CAR Gene Delivery by T-cell Targeted Lentiviral Vectors is Enhanced by Rapamycin Induced Reduction of Antiviral Mechanisms.

Lentiviral vectors (LV) have become the dominant tool for stable gene transfer into lymphocytes including chimeric antigen receptor (CAR) gene delivery to T cells, a major breakthrough in cancer therapy. Yet, room for improvement remains, especially for the latest LV generations delivering genes selectively into T cell subtypes, a key requirement for in vivo CAR T cell generation. Toward improving gene transfer rates with these vectors, whole transcriptome analyses on human T lymphocytes are conducted after exposure to CAR-encoding conventional vectors (VSV-LV) and vectors targeted to CD8+ (CD8-LV) or CD4+ T cells (CD4-LV). Genes related to quiescence and antiviral restriction are found to be upregulated in CAR-negative cells exposed to all types of LVs. Down-modulation of various antiviral restriction factors, including the interferon-induced transmembrane proteins (IFITMs) is achieved with rapamycin as verified by mass spectrometry (LC-MS). Strikingly, rapamycin enhances transduction by up to 7-fold for CD8-LV and CD4-LV without compromising CAR T cell activities but does not improve VSV-LV. When administered to humanized mice, CD8-LV results in higher rates of green fluorescent protein (GFP) gene delivery. Also in vivo CAR T cell generation is improved in kinetics and tumor control, however to a moderate extent, leaving room for improvement by optimizing the rapamycin administration schedule. The data favor multi-omics approaches for improvements in gene delivery.

Phase 2 studies of lenalidomide, subcutaneous bortezomib, and dexamethasone as induction therapy in patients with newly diagnosed multiple myeloma.

There are limited prospective data on lenalidomide, subcutaneous bortezomib, and dexamethasone (RsqVd) in transplant-eligible/transplant-ineligible patients with newly diagnosed multiple myeloma. Reliable biomarkers for efficacy and toxicity are required to better tailor therapy. Two parallel studies were conducted by Cancer Trials Ireland (CTI; NCT02219178) and the Dana-Farber Cancer Institute (DFCI; NCT02441686). Patients received four 21-day cycles of RsqVd and could then receive either another 4 cycles of RsqVd or undergo autologous stem cell transplant. Postinduction/posttransplant, patients received lenalidomide maintenance, with bortezomib included for high-risk patients. The primary endpoint was overall response rate (ORR) after 4 cycles of RsqVd. Eighty-eight patients were enrolled and 84 treated across the two studies; median age was 64.7 (CTI study) and 60.0 years (DFCI study), and 59% and 57% had stage II-III disease. Pooled ORR after 4 cycles in evaluable patients was 93.5%, including 48.1% complete or very good partial responses (CTI study: 91.9%, 59.5%; DFCI study: 95.0%, 37.5%), and in the all-treated population was 85.7% (44.0%). Patients received a median of 4 (CTI study) and 8 (DFCI study) RsqVd cycles; 60% and 31% of patients (CTI study) and 33% and 51% of patients (DFCI study) underwent transplant or received further RsqVd induction, respectively. The most common toxicity was peripheral neuropathy (pooled: 68%, 7% grade 3-4; CTI study: 57%, 7%; DFCI study: 79%, 7%). Proteomics analyses indicated elevated kallikrein-6 in good versus poor responders, decreased midkine in good responders, and elevated macrophage inflammatory protein 1-alpha in patients who stopped treatment from neurotoxicity, suggesting predictive biomarkers warranting further investigation.

Identification of Protein Biomarker Signatures for Acute Myeloid Leukemia (AML) Using Both Nontargeted and Targeted Approaches.

Acute myeloid leukemia (AML) is characterized by an increasing number of clonal myeloid blast cells which are incapable of differentiating into mature leukocytes. AML risk stratification is based on genetic background, which also serves as a means to identify the optimal treatment of individual patients. However, constant refinements are needed, and the inclusion of significant measurements, based on the various omics approaches that are currently available to researchers/clinicians, have the potential to increase overall accuracy with respect to patient management. Using both nontargeted (label-free mass spectrometry) and targeted (multiplex immunoassays) proteomics, a range of proteins were found to be significantly changed in AML patients with different genetic backgrounds. The inclusion of validated proteomic biomarker panels could be an important factor in the prognostic classification of AML patients. The ability to measure both cellular and secreted analytes, at diagnosis and during the course of treatment, has advantages in identifying transforming biological mechanisms in patients, assisting important clinical management decisions.

S100 Calcium Binding Protein Family Members Associate With Poor Patient Outcome and Response to Proteasome Inhibition in Multiple Myeloma.

Despite several new therapeutic options, multiple myeloma (MM) patients experience multiple relapses and inevitably become refractory to treatment. Insights into drug resistance mechanisms may lead to the development of novel treatment strategies. The S100 family is comprised of 21 calcium binding protein members with 17 S100 genes located in the 1q21 region, which is commonly amplified in MM. Dysregulated expression of S100 family members is associated with tumor initiation, progression and inflammation. However, the relationship between the S100 family and MM pathogenesis and drug response is unknown. In this study, the roles of S100 members were systematically studied at the copy number, transcriptional and protein level with patients' survival and drug response. Copy number analysis revealed a predominant pattern of gains occurring in S100 genes clustering in the 1q21 locus. In general, gains of genes encoding S100 family members associated with worse patient survival. However, S100 gene copy number and S100 gene expression did not necessarily correlate, and high expression of S100A4 associated with poor patient survival. Furthermore, integrated analysis of S100 gene expression and ex vivo drug sensitivity data showed significant negative correlation between expression of S100 family members (S100A8, S100A9, and S100A12) and sensitivity to some drugs used in current MM treatment, including proteasome inhibitors (bortezomib, carfilzomib, and ixazomib) and histone deacetylase inhibitor panobinostat. Combined proteomic and pharmacological data exhibited significant negative association of S100 members (S100A4, S100A8, and S100A9) with proteasome inhibitors and panobinostat. Clinically, the higher expression of S100A4 and S100A10 were significantly linked to shorter progression free survival in patients receiving carfilzomib-based therapy. The results indicate an association and highlight the potential functional importance of S100 members on chromosome 1q21 in the development of MM and resistance to established myeloma drugs, including proteasome inhibitors.

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients.

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.

Saliva-omics in plasma cell disorders- Proof of concept and potential as a non-invasive tool for monitoring disease burden.

Multiple Myeloma (MM), the second most common lymphoid cancer worldwide, is characterised by the uninhibited proliferation of terminally differentiated B-lymphocytes. Leading to The diagnosis typically requires the presence of a monoclonal protein (M protein) and the demonstration of CRAB features (hypercalcemia, renal impairment, anaemia and bone lesions). MM is considered incurable as, due to serial clonal evolution, the vast majority of patients succumb to treatment-refractory disease. MGUS (Monoclonal Gammopathy of Unknown Uncertain Significance) is the pre-malignant form of MM and, although 93% of MM patients exhibit M protein production associated with MGUS before diagnosis, little is known about the switch from pre-malignant to malignant disease. To explore this disease transition further, LC-MS/MS analysis was carried out to identify potential salivary biomarkers to monitor disease burden. FABP5 was detected in saliva as having a significant increase in abundance when MGUS was compared to symptomatic MM. The levels of FABP5 decreased after treatment indicating correlation with tumour burden. This finding was validated using western blot analysis and ELISA analysis. SIGNIFICANCE: The field of biomarker discovery has focused largely on serum as a biofluid. Saliva is a readily available biofluid that, as a biomarker resource, has been relatively un-explored. The identification of changes in saliva indicating disease progression underlines the utility of saliva as a non-invasive source of informative biomarkers reflecting disease burden and progression.