High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment.

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer cells in single-cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication.

BACKGROUND: The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers. METHODS: We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function. RESULTS: We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2. CONCLUSIONS: Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.

Robust detection of clinically relevant features in single-cell RNA profiles of patient-matched fresh and formalin-fixed paraffin-embedded (FFPE) lung cancer tissue.

PURPOSE: Single-cell transcriptional profiling reveals cell heterogeneity and clinically relevant traits in intra-operatively collected patient-derived tissue. So far, single-cell studies have been constrained by the requirement for prospectively collected fresh or cryopreserved tissue. This limitation might be overcome by recent technical developments enabling single-cell analysis of FFPE tissue. METHODS: We benchmark single-cell profiles from patient-matched fresh, cryopreserved and archival FFPE cancer tissue. RESULTS: We find that fresh tissue and FFPE routine blocks can be employed for the robust detection of clinically relevant traits on the single-cell level. Specifically, single-cell maps of fresh patient tissues and corresponding FFPE tissue blocks could be integrated into common low-dimensional representations, and cell subtype clusters showed highly correlated transcriptional strengths of signaling pathway, hallmark, and clinically useful signatures, although expression of single genes varied due to technological differences. FFPE tissue blocks revealed higher cell diversity compared to fresh tissue. In contrast, single-cell profiling of cryopreserved tissue was prone to artifacts in the clinical setting. CONCLUSION: Our analysis highlights the potential of single-cell profiling in the analysis of retrospectively and prospectively collected archival pathology cohorts and increases the applicability in translational research.

Negative Hyperselection of Resistance Mutations for Panitumumab Maintenance in RAS Wild-Type Metastatic Colorectal Cancer (PanaMa Phase II Trial, AIO KRK 0212).

PURPOSE: We evaluated additional mutations in RAS wild-type (WT) metastatic colorectal cancer (mCRC) as prognostic and predictive biomarkers for the efficacy of added panitumumab to a 5-fluorouracil plus folinic acid (FU/FA) maintenance as pre-specified analysis of the randomized PanaMa trial. PATIENTS AND METHODS: Mutations (MUT) were identified using targeted next-generation sequencing (NGS; Illumina Cancer Hotspot Panel v2) and IHC. RAS/BRAF V600E/PIK3CA/AKT1/ALK1/ERBB2/PTEN MUT and HER2/neu overexpressions were negatively hyperselected and correlated with median progression-free survival (PFS) and overall survival (OS) since start of maintenance treatment, and objective response rates (ORR). Univariate/multivariate Cox regression estimated hazard ratios (HR) and 95% confidence intervals (CI). RESULTS: 202 of 248 patients (81.5%) of the full analysis set (FAS) had available NGS data: hyperselection WT, 162 (80.2%); MUT, 40 (19.8%). From start of maintenance therapy, hyperselection WT tumors were associated with longer median PFS as compared with hyperselection MUT mCRC (7.5 vs. 5.4 months; HR, 0.75; 95% CI, 0.52-1.07; P = 0.11), OS (28.7 vs. 22.2 months; HR, 0.53; 95% CI, 0.36-0.77; P = 0.001), and higher ORR (35.8% vs. 25.0%, P = 0.26). The addition of panitumumab to maintenance was associated with significant benefit in hyperselection WT tumors for PFS (9.2 vs. 6.0 months; HR, 0.66; 95% CI, 0.47-0.93; P = 0.02) and numerically also for OS (36.9 vs. 24.9 months; HR, 0.91; 95% CI, 0.61-1.36; P = 0.50), but not in hyperselection MUT tumors. Hyperselection status interacted with maintenance treatment arms in terms of PFS (P = 0.06) and OS (P = 0.009). CONCLUSIONS: Extended molecular profiling beyond RAS may have the potential to improve the patient selection for anti-EGFR containing maintenance regimens.

BannMI deciphers potential n-to-1 information transduction in signaling pathways to unravel message of intrinsic apoptosis.

Motivation: Cell fate decisions, such as apoptosis or proliferation, are communicated via signaling pathways. The pathways are heavily intertwined and often consist of sequential interaction of proteins (kinases). Information integration takes place on the protein level via n-to-1 interactions. A state-of-the-art procedure to quantify information flow (edges) between signaling proteins (nodes) is network inference. However, edge weight calculation typically refers to 1-to-1 interactions only and relies on mean protein phosphorylation levels instead of single cell distributions. Information theoretic measures such as the mutual information (MI) have the potential to overcome these shortcomings but are still rarely used. Results: This work proposes a Bayesian nearest neighbor-based MI estimator (BannMI) to quantify n-to-1 kinase dependency in signaling pathways. BannMI outperforms the state-of-the-art MI estimator on protein-like data in terms of mean squared error and Pearson correlation. Using BannMI, we analyze apoptotic signaling in phosphoproteomic cancerous and noncancerous breast cell line data. Our work provides evidence for cooperative signaling of several kinases in programmed cell death and identifies a potential key role of the mitogen-activated protein kinase p38. Availability and implementation: Source code and applications are available at: https://github.com/zuiop11/nn_info and can be downloaded via Pip as Python package: nn-info.

LRP1B-a prognostic marker in tubo-ovarian high-grade serous carcinoma.

Low-density lipoprotein (LDL) receptor-related protein 1B (LRP1B) is a member of the LDL receptor family and has often been discussed as a tumor suppressor gene, as its down-regulation is correlated with a poor prognosis in multiple carcinoma entities. Due to the high metastasis rate into the fatty peritoneal cavity and current research findings showing a dysregulation of lipid metabolism in tubo-ovarian high-grade serous carcinoma (HGSC), we questioned the prognostic impact of the LRP1B protein expression. We examined a well-characterized large cohort of 571 patients with primary HGSC and analyzed the LRP1B protein expression via immunohistochemical staining (both in tumor and stroma cells separately), performed precise bioimage analysis with QuPath, and calculated the prognostic impact using SPSS. Our results demonstrate that LRP1B functions as a significant prognostic marker for overall survival (OS) and progression-free survival (PFS) in HGSC on the protein level. High cytoplasmic expression of LRP1B in tumor, stroma, and combined tumor and stroma cells has a significantly positive association with a mean prolongation of the OS by 42 months (P = .005), 29 months (P = .005), and 25 months (P = .001), respectively. Additionally, the mean PFS was 18 months longer in tumor (P = .002), 19 months in stroma (P = .004), and 19 months in both cell types combined (P = .01). Our results remained significant in multivariate analysis. We envision LRP1B as a potential prognostic tool that could help us understand the functional role of lipid metabolism in advanced HGSC, especially regarding liposomal medications.

Increased expression of IDO1 is associated with improved survival and increased number of TILs in patients with high-grade serous ovarian cancer.

BACKGROUND: The enzyme indoleamine 2,3-dioxygenase 1 (IDO1) plays a crucial role in regulating the immune system's response to tumors, but its exact role in cancer, especially in high-grade serous ovarian cancer (HGSOC), remains controversial. We aimed to investigate the prognostic impact of IDO1 expression and its correlation with tumor-infiltrating lymphocytes (TILs) in HGSOC. METHODS: Immunohistochemical (IHC) staining and bioimage analysis using the QuPath software were employed to assess IDO1 protein expression in a well-characterized cohort of 507 patients with primary HGSOC. Statistical evaluation was performed using SPSS, and in silico validation considering IDO1 mRNA expression in bulk and single-cell gene expression datasets was conducted. Additionally, IDO1 expression in interferon-gamma (IFNG) stimulated HGSOC cell lines was analyzed. RESULTS: Our findings revealed that IDO1 protein and mRNA expression serve as positive prognostic markers for overall survival (OS) and progression-free survival (PFS) in HGSOC. High IDO1 expression was associated with a significant improvement in OS by 21 months (p < 0.001) and PFS by 6 months (p = 0.016). Notably, elevated IDO1 expression correlated with an increased number of CD3+ (p < 0.001), CD4+ (p < 0.001), and CD8+ TILs (p < 0.001). Furthermore, high IDO1 mRNA expression and protein level were found to be associated with enhanced responsiveness to pro-inflammatory cytokines, particularly IFNG. CONCLUSIONS: Our study provides evidence that IDO1 expression serves as a positive prognostic marker in HGSOC and is associated with an increased number of CD3+, CD4+ and CD8+ TILs. Understanding the intricate relationship between IDO1, TILs, and the tumor microenvironment may hold the key to improving outcomes in HGSOC.

High EVI1 and PARP1 expression as favourable prognostic markers in high-grade serous ovarian carcinoma.

BACKGROUND: Mechanisms of development and progression of high-grade serous ovarian cancer (HGSOC) are poorly understood. EVI1 and PARP1, part of TGF-ß pathway, are upregulated in cancers with DNA repair deficiencies with DNA repair deficiencies and may influce disease progression and survival. Therefore we questioned the prognostic significance of protein expression of EVI1 alone and in combination with PARP1 and analyzed them in a cohort of patients with HGSOC. METHODS: For 562 HGSOC patients, we evaluated EVI1 and PARP1 expression by immunohistochemical staining on tissue microarrays with QuPath digital semi-automatic positive cell detection. RESULTS: High EVI1 expressing (> 30% positive tumor cells) HGSOC were associated with improved progression-free survival (PFS) (HR = 0.66, 95% CI: 0.504-0.852, p = 0.002) and overall survival (OS) (HR = 0.45, 95% CI: 0.352-0.563, p < 0.001), including multivariate analysis. Most interestingly, mutual high expression of both proteins identifies a group with particularly good prognosis. Our findings were proven technically and clinically using bioinformatical data sets for single-cell sequencing, copy number variation and gene as well as protein expression. CONCLUSIONS: EVI1 and PARP1 are robust prognostic biomarkers for favorable prognosis in HGSOC and imply further research with respect to their reciprocity.

DNA methylation-based classifier differentiates intrahepatic pancreato-biliary tumours.

BACKGROUND: Differentiating intrahepatic cholangiocarcinomas (iCCA) from hepatic metastases of pancreatic ductal adenocarcinoma (PAAD) is challenging. Both tumours have similar morphological and immunohistochemical pattern and share multiple driver mutations. We hypothesised that DNA methylation-based machine-learning algorithms may help perform this task. METHODS: We assembled genome-wide DNA methylation data for iCCA (n = 259), PAAD (n = 431), and normal bile duct (n = 70) from publicly available sources. We split this cohort into a reference (n = 399) and a validation set (n = 361). Using the reference cohort, we trained three machine learning models to differentiate between these entities. Furthermore, we validated the classifiers on the technical validation set and used an internal cohort (n = 72) to test our classifier. FINDINGS: On the validation cohort, the neural network, support vector machine, and the random forest classifiers reached accuracies of 97.68%, 95.62%, and 96.5%, respectively. Filtering by anomaly detection and thresholds improved the accuracy to 99.07% (37 samples excluded by filtering), 96.22% (17 samples excluded), and 100% (44 samples excluded) for the neural network, support vector machine and random forest, respectively. Because of best balance between accuracy and number of predictable cases we tested the neural network with applied filters on the in-house cohort, obtaining an accuracy of 95.45%. INTERPRETATION: We developed a classifier that can differentiate between iCCAs, intrahepatic metastases of a PAAD, and normal bile duct tissue with high accuracy. This tool can be used for improving the diagnosis of pancreato-biliary cancers of the liver. FUNDING: This work was supported by Berlin Institute of Health (JCS Program), DKTK Berlin (Young Investigator Grant 2022), German Research Foundation (493697503 and 314905040 - SFB/TRR 209 Liver Cancer B01), and German Cancer Aid (70113922).

Tryptophan depletion sensitizes the AHR pathway by increasing AHR expression and GCN2/LAT1-mediated kynurenine uptake, and potentiates induction of regulatory T lymphocytes.

BACKGROUND: Indoleamine 2,3-dioxygenase 1 (IDO1) and tryptophan-dioxygenase (TDO) are enzymes catabolizing the essential amino acid tryptophan into kynurenine. Expression of these enzymes is frequently observed in advanced-stage cancers and is associated with poor disease prognosis and immune suppression. Mechanistically, the respective roles of tryptophan shortage and kynurenine production in suppressing immunity remain unclear. Kynurenine was proposed as an endogenous ligand for the aryl hydrocarbon receptor (AHR), which can regulate inflammation and immunity. However, controversy remains regarding the role of AHR in IDO1/TDO-mediated immune suppression, as well as the involvement of kynurenine. In this study, we aimed to clarify the link between IDO1/TDO expression, AHR pathway activation and immune suppression. METHODS: AHR expression and activation was analyzed by RT-qPCR and western blot analysis in cells engineered to express IDO1/TDO, or cultured in medium mimicking tryptophan catabolism by IDO1/TDO. In vitro differentiation of naïve CD4+ T cells into regulatory T cells (Tregs) was compared in T cells isolated from mice bearing different Ahr alleles or a knockout of Ahr, and cultured in medium with or without tryptophan and kynurenine. RESULTS: We confirmed that IDO1/TDO expression activated AHR in HEK-293-E cells, as measured by the induction of AHR target genes. Unexpectedly, AHR was also overexpressed on IDO1/TDO expression. AHR overexpression did not depend on kynurenine but was triggered by tryptophan deprivation. Multiple human tumor cell lines overexpressed AHR on tryptophan deprivation. AHR overexpression was not dependent on general control non-derepressible 2 (GCN2), and strongly sensitized the AHR pathway. As a result, kynurenine and other tryptophan catabolites, which are weak AHR agonists in normal conditions, strongly induced AHR target genes in tryptophan-depleted conditions. Tryptophan depletion also increased kynurenine uptake by increasing SLC7A5 (LAT1) expression in a GCN2-dependent manner. Tryptophan deprivation potentiated Treg differentiation from naïve CD4+ T cells isolated from mice bearing an AHR allele of weak affinity similar to the human AHR. CONCLUSIONS: Tryptophan deprivation sensitizes the AHR pathway by inducing AHR overexpression and increasing cellular kynurenine uptake. As a result, tryptophan catabolites such as kynurenine more potently activate AHR, and Treg differentiation is promoted. Our results propose a molecular explanation for the combined roles of tryptophan deprivation and kynurenine production in mediating IDO1/TDO-induced immune suppression.

Oncogenic signaling is coupled to colorectal cancer cell differentiation state.

Colorectal cancer progression is intrinsically linked to stepwise deregulation of the intestinal differentiation trajectory. In this process, sequential mutations of APC, KRAS, TP53, and SMAD4 enable oncogenic signaling and establish the hallmarks of cancer. Here, we use mass cytometry of isogenic human colon organoids and patient-derived cancer organoids to capture oncogenic signaling, cell phenotypes, and differentiation states in a high-dimensional single-cell map. We define a differentiation axis in all tumor progression states from normal to cancer. Our data show that colorectal cancer driver mutations shape the distribution of cells along the differentiation axis. In this regard, subsequent mutations can have stem cell promoting or restricting effects. Individual nodes of the cancer cell signaling network remain coupled to the differentiation state, regardless of the presence of driver mutations. We use single-cell RNA sequencing to link the (phospho-)protein signaling network to transcriptomic states with biological and clinical relevance. Our work highlights how oncogenes gradually shape signaling and transcriptomes during tumor progression.

Transcriptomic Deconvolution of Neuroendocrine Neoplasms Predicts Clinically Relevant Characteristics.

Pancreatic neuroendocrine neoplasms (panNENs) are a rare yet diverse type of neoplasia whose precise clinical-pathological classification is frequently challenging. Since incorrect classifications can affect treatment decisions, additional tools which support the diagnosis, such as machine learning (ML) techniques, are critically needed but generally unavailable due to the scarcity of suitable ML training data for rare panNENs. Here, we demonstrate that a multi-step ML framework predicts clinically relevant panNEN characteristics while being exclusively trained on widely available data of a healthy origin. The approach classifies panNENs by deconvolving their transcriptomes into cell type proportions based on shared gene expression profiles with healthy pancreatic cell types. The deconvolution results were found to provide a prognostic value with respect to the prediction of the overall patient survival time, neoplastic grading, and carcinoma versus tumor subclassification. The performance with which a proliferation rate agnostic deconvolution ML model could predict the clinical characteristics was found to be comparable to that of a comparative baseline model trained on the proliferation rate-informed MKI67 levels. The approach is novel in that it complements established proliferation rate-oriented classification schemes whose results can be reproduced and further refined by differentiating between identically graded subgroups. By including non-endocrine cell types, the deconvolution approach furthermore provides an in silico quantification of panNEN dedifferentiation, optimizing it for challenging clinical classification tasks in more aggressive panNEN subtypes.

Silencing effects of mutant RAS signalling on transcriptomes.

Mutated genes of the RAS family encoding small GTP-binding proteins drive numerous cancers, including pancreatic, colon and lung tumors. Besides the numerous effects of mutant RAS gene expression on aberrant proliferation, transformed phenotypes, metabolism, and therapy resistance, the most striking consequences of chronic RAS activation are changes of the genetic program. By performing systematic gene expression studies in cellular models that allow comparisons of pre-neoplastic with RAS-transformed cells, we and others have estimated that 7 percent or more of all transcripts are altered in conjunction with the expression of the oncogene. In this context, the number of up-regulated transcripts approximates that of down-regulated transcripts. While up-regulated transcription factors such as MYC, FOSL1, and HMGA2 have been identified and characterized as RAS-responsive drivers of the altered transcriptome, the suppressed factors have been less well studied as potential regulators of the genetic program and transformed phenotype in the breadth of their occurrence. We therefore have collected information on downregulated RAS-responsive factors and discuss their potential role as tumor suppressors that are likely to antagonize active cancer drivers. To better understand the active mechanisms that entail anti-RAS function and those that lead to loss of tumor suppressor activity, we focus on the tumor suppressor HREV107 (alias PLAAT3 [Phospholipase A and acyltransferase 3], PLA2G16 [Phospholipase A2, group XVI] and HRASLS3 [HRAS-like suppressor 3]). Inactivating HREV107 mutations in tumors are extremely rare, hence epigenetic causes modulated by the RAS pathway are likely to lead to down-regulation and loss of function.

Combination Therapies with CDK4/6 Inhibitors to Treat KRAS-Mutant Pancreatic Cancer.

Mutational loss of CDKN2A (encoding p16INK4A) tumor-suppressor function is a key genetic step that complements activation of KRAS in promoting the development and malignant growth of pancreatic ductal adenocarcinoma (PDAC). However, pharmacologic restoration of p16INK4A function with inhibitors of CDK4 and CDK6 (CDK4/6) has shown limited clinical efficacy in PDAC. Here, we found that concurrent treatment with both a CDK4/6 inhibitor (CDK4/6i) and an ERK-MAPK inhibitor (ERKi) synergistically suppresses the growth of PDAC cell lines and organoids by cooperatively blocking CDK4/6i-induced compensatory upregulation of ERK, PI3K, antiapoptotic signaling, and MYC expression. On the basis of these findings, a Phase I clinical trial was initiated to evaluate the ERKi ulixertinib in combination with the CDK4/6i palbociclib in patients with advanced PDAC (NCT03454035). As inhibition of other proteins might also counter CDK4/6i-mediated signaling changes to increase cellular CDK4/6i sensitivity, a CRISPR-Cas9 loss-of-function screen was conducted that revealed a spectrum of functionally diverse genes whose loss enhanced CDK4/6i growth inhibitory activity. These genes were enriched around diverse signaling nodes, including cell-cycle regulatory proteins centered on CDK2 activation, PI3K-AKT-mTOR signaling, SRC family kinases, HDAC proteins, autophagy-activating pathways, chromosome regulation and maintenance, and DNA damage and repair pathways. Novel therapeutic combinations were validated using siRNA and small-molecule inhibitor-based approaches. In addition, genes whose loss imparts a survival advantage were identified (e.g., RB1, PTEN, FBXW7), suggesting possible resistance mechanisms to CDK4/6 inhibition. In summary, this study has identified novel combinations with CDK4/6i that may have clinical benefit to patients with PDAC. SIGNIFICANCE: CRISPR-Cas9 screening and protein activity mapping reveal combinations that increase potency of CDK4/6 inhibitors and overcome drug-induced compensations in pancreatic cancer.

Clonality and timing of relapsing colorectal cancer metastasis revealed through whole-genome single-cell sequencing.

Recurrence of tumor cells following local and systemic therapy is a significant hurdle in cancer. Most patients with metastatic colorectal cancer (mCRC) will relapse, despite resection of the metastatic lesions. A better understanding of the evolutionary history of recurrent lesions is required to identify the spatial and temporal patterns of metastatic progression and expose the genetic and evolutionary determinants of therapeutic resistance. With this goal in mind, here we leveraged a unique single-cell whole-genome sequencing dataset from recurrent hepatic lesions of an mCRC patient. Our phylogenetic analysis confirms that the treatment induced a severe demographic bottleneck in the liver metastasis but also that a previously diverged lineage survived this surgery, possibly after migration to a different site in the liver. This lineage evolved very slowly for two years under adjuvant drug therapy and diversified again in a very short period. We identified several non-silent mutations specific to this lineage and inferred a substantial contribution of chemotherapy to the overall, genome-wide mutational burden. All in all, our study suggests that mCRC subclones can migrate locally and evade resection, keep evolving despite rounds of chemotherapy, and re-expand explosively.

DNA methylation reveals distinct cells of origin for pancreatic neuroendocrine carcinomas and pancreatic neuroendocrine tumors.

BACKGROUND: Pancreatic neuroendocrine neoplasms (PanNENs) fall into two subclasses: the well-differentiated, low- to high-grade pancreatic neuroendocrine tumors (PanNETs), and the poorly-differentiated, high-grade pancreatic neuroendocrine carcinomas (PanNECs). While recent studies suggest an endocrine descent of PanNETs, the origin of PanNECs remains unknown. METHODS: We performed DNA methylation analysis for 57 PanNEN samples and found that distinct methylation profiles separated PanNENs into two major groups, clearly distinguishing high-grade PanNECs from other PanNETs including high-grade NETG3. DNA alterations and immunohistochemistry of cell-type markers PDX1, ARX, and SOX9 were utilized to further characterize PanNECs and their cell of origin in the pancreas. RESULTS: Phylo-epigenetic and cell-type signature features derived from alpha, beta, acinar, and ductal adult cells suggest an exocrine cell of origin for PanNECs, thus separating them in cell lineage from other PanNENs of endocrine origin. CONCLUSIONS: Our study provides a robust and clinically applicable method to clearly distinguish PanNECs from G3 PanNETs, improving patient stratification.

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 noninflammatory 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, TGFß 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 noninflammatory and vessel-rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets.

Triple Targeting of HER Receptors Overcomes Heregulin-mediated Resistance to EGFR Blockade in Colorectal Cancer.

Current treatment options for patients with advanced colorectal cancers include anti-EGFR/HER1 therapy with the blocking antibody cetuximab. Although a subset of patients with KRAS WT disease initially respond to the treatment, resistance develops in almost all cases. Relapse has been associated with the production of the ligand heregulin (HRG) and/or compensatory signaling involving the receptor tyrosine kinases HER2 and HER3. Here, we provide evidence that triple-HER receptor blockade based on a newly developed bispecific EGFR×HER3-targeting antibody (scDb-Fc) together with the HER2-blocking antibody trastuzumab effectively inhibited HRG-induced HER receptor phosphorylation, downstream signaling, proliferation, and stem cell expansion of DiFi and LIM1215 colorectal cancer cells. Comparative analyses revealed that the biological activity of scDb-Fc plus trastuzumab was sometimes even superior to that of the combination of the parental antibodies, with PI3K/Akt pathway inhibition correlating with improved therapeutic response and apoptosis induction as seen by single-cell analysis. Importantly, growth suppression by triple-HER targeting was recapitulated in primary KRAS WT patient-derived organoid cultures exposed to HRG. Collectively, our results provide strong support for a pan-HER receptor blocking approach to combat anti-EGFR therapy resistance of KRAS WT colorectal cancer tumors mediated by the upregulation of HRG and/or HER2/HER3 signaling.

Rapid testing of candidate oncogenes and tumour suppressor genes in signal transduction and neoplastic transformation.

The COSMIC database (version 94) lists 576 genes in the Cancer Gene Census which have a defined function as drivers of malignancy (oncogenes) or as tumour suppressors (Tier 1). In addition, there are 147 genes with similar functions, but which are less well characterised (Tier 2). Furthermore, next-generation sequencing projects in the context of precision oncology activities are constantly discovering new ones. Since cancer genes differ from their wild-type precursors in numerous molecular and biochemical properties and exert significant differential effects on downstream processes, simple assays that can uncover oncogenic or anti-oncogenic functionality are desirable and may precede more sophisticated analyses. We describe simple functional assays for PTPN11 (protein-tyrosine phosphatase, non-receptor-type 11)/SHP2 mutants, which are typically found in RASopathies and exhibit potential oncogenic activity. We have also designed a functional test for lysyl oxidase (LOX), a prototypical class II tumour suppressor gene whose loss of function may contribute to neoplastic transformation by RAS oncogenes. Moreover, we applied this test to analyse three co-regulated, RAS-responsive genes for transformation-suppressive activity. The integration of these tests into systems biology studies will contribute to a better understanding of cellular networks in cancer.

Mucosal melanomas of different anatomic sites share a common global DNA methylation profile with cutaneous melanoma but show location-dependent patterns of genetic and epigenetic alterations.

Cutaneous, ocular, and mucosal melanomas are histologically indistinguishable tumors that are driven by a different spectrum of genetic alterations. With current methods, identification of the site of origin of a melanoma metastasis is challenging. DNA methylation profiling has shown promise for the identification of the site of tumor origin in various settings. Here we explore the DNA methylation landscape of melanomas from different sites and analyze if different melanoma origins can be distinguished by their epigenetic profile. We performed DNA methylation analysis, next generation DNA panel sequencing, and copy number analysis of 82 non-cutaneous and 25 cutaneous melanoma samples. We further analyzed eight normal melanocyte cell culture preparations. DNA methylation analysis separated uveal melanomas from melanomas of other primary sites. Mucosal, conjunctival, and cutaneous melanomas shared a common global DNA methylation profile. Still, we observed location-dependent DNA methylation differences in cancer-related genes, such as low frequencies of RARB (7/63) and CDKN2A promoter methylation (6/63) in mucosal melanomas, or a high frequency of APC promoter methylation in conjunctival melanomas (6/9). Furthermore, all investigated melanomas of the paranasal sinus showed loss of PTEN expression (9/9), mainly caused by promoter methylation. This was less frequently seen in melanomas of other sites (24/98). Copy number analysis revealed recurrent amplifications in mucosal melanomas, including chromosomes 4q, 5p, 11q and 12q. Most melanomas of the oral cavity showed gains of chromosome 5p with TERT amplification (8/10), while 11q amplifications were enriched in melanomas of the nasal cavity (7/16). In summary, mucosal, conjunctival, and cutaneous melanomas show a surprisingly similar global DNA methylation profile and identification of the site of origin by DNA methylation testing is likely not feasible. Still, our study demonstrates tumor location-dependent differences of promoter methylation frequencies in specific cancer-related genes together with tumor site-specific enrichment for specific chromosomal changes and genetic mutations. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.