Xerna™ TME Panel is a machine learning-based transcriptomic biomarker designed to predict therapeutic response in multiple cancers.

Introduction: Most predictive biomarkers approved for clinical use measure single analytes such as genetic alteration or protein overexpression. We developed and validated a novel biomarker with the aim of achieving broad clinical utility. The Xerna™ TME Panel is a pan-tumor, RNA expression-based classifier, designed to predict response to multiple tumor microenvironment (TME)-targeted therapies, including immunotherapies and anti-angiogenic agents. Methods: The Panel algorithm is an artificial neural network (ANN) trained with an input signature of 124 genes that was optimized across various solid tumors. From the 298-patient training data, the model learned to discriminate four TME subtypes: Angiogenic (A), Immune Active (IA), Immune Desert (ID), and Immune Suppressed (IS). The final classifier was evaluated in four independent clinical cohorts to test whether TME subtype could predict response to anti-angiogenic agents and immunotherapies across gastric, ovarian, and melanoma datasets. Results: The TME subtypes represent stromal phenotypes defined by angiogenesis and immune biological axes. The model yields clear boundaries between biomarker-positive and -negative and showed 1.6-to-7-fold enrichment of clinical benefit for multiple therapeutic hypotheses. The Panel performed better across all criteria compared to a null model for gastric and ovarian anti-angiogenic datasets. It also outperformed PD-L1 combined positive score (>1) in accuracy, specificity, and positive predictive value (PPV), and microsatellite-instability high (MSI-H) in sensitivity and negative predictive value (NPV) for the gastric immunotherapy cohort. Discussion: The TME Panel's strong performance on diverse datasets suggests it may be amenable for use as a clinical diagnostic for varied cancer types and therapeutic modalities.

Phase Ib Study of Navicixizumab Plus Paclitaxel in Patients With Platinum-Resistant Ovarian, Primary Peritoneal, or Fallopian Tube Cancer.

PURPOSE: This phase Ib study evaluated the safety and efficacy of paclitaxel plus navicixizumab, a bispecific antiangiogenic antibody to vascular endothelial growth factor and delta-like ligand 4, against platinum-resistant ovarian cancer. PATIENTS AND METHODS: This open-label, nonrandomized, dose-escalation and -expansion study included 44 patients with previously treated, recurrent, platinum-resistant grade 2/3 ovarian cancer. Treatment was intravenous navicixizumab (3 mg/kg or 4 mg/kg once every 2 weeks) plus paclitaxel (80 mg/m2 intravenously on days 0, 7, and 14 of 28-day cycles). The primary and secondary objectives were to evaluate the safety and efficacy of navicixizumab plus paclitaxel. An RNA-based diagnostic panel was retrospectively used to test the hypothesis that tumors with high angiogenesis or immune-suppressed tumor microenvironment (TME) subtypes (biomarker-positive) are more likely to respond to navicixizumab than those with immune-active/-desert TME subtypes (biomarker-negative). RNA expression was analyzed in available pretreatment tumor tissue to classify 33 patients' TME subtypes, and TME panel findings were correlated with tumor response. RESULTS: The dose-escalation cohorts enrolled patients at navicixizumab doses of 3 mg/kg once every 2 weeks (n = 3) and 4 mg/kg once every 2 weeks (n = 2); 3 mg/kg was selected for expansion (n = 39). No dose-limiting toxicities occurred. The most common grade 3/4 treatment-related adverse events were hypertension (40.9%), neutropenia (6.8%), and thrombocytopenia (4.5%). Pulmonary hypertension occurred in 18.2% (grade 1-2). The overall objective response rate was 43.2% (95% CI, 28.3 to 59.0): 33.3% (95% CI, 17.3 to 52.8) in patients previously treated with bevacizumab, 64.3% (95% CI, 35.1 to 87.2) in bevacizumab-naive patients, and 62% (95% CI, 31.6 to 86.1) in biomarker-positive patients. The median duration of response was 6 months (95% CI, 5.4 months to not estimable). CONCLUSION: Navicixizumab plus paclitaxel demonstrated promising clinical activity in bevacizumab-treated and -naive patients with platinum-resistant ovarian cancer, with manageable toxicity.

Asia-Pacific Hematology Consortium Report on approach to multiple myeloma. Survey results from the 6th International Hematologic Malignancies Conference: Bridging the Gap 2015, Beijing, China.

The Asia-Pacific Hematology Consortium (APHCON), in partnership with MDRingTM, a mobile global physician education network, has initiated a detailed longitudinal study of physician knowledge and practice preferences in the Asia-Pacific sphere. The first dataset comes from a series of surveys answered by delegates at the APHCON Bridging The Gap (BTG) conference in Beijing in January, 2015. In this report we present our findings regarding diagnosis and treatment of multiple myeloma (MM). We aim to create a conduit for physicians in this region to share their experiences with the rest of the world, to identify areas of consensus and best practices, and to highlight opportunities for improvement in communication, education and patient care.

Leaps and lulls in the developmental transcriptome of Dictyostelium discoideum.

BACKGROUND: Development of the soil amoeba Dictyostelium discoideum is triggered by starvation. When placed on a solid substrate, the starving solitary amoebae cease growth, communicate via extracellular cAMP, aggregate by tens of thousands and develop into multicellular organisms. Early phases of the developmental program are often studied in cells starved in suspension while cAMP is provided exogenously. Previous studies revealed massive shifts in the transcriptome under both developmental conditions and a close relationship between gene expression and morphogenesis, but were limited by the sampling frequency and the resolution of the methods. RESULTS: Here, we combine the superior depth and specificity of RNA-seq-based analysis of mRNA abundance with high frequency sampling during filter development and cAMP pulsing in suspension. We found that the developmental transcriptome exhibits mostly gradual changes interspersed by a few instances of large shifts. For each time point we treated the entire transcriptome as single phenotype, and were able to characterize development as groups of similar time points separated by gaps. The grouped time points represented gradual changes in mRNA abundance, or molecular phenotype, and the gaps represented times during which many genes are differentially expressed rapidly, and thus the phenotype changes dramatically. Comparing developmental experiments revealed that gene expression in filter developed cells lagged behind those treated with exogenous cAMP in suspension. The high sampling frequency revealed many genes whose regulation is reproducibly more complex than indicated by previous studies. Gene Ontology enrichment analysis suggested that the transition to multicellularity coincided with rapid accumulation of transcripts associated with DNA processes and mitosis. Later development included the up-regulation of organic signaling molecules and co-factor biosynthesis. Our analysis also demonstrated a high level of synchrony among the developing structures throughout development. CONCLUSIONS: Our data describe D. discoideum development as a series of coordinated cellular and multicellular activities. Coordination occurred within fields of aggregating cells and among multicellular bodies, such as mounds or migratory slugs that experience both cell-cell contact and various soluble signaling regimes. These time courses, sampled at the highest temporal resolution to date in this system, provide a comprehensive resource for studies of developmental gene expression.