PARP inhibition with rucaparib alone followed by combination with atezolizumab: Phase Ib COUPLET clinical study in advanced gynaecological and triple-negative breast cancers.

BACKGROUND: Combining PARP inhibitors (PARPis) with immune checkpoint inhibitors may improve clinical outcomes in selected cancers. We evaluated rucaparib and atezolizumab in advanced gynaecological or triple-negative breast cancer (TNBC). METHODS: After identifying the recommended dose, patients with PARPi-naive BRCA-mutated or homologous recombination-deficient/loss-of-heterozygosity-high platinum-sensitive ovarian cancer or TNBC received rucaparib plus atezolizumab. Tumour biopsies were collected pre-treatment, during single-agent rucaparib run-in, and after starting combination therapy. RESULTS: The most common adverse events with rucaparib 600 mg twice daily and atezolizumab 1200 mg on Day 1 every 3 weeks were gastrointestinal effects, fatigue, liver enzyme elevations, and anaemia. Responding patients typically had BRCA-mutated tumours and higher pre-treatment tumour levels of PD-L1 and CD8 + T cells. Markers of DNA damage repair decreased during rucaparib run-in and combination treatment in responders, but typically increased in non-responders. Apoptosis signature expression showed the reverse. CD8 + T-cell activity and STING pathway activation increased during rucaparib run-in, increasing further with atezolizumab. CONCLUSIONS: In this small study, rucaparib plus atezolizumab demonstrated acceptable safety and activity in BRCA-mutated tumours. Increasing anti-tumour immunity and inflammation might be a key mechanism of action for clinical benefit from the combination, potentially guiding more targeted development of such regimens. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (NCT03101280).

Detection of latent brain states from baseline neural activity in the amygdala.

The amygdala responds to a large variety of socially and emotionally salient environmental and interoceptive stimuli. The context in which these stimuli occur determines their social and emotional significance. In canonical neurophysiological studies, the fast-paced succession of stimuli and events induce phasic changes in neural activity. During inter-trial intervals neural activity is expected to return to a stable and relatively featureless baseline. Context, such as the presence of a social partner, or the similarity of trials in a blocked design, induces brain states that can transcend the fast-paced succession of stimuli and can be recovered from the baseline firing rate of neurons. Indeed, the baseline firing rates of neurons in the amygdala change between blocks of trials of gentle grooming touch, delivered by a trusted social partner, and non-social airflow stimuli, delivered by a computer-controlled air valve. In this experimental paradigm, the presence of the groomer alone was sufficient to induce small but significant changes in baseline firing rates. Here, we examine local field potentials (LFP) recorded during these baseline periods to determine whether context was encoded by network dynamics that emerge in the local field potentials from the activity of large ensembles of neurons. We found that machine learning techniques can reliably decode social vs. non-social context from spectrograms of baseline local field potentials. Notably, decoding accuracy improved significantly with access to broad-band information. No significant differences were detected between the nuclei of the amygdala that receive direct or indirect inputs from areas of the prefrontal cortex known to coordinate flexible, context-dependent behaviors. The lack of nuclear specificity suggests that context-related synaptic inputs arise from a shared source, possibly interoceptive inputs that signal the sympathetic- vs. parasympathetic-dominated states characterizing non-social and social blocks, respectively.

Efficient models of cortical activity via local dynamic equilibria and coarse-grained interactions.

Biologically detailed models of brain circuitry are challenging to build and simulate due to the large number of neurons, their complex interactions, and the many unknown physiological parameters. Simplified mathematical models are more tractable, but harder to evaluate when too far removed from neuroanatomy/physiology. We propose that a multiscale model, coarse-grained (CG) while preserving local biological details, offers the best balance between biological realism and computability. This paper presents such a model. Generally, CG models focus on the interaction between groups of neurons-here termed "pixels"-rather than individual cells. In our case, dynamics are alternately updated at intra- and interpixel scales, with one informing the other, until convergence to equilibrium is achieved on both scales. An innovation is how we exploit the underlying biology: Taking advantage of the similarity in local anatomical structures across large regions of the cortex, we model intrapixel dynamics as a single dynamical system driven by "external" inputs. These inputs vary with events external to the pixel, but their ranges can be estimated a priori. Precomputing and tabulating all potential local responses speed up the updating procedure significantly compared to direct multiscale simulation. We illustrate our methodology using a model of the primate visual cortex. Except for local neuron-to-neuron variability (necessarily lost in any CG approximation) our model reproduces various features of large-scale network models at a tiny fraction of the computational cost. These include neuronal responses as a consequence of their orientation selectivity, a primary function of visual neurons.

Targeting a lineage-specific PI3KÉ£-Akt signaling module in acute myeloid leukemia using a heterobifunctional degrader molecule.

Dose-limiting toxicity poses a major limitation to the clinical utility of targeted cancer therapies, often arising from target engagement in nonmalignant tissues. This obstacle can be minimized by targeting cancer dependencies driven by proteins with tissue-restricted and/or tumor-restricted expression. In line with another recent report, we show here that, in acute myeloid leukemia (AML), suppression of the myeloid-restricted PIK3CG/p110γ-PIK3R5/p101 axis inhibits protein kinase B/Akt signaling and compromises AML cell fitness. Furthermore, silencing the genes encoding PIK3CG/p110γ or PIK3R5/p101 sensitizes AML cells to established AML therapies. Importantly, we find that existing small-molecule inhibitors against PIK3CG are insufficient to achieve a sustained long-term antileukemic effect. To address this concern, we developed a proteolysis-targeting chimera (PROTAC) heterobifunctional molecule that specifically degrades PIK3CG and potently suppresses AML progression alone and in combination with venetoclax in human AML cell lines, primary samples from patients with AML and syngeneic mouse models.

PitViper: a software for comparative meta-analysis and annotation of functional screening data.

Recent advancements in shRNA and Cas protein technologies have enabled functional screening methods targeting genes or non-coding regions using single or pooled shRNA and sgRNA. CRISPR-based systems have also been developed for modulating DNA accessibility, resulting in CRISPR-mediated interference (CRISPRi) or activation (CRISPRa) of targeted genes or genomic DNA elements. However, there is still a lack of software tools for integrating diverse array of functional genomics screening outputs that could offer a cohesive framework for comprehensive data integration. Here, we developed PitViper, a flexible and interactive open-source software designed to fill this gap, providing reliable results for the type of elements being screened. It is an end-to-end automated and reproducible bioinformatics pipeline integrating gold-standard methods for functional screening analysis. Our sensitivity analyses demonstrate that PitViper is a useful tool for identifying potential super-enhancer liabilities in a leukemia cell line through genome-wide CRISPRi-based screening. It offers a robust, flexible, and interactive solution for integrating data analysis and reanalysis from functional screening methods, making it a valuable resource for researchers in the field.

The SAGA acetyltransferase module is required for the maintenance of MAF and MYC oncogenic gene expression programs in multiple myeloma.

Despite recent advances in therapeutic treatments, multiple myeloma (MM) remains an incurable malignancy. Epigenetic factors contribute to the initiation, progression, relapse, and clonal heterogeneity in MM, but our knowledge on epigenetic mechanisms underlying MM development is far from complete. The SAGA complex serves as a coactivator in transcription and catalyzes acetylation and deubiquitylation. Analyses of datasets in the Cancer Dependency Map Project revealed many SAGA components are selective dependencies in MM. To define SAGA-specific functions, we focused on ADA2B, the only subunit in the lysine acetyltransferase (KAT) module that specifically functions in SAGA. Integration of RNA-seq, ATAC-seq, and CUT&RUN results identified pathways directly regulated by ADA2B include MTORC1 signaling, MYC, E2F, and MM-specific MAF oncogenic programs. We discovered that ADA2B is recruited to MAF and MYC gene targets, and that MAF shares a majority of its targets with MYC in MM cells. Furthermore, we found the SANT domain of ADA2B is required for interaction with both GCN5 and PCAF acetyltransferases, incorporation into SAGA, and ADA2B protein stability. Our findings uncover previously unknown SAGA KAT module-dependent mechanisms controlling MM cell growth, revealing a vulnerability that might be exploited for future development of MM therapy.

Anti-CD19 Chimeric Antigen Receptor T-Cell Therapy for Richter Transformation: An International, Multicenter, Retrospective Study.

PURPOSE: Outcomes for Richter transformation (RT) are poor with current therapies. The efficacy and safety of anti-CD19 chimeric antigen receptor T-cell therapy (CAR-T) for RT are not established. METHODS: We performed an international multicenter retrospective study of patients with RT who received CAR-T. Patient, disease, and treatment characteristics were summarized using descriptive statistics, and modeling analyses were used to determine association with progression-free survival (PFS) and overall survival (OS). PFS and OS were estimated from the date of CAR-T infusion. RESULTS: Sixty-nine patients were identified. The median age at CAR-T infusion was 64 years (range, 27-80). Patients had a median of four (range, 1-15) previous lines of therapy for CLL and/or RT, including previous Bruton tyrosine kinase inhibitor and/or BCL2 inhibitor therapy in 58 (84%) patients. The CAR-T product administered was axicabtagene ciloleucel in 44 patients (64%), tisagenlecleucel in 17 patients (25%), lisocabtagene maraleucel in seven patients (10%), and brexucabtagene autoleucel in one patient (1%). Eleven patients (16%) and 25 patients (37%) experienced grade ≥3 cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome, respectively. The overall response rate was 63%, with 46% attaining a complete response (CR). After a median follow-up of 24 months, the median PFS was 4.7 months (95% CI, 2.0 to 6.9); the 2-year PFS was 29% (95% CI, 18 to 41). The median OS was 8.5 months (95% CI, 5.1 to 25.4); the 2-year OS was 38% (95% CI, 26 to 50). The median duration of response was 27.6 months (95% CI, 14.5 to not reached) for patients achieving CR. CONCLUSION: CAR-T demonstrates clinical efficacy for patients with RT.

Canonical AREs are tumor suppressive regulatory elements in the prostate.

The androgen receptor (AR) is the central determinant of prostate tissue identity and differentiation, controlling normal, growth-suppressive prostate-specific gene expression 1 . It is also a key driver of prostate tumorigenesis, becoming "hijacked" to drive oncogenic transcription 2-5 . However, the regulatory elements determining the execution of the growth suppressive AR transcriptional program, and whether this can be reactivated in prostate cancer (PCa) cells remains unclear. Canonical androgen response element (ARE) motifs are the classic DNA binding element for AR 6 . Here, we used a genome-wide strategy to modulate regulatory elements containing AREs to define distinct AR transcriptional programs. We find that activation of these AREs is specifically associated with differentiation and growth suppressive transcription, and this can be reactivated to cause death in AR + PCa cells. In contrast, repression of AREs is well tolerated by PCa cells, but deleterious to normal prostate cells. Finally, gene expression signatures driven by ARE activity are associated with improved prognosis and luminal phenotypes in human PCa patients. This study demonstrates that canonical AREs are responsible for a normal, growth-suppressive, lineage-specific transcriptional program, that this can be reengaged in PCa cells for potential therapeutic benefit, and genes controlled by this mechanism are clinically relevant in human PCa patients.

eSVD-DE: cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings.

BACKGROUND: Single-cell RNA-sequencing (scRNA) datasets are becoming increasingly popular in clinical and cohort studies, but there is a lack of methods to investigate differentially expressed (DE) genes among such datasets with numerous individuals. While numerous methods exist to find DE genes for scRNA data from limited individuals, differential-expression testing for large cohorts of case and control individuals using scRNA data poses unique challenges due to substantial effects of human variation, i.e., individual-level confounding covariates that are difficult to account for in the presence of sparsely-observed genes. RESULTS: We develop the eSVD-DE, a matrix factorization that pools information across genes and removes confounding covariate effects, followed by a novel two-sample test in mean expression between case and control individuals. In general, differential testing after dimension reduction yields an inflation of Type-1 errors. However, we overcome this by testing for differences between the case and control individuals' posterior mean distributions via a hierarchical model. In previously published datasets of various biological systems, eSVD-DE has more accuracy and power compared to other DE methods typically repurposed for analyzing cohort-wide differential expression. CONCLUSIONS: eSVD-DE proposes a novel and powerful way to test for DE genes among cohorts after performing a dimension reduction. Accurate identification of differential expression on the individual level, instead of the cell level, is important for linking scRNA-seq studies to our understanding of the human population.

The therapeutically actionable long non-coding RNA 'T-RECS' is essential to cancer cells' survival in NRAS/MAPK-driven melanoma.

Finding effective therapeutic targets to treat NRAS-mutated melanoma remains a challenge. Long non-coding RNAs (lncRNAs) recently emerged as essential regulators of tumorigenesis. Using a discovery approach combining experimental models and unbiased computational analysis complemented by validation in patient biospecimens, we identified a nuclear-enriched lncRNA (AC004540.4) that is upregulated in NRAS/MAPK-dependent melanoma, and that we named T-RECS. Considering potential innovative treatment strategies, we designed antisense oligonucleotides (ASOs) to target T-RECS. T-RECS ASOs reduced the growth of melanoma cells and induced apoptotic cell death, while having minimal impact on normal primary melanocytes. Mechanistically, treatment with T-RECS ASOs downregulated the activity of pro-survival kinases and reduced the protein stability of hnRNPA2/B1, a pro-oncogenic regulator of MAPK signaling. Using patient- and cell line- derived tumor xenograft mouse models, we demonstrated that systemic treatment with T-RECS ASOs significantly suppressed the growth of melanoma tumors, with no noticeable toxicity. ASO-mediated T-RECS inhibition represents a promising RNA-targeting approach to improve the outcome of MAPK pathway-activated melanoma.

RNF4 prevents genomic instability caused by chronic DNA under-replication.

Eukaryotic genome stability is maintained by a complex and diverse set of molecular processes. One class of enzymes that promotes proper DNA repair, replication and cell cycle progression comprises small ubiquitin-like modifier (SUMO)-targeted E3 ligases, or STUbLs. Previously, we reported a role for the budding yeast STUbL synthetically lethal with sgs1 (Slx) 5/8 in preventing G2/M-phase arrest in a minichromosome maintenance protein 10 (Mcm10)-deficient model of replication stress. Here, we extend these studies to human cells, examining the requirement for the human STUbL RING finger protein 4 (RNF4) in MCM10 mutant cancer cells. We find that MCM10 and RNF4 independently promote origin firing but regulate DNA synthesis epistatically and, unlike in yeast, the negative genetic interaction between RNF4 and MCM10 causes cells to accumulate in G1-phase. When MCM10 is deficient, RNF4 prevents excessive DNA under-replication at hard-to-replicate regions that results in large DNA copy number alterations and severely reduced viability. Overall, our findings highlight that STUbLs participate in species-specific mechanisms to maintain genome stability, and that human RNF4 is required for origin activation in the presence of chronic replication stress.

A scalable platform for efficient CRISPR-Cas9 chemical-genetic screens of DNA damage-inducing compounds.

Current approaches to define chemical-genetic interactions (CGIs) in human cell lines are resource-intensive. We designed a scalable chemical-genetic screening platform by generating a DNA damage response (DDR)-focused custom sgRNA library targeting 1011 genes with 3033 sgRNAs. We performed five proof-of-principle compound screens and found that the compounds' known modes-of-action (MoA) were enriched among the compounds' CGIs. These scalable screens recapitulated expected CGIs at a comparable signal-to-noise ratio (SNR) relative to genome-wide screens. Furthermore, time-resolved CGIs, captured by sequencing screens at various time points, suggested an unexpected, late interstrand-crosslinking (ICL) repair pathway response to camptothecin-induced DNA damage. Our approach can facilitate screening compounds at scale with 20-fold fewer resources than commonly used genome-wide libraries and produce biologically informative CGI profiles.

Up-to-Date Colonoscopy Use in Asian and Hispanic Subgroups in New York City, 2003-2016.

BACKGROUND: Colorectal cancer screening uptake in the United States overall has increased, but racial/ethnic disparities persist and data on colonoscopy uptake by racial/ethnic subgroups are lacking. We sought to better characterize these trends and to identify predictors of colonoscopy uptake, particularly among Asian and Hispanic subgroups. STUDY: We used data from the New York City Community Health Survey to generate estimates of up-to-date colonoscopy use in Asian and Hispanic subgroups across 6 time periods spanning 2003-2016. For each subgroup, we calculated the percent change in colonoscopy uptake over the study period and the difference in uptake compared to non-Hispanic Whites in 2015-2016. We also used multivariable logistic regression to identify predictors of colonoscopy uptake. RESULTS: All racial and ethnic subgroups with reliable estimates saw a net increase in colonoscopy uptake between 2003 and 2016. In 2015-2016, compared with non-Hispanic Whites, Puerto Ricans, Dominicans, and Central/South Americans had higher colonoscopy uptake, whereas Chinese, Asian Indians, and Mexicans had lower uptake. On multivariable analysis, age, marital status, insurance status, primary care provider, receipt of flu vaccine, frequency of exercise, and smoking status were the most consistent predictors of colonoscopy uptake (≥4 time periods). CONCLUSIONS: We found significant variation in colonoscopy uptake among Asian and Hispanic subgroups. We also identified numerous demographic, socioeconomic, and health-related predictors of colonoscopy uptake. These findings highlight the importance of examining health disparities through the lens of disaggregated racial/ethnic subgroups and have the potential to inform future public health interventions.

Fracture strength of screw-retained zirconia crowns assembled on zirconia and titanium implants.

PURPOSE: This in vitro study evaluated the fracture strength of screw-retained zirconia crowns connected to zirconia (Zr) and titanium (Ti) implants after undergoing a simulation of 5 years of clinical use. MATERIALS AND METHODS: Forty-eight screw-retained zirconia crowns were fabricated and assembled on four implant systems, with 12 in each group: (1) Zr implant (pure ceramic; Straumann AG) (PZr); (2) Zr implant (NobelPearl; Nobel Biocare) (NPZr); (3) Ti-Zr implant (Bone Level Roxolid; Straumann AG) (RSTiZr); (4) Ti implant (Conical Connection PMC; Nobel Biocare) (NRTi). Crowns were luted to their associated abutments using resin cement and then torqued to their assigned implants at the recommended torque value. Specimens were subjected to dynamic loading for 1,200,000 loading cycles. Fracture strength, measured in Newtons (N), was tested under static compression load using a universal testing machine at an angle of 30°. One-way ANOVA and Tukey's multiple comparisons post hoc test were used to compare the mean fracture values between the groups at a significance level of 0.05. RESULTS: The average fracture strengths for the RSTiZr and NRTi groups were 1207 ± 202 and 1073 ± 217 N, respectively, which was significantly (p < 0.0001) higher than the PZr and NPZr groups (712 ± 76 and 571.6 ± 167 N, respectively). However, no significant difference was found between the fracture strength value of RSTiZr and NRTi (p = 0.260) or PZr and NPZr (p = 0.256) groups. CONCLUSIONS: Zirconia crowns connected to Zr implants have the potential to withstand the average physiological occlusal forces which occur in the anterior and premolar regions.

eSVD-DE: Cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings.

Background: Single-cell RNA-sequencing (scRNA) datasets are becoming increasingly popular in clinical and cohort studies, but there is a lack of methods to investigate differentially expressed (DE) genes among such datasets with numerous individuals. While numerous methods exist to find DE genes for scRNA data from limited individuals, differential-expression testing for large cohorts of case and control individuals using scRNA data poses unique challenges due to substantial effects of human variation, i.e., individual-level confounding covariates that are difficult to account for in the presence of sparsely-observed genes. Results: We develop the eSVD-DE, a matrix factorization that pools information across genes and removes confounding covariate effects, followed by a novel two-sample test in mean expression between case and control individuals. In general, differential testing after dimension reduction yields an inflation of Type-1 errors. However, we overcome this by testing for differences between the case and control individuals' posterior mean distributions via a hierarchical model. In previously published datasets of various biological systems, eSVD-DE has more accuracy and power compared to other DE methods typically repurposed for analyzing cohort-wide differential expression. Conclusions: eSVD-DE proposes a novel and powerful way to test for DE genes among cohorts after performing a dimension reduction. Accurate identification of differential expression on the individual level, instead of the cell level, is important for linking scRNA-seq studies to our understanding of the human population.

Effects of sleep on breakfast behaviors in recently unemployed adults.

OBJECTIVES: Skipping meals is linked to negative cardiometabolic health outcomes. Few studies have examined the effects of breakfast skipping after disruptive life events, like job loss. The present analyses examine whether sleep timing, duration, and continuity are associated with breakfast eating among 186 adults who recently (past 90 days) experienced involuntary unemployment from the Assessing Daily Activity Patterns Through Occupational Transitions (ADAPT) study. METHODS: We conducted both cross-sectional and 18-month longitudinal analyses to assess the relationship between actigraphic sleep after job loss and breakfast eating. RESULTS: Later sleep timing was associated with a lower percentage of days breakfast was eaten at baseline (B = -0.09, SE = 0.02, P < .001) and longitudinally over 18 months (estimate = -0.04; SE = 0.02; P < .05). No other sleep indices were associated with breakfast consumption cross-sectionally or prospectively. CONCLUSIONS: Unemployed adults with a delay in sleep timing are more likely to skip breakfast than adults with an advancement in sleep timing. Future studies are necessary to test chronobiological mechanisms by which sleep timing might impact breakfast eating. With the understanding that sleep timing is linked to breakfast eating, the advancement of sleep timing may provide a pathway for the promotion of breakfast eating, ultimately preventing cardiometabolic disease.

Systematic comparison of rAAV vectors manufactured using large-scale suspension cultures of Sf9 and HEK293 cells.

Recombinant adeno-associated virus (rAAV) vectors could be manufactured by plasmid transfection into human embryonic kidney 293 (HEK293) cells or baculovirus infection of Spodoptera frugiperda (Sf9) insect cells. However, systematic comparisons between these systems using large-scale, high-quality AAV vectors are lacking. rAAV from Sf9 cells (Sf9-rAAV) at 2-50 L and HEK293 cells (HEK-rAAV) at 2-200 L scales were characterized. HEK-rAAV had ∼40-fold lower yields but ∼10-fold more host cell DNA measured by droplet digital PCR and next-generation sequencing, respectively. The electron microscope observed a lower full/empty capsid ratio in HEK-rAAV (70.8%) than Sf9-rAAV (93.2%), while dynamic light scattering and high-performance liquid chromatography analysis showed that HEK-rAAV had more aggregation. Liquid chromatography tandem mass spectrometry identified different post-translational modification profiles between Sf9-rAAV and HEK-rAAV. Furthermore, Sf9-rAAV had a higher tissue culture infectious dose/viral genome than HEK-rAAV, indicating better infectivity. Additionally, Sf9-rAAV achieved higher in vitro transgene expression, as measured by ELISA. Finally, after intravitreal dosing into a mouse laser choroidal neovascularization model, Sf9-rAAV and HEK-rAAV achieved similar efficacy. Overall, this study detected notable differences in the physiochemical characteristics of HEK-rAAV and Sf9-rAAV. However, the in vitro and in vivo biological functions of the rAAV from these systems were highly comparable. Sf9-rAAV may be preferred over HEK293-rAAV for advantages in yields, full/empty ratio, scalability, and cost.

The therapeutically actionable long non-coding RNA 'T-RECS' is essential to cancer cells' survival in NRAS/MAPK-driven melanoma.

Finding effective therapeutic targets to treat NRAS-mutated melanoma remains a challenge. Long non-coding RNAs (lncRNAs) recently emerged as essential regulators of tumorigenesis. Using a discovery approach combining experimental models and unbiased computational analysis complemented by validation in patient biospecimens, we identified a nuclear-enriched lncRNA (AC004540.4) that is upregulated in NRAS/MAPK-dependent melanoma, and that we named T-RECS. Considering potential innovative treatment strategies, we designed antisense oligonucleotides (ASOs) to target T-RECS. T-RECS ASOs reduced the growth of melanoma cells and induced apoptotic cell death, while having minimal impacton normal primary melanocytes. Mechanistically, treatment with T-RECS ASOs downregulated the activity of pro-survival kinases and reduced the protein stability of hnRNPA2/B1, a pro-oncogenic regulator of MAPK signaling. Using patient- and cell line- derived tumor xenograft mouse models, we demonstrated that systemic treatment with T-RECS ASOs significantly suppressed the growth of melanoma tumors, with no noticeable toxicity. ASO-mediated T-RECS inhibition represents a promising RNA-targeting approach to improve the outcome of MAPK pathway-activated melanoma.

Breast Cancer Treatment: To tARget or Not? That Is the Question.

To assess AR's role in TNBC treatment, various existing and completed clinical trials targeting AR or co-targeting AR with other pertinent signaling molecules were analyzed. Cyclin-dependent kinase 4/6 (CDK4/6), cytochrome P450 17α-hydroxylase/17,20-lyase (CYP17 lyase), and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway were some of the most prevalent biomarkers used in combination therapy with AR inhibitors in these trials. Studying how AR functions in tandem with these molecules can have increasing breakthroughs in the treatment options for TNBC. Previous studies have been largely unsuccessful in utilizing AR as the sole drug target for systemic targeted treatment in TNBC. However, there is a lack of other commonly used drug target biomarkers in the treatment of this disease, as well. Thus, analyzing the clinical benefit rate (CBR) within clinical trials that use combination therapy can prove to be imperative to the progression of improving treatment options and prognoses.

Immobilization of azide-functionalized proteins to micro- and nanoparticles directly from cell lysate.

Immobilization of proteins and enzymes on solid supports has been utilized in a variety of applications, from improved protein stability on supported catalysts in industrial processes to fabrication of biosensors, biochips, and microdevices. A critical requirement for these applications is facile yet stable covalent conjugation between the immobilized and fully active protein and the solid support to produce stable, highly bio-active conjugates. Here, we report functionalization of solid surfaces (gold nanoparticles and magnetic beads) with bio-active proteins using site-specific and biorthogonal labeling and azide-alkyne cycloaddition, a click chemistry. Specifically, we recombinantly express and selectively label calcium-dependent proteins, calmodulin and calcineurin, and cAMP-dependent protein kinase A (PKA) with N-terminal azide-tags for efficient conjugation to nanoparticles and magnetic beads. We successfully immobilized the proteins on to the solid supports directly from the cell lysate with click chemistry, forgoing the step of purification. This approach is optimized to yield low particle aggregation and high levels of protein activity post-conjugation. The entire process enables streamlined workflows for bioconjugation and highly active conjugated proteins.