Deciphering molecular mechanisms underlying chemoresistance in relapsed AML patients: towards precision medicine overcoming drug resistance

Abstract

Background: Acute myeloid leukemia (AML) remains a devastating disease with a 5-year survival rate of less than 30%. AML treatment has undergone significant changes in recent years, incorporating novel targeted therapies along with improvements in allogeneic bone marrow transplantation techniques. However, the standard of care remains cytarabine and anthracyclines, and the primary hindrance towards curative treatment is the frequent emergence of intrinsic and acquired anticancer drug resistance. In this respect, patients presenting with chemoresistant AML face dismal prognosis even with most advanced therapies. Herein, we aimed to explore the potential implementation of the characterization of chemoresistance mechanisms in individual AML patients towards efficacious personalized medicine.

Methods: Towards the identification of tailored treatments for individual patients, we herein present the cases of relapsed AML patients, and compare them to patients displaying durable remissions following the same chemotherapeutic induction treatment. We quantified the expression levels of specific genes mediating drug transport and metabolism, nucleotide biosynthesis, and apoptosis, in order to decipher the molecular mechanisms underlying intrinsic and/or acquired chemoresistance modalities in relapsed patients. This was achieved by real-time PCR using patient cDNA, and could be readily implemented in the clinical setting.

Results: This analysis revealed pre-existing differences in gene expression levels between the relapsed patients and patients with lasting remissions, as well as drug-induced alterations at different relapse stages compared to diagnosis. Each of the relapsed patients displayed unique chemoresistance mechanisms following similar treatment protocols, which could have been missed in a large study aimed at identifying common drug resistance determinants.

Conclusions: Our findings emphasize the need for standardized evaluation of key drug transport and metabolism genes as an integral component of routine AML management, thereby allowing for the selection of treatments of choice for individual patients. This approach could facilitate the design of efficacious personalized treatment regimens, thereby reducing relapse rates of therapy refractory disease.

Keywords: AML; Chemotherapy; Drug metabolism; Intrinsic/acquired chemoresistance; Precision medicine; Relapse; Resistance modalities.

Fig. 1

Patient 1 timeline. Depiction of all treatment courses and subsequent outcomes of patient 1, showing the stages from which specimens were obtained for analysis. Abbreviations: DNR, daunorubicin; Ara-C, Cytarabine; HiDAC, high dose Ara-C; HSCT, hematopoietic stem cell transplantation; MX, mitoxantrone; VP-16, etoposide; VEN, venetoclax

Fig. 2

Expression levels of nucleoside influx transporters and nucleoside salvage pathway enzymes. RNA was purified from AML patient specimens using tri reagent as described in the Methods section. Gene expression levels were determined using quantitative RT-PCR. a, b Comparison of the expression levels at diagnosis in patients with good response to chemotherapy (GR1-5) and in relapsed patients (P1-D and P2-D). The results are presented as fold over GUSB which served as an internal control. c, d Comparison of the expression levels at the diagnosis and relapse stages in the relapsed patients. Results shown are normalized to GUSB which served as an internal control, and presented as fold over the expression levels of P1-D

Fig. 3

Correlation of gene expression levels with overall survival in AML. The GEPIA2 server was used to generate correlation analyses between gene expression levels in AML bone marrow specimens from the cancer genome atlas (TCGA) and overall patient survival. Gene expression levels were normalized to POLR1D

Fig. 4

RNA expression of drug efflux transporters, lysosomal proteins and cholesterol biosynthesis enzymes. RNA was purified from AML patient specimens using tri reagent, and gene expression levels were evaluated using quantitative RT-PCR, as described in the Methods section. Gene expression levels in relapsed patients (P1 and P2) at the different stages of their disease were compared to those in patients with good response to chemotherapy (GR1-5) at diagnosis. a–c Multidrug resistance efflux transporters, d Lysosomal proteins, and e Cholesterol biosynthesis enzymes. The results are displayed as fold over the internal control, GUSB

Fig. 5

RNA expression of genes encoding for anti-apoptotic proteins. RNA was purified from AML patient specimens using tri reagent, and gene expression levels were quantified using RT-PCR as described in the Methods section. The expression levels of Bcl-2 (a), Bcl-XL (b), and Mcl-1 (c) in relapsed patients (P1 and P2) at different stages of their disease, were compared to those in patients with good response to chemotherapy (GR1-5) at diagnosis. The results are presented as fold over the internal control, GUSB

Fig. 6

RNA expression of de novo nucleotide biosynthesis pathway (DNSP) and folate metabolism genes. RNA was purified from AML patient specimens using tri reagent as described in the Methods section. Gene expression levels were evaluated using quantitative RT-PCR in relapsed patients (P1 and P2) at the different stages of their disease. The results are normalized to GUSB which served as an internal control, and presented as fold over P1-D

Fig. 7

Patient 2 timeline. Depiction of all treatment courses and subsequent outcomes of patient 2, showing the stages from which specimens were derived for analysis. Abbreviations: DNR, daunorubicin; Ara-C, Cytarabine; HiDAC, high-dose Ara-C; MX, mitoxantrone; VP-16, etoposide; HSCT, hematopoietic stem cell transplantation; GO, gemtuzumab ozogamicin; MTX, methotrexate; CAR, chimeric antigen receptor

Fig. 8

Summary of the chemotherapeutic treatments and consequent gene expression alterations. This scheme showcases the potential associations between specific drug treatments and gene expression changes which possibly conferred drug resistance and contributed to relapse. The assignment of changes to specific stages in P1 is only implied, as the relapse specimen was obtained after all of the treatments. Chemotherapeutic drugs that plausibly induced remission are denoted in green