The rapid technological developments in diagnostics and innovations in multimodal therapy in the field of hematology and medical oncology were the focus of the annual conference. While immunotherapies with monoclonal tumor-specific antibodies and checkpoint inhibitors already dominate everyday oncological practice, immunotherapeutic combination approaches and cell therapy-based immunotherapies are the focus of current clinical trials. These were examined and discussed in more detail.
Regulatory T cells (Tregs) play a critical role in maintaining immune tolerance, but their presence in the tumor microenvironment (TME) can dampen the anti-tumor immune response. The pro-inflammatory cytokine IL-23, which is mainly produced by myeloid cells, paradoxically promotes tumor growth in preclinical models and correlates with poor clinical outcomes. However, the specific mechanisms underlying the tumor-promoting effects of IL-23 are still unclear. In one study, several preclinical cancer models were used together with a new reporter mouse strain and single cell analyses to comprehensively map the cellular responders and sources of IL-23 in the TME [1]. In addition, the effects of IL23R signaling in Tregs within the TME were investigated using conditional knockout mice. The aim was to understand the influence of IL23R on Treg stability and suppressive function in both murine and human TME.
In the study, tumor-associated macrophages were identified as the primary producers of IL-23 in the TME. Among the cells that sense IL-23, a subset of highly suppressive tumor-infiltrating Tregs was discovered. The specific ablation of Il23r in Tregs led to significantly reduced tumor growth in various preclinical models. Remarkably, the reduction in tumor growth observed with Treg-specific ablation matched the kinetics observed in mice with complete Il23r loss. This indicates that Tregs are the relevant target of IL-23 in the TME. Mechanistically, IL23R signaling promotes an eectorTreg (eTreg) program characterized by increased expression of the master transcription factor Foxp3 and key downstream targets involved in suppressive function. IL23r-depleted Tregs showed a reduced suppressive capacity and signs of Treg destabilization. Transcriptome analysis revealed that IL23R signaling is crucial for the transition of Tregs from an activated to an eTreg differentiation program. Importantly, these results have been validated in the context of human cancer in various solid tumor types.
Real-world data for breast cancer
Oncogenes are part of a complex genomic landscape that is characterized by additional changes. These could in turn be target structures or potential biomarkers for the response to therapy. An OncoVision platform was developed and implemented. This is an automated, clinically oriented informatics platform for the identification and dynamic tracking of patients based on molecular and clinical criteria [2]. The study analyzed 122 patients with advanced breast cancer who underwent hybrid-capture-based next-generation sequencing to identify clinically relevant genomic changes. The data was then analyzed for the occurrence of co-changes using the OncoVision platform. Molecular patterns were evaluated for each patient, with the first gene partner representing an alteration listed in the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT).
The OncoVision platform successfully identified molecular patterns. At least one co-modification was identified in a total of 58.2% of patients, and 61 patients (50.0%) were found to have two potentially vulnerable genetic alterations. In 10 (8.2%) patients, three co-modifications listed in ESCAT were detected. The OncoVision platform detected concomitant therapy-relevant changes in over 50% of the patients examined. As the landscape of molecularly targeted therapies expands, combinations of personalized therapies are becoming increasingly relevant. The OncoVision platform is a novel and effective method for identifying therapy-relevant molecular patterns in breast cancer.
Lung cancer in the palliative setting
Treatment options for patients with small cell lung cancer (SCLC) have improved significantly with the approval of the first two checkpoint inhibitors (CPI), atezolizumab and durvalumab, for stage IV SCLC. Has the introduction of CPI influenced the use of PCI? What are the patient and tumor characteristics of patients with and without CPI-containing first-line therapy and within these groups with and without PCI? A study investigated these questions [3]. CRISP is a prospective, multicenter clinical research platform with the aim of understanding the treatment reality of patients with lung cancer in Germany. Between September 2019 and April 2021, 114 sites in Germany recruited 817 patients diagnosed with SCLC at all stages. In addition to details on patient and tumor characteristics, systemic treatments and outcome, information on radiotherapy, such as PCI, was also collected.
149 patients without documented CNS metastases and with completed first-line treatment with best response CR/PR/SD were identified as potentially suitable for PCI treatment. Of the 149 patients, 114 patients (77%) were treated with and 35 patients (23%) without first-line CPI. Of the 114 patients with CPI treatment who were eligible for PCI, 25 patients (22%) received PCI, 78 patients (68%) did not receive PCI and 11 patients (10%) still had the possibility of receiving PCI in the future. All in all, CPI in combination with chemotherapy has quickly become the new standard of care for extensive stage SCLC. The patient characteristics of patients treated with and without CPI do not show any major differences. This suggests that no specific patient characteristics influence decision making for CPI treatment. PCI was performed in a quarter to a third of the eligible patients. In the group of patients with first-line CPI treatment, more female and median younger patients received PCI.
Pancreatic cancer and the role of checkpoint inhibitors
Immune checkpoint inhibitors (ICI) targeting programmed cell death protein 1-ligand 1 (PD-L1) or its receptor PD-1 have not improved therapeutic outcomes in pancreatic ductal adenocarcinoma (PDAC) despite success in other cancers. Resistance to PDAC is usually explained by the immunosuppressive nature of the PDAC tumor microenvironment (TME). Macrophages represent an abundant immune cell population in the TME of PDAC and can either support or inhibit tumor progression depending on their phenotype. To better understand PD-L1/PD-1 inhibitor treatment failure in PDAC, one study examined PD-L1 expression in the context of a dynamic TME in PDAC, focusing on the influence of macrophages [4]. Surgically excised PDAC samples and corresponding liver metastases were immunohistochemically stained and PD-L1 expression in the tumor and TME was determined. To investigate the effects of cell interactions on PD-L1 expression, a 3D spheroid co-culture model of PDAC cells and different ratios of M1- and M2-like polarized macrophages and CD8+ T cells was developed. The effect of treatment with ICI on tumor cell viability and the phenotype of macrophages and CD8+ T cells was determined by apoptosis assay, ow cytometry and analysis of culture supernatants.
Immunohistochemical analysis confirmed that PD-L1 is mainly expressed by stromal cells, including macrophages. A high local abundance of macrophages and strong PD-L1 staining were frequently found at the invasion fronts of tumor lesions, between CD8+ T cells and tumor cells. In agreement with the in situ results, high PD-L1 expression was observed in macrophages rather than PDAC cells in the 3D culture model. The effector phenotype of the co-cultured CD8+ T cells, as evidenced by the expression of activation markers and the release of ector molecules, was enhanced in the PDAC macrophage co-culture spheroids. However, the apoptosis of PDAC cells was not increased by this enhanced effector phenotype. In addition, ICI treatment with durvalumab or pembrolizumab alone or in combination with gemcitabine had little effect on the effector phenotype of CD8+ T cells or apoptosis of PDAC cells.
Inhibition of the PD-1/PD-L1 axis did not lead to an improvement in the cytotoxic phenotype of the CD8+ T cells, although the macrophages showed strong PD-L1 expression. This suggests that alternative mechanisms dominate the immune defense in PDAC.
New risk factors for CLL
In the era of chemoimmunotherapy (CIT) in CLL, several biological risk factors for shorter progression-free survival (PFS) and overall survival (OS) have emerged. The CLL-IPI, which includes the most important unfavorable factors (TP53 and IGHV status, ß2-MG, age, stage), reliably predicts the results of CIT. BTK (BTKi) and Bcl-2 inhibitors have now become widely accepted in first-line and relapse therapy. It is therefore important to review the prognostic value of these known risk factors in the context of new drugs and to identify new prognostic factors [5].
TP53 aberrations (TP53ab) have the strongest negative effect on the results of CIT. In the context of BTKi, the presence of TP53ab is still associated with poorer PFS and OS1 overall. In various large studies with BTKi, no difference in PFS was observed between patients with and without TP53ab. In the context of time-limited venetoclax (ven) + obinutuzumab, TP53ab is still an independent prognostic factor for a shorter PFS. Non-mutated IGHV (U-CLL) is associated with poorer PFS and OS in CIT. With BTKi treatment, only a few studies observed a shorter PFS in patients with U-CLL, while the long-term follow-up of most pivotal BTKi studies showed no significant impact of U-CLL on PFS, underlining the important role of BTKi in this patient group. In the CLL13 and CLL14 studies, patients with U-CLL who received time-limited ven combinations had a significantly shorter PFS, although this was far less pronounced than with CIT. Complex karyotypes are associated with poorer outcomes in patients treated with CIT. In patients treated with ibrutinib, an increasing number of aberrations also led to a shorter PFS and OS. With ven-based combinations, not three but only five aberrations were an independent risk factor for a shorter PFS. In addition to these established risk factors, large studies using integrative multi-omic approaches have proposed new biological subgroups based on genomic/epigenomic/proteomic traits. However, these results need to be validated in more homogeneous and timely treated patient populations.
Most established biological risk factors such as TP53ab, U-CLL, CKT and ß2-MG continue to play a (reduced) role in connection with BTK and Bcl-2 inhibition. TP53ab and U-CLL appear to be more prognostic with time-limited ven combinations than with continuous BTKi treatment. However, there is a lack of data from direct comparisons.
Congress: Annual Meeting of the German, Austrian and Swiss Society for Hematology and Medical Oncology
Literature:
- Wertheimer T, Zwicky P, Rindlisbacher L, et al.: IL-23 stabilizes an effector Treg program in the tumor microenvironment. V34. DGHO 2023. Oncol Res Treat 2023; 46(suppl 5): 1–354.
- Hempel L, Ebner F, Veloso de Oliveira J, et al.: Real-world outcomes of an automated physician support system for analysis of actionable co-alterations and molecular biomarker patterns in advanced breast cancer patients. V43. DGHO 2023. Oncol Res Treat 2023; 46(suppl 5): 1–354.
- Reck M, Gauler T, Waller CF, et al.: SCLC patients treated with vs without prophylactic cranial irradiation in palliative setting after systemic treatment with checkpoint inhibitors – Data from the Clinical Research platform Into molecular testing, treatment and outcome of (non-) Small cell lung carcinoma Patients (CRISP; AIO-TRK-0315). V46. DGHO 2023. Oncol Res Treat 2023; 46(suppl 5):1–354.
- Daunke T, Beckinger S, Rahn S, et al.: Analysis of the immune checkpoint regulator PD-L1 in the tumor-stroma interplay of pancreatic ductal adenocarcinoma with a focus on the role of macrophages. V55. DGHO 2023. Oncol Res Treat 2023; 46(suppl 5): 1–354.
- Fürstenau M: New biological risk factors. V68. DGHO 2023. Oncol Res Treat 2023; 46(suppl 5): 1–354.
InFo ONKOLOGIE & HÄMATOLOGIE 2023; 11(5): 30–31
