Biology subjects

Wiita, A. P.

Publications and source records attributed to Wiita, A. P..

25 records · Page 2Linked to original sources

bioRxiv2019

Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis

Multiple myeloma (MM) cell lines are routinely used to model the disease. However, a long-standing question is how well these cell lines truly represent tumor cells in patients. Here, we employ a recently-described method of transcriptional correlation profiling to compare similarity of 66 MM cell lines to 779 newly-diagnosed MM patient tumors. We found that individual MM lines differ significantly with respect to patient tumor representation, with median R ranging from 0.35-0.54. ANBL-6 was the "best" line, markedly exceeding all others (p < 2.2e-16). Notably, some widely-used cell lines (RPMI-8226, U-266) scored poorly in our patient similarity ranking (48 and 52 of 66, respectively). Lines cultured with interleukin-6 showed significantly improved correlations with patient tumor (p = 9.5e-4). When common MM genomic features were matched between cell lines and patients, only t(4;14) and t(14;16) led to increased transcriptional correlation. To demonstrate utility of our top-ranked line for preclinical studies, we showed that intravenously-implanted ANBL-6 proliferates in hematopoietic organs in immunocompromised mice. Overall, our large-scale quantitative correlation analysis, utilizing emerging datasets, provides a resource informing the MM community of cell lines that may be most reliable for modeling patient disease while also elucidating biological differences between cell lines and tumors.

cancer biology↗

bioRxiv2019

CRISPR-based screens uncover determinants of immunotherapy response and potential combination therapy strategies

Cancer cells commonly develop resistance to immunotherapy by loss of antigen expression. Combinatorial treatments that increase levels of the target antigen on the surface of cancer cells have the potential to restore efficacy to immunotherapy. Here, we use our CRISPR interference and CRISPR activation-based functional genomics platform to systematically identify pathways controlling cell-surface expression of the multiple myeloma immunotherapy antigen - B cell maturation antigen, BCMA. We discovered that pharmacological inhibition of HDAC7 and the Sec61 complex increased cell-surface BCMA, including in primary patient cells. Importantly, pharmacological Sec61 inhibition enhanced the anti-myeloma efficacy of a BCMA-targeted antibody-drug conjugate. A CRISPR interference CAR-T coculture screen enabled us to identify both antigen-dependent and -independent mechanisms controlling response of myeloma cells to BCMA-targeted CAR-T cells. Thus, our study demonstrates the potential of CRISPR screens to uncover mechanisms controlling response of cancer cells to immunotherapy and to suggest potential combination therapies. Key PointsO_LIUsing CRISPR screens, we systematically identify mechanisms increasing expression of the immunotherapy target BCMA and ADC efficacy. C_LIO_LIWe also identify antigen-independent mechanisms regulating response of cancer cells to BCMA-CAR-T cells. C_LI

cancer biology↗

bioRxiv2019

Mitochondrial dysfunction is signaled to the integrated stress response by OMA1, DELE1 and HRI

In mammalian cells, mitochondrial dysfunction triggers the integrated stress response (ISR), in which eIF2 phosphorylation upregulates the transcription factor ATF4. However, how mitochondrial stress is relayed to the ISR is unknown. We found that HRI is the eIF2 kinase necessary and sufficient for this relay. Using an unbiased CRISPRi screen, we identified factors upstream of HRI: OMA1, a mitochondrial stress-activated protease, and DELE1, a little-characterized protein we found to be associated with the inner mitochondrial membrane. Mitochondrial stress stimulates the OMA1-dependent cleavage of DELE1, leading to its accumulation in the cytosol, where it interacts with HRI and activates its eIF2 kinase activity. Blockade of the OMA1-DELE1-HRI pathway is beneficial during some, but not all types of mitochondrial stress, and leads to an alternative response that induces specific molecular chaperones. Therefore, this pathway is a potential therapeutic target enabling fine-tuning of the ISR for beneficial outcomes in diseases involving mitochondrial dysfunction.

cell biology↗

bioRxiv2019

Integrated Phosphoproteomics and Transcriptional Classifiers Reveal Hidden RAS Signaling Dynamics in Multiple Myeloma

A major driver of multiple myeloma is thought to be aberrant signaling, yet no kinase inhibitors have proven successful in the clinic. Here, we employ an integrated, systems approach combining phosphoproteomic and transcriptome analysis to dissect cellular signaling in multiple myeloma to inform precision medicine strategies. Collectively, these predictive models identify vulnerable signaling signatures and highlight surprising differences in functional signaling patterns between NRAS and KRAS mutants invisible to the genomic landscape. Transcriptional analysis suggests that aberrant MAPK pathway activation is only present in a fraction of RAS-mutated vs. WT RAS patients. These high-MAPK patients, enriched for NRAS Q61 mutations, have inferior outcomes whereas RAS mutations overall carry no survival impact. We further develop an interactive software tool to relate pharmacologic and genetic kinase dependencies in myeloma. These results may lead to improved stratification of MM patients in clinical trials while also revealing unexplored modes of Ras biology.

cancer biology↗

bioRxiv2018

Proteasome inhibitor-induced modulation reveals the spliceosome as a specific therapeutic vulnerability in multiple myeloma

Enhancing the efficacy of proteasome inhibitors is a central goal in myeloma therapy. We proposed that signaling-level responses after PI would reveal new mechanisms of action that could be therapeutically exploited. Unbiased phosphoproteomics after the PI carfilzomib surprisingly demonstrated the most prominent phosphorylation changes on splicing related proteins. Spliceosome modulation was invisible to RNA or protein abundance alone. Transcriptome analysis after PI demonstrated broad-scale intron retention, suggestive of spliceosome interference, as well as specific alternative splicing of protein homeostasis machinery components. These findings led us to evaluate direct spliceosome inhibition in myeloma, which synergized with carfilzomib and showed potent anti-tumor activity. Functional genomics and exome sequencing further supported the spliceosome as a specific vulnerability in myeloma. Our results propose splicing interference as an unrecognized modality of PI mechanism, reveal additional modes of spliceosome modulation, and suggest spliceosome targeting as a promising therapeutic strategy in myeloma. SignificanceNew ways to enhance PI efficacy are of major interest. We combine systems-level analyses to discover that PIs specifically interfere with splicing and that myeloma is selectively vulnerable to spliceosome inhibition. We reveal a new approach to advance myeloma therapy and uncover broader roles of splicing modulation in cancer.

cancer biology↗

bioRxiv2017

Repurposing Tofacitinib As An Anti-Myeloma Therapeutic To Reverse Growth-Promoting Effects Of The Bone Marrow Microenvironment

The myeloma bone marrow microenvironment promotes proliferation of malignant plasma cells and resistance to therapy. Interleukin-6 (IL-6) and downstream JAK/STAT signaling are thought to be central components of these microenvironment-induced phenotypes. In a prior drug repurposing screen, we identified tofacitinib, a pan-JAK inhibitor FDA-approved for rheumatoid arthritis, as an agent that may reverse the tumor-stimulating effects of bone marrow mesenchymal stromal cells. Here, we validated both in vitro, in stromal-responsive human myeloma cell lines, and in vivo, in orthotopic disseminated murine xenograft models of myeloma, that tofacitinib showed both single-agent and combination therapeutic efficacy in myeloma models. Surprisingly, we found that ruxolitinib, an FDA-approved agent targeting JAK1 and JAK2, did not lead to the same anti-myeloma effects. Combination with a novel irreversible JAK3-selective inhibitor also did not enhance ruxolitinib effects. RNA-seq and unbiased phosphoproteomics revealed that marrow stromal cells stimulate a JAK/STAT-mediated proliferative program in myeloma plasma cells, and tofacitinib reversed the large majority of these pro-growth signals. Taken together, our results suggest that tofacitinib specifically reverses the growth-promoting effects of the tumor microenvironment through blocking an IL-6-mediated signaling axis. As tofacitinib is already FDA-approved, these results can be rapidly translated into potential clinical benefits for myeloma patients.

cancer biology↗

bioRxiv2016

Time-resolved proteomics vs. ribosome profiling reveals translation dynamics under stress

Many small molecule chemotherapeutics induce stresses that globally inhibit mRNA translation, remodeling the cancer proteome and governing response to treatment. Here we measured protein synthesis in multiple myeloma cells treated with low-dose bortezomib by coupling pulsed-SILAC (pSILAC) with high-accuracy targeted quantitative proteomics. We found that direct measurement of protein synthesis by pSILAC correlated well with the indirect measurement of protein synthesis by ribosome profiling under conditions of robust translation. By developing a statistical model integrating longitudinal proteomic and mRNA-seq measurements, we found that proteomics could directly detect global alterations in translational rate as a function of therapy-induced stress after prolonged bortezomib exposure. Finally, the model we develop here, in combination with our experimental data including both protein synthesis and degradation, predicts changes in proteome remodeling under a variety of cellular perturbations. pSILAC therefore provides an important complement to ribosome profiling in directly measuring proteome dynamics under conditions of cellular stress.

cancer biology↗