The single-cell transcriptional landscape of lung carcinoid tumors

Lung carcinoid tumors, also referred to as pulmonary neuroendocrine tumors or lung carcinoids, are rare neoplasms of the lung with a more favorable prognosis than other subtypes of lung cancer. Still, some patients suffer from relapsed disease and metastatic spread. Several recent single-cell studies have provided detailed insights into the cellular heterogeneity of more common lung cancers, such as adeno- and squamous cell carcinoma. However, the characteristics of lung carcinoids on the single-cell level are yet completely unknown. To study the cellular composition and single-cell gene expression profiles in lung carcinoids, we applied single-cell RNA sequencing to three lung carcinoid tumor samples and normal lung tissue. The single-cell transcriptomes of carcinoid tumor cells reflected intertumoral heterogeneity associated with clinicopathological features, such as tumor necrosis and proliferation index. The immune microenvironment was specifically enriched in non-inflammatory monocyte-derived myeloid cells. Tumor-associated endothelial cells were characterized by distinct gene expression profiles. A spectrum of vascular smooth muscle cells and pericytes predominated the stromal microenvironment. We found a small proportion of myofibroblasts exhibiting features reminiscent of cancer-associated fibroblasts. Stromal and immune cells exhibited potential paracrine interactions which may shape the microenvironment via NOTCH, VEGF, TGFβ and JAK/STAT signaling. Moreover, single-cell gene signatures of pericytes and myofibroblasts demonstrated prognostic value in bulk gene expression data. Here, we provide first comprehensive insights into the cellular composition and single-cell gene expression profiles in lung carcinoids, demonstrating the non-inflammatory and vessel-rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets

A lactate shuttle system between tumour and stromal cells is associated with poor prognosis in prostate cancer

Background In a malignant tumour, cancer cells are embedded in stromal cells, namely cancer-associated fibroblasts (CAFs). These CAFs are now accepted as important players in cancer dynamics, being involved in tumour growth and progression. Although there are various reports on the interaction between tumour and stromal cells, the clinico-pathological significance of this cross-talk is still largely unknown. In this study, we aimed to characterise the expression of key metabolic proteins involved in glucose transport, pyruvate/lactate shuttle system, glycolytic metabolism and fatty acid oxidation in CAFs and tumour cells in different stages of malignant transformation. We further aimed to contextualise the clinico-pathological significance of these protein expression profiles with reference to known prognostic indicators, including biochemical recurrence in pT stage. Methods Prostate tissues were obtained from 480 patients with a median age of 64 years following radical prostatectomy with no previous hormonal therapy. Tissues were analysed for the expression of several key metabolism-related proteins in glands and surrounding fibroblasts by immunohistochemistry. Reliable markers of prognosis such as pT stage and biochemical recurrence were assessed for each case. Results We observed that prostate cancer cells did not rely mainly on glycolytic metabolism, while there was a high expression of MCT4 and CAIX - in CAFs. This corroborates the hypothesis of the "Reverse Warburg effect" in prostate cancer, in which fibroblasts are under oxidative stress and express CAIX, an established hypoxia marker. We found that alterations in the expression of metabolism-related proteins were already evident in the early stages of malignant transformation, suggesting the continuing alteration of CAFs from an early stage. Additionally, and for the first time, we show that cases showing high MCT4 expression in CAFs with concomitant strong MCT1 expression in prostate cancer (PCa) cells are associated with poor clinical outcome, namely pT3 stage of the tumour. Conclusions In summary, this work demonstrates for the first time the clinico-pathological significance of the lactate shuttle in prostate cancer. It also suggests that other alterations in CAFs may be useful prognostic factors, and further supports the use of MCT1/MCT4 as targets for PCa therapy.NPG received a fellowship from the Portuguese Foundation for Science and Technology (FCT), refs. SFRH/BD/61027/2009. This work was supported by the FCT grant ref. PTDC/SAUMET/113415/2009, under the scope of "Programa Operacional Tematico Factores de Competitividade" (COMPETE) of "Quadro Comunitario de Apoio III" and co-financed by Fundo Comunitario Europeu FEDER. JA was supported by a Boehringer Ingelheim Fonds fellowship

Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma

Recent developments in immuno-oncology demonstrate that not only cancer cells, but also the tumor microenvironment can guide precision medicine. A comprehensive and in-depth characterization of the tumor microenvironment is challenging since its cell populations are diverse and can be important even if scarce. To identify clinically relevant microenvironmental and cancer features, we applied single-cell RNA sequencing to ten human lung adenocarcinomas and ten normal control tissues. Our analyses revealed heterogeneous carcinoma cell transcriptomes reflecting histological grade and oncogenic pathway activities, and two distinct microenvironmental patterns. The immune-activated CP(2)E microenvironment was composed of cancer-associated myofibroblasts, proinflammatory monocyte-derived macrophages, plasmacytoid dendritic cells and exhausted CD8+ T cells, and was prognostically unfavorable. In contrast, the inert N(3)MC microenvironment was characterized by normal-like myofibroblasts, non-inflammatory monocyte-derived macrophages, NK cells, myeloid dendritic cells and conventional T cells, and was associated with a favorable prognosis. Microenvironmental marker genes and signatures identified in single-cell profiles had progonostic value in bulk tumor profiles. In summary, single-cell RNA profiling of lung adenocarcinoma provides additional prognostic information based on the microenvironment, and may help to predict therapy response and to reveal possible target cell populations for future therapeutic approaches

Aberrant Expression and Subcellular Localization of ECT2 Drives Colorectal Cancer Progression and Growth

ECT2 is an activator of RHO GTPases that is essential for cytokinesis. In addition, ECT2 was identified as an oncoprotein when expressed ectopically in NIH/3T3 fibroblasts. However, oncogenic activation of ECT2 resulted from N-terminal truncation, and such truncated ECT2 proteins have not been found in patients with cancer. In this study, we observed elevated expression of fulllength ECT2 protein in preneoplastic colon adenomas, driven by increased ECT2mRNAabundance and associated with APC tumorsuppressor loss. Elevated ECT2 levels were detected in the cytoplasm and nucleus of colorectal cancer tissue, suggesting cytoplasmic mislocalization as one mechanism of early oncogenic ECT2 activation. Importantly, elevated nuclear ECT2 correlated with poorly differentiated tumors, and a low cytoplasmic:nuclear ratio of ECT2 protein correlated with poor patient survival, suggesting that nuclear and cytoplasmic ECT2 play distinct roles in colorectal cancer. Depletion of ECT2 reduced anchorage-independent cancer cell growth and invasion independent of its function in cytokinesis, and loss of Ect2 extended survival in a KrasG12D Apc-null colon cancer mouse model. Expression of ECT2 variants with impaired nuclear localization or guanine nucleotide exchange catalytic activity failed to restore cancer cell growth or invasion, indicating that active, nuclear ECT2 is required to support tumor progression. Nuclear ECT2 promoted ribosomal DNA transcription and ribosome biogenesis in colorectal cancer. These results support a driver role for both cytoplasmic and nuclear ECT2 overexpression in colorectal cancer and emphasize the critical role of precise subcellular localization in dictating ECT2 function in neoplastic cells

Benchmarking whole exome sequencing in the German Network for Personalized Medicine

Introduction Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. Methods To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics investigating somatic and germline variants, copy-number alteration (CNA), and different complex biomarkers. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. In addition, all raw data were re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. Results The mean positive percentage agreement (PPA) of somatic variant calling was 76% and positive predictive value (PPV) 89% compared a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88% for all and 97% for clinically relevant variants. CNA calls were concordant for 82% of genomic regions. Calls of homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94%, 93%, and 93% respectively. Variability of CNAs and complex biomarkers did not increase considerably using the central pipeline and was hence attributed to wet-lab differences. Conclusion Continuous optimization of bioinformatic workflows and participating in round robin tests are recommend

DNA methylation-based classification of sinonasal tumors

The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs