Capillary Isoelectric Focusing-Mass Spectrometry Method for the Separation and Online Characterization of Intact Monoclonal Antibody Charge Variants

We report a new online capillary isoelectric focusing-mass spectrometry (CIEF-MS) method for monoclonal antibody (mAb) charge variant analysis using an electrokinetically pumped sheath-flow nanospray ion source and a time-of-flight MS with pressure-assisted chemical mobilization. To develop a successful, reliable CIEF-MS method for mAb, we have selected and optimized many critical, interrelating reagents and parameters that include (1) MS-friendly anolyte and catholyte; (2) a glycerol enhanced sample mixture that reduced non-CIEF electrophoretic mobility and band broadening; (3) ampholyte selected for balancing resolution and MS sensitivity; (4) sheath liquid composition optimized for efficient focusing, mobilization, and electrospray ionization; (5) judiciously selected CIEF running parameters including injection amount, field strength, and applied pressure. The fundamental premise of CIEF was well maintained as verified by the linear correlation (<i>R</i>² = 0.99) between p<i>I</i> values and migration time using a mixture of p<i>I</i> markers. In addition, the charge variant profiles of trastuzumab, bevacizumab, infliximab, and cetuximab, obtained using this CIEF-MS method, were corroborated by imaged CIEF-UV (iCIEF-UV) analyses. The relative standard deviations (RSD) of absolute migration time of p<i>I</i> markers were all less than 5% (<i>n</i> = 4). Triplicate analyses of bevacizumab showed RSD less than 1% for relative migration time to an internal standard and RSD of 7% for absolute MS peak area. Moreover, the antibody charge variants were characterized using the online intact MS data. To the best of our knowledge, this is the first time that direct online MS detection and characterization were achieved for mAb charge variants resolved by CIEF as indicated by a well-established linear pH gradient and correlated CIEF-UV charge variant profiles

Image_1_The role of YAP1 in survival prediction, immune modulation, and drug response: A pan-cancer perspective.jpeg

IntroductionDysregulation of the Hippo signaling pathway has been implicated in multiple pathologies, including cancer, and YAP1 is the major effector of the pathway. In this study, we assessed the role of YAP1 in prognostic value, immunomodulation, and drug response from a pan-cancer perspective.MethodsWe compared YAP1 expression between normal and cancerous tissues and among different pathologic stages survival analysis and gene set enrichment analysis were performed. Additionally, we performed correlation analyses of YAP1 expression with RNA modification-related gene expression, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint regulator expression, and infiltration of immune cells. Correlations between YAP1 expression and IC50s (half-maximal inhibitory concentrations) of drugs in the CellMiner database were calculated.ResultsWe found that YAP1 was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications, particularly m6A methylation. High expression of YAP1 was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. YAP1 expression was negatively correlated with the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, and positively correlated with the infiltration of myeloid-derived suppressor cells (MDSCs) and cancer-associated fibroblasts (CAFs) in pan-cancer. Higher YAP1 expression showed upregulation of TGF-β signaling, Hedgehog signaling, and KRAS signaling. IC50s of FDA-approved chemotherapeutic drugs capable of inhibiting DNA synthesis, including teniposide, dacarbazine, and doxorubicin, as well as inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials were negatively correlated with YAP1 expression.DiscussionIn conclusion, YAP1 is aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of YAP1 is associated with poor survival outcomes in certain cancer types. YAP1 may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The tumor-promoting activity of YAP1 is attributed to the activation of TGF-β, Hedgehog, and KRAS signaling pathways. AZD2858 and varlitinib might be effective in cancer patients with high YAP1 expression.</p

Image_4_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Image_5_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Table_1_The role of YAP1 in survival prediction, immune modulation, and drug response: A pan-cancer perspective.xlsx

IntroductionDysregulation of the Hippo signaling pathway has been implicated in multiple pathologies, including cancer, and YAP1 is the major effector of the pathway. In this study, we assessed the role of YAP1 in prognostic value, immunomodulation, and drug response from a pan-cancer perspective.MethodsWe compared YAP1 expression between normal and cancerous tissues and among different pathologic stages survival analysis and gene set enrichment analysis were performed. Additionally, we performed correlation analyses of YAP1 expression with RNA modification-related gene expression, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint regulator expression, and infiltration of immune cells. Correlations between YAP1 expression and IC50s (half-maximal inhibitory concentrations) of drugs in the CellMiner database were calculated.ResultsWe found that YAP1 was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications, particularly m6A methylation. High expression of YAP1 was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. YAP1 expression was negatively correlated with the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, and positively correlated with the infiltration of myeloid-derived suppressor cells (MDSCs) and cancer-associated fibroblasts (CAFs) in pan-cancer. Higher YAP1 expression showed upregulation of TGF-β signaling, Hedgehog signaling, and KRAS signaling. IC50s of FDA-approved chemotherapeutic drugs capable of inhibiting DNA synthesis, including teniposide, dacarbazine, and doxorubicin, as well as inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials were negatively correlated with YAP1 expression.DiscussionIn conclusion, YAP1 is aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of YAP1 is associated with poor survival outcomes in certain cancer types. YAP1 may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The tumor-promoting activity of YAP1 is attributed to the activation of TGF-β, Hedgehog, and KRAS signaling pathways. AZD2858 and varlitinib might be effective in cancer patients with high YAP1 expression.</p

Image_3_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Table_1_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.xlsx

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Image_1_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Image_2_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Dimeric Macrocyclic Antagonists of Inhibitor of Apoptosis Proteins for the Treatment of Cancer

A series of dimeric macrocyclic compounds were prepared and evaluated as antagonists for inhibitor of apoptosis proteins. The most potent analogue <b>11</b>, which binds to XIAP and c-IAP proteins with high affinity and induces caspase-3 activation and ultimately cell apoptosis, inhibits growth of human melanoma and colorectal cell lines at low nanomolar concentrations. Furthermore, compound <b>11</b> demonstrated significant antitumor activity in the A875 human melanoma xenograft model at doses as low as 2 mg/kg on a q3d schedule