Tumor-Infiltrating Lymphocytes (TILs) in Epithelial Ovarian Cancer: Heterogeneity, Prognostic Impact, and Relationship with Immune Checkpoints

Artificial Intelligence-Based Histopathological Subtyping of High-Grade Serous Ovarian Cancer

Four subtypes of ovarian high-grade serous carcinoma (HGSC) have previously been identified, each with different prognoses and drug sensitivities. However, the accuracy of classification depended on the assessor's experience. This study aimed to develop a universal algorithm for HGSC-subtype classification using deep learning techniques. An artificial intelligence (AI)-based classification algorithm, which replicates the consensus diagnosis of pathologists, was formulated to analyze the morphological patterns and tumor-infiltrating lymphocyte counts for each tile extracted from whole slide images of ovarian HGSC available in The Cancer Genome Atlas (TCGA) data set. The accuracy of the algorithm was determined using the validation set from the Japanese Gynecologic Oncology Group 3022A1 (JGOG3022A1) and Kindai and Kyoto University (Kindai/Kyoto) cohorts. The algorithm classified the four HGSC-subtypes with mean accuracies of 0.933, 0.910, and 0.862 for the TCGA, JGOG3022A1, and Kindai/Kyoto cohorts, respectively. To compare mesenchymal transition (MT) with non-MT groups, overall survival analysis was performed in the TCGA data set. The AI-based prediction of HGSC-subtype classification in TCGA cases showed that the MT group had a worse prognosis than the non-MT group (P = 0.017). Furthermore, Cox proportional hazard regression analysis identified AI-based MT subtype classification prediction as a contributing factor along with residual disease after surgery, stage, and age. In conclusion, a robust AI-based HGSC-subtype classification algorithm was established using virtual slides of ovarian HGSC.

Immunotherapy and the ovarian cancer microenvironment: Exploring potential strategies for enhanced treatment efficacy

Despite progress in cancer immunotherapy, ovarian cancer (OC) prognosis continues to be disappointing. Recent studies have shed light on how not just tumour cells, but also the complex tumour microenvironment, contribute to this unfavourable outcome of OC immunotherapy. The complexities of the immune microenvironment categorize OC as a 'cold tumour'. Nonetheless, understanding the precise mechanisms through which the microenvironment influences the effectiveness of OC immunotherapy remains an ongoing scientific endeavour. This review primarily aims to dissect the inherent characteristics and behaviours of diverse cells within the immune microenvironment, along with an exploration into its reprogramming and metabolic changes. It is expected that these insights will elucidate the operational dynamics of the immune microenvironment in OC and lay a theoretical groundwork for improving the efficacy of immunotherapy in OC management.

Role of TIM-3 in ovarian cancer: the forsaken cop or a new noble

T cell immunoglobulin and mucin domain-3 (TIM-3), a crucial immune checkpoint following PD1 and CTLA4, is widely found in several immune cells. Nonetheless, its performance in recent clinical trials appears disappointing. Ovarian cancer (OC), a malignant tumor with a high mortality rate in gynecology, faces significant hurdles in immunotherapy. The broad presence of TIM-3 offers a new opportunity for immunotherapy in OC. This study reviews the role of TIM-3 in OC and assesses its potential as a target for immunotherapy. The regulatory effects of TIM-3 on the immune microenvironment in OC are discussed, with a focus on preclinical studies that demonstrate TIM-3's modulation of various immune cells in OC. Additionally, the potential therapeutic advantages and challenges of targeting TIM-3 in OC are examined.

A Deep Learning-Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study developed two convolutional neural network models to detect TILs and to determine their spatial location in whole slide images, and established a spatial assessment pipeline to objectively quantify intraepithelial and stromal TILs in patients with high-grade serous ovarian carcinoma. The predictions of the established models showed a significant positive correlation with the number of CD8+ T cells and immune gene expressions. Patients with a higher density of intraepithelial TILs had a significantly prolonged overall survival and progression-free survival in multiple cohorts. On the basis of the density of intraepithelial and stromal TILs, patients were classified into three immunophenotypes: immune inflamed, excluded, and desert. The immune-desert subgroup showed the worst prognosis. Gene expression analysis showed that the immune-desert subgroup had lower immune cytolytic activity and T-cell-inflamed gene-expression profile scores, whereas the immune-excluded subgroup had higher expression of interferon-γ and programmed death 1 receptor signaling pathway. The established evaluation method provided detailed and comprehensive quantification of intraepithelial and stromal TILs throughout hematoxylin and eosin-stained slides. It has potential for clinical application for personalized treatment of patients with ovarian cancer.

Prognostic significance of peripheral and tumor-infiltrating lymphocytes in newly diagnosed stage III/IV non-small-cell lung cancer

Background and aim

Lymphocytes are effector cells that fight cancer by killing tumor cells. Here, we aim to explore the prognostic significance of both peripheral and tumor-infiltrating lymphocytes (TILs) in newly diagnosed stage III/IV non-small-cell lung cancer (NSCLC).

Materials and methods

In total, 105 cases of newly diagnosed stage III/IV NSCLC from July 2017 to October 2022 at the Tianjin Beichen Hospital were retrospectively investigated. Peripheral blood samples at the time of diagnosis and tumor tissue slices from these patients were collected. General peripheral blood cell composition and TILs were measured and analyzed via an automatic blood analyzer and immunofluorescence staining analysis. The overall survival (OS) time of all patients was also obtained and analyzed.

Results

The median overall survival (mOS) of all patients is 12 months. The 1-, 2-, and 3-year overall survival rates were 60.5, 28.4, and 18.6%, respectively. Peripheral lymphocyte and neutrophil percentages, serum C-reactive protein (CRP) expression, tumor size, and tumor pathology are the prognostic factors of OS for newly diagnosed stage III/IV NSCLC patients. Moreover, patients with high tumor CD4+ and CD8+ T cell infiltration survived significantly longer compared to patients with low tumor CD4+ and CD8+ T cell infiltration (p < 0.0001 and p = 0.011, respectively). Compared to low tumor CD33+ cell infiltration, high tumor CD33+ cell infiltration was associated with worse OS (p = 0.018). High tumor CD8+ T cell infiltration was associated with lower peripheral lymphocyte number, lower serum CRP expression, smaller tumor size, and better tumor pathology (p = 0.012, p = 0.040, p = 0.012, and p = 0.029, respectively).

Conclusion

Increased numbers of peripheral lymphocytes, CD33+ cells, CD4+ TILs, and CD8+ TILs were significantly associated with OS in newly diagnosed stage III/IV NSCLC patients, which were positively associated with several basic clinical factors.

Tumor cell cytoplasmic metallothionein expression associates with differential tumor immunogenicity and prognostic outcome in high-grade serous ovarian carcinoma

Background

The underlying mechanism of high T-cell presence as a favorable prognostic factor in high-grade serous ovarian carcinoma (HGSOC) is not yet understood. In addition to immune cells, various cofactors are essential for immune processes. One of those are metallothioneins (MTs), metal-binding proteins comprising various isoforms. MTs play a role in tumor development and drug resistance. Moreover, MTs influence inflammatory processes by regulating zinc homeostasis. In particular, T-cell function and polarization are particularly susceptible to changes in zinc status. The aim of the present study was to investigate a possible role of MT-mediated immune response and its association with prognostic outcome in ovarian cancer.

Methods

A retrospective study was conducted on a clinically well-characterized cohort of 24 patients with HGSOC treated at the University Hospital of Essen. Gene expression patterns for anti-cancer immunogenicity-related targets were performed using the NanoString nCounter platform for digital gene expression analysis with the appurtenant PanCancer Immune Profiling panel, consisting of 770 targets and 30 reference genes. Tumor-associated immunohistochemical MT protein expression was evaluated using a semi-quantitative four-tier Immunohistochemistry (IHC) scoring.

Results

MT immunoexpression was detected in 43% (10/23) of all HGSOC samples. MT immunoexpression levels showed a significant association to survival, leading to prolonged progression-free and overall survival in positively stained tumors. Furthermore, T-cell receptor signaling gene signature showed a strong activation in MT-positive tumors. Activated downstream signaling cascades resulting in elevated interferon-gamma expression with a shift in the balance between T helper cells (TH1 and TH2) could be observed in the MT-positive subgroup. In addition, a higher expression pattern of perforin and several granzymes could be detected, overall suggestive of acute, targeted anti-cancer immune response in MT-positive samples.

Conclusion

This is the first study combining broad, digital mRNA screening of anti-tumor immune response-associated genes and their relation to MT-I/II in ovarian cancer. MT overexpression is associated with molecular characteristics of an anti-cancer immune response and is a strong prognostic marker in ovarian HGSOC. The observed immune cell activation associated with tumor MT expression comprises but is not limited to T cells and natural killer cells.

Evaluation of Immune Infiltrates in Ovarian Endometriosis and Endometriosis-Associated Ovarian Cancer: Relationship with Histological and Clinical Features

BACKGROUND

the association between ovarian endometriosis (OE) and endometriosis-associated ovarian cancer (EAOC) is extensively documented, and misfunction of the immune system might be involved. The primary objective of this study was to identify and compare the spatial distribution of tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs) in OE and EAOC. Secondary objectives included the analysis of the relationship between immunosuppressive populations and T-cell exhaustion markers in both groups.

METHODS

TILs (CD3, CD4, and CD8) and macrophages (CD163) were assessed by immunochemistry. Exhaustion markers (PD-1, TIM3, CD39, and FOXP3) and their relationship with tumour-associated macrophages (CD163) were assessed by immunofluorescence on paraffin-embedded samples from n = 43 OE and n = 54 EAOC patients.

RESULTS

we observed a predominantly intraepithelial CD3+ distribution in OE but both an intraepithelial and stromal pattern in EAOC (p < 0.001). TILs were more abundant in OE (p < 0.001), but higher TILs significantly correlated with a longer overall survival and disease-free survival in EAOC (p < 0.05). CD39 and FOXP3 significantly correlated with each other and CD163 (p < 0.05) at the epithelial level in moderate/intense CD4 EAOC, whereas in moderate/intense CD8+, PD-1+ and TIM3+ significantly correlated (p = 0.009). Finally, T-cell exhaustion markers FOXP3-CD39 were decreased and PD-1-TIM3 were significantly increased in EAOC (p < 0.05).

CONCLUSIONS

the dysregulation of TILs, TAMs, and T-cell exhaustion might play a role in the malignization of OE to EAOC.

Stromal Tumor-Infiltrating Lymphocytes Associated with Immunohistopathology and Molecular Subtypes of Breast Cancer in Vietnam

OBJECTIVE

Breast cancer is a heterogeneous disease with varied symptoms and pathogenesis, as well as variable prognosis and therapeutic outcomes. Stromal tumor-infiltrating lymphocytes, one of the tumor microenvironment factors, has been recognized as an important immunological biomarker that reflected the antitumor immune response in breast cancer.

METHODS

We analyzed 207 invasive breast cancer patients who had lumpectomy or mastectomy and have not received any pre-operative treatment. Clinicopathological characteristics, immunohistochemistry characteristics, molecular subtypes classification and stromal TILs evaluation were investigated.

RESULT

Stromal TILs correlated with well-established prognostic markers. Tumor grade showed significantly higher sTILs percentages in high-grade tumors than in low-grade tumors (p<0.001). There was a statistically significant association between intermediate and high levels of sTILs and a high Ki-67 index (p< 0.001). ER/PR negative was significantly related to high sTILs. Mean sTILs score was significantly higher in TNBC (40.1±31.6%) compared to others, statistically significant (p<0.001). In HER2-negative breast cancer, sTILs were significantly associated with histologic grade, ER status, PR status, and Ki67 index.

CONCLUSION

sTILs played an important role, associated with unfavorable factors in breast cancer. Our findings support the use of stromal sTILs to identify a more aggressive phenotype of tumors.

Current Understanding on Why Ovarian Cancer Is Resistant to Immune Checkpoint Inhibitors

The standard treatment of ovarian cancer (OC) patients, including debulking surgery and first-line chemotherapy, is unsatisfactory because of recurrent episodes in the majority (~70%) of patients with advanced OC. Clinical trials have shown only a modest (10-15%) response of OC individuals to treatment based on immune checkpoint inhibitors (ICIs). The resistance of OC to therapy is caused by various factors, including OC heterogeneity, low density of tumor-infiltrating lymphocytes (TILs), non-cellular and cellular interactions in the tumor microenvironment (TME), as well as a network of microRNA regulating immune checkpoint pathways. Moreover, ICIs are the most efficient in tumors that are marked by high microsatellite instability and high tumor mutation burden, which is rare among OC patients. The great challenge in ICI implementation is connected with distinguishing hyper-, pseudo-, and real progression of the disease. The understanding of the immunological, molecular, and genetic mechanisms of OC resistance is crucial to selecting the group of OC individuals in whom personalized treatment would be beneficial. In this review, we summarize current knowledge about the selected factors inducing OC resistance and discuss the future directions of ICI-based immunotherapy development for OC patients.

Immune Checkpoint Inhibitors in Cancer Therapy-How Can We Improve Clinical Benefits?

Immune checkpoint inhibitors (ICIs) are in the spotlight of cancer treatment by increasing the probability for long-term survival in patients with metastatic disease and by considerably prolonging progression-free survival in patients at early disease stages [...].