Biomarkers of response to ibrutinib plus nivolumab in relapsed diffuse large B-cell lymphoma, follicular lymphoma, or Richter's transformation

Biomarcadors; Ibrutinib; Limfoma no hodgkinBiomarkers; Ibrutinib; Non-hodgkin's lymphomaBiomarcadores; Ibrutinib; Linfoma no hodgkinWe analyzed potential biomarkers of response to ibrutinib plus nivolumab in biopsies from patients with diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and Richter's transformation (RT) from the LYM1002 phase I/IIa study, using programmed death ligand 1 (PD-L1) immunohistochemistry, whole exome sequencing (WES), and gene expression profiling (GEP). In DLBCL, PD-L1 elevation was more frequent in responders versus nonresponders (5/8 [62.5%] vs. 3/16 [18.8%]; p = 0.065; complete response 37.5% vs. 0%; p = 0.028). Overall response rates for patients with WES and GEP data, respectively, were: DLBCL (38.5% and 29.6%); FL (46.2% and 43.5%); RT (76.5% and 81.3%). In DLBCL, WES analyses demonstrated that mutations in RNF213 (40.0% vs. 6.2%; p = 0.055), KLHL14 (30.0% vs. 0%; p = 0.046), and LRP1B (30.0% vs. 6.2%; p = 0.264) were more frequent in responders. No responders had mutations in EBF1, ADAMTS20, AKAP9, TP53, MYD88 , or TNFRSF14 , while the frequency of these mutations in nonresponders ranged from 12.5% to 18.8%. In FL and RT, genes with different mutation frequencies in responders versus nonresponders were: BCL2 (75.0% vs. 28.6%; p = 0.047) and ROS1 (0% vs. 50.0%; p = 0.044), respectively. Per GEP, the most upregulated genes in responders were LEF1 and BTLA (overall), and CRTAM (germinal center B-cell–like DLBCL). Enriched pathways were related to immune activation in responders and resistance-associated proliferation/replication in nonresponders. This preliminary work may help to generate hypotheses regarding genetically defined subsets of DLBCL, FL, and RT patients most likely to benefit from ibrutinib plus nivolumab.Sponsored by Janssen Research & Development, LLC

The In Vivo Kinetics of RNA Polymerase II Elongation during Co-Transcriptional Splicing

Kinetic analysis shows that RNA polymerase elongation kinetics are not modulated by co-transcriptional splicing and that post-transcriptional splicing can proceed at the site of transcription without the presence of the polymerase

Biomarkers of response to ibrutinib plus nivolumab in relapsed diffuse large B-cell lymphoma, follicular lymphoma, or Richter's transformation

We analyzed potential biomarkers of response to ibrutinib plus nivolumab in biopsies from patients with diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and Richter's transformation (RT) from the LYM1002 phase I/IIa study, using programmed death ligand 1 (PD-L1) immunohistochemistry, whole exome sequencing (WES), and gene expression profiling (GEP). In DLBCL, PD-L1 elevation was more frequent in responders versus nonresponders (5/8 [62.5%] vs. 3/16 [18.8%]; p = 0.065; complete response 37.5% vs. 0%; p = 0.028). Overall response rates for patients with WES and GEP data, respectively, were: DLBCL (38.5% and 29.6%); FL (46.2% and 43.5%); RT (76.5% and 81.3%). In DLBCL, WES analyses demonstrated that mutations in RNF213 (40.0% vs. 6.2%; p = 0.055), KLHL14 (30.0% vs. 0%; p = 0.046), and LRP1B (30.0% vs. 6.2%; p = 0.264) were more frequent in responders. No responders had mutations in EBF1, ADAMTS20, AKAP9, TP53, MYD88, or TNFRSF14, while the frequency of these mutations in nonresponders ranged from 12.5% to 18.8%. In FL and RT, genes with different mutation frequencies in responders versus nonresponders were: BCL2 (75.0% vs. 28.6%; p = 0.047) and ROS1 (0% vs. 50.0%; p = 0.044), respectively. Per GEP, the most upregulated genes in responders were LEF1 and BTLA (overall), and CRTAM (germinal center B-cell-like DLBCL). Enriched pathways were related to immune activation in responders and resistance-associated proliferation/replication in nonresponders. This preliminary work may help to generate hypotheses regarding genetically defined subsets of DLBCL, FL, and RT patients most likely to benefit from ibrutinib plus nivoluma

The differential interaction of snRNPs with pre-mRNA reveals splicing kinetics in living cells

GFP-tagged snRNP components reveal the dynamics and rate for spliceosome assembly in vivo

Biological Insights From Plasma Proteomics of Non-small Cell Lung Cancer Patients Treated With Immunotherapy

INTRODUCTION: Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. METHODS: Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. RESULTS: The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. CONCLUSIONS: Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome

The In Vivo Kinetics of RNA Polymerase II Elongation during Co-Transcriptional Splicing

Kinetic analysis shows that RNA polymerase elongation kinetics are not modulated by co-transcriptional splicing and that post-transcriptional splicing can proceed at the site of transcription without the presence of the polymerase

Evolutionary Psychology and Mental Health

AN EVOLUTIONARY PERSPECTIVE revolutionized our understanding of behavior over a generation ago, but most mental health clinicians and researchers still view evolution as an interesting or even threatening alternative, instead of recognizing it as an essential basic science for understanding mental disorders. Many factors explain this lag in incorporating new knowledge, but the most important may be the clinician’s pragmatic focus on finding ways to help people now. Evolutionary researchers have not found a new treatment for a single mental disorder, so why should mental health clinicians and researchers care about evolutionary psychology (EP)? This chapter attempts to answer that question. The greatest value of an evolutionary approach is not some specific find- ing or new therapy, but is instead the framework it provides for uniting all aspects of a biopsychosocial model. Perhaps equally valuable is the deeper empathy fostered by an evolutionary perspective on life’s vicissitudes. An evolutionary perspective does not compete with other theories that try to explain why some people have mental disorders and others do not. Instead, it asks a fundamentally differ- ent question: Why has natural selection left all humans so vulnerable to mental disorders? At first, the question seems senseless. Natural selection shapes mecha- nisms that work, so how can it help us understand why the mind fails? It is also difficult to see how it is useful to know why we are vulnerable. Who cares why all humans are vulnerable to depression, when the goal is to help the individual who is depressed here and now? Surmounting these conceptual hurdles is a challenge that requires time and effort. Researchers and clinicians will make the effort when they know what evolution offers to the understanding of mental disorders.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145726/1/Nesse - 2015 - Evolutionary Psychology and Mental Health.pdfDescription of Nesse - 2015 - Evolutionary Psychology and Mental Health.pdf : Chapte