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Background: Philadelphia chromosome (Ph)–like B‐acute lymphoblastic leukemia (B‐ALL) is a clinically significant, high‐risk genetic subtype of B‐ALL cases. There are few data on the incidence, characterization, and treatment outcomes of Ph‐like ALL cases from low‐ and middle‐income countries. There is a pressing need to establish a well‐organized/cost‐effective approach for identifying Ph‐like ALL instances. Methods: Multiplex reverse transcriptase polymerase chain reaction, nCounter NanoString, and fluorescence in situ hybridization were used to detect and characterize Ph‐like ALL cases among recurrent genetic abnormalities (RGA)neg B‐ALL cases. At the end of induction therapy, flow cytometry‐minimal residual disease (MRD) assay was used to quantify MRD positivity in Ph‐like ALL cases. Results: Of 130 newly diagnosed B‐ALL cases, 25% (BCR::ABL1), 4% (ETV6::RUNX1), 5% (TCF3::PBX1), 2% (KM2TA::AFF1), and 65% RGAneg B‐ALL cases were revealed by multiplex reverse transcriptase polymerase chain reaction. Among RGAneg B‐ALL cases, 24% Ph‐like ALL cases using nCounter NanoString were identified, with 48% CRLF2high cases with 45% CRLF2::P2RY8 and 18% CRLF2::IGH rearrangements(∼r) revealed by fluorescence in situ hybridization. In 52% of CRLF2low cases, 17% ABL1 and JAK2∼r 8% EPOR::IGH & PDGRFB∼r were identified. Ph‐like ALL cases had higher total leukocyte count (p <.05), male preponderance (p <.05), and high MRD‐positivity/induction failure compared with RGAneg B‐ALL cases. Furthermore, in Ph‐like ALL cases, 11 significant genes using quantitative polymerase chain reaction were identified and validated. CRLF2, IGJ, CEACAM6, MUC4, SPATS2L and NRXN3 genes were overexpressed and show statistical significance (p <.05) in Ph‐like ALL cases. Conclusions: This study showed the high incidence of Ph‐like ALL cases with kinase activating alterations and treatment outcomes from low‐ and middle‐income region. Furthermore, a surrogate cost‐effective multiplex panel of 11 overexpressed genes for the prompt detection of Ph‐like ALL cases is proposed. Plain Language Summary: Identification of recurrent gene abnormalities (RGA)neg B‐acute lymphoblastic leukemia (B‐ALL) cases using multiplex‐reverse transcriptase polymerase chain reaction.Identification and characterization of Philadelphia (Ph)–like ALL cases using nCounter NanoString gene expression profiling and fluorescence in situ hybridization.Furthermore, Ph‐like ALL cases were characterized according to CRLF2 expression and kinase‐activating genomic alterations. Minimal residual disease of Ph‐like ALL cases were quantified using flow cytometry‐minimal residual disease assay.A surrogate molecular approach was established to detect Ph‐like ALL cases from low‐ and middle‐income countries. A surrogate approach for the rapid baseline detection of Philadelphia chromosome (Ph)–like acute lymphoblastic leukemia cases, followed by its kinase gene alterations. Early detection of Ph–like acute lymphoblastic leukemia cases is extremely important to start personalized treatments to improve the overall survival/outcomes of these cases. [ABSTRACT FROM AUTHOR]

Gene expression profiling is the criterion standard for recognizing Ph-like ALL signatures among B-ALLs. The prerequisite of GEP is the accurate normalization of target genes with stable expression of housekeeping genes in a quantitative PCR. HKGs exhibit differential expression in the different experimental conditions and affect the target genes' expression, leading to imprecise qPCR results. The selection of stable HKGs is crucial in GEP experiments, especially in identifying high-risk Ph-like ALL cases. We have evaluated the expression stability of nine HKGs (GAPDH, ACTB, GUSB, RNA18S, EEF2, PGK1, B2M, TBP and ABL1) in identified Ph-like ALLs and Ph-negative (n = 23 each) using six algorithms, 4 traditional softwares; geNorm, BestKeeper, NormFinder, Delta Cq value method, and two algorithms, RefFinderTM and ComprFinder. Further, we have validated the expression of 8 overexpressed normalized genes in Ph-like ALL cases (JCHAIN, CA6, MUC4, SPATS2L, BMPR1B, CRLF2, ADGRF1 and NRXN3). GeNorm, BestKeeper, NormFinder, Delta Cq value method, RefFinderTM and ComprFinder algorithm analysis revealed that EEF2, GAPDH, and PGK1 form the best representative HKGs in Ph-like ALL cases, while RNA18s, ß-actin, and ABL1 in Ph-negative ALLs. Lastly, we performed a correlation analysis and found that the combination of EEF2, GAPDH, and PGK1 represents the best combination with a very high correlation in Ph-like ALL cases. This is the first report that shows EEF2, GAPDH, and PGK1 are the best HKG genes and can be used in the diagnostic panel of Ph-like ALL cases using qPCR at baseline diagnosis. [ABSTRACT FROM AUTHOR]

Background: The published literature on hematological, clinical, flowcytometric‐immunophenotyping, and minimal residual disease outcomes of the prognostically important genetic subtypes of acute lymphoblastic leukemia (ALL) is scarce from low‐income countries. For newer classifications such as BCR::ABL1‐like ALLs, the scarcity of patient‐level data is even more pronounced. Methods: The authors performed comprehensive detection of recurrent gene fusions and BCR::ABL1‐like ALL cases followed by immunophenotypic profiling and obtained clinical outcome parameters for a large cohort (n = 1021) of patients from India. This cohort included a significant number of patients with BCR::ABL1‐like ALL subtype and other genetic subtypes of ALL. Results: Patients with BCR::ABL1‐positive and BCR::ABL1‐like ALL were significantly older, had male preponderance, and expressed a higher white blood cell count than BCR::ABL1‐negative cases (p <.05). Logistic regression modeling of B‐lineage‐ALL (B‐ALL) subtypes revealed that cluster of differentiation (CD)36 is a strong statistically significant predictive marker of BCR::ABL1‐like ALL (p <.05). Furthermore, patients with BCR::ABL1‐like ALLs show a significantly higher frequency of CD36 expression compared to BCR::ABL1‐negative ALLs (p <.05). In terms of clinical symptoms, lymphadenopathy is a strong statistically significant predictive marker in BCR::ABL1‐like ALLs compared to BCR::ABL1‐negative ALL cases (p <.05). In terms of treatment outcomes, minimal residual disease (MRD) positivity in BCR::ABL1‐positive ALL cases were statistically significant (p <.05), and BCR::ABL1‐like ALL cases had high MRD‐positivity as compared to BCR::ABL1‐negative ALL cases but did not show statistical significance. Conclusions: The findings evince the use of novel therapies and personalized treatment regimens to improve the overall survival of the newer incorporated entities in B‐ALLs. This is the first report characterizing the hematological, clinical, flowcytometric‐immunophenotyping, and minimal residual disease outcomes of the prognostically significant subtypes of ALLs in patients from India. Plain Language Summary: Characterizing the hematological, clinical, flowcytometric‐immunophenotyping, and minimal residual disease outcomes of the prognostically significant subtypes (n = 1021) of acute lymphoblastic leukemia (ALLs) in patients from India.We have made two independent logistic regression models of cluster of differentiation (CD) markers and clinical symptoms to differentiate prognostically significant subtypes of ALLs.Logistic regression analysis of CD markers revealed CD36 as a strong predictor in BCR::ABL1‐like ALL cases compared to BCR::ABL1‐negative ALL cases.Logistic regression analysis of clinical symptoms revealed lymphadenopathy significantly predicts BCR::ABL1‐like ALLs (p <.05).In terms of treatment outcomes, BCR::ABL1‐positive ALL had statistically significant minimal residual disease (MRD) (p <.05), and BCR::ABL1‐like ALL cases had high MRD‐positivity but did not show statistical significance as compared to BCR::ABL1‐negative ALLs. This study characterizes prognostically significant genetic subtypes of B‐acute lymphoblastic leukemia (B‐ALL). Logistic regression modeling of cluster of differentiation markers and clinical symptoms is used to predict various genetic subtypes of B‐ALL. [ABSTRACT FROM AUTHOR]

Background: Early detection of BCR::ABL1-like ALL could impact treatment management and improve the overall survival/outcome. BCR::ABL1-like ALL cases are characterised by diverse genetic alterations activating cytokine receptors and kinase signalling. Its detection is still an unmet need in low–middle-income countries due to the unavailability of a patented TLDA assay. Methods: This study's rationale is to identify BCR::ABL1-like ALLs using the PHi-RACE classifier, followed by the characterisation of underlying adverse genetic alterations in recurrent gene abnormalities negative (RGAneg) B-ALLs (n = 108). Results: We identified 34.25% (37/108) BCR::ABL1-like ALLs using PHi-RACE classifier, characterised by TSLPR/CRLF2 expression (11.58%), IKZF1 (Δ4–7) deletion (18.9%) and chimeric gene fusions (34.61%). In overexpressed TSLPR/CRLF2 BCR::ABL1-like ALLs, we identified 33.33% (1/3) CRLF2::IGH and 33.33% (1/3) EPOR::IGH rearrangements with concomitant JAK2 mutation R683S (50%). We identified 18.91% CD13 (P = 0.02) and 27.02% CD33 (P = 0.05) aberrant myeloid markers positivity, which was significantly higher in BCR::ABL1-like ALLs compared to non-BCR::ABL1-like ALLs. MRD positivity was considerably higher (40% in BCR::ABL1-like vs. 19.29% in non-BCR::ABL1-like ALLs). Conclusions: With this practical approach, we reported a high incidence of BCR::ABL1-like ALLs, and a lower frequency of CRLF2 alteration & associated CGFs. Recognising this entity, early at diagnosis is crucial to optimise personalised treatment strategies. [ABSTRACT FROM AUTHOR]

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. The identification of Philadelphia chromosome (Ph)–like acute lymphoblastic leukemia (ALL) cases with NanoString nCounter digital‐barcoded gene expression profiling was examined in Indian patients. A higher incidence of Ph‐like ALL cases (32.05%) was identified. Furthermore, genomic and proteomic characterization of Ph‐like ALL cases was performed in Indian patients. This is the first report on the incidence and characterization of Ph‐like ALL cases from developing nations. [ABSTRACT FROM AUTHOR]

For the detection of BCR-ABL1-like ALL cases, two methodologies, specifically Gene expression profiling (GEP) or Next-generation targeted sequencing (NGS) and TaqMan based low-density (TLDA) card, are being used. NGS is very costly and TLDA is not widely commercially available. In this study, we quantified the expression of 8 selected overexpressed genes in 536 B-ALL cases. We identified 26.67% (143/536) BCR-ABL1-like ALLs using hierarchical clustering and principal component analysis. BCR-ABL1-like ALL cases were significantly older at presentation (p = 0.036) and had male preponderance (p = 0.047) compared to BCR-ABL1-negative ALL cases. MRD-positivity and induction failure were more commonest in BCR-ABL1-like ALL cases (30.55 vs.19.35% in BCR-ABL1-negative ALL cases). Lastly, we built a PHi-RACE classifier (sensitivity = 95.2%, specificity= 83.7%, AUC= 0.927) using logistic regression to detect BCR-ABL1-like ALL cases promptly at diagnosis. This classifier is beneficial for hematologists in quick decision making at baseline to start tailored treatment regimes. [ABSTRACT FROM AUTHOR]

Objective: Based on the immunophenotype, acute lymphoblastic leukemia (ALL) can be categorized into B-cell or T-cell lineages. B-cell precursor ALL (BCP-ALL) cases show various genetic/molecular abnormalities, and varying frequencies of chimeric fusion transcripts in BCP-ALL cases are reported from different parts of the world. We studied the immunophenotypic aberrancy profiles of a large number of BCP-ALL cases with respect to various common chimeric fusion transcripts. Materials and Methods: Flow cytometric immunophenotyping and multiplex reverse-transcription polymerase chain reaction assays were performed for 986 BCP-ALL cases. Results: Among 986 BCP-ALL cases, the incidence of various fusion transcripts was 38.36% in adult cases and 20.68% in pediatric cases. Adult BCP-ALL patients with t(9;22)(BCR-ABL1) fusion transcripts and expression of aberrant myeloid markers were significantly older at presentation (p=0.0218) with male preponderance (p=0.0246) compared to those without aberrant myeloid expression. In pediatric patients with the t(12;21)(ETV6-RUNX1) chimeric fusion transcript, aberrant expression of CD13 was observed in 39.13%, CD33 in 36.95%, and CD117 in 8.69% of patients, respectively. Pediatric BCP-ALL patients with the ETV6-RUNX1 fusion transcript and expression of aberrant myeloid markers were not significantly different compared to those without with respect to demographic and clinical/hematological characteristics (p=0.5955). Aberrant myeloid markers were rarely or never expressed in pediatric and adult BCP-ALL patients with the t(4;11)(KTM2A-AF4) and t(1;19)(TCF3-PBX1) fusion transcripts. Conclusion: Aberrant myeloid markers were frequently expressed among BCP-ALL patients with the t(9;22)(BCR-ABL1) and t(12;21) (ETV6-RUNX1) fusion transcripts. However, BCP-ALL patients with the t(4;11)(KTM2A-AF4) and t(1;19)(TCF3-PBX1) fusion transcripts rarely or never expressed aberrant myeloid markers. Aberrant myeloid CD markers can be used in predicting chimeric fusion transcripts at baseline so as to plan appropriate tyrosine kinase inhibitor therapy in cases of BCP-ALL with specific chimeric fusion transcripts. This study has delineated the relationship of chimeric fusion transcripts with the aberrant expression of myeloid markers in a large cohort of BCP-ALL cases. [ABSTRACT FROM AUTHOR]

Introduction: Flow cytometry‐based paroxysmal nocturnal hemoglobinuria (PNH) testing involves utilization of monoclonal antibodies against GPI‐linked proteins and FLAER. The ability of FLAER to bind to a wide variety of GPI‐linked structures and to be utilized across different leukocyte subsets is remarkable. We hypothesize that FLAER as a standalone reagent may be equally effective for detecting PNH clones. The present study intends to compare the results of a FLAER alone‐based strategy to the recommended FLAER+GPI‐linked protein‐based approach for applicability in clinical settings. Methods: EDTA‐anticoagulated blood samples from patients for PNH workup were tested for PNH by multiparametric flow cytometry. A conventional panel comprising gating markers (CD45 for WBC, CD15 for granulocytes, and CD64 for monocytes) and a combination of FLAER and GPI‐linked markers, such as CD24 and CD14, henceforth referred to as the "routine panel," was employed. Second, a "FLAER‐only panel" comprising the gating markers and FLAER alone (excluding the GPI‐linked markers CD24 and CD14) was set up. The samples were processed using the lyse‐wash‐stain‐wash technique, and events were acquired on BC Navios Ex flow cytometer (Beckman Coulter, Inc., USA) and analyzed on Kaluza Software 2.1. The presence of a PNH clone was reported at a value of ≥0.01%. Results: A total of 209 patients were tested. Both panels found a PNH clone in 20.1% of patients (n = 42/209) with a 100% concordance rate. The PNH clone range for granulocytes was 0.01%–89.68%, and for monocyte was 0.04%–96.09% in the routine panel. The range in the FLAER‐only panel for granulocytes was 0.01%–89.61%, and for monocytes, it was 0.01%–96.05%. Pearson correlation statistics revealed a significant correlation between the size of the PNH clone of granulocytes and monocytes among the two panels tested (granulocytes r = 0.9999, p < 0.0001, 95% CI = 0.9999 to 1.000; monocytes r = 0.9974, p < 0.0001, 95% CI = 0.9966–0.9980). Conclusion: Based on our results, FLAER as a standalone marker is specific and sensitive for identifying PNH clones in granulocytes and monocytes, even for high‐sensitivity PNH assay. The proposed "FLAER‐only panel" panel is efficient and cost‐effective for highly sensitive PNH testing in two different cell lineages, especially in resource‐limited clinical settings. [ABSTRACT FROM AUTHOR]