scholarly journals Association of a novel endometrial cancer biomarker panel with prognostic risk, platinum insensitivity, and targetable therapeutic options

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245664
Author(s):  
Jesus Gonzalez Bosquet ◽  
Qing Zhang ◽  
William A. Cliby ◽  
Jamie N. Bakkum-Gamez ◽  
Ling Cen ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Dna Sequences ◽  
Myometrial Invasion ◽  
Molecular Classification ◽  
Therapeutic Options ◽  
The Cancer Genome Atlas ◽  
Biomarker Panel ◽  
Phosphatase 2A ◽  
Cancer Genome Atlas ◽  
Molecular Aberrations

During the past decade, the age-adjusted mortality rate for endometrial cancer (EC) increased 1.9% annually with TP53 mutant (TP53-mu) EC disproportionally represented in advanced disease and deaths. Therefore, we aimed to assess pivotal molecular parameters that differentiate clinical outcomes in high- and low-risk EC. Using the Cancer Genome Atlas, we analyzed EC specimens with available DNA sequences and quantitative gene-specific RNA expression data. After polymerase ɛ (POLE)-mutant specimens were excluded, differential gene-specific mutations and mRNA expressions were annotated and integrated. Consequent to TP53-mu failure to induce p21, derepression of multiple oncogenes harboring promoter p21 repressive sites was observed, including CCNA2 and FOXM1 (P < .001 compared with TP53 wild type [TP53-wt]). TP53-wt EC with high CCNA2 expression (CCNA2-H) had a targeted transcriptomic profile similar to that of TP53-mu EC, suggesting CCNA2 is a seminal determinant for both TP53-wt and TP53-mu EC. CCNA2 enhances E2F1 function, upregulating FOXM1 and CIP2A, as observed in TP53-mu and CCNA2-H TP53-wt EC (P < .001). CIP2A inhibits protein phosphatase 2A, leading to AKT inactivation of GSK3β and restricted oncoprotein degradation; PPP2R1A and FBXW7 mutations yield similar results. Upregulation of FOXM1 and failed degradation of FOXM1 is evidenced by marked upregulation of multiple homologous recombination genes (P < .001). Integrating these molecular aberrations generated a molecular biomarker panel with significant prognostic discrimination (P = 5.8×10−7); adjusting for age, histology, grade, myometrial invasion, TP53 status, and stage, only CCNA2-H/E2F1-H (P = .0003), FBXW7-mu/PPP2R1A-mu (P = .0002), and stage (P = .017) were significant. The generated prognostic molecular classification system identifies dissimilar signaling aberrations potentially amenable to targetable therapeutic options.

scholarly journals Fertility Sparing Treatments in Endometrial Cancer Patients: The Potential Role of the New Molecular Classification

2021 ◽  
Vol 22 (22) ◽  
pp. 12248
Author(s):  
Anna Franca Cavaliere ◽  
Federica Perelli ◽  
Simona Zaami ◽  
Marco D’Indinosante ◽  
Irene Turrini ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Cancer Patients ◽  
Young Patients ◽  
Hormonal Treatment ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Gynecological Malignancy ◽  
Oncological Safety ◽  
Fertility Sparing ◽  
Cancer Genome Atlas

Endometrial cancer is the most frequent gynecological malignancy, and, although epidemiologically it mainly affects advanced age women, it can also affect young patients who want children and who have not yet completed their procreative project. Fertility sparing treatments are the subject of many studies and research in continuous evolution, and represent a light of hope for young cancer patients who find themselves having to face an oncological path before fulfilling their desire for motherhood. The advances in molecular biology and the more precise clinical and prognostic classification of endometrial cancer based on the 2013 The Cancer Genome Atlas classification allow for the selection of patients who can be submitted to fertility sparing treatments with increasing oncological safety. It would also be possible to predict the response to hormonal treatment by investigating the state of the genes of the mismatch repair.

scholarly journals Racial differences in endometrial cancer molecular portraits in The Cancer Genome Atlas

Oncotarget ◽  
2018 ◽  
Vol 9 (24) ◽  
pp. 17093-17103 ◽  
Author(s):  
David S. Guttery ◽  
Kevin Blighe ◽  
Konstantinos Polymeros ◽  
R. Paul Symonds ◽  
Salvador Macip ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Racial Differences ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Interfocal heterogeneity challenges the clinical usefulness of molecular classification of primary prostate cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kristina Totland Carm ◽  
Andreas M. Hoff ◽  
Anne Cathrine Bakken ◽  
Ulrika Axcrona ◽  
Karol Axcrona ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Classification ◽  
Primary Diagnosis ◽  
The Cancer Genome Atlas ◽  
Clinical Usefulness ◽  
Whole Exome ◽  
Primary Prostate Cancer ◽  
Cancer Genome Atlas ◽  
Prostate Cancers

Abstract Prostate cancer is a highly heterogeneous disease and typically multiple distinct cancer foci are present at primary diagnosis. Molecular classification of prostate cancer can potentially aid the precision of diagnosis and treatment. A promising genomic classifier was published by The Cancer Genome Atlas (TCGA), successfully classifying 74% of primary prostate cancers into seven groups based on one cancer sample per patient. Here, we explore the clinical usefulness of this classification by testing the classifier’s performance in a multifocal context. We analyzed 106 cancer samples from 85 distinct cancer foci within 39 patients. By somatic mutation data from whole-exome sequencing and targeted qualitative and quantitative gene expression assays, 31% of the patients were uniquely classified into one of the seven TCGA classes. Further, different samples from the same focus had conflicting classification in 12% of the foci. In conclusion, the level of both intra- and interfocal heterogeneity is extensive and must be taken into consideration in the development of clinically useful molecular classification of primary prostate cancer.

TNFα signalling predicts poor prognosis of patients with endometrial cancer

2020 ◽  
Vol 41 (8) ◽  
pp. 1065-1073
Author(s):  
Verena Wieser ◽  
Samira Abdel Azim ◽  
Susanne Sprung ◽  
Katharina Knoll ◽  
Johanna Kögl ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Clinical Outcome ◽  
The Cancer Genome Atlas ◽  
Western World ◽  
Low Grade ◽  
Necrosis Factor Alpha ◽  
Cancer Genome Atlas ◽  
Factor Alpha ◽  
The Impact

Abstract Endometrial cancer (EC) is the most common gynaecologic tumour in the Western world. Previous studies have implicated an imbalance of oestrogens and progestogens in the development of most ECs, while the role of low-grade tissue inflammation remains largely unexplored. We investigated the impact of tumour necrosis factor alpha (TNFα), a central mediator of inflammation and spermatogenesis-associated protein 2 (SPATA2), a regulator of TNF receptor signalling, on clinical outcomes in EC. We evaluated TNFA and SPATA2 transcript levels in 239 EC patients and 25 non-malignant control tissues. Findings were validated in a cohort of 332 EC patients from The Cancer Genome Atlas (TCGA). Expression of TNFA and SPATA2 was increased in EC when compared with control tissues (P &lt; 0.001). TNFA expression correlated with SPATA2 expression in non-malignant (P = 0.003, rS = 0.568) and EC tissue (P = 0.005, rS = 0.179). High TNFA and SPATA2 expression were associated with poor recurrence-free survival (RFS; P = 0.049 and P = 0.018) and disease-specific (P = 0.034 and P = 0.002) survival. Increased SPATA2 expression was also associated with decreased overall survival (OS; P = 0.013). In multivariate analysis, both TNFA and SPATA2 were predictors of clinical outcome. The impact of SPATA2 on RFS and OS could be validated in the TCGA cohort. Our study demonstrates that ECs exhibit a TNF signature which predicts clinical outcome. These findings indicate that TNF signalling modulates the course of EC, which could be therapeutically utilized in the future.

scholarly journals The emerging role of molecular pathology in directing the systemic treatment of endometrial cancer

2021 ◽  
Vol 13 ◽  
pp. 175883592110359
Author(s):  
Amy Jamieson ◽  
Tjalling Bosse ◽  
Jessica N. McAlpine
Keyword(s):  
Endometrial Cancer ◽  
Molecular Subtypes ◽  
Treatment Decision ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Molecular Profile ◽  
Therapeutic Implications ◽  
Treatment Decision Making ◽  
Exciting Time ◽  
Classification Tool

Following the discovery of the four molecular subtypes of endometrial cancer (EC) by The Cancer Genome Atlas (TCGA) in 2013, subsequent studies used surrogate markers to develop and validate a clinically relevant EC classification tool to recapitulate TCGA subtypes. Molecular classification combines focused sequencing ( POLE) and immunohistochemistry (mismatch repair and p53 proteins) to assign patients with EC to one of four molecular subtypes: POLEmut, MMRd, p53abn and NSMP (no specific molecular profile). Unlike histopathological evaluation, the molecular subtyping of EC offers an objective and reproducible classification system that has been shown to have prognostic value and therapeutic implications. It is an exciting time in EC care where we have moved beyond treatment based on histomorphology alone, and molecular classification will now finally allow assessment of treatment efficacy within biologically similar tumours. It is now recommended that molecular classification should be considered for all ECs, and should be performed routinely in all high grade tumours. It is also recommended to incorporate molecular classification into standard pathology reporting and treatment decision-making algorithms. In this review, we will discuss how the molecular classification of EC can be used to guide both conventional and targeted therapy in this new molecular era.

scholarly journals Identification of immune-related subtypes of colorectal cancer to improve antitumor immunotherapy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaobo Zheng ◽  
Yong Gao ◽  
Chune Yu ◽  
Guiquan Fan ◽  
Pengwu Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Checkpoint Inhibitors ◽  
Molecular Classification ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Training Cohort ◽  
Immune System Activation ◽  
Antitumor Immunotherapy ◽  
Cancer Genome Atlas ◽  
Tumor Management

AbstractImmunotherapy involving immune checkpoint inhibitors (ICIs) for enhancing immune system activation is promising for tumor management. However, the patients’ responses to ICIs are different. Here, we applied a non-negative matrix factorization algorithm to establish a robust immune molecular classification system for colorectal cancer (CRC). We obtained data of 1503 CRC patients (training cohort: 488 from The Cancer Genome Atlas; validation cohort: 1015 from the Gene Expression Omnibus). In the training cohort, 42.8% of patients who exhibited significantly higher immunocyte infiltration and enrichment of immune response-associated signatures were subdivided into immune classes. Within the immune class, 53.1% of patients were associated with a worse overall prognosis and belonged to the immune-suppressed subclass, characterized by the activation of stroma-related signatures, genes, immune-suppressive cells, and signaling. The remaining immune class patients belonged to the immune-activated subclass, which was associated with a better prognosis and response to anti-PD-1 therapy. Immune-related subtypes were associated with different copy number alterations, tumor-infiltrating lymphocyte enrichment, PD-1/PD-L1 expression, mutation landscape, and cancer stemness. These results were validated in patients with microsatellite instable CRC. We described a novel immune-related class of CRC, which may be used for selecting candidate patients with CRC for immunotherapy and tailoring optimal immunotherapeutic treatment.

scholarly journals A radiogenomics application for prognostic profiling of endometrial cancer

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Erling A. Hoivik ◽  
Erlend Hodneland ◽  
Julie A. Dybvik ◽  
Kari S. Wagner-Larsen ◽  
Kristine E. Fasmer ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Treatment Strategies ◽  
Risk Groups ◽  
The Cancer Genome Atlas ◽  
Tumor Segmentation ◽  
Poor Survival ◽  
Cancer Genome Atlas ◽  
Automated Machine Learning ◽  
Magnetic Resonance Imaging Mri

AbstractPrognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecular biomarkers (n = 550 patients) aiming to identify aggressive tumor features in a study including 866 EC patients. Whole-volume tumor radiomic profiling from manually (radiologists) segmented tumors (n = 138 patients) yielded clusters identifying patients with high-risk histological features and poor survival. Radiomic profiling by a fully automated machine learning (ML)-based tumor segmentation algorithm (n = 336 patients) reproduced the same radiomic prognostic groups. From these radiomic risk-groups, an 11-gene high-risk signature was defined, and its prognostic role was reproduced in orthologous validation cohorts (n = 554 patients) and aligned with The Cancer Genome Atlas (TCGA) molecular class with poor survival (copy-number-high/p53-altered). We conclude that MRI-based integrated radiogenomics profiling provides refined tumor characterization that may aid in prognostication and guide future treatment strategies in EC.

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