Prognostic implications of tumor-infiltrating T cells in early-stage endometrial cancer

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.

Prediction of Deep Myometrial Infiltration, Clinical Risk Category, Histological Type, and Lymphovascular Space Invasion in Women with Endometrial Cancer Based on Clinical and T2-Weighted MRI Radiomic Features

PURPOSE

To predict deep myometrial infiltration (DMI), clinical risk category, histological type, and lymphovascular space invasion (LVSI) in women with endometrial cancer using machine learning classification methods based on clinical and image signatures from T2-weighted MR images.

METHODS

A training dataset containing 413 patients and an independent testing dataset consisting of 82 cases were employed in this retrospective study. Manual segmentation of the whole tumor volume on sagittal T2-weighted MRI was performed. Clinical and radiomic features were extracted to predict: (i) DMI of endometrial cancer patients, (ii) endometrial cancer clinical high-risk level, (iii) histological subtype of tumor, and (iv) presence of LVSI. A classification model with different automatically selected hyperparameter values was created. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, F1 score, average recall, and average precision were calculated to evaluate different models.

RESULTS

Based on the independent external testing dataset, the AUCs for DMI, high-risk endometrial cancer, endometrial histological type, and LVSI classification were 0.79, 0.82, 0.91, and 0.85, respectively. The corresponding 95% confidence intervals (CI) of the AUCs were [0.69, 0.89], [0.75, 0.91], [0.83, 0.97], and [0.77, 0.93], respectively.

CONCLUSION

It is possible to classify endometrial cancer DMI, risk, histology type, and LVSI using different machine learning methods.

Spatial distribution of CD3- and CD8-positive lymphocytes as pretest for POLE wild-type in molecular subgroups of endometrial carcinoma

Introduction

Over the years, the molecular classification of endometrial carcinoma has evolved significantly. Both POLEmut and MMRdef cases share tumor biological similarities like high tumor mutational burden and induce strong lymphatic reactions. While therefore use case scenarios for pretesting with tumor-infiltrating lymphocytes to replace molecular analysis did not show promising results, such testing may be warranted in cases where an inverse prediction, such as that of POLEwt, is being considered. For that reason we used a spatial digital pathology method to quantitatively examine CD3⁺ and CD8⁺ immune infiltrates in comparison to conventional histopathological parameters, prognostics and as potential pretest before molecular analysis.

Methods

We applied a four-color multiplex immunofluorescence assay for pan-cytokeratin, CD3, CD8, and DAPI on 252 endometrial carcinomas as testing and compared it to further 213 cases as validation cohort from a similar multiplexing assay. We quantitatively assessed immune infiltrates in microscopic distances within the carcinoma, in a close distance of 50 microns, and in more distant areas.

Results

Regarding prognostics, high CD3⁺ and CD8⁺ densities in intra-tumoral and close subregions pointed toward a favorable outcome. However, TCGA subtyping outperforms prognostication of CD3 and CD8 based parameters. Different CD3⁺ and CD8⁺ densities were significantly associated with the TCGA subgroups, but not consistently for histopathological parameter. In the testing cohort, intra-tumoral densities of less than 50 intra-tumoral CD8⁺ cells/mm² were the most suitable parameter to assume a POLEwt, irrespective of an MMRdef, NSMP or p53abn background. An application to the validation cohort corroborates these findings with an overall sensitivity of 95.5%.

Discussion

Molecular confirmation of POLEmut cases remains the gold standard. Even if CD3⁺ and CD8⁺ cell densities appeared less prognostic than TCGA, low intra-tumoral CD8⁺ values predict a POLE wild-type at substantial percentage rates, but not vice versa. This inverse correlation might be useful to increase pretest probabilities in consecutive POLE testing. Molecular subtyping is currently not conducted in one-third of cases deemed low-risk based on conventional clinical and histopathological parameters. However, this percentage could potentially be increased to two-thirds by excluding sequencing of predicted POLE wild-type cases, which could be determined through precise quantification of intra-tumoral CD8⁺ cells.

Biomarkers of tumor-reactive CD4+ and CD8+ TILs associate with improved prognosis in endometrial cancer

BACKGROUND

Despite the growing interest in immunotherapeutic interventions for endometrial cancer (EC), the prevalence, phenotype, specificity and prognostic value of tumor infiltrating lymphocytes (TILs) in this tumor type remains unclear.

METHODS

To better understand the role of TILs in EC, we analyzed the phenotypic traits of CD8⁺ and CD4⁺ EC^-resident T cells from 47 primary tumors by high-dimensional flow cytometry. In addition, CD8⁺ and CD4⁺ TIL subpopulations were isolated based on the differential expression of programmed cell death protein-1 (PD-1) (negative, dim and high) and CD39 (positive or negative) by fluorescence activated cell sorting (FACS), expanded in vitro, and screened for autologous tumor recognition. We further investigated whether phenotypic markers preferentially expressed on CD8⁺ and CD4⁺ tumor-reactive TIL subsets were associated with the four distinct molecular subtypes of EC, tumor mutational burden and patient survival.

RESULTS

We found that CD8⁺TILs expressing high levels of PD-1 (PD-1hi) co-expressed CD39, TIM-3, HLA-DR and CXCL13, as compared with TILs lacking or displaying intermediate levels of PD-1 expression (PD-1^- and PD-1^dim, respectively). Autologous tumor reactivity of sorted and in vitro expanded CD8+ TILs demonstrated that the CD8⁺PD-1^dimCD39⁺ and PD-1^hiCD39⁺ T cell subsets both contained tumor-reactive TILs and that a higher level of PD-1 expression was associated with increased CD39 and a superior frequency of tumor reactivity. With respect to CD4⁺ T conventional (Tconv) TILs, co-expression of inhibitory and activation markers was more apparent on PD-1^hi compared with PD-1^- or PD-1^dim T cells, and in fact, it was the CD4⁺PD-1^hi subpopulation that accumulated the antitumor T cells irrespective of CD39 expression. Most importantly, detection of CD8⁺PD-1^hiCD39+ and CD4⁺PD-1^hi tumor-reactive T-cell subsets, but also markers specifically expressed by these subpopulations of TILs, that is, PD-1^hi, CD39, CXCL13 and CD103 by CD8⁺ TILs and PD-1^hi and CXCL13 by CD4⁺ Tconv TILs, correlated with prolonged survival of patients with EC.

CONCLUSIONS

Our results demonstrate that EC are frequently infiltrated by tumor-reactive TILs, and that expression of PD-1^hi and CD39 or PD-1^hi can be used to select and expand CD8⁺ and CD4⁺ tumor-reactive TILs, respectively. In addition, biomarkers preferentially expressed on tumor-reactive TILs, rather than the frequency of CD3⁺, CD8⁺ and CD4⁺ lymphocytes, hold prognostic value suggesting their protective role in antitumor immunity.

Tumor immune microenvironment in endometrial cancer of different molecular subtypes: evidence from a retrospective observational study

Objective

Tumor immune microenvironmental features may predict survival and guide treatment. This study aimed to comprehensively decipher the immunological features of different molecular subtypes of endometrial cancer.

Methods

In this retrospective study, 26 patients with primary endometrial cancer and four with recurrent disease treated in our center from December 2018 to November 2021 were included. Next-generation sequencing was performed on tumor samples. Patients were classified into four subtypes, including POLE mutant, microsatellite instability high (MSI-H), no specific molecular profile (NSMP) and TP53 mutant subtypes. Tumor-infiltrating immune cells were quantified using multiplex immunofluorescence assays.

Results

Of the 26 primary endometrial cancer cases, three were POLE mutant, six were MSI-H, eight were NSMP and nine were TP53 mutant. Of the four recurrent cases, two belonged to the NSMP subtype and two belonged to the TP53 mutant subtype. The tumor mutation burden (TMB) levels of POLE mutant and MSI-H cases were significantly higher than that of the other two subtypes (p< 0.001). We combined POLE mutant and MSI-H subtypes into the TMB high (TMB-H) subtype. The TMB-H subtype showed a high degree of infiltration of CD8⁺ T cells. In the NSMP subtype, the overall degree of intra-tumoral infiltrating immune cells was low. In the TP53 mutant subtype, the densities of both PD-L1⁺ macrophages (p = 0.047) and PD-1⁺ T cells (p = 0.034) in tumor parenchyma were the highest among the four subtypes.

Conclusion

Endometrial cancer of TMB-H, NSMP and TP53 mutant subtypes displayed phenotypes of normal immune response, absence of immune infiltration, and suppressed immune response, respectively. These features may provide mechanistic explanations for the differences in patients' prognosis and efficacy of immune checkpoint blockade therapies among different endometrial cancer subtypes.

Importance of the endometrial immune environment in endometrial cancer and associated therapies

Endometrial cancer is rising in prevalence. The standard treatment modality of hysterectomy is becoming increasingly inadequate due primarily to the direct link between endometrial cancer and high BMI which increases surgical risks. This is an immunogenic cancer, with unique molecular subtypes associated with differential immune infiltration. Despite the immunogenicity of endometrial cancer, there is limited pre-clinical and clinical evidence of the function of immune cells in both the normal and cancerous endometrium. Immune checkpoint inhibitors for endometrial cancer are the most well studied type of immune therapy but these are not currently used as standard-of-care and importantly, they represent only one method of immune manipulation. There is limited evidence regarding the use of other immunotherapies as surgical adjuvants or alternatives. Levonorgestrel-loaded intra-uterine systems can also be effective for early-stage disease, but with varying success. There is currently no known reason as to what predisposes some patients to respond while others do not. As hormones can directly influence immune cell function, it is worth investigating the immune compartment in this context. This review assesses the immunological components of the endometrium and describes how the immune microenvironment changes with hormones, obesity, and in progression to malignancy. It also describes the importance of investigating novel pathways for immunotherapy.

Identifying immune cells-related phenotype to predict immunotherapy and clinical outcome in gastric cancer

Background

The tumor microenvironment is mainly composed of tumor-infiltrating immune cells (TIICs), fibroblast, extracellular matrix, and secreted factors. TIICs are often associated with sensitivity to immunotherapy and the prognosis of multiple cancers, yet the predictive role of individual cells on tumor prognosis is limited.

Methods

Based on single-sample gene set enrichment analysis, we combined three Gene Expression Omnibus (GEO) cohorts to build a TIIC model for risk stratification and prognosis prediction. The performance of the TIIC model was validated using our clinical cohort and the TCGA cohort. To assess the predictive power of the TIIC model for immunotherapy, we plotted the receiver operating characteristic curve with the IMvigor210 and GSE135222 cohorts.

Results

Chemokines, tumor-infiltrating immune cells, and immunomodulators differed between the two TIIC groups. The TIIC model was vital for predicting the outcome of immunotherapy. In our clinical samples, we verified that the expression levels of PD-1 and PD-L1 were higher in the low TIIC score group than in the high TIIC score group, both in the tumor and stroma.

Conclusions

Collectively, the TIIC model could provide a novel idea for immune cell targeting strategies in gastric cancer and predict the survival outcome of patients.

Clinical Value Analysis of Combined Vaginal Ultrasound, Magnetic Resonance Dispersion Weighted Imaging, and Multilayer Spiral CT in the Diagnosis of Endometrial Cancer Using Deep VGG-16 AdaBoost Hybrid Classifier

Endometrial carcinoma is one of the most common disorders of the female reproductive system. Every year, around 76,000 women die from endometrial cancer around the world. Endometrial cancer is a significant factor in women’s health, particularly in industrialized nations, where the prevalence of this tumor type is the greatest. It is an important concern in women’s health because of disease mortality and the rising number of new diagnoses. The aim of the study was to investigate the clinical value of combined transvaginal ultrasound, magnetic resonance dispersion weighted imaging, and multilayer spiral computed tomography (CT) in the diagnosis of early-stage endometrial cancer. Initially, the dataset is collected that consisted of a total of 100 cases and split into the control group and experimental group of 50 cases in each group. The control group is diagnosed using conventional Doppler ultrasound diagnostic machine. The experimental group is diagnosed with combined ultrasound method. The ultrasound images thus obtained are preprocessed using the speckle-free adaptive wiener filter. The preprocessed images are segmented using the fuzzy clustering segmentation method. The features are extracted by the independent component analysis (ICA) method. We have proposed the deep VGG-16 AdaBoost hybrid classifier for classifying the normal and abnormal images. The clinical value of the diagnosis is analyzed using the parameters like diagnostic accuracy, specificity, sensitivity, and kappa coefficient. It is observed that the clinical value is better for the experimental group than the control group.

Gel-Based Proteomic Identification of Suprabasin as a Potential New Candidate Biomarker in Endometrial Cancer

Endometrial cancer (EC) is the most frequent gynaecologic cancer in postmenopausal women. We used 2D-DIGE and mass spectrometry to identify candidate biomarkers in endometrial cancer, analysing the serum protein contents of 10 patients versus 10 control subjects. Using gel-based proteomics, we identified 24 candidate biomarkers, considering only spots with a fold change in volume percentage ≥ 1.5 or intensity change ≤ 0.6, which were significantly different between cases and controls (p < 0.05). We used Western blotting analysis both in the serum and tissue of 43 patients for data validation. Among the identified proteins, we selected Suprabasin (SBSN), an oncogene previously associated with poor prognosis in different cancers. SBSN principal isoforms were subjected to Western blotting analysis in serum and surgery-excised tissue: both isoforms were downregulated in the tissue. However, in serum, isoform 1 was upregulated, while isoform 2 was downregulated. Data-mining on the TCGA and GTEx projects, using the GEPIA2.0 interface, indicated a diminished SBSN expression in the Uterine Corpus Endometrial Cancer (UCEC) database compared to normal tissue, confirming proteomic results. These results suggest that SBSN, specifically isoform 2, in tissue or serum, could be a potential novel biomarker in endometrial cancer.