Secretome Analysis Using Affinity Proteomics and Immunoassays: A Focus on Tumor Biology.

The study of the cellular secretome using proteomic techniques continues to capture the attention of the research community across a broad range of topics in biomedical research. Due to their untargeted nature, independence from the model system used, historically superior depth of analysis, as well as comparative affordability, mass spectrometry-based approaches traditionally dominate such analyses. More recently, however, affinity-based proteomic assays have massively gained in analytical depth, which together with their high sensitivity, dynamic range coverage as well as high throughput capabilities render them exquisitely suited to secretome analysis. In this review, we revisit the analytical challenges implied by secretomics and provide an overview of affinity-based proteomic platforms currently available for such analyses, using the study of the tumor secretome as an example for basic and translational research.

PI3K/AKT confers intrinsic and acquired resistance to pirtobrutinib in chronic lymphocytic leukemia.

PURPOSE: Pirtobrutinib, a non-covalent Bruton's tyrosine kinase (BTK) inhibitor, has been approved as the first agent to overcome resistance to covalent BTK inhibitors (such as ibrutinib, acalabrutinib, and zanubrutinib). However, the mechanisms of pirtobrutinib resistance in chronic lymphocytic leukemia (CLL) remain poorly understood. METHODS: To investigate pirtobrutinib resistance, we established resistant cell models using BTK knock-out via CRISPR-Cas9 or chronic exposure to pirtobrutinib in MEC-1 cells. These models mimicked intrinsic or acquired resistance, respectively. We then analyzed differential protein expression between wild-type (WT) and resistant MEC-1 cells using Revers Phase Protein microArray (RPPA) and confirmed the findings through Western Blot. Additionally, we evaluated potential drugs to overcome pirtobrutinib resistance by conducting cell proliferation assays, apoptosis studies, and animal experiments using both sensitive and resistant cells. RESULTS: MEC-1 cells developed resistance to pirtobrutinib either through BTK knock-out or prolonged drug exposure over three months. RPPA analysis revealed significant activation of proteins related to the PI3K/AKT pathway, including AKT and S6, in the resistant cells. Western Blot confirmed increased phosphorylation of AKT and S6 in pirtobrutinib-resistant MEC-1 cells. Notably, both the PI3K inhibitor (CAL101) and the AKT inhibitor (MK2206) effectively reduced cell proliferation and induced apoptosis in the resistant cells. The anti-tumor efficacy of these drugs was mediated by inhibiting the PI3K/AKT pathway. In vivo animal studies further supported the potential of targeting PI3K/AKT to overcome both intrinsic and acquired resistance to pirtobrutinib. CONCLUSION: The PI3K/AKT pathway plays a crucial role in both intrinsic and acquired resistance to pirtobrutinib in CLL. Therapeutically targeting this pathway may offer a promising strategy to overcome pirtobrutinib resistance.

Reverse Phase Proteomic Array Profiling of Asparagine Synthetase Expression in Newly Diagnosed Acute Myeloid Leukemia.

Asparaginase-based therapy is a cornerstone in acute lymphoblastic leukemia (ALL) treatment, capitalizing on the methylation status of the asparagine synthetase (ASNS) gene, which renders ALL cells reliant on extracellular asparagine. Contrastingly, ASNS expression in acute myeloid leukemia (AML) has not been thoroughly investigated, despite studies suggesting that AML with chromosome 7/7q deletions might have reduced ASNS levels. Here, we leverage reverse phase protein arrays to measure ASNS expression in 810 AML patients and assess its impact on outcomes. We find that AML with inv(16) has the lowest overall ASNS expression. While AML with deletion 7/7q had ASNS levels slightly lower than those of AML without deletion 7/7q, this observation was not significant. Low ASNS expression correlated with improved overall survival (46 versus 54 weeks, respectively, p = 0.011), whereas higher ASNS levels were associated with better response to venetoclax-based therapy. Protein correlation analysis demonstrated association between ASNS and proteins involved in methylation and DNA repair. In conclusion, while ASNS expression was not lower in patients with deletion 7/7q as initially predicted, ASNS levels were highly variable across AML patients. Further studies are needed to assess whether patients with low ASNS expression are susceptible to asparaginase-based therapy due to their inability to augment compensatory ASNS expression upon asparagine depletion.

Comparison of RNA-Seq and microarray in the prediction of protein expression and survival prediction.

Gene expression profiling using RNA-sequencing (RNA-seq) and microarray technologies is widely used in cancer research to identify biomarkers for clinical endpoint prediction. We compared the performance of these two methods in predicting protein expression and clinical endpoints using The Cancer Genome Atlas (TCGA) datasets of lung cancer, colorectal cancer, renal cancer, breast cancer, endometrial cancer, and ovarian cancer. We calculated the correlation coefficients between gene expression measured by RNA-seq or microarray and protein expression measured by reverse phase protein array (RPPA). In addition, after selecting the top 103 survival-related genes, we compared the random forest survival prediction model performance across test platforms and cancer types. Both RNA-seq and microarray data were retrieved from TCGA dataset. Most genes showed similar correlation coefficients between RNA-seq and microarray, but 16 genes exhibited significant differences between the two methods. The BAX gene was recurrently found in colorectal cancer, renal cancer, and ovarian cancer, and the PIK3CA gene belonged to renal cancer and breast cancer. Furthermore, the survival prediction model using microarray was better than the RNA-seq model in colorectal cancer, renal cancer, and lung cancer, but the RNA-seq model was better in ovarian and endometrial cancer. Our results showed good correlation between mRNA levels and protein measured by RPPA. While RNA-seq and microarray performance were similar, some genes showed differences, and further clinical significance should be evaluated. Additionally, our survival prediction model results were controversial.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial.

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

Investigating genomic, proteomic, and post-transcriptional regulation profiles in colorectal cancer: a comparative study between primary tumors and associated metastases.

INTRODUCTION: Approximately 50% of patients with primary colorectal carcinoma develop liver metastases. This study investigates the possible molecular discrepancies between primary colorectal cancer (pCRC) and their respective metastases. METHODS: A total of 22 pairs of pCRC and metastases were tested. Mutation profiling of 26 cancer-associated genes was undertaken in 22/22primary-metastasis tumour pairs using next-generation sequencing, whilst the expression of a panel of six microRNAs (miRNAs) was investigated using qPCRin 21/22 pairs and 22 protein biomarkers was tested using Reverse Phase Protein Array (RPPA)in 20/22 patients' tumour pairs. RESULTS: Among the primary and metastatic tumours the mutation rates for the individual genes are as follows:TP53 (86%), APC (44%), KRAS (36%), PIK3CA (9%), SMAD4 (9%), NRAS (9%) and 4% for FBXW7, BRAF, GNAS and CDH1. The primary-metastasis tumour mutation status was identical in 54/60 (90%) loci. However, there was discordance in heterogeneity status in 40/58 genetic loci (z-score = 6.246, difference = 0.3793, P < 0.0001). Furthermore, there was loss of concordance in miRNA expression status between primary and metastatic tumours, and 57.14-80.95% of the primary-metastases tumour pairs showed altered primary-metastasis relative expression in all the miRNAs tested. Moreover, 16 of 20 (80%) tumour pairs showed alteration in at least 3 of 6 (50%) of the protein biomarker pathways analysed. CONCLUSION: The molecular alterations of primary colorectal tumours differ significantly from those of their matched metastases. These differences have profound implications for patients' prognoses and response to therapy.

Large-scale pathway reconstruction and colorimetric screening accelerate cellular metabolism engineering.

The capability to manipulate and analyze hard-wired metabolic pathways sets the pace at which we can engineer cellular metabolism. Here, we present a framework to extensively rewrite the central metabolic pathway for malonyl-CoA biosynthesis in yeast and readily assess malonyl-CoA output based on pathway-scale DNA reconstruction in combination with colorimetric screening (Pracs). We applied Pracs to generate and test millions of enzyme variants by introducing genetic mutations into the whole set of genes encoding the malonyl-CoA biosynthetic pathway and identified hundreds of beneficial enzyme mutants with increased malonyl-CoA output. Furthermore, the synthetic pathways reconstructed by randomly integrating these beneficial enzyme variants generated vast phenotypic diversity, with some displaying higher production of malonyl-CoA as well as other metabolites, such as carotenoids and betaxanthin, thus demonstrating the generic utility of Pracs to efficiently orchestrate central metabolism to optimize the production of different chemicals in various metabolic pathways. Pracs will be broadly useful to advance our ability to understand and engineer cellular metabolism.

Liver X receptors induce antiproliferative effects in basal-like breast cancer.

Liver X receptors (LXRs) are nuclear transcription factors important in the regulation of cholesterol transport, and glucose and fatty acid metabolism. The antiproliferative role of LXRs has been studied in a variety of malignancies and may represent a therapeutic opportunity in cancers lacking targeted therapies, such as triple-negative breast cancer. In this study, we investigated the impact of LXR agonists alone and in combination with carboplatin in preclinical models of breast cancer. In vitro experiments revealed a dose-dependent decrease in tumor cell proliferation in estrogen receptor-positive breast cancer cells, whereas LXR activation in vivo resulted in an increased growth inhibitory effect in a basal-like breast cancer model (in combination with carboplatin). Functional proteomic analysis identified differences in protein expression between responding and nonresponding models related to Akt activity, cell-cycle progression, and DNA repair. Furthermore, pathway analysis suggested that the LXR agonist in combination with carboplatin inhibits the activity of targets of E2F transcription factors and affects cholesterol homeostasis in basal-like breast cancer.

Valosin-containing protein (VCP/p97) is prognostically unfavorable in pediatric AML, and negatively correlates with unfolded protein response proteins IRE1 and GRP78: A report from the Children's Oncology Group.

PURPOSE: The endoplasmic reticulum (ER) is the major site of protein synthesis and folding in the cell. ER-associated degradation (ERAD) and unfolded protein response (UPR) are the main mechanisms of ER-mediated cell stress adaptation. Targeting the cell stress response is a promising therapeutic approach in acute myeloid leukemia (AML). EXPERIMENTAL DESIGN: Protein expression levels of valosin-containing protein (VCP), a chief element of ERAD, were measured in peripheral blood samples from in 483 pediatric AML patients using reverse phase protein array methodology. Patients participated in the Children's Oncology Group AAML1031 phase 3 clinical trial that randomized patients to standard chemotherapy (cytarabine (Ara-C), daunorubicin, and etoposide [ADE]) versus ADE plus bortezomib (ADE+BTZ). RESULTS: Low-VCP expression was significantly associated with favorable 5-year overall survival (OS) rate compared to middle-high-VCP expression (81% versus 63%, p < 0.001), independent of additional bortezomib treatment. Multivariable Cox regression analysis identified VCP as independent predictor of clinical outcome. UPR proteins IRE1 and GRP78 had significant negative correlation with VCP. Five-year OS in patients characterized by low-VCP, moderately high-IRE1 and high-GRP78 improved after treatment with ADE+BTZ versus ADE (66% versus 88%, p = 0.026). CONCLUSION AND CLINICAL RELEVANCE: Our findings suggest the potential of the protein VCP as biomarker in prognostication prediction in pediatric AML.

Reverse Phase Protein Array Profiling Identifies Recurrent Protein Expression Patterns of DNA Damage-Related Proteins across Acute and Chronic Leukemia: Samples from Adults and the Children's Oncology Group.

DNA damage response (DNADR) recognition and repair (DDR) pathways affect carcinogenesis and therapy responsiveness in cancers, including leukemia. We measured protein expression levels of 16 DNADR and DDR proteins using the Reverse Phase Protein Array methodology in acute myeloid (AML) (n = 1310), T-cell acute lymphoblastic leukemia (T-ALL) (n = 361) and chronic lymphocytic leukemia (CLL) (n = 795) cases. Clustering analysis identified five protein expression clusters; three were unique compared to normal CD34+ cells. Individual protein expression differed by disease for 14/16 proteins, with five highest in CLL and nine in T-ALL, and by age in T-ALL and AML (six and eleven proteins, respectively), but not CLL (n = 0). Most (96%) of the CLL cases clustered in one cluster; the other 4% were characterized by higher frequencies of deletion 13q and 17p, and fared poorly (p < 0.001). T-ALL predominated in C1 and AML in C5, but both occurred in all four acute-dominated clusters. Protein clusters showed similar implications for survival and remission duration in pediatric and adult T-ALL and AML populations, with C5 doing best in all. In summary, DNADR and DDR protein expression was abnormal in leukemia and formed recurrent clusters that were shared across the leukemias with shared prognostic implications across diseases, and individual proteins showed age- and disease-related differences.