FGFR1 is upregulated in T-ALL and associated with dismal prognosis in patients
To identify potential targets for the treatment of T-ALL, we analyzed gene expression profiles of our previous T-ALL cohort 39 and another T-ALL RNA-seq dataset 40, and identified 226 genes and 264 genes that were upregulated in T-ALL respectively (Fig. 1a and Supplementary Fig. 1a). 35 common genes were shared by both upregulated groups, several of which were involved in the progression of T-ALL as previous reported, such as STMN1, CD99, SOX4, MYB, CDK6 and TOX (Supplementary Fig. 1b). However, the functional roles of FGFR1, one of the significantly upregulated 35 genes, remains largely unclear in T-ALL. (Fig. 1b, c). We detected the expression of the FGFR family (FGFR1-4) in T-ALL and found that only FGFR1 was expressed in T-ALL (Supplementary Fig. 1c).
Next, we confirmed that FGFR1 was upregulated in T-ALL cell lines and primary T-ALL blasts compared to normal T cells at both transcription and translation levels (Fig. 1d, e). Since the upregulation of FGFR1 has been reported in numerous malignancies 41, we summarized the transcription level of FGFR1 in various types of leukemia or lymphoma through the Cancer Cell Line Encyclopedia database (CCLE), and revealed that the FGFR1 was highest expressed in T-ALL compared with other hematopoietic malignancies (Fig. 1f). Subsequently, we identified that the expression of FGFR1 in relapsed T-ALL samples was not significantly reduced compared to the primary T-ALL blasts (Supplementary Fig. 1d), indicating that the FGFR1-directed therapy also has therapeutic potential in relapsed T-ALL patients. Importantly, T-ALL patients with higher FGFR1 expression were more prone to relapse or other adverse events and had shorter survival time than patients with lower FGFR1 expression (TARGET, phs000464) (Fig. 1g, h). The comparable results were observed in a B-ALL cohort (TARGET, phs000463) (Supplementary Fig. 1e, f). Taken together, FGFR1 was substantially elevated in T-ALL and negatively related to the prognosis of the T-ALL patients.
FGFR1 is a potential therapeutic target in T-ALL but leukemia cells are resistant to FGFR1 inhibitors
Next, we examined the functional roles of FGFR1 in T-ALL. After silencing the FGFR1 in human T-ALL cell lines through RNA interference, the proliferation and survival of T-ALL cells were impaired observably (Fig. 2a-d). Then, we inhibited the function of FGFR1 through its inhibitors, and found that all T-ALL cell lines were insensitive to FGFR1 inhibitor AZD4547 (IC50 > 3 µM) and did not even respond to another FGFR1 inhibitor PD-166866 compared to normal T cells (low FGFR1 expression) (Fig. 1e, f). To further evaluate the anti-T-ALL efficiency of blocking FGFR1 in vivo, we established cell-derived xenograft (CDX) based on fluorescence-labeled Jurkat or FGFR1-knockdown Jurkat cells, As the schematic diagram showing, AZD4547 (30 mg/kg/2 days) or PD-166866 (30 mg/kg/2 days) was administrated from day 14 to day 28 (Fig. 2g). Both AZD4547 and PD-166866 did not suppress the growth of human T-ALL cells, while the FGFR1 knockdown significantly inhibited the progression of T-ALL cells in vivo (Fig. 2h, i). Similarly, the survival time of mice was extended in the FGFR1 knockdown group, but not in the AZD4547 or PD-166866 treatment groups (Fig. 2j). We also analyzed the bone marrow invasion in CDX through flow cytometry analysis, and found that both of the FGFR1 inhibitors could not significantly prevent the leukemia cells invading to bone marrow compared to FGFR1 knockdown group (Fig. 2k, l). Together, FGFR1 was essential for T-ALL progression but the leukemia cells were resistant to FGFR1 inhibitors.
Atf4 Is Essential For The Resistance Against Fgfr1 Inhibitors
To comprehend the mechanism under the resistance of T-ALL cells against FGFR1 inhibitors, we performed RNA-seq in Jurkat cells after FGFR1 knockdown or treatment with FGFR1 inhibitors. The differentially expressed genes (DEGs) compared with the control group were summarized in the heatmap, and the DEGs were similar between AZD4547 and PD-166866 treatment groups (Fig. 3a). Only 28 DEGs co-changed in all three groups, while 598 common DEGs were shared in FGFR1 inhibitors treated groups (Fig. 3b), suggesting that the 570 DEGs had potential relevance to the FGFR1 inhibitors resistance. These 570 DEGs were significantly enriched in several pathways about survival-promoting metabolism, including amino acid metabolism, carbon metabolism and glucose, and fructose metabolism (Fig. 3c). Whereas, the pathways enriched of the DEGs in FGFR1 knockdown group were the transcriptional misregulation in cancer and FoxO signaling pathway, which were related to gene expression and cell fate decisions 42, 43, which were dramatically different from those pathways in the groups of FGFR1 inhibitors (Supplementary Fig. 2a).
To enquire whether there was a sponsor gene to drive these transformations of 570 DEGs, we analyzed the upstream transcription factors (TFs) through ChEA3 30. Among the predicted TFs, ATF4 scored the highest with the minimum p-value (1.82×10− 16) and maximum genes coverage (Fig. 3d). However, the TFs enriched by DEGs in FGFR1 knockdown group were obviously distinct (Supplementary Fig. 2b). We also examined the Transcripts Per Million (TPM) of ATF4 in different groups of RNA-seq and found that the ATF4 highly increased in both AZD4547 and PD-166866 treatment groups, while not in FGFR1 knockdown group (Fig. 3e). The transcription and protein levels of ATF4 was gradually increased over time after AZD4547 and PD-166866 treatment in human T-ALL cell lines (Fig. 3f-h). However, we found that ATF4 did not elevate in FGFR1 knockdown Jurkat cells, indicating that the upregulated of ATF4 was not due to functional deficiency of FGFR1 (Fig. 3i). The Jurkat cells were more sensitive to AZD4547 after ATF4 knockdown compared with the control group (Fig. 3j). To amplify the feature and make it feasible to identify critical factors of drug resistance, we further developed a more resistant Jurkat cell line (Jurkat-AZD) through continuously exposing to AZD4547 for a long time (Supplementary Fig. 2c, d). Consistently, the Jurkat-AZD cells became less resistant to AZD4547 after ATF4 knockdown (Fig. 3k). These results indicated that ATF4 was important for the resistance to FGFR1 inhibitors in T-ALL cells.
Atf4 Is Induced By Enhanced Chromatin Accessibility Combined With Gcn2-mediated Translational Activation
To investigate the molecular mechanism behind ATF4 upregulation after FGFR1 inhibitors treatment, we performed ATAC-seq with high spatial resolution. Overall, the average ATAC-seq signal around the transcription start sites (TSSs) was increased after AZD4547 treatment (Fig. 4a, b). The distribution of the average ATAC-seq signal in different regions also changed, especially increased in the regions of promotors (Fig. 4c). We identified the significant active TFs (top 20) based on RNA-seq data (Fig. 4d), and screened the motifs of transcription factors that significantly enriched in the regions of promotors by ATAC-seq data synchronously (Fig. 4e). Together with 570 DEGs in both FGFR1 inhibitors groups, we found that only two common TFs were shared in all three groups, one was ATF4 (Fig. 4f). These results were consistent with our above data that ATF4 was at the vital place for initiating these transcriptional changes. Subsequently, we examined the change in the ATF4 promotor region and found the chromatin accessibility was enhanced after AZD4547 treatment (Fig. 4g), as well as in the promotor region of ASNS, which was the direct target gene of ATF4 (Fig. 4h). These data indicated that increased chromatin accessibility in its promotor region was a potential cause of the transcriptional upregulation of ATF4.
The translation of ATF4 could be induced by eIF2α through integrated stress response (ISR) when cells suffered multiple survival pressures 44. Amino acid deprivation and endoplasmic reticulum (ER) stress could activate eIF2α through GCN2 and PERK respectively, which were closely related to amino acid metabolism and proteostasis 45. Here, we examined the possible involvement of these stress-related kinases in the initiation of ATF4 translation. Based on 570 DEGs from RNA-seq, we observed that the amino acid deprivation pathway was highly enriched, which is closely related to the GCN2 kinase (Fig. 4i). The increase of ATF4 was ceased after GCN2 knockdown (Fig. 4j), but not entirely suppressed after PERK knockdown (Fig. 4k). We further functionally determined the role of GCN2 in drug resistance, found that Jurkat cells were more sensitive to AZD4547 with GCN2 knockdown (Fig. 4l), but not with PERK knockdown (Data not shown). Similar results were obtained when we combined AZD4547 with SP600125 (a GCN2 inhibitor) 46, 47 (Fig. 4m). These results indicated that the translational upregulation of ATF4 mediated by AZD4547 was mainly due to GCN2-eIF2α pathway.
Atf4 Is A Crucial Initiator To Drive The Reprogramming Of Amino Acid Metabolism
We have indicated that the DEGs in the groups of FGFR1 inhibitors were enriched in metabolic pathways (Fig. 3c) and identified that the ATF4 was the initiator of these transformations (Fig. 3d and Fig. 4f). We further identified that these typical DEGs mainly divided into three categories, including kinases about metabolism, transporter, and aminoacyl-tRNA biosynthesis, and all of these DEGs were significantly elevated in both groups of FGFR1 inhibitors (Fig. 5a). mRNA levels of these typical genes were dramatically increased, and chromatin accessibility around some of these genes was enhanced after AZD4547 treatment (Supplementary Fig. 3a-d). The upregulated expression of mRNAs was blocked after knockdown of ATF4 (Fig. 5b-d). Next, we selected several typical genes to confirm the tendencies in the protein levels, and found that the protein levels of ASNS, ASS1, PHGDH, and SLC1A5 were significantly increased, with the protein of ATF4 increasing ahead of these proteins (Fig. 5e), Besides, these upregulations of proteins were similar in the more resistant Jurkat cells (Jurkat-AZD) (Fig. 5f). These AZD4547 induced upregulations were also interdicted after ATF4 knockdown (Fig. 5g). Together, the upregulations of these metabolic genes were induced by ATF4 when cells exposed to FGFR1 inhibitors.
Since these typical DEGs had relevance to amino acid biosynthesis and uptake, we next quantified the intracellular amino acids and their metabolites through the targeted metabolomics analysis (Supplementary Table 1). Plentiful amino acids and metabolites significantly increased in the more resistant Jurkat cells (Jurkat-AZD) and came down after ATF4 knockdown. Especially, Asn, Arg and other essential amino acids (EAAs) that were related to ASNS, ASS1, and SLC1A5 (Fig. 5h and Supplementary Fig. 3e). Subsequently, we systematically revealed that these differential amino acids, and found these differential metabolites were mainly enriched in the pathways about central carbon metabolism (related to PHGDH 48), alanine/aspartate/glutamate/glycine/serine/ threonine metabolism, mineral absorption and TCA cycle, all of which were essential for cell survival and proliferation 49. Importantly, these metabolic pathways were enhanced in the more resistant Jurkat cells (Jurkat-AZD) and fell back after ATF4 knockdown (Fig. 5h), suggesting that ATF4 upregulated the intracellular quantities of amino acids under FGFR1 inhibitor treatment.
Targeting Mtor Could Overcome The Resistance Against Fgfr1 Inhibitors
To investigate the strategy of concomitant medications to overcome this resistance therapeutically, we performed drug screening (2059 approved drugs). After two rounds of screening, 30 drugs that had synergistic effects with AZD4547 were identified with the coefficient of drug interaction (CDI) < 1 38 (Fig. 6a, Supplementary Table 2). The targets of these drugs were significantly enriched in angiogenesis and PI3K/Akt/mTOR signaling (Fig. 6b). Since the PI3K/Akt/mTOR pathway was relevant to amino acid metabolism 50, we focused on this pathway and found all of these three drugs (Temsirolimus, Rapamycin, and Zotarolimus) were the inhibitors of mTOR (Fig. 6c).
After further verification, we found that the combination of Rapamycin and AZD4547 could significantly inhibit the viability of T-ALL cells, including Jurkat (CDI minimum = 0.12), MOLT-4 (CDI minimum = 0.35) and MOLT-16 (CDI minimum = 0.45) (Fig. 6d and Supplementary Fig. 4a, b). However, PKI-587, a PI3K inhibitor, did not exhibit obvious synergy with AZD4547 (Supplementary Fig. 4c), indicating that the mTOR pathway, not the PI3K/AKT pathway, contributed to the FGFR1 drug resistance. We also found that the Jurkat-AZD cells were more sensitive to Rapamycin (Fig. 6e). These results indicated that mTOR was an indispensable effector for drug resistance, and the resistance to FGFR1 inhibitors could enhance the sensibility of cells to Rapamycin. We further found that ATF4 was induced by FGFR1 inhibitors in other FGFR1-upregulated malignancies, such as NCI-H1299 (NSCLC), OVCAR-8 (ovarian cancer), and SW620 (colorectal cancer) cells (Supplementary Fig. 4d, e), and the strategy of concomitant drugs was also applicable to these cell lines (Supplementary Fig. 4f-h). These suggested that the resistance to FGFR1 inhibitors mediated by ATF4 was universal and that targeting mTOR could overcome this resistance synergistically.
To further confirm the synergistic effect in vivo, we established the Jurkat-luci cell-derived xenograft mouse models (CDX). AZD4547 (30 mg/kg/2 days), Rapamycin (3 mg/kg/2 days) or the combination of these two drugs were administrated from day 17 to 29 intraperitoneally (Fig. 6f). The T-ALL progression in the combination group was significantly inhibited compared with other groups (Fig. 6g, h). The combination of AZD4547 and Rapamycin prolonged the survival time of the CDX (Fig. 6i), and significantly reduced the bone marrow invasion of T-ALL cells (Fig. 6j, k). Together, our data indicated that synergistically targeting FGFR1 and mTOR could inhibit the progression of T-ALL cells in vitro and in vivo.
Reprogramming Of Amino Acid Metabolism Induces The Activation Of Mtorc1
The synergistic effect of AZD4547 and Rapamycin suggested that there might exist a compensatory activation of mTOR. We further monitored the phosphorylation ribosome protein S6 (p-S6), a reliable marker of mTORC1 activation, for a long time with AZD4547 treatment. The phosphorylation of S6 was decreased in the first few days, but restored after a long time under AZD4547 treatment (Fig. 7a). We further used the more resistant Jurkat cells (Jurkat-AZD) to amplify the feature of drug resistance and identified the crucial factors, found that the phosphorylation of S6 did not reduce in the more resistant Jurkat cells (Jurkat-AZD) compared to Jurkat cells under AZD4547 treatment (Fig. 7b). Since the ribosome protein S6 is involved with translation, we also found of translational efficiency of total proteins was impaired in Jurkat cells, but did not decrease in the more resistant Jurkat cells (Jurkat-AZD) (Supplementary Fig. 5a, b). These results highlighted that the compensatory activation of mTORC1 was essential for the resistance to FGFR1 inhibitors.
To explore the connection between amino acid metabolism and the activation of mTORC1, we knockdown the ATF4 in the more resistant Jurkat cells (Jurkat-AZD), which had high ATF4 expression, found the phosphorylation of S6 and typical proteins (ASNS, ASS1, SLC1A5, and PHGDH) were significantly reduced (Fig. 7c). The translational efficiency was dramatically reduced after ATF4 knockdown in both cell lines (Supplementary Fig. 5c). Importantly, we found the phosphorylation of S6 was significantly decreased after knockdown of ASNS, ASS1, SLC1A5, and PHGDH respectively. The Jurkat-AZD cells became more sensitive to AZD4547 and PD-166866 (Fig. 7d-g and Supplementary Fig. 5d-g). In summary, the reprogramming of amino acid metabolism induced the activation of mTORC1 and further contributed to resistance against FGFR1 inhibitors.