Raman spectroscopy biochemical characterisation of bladder cancer cisplatin resistance regulated by FDFT1: a review

Spectroscopic diagnosis and metabolite characterization of cisplatin resistance regulated by FDFT1 in bladder cancer tissue

As is the case for most solid tumours, chemotherapy remains the backbone in the management of metastatic disease. However, the occurrence of chemotherapy resistance is a cause to worry, especially in bladder cancer. Extensive evidence indicates molecular changes in bladder cancer cells to be the underlying cause of chemotherapy resistance, including the reduced expression of farnesyl-diphosphate farnesyltransferase 1 (FDFT1) - a gene involved in cholesterol biosynthesis. This can likely be a hallmark in examining the resistance and sensitivity of chemotherapy drugs. This work performs spectroscopic analysis and metabolite characterization on resistant, sensitive, stable-disease and healthy bladder tissues. Raman spectroscopy has detected peaks at around 1003 cm-1 (squalene), 1178 cm-1 (cholesterol), 1258 cm-1 (cholesteryl ester), 1343 cm-1 (collagen), 1525 cm-1 (carotenoid), 1575 cm-1 (DNA bases) and 1608 cm-1 (cytosine). The peak parameters were examined, and statistical analysis was performed on the peak features, attaining significant differences between the sample groups. Small-angle x-ray scattering (SAXS) measurements observed the triglyceride peak together with 6th, 7th and 8th - order collagen peaks; peak parameters were also determined. Neutron activation analysis (NAA) detected seven trace elements. Carbon (Ca), magnesium (Mg), chlorine (Cl) and sodium (Na) have been found to have the greatest concentration in the sample groups, suggestive of a role as a biomarker for cisplatin resistance studies. Results from the present research are suggested to provide an important insight into understanding the development of drug resistance in bladder cancer, opening up the possibility of novel avenues for treatment through personalised interventions.

The mechanism and clinical application of farnesyl diphosphate farnesyltransferase 1 in cancer metabolism

Cancer poses a significant risk to human well-being. Among the crucial characteristics of cancer is metabolic reprogramming. To meet the relentless metabolic needs, cancer cells enhance cholesterol metabolism within the adverse tumor microenvironment. Reprograming cholesterol metabolism includes a series of modifications in the synthesis, absorption, esterification, and metabolites associated with cholesterol. These adjustments have a strong correlation with the proliferation, invasion, metastasis, and other characteristics of malignant tumors. FDFT1, also known as farnesyl diphosphate farnesyltransferase 1, is an enzyme crucial in the process of cholesterol biosynthesis. Its significant involvement in tumor metabolism has garnered considerable interest. The significance of FDFT1 in cancer metabolism cannot be overstated, as it actively interacts with cancer cells. This paper aims to analyze and consolidate the mechanism of FDFT1 in cancer metabolism and explore its clinical application. The goal is to contribute new strategies and targets for the prevention and treatment of cancer metabolism.

Non-coding RNA transcripts, incredible modulators of cisplatin chemo-resistance in bladder cancer through operating a broad spectrum of cellular processes and signaling mechanism

Bladder cancer (BC) is a highly frequent neoplasm in correlation with significant rate of morbidity, mortality, and cost. The onset of BC is predominantly triggered by environmental and/or occupational exposures to carcinogens, such as tobacco. There are two distinct pathways by which BC can be developed, including non-muscle-invasive papillary tumors (NMIBC) and non-papillary (or solid) muscle-invasive tumors (MIBC). The Cancer Genome Atlas project has further recognized key genetic drivers of MIBC along with its subtypes with particular properties and therapeutic responses; nonetheless, NMIBC is the predominant BC presentation among the suffering individuals. Radical cystoprostatectomy, radiotherapy, and chemotherapy have been verified to be the common therapeutic interventions in metastatic tumors, among which chemotherapeutics are more conventionally utilized. Although multiple chemo drugs have been broadly administered for BC treatment, cisplatin is reportedly the most effective chemo drug against the corresponding malignancy. Notwithstanding, tumor recurrence is usually occurred following the consumption of cisplatin regimens, particularly due to the progression of chemo-resistant trait. In this framework, non-coding RNAs (ncRNAs), as abundant RNA transcripts arise from the human genome, are introduced to serve as crucial contributors to tumor expansion and cisplatin chemo-resistance in bladder neoplasm. In the current review, we first investigated the best-known ncRNAs, i.e. microRNAs (miRNAs), long ncRNAs (lncRNAs), and circular RNAs (circRNAs), correlated with cisplatin chemo-resistance in BC cells and tissues. We noticed that these ncRNAs could mediate the BC-related cisplatin-resistant phenotype through diverse cellular processes and signaling mechanisms, reviewed here. Eventually, diagnostic and prognostic potential of ncRNAs, as well as their therapeutic capabilities were highlighted in regard to BC management.

A Raman spectral marker for the iso-octyl chain structure of cholesterol

Raman spectroscopy provides label-free, specific analysis of biomolecular structure and interactions. It could have a greater impact with improved characterization of complex fingerprint vibrations. Many Raman peaks have been assigned to cholesterol, for example, but the molecular vibrations associated with those peaks are not known. In this report, time-dependent density functional theory calculations of the Raman spectrum of cholesterol are compared to measurements on microcrystalline powder to identify 23 peaks in the Raman spectrum. Among them, a band of six peaks is found to be sensitive to the conformational structure of cholesterol's iso-octyl chain. Calculations on 10 conformers in this spectral band are fit to experimental spectra to probe the cholesterol chain structure in purified powder and in phospholipid vesicles. In vesicles, the chain is found to bend perpendicular to the steroid rings, supporting the case that the chain is a dynamic structure that contributes to lipid condensation and other effects of cholesterol in biomembranes. Statement of Significance: Here we use density functional theory to identify a band of six peaks in cholesterol's Raman spectrum that is sensitive to the conformational structure of cholesterol's chain. Raman spectra were analyzed to show that in fluid-phase lipid membranes, about half of the cholesterol chains point perpendicular to the steroid rings. This new method of label-free structural analysis could make significant contributions to our understanding of cholesterol's critical role in biomembrane structure and function. More broadly, the results show that computational quantum chemistry Raman spectroscopy can make significant new contributions to molecular structure when spectra are interpreted with computational quantum chemistry.

The lipid metabolism remodeling: A hurdle in breast cancer therapy

Lipids, as one of the three primary energy sources, provide energy for all cellular life activities. Lipids are also known to be involved in the formation of cell membranes and play an important role as signaling molecules in the intracellular and microenvironment. Tumor cells actively or passively remodel lipid metabolism, using the function of lipids in various important cellular life activities to evade therapeutic attack. Breast cancer has become the leading cause of cancer-related deaths in women, which is partly due to therapeutic resistance. It is necessary to fully elucidate the formation and mechanisms of chemoresistance to improve breast cancer patient survival rates. Altered lipid metabolism has been observed in breast cancer with therapeutic resistance, indicating that targeting lipid reprogramming is a promising anticancer strategy.

Promising applications of nanotechnology in inhibiting chemo-resistance in solid tumors by targeting epithelial-mesenchymal transition (EMT)

The resistance of cancer cells to chemotherapy, also known as chemo-resistance, poses a significant obstacle to cancer treatment and can ultimately result in patient mortality. Epithelial-mesenchymal transition (EMT) is one of the many factors and processes responsible for chemo-resistance. Studies have shown that targeting EMT can help overcome chemo-resistance, and nanotechnology and nanomedicine have emerged as promising approaches to achieve this goal. This article discusses the potential of nanotechnology in inhibiting EMT and proposes a viable strategy to combat chemo-resistance in various solid tumors, including breast cancer, lung cancer, pancreatic cancer, glioblastoma, ovarian cancer, gastric cancer, and hepatocellular carcinoma. While nanotechnology has shown promising results in targeting EMT, further research is necessary to explore its full potential in overcoming chemo-resistance and discovering more effective methods in the future.

Monitoring Metabolic Changes in Response to Chemotherapies in Cancer with Raman Spectroscopy and Metabolomics

Resistance to clinical therapies remains a major barrier in cancer management. There is a critical need for rapid and highly sensitive diagnostic tools that enable early prediction of treatment response to allow accurate clinical decisions. Here, Raman spectroscopy was employed to monitor changes in key metabolites as early predictors of response in KRAS-mutant colorectal cancer (CRC) cells, HCT116, treated with chemotherapies. We show at the single cell level that HCT116 is resistant to cetuximab (CTX), the first-line treatment in CRC, but this resistance can be overcome with pre-sensitization of cells with oxaliplatin (OX). In combination treatment of CTX + OX, sequential delivery of OX followed by CTX rather than simultaneous administration of drugs was observed to be critical for effective therapy. Our results demonstrated that metabolic changes are well aligned to cellular mechanical changes where Young's modulus decreased after effective treatment, indicating that both changes in mechanical properties and metabolism in cells are likely responsible for cancer proliferation. Raman findings were verified with mass spectrometry (MS) metabolomics, and both platforms showed changes in lipids, nucleic acids, and amino acids as predictors of resistance/response. Finally, key metabolic pathways enriched were identified when cells are resistant to CTX but downregulated with effective treatment. This study highlights that drug-induced metabolic changes both at the single cell level (Raman) and ensemble level (MS) have the potential to identify mechanisms of response to clinical cancer therapies.

Integrated multi-omics and machine learning approach reveals lipid metabolic biomarkers and signaling in age-related meibomian gland dysfunction

Meibomian gland dysfunction (MGD) is a prevalent inflammatory disorder of the ocular surface that significantly impacts patients' vision and quality of life. The underlying mechanism of aging and MGD remains largely uncharacterized. The aim of this work is to investigate lipid metabolic alterations in age-related MGD (ARMGD) through integrated proteomics, lipidomics and machine learning (ML) approach. For this purpose, we collected samples of female mouse meibomian glands (MGs) dissected from eyelids at age two months (n = 9) and two years (n = 9) for proteomic and lipidomic profilings using the liquid chromatography with tandem mass spectrometry (LC-MS/MS) method. To further identify ARMGD-related lipid biomarkers, ML model was established using the least absolute shrinkage and selection operator (LASSO) algorithm. For proteomic profiling, 375 differentially expressed proteins were detected. Functional analyses indicated the leading role of cholesterol biosynthesis in the aging process of MGs. Several proteins were proposed as potential biomarkers, including lanosterol synthase (Lss), 24-dehydrocholesterol reductase (Dhcr24), and farnesyl diphosphate farnesyl transferase 1 (Fdft1). Concomitantly, lipidomic analysis unveiled 47 lipid species that were differentially expressed and clustered into four classes. The most notable age-related alterations involved a decline in cholesteryl esters (ChE) levels and an increase in triradylglycerols (TG) levels, accompanied by significant differences in their lipid unsaturation patterns. Through ML construction, it was confirmed that ChE(26:0), ChE(26:1), and ChE(30:1) represent the most promising diagnostic molecules. The present study identified essential proteins, lipids, and signaling pathways in age-related MGD (ARMGD), providing a reference landscape to facilitate novel strategies for the disease transformation.

Peptidase inhibitor (PI16) impairs bladder cancer metastasis by inhibiting NF-κB activation via disrupting multiple-site ubiquitination of NEMO

BACKGROUND

Bladder cancer (BLCA) is a malignancy that frequently metastasizes and leads to poor patient prognosis. It is essential to understand the molecular mechanisms underlying the progression and metastasis of BLCA and identify potential biomarkers.

METHODS

The expression of peptidase inhibitor 16 (PI16) was analysed using quantitative PCR, immunoblotting and immunohistochemistry assays. The functional roles of PI16 were evaluated using wound healing, transwell, and human umbilical vein endothelial cell tube formation assays, as well as in vivo tumour models. The effects of PI16 on nuclear factor κB (NF-κB) signalling activation were examined using luciferase reporter gene systems, immunoblotting and immunofluorescence assays. Co-immunoprecipitation was used to investigate the interaction of PI16 with annexin-A1 (ANXA1) and NEMO.

RESULTS

PI16 expression was downregulated in bladder cancer tissues, and lower PI16 levels correlated with disease progression and poor survival in patients with BLCA. Overexpressing PI16 inhibited BLCA cell growth, motility, invasion and angiogenesis in vitro and in vivo, while silencing PI16 had the opposite effects. Mechanistically, PI16 inhibited the activation of the NF-κB pathway by interacting with ANXA1, which inhibited K63 and M1 ubiquitination of NEMO.

CONCLUSIONS

These results indicate that PI16 functions as a tumour suppressor in BLCA by inhibiting tumour growth and metastasis. Additionally, PI16 may serve as a potential biomarker for metastatic BLCA.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer

Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Raman microspectroscopy fingerprinting of organoid differentiation state

Background

Organoids, which are organs grown in a dish from stem or progenitor cells, model the structure and function of organs and can be used to define molecular events during organ formation, model human disease, assess drug responses, and perform grafting in vivo for regenerative medicine approaches. For therapeutic applications, there is a need for nondestructive methods to identify the differentiation state of unlabeled organoids in response to treatment with growth factors or pharmacologicals.

Methods

Using complex 3D submandibular salivary gland organoids developed from embryonic progenitor cells, which respond to EGF by proliferating and FGF2 by undergoing branching morphogenesis and proacinar differentiation, we developed Raman confocal microspectroscopy methods to define Raman signatures for each of these organoid states using both fixed and live organoids.

Results

Three separate quantitative comparisons, Raman spectral features, multivariate analysis, and machine learning, classified distinct organoid differentiation signatures and revealed that the Raman spectral signatures were predictive of organoid phenotype.

Conclusions

As the organoids were unlabeled, intact, and hydrated at the time of imaging, Raman spectral fingerprints can be used to noninvasively distinguish between different organoid phenotypes for future applications in disease modeling, drug screening, and regenerative medicine.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11658-022-00347-3.

Salivary gland organoids have unique Raman signatures detectable with a confocal-based Raman imaging approach.

Raman signatures can be detected in unlabeled fixed or live organoids.

Raman spectral signatures effectively predict organoid phenotypes.

Raman spectroscopy and multivariate analysis as potential tool to follow Alzheimer's disease progression

Raman spectroscopy is an emerging tool in the research and diagnosis of different diseases, including neurodegenerative disorders. In this work, blood serum samples collected from healthy controls and dementia patients were analysed by Raman spectroscopy to develop a classification model for the diagnosis of dementia of Alzheimer’s type (DAT). Raman spectra were processed by means of multivariate tools for multivariate analysis. Lower concentration levels of carotenoids were detected in blood serum from patients, which allowed for a good discrimination with respect to controls, such as 93% of correct predictions on the test set with random forest. We also hypothesize that carotenoid levels might be informative about the severity and progression of the disease, since the intensity of carotenoid signals decreased from the early stage to more severe patients. These encouraging results suggest the possibility to use Raman spectroscopy for the analysis of alternative biofluids (e.g. saliva) and the unobtrusive diagnosis of other neurodegenerative disorders.

Toward a SERS Diagnostic Tool for Discrimination between Cancerous and Normal Bladder Tissues via Analysis of the Extracellular Fluid

Vibrational spectroscopy provides the possibility for sensitive and precise detection of chemical changes in biomolecules due to development of cancers. In this work, label-free near-infrared surface enhanced Raman spectroscopy (SERS) was applied for the differentiation between cancerous and normal human bladder tissues via analysis of the extracellular fluid of the tissue. Specific cancer-related SERS marker bands were identified by using a 1064 nm excitation wavelength. The prominent spectral marker band was found to be located near 1052 cm^-1 and was assigned to the C-C, C-O, and C-N stretching vibrations of lactic acid and/or cysteine molecules. The correct identification of 80% of samples is achieved with even limited data set and could be further improved. The further development of such a detection method could be implemented in clinical practice for the aid of surgeons in determining of boundaries of malignant tumors during the surgery.