Prognostic Utility of the Patient-Derived AML Cells' Ex Vivo Drug Sensitivity Results

December 7, 2023

Authors: Silvia Park, Sung-Soo Park, Byoung Sik Cho, Sungwon Lim, Kwan Hyun Kim, Gyucheol Choi, Seunghyeok Ham, Seongjoon Lee, Sesun Park, Gunjae Lee, Junyoung Lee, Edward Song, Jamin Koo, Heeje Kim

Genomic mutational profiles substantially influence selection of the treatment as they impact drug responses. However, the expected response to a specific treatment based on the data from a large group of the patients with the similar mutational profile is not always equal to the actual response observed at an individual basis. In this study, we measured ex vivo sensitivity of the patient-derived AML cells to 21 different anti-cancer drugs and assessed their prognostic utility.

The ex vivo drug sensitivity analysis was performed using the bone marrow (BM) aspirates of 45 out of 58 AML patients (78%), which contained sufficient number of live cancer cells. The isolated blast cells were incubated for 72 hours with various concentrations of the 21 drugs used to treat hematologic malignancies, and changes in viability were measured using the Alamar Blue assay. For each drug, we calculated the individual patient's drug sensitivity in terms of the three metrics-IC 50 (the drug concentration to inhibit cell population by 50%), area under the curve (AUC, area under the viability curve for a cell population over the tested drug concentration range), and E max (the fraction of viable cells at the highest drug concentrations tested). In the context of drug potency, smaller values of IC 50 AUC and E max correspond to high drug sensitivities.

After sample acquisition, 14 out of 45 patients did not receive treatment while the remaining patients received the following treatments: Venetoclax plus hypomethylating agent (VEN+HMA) in either the newly diagnosed (ND) (n=9) or relapsed/refractory (R/R) setting (n=6), Anthracycline plus cytarabine(AraC) based induction (n=8) or reinduction (n=4), and others (n=4). Expectedly, the values of AUC, IC 50 and E max differed substantially across the cohort for all 21 drugs, in alignment with unequal responses and survival across the patients treated with the same regimen; the range of E max, for example, spanned 0 to 100% for 17 of the 21 drugs. We confirmed that the interpersonal differences in the drug sensitivity metrics were at least 8-fold greater than the variability observed across replicate experiments performed using the leukemia cell line HL60.

Given the various disease setting and treatment modalities, we focused on the patients receiving the VEN+HMA (n=15) and Anthra + AraC based (re)induction (n=12) for further analysis. Upon evaluating the predictive utility of the drug sensitivity metrics, we found that the E max of VEN was the most effective in predicting survival after the administration of VEN+HMA, with an ROC-AUC of 0.84. The median E max of VEN was significantly higher (38% vs 17%) among the patients who died within 2 months of the first administration (n = 4) compared to those who survived (n = 11). When stratified into the high vs low risk subgroups based on the E max of VEN, overall survival of the low risk subgroup was significantly ( P=0.0025) superior with hazard ratio of 8.9 (95% CI, 0.7 - 108.9). On the other hand, the AUC of VEN exhibited the strongest utility in predicting the response (CR(i)) to VEN+HMA therapy, with an ROC-AUC of 0.72. While the E max or AUC values of the HMA drugs did not show any strong correlation to the treatment outcomes. We observed the similar tendency for other treatments including Anthracycline + AraC; E max of idarubicin (IDA) was significantly higher (21% vs 3+1%) for the patient who died (n = 1) within 100 days of the regimen administration than those who survived (n = 7). In contrast, E max of ARA was non-discriminant (21% vs 15+10%) although the values were in general much lower than those observed for the HMA drugs. ROC-AUC of survival and response prediction was 1.00 based on E max of IDA, however, a bigger cohort is needed to confirm the statistical significance of the observed utility.

In conclusion, we report that our proprietary ex vivo drug sensitivity platform may have clinical utility in selecting the best-fitting therapy for AML patients in an individualized manner. Interestingly, different metrics representing the ex vivo drug sensitivity had disparate utility in prediction the clinical outcome. E max, which correlates to the proportion of the drug-resistant cancer cells, was particularly useful in discriminating overall survival in patients treated with VEN + HMA or Anthracycline + AraC regimens, while AUC showed promise in predicting response specifically in patients treated with VEN + HMA.

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