Biology subjects

Varadhan, R.

Publications and source records attributed to Varadhan, R..

5 recordsLinked to original sources

bioRxiv2024

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable, but is hindered by the limited performance of existing biomarkers. Here, we leveraged in-silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We tested 90 biomarker candidates, including various cellular and molecular species, by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pre-treatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.

systems biology↗

bioRxiv2023

Spatial and Compositional Biomarkers in Tumor Microenvironment Predicts Clinical Outcomes in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options, which warrants identification of novel therapeutic targets. Deciphering nuances in the tumor microenvironment (TME) may unveil insightful links between anti-tumor immunity and clinical outcomes, yet such connections remain underexplored. Here we employed a dataset derived from imaging mass cytometry of 58 TNBC patient specimens at single-cell resolution and performed in-depth quantifications with a suite of multi-scale computational algorithms. We detected distinct cell distribution patterns among clinical subgroups, potentially stemming from different infiltration related to tumor vasculature and fibroblast heterogeneity. Spatial analysis also identified ten recurrent cellular neighborhoods (CNs) - a collection of local TME characteristics with unique cell components. Coupling of the prevalence of pan-immune and perivasculature immune hotspot CNs, enrichment of inter-CN interactions was associated with improved survival. Using a deep learning model trained on engineered spatial data, we can with high accuracy (mean AUC of 5-fold cross-validation = 0.71) how a separate cohort of patients in the NeoTRIP clinical trial will respond to treatment based on baseline TME features. These data reinforce that the TME architecture is structured in cellular compositions, spatial organizations, vasculature biology, and molecular profiles, and suggest novel imaging-based biomarkers for treatment development in the context of TNBC.

bioinformatics↗

bioRxiv2021

Engineering CAR-NK cells to secrete IL15 sustains their anti-AML functionality, but is associated with systemic toxicities

BackgroundThe prognosis of patients with recurrent/refractory acute myelogenous leukemia (AML) remains poor and cell-based immunotherapies hold promise to improve outcomes. NK cells can elicit an anti-leukemic response via a repertoire of activating receptors that bind AML surface ligands. NK cell adoptive transfer is safe but thus far has shown limited anti-AML efficacy. Here, we aimed to overcome this limitation by engineering NK cells to express chimeric antigen receptors (CARs) to boost their anti-AML activity, and interleukin-15 (IL15) to enhance their persistence. MethodsWe characterized in detail NK cell populations expressing a panel of AML (CD123)-specific CARs and/or IL15 in vitro and in AML xenograft models. ResultsCARs with 2B4.{zeta} or 4-1BB.{zeta} signaling domains demonstrated greater cell surface expression and endowed NK cells with improved anti-AML activity in vitro. Initial in vivo testing revealed that only 2B4.{zeta} CAR-NK cells had improved anti-AML activity in comparison to untransduced (UTD) and 4-1BB.{zeta} CAR-NK cells. However, the benefit was transient due to limited CAR-NK cell persistence. Transgenic expression of secretory (s)IL15 in 2B4.{zeta} CAR and UTD NK cells improved their effector function in the setting of chronic antigen simulation in vitro. Multiparameter flow analysis after chronic antigen exposure identified the expansion of unique NK cell subsets. 2B4.{zeta}/sIL15 CAR and sIL15 NK cells maintained an overall activated NK cell phenotype. This was confirmed by transcriptomic analysis, which revealed a highly proliferative and activated signature in these NK cell groups. In vivo, 2B4.{zeta}/sIL15 CAR-NK cells had potent anti-AML activity in one model, while 2B4.{zeta}/sIL15 CAR and sIL15 NK cells induced lethal toxicity in a second model. ConclusionTransgenic expression of CD123-CARs and sIL15 enabled NK cells to function in the setting of chronic antigen exposure but was associated with systemic toxicities. Thus, our study provides the impetus to explore inducible and controllable expression systems to provide cytokine signals to AML-specific CAR-NK cells before embarking on early phase clinical testing. O_FIG O_LINKSMALLFIG WIDTH=161 HEIGHT=200 SRC="FIGDIR/small/461509v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@4d09eaorg.highwire.dtl.DTLVardef@1c61411org.highwire.dtl.DTLVardef@14f8097org.highwire.dtl.DTLVardef@8375ac_HPS_FORMAT_FIGEXP M_FIG C_FIG In BriefSecretion of IL15 from anti-CD123.2B4.CD3{zeta} CAR-NK cells enhances their activation and killing potential against Acute Myelogenous Leukemia, but carries the risk of severe systemic toxicity.

immunology↗

bioRxiv2021

The role of the atypical chemokine receptor CCRL2 in myelodysplastic syndrome and secondary acute myeloid leukemia

The identification of new molecular pathways supporting the growth of myelodysplastic syndrome (MDS) stem and progenitor cells is needed to understand clinical variation and develop targeted therapies. Within myeloid malignancies, men have worse outcomes compared to women, suggesting male sex hormone driven effects in malignant hematopoiesis. The androgen receptor promotes the expression of five granulocyte-colony factor receptor regulated genes. Among them, CCRL2 encodes an atypical chemokine receptor that regulates cytokine signaling in differentiated granulocytes but its role in myeloid malignancies is unknown. Our study revealed that CCRL2 is upregulated in stem and progenitor cells from patients with MDS and secondary acute leukemia. CCRL2 knockdown suppressed the growth and clonogenicity of MDS92 and MDS-L cells in vitro and in vivo. Moreover, CCRL2 knockdown significantly suppressed the phosphorylation of JAK2, STAT3, and STAT5 in MDS cells. CCRL2 co-precipitated with JAK2 and its suppression decreased the interaction of JAK2 with STAT proteins. Cell lines expressing JAK2V617F showed less effect of CCRL2 knockdown on growth and clonogenicity compared to those expressing wild type. However, the selective JAK2 inhibitor fedratinib potentiated the effects of CCRL2 knockdown in MDS and leukemia cells expressing both wild type JAK2 and JAK2V617F. In conclusion, our results implicate CCRL2 as a mediator of MDS and secondary acute leukemia cell growth, in part through JAK2/STAT signaling.

cancer biology↗

bioRxiv2017

Patterns of sedentary and active time accumulation are associated with mortality in US adults: The NHANES study

PurposeSedentary behavior has become a public health pandemic and has been associated with a variety of comorbidities including cardiovascular disease, type 2 diabetes, and some cancers. Previous studies have also shown that excessive amount of sedentary behavior is associated with all-cause mortality. However, no studies investigated whether patterns of sedentary and active time accumulation are associated with mortality independently of total sedentary and total active times. This study addresses this question by i) comparing several analytical ways to quantify patterns of both sedentary and active time accumulation through metrics of fragmentation of objectively-measured physical activity and ii) exploring the association of these metrics with all-cause mortality in a nationally representative US sample of elderly adults.\n\nMethodsThe accelerometry data of 3400 participants aged 50 to 84 in the National Health and Nutrition Examination Survey 2003-2006 cohorts were analyzed. Ten fragmentation metrics were calculated to quantify the duration of sedentary and active bouts: average bout duration, Gini index, average hazard, between-state transition probability, and the parameter of power law distribution. The association of these fragmentation metrics with all-cause mortality followed through December 31, 2011 was assessed with survey-weighted Cox proportional hazard models.\n\nResultsIn models adjusted for age, sex, race/ethnicity, education, body mass index, common comorbidities, and total sedentary/active time, four fragmentation metrics were associated with lower mortality risk: average active bout duration (HR=0.72 for 1SD increase, 95% CI = 0.590.88), Gini index for active bouts (HR = 0.75, 95% CI = 0.64-0.86), the parameter of power law distribution for sedentary bouts (HR = 0.75, 95% CI = 0.63-0.90), and sedentary-to-active transition probability (HR = 0.77, 95% CI = 0.61-0.96), and four fragmentation metrics were associated with higher mortality risk: the active-to-sedentary transition probability (HR = 1.40, 95% CI=1.23-1.58), the parameter of power law distribution for active bouts (HR = 1.33, 95% CI = 1.16-1.52), average hazard for durations of active bouts (HR = 1.32, 95% CI = 1.18-1.48), and average sedentary bout duration (HR =1.07, 95% CI = 1.01-1.13). After sensitivity analysis, average sedentary bout duration and sedentary-to-active transition probability became insignificant.\n\nConclusionLonger average duration of active bouts, a lower probability of transitioning from active to sedentary behavior, and a higher normalized variability of active bout durations were strongly negatively associated with all-cause mortality independently of total active time. A larger proportion of longer sedentary bouts were positively associated with all-cause mortality independently of total sedentary time. The results also suggested a nonlinear association of average active bout duration with mortality that corresponded to the largest risk increase in subjects with average active bout duration less than 3 minutes.

epidemiology↗