Outcome of risk adapted therapy for relapsed/refractory acute lymphoblastic leukemia in children

Outcomes of children treated for relapsed or refractory acute lymphoblastic leukemia: A single tertiary care center experience

BACKGROUND

Acute lymphoblastic leukemia (ALL) is one of the most common malignancies among children. Despite success in frontline treatment, 20% of children will relapse or show resistance to treatment.

AIM

The aim of this study is to evaluate the clinical characteristics of children diagnosed and treated for refractory or relapsed ALL and determine 3-year overall survival (OS) outcomes.

METHOD

This study involved a retrospective chart review of patients aged 1-14 years diagnosed with ALL during January 2002 to December 2018. Data were extracted for baseline characteristics at diagnosis and at relapse.

RESULTS

A total of 347 newly diagnosed children with ALL were identified, among whom there were three induction failures (IF) and 28 relapses, resulting in a cohort of 31 patients with a relapse rate of 9%. The male-to-female ratio was 4.16:1, and the mean duration of first complete remission (CR1) was 26 months. Fifteen (48%) patients relapsed ≤18 months, 7 (23%) during 18-36 months, and 9 (29%) relapsed >36 months of IF or CR1. Nineteen patients (61%) had isolated bone marrow (BM) relapse, 7 (23%) patients experienced isolated extramedullary relapse (5 isolated CNS relapse and 2 isolated testicular relapse), and 5 (16%) patients experienced BM involvement with other sites (4 BM + CNS and 1 BM + testis). The 3-year OS of the cohort was 62.3%, while in patients with CR post first-salvage therapy, a 3-year OS of 79.5% was observed (p value <.05 compared with patients who did not achieve remission post first-salvage therapy, 3-year OS: 46.4%). The same statistical difference was observed in 3-year OS when comparing the duration of remission of CR prior to relapse: ≤18 months, 33.2%; 18-36 months, 66.7%; and >36 months, 87.5%. The same trend continued when comparing 3-year OS based on risk stratification at relapse: low risk (LR), 83.3%; intermediate risk (IR), 80%; and high risk (HR), 44.8%.

CONCLUSION

The incidence and outcomes reported are comparable to internationally reported data regarding the duration of CR1. Risk stratification at relapse and remission status post-salvage therapy were identified as significant prognostic factors for survival. No survival difference was observed among patients who received hematopoietic stem cell transplantation after induction compared with those who received chemotherapy, which could be attributed to the smaller sample size, warranting a multi-institutional observational study. These findings corroborate the need for novel therapies and treatment approaches.

Proteomic analysis of cerebrospinal fluid in pediatric acute lymphoblastic leukemia patients: a pilot study

Purpose

Involvement of central nervous system in acute lymphoblastic leukemia (CNSL) remains one of the major causes of pediatric acute lymphoblastic leukemia (ALL) treatment failure. However, the current understanding of the pathological process of CNSL is still limited. This study aimed to better understand the protein expression in cerebrospinal fluid (CSF) of ALL and discover valuable prognostic biomarkers.

Materials and methods

CSF samples were obtained from ALL patients and healthy controls. Comparative proteomic profiling using label-free liquid chromatography-tandem mass spectrometry was performed to detect differentially expressed proteins.

Results

In the present study, 51 differentially expressed proteins were found. Among them, two core clusters including ten proteins (TIMP1, LGALS3BP, A2M, FN1, AHSG, HRG, ITIH4, CF I, C2, and C4a) might be crucial for tumorigenesis and progression of ALL and can be potentially valuable indicators of CNSL.

Conclusion

These differentially expressed proteins of ALL children with central nervous system involvement and normal children may work as diagnostic and prognostic factors of ALL patients.

Predicting Ewing Sarcoma Treatment Outcome Using Infrared Spectroscopy and Machine Learning

Background: Improved outcome prediction is vital for the delivery of risk-adjusted, appropriate and effective care to paediatric patients with Ewing sarcoma—the second most common paediatric malignant bone tumour. Fourier transform infrared (FTIR) spectroscopy of tissues allows the bulk biochemical content of a biological sample to be probed and makes possible the study and diagnosis of disease. Methods: In this retrospective study, FTIR spectra of sections of biopsy-obtained bone tissue were recorded. Twenty-seven patients (between 5 and 20 years of age) with newly diagnosed Ewing sarcoma of bone were included in this study. The prognostic value of FTIR spectra obtained from Ewing sarcoma (ES) tumours before and after neoadjuvant chemotherapy were analysed in combination with various data-reduction and machine learning approaches. Results: Random forest and linear discriminant analysis supervised learning models were able to correctly predict patient mortality in 92% of cases using leave-one-out cross-validation. The best performing model for predicting patient relapse was a linear Support Vector Machine trained on the observed spectral changes as a result of chemotherapy treatment, which achieved 92% accuracy. Conclusion: FTIR spectra of tumour biopsy samples may predict treatment outcome in paediatric Ewing sarcoma patients with greater than 92% accuracy.