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pmid:39872530

Identification and validation of BATF as a prognostic biomarker and regulator of immune cell infiltration in acute myeloid leukemia.

Zhe Zhao · Dongmei Wang · Xue Sheng · Shuying Li · Tingting Liu · Mengyuan Chang · Lei Feng · Di Zhang · Chunyan Ji · Fei Lu · Jingjing Ye

Frontiers in immunology · 2024 doi:10.3389/fimmu.2024.1429855

Paper

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Experiment

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Data

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pmid:39872530
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science-record
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2026-11-01T20:30:09Z
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2026-11-01T22:13:34Z
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paper object · 10 fields
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title
Identification and validation of BATF as a prognostic biomarker and regulator of immune cell infiltration in acute myeloid leukemia.
doi
10.3389/fimmu.2024.1429855
pmid
39872530
authors array · 11 items
[0]
Zhe Zhao
[1]
Dongmei Wang
[2]
Xue Sheng
[3]
Shuying Li
[4]
Tingting Liu
[5]
Mengyuan Chang
[6]
Lei Feng
[7]
Di Zhang
[8]
Chunyan Ji
[9]
Fei Lu
[10]
Jingjing Ye
journal
Frontiers in immunology
year
2024
abstract
Background: Basic leucine zipper ATF-like transcription factor (BATF) is a nuclear basic leucine zipper protein affiliated with the AP-1/ATF superfamily. Previous research has confirmed that BATF expression plays a significant role in the tumour microenvironment. However, the associations between BATF expression and prognoses in acute myeloid leukaemia (AML) patients and their immunological effects remain unclear. Methods: Genomic and clinical AML data were got from the TCGA (TCGA-LAML) and GEO (GSE37642) databases for the subsequent analysis. The expression levels of BATF in AML patients were assessed using GEPIA, and the results were verified by qRT-PCR and Western blotting. In the meantime, the prognostic value of BATF was evaluated using univariate and multivariate analyses, receiver operating characteristic (ROC) curve (AUC) analysis, and Kaplan-Meier (KM) survival analysis. EdU, colony formation, and CCK-8 assays were employed to evaluate the proliferation of cells. Moreover, we detected the association of BATF expression with drug sensitivity through database analysis and in vivo experiments. To further investigate the mechanism of action of BATF in AML, RNA sequencing (RNA-seq) analysis was performed, followed by pathway enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Meanwhile, we detected the connection between BATF expression and the proportions of immune cells via flow cytometry in C1498 mouse model of AML. Finally, we investigated the association between BATF expression and cell-cell communication within the AML cell population using single-cell sequencing. Results: In this study, we thoroughly investigated the role of BATF in AML. First, we observed a significant elevation in the expression of BATF in patients and cells in AML. Further analysis revealed an association between high BATF expression and poor prognosis in AML. Additionally, BATF expression was found to promote the proliferative capacity of AML cells. Moreover, the results showed that the expression level of BATF dramatically affected the effect of chemotherapy in AML patients. We also discovered that BATF expression could activate multiple immune-related pathways, altering the proportions of CD8+T cells and NK cells, suggesting that BATF may be a regulator of immune cell infiltration. Finally, there were differences in receptor ligand pairs between AML cells with high and low expression of BATF and immune cells. Conclusion: Bioinformatics analysis and experimental verification revealed that BATF expression could alter the proportions of CD8+T cells and NK cells in AML and affect drug sensitivity, making it a potential treatment target for AML.
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Based on the GDSC database, antitumour drug response was predicted by the R package “OncoPredict” for each AML patient with high and low expression.
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sections[6] "Immune checkpoint genes and drug sensitivity analysis" paragraph 2
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Based on the GDSC database, antitumour drug response was predicted by the R package “OncoPredict” for each AML patient with high and low expression.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
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sections[26] "Data availability statement" paragraph 2
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
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https://doi.org/10.3389/fimmu.2024.1429855
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
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[480]
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[485]
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[490]
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[492]
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[493]
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[494]
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[495]
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[496]
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[497]
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[498]
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[499]
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[500]
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[501]
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[502]
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[503]
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[504]
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[505]
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[506]
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[507]
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[508]
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[509]
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[510]
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[511]
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[512]
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[513]
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[514]
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[515]
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[516]
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[517]
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[518]
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[519]
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[520]
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[521]
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[522]
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[523]
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[524]
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[525]
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[526]
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[527]
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[528]
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[529]
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[530]
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[531]
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[532]
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[533]
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[534]
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[535]
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[536]
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[537]
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[538]
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[539]
GSM924135
[540]
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[541]
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[542]
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[543]
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[544]
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[545]
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[546]
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[547]
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[548]
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[549]
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[550]
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[551]
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[552]
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[553]
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[554]
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[555]
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[556]
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[557]
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[558]
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[559]
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[560]
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[561]
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[562]
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[563]
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[564]
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[565]
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[566]
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[567]
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[568]
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[569]
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[570]
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[571]
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[572]
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[573]
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[574]
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[575]
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[576]
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[577]
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[578]
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[579]
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[580]
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[581]
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[582]
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[583]
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[584]
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[585]
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[586]
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[587]
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[588]
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[589]
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[590]
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[591]
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[592]
GSM924188
[593]
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[594]
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[595]
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[596]
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[597]
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[598]
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[599]
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[600]
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[601]
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[602]
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[603]
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[604]
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[605]
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[606]
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[607]
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[608]
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[609]
GSM924205
[610]
GSM924206
[611]
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[612]
GSM924208
[613]
GSM924209
[614]
GSM924210
[615]
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[616]
GSM924212
[617]
GSM924213
[618]
GSM924214
[619]
GSM924215
[620]
GSM924216
[621]
GSM924217
[622]
GSM924218
[623]
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[624]
GSM924220
[625]
GSM924221
[626]
GSM924222
[627]
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[628]
GSM924224
[629]
GSM924225
[630]
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[631]
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[632]
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[633]
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[634]
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[635]
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[636]
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[637]
GSM924233
[638]
GSM924234
[639]
GSM924235
[640]
GSM924236
[641]
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[642]
GSM924238
[643]
GSM924239
[644]
GSM924240
[645]
GSM924241
[646]
GSM924242
[647]
GSM924243
[648]
GSM924244
[649]
GSM924245
[650]
GSM924246
[651]
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[652]
GSM924248
[653]
GSM924249
[654]
GSM924250
[655]
GSM924251
[656]
GSM924252
[657]
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[658]
GSM924254
[659]
GSM924255
[660]
GSM924256
[661]
GSM924257
[662]
GSM924258
[663]
GSM924259
[664]
GSM924260
[665]
GSM924261
[666]
GSM924262
[667]
GSM924263
[668]
GSM924264
[669]
GSM924265
[670]
GSM924266
[671]
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[672]
GSM924268
[673]
GSM924269
[674]
GSM924270
[675]
GSM924271
[676]
GSM924272
[677]
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[678]
GSM924274
[679]
GSM924275
[680]
GSM924276
[681]
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[682]
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[683]
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[684]
GSM924280
[685]
GSM924281
[686]
GSM924282
[687]
GSM924283
[688]
GSM924284
[689]
GSM924285
[690]
GSM924286
[691]
GSM924287
[692]
GSM924288
[693]
GSM924289
[694]
GSM924290
[695]
GSM924291
[696]
GSM924292
[697]
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[698]
GSM924294
[699]
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[700]
GSM924296
[701]
GSM924297
[702]
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[703]
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[704]
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[705]
GSM924301
[706]
GSM924302
[707]
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[708]
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[709]
GSM924305
[710]
GSM924306
[711]
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[712]
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[713]
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[714]
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[715]
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[716]
GSM924312
[717]
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[718]
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[719]
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[720]
GSM924316
[721]
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[722]
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[723]
GSM924319
[724]
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[725]
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[726]
GSM924322
[727]
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[728]
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[729]
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[730]
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[731]
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[732]
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[733]
GSM924329
[734]
GSM924330
[735]
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[736]
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[737]
GSM924333
[738]
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[739]
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[740]
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[741]
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[742]
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[743]
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[744]
GSM924340
[745]
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[746]
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[747]
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[748]
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[749]
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[750]
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[751]
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[752]
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[753]
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[754]
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[755]
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[756]
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[757]
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[758]
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[759]
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[760]
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[761]
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[762]
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[763]
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[764]
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[765]
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[766]
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[767]
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[768]
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[769]
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[770]
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[771]
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[772]
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[773]
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[774]
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[775]
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[776]
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[777]
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[778]
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[779]
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[780]
GSM924376
[781]
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[782]
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[783]
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[784]
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[785]
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[786]
GSM924382
[787]
GSM924383
[788]
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[789]
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[790]
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[791]
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[792]
GSM924388
[793]
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[794]
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[795]
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[796]
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[797]
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[798]
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[799]
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[800]
GSM924396
[801]
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[802]
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[803]
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[804]
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[805]
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[806]
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[807]
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[808]
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[809]
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[810]
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[811]
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[812]
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[813]
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[814]
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[815]
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[816]
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[817]
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[818]
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[819]
GSM924415
[820]
GSM924416
[821]
GSM924417
[822]
GSM924418
[823]
GSM924419
[824]
GSM924420
[825]
GSM924421
[826]
GSM924422
[827]
GSM924423
[828]
GSM924424
[829]
GSM924425
[830]
GSM924426
[831]
GSM924427
[832]
GSM924428
[833]
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[834]
GSM924430
[835]
GSM924431
[836]
GSM924432
[837]
GSM924433
[838]
GSM924434
[839]
GSM924435
[840]
GSM924436
[841]
GSM924437
[842]
GSM924438
[843]
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[844]
GSM924440
[845]
GSM924441
[846]
GSM924442
[847]
GSM924443
[848]
GSM924444
[849]
GSM924445
[850]
GSM924446
[851]
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[852]
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[853]
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[854]
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[855]
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[856]
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[857]
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[858]
GSM924454
[859]
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[860]
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[861]
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[862]
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[863]
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[864]
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[865]
GSM924461
[866]
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[867]
GSM924463
[868]
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[869]
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[870]
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[871]
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[872]
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[873]
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[874]
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[875]
GSM924471
[876]
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[877]
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[878]
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[879]
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[880]
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[881]
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[882]
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[883]
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[884]
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[885]
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[886]
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[887]
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[888]
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[889]
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[890]
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[891]
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[892]
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[893]
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[894]
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[895]
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[896]
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[897]
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[898]
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[899]
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[900]
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[901]
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[902]
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[903]
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[904]
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[905]
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[906]
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[907]
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[908]
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[909]
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[910]
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[911]
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[912]
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[913]
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[914]
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[915]
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[916]
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[917]
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[918]
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[919]
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[920]
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[921]
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[922]
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[923]
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[926]
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[929]
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[931]
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[932]
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[933]
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[935]
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[936]
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[938]
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[939]
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[940]
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[942]
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[943]
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[944]
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[947]
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[953]
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[959]
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[960]
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[963]
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[965]
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[966]
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[967]
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[968]
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[969]
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[970]
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[971]
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[972]
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[973]
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[974]
GSM924570
[975]
GSM924571
[976]
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[977]
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[978]
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[979]
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[980]
GSM924576
[981]
GSM924577
[982]
GSM924578
[983]
GSM924579
sample_count
984
group_sizes
null
group_sizes_basis
null
platform
570;96;97
taxon
Homo sapiens
title
Prognostic gene signature for AML
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 2 items
[0]
asset:data:geo:GSE37642 not downloaded
[1]
asset:data:geo:GSE37642 licence not read
analysis object · 4 fields
state
partial
methods array · 7 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
kaplan_meier
label
Survival analysis
dsl_operations array · 1 item
[0]
survival_km
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.7
band
medium
quote
Kaplan-Meier
[1] object · 10 fields
id
method-2
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
Cox regression
[2] object · 10 fields
id
method-3
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
band
high
quote
log-rank
[3] object · 10 fields
id
method-4
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
pathway enrichment
[4] object · 10 fields
id
method-5
family
sequence_alignment
specific
blast
label
Sequence alignment / homology
dsl_operations array · 2 items
[0]
sequence_align
[1]
alignment_identity
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
sequence_records
evidence object · 3 fields
score
0.8
band
high
quote
blast
[5] object · 10 fields
id
method-6
family
diagnostic_evaluation
specific
roc
label
Diagnostic test evaluation
dsl_operations array · 6 items
[0]
confusion_counts
[1]
roc_curve
[2]
sensitivity_specificity
[3]
solve_confusion_matrix
[4]
classification_metrics
[5]
published_precision_envelope
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
reference_standard_and_test
evidence object · 3 fields
score
0.8
band
high
quote
ROC curve
[6] object · 10 fields
id
method-7
family
null
specific
null
label
OncoPredict
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Based on the GDSC database, antitumour drug response was predicted by the R package “OncoPredict” for each AML patient with high and low expression.
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
[0]
survival_km
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 1 item
[0]
GSE37642
resolved_accessions array · 1 item
[0]
GSE37642
statements array · 1 item
[0]
The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
basis
The paper names GSE37642 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
survival_km
assets array · 2 items
[0]
source:pmid:39872530
[1]
data:geo:GSE37642
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE37642
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-11-01T19:45:26Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
10122
completion_tokens
1930
cached_tokens
264
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:39872530
type
paper
label
pmid:39872530
[1] object · 3 fields
id
source:pmid:39872530
type
manuscript
label
PMID 39872530 full text
[2] object · 3 fields
id
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and the results were verified by qRT-PCR and Western blotting. In the meantime, the prognostic value of BA
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Figures 1B–D ). In addition, the qRT-PCR and Western blotting results also showed that BATF was overexpres
[2]
ients (n=12) and healthy controls (n=8). (D) Western blotting analysis of BATF expression in patients with
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of immune cells via flow cytometry in C1498 mouse model of AML. Finally, we investigated the associa
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ug sensitivity through database analysis and in vivo experiments. To further investigate the mech
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sm of action of BATF in AML, RNA sequencing (RNA-seq) analysis was performed, followed by pathway
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gate the mechanism of action of BATF in AML, RNA sequencing (RNA-seq) analysis was performed, followed b
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39872530", "kind": "science-record", "revision": 3, "content_hash": "sha256:33855076fd59eeb6d519071342cdf24a42538e37c2d94b14a9f49f53d5895a6a", "created_at": "2026-11-01T20:30:09Z", "updated_at": "2026-11-01T22:13:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of BATF as a prognostic biomarker and regulator of immune cell infiltration in acute myeloid leukemia.", "doi": "10.3389/fimmu.2024.1429855", "pmid": "39872530", "authors": ["Zhe Zhao", "Dongmei Wang", "Xue Sheng", "Shuying Li", "Tingting Liu", "Mengyuan Chang", "Lei Feng", "Di Zhang", "Chunyan Ji", "Fei Lu", "Jingjing Ye"], "journal": "Frontiers in immunology", "year": 2024, "abstract": "Background: Basic leucine zipper ATF-like transcription factor (BATF) is a nuclear basic leucine zipper protein affiliated with the AP-1/ATF superfamily. Previous research has confirmed that BATF expression plays a significant role in the tumour microenvironment. However, the associations between BATF expression and prognoses in acute myeloid leukaemia (AML) patients and their immunological effects remain unclear.\nMethods: Genomic and clinical AML data were got from the TCGA (TCGA-LAML) and GEO (GSE37642) databases for the subsequent analysis. The expression levels of BATF in AML patients were assessed using GEPIA, and the results were verified by qRT-PCR and Western blotting. In the meantime, the prognostic value of BATF was evaluated using univariate and multivariate analyses, receiver operating characteristic (ROC) curve (AUC) analysis, and Kaplan-Meier (KM) survival analysis. EdU, colony formation, and CCK-8 assays were employed to evaluate the proliferation of cells. Moreover, we detected the association of BATF expression with drug sensitivity through database analysis and in vivo experiments. To further investigate the mechanism of action of BATF in AML, RNA sequencing (RNA-seq) analysis was performed, followed by pathway enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Meanwhile, we detected the connection between BATF expression and the proportions of immune cells via flow cytometry in C1498 mouse model of AML. Finally, we investigated the association between BATF expression and cell-cell communication within the AML cell population using single-cell sequencing.\nResults: In this study, we thoroughly investigated the role of BATF in AML. First, we observed a significant elevation in the expression of BATF in patients and cells in AML. Further analysis revealed an association between high BATF expression and poor prognosis in AML. Additionally, BATF expression was found to promote the proliferative capacity of AML cells. Moreover, the results showed that the expression level of BATF dramatically affected the effect of chemotherapy in AML patients. We also discovered that BATF expression could activate multiple immune-related pathways, altering the proportions of CD8+T cells and NK cells, suggesting that BATF may be a regulator of immune cell infiltration. Finally, there were differences in receptor ligand pairs between AML cells with high and low expression of BATF and immune cells.\nConclusion: Bioinformatics analysis and experimental verification revealed that BATF expression could alter the proportions of CD8+T cells and NK cells in AML and affect drug sensitivity, making it a potential treatment target for AML.", "claims": [{"id": "claim-method", "statement": "Based on the GDSC database, antitumour drug response was predicted by the R package “OncoPredict” for each AML patient with high and low expression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39872530", "locator": "sections[6] \"Immune checkpoint genes and drug sensitivity analysis\" paragraph 2", "quote": "Based on the GDSC database, antitumour drug response was predicted by the R package “OncoPredict” for each AML patient with high and low expression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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In the meantime, the prognostic value of BA", "Figures 1B–D ). In addition, the qRT-PCR and Western blotting results also showed that BATF was overexpres", "ients (n=12) and healthy controls (n=8). (D) Western blotting analysis of BATF expression in patients with", "cells compared to that in control cells. (F) Western blotting analysis of BATF expression in AML cell line"], "order_basis": "paper_text_order:756", "id": "assay:1"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["urvival analysis. EdU, colony formation, and CCK-8 assays were employed to evaluate the prolife"], "order_basis": "paper_text_order:1008", "id": "assay:2"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["of immune cells via flow cytometry in C1498 mouse model of AML. Finally, we investigated the associa", "ug sensitivity through database analysis and in vivo experiments. To further investigate the mech", "of immune cells via flow cytometry in C1498 mouse model of AML. Finally, we investigated the a"], "order_basis": "paper_text_order:1184", "id": "assay:3"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["sm of action of BATF in AML, RNA sequencing (RNA-seq) analysis was performed, followed by pathway", "gate the mechanism of action of BATF in AML, RNA sequencing (RNA-seq) analysis was performed, followed b"], "order_basis": "paper_text_order:1268", "id": "assay:4"}, {"role": "data_generation", "definition_id": "flow_cytometry", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["sion and the proportions of immune cells via flow cytometry in C1498 mouse model of AML. Finally, we inv"], "order_basis": "paper_text_order:1530", "id": "assay:5"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ATCC. THP-1 and MOLM-13 cells were routinely cultured in RPMI-1640 (Gibco) with 10% FBS (Gibco). Kasu", "(Gibco). Kasumi-1, HL-60 and KG-1 cells were cultured in IMDM (Gibco) supplemented with 20% FBS. OCI-", "pplemented with 20% FBS. OCI-AML3 cells were cultured in RPMI-1640 supplemented with 20% FBS, while H"], "order_basis": "paper_text_order:3762", "id": "assay:6"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:7"}]}