Rapid Identification of Biotherapeutics with Label-Free Raman Spectroscopy

Raman spectroscopy and its plasmon-enhanced counterparts: A toolbox to probe protein dynamics and aggregation

Protein unfolding and aggregation are often correlated with numerous diseases such as Alzheimer's, Parkinson's, Huntington's, and other debilitating neurological disorders. Such adverse events consist of a plethora of competing mechanisms, particularly interactions that control the stability and cooperativity of the process. However, it remains challenging to probe the molecular mechanism of protein dynamics such as aggregation, and monitor them in real-time under physiological conditions. Recently, Raman spectroscopy and its plasmon-enhanced counterparts, such as surface-enhanced Raman spectroscopy (SERS) and tip-enhanced Raman spectroscopy (TERS), have emerged as sensitive analytical tools that have the potential to perform molecular studies of functional groups and are showing significant promise in probing events related to protein aggregation. We summarize the fundamental working principles of Raman, SERS, and TERS as nondestructive, easy-to-perform, and fast tools for probing protein dynamics and aggregation. Finally, we highlight the utility of these techniques for the analysis of vibrational spectra of aggregation of proteins from various sources such as tissues, pathogens, food, biopharmaceuticals, and lastly, biological fouling to retrieve precise chemical information, which can be potentially translated to practical applications and point-of-care (PoC) devices. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > Diagnostic Nanodevices Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Identification of monoclonal antibody drug substances using non-destructive Raman spectroscopy

Monoclonal antibodies provide highly specific and effective therapies for the treatment of chronic diseases. These protein-based therapeutics, or drug substances, are transported in single used plastic packaging to fill finish sites. According to good manufacturing practice guidelines, each drug substance needs to be identified before manufacturing of the drug product. However, considering their complex structure, it is challenging to correctly identify therapeutic proteins in an efficient manner. Common analytical techniques for therapeutic protein identification are SDS-gel electrophoresis, enzyme linked immunosorbent assays, high performance liquid chromatography and mass spectrometry-based assays. Although effective in correctly identifying the protein therapeutic, most of these techniques need extensive sample preparation and removal of samples from their containers. This step not only risks contamination but the sample taken for the identification is destroyed and cannot be re-used. Moreover, these techniques are often time consuming, sometimes taking several days to process. Here, we address these challenges by developing a rapid and non-destructive identification technique for monoclonal antibody-based drug substances. Raman spectroscopy in combination with chemometrics were used to identify three monoclonal antibody drug substances. This study explored the impact of laser exposure, time out of refrigerator and multiple freeze thaw cycles on the stability of monoclonal antibodies. and demonstrated the potential of using Raman spectroscopy for the identification of protein-based drug substances in the biopharmaceutical industry.

Direct visualization of general anesthetic propofol on neurons by stimulated Raman scattering microscopy

The consensus for the precise mechanism of action of general anesthetics is through allosteric interactions with GABA receptors in neurons. However, it has been speculated that these anesthetics may also interact with the plasma membrane on some level. Owing to the small size of anesthetics, direct visualization of these interactions is difficult to achieve. We demonstrate the ability to directly visualize a deuterated analog of propofol in living cells using stimulated Raman scattering (SRS) microscopy. Our findings support the theory that propofol is highly concentrated and interacts primarily through non-specific binding to the plasma membrane of neurons. Additionally, we show that SRS microscopy can be used to monitor the dynamics of propofol binding using real-time, live-cell imaging. The strategy used to visualize propofol can be applied to other small molecule drugs that have been previously invisible to traditional imaging techniques

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Multi-modal SRS developed for real-time biological imaging of small molecule substances

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Propofol primarily concentrates at the cell membrane of neurons

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Anesthesia dynamics can be monitored in real-time with SRS

Multi-attribute Raman spectroscopy (MARS) for monitoring product quality attributes in formulated monoclonal antibody therapeutics

Rapid release of biopharmaceutical products enables a more efficient drug manufacturing process. Multi-attribute methods that target several product quality attributes (PQAs) at one time are an essential pillar of the rapid-release strategy. The novel, high-throughput, and nondestructive multi-attribute Raman spectroscopy (MARS) method combines Raman spectroscopy, design of experiments, and multivariate data analysis (MVDA). MARS allows the measurement of multiple PQAs for formulated protein therapeutics without sample preparation from a single spectroscopic scan. Variable importance in projection analysis is used to associate the chemical and spectral basis of targeted PQAs, which assists in model interpretation and selection. This study shows the feasibility of MARS for the measurement of both protein purity-related and formulation-related PQAs; measurements of protein concentration, osmolality, and some formulation additives were achieved by a generic multiproduct model for various protein products containing the same formulation components. MARS demonstrates the potential to be a powerful methodology to improve the efficiency of biopharmaceutical development and manufacturing, as it features fast turnaround time, good robustness, less human intervention, and potential for automation.

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy

Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack of reliable biomarkers for prediction and evaluation of treatment response. Here, we demonstrate the first application of label-free Raman spectroscopy for elucidating biomolecular changes induced by anti-CTLA4 and anti-PD-L1 immune checkpoint inhibitors (ICI) in the tumor microenvironment (TME) of colorectal tumor xenografts. Multivariate curve resolution-alternating least squares (MCR-ALS) decomposition of Raman spectral datasets revealed early changes in lipid, nucleic acid, and collagen content following therapy. Support vector machine classifiers and random forests analysis provided excellent prediction accuracies for response to both ICIs and delineated spectral markers specific to each therapy, consistent with their differential mechanisms of action. Corroborated by proteomics analysis, our observation of biomolecular changes in the TME should catalyze detailed investigations for translating such markers and label-free Raman spectroscopy for clinical monitoring of immunotherapy response in cancer patients. SIGNIFICANCE: This study provides first-in-class evidence that optical spectroscopy allows sensitive detection of early changes in the biomolecular composition of tumors that predict response to immunotherapy with immune checkpoint inhibitors.

Label-free Raman spectroscopy: A potential tool for early diagnosis of diabetic keratopathy

Diabetes has become a major public health problem worldwide, and the incidence of diabetes has been increasing progressively. Diabetes is prone to cause various complications, among which diabetic keratopathy (DK) emphasizes the significant impact on the cornea. The current diagnosis of DK lacks biochemical markers that can be used for early and non-invasive screening and detection. In contrast, in this study, Raman spectroscopy, which demonstrates non-destructive, label-free features, especially the unique advantage of providing molecular fingerprint information for target substances, were utilized to interrogate the intrinsic information of the corneal tissues from normal and diabetic mouse models, respectively. Visually, the Raman spectral response derived from the biochemical components and biochemical differences between the two groups were compared. Moreover, multivariate analysis methods such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were carried out for advanced statistical analysis. PCA yields a diagnostic results of 57.4% sensitivity, 89.2% specificity, 74.8% accuracy between the diabetic group and control group; Moreover, PLS-DA was employed to enhance the diagnostic ability, showing 76.1% sensitivity, 86.1% specificity, and 87.6% accuracy between the diabetic group and control group. Our proof-of-concept results show the potential of Raman spectroscopy-based techniques to help explore the underlying pathogenesis of DK disease and thus be further expanded for potential applications in the early screening of diabetic diseases.

A simple, rapid, and robust "on-the-go" identity testing of biotherapeutics using FTIR spectroscopy

The stunning rise of biotherapeutics as successful treatments of complex and hard-to-treat diseases, in particular cancer, has necessitated the development of a rapid analytical method capable of differentiating these otherwise significantly similar antibody-based products. The existing methods for product identification pose significant drawbacks in terms of the consumption of time and labor. Here, we present an FTIR spectroscopy-based simple, rapid, and robust method that is capable of differentiating between the biotherapeutics (both innovator products and biosimilars). The proposed approach uses partial least-squares-discriminant analysis to pinpoint subtle differences in the FTIR spectra of the samples, enabling us to not only identify the product but also calculate its concentration. This FTIR-based method can be used to fulfill the identity testing requirement of a pharmaceutical drug in its final packaged form set by the US Food and Drug Administration. Along with this, identity testing can also be deployed at multiple steps in the manufacturing process and can also be used by the appropriate regulatory or government agency for tackling counterfeits of biotherapeutic products.

Understanding the discrimination and quantification of monoclonal antibodies preparations using Raman spectroscopy

The use of Raman spectroscopy for analytical quality control of anticancer drug preparations in clinical pharmaceutical dispensing units is increasing in popularity, notably supported by commercially available, purpose designed instruments. Although not legislatively compulsory, analytical methods are frequently used post-preparation to verify the accuracy of a preparation in terms of identity and quantity of the drug in solution. However, while the rapid, cost effective and label free analysis achieved with Raman spectroscopy is appealing, it is important to understand the molecular origin of the spectral contributions collected from the solution of actives and excipients, to evaluate the strength and limitation for the technique, which can be used to identify and quantify either the prescribed commercial formulation, and/or the active drug itself, in personalised solutions. In the current study, four commercial formulations, Erbitux®, Truxima®, Ontruzant® and Avastin® of monoclonal antibodies (mAbs), corresponding respectively to cetuximab, rituximab, trastuzumab and bevacizumab have been used to highlight the key role of excipients in discrimination and quantification of the formulations. It is demonstrated that protein based anticancer drugs such as mAbs have a relatively weak Raman response, while excipients such as glycine, trehalose or histidine contribute significantly to the spectra. Multivariate analysis (partial least square regression and partial least square discriminant analysis) further demonstrates that the signatures of the mAbs themselves are not prominent in mathematical models and that those of the excipients are solely responsible for the differentiation of formulation and accurate determination of concentrations. While Raman spectroscopy can successfully validate the conformity of mAbs intravenous infusion solutions, the basis for the analysis should be considered, and special caution should be given to excipient compositions in commercial formulations to ensure reliability and reproducibility of the analysis.

High-Throughput Raman Spectroscopy Combined with Innovate Data Analysis Workflow to Enhance Biopharmaceutical Process Development

Raman spectroscopy has the potential to revolutionise many aspects of biopharmaceutical process development. The widespread adoption of this promising technology has been hindered by the high cost associated with individual probes and the challenge of measuring low sample volumes. To address these issues, this paper investigates the potential of an emerging new high-throughput (HT) Raman spectroscopy microscope combined with a novel data analysis workflow to replace off-line analytics for upstream and downstream operations. On the upstream front, the case study involved the at-line monitoring of an HT micro-bioreactor system cultivating two mammalian cell cultures expressing two different therapeutic proteins. The spectra generated were analysed using a partial least squares (PLS) model. This enabled the successful prediction of the glucose, lactate, antibody, and viable cell density concentrations directly from the Raman spectra without reliance on multiple off-line analytical devices and using only a single low-volume sample (50–300 μL). However, upon the subsequent investigation of these models, only the glucose and lactate models appeared to be robust based upon their model coefficients containing the expected Raman vibrational signatures. On the downstream front, the HT Raman device was incorporated into the development of a cation exchange chromatography step for an Fc-fusion protein to compare different elution conditions. PLS models were derived from the spectra and were found to predict accurately monomer purity and concentration. The low molecular weight (LMW) and high molecular weight (HMW) species concentrations were found to be too low to be predicted accurately by the Raman device. However, the method enabled the classification of samples based on protein concentration and monomer purity, allowing a prioritisation and reduction in samples analysed using A280 UV absorbance and high-performance liquid chromatography (HPLC). The flexibility and highly configurable nature of this HT Raman spectroscopy microscope makes it an ideal tool for bioprocess research and development, and is a cost-effective solution based on its ability to support a large range of unit operations in both upstream and downstream process operations.

Rapid, Label-free Optical Spectroscopy Platform for Diagnosis of Heparin-Induced Thrombocytopenia

The use of surface-enhanced Raman spectroscopy (SERS) to determine spectral markers for the diagnosis of heparin-induced thrombocytopenia (HIT), a difficult-to-diagnose immune-related complication that often leads to limb ischemia and thromboembolism, is proposed. The ability to produce distinct molecular signatures without the addition of labels enables unbiased inquiry and makes SERS an attractive complementary diagnostic tool. A capillary-tube-derived SERS platform offers ultrasensitive, label-free measurement as well as efficient handling of blood serum samples. This shows excellent reproducibility, long-term stability and provides an alternative diagnostic rubric for the determination of HIT by leveraging machine-learning-based classification of the spectroscopic data. We envision that a portable Raman instrument could be combined with the capillary-tube-based SERS analytical tool for diagnosis of HIT in the clinical laboratory, without perturbing the existing diagnostic workflow.

Shedding Light on the Trehalose-Enabled Mucopermeation of Nanoparticles with Label-Free Raman Spectroscopy

Nanoparticle-based drug delivery systems have attracted significant interest owing to their promise as tunable platforms that offer improved intracellular release of cargo therapeutics. However, significant challenges remain in maintaining the physiological stability of the mucosal matrix due to the nanoparticle-induced reduction in the matrix diffusivity and promotion of mucin aggregation. Such aggregation also adversely impacts the permeability of the nanoparticles, and thus, diminishes the efficacy of nanoparticle-based formulations. Here, an entirely complementary approach is proposed to the existing nanoparticle functionalization methods to address these challenges by using trehalose, a naturally occurring disaccharide that offers exceptional protein stabilization. Plasmon-enhanced Raman spectroscopy and far-red fluorescence emission of the plasmonic silver nanoparticulate clusters are harnessed to create a unique dual-functional, aggregating, and imaging agent that obviates the need of an additional reporter to investigate mucus-nanoparticle interactions. These spectroscopy-based density mapping tools uncover the mechanism of mucus-nanoparticle interactions and establish the protective role of trehalose microenvironment in minimizing the nanoparticle aggregation. Thus, in contrast to the prevailing belief, these results demonstrate that nonfunctionalized nanoparticles may rapidly penetrate through mucus barriers, and by leveraging the bioprotectant attributes of trehalose, an in vivo milieu for efficient mucosal drug delivery can be generated.

Rapid, quantitative determination of aggregation and particle formation for antibody drug conjugate therapeutics with label-free Raman spectroscopy

Lot release and stability testing of biologics are essential parts of the quality control strategy for ensuring therapeutic material dosed to patients is safe and efficacious, and consistent with previous clinical and toxicological experience. Characterization of protein aggregation is of particular significance, as aggregates may lose the intrinsic pharmaceutical properties as well as engage with the immune system instigating undesirable downstream immunogenicity. While important, real-time identification and quantification of subvisible particles in the monoclonal antibody (mAb) drug products remains inaccessible with existing techniques due to limitations in measurement time, sensitivity or experimental conditions. Here, owing to its exquisite molecular specificity, non-perturbative nature and lack of sample preparation requirements, we propose label-free Raman spectroscopy in conjunction with multivariate analysis as a solution to this unmet need. By leveraging subtle, but consistent, differences in vibrational modes of the biologics, we have developed a support vector machine-based regression model that provides fast, accurate prediction for a wide range of protein aggregations. Moreover, in blinded experiments, the model shows the ability to precisely differentiate between aggregation levels in mAb like product samples pre- and post-isothermal incubation, where an increase in aggregate levels was experimentally determined. In addition to offering fresh insights into mAb like product-specific aggregation mechanisms that can improve engineering of new protein therapeutics, our results highlight the potential of Raman spectroscopy as an in-line analytical tool for monitoring protein particle formation.

Ultrasensitive Detection of Hepatotoxic Microcystin Production from Cyanobacteria Using Surface-Enhanced Raman Scattering Immunosensor

Microcystin-LR (MC-LR) is considered the most common hazardous toxin produced during harmful algal blooms. In addition to potential risk of long-term exposure to low concentrations in drinking water, acute toxicity due to MC-LR resulting from algal blooms could result in fatalities in rare cases. Although several methods are currently available to detect MC-LR, development of a low-cost, ultrasensitive measurement method would help limit exposure by enabling early detection and continuous monitoring of MC-LR. Here, we develop a surface-enhanced Raman scattering (SERS) spectroscopic immunosensor for detection and quantification of the hepatotoxic MC-LR toxin in aquatic settings with excellent robustness, selectivity, and sensitivity. We demonstrate that the developed SERS sensor can reach a limit of detection (0.014 μg/L) at least 1 order of magnitude lower and display a linear dynamic detection range (0.01 μg/L to 100 μg/L) 2 orders of magnitude wider in comparison to the commercial enzyme-linked immunosorbent assay test. The superior analytical performance of this SERS immunosensor enables monitoring of the dynamic production of MC-LR from a Microcystis aeruginosa culture. We believe that the present method could serve as a useful tool for detection of hepatotoxic microcystin toxins in various aquatic settings such as drinking water, lakes, and reservoirs. Further development of this technique could result in single-cell microcystin resolution or real-time monitoring to mitigate the associated toxicity and economic loss.

Label-Free Raman Spectroscopy Reveals Signatures of Radiation Resistance in the Tumor Microenvironment

Delay in the assessment of tumor response to radiotherapy continues to pose a major challenge to quality of life for patients with nonresponsive tumors. Here, we exploited label-free Raman spectroscopic mapping to elucidate radiation-induced biomolecular changes in tumors and uncovered latent microenvironmental differences between treatment-resistant and -sensitive tumors. We used isogenic radiation-resistant and -sensitive A549 human lung cancer cells and human head and neck squamous cell carcinoma (HNSCC) cell lines (UM-SCC-47 and UM-SCC-22B, respectively) to grow tumor xenografts in athymic nude mice and demonstrated the molecular specificity and quantitative nature of Raman spectroscopic tissue assessments. Raman spectra obtained from untreated and treated tumors were subjected to chemometric analysis using multivariate curve resolution-alternating least squares (MCR-ALS) and support vector machine (SVM) to quantify biomolecular differences in the tumor microenvironment. The Raman measurements revealed significant and reliable differences in lipid and collagen content postradiation in the tumor microenvironment, with consistently greater changes observed in the radiation-sensitive tumors. In addition to accurately evaluating tumor response to therapy, the combination of Raman spectral markers potentially offers a route to predicting response in untreated tumors prior to commencing treatment. Combined with its noninvasive nature, our findings provide a rationale for in vivo studies using Raman spectroscopy, with the ultimate goal of clinical translation for patient stratification and guiding adaptation of radiotherapy during the course of treatment. SIGNIFICANCE: These findings highlight the sensitivity of label-free Raman spectroscopy to changes induced by radiotherapy and indicate the potential to predict radiation resistance prior to commencing therapy.

Raman spectroscopy for the diagnosis of unlabeled and unstained histopathological tissue specimens

AIM

To investigate the possibility of diagnosing gastric cancer from an unstained pathological tissue using Raman spectroscopy, and to compare the findings to those obtained with conventional histopathology.

METHODS

We produced two consecutive tissue specimens from areas with and without cancer lesions in the surgically resected stomach of a patient with gastric cancer. One of the two tissue specimens was stained with hematoxylin and eosin and used as a reference for laser irradiation positioning by the spectroscopic method. The other specimen was left unstained and used for Raman spectroscopy analysis.

RESULTS

A significant Raman scattering spectrum could be obtained at all measurement points. Raman scattering spectrum intensities of 725 cm^-1 and 782 cm^-1, are associated with the nucleotides adenine and cytosine, respectively. The Raman scattering spectrum intensity ratios of 782 cm^-1/620 cm^-1, 782 cm^-1/756 cm^-1, 782 cm^-1/1250 cm^-1, and 782 ​​cm^-1/1263 cm^-1 in the gastric adenocarcinoma tissue were significantly higher than those in the normal stomach tissue.

CONCLUSION

The results of this preliminary experiment suggest the feasibility of our spectroscopic method as a diagnostic tool for gastric cancer using unstained pathological specimens.

Surface-enhanced Raman scattering for the detection of polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a multi-factorial heterogeneous syndrome that affects many women of reproductive age. This work demonstrates how the surface-enhanced Raman scattering (SERS) technique can be used to differentiate between PCOS and non-PCOS patients. We determine that the use of SERS, in conjunction with partial least squares (PLS) and principal component analysis (PCA), allows us to detect PCOS in patient samples. Although the role of chemerin in the pathogenesis of PCOS patients is not clear, this work enables us to measure their chemerin levels using the PLS regression method.

Label-free Raman spectroscopy provides early determination and precise localization of breast cancer-colonized bone alterations

Raman spectral markers offer new routes to recognition of biomolecular alterations at sites of nascent and progressing metastatic cancer in bone.

Breast neoplasms frequently colonize bone and induce development of osteolytic bone lesions by disrupting the homeostasis of the bone microenvironment. This degenerative process can lead to bone pain and pathological bone fracture, a major cause of cancer morbidity and diminished quality of life, which is exacerbated by our limited ability to monitor early metastatic disease in bone and assess fracture risk. Spurred by its label-free, real-time nature and its exquisite molecular specificity, we employed spontaneous Raman spectroscopy to assess and quantify early metastasis driven biochemical alterations to bone composition. As early as two weeks after intracardiac inoculations of MDA-MB-435 breast cancer cells in NOD-SCID mice, Raman spectroscopic measurements in the femur and spine revealed consistent changes in carbonate substitution, overall mineralization as well as crystallinity increase in tumor-bearing bones when compared with their normal counterparts. Our observations reveal the possibility of early stage detection of biochemical changes in the tumor-bearing bones – significantly before morphological variations are captured through radiographic diagnosis. This study paves the way for a better molecular understanding of altered bone remodeling in such metastatic niches, and for further clinical studies with the goal of establishing a non-invasive tool for early metastasis detection and prediction of pathological fracture risk in breast cancer.

Exploring Morphological and Biochemical Linkages in Fungal Growth with Label-Free Light Sheet Microscopy and Raman Spectroscopy

Imaging tip growth in fungal hyphae is highly warranted to unravel the molecular mechanism of this extraordinarily precise and localized phenomenon. In situ probing of fungal cultures, however, have been challenging due to their inherent complexity and light penetration issues associated with conventional optical imaging. In this work, we report a label-free approach using a combination of light sheet microscopy and Raman spectroscopy to obtain concomitant morphological and biochemical information from the growing specimen. We show that the variance in morphology in the symbiotic fungus Piriformospora indica are rooted in the underlying differences in chemical composition in the specific growth zones. Our findings suggest that this potent two-pronged approach can comprehensively characterize growth areas and elucidate microbe interactions in still developing colonies with high sensitivity and multiplexing capability.

Label-Free Raman Spectroscopy Detects Stromal Adaptations in Premetastatic Lungs Primed by Breast Cancer

Recent advances in animal modeling, imaging technology, and functional genomics have permitted precise molecular observations of the metastatic process. However, a comprehensive understanding of the premetastatic niche remains elusive, owing to the limited tools that can map subtle differences in molecular mediators in organ-specific microenvironments. Here, we report the ability to detect premetastatic changes in the lung microenvironment, in response to primary breast tumors, using a combination of metastatic mouse models, Raman spectroscopy, and multivariate analysis of consistent patterns in molecular expression. We used tdTomato fluorescent protein expressing MDA-MB-231 and MCF-7 cells of high and low metastatic potential, respectively, to grow orthotopic xenografts in athymic nude mice and allow spontaneous dissemination from the primary mammary fat pad tumor. Label-free Raman spectroscopic mapping was used to record the molecular content of premetastatic lungs. These measurements show reliable distinctions in vibrational features, characteristic of the collageneous stroma and its cross-linkers as well as proteoglycans, which uniquely identify the metastatic potential of the primary tumor by recapitulating the compositional changes in the lungs. Consistent with histological assessment and gene expression analysis, our study suggests that remodeling of the extracellular matrix components may present promising markers for objective recognition of the premetastatic niche, independent of conventional clinical information. Cancer Res; 77(2); 247-56. ©2016 AACR.