Low gene expression of TNF, IL17A, IL23A, and IL12B in tumors: A safety surrogate to predict cancer survival associated with biologic therapies
Authors: Nikolai Klebanov, Lourdes M. Perez-Chada, Sameer Gupta, Alice B. Gottlieb, Joseph F. Merola
Journal: Journal of the American Academy of Dermatology (2020)

To the Editor: While tumor necrosis factor (TNF), interleukin (IL) 17, IL-23, and IL-12/23 inhibitors have revolutionized psoriasis management, their safety in patients with active or recent malignancy remains an area of unmet need.1Elmets C.A. Leonardi C.L. Davis D.M.R. et al.Joint AAD-NPF guidelines of care for the management and treatment of psoriasis with awareness and attention to comorbidities.J Am Acad Dermatol. 2019; 80: 1073-1113Abstract Full Text Full Text PDF PubMed Scopus (286) Google Scholar We explored the relationship between low expression of key genes encoding the respective targets of these biologic molecules as a surrogate for targeted biologic therapy and overall survival across multiple cancers using data from The Cancer Genome Atlas (https://www.cancer.gov/tcga). We retrieved clinical data and tumor RNA sequencing gene expression data for 31 malignancies. All patients had active cancer during sample collection. We used Cox proportional hazards to model overall survival as a function of low and high TNF, IL17A, IL23A, and IL12B expression (split by median expression value). To mitigate the false discovery rate (FDR) owing to multiple testing among distinct cancers, we applied a highly conservative FDR P value correction to the results of the multivariate hazards models after adjusting for sex, age at diagnosis, and pathologic tumor stage. After removing cohorts that had relatively low (<10th percentile) numbers of patients, 27 malignancies were evaluated (9274 patients, Table I). In general, we found a reassuring pattern of no impact on survival across multiple malignancies. Four potentially "harmful" associations were identified (Fig 1): low TNF expression in cutaneous melanoma (n = 430) had a survival hazard ratio (HR) of 1.65 (95% confidence interval [CI], 1.24-2.19; P-FDR = .017), and low TNF-expression in sarcoma (n = 262) had a HR of 1.92 (95% CI, 1.27-2.89; P-FDR = .025). Low IL12B expression in cutaneous melanoma had a HR of 1.64 (95% CI, 1.23-2.17; P-FDR = .006), and in breast invasive carcinoma (n = 1076) had a HR of 1.72 (95% CI, 1.24-2.41; P-FDR = .009).Table IClinical characteristics of cancer patient cohortsCancerTotal (N = 9274)Ex.Age at diagnosis, median (IQR), yMale, No. (%)Female, No. (%)Stage 0-II, No. (%)Stage III-IV, No. (%)Alive, No. (%)Dead, No (%)Time-to-follow-up, median (IQR), moAdrenocortical CA7749 (25)29 (38)48 (62)46 (60)31 (40)50 (65)27 (35)38.5 (45.8)Bladder CA40569 (16)299 (74)106 (26)131 (32)274 (68)228 (56)177 (44)17.6 (20.3)Breast invasive CA107659 (19)12 (1)1064 (99)792 (74)284 (26)924 (86)152 (14)28.2 (40.4)Cervical SCC29546 (18)0 (0)295 (100)229 (78)66 (22)223 (76)72 (24)21.6 (30.3)Cholangiocarcinoma36∗Cholangiocarcinoma, lymphoma, kidney chromophobe, and uterine carcinosarcoma were excluded from analysis due to low number of patients/survival events (n = <10th percentile of n).67 (16)16 (44)20 (56)28 (78)8 (22)18 (50)18 (50)21.2 (26.7)Colon adenocarcinoma18972 (17)91 (48)98 (52)109 (58)80 (42)151 (80)38 (20)24 (22.5)Diffuse large B-cell lymphoma41∗Cholangiocarcinoma, lymphoma, kidney chromophobe, and uterine carcinosarcoma were excluded from analysis due to low number of patients/survival events (n = <10th percentile of n).56 (22)18 (44)23 (56)24 (59)17 (41)34 (83)7 (17)31.7 (32.4)Esophageal CA16260 (19)138 (85)24 (15)97 (60)65 (40)97 (60)65 (40)13.4 (14.3)Glioblastoma multiforme17160 (19)111 (65)60 (35)Stage unavailableStage unavailable32 (19)139 (81)12.3 (12.3)Head and neck SCC52161 (15)385 (74)136 (26)111 (21)410 (79)300 (58)221 (42)21.2 (26.3)Kidney chromophobe65∗Cholangiocarcinoma, lymphoma, kidney chromophobe, and uterine carcinosarcoma were excluded from analysis due to low number of patients/survival events (n = <10th percentile of n).50 (19)38 (58)27 (42)45 (69)20 (31)56 (86)9 (14)73.9 (70.6)Kidney RCC53161 (18)343 (65)188 (35)325 (61)206 (39)358 (67)173 (33)39.4 (45.2)Kidney renal papillary cell CA28662 (18)211 (74)75 (26)201 (70)85 (30)242 (85)44 (15)25.2 (35.7)Acute myeloid leukemia (AML)16359 (23)88 (54)75 (46)Stage unavailableStage unavailable58 (36)105 (64)11 (21)Brain lower grade glioma (LGG)52741 (21)290 (55)237 (45)Stage unavailableStage unavailable394 (75)133 (25)23.2 (27.1)Liver HCC34661 (17)236 (68)110 (32)256 (74)90 (26)232 (67)114 (33)19 (25.7)Lung adenocarcinoma48066 (13)221 (46)259 (54)374 (78)106 (22)308 (64)172 (36)21.1 (21.6)Lung SCC48568 (11)358 (74)127 (26)395 (81)90 (19)275 (57)210 (43)21.4 (29.6)Ovarian serous CA29358 (16)0 (0)293 (100)21 (7)272 (93)115 (39)178 (61)31.6 (37.1)Pancreatic adenocarcinoma17765 (16)97 (55)80 (45)168 (95)9 (5)84 (47)93 (53)15.2 (12.8)Pheochromocytoma/paraganglioma18446 (23)82 (45)102 (55)Stage unavailableStage unavailable176 (96)8 (4)24.7 (32.3)Prostate adenocarcinoma48761 (10)487 (100)0 (0)Stage unavailableStage unavailable477 (98)10 (2)30.4 (31.4)Rectum adenocarcinoma7267 (11)39 (54)33 (46)43 (60)29 (40)63 (88)9 (13)17.5 (28.6)Sarcoma26261 (19)119 (45)143 (55)Stage unavailableStage unavailable164 (63)98 (37)31.3 (35.8)Skin cutaneous melanoma43058 (23)268 (62)162 (38)235 (55)195 (45)225 (52)205 (48)34.5 (58.8)Stomach adenocarcinoma38267 (15)243 (64)139 (36)173 (45)209 (55)232 (61)150 (39)14.8 (16.5)Thyroid carcinoma50746 (23)139 (27)368 (73)339 (67)168 (33)491 (97)16 (3)30.9 (31.9)Thymoma11960 (20)63 (53)56 (47)Stage unavailableStage unavailable110 (92)9 (8)40.1 (41.1)Endometrial CA36963 (13)0 (0)369 (100)271 (73)98 (27)310 (84)59 (16)33.4 (41.2)Uterine carcinosarcoma56∗Cholangiocarcinoma, lymphoma, kidney chromophobe, and uterine carcinosarcoma were excluded from analysis due to low number of patients/survival events (n = <10th percentile of n).69 (14)0 (0)56 (100)26 (46)30 (54)22 (39)34 (61)20 (19.3)Uveal melanoma8062 (23)45 (56)35 (44)39 (49)41 (51)57 (71)23 (29)25.8 (24.1)CA, Carcinoma; Ex., excluded; HCC, hepatocellular carcinoma; IQR, interquartile range; RCC, renal clear cell carcinoma; SCC, squamous cell carcinoma.∗ Cholangiocarcinoma, lymphoma, kidney chromophobe, and uterine carcinosarcoma were excluded from analysis due to low number of patients/survival events (n = <10th percentile of n). Open table in a new tab CA, Carcinoma; Ex., excluded; HCC, hepatocellular carcinoma; IQR, interquartile range; RCC, renal clear cell carcinoma; SCC, squamous cell carcinoma. Conversely, low expression of IL17A had no impact on cancer survival. Low IL23A expression was associated with a survival "benefit" in renal clear cell carcinoma (n = 531), with a HR of 0.53 (95% CI, 0.38-0.73; P-FDR = .003). Low IL12B was associated with benefit in brain lower-grade glioma (n = 527; HR, 0.53; 95% CI, 0.37-0.76; P-FDR = .006) and uveal melanoma (n = 80; HR, 0.17; 95% CI, 0.07-0.42; P-FDR = .004). Overall, these findings suggest safety/clinical compatibility of TNF, IL17, IL23, and IL-12/23 inhibitors with many malignancies from a mechanistic standpoint. Indeed, TNF and IL-12/23 inhibitors appear to affect the oncogenic pathways underlying only a few specific malignancies. Intriguingly, several of the associations found in our study correlate with preclinical and clinical data of malignancy risk with targeted molecules.2Montfort A. Colacios C. Levade T. Andrieu-Abadie N. Meyer N. Segui B. The TNF paradox in cancer progression and immunotherapy.Front Immunol. 2019; 10: 1818Crossref PubMed Scopus (190) Google Scholar, 3Fu Q. Xu L. Wang Y. et al.Tumor-associated macrophage-derived interleukin-23 interlinks kidney cancer glutamine addiction with immune evasion.Eur Urol. 2019; 75: 752-763Abstract Full Text Full Text PDF PubMed Scopus (124) Google Scholar, 4Lei J. Rudolph A. Moysich K.B. et al.Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy.Breast Cancer Res. 2015; 17: 18Crossref PubMed Scopus (20) Google Scholar Study limitations include that confounding by treatment could not be estimated due to limited data in The Cancer Genome Atlas. Expression of key psoriasis pathway mediators were used as proxies for the likely effects of biologics, but actual data on biologic use was not available, and the patient population was not known to have psoriasis. While tumors present a complex cytokine network, we limited our analysis to individual cytokine levels which we believe represents the closest surrogate to individual targeted cytokine therapy. Finally, we excluded proteomic data because these are inconsistently available in The Cancer Genome Atlas. However, evidence suggests that clinical phenotypic traits may correlate better with transcript rather than protein levels.5Ghazalpour A. Bennett B. Petyuk V.A. et al.Comparative analysis of proteome and transcriptome variation in mouse.PLoS Genet. 2011; 7: e1001393Crossref PubMed Scopus (458) Google Scholar This study represents a novel surrogate and conceptual approach to assessing pharmacologic safety in this population. This hypothesis-generating work should lead to mechanistic, preclinical and clinical studies to confirm our findings and, together, provide evidence to guide clinical decisions.