Multi-omics profiling reveals distinct microenvironment characterization of endometrial cancer

A Comprehensive Review of the Endometrial Receptivity Array in Euploid Embryo Transfer Cycles

The Endometrial Receptivity Array (ERA) is a revolutionary molecular diagnostic tool that determines the optimal timing for embryo transfer by analyzing the gene expression profile of endometrial tissue. This comprehensive review examines the significance and application of ERA in euploid embryo transfer cycles, where the implantation of embryos with the correct number of chromosomes is critical for achieving successful pregnancy outcomes. This review underscores its role in enhancing implantation rates and reducing pregnancy loss by assessing the evolution, methodology, clinical applications, efficacy, and challenges associated with ERA. Key findings highlight ERA's superior accuracy in identifying the window of implantation compared to traditional methods, resulting in improved clinical outcomes in assisted reproductive technology (ART) cycles. Despite its benefits, the review acknowledges challenges such as cost, accessibility, and the need for standardization. Recommendations for clinical practice emphasize the integration of ERA into routine ART protocols, comprehensive patient counseling, and the importance of multidisciplinary collaboration. The review outlines promising prospects, including technological advancements to make ERA more cost-effective, the development of refined gene expression profiles, and the potential integration with other emerging ART technologies. Further research directions include long-term studies on the outcomes of ERA-guided pregnancies and exploring its application in cases of recurrent implantation failure and unexplained infertility. Overall, ERA represents a significant advancement in reproductive medicine, offering a personalized approach to embryo transfer timing that can significantly improve the success rates of euploid embryo transfers.

The Clinical and Pathological Characteristics of POLE-Mutated Endometrial Cancer: A Comprehensive Review

Endometrial cancer shows high histological and molecular heterogeneity. The POLE mutation is a significant molecular alteration in endometrial cancer, leading to the identification of a specific subtype known as POLE-mutated endometrial cancer. This subtype exhibits a high tumor mutation burden, abundant lymphocyte infiltration, and a favorable prognosis, making it a promising candidate for immune checkpoint inhibitor therapy. This paper presents a comprehensive review of the clinical and pathological characteristics, outcomes, treatment advancements, pathogenic POLE gene detection, and alternative testing methods for POLE-mutated endometrial cancer.

Re-stratification of patients with copy-number low endometrial cancer by clinicopathological characteristics

OBJECTIVE

To stratify patients with copy-number low (CNL) endometrial cancer (EC) by clinicopathological characteristics.

METHODS

EC patients who underwent surgery between June 2018 and June 2022 at Peking University People's Hospital were included and further classified according to TCGA molecular subtyping: POLE ultramutated, microsatellite instability high (MSI-H), CNL, and copy-number high (CNH). Clinicopathological characteristics and prognosis of CNL patients were retrospectively reviewed. The Cox proportional hazards regression model was applied to perform univariate and multivariate analysis, and independent risk factors were identified. Differentially expressed genes (DEGs) according to overall survival (OS) were screened based on the transcriptome of CNL cases from the TCGA program. Finally, a nomogram was established, with an accuracy analysis performed.

RESULTS

(1) A total of 279 EC patients were included, of whom 168 (60.2%) were in the CNL group. A total of 21 patients had recurrence and 6 patients deceased, and no significant difference in recurrence-free survival (RFS) was exhibited among the four molecular subtypes (P = 0.104), but that in overall survival (OS) was statistically significant (P = 0.036). (2) CNL patients were divided into recurrence and non-recurrence groups, and significant differences (P < 0.05) were found between the two groups in terms of pathological subtype, FIGO stage, ER, PR, glycated hemoglobin (HbA1c), and high-density lipoprotein cholesterol (HDL-C). All the above factors were included in univariate and multivariate Cox regression models, among which pathological subtype, PR, and HDL-C were statistically different (P < 0.05), resulting in three independent risk factors for the prognosis of patients in the CNL group. (3) By comparing the transcriptome of tumor tissues between living and deceased CNL patients from the TCGA database, 903 (4.4%) DEGs were screened, with four lipid metabolism pathways significantly enriched. Finally, a nomogram was established, and internal cross-validation was performed, showing good discrimination accuracy with an AUC of 0.831 and a C-index of 0.748 (95% CI 0.444-1.052). (4) According to the established nomogram and the median total score (85.89), patients were divided into the high score group (n = 85) and low score group (n = 83), and the 8 patients with recurrence were all in the high score group. Survival analysis was performed between the two groups, and the difference in RFS was statistically significant (P = 0.010).

CONCLUSION

In the CNL group of EC patients, pathological subtype, PR, and HDL-C were independent prognostic risk factors, the nomogram established based upon which had a good predictive ability for the recurrence risk of patients with CNL EC.

Features of the immunosuppressive tumor microenvironment in endometrial cancer based on molecular subtype

Endometrial cancer (EC) is one of the three most prevalent gynecological tumors affecting women and is the most prevalent gynecological malignancy in the developed world. Its incidence is rapidly increasing worldwide, mostly affecting postmenopausal women, whereas recently its prevalence has increased in younger people. EC is an immune gene disease and many studies have shown that the tumor-immunosuppressive microenvironment plays an important role in cancer progression. In recent years, findings regarding the immunosuppressive tumor microenvironment (ITME) of EC have included immune evasion mechanisms and immunotherapy, which are mostly immune checkpoint inhibitors (ICI) for EC. Recently studies on the ITME of different molecular types of EC have found that different molecular types may have different ITME. With the research on the immune microenvironment of EC, a new immunophenotype classification based on the immune microenvironment has been carried out in recent years. However, the impact of the ITME on EC remains unclear, and the immunophenotype of EC remains limited to the research stage. Our review describes recent findings regarding the ITME features of different EC molecular types. The advent of immunotherapy has brought hope for improved efficacy and prognosis in patients with advanced or recurrent EC. The efficacy and safety of ICIs combination therapy remains the focus of future research.

Impact of immune infiltration signatures on prognosis in endometrial carcinoma is dependent on the underlying molecular subtype

OBJECTIVES

Increased numbers of tumor infiltrating lymphocytes (TIL) in endometrial cancer (EC) are associated with improved survival, but it is unclear how this prognostic significance relates to the underlying EC molecular subtype. In this explorative hypothesis-generating study, we sought to define the immune signatures associated with the molecular subtypes of EC (i.e., POLE-mutated, microsatellite unstable (MSI-high), copy number (CN)-low, and CN-high) and to determine their correlation with patient outcomes.

METHODS

RNA-sequencing and molecular subtype data of 232 primary ECs were obtained from The Cancer Genome Atlas. Deconvolution of bulk gene expression data was performed using single sample Gene Set Enrichment Analysis (ssGSEA) and Cell type Identification By Estimating Relative Subsets Of known RNA Transcripts (CIBERSORT). The association of the resultant immune signatures with overall survival was determined across molecular subtypes.

RESULTS

Statistically significant differences in enrichment were identified in 16/30 and 6/23 immune gene sets by ssGSEA and CIBERSORT, respectively. Signature of CD8+ cells in ECs of CN-high molecular subtype was associated with improved overall survival by ssGSEA (p = 0.0108), while CD8 signatures did not appear to be prognostic in MSI-high (p = 0.74) or CN-low EC molecular subtypes (p = 0.793). Of all molecular subtypes, CN-high ECs exhibited the lowest levels of CD8+ T cell infiltration. Consistent with antigen-induced T cell activation and exhaustion, enrichment for immunomodulatory receptors was predominantly observed in ECs of MSI-high and POLE-mutated molecular subtypes.

CONCLUSIONS

Deconvolution of bulk gene expression data can be used to identify populations of immune infiltrated endometrial cancers with improved survival. These data support the existence of unique mechanisms of immune resistance within molecular subgroups of the disease.

Immunosuppressive tumor microenvironment in Uterine Serous Carcinoma via CCL7 signal with myeloid-derived suppressor cells

Serous carcinoma of the uterus (USC) is a pathological subtype of high-grade endometrial cancers, with no effective treatment for advanced cases. Since such refractory tumors frequently harbor anti-tumor immune tolerance, many immunotherapies have been investigated for various malignant tumors using immuno-competent animal models mimicking their local immunities. In this study, we established an orthotopic mouse model of high-grade endometrial cancer and evaluated the local tumor immunity to explore the efficacy of immunotherapies against USC. A multivariate analysis of 62 human USC cases revealed that the tumor infiltrating cell status, few CD8+ cells and abundant myeloid-derived suppressor cells (MDSCs), was an independent prognostic factor (p<0.005). A murine endometrial cancer cell (mECC) was obtained from C57BL/6 mice via endometrium-specific deletion of Pten and Tp53, and another high-grade cell (HPmECC) was established by further overexpressing Myc in mECCs. HPmECCs exhibited higher capacities of migration and anchorage-independent proliferation than mECCs (p<0.01, p<0.0001), and when both types of cells were inoculated into the uterus of C57BL/6 mice, the prognosis of mice bearing HPmECC-derived tumors was significantly poorer (p<0.001). Histopathological analysis of HPmECC orthotopic tumors showed serous carcinoma-like features with prominent tumor infiltration of MDSCs (p<0.05), and anti Gr-1 antibody treatment significantly prolonged the prognosis of HPmECC-derived tumor-bearing mice (p<0.05). High CCL7 expression was observed in human USC and HPmECC, and MDSCs migration was promoted in a CCL7 concentration-dependent manner. These results indicate that anti-tumor immunity is suppressed in USC due to increased number of tumor-infiltrating MDSCs via CCL signal.

Association of laboratorial parameters and prognostic factors in uterine corpus cancer

OBJECTIVE

The aims were to compare the red blood cells, platelet count, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, red cell distribution width, and fasting glucose in peripheral blood of patients with benign and malignant uterine neoplasms and to relate these laboratory parameters with prognostic factors and overall survival in cancer.

METHODS

The results of the laboratory parameters were analyzed using the Mann-Whitney U test. Receiver operating characteristic curves were used to find the cutoff values. Overall survival was estimated using the Kaplan-Meyer method.

RESULTS

Higher values of neutrophil-lymphocyte ratio and fasting glucose were found in cancer patients. Higher platelet-lymphocyte ratio values were associated with other subtypes when compared with endometrioid subtype; higher values of red cell distribution width were found in stage II/IV when compared with stage I; lower hemoglobin values were related to stage II/IV and nonendometrioid histological type. Platelet-lymphocyte ratio <145.56 was associated with longer overall survival.

CONCLUSION

Hemoglobin and platelet-lymphocyte ratio values are prognostic factors in uterine corpus cancer.

Bioinformatic profiling identifies prognosis-related genes in the immune microenvironment of endometrial carcinoma

Endometrial carcinoma (EC) is a common malignancy of female genital system which exhibits a unique immune profile. It is a promising strategy to quantify immune patterns of EC for predicting prognosis and therapeutic efficiency. Here, we attempted to identify the possible immune microenvironment-related prognostic markers of EC. We obtained the RNA sequencing and corresponding clinical data of EC from TCGA database. Then, 3 immune scores based on the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm were computed. Correlation between above ESTIMATE scores and other immune-related scores, molecular subtypes, prognosis, and gene mutation status (including BRCA and TP53) were further analyzed. Afterwards, gene modules associated with the ESTIMATE scores were screened out through hierarchical clustering analysis and weighted gene co-expression network analysis (WGCNA). Differentially expressed analysis was performed and genes shared by the most relevant modules were found out. KEGG pathway enrichment analysis was conducted to explore the biological functions of those genes. Survival analysis was carried out to identify prognostic immune-related genes and GSE17025 database was further used to confirm the correlation between immune-related genes and the ImmuneScore. The immune-related scores based on ESTIMATE algorithm was closely related to the immune microenvironment of EC. 3 gene modules that had the closest correlations with 3 ESTIMATE scores were obtained. 109 immune-related genes were preliminarily found out and 29 pathways were significantly enriched, most of which were associated with immune response. Univariate survival analysis revealed that there were 14 genes positively associated with both OS and PFS. Among which, 11 genes showed marked correlations with ImmuneScore values in GSE17025 database. Our current study profiled the immune status and identified 14 novel immune-related prognostic biomarkers for EC. Our findings may help to investigate the complicated tumor microenvironment and develop novel individualized therapeutic targets for EC.

Integrative genome-scale analysis of immune infiltration in esophageal carcinoma

To explore the molecular mechanism in the esophageal squamous carcinoma (ESCC) environment, we selected datasets of ESCC patients from The Cancer Genome Atlas (TCGA) (n = 78) and explored the infiltration condition of 24 immune cells in each sample. We assorted the microenvironment of ESCC into two Infiltration groups (I and II) and built a random forest classifier model. We showed traits of gene and clinicopathology in the tumor microenvironment (TME) phenotypes systematically. Infiltration I had low infiltration of immune cells and immunomodulators but relatively higher mutation load, while Infiltration II was enriched with cytotoxic T cells and immunosuppressive cells. The upregulation of several immune cytokines like IFN-γ, TNF-β, and PD-L1 was seen in Infiltration II. The infiltration group was an independent predictor of prognosis showed by Multivariable Cox analysis (Infiltration II vs. I, hazard ratio = 2.73, 95% confidence interval = 1.08-6.91, p = 0.03). All the results can be verified in datasets from the Gene Expression Omnibus database (GEO) and our institution (n = 98). Our results demonstrate a synthesis of the infiltration pattern of the immune in ESCC. We reveal the mechanism of TME, which may contribute to the progress of immunotherapy for patients with ESCC.

Identification of Driver Genes Regulating the T-Cell-Infiltrating Levels in Hepatocellular Carcinoma

The driver genes regulating T-cell infiltration are important for understanding immune-escape mechanisms and developing more effective immunotherapy. However, researches in this field have rarely been reported in hepatocellular carcinoma (HCC). In the present study, we identified cancer driver genes triggered by copy number alterations such as CDKN2B, MYC, TSC1, TP53, and GSK3B. The T-cell infiltration levels were significantly decreased in both HCC and recurrent HCC tissues compared with the adjacent normal liver tissues. Remarkably, we identified that copy number losses of MAX and TP53 were candidate driver genes that significantly suppress T-cell infiltration in HCC. Accordingly, their downstream oncogenic pathway, cell cycle, was significantly activated in the low T-cell infiltration HCC. Moreover, the chemokine-related target genes by TP53, which played key roles in T-cell recruitment, were also downregulated in HCC with TP53/MAX deletions, suggesting that copy number losses in MAX and TP53 might result in T-cell depletion in HCC via downregulating chemokines. Clinically, the T-cell infiltration levels and chemokines activity could accurately predict the response of sorafenib, and the prognostic outcomes in HCC. In conclusion, the systematic analysis not only facilitates identification of driver genes and signaling pathways involved in T-cell infiltration and immune escape, but also gains more insights into the functional roles of T cells in HCC.

Identification of prognostic and immune-related gene signatures in the tumor microenvironment of endometrial cancer

Uterine corpus endometrial cancer (UCEC) is one of the most prevalent female malignancies in clinical practice. Due to the lack of effective biomarkers and personalized treatments, the prognosis of advanced-stage EC remains unfavorable. Modulation of the immune microenvironment is closely related to the onset and development of endometrial cancer. In the present study, we attempt to systematically analyze the characteristics of the immune microenvironment of endometrial cancer and investigate its association with clinical features by applying bioinformatics. RNA-Seq in TCGA (The Cancer Genome Atlas) and clinical follow-up information of patents were used for analysis. The Tumor Microenvironment (TME) score infiltration patterns of 523 endometrial cancer patients were evaluated using CIBERSORT. Random forest, multivariable cox analysis were used to build the TME score. Fisher's exact test was used to compare the genes that show significant differences in the frequency of mutations between groups. Two TME phenotypes were defined. There is a significant relationship between the TME score and grade. High TME score samples are highly expressed in immune activation, TGF pathway activation and immune checkpoint genes, and low TME score samples have high frequency mutations of PTEN, CSE1L and ITGB3. Therefore, describing the comprehensive landscape of UCEC's TME characteristics may help explain patients' response to immunotherapy and provide new strategies for cancer treatment.

Metabolomic Biomarkers for Detection, Prognosis and Identifying Recurrence in Endometrial Cancer

Metabolic reprogramming is increasingly recognised as one of the defining hallmarks of tumorigenesis. There is compelling evidence to suggest that endometrial cancer develops and progresses in the context of profound metabolic dysfunction. Whilst the incidence of endometrial cancer continues to rise in parallel with the global epidemic of obesity, there are, as yet, no validated biomarkers that can aid risk prediction, early detection, prognostic evaluation or surveillance. Advances in high-throughput technologies have, in recent times, shown promise for biomarker discovery based on genomic, transcriptomic, proteomic and metabolomic platforms. Metabolomics, the large-scale study of metabolites, deals with the downstream products of the other omics technologies and thus best reflects the human phenotype. This review aims to provide a summary and critical synthesis of the existing literature with the ultimate goal of identifying the most promising metabolite biomarkers that can augment current endometrial cancer diagnostic, prognostic and recurrence surveillance strategies. Identified metabolites and their biochemical pathways are discussed in the context of what we know about endometrial carcinogenesis and their potential clinical utility is evaluated. Finally, we underscore the challenges inherent in metabolomic biomarker discovery and validation and provide fresh perspectives and directions for future endometrial cancer biomarker research.

Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies

Background: Although immunotherapy with checkpoint inhibitors is changing the face of lung adenocarcinoma (LUAD) treatments, only limited patients could benefit from it. Therefore, we aimed to develop an immune-relevant-gene-based signature to predict LUAD patients' prognosis and to characterize their tumor microenvironment thus guiding therapeutic strategy.

Methods and Materials: Gene expression data of LUAD patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were systematically analyzed. We performed Cox regression and random survival forest algorithm to identify immune-relevant genes with potential prognostic value. A risk score formula was then established by integrating these selected genes and patients were classified into high- and low-risk score group. Differentially expressed genes, infiltration level of immune cells, and several immune-associated molecules were further compared across the two groups.

Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21–34.95, P < 0.001). We also found the distinct immune infiltration patterns in the two groups that several immune cells like cytotoxic cells and immune checkpoint molecules were significantly enriched and upregulated in patients from the high-risk group. These findings were further validated in two independent LUAD cohorts.

Conclusion: Our risk score formula could serve as a powerful and accurate tool for predicting survival of LUAD patients and may facilitate clinicians to choose the optimal therapeutic regimen more precisely.

Identification and validation of tumor environment phenotypes in lung adenocarcinoma by integrative genome-scale analysis

PURPOSE

To comprehensively elucidate the landscape of the tumor environment (TME) of lung adenocarcinoma (LUAD), which has a profound impact on prognosis and response to immunotherapy.

METHODS AND MATERIALS

Using a large dataset of LUAD patients from The Cancer Genome Atlas, Gene Expression Omnibus database (GEO), and our institution (n = 1411), we estimated the infiltration pattern of 24 immune cell populations in each sample and systematically correlated the TME phenotypes with genomic traits and clinicopathologic characteristics.

RESULTS

The LUAD microenvironment was classified into two distinct TME clusters (A and B), and a random forest classifier model was constructed. TMEcluster A was characterized by sparse distribution of immune cell infiltration, relatively low levels of immunomodulators and slightly higher mutation load. By contrast, enrichment of both cytotoxic T cells and immunosuppressor cells was observed in TMEcluster B. Moreover, several immune-related cytokines or markers including IFN-γ, TNF-β, and several immune checkpoint molecules such as PD-L1 were also upregulated in TMEcluster B. Multivariable Cox analysis revealed that the TMEcluster was an independent prognostic factor (TMEcluster B vs. A, hazard ratio = 0.68, 95% confidence interval = 0.50-0.91, p = 0.010). These findings were all externally validated in the data from the GEO database and our institution.

CONCLUSIONS

Our findings describe a comprehensive landscape of LUAD immune infiltration pattern and integrate several previously proposed biomarkers associated with distinct immunophenotypes, thus shedding light on how tumors interact with immune microenvironment. Our results may guide a more precise immune therapeutic strategy for LUAD patients.