Developmental Deconvolution for Classification of Cancer Origin

Moiso, Enrico; Farahani, Alexander; Marble, Hetal D.; Hendricks, Austin; Mildrum, Samuel; Levine, Stuart S.; Lennerz, Jochen K.; Garg, Salil

doi:10.1158/2159-8290.cd-21-1443

Cited by 18 publications

(11 citation statements)

References 53 publications

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“…Some studies including eQTL [ 31 ] and REO [ 60 ] now analyze multiple genes simultaneously, increasing dimensionality of research. Secondly, the expansion of research tools: with the rapid changes in relevant technologies, the tools used by researchers have changed from PCR to second-generation sequencing [ 32 , 52–56 , 59 ] and tumor developmental atlas [ 94 ], thus achieving greater efficiency and accuracy. Thirdly, the expansion of materials used: research has expanded beyond traditional tumor tissue.…”

Section: Discussionmentioning

confidence: 99%

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New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

Ma,

Wu,

Chen

et al. 2024

Briefings in Bioinformatics

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Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

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Section: Discussionmentioning

confidence: 99%

“…The atlas aims to establish correlations between cancer biology and development. The team used a developmental multilayer perceptron (D-MLP) classifier constructed from this atlas, which showed remarkable accuracy of 0.974 in identifying TOO [ 94 ]. Image omics could also determine the TOO of CUP.…”

Section: Main Textmentioning

confidence: 99%

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

Ma,

Wu,

Chen

et al. 2024

Briefings in Bioinformatics

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“…Involving in antiviral and genomic responses to virus; 4. Contribution to the dedifferentiation and stemness of HNSCC cells through gene transcription related to craniomaxillofacial development [41].…”

Section: Transcriptomic Alterations Will Cluster and Reveal The Assoc...mentioning

confidence: 99%

Quantified Pathway Mutations Associate Epithelial- Mesenchymal Transition and Immune Escape with Poor Prognosis and Immunotherapy Resistance of Head and Neck Squamous Cell Carcinoma

Huang

Liu

et al. 2023

Preprint

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Background Pathway mutations have been calculated to predict the poor prognosis and immunotherapy resistance in head and neck squamous cell carcinoma (HNSCC). To uncover the unique markers predicting prognosis and immune therapy response, the accurately quantified pathway mutations are required to evaluate epithelial-mesenchymal transition (EMT) and immune escape. Yet, there is a lack of score to accurately quantify pathway mutations. Material and methods Firstly, we proposed Individualized Weighted Hallmark Gene Set Mutation Burden (IWHMB, https://github.com/YuHongHuang-lab/IWHMB) which integrated pathway structure information and eliminated the interference of global Tumor Mutation Burden to accurately quantify pathway mutations. Subsequently, to further elucidate the association of IWHMB with EMT and immune escape, support vector machine regression model was used to identify IWHMB-related transcriptomic features (IRG), while Adversarially Regularized Graph Autoencoder (ARVGA) was used to further resolve IRG network features. Finally, Random walk with restart algorithm was used to identify biomarkers for predicting ICI response. Results We quantified the HNSCC pathway mutation signature and identified pathway mutation subtypes using IWHMB. The IWHMB-related transcriptomic features (IRG) identified by support vector machine regression were divided into 5 communities by ARVGA, among which the community 1 that enriched with malignant mesenchymal components promoted EMT dynamically and regulated immune patterns associated with ICI responses. Bridge Hub Gene (BHG) identified by random walk with restart was key to IWHMB in EMT and immune escape, thus, more predictive for ICI response than other 70 Public signatures. Conclusion In summary, the novel pathway mutation scoring-IWHMB suggested that the elevated malignancy mediated by pathway mutations is a major cause of poor prognosis and immunotherapy failure in HNSCC, and is capable of identifying novel biomarkers to predict immunotherapy response.

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“…The Cancer Genome Atlas (TCGA) utilizes high-throughput next-genome sequencing (NGS) and bioinformatics to provide gene expression data for 33 tumor types [7], including HNSC [8]. This freely accessible data resource has signi cantly enhanced the capabilities of the tumor research community in diagnosing, treating, and predicting outcomes for cancer patients [7].…”

Section: Introductionmentioning

confidence: 99%

PLCXD2 expression relates to the immune microenvironment and prognosis of head and neck squamous cell carcinoma

Han,

Tang,

Zhang

et al. 2024

Preprint

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Objective — Despite the advances in oncology, the prognosis of head and neck squamous cell carcinoma (HNSC) patients remains dismal. In this study, we aimed to determine the relevance of PLCXD2 expression in the tumor microenvironment to the HNSC patient clinicopathological features. Methods — Gene expression analysis and multicolor immunofluorescence histochemistry with HNSC tissuemicroarrays were conducted to examine the relation between PLCXD2 expression and patient outcomes. Additionally, Spearman correlation analysis was used to assess the relationship between PLCXD2 protein expression and tumor immune infiltrating cells (TIICs), as well as immune checkpoints (PD-1, PD-L1, and CTLA-4) in HNSC tissue, while Chi-square test and Cox proportional-hazards models were employed to validate the correlation between PLCXD2 protein levels and clinicopathological characteristics with patient survival. Results — Our findings revealed higher PLCXD2 expression in HNSC tissue compared to control benign tissues. Additionally, we observed a distinct association between the presence of PLCXD2 protein in cancer nests and various TIICs, including CD4+ T cells, CD8+ T cells, dendritic cells, as well as CTLA-4+ cells in HNSC tissues. Furthermore, we demonstrated a correlation between PLCXD2 protein expression in cancer cells and advanced TNM stage, as well as a poorer prognosis. Conclusion — Taken together, this study supports PLCXD2 as an independent prognostic marker and a potentially promising target for immunotherapy in HNSC.

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Developmental Deconvolution for Classification of Cancer Origin

Cited by 18 publications

References 53 publications

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

Quantified Pathway Mutations Associate Epithelial- Mesenchymal Transition and Immune Escape with Poor Prognosis and Immunotherapy Resistance of Head and Neck Squamous Cell Carcinoma

PLCXD2 expression relates to the immune microenvironment and prognosis of head and neck squamous cell carcinoma

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