@article{SolimandoDaViaBollietal.2022,
  author    = {Solimando, Antonio Giovanni and Da Vi{\`a}, Matteo Claudio and Bolli, Niccol{\`o} and Steinbrunn, Torsten},
  title     = {The route of the malignant plasma cell in its survival niche: exploring "Multiple Myelomas"},
  series = {Cancers},
  volume    = {14},
  journal   = {Cancers},
  number    = {13},
  issn      = {2072-6694},
  doi       = {10.3390/cancers14133271},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281728},
  year      = {2022},
  abstract  = {Growing evidence points to multiple myeloma (MM) and its stromal microenvironment using several mechanisms to subvert effective immune and anti-tumor responses. Recent advances have uncovered the tumor-stromal cell influence in regulating the immune-microenvironment and have envisioned targeting these suppressive pathways to improve therapeutic outcomes. Nevertheless, some subgroups of patients include those with particularly unfavorable prognoses. Biological stratification can be used to categorize patient-, disease- or therapy-related factors, or alternatively, these biological determinants can be included in a dynamic model that customizes a given treatment to a specific patient. Genetic heterogeneity and current knowledge enforce a systematic and comprehensive bench-to-bedside approach. Given the increasing role of cancer stem cells (CSCs) in better characterizing the pathogenesis of solid and hematological malignancies, disease relapse, and drug resistance, identifying and describing CSCs is of paramount importance in the management of MM. Even though the function of CSCs is well-known in other cancer types, their role in MM remains elusive. With this review, we aim to provide an update on MM homing and resilience in the bone marrow micro milieu. These data are particularly interesting for clinicians facing unmet medical needs while designing novel treatment approaches for MM.},
  language  = {en}
}
@article{WalkerMavrommatisWardelletal.2019,
  author    = {Walker, Brian A. and Mavrommatis, Konstantinos and Wardell, Christopher P. and Ashby, T. Cody and Bauer, Michael and Davies, Faith and Rosenthal, Adam and Wang, Hongwei and Qu, Pingping and Hoering, Antje and Samur, Mehmet and Towfic, Fadi and Ortiz, Maria and Flynt, Erin and Yu, Zhinuan and Yang, Zhihong and Rozelle, Dan and Obenauer, John and Trotter, Matthew and Auclair, Daniel and Keats, Jonathan and Bolli, Niccolo and Fulciniti, Mariateresa and Szalat, Raphael and Moreau, Phillipe and Durie, Brian and Stewart, A. Keith and Goldschmidt, Hartmut and Raab, Marc S. and Einsele, Hermann and Sonneveld, Pieter and San Miguel, Jesus and Lonial, Sagar and Jackson, Graham H. and Anderson, Kenneth C. and Avet-Loiseau, Herve and Munshi, Nikhil and Thakurta, Anjan and Morgan, Gareth},
  title     = {A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis},
  series = {Leukemia},
  volume    = {33},
  journal   = {Leukemia},
  doi       = {10.1038/s41375-018-0196-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-233299},
  pages     = {159-170},
  year      = {2019},
  abstract  = {Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R2 = 18.4\% and 25.2\%, respectively). Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R2 of 34.3\% for PFS and 46.5\% for OS. A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1\% of the population (median PFS = 15.4 months; OS = 20.7 months) that was validated in an independent dataset. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.},
  language  = {en}
}