Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome.

Pancreatic cancer remains a disease with unmet clinical needs and inadequate diagnostic, prognostic, and predictive biomarkers. In-depth characterization of the disease proteome is limited. This study thus aims to define and describe protein networks underlying pancreatic cancer and identify protein centric subtypes with clinical relevance. Mass spectrometry-based proteomics was used to identify and quantify the proteome in tumor tissue, tumor-adjacent tissue, and patient-derived xenografts (PDX)-derived cell lines from patients with pancreatic cancer, and tissues from patients with chronic pancreatitis. We identified, quantified, and characterized 11,634 proteins from 72 pancreatic tissue samples. Network focused analysis of the proteomics data led to identification of a tumor epithelium-specific module and an extracellular matrix (ECM)-associated module that discriminated pancreatic tumor tissue from both tumor adjacent tissue and pancreatitis tissue. On the basis of the ECM module, we defined an ECM-high and an ECM-low subgroup, where the ECM-high subgroup was associated with poor prognosis (median survival months: 15.3 vs. 22.9 months; log-rank test, P = 0.02). The ECM-high tumors were characterized by elevated epithelial-mesenchymal transition and glycolytic activities, and low oxidative phosphorylation, E2F, and DNA repair pathway activities. This study offers novel insights into the protein network underlying pancreatic cancer opening up for proteome precision medicine development. Significance: Pancreatic cancer lacks reliable biomarkers for prognostication and treatment of patients. We analyzed the proteome of pancreatic tumors, nonmalignant tissues of the pancreas and PDX-derived cell lines, and identified proteins that discriminate between patients with good and poor survival. The proteomics data also unraveled potential novel drug targets.

Dynamic changes in the T cell receptor repertoire during treatment with radiotherapy combined with an immune checkpoint inhibitor.

Previous studies have indicated a synergistic effect between radiotherapy and immunotherapy. A better understanding of how this combination affects the immune system can help to clarify its role in the treatment of metastatic cancer. We performed T cell receptor (TCR) sequencing on 46 sequentially collected samples from 15 patients with stage IV non-small cell lung cancer, receiving stereotactic body radiotherapy combined with a programmed cell death ligand-1 (PD-L1) inhibitor. TCR repertoire diversity was assessed using Rényi diversity curves and the Shannon diversity index. TCR clones were tracked over time. We found decreasing or stable diversity in the best responders, and an increase in diversity at progression in patients with an initial response. Expansion of TCR clones was more often seen in responders. Several patients also developed new clones of high abundance. This seemed to be more related to radiotherapy than to immune checkpoint blockade. In summary, we observed similar dynamics in the TCR repertoire as have been described with immunotherapy alone. In addition, the occurrence of new unique clones of high abundance after radiotherapy may indicate that radiotherapy functions as a personalized cancer vaccine.

Immune checkpoint blockade in the treatment of advanced non-small cell lung cancer - predictors of response and impact of previous radiotherapy.

BACKGROUND: The implementation of immune checkpoint inhibitors (ICI) into the standard care of advanced non-small cell lung cancer (NSCLC) has improved prognosis for this group of patients. However, long-term survival is rare. The aim of the study was to identify predictors of response and, especially, to investigate the impact radiotherapy might have on duration of response. MATERIAL AND METHODS: The association between pretreatment patient/tumor characteristics and progression-free survival (PFS), overall survival (OS), and lung cancer-specific survival was investigated in 78 patients receiving an ICI as ≥2nd line treatment for advanced NSCLC, using Cox regression analysis. Due to competing risk, cause-specific deaths were also examined with cumulative incidence plots. RESULTS: Median OS was 12.6 months (95% CI 7.8-18.2) and median PFS 4.1 months (95% CI 3.0-6.2), after median follow-up time of 49.7 months (range 20.9-51.5). Increasing CRP and neutrophil/lymphocyte ratio (NLR), were associated with poor PFS (CRP: HR 1.49, 95% CI 1.12-1.98; NLR: HR 1.59, 95% CI 1.22-1.85) and OS (CRP: HR 1.94, 95% CI 1.47-2.56; NLR: HR 1.54, 95% CI 1.27-1.87). Radiotherapy prior to immunotherapy was not significantly associated with patient outcome. However, when the dataset was split at 6 months of follow-up, to be able to identify early and late predictors of prognosis, we found that patients receiving radiotherapy <6 months prior to immunotherapy had better PFS (HR: 0.27, 95% CI 0.09-0.84) and lung cancer-specific survival (HR: 0.41, 95% CI 0.18-0.95) after the first 6 months of follow-up, while increasing CRP (PFS: HR1.61, 95% CI 1.21-2.14; OS: HR2.04, 95% CI 1.51-2.74) and NLR (PFS: HR 1.57, 95% CI 1.29-1.91; OS: HR 1.63, 95% CI 1.35-1.97) were predictors of poor short-term prognosis. CONCLUSIONS: Radiotherapy may be of importance to achieve a long-lasting response to immunotherapy, while indicators of systemic inflammation can help in identifying patients with poor short-term prognosis.

An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment.

How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture.

Identification of microRNAs involved in pathways which characterize the expression subtypes of NSCLC.

Dysregulation of microRNAs is a common mechanism in the development of lung cancer, but the relationship between microRNAs and expression subtypes in non-small-cell lung cancer (NSCLC) is poorly explored. Here, we analyzed microRNA expression from 241 NSCLC samples and correlated this with the expression subtypes of adenocarcinomas (AD) and squamous cell carcinomas (SCC) to identify microRNAs specific for each subtype. Gene set variation analysis and the hallmark gene set were utilized to calculate gene set scores specific for each sample, and these were further correlated with the expression of the subtype-specific microRNAs. In ADs, we identified nine aberrantly regulated microRNAs in the terminal respiratory unit (TRU), three in the proximal inflammatory (PI), and nine in the proximal proliferative subtype (PP). In SCCs, 1, 5, 5, and 9 microRNAs were significantly dysregulated in the basal, primitive, classical, and secretory subtypes, respectively. The subtype-specific microRNAs were highly correlated to specific gene sets, and a distinct pattern of biological processes with high immune activity for the AD PI and SCC secretory subtypes, and upregulation of cell cycle-related processes in AD PP, SCC primitive, and SCC classical subtypes were found. Several in silico predicted targets within the gene sets were identified for the subtype-specific microRNAs, underpinning the findings. The results were significantly validated in the LUAD (n = 492) and LUSC (n = 380) TCGA dataset (False discovery rates-corrected P-value < 0.05). Our study provides novel insight into how expression subtypes determined with discrete biological processes may be regulated by subtype-specific microRNAs. These results may have importance for the development of combinatory therapeutic strategies for lung cancer patients.

miRNA expression changes during the course of neoadjuvant bevacizumab and chemotherapy treatment in breast cancer.

One of the hallmarks of cancer is sustained angiogenesis. Favorable results have been reported in some breast cancer (BC) patients receiving antiangiogenic therapy with bevacizumab (Bev) in combination with chemotherapy, and further knowledge on how Bev can be optimally combined with conventional treatment to increase efficacy is strongly needed. In this randomized, neoadjuvant phase II clinical trial, 132 patients with HER2-negative, nonmetastatic BC were treated with Bev in combination with sequential chemotherapy. Biopsies were sampled before treatment, after 12 weeks with anthracycline and after taxane therapy at week 25. MicroRNA (miRNA) expression profiling was performed on biopsies from each time point. Altogether, 241 biopsies were analyzed with the aim of identifying miRNA-based biomarkers of response to therapy. Results from the miRNA analyses were reported for the ER-positive cohort, which were previously demonstrated to benefit from antiangiogenic therapy in this study. For both treatment arms of this cohort, significantly different expression was observed for 217 miRNAs between objective responding and nonresponding patients before treatment initiation. These miRNAs have been linked to regulation of epithelial-mesenchymal transition, metastasis, and tumor growth, among other processes. Bev in combination with chemotherapy resulted in similar miRNA changes to chemotherapy alone. However, the deregulation of miRNA expression occurred earlier in the Bev arm. In both arms, tumor suppressor miRNAs were found upregulated after treatment, while oncogenic miRNAs were downregulated in the Bev arm. Patients responding to Bev showed a strong correlation between deregulated miRNAs and decreased proliferation score during the course of treatment, with downregulation of miR-4465 as the strongest indicator of reduced proliferation. Integrative analyses at miRNA-, gene-, and protein expression further indicated a longitudinal decrease in proliferation. Altogether, the results indicate that proliferation might represent a predictive factor for increased Bev sensitivity, which may aid in the identification of patients who could potentially benefit from Bev.

The immune microenvironment in non-small cell lung cancer is predictive of prognosis after surgery.

The impact of the tumor immune microenvironment on overall survival in non-small cell lung cancer (NSCLC) has been studied, but there is little information on its relevance for risk of relapse after surgery. Understanding more about the immune microenvironment in previously untreated NSCLC could help in identifying high-risk patients and patients more likely to benefit from neoadjuvant/adjuvant immunotherapy. Here, we examined gene expression in 399 surgically derived NSCLC samples and 47 samples from normal lung, using Agilent microarray and RNA sequencing. In 335 of the tumor samples, programmed death-ligand 1 (PD-L1) expression was evaluated by immunohistochemistry. Gene expression was used to estimate content of immune cells and to calculate an immune score. Properties of the immune microenvironment, and its impact on prognosis, were compared in histological subgroups and gene expression subtypes. Tumors with an active immune microenvironment were found for both adenocarcinomas (AD) and squamous cell carcinomas (SCC). In AD, high immune score and high estimates of several immune cell types belonging to the adaptive immune system were associated with better progression-free survival (PFS), while in SCC, no association between immune characteristics and PFS was found. The immune microenvironment, including PD-L1 expression, and its impact on prognosis showed clear differences in AD and SCC gene expression subtypes. In conclusion, the NSCLC immune microenvironment is predictive of prognosis after surgery. Lung AD and SCC gene expression subtypes should be investigated as potential prognostic biomarkers in patients treated with immune checkpoint inhibitors.

miR-342-5p as a Potential Regulator of HER2 Breast Cancer Cell Growth.

BACKGROUND: HER2 positive Breast Cancers (BC) have aggressive behavior and poor prognosis. Previously, we have identified miR-342-5p as an upstream regulator of HER2 signaling, as well as inhibitor of HER2 positive BC cell line growth. OBJECTIVE: Here, we aimed to further investigate the molecular mechanisms behind miR-342-5pinduced HER2 pathway deregulation. METHOD: Two HER2 amplified breast cancer cell lines were transiently transfected with miR-342-5p mimic or negative control, and gene expression was analyzed by Agilent microarrays. Three clinical datasets with BC patients were used to identify correlations between candidate genes and miR-342- 5p, and associations with survival. RESULTS: Pathway analyses of all deregulated genes revealed a significant suppression of the HER2 downstream pathways ERK/MAPK and SAPK/JNK, whereas the miR-342-5p predicted target genes were enriched for pathways associated with cell motility.Biological functions linked to mitochondrial stability were ranked among the top toxicological functions in both gene lists. Among the most deregulated genes, Cytochrome B5 Reductase 3 (CYB5R3) and Rap Guanine Nucleotide Exchange Factor 6 (RAPGEF6) significantly anticorrelated and correlated, respectively, with miR-342-5p in all three clinical BC datasets. Low CYB5R3 levels and high RAPGEF6 levels were significantly associated with survival, although this was not directly associated with HER2 expression. CONCLUSION: Our data suggest that miR-342-5p overexpression in HER2 positive BC cell lines elicits broad effects on HER2 downstream signaling, cell motility and mitochondrial stability. Together these effects may render cells less proliferative and more sensitive to cellular stress.

Intratumor heterogeneity defines treatment-resistant HER2+ breast tumors.

Targeted therapy for patients with HER2-positive (HER2+) breast cancer has improved overall survival, but many patients still suffer relapse and death from the disease. Intratumor heterogeneity of both estrogen receptor (ER) and HER2 expression has been proposed to play a key role in treatment failure, but little work has been done to comprehensively study this heterogeneity at the single-cell level. In this study, we explored the clinical impact of intratumor heterogeneity of ER protein expression, HER2 protein expression, and HER2 gene copy number alterations. Using combined immunofluorescence and in situ hybridization on tissue sections followed by a validated computational approach, we analyzed more than 13 000 single tumor cells across 37 HER2+ breast tumors. The samples were taken both before and after neoadjuvant chemotherapy plus HER2-targeted treatment, enabling us to study tumor evolution as well. We found that intratumor heterogeneity for HER2 copy number varied substantially between patient samples. Highly heterogeneous tumors were associated with significantly shorter disease-free survival and fewer long-term survivors. Patients for which HER2 characteristics did not change during treatment had a significantly worse outcome. This work shows the impact of intratumor heterogeneity in molecular diagnostics for treatment selection in HER2+ breast cancer patients and the power of computational scoring methods to evaluate in situ molecular markers in tissue biopsies.

Correction to: A systematic comparison of copy number alterations in four types of female cancer.

After publication of the original article [1] the authors found that the article contained an incorrect version of Fig. 4. This does not affect the results and conclusions of the article.

DNA methylation at enhancers identifies distinct breast cancer lineages.

Breast cancers exhibit genome-wide aberrant DNA methylation patterns. To investigate how these affect the transcriptome and which changes are linked to transformation or progression, we apply genome-wide expression-methylation quantitative trait loci (emQTL) analysis between DNA methylation and gene expression. On a whole genome scale, in cis and in trans, DNA methylation and gene expression have remarkably and reproducibly conserved patterns of association in three breast cancer cohorts (n = 104, n = 253 and n = 277). The expression-methylation quantitative trait loci associations form two main clusters; one relates to tumor infiltrating immune cell signatures and the other to estrogen receptor signaling. In the estrogen related cluster, using ChromHMM segmentation and transcription factor chromatin immunoprecipitation sequencing data, we identify transcriptional networks regulated in a cell lineage-specific manner by DNA methylation at enhancers. These networks are strongly dominated by ERα, FOXA1 or GATA3 and their targets were functionally validated using knockdown by small interfering RNA or GRO-seq analysis after transcriptional stimulation with estrogen.

A systematic comparison of copy number alterations in four types of female cancer.

BACKGROUND: Detection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways. METHODS: In this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altered regions and the associated genes were analyzed by Ingenuity Pathway Analysis (IPA) to detect over-represented pathways and functions within the identified gene sets. RESULTS AND DISCUSSION: Analyses of high-resolution copy number alterations in four different female cancer types are presented. For appropriately adjusted segmentation parameters the two segmentation algorithms CBS and PCF performed similarly. We identified one region at 8q24.3 with focal aberrations that was altered at significant frequency across all four cancer types. Considering both, broad regions and focal peaks, three additional regions with gains at significant frequency were revealed at 1p21.1, 8p22, and 13q21.33, respectively. Several of these events involve known cancer-related genes, like PPP2R2A, PSCA, PTP4A3, and PTK2. In the female reproductive system (ovarian, endometrial, and cervix [OEC]), we discovered three common events: copy number gains at 5p15.33 and 15q11.2, further a copy number loss at 8p21.2. Interestingly, as many as 75% of the aberrations (75% amplifications and 86% deletions) identified by GISTIC were specific for just one cancer type and represented distinct molecular pathways. CONCLUSIONS: Our results disclose that some prominent copy number changes are shared in the four examined female, hormone-dependent cancer whereas others are definitive to specific cancer types.

Differential DNA methylation analysis of breast cancer reveals the impact of immune signaling in radiation therapy.

Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation (n = 20) and after receiving 10-24 Gray (Gy) (n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected for technical validation by pyrosequencing. Eighty-two differentially methylated genes were identified in irradiated (n = 11) versus nonirradiated (n = 19) samples (false discovery rate, FDR = 1.1%). Methylation levels in pathways belonging to the immune system were most altered after RT. Based on methylation levels before irradiation, a panel of five genes (H2AFY, CTSA, LTC4S, IL5RA and RB1) were significantly associated with clinical response (p = 0.041). Furthermore, the degree of methylation changes for 2,516 probes correlated with the given radiation dose. Within the 2,516 probes, an enrichment for pathways involved in cellular immune response, proliferation and apoptosis was identified (FDR < 5%). Here, we observed clear differences in methylation levels induced by radiation, some associated with response to treatment. Our study adds knowledge on the molecular mechanisms behind radiation response.

Genome-wide association study in breast cancer survivors reveals SNPs associated with gene expression of genes belonging to MHC class I and II.

INTRODUCTION: We investigated the effect of genetic variation on gene expression in blood from a cohort of BC survivors. Further, we investigated the associations that were specific for BC survivors by performing identical analyses for a group of healthy women and comparing the results. METHODS: eQTL analysis was performed for 288 BC survivors (full data set). Further, using a subset of the data, eQTL analyses were performed on 288 BC survivors and on 81 healthy women separately and results were compared. RESULTS: A large number of associations were observed for the BC survivors, and the expression of human leukocyte antigen genes was found associated with SNPs in 100 genes. The comparison analyses with healthy women revealed associations occurring specifically in BC survivors, and the genes showed enrichment for immune system processes. CONCLUSIONS: The results suggest that the immune system has a different constitution in BC survivors compared to healthy women.

SNP in TXNRD2 associated with radiation-induced fibrosis: a study of genetic variation in reactive oxygen species metabolism and signaling.

PURPOSE: The aim of the study was to identify noninvasive markers of treatment-induced side effects. Reactive oxygen species (ROS) are generated after irradiation, and genetic variation in genes related to ROS metabolism might influence the level of radiation-induced adverse effects (AEs). METHODS AND MATERIALS: 92 breast cancer (BC) survivors previously treated with hypofractionated radiation therapy were assessed for the AEs subcutaneous atrophy and fibrosis, costal fractures, lung fibrosis, pleural thickening, and telangiectasias (median follow-up time 17.1 years). Single-nucleotide polymorphisms (SNPs) in 203 genes were analyzed for association to AE grade. SNPs associated with subcutaneous fibrosis were validated in an independent BC survivor material (n=283). The influence of the studied genetic variation on messenger ribonucleic acid (mRNA) expression level of 18 genes previously associated with fibrosis was assessed in fibroblast cell lines from BC patients. RESULTS: Subcutaneous fibrosis and atrophy had the highest correlation (r=0.76) of all assessed AEs. The nonsynonymous SNP rs1139793 in TXNRD2 was associated with grade of subcutaneous fibrosis, the reference T-allele being more prevalent in the group experiencing severe levels of fibrosis. This was confirmed in another sample cohort of 283 BC survivors, and rs1139793 was found significantly associated with mRNA expression level of TXNRD2 in blood. Genetic variation in 24 ROS-related genes, including EGFR, CENPE, APEX1, and GSTP1, was associated with mRNA expression of 14 genes previously linked to fibrosis (P≤.005). CONCLUSION: Development of subcutaneous fibrosis can be associated with genetic variation in the mitochondrial enzyme TXNRD2, critically involved in removal of ROS, and maintenance of the intracellular redox balance.

Methylation profiling with a panel of cancer related genes: association with estrogen receptor, TP53 mutation status and expression subtypes in sporadic breast cancer.

Breast cancer is a heterogeneous disease that can be divided in subtypes based on histology, gene expression profiles as well as differences in genomic aberrations. Distinct global DNA methylation profiles have been reported in normal breast epithelial cells as well as in breast tumors. However, the influence of the tumor methylome on the previously described subgroups of breast cancer is not fully understood. Here we report the DNA methylation profiles of 80 breast tumors using a panel of 807 cancer related genes interrogating 1505 CpG sites. We identified three major clusters based on the methylation profiles; one consisting of mainly tumors of myoepithelial origin and two other clusters with tumors of predominantly luminal epithelial origin. The clusters were different with respect to estrogen receptor status, TP53 status, ErbB2 status and grade. The most significantly differentially methylated genes including HDAC1, TFF1, OGG1, BMP3, FZD9 and HOXA11 were confirmed by pyrosequencing. Gene Ontology analysis revealed enrichment for genes involved in developmental processes including homeobox domain genes (HOXA9, HOXA11, PAX6, MYBL2, ISL1 and IPF1) and (ETS1, HDAC1, CREBBP, GAS7, SPI1 and TBX1). Extensive correlation to mRNA expression was observed. Pathway analyses identified a significant association with canonical (curated) pathways such as hepatic fibrosis including genes like EGF, NGFR and TNF, dendritic cell maturation and the NF-κB signaling pathway. Our results show that breast tumor expression subtypes harbor major epigenetic differences and tumors with similar gene expression profiles might belong to epigenetically different subtypes. Some of the transcription factors identified, with key roles in differentiation and development might play a role in inducing and maintaining the different phenotypes.