Rapid identification of BCR/ABL1-like acute lymphoblastic leukaemia patients using a predictive statistical model based on quantitative real time-polymerase chain reaction: clinical, prognostic and therapeutic implications.

BCR/ABL1-like acute lymphoblastic leukaemia (ALL) is a subgroup of B-lineage acute lymphoblastic leukaemia that occurs within cases without recurrent molecular rearrangements. Gene expression profiling (GEP) can identify these cases but it is expensive and not widely available. Using GEP, we identified 10 genes specifically overexpressed by BCR/ABL1-like ALL cases and used their expression values - assessed by quantitative real time-polymerase chain reaction (Q-RT-PCR) in 26 BCR/ABL1-like and 26 non-BCR/ABL1-like cases to build a statistical "BCR/ABL1-like predictor", for the identification of BCR/ABL1-like cases. By screening 142 B-lineage ALL patients with the "BCR/ABL1-like predictor", we identified 28/142 BCR/ABL1-like patients (19·7%). Overall, BCR/ABL1-like cases were enriched in JAK/STAT mutations (P < 0·001), IKZF1 deletions (P < 0·001) and rearrangements involving cytokine receptors and tyrosine kinases (P = 0·001), thus corroborating the validity of the prediction. Clinically, the BCR/ABL1-like cases identified by the BCR/ABL1-like predictor achieved a lower rate of complete remission (P = 0·014) and a worse event-free survival (P = 0·0009) compared to non-BCR/ABL1-like ALL. Consistently, primary cells from BCR/ABL1-like cases responded in vitro to ponatinib. We propose a simple tool based on Q-RT-PCR and a statistical model that is capable of easily, quickly and reliably identifying BCR/ABL1-like ALL cases at diagnosis

Tailoring CD19xCD3-DART exposure enhances T-cells to eradication of B-cell neoplasms.

Many patients with B-cell malignancies can be successfully treated, although tumor eradication is rarely achieved. T-cell-directed killing of tumor cells using engineered T-cells or bispecific antibodies is a promising approach for the treatment of hematologic malignancies. We investigated the efficacy of CD19xCD3 DART bispecific antibody in a broad panel of human primary B-cell malignancies. The CD19xCD3 DART identified 2 distinct subsets of patients, in which the neoplastic lymphocytes were eliminated with rapid or slow kinetics. Delayed responses were always overcome by a prolonged or repeated DART exposure. Both CD4 and CD8 effector cytotoxic cells were generated, and DART-mediated killing of CD4+ cells into cytotoxic effectors required the presence of CD8+ cells. Serial exposures to DART led to the exponential expansion of CD4 + and CD8 + cells and to the sequential ablation of neoplastic cells in absence of a PD-L1-mediated exhaustion. Lastly, patient-derived neoplastic B-cells (B-Acute Lymphoblast Leukemia and Diffuse Large B Cell Lymphoma) could be proficiently eradicated in a xenograft mouse model by DART-armed cytokine induced killer (CIK) cells. Collectively, patient tailored DART exposures can result in the effective elimination of CD19 positive leukemia and B-cell lymphoma and the association of bispecific antibodies with unmatched CIK cells represents an effective modality for the treatment of CD19 positive leukemia/lymphoma

ZFX Mediates Non-canonical Oncogenic Functions of the Androgen Receptor Splice Variant 7 in Castrate-Resistant Prostate Cancer

Androgen receptor splice variant 7 (AR-V7) is crucial for prostate cancer progression and therapeutic resistance. We show that, independent of ligand, AR-V7 binds both androgen-responsive elements (AREs) and non-canonical sites distinct from full-length AR (AR-FL) targets. Consequently, AR-V7 not only recapitulates AR-FL's partial functions but also regulates an additional gene expression program uniquely via binding to gene promoters rather than ARE enhancers. AR-V7 binding and AR-V7-mediated activation at these unique targets do not require FOXA1 but rely on ZFX and BRD4. Knockdown of ZFX or select unique targets of AR-V7/ZFX, or BRD4 inhibition, suppresses growth of castration-resistant prostate cancer cells. We also define an AR-V7 direct target gene signature that correlates with AR-V7 expression in primary tumors, differentiates metastatic prostate cancer from normal, and predicts poor prognosis. Thus, AR-V7 has both ARE/FOXA1 canonical and ZFX-directed non-canonical regulatory functions in the evolution of anti-androgen therapeutic resistance, providing information to guide effective therapeutic strategies. By cistrome profiling of endogenous androgen receptor (AR) versus an AR splice variant, AR-V7, Cai et al. uncovered non-canonical pathways uniquely targeted by AR-V7 and ZFX, a previously unknown AR-V7 partner. Targeting cofactors (ZFX or BRD4) or non-canonical downstream pathways of AR-V7 provides potential therapeutic ways for treating prostate cancer

The novel lncRNA BlackMamba controls the neoplastic phenotype of ALK- anaplastic large cell lymphoma by regulating the DNA helicase HELLS.

The molecular mechanisms leading to the transformation of anaplastic lymphoma kinase negative (ALK-) anaplastic large cell lymphoma (ALCL) have been only in part elucidated. To identify new culprits which promote and drive ALCL, we performed a total transcriptome sequencing and discovered 1208 previously unknown intergenic long noncoding RNAs (lncRNAs), including 18 lncRNAs preferentially expressed in ALCL. We selected an unknown lncRNA, BlackMamba, with an ALK- ALCL preferential expression, for molecular and functional studies. BlackMamba is a chromatin-associated lncRNA regulated by STAT3 via a canonical transcriptional signaling pathway. Knockdown experiments demonstrated that BlackMamba contributes to the pathogenesis of ALCL regulating cell growth and cell morphology. Mechanistically, BlackMamba interacts with the DNA helicase HELLS controlling its recruitment to the promoter regions of cell-architecture-related genes, fostering their expression. Collectively, these findings provide evidence of a previously unknown tumorigenic role of STAT3 via a lncRNA-DNA helicase axis and reveal an undiscovered role for lncRNA in the maintenance of the neoplastic phenotype of ALK-ALCL

Repeat pneumococcal polysaccharide vaccination does not impair functional immune responses among Indigenous Australians.

Indigenous Australians experience one of the highest rates of pneumococcal disease globally. In the Northern Territory of Australia, a unique government-funded vaccination schedule for Indigenous Australian adults comprising multiple lifetime doses of the pneumococcal polysaccharide vaccine is currently implemented. Despite this programme, rates of pneumococcal disease do not appear to be declining, with concerns raised over the potential for immune hyporesponse associated with the use of this vaccine. We undertook a study to examine the immunogenicity and immune function of a single and repeat pneumococcal polysaccharide vaccination among Indigenous adults compared to non-Indigenous adults. Our results found that immune function, as measured by opsonophagocytic and memory B-cell responses, were similar between the Indigenous groups but lower for some serotypes in comparison with the non-Indigenous group. This is the first study to document the immunogenicity following repeat 23-valent pneumococcal polysaccharide vaccine administration among Indigenous Australian adults, and reinforces the continued need for optimal pneumococcal vaccination programmes among high-risk populations

Inhibition of FGF receptor blocks adaptive resistance to RET inhibition in CCDC6-RET-rearranged thyroid cancer.

Genetic alterations in RET lead to activation of ERK and AKT signaling and are associated with hereditary and sporadic thyroid cancer and lung cancer. Highly selective RET inhibitors have recently entered clinical use after demonstrating efficacy in treating patients with diverse tumor types harboring RET gene rearrangements or activating mutations. In order to understand resistance mechanisms arising after treatment with RET inhibitors, we performed a comprehensive molecular and genomic analysis of a patient with RET-rearranged thyroid cancer. Using a combination of drug screening and proteomic and biochemical profiling, we identified an adaptive resistance to RET inhibitors that reactivates ERK signaling within hours of drug exposure. We found that activation of FGFR signaling is a mechanism of adaptive resistance to RET inhibitors that activates ERK signaling. Combined inhibition of FGFR and RET prevented the development of adaptive resistance to RET inhibitors, reduced cell viability, and decreased tumor growth in cellular and animal models of CCDC6-RET-rearranged thyroid cancer

Opposing transcriptional programs of KLF5 and AR emerge during therapy for advanced prostate cancer.

Endocrine therapies for prostate cancer inhibit the androgen receptor (AR) transcription factor. In most cases, AR activity resumes during therapy and drives progression to castration-resistant prostate cancer (CRPC). However, therapy can also promote lineage plasticity and select for AR-independent phenotypes that are uniformly lethal. Here, we demonstrate the stem cell transcription factor Krüppel-like factor 5 (KLF5) is low or absent in prostate cancers prior to endocrine therapy, but induced in a subset of CRPC, including CRPC displaying lineage plasticity. KLF5 and AR physically interact on chromatin and drive opposing transcriptional programs, with KLF5 promoting cellular migration, anchorage-independent growth, and basal epithelial cell phenotypes. We identify ERBB2 as a point of transcriptional convergence displaying activation by KLF5 and repression by AR. ERBB2 inhibitors preferentially block KLF5-driven oncogenic phenotypes. These findings implicate KLF5 as an oncogene that can be upregulated in CRPC to oppose AR activities and promote lineage plasticity

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing