TIM3 Checkpoint Inhibition Fails to Prolong Survival in Ovarian Cancer-Bearing Mice.

Immune checkpoint inhibitor (ICI) therapy has proven revolutionary in the treatment of some cancers. However, ovarian cancer remains unresponsive to current leading ICIs, such as anti-PD1 or anti-PD-L1. In this article, we explored the potential of an upcoming checkpoint molecule, T-cell immunoglobulin and mucin domain 3 (TIM3), for the treatment of ovarian cancer using a syngeneic orthotopic mouse model (ID8-fLuc). Besides therapeutic efficacy, we focused on exploring immune changes in tumor tissue and peritoneal fluid. Our results showed no improvement in survival in ovarian cancer-bearing mice after anti-TIM3 treatment when used as monotherapy nor when combined with anti-PD1 or standard-of-care chemotherapy (carboplatin/paclitaxel). This was reflected in the unaltered immune infiltration in treated mice compared to control mice. Altering the order of drug administration within the combination treatment altered the survival results, but did not result in a survival benefit over chemotherapy alone. These findings highlight the need for further preclinical studies to find beneficial treatment schemes and combination therapies for ovarian cancer.

Toward more accurate preclinical glioblastoma modeling: Reverse translation of clinical standard of care in a glioblastoma mouse model.

Glioblastoma (GBM) is the deadliest of all brain cancers. GBM patients receive an intensive treatment schedule consisting of surgery, radiotherapy and chemotherapy, which only modestly extends patient survival. Therefore, preclinical studies are testing novel experimental treatments. In such preclinical studies, these treatments are administered as monotherapy in the majority of cases; conversely, in patients the new treatments are always combined with the standard of care. Most likely, this difference contributes to the failure of clinical trials despite the successes of the preclinical studies. In this methodological study, we show in detail how to implement the full clinical standard of care in preclinical GBM research. Systematically testing new treatments, including cellular immunotherapies, in combination with the clinical standard of care can result in a better translation of preclinical results to the clinic and ultimately increase patient survival.

Management of Uterine Fibroids and Sarcomas: The Palermo Position Paper.

BACKGROUND: Uterine fibroids are benign monoclonal tumors originating from the smooth muscle cells of the myometrium, constituting the most prevalent pathology within the female genital tract. Uterine sarcomas, although rare, still represent a diagnostic challenge and should be managed in centers with adequate expertise in gynecological oncology. OBJECTIVES: This article is aimed to summarize and discuss cutting-edge elements about the diagnosis and management of uterine fibroids and sarcomas. METHODS: This paper is a report of the lectures presented in an expert meeting about uterine fibroids and sarcomas held in Palermo in February 2023. OUTCOME: Overall, the combination of novel molecular pathways may help combine biomarkers and expert ultrasound for the differential diagnosis of uterine fibroids and sarcomas. On the one hand, molecular and cellular maps of uterine fibroids and matched myometrium may enhance our understanding of tumor development compared to histologic analysis and whole tissue transcriptomics, and support the development of minimally invasive treatment strategies; on the other hand, ultrasound imaging allows in most of the cases a proper mapping the fibroids and to differentiate between benign and malignant lesions, which need appropriate management. CONCLUSIONS AND OUTLOOK: The choice of uterine fibroid management, including pharmacological approaches, surgical treatment, or other strategies, such as high-intensity focused ultrasound (HIFU), should be carefully considered, taking into account the characteristics of the patient and reproductive prognosis.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery.

BACKGROUND: Several diagnostic prediction models to help clinicians discriminate between benign and malignant adnexal masses are available. This study is a head-to-head comparison of the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with that of the Risk of Ovarian Malignancy Algorithm (ROMA). METHODS: This is a retrospective study based on prospectively included consecutive women with an adnexal tumour scheduled for surgery at five oncology centres and one non-oncology centre in four countries between 2015 and 2019. The reference standard was histology. Model performance for ADNEX and ROMA was evaluated regarding discrimination, calibration, and clinical utility. RESULTS: The primary analysis included 894 patients, of whom 434 (49%) had a malignant tumour. The area under the receiver operating characteristic curve (AUC) was 0.92 (95% CI 0.88-0.95) for ADNEX with CA125, 0.90 (0.84-0.94) for ADNEX without CA125, and 0.85 (0.80-0.89) for ROMA. ROMA, and to a lesser extent ADNEX, underestimated the risk of malignancy. Clinical utility was highest for ADNEX. ROMA had no clinical utility at decision thresholds <27%. CONCLUSIONS: ADNEX had better ability to discriminate between benign and malignant adnexal tumours and higher clinical utility than ROMA. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov NCT01698632 and NCT02847832.

Preclinical studies performed in appropriate models could help identify optimal timing of combined chemotherapy and immunotherapy.

Immune checkpoint inhibitors (ICI) have been revolutionary in the field of cancer therapy. However, their success is limited to specific indications and cancer types. Recently, the combination treatment of ICI and chemotherapy has gained more attention to overcome this limitation. Unfortunately, many clinical trials testing these combinations have provided limited success. This can partly be attributed to an inadequate choice of preclinical models and the lack of scientific rationale to select the most effective immune-oncological combination. In this review, we have analyzed the existing preclinical evidence on this topic, which is only limitedly available. Furthermore, this preclinical data indicates that besides the selection of a specific drug and dose, also the sequence or order of the combination treatment influences the study outcome. Therefore, we conclude that the success of clinical combination trials could be enhanced by improving the preclinical set up, in order to identify the optimal treatment combination and schedule to enhance the anti-tumor immunity.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Drug Repurposing for Targeting Myeloid-Derived Suppressor-Cell-Generated Immunosuppression in Ovarian Cancer: A Literature Review of Potential Candidates.

The lethality of patients with ovarian cancer (OC) remains high. Current treatment strategies often do not lead to the desired outcome due to the development of therapy resistance, resulting in high relapse rates. Additionally, clinical trials testing immunotherapy against OC have failed to reach significant results to date. The OC tumor microenvironment and specifically myeloid-derived suppressor cells (MDSC) are known to generate immunosuppression and inhibit the anti-tumor immune response following immunotherapy treatment. Our review aims to characterize potential candidate treatments to target MDSC in OC through drug-repurposing. A literature search identified repurposable compounds with evidence of their suppressing the effect of MDSC. A total of seventeen compounds were withheld, of which four were considered the most promising. Lurbinectedin, metformin, celecoxib, and 5-azacytidine have reported preclinical effects on MDSC and clinical evidence in OC. They have all been approved for a different indication, characterizing them as the most promising candidates for repurposing to treat patients with OC.

Trial watch: chemotherapy-induced immunogenic cell death in oncology.

Immunogenic cell death (ICD) refers to an immunologically distinct process of regulated cell death that activates, rather than suppresses, innate and adaptive immune responses. Such responses culminate into T cell-driven immunity against antigens derived from dying cancer cells. The potency of ICD is dependent on the immunogenicity of dying cells as defined by the antigenicity of these cells and their ability to expose immunostimulatory molecules like damage-associated molecular patterns (DAMPs) and cytokines like type I interferons (IFNs). Moreover, it is crucial that the host's immune system can adequately detect the antigenicity and adjuvanticity of these dying cells. Over the years, several well-known chemotherapies have been validated as potent ICD inducers, including (but not limited to) anthracyclines, paclitaxels, and oxaliplatin. Such ICD-inducing chemotherapeutic drugs can serve as important combinatorial partners for anti-cancer immunotherapies against highly immuno-resistant tumors. In this Trial Watch, we describe current trends in the preclinical and clinical integration of ICD-inducing chemotherapy in the existing immuno-oncological paradigms.

Radiation dose-escalation and dose-fractionation modulate the immune microenvironment, cancer stem cells and vasculature in experimental high-grade gliomas.

BACKGROUND: In the context of high-grade gliomas (HGGs), very little evidence is available concerning the optimal radiotherapy (RT) schedule to be used in radioimmunotherapy combinations. This studied was aimed at shedding new light in this field by analyzing the effects of RT dose escalation and dose fractionation on the tumor microenvironment of experimental HGGs. METHODS: Neurospheres (NS) CT-2A HGG-bearing C57BL/6 mice were treated with stereotactic RT. For dose-escalation experiments, mice received 2, 4 or 8 Gy as single administrations. For dose-fractionation experiments, mice received 4 Gy as a single fraction or multiple (1.33x3 Gy) fractions. The impact of the RT schedule on murine survival and tumor immunity was evaluated. Modifications of glioma stem cells (GSCs), tumor vasculature and tumor cell replication were also assessed. RESULTS: RT dose-escalation was associated with an improved immune profile, with higher CD8+ T cells and CD8+ T cells/regulatory T cells (Tregs) ratio (P=0.0003 and P=0.0022, respectively) and lower total tumor associated microglia/macrophages (TAMs), M2 TAMs and monocytic myeloid derived suppressor cells (mMDSCs) (P=0.0011, P=0.0024 and P<0.0001, respectively). The progressive increase of RT dosages prolonged survival (P<0.0001) and reduced tumor vasculature (P=0.069), tumor cell proliferation (P<0.0001) and the amount of GSCs (P=0.0132 or lower). Compared to the unfractionated regimen, RT dose-fractionation negatively affected tumor immunity by inducing higher total TAMs, M2 TAMs and mMDSCs (P=0.0051, P=0.0036 and P=0.0436, respectively). Fractionation also induced a shorter survival (P=0.0078), a higher amount of GSCs (P=0.0015 or lower) and a higher degree of tumor cell proliferation (P=0.0003). CONCLUSIONS: This study demonstrates that RT dosage and fractionation significantly influence survival, tumor immunity and GSCs in experimental HGGs. These findings should be taken into account when aiming at designing more synergistic and effective radio-immunotherapy combinations.

A Microfluidics Approach for Ovarian Cancer Immune Monitoring in an Outpatient Setting.

Among cancer diagnoses in women, ovarian cancer has the fifth-highest mortality rate. Current treatments are unsatisfactory, and new therapies are highly needed. Immunotherapies show great promise but have not reached their full potential in ovarian cancer patients. Implementation of an immune readout could offer better guidance and development of immunotherapies. However, immune profiling is often performed using a flow cytometer, which is bulky, complex, and expensive. This equipment is centralized and operated by highly trained personnel, making it cumbersome and time-consuming. We aim to develop a disposable microfluidic chip capable of performing an immune readout with the sensitivity needed to guide diagnostic decision making as close as possible to the patient. As a proof of concept of the fluidics module of this concept, acquisition of a limited immune panel based on CD45, CD8, programmed cell death protein 1 (PD1), and a live/dead marker was compared to a conventional flow cytometer (BD FACSymphony). Based on a dataset of peripheral blood mononuclear cells of 15 patients with ovarian cancer across different stages of treatment, we obtained a 99% correlation coefficient for the detection of CD8+PD1+ T cells relative to the total amount of CD45+ white blood cells. Upon further system development comprising further miniaturization of optics, this microfluidics chip could enable immune monitoring in an outpatient setting, facilitating rapid acquisition of data without the need for highly trained staff.

Intraperitoneal alpha therapy with 224Ra-labeled microparticles combined with chemotherapy in an ovarian cancer mouse model.

A novel alpha-therapy consisting of 224Ra-labeled calcium carbonate microparticles (224Ra-CaCO3-MP) has been designed to treat micrometastatic peritoneal disease via intraperitoneal (IP) administration. This preclinical study aimed to evaluate its efficacy and tolerability when given as a single treatment or in combination with standard of care chemotherapy regimens, in a syngeneic model of ovarian cancer in immune competent mice. Female C57BL/6 mice bearing ID8-fLuc ovarian cancer were treated with 224Ra-CaCO3-MP 1 day after IP tumor cell inoculation. The activity dosages of 224Ra ranged from 14 to 39 kBq/mouse. Additionally, 224Ra-CaCO3-MP treatment was followed by either carboplatin (80 mg/kg)-pegylated liposomal doxorubicin (PLD, 1.6 mg/kg) or carboplatin (60 mg/kg)-paclitaxel (10 mg/kg) on day 14 post tumor cell inoculation. All treatments were administered via IP injections. Readouts included survival, clinical signs, and body weight development over time. There was a slight therapeutic benefit after single treatment with 224Ra-CaCO3-MP compared to the vehicle control, with median survival ratios (MSRs) ranging between 1.1 and 1.3. The sequential administration of 224Ra-CaCO3-MP with either carboplatin-paclitaxel or carboplatin-PLD indicated a synergistic effect on overall survival at certain 224Ra activities. Moreover, the combinations tested appeared well tolerated in terms of weight assessment in the first 4 weeks after treatment. Overall, this research supports the further evaluation of 224Ra-CaCO3-MP in patients with ovarian cancer. However, the most optimal chemotherapy regimen to combine with 224Ra-CaCO3-MP should be identified to fully exploit its therapeutic potential.

Dendritic Cell Vaccines: A Promising Approach in the Fight against Ovarian Cancer.

Ovarian cancer (OC) is the deadliest gynecological malignancy in developed countries and is the seventh-highest cause of death in women diagnosed with cancer worldwide. Currently, several therapies are in use against OC, including debulking surgery, chemotherapy, as well as targeted therapies. Even though the current standard-of-care therapies improve survival, a vast majority of OC patients relapse. Additionally, immunotherapies have only resulted in meager patient outcomes, potentially owing to the intricate immunosuppressive nexus within the tumor microenvironment. In this scenario, dendritic cell (DC) vaccination could serve as a potential addition to the therapeutic options available against OC. In this review, we provide an overview of current therapies in OC, focusing on immunotherapies. Next, we highlight the potential of using DC vaccines in OC by underscoring the different DC subsets and their functions in OC. Finally, we provide an overview of the advances and pitfalls of current DC vaccine strategies in OC while providing future perspectives that could improve patient outcomes.

Do autoimmune diseases influence the onset and progression of ovarian cancer? A systematic review and meta-analysis.

OBJECTIVE: Ovarian cancer remains the fifth leading cause of cancer-related deaths in women. The immune system influences the onset and progression of ovarian cancer. Therefore, we aimed to study the behavior of ovarian cancer in patients with a pre-existing immune dysfunction, more specifically autoimmune disease. METHODS: For this systematic review we carried out a systematic search of four electronic databases (MEDLINE, Embase, CENTRAL, Web of Science) with the two main search terms "autoimmunity" and "ovarian cancer" up to May 10, 2020. We included 36 different autoimmune diseases in our search. From the 4799 screened records, we identified 53 relevant articles for our review, of which 48 were used in our meta-analysis. RESULTS: The incidence of ovarian cancer was significantly lower in patients with multiple sclerosis (standardized incidence ratio (SIR) 0.76, 95% CI 0.60 to 0.96). There was a tendency towards a lower risk of ovarian cancer in patients with systematic lupus erythematosus (SIR 0.89, 95% CI 0.68 to 1.15) and a tendency towards a higher risk in those with type 1 diabetes mellitus (SIR 1.49, 95% CI 0.98 to 2.28); however, this was not statistically significant. No conclusions could be drawn on mortality or the influence of immunosuppressive drugs used in the treatment of autoimmune diseases and the incidence of ovarian cancer. CONCLUSIONS: Our study showed a decreased incidence of ovarian cancer in patients with multiple sclerosis. However, further investigation on the role of the immune system in the development of ovarian cancer in women with autoimmune diseases remains necessary.

Liquid Biopsy in Glioblastoma.

Glioblastoma (GBM) is the most common and aggressive primary brain tumor. Despite recent advances in therapy modalities, the overall survival of GBM patients remains poor. GBM diagnosis relies on neuroimaging techniques. However, confirmation via histopathological and molecular analysis is necessary. Given the intrinsic limitations of such techniques, liquid biopsy (mainly via blood samples) emerged as a non-invasive and easy-to-implement alternative that could aid in both the diagnosis and the follow-up of GBM patients. Cancer cells release tumoral content into the bloodstream, such as circulating tumor DNA, circulating microRNAs, circulating tumor cells, extracellular vesicles, or circulating nucleosomes: all these could serve as a marker of GBM. In this narrative review, we discuss the current knowledge, the advantages, and the disadvantages of each circulating biomarker so far proposed.

Peripheral gene signatures reveal distinct cancer patient immunotypes with therapeutic implications for autologous DC-based vaccines.

Dendritic cells (DCs) have received considerable attention as potential targets for the development of novel cancer immunotherapies. However, the clinical efficacy of DC-based vaccines remains suboptimal, largely reflecting local and systemic immunosuppression at baseline. An autologous DC-based vaccine (DCVAC) has recently been shown to improve progression-free survival and overall survival in randomized clinical trials enrolling patients with lung cancer (SLU01, NCT02470468) or ovarian carcinoma (SOV01, NCT02107937), but not metastatic castration-resistant prostate cancer (SP005, NCT02111577), despite a good safety profile across all cohorts. We performed biomolecular and cytofluorometric analyses on peripheral blood samples collected prior to immunotherapy from 1000 patients enrolled in these trials, with the objective of identifying immunological biomarkers that may improve the clinical management of DCVAC-treated patients. Gene signatures reflecting adaptive immunity and T cell activation were associated with favorable disease outcomes and responses to DCVAC in patients with prostate and lung cancer, but not ovarian carcinoma. By contrast, the clinical benefits of DCVAC were more pronounced among patients with ovarian carcinoma exhibiting reduced expression of T cell-associated genes, especially those linked to TH2-like signature and immunosuppressive regulatory T (TREG) cells. Clinical responses to DCVAC were accompanied by signs of antitumor immunity in the peripheral blood. Our findings suggest that circulating signatures of antitumor immunity may provide a useful tool for monitoring the potency of autologous DC-based immunotherapy.

Trial watch: Dendritic cell (DC)-based immunotherapy for cancer.

Dendritic cell (DC)-based vaccination for cancer treatment has seen considerable development over recent decades. However, this field is currently in a state of flux toward niche-applications, owing to recent paradigm-shifts in immuno-oncology mobilized by T cell-targeting immunotherapies. DC vaccines are typically generated using autologous (patient-derived) DCs exposed to tumor-associated or -specific antigens (TAAs or TSAs), in the presence of immunostimulatory molecules to induce DC maturation, followed by reinfusion into patients. Accordingly, DC vaccines can induce TAA/TSA-specific CD8+/CD4+ T cell responses. Yet, DC vaccination still shows suboptimal anti-tumor efficacy in the clinic. Extensive efforts are ongoing to improve the immunogenicity and efficacy of DC vaccines, often by employing combinatorial chemo-immunotherapy regimens. In this Trial Watch, we summarize the recent preclinical and clinical developments in this field and discuss the ongoing trends and future perspectives of DC-based immunotherapy for oncological indications.

Pan-Cancer Detection and Typing by Mining Patterns in Large Genome-Wide Cell-Free DNA Sequencing Datasets.

BACKGROUND: Cell-free DNA (cfDNA) analysis holds great promise for non-invasive cancer screening, diagnosis, and monitoring. We hypothesized that mining the patterns of cfDNA shallow whole-genome sequencing datasets from patients with cancer could improve cancer detection. METHODS: By applying unsupervised clustering and supervised machine learning on large cfDNA shallow whole-genome sequencing datasets from healthy individuals (n = 367) and patients with different hematological (n = 238) and solid malignancies (n = 320), we identified cfDNA signatures that enabled cancer detection and typing. RESULTS: Unsupervised clustering revealed cancer type-specific sub-grouping. Classification using a supervised machine learning model yielded accuracies of 96% and 65% in discriminating hematological and solid malignancies from healthy controls, respectively. The accuracy of disease type prediction was 85% and 70% for the hematological and solid cancers, respectively. The potential utility of managing a specific cancer was demonstrated by classifying benign from invasive and borderline adnexal masses with an area under the curve of 0.87 and 0.74, respectively. CONCLUSIONS: This approach provides a generic analytical strategy for non-invasive pan-cancer detection and cancer type prediction.