Detection of dendritic cell subsets in the tumor microenvironment by multiplex immunohistochemistry

Dendritic cells (DCs) are essential in antitumor immunity. In humans, three main DC subsets are defined: two types of conventional DCs (cDC1s and cDC2s) and plasmacytoid DCs (pDCs). To study DC subsets in the tumor microenvironment (TME), it is important to correctly identify them in tumor tissues. Tumor-derived DCs are often analyzed in cell suspensions in which spatial information about DCs which can be important to determine their function within the TME is lost. Therefore, we developed the first standardized and optimized multiplex immunohistochemistry panel, simultaneously detecting cDC1s, cDC2s, and pDCs within their tissue context. We report on this panel's development, validation, and quantitative analysis. A multiplex immunohistochemistry panel consisting of CD1c, CD303, X-C motif chemokine receptor 1, CD14, CD19, a tumor marker, and DAPI was established. The ImmuNet machine learning pipeline was trained for the detection of DC subsets. The performance of ImmuNet was compared with conventional cell phenotyping software. Ultimately, frequencies of DC subsets within several tumors were defined. In conclusion, this panel provides a method to study cDC1s, cDC2s, and pDCs in the spatial context of the TME, which supports unraveling their specific roles in antitumor immunity.

Multiplex Immunohistochemical Analysis of the Spatial Immune Cell Landscape of the Tumor Microenvironment

The immune cell landscape of the tumor microenvironment potentially contains information for the discovery of prognostic and predictive biomarkers. Multiplex immunohistochemistry is a valuable tool to visualize and identify different types of immune cells in tumor tissues while retaining its spatial information. Here we provide detailed protocols to analyze lymphocyte, myeloid, and dendritic cell populations in tissue sections. Starting from cutting formalin-fixed paraffin-embedded sections, automatic multiplex staining procedures on an automated platform, scanning of the slides on a multispectral imaging microscope, to the analysis of images using an in-house-developed machine learning algorithm ImmuNet. These protocols can be applied to a variety of tumor specimens by simply switching tumor markers to analyze immune cells in different compartments of the sample (tumor versus invasive margin) and apply nearest-neighbor analysis. This analysis is not limited to tumor samples but can also be applied to other (non-)pathogenic tissues. Improvements to the equipment and workflow over the past few years have significantly shortened throughput times, which facilitates the future application of this procedure in the diagnostic setting.

[The glucagon test in diagnosis of secondary adrenal insufficiency after craniospinal irradiation: the feasibility of application, the features of performing the test, and its diagnostic informativity]

BACKGROUND

The glucagon test (GT) is a promising alternative to the insulin hypoglycemia test (IHT) in diagnosis of secondary adrenal insufficiency (SAI).

AIM

To study the feasibility of using the GT in patients after craniospinal irradiation and to determine the cut-off value to rule out SAI.

METHODS

A total of 28 patients (14 males and 14 females) with the median age of 19 years (17; 23) who had undergone combination treatment (surgery, craniospinal irradiation (35 Gy) with boost to the tumor bed, and polychemotherapy) of extrapituitary brain tumors no later than 2 years before study initiation and 10 healthy volunteers of matching sex and age were examined. All the subjects underwent the GT and IHT with an interval of at least 57 days. The cortisol, ACTH, and glucose levels were measured.

RESULTS

Twelve out of 28 patients were diagnosed with SAI according to the IHT results. ROC analysis revealed that cortisol release during the GT 499 nmol/L ruled out SAI [100% sensitivity (Se); 62% specificity (Sp)], while the absence of a rise 340 nmol/l verified SAI (Sp 100%; 55% Se). For GT, the area under a curve (AUC) was 93.6%, which corresponds to a very good diagnostic informativity. In 19 patients, the IHT and GT results were concordant (in ten patients, the release of cortisol occurred above the cut-off value in both tests; no release was detected in nine patients). In nine cases, the results were discordant: the maximum cortisol level detected in the GT was 500 nmol/l, but the IHT results ruled out SAI (the GT yielded a false positive outcome). Contrariwise, in three (10.7%) patients the release of cortisol detected in the GT was adequate, while being insufficient in the IHT test. Adverse events (nausea) were reported during the GT test in 9 (25%) subjects; one patient had hypoglycemia (1.8 mmol/l).

CONCLUSION

GT is highly informative and can be used as a first-level stimulation test for ruling out SAI in patients exposed to craniospinal irradiation performed to manage brain tumors. The cortisol level of 500 nmol/L is the best cut-off value for ruling out SAI according to the GT results. The insulin hypoglycemia test is used as the second-level supporting test in patients with positive GT results.

[Clinical features and diagnosis of secondary adrenal insufficiency followed complex treatment nonpituitary brain tumors]

BACKGROUND

The most of the current studies include patients who are different by the etiology of secondary adrenal insufficiency (SAI), or investigate SAI among other late effects of the radiation therapy.

AIMS

To describe the features of SAI and to select the best method of screening SAI in adult patients followed complex treatment of nonpituitary brain tumors in childhood.

MATERIALS AND METHODS

It was the retrospective cross-sectional study. 31 patients after the complex treatment of nonpituitary brain tumors in childhood and 20 healthy volunteers were examined. Age and sex ratio were comparable between the groups. Biochemical and clinical blood tests, levels of cortisol, ACTH, DHEA-C were evaluated. The insulin tolerance test (ITT) was performed for all patients and 11 volunteers.

RESULTS

The prevalence of SAI by ITT was 45.2%. The levels of basal cortisol (BC) were significantly higher in patients without SAI in comparison with the SAI group and volunteers (505 [340; 650] vs 323 [233; 382] and 372 [263; 489] nmol / l; pSAI- without_SAI=0.001; pwihtout_SAI-healthy = 0.04). The SAI group had DHEA-C significantly lower than in other groups one (3.1 [1.8; 3.4] vs 5.1 [2.5; 6.4] and 6.8 [4.1; 8.9]; рSAI- without_SAI = 0.036; pSAI-healthy = 0.001). ROC analysis showed that BC and DHEA-S can be used as high-quality screening tests for SAI (AUC = 89.3% and 88.3%). The maximum level of cortisol (656 [608-686] vs 634 [548-677]; p = 1) and the time of its increase (45 and 60 min) did not differ during ITT in patients without SAI and volunteers. Side effects: delayed hypoglycemia occurred in 4/14 patients of the SAI group 4090 minutes late of injection 60-80 ml of 40% glucose solution for stopping hypoglycemia in the test.

CONCLUSIONS

45.2% of patients followed craniospinal irradiation had SAI that is characterized by a decrease in DHEA-C levels. A highly normal level of basal cortisol was observed in 45% of patients without SAI. DHEA-C and blood cortisol can be used for SAI screening.