Publications by authors named "David J H Shih"

Article Synopsis
  • Human cytomegalovirus (HCMV) is a significant cause of birth defects and severe infections after transplants, but a vaccine for it is still needed.
  • V160 is a new vaccine that showed 42.4% efficacy in preventing HCMV infection in a study with seronegative women.
  • This research investigates how V160 stimulates T cell responses, revealing the presence of specific, effective CD8 T cells and identifying different types of T cell clones with varying expansion behaviors post-vaccination.
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  • Deep learning models used for predicting disease risks face challenges like time-varying factors, rare cases, imbalanced data, and delayed diagnoses, especially in complex conditions like hepatocellular carcinoma related to nonalcoholic fatty liver disease.
  • This study analyzed the performance of deep learning models on a large patient cohort from electronic health records and focused on refining prediction strategies to deal with delayed diagnoses and covariate imbalance.
  • Key findings included the effectiveness of modeling time-varying data, the positive impact of transfer learning on data scarcity, and the negative effects of sex bias, highlighting the need for balanced data in training.
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SMARCB1 loss has long been observed in many solid tumors. However, there is a need to elucidate targetable pathways driving growth and metastasis in SMARCB1-deficient tumors. Here, we demonstrate that SMARCB1 deficiency, defined as genomic SMARCB1 copy number loss associated with reduced mRNA, drives disease progression in patients with bladder cancer by engaging STAT3.

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  • Deep learning models have proven effective in biomedical applications but face challenges like time-varying data, rare occurrences, and imbalances in covariates, especially when predicting one disease related to another, as seen with hepatocellular carcinoma in patients with nonalcoholic fatty liver disease.
  • This study aims to explore how these factors impact model performance and to develop strategies that enhance disease risk prediction.
  • The researchers used two deep learning models on a large dataset to demonstrate that addressing time-varying covariates and implementing transfer learning can improve prediction accuracy, revealing that sex bias significantly affects model performance.
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Background: The integration of next-generation sequencing (NGS) comprehensive gene profiling (CGP) into clinical practice is playing an increasingly important role in oncology. Therefore, the HKU-HKSH Multi-disciplinary Molecular Tumour Board (MTB) was established to advance precision oncology in Hong Kong. A multicenter retrospective study investigated the feasibility of the HKU-HKSH MTB in determining genome-guided therapy for treatment-refractory solid cancers in Hong Kong.

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Background: Tumour mutational burden (TMB) has emerged as a predictive marker for responsiveness to immune checkpoint inhibitors (ICI) in multiple tumour types. It can be calculated from somatic mutations detected from whole exome or targeted panel sequencing data. As mutations are unevenly distributed across the cancer genome, the clinical implications from TMB calculated using different genomic regions are not clear.

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Unlabelled: Multicellularity was a watershed development in evolution. However, it also meant that individual cells could escape regulatory mechanisms that restrict proliferation at a severe cost to the organism: cancer. From the standpoint of cellular organization, evolutionary complexity scales to organize different molecules within the intracellular milieu.

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Motivation: Cross-sectional analyses of primary cancer genomes have identified regions of recurrent somatic copy-number alteration, many of which result from positive selection during cancer formation and contain driver genes. However, no effective approach exists for identifying genomic loci under significantly different degrees of selection in cancers of different subtypes, anatomic sites or disease stages.

Results: CNGPLD is a new tool for performing case-control somatic copy-number analysis that facilitates the discovery of differentially amplified or deleted copy-number aberrations in a case group of cancer compared with a control group of cancer.

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Article Synopsis
  • Acquired resistance and clonal heterogeneity present major hurdles in cancer treatment, and existing computational tools are inadequate for discovering new therapies to combat resistance.
  • Researchers developed a bioinformatic approach using high-throughput transcriptomic databases to identify candidate drugs for combinatorial therapy against resistance, focusing on PARP inhibitors in triple-negative inflammatory breast cancer.
  • The study revealed considerable transcriptomic diversity among resistant clones, indicating that while these changes might not directly cause resistance, they create a shared vulnerability that can be targeted with specific drugs, enhancing strategies for precision oncology.
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Nucleotide excision repair (NER) resolves DNA adducts, such as those caused by ultraviolet light. Deficient NER (dNER) results in a higher mutation rate that can predispose to cancer development and premature ageing phenotypes. Here, we used isogenic dNER model cell lines to establish a gene expression signature that can accurately predict functional NER capacity in both cell lines and patient samples.

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Defect in DNA damage response (DDR) is a common feature of cancer cells, which regulates tumor growth and therapeutic response. Recently, the approval of immune checkpoint blockade (ICB) for tumors with defective mismatch repair has paved the way for investigating the role of other DDR defects in sensitizing cancer to ICB therapy. Despite great progress in understanding DDR pathways, the mechanisms that link DDR defects and ICB response remain incompletely understood.

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Primary cutaneous γδ T cell lymphomas (PCGDTLs) represent a heterogeneous group of uncommon but aggressive cancers. Herein, we perform genome-wide DNA, RNA, and T cell receptor (TCR) sequencing on 29 cutaneous γδ lymphomas. We find that PCGDTLs are not uniformly derived from Vδ2 cells.

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  • Brain metastases from lung adenocarcinoma (BM-LUAD) are a major cause of death, prompting research into genetic factors that support their development.
  • Whole-exome sequencing of 73 BM-LUAD cases revealed candidate genes with significant changes compared to primary lung adenocarcinoma, with highlights on MYC, YAP1, and MMP13 having higher amplification rates.
  • Functional tests in mouse models showed that overexpressing MYC, YAP1, or MMP13 increased brain metastasis, indicating that genetic alterations play a key role in the progression of these tumors.
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Deficient DNA mismatch repair (dMMR) induces a hypermutator phenotype that can lead to tumorigenesis; however, the functional impact of the high mutation burden resulting from this phenotype remains poorly explored. Here, we demonstrate that dMMR-induced destabilizing mutations lead to proteome instability in dMMR tumors, resulting in an abundance of misfolded protein aggregates. To compensate, dMMR cells utilize a Nedd8-mediated degradation pathway to facilitate clearance of misfolded proteins.

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The chromatin remodeling factor chromodomain helicase DNA-binding protein 4 (CHD4) is a core component of the nucleosome remodeling and deacetylase (NuRD) complex. Due to its important role in DNA damage repair, CHD4 has been identified as a key determinant in cancer progression, stem cell differentiation, and T cell and B cell development. Accumulating evidence has revealed that CHD4 can function in NuRD dependent and independent manner in response to DNA damage.

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Posterior fossa ependymoma comprise three distinct molecular variants, termed PF-EPN-A (PFA), PF-EPN-B (PFB), and PF-EPN-SE (subependymoma). Clinically, they are very disparate and PFB tumors are currently being considered for a trial of radiation avoidance. However, to move forward, unraveling the heterogeneity within PFB would be highly desirable.

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While the preponderance of morbidity and mortality in medulloblastoma patients are due to metastatic disease, most research focuses on the primary tumor due to a dearth of metastatic tissue samples and model systems. Medulloblastoma metastases are found almost exclusively on the leptomeningeal surface of the brain and spinal cord; dissemination is therefore thought to occur through shedding of primary tumor cells into the cerebrospinal fluid followed by distal re-implantation on the leptomeninges. We present evidence for medulloblastoma circulating tumor cells (CTCs) in therapy-naive patients and demonstrate in vivo, through flank xenografting and parabiosis, that medulloblastoma CTCs can spread through the blood to the leptomeningeal space to form leptomeningeal metastases.

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While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of medulloblastoma.

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Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy.

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Background: Patients with incomplete surgical resection of medulloblastoma are controversially regarded as having a marker of high-risk disease, which leads to patients undergoing aggressive surgical resections, so-called second-look surgeries, and intensified chemoradiotherapy. All previous studies assessing the clinical importance of extent of resection have not accounted for molecular subgroup. We analysed the prognostic value of extent of resection in a subgroup-specific manner.

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The development of targeted anti-cancer therapies through the study of cancer genomes is intended to increase survival rates and decrease treatment-related toxicity. We treated a transposon-driven, functional genomic mouse model of medulloblastoma with 'humanized' in vivo therapy (microneurosurgical tumour resection followed by multi-fractionated, image-guided radiotherapy). Genetic events in recurrent murine medulloblastoma exhibit a very poor overlap with those in matched murine diagnostic samples (<5%).

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TP53 mutations confer subgroup specific poor survival for children with medulloblastoma. We hypothesized that WNT activation which is associated with improved survival for such children abrogates TP53 related radioresistance and can be used to sensitize TP53 mutant tumors for radiation. We examined the subgroup-specific role of TP53 mutations in a cohort of 314 patients treated with radiation.

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Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified.

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