Dai, Yun

Abstract1q gain (+1q) is the most common high‐risk cytogenetic abnormality (HRCA) in patients with multiple myeloma (MM). However, its prognostic value remains unclear in the era of novel agents. Here, we retrospectively analyzed the impact of +1q on the outcomes of 934 patients newly diagnosed with MM. +1q was identified in 53.1% of patients and verified as an independent variate for inferior overall survival (OS) (hazard ratio, 1.400; 95% confidence interval, 1.097–1.787; p = .007). Concurrence of other HRCAs (particularly t(14;16) and del(17p)) further exacerbated the outcomes of patients with +1q, suggesting prognostic heterogeneity. Thus, a risk‐scoring algorithm based on four risk variates (t(14;16), hypercalcemia, ISS III, and high LDH) was developed to estimate the outcomes of patients with +1q. Of the patients, 376 evaluable patients with +1q were re‐stratified into low (31.6%), intermediate (61.7%), and high risk (6.7%) groups, with significantly different progression‐free survival and OS (p < .0001), in association with early relapse of the disease. The prognostic value of this model was validated in the CoMMpass cohort. While attaining undetectable MRD largely circumvented the adverse impact of +1q, it scarcely ameliorated the outcome of the patients with high risk, who likely represent a subset of patients with extremely poor survival. Hence, patients with +1q are a heterogeneous group of high‐risk patients, therefore underlining the necessity for their re‐stratification. The proposed simple risk‐scoring model can estimate the outcomes of patients with +1q, which may help guide risk‐adapted treatment for such patients.

Abstract A complex network precisely regulates the cell cycle through the G1, S, G2, and M phases and is the basis for cell division under physiological and pathological conditions. On the one hand, the transition from one phase to another as well as the progression within each phase is driven by the specific cyclin-dependent kinases (CDKs; e.g., CDK1, CDK2, CDK4, CDK6, and CDK7), together with their exclusive partner cyclins (e.g., cyclin A1, B1, D1–3, and E1). On the other hand, these phases are negatively regulated by endogenous CDK inhibitors such as p16ink4a, p18ink4c, p19ink4d, p21cip1, and p27kip1. In addition, several checkpoints control the commitment of cells to replicate DNA and undergo mitosis, thereby avoiding the passage of genomic errors to daughter cells. CDKs are often constitutively activated in cancer, which is characterized by the uncontrolled proliferation of transformed cells, due to genetic and epigenetic abnormalities in the genes involved in the cell cycle. Moreover, several oncogenes and defective tumor suppressors promote malignant changes by stimulating cell cycle entry and progression or disrupting DNA damage responses, including the cell cycle checkpoints, DNA repair mechanisms, and apoptosis. Thus, genes or proteins related to cell cycle regulation remain the main targets of interest in the treatment of various cancer types, including hematologic malignancies. In this context, advances in the understanding of the cell cycle regulatory machinery provide a basis for the development of novel therapeutic approaches. The present article summarizes the pathways as well as their genetic and epigenetic alterations that regulate the cell cycle; moreover, it discusses the various approved or potential therapeutic targets associated with the cell cycle, focusing on hematologic malignancies.

Abstract1q21 gain is a common cytogenetic abnormality featuring high‐risk multiple myeloma (HRMM). However, the molecular mechanism underlying the adverse prognostic effect of 1q21 gain remains largely unclear. Here, we report that ARNT/HIF‐1β, a 1q21 gene, is highly expressed in HRMM and induced by microenvironmental hypoxia, which confers drug resistance and correlates with inferior outcome. Analysis of the gene expression profile database revealed that ARNT expression was upregulated in MM and increased with disease progression or in HRMM subtypes (particularly 1q21 gain), while correlated to shorter overall survival. In a cohort of 40 MM patients, qPCR further validated that ARNT expression was higher in MM patients than normal donors. MM cells carrying 1q21 gain or acquired drug resistance displayed a robust increase in HIF‐1β protein level. Hypoxia induced HIF‐1β expression via a NF‐κB‐dependent process. Notably, HIF‐1β overexpression impaired bortezomib sensitivity, whereas shRNA knockdown of ARNT reversed hypoxia‐mediated drug resistance. Together, these findings suggest that ARNT/HIF‐1β might represent a novel biomarker for risk stratification and prognosis of HRMM patients, as well as a potential therapeutic target for overcoming 1q21 gain‐ or microenvironment‐mediated and acquired drug resistance in MM.