Genomic and proteomic characterization of Philadelphia-like B-lineage acute lymphoblastic leukemia: A report of Indian patients.

BACKGROUND

The gold standard for the identification of Philadelphia (Ph)-like acute lymphoblastic leukemia (ALL) patients is gene expression profiling. Because of its diverse nature, its identification is extremely difficult and expensive. On the genomic and proteomic landscape of Ph-like ALL patients, there is a paucity of published literature from developing countries.

METHODS

The authors used digital barcoded nCounter NanoString gene expression profiling for its detection, followed by molecular and proteomic characterization using fluorescence in situ hybridization and liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

The authors found 32.05% Ph-like ALL patients and their median age at presentation was considerably higher than Ph-negative ALL cases (p = .0306). Furthermore, we identified 20% CRLF2 overexpressed cases having 8.33% CRLF2-IGH translocation with concomitant R683S mutation and 8.33% CRLF2-P2RY8 translocation. In 80% of CRLF2 downregulated cases, we identified 10% as having JAK2 rearrangement. Minimal residual disease-positivity was more common in Ph-like ALL cases (55.55% vs. 25% in Ph-negative ALL cases). Immunoglobulin J chain (Jchain), small nuclear ribonucleoprotein SmD1 (SNRPD1), immunoglobulin κ constant (IGKC), NADH dehydrogenase (ubiquinone) 1 α subcomplex subunit 2 (NDUFA2), histone H2AX (H2AFX), charged multivesicular body protein 4b (CHMP4B), and carbonyl reductase (NADPH) (CBR1) proteins were identified to be substantially expressed in Ph-like ALL patients, using LC-MS/MS. Gene enrichment analysis indicated that involvement of spliceosomal mediated messenger RNA splicing pathway and four microRNAs was statistically significant in Ph-like ALL patients.

CONCLUSIONS

For the first time, we have described incidence, molecular, and proteomic characterization of Ph-like ALL, in developing nations.

PLAIN LANGUAGE SUMMARY

In developing countries, detecting Philadelphia (Ph)-like B-lineage acute lymphoblastic leukemia is complicated and challenging due to its diverse genetic landscape. There is no well-defined and cost-effective methodology for its detection. The incidence of this high-risk subtype is very high in adult cases, and there is an urgent need for its accurate detection. We have developed an online PHi-RACE classifier for its rapid detection, followed by delineating the genomic and proteomic landscape of Ph-like acute lymphoblastic leukemias for the first time in Indian patients.