Publications by authors named "Yoojoo Lim"

Little is known about changes in the abundance of tumor-infiltrating lymphocytes (TILs) and immune phenotype (IP) in recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC). We aimed to compare the TILs and IP between initial and recurrent HNSCCs using paired analysis. Thirty-seven patients who experienced recurrence after surgical resection and received treatment with immune checkpoint inhibitors (ICIs) between June 2014 and June 2023 were included.

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  • The study investigates the differences in tumor microenvironments (TMEs) between primary tumors and regional lymph node metastases (LNMs) in head and neck squamous cell carcinoma (HNSCC), focusing on tumor-infiltrating lymphocytes (TILs) and immune phenotypes.
  • Results showed no significant correlation in TIL densities between primary tumors and LNMs, and discordance in immune phenotypes was observed in 57.1% of patients, suggesting variability in patient responses to treatment.
  • Patients with higher TIL levels and inflamed immune phenotypes experienced longer progression-free survival, indicating that assessing TMEs in both primary tumors and LNMs could enhance the effectiveness of immune checkpoint inhibitors (ICIs) in
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  • Anti-PD1/L1 immunotherapy has shown promise when combined with chemotherapy for advanced biliary tract cancer (BTC), yet no predictive biomarker has been identified for its effectiveness.
  • Researchers analyzed tumor-infiltrating lymphocytes (TIL) using AI-powered immune phenotype (AI-IP) analysis on tissue samples from 339 advanced BTC patients undergoing anti-PD1 treatment.
  • The study found that patients with an "inflamed" immune phenotype (high TIL) had significantly better treatment responses and survival rates compared to those with "noninflamed" phenotypes, suggesting AI-IP could be a useful predictor of outcomes for anti-PD1 therapy in BTC.
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  • Apocrine differentiation and androgen receptor (AR) positivity are specific characteristics in a type of breast cancer called triple-negative breast cancer (TNBC) that might help predict treatment outcomes.
  • This study analyzed 232 TNBC patients who received neoadjuvant chemotherapy (NAC) to determine how apocrine features, AR status, and tumor-infiltrating lymphocytes (TILs) influenced their response to treatment.
  • The findings suggest that while apocrine morphology relates to lower chemotherapy response rates, AR expression does not significantly impact outcomes, highlighting the importance of recognizing apocrine features in clinical settings.
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Purpose: Clinical implications of neoadjuvant immunotherapy in patients with locally advanced but resectable head and neck squamous cell carcinoma (HNSCC) remain largely unexplored.

Patients And Methods: Patients with resectable HNSCC were randomized to receive a single dose of preoperative durvalumab (D) with or without tremelimumab (T) before resection, followed by postoperative (chemo)radiotherapy based on multidisciplinary discretion and 1-year D treatment. Artificial intelligence (AI)-powered spatial distribution analysis of tumor-infiltrating lymphocytes and high-dimensional profiling of circulating immune cells tracked dynamic intratumoral and systemic immune responses.

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Background: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types.

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Background: While immunotherapy combined with chemotherapy (Chemo-IO) is generally recognized for providing superior outcomes compared to monotherapy (mono-IO), it is associated with a higher incidence of treatment-related adverse events (TRAEs), which may lead to treatment discontinuation. In this study, we compared the rates of treatment discontinuation between mono-IO and Chemo-IO as first-line treatments for various solid tumors.

Methods: We systematically reviewed clinical trials from databases (PubMed, Embase, Cochrane Library, and an additional source) published from January 1, 2018, to July 10, 2023.

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Purpose: There have been needs to improve the sensitivity of liquid biopsy. This report aims to report the analytical and clinical validation of a next-generation sequencing (NGS)-based circulating tumor DNA (ctDNA) assay.

Materials And Methods: Analytical validation was conducted in vitro by evaluating the limit of detection (LOD), precision, and specificity for various genomic aberrations.

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Tumor-infiltrating lymphocytes (TIL) have been suggested as an important prognostic marker in colorectal cancer, but assessment usually requires additional tissue processing and interpretational efforts. The aim of this study is to assess the clinical significance of artificial intelligence (AI)-powered spatial TIL analysis using only a hematoxylin and eosin (H&E)-stained whole-slide image (WSI) for the prediction of prognosis in stage II-III colon cancer treated with surgery and adjuvant therapy. In this retrospective study, we used Lunit SCOPE IO, an AI-powered H&E WSI analyzer, to assess intratumoral TIL (iTIL) and tumor-related stromal TIL (sTIL) densities from WSIs of 289 patients.

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Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay.

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Background: This study analyzed the predictive value of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in recurrent or metastatic (R/M) adenoid cystic carcinoma (ACC) treated with axitinib.

Methods: Patients from a multicenter, prospective phase II trial evaluating axitinib efficacy in R/M ACC were included in this study. H&E whole-side images of archival tumor tissues were analyzed by Lunit SCOPE IO, an AI-powered spatial TIL analyzer.

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Background: Thymic epithelial tumors (TET) are rare malignancies and lack well-defined biomarkers for neoadjuvant therapy. This study aimed to evaluate the clinical utility of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in TET.

Methods: Patients initially diagnosed with unresectable thymoma or thymic carcinoma who underwent neoadjuvant therapy between January 2004 and December 2021 formed our study population.

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The regulatory effect of non-coding large-scale structural variations (SVs) on proto-oncogene activation remains unclear. This study investigated SV-mediated gene dysregulation by profiling 3D cancer genome maps from 40 patients with colorectal cancer (CRC). We developed a machine learning-based method for spatial characterization of the altered 3D cancer genome.

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Purpose: The aim of this study was to assess the role of the shear-wave velocity (SWV) value in predicting chemotherapeutic response and progression-free survival (PFS) in patients with colorectal cancer liver metastasis (CRLM).

Methods: In this prospective single-center study, participants with CRLM scheduled for chemotherapy were enrolled between May 2018 and June 2021. SWV measurements were obtained using shear-wave elastography at the CRLM site before and after initiating chemotherapy.

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Traditional tissue-based assessments of genomic alterations in castration-resistant prostate cancer (CRPC) can be challenging. To evaluate the real-world clinical utility of liquid biopsies for the evaluation of genomic alterations in CRPC, we preemptively collected available plasma samples and archival tissue samples from patients that were being treated for clinically confirmed CRPC. The cell-free DNA (cfDNA) and tumor tissue DNA were analyzed using the AlphaLiquid100-HRR panel.

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Background: Postoperative minimal residual disease (MRD) detection using circulating-tumour DNA (ctDNA) requires a highly sensitive analysis platform. We have developed a tumour-informed, hybrid-capture ctDNA sequencing MRD assay.

Methods: Personalised target-capture panels for ctDNA detection were designed using individual variants identified in tumour whole-exome sequencing of each patient.

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Emerging new mutations after treatment can provide clues to acquired resistant mechanisms. Circulating tumor DNA (ctDNA) sequencing has enabled noninvasive repeated tumor mutational profiling. We aimed to investigate newly emerging mutations in ctDNA after disease progression in metastatic colorectal cancer (mCRC).

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Purpose: Circulating tumor DNA (ctDNA) is emerging as a valuable non-invasive tool to identify tumor heterogeneity and tumor burden. This study investigated ctDNA dynamics in metastatic colorectal cancer patients treated with regorafenib.

Materials And Methods: In this prospective biomarker study, plasma cell-free DNA (cfDNA) samples obtained at baseline, at the first response evaluation after 2 cycles of treatment, and at the time of progressive disease were sequenced using a targeted next-generation sequencing platform which included 106 genes.

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Poly(ADP-ribose) polymerase inhibitors have been shown dramatic responses in patients with BRCAness. However, clinical studies have been limited to breast cancer patients with germline mutations. Here, we describe a patient with metastatic breast cancer who had a rare BRCA1 somatic mutation (BRCA1 c.

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Article Synopsis
  • Circulating tumour DNA (ctDNA) is a promising biomarker for cancer due to its accessibility and ability to reflect the tumour's genetic profile over time, although its clinical usefulness in monitoring has yet to be fully established.
  • A study analyzed 272 blood samples from 62 metastatic colorectal cancer patients undergoing chemotherapy, finding that 90.3% had ctDNA mutations before treatment; clearing ctDNA after treatment correlated with longer progression-free survival.
  • The research revealed that ctDNA monitoring was able to detect disease progression earlier than imaging in over half of the patients and identified new mutations that could inform targeted therapies, suggesting ctDNA offers valuable insights for personalized treatment.
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Circulating tumor DNA (ctDNA) may reveal dynamic tumor status during therapy. We conducted serial ctDNA analysis to investigate potential association with clinical outcome in metastatic colorectal cancer (mCRC) patients receiving chemotherapy. Tissue KRAS/NRAS wild-type mCRC patients were enrolled and treated with first-line cetuximab-containing chemotherapy.

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Tumor heterogeneity is one of the ongoing huddles in the field of colon cancer therapy. It is evident that there are countless clones which exhibit different phenotypes and therefore, single cell analysis is inevitable. Cancer stem cells (CSCs) are rare cell population within tumor which is known to function in cancer metastasis and recurrence.

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Background: In-hospital cardiopulmonary resuscitation (CPR) is one of undesirable situations. We tried to identify and characterize a potentially avoidable CPR in cancer patients who were hospitalized in hematology and oncology wards.

Methods: A potentially avoidable CPR was determined based on chemotherapy setting, disease status and clinical situation at the time when a cardiopulmonary arrest occurred, by using a consensus-driven medical records review of two physicians.

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Among prospectively enrolled adult patients with cancer receiving immune checkpoint inhibitors (ICIs; n = 46) or cytotoxic agents (n = 90), seroprotection and seroconversion rates after seasonal quadrivalent influenza vaccinations were higher with ICI than with cytotoxic chemotherapy. These results support annual influenza vaccinations for cancer patients receiving ICIs. Clinical Trials Registration clinicaltrials.

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We report a novel transcriptomic analysis workflow called LiEB (Life cycle of Epstein-Barr virus) to characterize distributions of oncogenic virus, Epstein-Barr virus (EBV) infection in human tumors. We analyzed 851 The Cancer Genome Atlas whole-transcriptome sequencing (WTS) data to investigate EBV infection by life cycle information using three-step LiEB workflow: 1) characterize virus infection generally; 2) align transcriptome sequences against a hybrid human-EBV genome, and 3) quantify EBV gene expression. Our results agreed with EBV infection status of public cell line data.

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