Identification of pan-cancer/testis genes and validation of therapeutic targeting in triple-negative breast cancer: Lin28a-based and Siglece-based vaccination induces antitumor immunity and inhibits metastasis.

BACKGROUND: Cancer-testis (CT) genes are targets for tumor antigen-specific immunotherapy given that their expression is normally restricted to the immune-privileged testis in healthy individuals with aberrant expression in tumor tissues. While they represent targetable germ tissue antigens and play important functional roles in tumorigenesis, there is currently no standardized approach for identifying clinically relevant CT genes. Optimized algorithms and validated methods for accurate prediction of reliable CT antigens (CTAs) with high immunogenicity are also lacking. METHODS: Sequencing data from the Genotype-Tissue Expression (GTEx) and The Genomic Data Commons (GDC) databases was used for the development of a bioinformatic pipeline to identify CT exclusive genes. A CT germness score was calculated based on the number of CT genes expressed within a tumor type and their degree of expression. The impact of tumor germness on clinical outcome was evaluated using healthy GTEx and GDC tumor samples. We then used a triple-negative breast cancer mouse model to develop and test an algorithm that predicts epitope immunogenicity based on the identification of germline sequences with strong major histocompatibility complex class I (MHCI) and MHCII binding affinities. Germline sequences for CT genes were synthesized as long synthetic peptide vaccines and tested in the 4T1 triple-negative model of invasive breast cancer with Poly(I:C) adjuvant. Vaccine immunogenicity was determined by flow cytometric analysis of in vitro and in vivo T-cell responses. Primary tumor growth and lung metastasis was evaluated by histopathology, flow cytometry and colony formation assay. RESULTS: We developed a new bioinformatic pipeline to reliably identify CT exclusive genes as immunogenic targets for immunotherapy. We identified CT genes that are exclusively expressed within the testis, lack detectable thymic expression, and are significantly expressed in multiple tumor types. High tumor germness correlated with tumor progression but not with tumor mutation burden, supporting CTAs as appealing targets in low mutation burden tumors. Importantly, tumor germness also correlated with markers of antitumor immunity. Vaccination of 4T1 tumor-bearing mice with Siglece and Lin28a antigens resulted in increased T-cell antitumor immunity and reduced primary tumor growth and lung metastases. CONCLUSION: Our results present a novel strategy for the identification of highly immunogenic CTAs for the development of targeted vaccines that induce antitumor immunity and inhibit metastasis.

Identification of pan-cancer/testis genes and validation of therapeutic targeting in triple-negative breast cancer: Lin28a- and Siglece-based vaccination induces anti-tumor immunity and inhibits metastasis.

Background: Cancer-testis (CT) genes are targets for tumor antigen-specific immunotherapy given that their expression is normally restricted to the immune-privileged testis in healthy individuals with aberrant expression in tumor tissues. While they represent targetable germ-tissue antigens and play important functional roles in tumorigenesis, there is currently no standardized approach for identifying clinically relevant CT genes. Optimized algorithms and validated methods for accurate prediction of reliable CT antigens with high immunogenicity are also lacking. Methods: Sequencing data from the Genotype-Tissue Expression (GTEx) and The Genomic Data Commons (GDC) databases was utilized for the development of a bioinformatic pipeline to identify CT exclusive genes. A CT germness score was calculated based on the number of CT genes expressed within a tumor type and their degree of expression. The impact of tumor germness with clinical outcome was evaluated using healthy GTEx and GDC tumor samples. We then used a triple-negative breast cancer mouse model to develop and test an algorithm that predicts epitope immunogenicity based on the identification of germline sequences with strong MHCI and MHCII binding affinities. Germline sequences for CT genes were synthesized as long synthetic peptide vaccines and tested in the 4T1 triple-negative model of invasive breast cancer with Poly(I:C) adjuvant. Vaccine immunogenicity was determined by flow cytometric analysis of in vitro and in vivo T cell responses. Primary tumor growth and lung metastasis was evaluated by histopathology, flow cytometry and colony formation assay. Results: We developed a new bioinformatic pipeline to reliably identify CT exclusive genes as immunogenic targets for immunotherapy. We identified CT genes that are exclusively expressed within the testis, lack detectable thymic expression, and are significantly expressed in multiple tumor types. High tumor germness correlated with tumor progression but not with tumor mutation burden, supporting CT antigens as appealing targets in low mutation burden tumors. Importantly, tumor germness also correlated with markers of anti-tumor immunity. Vaccination of 4T1 tumor bearing mice with Siglece and Lin28a antigens resulted in increased T cell anti-tumor immunity and reduced primary tumor growth and lung metastases. Conclusion: Our results present a novel strategy for the identification of highly immunogenic CT antigens for the development of targeted vaccines that induce anti-tumor immunity and inhibit metastasis.

Scaling up reproducible research for single-cell transcriptomics using MetaNeighbor.

Single-cell RNA-sequencing data have significantly advanced the characterization of cell-type diversity and composition. However, cell-type definitions vary across data and analysis pipelines, raising concerns about cell-type validity and generalizability. With MetaNeighbor, we proposed an efficient and robust quantification of cell-type replicability that preserves dataset independence and is highly scalable compared to dataset integration. In this protocol, we show how MetaNeighbor can be used to characterize cell-type replicability by following a simple three-step procedure: gene filtering, neighbor voting and visualization. We show how these steps can be tailored to quantify cell-type replicability, determine gene sets that contribute to cell-type identity and pretrain a model on a reference taxonomy to rapidly assess newly generated data. The protocol is based on an open-source R package available from Bioconductor and GitHub, requires basic familiarity with Rstudio or the R command line and can typically be run in <5 min for millions of cells.

Single-cell co-expression analysis reveals that transcriptional modules are shared across cell types in the brain.

Gene-gene relationships are commonly measured via the co-variation of gene expression across samples, also known as gene co-expression. Because shared expression patterns are thought to reflect shared function, co-expression networks describe functional relationships between genes, including co-regulation. However, the heterogeneity of cell types in bulk RNA-seq samples creates connections in co-expression networks that potentially obscure co-regulatory modules. The brain initiative cell census network (BICCN) single-cell RNA sequencing (scRNA-seq) datasets provide an unparalleled opportunity to understand how gene-gene relationships shape cell identity. Comparison of the BICCN data (500,000 cells/nuclei across 7 BICCN datasets) with that of bulk RNA-seq networks (2,000 mouse brain samples across 52 studies) reveals a consistent topology reflecting a shared co-regulatory signal. Differential signals between broad cell classes persist in driving variation at finer levels, indicating that convergent regulatory processes affect cell phenotype at multiple scales.

Inability of Current Dosing to Achieve Carboplatin Therapeutic Targets in People with Advanced Non-Small Cell Lung Cancer: Impact of Systemic Inflammation on Carboplatin Exposure and Clinical Outcomes.

BACKGROUND: The presence of elevated systemic inflammation in people with advanced non-small cell lung cancer (NSCLC) is associated with significantly shorter survival following carboplatin-based chemotherapy. OBJECTIVE: This study investigated whether novel factors, such as systemic inflammation [platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR)], impact carboplatin pharmacokinetics and drug utilisation. The study also examined the ability of current and alternate dosing regimens to meet therapeutic targets. METHODS: Seventy-two people with advanced NSCLC treated with carboplatin-based (460-1050 mg) doublet chemotherapy were recruited and pharmacokinetic data (n = 61) were analysed using non-linear mixed modelling. Covariate analysis was performed to investigate the impact of standard and novel patient characteristics of carboplatin pharmacokinetics. A Monte Carlo simulation of 100,000 representative NSCLC patients evaluated the ability of the Calvert formula and novel dosing strategies to achieve the targeted therapeutic range. The associations between systemic inflammation and chemotherapy drug utilisation (cycles received, relative dose intensity (RDI) and second-line uptake) and clinical endpoints were also investigated in the pharmacokinetic cohort, and two independent cohorts of people with advanced NSCLC from the Chemotherapy Dosing in Cancer-Related Inflammation (CDCRI) database that were administered carboplatin-paclitaxel (n = 37) or carboplatin-gemcitabine (n = 358). RESULTS: In all cohorts, 25-53% of people had elevated systemic inflammation (NLR > 5 or PLR > 300). In the pharmacokinetic cohort, no patients achieved the desired therapeutic target of carboplatin. Carboplatin exposure was related to renal function, as estimated using the Cockcroft-Gault formula, albumin and inflammation (NLR). In the pharmacokinetic cohort, increasing carboplatin area under the curve (AUC) correlated with greater reductions in red blood cells and haemoglobin. In this cohort, the average measured AUC of partial responders was 2.4 mg·min/mL. Also in the pharmacokinetic cohort, only 12% of people with an NLR > 5 received four or more cycles of chemotherapy, compared with 62% of patients with an NLR ≤ 5 (p < 0.001). For people in the CDCRI cohort receiving carboplatin-gemcitabine, those with an NLR > 5 also received less cycles (four or more cycles, 41% vs. 60%; p < 0.01) as well as less second-line chemotherapy (46% vs. 60%; p = 0.02) compared with patients without inflammation. People in the pharmacokinetic cohort with an NLR > 5 had 12 months less median survival compared with people with an NLR ≤ 5 (6.5 vs. 18 months; p = 0.08). Similarly, overall survival was significantly shortened in people in the CDCRI cohort receiving carboplatin-gemcitabine with an NLR > 5 compared with those with an NLR ≤ 5 (7 vs. 12 months; p < 0.001), and Cox regression analysis showed a 1.5-fold (1.3-2.1; p < 0.001) increased hazard of death associated with the increased systemic inflammation. Simulations of the newly developed model-based and Calvert dosing assessed the ability to reach this study's proposed actual target AUC of 2.2-2.6 mg·min/mL. These showed current Calvert dosing was predicted to result in substantial overexposure in patients with high systemic inflammation. The newly developed model showed equivalent levels of carboplatin therapeutic target achievement across the spectrum of inflammation observed in the lung cancer population. CONCLUSION: An alternate model-based dosing strategy for carboplatin was developed and is predicted to result in consistent drug exposure across the population and improve attainment of therapeutic targets. Further studies of this new model are warranted in people with advanced NSCLC.

Systemic inflammation is an independent predictive marker of clinical outcomes in mucosal squamous cell carcinoma of the head and neck in oropharyngeal and non-oropharyngeal patients.

BACKGROUND: Currently there are very few biomarkers to identify head and neck squamous cell carcinoma (HNSCC) cancer patients at a greater risk of recurrence and shortened survival. This study aimed to investigate whether a marker of systemic inflammation, the neutrophil-to-lymphocyte ratio (NLR), was predictive of clinical outcomes in a heterogeneous cohort of HNSCC cancer patients. METHODS: We performed a retrospective analysis to identify associations between NLR and clinicopathological features to recurrence free survival (RFS) and overall survival (OS). Univariate analysis was used to identify associations and selected variables were included in multivariable Cox regression analysis to determine predictive value. RESULTS: A total of 145 patients with stage I-IV HNSCC that had undergone radiotherapy were analysed. Seventy-six of these patients had oropharyngeal cancer and 69 had non-oropharyngeal HNSCC and these populations were analysed separately. NLR was not associated to any clinicopathological variable. On univariate analysis, NLR showed associations with RFS and OS in both sub-populations. Multivariable analysis showed patients with NLR > 5 had shortened OS in both sub-populations but NLR > 5 only predicted RFS in oropharyngeal patients. Poor performance status predicted OS in both sub-populations and current smokers had shortened OS and RFS in non-oropharyngeal patients. CONCLUSIONS: The results show patients with NLR > 5 predict for shorter overall survival. Further prospective validation studies in larger cohorts are required to determine the clinical applicability of NLR for prognostication in HNSCC patients.

A feasibility study for using ABS plastic and a low-cost 3D printer for patient-specific brachytherapy mould design.

This feasibility study aims to determine if a low-cost 3D printer (BitsFromBytes 3D Touch) with ABS plastic can print custom mould structures and catheter channels defined in a brachytherapy treatment planning system (Nucletron Oncentra) for patient-specific treatment. Printer accuracy was evaluated through physical measurement, and print quality was investigated by adjusting print parameters (print speed, layer thickness, percentage infill). Catheter positioning and reproducibility were measured over repeated insertions. ABS plastic water equivalency was investigated by comparing Ir-192 HDR source dose distributions, measured with radiochromic film, in ABS plastic and in water. Structures and catheter channels were printed accurately to within 0.5 mm laterally and 1 mm in the vertical print direction. Adjusting print parameters could reduce print time, albeit with reduced print quality. 3.5 mm channel diameters allowed for easy catheter insertion. Catheter positioning was reproducible to within 0.5 mm but, because of catheter flex within the channel, was on average 1 mm offset from defined TPS positions. This offset could be accounted for by repeating the treatment planning CT scan with the printed mould positioned on the patient. Dose attenuation in ABS plastic and in water was equivalent to within the measurement limitations. While clinical uses for this particular low-cost printer and ABS plastic are limited by print size restrictions and non-certification for biocompatibility, it has been demonstrated that a low-cost 3D printer set-up can accurately create custom moulds and catheter channels potentially acceptable for clinical use.

Fluorescent sensing of monofunctional platinum species.

We report here FDCPt1, a novel selective fluorescent sensor for monofunctional platinum species. In the presence of such species, FDCPt1 exhibits a 70-fold increase in fluorescence emission, and can be used to monitor the metabolism of Pt(II)-based complexes in colorectal cancer cells. This probe is therefore expected to be valuable in studying changes in Pt coordination and distribution during chemotherapy.