BCR (CD79A and CD79B), NOTCH pathway (NOTCH2, NOTCH1 and SGK1) and MYD88pL265P. Immunohistochemical analysis showed consistent MYC expression, which was higher in cases with MYC rearrangements, together with phospho-STAT3 (Tyr705) overexpression in cases with STAT3 SH2 domain mutations. Microenvironmental cell populations were heterogeneous and unrelated to EBV, with enrichment of tumor-associated macrophages (TAM) and PD1-positive T cells. PD-L1 was expressed in all cases in the TAM population but only in the neoplastic cells in five cases (4 of 14 EBV-positive cases). HLA expression was absent in the majority of cases of plasmablastic lymphoma. In summary, the mutational profile of plasmablastic lymphoma is heterogeneous and related to EBV infection. Genetic events in MYC, STAT3 and PRDM1/Blimp1 are more frequent in EBV-positive disease. An enrichment in TAM and PD1 reactive T lymphocytes is found in the microenvironment of plasmablastic lymphoma and a fraction of the neoplastic cells express PD-L1.

Abstract A05: Pharmacodynamics of immune checkpoint blockade therapy indicate drivers of response

Abstract To identify drivers of response and resistance we analyzed RNA-seq data from biopsies of 78 patients (pts) enrolled in the BMS 038 clinical trial. Pts with metastatic melanoma had biopsies at baseline and on treatment while receiving immune checkpoint blockade therapy, either nivolumab single agent (N = 23 after ipilimumab progression, N = 24 ipilimumab-naive) or combination ipilimumab and nivolumab (N = 28). In the combined data set, there were 28 pts with progressive disease (PD), 18 with stable disease (SD) and 25 with complete or partial response (CRPR). We used Microenvironment Cell Populations (MCP)-Counter to perform RNA deconvolution to assess levels of immune cell infiltration in each sample. T-cell infiltration was significantly higher in CRPR at baseline relative to PD (p-value &amp;lt; 0.007 consistent with previous observations (Tumeh et al., Nature 2014). In CRPR, T-cell infiltration increased significantly on treatment relative to baseline (p-value &amp;lt; 0.000427) as expected. Surprisingly, T-cell infiltration also increased in on-treatment biopsies in both SD (p-value &amp;lt; 0.003) and PD (p-value &amp;lt; 0.0182), although the increase was lower than in CRPR. These data indicate that even without clinically observable response, there is pharmacodynamic evidence of activity. In addition to changes in the tumor microenvironment, samples exhibited tumor-specific changes in gene expression with the potential to impact response to immune blockade therapy. Wnt signaling is a mechanism of immune exclusion as a result of β-catenin suppressing the expression of chemokines necessary to attract dendritic cells key for full immune infiltration. In our cohort, Wnt signaling levels did not differ significantly before anti-PD1 therapy; however, only responders showed a significant decrease in Wnt signaling (p-value &amp;lt; 0.003) on treatment, with a concomitant decrease in the Wnt target gene MYC, which is immunosuppressive in addition to driving tumor cell proliferation. In addition, consistent with the previously reported role of Wnt signaling in suppressing dendritic cell infiltration, responding biopsies showed a significant increase in dendritic cells (p-value &amp;lt; 0.013) on treatment. Importantly, dendritic cells only significantly increased in biopsies of responding pts on combination therapy (p-value = 0.004). The increase in dendritic cells in the combination therapy, likely the result of the increased T cells at the tumor site released by removing the anti-CTLA4 immune blockade using ipilimumab, has the potential to explain the increased overall immune response in these cases. Together these data indicate that most tumors exhibit an immune response to immune blockade therapy, whether or not it results in a clinical response, and that clinical response to immune blockade therapy has decreased Wnt signaling and increase in dendritic cells. Our findings imply that interventions bringing T cells and dendritic cells into the tumor and inhibiting Wnt signaling should be a focus of combination therapeutic efforts. Note: This abstract was not presented at the conference. Citation Format: Catherine S. Grasso, Jennifer Tsoi, Gabriel Abril-Rodriguez, Michael J. Quist, Petra Ross-MacDonald, Megan Wind-Rotolo, Antoni Ribas. Pharmacodynamics of immune checkpoint blockade therapy indicate drivers of response [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr A05.

Abstract IA01: Turning the heat up on pancreatic cancer: Lessons on overcoming a “cold” immunologic microenvironment

Abstract Immune checkpoint inhibitors (ICIs) are providing durable clinical responses in about 20% of cancer patients, but these agents have minimal effect in cancers without intratumoral T cells. Approaches that turn currently unresponsive cancers into ones that are more “antigenic” are needed to sensitize tumors to ICIs. Tumor genome mutations can express mutant proteins that are tumor-specific and not expressed on normal cells (neoantigens), and cancers with the highest mutational burdens are more likely to respond to single-agent ICIs. However, most cancers have lower mutational loads resulting in lower antigenicity, weaker endogenous T-cell repertoires, and T cells in the tumor. The best example of a high mutation load cancer is mismatch repair deficient (MMRd) cancers; these cancers often have &amp;gt;1,000 mutations/exome and have a &amp;gt;50% response to anti-PD-1 ICIs. However, cancers including pancreatic ductal adenocarcinoma (PDA) and microsatellite stable colorectal carcinoma (MSS CRC) have on average only 50-70 expressed mutations per exome and do not respond to single-agent ICIs. Emerging data suggest that it should be possible to develop precision immunology approaches that combine a neoantigen targeting vaccine to activate and expand the limited repertoire of T cells specific for the expressed neoantigens found in low-mutation cancers, with ICIs to induce clinically relevant antitumor responses. Challenges to successful immunization include knowledge about the repertoire and functional state of pre-existing antitumor T cells, identification of the best adjuvants, and approaches that more precisely predict which expressed neoantigens are the best T-cell targets for immunization. In addition, we now appreciate that there are many different immune-regulatory signals on T cells, monocytes and other tumor microenvironment cell populations that are likely regulated by the genetic alterations specific to a given patient’s tumor. This talk will discuss current knowledge of precision immune oncology and novel clinical trial approaches under development.

Regulation of gene expression by DNA methylation with cytotoxic T lymphocytes evaluation in consensus molecular subtypes of colorectal cancer.

25 Background: Low cytotoxic T lymphocyte (CTLs) infiltration in colorectal cancer (CRC) tumors is a challenge to treatment with immune checkpoint inhibitors. Consensus molecular subtypes (CMS) classify patients based on tumor attributes, and CMS1 patients include the majority of patients with high CTL infiltration and “inflamed” tumors. Epigenetic modification plays a critical role in gene expression and therapy resistance. Therefore, in this study we compared DNA methylation, gene expression, and CTL infiltration of CMS1 patients to other CMS groups to determine targets for improving immunotherapy in CRC. Methods: RNA-seq (n = 511) and DNA methylation (n = 316) from The Cancer Genome Atlas databases were used to determine gene expression and methylation profiles based on CMSs. CMS1 was used as a reference and compared to other subtypes (CMS2-4). Microenvironment Cell Populations- counter (MCPcounter) was used to determine tumor CTL infiltration. Genes with significantly different expression (p &lt; 0.01, LogFC≥|1.5|) and difference of mean methylation β value ≥|0.25| were integrated for Pearson correlation coefficient analysis with MCPcounter score (r &gt; |0.7|). Results: Comparing CMS1 and CMS2, ARHGAP9, TBX21, and LAG3 were differentially methylated and correlated with CTL scores. ARHGAP9 and TBX21 were decreased and hypomethylated in CMS2. Comparing CMS1 and CMS3, ARHGAP9, TBX21, FMNL1, HLA-DPB1, and STX11 were downregulated in CMS3 and highly correlated with CTL scores. ARHGAP9, FMNL1, HLA-DPB1, and STX11 were hypomethylated in CMS3 and TBX21 was methylated in both, but had a higher methylation ratio in CMS1. Comparing CMS1 and CMS4, TBX21 was the only gene downregulated, hypomethylated, and highly correlated with CTL scores in CMS4 patients. Conclusions: We found six genes differentially expressed, differentially methylated, and highly correlated with CTL infiltration when comparing CMS1 to other CMS groups. Specifically, TBX21 was the only gene highly correlated with CTL scores with differential gene expression and methylation in CMS2-4 when compared to CMS1. Thus, T-bet may be a critical regulator of T cell responses in CRC.

Network analysis to reveal BTK as a link between myeloid and T cells in TLR signaling in colorectal cancer.

30 Background: Colorectal cancer (CRC) is the second-leading cause of cancer mortality in the US today. Recent advances in immunotherapy have only been shown to benefit a limited subgroup of patients with CRC. In other malignancies, activation of Toll-like receptors (TLRs) has been shown to overcome resistance to immunotherapy, such as immune checkpoint inhibition (ICI). In this study, using publicly available data and informatics-based analysis, we identified BTK as a critical link between TLR signaling and T cells in the CRC tumor microenvironment. Methods: Using RNA-seq data from The Cancer Genome Atlas (TCGA) and the Microenvironment Cell Populations (MCP)-Counter, abundance scores were generated for the tumor microenvironment of each patient. A curated TLR gene panel was generated using Reactome and GO. Pearson analysis was used to evaluate each pairwise combination of genes and cell-types. Significance was determined by the correlation coefficient, r ≥ | 0.7 | with a p-value &lt; 0.05. Network analysis was performed using the Girvan–Newman algorithm to establish critical connections across these features. Results: After establishing a 453 gene TLR panel and creating MCP-Counter scores, correlation analysis demonstrated strong correlations between 54 different genes and 7 cell-types. As expected the most genes were associated with monocytic lineage cells' (30) and 'myeloid dendritic cells' (7). Only 5 genes were significantly associated with 'T cells'. Genes and cell-types that were highly correlated were then further analyzed for network association. From this analysis, BTK was identified as a critical edge acting as the primary link between ‘myeloid cells’ and ‘T cells’. Conclusions: Developing novel strategies for the treatment of CRC is critical and immunotherapy represents an area ripe for advancement. Informatics based analysis combined with publicly available data provides us with an opportunity to shape pre-clinical and translational studies. Using this approach, we have identified BTK as a critical link between myeloid cells and T cells in the tumor microenvironment in CRC. Further studies in our laboratory will focus confirming these findings for translation into patients.

Transcriptional Characterization Of The Tumor Immune Microenvironment And Its Prognostic Value For Locally Advanced Lung Adenocarcinoma In A Chinese Population.

ObjectiveWe investigated the relationship of the transcriptional tumor immune microenvironment with prognosis of patients with locally advanced lung adenocarcinoma (LUAD).Materials and methodsA targeted RNA-Seq approach was used to measure the abundance of 395 immune-related transcripts of 24 formalin-fixed paraffin embedded (FFPE) tumor specimens from our institution and transcription data of 85 matched LUAD samples from The Cancer Genome Atlas (TCGA). Gene set variation analysis (GSVA) was used to identify gene sets related to prognosis, and the microenvironment cell-population (MCP)-counter method was used to quantify infiltrated immune cells. Survival analysis with the log rank test was used to determine the relationships of different immune-related transcripts with prognosis. Cox proportional hazards models were also used to identify risk factors associated with poor prognosis.ResultsAmong our patients, GSVA and the log rank test demonstrated that enrichment of the antigen processing pathway (P = 0.01) correlated with a favorable prognosis. MCP-counter and survival analysis demonstrated that greater CD8 T cell infiltration correlated with a favorable prognosis (P = 0.05), but greater infiltration of neutrophils (P = 0.014) and NK cells (P = 0.015) correlated with poor prognoses. Cox hazard analysis showed that greater infiltration of neutrophils was an independent risk factor for poor prognosis. These results were consistent with LUAD data from TCGA.ConclusionWhen integrated with computational bioinformatics methods, targeted RNA-Seq from FFPE specimens provides profiles of the tumor immune microenvironment that have prognostic value for patients with locally advanced LUAD.

Exploratory analyses of consensus molecular subtype-dependent associations of TP53 mutations with immunomodulation and prognosis in colorectal cancer

BackgroundAccumulating evidence suggests immunomodulatory and context-dependent effects of TP53 mutations in cancer. We performed an exploratory analysis of the transcriptional, immunobiological and prognostic associations of TP53 mutations within the gene expression-based consensus molecular subtypes (CMSs) of colorectal cancer (CRC).Materials and methodsIn a single-hospital series of 401 stage I–IV primary CRCs, we sequenced the whole coding region of TP53 and analysed CMS-dependent transcriptional consequences of the mutations by gene expression profiling. Immunomodulatory associations were validated by multiplex, fluorescence-based immunohistochemistry of immune cell markers. Prognostic associations of TP53 mutations were analysed in an aggregated series of 635 patients classified according to CMS, including publicly available data from a French multicentre cohort (GSE39582).ResultsTP53 mutations were found in 60% of the CRCs. However, gene set enrichment analyses indicated that their transcriptional consequences varied among the CMSs and were most pronounced in CMS1-immune and CMS4-mesenchymal. Subtype specificity was primarily seen as an upregulation of gene sets reflecting cell cycle progression in CMS4 and a downregulation of T cell activity in CMS1. The subtype-dependent immunomodulatory associations were reinforced by significant depletion of several immune cell populations in mutated tumours compared with wild-type (wt) tumours exclusively in CMS1, including cytotoxic lymphocytes (adjusted p value in CMS1=0.002 and CMS2−4>0.9, Microenvironment Cell Populations (MCP)-counter algorithm). This was validated by immunohistochemistry-based quantification of tumour infiltrating CD8+ cells. Within CMS1, the immunomodulatory association of TP53 mutations was strongest among microsatellite stable (MSS) tumours, and this translated into a propensity for metastatic disease and poor prognostic value of the mutations specifically in the CMS1/MSS subtype (both series overall survival: TP53 mutation vs wt: HR 5.52, p=0.028).ConclusionsIntegration of TP53 mutation status with the CMS framework in primary CRC suggested subtype-dependent immunobiological associations with prognostic and potentially immunotherapeutic implications, warranting independent validation.

Bioinformatics profiling utilized a nine immune-related long noncoding RNA signature as a prognostic target for pancreatic cancer.

To identify an immune-related long noncoding RNA (lncRNA) signature with potential prognostic value for patients with pancreatic cancer. Pancreatic cancer samples with available clinical information and whole genomic mRNA expression data obtained from The Cancer Genome Atlas (TCGA) were enrolled in our research. The immune score of each sample was calculated according to the expression level of immune-related genes and used to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high- and low-risk groups were separated on the basis of the median risk score. The prediction reliability was further evaluated in the validation set and combination set. Both gene set enrichment analysis (GSEA) and principal component analysis (PCA) were performed for functional annotation, and the microenvironment cell population record was applied to evaluate the immune composition and purity of the tumor. A cohort of 176 samples was included in this study. A total of 163 immune-related lncRNAs were collected according to Pearson correlation analyses between immune score and lncRNA expression |R| > 0.5, P < 0.01). Nine immune-related lncRNAs (AL138966.2, AL133520.1, AC142472.1, AC127024.5, AC116913.1, AC083880.1, AC124016.1, AC008443.5, and AC092171.5) with the most significant prognostic values (P < 0.01) were identified. In the training set, it was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group (P < 0.001); meanwhile, similar results were found in the validation set, combination set and various stratified sets (P < 0.05, P < 0.001, P < 0.05, respectively). Moreover, the signature was identified as an independent prognostic factor and significantly associated with the OS of pancreatic cancer. The area under curve (AUC) of the receiver operating characteristic curve (ROC curve) for the nine lncRNA signature in predicting the 2-year survival rate was 0.703. In addition, the low-risk and high-risk groups displayed different distributed patterns in PCA and different immune statuses in the GSEA. The signature indicated decreased purity of the tumor by implying a lower proportion of cancer cells along with an increasing enrichment of fibroblasts, myeloid dendritic cells, and monocytic lineage cells. Our research suggests that the immune-related lncRNA signature possesses latent prognostic value for patients with pancreatic cancer and may provide new information for immunological research and treatment in pancreatic cancer.

PO-390 Image-guided stereotactic molecular profiling of samples taken in- and outside conventional tumour boundaries highlight extensive infiltration of tumour cells in diffuse gliomas

IntroductionDiffuse gliomas are highly infiltrative tumours of the central nervous system that lack effective treatment options and suffer from poor survival. We and others have used DNA methylation and gene expression profiling to stratify these tumours into clinically relevant subtypes. Nevertheless, diffuse gliomas are notoriously heterogeneous and a single biopsy is unlikely to reflect all tumour cell populations. Advanced sampling schemes guided by imaging are needed for accurate delineation of heterogeneity.Material and methodsWe obtained 74 stereotactic image-guided biopsies in eight patients with glioma prior to craniotomy in addition to 102 multi-sector glioma samples from 25 patients from outside sources. Patients underwent extensive imaging including standard magnetic resonance imaging and various advanced modalities. For each patient, multiple biopsies were taken from the tumour core, tumour margin and outside of visible imaging abnormalities and each sample was histologically assessed by two board-certified pathologists. We performed methylation profiling on all samples. We used supervised machine learning to determine methylation subtype composition and predict transcriptional subtypes in each sample. Genome wide DNA copy number was inferred.Results and discussionsPrincipal component analysis of DNA methylation separated samples based on IDH status and tumour cell content. Tumour signal could be detected in samples far outside tumour margins on standard MRI, despite demonstrating lower tumour purity and inconclusive tumour subtypes. Samples taken from inside imaging abnormalities demonstrated concordant methylation subtypes, suggesting that this classifier is reliable and not subject to heterogeneity due to microenvironment cell populations as often the case with gene expression subtyping. Despite uniformity in classification, IDH mutant tumours demonstrated a higher degree of epigenetic heterogeneity compared to wild-type tumours, reflecting hypermethylation established by IDH oncometabolites. Although still imperfect, advanced imaging substantially improved tumour delineation. While samples from inside imaging abnormalities are optimal for diagnostic use, tumour cells infiltrate well beyond these boundaries and treatment of these regions should be considered when safe and feasible.ConclusionThese data show methylation profiling is stable across multiple biopsies and could serve as a powerful diagnostic biomarker. Moreover, advanced imaging can more accurately delineate tumour margins and could help direct treatment.

3D bone models to study the complex physical and cellular interactions between tumor and the bone microenvironment.

As the complexity of interactions between tumor and its microenvironment has become more evident, a critical need to engineer in vitro models that veritably recapitulate the 3D microenvironment and relevant cell populations has arisen. This need has caused many groups to move away from the traditional 2D, tissue culture plastic paradigms in favor of 3D models with materials that more closely replicate the in vivo milieu. Creating these 3D models remains a difficult endeavor for hard and soft tissues alike as the selection of materials, fabrication processes, and optimal conditions for supporting multiple cell populations makes model development a nontrivial task. Bone tissue in particular is uniquely difficult to model in part because of the limited availability of materials that can accurately capture bone rigidity and architecture, and also due to the dependence of both bone and tumor cell behavior on mechanical signaling. Additionally, the bone is a complex cellular microenvironment with multiple cell types present, including relatively immature, pluripotent cells in the bone marrow. This prospect will focus on the current 3D models in development to more accurately replicate the bone microenvironment, which will help facilitate improved understanding of bone turnover, tumor-bone interactions, and drug response. These studies have demonstrated the importance of accurately modelling the bone microenvironment in order to fully understand signaling and drug response, and the significant effects that model properties such as architecture, rigidity, and dynamic mechanical factors have on tumor and bone cell response.

Immune gene expression and response to chemotherapy in advanced breast cancer

Background:Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting.Methods:In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method.Results:Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03–2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43–10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders.Conclusions:Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.

* The Impact of Age on Skeletal Muscle Progenitor Cell Survival and Fate After Injury.

Sarcopenia is defined as the loss of skeletal muscle mass and function due to age, and represents a major cause of disability in the elderly population. The contributing factors to the onset of sarcopenia are not well defined, but appear to involve age-dependent changes in both the tissue microenvironment and muscle progenitor cell (MPC) population. MPC transplantation has the potential to be a novel therapy for treatment of muscle dysfunction due to aging or injury, but has not shown significant clinical efficacy to date. The goal of this research was to use a rat model of skeletal muscle injury to examine the differential effects of age on MPC survival, differentiation, and tissue regeneration after transplantation. Fluorescently labeled MPCs, derived from young (YMPCs) and adult (AMPCs) donor rats, were transplanted in the injured tibialis anterior (TA) muscles of young, adult, and aged rats. Our results demonstrated that integration and maturation of YMPCs into mature myofibers were dependent on the age of the host microenvironment; whereas, the integration and maturation of AMPCs were less dependent on age and more dependent on intrinsic cellular changes. These data suggest that the age of both the host microenvironment and cells for transplantation must be considered when designing cell therapy regimens.

Natural killer-like signature observed post therapy in locally advanced rectal cancer is a determinant of pathological response and improved survival.

Around 12-15% of patients with locally advanced rectal cancer undergo a pathologically complete response (tumor regression grade 4) to long-course preoperative chemoradiotherapy; the remainder exhibit a spectrum of tumor regression (tumor regression grade 1-3). Understanding therapy-related transcriptional alterations may enable better prediction of response as measured by progression-free and overall survival, in addition to aiding the development of improved strategies based on the underlying biology of the disease. To this end, we performed high-throughput gene expression profiling in 40 pairs of formalin-fixed paraffin-embedded rectal cancer biopsies and matched resections following long-course preoperative chemoradiotherapy (discovery cohort). Differential gene expression analysis was performed contrasting tumor regression grades in resections. Enumeration of the tumor microenvironment cell population was undertaken using in silico analysis of the transcriptional data, and real-time PCR validation of NCR1 undertaken. Immunohistochemistry and survival analysis was used to measure CD56+ cell populations in an independent cohort (n=150). Gene expression traits observed following long-course preoperative chemoradiotherapy in the discovery cohort suggested an increased abundance of natural killer cells in tumors that displayed a clinical response to CRT in a tumor regression grade-dependent manner. CD56+ natural killer-cell populations were measured by immunohistochemistry and found to be significantly higher in tumor regression grade 3 patients compared with tumor regression grade 1-2 in the validation cohort. Furthermore, it was observed that patients positive for CD56 cells after therapy had a better overall survival (HR=0.282, 95% CI=0.109-0.729, χ2=7.854, P=0.005). In conclusion, we have identified a novel post-therapeutic natural killer-like transcription signature in patients responding to long-course preoperative chemoradiotherapy. Furthermore, patients with a higher abundance of CD56-positive natural killer cells post long-course preoperative chemoradiotherapy had better overall survival. Therefore, harnessing a natural killer-like response after therapy may improve outcomes for locally advanced rectal cancer patients. Finally, we hypothesize that future assessment of this natural killer-like response in on-treatment biopsy material may inform clinical decision-making for treatment duration.

STAT3 in cancer: A double edged sword

The transcription factor signal transducer and activator of transcription (STAT) 3 is activated downstream of cytokines, growth factors and oncogenes to mediate their functions under both physiological and pathological conditions. In particular, aberrant/unrestrained STAT3 activity is detected in a wide variety of tumors, driving multiple pro-oncogenic functions. For that, STAT3 is widely considered as an oncogene and is the object of intense translational studies. One of the distinctive features of this factor is however, its ability to elicit different and sometimes contrasting effects under different conditions. In particular, STAT3 activities have been shown to be either pro-oncogenic or tumor-suppressive according to the tumor aetiology/mutational landscape, suggesting that the molecular bases underlining its functions are still incompletely understood. Here we discuss some of the properties that may provide the bases to explain STAT3 heterogeneous functions, and in particular how post-translational modifications contribute shaping its sub-cellular localization and activities, the cross talk between these activities and cell metabolic conditions, and finally how its functions can control the behaviour of both tumor and tumor microenvironment cell populations.

Effect of TCHL-based therapy on immune cell content in on-treatment, neoadjuvant-treated HER2-positive breast cancer patients.

583 Background: In the TCHL trial (NCT01485926) 78 women with HER2-positive breast cancer (BC) underwent neo-adjuvant treatment with either TCH (Docetaxel, Carboplatin, Trastuzumab) or TCHL (TCH + Lapatinib) therapy. Of the 78 patients, 24 consented to an optional on-treatment biopsy 20 days after 1 cycle of therapy. We analysed the impact of tumour infiltrating lymphocytes (TILs) on pathological complete response (pCR) and also determined the impact of TCH/TCHL therapy on immune cell modulation after 20 days of treatment. Methods: We assessed TIL and stromal lymphocytes (SL) counts using immunohistochemical staining with Haemotoxalyin+Eosin, AE1/AE3 and CD45 in formalin fixed paraffin embedded (FFPE) baseline biopsy samples and in fresh frozen (FF) biopsies taken 20-days post cycle 1 (Day-20) of TCH/TCHL. RNA libraries were generated, using the Truseq mRNA library prep kit on the Neoprep platform and sequenced on the NextSeq 500. We measured the transcriptomic profile of 8 pre and on-treatment sample pairs and then used the Microenvironment Cell Populations (MCP)-counter method to measure the abundance of 10 immune cell populations (T cells, CD8 T cells, cytotoxic lymphocytes, NK cells, B lineage, myeloid dendritic cells, neutrophils, endothelial cells and fibroblasts). Results: We found that higher baseline levels of TILs (p = 0.045) but not SL were associated with an increased likelihood of a patient achieving a pCR to TCH/L based therapy. We found in day 20 on-treatment biopsies of women that subsequently went onto have a pCR that levels of SLs but not TILs were significantly higher (p = 0.049) than in those women who did not have a pCR. Finally we found significant increases in the level of monocytes (p = 0.05) and fibroblasts (p = 0.01), but not other immune cell populations, in the day 20 on-treatment biopsies in comparison with the mutated pre-treatment biopsies. Conclusions: In our study baseline TILs but not SLs have a predictive role in the likelihood of a patient achieving a pCR. We also found that TCHL based therapy significantly altered both monocytes and fibroblasts, indicating a possible role for these immune subtypes in response to TCHL therapy.