Preoperative CA125 Significantly Improves Risk Stratification in High-Grade Endometrial Cancer

Advanced stage; Endometrial cancer; OutcomeEtapa avançada; Càncer d'endometri; ResultatEtapa avanzada; Cáncer de endometrio; ResultadoPatients with high-grade endometrial carcinoma (EC) have an increased risk of tumor spread and lymph node metastasis (LNM). Preoperative imaging and CA125 can be used in work-up. As data on cancer antigen 125 (CA125) in high-grade EC are limited, we aimed to study primarily the predictive value of CA125, and secondarily the contributive value of computed tomography (CT) for advanced stage and LNM. Patients with high-grade EC (n = 333) and available preoperative CA125 were included retrospectively. The association of CA125 and CT findings with LNM was analyzed by logistic regression. Elevated CA125 ((>35 U/mL), (35.2% (68/193)) was significantly associated with stage III-IV disease (60.3% (41/68)) compared with normal CA125 (20.8% (26/125), [p < 0.001]), and with reduced disease-specific—(DSS) (p < 0.001) and overall survival (OS) (p < 0.001). The overall accuracy of predicting LNM by CT resulted in an area under the curve (AUC) of 0.623 (p < 0.001) independent of CA125. Stratification by CA125 resulted in an AUC of 0.484 (normal), and 0.660 (elevated). In multivariate analysis elevated CA125, non-endometrioid histology, pathological deep myometrial invasion ≥50%, and cervical involvement were significant predictors of LNM, whereas suspected LNM on CT was not. This shows that elevated CA125 is a relevant independent predictor of advanced stage and outcome specifically in high-grade EC

Improved discrimination of melanotic schwannoma from melanocytic lesions by combined morphological and GNAQ mutational analysis

The histological differential diagnosis between melanotic schwannoma, primary leptomeningeal melanocytic lesions and cellular blue nevus can be challenging. Correct diagnosis of melanotic schwannoma is important to select patients who need clinical evaluation for possible association with Carney complex. Recently, we described the presence of activating codon 209 mutations in the GNAQ gene in primary leptomeningeal melanocytic lesions. Identical codon 209 mutations have been described in blue nevi. The aims of the present study were to (1) perform a histological review of a series of lesions (initially) diagnosed as melanotic schwannoma and analyze them for GNAQ mutations, and (2) test the diagnostic value of GNAQ mutational analysis in the differential diagnosis with leptomeningeal melanocytic lesions. We retrieved 25 cases that were initially diagnosed as melanotic schwannoma. All cases were reviewed using established criteria and analyzed for GNAQ codon 209 mutations. After review, nine cases were classified as melanotic schwannoma. GNAQ mutations were absent in these nine cases. The remaining cases were reclassified as conventional schwannoma (n = 9), melanocytoma (n = 4), blue nevus (n = 1) and lesions that could not be classified with certainty as melanotic schwannoma or melanocytoma (n = 2). GNAQ codon 209 mutations were present in 3/4 melanocytomas and the blue nevus. Including results from our previous study in leptomeningeal melanocytic lesions, GNAQ mutations were highly specific (100%) for leptomeningeal melanocytic lesions compared to melanotic schwannoma (sensitivity 43%). We conclude that a detailed analysis of morphology combined with GNAQ mutational analysis can aid in the differential diagnosis of melanotic schwannoma with leptomeningeal melanocytic lesions

Activating mutations of the GNAQ gene: a frequent event in primary melanocytic neoplasms of the central nervous system

Primary melanocytic neoplasms of the central nervous system (CNS) are uncommon neoplasms derived from melanocytes that normally can be found in the leptomeninges. They cover a spectrum of malignancy grades ranging from low-grade melanocytomas to lesions of intermediate malignancy and overtly malignant melanomas. Characteristic genetic alterations in this group of neoplasms have not yet been identified. Using direct sequencing, we investigated 19 primary melanocytic lesions of the CNS (12 melanocytomas, 3 intermediate-grade melanocytomas, and 4 melanomas) for hotspot oncogenic mutations commonly found in melanocytic tumors of the skin (BRAF, NRAS, and HRAS genes) and uvea (GNAQ gene). Somatic mutations in the GNAQ gene at codon 209, resulting in constitutive activation of GNAQ, were detected in 7/19 (37%) tumors, including 6/12 melanocytomas, 0/3 intermediate-grade melanocytomas, and 1/4 melanomas. These GNAQ-mutated tumors were predominantly located around the spinal cord (6/7). One melanoma carried a BRAF point mutation that is frequently found in cutaneous melanomas (c.1799 T>A, p.V600E), raising the question whether this is a metastatic rather than a primary tumor. No HRAS or NRAS mutations were detected. We conclude that somatic mutations in the GNAQ gene at codon 209 are a frequent event in primary melanocytic neoplasms of the CNS. This finding provides new insight in the pathogenesis of these lesions and suggests that GNAQ-dependent mitogen-activated kinase signaling is a promising therapeutic target in these tumors. The prognostic and predictive value of GNAQ mutations in primary melanocytic lesions of the CNS needs to be determined in future studies

Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study

Background: Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node metastasis (LNM) is challenging in endometrial cancer, and although several biomarkers are related to LNM, none of them are incorporated in clinical practice. The aim of this study was to develop and externally validate a preoperative BN to predict LNM and outcome in endometrial cancer patients.Methods and findings: Within the European Network for Individualized Treatment of Endometrial Cancer (ENI-TEC), we performed a retrospective multicenter cohort study including 763 patients, median age 65 years (interquartile range [IQR] 58-71), surgically treated for endometrial cancer between February 1995 and August 2013 at one of the 10 participating European hospitals. A BN was developed using score-based machine learning in addition to expert knowledge. Our main outcome measures were LNM and 5-year disease-specific survival (DSS). Preoperative clinical, histopathological, and molecular biomarkers were included in the network. External validation was performed using 2 prospective study cohorts: the Molecular Markers in Treatment in Endometrial Cancer (MoMaTEC) study cohort, including 446 Norwegian patients, median age 64 years (IQR 59-74), treated between May 2001 and 2010; and the PIpelle Prospective ENDOmetrial carcinoma (PIPENDO) study cohort, including 384 Dutch patients, median age 66 years (IQR 60-73), treated between September 2011 and December 2013. A BN called ENDORISK (preoperative risk stratification in endometrial cancer) was developed including the following predictors: preoperative tumor grade; immunohistochemical expression of estrogen receptor (ER), progesterone receptor (PR), p53, and L1 cell adhesion molecule (L1CAM); cancer antigen 125 serum level; thrombocyte count; imaging results on lymphadenopathy; and cervical cytology. In the MoMaTEC cohort, the area under the curve (AUC) was 0.82 (95% confidence interval [CI] 0.76-0.88) for LNM and 0.82 (95% CI 0.77-0.87) for 5-year DSS. In the PIPENDO cohort, the AUC for 5-year DSS was 0.84 (95% CI 0.78-0.90). The network was well-calibrated. In the MoMaTEC cohort, 249 patients (55.8%) were classified with Conclusions: In this study, we illustrated how BNs can be used for individualizing clinical decision-making in oncology by incorporating easily accessible and multimodal biomarkers. The network shows the complex interactions underlying the carcinogenetic process of endometrial cancer by its graphical representation. A prospective feasibility study will be needed prior to implementation in the clinic.</div

SF3B1 and EIF1AX mutations occur in primary leptomeningeal melanocytic neoplasms; yet another similarity to uveal melanomas

INTRODUCTION: Like uveal melanomas, primary leptomeningeal melanocytic neoplasms (LMNs) frequently carry GNAQ and GNA11 mutations. However, it is currently unknown whether these LMNs harbor mutations in BAP1, SF3B1 and/or EIF1AX like uveal melanomas as well. In this study, we used Sanger sequencing for the detection of mutations in SF3B1 (hotspots in exon 14 and 15) and EIF1AX (exon 1 and 2 and flanking intronic regions) in a series of 24 primary LMNs. Additionally, BAP1 immunohistochemistry was used as a surrogate marker for the detection of inactivating mutations in the BAP1 gene. RESULTS: Mutations in either SF3B1 or EIF1AX were identified in 8 out of 24 primary LMNs (33 %). The presence of these mutations was mutually exclusive and occurred in primary LMNs of different malignancy grades (melanocytomas, intermediate-grade melanocytic tumors, melanomas). Complete absence of nuclear BAP1 staining as is typically seen in BAP1-mutated tumors was not observed. CONCLUSIONS: Our finding that an SF3B1 or EIF1AX mutation is present in a substantial subset of primary LMNs underscores that these tumors genetically resemble uveal melanoma and are different from cutaneous melanoma at the genetic level. This information may not only aid in the differential diagnosis of primary versus metastatic melanocytic tumor in/around the central nervous system, but also in the identification of more promising therapeutic approaches targeting the molecular pathways involved in the oncogenesis of LMNs. As none of the primary LMNs in our series showed complete loss of nuclear BAP1 protein, it is unlikely that BAP1 mutations are frequent in these tumors but the role of this gene warrants further investigation

Mutations in G Protein Encoding Genes and Chromosomal Alterations in Primary Leptomeningeal Melanocytic Neoplasms

Limited data is available on the genetic features of primary leptomeningeal melanocytic neoplasms (LMNs). Similarities with uveal melanoma were recently suggested as both entities harbor oncogenic mutations in GNAQ and GNA11. Whether primary LMNs share additional genetic alterations with uveal melanoma including copy number variations is unknown. Twenty primary LMNs ranging from benign and intermediate-grade melanocytomas to melanomas were tested by direct sequencing for hotspot mutations in the genes GNA11, GNAQ, BRAF, NRAS and HRAS. Furthermore, the lesions were tested for copy number variations of chromosomes frequently present in uveal melanoma (1p, 3, 6 and 8q) by multiplex ligation-dependent probe amplification (MLPA). Genome-wide analyses of copy number alterations of two leptomeningeal melanocytic neoplasms were performed using the OncoScan SNP-array. GNAQQ209 mutations were present in eleven LMNs, while two of 20 cases carried a GNA11Q209 mutation. No BRAF, HRAS or NRAS hotspot mutations were detected. Monosomy 3 and gain of 8q were present in one leptomeningeal melanoma, and one intermediate-grade melanocytoma harbored a gain of chromosome 6. With MLPA, the melanocytomas did not show any further gross chromosomal variations. Our data shows that primary LMNs, like uveal melanoma, harbor oncogenic mutations in GNAQ and GNA11 but lack mutations in BRAF, NRAS and HRAS. This finding may help in the differential diagnosis between a primary LMN and a metastasis from a cutaneous melanoma to the central nervous system. Copy number variations in some aggressive LMNs resemble those present in uveal melanoma but their prognostic significance is unclear

Whole-exome sequencing of a meningeal melanocytic tumour reveals activating CYSLTR2 and EIF1AX hotspot mutations and similarities to uveal melanoma

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Computer-Aided Assessment of Melanocytic Lesions by Means of a Mitosis Algorithm

An increasing number of pathology laboratories are now fully digitised, using whole slide imaging (WSI) for routine diagnostics. WSI paves the road to use artificial intelligence (AI) that will play an increasing role in computer-aided diagnosis (CAD). In melanocytic skin lesions, the presence of a dermal mitosis may be an important clue for an intermediate or a malignant lesion and may indicate worse prognosis. In this study a mitosis algorithm primarily developed for breast carcinoma is applied to melanocytic skin lesions. This study aimed to assess whether the algorithm could be used in diagnosing melanocytic lesions, and to study the added value in diagnosing melanocytic lesions in a practical setting. WSIs of a set of hematoxylin and eosin (H&amp;E) stained slides of 99 melanocytic lesions (35 nevi, 4 intermediate melanocytic lesions, and 60 malignant melanomas, including 10 nevoid melanomas), for which a consensus diagnosis was reached by three academic pathologists, were subjected to a mitosis algorithm based on AI. Two academic and six general pathologists specialized in dermatopathology examined the WSI cases two times, first without mitosis annotations and after a washout period of at least 2 months with mitosis annotations based on the algorithm. The algorithm indicated true mitosis in lesional cells, i.e., melanocytes, and non-lesional cells, i.e., mainly keratinocytes and inflammatory cells. A high number of false positive mitosis was indicated as well, comprising melanin pigment, sebaceous glands nuclei, and spindle cell nuclei such as stromal cells and neuroid differentiated melanocytes. All but one pathologist reported more often a dermal mitosis with the mitosis algorithm, which on a regular basis, was incorrectly attributed to mitoses from mainly inflammatory cells. The overall concordance of the pathologists with the consensus diagnosis for all cases excluding nevoid melanoma (n = 89) appeared to be comparable with and without the use of AI (89% vs. 90%). However, the concordance increased by using AI in nevoid melanoma cases (n = 10) (75% vs. 68%). This study showed that in general cases, pathologists perform similarly with the aid of a mitosis algorithm developed primarily for breast cancer. In nevoid melanoma cases, pathologists perform better with the algorithm. From this study, it can be learned that pathologists need to be aware of potential pitfalls using CAD on H&amp;E slides, e.g., misinterpreting dermal mitoses in non-melanotic cells.Funding Agencies|Innovative Medicines Initiative 2 Joint Undertaking [945358]; European UnionEuropean Commission; EFPIA</p

Copy number variation analysis and methylome profiling of a GNAQ-mutant primary meningeal melanocytic tumor and its liver metastasis

Primary meningeal melanocytic tumors have genetic similarities with uveal melanomas, including GNAQ or GNA11 mutations. While BAP1 mutations and loss of chromosome 3 have adverse prognostic meaning in uveal melanoma, genetic alterations associated with metastasis have not been investigated in primary meningeal melanocytic tumors. We describe a 43-year-old female with a GNAQ-mutated, BAP1-wt melanocytic tumor originating in the parietal brain region and liver metastases 4 years after initial diagnosis. After repeated surgery and chemotherapy she was treated with the immunomodulatory agent ipilimumab. Tissue from the primary and recurrent intracranial tumor (histologically originally diagnosed as intermediate-grade melanocytoma resp. melanoma) and from the liver metastasis was investigated for genome-wide copy number variations and DNA methylation profile. Complete loss of 10p and 19p, partial loss of 16p and a small deletion on 10q were only present in the liver metastasis and not in the intracranial tumors. The DNA methylation profiles of the intracranial tumors and the liver metastasis resembled those of meningeal melanocytomas. In conclusion, in this report we show that a distant metastasis of a meningeal melanocytic tumor has a similar methylation profile as the primary tumor and suggest that particular copy number variations may be associated with metastatic behavior