A Quantitative Digital Analysis of Tissue Immune Components Reveals an Immunosuppressive and Anergic Immune Response with Relevant Prognostic Significance in Glioblastoma

Integrated MRI radiomics, tumor microenvironment, and clinical risk factors for improving survival prediction in patients with glioblastomas

PURPOSE

To construct a comprehensive model for predicting the prognosis of patients with glioblastoma (GB) using a radiomics method and integrating clinical risk factors, tumor microenvironment (TME), and imaging characteristics.

MATERIALS AND METHODS

In this retrospective study, we included 148 patients (85 males and 63 females; median age 53 years) with isocitrate dehydrogenase-wildtype GB between January 2016 and April 2022. Patients were randomly divided into the training (n = 104) and test (n = 44) sets. The best feature combination related to GB overall survival (OS) was selected using LASSO Cox regression analyses. Clinical, radiomics, clinical-radiomics, clinical-TME, and clinical-radiomics-TME models were established. The models' concordance index (C-index) was evaluated. The survival curve was drawn using the Kaplan-Meier method, and the prognostic stratification ability of the model was tested.

RESULTS

LASSO Cox analyses were used to screen the factors related to OS in patients with GB, including MGMT (hazard ratio [HR] = 0.642; 95% CI 0.414-0.997; P = 0.046), TERT (HR = 1.755; 95% CI 1.095-2.813; P = 0.019), peritumoral edema (HR = 1.013; 95% CI 0.999-1.027; P = 0.049), tumor purity (TP; HR = 0.982; 95% CI 0.964-1.000; P = 0.054), CD163 + tumor-associated macrophages (TAMs; HR = 1.049; 95% CI 1.021-1.078; P < 0.001), CD68 + TAMs (HR = 1.055; 95% CI 1.018-1.093; P = 0.004), and the six radiomics features. The clinical-radiomics-TME model had the best survival prediction ability, the C‑index was 0.768 (0.717-0.819). The AUC of 1‑, 2‑, and 3‑year OS prediction in the test set was 0.842, 0.844, and 0.795, respectively.

CONCLUSION

The clinical-radiomics-TME model is the most effective for predicting the survival of patients with GB. Radiomics features, TP, and TAMs play important roles in the prognostic model.

Targeting PD-1/PD-L1 in tumor immunotherapy: Mechanisms and interactions with host growth regulatory pathways

Tumor immunotherapy has garnered considerable attention, emerging as a new standard of care in cancer treatment. The conventional targets, such as VEGF and EGFR, have been extended to others including BRAF and PD-1/PD-L1, which have shown significant potential in recent cancer treatments. This review aims to succinctly overview the impact and mechanisms of therapies that modulate PD-1/PD-L1 expression by targeting VEGF, EGFR, LAG-3, CTLA-4 and BRAF. We investigated how modulation of PD-1/PD-L1 expression impacts growth factor signaling, shedding light on the interplay between immunomodulatory pathways and growth factor networks within the tumor microenvironment. By elucidating these interactions, we aim to provide insights into novel potential synergistic therapeutic strategies for cancer immunotherapy.

Prediction of Meningioma Grade Using Hematological Parameters

OBJECTIVE

Predicting the aggressiveness of meningiomas may influence the surgical strategy timing. Because of the paucity of robust markers, the systemic immune-inflammation (SII) index is a novel biomarker to be an independent predictor of poor prognosis in various cancers including gliomas. We aimed to investigate the value of SII as well as neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) indices in predicting prognosis.

METHODS

Records including demographic, clinical, and laboratory data of patients operated on due to intracranial meningioma in 2017-2023 were retrospectively reviewed.

RESULTS

A total of 234 patients were included in this study. All of SII index, NLR, and PLR values at presentation were significantly higher in grade ≥2 meningiomas. A positive correlation was observed between SII index and Ki67 index (r=0.313; P<0.001); between NLR and Ki67 index (r=0.330; P<0.001); and between PLR and Ki67 index (r=0.223; P<0.01). SII index (optimal cutoff level >618), NLR (optimal cutoff level >3.53), and PLR (optimal cutoff level >121.2) showed significant predictive values.

CONCLUSIONS

This is the first study to assess the prognostic value of the SII index in patients with intracranial meningiomas. Increased SII index, NLR and PLR were correlated with higher grade and higher Ki-67 index. They also harbor the potential to screen patients that may need more aggressive treatments or more frequent follow-up examinations.

Correlation of tumor-associated macrophage infiltration in glioblastoma with magnetic resonance imaging characteristics: a retrospective cross-sectional study

Background

Glioblastoma (Gb) is the most common primary malignant tumor of brain with poor prognosis. Immune cells are the main factors affecting the prognosis of Gb, tumor-associated macrophages (TAMs) are the predominant infiltrating immune cell population in the immune microenvironment of Gb. Analyzing the relationship between magnetic resonance imaging (MRI) features and TAMs of Gb, and using imaging features to characterize the infiltration level of TAMs in tumor tissue may provide indicators for clinical decision-making and prognosis evaluation of Gb.

Methods

Data from 140 in patients with isocitrate dehydrogenase (IDH) wild-type Gb diagnosed via histopathology and molecular diagnosis in the Second Hospital of Lanzhou University from January 2018 to April 2022 were collected in this retrospective, cross-sectional study. MRI images were reviewed for lesion location, cyst, necrosis, hemorrhage, contrast-enhanced T1-weighted MRI signal intensity, average apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Immunohistochemical staining with anti-CD163 and anti-CD68 antibodies was employed for macrophage detection. The positive cell percentage was estimated in 9 microscopic fields at 400× magnification per whole-slide image with ImageJ software (National Institutes of Health). Additionally, the relationship between MRI features, molecular, states and the positive CD68 and CD163 expression was analyzed.

Results

Our study discovered that the mean or median values of CD68+ and CD163+ TAMs were 7.39% and 14.98%, respectively. There was an obvious correlation between CD163+ TAMs and CD68+ TAMs (r=0.497; P=0.000). CD68+ and CD163+ macrophage infiltration correlated with age at diagnosis in patients with Gb (CD68+: r=0.230, P=0.006; CD163+: r=0.172, P=0.042). The levels of Gb TAM infiltration in different tumor locations varied, with the temporal lobe having the highest CD163+ macrophage and CD68+ macrophage infiltration (18.58% and 9.46%, respectively). CD163+ macrophage infiltration was positively correlated with ADCmean (r=0.208; P=0.014). The infiltration of CD68+ macrophages differed significantly between groups with varying degrees of tumor enhancement (H =4.228; P=0.017). There was a significant difference in CD68+ TAMs and CD163+ TAMs between the wild-type and mutant-type telomerase reverse transcriptase (TERT) types (P=0.004 and P=0.031, respectively).

Conclusions

Age, location of the tumor, degree of tumor enhancement, ADC value, and TERT mutation status were associated with macrophage infiltration. These findings may serve as an effective tool for characterizing the tumor microenvironment in patients with Gb.

Barriers to overcoming immunotherapy resistance in glioblastoma

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor, known for its poor prognosis and high recurrence rate. Current standard of care includes surgical resection followed by combined radiotherapy and chemotherapy. Although immunotherapies have yielded promising results in hematological malignancies, their successful application in GBM remains limited due to a host of immunosuppressive factors unique to GBM. As a result of these roadblocks, research efforts have focused on utilizing combinatorial immunotherapies that target networks of immune processes in GBM with promising results in both preclinical and clinical trials, although limitations in overcoming the immunosuppressive factors within GBM remain. In this review, we aim to discuss the intrinsic and adaptive immune resistance unique to GBM and to summarize the current evidence and outcomes of engineered and non-engineered treatments targeted at overcoming GBM resistance to immunotherapy. Additionally, we aim to highlight the most promising strategies of targeted GBM immunotherapy combinatorial treatments and the insights that may directly improve the current patient prognosis and clinical care.

Prognostic role of the pretreatment systemic immune-inflammation index in patients with glioma: A meta-analysis

Background

The systemic immune-inflammation index (SII) has been recognized as the indicator that reflects the status of immune responses. The SII is related to the prognostic outcome of many malignancies, whereas its role in gliomas is controversial. For patients with glioma, we, therefore, conducted a meta-analysis to determine if the SII has a prognostic value.

Methods

Studies relevant to this topic were searched from 16 October 2022 in several databases. In patients with glioma, the relation of the SII level with the patient prognosis was analyzed based on hazard ratios (HRs) as well as corresponding 95% confidence intervals (CIs). Moreover, subgroup analysis was conducted to examine a possible heterogeneity source.

Results

There were eight articles involving 1,426 cases enrolled in the present meta-analysis. The increased SII level predicted the dismal overall survival (OS) (HR = 1.81, 95% CI = 1.55–2.12, p &lt; 0.001) of glioma cases. Furthermore, an increased SII level also predicted the prognosis of progression-free survival (PFS) (HR = 1.87, 95% CI = 1.44–2.43, p &lt; 0.001) in gliomas. An increased SII was significantly associated with a Ki-67 index of ≥30% (OR = 1.72, 95% CI = 1.10–2.69, p = 0.017). However, a high SII was not correlated with gender (OR = 1.05, 95% CI = 0.78–1.41, p = 0.734), KPS score (OR = 0.64, 95% CI = 0.17–2.37, p = 0.505), or symptom duration (OR 1.22, 95% CI 0.37–4.06, p = 0.745).

Conclusion

There was a significant relation between an increased SII level with poor OS and the PFS of glioma cases. Moreover, patients with glioma with a high SII value have a positive relationship with a Ki-67 of ≥30%.

Immunophenotyping of Circulating and Intratumoral Myeloid and T Cells in Glioblastoma Patients

Glioblastoma is the most common and lethal primary brain malignancy that almost inevitably recurs as therapy-refractory cancer. While the success of immune checkpoint blockade (ICB) revealed the immense potential of immune-targeted therapies in several types of cancers outside the central nervous system, it failed to show objective responses in glioblastoma patients as of now. The ability of glioblastoma cells to drive multiple modes of T cell dysfunction while exhibiting low-quality neoepitopes, low-mutational load, and poor antigen priming limits anti-tumor immunity and efficacy of antigen-unspecific immunotherapies such as ICB. An in-depth understanding of the GBM immune landscape is essential to delineate and reprogram such immunosuppressive circuits during disease progression. In this view, the present study aimed to characterize the peripheral and intratumoral immune compartments of 35 glioblastoma patients compared to age- and sex-matched healthy control probands, particularly focusing on exhaustion signatures on myeloid and T cell subsets. Compared to healthy control participants, different immune signatures were already found in the peripheral circulation, partially related to the steroid medication the patients received. Intratumoral CD4+ and CD8+ TEM cells (CD62L^low/CD45RO^high) revealed a high expression of PD1, which was also increased on intratumoral, pro-tumorigenic macrophages/microglia. Histopathological analysis further identified high PSGL-1 expression levels of the latter, which has recently been linked to increased metastasis in melanoma and colon cancer via P-selectin-mediated platelet activation. Overall, the present study comprises immunophenotyping of a patient cohort to give implications for eligible immunotherapeutic targets in neurooncology in the future.