Loss of GABARAP mediates resistance to immunogenic chemotherapy in multiple myeloma.

ABSTRACT: Immunogenic cell death (ICD) is a form of cell death by which cancer treatments can induce a clinically relevant antitumor immune response in a broad range of cancers. In multiple myeloma (MM), the proteasome inhibitor bortezomib is an ICD inducer and creates durable therapeutic responses in patients. However, eventual relapse and resistance to bortezomib appear inevitable. Here, by integrating patient transcriptomic data with an analysis of calreticulin (CRT) protein interactors, we found that GABA type A receptor-associated protein (GABARAP) is a key player whose loss prevented tumor cell death from being perceived as immunogenic after bortezomib treatment. GABARAP is located on chromosome 17p, which is commonly deleted in patients with high risk MM. GABARAP deletion impaired the exposure of the eat-me signal CRT on the surface of dying MM cells in vitro and in vivo, thus reducing tumor cell phagocytosis by dendritic cells and the subsequent antitumor T-cell response. Low GABARAP was independently associated with shorter survival in patients with MM and reduced tumor immune infiltration. Mechanistically, we found that GABARAP deletion blocked ICD signaling by decreasing autophagy and altering Golgi apparatus morphology, with consequent defects in the downstream vesicular transport of CRT. Conversely, upregulating autophagy using rapamycin restored Golgi morphology, CRT exposure, and ICD signaling in GABARAPKO cells undergoing bortezomib treatment. Therefore, coupling an ICD inducer, such as bortezomib, with an autophagy inducer, such as rapamycin, may improve patient outcomes in MM, in which low GABARAP in the form of del(17p) is common and leads to worse outcomes.

Bone marrow stromal cells induce chromatin remodeling in multiple myeloma cells leading to transcriptional changes.

The natural history of multiple myeloma is characterized by its localization to the bone marrow and its interaction with bone marrow stromal cells. The bone marrow stromal cells provide growth and survival signals, thereby promoting the development of drug resistance. Here, we show that the interaction between bone marrow stromal cells and myeloma cells (using human cell lines) induces chromatin remodeling of cis-regulatory elements and is associated with changes in the expression of genes involved in the cell migration and cytokine signaling. The expression of genes involved in these stromal interactions are observed in extramedullary disease in patients with myeloma and provides the rationale for survival of myeloma cells outside of the bone marrow microenvironment. Expression of these stromal interaction genes is also observed in a subset of patients with newly diagnosed myeloma and are akin to the transcriptional program of extramedullary disease. The presence of such adverse stromal interactions in newly diagnosed myeloma is associated with accelerated disease dissemination, predicts the early development of therapeutic resistance, and is of independent prognostic significance. These stromal cell induced transcriptomic and epigenomic changes both predict long-term outcomes and identify therapeutic targets in the tumor microenvironment for the development of novel therapeutic approaches.

Natural Language Processing Algorithm to Extract Multiple Myeloma Stage From Oncology Notes in the Veterans Affairs Healthcare System.

PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to develop and validate a natural language processing (NLP) algorithm to extract oncologists' documentation of stage in the national Veterans Affairs (VA) Healthcare System. METHODS: Using nationwide electronic health record (EHR) and cancer registry data from the VA Corporate Data Warehouse, we developed and validated a rule-based NLP algorithm to extract oncologist-determined MM stage. To that end, a clinician annotated MM stage within over 5,000 short snippets of clinical notes, and annotated MM stage at MM treatment initiation for 200 patients. These were allocated into snippet- and patient-level development and validation sets. We developed MM stage extraction and roll-up algorithms within the development sets. After the algorithms were finalized, we validated them using standard measures in held-out validation sets. RESULTS: We developed algorithms for three different MM staging systems that have been in widespread use (Revised International Staging System [R-ISS], International Staging System [ISS], and Durie-Salmon [DS]) and for stage reported without a clearly defined system. Precision and recall were uniformly high for MM stage at the snippet level, ranging from 0.92 to 0.99 for the different MM staging systems. Performance in identifying for MM stage at treatment initiation at the patient level was also excellent, with precision of 0.92, 0.96, 0.90, and 0.86 and recall of 0.99, 0.98, 0.94, and 0.92 for R-ISS, ISS, DS, and unclear stage, respectively. CONCLUSION: Our MM stage extraction algorithm uses rule-based NLP and data aggregation to accurately measure MM stage documented in oncology notes and pathology reports in VA's national EHR system. It may be adapted to other systems where MM stage is recorded in clinical notes.

Venetoclax resistance leads to broad resistance to standard-of-care anti-MM agents, but not to immunotherapies.

ABSTACT: To our knowledge, venetoclax is the first example of personalized medicine for multiple myeloma (MM), with meaningful clinical activity as a monotherapy and in combination in patients with myeloma harboring the t(11:14) translocation. However, despite the high response rates and prolonged progression-free survival, a significant proportion of patients eventually relapse. Here, we aim to study adaptive molecular responses after the acquisition of venetoclax resistance in sensitive t(11:14) MM cell models. We therefore generated single-cell venetoclax-resistant t(11:14) MM cell lines and investigated the mechanisms contributing to resistance as well as the cells' sensitivity to other treatments. Our data suggest that acquired resistance to venetoclax is characterized by reduced mitochondrial priming and changes in B-cell lymphoma-2 (BCL-2) family proteins' expression in MM cells, conferring broad resistance to standard-of-care antimyeloma drugs. However, our results show that the resistant cells are still sensitive to immunotherapeutic treatments, highlighting the need to consider appropriate sequencing of these treatments after venetoclax-based regimens.

Round Table Discussion on Optimal Clinical Trial Design in Precursor Multiple Myeloma.

SUMMARY: While the current approach to precursor hematologic conditions is to "watch and wait," this may change with the development of therapies that are safe and extend survival or delay the onset of symptomatic disease. The goal of future therapies in precursor hematologic conditions is to improve survival and prevent or delay the development of symptomatic disease while maximizing safety. Clinical trial considerations in this field include identifying an appropriate at-risk population, safety assessments, dose selection, primary and secondary trial endpoints including surrogate endpoints, control arms, and quality-of-life metrics, all of which may enable more precise benefit-risk assessment.

Acute Lymphoblastic Leukemia with Myeloid Mutations Is a High-Risk Disease Associated with Clonal Hematopoiesis.

Myeloid neoplasms arise from preexisting clonal hematopoiesis (CH); however, the role of CH in the pathogenesis of acute lymphoblastic leukemia (ALL) is unknown. We found that 18% of adult ALL cases harbored TP53, and 16% had myeloid CH-associated gene mutations. ALL with myeloid mutations (MyM) had distinct genetic and clinical characteristics, associated with inferior survival. By using single-cell proteogenomic analysis, we demonstrated that myeloid mutations were present years before the diagnosis of ALL, and a subset of these clones expanded over time to manifest as dominant clones in ALL. Single-cell RNA sequencing revealed upregulation of genes associated with cell survival and resistance to apoptosis in B-ALL with MyM, which responds better to newer immunotherapeutic approaches. These findings define ALL with MyM as a high-risk disease that can arise from antecedent CH and offer new mechanistic insights to develop better therapeutic and preventative strategies. SIGNIFICANCE: CH is a precursor lesion for lymphoblastic leukemogenesis. ALL with MyM has distinct genetic and clinical characteristics, associated with adverse survival outcomes after chemotherapy. CH can precede ALL years before diagnosis, and ALL with MyM is enriched with activated T cells that respond to immunotherapies such as blinatumomab. See related commentary by Iacobucci, p. 142.