Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with ...different systems, can be compared on an equal footing.
An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise.
Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility.
A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.
Effectiveness of surgery as a cancer treatment is reduced when all cancer cells are not detected during surgery, leading to recurrences that negatively impact survival. To maximize cancer cell ...detection during cancer surgery, we designed an
intraoperative, label-free, optical cancer detection system that combines intrinsic fluorescence spectroscopy, diffuse reflectance spectroscopy, and Raman spectroscopy. Using this multimodal optical cancer detection system, we found that brain, lung, colon, and skin cancers could be detected
during surgery with an accuracy, sensitivity, and specificity of 97%, 100%, and 93%, respectively. This highly sensitive optical molecular imaging approach can profoundly impact a wide range of surgical and noninvasive interventional oncology procedures by improving cancer detection capabilities, thereby reducing cancer burden and improving survival and quality of life.
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Single-cell technologies have enabled the characterization of the tumour microenvironment at unprecedented depth and have revealed vast cellular diversity among tumour cells and their niche. ...Anti-tumour immunity relies on cell-cell relationships within the tumour microenvironment
, yet many single-cell studies lack spatial context and rely on dissociated tissues
. Here we applied imaging mass cytometry to characterize the immunological landscape of 139 high-grade glioma and 46 brain metastasis tumours from patients. Single-cell analysis of more than 1.1 million cells across 389 high-dimensional histopathology images enabled the spatial resolution of immune lineages and activation states, revealing differences in immune landscapes between primary tumours and brain metastases from diverse solid cancers. These analyses revealed cellular neighbourhoods associated with survival in patients with glioblastoma, which we leveraged to identify a unique population of myeloperoxidase (MPO)-positive macrophages associated with long-term survival. Our findings provide insight into the biology of primary and metastatic brain tumours, reinforcing the value of integrating spatial resolution to single-cell datasets to dissect the microenvironmental contexture of cancer.
Raman spectroscopy imaging is a technique that can be adapted for intraoperative tissue characterization to be used for surgical guidance. Here we present a macroscopic line scanning Raman imaging ...system that has been modified to ensure suitability for intraoperative use. The imaging system has a field of view of 1 × 1 cm
and acquires Raman fingerprint images of 40 × 42 pixels, typically in less than 5 minutes. The system is mounted on a mobile cart, it is equiped with a passive support arm and possesses a removable and sterilizable probe muzzle. The results of a proof of concept study are presented in porcine adipose and muscle tissue. Supervised machine learning models (support vector machines and random forests) were trained and they were tested on a holdout dataset consisting of 7 Raman images (10 080 spectra) acquired in different animal tissues. This led to a detection accuracy >96% and prediction confidence maps providing a quantitative detection assessment for tissue border visualization. Further testing was accomplished on a dataset acquired with the imaging probe's contact muzzle and tailored classification models showed robust classifications capabilities with specificity, sensitivity and accuracy all surpassing 95% with a support vector machine classifier. Finally, laser safety, biosafety and sterilization of the system was assest. The safety assessment showed that the system's laser can be operated safetly according to the American National Standards Institute's standard for maximum permissible exposures for eyes and skin. It was further shown that during tissue interrogation, the temperature-history in cumulative equivalent minutes at 43 °C (CEM43 °C) never exceeded a safe threshold of 5 min.
Background. The development of 2 unassociated brain cancers in the same patient is a rare occurrence. Secondary cancers are generally thought to develop as an oncogenic consequence of the radiation ...therapy delivered to treat the primary cancers, always requiring a significant time interval between radiation treatment and secondary cancer development. Case Description. We report the development of an undifferentiated myxoid sarcoma only 13 months following radiation therapy for a glioblastoma. Conclusion. This case represents the shortest time interval reported between radiation therapy and secondary brain cancer development.
Invasive brain cancer cells cannot be visualized during surgery and so they are often not removed. These residual cancer cells give rise to recurrences. In vivo Raman spectroscopy can detect these ...invasive cancer cells in patients with grade 2 to 4 gliomas. The robustness of this Raman signal can be dampened by spectral artifacts generated by lights in the operating room. We found that artificial neural networks (ANNs) can overcome these spectral artifacts using nonparametric and adaptive models to detect complex nonlinear spectral characteristics. Coupling ANN with Raman spectroscopy simplifies the intraoperative use of Raman spectroscopy by limiting changes required to the standard neurosurgical workflow. The ability to detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery and improve patient survival.
Surgical treatment of brain cancer is limited by the inability of current imaging capabilities such as magnetic resonance imaging (MRI) to detect the entirety of this locally invasive cancer. This ...results in residual cancer cells remaining following surgery, leading to recurrence and death. We demonstrate that intraoperative Raman spectroscopy can detect invasive cancer cells centimeters beyond pathological T1-contrast-enhanced and T2-weighted MRI signals. This intraoperative optical guide can be used to detect invasive cancer cells and minimize post-surgical cancer burden. The detection of distant invasive cancer cells beyond MRI signal has the potential to increase the effectiveness of surgery and directly lengthen patient survival.
Raman spectroscopy is a promising tool for neurosurgical guidance and cancer research. Quantitative analysis of the Raman signal from living tissues is, however, limited. Their molecular composition ...is convoluted and influenced by clinical factors, and access to data is limited. To ensure acceptance of this technology by clinicians and cancer scientists, we need to adapt the analytical methods to more closely model the Raman-generating process. Our objective is to use feature engineering to develop a new representation for spectral data specifically tailored for brain diagnosis that improves interpretability of the Raman signal while retaining enough information to accurately predict tissue content. The method consists of band fitting of Raman bands which consistently appear in the brain Raman literature, and the generation of new features representing the pairwise interaction between bands and the interaction between bands and patient age. Our technique was applied to a dataset of 547 in situ Raman spectra from 65 patients undergoing glioma resection. It showed superior predictive capacities to a principal component analysis dimensionality reduction. After analysis through a Bayesian framework, we were able to identify the oncogenic processes that characterize glioma: increased nucleic acid content, overexpression of type IV collagen and shift in the primary metabolic engine. Our results demonstrate how this mathematical transformation of the Raman signal allows the first biological, statistically robust analysis of in vivo Raman spectra from brain tissue.
Glioblastoma is the most lethal primary brain cancer. Clinical outcomes for glioblastoma remain poor, and new treatments are needed.
To investigate whether adding autologous tumor lysate-loaded ...dendritic cell vaccine (DCVax-L) to standard of care (SOC) extends survival among patients with glioblastoma.
This phase 3, prospective, externally controlled nonrandomized trial compared overall survival (OS) in patients with newly diagnosed glioblastoma (nGBM) and recurrent glioblastoma (rGBM) treated with DCVax-L plus SOC vs contemporaneous matched external control patients treated with SOC. This international, multicenter trial was conducted at 94 sites in 4 countries from August 2007 to November 2015. Data analysis was conducted from October 2020 to September 2021.
The active treatment was DCVax-L plus SOC temozolomide. The nGBM external control patients received SOC temozolomide and placebo; the rGBM external controls received approved rGBM therapies.
The primary and secondary end points compared overall survival (OS) in nGBM and rGBM, respectively, with contemporaneous matched external control populations from the control groups of other formal randomized clinical trials.
A total of 331 patients were enrolled in the trial, with 232 randomized to the DCVax-L group and 99 to the placebo group. Median OS (mOS) for the 232 patients with nGBM receiving DCVax-L was 19.3 (95% CI, 17.5-21.3) months from randomization (22.4 months from surgery) vs 16.5 (95% CI, 16.0-17.5) months from randomization in control patients (HR = 0.80; 98% CI, 0.00-0.94; P = .002). Survival at 48 months from randomization was 15.7% vs 9.9%, and at 60 months, it was 13.0% vs 5.7%. For 64 patients with rGBM receiving DCVax-L, mOS was 13.2 (95% CI, 9.7-16.8) months from relapse vs 7.8 (95% CI, 7.2-8.2) months among control patients (HR, 0.58; 98% CI, 0.00-0.76; P < .001). Survival at 24 and 30 months after recurrence was 20.7% vs 9.6% and 11.1% vs 5.1%, respectively. Survival was improved in patients with nGBM with methylated MGMT receiving DCVax-L compared with external control patients (HR, 0.74; 98% CI, 0.55-1.00; P = .03).
In this study, adding DCVax-L to SOC resulted in clinically meaningful and statistically significant extension of survival for patients with both nGBM and rGBM compared with contemporaneous, matched external controls who received SOC alone.
ClinicalTrials.gov Identifier: NCT00045968.
Emerging data suggest that a subset of patients with diffuse isocitrate dehydrogenase (IDH)-mutant low-grade glioma (LGG) who receive adjuvant temozolomide (TMZ) recur with hypermutation in ...association with malignant progression to higher-grade tumors. It is currently unclear why some TMZ-treated LGG patients recur with hypermutation while others do not. MGMT encodes O6-methylguanine-DNA methyltransferase, a DNA repair protein that removes cytotoxic and potentially mutagenic lesions induced by TMZ. Here, we hypothesize that epigenetic silencing of MGMT by promoter methylation facilitates TMZ-induced mutagenesis in LGG patients and contributes to development of hypermutation at recurrence.
We utilize a quantitative deep sequencing assay to characterize MGMT promoter methylation in 109 surgical tissue specimens from initial tumors and post-treatment recurrences of 37 TMZ-treated LGG patients. We utilize methylation arrays to validate our sequencing assay, RNA sequencing to assess the relationship between methylation and gene expression, and exome sequencing to determine hypermutation status.
Methylation level at the MGMT promoter is significantly higher in initial tumors of patients that develop hypermutation at recurrence relative to initial tumors of patients that do not (45.7% vs 34.8%, P = 0.027). Methylation level in initial tumors can predict hypermutation at recurrence in univariate models and multivariate models that incorporate patient age and molecular subtype.
These findings reveal a mechanistic basis for observed differences in patient susceptibility to TMZ-driven hypermutation. Furthermore, they establish MGMT promoter methylation level as a potential biomarker to inform clinical management of LGG patients, including monitoring and treatment decisions, by predicting risk of hypermutation at recurrence.
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