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Developing targeted therapies for neuroblastoma by dissecting the effects of metabolic reprogramming on tumor microenvironments and progression

This repo includes the core data of our study, other data would be accessed upon reasonable request.

A typical example of our validation works [immune microenvironment validation]

Employing Singscore to validate ssGSEA-based results of immune microenvironment

In the present study, we evaluated the immune cell infiltration of NBL using ssGSEA and came to the following conclusions:

Among 28 immune cellular components, 14 presented significantly reduced infiltration abundance in the MPS-I NBL group (Figure 6 A). These cell types included T helper 2 (Th2) cells (log2 Fold-change: -0.08), neutrophils (-0.09), T cell co-inhibition (-0.11), check-point (-0.11), interstitial dendritic cells(iDCs, -0.11), tumor infiltrating lymphocyte (TIL, -0.13), C-C chemokine receptor (CCR, -0.13), inflammation-promoting (-0.15), T helper 1 (Th1) cells (-0.15), cytolytic activity (-0.18), mast cells(-0.21), T cell co-stimulation(-0.21), antigen presenting cells (APC) co-stimulation(-0.27), and dendritic cells (DCs, -0.31), as shown in Figure 6 B and Table S11. Additionally, there was a positive correlation between the infiltration abundance of these 14 cellular components and all of these cellular components had a negative correlation with the MPS score, indicating that these immune cell components interact dynamically during NBL progression (Figure 6 C). Collectively, such a significant differential profile in infiltration abundance and dynamic interaction network of key immune cells could indicate the cellular mechanisms underlying the malignant progression of MPS-I NBL, eventually forming a specific immunosuppressive microenvironment that highly potentiates the poor prognosis of MPS-I NBL.

To further critically validate the results of ssGSEA, we used singscore to reassess the immune cell infiltration of neuroblastoma.

Singscore is a simple single-sample gene signature scoring method that uses rank-based statistics to analyze the sample's gene expression profile. It scores the expression activities of gene sets at a single-sample level.

Singscore confirmed the immunosuppressive microenvironment of MPS-I NBL, which is similar to ssGSEA results

Utilizing a gene set and normalization function analogous to those employed in ssGSEA analyses, Singscore meticulously evaluated the infiltration of immune cells within neuroblastoma. Our findings indicate a marked similarity between the immune cell infiltration profiles of neuroblastoma as discerned through Singscore and ssGSEA. Out of the 14 differentially infiltrated immune cell types identified via ssGSEA, Singscore was able to confirm 13 (Table. 1 and Table. 2). Only Mast_cells could not be identified.

Table. 1 ssGSEA results

Cell MeanTrain.high MeanTrain.low log2FC.Train pTrain WTrain pTest WTest MeanTest.high MeanTest.low log2FC.Test
APC_co_stimulation 0.4514 0.5458 -0.2740 7.26E-13 6724 4.59E-12 7056 0.4450 0.5384 -0.2748
CCR 0.4341 0.4750 -0.1297 9.99E-13 6760 3.15E-10 7574 0.4324 0.4695 -0.1190
Check-point 0.4053 0.4363 -0.1063 5.57E-07 8506 0.000153 9645 0.4063 0.4298 -0.0809
Cytolytic_activity 0.4732 0.5355 -0.1784 1.67E-05 9082 6.63E-05 9477 0.4685 0.5367 -0.1962
DCs 0.3545 0.4391 -0.3085 1.29E-07 8280 3.19E-06 8924 0.3528 0.4262 -0.2729
iDCs 0.1911 0.2066 -0.1131 0.002849 10167.5 0.039349 11071.5 0.2012 0.1907 0.0780
Inflammation-promoting 0.4753 0.5277 -0.1510 1.95E-05 9110 0.000762 9992 0.4719 0.5171 -0.1320
Mast_cells 0.2423 0.2808 -0.2128 0.040060 10932 0.014358 10751 0.2361 0.2705 -0.1965
Neutrophils 0.5015 0.5326 -0.0870 2.80E-08 8056 2.84E-06 8904 0.5005 0.5276 -0.0758
T_cell_co-inhibition 0.3649 0.3925 -0.1052 9.94E-05 9421 0.001504 10151 0.3606 0.3812 -0.0803
T_cell_co-stimulation 0.4004 0.4645 -0.2142 2.97E-09 7744 9.77E-09 8034 0.3916 0.4563 -0.2206
Th1_cells 0.3531 0.3921 -0.1512 7.08E-05 9354 7.67E-06 9076 0.3397 0.3876 -0.1904
Th2_cells 0.5130 0.5434 -0.0832 0.001607 10027 0.000411 9854 0.5090 0.5405 -0.0868
TIL 0.4763 0.5201 -0.1270 2.48E-06 8749 0.000173 9670 0.4727 0.5062 -0.0988

Table. 2 Singscore results

Cell MeanTrain.high MeanTrain.low log2FC.Train pTrain WTrain pTest WTest MeanTest.high MeanTest.low log2FC.Test
APC_co_stimulation 0.4379 0.5233 -0.2570 4.38E-12 6929.5 2.63E-11 7264 0.4322 0.5153 -0.2538
CCR 0.3878 0.4265 -0.1370 5.27E-12 6951 1.85E-09 7806 0.3865 0.4202 -0.1204
Check-point 0.3900 0.4208 -0.1098 1.91E-06 8706 0.000317 9798 0.3908 0.4140 -0.0833
Cytolytic_activity 0.4618 0.5136 -0.1536 4.82E-05 9279.5 0.000267 9761 0.4612 0.5148 -0.1585
DCs 0.3485 0.4251 -0.2865 3.11E-06 8787 6.84E-05 9483 0.3487 0.4128 -0.2434
iDCs 0.2024 0.2299 -0.1837 0.002679 10152.5 0.037736 11057.5 0.2147 0.2143 0.0030
Inflammation-promoting 0.4561 0.5051 -0.1470 8.46E-05 9389 0.002681 10293 0.4534 0.4933 -0.1218
Neutrophils 0.4554 0.4813 -0.0797 2.89E-06 8775 1.22E-05 9159.5 0.4526 0.4772 -0.0764
T_cell_co-inhibition 0.3581 0.3870 -0.1118 0.000141 9491.5 0.006026 10504.5 0.3540 0.3734 -0.0769
T_cell_co-stimulation 0.3959 0.4587 -0.2122 4.63E-09 7804 2.69E-08 8178 0.3880 0.4503 -0.2150
Th1_cells 0.3319 0.3652 -0.1382 0.001336 9983 0.000461 9879.5 0.3192 0.3598 -0.1727
Th2_cells 0.4520 0.4882 -0.1113 0.000411 9716 0.000929 10037.5 0.4501 0.4824 -0.1001
TIL 0.4683 0.5095 -0.1215 9.69E-06 8984 0.000396 9846 0.4645 0.4952 -0.0924

The altas of these 14 immune cells identified by singscore was also similar to ssGSEA results (Figure. 1 and 2)

Figure. 1 ssGSEA results Figure. 2 singscore GSresults

These results confirmed the reliability of our previous data