The Cancer Genome Atlas Classification Research Articles

Metastasis-free survival of uveal melanoma by tumour size category based on The Cancer Genome Atlas (TCGA) classification in 1001 cases.

Uveal melanoma (UM) can be classified by tumour size category and by The Cancer Genome Atlas (TCGA) groups (cytogenetic-based, 4-category prognostic classification into Groups A-D). This study was conducted to assess impact on metastasis-free survival (MFS) in UM by tumour size category based on correlation with TCGA classification. Retrospective analysis of 1001 cases categorised as small (0.0-3.0 mm), medium (3.1-8.0 mm) and large (≥8.1 mm), grouped by TCGA classification. Of 1001 cases, TCGA Groups (A/B/C/D) included small (n = 270, 75%/11%/13%/1%), medium (n = 503, 46%/14%/27%/13%) and large (n = 228, 23%/19%/38%/20%) UM. The 5-and 10-year Kaplan-Meier MFS for small UM revealed Group A (98%, 98%), Group B (100%, 100%), Group C (86%, NA) and Group D (100%, NA). For medium UM, the values dropped with Group A (95%, 93%), Group B (90%, 90%), Group C (68%, 38%), and Group D (44%, NA). For large UM, the values dropped further with Group A (94%, 86%), Group B (85%, NA), Group C (40%, 28%), and Group D (23%, NA). Additionally, a comparison (small vs. medium vs. large tumour size category) revealed TCGA low-risk grouping (Groups A or B) in 86% vs. 60% vs. 58% cases with UM. By tumour size category, favourable cytogenetics (Groups A or B) is found in 86% of small tumours, 60% of medium tumours, and 58% of large tumours. The MFS at 10 years for favourable cytogenetics was 98% for small tumours, 92% for medium tumours, and 54% for large tumours. Tumour size category can serve as a surrogate for TCGA.

Can Endometrial Cytology Identify Patients Who Would Benefit from Immunotherapy?

Introduction: Patients with polymerase epsilon (POLE) mutation (POLEmut) subtype, MMR-deficient (MMR-d) subtype as classified by The Cancer Genome Atlas (TCGA), and a high tumor mutation burden (TMB-high) potentially benefit from immunotherapy. However, characteristics of the cytological morphology within these populations remain unknown. Methods: DNA extracted from formalin-fixed paraffin-embedded tissues was subjected to next-generation sequencing analysis. Genomic mutations related to gynecological cancers, TMB, and microsatellite instability were analyzed and were placed in four TCGA classification types. The following morphological cytological investigations were conducted on endometrial cancer using a liquid-based preparation method, prior to the commencement of initial treatment: (i) cytological backgrounds; (ii) differences between each count of neutrophils and lymphocytes as described below. Results: Insignificant differences in the cytological background patterns of TCGA groups and TMB status were found. Although there was no significant difference in neutrophil count (p = 0.955) in the TCGA groups, POLEmut and MMR-d had significantly higher lymphocyte counts than no specific molecular profile (NSMP) (p = 0.019 and 0.037, respectively); furthermore, p53mut also tended to be significant (p = 0.064). Lymphocyte counts in TMB-high were also significantly greater than TMB-low (p = 0.002). POLEmut showed a positive correlation between TMB levels and lymphocyte counts. For predicting patients with POLEmut plus MMR-d, lymphocyte counts demonstrated a superior diagnostic accuracy of area under the curve (AUC) (0.70, 95% CI: 0.57–0.84), with a cutoff value of 26 high-power field. Conclusion: Lymphocyte count using liquid-based cytology for patients with endometrial cancer may predict POLEmut plus MMR-d of TCGA groups and TMB-high in those who can benefit from immunotherapy.

The Cancer Genome Atlas for uveal melanoma is predictive of patient outcomes

Uveal melanoma (UM) is the most common primary eye malignancy. Despite excellent local tumor rates, UM is a life-threatening disease with moderate systemic metastatic rates. In the past, certain clinical features were shown to be predictive of patient prognosis, including tumor thickness, tumor diameter, ciliary body involvement, and histopathologic factors. Genetic markers have lately been used to predict patient outcomes. The Cancer Genome Atlas (TCGA) is a worldwide effort developed by the National Cancer Institute and the National Human Genome Research Institute to study numerous mutations in various cancer types. TCGA has explored chromosome copy number alterations in UM, messenger RNA, micro-RNA, and long noncoding RNA expression levels and established four prognostic classes: group A (chromosome 3 and 8 disomy), group B (chromosome 3 disomy and 8q gain), group C (chromosome 3 monosomy and/or 8q gain), and group D (chromosome 3 monosomy and multiple 8q gains). Multiple studies have validated TCGA classification and have reported that it has been highly predictive of UM metastasis and patient survival.

The role of TCGA molecular classification in clear cell endometrial carcinoma.

Clear cell endometrial carcinoma (CCEC) represents a relatively rare and heterogeneous entity. Based on The Cancer Genome Atlas (TCGA) molecular classification, the risk stratification and management of endometrial cancer (EC) have been improved. Although the relationship of CCEC with the TCGA classification is less well understood, data has emerged to suggest that molecular classification plays an important role in the prognosis and management of CCEC. Most of patients with CCEC are characterized by p53abn or NSMP type and the prognosis of these patients is poor, whereas those with MMRd or POLEmut seem to have a favorable prognosis. Adjuvant therapy is recommended in CCEC with p53abn and NSMP. Advanced/recurrent CCEC with MMRd benefit much more from immune checkpoint inhibitors after the failure of platinum-based chemotherapy. In addition, bevacizumab plus chemotherapy upfront seems to improve outcomes of advanced/recurrent patients whose tumors harbored mutated TP53, including CCECs with p53abn. Further studies which exclusively recruit CCEC are urgently needed to better understand the role of molecular classification in CCEC. This review will provide an overview of our current understanding of TCGA classification in CCEC.

Determination of the Cancer Genome Atlas (TCGA) Endometrial Cancer Molecular Subtypes Using the Variant Interpretation and Clinical Decision Support Software MH Guide

The Cancer Genome Atlas (TCGA) network (United States National Cancer Institute) identified four molecular endometrial cancer (EC) subtypes using an extensive multi-method approach. The aim of this study was to determine the four TCGA EC molecular subtypes using a single-method whole-exome sequencing (WES)-based approach provided by MH Guide (Molecular Health, Heidelberg, Germany). WES and clinical data of n = 232 EC patients were obtained from TCGA. The four TCGA EC molecular subtypes designated as (i) Mutated Polymerase ε (POLE), (ii) Microsatellite Instability (MSI), (iii) Copy Number (CN) low and, (iv) CN-high were determined using the MH Guide software. The prognostic value of the subtypes determined by MH Guide were compared with the TCGA classification. Analysis of WES data using the MH Guide software led to the precise identification of the four EC molecular subtypes analogous to the TCGA classification. Both approaches displayed high concordance in terms of prognostic significance. The multi-method-based TCGA EC molecular subtypes can reliably be reproduced by the single-method-based MH Guide approach. The easy-to-implement single-method MH Guide approach represents a promising diagnostic tool.

Clinical characteristics and prognostic characterization of endometrial carcinoma: a comparative analysis of molecular typing protocols

BackgroundEndometrial carcinoma (EC) is one of the most common gynecological malignancies in China and globally, accounting for the fourth-prevalent cancer in women. Although numerous studies have confirmed prognostic value of The Cancer Genome Atlas (TCGA) molecular subgroups, it is unclear how they are combined with histological features. The main objective of this study was to compare ProMisE and TCGA classification for the rapid and accurate prediction of prognosis within EC patients, together with the provision of a revised strategy for individualized diagnosis and treatment of patients.MethodsWithin this study, 70 patients with EC from Beijing Tsinghua Changgeng Hospital (affiliated to Tsinghua University) were retrospectively examined between July 2015 and December 2021. Samples were processed for determination of clinical markers, together with ProMisE and TCGA classification.ResultsComparative analysis across four TCGA types (POLE, Low-CN, High-CN, and MSI-H) and age, was statistically significant (χ²= 7.000, p = 0.029). There was no significant difference observed among the four TCGA types and FIGO stage, vascular invasion and depth of invasion, or lymph node metastasis and tumor area. There was no significant association between the expression of Vimentin, Ki-67, PTEN, MSH2, PAX-8, β-catenin, CD10, ER, PR, P16, MLH1, and PMS2 with the four TCGA types. In addition, p63 expression (χ²= 11.09, p = 0.029) and p53 expression (χ²= 11.585, p = 0.005) were statistically significant. Numerous models demonstrated that patients with POLE mutations and low-CN had higher progression free survival (PFS) and overall survival (OS), whereas those with high-CN had lowest values. The log-rank test revealed that the survival rate of PR-positive and ER-positive patients was significantly higher (p < 0.001).ConclusionOverall, these results can be of additional benefit for clinical applications, in comparison to the ProMisE classification method. In addition, PR, ER, vascular infiltration, hyperlipidemia and atherosclerosis were found to be the key factors affecting EC prognosis.

Molecular Classification of Endometrial Carcinoma: Protocol for a Cohort Study.

BackgroundEndometrial carcinoma (EC) is the most common gynecologic malignancy in developed countries and the fourth most frequent in women worldwide. The cornerstone of treatment for EC is surgery. Clinicopathological features are currently used to help determine the individual risk of recurrence and the need for adjuvant treatment after surgery. Nonetheless, there is significant interobserver variability in assigning histologic subtype when using a morphological classification, revealing the need for a more unified approach. The Cancer Genome Atlas (TCGA) project identified 4 distinct prognostic EC subtypes based on genomic abnormalities. Surrogate assays including 3 immunohistochemical markers (p53, MSH6, and PMS2) and 1 molecular test (mutation analysis of the exonuclease domain of DNA polymerase epsilon; POLE) allowed the development and validation of a simplified molecular classifier that correlates with the TCGA classification, has prognostic value, and can easily be used in clinical practice. This molecular classification categorizes EC in 4 subtypes: POLE mutated, mismatch repair–deficient, p53 abnormal, and no specific molecular profile. Applying this classification in clinical practice will help tailor adjuvant treatment decisions.ObjectiveThe aim of this study is to retrospectively apply this novel molecular classification to a cohort of patients with EC treated in a comprehensive cancer center, to assess its applicability in clinical practice, to evaluate clinical outcomes by molecular subtypes, and to assess its prognostic value.MethodsIn this retrospective cohort study, patients with primary EC diagnosed during and after 2013 and treated or followed at our institution, after definite surgery, will be included. Demographic and clinicopathological data will be obtained from electronic health records and from pathology reports. Laboratory methods will include immunohistochemical study of p53 and mismatch repair proteins, as well as POLE mutational analysis by genetic sequencing. The primary end point is recurrence-free survival and secondary end points are disease-specific survival and overall survival. A descriptive analysis of variables will be carried out. Survival analysis will be performed using the Kaplan-Meier method and the groups will be compared using the log-rank test.ResultsThis protocol was reviewed and approved by the Instituto Português de Oncologia do Porto, Portugal, ethics committee in October 2021; patient selection from our cancer registry began the same month. A total of 160 patients will be included. This work will present real-life results that will allow a better understanding of the Portuguese EC population and the distribution of the molecular subgroups throughout. We will use these results to understand the prognostic value of this classification in our population and its role in adjuvant therapy decisions. This study is anticipated to conclude in December 2022.ConclusionsThis study will provide important information regarding these women’s outcomes according to this new molecular classification and will support its use when discussing a patient’s need for adjuvant treatment.International Registered Report Identifier (IRRID)PRR1-10.2196/34461

Molecular subtyping of gastroesophageal dysplasia heterogeneity according to TCGA/ACRG classes

Gastric adenocarcinoma has recently been classified into several subtypes on the basis of molecular profiling, which has been successfully reproduced by immunohistochemistry (IHC) and in situ hybridization (ISH). A series of 73 gastroesophageal dysplastic lesions (37 gastric dysplasia and 36 Barrett dysplasia; 44 low-grade dysplasia and 29 high-grade dysplasia) was investigated for mismatch repair proteins, E-cadherin, p53, and EBER status, to reproduce The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) molecular clustering. Overall, the dysplastic lesions were classified as follows: according to TCGA classification, EBV, 0/73 (0%), MSI, 6/73 (8.2%), GS, 4/73 (5.5%), CIN, 63/73 (86.3%); according to ACRG molecular subtyping, MSI, 6/73 (8.2%), MSS/EMT, 4/73 (5.5%), MSS/TP53−, 33/73 (45.2%), MSS/TP53+, 30/73 (41.1%). A positive association was found between MSS/TP53− and Barrett dysplasia (p = 0.0004), between MSS/TP53+ and LG dysplasia (p = 0.001) and between MSS/TP53+ and gastric dysplasia (p = 0.0018). Gastroesophageal dysplastic lesions proved to be heterogenous in terms of TCGA/ACRG classes, but with a different distribution from that of cancers, with no EBV-positive cases, an increasing presence of mismatch repair deficiency from low grade to high grade lesions, and a prevalence of p53 aberrations in Barrett dysplasia. The present study further demonstrated that gastroesophageal dysplastic lesions may be characterized by alterations in predictive/prognostic biomarkers, and this should be considered in routine diagnostic.

Molecular and pathologic data can guide selection of endometrioid endometrial cancer patients for ovarian preservation (239)

<b>Objectives:</b> To investigate the association of The Cancer Genome Atlas (TCGA) molecular subtype, <i>CTNNB1</i> (B-catenin) hotspot mutation, and pathologic factors with concurrent or recurrent ovarian disease in endometrial cancer (EC) patients (pts). <b>Methods:</b> EC pts aged ≤50 years were grouped by those electing oophorectomy (BO) versus ovarian preservation (OP) at staging surgery (January 2010-June 2021). ECs were classified as TCGA subtypes using a clinical tumor-normal next-generation sequencing (NGS) assay and immunohistochemistry data: <i>POLE</i> hotspot mutated, microsatellite instability-high (MSI-H), copy number high (CN-high), or copy number low (CN-low). <i>CTNNB1</i> hotspot mutations were classified. Germline data identified Lynch syndrome pts. Associations between molecular/pathologic features and concurrent ovarian disease (synchronous or metastatic) in BO pts were compared with Wilcoxon rank-sum and Fisher's exact tests. Associations with isolated ovarian recurrences in OP pts were examined with time to event outcomes. <b>Results:</b> Of 420 pts, 317 underwent BO, and 103 OP followed institutional guidelines (Table 1). Among BO pts with NGS (<i>n</i>=90), 14 (16%) had <i>POLE,</i> 22 (24%) MSI-H, six (7%) CN-high and 48 (53%) CN-low EC. Pathogenic <i>CTNNB1</i> mutations were present in 30/90 (33%) ECs. Of 102 pts with germline testing, 28 (28%) had Lynch syndrome. TCGA classification for OP pts with NGS (<i>n</i>=37) included six (16%) <i>POLE</i>, one (3%) MSI-H, one (3%) CN-high and 29 (78%) CN-low EC. Pathogenic <i>CTNNB1</i> mutations were present in 19/37 (51%) ECs. One of 23 (4%) pts with germline testing had Lynch syndrome. Of 317 BO pts, 27 (9%) had a concurrent ovarian disease. Among BO pts with NGS, concurrent ovarian tumors were diagnosed in 0/14 (0%) <i>POLE</i>, 2/48 (4%) CN-low, 10/22 (45%) MSI-H and 3/6 (50%) CN-high ECs (p<0.001). Concurrent ovarian disease was present in 1/37 (3%) hotspot <i>CTNNB1</i> mutated versus 9/58 (16%) wildtype/<i>CTNNB1</i> non-hotspot mutated ECs (p=0.15). Seven of 28 (25%) Lynch versus 7/74 (10%) non-Lynch syndrome pts had concurrent ovarian tumors (p=0.06). In BO pts, concurrent ovarian disease was associated with FIGO grade 2-3 versus grade 1 EC (20% vs 5%; p<0.001), positive versus negative lymphovascular space invasion (LVSI) (20% vs 7%; p=0.004), positive versus negative washings (28% vs 7%; p=0.016) and ≥50% versus <50% myoinvasion (24% vs 7%; p=0.006). Of 103 OP pts, four (4%) had isolated ovarian recurrences over a median follow-up of 17 months. Two pts had high-risk pathologic features and two had high-risk molecular features (CN-high EC and Lynch syndrome). <b>Conclusions:</b> Molecular and pathologic data improve risk stratification of pre-menopausal EC pts and enhance patient selection for ovarian preservation. In addition to Lynch syndrome, concurrent ovarian disease was seen more frequently in CN-high and MSI-H tumors or those with grade 2-3, LVSI, deep myoinvasion, and positive washings. Isolated ovarian recurrences may be independently associated with high-risk molecular features.

High-grade endometrial carcinomas: Morphologic spectrum and molecular classification.

High-grade endometrial carcinoma (HGEC) is a heterogeneous group of tumors with various morphologic, genetic, and clinical characteristics. Morphologically, HGEC includes high-grade endometrioid carcinoma, serous carcinoma, clear cell carcinoma, undifferentiated/dedifferentiated carcinoma, and carcinosarcoma. The morphologic classification has been used for prognostication and treatment decisions. However, patient management based on morphologic classification is limited by suboptimal interobserver reproducibility, variable clinical outcomes observed within the same histotype, and frequent discordant histotyping/grading between biopsy and hysterectomy specimens. Recent studies from The Cancer Genome Atlas (TCGA) Research Network established four distinct molecular subtypes: POLE-ultramutated, microsatellite unstable, copy number high, and copy number low groups. Compared to histotyping, the TCGA molecular classification appears superior in risk stratification. The best prognosis is seen in the POLE-ultramutated group and the worst in copy number high group, while the prognosis in the microsatellite unstable and copy number low groups is in between. The TCGA subtyping is more reproducible and shows a better concordance between endometrial biopsy and resection specimens. It has now become apparent that the molecular classification can supplement histotyping in patient management. This article provides an overview of the pathologic diagnosis/differential diagnosis of HGEC and the TCGA classification of endometrial cancers, with the clinical significance and applications of TCGA classification briefly discussed when appropriate.

MASTHEAD (p/u from previous issue)

High-grade endometrial carcinoma (HGEC) is a heterogeneous group of tumors with various morphologic, genetic, and clinical characteristics. Morphologically, HGEC includes high-grade endometrioid carcinoma, serous carcinoma, clear cell carcinoma, undifferentiated/dedifferentiated carcinoma, and carcinosarcoma. The morphologic classification has been used for prognostication and treatment decisions. However, patient management based on morphologic classification is limited by suboptimal interobserver reproducibility, variable clinical outcomes observed within the same histotype, and frequent discordant histotyping/grading between biopsy and hysterectomy specimens. Recent studies from The Cancer Genome Atlas (TCGA) Research Network established four distinct molecular subtypes: POLE-ultramutated, microsatellite unstable, copy number high, and copy number low groups. Compared to histotyping, the TCGA molecular classification appears superior in risk stratification. The best prognosis is seen in the POLE-ultramutated group and the worst in copy number high group, while the prognosis in the microsatellite unstable and copy number low groups is in between. The TCGA subtyping is more reproducible and shows a better concordance between endometrial biopsy and resection specimens. It has now become apparent that the molecular classification can supplement histotyping in patient management. This article provides an overview of the pathologic diagnosis/differential diagnosis of HGEC and the TCGA classification of endometrial cancers, with the clinical significance and applications of TCGA classification briefly discussed when appropriate.

TCGA molecular classification in endometriosis-associated ovarian carcinomas: Novel data on clear cell carcinoma

BackgroundClear cell and endometrioid ovarian carcinomas (OCC and OEC, respectively) have a presumed origin in endometriosis and share molecular alterations with each other and with their endometrial counterparts. The Cancer Genome Atlas (TCGA)-based molecular classification stratifies endometrial carcinomas into four categories: POLE mutated (POLEmut), mismatch repair deficient (MMRd), p53 abnormal (p53abn) and no specific molecular profile (NSMP) with divergent prognoses. The subsequent studies are indicative that this TCGA classification has some value in OEC, but the knowledge related to OCC is limited. MethodsEndometrial carcinoma molecular classification was evaluated and compared in a large series of OCCs (n = 115) and OECs (n = 158). POLE mutation analysis and tissue microarray-based immunohistochemistry for mismatch repair and p53 proteins were performed. ResultsThe distribution to the molecular groups was as follows: POLEmut 0.9%/3.2%, MMRd 3.5%/6.3%, p53abn 20%/30%, and NSMP 76%/60% in OCCs/OECs, respectively. The proportion of NSMP tumors was the largest in both histological types and significantly higher in OCC than OEC (p = 0.009). The molecular classification correlated significantly with DSS in both OCCs and OECs (p < 0.001 and p = 0.009, respectively), and with DFS in OCCs (p = 0.001). POLEmut and MMRd OCCs carried excellent prognosis, whereas MMRd OECs presented with poorer outcome. The p53abn group was associated with the poorest prognosis in both tumor types, particularly emphasized in OCCs. ConclusionsTCGA molecular classification associated with patient outcome in both histotypes, and the difference in prognosis between the molecular groups was even more marked in OCC. The large amount of NSMP tumors highlights the need for further studies.

Non-Helicobacter pylori Helicobacter (NHPH) positive gastric cancer

Genetic analysis and culturing techniques for gastric non-Helicobacter pylori Helicobacter (NHPH) are progressing. NHPH is reported to accompany nodular gastritis, gastric MALT lymphoma, and mild gastritis. However, only a few gastric cancer cases infected by NHPH have been reported. PCR analysis specific for NHPH and H. pylori was performed for DNA from gastric mucosa of 282 Korean gastric cancer patients, who were treated with endoscopic submucosal dissection. For more precise strain detection of NHPH, NHPH-positive mucosa was stained by immunohistochemistry specific for Helicobacter suis. The Cancer Genome Atlas (TCGA) classification was analyzed for these 3 gastric cancer sub-groups by in situ hybridization and immunohistochemistry. Among 281 patients, 3 patients (1.1%) were positive for NHPH. One patient (Patient 1) was also positive for H. pylori by PCR, another patient (Patient 3) was positive for serum IgG for H. pylori, and the other patient (Patient 2) had no evidence for H. pylori infection. Gastric mucosa of Patients 2 and 3 were positive for H. suis staining. All three NHPH-positive gastric cancers were located in the antrum, and belonged to the Chromosomal Instability Type of TCGA classification. Gastric NHPH can be a cause of gastric cancer, although likely with lower pathogenesis than H. pylori.

Reproduction of the Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) Gastric Cancer Molecular Classifications and Their Association with Clinicopathological Characteristics and Overall Survival in Moroccan Patients.

Introduction The Cancer Genome Atlas (TCGA) project and Asian Cancer Research Group (ACRG) recently categorized gastric cancer into molecular subtypes. Nevertheless, these classification systems require high cost and sophisticated molecular technologies, preventing their widespread use in the clinic. This study is aimed to generating molecular subtypes of gastric cancer using techniques available in routine diagnostic practice in a series of Moroccan gastric cancer patients. In addition, we assessed the associations between molecular subtypes, clinicopathological features, and prognosis. Methods Ninety-seven gastric cancer cases were classified according to TCGA, ACRG, and integrated classifications using a panel of four molecular markers (EBV, MSI, E-cadherin, and p53). HER2 status and PD-L1 expression were also evaluated. These markers were analyzed using immunohistochemistry (E-cadherin, p53, HER2, and PD-L1), in situ hybridization (EBV and HER2 equivocal cases), and multiplex PCR (MSI). Results Our results showed that the subtypes presented distinct clinicopathological features and prognosis. EBV-positive gastric cancers were found exclusively in male patients. The GS (TCGA classification), MSS/EMT (ACRG classification), and E-cadherin aberrant subtype (integrated classification) presented the Lauren diffuse histology enrichment and tended to be diagnosed at a younger age. The MSI subtype was associated with a better overall survival across all classifications (TCGA, ACRG, and integrated classification). The worst prognosis was observed in the EBV subtype (TCGA and integrated classification) and MSS/EMT subtype (ACRG classification). Discussion/Conclusion. We reported a reproducible and affordable gastric cancer subtyping algorithms that can reproduce the recently recognized TCGA, ACRG, and integrated gastric cancer classifications, using techniques available in routine diagnosis. These simplified classifications can be employed not only for molecular classification but also in predicting the prognosis of gastric cancer patients.

Invited Commentary: Radiogenomics Applied to Select Abdominal Tumors.

Invited Commentary: Radiogenomics Applied to Select Abdominal Tumors.

TCGA Classification of Endometrial Cancer: the Place of Carcinosarcoma.

In 2013, The Cancer Genome Atlas (TCGA) Research Network found four novel prognostic subgroups of endometrial carcinoma: POLE/ultramutated (POLE), microsatellite-instable/hypermutated (MSI), copy-number-low/TP53-wild-type (CNL), and copy-number-highTP53-mutant (CNH). However, poor is known regarding uncommon histotypes of endometrial cancer. We aimed to assess the genetic profile of uterine carcinosarcoma (UCS) on the light of these findings. A systematic review and meta-analysis was performed through electronic databases searching (up to July 2019). All studies assessing UCS series for the TCGA classification were included. For each TCGA subgroup, pooled prevalence on the total UCS number was calculated. Four studies with 231 patients were included. Pooled prevalence of the TCGA subgroups were: 5.3% for the POLE subgroup, 7.3% for the MSI subgroup, 73.9% for the CNH subgroup, 13.5% for the CNL subgroup. The CNH subgroup predominates in UCS, while subgroups with high mutational load (POLE and MSI) are less common. UCS appears as a preferential evolution of CNH carcinomas.

TCGA molecular subgroups and FIGO grade in endometrial endometrioid carcinoma.

International Federation of Gynecology and Obstetrics (FIGO) grade is a crucial factor in the current system for the risk stratification of endometrial endometrioid carcinoma (EC). The Cancer Genome Atlas (TCGA) demonstrated four molecular prognostic subgroups for EC: POLE (good prognosis), microsatellite-instable (MSI, intermediate prognosis), copy-number-high (CNH, poor prognosis), and copy-number-low (CNL, variable prognosis). To assess how the prevalence of the TCGA molecular subgroups changes from low-grade (G1-2) to high-grade (G3) EC, to understand how it may affect the current risk-assessment system. A systematic review and meta-analysis was carried out by searching seven electronic databases from January 2013 to September 2019 for studies assessing the TCGA classification G1-2 and G3 EC. Pooled prevalence of the TCGA subgroups was calculated in EC. The association of each subgroup with grade was assessed using odds ratio (OR), with a significant p value < 0.05. Nine studies with 3185 patients were included. G3 EC showed significantly higher prevalence of the POLE subgroup (12.1% vs 6.2%; OR = 2.13; p = 0.0001), of the MSI subgroup (39.7% vs 24.7%; OR = 2.15; p = 0.0003) and of the CNH subgroup (21.3% vs 4.7%; OR = 5.25; p < 0.00001), and significantly lower prevalence of the CNL subgroup (28% vs 63.5%; OR = 0.2; p < 0.00001) than G1-2 EC. The prevalence of the TCGA subgroups is not in accordance with the prognostic value of FIGO grade, indicating that the current risk stratification of EC will be heavily affected by molecular signature.

Accuracy of The Cancer Genome Atlas Classification vs American Joint Committee on Cancer Classification for Prediction of Metastasis in Patients With Uveal Melanoma

The Cancer Genome Atlas (TCGA) classification is a newly emerging method for prediction of uveal melanoma (UM)-related metastasis and death. Limited information is available regarding the accuracy of the TCGA classification for prediction of metastasis in patients with UM. To investigate the accuracy of the TCGA classification for predicting UM-related metastasis compared with the American Joint Committee on Cancer (AJCC) classification. In this retrospective cohort study, patients with UM treated with plaque radiotherapy at a tertiary referral center from October 1, 2008, to December 31, 2018, were evaluated. All patients with tumors classified according to the American Joint Committee on Cancer Staging Manual, 8th Edition, and who completed pretreatment fine-needle aspiration biopsy sampling for genetic analysis of chromosomes 3 and 8 for TCGA classification were included. Tumors were classified into 4 categories, 17 subcategories, and 4 stages using AJCC classification and further grouped into 4 classes using TCGA classification. Value of TCGA classification vs AJCC classification for predicting UM-related metastasis. Of 642 included patients, 331 (51.6%) were women, and the mean (SD) age was 58.0 (13.8) years. There were 642 tumors from 642 patients classified according to both AJCC and TCGA classifications. The mean (range) follow-up time for the entire cohort was 43.7 (1.4-159.2) months. At 5 years, TCGA classification showed higher value for prediction of metastasis (4 TCGA classes: Wald statistic, 94.8; hazard ratio [HR], 2.8; 95% CI, 2.3-3.5; P < .001; 4 AJCC categories: Wald statistic, 67.5; HR, 2.6; 95% CI, 2.1-3.2; P < .001; 17 AJCC subcategories: Wald statistic, 74.3; HR, 1.3; 95% CI, 1.2-1.3; P < .001; 4 AJCC stages: Wald statistic, 67.0; HR, not applicable; P < .001). After entering TCGA and AJCC classifications into a multivariate model, TCGA classification still showed higher value for prediction of metastasis (TCGA classification: Wald statistic, 61.5; HR, 2.4; 95% CI, 1.9-2.9; P < .001; AJCC classification: Wald statistic, 35.5; HR, 1.9; 95% CI, 1.5-2.4; P < .001). These results suggest that TCGA classification provides accuracy that is superior to AJCC categories, subcategories, and stages for predicting metastasis from UM. When genetic testing is available, TCGA classification can provide a more accurate way to identify patients at high risk of metastasis who might benefit from adjuvant therapy.

Reclassifying endometrial carcinomas with a combined morphological and molecular approach.

Currently, endometrial carcinoma diagnosis is based on morphology, often supplemented by immunohistochemistry. However, especially with high-grade endometrial carcinomas, there is considerable interobserver variability in diagnosis calling into question the value of morphology in stratifying these tumours into different prognostic and therapeutic groups. The purpose of this review is to provide an update on the recently described molecular classification of endometrial carcinoma. In 2013, the Cancer Genome Atlas (TCGA) published a seminal molecular study of endometrial carcinomas of endometrioid, serous and mixed types. This revealed that endometrial carcinoma consists of four intrinsic molecular subtypes: POLE (ultramutated), microsatellite instabilty (hypermutated), copy-number low (also referred to as microsatellite stable or no specific molecular profile) and copy-number high (serous-like). These four molecular subtypes are of prognostic significance with POLE tumours having the best and copy-number high, the worst prognosis. It is likely that TCGA classification will become the mainstay of endometrial carcinoma diagnosis in the coming years and various strategies (Proactive Molecular Risk Classifier for Endometrial Cancer and the TransPORTEC classifiers) have been proposed for a combined morphological-molecular classification which can be undertaken in most pathology laboratories. This will necessitate routine undertaking of POLE mutation analysis in some endometrial carcinomas and require an appropriate infrastructure.

Genetic Analysis of Uveal Melanoma in 658 Patients Using the Cancer Genome Atlas Classification of Uveal Melanoma as A, B, C, and D

The Cancer Genome Atlas (TCGA) classification has been validated for uveal melanoma (UM) prognostication. We applied TCGA classification to UM biopsied using fine-needle aspiration biopsy (FNAB) to determine the predictability for metastasis and death. Retrospective cohort study. Patients with UM treated with plaque radiotherapy at Wills Eye Hospital, Philadelphia, Pennsylvania, from October 1, 2008, through December 31, 2018, who completed genetic analysis of chromosomes 3 and 8 after FNAB. Tumors were classified as A, B, C, or D and were compared using the chi-square test, Fisher exact test, analysis of variance, and Kaplan-Meier analysis. Metastasis and death. Six hundred fifty-eight UM patients were categorized accordingly as TCGA class A (n= 342 [52%]), B (n= 91 [14%]), C (n= 118 [18%]), and D (n= 107 [16%]). More advanced tumor classification revealed older mean patient age (56 vs. 53 vs. 60 vs. 63 years, respectively; P < 0.001), worse presenting visual acuity (20/20-20/50: 81% vs. 67% vs. 71% vs. 66%, respectively; P < 0.001), greater distance from the optic disc (3.5vs. 4.9 vs. 5.7 vs. 5.3 mm, respectively; P < 0.001), larger tumor basal diameter (10.3 vs. 12.9 vs. 13.9 vs. 15.3mm, respectively; P < 0.001), and greater tumor thickness (4.3 vs. 6.1 vs. 6.6 vs. 7.5 mm, respectively; P<0.001). After mean follow-up (47.6 vs. 47.6 vs. 42.9 vs. 28.7 months, respectively; P < 0.001), more advanced TCGA class was associated with increased risk of metastasis (3% vs. 10% vs. 25% vs. 41%, respectively; P<0.001) and death (1% vs. 0% vs. 3% vs. 9%, respectively; P < 0.001). Compared with class A, the 5-year hazard ratio for metastasis increased at 4.1 (B vs. A; P= 0.01), 10.1 (C vs. A; P < 0.001), and 30.0 (D vs. A; P< 0.001). The 5-year hazard ratio for death increased at 3.1 (C vs. A; P= 0.11) and 13.7 (D vs. A; P<0.001) with no deaths in class B. Grouping of UM using TCGA classification predicts the risk of melanoma-related metastasis and death.