Commonly used medications and endometrial cancer survival: a population-based cohort study.

Genomic Identification of Significant Targets (GISTIC) outputs for Circular Binary Segmentation (CBS) - or Piecewise Constant Fit (PCF) - segmented input data. The number of peaks attained by GISTIC on the y-axis is plotted against the two changing parameters α for CBS and γ for PCF on the x-axis. GISTIC peaks of amplification applying CBS-segmented data are illustrated in pink and PCF-segmented data in red, respectively. Deletion peaks are colored in green for CBS-segmented input data and in blue for PCF-segmented data. From top to bottom are shown GISTIC focal peaks for breast, ovarian, endometrial, and cervical cancers, to the left for PCF-segmented input data (A, C, E, and G) and to the right for CBS-segmented input data (B, D, F and H), respectively. For further analysis are the selected α and γ highlighted with a colored square. (PDF 362 kb

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

Presenting overrepresented words

En webapplikasjon for å presentere og analysere statistikk om overrepresenterte ord i DNA fra bakterier, samt verktøy for å jobbe med denne informasjonen i enkeltstående python-programmer

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

Peer reviewe

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

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

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

Abstract 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

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

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. Note to Correction: 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

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