Immune Modeling Analysis Reveals Immunologic Signatures Associated With Improved Outcomes in High Grade Serous Ovarian Cancer

Overview of splicing variation in ovarian cancer

Ovarian cancer remains one of the deadliest gynecological malignancies, with a persistently high mortality rate despite promising advancements in immunotherapy. Aberrant splicing events play a crucial role in cancer heterogeneity and treatment resistance. Many splicing variants, especially those involving key molecular markers such as BRCA1/2, are closely linked to disease progression and treatment outcomes. These variants and related splicing factors hold significant clinical value as diagnostic and prognostic biomarkers and therapeutic targets. This review provides a comprehensive overview of splicing variants in ovarian cancer, emphasizing their role in metastasis and resistance, and offers insights to advance biomarker development and treatment strategies.

A patient stratification signature mirrors the immunogenic potential of high grade serous ovarian cancers

BACKGROUND

While high-grade serous ovarian cancer (HGSC) has proven largely resistant to immunotherapy, sporadic incidents of partial and complete response have been observed in clinical trials and case reports. These observations suggest that a molecular basis for effective immunity may exist within a subpopulation of HGSC. Herein, we developed an algorithm, CONSTRU (Computing Prognostic Marker Dependencies by Successive Testing of Gene-Stratified Subgroups), to facilitate the discovery and characterization of molecular backgrounds of HGSC that confer resistance or susceptibility to protective anti-tumor immunity.

METHODS

We used CONSTRU to identify genes from tumor expression profiles that influence the prognostic power of an established immune cytolytic activity signature (CYTscore). From the identified genes, we developed a stratification signature (STRATsig) that partitioned patient populations into tertiles that varied markedly by CYTscore prognostic power. The tertile groups were then analyzed for distinguishing biological, clinical and immunological properties using integrative bioinformatics approaches.

RESULTS

Patient survival and molecular measures of immune suppression, evasion and dysfunction varied significantly across STRATsig tertiles in validation cohorts. Tumors comprising STRATsig tertile 1 (S-T1) showed no immune-survival benefit and displayed a hyper-immune suppressed state marked by activation of TGF-β, Wnt/β-catenin and adenosine-mediated immunosuppressive pathways, with concurrent T cell dysfunction, reduced potential for antigen presentation, and enrichment of cancer-associated fibroblasts. By contrast, S-T3 tumors exhibited diminished immunosuppressive signaling, heightened antigen presentation machinery, lowered T cell dysfunction, and a significant CYTscore-survival benefit that correlated with mutational burden in a manner consistent with anti-tumor immunoediting. These tumors also showed elevated activity of DNA damage/repair, cell cycle/proliferation and oxidative phosphorylation, and displayed greater proportions of Th1 CD4 + T cells. In these patients, but not those of S-T1 or S-T2, validated predictors of immunotherapy response were prognostic of longer patient survival. Further analyses showed that STRATsig tertile properties were not explained by known HGSC molecular or clinical subtypes or singular immune mechanisms.

CONCLUSIONS

STRATsig is a composite of parallel immunoregulatory pathways that mirrors tumor immunogenic potential. Approximately one-third of HGSC cases classify as S-T3 and display a hypo-immunosuppressed and antigenic molecular composition that favors immunologic tumor control. These patients may show heightened responsiveness to current immunotherapies.

TFF3 and PVRL2 co-targeting identified by multi-omics approach as an effective cancer immunosuppression strategy

BACKGROUND

The immunosuppressive tumour microenvironment (TME) plays a critical role in cancer progression and relapse by significantly influencing cancer pathogenesis through autocrine and paracrine signalling. Trefoil factor 3 (TFF3), a secreted protein, has been implicated in modulating the TME to promote cancer advancement. Herein, we investigated the potential association between TFF3 and key immunosuppressive TME components to distinguish a co-targetable oncotherapeutic strategy.

METHODS

The TFF3-PVRL2 association were identified and investigated by integrating multiple bioinformatic-tools. The virtual compound screening for PVRL2 inhibitors was done with EasyVS. The TFF3-PVRL2 protein-level correlation was validated by immunoblotting, and the effectiveness of co-inhibiting TFF3 and PVRL2 was assessed using siRNA and AMPC (a TFF3 inhibitor).

RESULTS

Analysis of the TISIDB database revealed a positive correlation between TFF3 and PVRL2 mRNA levels across multiple cancer types. This correlation was confirmed at the protein level through immunoblot analysis. Further evaluation using TCGA pan-cancer datasets demonstrated that TFF3 and PVRL2 interact to establish an immunosuppressive TME, promoting cancer progression in BRCA, LUAD, PAAD, PRAD, and STAD. Enrichment analyses of positively correlated genes, PPI network hub proteins, and ceRNA networks involving TFF3 and PVRL2, conducted using LinkedOmics, STRING, and Cytoscape, provided insights into their potential co-functions in cancer. A cell-based assay was performed to evaluate the combined therapeutic efficacy of targeting both, TFF3 and PVRL2 and virtual screening identified potential drugs for inhibiting PVRL2.

CONCLUSION

PVRL2 has emerged as a promising immunoinhibitory target with significant associations with TFF3 and represents a key co-targetable molecule for effective oncotherapeutic strategies.

The Nectin family ligands, PVRL2 and PVR, in cancer immunology and immunotherapy

In recent years, immunotherapy has emerged as a crucial component of cancer treatment. However, its efficacy remains limited across various cancer types, highlighting unmet needs. Poliovirus receptor-related 2 (PVRL2) and Poliovirus receptor (PVR) are members of the Nectin and Nectin-like Molecules family, known for their role as cell-cell adhesion molecules. With the development of immunotherapy, their involvement in tumor immune mechanisms as immune checkpoint factors has garnered significant attention. PVRL2 and PVR are predominantly expressed on tumor cells and antigen-presenting cells, binding to PVRIG and TIGIT, respectively, which are primarily found on T and NK cells, thereby suppressing antitumor immunity. Notably, gynecological cancers such as ovarian and endometrial cancers exhibit high expression levels of PVRL2 and PVR, with similar trends observed in various other solid and hematologic tumors. Targeting these immune checkpoint pathways offers a promising therapeutic avenue, potentially in combination with existing treatments. However, the immunomodulatory mechanism involving these bindings, known as the DNAM-1 axis, is complex, underscoring the importance of understanding it for developing novel therapies. This article comprehensively reviews the immunomodulatory mechanisms centered on PVRL2 and PVR, elucidating their implications for various cancer types.

Cyclooxygenase-2 Blockade Is Crucial to Restore Natural Killer Cell Activity before Anti-CTLA-4 Therapy against High-Grade Serous Ovarian Cancer

Chronic inflammation influences the tumor immune microenvironment (TIME) in high-grade serous ovarian cancer (HGSOC). Specifically, cyclooxygenase-2 (COX-2) overexpression promotes cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) expression. Notably, elevated COX-2 levels in the TIME have been associated with reduced response to anti-CTLA-4 immunotherapy. However, the precise impact of COX-2, encoded by PTGS2, on the immune profile remains unknown. To address this, we performed an integrated bioinformatics analysis using data from the HGSOC cohorts (TCGA-OV, n = 368; Australian cohort AOCS, n = 80; GSE26193, n = 62; and GSE30161, n = 45). Employing Gene Set Variation Analysis (GSVA), MIXTURE and Ecotyper cell deconvolution algorithms, we concluded that COX-2 was linked to immune cell ecosystems associated with shorter survival, cell dysfunction and lower NK cell effector cytotoxicity capacity. Next, we validated these results by characterizing circulating NK cells from HGSOC patients through flow cytometry and cytotoxic assays while undergoing COX-2 and CTLA-4 blockade. The blockade of COX-2 improved the cytotoxic capacity of NK cells against HGSOC cell lines. Our findings underscore the relevance of COX-2 in shaping the TIME and suggest its potential as a prognostic indicator and therapeutic target. Increased COX-2 expression may hamper the effectivity of immunotherapies that require NK cell effector function. These results provide a foundation for experimental validation and clinical trials investigating combined therapies targeting COX-2 and CTLA-4 in HGSOC.

Multiplex serum immune profiling reveals circulating LAG-3 is associated with improved patient survival in high grade serous ovarian cancer

OBJECTIVE

High grade serous ovarian cancer (HGSOC) exhibits low response rates to clinically available immunotherapies. Nevertheless, emerging research has demonstrated that certain immune factors are predictive for HGSOC patient clinical outcomes, with our own groups previous work demonstrating that intratumoral levels of the immune checkpoint receptor LAG-3 is associated with improved patient survival. In this current study we sought to uncover non-invasive circulating immune prognostic and predictive signatures in HGSOC.

METHODS

A multiplex approach was employed that examined circulating levels of immune checkpoint receptors LAG-3 and PD-1 along with 48 common cytokine and chemokines in a cohort of 75 HGSOC treatment naïve patient serum samples.

RESULTS

Elevated serum LAG-3 was significantly associated with improved progression-free survival (PFS) and overall survival (OS) in HGSOC, while circulating PD-1 levels were largely unrelated with patient clinical outcomes. Cytokine and chemokine analysis revealed lower IL-15 expression correlated with improved PFS and OS, while increased IL-1α, IL-1Ra, IL-6, IL8 and VEGF were significantly associated with preoperative CA-125 levels. ROC analysis demonstrated that serum LAG-3 levels exhibited consistent reasonable predictability as a single agent.

CONCLUSIONS

Serum-derived LAG-3 was identified out of a diverse array of chemokine and cytokines as the immune-based factor most significantly associated with improved HGSOC survival. These findings suggest that LAG-3 could be implemented as a non-invasive patient predictive marker for improved HGSOC clinical outcomes.

Integration of local and systemic immunity in ovarian cancer: Implications for immunotherapy

Cancer is a disease that induces many local and systemic changes in immunity. The difficult nature of ovarian cancer stems from the lack of characteristic symptoms that contributes to a delayed diagnosis and treatment. Despite the enormous progress in immunotherapy, its efficacy remains limited. The heterogeneity of tumors, lack of diagnostic biomarkers, and complex immune landscape are the main challenges in the treatment of ovarian cancer. Integrative approaches that combine the tumor microenvironment - local immunity - together with periphery - systemic immunity - are urgently needed to improve the understanding of the disease and the efficacy of treatment. In fact, multiparametric analyses are poised to improve our understanding of ovarian tumor immunology. We outline an integrative approach including local and systemic immunity in ovarian cancer. Understanding the nature of both localized and systemic immune responses will be crucial to boosting the efficacy of immunotherapies in ovarian cancer patients.

The Role of TIM-3 and LAG-3 in the Microenvironment and Immunotherapy of Ovarian Cancer

Ovarian cancer has the highest mortality rate among gynecologic malignancies. The main treatment options are surgical removal of the tumor and chemotherapy. Cancer treatment has been revolutionized by immunotherapy, which has developed explosively over the past two decades. Clinical anticancer strategies used in immunotherapy include therapies based on the inhibition of PD-1, PD-L1 or CTLA-4. Despite encouraging results, a large proportion of cancer patients are resistant to these therapies or eventually develop resistance. It is important to perform research that will focus on immunotherapy based on other immune checkpoint inhibitors. The aim of the review was to analyze studies considering the expression of TIM-3 and LAG-3 in the ovarian cancer microenvironment and considering immunotherapy for ovarian cancer that includes antibodies directed against TIM-3 and LAG-3. As the data showed, the expression of the described immune checkpoints was shown in different ways. Higher TIM-3 expression was associated with a more advanced tumor stage. Both TIM-3 and LAG-3 were co-expressed with PD-1 in a large proportion of studies. The effect of LAG-3 expression on progression-free survival and/or overall survival is inconclusive and certainly requires further study. Co-expression of immune checkpoints prompts combination therapies using anti-LAG-3 or anti-TIM-3. Research on immune checkpoints, especially TIM-3 and LAG-3, should be further developed.

Adaptive transcriptomic and immune infiltrate responses in the tumor immune microenvironment following neoadjuvant chemotherapy in high grade serous ovarian cancer reveal novel prognostic associations and activation of pro-tumorigenic pathways

The high rate of ovarian cancer recurrence and chemoresistance necessitates further research into how chemotherapy affects the tumor immune microenvironment (TIME). While studies have shown that immune infiltrate increases following neoadjuvant (NACT) chemotherapy, there lacks a comprehensive understanding of chemotherapy-induced effects on immunotranscriptomics and cancer-related pathways and their relationship with immune infiltrate and patient responses. In this study, we performed NanoString nCounter^® PanCancer IO360 analysis of 31 high grade serous ovarian cancer (HGSOC) patients with matched pre-treatment biopsy and post-NACT tumor. We observed increases in pro-tumorigenic and immunoregulatory pathways and immune infiltrate following NACT, with striking increases in a cohort of genes centered on the transcription factors ATF3 and EGR1. Using quantitative PCR, we analyzed several of the top upregulated genes in HGSOC cell lines, noting that two of them, ATF3 and AREG, were consistently upregulated with chemotherapy exposure and significantly increased in platinum resistant cells compared to their sensitive counterparts. Furthermore, we observed that pre-NACT immune infiltrate and pathway scores were not strikingly related to platinum free interval (PFI), but post-NACT immune infiltrate, pathway scores, and gene expression were. Finally, we found that higher levels of a cohort of proliferative and DNA damage-related genes was related to shorter PFI. This study underscores the complex alterations in the ovarian TIME following chemotherapy exposure and begins to untangle how immunologic factors are involved in mediating chemotherapy response, which will allow for the future development of novel immunologic therapies to combat chemoresistance.

Neoadjuvant Therapy Induces a Potent Immune Response to Sarcoma, Dominated by Myeloid and B Cells

PURPOSE

To characterize changes in the soft-tissue sarcoma (STS) tumor immune microenvironment induced by standard neoadjuvant therapy with the goal of informing neoadjuvant immunotherapy trial design.

EXPERIMENTAL DESIGN

Paired pre- and postneoadjuvant therapy specimens were retrospectively identified for 32 patients with STSs and analyzed by three modalities: multiplexed IHC, NanoString, and RNA sequencing with ImmunoPrism analysis.

RESULTS

All 32 patients, representing a variety of STS histologic subtypes, received neoadjuvant radiotherapy and 21 (66%) received chemotherapy prior to radiotherapy. The most prevalent immune cells in the tumor before neoadjuvant therapy were myeloid cells (45% of all immune cells) and B cells (37%), with T (13%) and natural killer (NK) cells (5%) also present. Neoadjuvant therapy significantly increased the total immune cells infiltrating the tumors across all histologic subtypes for patients receiving neoadjuvant radiotherapy with or without chemotherapy. An increase in the percentage of monocytes and macrophages, particularly M2 macrophages, B cells, and CD4+ T cells was observed postneoadjuvant therapy. Upregulation of genes and cytokines associated with antigen presentation was also observed, and a favorable pathologic response (≥90% necrosis postneoadjuvant therapy) was associated with an increase in monocytic infiltrate. Upregulation of the T-cell checkpoint TIM3 and downregulation of OX40 were observed posttreatment.

CONCLUSIONS

Standard neoadjuvant therapy induces both immunostimulatory and immunosuppressive effects within a complex sarcoma microenvironment dominated by myeloid and B cells. This work informs ongoing efforts to incorporate immune checkpoint inhibitors and novel immunotherapies into the neoadjuvant setting for STSs.

Update on lymphocyte-activation gene 3 (LAG-3) in cancers: from biological properties to clinical applications

Immunotherapy that targets checkpoints, especially programmed cell death protein 1 and programmed cell death ligand 1, has revolutionized cancer therapy regimens. The overall response rate to mono-immunotherapy, however, is limited, emphasizing the need to potentiate the efficacy of these regimens. The functions of immune cells are modulated by multiple stimulatory and inhibitory molecules, including lymphocyte activation gene 3 (LAG-3). LAG-3 is co-expressed together with other inhibitory checkpoints and plays key roles in immune suppression. Increasing evidence, particularly in the last 5 years, has shown the potential of LAG-3 blockade in anti-tumor immunity. This review provides an update on the biological properties and clinical applications of LAG-3 in cancers.

Prognostic immunologic signatures in epithelial ovarian cancer

Epithelial Ovarian Cancer (EOC) is a deadly gynecologic malignancy in which patients frequently develop recurrent disease following initial platinum-taxane chemotherapy. Analogous to many other cancer subtypes, EOC clinical trials have centered upon immunotherapeutic approaches, most notably programmed cell death 1 (PD-1) inhibitors. While response rates to these immunotherapies in EOC patients have been low, evidence suggests that ovarian tumors are immunogenic and that immune-related genomic profiles can serve as prognostic markers. This review will discuss recent advances in the development of immune-based prognostic signatures in EOC that predict patient clinical outcomes, as well as emphasize specific research areas that need to be addressed to drive this field forward.

Comprehensive analysis of prognosis-related alternative splicing events in ovarian cancer

Ovarian cancer (OV) is characterized by high incidence and poor prognosis. Increasing evidence indicates that aberrant alternative splicing (AS) events are associated with the pathogenesis of cancer. We examined prognosis-related alternative splicing events and constructed a clinically applicable model to predict patients’ outcomes. Public database including The Cancer Genome Atlas (TCGA), TCGA SpliceSeq, and the Genomics of Drug Sensitivity in Cancer databases were used to detect the AS expression, immune cell infiltration and IC50. The prognosis-related AS model was constructed and validated by using Cox regression, LASSO regression, C-index, calibration plots, and ROC curves. A total of eight AS events (including FLT3LG|50942|AP) were selected to establish the prognosis-related AS model. Compared with high-risk group, low-risk group had a better outcome (P = 1.794e-06), was more sensitive to paclitaxel (P = 0.022), and higher proportions of plasma cells. We explored the upstream regulatory mechanisms of prognosis-related AS and found that two splicing factor and 156 tag single nucleotide polymorphisms may be involved in the regulation of prognosis-related AS. In order to assess patient prognosis more comprehensively, we constructed a clinically applicable model combining risk score and clinicopathological features, and the 1 -, and 3-year AUCs of the clinically applicable model were 0.812, and 0.726, which were 7.5% and 3.3% higher than that of the risk score. We constructed a prognostic signature for OV patients and comprehensively analysed the regulatory characteristics of the prognostic AS events in OV.

CD4+ T cell and M2 macrophage infiltration predict dedifferentiated liposarcoma patient outcomes

Background

Dedifferentiated liposarcoma (DDLPS) is one of the most common soft tissue sarcoma subtypes and is devastating in the advanced/metastatic stage. Despite the observation of clinical responses to PD-1 inhibitors, little is known about the immune microenvironment in relation to patient prognosis.

Methods

We performed a retrospective study of 61 patients with DDLPS. We completed deep sequencing of the T-cell receptor (TCR) β-chain and RNA sequencing for predictive modeling, evaluating both immune markers and tumor escape genes. Hierarchical clustering and recursive partitioning were employed to elucidate relationships of cellular infiltrates within the tumor microenvironment, while an immune score for single markers was created as a predictive tool.

Results

Although many DDLPS samples had low TCR clonality, high TCR clonality combined with low T-cell fraction predicted lower 3-year overall survival (p=0.05). Higher levels of CD14+ monocytes (p=0.02) inversely correlated with 3-year recurrence-free survival (RFS), while CD4+ T-cell infiltration (p=0.05) was associated with a higher RFS. Genes associated with longer RFS included PD-1 (p=0.003), ICOS (p=0.006), BTLA (p=0.033), and CTLA4 (p=0.02). In a composite immune score, CD4+ T cells had the strongest positive predictive value, while CD14+ monocytes and M2 macrophages had the strongest negative predictive values.

Conclusions

Immune cell infiltration predicts clinical outcome in DDLPS, with CD4+ cells associated with better outcomes; CD14+ cells and M2 macrophages are associated with worse outcomes. Future checkpoint inhibitor studies in DDLPS should incorporate immunosequencing and gene expression profiling techniques that can generate immune landscape profiles.