Self-Functionalized Superlattice Nanosensor Enables Glioblastoma Diagnosis Using Liquid Biopsy.

Glioblastoma (GBM), the most aggressive and lethal brain cancer, is detected only in the advanced stage, resulting in a median survival rate of 15 months. Therefore, there is an urgent need to establish GBM diagnosis tools to identify the tumor accurately. The clinical relevance of the current liquid biopsy techniques for GBM diagnosis remains mostly undetermined, owing to the challenges posed by the blood-brain barrier (BBB) that restricts biomarkers entering the circulation, resulting in the unavailability of clinically validated circulating GBM markers. GBM-specific liquid biopsy for diagnosis and prognosis of GBM has not yet been developed. Here, we introduce extracellular vesicles of GBM cancer stem cells (GBM CSC-EVs) as a previously unattempted, stand-alone GBM diagnosis modality. As GBM CSCs are fundamental building blocks of tumor initiation and recurrence, it is desirable to investigate these reliable signals of malignancy in circulation for accurate GBM diagnosis. So far, there are no clinically validated circulating biomarkers available for GBM. Therefore, a marker-free approach was essential since conventional liquid biopsy relying on isolation methodology was not viable. Additionally, a mechanism capable of trace-level detection was crucial to detecting the rare GBM CSC-EVs from the complex environment in circulation. To break these barriers, we applied an ultrasensitive superlattice sensor, self-functionalized for surface-enhanced Raman scattering (SERS), to obtain holistic molecular profiling of GBM CSC-EVs with a marker-free approach. The superlattice sensor exhibited substantial SERS enhancement and ultralow limit of detection (LOD of attomolar 10-18 M concentration) essential for trace-level detection of invisible GBM CSC-EVs directly from patient serum (without isolation). We detected as low as 5 EVs in 5 µL of solution, achieving the lowest LOD compared to existing SERS-based studies. We have experimentally demonstrated the crucial role of the signals of GBM CSC-EVs in the precise detection of glioblastoma. This was evident from the unique molecular profiles of GBM CSC-EVs demonstrating significant variation compared to noncancer EVs and EVs of GBM cancer cells, thus adding more clarity to the current understanding of GBM CSC-EVs. Preliminary validation of our approach was undertaken with a small amount of peripheral blood (5 µL) derived from GBM patients with 100% sensitivity and 97% specificity. Identification of the signals of GBM CSC-EV in clinical sera specimens demonstrated that our technology could be used for accurate GBM detection. Our technology has the potential to improve GBM liquid biopsy, including real-time surveillance of GBM evolution in patients upon clinical validation. This demonstration of liquid biopsy with GBM CSC-EV provides an opportunity to introduce a paradigm potentially impacting the current landscape of GBM diagnosis.

DNA Methylation Signatures of Tumor-Associated Natural Killer Cells with Self-Functionalized Nanosensor Enable Colorectal Cancer Diagnosis.

Natural killer (NK) cells undergo multiple DNA genomic alterations, especially methylation-based modifications that affect activation and function. Several epigenetic modifier markers have been targeted for immunotherapy to date, but the possibility of cancer diagnosis using NK cell's DNA has been overlooked. Here, we investigated the potential use of NK cell DNA genome modifications as markers for the diagnosis of colorectal cancer (CRC) and validated their efficacy in CRC patients. Using Raman spectroscopy as the detection methodology, we identified CRC-specific methylation signatures by comparing CRC-interacted NK cells to healthy circulating NK cells. Subsequently, we identified methylation-dependent alterations in these NK cell populations. These markers were then utilized by a machine learning algorithm to develop a diagnostic model with predictive capabilities. The diagnostic prediction model accurately differentiated CRC patients from normal controls. Our findings demonstrated the utility of NK DNA markers in the diagnosis of CRC.

Dual-Purpose 3D-Silica Nanostructure Matrix for Rapid Epigenetic Reprogramming of Tumor Cell to Cancer Stem Cell Spheroid.

Cancer stem cells (CSCs), a rare subpopulation responsible for tumorigenesis and therapeutic resistance, are difficult to characterize and isolate. Conventional method of growing CSCs takes up to 2-8 weeks inhibiting the rate of research. Therefore, rapid reprogramming (RR) of tumor cells into CSCs is crucial to accelerate the stem cell oncology research. The current RR techniques cannot be utilized for CSC RR due to many limitations posed due to isolation requirements resulting in loss of vital data. Hence, a technique that can induce CSC RR without the need for isolation procedures is needed. Here, fabrication of a 3D-silica nanostructured extracellular matrix for RR and in situ monitoring is reported. The RR is tested using three preclinical cancer models. The 3D matrix and a zeta potential study confirm an intense material-cellular interaction resulting in the enhanced expressions of surface and epigenetic biomarkers. Cancer cells require only 3-day period to form CSC spheroids with 3D-silica extracellular matrix. Real-time single-cell monitoring of the methylene blue-induced photodynamic demonstrates the dual functionality. To the authors' knowledge, this is the first study to demonstrate a CSC epigenetic reprogramming using nanostructures. These findings may pave the path for accelerating the stem cell research in oncology.

DEEP Surveillance of Brain Cancer Using Self-Functionalized 3D Nanoprobes for Noninvasive Liquid Biopsy.

Brain cancers, one of the most fatal malignancies, require accurate diagnosis for guided therapeutic intervention. However, conventional methods for brain cancer prognosis (imaging and tissue biopsy) face challenges due to the complex nature and inaccessible anatomy of the brain. Therefore, deep analysis of brain cancer is necessary to (i) detect the presence of a malignant tumor, (ii) identify primary or secondary origin, and (iii) find where the tumor is housed. In order to provide a diagnostic technique with such exhaustive information here, we attempted a liquid biopsy-based deep surveillance of brain cancer using a very minimal amount of blood serum (5 µL) in real time. We hypothesize that holistic analysis of serum can act as a reliable source for deep brain cancer surveillance. To identify minute amounts of tumor-derived material in circulation, we synthesized an ultrasensitive 3D nanosensor, adopted SERS as a diagnostic methodology, and undertook a DEEP neural network-based brain cancer surveillance. Detection of primary and secondary tumor achieved 100% accuracy. Prediction of intracranial tumor location achieved 96% accuracy. This modality of using patient sera for deep surveillance is a promising noninvasive liquid biopsy tool with the potential to complement current brain cancer diagnostic methodologies.

Minimally invasive detection of cancer using metabolic changes in tumor-associated natural killer cells with Oncoimmune probes.

Natural Killer (NK) cells, a subset of innate immune cells, undergo cancer-specific changes during tumor progression. Therefore, tracking NK cell activity in circulation has potential for cancer diagnosis. Identification of tumor associated NK cells remains a challenge as most of the cancer antigens are unknown. Here, we introduce tumor-associated circulating NK cell profiling (CNKP) as a stand-alone cancer diagnostic modality with a liquid biopsy. Metabolic profiles of NK cell activation as a result of tumor interaction are detected with a SERS functionalized OncoImmune probe platform. We show that the cancer stem cell-associated NK cell is of value in cancer diagnosis. Through machine learning, the features of NK cell activity in patient blood could identify cancer from non-cancer using 5uL of peripheral blood with 100% accuracy and localization of cancer with 93% accuracy. These results show the feasibility of minimally invasive cancer diagnostics using circulating NK cells.

Cancer Stem Cell Derived Extracellular Vesicles with Self-Functionalized 3D Nanosensor for Real-Time Cancer Diagnosis: Eliminating the Roadblocks in Liquid Biopsy.

Liquid biopsy for determining the presence of cancer and the underlying tissue of origin is crucial to overcome the limitations of existing tissue biopsy and imaging-based techniques by capturing critical information from the dynamic tumor heterogeneity. A newly emerging liquid biopsy with extracellular vesicles (EVs) is gaining momentum, but its clinical relevance is in question due to the biological and technical challenges posed by existing technologies. The biological barriers of existing technologies include the inability to generate fundamental details of molecular structure, chemical composition as well as functional variations in EVs by gathering simultaneous information on multiple intra-EV molecules, unavailability of holistic qualitative analysis, in addition to the inability to identify tissue of origin. Technological barriers include reliance on EV isolation with a few labeled biomarkers, resulting in the inability to generate comprehensive information on the disease. A more favorable approach would be to generate holistic information on the disease without the use of labels. Such a marker-free diagnosis is impossible with the existing liquid biopsy due to the unavailability clinically validated cancer stem cells (CSC)-specific markers and dependence of existing technologies on EV isolation, undermining the clinical relevance of EV-based liquid biopsy. Here, CSC EVs were employed as an independent liquid biopsy modality. We hypothesize that tracking the signals of CSCs in peripheral blood with CSC EVs will provide a reliable solution for accurate cancer diagnosis, as CSC are the originators of tumor contributing to tumor heterogeneity. We report nanoengineered 3D sensors of extremely small nano-scaled probes self-functionalized for SERS, enabling integrative molecular and functional profiling of otherwise undetectable CSC EVs. A substantially enhanced SERS and ultralow limit of detection (10 EVs per 10 µL) were achieved. This was attributed to the efficient probe-EV interaction due to the 3D networks of nanoprobes, ensuring simultaneous detection of multiple EV signals. We experimentally demonstrate the crucial role of CSC EVs in cancer diagnosis. We then completed a pilot validation of this modality for cancer detection as well as for identification of the tissue of origin. An artificial neural network distinguished cancer from noncancer with 100% sensitivity and 100% specificity for three hard to detect cancers (breast, lung, and colorectal cancer). Binary classification to distinguish one tissue of origin against all other achieved 100% accuracy, while simultaneous identification of all three tissues of origin with multiclass classification achieved up to 79% accuracy. This noninvasive tool may complement existing cancer diagnostics, treatment monitoring as well as longitudinal disease monitoring by validation with a large cohort of clinical samples.

Glioblastoma Associated Natural Killer Cell EVs Generating Tumour-Specific Signatures: Noninvasive GBM Liquid Biopsy with Self-Functionalized Quantum Probes.

Diagnosis of glioblastoma (GBM) poses a recurring struggle due to many factors, including the presence of the blood-brain barrier (BBB) in addition to the significant tumor heterogeneity. Natural killer (NK) cells of the innate immune system are the primary immune surveillance mechanism for GBM and identify GBM tumors without any previous sensitization. The metabolic reprogramming of NK cells during GBM association is expected to be reflected in its extracellular vesicles. Therefore, tracking the activity of NK cell vesicles in circulation (circulating immune vesicles, CIVs) has great potential for accurate GBM diagnosis. However, identification GBM associated CIVs in circulation is immensely challenging as there is no availability of clinically validated GBM-specific circulating biomarkers. Here, we present GBM associated CIV profiling for noninvasive GBM diagnosis. We investigated the feasibility of using the signals derived from GBM associated CIVs as a de novo methodology for GBM diagnosis. An ultrasensitive sensor and a marker-free approach were essential for the detection of rare signals of GBM associated CIVs. For this purpose, we designed GBM ImmunoProfiler platform using scalable ultrafast laser multiphoton ionization mechanism and adopted surface enhanced Raman spectroscopy (SERS) ensuring simultaneous detection of multiple CIV signals to identify GBM. We experimentally demonstrated that GBM associated CIVs carry unique, tumor-specific signals. The features of GBM associated CIVs were explored through machine learning identifying its similarity with GBM patient blood (without cell isolation) using a very small amount of peripheral blood (5 µL) with 96.82% sensitivity and 100% specificity. In addition, we demonstrated that a tumor associated CIV profile can classify between multiple brain cancer types (astrocytoma, oligodendroglioma, and glioblastoma). We also experimentally demonstrated significant variation in the immune checkpoint protein expression (PDL-1 and CTLA-4) between GBM associated CIVs and uninteracted CIVs. Preclinical analysis with serum specimens of GBM patients showed the possibility of using our technology for minimally invasive GBM diagnosis. With clinical validation, our technology has potential to improve GBM diagnostics with a useful, minimally invasive GBM liquid biopsy.

Holistic Analysis of Glioblastoma Stem Cell DNA Using Nanoengineered Plasmonic Metasensor for Glioblastoma Diagnosis.

The clinical relevance of liquid biopsy for glioblastoma (GBM) remains undetermined due to practical and biological limitations such as absence of a reliable GBM-specific biomarker, trace levels in circulation due to the blood-brain-barrier, and lack of a sensitive method to detect the trace levels of biomarkers. It is hypothesized that GBM stem cell (GSC)-associated cell free DNA can function as reliable biomarker for GBM because it accounts for tumor heterogeneity and provide accurate molecular information about the cancer. An integrative methodology is used for GBM diagnosis by utilizing the sub-single molecular sensitivity of nanoengineered plasmonic metasensors for real-time genomic profiling of GSC DNA. The nanoengineered metasensors can detect the rare circulating GSC-DNA accurately from just 5 µL of blood and the test can be performed in under 10 min. Analysis of clinical serum samples from GBM patients and healthy volunteers demonstrates that the technology yielded an accurate classification of GBM in an independent validation cohort (accuracy 98.3%, specificity 100%). The methodology detects GBM-signatures from the patient blood rapidly within the half-life period of cfDNA in circulation, non-invasively and amplification-free with a high diagnostic accuracy. With clinical validation, this methodology can evolve as a clinically viable diagnostic tool for fatal and hard-to-detect cancer like GBM.

Cancer Stem Cell DNA Enabled Real-Time Genotyping with Self-Functionalized Quantum Superstructures-Overcoming the Barriers of Noninvasive cfDNA Cancer Diagnostics.

Cancer diagnosis and determining its tissue of origin are crucial for clinical implementation of personalized medicine. Conventional diagnostic techniques such as imaging and tissue biopsy are unable to capture the dynamic tumor landscape. Although circulating tumor DNA (ctDNA) shows promise for diagnosis, the clinical relevance of ctDNA remains largely undetermined due to several biological and technical complexities. Here, cancer stem cell-ctDNA is used to overcome the biological complexities like the inability for molecular analysis of ctDNA and dependence on ctDNA concentration rather than the molecular profile. Ultrasensitive quantum superstructures overcome the technical complexities of trace-level detection and rapid diagnosis to detect ctDNA within its short half-life. Activation of multiple surface enhanced Raman scattering mechanisms of the quantum superstructures achieved a very high enhancement factor (1.35 × 1011 ) and detection at ultralow concentration (10-15 M) with very high reliability (RSD: 3-12%). Pilot validation with clinical plasma samples from an independent validation cohort achieved a diagnosis sensitivity of ≈95% and specificity of 83%. Quantum superstructures identified the tissue of origin with ≈75-86% sensitivity and ≈92-96% specificity. With large scale clinical validation, the technology can develop into a clinically useful liquid biopsy tool improving cancer diagnostics.

Tracking the Evolution of Metastasis with Self-Functionalized 3D Nanoprobes.

Despite recent advances in cancer treatment, metastasis is the cause of mortality in 90% of cancer cases. It has now been well-established that dissemination of cancer cells to distant sites occurs very early during tumorigenesis, resulting in the minimal effect of surgical or chemotherapeutic treatments after the detection of metastasis. The underlying reason for this challenge is mostly due to the limited understanding of molecular mechanisms of the metastasis cascade, particularly related to metastatic traits. Therefore, there is an urgent need to investigate this currently invisible evolution of metastasis. The tracking of metastasis evolution has not been addressed yet. Here, we introduce, for the first time, a synchronous approach to unveil the molecular mechanisms of the metastasis cascade. As cancer stem cells (CSCs) demonstrate cancer initiation, drug resistance, metastasis, and tumor relapse and can exist in a quasi-intermediate epithelial-mesenchymal transition state, the tumor-initiating events during a CSCs metamorphosis were monitored with single-cell sensitivity. Because of the invasive and resistive properties of the metastable intermediate CSCs, investigation of the molecular profiles of the quasi-intermediate CSCs was necessary for the detection of metastasis dissemination. For this purpose, the ultrasensitive technique of surface-enhanced Raman scattering (SERS) was adopted. Titanium-based, biocompatible three-dimensional (3D) nanoprobes that were synthesized for multiphoton ionization achieved a substantial SERS enhancement of ∼80-fold due to the oxygen vacancy-enriched composition of the nanoprobes. The 3D interconnected complex nanoarchitecture of the nanoprobes enabled us to entrap the nonadherent CSCs of three metastatic cancer cell lines (triple negative breast adenocarcinoma (MDAMB231), human Caucasian colon adenocarcinoma (COLO 205), and cervical adenocarcinoma (HeLa)─all very aggressive forms of cancer). The nanoprobes not only promoted the CSC proliferation to successfully attain the quasi-intermediate states but also monitored its reprogramming into a cancer cell state. The nanoprobes substantially amplified weak intracellular Raman signals to capture the molecular events during a CSC transformation. The detection of cancer was achieved with 100% accuracy. We experimentally demonstrated that the molecular signatures of CSC reprogramming are cancer-type specific. This observation enabled us to identify the origin of metastasis with 100% accuracy, providing more clarity on the relatively unknown quasi-intermediate states. This first demonstration of CSC-based tracking of metastasis evolution has the potential to provide an insightful perspective of tumorigenesis that could be useful in cancer diagnosis and prognosis as well as in the monitoring of therapeutic interventions.

Boosting the sub-cellular biomolecular cancer signals by self-functionalized tag-free nano sensor.

Surface Enhanced Raman Scattering (SERS)-based sub-cellular cancer diagnosis can simultaneously obtain multiple biomolecular signals crucial in diagnostic platform for a heterogeneous disease like cancer. But, SERS-probes being typically tagged with chemical functionalization demonstrate limitations due to adverse biocompatibility, ineffective cellular internalization, SERS-signal quenching and spectral contamination. Although, tag-free SERS-probes overcome these limitations; complexity in spectral interpretation and detection insensitivity make it disadvantageous. In this study, we have exploited the inherent charges of cellular biomolecules and introduced self-functionalized complementary charged, tag-free SERS nano probes for biomolecule-specific investigation. Extremely small nano probes (sub 10 nm), synthesized with multiphoton ionization were functionalized with charge by physical synthesis without any ligands or chemical processes. The probes demonstrated significant SERS (EF~106) with analyte molecules (4ATP & 4MBA). Multifold signal boost was achieved for the signals of cellular components - amplification of ~7 fold for DNA, ~16 fold for proteins and ~24 fold for lipids with the commentary charged nano probes as compared to the neutral nano probes. The signal boost was attributed to the efficient delivery of extremely small, complementary charged probes to the cellular biomolecules of interest enabling simultaneous detection of sub-cellular biomolecules such as DNA, proteins and lipids and with high reproducibility. Cancer classification and investigation of drug resistance in cancer with single cell sensitivity was demonstrated. Such biomolecule-specific investigation of cancer from intact cells will open pathways for comprehensive cancer diagnosis.

Prediction of Cancer Stem Cell Fate by Surface-Enhanced Raman Scattering Functionalized Nanoprobes.

Cancer stem cells (CSCs) are the fundamental building blocks of cancer dissemination, so it is desirable to develop a technique to predict the behavior of CSCs during tumor initiation and relapse. It will provide a powerful tool for pathological prognosis. Currently, there exists no method of such prediction. Here, we introduce nickel-based functionalized nanoprobe facilitated surface enhanced Raman scattering (SERS) for prediction of cancer dissemination by undertaking CSC-based surveillance. SERS profiling of CSCs of various cell lines (breast cancer, cervical cancer, and lung cancer) was compared with their cancer counterparts for the prediction of prognosis, with statistical significance of single-cell sensitivity. The single-cell sensitivity is critical as even a few CSCs are capable of initiating a tumor. Intermediate states of CSC transmutation to cancer cells and its reverse were monitored, and nanoprobe-assisted SERS profiling was undertaken. We experimentally demonstrated that the quasi-intermediate CSC states have dissimilar profiles during the transformation from cancer to CSC and vice versa enabling statistical differentiation without ambiguity. It was also observed that molecular signatures of these opposite pathways are cancer-type specific. This observation provided additional clarity to the current understanding of relatively unfamiliar quasi-intermediate states; making it possible to predict CSC dissemination for variety of cancers with ∼99% accuracy. Nano probe-based prediction of CSC fate is a powerful prediction tool for ultrasensitive prognosis of malignancy in a complex environment. Such CSC-based cancer prognosis has never been proposed before. This prediction technique has potential to provide insights for cancer diagnosis and prognosis as well as for obtaining information instrumental in designing of meaningful CSC-based cancer therapeutics.

Non plasmonic semiconductor quantum SERS probe as a pathway for in vitro cancer detection.

Surface-enhanced Raman scattering (SERS)-based cancer diagnostics is an important analytical tool in early detection of cancer. Current work in SERS focuses on plasmonic nanomaterials that suffer from coagulation, selectivity, and adverse biocompatibility when used in vitro, limiting this research to stand-alone biomolecule sensing. Here we introduce a label-free, biocompatible, ZnO-based, 3D semiconductor quantum probe as a pathway for in vitro diagnosis of cancer. By reducing size of the probes to quantum scale, we observed a unique phenomenon of exponential increase in the SERS enhancement up to ~106 at nanomolar concentration. The quantum probes are decorated on a nano-dendrite platform functionalized for cell adhesion, proliferation, and label-free application. The quantum probes demonstrate discrimination of cancerous and non-cancerous cells along with biomolecular sensing of DNA, RNA, proteins and lipids in vitro. The limit of detection is up to a single-cell-level detection.